sha
null | last_modified
null | library_name
stringclasses 154
values | text
stringlengths 1
900k
| metadata
stringlengths 2
348k
| pipeline_tag
stringclasses 45
values | id
stringlengths 5
122
| tags
sequencelengths 1
1.84k
| created_at
stringlengths 25
25
| arxiv
sequencelengths 0
201
| languages
sequencelengths 0
1.83k
| tags_str
stringlengths 17
9.34k
| text_str
stringlengths 0
389k
| text_lists
sequencelengths 0
722
| processed_texts
sequencelengths 1
723
| tokens_length
sequencelengths 1
723
| input_texts
sequencelengths 1
61
| embeddings
sequencelengths 768
768
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-large-bn-adapter-3.17M-squad-model1
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 95
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "roberta-large", "model-index": [{"name": "roberta-large-bn-adapter-3.17M-squad-model1", "results": []}]} | null | varun-v-rao/roberta-large-bn-adapter-3.17M-squad-model1 | [
"tensorboard",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:roberta-large",
"license:mit",
"region:us"
] | 2024-02-08T23:27:51+00:00 | [] | [] | TAGS
#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-roberta-large #license-mit #region-us
|
# roberta-large-bn-adapter-3.17M-squad-model1
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 95
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# roberta-large-bn-adapter-3.17M-squad-model1\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 95\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-roberta-large #license-mit #region-us \n",
"# roberta-large-bn-adapter-3.17M-squad-model1\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 95\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
45,
42,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-roberta-large #license-mit #region-us \n# roberta-large-bn-adapter-3.17M-squad-model1\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 95\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.09783737361431122,
0.0821661576628685,
-0.002396923489868641,
0.08192817866802216,
0.16858719289302826,
0.026626355946063995,
0.13266003131866455,
0.10517166554927826,
-0.12186796963214874,
0.04571487382054329,
0.0802539810538292,
0.030518895015120506,
0.032589636743068695,
0.12440831959247589,
-0.008904598653316498,
-0.26162558794021606,
-0.007536961231380701,
0.02631085179746151,
-0.12360232323408127,
0.09760981053113937,
0.1271788775920868,
-0.10913736373186111,
0.0642058327794075,
0.0217742882668972,
-0.2301023304462433,
0.024101069197058678,
-0.004632732830941677,
-0.07785262167453766,
0.09658672660589218,
0.0074787079356610775,
0.11582495272159576,
-0.006096763536334038,
0.11900009959936142,
-0.11525873839855194,
0.010707109235227108,
0.0458575077354908,
0.043810226023197174,
0.10961060971021652,
0.030664095655083656,
0.03399182856082916,
0.12474654614925385,
-0.08204752951860428,
0.08451329171657562,
0.03317917138338089,
-0.07548733800649643,
-0.23750238120555878,
-0.08755161613225937,
0.09962987899780273,
0.048712730407714844,
0.08903244882822037,
0.004073187708854675,
0.15893933176994324,
-0.09858370572328568,
0.058649368584156036,
0.2264721840620041,
-0.2789793610572815,
-0.08029302954673767,
0.06168477237224579,
0.06913291662931442,
0.06480744481086731,
-0.10726308077573776,
-0.031870853155851364,
0.041497573256492615,
0.044952720403671265,
0.10308399796485901,
-0.01688048429787159,
-0.05443558841943741,
-0.002070169197395444,
-0.12922151386737823,
-0.030052542686462402,
0.22059401869773865,
0.025904204696416855,
-0.05227050185203552,
-0.058071304112672806,
-0.04001998156309128,
-0.06724830716848373,
-0.03020302765071392,
-0.02421426959335804,
0.02090490236878395,
-0.06773726642131805,
-0.1287892460823059,
-0.08140432089567184,
-0.09667452424764633,
-0.0788179561495781,
-0.0074911280535161495,
0.16646386682987213,
0.054116617888212204,
0.038828980177640915,
-0.08393727988004684,
0.11296417564153671,
0.002461072988808155,
-0.11685045808553696,
0.004980320110917091,
-0.014987564645707607,
-0.03494059294462204,
-0.033809639513492584,
-0.049869418144226074,
-0.01863531954586506,
0.021679246798157692,
0.1840806007385254,
-0.07326236367225647,
0.021922165527939796,
0.0244708601385355,
0.03552459925413132,
-0.02692941389977932,
0.15333695709705353,
-0.08246394246816635,
-0.018268825486302376,
0.03158602491021156,
0.08880893141031265,
0.019231105223298073,
0.007464607711881399,
-0.10341718047857285,
-0.038497619330883026,
0.09264205396175385,
0.04508817568421364,
-0.03844042494893074,
0.017862429842352867,
0.008976214565336704,
-0.043355174362659454,
0.028773825615644455,
-0.10236534476280212,
0.014149014838039875,
-0.00225772219710052,
-0.09870250523090363,
-0.012819847092032433,
0.017152097076177597,
-0.016188932582736015,
-0.017579859122633934,
0.06841397285461426,
-0.10719937086105347,
-0.022159770131111145,
-0.09597273170948029,
-0.07866299897432327,
0.006931731011718512,
-0.08479895442724228,
0.022667057812213898,
-0.09858443588018417,
-0.13780224323272705,
0.00299724075011909,
0.013775026425719261,
-0.0606851726770401,
-0.059487234801054,
0.004977188538759947,
-0.08794556558132172,
0.0013053282164037228,
-0.007010524161159992,
0.16889838874340057,
-0.01717674359679222,
0.10402901470661163,
0.06198296323418617,
0.0269505362957716,
-0.028046615421772003,
0.04228486120700836,
-0.08741483837366104,
0.018397917971014977,
-0.1534460335969925,
0.018976857885718346,
-0.0821494311094284,
0.030384935438632965,
-0.1083318367600441,
-0.1188286691904068,
0.008527219295501709,
-0.016199681907892227,
0.08797146379947662,
0.08071883022785187,
-0.08457856625318527,
-0.057644132524728775,
0.14537228643894196,
-0.07720360904932022,
-0.08192840218544006,
0.09994523972272873,
-0.03918176144361496,
0.052259333431720734,
0.03879334777593613,
0.1458156853914261,
0.09961552172899246,
-0.0845053642988205,
-0.029271062463521957,
0.011255626566708088,
0.061839960515499115,
-0.07220472395420074,
0.09938447922468185,
0.014811684377491474,
-0.0014902516268193722,
0.040910836309194565,
-0.06423058360815048,
0.041218992322683334,
-0.10338504612445831,
-0.07114320993423462,
-0.0556921623647213,
-0.09424719214439392,
0.040157563984394073,
0.04718128964304924,
0.056791339069604874,
-0.06436965614557266,
-0.09839310497045517,
0.11321171373128891,
0.16514356434345245,
-0.03732854500412941,
0.005028459243476391,
-0.08903351426124573,
0.10822097212076187,
-0.10287519544363022,
-0.02066834084689617,
-0.2075979858636856,
-0.07077357172966003,
0.02813609503209591,
-0.0012904448667541146,
0.048221979290246964,
0.011936549097299576,
0.06500369310379028,
0.06159750372171402,
-0.05467832460999489,
-0.02261263318359852,
-0.1277841478586197,
-0.029718991369009018,
-0.0819530189037323,
-0.1699294000864029,
-0.09415271878242493,
-0.03383069857954979,
0.16080939769744873,
-0.19944244623184204,
0.023805176839232445,
-0.012420397251844406,
0.1308799684047699,
0.03445974364876747,
-0.03168034553527832,
-0.015360644087195396,
0.046839963644742966,
-0.013520766980946064,
-0.07643220573663712,
0.03712470456957817,
0.013227499090135098,
-0.06318354606628418,
-0.07157699763774872,
-0.09324164688587189,
0.08926848322153091,
0.1052817702293396,
0.04591146484017372,
-0.0734015479683876,
0.012381108477711678,
-0.08921980857849121,
-0.03002905286848545,
-0.0448836050927639,
-0.011043579317629337,
0.11137701570987701,
-0.0007402091869153082,
0.14374816417694092,
-0.08074809610843658,
-0.05365746095776558,
0.03403875231742859,
-0.011365818791091442,
0.015239475294947624,
0.07833012193441391,
0.10749654471874237,
-0.1059083491563797,
0.09125689417123795,
0.09355524182319641,
-0.10645606368780136,
0.17040780186653137,
-0.06352037936449051,
-0.09817420691251755,
-0.039280034601688385,
-0.013937050476670265,
0.007237577345222235,
0.16352687776088715,
-0.07103938609361649,
-0.0018963635666295886,
0.048065025359392166,
-0.0051344940438866615,
0.04780099540948868,
-0.16793836653232574,
-0.014122098684310913,
-0.0031856524292379618,
-0.016599159687757492,
0.0020965959411114454,
0.016210459172725677,
0.02435307390987873,
0.10183294117450714,
0.029306354001164436,
-0.03132051229476929,
0.02720722183585167,
0.01265014335513115,
-0.05198804661631584,
0.19817021489143372,
-0.07203835994005203,
-0.11468852311372757,
-0.15864183008670807,
0.04844869300723076,
-0.06690119206905365,
-0.031109683215618134,
0.012657048180699348,
-0.08084124326705933,
-0.02522408217191696,
-0.057204484939575195,
0.046960748732089996,
-0.05002422258257866,
0.010454412549734116,
0.0030568225774914026,
0.042449548840522766,
0.08773473650217056,
-0.14701522886753082,
0.02608061209321022,
-0.050966646522283554,
-0.11851796507835388,
-0.0030731221195310354,
0.06289158016443253,
0.11070500314235687,
0.09955046325922012,
-0.03140857815742493,
0.013666224665939808,
-0.034115299582481384,
0.21152938902378082,
-0.07130234688520432,
-0.02078378014266491,
0.16329091787338257,
0.028853021562099457,
0.03456728905439377,
0.07503208518028259,
0.0544942207634449,
-0.05810346081852913,
0.012886014766991138,
0.04351161792874336,
-0.03151759132742882,
-0.2514289319515228,
-0.03189270570874214,
-0.04305511340498924,
-0.03630872815847397,
0.09354880452156067,
0.05385061725974083,
-0.00686113303527236,
0.08264023065567017,
-0.020370611920952797,
0.07521001994609833,
-0.05587927997112274,
0.09865691512823105,
0.09887512028217316,
0.035812877118587494,
0.10688784718513489,
-0.05275086686015129,
-0.05495999753475189,
0.060435160994529724,
0.02817457728087902,
0.2947857081890106,
-0.04868864268064499,
0.09284473210573196,
0.0499693937599659,
0.14869244396686554,
-0.014660488814115524,
0.06379768252372742,
-0.006876303814351559,
-0.005124058108776808,
-0.006945288274437189,
-0.05018564686179161,
-0.0014859085204079747,
-0.009991118684411049,
-0.02002621442079544,
0.0923081561923027,
-0.0979742631316185,
0.021110065281391144,
0.01466294378042221,
0.2486708015203476,
0.01793542318046093,
-0.2954712510108948,
-0.12324503064155579,
0.0007926716934889555,
-0.014805369079113007,
-0.055316247045993805,
0.01915392465889454,
0.12238297611474991,
-0.11472741514444351,
-0.005924934521317482,
-0.06568564474582672,
0.07477115839719772,
-0.019477926194667816,
-0.005856055300682783,
0.0392809696495533,
0.17788827419281006,
0.009342883713543415,
0.09649442136287689,
-0.19768284261226654,
0.2234751582145691,
0.017291923984885216,
0.10524936765432358,
-0.04629451781511307,
0.02661857381463051,
0.01643175259232521,
0.053215399384498596,
0.06341367214918137,
-0.01287909783422947,
0.004324630368500948,
-0.1684418022632599,
-0.06262292712926865,
0.03670629858970642,
0.09857767075300217,
-0.04222719743847847,
0.10479053854942322,
-0.051644813269376755,
0.019210880622267723,
0.03876712918281555,
-0.08493667840957642,
-0.134267196059227,
-0.10151757299900055,
-0.00046995558659546077,
0.003040631767362356,
-0.09047763794660568,
-0.09931254386901855,
-0.09970904141664505,
0.005378240719437599,
0.13500791788101196,
-0.023825274780392647,
-0.04213223606348038,
-0.1304141879081726,
0.12362059950828552,
0.14059843122959137,
-0.07381221652030945,
0.024579036980867386,
-0.00254381587728858,
0.1329294741153717,
0.004082007799297571,
-0.08208347856998444,
0.043611831963062286,
-0.06985323131084442,
-0.18249313533306122,
-0.024350721389055252,
0.12604855000972748,
0.021892348304390907,
0.0472501665353775,
-0.013533956371247768,
0.012820005416870117,
-0.009985755197703838,
-0.09255080670118332,
0.007090924307703972,
0.017343411222100258,
0.03990758955478668,
0.032377224415540695,
-0.06693851202726364,
0.01707206293940544,
-0.021839115768671036,
-0.003101691137999296,
0.13456660509109497,
0.21716876327991486,
-0.09081722795963287,
0.0380733460187912,
0.0850718542933464,
-0.0492679700255394,
-0.1758173108100891,
0.050463661551475525,
0.09504866600036621,
0.021073199808597565,
0.0479850098490715,
-0.20106689631938934,
0.12098206579685211,
0.09536116570234299,
-0.03225187584757805,
0.051986437290906906,
-0.2961864471435547,
-0.11027185618877411,
0.08952740579843521,
0.13424281775951385,
0.066915363073349,
-0.13793489336967468,
-0.029057057574391365,
-0.01949911378324032,
-0.1354321986436844,
0.11241410672664642,
-0.1455904096364975,
0.11740127205848694,
-0.034199975430965424,
0.12104491144418716,
0.014218463562428951,
-0.05088868364691734,
0.12695059180259705,
-0.0050466107204556465,
0.0766453891992569,
-0.036170635372400284,
-0.04669941961765289,
0.18466955423355103,
-0.03390634059906006,
0.055952493101358414,
-0.023318076506257057,
0.07199308276176453,
-0.14695040881633759,
-0.02389252558350563,
-0.09088695794343948,
0.06882747262716293,
-0.05213363841176033,
-0.06649088114500046,
-0.06071300804615021,
0.07437583804130554,
-0.02486889809370041,
-0.028928223997354507,
0.08534619957208633,
0.047867804765701294,
0.09306655079126358,
0.0904882624745369,
0.08027594536542892,
0.03435366600751877,
-0.08559559285640717,
-0.003095811465755105,
-0.028407178819179535,
0.08928140997886658,
-0.1541280299425125,
-0.0018873665248975158,
0.09306029230356216,
0.050281722098588943,
0.09786633402109146,
0.0606965571641922,
-0.09037274867296219,
0.03819485381245613,
0.06046450883150101,
-0.11276672035455704,
-0.14755944907665253,
-0.03220801055431366,
-0.004285271745175123,
-0.16005156934261322,
0.07332099974155426,
0.10883725434541702,
-0.08309375494718552,
-0.03659789264202118,
-0.01066635362803936,
-0.007882712408900261,
-0.047264307737350464,
0.1798589527606964,
0.09592965990304947,
0.06836505234241486,
-0.08903204649686813,
0.10768823325634003,
0.08374371379613876,
-0.021441666409373283,
0.03311031684279442,
0.07803267985582352,
-0.0766698345541954,
-0.017967158928513527,
0.01640743389725685,
0.14184555411338806,
-0.07057704031467438,
-0.048244133591651917,
-0.13557037711143494,
-0.08834309130907059,
0.04763270542025566,
0.07775047421455383,
0.06491994857788086,
-0.024193575605750084,
-0.052892010658979416,
0.04889318719506264,
-0.1730174869298935,
0.09951172769069672,
0.02918144501745701,
0.07935532182455063,
-0.1452540010213852,
0.0928630456328392,
0.004651967436075211,
0.05354597792029381,
-0.02123565971851349,
0.00844243261963129,
-0.1095491498708725,
-0.00454935384914279,
-0.11958581209182739,
-0.028011662885546684,
-0.0003825390012934804,
0.006730859633535147,
-0.028267590329051018,
-0.05467488616704941,
-0.06340306252241135,
0.05791742727160454,
-0.08446598052978516,
-0.040297891944646835,
0.028071437031030655,
0.04772070050239563,
-0.12553849816322327,
0.017923463135957718,
0.016105279326438904,
-0.08497074246406555,
0.09622389078140259,
0.06161496415734291,
0.05362062156200409,
0.044757191091775894,
-0.06335988640785217,
-0.030858933925628662,
-0.0009609661647118628,
0.012156946584582329,
0.06937342137098312,
-0.07046043127775192,
0.012374868616461754,
-0.039262644946575165,
0.06460569053888321,
0.0034293499775230885,
0.05547463148832321,
-0.13957031071186066,
-0.011316805146634579,
-0.06453107297420502,
-0.04057835415005684,
-0.0810714066028595,
0.047904882580041885,
0.07123551517724991,
0.05918179824948311,
0.15040066838264465,
-0.06252079457044601,
0.016217807307839394,
-0.2079949527978897,
-0.01570730097591877,
-0.030245205387473106,
-0.060426000505685806,
-0.10327497124671936,
-0.025644294917583466,
0.05480342358350754,
-0.05092798173427582,
0.0967259407043457,
0.0003434201062191278,
0.07660413533449173,
0.03875262662768364,
-0.024583691731095314,
-0.010357259772717953,
0.009742417372763157,
0.19242101907730103,
0.062177710235118866,
-0.001676856423728168,
0.06444691866636276,
0.009491851553320885,
0.060183536261320114,
0.08757877349853516,
0.14583788812160492,
0.152916818857193,
-0.01874944195151329,
0.05675667151808739,
0.11292627453804016,
-0.05977495014667511,
-0.12633393704891205,
0.10124791413545609,
0.011520485393702984,
0.06790068000555038,
-0.04490690678358078,
0.15534871816635132,
0.16978129744529724,
-0.14106254279613495,
0.029115846380591393,
-0.05015481635928154,
-0.07609029114246368,
-0.08700749278068542,
-0.03115811198949814,
-0.07537836581468582,
-0.11584453284740448,
0.03652508929371834,
-0.1245385929942131,
-0.031111881136894226,
0.10072728246450424,
0.0006885137991048396,
-0.01740344427525997,
0.14615829288959503,
0.02420779876410961,
0.01525343582034111,
0.04852665960788727,
0.003119747620075941,
-0.02280067279934883,
-0.05381449684500694,
-0.05258278548717499,
0.03966592624783516,
0.0012595891021192074,
0.07874331623315811,
-0.04858465865254402,
-0.03887329623103142,
0.03407768905162811,
-0.0045951721258461475,
-0.07113726437091827,
0.018799742683768272,
0.02354750968515873,
0.05625486746430397,
0.031087759882211685,
0.01662687212228775,
-0.009946632198989391,
-0.0480937659740448,
0.267952561378479,
-0.06770677864551544,
-0.09412901103496552,
-0.11890050023794174,
0.18252350389957428,
0.017797477543354034,
-0.039754923433065414,
0.05095566809177399,
-0.10850100964307785,
-0.03182963281869888,
0.17313775420188904,
0.19273190200328827,
-0.03534087538719177,
-0.025043444707989693,
0.02737569250166416,
-0.029715904965996742,
-0.08418506383895874,
0.14331014454364777,
0.09583327919244766,
0.07247387617826462,
-0.0646587461233139,
-0.014010822400450706,
-0.028384478762745857,
-0.014167612418532372,
-0.05034932866692543,
0.0760764628648758,
0.033529479056596756,
-0.001142109395004809,
-0.04870030656456947,
0.04967821016907692,
-0.014208009466528893,
-0.18567980825901031,
0.046122025698423386,
-0.13799874484539032,
-0.18792665004730225,
-0.0405728705227375,
0.07072988897562027,
-0.017950892448425293,
0.07596403360366821,
-0.03582484647631645,
0.004423356615006924,
0.08259476721286774,
-0.012133053503930569,
-0.07184142619371414,
-0.09991654008626938,
0.12925246357917786,
-0.0416996143758297,
0.2062440812587738,
-0.038086507469415665,
0.08139209449291229,
0.12204752117395401,
0.003101378446444869,
-0.14936493337154388,
0.0111487852409482,
0.06438267976045609,
-0.05818468704819679,
0.016608286648988724,
0.1701349914073944,
-0.03258698433637619,
0.08513966202735901,
0.018012937158346176,
-0.1213054433465004,
-0.026194049045443535,
-0.04787471890449524,
-0.001384108210913837,
-0.08131887018680573,
0.0049184164963662624,
-0.07134945690631866,
0.14682206511497498,
0.19405704736709595,
-0.05085720866918564,
-0.03129274398088455,
-0.10341523587703705,
0.05440037325024605,
0.0933133214712143,
0.06873221695423126,
-0.019132113084197044,
-0.19454531371593475,
-0.006033401470631361,
0.034837983548641205,
-0.004421381279826164,
-0.3039310872554779,
-0.058688923716545105,
0.03918454796075821,
-0.045662812888622284,
-0.07117811590433121,
0.09060872346162796,
0.0914008766412735,
0.053797148168087006,
-0.040586937218904495,
-0.07803156971931458,
-0.09448783844709396,
0.12404549866914749,
-0.18538512289524078,
-0.06006547436118126
] |
null | null | transformers |
# Uploaded model
- **Developed by:** smotoc
- **License:** apache-2.0
- **Finetuned from model :** teknium/OpenHermes-2.5-Mistral-7B
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "gguf"], "base_model": "teknium/OpenHermes-2.5-Mistral-7B"} | null | smotoc/HerFoxy_7B | [
"transformers",
"pytorch",
"gguf",
"mistral",
"text-generation-inference",
"unsloth",
"en",
"base_model:teknium/OpenHermes-2.5-Mistral-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-08T23:31:03+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gguf #mistral #text-generation-inference #unsloth #en #base_model-teknium/OpenHermes-2.5-Mistral-7B #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: smotoc
- License: apache-2.0
- Finetuned from model : teknium/OpenHermes-2.5-Mistral-7B
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: smotoc\n- License: apache-2.0\n- Finetuned from model : teknium/OpenHermes-2.5-Mistral-7B\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
"TAGS\n#transformers #pytorch #gguf #mistral #text-generation-inference #unsloth #en #base_model-teknium/OpenHermes-2.5-Mistral-7B #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: smotoc\n- License: apache-2.0\n- Finetuned from model : teknium/OpenHermes-2.5-Mistral-7B\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
68,
79
] | [
"passage: TAGS\n#transformers #pytorch #gguf #mistral #text-generation-inference #unsloth #en #base_model-teknium/OpenHermes-2.5-Mistral-7B #license-apache-2.0 #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: smotoc\n- License: apache-2.0\n- Finetuned from model : teknium/OpenHermes-2.5-Mistral-7B\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
-0.10498516261577606,
0.0364699587225914,
-0.003625475103035569,
0.09558098763227463,
0.0453031025826931,
0.030662482604384422,
0.11055189371109009,
0.09103284031152725,
0.14737747609615326,
-0.05260529741644859,
0.10282406955957413,
0.12301012873649597,
-0.006046116817742586,
0.0512939989566803,
-0.03389042243361473,
-0.25030431151390076,
0.10370063781738281,
-0.04055100679397583,
-0.08602358400821686,
0.0542733334004879,
0.08584076911211014,
-0.005943635944277048,
0.07462301850318909,
-0.0307355597615242,
-0.013099211268126965,
-0.02460085041821003,
-0.048537302762269974,
-0.022121191024780273,
0.041627444326877594,
0.03304784372448921,
-0.04081805795431137,
0.04516078904271126,
0.05147973820567131,
-0.03164512291550636,
0.05450141429901123,
0.020523320883512497,
0.00972791388630867,
0.0994257777929306,
0.016509879380464554,
0.06788337230682373,
0.1898358166217804,
-0.011772616766393185,
-0.04721936956048012,
0.043358221650123596,
-0.014715960249304771,
-0.1374058574438095,
-0.07819214463233948,
0.08242038637399673,
0.009007800370454788,
0.06832615286111832,
0.053360700607299805,
0.1598331183195114,
-0.05615952983498573,
0.06329809129238129,
0.21066881716251373,
-0.241567924618721,
-0.08704139292240143,
0.11679638922214508,
0.03365033119916916,
0.034934643656015396,
-0.03035329096019268,
0.008947581052780151,
0.025873208418488503,
0.009111106395721436,
0.015624300576746464,
-0.043489132076501846,
-0.08836522698402405,
0.027450842782855034,
-0.12625598907470703,
-0.008301610127091408,
0.23507028818130493,
0.0840425193309784,
-0.06261011958122253,
0.02222835272550583,
-0.1845078021287918,
0.1424296647310257,
-0.037636205554008484,
-0.008044338785111904,
0.058809515088796616,
0.07901910692453384,
0.0216106865555048,
-0.1277419775724411,
-0.057795409113168716,
-0.057738929986953735,
-0.12538649141788483,
0.10077905654907227,
0.053952764719724655,
0.12338976562023163,
-0.04577739164233208,
0.09139039367437363,
-0.031071875244379044,
-0.12157243490219116,
-0.07547035068273544,
-0.10418280214071274,
0.08520589023828506,
0.046832676976919174,
-0.046571340411901474,
0.005700550973415375,
0.10752058774232864,
0.2618826925754547,
0.04062514379620552,
0.04240327700972557,
0.09068074077367783,
0.051185403019189835,
-0.050575677305459976,
0.04187483340501785,
-0.13026365637779236,
-0.057621799409389496,
0.11519362777471542,
0.006149733904749155,
0.07104237377643585,
-0.017864996567368507,
-0.082846499979496,
-0.09406548738479614,
-0.018690528348088264,
-0.013821463100612164,
0.05034557729959488,
0.11385627090930939,
0.04805614426732063,
-0.0924355611205101,
0.24858537316322327,
-0.061076339334249496,
-0.04486897587776184,
0.01302634458988905,
-0.10106777399778366,
0.18519607186317444,
0.14242033660411835,
0.001723920227959752,
-0.040976330637931824,
-0.07091138511896133,
-0.04272177442908287,
0.02177475392818451,
-0.009583558887243271,
-0.03337554261088371,
0.057378239929676056,
-0.04471338167786598,
0.0019445387879386544,
-0.1246037632226944,
-0.2702426612377167,
0.03969211131334305,
0.17053169012069702,
-0.013909237459301949,
-0.06655896455049515,
-0.007320960517972708,
-0.0428064689040184,
0.016210269182920456,
-0.010740584693849087,
0.027158468961715698,
-0.07171637564897537,
0.00560654466971755,
-0.10523400455713272,
0.06587499380111694,
-0.21908947825431824,
0.016368279233574867,
-0.10288155823945999,
0.0033729735296219587,
-0.0904635339975357,
0.03489018604159355,
-0.0645589828491211,
0.12050247192382812,
-0.10118100047111511,
-0.033864110708236694,
-0.06569229811429977,
-0.033268723636865616,
0.04942235350608826,
0.1704418957233429,
-0.11478164792060852,
0.03604349121451378,
0.12391096353530884,
-0.04918965697288513,
-0.14322783052921295,
0.1456487476825714,
0.007686870638281107,
0.052532751113176346,
0.04471943527460098,
0.07236885279417038,
0.12878923118114471,
-0.1426335871219635,
0.11423359811306,
0.16478873789310455,
-0.043731607496738434,
-0.0841120108962059,
0.10225306451320648,
-0.008254480548202991,
-0.07647130638360977,
0.09368626028299332,
-0.11911161988973618,
0.09078069031238556,
-0.012668432667851448,
-0.05374695733189583,
-0.12062001973390579,
-0.07138697803020477,
0.007350736763328314,
-0.016949985176324844,
0.03579184040427208,
0.01529981940984726,
-0.026044944301247597,
0.03858538717031479,
0.16900332272052765,
-0.034205880016088486,
0.03007795661687851,
-0.032809700816869736,
0.08316411077976227,
-0.054178375750780106,
0.06113007664680481,
-0.10285229980945587,
0.009402918629348278,
-0.003016107017174363,
-0.05165380239486694,
0.058681316673755646,
0.06818310171365738,
0.08962252736091614,
0.0016036831075325608,
-0.004388832021504641,
0.019881758838891983,
0.04802200570702553,
-0.007135399151593447,
-0.05077774450182915,
-0.1413257122039795,
-0.016861828044056892,
-0.02504606731235981,
0.12588945031166077,
-0.033372193574905396,
0.0595005564391613,
-0.07723648101091385,
0.06104639172554016,
-0.032002124935388565,
0.057048019021749496,
0.045110125094652176,
-0.13008713722229004,
-0.006043596658855677,
-0.08908572047948837,
0.0991070568561554,
0.07531578838825226,
-0.07481323182582855,
0.08843234926462173,
-0.02246014215052128,
0.09509642422199249,
0.13654187321662903,
0.004444189369678497,
0.0749787911772728,
-0.015677571296691895,
-0.07696202397346497,
-0.024279994890093803,
0.05231751874089241,
0.04507745802402496,
-0.012676374986767769,
-0.010631884448230267,
0.0882316306233406,
-0.10080533474683762,
-0.03566991910338402,
0.008697187528014183,
-0.05845412239432335,
0.027793489396572113,
0.049053557217121124,
0.12363243103027344,
-0.18009160459041595,
0.018595237284898758,
0.25874850153923035,
-0.08503896743059158,
0.09644022583961487,
-0.03892634063959122,
-0.0627836361527443,
0.009828619658946991,
0.036872293800115585,
-0.03698384016752243,
0.031956061720848083,
-0.1367114931344986,
0.06232893094420433,
0.06440634280443192,
-0.0009292152826674283,
0.05007006973028183,
-0.10444203019142151,
0.00799910631030798,
-0.027610069140791893,
-0.061653390526771545,
-0.015873746946454048,
0.11950352787971497,
-0.06544078886508942,
0.07204538583755493,
-0.029961904510855675,
-0.10168279707431793,
0.029338490217924118,
0.03219497203826904,
-0.061547987163066864,
0.129034161567688,
-0.08006878942251205,
-0.007452335674315691,
-0.10151080042123795,
-0.012312238104641438,
-0.12166920304298401,
-0.03462270274758339,
0.0605292022228241,
0.013043353334069252,
-0.05076630786061287,
-0.10562964528799057,
-0.09836506098508835,
0.0593516007065773,
0.026800069957971573,
0.07256190478801727,
0.00953588169068098,
0.051781609654426575,
-0.1261533945798874,
-0.026996277272701263,
-0.03990321606397629,
-0.08307819813489914,
0.03149890527129173,
-0.09003584831953049,
0.06348977982997894,
0.10831014066934586,
0.023095110431313515,
-0.0026333313435316086,
0.06671593338251114,
0.19590537250041962,
0.027479374781250954,
0.10592435300350189,
0.21487106382846832,
0.039060067385435104,
0.10502614825963974,
0.11182946711778641,
0.021143410354852676,
-0.03497007489204407,
-0.004174654837697744,
-0.04418264329433441,
-0.03211992606520653,
-0.20739556849002838,
-0.033313602209091187,
-0.11797183752059937,
0.06684917956590652,
0.04464784637093544,
0.07629671692848206,
0.011356085538864136,
0.1377943754196167,
-0.0951133444905281,
0.05057116225361824,
0.06436245143413544,
0.06847304850816727,
0.03809862583875656,
0.03798382729291916,
0.04558796435594559,
-0.10546549409627914,
0.038309160619974136,
0.1671738475561142,
0.03320307284593582,
0.1818724423646927,
-0.0356152206659317,
0.05043361335992813,
0.061354875564575195,
0.15486228466033936,
-0.007710515987128019,
0.12482288479804993,
-0.04221367835998535,
0.015522939153015614,
-0.09887275099754333,
-0.08639423549175262,
-0.017866535112261772,
0.047520313411951065,
-0.1362583041191101,
-0.010174760594964027,
0.020076068118214607,
0.1157265305519104,
0.0945054292678833,
0.20248065888881683,
0.0286712609231472,
-0.23119688034057617,
-0.11589684337377548,
0.040331773459911346,
0.03997035697102547,
-0.004564469680190086,
0.031195059418678284,
0.00504138832911849,
-0.06292634457349777,
0.10266587883234024,
-0.05390964448451996,
0.1314365714788437,
0.12189345806837082,
0.022277796640992165,
0.03919233754277229,
0.17207089066505432,
0.06121356412768364,
0.07518628239631653,
-0.1632825881242752,
0.11229467391967773,
-0.016975626349449158,
0.029026230797171593,
-0.06326840817928314,
-0.002710912376642227,
0.16351521015167236,
0.1702432632446289,
0.05605895817279816,
0.034373894333839417,
-0.0021705529652535915,
0.10884613543748856,
-0.15216343104839325,
0.07561345398426056,
-0.01963752508163452,
0.0186956524848938,
0.03319190815091133,
-0.08090861141681671,
-0.05270320549607277,
0.03317716345191002,
0.17312480509281158,
-0.13017155230045319,
-0.0899718627333641,
0.03101753443479538,
0.03332454711198807,
-0.11835817992687225,
-0.03854251652956009,
-0.008412642404437065,
-0.10274378210306168,
0.1321839839220047,
0.05177046358585358,
-0.07486463338136673,
-0.10102855414152145,
-0.057218026369810104,
0.14468471705913544,
-0.10524391382932663,
0.02508610673248768,
-0.08685562014579773,
-0.008873489685356617,
0.019242996349930763,
-0.21640606224536896,
0.07035043835639954,
-0.12303697317838669,
-0.050905726850032806,
0.020316272974014282,
0.01586228422820568,
-0.07395639270544052,
0.006864078808575869,
-0.005797362886369228,
-0.04762912541627884,
-0.12236075103282928,
-0.13290755450725555,
-0.0741298645734787,
0.22333762049674988,
-0.07796408981084824,
-0.018153881654143333,
-0.08594310283660889,
-0.06809692829847336,
0.023087287321686745,
0.01988859847187996,
0.026851732283830643,
0.19230866432189941,
-0.039713941514492035,
0.09401530027389526,
0.20857857167720795,
-0.03000938706099987,
-0.24183189868927002,
-0.09441863745450974,
-0.05615324527025223,
-0.0704435333609581,
-0.04619818925857544,
-0.08216237276792526,
0.13687977194786072,
0.06516490131616592,
-0.052832767367362976,
0.09705425798892975,
-0.2760331332683563,
-0.10448186844587326,
0.11738933622837067,
0.031157121062278748,
0.32707345485687256,
-0.10380032658576965,
-0.04505014419555664,
-0.08923214673995972,
-0.27298295497894287,
0.04393424093723297,
-0.23448032140731812,
0.08135245740413666,
-0.04466574266552925,
-0.000930603186134249,
-0.022598475217819214,
-0.04542595520615578,
0.13156986236572266,
-0.005172577686607838,
0.08145210146903992,
-0.09973607212305069,
0.07799182832241058,
0.10293931514024734,
-0.08280801773071289,
0.21458548307418823,
-0.10658910870552063,
0.09908643364906311,
-0.006700228434056044,
-0.01063226442784071,
-0.047662995755672455,
0.034603796899318695,
0.018831808120012283,
-0.047404687851667404,
-0.036613162606954575,
-0.022484691813588142,
0.06180264800786972,
0.01107808854430914,
0.11094038933515549,
0.08640864491462708,
-0.058281153440475464,
0.13392217457294464,
0.006758044008165598,
-0.18583624064922333,
0.03841207176446915,
-0.07961548119783401,
-0.025171609595417976,
0.07811298221349716,
-0.1815546751022339,
0.007742729969322681,
0.08316517621278763,
-0.0136191975325346,
0.010948697105050087,
0.024922320619225502,
0.028956905007362366,
-0.008500037714838982,
0.003681042231619358,
-0.1358673870563507,
-0.11579402536153793,
-0.04248527064919472,
0.040357936173677444,
-0.051318541169166565,
0.10834817588329315,
0.13632309436798096,
-0.08754058182239532,
0.001591388718225062,
0.009139223955571651,
0.021483633667230606,
-0.028647318482398987,
0.05737527459859848,
0.05522806942462921,
-0.04080449417233467,
-0.10499705374240875,
0.15619392693042755,
-0.012317907065153122,
-0.027976954355835915,
-0.042932309210300446,
0.10010363906621933,
-0.19317302107810974,
-0.10504575818777084,
0.002225870732218027,
0.00957506150007248,
-0.13683244585990906,
-0.02485588565468788,
-0.07657615095376968,
-0.02828086167573929,
0.06601503491401672,
0.009017178788781166,
0.10565965622663498,
-0.009175221435725689,
-0.03210795298218727,
0.0033978449646383524,
0.005155104212462902,
0.05072961747646332,
0.07492031902074814,
0.050247080624103546,
-0.15887567400932312,
-0.00681664701551199,
-0.031336501240730286,
0.06435937434434891,
-0.03895453363656998,
-0.016149599105119705,
-0.03233471140265465,
-0.023817740380764008,
-0.27201327681541443,
0.0450795516371727,
-0.08071254193782806,
0.024556290358304977,
-0.01886368915438652,
-0.06892245262861252,
-0.04302924871444702,
0.0981004387140274,
-0.08433005958795547,
-0.03799382969737053,
-0.03001410700380802,
0.010217815637588501,
-0.08411221951246262,
-0.04461030289530754,
0.027172887697815895,
-0.06607352197170258,
0.07023784518241882,
0.14997759461402893,
-0.12005438655614853,
-0.0013526168186217546,
-0.24033613502979279,
-0.10767682641744614,
0.028618989512324333,
0.06663215905427933,
0.006898127496242523,
0.035879384726285934,
-0.015434644185006618,
0.036520469933748245,
0.049044881016016006,
-0.07953207194805145,
0.07775717973709106,
-0.05913461744785309,
-0.04662585258483887,
-0.05679690092802048,
-0.005852740723639727,
-0.0575384758412838,
-0.05774988606572151,
0.09453525394201279,
0.10944030433893204,
0.1338561624288559,
-0.006927595008164644,
-0.02188684605062008,
-0.18236114084720612,
-0.008372917771339417,
0.04445892944931984,
-0.09412054717540741,
-0.1665492057800293,
-0.050719521939754486,
0.024175889790058136,
-0.032300837337970734,
0.10517062991857529,
-0.048769306391477585,
-0.08351553976535797,
-0.028911596164107323,
0.06932023912668228,
0.022945625707507133,
-0.0289438609033823,
0.2292170226573944,
0.04162126034498215,
0.06292332708835602,
-0.06140192225575447,
0.018817687407135963,
0.07748983055353165,
0.01943891867995262,
0.0600278377532959,
0.12266003340482712,
0.04806028679013252,
0.14516307413578033,
0.004398169461637735,
0.08705143630504608,
-0.04277287423610687,
0.01625365950167179,
0.03203446418046951,
0.09107686579227448,
-0.057386063039302826,
0.08994290977716446,
0.1768583059310913,
-0.05931318551301956,
-0.010782078839838505,
0.003495265729725361,
-0.01573161594569683,
-0.14440138638019562,
-0.20393793284893036,
-0.09776784479618073,
-0.1765361875295639,
-0.015917174518108368,
-0.05597010999917984,
0.02213074266910553,
0.02594097889959812,
0.03663446009159088,
0.023649387061595917,
0.01954243704676628,
-0.0729900375008583,
-0.08129862695932388,
0.06181829422712326,
-0.036853328347206116,
-0.10621769726276398,
0.11165682971477509,
-0.05407483130693436,
0.07063706964254379,
-0.022108476608991623,
0.008377177640795708,
0.016583530232310295,
0.07231378555297852,
0.05007003992795944,
-0.04502952843904495,
-0.053448356688022614,
-0.05155692994594574,
0.03487345948815346,
-0.027050675824284554,
0.04287170618772507,
0.06099875271320343,
-0.008140865713357925,
0.0486532598733902,
0.1920667588710785,
-0.08570151031017303,
-0.19509634375572205,
-0.13086803257465363,
0.08022347837686539,
-0.032269127666950226,
-0.004959249868988991,
0.0359724685549736,
-0.02442748099565506,
-0.008283272385597229,
0.177924245595932,
0.21053336560726166,
-0.12100755423307419,
-0.009412324987351894,
0.027975209057331085,
-0.0017672149697318673,
-0.021124009042978287,
0.1194051131606102,
0.11050538718700409,
0.09173506498336792,
-0.030249468982219696,
-0.02721751108765602,
-0.0129821402952075,
-0.01870666816830635,
-0.13424545526504517,
-0.007884531281888485,
-0.06735359877347946,
-0.075515978038311,
-0.003160963300615549,
0.021999746561050415,
-0.0993674173951149,
-0.04006391391158104,
-0.09017987549304962,
0.014115219935774803,
-0.04260812699794769,
-0.08159615099430084,
0.025351691991090775,
0.11934652924537659,
0.026205863803625107,
-0.10038264840841293,
0.0488508939743042,
0.20790626108646393,
-0.03376692533493042,
-0.16490232944488525,
-0.031307026743888855,
0.08699999749660492,
0.023960454389452934,
0.11794651299715042,
0.041936878114938736,
0.053369034081697464,
0.048992834985256195,
-0.01211909856647253,
-0.16663934290409088,
0.024587510153651237,
0.0033365737181156874,
-0.030966753140091896,
0.024753829464316368,
-0.06415101140737534,
-0.06506741046905518,
-0.048846516758203506,
0.04056546837091446,
0.01381391379982233,
-0.05445403233170509,
0.16024427115917206,
-0.0486917644739151,
-0.07770135998725891,
0.04740011692047119,
-0.09201286733150482,
0.10381776839494705,
0.07563112676143646,
-0.05197979509830475,
-0.04260885342955589,
-0.10154105722904205,
0.04454544186592102,
0.03240899369120598,
-0.16535161435604095,
-0.024265266954898834,
-0.016545461490750313,
-0.01683248020708561,
-0.058736737817525864,
0.0660790428519249,
-0.050818853080272675,
-0.07383672893047333,
-0.10225870460271835,
-0.03694739565253258,
-0.04536743834614754,
0.04884091392159462,
0.09146769344806671,
0.01822151616215706,
0.0018056174740195274,
0.003875080728903413,
-0.04135112091898918,
0.04311564564704895,
-0.08083830773830414,
-0.06807556748390198
] |
null | null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama2_instruct_generation
This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6728
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 0.03
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9239 | 0.0 | 20 | 1.8081 |
| 1.8915 | 0.01 | 40 | 1.7801 |
| 1.9622 | 0.01 | 60 | 1.7659 |
| 1.8338 | 0.01 | 80 | 1.7555 |
| 1.8614 | 0.01 | 100 | 1.7390 |
| 1.8221 | 0.02 | 120 | 1.7068 |
| 1.7601 | 0.02 | 140 | 1.7031 |
| 1.8557 | 0.02 | 160 | 1.6985 |
| 1.8575 | 0.02 | 180 | 1.6942 |
| 1.777 | 0.03 | 200 | 1.6925 |
| 1.8087 | 0.03 | 220 | 1.6904 |
| 1.856 | 0.03 | 240 | 1.6884 |
| 1.7704 | 0.04 | 260 | 1.6870 |
| 1.819 | 0.04 | 280 | 1.6838 |
| 1.8136 | 0.04 | 300 | 1.6836 |
| 1.768 | 0.04 | 320 | 1.6821 |
| 1.7937 | 0.05 | 340 | 1.6809 |
| 1.8045 | 0.05 | 360 | 1.6791 |
| 1.7958 | 0.05 | 380 | 1.6784 |
| 1.7995 | 0.05 | 400 | 1.6790 |
| 1.805 | 0.06 | 420 | 1.6775 |
| 1.9388 | 0.06 | 440 | 1.6742 |
| 1.8304 | 0.06 | 460 | 1.6742 |
| 1.8732 | 0.07 | 480 | 1.6729 |
| 1.8443 | 0.07 | 500 | 1.6728 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 | {"library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "NousResearch/Llama-2-7b-hf", "model-index": [{"name": "llama2_instruct_generation", "results": []}]} | null | 4ndr3w/llama2_instruct_generation | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:NousResearch/Llama-2-7b-hf",
"region:us"
] | 2024-02-08T23:31:34+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-NousResearch/Llama-2-7b-hf #region-us
| llama2\_instruct\_generation
============================
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6728
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0002
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_steps: 0.03
* training\_steps: 500
### Training results
### Framework versions
* PEFT 0.8.2
* Transformers 4.37.2
* Pytorch 2.1.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_steps: 0.03\n* training\\_steps: 500",
"### Training results",
"### Framework versions\n\n\n* PEFT 0.8.2\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-NousResearch/Llama-2-7b-hf #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_steps: 0.03\n* training\\_steps: 500",
"### Training results",
"### Framework versions\n\n\n* PEFT 0.8.2\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
55,
115,
4,
39
] | [
"passage: TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-NousResearch/Llama-2-7b-hf #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_steps: 0.03\n* training\\_steps: 500### Training results### Framework versions\n\n\n* PEFT 0.8.2\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.13159698247909546,
0.09082811325788498,
-0.0019020942272618413,
0.11614035069942474,
0.13806813955307007,
0.013884283602237701,
0.11743145436048508,
0.12147253006696701,
-0.07303734868764877,
0.07944675534963608,
0.14113666117191315,
0.09587837010622025,
0.025106655433773994,
0.17647849023342133,
-0.047084156423807144,
-0.22559134662151337,
-0.002011822769418359,
-0.004183006472885609,
-0.056936681270599365,
0.1248292401432991,
0.06357748806476593,
-0.14048565924167633,
0.07970494031906128,
-0.035985276103019714,
-0.18999339640140533,
0.005502977874130011,
0.01488175243139267,
-0.008603818714618683,
0.13545742630958557,
-0.011397521011531353,
0.1231822669506073,
0.03535209223628044,
0.11093419790267944,
-0.20172962546348572,
0.01673748716711998,
0.08004943281412125,
0.019260013476014137,
0.08886656910181046,
0.0583638995885849,
-0.016051173210144043,
0.08563219755887985,
-0.11216452717781067,
0.047027625143527985,
0.013415657915174961,
-0.14675626158714294,
-0.1919965296983719,
-0.09922414273023605,
0.019948866218328476,
0.08260692656040192,
0.07529230415821075,
-0.012804991565644741,
0.14064863324165344,
-0.06383136659860611,
0.09259563684463501,
0.2522661089897156,
-0.2654174566268921,
-0.09672597795724869,
0.03905363753437996,
0.026603903621435165,
0.1263720840215683,
-0.134700745344162,
-0.007726091425865889,
0.05403480678796768,
0.03628009930253029,
0.13541631400585175,
-0.022917769849300385,
-0.07362456619739532,
0.017032600939273834,
-0.13955193758010864,
0.0018531017703935504,
0.100175641477108,
0.04325474053621292,
-0.031151829287409782,
-0.00876437034457922,
-0.08230523765087128,
-0.18888944387435913,
-0.05011565983295441,
-0.027408022433519363,
0.048793770372867584,
-0.050148800015449524,
-0.06773196905851364,
-0.03599317744374275,
-0.0954461395740509,
-0.09265832602977753,
-0.020076971501111984,
0.14130045473575592,
0.0297453124076128,
0.008808094076812267,
-0.012827953323721886,
0.1267952024936676,
-0.016814779490232468,
-0.13892847299575806,
0.020562946796417236,
0.031416844576597214,
-0.05182338133454323,
-0.05463271960616112,
-0.049826085567474365,
-0.054499994963407516,
0.02733057551085949,
0.1100035309791565,
-0.11602457612752914,
0.07374769449234009,
0.02362135238945484,
0.0353519581258297,
-0.10606957972049713,
0.1161566898226738,
-0.07982073724269867,
-0.03378061577677727,
0.006701274774968624,
0.10664350539445877,
0.016891272738575935,
-0.007876898162066936,
-0.07392404973506927,
0.04263667017221451,
0.10422446578741074,
0.003944649361073971,
-0.056016430258750916,
0.035409118980169296,
-0.056691303849220276,
0.007334244437515736,
-0.016251392662525177,
-0.09620019793510437,
0.039154328405857086,
0.019040722399950027,
-0.05509679764509201,
-0.06131269037723541,
0.00031637688516639173,
0.01393379457294941,
0.01819239929318428,
0.10832563787698746,
-0.1140148788690567,
0.042809583246707916,
-0.09673650562763214,
-0.10991482436656952,
0.001646671211346984,
-0.09973377734422684,
-0.0006175186717882752,
-0.07028539478778839,
-0.1784728616476059,
-0.046691447496414185,
0.05778234452009201,
-0.06687037646770477,
-0.006068936549127102,
-0.07039432227611542,
-0.09133899956941605,
0.012464000843465328,
-0.00693807378411293,
0.12695565819740295,
-0.07202377915382385,
0.1211315244436264,
0.006567645817995071,
0.06719581037759781,
-0.038250114768743515,
0.020734576508402824,
-0.07904309034347534,
0.048517026007175446,
-0.1779056340456009,
0.036770645529031754,
-0.07504396885633469,
0.05080311745405197,
-0.09950095415115356,
-0.07098324596881866,
-0.04196969047188759,
-0.0008921317057684064,
0.11116773635149002,
0.14340277016162872,
-0.23340818285942078,
-0.046060413122177124,
0.1763489693403244,
-0.06834496557712555,
-0.09970871359109879,
0.11275238543748856,
-0.05998576432466507,
0.06495912373065948,
0.05185548588633537,
0.22969341278076172,
0.06434602290391922,
-0.10832510888576508,
0.013544921763241291,
-0.028006665408611298,
0.07215582579374313,
-0.028255287557840347,
0.040728241205215454,
-0.0027621129993349314,
0.01762871816754341,
0.009216014295816422,
-0.0474122054874897,
0.03276180103421211,
-0.11149640381336212,
-0.07576847821474075,
-0.03070453554391861,
-0.1128845065832138,
0.03991573303937912,
0.060984931886196136,
0.05753679201006889,
-0.10753083229064941,
-0.08127839118242264,
0.07465328276157379,
0.08580656349658966,
-0.06548922508955002,
0.024585286155343056,
-0.043673962354660034,
0.07194507122039795,
-0.07038328051567078,
-0.03532438725233078,
-0.16421592235565186,
-0.06735671311616898,
0.002012982266023755,
0.029783261939883232,
-0.01180114783346653,
-0.000572803255636245,
0.10297748446464539,
0.07965953648090363,
-0.07174836099147797,
-0.02847411297261715,
-0.033096954226493835,
0.014363096095621586,
-0.13657373189926147,
-0.2328273504972458,
-0.022930286824703217,
-0.04050860181450844,
0.1501767784357071,
-0.23929166793823242,
0.03051971085369587,
0.010287766344845295,
0.09293410927057266,
0.044498980045318604,
-0.05973571911454201,
-0.02039284072816372,
0.07095915079116821,
-0.019051438197493553,
-0.07896297425031662,
0.057149264961481094,
-0.007335355505347252,
-0.06639008969068527,
-0.055831290781497955,
-0.13228294253349304,
0.15751545131206512,
0.10019975155591965,
-0.004078176338225603,
-0.11744052171707153,
-0.015779897570610046,
-0.06322822719812393,
-0.036502737551927567,
-0.04921418055891991,
0.03083452768623829,
0.11007975041866302,
0.019866736605763435,
0.12157699465751648,
-0.07887081801891327,
-0.04035579413175583,
0.028628267347812653,
-0.0353383868932724,
0.037596773356199265,
0.13556770980358124,
0.11222170293331146,
-0.059346333146095276,
0.13695555925369263,
0.10825370997190475,
-0.07981329411268234,
0.13911008834838867,
-0.03440477326512337,
-0.08606589585542679,
-0.03794604912400246,
0.029767198488116264,
0.004033701494336128,
0.17581979930400848,
-0.04065689817070961,
0.018133889883756638,
-0.00915293488651514,
0.018310146406292915,
0.021579058840870857,
-0.23123903572559357,
-0.054207079112529755,
0.012447454035282135,
-0.050882983952760696,
-0.01968756690621376,
-0.028977034613490105,
-0.006387786474078894,
0.1120993047952652,
-0.005732215475291014,
-0.07282625138759613,
0.004286652430891991,
0.009777277708053589,
-0.07454332709312439,
0.21290716528892517,
-0.08575431257486343,
-0.08484464138746262,
-0.0754992738366127,
-0.018611431121826172,
-0.036374494433403015,
0.0036191660910844803,
0.04045433923602104,
-0.07442764192819595,
0.00018111120152752846,
-0.11311650276184082,
-0.0440329872071743,
0.037834275513887405,
0.012391475029289722,
-0.016802283003926277,
-0.027992993593215942,
0.08397715538740158,
-0.08531919121742249,
0.006809047888964415,
-0.05969483405351639,
-0.04843556880950928,
0.052767496556043625,
0.05790656432509422,
0.12960083782672882,
0.14015744626522064,
0.0019301420543342829,
0.013662034645676613,
-0.022462235763669014,
0.242950901389122,
-0.08767858147621155,
0.020257355645298958,
0.07768021523952484,
-0.0017462483374401927,
0.05803244933485985,
0.13787630200386047,
0.07052753120660782,
-0.11454695463180542,
0.010713723488152027,
0.057941898703575134,
-0.03501594066619873,
-0.18141275644302368,
-0.02256263978779316,
-0.03767111152410507,
-0.03976026549935341,
0.07342684268951416,
0.03600732982158661,
-0.025129875168204308,
0.04583367332816124,
0.050631262362003326,
0.008678087964653969,
-0.03973705321550369,
0.0468391478061676,
0.005231901537626982,
0.03599165380001068,
0.10760759562253952,
-0.023070793598890305,
-0.041652750223875046,
0.029734624549746513,
0.010758333839476109,
0.22428634762763977,
-0.027040299028158188,
0.08682271093130112,
0.0599210262298584,
0.18581709265708923,
-0.0265756007283926,
0.06374605000019073,
0.009617885574698448,
-0.06286235898733139,
-0.008167329244315624,
-0.051015015691518784,
-0.020028039813041687,
0.026187272742390633,
-0.06075781583786011,
0.057213034480810165,
-0.08816581219434738,
0.00804157741367817,
0.06326702982187271,
0.2788654863834381,
0.07106366008520126,
-0.322451651096344,
-0.06810558587312698,
0.007120989728718996,
-0.007955084554851055,
-0.03712650388479233,
0.01400902308523655,
0.18586185574531555,
-0.05848078802227974,
0.011783751659095287,
-0.0798751562833786,
0.0667620450258255,
-0.017799410969018936,
0.041648052632808685,
0.05409470945596695,
0.12179894000291824,
-0.03800077736377716,
0.035505060106515884,
-0.2612622082233429,
0.3067564368247986,
0.026420779526233673,
0.09423831105232239,
-0.02763364277780056,
-0.03294151648879051,
0.030412137508392334,
0.04923681169748306,
0.09148463606834412,
-0.00021125024068169296,
-0.05725486949086189,
-0.21652843058109283,
-0.08968980610370636,
0.04382084682583809,
0.11745265871286392,
-0.046150606125593185,
0.1079355999827385,
-0.0025831330567598343,
0.0027370131574571133,
0.05580393224954605,
-0.04576778784394264,
-0.08679673075675964,
-0.0596378929913044,
-0.014007876627147198,
0.012108425609767437,
-0.046774908900260925,
-0.07707913964986801,
-0.10244043171405792,
-0.08720798790454865,
0.11243487149477005,
-0.034056998789310455,
-0.01949567161500454,
-0.13592001795768738,
0.08023295551538467,
0.08837778866291046,
-0.06623832881450653,
0.01114803645759821,
0.03423485904932022,
0.053143274039030075,
0.03578591346740723,
-0.02040780521929264,
0.12657763063907623,
-0.057028528302907944,
-0.17248159646987915,
-0.07195994257926941,
0.1074533611536026,
0.06939782202243805,
0.055705923587083817,
-0.023082612082362175,
0.03714390844106674,
-0.0009311249013990164,
-0.08736453950405121,
0.05834997817873955,
-0.005130249075591564,
0.04963042587041855,
0.009922358207404613,
-0.059730786830186844,
0.06868813186883926,
-0.052705131471157074,
-0.02397601678967476,
0.1269729733467102,
0.31783607602119446,
-0.08734532445669174,
0.032418906688690186,
0.03743632510304451,
-0.06855465471744537,
-0.20485243201255798,
0.08661229908466339,
0.06684688478708267,
0.014799181371927261,
0.07846053689718246,
-0.16281351447105408,
0.0914398580789566,
0.13370917737483978,
-0.016265105456113815,
0.1528962403535843,
-0.3149532675743103,
-0.12227938324213028,
0.07359487563371658,
0.16113412380218506,
0.09006591886281967,
-0.15591664612293243,
-0.02957124635577202,
0.0056481314823031425,
-0.07488568872213364,
0.06484676897525787,
-0.14647600054740906,
0.11352652311325073,
-0.008018549531698227,
0.056500233709812164,
0.019431930035352707,
-0.0651618167757988,
0.13603289425373077,
-0.007677392568439245,
0.1298249512910843,
-0.027462869882583618,
0.00017229083459824324,
0.04018906503915787,
-0.059564776718616486,
-0.0007554350886493921,
-0.06670045107603073,
0.035950325429439545,
-0.05574862286448479,
-0.00638933852314949,
-0.09890008717775345,
0.020802391692996025,
-0.0423106774687767,
-0.05853336676955223,
-0.020101752132177353,
0.05046472325921059,
0.05045793578028679,
-0.010392682626843452,
0.09787792712450027,
-0.021578477695584297,
0.18151070177555084,
0.1167941689491272,
0.05194520577788353,
-0.05827014520764351,
-0.03661877289414406,
0.006430300883948803,
-0.020043138414621353,
0.037105146795511246,
-0.15062826871871948,
0.023921549320220947,
0.14064916968345642,
0.03639879450201988,
0.12288878113031387,
0.06807297468185425,
-0.04839986935257912,
0.014939329586923122,
0.06524438410997391,
-0.1713038980960846,
-0.1256851702928543,
0.011669049970805645,
-0.06689171493053436,
-0.12116467952728271,
0.0491439625620842,
0.1260042041540146,
-0.06504301726818085,
0.0009036299888975918,
-0.013669978827238083,
0.032292790710926056,
-0.044753819704055786,
0.23121120035648346,
0.07032239437103271,
0.05672699958086014,
-0.08385995030403137,
0.06335239112377167,
0.0233678687363863,
-0.05515926331281662,
0.02812754362821579,
0.06749401241540909,
-0.08373232185840607,
-0.023024730384349823,
0.10370562970638275,
0.17669396102428436,
-0.0009927510982379317,
-0.022614233195781708,
-0.1536422222852707,
-0.09048494696617126,
0.04948248714208603,
0.20762085914611816,
0.06340506672859192,
0.010039066895842552,
-0.020685521885752678,
0.013452933169901371,
-0.13195645809173584,
0.10094907879829407,
0.04707048088312149,
0.0831163078546524,
-0.1298723965883255,
0.16881634294986725,
-0.02215495891869068,
0.018075717613101006,
-0.03062490187585354,
0.049260467290878296,
-0.13307209312915802,
0.007386357057839632,
-0.1371866911649704,
-0.03568213805556297,
-0.011326177045702934,
-0.01318325288593769,
0.005363720469176769,
-0.062314216047525406,
-0.07148857414722443,
0.007982299663126469,
-0.12031708657741547,
-0.02423214726150036,
0.03494172543287277,
0.0280293058604002,
-0.12478294223546982,
-0.02754775807261467,
0.02934405393898487,
-0.06783928722143173,
0.06656761467456818,
0.028852159157395363,
0.023022625595331192,
0.054606832563877106,
-0.17452797293663025,
0.02461094968020916,
0.03803294152021408,
-0.026738012209534645,
0.061713047325611115,
-0.07003047317266464,
-0.02629823423922062,
-0.03691922873258591,
0.06185194477438927,
0.024504246190190315,
0.07412097603082657,
-0.11616135388612747,
0.027666810899972916,
-0.04577159509062767,
-0.06139349937438965,
-0.05543227866292,
0.021862955763936043,
0.06390759348869324,
0.03243829682469368,
0.15272119641304016,
-0.09345521777868271,
0.030018772929906845,
-0.22225189208984375,
-0.01875253953039646,
0.0025134508032351732,
-0.08839050680398941,
-0.09274548292160034,
-0.03689824789762497,
0.10086053609848022,
-0.05732670798897743,
0.09653633832931519,
0.004709500819444656,
0.03868068754673004,
0.024370279163122177,
-0.07980536669492722,
-0.010965021327137947,
0.030967703089118004,
0.17882078886032104,
0.01563093811273575,
-0.042906440794467926,
0.05700652673840523,
0.060672301799058914,
0.08418811857700348,
0.10466766357421875,
0.2280784398317337,
0.14748646318912506,
-0.005881519056856632,
0.09021171182394028,
0.01757425256073475,
-0.08627038449048996,
-0.10349864512681961,
0.10035809129476547,
-0.06795518845319748,
0.07581813633441925,
-0.04228260740637779,
0.19554147124290466,
0.09296460449695587,
-0.17159150540828705,
0.019475962966680527,
-0.055532682687044144,
-0.1038079708814621,
-0.11132887750864029,
-0.024321598932147026,
-0.08916375786066055,
-0.14796574413776398,
0.0008173449314199388,
-0.1137663871049881,
0.017420217394828796,
0.13833118975162506,
0.01629234105348587,
0.01280228141695261,
0.19954757392406464,
0.059066042304039,
0.04416282847523689,
0.05455011501908302,
0.022697139531373978,
-0.01721194200217724,
-0.0782986581325531,
-0.10353001207113266,
0.016965437680482864,
-0.03892311453819275,
0.03649540990591049,
-0.06587396562099457,
-0.04216984286904335,
0.0449962243437767,
-0.009044402278959751,
-0.10355991125106812,
0.020580649375915527,
0.01831197738647461,
0.04647715762257576,
0.02259236015379429,
0.0360855758190155,
-0.003995947074145079,
-0.023989368230104446,
0.2589779198169708,
-0.0775478258728981,
-0.030537301674485207,
-0.10948259383440018,
0.2862708270549774,
0.028900576755404472,
0.011265831999480724,
0.006412503309547901,
-0.10604444891214371,
0.025908472016453743,
0.1937614232301712,
0.1748684048652649,
-0.14562995731830597,
0.0021375021897256374,
-0.014229255728423595,
-0.0068125431425869465,
-0.05527873709797859,
0.10939084738492966,
0.08952733129262924,
0.012878216803073883,
-0.09950686246156693,
-0.04191477969288826,
-0.038673076778650284,
-0.026051882654428482,
-0.0556369349360466,
0.03923555463552475,
0.04126104712486267,
0.03710334375500679,
-0.07552030682563782,
0.07508091628551483,
-0.04724143445491791,
-0.1558532416820526,
0.074189193546772,
-0.1970071941614151,
-0.17409774661064148,
-0.014708945527672768,
0.06497570127248764,
-0.017326926812529564,
0.05595823749899864,
-0.03899608552455902,
0.0018353781197220087,
0.07085004448890686,
-0.03778069466352463,
-0.024046223610639572,
-0.10074711591005325,
0.06723732501268387,
-0.1259259134531021,
0.2303810715675354,
-0.05227465182542801,
0.007071623113006353,
0.12367842346429825,
0.022913500666618347,
-0.08477617055177689,
0.08755321055650711,
0.05102904513478279,
-0.10825428366661072,
0.003221701132133603,
0.1210891455411911,
-0.047206055372953415,
0.08581392467021942,
0.05826722830533981,
-0.12105429917573929,
0.007427528966218233,
-0.051937561482191086,
-0.050041329115629196,
-0.0425984151661396,
-0.044129692018032074,
-0.04494886472821236,
0.13682223856449127,
0.19152052700519562,
-0.030460525304079056,
0.05076952651143074,
-0.06677298247814178,
0.03240887075662613,
0.0518043115735054,
0.07700208574533463,
-0.046282730996608734,
-0.25709787011146545,
0.037929635494947433,
0.0627780631184578,
-0.03076905757188797,
-0.251160204410553,
-0.08160525560379028,
0.013826558366417885,
-0.04782271385192871,
-0.06321163475513458,
0.10031105577945709,
0.08680203557014465,
0.0668012872338295,
-0.057996246963739395,
-0.10430809110403061,
-0.061703164130449295,
0.17144586145877838,
-0.1320708692073822,
-0.08404595404863358
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | text-generation | lillybak/QA-Physics_QLoRA-mistral-7b-50epochs-v1 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | 2024-02-08T23:34:31+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
59,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.04788382723927498,
0.16171279549598694,
-0.005352917592972517,
0.02136841043829918,
0.09686184674501419,
0.015111604705452919,
0.07137951999902725,
0.10955451428890228,
-0.020038405433297157,
0.11244286596775055,
0.03330032527446747,
0.09441220015287399,
0.11357662081718445,
0.14772894978523254,
-0.003575492650270462,
-0.232261523604393,
0.05006932094693184,
-0.1246371790766716,
-0.03666049614548683,
0.11627218872308731,
0.15057805180549622,
-0.10109459608793259,
0.0756460502743721,
-0.030913641676306725,
-0.009812407195568085,
-0.033390406519174576,
-0.05693698301911354,
-0.04944330081343651,
0.05103539675474167,
0.07355327904224396,
0.06860782206058502,
0.004711335990577936,
0.09396199136972427,
-0.2655787467956543,
0.020426444709300995,
0.07093948125839233,
-0.0019974696915596724,
0.07591848820447922,
0.05331665277481079,
-0.07516877353191376,
0.09268398582935333,
-0.050851862877607346,
0.14750060439109802,
0.07999978214502335,
-0.09178632497787476,
-0.1916678249835968,
-0.08780492842197418,
0.1011761948466301,
0.18467943370342255,
0.04421152547001839,
-0.023150887340307236,
0.10070723295211792,
-0.08664919435977936,
0.011689732782542706,
0.05446745082736015,
-0.06747105717658997,
-0.052418507635593414,
0.06491605937480927,
0.0793420672416687,
0.0767722949385643,
-0.12429667264223099,
-0.02174406498670578,
0.008611103519797325,
0.00887030828744173,
0.0814518854022026,
0.02427673526108265,
0.15523891150951385,
0.04025983437895775,
-0.12765221297740936,
-0.04938573017716408,
0.1069699227809906,
0.04103906825184822,
-0.04726257547736168,
-0.25091874599456787,
-0.02940361201763153,
-0.025307154282927513,
-0.0306085217744112,
-0.03984487056732178,
0.04118539020419121,
-0.006947068031877279,
0.08044755458831787,
-0.00699204858392477,
-0.07604070007801056,
-0.03760726749897003,
0.06074252352118492,
0.061373963952064514,
0.026066971942782402,
-0.012132911942899227,
0.010845172218978405,
0.11657512187957764,
0.10491005331277847,
-0.12471938878297806,
-0.05219554528594017,
-0.06468912214040756,
-0.07947935909032822,
-0.043697141110897064,
0.03412042558193207,
0.041996799409389496,
0.0503966324031353,
0.24876368045806885,
0.013237204402685165,
0.05510834604501724,
0.03997663035988808,
0.009734313935041428,
0.06435027718544006,
0.11203338205814362,
-0.06008143350481987,
-0.09627178311347961,
-0.027062542736530304,
0.09033986181020737,
0.010054918937385082,
-0.04071144387125969,
-0.05739009380340576,
0.0623612105846405,
0.0185408778488636,
0.11882077902555466,
0.08993595838546753,
0.0032226061448454857,
-0.07099147886037827,
-0.06380297243595123,
0.1967260092496872,
-0.16188356280326843,
0.047058627009391785,
0.0354633666574955,
-0.038969624787569046,
-0.0023125922307372093,
0.007358122151345015,
0.025436079129576683,
-0.01989656314253807,
0.09119832515716553,
-0.05659566447138786,
-0.040517594665288925,
-0.10913336277008057,
-0.03569170460104942,
0.032513219863176346,
0.010858619585633278,
-0.03217906504869461,
-0.030786113813519478,
-0.08418484032154083,
-0.06755144894123077,
0.09449765086174011,
-0.07364831864833832,
-0.053648900240659714,
-0.01785014383494854,
-0.07429704070091248,
0.025341181084513664,
0.02034521847963333,
0.07678651064634323,
-0.019926751032471657,
0.04245077818632126,
-0.05644877254962921,
0.059700917452573776,
0.10742949694395065,
0.033078111708164215,
-0.05497613549232483,
0.06192035973072052,
-0.24182282388210297,
0.10019542276859283,
-0.06878995895385742,
0.05493709444999695,
-0.1513376086950302,
-0.0262905303388834,
0.049252137541770935,
0.0076136840507388115,
-0.010768214240670204,
0.13709646463394165,
-0.21793904900550842,
-0.028675777837634087,
0.16038778424263,
-0.09573561698198318,
-0.07581635564565659,
0.061356328427791595,
-0.053495727479457855,
0.10603067278862,
0.041206974536180496,
-0.0253668911755085,
0.06327881664037704,
-0.1329721212387085,
0.0035808775573968887,
-0.045546747744083405,
-0.018045976758003235,
0.16059941053390503,
0.07648856192827225,
-0.06927888095378876,
0.07070852816104889,
0.024078376591205597,
-0.026113634929060936,
-0.046159777790308,
-0.018227294087409973,
-0.1095207929611206,
0.010817212983965874,
-0.060132887214422226,
0.02282119169831276,
-0.025257518514990807,
-0.09224134683609009,
-0.028882192447781563,
-0.17473143339157104,
-0.01543671078979969,
0.0841502845287323,
-0.008552714250981808,
-0.019770942628383636,
-0.11773128807544708,
0.014404429122805595,
0.038445498794317245,
0.0027449382469058037,
-0.13180501759052277,
-0.050576433539390564,
0.027280667796730995,
-0.1619797945022583,
0.03360215947031975,
-0.051585033535957336,
0.05001852661371231,
0.0318891666829586,
-0.03249809890985489,
-0.028068941086530685,
0.022396177053451538,
0.005391599610447884,
-0.013861955143511295,
-0.24684561789035797,
-0.02524387463927269,
-0.022996457293629646,
0.16599495708942413,
-0.21521428227424622,
0.03807735815644264,
0.0733959823846817,
0.1517697423696518,
0.009051989763975143,
-0.03698690980672836,
0.0017559787956997752,
-0.07388318330049515,
-0.03124045953154564,
-0.05945143476128578,
-0.007037308998405933,
-0.03604515269398689,
-0.05787331610918045,
0.047536347061395645,
-0.16902238130569458,
-0.02949199639260769,
0.10039274394512177,
0.06592373549938202,
-0.13678009808063507,
-0.022425442934036255,
-0.034927621483802795,
-0.04287220165133476,
-0.05416050925850868,
-0.05881212651729584,
0.10532104223966599,
0.05762924998998642,
0.04464157670736313,
-0.0650712326169014,
-0.07518194615840912,
0.00088359450455755,
-0.020143218338489532,
-0.023713968694210052,
0.09234753251075745,
0.07105407863855362,
-0.126350998878479,
0.09208080917596817,
0.10551702976226807,
0.08511383831501007,
0.09815585613250732,
-0.024149423465132713,
-0.08191148191690445,
-0.050659939646720886,
0.02379353903234005,
0.01600629836320877,
0.13259312510490417,
-0.010838953778147697,
0.05292908474802971,
0.04124988242983818,
-0.013232617639005184,
0.009245194494724274,
-0.0925365537405014,
0.03198198601603508,
0.03315291553735733,
-0.018429066985845566,
0.039537809789180756,
-0.03881950303912163,
0.020082874223589897,
0.08976095914840698,
0.047349054366350174,
0.039120472967624664,
0.014505230821669102,
-0.046636730432510376,
-0.11192648112773895,
0.16611367464065552,
-0.12793833017349243,
-0.23291675746440887,
-0.14571763575077057,
0.003718912834301591,
0.03641049191355705,
-0.010390745475888252,
0.002204331336542964,
-0.06504169851541519,
-0.11800546944141388,
-0.09107901155948639,
0.010856508277356625,
0.049631036818027496,
-0.08566083759069443,
-0.05643118917942047,
0.05523066222667694,
0.039479292929172516,
-0.14542964100837708,
0.01921185478568077,
0.04928894340991974,
-0.09167466312646866,
-0.008233107626438141,
0.08074086904525757,
0.06674882769584656,
0.18043169379234314,
0.013242475688457489,
-0.022343328222632408,
0.032658565789461136,
0.21998950839042664,
-0.1353374421596527,
0.1128942146897316,
0.14020681381225586,
-0.09332811832427979,
0.08355985581874847,
0.20060832798480988,
0.04187845438718796,
-0.10058243572711945,
0.03296395763754845,
0.017997587099671364,
-0.030420765280723572,
-0.24256370961666107,
-0.07092253863811493,
-0.00026266687200404704,
-0.0599735751748085,
0.07366035133600235,
0.08954169601202011,
0.09123681485652924,
0.01494339108467102,
-0.0955287516117096,
-0.080891452729702,
0.056770894676446915,
0.10385555773973465,
0.019311824813485146,
-0.012641520239412785,
0.09103459119796753,
-0.03278684988617897,
0.016931859776377678,
0.0904497355222702,
0.0008944828878156841,
0.17511117458343506,
0.058405566960573196,
0.18374158442020416,
0.0765325129032135,
0.07154922187328339,
0.015365427359938622,
0.009895091876387596,
0.017764348536729813,
0.02660132572054863,
-0.0053646075539290905,
-0.08453443646430969,
-0.014433449134230614,
0.11945675313472748,
0.07353336364030838,
0.017197363078594208,
0.016192223876714706,
-0.04000629484653473,
0.08344162255525589,
0.17407093942165375,
-0.003780076280236244,
-0.18052507936954498,
-0.06431038677692413,
0.08350689709186554,
-0.09346359968185425,
-0.10017222911119461,
-0.02494942955672741,
0.030767329037189484,
-0.17044265568256378,
0.0249007735401392,
-0.016930779442191124,
0.11206945031881332,
-0.13528640568256378,
-0.019095007330179214,
0.06340263038873672,
0.07177523523569107,
-0.0006523873889818788,
0.058229442685842514,
-0.16294988989830017,
0.10450614243745804,
0.012098570354282856,
0.06693841516971588,
-0.09612328559160233,
0.09953869134187698,
-0.005955029278993607,
-0.010155374184250832,
0.1313311606645584,
0.009115277789533138,
-0.07581817358732224,
-0.07944932579994202,
-0.09122282266616821,
-0.009041238576173782,
0.126266211271286,
-0.14647246897220612,
0.08482405543327332,
-0.03597019985318184,
-0.0416097566485405,
0.002930275397375226,
-0.10596253722906113,
-0.12220548838376999,
-0.18631164729595184,
0.055513981729745865,
-0.13507777452468872,
0.03854088857769966,
-0.10657316446304321,
-0.035541050136089325,
-0.030116569250822067,
0.18516884744167328,
-0.22976601123809814,
-0.06906338781118393,
-0.15047605335712433,
-0.09873856604099274,
0.14586862921714783,
-0.050321947783231735,
0.08481817692518234,
-0.00589280528947711,
0.1804574877023697,
0.02166794426739216,
-0.021489109843969345,
0.09810362011194229,
-0.09247367084026337,
-0.19692669808864594,
-0.08017813414335251,
0.15722282230854034,
0.13640479743480682,
0.036161039024591446,
-0.003470085794106126,
0.038310710340738297,
-0.019128555431962013,
-0.12300188839435577,
0.021808674558997154,
0.17748361825942993,
0.06226111575961113,
0.02378440462052822,
-0.025610120967030525,
-0.11692396551370621,
-0.06900777667760849,
-0.03363456577062607,
0.030739158391952515,
0.1859661191701889,
-0.07158373296260834,
0.18602654337882996,
0.14774003624916077,
-0.058341678231954575,
-0.19670341908931732,
0.009590700268745422,
0.0356709361076355,
0.0062993373721838,
0.03402268886566162,
-0.20171645283699036,
0.08260589838027954,
-0.0000703737823641859,
-0.05092230439186096,
0.12990811467170715,
-0.1724688857793808,
-0.15031461417675018,
0.07340911030769348,
0.036582015454769135,
-0.191009521484375,
-0.11979404836893082,
-0.08877003937959671,
-0.05305791646242142,
-0.18255825340747833,
0.10235996544361115,
0.03505839407444,
0.007234846707433462,
0.033568330109119415,
0.030296791344881058,
0.016846131533384323,
-0.03902881219983101,
0.19317437708377838,
-0.025881100445985794,
0.03175598382949829,
-0.08486942201852798,
-0.0721178725361824,
0.04698624834418297,
-0.05440608412027359,
0.07560842484235764,
-0.02850610576570034,
0.010811456479132175,
-0.10112031549215317,
-0.04238447546958923,
-0.02994711697101593,
0.014171373099088669,
-0.09643256664276123,
-0.0892103835940361,
-0.04899745434522629,
0.09385206550359726,
0.09383191168308258,
-0.03679990395903587,
-0.033308759331703186,
-0.0708332359790802,
0.04319954290986061,
0.1834612935781479,
0.1771630197763443,
0.04282272979617119,
-0.07718019932508469,
-0.004353965632617474,
-0.012391943484544754,
0.04512987285852432,
-0.216888889670372,
0.0646008849143982,
0.04998873919248581,
0.017488451674580574,
0.119838647544384,
-0.02023271657526493,
-0.15518377721309662,
-0.06958208978176117,
0.06293158233165741,
-0.05947147309780121,
-0.19729353487491608,
0.005153949372470379,
0.05639190226793289,
-0.16896353662014008,
-0.04793788120150566,
0.04407742992043495,
-0.004272493068128824,
-0.04013913497328758,
0.019694777205586433,
0.08993566036224365,
0.003983452916145325,
0.06979537010192871,
0.057179566472768784,
0.08297405391931534,
-0.10303977131843567,
0.07298099994659424,
0.08502772450447083,
-0.07904176414012909,
0.02611508034169674,
0.09225213527679443,
-0.05959508195519447,
-0.03061521053314209,
0.024558385834097862,
0.08217264711856842,
0.011403042823076248,
-0.04143837094306946,
0.011890463531017303,
-0.10493540018796921,
0.061552610248327255,
0.0872589722275734,
0.033055905252695084,
0.014960144646465778,
0.0323425829410553,
0.04615075886249542,
-0.06838563084602356,
0.12262481451034546,
0.028603000566363335,
0.01619773730635643,
-0.039672788232564926,
-0.04883408173918724,
0.023656455799937248,
-0.03148266673088074,
-0.006783190183341503,
-0.034929223358631134,
-0.07470342516899109,
-0.017337948083877563,
-0.16813358664512634,
-0.015706919133663177,
-0.04851626604795456,
0.01141374558210373,
0.030727919191122055,
-0.039717670530080795,
0.008398020640015602,
0.007660517003387213,
-0.0750393494963646,
-0.06366884708404541,
-0.022168075665831566,
0.09360232949256897,
-0.16274383664131165,
0.0231650248169899,
0.08795329183340073,
-0.12010334432125092,
0.093709796667099,
0.017991894856095314,
-0.005580618511885405,
0.030415862798690796,
-0.15203481912612915,
0.03863019123673439,
-0.030480829998850822,
0.014001374132931232,
0.0430658757686615,
-0.2246030569076538,
-0.00014216898125596344,
-0.03392428159713745,
-0.06211007013916969,
-0.008089113049209118,
-0.03614491969347,
-0.11279971152544022,
0.10460628569126129,
0.00755698699504137,
-0.09058507531881332,
-0.031222015619277954,
0.03175928816199303,
0.08461960405111313,
-0.023131132125854492,
0.15904083847999573,
-0.003058732021600008,
0.07367146760225296,
-0.16738978028297424,
-0.019550222903490067,
-0.009911867789924145,
0.019858263432979584,
-0.021036015823483467,
-0.013049607165157795,
0.039891984313726425,
-0.023009097203612328,
0.1832437962293625,
-0.02614782750606537,
0.02115444466471672,
0.06662114709615707,
0.031309690326452255,
-0.027116473764181137,
0.10507345199584961,
0.05415768921375275,
0.02187212184071541,
0.019098330289125443,
0.0009401091956533492,
-0.04275880753993988,
-0.026286903768777847,
-0.20222914218902588,
0.06478860974311829,
0.14196400344371796,
0.09015882015228271,
-0.019612208008766174,
0.082443006336689,
-0.09847161918878555,
-0.11266232281923294,
0.12008036673069,
-0.05389230325818062,
-0.005624994169920683,
-0.06746947765350342,
0.1300724893808365,
0.1476544737815857,
-0.19186675548553467,
0.07097877562046051,
-0.06951600313186646,
-0.049371387809515,
-0.11596925556659698,
-0.19563089311122894,
-0.0579688623547554,
-0.05182981118559837,
-0.01601085439324379,
-0.04734842851758003,
0.07465895265340805,
0.05611773207783699,
0.007687699515372515,
-0.0008743742946535349,
0.06143457442522049,
-0.025334985926747322,
-0.00020855919865425676,
0.026871640235185623,
0.06543756276369095,
0.01277367677539587,
-0.028740158304572105,
0.017883067950606346,
-0.009029596112668514,
0.04200661554932594,
0.06335420906543732,
0.04628584161400795,
-0.029481444507837296,
0.015326657332479954,
-0.04012451693415642,
-0.10723566263914108,
0.0419759564101696,
-0.027193402871489525,
-0.08225540816783905,
0.14785805344581604,
0.02399633452296257,
0.009130166843533516,
-0.019807780161499977,
0.24066896736621857,
-0.07349257171154022,
-0.09820521622896194,
-0.1490466147661209,
0.10572494566440582,
-0.04344555735588074,
0.06301548331975937,
0.046267855912446976,
-0.10314686596393585,
0.017511071637272835,
0.12181373685598373,
0.1645330935716629,
-0.0424080528318882,
0.020746879279613495,
0.0270154420286417,
0.0042765699326992035,
-0.03603396192193031,
0.05116730183362961,
0.06923956423997879,
0.15690730512142181,
-0.04900969937443733,
0.09728439897298813,
-0.0028536769095808268,
-0.09575258195400238,
-0.03706898167729378,
0.11544451117515564,
-0.015991076827049255,
0.016934793442487717,
-0.05673288553953171,
0.11960674822330475,
-0.06204056739807129,
-0.23141460120677948,
0.059825554490089417,
-0.0669918954372406,
-0.136424258351326,
-0.021505871787667274,
0.08302503079175949,
-0.012656555511057377,
0.027061283588409424,
0.07233231514692307,
-0.07476846873760223,
0.1983826905488968,
0.036584943532943726,
-0.05408371239900589,
-0.05269603058695793,
0.08472228795289993,
-0.10221095383167267,
0.2712222933769226,
0.01703515276312828,
0.05113283172249794,
0.10301852226257324,
-0.012269208207726479,
-0.13325491547584534,
0.021790657192468643,
0.09555859118700027,
-0.09376159310340881,
0.04151248186826706,
0.19850991666316986,
0.00041501864325255156,
0.12115148454904556,
0.08070485293865204,
-0.07617492228746414,
0.04874774441123009,
-0.09502684324979782,
-0.07229389250278473,
-0.08947079628705978,
0.09731078147888184,
-0.07675671577453613,
0.14196333289146423,
0.13027575612068176,
-0.05282389745116234,
0.009622754529118538,
-0.02872757986187935,
0.046359382569789886,
0.0037509698886424303,
0.1005694642663002,
0.008517593145370483,
-0.18598082661628723,
0.021583275869488716,
0.013244304805994034,
0.10594569146633148,
-0.1648784875869751,
-0.09909144788980484,
0.03998237103223801,
0.0028793413657695055,
-0.06011311709880829,
0.12933798134326935,
0.060960717499256134,
0.04498228803277016,
-0.0423818863928318,
-0.02333086170256138,
-0.009747753851115704,
0.13612231612205505,
-0.10099201649427414,
0.0027629989199340343
] |
null | null | transformers |
# Model Card for Model (h2o-danube-1.8b-chat-sft-merge_fourier-v1)
```
models merge fourier :
- h2oai/h2o-danube-1.8b-chat
- h2oai/h2o-danube-1.8b-sft
```
```Python
from transformers import AutoModelForCausalLM, AutoTokenizer,pipeline
import torch
model_id="NickyNicky/h2o-danube-1.8b-chat-sft-merge_fourier-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id,
device_map="auto",
trust_remote_code=True,
# load_in_4bit=True,
).eval() #
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer
)
txt= "dame un ejemplo del lenguaje de programacion Python"
messages = [
{"role": "user", "content":txt},
]
prompt = pipe.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
)
res = pipe(
prompt,
max_new_tokens=2056,
do_sample=True,
temperature=0.31, # 0.31 # 0.41
)
print(res[0]["generated_text"])
###### OUTPUT:
# <|prompt|>dame un ejemplo del lenguaje de programacion Python</s><|answer|> ¡Dame un ejemplo del lenguaje de programación Python!
# Python es una linguita de programación que se utiliza para crear aplicaciones y programas en la computadora. Es muy fácil de usar y tiene una estructura de programación simple, lo que lo hace ideal para principiantes.
# A continuación, te proporciono un ejemplo simple de una función en Python:
# ```python
# def suma_integers(num1, num2):
# return num1 + num2
# num1 = 5
# num2 = 2
# result = suma_integers(num1, num2)
# print(result)
# ```
# Esta función calcula el sumo de los números 5 y 2, lo que es 7.
# En este ejemplo, la función suma_integers(num1, num2) recibe dos números como parámetros y calcula el sumo de ellos. La función devuelve el resultado, que es 7.
# Es importante mencionar que Python tiene una gran variedad de funciones y métodos, y es posible crear funciones para hacer todo tipo de cosas. Además, Python tiene una gran comunidad de usuarios y desarrolladores, lo que te permite encontrar soluciones a tus problemas de programación.
``` | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge"], "widget": [{"text": "<|prompt|>dame un ejemplo del lenguaje de programacion Python</s><|answer|> \n"}]} | text-generation | NickyNicky/h2o-danube-1.8b-chat-sft-merge_fourier-v1 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"conversational",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-08T23:36:29+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #merge #conversational #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model (h2o-danube-1.8b-chat-sft-merge_fourier-v1)
!image/png
python
# def suma_integers(num1, num2):
# return num1 + num2
# num1 = 5
# num2 = 2
# result = suma_integers(num1, num2)
# print(result)
# | [
"# Model Card for Model (h2o-danube-1.8b-chat-sft-merge_fourier-v1)\n\n!image/png\n\n\n\n\npython",
"# def suma_integers(num1, num2):",
"# return num1 + num2",
"# num1 = 5",
"# num2 = 2",
"# result = suma_integers(num1, num2)",
"# print(result)",
"#"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #merge #conversational #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model (h2o-danube-1.8b-chat-sft-merge_fourier-v1)\n\n!image/png\n\n\n\n\npython",
"# def suma_integers(num1, num2):",
"# return num1 + num2",
"# num1 = 5",
"# num2 = 2",
"# result = suma_integers(num1, num2)",
"# print(result)",
"#"
] | [
64,
36,
14,
7,
5,
5,
13,
6,
1
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #merge #conversational #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model (h2o-danube-1.8b-chat-sft-merge_fourier-v1)\n\n!image/png\n\n\n\n\npython# def suma_integers(num1, num2):# return num1 + num2# num1 = 5# num2 = 2# result = suma_integers(num1, num2)# print(result)#"
] | [
-0.03747275844216347,
0.10352818667888641,
-0.0037475500721484423,
0.04047519713640213,
0.10900994390249252,
0.020114706829190254,
0.14427898824214935,
0.07359565794467926,
-0.012919273227453232,
0.05694779381155968,
0.11853673309087753,
0.1342622935771942,
0.09082753211259842,
0.13903158903121948,
-0.07924407720565796,
-0.1705283224582672,
0.10830186307430267,
-0.045857612043619156,
-0.07508397847414017,
0.05861804261803627,
0.05923372879624367,
-0.015718601644039154,
0.10760025680065155,
-0.018347907811403275,
-0.09541800618171692,
0.0005956526729278266,
-0.013688488863408566,
-0.041634052991867065,
0.05110965669155121,
0.11200784146785736,
-0.025925640016794205,
0.08967307955026627,
0.01070696022361517,
-0.19198894500732422,
0.02910550683736801,
0.05162128433585167,
-0.046915873885154724,
0.03159533441066742,
0.08062199503183365,
0.004163844510912895,
0.2211746722459793,
-0.028411075472831726,
-0.024182835593819618,
0.0812564268708229,
-0.05868883430957794,
-0.06903945654630661,
-0.053408026695251465,
0.05682854726910591,
0.12935461103916168,
0.03710639476776123,
-0.026507457718253136,
0.04628906771540642,
0.004040676634758711,
0.04432246461510658,
-0.023140357807278633,
-0.2427184134721756,
-0.0028300497215241194,
0.10118895769119263,
-0.027173060923814774,
0.04478290304541588,
0.042555034160614014,
0.010110320523381233,
0.0376911498606205,
-0.030749961733818054,
-0.04907861351966858,
-0.013241183012723923,
0.19284047186374664,
-0.019450301304459572,
-0.1363297700881958,
-0.03359965980052948,
0.1582275629043579,
0.08038565516471863,
-0.007597155869007111,
-0.056715916842222214,
-0.11877131462097168,
0.0018453578231856227,
-0.05754926800727844,
-0.015326512046158314,
-0.005127672106027603,
0.062172915786504745,
0.0831741914153099,
0.06312809884548187,
-0.0604303777217865,
-0.0028592192102223635,
-0.08043758571147919,
-0.07516417652368546,
0.047078512609004974,
0.04519424960017204,
-0.11579295992851257,
0.0167202390730381,
-0.0431862436234951,
-0.09271266311407089,
-0.015787312760949135,
-0.05096318572759628,
0.012471013702452183,
0.02866337075829506,
-0.02513664960861206,
-0.12539227306842804,
0.14439460635185242,
0.03087487444281578,
-0.026159219443798065,
0.13602595031261444,
-0.060527652502059937,
0.04760046303272247,
0.038268256932497025,
-0.10473115742206573,
-0.07821392267942429,
-0.07338964194059372,
0.019470885396003723,
0.024303410202264786,
0.10292791575193405,
-0.031167414039373398,
-0.09124698489904404,
0.07327041774988174,
0.028152117505669594,
-0.005348674952983856,
0.025498896837234497,
0.08485466986894608,
0.013560602441430092,
-0.003775529796257615,
0.1038181334733963,
-0.07467693835496902,
0.0016557108610868454,
0.05545136705040932,
0.015876924619078636,
0.1421070545911789,
0.06129658594727516,
0.004773339722305536,
-0.07862874865531921,
0.02718511037528515,
-0.04720762372016907,
-0.03309791162610054,
-0.008363308385014534,
-0.08526869863271713,
0.0699516162276268,
0.02814682386815548,
-0.0321885384619236,
-0.12129171937704086,
-0.06064189225435257,
0.057370495051145554,
0.07070216536521912,
-0.060609739273786545,
-0.006789590697735548,
-0.08670259267091751,
0.020755352452397346,
0.006669976748526096,
0.02188987284898758,
-0.03439849987626076,
-0.05188644304871559,
0.0440305694937706,
0.057937271893024445,
0.10616455227136612,
-0.1311778724193573,
-0.00039149235817603767,
-0.062048573046922684,
0.10266029089689255,
-0.028256049379706383,
0.062119439244270325,
-0.03691554069519043,
0.031238863244652748,
-0.11162170767784119,
-0.05119670182466507,
-0.03842538222670555,
-0.030103551223874092,
0.061163563281297684,
0.14772051572799683,
-0.07367337495088577,
-0.05157340317964554,
0.16799895465373993,
-0.14798086881637573,
-0.1980794370174408,
0.15368464589118958,
0.010735951364040375,
-0.03529000282287598,
-0.012909738346934319,
0.13305321335792542,
0.06237686052918434,
-0.02303163707256317,
0.01417213398963213,
0.06380969285964966,
-0.043891891837120056,
-0.05870410054922104,
0.0842023640871048,
0.014244439080357552,
-0.26067227125167847,
0.06388861685991287,
0.10955042392015457,
0.056185267865657806,
-0.021453605964779854,
-0.08503404259681702,
-0.061151884496212006,
-0.032753705978393555,
0.05861792340874672,
-0.04058320075273514,
-0.0017161930445581675,
-0.06521233171224594,
-0.04596647992730141,
-0.00535937212407589,
0.073312908411026,
-0.07925025373697281,
-0.02877345308661461,
-0.07717265188694,
0.13431979715824127,
-0.13794966042041779,
0.07438313215970993,
-0.030352482572197914,
0.002232395811006427,
-0.05098023638129234,
-0.10547720640897751,
0.006857556756585836,
0.07726061344146729,
0.04206652194261551,
0.09777642786502838,
0.02104821614921093,
0.015648648142814636,
0.1735777109861374,
0.04779389128088951,
-0.004510446451604366,
-0.13253921270370483,
0.018934309482574463,
-0.015487243421375751,
0.3167223036289215,
-0.13913974165916443,
0.03540914133191109,
-0.05582767724990845,
0.07756800204515457,
-0.0955718383193016,
0.026163149625062943,
-0.010900715366005898,
-0.016035834327340126,
-0.05759555473923683,
0.02236943505704403,
0.08679790794849396,
0.03710081800818443,
-0.1014392226934433,
0.029835719615221024,
-0.25491607189178467,
0.07610112428665161,
0.1635076105594635,
-0.016187334433197975,
0.014336738735437393,
-0.005968588404357433,
-0.023489316925406456,
-0.030609026551246643,
0.023142801597714424,
0.042637839913368225,
-0.10019265115261078,
-0.008566601201891899,
0.13049107789993286,
-0.05945725739002228,
0.017324797809123993,
0.1207825317978859,
-0.06912516802549362,
-0.09376677125692368,
0.06804248690605164,
0.15575480461120605,
-0.22915080189704895,
0.08490400016307831,
0.14582830667495728,
-0.009268246591091156,
0.0575280599296093,
-0.003865934908390045,
-0.02049662359058857,
-0.040702935308218,
0.09250861406326294,
0.010893183760344982,
-0.008049342781305313,
-0.15791726112365723,
0.08263714611530304,
0.04237981513142586,
0.010608010925352573,
0.05974072590470314,
-0.10100309550762177,
0.00863607693463564,
0.04195411875844002,
-0.02193579450249672,
-0.07821942865848541,
0.078358493745327,
0.0015364931896328926,
0.06831226497888565,
-0.013178888708353043,
-0.024091526865959167,
0.06188448145985603,
0.004648409318178892,
-0.15738271176815033,
0.17879721522331238,
-0.09953831136226654,
-0.26375073194503784,
-0.1509033888578415,
-0.09704231470823288,
-0.13545380532741547,
-0.006433278322219849,
0.11141418665647507,
-0.05481800436973572,
-0.06389099359512329,
-0.16927044093608856,
-0.07618353515863419,
-0.11706386506557465,
0.019969278946518898,
0.03092571720480919,
-0.024919403716921806,
0.0773051381111145,
-0.0833158791065216,
-0.020077073946595192,
0.038364227861166,
0.02192852832376957,
0.0921202227473259,
-0.051809921860694885,
0.0822342187166214,
0.18000370264053345,
-0.07652261108160019,
0.053895194083452225,
0.02176973782479763,
0.18493294715881348,
0.07627616822719574,
0.03729066625237465,
0.1428777575492859,
-0.038204509764909744,
0.09030427783727646,
0.1537596434354782,
-0.024441741406917572,
-0.03783542290329933,
0.027611160650849342,
-0.04060904309153557,
-0.0721411406993866,
-0.1341550499200821,
-0.09190095216035843,
-0.07408349961042404,
0.13767708837985992,
0.06701377034187317,
0.07027515769004822,
0.02293306216597557,
0.1094038337469101,
-0.011303335428237915,
-0.0010701706632971764,
0.045788418501615524,
0.07585426419973373,
0.23432141542434692,
0.012316226959228516,
0.08628575503826141,
-0.09003902226686478,
-0.024575715884566307,
0.07583052664995193,
0.0009008969063870609,
-0.015445515513420105,
0.054900161921978,
0.017681241035461426,
0.06505928933620453,
0.12051999568939209,
0.04549141600728035,
0.07649204134941101,
0.007908818311989307,
0.017476124688982964,
-0.03325952962040901,
-0.07452716678380966,
-0.045219238847494125,
0.04119691997766495,
-0.033826831728219986,
-0.007588275708258152,
-0.11682804673910141,
0.12974263727664948,
0.05288580432534218,
-0.04569359868764877,
0.1318206936120987,
-0.29449936747550964,
-0.0740407258272171,
0.055314406752586365,
0.07548762112855911,
-0.029497496783733368,
0.0352092981338501,
0.009678514674305916,
0.00187345698941499,
0.11682536453008652,
-0.05834488943219185,
0.07312732189893723,
0.05433344841003418,
0.04272117838263512,
-0.022115889936685562,
0.07243991643190384,
0.029528288170695305,
0.0943542942404747,
-0.18195492029190063,
0.0675823837518692,
-0.018081679940223694,
-0.0037747803144156933,
-0.03927454352378845,
0.05888131633400917,
-0.026922352612018585,
0.09720094501972198,
0.07108709961175919,
0.004322395194321871,
-0.1676100194454193,
-0.04557487368583679,
-0.024786697700619698,
0.07771164178848267,
0.039243634790182114,
0.09734359383583069,
0.019666388630867004,
-0.06010929122567177,
-0.032198917120695114,
0.025480521842837334,
0.1493852436542511,
-0.12056463956832886,
-0.1889582872390747,
0.07588275521993637,
0.02198564074933529,
0.014537249691784382,
-0.01636022888123989,
0.025429742410779,
-0.16473819315433502,
0.23087738454341888,
-0.008157942444086075,
-0.05193757638335228,
-0.07359519600868225,
-0.009095350280404091,
0.010523821227252483,
-0.05796431750059128,
0.036544542759656906,
-0.10604072362184525,
0.05056718364357948,
-0.05917389690876007,
-0.21457864344120026,
0.09453945606946945,
-0.08105967193841934,
-0.012863428331911564,
-0.032461799681186676,
0.08765105903148651,
-0.061967965215444565,
-0.02136163040995598,
0.030085517093539238,
-0.017612654715776443,
-0.07231433689594269,
-0.10780734568834305,
0.017175516113638878,
0.1393977552652359,
0.013222680427134037,
-0.04491284862160683,
-0.015558015555143356,
-0.08959995210170746,
0.030790574848651886,
-0.008677440695464611,
0.1557367444038391,
0.26404649019241333,
-0.0713922381401062,
0.056960541754961014,
0.1835627406835556,
-0.039509814232587814,
-0.1879027932882309,
-0.10232368111610413,
-0.1135404035449028,
-0.034517496824264526,
-0.03400266543030739,
-0.028233632445335388,
0.09005728363990784,
0.11076442152261734,
-0.020999059081077576,
0.04835067689418793,
-0.3399757146835327,
-0.07674887776374817,
0.09993799030780792,
0.1308303028345108,
0.2711920142173767,
-0.13126008212566376,
-0.03351277485489845,
-0.1326773315668106,
-0.2885020971298218,
0.13566824793815613,
-0.10007096827030182,
0.041074782609939575,
-0.004601439461112022,
0.029464976862072945,
-0.012452557682991028,
-0.09006834030151367,
0.11411092430353165,
-0.027530362829566002,
0.0017053240444511175,
-0.08831718564033508,
0.05938190966844559,
0.02963731810450554,
-0.060919176787137985,
0.12567265331745148,
-0.23325547575950623,
0.08399078249931335,
-0.015218136832118034,
-0.03693964704871178,
0.0008452166221104562,
0.01584404706954956,
-0.038211967796087265,
-0.0426662340760231,
-0.05015033110976219,
-0.05260251462459564,
0.14820422232151031,
-0.00960957258939743,
0.04856500402092934,
-0.01779591105878353,
0.09648575633764267,
0.2817017734050751,
0.022755401208996773,
-0.09092514961957932,
0.052255779504776,
-0.01947818696498871,
-0.08234371244907379,
0.03587288409471512,
-0.1784743070602417,
0.05155624449253082,
0.08074015378952026,
-0.04394323751330376,
0.1328776627779007,
0.07559364289045334,
0.01044557522982359,
-0.014650875702500343,
0.0948331207036972,
-0.14407211542129517,
-0.32642892003059387,
-0.019503876566886902,
0.08537358045578003,
-0.05255074054002762,
0.05512741580605507,
0.09290942549705505,
-0.0924290344119072,
0.029182543978095055,
0.02144905924797058,
0.06500047445297241,
-0.07303652912378311,
0.037740226835012436,
-0.01815054938197136,
0.06347189098596573,
-0.09407756477594376,
0.08028110861778259,
0.01476456131786108,
-0.22292083501815796,
0.020485684275627136,
0.11636584252119064,
-0.13326182961463928,
-0.11243841052055359,
-0.02774820104241371,
0.11363346874713898,
-0.04202289879322052,
-0.05559046193957329,
-0.028590798377990723,
-0.15114867687225342,
0.05392879247665405,
0.0409369021654129,
0.006681577768176794,
0.027770664542913437,
-0.006864290684461594,
-0.02714282087981701,
-0.1202058270573616,
0.07444927841424942,
0.03920263051986694,
0.04780289903283119,
-0.05928954482078552,
0.002437837887555361,
-0.05092358589172363,
0.039492469280958176,
-0.035344257950782776,
-0.025554288178682327,
-0.10533951967954636,
-0.04685680568218231,
-0.20865657925605774,
0.04229225590825081,
-0.17898081243038177,
-0.020802166312932968,
0.04610968753695488,
0.059228990226984024,
-0.007012976333498955,
0.009706229902803898,
-0.028351223096251488,
-0.03589138761162758,
-0.04669793322682381,
0.0395590178668499,
-0.08423496782779694,
0.044896647334098816,
-0.014412105083465576,
-0.06760386377573013,
0.042799580842256546,
0.04125301539897919,
-0.10229887813329697,
0.020087674260139465,
-0.1165444403886795,
-0.05940791592001915,
0.08303287625312805,
0.017489660531282425,
0.008295278996229172,
-0.06959091126918793,
0.020001642405986786,
0.09199561178684235,
-0.07813888043165207,
-0.019465884193778038,
0.04618506506085396,
-0.054485417902469635,
0.011321513913571835,
-0.13723969459533691,
-0.04259313642978668,
-0.032681986689567566,
-0.05861632525920868,
0.025189319625496864,
0.025881603360176086,
0.15651358664035797,
-0.09267204254865646,
0.03575262427330017,
-0.13110117614269257,
-0.05779772624373436,
0.05609821155667305,
-0.08181170374155045,
-0.05906228721141815,
-0.0493927001953125,
-0.0019863497000187635,
-0.04143841564655304,
0.10719425976276398,
-0.017832987010478973,
-0.09123950451612473,
0.03552592173218727,
-0.0457066185772419,
0.014867626130580902,
0.026487110182642937,
0.3600579500198364,
0.06300460547208786,
-0.010622815228998661,
-0.09939664602279663,
0.009033109992742538,
0.05026937276124954,
0.09070208668708801,
0.08728419244289398,
0.06402627378702164,
-0.09137756377458572,
0.0834047794342041,
0.00007335067493841052,
0.02126113325357437,
-0.05943525210022926,
0.14436544477939606,
-0.10308106243610382,
0.13510382175445557,
-0.001177001977339387,
0.11180947721004486,
0.19821558892726898,
-0.03785836324095726,
-0.03491959720849991,
-0.058803729712963104,
-0.07888758927583694,
-0.12445070594549179,
-0.17589494585990906,
-0.12928137183189392,
-0.184883713722229,
0.0003878108982462436,
-0.040580060333013535,
0.03085780330002308,
0.04156634584069252,
0.08574681729078293,
-0.02878640778362751,
0.02163480781018734,
0.0762527585029602,
0.017924636602401733,
-0.06434091925621033,
-0.030199570581316948,
-0.049499452114105225,
0.0956125557422638,
-0.049060940742492676,
0.04816965386271477,
-0.0382872149348259,
0.044562552124261856,
0.04999183118343353,
0.05893697962164879,
0.13006184995174408,
-0.06931415945291519,
-0.07927156984806061,
-0.004054846707731485,
0.03913681581616402,
-0.013585664331912994,
0.09193733334541321,
0.04551279917359352,
-0.033843327313661575,
0.006104258354753256,
-0.0022087167017161846,
-0.055627454072237015,
-0.10233277082443237,
-0.08697394281625748,
0.30737486481666565,
-0.03996776044368744,
0.09840744733810425,
0.02945731393992901,
-0.060353636741638184,
-0.06405160576105118,
0.16206832230091095,
0.2665911316871643,
-0.007329457905143499,
-0.008141173049807549,
-0.018079956993460655,
0.004464336205273867,
0.03068876825273037,
0.08204422891139984,
0.03984944149851799,
0.15191611647605896,
-0.015619015321135521,
0.08935923129320145,
-0.059979259967803955,
-0.04319857805967331,
-0.07770377397537231,
0.05323339253664017,
-0.011347751133143902,
-0.06795381009578705,
0.03300327807664871,
0.06433811783790588,
-0.14139069616794586,
0.05292779207229614,
-0.017487704753875732,
0.000567382201552391,
-0.028323892503976822,
-0.02423214539885521,
0.09602866321802139,
-0.011356491595506668,
-0.0003226579283364117,
-0.08843173831701279,
-0.015677621588110924,
0.1706002950668335,
0.0006584234652109444,
-0.15653236210346222,
-0.0035120060201734304,
-0.06078299880027771,
0.05793485417962074,
0.03188493102788925,
0.06195876747369766,
-0.01223831344395876,
0.08536970615386963,
0.08004499226808548,
-0.06980501860380173,
0.11760752648115158,
0.02835790626704693,
0.0025068114046007395,
0.036656707525253296,
-0.007624475285410881,
-0.027017422020435333,
0.06435640901327133,
0.031960379332304,
-0.12181181460618973,
-0.014476237818598747,
-0.07944763451814651,
-0.0388617180287838,
-0.014816791750490665,
0.02191772684454918,
-0.022876663133502007,
0.0989956259727478,
0.08478987962007523,
-0.023674266412854195,
0.013919342309236526,
-0.020119721069931984,
0.05292715132236481,
-0.044710177928209305,
0.010129247792065144,
0.01438807975500822,
-0.1419345736503601,
-0.011649856343865395,
-0.0804276093840599,
0.06801571696996689,
-0.2824021279811859,
-0.02378019131720066,
-0.12450159341096878,
0.041721440851688385,
-0.09477867186069489,
0.11203467845916748,
0.1956896334886551,
0.000434061890700832,
-0.09367819875478745,
-0.1423875242471695,
-0.0091690793633461,
0.16019299626350403,
0.01415165513753891,
-0.09549343585968018
] |
null | null | pyannote-audio |
Using this open-source pipeline in production?
Make the most of it thanks to our [consulting services](https://herve.niderb.fr/consulting.html).
# 🎹 Speaker diarization 3.1
This pipeline is the same as [`pyannote/speaker-diarization-3.0`](https://hf.co/pyannote/speaker-diarization-3.1) except it removes the [problematic](https://github.com/pyannote/pyannote-audio/issues/1537) use of `onnxruntime`.
Both speaker segmentation and embedding now run in pure PyTorch. This should ease deployment and possibly speed up inference.
It requires pyannote.audio version 3.1 or higher.
It ingests mono audio sampled at 16kHz and outputs speaker diarization as an [`Annotation`](http://pyannote.github.io/pyannote-core/structure.html#annotation) instance:
- stereo or multi-channel audio files are automatically downmixed to mono by averaging the channels.
- audio files sampled at a different rate are resampled to 16kHz automatically upon loading.
## Requirements
1. Install [`pyannote.audio`](https://github.com/pyannote/pyannote-audio) `3.1` with `pip install pyannote.audio`
2. Accept [`pyannote/segmentation-3.0`](https://hf.co/pyannote/segmentation-3.0) user conditions
3. Accept [`pyannote/speaker-diarization-3.1`](https://hf.co/pyannote-speaker-diarization-3.1) user conditions
4. Create access token at [`hf.co/settings/tokens`](https://hf.co/settings/tokens).
## Usage
```python
# instantiate the pipeline
from pyannote.audio import Pipeline
pipeline = Pipeline.from_pretrained(
"pyannote/speaker-diarization-3.1",
use_auth_token="HUGGINGFACE_ACCESS_TOKEN_GOES_HERE")
# run the pipeline on an audio file
diarization = pipeline("audio.wav")
# dump the diarization output to disk using RTTM format
with open("audio.rttm", "w") as rttm:
diarization.write_rttm(rttm)
```
### Processing on GPU
`pyannote.audio` pipelines run on CPU by default.
You can send them to GPU with the following lines:
```python
import torch
pipeline.to(torch.device("cuda"))
```
### Processing from memory
Pre-loading audio files in memory may result in faster processing:
```python
waveform, sample_rate = torchaudio.load("audio.wav")
diarization = pipeline({"waveform": waveform, "sample_rate": sample_rate})
```
### Monitoring progress
Hooks are available to monitor the progress of the pipeline:
```python
from pyannote.audio.pipelines.utils.hook import ProgressHook
with ProgressHook() as hook:
diarization = pipeline("audio.wav", hook=hook)
```
### Controlling the number of speakers
In case the number of speakers is known in advance, one can use the `num_speakers` option:
```python
diarization = pipeline("audio.wav", num_speakers=2)
```
One can also provide lower and/or upper bounds on the number of speakers using `min_speakers` and `max_speakers` options:
```python
diarization = pipeline("audio.wav", min_speakers=2, max_speakers=5)
```
## Benchmark
This pipeline has been benchmarked on a large collection of datasets.
Processing is fully automatic:
- no manual voice activity detection (as is sometimes the case in the literature)
- no manual number of speakers (though it is possible to provide it to the pipeline)
- no fine-tuning of the internal models nor tuning of the pipeline hyper-parameters to each dataset
... with the least forgiving diarization error rate (DER) setup (named _"Full"_ in [this paper](https://doi.org/10.1016/j.csl.2021.101254)):
- no forgiveness collar
- evaluation of overlapped speech
| Benchmark | [DER%](. "Diarization error rate") | [FA%](. "False alarm rate") | [Miss%](. "Missed detection rate") | [Conf%](. "Speaker confusion rate") | Expected output | File-level evaluation |
| ------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------- | --------------------------- | ---------------------------------- | ----------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| [AISHELL-4](http://www.openslr.org/111/) | 12.2 | 3.8 | 4.4 | 4.0 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AISHELL.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AISHELL.SpeakerDiarization.Benchmark.test.eval) |
| [AliMeeting (_channel 1_)](https://www.openslr.org/119/) | 24.4 | 4.4 | 10.0 | 10.0 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AliMeeting.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AliMeeting.SpeakerDiarization.Benchmark.test.eval) |
| [AMI (_headset mix,_](https://groups.inf.ed.ac.uk/ami/corpus/) [_only_words_)](https://github.com/BUTSpeechFIT/AMI-diarization-setup) | 18.8 | 3.6 | 9.5 | 5.7 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AMI.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AMI.SpeakerDiarization.Benchmark.test.eval) |
| [AMI (_array1, channel 1,_](https://groups.inf.ed.ac.uk/ami/corpus/) [_only_words)_](https://github.com/BUTSpeechFIT/AMI-diarization-setup) | 22.4 | 3.8 | 11.2 | 7.5 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AMI-SDM.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AMI-SDM.SpeakerDiarization.Benchmark.test.eval) |
| [AVA-AVD](https://arxiv.org/abs/2111.14448) | 50.0 | 10.8 | 15.7 | 23.4 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AVA-AVD.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/AVA-AVD.SpeakerDiarization.Benchmark.test.eval) |
| [DIHARD 3 (_Full_)](https://arxiv.org/abs/2012.01477) | 21.7 | 6.2 | 8.1 | 7.3 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/DIHARD.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/DIHARD.SpeakerDiarization.Benchmark.test.eval) |
| [MSDWild](https://x-lance.github.io/MSDWILD/) | 25.3 | 5.8 | 8.0 | 11.5 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/MSDWILD.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/MSDWILD.SpeakerDiarization.Benchmark.test.eval) |
| [REPERE (_phase 2_)](https://islrn.org/resources/360-758-359-485-0/) | 7.8 | 1.8 | 2.6 | 3.5 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/REPERE.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/REPERE.SpeakerDiarization.Benchmark.test.eval) |
| [VoxConverse (_v0.3_)](https://github.com/joonson/voxconverse) | 11.3 | 4.1 | 3.4 | 3.8 | [RTTM](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/VoxConverse.SpeakerDiarization.Benchmark.test.rttm) | [eval](https://huggingface.co/pyannote/speaker-diarization-3.1/blob/main/reproducible_research/VoxConverse.SpeakerDiarization.Benchmark.test.eval) |
## Citations
```bibtex
@inproceedings{Plaquet23,
author={Alexis Plaquet and Hervé Bredin},
title={{Powerset multi-class cross entropy loss for neural speaker diarization}},
year=2023,
booktitle={Proc. INTERSPEECH 2023},
}
```
```bibtex
@inproceedings{Bredin23,
author={Hervé Bredin},
title={{pyannote.audio 2.1 speaker diarization pipeline: principle, benchmark, and recipe}},
year=2023,
booktitle={Proc. INTERSPEECH 2023},
}
```
| {"license": "mit", "tags": ["pyannote", "pyannote-audio", "pyannote-audio-pipeline", "audio", "voice", "speech", "speaker", "speaker-diarization", "speaker-change-detection", "voice-activity-detection", "overlapped-speech-detection", "automatic-speech-recognition"], "extra_gated_prompt": "The collected information will help acquire a better knowledge of pyannote.audio userbase and help its maintainers improve it further. Though this pipeline uses MIT license and will always remain open-source, we will occasionnally email you about premium pipelines and paid services around pyannote.", "extra_gated_fields": {"Company/university": "text", "Website": "text"}} | automatic-speech-recognition | collinbarnwell/pyannote-speaker-diarization-31 | [
"pyannote-audio",
"pyannote",
"pyannote-audio-pipeline",
"audio",
"voice",
"speech",
"speaker",
"speaker-diarization",
"speaker-change-detection",
"voice-activity-detection",
"overlapped-speech-detection",
"automatic-speech-recognition",
"arxiv:2111.14448",
"arxiv:2012.01477",
"license:mit",
"endpoints_compatible",
"region:us"
] | 2024-02-08T23:36:41+00:00 | [
"2111.14448",
"2012.01477"
] | [] | TAGS
#pyannote-audio #pyannote #pyannote-audio-pipeline #audio #voice #speech #speaker #speaker-diarization #speaker-change-detection #voice-activity-detection #overlapped-speech-detection #automatic-speech-recognition #arxiv-2111.14448 #arxiv-2012.01477 #license-mit #endpoints_compatible #region-us
| Using this open-source pipeline in production?
Make the most of it thanks to our consulting services.
Speaker diarization 3.1
=======================
This pipeline is the same as 'pyannote/speaker-diarization-3.0' except it removes the problematic use of 'onnxruntime'.
Both speaker segmentation and embedding now run in pure PyTorch. This should ease deployment and possibly speed up inference.
It requires URL version 3.1 or higher.
It ingests mono audio sampled at 16kHz and outputs speaker diarization as an 'Annotation' instance:
* stereo or multi-channel audio files are automatically downmixed to mono by averaging the channels.
* audio files sampled at a different rate are resampled to 16kHz automatically upon loading.
Requirements
------------
1. Install 'URL' '3.1' with 'pip install URL'
2. Accept 'pyannote/segmentation-3.0' user conditions
3. Accept 'pyannote/speaker-diarization-3.1' user conditions
4. Create access token at 'URL
Usage
-----
### Processing on GPU
'URL' pipelines run on CPU by default.
You can send them to GPU with the following lines:
### Processing from memory
Pre-loading audio files in memory may result in faster processing:
### Monitoring progress
Hooks are available to monitor the progress of the pipeline:
### Controlling the number of speakers
In case the number of speakers is known in advance, one can use the 'num\_speakers' option:
One can also provide lower and/or upper bounds on the number of speakers using 'min\_speakers' and 'max\_speakers' options:
Benchmark
---------
This pipeline has been benchmarked on a large collection of datasets.
Processing is fully automatic:
* no manual voice activity detection (as is sometimes the case in the literature)
* no manual number of speakers (though it is possible to provide it to the pipeline)
* no fine-tuning of the internal models nor tuning of the pipeline hyper-parameters to each dataset
... with the least forgiving diarization error rate (DER) setup (named *"Full"* in this paper):
* no forgiveness collar
* evaluation of overlapped speech
s
| [
"### Processing on GPU\n\n\n'URL' pipelines run on CPU by default.\nYou can send them to GPU with the following lines:",
"### Processing from memory\n\n\nPre-loading audio files in memory may result in faster processing:",
"### Monitoring progress\n\n\nHooks are available to monitor the progress of the pipeline:",
"### Controlling the number of speakers\n\n\nIn case the number of speakers is known in advance, one can use the 'num\\_speakers' option:\n\n\nOne can also provide lower and/or upper bounds on the number of speakers using 'min\\_speakers' and 'max\\_speakers' options:\n\n\nBenchmark\n---------\n\n\nThis pipeline has been benchmarked on a large collection of datasets.\n\n\nProcessing is fully automatic:\n\n\n* no manual voice activity detection (as is sometimes the case in the literature)\n* no manual number of speakers (though it is possible to provide it to the pipeline)\n* no fine-tuning of the internal models nor tuning of the pipeline hyper-parameters to each dataset\n\n\n... with the least forgiving diarization error rate (DER) setup (named *\"Full\"* in this paper):\n\n\n* no forgiveness collar\n* evaluation of overlapped speech\n\n\n\ns"
] | [
"TAGS\n#pyannote-audio #pyannote #pyannote-audio-pipeline #audio #voice #speech #speaker #speaker-diarization #speaker-change-detection #voice-activity-detection #overlapped-speech-detection #automatic-speech-recognition #arxiv-2111.14448 #arxiv-2012.01477 #license-mit #endpoints_compatible #region-us \n",
"### Processing on GPU\n\n\n'URL' pipelines run on CPU by default.\nYou can send them to GPU with the following lines:",
"### Processing from memory\n\n\nPre-loading audio files in memory may result in faster processing:",
"### Monitoring progress\n\n\nHooks are available to monitor the progress of the pipeline:",
"### Controlling the number of speakers\n\n\nIn case the number of speakers is known in advance, one can use the 'num\\_speakers' option:\n\n\nOne can also provide lower and/or upper bounds on the number of speakers using 'min\\_speakers' and 'max\\_speakers' options:\n\n\nBenchmark\n---------\n\n\nThis pipeline has been benchmarked on a large collection of datasets.\n\n\nProcessing is fully automatic:\n\n\n* no manual voice activity detection (as is sometimes the case in the literature)\n* no manual number of speakers (though it is possible to provide it to the pipeline)\n* no fine-tuning of the internal models nor tuning of the pipeline hyper-parameters to each dataset\n\n\n... with the least forgiving diarization error rate (DER) setup (named *\"Full\"* in this paper):\n\n\n* no forgiveness collar\n* evaluation of overlapped speech\n\n\n\ns"
] | [
117,
28,
22,
18,
207
] | [
"passage: TAGS\n#pyannote-audio #pyannote #pyannote-audio-pipeline #audio #voice #speech #speaker #speaker-diarization #speaker-change-detection #voice-activity-detection #overlapped-speech-detection #automatic-speech-recognition #arxiv-2111.14448 #arxiv-2012.01477 #license-mit #endpoints_compatible #region-us \n### Processing on GPU\n\n\n'URL' pipelines run on CPU by default.\nYou can send them to GPU with the following lines:### Processing from memory\n\n\nPre-loading audio files in memory may result in faster processing:### Monitoring progress\n\n\nHooks are available to monitor the progress of the pipeline:### Controlling the number of speakers\n\n\nIn case the number of speakers is known in advance, one can use the 'num\\_speakers' option:\n\n\nOne can also provide lower and/or upper bounds on the number of speakers using 'min\\_speakers' and 'max\\_speakers' options:\n\n\nBenchmark\n---------\n\n\nThis pipeline has been benchmarked on a large collection of datasets.\n\n\nProcessing is fully automatic:\n\n\n* no manual voice activity detection (as is sometimes the case in the literature)\n* no manual number of speakers (though it is possible to provide it to the pipeline)\n* no fine-tuning of the internal models nor tuning of the pipeline hyper-parameters to each dataset\n\n\n... with the least forgiving diarization error rate (DER) setup (named *\"Full\"* in this paper):\n\n\n* no forgiveness collar\n* evaluation of overlapped speech\n\n\n\ns"
] | [
-0.11315863579511642,
0.1324245184659958,
-0.0029949983581900597,
0.08064357191324234,
0.05866367742419243,
-0.03650261089205742,
0.026370536535978317,
0.12453852593898773,
0.07541081309318542,
0.13337677717208862,
-0.02547275833785534,
0.058716632425785065,
0.03119896911084652,
0.12699371576309204,
0.02430434338748455,
-0.10003037005662918,
0.01475631445646286,
-0.09122397005558014,
0.20527301728725433,
0.09802389144897461,
0.0651465356349945,
-0.0973283052444458,
0.0262719988822937,
-0.04595125466585159,
0.008315415121614933,
0.008863905444741249,
0.011237568221986294,
-0.08196070045232773,
0.07558188587427139,
0.006162042263895273,
-0.020027225837111473,
0.0008841327507980168,
0.05649949982762337,
-0.15276816487312317,
0.021994352340698242,
0.09245866537094116,
0.02753608115017414,
0.023084376007318497,
0.09999876469373703,
-0.06663589179515839,
0.03171224892139435,
-0.0431399792432785,
0.04470551013946533,
0.04654260724782944,
-0.04322401061654091,
-0.2218206822872162,
-0.042900096625089645,
0.020228352397680283,
0.10974934697151184,
0.07685477286577225,
-0.04687109962105751,
0.11198534816503525,
-0.057036083191633224,
0.07057157158851624,
0.1331658661365509,
-0.17262324690818787,
0.016049440950155258,
-0.01654069498181343,
-0.005774789955466986,
0.09864278137683868,
-0.09203403443098068,
-0.0683865174651146,
-0.04614722728729248,
0.0185792688280344,
0.003484840504825115,
-0.019592316821217537,
0.009043464437127113,
-0.04431096836924553,
-0.08341792970895767,
-0.09047489613294601,
0.06805478781461716,
-0.03064614161849022,
-0.09095760434865952,
-0.20866401493549347,
-0.0538753867149353,
-0.13302095234394073,
-0.02333092875778675,
0.06084546819329262,
-0.00004418556272867136,
0.01764899119734764,
0.07321978360414505,
0.03657250851392746,
-0.08411048352718353,
-0.10321928560733795,
-0.0688663125038147,
0.08371907472610474,
0.04703384265303612,
0.0034995221067219973,
0.05617231875658035,
0.12948282063007355,
0.02149582840502262,
-0.058435242623090744,
-0.032442137598991394,
-0.006063118111342192,
-0.16534964740276337,
0.022551942616701126,
-0.005741554778069258,
-0.03361796215176582,
0.014346796087920666,
0.1661020964384079,
0.04857875406742096,
0.06309007108211517,
-0.03756699711084366,
0.010576151311397552,
0.049235645681619644,
0.007902937941253185,
-0.05249006301164627,
-0.07927988469600677,
0.04311387240886688,
0.08005385100841522,
0.12552160024642944,
-0.02298896759748459,
-0.020849866792559624,
0.00557284988462925,
0.04410002753138542,
0.053401608020067215,
0.06267690658569336,
-0.02052980475127697,
-0.10480742901563644,
-0.06929168850183487,
0.10078981518745422,
-0.19668398797512054,
0.005035137291997671,
0.08510150760412216,
0.023989640176296234,
-0.021282831206917763,
-0.0337543785572052,
-0.02559071220457554,
-0.10296278446912766,
0.07181406021118164,
-0.026583965867757797,
-0.028198445215821266,
-0.05680140480399132,
-0.047973621636629105,
0.05041472986340523,
-0.05205157399177551,
-0.08036991208791733,
-0.07735969126224518,
-0.08083564788103104,
-0.028694111853837967,
0.028212660923600197,
-0.08062385767698288,
-0.02123996801674366,
0.024334395304322243,
-0.006045314017683268,
0.02893993817269802,
-0.0657382383942604,
0.056721195578575134,
-0.07604353129863739,
0.08643162250518799,
0.04834277555346489,
0.09112647920846939,
0.11414487659931183,
0.032957591116428375,
-0.10146941244602203,
0.014061534777283669,
-0.1736961156129837,
0.17644421756267548,
-0.08752364665269852,
-0.036342721432447433,
-0.09289763122797012,
-0.0325072780251503,
-0.07235675305128098,
0.012893659994006157,
0.033099349588155746,
0.09094499051570892,
-0.18532870709896088,
-0.08737225085496902,
0.1283610314130783,
-0.1125050038099289,
0.010488267056643963,
0.156629279255867,
0.02496211975812912,
-0.027858685702085495,
0.08426512777805328,
0.2241760790348053,
0.04410174861550331,
-0.17785613238811493,
-0.13539840281009674,
-0.0403631217777729,
-0.051007162779569626,
0.07349896430969238,
0.12031035870313644,
-0.03217205032706261,
0.09058531373739243,
0.031419575214385986,
0.019896281883120537,
-0.03439021855592728,
0.041034333407878876,
-0.08150942623615265,
-0.0069086807779967785,
-0.008158796466886997,
0.004807143472135067,
0.021962853148579597,
-0.06542529910802841,
-0.0281104426831007,
-0.11754845082759857,
-0.052629102021455765,
0.10952935367822647,
-0.0586434043943882,
0.045852623879909515,
-0.1297355443239212,
0.08209385722875595,
-0.08176515251398087,
0.01217653788626194,
-0.2184949517250061,
0.05634605884552002,
0.04543314129114151,
-0.23042231798171997,
0.07943728566169739,
-0.07887063920497894,
0.03312809765338898,
0.06767541915178299,
0.01670137047767639,
0.022828878834843636,
0.04285110533237457,
-0.034459494054317474,
-0.05116765946149826,
-0.13848279416561127,
-0.025676479563117027,
-0.022453386336565018,
0.12299315631389618,
-0.08065852522850037,
-0.03803769871592522,
0.1253345012664795,
0.08297277241945267,
0.026861879974603653,
-0.09177915006875992,
0.035428497940301895,
0.008951305411756039,
-0.0016921389615163207,
-0.022386429831385612,
0.031284529715776443,
-0.034639425575733185,
0.04131656885147095,
0.07417315989732742,
-0.23044778406620026,
-0.028206761926412582,
0.14411914348602295,
0.08859990537166595,
-0.03227300941944122,
-0.010691936127841473,
-0.03969082236289978,
-0.05003465712070465,
-0.046923913061618805,
-0.0722639188170433,
0.20704017579555511,
0.07539786398410797,
0.0820193886756897,
-0.10786261409521103,
-0.01072201319038868,
0.03203337639570236,
0.020570769906044006,
0.0020094774663448334,
0.12410277873277664,
0.036075059324502945,
0.015468472614884377,
0.0401604138314724,
-0.0349276177585125,
-0.027267402037978172,
0.10797424614429474,
0.040704719722270966,
-0.15384016931056976,
0.013052763417363167,
0.007641776464879513,
0.05095420405268669,
0.09438247978687286,
-0.07870794832706451,
0.0429210402071476,
0.060629185289144516,
-0.004454811103641987,
0.012790968641638756,
-0.11336715519428253,
0.07401121407747269,
0.004478742368519306,
-0.055048372596502304,
-0.0049476525746285915,
0.017129674553871155,
0.02155948430299759,
0.08938567340373993,
-0.03077058121562004,
0.038267917931079865,
-0.0015006196917966008,
-0.0730140209197998,
-0.07099298387765884,
0.082920141518116,
-0.07280375063419342,
-0.3816280663013458,
-0.14006222784519196,
-0.04454808682203293,
-0.030287597328424454,
0.03937549144029617,
0.06635782122612,
-0.0533556304872036,
-0.09356646984815598,
-0.1029018759727478,
-0.00021206097153481096,
0.06638070940971375,
-0.061702776700258255,
-0.055778104811906815,
0.07790210098028183,
0.08161311596632004,
-0.09851256012916565,
0.006640155799686909,
-0.004839060362428427,
-0.08462586253881454,
0.026482855901122093,
0.13290201127529144,
0.024653958156704903,
0.12710025906562805,
0.09052667021751404,
-0.037771787494421005,
0.009531260468065739,
0.08954542875289917,
-0.08894339203834534,
0.03220950812101364,
0.1736469268798828,
-0.04508551210165024,
0.018518300727009773,
0.14899493753910065,
0.013379737734794617,
-0.08564736694097519,
0.022840401157736778,
0.054517701268196106,
-0.06671538203954697,
-0.16434040665626526,
-0.11561955511569977,
-0.09566362202167511,
0.009548237547278404,
0.1385212242603302,
0.06614796072244644,
-0.09810054302215576,
-0.0341765359044075,
-0.045506801456213,
-0.0011907416628673673,
0.04486647993326187,
0.057445090264081955,
0.19394703209400177,
-0.020488616079092026,
0.1005619540810585,
-0.07000754028558731,
-0.001937803695909679,
0.10252378135919571,
0.10631260275840759,
0.14295992255210876,
-0.06287577003240585,
0.22132310271263123,
0.059175826609134674,
0.07602682709693909,
0.07668691873550415,
0.01845526322722435,
-0.04001329839229584,
0.05659422650933266,
0.0017347472021356225,
-0.12269871681928635,
-0.1122940182685852,
0.01661822572350502,
0.0769675076007843,
-0.06973368674516678,
0.024161668494343758,
-0.05192815512418747,
0.06454214453697205,
0.15219326317310333,
0.07620171457529068,
-0.13955235481262207,
-0.034758083522319794,
-0.007635517045855522,
-0.11923656612634659,
-0.033940017223358154,
0.014635274186730385,
0.08970866352319717,
-0.0835280641913414,
-0.026578592136502266,
-0.01810891181230545,
0.06389648467302322,
-0.1726243644952774,
-0.01448242086917162,
0.02532014064490795,
0.09953398257493973,
0.04266884922981262,
0.05203849449753761,
-0.07941260188817978,
0.1155925765633583,
0.012164784595370293,
0.09552007168531418,
-0.06992527097463608,
0.0240938700735569,
0.026722107082605362,
-0.14172355830669403,
0.13357968628406525,
-0.012479758821427822,
0.0022935434244573116,
-0.10827386379241943,
-0.235312819480896,
0.011337649077177048,
0.06502940505743027,
-0.016662968322634697,
0.04885051026940346,
-0.01326623372733593,
-0.03369082137942314,
-0.05760056525468826,
-0.0765855684876442,
-0.05296659469604492,
-0.16850583255290985,
0.06949072331190109,
0.012867876328527927,
-0.03299570456147194,
-0.036973435431718826,
-0.06747538596391678,
0.007259501609951258,
0.0920901894569397,
-0.21758852899074554,
-0.05748789384961128,
-0.09306172281503677,
-0.0936330184340477,
0.149629145860672,
-0.024859901517629623,
0.03452003374695778,
0.008344185538589954,
0.12360453605651855,
0.006365528330206871,
-0.08646858483552933,
0.08364524692296982,
-0.054556459188461304,
-0.15510736405849457,
-0.04009919986128807,
0.1946556270122528,
0.044125549495220184,
0.06230524554848671,
-0.032901469618082047,
0.0696791335940361,
-0.018751826137304306,
-0.0634821355342865,
0.027247019112110138,
0.16746173799037933,
0.058804579079151154,
0.07085639983415604,
-0.023203643038868904,
-0.1785041242837906,
-0.05785807594656944,
-0.011607075110077858,
0.10063204169273376,
0.22980576753616333,
-0.049990683794021606,
0.25992387533187866,
0.17920763790607452,
-0.059542618691921234,
-0.2543586194515228,
-0.05733590945601463,
0.08810766786336899,
0.012432361952960491,
-0.013154841959476471,
-0.19792461395263672,
0.13846513628959656,
0.10594698786735535,
-0.05813679099082947,
0.1128869578242302,
-0.2496546357870102,
-0.13869346678256989,
0.0573403537273407,
-0.014583282172679901,
-0.09783133119344711,
-0.07108373939990997,
-0.035451702773571014,
-0.07214238494634628,
-0.09564744681119919,
0.09994815289974213,
0.012780416756868362,
0.1605825126171112,
-0.011136717163026333,
-0.006326969712972641,
0.020033029839396477,
-0.08925624936819077,
0.06402113288640976,
0.007924809120595455,
0.011696116998791695,
-0.028088243678212166,
0.057740431278944016,
0.04696565866470337,
-0.01887885481119156,
0.12489636987447739,
-0.0460515059530735,
0.011509453877806664,
-0.06242426857352257,
-0.11662929505109787,
-0.005443870089948177,
0.01576276868581772,
0.015257403254508972,
-0.039204347878694534,
-0.02269269898533821,
0.0494459792971611,
-0.0003829448251053691,
-0.03241914510726929,
-0.024412045255303383,
-0.07947449386119843,
-0.04712167754769325,
0.21425825357437134,
0.15369181334972382,
-0.054608915001153946,
-0.2227526605129242,
-0.016312681138515472,
-0.01605866849422455,
0.036235179752111435,
-0.07445274293422699,
0.08370444923639297,
0.09467482566833496,
0.03335889056324959,
0.04737330973148346,
0.0035073193721473217,
-0.0901375412940979,
0.03698553517460823,
0.05832996219396591,
-0.0900506004691124,
-0.08546017855405807,
0.07628826797008514,
0.051430512219667435,
-0.08003323525190353,
-0.06407647579908371,
0.08328965306282043,
-0.006227121222764254,
-0.029953667894005775,
0.0262923501431942,
0.07202675193548203,
-0.008936414495110512,
0.17621135711669922,
-0.036804795265197754,
0.04182452708482742,
-0.12883371114730835,
0.13478025794029236,
0.07935637980699539,
-0.1776587814092636,
0.03466170281171799,
0.1130431666970253,
-0.08629783242940903,
-0.05595969781279564,
-0.13637696206569672,
-0.06520155072212219,
0.10909584164619446,
0.010507719591259956,
-0.013849915005266666,
-0.018906958401203156,
0.06717634946107864,
-0.0193104837089777,
0.05018682777881622,
0.06818582117557526,
-0.06219283863902092,
-0.01855543442070484,
-0.08694042265415192,
0.12839239835739136,
-0.010646183975040913,
0.005144573748111725,
-0.07213153690099716,
0.05019574612379074,
0.06352602690458298,
-0.06496591866016388,
-0.024748163297772408,
-0.08365899324417114,
-0.06184857338666916,
0.019190553575754166,
-0.11705934256315231,
0.04823160171508789,
-0.07418982684612274,
0.004875349346548319,
-0.0019994385074824095,
0.0427657850086689,
-0.014390656724572182,
0.049509402364492416,
-0.07196896523237228,
-0.0558677539229393,
-0.042977672070264816,
0.039764560759067535,
-0.1438199132680893,
0.014540363103151321,
0.07224562764167786,
-0.09017154574394226,
0.12600035965442657,
0.12032735347747803,
-0.043036919087171555,
0.0009269868023693562,
-0.07685878872871399,
-0.10266803205013275,
0.012140054255723953,
0.11484623700380325,
0.003555783536285162,
-0.1453610509634018,
0.03400304540991783,
0.06544645130634308,
-0.033236369490623474,
0.007913858629763126,
0.166604682803154,
-0.13153307139873505,
0.07776468247175217,
-0.02119586244225502,
-0.06285859644412994,
-0.04385915771126747,
-0.003450612770393491,
0.08241237699985504,
0.07579739391803741,
0.14829176664352417,
-0.0642826035618782,
0.01574442721903324,
-0.14791987836360931,
-0.01604977622628212,
-0.029590845108032227,
-0.031777460128068924,
-0.09888108819723129,
-0.01545894704759121,
0.08968383073806763,
0.01490966696292162,
0.2265622615814209,
0.025368794798851013,
-0.0759224072098732,
0.04727671295404434,
-0.03323293477296829,
-0.009182523936033249,
0.03381168842315674,
0.0753321722149849,
0.047481708228588104,
-0.007505688816308975,
0.043289199471473694,
-0.03829876706004143,
0.01955079846084118,
0.04117274656891823,
0.05096453055739403,
0.21823720633983612,
0.13553659617900848,
-0.03345939517021179,
0.05374538153409958,
-0.11169421672821045,
-0.2078210562467575,
0.1602451503276825,
-0.17322176694869995,
0.08249057829380035,
-0.067253977060318,
0.15158556401729584,
0.08888760954141617,
-0.07851912081241608,
0.10242316871881485,
-0.06781546771526337,
-0.0419725738465786,
-0.10243664681911469,
-0.14858026802539825,
-0.0358375608921051,
-0.049949321895837784,
-0.0036524401511996984,
-0.03777443617582321,
0.04289780557155609,
0.06339820474386215,
0.04148486256599426,
0.00801653042435646,
0.15508848428726196,
-0.10272093862295151,
-0.04135924205183983,
0.010647875256836414,
0.0047741844318807125,
-0.036704715341329575,
0.06670636683702469,
-0.0005687395459972322,
0.07633022964000702,
-0.0011917692609131336,
0.09750604629516602,
0.050003789365291595,
0.005683412775397301,
0.020602505654096603,
-0.037402134388685226,
-0.03982524946331978,
0.014119908213615417,
-0.008057065308094025,
0.0016778598073869944,
0.1873907446861267,
0.08590134978294373,
-0.05224417522549629,
-0.008101338520646095,
0.21677392721176147,
-0.02582767978310585,
-0.07706017792224884,
-0.09668423980474472,
0.20543637871742249,
-0.01878844015300274,
0.00668369559571147,
-0.01699789986014366,
-0.1070176512002945,
-0.0036179206799715757,
0.15167783200740814,
0.17910394072532654,
-0.06978513300418854,
0.0032496440690010786,
0.0196119025349617,
-0.0008223890908993781,
-0.044873978942632675,
0.10080777108669281,
0.08329320698976517,
0.378248929977417,
-0.017125144600868225,
0.023984966799616814,
-0.00045240166946314275,
-0.029841920360922813,
-0.06013641506433487,
0.08564383536577225,
-0.1029982790350914,
0.0023018631618469954,
-0.09937633574008942,
0.023047439754009247,
-0.015571429394185543,
-0.16996173560619354,
0.011176057159900665,
-0.08015211671590805,
-0.12699289619922638,
0.03315217047929764,
0.07829569280147552,
-0.011434786021709442,
-0.01377973984926939,
0.01378476619720459,
0.029698390513658524,
-0.012216287665069103,
0.010315795429050922,
-0.09362272918224335,
-0.03325098007917404,
0.043498240411281586,
-0.01650671660900116,
0.22030109167099,
-0.01608654484152794,
0.1011231392621994,
0.05749320983886719,
0.047359224408864975,
-0.14792171120643616,
0.07876626402139664,
-0.008979006670415401,
-0.2307719886302948,
0.02392943575978279,
0.21970833837985992,
-0.015481164678931236,
0.1298559308052063,
0.0710814893245697,
0.024924829602241516,
0.019155526533722878,
-0.04492567107081413,
0.0088843097910285,
-0.1086999848484993,
0.02202797681093216,
-0.09395282715559006,
0.0847911611199379,
0.07847113162279129,
-0.00643180962651968,
-0.01151368673890829,
-0.06622694432735443,
0.04784928262233734,
-0.009146765805780888,
0.021911337971687317,
0.006811400409787893,
-0.24348483979701996,
0.04628323018550873,
-0.04495147988200188,
0.023829329758882523,
-0.24758026003837585,
-0.12796464562416077,
0.035699110478162766,
-0.04264306277036667,
-0.08282840251922607,
0.0600830502808094,
-0.004130123648792505,
0.03364090994000435,
-0.03920703008770943,
-0.04383524879813194,
0.05529235675930977,
0.09581420570611954,
-0.12889821827411652,
-0.0646250769495964
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SMIDS_3x_beit_large_SGD_lr001_fold3
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2570
- Accuracy: 0.9133
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.588 | 1.0 | 450 | 0.5706 | 0.775 |
| 0.404 | 2.0 | 900 | 0.4149 | 0.84 |
| 0.383 | 3.0 | 1350 | 0.3523 | 0.8633 |
| 0.3184 | 4.0 | 1800 | 0.3205 | 0.8717 |
| 0.3585 | 5.0 | 2250 | 0.2990 | 0.8867 |
| 0.259 | 6.0 | 2700 | 0.2842 | 0.8983 |
| 0.2002 | 7.0 | 3150 | 0.2781 | 0.8933 |
| 0.2293 | 8.0 | 3600 | 0.2733 | 0.8967 |
| 0.2003 | 9.0 | 4050 | 0.2660 | 0.9033 |
| 0.2197 | 10.0 | 4500 | 0.2586 | 0.9017 |
| 0.3087 | 11.0 | 4950 | 0.2560 | 0.8967 |
| 0.2828 | 12.0 | 5400 | 0.2523 | 0.9017 |
| 0.2009 | 13.0 | 5850 | 0.2527 | 0.905 |
| 0.2364 | 14.0 | 6300 | 0.2562 | 0.9033 |
| 0.1454 | 15.0 | 6750 | 0.2483 | 0.9033 |
| 0.2215 | 16.0 | 7200 | 0.2471 | 0.9 |
| 0.1406 | 17.0 | 7650 | 0.2445 | 0.9067 |
| 0.1551 | 18.0 | 8100 | 0.2486 | 0.9083 |
| 0.1678 | 19.0 | 8550 | 0.2476 | 0.9083 |
| 0.1917 | 20.0 | 9000 | 0.2476 | 0.9067 |
| 0.227 | 21.0 | 9450 | 0.2503 | 0.91 |
| 0.1666 | 22.0 | 9900 | 0.2478 | 0.9067 |
| 0.1877 | 23.0 | 10350 | 0.2493 | 0.9117 |
| 0.2319 | 24.0 | 10800 | 0.2472 | 0.9067 |
| 0.1923 | 25.0 | 11250 | 0.2469 | 0.9083 |
| 0.1443 | 26.0 | 11700 | 0.2468 | 0.9117 |
| 0.1359 | 27.0 | 12150 | 0.2476 | 0.9117 |
| 0.1931 | 28.0 | 12600 | 0.2501 | 0.9083 |
| 0.127 | 29.0 | 13050 | 0.2495 | 0.9117 |
| 0.1963 | 30.0 | 13500 | 0.2499 | 0.9117 |
| 0.2133 | 31.0 | 13950 | 0.2518 | 0.9133 |
| 0.1326 | 32.0 | 14400 | 0.2532 | 0.9117 |
| 0.188 | 33.0 | 14850 | 0.2524 | 0.9117 |
| 0.1729 | 34.0 | 15300 | 0.2510 | 0.9117 |
| 0.1433 | 35.0 | 15750 | 0.2536 | 0.9117 |
| 0.1375 | 36.0 | 16200 | 0.2513 | 0.9133 |
| 0.0966 | 37.0 | 16650 | 0.2528 | 0.9167 |
| 0.1442 | 38.0 | 17100 | 0.2522 | 0.915 |
| 0.0864 | 39.0 | 17550 | 0.2534 | 0.9133 |
| 0.1498 | 40.0 | 18000 | 0.2539 | 0.915 |
| 0.1135 | 41.0 | 18450 | 0.2554 | 0.915 |
| 0.1675 | 42.0 | 18900 | 0.2546 | 0.915 |
| 0.1716 | 43.0 | 19350 | 0.2550 | 0.9167 |
| 0.1226 | 44.0 | 19800 | 0.2557 | 0.9133 |
| 0.1652 | 45.0 | 20250 | 0.2564 | 0.9117 |
| 0.1688 | 46.0 | 20700 | 0.2569 | 0.9133 |
| 0.1994 | 47.0 | 21150 | 0.2572 | 0.9133 |
| 0.088 | 48.0 | 21600 | 0.2573 | 0.9133 |
| 0.219 | 49.0 | 22050 | 0.2571 | 0.9133 |
| 0.104 | 50.0 | 22500 | 0.2570 | 0.9133 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_3x_beit_large_SGD_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9133333333333333, "name": "Accuracy"}]}]}]} | image-classification | onizukal/SMIDS_3x_beit_large_SGD_lr001_fold3 | [
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-large-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-08T23:38:23+00:00 | [] | [] | TAGS
#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| SMIDS\_3x\_beit\_large\_SGD\_lr001\_fold3
=========================================
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2570
* Accuracy: 0.9133
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.2
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
"TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
81,
115,
4,
30
] | [
"passage: TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
-0.1293599158525467,
0.1724882274866104,
-0.0023454553447663784,
0.13587836921215057,
0.11250235140323639,
0.015344180166721344,
0.13944171369075775,
0.16905122995376587,
-0.08231265097856522,
0.04725457355380058,
0.1399839073419571,
0.13659004867076874,
0.046719420701265335,
0.19427457451820374,
-0.05236957222223282,
-0.2601667046546936,
0.04119328409433365,
0.03234807401895523,
-0.02075078710913658,
0.12314869463443756,
0.09301083534955978,
-0.13055187463760376,
0.11641614139080048,
0.030263151973485947,
-0.1994711011648178,
-0.03690062463283539,
-0.00742433313280344,
-0.06729142367839813,
0.10523199290037155,
-0.003170925425365567,
0.06897550076246262,
0.03744976967573166,
0.0835329070687294,
-0.13024620711803436,
0.0019813377875834703,
0.043246712535619736,
0.0064185261726379395,
0.10353662818670273,
0.05471734330058098,
-0.015182994306087494,
0.07030405849218369,
-0.06875743716955185,
0.06702885776758194,
0.009385199286043644,
-0.11313743144273758,
-0.26980340480804443,
-0.10223843902349472,
0.07157823443412781,
0.08217991888523102,
0.068179190158844,
0.008332090452313423,
0.1646922081708908,
-0.015027978457510471,
0.10447341948747635,
0.23090173304080963,
-0.2640359699726105,
-0.055165741592645645,
0.0294360164552927,
0.014914325438439846,
0.06473758071660995,
-0.10603974759578705,
-0.018760167062282562,
0.02059783600270748,
0.044390130788087845,
0.1409236192703247,
-0.010635782033205032,
-0.02811739780008793,
-0.021928580477833748,
-0.10847067832946777,
-0.08875154703855515,
0.18579065799713135,
0.058072153478860855,
-0.04802494868636131,
-0.07736620306968689,
-0.07186304777860641,
-0.17165552079677582,
-0.041741833090782166,
0.009797174483537674,
0.04154014587402344,
-0.04674985632300377,
-0.10634559392929077,
-0.030910290777683258,
-0.07805538177490234,
-0.051461391150951385,
-0.023120464757084846,
0.1351369321346283,
0.03383360058069229,
0.05723920464515686,
-0.03597215935587883,
0.09929350018501282,
0.0073938071727752686,
-0.17543649673461914,
-0.028137801215052605,
-0.0017277015140280128,
0.015125435777008533,
-0.01991228759288788,
-0.030262885615229607,
-0.06523662805557251,
-0.001314454828388989,
0.1489848643541336,
-0.06082969531416893,
0.060913555324077606,
-0.007318461779505014,
0.04020942002534866,
-0.048562191426754,
0.1864238679409027,
-0.02870783396065235,
-0.01659870520234108,
0.0207351166754961,
0.08822518587112427,
0.06836054474115372,
-0.036532942205667496,
-0.12525734305381775,
0.03098621405661106,
0.12811045348644257,
0.0029374780133366585,
-0.021369412541389465,
0.05286439135670662,
-0.0643334686756134,
-0.0587083138525486,
0.09228596836328506,
-0.08908151835203171,
0.034838590770959854,
-0.010374085046350956,
-0.084370456635952,
-0.06779533624649048,
0.027354132384061813,
0.01850878819823265,
-0.0004323708708398044,
0.07165450602769852,
-0.09108522534370422,
0.014963540248572826,
-0.06533985584974289,
-0.10081785917282104,
0.016071073710918427,
-0.1107335016131401,
0.012424856424331665,
-0.09663169085979462,
-0.19710472226142883,
0.006891206838190556,
0.07721206545829773,
-0.05610070005059242,
-0.06814593821763992,
-0.03639180585741997,
-0.07652068138122559,
0.04154945909976959,
-0.011949662119150162,
0.07310567051172256,
-0.0747697651386261,
0.0913747176527977,
0.022405456751585007,
0.08734618872404099,
-0.05631003528833389,
0.0460691936314106,
-0.1024455726146698,
0.04984736442565918,
-0.19827407598495483,
0.0799676924943924,
-0.0493633896112442,
0.0617455318570137,
-0.09557844698429108,
-0.10542625933885574,
0.03370443359017372,
-0.05006959289312363,
0.06861566007137299,
0.0974634513258934,
-0.1729826033115387,
-0.057957619428634644,
0.1353495568037033,
-0.09663163125514984,
-0.14797286689281464,
0.10109983384609222,
-0.050693199038505554,
0.01928282529115677,
0.047161467373371124,
0.21422064304351807,
0.06321150809526443,
-0.09143578261137009,
-0.02580295503139496,
-0.03329068049788475,
0.04440530762076378,
-0.06494591385126114,
0.10175396502017975,
0.027680888772010803,
0.05365157872438431,
0.023984158411622047,
-0.032899804413318634,
0.03856229409575462,
-0.08387355506420135,
-0.10054522752761841,
-0.05070185661315918,
-0.08565592765808105,
0.039397966116666794,
0.05604296177625656,
0.05994046851992607,
-0.10856401175260544,
-0.09017187356948853,
0.04204317927360535,
0.0943065956234932,
-0.07395226508378983,
0.028962817043066025,
-0.09000826627016068,
0.11608705669641495,
-0.08325600624084473,
-0.02390553615987301,
-0.1791052222251892,
-0.04241684824228287,
0.040629271417856216,
-0.01629319041967392,
-0.006912850774824619,
-0.048891667276620865,
0.07074255496263504,
0.08783093094825745,
-0.05235742777585983,
-0.05203414335846901,
-0.05522594600915909,
0.008213330060243607,
-0.1105295866727829,
-0.1776295155286789,
-0.08015653491020203,
-0.0380605012178421,
0.14977632462978363,
-0.15268713235855103,
0.022225622087717056,
0.061116840690374374,
0.12500962615013123,
0.059797611087560654,
-0.04723487049341202,
-0.007436409126967192,
0.021452799439430237,
-0.05571167171001434,
-0.08678608387708664,
0.05719248577952385,
0.03528200834989548,
-0.07155010849237442,
-0.019102152436971664,
-0.10049699991941452,
0.1498662531375885,
0.13190734386444092,
-0.0015375686343759298,
-0.04512632265686989,
-0.01160994078963995,
-0.06610778719186783,
-0.030441991984844208,
-0.04081778973340988,
0.018804829567670822,
0.10142559558153152,
0.01744643971323967,
0.14419154822826385,
-0.09178037941455841,
-0.036961425095796585,
0.053544968366622925,
-0.028453968465328217,
-0.0331195667386055,
0.07361359149217606,
0.02190210297703743,
-0.14263916015625,
0.15015269815921783,
0.14882412552833557,
-0.04894813522696495,
0.12402692437171936,
-0.036747027188539505,
-0.0615357980132103,
-0.044876549392938614,
-0.037704430520534515,
0.014213677495718002,
0.1403394341468811,
-0.08333314955234528,
-0.005919712595641613,
0.05630137771368027,
0.019257593899965286,
-0.007085299585014582,
-0.18072617053985596,
0.0006808378966525197,
0.03521978110074997,
-0.04604950174689293,
-0.02278841845691204,
-0.014470276422798634,
0.0007941273506730795,
0.09172741323709488,
0.019804218783974648,
-0.07102026045322418,
0.05166372284293175,
0.010580740869045258,
-0.05623085796833038,
0.16415521502494812,
-0.07910753041505814,
-0.19727325439453125,
-0.11776646971702576,
-0.08754957467317581,
-0.10735819488763809,
0.013021474704146385,
0.06737184524536133,
-0.050448641180992126,
-0.04938974231481552,
-0.10206248611211777,
-0.04453543201088905,
0.021900271996855736,
0.02429220825433731,
0.05370878055691719,
-0.008031168952584267,
0.08405356109142303,
-0.09224440902471542,
-0.03291117399930954,
-0.014789600856602192,
0.018657125532627106,
0.06682770699262619,
0.018715238198637962,
0.11069032549858093,
0.08161229640245438,
-0.02844928205013275,
0.05646483600139618,
-0.01682325080037117,
0.2655041813850403,
-0.06765957176685333,
-0.006789656355977058,
0.13932959735393524,
-0.013368978165090084,
0.08428963273763657,
0.1268712729215622,
0.04151352122426033,
-0.09555158019065857,
-0.013173693791031837,
-0.00024822441628202796,
-0.05275752767920494,
-0.1537386178970337,
-0.04163756221532822,
-0.045641690492630005,
-0.0021682933438569307,
0.13930507004261017,
0.03818075731396675,
0.02474883571267128,
0.07807637751102448,
0.020041609182953835,
0.05664918199181557,
-0.017527885735034943,
0.10406769812107086,
0.08156019449234009,
0.06448414921760559,
0.13368317484855652,
-0.03653626888990402,
-0.019387291744351387,
0.05662747099995613,
0.04215037450194359,
0.20423758029937744,
-0.02541770040988922,
0.14701254665851593,
0.02641657367348671,
0.19307395815849304,
0.017521383240818977,
0.0728468969464302,
-0.014410126954317093,
0.0009393728105351329,
-0.019274147227406502,
-0.04702805355191231,
-0.06427313387393951,
0.03288881108164787,
-0.016649875789880753,
0.05632343888282776,
-0.09356046468019485,
0.039105307310819626,
0.059592608362436295,
0.30666422843933105,
0.06539998203516006,
-0.4122132360935211,
-0.09836560487747192,
0.012291035614907742,
0.0009865236934274435,
-0.055195607244968414,
-0.0072626820765435696,
0.0979013666510582,
-0.09949664771556854,
0.08215389400720596,
-0.09418605268001556,
0.08514873683452606,
-0.0845724418759346,
0.020298872143030167,
0.07689075917005539,
0.056060366332530975,
0.013226890936493874,
0.05964293330907822,
-0.21821673214435577,
0.24971400201320648,
0.018467964604496956,
0.04422129690647125,
-0.08908867090940475,
0.010060982778668404,
0.033364444971084595,
0.059161990880966187,
0.08554306626319885,
0.005977867171168327,
-0.09024009108543396,
-0.18880225718021393,
-0.1258762925863266,
0.0005427713040262461,
0.06169470399618149,
-0.036699384450912476,
0.09451829642057419,
-0.018175894394516945,
-0.012127134948968887,
0.021332256495952606,
0.0005201056483201683,
-0.03501477465033531,
-0.103630930185318,
0.02024604007601738,
0.034688886255025864,
-0.012138742953538895,
-0.06473075598478317,
-0.11475593596696854,
-0.03554871678352356,
0.16192500293254852,
0.05505121126770973,
-0.07524240761995316,
-0.1408705860376358,
0.07218684256076813,
0.07781627029180527,
-0.0855332687497139,
0.039305757731199265,
-0.016779718920588493,
0.14986851811408997,
0.020937321707606316,
-0.08943228423595428,
0.10178638249635696,
-0.05869165062904358,
-0.17860572040081024,
-0.041185978800058365,
0.09929849207401276,
0.007366738747805357,
0.05263189971446991,
0.004192214459180832,
0.06014186516404152,
-0.035002902150154114,
-0.0584394596517086,
0.06681792438030243,
-0.0073097143322229385,
0.10614755749702454,
-0.014883637428283691,
0.00864378735423088,
0.029195772483944893,
-0.04613848030567169,
0.00009839441918302327,
0.1684505194425583,
0.24079899489879608,
-0.10403203964233398,
0.060546230524778366,
0.03012177161872387,
-0.030879246070981026,
-0.18261685967445374,
0.010319743305444717,
0.07656802982091904,
-0.0001991603203350678,
0.04173794388771057,
-0.16060468554496765,
0.055176541209220886,
0.10514935851097107,
-0.043303944170475006,
0.08152011036872864,
-0.2768779397010803,
-0.11840421706438065,
0.0923023670911789,
0.138164222240448,
0.0691317543387413,
-0.13107311725616455,
-0.04327763617038727,
-0.041234806180000305,
-0.17335952818393707,
0.13665583729743958,
-0.05704028159379959,
0.11501350998878479,
-0.039327461272478104,
0.08051838725805283,
0.014901114627718925,
-0.056082114577293396,
0.14561402797698975,
0.005515002179890871,
0.08661133795976639,
-0.07185279577970505,
-0.0014093852369114757,
0.10643326491117477,
-0.10252601653337479,
0.07192501425743103,
-0.0869532898068428,
0.06187514215707779,
-0.10810889303684235,
-0.0037693935446441174,
-0.07425615191459656,
0.013987713493406773,
-0.013397954404354095,
-0.048907287418842316,
-0.0448833703994751,
0.03488645330071449,
0.06301422417163849,
-0.018155096098780632,
0.20988906919956207,
0.06445588916540146,
0.0862940326333046,
0.1728745847940445,
0.05397673323750496,
-0.10576145350933075,
-0.09408308565616608,
-0.04430058225989342,
-0.029343122616410255,
0.059755485504865646,
-0.13705183565616608,
0.053009506314992905,
0.12004052102565765,
0.013443393632769585,
0.1280696988105774,
0.05582417547702789,
-0.030783196911215782,
0.035687193274497986,
0.06206676363945007,
-0.1721130907535553,
-0.08640376478433609,
-0.010029762983322144,
0.030597826465964317,
-0.13003188371658325,
0.045725177973508835,
0.12137939780950546,
-0.0593545101583004,
-0.014887568540871143,
-0.004342919681221247,
0.03682979568839073,
-0.009421703405678272,
0.15946903824806213,
0.047883741557598114,
0.05509158596396446,
-0.11808934807777405,
0.11348052322864532,
0.057328153401613235,
-0.0728185623884201,
0.032391179352998734,
0.05030714347958565,
-0.10392948985099792,
-0.021465230733156204,
0.031419817358255386,
0.14932547509670258,
-0.06275127828121185,
-0.045640427619218826,
-0.13568063080310822,
-0.091814324259758,
0.06645428389310837,
0.07967224717140198,
0.0933644250035286,
0.01663324609398842,
-0.03539150580763817,
-0.013165266253054142,
-0.10855977237224579,
0.10982618480920792,
0.04324139654636383,
0.09105362743139267,
-0.17992232739925385,
0.054193608462810516,
-0.0015555275604128838,
0.07246194779872894,
-0.021836427971720695,
-0.00042325531831011176,
-0.08788467198610306,
0.003508437890559435,
-0.10813499987125397,
0.02464236691594124,
-0.052905477583408356,
0.006243168842047453,
-0.02064651995897293,
-0.0580705925822258,
-0.06364380568265915,
0.024784497916698456,
-0.11918067932128906,
-0.053243763744831085,
0.02146504819393158,
0.031834639608860016,
-0.12016978859901428,
-0.04392008110880852,
0.020345089957118034,
-0.08986733108758926,
0.09774119406938553,
0.06029992923140526,
-0.008077923208475113,
0.00773270707577467,
0.0036002967972308397,
-0.02274298295378685,
0.0666942149400711,
0.007561622653156519,
0.08597277849912643,
-0.1152612566947937,
-0.0221384409815073,
0.01634843461215496,
-0.004547150805592537,
0.017726117745041847,
0.15840598940849304,
-0.12086156010627747,
-0.0003179961640853435,
-0.014678256586194038,
-0.06600851565599442,
-0.06344839930534363,
0.06893838196992874,
0.10903503000736237,
0.02346671372652054,
0.21181334555149078,
-0.054371658712625504,
0.015811823308467865,
-0.20995409786701202,
-0.011581460013985634,
0.005185890011489391,
-0.1388559192419052,
-0.10497695952653885,
-0.03237957879900932,
0.06376256048679352,
-0.07031478732824326,
0.11765085160732269,
0.03525954857468605,
0.02161695808172226,
0.02906344085931778,
0.025029366835951805,
-0.0031726681627333164,
0.013450034894049168,
0.16309522092342377,
0.014403261244297028,
-0.028442582115530968,
0.12852592766284943,
0.028986822813749313,
0.09334488213062286,
0.11778779327869415,
0.17672526836395264,
0.11388354748487473,
0.04729508236050606,
0.09055530279874802,
0.05202596262097359,
-0.025968270376324654,
-0.22174733877182007,
0.03601896017789841,
-0.03978736698627472,
0.1488790065050125,
-0.0030294209718704224,
0.15902450680732727,
0.0920415073633194,
-0.18360793590545654,
0.040488436818122864,
-0.03700747340917587,
-0.0790853351354599,
-0.08454839885234833,
-0.12155362963676453,
-0.10311590880155563,
-0.15089921653270721,
0.002945262473076582,
-0.1040843203663826,
0.023338600993156433,
0.11202728003263474,
-0.008582104928791523,
-0.009919910691678524,
0.116677425801754,
-0.02631515823304653,
0.026041926816105843,
0.03836518153548241,
0.00608045794069767,
-0.059937771409749985,
-0.044151950627565384,
-0.08065995573997498,
0.014101422391831875,
0.032313644886016846,
0.05599058046936989,
-0.03235676884651184,
-0.007023791316896677,
0.03841041401028633,
-0.010091220960021019,
-0.12353866547346115,
0.01347822230309248,
0.005028906278312206,
0.05164548382163048,
0.0008541525457985699,
0.012780209071934223,
0.03201600909233093,
-0.015217483974993229,
0.19341084361076355,
-0.07325411587953568,
-0.027416478842496872,
-0.1228807121515274,
0.17896701395511627,
0.0026140701957046986,
-0.04994320869445801,
0.05295133590698242,
-0.09137362241744995,
-0.020702529698610306,
0.15485265851020813,
0.1892986297607422,
-0.07158271223306656,
-0.016520513221621513,
-0.017527583986520767,
-0.013897030614316463,
-0.022615507245063782,
0.09919055551290512,
0.0991419330239296,
-0.0069245584309101105,
-0.0751221776008606,
-0.028980256989598274,
-0.06606413424015045,
-0.034512959420681,
-0.03850788250565529,
0.06925404816865921,
-0.004570751916617155,
0.0070457919500768185,
-0.07483471930027008,
0.04310325160622597,
-0.02210995741188526,
-0.06085818260908127,
0.06226903945207596,
-0.21256737411022186,
-0.17790570855140686,
0.006773421075195074,
0.07538973540067673,
0.0015973751433193684,
0.0461571104824543,
-0.009913075715303421,
0.018662674352526665,
0.07594356685876846,
-0.02225665934383869,
-0.08672447502613068,
-0.09593749046325684,
0.10812120139598846,
-0.13375911116600037,
0.2528570294380188,
-0.03883460536599159,
0.03583916276693344,
0.12127543240785599,
0.041867125779390335,
-0.1335451751947403,
0.03351692110300064,
0.03981999680399895,
-0.032485269010066986,
0.00548918079584837,
0.14240407943725586,
-0.03740047290921211,
0.07958021014928818,
0.0458458811044693,
-0.1027912050485611,
-0.03964604437351227,
-0.04966754838824272,
-0.011354409158229828,
-0.024445757269859314,
-0.054610975086688995,
-0.036348532885313034,
0.13227923214435577,
0.17175258696079254,
-0.042096637189388275,
-0.023690558969974518,
-0.06475082784891129,
0.030860183760523796,
0.07729368656873703,
-0.03295742720365524,
-0.052064236253499985,
-0.23603148758411407,
0.0024359924718737602,
0.05229694023728371,
-0.013576737605035305,
-0.20701472461223602,
-0.110505111515522,
0.0060418094508349895,
-0.05801977962255478,
-0.07628542929887772,
0.09231390058994293,
0.06255589425563812,
0.035103797912597656,
-0.06320928037166595,
0.038133736699819565,
-0.07872021943330765,
0.14179112017154694,
-0.14508864283561707,
-0.07859515398740768
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | asifhaider/asif-train-200e-all-codellama-7b-ft | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-08T23:43:24+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
31,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06646376848220825,
0.2168014943599701,
-0.00225935154594481,
0.023818302899599075,
0.1271018385887146,
-0.001635765191167593,
0.04218708351254463,
0.13324736058712006,
-0.020175931975245476,
0.11144465953111649,
0.046588581055402756,
0.09377603232860565,
0.09928803145885468,
0.18404334783554077,
0.04859916493296623,
-0.2059975117444992,
0.007056170143187046,
-0.09090408682823181,
0.014076028019189835,
0.1116579994559288,
0.13719257712364197,
-0.10291384905576706,
0.08272874355316162,
-0.04045208916068077,
-0.02019004337489605,
0.00012576708104461432,
-0.09259183704853058,
-0.07032395154237747,
0.06885425746440887,
0.06264153122901917,
0.051234472543001175,
0.001456156256608665,
0.09140396863222122,
-0.2864592671394348,
0.017265573143959045,
0.08406311273574829,
0.0027674848679453135,
0.06290827691555023,
0.07236549258232117,
-0.07389893382787704,
0.11328595131635666,
-0.08021481335163116,
0.13019037246704102,
0.08625296503305435,
-0.062064990401268005,
-0.23071379959583282,
-0.07525765895843506,
0.0963398814201355,
0.12251301854848862,
0.06215599179267883,
-0.022921854630112648,
0.15455181896686554,
-0.06248689442873001,
0.012971068732440472,
0.1294165402650833,
-0.11526761949062347,
-0.05572471022605896,
0.061741601675748825,
0.11775490641593933,
0.10740239918231964,
-0.14110268652439117,
-0.0017287094378843904,
0.04900608956813812,
0.029121357947587967,
0.08589313924312592,
0.022661056369543076,
0.12003941088914871,
0.04652795568108559,
-0.13695219159126282,
-0.04037507623434067,
0.12011898308992386,
0.038862764835357666,
-0.06446044892072678,
-0.2168138176202774,
-0.006778308190405369,
-0.0601806715130806,
-0.014732478186488152,
-0.07019448280334473,
0.039128515869379044,
-0.02470310963690281,
0.07317749410867691,
-0.04465159401297569,
-0.1063927412033081,
-0.0421026237308979,
0.0892222449183464,
0.07748593389987946,
0.011527054943144321,
-0.02519804798066616,
0.04627908393740654,
0.13455867767333984,
0.05402068421244621,
-0.10399353504180908,
-0.07017925381660461,
-0.06942764669656754,
-0.09420394152402878,
-0.04035796597599983,
0.056760527193546295,
0.031942449510097504,
0.02665667235851288,
0.22703726589679718,
0.016653569415211678,
0.04155244305729866,
0.0224777739495039,
0.01032855175435543,
0.043662428855895996,
0.0955500528216362,
-0.05303520709276199,
-0.15660029649734497,
-0.04072032496333122,
0.09077946096658707,
-0.0027527001220732927,
-0.036689214408397675,
-0.03966725245118141,
0.03849169611930847,
0.06843466311693192,
0.13122352957725525,
0.07552056759595871,
-0.017929591238498688,
-0.04813180863857269,
-0.030096933245658875,
0.23523783683776855,
-0.1493375599384308,
0.04426715523004532,
-0.02271856553852558,
-0.01804111897945404,
-0.03908449783921242,
0.03597262129187584,
0.022118929773569107,
-0.000004518366949923802,
0.09706240892410278,
-0.058981191366910934,
-0.05378659814596176,
-0.10168042778968811,
-0.03272576630115509,
0.04088849574327469,
-0.013975566253066063,
-0.010589460842311382,
-0.09025166928768158,
-0.09490354359149933,
-0.04766594246029854,
0.05537205561995506,
-0.05123869329690933,
-0.03770573064684868,
0.009465423412621021,
-0.08151785284280777,
-0.005444355774670839,
-0.005417742300778627,
0.10699385404586792,
-0.03222226724028587,
0.04445803165435791,
-0.027600755915045738,
0.05225523188710213,
0.09919606149196625,
0.031576547771692276,
-0.0773419588804245,
0.0561848059296608,
-0.22559374570846558,
0.07503069192171097,
-0.11481974273920059,
0.04335082694888115,
-0.1704932004213333,
-0.042439818382263184,
0.005444696638733149,
0.0139949731528759,
0.013206101022660732,
0.12720820307731628,
-0.19255615770816803,
-0.01654396951198578,
0.13260798156261444,
-0.09212633967399597,
-0.118110790848732,
0.07884611934423447,
-0.029701577499508858,
0.1624738723039627,
0.04682036489248276,
-0.027025915682315826,
0.09224298596382141,
-0.16434773802757263,
-0.07092688232660294,
-0.00949116237461567,
-0.01727987825870514,
0.12109188735485077,
0.07512219995260239,
-0.05991523340344429,
0.046571120619773865,
0.02832140028476715,
-0.038078423589468,
-0.04424772411584854,
-0.050857074558734894,
-0.10884185880422592,
-0.01070026308298111,
-0.08987759798765182,
0.04065500199794769,
-0.01250192429870367,
-0.07916021347045898,
-0.029885273426771164,
-0.18612512946128845,
-0.0030564051121473312,
0.10038342326879501,
0.0035033065360039473,
-0.005652366206049919,
-0.08666291832923889,
0.026358824223279953,
-0.03112892620265484,
-0.008404186926782131,
-0.16764774918556213,
-0.04399421438574791,
0.046902090311050415,
-0.16094985604286194,
0.020117372274398804,
-0.06413903087377548,
0.06334125250577927,
0.03641495108604431,
-0.05590536445379257,
-0.0248766727745533,
-0.01730942726135254,
0.011945613659918308,
-0.05083848536014557,
-0.18994836509227753,
-0.056277405470609665,
-0.037882111966609955,
0.149809330701828,
-0.25956398248672485,
0.032966937869787216,
0.051140617579221725,
0.14649195969104767,
0.00406361510977149,
-0.05115427449345589,
0.01429014839231968,
-0.05360214412212372,
-0.054652128368616104,
-0.06746816635131836,
-0.006135428790003061,
-0.027576493099331856,
-0.05147203803062439,
0.019243421033024788,
-0.1755700707435608,
-0.021410830318927765,
0.09424154460430145,
0.12876708805561066,
-0.1486445665359497,
-0.018640631809830666,
-0.048725154250860214,
-0.06339836865663528,
-0.0715010017156601,
-0.07038594037294388,
0.10712739825248718,
0.0513901449739933,
0.04796046018600464,
-0.07435787469148636,
-0.07092321664094925,
0.02726263552904129,
0.006906150374561548,
-0.03382374346256256,
0.08727246522903442,
0.05199531093239784,
-0.09209315478801727,
0.0756213590502739,
0.1092359870672226,
0.07177663594484329,
0.09363535046577454,
0.01574566215276718,
-0.11756632477045059,
-0.028492970392107964,
0.036266472190618515,
0.02740776725113392,
0.1465986967086792,
-0.05952361226081848,
0.04016614332795143,
0.04494241625070572,
-0.04170418903231621,
0.022319864481687546,
-0.08787637203931808,
0.024075502529740334,
0.025203049182891846,
-0.0034381982404738665,
0.06284574419260025,
-0.02525499276816845,
-0.0050758360885083675,
0.07016654312610626,
0.047779910266399384,
0.04621000960469246,
0.009655474685132504,
-0.01720241829752922,
-0.1047825813293457,
0.16950392723083496,
-0.0951867327094078,
-0.269941508769989,
-0.17632324993610382,
0.026197833940386772,
0.04035249724984169,
-0.022378476336598396,
0.031619444489479065,
-0.07056326419115067,
-0.10630585998296738,
-0.1060405746102333,
-0.002429972169920802,
0.01714223250746727,
-0.06364088505506516,
-0.0741225928068161,
0.07348573952913284,
0.04382912442088127,
-0.14902326464653015,
0.038552410900592804,
0.055694397538900375,
-0.057955220341682434,
-0.0233661737293005,
0.09118817001581192,
0.12397737801074982,
0.14583967626094818,
-0.021366750821471214,
-0.028626007959246635,
0.029004426673054695,
0.19620531797409058,
-0.13469526171684265,
0.10371150821447372,
0.13814030587673187,
-0.04545360431075096,
0.08360563963651657,
0.1560150384902954,
0.029186224564909935,
-0.08317049592733383,
0.05044832453131676,
0.04082648828625679,
-0.043159641325473785,
-0.2666129767894745,
-0.0534592866897583,
0.012832709588110447,
-0.06255637854337692,
0.09786593168973923,
0.10183793306350708,
0.11542957276105881,
0.034910861402750015,
-0.07166364789009094,
-0.043925940990448,
-0.0058974819257855415,
0.11737963557243347,
-0.05490213260054588,
-0.012639665976166725,
0.07686592638492584,
-0.05086168646812439,
0.005355054512619972,
0.10266812145709991,
0.02973790094256401,
0.17442677915096283,
0.020399179309606552,
0.11231429129838943,
0.06195578724145889,
0.08633565157651901,
0.0007386076031252742,
0.02951662428677082,
0.05147615820169449,
0.017203815281391144,
-0.002300140680745244,
-0.10421168059110641,
-0.006156572140753269,
0.1449710875749588,
0.028103826567530632,
0.029669636860489845,
-0.0018948549404740334,
-0.005003341939300299,
0.05121048167347908,
0.1746254414319992,
-0.011592294089496136,
-0.22072425484657288,
-0.0845772922039032,
0.06936841458082199,
-0.06218599155545235,
-0.12968985736370087,
-0.026130788028240204,
0.045467354357242584,
-0.17519839107990265,
0.026703642681241035,
-0.027433741837739944,
0.0919293761253357,
-0.09345759451389313,
-0.02221956104040146,
0.03687324374914169,
0.084866963326931,
-0.014529162086546421,
0.08703910559415817,
-0.14498743414878845,
0.11886418610811234,
0.02978132851421833,
0.09024628251791,
-0.11081171780824661,
0.07909037172794342,
-0.007550720125436783,
0.009180475026369095,
0.19379350543022156,
-0.011335089802742004,
-0.03514958545565605,
-0.08774717897176743,
-0.11210042238235474,
-0.013537433929741383,
0.12687496840953827,
-0.1243172138929367,
0.08773399889469147,
-0.015198243781924248,
-0.044079482555389404,
0.00937260314822197,
-0.12100647389888763,
-0.17273177206516266,
-0.19628387689590454,
0.05585884302854538,
-0.09575839340686798,
0.025643249973654747,
-0.11914430558681488,
-0.07089093327522278,
-0.02952558360993862,
0.241120383143425,
-0.1745356321334839,
-0.06510113179683685,
-0.1468164622783661,
-0.046294767409563065,
0.1662203073501587,
-0.04437198117375374,
0.0718095526099205,
-0.0208172257989645,
0.20345525443553925,
0.005988610442727804,
-0.004939318168908358,
0.06724198162555695,
-0.08892562240362167,
-0.16873881220817566,
-0.06771010160446167,
0.1510489284992218,
0.11680185794830322,
0.04907919466495514,
-0.002248800592496991,
0.0011772146681323647,
-0.016943959519267082,
-0.1137804463505745,
-0.0033210667315870523,
0.16037839651107788,
0.03878779336810112,
0.025986969470977783,
-0.05243593826889992,
-0.08797456324100494,
-0.06899320334196091,
-0.06853509694337845,
0.06221301481127739,
0.19590823352336884,
-0.10376439243555069,
0.1700313836336136,
0.147536963224411,
-0.07305635511875153,
-0.23175598680973053,
0.035342130810022354,
0.04983805492520332,
0.0014306638622656465,
0.04886869341135025,
-0.18252557516098022,
0.10521943867206573,
0.019543392583727837,
-0.05505957826972008,
0.13485197722911835,
-0.1557481735944748,
-0.1552847921848297,
0.0722852572798729,
0.03904085233807564,
-0.22423844039440155,
-0.1354004591703415,
-0.09622503817081451,
-0.05825018882751465,
-0.14065024256706238,
0.06054598465561867,
-0.002136280992999673,
0.015948504209518433,
0.03500790148973465,
-0.0015643214574083686,
0.027123261243104935,
-0.058935679495334625,
0.18609118461608887,
-0.004065449349582195,
0.020676052197813988,
-0.060264769941568375,
-0.0478842556476593,
0.09839435666799545,
-0.06130504235625267,
0.12208222597837448,
0.004057085141539574,
0.01594383642077446,
-0.10362856835126877,
-0.048314861953258514,
-0.04328322783112526,
0.05154227837920189,
-0.07548051327466965,
-0.10070807486772537,
-0.043625857681035995,
0.08841723203659058,
0.07005169242620468,
-0.03383097052574158,
0.00549331633374095,
-0.07189501076936722,
0.10019614547491074,
0.17795267701148987,
0.17573626339435577,
0.009926567785441875,
-0.07241068035364151,
0.01677953451871872,
-0.04142116755247116,
0.044231921434402466,
-0.2513144314289093,
0.03756171092391014,
0.06098250672221184,
0.029438555240631104,
0.09217222779989243,
-0.020435843616724014,
-0.1820858269929886,
-0.04050002992153168,
0.08094815909862518,
-0.05452597141265869,
-0.22617179155349731,
-0.019085140898823738,
0.0954197570681572,
-0.2020406424999237,
-0.007372708059847355,
0.03995226323604584,
-0.048725228756666183,
-0.023169852793216705,
0.00010950004070764408,
0.06317184865474701,
0.002471912419423461,
0.09773622453212738,
0.0735151618719101,
0.09715340286493301,
-0.08337292820215225,
0.10562895983457565,
0.10150538384914398,
-0.09572599828243256,
0.03605884686112404,
0.06754924356937408,
-0.05300498008728027,
-0.043293699622154236,
0.03665391728281975,
0.033023297786712646,
0.005234600510448217,
-0.060321882367134094,
0.013913018628954887,
-0.036497246474027634,
0.044923391193151474,
0.08326134830713272,
0.03754979372024536,
-0.013354414142668247,
0.06462216377258301,
0.03401726484298706,
-0.10898099094629288,
0.10366570204496384,
0.01731540448963642,
0.04105307161808014,
-0.08384523540735245,
-0.019968897104263306,
0.035425446927547455,
0.030576206743717194,
-0.01765924133360386,
-0.02306121215224266,
-0.02860277332365513,
-0.01614218018949032,
-0.14299540221691132,
-0.023106401786208153,
-0.07243485748767853,
0.006181265693157911,
0.014656842686235905,
-0.031884219497442245,
-0.011233693920075893,
0.02475680410861969,
-0.06979699432849884,
-0.07426341623067856,
-0.006949664559215307,
0.09833318740129471,
-0.15115703642368317,
0.008848577737808228,
0.06907843053340912,
-0.11088496446609497,
0.08190931379795074,
-0.008411259390413761,
0.016245156526565552,
0.022527478635311127,
-0.15448406338691711,
0.05601610988378525,
0.0008648968650959432,
0.01916889287531376,
0.025886621326208115,
-0.16471809148788452,
0.004104440100491047,
-0.04661374166607857,
-0.02149827405810356,
-0.00004464812809601426,
-0.02647159807384014,
-0.12325995415449142,
0.06858719140291214,
-0.015622655861079693,
-0.035931166261434555,
-0.02701525390148163,
0.0539589487016201,
0.07888586074113846,
-0.027474910020828247,
0.10445091128349304,
-0.008690856397151947,
0.04941811040043831,
-0.16801609098911285,
-0.02470702864229679,
-0.04982255399227142,
0.019377702847123146,
0.009884213097393513,
-0.007693959400057793,
0.04183054715394974,
-0.00976533442735672,
0.21883612871170044,
-0.05075952783226967,
0.1607085019350052,
0.05847611650824547,
-0.017352959141135216,
-0.0007513365126214921,
0.06180921941995621,
0.05997028574347496,
0.04658793285489082,
0.009480604901909828,
0.023740366101264954,
-0.022450892254710197,
-0.006695089396089315,
-0.15932634472846985,
0.01890849508345127,
0.14999441802501678,
0.06301083415746689,
0.024745315313339233,
0.05866100639104843,
-0.12775006890296936,
-0.12135478109121323,
0.09311001747846603,
-0.026755332946777344,
0.00928465835750103,
-0.08245618641376495,
0.1358020007610321,
0.14980104565620422,
-0.14000412821769714,
0.05256148427724838,
-0.06134212389588356,
-0.05217423290014267,
-0.10388828068971634,
-0.12032219022512436,
-0.05887215584516525,
-0.053666237741708755,
0.002330566756427288,
-0.03760887682437897,
0.054546963423490524,
0.03344334661960602,
-0.009351172484457493,
-0.00022941511997487396,
0.13597318530082703,
-0.019751882180571556,
-0.0028988157864660025,
0.048313532024621964,
0.03693558648228645,
0.02373051457107067,
-0.05275435373187065,
0.02940409444272518,
0.02539868652820587,
0.032232340425252914,
0.06546790152788162,
0.033412106335163116,
-0.047448933124542236,
0.03804153576493263,
-0.0025254099164158106,
-0.11207924783229828,
0.019641218706965446,
-0.00460948096588254,
-0.0742158442735672,
0.1268945336341858,
0.0407399944961071,
0.010224059224128723,
-0.03741471841931343,
0.24361543357372284,
-0.06653323769569397,
-0.06378097087144852,
-0.13251738250255585,
0.10491154342889786,
-0.0027236645109951496,
0.06476365029811859,
0.023412218317389488,
-0.1284150779247284,
0.005243356805294752,
0.13858191668987274,
0.12181595712900162,
0.0045748427510261536,
0.009228081442415714,
0.0518609918653965,
0.0025186820421367884,
-0.06998204439878464,
0.054019294679164886,
0.06992026418447495,
0.12919506430625916,
-0.07847554981708527,
0.07680778950452805,
0.0006860480643808842,
-0.08370215445756912,
-0.02947772853076458,
0.11312682181596756,
-0.0409729965031147,
0.03491825982928276,
-0.047444481402635574,
0.10916327685117722,
-0.05787910893559456,
-0.29412412643432617,
0.02350960113108158,
-0.09588567912578583,
-0.15202060341835022,
-0.018367812037467957,
0.05944539234042168,
-0.02624768204987049,
0.018029648810625076,
0.06971040368080139,
-0.06011629104614258,
0.20098382234573364,
0.0335683599114418,
-0.07864278554916382,
-0.0664360448718071,
0.04837050288915634,
-0.06564252078533173,
0.2949807047843933,
0.008418165147304535,
0.02863333560526371,
0.10770907253026962,
-0.03253700211644173,
-0.18271861970424652,
0.010723991319537163,
0.1133992001414299,
-0.08056149631738663,
0.08200647681951523,
0.19000613689422607,
-0.012578671798110008,
0.1209007054567337,
0.05294662341475487,
-0.047376248985528946,
0.04217283055186272,
-0.03389401361346245,
-0.051268599927425385,
-0.10752558708190918,
0.058453381061553955,
-0.05909625440835953,
0.15447644889354706,
0.10152646154165268,
-0.05671518296003342,
-0.004550917539745569,
-0.05555408447980881,
0.04875178262591362,
0.01804669201374054,
0.12263146042823792,
0.02951994352042675,
-0.1865430772304535,
0.032826557755470276,
-0.01144319772720337,
0.10186848044395447,
-0.25588861107826233,
-0.08421015739440918,
0.08833149075508118,
-0.011924264021217823,
-0.05105875805020332,
0.10560628771781921,
0.057650718837976456,
0.04243382066488266,
-0.043439045548439026,
-0.10480839014053345,
-0.02186836116015911,
0.14663739502429962,
-0.1469624787569046,
-0.025013303384184837
] |
null | null | transformers |
🎉 Introducing **CustomGPT2Conversational** 🤖
🚀 Dive into the world of limitless conversations with our fine-tuned model!
🎨 **Unique Features**:
- 💬 Seamlessly generates engaging and contextually relevant responses.
- 🧠 Fine-tuned for conversational tasks, ensuring natural and fluid interactions.
- 🌟 Employs cutting-edge technologies to deliver state-of-the-art performance.
🔧 **Technical Specifications**:
- 🛠 Architecture: GPT2LMHeadModel
- 📏 Parameters: 24 layers, 2048 hidden size, 16 attention heads
- 🧮 Dropout: Attention dropout of 0.1, embedding dropout of 0.1, and residual dropout of 0.1
- 🎚 Activation Function: GELU (Gaussian Error Linear Unit)
- 📊 Metrics: Achieves outstanding perplexity and accuracy scores
🛠 **Configuration Details**:
- 📝 Task-Specific Parameters: Early stopping, length penalty, beam search, and more to enhance conversational quality.
- 📈 Dynamic Adaptation: Adaptable to changing environmental conditions for optimal performance.
- 📚 Language Support: Primarily English with potential for multilingual applications.
🌟 **Pipeline Tag**: Conversational 🗣️
📚 **Dataset**: Utilizes data from the LDJnr/Capybara dataset 🦙
🔗 **Library and Version**: Transformers v4.37.2 📚
🔑 **License**: Apache-2.0 📜
Get ready to experience the next level of conversational AI with **CustomGPT2Conversational**! 🚀🤖 | {"language": "en", "license": "apache-2.0", "tags": ["conversational", "state-of-the-art"], "metrics": ["perplexity", "accuracy", "bleu"], "_name_or_path": "CustomGPT2ConversationalModel", "model_type": "gpt2", "architectures": ["GPT2LMHeadModel"], "tokenizer_config": {"bos_token_id": 50256, "eos_token_id": 50256, "n_positions": 2048, "padding_side": "left", "truncation_side": "right"}, "config": {"activation_function": "gelu_new", "attn_pdrop": 0.1, "embd_pdrop": 0.1, "initializer_range": 0.02, "layer_norm_epsilon": 1e-05, "n_ctx": 2048, "n_embd": 2048, "n_head": 16, "n_layer": 36, "n_positions": 2048, "resid_pdrop": 0.1, "vocab_size": 50257, "scale_attn_weights": true, "gradient_checkpointing": true, "use_cache": true}, "task_specific_params": {"conversational": {"max_length": 1024, "min_length": 20, "temperature": 0.7, "top_k": 40, "top_p": 0.95, "num_beams": 5, "no_repeat_ngram_size": 3, "early_stopping": true, "length_penalty": 2, "do_sample": true, "frequency_penalty": 0.5, "presence_penalty": 0.5}}, "use_cache": true, "torch_dtype": "float32", "transformers_version": "4.37.2", "pipeline_tag": "conversational"} | text-generation | ayjays132/CustomGPT2Conversational | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"conversational",
"state-of-the-art",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-08T23:45:23+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #gpt2 #text-generation #conversational #state-of-the-art #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
Introducing CustomGPT2Conversational
Dive into the world of limitless conversations with our fine-tuned model!
Unique Features:
- Seamlessly generates engaging and contextually relevant responses.
- Fine-tuned for conversational tasks, ensuring natural and fluid interactions.
- Employs cutting-edge technologies to deliver state-of-the-art performance.
Technical Specifications:
- Architecture: GPT2LMHeadModel
- Parameters: 24 layers, 2048 hidden size, 16 attention heads
- Dropout: Attention dropout of 0.1, embedding dropout of 0.1, and residual dropout of 0.1
- Activation Function: GELU (Gaussian Error Linear Unit)
- Metrics: Achieves outstanding perplexity and accuracy scores
Configuration Details:
- Task-Specific Parameters: Early stopping, length penalty, beam search, and more to enhance conversational quality.
- Dynamic Adaptation: Adaptable to changing environmental conditions for optimal performance.
- Language Support: Primarily English with potential for multilingual applications.
Pipeline Tag: Conversational ️
Dataset: Utilizes data from the LDJnr/Capybara dataset
Library and Version: Transformers v4.37.2
License: Apache-2.0
Get ready to experience the next level of conversational AI with CustomGPT2Conversational! | [] | [
"TAGS\n#transformers #safetensors #gpt2 #text-generation #conversational #state-of-the-art #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] | [
70
] | [
"passage: TAGS\n#transformers #safetensors #gpt2 #text-generation #conversational #state-of-the-art #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] | [
-0.009265601634979248,
0.06791148334741592,
-0.00627034530043602,
0.021359162405133247,
0.05932557210326195,
-0.017279285937547684,
0.16106323897838593,
0.12712761759757996,
-0.046437639743089676,
-0.03648752719163895,
0.18217532336711884,
0.1703614443540573,
-0.0026096089277416468,
0.11454074084758759,
-0.07611172646284103,
-0.1662820279598236,
0.10388783365488052,
-0.0163131020963192,
-0.011559568345546722,
0.10607138276100159,
0.13007432222366333,
-0.005812882445752621,
0.06411222368478775,
-0.026538556441664696,
-0.06156986951828003,
-0.01112345140427351,
0.06946985423564911,
-0.14220784604549408,
0.11022044718265533,
0.047229159623384476,
0.028534721583127975,
0.07009553164243698,
-0.040643054991960526,
-0.20049642026424408,
0.02424873784184456,
0.03031550906598568,
-0.07075002789497375,
0.03926767408847809,
0.01819382794201374,
-0.05321207642555237,
0.06428627669811249,
0.03234462812542915,
-0.03032345324754715,
0.08900561183691025,
-0.12814554572105408,
-0.10508864372968674,
-0.06659162044525146,
0.027758143842220306,
0.1023978739976883,
0.08555837720632553,
-0.020202767103910446,
0.12613534927368164,
-0.019964685663580894,
0.06839252263307571,
0.09565693140029907,
-0.3804139196872711,
0.0004063262604176998,
0.058094464242458344,
0.04405759274959564,
0.06618615239858627,
-0.023361103609204292,
0.08902118355035782,
0.06589233130216599,
-0.00835504848510027,
0.04394221678376198,
-0.0439775250852108,
-0.10260690003633499,
0.029244912788271904,
-0.07219139486551285,
-0.04759025573730469,
0.26813703775405884,
-0.002659194404259324,
0.011950020678341389,
-0.06662397086620331,
-0.08900696039199829,
0.0358675979077816,
-0.020655106753110886,
-0.0019710941705852747,
-0.01147530972957611,
0.12326967716217041,
0.018686329945921898,
-0.07615120708942413,
-0.1506521850824356,
-0.029720738530158997,
-0.15803928673267365,
0.09109113365411758,
0.004591328091919422,
0.045493725687265396,
-0.14303240180015564,
0.059355806559324265,
-0.019735166803002357,
-0.1089833527803421,
-0.027224058285355568,
-0.09358413517475128,
0.1044103279709816,
0.024208825081586838,
-0.02347087487578392,
-0.022522374987602234,
0.17943155765533447,
0.20462071895599365,
-0.011645489372313023,
0.022181611508131027,
-0.0858277827501297,
0.08509711921215057,
-0.036802709102630615,
0.03242175653576851,
0.03873942419886589,
-0.047782380133867264,
0.11549756675958633,
-0.09247143566608429,
0.08907417953014374,
-0.04026998206973076,
-0.13261523842811584,
0.01917078159749508,
-0.002575916238129139,
0.12144849449396133,
0.055390603840351105,
0.10311158001422882,
-0.03981010615825653,
0.061961572617292404,
0.10790222138166428,
-0.04808284342288971,
-0.02047923393547535,
-0.010160230100154877,
0.06303317844867706,
0.0009189292322844267,
0.048611365258693695,
0.07337427884340286,
-0.060638055205345154,
-0.0031037828885018826,
-0.03664160519838333,
-0.05265943333506584,
-0.01727444678544998,
-0.015327712520956993,
0.059545911848545074,
-0.008668042719364166,
0.017670998349785805,
-0.17269805073738098,
-0.1725185662508011,
0.03551050275564194,
0.03446930646896362,
-0.008072319440543652,
-0.07432515174150467,
-0.022514017298817635,
-0.023631233721971512,
0.045053958892822266,
-0.0881974995136261,
-0.057776980102062225,
-0.09521176666021347,
0.06969863176345825,
-0.03805159032344818,
0.05207260698080063,
-0.17402566969394684,
0.033886492252349854,
-0.12218892574310303,
-0.003076642518863082,
-0.036995116621255875,
0.028363175690174103,
-0.06048477813601494,
0.16497555375099182,
-0.052507586777210236,
0.029527854174375534,
-0.02887762524187565,
0.038230471312999725,
-0.04159339517354965,
0.18547871708869934,
-0.09126754850149155,
-0.04052247479557991,
0.2987164258956909,
-0.12270715832710266,
-0.2342544049024582,
0.13026168942451477,
0.025300759822130203,
0.06689541786909103,
0.12204170227050781,
0.17500853538513184,
-0.008007093332707882,
-0.034803491085767746,
0.06720221042633057,
0.12498270720243454,
-0.09693199396133423,
-0.0462292842566967,
0.045949120074510574,
-0.0618450902402401,
-0.11722827702760696,
0.035057444125413895,
0.0233902744948864,
0.07593949139118195,
0.01063648983836174,
-0.06798254698514938,
-0.06255146861076355,
-0.04038230702280998,
0.025521820411086082,
-0.06481022387742996,
0.02066834643483162,
-0.12210746854543686,
-0.04873598739504814,
-0.08581450581550598,
0.004256164655089378,
0.00944108609110117,
0.03227843716740608,
-0.09122005850076675,
0.04146360605955124,
0.02337537333369255,
0.08005084842443466,
-0.06332392245531082,
-0.0714055746793747,
-0.018892353400588036,
0.07865434139966965,
0.030040448531508446,
0.016339058056473732,
0.06545258313417435,
-0.02461497113108635,
-0.01686929725110531,
0.002685180166736245,
0.16475893557071686,
0.03320099413394928,
-0.026000142097473145,
-0.12606999278068542,
0.1334395855665207,
-0.03768826648592949,
0.10341676324605942,
-0.05369172617793083,
0.03505841642618179,
0.08293682336807251,
0.06905211508274078,
-0.008929426781833172,
0.062438081949949265,
-0.01014801487326622,
-0.0512264259159565,
-0.06372354924678802,
-0.02537042833864689,
0.08315061777830124,
0.0489812009036541,
-0.1110115721821785,
0.20634984970092773,
-0.16756413877010345,
0.2554324269294739,
0.19658499956130981,
-0.17082594335079193,
0.04072364419698715,
-0.03629964590072632,
-0.021443447098135948,
0.008221447467803955,
0.01977570727467537,
-0.02552456595003605,
0.03473443537950516,
-0.024309882894158363,
0.1418076753616333,
-0.06468082219362259,
-0.030160877853631973,
-0.01654811017215252,
-0.0859016478061676,
-0.011020291596651077,
0.02565413899719715,
0.05918939784169197,
-0.169944167137146,
0.19149376451969147,
0.2864590883255005,
0.016029449179768562,
0.12170196324586868,
-0.038996826857328415,
0.01171357836574316,
0.05481545254588127,
0.04687491059303284,
-0.008447076193988323,
-0.02127029187977314,
-0.16321757435798645,
0.006069617345929146,
0.08187778294086456,
0.0433548279106617,
0.05389415845274925,
-0.12579472362995148,
-0.05491071194410324,
-0.008079382590949535,
-0.06374865025281906,
0.0029487002175301313,
0.048016536980867386,
-0.04137295112013817,
0.13094519078731537,
-0.02493908628821373,
-0.04391888529062271,
0.12229122966527939,
0.013237562030553818,
-0.10081075876951218,
0.1464461237192154,
-0.15894493460655212,
-0.2900393605232239,
-0.13502828776836395,
-0.11809680610895157,
-0.05989144369959831,
0.053191542625427246,
0.1712193638086319,
-0.08760437369346619,
-0.056314803659915924,
-0.0520997978746891,
0.0014653302496299148,
0.021973108872771263,
0.019129808992147446,
0.0025755634997040033,
0.04149094596505165,
-0.0036348330322653055,
-0.12993104755878448,
-0.044284697622060776,
0.031656064093112946,
-0.07522539049386978,
0.11483612656593323,
-0.06429187953472137,
0.09930334985256195,
0.13124702870845795,
0.044979799538850784,
0.01632075011730194,
-0.05781667307019234,
0.132088303565979,
-0.07134640216827393,
0.01135318260639906,
0.19715750217437744,
-0.037327609956264496,
0.0632740706205368,
0.13759341835975647,
-0.007182329893112183,
-0.10248716175556183,
0.0617179237306118,
-0.04803209751844406,
-0.07899565249681473,
-0.2425273209810257,
-0.1037101075053215,
-0.0733756348490715,
0.1257612556219101,
0.01431795209646225,
0.07395648211240768,
0.1567840874195099,
0.08989890664815903,
-0.06768149137496948,
-0.004260130226612091,
0.1008206307888031,
0.09820107370615005,
0.2056255042552948,
-0.05324086919426918,
0.13600847125053406,
-0.10819834470748901,
-0.08837351202964783,
0.12993058562278748,
0.07048206031322479,
0.04443103075027466,
0.10303476452827454,
0.09587202966213226,
0.060877252370119095,
0.11230497062206268,
0.07486339658498764,
0.09977909177541733,
0.047825202345848083,
-0.02959517203271389,
-0.04947324097156525,
-0.05331505835056305,
-0.05633426457643509,
0.07261528074741364,
-0.09730403125286102,
-0.13592591881752014,
0.021521633490920067,
-0.030692793428897858,
0.13590030372142792,
0.1419079303741455,
0.06200799345970154,
-0.17618393898010254,
-0.011711349710822105,
0.12073638290166855,
0.006017863284796476,
-0.09163294732570648,
0.11482793092727661,
-0.00037316695670597255,
-0.06361211836338043,
0.12405743449926376,
-0.028300121426582336,
0.10979735106229782,
-0.004514265805482864,
0.06405027210712433,
-0.0765780657529831,
-0.07683982700109482,
0.012898308224976063,
0.12508291006088257,
-0.32936862111091614,
0.17567817866802216,
-0.004650861956179142,
-0.0005091044004075229,
-0.08828498423099518,
0.030403172597289085,
0.04620429128408432,
0.16414526104927063,
0.15587769448757172,
-0.01695176027715206,
-0.09812293201684952,
0.036523424088954926,
-0.06423155963420868,
0.06547656655311584,
0.07837750762701035,
-0.005137963220477104,
-0.03479740396142006,
-0.0663994774222374,
-0.0047190627083182335,
0.024992888793349266,
-0.022572685033082962,
-0.07833869755268097,
-0.15396882593631744,
0.0579276904463768,
0.11969032883644104,
0.1234072595834732,
-0.05725111812353134,
0.036667197942733765,
-0.1301153153181076,
0.23078103363513947,
-0.09618547558784485,
-0.07394437491893768,
-0.0956135019659996,
-0.12179289758205414,
-0.01667959615588188,
-0.030210459604859352,
0.052537523210048676,
-0.07003724575042725,
0.05224599316716194,
-0.05842083320021629,
-0.1737748682498932,
0.1282900720834732,
-0.13559694588184357,
-0.06002121418714523,
-0.026732122525572777,
0.14373460412025452,
-0.08012286573648453,
-0.011473113670945168,
0.05535760521888733,
0.020284701138734818,
-0.08575210720300674,
-0.1354319006204605,
0.03752334043383598,
0.010314010083675385,
0.031257230788469315,
-0.034277744591236115,
-0.06189711019396782,
-0.11265584826469421,
-0.011314738541841507,
-0.07287709414958954,
0.26101788878440857,
0.23352842032909393,
-0.06013838201761246,
0.17107918858528137,
0.18956361711025238,
-0.07173273712396622,
-0.3293853998184204,
-0.1509861946105957,
-0.19191642105579376,
-0.10104246437549591,
-0.018055247142910957,
-0.1174032911658287,
0.08139850944280624,
0.037000637501478195,
-0.09105591475963593,
0.08548818528652191,
-0.17219285666942596,
-0.09315292537212372,
0.18981653451919556,
-0.01100071333348751,
0.31247180700302124,
-0.18512187898159027,
-0.10010173171758652,
-0.13317351043224335,
-0.13522623479366302,
0.15189747512340546,
-0.19988051056861877,
0.05451180413365364,
0.03844037652015686,
0.017345216125249863,
0.00240028346888721,
-0.03431117162108421,
0.11533763259649277,
-0.07285816222429276,
0.010432828217744827,
-0.13946160674095154,
0.08011050522327423,
0.08224375545978546,
-0.015463043004274368,
0.06795661896467209,
-0.17855383455753326,
0.03458312526345253,
0.007766085676848888,
-0.03343711048364639,
-0.026326043531298637,
0.07511456310749054,
0.015080993063747883,
-0.09186919778585434,
-0.05226987227797508,
-0.08598307520151138,
0.026714874431490898,
0.001508317538537085,
0.22514376044273376,
-0.036288052797317505,
0.1424722522497177,
0.10655148327350616,
0.13840031623840332,
-0.17210344970226288,
0.07911733537912369,
-0.04908186197280884,
-0.09904353320598602,
0.06038530915975571,
-0.1831212192773819,
0.08352533727884293,
0.045396387577056885,
-0.0710851401090622,
0.0972534790635109,
0.06409518420696259,
-0.006632225122302771,
-0.002008146373555064,
0.14334657788276672,
-0.2137477695941925,
-0.07597371190786362,
-0.03361176699399948,
0.12310382723808289,
0.06638884544372559,
0.11849456280469894,
0.18007446825504303,
0.0066411904990673065,
-0.013618966564536095,
-0.0010259498376399279,
0.06903589516878128,
-0.06415253132581711,
0.01723237708210945,
-0.006534114480018616,
-0.011043807491660118,
-0.1198449358344078,
0.1128786951303482,
-0.010064736008644104,
-0.13322892785072327,
0.025517160072922707,
0.0903802141547203,
-0.13868214190006256,
-0.13621121644973755,
-0.003556951880455017,
0.05101970583200455,
-0.0948781818151474,
-0.09925493597984314,
-0.033193524926900864,
-0.16842088103294373,
0.037032149732112885,
0.12059679627418518,
0.06036222353577614,
0.07439617812633514,
0.0330113060772419,
-0.011836735531687737,
0.012192443944513798,
0.0124566201120615,
-0.0632443055510521,
0.016773374751210213,
-0.09833100438117981,
-0.016555694863200188,
-0.017759358510375023,
0.029650812968611717,
-0.06638546288013458,
-0.01324768178164959,
-0.10552877932786942,
0.0065209041349589825,
-0.13792937994003296,
-0.01603958010673523,
-0.10062519460916519,
-0.015275760553777218,
0.016712823882699013,
-0.049867600202560425,
-0.02955569140613079,
-0.026914864778518677,
-0.08314301818609238,
-0.012472065165638924,
-0.03779420256614685,
0.04973091930150986,
-0.1356562376022339,
-0.007603667676448822,
0.07208368182182312,
-0.027824945747852325,
0.1600191295146942,
0.0684603750705719,
-0.08900149166584015,
0.08718202263116837,
-0.24445629119873047,
-0.04082603007555008,
0.11797032505273819,
0.007188534364104271,
-0.016680311411619186,
0.04547156020998955,
-0.01813153363764286,
0.12065885215997696,
-0.00005395096377469599,
0.04920792579650879,
0.02619043178856373,
-0.0917249247431755,
0.011762999929487705,
-0.026453057304024696,
-0.09839071333408356,
-0.015361231751739979,
-0.10484030097723007,
0.08324328064918518,
-0.020631693303585052,
0.15730009973049164,
-0.07602660357952118,
0.013789808377623558,
-0.05505817010998726,
0.03825082629919052,
0.013622372411191463,
-0.1607273817062378,
-0.14499080181121826,
-0.04967982694506645,
-0.015387996099889278,
-0.013632822781801224,
0.25855380296707153,
-0.007784146815538406,
-0.07335822284221649,
0.08786394447088242,
0.038686603307724,
0.0591953881084919,
0.020798109471797943,
0.24854108691215515,
0.07207567244768143,
-0.031788334250450134,
-0.15795426070690155,
-0.0014662690227851272,
0.04797683656215668,
-0.13074278831481934,
0.06687858700752258,
0.05214749649167061,
-0.011785249225795269,
0.08583048731088638,
0.004851840436458588,
0.00036373583134263754,
-0.07212214916944504,
-0.07335876673460007,
-0.040381815284490585,
0.05423079431056976,
-0.010976186022162437,
0.08631565421819687,
0.19704513251781464,
-0.012905956245958805,
-0.024411611258983612,
-0.06608832627534866,
-0.021131500601768494,
-0.17113232612609863,
-0.12168329954147339,
-0.0988253802061081,
-0.15895286202430725,
0.004963740240782499,
-0.08432192355394363,
0.047781698405742645,
0.03581623733043671,
0.052531689405441284,
-0.05360713228583336,
0.07405535876750946,
-0.04616786912083626,
-0.06734583526849747,
0.030917206779122353,
-0.03587106242775917,
0.019989250227808952,
0.006255217827856541,
-0.0708259791135788,
-0.051343176513910294,
0.020699042826890945,
-0.011617091484367847,
0.07063113152980804,
0.007212774362415075,
0.06595509499311447,
-0.1245507299900055,
-0.045792143791913986,
-0.047461289912462234,
0.07141250371932983,
-0.04111293703317642,
0.12873387336730957,
0.027181409299373627,
-0.026212451979517937,
0.12122615426778793,
0.215773344039917,
-0.07195766270160675,
-0.1593477725982666,
-0.08744004368782043,
0.14522215723991394,
-0.02046607807278633,
0.10837795585393906,
-0.033450741320848465,
0.0024191655684262514,
-0.02263929881155491,
0.31060633063316345,
0.26844966411590576,
-0.04500637575984001,
0.026000086218118668,
-0.06507506966590881,
0.03699146583676338,
0.04304457828402519,
0.09986873716115952,
0.11314033716917038,
0.20223204791545868,
-0.05097540467977524,
-0.023520398885011673,
0.007631699554622173,
0.008249561302363873,
-0.13550794124603271,
0.0756058394908905,
-0.035348378121852875,
-0.045333199203014374,
0.0008963751024566591,
0.11469786614179611,
-0.10783757269382477,
0.08876500278711319,
-0.12757131457328796,
-0.08225731551647186,
-0.022692618891596794,
0.03500136360526085,
0.15366049110889435,
-0.00076050974894315,
0.029379257932305336,
0.004972926340997219,
-0.07623390108346939,
0.07000384479761124,
0.0011519676772877574,
-0.18585644662380219,
0.02521953359246254,
0.034064047038555145,
-0.052420102059841156,
0.1444118469953537,
0.017661266028881073,
0.04217566177248955,
0.07933498919010162,
0.016833707690238953,
-0.07138318568468094,
0.12775740027427673,
0.009597206488251686,
-0.04876182600855827,
0.034084502607584,
-0.07205130904912949,
-0.01759001612663269,
-0.03189719840884209,
0.07615228742361069,
-0.10717002302408218,
0.046764932572841644,
0.06091400235891342,
-0.10485002398490906,
-0.031493403017520905,
0.03284086287021637,
-0.1001647487282753,
0.06539298593997955,
-0.007153247017413378,
-0.04435579851269722,
0.007201276253908873,
-0.04304330423474312,
0.009860191494226456,
-0.01959502324461937,
-0.12916697561740875,
-0.02507382072508335,
-0.09515261650085449,
-0.065756656229496,
0.113176129758358,
0.039058465510606766,
-0.18142549693584442,
-0.007861214689910412,
-0.08102959394454956,
0.07369863986968994,
-0.17520920932292938,
0.04457900673151016,
0.1597604900598526,
-0.005688674747943878,
-0.011852195486426353,
-0.0821712538599968,
0.0479925163090229,
0.06317367404699326,
-0.028669022023677826,
-0.0854073166847229
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# perioli_vgm_v8.4.2
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0127
- Precision: 0.9343
- Recall: 0.8993
- F1: 0.9165
- Accuracy: 0.9975
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1700
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.33 | 100 | 0.0934 | 0.4189 | 0.1452 | 0.2157 | 0.9766 |
| No log | 0.66 | 200 | 0.0590 | 0.5528 | 0.3677 | 0.4416 | 0.9825 |
| No log | 0.99 | 300 | 0.0367 | 0.7254 | 0.6745 | 0.6990 | 0.9895 |
| No log | 1.32 | 400 | 0.0248 | 0.7958 | 0.7939 | 0.7948 | 0.9935 |
| 0.0816 | 1.64 | 500 | 0.0232 | 0.8329 | 0.7471 | 0.7877 | 0.9937 |
| 0.0816 | 1.97 | 600 | 0.0209 | 0.8023 | 0.8173 | 0.8097 | 0.9942 |
| 0.0816 | 2.3 | 700 | 0.0229 | 0.7878 | 0.8173 | 0.8023 | 0.9936 |
| 0.0816 | 2.63 | 800 | 0.0224 | 0.7778 | 0.8197 | 0.7982 | 0.9934 |
| 0.0816 | 2.96 | 900 | 0.0158 | 0.8960 | 0.8478 | 0.8712 | 0.9963 |
| 0.0142 | 3.29 | 1000 | 0.0144 | 0.8900 | 0.8712 | 0.8805 | 0.9969 |
| 0.0142 | 3.62 | 1100 | 0.0155 | 0.8456 | 0.8595 | 0.8525 | 0.9958 |
| 0.0142 | 3.95 | 1200 | 0.0139 | 0.9121 | 0.8993 | 0.9057 | 0.9971 |
| 0.0142 | 4.28 | 1300 | 0.0134 | 0.9126 | 0.8806 | 0.8963 | 0.9973 |
| 0.0142 | 4.61 | 1400 | 0.0128 | 0.9185 | 0.8970 | 0.9076 | 0.9973 |
| 0.006 | 4.93 | 1500 | 0.0122 | 0.9165 | 0.8993 | 0.9078 | 0.9974 |
| 0.006 | 5.26 | 1600 | 0.0126 | 0.9251 | 0.8970 | 0.9108 | 0.9974 |
| 0.006 | 5.59 | 1700 | 0.0127 | 0.9343 | 0.8993 | 0.9165 | 0.9975 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 2.2.2
- Tokenizers 0.13.3
| {"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["sroie"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "perioli_vgm_v8.4.2", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.9343065693430657, "name": "Precision"}, {"type": "recall", "value": 0.8992974238875878, "name": "Recall"}, {"type": "f1", "value": 0.9164677804295943, "name": "F1"}, {"type": "accuracy", "value": 0.9975032101583678, "name": "Accuracy"}]}]}]} | token-classification | atatavana/perioli_vgm_v8.4.2 | [
"transformers",
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"generated_from_trainer",
"dataset:sroie",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T00:00:00+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| perioli\_vgm\_v8.4.2
====================
This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0127
* Precision: 0.9343
* Recall: 0.8993
* F1: 0.9165
* Accuracy: 0.9975
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1700
### Training results
### Framework versions
* Transformers 4.28.0
* Pytorch 2.1.0+cu121
* Datasets 2.2.2
* Tokenizers 0.13.3
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 1700",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.28.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.2.2\n* Tokenizers 0.13.3"
] | [
"TAGS\n#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 1700",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.28.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.2.2\n* Tokenizers 0.13.3"
] | [
76,
97,
4,
35
] | [
"passage: TAGS\n#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 1700### Training results### Framework versions\n\n\n* Transformers 4.28.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.2.2\n* Tokenizers 0.13.3"
] | [
-0.1165132075548172,
0.10597249865531921,
-0.0019520316272974014,
0.12319137156009674,
0.15714602172374725,
0.023390814661979675,
0.12868721783161163,
0.12458505481481552,
-0.0563255175948143,
0.02687874250113964,
0.13291920721530914,
0.13486045598983765,
0.0282298494130373,
0.1535216122865677,
-0.04592321068048477,
-0.24855442345142365,
-0.012420324608683586,
0.045835230499506,
-0.05617136508226395,
0.13598495721817017,
0.09772076457738876,
-0.12639836966991425,
0.0944003015756607,
0.008797839283943176,
-0.20716004073619843,
-0.01811758242547512,
0.02698434330523014,
-0.04852525144815445,
0.1493508219718933,
0.02991623803973198,
0.12977096438407898,
0.02364775910973549,
0.10122757405042648,
-0.15735383331775665,
0.012224623933434486,
0.048029813915491104,
0.00605202279984951,
0.10472234338521957,
0.03936590626835823,
0.01646006852388382,
0.05082528293132782,
-0.07225865870714188,
0.05735943093895912,
0.013437849469482899,
-0.13269872963428497,
-0.21272769570350647,
-0.09240495413541794,
0.05147380754351616,
0.09002520889043808,
0.08077801764011383,
0.0010925043607130647,
0.14964327216148376,
-0.06170888617634773,
0.07744140177965164,
0.16972465813159943,
-0.2889956533908844,
-0.07030642777681351,
0.06948539614677429,
0.023615319281816483,
0.059562452137470245,
-0.10287438333034515,
-0.0214206762611866,
0.037556447088718414,
0.03733541816473007,
0.14432528614997864,
-0.026991166174411774,
-0.02613627165555954,
0.013810443691909313,
-0.1363186240196228,
-0.03875809162855148,
0.153830423951149,
0.04916210100054741,
-0.03821761906147003,
-0.05195573717355728,
-0.045566800981760025,
-0.12866872549057007,
-0.03440840169787407,
-0.0038594501093029976,
0.037218913435935974,
-0.02649196982383728,
-0.10445668548345566,
-0.028410745784640312,
-0.10874900966882706,
-0.068268783390522,
-0.05903387442231178,
0.11269046366214752,
0.009850203059613705,
0.011184087023139,
-0.014972720295190811,
0.11711819469928741,
0.000499756948556751,
-0.12891851365566254,
0.03412466496229172,
0.020659344270825386,
-0.033493224531412125,
-0.06577789038419724,
-0.0408455953001976,
-0.04665093496441841,
-0.01462110411375761,
0.11798760294914246,
-0.013294023461639881,
0.024236278608441353,
0.024539638310670853,
0.05201911926269531,
-0.09830750524997711,
0.1934848129749298,
-0.0510324127972126,
-0.03367414325475693,
-0.0008214142289943993,
0.09021010249853134,
0.01910199224948883,
-0.018185345456004143,
-0.14833803474903107,
0.004933029878884554,
0.0857735127210617,
0.010403532534837723,
-0.04271897301077843,
0.05452720820903778,
-0.06432904303073883,
-0.041469279676675797,
0.06236148998141289,
-0.07342458516359329,
0.027799228206276894,
-0.01385791040956974,
-0.07542473077774048,
-0.050360824912786484,
0.004822086077183485,
0.029561296105384827,
0.014900276437401772,
0.11827272921800613,
-0.10860561579465866,
0.020673608407378197,
-0.08876469731330872,
-0.10463200509548187,
0.017017854377627373,
-0.09392787516117096,
0.01636771485209465,
-0.0976698100566864,
-0.1861819177865982,
-0.016002444550395012,
0.06050257012248039,
-0.03690081089735031,
-0.0731666088104248,
-0.0417947843670845,
-0.06212358921766281,
0.009940908290445805,
-0.015047998167574406,
0.12781250476837158,
-0.061730530112981796,
0.10470479726791382,
0.009824857115745544,
0.055416353046894073,
-0.05009499937295914,
0.04359566792845726,
-0.09580595791339874,
0.032704684883356094,
-0.1477450281381607,
0.032659683376550674,
-0.0357498936355114,
0.06730698049068451,
-0.11013822257518768,
-0.08658695966005325,
0.019085358828306198,
-0.012988276779651642,
0.06274760514497757,
0.08659254759550095,
-0.1851939558982849,
-0.07045532763004303,
0.14420713484287262,
-0.05743787810206413,
-0.12820619344711304,
0.13074542582035065,
-0.06537670642137527,
0.06059064716100693,
0.056505218148231506,
0.17428143322467804,
0.08782877027988434,
-0.08839546889066696,
0.022100375965237617,
0.00987119972705841,
0.06108599901199341,
-0.08440554887056351,
0.0989861860871315,
-0.0025462491903454065,
0.02928123064339161,
0.005561684258282185,
-0.06565381586551666,
0.06212238967418671,
-0.082799531519413,
-0.09215740859508514,
-0.011199037544429302,
-0.09309019893407822,
0.06012377515435219,
0.06377532333135605,
0.06455100327730179,
-0.08326989412307739,
-0.08726605027914047,
0.0630672499537468,
0.08725611865520477,
-0.044074080884456635,
0.02229885384440422,
-0.08052731305360794,
0.07796028256416321,
-0.07463788241147995,
-0.03027799353003502,
-0.1549467146396637,
-0.04595085233449936,
0.008738121949136257,
0.033367522060871124,
0.016619207337498665,
0.021894365549087524,
0.062072210013866425,
0.058541953563690186,
-0.06332527846097946,
-0.018253864720463753,
-0.02697407267987728,
0.00028501730412244797,
-0.12994793057441711,
-0.1934453248977661,
-0.05602720007300377,
-0.028994277119636536,
0.17420269548892975,
-0.21906808018684387,
0.035594481974840164,
0.001109401579014957,
0.09672154486179352,
0.03901401534676552,
-0.021681953221559525,
-0.037903860211372375,
0.0711505115032196,
-0.03493374213576317,
-0.057445306330919266,
0.07801154255867004,
0.019479641690850258,
-0.11456521600484848,
-0.014983057044446468,
-0.12310069054365158,
0.15792714059352875,
0.12159661948680878,
-0.07877414673566818,
-0.07386390119791031,
-0.03407735377550125,
-0.04507971182465553,
-0.029569527134299278,
-0.050338998436927795,
0.0059069618582725525,
0.13866370916366577,
0.014572342857718468,
0.16197432577610016,
-0.06827056407928467,
-0.047755468636751175,
0.026510506868362427,
-0.02870652824640274,
0.006937877740710974,
0.11072196811437607,
0.10394875705242157,
-0.11297428607940674,
0.15404577553272247,
0.16462641954421997,
-0.06267125904560089,
0.1346724033355713,
-0.031567927449941635,
-0.0664820745587349,
-0.0457468256354332,
-0.022751767188310623,
0.013955158181488514,
0.13740772008895874,
-0.08640334755182266,
-0.009073878638446331,
0.024946697056293488,
0.018167372792959213,
0.001731729949824512,
-0.2268887162208557,
-0.048268064856529236,
0.04151204228401184,
-0.03668302297592163,
-0.02775469422340393,
-0.014670983888208866,
-0.010690940544009209,
0.09666465222835541,
0.02974453754723072,
-0.09230415523052216,
0.05052775517106056,
0.0007106898701749742,
-0.07862670719623566,
0.19437897205352783,
-0.0663037821650505,
-0.15152668952941895,
-0.15272705256938934,
-0.08721968531608582,
-0.03441140800714493,
0.02024993672966957,
0.029190191999077797,
-0.062065426260232925,
-0.019383994862437248,
-0.07645303755998611,
-0.020821891725063324,
-0.01461486704647541,
0.018928006291389465,
0.00866005476564169,
-0.0016298231203109026,
0.0663374662399292,
-0.07752201706171036,
-0.004811584949493408,
-0.038586124777793884,
-0.02816024236381054,
0.036987125873565674,
0.014069506898522377,
0.11337785422801971,
0.15737344324588776,
-0.011600208468735218,
0.009734920226037502,
-0.045746348798274994,
0.21762800216674805,
-0.08839674293994904,
-0.020439259707927704,
0.1444741040468216,
-0.032297924160957336,
0.055944301187992096,
0.13715700805187225,
0.07270176708698273,
-0.08096623420715332,
0.0013971625594422221,
0.015139828436076641,
-0.04663737863302231,
-0.18936645984649658,
-0.04114469140768051,
-0.05845748633146286,
0.002064716536551714,
0.10217631608247757,
0.016472261399030685,
0.02033218927681446,
0.06836002320051193,
0.0351567268371582,
0.08127100765705109,
-0.03931700065732002,
0.07511388510465622,
0.10525166988372803,
0.042907897382974625,
0.1353534609079361,
-0.03432675823569298,
-0.048851754516363144,
0.03831908479332924,
0.035476166754961014,
0.203471839427948,
0.01429230347275734,
0.16364005208015442,
0.03867523744702339,
0.16127566993236542,
0.01006758026778698,
0.04522306099534035,
0.007991410791873932,
-0.03623126074671745,
-0.020945845171809196,
-0.030174709856510162,
-0.03164207562804222,
0.0330965593457222,
-0.014445261098444462,
0.039690591394901276,
-0.10219459235668182,
0.00864358153194189,
0.04448332637548447,
0.2339535355567932,
0.060959745198488235,
-0.34559160470962524,
-0.10193764418363571,
0.01011213380843401,
-0.020615315064787865,
-0.021694369614124298,
0.005051190499216318,
0.11524498462677002,
-0.09772008657455444,
0.01837536133825779,
-0.08476293832063675,
0.08983944356441498,
-0.06567179411649704,
0.03647064417600632,
0.08177351206541061,
0.07720474898815155,
-0.005695265717804432,
0.07281363010406494,
-0.25747957825660706,
0.2971262037754059,
0.016897324472665787,
0.05056970193982124,
-0.06452398002147675,
-0.01017259992659092,
0.028906190767884254,
0.07803358882665634,
0.08898045122623444,
-0.00664095301181078,
-0.0366218276321888,
-0.21911801397800446,
-0.0648498609662056,
0.00832293089479208,
0.06987731903791428,
-0.06319884955883026,
0.09200473129749298,
-0.03845886513590813,
0.003518753219395876,
0.06396953016519547,
0.014061895199120045,
-0.014691281132400036,
-0.09339455515146255,
0.0123517457395792,
0.024387627840042114,
-0.04426262900233269,
-0.06747911870479584,
-0.11110543459653854,
-0.09811043739318848,
0.14165467023849487,
-0.0352286659181118,
-0.02992328815162182,
-0.11591783910989761,
0.08490078151226044,
0.07158420979976654,
-0.08774170279502869,
0.028095660731196404,
0.002287184353917837,
0.10264036804437637,
0.015387613326311111,
-0.03703668713569641,
0.11191489547491074,
-0.06795964390039444,
-0.1640709489583969,
-0.07671213895082474,
0.11866312474012375,
0.013943483121693134,
0.07415607571601868,
0.0019117941847071052,
0.026255404576659203,
-0.031204847618937492,
-0.06452170759439468,
0.0504596084356308,
-0.027475256472826004,
0.06333968043327332,
-0.002429716754704714,
-0.024329641833901405,
0.031941451132297516,
-0.0588233508169651,
-0.04285973310470581,
0.17425264418125153,
0.2783372402191162,
-0.10473806411027908,
0.02550494112074375,
0.031456828117370605,
-0.058104559779167175,
-0.19266429543495178,
0.05530862882733345,
0.04696085304021835,
0.02257278561592102,
0.054644230753183365,
-0.1634131819009781,
0.07671432942152023,
0.09297188371419907,
-0.031009944155812263,
0.08894751220941544,
-0.29770129919052124,
-0.12582464516162872,
0.08974460512399673,
0.12286146730184555,
0.09849372506141663,
-0.12315022200345993,
-0.03475816175341606,
-0.016614515334367752,
-0.12213976681232452,
0.11292705684900284,
-0.06332333385944366,
0.11165187507867813,
-0.010991529561579227,
0.08606194704771042,
0.010619684122502804,
-0.05558444932103157,
0.13166064023971558,
0.00926920399069786,
0.0865422934293747,
-0.050969935953617096,
-0.04710594192147255,
0.056608572602272034,
-0.049580883234739304,
-0.005396123975515366,
-0.06305837631225586,
0.019633380696177483,
-0.1162482500076294,
-0.020464779809117317,
-0.0748581811785698,
0.018856722861528397,
-0.030366582795977592,
-0.07032668590545654,
-0.029409384354948997,
0.061282869428396225,
0.04302019625902176,
-0.016377758234739304,
0.1445532739162445,
0.009527098387479782,
0.13775165379047394,
0.11684580892324448,
0.08798136562108994,
-0.05714839696884155,
-0.06056362763047218,
-0.02007509581744671,
-0.03405044972896576,
0.055523209273815155,
-0.1455579251050949,
0.02706305868923664,
0.13157549500465393,
0.025556396692991257,
0.14405222237110138,
0.07225269824266434,
-0.029484622180461884,
0.01862383261322975,
0.06705799698829651,
-0.14650729298591614,
-0.09127482026815414,
-0.00969458557665348,
-0.0283964816480875,
-0.13846629858016968,
0.024204393848776817,
0.12056586891412735,
-0.0626775249838829,
-0.009223749861121178,
0.006996717769652605,
-0.0003222329542040825,
-0.04680943861603737,
0.17999140918254852,
0.06656351685523987,
0.057325318455696106,
-0.08651702105998993,
0.05636855959892273,
0.06821127235889435,
-0.06654525548219681,
-0.008234587498009205,
0.03717451170086861,
-0.09918038547039032,
-0.04080740734934807,
0.008421685546636581,
0.1403830498456955,
-0.0871654525399208,
-0.030201079323887825,
-0.14547571539878845,
-0.099268838763237,
0.06115695834159851,
0.1443667709827423,
0.10366900265216827,
0.006922292523086071,
-0.04803794249892235,
0.0032102265395224094,
-0.11579860001802444,
0.09916761517524719,
0.03996140509843826,
0.0777585506439209,
-0.15149009227752686,
0.1633097529411316,
-0.0132077531889081,
0.051738180220127106,
-0.01970411092042923,
0.030374448746442795,
-0.10151221603155136,
0.01576559990644455,
-0.105872742831707,
-0.025845026597380638,
-0.03519893065094948,
-0.0014874377520754933,
-0.004017881583422422,
-0.06170635670423508,
-0.04690584912896156,
0.0028580091893672943,
-0.11468727141618729,
-0.020537059754133224,
0.039287690073251724,
0.052464865148067474,
-0.10088138282299042,
-0.04056623950600624,
0.027180489152669907,
-0.059053175151348114,
0.07486223429441452,
0.0036358037032186985,
0.034156251698732376,
0.033830877393484116,
-0.0950227901339531,
0.014940885826945305,
0.0343322716653347,
0.01657162606716156,
0.07220789045095444,
-0.09338527917861938,
-0.009345118887722492,
-0.020273422822356224,
0.03554852679371834,
0.030959950760006905,
0.08663485199213028,
-0.1262335330247879,
0.0033470632042735815,
-0.005224904045462608,
-0.06463352590799332,
-0.06258470565080643,
0.049794819205999374,
0.06877264380455017,
0.0464407354593277,
0.19835366308689117,
-0.0685298889875412,
0.03858978673815727,
-0.20185071229934692,
-0.0032645633909851313,
-0.014111681841313839,
-0.10567241162061691,
-0.10218694806098938,
-0.0711648017168045,
0.0598459392786026,
-0.060374826192855835,
0.1153935045003891,
0.033430315554142,
0.06434463709592819,
0.04026041924953461,
-0.008527813479304314,
0.038018614053726196,
0.016542142257094383,
0.17760157585144043,
0.03403298556804657,
-0.0351828895509243,
0.07094263285398483,
0.042170073837041855,
0.08416607975959778,
0.12063754349946976,
0.17473256587982178,
0.13390296697616577,
0.014307533390820026,
0.07447614520788193,
0.04670679569244385,
-0.04642423614859581,
-0.1897651106119156,
0.017579246312379837,
-0.04330334812402725,
0.10068013519048691,
-0.025978008285164833,
0.19878289103507996,
0.0767318457365036,
-0.17974528670310974,
0.02080698125064373,
-0.06107040494680405,
-0.08257361501455307,
-0.09700522571802139,
-0.08617841452360153,
-0.07916542887687683,
-0.11669672280550003,
-0.00042280388879589736,
-0.09729179739952087,
0.006519170477986336,
0.14736558496952057,
-0.002920211525633931,
-0.015093962661921978,
0.12601333856582642,
-0.0031815606635063887,
0.02679668366909027,
0.0554468035697937,
0.011789611540734768,
-0.013236981816589832,
-0.1040344163775444,
-0.06578290462493896,
-0.013315732590854168,
-0.029384462162852287,
0.03328058123588562,
-0.07589897513389587,
-0.022294363006949425,
0.022936902940273285,
-0.008211367763578892,
-0.11150160431861877,
0.005896851420402527,
0.02192428708076477,
0.06309645622968674,
0.040776271373033524,
0.00933629646897316,
0.031505193561315536,
-0.014290533028542995,
0.2287818044424057,
-0.07566767185926437,
-0.04758008196949959,
-0.11735547333955765,
0.24673226475715637,
0.0035863365046679974,
-0.025984149426221848,
0.02533208578824997,
-0.07378644496202469,
0.02835659496486187,
0.22944121062755585,
0.1949862390756607,
-0.1219710260629654,
-0.007102805655449629,
0.014369635842740536,
-0.00910113099962473,
-0.028047695755958557,
0.11576266586780548,
0.08496968448162079,
0.014023649506270885,
-0.09555067867040634,
-0.04835996404290199,
-0.06589135527610779,
-0.018000010401010513,
-0.010035109706223011,
0.05440864339470863,
0.035478632897138596,
0.01620304398238659,
-0.055793944746255875,
0.06584981083869934,
-0.04679090157151222,
-0.10344558954238892,
0.06857932358980179,
-0.21518279612064362,
-0.16575740277767181,
-0.014180092141032219,
0.07901797443628311,
-0.004480632487684488,
0.061046261340379715,
-0.03699149563908577,
0.020519902929663658,
0.05954083055257797,
-0.020762091502547264,
-0.06562278419733047,
-0.07635336369276047,
0.10639318078756332,
-0.07777900993824005,
0.2169117033481598,
-0.05881500244140625,
0.06402305513620377,
0.12370072305202484,
0.060438528656959534,
-0.08236750215291977,
0.04437360167503357,
0.05938475579023361,
-0.038878895342350006,
0.031247150152921677,
0.09470835328102112,
-0.03580373898148537,
0.11713137477636337,
0.054360270500183105,
-0.13559983670711517,
0.018241677433252335,
-0.08353396505117416,
-0.054305218160152435,
-0.04665365815162659,
-0.03802964836359024,
-0.047818221151828766,
0.1521737277507782,
0.20158375799655914,
-0.03687775135040283,
-0.019587581977248192,
-0.057963937520980835,
0.0003401869907975197,
0.07773618400096893,
0.03347797691822052,
-0.0741092711687088,
-0.20496414601802826,
0.0005002533434890211,
0.04280778393149376,
-0.016836320981383324,
-0.24179786443710327,
-0.0937645435333252,
0.0017334844451397657,
-0.0667029395699501,
-0.0709085613489151,
0.10269737988710403,
0.07794422656297684,
0.04918931424617767,
-0.06527391076087952,
-0.03597431629896164,
-0.06458111107349396,
0.12903977930545807,
-0.1459769904613495,
-0.08814410865306854
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SMIDS_3x_beit_large_Adamax_lr0001_fold3
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0371
- Accuracy: 0.9083
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2567 | 1.0 | 450 | 0.2701 | 0.9083 |
| 0.1294 | 2.0 | 900 | 0.3454 | 0.9033 |
| 0.151 | 3.0 | 1350 | 0.4477 | 0.9067 |
| 0.0465 | 4.0 | 1800 | 0.5011 | 0.9117 |
| 0.0072 | 5.0 | 2250 | 0.6717 | 0.9 |
| 0.0539 | 6.0 | 2700 | 0.6596 | 0.9167 |
| 0.0 | 7.0 | 3150 | 0.7166 | 0.9117 |
| 0.0533 | 8.0 | 3600 | 0.6612 | 0.91 |
| 0.0005 | 9.0 | 4050 | 0.7994 | 0.9067 |
| 0.0011 | 10.0 | 4500 | 0.8564 | 0.9067 |
| 0.0 | 11.0 | 4950 | 0.7592 | 0.915 |
| 0.0007 | 12.0 | 5400 | 0.8444 | 0.9033 |
| 0.0135 | 13.0 | 5850 | 0.7348 | 0.9167 |
| 0.0002 | 14.0 | 6300 | 0.7821 | 0.9117 |
| 0.0 | 15.0 | 6750 | 0.8898 | 0.9167 |
| 0.0 | 16.0 | 7200 | 0.8152 | 0.9167 |
| 0.0 | 17.0 | 7650 | 0.7922 | 0.92 |
| 0.0 | 18.0 | 8100 | 0.8739 | 0.9183 |
| 0.0017 | 19.0 | 8550 | 0.8317 | 0.9167 |
| 0.0 | 20.0 | 9000 | 0.8336 | 0.9067 |
| 0.0 | 21.0 | 9450 | 0.8413 | 0.915 |
| 0.0 | 22.0 | 9900 | 0.8954 | 0.915 |
| 0.0 | 23.0 | 10350 | 0.7872 | 0.9167 |
| 0.0 | 24.0 | 10800 | 0.7808 | 0.9217 |
| 0.0 | 25.0 | 11250 | 0.8082 | 0.9183 |
| 0.0 | 26.0 | 11700 | 0.8344 | 0.9167 |
| 0.0 | 27.0 | 12150 | 0.8127 | 0.9233 |
| 0.0 | 28.0 | 12600 | 0.8252 | 0.9217 |
| 0.0 | 29.0 | 13050 | 0.8478 | 0.925 |
| 0.0 | 30.0 | 13500 | 0.8276 | 0.925 |
| 0.0 | 31.0 | 13950 | 0.8327 | 0.9233 |
| 0.0 | 32.0 | 14400 | 0.9020 | 0.9183 |
| 0.0 | 33.0 | 14850 | 0.8907 | 0.9183 |
| 0.0 | 34.0 | 15300 | 0.8860 | 0.9167 |
| 0.0 | 35.0 | 15750 | 0.8736 | 0.9183 |
| 0.0 | 36.0 | 16200 | 0.8914 | 0.9183 |
| 0.0 | 37.0 | 16650 | 0.9275 | 0.9233 |
| 0.0 | 38.0 | 17100 | 0.9066 | 0.92 |
| 0.0 | 39.0 | 17550 | 0.9662 | 0.9167 |
| 0.0 | 40.0 | 18000 | 0.9269 | 0.9183 |
| 0.0 | 41.0 | 18450 | 0.9781 | 0.9167 |
| 0.0 | 42.0 | 18900 | 0.9872 | 0.9183 |
| 0.0 | 43.0 | 19350 | 1.0461 | 0.91 |
| 0.0 | 44.0 | 19800 | 1.0426 | 0.91 |
| 0.0 | 45.0 | 20250 | 1.0523 | 0.91 |
| 0.0 | 46.0 | 20700 | 1.0475 | 0.91 |
| 0.0 | 47.0 | 21150 | 1.0421 | 0.91 |
| 0.0 | 48.0 | 21600 | 1.0396 | 0.9083 |
| 0.0 | 49.0 | 22050 | 1.0382 | 0.9083 |
| 0.0 | 50.0 | 22500 | 1.0371 | 0.9083 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_3x_beit_large_Adamax_lr0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9083333333333333, "name": "Accuracy"}]}]}]} | image-classification | onizukal/SMIDS_3x_beit_large_Adamax_lr0001_fold3 | [
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-large-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T00:04:37+00:00 | [] | [] | TAGS
#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| SMIDS\_3x\_beit\_large\_Adamax\_lr0001\_fold3
=============================================
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0371
* Accuracy: 0.9083
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.2
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
"TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
81,
115,
4,
30
] | [
"passage: TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
-0.12968555092811584,
0.17251011729240417,
-0.0023243443574756384,
0.1362919956445694,
0.1120586097240448,
0.015268749557435513,
0.14003369212150574,
0.16890837252140045,
-0.08239254355430603,
0.046998485922813416,
0.14023225009441376,
0.13628867268562317,
0.046756189316511154,
0.19432850182056427,
-0.052493587136268616,
-0.26022207736968994,
0.04113864526152611,
0.032812196761369705,
-0.020441479980945587,
0.1235608458518982,
0.09337224811315536,
-0.13087525963783264,
0.11667836457490921,
0.0301132183521986,
-0.20004093647003174,
-0.036873914301395416,
-0.007245634216815233,
-0.06722474098205566,
0.10533155500888824,
-0.0034045001957565546,
0.0691065788269043,
0.03768180310726166,
0.08387713134288788,
-0.13018712401390076,
0.002076903358101845,
0.042768821120262146,
0.0062860166653990746,
0.10383369028568268,
0.054196570068597794,
-0.015545758418738842,
0.0701410248875618,
-0.06851525604724884,
0.0672622099518776,
0.009240911342203617,
-0.11321496963500977,
-0.2700493633747101,
-0.10203396528959274,
0.07240316271781921,
0.08221714198589325,
0.06822962313890457,
0.008172801695764065,
0.16417047381401062,
-0.014714903198182583,
0.10454332083463669,
0.23100516200065613,
-0.26415953040122986,
-0.05532161891460419,
0.029576225206255913,
0.015004046261310577,
0.06490366160869598,
-0.10617698729038239,
-0.01859438419342041,
0.020827138796448708,
0.04436356946825981,
0.1411312073469162,
-0.010821618139743805,
-0.028378209099173546,
-0.021572042256593704,
-0.10856294631958008,
-0.08875563740730286,
0.18566860258579254,
0.05809066444635391,
-0.048288628458976746,
-0.07735078781843185,
-0.07127056270837784,
-0.17220835387706757,
-0.041861895471811295,
0.009548050351440907,
0.041730549186468124,
-0.04684269055724144,
-0.10686429589986801,
-0.031055882573127747,
-0.078252874314785,
-0.051669858396053314,
-0.023303553462028503,
0.13525931537151337,
0.03357808664441109,
0.05729198828339577,
-0.03593141585588455,
0.09915280342102051,
0.006841922644525766,
-0.17527513206005096,
-0.028045548126101494,
-0.0016165260458365083,
0.01563161052763462,
-0.020048104226589203,
-0.03057136945426464,
-0.06562764942646027,
-0.0016239769756793976,
0.149040088057518,
-0.06106079742312431,
0.06079873815178871,
-0.0069216229021549225,
0.04031313583254814,
-0.0486484132707119,
0.18668954074382782,
-0.028643600642681122,
-0.016713637858629227,
0.02057800441980362,
0.08857519924640656,
0.06818821281194687,
-0.03644402697682381,
-0.12566283345222473,
0.03087625838816166,
0.1283741444349289,
0.0027549222577363253,
-0.021953243762254715,
0.053039632737636566,
-0.06444176286458969,
-0.05842158570885658,
0.09141092747449875,
-0.08884678035974503,
0.03514961525797844,
-0.01055920124053955,
-0.08416686952114105,
-0.06807748228311539,
0.02709859050810337,
0.018840007483959198,
-0.00014874596672598273,
0.07201956957578659,
-0.09116632491350174,
0.015490563586354256,
-0.06551176309585571,
-0.10091431438922882,
0.01564670167863369,
-0.11040772497653961,
0.012323775328695774,
-0.09688954800367355,
-0.1969451904296875,
0.006960712838917971,
0.07738039642572403,
-0.05607226490974426,
-0.06792453676462173,
-0.03661259636282921,
-0.07637017965316772,
0.04143770784139633,
-0.01186586357653141,
0.07317496836185455,
-0.07456725090742111,
0.09119440615177155,
0.02237127535045147,
0.08760105073451996,
-0.056383248418569565,
0.04597126320004463,
-0.10241573303937912,
0.04992371052503586,
-0.19877833127975464,
0.07988634705543518,
-0.049189720302820206,
0.06190093979239464,
-0.09581396728754044,
-0.10568851977586746,
0.033553607761859894,
-0.04994693025946617,
0.068512924015522,
0.09739063680171967,
-0.17317676544189453,
-0.05787286534905434,
0.13517500460147858,
-0.09691634029150009,
-0.14840039610862732,
0.10115666687488556,
-0.05093328654766083,
0.019768450409173965,
0.04739697277545929,
0.21447287499904633,
0.062935970723629,
-0.0910891741514206,
-0.025994082912802696,
-0.03333966061472893,
0.044677652418613434,
-0.06483115255832672,
0.101903036236763,
0.027484174817800522,
0.0531504862010479,
0.02367355115711689,
-0.03332329913973808,
0.03818739578127861,
-0.08385370671749115,
-0.10085898637771606,
-0.05038752406835556,
-0.08557170629501343,
0.039683446288108826,
0.05594057962298393,
0.059847064316272736,
-0.10873348265886307,
-0.09023979306221008,
0.041734639555215836,
0.09406744688749313,
-0.07396076619625092,
0.02903648279607296,
-0.0904788002371788,
0.11622294038534164,
-0.08363831788301468,
-0.02404896728694439,
-0.17903628945350647,
-0.0417308546602726,
0.04055763781070709,
-0.01668366603553295,
-0.006775525398552418,
-0.0494389571249485,
0.07092705368995667,
0.087753064930439,
-0.05281677842140198,
-0.052284084260463715,
-0.05530114471912384,
0.008562305010855198,
-0.11059658974409103,
-0.1778055727481842,
-0.080107681453228,
-0.03797448053956032,
0.15019145607948303,
-0.15246915817260742,
0.0224970243871212,
0.0616903156042099,
0.12470164895057678,
0.05992257222533226,
-0.0469760037958622,
-0.007631834130734205,
0.0217386856675148,
-0.05561714619398117,
-0.0865136981010437,
0.05727535858750343,
0.035165008157491684,
-0.07172347605228424,
-0.019373787567019463,
-0.10040221363306046,
0.15015454590320587,
0.13185308873653412,
-0.0021352346520870924,
-0.045590728521347046,
-0.012053865939378738,
-0.06572475284337997,
-0.030354894697666168,
-0.04096601903438568,
0.01860888861119747,
0.1020345464348793,
0.017360014840960503,
0.14407898485660553,
-0.09213681519031525,
-0.037007302045822144,
0.053231216967105865,
-0.028658904135227203,
-0.03313332051038742,
0.0737093985080719,
0.021478038281202316,
-0.14289474487304688,
0.1502111405134201,
0.14915579557418823,
-0.04949729144573212,
0.12371271848678589,
-0.03663388267159462,
-0.06141006201505661,
-0.04545919969677925,
-0.03777514770627022,
0.01429951936006546,
0.1407921016216278,
-0.08363746106624603,
-0.006257671397179365,
0.05626929551362991,
0.018998416140675545,
-0.007220869418233633,
-0.1808812916278839,
0.0005758196348324418,
0.03530525416135788,
-0.04614398628473282,
-0.022574707865715027,
-0.014720434322953224,
0.000520858506206423,
0.09188775718212128,
0.02001834660768509,
-0.07113038748502731,
0.05185159295797348,
0.010694033466279507,
-0.056145116686820984,
0.16459684073925018,
-0.07884351164102554,
-0.19753409922122955,
-0.11793240904808044,
-0.08745986223220825,
-0.10736268758773804,
0.013000035658478737,
0.067270427942276,
-0.050670597702264786,
-0.04932181537151337,
-0.1026671901345253,
-0.044550344347953796,
0.021845674142241478,
0.024347107857465744,
0.053595975041389465,
-0.00796813890337944,
0.08411940932273865,
-0.09194666892290115,
-0.03317512199282646,
-0.014813165180385113,
0.01894056238234043,
0.0670066773891449,
0.01914203353226185,
0.11091019958257675,
0.08160436898469925,
-0.0286879725754261,
0.05666669085621834,
-0.01685662567615509,
0.26526889204978943,
-0.06748054921627045,
-0.006749235559254885,
0.1391732543706894,
-0.013490693643689156,
0.0842166393995285,
0.12729591131210327,
0.04176322743296623,
-0.0955888107419014,
-0.01310211792588234,
-0.0005005627172067761,
-0.05257550999522209,
-0.1536482274532318,
-0.04132819548249245,
-0.04548354819417,
-0.0018228141125291586,
0.13951772451400757,
0.038064174354076385,
0.02505229413509369,
0.07843583822250366,
0.020602436736226082,
0.05678323283791542,
-0.0175874512642622,
0.10429482907056808,
0.08156884461641312,
0.06449971348047256,
0.13376133143901825,
-0.036523740738630295,
-0.019790813326835632,
0.05638623237609863,
0.042081572115421295,
0.20467498898506165,
-0.025362396612763405,
0.14717818796634674,
0.026553483679890633,
0.19327539205551147,
0.017808275297284126,
0.07306244969367981,
-0.014873637817800045,
0.0007499073399230838,
-0.019323905929923058,
-0.04713669419288635,
-0.0638502836227417,
0.03312433883547783,
-0.016851995140314102,
0.05682634562253952,
-0.09328699111938477,
0.03906902298331261,
0.05959288775920868,
0.30634987354278564,
0.0654144361615181,
-0.4125381410121918,
-0.09821337461471558,
0.012344546616077423,
0.0008716733427718282,
-0.05509618669748306,
-0.007402430288493633,
0.0980701595544815,
-0.09973937273025513,
0.0819711834192276,
-0.09416680037975311,
0.08507230132818222,
-0.0846736952662468,
0.020382488146424294,
0.07683569937944412,
0.055889930576086044,
0.012921135872602463,
0.05964238941669464,
-0.21880683302879333,
0.2499670386314392,
0.01837102696299553,
0.04415145888924599,
-0.08875706046819687,
0.009965145029127598,
0.03320525959134102,
0.05923061817884445,
0.08590700477361679,
0.0061045982874929905,
-0.09025654941797256,
-0.18889141082763672,
-0.12562422454357147,
0.000394518458051607,
0.06176565960049629,
-0.03729195147752762,
0.09444484859704971,
-0.018019067123532295,
-0.012201022356748581,
0.02127370797097683,
0.0009904175531119108,
-0.035084888339042664,
-0.10356581956148148,
0.02010609768331051,
0.03430531173944473,
-0.011726552620530128,
-0.06489048153162003,
-0.11480618268251419,
-0.035277001559734344,
0.16168422996997833,
0.05518770217895508,
-0.07543513178825378,
-0.14076673984527588,
0.0721859410405159,
0.0775376707315445,
-0.08563373237848282,
0.03936640918254852,
-0.016648126766085625,
0.14995604753494263,
0.020845195278525352,
-0.0889848992228508,
0.10199198871850967,
-0.05838112160563469,
-0.17863209545612335,
-0.04141612723469734,
0.09901762008666992,
0.007052883040159941,
0.05273612216114998,
0.004226623103022575,
0.06022334843873978,
-0.03518751636147499,
-0.05844981223344803,
0.06672939658164978,
-0.007545650005340576,
0.10645230114459991,
-0.014578265137970448,
0.008669902570545673,
0.028680432587862015,
-0.046410609036684036,
0.00012374592188280076,
0.1686571091413498,
0.24114695191383362,
-0.10427109152078629,
0.060499124228954315,
0.03038850799202919,
-0.030858036130666733,
-0.18259160220623016,
0.01086394116282463,
0.07622820883989334,
-0.00013084696547593921,
0.04143662750720978,
-0.1601918637752533,
0.05532059073448181,
0.10498367995023727,
-0.043228019028902054,
0.08107142895460129,
-0.27694207429885864,
-0.1185181736946106,
0.09238865971565247,
0.13856256008148193,
0.06877914071083069,
-0.13106170296669006,
-0.043299052864313126,
-0.041688259690999985,
-0.17338812351226807,
0.13653364777565002,
-0.057192787528038025,
0.1145344004034996,
-0.039500072598457336,
0.08082033693790436,
0.014952262863516808,
-0.056017596274614334,
0.14574900269508362,
0.0056154001504182816,
0.08686088770627975,
-0.07213473320007324,
-0.0020430299919098616,
0.10663212835788727,
-0.10254329442977905,
0.07232339680194855,
-0.08735590428113937,
0.0618043914437294,
-0.10790637135505676,
-0.003900582902133465,
-0.07402003556489944,
0.013697824440896511,
-0.01366274245083332,
-0.04917207732796669,
-0.04516566917300224,
0.03515308350324631,
0.0627121776342392,
-0.01822420209646225,
0.20940853655338287,
0.06430324167013168,
0.08635561168193817,
0.1727360188961029,
0.054769597947597504,
-0.10558480769395828,
-0.09403572231531143,
-0.043973103165626526,
-0.029537810012698174,
0.05986782908439636,
-0.1372820883989334,
0.0528247207403183,
0.11996810883283615,
0.013451187871396542,
0.12858225405216217,
0.055897701531648636,
-0.030677761882543564,
0.03560479357838631,
0.062153734266757965,
-0.17216050624847412,
-0.08662130683660507,
-0.009840693324804306,
0.030872231349349022,
-0.13055209815502167,
0.0458756685256958,
0.12116101384162903,
-0.05953402817249298,
-0.015017039142549038,
-0.004467411432415247,
0.03673877567052841,
-0.00978675577789545,
0.15920081734657288,
0.048089753836393356,
0.055168475955724716,
-0.11802823096513748,
0.11332250386476517,
0.05730176344513893,
-0.07302459329366684,
0.03206014260649681,
0.05020790174603462,
-0.1039617657661438,
-0.021727759391069412,
0.03114185482263565,
0.15037071704864502,
-0.06283780187368393,
-0.045329563319683075,
-0.1358855813741684,
-0.09226331859827042,
0.06643375009298325,
0.07981554418802261,
0.09349396824836731,
0.016502337530255318,
-0.03525979816913605,
-0.013309485279023647,
-0.10845191776752472,
0.11000601947307587,
0.04338005557656288,
0.09121100604534149,
-0.17974577844142914,
0.05434896796941757,
-0.001805671607144177,
0.07240304350852966,
-0.02173563651740551,
-0.00018242778605781496,
-0.08797106891870499,
0.0035262287128716707,
-0.10818753391504288,
0.024682866409420967,
-0.052850391715765,
0.006376184988766909,
-0.020511267706751823,
-0.05819518491625786,
-0.06372886151075363,
0.024663057178258896,
-0.1193968653678894,
-0.05304655060172081,
0.02193489298224449,
0.03176874667406082,
-0.11983832716941833,
-0.04395153746008873,
0.02043171599507332,
-0.08966860175132751,
0.09786758571863174,
0.06017395853996277,
-0.00797541905194521,
0.007467431016266346,
0.0038150406908243895,
-0.022212069481611252,
0.06630469858646393,
0.0074848150834441185,
0.08584009110927582,
-0.11553936451673508,
-0.022143544629216194,
0.016299601644277573,
-0.004447818733751774,
0.018147116526961327,
0.1585858017206192,
-0.12092386186122894,
0.00018621055642142892,
-0.014765054918825626,
-0.06592588871717453,
-0.06358986347913742,
0.0692417323589325,
0.10919524729251862,
0.02367839775979519,
0.2122299075126648,
-0.054594267159700394,
0.015877852216362953,
-0.21000300347805023,
-0.011462570168077946,
0.005311926826834679,
-0.13887609541416168,
-0.10537440329790115,
-0.032787878066301346,
0.0637630894780159,
-0.07039659470319748,
0.1177176982164383,
0.03537357598543167,
0.020886771380901337,
0.02911887876689434,
0.024869181215763092,
-0.002677198965102434,
0.013766518794000149,
0.1633930504322052,
0.014011929742991924,
-0.02872646041214466,
0.1283825933933258,
0.029096294194459915,
0.09337089955806732,
0.11805824935436249,
0.1763046532869339,
0.11451227962970734,
0.0477789007127285,
0.09043081104755402,
0.0520024336874485,
-0.02513159066438675,
-0.22147811949253082,
0.036259569227695465,
-0.039764102548360825,
0.1483127623796463,
-0.0033327124547213316,
0.15980194509029388,
0.09223487228155136,
-0.18392090499401093,
0.040660299360752106,
-0.037005215883255005,
-0.07937940210103989,
-0.08421849459409714,
-0.12178675830364227,
-0.1033017709851265,
-0.1509413868188858,
0.0028559700585901737,
-0.10428426414728165,
0.022927863523364067,
0.11217869818210602,
-0.008710348978638649,
-0.010019375011324883,
0.11695955693721771,
-0.026584560051560402,
0.026202335953712463,
0.03870072960853577,
0.00616151699796319,
-0.05987776443362236,
-0.04411191865801811,
-0.08036603778600693,
0.014018801040947437,
0.03200533241033554,
0.055842287838459015,
-0.03226681798696518,
-0.007200593128800392,
0.03782269358634949,
-0.009845683351159096,
-0.12363012880086899,
0.013544945046305656,
0.004753641318529844,
0.05189259722828865,
0.0008605605689808726,
0.01290043629705906,
0.03187544271349907,
-0.015199882909655571,
0.193119078874588,
-0.07321906089782715,
-0.02744952403008938,
-0.12274995446205139,
0.17869888246059418,
0.0023205638863146305,
-0.049724213778972626,
0.05292708799242973,
-0.09127075970172882,
-0.020290102809667587,
0.1547212302684784,
0.18941837549209595,
-0.07176556438207626,
-0.01638839766383171,
-0.017501909285783768,
-0.01388427522033453,
-0.022741587832570076,
0.09889717400074005,
0.09887372702360153,
-0.007504772394895554,
-0.07518953084945679,
-0.028498217463493347,
-0.06611054390668869,
-0.03444022685289383,
-0.03838160261511803,
0.06909165531396866,
-0.004605968948453665,
0.007089514285326004,
-0.0751754567027092,
0.04334408789873123,
-0.02207781746983528,
-0.060899440199136734,
0.06262887269258499,
-0.21282166242599487,
-0.17796695232391357,
0.006926008500158787,
0.07579630613327026,
0.0016649233875796199,
0.04621230810880661,
-0.010005760937929153,
0.018681904301047325,
0.07549776136875153,
-0.022177988663315773,
-0.0866948589682579,
-0.09604813903570175,
0.1083223819732666,
-0.1344224065542221,
0.25299492478370667,
-0.03893125429749489,
0.035907670855522156,
0.12175600975751877,
0.041717030107975006,
-0.13353091478347778,
0.033571965992450714,
0.03969275578856468,
-0.03212675452232361,
0.005746500100940466,
0.14248594641685486,
-0.037242501974105835,
0.07988674938678741,
0.04599026218056679,
-0.10243327170610428,
-0.039464809000492096,
-0.04960913211107254,
-0.011240639723837376,
-0.024744588881731033,
-0.05439573898911476,
-0.03649099916219711,
0.13208730518817902,
0.17168967425823212,
-0.04232889041304588,
-0.023784559220075607,
-0.06460724771022797,
0.030773790553212166,
0.0774260088801384,
-0.033050306141376495,
-0.05197038874030113,
-0.23585109412670135,
0.0024181774351745844,
0.05249672383069992,
-0.013345940038561821,
-0.20789918303489685,
-0.11062979698181152,
0.006115853786468506,
-0.05795856565237045,
-0.07630864530801773,
0.09230074286460876,
0.06326484680175781,
0.035358402878046036,
-0.06319575011730194,
0.03810267895460129,
-0.07874377071857452,
0.1419457346200943,
-0.1448507308959961,
-0.07860494405031204
] |
null | null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.8.2 | {"library_name": "peft", "base_model": "mistralai/Mixtral-8x7B-Instruct-v0.1"} | null | antonvo/mixtral-select-v1 | [
"peft",
"safetensors",
"mixtral",
"arxiv:1910.09700",
"base_model:mistralai/Mixtral-8x7B-Instruct-v0.1",
"4-bit",
"region:us"
] | 2024-02-09T00:06:12+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #safetensors #mixtral #arxiv-1910.09700 #base_model-mistralai/Mixtral-8x7B-Instruct-v0.1 #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
### Framework versions
- PEFT 0.8.2 | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact",
"### Framework versions\n\n- PEFT 0.8.2"
] | [
"TAGS\n#peft #safetensors #mixtral #arxiv-1910.09700 #base_model-mistralai/Mixtral-8x7B-Instruct-v0.1 #4-bit #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact",
"### Framework versions\n\n- PEFT 0.8.2"
] | [
51,
6,
3,
54,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4,
11
] | [
"passage: TAGS\n#peft #safetensors #mixtral #arxiv-1910.09700 #base_model-mistralai/Mixtral-8x7B-Instruct-v0.1 #4-bit #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact### Framework versions\n\n- PEFT 0.8.2"
] | [
-0.10251504927873611,
0.20373693108558655,
-0.0029806187376379967,
0.028733160346746445,
0.09497389197349548,
0.01764267310500145,
0.057038694620132446,
0.1287032514810562,
0.0128909507766366,
0.13016240298748016,
0.05509498715400696,
0.10375592857599258,
0.11366971582174301,
0.24187664687633514,
0.00406277971342206,
-0.19185124337673187,
0.023020947352051735,
-0.09485872089862823,
0.006581571418792009,
0.11781952530145645,
0.13734377920627594,
-0.1060316190123558,
0.0751214474439621,
-0.022442102432250977,
0.005303474608808756,
-0.030825186520814896,
-0.0766751617193222,
-0.03766942024230957,
0.05439029633998871,
0.05975298956036568,
0.03355460986495018,
-0.006985093932598829,
0.0922321081161499,
-0.2715054154396057,
0.012526068836450577,
0.05675408989191055,
0.010183194652199745,
0.07977577298879623,
0.10833090543746948,
-0.0346086323261261,
0.12219321727752686,
-0.04290022328495979,
0.12652692198753357,
0.08525680750608444,
-0.07998355478048325,
-0.2297004610300064,
-0.080426886677742,
0.07684158533811569,
0.16972006857395172,
0.06932324171066284,
-0.03373773768544197,
0.13002200424671173,
-0.06606152653694153,
0.01538299210369587,
0.0861271470785141,
-0.11262787878513336,
-0.07531259208917618,
0.061673689633607864,
0.11219746619462967,
0.08889374881982803,
-0.12418624758720398,
-0.03206351399421692,
0.03724300488829613,
0.041227541863918304,
0.08002609759569168,
0.017795423045754433,
0.16806690394878387,
0.03422457352280617,
-0.14525416493415833,
-0.051488373428583145,
0.13708198070526123,
0.024141287431120872,
-0.04804939404129982,
-0.23597337305545807,
-0.013368546962738037,
-0.06597106158733368,
-0.03375716507434845,
-0.058522097766399384,
0.033577993512153625,
0.00032110881875269115,
0.1143890842795372,
-0.03560357913374901,
-0.08561250567436218,
-0.01779942400753498,
0.10882898420095444,
0.08448468148708344,
0.015028750523924828,
-0.014944080263376236,
0.0349264033138752,
0.12542980909347534,
0.06539697200059891,
-0.11406470835208893,
-0.045396286994218826,
-0.07186108827590942,
-0.05688225477933884,
-0.0322645828127861,
0.05514669790863991,
0.026887299492955208,
0.04396955296397209,
0.23244215548038483,
-0.008600415661931038,
0.058228470385074615,
0.045206934213638306,
0.014844055287539959,
0.039049018174409866,
0.0809558555483818,
-0.06178729236125946,
-0.19003230333328247,
-0.02811368741095066,
0.1037617027759552,
0.009480954147875309,
-0.0236408282071352,
-0.031626809388399124,
0.035004872828722,
0.03808356821537018,
0.11681250482797623,
0.09727825224399567,
-0.01998281665146351,
-0.06831733137369156,
-0.051899176090955734,
0.2189456969499588,
-0.15254028141498566,
0.04291049763560295,
0.012163523584604263,
-0.024112148210406303,
-0.04967283830046654,
0.012647828087210655,
0.01760226860642433,
-0.023975972086191177,
0.11450463533401489,
-0.06277041137218475,
-0.04611339792609215,
-0.10942637175321579,
-0.048221655189991,
0.03686324506998062,
0.014945974573493004,
-0.04276121035218239,
-0.04761594906449318,
-0.0783640518784523,
-0.08570438623428345,
0.08867911249399185,
-0.06184659153223038,
-0.06592725217342377,
-0.020152969285845757,
-0.07570280879735947,
0.02243632636964321,
0.014058404602110386,
0.09572537988424301,
-0.037238359451293945,
0.047928351908922195,
-0.032767895609140396,
0.06963062286376953,
0.09761054068803787,
0.03806249052286148,
-0.06723514944314957,
0.06278952956199646,
-0.19399981200695038,
0.07630135118961334,
-0.10044590383768082,
0.031186340376734734,
-0.17021223902702332,
-0.01909954659640789,
0.012409287504851818,
0.017359597608447075,
0.03338512405753136,
0.1471027284860611,
-0.2053186297416687,
-0.02364191971719265,
0.154048353433609,
-0.10433979332447052,
-0.11821354180574417,
0.05681162327528,
-0.032443415373563766,
0.16366121172904968,
0.024942917749285698,
-0.004531614016741514,
0.10111095756292343,
-0.15254567563533783,
-0.028551137074828148,
-0.02273205667734146,
0.011300460435450077,
0.08977165818214417,
0.07409755140542984,
-0.08260131627321243,
0.019732631742954254,
0.023201745003461838,
-0.05098153278231621,
-0.002640197519212961,
-0.04667156562209129,
-0.0983772799372673,
0.01206972450017929,
-0.09328702092170715,
0.027528533712029457,
0.0016967070987448096,
-0.07823655009269714,
-0.01804092340171337,
-0.14169909060001373,
-0.05430042743682861,
0.0929579958319664,
0.013747984543442726,
-0.020492438226938248,
-0.07427297532558441,
0.03803800046443939,
-0.03723304346203804,
-0.01831679791212082,
-0.1518179029226303,
-0.027333397418260574,
0.038912221789360046,
-0.14702853560447693,
-0.012692428193986416,
-0.10219695419073105,
0.06846193969249725,
0.02191338874399662,
-0.05845494568347931,
-0.037357863038778305,
0.02496611885726452,
-0.0022480885963886976,
-0.05920794606208801,
-0.21229666471481323,
-0.04177997633814812,
-0.04351719841361046,
0.1501489132642746,
-0.22678041458129883,
0.03659762814640999,
0.02033846266567707,
0.13114935159683228,
0.014217454940080643,
-0.07086353749036789,
0.03023962862789631,
-0.05600706487894058,
-0.027132300660014153,
-0.0735415369272232,
-0.0017258558655157685,
-0.0031731780618429184,
-0.032345984131097794,
0.025992227718234062,
-0.14305482804775238,
-0.035237327218055725,
0.08862468600273132,
0.0929306373000145,
-0.15084387362003326,
-0.010230003856122494,
-0.052604757249355316,
-0.06689053773880005,
-0.08704141527414322,
-0.06916619837284088,
0.07211054116487503,
0.05509808287024498,
0.05668535828590393,
-0.07606687396764755,
-0.06439974159002304,
0.019046779721975327,
-0.0013894631993025541,
-0.02748206816613674,
0.1177799329161644,
0.08060631901025772,
-0.0917164757847786,
0.08887536823749542,
0.08389166742563248,
0.061418864876031876,
0.08293266594409943,
-0.004256698302924633,
-0.109291210770607,
-0.028836967423558235,
0.06615187227725983,
0.019518643617630005,
0.14280946552753448,
-0.05322348326444626,
0.044329702854156494,
0.051447320729494095,
-0.04514295980334282,
0.03704513981938362,
-0.09771290421485901,
0.018874099478125572,
0.004956486634910107,
-0.010413081385195255,
0.05821092426776886,
-0.009699239395558834,
0.0017007337883114815,
0.08309818059206009,
0.062361814081668854,
0.02917321026325226,
0.019770292565226555,
-0.0332043431699276,
-0.1326669603586197,
0.1614207625389099,
-0.09583534300327301,
-0.23629605770111084,
-0.15576624870300293,
0.0228313859552145,
0.04290829598903656,
-0.024413853883743286,
0.026529734954237938,
-0.033993881195783615,
-0.10976745933294296,
-0.09228571504354477,
-0.0006130816764198244,
0.027164015918970108,
-0.06382694095373154,
-0.05605800449848175,
0.044154323637485504,
0.04767461493611336,
-0.12635067105293274,
0.032262787222862244,
0.05772260203957558,
0.0019380736630409956,
-0.004002261441200972,
0.06641621887683868,
0.0947459414601326,
0.16288335621356964,
0.007431069854646921,
-0.000017055108401109464,
0.046510249376297,
0.27210816740989685,
-0.14469854533672333,
0.11366629600524902,
0.12663190066814423,
-0.046330228447914124,
0.08772507309913635,
0.18445226550102234,
0.041506506502628326,
-0.08668006211519241,
0.03535948693752289,
0.033639147877693176,
-0.028747497126460075,
-0.2516976594924927,
-0.07774288952350616,
-0.01987442374229431,
-0.06681238114833832,
0.0948958769440651,
0.0926567018032074,
0.08240493386983871,
0.029779823496937752,
-0.07608015835285187,
-0.0589514784514904,
0.03540777787566185,
0.10752695053815842,
-0.029095053672790527,
0.003813758958131075,
0.07770686596632004,
-0.039821550250053406,
0.005608845967799425,
0.09869350492954254,
-0.01326720044016838,
0.1674787402153015,
0.03559323400259018,
0.10047435015439987,
0.06343573331832886,
0.09249018132686615,
-0.01037551648914814,
0.04706372320652008,
0.02689727023243904,
0.024864377453923225,
0.003381895599886775,
-0.09741800278425217,
0.00967713538557291,
0.13068550825119019,
0.029209580272436142,
0.03245413675904274,
0.019955717027187347,
-0.03385090082883835,
0.03973628208041191,
0.21623070538043976,
-0.002058799145743251,
-0.19922323524951935,
-0.07676326483488083,
0.061026010662317276,
-0.0885457918047905,
-0.14074864983558655,
-0.003823651000857353,
0.0402127169072628,
-0.1712646782398224,
0.024815758690238,
-0.048084553331136703,
0.09582160413265228,
-0.07943813502788544,
-0.03836166113615036,
0.09968674927949905,
0.06497028470039368,
-0.020559079945087433,
0.05651417374610901,
-0.15690559148788452,
0.12195199728012085,
0.026111174374818802,
0.0711050033569336,
-0.10120592266321182,
0.09865027666091919,
0.008601448498666286,
-0.03093465231359005,
0.17987176775932312,
-0.0008453016635030508,
-0.051005974411964417,
-0.0824253186583519,
-0.07906688004732132,
-0.02725568786263466,
0.09815347194671631,
-0.12179281562566757,
0.0728633776307106,
-0.02727397158741951,
-0.04304443672299385,
-0.005694510415196419,
-0.09871108084917068,
-0.12338851392269135,
-0.1814395934343338,
0.0692959800362587,
-0.07158946245908737,
0.0036791532766073942,
-0.1059945747256279,
-0.06309361010789871,
-0.021348915994167328,
0.1939249038696289,
-0.1834954023361206,
-0.10340641438961029,
-0.14972525835037231,
-0.07469151169061661,
0.17290380597114563,
-0.04254169017076492,
0.08455236256122589,
-0.0047736321575939655,
0.17168676853179932,
-0.010271238163113594,
-0.005716189742088318,
0.08037503063678741,
-0.09688833355903625,
-0.18873563408851624,
-0.052418533712625504,
0.16931897401809692,
0.11823409050703049,
0.038916170597076416,
-0.027071280404925346,
0.01873818226158619,
-0.035727690905332565,
-0.11468755453824997,
0.016167761757969856,
0.16131597757339478,
0.03193225339055061,
-0.0026233976241201162,
-0.024964233860373497,
-0.11905229091644287,
-0.056721873581409454,
-0.06828567385673523,
0.018959403038024902,
0.21201151609420776,
-0.08925259858369827,
0.16960357129573822,
0.11465572565793991,
-0.04964767023921013,
-0.21368850767612457,
0.02738700434565544,
0.050601180642843246,
0.007862290367484093,
0.04090026393532753,
-0.18459303677082062,
0.082403764128685,
-0.0023123163264244795,
-0.07720497995615005,
0.16692018508911133,
-0.19629113376140594,
-0.13157065212726593,
0.07515297085046768,
0.026786331087350845,
-0.23029430210590363,
-0.13635167479515076,
-0.1141519844532013,
-0.02053133025765419,
-0.1247294470667839,
0.02790723368525505,
0.042018286883831024,
0.010257444344460964,
0.019643856212496758,
0.0050584785640239716,
0.041474733501672745,
-0.06066058576107025,
0.19732172787189484,
-0.033443059772253036,
0.004876338876783848,
-0.052613504230976105,
-0.08463311940431595,
0.024286504834890366,
-0.05179975926876068,
0.10656406730413437,
-0.00009223517554346472,
0.020883971825242043,
-0.14789186418056488,
-0.04173469543457031,
-0.06475001573562622,
0.021073848009109497,
-0.0840996503829956,
-0.08722734451293945,
-0.051354553550481796,
0.0884907990694046,
0.10395373404026031,
-0.023932820186018944,
-0.0030752087477594614,
-0.07487171143293381,
0.08013106882572174,
0.20500226318836212,
0.16134004294872284,
0.03653319925069809,
-0.05972214415669441,
0.006159000564366579,
-0.033327214419841766,
0.03435491397976875,
-0.2275959700345993,
0.039157457649707794,
0.06771322339773178,
0.03166059032082558,
0.08367626368999481,
-0.012110726907849312,
-0.16096679866313934,
-0.05884779989719391,
0.0830356553196907,
-0.07458921521902084,
-0.19115059077739716,
-0.03767770156264305,
0.06764770299196243,
-0.20069538056850433,
-0.05188556760549545,
0.035252004861831665,
-0.030189616605639458,
-0.029298273846507072,
0.008208008483052254,
0.0823303684592247,
0.0018155944999307394,
0.10326472669839859,
0.062047798186540604,
0.09512084722518921,
-0.10393034666776657,
0.079788938164711,
0.09080109745264053,
-0.051434777677059174,
0.013019481673836708,
0.13063102960586548,
-0.05699380114674568,
-0.029472285881638527,
0.04373744875192642,
0.061345282942056656,
0.020567551255226135,
-0.050341349095106125,
0.014086632989346981,
-0.05529917776584625,
0.05845646932721138,
0.08438394963741302,
0.021126508712768555,
-0.019112201407551765,
0.06357726454734802,
0.02037106640636921,
-0.0888981744647026,
0.11993900686502457,
0.06316294521093369,
0.024650273844599724,
-0.0556950569152832,
-0.015354536473751068,
-0.015701157972216606,
-0.009343701414763927,
-0.012521067634224892,
-0.005695697385817766,
-0.05692828446626663,
-0.00862195435911417,
-0.11350027471780777,
0.012684555724263191,
-0.09236891567707062,
0.006020274944603443,
0.020701779052615166,
-0.03818422555923462,
-0.004555657040327787,
0.005658733658492565,
-0.08352992683649063,
-0.06521429121494293,
-0.021363195031881332,
0.09194210171699524,
-0.1259680539369583,
0.013643713667988777,
0.06430648267269135,
-0.11147690564393997,
0.07295428961515427,
-0.007576596923172474,
0.014124995097517967,
-0.0010084710083901882,
-0.13861747086048126,
0.03905823081731796,
-0.011331486515700817,
0.0010302126174792647,
0.02262609824538231,
-0.17347747087478638,
-0.0015715803019702435,
-0.049401845782995224,
-0.06866316497325897,
0.006487281061708927,
-0.03524038568139076,
-0.13358815014362335,
0.09337123483419418,
-0.008932087570428848,
-0.057225704193115234,
-0.02712862938642502,
0.04593293368816376,
0.09652376919984818,
-0.022705763578414917,
0.09944731742143631,
-0.031298257410526276,
0.0701262429356575,
-0.17019037902355194,
-0.0067917341366410255,
-0.025496307760477066,
0.031778816133737564,
-0.01916552148759365,
-0.0167818833142519,
0.05400339886546135,
-0.011554270051419735,
0.17191195487976074,
-0.02640879899263382,
0.09912373870611191,
0.05101047456264496,
-0.022654559463262558,
0.019093558192253113,
0.06830336153507233,
0.06239568069577217,
-0.0003259815857745707,
0.00009430608770344406,
0.029531942680478096,
-0.01196830254048109,
-0.03822775557637215,
-0.14161108434200287,
0.023598549887537956,
0.1626441925764084,
0.06600828468799591,
0.03031802363693714,
0.01786702312529087,
-0.15057028830051422,
-0.0847347304224968,
0.11917740851640701,
-0.023421635851264,
0.0036570513620972633,
-0.0769183561205864,
0.18235129117965698,
0.11824735999107361,
-0.18070951104164124,
0.05887798219919205,
-0.06042686477303505,
-0.033991262316703796,
-0.11759143322706223,
-0.136193186044693,
-0.05782987177371979,
-0.049268145114183426,
-0.014383310452103615,
-0.05290687456727028,
0.06682004779577255,
0.031796276569366455,
0.00010153334005735815,
-0.004509795922785997,
0.1034146249294281,
-0.014695505611598492,
-0.026574531570076942,
0.06811680644750595,
0.0615064837038517,
0.03374037146568298,
-0.08492985367774963,
-0.003438834333792329,
-0.0007852258277125657,
0.0032275705598294735,
0.060022883117198944,
0.0233335942029953,
-0.06116621196269989,
0.027950799092650414,
-0.0002580464642960578,
-0.11683737486600876,
0.03805046156048775,
-0.01505571324378252,
-0.04751316457986832,
0.14810679852962494,
0.03734319657087326,
0.013780953362584114,
-0.030238395556807518,
0.22829750180244446,
-0.08840431272983551,
-0.06625466793775558,
-0.14369504153728485,
0.07791340351104736,
-0.0346979945898056,
0.04137866571545601,
0.033940233290195465,
-0.11910601705312729,
0.006502497009932995,
0.16299113631248474,
0.13234223425388336,
-0.002203271258622408,
0.0077172392047941685,
0.0592636913061142,
0.0026213712990283966,
-0.04133761674165726,
0.028705747798085213,
0.058003947138786316,
0.17310099303722382,
-0.07453900575637817,
0.08141510933637619,
-0.017636172473430634,
-0.0728001594543457,
-0.024857884272933006,
0.13058452308177948,
-0.012537152506411076,
0.014683205634355545,
-0.05954236164689064,
0.1354656219482422,
-0.049803078174591064,
-0.2335961014032364,
0.04512208327651024,
-0.08787742257118225,
-0.14479903876781464,
-0.03060849942266941,
0.0060277413576841354,
-0.008060120977461338,
0.017211658880114555,
0.06731033325195312,
-0.04768627509474754,
0.19368954002857208,
0.033856913447380066,
-0.06872602552175522,
-0.085251085460186,
0.047738902270793915,
-0.13756030797958374,
0.2848971486091614,
0.02231711894273758,
0.03016486205160618,
0.10287673026323318,
-0.028739359229803085,
-0.16205044090747833,
0.0119076082482934,
0.11892281472682953,
-0.08096545934677124,
0.06167276203632355,
0.17453166842460632,
-0.004223288968205452,
0.14502662420272827,
0.05382874980568886,
-0.052841514348983765,
0.03894348442554474,
-0.04091041907668114,
-0.05369218438863754,
-0.11429803818464279,
0.07267328351736069,
-0.06582996994256973,
0.1566268801689148,
0.12536391615867615,
-0.06056053936481476,
-0.006532680243253708,
-0.02648353762924671,
0.07194964587688446,
0.009616924449801445,
0.13301241397857666,
0.018346505239605904,
-0.19352127611637115,
0.04223870486021042,
-0.02572724036872387,
0.1124657690525055,
-0.2086636871099472,
-0.0669953003525734,
0.045480918139219284,
-0.021722689270973206,
-0.07734902948141098,
0.11347471922636032,
0.043656621128320694,
0.013952852226793766,
-0.03130042552947998,
-0.08247026056051254,
-0.0006373357027769089,
0.15109725296497345,
-0.10455065965652466,
-0.008906422182917595
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-bn-adapter-1.79M-squad-model1
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 90
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "t5-base", "model-index": [{"name": "t5-base-bn-adapter-1.79M-squad-model1", "results": []}]} | null | varun-v-rao/t5-base-bn-adapter-1.79M-squad-model1 | [
"tensorboard",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:t5-base",
"license:apache-2.0",
"region:us"
] | 2024-02-09T00:07:06+00:00 | [] | [] | TAGS
#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #region-us
|
# t5-base-bn-adapter-1.79M-squad-model1
This model is a fine-tuned version of t5-base on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 90
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# t5-base-bn-adapter-1.79M-squad-model1\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 90\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #region-us \n",
"# t5-base-bn-adapter-1.79M-squad-model1\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 90\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
46,
38,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #region-us \n# t5-base-bn-adapter-1.79M-squad-model1\n\nThis model is a fine-tuned version of t5-base on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 90\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.11920444667339325,
0.07158177345991135,
-0.0016665573930367827,
0.09073277562856674,
0.1534910500049591,
0.042715661227703094,
0.11747884005308151,
0.12070333957672119,
-0.13261274993419647,
0.023384753614664078,
0.06566249579191208,
0.051090843975543976,
0.05223705619573593,
0.117434561252594,
0.005760308355093002,
-0.25371554493904114,
0.0024512794334441423,
0.029579631984233856,
-0.09953830391168594,
0.12210278958082199,
0.1238512471318245,
-0.0754394456744194,
0.06891082972288132,
0.031222756952047348,
-0.2132720947265625,
0.036997366696596146,
0.015448075719177723,
-0.07779575884342194,
0.1213490292429924,
0.006004405207931995,
0.11146405339241028,
0.013238313607871532,
0.13950634002685547,
-0.12776491045951843,
0.0081805270165205,
0.09087430685758591,
0.006100649479776621,
0.10534965246915817,
0.03256969153881073,
0.035533562302589417,
0.15503281354904175,
-0.09755746275186539,
0.08629388362169266,
0.05064565688371658,
-0.08341662585735321,
-0.1809214949607849,
-0.06744632124900818,
0.12069644778966904,
0.07624788582324982,
0.086159847676754,
0.007401235867291689,
0.1551835536956787,
-0.08411592245101929,
0.06799846887588501,
0.1988927125930786,
-0.311496764421463,
-0.06843513995409012,
0.04825035110116005,
0.04139144346117973,
0.06849783658981323,
-0.0737188532948494,
-0.03955179452896118,
0.047253143042325974,
0.052281059324741364,
0.11412734538316727,
0.010213172994554043,
-0.08396176993846893,
0.007833593524992466,
-0.14470386505126953,
-0.043395981192588806,
0.2030583918094635,
0.033006493002176285,
-0.05234001949429512,
-0.023787008598446846,
-0.0882527083158493,
-0.11842361092567444,
0.0036838543601334095,
-0.04742790013551712,
0.017678475007414818,
-0.03650044649839401,
-0.08435703068971634,
-0.06860373169183731,
-0.09227132797241211,
-0.08913098275661469,
-0.021751921623945236,
0.12141519039869308,
0.0717131569981575,
0.04432634264230728,
-0.05686130002140999,
0.15214504301548004,
0.013525983318686485,
-0.11603481322526932,
0.010873980820178986,
-0.0028919274918735027,
-0.08028291910886765,
-0.042773883789777756,
-0.048719003796577454,
-0.03351273387670517,
-0.012948641553521156,
0.1369270384311676,
-0.056230902671813965,
0.00967696774750948,
0.03161066770553589,
0.022532179951667786,
-0.042712271213531494,
0.12963557243347168,
-0.11337412148714066,
0.00989905558526516,
0.04225251451134682,
0.09124527871608734,
0.010809277184307575,
0.0001832451089285314,
-0.10083801299333572,
-0.05162394419312477,
0.11707993596792221,
0.04404136911034584,
-0.044316068291664124,
0.035262271761894226,
-0.016072764992713928,
-0.051223210990428925,
0.011809824034571648,
-0.11176230758428574,
-0.014311764389276505,
-0.017938688397407532,
-0.11772105097770691,
-0.030338719487190247,
0.03980414569377899,
-0.015734033659100533,
-0.057619888335466385,
0.016122084110975266,
-0.10328621417284012,
-0.020476439967751503,
-0.08954379707574844,
-0.07631752640008926,
0.012600923888385296,
-0.08639737963676453,
-0.004820732865482569,
-0.10163533687591553,
-0.167888805270195,
0.011990773491561413,
0.03190568834543228,
-0.056760501116514206,
-0.08386372029781342,
-0.011422925628721714,
-0.07886295765638351,
0.0010907307732850313,
-0.012352775782346725,
0.1374150812625885,
-0.03393430635333061,
0.09965114295482635,
0.03114032931625843,
0.025059327483177185,
-0.009654125198721886,
0.03902167081832886,
-0.08009150624275208,
0.02295665442943573,
-0.13173902034759521,
0.04656479135155678,
-0.05025172606110573,
0.007646449841558933,
-0.11730252206325531,
-0.11229861527681351,
0.020214742049574852,
-0.03705062344670296,
0.10178133100271225,
0.10479343682527542,
-0.15289746224880219,
-0.03608424589037895,
0.11363083869218826,
-0.08830272406339645,
-0.10435109585523605,
0.1052270382642746,
-0.033860478550195694,
0.048260413110256195,
0.039217278361320496,
0.12299071252346039,
0.08705134689807892,
-0.10863030701875687,
-0.005601165816187859,
0.028085121884942055,
0.023487215861678123,
-0.062414687126874924,
0.09077528864145279,
0.028033308684825897,
-0.03257381170988083,
0.021108705550432205,
-0.07946478575468063,
0.04766697809100151,
-0.1014479473233223,
-0.08478480577468872,
-0.07492899894714355,
-0.09019410610198975,
0.06815921515226364,
0.040838927030563354,
0.039699118584394455,
-0.05405646562576294,
-0.1234181821346283,
0.12472217530012131,
0.15587212145328522,
-0.03707684576511383,
0.019221046939492226,
-0.10912568867206573,
0.09561968594789505,
-0.08629318326711655,
-0.01826322451233864,
-0.20440874993801117,
-0.09815479069948196,
0.020645253360271454,
-0.02522142603993416,
0.04793109372258186,
0.02279929257929325,
0.05442837253212929,
0.08099458366632462,
-0.05196317285299301,
-0.03625283017754555,
-0.14389535784721375,
-0.015045447275042534,
-0.08572052419185638,
-0.1939649134874344,
-0.09942390024662018,
-0.00990287121385336,
0.15818549692630768,
-0.18194586038589478,
0.03421047702431679,
-0.010177716612815857,
0.13701343536376953,
0.01586114801466465,
-0.026558052748441696,
-0.012239917181432247,
0.037520769983530045,
-0.022495446726679802,
-0.09406905621290207,
0.04163534194231033,
0.02020011469721794,
-0.09058275073766708,
-0.052480895072221756,
-0.08770043402910233,
0.093332938849926,
0.09957565367221832,
0.01939534582197666,
-0.08527256548404694,
0.036584727466106415,
-0.09347234666347504,
-0.04717230051755905,
-0.041833773255348206,
-0.008638041093945503,
0.15728899836540222,
-0.004098376724869013,
0.135391965508461,
-0.0916740670800209,
-0.06116257980465889,
0.02228327840566635,
0.01061347033828497,
0.020314441993832588,
0.06137656792998314,
0.0863618552684784,
-0.11050651967525482,
0.0757918655872345,
0.09813687205314636,
-0.08212076127529144,
0.13463152945041656,
-0.06663025170564651,
-0.10685397684574127,
-0.03744623437523842,
0.0005223437328822911,
-0.0035211737267673016,
0.17558801174163818,
-0.12282666563987732,
0.008109286427497864,
0.03561696410179138,
-0.0056081353686749935,
0.042629584670066833,
-0.1962900310754776,
-0.017596906051039696,
0.016062237322330475,
-0.03875671327114105,
-0.049874380230903625,
-0.008968791924417019,
0.02177153341472149,
0.11824825406074524,
0.019151484593749046,
-0.05099419876933098,
0.03978992626070976,
0.01419299840927124,
-0.0814436599612236,
0.18850383162498474,
-0.09280788153409958,
-0.11535783112049103,
-0.11870252341032028,
0.09397954493761063,
-0.0679432600736618,
-0.03187727555632591,
0.0012889467179775238,
-0.08597160875797272,
-0.01822713389992714,
-0.06955408304929733,
0.030947627499699593,
-0.035758744925260544,
0.019400712102651596,
-0.004048448521643877,
0.036194708198308945,
0.1168830618262291,
-0.14742565155029297,
0.03341221064329147,
-0.032479412853717804,
-0.11684851348400116,
-0.01775042898952961,
0.047323599457740784,
0.09864417463541031,
0.1508256047964096,
-0.045111238956451416,
0.024726659059524536,
-0.0374392569065094,
0.21817655861377716,
-0.05368764325976372,
-0.003640196518972516,
0.1573529988527298,
0.01708952710032463,
0.030875008553266525,
0.09165745973587036,
0.03463137149810791,
-0.056270256638526917,
0.0175618976354599,
0.04101921245455742,
-0.02843509614467621,
-0.2696128785610199,
-0.023974934592843056,
-0.03473299741744995,
-0.05440274626016617,
0.08892892301082611,
0.04803696274757385,
0.02144128642976284,
0.07115720957517624,
-0.02051531709730625,
0.0844603031873703,
-0.05197259783744812,
0.0768546611070633,
0.07780525833368301,
0.03384333848953247,
0.08830046653747559,
-0.039647411555051804,
-0.0272802896797657,
0.062379490584135056,
0.03817717358469963,
0.25188949704170227,
-0.07439607381820679,
0.11633618175983429,
0.04754364863038063,
0.21960537135601044,
-0.027509231120347977,
0.0743926391005516,
0.0008248783997260034,
0.00722510414198041,
0.011072909459471703,
-0.0493951216340065,
-0.01734287664294243,
0.004520519636571407,
-0.04231788590550423,
0.08983692526817322,
-0.10993461310863495,
0.05037650465965271,
0.014555160887539387,
0.2863630950450897,
0.04292957857251167,
-0.3152382969856262,
-0.11912418901920319,
-0.02662159688770771,
-0.018011730164289474,
-0.05857617035508156,
0.021610675379633904,
0.12722711265087128,
-0.09379424154758453,
0.001385331037454307,
-0.06469190865755081,
0.07633038610219955,
-0.009220210835337639,
-0.017884111031889915,
0.08632870018482208,
0.16678868234157562,
0.005502653308212757,
0.0959969311952591,
-0.21256014704704285,
0.22485293447971344,
0.01662125624716282,
0.09968838095664978,
-0.05441916361451149,
0.021833166480064392,
0.013971016742289066,
0.09960832446813583,
0.07475165277719498,
0.003279742319136858,
-0.011963863857090473,
-0.1541331559419632,
-0.07561556994915009,
0.03546348586678505,
0.07451393455266953,
-0.04164907708764076,
0.08866546303033829,
-0.05014996975660324,
0.021626846864819527,
0.057912278920412064,
-0.03840603306889534,
-0.18212808668613434,
-0.07718677818775177,
0.005335732828825712,
-0.015781519934535027,
-0.04565192759037018,
-0.10198527574539185,
-0.11716301739215851,
0.03327350690960884,
0.1430089771747589,
-0.027448615059256554,
-0.06242864951491356,
-0.1379999965429306,
0.10853959619998932,
0.1329064965248108,
-0.06303444504737854,
0.02153768204152584,
0.021801987662911415,
0.12289226055145264,
0.038414549082517624,
-0.11044283211231232,
0.06143786013126373,
-0.0686250627040863,
-0.1737479269504547,
-0.03966044262051582,
0.131849005818367,
0.035661667585372925,
0.05886196717619896,
-0.008189919404685497,
-0.025133559480309486,
0.01419215276837349,
-0.07798991352319717,
0.009156090207397938,
0.010954856872558594,
0.0362149216234684,
0.019166849553585052,
-0.06734105944633484,
0.01730211451649666,
-0.04240140691399574,
0.0043149893172085285,
0.11573703587055206,
0.18074612319469452,
-0.08367753773927689,
0.04147209972143173,
0.07844296097755432,
-0.06274478882551193,
-0.14431387186050415,
0.0443512462079525,
0.1053905040025711,
0.03172452002763748,
0.022726405411958694,
-0.19820749759674072,
0.09142417460680008,
0.09309349954128265,
-0.018880613148212433,
0.04307267814874649,
-0.34914281964302063,
-0.13196086883544922,
0.09131023287773132,
0.14741063117980957,
0.05793667957186699,
-0.11472389847040176,
-0.01397332176566124,
-0.004482598975300789,
-0.12306398153305054,
0.1323293000459671,
-0.16731728613376617,
0.09375134110450745,
-0.022829774767160416,
0.0968291386961937,
0.022460320964455605,
-0.03303937241435051,
0.10926852375268936,
0.020709076896309853,
0.07397609949111938,
-0.04667685925960541,
-0.004854730796068907,
0.18015435338020325,
-0.0544818639755249,
0.0645461231470108,
-0.004339762032032013,
0.08582098037004471,
-0.1389322429895401,
-0.009114309214055538,
-0.0894080400466919,
0.05828610062599182,
-0.05294675752520561,
-0.08356840163469315,
-0.03968409448862076,
0.06361287832260132,
0.015768198296427727,
-0.050838205963373184,
0.0595659464597702,
0.0659555047750473,
0.10495802015066147,
0.10125112533569336,
0.08568434417247772,
-0.0006430222420021892,
-0.088694728910923,
0.005232944153249264,
-0.009645656682550907,
0.09165839850902557,
-0.1606777161359787,
0.003934097476303577,
0.1098586767911911,
0.042695313692092896,
0.09860207140445709,
0.06250456720590591,
-0.08483651280403137,
0.015915576368570328,
0.048210509121418,
-0.1208774670958519,
-0.14340393245220184,
-0.05089467018842697,
-0.03419749438762665,
-0.1449601799249649,
0.0689895898103714,
0.09814473986625671,
-0.10783879458904266,
-0.026212265715003014,
-0.0031662536785006523,
-0.016420893371105194,
-0.06694690138101578,
0.18329071998596191,
0.09050212055444717,
0.07077553123235703,
-0.08324069529771805,
0.12102989852428436,
0.0734596997499466,
-0.05645517259836197,
0.032622236758470535,
0.06166142597794533,
-0.10171237587928772,
-0.01532676164060831,
0.05186986178159714,
0.11427143216133118,
-0.08546730130910873,
-0.0564710907638073,
-0.12375089526176453,
-0.08746318519115448,
0.0506574772298336,
0.11683358997106552,
0.05708658695220947,
0.01696767471730709,
-0.05128894001245499,
0.03196248039603233,
-0.14943638443946838,
0.09364419430494308,
0.037799615412950516,
0.06966561824083328,
-0.16375495493412018,
0.14645366370677948,
0.018796173855662346,
0.08381102979183197,
-0.03129027038812637,
0.014438048005104065,
-0.08857043832540512,
0.0003809033369179815,
-0.15696850419044495,
-0.03212543949484825,
-0.0051992833614349365,
0.012114125303924084,
-0.007720802910625935,
-0.05657292529940605,
-0.05699744075536728,
0.0754450336098671,
-0.07601722329854965,
-0.04154570400714874,
0.03687426820397377,
0.031462762504816055,
-0.1190628930926323,
0.01336634624749422,
0.0030954722315073013,
-0.09378926455974579,
0.10329324007034302,
0.05727072060108185,
0.02822932042181492,
0.049870871007442474,
-0.06414100527763367,
-0.013564708642661572,
0.003229260677471757,
0.028356682509183884,
0.07381319999694824,
-0.07759197801351547,
0.02226400189101696,
-0.03943835571408272,
0.021867452189326286,
-0.006197532173246145,
0.06389223784208298,
-0.11319231986999512,
-0.0426732562482357,
-0.04328160732984543,
-0.021885402500629425,
-0.0813705325126648,
0.04438070207834244,
0.08910434693098068,
0.047701045870780945,
0.14738737046718597,
-0.05890762433409691,
0.013599899597465992,
-0.22631007432937622,
-0.026170922443270683,
-0.007259038742631674,
-0.018243232741951942,
-0.08743735402822495,
-0.03435809537768364,
0.06414969265460968,
-0.0662410706281662,
0.07070169597864151,
-0.01033693179488182,
0.10564707219600677,
0.034354306757450104,
-0.005574742332100868,
-0.004925660789012909,
0.012407663278281689,
0.19571687281131744,
0.035823285579681396,
0.0011568950721994042,
0.05591818690299988,
-0.009100617840886116,
0.05846293643116951,
0.06164718046784401,
0.1607387810945511,
0.09108588099479675,
-0.01768326573073864,
0.08076601475477219,
0.10418123751878738,
-0.08251244574785233,
-0.15296144783496857,
0.07978984713554382,
-0.017539042979478836,
0.09471005946397781,
-0.030558006837964058,
0.15362495183944702,
0.15331903100013733,
-0.1413915902376175,
0.030166398733854294,
-0.03150241822004318,
-0.09375420212745667,
-0.08658471703529358,
-0.06212626397609711,
-0.04957326874136925,
-0.15314450860023499,
0.023935696110129356,
-0.11744966357946396,
-0.02627653069794178,
0.10490171611309052,
0.011394201777875423,
-0.017022205516695976,
0.1487056314945221,
0.04888493940234184,
0.006795891094952822,
0.047754257917404175,
0.022657861933112144,
-0.009955975227057934,
-0.05887535586953163,
-0.059536002576351166,
0.054522834718227386,
-0.012204678729176521,
0.061817485839128494,
-0.07324223965406418,
-0.011567777954041958,
0.0534968227148056,
0.0059860278852283955,
-0.06356993317604065,
0.02707015909254551,
-0.002842262852936983,
0.04385166987776756,
0.04319809377193451,
0.03381424769759178,
0.0058609009720385075,
-0.042579639703035355,
0.256626158952713,
-0.06352502107620239,
-0.09089769423007965,
-0.14852800965309143,
0.21173688769340515,
0.021475540474057198,
-0.0563192255795002,
0.0866769403219223,
-0.11093603819608688,
-0.030266331508755684,
0.15107598900794983,
0.1612277328968048,
-0.052410826086997986,
-0.0389140322804451,
0.0021242541261017323,
-0.03136628866195679,
-0.09142883867025375,
0.1670924574136734,
0.10325080156326294,
0.048173848539590836,
-0.06790584325790405,
-0.013640334829688072,
-0.03961553797125816,
-0.0064341602846980095,
-0.027868349105119705,
0.09012388437986374,
0.03272826224565506,
-0.003773485077545047,
-0.035582005977630615,
0.05674228072166443,
-0.016876816749572754,
-0.1613111048936844,
0.0508805476129055,
-0.1147816851735115,
-0.1803688108921051,
-0.05194495990872383,
0.08138155192136765,
-0.01657106913626194,
0.06947775185108185,
-0.03402578830718994,
0.01954742893576622,
0.12812307476997375,
-0.005714937578886747,
-0.08820200711488724,
-0.10338789969682693,
0.12392221391201019,
-0.06490545719861984,
0.21541434526443481,
-0.031980857253074646,
0.0858875960111618,
0.11240371316671371,
0.026196401566267014,
-0.1643855720758438,
0.019458279013633728,
0.05292201414704323,
-0.04109765589237213,
0.008648027665913105,
0.1569371372461319,
-0.02089645154774189,
0.06465910375118256,
0.015178103931248188,
-0.11400289088487625,
-0.030534742400050163,
-0.05454938858747482,
0.009550565853714943,
-0.08213230967521667,
0.0005007359432056546,
-0.05770917609333992,
0.14366234838962555,
0.200384721159935,
-0.05960604175925255,
-0.0007310231449082494,
-0.12382712215185165,
0.02623838372528553,
0.07623278349637985,
0.06357777118682861,
0.007553889881819487,
-0.17447884380817413,
0.012560437433421612,
0.0139114148914814,
-0.014660361222922802,
-0.22354735434055328,
-0.08069199323654175,
0.05520879849791527,
-0.08561322838068008,
-0.08573011308908463,
0.1068849191069603,
0.09150130301713943,
0.07437444478273392,
-0.028743674978613853,
-0.0312931202352047,
-0.0832265168428421,
0.12468142807483673,
-0.17879872024059296,
-0.07320009917020798
] |
null | null | adapter-transformers |
# Adapter `tawfikgh/xsum_summary_adapter-v1` for gpt2
An [adapter](https://adapterhub.ml) for the `gpt2` model that was trained on the [summary/xsum](https://adapterhub.ml/explore/summary/xsum/) dataset.
This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library.
## Usage
First, install `adapters`:
```
pip install -U adapters
```
Now, the adapter can be loaded and activated like this:
```python
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("gpt2")
adapter_name = model.load_adapter("tawfikgh/xsum_summary_adapter-v1", source="hf", set_active=True)
```
## Architecture & Training
<!-- Add some description here -->
## Evaluation results
<!-- Add some description here -->
## Citation
<!-- Add some description here --> | {"tags": ["gpt2", "adapterhub:summary/xsum", "adapter-transformers"], "datasets": ["xsum"]} | null | tawfikgh/xsum_summary_adapter-v1 | [
"adapter-transformers",
"gpt2",
"adapterhub:summary/xsum",
"dataset:xsum",
"region:us"
] | 2024-02-09T00:18:29+00:00 | [] | [] | TAGS
#adapter-transformers #gpt2 #adapterhub-summary/xsum #dataset-xsum #region-us
|
# Adapter 'tawfikgh/xsum_summary_adapter-v1' for gpt2
An adapter for the 'gpt2' model that was trained on the summary/xsum dataset.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'adapters':
Now, the adapter can be loaded and activated like this:
## Architecture & Training
## Evaluation results
| [
"# Adapter 'tawfikgh/xsum_summary_adapter-v1' for gpt2\n\nAn adapter for the 'gpt2' model that was trained on the summary/xsum dataset.\n\nThis adapter was created for usage with the Adapters library.",
"## Usage\n\nFirst, install 'adapters':\n\n\n\nNow, the adapter can be loaded and activated like this:",
"## Architecture & Training",
"## Evaluation results"
] | [
"TAGS\n#adapter-transformers #gpt2 #adapterhub-summary/xsum #dataset-xsum #region-us \n",
"# Adapter 'tawfikgh/xsum_summary_adapter-v1' for gpt2\n\nAn adapter for the 'gpt2' model that was trained on the summary/xsum dataset.\n\nThis adapter was created for usage with the Adapters library.",
"## Usage\n\nFirst, install 'adapters':\n\n\n\nNow, the adapter can be loaded and activated like this:",
"## Architecture & Training",
"## Evaluation results"
] | [
30,
60,
25,
5,
4
] | [
"passage: TAGS\n#adapter-transformers #gpt2 #adapterhub-summary/xsum #dataset-xsum #region-us \n# Adapter 'tawfikgh/xsum_summary_adapter-v1' for gpt2\n\nAn adapter for the 'gpt2' model that was trained on the summary/xsum dataset.\n\nThis adapter was created for usage with the Adapters library.## Usage\n\nFirst, install 'adapters':\n\n\n\nNow, the adapter can be loaded and activated like this:## Architecture & Training## Evaluation results"
] | [
-0.06922569125890732,
-0.1410350650548935,
-0.0034330757334828377,
0.04731537029147148,
0.16069498658180237,
0.08827342092990875,
0.1587032526731491,
0.047121528536081314,
0.19370387494564056,
-0.05303262919187546,
0.06686457991600037,
0.12414770573377609,
0.09265433251857758,
0.1382020115852356,
0.07775133103132248,
-0.12868541479110718,
0.013188824988901615,
0.06484507024288177,
-0.2174585908651352,
0.1276738941669464,
0.12292748689651489,
-0.004667793400585651,
0.13863886892795563,
0.08948217332363129,
-0.11112295836210251,
0.0449175164103508,
0.09481523931026459,
-0.11993271112442017,
0.11426018923521042,
0.09290511906147003,
0.09462794661521912,
0.09353381395339966,
0.03298015519976616,
-0.11417078971862793,
-0.0018067179480567575,
0.07339785993099213,
-0.014125832356512547,
0.02347802370786667,
0.02318044938147068,
0.062639020383358,
0.11089767515659332,
0.07463794201612473,
0.029185064136981964,
0.06843196600675583,
-0.108638234436512,
-0.25565826892852783,
0.005278693977743387,
0.09192284941673279,
0.05119245499372482,
0.029501456767320633,
0.028857635334134102,
0.029504211619496346,
0.035712309181690216,
0.013850491493940353,
0.1623615324497223,
-0.28127560019493103,
0.012242674827575684,
0.027591293677687645,
0.06058841571211815,
0.07746971398591995,
0.059843510389328,
0.06886230409145355,
-0.013687928207218647,
0.046593938022851944,
0.10923198610544205,
-0.06154126673936844,
-0.002361857332289219,
0.05358093976974487,
-0.1873275339603424,
-0.08706541359424591,
0.3133140802383423,
-0.07111214846372604,
-0.07559739798307419,
-0.016041778028011322,
-0.05340578779578209,
0.05002126842737198,
0.05555681884288788,
-0.13454486429691315,
-0.03309205174446106,
0.0975305438041687,
-0.017112163826823235,
-0.19141441583633423,
-0.12206614762544632,
-0.15433147549629211,
-0.1593698412179947,
0.29531580209732056,
-0.020878272131085396,
0.09055601060390472,
-0.036298442631959915,
0.10860776901245117,
-0.08112742751836777,
-0.00739659508690238,
-0.042715877294540405,
-0.09591161459684372,
-0.02058774046599865,
0.004937928169965744,
0.0027745903935283422,
-0.2077290564775467,
0.04940643906593323,
0.04790031909942627,
0.12299063056707382,
0.03011791594326496,
0.056382108479738235,
0.07960130274295807,
-0.0046190437860786915,
0.1726573258638382,
-0.09672861546278,
0.014141837134957314,
0.0026218437124043703,
-0.04048757627606392,
-0.07687283307313919,
-0.07755580544471741,
-0.10596903413534164,
-0.0493522584438324,
-0.03801364824175835,
0.05828208476305008,
0.020075282081961632,
0.11697299033403397,
-0.08279509097337723,
-0.07230661064386368,
0.034818656742572784,
-0.05813802033662796,
-0.031380489468574524,
-0.06129160895943642,
-0.015304544009268284,
0.007669615559279919,
0.12741951644420624,
-0.030188418924808502,
-0.013319588266313076,
-0.0273010041564703,
-0.06637008488178253,
-0.06022635102272034,
-0.010897739790380001,
-0.0751410499215126,
-0.020945578813552856,
-0.04921465739607811,
0.005774686112999916,
-0.17946015298366547,
-0.09999008476734161,
0.04811478778719902,
0.08454248309135437,
0.019518043845891953,
0.061399780213832855,
0.07269874215126038,
0.06689324229955673,
0.019917063415050507,
-0.06237555667757988,
0.054237622767686844,
-0.039573751389980316,
0.0796901136636734,
0.007497558370232582,
0.07947655767202377,
-0.11341948062181473,
0.05409276485443115,
-0.06390380859375,
0.03622462600469589,
-0.12420041114091873,
0.08139673620462418,
-0.10166077315807343,
-0.06369968503713608,
-0.12879396975040436,
0.00794905424118042,
-0.00034836982376873493,
0.05427918583154678,
0.059231940656900406,
0.07109992951154709,
-0.08104760944843292,
-0.08444112539291382,
0.17400261759757996,
-0.2306237667798996,
-0.17703181505203247,
0.03313655033707619,
0.06603766232728958,
0.16931946575641632,
0.040234893560409546,
0.09964025765657425,
0.0860019400715828,
-0.0747014582157135,
-0.022061577066779137,
0.09297788143157959,
-0.17696015536785126,
-0.047053996473550797,
0.080743208527565,
0.06042555347084999,
-0.2426031231880188,
-0.002946342108771205,
-0.08309533447027206,
0.1461060792207718,
-0.02475590631365776,
-0.02414230816066265,
-0.06252317130565643,
-0.04966655373573303,
0.0848640576004982,
-0.04499846324324608,
-0.07893313467502594,
0.049748677760362625,
-0.11023171246051788,
0.047469355165958405,
0.08470853418111801,
-0.035656869411468506,
-0.013661316595971584,
-0.17902547121047974,
0.08357696235179901,
-0.1327446848154068,
0.03165478631854057,
-0.06353005766868591,
0.008563403971493244,
-0.012958693318068981,
0.02328360266983509,
0.03607529029250145,
0.12272530794143677,
0.12034866958856583,
-0.013342234306037426,
-0.010662137530744076,
-0.011473841033875942,
-0.03520333021879196,
0.0521208718419075,
0.003821006743237376,
-0.09607777744531631,
-0.026234984397888184,
-0.022351818159222603,
0.04552118107676506,
-0.03705720603466034,
0.03819604963064194,
0.15966524183750153,
-0.009100306779146194,
0.02361670322716236,
-0.011868116445839405,
-0.028763622045516968,
-0.044001057744026184,
-0.002781266113743186,
-0.09228681027889252,
0.03555983304977417,
0.009963175281882286,
-0.08139525353908539,
0.20374442636966705,
-0.10513357073068619,
0.10837092995643616,
0.10604532063007355,
-0.039766378700733185,
-0.03084496222436428,
0.02567308023571968,
-0.009939413517713547,
-0.03310595080256462,
0.03573911637067795,
-0.06756649911403656,
0.2140229195356369,
-0.00961318425834179,
0.019931098446249962,
-0.036095887422561646,
0.021483242511749268,
0.060225170105695724,
-0.04584232717752457,
0.015918616205453873,
-0.03779160603880882,
0.16358473896980286,
-0.2224772423505783,
0.06668145954608917,
0.23498377203941345,
0.05887895077466965,
0.06338508427143097,
0.04033416509628296,
-0.06809418648481369,
-0.05310148745775223,
-0.043673884123563766,
0.03009827807545662,
0.10421937704086304,
-0.18300992250442505,
0.017729967832565308,
0.060435857623815536,
-0.004756493028253317,
0.06754118204116821,
-0.11560653150081635,
0.013576346449553967,
0.05814700201153755,
-0.05803796276450157,
-0.009708462283015251,
0.03913374990224838,
-0.031782545149326324,
0.07300024479627609,
0.012080516666173935,
0.10114865005016327,
0.07057900726795197,
0.050077371299266815,
-0.07204250246286392,
0.14001505076885223,
-0.0658644437789917,
-0.3097683787345886,
-0.12993144989013672,
-0.07458573579788208,
0.040388092398643494,
0.06247483938932419,
0.07292557507753372,
-0.08658977597951889,
-0.03882170468568802,
0.018976788967847824,
0.23984193801879883,
-0.06270452588796616,
0.0796196311712265,
-0.019239414483308792,
-0.021705981343984604,
0.07154331356287003,
-0.1103934571146965,
-0.02206745184957981,
0.044206179678440094,
-0.19619861245155334,
0.07859444618225098,
-0.042417142540216446,
0.01626235991716385,
0.14390668272972107,
-0.011792963370680809,
0.046350788325071335,
-0.02918636053800583,
0.12442272901535034,
-0.08382926136255264,
0.005923476070165634,
0.1755252629518509,
-0.07131442427635193,
0.018560826778411865,
-0.002312622033059597,
-0.011024640873074532,
-0.07305252552032471,
-0.030865337699651718,
-0.04777515307068825,
-0.13800379633903503,
-0.22314049303531647,
-0.03336286172270775,
-0.020562442019581795,
0.08541608601808548,
0.1340361386537552,
0.046403829008340836,
-0.008027227595448494,
0.1927553117275238,
0.05213673412799835,
0.006371630355715752,
-0.062469955533742905,
-0.004366230685263872,
0.15773539245128632,
-0.027447141706943512,
0.08584802597761154,
-0.09222870320081711,
0.014747136272490025,
0.1712910383939743,
0.06524990499019623,
0.1856173276901245,
0.005297624506056309,
-0.0044119711965322495,
0.08537983894348145,
-0.06018536165356636,
0.0354778990149498,
0.18340834975242615,
-0.013146880082786083,
-0.035788245499134064,
-0.018538063392043114,
0.004462941084057093,
-0.1388990879058838,
0.07697191834449768,
0.07289889454841614,
-0.1531677544116974,
-0.020761819556355476,
0.06834858655929565,
0.0652317926287651,
0.016351277008652687,
-0.0010357173159718513,
-0.20477432012557983,
-0.0795271098613739,
-0.038355257362127304,
-0.009270108304917812,
-0.09152401238679886,
0.016619710251688957,
0.12498625367879868,
-0.09532769024372101,
0.03849538788199425,
-0.006699227262288332,
0.05148894712328911,
-0.15500576794147491,
-0.06864568591117859,
0.0680786594748497,
0.04266568645834923,
-0.006467550061643124,
0.10426007956266403,
-0.2504407465457916,
0.127184197306633,
0.016937393695116043,
-0.027043459936976433,
-0.11517717689275742,
0.0408795028924942,
0.035399045795202255,
0.0903128832578659,
0.10272462666034698,
0.06794614344835281,
-0.0987406075000763,
-0.18453992903232574,
-0.10032796859741211,
0.08386296033859253,
0.03650394082069397,
-0.06732654571533203,
-0.012032728642225266,
-0.06381092220544815,
0.08765027672052383,
0.02990352176129818,
-0.030353683978319168,
-0.059261515736579895,
-0.15607476234436035,
0.1002703383564949,
0.07756432145833969,
0.024961767718195915,
-0.09647002071142197,
-0.0345841646194458,
0.06737404316663742,
0.20005984604358673,
-0.038566023111343384,
-0.11445830017328262,
-0.13386116921901703,
0.003151307115331292,
0.09643539041280746,
-0.05680720880627632,
0.08293250948190689,
0.03587339445948601,
-0.003664627205580473,
0.03148680925369263,
-0.12415484338998795,
0.14133994281291962,
-0.09073679149150848,
-0.008140673860907555,
-0.02041490189731121,
0.028358548879623413,
0.04350391775369644,
0.024559075012803078,
0.01809334009885788,
-0.04344810172915459,
0.03047955594956875,
-0.11971504986286163,
0.06537284702062607,
-0.06821659952402115,
-0.15457020699977875,
0.014545897953212261,
0.08268439024686813,
0.11926273256540298,
-0.00637674517929554,
-0.06617100536823273,
0.15901871025562286,
0.0668376013636589,
-0.046501267701387405,
0.12945333123207092,
0.0007323115132749081,
-0.05339948460459709,
-0.2681587338447571,
-0.08211515098810196,
0.02058345638215542,
-0.020085502415895462,
0.029551073908805847,
-0.2641385495662689,
0.1111401617527008,
0.040546730160713196,
-0.030666492879390717,
0.16355811059474945,
-0.14639179408550262,
-0.052745576947927475,
0.15957677364349365,
0.07009875774383545,
0.15045803785324097,
-0.10435120016336441,
-0.0671573057770729,
0.013485027477145195,
-0.17214380204677582,
0.13602755963802338,
-0.04380112141370773,
0.09805659204721451,
-0.04417608678340912,
0.07502187043428421,
0.025023851543664932,
-0.015428808517754078,
0.1259635090827942,
-0.061088379472494125,
-0.057557906955480576,
-0.09994423389434814,
0.008482538163661957,
0.16218100488185883,
0.013505605049431324,
0.022602582350373268,
-0.0953432098031044,
0.03145356848835945,
-0.08834294974803925,
-0.10589798539876938,
-0.006771237589418888,
0.08329402655363083,
0.047074347734451294,
-0.14705078303813934,
-0.0259014293551445,
-0.02500845119357109,
-0.06133992597460747,
-0.05461500957608223,
-0.15697984397411346,
-0.039988745003938675,
0.0034310726914554834,
0.0938071459531784,
0.03214515000581741,
-0.08866206556558609,
-0.11366752535104752,
-0.016626980155706406,
-0.013384711928665638,
0.10812435299158096,
-0.1683005392551422,
0.10719043761491776,
0.034893523901700974,
-0.03901401907205582,
0.06889413297176361,
0.07917740941047668,
-0.05512883886694908,
0.010085930116474628,
0.13964007794857025,
-0.10196053236722946,
-0.04842297360301018,
-0.037864718586206436,
0.10917171090841293,
0.012543167918920517,
0.07933558523654938,
0.17054681479930878,
0.001970743527635932,
-0.012401057407259941,
-0.012090763077139854,
0.00027926350594498217,
-0.1399276852607727,
0.13482558727264404,
0.026362653821706772,
0.04698352888226509,
-0.055531203746795654,
0.04107575863599777,
0.0022574057802557945,
-0.09325399994850159,
0.03461091220378876,
-0.08309724181890488,
-0.0866905003786087,
-0.06018033251166344,
-0.041954271495342255,
-0.03906242176890373,
-0.12998130917549133,
-0.13180528581142426,
0.0248866006731987,
-0.09004689753055573,
0.022268924862146378,
0.03919677808880806,
0.038761407136917114,
0.06014397367835045,
-0.009432942606508732,
0.02118944562971592,
-0.03846755623817444,
-0.013192691840231419,
-0.03948579356074333,
0.04424258694052696,
-0.16779181361198425,
0.011597362346947193,
0.04341789335012436,
0.0837404802441597,
-0.09024477005004883,
-0.01488596573472023,
-0.09862782806158066,
0.005559747107326984,
-0.11540769785642624,
-0.009691809304058552,
-0.05265090987086296,
-0.019047798588871956,
0.09019581228494644,
-0.10303604602813721,
-0.11062462627887726,
0.052343569695949554,
-0.08995334059000015,
0.018025565892457962,
0.018793728202581406,
0.03705751895904541,
-0.04976717382669449,
-0.033168621361255646,
0.08293519169092178,
-0.045408010482788086,
0.11968578398227692,
0.10771539062261581,
-0.03768594563007355,
0.030340006574988365,
-0.059191860258579254,
0.026922186836600304,
0.03653475642204285,
0.05085207149386406,
-0.038990993052721024,
-0.11297938227653503,
0.09846328943967819,
0.00009290316666010767,
-0.024848971515893936,
0.015962747856974602,
0.2218662053346634,
-0.020438507199287415,
0.04284776747226715,
-0.08081351965665817,
0.016542205587029457,
0.0018622579518705606,
0.017931783571839333,
0.0775117576122284,
0.13066786527633667,
0.05339471995830536,
-0.05305019021034241,
0.023215675726532936,
-0.1134507805109024,
0.04796968773007393,
0.009847461245954037,
-0.012626460753381252,
0.21354348957538605,
-0.07567325234413147,
-0.011120596900582314,
-0.0021391899790614843,
0.36368000507354736,
-0.034998081624507904,
-0.03947965055704117,
-0.0003200726059731096,
0.018490439280867577,
0.056894294917583466,
-0.06595032662153244,
0.24354076385498047,
0.03248678520321846,
0.026915378868579865,
-0.045648712664842606,
0.08008834719657898,
0.039073459804058075,
0.018556974828243256,
0.10789669305086136,
-0.05288293957710266,
-0.08341607451438904,
0.04072330519556999,
0.007909267209470272,
-0.06115194782614708,
-0.1530919373035431,
-0.09249581396579742,
-0.10105227679014206,
0.03402719274163246,
0.01646846905350685,
0.1808527261018753,
0.092348113656044,
0.0362519808113575,
0.03644612058997154,
0.044680528342723846,
-0.018664920702576637,
-0.11716790497303009,
-0.10500418394804001,
-0.06536605209112167,
-0.24604558944702148,
-0.01952730305492878,
-0.01912771910429001,
-0.03840333968400955,
0.12082155048847198,
0.00653251726180315,
0.03428143635392189,
0.19918376207351685,
-0.03354213386774063,
-0.059998322278261185,
-0.02879091538488865,
-0.04323379322886467,
-0.05230677127838135,
-0.0863572284579277,
0.0015172812854871154,
-0.004625207278877497,
0.13305146992206573,
0.04499693959951401,
0.015823571011424065,
-0.0726652443408966,
0.06213922053575516,
-0.035806041210889816,
-0.045911382883787155,
-0.14163394272327423,
0.001928873360157013,
-0.11616405844688416,
0.012727584689855576,
-0.05188954994082451,
0.005599526222795248,
0.012400805950164795,
0.10158265382051468,
-0.047617726027965546,
-0.15215027332305908,
-0.10272032022476196,
0.09241324663162231,
-0.09019617736339569,
0.03954029083251953,
-0.009012546390295029,
0.00629040040075779,
-0.03302996978163719,
0.18110992014408112,
0.1342141032218933,
-0.02625930681824684,
0.03846939280629158,
0.04397016763687134,
0.018062755465507507,
-0.007235268596559763,
0.13895313441753387,
-0.01986592262983322,
0.07473210990428925,
-0.028549568727612495,
-0.12138435989618301,
-0.07249752432107925,
0.017649412155151367,
0.10912179946899414,
0.08682022243738174,
0.019414901733398438,
0.0005556691903620958,
-0.05909574776887894,
0.0746980682015419,
-0.03608265519142151,
-0.03459202125668526,
0.004794461652636528,
0.005204625427722931,
-0.045692771673202515,
-0.026770656928420067,
0.07049356400966644,
-0.04326937347650528,
0.027518052607774734,
-0.010839353315532207,
-0.03750996291637421,
-0.02185272052884102,
0.10216748714447021,
-0.2628922164440155,
0.0315353125333786,
0.08901524543762207,
-0.003555664326995611,
0.23659907281398773,
-0.046441271901130676,
0.06689593195915222,
0.04330317676067352,
0.028808245435357094,
-0.1247711330652237,
0.021786484867334366,
-0.021062379702925682,
-0.10111837834119797,
-0.050942860543727875,
-0.030679447576403618,
-0.05712876841425896,
0.0016996056074276567,
0.018024614080786705,
-0.08806265145540237,
-0.0027608065865933895,
0.050118912011384964,
-0.0009374605142511427,
0.008443632163107395,
-0.08507417142391205,
-0.09702782332897186,
0.13383273780345917,
0.013544685207307339,
0.005954130087047815,
-0.0515630878508091,
-0.1324554830789566,
0.07368413358926773,
0.03343818709254265,
0.0967612937092781,
-0.03428277000784874,
-0.08286052942276001,
-0.08557553589344025,
0.003756727324798703,
0.006944849155843258,
-0.13757473230361938,
-0.0019162065582349896,
-0.04195171222090721,
-0.0295792818069458,
-0.04643866792321205,
0.1206413209438324,
0.07716703414916992,
0.08186215907335281,
-0.02600518986582756,
-0.006960775703191757,
0.007267984561622143,
0.08977925777435303,
-0.19107849895954132,
-0.04478580504655838
] |
null | null | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-CartPole-v1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{"type": "mean_reward", "value": "500.00 +/- 0.00", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | atmikah/Reinforce-CartPole-v1 | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | 2024-02-09T00:31:18+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
39,
54
] | [
"passage: TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
0.007526164408773184,
-0.12498430907726288,
-0.0013541718944907188,
0.09601131081581116,
0.11848696321249008,
-0.04186001420021057,
0.11405468732118607,
0.05624859035015106,
0.09539441019296646,
0.04239490255713463,
0.13636724650859833,
0.06906966865062714,
-0.004102868959307671,
0.12412862479686737,
0.09840741008520126,
-0.26058563590049744,
0.07420794665813446,
-0.04403980076313019,
-0.009944677352905273,
0.10139261186122894,
0.07836852967739105,
-0.08325441926717758,
0.051592715084552765,
0.00009572553972247988,
-0.044259943068027496,
0.0321260429918766,
0.013628939166665077,
-0.053157225251197815,
0.1606452465057373,
-0.07313758134841919,
0.10494591295719147,
-0.03843724727630615,
0.14574295282363892,
-0.1126825287938118,
0.04758213832974434,
0.05111503228545189,
-0.04548581689596176,
0.03848232328891754,
-0.12538743019104004,
-0.06033875793218613,
0.026815801858901978,
-0.015865681692957878,
0.12249194830656052,
0.03647647053003311,
-0.1777559220790863,
-0.13461355865001678,
-0.0165896974503994,
0.12325166910886765,
0.1627800315618515,
0.00512364786118269,
0.014270431362092495,
0.16791965067386627,
-0.1761058121919632,
0.025937072932720184,
0.11400806158781052,
-0.37275227904319763,
-0.00034436015994288027,
0.2240462601184845,
0.06164427846670151,
0.1252165287733078,
-0.12646614015102386,
0.010440526530146599,
0.07403992861509323,
0.04368630796670914,
0.049784936010837555,
-0.015430688858032227,
-0.12260042130947113,
0.08455035835504532,
-0.1383819431066513,
-0.058066487312316895,
0.1495426446199417,
-0.019741326570510864,
-0.009476418606936932,
-0.016515808179974556,
-0.009238536469638348,
-0.050979889929294586,
-0.03430935740470886,
-0.11778499186038971,
0.10755524039268494,
0.04975730925798416,
0.0038771627005189657,
-0.04602450504899025,
-0.05612579360604286,
-0.09815777093172073,
-0.03123871050775051,
0.0372777059674263,
-0.013706400990486145,
0.01091629359871149,
0.027692900970578194,
0.09935613721609116,
-0.13446329534053802,
0.01825822703540325,
-0.028096558526158333,
-0.028040969744324684,
-0.1316804438829422,
-0.11984307318925858,
-0.026084421202540398,
0.004223645199090242,
0.03029833547770977,
0.20433813333511353,
0.020139509811997414,
0.059011414647102356,
-0.0022708347532898188,
0.09776382148265839,
0.029780851677060127,
0.13517548143863678,
-0.04466623440384865,
0.19488364458084106,
0.07711011171340942,
0.05364556983113289,
0.03204274922609329,
-0.05344729498028755,
-0.19369827210903168,
0.04861246794462204,
0.06659778952598572,
0.08274952322244644,
-0.1178959533572197,
0.0059632807970047,
-0.10316018015146255,
0.0028950648847967386,
-0.10474003106355667,
-0.0642905905842781,
-0.02892979420721531,
0.031841445714235306,
-0.10535725951194763,
0.028785312548279762,
0.025052599608898163,
0.04140377417206764,
0.0676041767001152,
-0.12253966927528381,
-0.07404746115207672,
-0.021733485162258148,
-0.12817098200321198,
-0.09923440217971802,
0.08802318572998047,
-0.026199497282505035,
-0.005110981408506632,
-0.1253623217344284,
-0.2661486268043518,
-0.05670225992798805,
0.06396034359931946,
-0.03231031447649002,
-0.08589376509189606,
-0.1633463054895401,
0.026403428986668587,
-0.07700273394584656,
0.05221332609653473,
0.04776721075177193,
-0.03665859252214432,
0.02023705095052719,
-0.07958202809095383,
0.12739010155200958,
0.049698662012815475,
0.00541001046076417,
-0.09916839748620987,
0.07882837951183319,
-0.3034103214740753,
-0.02581131085753441,
-0.15228183567523956,
0.0772043839097023,
-0.07893010973930359,
0.01308529730886221,
0.05044940114021301,
0.043790437281131744,
-0.016942394897341728,
0.16269747912883759,
-0.17043575644493103,
-0.05301272124052048,
0.026445282623171806,
-0.09261117875576019,
-0.09916394203901291,
0.07275339215993881,
-0.06339669227600098,
0.21263530850410461,
0.08751397579908371,
0.17006252706050873,
-0.011036526411771774,
-0.16256992518901825,
0.1207515075802803,
0.07522942125797272,
-0.1639646589756012,
0.004287737421691418,
0.061784300953149796,
-0.0016935690073296428,
0.02746843732893467,
-0.01872866041958332,
-0.07289361208677292,
0.06302516162395477,
-0.07825060933828354,
0.022581040859222412,
0.06258945167064667,
-0.09531243145465851,
0.23986859619617462,
-0.005434412509202957,
0.0862451046705246,
-0.025957979261875153,
-0.09802921861410141,
0.00908072479069233,
0.07164718210697174,
-0.0014321404742076993,
0.01703714393079281,
-0.14553219079971313,
0.23044352233409882,
-0.07965081930160522,
0.011176814325153828,
-0.11607582122087479,
-0.1256982982158661,
0.011873425915837288,
0.13336114585399628,
0.059921663254499435,
0.16569606959819794,
0.09518871456384659,
-0.032197169959545135,
0.017584815621376038,
-0.0023385772947221994,
-0.09040450304746628,
0.01580043137073517,
-0.0021571461111307144,
-0.12167251110076904,
-0.07353103160858154,
-0.08134473115205765,
0.12585052847862244,
-0.20988115668296814,
0.015492538921535015,
0.04099845886230469,
0.008103687316179276,
0.04467369243502617,
0.023746047168970108,
-0.013269703835248947,
-0.00007021807687124237,
0.03244573250412941,
-0.10098352283239365,
0.12937165796756744,
0.013381263241171837,
0.014676140621304512,
-0.006365173030644655,
-0.05572463944554329,
0.03720450773835182,
0.040439579635858536,
-0.11237845569849014,
-0.11330515146255493,
-0.009658765979111195,
-0.0015364213613793254,
0.02637762948870659,
-0.022321155294775963,
0.052120618522167206,
0.27587956190109253,
0.05387469753623009,
0.10401033610105515,
-0.05769326910376549,
0.015315087512135506,
-0.015322818420827389,
-0.07135670632123947,
0.06358719617128372,
0.025013601407408714,
0.08050397783517838,
-0.03531401976943016,
0.03759452700614929,
0.1675453782081604,
-0.015888912603259087,
0.11127935349941254,
-0.06545067578554153,
-0.03844274953007698,
-0.043109722435474396,
0.05627678707242012,
0.015021559782326221,
0.04564907029271126,
0.0000015355876712419558,
-0.08444724231958389,
-0.03503387048840523,
-0.03988509997725487,
-0.010637006722390652,
-0.12273643165826797,
-0.00499896751716733,
0.01265440508723259,
-0.021940499544143677,
0.04488934203982353,
0.07375624030828476,
-0.04849626496434212,
0.025821007788181305,
0.06070821359753609,
-0.10193055868148804,
0.08957115560770035,
0.015067169442772865,
-0.06946801394224167,
0.13769419491291046,
-0.07484805583953857,
-0.045293889939785004,
-0.1025395318865776,
-0.1568877100944519,
0.09384927153587341,
0.06704871356487274,
-0.05427970737218857,
-0.1503879576921463,
-0.0016851738328114152,
-0.008973666466772556,
0.09206123650074005,
-0.006399387493729591,
-0.12621140480041504,
0.01989075168967247,
0.08295059949159622,
-0.05633419007062912,
-0.09804849326610565,
-0.0075809285044670105,
-0.05280788615345955,
-0.17707788944244385,
-0.03888550028204918,
-0.06398582458496094,
-0.06734282523393631,
0.23586803674697876,
0.02017230913043022,
0.08274748176336288,
-0.044721852988004684,
0.04250151664018631,
-0.012231717817485332,
0.0006326579605229199,
0.10689259320497513,
-0.09043551236391068,
-0.017900818958878517,
-0.001320177922025323,
-0.024820495396852493,
-0.07327181100845337,
0.029733488336205482,
-0.04272191599011421,
-0.08249637484550476,
-0.1415451467037201,
-0.04993678629398346,
-0.011005163192749023,
0.10754310339689255,
0.07337497919797897,
0.0048001972027122974,
-0.11733713001012802,
0.062058478593826294,
0.13692134618759155,
0.031207585707306862,
0.004062763415277004,
0.028157465159893036,
0.14977529644966125,
-0.10706274956464767,
-0.022463621571660042,
-0.038119975477457047,
-0.054863203316926956,
0.004114252515137196,
0.016883620992302895,
0.08840765058994293,
0.1410384476184845,
0.11468084901571274,
0.047563645988702774,
0.0464191697537899,
0.06561273336410522,
0.1694946140050888,
0.059157438576221466,
-0.10448314249515533,
-0.044678982347249985,
-0.0040070898830890656,
-0.10903503000736237,
0.057307638227939606,
0.16030821204185486,
0.06326017528772354,
-0.14463356137275696,
0.021787412464618683,
-0.038982175290584564,
0.13649246096611023,
0.020638149231672287,
-0.2677258849143982,
-0.008139112964272499,
0.023630544543266296,
-0.0010347915813326836,
-0.012379839085042477,
0.10821118950843811,
-0.040134772658348083,
-0.233198344707489,
-0.12299054861068726,
0.010077533312141895,
0.031144635751843452,
-0.1509784311056137,
0.015542911365628242,
-0.14036494493484497,
0.08027976751327515,
-0.007007129956036806,
0.07418135553598404,
-0.025149788707494736,
0.15060245990753174,
-0.028731435537338257,
0.01628703810274601,
-0.07902143895626068,
-0.047717493027448654,
0.09898673743009567,
-0.0046631391160190105,
0.1931537538766861,
0.005480166990309954,
-0.023713182657957077,
-0.12098433077335358,
-0.05229806900024414,
-0.04967813938856125,
0.010598190128803253,
-0.05373382940888405,
0.0765683576464653,
-0.02441473677754402,
-0.0039579677395522594,
-0.010900177992880344,
0.08942947536706924,
-0.05291692912578583,
0.03636563941836357,
-0.11246588081121445,
-0.05034820735454559,
0.14550213515758514,
-0.09163831174373627,
-0.10174685716629028,
-0.16205860674381256,
0.14137998223304749,
0.15070600807666779,
0.058216437697410583,
-0.04001476243138313,
0.03867831453680992,
-0.019183965399861336,
-0.024241572245955467,
0.07880574464797974,
0.009653856977820396,
0.1324782371520996,
-0.08983246237039566,
0.014327390119433403,
0.14589735865592957,
-0.05275948345661163,
0.016191845759749413,
-0.02304735779762268,
0.12202176451683044,
0.04650457948446274,
0.06189403310418129,
0.018547222018241882,
0.06655703485012054,
0.06466961652040482,
-0.02262885868549347,
0.08456692099571228,
0.030712679028511047,
-0.18644161522388458,
0.058530256152153015,
-0.09805119782686234,
0.22581584751605988,
0.05066308751702309,
0.06047345697879791,
0.2993181645870209,
0.21986234188079834,
-0.05372472479939461,
0.1669820249080658,
0.044286344200372696,
-0.05891284719109535,
-0.21245966851711273,
-0.03684934973716736,
-0.030655447393655777,
0.09436552971601486,
0.15607263147830963,
-0.0981721356511116,
-0.04201313853263855,
-0.00972361396998167,
-0.032264553010463715,
0.020120708271861076,
-0.24663487076759338,
-0.01734781451523304,
0.14379777014255524,
0.10629188269376755,
0.2451348900794983,
-0.006132842972874641,
0.023609744384884834,
0.049030207097530365,
0.018605992197990417,
-0.02483358606696129,
-0.21013511717319489,
0.09079083055257797,
0.006071676965802908,
0.04935038834810257,
0.022885039448738098,
-0.006052911281585693,
0.04500092566013336,
-0.073696069419384,
0.08904470503330231,
-0.08561883866786957,
-0.08341272175312042,
0.2185351401567459,
-0.03945168852806091,
-0.00661163916811347,
0.12917985022068024,
-0.011526807211339474,
-0.1097102016210556,
-0.015364703722298145,
0.027403371408581734,
0.030678823590278625,
-0.030246863141655922,
-0.03609466925263405,
0.024012766778469086,
0.10202405601739883,
-0.04282205551862717,
0.04565315693616867,
0.10240072011947632,
-0.020902957767248154,
0.15945613384246826,
0.13205459713935852,
0.10420060157775879,
0.002927543595433235,
-0.06464727967977524,
0.014349685050547123,
-0.055471502244472504,
0.02962767891585827,
-0.17038846015930176,
-0.0070191239938139915,
0.055695805698633194,
0.04772466421127319,
0.0945243164896965,
0.11333164572715759,
-0.127106174826622,
0.0300484336912632,
0.028996523469686508,
-0.06286120414733887,
-0.06029998138546944,
-0.002275418024510145,
-0.016458535566926003,
-0.008173024281859398,
-0.09947093576192856,
0.07884971052408218,
-0.10555081814527512,
-0.03306307643651962,
0.05025126785039902,
-0.0607193186879158,
-0.12852220237255096,
-0.010904680006206036,
0.1252979338169098,
0.061709314584732056,
-0.05078592896461487,
0.14939077198505402,
0.06109785661101341,
-0.08055379986763,
0.037185851484537125,
0.027442200109362602,
-0.08008874952793121,
-0.10198270529508591,
-0.0004569833690766245,
0.31761088967323303,
0.06076094135642052,
-0.0329466350376606,
-0.11946453154087067,
-0.15002015233039856,
0.04840146750211716,
0.1035679280757904,
0.12359631806612015,
0.011757869273424149,
-0.05322748050093651,
0.02236519381403923,
-0.05275069922208786,
0.03814244270324707,
0.06910209357738495,
-0.03928454965353012,
-0.13761694729328156,
0.0077122850343585014,
0.026647454127669334,
0.10174071043729782,
-0.06771174818277359,
-0.09184598177671432,
-0.18085066974163055,
0.09208621084690094,
-0.03432070091366768,
-0.10890032351016998,
0.027215104550123215,
-0.017406610772013664,
0.014248576015233994,
0.07639352232217789,
-0.047281619161367416,
0.01244808267802,
-0.1517520695924759,
0.07082249224185944,
0.05706808716058731,
0.08926787972450256,
0.000014311663107946515,
-0.054843269288539886,
0.07618319988250732,
-0.05763502046465874,
0.06680037826299667,
-0.053477559238672256,
0.005539732985198498,
0.10781200975179672,
-0.23264040052890778,
-0.021164139732718468,
0.009476077742874622,
-0.04681631922721863,
0.08765807747840881,
-0.19047698378562927,
0.024190550670027733,
-0.08897756040096283,
-0.024605726823210716,
0.01802127994596958,
-0.1086471825838089,
-0.04306677728891373,
0.08475461602210999,
0.037119291722774506,
-0.031288959085941315,
-0.04612116143107414,
-0.019314980134367943,
-0.0914498046040535,
0.053634315729141235,
0.07442525774240494,
-0.0687926784157753,
0.08314394950866699,
-0.05507456883788109,
0.00841207429766655,
-0.052043743431568146,
0.06760627031326294,
-0.012366239912807941,
-0.12672528624534607,
-0.02123171091079712,
-0.044928714632987976,
0.11662110686302185,
-0.023402327671647072,
0.022080281749367714,
0.014599837362766266,
0.0323631577193737,
-0.012065601535141468,
0.05028461292386055,
0.1019197478890419,
0.05136820673942566,
0.014879679307341576,
0.02292765863239765,
0.055746350437402725,
0.0757644772529602,
-0.1134679913520813,
0.06457309424877167,
-0.02098844014108181,
-0.08620109409093857,
0.1013324111700058,
0.06909440457820892,
0.037490107119083405,
0.15593400597572327,
0.22674402594566345,
0.10539932548999786,
-0.03564648702740669,
-0.03126971051096916,
0.12967991828918457,
0.17799612879753113,
-0.07682197540998459,
0.015780627727508545,
-0.0020607721526175737,
-0.017265556380152702,
-0.09849067777395248,
-0.13722245395183563,
-0.060460351407527924,
-0.2453264594078064,
0.1078341007232666,
-0.03288164362311363,
-0.04169659689068794,
0.128489688038826,
0.027952738106250763,
0.03724630922079086,
0.08183616399765015,
-0.12909026443958282,
-0.013460557907819748,
0.07749562710523605,
-0.08914026618003845,
-0.033571500331163406,
-0.17521262168884277,
-0.06771576404571533,
-0.08741120994091034,
-0.15989220142364502,
-0.06844990700483322,
0.029948782175779343,
0.035394806414842606,
0.010386589914560318,
-0.039711855351924896,
-0.01962728053331375,
0.011063394136726856,
-0.0025537724141031504,
-0.04985455423593521,
-0.01753084547817707,
0.021317757666110992,
-0.11333847790956497,
-0.024336790665984154,
0.16320326924324036,
-0.03297848999500275,
-0.18396754562854767,
-0.0405106395483017,
0.2157316505908966,
0.025046708062291145,
0.0590171180665493,
-0.073721744120121,
-0.016323629766702652,
0.021523483097553253,
0.20813441276550293,
0.10171995311975479,
-0.10821312665939331,
0.015457749366760254,
-0.03655189648270607,
0.0013793212128803134,
-0.061893612146377563,
0.10775819420814514,
0.06519263982772827,
-0.07549984753131866,
-0.17567221820354462,
-0.04389495030045509,
-0.08628730475902557,
0.03370477631688118,
-0.14383791387081146,
-0.03786516562104225,
0.1168690100312233,
0.004516853019595146,
-0.053927481174468994,
0.07883694022893906,
-0.17713546752929688,
0.03441957011818886,
-0.04880853369832039,
-0.13215437531471252,
-0.09491758048534393,
-0.10123858600854874,
0.0027463934384286404,
0.08913854509592056,
0.15567956864833832,
-0.06151591241359711,
-0.07471925020217896,
-0.009579092264175415,
-0.028091613203287125,
-0.052700337022542953,
-0.07900123298168182,
0.059512585401535034,
0.0007560851518064737,
0.16147300601005554,
-0.07439453154802322,
0.09558981657028198,
0.09099138528108597,
-0.021246420219540596,
-0.00915549136698246,
0.032866667956113815,
-0.003863809397444129,
-0.07436864078044891,
-0.04970616102218628,
0.02312966249883175,
0.027639856562018394,
0.10846075415611267,
-0.030836544930934906,
-0.1934703141450882,
0.11230092495679855,
0.09140218049287796,
-0.04296138137578964,
-0.046487610787153244,
0.05351927503943443,
-0.07097935676574707,
0.1252279132604599,
0.03444884717464447,
-0.02163051813840866,
0.013762647286057472,
-0.06370721012353897,
0.08370721340179443,
0.11594565212726593,
-0.048265840858221054,
-0.08278503268957138,
-0.06164652109146118,
0.012770666740834713,
0.02961382456123829,
-0.13650155067443848,
-0.21160630881786346,
-0.10802312940359116,
-0.1383298933506012,
0.004740108735859394,
-0.04703504592180252,
0.08498300611972809,
0.12991970777511597,
0.09780163317918777,
-0.011416295543313026,
-0.004867587238550186,
0.018085451796650887,
0.13192623853683472,
-0.11232008039951324,
-0.08192373812198639
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-squad-model2
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 29
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "t5-base", "model-index": [{"name": "t5-base-squad-model2", "results": []}]} | question-answering | varun-v-rao/t5-base-squad-model2 | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"question-answering",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:t5-base",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T00:46:23+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us
|
# t5-base-squad-model2
This model is a fine-tuned version of t5-base on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 29
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# t5-base-squad-model2\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 29\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us \n",
"# t5-base-squad-model2\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 29\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
80,
30,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us \n# t5-base-squad-model2\n\nThis model is a fine-tuned version of t5-base on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 29\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.08203426003456116,
0.11065910011529922,
-0.0016819997690618038,
0.10047750920057297,
0.13935765624046326,
0.021811259910464287,
0.1232818216085434,
0.12609174847602844,
-0.10761711001396179,
0.052224718034267426,
0.05730501934885979,
0.057896990329027176,
0.04485779255628586,
0.11282007396221161,
-0.02528274990618229,
-0.2181137353181839,
0.00674412539228797,
-0.017664499580860138,
-0.06751634925603867,
0.11600388586521149,
0.10401846468448639,
-0.09369777143001556,
0.08458360284566879,
-0.01536895614117384,
-0.13385753333568573,
0.05674915760755539,
-0.008593970909714699,
-0.04556487128138542,
0.1148277223110199,
0.0292197372764349,
0.08440659195184708,
0.0031005952041596174,
0.14328448474407196,
-0.2360157072544098,
0.007167720701545477,
0.09813667833805084,
0.00748076057061553,
0.06843788176774979,
0.03740604966878891,
-0.0018520555458962917,
0.10350238531827927,
-0.15865254402160645,
0.10004507750272751,
0.03878706693649292,
-0.07642459869384766,
-0.13487090170383453,
-0.07771722227334976,
0.08009575307369232,
0.10488855838775635,
0.10614199936389923,
0.0036161362659186125,
0.16207021474838257,
-0.07477714866399765,
0.0924118310213089,
0.19894006848335266,
-0.2821524143218994,
-0.059205278754234314,
0.07556156069040298,
0.06090913712978363,
0.10106809437274933,
-0.10405018925666809,
-0.015184828080236912,
0.04834911599755287,
0.023327132686972618,
0.08920154720544815,
-0.021891748532652855,
-0.11641500145196915,
0.02463279850780964,
-0.1409067064523697,
-0.012454265728592873,
0.18342973291873932,
0.06453432142734528,
-0.03854474797844887,
-0.06814708560705185,
-0.07360224425792694,
-0.06922393292188644,
-0.011472287587821484,
-0.05691900849342346,
0.04654105007648468,
-0.04427015036344528,
-0.049448687583208084,
-0.0543418824672699,
-0.08723228424787521,
-0.08563282340765,
-0.003315844340249896,
0.07273577898740768,
0.05487615987658501,
0.013492857106029987,
-0.04625789076089859,
0.1016843169927597,
-0.01537109911441803,
-0.10760919004678726,
-0.01696527935564518,
0.009772291406989098,
-0.08706949651241302,
-0.054935604333877563,
-0.013483302667737007,
-0.0505877323448658,
0.02547444961965084,
0.13777664303779602,
-0.0637887641787529,
0.0465933233499527,
0.004280639812350273,
-0.0014779255725443363,
-0.02938738279044628,
0.11518240720033646,
-0.07290060818195343,
-0.05045764520764351,
0.02839493751525879,
0.09319821000099182,
0.034780312329530716,
-0.0010145240230485797,
-0.0891706719994545,
-0.016580546274781227,
0.10572154074907303,
0.0833943784236908,
-0.02567404881119728,
0.049311645328998566,
-0.011267566122114658,
-0.02371101826429367,
0.02131064049899578,
-0.13933978974819183,
0.024422312155365944,
-0.017641019076108932,
-0.07245379686355591,
-0.07182565331459045,
0.04119158908724785,
0.003018931718543172,
-0.032783765345811844,
0.04196704179048538,
-0.084658682346344,
-0.014320101588964462,
-0.08003704994916916,
-0.08453567326068878,
0.02190585993230343,
-0.042268600314855576,
-0.006239903159439564,
-0.08397714793682098,
-0.22812014818191528,
-0.02947826310992241,
0.025679755955934525,
-0.043448444455862045,
-0.04211566597223282,
-0.04883703589439392,
-0.07357145845890045,
-0.01058946456760168,
-0.0013880670303478837,
0.10782884061336517,
-0.05678074434399605,
0.07936554402112961,
0.0013707062462344766,
0.021084612235426903,
0.013774935156106949,
0.025708990171551704,
-0.10554298013448715,
0.020312868058681488,
-0.1328088641166687,
0.0408746674656868,
-0.07812254130840302,
0.04484803229570389,
-0.12091714888811111,
-0.09278690069913864,
0.008809794671833515,
-0.015884162858128548,
0.04437942057847977,
0.12369334697723389,
-0.1855294555425644,
-0.004611751064658165,
0.15372924506664276,
-0.09717994183301926,
-0.11696331202983856,
0.1087268516421318,
-0.04224224016070366,
0.038175612688064575,
0.07226137071847916,
0.1623501479625702,
0.10458196699619293,
-0.140941321849823,
0.003137905616313219,
-0.001475414028391242,
0.036074891686439514,
0.004176894668489695,
0.06135927140712738,
-0.002956051379442215,
0.004164284095168114,
0.0032498163636773825,
-0.07936974614858627,
0.0052977269515395164,
-0.07823508977890015,
-0.08737517148256302,
-0.06409076601266861,
-0.10246732831001282,
0.026003535836935043,
0.043303586542606354,
0.016304997727274895,
-0.07806644588708878,
-0.11747787892818451,
0.10947192460298538,
0.1295355260372162,
-0.05447714775800705,
0.009679285809397697,
-0.08265732228755951,
0.042539872229099274,
-0.032439086586236954,
-0.023731838911771774,
-0.17116858065128326,
-0.14106233417987823,
0.023132504895329475,
-0.06324435025453568,
0.05023927614092827,
0.023707780987024307,
0.0643409937620163,
0.07433830946683884,
-0.0660671517252922,
-0.031057516112923622,
-0.06877744197845459,
0.01557842455804348,
-0.08195603638887405,
-0.21471291780471802,
-0.03588913008570671,
-0.01868412271142006,
0.1298980712890625,
-0.25154557824134827,
0.03277813270688057,
-0.03579235076904297,
0.11871139705181122,
0.02735299803316593,
-0.03568169102072716,
0.008799893781542778,
0.030654918402433395,
-0.01761370338499546,
-0.09334834665060043,
0.02953750267624855,
-0.00798723567277193,
-0.07572582364082336,
-0.06182793155312538,
-0.1562979817390442,
0.08442869782447815,
0.07468972355127335,
0.05078939348459244,
-0.09981214255094528,
0.01802113652229309,
-0.060191307216882706,
-0.04740860313177109,
-0.0822826400399208,
-0.016620447859168053,
0.13082420825958252,
-0.005218698177486658,
0.11073101311922073,
-0.07124467939138412,
-0.06938707828521729,
-0.0030648070387542248,
-0.003574098227545619,
0.003877786686643958,
0.09040279686450958,
0.06799999624490738,
-0.1366758942604065,
0.09747496247291565,
0.08202674984931946,
-0.0530635342001915,
0.14081278443336487,
-0.06021961197257042,
-0.08006232231855392,
-0.02787468209862709,
0.03477795422077179,
-0.006478535942733288,
0.1485806703567505,
-0.10286147892475128,
0.013221804052591324,
0.017640527337789536,
0.0018373554339632392,
0.02076488547027111,
-0.17467308044433594,
-0.028166593983769417,
0.023242764174938202,
-0.06101435050368309,
-0.018843401223421097,
-0.02601606585085392,
0.023096144199371338,
0.10145694017410278,
0.002366049215197563,
-0.02897617407143116,
0.018103105947375298,
-0.009453465230762959,
-0.10723848640918732,
0.1934753805398941,
-0.10575251281261444,
-0.1439254730939865,
-0.11340662091970444,
0.06810970604419708,
-0.06246214732527733,
-0.0308392234146595,
0.03136938437819481,
-0.08371525257825851,
-0.05580437555909157,
-0.12384680658578873,
-0.0035811217967420816,
-0.014981596730649471,
-0.017834370955824852,
-0.004304408095777035,
0.032214779406785965,
0.0916433334350586,
-0.14602679014205933,
0.02513333223760128,
-0.010214286856353283,
-0.11595380306243896,
-0.019705314189195633,
0.048061955720186234,
0.12851525843143463,
0.1370251476764679,
-0.024196280166506767,
0.012743480503559113,
-0.037169162184000015,
0.20919540524482727,
-0.05931224301457405,
0.03139904886484146,
0.12785936892032623,
0.018199646845459938,
0.04417696222662926,
0.14763540029525757,
0.02663147635757923,
-0.0875212699174881,
0.046175796538591385,
0.08430948853492737,
-0.01416543498635292,
-0.2581101357936859,
-0.0328667014837265,
-0.024120105430483818,
-0.047712359577417374,
0.06342551112174988,
0.06912191957235336,
0.04689537733793259,
0.037433870136737823,
-0.013472075574100018,
0.025945434346795082,
0.003928810823708773,
0.07926645874977112,
0.08558339625597,
0.03269090875983238,
0.08856114000082016,
-0.048979006707668304,
-0.033467113971710205,
0.06326423585414886,
0.017657475546002388,
0.25229761004447937,
-0.02271505631506443,
0.10112053155899048,
0.05118168145418167,
0.15683159232139587,
-0.029653795063495636,
0.035017210990190506,
0.009002422913908958,
-0.002042410895228386,
0.016783561557531357,
-0.06791169196367264,
0.0025461879558861256,
0.041515786200761795,
-0.057395849376916885,
0.060874905437231064,
-0.068589948117733,
0.05379288271069527,
0.03563915193080902,
0.24404042959213257,
0.032409582287073135,
-0.27998846769332886,
-0.07990856468677521,
0.014964614063501358,
-0.03418358042836189,
-0.04984736070036888,
0.03206649422645569,
0.1380094587802887,
-0.09632910043001175,
0.04732443764805794,
-0.05211436748504639,
0.07962179183959961,
-0.01594449207186699,
-0.0075072115287184715,
0.05710288882255554,
0.12012013047933578,
-0.02128790318965912,
0.10063663125038147,
-0.2166779488325119,
0.22474704682826996,
0.02306962013244629,
0.11467930674552917,
-0.04933800920844078,
0.02035774476826191,
0.0053285215981304646,
0.11065708845853806,
0.12913918495178223,
-0.0028388691134750843,
-0.043949488550424576,
-0.1578037440776825,
-0.06272520124912262,
0.052077338099479675,
0.09311274439096451,
-0.020066361874341965,
0.08690434694290161,
-0.05804290622472763,
-0.005620360374450684,
0.06763733178377151,
-0.06264840811491013,
-0.1985548436641693,
-0.10730865597724915,
-0.0036960726138204336,
0.0016432296251878142,
-0.04018862545490265,
-0.09671155363321304,
-0.08948107063770294,
-0.02809663489460945,
0.16383324563503265,
-0.001958026085048914,
-0.04974992573261261,
-0.1261710524559021,
0.06725040823221207,
0.10797668248414993,
-0.0646156445145607,
0.017600789666175842,
0.02146616019308567,
0.10471723973751068,
0.05175989121198654,
-0.0892481878399849,
0.07135740667581558,
-0.06995679438114166,
-0.1613006293773651,
-0.055670663714408875,
0.12543712556362152,
0.055881645530462265,
0.043846242129802704,
0.004189259838312864,
0.004420515149831772,
0.01956389658153057,
-0.08848829567432404,
-0.0033884146250784397,
0.07291977852582932,
0.06464040279388428,
0.04845638573169708,
-0.09569904208183289,
-0.017740342766046524,
-0.047430768609046936,
-0.03355620428919792,
0.1178261861205101,
0.19159311056137085,
-0.08107860386371613,
0.06473159044981003,
0.08965755254030228,
-0.08301001042127609,
-0.1728755682706833,
0.06225203722715378,
0.049066197127103806,
0.0008080843253992498,
0.06920042634010315,
-0.1517707258462906,
0.12300257384777069,
0.10514790564775467,
-0.018518876284360886,
0.054399482905864716,
-0.3470129668712616,
-0.14532333612442017,
0.08914636820554733,
0.14560599625110626,
-0.005960289388895035,
-0.16490374505519867,
-0.030502209439873695,
-0.016083769500255585,
-0.1359817087650299,
0.10893117636442184,
-0.13768933713436127,
0.08253955096006393,
-0.00026527553563937545,
0.08668804168701172,
0.01939386874437332,
-0.03721144422888756,
0.11609484255313873,
0.02551165223121643,
0.09845961630344391,
-0.06799408048391342,
0.004090990871191025,
0.12202411144971848,
-0.06842152029275894,
0.07554556429386139,
-0.05600649490952492,
0.08924535661935806,
-0.12343239784240723,
-0.018662482500076294,
-0.06974511593580246,
0.06301376223564148,
-0.06003523990511894,
-0.07463063299655914,
-0.05719956383109093,
0.06704091280698776,
0.05832669138908386,
-0.04029722511768341,
0.0761159136891365,
0.011258282698690891,
0.1251584142446518,
0.09779548645019531,
0.11059221625328064,
0.0016993448371067643,
-0.07672754675149918,
0.0016073068836703897,
-0.023860277608036995,
0.04791044443845749,
-0.13239021599292755,
0.028565317392349243,
0.11307202279567719,
0.052475620061159134,
0.1350308656692505,
0.029281631112098694,
-0.05494968593120575,
-0.015283954329788685,
0.037219129502773285,
-0.125030517578125,
-0.20573846995830536,
-0.010783643461763859,
-0.05459095537662506,
-0.14594946801662445,
0.045736297965049744,
0.09316933155059814,
-0.0742952898144722,
-0.007726536598056555,
-0.014944418333470821,
0.041779328137636185,
-0.029310202226042747,
0.17227770388126373,
0.06993696838617325,
0.0666336938738823,
-0.07038680464029312,
0.11917293071746826,
0.07921918481588364,
-0.05351634323596954,
0.04036644473671913,
0.08012387901544571,
-0.08917611092329025,
-0.03246812894940376,
0.08563706278800964,
0.1748948097229004,
-0.057068198919296265,
-0.05516095831990242,
-0.10063402354717255,
-0.0881732702255249,
0.03032350353896618,
0.16660967469215393,
0.031203122809529305,
-0.0064057703129947186,
-0.008465597406029701,
0.02831769920885563,
-0.13557547330856323,
0.126370370388031,
0.04006581008434296,
0.07544855773448944,
-0.16219913959503174,
0.0995279997587204,
0.015190532431006432,
0.03393395617604256,
-0.018613815307617188,
0.043497730046510696,
-0.10083047300577164,
-0.01461636833846569,
-0.1519405096769333,
-0.007456901017576456,
-0.026274241507053375,
0.019984712824225426,
-0.005987163167446852,
-0.061662133783102036,
-0.051929865032434464,
0.06030148267745972,
-0.05410182103514671,
-0.050631288439035416,
0.030743155628442764,
0.06110898032784462,
-0.16860979795455933,
-0.011856782250106335,
0.015411213040351868,
-0.07966632395982742,
0.07222895324230194,
0.029703330248594284,
0.014420103281736374,
0.04282423481345177,
-0.14985914528369904,
0.018866805359721184,
0.017326224595308304,
0.033474572002887726,
0.05862177908420563,
-0.09955675899982452,
-0.010173297487199306,
-0.020631220191717148,
0.029267294332385063,
0.021570216864347458,
0.04168185964226723,
-0.11116240173578262,
0.0005896546645089984,
-0.06769615411758423,
-0.04622781276702881,
-0.05762898176908493,
0.03538770601153374,
0.09862358123064041,
0.007701965048909187,
0.1577652543783188,
-0.09091487526893616,
0.03426823392510414,
-0.22259698808193207,
-0.03212129324674606,
0.010042262263596058,
-0.0228367131203413,
-0.0793195515871048,
-0.023865986615419388,
0.0679468959569931,
-0.06847453862428665,
0.11063585430383682,
-0.0036619023885577917,
0.10561728477478027,
0.04649045318365097,
-0.029406826943159103,
0.01965114288032055,
0.007273469585925341,
0.18516680598258972,
0.0151735320687294,
-0.020603863522410393,
0.06997286528348923,
-0.03127337619662285,
0.05613738298416138,
-0.0060507310554385185,
0.19055671989917755,
0.15152166783809662,
-0.05353768169879913,
0.04778154566884041,
0.08553119748830795,
-0.1068502813577652,
-0.11674223095178604,
0.08999370038509369,
-0.019115183502435684,
0.10151840001344681,
-0.04922805353999138,
0.17778100073337555,
0.14968349039554596,
-0.15752805769443512,
0.03633855655789375,
-0.0610618032515049,
-0.11081690341234207,
-0.10852128267288208,
-0.06572961807250977,
-0.08481204509735107,
-0.1328619122505188,
0.019075242802500725,
-0.1298137754201889,
0.032141249626874924,
0.07746420800685883,
0.015038161538541317,
0.0030878332909196615,
0.1756582260131836,
0.006690336391329765,
0.02804037556052208,
0.0273228008300066,
0.01993599161505699,
-0.012421145103871822,
-0.04692392796278,
-0.03959842398762703,
0.06181535869836807,
-0.006068205926567316,
0.04533436521887779,
-0.044913966208696365,
0.007133117876946926,
0.048172302544116974,
-0.022874677553772926,
-0.05874646082520485,
0.025853140279650688,
0.020210616290569305,
0.028318269178271294,
0.06020994856953621,
0.06825204938650131,
-0.006749590393155813,
-0.022413291037082672,
0.2913503050804138,
-0.06826803088188171,
-0.11473216116428375,
-0.12076225131750107,
0.19183537364006042,
0.019776014611124992,
-0.012969044968485832,
0.06860006600618362,
-0.1380060911178589,
0.012909915298223495,
0.174852192401886,
0.15461546182632446,
-0.03979024291038513,
-0.011400857008993626,
-0.027632329612970352,
-0.01663077622652054,
-0.06294157356023788,
0.10657313466072083,
0.10595066845417023,
0.04904169961810112,
-0.04918203502893448,
-0.01952115260064602,
-0.01526995375752449,
-0.01972854882478714,
-0.07680432498455048,
0.07980167865753174,
0.03262222558259964,
0.006688468623906374,
-0.01735103875398636,
0.09396477043628693,
-0.01063530147075653,
-0.19190864264965057,
0.024616317823529243,
-0.14110402762889862,
-0.15609735250473022,
-0.0361553318798542,
0.11560121923685074,
-0.032187577337026596,
0.029838135465979576,
-0.020610982552170753,
0.0005054640932939947,
0.113372303545475,
-0.004489431623369455,
-0.08595030754804611,
-0.1162530928850174,
0.07719866186380386,
-0.07633582502603531,
0.24955369532108307,
-0.008075480349361897,
0.0555214062333107,
0.11538003385066986,
-0.007117745000869036,
-0.14202676713466644,
0.07729125022888184,
0.06789766997098923,
-0.06081691011786461,
0.032159723341464996,
0.14066456258296967,
-0.03585924953222275,
0.11388671398162842,
0.036539532244205475,
-0.09537190943956375,
-0.009882474318146706,
-0.0319940522313118,
-0.025911763310432434,
-0.09945324063301086,
0.007515639998018742,
-0.07273634523153305,
0.15190492570400238,
0.17252972722053528,
-0.043357089161872864,
0.034151289612054825,
-0.09220965206623077,
0.030094072222709656,
0.06374706327915192,
0.08068882673978806,
0.009965452365577221,
-0.19652359187602997,
0.03607618063688278,
-0.003618159331381321,
0.028011173009872437,
-0.2549375891685486,
-0.08641305565834045,
0.044443171471357346,
-0.048889193683862686,
-0.07121796160936356,
0.11605814844369888,
0.12553712725639343,
0.045848459005355835,
-0.03825660049915314,
-0.12923865020275116,
-0.04617660865187645,
0.1607503592967987,
-0.15580075979232788,
-0.062290191650390625
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# speech-emotion-recognition
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5578
- Accuracy: 0.8225
- Precision: 0.8278
- Recall: 0.8225
- F1: 0.8212
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.3499 | 1.0 | 394 | 1.2619 | 0.7120 | 0.7251 | 0.7120 | 0.7116 |
| 0.6955 | 2.0 | 788 | 0.7781 | 0.7799 | 0.7919 | 0.7799 | 0.7793 |
| 0.8665 | 3.0 | 1182 | 0.5578 | 0.8225 | 0.8278 | 0.8225 | 0.8212 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "jonatasgrosman/wav2vec2-large-xlsr-53-english", "model-index": [{"name": "speech-emotion-recognition", "results": []}]} | audio-classification | Firdho/speech-emotion-recognition | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"base_model:jonatasgrosman/wav2vec2-large-xlsr-53-english",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-09T00:47:14+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #wav2vec2 #audio-classification #generated_from_trainer #base_model-jonatasgrosman/wav2vec2-large-xlsr-53-english #license-apache-2.0 #endpoints_compatible #region-us
| speech-emotion-recognition
==========================
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-english on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5578
* Accuracy: 0.8225
* Precision: 0.8278
* Recall: 0.8225
* F1: 0.8212
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 10
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 5\n* total\\_train\\_batch\\_size: 10\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #wav2vec2 #audio-classification #generated_from_trainer #base_model-jonatasgrosman/wav2vec2-large-xlsr-53-english #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 5\n* total\\_train\\_batch\\_size: 10\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
79,
159,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #wav2vec2 #audio-classification #generated_from_trainer #base_model-jonatasgrosman/wav2vec2-large-xlsr-53-english #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 5\n* total\\_train\\_batch\\_size: 10\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.10518699884414673,
0.12368115037679672,
-0.0036324546672403812,
0.05787859857082367,
0.09098057448863983,
0.01870361901819706,
0.12383855879306793,
0.13973352313041687,
-0.07820570468902588,
0.10721492022275925,
0.10307864844799042,
0.09557756781578064,
0.06550167500972748,
0.14174418151378632,
-0.02608625404536724,
-0.27936992049217224,
0.024250688031315804,
-0.0010042646899819374,
-0.12884199619293213,
0.10901656746864319,
0.07783406227827072,
-0.10419812798500061,
0.04499935358762741,
0.00943443551659584,
-0.10569141805171967,
-0.0010024885414168239,
-0.029574507847428322,
-0.05615762621164322,
0.09061374515295029,
0.050998784601688385,
0.08019616454839706,
0.05528383329510689,
0.0693289041519165,
-0.2692255675792694,
0.01702243648469448,
0.0585995614528656,
0.004156877286732197,
0.0742829367518425,
0.11594434827566147,
-0.01911466382443905,
0.09702914208173752,
-0.09241627901792526,
0.07781436294317245,
0.035759590566158295,
-0.10062076896429062,
-0.29362648725509644,
-0.0932949110865593,
0.044710371643304825,
0.1449705809354782,
0.06402264535427094,
-0.025038041174411774,
0.07225974649190903,
-0.06492764502763748,
0.08099097013473511,
0.25851431488990784,
-0.2722908556461334,
-0.07016978412866592,
0.01582910120487213,
0.06908035278320312,
0.06604558974504471,
-0.1164911612868309,
-0.014119277708232403,
0.0316573791205883,
0.019537145271897316,
0.1231597289443016,
-0.0010802409378811717,
0.0778493881225586,
0.0045996373519301414,
-0.1419505476951599,
-0.038608115166425705,
0.11062608659267426,
0.0953473150730133,
-0.024640478193759918,
-0.11363878846168518,
-0.019372230395674706,
-0.2139604091644287,
-0.0463525615632534,
-0.007649964652955532,
0.03183777257800102,
-0.044764287769794464,
-0.08719607442617416,
0.026922890916466713,
-0.061672016978263855,
-0.06738130003213882,
0.03189905732870102,
0.1327858567237854,
0.044709958136081696,
-0.028520604595541954,
0.025158118456602097,
0.09809023141860962,
0.028498342260718346,
-0.1579609364271164,
0.00971533078700304,
0.0226243007928133,
-0.11338963359594345,
-0.03839028254151344,
-0.00971190631389618,
-0.034093983471393585,
0.025176580995321274,
0.1510128527879715,
-0.0421200729906559,
0.09286996722221375,
0.039145972579717636,
0.02903996780514717,
-0.06514078378677368,
0.12250436097383499,
-0.04832005500793457,
-0.10377759486436844,
-0.04735938832163811,
0.11973683536052704,
0.025796646252274513,
-0.018382182344794273,
-0.09513295441865921,
0.037667009979486465,
0.09926386177539825,
0.034234434366226196,
-0.012242969125509262,
0.0026736133731901646,
-0.08993225544691086,
-0.03745439648628235,
0.04715617373585701,
-0.08801983296871185,
0.06204666942358017,
0.030281146988272667,
-0.026649488136172295,
-0.006082155741751194,
-0.017654554918408394,
0.03446243330836296,
0.014119871892035007,
0.15174610912799835,
-0.06381433457136154,
-0.0071845948696136475,
-0.060021184384822845,
-0.08802450448274612,
0.043445002287626266,
-0.06472112238407135,
0.01468653418123722,
-0.05760057643055916,
-0.0706615224480629,
-0.04952007904648781,
0.07985640317201614,
-0.04924006015062332,
-0.08054304867982864,
-0.05833514407277107,
-0.06019287928938866,
0.0633416622877121,
-0.01651502586901188,
0.13328704237937927,
-0.07266650348901749,
0.09117665141820908,
0.0007302952581085265,
0.06891779601573944,
0.046457190066576004,
0.05962762236595154,
-0.041066963225603104,
0.0635981485247612,
-0.21413567662239075,
0.048915568739175797,
-0.0867675170302391,
0.04070555791258812,
-0.14962004125118256,
-0.09293115884065628,
-0.012902756221592426,
-0.0005041087861172855,
0.06218266487121582,
0.08693911135196686,
-0.17064417898654938,
-0.11007576435804367,
0.1439054161310196,
-0.08406856656074524,
-0.09024518728256226,
0.14188291132450104,
-0.01501381490379572,
-0.052840691059827805,
0.028036149218678474,
0.1643662005662918,
0.1294102519750595,
-0.11360223591327667,
-0.012395652942359447,
-0.05729973688721657,
0.11456552892923355,
0.0350639745593071,
0.11614243686199188,
-0.04059140011668205,
0.023082785308361053,
-0.012744666077196598,
-0.0225830078125,
0.05362006649374962,
-0.06535537540912628,
-0.07911815494298935,
-0.005875011906027794,
-0.07000228762626648,
0.037001896649599075,
0.04581817612051964,
0.01974535547196865,
-0.0934377983212471,
-0.1351962834596634,
0.02548946999013424,
0.09492076933383942,
-0.08113622665405273,
0.027521494776010513,
-0.061295170336961746,
0.08435548841953278,
-0.06254883110523224,
-0.020041627809405327,
-0.14389654994010925,
-0.00886415783315897,
0.032823629677295685,
-0.07310757786035538,
0.009782226756215096,
-0.008526603691279888,
0.07082270085811615,
0.07033591717481613,
-0.07096154987812042,
-0.08304157108068466,
-0.049038589000701904,
0.008840653114020824,
-0.06503074616193771,
-0.2631264328956604,
-0.05898119509220123,
-0.039133645594120026,
0.12776942551136017,
-0.21119223535060883,
0.0010117273777723312,
0.029405809938907623,
0.13495302200317383,
0.06593117862939835,
-0.053892239928245544,
0.005081655457615852,
0.07959699630737305,
-0.02263224497437477,
-0.06554868817329407,
0.03799163177609444,
-0.004995558876544237,
-0.12284249067306519,
-0.015645746141672134,
-0.14778754115104675,
0.1376521736383438,
0.09082085639238358,
0.035030413419008255,
-0.09334732592105865,
-0.08526108413934708,
-0.05871126800775528,
-0.054461769759655,
-0.04247567430138588,
0.01898898556828499,
0.15312370657920837,
0.025198042392730713,
0.1034284383058548,
-0.07659208029508591,
-0.046795278787612915,
0.05025389418005943,
0.009478162042796612,
-0.03832540661096573,
0.13272619247436523,
0.0741768330335617,
-0.07706354558467865,
0.12106499820947647,
0.1762889176607132,
-0.051054228097200394,
0.16697224974632263,
-0.06456906348466873,
-0.09887009114027023,
-0.047617800533771515,
0.024546191096305847,
0.02673858031630516,
0.11344786733388901,
-0.1068497821688652,
0.00548840407282114,
0.013079767115414143,
0.03721378371119499,
-0.008998367935419083,
-0.1693560928106308,
-0.015036696568131447,
0.055695075541734695,
-0.05410945042967796,
-0.004167201928794384,
-0.015556872822344303,
-0.011669513769447803,
0.07737381011247635,
0.01578608714044094,
-0.06026070564985275,
0.0029470850713551044,
-0.005130012519657612,
-0.07668893039226532,
0.1684410572052002,
-0.10538196563720703,
-0.12112079560756683,
-0.1299535632133484,
-0.04427269473671913,
-0.019517483189702034,
-0.016272760927677155,
0.06050163507461548,
-0.09632697701454163,
-0.038655348122119904,
-0.06917066872119904,
0.032822757959365845,
-0.04909759387373924,
0.03847914934158325,
0.018877914175391197,
0.01090250350534916,
0.05626872926950455,
-0.07643723487854004,
0.021162981167435646,
0.0046285297721624374,
-0.005191913340240717,
0.01979619823396206,
0.027410851791501045,
0.08855324983596802,
0.15577344596385956,
0.04933756962418556,
0.021942641586065292,
-0.04855499789118767,
0.17438475787639618,
-0.11628057807683945,
0.008601146750152111,
0.08636147528886795,
-0.018272655084729195,
0.05338968709111214,
0.1801246553659439,
0.057385388761758804,
-0.06868050247430801,
0.008536389097571373,
0.04482313618063927,
-0.021022796630859375,
-0.22473971545696259,
-0.016123991459608078,
-0.05668864771723747,
-0.0018224556697532535,
0.11164809763431549,
0.03367467597126961,
-0.0006479699513874948,
0.03860755264759064,
-0.01744776964187622,
0.006653809919953346,
0.020779311656951904,
0.0739000141620636,
0.05025215819478035,
0.052940163761377335,
0.11192303150892258,
-0.023401089012622833,
-0.021605927497148514,
0.03894898295402527,
0.029512856155633926,
0.2186577469110489,
0.030414439737796783,
0.16526886820793152,
0.053375616669654846,
0.12582461535930634,
0.023396162316203117,
0.03232264518737793,
0.02064528316259384,
-0.03249058872461319,
0.0006018484709784389,
-0.059594955295324326,
0.0069227395579218864,
0.050288647413253784,
0.08767054229974747,
0.03558948636054993,
-0.11754875630140305,
0.015575992874801159,
0.021293528378009796,
0.30083563923835754,
0.08206571638584137,
-0.28105682134628296,
-0.07139755040407181,
0.02483915351331234,
-0.05965045467019081,
-0.016748027876019478,
0.025256086140871048,
0.1160694882273674,
-0.06741350144147873,
0.10212892293930054,
-0.07192040234804153,
0.07871750742197037,
-0.0693499818444252,
-0.00756143918260932,
0.08299066871404648,
0.0879659503698349,
-0.0169233251363039,
0.04151051864027977,
-0.21882183849811554,
0.2810327708721161,
0.013628127984702587,
0.06001924350857735,
-0.023204972967505455,
0.03615572303533554,
0.024247143417596817,
-0.0009864956373348832,
0.10500473529100418,
-0.01384175568819046,
-0.16547724604606628,
-0.177078977227211,
-0.10621600598096848,
-0.0023213315289467573,
0.1195874810218811,
-0.06928049772977829,
0.10678204149007797,
-0.023752335458993912,
-0.03378155082464218,
0.042712558060884476,
-0.03632122278213501,
-0.0972464308142662,
-0.13166877627372742,
0.020987754687666893,
0.00875452533364296,
0.039373740553855896,
-0.09075053781270981,
-0.11150858551263809,
-0.10998830199241638,
0.15618541836738586,
-0.08644678443670273,
-0.01370137371122837,
-0.1334535777568817,
0.06163351237773895,
0.1366562694311142,
-0.07202558219432831,
0.05307118967175484,
0.0040569365955889225,
0.12435465306043625,
-0.005341462325304747,
-0.02474176697432995,
0.11576807498931885,
-0.07855641841888428,
-0.20079638063907623,
-0.08053895086050034,
0.1747526079416275,
0.03890223428606987,
0.06995844841003418,
-0.029047036543488503,
0.03896133229136467,
0.019352836534380913,
-0.06833843141794205,
0.08665310591459274,
0.030189793556928635,
0.03716811537742615,
0.02266058512032032,
-0.01296558789908886,
-0.021294793114066124,
-0.041860777884721756,
-0.06999600678682327,
0.12373314797878265,
0.3256804645061493,
-0.0991104245185852,
0.07649152725934982,
0.03439576178789139,
-0.05006136745214462,
-0.12681818008422852,
0.014380129985511303,
0.12750539183616638,
0.027844667434692383,
0.057920292019844055,
-0.1890200823545456,
0.05582377687096596,
0.08299048244953156,
-0.01799771748483181,
0.08344358205795288,
-0.3132348954677582,
-0.12173694372177124,
0.0780956894159317,
0.10463792085647583,
-0.022112740203738213,
-0.16709230840206146,
-0.06126285344362259,
-0.006886112038046122,
-0.12002220749855042,
0.0663600042462349,
-0.034333113580942154,
0.11588645726442337,
-0.0073329126462340355,
0.0031496863812208176,
0.017397373914718628,
-0.04941803589463234,
0.14292477071285248,
-0.01791626587510109,
0.061943329870700836,
-0.015080858021974564,
0.026259565725922585,
-0.016993921250104904,
-0.0757536068558693,
-0.024815727025270462,
-0.11269477754831314,
-0.0070486669428646564,
-0.09899801760911942,
-0.02983926050364971,
-0.06419183313846588,
0.011859051883220673,
-0.057079024612903595,
-0.03369151055812836,
-0.0394231453537941,
0.05193300172686577,
0.0732850730419159,
-0.01620100997388363,
0.17697910964488983,
-0.02887101285159588,
0.15244151651859283,
0.11151618510484695,
0.09394055604934692,
-0.008160420693457127,
-0.1271066963672638,
-0.014602669514715672,
-0.03715066239237785,
0.0476379320025444,
-0.12573756277561188,
0.036131177097558975,
0.13357263803482056,
0.030541595071554184,
0.14020861685276031,
0.04945773631334305,
-0.07477262616157532,
0.013726949691772461,
0.0831402987241745,
-0.09083251655101776,
-0.14029139280319214,
-0.01687762886285782,
0.03199515491724014,
-0.13957157731056213,
-0.00946562085300684,
0.1029912531375885,
-0.02318866178393364,
-0.015557447448372841,
0.027717260643839836,
0.03248385712504387,
-0.03032543510198593,
0.20139306783676147,
0.009904096834361553,
0.07443281263113022,
-0.0863531157374382,
0.08303049206733704,
0.05726098641753197,
-0.1861402839422226,
0.0282756257802248,
0.07855633646249771,
-0.05737313628196716,
-0.013486378826200962,
0.065048448741436,
0.11698972433805466,
0.024596741423010826,
-0.04287725314497948,
-0.11168402433395386,
-0.13790981471538544,
0.08340010046958923,
0.1086362674832344,
0.04063330218195915,
0.004225339740514755,
-0.006605126895010471,
0.035292696207761765,
-0.0788511112332344,
0.1195891723036766,
0.07479636371135712,
0.08528471738100052,
-0.17074702680110931,
0.07446150481700897,
0.004302742891013622,
-0.016533933579921722,
0.0020530952606350183,
0.0173985306173563,
-0.12585152685642242,
-0.006442862097173929,
-0.09242075681686401,
-0.014092326164245605,
-0.07610084861516953,
0.0015892329392954707,
0.0008597550331614912,
-0.04035310819745064,
-0.050911758095026016,
0.005173469427973032,
-0.10558819025754929,
-0.04366205260157585,
-0.012436684221029282,
0.07808168977499008,
-0.09323395788669586,
-0.022280683740973473,
0.03523595631122589,
-0.10769937932491302,
0.07866713404655457,
0.0030407530721277,
0.042104572057724,
0.00016860797768458724,
-0.11222607642412186,
0.011842072010040283,
0.037065885961055756,
-0.02356710284948349,
0.024418365210294724,
-0.20575359463691711,
-0.025991292670369148,
-0.03742844611406326,
0.006130073219537735,
-0.0019339852733537555,
0.030027534812688828,
-0.11879522353410721,
-0.018935400992631912,
-0.04678754881024361,
-0.08143627643585205,
-0.05031152442097664,
0.05140606686472893,
0.09576042741537094,
-0.0021452659275382757,
0.18441547453403473,
-0.08740504086017609,
0.05602816864848137,
-0.21793465316295624,
0.003632736625149846,
-0.014593303203582764,
-0.06659825891256332,
-0.07237094640731812,
-0.026219720020890236,
0.061498284339904785,
-0.05639386922121048,
0.07428983598947525,
-0.05724278837442398,
0.042798928916454315,
0.037277884781360626,
-0.10524462908506393,
0.03029327094554901,
0.04626888409256935,
0.17632728815078735,
0.03238748759031296,
-0.03255358710885048,
0.05471375957131386,
0.009021805599331856,
0.0733494907617569,
0.14441674947738647,
0.14414942264556885,
0.1559896022081375,
0.011571335606276989,
0.07546219229698181,
0.034525495022535324,
-0.11232157796621323,
-0.16340860724449158,
0.152369424700737,
-0.03459249809384346,
0.14427565038204193,
0.008099389262497425,
0.1935565024614334,
0.12120825797319412,
-0.21145480871200562,
0.046602681279182434,
-0.02924863062798977,
-0.07559054344892502,
-0.10754385590553284,
-0.09916255623102188,
-0.09235075861215591,
-0.19892282783985138,
0.011044303886592388,
-0.09665064513683319,
0.05004044994711876,
0.01963702216744423,
0.03523371368646622,
0.05051971599459648,
0.1152326688170433,
0.03875843808054924,
0.015703506767749786,
0.08081740140914917,
0.026772603392601013,
-0.03713848814368248,
-0.02871955931186676,
-0.07308831065893173,
0.033869192004203796,
-0.07300525158643723,
0.032612234354019165,
-0.053171999752521515,
-0.07982022315263748,
0.06972220540046692,
0.019634060561656952,
-0.11050160974264145,
0.03103186935186386,
-0.008101538754999638,
0.059209272265434265,
0.10080839693546295,
0.018422864377498627,
-0.002827971475198865,
-0.01817464455962181,
0.2040010690689087,
-0.08139519393444061,
-0.017668478190898895,
-0.13025511801242828,
0.1977713406085968,
-0.010200712829828262,
0.0009408509358763695,
0.021480903029441833,
-0.07545770704746246,
0.01842064969241619,
0.12706971168518066,
0.14364266395568848,
0.007530979346483946,
-0.015524502843618393,
0.01939953677356243,
-0.01046357024461031,
-0.031118720769882202,
0.052860554307699203,
0.09846686571836472,
0.05541197210550308,
-0.06729558855295181,
-0.04123183712363243,
-0.05206342041492462,
-0.04423115402460098,
-0.01413055695593357,
0.06531167775392532,
0.04344567656517029,
-0.011079533025622368,
-0.011068766005337238,
0.11237432807683945,
-0.036655720323324203,
-0.10932854562997818,
0.062044404447078705,
-0.18569591641426086,
-0.17580871284008026,
-0.03805031627416611,
0.10787943005561829,
0.012761441990733147,
0.04367982968688011,
0.0016099688364192843,
-0.0493064820766449,
0.08811184763908386,
-0.005291431676596403,
-0.05960943177342415,
-0.10741972178220749,
0.0693284347653389,
-0.07471293956041336,
0.17284037172794342,
-0.034226786345243454,
0.027081284672021866,
0.12084991484880447,
0.06988731771707535,
-0.07551959156990051,
0.024487655609846115,
0.0789942517876625,
-0.1144154965877533,
0.033053889870643616,
0.1778060346841812,
-0.04339855909347534,
0.16749271750450134,
0.05693352222442627,
-0.08180876821279526,
0.02873062528669834,
-0.11371272057294846,
-0.07276719808578491,
-0.03598417714238167,
0.021023357287049294,
-0.043165452778339386,
0.14706926047801971,
0.18567372858524323,
-0.05048573762178421,
-0.02557164803147316,
-0.03911668807268143,
0.0285146776586771,
0.06304611265659332,
0.1390354484319687,
-0.026761211454868317,
-0.2483118623495102,
0.04094237834215164,
0.024242645129561424,
0.022385239601135254,
-0.22817851603031158,
-0.11149819940328598,
0.02146201580762863,
-0.04169055074453354,
-0.0958203449845314,
0.10472977161407471,
0.0691458210349083,
0.049549948424100876,
-0.07140195369720459,
-0.11192598938941956,
-0.0354519821703434,
0.16015829145908356,
-0.16524620354175568,
-0.05560872703790665
] |
null | null | null | # Matcha-TTS NgNgNgan
Demo 🤗 HuggingFace space: https://huggingface.co/spaces/doof-ferb/MatchaTTS_ngngngan
## License
In accordance with the terms of the CC-BY-NC-SA-4.0 license, the use of my checkpoints and any audio output generated by them for commercial purposes is strictly prohibited. This includes, but is not limited to:
- online and offline voice cloning as a service
- online and offline text-to-speech as a service
- content creation for monetization on social media platforms
Căn cứ vào các điều khoản của giấp phép CC-BY-NC-SA-4.0, việc sử dụng các checkpoints này và bất kỳ đầu ra âm thanh nào được tạo bởi chúng đều bị nghiêm cấm sử dụng cho mục đích thương mại. Điều này bao gồm, nhưng không giới hạn ở:
- các dịch vụ nhân bản giọng nói trực tuyến và ngoại tuyến
- các dịch vụ chuyển văn bản thành giọng nói trực tuyến và ngoại tuyến
- tạo nội dung để kiếm tiền trên các nền tảng mạng xã hội
## What is Matcha-TTS?
original: https://github.com/shivammehta25/Matcha-TTS
vocoder copied from:
- `hifigan_univ_v1`: https://github.com/shivammehta25/Matcha-TTS-checkpoints/releases/download/v1.0/g_02500000
- `hifigan_T2_v1`: https://github.com/shivammehta25/Matcha-TTS-checkpoints/releases/download/v1.0/generator_v1
## About this repo
- speaker: Vietnamese M.C. Nguyễn Ngọc Ngạn
- data scraping code: https://github.com/phineas-pta/speech-synthesis-ngngngan
- 4h50min audio, 6.6k samples
- batch size = 16 ⇒ 1 epoch = 363 steps
- train locally from scratch, ≈ 3 minute/epoch
- train 600 epochs, save ckpt every 20 epoch, select ckpt at 420th epoch
- i haven’t tested all the checkpoints 1 by 1
| {"language": "vi", "license": "cc-by-nc-sa-4.0", "pipeline_tag": "text-to-speech", "inference": false} | text-to-speech | doof-ferb/matcha_ngngngan | [
"tensorboard",
"text-to-speech",
"vi",
"license:cc-by-nc-sa-4.0",
"has_space",
"region:us"
] | 2024-02-09T00:48:31+00:00 | [] | [
"vi"
] | TAGS
#tensorboard #text-to-speech #vi #license-cc-by-nc-sa-4.0 #has_space #region-us
| # Matcha-TTS NgNgNgan
Demo HuggingFace space: URL
## License
!license
In accordance with the terms of the CC-BY-NC-SA-4.0 license, the use of my checkpoints and any audio output generated by them for commercial purposes is strictly prohibited. This includes, but is not limited to:
- online and offline voice cloning as a service
- online and offline text-to-speech as a service
- content creation for monetization on social media platforms
Căn cứ vào các điều khoản của giấp phép CC-BY-NC-SA-4.0, việc sử dụng các checkpoints này và bất kỳ đầu ra âm thanh nào được tạo bởi chúng đều bị nghiêm cấm sử dụng cho mục đích thương mại. Điều này bao gồm, nhưng không giới hạn ở:
- các dịch vụ nhân bản giọng nói trực tuyến và ngoại tuyến
- các dịch vụ chuyển văn bản thành giọng nói trực tuyến và ngoại tuyến
- tạo nội dung để kiếm tiền trên các nền tảng mạng xã hội
## What is Matcha-TTS?
original: URL
vocoder copied from:
- 'hifigan_univ_v1': URL
- 'hifigan_T2_v1': URL
## About this repo
- speaker: Vietnamese M.C. Nguyễn Ngọc Ngạn
- data scraping code: URL
- 4h50min audio, 6.6k samples
- batch size = 16 ⇒ 1 epoch = 363 steps
- train locally from scratch, ≈ 3 minute/epoch
- train 600 epochs, save ckpt every 20 epoch, select ckpt at 420th epoch
- i haven’t tested all the checkpoints 1 by 1
| [
"# Matcha-TTS NgNgNgan\n\nDemo HuggingFace space: URL",
"## License\n\n!license\n\nIn accordance with the terms of the CC-BY-NC-SA-4.0 license, the use of my checkpoints and any audio output generated by them for commercial purposes is strictly prohibited. This includes, but is not limited to:\n- online and offline voice cloning as a service\n- online and offline text-to-speech as a service\n- content creation for monetization on social media platforms\n\nCăn cứ vào các điều khoản của giấp phép CC-BY-NC-SA-4.0, việc sử dụng các checkpoints này và bất kỳ đầu ra âm thanh nào được tạo bởi chúng đều bị nghiêm cấm sử dụng cho mục đích thương mại. Điều này bao gồm, nhưng không giới hạn ở:\n- các dịch vụ nhân bản giọng nói trực tuyến và ngoại tuyến\n- các dịch vụ chuyển văn bản thành giọng nói trực tuyến và ngoại tuyến\n- tạo nội dung để kiếm tiền trên các nền tảng mạng xã hội",
"## What is Matcha-TTS?\n\noriginal: URL\n\nvocoder copied from:\n- 'hifigan_univ_v1': URL\n- 'hifigan_T2_v1': URL",
"## About this repo\n\n- speaker: Vietnamese M.C. Nguyễn Ngọc Ngạn\n- data scraping code: URL\n- 4h50min audio, 6.6k samples\n- batch size = 16 ⇒ 1 epoch = 363 steps\n- train locally from scratch, ≈ 3 minute/epoch\n- train 600 epochs, save ckpt every 20 epoch, select ckpt at 420th epoch\n- i haven’t tested all the checkpoints 1 by 1"
] | [
"TAGS\n#tensorboard #text-to-speech #vi #license-cc-by-nc-sa-4.0 #has_space #region-us \n",
"# Matcha-TTS NgNgNgan\n\nDemo HuggingFace space: URL",
"## License\n\n!license\n\nIn accordance with the terms of the CC-BY-NC-SA-4.0 license, the use of my checkpoints and any audio output generated by them for commercial purposes is strictly prohibited. This includes, but is not limited to:\n- online and offline voice cloning as a service\n- online and offline text-to-speech as a service\n- content creation for monetization on social media platforms\n\nCăn cứ vào các điều khoản của giấp phép CC-BY-NC-SA-4.0, việc sử dụng các checkpoints này và bất kỳ đầu ra âm thanh nào được tạo bởi chúng đều bị nghiêm cấm sử dụng cho mục đích thương mại. Điều này bao gồm, nhưng không giới hạn ở:\n- các dịch vụ nhân bản giọng nói trực tuyến và ngoại tuyến\n- các dịch vụ chuyển văn bản thành giọng nói trực tuyến và ngoại tuyến\n- tạo nội dung để kiếm tiền trên các nền tảng mạng xã hội",
"## What is Matcha-TTS?\n\noriginal: URL\n\nvocoder copied from:\n- 'hifigan_univ_v1': URL\n- 'hifigan_T2_v1': URL",
"## About this repo\n\n- speaker: Vietnamese M.C. Nguyễn Ngọc Ngạn\n- data scraping code: URL\n- 4h50min audio, 6.6k samples\n- batch size = 16 ⇒ 1 epoch = 363 steps\n- train locally from scratch, ≈ 3 minute/epoch\n- train 600 epochs, save ckpt every 20 epoch, select ckpt at 420th epoch\n- i haven’t tested all the checkpoints 1 by 1"
] | [
36,
18,
197,
47,
109
] | [
"passage: TAGS\n#tensorboard #text-to-speech #vi #license-cc-by-nc-sa-4.0 #has_space #region-us \n# Matcha-TTS NgNgNgan\n\nDemo HuggingFace space: URL## License\n\n!license\n\nIn accordance with the terms of the CC-BY-NC-SA-4.0 license, the use of my checkpoints and any audio output generated by them for commercial purposes is strictly prohibited. This includes, but is not limited to:\n- online and offline voice cloning as a service\n- online and offline text-to-speech as a service\n- content creation for monetization on social media platforms\n\nCăn cứ vào các điều khoản của giấp phép CC-BY-NC-SA-4.0, việc sử dụng các checkpoints này và bất kỳ đầu ra âm thanh nào được tạo bởi chúng đều bị nghiêm cấm sử dụng cho mục đích thương mại. Điều này bao gồm, nhưng không giới hạn ở:\n- các dịch vụ nhân bản giọng nói trực tuyến và ngoại tuyến\n- các dịch vụ chuyển văn bản thành giọng nói trực tuyến và ngoại tuyến\n- tạo nội dung để kiếm tiền trên các nền tảng mạng xã hội## What is Matcha-TTS?\n\noriginal: URL\n\nvocoder copied from:\n- 'hifigan_univ_v1': URL\n- 'hifigan_T2_v1': URL## About this repo\n\n- speaker: Vietnamese M.C. Nguyễn Ngọc Ngạn\n- data scraping code: URL\n- 4h50min audio, 6.6k samples\n- batch size = 16 ⇒ 1 epoch = 363 steps\n- train locally from scratch, ≈ 3 minute/epoch\n- train 600 epochs, save ckpt every 20 epoch, select ckpt at 420th epoch\n- i haven’t tested all the checkpoints 1 by 1"
] | [
0.029605625197291374,
0.11091212928295135,
-0.008080118335783482,
0.022682487964630127,
0.003834137925878167,
-0.05872451886534691,
0.0897873044013977,
0.0871528759598732,
-0.042142998427152634,
0.05206190422177315,
-0.02898997813463211,
-0.01868230476975441,
0.0786794051527977,
0.13266178965568542,
0.00996348261833191,
-0.1086404100060463,
0.054352954030036926,
-0.054431065917015076,
-0.03316903114318848,
0.06990289688110352,
0.09062793105840683,
0.003956334665417671,
0.06131073459982872,
-0.02633448876440525,
-0.02078087627887726,
-0.02027709037065506,
-0.04984192177653313,
-0.03195101022720337,
0.0004564654955174774,
0.035153888165950775,
-0.000882561958860606,
0.0539562851190567,
0.042423754930496216,
-0.14606626331806183,
0.018074335530400276,
0.03627489507198334,
-0.051724039018154144,
-0.013541954569518566,
0.03554006293416023,
0.04328182339668274,
0.13567183911800385,
0.031160341575741768,
-0.03410514071583748,
0.055072590708732605,
-0.06375646591186523,
-0.0726504921913147,
-0.09389239549636841,
0.042845480144023895,
0.09917621314525604,
0.10301096737384796,
-0.06450670212507248,
0.18079599738121033,
-0.1093268096446991,
0.029450714588165283,
0.12033984810113907,
-0.13954603672027588,
0.012312917038798332,
0.07846973091363907,
0.09415587037801743,
0.04776274040341377,
-0.08161014318466187,
-0.003274732269346714,
0.06293628364801407,
0.04884149879217148,
-0.019974756985902786,
-0.07558001577854156,
-0.04689154028892517,
-0.02417631819844246,
-0.10909485816955566,
-0.004388941451907158,
0.19020196795463562,
0.03967136889696121,
-0.06694114953279495,
-0.09561643749475479,
-0.020225010812282562,
0.034720391035079956,
-0.018867995589971542,
0.00976940244436264,
0.01220846176147461,
0.02233077771961689,
0.012256897985935211,
-0.04693928733468056,
-0.06593094766139984,
-0.01162776630371809,
-0.002825336065143347,
-0.11498945206403732,
0.027623379603028297,
0.01035785861313343,
0.03526902198791504,
0.0859387069940567,
0.0019656086806207895,
-0.033920202404260635,
-0.01497045811265707,
-0.02954903617501259,
-0.027727464213967323,
-0.01771187037229538,
0.026987604796886444,
0.020002951845526695,
0.06101232394576073,
0.08074207603931427,
0.01545325294137001,
0.013005943037569523,
-0.09408879280090332,
0.028418950736522675,
0.08545168489217758,
0.007810595910996199,
-0.07411738485097885,
0.018450720235705376,
0.04652709141373634,
0.061433322727680206,
-0.01966349594295025,
-0.024989381432533264,
-0.06632450222969055,
0.08562968671321869,
-0.029839377850294113,
0.044799238443374634,
0.06834098696708679,
0.012565686367452145,
-0.04238855093717575,
-0.02559649385511875,
0.1663074791431427,
-0.07154271006584167,
0.006020227447152138,
0.02218131721019745,
0.004545831587165594,
-0.02605380490422249,
0.010768634267151356,
0.0441054105758667,
-0.08885851502418518,
0.006996850483119488,
-0.010976848192512989,
-0.016699912026524544,
-0.028186775743961334,
-0.031782735139131546,
0.08077552914619446,
-0.002079743193462491,
-0.08383505791425705,
-0.060131486505270004,
0.0445382222533226,
-0.05918722227215767,
0.023104814812541008,
-0.04085707664489746,
-0.0615861602127552,
0.0018784204730764031,
-0.0493890754878521,
-0.01959812454879284,
0.01811983808875084,
-0.00420340895652771,
-0.05766989290714264,
0.03807198628783226,
-0.04689187556505203,
0.014922727830708027,
0.051236748695373535,
0.03950973600149155,
-0.08689706772565842,
0.04261151701211929,
-0.09345010668039322,
0.024017130956053734,
-0.11310994625091553,
-0.03733576461672783,
-0.04185577481985092,
-0.03445605933666229,
-0.018351005390286446,
0.01618710719048977,
-0.03985409066081047,
0.10322747379541397,
-0.1968204230070114,
-0.00456775538623333,
0.1254822462797165,
-0.1137709841132164,
-0.047030333429574966,
0.17035186290740967,
0.004238490480929613,
0.01816072314977646,
0.013247291557490826,
0.11372014135122299,
0.10417252779006958,
-0.21013620495796204,
-0.008584861643612385,
0.04596846550703049,
-0.06670200824737549,
0.08651705831289291,
0.07203801721334457,
-0.0864752009510994,
0.08663515746593475,
-0.01839105598628521,
-0.016416704282164574,
-0.03233693540096283,
0.00022582428937312216,
-0.02096124365925789,
0.010208860039710999,
-0.00724978931248188,
-0.014227466657757759,
-0.03563181683421135,
-0.05906457453966141,
-0.007452636491507292,
-0.048154059797525406,
-0.049363989382982254,
0.03867661952972412,
-0.01551798265427351,
0.06202622130513191,
-0.09073818475008011,
0.11129746586084366,
0.028689060360193253,
0.006363199092447758,
-0.06050954759120941,
-0.0030765440315008163,
0.053822290152311325,
-0.1258430778980255,
0.17140379548072815,
0.09163463115692139,
-0.021363697946071625,
0.0220290906727314,
-0.01783973164856434,
0.029052941128611565,
-0.049994006752967834,
-0.010749150067567825,
-0.01312976609915495,
-0.08064562827348709,
0.01983996108174324,
-0.011259258724749088,
0.057096321135759354,
-0.06366950273513794,
-0.026051005348563194,
0.11943160742521286,
0.07379943132400513,
0.0020964653231203556,
0.007546990178525448,
0.05464458465576172,
0.0076185730285942554,
-0.019015150144696236,
-0.00526600144803524,
-0.006627033930271864,
0.02617664635181427,
-0.0180400088429451,
0.16474974155426025,
-0.08160300552845001,
-0.02386675961315632,
0.09614650160074234,
-0.027693433687090874,
-0.012771746143698692,
0.05067183077335358,
-0.0026503659319132566,
-0.036373451352119446,
-0.07587288320064545,
-0.043950989842414856,
0.10134898126125336,
0.021494651213288307,
0.08366759121417999,
-0.10693570971488953,
-0.04340844601392746,
0.00998872984200716,
-0.07828238606452942,
-0.031461331993341446,
0.0361722856760025,
0.06450711935758591,
-0.03169379383325577,
0.09394561499357224,
0.07830627262592316,
0.05489389970898628,
0.11965017020702362,
-0.04975900426506996,
-0.05821208655834198,
-0.06553273648023605,
0.07686498016119003,
-0.0120602548122406,
0.04558161646127701,
0.03355895355343819,
0.03587241470813751,
0.04928164929151535,
0.046529024839401245,
0.04443371295928955,
-0.09613623470067978,
-0.013996674679219723,
-0.018959200009703636,
-0.0624656043946743,
-0.05971600487828255,
0.027904478833079338,
0.03287328779697418,
0.04964680224657059,
0.028587844222784042,
0.020123353227972984,
-0.0026255811098963022,
-0.05317912995815277,
-0.09578129649162292,
0.0466349795460701,
-0.11861925572156906,
-0.2097833901643753,
-0.1616995632648468,
-0.009904528968036175,
-0.046517837792634964,
0.007551014889031649,
0.03987501561641693,
-0.05068804696202278,
-0.07824154198169708,
-0.13916988670825958,
-0.01993078924715519,
-0.027268143370747566,
-0.09441141039133072,
-0.04194847494363785,
0.07292336225509644,
-0.01036196481436491,
-0.08754531294107437,
0.019642384722828865,
0.03564907982945442,
-0.008234117180109024,
0.016691796481609344,
0.007858180440962315,
0.05952797457575798,
0.06956224143505096,
0.040904123336076736,
-0.021672463044524193,
-0.03702780604362488,
0.1922457069158554,
-0.08213653415441513,
0.07673332840204239,
0.045563701540231705,
-0.020776964724063873,
0.07449530810117722,
0.1484355926513672,
0.015386154875159264,
-0.0331152118742466,
0.03742411360144615,
0.0706573948264122,
-0.011506401002407074,
-0.16430236399173737,
-0.08011280000209808,
-0.07116426527500153,
0.06893830746412277,
-0.019128333777189255,
0.04138416796922684,
0.06709969788789749,
-0.04106324911117554,
-0.06658819317817688,
0.021334541961550713,
0.11568491160869598,
0.04064265266060829,
0.046390097588300705,
-0.014501377940177917,
0.019879456609487534,
-0.06392143666744232,
0.00577043229714036,
0.16134069859981537,
0.023779356852173805,
0.22530902922153473,
0.03537493571639061,
0.16765977442264557,
0.10520658642053604,
0.13853491842746735,
0.0809418335556984,
-0.010156070813536644,
-0.012027946300804615,
0.039339058101177216,
-0.02733766846358776,
-0.07978450506925583,
0.10925748199224472,
0.04193367809057236,
0.1295313835144043,
-0.14626920223236084,
0.03604681417346001,
-0.02433646097779274,
0.04433653876185417,
0.19044454395771027,
0.033501047641038895,
0.0010328366188332438,
0.06233232095837593,
0.0337456539273262,
-0.007500697858631611,
-0.030116315931081772,
0.05744713544845581,
0.10150884836912155,
-0.1363200545310974,
0.019301315769553185,
0.024906937032938004,
0.09038569778203964,
-0.05892883613705635,
-0.02737279050052166,
0.04502589628100395,
-0.04536175727844238,
-0.008229556493461132,
0.07037977129220963,
-0.123691625893116,
0.14861564338207245,
0.0003064797492697835,
-0.022975269705057144,
-0.021891435608267784,
0.011615961790084839,
-0.02747800014913082,
0.009570580907166004,
0.09002518653869629,
0.05373801663517952,
-0.15218743681907654,
-0.03000606782734394,
-0.05538085848093033,
-0.04327403008937836,
0.09838777780532837,
-0.0059909215196967125,
0.02051498182117939,
-0.05578912794589996,
-0.011871044524013996,
-0.028557751327753067,
-0.05292759835720062,
-0.06770919263362885,
-0.08468067646026611,
0.05982028692960739,
0.018027279525995255,
0.007702285423874855,
-0.03926316648721695,
0.0075554754585027695,
-0.10018865764141083,
0.12111508101224899,
-0.18041345477104187,
-0.010831163264811039,
-0.04651828110218048,
-0.14012862741947174,
0.11066949367523193,
0.013120347633957863,
0.023465197533369064,
-0.03920438140630722,
0.06551291048526764,
-0.04228280484676361,
-0.05534559488296509,
0.046221598982810974,
-0.04287249967455864,
-0.1520380824804306,
-0.007230713963508606,
0.18265530467033386,
0.055964916944503784,
0.02451956644654274,
-0.018444711342453957,
-0.0033921971917152405,
-0.01259608007967472,
-0.11874054372310638,
-0.03489242494106293,
0.005749260541051626,
0.034762416034936905,
0.05630258098244667,
-0.08563319593667984,
-0.13886675238609314,
-0.08203331381082535,
-0.09043926745653152,
-0.008627374656498432,
0.3025311529636383,
-0.01182313822209835,
0.12640489637851715,
0.1785331815481186,
-0.06067686155438423,
-0.15940192341804504,
-0.07705779373645782,
-0.05250975489616394,
-0.06287847459316254,
0.06832710653543472,
-0.03971263766288757,
-0.005177492741495371,
0.026214471086859703,
-0.0008737978059798479,
0.04848359897732735,
-0.18522654473781586,
-0.09975748509168625,
0.008858171291649342,
-0.07833568006753922,
-0.05011224001646042,
-0.05085047706961632,
-0.06099650636315346,
-0.017516257241368294,
-0.20111581683158875,
0.049901362508535385,
-0.07301926612854004,
0.03654451295733452,
0.07167410850524902,
0.03861325979232788,
-0.004567249212414026,
-0.017084913328289986,
0.08499274402856827,
0.015157224610447884,
0.06104395538568497,
-0.09029457718133926,
-0.039319492876529694,
0.11364755034446716,
-0.0006092565017752349,
0.07884956151247025,
-0.029587626457214355,
-0.008668551221489906,
-0.07210776954889297,
0.0024612750858068466,
-0.04524124041199684,
0.04669710621237755,
-0.04934704303741455,
-0.02007092908024788,
-0.1293167769908905,
0.08308497816324234,
0.059789661318063736,
-0.011970971710979939,
0.0017582523869350553,
-0.05045575276017189,
-0.026978619396686554,
0.2186005413532257,
0.03802352771162987,
0.014162399806082249,
-0.046157196164131165,
-0.022189395502209663,
-0.029221810400485992,
0.029940402135252953,
0.021850161254405975,
0.05195203050971031,
0.05437995493412018,
-0.007632824592292309,
0.10122586786746979,
-0.003281043143942952,
-0.10520584136247635,
0.03175942599773407,
0.04579407721757889,
-0.039449308067560196,
-0.09299242496490479,
-0.02768436074256897,
-0.07085959613323212,
-0.013063164427876472,
-0.06420714408159256,
0.08264331519603729,
-0.0073358057998120785,
0.003954243380576372,
0.039294589310884476,
0.030960688367486,
-0.03984515368938446,
-0.00600383710116148,
-0.016165271401405334,
0.03182204067707062,
-0.07471669465303421,
0.13770978152751923,
0.093648262321949,
-0.049764618277549744,
-0.022557901218533516,
0.07645592093467712,
-0.08327891677618027,
-0.058062728494405746,
0.08645054697990417,
0.006307555828243494,
0.06960858404636383,
-0.019045790657401085,
0.02491973154246807,
-0.0571119524538517,
0.005239926278591156,
0.1124696210026741,
0.02641146257519722,
0.043371740728616714,
0.07799241691827774,
0.03239275887608528,
-0.0515894815325737,
0.06498976051807404,
0.043345797806978226,
0.00029977597296237946,
-0.07218295335769653,
0.0287492498755455,
0.05496549233794212,
0.05587483197450638,
-0.03348785266280174,
-0.041512612253427505,
-0.06229611486196518,
0.009333324618637562,
-0.009058314375579357,
0.015268310904502869,
-0.055100951343774796,
-0.015888575464487076,
-0.02991313673555851,
-0.01758412830531597,
-0.023773515596985817,
0.03700797259807587,
-0.0167549978941679,
-0.021259037777781487,
-0.023237550631165504,
0.05088253319263458,
-0.1422394961118698,
-0.006844919640570879,
0.08676214516162872,
-0.04225507006049156,
0.04878583177924156,
0.008692755363881588,
-0.06041339784860611,
-0.021584823727607727,
-0.05272950232028961,
-0.01425833161920309,
0.012039355002343655,
0.04110369086265564,
-0.003078002482652664,
-0.09894484281539917,
0.007149931974709034,
0.005462069064378738,
0.01623811386525631,
0.012569810263812542,
0.08687160164117813,
-0.09759047627449036,
-0.029821990057826042,
-0.05390200391411781,
-0.0925850048661232,
-0.011221082881093025,
0.01389066968113184,
0.11299261450767517,
0.021391404792666435,
0.1158585175871849,
-0.04411063343286514,
0.027180377393960953,
-0.06862033903598785,
-0.03850904479622841,
0.037232905626297,
0.01612168550491333,
-0.0006162493373267353,
-0.04365652799606323,
0.0005687308148480952,
-0.046202048659324646,
0.16312865912914276,
-0.004626862704753876,
-0.046087596565485,
0.04391917958855629,
-0.006060699932277203,
-0.1021375060081482,
0.05614418163895607,
0.015717240050435066,
-0.026158148422837257,
-0.04396359249949455,
-0.09352470934391022,
-0.0788576528429985,
-0.031064489856362343,
-0.11728288233280182,
-0.007090223953127861,
0.11367544531822205,
0.06763821095228195,
-0.011775380000472069,
0.09396306425333023,
-0.08116207271814346,
-0.10524452477693558,
0.09251689165830612,
-0.030051875859498978,
0.07937052845954895,
-0.0818023532629013,
0.10629790276288986,
0.07891537249088287,
-0.09293965995311737,
0.08071964979171753,
0.0017421963857486844,
-0.04135284945368767,
-0.05793224275112152,
-0.21442410349845886,
-0.0531909242272377,
-0.09650397300720215,
0.03488598391413689,
-0.033652164041996,
0.09797310084104538,
0.057490598410367966,
0.05451119318604469,
-0.04854235798120499,
0.08009202033281326,
-0.17670372128486633,
-0.09857072681188583,
0.027533693239092827,
-0.021294765174388885,
-0.022155430167913437,
0.01883482001721859,
0.029224418103694916,
0.06987696886062622,
-0.018081968650221825,
0.02884921431541443,
0.060670334845781326,
0.02678787335753441,
0.041429147124290466,
-0.12421786785125732,
-0.04666396602988243,
0.020803119987249374,
-0.015183789655566216,
-0.017515379935503006,
0.17433276772499084,
0.07015681266784668,
-0.03342769667506218,
0.03418257087469101,
0.1279134452342987,
-0.05270977318286896,
-0.15166440606117249,
-0.1372893750667572,
0.023806115612387657,
-0.043964166194200516,
0.020801689475774765,
-0.01133036706596613,
-0.0593172051012516,
-0.024167196825146675,
0.19621336460113525,
0.14498892426490784,
-0.06448855996131897,
-0.00011761795758502558,
-0.005544417537748814,
0.011367175728082657,
-0.011422616429626942,
0.07451476156711578,
0.05973058566451073,
0.15384022891521454,
0.015682928264141083,
-0.02518502064049244,
-0.0536927729845047,
-0.03836454451084137,
-0.08604766428470612,
0.09358958899974823,
-0.039455294609069824,
-0.03770530968904495,
-0.02661612443625927,
0.08073510229587555,
-0.1060624048113823,
-0.11752346158027649,
-0.05587122589349747,
-0.016679057851433754,
-0.015166177414357662,
0.03342228755354881,
-0.019101379439234734,
0.024672195315361023,
-0.017015181481838226,
0.019775070250034332,
-0.018144750967621803,
0.15764446556568146,
0.0020685954950749874,
-0.024983281269669533,
-0.030873123556375504,
0.02185562066733837,
-0.1509784758090973,
0.1115628331899643,
0.03348124027252197,
0.11744067072868347,
0.02327633835375309,
0.017100432887673378,
-0.023827381432056427,
0.1434284895658493,
0.06657973676919937,
-0.09270530939102173,
-0.05413481593132019,
0.08280827850103378,
-0.017053965479135513,
0.15446071326732635,
0.05097668245434761,
0.029603511095046997,
0.051845747977495193,
-0.024529624730348587,
0.025591520592570305,
-0.1250917762517929,
0.05767493322491646,
-0.1356215626001358,
0.12019103765487671,
0.051046013832092285,
-0.013476945459842682,
0.016049563884735107,
-0.03638850152492523,
0.01642772927880287,
-0.023789087310433388,
0.024975435808300972,
0.04468713328242302,
-0.11880229413509369,
0.025207947939634323,
0.011392764747142792,
0.0986405462026596,
-0.11705417931079865,
-0.030470889061689377,
-0.021880585700273514,
-0.0028114914894104004,
-0.003742594737559557,
0.10290966182947159,
0.02458440326154232,
-0.011593473143875599,
-0.04627591744065285,
-0.08339562267065048,
0.007057904731482267,
0.06780644506216049,
-0.07367172837257385,
-0.028759226202964783
] |
null | null | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 3.527578115463257
f1_macro: 0.23136507936507936
f1_micro: 0.30666666666666664
f1_weighted: 0.23136507936507936
precision_macro: 0.20333333333333334
precision_micro: 0.30666666666666664
precision_weighted: 0.20333333333333334
recall_macro: 0.30666666666666664
recall_micro: 0.30666666666666664
recall_weighted: 0.30666666666666664
accuracy: 0.30666666666666664
| {"tags": ["autotrain", "image-classification"], "datasets": ["autotrain-vhcyp-17adu/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]} | image-classification | tferreira6/autotrain-vhcyp-17adu | [
"transformers",
"safetensors",
"vit",
"image-classification",
"autotrain",
"dataset:autotrain-vhcyp-17adu/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | 2024-02-09T00:48:38+00:00 | [] | [] | TAGS
#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-vhcyp-17adu/autotrain-data #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 3.527578115463257
f1_macro: 0.23136507936507936
f1_micro: 0.30666666666666664
f1_weighted: 0.23136507936507936
precision_macro: 0.20333333333333334
precision_micro: 0.30666666666666664
precision_weighted: 0.20333333333333334
recall_macro: 0.30666666666666664
recall_micro: 0.30666666666666664
recall_weighted: 0.30666666666666664
accuracy: 0.30666666666666664
| [
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 3.527578115463257\n\nf1_macro: 0.23136507936507936\n\nf1_micro: 0.30666666666666664\n\nf1_weighted: 0.23136507936507936\n\nprecision_macro: 0.20333333333333334\n\nprecision_micro: 0.30666666666666664\n\nprecision_weighted: 0.20333333333333334\n\nrecall_macro: 0.30666666666666664\n\nrecall_micro: 0.30666666666666664\n\nrecall_weighted: 0.30666666666666664\n\naccuracy: 0.30666666666666664"
] | [
"TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-vhcyp-17adu/autotrain-data #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 3.527578115463257\n\nf1_macro: 0.23136507936507936\n\nf1_micro: 0.30666666666666664\n\nf1_weighted: 0.23136507936507936\n\nprecision_macro: 0.20333333333333334\n\nprecision_micro: 0.30666666666666664\n\nprecision_weighted: 0.20333333333333334\n\nrecall_macro: 0.30666666666666664\n\nrecall_micro: 0.30666666666666664\n\nrecall_weighted: 0.30666666666666664\n\naccuracy: 0.30666666666666664"
] | [
65,
16,
143
] | [
"passage: TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-vhcyp-17adu/autotrain-data #autotrain_compatible #endpoints_compatible #has_space #region-us \n# Model Trained Using AutoTrain\n\n- Problem type: Image Classification## Validation Metricsg\nloss: 3.527578115463257\n\nf1_macro: 0.23136507936507936\n\nf1_micro: 0.30666666666666664\n\nf1_weighted: 0.23136507936507936\n\nprecision_macro: 0.20333333333333334\n\nprecision_micro: 0.30666666666666664\n\nprecision_weighted: 0.20333333333333334\n\nrecall_macro: 0.30666666666666664\n\nrecall_micro: 0.30666666666666664\n\nrecall_weighted: 0.30666666666666664\n\naccuracy: 0.30666666666666664"
] | [
-0.12416823953390121,
0.15070916712284088,
-0.0007656615925952792,
0.09881675988435745,
0.11191095411777496,
0.026883088052272797,
0.08298516273498535,
0.13812287151813507,
-0.02311043068766594,
0.1499800831079483,
0.1511887162923813,
0.10344016551971436,
0.07393943518400192,
0.13842634856700897,
-0.12920567393302917,
-0.15105228126049042,
0.04241715744137764,
0.01684860698878765,
0.05231707543134689,
0.06968892365694046,
0.05697490647435188,
-0.1425311267375946,
0.10768924653530121,
-0.034235630184412,
-0.22323140501976013,
0.025925882160663605,
0.11057019978761673,
-0.09755536913871765,
0.0869382992386818,
0.09784191846847534,
0.09054206311702728,
0.008334568701684475,
0.12151694297790527,
-0.06764699518680573,
-0.027759088203310966,
0.019993692636489868,
-0.008316931314766407,
0.06876126676797867,
0.13987109065055847,
0.019254010170698166,
-0.031109629198908806,
-0.07359665632247925,
0.06034287437796593,
0.036869194358587265,
-0.08797648549079895,
-0.09418699890375137,
-0.10065123438835144,
0.05596020817756653,
0.08415712416172028,
0.0831339955329895,
-0.021037863567471504,
0.18327049911022186,
-0.035321976989507675,
0.08603402227163315,
0.11778832972049713,
-0.22295907139778137,
-0.07902288436889648,
0.16670717298984528,
-0.05668884515762329,
-0.06210226193070412,
-0.08270207047462463,
0.07446061074733734,
0.12078890204429626,
0.0034719144459813833,
0.04480087012052536,
-0.0025507905520498753,
-0.04169850051403046,
0.025139261037111282,
-0.10175459831953049,
-0.058506086468696594,
0.16798515617847443,
0.03965853899717331,
-0.06718630343675613,
-0.101887047290802,
-0.05879578739404678,
-0.1017015352845192,
-0.07136408239603043,
-0.039632949978113174,
0.014495364390313625,
-0.07695478945970535,
-0.0826556459069252,
0.10903801769018173,
-0.04762357473373413,
-0.10505650192499161,
-0.11567100137472153,
0.07053297013044357,
-0.006884059868752956,
0.04137815535068512,
0.030268333852291107,
0.04391973465681076,
-0.037119582295417786,
-0.10985878109931946,
0.006344067398458719,
0.016378287225961685,
-0.09240171313285828,
-0.051169391721487045,
0.008575269021093845,
0.013898409903049469,
0.011805410496890545,
0.11446048319339752,
0.017754584550857544,
0.06884202361106873,
-0.03805358707904816,
-0.006457551382482052,
-0.061365045607089996,
0.19359423220157623,
-0.1311575025320053,
-0.050476089119911194,
0.005914727225899696,
0.039805926382541656,
0.027820752933621407,
-0.003913506865501404,
-0.053173042833805084,
-0.10928060859441757,
0.16820409893989563,
0.03225835785269737,
-0.021125273779034615,
0.040092576295137405,
-0.0630664974451065,
-0.00669511966407299,
0.003975411411374807,
-0.08322755992412567,
0.026811836287379265,
-0.053173091262578964,
-0.1378820389509201,
-0.011868693865835667,
0.05583596229553223,
-0.002979050623252988,
-0.0329720675945282,
0.08993098884820938,
-0.13047485053539276,
0.0074372426606714725,
-0.0628574788570404,
-0.13071244955062866,
0.039759375154972076,
-0.018685856834053993,
-0.008802920579910278,
-0.12247542291879654,
-0.16980966925621033,
-0.05808447673916817,
-0.04410060867667198,
-0.11958039551973343,
0.01300128549337387,
-0.03454022482037544,
-0.08285225182771683,
0.08285428583621979,
0.02128421515226364,
0.11325206607580185,
-0.016001109033823013,
0.056041400879621506,
0.07392631471157074,
0.11468589305877686,
0.012176908552646637,
0.01773792877793312,
-0.06575558334589005,
0.01837361976504326,
-0.174446702003479,
0.017887620255351067,
-0.072088323533535,
0.03328913077712059,
-0.11112958937883377,
-0.02957826294004917,
0.06844963133335114,
-0.004462224431335926,
0.06836556643247604,
0.17197251319885254,
-0.1327309012413025,
-0.002987208077684045,
0.06769521534442902,
-0.06905090063810349,
-0.1063096895813942,
0.10867536067962646,
-0.0030429346952587366,
0.01822005771100521,
0.02492440678179264,
0.060559045523405075,
0.009245812892913818,
-0.10635723173618317,
-0.07003811746835709,
-0.044884368777275085,
-0.02672617696225643,
-0.016382070258259773,
0.05948694795370102,
0.021137434989213943,
-0.11099397391080856,
0.019979335367679596,
0.037533171474933624,
0.009839886799454689,
-0.08966594189405441,
-0.06420532613992691,
-0.04275206848978996,
-0.06093611568212509,
0.03805159777402878,
0.03157699480652809,
0.037691183388233185,
-0.08373268693685532,
-0.06620663404464722,
0.04072066396474838,
0.1065007820725441,
-0.013191514648497105,
-0.06095299497246742,
-0.1233622133731842,
0.07342134416103363,
-0.18672960996627808,
-0.02215866558253765,
-0.16082774102687836,
-0.09393040835857391,
0.0016869123792275786,
0.024611039087176323,
-0.032273899763822556,
-0.053901344537734985,
0.09867563098669052,
0.044068772345781326,
-0.06424663215875626,
-0.04719310626387596,
0.08052263408899307,
0.010406439192593098,
-0.10688060522079468,
-0.10274167358875275,
-0.01299977581948042,
0.00011662377801258117,
0.1847134679555893,
-0.18419797718524933,
-0.031473007053136826,
0.04556776583194733,
0.09512076526880264,
0.03389300778508186,
-0.002149680396541953,
-0.0017687262734398246,
0.029235633090138435,
-0.03469839319586754,
-0.0844435915350914,
0.04397904500365257,
-0.06296265870332718,
-0.05608426779508591,
0.033191557973623276,
-0.24677586555480957,
0.25215283036231995,
0.14478956162929535,
-0.003912969026714563,
-0.11195380985736847,
-0.02681700326502323,
0.020401155576109886,
-0.05570138990879059,
-0.08691570907831192,
-0.0007708648918196559,
-0.06744856387376785,
-0.02586338482797146,
0.09878966957330704,
-0.06240072101354599,
-0.03194109722971916,
0.06241676211357117,
-0.003731675446033478,
-0.10993457585573196,
0.15950968861579895,
-0.0013992362655699253,
-0.15879152715206146,
0.12272163480520248,
0.07012754678726196,
-0.0835915133357048,
0.09785622358322144,
0.010184082202613354,
-0.06445043534040451,
-0.06353867053985596,
-0.036583974957466125,
0.05322417989373207,
0.1257706582546234,
0.042570389807224274,
0.028613384813070297,
0.04778517037630081,
-0.027495108544826508,
-0.028244346380233765,
-0.10846896469593048,
-0.0052362894639372826,
0.006066648289561272,
-0.016755910590291023,
0.031264159828424454,
0.0055636134929955006,
0.049205929040908813,
0.17503312230110168,
0.007353473454713821,
-0.07755301892757416,
0.03192151337862015,
-0.009742841124534607,
-0.06414946913719177,
0.1949780285358429,
-0.08464474976062775,
-0.16103698313236237,
-0.1607864946126938,
-0.03298060968518257,
-0.08246883749961853,
0.0020149967167526484,
-0.031857024878263474,
-0.08961161226034164,
-0.11510404199361801,
-0.07520487904548645,
-0.024744108319282532,
0.007301482371985912,
-0.023571863770484924,
0.03185611590743065,
-0.013342665508389473,
0.08915328979492188,
-0.06106938049197197,
-0.05718010663986206,
-0.02759452350437641,
-0.04064983129501343,
0.10879021883010864,
0.007785888854414225,
0.14913798868656158,
0.12787990272045135,
-0.04976682364940643,
0.04338381066918373,
-0.02963886968791485,
0.1562252938747406,
-0.03415090590715408,
0.010681682266294956,
0.19473512470722198,
0.0642317607998848,
0.011701839976012707,
0.12999729812145233,
0.010490723885595798,
-0.10499156266450882,
0.03453105315566063,
0.047962795943021774,
-0.019775256514549255,
-0.11977116018533707,
-0.1205630749464035,
0.007533237338066101,
0.0232444666326046,
0.143610879778862,
0.013797527179121971,
0.0646204724907875,
0.09830299019813538,
-0.004873303696513176,
0.0935240238904953,
-0.03159309923648834,
0.08053480833768845,
0.13453000783920288,
0.0452132448554039,
0.1745966672897339,
-0.05517326295375824,
-0.025462297722697258,
0.05652394890785217,
-0.036512359976768494,
0.07749339193105698,
0.0066206506453454494,
0.010079801082611084,
-0.04014933854341507,
0.12541797757148743,
0.057067446410655975,
0.10293199121952057,
0.07088981568813324,
-0.058435581624507904,
0.008505154401063919,
-0.10439015924930573,
-0.07415986061096191,
0.04084429517388344,
0.008809952065348625,
0.07114524394273758,
-0.11597532033920288,
0.05242585763335228,
0.028414146974682808,
0.09630970656871796,
0.1095505952835083,
-0.45885205268859863,
-0.08116469532251358,
0.04849855229258537,
0.040582168847322464,
-0.12889815866947174,
-0.012599245645105839,
0.05497359856963158,
-0.10232263058423996,
0.03451557829976082,
-0.05706857517361641,
0.08634737879037857,
-0.0378214530646801,
-0.0016307187033817172,
-0.041279833763837814,
0.05835752934217453,
-0.0318024717271328,
0.04833013564348221,
-0.2324751317501068,
0.20306609570980072,
0.06328944116830826,
0.045946523547172546,
-0.09417898207902908,
0.004998066462576389,
0.07077167183160782,
0.002712615765631199,
0.1631646305322647,
-0.014265548437833786,
-0.1365078240633011,
-0.35112637281417847,
-0.06149093061685562,
-0.02513878047466278,
0.038971029222011566,
0.02753269113600254,
0.1059923768043518,
-0.04597959294915199,
-0.04619750380516052,
0.04291030764579773,
-0.04436127841472626,
-0.11272954195737839,
-0.02811061218380928,
0.011199495755136013,
0.07201606780290604,
-0.005065043922513723,
-0.06155157834291458,
-0.09671677649021149,
-0.07167878746986389,
0.0800216794013977,
-0.03816917911171913,
-0.031277190893888474,
-0.17149773240089417,
0.12941545248031616,
0.12345574051141739,
-0.08444619178771973,
0.05669381469488144,
-0.007284512743353844,
0.1271052211523056,
0.012630641460418701,
-0.11235310137271881,
0.12740810215473175,
-0.08994461596012115,
-0.11605251580476761,
-0.011209221556782722,
0.03806576505303383,
-0.026288146153092384,
0.029577268287539482,
0.030329842120409012,
0.07772073894739151,
0.0233968123793602,
-0.07016022503376007,
0.0990007221698761,
0.0179096981883049,
0.1501038670539856,
0.10248486697673798,
-0.004653522744774818,
-0.14811284840106964,
-0.05061361938714981,
0.015068894252181053,
0.06342747062444687,
0.3109303116798401,
-0.09057068824768066,
-0.07993514090776443,
0.04690514877438545,
-0.01461105514317751,
-0.2799134850502014,
0.05532511696219444,
-0.02836647443473339,
0.05833802744746208,
-0.010635479353368282,
-0.0031269488390535116,
0.09331183135509491,
0.12306290864944458,
-0.03904356434941292,
-0.006228825077414513,
-0.23724332451820374,
-0.1254240870475769,
0.21128785610198975,
0.13653017580509186,
0.08791371434926987,
-0.09682521969079971,
-0.04484109953045845,
-0.11592565476894379,
-0.13060355186462402,
0.042141690850257874,
0.018717816099524498,
0.07281886786222458,
-0.06568655371665955,
0.01893937774002552,
0.06678161770105362,
-0.07828978449106216,
0.13022689521312714,
-0.05740927532315254,
0.11783527582883835,
-0.07904071360826492,
-0.05648369714617729,
0.007412015926092863,
-0.08092106133699417,
0.13692688941955566,
0.0641256794333458,
0.07097900658845901,
-0.10685248672962189,
-0.010961915366351604,
-0.030246954411268234,
0.059918053448200226,
-0.04909466952085495,
-0.052232012152671814,
-0.03519836440682411,
0.06677985191345215,
-0.0552058145403862,
-0.07360414415597916,
-0.012732445262372494,
-0.016064276918768883,
0.07174593210220337,
0.20814719796180725,
0.0699576660990715,
-0.01611764170229435,
0.03038850799202919,
0.04578360542654991,
-0.05159152299165726,
0.08811981230974197,
-0.061062708497047424,
0.06783448904752731,
0.12887407839298248,
0.01081254705786705,
0.1354859173297882,
0.06216365098953247,
-0.0356527641415596,
-0.03072388283908367,
0.05047861859202385,
-0.13065564632415771,
-0.0111943194642663,
-0.03256819024682045,
-0.007341690827161074,
-0.01868220791220665,
-0.03574923425912857,
0.11132603138685226,
-0.07473690807819366,
0.02470235526561737,
0.000009725447853270452,
0.03415987640619278,
0.040042150765657425,
0.25682342052459717,
0.024344881996512413,
0.056089483201503754,
-0.09998880326747894,
0.10997949540615082,
0.06106410548090935,
-0.14050213992595673,
0.042326364666223526,
0.013128581456840038,
-0.06161271408200264,
-0.027460448443889618,
0.0382438488304615,
0.1783600002527237,
-0.16147495806217194,
-0.04487724229693413,
-0.09999954700469971,
-0.15529698133468628,
0.06615244597196579,
0.23833979666233063,
0.09469994902610779,
0.014854063279926777,
0.027993345633149147,
-0.0670921802520752,
-0.10816099494695663,
0.1071743294596672,
0.10205385833978653,
0.05819469317793846,
-0.15299688279628754,
0.12483102828264236,
-0.057382699102163315,
0.010720418766140938,
-0.04889237508177757,
0.026542237028479576,
-0.17252539098262787,
-0.00377416773699224,
-0.09349595755338669,
0.06088493391871452,
-0.03556299954652786,
0.0055048298090696335,
-0.02410080097615719,
-0.00307336263358593,
-0.046136002987623215,
0.03556031361222267,
-0.052179690450429916,
-0.04056163877248764,
0.028096873313188553,
0.04696002975106239,
-0.11109428107738495,
-0.08499173820018768,
0.05113694816827774,
-0.03569474443793297,
0.03668728843331337,
0.04054156318306923,
0.0902651995420456,
0.012815704569220543,
-0.05789955332875252,
-0.04070204868912697,
0.10172560811042786,
-0.02738649956882,
0.06918666511774063,
-0.1440240889787674,
0.04072033613920212,
-0.0017736343434080482,
0.008523503318428993,
0.045674826949834824,
0.07146941125392914,
-0.09803339093923569,
-0.041316017508506775,
-0.10344942659139633,
-0.043267861008644104,
-0.1270975023508072,
0.07541947811841965,
0.1615455150604248,
-0.0027444190345704556,
0.0800856426358223,
-0.10548754036426544,
-0.020911093801259995,
-0.206428661942482,
0.0015354588394984603,
-0.051290251314640045,
-0.12819118797779083,
-0.0867268443107605,
0.021250246092677116,
0.09764958173036575,
-0.022931594401597977,
0.029065577313303947,
0.005027365405112505,
-0.01858954317867756,
0.05332029610872269,
0.08689440041780472,
-0.037034373730421066,
0.012287330813705921,
0.1581961214542389,
0.06526977568864822,
-0.027891745790839195,
0.05713658407330513,
0.09156706184148788,
0.11936698853969574,
0.07167994976043701,
0.038870252668857574,
0.09064436703920364,
-0.04617707431316376,
0.13454307615756989,
0.061064478009939194,
-0.09157916158437729,
-0.049127690494060516,
0.10994300991296768,
-0.16451102495193481,
0.0483863390982151,
-0.05487310513854027,
-0.013828903436660767,
0.15938322246074677,
-0.11925076693296432,
0.008127245120704174,
-0.11034094542264938,
-0.06900079548358917,
-0.1343376338481903,
-0.08916119486093521,
-0.14504681527614594,
-0.05115833878517151,
0.012231608852744102,
-0.09961740672588348,
0.050292424857616425,
0.17668180167675018,
0.033124472945928574,
0.00003515086427796632,
0.1639936864376068,
-0.15445417165756226,
0.0009068918297998607,
0.03541262075304985,
0.0008228395017795265,
-0.03770365193486214,
-0.023191535845398903,
-0.038125135004520416,
0.05654749274253845,
0.012810906395316124,
0.03070610947906971,
-0.005277659278362989,
0.01977064087986946,
0.05319744721055031,
0.021715255454182625,
-0.11007966101169586,
-0.02286677435040474,
0.029630329459905624,
0.03346620127558708,
0.05669410899281502,
0.0014095912920311093,
0.06118255853652954,
-0.03943783417344093,
0.23071008920669556,
-0.11129837483167648,
0.01210339181125164,
-0.0869428887963295,
0.23191052675247192,
-0.0032091171015053988,
0.08651132881641388,
0.0036427448503673077,
-0.057313501834869385,
0.048124995082616806,
0.12536264955997467,
0.07566207647323608,
-0.04490024596452713,
-0.045968469232320786,
-0.020405469462275505,
-0.01730520837008953,
-0.06800942867994308,
0.09043649584054947,
0.041921466588974,
0.049983151257038116,
-0.07644736766815186,
0.057483457028865814,
-0.006531901191920042,
-0.05165386199951172,
-0.004975583869963884,
0.055738937109708786,
0.004958692472428083,
0.04247989505529404,
-0.056674402207136154,
0.05084065720438957,
0.025095028802752495,
0.03260224685072899,
0.13597115874290466,
-0.14148040115833282,
-0.1498299092054367,
0.03460400179028511,
-0.0016101606888696551,
-0.03279001638293266,
0.08478526026010513,
-0.08828749507665634,
0.03590983897447586,
-0.03709748014807701,
-0.0008831085870042443,
-0.12364042550325394,
-0.11349888890981674,
-0.0010122250532731414,
0.13435938954353333,
0.26231735944747925,
0.008248287253081799,
0.06730645149946213,
0.13149015605449677,
-0.047914765775203705,
-0.17819344997406006,
0.10937605798244476,
0.0010466664098203182,
-0.12909871339797974,
0.1079656183719635,
0.16871194541454315,
-0.00856894813477993,
0.17325282096862793,
0.019474651664495468,
-0.18468716740608215,
0.008429020643234253,
-0.038270533084869385,
-0.004834471270442009,
-0.05403490737080574,
0.0339292474091053,
-0.05488072708249092,
0.15204589068889618,
0.13864247500896454,
-0.023379307240247726,
0.000921926402952522,
-0.04473353177309036,
0.03816674277186394,
0.004134142305701971,
0.047976184636354446,
0.026224419474601746,
-0.1001281812787056,
0.08224641531705856,
-0.10584178566932678,
-0.017857003957033157,
-0.2966742515563965,
-0.06469752639532089,
-0.04323991760611534,
-0.07972373813390732,
-0.06117084622383118,
0.11005397140979767,
0.1126701831817627,
0.043539173901081085,
-0.05168318748474121,
-0.196690171957016,
0.03608985245227814,
0.14418929815292358,
-0.06739114224910736,
-0.1031310185790062
] |
null | null | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - Aur0ra25/aur0ra_lora
<Gallery />
## Model description
These are Aur0ra25/aur0ra_lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
## Trigger words
You should use a photo of aur0ra to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](Aur0ra25/aur0ra_lora/tree/main) them in the Files & versions tab.
## Intended uses & limitations
#### How to use
```python
# TODO: add an example code snippet for running this diffusion pipeline
```
#### Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
## Training details
[TODO: describe the data used to train the model] | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora", "template:sd-lora"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of aur0ra", "widget": []} | text-to-image | Aur0ra25/aur0ra_lora | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"lora",
"template:sd-lora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | 2024-02-09T00:50:45+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion-xl #stable-diffusion-xl-diffusers #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - Aur0ra25/aur0ra_lora
<Gallery />
## Model description
These are Aur0ra25/aur0ra_lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
## Trigger words
You should use a photo of aur0ra to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
## Intended uses & limitations
#### How to use
#### Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
## Training details
[TODO: describe the data used to train the model] | [
"# SDXL LoRA DreamBooth - Aur0ra25/aur0ra_lora\n\n<Gallery />",
"## Model description\n\nThese are Aur0ra25/aur0ra_lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.\n\nThe weights were trained using DreamBooth.\n\nLoRA for the text encoder was enabled: False.\n\nSpecial VAE used for training: madebyollin/sdxl-vae-fp16-fix.",
"## Trigger words\n\nYou should use a photo of aur0ra to trigger the image generation.",
"## Download model\n\nWeights for this model are available in Safetensors format.\n\nDownload them in the Files & versions tab.",
"## Intended uses & limitations",
"#### How to use",
"#### Limitations and bias\n\n[TODO: provide examples of latent issues and potential remediations]",
"## Training details\n\n[TODO: describe the data used to train the model]"
] | [
"TAGS\n#diffusers #text-to-image #stable-diffusion-xl #stable-diffusion-xl-diffusers #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us \n",
"# SDXL LoRA DreamBooth - Aur0ra25/aur0ra_lora\n\n<Gallery />",
"## Model description\n\nThese are Aur0ra25/aur0ra_lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.\n\nThe weights were trained using DreamBooth.\n\nLoRA for the text encoder was enabled: False.\n\nSpecial VAE used for training: madebyollin/sdxl-vae-fp16-fix.",
"## Trigger words\n\nYou should use a photo of aur0ra to trigger the image generation.",
"## Download model\n\nWeights for this model are available in Safetensors format.\n\nDownload them in the Files & versions tab.",
"## Intended uses & limitations",
"#### How to use",
"#### Limitations and bias\n\n[TODO: provide examples of latent issues and potential remediations]",
"## Training details\n\n[TODO: describe the data used to train the model]"
] | [
78,
26,
91,
19,
28,
9,
5,
24,
16
] | [
"passage: TAGS\n#diffusers #text-to-image #stable-diffusion-xl #stable-diffusion-xl-diffusers #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us \n# SDXL LoRA DreamBooth - Aur0ra25/aur0ra_lora\n\n<Gallery />## Model description\n\nThese are Aur0ra25/aur0ra_lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.\n\nThe weights were trained using DreamBooth.\n\nLoRA for the text encoder was enabled: False.\n\nSpecial VAE used for training: madebyollin/sdxl-vae-fp16-fix.## Trigger words\n\nYou should use a photo of aur0ra to trigger the image generation.## Download model\n\nWeights for this model are available in Safetensors format.\n\nDownload them in the Files & versions tab.## Intended uses & limitations#### How to use#### Limitations and bias\n\n[TODO: provide examples of latent issues and potential remediations]## Training details\n\n[TODO: describe the data used to train the model]"
] | [
-0.06693082302808762,
0.1643020063638687,
-0.001275162328965962,
0.050719309598207474,
0.15584687888622284,
0.013469896279275417,
0.17503495514392853,
0.1360158771276474,
0.03313284367322922,
0.08923424780368805,
0.0018252120353281498,
0.004133358132094145,
0.08800595253705978,
0.18377915024757385,
-0.016405079513788223,
-0.27299004793167114,
0.015739699825644493,
-0.0279998816549778,
-0.059578366577625275,
0.034726351499557495,
0.07511947304010391,
-0.07214692234992981,
0.09328998625278473,
-0.0160723514854908,
-0.055931173264980316,
0.0577990859746933,
-0.047546230256557465,
-0.03901556134223938,
0.0014131031930446625,
0.06502491980791092,
0.051632970571517944,
0.03238982707262039,
0.10153761506080627,
-0.2468499392271042,
0.011716246604919434,
0.08485591411590576,
-0.015600237064063549,
0.06420853734016418,
0.04191524162888527,
-0.10534949600696564,
0.13896968960762024,
-0.10780922323465347,
0.08209890872240067,
0.0709897130727768,
-0.051358483731746674,
-0.12356799840927124,
-0.027673067525029182,
0.03181464225053787,
0.07901756465435028,
0.11987964063882828,
-0.0026328093372285366,
0.06524170190095901,
0.03145245835185051,
0.03213667497038841,
0.2562313675880432,
-0.09457485377788544,
-0.06317101418972015,
0.1815788894891739,
0.03786204382777214,
0.097752146422863,
-0.0659872367978096,
0.017415130510926247,
0.09040568023920059,
-0.02119888737797737,
0.07766943424940109,
-0.03962233290076256,
0.04833086207509041,
-0.061354510486125946,
-0.12581883370876312,
-0.016608422622084618,
0.21709080040454865,
0.016511844471096992,
-0.05658277869224548,
-0.15677569806575775,
-0.05469419062137604,
0.06524735689163208,
-0.01962008699774742,
-0.027370471507310867,
0.042413949966430664,
-0.01108236238360405,
0.029573265463113785,
-0.08809002488851547,
-0.043906815350055695,
-0.05533571168780327,
0.0731729194521904,
0.11773408949375153,
0.0016972529701888561,
0.024334613233804703,
-0.003314147237688303,
0.11143305897712708,
-0.06770716607570648,
-0.15524807572364807,
0.002424790058284998,
-0.0637534111738205,
-0.04681692272424698,
-0.002807229058817029,
0.019912121817469597,
-0.11312932521104813,
0.05273440107703209,
0.05642377585172653,
0.03761231526732445,
0.010316189378499985,
-0.08806651085615158,
0.01523617934435606,
0.050890836864709854,
0.09915228933095932,
-0.03816276788711548,
-0.12465693801641464,
0.04380537569522858,
0.07248350977897644,
0.010870637372136116,
-0.033075690269470215,
-0.08461547642946243,
-0.0003813659423030913,
-0.04789133369922638,
0.08030442148447037,
0.06282208114862442,
-0.00779374223202467,
-0.08017074316740036,
-0.06036782264709473,
0.13233788311481476,
-0.11688081175088882,
-0.0013976675691083074,
-0.03922809287905693,
-0.09693940728902817,
0.05024956166744232,
0.120659738779068,
0.04280568286776543,
-0.04862932488322258,
0.05626390874385834,
-0.07876883447170258,
-0.018052512779831886,
-0.10308143496513367,
-0.10694020986557007,
-0.0011917835799977183,
-0.07843606919050217,
0.005821485072374344,
-0.07140348106622696,
-0.23669753968715668,
-0.06545913219451904,
0.036261387169361115,
-0.07616855204105377,
-0.03304824233055115,
-0.05904660001397133,
-0.05613128840923309,
-0.028034860268235207,
0.034655410796403885,
0.05397016927599907,
0.0009534501587040722,
0.035785626620054245,
-0.0110895074903965,
0.061187744140625,
0.03714834898710251,
0.029715994372963905,
-0.10110963135957718,
0.051966167986392975,
-0.16289904713630676,
0.1631031185388565,
-0.09759346395730972,
0.05187223479151726,
-0.14335794746875763,
-0.06555911153554916,
-0.03261261433362961,
-0.019481640309095383,
0.0038347002118825912,
0.1630474179983139,
-0.20908953249454498,
-0.03585298731923103,
0.14706043899059296,
-0.16835570335388184,
-0.06597772240638733,
0.03309725597500801,
-0.04569588974118233,
0.11076430976390839,
0.09273446351289749,
0.09942640364170074,
0.14519250392913818,
-0.20648665726184845,
-0.024497997015714645,
-0.0350557379424572,
0.05827471613883972,
0.033764131367206573,
0.08769414573907852,
0.015980930998921394,
0.004975669085979462,
0.01897445321083069,
-0.09386087954044342,
0.024532843381166458,
-0.03200456127524376,
-0.05509188398718834,
-0.018855586647987366,
-0.08030165731906891,
-0.030812622979283333,
0.024818554520606995,
-0.023684125393629074,
0.02474401518702507,
-0.06122879311442375,
0.07517088204622269,
0.11777833104133606,
-0.07882406562566757,
-0.009731504134833813,
-0.027286332100629807,
0.02632247656583786,
-0.12047505378723145,
-0.01416967622935772,
-0.13270705938339233,
-0.12627995014190674,
0.04412306100130081,
-0.008245679549872875,
0.03810279816389084,
0.03728289529681206,
0.05208057910203934,
0.05433133244514465,
-0.05710870027542114,
-0.03594003617763519,
-0.018186187371611595,
-0.01874684728682041,
-0.030153512954711914,
-0.14540401101112366,
-0.03476497903466225,
-0.07183707505464554,
0.074797123670578,
-0.2088758796453476,
0.049055300652980804,
0.06222095340490341,
0.13431836664676666,
0.09097409248352051,
-0.04636615142226219,
0.06998980045318604,
-0.0032640579156577587,
-0.014847008511424065,
-0.1072690337896347,
-0.021384892985224724,
-0.008359056897461414,
-0.12391301244497299,
0.079985111951828,
-0.15220673382282257,
0.03737085312604904,
0.11375218629837036,
0.1251411885023117,
-0.03650288283824921,
-0.09221269190311432,
-0.0631106048822403,
-0.02033301256597042,
-0.11515455693006516,
-0.025876140221953392,
0.09976505488157272,
0.0019106249092146754,
0.08458305895328522,
-0.0777655690908432,
-0.0005465446738526225,
0.02007296495139599,
-0.0007637250819243491,
-0.051378827542066574,
0.08800716698169708,
0.026499217376112938,
-0.03210115432739258,
0.08143291622400284,
-0.015312379226088524,
0.0047188871540129185,
0.1637098491191864,
0.03199009224772453,
-0.11121370643377304,
-0.014423614367842674,
-0.0039847251027822495,
0.04150350019335747,
0.06354492902755737,
0.04669233784079552,
0.049111124128103256,
0.04456554725766182,
-0.013985544443130493,
0.028370151296257973,
-0.10147884488105774,
-0.006825776770710945,
0.03621881827712059,
-0.06431826204061508,
0.09149237722158432,
0.02044081874191761,
-0.0468469113111496,
0.06775179505348206,
-0.015567956492304802,
0.056962527334690094,
0.005873809102922678,
-0.05000955983996391,
-0.10838638246059418,
0.10994570702314377,
-0.0603216215968132,
-0.1598796397447586,
-0.12470214068889618,
0.04931964725255966,
-0.0402187742292881,
0.017657045274972916,
0.01625390723347664,
-0.04153118282556534,
-0.09419040381908417,
-0.09416209906339645,
0.06335379928350449,
-0.02414180524647236,
-0.00635289354249835,
0.03203302621841431,
0.057437241077423096,
0.039268068969249725,
-0.11525993049144745,
-0.012126860208809376,
0.020283887162804604,
-0.10161803662776947,
-0.029823362827301025,
-0.04720050096511841,
0.1119132712483406,
0.07352209836244583,
0.03111363761126995,
0.0356186144053936,
-0.01902010291814804,
0.21426458656787872,
-0.08512415736913681,
0.08337359130382538,
0.25169864296913147,
0.0339038111269474,
0.0806112065911293,
0.13207773864269257,
0.007923114113509655,
-0.0627773329615593,
0.07364356517791748,
0.056214090436697006,
-0.10129909217357635,
-0.20468375086784363,
-0.10848518460988998,
-0.05627046898007393,
-0.03669222071766853,
0.1076398491859436,
0.07484667748212814,
0.12807340919971466,
0.10959973931312561,
-0.0653492882847786,
0.057494647800922394,
0.060271698981523514,
0.11525098234415054,
-0.02294733002781868,
0.01696072891354561,
0.04379187896847725,
-0.06800410151481628,
-0.007026019040495157,
0.11250104755163193,
0.03731215000152588,
0.2563801109790802,
-0.08244876563549042,
0.01934932917356491,
0.031889408826828,
0.022007498890161514,
0.02152937836945057,
0.04680709168314934,
-0.021328415721654892,
0.016339043155312538,
-0.03866931051015854,
-0.13109703361988068,
0.0037163831293582916,
0.15072426199913025,
-0.023328818380832672,
0.029202774167060852,
-0.015427078120410442,
0.01680806651711464,
0.018877753987908363,
0.1137535572052002,
0.005802057217806578,
-0.2804754078388214,
-0.002268268493935466,
0.08190403878688812,
0.04665149003267288,
-0.03362414240837097,
-0.0026854912284761667,
0.13395114243030548,
-0.131003275513649,
0.09125018119812012,
-0.054270170629024506,
0.09631143510341644,
-0.07512369751930237,
-0.057132985442876816,
0.034999314695596695,
0.11259869486093521,
-0.04006223380565643,
0.08298645913600922,
-0.2141510546207428,
0.09669323265552521,
0.00911251362413168,
0.07640702277421951,
-0.08024581521749496,
0.05673709884285927,
0.029429635033011436,
0.021174611523747444,
0.17167584598064423,
-0.02602536231279373,
0.04258314147591591,
-0.07120812684297562,
-0.09631122648715973,
-0.012459042482078075,
0.03105388954281807,
-0.13577277958393097,
0.07151231914758682,
-0.009276696480810642,
-0.010887324810028076,
0.005994058214128017,
-0.003219808219000697,
-0.14744800329208374,
-0.15604203939437866,
0.03348270058631897,
0.04427168145775795,
0.047144800424575806,
-0.08304037898778915,
-0.06086293235421181,
0.04562355577945709,
0.10233521461486816,
-0.009676916524767876,
-0.14212898910045624,
-0.16137787699699402,
0.007389826700091362,
0.1846752166748047,
-0.049214571714401245,
0.009428774937987328,
0.03730231896042824,
0.19890473783016205,
-0.09221481531858444,
-0.09584363549947739,
0.03236929327249527,
-0.0960988774895668,
-0.18344785273075104,
-0.04627564921975136,
0.10162961483001709,
0.0789358913898468,
0.03384290635585785,
-0.012229878455400467,
0.03391807898879051,
0.017489613965153694,
-0.10427939891815186,
0.009115182794630527,
0.1911451518535614,
0.05756799504160881,
0.09162060916423798,
-0.00021158788877073675,
-0.0936763733625412,
-0.07869578152894974,
0.009099964052438736,
-0.019519450142979622,
0.17310741543769836,
-0.042824387550354004,
0.07831607013940811,
0.022985132411122322,
-0.11174602806568146,
-0.16342465579509735,
0.06677640974521637,
0.08265089988708496,
0.0058290995657444,
0.05329150706529617,
-0.1954469084739685,
0.0890071764588356,
0.03584575653076172,
-0.03952817618846893,
0.08191327750682831,
-0.333379328250885,
-0.11189301311969757,
-0.016367755830287933,
0.10376781970262527,
0.020318156108260155,
-0.16526715457439423,
-0.046547744423151016,
-0.08871370553970337,
-0.06843885779380798,
0.13978789746761322,
-0.07398157566785812,
0.02538374625146389,
0.008505095727741718,
0.04099312052130699,
0.06121799349784851,
-0.04317237436771393,
0.10939204692840576,
-0.005088697653263807,
0.052593350410461426,
-0.07997602969408035,
0.009446941316127777,
0.10323534160852432,
-0.07915426045656204,
0.09607764333486557,
-0.07568033039569855,
0.05144460126757622,
-0.1076805591583252,
-0.07058510929346085,
-0.00022576363699045032,
0.06207485496997833,
-0.03466636687517166,
-0.11674211919307709,
-0.050388287752866745,
0.09090690314769745,
0.11708695441484451,
0.010170343331992626,
-0.017022963613271713,
-0.06017731875181198,
-0.0032072123140096664,
0.1582307368516922,
0.0711083635687828,
0.14465434849262238,
-0.07223662734031677,
-0.008611280471086502,
0.001510157249867916,
0.07557633519172668,
-0.20416200160980225,
0.0283221285790205,
0.08545829355716705,
0.014533299021422863,
0.13370291888713837,
0.00975071918219328,
-0.10068682581186295,
0.03965456411242485,
0.0337919257581234,
-0.06637891381978989,
-0.11992651224136353,
-0.06513841450214386,
-0.007364634890109301,
-0.0972602516412735,
-0.03391391411423683,
0.12743248045444489,
-0.0961679071187973,
0.017753858119249344,
-0.016342395916581154,
0.08118755370378494,
-0.025123270228505135,
0.08605775982141495,
0.03806379437446594,
0.019379910081624985,
-0.07629664987325668,
0.10297372192144394,
0.10270491987466812,
-0.07464878261089325,
0.04144377261400223,
0.07942548394203186,
-0.05577917769551277,
0.004031156189739704,
-0.06811679154634476,
0.1448889523744583,
-0.08277969062328339,
-0.027287833392620087,
-0.06671692430973053,
-0.07193242758512497,
0.0018880571005865932,
0.07699693739414215,
0.02923557348549366,
-0.007154164370149374,
0.0071779461577534676,
-0.017246849834918976,
-0.1456923484802246,
0.09592992812395096,
0.04499281197786331,
0.043672557920217514,
-0.16596552729606628,
-0.006288935896009207,
0.029192455112934113,
-0.018213525414466858,
-0.046585872769355774,
-0.016759896650910378,
-0.08452361077070236,
-0.006480269134044647,
-0.049803487956523895,
0.08295485377311707,
-0.08642953634262085,
-0.001759574399329722,
-0.06374969333410263,
-0.06366530060768127,
-0.013327045366168022,
0.0694417878985405,
-0.0427568219602108,
-0.032657165080308914,
-0.021271023899316788,
0.07887544482946396,
-0.11298414319753647,
-0.05950905755162239,
0.04601999744772911,
-0.0985897108912468,
0.050357356667518616,
-0.019529353827238083,
-0.0374632403254509,
-0.03939114883542061,
-0.13009655475616455,
0.06899270415306091,
0.07174666970968246,
0.00447422731667757,
0.01878543198108673,
-0.03900688514113426,
0.006666440051048994,
-0.0073649343103170395,
-0.048280179500579834,
-0.031345024704933167,
-0.01848416216671467,
-0.1435515284538269,
0.01397894136607647,
-0.020042264834046364,
-0.027936967089772224,
-0.03945401310920715,
0.08228254318237305,
0.14975827932357788,
0.05875791236758232,
0.08645182102918625,
-0.059314340353012085,
0.12088875472545624,
-0.19533760845661163,
-0.03366587683558464,
0.024682147428393364,
0.01791744865477085,
-0.02901364304125309,
-0.023346878588199615,
0.047792948782444,
-0.031417571008205414,
0.17225541174411774,
0.059727832674980164,
0.05083945766091347,
0.016055338084697723,
-0.014243162237107754,
0.08193694800138474,
0.021112989634275436,
0.1748899668455124,
0.03323021158576012,
0.04162804037332535,
0.01708843745291233,
0.024235915392637253,
0.05677158012986183,
0.034184396266937256,
0.03359081223607063,
0.08856012672185898,
0.05167212337255478,
0.03057696297764778,
0.04092105105519295,
-0.04269470274448395,
-0.07359869033098221,
0.09046352654695511,
0.020055001601576805,
0.036984317004680634,
-0.06221385300159454,
0.04912291839718819,
0.14185047149658203,
-0.15173523128032684,
0.04579537734389305,
0.08147655427455902,
-0.06423469632863998,
-0.0955449640750885,
-0.20626868307590485,
-0.07823005318641663,
-0.13315968215465546,
0.03122902475297451,
-0.1270115226507187,
0.06470371037721634,
0.06593577563762665,
-0.019280390813946724,
0.026595378294587135,
0.11993516981601715,
-0.058877576142549515,
-0.03581802919507027,
0.02927938662469387,
-0.0012050915975123644,
0.00977576244622469,
0.030522489920258522,
-0.009019440971314907,
0.07987171411514282,
0.047749266028404236,
0.019076935946941376,
0.031063752248883247,
0.04965241253376007,
0.05871771648526192,
-0.0159202441573143,
-0.05977235361933708,
-0.017657240852713585,
0.001287786290049553,
0.004710798617452383,
0.1920710802078247,
0.05183535814285278,
-0.0383387953042984,
-0.027705321088433266,
0.2133033573627472,
-0.08401360362768173,
-0.05303496867418289,
-0.14965404570102692,
0.08058542013168335,
-0.012821737676858902,
0.006266152486205101,
0.006961419712752104,
-0.11399596184492111,
0.0063846115954220295,
0.12393750250339508,
0.19406558573246002,
0.017949366942048073,
-0.004830930382013321,
-0.04366760700941086,
-0.010928910225629807,
-0.02483837865293026,
0.017154529690742493,
0.030279651284217834,
0.2000604122877121,
-0.07879547029733658,
0.07078283280134201,
-0.026088550686836243,
-0.053252097219228745,
-0.02775493636727333,
0.0593523234128952,
-0.03506253659725189,
-0.014741660095751286,
-0.016557034105062485,
0.11058248579502106,
-0.0864366963505745,
-0.21550637483596802,
0.12914541363716125,
-0.12377467006444931,
-0.07989512383937836,
-0.06097528338432312,
-0.027401307597756386,
0.03670848160982132,
0.036381009966135025,
-0.021708862856030464,
-0.030360450968146324,
0.1155305802822113,
0.004354898817837238,
-0.11472573131322861,
-0.06081819534301758,
0.009662766009569168,
-0.07786107808351517,
0.20036403834819794,
-0.022927213460206985,
-0.004781572613865137,
0.043108753859996796,
-0.026455556973814964,
-0.132254958152771,
0.0359916090965271,
0.026812994852662086,
-0.07877126336097717,
-0.00800278689712286,
0.14893421530723572,
-0.08017948269844055,
0.13841165602207184,
0.04441956803202629,
-0.11532653123140335,
-0.004622371401637793,
-0.004173648543655872,
-0.020572969689965248,
-0.11562061309814453,
0.015731951221823692,
-0.12073475867509842,
0.13514472544193268,
0.15305043756961823,
-0.04023570567369461,
0.009345137514173985,
-0.04680601879954338,
0.05894000083208084,
0.021603958681225777,
0.09735981374979019,
0.0305305328220129,
-0.07121263444423676,
-0.04015578702092171,
0.07094407081604004,
0.04972734674811363,
-0.22759324312210083,
-0.039813823997974396,
-0.07156959921121597,
-0.06806416809558868,
-0.008739834651350975,
0.06244660168886185,
0.11362890154123306,
0.008699108846485615,
-0.0348132960498333,
-0.19684144854545593,
0.034486740827560425,
0.11067314445972443,
-0.09790126979351044,
-0.02694164589047432
] |
null | null | transformers |
## Exllama v2 Quantizations of Pasta-PrimaMaid-7b
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.13">turboderp's ExLlamaV2 v0.0.13</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
Original model: https://huggingface.co/Test157t/Pasta-PrimaMaid-7b
| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
| [8_0](https://huggingface.co/bartowski/Pasta-PrimaMaid-7b-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/bartowski/Pasta-PrimaMaid-7b-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
| [5_0](https://huggingface.co/bartowski/Pasta-PrimaMaid-7b-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB | 9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
| [4_25](https://huggingface.co/bartowski/Pasta-PrimaMaid-7b-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| [3_5](https://huggingface.co/bartowski/Pasta-PrimaMaid-7b-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
## Download instructions
With git:
```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Pasta-PrimaMaid-7b-exl2 Pasta-PrimaMaid-7b-exl2-6_5
```
With huggingface hub (credit to TheBloke for instructions):
```shell
pip3 install huggingface-hub
```
To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Pasta-PrimaMaid-7b-exl2`:
```shell
mkdir Pasta-PrimaMaid-7b-exl2
huggingface-cli download bartowski/Pasta-PrimaMaid-7b-exl2 --local-dir Pasta-PrimaMaid-7b-exl2 --local-dir-use-symlinks False
```
To download from a different branch, add the `--revision` parameter:
Linux:
```shell
mkdir Pasta-PrimaMaid-7b-exl2-6_5
huggingface-cli download bartowski/Pasta-PrimaMaid-7b-exl2 --revision 6_5 --local-dir Pasta-PrimaMaid-7b-exl2-6_5 --local-dir-use-symlinks False
```
Windows (which apparently doesn't like _ in folders sometimes?):
```shell
mkdir Pasta-PrimaMaid-7b-exl2-6.5
huggingface-cli download bartowski/Pasta-PrimaMaid-7b-exl2 --revision 6_5 --local-dir Pasta-PrimaMaid-7b-exl2-6.5 --local-dir-use-symlinks False
```
Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Test157t/Kunocchini-7b", "Test157t/Pasta-Made_7b"], "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | text-generation | bartowski/Pasta-PrimaMaid-7b-exl2 | [
"transformers",
"mergekit",
"merge",
"text-generation",
"base_model:Test157t/Kunocchini-7b",
"base_model:Test157t/Pasta-Made_7b",
"endpoints_compatible",
"region:us"
] | 2024-02-09T00:52:28+00:00 | [] | [] | TAGS
#transformers #mergekit #merge #text-generation #base_model-Test157t/Kunocchini-7b #base_model-Test157t/Pasta-Made_7b #endpoints_compatible #region-us
| Exllama v2 Quantizations of Pasta-PrimaMaid-7b
----------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.13 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits per weight, with the main one containing only the URL for further conversions.
Original model: URL
Download instructions
---------------------
With git:
With huggingface hub (credit to TheBloke for instructions):
To download the 'main' (only useful if you only care about URL) branch to a folder called 'Pasta-PrimaMaid-7b-exl2':
To download from a different branch, add the '--revision' parameter:
Linux:
Windows (which apparently doesn't like \_ in folders sometimes?):
Want to support my work? Visit my ko-fi page here: URL
| [] | [
"TAGS\n#transformers #mergekit #merge #text-generation #base_model-Test157t/Kunocchini-7b #base_model-Test157t/Pasta-Made_7b #endpoints_compatible #region-us \n"
] | [
61
] | [
"passage: TAGS\n#transformers #mergekit #merge #text-generation #base_model-Test157t/Kunocchini-7b #base_model-Test157t/Pasta-Made_7b #endpoints_compatible #region-us \n"
] | [
-0.09623723477125168,
-0.06431914120912552,
-0.0011625479673966765,
-0.03835945948958397,
0.0685003250837326,
0.06144099310040474,
0.14794278144836426,
0.1754496991634369,
0.11503976583480835,
0.041587140411138535,
0.11381793767213821,
0.11817989498376846,
0.016868943348526955,
0.15041367709636688,
-0.08522611856460571,
-0.16942767798900604,
0.09344116598367691,
0.10408157110214233,
-0.16058266162872314,
0.10912534594535828,
0.10581883043050766,
-0.04757693409919739,
0.10650788247585297,
-0.018444746732711792,
-0.1778588443994522,
0.0997055172920227,
0.010435403324663639,
-0.04255690425634384,
0.07871360331773758,
0.08783339709043503,
0.13645689189434052,
0.044700343161821365,
-0.11023647338151932,
-0.19031359255313873,
0.03296532481908798,
0.020183423534035683,
-0.030542679131031036,
0.018870888277888298,
0.06278359144926071,
-0.018123149871826172,
0.10532983392477036,
-0.015024082735180855,
-0.016547776758670807,
0.08088702708482742,
-0.13518697023391724,
-0.011532891541719437,
-0.09537764638662338,
0.07933299988508224,
0.09509487450122833,
0.06807471066713333,
-0.013026410713791847,
0.0879233106970787,
-0.05526517704129219,
0.08386443555355072,
0.13536010682582855,
-0.24004624783992767,
-0.047442540526390076,
0.14316372573375702,
0.11061859130859375,
-0.009038299322128296,
0.04004500061273575,
0.06822522729635239,
0.08489430695772171,
-0.04086003080010414,
-0.13809919357299805,
-0.08225499093532562,
0.12230143696069717,
0.013724200427532196,
-0.08748184889554977,
-0.046523112803697586,
0.19903509318828583,
0.014313006773591042,
0.04706588014960289,
-0.033758293837308884,
-0.09612959623336792,
-0.00995637383311987,
-0.01648634672164917,
-0.040618620812892914,
-0.023404086008667946,
0.053056202828884125,
0.04416268691420555,
-0.07529541105031967,
-0.0579100027680397,
-0.07362248003482819,
-0.12839791178703308,
0.2333962321281433,
0.007594017777591944,
0.022098563611507416,
-0.1251564621925354,
0.024699317291378975,
-0.10585775971412659,
-0.13466131687164307,
-0.01564401015639305,
-0.08648033440113068,
-0.009199690073728561,
-0.024226093664765358,
-0.12058776617050171,
-0.13864660263061523,
0.16124647855758667,
0.21526288986206055,
-0.02521851845085621,
0.05916894972324371,
0.02946019172668457,
0.06580237299203873,
0.007789726369082928,
0.05272505804896355,
-0.05671316012740135,
-0.1259777843952179,
-0.013557860627770424,
-0.019506797194480896,
-0.013402328826487064,
-0.008709144778549671,
-0.07562168687582016,
-0.08234168589115143,
-0.015437907539308071,
0.03457362949848175,
0.08603417873382568,
0.02446833625435829,
-0.051621779799461365,
-0.036820974200963974,
0.06002679467201233,
-0.07103640586137772,
-0.013609498739242554,
-0.02882460504770279,
0.012368598952889442,
0.13533291220664978,
-0.021477745845913887,
0.028251543641090393,
-0.0059584323316812515,
0.007343006785959005,
-0.07715883105993271,
-0.043511126190423965,
-0.06975772976875305,
-0.019027650356292725,
0.05690516531467438,
-0.1621578186750412,
0.03169220685958862,
-0.10438980162143707,
-0.16395257413387299,
-0.032956697046756744,
0.035839617252349854,
-0.06410066038370132,
0.011998482048511505,
-0.023518623784184456,
0.02886449731886387,
0.022504983469843864,
-0.013211779296398163,
-0.026109281927347183,
-0.04538197070360184,
-0.0006920142914168537,
0.06022033840417862,
0.054403431713581085,
-0.12024351954460144,
0.0434296652674675,
-0.07920163124799728,
0.09910646826028824,
-0.17130273580551147,
0.05576203763484955,
-0.10498479008674622,
0.13907910883426666,
-0.08871295303106308,
0.014591503888368607,
-0.11976596713066101,
0.029038282111287117,
0.060773346573114395,
0.21250732243061066,
-0.054328553378582,
-0.07720742374658585,
0.11543018370866776,
-0.08711223304271698,
-0.18696492910385132,
0.06973008066415787,
0.008451147936284542,
0.060610443353652954,
0.0661083310842514,
0.23806963860988617,
0.11853480339050293,
0.013017420656979084,
0.02566785179078579,
0.1048012375831604,
-0.033503901213407516,
-0.08727008104324341,
0.07769753783941269,
-0.05594876781105995,
-0.15965567529201508,
0.049240291118621826,
0.018556227907538414,
0.0809331163764,
-0.05853476747870445,
-0.03907089680433273,
-0.09511730819940567,
-0.08296579867601395,
0.1022387146949768,
0.00938963983207941,
0.09319838136434555,
-0.10135648399591446,
-0.033352456986904144,
0.061623141169548035,
0.07934479415416718,
-0.04295671731233597,
0.019881051033735275,
-0.032981038093566895,
0.23691987991333008,
-0.1459982842206955,
0.020127341151237488,
-0.14514978229999542,
-0.058098211884498596,
-0.0019478339236229658,
0.052558593451976776,
-0.021873710677027702,
0.08244077861309052,
0.07330521196126938,
-0.13487376272678375,
-0.03669840842485428,
-0.004548848606646061,
0.08012332767248154,
0.05954127386212349,
-0.05012429133057594,
-0.11100375652313232,
-0.02737237885594368,
-0.06010127812623978,
0.07676853239536285,
-0.028862347826361656,
0.018551606684923172,
0.05095077306032181,
0.2061133235692978,
-0.055416446179151535,
0.04360884428024292,
-0.005330060608685017,
0.029920585453510284,
-0.03744353726506233,
0.010579703375697136,
0.0703728124499321,
-0.016524698585271835,
-0.1191399022936821,
0.09952451288700104,
0.005234544165432453,
0.10819629579782486,
0.1283913254737854,
-0.1552422046661377,
-0.005398586392402649,
-0.03865819424390793,
-0.020147424191236496,
-0.010469253174960613,
0.07812540233135223,
-0.04049450904130936,
0.03352295234799385,
-0.01889340952038765,
0.10312012583017349,
-0.0893554836511612,
-0.013380780816078186,
0.014913945458829403,
-0.04081180319190025,
-0.05969691276550293,
0.060457561165094376,
0.017045261338353157,
-0.2526445686817169,
0.16048982739448547,
0.2278134822845459,
0.02336120791733265,
0.16248930990695953,
-0.036151353269815445,
-0.05348079651594162,
-0.009834346361458302,
0.07283960282802582,
-0.04525107145309448,
0.025599900633096695,
-0.25999245047569275,
0.03713545948266983,
0.03608536347746849,
0.01862463541328907,
0.13456375896930695,
-0.07251494377851486,
0.0030502313748002052,
0.02463904395699501,
-0.012544562108814716,
0.041594307869672775,
0.11243860423564911,
-0.0018286179983988404,
0.07002276927232742,
0.06724507361650467,
-0.008053592406213284,
0.07319995760917664,
0.003940104506909847,
-0.06230087950825691,
0.2154003381729126,
-0.11754095554351807,
-0.2100459188222885,
-0.17886729538440704,
-0.05836866423487663,
-0.0986686423420906,
0.016115592792630196,
0.06440234184265137,
-0.09647392481565475,
-0.004397151060402393,
-0.014891650527715683,
0.0406116247177124,
-0.024900181218981743,
0.0013009357498958707,
0.014347773976624012,
0.05140731856226921,
-0.040914930403232574,
-0.06535279750823975,
-0.049433499574661255,
0.017291247844696045,
0.038595329970121384,
0.01743883080780506,
-0.2010868787765503,
0.11581377685070038,
0.13737112283706665,
0.010006893426179886,
0.028790658339858055,
-0.008635682053864002,
0.17414826154708862,
-0.10319304466247559,
0.020495638251304626,
0.19725018739700317,
-0.030173707753419876,
0.02954133041203022,
0.1335480958223343,
-0.01804816722869873,
-0.06366636604070663,
-0.009175604209303856,
-0.02619200013577938,
-0.04584358260035515,
-0.2512454092502594,
-0.0790342167019844,
-0.13999037444591522,
0.04675262048840523,
0.020495116710662842,
0.01693391241133213,
0.056742291897535324,
0.11538323014974594,
-0.00808910932391882,
-0.040522217750549316,
-0.044555291533470154,
0.04318960756063461,
0.2531614303588867,
-0.032880403101444244,
0.09820958226919174,
-0.0857490748167038,
-0.018939681351184845,
0.07310189306735992,
0.10650409013032913,
0.08921323716640472,
0.09969374537467957,
0.10898073762655258,
0.057238154113292694,
0.08373714983463287,
0.10367827862501144,
0.08791878074407578,
0.0011086080921813846,
-0.03986506909132004,
0.008479936048388481,
-0.03592073172330856,
-0.0325496643781662,
0.044499851763248444,
0.004284678492695093,
-0.08125154674053192,
-0.05909628048539162,
-0.11608068645000458,
0.07442664355039597,
0.15175075829029083,
0.13840621709823608,
-0.22710084915161133,
-0.049595657736063004,
0.044825535267591476,
-0.001888349070213735,
-0.08800698071718216,
0.013657073490321636,
-0.04122095927596092,
-0.10164155066013336,
0.13876502215862274,
-0.021926015615463257,
0.12960489094257355,
0.0847645252943039,
0.003758417209610343,
-0.001957748318091035,
-0.056444425135850906,
-0.009983513504266739,
0.09715864807367325,
-0.1720578670501709,
0.2394528090953827,
-0.0004947633715346456,
-0.050278861075639725,
-0.0411432683467865,
0.020914578810334206,
0.005545074585825205,
0.20239274203777313,
0.07780776917934418,
0.008746420033276081,
-0.06043311581015587,
-0.06878781318664551,
-0.02124028280377388,
0.013248042203485966,
0.10311365127563477,
0.007345204707235098,
0.04578077793121338,
-0.03796343877911568,
-0.022919775918126106,
-0.009223287925124168,
0.054089222103357315,
-0.10405005514621735,
-0.1282818466424942,
0.07477673888206482,
-0.004900017287582159,
0.03017255663871765,
-0.0398288369178772,
-0.01004744227975607,
-0.021570321172475815,
0.25952503085136414,
0.02875746600329876,
-0.056555259972810745,
-0.13349711894989014,
-0.031713590025901794,
0.18493303656578064,
-0.06466055661439896,
0.07729916274547577,
-0.0910867229104042,
-0.0034439638257026672,
-0.07292640954256058,
-0.18082161247730255,
0.12030895054340363,
-0.08872931450605392,
-0.05073565989732742,
-0.0129861356690526,
0.1192120611667633,
-0.10568200796842575,
0.00998113676905632,
0.050259578973054886,
0.02698945254087448,
-0.08234818279743195,
-0.025609007105231285,
-0.06107417121529579,
0.029739592224359512,
-0.006362795829772949,
0.13225509226322174,
-0.03343604505062103,
0.026558050885796547,
-0.015549498610198498,
-0.00423450767993927,
0.17783941328525543,
0.21146292984485626,
-0.013566174544394016,
0.05331728607416153,
0.07211358100175858,
-0.0819794088602066,
-0.22735562920570374,
0.030796227976679802,
-0.06420554965734482,
0.027382895350456238,
-0.07679858803749084,
-0.05797884240746498,
0.077545166015625,
0.09783127903938293,
-0.01011241227388382,
0.06565705686807632,
-0.24148163199424744,
-0.10817886143922806,
0.06628701835870743,
0.002436669310554862,
0.3588218688964844,
-0.13023057579994202,
-0.10045310109853745,
-0.11089777201414108,
-0.21516969799995422,
-0.04486881196498871,
-0.05655056983232498,
0.08651161938905716,
-0.06073346361517906,
-0.06734752655029297,
0.016677819192409515,
-0.06641053408384323,
0.16184332966804504,
-0.018160482868552208,
-0.003764605149626732,
-0.07168092578649521,
-0.008842675015330315,
0.11225070804357529,
-0.03812243416905403,
0.019174832850694656,
-0.07121337950229645,
0.04411093890666962,
-0.19268864393234253,
-0.05805649608373642,
-0.05817718058824539,
0.07161061465740204,
-0.012849816121160984,
-0.01403010543435812,
-0.057371046394109726,
0.020639359951019287,
-0.018743697553873062,
0.012848224490880966,
0.207493856549263,
-0.09477792680263519,
0.1672140210866928,
0.15925750136375427,
0.09092643111944199,
-0.15869133174419403,
0.008037559688091278,
0.04431905597448349,
-0.0635414719581604,
0.04034915566444397,
-0.14210568368434906,
-0.005090105347335339,
0.11223337054252625,
-0.015043203718960285,
0.025128310546278954,
0.07576651126146317,
-0.018031755462288857,
-0.008335491642355919,
0.13509994745254517,
-0.12141330540180206,
-0.06352226436138153,
-0.08032521605491638,
-0.1231825202703476,
-0.04031679034233093,
0.06912040710449219,
0.1621164232492447,
0.01625644415616989,
-0.016547050327062607,
-0.026764385402202606,
-0.04095156863331795,
-0.17326435446739197,
0.11485661566257477,
0.05952739343047142,
0.034829676151275635,
-0.065721794962883,
0.07581192255020142,
-0.032937079668045044,
-0.19914022088050842,
-0.020465441048145294,
0.06921610981225967,
-0.10807644575834274,
-0.10438752919435501,
0.0045451028272509575,
0.17504341900348663,
-0.1637970358133316,
-0.061067137867212296,
-0.1755000650882721,
-0.10623932629823685,
0.07138167321681976,
0.24650156497955322,
0.12787866592407227,
0.04802006483078003,
0.030733002349734306,
-0.05832080915570259,
-0.009107534773647785,
-0.0024224913213402033,
0.05936857685446739,
0.09188548475503922,
-0.054518647491931915,
-0.08323899656534195,
-0.059728458523750305,
0.0973295047879219,
-0.06966398656368256,
-0.011679375544190407,
-0.18489553034305573,
0.009243924170732498,
-0.21316727995872498,
-0.07794177532196045,
-0.12060249596834183,
-0.0775633305311203,
-0.014237727038562298,
-0.04437021166086197,
-0.07045876234769821,
-0.012912559323012829,
-0.08572914451360703,
-0.011605193838477135,
-0.03500847518444061,
0.02888253703713417,
-0.05161851644515991,
0.04419703781604767,
0.11545531451702118,
-0.06506840139627457,
0.03953055292367935,
0.04369288310408592,
-0.03191199153661728,
0.028315603733062744,
-0.09324710071086884,
-0.08102981001138687,
0.007586262654513121,
0.0054823472164571285,
0.022856932133436203,
-0.05745774507522583,
0.043614793568849564,
0.08058211207389832,
0.052264027297496796,
0.043759699910879135,
0.02478727139532566,
-0.06898274272680283,
-0.032124850898981094,
-0.058661218732595444,
-0.11867764592170715,
-0.02968103624880314,
-0.023278001695871353,
0.12969842553138733,
0.07030405104160309,
0.07376160472631454,
-0.02421250008046627,
0.06076155975461006,
-0.0944368839263916,
-0.011461959220468998,
-0.0008764176163822412,
-0.1497274935245514,
0.07071086764335632,
-0.09569869935512543,
0.018946461379528046,
0.02723236382007599,
0.2508068382740021,
-0.03765539452433586,
0.010905999690294266,
0.059665072709321976,
-0.05640942603349686,
0.14222846925258636,
0.06272582709789276,
0.3898376226425171,
0.09451044350862503,
-0.006279545370489359,
-0.08375618606805801,
0.09248429536819458,
-0.01256211381405592,
0.03721513971686363,
0.06374073028564453,
0.23024104535579681,
-0.06867983192205429,
0.1461523324251175,
0.08270582556724548,
0.06889330595731735,
0.05786386504769325,
-0.13401047885417938,
-0.044654130935668945,
0.047474123537540436,
0.008810335770249367,
0.08688074350357056,
0.13732139766216278,
-0.17817263305187225,
0.051554467529058456,
-0.01897767372429371,
-0.062234945595264435,
-0.11092840135097504,
-0.07331305742263794,
-0.10422122478485107,
-0.25713804364204407,
0.03200848773121834,
-0.10339856147766113,
0.003841760102659464,
0.07641155272722244,
0.026160622015595436,
-0.04393390193581581,
0.19986572861671448,
-0.001828452106565237,
-0.05887078493833542,
0.10221128910779953,
-0.03269626945257187,
0.015076139010488987,
0.01824057660996914,
-0.09007952362298965,
-0.04247007891535759,
-0.07671116292476654,
-0.052995502948760986,
0.013751981779932976,
-0.07719293236732483,
0.02738775499165058,
-0.03758789598941803,
-0.09431189298629761,
-0.025944698601961136,
0.04342767968773842,
0.02846486307680607,
0.057151127606630325,
-0.0031960085034370422,
0.01338167954236269,
0.011403597891330719,
0.1330472081899643,
-0.03735426068305969,
-0.08827794343233109,
-0.08786625415086746,
0.0973992869257927,
0.03294992819428444,
0.08464911580085754,
-0.03650180250406265,
-0.0390106737613678,
-0.004637981299310923,
0.26208624243736267,
0.2490999698638916,
-0.005020276643335819,
-0.009620373137295246,
0.052640918642282486,
0.03532904386520386,
0.10489767789840698,
0.10453048348426819,
0.0002284320507897064,
0.06527575105428696,
-0.07221727818250656,
-0.059715814888477325,
0.0146550377830863,
-0.0909515991806984,
-0.09708347171545029,
0.02171485312283039,
0.10558350384235382,
-0.11215648800134659,
-0.00885938759893179,
0.175667867064476,
-0.09451352804899216,
0.1271073967218399,
0.09197712689638138,
-0.18224747478961945,
-0.1060890331864357,
-0.09551283717155457,
0.11324413120746613,
-0.06532873213291168,
0.0956188514828682,
-0.04692727327346802,
-0.061658307909965515,
0.07410868257284164,
0.011755240149796009,
-0.1469341516494751,
-0.16875837743282318,
0.05101699382066727,
-0.03223783150315285,
-0.07086309045553207,
-0.021014010533690453,
0.048170994967222214,
0.15681906044483185,
0.038346391171216965,
-0.06388033926486969,
-0.005617950577288866,
0.0550287626683712,
-0.03540691360831261,
0.00958249531686306,
-0.015908481553196907,
0.005932911764830351,
-0.017886970192193985,
0.04737699031829834,
-0.1825786530971527,
0.07550656795501709,
-0.02242335118353367,
0.02849075011909008,
-0.11475329846143723,
0.027424262836575508,
-0.10705941170454025,
0.13937577605247498,
0.1532537341117859,
-0.04258910194039345,
-0.009149597957730293,
-0.010196946561336517,
0.04959799349308014,
0.07419855892658234,
0.07160820066928864,
-0.10996971279382706,
-0.18436278402805328,
-0.0853414461016655,
0.07796876132488251,
-0.026331497356295586,
-0.21722282469272614,
-0.057245947420597076,
-0.08812010288238525,
0.031859803944826126,
-0.03577951341867447,
0.11404328793287277,
0.11010612547397614,
0.00804015714675188,
0.004696210380643606,
-0.26549482345581055,
0.011738717555999756,
0.1021011546254158,
-0.1096692681312561,
-0.0925757884979248
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# nees-bert-base-portuguese-cased-finetuned-ner
This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0349
- Precision: 0.6141
- Recall: 0.7093
- F1: 0.6583
- Accuracy: 0.9933
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 364 | 0.0189 | 0.0 | 0.0 | 0.0 | 0.9936 |
| 0.0259 | 2.0 | 728 | 0.0170 | 0.625 | 0.3876 | 0.4785 | 0.9940 |
| 0.0159 | 3.0 | 1092 | 0.0238 | 0.6015 | 0.6085 | 0.6050 | 0.9941 |
| 0.0159 | 4.0 | 1456 | 0.0228 | 0.5163 | 0.6744 | 0.5849 | 0.9943 |
| 0.0129 | 5.0 | 1820 | 0.0139 | 0.5353 | 0.6473 | 0.5860 | 0.9930 |
| 0.01 | 6.0 | 2184 | 0.0209 | 0.6138 | 0.6899 | 0.6496 | 0.9933 |
| 0.0063 | 7.0 | 2548 | 0.0285 | 0.4970 | 0.6473 | 0.5623 | 0.9923 |
| 0.0063 | 8.0 | 2912 | 0.0372 | 0.6 | 0.6860 | 0.6401 | 0.9927 |
| 0.0035 | 9.0 | 3276 | 0.0382 | 0.6289 | 0.7093 | 0.6667 | 0.9931 |
| 0.003 | 10.0 | 3640 | 0.0349 | 0.6141 | 0.7093 | 0.6583 | 0.9933 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "neuralmind/bert-base-portuguese-cased", "model-index": [{"name": "nees-bert-base-portuguese-cased-finetuned-ner", "results": []}]} | token-classification | yuridrcosta/nees-bert-base-portuguese-cased-finetuned-ner | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:neuralmind/bert-base-portuguese-cased",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T00:54:55+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #token-classification #generated_from_trainer #base_model-neuralmind/bert-base-portuguese-cased #license-mit #autotrain_compatible #endpoints_compatible #region-us
| nees-bert-base-portuguese-cased-finetuned-ner
=============================================
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0349
* Precision: 0.6141
* Recall: 0.7093
* F1: 0.6583
* Accuracy: 0.9933
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #bert #token-classification #generated_from_trainer #base_model-neuralmind/bert-base-portuguese-cased #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
73,
98,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #bert #token-classification #generated_from_trainer #base_model-neuralmind/bert-base-portuguese-cased #license-mit #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.10049349814653397,
0.10624450445175171,
-0.002645322820171714,
0.11442355066537857,
0.15609605610370636,
0.012205423787236214,
0.1432584822177887,
0.10422838479280472,
-0.06371830403804779,
0.06251199543476105,
0.1182883158326149,
0.11836466193199158,
0.019051462411880493,
0.09654796123504639,
-0.04238543286919594,
-0.23691216111183167,
0.02768847532570362,
0.03581949695944786,
-0.07066327333450317,
0.10217471420764923,
0.08105681091547012,
-0.14052501320838928,
0.08320846408605576,
-0.0004264755407348275,
-0.17350362241268158,
0.01264219544827938,
0.036940306425094604,
-0.06388162076473236,
0.13200360536575317,
0.03505326807498932,
0.15083973109722137,
0.027823833748698235,
0.0922355130314827,
-0.16767403483390808,
0.00901632197201252,
0.04497109726071358,
0.007266210857778788,
0.0814327597618103,
0.056817419826984406,
-0.006317065563052893,
0.05324813351035118,
-0.06959109753370285,
0.06359723955392838,
0.012474977411329746,
-0.15288056433200836,
-0.23756130039691925,
-0.07565578073263168,
0.02683330327272415,
0.07940077781677246,
0.08822549879550934,
-0.02214403636753559,
0.145689457654953,
-0.05722828209400177,
0.07380557805299759,
0.22494696080684662,
-0.3092030882835388,
-0.07517974823713303,
0.03332541510462761,
0.01567758060991764,
0.06353896856307983,
-0.09308890253305435,
-0.016059786081314087,
0.07263124734163284,
0.01426868699491024,
0.12242766469717026,
-0.03440927341580391,
-0.006333347875624895,
0.005987616255879402,
-0.14370329678058624,
-0.017663367092609406,
0.12058154493570328,
0.056888896971940994,
-0.03960178792476654,
-0.03260575607419014,
-0.05707215517759323,
-0.12530027329921722,
-0.05221470817923546,
-0.011032093316316605,
0.03952556475996971,
-0.03453795611858368,
-0.053449589759111404,
-0.008729762397706509,
-0.08937094360589981,
-0.06241043284535408,
-0.05539333075284958,
0.17725996673107147,
0.03276887536048889,
-0.011790230870246887,
0.01444239355623722,
0.08901908248662949,
-0.03745262324810028,
-0.1386125087738037,
0.03678479418158531,
0.036819323897361755,
-0.013401533477008343,
-0.060771431773900986,
-0.029851391911506653,
-0.07245469838380814,
0.01666206493973732,
0.11778920143842697,
-0.014220412820577621,
0.030459633097052574,
0.00026422241353429854,
0.04433303698897362,
-0.10181737691164017,
0.18545040488243103,
-0.09405811876058578,
-0.014915143139660358,
0.014439992606639862,
0.0790034607052803,
0.030233174562454224,
-0.006282573565840721,
-0.14564718306064606,
0.029941996559500694,
0.10479890555143356,
0.020007280632853508,
-0.07196866720914841,
0.06605753302574158,
-0.0628972053527832,
-0.028138110414147377,
0.009536185301840305,
-0.07825502008199692,
0.03312157839536667,
0.015690231695771217,
-0.07208528369665146,
-0.03821217641234398,
-0.0023759605828672647,
0.021880460903048515,
0.010239891707897186,
0.11174746602773666,
-0.10549698024988174,
0.011100644245743752,
-0.09618774056434631,
-0.14907537400722504,
0.01134202815592289,
-0.07854358851909637,
0.029983729124069214,
-0.10952726006507874,
-0.14265196025371552,
-0.019473565742373466,
0.05389537662267685,
-0.05221737548708916,
-0.0016506934771314263,
-0.06847940385341644,
-0.08350485563278198,
0.00012264114047866315,
-0.01078241690993309,
0.049820926040410995,
-0.05835247412323952,
0.10234435647726059,
0.05815594643354416,
0.06685472279787064,
-0.05953923612833023,
0.034915726631879807,
-0.1041160300374031,
0.03985632210969925,
-0.21115471422672272,
0.03706541657447815,
-0.06968359649181366,
0.06589986383914948,
-0.09243176877498627,
-0.08452677726745605,
0.0007883256184868515,
0.00034973578294739127,
0.09047218412160873,
0.10096196085214615,
-0.17343316972255707,
-0.08568967133760452,
0.17699439823627472,
-0.08028225600719452,
-0.1359146684408188,
0.1370035707950592,
-0.06501799821853638,
0.07206588238477707,
0.06893264502286911,
0.20826002955436707,
0.05678563192486763,
-0.08790496736764908,
0.021899618208408356,
-0.05325113981962204,
0.06286082416772842,
-0.021816778928041458,
0.07781259715557098,
-0.00013244501315057278,
-0.003724050475284457,
0.010962068103253841,
-0.07298722118139267,
0.07678935676813126,
-0.08321995288133621,
-0.08205832540988922,
-0.003999026492238045,
-0.10312367975711823,
0.08602773398160934,
0.06420303881168365,
0.06989198178052902,
-0.11105519533157349,
-0.08040279895067215,
0.08433470129966736,
0.05707711726427078,
-0.07228749245405197,
0.005203812383115292,
-0.08914080262184143,
0.09820585697889328,
-0.09511756896972656,
-0.03296980261802673,
-0.14741073548793793,
-0.06182880699634552,
0.021822532638907433,
0.017360186204314232,
0.03685244545340538,
0.00785117782652378,
0.0781547874212265,
0.08488550037145615,
-0.06628425419330597,
-0.03965866565704346,
-0.025232499465346336,
0.020214062184095383,
-0.1004854217171669,
-0.19735756516456604,
-0.006235097534954548,
-0.02433331310749054,
0.1460929960012436,
-0.22455839812755585,
0.04466426372528076,
-0.006225300952792168,
0.11289506405591965,
0.04223361238837242,
-0.014114536345005035,
-0.03817078843712807,
0.06864200532436371,
-0.030234357342123985,
-0.07255687564611435,
0.07034964859485626,
-0.007083744276314974,
-0.0900934487581253,
-0.0484246201813221,
-0.15840330719947815,
0.2023916095495224,
0.12853509187698364,
-0.06617612391710281,
-0.08368147164583206,
0.00956912711262703,
-0.029140828177332878,
-0.019896848127245903,
-0.04093305021524429,
0.0006428785272873938,
0.160429447889328,
-0.00005517598401638679,
0.1482526659965515,
-0.09844273328781128,
-0.019112603738904,
0.04049881920218468,
-0.03909531980752945,
0.002611362375319004,
0.10927242040634155,
0.0928485170006752,
-0.12938976287841797,
0.15503881871700287,
0.14655941724777222,
-0.08559605479240417,
0.14809954166412354,
-0.036033306270837784,
-0.05896734818816185,
-0.038775548338890076,
0.009672078303992748,
0.023670116439461708,
0.14153942465782166,
-0.13774468004703522,
-0.010494171641767025,
0.008928430266678333,
0.007094866130501032,
0.0031532656867057085,
-0.20905587077140808,
-0.03289813548326492,
0.03430796042084694,
-0.03440161794424057,
0.00902998261153698,
-0.01899656653404236,
-0.004757898394018412,
0.10050367563962936,
0.014028040692210197,
-0.09736138582229614,
0.02858356572687626,
-0.00019848777446895838,
-0.07958469539880753,
0.19376952946186066,
-0.0795438140630722,
-0.13643553853034973,
-0.13511218130588531,
-0.0449528731405735,
-0.05861412361264229,
0.045633114874362946,
0.04946074262261391,
-0.07730257511138916,
-0.030415231361985207,
-0.07816893607378006,
0.025145793333649635,
0.032748281955718994,
0.025721406564116478,
0.00002951707210741006,
-0.0000741770927561447,
0.06550581753253937,
-0.09210316836833954,
-0.007838624529540539,
-0.04362216219305992,
-0.039046600461006165,
0.013384540565311909,
-0.0021893256343901157,
0.1311655193567276,
0.16654065251350403,
-0.029032383114099503,
0.007192411459982395,
-0.035146843641996384,
0.24228189885616302,
-0.0824468582868576,
-0.013412641361355782,
0.11076445877552032,
-0.030166927725076675,
0.030648326501250267,
0.16560091078281403,
0.06867150217294693,
-0.09808478504419327,
0.013074914924800396,
0.04573122784495354,
-0.021242927759885788,
-0.20553861558437347,
-0.03531816229224205,
-0.039215799421072006,
0.0012730180751532316,
0.10212995111942291,
0.01722596399486065,
0.015778323635458946,
0.0774432048201561,
0.029807912185788155,
0.058529991656541824,
-0.016191089525818825,
0.08236394822597504,
0.11015667021274567,
0.0320163369178772,
0.11866843700408936,
-0.03253442794084549,
-0.10092760622501373,
0.033001579344272614,
0.0011760350316762924,
0.19428908824920654,
0.037237897515296936,
0.15586331486701965,
0.04735531657934189,
0.1578560471534729,
-0.005833130329847336,
0.07375430315732956,
-0.006113084498792887,
-0.058718450367450714,
-0.022410154342651367,
-0.046290602535009384,
-0.036043863743543625,
0.019303541630506516,
-0.04072122648358345,
0.07112599909305573,
-0.11544277518987656,
-0.016283389180898666,
0.06011148914694786,
0.18847115337848663,
0.05802146717905998,
-0.3314526081085205,
-0.08640242367982864,
0.019061563536524773,
-0.013876966200768948,
-0.02810264565050602,
0.016599880531430244,
0.13936343789100647,
-0.05322698503732681,
0.011777346022427082,
-0.07585421204566956,
0.07938394695520401,
-0.05325854569673538,
0.03981192037463188,
0.032380543649196625,
0.07168133556842804,
-0.015565873123705387,
0.07039886713027954,
-0.23240529000759125,
0.28788986802101135,
0.01834595762193203,
0.0653534084558487,
-0.045445516705513,
-0.014127103611826897,
0.02873239666223526,
0.09003068506717682,
0.07952097803354263,
-0.014534135349094868,
-0.049622196704149246,
-0.2124696969985962,
-0.04425395280122757,
0.013376499526202679,
0.0956004336476326,
-0.05773891881108284,
0.11553440988063812,
-0.02402598038315773,
-0.0042722891084849834,
0.07546164840459824,
0.013990459032356739,
-0.07520702481269836,
-0.08449992537498474,
-0.004361776635050774,
0.03147794306278229,
-0.012905992567539215,
-0.07933061569929123,
-0.11057911068201065,
-0.14068225026130676,
0.15632018446922302,
-0.03391431272029877,
-0.01930680125951767,
-0.11804699897766113,
0.08039913326501846,
0.06885774433612823,
-0.07808670401573181,
0.03011220321059227,
0.0024639980401843786,
0.10463263094425201,
0.014702307991683483,
-0.024894459173083305,
0.14964863657951355,
-0.06278126686811447,
-0.15461178123950958,
-0.08678516745567322,
0.1160811260342598,
0.02770482935011387,
0.056816890835762024,
0.002356358338147402,
0.0021852811332792044,
0.01267315074801445,
-0.07347533851861954,
0.03083939477801323,
-0.024741528555750847,
0.028974642977118492,
0.007991841994225979,
-0.0672379657626152,
-0.005185349378734827,
-0.0779576376080513,
-0.013980740681290627,
0.15926337242126465,
0.26239100098609924,
-0.08955955505371094,
-0.021886352449655533,
0.05736469477415085,
-0.060946665704250336,
-0.19852234423160553,
0.07061510533094406,
0.05528941750526428,
0.01014158595353365,
0.03308980166912079,
-0.14479833841323853,
0.09432032704353333,
0.09777885675430298,
-0.022221548482775688,
0.075111523270607,
-0.2793009579181671,
-0.12380974739789963,
0.1272878497838974,
0.16836553812026978,
0.1232513040304184,
-0.150437131524086,
-0.036726467311382294,
-0.02979184500873089,
-0.1130470260977745,
0.10382863134145737,
-0.12175419926643372,
0.1066197082400322,
0.015153810381889343,
0.0671059638261795,
0.015927627682685852,
-0.053154122084379196,
0.12531253695487976,
-0.004408791661262512,
0.1107335314154625,
-0.04537932947278023,
-0.06024156138300896,
0.07162398099899292,
-0.044745802879333496,
0.012949833646416664,
-0.028276683762669563,
0.020172718912363052,
-0.04472023621201515,
-0.03871111944317818,
-0.06263131648302078,
0.0376899391412735,
-0.028170675039291382,
-0.06863760203123093,
-0.045724835246801376,
0.05216855928301811,
0.035582367330789566,
0.00014032554463483393,
0.14200253784656525,
0.0008071770425885916,
0.13153764605522156,
0.1106768473982811,
0.085059754550457,
-0.06439719349145889,
-0.01975826360285282,
0.008924047462642193,
-0.025529034435749054,
0.05783046409487724,
-0.11677788197994232,
0.04173136502504349,
0.13824358582496643,
0.0036212727427482605,
0.15388181805610657,
0.07020627707242966,
-0.056786052882671356,
0.007575094234198332,
0.06564067304134369,
-0.13796551525592804,
-0.1268739551305771,
-0.016442887485027313,
-0.03663645312190056,
-0.11079461127519608,
0.04852473735809326,
0.12079876661300659,
-0.07095411419868469,
-0.00815837737172842,
-0.0020777820609509945,
-0.0273162592202425,
-0.04015812650322914,
0.17870809137821198,
0.07509902864694595,
0.04400444030761719,
-0.07680719345808029,
0.06783325225114822,
0.05896715819835663,
-0.09666691720485687,
0.00254427851177752,
0.0398799292743206,
-0.09300633519887924,
-0.04739081487059593,
0.043598443269729614,
0.2442166656255722,
-0.054715368896722794,
-0.04265778511762619,
-0.1609128713607788,
-0.11861301958560944,
0.04046660661697388,
0.189676433801651,
0.09388823807239532,
-0.00479810731485486,
-0.03407733514904976,
0.015160446055233479,
-0.1146128848195076,
0.11918272078037262,
0.03571176528930664,
0.08576706796884537,
-0.1432957798242569,
0.13459211587905884,
-0.003617494134232402,
-0.008111564442515373,
-0.029363995417952538,
0.04109765961766243,
-0.13870026171207428,
0.005097880959510803,
-0.11244940757751465,
-0.01682785525918007,
-0.03332750126719475,
0.000916013668756932,
0.01071842946112156,
-0.07764504849910736,
-0.061463143676519394,
-0.00377806113101542,
-0.1152583435177803,
-0.008662155829370022,
0.05185098201036453,
0.058264728635549545,
-0.09704618155956268,
-0.054380279034376144,
0.01701330579817295,
-0.06113025173544884,
0.06469541043043137,
0.0057425773702561855,
0.035020772367715836,
0.06688417494297028,
-0.15339559316635132,
0.024340275675058365,
0.0562572106719017,
0.01001184806227684,
0.07185877859592438,
-0.11850062757730484,
-0.00467970734462142,
-0.009466472081840038,
0.061163149774074554,
0.02150917425751686,
0.06720461696386337,
-0.11660371720790863,
-0.0032833456061780453,
-0.011555822566151619,
-0.07918892800807953,
-0.039341364055871964,
0.03257414698600769,
0.07107432186603546,
-0.009609604254364967,
0.19351518154144287,
-0.09270502626895905,
0.035181913524866104,
-0.19288620352745056,
0.002618424128741026,
-0.013503705151379108,
-0.10898730903863907,
-0.09925908595323563,
-0.061182357370853424,
0.04749201238155365,
-0.060823917388916016,
0.12141243368387222,
0.027773410081863403,
0.05539768189191818,
0.02715343050658703,
-0.053021032363176346,
0.0541495643556118,
0.03808016702532768,
0.2104673981666565,
0.041423410177230835,
-0.04606495797634125,
0.015897903591394424,
0.05595678091049194,
0.10389067977666855,
0.12438850104808807,
0.15893951058387756,
0.1502613127231598,
-0.014994252473115921,
0.09901987016201019,
0.05983346700668335,
-0.033143192529678345,
-0.1464586853981018,
0.0595463402569294,
-0.009636391885578632,
0.0704192966222763,
-0.00827029813081026,
0.2119021862745285,
0.12102268636226654,
-0.15515656769275665,
0.022798873484134674,
-0.03875298798084259,
-0.08514835685491562,
-0.09596916288137436,
-0.07150732725858688,
-0.09260421991348267,
-0.151734858751297,
-0.0015744231641292572,
-0.11666455119848251,
-0.016151729971170425,
0.07368229329586029,
0.009484010748565197,
-0.022985156625509262,
0.19509050250053406,
-0.008386600762605667,
0.021068749949336052,
0.0638391450047493,
0.020844656974077225,
-0.030319450423121452,
-0.09916175901889801,
-0.0676327645778656,
-0.019723540171980858,
-0.013028844259679317,
0.017435215413570404,
-0.049083322286605835,
-0.03395853191614151,
0.01971013844013214,
0.0003174451703671366,
-0.11100246757268906,
0.01166487392038107,
0.021127348765730858,
0.04868080094456673,
0.05661781504750252,
0.0005547536420635879,
-0.002639921847730875,
-0.008107281289994717,
0.1943029910326004,
-0.07268054038286209,
-0.05331173911690712,
-0.11516677588224411,
0.22440941631793976,
0.015243899077177048,
0.03436531871557236,
-0.004327019210904837,
-0.09560821950435638,
0.038465410470962524,
0.251152366399765,
0.172939732670784,
-0.08577646315097809,
-0.006458924617618322,
-0.0031840300653129816,
-0.009093583561480045,
-0.04078655317425728,
0.07555714249610901,
0.08658497035503387,
0.011074453592300415,
-0.08410365134477615,
-0.056734535843133926,
-0.05410623177886009,
-0.00623110868036747,
-0.04091690480709076,
0.05723300203680992,
0.05478827655315399,
0.02476840652525425,
-0.0725964605808258,
0.07185538858175278,
-0.05287015065550804,
-0.11580503731966019,
0.07085483521223068,
-0.19532820582389832,
-0.15568678081035614,
-0.030358344316482544,
0.07851944863796234,
-0.002399775432422757,
0.07429640740156174,
-0.03776739910244942,
-0.007292586844414473,
0.05797738954424858,
-0.008245788514614105,
-0.07352397590875626,
-0.08381626754999161,
0.055427636951208115,
-0.08050442487001419,
0.250444233417511,
-0.042512938380241394,
0.03415174409747124,
0.14242298901081085,
0.039363425225019455,
-0.08148670196533203,
0.07652456313371658,
0.05666673928499222,
-0.05947893112897873,
0.037271514534950256,
0.08413369208574295,
-0.03385768458247185,
0.12444119900465012,
0.05285758897662163,
-0.17631666362285614,
0.023814532905817032,
-0.05943213775753975,
-0.07708248496055603,
-0.06505299359560013,
-0.010919741354882717,
-0.06800523400306702,
0.13030129671096802,
0.1843939572572708,
-0.03349996358156204,
-0.001499292440712452,
-0.043817874044179916,
0.02274709939956665,
0.08989305794239044,
0.07844333350658417,
-0.03784877061843872,
-0.24013321101665497,
0.011571431532502174,
0.05844467133283615,
-0.02385619282722473,
-0.30640721321105957,
-0.07398094981908798,
-0.007657268084585667,
-0.046330515295267105,
-0.0838453397154808,
0.08202686160802841,
0.08809994161128998,
0.06196825951337814,
-0.06379372626543045,
-0.12316949665546417,
-0.07574265450239182,
0.15210212767124176,
-0.11632414162158966,
-0.09427733719348907
] |
null | null | null |
# [ICLR'24] Guiding Instruction-based Image Editing via Multimodal Large Language Models
This repo contains [LLaVA-7B](https://huggingface.co/liuhaotian/LLaVA-Lightning-7B-delta-v1-1) and [pre-trained MGIE ckpt](https://docs-assets.developer.apple.com/ml-research/models/mgie/mgie_7b.tar.gz) (on IPr2Pr + MagicBrush) for [MGIE](https://huggingface.co/spaces/tsujuifu/ml-mgie)
<img src="https://raw.githubusercontent.com/apple/ml-mgie/main/mgie.png" width="60%" />
Please follow the [offical repo](https://github.com/apple/ml-mgie) and [ipynb](https://github.com/apple/ml-mgie/blob/main/demo.ipynb) to use it
<img src="https://raw.githubusercontent.com/apple/ml-mgie/main/demo.png" width="60%" />
```
@inproceedings{fu2024mgie,
author = {Tsu-Jui Fu and Wenze Hu and Xianzhi Du and William Yang Wang and Yinfei Yang, and Zhe Gan},
title = {{Guiding Instruction-based Image Editing via Multimodal Large Language Models}},
booktitle = {International Conference on Learning Representations (ICLR)},
year = {2024}
}
```
| {"license": "other", "license_name": "ml-mgie", "license_link": "https://github.com/apple/ml-mgie/blob/main/LICENSE.txt"} | null | tsujuifu/ml-mgie | [
"license:other",
"has_space",
"region:us"
] | 2024-02-09T00:58:49+00:00 | [] | [] | TAGS
#license-other #has_space #region-us
|
# [ICLR'24] Guiding Instruction-based Image Editing via Multimodal Large Language Models
This repo contains LLaVA-7B and pre-trained MGIE ckpt (on IPr2Pr + MagicBrush) for MGIE
<img src="URL width="60%" />
Please follow the offical repo and ipynb to use it
<img src="URL width="60%" />
| [
"# [ICLR'24] Guiding Instruction-based Image Editing via Multimodal Large Language Models\nThis repo contains LLaVA-7B and pre-trained MGIE ckpt (on IPr2Pr + MagicBrush) for MGIE\n<img src=\"URL width=\"60%\" />\n\nPlease follow the offical repo and ipynb to use it\n<img src=\"URL width=\"60%\" />"
] | [
"TAGS\n#license-other #has_space #region-us \n",
"# [ICLR'24] Guiding Instruction-based Image Editing via Multimodal Large Language Models\nThis repo contains LLaVA-7B and pre-trained MGIE ckpt (on IPr2Pr + MagicBrush) for MGIE\n<img src=\"URL width=\"60%\" />\n\nPlease follow the offical repo and ipynb to use it\n<img src=\"URL width=\"60%\" />"
] | [
15,
98
] | [
"passage: TAGS\n#license-other #has_space #region-us \n# [ICLR'24] Guiding Instruction-based Image Editing via Multimodal Large Language Models\nThis repo contains LLaVA-7B and pre-trained MGIE ckpt (on IPr2Pr + MagicBrush) for MGIE\n<img src=\"URL width=\"60%\" />\n\nPlease follow the offical repo and ipynb to use it\n<img src=\"URL width=\"60%\" />"
] | [
-0.014697798527777195,
-0.008601823821663857,
0.0008758558542467654,
0.048356276005506516,
0.0643477663397789,
0.04351639375090599,
0.19361908733844757,
0.10466273874044418,
0.04297538846731186,
-0.009472490288317204,
0.0067598652094602585,
0.06262052059173584,
-0.010109848342835903,
-0.012950493954122066,
0.04692211374640465,
-0.2612130343914032,
0.0006468618521466851,
-0.03506740182638168,
-0.062278371304273605,
0.06416837126016617,
0.060927148908376694,
-0.033282551914453506,
0.09411081671714783,
0.0015524075133726,
-0.15009036660194397,
0.011393317021429539,
-0.019041473045945168,
-0.0688171312212944,
0.06457749009132385,
0.028042349964380264,
-0.028122534975409508,
0.03451419621706009,
0.07835900783538818,
-0.13444937765598297,
0.03591540455818176,
0.008405737578868866,
-0.05609789863228798,
0.01069647166877985,
0.10888306051492691,
0.09795588254928589,
0.1061110571026802,
0.0016270208870992064,
-0.038965560495853424,
-0.03914504870772362,
-0.05314149707555771,
-0.010364026762545109,
-0.00827672891318798,
0.08628376573324203,
0.035158637911081314,
0.05399731174111366,
0.06773032248020172,
0.0925637036561966,
-0.11390266567468643,
0.06712840497493744,
0.136595219373703,
-0.19726191461086273,
0.003720484208315611,
0.28527525067329407,
-0.07186423987150192,
0.1268807053565979,
-0.06366076320409775,
0.1263047307729721,
0.042554039508104324,
-0.03733329102396965,
-0.10349176824092865,
-0.021876316517591476,
0.0011328713735565543,
-0.009993732906877995,
-0.02876892127096653,
-0.10090187937021255,
0.2680184543132782,
0.041242051869630814,
-0.00795452855527401,
-0.059339072555303574,
-0.03607168421149254,
0.06734910607337952,
-0.08091123402118683,
0.12971198558807373,
0.0712231993675232,
0.06836243718862534,
-0.09601723402738571,
-0.0458257719874382,
-0.12957322597503662,
-0.08731793612241745,
-0.06493478268384933,
0.11650494486093521,
0.01877165026962757,
0.09178333729505539,
-0.08744632452726364,
0.0701623186469078,
-0.16640864312648773,
-0.02831135503947735,
-0.031860750168561935,
-0.03288157656788826,
0.08333005756139755,
0.06214321032166481,
-0.0541703887283802,
0.03720429539680481,
0.06513058394193649,
0.09129302203655243,
-0.015945307910442352,
-0.0020434651523828506,
-0.01983601786196232,
0.1546676903963089,
0.04880818352103233,
0.020325401797890663,
-0.13518771529197693,
0.15319962799549103,
0.04020575433969498,
-0.06021462380886078,
0.024681324139237404,
-0.06334840506315231,
-0.10222332179546356,
-0.08711306005716324,
-0.11646733433008194,
0.019475137814879417,
-0.036211006343364716,
0.031618256121873856,
-0.015696147456765175,
-0.006327467039227486,
0.19545888900756836,
-0.042248524725437164,
0.019434534013271332,
-0.08374009281396866,
0.0042564962059259415,
0.02699553221464157,
0.08430285006761551,
-0.0001229017216246575,
0.0038679407443851233,
-0.004797532223165035,
-0.022604210302233696,
0.0971900001168251,
-0.07606383413076401,
-0.02169460989534855,
0.03828659653663635,
0.14195199310779572,
0.011687740683555603,
-0.14940056204795837,
-0.046420346945524216,
-0.00688303355127573,
0.04405692219734192,
-0.024508917704224586,
0.06293996423482895,
0.06459641456604004,
0.0051672435365617275,
0.000311625306494534,
-0.0005134362727403641,
-0.052313294261693954,
-0.07296661287546158,
0.056933917105197906,
-0.08780871331691742,
0.13640201091766357,
-0.1878725290298462,
0.02220321074128151,
-0.031896308064460754,
0.013895764015614986,
-0.13470254838466644,
0.07233881205320358,
-0.07877633720636368,
-0.02342054434120655,
0.017381491139531136,
-0.030512135475873947,
-0.10241411626338959,
0.04644398018717766,
0.009075651876628399,
0.07678068429231644,
-0.1330520659685135,
-0.004338492639362812,
0.1275099366903305,
-0.12773415446281433,
-0.07132760435342789,
0.08090485632419586,
0.014033199287950993,
-0.0030602281913161278,
-0.027326054871082306,
0.16244006156921387,
-0.002092052483931184,
-0.08230867236852646,
0.05011923983693123,
0.13015630841255188,
-0.07650504261255264,
-0.13894908130168915,
0.06735334545373917,
0.05558187514543533,
0.010783130303025246,
0.0480184480547905,
-0.07482998818159103,
0.08214152604341507,
-0.040176570415496826,
-0.05125374719500542,
-0.06018069013953209,
0.026968903839588165,
-0.12537261843681335,
0.021500898525118828,
0.0630604475736618,
-0.04688682407140732,
0.012219817377626896,
-0.08313080668449402,
0.11574826389551163,
-0.02715689316391945,
0.037642426788806915,
-0.01513988059014082,
0.051267046481370926,
-0.11784373223781586,
0.010876549407839775,
-0.11188889294862747,
0.028744379058480263,
-0.055165015161037445,
0.10623010247945786,
0.12872913479804993,
0.1054534912109375,
0.027260156348347664,
-0.009426446631550789,
-0.04107740521430969,
0.019634392112493515,
-0.050099167972803116,
-0.05285649001598358,
-0.010128466412425041,
-0.06659428775310516,
0.036513641476631165,
-0.041591010987758636,
0.06140606477856636,
-0.0695551186800003,
-0.010196903720498085,
0.07559020817279816,
0.010083482600748539,
-0.0026711325626820326,
0.036788396537303925,
0.05215080454945564,
-0.015348252840340137,
-0.06926022469997406,
-0.02460353821516037,
0.03360791131854057,
0.018305525183677673,
0.016031377017498016,
0.14226865768432617,
-0.005671686492860317,
0.1472279280424118,
0.19872884452342987,
-0.18917173147201538,
-0.022130275145173073,
-0.07675610482692719,
0.025535723194479942,
0.03722718358039856,
-0.07080771774053574,
0.08783051371574402,
-0.017540961503982544,
-0.026527224108576775,
0.08830519765615463,
-0.07472091168165207,
0.05754956230521202,
-0.0110594118013978,
-0.08758129179477692,
-0.09736574441194534,
0.013932679779827595,
0.22900177538394928,
-0.04336119070649147,
0.04120137542486191,
0.2769820988178253,
-0.020535200834274292,
0.16861476004123688,
0.019879143685102463,
-0.11007403582334518,
0.03310609236359596,
0.044047094881534576,
-0.00044747607898898423,
0.04770234227180481,
-0.0884905457496643,
-0.07362336665391922,
0.07740743458271027,
-0.009965130127966404,
0.054204992949962616,
-0.19459089636802673,
-0.04825534299015999,
0.006039606407284737,
-0.0300563033670187,
-0.13650739192962646,
0.0375409834086895,
-0.02813086472451687,
0.08156749606132507,
-0.042610395699739456,
-0.04428425803780556,
0.03186008334159851,
-0.018970752134919167,
0.007816951721906662,
0.09805925190448761,
-0.036253221333026886,
-0.24794630706310272,
-0.19259828329086304,
-0.01050565019249916,
-0.14415912330150604,
0.006049653049558401,
0.009047338739037514,
-0.12193500995635986,
-0.06321196258068085,
-0.06064597889780998,
-0.10537044703960419,
-0.06566454470157623,
-0.03994585573673248,
0.02808178775012493,
0.08561999350786209,
-0.031076792627573013,
-0.12637081742286682,
-0.03213699534535408,
0.007986723445355892,
-0.03561251610517502,
0.18846872448921204,
-0.043240562081336975,
0.12328924238681793,
0.11801882833242416,
-0.06275381147861481,
0.07324519008398056,
0.0779464915394783,
0.1201133206486702,
-0.09505190700292587,
-0.05852502956986427,
0.19482696056365967,
0.11704137921333313,
0.040321968495845795,
0.06976588815450668,
0.08301752060651779,
-0.12923510372638702,
-0.013690179213881493,
-0.010631983168423176,
-0.13177743554115295,
-0.0605318509042263,
-0.08469833433628082,
-0.08623209595680237,
-0.06782065331935883,
0.04429945349693298,
0.08653117716312408,
-0.0052626789547502995,
0.08465355634689331,
0.0002203828189522028,
0.0991397574543953,
0.012901871465146542,
0.0787842720746994,
0.04930571839213371,
-0.08215144276618958,
0.03557834029197693,
-0.07794111222028732,
-0.0468154102563858,
0.1292250007390976,
0.151027113199234,
0.11662742495536804,
0.0031737072858959436,
0.04258835315704346,
0.06148827448487282,
0.10998157411813736,
0.127054825425148,
0.1066625714302063,
-0.01753474771976471,
-0.038312625139951706,
-0.030328063294291496,
-0.041850801557302475,
-0.034984130412340164,
0.0619332529604435,
0.007354031316936016,
-0.22494062781333923,
0.0742119550704956,
0.0376630574464798,
0.03574002534151077,
0.06953583657741547,
0.014887925237417221,
-0.18261902034282684,
0.10573803633451462,
0.0060550756752491,
0.08242864161729813,
-0.08531902730464935,
0.08632190525531769,
0.15961667895317078,
0.021622534841299057,
0.0036733068991452456,
0.031094353646039963,
0.09965717047452927,
-0.12384533882141113,
-0.02246401272714138,
-0.06777218729257584,
-0.05975302681326866,
0.014340396039187908,
0.11177138984203339,
-0.06431098282337189,
0.11486278474330902,
0.013252637349069118,
-0.09062839299440384,
-0.14199383556842804,
-0.03616970404982567,
0.0972597524523735,
0.1918221116065979,
0.08668459206819534,
0.05279332399368286,
-0.02483927458524704,
-0.1657259166240692,
-0.043789561837911606,
-0.04443531110882759,
0.10408008098602295,
0.05878736451268196,
-0.035962533205747604,
-0.004549034871160984,
-0.012314003892242908,
-0.011706004850566387,
-0.027391424402594566,
-0.08494110405445099,
-0.16741333901882172,
0.04213171824812889,
0.161431685090065,
-0.0321635901927948,
-0.05812876671552658,
-0.006721745245158672,
-0.06714748591184616,
0.1815410554409027,
0.20739862322807312,
0.011176477186381817,
-0.08216418325901031,
0.04587891697883606,
0.04328923672437668,
-0.011223101057112217,
-0.003104020841419697,
-0.03066750429570675,
0.12833939492702484,
-0.03458939120173454,
-0.08431604504585266,
0.06021013855934143,
-0.07803752273321152,
0.04774533212184906,
0.03090686723589897,
0.040975842624902725,
-0.1653517335653305,
-0.014475608244538307,
0.02613176219165325,
-0.006918191909790039,
-0.029276501387357712,
-0.14411531388759613,
0.027651675045490265,
0.0019924910739064217,
-0.035659004002809525,
0.13158689439296722,
-0.07773138582706451,
0.0511992946267128,
0.06285156309604645,
-0.07147981971502304,
0.1530226469039917,
0.14411087334156036,
-0.01851700060069561,
-0.016081353649497032,
0.1291254460811615,
0.02494426816701889,
-0.27920567989349365,
-0.062143243849277496,
-0.13060986995697021,
-0.03960293531417847,
0.024341478943824768,
-0.060290370136499405,
0.09247340261936188,
0.10590226948261261,
-0.0362231507897377,
0.15718257427215576,
-0.18364658951759338,
-0.10365912318229675,
0.0046412209048867226,
0.09453437477350235,
0.17811717092990875,
-0.1196107268333435,
0.0004183765850029886,
-0.10129257291555405,
-0.10105349123477936,
-0.00263018487021327,
-0.08640260249376297,
0.14516635239124298,
-0.04273727536201477,
0.06916655600070953,
0.00627374229952693,
-0.039776746183633804,
0.12016551196575165,
-0.01711420714855194,
0.14045874774456024,
-0.10266853868961334,
0.0019089828711003065,
0.15781943500041962,
-0.01959775574505329,
0.1186632588505745,
-0.010492010973393917,
0.008432324975728989,
-0.060511816293001175,
-0.03478718549013138,
-0.03072049282491207,
-0.06909898668527603,
0.04440007731318474,
-0.019546015188097954,
-0.0554291196167469,
0.04076049104332924,
-0.10366980731487274,
0.02482536993920803,
0.16685107350349426,
-0.04113435745239258,
-0.1502581387758255,
0.07788362354040146,
-0.011567908339202404,
-0.1906050145626068,
-0.06391450017690659,
-0.0719803124666214,
-0.030931854620575905,
0.11518080532550812,
-0.20401179790496826,
0.059433821588754654,
-0.009433723986148834,
0.06225909665226936,
0.0628930926322937,
0.05601437762379646,
0.004311622120440006,
0.06055440008640289,
0.16439500451087952,
-0.03752930089831352,
-0.08379761874675751,
-0.0016448023961856961,
0.11645222455263138,
0.16127946972846985,
-0.013437502086162567,
0.10461970418691635,
-0.033636365085840225,
0.05312018096446991,
-0.004442357458174229,
0.0341477245092392,
-0.03246862813830376,
0.00070272630546242,
0.0905686467885971,
-0.058746010065078735,
-0.15686991810798645,
0.08962222188711166,
0.006419005338102579,
-0.018974434584379196,
-0.047436751425266266,
0.025642994791269302,
-0.04977834224700928,
-0.13657334446907043,
0.023281719535589218,
0.03152008727192879,
-0.09488952904939651,
-0.07811148464679718,
-0.024676069617271423,
-0.015708530321717262,
0.028181670233607292,
-0.21139128506183624,
0.08012328296899796,
-0.07838321477174759,
-0.018451450392603874,
-0.06377287954092026,
-0.044199373573064804,
-0.0384235717356205,
-0.096794992685318,
0.08561955392360687,
-0.19339579343795776,
0.0019489196129143238,
-0.015653835609555244,
0.0639394074678421,
-0.05895278975367546,
-0.04949621111154556,
-0.050181515514850616,
0.05203239619731903,
-0.06101089343428612,
0.03579607978463173,
-0.09404606372117996,
0.027688264846801758,
0.026195628568530083,
0.023767594248056412,
-0.044994860887527466,
0.0035251539666205645,
-0.1572466641664505,
-0.0790613666176796,
-0.05541222169995308,
0.06419958919286728,
-0.038145098835229874,
-0.05301710218191147,
0.002192520769312978,
-0.030279111117124557,
0.05139854550361633,
0.004428104031831026,
-0.056481923907995224,
0.020955950021743774,
-0.18758396804332733,
-0.13933250308036804,
0.1579718142747879,
0.08853195607662201,
-0.011797592043876648,
0.13044047355651855,
0.08182952553033829,
0.03383815661072731,
0.04293733090162277,
0.0036793211475014687,
-0.02989526279270649,
-0.07472492754459381,
-0.04954255744814873,
-0.2039845883846283,
-0.1425117403268814,
-0.033050596714019775,
0.05593114718794823,
0.16213969886302948,
0.06937026977539062,
0.07168471813201904,
-0.028082814067602158,
-0.016409603878855705,
-0.06235799193382263,
0.0223558247089386,
0.015511222183704376,
-0.07386502623558044,
0.05353255197405815,
-0.10111437737941742,
0.014720848761498928,
-0.06509564816951752,
0.26006776094436646,
0.09897424280643463,
-0.12677328288555145,
-0.0451771505177021,
0.10468726605176926,
0.02257774956524372,
-0.05891003459692001,
0.14281222224235535,
0.07892460376024246,
0.03362635150551796,
-0.06188327074050903,
0.031647779047489166,
0.13117258250713348,
0.04190057888627052,
-0.02754749357700348,
0.09940183162689209,
-0.0014806374674662948,
0.04792178049683571,
0.1425810307264328,
-0.07018842548131943,
-0.05670250952243805,
-0.029985321685671806,
-0.030732201412320137,
0.11598341166973114,
-0.08562318980693817,
-0.09682799130678177,
0.18477676808834076,
-0.06082598492503166,
0.02104971371591091,
0.023261522874236107,
-0.0015865287277847528,
-0.041569750756025314,
-0.1564418226480484,
-0.09330504387617111,
-0.2040412724018097,
0.09217511117458344,
-0.04406812787055969,
0.04879050329327583,
0.23950563371181488,
0.0651322454214096,
0.01372340228408575,
0.04929867014288902,
-0.14944060146808624,
-0.052574191242456436,
0.06955070048570633,
-0.038962364196777344,
-0.020099634304642677,
-0.024826478213071823,
-0.04419475793838501,
0.07030735909938812,
-0.12861190736293793,
0.006945594679564238,
0.04307423159480095,
0.045130521059036255,
-0.015086186118423939,
-0.06928681582212448,
-0.03579038754105568,
-0.08663754910230637,
-0.003441507462412119,
0.06828153133392334,
0.1255185306072235,
0.017897531390190125,
-0.03388343006372452,
0.019256023690104485,
0.057563416659832,
-0.06344549357891083,
-0.10355085134506226,
-0.062468595802783966,
-0.0968911424279213,
-0.05545134097337723,
0.05918493866920471,
-0.07841818034648895,
-0.08036113530397415,
-0.041365791112184525,
0.1357436180114746,
0.15550407767295837,
-0.11653143167495728,
0.010827410966157913,
0.03549472987651825,
0.0015520489541813731,
-0.030727319419384003,
0.16467824578285217,
0.08762182295322418,
0.12463954836130142,
-0.041070401668548584,
-0.11283450573682785,
-0.059389762580394745,
-0.022391188889741898,
-0.08780545741319656,
0.0006588651449419558,
0.011981434188783169,
-0.11154908686876297,
-0.10332443565130234,
0.06164862588047981,
0.038479994982481,
0.03186924383044243,
0.20474933087825775,
-0.0441768541932106,
-0.027725566178560257,
0.013277865946292877,
-0.06580532342195511,
0.024266377091407776,
0.012721225619316101,
-0.11313915997743607,
0.04867281764745712,
-0.05574379488825798,
0.008133755065500736,
-0.21450041234493256,
-0.02396976575255394,
0.0125673683360219,
0.1146816536784172,
0.10437556356191635,
0.034924041479825974,
0.10899908095598221,
0.030155571177601814,
-0.019822292029857635,
-0.03856069594621658,
0.13681615889072418,
-0.08107729256153107,
-0.022947540506720543,
-0.02185390330851078,
0.07369311898946762,
-0.08034839481115341,
-0.09542995691299438,
0.052314963191747665,
0.014229980297386646,
0.01780458725988865,
0.09716033935546875,
0.0032052749302238226,
-0.10554719716310501,
-0.0035284620244055986,
-0.10008540004491806,
0.0852997899055481,
0.09224660694599152,
0.039044808596372604,
-0.038513194769620895,
-0.02210369147360325,
0.06943176686763763,
0.053860150277614594,
-0.17672504484653473,
-0.0694071501493454,
0.04382159933447838,
-0.08091859519481659,
-0.05205432325601578,
0.01217854954302311,
-0.1139805018901825,
-0.04630088433623314,
-0.05110332742333412,
-0.020897960290312767,
-0.05362570658326149,
0.09442192316055298,
0.204613596200943,
0.0208317581564188,
0.012614100240170956,
-0.16559912264347076,
0.07320509850978851,
-0.006955303717404604,
-0.07592230290174484,
-0.056315720081329346
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 53
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "53", "results": []}]} | text-classification | santiadavani/53 | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T00:59:09+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# 53
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# 53\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# 53\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
68,
28,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# 53\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0### Training results### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.10678794980049133,
0.08769336342811584,
-0.0013050627894699574,
0.08077242970466614,
0.16878284513950348,
0.014785380102694035,
0.13274168968200684,
0.09867805242538452,
-0.12366567552089691,
0.04448345676064491,
0.07013016194105148,
0.08758394420146942,
0.015192561782896519,
0.11609484255313873,
-0.059094347059726715,
-0.23396825790405273,
0.019011735916137695,
0.00721259880810976,
-0.10477281361818314,
0.09664081037044525,
0.11771662533283234,
-0.10910356789827347,
0.06707906723022461,
0.01084587350487709,
-0.18047353625297546,
0.026412049308419228,
-0.011069241911172867,
-0.0523865632712841,
0.10092683881521225,
0.029330763965845108,
0.12563200294971466,
0.02023474872112274,
0.1237497627735138,
-0.2015005499124527,
-0.0013678902760148048,
0.0875914916396141,
0.03457673639059067,
0.06952688843011856,
0.02292088232934475,
-0.017746564000844955,
0.07761863619089127,
-0.11195401847362518,
0.09947777539491653,
0.04241572320461273,
-0.08656398206949234,
-0.18160158395767212,
-0.10103590041399002,
0.07150430232286453,
0.10092165321111679,
0.10314234346151352,
0.0024816475342959166,
0.12651924788951874,
-0.09422872960567474,
0.07366573065519333,
0.1877046525478363,
-0.2675301134586334,
-0.07552284002304077,
0.07231037318706512,
0.048350557684898376,
0.05382445082068443,
-0.1005413606762886,
-0.012238096445798874,
0.08467455208301544,
0.0356171540915966,
0.09657885134220123,
-0.013726525940001011,
-0.1004929319024086,
-0.013070620596408844,
-0.13054032623767853,
0.0035927260760217905,
0.18893100321292877,
0.04192623868584633,
-0.0705224797129631,
-0.0710238590836525,
-0.05295942351222038,
-0.08216933161020279,
-0.02363699860870838,
-0.04850691556930542,
0.053151026368141174,
-0.03142639249563217,
-0.06874245405197144,
-0.05189201980829239,
-0.08751823753118515,
-0.06740368157625198,
0.002301874104887247,
0.13774210214614868,
0.03591189160943031,
0.006837515626102686,
-0.04429135471582413,
0.11257161945104599,
-0.02921552211046219,
-0.12319083511829376,
-0.023641355335712433,
-0.017759103327989578,
-0.028939245268702507,
-0.07178061455488205,
-0.06861356645822525,
-0.01189446821808815,
0.010798570699989796,
0.19398082792758942,
-0.0854777991771698,
0.05841348320245743,
0.003221150953322649,
0.012266641482710838,
-0.04866296052932739,
0.14454393088817596,
-0.03540858253836632,
-0.028547657653689384,
0.013262920081615448,
0.09353034943342209,
0.018880868330597878,
-0.006156489253044128,
-0.08478555828332901,
-0.0018772280309349298,
0.0804952010512352,
0.0515061691403389,
-0.06474215537309647,
0.04290461540222168,
-0.03451385721564293,
-0.022594641894102097,
0.0008574211387895048,
-0.11385899782180786,
0.026897329837083817,
-0.00922408513724804,
-0.07624045014381409,
-0.0017301389016211033,
0.047492336481809616,
0.022282738238573074,
-0.00030579371377825737,
0.1153908371925354,
-0.09003756940364838,
0.0028277861420065165,
-0.11044324189424515,
-0.08008812367916107,
-0.001667453907430172,
-0.06128593161702156,
0.002275676466524601,
-0.08915190398693085,
-0.2174098938703537,
-0.037408050149679184,
0.055611662566661835,
-0.02395288459956646,
-0.02665414661169052,
-0.05119123309850693,
-0.08469770848751068,
0.013112050481140614,
-0.01216356921941042,
0.09859229624271393,
-0.0492016039788723,
0.0733550563454628,
0.03564151003956795,
0.024843409657478333,
-0.028056055307388306,
0.03544750064611435,
-0.0985502079129219,
0.03287218511104584,
-0.1458699107170105,
0.06311050057411194,
-0.09318088740110397,
0.05852646753191948,
-0.08437128365039825,
-0.09922625124454498,
0.0009033364476636052,
-0.0001734162651700899,
0.0667300820350647,
0.12094101309776306,
-0.18655668199062347,
-0.038114145398139954,
0.1343975067138672,
-0.09571492671966553,
-0.1084568202495575,
0.07866028696298599,
-0.054986730217933655,
0.0787569135427475,
0.07120832800865173,
0.11629912257194519,
0.10043245553970337,
-0.11698909103870392,
-0.02854125387966633,
0.004096839111298323,
0.07916007936000824,
0.026286503300070763,
0.03837396949529648,
-0.021027803421020508,
-0.0057584550231695175,
0.024805711582303047,
-0.08000075817108154,
-0.016947755590081215,
-0.09221801161766052,
-0.0874103456735611,
-0.06595423072576523,
-0.10412535816431046,
0.05720282346010208,
0.03233826905488968,
0.055426012724637985,
-0.08347232639789581,
-0.10431381314992905,
0.15836122632026672,
0.1299564689397812,
-0.060813166201114655,
0.02299037203192711,
-0.07388221472501755,
0.05273229256272316,
-0.003915478941053152,
-0.02808189205825329,
-0.2018412947654724,
-0.11016777902841568,
0.010861105285584927,
-0.017813824117183685,
0.024894777685403824,
-0.005024271085858345,
0.05550966411828995,
0.07981523871421814,
-0.06923949718475342,
-0.023056386038661003,
-0.09182965755462646,
0.0073493123054504395,
-0.09261318296194077,
-0.20160655677318573,
-0.04770577698945999,
-0.02626965008676052,
0.1779720038175583,
-0.24336588382720947,
0.04308048263192177,
-0.027373887598514557,
0.13885967433452606,
0.03475048765540123,
-0.032346874475479126,
-0.047434572130441666,
0.0673438012599945,
-0.03735700994729996,
-0.08987075090408325,
0.04230928421020508,
0.01124707330018282,
-0.0786629319190979,
-0.09575019031763077,
-0.13152600824832916,
0.08205293118953705,
0.10707493126392365,
-0.006985189858824015,
-0.09221386909484863,
-0.0006219008937478065,
-0.06142977625131607,
-0.026862211525440216,
-0.06699108332395554,
-0.004258465953171253,
0.13353757560253143,
-0.010227616876363754,
0.1369379162788391,
-0.06435435265302658,
-0.05459655821323395,
-0.0056598130613565445,
-0.024486280977725983,
0.007815253920853138,
0.053317841142416,
0.08167057484388351,
-0.07801443338394165,
0.11636382341384888,
0.12445544451475143,
-0.09038352221250534,
0.148795485496521,
-0.05325226113200188,
-0.060603827238082886,
-0.010947714559733868,
0.007165068760514259,
0.004283405840396881,
0.11594834178686142,
-0.10428031533956528,
0.007620343938469887,
0.008139298297464848,
0.022547170519828796,
0.043560273945331573,
-0.18838001787662506,
0.0007795259007252753,
0.023522743955254555,
-0.03035406954586506,
-0.01646486483514309,
-0.023613138124346733,
0.009305136278271675,
0.07791831344366074,
0.009144190698862076,
-0.0192713662981987,
0.04025687277317047,
0.002069783629849553,
-0.08058365434408188,
0.20896384119987488,
-0.13153302669525146,
-0.11588385701179504,
-0.12297317385673523,
0.01060903538018465,
-0.0741189643740654,
-0.004655811470001936,
0.038926005363464355,
-0.09403932839632034,
-0.05389925092458725,
-0.07848718762397766,
0.004825168289244175,
0.0009836452081799507,
-0.01012545544654131,
0.05114907771348953,
0.020595557987689972,
0.10403694212436676,
-0.14968174695968628,
0.006230234168469906,
-0.021199118345975876,
-0.1115034967660904,
-0.003381977090612054,
0.04353887960314751,
0.09463654458522797,
0.13748037815093994,
-0.012884069234132767,
0.002891270909458399,
-0.024438146501779556,
0.24179989099502563,
-0.06340466439723969,
-0.030336624011397362,
0.13222241401672363,
0.009617499075829983,
0.04183894768357277,
0.11642460525035858,
0.04960573837161064,
-0.12305529415607452,
0.04567285254597664,
0.09303693473339081,
-0.014788745902478695,
-0.23744970560073853,
-0.042259640991687775,
-0.02916993573307991,
-0.06736918538808823,
0.07014096528291702,
0.037167999893426895,
0.04696507379412651,
0.06085803359746933,
-0.014743066392838955,
0.06326425820589066,
-0.003750502597540617,
0.09210946410894394,
0.10434763133525848,
0.03539421409368515,
0.1207016110420227,
-0.033238038420677185,
-0.021648423746228218,
0.058975767344236374,
-0.022003173828125,
0.2765871286392212,
0.001307305763475597,
0.04704730957746506,
0.07653115689754486,
0.1337576061487198,
-0.024241415783762932,
0.053520068526268005,
0.0115834204480052,
-0.026548542082309723,
0.011339209042489529,
-0.06897220015525818,
-0.020823851227760315,
0.030315615236759186,
-0.07866009324789047,
0.07812239974737167,
-0.11867834627628326,
0.0376877598464489,
0.05371963605284691,
0.2678907811641693,
0.03410246968269348,
-0.3015981912612915,
-0.10529171675443649,
0.019014611840248108,
-0.02189633995294571,
-0.061215467751026154,
0.017255602404475212,
0.08665192127227783,
-0.11035259068012238,
0.06490561366081238,
-0.0584915466606617,
0.09971290081739426,
0.017701365053653717,
0.021238120272755623,
0.06429774314165115,
0.12145137786865234,
-0.008773966692388058,
0.06720974296331406,
-0.2596789002418518,
0.20803622901439667,
0.019929509609937668,
0.1403491199016571,
-0.02856471762061119,
0.03159860521554947,
0.041584692895412445,
0.1485728621482849,
0.06689679622650146,
-0.011435824446380138,
-0.02620701864361763,
-0.16973385214805603,
-0.027806038036942482,
0.03601557016372681,
0.12304137647151947,
-0.04200863465666771,
0.10158918052911758,
-0.04897953197360039,
0.01832413859665394,
0.07047237455844879,
-0.050120968371629715,
-0.2081843614578247,
-0.11665152758359909,
-0.0019406910287216306,
0.0017203952884301543,
0.004813237115740776,
-0.10155285894870758,
-0.10174953192472458,
-0.03421560302376747,
0.16958148777484894,
-0.03661532700061798,
-0.044161904603242874,
-0.12981945276260376,
0.06377647817134857,
0.10000841319561005,
-0.04884358122944832,
0.04311711713671684,
0.021335404366254807,
0.12397997826337814,
0.0289998110383749,
-0.0806875005364418,
0.056081950664520264,
-0.09165254235267639,
-0.18483853340148926,
-0.04989304766058922,
0.10424578934907913,
0.0540023148059845,
0.02650219015777111,
0.0012100337771698833,
0.014676024205982685,
0.01850569061934948,
-0.09583073109388351,
-0.025563087314367294,
0.08433236926794052,
0.08415199816226959,
0.05921359360218048,
-0.0952153354883194,
-0.008272363804280758,
-0.041368793696165085,
-0.012169243767857552,
0.10107510536909103,
0.22681987285614014,
-0.07973495870828629,
0.02649502456188202,
0.07368467003107071,
-0.08849461376667023,
-0.18283018469810486,
0.10065224766731262,
0.09672421216964722,
0.005821743048727512,
0.036150988191366196,
-0.1907147616147995,
0.13946646451950073,
0.12232092022895813,
-0.02629717066884041,
0.09206075221300125,
-0.2955150902271271,
-0.14881791174411774,
0.09392258524894714,
0.10908643156290054,
0.05603542551398277,
-0.1409219652414322,
-0.034024421125650406,
-0.06054290011525154,
-0.1417686641216278,
0.12558284401893616,
-0.14985305070877075,
0.099180668592453,
0.008154988288879395,
0.06711768358945847,
0.011406364850699902,
-0.02846383862197399,
0.1565815657377243,
0.023395685479044914,
0.11632206290960312,
-0.04676567763090134,
0.026448018848896027,
0.09872841089963913,
-0.06960848718881607,
0.0250727366656065,
-0.044090647250413895,
0.07289956510066986,
-0.08714265376329422,
-0.02623869851231575,
-0.06442391127347946,
0.07793866842985153,
-0.07023382186889648,
-0.07284792512655258,
-0.05067090690135956,
0.04919366165995598,
0.041654396802186966,
-0.030460156500339508,
0.0881424993276596,
0.008942066691815853,
0.1526954472064972,
0.0893138200044632,
0.10961806029081345,
-0.05534173175692558,
-0.0571376271545887,
0.011555688455700874,
-0.03068879432976246,
0.08288562297821045,
-0.14573130011558533,
0.03666273131966591,
0.11422557383775711,
0.04437848925590515,
0.146060049533844,
0.06632336974143982,
-0.04031035304069519,
0.010648730210959911,
0.057390715926885605,
-0.11379875242710114,
-0.11290381848812103,
-0.009179922752082348,
-0.03171810880303383,
-0.12419988960027695,
0.06811319291591644,
0.1194993257522583,
-0.07458092272281647,
-0.0012341138208284974,
-0.016050178557634354,
0.000042899777326965705,
-0.05200850963592529,
0.1815958470106125,
0.04343156889081001,
0.06060409173369408,
-0.08274077624082565,
0.12353100627660751,
0.04808146134018898,
-0.061686981469392776,
0.02315797470510006,
0.03967661038041115,
-0.09083377569913864,
-0.02776200883090496,
0.04546099528670311,
0.17046672105789185,
-0.06669630110263824,
-0.06155848503112793,
-0.11344192922115326,
-0.10336852073669434,
0.03551952913403511,
0.15730054676532745,
0.07116422802209854,
0.000006267199296416948,
-0.03493575006723404,
0.05585058778524399,
-0.1460590958595276,
0.08313468098640442,
0.04465341195464134,
0.08923614770174026,
-0.16591285169124603,
0.1365906298160553,
0.020512396469712257,
0.003617255948483944,
-0.015947014093399048,
0.023536020889878273,
-0.10229742527008057,
-0.020488210022449493,
-0.1830914169549942,
-0.025500411167740822,
-0.020190630108118057,
0.009544351138174534,
-0.00013880473852623254,
-0.035985834896564484,
-0.06109456345438957,
0.058174390345811844,
-0.07106319069862366,
-0.048737600445747375,
0.033731311559677124,
0.04861007630825043,
-0.14426013827323914,
0.002119731390848756,
0.020161520689725876,
-0.10105059295892715,
0.065279521048069,
0.05447719246149063,
0.023638438433408737,
0.06010090187191963,
-0.14835169911384583,
-0.015181336551904678,
0.040962688624858856,
0.01871742680668831,
0.056840088218450546,
-0.08203495293855667,
-0.015346254222095013,
-0.01682736538350582,
0.07506712526082993,
0.016977649182081223,
0.06693439930677414,
-0.12108927965164185,
-0.026215359568595886,
-0.03406717628240585,
-0.04418996721506119,
-0.0540788508951664,
0.03291994705796242,
0.1123986467719078,
0.03899873420596123,
0.19915132224559784,
-0.09171172976493835,
0.008706506341695786,
-0.186263769865036,
-0.025413937866687775,
-0.010394321754574776,
-0.04062725603580475,
-0.09145847707986832,
-0.034925781190395355,
0.059219930320978165,
-0.06912132352590561,
0.11791868507862091,
-0.02887267991900444,
0.10020327568054199,
0.04500315710902214,
-0.056708600372076035,
-0.016834503039717674,
0.023047976195812225,
0.22715047001838684,
0.0609460286796093,
0.0027751652523875237,
0.044491756707429886,
0.013975207693874836,
0.07876931130886078,
0.02827344834804535,
0.2077685445547104,
0.14979033172130585,
-0.08858257532119751,
0.07960982620716095,
0.05267234891653061,
-0.09195675700902939,
-0.14499659836292267,
0.07609432190656662,
-0.021508892998099327,
0.09837324172258377,
-0.057085540145635605,
0.12680473923683167,
0.11898397654294968,
-0.16771115362644196,
0.037197310477495193,
-0.07325377315282822,
-0.10102216899394989,
-0.13046672940254211,
-0.008010834455490112,
-0.0778743103146553,
-0.1569751352071762,
0.019240446388721466,
-0.14147727191448212,
0.028959892690181732,
0.0964077040553093,
-0.0009152169805020094,
0.0010988012654706836,
0.17475855350494385,
-0.05404646694660187,
0.016595834866166115,
0.055040206760168076,
-0.006524819880723953,
-0.02256426215171814,
-0.0826011374592781,
-0.08298680931329727,
0.029341507703065872,
-0.006139393895864487,
0.04751134291291237,
-0.05238649621605873,
-0.026083752512931824,
0.03464430570602417,
-0.003870390122756362,
-0.05791284143924713,
0.036486610770225525,
0.034634459763765335,
0.03701277822256088,
0.05012660473585129,
0.030577408149838448,
-0.010507609695196152,
-0.01843695528805256,
0.2958126962184906,
-0.09873739629983902,
-0.11360407620668411,
-0.15301513671875,
0.23381663858890533,
0.04707993194460869,
0.002008333569392562,
0.04964518919587135,
-0.11948707699775696,
-0.0041412534192204475,
0.16726349294185638,
0.14639630913734436,
-0.06296266615390778,
-0.015804514288902283,
-0.023138931021094322,
-0.022298762574791908,
-0.07902220636606216,
0.12516584992408752,
0.11827508360147476,
0.03858710825443268,
-0.04367116093635559,
-0.03368457779288292,
-0.0031403976026922464,
-0.02480893023312092,
-0.07405909895896912,
0.08207561820745468,
0.0003751111507881433,
-0.009143037721514702,
-0.031231602653861046,
0.06910526752471924,
-0.011280926875770092,
-0.14346912503242493,
0.06558849662542343,
-0.14264391362667084,
-0.16619078814983368,
-0.0342877134680748,
0.07873690128326416,
-0.032436106353998184,
0.055872052907943726,
-0.018691005185246468,
-0.02895764634013176,
0.14342164993286133,
-0.026306338608264923,
-0.025356749072670937,
-0.12359992414712906,
0.08617809414863586,
-0.060821935534477234,
0.23556892573833466,
-0.012732401490211487,
0.04917886108160019,
0.11620552092790604,
0.030861783772706985,
-0.10193240642547607,
0.055455923080444336,
0.05631769821047783,
-0.07617123425006866,
0.023929189890623093,
0.11562535166740417,
-0.05722607299685478,
0.11589763313531876,
0.03750570863485336,
-0.1832413226366043,
0.006848826538771391,
0.002806276548653841,
-0.06634443998336792,
-0.09139077365398407,
-0.007660645060241222,
-0.08132889866828918,
0.13231736421585083,
0.20330868661403656,
-0.0408477745950222,
0.018641291186213493,
-0.06542740017175674,
0.05956175923347473,
0.05762975290417671,
0.08220073580741882,
-0.035871244966983795,
-0.24775312840938568,
0.04101475328207016,
0.04745516926050186,
-0.006183004472404718,
-0.24947184324264526,
-0.08073079586029053,
0.052240341901779175,
-0.045306503772735596,
-0.05826854333281517,
0.10150035470724106,
0.09162644296884537,
0.036607787013053894,
-0.0451054722070694,
-0.12828843295574188,
-0.07528138905763626,
0.16758212447166443,
-0.13878478109836578,
-0.071743905544281
] |
null | null | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 3.4111719131469727
f1_macro: 0.34247619047619043
f1_micro: 0.42666666666666675
f1_weighted: 0.34247619047619043
precision_macro: 0.3122222222222222
precision_micro: 0.4266666666666667
precision_weighted: 0.3122222222222222
recall_macro: 0.4266666666666667
recall_micro: 0.4266666666666667
recall_weighted: 0.4266666666666667
accuracy: 0.4266666666666667
| {"tags": ["autotrain", "image-classification"], "datasets": ["autotrain-lhscs-6ppe1/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]} | image-classification | tferreira6/autotrain-lhscs-6ppe1 | [
"transformers",
"safetensors",
"vit",
"image-classification",
"autotrain",
"dataset:autotrain-lhscs-6ppe1/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:00:40+00:00 | [] | [] | TAGS
#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-lhscs-6ppe1/autotrain-data #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 3.4111719131469727
f1_macro: 0.34247619047619043
f1_micro: 0.42666666666666675
f1_weighted: 0.34247619047619043
precision_macro: 0.3122222222222222
precision_micro: 0.4266666666666667
precision_weighted: 0.3122222222222222
recall_macro: 0.4266666666666667
recall_micro: 0.4266666666666667
recall_weighted: 0.4266666666666667
accuracy: 0.4266666666666667
| [
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 3.4111719131469727\n\nf1_macro: 0.34247619047619043\n\nf1_micro: 0.42666666666666675\n\nf1_weighted: 0.34247619047619043\n\nprecision_macro: 0.3122222222222222\n\nprecision_micro: 0.4266666666666667\n\nprecision_weighted: 0.3122222222222222\n\nrecall_macro: 0.4266666666666667\n\nrecall_micro: 0.4266666666666667\n\nrecall_weighted: 0.4266666666666667\n\naccuracy: 0.4266666666666667"
] | [
"TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-lhscs-6ppe1/autotrain-data #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 3.4111719131469727\n\nf1_macro: 0.34247619047619043\n\nf1_micro: 0.42666666666666675\n\nf1_weighted: 0.34247619047619043\n\nprecision_macro: 0.3122222222222222\n\nprecision_micro: 0.4266666666666667\n\nprecision_weighted: 0.3122222222222222\n\nrecall_macro: 0.4266666666666667\n\nrecall_micro: 0.4266666666666667\n\nrecall_weighted: 0.4266666666666667\n\naccuracy: 0.4266666666666667"
] | [
60,
16,
144
] | [
"passage: TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-lhscs-6ppe1/autotrain-data #autotrain_compatible #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\n- Problem type: Image Classification## Validation Metricsg\nloss: 3.4111719131469727\n\nf1_macro: 0.34247619047619043\n\nf1_micro: 0.42666666666666675\n\nf1_weighted: 0.34247619047619043\n\nprecision_macro: 0.3122222222222222\n\nprecision_micro: 0.4266666666666667\n\nprecision_weighted: 0.3122222222222222\n\nrecall_macro: 0.4266666666666667\n\nrecall_micro: 0.4266666666666667\n\nrecall_weighted: 0.4266666666666667\n\naccuracy: 0.4266666666666667"
] | [
-0.1261870414018631,
0.15001098811626434,
-0.0018621704075485468,
0.12249964475631714,
0.13066023588180542,
0.04470780864357948,
0.09672421962022781,
0.13195787370204926,
-0.020343132317066193,
0.12742295861244202,
0.14445994794368744,
0.1205647885799408,
0.06452661007642746,
0.1299312710762024,
-0.1244451254606247,
-0.1795155555009842,
0.03360379487276077,
0.019610662013292313,
0.056568048894405365,
0.06846459954977036,
0.06375361233949661,
-0.12443313747644424,
0.10602979362010956,
-0.03614059090614319,
-0.23033276200294495,
0.005786196328699589,
0.13339562714099884,
-0.08775584399700165,
0.09892961382865906,
0.08828628063201904,
0.0866585522890091,
0.01719614304602146,
0.11948573589324951,
-0.07077682018280029,
-0.019011346623301506,
0.01912614330649376,
-0.004733526613563299,
0.06813611090183258,
0.16230061650276184,
0.031302016228437424,
-0.06112422049045563,
-0.06324658542871475,
0.05080785974860191,
0.0532514788210392,
-0.09421194344758987,
-0.10333159565925598,
-0.12218619138002396,
0.06384487450122833,
0.1053255945444107,
0.08432208001613617,
-0.013296956196427345,
0.1622549295425415,
-0.02960982918739319,
0.0855337455868721,
0.11397067457437515,
-0.24062199890613556,
-0.07230529189109802,
0.15607014298439026,
-0.030096745118498802,
-0.07886301726102829,
-0.09132064878940582,
0.08366449177265167,
0.11422159522771835,
0.0006613775040023029,
0.03300035744905472,
-0.02861786261200905,
-0.0276262778788805,
0.01022551953792572,
-0.09165383875370026,
-0.034981727600097656,
0.15436871349811554,
0.03608937934041023,
-0.06806592643260956,
-0.08607039600610733,
-0.03777877986431122,
-0.0968480184674263,
-0.06593445688486099,
-0.0279525313526392,
0.010398373939096928,
-0.06312692910432816,
-0.06176332011818886,
0.07553912699222565,
-0.06063057482242584,
-0.09810242056846619,
-0.1235644593834877,
0.06889608502388,
-0.010020159184932709,
0.03464621305465698,
0.022416966035962105,
0.040040139108896255,
-0.06003626808524132,
-0.10150253772735596,
0.012075334787368774,
-0.0020778088364750147,
-0.08403825014829636,
-0.051178526133298874,
0.01980777457356453,
-0.01828869804739952,
0.010852202773094177,
0.11464335024356842,
-0.003983120433986187,
0.0723041370511055,
-0.04266901686787605,
0.010833699256181717,
-0.06749860942363739,
0.162863627076149,
-0.1152658760547638,
-0.05173320323228836,
0.015620985068380833,
0.04238691180944443,
0.01761375181376934,
-0.016554847359657288,
-0.07150223106145859,
-0.09752710163593292,
0.15938560664653778,
0.04449162259697914,
0.007937412708997726,
0.04170554131269455,
-0.07217134535312653,
-0.019553303718566895,
-0.0017041951650753617,
-0.07434692233800888,
0.036460839211940765,
-0.053094055503606796,
-0.10639377683401108,
-0.020039115101099014,
0.05495286360383034,
-0.0023816432803869247,
-0.030643584206700325,
0.11815819889307022,
-0.12999354302883148,
0.00825412292033434,
-0.06419592350721359,
-0.12482131272554398,
0.03829050809144974,
-0.05202942341566086,
-0.020106583833694458,
-0.117938332259655,
-0.17977434396743774,
-0.04148172587156296,
-0.03819064423441887,
-0.10522330552339554,
0.009373998269438744,
-0.015218627639114857,
-0.08200254291296005,
0.0693434402346611,
0.022699862718582153,
0.07334329932928085,
-0.005896106828004122,
0.05409980192780495,
0.06177470460534096,
0.10365565121173859,
-0.023337706923484802,
0.01488443836569786,
-0.05660124868154526,
0.028769785538315773,
-0.19777990877628326,
0.0074211847968399525,
-0.0609562061727047,
0.0454549565911293,
-0.10910630971193314,
-0.026443513110280037,
0.07127653062343597,
-0.0036736202891916037,
0.05452475696802139,
0.1834065020084381,
-0.14675727486610413,
-0.008741451427340508,
0.07347210496664047,
-0.08113151788711548,
-0.10941992700099945,
0.11181546002626419,
0.002814300823956728,
0.008709504269063473,
0.02460014820098877,
0.08723141998052597,
0.036438409239053726,
-0.0916108563542366,
-0.07204355299472809,
-0.06358400732278824,
-0.05740578845143318,
-0.016338007524609566,
0.05858854204416275,
0.0036993790417909622,
-0.1083429604768753,
0.019178036600351334,
0.03005628101527691,
0.004070497117936611,
-0.10203693807125092,
-0.058638229966163635,
-0.03860745206475258,
-0.05216256156563759,
0.048797205090522766,
0.034748103469610214,
0.038960088044404984,
-0.08050467818975449,
-0.05230002477765083,
0.04923716560006142,
0.08617880940437317,
0.004197996109724045,
-0.045607708394527435,
-0.1402546614408493,
0.08164601773023605,
-0.17267778515815735,
-0.01877165213227272,
-0.158890500664711,
-0.10513605922460556,
0.003928019665181637,
0.007768905255943537,
-0.02272053062915802,
-0.07374608516693115,
0.09688681364059448,
0.049025602638721466,
-0.07648327946662903,
-0.05185098946094513,
0.07974157482385635,
0.0009064229088835418,
-0.1193869337439537,
-0.13482648134231567,
-0.009171808138489723,
0.0009588104439899325,
0.17413824796676636,
-0.19024963676929474,
-0.018065424636006355,
0.05257159098982811,
0.0945252999663353,
0.04382343217730522,
-0.009465578943490982,
-0.012014227919280529,
0.015377635136246681,
-0.03857261687517166,
-0.06465719640254974,
0.04919944703578949,
-0.05903718248009682,
-0.05079195648431778,
0.036262739449739456,
-0.24317210912704468,
0.2286568135023117,
0.13944046199321747,
-0.018069174140691757,
-0.11494217067956924,
-0.03469211235642433,
0.015333276242017746,
-0.05359536409378052,
-0.08273955434560776,
-0.024034518748521805,
-0.05603577941656113,
-0.01673588529229164,
0.10927481949329376,
-0.044936150312423706,
-0.026708262041211128,
0.06651731580495834,
-0.005038333125412464,
-0.09665580838918686,
0.13643428683280945,
0.02492477372288704,
-0.17372767627239227,
0.1324383020401001,
0.07399845868349075,
-0.0664130449295044,
0.1017654612660408,
0.025047969073057175,
-0.04945028945803642,
-0.07103094458580017,
-0.03339438885450363,
0.0728364810347557,
0.133822500705719,
0.045541588217020035,
0.03909210488200188,
0.054571881890296936,
-0.019109174609184265,
-0.031016798689961433,
-0.11154652386903763,
-0.012938050553202629,
-0.004118483513593674,
-0.010599522851407528,
0.03531831130385399,
0.0015862262807786465,
0.05522950738668442,
0.16813777387142181,
0.02434631995856762,
-0.060319289565086365,
0.048498038202524185,
-0.011109285987913609,
-0.07541583478450775,
0.2032560110092163,
-0.09427648037672043,
-0.18539389967918396,
-0.17576399445533752,
-0.03535035625100136,
-0.08155534416437149,
0.004308909177780151,
-0.01703720912337303,
-0.09427952021360397,
-0.11430523544549942,
-0.0774296298623085,
-0.007448768708854914,
0.010481310077011585,
0.0006958239828236401,
0.021507462486624718,
0.0042012762278318405,
0.07081109285354614,
-0.05345834046602249,
-0.0502469502389431,
-0.013885792344808578,
-0.03722434118390083,
0.11483362317085266,
0.0019685719162225723,
0.14801429212093353,
0.12339147180318832,
-0.038891177624464035,
0.04163556545972824,
-0.029334336519241333,
0.15902245044708252,
-0.048061806708574295,
0.029103221371769905,
0.1868458390235901,
0.03932555764913559,
0.022352807223796844,
0.1396728754043579,
0.010585633106529713,
-0.09899156540632248,
0.03410044685006142,
0.05969749391078949,
-0.023026851937174797,
-0.14739833772182465,
-0.11654135584831238,
0.0007971557206474245,
0.07127821445465088,
0.12005776166915894,
0.02268507145345211,
0.07928534597158432,
0.09531775861978531,
0.013221471570432186,
0.0817747637629509,
-0.021276967599987984,
0.10509668290615082,
0.12290758639574051,
0.03348758816719055,
0.17530600726604462,
-0.05277363955974579,
-0.01625896245241165,
0.07583523541688919,
-0.03739582374691963,
0.12407871335744858,
0.03052056021988392,
0.021281428635120392,
-0.024007443338632584,
0.11841458827257156,
0.06625103950500488,
0.10027161985635757,
0.05935094878077507,
-0.055577922612428665,
0.02053699642419815,
-0.08470679074525833,
-0.04403998330235481,
0.03838708996772766,
-0.0022525384556502104,
0.0635451003909111,
-0.12325546145439148,
0.07526428252458572,
0.03598225116729736,
0.13858819007873535,
0.10314135998487473,
-0.44104376435279846,
-0.07544305920600891,
0.04378170147538185,
0.040297236293554306,
-0.11336379498243332,
-0.023288343101739883,
0.053568195551633835,
-0.10572268813848495,
0.04395333305001259,
-0.07341685146093369,
0.09343300759792328,
-0.03697207570075989,
0.0008027717703953385,
-0.013066955842077732,
0.03955862671136856,
-0.03519425168633461,
0.03211108222603798,
-0.21167626976966858,
0.20928159356117249,
0.06829540431499481,
0.03633777052164078,
-0.08106058835983276,
-0.0025881407782435417,
0.068772092461586,
0.05425063148140907,
0.18053902685642242,
-0.011306106112897396,
-0.12105139344930649,
-0.3300926089286804,
-0.05789639800786972,
-0.03754425048828125,
0.06966724991798401,
0.017132770270109177,
0.09514539688825607,
-0.062139980494976044,
-0.03823958337306976,
0.03635052219033241,
-0.0458952933549881,
-0.11191390454769135,
-0.035221219062805176,
0.028998132795095444,
0.04490730166435242,
0.002426253631711006,
-0.06037956103682518,
-0.0826481357216835,
-0.058152005076408386,
0.12734463810920715,
-0.09833725541830063,
-0.021636230871081352,
-0.1827836036682129,
0.10669553279876709,
0.11763733625411987,
-0.09139067679643631,
0.07095994055271149,
-0.02315174601972103,
0.11931481212377548,
0.0070023504085838795,
-0.1127694845199585,
0.13284482061862946,
-0.09835464507341385,
-0.1318654865026474,
-0.030743712559342384,
0.049026645720005035,
-0.03655434027314186,
0.036332305520772934,
0.040891412645578384,
0.05957070365548134,
0.03793531283736229,
-0.07570313662290573,
0.10182840377092361,
0.014303005300462246,
0.1564943790435791,
0.08343996107578278,
-0.02545764483511448,
-0.13829490542411804,
-0.04727565497159958,
-0.004504100885242224,
0.07990441471338272,
0.33865758776664734,
-0.08702776581048965,
-0.06055230274796486,
0.05070722475647926,
-0.027073679491877556,
-0.2951648235321045,
0.08195491880178452,
-0.041533101350069046,
0.03311316668987274,
-0.0037477249279618263,
-0.005172124132514,
0.10227522999048233,
0.14520937204360962,
-0.04402587562799454,
0.03326563909649849,
-0.2316388040781021,
-0.13106100261211395,
0.17060711979866028,
0.1418619304895401,
0.09322217106819153,
-0.13783647119998932,
-0.05608947575092316,
-0.11996994912624359,
-0.15716823935508728,
0.053298305720090866,
-0.00001824061109800823,
0.07643041014671326,
-0.05623937398195267,
0.0008630292722955346,
0.0608692467212677,
-0.08300419896841049,
0.1382666975259781,
-0.061206504702568054,
0.1160656064748764,
-0.09526419639587402,
-0.0783652737736702,
0.01662357710301876,
-0.07251749187707901,
0.11639097332954407,
0.06792986392974854,
0.0673234760761261,
-0.10541945695877075,
-0.018743643537163734,
-0.03295008838176727,
0.06364292651414871,
-0.05229635909199715,
-0.06758386641740799,
-0.039914991706609726,
0.07718487828969955,
-0.06183493882417679,
-0.05193081498146057,
0.011838928796350956,
-0.020341284573078156,
0.0629630759358406,
0.2007065713405609,
0.0965387374162674,
-0.023384051397442818,
0.016331244260072708,
0.04077284783124924,
-0.06599632650613785,
0.0840788409113884,
-0.05277354642748833,
0.07165037095546722,
0.1310282200574875,
0.010578937828540802,
0.13564005494117737,
0.072813980281353,
-0.02401292510330677,
-0.02817738801240921,
0.07185154408216476,
-0.13137686252593994,
-0.050737183541059494,
-0.01956879533827305,
0.024653468281030655,
-0.02344100922346115,
-0.015319010242819786,
0.12348772585391998,
-0.04974377527832985,
0.018574243411421776,
0.0013244178844615817,
0.03274909779429436,
0.039188358932733536,
0.24745316803455353,
0.020076598972082138,
0.052566953003406525,
-0.0893896147608757,
0.11536028236150742,
0.0573849231004715,
-0.144806906580925,
0.016597595065832138,
0.04919774457812309,
-0.06829636543989182,
-0.04607034847140312,
0.049980323761701584,
0.1813073754310608,
-0.16502442955970764,
-0.03289514407515526,
-0.09872506558895111,
-0.15378569066524506,
0.05687645450234413,
0.23568086326122284,
0.07516618818044662,
0.004757495131343603,
0.044353049248456955,
-0.05817495658993721,
-0.13174638152122498,
0.08909633755683899,
0.08484441787004471,
0.06426701694726944,
-0.160757914185524,
0.12239430099725723,
-0.06297878921031952,
0.02185867168009281,
-0.05313797667622566,
0.044216763228178024,
-0.1909298300743103,
-0.008576326072216034,
-0.08364695310592651,
0.06102064624428749,
-0.044443320482969284,
-0.00676585640758276,
-0.02864660508930683,
-0.010457472875714302,
-0.03929664567112923,
0.01952284574508667,
-0.052901629358530045,
-0.056405626237392426,
0.03651951998472214,
0.04014606028795242,
-0.09393704682588577,
-0.07838481664657593,
0.049008410423994064,
-0.032663844525814056,
0.06537500768899918,
0.018805351108312607,
0.0827101618051529,
0.005648316349834204,
-0.06519793719053268,
-0.03818022087216377,
0.09162750840187073,
-0.039334602653980255,
0.05865149945020676,
-0.14146170020103455,
0.025477390736341476,
-0.009184880182147026,
0.01783798821270466,
0.05077096447348595,
0.0868426039814949,
-0.1123226061463356,
-0.008708593435585499,
-0.09936799854040146,
-0.06119409203529358,
-0.11679544299840927,
0.05731043592095375,
0.15751706063747406,
-0.017476173117756844,
0.0922863706946373,
-0.10028355568647385,
0.006262496113777161,
-0.19513851404190063,
0.006638313177973032,
-0.044694386422634125,
-0.11985136568546295,
-0.06613653898239136,
0.026300178840756416,
0.09043024480342865,
-0.029660629108548164,
0.012037261389195919,
0.009706905111670494,
-0.00599247869104147,
0.0646761804819107,
0.07928905636072159,
-0.0417180135846138,
0.019160250201821327,
0.14965850114822388,
0.06080441549420357,
-0.03208713233470917,
0.04429170861840248,
0.09524497389793396,
0.0997612327337265,
0.04871079698204994,
0.07073945552110672,
0.11212500184774399,
-0.05978461354970932,
0.11619561910629272,
0.06607048213481903,
-0.08593148738145828,
-0.0892849788069725,
0.09918534010648727,
-0.1525428146123886,
0.06243383139371872,
-0.05038346350193024,
-0.005341134965419769,
0.16703477501869202,
-0.113468699157238,
0.022179529070854187,
-0.10008552670478821,
-0.07158453017473221,
-0.13347932696342468,
-0.10027745366096497,
-0.14819781482219696,
-0.03403273969888687,
0.016080211848020554,
-0.08887168765068054,
0.05386386811733246,
0.16452568769454956,
0.030496465042233467,
-0.005124837160110474,
0.1665368676185608,
-0.17537273466587067,
0.013958277180790901,
0.044307246804237366,
0.007948407903313637,
-0.04682816565036774,
-0.012855739332735538,
-0.03616245090961456,
0.03668146952986717,
0.016221269965171814,
0.01670941524207592,
-0.0018177414312958717,
0.007811996154487133,
0.044871736317873,
0.025766948238015175,
-0.11423912644386292,
-0.01603643409907818,
0.03211980685591698,
0.028137292712926865,
0.06943197548389435,
-0.010279837064445019,
0.058668915182352066,
-0.02846350148320198,
0.21695129573345184,
-0.10119403153657913,
-0.0014371504075825214,
-0.08230102807283401,
0.22942446172237396,
-0.006552602630108595,
0.07750213891267776,
-0.008829636499285698,
-0.06449645757675171,
0.059493277221918106,
0.16075699031352997,
0.10671989619731903,
-0.0496722012758255,
-0.04443570598959923,
-0.017038803547620773,
-0.012889454141259193,
-0.05377618595957756,
0.10253056138753891,
0.03361509367823601,
0.06509241461753845,
-0.06778482347726822,
0.06472241878509521,
-0.0044476790353655815,
-0.04623736813664436,
-0.015383734367787838,
0.06186458095908165,
0.01546439528465271,
0.05118902772665024,
-0.05150635540485382,
0.06163453683257103,
0.009262900799512863,
0.05241239070892334,
0.13391001522541046,
-0.13808412849903107,
-0.15246139466762543,
0.02710404247045517,
0.0277894027531147,
-0.04831511899828911,
0.08315443247556686,
-0.0742994025349617,
0.015582560561597347,
-0.046874724328517914,
-0.007886537350714207,
-0.1431698203086853,
-0.11207865923643112,
-0.015276740305125713,
0.11160977929830551,
0.28255990147590637,
0.007648525293916464,
0.04828721657395363,
0.13440081477165222,
-0.051339950412511826,
-0.18514740467071533,
0.0882306769490242,
-0.0006922412430867553,
-0.13334108889102936,
0.10832110792398453,
0.17517688870429993,
-0.01854667253792286,
0.1629313826560974,
0.016213184222579002,
-0.200296550989151,
0.006217789836227894,
-0.03095206804573536,
-0.01921732723712921,
-0.054648853838443756,
0.03727603331208229,
-0.07009971886873245,
0.1486731916666031,
0.1407376527786255,
-0.022108742967247963,
-0.004916728008538485,
-0.056537043303251266,
0.04439380392432213,
0.024535944685339928,
0.05405556038022041,
0.010469593107700348,
-0.11138717830181122,
0.07833635061979294,
-0.10497134923934937,
-0.021873880177736282,
-0.3025946021080017,
-0.07363159954547882,
-0.05513410642743111,
-0.06759218126535416,
-0.08035670965909958,
0.1031649112701416,
0.12434966117143631,
0.03841947391629219,
-0.04387076944112778,
-0.21654722094535828,
0.034618496894836426,
0.14036743342876434,
-0.0661061555147171,
-0.10817544907331467
] |
null | null | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: Katelie/soccertwos
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
| {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | reinforcement-learning | Katelie/soccertwos | [
"ml-agents",
"tensorboard",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | 2024-02-09T01:01:54+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
browser: URL
- A *longer tutorial* to understand how works ML-Agents:
URL
### Resume the training
### Watch your Agent play
You can watch your agent playing directly in your browser
1. If the environment is part of ML-Agents official environments, go to URL
2. Step 1: Find your model_id: Katelie/soccertwos
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play
| [
"# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: Katelie/soccertwos\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
"TAGS\n#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us \n",
"# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: Katelie/soccertwos\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
52,
201
] | [
"passage: TAGS\n#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us \n# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: Katelie/soccertwos\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
-0.0014991125790402293,
-0.010211760178208351,
-0.0048792799934744835,
0.06492342799901962,
0.16284100711345673,
-0.022064486518502235,
0.11134949326515198,
0.11755817383527756,
0.12135831266641617,
0.08231563121080399,
0.07241103798151016,
0.03327445313334465,
0.05356543883681297,
0.10539374500513077,
0.07747947424650192,
-0.13294240832328796,
-0.028437623754143715,
-0.11758546531200409,
0.008115028031170368,
0.05153433606028557,
0.08090504258871078,
-0.05580921471118927,
0.06773880124092102,
0.04028182476758957,
-0.06527674198150635,
0.01438615657389164,
-0.05757780000567436,
-0.035966601222753525,
0.02334219217300415,
0.003981268499046564,
0.018122920766472816,
-0.05502176657319069,
0.09449722617864609,
-0.20404231548309326,
0.026069091632962227,
0.048547014594078064,
0.005175100639462471,
-0.06273680180311203,
0.11825712770223618,
0.052270252257585526,
0.0918743684887886,
-0.0791960284113884,
0.10220981389284134,
0.04164750874042511,
-0.0756165161728859,
0.06206054985523224,
-0.09449345618486404,
-0.0016742571024224162,
0.2003834992647171,
0.1464530974626541,
0.00914975255727768,
0.07686121016740799,
-0.0513618029654026,
0.006803486496210098,
0.1588933765888214,
-0.2717328369617462,
-0.07092650979757309,
0.09422922879457474,
-0.029435759410262108,
0.09396503120660782,
-0.026960095390677452,
0.06382231414318085,
-0.00989198125898838,
0.019418969750404358,
-0.05212710052728653,
0.01800648495554924,
0.17961658537387848,
0.004842408932745457,
-0.029272716492414474,
-0.1115386113524437,
-0.0023393696174025536,
0.06472740322351456,
-0.046029869467020035,
-0.16548851132392883,
0.0359661839902401,
0.1368931382894516,
-0.0497010312974453,
0.0024121180176734924,
0.07244566828012466,
0.008444448933005333,
-0.05158771574497223,
-0.12834684550762177,
-0.04821402207016945,
-0.04142751172184944,
0.04711972177028656,
0.0751984640955925,
-0.021474162116646767,
-0.032778870314359665,
0.05067053809762001,
0.07701864093542099,
0.04085688665509224,
-0.03816772997379303,
-0.02539513073861599,
0.0049353837966918945,
-0.15626463294029236,
-0.08093072474002838,
-0.020642977207899094,
-0.0009881970472633839,
0.05900373309850693,
0.10855910927057266,
0.12660010159015656,
0.011249426752328873,
0.00045010869507677853,
0.06192291900515556,
-0.015048983506858349,
0.05759602040052414,
-0.004033313132822514,
0.0024638930335640907,
0.028545159846544266,
0.03897395357489586,
0.030961105599999428,
-0.09627371281385422,
-0.0882381796836853,
0.08591455221176147,
-0.15118767321109772,
0.10611209273338318,
0.1377672553062439,
-0.031154094263911247,
-0.04408416897058487,
-0.04187970981001854,
0.030915038660168648,
-0.12090282887220383,
0.09231516718864441,
0.046182043850421906,
-0.049507033079862595,
-0.10978826880455017,
-0.049298662692308426,
0.054127782583236694,
-0.068401999771595,
0.0044896784238517284,
-0.014232863672077656,
0.043602827936410904,
0.01002657413482666,
-0.00667476886883378,
0.06434377282857895,
-0.10401718318462372,
-0.0030790751334279776,
-0.1458655595779419,
-0.10908427089452744,
-0.06651883572340012,
0.05300268530845642,
-0.10310742259025574,
-0.08921530097723007,
-0.09458310157060623,
0.010949674062430859,
-0.09471186995506287,
0.05976935848593712,
-0.07740054279565811,
-0.06506069004535675,
-0.03208041936159134,
-0.0486334003508091,
0.07177745550870895,
0.08577627688646317,
0.04461539164185524,
-0.03907780721783638,
0.023375671356916428,
-0.1692979335784912,
0.17577186226844788,
-0.09529364109039307,
0.14711852371692657,
-0.0770721584558487,
0.06711499392986298,
0.041038960218429565,
0.026415858417749405,
0.06960272789001465,
0.11468615382909775,
-0.04404579475522041,
-0.10119561105966568,
0.08686031401157379,
-0.04833575710654259,
-0.1657640039920807,
0.07523811608552933,
0.028359917923808098,
0.0603923574090004,
0.05582085996866226,
0.2379225492477417,
0.22200685739517212,
-0.25133734941482544,
0.12828262150287628,
-0.01650581881403923,
-0.12125343829393387,
0.006045283749699593,
0.09508807212114334,
-0.10373057425022125,
0.08237281441688538,
-0.0382068008184433,
-0.2077990621328354,
0.11028881371021271,
-0.028646478429436684,
-0.08316144347190857,
0.03826674446463585,
-0.09283685684204102,
-0.04131242632865906,
0.007943883538246155,
0.02369341067969799,
-0.06271975487470627,
-0.006316633895039558,
-0.04511939361691475,
0.03149450197815895,
-0.03160332888364792,
0.05999511480331421,
-0.060226667672395706,
0.1343609094619751,
0.014231803826987743,
0.012653154321014881,
-0.12269731611013412,
-0.13903865218162537,
0.008249658159911633,
0.11330249905586243,
0.10317332297563553,
-0.06419507414102554,
0.0358714833855629,
0.1100507602095604,
0.017628198489546776,
-0.06340708583593369,
-0.11430185288190842,
0.0071047586388885975,
-0.033734045922756195,
-0.11826246976852417,
-0.026153558865189552,
-0.06103995814919472,
0.07992921024560928,
-0.14513352513313293,
0.04118106886744499,
-0.10176920890808105,
0.07704684138298035,
0.0005519040860235691,
-0.04953128844499588,
-0.013734202831983566,
0.04339377582073212,
0.04348835349082947,
-0.06857253611087799,
0.12111309915781021,
0.021897053346037865,
-0.06684190034866333,
0.02430116944015026,
0.052297018468379974,
-0.07932230830192566,
0.09925784170627594,
0.0014720208710059524,
-0.02012823149561882,
0.041540611535310745,
-0.04108472168445587,
-0.0037046419456601143,
-0.11734242737293243,
-0.025308599695563316,
0.22126202285289764,
0.0888233408331871,
0.10474405437707901,
-0.08748668432235718,
-0.028491809964179993,
0.011610572226345539,
-0.05812537670135498,
-0.05573524907231331,
0.08166010677814484,
0.010437635704874992,
-0.019793130457401276,
0.010536293499171734,
0.04668181762099266,
0.11522737890481949,
0.14634516835212708,
0.02012365497648716,
-0.10293537378311157,
0.03991958498954773,
0.11656928062438965,
0.03221346437931061,
0.0033544173929840326,
0.024143598973751068,
-0.05035952106118202,
-0.02008373849093914,
-0.02176993526518345,
-0.05638391152024269,
-0.11271826177835464,
-0.07556246966123581,
0.0599965862929821,
-0.03908468782901764,
-0.019715821370482445,
-0.05139932408928871,
-0.012323953211307526,
0.06709303706884384,
0.09300435334444046,
0.013566788285970688,
0.018875179812312126,
-0.06355325877666473,
-0.1207541674375534,
0.05833350867033005,
-0.08721493184566498,
-0.17355503141880035,
-0.12027590721845627,
-0.057812049984931946,
-0.06855160742998123,
0.0484028160572052,
0.07013485580682755,
-0.1278841346502304,
0.005827048793435097,
-0.09976095706224442,
-0.03815505653619766,
0.024891257286071777,
-0.07706098258495331,
0.17638979852199554,
0.12096869945526123,
-0.011136033572256565,
-0.08033731579780579,
-0.00455126678571105,
0.011367599479854107,
-0.09917603433132172,
-0.034613970667123795,
0.019591251388192177,
0.11434962600469589,
0.08717110008001328,
-0.007967748679220676,
0.04046152904629707,
-0.03495846688747406,
0.07522572576999664,
-0.08854236453771591,
0.0258766021579504,
0.072099968791008,
-0.013370649889111519,
0.0975833311676979,
0.06166958063840866,
0.032946161925792694,
-0.012447270564734936,
0.0392276830971241,
0.0051829637959599495,
-0.05954258143901825,
-0.2039978951215744,
-0.11770149320363998,
-0.01673722267150879,
0.12938709557056427,
0.10334306955337524,
0.07824055105447769,
-0.0664205327630043,
-0.005072892643511295,
0.010717482306063175,
-0.09177346527576447,
0.14776095747947693,
0.11296295374631882,
-0.06960571557283401,
-0.0005770488060079515,
0.017506321892142296,
-0.06207729130983353,
0.017882896587252617,
0.08546725660562515,
-0.033782534301280975,
0.0978723019361496,
0.050209272652864456,
0.058361027389764786,
0.036903075873851776,
-0.0721731185913086,
-0.07118769735097885,
0.08617960661649704,
0.05911516025662422,
-0.0018463233718648553,
-0.0336974635720253,
-0.06184994429349899,
-0.033556487411260605,
0.06234318017959595,
0.13902363181114197,
-0.06396505981683731,
-0.13803452253341675,
0.0849199965596199,
0.1031106561422348,
0.1472749561071396,
0.037732332944869995,
-0.12581288814544678,
-0.034497737884521484,
-0.008991502225399017,
-0.09652511030435562,
0.03660609945654869,
0.012064938433468342,
0.06924911588430405,
-0.16994793713092804,
0.03325648233294487,
0.08553922921419144,
0.13556154072284698,
0.0086738932877779,
-0.0021786182187497616,
0.049982503056526184,
0.03260469064116478,
-0.005289791151881218,
0.05849757045507431,
-0.12055537104606628,
0.06515572965145111,
-0.014938950538635254,
0.09405479580163956,
-0.04294515401124954,
-0.014277092181146145,
0.0567183755338192,
-0.01968984492123127,
0.15216375887393951,
0.06605393439531326,
-0.09452025592327118,
-0.14821887016296387,
-0.1023777425289154,
-0.07764542102813721,
-0.005706129129976034,
-0.06554152816534042,
0.07487490773200989,
0.0014518690295517445,
-0.025630177929997444,
-0.09623768925666809,
0.058143530040979385,
-0.049255918711423874,
-0.09208827465772629,
-0.04294399917125702,
-0.028005115687847137,
0.02845388650894165,
-0.039763662964105606,
-0.002559349639341235,
-0.024226821959018707,
0.16398504376411438,
0.13426339626312256,
-0.03350145369768143,
-0.08127539604902267,
0.002237915061414242,
-0.08877076953649521,
-0.025483431294560432,
0.05197054147720337,
0.020442547276616096,
0.0943569540977478,
-0.09216149896383286,
0.0102319847792387,
-0.019504191353917122,
-0.11566006392240524,
-0.0645437240600586,
-0.019880788400769234,
0.1859523206949234,
0.052837010473012924,
0.03288344666361809,
0.0357363261282444,
0.046220820397138596,
-0.006043924484401941,
-0.07621755450963974,
0.1807829886674881,
0.1567860245704651,
-0.054096151143312454,
0.05899101868271828,
-0.02979259192943573,
0.028323443606495857,
-0.09437568485736847,
-0.0304042287170887,
0.19766904413700104,
0.26619160175323486,
-0.06291305273771286,
0.20914113521575928,
0.03928031772375107,
-0.09276342391967773,
-0.20569579303264618,
-0.04443882405757904,
0.05481367185711861,
-0.042011238634586334,
0.16981276869773865,
-0.13501183688640594,
0.08756686002016068,
0.0040095290169119835,
0.007156208623200655,
0.01580282486975193,
-0.18406878411769867,
-0.08694162964820862,
-0.01190923061221838,
0.06972193717956543,
-0.008062145672738552,
-0.058126550167798996,
-0.05150054395198822,
-0.017766224220395088,
-0.19087184965610504,
0.03690486401319504,
-0.15752002596855164,
0.042342863976955414,
0.025545518845319748,
0.054051030427217484,
0.050864141434431076,
-0.004025780130177736,
0.15341098606586456,
0.0031425096094608307,
-0.04890517145395279,
-0.07179345935583115,
0.0035011761356145144,
0.11204618960618973,
-0.07046245038509369,
0.04388513043522835,
0.04982389137148857,
-0.01664062775671482,
-0.18008770048618317,
0.011436562985181808,
-0.017935140058398247,
0.019658315926790237,
-0.030407646670937538,
0.018757976591587067,
-0.02105117216706276,
0.06643141806125641,
0.07994958013296127,
0.04969354718923569,
0.08742545545101166,
-0.008820951916277409,
-0.03087705932557583,
0.0534391924738884,
0.08846777677536011,
0.06516572088003159,
-0.09634079784154892,
-0.06470776349306107,
-0.06884525716304779,
0.00600469671189785,
-0.05280251428484917,
0.011841140687465668,
0.03907656669616699,
0.025898782536387444,
-0.04122181236743927,
0.04740855097770691,
-0.08887391537427902,
0.013857811689376831,
0.07485999166965485,
-0.035860128700733185,
-0.08516283333301544,
-0.075075663626194,
-0.05827381834387779,
0.017237653955817223,
-0.12634901702404022,
0.06633492559194565,
-0.022713912650942802,
-0.015365653671324253,
0.04886159300804138,
-0.013010849244892597,
-0.06823337078094482,
0.03055119886994362,
0.00002914530887210276,
0.03574385121464729,
-0.04094412550330162,
0.15717755258083344,
0.023543795570731163,
-0.03117663413286209,
0.024383794516324997,
0.14678123593330383,
-0.10814519226551056,
-0.08815585821866989,
-0.008318368345499039,
0.10041165351867676,
0.0729004293680191,
-0.0330449715256691,
0.0015873638913035393,
-0.06531057506799698,
0.08427045494318008,
-0.10746811330318451,
-0.028865259140729904,
-0.12518121302127838,
0.03783295676112175,
0.055289629846811295,
-0.0294911228120327,
0.11120086908340454,
-0.005748818162828684,
-0.047005798667669296,
-0.0978352501988411,
0.005519238766282797,
0.02253839187324047,
0.12302352488040924,
-0.001754813827574253,
-0.028272364288568497,
-0.14919878542423248,
0.030665017664432526,
-0.023729585111141205,
-0.017800215631723404,
-0.1420915424823761,
-0.014163224957883358,
-0.028214722871780396,
0.01431573648005724,
0.030886061489582062,
0.04118042439222336,
-0.03904825076460838,
-0.08619874715805054,
-0.03327614814043045,
0.1171814575791359,
-0.09133293479681015,
-0.026964742690324783,
-0.007543189451098442,
-0.03969153016805649,
0.05356641113758087,
0.050132036209106445,
-0.01666276715695858,
-0.022205833345651627,
-0.08012107014656067,
-0.015748711302876472,
-0.05395269766449928,
-0.05502593144774437,
0.07657128572463989,
-0.13973374664783478,
0.025935858488082886,
-0.023695172742009163,
-0.09057530015707016,
0.019799869507551193,
0.1262245774269104,
-0.02996429242193699,
0.08604138344526291,
0.02572418563067913,
-0.14337140321731567,
-0.08183924853801727,
0.011630597524344921,
0.08866284042596817,
0.04911824315786362,
0.07573943585157394,
-0.1049143448472023,
0.16954216361045837,
-0.11845642328262329,
-0.014610572718083858,
0.017915481701493263,
0.050674691796302795,
-0.022138597443699837,
-0.1522579938173294,
0.02261415868997574,
-0.032126642763614655,
0.06172195076942444,
0.07359331846237183,
0.06040111929178238,
0.018737955018877983,
-0.012739026919007301,
0.12914502620697021,
0.050077103078365326,
0.057616498321294785,
-0.03873823955655098,
0.0008583817398175597,
0.05495736747980118,
-0.0031301744747906923,
0.036121439188718796,
-0.10064952075481415,
0.10155057162046432,
0.08464554697275162,
0.1497366577386856,
0.04208642244338989,
0.07645617425441742,
-0.0778634175658226,
-0.14432553946971893,
-0.06083843484520912,
0.08008647710084915,
-0.045344289392232895,
-0.0627511590719223,
0.140438050031662,
0.15903903543949127,
-0.2594027519226074,
0.06165141612291336,
-0.028578462079167366,
0.04085016995668411,
-0.0579337403178215,
-0.08686982095241547,
0.016962964087724686,
-0.2225535660982132,
0.06302042305469513,
-0.0549938939511776,
-0.005165526643395424,
-0.09678297489881516,
-0.018546683713793755,
-0.003420709166675806,
0.07130482792854309,
-0.08186400681734085,
-0.0476754792034626,
0.08624355494976044,
-0.036451760679483414,
0.07294350862503052,
-0.022397294640541077,
-0.016193559393286705,
-0.042048145085573196,
-0.05299746245145798,
-0.015163196250796318,
0.0946117416024208,
-0.011124511249363422,
0.056130606681108475,
-0.06430202722549438,
-0.09294059127569199,
0.08823833614587784,
-0.02180570363998413,
0.007061481475830078,
0.0676240548491478,
0.08699686080217361,
-0.10308850556612015,
-0.023422162979841232,
0.1787729114294052,
-0.044653087854385376,
-0.05452912673354149,
-0.06416034698486328,
0.13216590881347656,
-0.009128978475928307,
-0.008618822321295738,
-0.025924701243638992,
-0.1461988389492035,
-0.0480520986020565,
0.2309553474187851,
0.1381613165140152,
-0.03894191235303879,
0.014174014329910278,
-0.060634490102529526,
0.006299354135990143,
0.04329492896795273,
0.10029363632202148,
0.030310891568660736,
0.0745539665222168,
-0.06559430807828903,
-0.04150402545928955,
-0.05366282910108566,
-0.051668930798769,
-0.1882760226726532,
0.03513472154736519,
0.05297506973147392,
-0.013684537261724472,
-0.049940261989831924,
0.13506491482257843,
-0.08089832961559296,
-0.08144575357437134,
0.1681671142578125,
-0.10177724063396454,
-0.04826808720827103,
-0.03244716301560402,
-0.022692596539855003,
0.04327918589115143,
0.09697119891643524,
0.05252482369542122,
0.05008825287222862,
0.07072976976633072,
-0.014498907141387463,
-0.07327570021152496,
-0.017595874145627022,
0.02139930985867977,
-0.1384768784046173,
0.19738416373729706,
-0.039145857095718384,
0.0216481015086174,
0.06044989451766014,
0.05319248512387276,
-0.12651613354682922,
0.007174340076744556,
0.030685003846883774,
-0.06541537493467331,
0.02724459022283554,
0.03978487476706505,
-0.0706198662519455,
-0.0007209510076791048,
0.09740503132343292,
-0.051070719957351685,
0.01952941343188286,
0.07409192621707916,
0.01268400251865387,
-0.05892183631658554,
0.10358394682407379,
-0.1344033181667328,
0.09717557579278946,
0.09644106030464172,
-0.059645045548677444,
0.029401112347841263,
-0.005062460899353027,
0.036776427179574966,
0.041893698275089264,
0.10025414079427719,
-0.02471979707479477,
-0.1243956908583641,
0.008621406741440296,
0.060362521559000015,
0.038951411843299866,
-0.257849782705307,
-0.09953822940587997,
-0.01109575480222702,
-0.04911181703209877,
-0.004936927929520607,
0.1271037459373474,
0.13151533901691437,
-0.06407437473535538,
-0.01969597116112709,
-0.20280717313289642,
0.038766901940107346,
0.1978783905506134,
-0.03391125798225403,
-0.021849777549505234
] |
null | null | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: nan
f1_macro: 0.0003508771929824561
f1_micro: 0.013333333333333336
f1_weighted: 0.0003508771929824561
precision_macro: 0.00017777777777777779
precision_micro: 0.013333333333333334
precision_weighted: 0.00017777777777777779
recall_macro: 0.013333333333333334
recall_micro: 0.013333333333333334
recall_weighted: 0.013333333333333334
accuracy: 0.013333333333333334
| {"tags": ["autotrain", "image-classification"], "datasets": ["autotrain-xrwes-v4giy/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]} | image-classification | tferreira6/autotrain-xrwes-v4giy | [
"transformers",
"safetensors",
"resnet",
"image-classification",
"autotrain",
"dataset:autotrain-xrwes-v4giy/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:05:35+00:00 | [] | [] | TAGS
#transformers #safetensors #resnet #image-classification #autotrain #dataset-autotrain-xrwes-v4giy/autotrain-data #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: nan
f1_macro: 0.0003508771929824561
f1_micro: 0.013333333333333336
f1_weighted: 0.0003508771929824561
precision_macro: 0.00017777777777777779
precision_micro: 0.013333333333333334
precision_weighted: 0.00017777777777777779
recall_macro: 0.013333333333333334
recall_micro: 0.013333333333333334
recall_weighted: 0.013333333333333334
accuracy: 0.013333333333333334
| [
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: nan\n\nf1_macro: 0.0003508771929824561\n\nf1_micro: 0.013333333333333336\n\nf1_weighted: 0.0003508771929824561\n\nprecision_macro: 0.00017777777777777779\n\nprecision_micro: 0.013333333333333334\n\nprecision_weighted: 0.00017777777777777779\n\nrecall_macro: 0.013333333333333334\n\nrecall_micro: 0.013333333333333334\n\nrecall_weighted: 0.013333333333333334\n\naccuracy: 0.013333333333333334"
] | [
"TAGS\n#transformers #safetensors #resnet #image-classification #autotrain #dataset-autotrain-xrwes-v4giy/autotrain-data #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: nan\n\nf1_macro: 0.0003508771929824561\n\nf1_micro: 0.013333333333333336\n\nf1_weighted: 0.0003508771929824561\n\nprecision_macro: 0.00017777777777777779\n\nprecision_micro: 0.013333333333333334\n\nprecision_weighted: 0.00017777777777777779\n\nrecall_macro: 0.013333333333333334\n\nrecall_micro: 0.013333333333333334\n\nrecall_weighted: 0.013333333333333334\n\naccuracy: 0.013333333333333334"
] | [
65,
16,
137
] | [
"passage: TAGS\n#transformers #safetensors #resnet #image-classification #autotrain #dataset-autotrain-xrwes-v4giy/autotrain-data #autotrain_compatible #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\n- Problem type: Image Classification## Validation Metricsg\nloss: nan\n\nf1_macro: 0.0003508771929824561\n\nf1_micro: 0.013333333333333336\n\nf1_weighted: 0.0003508771929824561\n\nprecision_macro: 0.00017777777777777779\n\nprecision_micro: 0.013333333333333334\n\nprecision_weighted: 0.00017777777777777779\n\nrecall_macro: 0.013333333333333334\n\nrecall_micro: 0.013333333333333334\n\nrecall_weighted: 0.013333333333333334\n\naccuracy: 0.013333333333333334"
] | [
-0.12424996495246887,
0.1292475461959839,
-0.0016868960810825229,
0.11562196165323257,
0.12828189134597778,
0.038222748786211014,
0.11350665241479874,
0.1090865284204483,
-0.038129277527332306,
0.11486569046974182,
0.14549162983894348,
0.09091278910636902,
0.06668806076049805,
0.1350703239440918,
-0.12548020482063293,
-0.1797861009836197,
0.047538068145513535,
0.018553566187620163,
0.07443307340145111,
0.08512824773788452,
0.08012120425701141,
-0.10966312885284424,
0.11527572572231293,
-0.025546954944729805,
-0.23133325576782227,
-0.0030129917431622744,
0.11718270182609558,
-0.08523595333099365,
0.09510032087564468,
0.09212280064821243,
0.11352098733186722,
0.011434136889874935,
0.14138126373291016,
-0.09845791757106781,
-0.0166870579123497,
0.0352352149784565,
-0.01550656370818615,
0.0686708614230156,
0.148432195186615,
0.016682498157024384,
-0.017860515043139458,
-0.04746523126959801,
0.06273414194583893,
0.06700683385133743,
-0.08797895908355713,
-0.09608276933431625,
-0.10568748414516449,
0.11665888875722885,
0.10326669365167618,
0.09154150635004044,
-0.00917279813438654,
0.1653679460287094,
-0.027436360716819763,
0.09880585968494415,
0.130936861038208,
-0.24190282821655273,
-0.08297999203205109,
0.1847059428691864,
-0.018268920481204987,
-0.07272236794233322,
-0.09169559925794601,
0.06713376939296722,
0.10038041323423386,
0.008293298073112965,
0.01908881776034832,
-0.02949371375143528,
-0.004252211656421423,
-0.0027641523629426956,
-0.09723342955112457,
-0.003525449661538005,
0.13464167714118958,
0.05855279043316841,
-0.0578971691429615,
-0.09761719405651093,
-0.05143020674586296,
-0.12465758621692657,
-0.07610374689102173,
-0.03509362041950226,
0.0023860845249146223,
-0.04354463517665863,
-0.06938038021326065,
0.095455102622509,
-0.05150281637907028,
-0.10730466991662979,
-0.10639839619398117,
0.08381740748882294,
-0.01167172472923994,
0.029984239488840103,
0.013760121539235115,
0.029327115043997765,
-0.023521259427070618,
-0.09472206979990005,
0.00830978062003851,
-0.014006398618221283,
-0.10078524053096771,
-0.05582226812839508,
0.003658175002783537,
-0.04084951430559158,
0.022428734228014946,
0.15417297184467316,
-0.019181355834007263,
0.06502530723810196,
-0.011685491539537907,
0.012480581179261208,
-0.07192503660917282,
0.15090471506118774,
-0.1322944164276123,
-0.07833841443061829,
0.0002757467154879123,
0.034521590918302536,
0.025727173313498497,
-0.009209400042891502,
-0.07110776007175446,
-0.07740306109189987,
0.13690604269504547,
0.019679969176650047,
-0.005600601434707642,
0.049683742225170135,
-0.07966753840446472,
-0.02306373231112957,
0.034315645694732666,
-0.06657728552818298,
0.02464624121785164,
-0.031060542911291122,
-0.10499648004770279,
-0.005201833322644234,
0.04551256448030472,
0.008117862045764923,
-0.010222435928881168,
0.1095128282904625,
-0.12257686257362366,
-0.0022653609048575163,
-0.06205372139811516,
-0.12720219790935516,
0.027732912451028824,
-0.015978507697582245,
-0.021676059812307358,
-0.12082649767398834,
-0.18544647097587585,
-0.05818791314959526,
-0.025120586156845093,
-0.10111356526613235,
0.011596830561757088,
-0.021435771137475967,
-0.08756636828184128,
0.07071326673030853,
0.025202320888638496,
0.0488426610827446,
-0.005695320200175047,
0.03772939741611481,
0.05018146336078644,
0.1138409823179245,
-0.03239026665687561,
0.0015812404453754425,
-0.06313499808311462,
0.021913770586252213,
-0.1766456812620163,
0.034567706286907196,
-0.06473779678344727,
0.06538171321153641,
-0.10537657141685486,
-0.028864901512861252,
0.04822070896625519,
0.00003625008321250789,
0.043509140610694885,
0.17183445394039154,
-0.1503993421792984,
-0.012885686941444874,
0.11020556092262268,
-0.0961405485868454,
-0.11286164820194244,
0.12108533084392548,
0.004700841382145882,
0.0012755305506289005,
0.03870869055390358,
0.07406611740589142,
0.03416994586586952,
-0.07755663245916367,
-0.08292633295059204,
-0.038333456963300705,
-0.04554881528019905,
-0.024204472079873085,
0.05870571359992027,
0.011658458039164543,
-0.08755648881196976,
0.011302954517304897,
0.004218461457639933,
0.02381567470729351,
-0.09827979654073715,
-0.07065124809741974,
-0.03641318529844284,
-0.06784870475530624,
0.04460381716489792,
0.0394870899617672,
0.03474219888448715,
-0.06752139329910278,
-0.07456633448600769,
0.02835713140666485,
0.096736378967762,
-0.0032874152529984713,
-0.042016152292490005,
-0.14641377329826355,
0.04951082170009613,
-0.12029008567333221,
-0.021357567980885506,
-0.16276629269123077,
-0.13018402457237244,
-0.004198852926492691,
-0.004366010893136263,
-0.022983791306614876,
-0.08169585466384888,
0.09694335609674454,
0.04541260376572609,
-0.07959528267383575,
-0.05340801924467087,
0.07492053508758545,
0.004323132336139679,
-0.1071358472108841,
-0.13677778840065002,
-0.024077095091342926,
-0.007665491197258234,
0.1823231279850006,
-0.21859535574913025,
-0.008794573135674,
0.048614926636219025,
0.09662741422653198,
0.04166075214743614,
-0.012947486713528633,
-0.02654070034623146,
0.025431456044316292,
-0.045467559248209,
-0.07377418130636215,
0.042901020497083664,
-0.03872105851769447,
-0.07973042875528336,
0.0028967815451323986,
-0.20900504291057587,
0.2424277365207672,
0.1240924820303917,
-0.043311137706041336,
-0.1322770118713379,
-0.006906080525368452,
0.005812359508126974,
-0.05394537001848221,
-0.0640002116560936,
-0.0001126733623095788,
-0.04130834341049194,
-0.00535723939538002,
0.09800723940134048,
-0.04655292630195618,
-0.016543664038181305,
0.0481095053255558,
-0.01568400114774704,
-0.0762488842010498,
0.12103056162595749,
0.020892882719635963,
-0.18277263641357422,
0.1241595670580864,
0.029609523713588715,
-0.09699505567550659,
0.09518945962190628,
0.025914905592799187,
-0.04344902187585831,
-0.06912847608327866,
-0.02377958968281746,
0.06617739051580429,
0.11274699866771698,
0.04346844181418419,
0.026697106659412384,
0.04892323166131973,
-0.03767012804746628,
-0.03280266001820564,
-0.10528239607810974,
-0.01253090612590313,
-0.0016898667672649026,
-0.024432921782135963,
0.04737458750605583,
-0.0014886140124872327,
0.03235999122262001,
0.1471693366765976,
0.010843993164598942,
-0.09122398495674133,
0.04799996688961983,
-0.014129084534943104,
-0.08278430253267288,
0.21597397327423096,
-0.06185654178261757,
-0.18769000470638275,
-0.1643609255552292,
-0.048726052045822144,
-0.10003570467233658,
0.006956813391298056,
-0.021198458969593048,
-0.10409516841173172,
-0.11078926175832748,
-0.08206086605787277,
-0.02699415571987629,
0.029088344424962997,
-0.001845139660872519,
0.03463556244969368,
0.0003036319394595921,
0.07576637715101242,
-0.049374546855688095,
-0.03580354526638985,
-0.022366246208548546,
-0.04659280925989151,
0.10182370990514755,
0.00026013003662228584,
0.1379730999469757,
0.15046921372413635,
-0.026067588478326797,
0.03677390143275261,
-0.026616539806127548,
0.17337532341480255,
-0.040316060185432434,
0.023628344759345055,
0.16587726771831512,
0.02795712649822235,
0.027077021077275276,
0.14438238739967346,
0.03316408395767212,
-0.09316419810056686,
0.03447090461850166,
0.06405824422836304,
-0.02414926514029503,
-0.14418508112430573,
-0.125917449593544,
0.007981203496456146,
0.05523008480668068,
0.10451803356409073,
0.029393194243311882,
0.10882710665464401,
0.11431080847978592,
0.009882627986371517,
0.07443063706159592,
-0.023666810244321823,
0.09795379638671875,
0.10095278173685074,
0.05282173678278923,
0.18399375677108765,
-0.057326704263687134,
-0.023448383435606956,
0.06825665384531021,
-0.0434703566133976,
0.11612585186958313,
0.034201961010694504,
0.0655667632818222,
-0.011996541172266006,
0.12181126326322556,
0.07139698415994644,
0.09115581214427948,
0.0668015405535698,
-0.07409131526947021,
0.03251997008919716,
-0.08114081621170044,
-0.0477452389895916,
0.04310382157564163,
-0.024300802499055862,
0.07732101529836655,
-0.10007526725530624,
0.11345356702804565,
0.03380996361374855,
0.15706470608711243,
0.07631564140319824,
-0.4597991406917572,
-0.07284446805715561,
0.027094366028904915,
0.04396228492259979,
-0.1156991571187973,
-0.011217441409826279,
0.04558316990733147,
-0.10762469470500946,
0.05436432361602783,
-0.07540453970432281,
0.09020857512950897,
-0.053860098123550415,
0.0007671687053516507,
0.0036436656955629587,
0.04575565457344055,
-0.023750940337777138,
0.021475141867995262,
-0.19720934331417084,
0.20772753655910492,
0.044469043612480164,
0.037375856190919876,
-0.07101773470640182,
-0.0024852456990629435,
0.0661294087767601,
0.07407839596271515,
0.19148866832256317,
-0.0177058856934309,
-0.11776086688041687,
-0.31095144152641296,
-0.04177284985780716,
-0.04366409406065941,
0.06210053712129593,
0.011011762544512749,
0.09467434883117676,
-0.06167175993323326,
-0.03438408300280571,
0.04645131528377533,
-0.02509295381605625,
-0.1262514889240265,
-0.03835273161530495,
0.019666846841573715,
0.07462670654058456,
-0.0038643768057227135,
-0.07863164693117142,
-0.08322037756443024,
-0.07608047127723694,
0.1397904008626938,
-0.09552223980426788,
-0.03201684728264809,
-0.17229023575782776,
0.10424936562776566,
0.1007644534111023,
-0.09440755844116211,
0.06738978624343872,
-0.0263045821338892,
0.11556488275527954,
0.011722583323717117,
-0.0991656556725502,
0.13717100024223328,
-0.11081206053495407,
-0.11543945223093033,
-0.03562551736831665,
0.02963949553668499,
-0.010155579075217247,
0.03489411622285843,
0.047935303300619125,
0.04533242806792259,
0.024057969450950623,
-0.08205967396497726,
0.0616241879761219,
-0.013749982230365276,
0.11570503562688828,
0.08831965923309326,
-0.021150337532162666,
-0.12672552466392517,
-0.05766613408923149,
0.012970059178769588,
0.09258691221475601,
0.29954326152801514,
-0.09252066165208817,
-0.0724484920501709,
0.05391456559300423,
-0.02099803276360035,
-0.28355926275253296,
0.055657465010881424,
-0.015295706689357758,
0.028814997524023056,
0.004073718562722206,
-0.020355330780148506,
0.1385454684495926,
0.147706538438797,
-0.046967390924692154,
0.011502165347337723,
-0.23199409246444702,
-0.1251065582036972,
0.19881851971149445,
0.1266908496618271,
0.08130844682455063,
-0.1562022566795349,
-0.061294324696063995,
-0.12695756554603577,
-0.12522833049297333,
0.0422750860452652,
-0.0006489668157882988,
0.06302115321159363,
-0.046653863042593,
-0.011538615450263023,
0.04785647988319397,
-0.08127135783433914,
0.13009613752365112,
-0.022930391132831573,
0.11945556849241257,
-0.09921594709157944,
-0.06619352847337723,
0.04117298498749733,
-0.0710296481847763,
0.1120719313621521,
0.05399876460433006,
0.06961704045534134,
-0.0925895944237709,
-0.02713247388601303,
-0.03449586406350136,
0.049511730670928955,
-0.03412741795182228,
-0.06671266257762909,
-0.04766845703125,
0.08255328238010406,
-0.03915362060070038,
-0.03157339245080948,
0.04156447947025299,
-0.020977644249796867,
0.08903021365404129,
0.19989971816539764,
0.0913170799612999,
-0.025927605107426643,
-0.014902681112289429,
0.016411272808909416,
-0.06276074796915054,
0.08366559445858002,
-0.03258723393082619,
0.06605741381645203,
0.12037140876054764,
0.008513389155268669,
0.13890843093395233,
0.07430768013000488,
-0.010734101757407188,
-0.033750612288713455,
0.08572204411029816,
-0.10946498066186905,
-0.03487888351082802,
-0.024253088980913162,
-0.01774134673178196,
-0.051801882684230804,
-0.0020074062049388885,
0.13473694026470184,
-0.05253433436155319,
0.03495664894580841,
-0.0037096082232892513,
0.03379108011722565,
0.005728825461119413,
0.23283204436302185,
0.026709480211138725,
0.05695550888776779,
-0.10180795192718506,
0.09886214137077332,
0.058785781264305115,
-0.08364374935626984,
-0.001686125178821385,
0.04240986332297325,
-0.08786971867084503,
-0.03175833076238632,
0.021113405004143715,
0.17747363448143005,
-0.18824337422847748,
-0.04753712937235832,
-0.11164093762636185,
-0.16276763379573822,
0.04615865647792816,
0.22835016250610352,
0.08955775201320648,
0.011504650115966797,
0.02604113519191742,
-0.05529727414250374,
-0.12555579841136932,
0.07882855832576752,
0.08892715722322464,
0.06762281060218811,
-0.18676167726516724,
0.12173744291067123,
-0.04567251354455948,
0.0009747951989993453,
-0.04796069115400314,
0.04704468697309494,
-0.18550026416778564,
0.002313090255483985,
-0.09287633746862411,
0.055793873965740204,
-0.0447675846517086,
0.009541626088321209,
-0.020200777798891068,
-0.00439761858433485,
-0.052638206630945206,
0.014619198627769947,
-0.04552789404988289,
-0.056251075118780136,
0.04765535518527031,
0.04868704080581665,
-0.09600604325532913,
-0.058606669306755066,
0.034693628549575806,
-0.03460796922445297,
0.05642986670136452,
0.015795892104506493,
0.06840869039297104,
-0.007546861190348864,
-0.100779689848423,
-0.027032839134335518,
0.10182306915521622,
-0.03606054559350014,
0.053757116198539734,
-0.10903319716453552,
0.01881723664700985,
-0.0032850659918040037,
0.02131507359445095,
0.056359630078077316,
0.06580408662557602,
-0.10305652022361755,
0.0077017429284751415,
-0.10780768096446991,
-0.03854450583457947,
-0.11383582651615143,
0.04457773268222809,
0.15791915357112885,
-0.014046847820281982,
0.1186855211853981,
-0.09761463105678558,
-0.00005232699913904071,
-0.20604901015758514,
0.013293848372995853,
-0.030861394479870796,
-0.0942612960934639,
-0.061086419969797134,
0.00945631880313158,
0.08404622972011566,
-0.02205614000558853,
0.05722640082240105,
-0.006800921633839607,
-0.023902922868728638,
0.06380389630794525,
0.10333842039108276,
-0.027470747008919716,
0.014009700156748295,
0.19065581262111664,
0.0873369500041008,
-0.036921728402376175,
0.055365096777677536,
0.078659787774086,
0.10429755598306656,
0.03818390890955925,
0.07059439271688461,
0.12037276476621628,
-0.07388264685869217,
0.12366579473018646,
0.06985274702310562,
-0.06791998445987701,
-0.06530303508043289,
0.09523225575685501,
-0.16276323795318604,
0.041574299335479736,
-0.04372834414243698,
0.013226913288235664,
0.18197840452194214,
-0.10939224064350128,
-0.0028771236538887024,
-0.06620590388774872,
-0.07250995188951492,
-0.14288330078125,
-0.11304590851068497,
-0.1491575837135315,
-0.05745183676481247,
0.021913627162575722,
-0.08902901411056519,
0.029872292652726173,
0.18360891938209534,
0.02622304856777191,
-0.0002496016677469015,
0.17335233092308044,
-0.17790235579013824,
0.022946370765566826,
0.0403658002614975,
-0.0028835637494921684,
-0.056975461542606354,
-0.02144307643175125,
-0.0437394343316555,
0.03300156071782112,
0.025905603542923927,
0.030387187376618385,
-0.010297560133039951,
0.0013103249948471785,
0.06459087878465652,
0.028278769925236702,
-0.11806637793779373,
-0.016668062657117844,
0.029181381687521935,
0.014125282876193523,
0.07393191754817963,
-0.008428764529526234,
0.052902016788721085,
-0.029703255742788315,
0.18905925750732422,
-0.10949984192848206,
-0.01661902852356434,
-0.10504753142595291,
0.17736804485321045,
-0.0034876628778874874,
0.08738494664430618,
-0.025024771690368652,
-0.06114548444747925,
0.05773890018463135,
0.1563854068517685,
0.12893332540988922,
-0.058434098958969116,
-0.041788250207901,
0.0073113408870995045,
-0.01683397777378559,
-0.07197993993759155,
0.0934271365404129,
0.033078666776418686,
0.07634130120277405,
-0.058706313371658325,
0.060860585421323776,
-0.005159957334399223,
-0.05619733780622482,
-0.024441909044981003,
0.04015330597758293,
0.02255462296307087,
0.061957623809576035,
-0.06176089122891426,
0.0861075296998024,
-0.019738515838980675,
0.04632646590471268,
0.13822369277477264,
-0.12272801250219345,
-0.146117702126503,
0.022381430491805077,
0.025084566324949265,
-0.03111615777015686,
0.08612586557865143,
-0.06069856137037277,
0.006349538918584585,
-0.02318832091987133,
-0.008890513330698013,
-0.13924354314804077,
-0.1060178279876709,
-0.019567180424928665,
0.09899567812681198,
0.2975042760372162,
0.004473465494811535,
0.049209676682949066,
0.13978832960128784,
-0.052967481315135956,
-0.17468124628067017,
0.10082078725099564,
-0.01963338442146778,
-0.1333613246679306,
0.10916417092084885,
0.16235089302062988,
-0.03260146453976631,
0.18682438135147095,
0.019240593537688255,
-0.21094760298728943,
0.012319231405854225,
-0.003909640479832888,
-0.013855431228876114,
-0.06946438550949097,
0.03635379672050476,
-0.061481062322854996,
0.15360033512115479,
0.14169947803020477,
-0.02200106717646122,
-0.00446306774392724,
-0.04477677866816521,
0.049239128828048706,
0.025003129616379738,
0.06049450859427452,
0.004668248817324638,
-0.13880540430545807,
0.0767989233136177,
-0.11890368908643723,
-0.010440975427627563,
-0.2878330945968628,
-0.07359427213668823,
-0.04565589129924774,
-0.05194716900587082,
-0.08214311301708221,
0.10224226862192154,
0.13468047976493835,
0.039121370762586594,
-0.03799950331449509,
-0.19812706112861633,
0.03259630873799324,
0.13355927169322968,
-0.07639570534229279,
-0.12773610651493073
] |
null | null | null |
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Using it with kornia:
```python
from kornia.contrib import VisionTransformer
vit_model = VisionTransformer.from_config('vit_l/16', pretrained=True)
...
```
Original weights from [AugReg](https://arxiv.org/abs/2106.10270) as recommended by [google research vision transformer repo](https://github.com/google-research/vision_transformer): This weight is based on the
[AugReg l ViT_L/16 pretrained on imagenet21k](https://storage.googleapis.com/vit_models/augreg/L_16-i21k-300ep-lr_0.001-aug_strong1-wd_0.1-do_0.0-sd_0.0.npz)
Weights converted to PyTorch for Kornia ViT implementation (by [@gau-nernst](https://github.com/gau-nernst) in [kornia/kornia#2786](https://github.com/kornia/kornia/pull/2786#discussion_r1482339811))
<details>
<summary>Convert jax checkpoint function</summary>
```
def convert_jax_checkpoint(np_state_dict: dict[str, np.ndarray]):
def get_weight(key: str) -> torch.Tensor:
return torch.from_numpy(np_state_dict[key])
state_dict = dict()
state_dict["patch_embedding.cls_token"] = get_weight("cls")
state_dict["patch_embedding.backbone.weight"] = get_weight("embedding/kernel").permute(3, 2, 0, 1) # conv »
state_dict["patch_embedding.backbone.bias"] = get_weight("embedding/bias")
state_dict["patch_embedding.positions"] = get_weight("Transformer/posembed_input/pos_embedding").squeeze(0)
# for i, block in enumerate(self.encoder.blocks):
for i in range(100):
prefix1 = f"encoder.blocks.{i}"
prefix2 = f"Transformer/encoderblock_{i}"
if f"{prefix2}/LayerNorm_0/scale" not in np_state_dict:
break
state_dict[f"{prefix1}.0.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_0/scale")
state_dict[f"{prefix1}.0.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_0/bias")
mha_prefix = f"{prefix2}/MultiHeadDotProductAttention_1"
qkv_weight = [get_weight(f"{mha_prefix}/{x}/kernel") for x in ["query", "key", "value"]]
qkv_bias = [get_weight(f"{mha_prefix}/{x}/bias") for x in ["query", "key", "value"]]
state_dict[f"{prefix1}.0.fn.1.qkv.weight"] = torch.cat(qkv_weight, 1).flatten(1).T
state_dict[f"{prefix1}.0.fn.1.qkv.bias"] = torch.cat(qkv_bias, 0).flatten()
state_dict[f"{prefix1}.0.fn.1.projection.weight"] = get_weight(f"{mha_prefix}/out/kernel").flatten(0, 1»
state_dict[f"{prefix1}.0.fn.1.projection.bias"] = get_weight(f"{mha_prefix}/out/bias")
state_dict[f"{prefix1}.1.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_2/scale")
state_dict[f"{prefix1}.1.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_2/bias")
state_dict[f"{prefix1}.1.fn.1.0.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/kernel").T
state_dict[f"{prefix1}.1.fn.1.0.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/bias")
state_dict[f"{prefix1}.1.fn.1.3.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/kernel").T
state_dict[f"{prefix1}.1.fn.1.3.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/bias")
state_dict["norm.weight"] = get_weight("Transformer/encoder_norm/scale")
state_dict["norm.bias"] = get_weight("Transformer/encoder_norm/bias")
return state_dict
```
</details> | {"license": "apache-2.0", "pipeline_tag": "image-classification"} | image-classification | kornia/vit_l16_augreg_i21k_r224 | [
"image-classification",
"arxiv:2106.10270",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:07:40+00:00 | [
"2106.10270"
] | [] | TAGS
#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us
|
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Using it with kornia:
Original weights from AugReg as recommended by google research vision transformer repo: This weight is based on the
AugReg l ViT_L/16 pretrained on imagenet21k
Weights converted to PyTorch for Kornia ViT implementation (by @gau-nernst in kornia/kornia#2786)
<details>
<summary>Convert jax checkpoint function</summary>
</details> | [] | [
"TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
27
] | [
"passage: TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
-0.06109374389052391,
0.20674705505371094,
-0.006548014469444752,
0.049976740032434464,
0.02543392963707447,
0.06775278598070145,
0.1434560865163803,
0.10054779052734375,
0.0873129591345787,
-0.0696193128824234,
0.16259659826755524,
0.07446799427270889,
0.027905816212296486,
-0.020278295502066612,
0.0003193104930687696,
-0.19860264658927917,
0.07249123603105545,
-0.01418757252395153,
-0.03743588179349899,
0.016364481300115585,
0.031079968437552452,
-0.03377098590135574,
0.06803242117166519,
-0.013396034017205238,
-0.12081167846918106,
-0.004631385672837496,
0.05561913177371025,
-0.04842509329319,
0.07639530301094055,
-0.0024446528404951096,
0.03034677915275097,
0.033661652356386185,
0.0436035580933094,
-0.18721453845500946,
-0.0013201063266023993,
-0.011022438295185566,
-0.13286513090133667,
0.06692822277545929,
0.12416379153728485,
0.0049120765179395676,
0.03520214185118675,
0.04749228432774544,
-0.1190459355711937,
0.007217442616820335,
-0.09456748515367508,
-0.2383200079202652,
-0.10159328579902649,
0.11124194413423538,
0.12468010187149048,
0.01974388025701046,
0.10125472396612167,
0.03719622269272804,
-0.12143778800964355,
0.007481607608497143,
0.07237470895051956,
-0.24169990420341492,
-0.010691691190004349,
0.1201784610748291,
-0.1079055592417717,
0.04524125158786774,
-0.03944199159741402,
0.09898041188716888,
0.0823771059513092,
-0.045112185180187225,
-0.11518827825784683,
-0.045906227082014084,
-0.11930672824382782,
0.05414021015167236,
0.02489721029996872,
-0.08919412642717361,
0.3176185190677643,
0.1532946676015854,
0.002456814516335726,
0.11417848616838455,
-0.034857455641031265,
0.03917086496949196,
-0.020580649375915527,
0.14350418746471405,
0.11800917983055115,
0.1277526319026947,
0.11405012756586075,
-0.018727514892816544,
-0.18136470019817352,
-0.06914898008108139,
-0.16194461286067963,
-0.04335305839776993,
-0.03692782297730446,
0.17465905845165253,
-0.1323341280221939,
-0.02526034042239189,
-0.1357729136943817,
-0.08216837048530579,
0.02422415465116501,
-0.0783277153968811,
0.17794139683246613,
0.12570883333683014,
-0.025183117017149925,
0.05908667668700218,
0.14745140075683594,
0.12899348139762878,
0.02096019685268402,
0.03532757610082626,
-0.10447050631046295,
0.19674737751483917,
-0.02905309945344925,
0.03755328059196472,
0.03452769294381142,
0.11503022909164429,
0.06668683886528015,
-0.08765921741724014,
0.09905751049518585,
-0.034111931920051575,
-0.1760949343442917,
-0.02817642129957676,
-0.0438312403857708,
0.051844481378793716,
-0.0005061799311079085,
-0.04923499748110771,
-0.07902505248785019,
0.02592616155743599,
0.20208676159381866,
0.005098436959087849,
0.00970771349966526,
-0.009410499595105648,
-0.01887846365571022,
-0.03703097999095917,
0.06327838450670242,
0.020843954756855965,
0.06386575847864151,
-0.00038021898944862187,
-0.07227174192667007,
0.04220779612660408,
0.0033467260655015707,
0.07464555650949478,
0.11725340783596039,
-0.033287424594163895,
0.031015444546937943,
-0.1253310889005661,
-0.06270439177751541,
0.03723682835698128,
0.086534284055233,
0.0028114039450883865,
0.01238210964947939,
0.11720160394906998,
0.014849238097667694,
0.03825271129608154,
-0.03593437746167183,
-0.060856327414512634,
-0.099258191883564,
0.055119361728429794,
-0.13103467226028442,
0.08423157781362534,
-0.2563755214214325,
0.011386703699827194,
-0.10534657537937164,
0.053238339722156525,
-0.09686396270990372,
-0.07819923013448715,
-0.13250695168972015,
0.2009194940328598,
-0.05468209087848663,
0.0034654189366847277,
-0.054602500051259995,
-0.00633781123906374,
-0.05506056174635887,
0.07645745575428009,
-0.15609174966812134,
0.02364489808678627,
0.08345842361450195,
-0.15114741027355194,
-0.13571877777576447,
-0.002641590777784586,
0.043754223734140396,
-0.07488250732421875,
-0.010925939306616783,
0.3182951807975769,
-0.03542245179414749,
-0.01839727908372879,
0.036988433450460434,
0.15065109729766846,
-0.08740837126970291,
-0.20893323421478271,
0.10468775033950806,
-0.09690731018781662,
-0.14157627522945404,
0.0215351153165102,
-0.13635723292827606,
0.10152363032102585,
0.040783826261758804,
-0.08645343035459518,
-0.02261362224817276,
-0.04002821445465088,
-0.04111453890800476,
0.012164331041276455,
0.05289793014526367,
-0.046031367033720016,
0.036598462611436844,
-0.10292722284793854,
0.05292672663927078,
0.08823665231466293,
0.03464950621128082,
-0.019848383963108063,
0.05194208770990372,
-0.0322202704846859,
-0.008407019078731537,
-0.06743084639310837,
0.03886767849326134,
0.009944709949195385,
-0.047629464417696,
0.08154439926147461,
-0.05256316438317299,
0.028394905850291252,
-0.08248095214366913,
-0.0052256197668612,
-0.03148965165019035,
-0.021348997950553894,
0.016548115760087967,
0.04151642695069313,
-0.15185265243053436,
0.05146369710564613,
0.027628103271126747,
0.06300205737352371,
-0.07534655928611755,
-0.06911735236644745,
0.13192912936210632,
-0.02104104869067669,
-0.006522714160382748,
0.09356412291526794,
0.007906613871455193,
-0.09177529066801071,
-0.01047999132424593,
-0.02048683352768421,
0.1222124695777893,
0.01773674599826336,
-0.03080260008573532,
0.15719905495643616,
0.004599755629897118,
0.1652202308177948,
0.19648905098438263,
-0.1871400624513626,
0.05895731970667839,
-0.04543163627386093,
0.03526407852768898,
-0.00021277944324538112,
0.058195192366838455,
0.030574873089790344,
-0.11539100110530853,
-0.0529194250702858,
0.04648087918758392,
-0.0637110099196434,
0.08189071714878082,
-0.016040494665503502,
-0.07081851363182068,
-0.09113258868455887,
-0.004617263562977314,
0.22731298208236694,
-0.22143718600273132,
0.13705743849277496,
0.44992348551750183,
-0.00563804479315877,
0.04384651407599449,
-0.07071708142757416,
-0.02926171012222767,
0.011590258218348026,
-0.016685742884874344,
-0.027885599061846733,
0.20283104479312897,
-0.037577949464321136,
-0.006611361168324947,
0.07687141746282578,
0.021334122866392136,
0.02833111397922039,
-0.2102135717868805,
-0.08647490292787552,
-0.01990378089249134,
-0.032265402376651764,
-0.106113001704216,
-0.03494508937001228,
-0.07398673892021179,
0.09487839788198471,
-0.00005973442966933362,
-0.13227896392345428,
0.12197559326887131,
-0.04474426805973053,
-0.053833432495594025,
0.1027798280119896,
-0.1763962209224701,
-0.23515380918979645,
-0.14439262449741364,
0.03435428440570831,
-0.07389409840106964,
0.033989984542131424,
0.05001555383205414,
-0.12449482828378677,
-0.042997002601623535,
0.009898168034851551,
-0.17011038959026337,
-0.0666801705956459,
-0.009744573384523392,
0.04772152379155159,
0.06096755340695381,
0.05611218884587288,
-0.07783979177474976,
-0.04949898272752762,
-0.03132689744234085,
0.022898364812135696,
0.13073059916496277,
-0.10337543487548828,
0.13391651213169098,
0.08956552296876907,
-0.0060893171466887,
0.037197306752204895,
0.024989010766148567,
0.06867308169603348,
-0.06233874335885048,
-0.009597424417734146,
0.15581579506397247,
-0.009040242061018944,
0.06215013191103935,
0.12999725341796875,
0.06666824221611023,
-0.09433972090482712,
-0.022919438779354095,
-0.01883879117667675,
-0.09602656215429306,
-0.19175516068935394,
-0.057091742753982544,
-0.049366164952516556,
0.08483017235994339,
0.14666369557380676,
0.11997713893651962,
0.16513875126838684,
0.09672091901302338,
0.017073094844818115,
0.032890960574150085,
0.011969516053795815,
0.02745753899216652,
0.09431096166372299,
-0.00256404560059309,
-0.00900819431990385,
-0.1345144361257553,
0.04063615947961807,
0.16199742257595062,
0.16016624867916107,
0.2346680760383606,
0.24405603110790253,
0.013032541610300541,
0.08629986643791199,
0.14010414481163025,
0.09959616512060165,
0.083418108522892,
0.014013865031301975,
0.0002983128360938281,
-0.07782557606697083,
-0.06522127240896225,
0.007191324606537819,
0.08919525146484375,
-0.056596651673316956,
-0.13630864024162292,
0.04233114793896675,
-0.15700164437294006,
0.043609846383333206,
0.08521639555692673,
0.10101553797721863,
-0.12919598817825317,
0.11238693445920944,
0.07870315760374069,
0.13523606956005096,
-0.033454976975917816,
0.12932239472866058,
-0.03169083222746849,
-0.008430219255387783,
0.1317882388830185,
0.007853557355701923,
0.08151012659072876,
-0.024717014282941818,
-0.0011054257629439235,
-0.017972934991121292,
-0.23283958435058594,
0.0644598975777626,
0.10178142786026001,
-0.11300219595432281,
0.27768510580062866,
0.031322941184043884,
-0.12874376773834229,
-0.04034474864602089,
-0.036046352237463,
0.12492694705724716,
0.22686100006103516,
0.1506083458662033,
0.08461418747901917,
-0.2186128795146942,
-0.015754923224449158,
-0.09932077676057816,
-0.0005119231645949185,
0.029082471504807472,
0.023185651749372482,
-0.18783825635910034,
0.0009278097422793508,
0.018264522776007652,
0.001460708910599351,
0.1566782295703888,
-0.10841827839612961,
-0.0659492164850235,
0.00179493788164109,
0.08047734946012497,
-0.04437811300158501,
-0.06396231800317764,
0.034309569746255875,
-0.013767643831670284,
0.036747898906469345,
-0.022247834131121635,
-0.004408868495374918,
-0.04094367474317551,
-0.12550413608551025,
0.021679183468222618,
-0.017714237794280052,
0.029833028092980385,
-0.08279894292354584,
-0.04034486040472984,
-0.06748219579458237,
-0.23039697110652924,
0.14154691994190216,
-0.07678768783807755,
0.016050616279244423,
-0.05765075236558914,
0.05977974832057953,
-0.0824442207813263,
0.00418700510635972,
-0.0022916689049452543,
0.056743767112493515,
-0.033833812922239304,
-0.10060850530862808,
0.1735401153564453,
-0.02724578231573105,
0.046342626214027405,
-0.00022314728994388133,
-0.05170644447207451,
-0.035063985735177994,
0.012569589540362358,
-0.02630540169775486,
0.1234268769621849,
0.2582937479019165,
-0.11369399726390839,
0.11319419741630554,
0.22277510166168213,
-0.08378475159406662,
-0.2901381254196167,
-0.0702567845582962,
-0.18003669381141663,
-0.1256219744682312,
0.052320681512355804,
-0.19621984660625458,
0.14071376621723175,
0.22147466242313385,
-0.14830414950847626,
0.229997918009758,
-0.14988930523395538,
-0.030987894162535667,
0.15975996851921082,
-0.0008190532680600882,
0.3081471621990204,
-0.19845253229141235,
-0.06818240880966187,
-0.12761925160884857,
-0.15836204588413239,
0.155714213848114,
-0.025408737361431122,
0.006225026212632656,
-0.007217234466224909,
-0.08931957185268402,
-0.02436586655676365,
0.004366954322904348,
0.24909676611423492,
0.004330891650170088,
0.16055257618427277,
-0.11767592281103134,
-0.12619024515151978,
0.11690738052129745,
-0.06503412872552872,
-0.0007165660499595106,
-0.10723470896482468,
-0.010643302462995052,
-0.11397052556276321,
0.09066908806562424,
-0.05764220282435417,
0.04375004768371582,
0.02174108289182186,
-0.017453894019126892,
-0.10904242843389511,
-0.005453106015920639,
-0.09661629796028137,
0.0515119843184948,
0.356973797082901,
0.056218892335891724,
-0.06076716259121895,
0.09476302564144135,
-0.045844666659832,
-0.09363016486167908,
-0.04768260940909386,
-0.12678976356983185,
-0.0685768872499466,
0.1280103325843811,
-0.30839988589286804,
0.06342349946498871,
0.060435857623815536,
-0.0101803969591856,
0.05798220634460449,
0.0419137105345726,
-0.008689306676387787,
-0.002610941184684634,
0.18246068060398102,
-0.041163694113492966,
-0.013913077302277088,
0.022781025618314743,
0.1528378427028656,
0.20284785330295563,
0.038649726659059525,
0.07634012401103973,
0.016211945563554764,
0.004480070900171995,
0.037742264568805695,
0.07341662049293518,
-0.0799650028347969,
-0.060552340000867844,
0.0995108038187027,
-0.0472230538725853,
-0.08839789032936096,
0.2580071687698364,
0.06586729735136032,
-0.040969472378492355,
-0.060587961226701736,
0.023097578436136246,
-0.06413619965314865,
-0.106551893055439,
-0.029016191139817238,
0.007275809999555349,
-0.14201894402503967,
-0.14605849981307983,
0.029940688982605934,
-0.055694930255413055,
-0.036023736000061035,
-0.0009951975662261248,
0.0818314328789711,
0.01024248544126749,
0.10877418518066406,
-0.050103265792131424,
0.1298569291830063,
-0.07700810581445694,
-0.21583467721939087,
0.044681038707494736,
-0.1390920728445053,
-0.24245065450668335,
0.05320950597524643,
0.07469253987073898,
-0.029019640758633614,
-0.011899758130311966,
-0.06899982690811157,
0.06061933934688568,
-0.1356326937675476,
0.12674148380756378,
-0.05317538231611252,
0.017484011128544807,
0.023907091468572617,
-0.030213210731744766,
-0.043195463716983795,
0.009983353316783905,
-0.15352073311805725,
-0.06672659516334534,
-0.0035989026073366404,
0.06315059959888458,
-0.0489853136241436,
-0.08843541145324707,
0.08217836916446686,
0.04006815701723099,
0.08011067658662796,
0.07868228107690811,
0.00977279432117939,
0.0726410523056984,
-0.18324869871139526,
-0.1208200752735138,
0.14623382687568665,
0.025101887062191963,
-0.048409875482320786,
0.08060428500175476,
-0.039926428347826004,
0.04881305247545242,
-0.08390691131353378,
0.006642403081059456,
0.0034260768443346024,
-0.1251237690448761,
-0.09406817704439163,
-0.09683351963758469,
-0.15214946866035461,
0.00039810591260902584,
-0.04967843368649483,
0.1913544088602066,
0.008625444024801254,
0.0807836502790451,
0.036689359694719315,
-0.006731836590915918,
-0.051704924553632736,
0.02872658520936966,
-0.041187088936567307,
-0.10434682667255402,
-0.17093461751937866,
-0.015617710538208485,
-0.0860636904835701,
-0.1006554514169693,
0.2431410551071167,
0.048497993499040604,
-0.1993618756532669,
0.02384042739868164,
0.18894675374031067,
-0.07109846919775009,
0.023319972679018974,
0.25406286120414734,
0.00019303734006825835,
0.025920644402503967,
-0.02808104082942009,
0.026976024731993675,
0.021667996421456337,
-0.02375073917210102,
0.026855897158384323,
0.12996679544448853,
0.043553244322538376,
0.032946716994047165,
0.14659735560417175,
-0.0173412524163723,
-0.08477585017681122,
0.022847771644592285,
0.061927322298288345,
0.1110801249742508,
0.04275544360280037,
0.04724521189928055,
0.21924637258052826,
-0.0042988271452486515,
-0.00025624613044783473,
-0.05579526722431183,
0.011268865317106247,
-0.08793025463819504,
-0.1877223551273346,
-0.05527739226818085,
-0.17583560943603516,
0.049897871911525726,
-0.004426159430295229,
-0.012788284569978714,
0.2909761965274811,
0.027319302782416344,
-0.0482502318918705,
-0.06282444298267365,
-0.16109506785869598,
-0.07760324329137802,
0.06602004915475845,
-0.00034622318344190717,
-0.07779118418693542,
-0.04654536023736,
-0.05229349806904793,
0.06716009229421616,
-0.0650051012635231,
-0.044580407440662384,
0.00833569560199976,
0.08897022902965546,
-0.0011313384165987372,
-0.059533439576625824,
-0.058417774736881256,
-0.07093261927366257,
0.007818278856575489,
-0.041152771562337875,
0.13718730211257935,
0.014150754548609257,
0.061706382781267166,
0.08388342708349228,
0.0832892581820488,
-0.04481666162610054,
-0.005954330787062645,
0.01730518601834774,
0.024704741314053535,
-0.14028121531009674,
0.07547515630722046,
-0.05182021111249924,
-0.046783607453107834,
0.011663789860904217,
0.16521625220775604,
0.19023829698562622,
-0.10069664567708969,
-0.03277084603905678,
-0.03297418728470802,
0.010275846347212791,
0.013714811764657497,
0.13700632750988007,
0.08500899374485016,
0.08871713280677795,
-0.032855018973350525,
-0.061874307692050934,
-0.06518110632896423,
0.015506909228861332,
-0.14511807262897491,
0.03136218339204788,
0.038375891745090485,
-0.08714506775140762,
-0.0889124721288681,
0.12509585916996002,
0.014278160408139229,
0.11131628602743149,
0.16461534798145294,
-0.05992981046438217,
-0.024726636707782745,
0.014439063146710396,
0.15600472688674927,
0.035410262644290924,
-0.006145869381725788,
-0.15497305989265442,
-0.06066638603806496,
-0.03294585272669792,
0.0111419428139925,
-0.3058968782424927,
-0.16970622539520264,
-0.008374981582164764,
-0.0351867713034153,
0.30137813091278076,
0.027061674743890762,
0.06243366748094559,
0.008204973302781582,
0.02186395600438118,
-0.10690846294164658,
0.08221492171287537,
-0.02377958409488201,
0.01824123226106167,
-0.08009807765483856,
-0.11080692708492279,
-0.03178728371858597,
-0.03495577722787857,
0.1160794198513031,
0.059739332646131516,
-0.02478528767824173,
0.20401827991008759,
-0.09265992045402527,
-0.053211916238069534,
0.013441485352814198,
-0.18209552764892578,
0.028789974749088287,
-0.048542529344558716,
-0.005964033771306276,
-0.13737298548221588,
-0.047639016062021255,
-0.04662676155567169,
0.07773999124765396,
-0.2452046424150467,
-0.04547024518251419,
0.22630788385868073,
-0.009974819608032703,
0.022548647597432137,
0.05865916237235069,
0.05990443006157875,
0.0051626162603497505,
-0.10867731273174286,
0.03566248342394829,
-0.07021775841712952,
0.012532292865216732,
0.11721400171518326,
-0.03954120725393295,
-0.00978852342814207,
-0.12052185088396072,
0.08994459360837936,
-0.02892490290105343,
0.04041118174791336,
-0.08855695277452469
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# glue_mrpc_nli_2
This model is a fine-tuned version of [santiadavani/glue_mrpc_nli_2](https://huggingface.co/santiadavani/glue_mrpc_nli_2) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "santiadavani/glue_mrpc_nli_2", "model-index": [{"name": "glue_mrpc_nli_2", "results": []}]} | text-classification | santiadavani/glue_mrpc_nli_2 | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:santiadavani/glue_mrpc_nli_2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:08:18+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-santiadavani/glue_mrpc_nli_2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# glue_mrpc_nli_2
This model is a fine-tuned version of santiadavani/glue_mrpc_nli_2 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# glue_mrpc_nli_2\n\nThis model is a fine-tuned version of santiadavani/glue_mrpc_nli_2 on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-santiadavani/glue_mrpc_nli_2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# glue_mrpc_nli_2\n\nThis model is a fine-tuned version of santiadavani/glue_mrpc_nli_2 on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
74,
43,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-santiadavani/glue_mrpc_nli_2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# glue_mrpc_nli_2\n\nThis model is a fine-tuned version of santiadavani/glue_mrpc_nli_2 on the None dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0### Training results### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.10405649244785309,
0.1922006607055664,
-0.0020786377135664225,
0.10906517505645752,
0.12588779628276825,
0.010394719429314137,
0.10936753451824188,
0.147222101688385,
-0.07634726911783218,
0.08000621199607849,
0.06619951128959656,
0.03230941295623779,
0.05347553640604019,
0.14830592274665833,
-0.025934753939509392,
-0.21359743177890778,
0.012292810715734959,
-0.030082428827881813,
-0.03328235074877739,
0.09574814140796661,
0.10358527302742004,
-0.08543957769870758,
0.08613219857215881,
-0.01920139789581299,
-0.11209938675165176,
0.021397516131401062,
-0.03156958520412445,
-0.05596744641661644,
0.07275082170963287,
-0.02017621137201786,
0.058004140853881836,
0.023980753496289253,
0.1449003964662552,
-0.24437417089939117,
-0.007257482968270779,
0.05669669434428215,
0.039505645632743835,
0.07424554973840714,
0.05534560605883598,
-0.021959524601697922,
0.048092085868120193,
-0.16975054144859314,
0.1065252423286438,
0.027063939720392227,
-0.07119451463222504,
-0.11437862366437912,
-0.09695091098546982,
0.08620107173919678,
0.10068698227405548,
0.09003560990095139,
0.022443562746047974,
0.14362573623657227,
-0.0545722097158432,
0.06931933015584946,
0.19880901277065277,
-0.2615048289299011,
-0.050153400748968124,
0.07805673032999039,
0.03239759802818298,
0.06027021259069443,
-0.12223818898200989,
0.0017809623386710882,
0.061244238168001175,
0.013860727660357952,
0.0981283038854599,
-0.0049483380280435085,
-0.08635489642620087,
-0.010341753251850605,
-0.11404336988925934,
-0.012099318206310272,
0.1846366971731186,
0.038908615708351135,
-0.050041165202856064,
-0.10850214213132858,
-0.02485530823469162,
-0.0833001360297203,
-0.008700063452124596,
-0.044529058039188385,
0.04600749909877777,
-0.041274234652519226,
-0.02946391887962818,
-0.04442320391535759,
-0.07454059273004532,
-0.08025319874286652,
0.039347097277641296,
0.08287211507558823,
0.035588011145591736,
0.00593718932941556,
0.0008286929805763066,
0.1046193465590477,
-0.03303692489862442,
-0.12927940487861633,
-0.041374050080776215,
-0.0029694403056055307,
-0.05814807489514351,
-0.07497572153806686,
-0.021113840863108635,
-0.018826698884367943,
0.0050461916252970695,
0.15504325926303864,
-0.0573810450732708,
0.05976173281669617,
0.00978732481598854,
0.0002555227547418326,
-0.03090624138712883,
0.12437024712562561,
-0.026469001546502113,
-0.0473768450319767,
0.01193310972303152,
0.09612667560577393,
0.02871250919997692,
-0.007808791473507881,
-0.06976127624511719,
-0.03077738918364048,
0.08111710846424103,
0.0821881890296936,
-0.04959547892212868,
0.030744072049856186,
-0.04231167957186699,
-0.0175110325217247,
0.019629791378974915,
-0.15403513610363007,
0.04463101923465729,
-0.02103136107325554,
-0.08163657784461975,
-0.05441632494330406,
0.0409630686044693,
0.007593077607452869,
-0.015521152876317501,
0.06520335376262665,
-0.06393968313932419,
-0.0054808370769023895,
-0.06862784922122955,
-0.026766519993543625,
0.04011422395706177,
-0.07699597626924515,
-0.005501818843185902,
-0.07509745657444,
-0.24990971386432648,
-0.034508250653743744,
0.028711361810564995,
-0.0722459927201271,
-0.023020802065730095,
-0.05971162021160126,
-0.045781396329402924,
0.0003900330630131066,
-0.00773828849196434,
0.06527718901634216,
-0.048940081149339676,
0.05433526635169983,
0.016346164047718048,
0.039445310831069946,
0.054039716720581055,
0.02925419621169567,
-0.1064765527844429,
0.038863979279994965,
-0.1000511646270752,
0.056757379323244095,
-0.0993453711271286,
0.04358746111392975,
-0.11426293849945068,
-0.08119205385446548,
-0.021108880639076233,
-0.047873977571725845,
0.04228140041232109,
0.16571559011936188,
-0.1655033975839615,
-0.008108610287308693,
0.16356703639030457,
-0.11276766657829285,
-0.1078333854675293,
0.09059284627437592,
-0.03331820294260979,
0.039826080203056335,
0.07561279088258743,
0.15488597750663757,
0.12735041975975037,
-0.15883547067642212,
-0.048552628606557846,
0.009660456329584122,
0.06478387862443924,
0.004857686813920736,
0.08640515804290771,
0.005088103003799915,
0.034146953374147415,
0.03193970024585724,
-0.08560366928577423,
-0.016400670632719994,
-0.06803222000598907,
-0.09456103295087814,
-0.06233692169189453,
-0.10843288898468018,
0.05317165330052376,
0.03616417944431305,
0.037520091980695724,
-0.07621091604232788,
-0.1030762642621994,
0.06419297307729721,
0.13947342336177826,
-0.05000102519989014,
0.005811168346554041,
-0.07178013026714325,
0.05295882374048233,
-0.04966384172439575,
-0.03789166361093521,
-0.16738030314445496,
-0.12531933188438416,
0.047987889498472214,
-0.06115536764264107,
0.03302457928657532,
-0.026918306946754456,
0.07564394176006317,
0.0828266516327858,
-0.07744681090116501,
-0.028471680358052254,
-0.07918264716863632,
0.019466150552034378,
-0.08015425503253937,
-0.17480958998203278,
-0.040506068617105484,
-0.04660864174365997,
0.1656891256570816,
-0.22912530601024628,
0.0367947518825531,
0.016346525400877,
0.16156227886676788,
0.038794729858636856,
-0.05620824173092842,
0.020583350211381912,
0.018905382603406906,
-0.008977585472166538,
-0.10370730608701706,
0.02376140095293522,
-0.003378775902092457,
-0.07099520415067673,
-0.05945358797907829,
-0.1158827468752861,
0.08091249316930771,
0.06851893663406372,
0.0902300477027893,
-0.0912167876958847,
-0.03195400908589363,
-0.050874147564172745,
-0.041441500186920166,
-0.09878306090831757,
0.004286611918359995,
0.15231522917747498,
0.012183456681668758,
0.11782540380954742,
-0.0623653382062912,
-0.07414460182189941,
-0.002114218892529607,
-0.0097233010455966,
-0.04733121395111084,
0.07009800523519516,
0.05084499344229698,
-0.08479061722755432,
0.10815718024969101,
0.1125175878405571,
-0.02647533267736435,
0.1270417422056198,
-0.048672184348106384,
-0.0902424305677414,
-0.03510970622301102,
0.022256461903452873,
-0.0036933585070073605,
0.1106179803609848,
-0.03580494597554207,
0.0024091824889183044,
0.019536765292286873,
0.018514763563871384,
0.02802298218011856,
-0.14798317849636078,
-0.012943372130393982,
0.03163673356175423,
-0.05443863570690155,
0.010493294335901737,
-0.02818199247121811,
0.004304441623389721,
0.07902126014232635,
0.015956507995724678,
-0.0008238639566116035,
0.03202288970351219,
-0.007253792602568865,
-0.08822644501924515,
0.15711140632629395,
-0.10796941071748734,
-0.1672932207584381,
-0.14338389039039612,
0.04695633798837662,
-0.04805799573659897,
-0.015948278829455376,
0.00453865434974432,
-0.09336409717798233,
-0.0534876212477684,
-0.10836224257946014,
-0.03838387876749039,
-0.025033151730895042,
-0.02099689468741417,
0.06967831403017044,
0.048941440880298615,
0.09244143217802048,
-0.11493247747421265,
0.007221576292067766,
0.015869110822677612,
-0.07015206664800644,
-0.022125571966171265,
0.024560701102018356,
0.11347722262144089,
0.09604643285274506,
-0.032064955681562424,
0.034666333347558975,
-0.0347466804087162,
0.17961500585079193,
-0.052074041217565536,
-0.006227486301213503,
0.13593058288097382,
0.01082060020416975,
0.038621656596660614,
0.12419718503952026,
0.01841992512345314,
-0.09250883758068085,
0.02725854702293873,
0.04592232406139374,
-0.02063809335231781,
-0.24429595470428467,
-0.05198664590716362,
-0.012290540151298046,
-0.03377015143632889,
0.09373059868812561,
0.06109488755464554,
0.020567266270518303,
0.045095425099134445,
-0.008367970585823059,
0.008403820917010307,
0.007999477908015251,
0.0965799018740654,
0.06575527042150497,
0.029085639864206314,
0.07682230323553085,
-0.039591144770383835,
-0.017659779638051987,
0.06345907598733902,
0.03321189433336258,
0.22982892394065857,
-0.01636424846947193,
0.0930568128824234,
0.014941088855266571,
0.14799267053604126,
-0.03309454396367073,
0.030357806012034416,
0.037829186767339706,
0.008633558638393879,
0.0163564532995224,
-0.08019915223121643,
-0.03617475926876068,
0.058134306222200394,
-0.04730486869812012,
0.05035008117556572,
-0.105574831366539,
0.05301198363304138,
0.03555860370397568,
0.21645301580429077,
0.045875925570726395,
-0.30469027161598206,
-0.07324326783418655,
0.03472769260406494,
-0.005709505174309015,
-0.038153961300849915,
0.0172535739839077,
0.10839475691318512,
-0.12030019611120224,
0.0876503512263298,
-0.04813205450773239,
0.08233777433633804,
-0.05010920390486717,
-0.006455378606915474,
0.056817930191755295,
0.07767051458358765,
0.004214379005134106,
0.10044136643409729,
-0.1733856499195099,
0.20220719277858734,
0.029918307438492775,
0.12719711661338806,
-0.051461540162563324,
0.03553299605846405,
0.020960411056876183,
0.10900931805372238,
0.157790407538414,
-0.016963474452495575,
-0.10901932418346405,
-0.18962644040584564,
-0.12314638495445251,
0.016651300713419914,
0.11075655370950699,
-0.05369117110967636,
0.07854267209768295,
-0.04828718677163124,
-0.01128888875246048,
0.040789537131786346,
-0.0923692062497139,
-0.1926930993795395,
-0.12571802735328674,
0.031404048204422,
0.02441949024796486,
-0.01982315070927143,
-0.0905708372592926,
-0.1114971861243248,
-0.05749930068850517,
0.19272635877132416,
0.003829116467386484,
-0.04496268555521965,
-0.1486499309539795,
0.0657263770699501,
0.11466215550899506,
-0.06478843092918396,
0.006381874438375235,
0.03040974773466587,
0.15822483599185944,
0.03157448396086693,
-0.07971002906560898,
0.027672259137034416,
-0.07349662482738495,
-0.16011615097522736,
-0.056519195437431335,
0.14474552869796753,
0.040337417274713516,
0.04437147080898285,
0.02343907579779625,
0.03358056768774986,
0.03988724201917648,
-0.0834842249751091,
0.014783663675189018,
0.0861140638589859,
0.09288159012794495,
0.04716465622186661,
-0.11103208363056183,
0.013401385396718979,
-0.04519379138946533,
-0.030563782900571823,
0.1191578209400177,
0.21319977939128876,
-0.09362570196390152,
0.09962625056505203,
0.07110141217708588,
-0.09793736785650253,
-0.1769639253616333,
0.057137779891490936,
0.060019828379154205,
0.011407312005758286,
0.08100391924381256,
-0.14797838032245636,
0.10862001031637192,
0.11017925292253494,
-0.031249510124325752,
0.014507424086332321,
-0.28656092286109924,
-0.11615174263715744,
0.061140891164541245,
0.10614067316055298,
-0.029320672154426575,
-0.13040591776371002,
-0.05353977903723717,
-0.023610299453139305,
-0.14204944670200348,
0.07377324253320694,
-0.08764100074768066,
0.08281321078538895,
-0.013830822892487049,
0.054780252277851105,
0.02579616941511631,
-0.04135958105325699,
0.14563634991645813,
0.03037972003221512,
0.07922147214412689,
-0.055426910519599915,
0.019813496619462967,
0.08254374563694,
-0.08966642618179321,
0.10396751761436462,
-0.05157453194260597,
0.0757460817694664,
-0.12774482369422913,
-0.03417041152715683,
-0.03126349300146103,
0.06845133751630783,
-0.0562724843621254,
-0.0570618137717247,
-0.04084650054574013,
0.08186328411102295,
0.06696177273988724,
-0.03193572163581848,
0.060053084045648575,
0.021842004731297493,
0.11305943876504898,
0.13169586658477783,
0.0939461812376976,
0.005257000215351582,
-0.07368055731058121,
-0.005115801468491554,
-0.0318119116127491,
0.029547955840826035,
-0.11533226817846298,
0.035452041774988174,
0.13265730440616608,
0.04204103350639343,
0.1369902789592743,
0.018757009878754616,
-0.03690941631793976,
-0.017775865271687508,
0.0429685078561306,
-0.11632435023784637,
-0.11659616976976395,
-0.020027920603752136,
-0.032706886529922485,
-0.1351689100265503,
0.02329714223742485,
0.10571563988924026,
-0.08970839530229568,
-0.004810470622032881,
-0.025059647858142853,
0.04810688644647598,
-0.02004644088447094,
0.1759452372789383,
0.04733656346797943,
0.05560074746608734,
-0.06420610845088959,
0.1474616676568985,
0.08367232978343964,
-0.07166881114244461,
0.04761986806988716,
0.048021987080574036,
-0.09388378262519836,
-0.03260134905576706,
0.0636986643075943,
0.16208700835704803,
0.0073293885216116905,
-0.061969757080078125,
-0.10698262602090836,
-0.07033833116292953,
0.03356640040874481,
0.08563282340765,
0.054152294993400574,
-0.0002189829683629796,
-0.017450833693146706,
0.01710476353764534,
-0.14171643555164337,
0.11837930232286453,
0.06614924222230911,
0.06190662831068039,
-0.17427553236484528,
0.0808819904923439,
0.0015094983391463757,
0.028078749775886536,
-0.022185716778039932,
0.030888503417372704,
-0.07196729630231857,
-0.02115960419178009,
-0.07378543168306351,
0.011140363290905952,
-0.03270949423313141,
0.01000689435750246,
-0.014698522165417671,
-0.054757311940193176,
-0.042033612728118896,
0.05225019156932831,
-0.04896554723381996,
-0.05470744147896767,
0.0004842362832278013,
0.07710307836532593,
-0.1488894373178482,
-0.03140539303421974,
0.031933389604091644,
-0.08702100068330765,
0.058247730135917664,
0.0367032065987587,
0.028193624690175056,
0.018675005063414574,
-0.1133570745587349,
0.01277798879891634,
0.03418092429637909,
0.03295138105750084,
0.034068167209625244,
-0.13345877826213837,
-0.006970818154513836,
-0.011833136901259422,
0.016621161252260208,
0.03194156661629677,
0.05658802390098572,
-0.11335846036672592,
-0.02935776300728321,
-0.06142245605587959,
-0.04852767661213875,
-0.04758407175540924,
0.04591071233153343,
0.13007324934005737,
0.0060004498809576035,
0.15277114510536194,
-0.08440817147493362,
0.05451301112771034,
-0.19239753484725952,
-0.022193247452378273,
0.00362808583304286,
-0.030645178630948067,
-0.1068684533238411,
-0.012894946150481701,
0.06835677474737167,
-0.053047750145196915,
0.12502612173557281,
-0.004375394433736801,
0.07830929011106491,
0.04819163680076599,
-0.048037849366664886,
-0.006998899392783642,
0.01105895359069109,
0.15654997527599335,
0.060087691992521286,
-0.019355710595846176,
0.10336494445800781,
-0.02704661712050438,
0.06511847674846649,
-0.019257891923189163,
0.14796631038188934,
0.1643097847700119,
-0.03278791159391403,
0.0679631233215332,
0.07353734970092773,
-0.09712175279855728,
-0.157537043094635,
0.08964747190475464,
-0.013680758886039257,
0.08074511587619781,
-0.04883340746164322,
0.1447005718946457,
0.10833431780338287,
-0.18122287094593048,
0.03703174740076065,
-0.06254702061414719,
-0.11028306186199188,
-0.11565123498439789,
-0.057130616158246994,
-0.09276083111763,
-0.10129964351654053,
0.026318499818444252,
-0.1154937744140625,
0.011945880018174648,
0.07300899922847748,
-0.003392888233065605,
0.008252543397247791,
0.16779039800167084,
-0.06448371708393097,
0.04145350679755211,
0.04725395143032074,
0.006415732204914093,
-0.008292329497635365,
-0.07768579572439194,
-0.04535632207989693,
0.03542697802186012,
0.017487624660134315,
0.06186183542013168,
-0.04084339365363121,
0.03466416522860527,
0.014266174286603928,
-0.0030849725008010864,
-0.06848397105932236,
0.017529236152768135,
0.014051511883735657,
0.038634877651929855,
0.04449935257434845,
0.05093813315033913,
-0.010415446013212204,
-0.025126149877905846,
0.26038119196891785,
-0.07334066927433014,
-0.05885649099946022,
-0.132529154419899,
0.15039585530757904,
0.0410178117454052,
-0.00268881069496274,
0.06117068603634834,
-0.12677352130413055,
0.006319175008684397,
0.14905770123004913,
0.13518746197223663,
-0.019961362704634666,
-0.009175158105790615,
-0.024657119065523148,
-0.010298146866261959,
-0.03575543314218521,
0.07289818674325943,
0.07838299125432968,
-0.008995183743536472,
-0.05481142923235893,
-0.004317705053836107,
0.005656068213284016,
-0.03912822902202606,
-0.08474694937467575,
0.07770940661430359,
-0.027704371139407158,
0.027895720675587654,
-0.03765803575515747,
0.08749493211507797,
0.015141664072871208,
-0.15709862112998962,
0.04835071787238121,
-0.1802673190832138,
-0.1762368530035019,
-0.008295045234262943,
0.07689858227968216,
-0.029687458649277687,
0.02963576279580593,
-0.009467653930187225,
-0.012141319923102856,
0.11663474142551422,
-0.006226364988833666,
-0.0618770457804203,
-0.09837980568408966,
0.0622466579079628,
-0.034295905381441116,
0.26652559638023376,
-0.0019331930670887232,
0.06127326563000679,
0.09655146300792694,
-0.01443750225007534,
-0.1576349288225174,
0.04127565398812294,
0.07329106330871582,
-0.040076784789562225,
0.03047352097928524,
0.15280543267726898,
-0.06183571368455887,
0.13848663866519928,
0.04138028249144554,
-0.10540232062339783,
-0.022498061880469322,
0.008785426616668701,
-0.02314239740371704,
-0.0903642326593399,
0.022604413330554962,
-0.05660371482372284,
0.16978472471237183,
0.16014957427978516,
-0.03894571214914322,
0.007818725891411304,
-0.058702632784843445,
0.0672730803489685,
0.05033092945814133,
0.06600558012723923,
0.0034543550573289394,
-0.1941559910774231,
0.0142142279073596,
0.029332730919122696,
0.03801153227686882,
-0.23978711664676666,
-0.11711785942316055,
0.04371627792716026,
-0.04727911949157715,
-0.0625816285610199,
0.11598893254995346,
0.09056444466114044,
0.02595508098602295,
-0.03405404090881348,
-0.16324909031391144,
-0.025585463270545006,
0.1293656975030899,
-0.16185453534126282,
-0.051118332892656326
] |
null | null | transformers | 
Thanks to @Kooten the man the myth the legend we have exl2 quants: https://huggingface.co/models?search=Kooten/Pasta-Lake-7b-exl2
Thanks to @bartowski the homie for the additional exl2 quants, please show him some support aswell: https://huggingface.co/bartowski/Pasta-Lake-7b-exl2/tree/main
Thanks also to @konz00 for the gguf quants: https://huggingface.co/konz00/Pasta-Lake-7b-GGUF
added ST preset files
### Models Merged
The following models were included in the merge:
* [Test157t/Pasta-PrimaMaid-7b](https://huggingface.co/Test157t/Pasta-PrimaMaid-7b)
* [macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: Test157t/Pasta-PrimaMaid-7b
layer_range: [0, 32]
- model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Pasta-PrimaMaid-7b
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: float16
```
| {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Test157t/Pasta-PrimaMaid-7b", "macadeliccc/WestLake-7B-v2-laser-truthy-dpo"]} | text-generation | Test157t/Pasta-Lake-7b | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"base_model:Test157t/Pasta-PrimaMaid-7b",
"base_model:macadeliccc/WestLake-7B-v2-laser-truthy-dpo",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T01:09:59+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #base_model-Test157t/Pasta-PrimaMaid-7b #base_model-macadeliccc/WestLake-7B-v2-laser-truthy-dpo #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| !image/png
Thanks to @Kooten the man the myth the legend we have exl2 quants: URL
Thanks to @bartowski the homie for the additional exl2 quants, please show him some support aswell: URL
Thanks also to @konz00 for the gguf quants: URL
added ST preset files
### Models Merged
The following models were included in the merge:
* Test157t/Pasta-PrimaMaid-7b
* macadeliccc/WestLake-7B-v2-laser-truthy-dpo
### Configuration
The following YAML configuration was used to produce this model:
!image/png
| [
"### Models Merged\n\nThe following models were included in the merge:\n* Test157t/Pasta-PrimaMaid-7b\n* macadeliccc/WestLake-7B-v2-laser-truthy-dpo",
"### Configuration\n\nThe following YAML configuration was used to produce this model:\n\n\n\n!image/png"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #mergekit #merge #base_model-Test157t/Pasta-PrimaMaid-7b #base_model-macadeliccc/WestLake-7B-v2-laser-truthy-dpo #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Models Merged\n\nThe following models were included in the merge:\n* Test157t/Pasta-PrimaMaid-7b\n* macadeliccc/WestLake-7B-v2-laser-truthy-dpo",
"### Configuration\n\nThe following YAML configuration was used to produce this model:\n\n\n\n!image/png"
] | [
98,
51,
21
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #mergekit #merge #base_model-Test157t/Pasta-PrimaMaid-7b #base_model-macadeliccc/WestLake-7B-v2-laser-truthy-dpo #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Models Merged\n\nThe following models were included in the merge:\n* Test157t/Pasta-PrimaMaid-7b\n* macadeliccc/WestLake-7B-v2-laser-truthy-dpo### Configuration\n\nThe following YAML configuration was used to produce this model:\n\n\n\n!image/png"
] | [
-0.11639684438705444,
-0.10186896473169327,
-0.002325835172086954,
-0.006495174486190081,
0.08726323395967484,
0.07058706134557724,
0.1921258419752121,
0.03635147958993912,
0.012113749980926514,
-0.0003558176686055958,
0.03850661963224411,
0.07197330892086029,
0.05035889893770218,
0.13808271288871765,
-0.029597260057926178,
-0.14367835223674774,
0.044835127890110016,
0.04209019988775253,
-0.19470950961112976,
0.10971236974000931,
0.0987018495798111,
-0.06913415342569351,
0.1090826541185379,
0.04150533303618431,
-0.18672405183315277,
0.05182621255517006,
-0.037542618811130524,
-0.001376010593958199,
0.08289783447980881,
0.07599970698356628,
0.09838669747114182,
0.08216842263936996,
-0.017859654501080513,
-0.10901766270399094,
0.04531385004520416,
0.007120436988770962,
0.004022896755486727,
0.04372801631689072,
0.10235418379306793,
0.0386933833360672,
0.07296007126569748,
-0.04339834302663803,
-0.009374753572046757,
0.03375064209103584,
-0.0929461121559143,
-0.060507770627737045,
-0.08879993855953217,
0.1259327083826065,
0.11112180352210999,
0.006169155240058899,
-0.0068107773549854755,
0.04895615950226784,
0.03212380036711693,
0.05039719492197037,
0.09736539423465729,
-0.24737484753131866,
-0.008292474783957005,
0.1374201476573944,
0.11540082097053528,
-0.07951952517032623,
0.05747060850262642,
0.03275525942444801,
0.04634738713502884,
-0.03776078298687935,
-0.022947244346141815,
-0.06646601110696793,
0.24855968356132507,
-0.04838079214096069,
-0.12151265144348145,
-0.025443118065595627,
0.2071259766817093,
-0.019143734127283096,
-0.02846841886639595,
-0.05807080492377281,
-0.11127274483442307,
0.04420353099703789,
-0.016896909102797508,
-0.017918352037668228,
-0.025178296491503716,
-0.0001847197418101132,
0.01783117651939392,
-0.052792102098464966,
-0.059084292501211166,
-0.08548051118850708,
-0.09647580236196518,
0.18829818069934845,
0.04752866551280022,
0.03466630354523659,
-0.09469077736139297,
0.12686102092266083,
-0.15253031253814697,
-0.13355028629302979,
0.023672660812735558,
-0.08916029334068298,
-0.024325381964445114,
-0.019854236394166946,
-0.09018895775079727,
-0.10959554463624954,
0.10844867676496506,
0.13087071478366852,
-0.03991382569074631,
0.0016403475310653448,
0.10537267476320267,
0.052017852663993835,
-0.00008870566671248525,
0.062131207436323166,
-0.15182024240493774,
-0.10101016610860825,
0.006969717796891928,
0.03688796982169151,
0.06456674635410309,
0.03790232166647911,
-0.08073021471500397,
-0.09093289822340012,
0.013951895758509636,
-0.0006764681893400848,
0.0579000748693943,
0.10064292699098587,
-0.02553153969347477,
-0.08304788917303085,
0.22269287705421448,
-0.0584072470664978,
-0.0017558742547407746,
0.004774017259478569,
0.0029359497129917145,
0.03210476040840149,
0.08296557515859604,
0.032090138643980026,
0.032143376767635345,
0.06851188838481903,
-0.04130829870700836,
-0.010272108018398285,
-0.08844690024852753,
-0.0700734332203865,
-0.0026679332368075848,
-0.006699227727949619,
0.0033651345875114202,
-0.07068177312612534,
-0.2734229862689972,
0.0038546810392290354,
0.019261743873357773,
-0.01284574531018734,
0.017693130299448967,
0.029492173343896866,
0.03832843527197838,
-0.02058313600718975,
0.012646928429603577,
0.022352231666445732,
0.012006334029138088,
0.016909284517169,
0.05458499863743782,
0.05861609801650047,
-0.11518348008394241,
0.0404130294919014,
-0.07948978990316391,
0.146921768784523,
-0.19359341263771057,
0.07606708258390427,
0.030657542869448662,
0.07874797284603119,
-0.051090043038129807,
-0.029957959428429604,
-0.01959468610584736,
0.02649705857038498,
0.07970713824033737,
0.15865586698055267,
-0.13718511164188385,
-0.07147204875946045,
0.07515537738800049,
-0.15692606568336487,
-0.15195927023887634,
0.038693252950906754,
0.009493744932115078,
0.05511820316314697,
0.047601599246263504,
0.17081250250339508,
0.12719623744487762,
-0.06100669503211975,
-0.014556407928466797,
-0.07080838084220886,
-0.012933917343616486,
-0.06734149903059006,
0.088727205991745,
-0.01734219864010811,
-0.2028988152742386,
0.042462389916181564,
-0.0268098134547472,
0.08085940778255463,
-0.07130035758018494,
-0.047289058566093445,
-0.10154025256633759,
-0.06910041719675064,
0.12670497596263885,
-0.0238005630671978,
-0.01608237996697426,
-0.06540069729089737,
-0.005354320164769888,
0.11606120318174362,
0.1098523661494255,
-0.0842929407954216,
-0.02333756536245346,
-0.012634271755814552,
0.13168808817863464,
-0.16366226971149445,
0.045781269669532776,
-0.06259168684482574,
-0.022884104400873184,
-0.02216341346502304,
0.01552050281316042,
0.0016381299355998635,
0.011657790280878544,
0.0956665426492691,
0.03908783942461014,
-0.05256393179297447,
-0.06422634422779083,
0.0601070374250412,
0.04687746986746788,
-0.007121647708117962,
-0.13458222150802612,
-0.06696570664644241,
-0.05370621383190155,
0.20731262862682343,
-0.06002584844827652,
0.06205739453434944,
-0.05806417390704155,
0.17222049832344055,
-0.016508115455508232,
0.05247671902179718,
0.06520390510559082,
0.031467415392398834,
0.009918780997395515,
0.002679952420294285,
0.059610117226839066,
0.02403838187456131,
-0.11106820404529572,
0.10194913297891617,
-0.1493176966905594,
0.04790761321783066,
0.10241315513849258,
-0.035318728536367416,
-0.0036390069872140884,
-0.12460966408252716,
-0.031183702871203423,
-0.0467790886759758,
0.062127403914928436,
-0.09854938834905624,
-0.011524506844580173,
-0.01949690468609333,
0.10895761847496033,
-0.05645013228058815,
-0.002810204401612282,
-0.0018513306276872754,
-0.06141500547528267,
-0.041714441031217575,
0.0737033560872078,
-0.006719214376062155,
-0.12499049305915833,
0.08935338258743286,
0.25731605291366577,
0.027881285175681114,
0.13314437866210938,
-0.012327621690928936,
-0.03336930274963379,
-0.06379956752061844,
-0.018695522099733353,
-0.0011079329997301102,
0.05467762053012848,
-0.079360730946064,
0.07162170112133026,
0.07702476531267166,
-0.04477990046143532,
0.08035688102245331,
-0.11426319181919098,
0.0037293198984116316,
0.056986384093761444,
-0.000042476924136281013,
0.05518536642193794,
0.10667665302753448,
0.01461885031312704,
0.05031228065490723,
-0.020189868286252022,
0.011529091745615005,
0.038659922778606415,
0.022373734042048454,
-0.08167973905801773,
0.16029144823551178,
-0.09851028025150299,
-0.19738538563251495,
-0.17561817169189453,
-0.05092989653348923,
-0.12126465141773224,
0.020350702106952667,
0.04321545735001564,
-0.04281653091311455,
-0.04943447932600975,
-0.04881363362073898,
0.145713672041893,
0.04297695681452751,
0.03543483465909958,
-0.008709094487130642,
0.003181618172675371,
0.05456763505935669,
-0.05572867393493652,
-0.021532710641622543,
0.016751836985349655,
-0.012463090009987354,
0.07350736111402512,
-0.05049550160765648,
0.11356726288795471,
0.1271810233592987,
-0.02689012698829174,
0.005066750571131706,
0.015352640300989151,
0.19403082132339478,
-0.05229983478784561,
0.06501327455043793,
0.21269266307353973,
-0.06536681950092316,
0.04971768334507942,
0.22481600940227509,
0.022553708404302597,
-0.005198766943067312,
0.0061072236858308315,
-0.07999874651432037,
-0.07417469471693039,
-0.1747739315032959,
-0.126810684800148,
-0.06102082505822182,
-0.01965055800974369,
0.02443670853972435,
0.019816379994153976,
0.058726973831653595,
0.09873705357313156,
-0.07678156346082687,
0.010477387346327305,
-0.012127813883125782,
0.04010207951068878,
0.20911337435245514,
0.001406497904099524,
0.0809260681271553,
-0.08018411695957184,
-0.07165920734405518,
0.034863896667957306,
0.06845248490571976,
0.11967825144529343,
0.06994151324033737,
0.0554083026945591,
0.1032601073384285,
0.016481952741742134,
0.09317188709974289,
0.11700745671987534,
-0.017604326829314232,
-0.023823687806725502,
-0.0015274606412276626,
-0.11931032687425613,
0.048453137278556824,
0.021733742207288742,
-0.10528811067342758,
0.05388401448726654,
-0.07063484191894531,
-0.04066848382353783,
0.05791030824184418,
0.07004359364509583,
0.10951279103755951,
-0.2677049934864044,
-0.05070239678025246,
0.030406830832362175,
0.0781712755560875,
-0.03460809215903282,
-0.08122347295284271,
-0.020239097997546196,
-0.011642755009233952,
0.1691904366016388,
-0.010864163748919964,
0.09701951593160629,
0.015595712698996067,
0.022138142958283424,
0.01629774086177349,
0.11409667134284973,
-0.00946812890470028,
0.045579809695482254,
-0.18428416550159454,
0.1818295568227768,
0.045351818203926086,
-0.026133878156542778,
-0.000428635161370039,
0.017022131010890007,
0.01861475221812725,
0.2182016521692276,
0.0042741321958601475,
-0.001010161591693759,
0.03941841423511505,
-0.026684805750846863,
-0.10215581953525543,
-0.00039378824294544756,
-0.022905932739377022,
-0.01466204971075058,
0.09922367334365845,
-0.028332004323601723,
-0.035580214112997055,
0.0007218783721327782,
0.10273436456918716,
-0.17986994981765747,
-0.08967171609401703,
0.07962172478437424,
0.026704823598265648,
0.03559580445289612,
-0.07919824868440628,
-0.029769450426101685,
-0.13272669911384583,
0.17817075550556183,
0.08155803382396698,
-0.10240752249956131,
-0.09258723258972168,
-0.06695394963026047,
0.15754246711730957,
-0.0651802346110344,
0.06622173637151718,
-0.032652128487825394,
0.05165936425328255,
-0.05353056639432907,
-0.18223616480827332,
0.06588473916053772,
-0.08565852791070938,
-0.06571957468986511,
-0.007795506156980991,
0.11972291022539139,
-0.06866517663002014,
0.016657916828989983,
0.018810175359249115,
0.027128376066684723,
-0.10852807015180588,
-0.04126532003283501,
0.011610481888055801,
0.1719287633895874,
-0.007302622776478529,
0.06478128582239151,
-0.02144855447113514,
-0.0872870460152626,
0.01618186943233013,
-0.008738416247069836,
0.09861883521080017,
0.18767386674880981,
-0.03305109962821007,
0.002997098956257105,
0.09748523682355881,
-0.05538041144609451,
-0.19623510539531708,
-0.03877299278974533,
-0.03718515485525131,
0.057325124740600586,
-0.036451663821935654,
-0.008751479908823967,
0.053145624697208405,
0.10585556924343109,
-0.002313641831278801,
0.0650515928864479,
-0.2537569999694824,
-0.16182726621627808,
0.059050459414720535,
0.07177487015724182,
0.18632692098617554,
-0.14343446493148804,
-0.07738108187913895,
-0.10252408683300018,
-0.18794751167297363,
0.0072166272439062595,
-0.16032695770263672,
0.0719246193766594,
-0.07105781883001328,
0.02756069228053093,
0.01720195636153221,
-0.0623769611120224,
0.16805198788642883,
-0.037673406302928925,
0.03757866099476814,
-0.08472815155982971,
0.03327189385890961,
0.11856652051210403,
-0.04962166026234627,
0.08692029118537903,
-0.08062931895256042,
0.053592029958963394,
-0.03016374073922634,
-0.05314118042588234,
-0.02928556315600872,
0.04265351966023445,
-0.043110884726047516,
-0.04358105733990669,
-0.053619567304849625,
-0.0004246975586283952,
-0.08072775602340698,
-0.03979305177927017,
-0.018184412270784378,
-0.04595109447836876,
0.06025126948952675,
0.18083418905735016,
0.06641946732997894,
-0.032278966158628464,
-0.021575434133410454,
0.03766284137964249,
-0.05407014116644859,
0.0673784539103508,
-0.08446221053600311,
0.00386089738458395,
0.10775775462388992,
-0.007961003109812737,
0.07657334953546524,
0.01429695077240467,
-0.02439727634191513,
-0.023441407829523087,
0.1052253469824791,
-0.19471831619739532,
-0.21308250725269318,
-0.07946769148111343,
0.02058991603553295,
-0.04730973392724991,
0.10254465043544769,
0.13642822206020355,
-0.029713278636336327,
-0.017794672399759293,
0.007265862543135881,
-0.045757170766592026,
-0.11101219803094864,
0.1666143834590912,
0.03712989762425423,
0.04056446999311447,
-0.09548580646514893,
0.010629258118569851,
-0.0029937720391899347,
-0.06096596643328667,
-0.06550142914056778,
0.013704012148082256,
-0.08813774585723877,
-0.07975973933935165,
-0.020926741883158684,
0.2122156023979187,
-0.10132111608982086,
-0.0819871723651886,
-0.13593994081020355,
-0.12563014030456543,
0.02806038036942482,
0.055586278438568115,
0.08168024569749832,
0.008891613222658634,
0.04108993336558342,
-0.0832790657877922,
-0.039346784353256226,
0.08153931051492691,
0.055323485285043716,
0.10799025744199753,
-0.13343998789787292,
0.044725820422172546,
-0.05062985420227051,
0.07593332976102829,
-0.05271968990564346,
0.016655294224619865,
-0.09091043472290039,
-0.014454922638833523,
-0.18436531722545624,
-0.04341720789670944,
-0.12046939879655838,
-0.037228427827358246,
-0.016755690798163414,
-0.017141524702310562,
-0.010721217840909958,
0.011790881864726543,
-0.027447832748293877,
-0.029015028849244118,
-0.027484837919473648,
0.009454576298594475,
-0.042638249695301056,
-0.02384292148053646,
0.0363842137157917,
-0.06237972527742386,
0.030724242329597473,
0.014072072692215443,
-0.056154340505599976,
-0.05144130438566208,
-0.08648261427879333,
-0.06762203574180603,
0.019840693101286888,
-0.010927018709480762,
0.03105456754565239,
-0.11982318758964539,
0.006541520357131958,
0.05374547839164734,
-0.05805223435163498,
-0.031435348093509674,
0.06705985963344574,
-0.059266597032547,
0.0020100753754377365,
-0.039740558713674545,
-0.031883466988801956,
-0.012942147441208363,
-0.02079629898071289,
0.08110084384679794,
0.10117087513208389,
0.09232473373413086,
-0.052816908806562424,
0.027170926332473755,
-0.1877116858959198,
-0.02528640441596508,
-0.01687011681497097,
-0.10941645503044128,
0.02291356585919857,
-0.09110051393508911,
-0.0020601963624358177,
0.020719578489661217,
0.18643847107887268,
-0.031426433473825455,
-0.04931328445672989,
-0.010249595157802105,
0.06976395100355148,
0.0974876880645752,
0.06067053973674774,
0.32960110902786255,
-0.006593691650778055,
0.050525423139333725,
-0.08521458506584167,
0.09277456998825073,
0.023954275995492935,
0.07705079764127731,
0.0314105749130249,
0.09097038954496384,
-0.06154586374759674,
0.029973508790135384,
0.1010134294629097,
0.035739827901124954,
-0.0012838668189942837,
-0.15415209531784058,
-0.020236071199178696,
0.031248189508914948,
-0.010944118723273277,
0.1468861699104309,
0.1510508954524994,
-0.14591440558433533,
0.034447863698005676,
0.03968542814254761,
-0.03325602784752846,
-0.05719057098031044,
-0.05187643691897392,
-0.1294952780008316,
-0.17455632984638214,
-0.02694561518728733,
-0.05374853312969208,
-0.06317999958992004,
0.03736768662929535,
-0.006342919077724218,
-0.028962548822164536,
0.19160079956054688,
0.10165457427501678,
-0.02102293260395527,
0.0050643859431147575,
-0.015405585989356041,
-0.01204835157841444,
0.011888773180544376,
-0.02918822504580021,
0.04747041314840317,
-0.043322429060935974,
-0.02911985293030739,
0.019060874357819557,
-0.00200672447681427,
0.04775865375995636,
-0.015917927026748657,
-0.08685921877622604,
-0.006815427914261818,
0.03837893158197403,
0.07433433830738068,
-0.03041239269077778,
-0.003980943001806736,
-0.009331751614809036,
-0.01478786114603281,
0.011818710714578629,
-0.0054327077232301235,
-0.13710203766822815,
-0.06347811967134476,
0.06736153364181519,
-0.05832621455192566,
0.025480931624770164,
0.054240502417087555,
-0.06075289100408554,
0.044878024607896805,
0.15711823105812073,
0.32927680015563965,
-0.008936668746173382,
0.008824209682643414,
-0.03590102866292,
0.018051449209451675,
0.035451337695121765,
0.0897226631641388,
0.0017228388460353017,
0.07494375109672546,
-0.04543039947748184,
0.03658023849129677,
-0.08085741847753525,
-0.06739649921655655,
-0.05076783150434494,
-0.010941398330032825,
0.04116298630833626,
-0.07573651522397995,
0.05915319174528122,
0.12312298268079758,
-0.0020209511276334524,
0.06622941046953201,
0.037645094096660614,
-0.09501731395721436,
-0.08246743679046631,
-0.06917525082826614,
0.14155393838882446,
-0.03476257622241974,
0.032779064029455185,
-0.0959579274058342,
0.01800774782896042,
0.11346407979726791,
-0.019194986671209335,
-0.08951574563980103,
-0.0869644284248352,
0.05247991904616356,
0.014419583603739738,
-0.05837099254131317,
-0.0023617330007255077,
0.07195638865232468,
0.09962692856788635,
0.004369995556771755,
-0.11737669259309769,
0.029882650822401047,
0.012849973514676094,
-0.03845038264989853,
0.05670316889882088,
0.00356733868829906,
-0.021553613245487213,
-0.07924829423427582,
0.01493833214044571,
-0.1257159560918808,
0.02694949135184288,
-0.02337116189301014,
-0.015474101528525352,
-0.09254536032676697,
0.08510228246450424,
-0.03658071905374527,
0.12884460389614105,
0.1123005673289299,
-0.04342590272426605,
0.04135098308324814,
-0.029820464551448822,
0.06511261314153671,
0.07496834546327591,
0.09034783393144608,
0.0036853321362286806,
-0.16237400472164154,
0.00006093239790061489,
0.06627389043569565,
0.029577646404504776,
-0.2463330328464508,
-0.08196164667606354,
-0.11937268078327179,
-0.050099730491638184,
-0.053747132420539856,
0.12968967854976654,
0.19151291251182556,
0.029297593981027603,
-0.008760935626924038,
-0.07368955761194229,
-0.04681076854467392,
0.07997919619083405,
-0.10550852119922638,
-0.092926986515522
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-cased-bn-adapter-895K-squad-model2
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-base-cased-bn-adapter-895K-squad-model2", "results": []}]} | null | varun-v-rao/bert-base-cased-bn-adapter-895K-squad-model2 | [
"tensorboard",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:bert-base-cased",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:12:08+00:00 | [] | [] | TAGS
#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-bert-base-cased #license-apache-2.0 #region-us
|
# bert-base-cased-bn-adapter-895K-squad-model2
This model is a fine-tuned version of bert-base-cased on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# bert-base-cased-bn-adapter-895K-squad-model2\n\nThis model is a fine-tuned version of bert-base-cased on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 48\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-bert-base-cased #license-apache-2.0 #region-us \n",
"# bert-base-cased-bn-adapter-895K-squad-model2\n\nThis model is a fine-tuned version of bert-base-cased on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 48\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
49,
45,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-bert-base-cased #license-apache-2.0 #region-us \n# bert-base-cased-bn-adapter-895K-squad-model2\n\nThis model is a fine-tuned version of bert-base-cased on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 48\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.08927477896213531,
0.03431662917137146,
-0.0006775152287445962,
0.07202958315610886,
0.17155243456363678,
0.013333809562027454,
0.13183347880840302,
0.09371402859687805,
-0.1194213479757309,
0.034045569598674774,
0.048588696867227554,
0.04258317872881889,
0.03724890574812889,
0.09075517952442169,
-0.01745746284723282,
-0.23771065473556519,
-0.0018891858635470271,
0.03504447266459465,
-0.11850535124540329,
0.08902372419834137,
0.11121739447116852,
-0.12168131023645401,
0.06472531706094742,
0.025667017325758934,
-0.2217511236667633,
0.05577120557427406,
-0.01055477187037468,
-0.03692782670259476,
0.10503626614809036,
0.023157306015491486,
0.13990367949008942,
-0.0080793472006917,
0.14725904166698456,
-0.16372297704219818,
0.007650574203580618,
0.09256387501955032,
0.035234641283750534,
0.08951587975025177,
0.01892371103167534,
0.044356681406497955,
0.07833529263734818,
-0.08435559272766113,
0.08725420385599136,
0.03387552872300148,
-0.07482081651687622,
-0.20244671404361725,
-0.07473955303430557,
0.039085499942302704,
0.10407603532075882,
0.07152516394853592,
-0.004902946762740612,
0.13238784670829773,
-0.059916749596595764,
0.06061309203505516,
0.19739751517772675,
-0.29147660732269287,
-0.09115881472826004,
0.0928725153207779,
0.056428149342536926,
0.07924453914165497,
-0.09805731475353241,
-0.013067356310784817,
0.06302721798419952,
0.048529766499996185,
0.10384673625230789,
-0.01413374487310648,
-0.11136592924594879,
0.009963266551494598,
-0.14457182586193085,
0.03234801068902016,
0.14691826701164246,
0.037709929049015045,
-0.06153438240289688,
-0.019475208595395088,
-0.05750582367181778,
-0.06867410987615585,
-0.055845022201538086,
-0.0479661263525486,
0.0663008987903595,
-0.03415520861744881,
-0.09072405099868774,
-0.08255825936794281,
-0.08460383862257004,
-0.09725534915924072,
-0.021642858162522316,
0.13053776323795319,
0.0372784323990345,
0.023712461814284325,
-0.0638301819562912,
0.10228431969881058,
-0.07247377187013626,
-0.11168540269136429,
0.0105548445135355,
0.013492804951965809,
-0.050469961017370224,
-0.0663457065820694,
-0.06969853490591049,
-0.05795465409755707,
0.007208665832877159,
0.13472816348075867,
-0.04978816956281662,
0.06402044743299484,
-0.022273734211921692,
0.021701358258724213,
-0.050016969442367554,
0.1564127653837204,
-0.061966706067323685,
-0.022288570180535316,
0.021264009177684784,
0.07891252636909485,
0.013054377399384975,
0.00577541533857584,
-0.11609920114278793,
0.015372669324278831,
0.06228010728955269,
0.011310701258480549,
-0.08258026093244553,
0.029687194153666496,
-0.023712215945124626,
-0.02790551632642746,
-0.004094075411558151,
-0.09924493730068207,
0.029701299965381622,
-0.017664866521954536,
-0.08947985619306564,
-0.032149966806173325,
0.022101877257227898,
0.015356221236288548,
0.006055859848856926,
0.08964858204126358,
-0.10508152097463608,
0.012499905191361904,
-0.128723606467247,
-0.10935948044061661,
0.006522737443447113,
-0.08793963491916656,
0.002026038011536002,
-0.06810227781534195,
-0.17587101459503174,
-0.006014819256961346,
0.0545838288962841,
-0.057783354073762894,
-0.031057083979249,
-0.029656626284122467,
-0.07397399097681046,
0.0022108403500169516,
-0.0114200534299016,
0.17477425932884216,
-0.04114449769258499,
0.058592457324266434,
0.037994012236595154,
0.032363615930080414,
-0.07606267929077148,
0.043274782598018646,
-0.06754942983388901,
0.02500844933092594,
-0.20860114693641663,
0.042622558772563934,
-0.10372962802648544,
0.041261740028858185,
-0.11129560321569443,
-0.07983291894197464,
0.009295257739722729,
0.003218358149752021,
0.1053449958562851,
0.07576598972082138,
-0.19115468859672546,
-0.04339860379695892,
0.10822529345750809,
-0.07369182258844376,
-0.09665772318840027,
0.08221302181482315,
-0.056040648370981216,
0.07537247985601425,
0.06669404357671738,
0.14817383885383606,
0.04602130129933357,
-0.1336485892534256,
-0.001348312245681882,
0.02396969310939312,
0.10959993302822113,
-0.03446056693792343,
0.04759354889392853,
-0.006956894416362047,
-0.006167617626488209,
0.022751064971089363,
-0.07074164599180222,
-0.006547231692820787,
-0.09325388073921204,
-0.06769027560949326,
-0.0502622127532959,
-0.10104329138994217,
0.010337003506720066,
0.034881841391325,
0.055233437567949295,
-0.07686435431241989,
-0.10261191427707672,
0.21622557938098907,
0.11858855187892914,
-0.05164124071598053,
0.025725921615958214,
-0.09414901584386826,
0.07130060344934464,
-0.07473675161600113,
-0.018094712868332863,
-0.20387259125709534,
-0.11016443371772766,
0.020003965124487877,
-0.02545391209423542,
0.06032578647136688,
0.03884643316268921,
0.05816154554486275,
0.06901677697896957,
-0.06166082248091698,
0.02257295697927475,
-0.09476204216480255,
-0.007917176000773907,
-0.13017596304416656,
-0.21160660684108734,
-0.07290294766426086,
-0.02480820007622242,
0.15763995051383972,
-0.2213720679283142,
0.031450800597667694,
-0.016722848638892174,
0.12037528306245804,
0.027209678664803505,
-0.03477172926068306,
-0.05403335019946098,
0.07209203392267227,
-0.0051043229177594185,
-0.07147631794214249,
0.050922781229019165,
0.01951046660542488,
-0.07464972883462906,
-0.09553202986717224,
-0.10502959787845612,
0.06308821588754654,
0.1039142832159996,
-0.027387848123908043,
-0.07140723615884781,
0.002271779580041766,
-0.055630046874284744,
-0.026699306443333626,
-0.06572070717811584,
-0.02107211947441101,
0.17102478444576263,
-0.00033330940641462803,
0.14338131248950958,
-0.0837084949016571,
-0.05749668926000595,
0.007534783333539963,
-0.006585804279893637,
0.033485498279333115,
0.05852920934557915,
0.10582184046506882,
-0.061974477022886276,
0.0910608321428299,
0.11747600883245468,
-0.11062166839838028,
0.13325701653957367,
-0.050682924687862396,
-0.07355687022209167,
-0.01673491857945919,
-0.027623716741800308,
-0.017190242186188698,
0.17103448510169983,
-0.1494956761598587,
-0.006284683011472225,
0.012989280745387077,
0.012120958417654037,
0.046040039509534836,
-0.2007782757282257,
0.00727046187967062,
0.011831816285848618,
-0.03129838407039642,
-0.029371460899710655,
-0.04021688923239708,
0.004358507227152586,
0.09513521939516068,
0.02680686116218567,
-0.03430909290909767,
0.013940983451902866,
-0.0016553245950490236,
-0.0664641335606575,
0.20348602533340454,
-0.11388060450553894,
-0.06194485351443291,
-0.12791267037391663,
-0.01651587150990963,
-0.07352036982774734,
-0.015484536997973919,
0.013339617289602757,
-0.10330071300268173,
-0.04543321579694748,
-0.0786278247833252,
0.040621161460876465,
0.00348230660893023,
-0.0012730404268950224,
0.040074724704027176,
-0.0016146365087479353,
0.12336711585521698,
-0.15412074327468872,
0.018205413594841957,
-0.05482612922787666,
-0.12734222412109375,
-0.04033057019114494,
0.07170051336288452,
0.09635121375322342,
0.13617467880249023,
-0.033528365194797516,
0.004818917252123356,
-0.02619905024766922,
0.251667857170105,
-0.05559870973229408,
-0.010889616794884205,
0.11411382257938385,
-0.004394495394080877,
0.030991675332188606,
0.11834089457988739,
0.07673555612564087,
-0.10665756464004517,
0.025389382615685463,
0.10282852500677109,
-0.027450939640402794,
-0.23976492881774902,
-0.02084062434732914,
-0.02500997483730316,
-0.08527103811502457,
0.0624200813472271,
0.04099922254681587,
-0.02489454858005047,
0.07324814051389694,
0.021525466814637184,
0.09634087234735489,
-0.044272664934396744,
0.0795605406165123,
0.10904688388109207,
0.03373643010854721,
0.12874597311019897,
-0.03896366432309151,
-0.032049063593149185,
0.0548584945499897,
0.021758846938610077,
0.2538875341415405,
-0.0058036004193127155,
0.08026868104934692,
0.07538820803165436,
0.1380309760570526,
-0.026463953778147697,
0.04809822887182236,
-0.023585708811879158,
-0.029412081465125084,
-0.003398849396035075,
-0.062450800091028214,
0.007044833153486252,
0.0024039647541940212,
-0.08100023865699768,
0.07323896884918213,
-0.07148528844118118,
0.0008831367595121264,
0.031550340354442596,
0.27068132162094116,
0.027985813096165657,
-0.2835753262042999,
-0.09226785600185394,
0.012826083227992058,
-0.022948991507291794,
-0.058069340884685516,
0.01569802314043045,
0.12234745174646378,
-0.07400553673505783,
0.03340773284435272,
-0.06007613614201546,
0.1053055003285408,
0.01174606941640377,
0.014193423092365265,
0.09031754732131958,
0.17794647812843323,
-0.008841737173497677,
0.06047366186976433,
-0.2258061319589615,
0.22473782300949097,
0.03980156034231186,
0.12510736286640167,
-0.030109113082289696,
0.02778751216828823,
0.02194232866168022,
0.09371253103017807,
0.03895967826247215,
-0.016634656116366386,
-0.013420412316918373,
-0.19067654013633728,
-0.025313008576631546,
0.06157071515917778,
0.10480569303035736,
-0.02726333774626255,
0.09668036550283432,
-0.030052611604332924,
0.019845526665449142,
0.0693608969449997,
-0.03890474885702133,
-0.17811457812786102,
-0.08297326415777206,
-0.03689367324113846,
0.00819624774158001,
-0.06539659202098846,
-0.08482660353183746,
-0.101803719997406,
-0.04469024017453194,
0.12244269996881485,
0.006781508214771748,
-0.03199049085378647,
-0.11633278429508209,
0.12041622400283813,
0.09409067034721375,
-0.0405505932867527,
0.02602897770702839,
0.01179608702659607,
0.12891507148742676,
0.04043088108301163,
-0.08349775522947311,
0.08132084459066391,
-0.07597365975379944,
-0.14228904247283936,
-0.05293380096554756,
0.08600544929504395,
0.06563922762870789,
0.042525097727775574,
-0.0014182126615196466,
0.011589031666517258,
0.01624956727027893,
-0.08828461170196533,
-0.008429702371358871,
0.007776372600346804,
0.05730421468615532,
0.02593676559627056,
-0.10373611748218536,
0.022772371768951416,
-0.021269500255584717,
0.010888850316405296,
0.08947664499282837,
0.21153557300567627,
-0.07252275198698044,
0.007914364337921143,
0.11402130872011185,
-0.0977349728345871,
-0.18290060758590698,
0.13258929550647736,
0.1137157678604126,
0.013262837193906307,
0.04556897282600403,
-0.2219117432832718,
0.1847393959760666,
0.1254771500825882,
-0.03248829022049904,
0.07286131381988525,
-0.2679871618747711,
-0.1473628431558609,
0.10074014216661453,
0.15086320042610168,
0.056201785802841187,
-0.144596666097641,
-0.026084519922733307,
-0.0519157350063324,
-0.14437022805213928,
0.14219383895397186,
-0.19212405383586884,
0.08831975609064102,
0.015318538062274456,
0.09627962857484818,
0.006392647512257099,
-0.02464928850531578,
0.13109831511974335,
0.028197156265378,
0.10799317061901093,
-0.03471425920724869,
0.0342598631978035,
0.13100799918174744,
-0.04017488658428192,
0.01631450653076172,
-0.029304087162017822,
0.040260471403598785,
-0.11240613460540771,
-0.00875661801546812,
-0.06039733812212944,
0.046334363520145416,
-0.05461467429995537,
-0.06688612699508667,
-0.04710613563656807,
0.045543771237134933,
-0.003080022055655718,
-0.03327644243836403,
0.10060015320777893,
0.00808057002723217,
0.15018139779567719,
0.10228659957647324,
0.10560021549463272,
-0.06764635443687439,
-0.05767346918582916,
0.0453341007232666,
-0.021635353565216064,
0.08846741914749146,
-0.1637887805700302,
0.017880059778690338,
0.10994560271501541,
0.038703273981809616,
0.12038775533437729,
0.06146133318543434,
-0.06621602922677994,
0.023254191502928734,
0.057090822607278824,
-0.09296881407499313,
-0.1451006978750229,
0.006507073063403368,
-0.013467498123645782,
-0.14056944847106934,
0.07663172483444214,
0.1128605529665947,
-0.07095124572515488,
-0.008585377596318722,
0.003339405171573162,
-0.01242885459214449,
-0.07256877422332764,
0.19506366550922394,
0.07148604840040207,
0.05717308819293976,
-0.09129080176353455,
0.10511957854032516,
0.05403996631503105,
-0.03854404389858246,
0.025668801739811897,
0.041737549006938934,
-0.07328381389379501,
-0.004934059455990791,
0.06462100893259048,
0.2150340974330902,
-0.06290988624095917,
-0.053014762699604034,
-0.11405964940786362,
-0.10187094658613205,
0.02897421084344387,
0.1724570095539093,
0.07406371831893921,
-0.04007736220955849,
-0.04824575409293175,
0.07312577962875366,
-0.13000734150409698,
0.08921270817518234,
0.009868227876722813,
0.09004651755094528,
-0.11282645910978317,
0.10160661488771439,
0.01797269470989704,
0.02146831713616848,
-0.02786771021783352,
0.03205856680870056,
-0.1081354096531868,
-0.012912631966173649,
-0.20556597411632538,
-0.03574127331376076,
0.005221834406256676,
0.007700295653194189,
-0.0037980866618454456,
-0.04829340800642967,
-0.07470612227916718,
0.04572317749261856,
-0.09791506826877594,
-0.0338292196393013,
0.048817165195941925,
0.038596589118242264,
-0.13746438920497894,
0.020009106025099754,
0.014638980850577354,
-0.07424797862768173,
0.05799810215830803,
0.02892928570508957,
0.040567152202129364,
0.0747394785284996,
-0.12035783380270004,
-0.00657103955745697,
0.016644952818751335,
0.03263498842716217,
0.09106732159852982,
-0.04079778864979744,
-0.00861932709813118,
-0.027940036728978157,
0.09717535227537155,
0.0016586999408900738,
0.08857803046703339,
-0.11140245944261551,
-0.024962494149804115,
-0.053780749440193176,
-0.04306229203939438,
-0.04763822630047798,
0.03815965726971626,
0.09676235169172287,
0.07771186530590057,
0.1609809398651123,
-0.07529310137033463,
-0.01629062183201313,
-0.2037472128868103,
-0.02389724738895893,
-0.0032930346205830574,
-0.047733958810567856,
-0.08809271454811096,
-0.06075518950819969,
0.062014177441596985,
-0.07125096768140793,
0.12163659185171127,
0.014175142161548138,
0.10477014631032944,
0.04963202774524689,
-0.02123350463807583,
-0.01753264106810093,
0.014517644420266151,
0.2000644952058792,
0.056028030812740326,
0.0034898354206234217,
0.057403791695833206,
0.03328057751059532,
0.07741745561361313,
0.08226265758275986,
0.18274228274822235,
0.13098111748695374,
-0.051435649394989014,
0.07951711118221283,
0.10489798337221146,
-0.07122109085321426,
-0.12878376245498657,
0.13779772818088531,
-0.03192916139960289,
0.10987570136785507,
-0.06518477201461792,
0.2049950361251831,
0.09116416424512863,
-0.16131539642810822,
0.04016858711838722,
-0.07245408743619919,
-0.09713801741600037,
-0.12162089347839355,
-0.01218631211668253,
-0.06769830733537674,
-0.1667999029159546,
0.015949977561831474,
-0.13984885811805725,
0.00602082721889019,
0.14985692501068115,
0.004010355565696955,
0.0096811568364501,
0.17600221931934357,
-0.036989305168390274,
0.028678979724645615,
0.04720871150493622,
0.0013476009480655193,
-0.016623176634311676,
-0.08894593268632889,
-0.07067330926656723,
0.04585903882980347,
0.011379827745258808,
0.05227173492312431,
-0.06069304049015045,
-0.02551719732582569,
0.03227760270237923,
0.008076217025518417,
-0.06270688772201538,
0.02263546735048294,
0.02627568691968918,
0.04959350451827049,
0.0401448979973793,
0.012521603144705296,
0.004587163217365742,
-0.03785352781414986,
0.26958879828453064,
-0.08092182874679565,
-0.08085157722234726,
-0.13898734748363495,
0.2019989788532257,
0.007740241941064596,
-0.007366191130131483,
0.042829133570194244,
-0.11032861471176147,
-0.029624082148075104,
0.18252058327198029,
0.14769898355007172,
-0.09833478182554245,
-0.03328900784254074,
0.0026515175122767687,
-0.029323821887373924,
-0.10121513903141022,
0.15549106895923615,
0.10913918912410736,
0.019444813951849937,
-0.06259772181510925,
-0.04126071557402611,
-0.018931180238723755,
-0.02377201057970524,
-0.04899248853325844,
0.0509362630546093,
0.04032962769269943,
0.0024797411169856787,
-0.03679836168885231,
0.05843081325292587,
-0.003690887475386262,
-0.222010537981987,
0.03933699056506157,
-0.12946145236492157,
-0.17969779670238495,
-0.04149214178323746,
0.08025268465280533,
-0.024469567462801933,
0.05462389066815376,
-0.043677229434251785,
0.012961531057953835,
0.12640409171581268,
-0.04130152240395546,
-0.014984030276536942,
-0.15704426169395447,
0.13402682542800903,
-0.10424041002988815,
0.22557179629802704,
-0.027810348197817802,
0.06210644170641899,
0.11857784539461136,
0.019846085458993912,
-0.10168296843767166,
0.03569536656141281,
0.047577086836099625,
-0.10595794022083282,
-0.002555929124355316,
0.12736406922340393,
-0.05374336987733841,
0.09823202341794968,
0.0240675900131464,
-0.13581614196300507,
0.0038234498351812363,
-0.07443156838417053,
-0.05704240873456001,
-0.07912884652614594,
-0.020547952502965927,
-0.11037765443325043,
0.12836353480815887,
0.2055443376302719,
-0.024853145703673363,
0.0038185908924788237,
-0.08770937472581863,
0.04031128063797951,
0.06073121726512909,
0.0906778872013092,
-0.03789136931300163,
-0.23926804959774017,
0.026891537010669708,
0.07070274651050568,
-0.03346090763807297,
-0.27248990535736084,
-0.06281262636184692,
0.07069720327854156,
-0.03549550101161003,
-0.05083216726779938,
0.0880420133471489,
0.11310786753892899,
0.054451845586299896,
-0.05852194502949715,
-0.16719064116477966,
-0.07668755948543549,
0.14458082616329193,
-0.14229021966457367,
-0.06998371332883835
] |
null | null | transformers |
## MiquMaid v2
Check out our blogpost about this model series [Here!](https://ikaridevgit.github.io/index.html?blog=blogid-6&bo=true#Miqu-base) - Join our Discord server [Here!](https://discord.gg/Bb8pRUXy3Z)
<center>[<a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B">V2-70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B-DPO">V2-70B-DPO</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B">V2-2x70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B-DPO">V2-2x70B-DPO</a>]
</br>
<div style="width: 100%;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/1ziZ_5Rl7bsQKFrgH6ZCf.png" style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca **prompting format**
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: [FP16](https://huggingface.co/NeverSleep/MiquMaid-v2-70B) - [GGUF](https://huggingface.co/NeverSleep/MiquMaid-v2-70B-GGUF)
## Training data used:
- [Aesir datasets](https://huggingface.co/MinervaAI)
- [NoRobots](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt)
- [limarp](https://huggingface.co/datasets/lemonilia/LimaRP)
- [toxic-dpo-v0.1-sharegpt](https://huggingface.co/datasets/Undi95/toxic-dpo-v0.1-sharegpt)
- [ToxicQAFinal](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAFinal)
### Custom format:
```
### Instruction:
{system prompt}
### Input:
{input}
### Response:
{reply}
```
## Others
Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).
IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | text-generation | LoneStriker/MiquMaid-v2-70B-2.4bpw-h6-exl2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T01:12:22+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## MiquMaid v2
Check out our blogpost about this model series Here! - Join our Discord server Here!
<center>[<a href="URL - <a href="URL - <a href="URL - <a href="URL
</br>
<div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: FP16 - GGUF
## Training data used:
- Aesir datasets
- NoRobots
- limarp
- toxic-dpo-v0.1-sharegpt
- ToxicQAFinal
### Custom format:
## Others
Undi: If you want to support us, you can here.
IkariDev: Visit my retro/neocities style website please kek | [
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
75,
121,
11,
30,
40,
5,
32
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.## Credits:\n- Undi\n- IkariDev## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal### Custom format:## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
-0.09447834640741348,
0.17205014824867249,
-0.005602731369435787,
0.01779203675687313,
0.11820747703313828,
0.045264896005392075,
0.11447285860776901,
0.15961068868637085,
0.06829394400119781,
0.05906902998685837,
0.0005873226327821612,
0.11407624930143356,
0.07548845559358597,
0.22948826849460602,
-0.006628913804888725,
-0.14427904784679413,
0.046850357204675674,
-0.026289891451597214,
-0.02635573409497738,
0.09569915384054184,
0.07466454803943634,
-0.04618130251765251,
0.0709284171462059,
0.010442404076457024,
-0.10720876604318619,
-0.017348533496260643,
0.0019323929445818067,
-0.05718233436346054,
0.04780259355902672,
0.04367207735776901,
0.0479082316160202,
0.05087536945939064,
0.00845402292907238,
-0.22662657499313354,
0.047140758484601974,
0.07308577746152878,
-0.025127466768026352,
0.07861552387475967,
0.10886233299970627,
-0.04211974889039993,
0.02646409347653389,
-0.03574787452816963,
-0.02210289053618908,
0.09350186586380005,
-0.11214648932218552,
-0.12319593131542206,
-0.11320719122886658,
0.13006889820098877,
0.06314875930547714,
0.08198896050453186,
0.0033554788678884506,
0.1101357564330101,
-0.07631256431341171,
0.07790177315473557,
0.20335930585861206,
-0.16871041059494019,
-0.02322721853852272,
0.05624805763363838,
-0.015333202667534351,
-0.05565005913376808,
-0.09832000732421875,
0.011083890683948994,
0.010926350019872189,
-0.019533375278115273,
-0.0038207839243113995,
-0.041167840361595154,
0.004284780006855726,
-0.06099749729037285,
-0.059463758021593094,
-0.016264086589217186,
0.24300093948841095,
0.0361378937959671,
-0.07370094209909439,
-0.0026136080268770456,
-0.006493517197668552,
0.11463554203510284,
-0.05098545923829079,
0.030949248000979424,
0.005614427383989096,
-0.0010702924337238073,
-0.0032837465405464172,
-0.04595240205526352,
-0.10275456309318542,
-0.05733378976583481,
-0.014142698608338833,
0.14566513895988464,
0.017552156001329422,
0.00008401479135500267,
-0.004768410697579384,
0.051651932299137115,
-0.10471507161855698,
-0.12298901379108429,
-0.06133059412240982,
-0.10231878608465195,
-0.005009785760194063,
-0.042668018490076065,
-0.022182224318385124,
-0.06640303134918213,
0.12371482700109482,
0.1403876692056656,
-0.04801563546061516,
-0.0030525391921401024,
-0.025033647194504738,
0.00783479306846857,
0.005412905476987362,
-0.00017629309149924666,
-0.07161558419466019,
-0.023959118872880936,
0.07290422171354294,
0.025751972571015358,
0.004980665165930986,
0.010289043188095093,
-0.044097792357206345,
-0.07064660638570786,
-0.04732796177268028,
0.05287690833210945,
0.07054515182971954,
0.06856327503919601,
-0.07649759203195572,
-0.047711774706840515,
0.22618921101093292,
-0.10658138245344162,
0.029063958674669266,
0.05863291397690773,
-0.007088409271091223,
0.10424129664897919,
0.06771936267614365,
-0.0006956448778510094,
-0.06505299359560013,
0.016184480860829353,
-0.041465580463409424,
0.03125211223959923,
-0.08675958216190338,
-0.05394180864095688,
0.0855826810002327,
0.0812700167298317,
-0.03331775963306427,
-0.1366315633058548,
-0.10328203439712524,
-0.01740688644349575,
0.02815520204603672,
-0.023310357704758644,
0.0012498353607952595,
0.04892998933792114,
-0.05491432547569275,
0.01405452098697424,
0.01705477572977543,
0.00629244651645422,
-0.05887370929121971,
0.07736124843358994,
0.022486159577965736,
0.09428157657384872,
0.019443463534116745,
0.025946028530597687,
-0.035123471170663834,
0.002149750478565693,
-0.23019294440746307,
0.05012257769703865,
-0.10595361143350601,
0.0038321600295603275,
-0.0922209694981575,
0.0014835012843832374,
-0.027800843119621277,
-0.009975400753319263,
0.0055687217973172665,
0.20525269210338593,
-0.14585432410240173,
-0.05596565082669258,
0.304247111082077,
-0.15955102443695068,
-0.09778694808483124,
0.09222670644521713,
0.03642375022172928,
-0.07440096139907837,
0.06239297613501549,
0.08249494433403015,
0.1056317463517189,
-0.16265460848808289,
-0.09710903465747833,
-0.011078423820436,
-0.022652560845017433,
-0.024000728502869606,
0.0878278836607933,
-0.018813995644450188,
0.03245491161942482,
0.019763432443141937,
-0.03379102423787117,
0.07007033377885818,
-0.025310136377811432,
-0.022386055439710617,
-0.03589578717947006,
-0.06099054589867592,
0.05183964595198631,
-0.002879094798117876,
-0.0388391874730587,
-0.006428318098187447,
-0.04584600031375885,
-0.06035709008574486,
0.13202428817749023,
-0.004858740605413914,
-0.020473629236221313,
-0.07851582020521164,
0.09554000943899155,
-0.05498090013861656,
0.03728895261883736,
-0.13830018043518066,
-0.06243045628070831,
0.0036350893788039684,
-0.0796012431383133,
0.02157106250524521,
-0.0041148848831653595,
0.05950147658586502,
0.038105957210063934,
-0.04352330043911934,
-0.028907326981425285,
-0.0057363444939255714,
0.004301073960959911,
-0.025426069274544716,
-0.1666073054075241,
-0.0007695230888202786,
-0.0551750548183918,
0.1374220848083496,
-0.16868118941783905,
0.05043652653694153,
0.05925111472606659,
0.16357283294200897,
0.03616755083203316,
-0.031011521816253662,
0.11654403805732727,
-0.03804580122232437,
-0.006411012262105942,
-0.03725241497159004,
0.0044607375748455524,
0.002538213739171624,
-0.011939228512346745,
0.10659566521644592,
-0.06065728887915611,
0.054277852177619934,
0.12642189860343933,
-0.01595868356525898,
-0.05425528809428215,
-0.06506265699863434,
-0.01521784346550703,
-0.006736948620527983,
-0.048000186681747437,
-0.047349583357572556,
0.02513136900961399,
0.0662446990609169,
0.07768423110246658,
-0.03797391429543495,
-0.008253731764853,
0.0011901968391612172,
-0.0948609709739685,
-0.0020795518066734076,
0.0409865640103817,
0.05132393538951874,
-0.14333368837833405,
0.09081240743398666,
0.09744595736265182,
-0.015339801087975502,
0.14312495291233063,
0.008754834532737732,
-0.1070873811841011,
-0.003728162497282028,
0.027940761297941208,
0.05264529958367348,
0.0774049460887909,
-0.03596934303641319,
0.02683958038687706,
0.08106063306331635,
-0.05121877044439316,
0.007932554930448532,
-0.09500398486852646,
-0.022678673267364502,
-0.013256699778139591,
-0.0758146122097969,
-0.04612674191594124,
0.03610261529684067,
0.030104612931609154,
0.0918031707406044,
-0.015134556218981743,
0.07633049786090851,
-0.0010367896175011992,
-0.02394755184650421,
-0.09206201136112213,
0.1670486181974411,
-0.0899675041437149,
-0.27366867661476135,
-0.1188458725810051,
-0.07167717814445496,
-0.04199657961726189,
0.004022621084004641,
0.02857130952179432,
-0.12134306877851486,
-0.07081691175699234,
-0.03115151636302471,
-0.0038425917737185955,
0.06778023391962051,
-0.03805195540189743,
-0.02431504614651203,
0.05526971071958542,
0.09138014912605286,
-0.07273191213607788,
-0.002759605646133423,
0.06194623187184334,
-0.037675220519304276,
0.08085193485021591,
0.008549315854907036,
0.10605848580598831,
0.04739413037896156,
0.03012051060795784,
0.0015264216344803572,
0.04311876371502876,
0.17313145101070404,
-0.10127022117376328,
0.09718520194292068,
0.20746180415153503,
0.0394415408372879,
0.08480402082204819,
0.15171074867248535,
0.05122246593236923,
-0.013119645416736603,
-0.005120322108268738,
0.04244927689433098,
0.011746162548661232,
-0.2427690476179123,
-0.061469703912734985,
-0.05656198412179947,
-0.054776955395936966,
0.022767482325434685,
0.047591015696525574,
0.0650729089975357,
0.1047578752040863,
-0.10416096448898315,
-0.016062086448073387,
0.022997045889496803,
0.09911724179983139,
0.047439564019441605,
0.022038234397768974,
0.061993930488824844,
-0.04141371324658394,
0.015599393285810947,
0.12155410647392273,
0.06473620980978012,
0.11147889494895935,
-0.023897795006632805,
0.08020832389593124,
0.06728237122297287,
0.0892438217997551,
0.0530114471912384,
0.06319621205329895,
0.04218849167227745,
-0.014131366275250912,
-0.0013301256112754345,
-0.08454640209674835,
-0.04801497980952263,
0.023290416225790977,
0.013235284946858883,
-0.057533953338861465,
-0.0392376184463501,
-0.01914895512163639,
0.07390332221984863,
0.1574147492647171,
0.04597143456339836,
-0.20930512249469757,
-0.05056460201740265,
0.033859558403491974,
-0.0003397460968699306,
-0.06584210693836212,
-0.033550359308719635,
0.05652978643774986,
-0.12203755974769592,
0.1039382740855217,
-0.02658943273127079,
0.09946075826883316,
-0.07054278254508972,
0.000789299956522882,
0.00494906771928072,
0.12713035941123962,
-0.023788869380950928,
0.09413742274045944,
-0.24859566986560822,
0.14139194786548615,
0.04770104959607124,
0.06752338260412216,
-0.05309014022350311,
0.028258029371500015,
0.0961327999830246,
0.12656870484352112,
0.10434279590845108,
0.020785793662071228,
0.06395822018384933,
-0.15350443124771118,
-0.11799371987581253,
0.006164612248539925,
0.02960512787103653,
-0.04779611900448799,
0.07287964969873428,
-0.0005067483871243894,
-0.06341438740491867,
-0.04712821915745735,
0.03289221227169037,
-0.19348879158496857,
-0.12983499467372894,
0.07045576721429825,
0.052490055561065674,
0.090853750705719,
-0.06709475815296173,
-0.03205195814371109,
-0.043046124279499054,
0.18290454149246216,
-0.03442198783159256,
-0.08606650680303574,
-0.1285882145166397,
-0.0006686998531222343,
0.09258218854665756,
-0.08165017515420914,
-0.005991893354803324,
-0.052048277109861374,
0.1894829422235489,
-0.035209737718105316,
-0.08786994218826294,
0.01570327952504158,
-0.15995244681835175,
-0.1281605362892151,
-0.0414857491850853,
0.12103712558746338,
-0.021659180521965027,
0.02213156595826149,
0.05526252090930939,
-0.020805859938263893,
0.008410685695707798,
-0.1123393177986145,
0.02350648306310177,
0.09350050985813141,
0.08948540687561035,
0.08400450646877289,
-0.11930029839277267,
-0.11843101680278778,
-0.10216961801052094,
-0.022528614848852158,
0.06181072071194649,
0.24282413721084595,
-0.02235415205359459,
0.037382837384939194,
0.13085247576236725,
-0.04928212612867355,
-0.19814851880073547,
-0.06996271014213562,
-0.00017375701281707734,
-0.037472743541002274,
0.02159503661096096,
-0.21408295631408691,
0.08694717288017273,
0.09358245879411697,
-0.030445247888565063,
0.09161640703678131,
-0.07194696366786957,
-0.06843597441911697,
0.04065357893705368,
0.07071772962808609,
0.0037067674566060305,
-0.1683196723461151,
-0.07113704830408096,
-0.06764888018369675,
-0.12663458287715912,
0.08166584372520447,
-0.1314810812473297,
0.08971400558948517,
-0.005421672947704792,
0.0671011433005333,
0.025563575327396393,
-0.06707208603620529,
0.11356908828020096,
-0.020757906138896942,
0.009567689150571823,
-0.07924797385931015,
0.012899143621325493,
0.022010432556271553,
-0.050428662449121475,
0.09034649282693863,
-0.02925287000834942,
0.01692429557442665,
-0.091850645840168,
-0.0007856881711632013,
-0.10224597156047821,
0.0437864288687706,
-0.038862090557813644,
-0.017533548176288605,
-0.008498632349073887,
0.07837546616792679,
0.03536466881632805,
0.010669435374438763,
-0.009266866371035576,
-0.04946504905819893,
0.10181041061878204,
0.17810481786727905,
0.10491631180047989,
0.0006870499346405268,
-0.07857012748718262,
-0.036821771413087845,
-0.053213875740766525,
0.050082918256521225,
-0.08183137327432632,
0.06681650131940842,
0.029605142772197723,
0.010572184808552265,
0.12429390102624893,
-0.0033586653880774975,
-0.12030913680791855,
-0.003338087350130081,
0.10895328968763351,
-0.12868796288967133,
-0.07275929301977158,
-0.020934229716658592,
0.05516009032726288,
-0.10196569561958313,
0.0011667415965348482,
0.1428048461675644,
-0.028892088681459427,
-0.028331711888313293,
0.014776935800909996,
0.07020314782857895,
-0.012796786613762379,
0.10238455981016159,
0.07413777709007263,
0.049551427364349365,
-0.12031137198209763,
0.05704139545559883,
0.03181569650769234,
-0.03592713922262192,
-0.0024339298252016306,
0.05667674541473389,
-0.10612429678440094,
-0.1119871735572815,
0.03397342190146446,
0.06045559421181679,
-0.015471268445253372,
-0.06184658035635948,
-0.020792635157704353,
-0.04714902117848396,
0.02126099169254303,
0.07590576261281967,
0.00995138380676508,
-0.008162305690348148,
0.08148860931396484,
-0.017391547560691833,
-0.08959554880857468,
0.06402577459812164,
0.010443227365612984,
0.03571965917944908,
-0.13038720190525055,
0.07408680766820908,
-0.015041174367070198,
0.006071531679481268,
-0.022530831396579742,
0.003641687100753188,
-0.10074226558208466,
-0.04254826903343201,
-0.07885435223579407,
0.06230726093053818,
-0.1484614759683609,
-0.020241795107722282,
-0.026183132082223892,
-0.022612975910305977,
0.015071062371134758,
0.019551774486899376,
-0.07782812416553497,
-0.04559153690934181,
-0.010346274822950363,
0.08449862152338028,
-0.16007104516029358,
-0.008523115888237953,
0.03327300027012825,
-0.06084582209587097,
0.0670776516199112,
0.08543620258569717,
-0.010745981708168983,
-0.011400423012673855,
-0.24030931293964386,
-0.05429427698254585,
0.060920946300029755,
0.04178236424922943,
0.015297153033316135,
-0.10723429918289185,
0.0352109931409359,
-0.01898287609219551,
-0.023456763476133347,
0.005050045438110828,
0.031953055411577225,
-0.08434974402189255,
0.024241402745246887,
-0.019039491191506386,
-0.04014326632022858,
-0.051917847245931625,
0.04262912645936012,
0.17145587503910065,
-0.014532416127622128,
0.1174297034740448,
-0.080752432346344,
0.054420918226242065,
-0.13401885330677032,
0.029829595237970352,
-0.001078542205505073,
-0.039962440729141235,
-0.02863360196352005,
-0.010570892132818699,
0.06349045038223267,
-0.010899520479142666,
0.09258676320314407,
-0.0552545003592968,
0.06722300499677658,
0.0190583486109972,
-0.09725376963615417,
0.007986992597579956,
-0.026470135897397995,
0.03294571489095688,
0.0396236926317215,
-0.006473933346569538,
0.009316735900938511,
0.00238132756203413,
0.02042953483760357,
-0.0582701601088047,
0.07976511865854263,
0.16147081553936005,
0.02053176984190941,
0.022807525470852852,
0.054943084716796875,
-0.07234697043895721,
-0.036924149841070175,
-0.04578930139541626,
-0.077462337911129,
0.06634023785591125,
-0.021255100145936012,
0.07374273985624313,
0.15307408571243286,
-0.12218204140663147,
0.038187239319086075,
-0.005237263161689043,
-0.03132057934999466,
-0.08196348696947098,
-0.1581864356994629,
-0.06715912371873856,
-0.08088500797748566,
0.011959434486925602,
-0.11438815295696259,
0.06888450682163239,
0.04325690120458603,
0.019395047798752785,
-0.017880942672491074,
0.13543029129505157,
0.03472369909286499,
-0.07543140649795532,
0.060917001217603683,
-0.02095349319279194,
-0.031358812004327774,
0.04272241145372391,
0.0006400952115654945,
0.06196298450231552,
-0.010582057759165764,
0.044258568435907364,
0.0559408999979496,
0.02938593178987503,
0.05811672285199165,
-0.06726688146591187,
-0.12517108023166656,
0.006359596271067858,
0.005888449959456921,
0.04039566218852997,
0.15003027021884918,
0.05136363208293915,
0.007397872861474752,
0.014586303383111954,
0.16361239552497864,
-0.038274187594652176,
-0.0431714691221714,
-0.15419889986515045,
0.011273895390331745,
-0.02001452073454857,
-0.009176031686365604,
-0.03663250058889389,
-0.10866829752922058,
-0.028140606358647346,
0.20135445892810822,
0.08363344520330429,
-0.049736183136701584,
0.026926010847091675,
-0.006478144787251949,
0.0070541067980229855,
0.006099193822592497,
0.08733457326889038,
0.05982113629579544,
0.11233042925596237,
-0.03476639464497566,
0.04225286468863487,
0.008952682837843895,
-0.042931120842695236,
-0.100910983979702,
0.05160531401634216,
-0.04183126986026764,
-0.029043002054095268,
-0.0207699965685606,
0.12725666165351868,
-0.06002918258309364,
-0.12053494155406952,
-0.05984590947628021,
-0.05843505263328552,
-0.09186802059412003,
-0.04533113166689873,
-0.021347900852560997,
0.08330697566270828,
0.03736959397792816,
-0.008225626312196255,
-0.006564581301063299,
0.18599693477153778,
-0.004363450221717358,
-0.06833065301179886,
-0.047022756189107895,
0.03228268772363663,
-0.009685746394097805,
0.13331912457942963,
0.02237250655889511,
0.06835850328207016,
0.08902639895677567,
-0.04617135971784592,
-0.13351397216320038,
0.05768809840083122,
0.01893182285130024,
-0.16012974083423615,
0.03900958225131035,
0.1735668033361435,
-0.019399257376790047,
0.004258662927895784,
0.07070906460285187,
-0.07974739372730255,
0.021498262882232666,
0.05192280188202858,
-0.017278648912906647,
-0.07030515372753143,
0.08999960869550705,
-0.09391003847122192,
0.11678098142147064,
0.17506007850170135,
-0.024389326572418213,
-0.013276796787977219,
-0.03903545066714287,
0.05904215946793556,
0.06406354159116745,
-0.016790268942713737,
-0.07218509912490845,
-0.10399819910526276,
0.01415897998958826,
-0.01502299215644598,
0.07969480007886887,
-0.13121938705444336,
-0.019862104207277298,
-0.05875250697135925,
-0.03522523120045662,
-0.09029058367013931,
0.07942423224449158,
0.06178797036409378,
0.053517896682024,
-0.021183528006076813,
-0.09516715258359909,
0.007413235958665609,
0.11255256831645966,
-0.14081521332263947,
-0.0646120086312294
] |
null | null | diffusers | # fcdsf
<Gallery />
## Model description
fgsdg
## Trigger words
You should use `dsfds` to trigger the image generation.
## Download model
[Download](/zz001/45435/tree/main) them in the Files & versions tab.
| {"license": "bigscience-openrail-m", "tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "wewe", "parameters": {"negative_prompt": "eretr"}, "output": {"url": "images/test.png"}}], "base_model": "InstantX/InstantID", "instance_prompt": "dsfds"} | text-to-image | zz001/45435 | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:InstantX/InstantID",
"license:bigscience-openrail-m",
"region:us"
] | 2024-02-09T01:12:43+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-InstantX/InstantID #license-bigscience-openrail-m #region-us
| # fcdsf
<Gallery />
## Model description
fgsdg
!URL
## Trigger words
You should use 'dsfds' to trigger the image generation.
## Download model
Download them in the Files & versions tab.
| [
"# fcdsf\n\n<Gallery />",
"## Model description \n\nfgsdg\n!URL",
"## Trigger words\n\nYou should use 'dsfds' to trigger the image generation.",
"## Download model\n\n\nDownload them in the Files & versions tab."
] | [
"TAGS\n#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-InstantX/InstantID #license-bigscience-openrail-m #region-us \n",
"# fcdsf\n\n<Gallery />",
"## Model description \n\nfgsdg\n!URL",
"## Trigger words\n\nYou should use 'dsfds' to trigger the image generation.",
"## Download model\n\n\nDownload them in the Files & versions tab."
] | [
58,
10,
9,
18,
14
] | [
"passage: TAGS\n#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-InstantX/InstantID #license-bigscience-openrail-m #region-us \n# fcdsf\n\n<Gallery />## Model description \n\nfgsdg\n!URL## Trigger words\n\nYou should use 'dsfds' to trigger the image generation.## Download model\n\n\nDownload them in the Files & versions tab."
] | [
-0.11219175159931183,
-0.013810201548039913,
-0.0040895589627325535,
0.048869337886571884,
0.10376913845539093,
0.03246120363473892,
0.16407015919685364,
0.043192919343709946,
0.1509876847267151,
0.04881671816110611,
0.1316148340702057,
0.061275456100702286,
0.020650293678045273,
0.23678487539291382,
-0.07125825434923172,
-0.22438770532608032,
0.05853695049881935,
-0.002553991274908185,
-0.11910584568977356,
-0.010545254684984684,
0.09266766160726547,
-0.06236831843852997,
0.14134915173053741,
-0.06473095715045929,
-0.15080755949020386,
-0.02371499128639698,
-0.0016543398378416896,
-0.040553413331508636,
0.032030194997787476,
0.08595074713230133,
-0.07511837780475616,
0.1366802304983139,
0.08817245811223984,
-0.04790607839822769,
0.0597541481256485,
-0.013149299658834934,
-0.0381072536110878,
0.058956079185009,
-0.0004028374678455293,
0.09113947302103043,
0.17531804740428925,
-0.0076414053328335285,
-0.038660913705825806,
-0.011089840903878212,
-0.05645294114947319,
-0.2324870079755783,
0.014394134283065796,
0.05981064587831497,
0.05341736972332001,
-0.02939451113343239,
0.0492996908724308,
-0.10202667862176895,
-0.004747712519019842,
0.0710642859339714,
0.09997521340847015,
-0.0877876803278923,
-0.03488006442785263,
0.2634302079677582,
0.04568307101726532,
0.12724071741104126,
-0.052496813237667084,
0.09656970202922821,
0.042925164103507996,
-0.03354619815945625,
0.013845075853168964,
-0.030534911900758743,
0.1300986111164093,
-0.04169337451457977,
-0.06537332385778427,
0.06948433071374893,
0.33351027965545654,
0.03422459214925766,
-0.039733804762363434,
-0.14576128125190735,
-0.08840502798557281,
0.1470816731452942,
-0.14365209639072418,
-0.07532811909914017,
0.06214994564652443,
0.03306064009666443,
0.06457280367612839,
-0.13622891902923584,
-0.06695988029241562,
-0.05277814716100693,
-0.06155415251851082,
0.1310448944568634,
-0.05331483855843544,
0.08975249528884888,
-0.05831212177872658,
0.03387998044490814,
-0.1412312388420105,
-0.16484078764915466,
-0.052136730402708054,
-0.16942501068115234,
0.10636545717716217,
0.06990735232830048,
-0.010052756406366825,
-0.03170796483755112,
0.13316521048545837,
0.08279146254062653,
0.07098066061735153,
-0.024104345589876175,
-0.010095756500959396,
0.10550206899642944,
0.031523697078228,
-0.019441308453679085,
-0.10488186776638031,
-0.008254697546362877,
0.08310751616954803,
0.034309178590774536,
0.03418195992708206,
-0.08048063516616821,
-0.1570851057767868,
-0.02342287078499794,
-0.16120624542236328,
-0.050619855523109436,
0.028163475915789604,
0.020873481407761574,
0.018611406907439232,
-0.05903162062168121,
0.21420620381832123,
0.01683899573981762,
-0.04257259517908096,
0.01638374850153923,
-0.05506424233317375,
0.1859571784734726,
0.07697789371013641,
0.004235551692545414,
0.16247068345546722,
0.10019471496343613,
-0.0704081580042839,
-0.04246688261628151,
-0.04903049021959305,
-0.013959732837975025,
-0.003952267579734325,
-0.042824238538742065,
0.0719626396894455,
-0.13525666296482086,
-0.23322468996047974,
0.01368328183889389,
0.05752553790807724,
-0.0655725747346878,
0.02540351264178753,
0.02052656002342701,
-0.08574438095092773,
0.05985395982861519,
0.01308355014771223,
-0.019008155912160873,
-0.05327865481376648,
0.09235725551843643,
-0.031397078186273575,
0.170715793967247,
-0.2774212062358856,
0.026116637513041496,
-0.048929326236248016,
0.030942179262638092,
-0.2298758625984192,
0.10049674659967422,
-0.12770672142505646,
0.06569044291973114,
0.01559280976653099,
-0.023966040462255478,
-0.0955338180065155,
0.05595054849982262,
0.009866503067314625,
0.24433310329914093,
-0.18802006542682648,
-0.04113287106156349,
0.0773729532957077,
-0.14504402875900269,
-0.09824329614639282,
0.0497555285692215,
-0.00979546271264553,
0.12428505718708038,
0.03354766592383385,
0.19665753841400146,
0.0584741048514843,
-0.17278464138507843,
0.09121984243392944,
0.16098327934741974,
-0.053476013243198395,
-0.034258633852005005,
0.0792485773563385,
0.0811735987663269,
0.0879461020231247,
0.09697438031435013,
-0.1219882071018219,
0.09181277453899384,
-0.05522884428501129,
-0.006401911377906799,
-0.009733668528497219,
-0.05056779459118843,
0.02487579546868801,
0.03446033596992493,
0.046208009123802185,
0.006879622116684914,
0.04632620885968208,
-0.006325963418930769,
0.059191253036260605,
0.0007151550380513072,
-0.056313656270504,
-0.03420534357428551,
0.12892456352710724,
-0.06775206327438354,
0.057508379220962524,
-0.03689740598201752,
-0.12289206683635712,
0.004635229241102934,
0.15997126698493958,
0.019249869510531425,
0.09395930171012878,
0.08650307357311249,
0.028439030051231384,
-0.024189630523324013,
0.055790454149246216,
0.032761912792921066,
-0.0499802827835083,
-0.004193323198705912,
-0.13732948899269104,
0.03515937179327011,
-0.08078278601169586,
0.07176246494054794,
-0.26197198033332825,
0.03131120279431343,
0.13257138431072235,
0.01412581279873848,
0.07504409551620483,
-0.02179671823978424,
-0.017430761829018593,
-0.08581749349832535,
-0.03727801516652107,
-0.0061340234242379665,
0.0638352558016777,
0.0007853748393245041,
-0.0562722347676754,
0.10639780014753342,
-0.01633928343653679,
0.2693837285041809,
0.1357211470603943,
0.0026955639477819204,
-0.024326208978891373,
-0.12033332139253616,
-0.008954491466283798,
0.0565362386405468,
0.049294471740722656,
-0.09390616416931152,
-0.10622332990169525,
-0.026708893477916718,
0.04392861947417259,
-0.03278012573719025,
0.05054810643196106,
0.06179462745785713,
-0.010023059323430061,
-0.05645092576742172,
0.05341720208525658,
0.1872262805700302,
-0.037164222449064255,
0.14241091907024384,
0.15057986974716187,
0.013790837489068508,
0.15760241448879242,
-0.059818871319293976,
-0.06577138602733612,
0.031485073268413544,
0.02302052453160286,
-0.03265108913183212,
0.22633326053619385,
-0.013664311729371548,
-0.008990069851279259,
0.08791720122098923,
-0.07813794165849686,
-0.008258369751274586,
-0.059485308825969696,
-0.09573130309581757,
0.03200095519423485,
-0.03855157643556595,
0.06716844439506531,
0.10576889663934708,
-0.0890154168009758,
0.11528690904378891,
-0.03974200040102005,
-0.10110599547624588,
0.03731268271803856,
-0.017321396619081497,
-0.056000351905822754,
0.10715049505233765,
-0.019439872354269028,
-0.13795672357082367,
-0.14142978191375732,
-0.019474904984235764,
-0.10604534298181534,
0.04631289094686508,
0.013530278578400612,
-0.04657885059714317,
-0.05083363875746727,
-0.019899612292647362,
-0.005757458042353392,
0.02569449320435524,
-0.04736833646893501,
0.02736371010541916,
-0.022224172949790955,
-0.07940039783716202,
-0.11520952731370926,
-0.03759603202342987,
-0.05235539376735687,
0.07990433275699615,
0.10263921320438385,
0.0018644973170012236,
0.12138314545154572,
0.04443350434303284,
0.06407169997692108,
0.015056408010423183,
0.03874557837843895,
0.24944579601287842,
-0.10317590087652206,
0.08355394750833511,
0.25707361102104187,
0.02462194859981537,
0.022527256980538368,
0.16030101478099823,
0.07588022947311401,
-0.1477510631084442,
0.016440169885754585,
-0.07373692095279694,
-0.1429019272327423,
-0.02169763296842575,
-0.08340350538492203,
-0.10225103050470352,
0.04675263911485672,
-0.05684226006269455,
0.04642026126384735,
0.09486677497625351,
0.16691266000270844,
0.007362920790910721,
0.018893593922257423,
0.06034240126609802,
0.015629302710294724,
0.10547707974910736,
-0.02095123939216137,
0.09241343289613724,
-0.04479977488517761,
-0.04098637029528618,
0.148548424243927,
-0.06886085867881775,
0.11248528212308884,
0.019612746313214302,
0.004736880771815777,
0.019279813393950462,
-0.04842907562851906,
0.09021831303834915,
0.0899139866232872,
-0.054702453315258026,
-0.07286283373832703,
-0.06138230860233307,
-0.13107575476169586,
0.03572864085435867,
0.11944364756345749,
-0.07554282993078232,
-0.09509609639644623,
0.0115659199655056,
0.014066268689930439,
-0.016917187720537186,
0.020213723182678223,
0.017972595989704132,
-0.2817154824733734,
-0.008939570747315884,
0.059519074857234955,
0.1487097144126892,
-0.0672890692949295,
0.02469281665980816,
0.1527627408504486,
-0.047211095690727234,
0.02640911191701889,
0.02869994193315506,
0.05518074333667755,
0.019246593117713928,
-0.006078486330807209,
0.020648876205086708,
0.025052694603800774,
0.02667776681482792,
-0.026713846251368523,
-0.2165721207857132,
0.03691646084189415,
0.006544168572872877,
-0.062148842960596085,
-0.02357036992907524,
0.019405361264944077,
0.0806269720196724,
0.17165759205818176,
0.1683603972196579,
0.005003298167139292,
0.013059496879577637,
-0.10600131005048752,
-0.09851148724555969,
0.007658340502530336,
0.09731565415859222,
-0.11702035367488861,
-0.04705654829740524,
0.050823427736759186,
0.0011675728019326925,
0.01085561141371727,
0.18384379148483276,
-0.08118124306201935,
-0.11370403319597244,
0.04144470766186714,
0.043277889490127563,
0.05017812177538872,
-0.021306157112121582,
0.001745707355439663,
-0.14302831888198853,
0.02396337129175663,
0.015914658084511757,
-0.1286846548318863,
-0.15109942853450775,
-0.023762330412864685,
0.002370159374549985,
-0.007363641634583473,
0.0774226039648056,
-0.021584106609225273,
0.05831499397754669,
-0.0335310660302639,
-0.2156745195388794,
0.09843920916318893,
-0.10847026109695435,
-0.06073674187064171,
-0.07991503924131393,
0.08793178200721741,
-0.019026126712560654,
-0.009837961755692959,
0.007960361428558826,
0.024392442777752876,
0.030740391463041306,
-0.11472055315971375,
0.06955544650554657,
0.09827612340450287,
-0.06048460677266121,
0.0171064306050539,
-0.08995542675256729,
0.03384923189878464,
0.08310503512620926,
0.032567739486694336,
0.05512700974941254,
0.30511000752449036,
-0.0910668596625328,
0.09043654054403305,
0.08824316412210464,
0.008719969540834427,
-0.3179195523262024,
0.04593261331319809,
-0.005577330477535725,
-0.009871047921478748,
0.013120496645569801,
-0.18858110904693604,
0.18493720889091492,
0.12318597733974457,
-0.06701914221048355,
0.34699222445487976,
-0.2359028160572052,
-0.10487741231918335,
0.017802363261580467,
0.07398757338523865,
0.23017892241477966,
-0.25155872106552124,
-0.0535244457423687,
-0.06710357218980789,
-0.20531602203845978,
0.16691383719444275,
-0.022370455786585808,
-0.007573007605969906,
-0.013810546137392521,
-0.0351940393447876,
0.03109908290207386,
-0.018648840487003326,
0.19547396898269653,
-0.04680759087204933,
0.1190771833062172,
-0.09848807007074356,
0.026474300771951675,
0.12320057302713394,
0.04172128811478615,
0.10926251113414764,
-0.029597699642181396,
0.0073945652693510056,
-0.14009717106819153,
-0.009635020978748798,
-0.04277098923921585,
0.05432911217212677,
-0.017316428944468498,
-0.1008039265871048,
-0.078281931579113,
0.006393310148268938,
-0.04860745370388031,
0.012310666963458061,
0.02189020998775959,
-0.06484829634428024,
0.021181384101510048,
0.16735254228115082,
-0.0009157651220448315,
-0.03867333382368088,
-0.03779057785868645,
-0.058547697961330414,
-0.044537849724292755,
0.10343633592128754,
-0.16207964718341827,
-0.030141755938529968,
0.10266754031181335,
0.05879128724336624,
0.05906257778406143,
0.0601731576025486,
0.05826098844408989,
0.06321591883897781,
0.12061617523431778,
-0.11298365890979767,
-0.17089249193668365,
-0.09735694527626038,
-0.05656903609633446,
0.08690164238214493,
0.009030969813466072,
0.10243993252515793,
-0.03205612301826477,
0.05278971046209335,
0.001980400877073407,
0.02235925756394863,
-0.03558384254574776,
0.03269890695810318,
0.119635671377182,
-0.009299438446760178,
-0.11974183470010757,
-0.013489007018506527,
-0.02990279532968998,
-0.02266782335937023,
-0.07884310930967331,
0.048971597105264664,
-0.08003703504800797,
-0.05123087763786316,
-0.06243326514959335,
0.05966835096478462,
-0.09065461903810501,
0.031785789877176285,
0.013113383203744888,
-0.1290709674358368,
-0.018025344237685204,
0.05505525320768356,
0.06145111843943596,
-0.06486516445875168,
0.03686016425490379,
0.07480965554714203,
0.012147479690611362,
0.053877245634794235,
-0.08178076893091202,
0.12401414662599564,
-0.183451846241951,
-0.12234146893024445,
-0.11277974396944046,
0.027017733082175255,
-0.13660933077335358,
0.004719817545264959,
-0.11582548916339874,
-0.02206086739897728,
-0.03956965357065201,
0.04039321094751358,
-0.058015376329422,
-0.0391322523355484,
-0.04173239320516586,
-0.040976203978061676,
0.009455294348299503,
-0.03153475001454353,
-0.08323682099580765,
-0.0070708682760596275,
0.011022202670574188,
0.020959826186299324,
-0.06503982096910477,
-0.07084520906209946,
-0.005234777927398682,
-0.07723215222358704,
0.11965179443359375,
0.07946843653917313,
-0.03551698103547096,
-0.057041049003601074,
-0.19363319873809814,
-0.005714720580726862,
0.1232849657535553,
0.08421323448419571,
-0.03654301166534424,
0.1432362198829651,
0.046927545219659805,
-0.03929935768246651,
-0.043282121419906616,
-0.0010348039213567972,
-0.015157323330640793,
-0.09511929005384445,
0.05528079345822334,
-0.10288834571838379,
0.019762134179472923,
-0.02243378385901451,
0.006126471795141697,
0.1582428216934204,
0.1296808421611786,
0.053694598376750946,
-0.048295311629772186,
0.010580637492239475,
-0.08673184365034103,
0.0007811617688275874,
0.04863766208291054,
-0.0991913452744484,
0.01638670079410076,
-0.08858619630336761,
0.01846483163535595,
-0.016855264082551003,
0.207858607172966,
0.033309582620859146,
-0.16021692752838135,
-0.008592711761593819,
-0.013226631097495556,
0.22431477904319763,
0.036652032285928726,
0.24237388372421265,
0.12866730988025665,
0.0686381459236145,
-0.10398421436548233,
0.140180304646492,
0.13774316012859344,
-0.03757069259881973,
0.007642779499292374,
0.10782214999198914,
-0.11774346977472305,
0.03601870685815811,
0.09401631355285645,
-0.01838318258523941,
0.057839419692754745,
-0.006582579575479031,
-0.017142686992883682,
0.0442298948764801,
-0.09323916584253311,
0.028515534475445747,
0.12867438793182373,
-0.07161515206098557,
0.04593445360660553,
0.046156276017427444,
-0.0068208943121135235,
-0.09063395857810974,
-0.11854435503482819,
-0.053804799914360046,
-0.1920260339975357,
0.03781392425298691,
-0.07239298522472382,
-0.02205936424434185,
0.047304827719926834,
0.04767894372344017,
-0.05657046288251877,
0.08059068024158478,
-0.07613296806812286,
-0.04946263134479523,
0.15306439995765686,
-0.046099547296762466,
-0.13869774341583252,
-0.09344114363193512,
-0.06137197092175484,
0.04669057950377464,
0.017653213813900948,
-0.023964177817106247,
0.039411306381225586,
-0.009627653285861015,
-0.0370730385184288,
-0.03443846479058266,
-0.04384420067071915,
-0.035976968705654144,
0.003468782640993595,
-0.046609967947006226,
0.05849044770002365,
0.0014876116765663028,
-0.009488780051469803,
0.003324696561321616,
0.10489656776189804,
-0.024774888530373573,
0.002552237594500184,
-0.04545534402132034,
-0.009088652208447456,
-0.11855422705411911,
0.149689719080925,
-0.09260216355323792,
-0.0784507542848587,
-0.06768792867660522,
0.12170428782701492,
0.20180152356624603,
-0.23830245435237885,
0.03328174725174904,
0.04190843179821968,
0.008921346627175808,
-0.037082310765981674,
0.12127195298671722,
0.028872204944491386,
0.32282185554504395,
-0.030027011409401894,
0.013061060570180416,
-0.04826844111084938,
-0.023271294310688972,
-0.08078894019126892,
0.009066312573850155,
0.08605712652206421,
-0.07036899775266647,
-0.07563349604606628,
0.07834035158157349,
-0.1981177031993866,
0.003424219088628888,
0.03092656284570694,
-0.0939374566078186,
-0.010268579237163067,
-0.09488548338413239,
-0.16360996663570404,
0.04564669355750084,
-0.03465176746249199,
-0.1130329817533493,
0.006905883084982634,
-0.06997187435626984,
-0.0258072130382061,
-0.10758759081363678,
0.039433885365724564,
0.023932939395308495,
-0.10218460857868195,
0.09686598926782608,
-0.05127086490392685,
0.047813404351472855,
-0.004328431095927954,
0.002059931168332696,
-0.04614792764186859,
0.004373989067971706,
0.013598755933344364,
-0.10561958700418472,
-0.0663791298866272,
0.06720733642578125,
-0.007893230766057968,
0.0011025724234059453,
0.0450160838663578,
-0.1270085722208023,
-0.0034479813184589148,
0.15740759670734406,
-0.09750876575708389,
-0.06278156489133835,
0.04047424718737602,
-0.14476454257965088,
0.049515292048454285,
0.023030726239085197,
0.022371532395482063,
-0.05272124707698822,
-0.03472520038485527,
0.07847268134355545,
0.10480236262083054,
-0.03523015230894089,
0.004485681187361479,
-0.050574418157339096,
-0.05512990057468414,
0.02541191130876541,
0.029620986431837082,
-0.1486896276473999,
-0.03153663128614426,
-0.14871947467327118,
0.08960813283920288,
0.010719960555434227,
0.012222325429320335,
0.21391133964061737,
-0.032717157155275345,
-0.027295086532831192,
-0.16602931916713715,
0.013713913038372993,
0.06172528117895126,
-0.07534159719944,
-0.032131899148225784
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SMIDS_3x_beit_large_SGD_lr001_fold4
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3993
- Accuracy: 0.8783
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5123 | 1.0 | 450 | 0.5552 | 0.755 |
| 0.3912 | 2.0 | 900 | 0.4114 | 0.84 |
| 0.2933 | 3.0 | 1350 | 0.3708 | 0.8567 |
| 0.3191 | 4.0 | 1800 | 0.3508 | 0.86 |
| 0.3317 | 5.0 | 2250 | 0.3423 | 0.8617 |
| 0.2689 | 6.0 | 2700 | 0.3391 | 0.87 |
| 0.2083 | 7.0 | 3150 | 0.3390 | 0.87 |
| 0.202 | 8.0 | 3600 | 0.3353 | 0.8717 |
| 0.1993 | 9.0 | 4050 | 0.3400 | 0.865 |
| 0.3128 | 10.0 | 4500 | 0.3384 | 0.8717 |
| 0.2573 | 11.0 | 4950 | 0.3395 | 0.87 |
| 0.2604 | 12.0 | 5400 | 0.3434 | 0.8683 |
| 0.2724 | 13.0 | 5850 | 0.3473 | 0.865 |
| 0.1732 | 14.0 | 6300 | 0.3517 | 0.8733 |
| 0.1189 | 15.0 | 6750 | 0.3454 | 0.875 |
| 0.2309 | 16.0 | 7200 | 0.3498 | 0.8733 |
| 0.1794 | 17.0 | 7650 | 0.3554 | 0.87 |
| 0.1566 | 18.0 | 8100 | 0.3589 | 0.8733 |
| 0.1969 | 19.0 | 8550 | 0.3571 | 0.8767 |
| 0.1369 | 20.0 | 9000 | 0.3609 | 0.8733 |
| 0.1339 | 21.0 | 9450 | 0.3617 | 0.875 |
| 0.1597 | 22.0 | 9900 | 0.3619 | 0.8717 |
| 0.1692 | 23.0 | 10350 | 0.3624 | 0.875 |
| 0.1417 | 24.0 | 10800 | 0.3692 | 0.8783 |
| 0.1306 | 25.0 | 11250 | 0.3685 | 0.875 |
| 0.1537 | 26.0 | 11700 | 0.3706 | 0.8717 |
| 0.0978 | 27.0 | 12150 | 0.3760 | 0.87 |
| 0.1927 | 28.0 | 12600 | 0.3793 | 0.8733 |
| 0.122 | 29.0 | 13050 | 0.3831 | 0.8733 |
| 0.1409 | 30.0 | 13500 | 0.3836 | 0.8733 |
| 0.0845 | 31.0 | 13950 | 0.3836 | 0.875 |
| 0.1488 | 32.0 | 14400 | 0.3862 | 0.8767 |
| 0.1769 | 33.0 | 14850 | 0.3835 | 0.8767 |
| 0.2002 | 34.0 | 15300 | 0.3867 | 0.8783 |
| 0.111 | 35.0 | 15750 | 0.3880 | 0.8817 |
| 0.201 | 36.0 | 16200 | 0.3894 | 0.8833 |
| 0.1149 | 37.0 | 16650 | 0.3946 | 0.8783 |
| 0.1112 | 38.0 | 17100 | 0.3958 | 0.8767 |
| 0.1167 | 39.0 | 17550 | 0.3959 | 0.8767 |
| 0.1078 | 40.0 | 18000 | 0.3977 | 0.88 |
| 0.119 | 41.0 | 18450 | 0.3983 | 0.8783 |
| 0.0522 | 42.0 | 18900 | 0.3979 | 0.8783 |
| 0.1313 | 43.0 | 19350 | 0.3981 | 0.88 |
| 0.0755 | 44.0 | 19800 | 0.3975 | 0.8767 |
| 0.1358 | 45.0 | 20250 | 0.3980 | 0.875 |
| 0.1454 | 46.0 | 20700 | 0.3986 | 0.8767 |
| 0.1499 | 47.0 | 21150 | 0.3982 | 0.8783 |
| 0.1051 | 48.0 | 21600 | 0.3992 | 0.8783 |
| 0.1082 | 49.0 | 22050 | 0.3993 | 0.8783 |
| 0.0415 | 50.0 | 22500 | 0.3993 | 0.8783 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_3x_beit_large_SGD_lr001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8783333333333333, "name": "Accuracy"}]}]}]} | image-classification | onizukal/SMIDS_3x_beit_large_SGD_lr001_fold4 | [
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-large-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:16:22+00:00 | [] | [] | TAGS
#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| SMIDS\_3x\_beit\_large\_SGD\_lr001\_fold4
=========================================
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3993
* Accuracy: 0.8783
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.2
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
"TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
81,
115,
4,
30
] | [
"passage: TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
-0.1293599158525467,
0.1724882274866104,
-0.0023454553447663784,
0.13587836921215057,
0.11250235140323639,
0.015344180166721344,
0.13944171369075775,
0.16905122995376587,
-0.08231265097856522,
0.04725457355380058,
0.1399839073419571,
0.13659004867076874,
0.046719420701265335,
0.19427457451820374,
-0.05236957222223282,
-0.2601667046546936,
0.04119328409433365,
0.03234807401895523,
-0.02075078710913658,
0.12314869463443756,
0.09301083534955978,
-0.13055187463760376,
0.11641614139080048,
0.030263151973485947,
-0.1994711011648178,
-0.03690062463283539,
-0.00742433313280344,
-0.06729142367839813,
0.10523199290037155,
-0.003170925425365567,
0.06897550076246262,
0.03744976967573166,
0.0835329070687294,
-0.13024620711803436,
0.0019813377875834703,
0.043246712535619736,
0.0064185261726379395,
0.10353662818670273,
0.05471734330058098,
-0.015182994306087494,
0.07030405849218369,
-0.06875743716955185,
0.06702885776758194,
0.009385199286043644,
-0.11313743144273758,
-0.26980340480804443,
-0.10223843902349472,
0.07157823443412781,
0.08217991888523102,
0.068179190158844,
0.008332090452313423,
0.1646922081708908,
-0.015027978457510471,
0.10447341948747635,
0.23090173304080963,
-0.2640359699726105,
-0.055165741592645645,
0.0294360164552927,
0.014914325438439846,
0.06473758071660995,
-0.10603974759578705,
-0.018760167062282562,
0.02059783600270748,
0.044390130788087845,
0.1409236192703247,
-0.010635782033205032,
-0.02811739780008793,
-0.021928580477833748,
-0.10847067832946777,
-0.08875154703855515,
0.18579065799713135,
0.058072153478860855,
-0.04802494868636131,
-0.07736620306968689,
-0.07186304777860641,
-0.17165552079677582,
-0.041741833090782166,
0.009797174483537674,
0.04154014587402344,
-0.04674985632300377,
-0.10634559392929077,
-0.030910290777683258,
-0.07805538177490234,
-0.051461391150951385,
-0.023120464757084846,
0.1351369321346283,
0.03383360058069229,
0.05723920464515686,
-0.03597215935587883,
0.09929350018501282,
0.0073938071727752686,
-0.17543649673461914,
-0.028137801215052605,
-0.0017277015140280128,
0.015125435777008533,
-0.01991228759288788,
-0.030262885615229607,
-0.06523662805557251,
-0.001314454828388989,
0.1489848643541336,
-0.06082969531416893,
0.060913555324077606,
-0.007318461779505014,
0.04020942002534866,
-0.048562191426754,
0.1864238679409027,
-0.02870783396065235,
-0.01659870520234108,
0.0207351166754961,
0.08822518587112427,
0.06836054474115372,
-0.036532942205667496,
-0.12525734305381775,
0.03098621405661106,
0.12811045348644257,
0.0029374780133366585,
-0.021369412541389465,
0.05286439135670662,
-0.0643334686756134,
-0.0587083138525486,
0.09228596836328506,
-0.08908151835203171,
0.034838590770959854,
-0.010374085046350956,
-0.084370456635952,
-0.06779533624649048,
0.027354132384061813,
0.01850878819823265,
-0.0004323708708398044,
0.07165450602769852,
-0.09108522534370422,
0.014963540248572826,
-0.06533985584974289,
-0.10081785917282104,
0.016071073710918427,
-0.1107335016131401,
0.012424856424331665,
-0.09663169085979462,
-0.19710472226142883,
0.006891206838190556,
0.07721206545829773,
-0.05610070005059242,
-0.06814593821763992,
-0.03639180585741997,
-0.07652068138122559,
0.04154945909976959,
-0.011949662119150162,
0.07310567051172256,
-0.0747697651386261,
0.0913747176527977,
0.022405456751585007,
0.08734618872404099,
-0.05631003528833389,
0.0460691936314106,
-0.1024455726146698,
0.04984736442565918,
-0.19827407598495483,
0.0799676924943924,
-0.0493633896112442,
0.0617455318570137,
-0.09557844698429108,
-0.10542625933885574,
0.03370443359017372,
-0.05006959289312363,
0.06861566007137299,
0.0974634513258934,
-0.1729826033115387,
-0.057957619428634644,
0.1353495568037033,
-0.09663163125514984,
-0.14797286689281464,
0.10109983384609222,
-0.050693199038505554,
0.01928282529115677,
0.047161467373371124,
0.21422064304351807,
0.06321150809526443,
-0.09143578261137009,
-0.02580295503139496,
-0.03329068049788475,
0.04440530762076378,
-0.06494591385126114,
0.10175396502017975,
0.027680888772010803,
0.05365157872438431,
0.023984158411622047,
-0.032899804413318634,
0.03856229409575462,
-0.08387355506420135,
-0.10054522752761841,
-0.05070185661315918,
-0.08565592765808105,
0.039397966116666794,
0.05604296177625656,
0.05994046851992607,
-0.10856401175260544,
-0.09017187356948853,
0.04204317927360535,
0.0943065956234932,
-0.07395226508378983,
0.028962817043066025,
-0.09000826627016068,
0.11608705669641495,
-0.08325600624084473,
-0.02390553615987301,
-0.1791052222251892,
-0.04241684824228287,
0.040629271417856216,
-0.01629319041967392,
-0.006912850774824619,
-0.048891667276620865,
0.07074255496263504,
0.08783093094825745,
-0.05235742777585983,
-0.05203414335846901,
-0.05522594600915909,
0.008213330060243607,
-0.1105295866727829,
-0.1776295155286789,
-0.08015653491020203,
-0.0380605012178421,
0.14977632462978363,
-0.15268713235855103,
0.022225622087717056,
0.061116840690374374,
0.12500962615013123,
0.059797611087560654,
-0.04723487049341202,
-0.007436409126967192,
0.021452799439430237,
-0.05571167171001434,
-0.08678608387708664,
0.05719248577952385,
0.03528200834989548,
-0.07155010849237442,
-0.019102152436971664,
-0.10049699991941452,
0.1498662531375885,
0.13190734386444092,
-0.0015375686343759298,
-0.04512632265686989,
-0.01160994078963995,
-0.06610778719186783,
-0.030441991984844208,
-0.04081778973340988,
0.018804829567670822,
0.10142559558153152,
0.01744643971323967,
0.14419154822826385,
-0.09178037941455841,
-0.036961425095796585,
0.053544968366622925,
-0.028453968465328217,
-0.0331195667386055,
0.07361359149217606,
0.02190210297703743,
-0.14263916015625,
0.15015269815921783,
0.14882412552833557,
-0.04894813522696495,
0.12402692437171936,
-0.036747027188539505,
-0.0615357980132103,
-0.044876549392938614,
-0.037704430520534515,
0.014213677495718002,
0.1403394341468811,
-0.08333314955234528,
-0.005919712595641613,
0.05630137771368027,
0.019257593899965286,
-0.007085299585014582,
-0.18072617053985596,
0.0006808378966525197,
0.03521978110074997,
-0.04604950174689293,
-0.02278841845691204,
-0.014470276422798634,
0.0007941273506730795,
0.09172741323709488,
0.019804218783974648,
-0.07102026045322418,
0.05166372284293175,
0.010580740869045258,
-0.05623085796833038,
0.16415521502494812,
-0.07910753041505814,
-0.19727325439453125,
-0.11776646971702576,
-0.08754957467317581,
-0.10735819488763809,
0.013021474704146385,
0.06737184524536133,
-0.050448641180992126,
-0.04938974231481552,
-0.10206248611211777,
-0.04453543201088905,
0.021900271996855736,
0.02429220825433731,
0.05370878055691719,
-0.008031168952584267,
0.08405356109142303,
-0.09224440902471542,
-0.03291117399930954,
-0.014789600856602192,
0.018657125532627106,
0.06682770699262619,
0.018715238198637962,
0.11069032549858093,
0.08161229640245438,
-0.02844928205013275,
0.05646483600139618,
-0.01682325080037117,
0.2655041813850403,
-0.06765957176685333,
-0.006789656355977058,
0.13932959735393524,
-0.013368978165090084,
0.08428963273763657,
0.1268712729215622,
0.04151352122426033,
-0.09555158019065857,
-0.013173693791031837,
-0.00024822441628202796,
-0.05275752767920494,
-0.1537386178970337,
-0.04163756221532822,
-0.045641690492630005,
-0.0021682933438569307,
0.13930507004261017,
0.03818075731396675,
0.02474883571267128,
0.07807637751102448,
0.020041609182953835,
0.05664918199181557,
-0.017527885735034943,
0.10406769812107086,
0.08156019449234009,
0.06448414921760559,
0.13368317484855652,
-0.03653626888990402,
-0.019387291744351387,
0.05662747099995613,
0.04215037450194359,
0.20423758029937744,
-0.02541770040988922,
0.14701254665851593,
0.02641657367348671,
0.19307395815849304,
0.017521383240818977,
0.0728468969464302,
-0.014410126954317093,
0.0009393728105351329,
-0.019274147227406502,
-0.04702805355191231,
-0.06427313387393951,
0.03288881108164787,
-0.016649875789880753,
0.05632343888282776,
-0.09356046468019485,
0.039105307310819626,
0.059592608362436295,
0.30666422843933105,
0.06539998203516006,
-0.4122132360935211,
-0.09836560487747192,
0.012291035614907742,
0.0009865236934274435,
-0.055195607244968414,
-0.0072626820765435696,
0.0979013666510582,
-0.09949664771556854,
0.08215389400720596,
-0.09418605268001556,
0.08514873683452606,
-0.0845724418759346,
0.020298872143030167,
0.07689075917005539,
0.056060366332530975,
0.013226890936493874,
0.05964293330907822,
-0.21821673214435577,
0.24971400201320648,
0.018467964604496956,
0.04422129690647125,
-0.08908867090940475,
0.010060982778668404,
0.033364444971084595,
0.059161990880966187,
0.08554306626319885,
0.005977867171168327,
-0.09024009108543396,
-0.18880225718021393,
-0.1258762925863266,
0.0005427713040262461,
0.06169470399618149,
-0.036699384450912476,
0.09451829642057419,
-0.018175894394516945,
-0.012127134948968887,
0.021332256495952606,
0.0005201056483201683,
-0.03501477465033531,
-0.103630930185318,
0.02024604007601738,
0.034688886255025864,
-0.012138742953538895,
-0.06473075598478317,
-0.11475593596696854,
-0.03554871678352356,
0.16192500293254852,
0.05505121126770973,
-0.07524240761995316,
-0.1408705860376358,
0.07218684256076813,
0.07781627029180527,
-0.0855332687497139,
0.039305757731199265,
-0.016779718920588493,
0.14986851811408997,
0.020937321707606316,
-0.08943228423595428,
0.10178638249635696,
-0.05869165062904358,
-0.17860572040081024,
-0.041185978800058365,
0.09929849207401276,
0.007366738747805357,
0.05263189971446991,
0.004192214459180832,
0.06014186516404152,
-0.035002902150154114,
-0.0584394596517086,
0.06681792438030243,
-0.0073097143322229385,
0.10614755749702454,
-0.014883637428283691,
0.00864378735423088,
0.029195772483944893,
-0.04613848030567169,
0.00009839441918302327,
0.1684505194425583,
0.24079899489879608,
-0.10403203964233398,
0.060546230524778366,
0.03012177161872387,
-0.030879246070981026,
-0.18261685967445374,
0.010319743305444717,
0.07656802982091904,
-0.0001991603203350678,
0.04173794388771057,
-0.16060468554496765,
0.055176541209220886,
0.10514935851097107,
-0.043303944170475006,
0.08152011036872864,
-0.2768779397010803,
-0.11840421706438065,
0.0923023670911789,
0.138164222240448,
0.0691317543387413,
-0.13107311725616455,
-0.04327763617038727,
-0.041234806180000305,
-0.17335952818393707,
0.13665583729743958,
-0.05704028159379959,
0.11501350998878479,
-0.039327461272478104,
0.08051838725805283,
0.014901114627718925,
-0.056082114577293396,
0.14561402797698975,
0.005515002179890871,
0.08661133795976639,
-0.07185279577970505,
-0.0014093852369114757,
0.10643326491117477,
-0.10252601653337479,
0.07192501425743103,
-0.0869532898068428,
0.06187514215707779,
-0.10810889303684235,
-0.0037693935446441174,
-0.07425615191459656,
0.013987713493406773,
-0.013397954404354095,
-0.048907287418842316,
-0.0448833703994751,
0.03488645330071449,
0.06301422417163849,
-0.018155096098780632,
0.20988906919956207,
0.06445588916540146,
0.0862940326333046,
0.1728745847940445,
0.05397673323750496,
-0.10576145350933075,
-0.09408308565616608,
-0.04430058225989342,
-0.029343122616410255,
0.059755485504865646,
-0.13705183565616608,
0.053009506314992905,
0.12004052102565765,
0.013443393632769585,
0.1280696988105774,
0.05582417547702789,
-0.030783196911215782,
0.035687193274497986,
0.06206676363945007,
-0.1721130907535553,
-0.08640376478433609,
-0.010029762983322144,
0.030597826465964317,
-0.13003188371658325,
0.045725177973508835,
0.12137939780950546,
-0.0593545101583004,
-0.014887568540871143,
-0.004342919681221247,
0.03682979568839073,
-0.009421703405678272,
0.15946903824806213,
0.047883741557598114,
0.05509158596396446,
-0.11808934807777405,
0.11348052322864532,
0.057328153401613235,
-0.0728185623884201,
0.032391179352998734,
0.05030714347958565,
-0.10392948985099792,
-0.021465230733156204,
0.031419817358255386,
0.14932547509670258,
-0.06275127828121185,
-0.045640427619218826,
-0.13568063080310822,
-0.091814324259758,
0.06645428389310837,
0.07967224717140198,
0.0933644250035286,
0.01663324609398842,
-0.03539150580763817,
-0.013165266253054142,
-0.10855977237224579,
0.10982618480920792,
0.04324139654636383,
0.09105362743139267,
-0.17992232739925385,
0.054193608462810516,
-0.0015555275604128838,
0.07246194779872894,
-0.021836427971720695,
-0.00042325531831011176,
-0.08788467198610306,
0.003508437890559435,
-0.10813499987125397,
0.02464236691594124,
-0.052905477583408356,
0.006243168842047453,
-0.02064651995897293,
-0.0580705925822258,
-0.06364380568265915,
0.024784497916698456,
-0.11918067932128906,
-0.053243763744831085,
0.02146504819393158,
0.031834639608860016,
-0.12016978859901428,
-0.04392008110880852,
0.020345089957118034,
-0.08986733108758926,
0.09774119406938553,
0.06029992923140526,
-0.008077923208475113,
0.00773270707577467,
0.0036002967972308397,
-0.02274298295378685,
0.0666942149400711,
0.007561622653156519,
0.08597277849912643,
-0.1152612566947937,
-0.0221384409815073,
0.01634843461215496,
-0.004547150805592537,
0.017726117745041847,
0.15840598940849304,
-0.12086156010627747,
-0.0003179961640853435,
-0.014678256586194038,
-0.06600851565599442,
-0.06344839930534363,
0.06893838196992874,
0.10903503000736237,
0.02346671372652054,
0.21181334555149078,
-0.054371658712625504,
0.015811823308467865,
-0.20995409786701202,
-0.011581460013985634,
0.005185890011489391,
-0.1388559192419052,
-0.10497695952653885,
-0.03237957879900932,
0.06376256048679352,
-0.07031478732824326,
0.11765085160732269,
0.03525954857468605,
0.02161695808172226,
0.02906344085931778,
0.025029366835951805,
-0.0031726681627333164,
0.013450034894049168,
0.16309522092342377,
0.014403261244297028,
-0.028442582115530968,
0.12852592766284943,
0.028986822813749313,
0.09334488213062286,
0.11778779327869415,
0.17672526836395264,
0.11388354748487473,
0.04729508236050606,
0.09055530279874802,
0.05202596262097359,
-0.025968270376324654,
-0.22174733877182007,
0.03601896017789841,
-0.03978736698627472,
0.1488790065050125,
-0.0030294209718704224,
0.15902450680732727,
0.0920415073633194,
-0.18360793590545654,
0.040488436818122864,
-0.03700747340917587,
-0.0790853351354599,
-0.08454839885234833,
-0.12155362963676453,
-0.10311590880155563,
-0.15089921653270721,
0.002945262473076582,
-0.1040843203663826,
0.023338600993156433,
0.11202728003263474,
-0.008582104928791523,
-0.009919910691678524,
0.116677425801754,
-0.02631515823304653,
0.026041926816105843,
0.03836518153548241,
0.00608045794069767,
-0.059937771409749985,
-0.044151950627565384,
-0.08065995573997498,
0.014101422391831875,
0.032313644886016846,
0.05599058046936989,
-0.03235676884651184,
-0.007023791316896677,
0.03841041401028633,
-0.010091220960021019,
-0.12353866547346115,
0.01347822230309248,
0.005028906278312206,
0.05164548382163048,
0.0008541525457985699,
0.012780209071934223,
0.03201600909233093,
-0.015217483974993229,
0.19341084361076355,
-0.07325411587953568,
-0.027416478842496872,
-0.1228807121515274,
0.17896701395511627,
0.0026140701957046986,
-0.04994320869445801,
0.05295133590698242,
-0.09137362241744995,
-0.020702529698610306,
0.15485265851020813,
0.1892986297607422,
-0.07158271223306656,
-0.016520513221621513,
-0.017527583986520767,
-0.013897030614316463,
-0.022615507245063782,
0.09919055551290512,
0.0991419330239296,
-0.0069245584309101105,
-0.0751221776008606,
-0.028980256989598274,
-0.06606413424015045,
-0.034512959420681,
-0.03850788250565529,
0.06925404816865921,
-0.004570751916617155,
0.0070457919500768185,
-0.07483471930027008,
0.04310325160622597,
-0.02210995741188526,
-0.06085818260908127,
0.06226903945207596,
-0.21256737411022186,
-0.17790570855140686,
0.006773421075195074,
0.07538973540067673,
0.0015973751433193684,
0.0461571104824543,
-0.009913075715303421,
0.018662674352526665,
0.07594356685876846,
-0.02225665934383869,
-0.08672447502613068,
-0.09593749046325684,
0.10812120139598846,
-0.13375911116600037,
0.2528570294380188,
-0.03883460536599159,
0.03583916276693344,
0.12127543240785599,
0.041867125779390335,
-0.1335451751947403,
0.03351692110300064,
0.03981999680399895,
-0.032485269010066986,
0.00548918079584837,
0.14240407943725586,
-0.03740047290921211,
0.07958021014928818,
0.0458458811044693,
-0.1027912050485611,
-0.03964604437351227,
-0.04966754838824272,
-0.011354409158229828,
-0.024445757269859314,
-0.054610975086688995,
-0.036348532885313034,
0.13227923214435577,
0.17175258696079254,
-0.042096637189388275,
-0.023690558969974518,
-0.06475082784891129,
0.030860183760523796,
0.07729368656873703,
-0.03295742720365524,
-0.052064236253499985,
-0.23603148758411407,
0.0024359924718737602,
0.05229694023728371,
-0.013576737605035305,
-0.20701472461223602,
-0.110505111515522,
0.0060418094508349895,
-0.05801977962255478,
-0.07628542929887772,
0.09231390058994293,
0.06255589425563812,
0.035103797912597656,
-0.06320928037166595,
0.038133736699819565,
-0.07872021943330765,
0.14179112017154694,
-0.14508864283561707,
-0.07859515398740768
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 58
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "58", "results": []}]} | text-classification | santiadavani/58 | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:18:32+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# 58
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# 58\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# 58\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
68,
28,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# 58\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0### Training results### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.10632430016994476,
0.08376043289899826,
-0.0013310388894751668,
0.08062975108623505,
0.16873915493488312,
0.014985418878495693,
0.1333063691854477,
0.09906605631113052,
-0.12141618877649307,
0.04399152100086212,
0.06968338787555695,
0.08868297934532166,
0.014544209465384483,
0.11516498029232025,
-0.05875144526362419,
-0.23377349972724915,
0.019322676584124565,
0.007634728215634823,
-0.10558457672595978,
0.09662479907274246,
0.11831335723400116,
-0.10908760130405426,
0.0676039531826973,
0.010956608690321445,
-0.17963089048862457,
0.026258505880832672,
-0.011339510791003704,
-0.05215458944439888,
0.10179828852415085,
0.0283953920006752,
0.12551827728748322,
0.01982267014682293,
0.12389350682497025,
-0.20138758420944214,
-0.0009590088739059865,
0.08799352496862411,
0.03487662971019745,
0.06959696114063263,
0.021884627640247345,
-0.01892954111099243,
0.07664072513580322,
-0.11193474382162094,
0.09979013353586197,
0.0423414520919323,
-0.08667174726724625,
-0.18142718076705933,
-0.10052748769521713,
0.06912969797849655,
0.10134491324424744,
0.1034068763256073,
0.002730501350015402,
0.1258474737405777,
-0.09511692821979523,
0.07324002683162689,
0.18818150460720062,
-0.26589417457580566,
-0.07542672008275986,
0.07308456301689148,
0.048225391656160355,
0.05455569177865982,
-0.1007329449057579,
-0.01228679995983839,
0.08472016453742981,
0.03564184531569481,
0.09648970514535904,
-0.014059693552553654,
-0.09892170131206512,
-0.013227573595941067,
-0.13032618165016174,
0.003635251196101308,
0.18846306204795837,
0.04206058382987976,
-0.0711125060915947,
-0.07131648808717728,
-0.05316224694252014,
-0.08069198578596115,
-0.023901041597127914,
-0.048735592514276505,
0.053400758653879166,
-0.03170222043991089,
-0.06921982020139694,
-0.052489615976810455,
-0.08737581968307495,
-0.06743745505809784,
0.002178560709580779,
0.13915875554084778,
0.03602847829461098,
0.0065796514973044395,
-0.044132959097623825,
0.11273759603500366,
-0.03011913038790226,
-0.12338399887084961,
-0.02430129051208496,
-0.01741299405694008,
-0.02917981706559658,
-0.07180623710155487,
-0.06901510059833527,
-0.012404965236783028,
0.010786086320877075,
0.19491775333881378,
-0.08733119815587997,
0.058671582490205765,
0.0038094527553766966,
0.012112436816096306,
-0.048856042325496674,
0.14290851354599,
-0.03547568991780281,
-0.02844950370490551,
0.012215184047818184,
0.09289421886205673,
0.018944287672638893,
-0.006516564171761274,
-0.08549907058477402,
-0.0016013085842132568,
0.08036082237958908,
0.05060311406850815,
-0.06473933160305023,
0.04298798367381096,
-0.03460439294576645,
-0.02288884110748768,
0.0019621194805949926,
-0.11358334124088287,
0.026268206536769867,
-0.009869867004454136,
-0.07714682817459106,
-0.004143154714256525,
0.04716916382312775,
0.02270396612584591,
0.00018402714340481907,
0.11685904860496521,
-0.09052851796150208,
0.003066025674343109,
-0.11099428683519363,
-0.07964669913053513,
-0.0014802587684243917,
-0.06268033385276794,
0.002886590315029025,
-0.08803248405456543,
-0.21907997131347656,
-0.03735936060547829,
0.056706514209508896,
-0.024254780262708664,
-0.026633329689502716,
-0.050456926226615906,
-0.08515461534261703,
0.01340435165911913,
-0.012282581999897957,
0.09855952113866806,
-0.049591973423957825,
0.07290840148925781,
0.035271529108285904,
0.02521033026278019,
-0.028772257268428802,
0.03554924577474594,
-0.09834246337413788,
0.03256252780556679,
-0.1479577124118805,
0.06384250521659851,
-0.09238181263208389,
0.05888120085000992,
-0.08404278755187988,
-0.09930568188428879,
-0.0009018696728162467,
0.0005449869204312563,
0.0672178789973259,
0.1208476722240448,
-0.1885015070438385,
-0.03823943808674812,
0.13254716992378235,
-0.09465458244085312,
-0.10917840898036957,
0.07874768227338791,
-0.0561155341565609,
0.07988554239273071,
0.07087241113185883,
0.11863812804222107,
0.09998998045921326,
-0.1180521547794342,
-0.02823018468916416,
0.003916271962225437,
0.07906985282897949,
0.026133401319384575,
0.0378902442753315,
-0.021500831469893456,
-0.0025396104902029037,
0.024461975321173668,
-0.07856395095586777,
-0.017341580241918564,
-0.09208086133003235,
-0.08739609271287918,
-0.0656285509467125,
-0.10456008464097977,
0.05711434409022331,
0.03265629708766937,
0.055503230541944504,
-0.08339352905750275,
-0.10426010936498642,
0.15912184119224548,
0.13048523664474487,
-0.060498930513858795,
0.02363893948495388,
-0.07407814264297485,
0.052946217358112335,
-0.0032571186311542988,
-0.027564765885472298,
-0.2030455321073532,
-0.10947815328836441,
0.01116043608635664,
-0.01874963566660881,
0.02567804418504238,
-0.005741868633776903,
0.05598997324705124,
0.07883820682764053,
-0.06967529654502869,
-0.022645995020866394,
-0.09145087748765945,
0.0071053276769816875,
-0.09291227906942368,
-0.20252840220928192,
-0.04693254828453064,
-0.026433685794472694,
0.17915362119674683,
-0.2427159696817398,
0.043479811400175095,
-0.02743643708527088,
0.1389872133731842,
0.034477584064006805,
-0.032069962471723557,
-0.04836161807179451,
0.06679694354534149,
-0.03746606782078743,
-0.09004855901002884,
0.04188358783721924,
0.011057211086153984,
-0.07746466994285583,
-0.09557422250509262,
-0.13079625368118286,
0.0806603655219078,
0.10751035064458847,
-0.0064460039138793945,
-0.0922747328877449,
0.0007073886226862669,
-0.06101689860224724,
-0.02679603174328804,
-0.06723283976316452,
-0.0034282479900866747,
0.13490687310695648,
-0.00968321505934,
0.13681083917617798,
-0.06496983021497726,
-0.05433259531855583,
-0.005602652207016945,
-0.02478095144033432,
0.008863137103617191,
0.05248906463384628,
0.07951296120882034,
-0.07648129016160965,
0.11608674377202988,
0.12464392930269241,
-0.09070397913455963,
0.14861318469047546,
-0.0532219298183918,
-0.060261256992816925,
-0.011147783137857914,
0.0061484333127737045,
0.003805682761594653,
0.11738912016153336,
-0.10430469363927841,
0.007202553562819958,
0.008172153495252132,
0.02254556678235531,
0.043648820370435715,
-0.18749429285526276,
0.0013397283619269729,
0.023362576961517334,
-0.030298691242933273,
-0.015435351990163326,
-0.0232109185308218,
0.009063010104000568,
0.07846304774284363,
0.00954202190041542,
-0.020340384915471077,
0.03999017924070358,
0.0019914936274290085,
-0.07991838455200195,
0.20955587923526764,
-0.13125410676002502,
-0.11541227251291275,
-0.12200018763542175,
0.010563479736447334,
-0.07470791786909103,
-0.003976047039031982,
0.038434647023677826,
-0.09501189738512039,
-0.0533568300306797,
-0.07777208834886551,
0.003265274688601494,
0.0020168402697890997,
-0.010847574099898338,
0.05067693069577217,
0.020228790119290352,
0.1043553575873375,
-0.14954617619514465,
0.005530208814889193,
-0.022207211703062057,
-0.11068351566791534,
-0.0030203629285097122,
0.04378199577331543,
0.09462730586528778,
0.1377386599779129,
-0.013035722076892853,
0.003106219694018364,
-0.024080542847514153,
0.2413570135831833,
-0.06495224684476852,
-0.02998233400285244,
0.1327710896730423,
0.010050075128674507,
0.04179757833480835,
0.11719124019145966,
0.0498649924993515,
-0.12346407026052475,
0.04595783352851868,
0.09384232014417648,
-0.01528585609048605,
-0.23756273090839386,
-0.043436650186777115,
-0.02965528890490532,
-0.06888715922832489,
0.06953571736812592,
0.03723163902759552,
0.05072549358010292,
0.06050294637680054,
-0.01503757480531931,
0.06307484954595566,
-0.0028689606115221977,
0.09291496127843857,
0.1049480065703392,
0.03554190695285797,
0.12126573175191879,
-0.032923392951488495,
-0.022130519151687622,
0.05907290428876877,
-0.022317960858345032,
0.27792033553123474,
0.000938605866394937,
0.04792866110801697,
0.07663292437791824,
0.1330409049987793,
-0.02450406923890114,
0.05334555357694626,
0.011154500767588615,
-0.026839707046747208,
0.010672706179320812,
-0.06861215084791183,
-0.020412767305970192,
0.030649594962596893,
-0.07875532656908035,
0.07735741883516312,
-0.1173587515950203,
0.038702644407749176,
0.05405274033546448,
0.26920953392982483,
0.034155454486608505,
-0.30215564370155334,
-0.1050439327955246,
0.019157638773322105,
-0.02168426103889942,
-0.06134088709950447,
0.016884878277778625,
0.08471408486366272,
-0.1097395122051239,
0.06559159606695175,
-0.058148182928562164,
0.09949693828821182,
0.01744331419467926,
0.021624673157930374,
0.0640910342335701,
0.12125679850578308,
-0.00937006063759327,
0.066970594227314,
-0.262323796749115,
0.2081647366285324,
0.019933469593524933,
0.14061559736728668,
-0.028697660192847252,
0.03150582313537598,
0.042032502591609955,
0.1474306732416153,
0.06721007823944092,
-0.011454517021775246,
-0.02236592210829258,
-0.1676708459854126,
-0.027204938232898712,
0.035323627293109894,
0.12294115871191025,
-0.04143182933330536,
0.1007358729839325,
-0.04869828373193741,
0.018307209014892578,
0.07056660205125809,
-0.049732740968465805,
-0.20828938484191895,
-0.11654529720544815,
-0.002162594348192215,
0.0007907635881565511,
0.0041277529671788216,
-0.10170025378465652,
-0.10167235136032104,
-0.03169788792729378,
0.16940738260746002,
-0.03440975025296211,
-0.04387631639838219,
-0.13012607395648956,
0.06206483393907547,
0.1003868356347084,
-0.0487334206700325,
0.04281187057495117,
0.021184533834457397,
0.12448131293058395,
0.028249530121684074,
-0.07998722046613693,
0.05569762736558914,
-0.09195733070373535,
-0.1843319833278656,
-0.05020938441157341,
0.10338547080755234,
0.054880570620298386,
0.026857875287532806,
0.0010980608640238643,
0.014662777073681355,
0.01798895187675953,
-0.09547311812639236,
-0.026223106309771538,
0.08263718336820602,
0.08432867377996445,
0.059132449328899384,
-0.09457886219024658,
-0.007583266124129295,
-0.042091693729162216,
-0.012118156999349594,
0.10034827142953873,
0.22496351599693298,
-0.07915917038917542,
0.026503488421440125,
0.07514365017414093,
-0.08793682605028152,
-0.1829657256603241,
0.10074294358491898,
0.09757836163043976,
0.0046389163471758366,
0.0342751145362854,
-0.1918891817331314,
0.13988403975963593,
0.12149292975664139,
-0.026535440236330032,
0.09070233255624771,
-0.29246124625205994,
-0.14971348643302917,
0.09512563049793243,
0.10761814564466476,
0.0564463846385479,
-0.14043673872947693,
-0.03390820696949959,
-0.06119367852807045,
-0.14043399691581726,
0.12598058581352234,
-0.15060997009277344,
0.09879504144191742,
0.007716695312410593,
0.06846416741609573,
0.011634987778961658,
-0.028334466740489006,
0.15637153387069702,
0.02480405569076538,
0.11693762242794037,
-0.047582414001226425,
0.025416092947125435,
0.09786291420459747,
-0.0704219713807106,
0.025592397898435593,
-0.042376622557640076,
0.07257113605737686,
-0.08688904345035553,
-0.02557356096804142,
-0.06470014154911041,
0.077933169901371,
-0.06990495324134827,
-0.07367502152919769,
-0.0521065779030323,
0.050017375499010086,
0.04074262082576752,
-0.030365224927663803,
0.09105116128921509,
0.009686417877674103,
0.1525733321905136,
0.08804824203252792,
0.11073670536279678,
-0.05881460756063461,
-0.05633991211652756,
0.01237400434911251,
-0.030229443684220314,
0.0824083462357521,
-0.14764799177646637,
0.036404337733983994,
0.11407659947872162,
0.044740356504917145,
0.14624354243278503,
0.06663703173398972,
-0.04120359569787979,
0.00996331125497818,
0.05786804109811783,
-0.11363127082586288,
-0.11230158805847168,
-0.008567063137888908,
-0.03274155035614967,
-0.12441876530647278,
0.06850390881299973,
0.11896292120218277,
-0.0736255869269371,
-0.0009258922655135393,
-0.015939874574542046,
0.00025657546939328313,
-0.052692681550979614,
0.18186374008655548,
0.04413030296564102,
0.060470398515462875,
-0.08344732224941254,
0.12373737245798111,
0.04822419956326485,
-0.06115879490971565,
0.022980844601988792,
0.03899436816573143,
-0.0909992903470993,
-0.027643276378512383,
0.04513051360845566,
0.17031601071357727,
-0.0679783970117569,
-0.06191341578960419,
-0.11359120160341263,
-0.10397335886955261,
0.035706792026758194,
0.1574740707874298,
0.07134904712438583,
-0.0006271533202379942,
-0.034973450005054474,
0.05584106221795082,
-0.14617471396923065,
0.08309142291545868,
0.044679075479507446,
0.08973381668329239,
-0.16543638706207275,
0.13368119299411774,
0.020568322390317917,
0.004759547300636768,
-0.015839342027902603,
0.023061921820044518,
-0.10162424296140671,
-0.019889649003744125,
-0.18435215950012207,
-0.02595280483365059,
-0.020287437364459038,
0.009407677687704563,
-0.00025207988801412284,
-0.03678009286522865,
-0.06151329725980759,
0.05796108394861221,
-0.07140572369098663,
-0.04869959503412247,
0.03447636216878891,
0.04916280135512352,
-0.14443464577198029,
0.0020035046618431807,
0.0195502657443285,
-0.10093317925930023,
0.06521781533956528,
0.05503857508301735,
0.023757329210639,
0.0602874681353569,
-0.14691689610481262,
-0.0158053170889616,
0.0408327616751194,
0.01933390647172928,
0.057313986122608185,
-0.081729456782341,
-0.015629203990101814,
-0.016751650720834732,
0.07559400796890259,
0.016700953245162964,
0.06593675911426544,
-0.12043490260839462,
-0.02391205169260502,
-0.034786470234394073,
-0.04450127109885216,
-0.05458379164338112,
0.03343591466546059,
0.11258745193481445,
0.040148839354515076,
0.1995326727628708,
-0.09070982038974762,
0.008368518203496933,
-0.18675023317337036,
-0.025227710604667664,
-0.01032810565084219,
-0.040664710104465485,
-0.09012070298194885,
-0.03590617701411247,
0.05908767133951187,
-0.0691462904214859,
0.1176743134856224,
-0.028011241927742958,
0.09976955503225327,
0.04477196931838989,
-0.05484714359045029,
-0.017523091286420822,
0.022950392216444016,
0.22515124082565308,
0.060967300087213516,
0.002626128029078245,
0.0446338914334774,
0.014948558993637562,
0.07875435799360275,
0.030169708654284477,
0.206746906042099,
0.1498807966709137,
-0.08832670003175735,
0.07905177026987076,
0.05296991765499115,
-0.0927424430847168,
-0.14297045767307281,
0.07676029950380325,
-0.02234361320734024,
0.09607052057981491,
-0.05569720268249512,
0.12728554010391235,
0.11979320645332336,
-0.16873124241828918,
0.03815329074859619,
-0.07285323739051819,
-0.10125263035297394,
-0.13018153607845306,
-0.0057907733134925365,
-0.07728757709264755,
-0.1571996957063675,
0.01936875469982624,
-0.14215941727161407,
0.028679242357611656,
0.09864120930433273,
-0.00027339698863215744,
0.0013644433347508311,
0.17548896372318268,
-0.055179089307785034,
0.016472268849611282,
0.05488002300262451,
-0.006666706874966621,
-0.022403426468372345,
-0.08240565657615662,
-0.08269576728343964,
0.02851887419819832,
-0.006594544742256403,
0.04754774644970894,
-0.052248403429985046,
-0.02564619854092598,
0.03486403450369835,
-0.003202072810381651,
-0.057601265609264374,
0.03670019283890724,
0.034508801996707916,
0.03657350689172745,
0.05156361311674118,
0.030152762308716774,
-0.010603711009025574,
-0.01827552728354931,
0.29646435379981995,
-0.09862782061100006,
-0.11471782624721527,
-0.15243472158908844,
0.23499080538749695,
0.04795175790786743,
0.0014660151209682226,
0.049161676317453384,
-0.11917326599359512,
-0.004409330897033215,
0.16676826775074005,
0.1478007733821869,
-0.06331122666597366,
-0.015946950763463974,
-0.022824542596936226,
-0.02229749970138073,
-0.0789668932557106,
0.12432248145341873,
0.11804518103599548,
0.04051744192838669,
-0.04374704137444496,
-0.03253358229994774,
-0.0030542423482984304,
-0.025175603106617928,
-0.07426364719867706,
0.08357742428779602,
0.0006771155167371035,
-0.009487474337220192,
-0.031188325956463814,
0.06931586563587189,
-0.01150433998554945,
-0.14401382207870483,
0.06560029089450836,
-0.14363157749176025,
-0.1658901423215866,
-0.0340343713760376,
0.07672588527202606,
-0.03280129283666611,
0.055958859622478485,
-0.01851586252450943,
-0.029347123578190804,
0.14180368185043335,
-0.026172727346420288,
-0.025454817339777946,
-0.12361860275268555,
0.08672722429037094,
-0.06286562234163284,
0.2357075810432434,
-0.013673357665538788,
0.04985558241605759,
0.11650336533784866,
0.030927835032343864,
-0.1014912948012352,
0.05542576313018799,
0.055691592395305634,
-0.07593544572591782,
0.02437596209347248,
0.11543170362710953,
-0.057048432528972626,
0.11356354504823685,
0.03801541030406952,
-0.18326163291931152,
0.0070986999198794365,
0.0030850551556795835,
-0.06726518273353577,
-0.09198780357837677,
-0.007598401978611946,
-0.08143912255764008,
0.13191452622413635,
0.2023448944091797,
-0.040554460138082504,
0.018884774297475815,
-0.06620561331510544,
0.05887870863080025,
0.05873207375407219,
0.08076854050159454,
-0.03663823381066322,
-0.24854104220867157,
0.041906800121068954,
0.04643175005912781,
-0.006878936197608709,
-0.2503490149974823,
-0.08024197071790695,
0.05289408192038536,
-0.04592717066407204,
-0.0573992021381855,
0.1012055054306984,
0.09224620461463928,
0.03717901557683945,
-0.0448731891810894,
-0.1258472204208374,
-0.07550729066133499,
0.1679271012544632,
-0.13882042467594147,
-0.0718119740486145
] |
null | null | transformers |
## MiquMaid v2
Check out our blogpost about this model series [Here!](https://ikaridevgit.github.io/index.html?blog=blogid-6&bo=true#Miqu-base) - Join our Discord server [Here!](https://discord.gg/Bb8pRUXy3Z)
<center>[<a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B">V2-70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B-DPO">V2-70B-DPO</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B">V2-2x70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B-DPO">V2-2x70B-DPO</a>]
</br>
<div style="width: 100%;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/1ziZ_5Rl7bsQKFrgH6ZCf.png" style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca **prompting format**
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: [FP16](https://huggingface.co/NeverSleep/MiquMaid-v2-70B) - [GGUF](https://huggingface.co/NeverSleep/MiquMaid-v2-70B-GGUF)
## Training data used:
- [Aesir datasets](https://huggingface.co/MinervaAI)
- [NoRobots](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt)
- [limarp](https://huggingface.co/datasets/lemonilia/LimaRP)
- [toxic-dpo-v0.1-sharegpt](https://huggingface.co/datasets/Undi95/toxic-dpo-v0.1-sharegpt)
- [ToxicQAFinal](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAFinal)
### Custom format:
```
### Instruction:
{system prompt}
### Input:
{input}
### Response:
{reply}
```
## Others
Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).
IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | text-generation | LoneStriker/MiquMaid-v2-70B-3.5bpw-h6-exl2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T01:22:50+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## MiquMaid v2
Check out our blogpost about this model series Here! - Join our Discord server Here!
<center>[<a href="URL - <a href="URL - <a href="URL - <a href="URL
</br>
<div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: FP16 - GGUF
## Training data used:
- Aesir datasets
- NoRobots
- limarp
- toxic-dpo-v0.1-sharegpt
- ToxicQAFinal
### Custom format:
## Others
Undi: If you want to support us, you can here.
IkariDev: Visit my retro/neocities style website please kek | [
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
75,
121,
11,
30,
40,
5,
32
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.## Credits:\n- Undi\n- IkariDev## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal### Custom format:## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
-0.09447834640741348,
0.17205014824867249,
-0.005602731369435787,
0.01779203675687313,
0.11820747703313828,
0.045264896005392075,
0.11447285860776901,
0.15961068868637085,
0.06829394400119781,
0.05906902998685837,
0.0005873226327821612,
0.11407624930143356,
0.07548845559358597,
0.22948826849460602,
-0.006628913804888725,
-0.14427904784679413,
0.046850357204675674,
-0.026289891451597214,
-0.02635573409497738,
0.09569915384054184,
0.07466454803943634,
-0.04618130251765251,
0.0709284171462059,
0.010442404076457024,
-0.10720876604318619,
-0.017348533496260643,
0.0019323929445818067,
-0.05718233436346054,
0.04780259355902672,
0.04367207735776901,
0.0479082316160202,
0.05087536945939064,
0.00845402292907238,
-0.22662657499313354,
0.047140758484601974,
0.07308577746152878,
-0.025127466768026352,
0.07861552387475967,
0.10886233299970627,
-0.04211974889039993,
0.02646409347653389,
-0.03574787452816963,
-0.02210289053618908,
0.09350186586380005,
-0.11214648932218552,
-0.12319593131542206,
-0.11320719122886658,
0.13006889820098877,
0.06314875930547714,
0.08198896050453186,
0.0033554788678884506,
0.1101357564330101,
-0.07631256431341171,
0.07790177315473557,
0.20335930585861206,
-0.16871041059494019,
-0.02322721853852272,
0.05624805763363838,
-0.015333202667534351,
-0.05565005913376808,
-0.09832000732421875,
0.011083890683948994,
0.010926350019872189,
-0.019533375278115273,
-0.0038207839243113995,
-0.041167840361595154,
0.004284780006855726,
-0.06099749729037285,
-0.059463758021593094,
-0.016264086589217186,
0.24300093948841095,
0.0361378937959671,
-0.07370094209909439,
-0.0026136080268770456,
-0.006493517197668552,
0.11463554203510284,
-0.05098545923829079,
0.030949248000979424,
0.005614427383989096,
-0.0010702924337238073,
-0.0032837465405464172,
-0.04595240205526352,
-0.10275456309318542,
-0.05733378976583481,
-0.014142698608338833,
0.14566513895988464,
0.017552156001329422,
0.00008401479135500267,
-0.004768410697579384,
0.051651932299137115,
-0.10471507161855698,
-0.12298901379108429,
-0.06133059412240982,
-0.10231878608465195,
-0.005009785760194063,
-0.042668018490076065,
-0.022182224318385124,
-0.06640303134918213,
0.12371482700109482,
0.1403876692056656,
-0.04801563546061516,
-0.0030525391921401024,
-0.025033647194504738,
0.00783479306846857,
0.005412905476987362,
-0.00017629309149924666,
-0.07161558419466019,
-0.023959118872880936,
0.07290422171354294,
0.025751972571015358,
0.004980665165930986,
0.010289043188095093,
-0.044097792357206345,
-0.07064660638570786,
-0.04732796177268028,
0.05287690833210945,
0.07054515182971954,
0.06856327503919601,
-0.07649759203195572,
-0.047711774706840515,
0.22618921101093292,
-0.10658138245344162,
0.029063958674669266,
0.05863291397690773,
-0.007088409271091223,
0.10424129664897919,
0.06771936267614365,
-0.0006956448778510094,
-0.06505299359560013,
0.016184480860829353,
-0.041465580463409424,
0.03125211223959923,
-0.08675958216190338,
-0.05394180864095688,
0.0855826810002327,
0.0812700167298317,
-0.03331775963306427,
-0.1366315633058548,
-0.10328203439712524,
-0.01740688644349575,
0.02815520204603672,
-0.023310357704758644,
0.0012498353607952595,
0.04892998933792114,
-0.05491432547569275,
0.01405452098697424,
0.01705477572977543,
0.00629244651645422,
-0.05887370929121971,
0.07736124843358994,
0.022486159577965736,
0.09428157657384872,
0.019443463534116745,
0.025946028530597687,
-0.035123471170663834,
0.002149750478565693,
-0.23019294440746307,
0.05012257769703865,
-0.10595361143350601,
0.0038321600295603275,
-0.0922209694981575,
0.0014835012843832374,
-0.027800843119621277,
-0.009975400753319263,
0.0055687217973172665,
0.20525269210338593,
-0.14585432410240173,
-0.05596565082669258,
0.304247111082077,
-0.15955102443695068,
-0.09778694808483124,
0.09222670644521713,
0.03642375022172928,
-0.07440096139907837,
0.06239297613501549,
0.08249494433403015,
0.1056317463517189,
-0.16265460848808289,
-0.09710903465747833,
-0.011078423820436,
-0.022652560845017433,
-0.024000728502869606,
0.0878278836607933,
-0.018813995644450188,
0.03245491161942482,
0.019763432443141937,
-0.03379102423787117,
0.07007033377885818,
-0.025310136377811432,
-0.022386055439710617,
-0.03589578717947006,
-0.06099054589867592,
0.05183964595198631,
-0.002879094798117876,
-0.0388391874730587,
-0.006428318098187447,
-0.04584600031375885,
-0.06035709008574486,
0.13202428817749023,
-0.004858740605413914,
-0.020473629236221313,
-0.07851582020521164,
0.09554000943899155,
-0.05498090013861656,
0.03728895261883736,
-0.13830018043518066,
-0.06243045628070831,
0.0036350893788039684,
-0.0796012431383133,
0.02157106250524521,
-0.0041148848831653595,
0.05950147658586502,
0.038105957210063934,
-0.04352330043911934,
-0.028907326981425285,
-0.0057363444939255714,
0.004301073960959911,
-0.025426069274544716,
-0.1666073054075241,
-0.0007695230888202786,
-0.0551750548183918,
0.1374220848083496,
-0.16868118941783905,
0.05043652653694153,
0.05925111472606659,
0.16357283294200897,
0.03616755083203316,
-0.031011521816253662,
0.11654403805732727,
-0.03804580122232437,
-0.006411012262105942,
-0.03725241497159004,
0.0044607375748455524,
0.002538213739171624,
-0.011939228512346745,
0.10659566521644592,
-0.06065728887915611,
0.054277852177619934,
0.12642189860343933,
-0.01595868356525898,
-0.05425528809428215,
-0.06506265699863434,
-0.01521784346550703,
-0.006736948620527983,
-0.048000186681747437,
-0.047349583357572556,
0.02513136900961399,
0.0662446990609169,
0.07768423110246658,
-0.03797391429543495,
-0.008253731764853,
0.0011901968391612172,
-0.0948609709739685,
-0.0020795518066734076,
0.0409865640103817,
0.05132393538951874,
-0.14333368837833405,
0.09081240743398666,
0.09744595736265182,
-0.015339801087975502,
0.14312495291233063,
0.008754834532737732,
-0.1070873811841011,
-0.003728162497282028,
0.027940761297941208,
0.05264529958367348,
0.0774049460887909,
-0.03596934303641319,
0.02683958038687706,
0.08106063306331635,
-0.05121877044439316,
0.007932554930448532,
-0.09500398486852646,
-0.022678673267364502,
-0.013256699778139591,
-0.0758146122097969,
-0.04612674191594124,
0.03610261529684067,
0.030104612931609154,
0.0918031707406044,
-0.015134556218981743,
0.07633049786090851,
-0.0010367896175011992,
-0.02394755184650421,
-0.09206201136112213,
0.1670486181974411,
-0.0899675041437149,
-0.27366867661476135,
-0.1188458725810051,
-0.07167717814445496,
-0.04199657961726189,
0.004022621084004641,
0.02857130952179432,
-0.12134306877851486,
-0.07081691175699234,
-0.03115151636302471,
-0.0038425917737185955,
0.06778023391962051,
-0.03805195540189743,
-0.02431504614651203,
0.05526971071958542,
0.09138014912605286,
-0.07273191213607788,
-0.002759605646133423,
0.06194623187184334,
-0.037675220519304276,
0.08085193485021591,
0.008549315854907036,
0.10605848580598831,
0.04739413037896156,
0.03012051060795784,
0.0015264216344803572,
0.04311876371502876,
0.17313145101070404,
-0.10127022117376328,
0.09718520194292068,
0.20746180415153503,
0.0394415408372879,
0.08480402082204819,
0.15171074867248535,
0.05122246593236923,
-0.013119645416736603,
-0.005120322108268738,
0.04244927689433098,
0.011746162548661232,
-0.2427690476179123,
-0.061469703912734985,
-0.05656198412179947,
-0.054776955395936966,
0.022767482325434685,
0.047591015696525574,
0.0650729089975357,
0.1047578752040863,
-0.10416096448898315,
-0.016062086448073387,
0.022997045889496803,
0.09911724179983139,
0.047439564019441605,
0.022038234397768974,
0.061993930488824844,
-0.04141371324658394,
0.015599393285810947,
0.12155410647392273,
0.06473620980978012,
0.11147889494895935,
-0.023897795006632805,
0.08020832389593124,
0.06728237122297287,
0.0892438217997551,
0.0530114471912384,
0.06319621205329895,
0.04218849167227745,
-0.014131366275250912,
-0.0013301256112754345,
-0.08454640209674835,
-0.04801497980952263,
0.023290416225790977,
0.013235284946858883,
-0.057533953338861465,
-0.0392376184463501,
-0.01914895512163639,
0.07390332221984863,
0.1574147492647171,
0.04597143456339836,
-0.20930512249469757,
-0.05056460201740265,
0.033859558403491974,
-0.0003397460968699306,
-0.06584210693836212,
-0.033550359308719635,
0.05652978643774986,
-0.12203755974769592,
0.1039382740855217,
-0.02658943273127079,
0.09946075826883316,
-0.07054278254508972,
0.000789299956522882,
0.00494906771928072,
0.12713035941123962,
-0.023788869380950928,
0.09413742274045944,
-0.24859566986560822,
0.14139194786548615,
0.04770104959607124,
0.06752338260412216,
-0.05309014022350311,
0.028258029371500015,
0.0961327999830246,
0.12656870484352112,
0.10434279590845108,
0.020785793662071228,
0.06395822018384933,
-0.15350443124771118,
-0.11799371987581253,
0.006164612248539925,
0.02960512787103653,
-0.04779611900448799,
0.07287964969873428,
-0.0005067483871243894,
-0.06341438740491867,
-0.04712821915745735,
0.03289221227169037,
-0.19348879158496857,
-0.12983499467372894,
0.07045576721429825,
0.052490055561065674,
0.090853750705719,
-0.06709475815296173,
-0.03205195814371109,
-0.043046124279499054,
0.18290454149246216,
-0.03442198783159256,
-0.08606650680303574,
-0.1285882145166397,
-0.0006686998531222343,
0.09258218854665756,
-0.08165017515420914,
-0.005991893354803324,
-0.052048277109861374,
0.1894829422235489,
-0.035209737718105316,
-0.08786994218826294,
0.01570327952504158,
-0.15995244681835175,
-0.1281605362892151,
-0.0414857491850853,
0.12103712558746338,
-0.021659180521965027,
0.02213156595826149,
0.05526252090930939,
-0.020805859938263893,
0.008410685695707798,
-0.1123393177986145,
0.02350648306310177,
0.09350050985813141,
0.08948540687561035,
0.08400450646877289,
-0.11930029839277267,
-0.11843101680278778,
-0.10216961801052094,
-0.022528614848852158,
0.06181072071194649,
0.24282413721084595,
-0.02235415205359459,
0.037382837384939194,
0.13085247576236725,
-0.04928212612867355,
-0.19814851880073547,
-0.06996271014213562,
-0.00017375701281707734,
-0.037472743541002274,
0.02159503661096096,
-0.21408295631408691,
0.08694717288017273,
0.09358245879411697,
-0.030445247888565063,
0.09161640703678131,
-0.07194696366786957,
-0.06843597441911697,
0.04065357893705368,
0.07071772962808609,
0.0037067674566060305,
-0.1683196723461151,
-0.07113704830408096,
-0.06764888018369675,
-0.12663458287715912,
0.08166584372520447,
-0.1314810812473297,
0.08971400558948517,
-0.005421672947704792,
0.0671011433005333,
0.025563575327396393,
-0.06707208603620529,
0.11356908828020096,
-0.020757906138896942,
0.009567689150571823,
-0.07924797385931015,
0.012899143621325493,
0.022010432556271553,
-0.050428662449121475,
0.09034649282693863,
-0.02925287000834942,
0.01692429557442665,
-0.091850645840168,
-0.0007856881711632013,
-0.10224597156047821,
0.0437864288687706,
-0.038862090557813644,
-0.017533548176288605,
-0.008498632349073887,
0.07837546616792679,
0.03536466881632805,
0.010669435374438763,
-0.009266866371035576,
-0.04946504905819893,
0.10181041061878204,
0.17810481786727905,
0.10491631180047989,
0.0006870499346405268,
-0.07857012748718262,
-0.036821771413087845,
-0.053213875740766525,
0.050082918256521225,
-0.08183137327432632,
0.06681650131940842,
0.029605142772197723,
0.010572184808552265,
0.12429390102624893,
-0.0033586653880774975,
-0.12030913680791855,
-0.003338087350130081,
0.10895328968763351,
-0.12868796288967133,
-0.07275929301977158,
-0.020934229716658592,
0.05516009032726288,
-0.10196569561958313,
0.0011667415965348482,
0.1428048461675644,
-0.028892088681459427,
-0.028331711888313293,
0.014776935800909996,
0.07020314782857895,
-0.012796786613762379,
0.10238455981016159,
0.07413777709007263,
0.049551427364349365,
-0.12031137198209763,
0.05704139545559883,
0.03181569650769234,
-0.03592713922262192,
-0.0024339298252016306,
0.05667674541473389,
-0.10612429678440094,
-0.1119871735572815,
0.03397342190146446,
0.06045559421181679,
-0.015471268445253372,
-0.06184658035635948,
-0.020792635157704353,
-0.04714902117848396,
0.02126099169254303,
0.07590576261281967,
0.00995138380676508,
-0.008162305690348148,
0.08148860931396484,
-0.017391547560691833,
-0.08959554880857468,
0.06402577459812164,
0.010443227365612984,
0.03571965917944908,
-0.13038720190525055,
0.07408680766820908,
-0.015041174367070198,
0.006071531679481268,
-0.022530831396579742,
0.003641687100753188,
-0.10074226558208466,
-0.04254826903343201,
-0.07885435223579407,
0.06230726093053818,
-0.1484614759683609,
-0.020241795107722282,
-0.026183132082223892,
-0.022612975910305977,
0.015071062371134758,
0.019551774486899376,
-0.07782812416553497,
-0.04559153690934181,
-0.010346274822950363,
0.08449862152338028,
-0.16007104516029358,
-0.008523115888237953,
0.03327300027012825,
-0.06084582209587097,
0.0670776516199112,
0.08543620258569717,
-0.010745981708168983,
-0.011400423012673855,
-0.24030931293964386,
-0.05429427698254585,
0.060920946300029755,
0.04178236424922943,
0.015297153033316135,
-0.10723429918289185,
0.0352109931409359,
-0.01898287609219551,
-0.023456763476133347,
0.005050045438110828,
0.031953055411577225,
-0.08434974402189255,
0.024241402745246887,
-0.019039491191506386,
-0.04014326632022858,
-0.051917847245931625,
0.04262912645936012,
0.17145587503910065,
-0.014532416127622128,
0.1174297034740448,
-0.080752432346344,
0.054420918226242065,
-0.13401885330677032,
0.029829595237970352,
-0.001078542205505073,
-0.039962440729141235,
-0.02863360196352005,
-0.010570892132818699,
0.06349045038223267,
-0.010899520479142666,
0.09258676320314407,
-0.0552545003592968,
0.06722300499677658,
0.0190583486109972,
-0.09725376963615417,
0.007986992597579956,
-0.026470135897397995,
0.03294571489095688,
0.0396236926317215,
-0.006473933346569538,
0.009316735900938511,
0.00238132756203413,
0.02042953483760357,
-0.0582701601088047,
0.07976511865854263,
0.16147081553936005,
0.02053176984190941,
0.022807525470852852,
0.054943084716796875,
-0.07234697043895721,
-0.036924149841070175,
-0.04578930139541626,
-0.077462337911129,
0.06634023785591125,
-0.021255100145936012,
0.07374273985624313,
0.15307408571243286,
-0.12218204140663147,
0.038187239319086075,
-0.005237263161689043,
-0.03132057934999466,
-0.08196348696947098,
-0.1581864356994629,
-0.06715912371873856,
-0.08088500797748566,
0.011959434486925602,
-0.11438815295696259,
0.06888450682163239,
0.04325690120458603,
0.019395047798752785,
-0.017880942672491074,
0.13543029129505157,
0.03472369909286499,
-0.07543140649795532,
0.060917001217603683,
-0.02095349319279194,
-0.031358812004327774,
0.04272241145372391,
0.0006400952115654945,
0.06196298450231552,
-0.010582057759165764,
0.044258568435907364,
0.0559408999979496,
0.02938593178987503,
0.05811672285199165,
-0.06726688146591187,
-0.12517108023166656,
0.006359596271067858,
0.005888449959456921,
0.04039566218852997,
0.15003027021884918,
0.05136363208293915,
0.007397872861474752,
0.014586303383111954,
0.16361239552497864,
-0.038274187594652176,
-0.0431714691221714,
-0.15419889986515045,
0.011273895390331745,
-0.02001452073454857,
-0.009176031686365604,
-0.03663250058889389,
-0.10866829752922058,
-0.028140606358647346,
0.20135445892810822,
0.08363344520330429,
-0.049736183136701584,
0.026926010847091675,
-0.006478144787251949,
0.0070541067980229855,
0.006099193822592497,
0.08733457326889038,
0.05982113629579544,
0.11233042925596237,
-0.03476639464497566,
0.04225286468863487,
0.008952682837843895,
-0.042931120842695236,
-0.100910983979702,
0.05160531401634216,
-0.04183126986026764,
-0.029043002054095268,
-0.0207699965685606,
0.12725666165351868,
-0.06002918258309364,
-0.12053494155406952,
-0.05984590947628021,
-0.05843505263328552,
-0.09186802059412003,
-0.04533113166689873,
-0.021347900852560997,
0.08330697566270828,
0.03736959397792816,
-0.008225626312196255,
-0.006564581301063299,
0.18599693477153778,
-0.004363450221717358,
-0.06833065301179886,
-0.047022756189107895,
0.03228268772363663,
-0.009685746394097805,
0.13331912457942963,
0.02237250655889511,
0.06835850328207016,
0.08902639895677567,
-0.04617135971784592,
-0.13351397216320038,
0.05768809840083122,
0.01893182285130024,
-0.16012974083423615,
0.03900958225131035,
0.1735668033361435,
-0.019399257376790047,
0.004258662927895784,
0.07070906460285187,
-0.07974739372730255,
0.021498262882232666,
0.05192280188202858,
-0.017278648912906647,
-0.07030515372753143,
0.08999960869550705,
-0.09391003847122192,
0.11678098142147064,
0.17506007850170135,
-0.024389326572418213,
-0.013276796787977219,
-0.03903545066714287,
0.05904215946793556,
0.06406354159116745,
-0.016790268942713737,
-0.07218509912490845,
-0.10399819910526276,
0.01415897998958826,
-0.01502299215644598,
0.07969480007886887,
-0.13121938705444336,
-0.019862104207277298,
-0.05875250697135925,
-0.03522523120045662,
-0.09029058367013931,
0.07942423224449158,
0.06178797036409378,
0.053517896682024,
-0.021183528006076813,
-0.09516715258359909,
0.007413235958665609,
0.11255256831645966,
-0.14081521332263947,
-0.0646120086312294
] |
null | null | null |
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
```python
from kornia.contrib import VisionTransformer
vit_model = VisionTransformer.from_config('vit_b/16', pretrained=True)
...
```
Original weights from [AugReg](https://arxiv.org/abs/2106.10270) as recommended by [google research vision transformer repo](https://github.com/google-research/vision_transformer): This weight is based on the
[AugReg ViT_B/16 pretrained on imagenet21k](https://storage.googleapis.com/vit_models/augreg/B_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0.npz)
Weights converted to PyTorch for Kornia ViT implementation (by [@gau-nernst](https://github.com/gau-nernst) in [kornia/kornia#2786](https://github.com/kornia/kornia/pull/2786#discussion_r1482339811))
<details>
<summary>Convert jax checkpoint function</summary>
```
def convert_jax_checkpoint(np_state_dict: dict[str, np.ndarray]):
def get_weight(key: str) -> torch.Tensor:
return torch.from_numpy(np_state_dict[key])
state_dict = dict()
state_dict["patch_embedding.cls_token"] = get_weight("cls")
state_dict["patch_embedding.backbone.weight"] = get_weight("embedding/kernel").permute(3, 2, 0, 1) # conv »
state_dict["patch_embedding.backbone.bias"] = get_weight("embedding/bias")
state_dict["patch_embedding.positions"] = get_weight("Transformer/posembed_input/pos_embedding").squeeze(0)
# for i, block in enumerate(self.encoder.blocks):
for i in range(100):
prefix1 = f"encoder.blocks.{i}"
prefix2 = f"Transformer/encoderblock_{i}"
if f"{prefix2}/LayerNorm_0/scale" not in np_state_dict:
break
state_dict[f"{prefix1}.0.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_0/scale")
state_dict[f"{prefix1}.0.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_0/bias")
mha_prefix = f"{prefix2}/MultiHeadDotProductAttention_1"
qkv_weight = [get_weight(f"{mha_prefix}/{x}/kernel") for x in ["query", "key", "value"]]
qkv_bias = [get_weight(f"{mha_prefix}/{x}/bias") for x in ["query", "key", "value"]]
state_dict[f"{prefix1}.0.fn.1.qkv.weight"] = torch.cat(qkv_weight, 1).flatten(1).T
state_dict[f"{prefix1}.0.fn.1.qkv.bias"] = torch.cat(qkv_bias, 0).flatten()
state_dict[f"{prefix1}.0.fn.1.projection.weight"] = get_weight(f"{mha_prefix}/out/kernel").flatten(0, 1»
state_dict[f"{prefix1}.0.fn.1.projection.bias"] = get_weight(f"{mha_prefix}/out/bias")
state_dict[f"{prefix1}.1.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_2/scale")
state_dict[f"{prefix1}.1.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_2/bias")
state_dict[f"{prefix1}.1.fn.1.0.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/kernel").T
state_dict[f"{prefix1}.1.fn.1.0.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/bias")
state_dict[f"{prefix1}.1.fn.1.3.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/kernel").T
state_dict[f"{prefix1}.1.fn.1.3.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/bias")
state_dict["norm.weight"] = get_weight("Transformer/encoder_norm/scale")
state_dict["norm.bias"] = get_weight("Transformer/encoder_norm/bias")
return state_dict
```
</details> | {"license": "apache-2.0", "pipeline_tag": "image-classification"} | image-classification | kornia/vit_b16_augreg_i21k_r224 | [
"image-classification",
"arxiv:2106.10270",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:26:52+00:00 | [
"2106.10270"
] | [] | TAGS
#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us
|
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Original weights from AugReg as recommended by google research vision transformer repo: This weight is based on the
AugReg ViT_B/16 pretrained on imagenet21k
Weights converted to PyTorch for Kornia ViT implementation (by @gau-nernst in kornia/kornia#2786)
<details>
<summary>Convert jax checkpoint function</summary>
</details> | [] | [
"TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
27
] | [
"passage: TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
-0.06109374389052391,
0.20674705505371094,
-0.006548014469444752,
0.049976740032434464,
0.02543392963707447,
0.06775278598070145,
0.1434560865163803,
0.10054779052734375,
0.0873129591345787,
-0.0696193128824234,
0.16259659826755524,
0.07446799427270889,
0.027905816212296486,
-0.020278295502066612,
0.0003193104930687696,
-0.19860264658927917,
0.07249123603105545,
-0.01418757252395153,
-0.03743588179349899,
0.016364481300115585,
0.031079968437552452,
-0.03377098590135574,
0.06803242117166519,
-0.013396034017205238,
-0.12081167846918106,
-0.004631385672837496,
0.05561913177371025,
-0.04842509329319,
0.07639530301094055,
-0.0024446528404951096,
0.03034677915275097,
0.033661652356386185,
0.0436035580933094,
-0.18721453845500946,
-0.0013201063266023993,
-0.011022438295185566,
-0.13286513090133667,
0.06692822277545929,
0.12416379153728485,
0.0049120765179395676,
0.03520214185118675,
0.04749228432774544,
-0.1190459355711937,
0.007217442616820335,
-0.09456748515367508,
-0.2383200079202652,
-0.10159328579902649,
0.11124194413423538,
0.12468010187149048,
0.01974388025701046,
0.10125472396612167,
0.03719622269272804,
-0.12143778800964355,
0.007481607608497143,
0.07237470895051956,
-0.24169990420341492,
-0.010691691190004349,
0.1201784610748291,
-0.1079055592417717,
0.04524125158786774,
-0.03944199159741402,
0.09898041188716888,
0.0823771059513092,
-0.045112185180187225,
-0.11518827825784683,
-0.045906227082014084,
-0.11930672824382782,
0.05414021015167236,
0.02489721029996872,
-0.08919412642717361,
0.3176185190677643,
0.1532946676015854,
0.002456814516335726,
0.11417848616838455,
-0.034857455641031265,
0.03917086496949196,
-0.020580649375915527,
0.14350418746471405,
0.11800917983055115,
0.1277526319026947,
0.11405012756586075,
-0.018727514892816544,
-0.18136470019817352,
-0.06914898008108139,
-0.16194461286067963,
-0.04335305839776993,
-0.03692782297730446,
0.17465905845165253,
-0.1323341280221939,
-0.02526034042239189,
-0.1357729136943817,
-0.08216837048530579,
0.02422415465116501,
-0.0783277153968811,
0.17794139683246613,
0.12570883333683014,
-0.025183117017149925,
0.05908667668700218,
0.14745140075683594,
0.12899348139762878,
0.02096019685268402,
0.03532757610082626,
-0.10447050631046295,
0.19674737751483917,
-0.02905309945344925,
0.03755328059196472,
0.03452769294381142,
0.11503022909164429,
0.06668683886528015,
-0.08765921741724014,
0.09905751049518585,
-0.034111931920051575,
-0.1760949343442917,
-0.02817642129957676,
-0.0438312403857708,
0.051844481378793716,
-0.0005061799311079085,
-0.04923499748110771,
-0.07902505248785019,
0.02592616155743599,
0.20208676159381866,
0.005098436959087849,
0.00970771349966526,
-0.009410499595105648,
-0.01887846365571022,
-0.03703097999095917,
0.06327838450670242,
0.020843954756855965,
0.06386575847864151,
-0.00038021898944862187,
-0.07227174192667007,
0.04220779612660408,
0.0033467260655015707,
0.07464555650949478,
0.11725340783596039,
-0.033287424594163895,
0.031015444546937943,
-0.1253310889005661,
-0.06270439177751541,
0.03723682835698128,
0.086534284055233,
0.0028114039450883865,
0.01238210964947939,
0.11720160394906998,
0.014849238097667694,
0.03825271129608154,
-0.03593437746167183,
-0.060856327414512634,
-0.099258191883564,
0.055119361728429794,
-0.13103467226028442,
0.08423157781362534,
-0.2563755214214325,
0.011386703699827194,
-0.10534657537937164,
0.053238339722156525,
-0.09686396270990372,
-0.07819923013448715,
-0.13250695168972015,
0.2009194940328598,
-0.05468209087848663,
0.0034654189366847277,
-0.054602500051259995,
-0.00633781123906374,
-0.05506056174635887,
0.07645745575428009,
-0.15609174966812134,
0.02364489808678627,
0.08345842361450195,
-0.15114741027355194,
-0.13571877777576447,
-0.002641590777784586,
0.043754223734140396,
-0.07488250732421875,
-0.010925939306616783,
0.3182951807975769,
-0.03542245179414749,
-0.01839727908372879,
0.036988433450460434,
0.15065109729766846,
-0.08740837126970291,
-0.20893323421478271,
0.10468775033950806,
-0.09690731018781662,
-0.14157627522945404,
0.0215351153165102,
-0.13635723292827606,
0.10152363032102585,
0.040783826261758804,
-0.08645343035459518,
-0.02261362224817276,
-0.04002821445465088,
-0.04111453890800476,
0.012164331041276455,
0.05289793014526367,
-0.046031367033720016,
0.036598462611436844,
-0.10292722284793854,
0.05292672663927078,
0.08823665231466293,
0.03464950621128082,
-0.019848383963108063,
0.05194208770990372,
-0.0322202704846859,
-0.008407019078731537,
-0.06743084639310837,
0.03886767849326134,
0.009944709949195385,
-0.047629464417696,
0.08154439926147461,
-0.05256316438317299,
0.028394905850291252,
-0.08248095214366913,
-0.0052256197668612,
-0.03148965165019035,
-0.021348997950553894,
0.016548115760087967,
0.04151642695069313,
-0.15185265243053436,
0.05146369710564613,
0.027628103271126747,
0.06300205737352371,
-0.07534655928611755,
-0.06911735236644745,
0.13192912936210632,
-0.02104104869067669,
-0.006522714160382748,
0.09356412291526794,
0.007906613871455193,
-0.09177529066801071,
-0.01047999132424593,
-0.02048683352768421,
0.1222124695777893,
0.01773674599826336,
-0.03080260008573532,
0.15719905495643616,
0.004599755629897118,
0.1652202308177948,
0.19648905098438263,
-0.1871400624513626,
0.05895731970667839,
-0.04543163627386093,
0.03526407852768898,
-0.00021277944324538112,
0.058195192366838455,
0.030574873089790344,
-0.11539100110530853,
-0.0529194250702858,
0.04648087918758392,
-0.0637110099196434,
0.08189071714878082,
-0.016040494665503502,
-0.07081851363182068,
-0.09113258868455887,
-0.004617263562977314,
0.22731298208236694,
-0.22143718600273132,
0.13705743849277496,
0.44992348551750183,
-0.00563804479315877,
0.04384651407599449,
-0.07071708142757416,
-0.02926171012222767,
0.011590258218348026,
-0.016685742884874344,
-0.027885599061846733,
0.20283104479312897,
-0.037577949464321136,
-0.006611361168324947,
0.07687141746282578,
0.021334122866392136,
0.02833111397922039,
-0.2102135717868805,
-0.08647490292787552,
-0.01990378089249134,
-0.032265402376651764,
-0.106113001704216,
-0.03494508937001228,
-0.07398673892021179,
0.09487839788198471,
-0.00005973442966933362,
-0.13227896392345428,
0.12197559326887131,
-0.04474426805973053,
-0.053833432495594025,
0.1027798280119896,
-0.1763962209224701,
-0.23515380918979645,
-0.14439262449741364,
0.03435428440570831,
-0.07389409840106964,
0.033989984542131424,
0.05001555383205414,
-0.12449482828378677,
-0.042997002601623535,
0.009898168034851551,
-0.17011038959026337,
-0.0666801705956459,
-0.009744573384523392,
0.04772152379155159,
0.06096755340695381,
0.05611218884587288,
-0.07783979177474976,
-0.04949898272752762,
-0.03132689744234085,
0.022898364812135696,
0.13073059916496277,
-0.10337543487548828,
0.13391651213169098,
0.08956552296876907,
-0.0060893171466887,
0.037197306752204895,
0.024989010766148567,
0.06867308169603348,
-0.06233874335885048,
-0.009597424417734146,
0.15581579506397247,
-0.009040242061018944,
0.06215013191103935,
0.12999725341796875,
0.06666824221611023,
-0.09433972090482712,
-0.022919438779354095,
-0.01883879117667675,
-0.09602656215429306,
-0.19175516068935394,
-0.057091742753982544,
-0.049366164952516556,
0.08483017235994339,
0.14666369557380676,
0.11997713893651962,
0.16513875126838684,
0.09672091901302338,
0.017073094844818115,
0.032890960574150085,
0.011969516053795815,
0.02745753899216652,
0.09431096166372299,
-0.00256404560059309,
-0.00900819431990385,
-0.1345144361257553,
0.04063615947961807,
0.16199742257595062,
0.16016624867916107,
0.2346680760383606,
0.24405603110790253,
0.013032541610300541,
0.08629986643791199,
0.14010414481163025,
0.09959616512060165,
0.083418108522892,
0.014013865031301975,
0.0002983128360938281,
-0.07782557606697083,
-0.06522127240896225,
0.007191324606537819,
0.08919525146484375,
-0.056596651673316956,
-0.13630864024162292,
0.04233114793896675,
-0.15700164437294006,
0.043609846383333206,
0.08521639555692673,
0.10101553797721863,
-0.12919598817825317,
0.11238693445920944,
0.07870315760374069,
0.13523606956005096,
-0.033454976975917816,
0.12932239472866058,
-0.03169083222746849,
-0.008430219255387783,
0.1317882388830185,
0.007853557355701923,
0.08151012659072876,
-0.024717014282941818,
-0.0011054257629439235,
-0.017972934991121292,
-0.23283958435058594,
0.0644598975777626,
0.10178142786026001,
-0.11300219595432281,
0.27768510580062866,
0.031322941184043884,
-0.12874376773834229,
-0.04034474864602089,
-0.036046352237463,
0.12492694705724716,
0.22686100006103516,
0.1506083458662033,
0.08461418747901917,
-0.2186128795146942,
-0.015754923224449158,
-0.09932077676057816,
-0.0005119231645949185,
0.029082471504807472,
0.023185651749372482,
-0.18783825635910034,
0.0009278097422793508,
0.018264522776007652,
0.001460708910599351,
0.1566782295703888,
-0.10841827839612961,
-0.0659492164850235,
0.00179493788164109,
0.08047734946012497,
-0.04437811300158501,
-0.06396231800317764,
0.034309569746255875,
-0.013767643831670284,
0.036747898906469345,
-0.022247834131121635,
-0.004408868495374918,
-0.04094367474317551,
-0.12550413608551025,
0.021679183468222618,
-0.017714237794280052,
0.029833028092980385,
-0.08279894292354584,
-0.04034486040472984,
-0.06748219579458237,
-0.23039697110652924,
0.14154691994190216,
-0.07678768783807755,
0.016050616279244423,
-0.05765075236558914,
0.05977974832057953,
-0.0824442207813263,
0.00418700510635972,
-0.0022916689049452543,
0.056743767112493515,
-0.033833812922239304,
-0.10060850530862808,
0.1735401153564453,
-0.02724578231573105,
0.046342626214027405,
-0.00022314728994388133,
-0.05170644447207451,
-0.035063985735177994,
0.012569589540362358,
-0.02630540169775486,
0.1234268769621849,
0.2582937479019165,
-0.11369399726390839,
0.11319419741630554,
0.22277510166168213,
-0.08378475159406662,
-0.2901381254196167,
-0.0702567845582962,
-0.18003669381141663,
-0.1256219744682312,
0.052320681512355804,
-0.19621984660625458,
0.14071376621723175,
0.22147466242313385,
-0.14830414950847626,
0.229997918009758,
-0.14988930523395538,
-0.030987894162535667,
0.15975996851921082,
-0.0008190532680600882,
0.3081471621990204,
-0.19845253229141235,
-0.06818240880966187,
-0.12761925160884857,
-0.15836204588413239,
0.155714213848114,
-0.025408737361431122,
0.006225026212632656,
-0.007217234466224909,
-0.08931957185268402,
-0.02436586655676365,
0.004366954322904348,
0.24909676611423492,
0.004330891650170088,
0.16055257618427277,
-0.11767592281103134,
-0.12619024515151978,
0.11690738052129745,
-0.06503412872552872,
-0.0007165660499595106,
-0.10723470896482468,
-0.010643302462995052,
-0.11397052556276321,
0.09066908806562424,
-0.05764220282435417,
0.04375004768371582,
0.02174108289182186,
-0.017453894019126892,
-0.10904242843389511,
-0.005453106015920639,
-0.09661629796028137,
0.0515119843184948,
0.356973797082901,
0.056218892335891724,
-0.06076716259121895,
0.09476302564144135,
-0.045844666659832,
-0.09363016486167908,
-0.04768260940909386,
-0.12678976356983185,
-0.0685768872499466,
0.1280103325843811,
-0.30839988589286804,
0.06342349946498871,
0.060435857623815536,
-0.0101803969591856,
0.05798220634460449,
0.0419137105345726,
-0.008689306676387787,
-0.002610941184684634,
0.18246068060398102,
-0.041163694113492966,
-0.013913077302277088,
0.022781025618314743,
0.1528378427028656,
0.20284785330295563,
0.038649726659059525,
0.07634012401103973,
0.016211945563554764,
0.004480070900171995,
0.037742264568805695,
0.07341662049293518,
-0.0799650028347969,
-0.060552340000867844,
0.0995108038187027,
-0.0472230538725853,
-0.08839789032936096,
0.2580071687698364,
0.06586729735136032,
-0.040969472378492355,
-0.060587961226701736,
0.023097578436136246,
-0.06413619965314865,
-0.106551893055439,
-0.029016191139817238,
0.007275809999555349,
-0.14201894402503967,
-0.14605849981307983,
0.029940688982605934,
-0.055694930255413055,
-0.036023736000061035,
-0.0009951975662261248,
0.0818314328789711,
0.01024248544126749,
0.10877418518066406,
-0.050103265792131424,
0.1298569291830063,
-0.07700810581445694,
-0.21583467721939087,
0.044681038707494736,
-0.1390920728445053,
-0.24245065450668335,
0.05320950597524643,
0.07469253987073898,
-0.029019640758633614,
-0.011899758130311966,
-0.06899982690811157,
0.06061933934688568,
-0.1356326937675476,
0.12674148380756378,
-0.05317538231611252,
0.017484011128544807,
0.023907091468572617,
-0.030213210731744766,
-0.043195463716983795,
0.009983353316783905,
-0.15352073311805725,
-0.06672659516334534,
-0.0035989026073366404,
0.06315059959888458,
-0.0489853136241436,
-0.08843541145324707,
0.08217836916446686,
0.04006815701723099,
0.08011067658662796,
0.07868228107690811,
0.00977279432117939,
0.0726410523056984,
-0.18324869871139526,
-0.1208200752735138,
0.14623382687568665,
0.025101887062191963,
-0.048409875482320786,
0.08060428500175476,
-0.039926428347826004,
0.04881305247545242,
-0.08390691131353378,
0.006642403081059456,
0.0034260768443346024,
-0.1251237690448761,
-0.09406817704439163,
-0.09683351963758469,
-0.15214946866035461,
0.00039810591260902584,
-0.04967843368649483,
0.1913544088602066,
0.008625444024801254,
0.0807836502790451,
0.036689359694719315,
-0.006731836590915918,
-0.051704924553632736,
0.02872658520936966,
-0.041187088936567307,
-0.10434682667255402,
-0.17093461751937866,
-0.015617710538208485,
-0.0860636904835701,
-0.1006554514169693,
0.2431410551071167,
0.048497993499040604,
-0.1993618756532669,
0.02384042739868164,
0.18894675374031067,
-0.07109846919775009,
0.023319972679018974,
0.25406286120414734,
0.00019303734006825835,
0.025920644402503967,
-0.02808104082942009,
0.026976024731993675,
0.021667996421456337,
-0.02375073917210102,
0.026855897158384323,
0.12996679544448853,
0.043553244322538376,
0.032946716994047165,
0.14659735560417175,
-0.0173412524163723,
-0.08477585017681122,
0.022847771644592285,
0.061927322298288345,
0.1110801249742508,
0.04275544360280037,
0.04724521189928055,
0.21924637258052826,
-0.0042988271452486515,
-0.00025624613044783473,
-0.05579526722431183,
0.011268865317106247,
-0.08793025463819504,
-0.1877223551273346,
-0.05527739226818085,
-0.17583560943603516,
0.049897871911525726,
-0.004426159430295229,
-0.012788284569978714,
0.2909761965274811,
0.027319302782416344,
-0.0482502318918705,
-0.06282444298267365,
-0.16109506785869598,
-0.07760324329137802,
0.06602004915475845,
-0.00034622318344190717,
-0.07779118418693542,
-0.04654536023736,
-0.05229349806904793,
0.06716009229421616,
-0.0650051012635231,
-0.044580407440662384,
0.00833569560199976,
0.08897022902965546,
-0.0011313384165987372,
-0.059533439576625824,
-0.058417774736881256,
-0.07093261927366257,
0.007818278856575489,
-0.041152771562337875,
0.13718730211257935,
0.014150754548609257,
0.061706382781267166,
0.08388342708349228,
0.0832892581820488,
-0.04481666162610054,
-0.005954330787062645,
0.01730518601834774,
0.024704741314053535,
-0.14028121531009674,
0.07547515630722046,
-0.05182021111249924,
-0.046783607453107834,
0.011663789860904217,
0.16521625220775604,
0.19023829698562622,
-0.10069664567708969,
-0.03277084603905678,
-0.03297418728470802,
0.010275846347212791,
0.013714811764657497,
0.13700632750988007,
0.08500899374485016,
0.08871713280677795,
-0.032855018973350525,
-0.061874307692050934,
-0.06518110632896423,
0.015506909228861332,
-0.14511807262897491,
0.03136218339204788,
0.038375891745090485,
-0.08714506775140762,
-0.0889124721288681,
0.12509585916996002,
0.014278160408139229,
0.11131628602743149,
0.16461534798145294,
-0.05992981046438217,
-0.024726636707782745,
0.014439063146710396,
0.15600472688674927,
0.035410262644290924,
-0.006145869381725788,
-0.15497305989265442,
-0.06066638603806496,
-0.03294585272669792,
0.0111419428139925,
-0.3058968782424927,
-0.16970622539520264,
-0.008374981582164764,
-0.0351867713034153,
0.30137813091278076,
0.027061674743890762,
0.06243366748094559,
0.008204973302781582,
0.02186395600438118,
-0.10690846294164658,
0.08221492171287537,
-0.02377958409488201,
0.01824123226106167,
-0.08009807765483856,
-0.11080692708492279,
-0.03178728371858597,
-0.03495577722787857,
0.1160794198513031,
0.059739332646131516,
-0.02478528767824173,
0.20401827991008759,
-0.09265992045402527,
-0.053211916238069534,
0.013441485352814198,
-0.18209552764892578,
0.028789974749088287,
-0.048542529344558716,
-0.005964033771306276,
-0.13737298548221588,
-0.047639016062021255,
-0.04662676155567169,
0.07773999124765396,
-0.2452046424150467,
-0.04547024518251419,
0.22630788385868073,
-0.009974819608032703,
0.022548647597432137,
0.05865916237235069,
0.05990443006157875,
0.0051626162603497505,
-0.10867731273174286,
0.03566248342394829,
-0.07021775841712952,
0.012532292865216732,
0.11721400171518326,
-0.03954120725393295,
-0.00978852342814207,
-0.12052185088396072,
0.08994459360837936,
-0.02892490290105343,
0.04041118174791336,
-0.08855695277452469
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# imdb_review_sentiement
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "imdb_review_sentiement", "results": []}]} | text-classification | santiadavani/imdb_review_sentiement | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:30:57+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# imdb_review_sentiement
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# imdb_review_sentiement\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# imdb_review_sentiement\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
68,
34,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# imdb_review_sentiement\n\nThis model is a fine-tuned version of distilbert-base-uncased on the None dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 5e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3.0### Training results### Framework versions\n\n- Transformers 4.36.2\n- Pytorch 2.1.2+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.0815630704164505,
0.10681691765785217,
-0.001710499171167612,
0.07818715274333954,
0.17010240256786346,
0.023199591785669327,
0.13228227198123932,
0.08503744006156921,
-0.10660085827112198,
0.04350532963871956,
0.05713402107357979,
0.09394398331642151,
0.017408844083547592,
0.11554141342639923,
-0.05530323460698128,
-0.21544750034809113,
0.032876260578632355,
-0.028984418138861656,
-0.06987989693880081,
0.09510418772697449,
0.10824794322252274,
-0.10464811325073242,
0.0631745234131813,
-0.00972173735499382,
-0.16411589086055756,
0.019993750378489494,
-0.012378365732729435,
-0.043431609869003296,
0.09359657019376755,
0.010524388402700424,
0.11140547692775726,
0.027613570913672447,
0.1268572211265564,
-0.23106952011585236,
0.0016397911822423339,
0.084072545170784,
0.03488333523273468,
0.0554078072309494,
0.038280561566352844,
0.0028137180488556623,
0.09843148291110992,
-0.1190982460975647,
0.10207458585500717,
0.033261559903621674,
-0.07353457063436508,
-0.13188865780830383,
-0.08834134787321091,
0.06598205864429474,
0.10069313645362854,
0.10979259759187698,
-0.005906869191676378,
0.12035619467496872,
-0.1195930540561676,
0.0769510343670845,
0.13609299063682556,
-0.2552538216114044,
-0.06834018975496292,
0.06896228343248367,
0.029370484873652458,
0.08963404595851898,
-0.10669426620006561,
-0.01437798235565424,
0.06786574423313141,
0.027471207082271576,
0.10104762762784958,
-0.0013056033058091998,
-0.0825469121336937,
-0.015532897785305977,
-0.14781136810779572,
-0.001527566695585847,
0.1804027557373047,
0.05647818744182587,
-0.06573429703712463,
-0.07624366879463196,
-0.0460224524140358,
-0.06613856554031372,
-0.02066180668771267,
-0.05494723096489906,
0.04731866344809532,
-0.0229698047041893,
-0.04830234870314598,
-0.03870076313614845,
-0.07641325891017914,
-0.055300693958997726,
0.00733028631657362,
0.11018972843885422,
0.05198495835065842,
-0.00798480398952961,
-0.018614472821354866,
0.09739013761281967,
-0.0019997856579720974,
-0.11338981986045837,
-0.007229590322822332,
-0.016646072268486023,
-0.04293665662407875,
-0.07849717885255814,
-0.06100442260503769,
-0.018863126635551453,
0.019049866124987602,
0.17122720181941986,
-0.07824230194091797,
0.05545390769839287,
0.0031382099259644747,
0.012237781658768654,
-0.045375581830739975,
0.12421441823244095,
-0.025955086573958397,
-0.04249327629804611,
0.01863357238471508,
0.1142895370721817,
0.025416597723960876,
-0.002529600402340293,
-0.0768953338265419,
0.011512779630720615,
0.10075826197862625,
0.06292257457971573,
-0.06566546857357025,
0.04761015251278877,
-0.04180584475398064,
-0.02092442288994789,
0.016280118376016617,
-0.11954521387815475,
0.03388288617134094,
-0.001837744377553463,
-0.06536798924207687,
-0.01647043041884899,
0.03829214349389076,
0.023756783455610275,
-0.007645102217793465,
0.10926727205514908,
-0.08197713643312454,
0.00847774650901556,
-0.10126665234565735,
-0.0765361338853836,
0.007180684246122837,
-0.04801510274410248,
-0.0020523713901638985,
-0.10129152238368988,
-0.19726672768592834,
-0.04530727490782738,
0.049587082117795944,
-0.020559227094054222,
-0.038076817989349365,
-0.07173559069633484,
-0.0741095170378685,
0.0025941089261323214,
-0.0010952678276225924,
0.0683552548289299,
-0.05510638281702995,
0.07018283009529114,
0.00817467924207449,
0.02160242199897766,
0.0012895953841507435,
0.033758413046598434,
-0.11374378949403763,
0.02296609990298748,
-0.13551437854766846,
0.06065788120031357,
-0.0948883518576622,
0.060612112283706665,
-0.08105897158384323,
-0.0886075422167778,
-0.010364266112446785,
-0.0078039332292973995,
0.0463993176817894,
0.13006414473056793,
-0.18165323138237,
-0.027149643748998642,
0.13966058194637299,
-0.09797881543636322,
-0.10004662722349167,
0.11201879382133484,
-0.0453060008585453,
0.04510195553302765,
0.07020484656095505,
0.14268885552883148,
0.08448344469070435,
-0.11419620364904404,
-0.02291985973715782,
-0.0020293514244258404,
0.06659804284572601,
0.0379989929497242,
0.049481574445962906,
-0.012671681120991707,
-0.019153492525219917,
0.018201366066932678,
-0.07260822504758835,
0.010863740928471088,
-0.0844285860657692,
-0.09007622301578522,
-0.05920617654919624,
-0.11001785844564438,
0.05242185667157173,
0.03634387254714966,
0.04727410152554512,
-0.08361990004777908,
-0.09833472967147827,
0.12490256130695343,
0.1266908198595047,
-0.06029198318719864,
0.012582806870341301,
-0.07048352062702179,
0.05361931025981903,
-0.012578155845403671,
-0.0185097549110651,
-0.18250808119773865,
-0.10887903720140457,
0.025234878063201904,
-0.03056090697646141,
0.0420939065515995,
0.004530956037342548,
0.045735400170087814,
0.09218166768550873,
-0.06491122394800186,
-0.03584549203515053,
-0.0809456929564476,
0.021611060947179794,
-0.08919848501682281,
-0.21574553847312927,
-0.017495788633823395,
-0.030347926542162895,
0.20285898447036743,
-0.2650829553604126,
0.04051840305328369,
-0.06084144860506058,
0.11727140843868256,
0.023007668554782867,
-0.0399869903922081,
-0.03393177688121796,
0.062384992837905884,
-0.034972451627254486,
-0.08261043578386307,
0.04619203880429268,
0.006878943182528019,
-0.07784873992204666,
-0.08815772086381912,
-0.1413719356060028,
0.07576211541891098,
0.10125474631786346,
-0.0041273655369877815,
-0.09262046962976456,
0.004294252954423428,
-0.05708060786128044,
-0.0324028916656971,
-0.07320613414049149,
0.019892562180757523,
0.13289614021778107,
-0.016195811331272125,
0.13142162561416626,
-0.05583169311285019,
-0.03928680345416069,
-0.015797575935721397,
-0.027508243918418884,
-0.006747481878846884,
0.0660509541630745,
0.09619410336017609,
-0.11524252593517303,
0.10854420810937881,
0.1417054980993271,
-0.0919623151421547,
0.13142916560173035,
-0.04735145345330238,
-0.060952380299568176,
0.0011557884281501174,
0.014664188958704472,
-0.00041910383151844144,
0.09274949133396149,
-0.09491107612848282,
0.01589159667491913,
0.004660234786570072,
0.02622941881418228,
0.039308104664087296,
-0.17688684165477753,
-0.00562546169385314,
0.02744702249765396,
-0.032116927206516266,
-0.023413894698023796,
-0.02588457427918911,
0.011483555659651756,
0.08487029373645782,
-0.0004933472373522818,
-0.03085881657898426,
0.03450474515557289,
0.000568218354601413,
-0.09256582707166672,
0.19029346108436584,
-0.13044534623622894,
-0.1169373095035553,
-0.10384906083345413,
0.03154494985938072,
-0.06880924105644226,
-0.0027823185082525015,
0.03840383514761925,
-0.10633178800344467,
-0.05345271900296211,
-0.09678009897470474,
-0.019214477390050888,
-0.007211677730083466,
-0.012418526224792004,
0.055658210068941116,
0.02046341262757778,
0.10014155507087708,
-0.12477323412895203,
0.0004695673706009984,
-0.009892015717923641,
-0.10638280212879181,
0.0014024225529283285,
0.047073110938072205,
0.11383991688489914,
0.13668422400951385,
-0.012200684286653996,
-0.005038190167397261,
-0.016420556232333183,
0.2332504838705063,
-0.05095813423395157,
-0.020592253655195236,
0.12538546323776245,
-0.007308723870664835,
0.042223911732435226,
0.13079415261745453,
0.03279055655002594,
-0.11735888570547104,
0.05256856605410576,
0.07568106800317764,
-0.009786252863705158,
-0.22464418411254883,
-0.058978233486413956,
-0.028592266142368317,
-0.06719979643821716,
0.06343827396631241,
0.03869364410638809,
0.037175629287958145,
0.04682045802474022,
-0.011149820871651173,
0.047793541103601456,
0.010312204249203205,
0.08396603167057037,
0.08595278114080429,
0.035276997834444046,
0.11016929149627686,
-0.03240511193871498,
-0.019882891327142715,
0.0578589104115963,
-0.041286639869213104,
0.254617840051651,
0.0026109947357326746,
0.0366770476102829,
0.07236520200967789,
0.1423192322254181,
-0.02056898921728134,
0.02964448370039463,
0.021311737596988678,
-0.025450648739933968,
0.006006112787872553,
-0.0591827891767025,
-0.03792019560933113,
0.03535763919353485,
-0.059067122638225555,
0.05978899821639061,
-0.11581739038228989,
0.06408198922872543,
0.06325795501470566,
0.22620557248592377,
0.028144873678684235,
-0.29457563161849976,
-0.09563993662595749,
0.026267407462000847,
-0.0223848819732666,
-0.03846762701869011,
0.015677528455853462,
0.09367015212774277,
-0.1027413159608841,
0.0494343638420105,
-0.046275801956653595,
0.08874243497848511,
-0.004865478724241257,
0.025629326701164246,
0.051578424870967865,
0.1342044174671173,
-0.00006128807581262663,
0.07825803011655807,
-0.25624895095825195,
0.18810680508613586,
0.006019224878400564,
0.13803595304489136,
-0.03568163514137268,
0.01829081028699875,
0.044026173651218414,
0.15457598865032196,
0.08301135152578354,
-0.0021203828509896994,
-0.0471770204603672,
-0.17248184978961945,
-0.038164738565683365,
0.03862699121236801,
0.11771978437900543,
-0.02663930505514145,
0.0861123576760292,
-0.0589049868285656,
0.013808061368763447,
0.06736622750759125,
-0.04195595160126686,
-0.223648801445961,
-0.12436027824878693,
-0.011717373505234718,
0.002371863229200244,
-0.002313403645530343,
-0.09527622908353806,
-0.08961047977209091,
-0.06797504425048828,
0.19229741394519806,
-0.013436625711619854,
-0.018228545784950256,
-0.12394856661558151,
0.0656907707452774,
0.07795067131519318,
-0.05464130640029907,
0.024829929694533348,
0.019018765538930893,
0.1104385182261467,
0.0329003781080246,
-0.07790998369455338,
0.05194913595914841,
-0.10800153762102127,
-0.16145430505275726,
-0.0588795468211174,
0.08813595026731491,
0.059731148183345795,
0.04371989890933037,
0.006926707457751036,
0.008975734934210777,
0.030534667894244194,
-0.08931636810302734,
-0.01862136460840702,
0.10743378847837448,
0.08322875201702118,
0.06662685424089432,
-0.1192227378487587,
-0.02788603864610195,
-0.0624927394092083,
-0.0378313809633255,
0.11255321651697159,
0.23414982855319977,
-0.07390623539686203,
0.03830033168196678,
0.07995857298374176,
-0.09241252392530441,
-0.18698129057884216,
0.0800803154706955,
0.07927090674638748,
0.0037675807252526283,
0.05183322727680206,
-0.1694587767124176,
0.13668407499790192,
0.12096620351076126,
-0.022892627865076065,
0.05393846705555916,
-0.30438387393951416,
-0.13909414410591125,
0.09124277532100677,
0.12672710418701172,
0.04301363229751587,
-0.14106333255767822,
-0.02774297259747982,
-0.05339115113019943,
-0.08989350497722626,
0.10685157030820847,
-0.12818409502506256,
0.09383467584848404,
0.01747230626642704,
0.039073873311281204,
0.013879840262234211,
-0.03549772500991821,
0.15019068121910095,
0.018734604120254517,
0.1079988181591034,
-0.0628942996263504,
0.03761667758226395,
0.05929453670978546,
-0.06280462443828583,
0.03679385408759117,
-0.05548061430454254,
0.07574544101953506,
-0.07008820027112961,
-0.02685975842177868,
-0.059386685490608215,
0.061929237097501755,
-0.057869020849466324,
-0.06638123840093613,
-0.047763943672180176,
0.0591004304587841,
0.07270414382219315,
-0.026271579787135124,
0.06964383274316788,
0.008763651363551617,
0.13666847348213196,
0.06900510936975479,
0.10633480548858643,
-0.030244356021285057,
-0.03272385522723198,
-0.007454698905348778,
-0.029699986800551414,
0.06442725658416748,
-0.11067840456962585,
0.031216660514473915,
0.10860810428857803,
0.022262493148446083,
0.15846014022827148,
0.05262387916445732,
-0.026903817430138588,
-0.004278372507542372,
0.05875556543469429,
-0.12216164916753769,
-0.1375851035118103,
-0.004125288221985102,
-0.03761978819966316,
-0.11597785353660583,
0.027485188096761703,
0.0987480953335762,
-0.07872926443815231,
0.004833837039768696,
-0.024292973801493645,
0.025484509766101837,
-0.040661539882421494,
0.17233194410800934,
0.031960200518369675,
0.05119242146611214,
-0.07282726466655731,
0.13855966925621033,
0.058439213782548904,
-0.0918058231472969,
0.03403441980481148,
0.04404200613498688,
-0.1080169752240181,
-0.037724513560533524,
0.07071100920438766,
0.17846110463142395,
-0.03337030112743378,
-0.05710437148809433,
-0.10811915248632431,
-0.10121569037437439,
0.03682625666260719,
0.10458400100469589,
0.06509630382061005,
-0.00953208189457655,
-0.03721289709210396,
0.04599572345614433,
-0.15526360273361206,
0.09082499146461487,
0.049779120832681656,
0.07753672450780869,
-0.17559002339839935,
0.12176602333784103,
0.01506127417087555,
-0.0027436609379947186,
-0.016731267794966698,
0.03821646794676781,
-0.10043347626924515,
-0.02416454814374447,
-0.15066727995872498,
-0.022805683314800262,
-0.02863263338804245,
0.0121535062789917,
0.003006635932251811,
-0.034732330590486526,
-0.043362539261579514,
0.04609205201268196,
-0.06656278669834137,
-0.05619079992175102,
0.02480200305581093,
0.06961345672607422,
-0.136943519115448,
-0.0009273327887058258,
0.019473861902952194,
-0.09966804832220078,
0.061577655375003815,
0.05508195608854294,
0.01886606402695179,
0.05620612949132919,
-0.17347030341625214,
-0.011994441971182823,
0.05497380718588829,
0.02193223312497139,
0.0443086251616478,
-0.08551935851573944,
-0.01622798852622509,
-0.0069620320573449135,
0.051035501062870026,
0.0224661473184824,
0.06810761988162994,
-0.10989958792924881,
-0.018446192145347595,
-0.04160718992352486,
-0.052875977009534836,
-0.05664648860692978,
0.02791665308177471,
0.10613613575696945,
0.019094640389084816,
0.21553382277488708,
-0.10463188588619232,
0.02152041345834732,
-0.17882534861564636,
-0.026994312182068825,
-0.0024495720863342285,
-0.03599868714809418,
-0.10036637634038925,
-0.03939634934067726,
0.06004621461033821,
-0.06277064234018326,
0.10426859557628632,
-0.02145211212337017,
0.0870189294219017,
0.04423999413847923,
-0.03954996168613434,
-0.0037730117328464985,
0.021094903349876404,
0.21445730328559875,
0.061754073947668076,
-0.014024071395397186,
0.036346133798360825,
-0.005528631154447794,
0.07998263835906982,
0.009438927285373211,
0.1979089379310608,
0.17799033224582672,
-0.08827266097068787,
0.07022717595100403,
0.04008632153272629,
-0.0983974039554596,
-0.14210624992847443,
0.09783757477998734,
-0.03639006242156029,
0.10640913993120193,
-0.047046806663274765,
0.15813466906547546,
0.1162266731262207,
-0.1678592413663864,
0.03314642235636711,
-0.07032328099012375,
-0.10172022134065628,
-0.12181849777698517,
-0.03288670629262924,
-0.08558344841003418,
-0.1378568708896637,
0.027053827419877052,
-0.1258772909641266,
0.028523700311779976,
0.07551911473274231,
0.00684100529178977,
-0.0021897524129599333,
0.17370197176933289,
-0.05173356086015701,
0.02146269753575325,
0.04979434609413147,
-0.01829974353313446,
-0.04214230924844742,
-0.06003430113196373,
-0.08182145655155182,
0.03620428219437599,
-0.008374309167265892,
0.0602395124733448,
-0.04872845113277435,
-0.03203538432717323,
0.04242294654250145,
-0.016375325620174408,
-0.06398656219244003,
0.04322042688727379,
0.02121293731033802,
0.02678968943655491,
0.0604732483625412,
0.0396021269261837,
-0.019832607358694077,
-0.012219793163239956,
0.2859797179698944,
-0.08506409078836441,
-0.11465106904506683,
-0.13785339891910553,
0.2328939288854599,
0.04985741525888443,
0.009727808646857738,
0.049643825739622116,
-0.11711949110031128,
0.006930796895176172,
0.15958277881145477,
0.1613108217716217,
-0.08047837018966675,
-0.015651626512408257,
-0.027293335646390915,
-0.020484376698732376,
-0.08554936945438385,
0.1280212700366974,
0.1155468299984932,
0.015342962928116322,
-0.03935972973704338,
-0.008278774097561836,
-0.017826948314905167,
-0.024438636377453804,
-0.07861654460430145,
0.06889926642179489,
0.013346927240490913,
0.0006072184187360108,
-0.0300686564296484,
0.07539141923189163,
-0.016474168747663498,
-0.1378338634967804,
0.032071616500616074,
-0.11965561658143997,
-0.16083559393882751,
-0.03550218790769577,
0.09480026364326477,
-0.026762738823890686,
0.04137390851974487,
-0.016571158543229103,
-0.0214998796582222,
0.1252685934305191,
-0.03149387985467911,
-0.01813718117773533,
-0.09123241156339645,
0.06131647899746895,
-0.027494382113218307,
0.2327432930469513,
-0.0014731434639543295,
0.05856919288635254,
0.11232245713472366,
0.025958824902772903,
-0.1037246435880661,
0.08018335700035095,
0.05281490832567215,
-0.05770621821284294,
0.04251919314265251,
0.13037090003490448,
-0.057691656053066254,
0.11808766424655914,
0.05414961278438568,
-0.15501536428928375,
0.01403003465384245,
-0.03488016501069069,
-0.08232045918703079,
-0.07220921665430069,
0.011476418934762478,
-0.07461760938167572,
0.15090544521808624,
0.20558148622512817,
-0.02903209999203682,
0.030944181606173515,
-0.06766960769891739,
0.05303093045949936,
0.0557352676987648,
0.08990517258644104,
-0.02890605665743351,
-0.2260856330394745,
0.02840287610888481,
0.017356906086206436,
0.011612770147621632,
-0.2505767047405243,
-0.09301982074975967,
0.027132613584399223,
-0.03868990018963814,
-0.08494749665260315,
0.10817858576774597,
0.1046280711889267,
0.03211691230535507,
-0.05006244406104088,
-0.14855755865573883,
-0.05866604670882225,
0.16111044585704803,
-0.1331375241279602,
-0.06405522674322128
] |
null | null | null |
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
```python
from kornia.contrib import VisionTransformer
vit_model = VisionTransformer.from_config('vit_s/16', pretrained=True)
...
```
Original weights from [AugReg](https://arxiv.org/abs/2106.10270) as recommended by [google research vision transformer repo](https://github.com/google-research/vision_transformer): This weight is based on the
[AugReg ViT_S/16 pretrained on imagenet21k](https://storage.googleapis.com/vit_models/augreg/S_16-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0.npz)
Weights converted to PyTorch for Kornia ViT implementation (by [@gau-nernst](https://github.com/gau-nernst) in [kornia/kornia#2786](https://github.com/kornia/kornia/pull/2786#discussion_r1482339811))
<details>
<summary>Convert jax checkpoint function</summary>
```
def convert_jax_checkpoint(np_state_dict: dict[str, np.ndarray]):
def get_weight(key: str) -> torch.Tensor:
return torch.from_numpy(np_state_dict[key])
state_dict = dict()
state_dict["patch_embedding.cls_token"] = get_weight("cls")
state_dict["patch_embedding.backbone.weight"] = get_weight("embedding/kernel").permute(3, 2, 0, 1) # conv »
state_dict["patch_embedding.backbone.bias"] = get_weight("embedding/bias")
state_dict["patch_embedding.positions"] = get_weight("Transformer/posembed_input/pos_embedding").squeeze(0)
# for i, block in enumerate(self.encoder.blocks):
for i in range(100):
prefix1 = f"encoder.blocks.{i}"
prefix2 = f"Transformer/encoderblock_{i}"
if f"{prefix2}/LayerNorm_0/scale" not in np_state_dict:
break
state_dict[f"{prefix1}.0.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_0/scale")
state_dict[f"{prefix1}.0.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_0/bias")
mha_prefix = f"{prefix2}/MultiHeadDotProductAttention_1"
qkv_weight = [get_weight(f"{mha_prefix}/{x}/kernel") for x in ["query", "key", "value"]]
qkv_bias = [get_weight(f"{mha_prefix}/{x}/bias") for x in ["query", "key", "value"]]
state_dict[f"{prefix1}.0.fn.1.qkv.weight"] = torch.cat(qkv_weight, 1).flatten(1).T
state_dict[f"{prefix1}.0.fn.1.qkv.bias"] = torch.cat(qkv_bias, 0).flatten()
state_dict[f"{prefix1}.0.fn.1.projection.weight"] = get_weight(f"{mha_prefix}/out/kernel").flatten(0, 1»
state_dict[f"{prefix1}.0.fn.1.projection.bias"] = get_weight(f"{mha_prefix}/out/bias")
state_dict[f"{prefix1}.1.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_2/scale")
state_dict[f"{prefix1}.1.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_2/bias")
state_dict[f"{prefix1}.1.fn.1.0.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/kernel").T
state_dict[f"{prefix1}.1.fn.1.0.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/bias")
state_dict[f"{prefix1}.1.fn.1.3.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/kernel").T
state_dict[f"{prefix1}.1.fn.1.3.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/bias")
state_dict["norm.weight"] = get_weight("Transformer/encoder_norm/scale")
state_dict["norm.bias"] = get_weight("Transformer/encoder_norm/bias")
return state_dict
```
</details> | {"license": "apache-2.0", "pipeline_tag": "image-classification"} | image-classification | kornia/vit_s16_augreg_i21k_r224 | [
"image-classification",
"arxiv:2106.10270",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:32:46+00:00 | [
"2106.10270"
] | [] | TAGS
#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us
|
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Original weights from AugReg as recommended by google research vision transformer repo: This weight is based on the
AugReg ViT_S/16 pretrained on imagenet21k
Weights converted to PyTorch for Kornia ViT implementation (by @gau-nernst in kornia/kornia#2786)
<details>
<summary>Convert jax checkpoint function</summary>
</details> | [] | [
"TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
27
] | [
"passage: TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
-0.06109374389052391,
0.20674705505371094,
-0.006548014469444752,
0.049976740032434464,
0.02543392963707447,
0.06775278598070145,
0.1434560865163803,
0.10054779052734375,
0.0873129591345787,
-0.0696193128824234,
0.16259659826755524,
0.07446799427270889,
0.027905816212296486,
-0.020278295502066612,
0.0003193104930687696,
-0.19860264658927917,
0.07249123603105545,
-0.01418757252395153,
-0.03743588179349899,
0.016364481300115585,
0.031079968437552452,
-0.03377098590135574,
0.06803242117166519,
-0.013396034017205238,
-0.12081167846918106,
-0.004631385672837496,
0.05561913177371025,
-0.04842509329319,
0.07639530301094055,
-0.0024446528404951096,
0.03034677915275097,
0.033661652356386185,
0.0436035580933094,
-0.18721453845500946,
-0.0013201063266023993,
-0.011022438295185566,
-0.13286513090133667,
0.06692822277545929,
0.12416379153728485,
0.0049120765179395676,
0.03520214185118675,
0.04749228432774544,
-0.1190459355711937,
0.007217442616820335,
-0.09456748515367508,
-0.2383200079202652,
-0.10159328579902649,
0.11124194413423538,
0.12468010187149048,
0.01974388025701046,
0.10125472396612167,
0.03719622269272804,
-0.12143778800964355,
0.007481607608497143,
0.07237470895051956,
-0.24169990420341492,
-0.010691691190004349,
0.1201784610748291,
-0.1079055592417717,
0.04524125158786774,
-0.03944199159741402,
0.09898041188716888,
0.0823771059513092,
-0.045112185180187225,
-0.11518827825784683,
-0.045906227082014084,
-0.11930672824382782,
0.05414021015167236,
0.02489721029996872,
-0.08919412642717361,
0.3176185190677643,
0.1532946676015854,
0.002456814516335726,
0.11417848616838455,
-0.034857455641031265,
0.03917086496949196,
-0.020580649375915527,
0.14350418746471405,
0.11800917983055115,
0.1277526319026947,
0.11405012756586075,
-0.018727514892816544,
-0.18136470019817352,
-0.06914898008108139,
-0.16194461286067963,
-0.04335305839776993,
-0.03692782297730446,
0.17465905845165253,
-0.1323341280221939,
-0.02526034042239189,
-0.1357729136943817,
-0.08216837048530579,
0.02422415465116501,
-0.0783277153968811,
0.17794139683246613,
0.12570883333683014,
-0.025183117017149925,
0.05908667668700218,
0.14745140075683594,
0.12899348139762878,
0.02096019685268402,
0.03532757610082626,
-0.10447050631046295,
0.19674737751483917,
-0.02905309945344925,
0.03755328059196472,
0.03452769294381142,
0.11503022909164429,
0.06668683886528015,
-0.08765921741724014,
0.09905751049518585,
-0.034111931920051575,
-0.1760949343442917,
-0.02817642129957676,
-0.0438312403857708,
0.051844481378793716,
-0.0005061799311079085,
-0.04923499748110771,
-0.07902505248785019,
0.02592616155743599,
0.20208676159381866,
0.005098436959087849,
0.00970771349966526,
-0.009410499595105648,
-0.01887846365571022,
-0.03703097999095917,
0.06327838450670242,
0.020843954756855965,
0.06386575847864151,
-0.00038021898944862187,
-0.07227174192667007,
0.04220779612660408,
0.0033467260655015707,
0.07464555650949478,
0.11725340783596039,
-0.033287424594163895,
0.031015444546937943,
-0.1253310889005661,
-0.06270439177751541,
0.03723682835698128,
0.086534284055233,
0.0028114039450883865,
0.01238210964947939,
0.11720160394906998,
0.014849238097667694,
0.03825271129608154,
-0.03593437746167183,
-0.060856327414512634,
-0.099258191883564,
0.055119361728429794,
-0.13103467226028442,
0.08423157781362534,
-0.2563755214214325,
0.011386703699827194,
-0.10534657537937164,
0.053238339722156525,
-0.09686396270990372,
-0.07819923013448715,
-0.13250695168972015,
0.2009194940328598,
-0.05468209087848663,
0.0034654189366847277,
-0.054602500051259995,
-0.00633781123906374,
-0.05506056174635887,
0.07645745575428009,
-0.15609174966812134,
0.02364489808678627,
0.08345842361450195,
-0.15114741027355194,
-0.13571877777576447,
-0.002641590777784586,
0.043754223734140396,
-0.07488250732421875,
-0.010925939306616783,
0.3182951807975769,
-0.03542245179414749,
-0.01839727908372879,
0.036988433450460434,
0.15065109729766846,
-0.08740837126970291,
-0.20893323421478271,
0.10468775033950806,
-0.09690731018781662,
-0.14157627522945404,
0.0215351153165102,
-0.13635723292827606,
0.10152363032102585,
0.040783826261758804,
-0.08645343035459518,
-0.02261362224817276,
-0.04002821445465088,
-0.04111453890800476,
0.012164331041276455,
0.05289793014526367,
-0.046031367033720016,
0.036598462611436844,
-0.10292722284793854,
0.05292672663927078,
0.08823665231466293,
0.03464950621128082,
-0.019848383963108063,
0.05194208770990372,
-0.0322202704846859,
-0.008407019078731537,
-0.06743084639310837,
0.03886767849326134,
0.009944709949195385,
-0.047629464417696,
0.08154439926147461,
-0.05256316438317299,
0.028394905850291252,
-0.08248095214366913,
-0.0052256197668612,
-0.03148965165019035,
-0.021348997950553894,
0.016548115760087967,
0.04151642695069313,
-0.15185265243053436,
0.05146369710564613,
0.027628103271126747,
0.06300205737352371,
-0.07534655928611755,
-0.06911735236644745,
0.13192912936210632,
-0.02104104869067669,
-0.006522714160382748,
0.09356412291526794,
0.007906613871455193,
-0.09177529066801071,
-0.01047999132424593,
-0.02048683352768421,
0.1222124695777893,
0.01773674599826336,
-0.03080260008573532,
0.15719905495643616,
0.004599755629897118,
0.1652202308177948,
0.19648905098438263,
-0.1871400624513626,
0.05895731970667839,
-0.04543163627386093,
0.03526407852768898,
-0.00021277944324538112,
0.058195192366838455,
0.030574873089790344,
-0.11539100110530853,
-0.0529194250702858,
0.04648087918758392,
-0.0637110099196434,
0.08189071714878082,
-0.016040494665503502,
-0.07081851363182068,
-0.09113258868455887,
-0.004617263562977314,
0.22731298208236694,
-0.22143718600273132,
0.13705743849277496,
0.44992348551750183,
-0.00563804479315877,
0.04384651407599449,
-0.07071708142757416,
-0.02926171012222767,
0.011590258218348026,
-0.016685742884874344,
-0.027885599061846733,
0.20283104479312897,
-0.037577949464321136,
-0.006611361168324947,
0.07687141746282578,
0.021334122866392136,
0.02833111397922039,
-0.2102135717868805,
-0.08647490292787552,
-0.01990378089249134,
-0.032265402376651764,
-0.106113001704216,
-0.03494508937001228,
-0.07398673892021179,
0.09487839788198471,
-0.00005973442966933362,
-0.13227896392345428,
0.12197559326887131,
-0.04474426805973053,
-0.053833432495594025,
0.1027798280119896,
-0.1763962209224701,
-0.23515380918979645,
-0.14439262449741364,
0.03435428440570831,
-0.07389409840106964,
0.033989984542131424,
0.05001555383205414,
-0.12449482828378677,
-0.042997002601623535,
0.009898168034851551,
-0.17011038959026337,
-0.0666801705956459,
-0.009744573384523392,
0.04772152379155159,
0.06096755340695381,
0.05611218884587288,
-0.07783979177474976,
-0.04949898272752762,
-0.03132689744234085,
0.022898364812135696,
0.13073059916496277,
-0.10337543487548828,
0.13391651213169098,
0.08956552296876907,
-0.0060893171466887,
0.037197306752204895,
0.024989010766148567,
0.06867308169603348,
-0.06233874335885048,
-0.009597424417734146,
0.15581579506397247,
-0.009040242061018944,
0.06215013191103935,
0.12999725341796875,
0.06666824221611023,
-0.09433972090482712,
-0.022919438779354095,
-0.01883879117667675,
-0.09602656215429306,
-0.19175516068935394,
-0.057091742753982544,
-0.049366164952516556,
0.08483017235994339,
0.14666369557380676,
0.11997713893651962,
0.16513875126838684,
0.09672091901302338,
0.017073094844818115,
0.032890960574150085,
0.011969516053795815,
0.02745753899216652,
0.09431096166372299,
-0.00256404560059309,
-0.00900819431990385,
-0.1345144361257553,
0.04063615947961807,
0.16199742257595062,
0.16016624867916107,
0.2346680760383606,
0.24405603110790253,
0.013032541610300541,
0.08629986643791199,
0.14010414481163025,
0.09959616512060165,
0.083418108522892,
0.014013865031301975,
0.0002983128360938281,
-0.07782557606697083,
-0.06522127240896225,
0.007191324606537819,
0.08919525146484375,
-0.056596651673316956,
-0.13630864024162292,
0.04233114793896675,
-0.15700164437294006,
0.043609846383333206,
0.08521639555692673,
0.10101553797721863,
-0.12919598817825317,
0.11238693445920944,
0.07870315760374069,
0.13523606956005096,
-0.033454976975917816,
0.12932239472866058,
-0.03169083222746849,
-0.008430219255387783,
0.1317882388830185,
0.007853557355701923,
0.08151012659072876,
-0.024717014282941818,
-0.0011054257629439235,
-0.017972934991121292,
-0.23283958435058594,
0.0644598975777626,
0.10178142786026001,
-0.11300219595432281,
0.27768510580062866,
0.031322941184043884,
-0.12874376773834229,
-0.04034474864602089,
-0.036046352237463,
0.12492694705724716,
0.22686100006103516,
0.1506083458662033,
0.08461418747901917,
-0.2186128795146942,
-0.015754923224449158,
-0.09932077676057816,
-0.0005119231645949185,
0.029082471504807472,
0.023185651749372482,
-0.18783825635910034,
0.0009278097422793508,
0.018264522776007652,
0.001460708910599351,
0.1566782295703888,
-0.10841827839612961,
-0.0659492164850235,
0.00179493788164109,
0.08047734946012497,
-0.04437811300158501,
-0.06396231800317764,
0.034309569746255875,
-0.013767643831670284,
0.036747898906469345,
-0.022247834131121635,
-0.004408868495374918,
-0.04094367474317551,
-0.12550413608551025,
0.021679183468222618,
-0.017714237794280052,
0.029833028092980385,
-0.08279894292354584,
-0.04034486040472984,
-0.06748219579458237,
-0.23039697110652924,
0.14154691994190216,
-0.07678768783807755,
0.016050616279244423,
-0.05765075236558914,
0.05977974832057953,
-0.0824442207813263,
0.00418700510635972,
-0.0022916689049452543,
0.056743767112493515,
-0.033833812922239304,
-0.10060850530862808,
0.1735401153564453,
-0.02724578231573105,
0.046342626214027405,
-0.00022314728994388133,
-0.05170644447207451,
-0.035063985735177994,
0.012569589540362358,
-0.02630540169775486,
0.1234268769621849,
0.2582937479019165,
-0.11369399726390839,
0.11319419741630554,
0.22277510166168213,
-0.08378475159406662,
-0.2901381254196167,
-0.0702567845582962,
-0.18003669381141663,
-0.1256219744682312,
0.052320681512355804,
-0.19621984660625458,
0.14071376621723175,
0.22147466242313385,
-0.14830414950847626,
0.229997918009758,
-0.14988930523395538,
-0.030987894162535667,
0.15975996851921082,
-0.0008190532680600882,
0.3081471621990204,
-0.19845253229141235,
-0.06818240880966187,
-0.12761925160884857,
-0.15836204588413239,
0.155714213848114,
-0.025408737361431122,
0.006225026212632656,
-0.007217234466224909,
-0.08931957185268402,
-0.02436586655676365,
0.004366954322904348,
0.24909676611423492,
0.004330891650170088,
0.16055257618427277,
-0.11767592281103134,
-0.12619024515151978,
0.11690738052129745,
-0.06503412872552872,
-0.0007165660499595106,
-0.10723470896482468,
-0.010643302462995052,
-0.11397052556276321,
0.09066908806562424,
-0.05764220282435417,
0.04375004768371582,
0.02174108289182186,
-0.017453894019126892,
-0.10904242843389511,
-0.005453106015920639,
-0.09661629796028137,
0.0515119843184948,
0.356973797082901,
0.056218892335891724,
-0.06076716259121895,
0.09476302564144135,
-0.045844666659832,
-0.09363016486167908,
-0.04768260940909386,
-0.12678976356983185,
-0.0685768872499466,
0.1280103325843811,
-0.30839988589286804,
0.06342349946498871,
0.060435857623815536,
-0.0101803969591856,
0.05798220634460449,
0.0419137105345726,
-0.008689306676387787,
-0.002610941184684634,
0.18246068060398102,
-0.041163694113492966,
-0.013913077302277088,
0.022781025618314743,
0.1528378427028656,
0.20284785330295563,
0.038649726659059525,
0.07634012401103973,
0.016211945563554764,
0.004480070900171995,
0.037742264568805695,
0.07341662049293518,
-0.0799650028347969,
-0.060552340000867844,
0.0995108038187027,
-0.0472230538725853,
-0.08839789032936096,
0.2580071687698364,
0.06586729735136032,
-0.040969472378492355,
-0.060587961226701736,
0.023097578436136246,
-0.06413619965314865,
-0.106551893055439,
-0.029016191139817238,
0.007275809999555349,
-0.14201894402503967,
-0.14605849981307983,
0.029940688982605934,
-0.055694930255413055,
-0.036023736000061035,
-0.0009951975662261248,
0.0818314328789711,
0.01024248544126749,
0.10877418518066406,
-0.050103265792131424,
0.1298569291830063,
-0.07700810581445694,
-0.21583467721939087,
0.044681038707494736,
-0.1390920728445053,
-0.24245065450668335,
0.05320950597524643,
0.07469253987073898,
-0.029019640758633614,
-0.011899758130311966,
-0.06899982690811157,
0.06061933934688568,
-0.1356326937675476,
0.12674148380756378,
-0.05317538231611252,
0.017484011128544807,
0.023907091468572617,
-0.030213210731744766,
-0.043195463716983795,
0.009983353316783905,
-0.15352073311805725,
-0.06672659516334534,
-0.0035989026073366404,
0.06315059959888458,
-0.0489853136241436,
-0.08843541145324707,
0.08217836916446686,
0.04006815701723099,
0.08011067658662796,
0.07868228107690811,
0.00977279432117939,
0.0726410523056984,
-0.18324869871139526,
-0.1208200752735138,
0.14623382687568665,
0.025101887062191963,
-0.048409875482320786,
0.08060428500175476,
-0.039926428347826004,
0.04881305247545242,
-0.08390691131353378,
0.006642403081059456,
0.0034260768443346024,
-0.1251237690448761,
-0.09406817704439163,
-0.09683351963758469,
-0.15214946866035461,
0.00039810591260902584,
-0.04967843368649483,
0.1913544088602066,
0.008625444024801254,
0.0807836502790451,
0.036689359694719315,
-0.006731836590915918,
-0.051704924553632736,
0.02872658520936966,
-0.041187088936567307,
-0.10434682667255402,
-0.17093461751937866,
-0.015617710538208485,
-0.0860636904835701,
-0.1006554514169693,
0.2431410551071167,
0.048497993499040604,
-0.1993618756532669,
0.02384042739868164,
0.18894675374031067,
-0.07109846919775009,
0.023319972679018974,
0.25406286120414734,
0.00019303734006825835,
0.025920644402503967,
-0.02808104082942009,
0.026976024731993675,
0.021667996421456337,
-0.02375073917210102,
0.026855897158384323,
0.12996679544448853,
0.043553244322538376,
0.032946716994047165,
0.14659735560417175,
-0.0173412524163723,
-0.08477585017681122,
0.022847771644592285,
0.061927322298288345,
0.1110801249742508,
0.04275544360280037,
0.04724521189928055,
0.21924637258052826,
-0.0042988271452486515,
-0.00025624613044783473,
-0.05579526722431183,
0.011268865317106247,
-0.08793025463819504,
-0.1877223551273346,
-0.05527739226818085,
-0.17583560943603516,
0.049897871911525726,
-0.004426159430295229,
-0.012788284569978714,
0.2909761965274811,
0.027319302782416344,
-0.0482502318918705,
-0.06282444298267365,
-0.16109506785869598,
-0.07760324329137802,
0.06602004915475845,
-0.00034622318344190717,
-0.07779118418693542,
-0.04654536023736,
-0.05229349806904793,
0.06716009229421616,
-0.0650051012635231,
-0.044580407440662384,
0.00833569560199976,
0.08897022902965546,
-0.0011313384165987372,
-0.059533439576625824,
-0.058417774736881256,
-0.07093261927366257,
0.007818278856575489,
-0.041152771562337875,
0.13718730211257935,
0.014150754548609257,
0.061706382781267166,
0.08388342708349228,
0.0832892581820488,
-0.04481666162610054,
-0.005954330787062645,
0.01730518601834774,
0.024704741314053535,
-0.14028121531009674,
0.07547515630722046,
-0.05182021111249924,
-0.046783607453107834,
0.011663789860904217,
0.16521625220775604,
0.19023829698562622,
-0.10069664567708969,
-0.03277084603905678,
-0.03297418728470802,
0.010275846347212791,
0.013714811764657497,
0.13700632750988007,
0.08500899374485016,
0.08871713280677795,
-0.032855018973350525,
-0.061874307692050934,
-0.06518110632896423,
0.015506909228861332,
-0.14511807262897491,
0.03136218339204788,
0.038375891745090485,
-0.08714506775140762,
-0.0889124721288681,
0.12509585916996002,
0.014278160408139229,
0.11131628602743149,
0.16461534798145294,
-0.05992981046438217,
-0.024726636707782745,
0.014439063146710396,
0.15600472688674927,
0.035410262644290924,
-0.006145869381725788,
-0.15497305989265442,
-0.06066638603806496,
-0.03294585272669792,
0.0111419428139925,
-0.3058968782424927,
-0.16970622539520264,
-0.008374981582164764,
-0.0351867713034153,
0.30137813091278076,
0.027061674743890762,
0.06243366748094559,
0.008204973302781582,
0.02186395600438118,
-0.10690846294164658,
0.08221492171287537,
-0.02377958409488201,
0.01824123226106167,
-0.08009807765483856,
-0.11080692708492279,
-0.03178728371858597,
-0.03495577722787857,
0.1160794198513031,
0.059739332646131516,
-0.02478528767824173,
0.20401827991008759,
-0.09265992045402527,
-0.053211916238069534,
0.013441485352814198,
-0.18209552764892578,
0.028789974749088287,
-0.048542529344558716,
-0.005964033771306276,
-0.13737298548221588,
-0.047639016062021255,
-0.04662676155567169,
0.07773999124765396,
-0.2452046424150467,
-0.04547024518251419,
0.22630788385868073,
-0.009974819608032703,
0.022548647597432137,
0.05865916237235069,
0.05990443006157875,
0.0051626162603497505,
-0.10867731273174286,
0.03566248342394829,
-0.07021775841712952,
0.012532292865216732,
0.11721400171518326,
-0.03954120725393295,
-0.00978852342814207,
-0.12052185088396072,
0.08994459360837936,
-0.02892490290105343,
0.04041118174791336,
-0.08855695277452469
] |
null | null | transformers |
# 🌔 moondream1
1.6B parameter model built by [@vikhyatk](https://x.com/vikhyatk) using SigLIP, Phi-1.5 and the LLaVa training dataset.
The model is release for research purposes only, commercial use is not allowed.
Try it out on [Huggingface Spaces](https://huggingface.co/spaces/vikhyatk/moondream1)!
**Usage**
```
pip install transformers timm einops
```
```python
from transformers import AutoModelForCausalLM, CodeGenTokenizerFast as Tokenizer
from PIL import Image
model_id = "vikhyatk/moondream1"
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
tokenizer = Tokenizer.from_pretrained(model_id)
image = Image.open('<IMAGE_PATH>')
enc_image = model.encode_image(image)
print(model.answer_question(enc_image, "<QUESTION>", tokenizer))
```
## Benchmarks
| Model | Parameters | VQAv2 | GQA | TextVQA |
| --- | --- | --- | --- | --- |
| LLaVA-1.5 | 13.3B | 80.0 | 63.3 | 61.3 |
| LLaVA-1.5 | 7.3B | 78.5 | 62.0 | 58.2 |
| **moondream1** | 1.6B | 74.7 | 57.9 | 35.6 |
## Examples
| Image | Examples |
| --- | --- |
|  | **What is the title of this book?**<br>The Little Book of Deep Learning<br><br>**What can you tell me about this book?**<br>The book in the image is titled "The Little Book of Deep Learning." It appears to be a guide or manual that provides information and instructions on the subject of deep learning. The book is described as being small and thin, making it easy to carry and read. It is set in a room with a view outside, suggesting that the person holding the book might be in a living or working space with a view. The content of the book is likely to be complex, as the title implies a focus on advanced concepts in deep learning.<br><br>**Where is the person standing?**<br> The person is standing on a balcony or deck, which is outside. |
|  | **What type of food is the girl holding?**<br>The girl is holding a hamburger.<br><br>**What color is the woman's hair?**<br>The woman's hair is white.<br><br>**What is the girl doing in the image?**<br>The girl in the image is eating a hamburger. |
|  | **What color is the train?**<br>The train is red.<br><br>**What is the bus doing in the image?**<br> The bus in the image is driving down a city street, passing through an intersection.<br><br>**What kind of public transportation is in the image?**<br>The image features a red train or trolley as the public transportation option. |
|  | **What is the girl looking at?**<br>The girl is looking at her reflection in the mirror.<br><br>**What color is the woman's hair?**<br>The woman's hair is brown.<br><br>**What is the woman doing in the mirror?**<br>The woman is adjusting her hair in the mirror. |
|  | **What might be the reason for the dog's aggressive behavior?**<br>The dog's aggressive behavior, including its growling, baring its teeth, and showing its sharp teeth, could be due to various reasons. It is possible that the dog is feeling threatened, scared, or defensive about something in its environment, such as another animal, a loud noise, or a person nearby. Alternatively, the dog might be reacting to a command it received from its owner, or it could be experiencing discomfort or pain, which is causing it to display aggressive behavior. It is essential to observe the dog's body language and context to determine the underlying cause of its aggressive behavior and respond accordingly to address its needs or concerns.<br><br>**What kind of dog is in the picture?**<br>The dog in the picture is a small, black and white chihuahua. |
| {"language": ["en"]} | text-generation | mohan007/moondream1 | [
"transformers",
"pytorch",
"safetensors",
"moondream1",
"text-generation",
"custom_code",
"en",
"autotrain_compatible",
"region:us"
] | 2024-02-09T01:33:42+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #moondream1 #text-generation #custom_code #en #autotrain_compatible #region-us
| moondream1
==========
1.6B parameter model built by @vikhyatk using SigLIP, Phi-1.5 and the LLaVa training dataset.
The model is release for research purposes only, commercial use is not allowed.
Try it out on Huggingface Spaces!
Usage
Benchmarks
----------
Examples
--------
| [] | [
"TAGS\n#transformers #pytorch #safetensors #moondream1 #text-generation #custom_code #en #autotrain_compatible #region-us \n"
] | [
43
] | [
"passage: TAGS\n#transformers #pytorch #safetensors #moondream1 #text-generation #custom_code #en #autotrain_compatible #region-us \n"
] | [
-0.015248452313244343,
0.08964310586452484,
-0.008828094229102135,
0.023286253213882446,
0.1400718241930008,
-0.0113251693546772,
0.16286692023277283,
0.05312793701887131,
0.0049938480369746685,
-0.00824032723903656,
0.17676874995231628,
0.1611221432685852,
-0.045357394963502884,
0.21555225551128387,
-0.060943055897951126,
-0.18859878182411194,
0.08813850581645966,
-0.02870422787964344,
0.05867134407162666,
0.11511646211147308,
0.029481306672096252,
-0.06957626342773438,
0.06829717010259628,
-0.09854756295681,
-0.08243854343891144,
0.02362283319234848,
0.0266481414437294,
-0.10410497337579727,
0.10556846857070923,
-0.019759217277169228,
0.1608782708644867,
0.0964139774441719,
-0.0325777642428875,
-0.11895224452018738,
0.03819456696510315,
-0.004521413240581751,
-0.07845786213874817,
0.04292387515306473,
0.07476028800010681,
-0.014275624416768551,
0.08366794884204865,
0.050930723547935486,
0.00924434419721365,
0.046562179923057556,
-0.16543790698051453,
-0.01553764846175909,
-0.006547646131366491,
-0.01845688186585903,
0.0632210522890091,
0.0887262374162674,
-0.009009119123220444,
0.22571584582328796,
-0.06343144923448563,
0.13396358489990234,
0.06732334941625595,
-0.23696671426296234,
-0.02067236788570881,
0.11666563898324966,
0.06682077050209045,
0.11106644570827484,
-0.029675638303160667,
0.04777851328253746,
0.058458905667066574,
0.022387247532606125,
0.01409637276083231,
-0.07238254696130753,
-0.11984749883413315,
-0.0013376728165894747,
-0.07874906063079834,
-0.0934484526515007,
0.20118308067321777,
-0.08914817869663239,
0.03755801171064377,
0.015639645978808403,
-0.1502244770526886,
-0.028938032686710358,
0.006521826144307852,
-0.013102912344038486,
-0.028796454891562462,
0.0619073323905468,
-0.03368092328310013,
-0.06235332787036896,
-0.1302417665719986,
-0.006874633487313986,
-0.15294179320335388,
0.2345045804977417,
0.0004893233417533338,
0.04614953696727753,
-0.16540652513504028,
0.054352112114429474,
0.12751427292823792,
-0.14496123790740967,
0.061595357954502106,
-0.09647513180971146,
0.07969670742750168,
0.027052395045757294,
-0.009323186241090298,
-0.06486446410417557,
0.1413448452949524,
0.12907664477825165,
-0.0681682825088501,
0.03516111150383949,
-0.03729196637868881,
0.08104296773672104,
0.02418556809425354,
0.06157352402806282,
0.07276637852191925,
-0.012763774022459984,
0.09358406066894531,
-0.03781638666987419,
0.10824856162071228,
-0.07136707007884979,
-0.1448676586151123,
-0.003927868325263262,
0.051954228430986404,
0.12718094885349274,
0.07678227871656418,
0.06692735850811005,
-0.07508817315101624,
0.021148575469851494,
0.14414691925048828,
-0.06611471623182297,
-0.022830424830317497,
0.017267560586333275,
0.05791742354631424,
-0.0595715194940567,
0.004164574202150106,
0.0018508529756218195,
-0.049342118203639984,
-0.003142628353089094,
-0.059048768132925034,
-0.04718686267733574,
-0.03702593967318535,
-0.04988650232553482,
0.03036275878548622,
-0.008830302394926548,
0.028514696285128593,
-0.1794547289609909,
-0.19844971597194672,
-0.0034218516666442156,
-0.011076546274125576,
0.009718147106468678,
-0.0336972251534462,
-0.08042903989553452,
-0.08274867385625839,
-0.0019429896492511034,
-0.0462658666074276,
-0.1385754495859146,
-0.036300696432590485,
0.12239327281713486,
0.007494723424315453,
0.06814511120319366,
-0.13714464008808136,
0.03054937906563282,
-0.20903345942497253,
-0.004522503819316626,
-0.06868480890989304,
0.030545415356755257,
0.00650800671428442,
0.17123278975486755,
0.057164907455444336,
-0.018041377887129784,
-0.0598519928753376,
0.04121110215783119,
0.004411988891661167,
0.2584138512611389,
-0.112223319709301,
-0.07875718176364899,
0.16562558710575104,
-0.17808768153190613,
-0.17159132659435272,
0.08896522969007492,
0.02191302180290222,
0.02706995978951454,
0.051994096487760544,
0.1739082932472229,
-0.021178938448429108,
0.015343318693339825,
0.0855451375246048,
0.05115650221705437,
-0.1388576179742813,
-0.10431960225105286,
0.019374269992113113,
0.010072621516883373,
-0.13942591845989227,
0.05200789496302605,
0.07134807854890823,
0.0931287631392479,
-0.051416072994470596,
-0.06669433414936066,
-0.021274561062455177,
-0.02608158439397812,
0.13286098837852478,
0.06616222858428955,
0.06917370855808258,
-0.11949176341295242,
0.017978766933083534,
-0.044043105095624924,
0.035142749547958374,
0.03250439465045929,
0.0019912547431886196,
-0.040759939700365067,
0.07812660187482834,
-0.003673706902191043,
0.044482648372650146,
-0.1300228238105774,
-0.07194912433624268,
0.008759669959545135,
0.06221141293644905,
-0.021776873618364334,
0.06819937378168106,
0.06807240098714828,
0.05484640970826149,
0.010799664072692394,
-0.0991506278514862,
0.0820334330201149,
-0.011401085183024406,
-0.00673326849937439,
-0.07630781829357147,
0.06734637916088104,
-0.07595118135213852,
0.021136930212378502,
-0.11561722308397293,
0.046838708221912384,
-0.015748176723718643,
0.0884242132306099,
0.007002418860793114,
0.017336977645754814,
0.01755053736269474,
0.06858889758586884,
-0.08691002428531647,
0.020130766555666924,
0.08944296091794968,
0.001204035826958716,
-0.11486956477165222,
0.14971855282783508,
-0.20606456696987152,
0.2789519429206848,
0.20184826850891113,
-0.26549336314201355,
0.030698319897055626,
0.09067808091640472,
-0.00380629557184875,
0.006326356437057257,
0.07009975612163544,
0.0056379614397883415,
0.011255782097578049,
-0.0005293602589517832,
0.18042857944965363,
-0.030561039224267006,
-0.010886027477681637,
0.01141599752008915,
-0.08278537541627884,
-0.08182674646377563,
0.09768971055746078,
-0.008996973745524883,
-0.0672689750790596,
0.20518460869789124,
0.25361934304237366,
0.03809722512960434,
0.2408827692270279,
-0.019431661814451218,
0.03156818076968193,
0.04884795472025871,
-0.007559977937489748,
-0.0313742458820343,
-0.024900661781430244,
-0.1037789136171341,
-0.017494887113571167,
0.045228760689496994,
-0.0340094119310379,
0.06746404618024826,
-0.13412636518478394,
-0.09688237309455872,
-0.024555601179599762,
0.012885909527540207,
-0.04954534024000168,
0.06038389354944229,
0.024626800790429115,
0.07523160427808762,
-0.07063689827919006,
-0.07815093547105789,
0.10546408593654633,
-0.0314481221139431,
-0.07100881636142731,
0.15300805866718292,
-0.142979234457016,
-0.35305336117744446,
-0.22723063826560974,
0.045431289821863174,
-0.06930143386125565,
0.05596979707479477,
0.10404496639966965,
-0.1332254409790039,
-0.011122766882181168,
-0.03041531890630722,
0.04482945054769516,
-0.04223579913377762,
-0.020188799127936363,
-0.03481011837720871,
0.07615269720554352,
-0.05358073115348816,
-0.06194072961807251,
-0.039482343941926956,
-0.0538097582757473,
-0.1051383763551712,
0.21862581372261047,
-0.10258669406175613,
0.11957704275846481,
0.14822816848754883,
-0.01798117719590664,
0.013660076074302197,
-0.00821329839527607,
0.16300615668296814,
-0.06866195052862167,
-0.010597611777484417,
0.22468475997447968,
-0.008588882163167,
0.08889482170343399,
0.1740744709968567,
0.022649379447102547,
-0.08324441313743591,
0.06863157451152802,
-0.12218613177537918,
-0.11692055314779282,
-0.19823315739631653,
-0.1292891949415207,
-0.077843576669693,
0.11659333854913712,
0.006877233274281025,
0.07025056332349777,
0.09581739455461502,
0.09091705828905106,
-0.009883406572043896,
-0.04595474898815155,
0.011676514521241188,
0.08971447497606277,
0.18378542363643646,
-0.010485874488949776,
0.1046135276556015,
-0.06270302087068558,
-0.1443491131067276,
0.09295576065778732,
-0.02438097633421421,
0.014199863187968731,
0.10376258939504623,
0.030403781682252884,
0.018265392631292343,
0.08125238120555878,
0.15412093698978424,
0.12368207424879074,
0.07462979853153229,
-0.006207322236150503,
-0.005142336245626211,
-0.05136819928884506,
-0.1389017254114151,
0.03959961608052254,
-0.04681811481714249,
-0.05380060151219368,
-0.010746415704488754,
-0.06707628071308136,
0.07435809075832367,
0.05782430246472359,
0.04924590513110161,
-0.22782301902770996,
-0.002158608753234148,
0.10195194184780121,
0.04141203314065933,
-0.056215085089206696,
0.0854351744055748,
0.0853448212146759,
-0.09630100429058075,
0.050910692662000656,
-0.01670592837035656,
0.06869374215602875,
-0.005483898799866438,
0.10718382894992828,
-0.14358240365982056,
-0.04277820885181427,
0.018281079828739166,
0.06166969984769821,
-0.2767584025859833,
0.22413954138755798,
-0.02339543215930462,
-0.01153501309454441,
-0.016395175829529762,
-0.011094948276877403,
0.03949330374598503,
0.1733345091342926,
0.08631125837564468,
0.02420489862561226,
-0.054009534418582916,
-0.19315248727798462,
-0.05127177760004997,
0.038499437272548676,
0.09359393268823624,
-0.0442911833524704,
-0.018222248181700706,
-0.014646947383880615,
-0.009255217388272285,
-0.05533553287386894,
-0.021276339888572693,
-0.0415719673037529,
-0.05689166486263275,
0.03386330232024193,
0.05241144448518753,
0.08972588926553726,
-0.0425550676882267,
-0.04371006041765213,
-0.042203690856695175,
0.0708925798535347,
-0.04502455145120621,
-0.08948212116956711,
-0.06827966123819351,
-0.14503486454486847,
0.07159797847270966,
-0.08420572429895401,
0.05494532734155655,
-0.07911455631256104,
-0.017508963122963905,
-0.1066991537809372,
-0.16539257764816284,
0.08267755061388016,
-0.1100737676024437,
-0.1323194056749344,
-0.06170764937996864,
0.1251591593027115,
-0.06503049284219742,
0.00790384504944086,
-0.013888940215110779,
0.0886685773730278,
-0.11254024505615234,
-0.08799801766872406,
0.02745121531188488,
-0.0629446730017662,
-0.03714277595281601,
0.05769180878996849,
-0.026728568598628044,
-0.10084951668977737,
-0.014880264177918434,
-0.03313471004366875,
0.19938671588897705,
0.36065617203712463,
-0.037959497421979904,
0.12357426434755325,
0.2904170751571655,
-0.04521173983812332,
-0.3741927444934845,
-0.15956950187683105,
-0.18162234127521515,
-0.039740946143865585,
0.047984685748815536,
-0.18532027304172516,
0.022205036133527756,
0.008679455146193504,
-0.05070371925830841,
0.05232071503996849,
-0.22717295587062836,
-0.07763192802667618,
0.17998893558979034,
0.06655628234148026,
0.35835984349250793,
-0.19214552640914917,
-0.0884874239563942,
-0.051131024956703186,
-0.08023011684417725,
0.05236431956291199,
-0.055436961352825165,
0.07750196754932404,
-0.038794416934251785,
0.060242608189582825,
0.06140526384115219,
-0.059198249131441116,
0.08143787086009979,
-0.05441579967737198,
0.07244869321584702,
-0.11824015527963638,
-0.045429401099681854,
0.13492131233215332,
0.0025495956651866436,
0.012210313230752945,
-0.03420086205005646,
0.04262823611497879,
-0.04146848991513252,
0.0030586111824959517,
-0.09393347054719925,
0.059933315962553024,
0.0020157669205218554,
-0.07230434566736221,
0.04803633317351341,
-0.045689165592193604,
-0.0429094098508358,
0.0195905901491642,
0.21971990168094635,
-0.015574237331748009,
0.170457661151886,
0.20829692482948303,
0.07689864933490753,
-0.08816573023796082,
0.17173902690410614,
-0.004766962490975857,
-0.08397001028060913,
0.0632505789399147,
-0.048375267535448074,
0.025037499144673347,
0.07322611659765244,
-0.006477715913206339,
0.026058154180645943,
0.08657092601060867,
0.005163464229553938,
0.015311170369386673,
0.14980506896972656,
-0.2548230290412903,
-0.09702286869287491,
-0.05194273963570595,
-0.016812127083539963,
0.10097111016511917,
0.1090548112988472,
0.1180814653635025,
-0.00544800516217947,
-0.036420512944459915,
-0.038236718624830246,
0.019494658336043358,
0.013407555408775806,
0.03599538281559944,
0.05545284226536751,
0.04389461502432823,
-0.12861931324005127,
0.0820579007267952,
0.04476076364517212,
-0.09669674187898636,
-0.000820303859654814,
0.20204848051071167,
-0.1112980917096138,
-0.13996033370494843,
-0.024029916152358055,
0.1287211775779724,
-0.07198476791381836,
-0.05456395447254181,
-0.11938802152872086,
-0.08674608170986176,
0.013341817073523998,
0.1469632089138031,
0.09028197079896927,
0.08414198458194733,
0.0062657012604177,
-0.011006737127900124,
-0.003133075777441263,
0.011488290503621101,
-0.020568372681736946,
0.04739849641919136,
-0.11186020076274872,
0.025313330814242363,
-0.001495736069045961,
0.1078239232301712,
-0.11063821613788605,
-0.09042239934206009,
-0.15540474653244019,
0.04453040286898613,
0.011699157766997814,
-0.031581729650497437,
-0.10137268155813217,
-0.04737061634659767,
-0.010144735686480999,
-0.054981719702482224,
-0.053524505347013474,
-0.005754717625677586,
-0.10793163627386093,
-0.0027083265595138073,
-0.013581587933003902,
0.0361405573785305,
-0.08752194792032242,
-0.025061199441552162,
0.10610125958919525,
-0.05242550000548363,
0.10251034796237946,
0.06737610697746277,
-0.08916035294532776,
0.08375611901283264,
-0.233934685587883,
-0.06719575077295303,
0.10719940811395645,
0.015818141400814056,
0.02849188819527626,
0.17563366889953613,
-0.024799592792987823,
0.06433472037315369,
0.008452417328953743,
0.044226326048374176,
0.12383292615413666,
-0.12553633749485016,
0.05461488291621208,
0.053302571177482605,
-0.18373680114746094,
-0.025952687487006187,
-0.05760576203465462,
0.05601389706134796,
-0.04620436578989029,
0.17884783446788788,
-0.1000986322760582,
0.09667575359344482,
-0.06954406946897507,
-0.0021284869872033596,
0.017978521063923836,
-0.19483663141727448,
-0.15160425007343292,
-0.07151086628437042,
0.01591845043003559,
0.007184510584920645,
0.17110712826251984,
0.03895064815878868,
-0.00548567296937108,
0.02278105542063713,
0.11293437331914902,
-0.000033496540709165856,
0.018487757071852684,
0.1685052365064621,
0.0756336897611618,
-0.06888438761234283,
-0.09969329833984375,
0.05364849045872688,
0.030363300815224648,
-0.028098342940211296,
0.03438226878643036,
0.055839654058218,
0.018489409238100052,
0.07037696242332458,
0.03201107680797577,
0.10999332368373871,
-0.049036990851163864,
-0.19256561994552612,
-0.025543294847011566,
0.04621981084346771,
-0.00197511725127697,
0.07514070719480515,
0.13463616371154785,
0.031312815845012665,
0.024785632267594337,
-0.035956162959337234,
-0.0050073959864676,
-0.14432387053966522,
-0.043355509638786316,
-0.09679476916790009,
-0.106371209025383,
0.027630994096398354,
-0.06032593175768852,
-0.007888467982411385,
0.09530738741159439,
0.005469182506203651,
-0.07811043411493301,
0.09863173961639404,
0.17761747539043427,
-0.05612241104245186,
0.01917245239019394,
-0.040751103311777115,
0.029912281781435013,
-0.01737220212817192,
-0.05609295144677162,
-0.062292322516441345,
0.01571318320930004,
-0.017655616626143456,
0.06611234694719315,
-0.05544291064143181,
0.036837782710790634,
-0.15960632264614105,
-0.13028086721897125,
-0.03246792033314705,
0.04853294417262077,
-0.05659298226237297,
0.07077721506357193,
0.031221095472574234,
-0.02372496947646141,
0.060037966817617416,
0.18713943660259247,
-0.01955767348408699,
-0.12971904873847961,
0.010139615274965763,
0.2814716696739197,
0.014596700668334961,
0.11264093965291977,
-0.020856231451034546,
-0.05485678091645241,
-0.10122714936733246,
0.21456722915172577,
0.32345524430274963,
-0.05400865152478218,
0.05202631279826164,
-0.028869641944766045,
0.032205745577812195,
0.02935805171728134,
0.14643266797065735,
0.08132115006446838,
0.20683462917804718,
-0.06800200790166855,
0.030913246795535088,
-0.06992840021848679,
-0.029472680762410164,
-0.1094549372792244,
0.033044036477804184,
0.01790226250886917,
-0.05159933120012283,
-0.07583180069923401,
0.07301095128059387,
-0.1939968764781952,
0.13502733409404755,
-0.02324007637798786,
-0.2155013233423233,
-0.004116395488381386,
-0.01962343230843544,
0.20039770007133484,
0.019666848704218864,
0.07628782838582993,
-0.017458321526646614,
-0.04431198909878731,
-0.0698080062866211,
-0.01938530057668686,
-0.17592260241508484,
0.014447744004428387,
0.04401005059480667,
-0.20890697836875916,
0.16690242290496826,
-0.0300102848559618,
0.011046464554965496,
0.06457824259996414,
0.02740892767906189,
-0.05263090506196022,
0.15950839221477509,
0.01183820515871048,
0.02400694042444229,
-0.004740757402032614,
0.03467407822608948,
0.022827478125691414,
-0.06359165161848068,
0.049191590398550034,
-0.10592580586671829,
0.04351077228784561,
0.0231868177652359,
-0.01969766430556774,
0.012859147042036057,
0.022506587207317352,
-0.040824148803949356,
0.030064590275287628,
0.013008292764425278,
0.006642073858529329,
0.015342820435762405,
-0.05397937819361687,
0.0010058432817459106,
-0.009256184101104736,
-0.08795041590929031,
-0.0678875669836998,
-0.08024060726165771,
-0.0784006267786026,
0.11031989008188248,
0.03772715851664543,
-0.25597235560417175,
0.019900955259799957,
-0.17209629714488983,
0.07960059493780136,
-0.1673961728811264,
0.04858506843447685,
0.07233548909425735,
0.01940852403640747,
0.02930682711303234,
-0.05626524239778519,
0.03802206739783287,
0.08230515569448471,
-0.07587584108114243,
-0.0925859659910202
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# FYP_deberta-v3_ms_squadv2
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9450
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.481 | 1.0 | 500 | 0.9488 |
| 0.687 | 2.0 | 1000 | 0.8755 |
| 0.4963 | 3.0 | 1500 | 0.9450 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/deberta-v3-base", "model-index": [{"name": "FYP_deberta-v3_ms_squadv2", "results": []}]} | question-answering | kxx-kkk/FYP_ms_squad | [
"transformers",
"tensorboard",
"safetensors",
"deberta-v2",
"question-answering",
"generated_from_trainer",
"base_model:microsoft/deberta-v3-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:35:37+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #deberta-v2 #question-answering #generated_from_trainer #base_model-microsoft/deberta-v3-base #license-mit #endpoints_compatible #region-us
| FYP\_deberta-v3\_ms\_squadv2
============================
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9450
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #deberta-v2 #question-answering #generated_from_trainer #base_model-microsoft/deberta-v3-base #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
65,
98,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #deberta-v2 #question-answering #generated_from_trainer #base_model-microsoft/deberta-v3-base #license-mit #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.10381829738616943,
0.05543964356184006,
-0.0019684697035700083,
0.09659669548273087,
0.14114250242710114,
0.029431670904159546,
0.1366124153137207,
0.10172947496175766,
-0.07658430933952332,
0.059148941189050674,
0.13786081969738007,
0.1331259310245514,
0.003916492685675621,
0.10380955785512924,
-0.05285065621137619,
-0.23138895630836487,
0.011195624247193336,
0.05028609186410904,
-0.08180717378854752,
0.10789848864078522,
0.09572360664606094,
-0.14705698192119598,
0.08164032548666,
-0.004204535391181707,
-0.18673640489578247,
0.03617598116397858,
0.008811824023723602,
-0.04264665022492409,
0.13855896890163422,
0.04161349684000015,
0.14547798037528992,
0.0306391641497612,
0.08585092425346375,
-0.19310103356838226,
0.016285425052046776,
0.06064919754862785,
-0.01193145476281643,
0.06637270003557205,
0.03414230793714523,
0.021672699600458145,
0.11185363680124283,
-0.08019924908876419,
0.07189125567674637,
0.025606440380215645,
-0.13314539194107056,
-0.25848329067230225,
-0.08868633955717087,
0.028498932719230652,
0.09175728261470795,
0.09827859699726105,
-0.01733391545712948,
0.1577724814414978,
-0.07219334691762924,
0.0822463259100914,
0.23259803652763367,
-0.3017599582672119,
-0.06392474472522736,
0.06329182535409927,
0.060407210141420364,
0.06952180713415146,
-0.09918422251939774,
-0.022713156417012215,
0.08064012229442596,
0.024372654035687447,
0.10179594159126282,
-0.03417203202843666,
-0.02147270366549492,
0.021231256425380707,
-0.1465202420949936,
-0.01412298996001482,
0.13104453682899475,
0.05881623551249504,
-0.04233885928988457,
-0.049490347504615784,
-0.05725359544157982,
-0.12464028596878052,
-0.024668579921126366,
-0.06250603497028351,
0.05204106494784355,
-0.04662610962986946,
-0.08639699965715408,
-0.013125412166118622,
-0.11514074355363846,
-0.10997717082500458,
-0.05627823993563652,
0.15472650527954102,
0.04583180323243141,
0.007370522245764732,
-0.04103749990463257,
0.10846691578626633,
-0.03309895098209381,
-0.13736291229724884,
-0.007961522787809372,
0.02365746907889843,
0.0007960108923725784,
-0.0522579662501812,
-0.052221331745386124,
-0.07304859906435013,
0.03067738004028797,
0.16128993034362793,
-0.07122034579515457,
0.04203873872756958,
0.03461543098092079,
0.032368242740631104,
-0.09460364282131195,
0.17120197415351868,
-0.07083006203174591,
-0.024237846955657005,
-0.003788246773183346,
0.06826156377792358,
0.03885885328054428,
0.005438337102532387,
-0.10960175096988678,
-0.0034798868000507355,
0.10498324781656265,
0.029357315972447395,
-0.05935452878475189,
0.06423874944448471,
-0.050893913954496384,
0.0006217233603820205,
0.024520784616470337,
-0.07061602920293808,
0.022275228053331375,
0.005837098229676485,
-0.06754803657531738,
-0.05093539133667946,
0.012553831562399864,
0.012571057304739952,
0.025585781782865524,
0.11022050678730011,
-0.10287374258041382,
-0.00027356063947081566,
-0.09698246419429779,
-0.12497546523809433,
0.019179081544280052,
-0.08017704635858536,
0.048156868666410446,
-0.11239098012447357,
-0.15220530331134796,
-0.016167649999260902,
0.033983077853918076,
-0.03396071121096611,
0.0009868713095784187,
-0.041082631796598434,
-0.08671524375677109,
-0.006389829330146313,
-0.022912809625267982,
0.08427968621253967,
-0.06097619980573654,
0.10426903516054153,
0.0761461853981018,
0.07196108996868134,
-0.05515319108963013,
0.03171224519610405,
-0.09358756989240646,
0.029103340581059456,
-0.19437113404273987,
0.002703889971598983,
-0.07103852927684784,
0.07447332888841629,
-0.08584396541118622,
-0.09467867761850357,
-0.004345466382801533,
0.021421978250145912,
0.09254085272550583,
0.0921989306807518,
-0.16086964309215546,
-0.05872507765889168,
0.154172882437706,
-0.10164537280797958,
-0.16629624366760254,
0.11124887317419052,
-0.04865622892975807,
0.06850969046354294,
0.06613042950630188,
0.17321845889091492,
0.0473790168762207,
-0.14787471294403076,
0.0034152723383158445,
-0.011297579854726791,
0.03349069505929947,
-0.03146197646856308,
0.05944034457206726,
-0.012774900533258915,
0.03677716106176376,
0.009146460331976414,
-0.0599614754319191,
0.035733964294195175,
-0.10087230056524277,
-0.06996764242649078,
-0.03679034858942032,
-0.1045265644788742,
0.027210403233766556,
0.07391532510519028,
0.055847518146038055,
-0.12409457564353943,
-0.09808170795440674,
0.11047452688217163,
0.08102352172136307,
-0.07346595823764801,
0.00785114523023367,
-0.09170734137296677,
0.06304359436035156,
-0.06880995631217957,
-0.03277114778757095,
-0.1433158963918686,
-0.06692947447299957,
-0.00012100816093152389,
-0.01432926394045353,
0.0016012206906452775,
0.05070940777659416,
0.0824512168765068,
0.062218792736530304,
-0.07113074511289597,
-0.03376549482345581,
-0.06686525046825409,
0.02308451011776924,
-0.11218280345201492,
-0.19682489335536957,
-0.027353409677743912,
-0.030175836756825447,
0.08086387068033218,
-0.21691367030143738,
0.04265988618135452,
0.024320850148797035,
0.0990024134516716,
0.04140666499733925,
-0.0020978557877242565,
-0.0475613996386528,
0.06763745099306107,
-0.026455193758010864,
-0.059912536293268204,
0.037751421332359314,
-0.001387943746522069,
-0.09708327054977417,
-0.06756714731454849,
-0.14260855317115784,
0.19955506920814514,
0.1384807527065277,
-0.08762115240097046,
-0.08619139343500137,
0.009217053651809692,
-0.05346629023551941,
-0.03321010619401932,
-0.031429506838321686,
-0.019948571920394897,
0.10962529480457306,
-0.025642864406108856,
0.12335225939750671,
-0.08749248832464218,
-0.041185274720191956,
0.015588769689202309,
-0.034792039543390274,
0.004117400851100683,
0.10235036909580231,
0.0971398800611496,
-0.10850455611944199,
0.14832226932048798,
0.16295741498470306,
-0.0929587334394455,
0.1289069801568985,
-0.04795454069972038,
-0.08764953166246414,
-0.03606577217578888,
0.01201422605663538,
0.012211772613227367,
0.15939290821552277,
-0.1489924043416977,
0.015100868418812752,
-0.0001388265227433294,
0.013130191713571548,
0.02683730609714985,
-0.22047990560531616,
-0.051724500954151154,
0.030962491407990456,
-0.048734400421381,
-0.018190771341323853,
-0.0006058210856281221,
-0.004659546073526144,
0.09250989556312561,
0.000952089496422559,
-0.05975375697016716,
0.03497617691755295,
-0.0035025430843234062,
-0.0802677720785141,
0.21919582784175873,
-0.05997788906097412,
-0.11164350807666779,
-0.10984619706869125,
-0.012180435471236706,
-0.023885123431682587,
0.026496170088648796,
0.07777079939842224,
-0.08113788068294525,
-0.03623843565583229,
-0.08563047647476196,
0.056351255625486374,
0.012961190193891525,
0.030317828059196472,
0.011628580279648304,
0.015364091843366623,
0.0863620713353157,
-0.13111667335033417,
0.0064240796491503716,
-0.06083964928984642,
-0.05964348092675209,
0.0313485749065876,
0.033002179116010666,
0.1366611272096634,
0.12298338115215302,
-0.016202809289097786,
-0.007817581295967102,
-0.03508370369672775,
0.252311110496521,
-0.08401273190975189,
-0.03817835450172424,
0.1403815895318985,
-0.019279813393950462,
0.03192221000790596,
0.1350611001253128,
0.06396351754665375,
-0.1184944361448288,
0.02809680625796318,
0.048465266823768616,
-0.022772198542952538,
-0.21735969185829163,
-0.005555941257625818,
-0.028503363952040672,
-0.004687315784394741,
0.06201925873756409,
0.03500615432858467,
0.040858544409275055,
0.06660914421081543,
0.019489888101816177,
0.04451194778084755,
-0.019542023539543152,
0.06685485690832138,
0.11693280190229416,
0.028793159872293472,
0.11950742453336716,
-0.05776162073016167,
-0.0704641342163086,
0.02202744036912918,
0.006146504543721676,
0.21544404327869415,
0.023526296019554138,
0.13115103542804718,
0.07663695514202118,
0.1426323801279068,
-0.00795180443674326,
0.054934658110141754,
-0.0031700499821454287,
-0.07212015986442566,
-0.002478399546816945,
-0.04567253962159157,
0.005324091762304306,
0.03977406397461891,
-0.07303184270858765,
0.06575038284063339,
-0.11053211987018585,
-0.0015916017582640052,
0.06470758467912674,
0.19755877554416656,
0.05867043510079384,
-0.32023540139198303,
-0.09853114932775497,
0.017378106713294983,
-0.021825216710567474,
-0.022144386544823647,
0.019532043486833572,
0.12900854647159576,
-0.04084300994873047,
0.024419274181127548,
-0.05275220051407814,
0.0769544467329979,
-0.022423142567276955,
0.048086684197187424,
0.06526654958724976,
0.09056355804204941,
-0.01306772232055664,
0.063175268471241,
-0.3093620240688324,
0.27062880992889404,
0.01730971969664097,
0.1007559522986412,
-0.04468522220849991,
-0.012389241717755795,
0.0010633268393576145,
0.06708605587482452,
0.08737896382808685,
-0.04196638613939285,
-0.03516937047243118,
-0.19088736176490784,
-0.018231047317385674,
0.03680465370416641,
0.11029957979917526,
-0.021633705124258995,
0.10591945052146912,
-0.01223383191972971,
0.017076672986149788,
0.09826047718524933,
-0.0037389923818409443,
-0.10718585550785065,
-0.07135245949029922,
-0.012477260082960129,
-0.00432724691927433,
-0.024608241394162178,
-0.09147729724645615,
-0.09474821388721466,
-0.10774881392717361,
0.11955576390028,
-0.0579385980963707,
-0.02445913851261139,
-0.09803375601768494,
0.08810102939605713,
0.07755686342716217,
-0.07386504858732224,
0.04816873371601105,
0.03343341127038002,
0.05995732918381691,
0.0371527224779129,
-0.041050564497709274,
0.13760462403297424,
-0.06817542761564255,
-0.1787680983543396,
-0.06954389810562134,
0.10022030025720596,
0.037549056112766266,
0.037816379219293594,
0.0012718435609713197,
-0.0008432233589701355,
-0.01012581679970026,
-0.0841451957821846,
0.035414427518844604,
-0.026863334700465202,
0.0589994341135025,
-0.017322946339845657,
-0.033268317580223083,
0.03876137733459473,
-0.044921450316905975,
-0.028015023097395897,
0.13013382256031036,
0.29808148741722107,
-0.0877947211265564,
-0.03100775182247162,
0.05863956734538078,
-0.04861544072628021,
-0.1977662593126297,
0.07991112768650055,
0.02996326982975006,
0.0066489847376942635,
0.06199134141206741,
-0.12685243785381317,
0.10391725599765778,
0.1281786412000656,
-0.026582270860671997,
0.12574276328086853,
-0.31603068113327026,
-0.14053021371364594,
0.12770523130893707,
0.1756119430065155,
0.09703518450260162,
-0.18098761141300201,
-0.031847208738327026,
-0.028144732117652893,
-0.15561455488204956,
0.08640532195568085,
-0.12449938803911209,
0.09831216186285019,
-0.01604439504444599,
0.0408511683344841,
0.00806540995836258,
-0.06759173423051834,
0.14698880910873413,
-0.011143984273076057,
0.12797240912914276,
-0.05931444838643074,
-0.019231360405683517,
0.07735902070999146,
-0.035478536039590836,
0.03265729919075966,
-0.07127656787633896,
0.03943898528814316,
-0.040472690016031265,
-0.04574945569038391,
-0.06005463749170303,
0.04203364998102188,
-0.05506500229239464,
-0.07463553547859192,
-0.05285942927002907,
0.031010806560516357,
0.0057152267545461655,
-0.026859359815716743,
0.14341707527637482,
-0.0002516089880373329,
0.14512325823307037,
0.10208620876073837,
0.08351584523916245,
-0.06009865924715996,
-0.048268985003232956,
0.024399951100349426,
-0.02916467934846878,
0.07888154685497284,
-0.13402040302753448,
0.03614574670791626,
0.12708835303783417,
0.020330997183918953,
0.1362829953432083,
0.07156180590391159,
-0.06448373943567276,
0.02416199818253517,
0.0644824281334877,
-0.1424759328365326,
-0.1617734432220459,
0.0017135401722043753,
-0.06995680928230286,
-0.10667669028043747,
0.10406738519668579,
0.09600353986024857,
-0.06177055090665817,
0.004453826230019331,
-0.005214917007833719,
-0.008304961025714874,
-0.04956164211034775,
0.19384653866291046,
0.08638657629489899,
0.04813167825341225,
-0.07031569629907608,
0.08055556565523148,
0.023948270827531815,
-0.09462953358888626,
0.004770199302583933,
0.0246378555893898,
-0.06217052787542343,
-0.04108681157231331,
0.03755277767777443,
0.17638392746448517,
-0.04274756833910942,
-0.05447353795170784,
-0.16316260397434235,
-0.11828406155109406,
0.04987569525837898,
0.19383184611797333,
0.10025148838758469,
0.019240155816078186,
-0.0019037773599848151,
0.046520352363586426,
-0.12129424512386322,
0.10485395044088364,
0.015884824097156525,
0.08844973891973495,
-0.1597699671983719,
0.12189546227455139,
-0.000478546746307984,
0.003872758010402322,
-0.026957549154758453,
0.06150210276246071,
-0.13881343603134155,
0.007885373197495937,
-0.15746857225894928,
-0.032183460891246796,
-0.040615130215883255,
-0.004687503911554813,
0.014424772933125496,
-0.07947926223278046,
-0.07135949283838272,
0.024189330637454987,
-0.09836786985397339,
-0.012753220275044441,
0.059583667665719986,
0.04655594378709793,
-0.13384301960468292,
-0.0380830354988575,
0.02273908071219921,
-0.06901784241199493,
0.06733791530132294,
0.019028890877962112,
0.03829183429479599,
0.055654507130384445,
-0.17221522331237793,
0.04341226816177368,
0.0680612251162529,
-0.00011202821769984439,
0.057674579322338104,
-0.08445199579000473,
-0.025944693014025688,
-0.006064743734896183,
0.05228004232048988,
0.008678227663040161,
0.04639394208788872,
-0.12729905545711517,
-0.00803515687584877,
-0.03291652724146843,
-0.07170906662940979,
-0.05456339567899704,
0.004687428940087557,
0.10034743696451187,
0.0011023569386452436,
0.1861734241247177,
-0.08022788166999817,
0.01615588553249836,
-0.21063698828220367,
0.001127017429098487,
0.004421671386808157,
-0.0783013254404068,
-0.08603532612323761,
-0.038148727267980576,
0.06160265952348709,
-0.0669197142124176,
0.14701321721076965,
-0.028064265847206116,
0.04235666245222092,
0.04490071162581444,
-0.06087266281247139,
0.07120080292224884,
0.03318661451339722,
0.2567991614341736,
0.005845381412655115,
-0.025475863367319107,
0.0016990938456729054,
0.047325294464826584,
0.09585858136415482,
0.07083946466445923,
0.1843101531267166,
0.18898583948612213,
-0.06332696229219437,
0.10166575759649277,
0.07215709984302521,
-0.05060960724949837,
-0.13643953204154968,
0.042462050914764404,
-0.010020879097282887,
0.05724712088704109,
-0.014450429938733578,
0.1890711784362793,
0.140627920627594,
-0.1540824919939041,
0.005831926595419645,
-0.06056005507707596,
-0.08159150183200836,
-0.1018461287021637,
-0.022828031331300735,
-0.0934397280216217,
-0.17034253478050232,
0.021051356568932533,
-0.11917464435100555,
-0.005907042883336544,
0.09241187572479248,
0.009168420918285847,
-0.025854233652353287,
0.21853826940059662,
0.05600437894463539,
0.040885020047426224,
0.032526250928640366,
0.013802939094603062,
-0.03139219433069229,
-0.0719776451587677,
-0.06107586249709129,
0.011171790771186352,
-0.033665165305137634,
0.006862667389214039,
-0.06069834530353546,
-0.07557602226734161,
0.026237620040774345,
-0.002457413589581847,
-0.087811179459095,
0.005838002078235149,
0.04812825843691826,
0.04296780005097389,
0.05675477907061577,
0.01161846425384283,
0.012559493072330952,
-0.011971255764365196,
0.20012496411800385,
-0.06711356341838837,
-0.06684572994709015,
-0.09148390591144562,
0.2152339220046997,
0.04558257758617401,
0.03967461735010147,
0.019949527457356453,
-0.10953698307275772,
0.03065023384988308,
0.19693723320960999,
0.16814041137695312,
-0.06949974596500397,
0.004644118715077639,
0.010142040438950062,
-0.009477143175899982,
-0.05946976691484451,
0.06862501055002213,
0.11863372474908829,
0.06117338687181473,
-0.07045784592628479,
-0.054975226521492004,
-0.03887112811207771,
-0.004258463159203529,
-0.016418106853961945,
0.05447130277752876,
0.0552789568901062,
0.012301395647227764,
-0.05284879729151726,
0.06932845711708069,
-0.028076689690351486,
-0.1414439082145691,
0.10062863677740097,
-0.18650822341442108,
-0.13551603257656097,
-0.008536526933312416,
0.12452880293130875,
-0.02784794010221958,
0.06821782886981964,
-0.04209345951676369,
-0.006163060665130615,
0.05936660245060921,
-0.011282973922789097,
-0.0807652622461319,
-0.09058614075183868,
0.07375401258468628,
-0.057236794382333755,
0.2214251458644867,
-0.04655138775706291,
0.08100631088018417,
0.1395723968744278,
0.04479595646262169,
-0.085710808634758,
0.10965999960899353,
0.06477101147174835,
-0.10309650748968124,
0.023486880585551262,
0.06887388229370117,
-0.030764801427721977,
0.1125839427113533,
0.05756469443440437,
-0.17370323836803436,
0.017539795488119125,
-0.05141088366508484,
-0.08396769315004349,
-0.07831043750047684,
-0.022971875965595245,
-0.06975920498371124,
0.12459374219179153,
0.18116888403892517,
-0.04183170944452286,
0.017328189685940742,
-0.04102650657296181,
0.04204118996858597,
0.08179289847612381,
0.06065557524561882,
-0.028332456946372986,
-0.2366221398115158,
0.0507507286965847,
0.07513764500617981,
-0.028082553297281265,
-0.245274156332016,
-0.08732671290636063,
0.014222291298210621,
-0.05921506509184837,
-0.07213522493839264,
0.06115119159221649,
0.11749490350484848,
0.06342321634292603,
-0.06430649757385254,
-0.11061112582683563,
-0.08660195022821426,
0.16492271423339844,
-0.1454499363899231,
-0.11135520786046982
] |
null | null | null |
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
```python
from kornia.contrib import VisionTransformer
vit_model = VisionTransformer.from_config('vit_ti/16', pretrained=True)
...
```
Original weights from [AugReg](https://arxiv.org/abs/2106.10270) as recommended by [google research vision transformer repo](https://github.com/google-research/vision_transformer): This weight is based on the
[AugReg ViT_Ti/16 pretrained on imagenet21k](https://storage.googleapis.com/vit_models/augreg/Ti_16-i21k-300ep-lr_0.001-aug_none-wd_0.03-do_0.0-sd_0.0.npz)
Weights converted to PyTorch for Kornia ViT implementation (by [@gau-nernst](https://github.com/gau-nernst) in [kornia/kornia#2786](https://github.com/kornia/kornia/pull/2786#discussion_r1482339811))
<details>
<summary>Convert jax checkpoint function</summary>
```
def convert_jax_checkpoint(np_state_dict: dict[str, np.ndarray]):
def get_weight(key: str) -> torch.Tensor:
return torch.from_numpy(np_state_dict[key])
state_dict = dict()
state_dict["patch_embedding.cls_token"] = get_weight("cls")
state_dict["patch_embedding.backbone.weight"] = get_weight("embedding/kernel").permute(3, 2, 0, 1) # conv »
state_dict["patch_embedding.backbone.bias"] = get_weight("embedding/bias")
state_dict["patch_embedding.positions"] = get_weight("Transformer/posembed_input/pos_embedding").squeeze(0)
# for i, block in enumerate(self.encoder.blocks):
for i in range(100):
prefix1 = f"encoder.blocks.{i}"
prefix2 = f"Transformer/encoderblock_{i}"
if f"{prefix2}/LayerNorm_0/scale" not in np_state_dict:
break
state_dict[f"{prefix1}.0.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_0/scale")
state_dict[f"{prefix1}.0.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_0/bias")
mha_prefix = f"{prefix2}/MultiHeadDotProductAttention_1"
qkv_weight = [get_weight(f"{mha_prefix}/{x}/kernel") for x in ["query", "key", "value"]]
qkv_bias = [get_weight(f"{mha_prefix}/{x}/bias") for x in ["query", "key", "value"]]
state_dict[f"{prefix1}.0.fn.1.qkv.weight"] = torch.cat(qkv_weight, 1).flatten(1).T
state_dict[f"{prefix1}.0.fn.1.qkv.bias"] = torch.cat(qkv_bias, 0).flatten()
state_dict[f"{prefix1}.0.fn.1.projection.weight"] = get_weight(f"{mha_prefix}/out/kernel").flatten(0, 1»
state_dict[f"{prefix1}.0.fn.1.projection.bias"] = get_weight(f"{mha_prefix}/out/bias")
state_dict[f"{prefix1}.1.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_2/scale")
state_dict[f"{prefix1}.1.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_2/bias")
state_dict[f"{prefix1}.1.fn.1.0.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/kernel").T
state_dict[f"{prefix1}.1.fn.1.0.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/bias")
state_dict[f"{prefix1}.1.fn.1.3.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/kernel").T
state_dict[f"{prefix1}.1.fn.1.3.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/bias")
state_dict["norm.weight"] = get_weight("Transformer/encoder_norm/scale")
state_dict["norm.bias"] = get_weight("Transformer/encoder_norm/bias")
return state_dict
```
</details> | {"license": "apache-2.0", "pipeline_tag": "image-classification"} | image-classification | kornia/vit_ti16_augreg_i21k_r224 | [
"image-classification",
"arxiv:2106.10270",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:35:50+00:00 | [
"2106.10270"
] | [] | TAGS
#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us
|
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Original weights from AugReg as recommended by google research vision transformer repo: This weight is based on the
AugReg ViT_Ti/16 pretrained on imagenet21k
Weights converted to PyTorch for Kornia ViT implementation (by @gau-nernst in kornia/kornia#2786)
<details>
<summary>Convert jax checkpoint function</summary>
</details> | [] | [
"TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
27
] | [
"passage: TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
-0.06109374389052391,
0.20674705505371094,
-0.006548014469444752,
0.049976740032434464,
0.02543392963707447,
0.06775278598070145,
0.1434560865163803,
0.10054779052734375,
0.0873129591345787,
-0.0696193128824234,
0.16259659826755524,
0.07446799427270889,
0.027905816212296486,
-0.020278295502066612,
0.0003193104930687696,
-0.19860264658927917,
0.07249123603105545,
-0.01418757252395153,
-0.03743588179349899,
0.016364481300115585,
0.031079968437552452,
-0.03377098590135574,
0.06803242117166519,
-0.013396034017205238,
-0.12081167846918106,
-0.004631385672837496,
0.05561913177371025,
-0.04842509329319,
0.07639530301094055,
-0.0024446528404951096,
0.03034677915275097,
0.033661652356386185,
0.0436035580933094,
-0.18721453845500946,
-0.0013201063266023993,
-0.011022438295185566,
-0.13286513090133667,
0.06692822277545929,
0.12416379153728485,
0.0049120765179395676,
0.03520214185118675,
0.04749228432774544,
-0.1190459355711937,
0.007217442616820335,
-0.09456748515367508,
-0.2383200079202652,
-0.10159328579902649,
0.11124194413423538,
0.12468010187149048,
0.01974388025701046,
0.10125472396612167,
0.03719622269272804,
-0.12143778800964355,
0.007481607608497143,
0.07237470895051956,
-0.24169990420341492,
-0.010691691190004349,
0.1201784610748291,
-0.1079055592417717,
0.04524125158786774,
-0.03944199159741402,
0.09898041188716888,
0.0823771059513092,
-0.045112185180187225,
-0.11518827825784683,
-0.045906227082014084,
-0.11930672824382782,
0.05414021015167236,
0.02489721029996872,
-0.08919412642717361,
0.3176185190677643,
0.1532946676015854,
0.002456814516335726,
0.11417848616838455,
-0.034857455641031265,
0.03917086496949196,
-0.020580649375915527,
0.14350418746471405,
0.11800917983055115,
0.1277526319026947,
0.11405012756586075,
-0.018727514892816544,
-0.18136470019817352,
-0.06914898008108139,
-0.16194461286067963,
-0.04335305839776993,
-0.03692782297730446,
0.17465905845165253,
-0.1323341280221939,
-0.02526034042239189,
-0.1357729136943817,
-0.08216837048530579,
0.02422415465116501,
-0.0783277153968811,
0.17794139683246613,
0.12570883333683014,
-0.025183117017149925,
0.05908667668700218,
0.14745140075683594,
0.12899348139762878,
0.02096019685268402,
0.03532757610082626,
-0.10447050631046295,
0.19674737751483917,
-0.02905309945344925,
0.03755328059196472,
0.03452769294381142,
0.11503022909164429,
0.06668683886528015,
-0.08765921741724014,
0.09905751049518585,
-0.034111931920051575,
-0.1760949343442917,
-0.02817642129957676,
-0.0438312403857708,
0.051844481378793716,
-0.0005061799311079085,
-0.04923499748110771,
-0.07902505248785019,
0.02592616155743599,
0.20208676159381866,
0.005098436959087849,
0.00970771349966526,
-0.009410499595105648,
-0.01887846365571022,
-0.03703097999095917,
0.06327838450670242,
0.020843954756855965,
0.06386575847864151,
-0.00038021898944862187,
-0.07227174192667007,
0.04220779612660408,
0.0033467260655015707,
0.07464555650949478,
0.11725340783596039,
-0.033287424594163895,
0.031015444546937943,
-0.1253310889005661,
-0.06270439177751541,
0.03723682835698128,
0.086534284055233,
0.0028114039450883865,
0.01238210964947939,
0.11720160394906998,
0.014849238097667694,
0.03825271129608154,
-0.03593437746167183,
-0.060856327414512634,
-0.099258191883564,
0.055119361728429794,
-0.13103467226028442,
0.08423157781362534,
-0.2563755214214325,
0.011386703699827194,
-0.10534657537937164,
0.053238339722156525,
-0.09686396270990372,
-0.07819923013448715,
-0.13250695168972015,
0.2009194940328598,
-0.05468209087848663,
0.0034654189366847277,
-0.054602500051259995,
-0.00633781123906374,
-0.05506056174635887,
0.07645745575428009,
-0.15609174966812134,
0.02364489808678627,
0.08345842361450195,
-0.15114741027355194,
-0.13571877777576447,
-0.002641590777784586,
0.043754223734140396,
-0.07488250732421875,
-0.010925939306616783,
0.3182951807975769,
-0.03542245179414749,
-0.01839727908372879,
0.036988433450460434,
0.15065109729766846,
-0.08740837126970291,
-0.20893323421478271,
0.10468775033950806,
-0.09690731018781662,
-0.14157627522945404,
0.0215351153165102,
-0.13635723292827606,
0.10152363032102585,
0.040783826261758804,
-0.08645343035459518,
-0.02261362224817276,
-0.04002821445465088,
-0.04111453890800476,
0.012164331041276455,
0.05289793014526367,
-0.046031367033720016,
0.036598462611436844,
-0.10292722284793854,
0.05292672663927078,
0.08823665231466293,
0.03464950621128082,
-0.019848383963108063,
0.05194208770990372,
-0.0322202704846859,
-0.008407019078731537,
-0.06743084639310837,
0.03886767849326134,
0.009944709949195385,
-0.047629464417696,
0.08154439926147461,
-0.05256316438317299,
0.028394905850291252,
-0.08248095214366913,
-0.0052256197668612,
-0.03148965165019035,
-0.021348997950553894,
0.016548115760087967,
0.04151642695069313,
-0.15185265243053436,
0.05146369710564613,
0.027628103271126747,
0.06300205737352371,
-0.07534655928611755,
-0.06911735236644745,
0.13192912936210632,
-0.02104104869067669,
-0.006522714160382748,
0.09356412291526794,
0.007906613871455193,
-0.09177529066801071,
-0.01047999132424593,
-0.02048683352768421,
0.1222124695777893,
0.01773674599826336,
-0.03080260008573532,
0.15719905495643616,
0.004599755629897118,
0.1652202308177948,
0.19648905098438263,
-0.1871400624513626,
0.05895731970667839,
-0.04543163627386093,
0.03526407852768898,
-0.00021277944324538112,
0.058195192366838455,
0.030574873089790344,
-0.11539100110530853,
-0.0529194250702858,
0.04648087918758392,
-0.0637110099196434,
0.08189071714878082,
-0.016040494665503502,
-0.07081851363182068,
-0.09113258868455887,
-0.004617263562977314,
0.22731298208236694,
-0.22143718600273132,
0.13705743849277496,
0.44992348551750183,
-0.00563804479315877,
0.04384651407599449,
-0.07071708142757416,
-0.02926171012222767,
0.011590258218348026,
-0.016685742884874344,
-0.027885599061846733,
0.20283104479312897,
-0.037577949464321136,
-0.006611361168324947,
0.07687141746282578,
0.021334122866392136,
0.02833111397922039,
-0.2102135717868805,
-0.08647490292787552,
-0.01990378089249134,
-0.032265402376651764,
-0.106113001704216,
-0.03494508937001228,
-0.07398673892021179,
0.09487839788198471,
-0.00005973442966933362,
-0.13227896392345428,
0.12197559326887131,
-0.04474426805973053,
-0.053833432495594025,
0.1027798280119896,
-0.1763962209224701,
-0.23515380918979645,
-0.14439262449741364,
0.03435428440570831,
-0.07389409840106964,
0.033989984542131424,
0.05001555383205414,
-0.12449482828378677,
-0.042997002601623535,
0.009898168034851551,
-0.17011038959026337,
-0.0666801705956459,
-0.009744573384523392,
0.04772152379155159,
0.06096755340695381,
0.05611218884587288,
-0.07783979177474976,
-0.04949898272752762,
-0.03132689744234085,
0.022898364812135696,
0.13073059916496277,
-0.10337543487548828,
0.13391651213169098,
0.08956552296876907,
-0.0060893171466887,
0.037197306752204895,
0.024989010766148567,
0.06867308169603348,
-0.06233874335885048,
-0.009597424417734146,
0.15581579506397247,
-0.009040242061018944,
0.06215013191103935,
0.12999725341796875,
0.06666824221611023,
-0.09433972090482712,
-0.022919438779354095,
-0.01883879117667675,
-0.09602656215429306,
-0.19175516068935394,
-0.057091742753982544,
-0.049366164952516556,
0.08483017235994339,
0.14666369557380676,
0.11997713893651962,
0.16513875126838684,
0.09672091901302338,
0.017073094844818115,
0.032890960574150085,
0.011969516053795815,
0.02745753899216652,
0.09431096166372299,
-0.00256404560059309,
-0.00900819431990385,
-0.1345144361257553,
0.04063615947961807,
0.16199742257595062,
0.16016624867916107,
0.2346680760383606,
0.24405603110790253,
0.013032541610300541,
0.08629986643791199,
0.14010414481163025,
0.09959616512060165,
0.083418108522892,
0.014013865031301975,
0.0002983128360938281,
-0.07782557606697083,
-0.06522127240896225,
0.007191324606537819,
0.08919525146484375,
-0.056596651673316956,
-0.13630864024162292,
0.04233114793896675,
-0.15700164437294006,
0.043609846383333206,
0.08521639555692673,
0.10101553797721863,
-0.12919598817825317,
0.11238693445920944,
0.07870315760374069,
0.13523606956005096,
-0.033454976975917816,
0.12932239472866058,
-0.03169083222746849,
-0.008430219255387783,
0.1317882388830185,
0.007853557355701923,
0.08151012659072876,
-0.024717014282941818,
-0.0011054257629439235,
-0.017972934991121292,
-0.23283958435058594,
0.0644598975777626,
0.10178142786026001,
-0.11300219595432281,
0.27768510580062866,
0.031322941184043884,
-0.12874376773834229,
-0.04034474864602089,
-0.036046352237463,
0.12492694705724716,
0.22686100006103516,
0.1506083458662033,
0.08461418747901917,
-0.2186128795146942,
-0.015754923224449158,
-0.09932077676057816,
-0.0005119231645949185,
0.029082471504807472,
0.023185651749372482,
-0.18783825635910034,
0.0009278097422793508,
0.018264522776007652,
0.001460708910599351,
0.1566782295703888,
-0.10841827839612961,
-0.0659492164850235,
0.00179493788164109,
0.08047734946012497,
-0.04437811300158501,
-0.06396231800317764,
0.034309569746255875,
-0.013767643831670284,
0.036747898906469345,
-0.022247834131121635,
-0.004408868495374918,
-0.04094367474317551,
-0.12550413608551025,
0.021679183468222618,
-0.017714237794280052,
0.029833028092980385,
-0.08279894292354584,
-0.04034486040472984,
-0.06748219579458237,
-0.23039697110652924,
0.14154691994190216,
-0.07678768783807755,
0.016050616279244423,
-0.05765075236558914,
0.05977974832057953,
-0.0824442207813263,
0.00418700510635972,
-0.0022916689049452543,
0.056743767112493515,
-0.033833812922239304,
-0.10060850530862808,
0.1735401153564453,
-0.02724578231573105,
0.046342626214027405,
-0.00022314728994388133,
-0.05170644447207451,
-0.035063985735177994,
0.012569589540362358,
-0.02630540169775486,
0.1234268769621849,
0.2582937479019165,
-0.11369399726390839,
0.11319419741630554,
0.22277510166168213,
-0.08378475159406662,
-0.2901381254196167,
-0.0702567845582962,
-0.18003669381141663,
-0.1256219744682312,
0.052320681512355804,
-0.19621984660625458,
0.14071376621723175,
0.22147466242313385,
-0.14830414950847626,
0.229997918009758,
-0.14988930523395538,
-0.030987894162535667,
0.15975996851921082,
-0.0008190532680600882,
0.3081471621990204,
-0.19845253229141235,
-0.06818240880966187,
-0.12761925160884857,
-0.15836204588413239,
0.155714213848114,
-0.025408737361431122,
0.006225026212632656,
-0.007217234466224909,
-0.08931957185268402,
-0.02436586655676365,
0.004366954322904348,
0.24909676611423492,
0.004330891650170088,
0.16055257618427277,
-0.11767592281103134,
-0.12619024515151978,
0.11690738052129745,
-0.06503412872552872,
-0.0007165660499595106,
-0.10723470896482468,
-0.010643302462995052,
-0.11397052556276321,
0.09066908806562424,
-0.05764220282435417,
0.04375004768371582,
0.02174108289182186,
-0.017453894019126892,
-0.10904242843389511,
-0.005453106015920639,
-0.09661629796028137,
0.0515119843184948,
0.356973797082901,
0.056218892335891724,
-0.06076716259121895,
0.09476302564144135,
-0.045844666659832,
-0.09363016486167908,
-0.04768260940909386,
-0.12678976356983185,
-0.0685768872499466,
0.1280103325843811,
-0.30839988589286804,
0.06342349946498871,
0.060435857623815536,
-0.0101803969591856,
0.05798220634460449,
0.0419137105345726,
-0.008689306676387787,
-0.002610941184684634,
0.18246068060398102,
-0.041163694113492966,
-0.013913077302277088,
0.022781025618314743,
0.1528378427028656,
0.20284785330295563,
0.038649726659059525,
0.07634012401103973,
0.016211945563554764,
0.004480070900171995,
0.037742264568805695,
0.07341662049293518,
-0.0799650028347969,
-0.060552340000867844,
0.0995108038187027,
-0.0472230538725853,
-0.08839789032936096,
0.2580071687698364,
0.06586729735136032,
-0.040969472378492355,
-0.060587961226701736,
0.023097578436136246,
-0.06413619965314865,
-0.106551893055439,
-0.029016191139817238,
0.007275809999555349,
-0.14201894402503967,
-0.14605849981307983,
0.029940688982605934,
-0.055694930255413055,
-0.036023736000061035,
-0.0009951975662261248,
0.0818314328789711,
0.01024248544126749,
0.10877418518066406,
-0.050103265792131424,
0.1298569291830063,
-0.07700810581445694,
-0.21583467721939087,
0.044681038707494736,
-0.1390920728445053,
-0.24245065450668335,
0.05320950597524643,
0.07469253987073898,
-0.029019640758633614,
-0.011899758130311966,
-0.06899982690811157,
0.06061933934688568,
-0.1356326937675476,
0.12674148380756378,
-0.05317538231611252,
0.017484011128544807,
0.023907091468572617,
-0.030213210731744766,
-0.043195463716983795,
0.009983353316783905,
-0.15352073311805725,
-0.06672659516334534,
-0.0035989026073366404,
0.06315059959888458,
-0.0489853136241436,
-0.08843541145324707,
0.08217836916446686,
0.04006815701723099,
0.08011067658662796,
0.07868228107690811,
0.00977279432117939,
0.0726410523056984,
-0.18324869871139526,
-0.1208200752735138,
0.14623382687568665,
0.025101887062191963,
-0.048409875482320786,
0.08060428500175476,
-0.039926428347826004,
0.04881305247545242,
-0.08390691131353378,
0.006642403081059456,
0.0034260768443346024,
-0.1251237690448761,
-0.09406817704439163,
-0.09683351963758469,
-0.15214946866035461,
0.00039810591260902584,
-0.04967843368649483,
0.1913544088602066,
0.008625444024801254,
0.0807836502790451,
0.036689359694719315,
-0.006731836590915918,
-0.051704924553632736,
0.02872658520936966,
-0.041187088936567307,
-0.10434682667255402,
-0.17093461751937866,
-0.015617710538208485,
-0.0860636904835701,
-0.1006554514169693,
0.2431410551071167,
0.048497993499040604,
-0.1993618756532669,
0.02384042739868164,
0.18894675374031067,
-0.07109846919775009,
0.023319972679018974,
0.25406286120414734,
0.00019303734006825835,
0.025920644402503967,
-0.02808104082942009,
0.026976024731993675,
0.021667996421456337,
-0.02375073917210102,
0.026855897158384323,
0.12996679544448853,
0.043553244322538376,
0.032946716994047165,
0.14659735560417175,
-0.0173412524163723,
-0.08477585017681122,
0.022847771644592285,
0.061927322298288345,
0.1110801249742508,
0.04275544360280037,
0.04724521189928055,
0.21924637258052826,
-0.0042988271452486515,
-0.00025624613044783473,
-0.05579526722431183,
0.011268865317106247,
-0.08793025463819504,
-0.1877223551273346,
-0.05527739226818085,
-0.17583560943603516,
0.049897871911525726,
-0.004426159430295229,
-0.012788284569978714,
0.2909761965274811,
0.027319302782416344,
-0.0482502318918705,
-0.06282444298267365,
-0.16109506785869598,
-0.07760324329137802,
0.06602004915475845,
-0.00034622318344190717,
-0.07779118418693542,
-0.04654536023736,
-0.05229349806904793,
0.06716009229421616,
-0.0650051012635231,
-0.044580407440662384,
0.00833569560199976,
0.08897022902965546,
-0.0011313384165987372,
-0.059533439576625824,
-0.058417774736881256,
-0.07093261927366257,
0.007818278856575489,
-0.041152771562337875,
0.13718730211257935,
0.014150754548609257,
0.061706382781267166,
0.08388342708349228,
0.0832892581820488,
-0.04481666162610054,
-0.005954330787062645,
0.01730518601834774,
0.024704741314053535,
-0.14028121531009674,
0.07547515630722046,
-0.05182021111249924,
-0.046783607453107834,
0.011663789860904217,
0.16521625220775604,
0.19023829698562622,
-0.10069664567708969,
-0.03277084603905678,
-0.03297418728470802,
0.010275846347212791,
0.013714811764657497,
0.13700632750988007,
0.08500899374485016,
0.08871713280677795,
-0.032855018973350525,
-0.061874307692050934,
-0.06518110632896423,
0.015506909228861332,
-0.14511807262897491,
0.03136218339204788,
0.038375891745090485,
-0.08714506775140762,
-0.0889124721288681,
0.12509585916996002,
0.014278160408139229,
0.11131628602743149,
0.16461534798145294,
-0.05992981046438217,
-0.024726636707782745,
0.014439063146710396,
0.15600472688674927,
0.035410262644290924,
-0.006145869381725788,
-0.15497305989265442,
-0.06066638603806496,
-0.03294585272669792,
0.0111419428139925,
-0.3058968782424927,
-0.16970622539520264,
-0.008374981582164764,
-0.0351867713034153,
0.30137813091278076,
0.027061674743890762,
0.06243366748094559,
0.008204973302781582,
0.02186395600438118,
-0.10690846294164658,
0.08221492171287537,
-0.02377958409488201,
0.01824123226106167,
-0.08009807765483856,
-0.11080692708492279,
-0.03178728371858597,
-0.03495577722787857,
0.1160794198513031,
0.059739332646131516,
-0.02478528767824173,
0.20401827991008759,
-0.09265992045402527,
-0.053211916238069534,
0.013441485352814198,
-0.18209552764892578,
0.028789974749088287,
-0.048542529344558716,
-0.005964033771306276,
-0.13737298548221588,
-0.047639016062021255,
-0.04662676155567169,
0.07773999124765396,
-0.2452046424150467,
-0.04547024518251419,
0.22630788385868073,
-0.009974819608032703,
0.022548647597432137,
0.05865916237235069,
0.05990443006157875,
0.0051626162603497505,
-0.10867731273174286,
0.03566248342394829,
-0.07021775841712952,
0.012532292865216732,
0.11721400171518326,
-0.03954120725393295,
-0.00978852342814207,
-0.12052185088396072,
0.08994459360837936,
-0.02892490290105343,
0.04041118174791336,
-0.08855695277452469
] |
null | null | transformers |
## MiquMaid v2
Check out our blogpost about this model series [Here!](https://ikaridevgit.github.io/index.html?blog=blogid-6&bo=true#Miqu-base) - Join our Discord server [Here!](https://discord.gg/Bb8pRUXy3Z)
<center>[<a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B">V2-70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B-DPO">V2-70B-DPO</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B">V2-2x70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B-DPO">V2-2x70B-DPO</a>]
</br>
<div style="width: 100%;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/1ziZ_5Rl7bsQKFrgH6ZCf.png" style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca **prompting format**
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: [FP16](https://huggingface.co/NeverSleep/MiquMaid-v2-70B) - [GGUF](https://huggingface.co/NeverSleep/MiquMaid-v2-70B-GGUF)
## Training data used:
- [Aesir datasets](https://huggingface.co/MinervaAI)
- [NoRobots](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt)
- [limarp](https://huggingface.co/datasets/lemonilia/LimaRP)
- [toxic-dpo-v0.1-sharegpt](https://huggingface.co/datasets/Undi95/toxic-dpo-v0.1-sharegpt)
- [ToxicQAFinal](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAFinal)
### Custom format:
```
### Instruction:
{system prompt}
### Input:
{input}
### Response:
{reply}
```
## Others
Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).
IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | text-generation | LoneStriker/MiquMaid-v2-70B-4.0bpw-h6-exl2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T01:36:02+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## MiquMaid v2
Check out our blogpost about this model series Here! - Join our Discord server Here!
<center>[<a href="URL - <a href="URL - <a href="URL - <a href="URL
</br>
<div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: FP16 - GGUF
## Training data used:
- Aesir datasets
- NoRobots
- limarp
- toxic-dpo-v0.1-sharegpt
- ToxicQAFinal
### Custom format:
## Others
Undi: If you want to support us, you can here.
IkariDev: Visit my retro/neocities style website please kek | [
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
75,
121,
11,
30,
40,
5,
32
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.## Credits:\n- Undi\n- IkariDev## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal### Custom format:## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
-0.09447834640741348,
0.17205014824867249,
-0.005602731369435787,
0.01779203675687313,
0.11820747703313828,
0.045264896005392075,
0.11447285860776901,
0.15961068868637085,
0.06829394400119781,
0.05906902998685837,
0.0005873226327821612,
0.11407624930143356,
0.07548845559358597,
0.22948826849460602,
-0.006628913804888725,
-0.14427904784679413,
0.046850357204675674,
-0.026289891451597214,
-0.02635573409497738,
0.09569915384054184,
0.07466454803943634,
-0.04618130251765251,
0.0709284171462059,
0.010442404076457024,
-0.10720876604318619,
-0.017348533496260643,
0.0019323929445818067,
-0.05718233436346054,
0.04780259355902672,
0.04367207735776901,
0.0479082316160202,
0.05087536945939064,
0.00845402292907238,
-0.22662657499313354,
0.047140758484601974,
0.07308577746152878,
-0.025127466768026352,
0.07861552387475967,
0.10886233299970627,
-0.04211974889039993,
0.02646409347653389,
-0.03574787452816963,
-0.02210289053618908,
0.09350186586380005,
-0.11214648932218552,
-0.12319593131542206,
-0.11320719122886658,
0.13006889820098877,
0.06314875930547714,
0.08198896050453186,
0.0033554788678884506,
0.1101357564330101,
-0.07631256431341171,
0.07790177315473557,
0.20335930585861206,
-0.16871041059494019,
-0.02322721853852272,
0.05624805763363838,
-0.015333202667534351,
-0.05565005913376808,
-0.09832000732421875,
0.011083890683948994,
0.010926350019872189,
-0.019533375278115273,
-0.0038207839243113995,
-0.041167840361595154,
0.004284780006855726,
-0.06099749729037285,
-0.059463758021593094,
-0.016264086589217186,
0.24300093948841095,
0.0361378937959671,
-0.07370094209909439,
-0.0026136080268770456,
-0.006493517197668552,
0.11463554203510284,
-0.05098545923829079,
0.030949248000979424,
0.005614427383989096,
-0.0010702924337238073,
-0.0032837465405464172,
-0.04595240205526352,
-0.10275456309318542,
-0.05733378976583481,
-0.014142698608338833,
0.14566513895988464,
0.017552156001329422,
0.00008401479135500267,
-0.004768410697579384,
0.051651932299137115,
-0.10471507161855698,
-0.12298901379108429,
-0.06133059412240982,
-0.10231878608465195,
-0.005009785760194063,
-0.042668018490076065,
-0.022182224318385124,
-0.06640303134918213,
0.12371482700109482,
0.1403876692056656,
-0.04801563546061516,
-0.0030525391921401024,
-0.025033647194504738,
0.00783479306846857,
0.005412905476987362,
-0.00017629309149924666,
-0.07161558419466019,
-0.023959118872880936,
0.07290422171354294,
0.025751972571015358,
0.004980665165930986,
0.010289043188095093,
-0.044097792357206345,
-0.07064660638570786,
-0.04732796177268028,
0.05287690833210945,
0.07054515182971954,
0.06856327503919601,
-0.07649759203195572,
-0.047711774706840515,
0.22618921101093292,
-0.10658138245344162,
0.029063958674669266,
0.05863291397690773,
-0.007088409271091223,
0.10424129664897919,
0.06771936267614365,
-0.0006956448778510094,
-0.06505299359560013,
0.016184480860829353,
-0.041465580463409424,
0.03125211223959923,
-0.08675958216190338,
-0.05394180864095688,
0.0855826810002327,
0.0812700167298317,
-0.03331775963306427,
-0.1366315633058548,
-0.10328203439712524,
-0.01740688644349575,
0.02815520204603672,
-0.023310357704758644,
0.0012498353607952595,
0.04892998933792114,
-0.05491432547569275,
0.01405452098697424,
0.01705477572977543,
0.00629244651645422,
-0.05887370929121971,
0.07736124843358994,
0.022486159577965736,
0.09428157657384872,
0.019443463534116745,
0.025946028530597687,
-0.035123471170663834,
0.002149750478565693,
-0.23019294440746307,
0.05012257769703865,
-0.10595361143350601,
0.0038321600295603275,
-0.0922209694981575,
0.0014835012843832374,
-0.027800843119621277,
-0.009975400753319263,
0.0055687217973172665,
0.20525269210338593,
-0.14585432410240173,
-0.05596565082669258,
0.304247111082077,
-0.15955102443695068,
-0.09778694808483124,
0.09222670644521713,
0.03642375022172928,
-0.07440096139907837,
0.06239297613501549,
0.08249494433403015,
0.1056317463517189,
-0.16265460848808289,
-0.09710903465747833,
-0.011078423820436,
-0.022652560845017433,
-0.024000728502869606,
0.0878278836607933,
-0.018813995644450188,
0.03245491161942482,
0.019763432443141937,
-0.03379102423787117,
0.07007033377885818,
-0.025310136377811432,
-0.022386055439710617,
-0.03589578717947006,
-0.06099054589867592,
0.05183964595198631,
-0.002879094798117876,
-0.0388391874730587,
-0.006428318098187447,
-0.04584600031375885,
-0.06035709008574486,
0.13202428817749023,
-0.004858740605413914,
-0.020473629236221313,
-0.07851582020521164,
0.09554000943899155,
-0.05498090013861656,
0.03728895261883736,
-0.13830018043518066,
-0.06243045628070831,
0.0036350893788039684,
-0.0796012431383133,
0.02157106250524521,
-0.0041148848831653595,
0.05950147658586502,
0.038105957210063934,
-0.04352330043911934,
-0.028907326981425285,
-0.0057363444939255714,
0.004301073960959911,
-0.025426069274544716,
-0.1666073054075241,
-0.0007695230888202786,
-0.0551750548183918,
0.1374220848083496,
-0.16868118941783905,
0.05043652653694153,
0.05925111472606659,
0.16357283294200897,
0.03616755083203316,
-0.031011521816253662,
0.11654403805732727,
-0.03804580122232437,
-0.006411012262105942,
-0.03725241497159004,
0.0044607375748455524,
0.002538213739171624,
-0.011939228512346745,
0.10659566521644592,
-0.06065728887915611,
0.054277852177619934,
0.12642189860343933,
-0.01595868356525898,
-0.05425528809428215,
-0.06506265699863434,
-0.01521784346550703,
-0.006736948620527983,
-0.048000186681747437,
-0.047349583357572556,
0.02513136900961399,
0.0662446990609169,
0.07768423110246658,
-0.03797391429543495,
-0.008253731764853,
0.0011901968391612172,
-0.0948609709739685,
-0.0020795518066734076,
0.0409865640103817,
0.05132393538951874,
-0.14333368837833405,
0.09081240743398666,
0.09744595736265182,
-0.015339801087975502,
0.14312495291233063,
0.008754834532737732,
-0.1070873811841011,
-0.003728162497282028,
0.027940761297941208,
0.05264529958367348,
0.0774049460887909,
-0.03596934303641319,
0.02683958038687706,
0.08106063306331635,
-0.05121877044439316,
0.007932554930448532,
-0.09500398486852646,
-0.022678673267364502,
-0.013256699778139591,
-0.0758146122097969,
-0.04612674191594124,
0.03610261529684067,
0.030104612931609154,
0.0918031707406044,
-0.015134556218981743,
0.07633049786090851,
-0.0010367896175011992,
-0.02394755184650421,
-0.09206201136112213,
0.1670486181974411,
-0.0899675041437149,
-0.27366867661476135,
-0.1188458725810051,
-0.07167717814445496,
-0.04199657961726189,
0.004022621084004641,
0.02857130952179432,
-0.12134306877851486,
-0.07081691175699234,
-0.03115151636302471,
-0.0038425917737185955,
0.06778023391962051,
-0.03805195540189743,
-0.02431504614651203,
0.05526971071958542,
0.09138014912605286,
-0.07273191213607788,
-0.002759605646133423,
0.06194623187184334,
-0.037675220519304276,
0.08085193485021591,
0.008549315854907036,
0.10605848580598831,
0.04739413037896156,
0.03012051060795784,
0.0015264216344803572,
0.04311876371502876,
0.17313145101070404,
-0.10127022117376328,
0.09718520194292068,
0.20746180415153503,
0.0394415408372879,
0.08480402082204819,
0.15171074867248535,
0.05122246593236923,
-0.013119645416736603,
-0.005120322108268738,
0.04244927689433098,
0.011746162548661232,
-0.2427690476179123,
-0.061469703912734985,
-0.05656198412179947,
-0.054776955395936966,
0.022767482325434685,
0.047591015696525574,
0.0650729089975357,
0.1047578752040863,
-0.10416096448898315,
-0.016062086448073387,
0.022997045889496803,
0.09911724179983139,
0.047439564019441605,
0.022038234397768974,
0.061993930488824844,
-0.04141371324658394,
0.015599393285810947,
0.12155410647392273,
0.06473620980978012,
0.11147889494895935,
-0.023897795006632805,
0.08020832389593124,
0.06728237122297287,
0.0892438217997551,
0.0530114471912384,
0.06319621205329895,
0.04218849167227745,
-0.014131366275250912,
-0.0013301256112754345,
-0.08454640209674835,
-0.04801497980952263,
0.023290416225790977,
0.013235284946858883,
-0.057533953338861465,
-0.0392376184463501,
-0.01914895512163639,
0.07390332221984863,
0.1574147492647171,
0.04597143456339836,
-0.20930512249469757,
-0.05056460201740265,
0.033859558403491974,
-0.0003397460968699306,
-0.06584210693836212,
-0.033550359308719635,
0.05652978643774986,
-0.12203755974769592,
0.1039382740855217,
-0.02658943273127079,
0.09946075826883316,
-0.07054278254508972,
0.000789299956522882,
0.00494906771928072,
0.12713035941123962,
-0.023788869380950928,
0.09413742274045944,
-0.24859566986560822,
0.14139194786548615,
0.04770104959607124,
0.06752338260412216,
-0.05309014022350311,
0.028258029371500015,
0.0961327999830246,
0.12656870484352112,
0.10434279590845108,
0.020785793662071228,
0.06395822018384933,
-0.15350443124771118,
-0.11799371987581253,
0.006164612248539925,
0.02960512787103653,
-0.04779611900448799,
0.07287964969873428,
-0.0005067483871243894,
-0.06341438740491867,
-0.04712821915745735,
0.03289221227169037,
-0.19348879158496857,
-0.12983499467372894,
0.07045576721429825,
0.052490055561065674,
0.090853750705719,
-0.06709475815296173,
-0.03205195814371109,
-0.043046124279499054,
0.18290454149246216,
-0.03442198783159256,
-0.08606650680303574,
-0.1285882145166397,
-0.0006686998531222343,
0.09258218854665756,
-0.08165017515420914,
-0.005991893354803324,
-0.052048277109861374,
0.1894829422235489,
-0.035209737718105316,
-0.08786994218826294,
0.01570327952504158,
-0.15995244681835175,
-0.1281605362892151,
-0.0414857491850853,
0.12103712558746338,
-0.021659180521965027,
0.02213156595826149,
0.05526252090930939,
-0.020805859938263893,
0.008410685695707798,
-0.1123393177986145,
0.02350648306310177,
0.09350050985813141,
0.08948540687561035,
0.08400450646877289,
-0.11930029839277267,
-0.11843101680278778,
-0.10216961801052094,
-0.022528614848852158,
0.06181072071194649,
0.24282413721084595,
-0.02235415205359459,
0.037382837384939194,
0.13085247576236725,
-0.04928212612867355,
-0.19814851880073547,
-0.06996271014213562,
-0.00017375701281707734,
-0.037472743541002274,
0.02159503661096096,
-0.21408295631408691,
0.08694717288017273,
0.09358245879411697,
-0.030445247888565063,
0.09161640703678131,
-0.07194696366786957,
-0.06843597441911697,
0.04065357893705368,
0.07071772962808609,
0.0037067674566060305,
-0.1683196723461151,
-0.07113704830408096,
-0.06764888018369675,
-0.12663458287715912,
0.08166584372520447,
-0.1314810812473297,
0.08971400558948517,
-0.005421672947704792,
0.0671011433005333,
0.025563575327396393,
-0.06707208603620529,
0.11356908828020096,
-0.020757906138896942,
0.009567689150571823,
-0.07924797385931015,
0.012899143621325493,
0.022010432556271553,
-0.050428662449121475,
0.09034649282693863,
-0.02925287000834942,
0.01692429557442665,
-0.091850645840168,
-0.0007856881711632013,
-0.10224597156047821,
0.0437864288687706,
-0.038862090557813644,
-0.017533548176288605,
-0.008498632349073887,
0.07837546616792679,
0.03536466881632805,
0.010669435374438763,
-0.009266866371035576,
-0.04946504905819893,
0.10181041061878204,
0.17810481786727905,
0.10491631180047989,
0.0006870499346405268,
-0.07857012748718262,
-0.036821771413087845,
-0.053213875740766525,
0.050082918256521225,
-0.08183137327432632,
0.06681650131940842,
0.029605142772197723,
0.010572184808552265,
0.12429390102624893,
-0.0033586653880774975,
-0.12030913680791855,
-0.003338087350130081,
0.10895328968763351,
-0.12868796288967133,
-0.07275929301977158,
-0.020934229716658592,
0.05516009032726288,
-0.10196569561958313,
0.0011667415965348482,
0.1428048461675644,
-0.028892088681459427,
-0.028331711888313293,
0.014776935800909996,
0.07020314782857895,
-0.012796786613762379,
0.10238455981016159,
0.07413777709007263,
0.049551427364349365,
-0.12031137198209763,
0.05704139545559883,
0.03181569650769234,
-0.03592713922262192,
-0.0024339298252016306,
0.05667674541473389,
-0.10612429678440094,
-0.1119871735572815,
0.03397342190146446,
0.06045559421181679,
-0.015471268445253372,
-0.06184658035635948,
-0.020792635157704353,
-0.04714902117848396,
0.02126099169254303,
0.07590576261281967,
0.00995138380676508,
-0.008162305690348148,
0.08148860931396484,
-0.017391547560691833,
-0.08959554880857468,
0.06402577459812164,
0.010443227365612984,
0.03571965917944908,
-0.13038720190525055,
0.07408680766820908,
-0.015041174367070198,
0.006071531679481268,
-0.022530831396579742,
0.003641687100753188,
-0.10074226558208466,
-0.04254826903343201,
-0.07885435223579407,
0.06230726093053818,
-0.1484614759683609,
-0.020241795107722282,
-0.026183132082223892,
-0.022612975910305977,
0.015071062371134758,
0.019551774486899376,
-0.07782812416553497,
-0.04559153690934181,
-0.010346274822950363,
0.08449862152338028,
-0.16007104516029358,
-0.008523115888237953,
0.03327300027012825,
-0.06084582209587097,
0.0670776516199112,
0.08543620258569717,
-0.010745981708168983,
-0.011400423012673855,
-0.24030931293964386,
-0.05429427698254585,
0.060920946300029755,
0.04178236424922943,
0.015297153033316135,
-0.10723429918289185,
0.0352109931409359,
-0.01898287609219551,
-0.023456763476133347,
0.005050045438110828,
0.031953055411577225,
-0.08434974402189255,
0.024241402745246887,
-0.019039491191506386,
-0.04014326632022858,
-0.051917847245931625,
0.04262912645936012,
0.17145587503910065,
-0.014532416127622128,
0.1174297034740448,
-0.080752432346344,
0.054420918226242065,
-0.13401885330677032,
0.029829595237970352,
-0.001078542205505073,
-0.039962440729141235,
-0.02863360196352005,
-0.010570892132818699,
0.06349045038223267,
-0.010899520479142666,
0.09258676320314407,
-0.0552545003592968,
0.06722300499677658,
0.0190583486109972,
-0.09725376963615417,
0.007986992597579956,
-0.026470135897397995,
0.03294571489095688,
0.0396236926317215,
-0.006473933346569538,
0.009316735900938511,
0.00238132756203413,
0.02042953483760357,
-0.0582701601088047,
0.07976511865854263,
0.16147081553936005,
0.02053176984190941,
0.022807525470852852,
0.054943084716796875,
-0.07234697043895721,
-0.036924149841070175,
-0.04578930139541626,
-0.077462337911129,
0.06634023785591125,
-0.021255100145936012,
0.07374273985624313,
0.15307408571243286,
-0.12218204140663147,
0.038187239319086075,
-0.005237263161689043,
-0.03132057934999466,
-0.08196348696947098,
-0.1581864356994629,
-0.06715912371873856,
-0.08088500797748566,
0.011959434486925602,
-0.11438815295696259,
0.06888450682163239,
0.04325690120458603,
0.019395047798752785,
-0.017880942672491074,
0.13543029129505157,
0.03472369909286499,
-0.07543140649795532,
0.060917001217603683,
-0.02095349319279194,
-0.031358812004327774,
0.04272241145372391,
0.0006400952115654945,
0.06196298450231552,
-0.010582057759165764,
0.044258568435907364,
0.0559408999979496,
0.02938593178987503,
0.05811672285199165,
-0.06726688146591187,
-0.12517108023166656,
0.006359596271067858,
0.005888449959456921,
0.04039566218852997,
0.15003027021884918,
0.05136363208293915,
0.007397872861474752,
0.014586303383111954,
0.16361239552497864,
-0.038274187594652176,
-0.0431714691221714,
-0.15419889986515045,
0.011273895390331745,
-0.02001452073454857,
-0.009176031686365604,
-0.03663250058889389,
-0.10866829752922058,
-0.028140606358647346,
0.20135445892810822,
0.08363344520330429,
-0.049736183136701584,
0.026926010847091675,
-0.006478144787251949,
0.0070541067980229855,
0.006099193822592497,
0.08733457326889038,
0.05982113629579544,
0.11233042925596237,
-0.03476639464497566,
0.04225286468863487,
0.008952682837843895,
-0.042931120842695236,
-0.100910983979702,
0.05160531401634216,
-0.04183126986026764,
-0.029043002054095268,
-0.0207699965685606,
0.12725666165351868,
-0.06002918258309364,
-0.12053494155406952,
-0.05984590947628021,
-0.05843505263328552,
-0.09186802059412003,
-0.04533113166689873,
-0.021347900852560997,
0.08330697566270828,
0.03736959397792816,
-0.008225626312196255,
-0.006564581301063299,
0.18599693477153778,
-0.004363450221717358,
-0.06833065301179886,
-0.047022756189107895,
0.03228268772363663,
-0.009685746394097805,
0.13331912457942963,
0.02237250655889511,
0.06835850328207016,
0.08902639895677567,
-0.04617135971784592,
-0.13351397216320038,
0.05768809840083122,
0.01893182285130024,
-0.16012974083423615,
0.03900958225131035,
0.1735668033361435,
-0.019399257376790047,
0.004258662927895784,
0.07070906460285187,
-0.07974739372730255,
0.021498262882232666,
0.05192280188202858,
-0.017278648912906647,
-0.07030515372753143,
0.08999960869550705,
-0.09391003847122192,
0.11678098142147064,
0.17506007850170135,
-0.024389326572418213,
-0.013276796787977219,
-0.03903545066714287,
0.05904215946793556,
0.06406354159116745,
-0.016790268942713737,
-0.07218509912490845,
-0.10399819910526276,
0.01415897998958826,
-0.01502299215644598,
0.07969480007886887,
-0.13121938705444336,
-0.019862104207277298,
-0.05875250697135925,
-0.03522523120045662,
-0.09029058367013931,
0.07942423224449158,
0.06178797036409378,
0.053517896682024,
-0.021183528006076813,
-0.09516715258359909,
0.007413235958665609,
0.11255256831645966,
-0.14081521332263947,
-0.0646120086312294
] |
null | null | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "cartpole-reinforce", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{"type": "mean_reward", "value": "500.00 +/- 0.00", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | vadhri/cartpole-reinforce | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | 2024-02-09T01:36:51+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
39,
54
] | [
"passage: TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
0.007526164408773184,
-0.12498430907726288,
-0.0013541718944907188,
0.09601131081581116,
0.11848696321249008,
-0.04186001420021057,
0.11405468732118607,
0.05624859035015106,
0.09539441019296646,
0.04239490255713463,
0.13636724650859833,
0.06906966865062714,
-0.004102868959307671,
0.12412862479686737,
0.09840741008520126,
-0.26058563590049744,
0.07420794665813446,
-0.04403980076313019,
-0.009944677352905273,
0.10139261186122894,
0.07836852967739105,
-0.08325441926717758,
0.051592715084552765,
0.00009572553972247988,
-0.044259943068027496,
0.0321260429918766,
0.013628939166665077,
-0.053157225251197815,
0.1606452465057373,
-0.07313758134841919,
0.10494591295719147,
-0.03843724727630615,
0.14574295282363892,
-0.1126825287938118,
0.04758213832974434,
0.05111503228545189,
-0.04548581689596176,
0.03848232328891754,
-0.12538743019104004,
-0.06033875793218613,
0.026815801858901978,
-0.015865681692957878,
0.12249194830656052,
0.03647647053003311,
-0.1777559220790863,
-0.13461355865001678,
-0.0165896974503994,
0.12325166910886765,
0.1627800315618515,
0.00512364786118269,
0.014270431362092495,
0.16791965067386627,
-0.1761058121919632,
0.025937072932720184,
0.11400806158781052,
-0.37275227904319763,
-0.00034436015994288027,
0.2240462601184845,
0.06164427846670151,
0.1252165287733078,
-0.12646614015102386,
0.010440526530146599,
0.07403992861509323,
0.04368630796670914,
0.049784936010837555,
-0.015430688858032227,
-0.12260042130947113,
0.08455035835504532,
-0.1383819431066513,
-0.058066487312316895,
0.1495426446199417,
-0.019741326570510864,
-0.009476418606936932,
-0.016515808179974556,
-0.009238536469638348,
-0.050979889929294586,
-0.03430935740470886,
-0.11778499186038971,
0.10755524039268494,
0.04975730925798416,
0.0038771627005189657,
-0.04602450504899025,
-0.05612579360604286,
-0.09815777093172073,
-0.03123871050775051,
0.0372777059674263,
-0.013706400990486145,
0.01091629359871149,
0.027692900970578194,
0.09935613721609116,
-0.13446329534053802,
0.01825822703540325,
-0.028096558526158333,
-0.028040969744324684,
-0.1316804438829422,
-0.11984307318925858,
-0.026084421202540398,
0.004223645199090242,
0.03029833547770977,
0.20433813333511353,
0.020139509811997414,
0.059011414647102356,
-0.0022708347532898188,
0.09776382148265839,
0.029780851677060127,
0.13517548143863678,
-0.04466623440384865,
0.19488364458084106,
0.07711011171340942,
0.05364556983113289,
0.03204274922609329,
-0.05344729498028755,
-0.19369827210903168,
0.04861246794462204,
0.06659778952598572,
0.08274952322244644,
-0.1178959533572197,
0.0059632807970047,
-0.10316018015146255,
0.0028950648847967386,
-0.10474003106355667,
-0.0642905905842781,
-0.02892979420721531,
0.031841445714235306,
-0.10535725951194763,
0.028785312548279762,
0.025052599608898163,
0.04140377417206764,
0.0676041767001152,
-0.12253966927528381,
-0.07404746115207672,
-0.021733485162258148,
-0.12817098200321198,
-0.09923440217971802,
0.08802318572998047,
-0.026199497282505035,
-0.005110981408506632,
-0.1253623217344284,
-0.2661486268043518,
-0.05670225992798805,
0.06396034359931946,
-0.03231031447649002,
-0.08589376509189606,
-0.1633463054895401,
0.026403428986668587,
-0.07700273394584656,
0.05221332609653473,
0.04776721075177193,
-0.03665859252214432,
0.02023705095052719,
-0.07958202809095383,
0.12739010155200958,
0.049698662012815475,
0.00541001046076417,
-0.09916839748620987,
0.07882837951183319,
-0.3034103214740753,
-0.02581131085753441,
-0.15228183567523956,
0.0772043839097023,
-0.07893010973930359,
0.01308529730886221,
0.05044940114021301,
0.043790437281131744,
-0.016942394897341728,
0.16269747912883759,
-0.17043575644493103,
-0.05301272124052048,
0.026445282623171806,
-0.09261117875576019,
-0.09916394203901291,
0.07275339215993881,
-0.06339669227600098,
0.21263530850410461,
0.08751397579908371,
0.17006252706050873,
-0.011036526411771774,
-0.16256992518901825,
0.1207515075802803,
0.07522942125797272,
-0.1639646589756012,
0.004287737421691418,
0.061784300953149796,
-0.0016935690073296428,
0.02746843732893467,
-0.01872866041958332,
-0.07289361208677292,
0.06302516162395477,
-0.07825060933828354,
0.022581040859222412,
0.06258945167064667,
-0.09531243145465851,
0.23986859619617462,
-0.005434412509202957,
0.0862451046705246,
-0.025957979261875153,
-0.09802921861410141,
0.00908072479069233,
0.07164718210697174,
-0.0014321404742076993,
0.01703714393079281,
-0.14553219079971313,
0.23044352233409882,
-0.07965081930160522,
0.011176814325153828,
-0.11607582122087479,
-0.1256982982158661,
0.011873425915837288,
0.13336114585399628,
0.059921663254499435,
0.16569606959819794,
0.09518871456384659,
-0.032197169959545135,
0.017584815621376038,
-0.0023385772947221994,
-0.09040450304746628,
0.01580043137073517,
-0.0021571461111307144,
-0.12167251110076904,
-0.07353103160858154,
-0.08134473115205765,
0.12585052847862244,
-0.20988115668296814,
0.015492538921535015,
0.04099845886230469,
0.008103687316179276,
0.04467369243502617,
0.023746047168970108,
-0.013269703835248947,
-0.00007021807687124237,
0.03244573250412941,
-0.10098352283239365,
0.12937165796756744,
0.013381263241171837,
0.014676140621304512,
-0.006365173030644655,
-0.05572463944554329,
0.03720450773835182,
0.040439579635858536,
-0.11237845569849014,
-0.11330515146255493,
-0.009658765979111195,
-0.0015364213613793254,
0.02637762948870659,
-0.022321155294775963,
0.052120618522167206,
0.27587956190109253,
0.05387469753623009,
0.10401033610105515,
-0.05769326910376549,
0.015315087512135506,
-0.015322818420827389,
-0.07135670632123947,
0.06358719617128372,
0.025013601407408714,
0.08050397783517838,
-0.03531401976943016,
0.03759452700614929,
0.1675453782081604,
-0.015888912603259087,
0.11127935349941254,
-0.06545067578554153,
-0.03844274953007698,
-0.043109722435474396,
0.05627678707242012,
0.015021559782326221,
0.04564907029271126,
0.0000015355876712419558,
-0.08444724231958389,
-0.03503387048840523,
-0.03988509997725487,
-0.010637006722390652,
-0.12273643165826797,
-0.00499896751716733,
0.01265440508723259,
-0.021940499544143677,
0.04488934203982353,
0.07375624030828476,
-0.04849626496434212,
0.025821007788181305,
0.06070821359753609,
-0.10193055868148804,
0.08957115560770035,
0.015067169442772865,
-0.06946801394224167,
0.13769419491291046,
-0.07484805583953857,
-0.045293889939785004,
-0.1025395318865776,
-0.1568877100944519,
0.09384927153587341,
0.06704871356487274,
-0.05427970737218857,
-0.1503879576921463,
-0.0016851738328114152,
-0.008973666466772556,
0.09206123650074005,
-0.006399387493729591,
-0.12621140480041504,
0.01989075168967247,
0.08295059949159622,
-0.05633419007062912,
-0.09804849326610565,
-0.0075809285044670105,
-0.05280788615345955,
-0.17707788944244385,
-0.03888550028204918,
-0.06398582458496094,
-0.06734282523393631,
0.23586803674697876,
0.02017230913043022,
0.08274748176336288,
-0.044721852988004684,
0.04250151664018631,
-0.012231717817485332,
0.0006326579605229199,
0.10689259320497513,
-0.09043551236391068,
-0.017900818958878517,
-0.001320177922025323,
-0.024820495396852493,
-0.07327181100845337,
0.029733488336205482,
-0.04272191599011421,
-0.08249637484550476,
-0.1415451467037201,
-0.04993678629398346,
-0.011005163192749023,
0.10754310339689255,
0.07337497919797897,
0.0048001972027122974,
-0.11733713001012802,
0.062058478593826294,
0.13692134618759155,
0.031207585707306862,
0.004062763415277004,
0.028157465159893036,
0.14977529644966125,
-0.10706274956464767,
-0.022463621571660042,
-0.038119975477457047,
-0.054863203316926956,
0.004114252515137196,
0.016883620992302895,
0.08840765058994293,
0.1410384476184845,
0.11468084901571274,
0.047563645988702774,
0.0464191697537899,
0.06561273336410522,
0.1694946140050888,
0.059157438576221466,
-0.10448314249515533,
-0.044678982347249985,
-0.0040070898830890656,
-0.10903503000736237,
0.057307638227939606,
0.16030821204185486,
0.06326017528772354,
-0.14463356137275696,
0.021787412464618683,
-0.038982175290584564,
0.13649246096611023,
0.020638149231672287,
-0.2677258849143982,
-0.008139112964272499,
0.023630544543266296,
-0.0010347915813326836,
-0.012379839085042477,
0.10821118950843811,
-0.040134772658348083,
-0.233198344707489,
-0.12299054861068726,
0.010077533312141895,
0.031144635751843452,
-0.1509784311056137,
0.015542911365628242,
-0.14036494493484497,
0.08027976751327515,
-0.007007129956036806,
0.07418135553598404,
-0.025149788707494736,
0.15060245990753174,
-0.028731435537338257,
0.01628703810274601,
-0.07902143895626068,
-0.047717493027448654,
0.09898673743009567,
-0.0046631391160190105,
0.1931537538766861,
0.005480166990309954,
-0.023713182657957077,
-0.12098433077335358,
-0.05229806900024414,
-0.04967813938856125,
0.010598190128803253,
-0.05373382940888405,
0.0765683576464653,
-0.02441473677754402,
-0.0039579677395522594,
-0.010900177992880344,
0.08942947536706924,
-0.05291692912578583,
0.03636563941836357,
-0.11246588081121445,
-0.05034820735454559,
0.14550213515758514,
-0.09163831174373627,
-0.10174685716629028,
-0.16205860674381256,
0.14137998223304749,
0.15070600807666779,
0.058216437697410583,
-0.04001476243138313,
0.03867831453680992,
-0.019183965399861336,
-0.024241572245955467,
0.07880574464797974,
0.009653856977820396,
0.1324782371520996,
-0.08983246237039566,
0.014327390119433403,
0.14589735865592957,
-0.05275948345661163,
0.016191845759749413,
-0.02304735779762268,
0.12202176451683044,
0.04650457948446274,
0.06189403310418129,
0.018547222018241882,
0.06655703485012054,
0.06466961652040482,
-0.02262885868549347,
0.08456692099571228,
0.030712679028511047,
-0.18644161522388458,
0.058530256152153015,
-0.09805119782686234,
0.22581584751605988,
0.05066308751702309,
0.06047345697879791,
0.2993181645870209,
0.21986234188079834,
-0.05372472479939461,
0.1669820249080658,
0.044286344200372696,
-0.05891284719109535,
-0.21245966851711273,
-0.03684934973716736,
-0.030655447393655777,
0.09436552971601486,
0.15607263147830963,
-0.0981721356511116,
-0.04201313853263855,
-0.00972361396998167,
-0.032264553010463715,
0.020120708271861076,
-0.24663487076759338,
-0.01734781451523304,
0.14379777014255524,
0.10629188269376755,
0.2451348900794983,
-0.006132842972874641,
0.023609744384884834,
0.049030207097530365,
0.018605992197990417,
-0.02483358606696129,
-0.21013511717319489,
0.09079083055257797,
0.006071676965802908,
0.04935038834810257,
0.022885039448738098,
-0.006052911281585693,
0.04500092566013336,
-0.073696069419384,
0.08904470503330231,
-0.08561883866786957,
-0.08341272175312042,
0.2185351401567459,
-0.03945168852806091,
-0.00661163916811347,
0.12917985022068024,
-0.011526807211339474,
-0.1097102016210556,
-0.015364703722298145,
0.027403371408581734,
0.030678823590278625,
-0.030246863141655922,
-0.03609466925263405,
0.024012766778469086,
0.10202405601739883,
-0.04282205551862717,
0.04565315693616867,
0.10240072011947632,
-0.020902957767248154,
0.15945613384246826,
0.13205459713935852,
0.10420060157775879,
0.002927543595433235,
-0.06464727967977524,
0.014349685050547123,
-0.055471502244472504,
0.02962767891585827,
-0.17038846015930176,
-0.0070191239938139915,
0.055695805698633194,
0.04772466421127319,
0.0945243164896965,
0.11333164572715759,
-0.127106174826622,
0.0300484336912632,
0.028996523469686508,
-0.06286120414733887,
-0.06029998138546944,
-0.002275418024510145,
-0.016458535566926003,
-0.008173024281859398,
-0.09947093576192856,
0.07884971052408218,
-0.10555081814527512,
-0.03306307643651962,
0.05025126785039902,
-0.0607193186879158,
-0.12852220237255096,
-0.010904680006206036,
0.1252979338169098,
0.061709314584732056,
-0.05078592896461487,
0.14939077198505402,
0.06109785661101341,
-0.08055379986763,
0.037185851484537125,
0.027442200109362602,
-0.08008874952793121,
-0.10198270529508591,
-0.0004569833690766245,
0.31761088967323303,
0.06076094135642052,
-0.0329466350376606,
-0.11946453154087067,
-0.15002015233039856,
0.04840146750211716,
0.1035679280757904,
0.12359631806612015,
0.011757869273424149,
-0.05322748050093651,
0.02236519381403923,
-0.05275069922208786,
0.03814244270324707,
0.06910209357738495,
-0.03928454965353012,
-0.13761694729328156,
0.0077122850343585014,
0.026647454127669334,
0.10174071043729782,
-0.06771174818277359,
-0.09184598177671432,
-0.18085066974163055,
0.09208621084690094,
-0.03432070091366768,
-0.10890032351016998,
0.027215104550123215,
-0.017406610772013664,
0.014248576015233994,
0.07639352232217789,
-0.047281619161367416,
0.01244808267802,
-0.1517520695924759,
0.07082249224185944,
0.05706808716058731,
0.08926787972450256,
0.000014311663107946515,
-0.054843269288539886,
0.07618319988250732,
-0.05763502046465874,
0.06680037826299667,
-0.053477559238672256,
0.005539732985198498,
0.10781200975179672,
-0.23264040052890778,
-0.021164139732718468,
0.009476077742874622,
-0.04681631922721863,
0.08765807747840881,
-0.19047698378562927,
0.024190550670027733,
-0.08897756040096283,
-0.024605726823210716,
0.01802127994596958,
-0.1086471825838089,
-0.04306677728891373,
0.08475461602210999,
0.037119291722774506,
-0.031288959085941315,
-0.04612116143107414,
-0.019314980134367943,
-0.0914498046040535,
0.053634315729141235,
0.07442525774240494,
-0.0687926784157753,
0.08314394950866699,
-0.05507456883788109,
0.00841207429766655,
-0.052043743431568146,
0.06760627031326294,
-0.012366239912807941,
-0.12672528624534607,
-0.02123171091079712,
-0.044928714632987976,
0.11662110686302185,
-0.023402327671647072,
0.022080281749367714,
0.014599837362766266,
0.0323631577193737,
-0.012065601535141468,
0.05028461292386055,
0.1019197478890419,
0.05136820673942566,
0.014879679307341576,
0.02292765863239765,
0.055746350437402725,
0.0757644772529602,
-0.1134679913520813,
0.06457309424877167,
-0.02098844014108181,
-0.08620109409093857,
0.1013324111700058,
0.06909440457820892,
0.037490107119083405,
0.15593400597572327,
0.22674402594566345,
0.10539932548999786,
-0.03564648702740669,
-0.03126971051096916,
0.12967991828918457,
0.17799612879753113,
-0.07682197540998459,
0.015780627727508545,
-0.0020607721526175737,
-0.017265556380152702,
-0.09849067777395248,
-0.13722245395183563,
-0.060460351407527924,
-0.2453264594078064,
0.1078341007232666,
-0.03288164362311363,
-0.04169659689068794,
0.128489688038826,
0.027952738106250763,
0.03724630922079086,
0.08183616399765015,
-0.12909026443958282,
-0.013460557907819748,
0.07749562710523605,
-0.08914026618003845,
-0.033571500331163406,
-0.17521262168884277,
-0.06771576404571533,
-0.08741120994091034,
-0.15989220142364502,
-0.06844990700483322,
0.029948782175779343,
0.035394806414842606,
0.010386589914560318,
-0.039711855351924896,
-0.01962728053331375,
0.011063394136726856,
-0.0025537724141031504,
-0.04985455423593521,
-0.01753084547817707,
0.021317757666110992,
-0.11333847790956497,
-0.024336790665984154,
0.16320326924324036,
-0.03297848999500275,
-0.18396754562854767,
-0.0405106395483017,
0.2157316505908966,
0.025046708062291145,
0.0590171180665493,
-0.073721744120121,
-0.016323629766702652,
0.021523483097553253,
0.20813441276550293,
0.10171995311975479,
-0.10821312665939331,
0.015457749366760254,
-0.03655189648270607,
0.0013793212128803134,
-0.061893612146377563,
0.10775819420814514,
0.06519263982772827,
-0.07549984753131866,
-0.17567221820354462,
-0.04389495030045509,
-0.08628730475902557,
0.03370477631688118,
-0.14383791387081146,
-0.03786516562104225,
0.1168690100312233,
0.004516853019595146,
-0.053927481174468994,
0.07883694022893906,
-0.17713546752929688,
0.03441957011818886,
-0.04880853369832039,
-0.13215437531471252,
-0.09491758048534393,
-0.10123858600854874,
0.0027463934384286404,
0.08913854509592056,
0.15567956864833832,
-0.06151591241359711,
-0.07471925020217896,
-0.009579092264175415,
-0.028091613203287125,
-0.052700337022542953,
-0.07900123298168182,
0.059512585401535034,
0.0007560851518064737,
0.16147300601005554,
-0.07439453154802322,
0.09558981657028198,
0.09099138528108597,
-0.021246420219540596,
-0.00915549136698246,
0.032866667956113815,
-0.003863809397444129,
-0.07436864078044891,
-0.04970616102218628,
0.02312966249883175,
0.027639856562018394,
0.10846075415611267,
-0.030836544930934906,
-0.1934703141450882,
0.11230092495679855,
0.09140218049287796,
-0.04296138137578964,
-0.046487610787153244,
0.05351927503943443,
-0.07097935676574707,
0.1252279132604599,
0.03444884717464447,
-0.02163051813840866,
0.013762647286057472,
-0.06370721012353897,
0.08370721340179443,
0.11594565212726593,
-0.048265840858221054,
-0.08278503268957138,
-0.06164652109146118,
0.012770666740834713,
0.02961382456123829,
-0.13650155067443848,
-0.21160630881786346,
-0.10802312940359116,
-0.1383298933506012,
0.004740108735859394,
-0.04703504592180252,
0.08498300611972809,
0.12991970777511597,
0.09780163317918777,
-0.011416295543313026,
-0.004867587238550186,
0.018085451796650887,
0.13192623853683472,
-0.11232008039951324,
-0.08192373812198639
] |
null | null | null |
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
```python
from kornia.contrib import VisionTransformer
vit_model = VisionTransformer.from_config('vit_b/32', pretrained=True)
...
```
Original weights from [AugReg](https://arxiv.org/abs/2106.10270) as recommended by [google research vision transformer repo](https://github.com/google-research/vision_transformer): This weight is based on the
[AugReg ViT_B/32 pretrained on imagenet21k](https://storage.googleapis.com/vit_models/augreg/B_32-i21k-300ep-lr_0.001-aug_light1-wd_0.1-do_0.0-sd_0.0.npz)
Weights converted to PyTorch for Kornia ViT implementation (by [@gau-nernst](https://github.com/gau-nernst) in [kornia/kornia#2786](https://github.com/kornia/kornia/pull/2786#discussion_r1482339811))
<details>
<summary>Convert jax checkpoint function</summary>
```
def convert_jax_checkpoint(np_state_dict: dict[str, np.ndarray]):
def get_weight(key: str) -> torch.Tensor:
return torch.from_numpy(np_state_dict[key])
state_dict = dict()
state_dict["patch_embedding.cls_token"] = get_weight("cls")
state_dict["patch_embedding.backbone.weight"] = get_weight("embedding/kernel").permute(3, 2, 0, 1) # conv »
state_dict["patch_embedding.backbone.bias"] = get_weight("embedding/bias")
state_dict["patch_embedding.positions"] = get_weight("Transformer/posembed_input/pos_embedding").squeeze(0)
# for i, block in enumerate(self.encoder.blocks):
for i in range(100):
prefix1 = f"encoder.blocks.{i}"
prefix2 = f"Transformer/encoderblock_{i}"
if f"{prefix2}/LayerNorm_0/scale" not in np_state_dict:
break
state_dict[f"{prefix1}.0.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_0/scale")
state_dict[f"{prefix1}.0.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_0/bias")
mha_prefix = f"{prefix2}/MultiHeadDotProductAttention_1"
qkv_weight = [get_weight(f"{mha_prefix}/{x}/kernel") for x in ["query", "key", "value"]]
qkv_bias = [get_weight(f"{mha_prefix}/{x}/bias") for x in ["query", "key", "value"]]
state_dict[f"{prefix1}.0.fn.1.qkv.weight"] = torch.cat(qkv_weight, 1).flatten(1).T
state_dict[f"{prefix1}.0.fn.1.qkv.bias"] = torch.cat(qkv_bias, 0).flatten()
state_dict[f"{prefix1}.0.fn.1.projection.weight"] = get_weight(f"{mha_prefix}/out/kernel").flatten(0, 1»
state_dict[f"{prefix1}.0.fn.1.projection.bias"] = get_weight(f"{mha_prefix}/out/bias")
state_dict[f"{prefix1}.1.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_2/scale")
state_dict[f"{prefix1}.1.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_2/bias")
state_dict[f"{prefix1}.1.fn.1.0.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/kernel").T
state_dict[f"{prefix1}.1.fn.1.0.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/bias")
state_dict[f"{prefix1}.1.fn.1.3.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/kernel").T
state_dict[f"{prefix1}.1.fn.1.3.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/bias")
state_dict["norm.weight"] = get_weight("Transformer/encoder_norm/scale")
state_dict["norm.bias"] = get_weight("Transformer/encoder_norm/bias")
return state_dict
```
</details> | {"license": "apache-2.0", "pipeline_tag": "image-classification"} | image-classification | kornia/vit_b32_augreg_i21k_r224 | [
"image-classification",
"arxiv:2106.10270",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:38:27+00:00 | [
"2106.10270"
] | [] | TAGS
#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us
|
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Original weights from AugReg as recommended by google research vision transformer repo: This weight is based on the
AugReg ViT_B/32 pretrained on imagenet21k
Weights converted to PyTorch for Kornia ViT implementation (by @gau-nernst in kornia/kornia#2786)
<details>
<summary>Convert jax checkpoint function</summary>
</details> | [] | [
"TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
27
] | [
"passage: TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
-0.06109374389052391,
0.20674705505371094,
-0.006548014469444752,
0.049976740032434464,
0.02543392963707447,
0.06775278598070145,
0.1434560865163803,
0.10054779052734375,
0.0873129591345787,
-0.0696193128824234,
0.16259659826755524,
0.07446799427270889,
0.027905816212296486,
-0.020278295502066612,
0.0003193104930687696,
-0.19860264658927917,
0.07249123603105545,
-0.01418757252395153,
-0.03743588179349899,
0.016364481300115585,
0.031079968437552452,
-0.03377098590135574,
0.06803242117166519,
-0.013396034017205238,
-0.12081167846918106,
-0.004631385672837496,
0.05561913177371025,
-0.04842509329319,
0.07639530301094055,
-0.0024446528404951096,
0.03034677915275097,
0.033661652356386185,
0.0436035580933094,
-0.18721453845500946,
-0.0013201063266023993,
-0.011022438295185566,
-0.13286513090133667,
0.06692822277545929,
0.12416379153728485,
0.0049120765179395676,
0.03520214185118675,
0.04749228432774544,
-0.1190459355711937,
0.007217442616820335,
-0.09456748515367508,
-0.2383200079202652,
-0.10159328579902649,
0.11124194413423538,
0.12468010187149048,
0.01974388025701046,
0.10125472396612167,
0.03719622269272804,
-0.12143778800964355,
0.007481607608497143,
0.07237470895051956,
-0.24169990420341492,
-0.010691691190004349,
0.1201784610748291,
-0.1079055592417717,
0.04524125158786774,
-0.03944199159741402,
0.09898041188716888,
0.0823771059513092,
-0.045112185180187225,
-0.11518827825784683,
-0.045906227082014084,
-0.11930672824382782,
0.05414021015167236,
0.02489721029996872,
-0.08919412642717361,
0.3176185190677643,
0.1532946676015854,
0.002456814516335726,
0.11417848616838455,
-0.034857455641031265,
0.03917086496949196,
-0.020580649375915527,
0.14350418746471405,
0.11800917983055115,
0.1277526319026947,
0.11405012756586075,
-0.018727514892816544,
-0.18136470019817352,
-0.06914898008108139,
-0.16194461286067963,
-0.04335305839776993,
-0.03692782297730446,
0.17465905845165253,
-0.1323341280221939,
-0.02526034042239189,
-0.1357729136943817,
-0.08216837048530579,
0.02422415465116501,
-0.0783277153968811,
0.17794139683246613,
0.12570883333683014,
-0.025183117017149925,
0.05908667668700218,
0.14745140075683594,
0.12899348139762878,
0.02096019685268402,
0.03532757610082626,
-0.10447050631046295,
0.19674737751483917,
-0.02905309945344925,
0.03755328059196472,
0.03452769294381142,
0.11503022909164429,
0.06668683886528015,
-0.08765921741724014,
0.09905751049518585,
-0.034111931920051575,
-0.1760949343442917,
-0.02817642129957676,
-0.0438312403857708,
0.051844481378793716,
-0.0005061799311079085,
-0.04923499748110771,
-0.07902505248785019,
0.02592616155743599,
0.20208676159381866,
0.005098436959087849,
0.00970771349966526,
-0.009410499595105648,
-0.01887846365571022,
-0.03703097999095917,
0.06327838450670242,
0.020843954756855965,
0.06386575847864151,
-0.00038021898944862187,
-0.07227174192667007,
0.04220779612660408,
0.0033467260655015707,
0.07464555650949478,
0.11725340783596039,
-0.033287424594163895,
0.031015444546937943,
-0.1253310889005661,
-0.06270439177751541,
0.03723682835698128,
0.086534284055233,
0.0028114039450883865,
0.01238210964947939,
0.11720160394906998,
0.014849238097667694,
0.03825271129608154,
-0.03593437746167183,
-0.060856327414512634,
-0.099258191883564,
0.055119361728429794,
-0.13103467226028442,
0.08423157781362534,
-0.2563755214214325,
0.011386703699827194,
-0.10534657537937164,
0.053238339722156525,
-0.09686396270990372,
-0.07819923013448715,
-0.13250695168972015,
0.2009194940328598,
-0.05468209087848663,
0.0034654189366847277,
-0.054602500051259995,
-0.00633781123906374,
-0.05506056174635887,
0.07645745575428009,
-0.15609174966812134,
0.02364489808678627,
0.08345842361450195,
-0.15114741027355194,
-0.13571877777576447,
-0.002641590777784586,
0.043754223734140396,
-0.07488250732421875,
-0.010925939306616783,
0.3182951807975769,
-0.03542245179414749,
-0.01839727908372879,
0.036988433450460434,
0.15065109729766846,
-0.08740837126970291,
-0.20893323421478271,
0.10468775033950806,
-0.09690731018781662,
-0.14157627522945404,
0.0215351153165102,
-0.13635723292827606,
0.10152363032102585,
0.040783826261758804,
-0.08645343035459518,
-0.02261362224817276,
-0.04002821445465088,
-0.04111453890800476,
0.012164331041276455,
0.05289793014526367,
-0.046031367033720016,
0.036598462611436844,
-0.10292722284793854,
0.05292672663927078,
0.08823665231466293,
0.03464950621128082,
-0.019848383963108063,
0.05194208770990372,
-0.0322202704846859,
-0.008407019078731537,
-0.06743084639310837,
0.03886767849326134,
0.009944709949195385,
-0.047629464417696,
0.08154439926147461,
-0.05256316438317299,
0.028394905850291252,
-0.08248095214366913,
-0.0052256197668612,
-0.03148965165019035,
-0.021348997950553894,
0.016548115760087967,
0.04151642695069313,
-0.15185265243053436,
0.05146369710564613,
0.027628103271126747,
0.06300205737352371,
-0.07534655928611755,
-0.06911735236644745,
0.13192912936210632,
-0.02104104869067669,
-0.006522714160382748,
0.09356412291526794,
0.007906613871455193,
-0.09177529066801071,
-0.01047999132424593,
-0.02048683352768421,
0.1222124695777893,
0.01773674599826336,
-0.03080260008573532,
0.15719905495643616,
0.004599755629897118,
0.1652202308177948,
0.19648905098438263,
-0.1871400624513626,
0.05895731970667839,
-0.04543163627386093,
0.03526407852768898,
-0.00021277944324538112,
0.058195192366838455,
0.030574873089790344,
-0.11539100110530853,
-0.0529194250702858,
0.04648087918758392,
-0.0637110099196434,
0.08189071714878082,
-0.016040494665503502,
-0.07081851363182068,
-0.09113258868455887,
-0.004617263562977314,
0.22731298208236694,
-0.22143718600273132,
0.13705743849277496,
0.44992348551750183,
-0.00563804479315877,
0.04384651407599449,
-0.07071708142757416,
-0.02926171012222767,
0.011590258218348026,
-0.016685742884874344,
-0.027885599061846733,
0.20283104479312897,
-0.037577949464321136,
-0.006611361168324947,
0.07687141746282578,
0.021334122866392136,
0.02833111397922039,
-0.2102135717868805,
-0.08647490292787552,
-0.01990378089249134,
-0.032265402376651764,
-0.106113001704216,
-0.03494508937001228,
-0.07398673892021179,
0.09487839788198471,
-0.00005973442966933362,
-0.13227896392345428,
0.12197559326887131,
-0.04474426805973053,
-0.053833432495594025,
0.1027798280119896,
-0.1763962209224701,
-0.23515380918979645,
-0.14439262449741364,
0.03435428440570831,
-0.07389409840106964,
0.033989984542131424,
0.05001555383205414,
-0.12449482828378677,
-0.042997002601623535,
0.009898168034851551,
-0.17011038959026337,
-0.0666801705956459,
-0.009744573384523392,
0.04772152379155159,
0.06096755340695381,
0.05611218884587288,
-0.07783979177474976,
-0.04949898272752762,
-0.03132689744234085,
0.022898364812135696,
0.13073059916496277,
-0.10337543487548828,
0.13391651213169098,
0.08956552296876907,
-0.0060893171466887,
0.037197306752204895,
0.024989010766148567,
0.06867308169603348,
-0.06233874335885048,
-0.009597424417734146,
0.15581579506397247,
-0.009040242061018944,
0.06215013191103935,
0.12999725341796875,
0.06666824221611023,
-0.09433972090482712,
-0.022919438779354095,
-0.01883879117667675,
-0.09602656215429306,
-0.19175516068935394,
-0.057091742753982544,
-0.049366164952516556,
0.08483017235994339,
0.14666369557380676,
0.11997713893651962,
0.16513875126838684,
0.09672091901302338,
0.017073094844818115,
0.032890960574150085,
0.011969516053795815,
0.02745753899216652,
0.09431096166372299,
-0.00256404560059309,
-0.00900819431990385,
-0.1345144361257553,
0.04063615947961807,
0.16199742257595062,
0.16016624867916107,
0.2346680760383606,
0.24405603110790253,
0.013032541610300541,
0.08629986643791199,
0.14010414481163025,
0.09959616512060165,
0.083418108522892,
0.014013865031301975,
0.0002983128360938281,
-0.07782557606697083,
-0.06522127240896225,
0.007191324606537819,
0.08919525146484375,
-0.056596651673316956,
-0.13630864024162292,
0.04233114793896675,
-0.15700164437294006,
0.043609846383333206,
0.08521639555692673,
0.10101553797721863,
-0.12919598817825317,
0.11238693445920944,
0.07870315760374069,
0.13523606956005096,
-0.033454976975917816,
0.12932239472866058,
-0.03169083222746849,
-0.008430219255387783,
0.1317882388830185,
0.007853557355701923,
0.08151012659072876,
-0.024717014282941818,
-0.0011054257629439235,
-0.017972934991121292,
-0.23283958435058594,
0.0644598975777626,
0.10178142786026001,
-0.11300219595432281,
0.27768510580062866,
0.031322941184043884,
-0.12874376773834229,
-0.04034474864602089,
-0.036046352237463,
0.12492694705724716,
0.22686100006103516,
0.1506083458662033,
0.08461418747901917,
-0.2186128795146942,
-0.015754923224449158,
-0.09932077676057816,
-0.0005119231645949185,
0.029082471504807472,
0.023185651749372482,
-0.18783825635910034,
0.0009278097422793508,
0.018264522776007652,
0.001460708910599351,
0.1566782295703888,
-0.10841827839612961,
-0.0659492164850235,
0.00179493788164109,
0.08047734946012497,
-0.04437811300158501,
-0.06396231800317764,
0.034309569746255875,
-0.013767643831670284,
0.036747898906469345,
-0.022247834131121635,
-0.004408868495374918,
-0.04094367474317551,
-0.12550413608551025,
0.021679183468222618,
-0.017714237794280052,
0.029833028092980385,
-0.08279894292354584,
-0.04034486040472984,
-0.06748219579458237,
-0.23039697110652924,
0.14154691994190216,
-0.07678768783807755,
0.016050616279244423,
-0.05765075236558914,
0.05977974832057953,
-0.0824442207813263,
0.00418700510635972,
-0.0022916689049452543,
0.056743767112493515,
-0.033833812922239304,
-0.10060850530862808,
0.1735401153564453,
-0.02724578231573105,
0.046342626214027405,
-0.00022314728994388133,
-0.05170644447207451,
-0.035063985735177994,
0.012569589540362358,
-0.02630540169775486,
0.1234268769621849,
0.2582937479019165,
-0.11369399726390839,
0.11319419741630554,
0.22277510166168213,
-0.08378475159406662,
-0.2901381254196167,
-0.0702567845582962,
-0.18003669381141663,
-0.1256219744682312,
0.052320681512355804,
-0.19621984660625458,
0.14071376621723175,
0.22147466242313385,
-0.14830414950847626,
0.229997918009758,
-0.14988930523395538,
-0.030987894162535667,
0.15975996851921082,
-0.0008190532680600882,
0.3081471621990204,
-0.19845253229141235,
-0.06818240880966187,
-0.12761925160884857,
-0.15836204588413239,
0.155714213848114,
-0.025408737361431122,
0.006225026212632656,
-0.007217234466224909,
-0.08931957185268402,
-0.02436586655676365,
0.004366954322904348,
0.24909676611423492,
0.004330891650170088,
0.16055257618427277,
-0.11767592281103134,
-0.12619024515151978,
0.11690738052129745,
-0.06503412872552872,
-0.0007165660499595106,
-0.10723470896482468,
-0.010643302462995052,
-0.11397052556276321,
0.09066908806562424,
-0.05764220282435417,
0.04375004768371582,
0.02174108289182186,
-0.017453894019126892,
-0.10904242843389511,
-0.005453106015920639,
-0.09661629796028137,
0.0515119843184948,
0.356973797082901,
0.056218892335891724,
-0.06076716259121895,
0.09476302564144135,
-0.045844666659832,
-0.09363016486167908,
-0.04768260940909386,
-0.12678976356983185,
-0.0685768872499466,
0.1280103325843811,
-0.30839988589286804,
0.06342349946498871,
0.060435857623815536,
-0.0101803969591856,
0.05798220634460449,
0.0419137105345726,
-0.008689306676387787,
-0.002610941184684634,
0.18246068060398102,
-0.041163694113492966,
-0.013913077302277088,
0.022781025618314743,
0.1528378427028656,
0.20284785330295563,
0.038649726659059525,
0.07634012401103973,
0.016211945563554764,
0.004480070900171995,
0.037742264568805695,
0.07341662049293518,
-0.0799650028347969,
-0.060552340000867844,
0.0995108038187027,
-0.0472230538725853,
-0.08839789032936096,
0.2580071687698364,
0.06586729735136032,
-0.040969472378492355,
-0.060587961226701736,
0.023097578436136246,
-0.06413619965314865,
-0.106551893055439,
-0.029016191139817238,
0.007275809999555349,
-0.14201894402503967,
-0.14605849981307983,
0.029940688982605934,
-0.055694930255413055,
-0.036023736000061035,
-0.0009951975662261248,
0.0818314328789711,
0.01024248544126749,
0.10877418518066406,
-0.050103265792131424,
0.1298569291830063,
-0.07700810581445694,
-0.21583467721939087,
0.044681038707494736,
-0.1390920728445053,
-0.24245065450668335,
0.05320950597524643,
0.07469253987073898,
-0.029019640758633614,
-0.011899758130311966,
-0.06899982690811157,
0.06061933934688568,
-0.1356326937675476,
0.12674148380756378,
-0.05317538231611252,
0.017484011128544807,
0.023907091468572617,
-0.030213210731744766,
-0.043195463716983795,
0.009983353316783905,
-0.15352073311805725,
-0.06672659516334534,
-0.0035989026073366404,
0.06315059959888458,
-0.0489853136241436,
-0.08843541145324707,
0.08217836916446686,
0.04006815701723099,
0.08011067658662796,
0.07868228107690811,
0.00977279432117939,
0.0726410523056984,
-0.18324869871139526,
-0.1208200752735138,
0.14623382687568665,
0.025101887062191963,
-0.048409875482320786,
0.08060428500175476,
-0.039926428347826004,
0.04881305247545242,
-0.08390691131353378,
0.006642403081059456,
0.0034260768443346024,
-0.1251237690448761,
-0.09406817704439163,
-0.09683351963758469,
-0.15214946866035461,
0.00039810591260902584,
-0.04967843368649483,
0.1913544088602066,
0.008625444024801254,
0.0807836502790451,
0.036689359694719315,
-0.006731836590915918,
-0.051704924553632736,
0.02872658520936966,
-0.041187088936567307,
-0.10434682667255402,
-0.17093461751937866,
-0.015617710538208485,
-0.0860636904835701,
-0.1006554514169693,
0.2431410551071167,
0.048497993499040604,
-0.1993618756532669,
0.02384042739868164,
0.18894675374031067,
-0.07109846919775009,
0.023319972679018974,
0.25406286120414734,
0.00019303734006825835,
0.025920644402503967,
-0.02808104082942009,
0.026976024731993675,
0.021667996421456337,
-0.02375073917210102,
0.026855897158384323,
0.12996679544448853,
0.043553244322538376,
0.032946716994047165,
0.14659735560417175,
-0.0173412524163723,
-0.08477585017681122,
0.022847771644592285,
0.061927322298288345,
0.1110801249742508,
0.04275544360280037,
0.04724521189928055,
0.21924637258052826,
-0.0042988271452486515,
-0.00025624613044783473,
-0.05579526722431183,
0.011268865317106247,
-0.08793025463819504,
-0.1877223551273346,
-0.05527739226818085,
-0.17583560943603516,
0.049897871911525726,
-0.004426159430295229,
-0.012788284569978714,
0.2909761965274811,
0.027319302782416344,
-0.0482502318918705,
-0.06282444298267365,
-0.16109506785869598,
-0.07760324329137802,
0.06602004915475845,
-0.00034622318344190717,
-0.07779118418693542,
-0.04654536023736,
-0.05229349806904793,
0.06716009229421616,
-0.0650051012635231,
-0.044580407440662384,
0.00833569560199976,
0.08897022902965546,
-0.0011313384165987372,
-0.059533439576625824,
-0.058417774736881256,
-0.07093261927366257,
0.007818278856575489,
-0.041152771562337875,
0.13718730211257935,
0.014150754548609257,
0.061706382781267166,
0.08388342708349228,
0.0832892581820488,
-0.04481666162610054,
-0.005954330787062645,
0.01730518601834774,
0.024704741314053535,
-0.14028121531009674,
0.07547515630722046,
-0.05182021111249924,
-0.046783607453107834,
0.011663789860904217,
0.16521625220775604,
0.19023829698562622,
-0.10069664567708969,
-0.03277084603905678,
-0.03297418728470802,
0.010275846347212791,
0.013714811764657497,
0.13700632750988007,
0.08500899374485016,
0.08871713280677795,
-0.032855018973350525,
-0.061874307692050934,
-0.06518110632896423,
0.015506909228861332,
-0.14511807262897491,
0.03136218339204788,
0.038375891745090485,
-0.08714506775140762,
-0.0889124721288681,
0.12509585916996002,
0.014278160408139229,
0.11131628602743149,
0.16461534798145294,
-0.05992981046438217,
-0.024726636707782745,
0.014439063146710396,
0.15600472688674927,
0.035410262644290924,
-0.006145869381725788,
-0.15497305989265442,
-0.06066638603806496,
-0.03294585272669792,
0.0111419428139925,
-0.3058968782424927,
-0.16970622539520264,
-0.008374981582164764,
-0.0351867713034153,
0.30137813091278076,
0.027061674743890762,
0.06243366748094559,
0.008204973302781582,
0.02186395600438118,
-0.10690846294164658,
0.08221492171287537,
-0.02377958409488201,
0.01824123226106167,
-0.08009807765483856,
-0.11080692708492279,
-0.03178728371858597,
-0.03495577722787857,
0.1160794198513031,
0.059739332646131516,
-0.02478528767824173,
0.20401827991008759,
-0.09265992045402527,
-0.053211916238069534,
0.013441485352814198,
-0.18209552764892578,
0.028789974749088287,
-0.048542529344558716,
-0.005964033771306276,
-0.13737298548221588,
-0.047639016062021255,
-0.04662676155567169,
0.07773999124765396,
-0.2452046424150467,
-0.04547024518251419,
0.22630788385868073,
-0.009974819608032703,
0.022548647597432137,
0.05865916237235069,
0.05990443006157875,
0.0051626162603497505,
-0.10867731273174286,
0.03566248342394829,
-0.07021775841712952,
0.012532292865216732,
0.11721400171518326,
-0.03954120725393295,
-0.00978852342814207,
-0.12052185088396072,
0.08994459360837936,
-0.02892490290105343,
0.04041118174791336,
-0.08855695277452469
] |
null | null | null |
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
```python
from kornia.contrib import VisionTransformer
vit_model = VisionTransformer.from_config('vit_s/32', pretrained=True)
...
```
Original weights from [AugReg](https://arxiv.org/abs/2106.10270) as recommended by [google research vision transformer repo](https://github.com/google-research/vision_transformer): This weight is based on the
[AugReg ViT_S/32 pretrained on imagenet21k](https://storage.googleapis.com/vit_models/augreg/S_32-i21k-300ep-lr_0.001-aug_none-wd_0.1-do_0.0-sd_0.0.npz)
Weights converted to PyTorch for Kornia ViT implementation (by [@gau-nernst](https://github.com/gau-nernst) in [kornia/kornia#2786](https://github.com/kornia/kornia/pull/2786#discussion_r1482339811))
<details>
<summary>Convert jax checkpoint function</summary>
```
def convert_jax_checkpoint(np_state_dict: dict[str, np.ndarray]):
def get_weight(key: str) -> torch.Tensor:
return torch.from_numpy(np_state_dict[key])
state_dict = dict()
state_dict["patch_embedding.cls_token"] = get_weight("cls")
state_dict["patch_embedding.backbone.weight"] = get_weight("embedding/kernel").permute(3, 2, 0, 1) # conv »
state_dict["patch_embedding.backbone.bias"] = get_weight("embedding/bias")
state_dict["patch_embedding.positions"] = get_weight("Transformer/posembed_input/pos_embedding").squeeze(0)
# for i, block in enumerate(self.encoder.blocks):
for i in range(100):
prefix1 = f"encoder.blocks.{i}"
prefix2 = f"Transformer/encoderblock_{i}"
if f"{prefix2}/LayerNorm_0/scale" not in np_state_dict:
break
state_dict[f"{prefix1}.0.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_0/scale")
state_dict[f"{prefix1}.0.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_0/bias")
mha_prefix = f"{prefix2}/MultiHeadDotProductAttention_1"
qkv_weight = [get_weight(f"{mha_prefix}/{x}/kernel") for x in ["query", "key", "value"]]
qkv_bias = [get_weight(f"{mha_prefix}/{x}/bias") for x in ["query", "key", "value"]]
state_dict[f"{prefix1}.0.fn.1.qkv.weight"] = torch.cat(qkv_weight, 1).flatten(1).T
state_dict[f"{prefix1}.0.fn.1.qkv.bias"] = torch.cat(qkv_bias, 0).flatten()
state_dict[f"{prefix1}.0.fn.1.projection.weight"] = get_weight(f"{mha_prefix}/out/kernel").flatten(0, 1»
state_dict[f"{prefix1}.0.fn.1.projection.bias"] = get_weight(f"{mha_prefix}/out/bias")
state_dict[f"{prefix1}.1.fn.0.weight"] = get_weight(f"{prefix2}/LayerNorm_2/scale")
state_dict[f"{prefix1}.1.fn.0.bias"] = get_weight(f"{prefix2}/LayerNorm_2/bias")
state_dict[f"{prefix1}.1.fn.1.0.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/kernel").T
state_dict[f"{prefix1}.1.fn.1.0.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_0/bias")
state_dict[f"{prefix1}.1.fn.1.3.weight"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/kernel").T
state_dict[f"{prefix1}.1.fn.1.3.bias"] = get_weight(f"{prefix2}/MlpBlock_3/Dense_1/bias")
state_dict["norm.weight"] = get_weight("Transformer/encoder_norm/scale")
state_dict["norm.bias"] = get_weight("Transformer/encoder_norm/bias")
return state_dict
```
</details> | {"license": "apache-2.0", "pipeline_tag": "image-classification"} | image-classification | kornia/vit_s32_i21k_augreg_i21k_r224 | [
"image-classification",
"arxiv:2106.10270",
"license:apache-2.0",
"region:us"
] | 2024-02-09T01:40:25+00:00 | [
"2106.10270"
] | [] | TAGS
#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us
|
Pytorch weights for Kornia ViT converted from the original google JAX vision-transformer repo.
Original weights from AugReg as recommended by google research vision transformer repo: This weight is based on the
AugReg ViT_S/32 pretrained on imagenet21k
Weights converted to PyTorch for Kornia ViT implementation (by @gau-nernst in kornia/kornia#2786)
<details>
<summary>Convert jax checkpoint function</summary>
</details> | [] | [
"TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
27
] | [
"passage: TAGS\n#image-classification #arxiv-2106.10270 #license-apache-2.0 #region-us \n"
] | [
-0.06109374389052391,
0.20674705505371094,
-0.006548014469444752,
0.049976740032434464,
0.02543392963707447,
0.06775278598070145,
0.1434560865163803,
0.10054779052734375,
0.0873129591345787,
-0.0696193128824234,
0.16259659826755524,
0.07446799427270889,
0.027905816212296486,
-0.020278295502066612,
0.0003193104930687696,
-0.19860264658927917,
0.07249123603105545,
-0.01418757252395153,
-0.03743588179349899,
0.016364481300115585,
0.031079968437552452,
-0.03377098590135574,
0.06803242117166519,
-0.013396034017205238,
-0.12081167846918106,
-0.004631385672837496,
0.05561913177371025,
-0.04842509329319,
0.07639530301094055,
-0.0024446528404951096,
0.03034677915275097,
0.033661652356386185,
0.0436035580933094,
-0.18721453845500946,
-0.0013201063266023993,
-0.011022438295185566,
-0.13286513090133667,
0.06692822277545929,
0.12416379153728485,
0.0049120765179395676,
0.03520214185118675,
0.04749228432774544,
-0.1190459355711937,
0.007217442616820335,
-0.09456748515367508,
-0.2383200079202652,
-0.10159328579902649,
0.11124194413423538,
0.12468010187149048,
0.01974388025701046,
0.10125472396612167,
0.03719622269272804,
-0.12143778800964355,
0.007481607608497143,
0.07237470895051956,
-0.24169990420341492,
-0.010691691190004349,
0.1201784610748291,
-0.1079055592417717,
0.04524125158786774,
-0.03944199159741402,
0.09898041188716888,
0.0823771059513092,
-0.045112185180187225,
-0.11518827825784683,
-0.045906227082014084,
-0.11930672824382782,
0.05414021015167236,
0.02489721029996872,
-0.08919412642717361,
0.3176185190677643,
0.1532946676015854,
0.002456814516335726,
0.11417848616838455,
-0.034857455641031265,
0.03917086496949196,
-0.020580649375915527,
0.14350418746471405,
0.11800917983055115,
0.1277526319026947,
0.11405012756586075,
-0.018727514892816544,
-0.18136470019817352,
-0.06914898008108139,
-0.16194461286067963,
-0.04335305839776993,
-0.03692782297730446,
0.17465905845165253,
-0.1323341280221939,
-0.02526034042239189,
-0.1357729136943817,
-0.08216837048530579,
0.02422415465116501,
-0.0783277153968811,
0.17794139683246613,
0.12570883333683014,
-0.025183117017149925,
0.05908667668700218,
0.14745140075683594,
0.12899348139762878,
0.02096019685268402,
0.03532757610082626,
-0.10447050631046295,
0.19674737751483917,
-0.02905309945344925,
0.03755328059196472,
0.03452769294381142,
0.11503022909164429,
0.06668683886528015,
-0.08765921741724014,
0.09905751049518585,
-0.034111931920051575,
-0.1760949343442917,
-0.02817642129957676,
-0.0438312403857708,
0.051844481378793716,
-0.0005061799311079085,
-0.04923499748110771,
-0.07902505248785019,
0.02592616155743599,
0.20208676159381866,
0.005098436959087849,
0.00970771349966526,
-0.009410499595105648,
-0.01887846365571022,
-0.03703097999095917,
0.06327838450670242,
0.020843954756855965,
0.06386575847864151,
-0.00038021898944862187,
-0.07227174192667007,
0.04220779612660408,
0.0033467260655015707,
0.07464555650949478,
0.11725340783596039,
-0.033287424594163895,
0.031015444546937943,
-0.1253310889005661,
-0.06270439177751541,
0.03723682835698128,
0.086534284055233,
0.0028114039450883865,
0.01238210964947939,
0.11720160394906998,
0.014849238097667694,
0.03825271129608154,
-0.03593437746167183,
-0.060856327414512634,
-0.099258191883564,
0.055119361728429794,
-0.13103467226028442,
0.08423157781362534,
-0.2563755214214325,
0.011386703699827194,
-0.10534657537937164,
0.053238339722156525,
-0.09686396270990372,
-0.07819923013448715,
-0.13250695168972015,
0.2009194940328598,
-0.05468209087848663,
0.0034654189366847277,
-0.054602500051259995,
-0.00633781123906374,
-0.05506056174635887,
0.07645745575428009,
-0.15609174966812134,
0.02364489808678627,
0.08345842361450195,
-0.15114741027355194,
-0.13571877777576447,
-0.002641590777784586,
0.043754223734140396,
-0.07488250732421875,
-0.010925939306616783,
0.3182951807975769,
-0.03542245179414749,
-0.01839727908372879,
0.036988433450460434,
0.15065109729766846,
-0.08740837126970291,
-0.20893323421478271,
0.10468775033950806,
-0.09690731018781662,
-0.14157627522945404,
0.0215351153165102,
-0.13635723292827606,
0.10152363032102585,
0.040783826261758804,
-0.08645343035459518,
-0.02261362224817276,
-0.04002821445465088,
-0.04111453890800476,
0.012164331041276455,
0.05289793014526367,
-0.046031367033720016,
0.036598462611436844,
-0.10292722284793854,
0.05292672663927078,
0.08823665231466293,
0.03464950621128082,
-0.019848383963108063,
0.05194208770990372,
-0.0322202704846859,
-0.008407019078731537,
-0.06743084639310837,
0.03886767849326134,
0.009944709949195385,
-0.047629464417696,
0.08154439926147461,
-0.05256316438317299,
0.028394905850291252,
-0.08248095214366913,
-0.0052256197668612,
-0.03148965165019035,
-0.021348997950553894,
0.016548115760087967,
0.04151642695069313,
-0.15185265243053436,
0.05146369710564613,
0.027628103271126747,
0.06300205737352371,
-0.07534655928611755,
-0.06911735236644745,
0.13192912936210632,
-0.02104104869067669,
-0.006522714160382748,
0.09356412291526794,
0.007906613871455193,
-0.09177529066801071,
-0.01047999132424593,
-0.02048683352768421,
0.1222124695777893,
0.01773674599826336,
-0.03080260008573532,
0.15719905495643616,
0.004599755629897118,
0.1652202308177948,
0.19648905098438263,
-0.1871400624513626,
0.05895731970667839,
-0.04543163627386093,
0.03526407852768898,
-0.00021277944324538112,
0.058195192366838455,
0.030574873089790344,
-0.11539100110530853,
-0.0529194250702858,
0.04648087918758392,
-0.0637110099196434,
0.08189071714878082,
-0.016040494665503502,
-0.07081851363182068,
-0.09113258868455887,
-0.004617263562977314,
0.22731298208236694,
-0.22143718600273132,
0.13705743849277496,
0.44992348551750183,
-0.00563804479315877,
0.04384651407599449,
-0.07071708142757416,
-0.02926171012222767,
0.011590258218348026,
-0.016685742884874344,
-0.027885599061846733,
0.20283104479312897,
-0.037577949464321136,
-0.006611361168324947,
0.07687141746282578,
0.021334122866392136,
0.02833111397922039,
-0.2102135717868805,
-0.08647490292787552,
-0.01990378089249134,
-0.032265402376651764,
-0.106113001704216,
-0.03494508937001228,
-0.07398673892021179,
0.09487839788198471,
-0.00005973442966933362,
-0.13227896392345428,
0.12197559326887131,
-0.04474426805973053,
-0.053833432495594025,
0.1027798280119896,
-0.1763962209224701,
-0.23515380918979645,
-0.14439262449741364,
0.03435428440570831,
-0.07389409840106964,
0.033989984542131424,
0.05001555383205414,
-0.12449482828378677,
-0.042997002601623535,
0.009898168034851551,
-0.17011038959026337,
-0.0666801705956459,
-0.009744573384523392,
0.04772152379155159,
0.06096755340695381,
0.05611218884587288,
-0.07783979177474976,
-0.04949898272752762,
-0.03132689744234085,
0.022898364812135696,
0.13073059916496277,
-0.10337543487548828,
0.13391651213169098,
0.08956552296876907,
-0.0060893171466887,
0.037197306752204895,
0.024989010766148567,
0.06867308169603348,
-0.06233874335885048,
-0.009597424417734146,
0.15581579506397247,
-0.009040242061018944,
0.06215013191103935,
0.12999725341796875,
0.06666824221611023,
-0.09433972090482712,
-0.022919438779354095,
-0.01883879117667675,
-0.09602656215429306,
-0.19175516068935394,
-0.057091742753982544,
-0.049366164952516556,
0.08483017235994339,
0.14666369557380676,
0.11997713893651962,
0.16513875126838684,
0.09672091901302338,
0.017073094844818115,
0.032890960574150085,
0.011969516053795815,
0.02745753899216652,
0.09431096166372299,
-0.00256404560059309,
-0.00900819431990385,
-0.1345144361257553,
0.04063615947961807,
0.16199742257595062,
0.16016624867916107,
0.2346680760383606,
0.24405603110790253,
0.013032541610300541,
0.08629986643791199,
0.14010414481163025,
0.09959616512060165,
0.083418108522892,
0.014013865031301975,
0.0002983128360938281,
-0.07782557606697083,
-0.06522127240896225,
0.007191324606537819,
0.08919525146484375,
-0.056596651673316956,
-0.13630864024162292,
0.04233114793896675,
-0.15700164437294006,
0.043609846383333206,
0.08521639555692673,
0.10101553797721863,
-0.12919598817825317,
0.11238693445920944,
0.07870315760374069,
0.13523606956005096,
-0.033454976975917816,
0.12932239472866058,
-0.03169083222746849,
-0.008430219255387783,
0.1317882388830185,
0.007853557355701923,
0.08151012659072876,
-0.024717014282941818,
-0.0011054257629439235,
-0.017972934991121292,
-0.23283958435058594,
0.0644598975777626,
0.10178142786026001,
-0.11300219595432281,
0.27768510580062866,
0.031322941184043884,
-0.12874376773834229,
-0.04034474864602089,
-0.036046352237463,
0.12492694705724716,
0.22686100006103516,
0.1506083458662033,
0.08461418747901917,
-0.2186128795146942,
-0.015754923224449158,
-0.09932077676057816,
-0.0005119231645949185,
0.029082471504807472,
0.023185651749372482,
-0.18783825635910034,
0.0009278097422793508,
0.018264522776007652,
0.001460708910599351,
0.1566782295703888,
-0.10841827839612961,
-0.0659492164850235,
0.00179493788164109,
0.08047734946012497,
-0.04437811300158501,
-0.06396231800317764,
0.034309569746255875,
-0.013767643831670284,
0.036747898906469345,
-0.022247834131121635,
-0.004408868495374918,
-0.04094367474317551,
-0.12550413608551025,
0.021679183468222618,
-0.017714237794280052,
0.029833028092980385,
-0.08279894292354584,
-0.04034486040472984,
-0.06748219579458237,
-0.23039697110652924,
0.14154691994190216,
-0.07678768783807755,
0.016050616279244423,
-0.05765075236558914,
0.05977974832057953,
-0.0824442207813263,
0.00418700510635972,
-0.0022916689049452543,
0.056743767112493515,
-0.033833812922239304,
-0.10060850530862808,
0.1735401153564453,
-0.02724578231573105,
0.046342626214027405,
-0.00022314728994388133,
-0.05170644447207451,
-0.035063985735177994,
0.012569589540362358,
-0.02630540169775486,
0.1234268769621849,
0.2582937479019165,
-0.11369399726390839,
0.11319419741630554,
0.22277510166168213,
-0.08378475159406662,
-0.2901381254196167,
-0.0702567845582962,
-0.18003669381141663,
-0.1256219744682312,
0.052320681512355804,
-0.19621984660625458,
0.14071376621723175,
0.22147466242313385,
-0.14830414950847626,
0.229997918009758,
-0.14988930523395538,
-0.030987894162535667,
0.15975996851921082,
-0.0008190532680600882,
0.3081471621990204,
-0.19845253229141235,
-0.06818240880966187,
-0.12761925160884857,
-0.15836204588413239,
0.155714213848114,
-0.025408737361431122,
0.006225026212632656,
-0.007217234466224909,
-0.08931957185268402,
-0.02436586655676365,
0.004366954322904348,
0.24909676611423492,
0.004330891650170088,
0.16055257618427277,
-0.11767592281103134,
-0.12619024515151978,
0.11690738052129745,
-0.06503412872552872,
-0.0007165660499595106,
-0.10723470896482468,
-0.010643302462995052,
-0.11397052556276321,
0.09066908806562424,
-0.05764220282435417,
0.04375004768371582,
0.02174108289182186,
-0.017453894019126892,
-0.10904242843389511,
-0.005453106015920639,
-0.09661629796028137,
0.0515119843184948,
0.356973797082901,
0.056218892335891724,
-0.06076716259121895,
0.09476302564144135,
-0.045844666659832,
-0.09363016486167908,
-0.04768260940909386,
-0.12678976356983185,
-0.0685768872499466,
0.1280103325843811,
-0.30839988589286804,
0.06342349946498871,
0.060435857623815536,
-0.0101803969591856,
0.05798220634460449,
0.0419137105345726,
-0.008689306676387787,
-0.002610941184684634,
0.18246068060398102,
-0.041163694113492966,
-0.013913077302277088,
0.022781025618314743,
0.1528378427028656,
0.20284785330295563,
0.038649726659059525,
0.07634012401103973,
0.016211945563554764,
0.004480070900171995,
0.037742264568805695,
0.07341662049293518,
-0.0799650028347969,
-0.060552340000867844,
0.0995108038187027,
-0.0472230538725853,
-0.08839789032936096,
0.2580071687698364,
0.06586729735136032,
-0.040969472378492355,
-0.060587961226701736,
0.023097578436136246,
-0.06413619965314865,
-0.106551893055439,
-0.029016191139817238,
0.007275809999555349,
-0.14201894402503967,
-0.14605849981307983,
0.029940688982605934,
-0.055694930255413055,
-0.036023736000061035,
-0.0009951975662261248,
0.0818314328789711,
0.01024248544126749,
0.10877418518066406,
-0.050103265792131424,
0.1298569291830063,
-0.07700810581445694,
-0.21583467721939087,
0.044681038707494736,
-0.1390920728445053,
-0.24245065450668335,
0.05320950597524643,
0.07469253987073898,
-0.029019640758633614,
-0.011899758130311966,
-0.06899982690811157,
0.06061933934688568,
-0.1356326937675476,
0.12674148380756378,
-0.05317538231611252,
0.017484011128544807,
0.023907091468572617,
-0.030213210731744766,
-0.043195463716983795,
0.009983353316783905,
-0.15352073311805725,
-0.06672659516334534,
-0.0035989026073366404,
0.06315059959888458,
-0.0489853136241436,
-0.08843541145324707,
0.08217836916446686,
0.04006815701723099,
0.08011067658662796,
0.07868228107690811,
0.00977279432117939,
0.0726410523056984,
-0.18324869871139526,
-0.1208200752735138,
0.14623382687568665,
0.025101887062191963,
-0.048409875482320786,
0.08060428500175476,
-0.039926428347826004,
0.04881305247545242,
-0.08390691131353378,
0.006642403081059456,
0.0034260768443346024,
-0.1251237690448761,
-0.09406817704439163,
-0.09683351963758469,
-0.15214946866035461,
0.00039810591260902584,
-0.04967843368649483,
0.1913544088602066,
0.008625444024801254,
0.0807836502790451,
0.036689359694719315,
-0.006731836590915918,
-0.051704924553632736,
0.02872658520936966,
-0.041187088936567307,
-0.10434682667255402,
-0.17093461751937866,
-0.015617710538208485,
-0.0860636904835701,
-0.1006554514169693,
0.2431410551071167,
0.048497993499040604,
-0.1993618756532669,
0.02384042739868164,
0.18894675374031067,
-0.07109846919775009,
0.023319972679018974,
0.25406286120414734,
0.00019303734006825835,
0.025920644402503967,
-0.02808104082942009,
0.026976024731993675,
0.021667996421456337,
-0.02375073917210102,
0.026855897158384323,
0.12996679544448853,
0.043553244322538376,
0.032946716994047165,
0.14659735560417175,
-0.0173412524163723,
-0.08477585017681122,
0.022847771644592285,
0.061927322298288345,
0.1110801249742508,
0.04275544360280037,
0.04724521189928055,
0.21924637258052826,
-0.0042988271452486515,
-0.00025624613044783473,
-0.05579526722431183,
0.011268865317106247,
-0.08793025463819504,
-0.1877223551273346,
-0.05527739226818085,
-0.17583560943603516,
0.049897871911525726,
-0.004426159430295229,
-0.012788284569978714,
0.2909761965274811,
0.027319302782416344,
-0.0482502318918705,
-0.06282444298267365,
-0.16109506785869598,
-0.07760324329137802,
0.06602004915475845,
-0.00034622318344190717,
-0.07779118418693542,
-0.04654536023736,
-0.05229349806904793,
0.06716009229421616,
-0.0650051012635231,
-0.044580407440662384,
0.00833569560199976,
0.08897022902965546,
-0.0011313384165987372,
-0.059533439576625824,
-0.058417774736881256,
-0.07093261927366257,
0.007818278856575489,
-0.041152771562337875,
0.13718730211257935,
0.014150754548609257,
0.061706382781267166,
0.08388342708349228,
0.0832892581820488,
-0.04481666162610054,
-0.005954330787062645,
0.01730518601834774,
0.024704741314053535,
-0.14028121531009674,
0.07547515630722046,
-0.05182021111249924,
-0.046783607453107834,
0.011663789860904217,
0.16521625220775604,
0.19023829698562622,
-0.10069664567708969,
-0.03277084603905678,
-0.03297418728470802,
0.010275846347212791,
0.013714811764657497,
0.13700632750988007,
0.08500899374485016,
0.08871713280677795,
-0.032855018973350525,
-0.061874307692050934,
-0.06518110632896423,
0.015506909228861332,
-0.14511807262897491,
0.03136218339204788,
0.038375891745090485,
-0.08714506775140762,
-0.0889124721288681,
0.12509585916996002,
0.014278160408139229,
0.11131628602743149,
0.16461534798145294,
-0.05992981046438217,
-0.024726636707782745,
0.014439063146710396,
0.15600472688674927,
0.035410262644290924,
-0.006145869381725788,
-0.15497305989265442,
-0.06066638603806496,
-0.03294585272669792,
0.0111419428139925,
-0.3058968782424927,
-0.16970622539520264,
-0.008374981582164764,
-0.0351867713034153,
0.30137813091278076,
0.027061674743890762,
0.06243366748094559,
0.008204973302781582,
0.02186395600438118,
-0.10690846294164658,
0.08221492171287537,
-0.02377958409488201,
0.01824123226106167,
-0.08009807765483856,
-0.11080692708492279,
-0.03178728371858597,
-0.03495577722787857,
0.1160794198513031,
0.059739332646131516,
-0.02478528767824173,
0.20401827991008759,
-0.09265992045402527,
-0.053211916238069534,
0.013441485352814198,
-0.18209552764892578,
0.028789974749088287,
-0.048542529344558716,
-0.005964033771306276,
-0.13737298548221588,
-0.047639016062021255,
-0.04662676155567169,
0.07773999124765396,
-0.2452046424150467,
-0.04547024518251419,
0.22630788385868073,
-0.009974819608032703,
0.022548647597432137,
0.05865916237235069,
0.05990443006157875,
0.0051626162603497505,
-0.10867731273174286,
0.03566248342394829,
-0.07021775841712952,
0.012532292865216732,
0.11721400171518326,
-0.03954120725393295,
-0.00978852342814207,
-0.12052185088396072,
0.08994459360837936,
-0.02892490290105343,
0.04041118174791336,
-0.08855695277452469
] |
null | null | transformers |
# Edit: As of 2024-02-10 this is currently the best performing 7B model on both the Open-LLM-Leaderboard as well as this (Nous Benchmark) [Leaderboard](https://huggingface.co/spaces/CultriX/Alt_LLM_LeaderBoard)
# NeuralTrix-7B-v1
NeuralTrix-7B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mlabonne/OmniBeagle-7B](https://huggingface.co/mlabonne/OmniBeagle-7B)
* [flemmingmiguel/MBX-7B-v3](https://huggingface.co/flemmingmiguel/MBX-7B-v3)
* [AiMavenAi/AiMaven-Prometheus](https://huggingface.co/AiMavenAi/AiMaven-Prometheus)
It was then trained with DPO using:
* https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
# no parameters necessary for base model
- model: mlabonne/OmniBeagle-7B
parameters:
density: 0.65
weight: 0.4
- model: flemmingmiguel/MBX-7B-v3
parameters:
density: 0.6
weight: 0.35
- model: AiMavenAi/AiMaven-Prometheus
parameters:
density: 0.6
weight: 0.35
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "CultriX/NeuralTrix-7B-v1"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "mlabonne/OmniBeagle-7B", "flemmingmiguel/MBX-7B-v3", "AiMavenAi/AiMaven-Prometheus"], "base_model": ["mlabonne/OmniBeagle-7B", "flemmingmiguel/MBX-7B-v3", "AiMavenAi/AiMaven-Prometheus"]} | text-generation | CultriX/NeuralTrix-7B-dpo | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"mlabonne/OmniBeagle-7B",
"flemmingmiguel/MBX-7B-v3",
"AiMavenAi/AiMaven-Prometheus",
"base_model:mlabonne/OmniBeagle-7B",
"base_model:flemmingmiguel/MBX-7B-v3",
"base_model:AiMavenAi/AiMaven-Prometheus",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T01:40:29+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #mlabonne/OmniBeagle-7B #flemmingmiguel/MBX-7B-v3 #AiMavenAi/AiMaven-Prometheus #base_model-mlabonne/OmniBeagle-7B #base_model-flemmingmiguel/MBX-7B-v3 #base_model-AiMavenAi/AiMaven-Prometheus #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Edit: As of 2024-02-10 this is currently the best performing 7B model on both the Open-LLM-Leaderboard as well as this (Nous Benchmark) Leaderboard
# NeuralTrix-7B-v1
NeuralTrix-7B-v1 is a merge of the following models using LazyMergekit:
* mlabonne/OmniBeagle-7B
* flemmingmiguel/MBX-7B-v3
* AiMavenAi/AiMaven-Prometheus
It was then trained with DPO using:
* URL
## Configuration
## Usage
| [
"# Edit: As of 2024-02-10 this is currently the best performing 7B model on both the Open-LLM-Leaderboard as well as this (Nous Benchmark) Leaderboard",
"# NeuralTrix-7B-v1\n\nNeuralTrix-7B-v1 is a merge of the following models using LazyMergekit:\n* mlabonne/OmniBeagle-7B\n* flemmingmiguel/MBX-7B-v3\n* AiMavenAi/AiMaven-Prometheus\n\nIt was then trained with DPO using: \n* URL",
"## Configuration",
"## Usage"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #mlabonne/OmniBeagle-7B #flemmingmiguel/MBX-7B-v3 #AiMavenAi/AiMaven-Prometheus #base_model-mlabonne/OmniBeagle-7B #base_model-flemmingmiguel/MBX-7B-v3 #base_model-AiMavenAi/AiMaven-Prometheus #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Edit: As of 2024-02-10 this is currently the best performing 7B model on both the Open-LLM-Leaderboard as well as this (Nous Benchmark) Leaderboard",
"# NeuralTrix-7B-v1\n\nNeuralTrix-7B-v1 is a merge of the following models using LazyMergekit:\n* mlabonne/OmniBeagle-7B\n* flemmingmiguel/MBX-7B-v3\n* AiMavenAi/AiMaven-Prometheus\n\nIt was then trained with DPO using: \n* URL",
"## Configuration",
"## Usage"
] | [
156,
43,
84,
4,
3
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #mlabonne/OmniBeagle-7B #flemmingmiguel/MBX-7B-v3 #AiMavenAi/AiMaven-Prometheus #base_model-mlabonne/OmniBeagle-7B #base_model-flemmingmiguel/MBX-7B-v3 #base_model-AiMavenAi/AiMaven-Prometheus #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Edit: As of 2024-02-10 this is currently the best performing 7B model on both the Open-LLM-Leaderboard as well as this (Nous Benchmark) Leaderboard# NeuralTrix-7B-v1\n\nNeuralTrix-7B-v1 is a merge of the following models using LazyMergekit:\n* mlabonne/OmniBeagle-7B\n* flemmingmiguel/MBX-7B-v3\n* AiMavenAi/AiMaven-Prometheus\n\nIt was then trained with DPO using: \n* URL## Configuration## Usage"
] | [
-0.07361216098070145,
0.03004509024322033,
-0.006210580468177795,
0.02386380173265934,
0.07831791043281555,
0.043553516268730164,
0.17047218978405,
0.10989539325237274,
0.023071547970175743,
0.037096671760082245,
0.0433441698551178,
0.11545345187187195,
0.03195162117481232,
0.09265244007110596,
-0.027268502861261368,
-0.20356597006320953,
0.07764051854610443,
-0.02253795973956585,
-0.04405812546610832,
0.06691020727157593,
0.12299385666847229,
-0.05510822683572769,
0.08232829719781876,
0.012478645890951157,
-0.06808096170425415,
0.012322927825152874,
-0.0008204241166822612,
-0.021725701168179512,
0.09456169605255127,
0.050689540803432465,
0.0911487266421318,
0.04584342986345291,
0.05158896744251251,
-0.16718977689743042,
0.019370062276721,
0.04923762008547783,
-0.01815810427069664,
0.044870976358652115,
0.08679616451263428,
-0.053210724145174026,
0.14687681198120117,
-0.014897591434419155,
0.047324229031801224,
0.06191888451576233,
-0.13337993621826172,
-0.1035233736038208,
-0.10428473353385925,
0.07025716453790665,
0.0569293387234211,
0.05472094938158989,
-0.01746799424290657,
0.116206593811512,
-0.034147121012210846,
0.0885576531291008,
0.12028960883617401,
-0.28402191400527954,
-0.023702170699834824,
0.1809600591659546,
0.05186620354652405,
-0.032925788313150406,
-0.039388835430145264,
0.04444891959428787,
-0.005175243131816387,
-0.0017317775636911392,
0.0792388767004013,
-0.04829556494951248,
0.17004910111427307,
-0.04579305648803711,
-0.12914380431175232,
-0.033705200999975204,
0.08720647543668747,
0.05923360586166382,
-0.013265437446534634,
-0.14326268434524536,
-0.0856359675526619,
0.025526195764541626,
-0.04167139157652855,
-0.08753422647714615,
0.0710349977016449,
0.003171295393258333,
0.09558463841676712,
-0.08073966950178146,
-0.03357774019241333,
-0.008292319253087044,
-0.03174559399485588,
0.07693317532539368,
-0.008441820740699768,
-0.01017819344997406,
-0.04869300127029419,
0.06104999780654907,
-0.10031760483980179,
-0.0994584858417511,
-0.04467517510056496,
-0.03019704297184944,
-0.06854474544525146,
-0.0510859377682209,
-0.05597271770238876,
-0.12426505237817764,
0.04624801501631737,
0.19477100670337677,
0.00256608915515244,
0.032112132757902145,
-0.00042440881952643394,
0.022252149879932404,
0.011452697217464447,
0.0717175230383873,
-0.07874175906181335,
-0.13595004379749298,
0.025278110057115555,
0.11374641209840775,
0.01924894191324711,
0.00802046898752451,
-0.05318083614110947,
-0.023022625595331192,
0.027101773768663406,
0.02285594493150711,
0.06145757436752319,
0.07306957244873047,
-0.07505399733781815,
-0.06595478951931,
0.1005309522151947,
-0.1477869749069214,
-0.002373697003349662,
-0.01418754830956459,
-0.07095668464899063,
0.059760820120573044,
0.09453710168600082,
0.04435182735323906,
-0.017538387328386307,
0.10713429003953934,
-0.05946538969874382,
-0.030437495559453964,
-0.0675586387515068,
-0.0963381752371788,
0.0015517103020101786,
-0.05585198104381561,
-0.046728815883398056,
-0.10751334577798843,
-0.22999021410942078,
-0.071888767182827,
0.06100671365857124,
-0.0014549650950357318,
-0.004126714542508125,
-0.07061663269996643,
-0.004779225215315819,
0.00483177462592721,
0.019175805151462555,
-0.018040921539068222,
-0.011321068741381168,
-0.007103745359927416,
-0.010457946918904781,
0.06311017274856567,
-0.06997471302747726,
0.03013673983514309,
-0.07118896394968033,
0.0753617063164711,
-0.1871347874403,
0.1202351450920105,
-0.05968747287988663,
0.046836573630571365,
-0.13173098862171173,
0.0029101017862558365,
-0.05142713710665703,
0.013401714153587818,
0.042083490639925,
0.12679067254066467,
-0.15768232941627502,
-0.074321448802948,
0.16484008729457855,
-0.12408401072025299,
-0.13848140835762024,
0.05584512650966644,
-0.01150893047451973,
0.08926312625408173,
0.07267927378416061,
0.14302843809127808,
0.12486625462770462,
-0.09810459613800049,
-0.05736733227968216,
-0.03867383301258087,
0.02238040417432785,
0.10172729194164276,
0.03795815259218216,
-0.034449003636837006,
0.054290011525154114,
0.014533784240484238,
-0.051920127123594284,
0.028549520298838615,
0.009825065732002258,
-0.08696361631155014,
-0.033428896218538284,
-0.06512662023305893,
0.032170847058296204,
-0.024512043222784996,
0.01768220029771328,
0.02473924122750759,
-0.0685182437300682,
0.09909101575613022,
0.13084696233272552,
-0.04299766570329666,
0.0044680689461529255,
-0.10122069716453552,
0.06460973620414734,
-0.012274685315787792,
0.044093213975429535,
-0.17044730484485626,
-0.14196690917015076,
0.0053374976851046085,
-0.12455639988183975,
-0.006585448049008846,
0.046633280813694,
0.09205666929483414,
0.021358205005526543,
-0.05932733044028282,
-0.03766574710607529,
-0.02142571471631527,
-0.0022249571047723293,
-0.016189444810152054,
-0.15715573728084564,
-0.08507052063941956,
-0.055081021040678024,
0.19235101342201233,
-0.1679701805114746,
0.054655540734529495,
0.012000658549368382,
0.17438139021396637,
0.05376484617590904,
-0.047083187848329544,
0.011860165745019913,
0.0003991004195995629,
-0.010856768116354942,
-0.03444324806332588,
0.06686563789844513,
0.008029742166399956,
-0.09686915576457977,
0.09275273978710175,
-0.1368487924337387,
0.04258254915475845,
0.0939682275056839,
0.03183411434292793,
-0.04722651094198227,
-0.0293512511998415,
-0.02493019960820675,
-0.0409686416387558,
0.025124432519078255,
-0.07094897329807281,
0.06365305930376053,
0.04440483823418617,
0.13364946842193604,
-0.06801240891218185,
-0.04751047119498253,
-0.002192565007135272,
0.005852452013641596,
-0.05703044682741165,
0.06295021623373032,
0.013427522033452988,
-0.1379200965166092,
0.050405412912368774,
0.12374598532915115,
0.020502453669905663,
0.12554769217967987,
0.0005698380991816521,
-0.04806046560406685,
-0.07725253701210022,
0.018458306789398193,
0.025818200781941414,
0.006112123839557171,
-0.08302967995405197,
0.024853138253092766,
0.037978965789079666,
0.03015734627842903,
0.03582455590367317,
-0.054476384073495865,
0.048930827528238297,
0.02596365474164486,
-0.056540437042713165,
0.08674556016921997,
0.06776919215917587,
-0.001702127861790359,
0.07475648820400238,
0.010108837857842445,
-0.03457585349678993,
-0.01014948170632124,
-0.030213434249162674,
-0.08733458817005157,
0.12542347609996796,
-0.07606442272663116,
-0.18791960179805756,
-0.11133935302495956,
-0.06119457632303238,
-0.10071203112602234,
0.0011228546500205994,
0.014381278306245804,
-0.008371375501155853,
-0.05074416100978851,
-0.06559331715106964,
0.062440838664770126,
0.01278475672006607,
-0.035969898104667664,
0.036702144891023636,
0.03887046128511429,
0.07223331928253174,
-0.1250227987766266,
-0.036169350147247314,
0.0009410047787241638,
-0.05314910039305687,
0.013029872439801693,
-0.0028958655893802643,
0.07280135154724121,
0.08589775860309601,
0.0165372546762228,
0.00999400019645691,
0.001830881112255156,
0.2361125648021698,
-0.06797774136066437,
0.05644010752439499,
0.17315594851970673,
-0.011325279250741005,
0.05468270555138588,
0.1363571733236313,
0.041389670222997665,
-0.09942399710416794,
0.007413162384182215,
0.05100693926215172,
-0.002423293190076947,
-0.1910836100578308,
-0.1055271103978157,
-0.03660767897963524,
-0.013138285838067532,
0.10440690070390701,
0.04488767310976982,
0.02258133329451084,
0.03588537871837616,
-0.04815758764743805,
0.04144788533449173,
0.05704544112086296,
0.04851682484149933,
0.14632873237133026,
0.012920090928673744,
0.1129726693034172,
-0.027113711461424828,
-0.0045925043523311615,
0.051159124821424484,
0.005122420843690634,
0.10036204010248184,
0.04579951614141464,
0.13423949480056763,
0.0791100561618805,
0.030801521614193916,
0.024681007489562035,
0.05374260991811752,
0.010690002702176571,
-0.0032156771048903465,
0.006704589817672968,
-0.1065497025847435,
-0.027816185727715492,
0.046548228710889816,
0.011775984428822994,
0.001027106074616313,
-0.03787519410252571,
0.049420058727264404,
0.07072354108095169,
0.22313407063484192,
0.050074636936187744,
-0.2703397274017334,
-0.04014638811349869,
-0.001416676794178784,
-0.01932748220860958,
-0.027062779292464256,
-0.04603644460439682,
-0.02983287163078785,
-0.13042043149471283,
0.13031740486621857,
-0.04391014948487282,
0.08336766809225082,
-0.10878803580999374,
0.021657943725585938,
0.03588676080107689,
0.046934522688388824,
0.017773713916540146,
0.03561389073729515,
-0.2379341572523117,
0.1499481350183487,
0.028888747096061707,
0.056305285543203354,
0.024349777027964592,
0.057149630039930344,
0.05681051313877106,
0.09452704340219498,
0.10438621044158936,
0.02092660777270794,
0.06312564015388489,
-0.03855999559164047,
-0.08872919529676437,
-0.034982871264219284,
0.05479871854186058,
-0.10118699073791504,
0.09113851189613342,
-0.037825822830200195,
-0.06453941762447357,
-0.004957006778568029,
0.07113789767026901,
-0.17886558175086975,
-0.11330076307058334,
0.09267094731330872,
0.0515182763338089,
0.08965172618627548,
-0.0853862538933754,
-0.03336627781391144,
-0.10108006745576859,
0.22854843735694885,
-0.001203211722895503,
-0.04524786025285721,
-0.11004839837551117,
0.038797877728939056,
0.07002580165863037,
-0.06913973391056061,
0.05982277914881706,
-0.027553316205739975,
0.0973149985074997,
-0.08069325983524323,
-0.09257521480321884,
0.04229290410876274,
-0.09767776727676392,
-0.08045101165771484,
-0.011622913181781769,
0.09005711227655411,
0.00878090225160122,
0.0006649084389209747,
0.041805531829595566,
0.05480315163731575,
0.03076750598847866,
-0.056941449642181396,
0.017170539125800133,
0.18227043747901917,
-0.03720469772815704,
0.0576191283762455,
-0.08358616381883621,
-0.09286323934793472,
-0.0437556728720665,
0.006794335786253214,
0.1333964467048645,
0.29735079407691956,
-0.033404670655727386,
0.06410616636276245,
0.13055749237537384,
-0.09247444570064545,
-0.18970391154289246,
-0.04092339798808098,
0.09115733951330185,
0.010949550196528435,
0.02385757304728031,
-0.17335784435272217,
0.08323781192302704,
0.11389478296041489,
-0.020576197654008865,
0.008426344953477383,
-0.3416063189506531,
-0.14339159429073334,
0.05131188780069351,
0.023656385019421577,
0.050764430314302444,
-0.09051487594842911,
-0.07962935417890549,
-0.06379501521587372,
-0.13292375206947327,
0.086619533598423,
0.007410259451717138,
0.06637655943632126,
-0.009029485285282135,
-0.0030514951795339584,
0.034958258271217346,
-0.025740724056959152,
0.13146552443504333,
0.007197726517915726,
0.02630447968840599,
-0.06721187382936478,
0.007497876882553101,
0.127523735165596,
-0.07938185334205627,
0.11364071071147919,
-0.012675046920776367,
0.02501179464161396,
-0.1214614287018776,
-0.03499237447977066,
-0.051744554191827774,
0.06638302654027939,
-0.051100123673677444,
-0.06490116566419601,
0.01948908157646656,
0.046574417501688004,
0.07903134822845459,
0.03565051779150963,
0.04517883062362671,
-0.05037762597203255,
0.05661523714661598,
0.1709713488817215,
0.10027532279491425,
-0.024587664753198624,
-0.11011441051959991,
-0.019483834505081177,
-0.0057855527848005295,
0.0501716285943985,
-0.053183313459157944,
0.04066143184900284,
0.08777029812335968,
0.0010135421762242913,
0.12740378081798553,
0.02583734504878521,
-0.09643819183111191,
-0.03545770049095154,
0.07898999750614166,
-0.13651564717292786,
-0.1553189754486084,
-0.01920972391963005,
-0.00388691877014935,
-0.0892072319984436,
-0.016694452613592148,
0.23282256722450256,
-0.032025691121816635,
0.0005498474929481745,
0.039761465042829514,
0.009775878861546516,
-0.060642797499895096,
0.09650932252407074,
-0.017380330711603165,
0.06005089357495308,
-0.08072137087583542,
0.08403068035840988,
0.08285839855670929,
-0.11542892456054688,
-0.02147769182920456,
0.10284759849309921,
-0.089589424431324,
-0.08173014223575592,
-0.1397438496351242,
0.169591024518013,
-0.057966336607933044,
-0.014872144907712936,
-0.0749741718173027,
-0.052816640585660934,
0.04304143786430359,
0.10194423049688339,
0.06543929874897003,
0.06603500247001648,
0.0030476870015263557,
-0.04254474490880966,
-0.04153918847441673,
0.0737854614853859,
0.041439950466156006,
0.07001624256372452,
-0.11401736736297607,
0.042610060423612595,
-0.01822715438902378,
-0.001556791947223246,
-0.014692757278680801,
-0.02020442858338356,
-0.10276816785335541,
-0.03938470780849457,
-0.1180810034275055,
-0.029821962118148804,
-0.07428235560655594,
-0.012775645591318607,
0.0024523409083485603,
0.02716987580060959,
-0.029193533584475517,
0.0072509534657001495,
-0.07995599508285522,
-0.0754479169845581,
-0.01775868609547615,
0.046224359422922134,
-0.1109686940908432,
-0.006945397239178419,
0.008755463175475597,
-0.07979292422533035,
0.0791507437825203,
0.0222481582313776,
0.02157861925661564,
-0.021727198734879494,
-0.03686048462986946,
-0.04100622236728668,
0.03878360986709595,
0.015427465550601482,
0.0330098532140255,
-0.12458878755569458,
0.010400964878499508,
-0.016671745106577873,
-0.03153951093554497,
0.012075179256498814,
0.09188077598810196,
-0.12752963602542877,
0.016514355316758156,
0.03642348200082779,
-0.00145761261228472,
-0.07026959955692291,
0.01598856784403324,
0.02083270438015461,
0.06336543709039688,
0.14810754358768463,
-0.0456928126513958,
0.03338267281651497,
-0.18599966168403625,
-0.006666637025773525,
-0.007186779286712408,
-0.06789931654930115,
0.014825698919594288,
-0.04096634313464165,
0.034037452191114426,
-0.053580835461616516,
0.07467909902334213,
0.014425180852413177,
-0.05833829939365387,
0.05163397639989853,
-0.06329326331615448,
-0.08193914592266083,
0.013889895752072334,
0.09317708760499954,
0.09207417815923691,
0.003600800409913063,
0.01281763520091772,
0.04060392081737518,
0.0005406652926467359,
0.04180917143821716,
0.06505191326141357,
0.13316841423511505,
0.04013576731085777,
0.06652476638555527,
0.08002574741840363,
-0.0454147532582283,
-0.07773582637310028,
0.06431487947702408,
-0.07211171835660934,
0.1152941882610321,
-0.05243420973420143,
0.10747818648815155,
0.12641653418540955,
-0.1522916853427887,
0.08691346645355225,
0.016046645119786263,
-0.02191869542002678,
-0.11353977024555206,
-0.1345362812280655,
-0.0763745978474617,
-0.07173309475183487,
0.006999035365879536,
-0.10537214577198029,
0.007419818080961704,
0.01992885395884514,
0.011421864852309227,
0.016313431784510612,
0.10470060259103775,
-0.11313645541667938,
-0.05642496421933174,
0.06706925481557846,
-0.028839990496635437,
-0.02210431732237339,
-0.04023250192403793,
-0.027443328872323036,
-0.0019675649236887693,
0.03460821881890297,
-0.018205100670456886,
0.013085833750665188,
0.02234838530421257,
0.041084177792072296,
-0.027230076491832733,
-0.09204494953155518,
0.008120565675199032,
0.01844634860754013,
-0.008076372556388378,
0.045847974717617035,
0.04846140369772911,
-0.041025545448064804,
-0.02553764171898365,
0.19033074378967285,
-0.021043287590146065,
-0.1233510971069336,
-0.11700393259525299,
0.14712044596672058,
0.03014901466667652,
0.054306209087371826,
-0.019820429384708405,
-0.058294836431741714,
0.007156180217862129,
0.16192321479320526,
0.2234269231557846,
-0.03127181902527809,
0.021179217845201492,
0.026293044909834862,
0.002702641300857067,
0.03221839666366577,
0.038198072463274,
0.04042976349592209,
0.13250048458576202,
-0.048326097428798676,
0.08311847597360611,
-0.026718372479081154,
-0.06862878799438477,
-0.019199637696146965,
0.09310309588909149,
0.0032551493495702744,
0.008139034733176231,
0.0055731963366270065,
0.07936061173677444,
-0.013173241168260574,
-0.09006708115339279,
0.012985155917704105,
-0.1281457245349884,
-0.12490355968475342,
-0.07438842207193375,
-0.0052215405739843845,
0.024547649547457695,
0.0942981019616127,
-0.006019662134349346,
-0.06648094207048416,
0.12957435846328735,
-0.028347643092274666,
-0.06516855210065842,
-0.12472101300954819,
0.020582599565386772,
-0.06526100635528564,
0.13417364656925201,
-0.02178007736802101,
0.005099967587739229,
0.09955117851495743,
0.0010477368487045169,
-0.11472882330417633,
0.024552054703235626,
0.022047627717256546,
-0.05317867919802666,
0.044338613748550415,
0.12486805766820908,
-0.025200145319104195,
0.13319028913974762,
0.024044450372457504,
-0.15045493841171265,
0.03820088878273964,
0.07434012740850449,
-0.06696309894323349,
-0.03572377189993858,
0.08128422498703003,
-0.036691442131996155,
0.095997154712677,
0.21153107285499573,
-0.026336612179875374,
0.020795587450265884,
-0.05118265002965927,
0.06435760110616684,
0.07754255831241608,
-0.0016972279408946633,
-0.06860635429620743,
-0.19291958212852478,
0.024098750203847885,
0.035486072301864624,
0.007689165882766247,
-0.17396271228790283,
-0.11718244850635529,
-0.016333645209670067,
-0.01976262964308262,
-0.05782073363661766,
0.10035135596990585,
0.11747130751609802,
0.018439892679452896,
-0.0036631084512919188,
-0.08605416119098663,
-0.003992888145148754,
0.09778624773025513,
-0.1249110996723175,
-0.10400845855474472
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_aio_model
This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "line-corporation/line-distilbert-base-japanese", "model-index": [{"name": "my_aio_model", "results": []}]} | multiple-choice | trtd56/practical_nlp_course_4 | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"multiple-choice",
"generated_from_trainer",
"base_model:line-corporation/line-distilbert-base-japanese",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:41:14+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #multiple-choice #generated_from_trainer #base_model-line-corporation/line-distilbert-base-japanese #license-apache-2.0 #endpoints_compatible #region-us
|
# my_aio_model
This model is a fine-tuned version of line-corporation/line-distilbert-base-japanese on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| [
"# my_aio_model\n\nThis model is a fine-tuned version of line-corporation/line-distilbert-base-japanese on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- training_steps: 500",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #distilbert #multiple-choice #generated_from_trainer #base_model-line-corporation/line-distilbert-base-japanese #license-apache-2.0 #endpoints_compatible #region-us \n",
"# my_aio_model\n\nThis model is a fine-tuned version of line-corporation/line-distilbert-base-japanese on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- training_steps: 500",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.1"
] | [
72,
40,
6,
12,
8,
3,
89,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #distilbert #multiple-choice #generated_from_trainer #base_model-line-corporation/line-distilbert-base-japanese #license-apache-2.0 #endpoints_compatible #region-us \n# my_aio_model\n\nThis model is a fine-tuned version of line-corporation/line-distilbert-base-japanese on the None dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- training_steps: 500### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.1"
] | [
-0.10887281596660614,
0.17516155540943146,
-0.0014288380043581128,
0.11293444782495499,
0.1407037228345871,
-0.0002234840503660962,
0.14152835309505463,
0.1481979340314865,
-0.08161043375730515,
0.05559602379798889,
0.03898683935403824,
0.028182901442050934,
0.05157214030623436,
0.1250828206539154,
-0.023645877838134766,
-0.2145644724369049,
0.010176862590014935,
-0.016002044081687927,
-0.04519921541213989,
0.10411261022090912,
0.10881384462118149,
-0.08659084141254425,
0.0689997747540474,
-0.005281277000904083,
-0.14215269684791565,
0.04366394877433777,
-0.028519054874777794,
-0.06027888506650925,
0.09682083129882812,
0.01676756702363491,
0.08724304288625717,
0.009691987186670303,
0.13467447459697723,
-0.2182246297597885,
-0.0027216640301048756,
0.0754493847489357,
0.03971760347485542,
0.07289446145296097,
0.027006538584828377,
-0.028974147513508797,
0.026095254346728325,
-0.1387150138616562,
0.09942453354597092,
0.02674253098666668,
-0.07575458288192749,
-0.14951281249523163,
-0.09159568697214127,
0.07971303164958954,
0.12480003386735916,
0.11721812188625336,
0.012839634902775288,
0.10969895124435425,
-0.06214708462357521,
0.06925851106643677,
0.19357718527317047,
-0.21307656168937683,
-0.046206437051296234,
0.05131695792078972,
0.05480257794260979,
0.09723299741744995,
-0.12732216715812683,
-0.02591848000884056,
0.0754883736371994,
0.0010281243594363332,
0.08256438374519348,
-0.030964910984039307,
-0.10308414697647095,
0.00014468107838183641,
-0.10264041274785995,
0.0036905426532030106,
0.2161218374967575,
0.049386754631996155,
-0.05751435458660126,
-0.09815844893455505,
-0.013066939078271389,
-0.10144618898630142,
-0.0263958889991045,
-0.014951418153941631,
0.05561850592494011,
-0.04466499388217926,
-0.0023931756149977446,
-0.06192572042346001,
-0.09635414183139801,
-0.08589424937963486,
0.021250886842608452,
0.10125445574522018,
0.039555393159389496,
-0.004788581281900406,
-0.034778133034706116,
0.10313516855239868,
-0.030264321714639664,
-0.12991487979888916,
-0.037935301661491394,
0.016902098432183266,
-0.07304506748914719,
-0.04092326760292053,
-0.022122986614704132,
-0.03777657076716423,
0.016089532524347305,
0.13362346589565277,
-0.04172511398792267,
0.05710615590214729,
-0.0011520222760736942,
0.008473547175526619,
-0.014972168020904064,
0.16376745700836182,
-0.038083698600530624,
-0.043856024742126465,
0.0072747161611914635,
0.10728197544813156,
0.02192244492471218,
-0.0065007018856704235,
-0.08952922374010086,
-0.014672636985778809,
0.07464376837015152,
0.091988705098629,
-0.03269202634692192,
0.027678027749061584,
-0.050424493849277496,
-0.014786304906010628,
0.030257824808359146,
-0.16649465262889862,
0.03942689672112465,
-0.02186274528503418,
-0.08712078630924225,
-0.04173232614994049,
0.02916448563337326,
0.00221617566421628,
-0.01778157614171505,
0.02088603563606739,
-0.06817833334207535,
-0.0042913928627967834,
-0.09338409453630447,
-0.05798529461026192,
0.019117649644613266,
-0.054730288684368134,
0.015678320080041885,
-0.0564311221241951,
-0.2321353703737259,
-0.07130838930606842,
0.028903856873512268,
-0.06189804896712303,
-0.03439395874738693,
-0.06161804124712944,
-0.05539068579673767,
-0.010552582331001759,
0.0003596611204557121,
0.09935934841632843,
-0.050092913210392,
0.07542259991168976,
0.011117922142148018,
0.01963295415043831,
0.045871201902627945,
0.04783580079674721,
-0.11145763099193573,
0.03413422778248787,
-0.12050244212150574,
0.07236308604478836,
-0.10773071646690369,
0.05482384189963341,
-0.1250990480184555,
-0.06317168474197388,
0.018117418512701988,
-0.010569892823696136,
0.026666678488254547,
0.14691531658172607,
-0.1801450550556183,
-0.01659328117966652,
0.13243618607521057,
-0.08609644323587418,
-0.07080823183059692,
0.07610918581485748,
-0.04698639735579491,
0.0860406756401062,
0.08228383213281631,
0.15922507643699646,
0.14068616926670074,
-0.12765055894851685,
-0.00216363905929029,
0.025994811207056046,
0.06820543855428696,
0.00549522927030921,
0.06835582107305527,
-0.0063240560702979565,
0.023064982146024704,
0.03564021736383438,
-0.11944261938333511,
-0.016557442024350166,
-0.05372855067253113,
-0.0807466208934784,
-0.03981849178671837,
-0.09497124701738358,
0.022407932206988335,
0.04083532467484474,
0.02964862622320652,
-0.06046156957745552,
-0.11153298616409302,
0.09803514182567596,
0.16000396013259888,
-0.06629939377307892,
-0.0009798109531402588,
-0.0703195184469223,
0.026148470118641853,
-0.04018017277121544,
-0.03515584021806717,
-0.1772647649049759,
-0.10291488468647003,
0.03255720064043999,
-0.07138632237911224,
0.036521270871162415,
0.01052808202803135,
0.05574832856655121,
0.05600669980049133,
-0.05582311376929283,
-0.04101017490029335,
-0.07410074770450592,
0.010835055261850357,
-0.07354926317930222,
-0.2002386599779129,
-0.033235274255275726,
-0.044454917311668396,
0.17010444402694702,
-0.23446929454803467,
0.041295621544122696,
-0.020333202555775642,
0.10217851400375366,
0.030753299593925476,
-0.03640677034854889,
0.0336509644985199,
0.032401785254478455,
-0.02027783915400505,
-0.11484625935554504,
0.014295881614089012,
0.0006623247754760087,
-0.08900648355484009,
-0.03182815760374069,
-0.12349632382392883,
0.07217911630868912,
0.07142359018325806,
0.10556845366954803,
-0.1029549390077591,
-0.021841371431946754,
-0.03527553007006645,
-0.047262296080589294,
-0.09703080356121063,
0.015130440704524517,
0.1586865484714508,
0.013170571066439152,
0.12413156777620316,
-0.0685042291879654,
-0.0582415871322155,
-0.005022861063480377,
-0.024417025968432426,
-0.022610291838645935,
0.08828265219926834,
0.04317173734307289,
-0.11083704233169556,
0.11676007509231567,
0.06314381211996078,
-0.04760880395770073,
0.1473282277584076,
-0.0612071268260479,
-0.08993489295244217,
-0.027297399938106537,
0.04669389873743057,
-0.0073503246530890465,
0.1446271687746048,
-0.08885521441698074,
-0.01195977907627821,
0.018689556047320366,
-0.0074369520880281925,
0.019537124782800674,
-0.17781734466552734,
-0.029785776510834694,
0.033500853925943375,
-0.04874115064740181,
0.007737867999821901,
-0.052833739668130875,
0.0015103680780157447,
0.08183377981185913,
-0.0015292972093448043,
-0.024384208023548126,
0.017888333648443222,
-0.006075224839150906,
-0.07885608077049255,
0.1900930255651474,
-0.10726309567689896,
-0.19009533524513245,
-0.13994358479976654,
0.023326139897108078,
-0.03331463038921356,
-0.01838678866624832,
0.008303442038595676,
-0.0956803485751152,
-0.04960238188505173,
-0.10433051735162735,
-0.012915018014609814,
-0.02331566996872425,
-0.03903232514858246,
0.02290489338338375,
0.047614842653274536,
0.08297055214643478,
-0.13291172683238983,
0.024014048278331757,
0.015971172600984573,
-0.09276121109724045,
-0.030642274767160416,
0.023235782980918884,
0.12071901559829712,
0.12644265592098236,
-0.0016432219417765737,
0.00012759410310536623,
-0.03120945394039154,
0.1506962925195694,
-0.10084524005651474,
0.013617887161672115,
0.1274360716342926,
0.015999209135770798,
0.033232517540454865,
0.14198802411556244,
0.026926441118121147,
-0.0951438844203949,
0.031772613525390625,
0.06180277839303017,
-0.011093150824308395,
-0.25536981225013733,
-0.013718505389988422,
-0.02915911376476288,
-0.057663172483444214,
0.08090303093194962,
0.0728786513209343,
0.05587223917245865,
0.043569207191467285,
-0.0014808138366788626,
0.05448150634765625,
0.01574922911822796,
0.0807684063911438,
0.05742236226797104,
0.013907189480960369,
0.08005541563034058,
-0.04092390090227127,
-0.009497581981122494,
0.06334859877824783,
0.061484385281801224,
0.25637906789779663,
-0.029681773856282234,
0.15836837887763977,
0.04224211722612381,
0.15230827033519745,
-0.025662075728178024,
0.018952425569295883,
0.029917025938630104,
0.008423011749982834,
0.007265047635883093,
-0.05698762834072113,
-0.008821509778499603,
0.04289398714900017,
-0.061205800622701645,
0.060271963477134705,
-0.08180242031812668,
0.017908604815602303,
0.013463698327541351,
0.24077793955802917,
0.030748896300792694,
-0.2816373407840729,
-0.07579950243234634,
0.031194135546684265,
-0.034142062067985535,
-0.06433020532131195,
0.016861438751220703,
0.12053634226322174,
-0.12151923030614853,
0.05784498155117035,
-0.042143408209085464,
0.08740228414535522,
-0.06439052522182465,
-0.015547007322311401,
0.04244396835565567,
0.08354032784700394,
-0.013547639362514019,
0.11071570962667465,
-0.23351609706878662,
0.22104871273040771,
0.02004748210310936,
0.1181592270731926,
-0.04516010358929634,
0.038857366889715195,
0.010856284759938717,
0.12274102866649628,
0.1446632593870163,
-0.02648414485156536,
-0.00999903678894043,
-0.17794077098369598,
-0.08882208168506622,
0.02269016206264496,
0.0729534924030304,
-0.04875187203288078,
0.07729022949934006,
-0.04952450841665268,
-0.009869277477264404,
0.0427762046456337,
-0.11306573450565338,
-0.15753331780433655,
-0.1478671431541443,
0.014628247357904911,
-0.008804971352219582,
-0.01839648187160492,
-0.09453535079956055,
-0.0934453159570694,
0.01741156540811062,
0.17274104058742523,
-0.002719472162425518,
-0.05858779698610306,
-0.15165045857429504,
0.07636483013629913,
0.1293923705816269,
-0.06623931229114532,
0.0008887066505849361,
0.026034237816929817,
0.14730626344680786,
0.04807429388165474,
-0.05315004289150238,
0.03080935962498188,
-0.06367861479520798,
-0.14903134107589722,
-0.055142611265182495,
0.12070387601852417,
0.04375486820936203,
0.04370792955160141,
-0.0032836715690791607,
-0.0011947196908295155,
0.028584027662873268,
-0.08203034847974777,
-0.01277580764144659,
0.1041344404220581,
0.07436642795801163,
0.05174920707941055,
-0.1041528582572937,
-0.02329224906861782,
-0.07084278017282486,
-0.048801835626363754,
0.08621850609779358,
0.1947391778230667,
-0.07421969622373581,
0.08977678418159485,
0.08587384968996048,
-0.11530288308858871,
-0.15253524482250214,
0.06988591700792313,
0.06385968625545502,
0.042739387601614,
0.05753248929977417,
-0.17111989855766296,
0.08920815587043762,
0.11498134583234787,
-0.03469271957874298,
0.04370561242103577,
-0.3396425247192383,
-0.12453585863113403,
0.07467352598905563,
0.11544638872146606,
-0.04006746783852577,
-0.14188700914382935,
-0.04744269698858261,
-0.030628550797700882,
-0.1104472428560257,
0.05942559242248535,
-0.0664040744304657,
0.10105086863040924,
0.003450619988143444,
0.06461456418037415,
0.02762385457754135,
-0.023598562926054,
0.15359270572662354,
0.020347755402326584,
0.09945946931838989,
-0.0525018572807312,
-0.011267672292888165,
0.10051870346069336,
-0.07182244956493378,
0.0899762511253357,
-0.05779768526554108,
0.06367195397615433,
-0.12997464835643768,
-0.042143359780311584,
-0.05200366675853729,
0.05992548540234566,
-0.06242724135518074,
-0.05614227429032326,
-0.0522463321685791,
0.0794040784239769,
0.033414870500564575,
-0.031433865427970886,
0.07810543477535248,
0.014346696436405182,
0.07910511642694473,
0.08445750176906586,
0.0967220589518547,
0.03409717604517937,
-0.11503011733293533,
-0.018319470807909966,
-0.01884622871875763,
0.0557887926697731,
-0.17354367673397064,
0.03399018198251724,
0.09850646555423737,
0.04670935869216919,
0.16198790073394775,
0.005073894746601582,
-0.05941163748502731,
0.002356885001063347,
0.03743786737322807,
-0.05891501158475876,
-0.15349553525447845,
-0.009862995706498623,
-0.03602591156959534,
-0.12476760149002075,
0.02053964138031006,
0.09963509440422058,
-0.0913989320397377,
-0.02253943681716919,
-0.02249990776181221,
0.044258058071136475,
-0.025566838681697845,
0.17777284979820251,
0.055510684847831726,
0.06369175016880035,
-0.07950195670127869,
0.1372295469045639,
0.10521955788135529,
-0.05019916966557503,
0.04728303477168083,
0.049047619104385376,
-0.06721817702054977,
-0.042152997106313705,
0.09797016531229019,
0.19062387943267822,
-0.01813846454024315,
-0.06735814362764359,
-0.12133518606424332,
-0.07232807576656342,
0.026587985455989838,
0.09443682432174683,
0.04523933678865433,
0.0018906067125499249,
-0.010894069448113441,
0.004795398097485304,
-0.14737945795059204,
0.10343571752309799,
0.050065990537405014,
0.061234649270772934,
-0.1681515872478485,
0.07364477962255478,
0.03828391805291176,
0.028635499998927116,
-0.012276194989681244,
0.01602129638195038,
-0.07983576506376266,
-0.007470514625310898,
-0.12204094231128693,
0.01805858127772808,
-0.012443209066987038,
0.017432428896427155,
-0.014193329960107803,
-0.064883291721344,
-0.03387579694390297,
0.05871066078543663,
-0.06005985662341118,
-0.05799376964569092,
0.008302937261760235,
0.07792334258556366,
-0.141193225979805,
-0.014357640407979488,
0.03540066257119179,
-0.08238963782787323,
0.04562748596072197,
0.02028544247150421,
0.021138330921530724,
0.025985483080148697,
-0.10175413638353348,
0.026052553206682205,
0.029825322329998016,
0.031140156090259552,
0.04931369051337242,
-0.10934043675661087,
-0.008807599544525146,
-0.01477863173931837,
0.030838072299957275,
0.008442998863756657,
0.017788998782634735,
-0.1236516609787941,
-0.03876178711652756,
-0.07304471731185913,
-0.05204034596681595,
-0.0630687028169632,
0.06864117830991745,
0.13661973178386688,
0.01611430197954178,
0.15476737916469574,
-0.06793627142906189,
0.05483030155301094,
-0.1929241120815277,
-0.03832673281431198,
-0.006248620804399252,
-0.03140682354569435,
-0.08555664867162704,
-0.040226176381111145,
0.06791919469833374,
-0.04831491783261299,
0.11565160751342773,
0.018762478604912758,
0.10972796380519867,
0.03319428116083145,
-0.055312249809503555,
0.01862446218729019,
0.028897522017359734,
0.16356290876865387,
0.03591609001159668,
0.0016135836485773325,
0.09556075930595398,
-0.018155718222260475,
0.05599108338356018,
0.018674306571483612,
0.11470749229192734,
0.17073990404605865,
-0.02041642740368843,
0.06037740781903267,
0.06380410492420197,
-0.11082661151885986,
-0.14349250495433807,
0.10355037450790405,
-0.03227490186691284,
0.08939790725708008,
-0.037189628928899765,
0.16539037227630615,
0.12096888571977615,
-0.17204149067401886,
0.06858555972576141,
-0.048266906291246414,
-0.11890743672847748,
-0.09237950295209885,
-0.0775659903883934,
-0.0869545042514801,
-0.1159202829003334,
0.010932540521025658,
-0.11888664960861206,
0.025830993428826332,
0.0812191516160965,
0.0044193877838552,
-0.0010277137625962496,
0.15235552191734314,
-0.00789755117148161,
0.000025341561922687106,
0.0642007514834404,
0.011185893788933754,
-0.004286400508135557,
-0.09559660404920578,
-0.028632566332817078,
0.051531098783016205,
0.005982246249914169,
0.049213528633117676,
-0.03714008629322052,
0.03036743402481079,
0.03954566642642021,
-0.0213729590177536,
-0.06836502999067307,
0.03280433639883995,
0.007146311923861504,
0.048575859516859055,
0.03640119731426239,
0.0625828430056572,
-0.00833962019532919,
-0.0171097069978714,
0.32923561334609985,
-0.0581214614212513,
-0.07531312853097916,
-0.14146485924720764,
0.16268503665924072,
0.016425028443336487,
-0.025930702686309814,
0.054227136075496674,
-0.13015243411064148,
0.012766835279762745,
0.1830914467573166,
0.11816632002592087,
-0.032733380794525146,
-0.02070743590593338,
-0.03379346430301666,
-0.018649181351065636,
-0.06885483860969543,
0.10202697664499283,
0.08634649962186813,
0.015343032777309418,
-0.054880812764167786,
-0.004426772240549326,
0.0020002061501145363,
-0.04805232957005501,
-0.0794120728969574,
0.10492458939552307,
-0.008226598612964153,
0.013738286681473255,
-0.043844953179359436,
0.09683232754468918,
0.024361833930015564,
-0.22350385785102844,
0.0621759332716465,
-0.14832504093647003,
-0.19518506526947021,
-0.03798827528953552,
0.11135696619749069,
-0.00903337448835373,
0.027928518131375313,
-0.0059534721076488495,
0.02012413740158081,
0.13883893191814423,
-0.0092693492770195,
-0.06225159764289856,
-0.1255604326725006,
0.07367222011089325,
-0.057563863694667816,
0.24048496782779694,
-0.0008102008723653853,
0.028781890869140625,
0.09375134855508804,
-0.014439485967159271,
-0.1481774002313614,
0.06244857981801033,
0.058699242770671844,
-0.022407235577702522,
0.0609477199614048,
0.14760686457157135,
-0.03982030227780342,
0.11833036690950394,
0.041775334626436234,
-0.10219614952802658,
0.004143558442592621,
-0.043395355343818665,
-0.02889985591173172,
-0.10699985176324844,
0.005710158962756395,
-0.07353122532367706,
0.1505574882030487,
0.18464180827140808,
-0.04487982019782066,
0.007229583337903023,
-0.06436774134635925,
0.06482509523630142,
0.061786096543073654,
0.08910351246595383,
-0.0018990195821970701,
-0.18389594554901123,
0.005892988760024309,
0.01287813950330019,
0.025390906259417534,
-0.2253294289112091,
-0.08679412305355072,
0.0492333360016346,
-0.07183410227298737,
-0.05747351050376892,
0.09867843240499496,
0.0944351851940155,
0.04401342570781708,
-0.04020841419696808,
-0.16373030841350555,
-0.027644082903862,
0.1349814236164093,
-0.14613096415996552,
-0.04509083181619644
] |
null | null | null | example output
写一个python程序抓取youtube最流行的内容：从网页获取数据，
以下是一个python脚本，可以从Youtube上抓取最受欢迎的视频并将其保存到本地文件中。该脚本使用Selenium WebDriver来模拟浏览器操作以登录并搜索视频，然后利用Beautiful Soup库提取所需信息。如果您需要任何帮助或修改建议，请随时告诉我！
```
from selenium import webdriver
from bs4 import BeautifulSoup as BS
import os
# 设置ChromeDriver路径
CHROMEDRIVER_PATH = './chromedriver.exe' # 更换为实际路径
def main():
# 启动Chrome浏览器并登录Youtube
browser = webdriver.Chrome(executable_path=CHROMEDRIVER_PATH)
browser.get('https://www.youtube.com/')
login_url = 'https://accounts.google.com/signin'
browser.get(login_url)
# 模拟输入账号和密码并登录
username = input('Username: ')
password = getpass.getpass() # 防止密码显示在终端上
submit_button = browser.find_element_by_class_name('whsLW', timeout=5)
submit_button.click()
# 在搜索栏中输入关键词并查找结果
search_query = 'most popular youtube videos today'
search_box = browser.find_element_by_id('search_query')
search_box.send_keys(search_query)
enter_key = browser.find_element_by_class_name('ytp-suggest-renderer__input-icon')
enter_key.click()
results = BS(browser.page_source, 'html.parser')
# 从搜索结果中提取出最受欢迎的视频链接并保存到本地文件
videos = results.find('ol', {'class': 'r'})
video_urls = [a['href'] for a in videos.find_all('a')]
saved_path = 'popular_videos/' + os.getcwd().split('/')[-2] + '_' + str(int(time.time())) + '/'
if not os.path.exists(saved_path):
os.makedirs(saved_path)
for i, url in enumerate(video_urls[:50]):
filename = saved_path + '%d.mp4' % (i+1)
urllib.request.urlretrieve(url, filename)
print('Downloaded top 50 videos to:', saved_path)
except Exception as e:
print(e)
``` | {} | null | cloudyu/60B_MoE_Coder_v3_gguf | [
"gguf",
"region:us"
] | 2024-02-09T01:41:35+00:00 | [] | [] | TAGS
#gguf #region-us
| example output
写一个python程序抓取youtube最流行的内容：从网页获取数据，
以下是一个python脚本，可以从Youtube上抓取最受欢迎的视频并将其保存到本地文件中。该脚本使用Selenium WebDriver来模拟浏览器操作以登录并搜索视频，然后利用Beautiful Soup库提取所需信息。如果您需要任何帮助或修改建议，请随时告诉我！
| [] | [
"TAGS\n#gguf #region-us \n"
] | [
9
] | [
"passage: TAGS\n#gguf #region-us \n"
] | [
0.030724648386240005,
0.026499787345528603,
-0.010017825290560722,
-0.05703527107834816,
0.08247160166501999,
0.07200847566127777,
0.01814177818596363,
0.020192064344882965,
0.2235025018453598,
0.017216520383954048,
0.1496623009443283,
-0.031233953312039375,
0.006174509879201651,
0.05538657680153847,
0.039407629519701004,
-0.19438467919826508,
0.058440499007701874,
-0.02356063388288021,
-0.020945189520716667,
0.01803453452885151,
-0.05310691148042679,
-0.04108472168445587,
0.022135348990559578,
-0.07881014049053192,
-0.15867982804775238,
0.0678698718547821,
0.017852067947387695,
0.0007025183876976371,
0.0820731669664383,
0.05882885307073593,
0.09657382220029831,
-0.024203501641750336,
-0.15220364928245544,
-0.18796531856060028,
0.0366438589990139,
-0.02974788099527359,
-0.10282598435878754,
0.022019000723958015,
0.029453158378601074,
-0.06967076659202576,
0.02238346077501774,
0.1427535116672516,
-0.10206039994955063,
0.051592033356428146,
-0.27165159583091736,
-0.1715938150882721,
-0.06585682183504105,
-0.025845954194664955,
-0.007345964200794697,
0.01241085771471262,
-0.0010092189768329263,
0.047266922891139984,
-0.20188692212104797,
-0.005631127394735813,
0.09329266101121902,
-0.25229454040527344,
0.02776304818689823,
0.21345718204975128,
-0.010520953685045242,
0.09873088449239731,
-0.05590669438242912,
0.14438565075397491,
0.03173782303929329,
-0.019559340551495552,
-0.1924813836812973,
-0.070224329829216,
-0.07177317887544632,
0.162109375,
-0.0823177620768547,
-0.11764442175626755,
0.24176421761512756,
0.009283576160669327,
-0.026472626253962517,
0.15598991513252258,
-0.029037300497293472,
-0.009749599732458591,
0.04555726423859596,
0.01668328419327736,
-0.010545015335083008,
0.1551385223865509,
0.17108163237571716,
-0.08598228543996811,
-0.10847756266593933,
-0.030579885467886925,
-0.2373785674571991,
0.2470305860042572,
-0.01911027915775776,
0.12945520877838135,
-0.20086053013801575,
0.018443629145622253,
-0.3247532844543457,
-0.0012029389617964625,
-0.010316703468561172,
-0.028618358075618744,
-0.006935348734259605,
0.009301352314651012,
-0.050316113978624344,
0.0739501491189003,
0.14580395817756653,
0.1393439620733261,
-0.11465669423341751,
0.060509420931339264,
-0.052172139286994934,
0.14876529574394226,
0.05827285721898079,
0.061183393001556396,
0.04079163819551468,
0.07037676870822906,
-0.008353544399142265,
-0.21633195877075195,
-0.029873060062527657,
-0.07057386636734009,
-0.08445251733064651,
-0.0130265261977911,
-0.13896764814853668,
0.11386743932962418,
-0.022273007780313492,
-0.07913482189178467,
-0.06810981780290604,
0.07626928389072418,
0.017650218680500984,
-0.008536403998732567,
-0.035703565925359726,
-0.012481719255447388,
0.022218508645892143,
-0.014872739091515541,
-0.1519843488931656,
0.02295425534248352,
0.10455024242401123,
0.07257117331027985,
-0.1489023119211197,
-0.011344035156071186,
-0.017298875376582146,
0.06959983706474304,
0.03884255141019821,
-0.10402916371822357,
0.04283881187438965,
-0.10747409611940384,
-0.08414466679096222,
0.022628657519817352,
-0.005062851123511791,
-0.0418001152575016,
0.13524691760540009,
0.03997812792658806,
0.040150050073862076,
-0.016940169036388397,
-0.04259050637483597,
-0.048133596777915955,
-0.07602019608020782,
0.07334327697753906,
0.05418020859360695,
0.027240034192800522,
-0.1915341019630432,
0.01154522504657507,
-0.048245880752801895,
0.09175369143486023,
-0.11856856942176819,
0.014575321227312088,
-0.08105122298002243,
0.1604209989309311,
0.0349995456635952,
0.09055875241756439,
-0.19562625885009766,
0.02605881541967392,
-0.06191767752170563,
0.1854621320962906,
-0.04451294615864754,
-0.11786319315433502,
0.2698904871940613,
-0.09105797111988068,
-0.040079716593027115,
0.056803084909915924,
0.06560484319925308,
-0.06272535026073456,
0.068723164498806,
0.4434472322463989,
-0.06556011736392975,
-0.07118581980466843,
0.05080527812242508,
0.17805561423301697,
-0.1262815296649933,
-0.09372174739837646,
0.09990617632865906,
-0.1480535864830017,
-0.211008220911026,
0.030864350497722626,
0.028955968096852303,
0.1494358479976654,
-0.06205282360315323,
-0.012456154450774193,
0.058214303106069565,
-0.013022401370108128,
0.046677324920892715,
0.03563477098941803,
0.11109840869903564,
-0.06493768095970154,
0.06851828098297119,
-0.16232267022132874,
0.016065504401922226,
0.1209988072514534,
-0.015012580901384354,
-0.04126624017953873,
0.14286154508590698,
-0.03809087723493576,
0.07199656218290329,
-0.07730832695960999,
-0.1804673671722412,
0.027612121775746346,
0.05621999502182007,
0.028122514486312866,
0.09176547825336456,
0.09526687115430832,
-0.039257392287254333,
0.0013902259524911642,
0.0329861082136631,
0.061223939061164856,
-0.007701692637056112,
0.015235940925776958,
-0.015374142676591873,
0.12888981401920319,
-0.07010363042354584,
-0.04155188798904419,
-0.09715848416090012,
-0.00889967754483223,
0.2288777232170105,
-0.01933911070227623,
0.02257734164595604,
-0.06854789704084396,
0.033186767250299454,
-0.0012386917369440198,
0.09506335854530334,
-0.017756229266524315,
0.06063338369131088,
-0.022011179476976395,
-0.06201287358999252,
0.11652727425098419,
-0.043086208403110504,
0.24556174874305725,
0.10792262107133865,
-0.07513239979743958,
-0.01741042546927929,
-0.0871582105755806,
-0.007020947523415089,
0.022898653522133827,
0.08814648538827896,
-0.04863424599170685,
0.06471672654151917,
-0.037898752838373184,
-0.0013588295551016927,
0.018808960914611816,
-0.008487841114401817,
-0.030526969581842422,
-0.04284367710351944,
-0.08270563185214996,
0.09057542681694031,
0.0691855251789093,
-0.13670015335083008,
0.17748047411441803,
0.2472171038389206,
0.1500423550605774,
0.2487964630126953,
-0.06485911458730698,
-0.014139159582555294,
-0.02016172744333744,
0.03673918917775154,
-0.020436765626072884,
0.13109654188156128,
-0.18929845094680786,
-0.032152432948350906,
0.02558354288339615,
0.029807843267917633,
0.10872193425893784,
-0.1365325003862381,
-0.1145850270986557,
-0.0379912331700325,
-0.047677598893642426,
-0.08257206529378891,
0.07034620642662048,
-0.12104500830173492,
0.03338077291846275,
0.07256745547056198,
0.0073080710135400295,
0.12201625853776932,
0.015417544171214104,
-0.055278971791267395,
0.0998256728053093,
-0.14543165266513824,
-0.2384990155696869,
-0.04642500355839729,
-0.10990478098392487,
0.001206184271723032,
0.05318264663219452,
0.016633260995149612,
-0.21265560388565063,
-0.01741623878479004,
0.11141498386859894,
0.06650645285844803,
-0.18111048638820648,
0.024138791486620903,
0.029385030269622803,
-0.004455238115042448,
-0.10212790220975876,
-0.012687300331890583,
-0.05387670546770096,
-0.11039627343416214,
-0.0691843032836914,
0.08163908869028091,
-0.06936442852020264,
0.11164893209934235,
0.1582336574792862,
0.11141853034496307,
0.11249161511659622,
-0.011774544604122639,
0.1976311057806015,
-0.14119699597358704,
-0.14489109814167023,
0.06405922025442123,
-0.014498869888484478,
0.03640124574303627,
0.08232609927654266,
0.04930112138390541,
-0.14269955456256866,
-0.04848511889576912,
-0.007545206230133772,
-0.1497725397348404,
-0.1323675513267517,
-0.05164776369929314,
-0.10658133774995804,
0.12379065901041031,
-0.06248227879405022,
0.10150982439517975,
0.11162466555833817,
0.017522823065519333,
0.11151766777038574,
-0.06246228888630867,
-0.054680291563272476,
-0.04807431995868683,
0.06297076493501663,
-0.05410824716091156,
-0.04205694422125816,
-0.06721562892198563,
-0.008002115413546562,
0.1349310278892517,
0.10885956883430481,
0.07581131905317307,
0.2265089601278305,
0.02780294418334961,
0.05355561524629593,
0.040789585560560226,
0.16015571355819702,
0.015284501947462559,
-0.0046128155663609505,
-0.08788388222455978,
-0.014365277253091335,
-0.0019687749445438385,
-0.031080376356840134,
-0.006052241660654545,
0.1340780407190323,
-0.2559821307659149,
0.03235609456896782,
-0.2989844083786011,
0.11946471780538559,
-0.1565471589565277,
0.07426489144563675,
0.05220162868499756,
0.030080994591116905,
0.08841689676046371,
0.035069406032562256,
-0.02871096506714821,
0.09149409085512161,
0.11694692075252533,
-0.12628670036792755,
0.01540512777864933,
0.04918349161744118,
0.052707213908433914,
-0.0142430504783988,
0.0931062400341034,
-0.11024625599384308,
-0.0737583339214325,
-0.0024255106691271067,
0.07025767862796783,
-0.2099330574274063,
0.23986183106899261,
0.03523903712630272,
-0.10871971398591995,
-0.021638909354805946,
-0.0547538623213768,
0.03316742554306984,
0.08983159810304642,
0.1342458724975586,
0.11251148581504822,
-0.11371640861034393,
-0.12470904737710953,
0.029020745307207108,
0.03679748624563217,
0.1757190227508545,
-0.09047917276620865,
-0.14164063334465027,
0.001811441034078598,
0.05263577029109001,
-0.053646381944417953,
0.07645093649625778,
-0.05327983945608139,
-0.0941789522767067,
0.03495060279965401,
0.04520740360021591,
0.00641082925722003,
-0.019971303641796112,
0.08110581338405609,
-0.02520396187901497,
0.085345059633255,
-0.04878882318735123,
0.00847524031996727,
-0.10202991217374802,
-0.03634759038686752,
0.04376819357275963,
-0.0722225159406662,
0.01614394783973694,
-0.09818518906831741,
-0.15651735663414001,
-0.08556577563285828,
-0.15303048491477966,
0.12497064471244812,
-0.052672382444143295,
0.10244213044643402,
-0.047614291310310364,
0.147609144449234,
-0.013274060562252998,
0.030878636986017227,
-0.05167607590556145,
0.028036773204803467,
0.011671020649373531,
-0.14858771860599518,
0.20959575474262238,
-0.1476162225008011,
-0.023819662630558014,
0.16589532792568207,
0.05426561459898949,
0.1161220371723175,
0.04555299133062363,
-0.0879630371928215,
0.23518426716327667,
0.2702784240245819,
-0.0007818902959115803,
0.17838320136070251,
0.2352202981710434,
-0.026693791151046753,
-0.2436053603887558,
-0.07260585576295853,
-0.2063993662595749,
-0.039628319442272186,
0.0004186074365861714,
-0.282958060503006,
0.06042884290218353,
0.17210599780082703,
-0.07570867985486984,
0.4319494664669037,
-0.22352926433086395,
0.03153151646256447,
0.13982820510864258,
-0.04242865741252899,
0.6181237101554871,
-0.1820172369480133,
-0.16550765931606293,
0.052592549473047256,
-0.1248052790760994,
0.11609237641096115,
-0.005267696920782328,
0.10048385709524155,
-0.00011838242062367499,
-0.02595684304833412,
0.03428659215569496,
-0.0409976989030838,
0.23620888590812683,
0.018790103495121002,
0.045043930411338806,
-0.09004033356904984,
-0.1538960188627243,
0.10746775567531586,
0.02556895837187767,
-0.10341835021972656,
0.03920651972293854,
-0.06092366203665733,
-0.10915451496839523,
0.011575369164347649,
-0.08317004889249802,
0.03433287888765335,
0.09550272673368454,
-0.050003789365291595,
-0.0652989074587822,
0.024777809157967567,
-0.16975140571594238,
0.028226720169186592,
0.1660151481628418,
-0.08661750704050064,
0.17001861333847046,
-0.04084239527583122,
-0.0947834923863411,
-0.15362800657749176,
-0.020637191832065582,
-0.07918675988912582,
-0.01597081869840622,
0.10419487953186035,
-0.11003783345222473,
0.006433290895074606,
0.09035904705524445,
0.002910176757723093,
0.07882846146821976,
0.09883374720811844,
-0.08716033399105072,
0.05550702288746834,
0.1730797290802002,
-0.21496161818504333,
-0.1694899946451187,
-0.04902869462966919,
-0.1887752115726471,
0.2065081000328064,
0.03903897479176521,
0.04895683750510216,
0.16432031989097595,
0.015995748341083527,
-0.010867753997445107,
-0.020683420822024345,
-0.11664224416017532,
0.00450828718021512,
0.04868127405643463,
-0.005741522181779146,
-0.11094820499420166,
0.13042977452278137,
0.05625306814908981,
-0.010265284217894077,
-0.04014173522591591,
0.1808832287788391,
-0.06324239075183868,
-0.06105973571538925,
-0.29144585132598877,
0.07338178157806396,
-0.10203809291124344,
-0.033191971480846405,
0.08307401835918427,
-0.024927617982029915,
-0.0012370682088658214,
0.14441034197807312,
0.009444275870919228,
0.1295502781867981,
0.031338974833488464,
0.03218937665224075,
0.14084547758102417,
-0.13805074989795685,
-0.14429166913032532,
-0.029582731425762177,
-0.08434601873159409,
-0.12847381830215454,
-0.016780147328972816,
0.1751313954591751,
-0.08363176882266998,
-0.12467111647129059,
-0.2756369411945343,
0.049299292266368866,
-0.0641724020242691,
-0.1138453483581543,
-0.03101496584713459,
-0.06544762849807739,
0.052310146391391754,
-0.040101904422044754,
0.014005003497004509,
-0.023109296336770058,
-0.14451682567596436,
0.0458921417593956,
0.06695213168859482,
0.03172319754958153,
-0.02931683138012886,
0.0015236766776069999,
0.15014788508415222,
0.026510147377848625,
0.16621503233909607,
0.22043149173259735,
0.061838917434215546,
0.20056213438510895,
-0.2713247239589691,
-0.10004157572984695,
0.10868333280086517,
-0.07527677714824677,
0.021882841363549232,
0.13841275870800018,
-0.01911449432373047,
-0.0495067797601223,
-0.03201347589492798,
0.08917038887739182,
-0.017281996086239815,
-0.08984966576099396,
-0.04857974499464035,
-0.003589637577533722,
-0.18503929674625397,
-0.0007536212215200067,
-0.15319249033927917,
0.1420021951198578,
0.04460230842232704,
-0.062356118112802505,
0.07465137541294098,
0.05997058004140854,
0.03977793827652931,
0.006764960940927267,
0.018739836290478706,
-0.14650356769561768,
0.01704270951449871,
-0.025170978158712387,
-0.006106532644480467,
0.03402095288038254,
0.34655115008354187,
-0.0466112419962883,
-0.07675225287675858,
-0.019784720614552498,
0.1001124382019043,
0.13863220810890198,
-0.009452453814446926,
0.13600659370422363,
0.13898764550685883,
-0.07470680773258209,
-0.12456237524747849,
0.10025309771299362,
-0.04034053534269333,
-0.15969179570674896,
0.12802298367023468,
-0.0435095950961113,
-0.016280202195048332,
0.04011611267924309,
-0.03383811563253403,
-0.08241409808397293,
0.04869242012500763,
-0.08193223923444748,
-0.03468599542975426,
-0.03921830281615257,
-0.019609715789556503,
-0.02835456281900406,
0.179523304104805,
-0.03646359592676163,
0.07318142801523209,
-0.02748848870396614,
0.010194642469286919,
-0.10395175963640213,
-0.1028568297624588,
0.05173351243138313,
-0.12340104579925537,
0.07964924722909927,
-0.03694985434412956,
0.030445387586951256,
0.22815105319023132,
0.02754553034901619,
0.015633730217814445,
0.13255921006202698,
-0.00819331593811512,
-0.0877854973077774,
0.03996758162975311,
-0.044342756271362305,
0.021794743835926056,
-0.030855976045131683,
-0.07628626376390457,
-0.0880078375339508,
-0.10075201094150543,
-0.049825526773929596,
0.03320961445569992,
-0.030442843213677406,
-0.05212388187646866,
-0.14976045489311218,
-0.02720625326037407,
-0.07237301766872406,
0.11920249462127686,
-0.09342960268259048,
0.08832328021526337,
-0.012045936658978462,
0.0026839354541152716,
0.037163145840168,
0.1505078673362732,
0.010094218887388706,
0.10494716465473175,
0.006677085533738136,
0.09218452870845795,
-0.06759306788444519,
0.14643312990665436,
-0.12665413320064545,
-0.02135086990892887,
-0.03415476530790329,
0.2331210970878601,
0.20847657322883606,
-0.11358945816755295,
0.009311644360423088,
0.03202449902892113,
0.04839635267853737,
0.185939759016037,
0.12599588930606842,
0.01761433109641075,
0.33329761028289795,
-0.059357043355703354,
-0.02227349951863289,
0.05721667781472206,
-0.00022221643303055316,
-0.06214975565671921,
0.0716261938214302,
0.08921460807323456,
0.013963594101369381,
-0.1257423460483551,
0.11072274297475815,
-0.21343208849430084,
0.15216094255447388,
0.07192383706569672,
-0.18375952541828156,
-0.009178245440125465,
-0.05186039209365845,
0.008210902102291584,
-0.027973614633083344,
0.13407447934150696,
-0.07003656774759293,
-0.1739543378353119,
-0.19977876543998718,
0.060681428760290146,
-0.35512542724609375,
-0.20812080800533295,
0.06384200602769852,
0.1383514702320099,
0.10808566957712173,
-0.06061858683824539,
-0.013316533528268337,
0.006446295417845249,
0.01029437780380249,
-0.019556531682610512,
0.028526417911052704,
-0.008326482027769089,
-0.05453765019774437,
-0.25444141030311584,
-0.006056090816855431,
0.0625600665807724,
-0.15240277349948883,
0.05618175491690636,
-0.017780732363462448,
-0.008800189942121506,
0.13029517233371735,
-0.021711476147174835,
0.03442413732409477,
0.00029493181500583887,
-0.16273388266563416,
0.031801287084817886,
0.035038504749536514,
0.03614772483706474,
-0.010639974847435951,
-0.04227915778756142,
-0.002239778870716691,
0.07848605513572693,
-0.054354216903448105,
-0.1438787877559662,
0.11021588742733002,
-0.026462025940418243,
0.21526864171028137,
-0.06517954170703888,
-0.033111389726400375,
0.023098714649677277,
-0.07031320035457611,
0.2018292248249054,
-0.03690796345472336,
0.05650625377893448,
0.1586160659790039,
0.018734993413090706,
0.019857894629240036,
-0.30062609910964966,
0.08813683688640594,
-0.024517416954040527,
0.006894893944263458,
-0.05270370468497276
] |
null | null | diffusers |
# DreamBooth trained by AutoTrain
Text encoder was not trained.
| {"tags": ["text-to-image", "diffusers", "autotrain"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "Lil B Flame Type Album", "inference": true} | text-to-image | Uggh/LilBFlameAlbumCovers | [
"diffusers",
"text-to-image",
"autotrain",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"has_space",
"region:us"
] | 2024-02-09T01:43:00+00:00 | [] | [] | TAGS
#diffusers #text-to-image #autotrain #base_model-stabilityai/stable-diffusion-xl-base-1.0 #has_space #region-us
|
# DreamBooth trained by AutoTrain
Text encoder was not trained.
| [
"# DreamBooth trained by AutoTrain\n\nText encoder was not trained."
] | [
"TAGS\n#diffusers #text-to-image #autotrain #base_model-stabilityai/stable-diffusion-xl-base-1.0 #has_space #region-us \n",
"# DreamBooth trained by AutoTrain\n\nText encoder was not trained."
] | [
45,
19
] | [
"passage: TAGS\n#diffusers #text-to-image #autotrain #base_model-stabilityai/stable-diffusion-xl-base-1.0 #has_space #region-us \n# DreamBooth trained by AutoTrain\n\nText encoder was not trained."
] | [
-0.02063869684934616,
0.12998254597187042,
-0.00014558587281499058,
0.05282456427812576,
0.16523675620555878,
0.04722703993320465,
0.16625140607357025,
0.08092519640922546,
-0.021600954234600067,
0.06268861889839172,
0.19911405444145203,
-0.005327701102942228,
0.005592701490968466,
0.22998546063899994,
-0.094501793384552,
-0.15147385001182556,
0.05843960493803024,
-0.017813973128795624,
0.08953600376844406,
0.04556926712393761,
0.01589704304933548,
-0.08332102000713348,
0.06851272284984589,
-0.1127990260720253,
-0.21184474229812622,
0.06736689060926437,
0.028242893517017365,
-0.08190154284238815,
0.023159906268119812,
0.057201284915208817,
0.11752432584762573,
0.05736266449093819,
0.06915528327226639,
-0.09377864748239517,
0.030588991940021515,
0.09211067855358124,
-0.037628743797540665,
0.060378964990377426,
0.002463718643411994,
0.007739691063761711,
-0.03909904137253761,
0.01951049454510212,
0.05348891019821167,
0.033195290714502335,
-0.09112479537725449,
0.09422965347766876,
0.008997537195682526,
0.05966416001319885,
0.005606517195701599,
0.1256808042526245,
-0.02887202799320221,
0.0914452075958252,
0.0028242841362953186,
0.10286186635494232,
0.050214264541864395,
-0.15577325224876404,
-0.05811230465769768,
0.22586119174957275,
0.06323451548814774,
0.18434374034404755,
-0.1056840792298317,
0.08215278387069702,
0.1282002329826355,
0.0043175057508051395,
-0.024307064712047577,
-0.0056144483387470245,
-0.053464896976947784,
-0.0875391811132431,
-0.04101261869072914,
-0.04863812029361725,
0.19171690940856934,
0.013884141109883785,
-0.014532854780554771,
-0.08809809386730194,
-0.1092078685760498,
-0.03936294838786125,
0.015471521764993668,
0.009576751850545406,
-0.05643317475914955,
0.06334297358989716,
-0.04036302492022514,
-0.0881064385175705,
-0.048688579350709915,
-0.03869857266545296,
-0.07886603474617004,
0.09238439798355103,
-0.0456368625164032,
0.0745692178606987,
-0.0938243567943573,
0.13909384608268738,
-0.026598775759339333,
-0.12820684909820557,
0.06501864641904831,
-0.0971466526389122,
0.015486733056604862,
0.06505174934864044,
-0.019916843622922897,
-0.1562809944152832,
0.019901327788829803,
0.030637366697192192,
0.07526841759681702,
0.05189061909914017,
-0.08258821815252304,
0.09015702456235886,
0.007376048713922501,
0.09042561054229736,
-0.016077103093266487,
-0.024903813377022743,
0.06223255768418312,
0.080438993871212,
0.023856146261096,
-0.14336538314819336,
-0.16565988957881927,
0.06790684908628464,
-0.017159676179289818,
0.04283891245722771,
0.03642508387565613,
-0.010275715962052345,
-0.031149128451943398,
-0.004403593484312296,
0.047221966087818146,
-0.04838476702570915,
0.023466823622584343,
-0.07434477657079697,
-0.008917812258005142,
0.014335056766867638,
0.1431507170200348,
0.007567800115793943,
-0.006044706329703331,
-0.008012169972062111,
-0.10112743824720383,
-0.01249670796096325,
-0.06397054344415665,
-0.082596056163311,
-0.05697616934776306,
-0.11640746891498566,
0.03807840123772621,
-0.16242456436157227,
-0.1366284042596817,
-0.010717466473579407,
0.012121928855776787,
-0.08239061385393143,
-0.0024879504926502705,
-0.08431833982467651,
-0.12462550401687622,
0.1450532078742981,
-0.013907280750572681,
-0.03597475588321686,
0.0006233238964341581,
0.06648663431406021,
-0.010329908691346645,
0.10745283216238022,
-0.17473040521144867,
0.01794232614338398,
-0.07896706461906433,
-0.0015359485987573862,
-0.08321953564882278,
0.16549469530582428,
-0.03203589841723442,
0.033024370670318604,
-0.03292569890618324,
0.04207007214426994,
0.0021412093192338943,
0.008031118661165237,
0.05329214408993721,
0.15599198639392853,
-0.19367799162864685,
-0.04072578251361847,
0.0876203402876854,
-0.08026987314224243,
-0.011655561625957489,
0.041991058737039566,
-0.022804416716098785,
0.047191135585308075,
0.005142057780176401,
0.15102070569992065,
-0.07513030618429184,
-0.1523657888174057,
-0.00003674626350402832,
0.019653983414173126,
-0.03947019204497337,
0.06174682825803757,
-0.03899246081709862,
0.060578037053346634,
-0.07573825865983963,
0.03253980353474617,
-0.005597305484116077,
0.08249075710773468,
-0.06469673663377762,
-0.07055705785751343,
-0.06726926565170288,
-0.021799663081765175,
0.06577687710523605,
0.01678086258471012,
0.07544080168008804,
-0.030378416180610657,
-0.07784181833267212,
0.03869107738137245,
0.04462023451924324,
-0.009920100681483746,
-0.007784112356603146,
-0.013205957598984241,
-0.04446694254875183,
-0.12920789420604706,
0.003658822737634182,
-0.09591405093669891,
-0.0857297033071518,
0.00785818975418806,
0.23912277817726135,
0.09514347463846207,
0.14679308235645294,
0.059998251497745514,
0.04194987192749977,
-0.031193705275654793,
-0.12705348432064056,
-0.0008300838526338339,
0.029192514717578888,
-0.08331938832998276,
-0.09998124092817307,
0.0904180034995079,
-0.09146905690431595,
-0.004678551107645035,
-0.1545001119375229,
0.007734695915132761,
-0.07803455740213394,
0.15830396115779877,
0.028678199276328087,
-0.031181402504444122,
-0.03010755404829979,
0.0402386300265789,
-0.09691616147756577,
-0.1099129319190979,
-0.0022663131821900606,
0.0153842493891716,
-0.0945914015173912,
0.06970567256212234,
-0.2405780851840973,
0.0574164092540741,
0.14391222596168518,
-0.005025625228881836,
-0.07321476936340332,
0.11765623092651367,
0.0489165261387825,
-0.013706451281905174,
-0.023128986358642578,
-0.02168380096554756,
0.1244552806019783,
-0.07626726478338242,
0.19949495792388916,
-0.01798384077847004,
0.08187845349311829,
0.05062877759337425,
-0.06974431127309799,
-0.135806143283844,
-0.000004087520210305229,
-0.03837069496512413,
-0.0334748737514019,
0.11700894683599472,
0.09331324696540833,
-0.060808680951595306,
0.27977684140205383,
0.002255344530567527,
-0.0019275352824479342,
-0.03330899775028229,
-0.014577753841876984,
-0.0332055389881134,
0.12854062020778656,
-0.012121065519750118,
0.00992091279476881,
0.015768490731716156,
-0.014307437464594841,
0.01476898044347763,
-0.09258662909269333,
-0.015657516196370125,
-0.029646404087543488,
-0.0163404643535614,
0.1258670836687088,
0.016155531629920006,
-0.035148244351148605,
0.07309972494840622,
-0.04378744959831238,
-0.0816405862569809,
0.11111503094434738,
-0.022147411480545998,
-0.0004421356425154954,
0.05905456468462944,
-0.15857146680355072,
-0.2807832360267639,
-0.1459890753030777,
0.005951586179435253,
-0.11860986053943634,
0.04109755903482437,
0.052975885570049286,
-0.10799627006053925,
-0.07004248350858688,
-0.08202385157346725,
-0.08629177510738373,
-0.05557532608509064,
0.0011311533162370324,
0.11728531867265701,
-0.06409677118062973,
0.05387398600578308,
-0.06229059770703316,
-0.00887343194335699,
-0.013896237127482891,
0.0027349803131073713,
0.09634215384721756,
0.02155768871307373,
0.04409273341298103,
0.20931857824325562,
-0.01992671564221382,
0.03497228026390076,
-0.007471531629562378,
0.25480857491493225,
-0.07225025445222855,
0.051100753247737885,
0.11487668752670288,
0.031045233830809593,
0.052618835121393204,
0.1828797161579132,
-0.01034550741314888,
-0.0642908588051796,
0.06494352221488953,
-0.012484862469136715,
-0.10492375493049622,
-0.11105634272098541,
-0.0924028679728508,
-0.04872503876686096,
-0.06293869018554688,
0.029581304639577866,
0.06633029878139496,
0.18465307354927063,
0.03403869643807411,
-0.0085936663672328,
0.038062650710344315,
-0.038405340164899826,
0.05253121256828308,
0.05000557377934456,
-0.054350171238183975,
0.10506314784288406,
-0.05272989347577095,
-0.07878284156322479,
0.09704536944627762,
0.029444830492138863,
0.08175686746835709,
-0.005787411238998175,
-0.051862932741642,
-0.054340463131666183,
0.05357728153467178,
0.12942302227020264,
0.016036581248044968,
0.0732298195362091,
-0.037278078496456146,
-0.04033561050891876,
-0.043483830988407135,
-0.012224663980305195,
0.08897408843040466,
0.023024603724479675,
0.013343557715415955,
-0.06517297029495239,
0.09141328185796738,
-0.0036450172774493694,
0.03365681692957878,
0.10284296423196793,
-0.24468940496444702,
0.03720756992697716,
0.05340345576405525,
0.009430313482880592,
-0.15917426347732544,
-0.001802100450731814,
0.2596781551837921,
-0.0778416246175766,
-0.016604389995336533,
-0.005158600863069296,
0.07767105102539062,
0.07948087900876999,
-0.01405559852719307,
-0.12727415561676025,
0.08470404893159866,
-0.03762264549732208,
-0.009994231164455414,
-0.21587730944156647,
0.04233643785119057,
0.006741201039403677,
0.09690377861261368,
-0.02572929486632347,
0.016345487907528877,
0.0344662107527256,
0.14141175150871277,
0.0716816708445549,
0.00973005685955286,
-0.08598282933235168,
-0.14106571674346924,
-0.08402053266763687,
-0.05161529779434204,
0.10742203146219254,
0.09498894214630127,
-0.004010304808616638,
-0.011004406958818436,
0.029761290177702904,
0.04038768634200096,
-0.048020366579294205,
-0.20780979096889496,
-0.12313251197338104,
0.03342318534851074,
0.18468953669071198,
0.07250070571899414,
-0.042261723428964615,
-0.07773694396018982,
0.058913350105285645,
0.15853528678417206,
-0.06002082675695419,
-0.03646547347307205,
-0.12438587844371796,
-0.01314868126064539,
0.04682208597660065,
-0.004984802100807428,
0.07632478326559067,
-0.11283677071332932,
0.055372435599565506,
-0.05680480971932411,
-0.15995463728904724,
0.08369133621454239,
-0.09573204070329666,
-0.09156695753335953,
-0.09880076348781586,
-0.02600095607340336,
-0.07628563791513443,
-0.01809440366923809,
0.02631893940269947,
0.03644336014986038,
-0.09317634254693985,
-0.08042453974485397,
0.07387512177228928,
0.052659958600997925,
-0.0790650025010109,
0.11336636543273926,
0.039935242384672165,
-0.05932047963142395,
0.009086593985557556,
-0.020160207524895668,
0.16297784447669983,
0.2692966163158417,
-0.09637150168418884,
0.1332009732723236,
0.10272762179374695,
-0.07975436747074127,
-0.2972416281700134,
-0.06331747770309448,
-0.001001058961264789,
0.033033158630132675,
-0.037056490778923035,
-0.08421573042869568,
0.01754319854080677,
-0.037301890552043915,
-0.026686429977416992,
0.09380273520946503,
-0.25594666600227356,
-0.07236529886722565,
0.12090659141540527,
0.011188359931111336,
0.3046357333660126,
-0.12652114033699036,
-0.03758466988801956,
-0.07161959260702133,
0.030579380691051483,
0.09310808032751083,
0.05593981221318245,
0.1552010029554367,
-0.01064409501850605,
0.029015347361564636,
0.016381043940782547,
-0.03504854813218117,
0.15569667518138885,
-0.09976516664028168,
0.07290340214967728,
-0.09811180084943771,
0.02065517008304596,
0.1682867556810379,
-0.07824182510375977,
0.06025531142950058,
-0.08820004016160965,
0.08328087627887726,
-0.14803707599639893,
0.024164263159036636,
-0.030000343918800354,
0.019950132817029953,
0.023836227133870125,
-0.09545804560184479,
-0.05183679237961769,
-0.024305418133735657,
0.031683988869190216,
0.0011127261677756906,
0.008928169496357441,
-0.03344632312655449,
0.021105246618390083,
0.31053033471107483,
-0.045023828744888306,
-0.08844760805368423,
-0.032576143741607666,
0.0008607114432379603,
-0.07616515457630157,
0.15518175065517426,
-0.140009805560112,
0.016880689188838005,
0.08636961877346039,
-0.028658051043748856,
0.19429416954517365,
0.04890631139278412,
-0.034792251884937286,
0.06410761177539825,
0.08606549352407455,
-0.17321881651878357,
0.023975208401679993,
-0.08413522690534592,
0.03825248405337334,
0.07573363929986954,
-0.08445089310407639,
0.1707473248243332,
-0.07278440147638321,
0.0452447347342968,
-0.039885539561510086,
0.022516414523124695,
-0.02864324487745762,
0.07788124680519104,
0.05243882164359093,
0.03179828077554703,
-0.08249194175004959,
0.1251235008239746,
0.038169246166944504,
-0.00042698116158135235,
0.13369235396385193,
0.09562437236309052,
-0.02339347079396248,
-0.029987553134560585,
-0.006221109069883823,
0.24116981029510498,
-0.1580258458852768,
-0.008135645650327206,
-0.04209064692258835,
-0.0893833190202713,
-0.022283220663666725,
0.033660776913166046,
0.004361500032246113,
0.008071556687355042,
-0.06307882070541382,
-0.04562815651297569,
-0.10188619047403336,
0.03915635868906975,
0.04616845026612282,
0.06768101453781128,
-0.2191275805234909,
0.009082616306841373,
0.027556031942367554,
0.05952044948935509,
-0.13306017220020294,
-0.09101494401693344,
-0.15259279310703278,
0.00039742272929288447,
-0.13059686124324799,
0.06406794488430023,
0.061592768877744675,
-0.04854949936270714,
0.035067036747932434,
-0.043882932513952255,
0.0004143699479755014,
0.028861405327916145,
-0.04535970091819763,
-0.011117871850728989,
0.015505447052419186,
0.006177510134875774,
-0.030567757785320282,
-0.053487807512283325,
-0.043063435703516006,
-0.029680561274290085,
0.054787784814834595,
0.02104547619819641,
-0.0758507251739502,
-0.023473115637898445,
-0.18298010528087616,
-0.01812969706952572,
0.13245733082294464,
0.002356436103582382,
-0.008200457319617271,
0.14597384631633759,
-0.03255922719836235,
0.02350054867565632,
0.045941680669784546,
0.00834833923727274,
0.04824364185333252,
-0.10032500326633453,
-0.11206801235675812,
-0.07519271969795227,
-0.05291133001446724,
-0.07905688136816025,
0.08345643430948257,
0.10799416899681091,
0.07442577183246613,
0.11548545211553574,
-0.13865616917610168,
0.0669560506939888,
-0.07766007632017136,
-0.0069593568332493305,
-0.02534155361354351,
-0.07888507097959518,
0.010779611766338348,
-0.010162390768527985,
0.045325834304094315,
-0.0136204082518816,
0.14034360647201538,
0.09084946662187576,
-0.13309991359710693,
-0.0024138707667589188,
-0.00929619837552309,
-0.02631843276321888,
-0.016799401491880417,
0.2551889717578888,
0.10145963728427887,
-0.006956462282687426,
-0.08942729234695435,
0.021860230714082718,
0.13579104840755463,
0.12235307693481445,
0.0031318129040300846,
0.015644969418644905,
0.024258719757199287,
0.16481736302375793,
0.003965459298342466,
-0.016579868271946907,
-0.059937287122011185,
0.03426060453057289,
-0.10462383925914764,
0.12247732281684875,
-0.11873367428779602,
-0.14781181514263153,
0.10172251611948013,
-0.02050800621509552,
-0.03943636640906334,
0.0037147165276110172,
-0.0770074650645256,
-0.09716072678565979,
-0.027703063562512398,
-0.06800327450037003,
-0.17266669869422913,
0.027315571904182434,
-0.06229201331734657,
0.12446222454309464,
0.06566920876502991,
0.0076821851544082165,
-0.07402129471302032,
0.09486519545316696,
0.02963947132229805,
-0.0744946077466011,
0.11698131263256073,
0.006778121460229158,
-0.004627263639122248,
-0.0994558110833168,
-0.04522183537483215,
0.07144024223089218,
0.1097252368927002,
-0.0014914624625816941,
0.062032222747802734,
0.03687533363699913,
0.07175064831972122,
-0.021852314472198486,
-0.1358582228422165,
0.009430473670363426,
0.06657078862190247,
-0.014820176176726818,
0.17750272154808044,
0.0526888370513916,
0.01400719489902258,
-0.033916763961315155,
0.20015233755111694,
-0.1060686707496643,
-0.08181434869766235,
-0.08442502468824387,
0.1438642144203186,
-0.10308082401752472,
0.12064629793167114,
-0.08840858936309814,
-0.10166779905557632,
-0.1078825369477272,
0.13028131425380707,
0.14787504076957703,
-0.1705704927444458,
-0.00973743386566639,
-0.059736791998147964,
-0.007106183096766472,
-0.04775403439998627,
0.1790471076965332,
0.027036966755986214,
0.0724797174334526,
-0.06618554890155792,
0.02645842544734478,
-0.05293412134051323,
-0.10053800046443939,
-0.07210712134838104,
-0.07806676626205444,
0.0033898563124239445,
-0.046734727919101715,
-0.1227606013417244,
-0.054156865924596786,
-0.1298540085554123,
0.07478922605514526,
0.13676925003528595,
-0.09898433089256287,
-0.036553580313920975,
0.0014106096932664514,
0.16058985888957977,
-0.02301349863409996,
-0.022042766213417053,
-0.07060083746910095,
0.055989354848861694,
0.09736833721399307,
-0.06496482342481613,
-0.017015384510159492,
-0.018570678308606148,
-0.058492738753557205,
-0.2682178318500519,
0.16817118227481842,
-0.004298606421798468,
0.03949829190969467,
0.031070971861481667,
0.03424987196922302,
-0.05919113755226135,
0.13132870197296143,
-0.048278603702783585,
-0.026828566566109657,
-0.026347270235419273,
0.1921045184135437,
-0.024049637839198112,
0.05515880510210991,
0.037085678428411484,
-0.14625179767608643,
-0.030122820287942886,
0.011054210364818573,
-0.07361718267202377,
0.004916774109005928,
-0.043997615575790405,
-0.020118191838264465,
0.11343158781528473,
0.033629145473241806,
-0.016268683597445488,
0.012032032944262028,
-0.01385825127363205,
0.004258410073816776,
-0.01866539753973484,
-0.0066040013916790485,
0.027589673176407814,
-0.1268121898174286,
-0.026856685057282448,
0.0937948226928711,
0.038554634898900986,
-0.2399676889181137,
-0.056827764958143234,
-0.20476673543453217,
0.0481138676404953,
-0.07275717705488205,
0.13741889595985413,
0.15254093706607819,
-0.023496365174651146,
-0.007380692288279533,
-0.12191148102283478,
0.015328208915889263,
0.04335465282201767,
0.00498174037784338,
-0.033090222626924515
] |
null | null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.7.2.dev0 | {"library_name": "peft", "base_model": "google/flan-t5-base"} | null | HeydarS/flan-t5-base_peft_v5 | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/flan-t5-base",
"region:us"
] | 2024-02-09T01:45:34+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #safetensors #arxiv-1910.09700 #base_model-google/flan-t5-base #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
### Framework versions
- PEFT 0.7.2.dev0 | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact",
"### Framework versions\n\n- PEFT 0.7.2.dev0"
] | [
"TAGS\n#peft #safetensors #arxiv-1910.09700 #base_model-google/flan-t5-base #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact",
"### Framework versions\n\n- PEFT 0.7.2.dev0"
] | [
35,
6,
3,
54,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4,
14
] | [
"passage: TAGS\n#peft #safetensors #arxiv-1910.09700 #base_model-google/flan-t5-base #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact### Framework versions\n\n- PEFT 0.7.2.dev0"
] | [
-0.10626745969057083,
0.1943962424993515,
-0.003387606469914317,
0.03603767976164818,
0.09226002544164658,
0.019435854628682137,
0.05228874087333679,
0.12314661592245102,
-0.03763783350586891,
0.10612741112709045,
0.0677775889635086,
0.1003333255648613,
0.10013683140277863,
0.20788270235061646,
0.01028058398514986,
-0.20106801390647888,
0.025792978703975677,
-0.09577292203903198,
-0.007508585229516029,
0.12317893654108047,
0.15051408112049103,
-0.09860456734895706,
0.08032377064228058,
-0.016225092113018036,
-0.01558137871325016,
-0.03681138902902603,
-0.07320638746023178,
-0.035057611763477325,
0.04912315681576729,
0.049064796417951584,
0.05871843919157982,
-0.00005916723603149876,
0.09118524193763733,
-0.26729705929756165,
0.019125372171401978,
0.04606068879365921,
-0.008893071673810482,
0.08542384952306747,
0.10275928676128387,
-0.03844038024544716,
0.12587106227874756,
-0.03221188858151436,
0.14311404526233673,
0.08030287176370621,
-0.09467478841543198,
-0.21773016452789307,
-0.0719180628657341,
0.0834791362285614,
0.1696113646030426,
0.07952837646007538,
-0.043143972754478455,
0.13347607851028442,
-0.09846170246601105,
0.01899239793419838,
0.04215628653764725,
-0.08037710934877396,
-0.0743836760520935,
0.05872213840484619,
0.10499230772256851,
0.053478822112083435,
-0.1377313882112503,
-0.030999790877103806,
0.022513283416628838,
0.04074760526418686,
0.08075147122144699,
0.018500911071896553,
0.14020903408527374,
0.032465290278196335,
-0.14929986000061035,
-0.04096416383981705,
0.13178586959838867,
0.03145142272114754,
-0.0386669859290123,
-0.22038984298706055,
0.009189976379275322,
-0.08269672095775604,
-0.026602445170283318,
-0.053094200789928436,
0.035357702523469925,
0.0009046635823324323,
0.09034530818462372,
-0.03193694353103638,
-0.09359759837388992,
-0.012948989868164062,
0.0944470688700676,
0.04649518430233002,
0.024375872686505318,
-0.025291787460446358,
0.006814958062022924,
0.1236046850681305,
0.05509087070822716,
-0.12566722929477692,
-0.05955754220485687,
-0.07080139219760895,
-0.04547770693898201,
-0.04806475341320038,
0.033843204379081726,
0.02901734784245491,
0.058218520134687424,
0.2488924115896225,
-0.030058603733778,
0.0549616776406765,
0.05447668582201004,
0.019564809277653694,
0.04267705976963043,
0.09505946934223175,
-0.05727843567728996,
-0.1486940234899521,
-0.01470540463924408,
0.09698048233985901,
-0.00953452754765749,
-0.019430894404649734,
-0.04841039329767227,
0.03599175065755844,
0.046676695346832275,
0.10488031059503555,
0.09370704740285873,
-0.0038008210249245167,
-0.07420773059129715,
-0.04932110756635666,
0.20879322290420532,
-0.14909665286540985,
0.04108875244855881,
0.02244400605559349,
-0.018436485901474953,
-0.06020741909742355,
0.013366634957492352,
0.017413243651390076,
-0.025361547246575356,
0.09793671220541,
-0.06251633912324905,
-0.04163913428783417,
-0.11557204276323318,
-0.021286284551024437,
0.038216814398765564,
0.013806617818772793,
-0.02672383189201355,
-0.035722583532333374,
-0.06411529332399368,
-0.0939604863524437,
0.10544420778751373,
-0.0658579021692276,
-0.06309971213340759,
-0.02974298782646656,
-0.09095096588134766,
0.016579419374465942,
0.028497256338596344,
0.11275363713502884,
-0.024662071838974953,
0.04416226968169212,
-0.014005821198225021,
0.060549791902303696,
0.07976043969392776,
0.037235476076602936,
-0.06926264613866806,
0.061339445412158966,
-0.19918614625930786,
0.09161697328090668,
-0.07697001099586487,
0.028699280694127083,
-0.15864884853363037,
-0.017035553231835365,
0.00033481643185950816,
0.020158562809228897,
0.039182908833026886,
0.15084892511367798,
-0.19582802057266235,
-0.02592594362795353,
0.1559358388185501,
-0.10197359323501587,
-0.12382874637842178,
0.042082399129867554,
-0.05455990135669708,
0.16270385682582855,
0.021871736273169518,
-0.009292042814195156,
0.09196344763040543,
-0.15284870564937592,
-0.02294968068599701,
-0.02839653380215168,
-0.005660604685544968,
0.10367421060800552,
0.08136079460382462,
-0.07848794758319855,
0.02571188658475876,
0.014831089414656162,
-0.041812699288129807,
-0.022545142099261284,
-0.053160153329372406,
-0.11061898618936539,
0.0009782188571989536,
-0.08726845681667328,
0.026618853211402893,
-0.008247734978795052,
-0.07610312849283218,
-0.01254703477025032,
-0.16181626915931702,
-0.02871214598417282,
0.07868514955043793,
0.01724299229681492,
-0.01901300996541977,
-0.09065431356430054,
0.03456268459558487,
-0.02381935343146324,
-0.024170242249965668,
-0.15777996182441711,
-0.0361778698861599,
0.01957101747393608,
-0.13848066329956055,
0.012914540246129036,
-0.12052971124649048,
0.066510409116745,
0.014045109041035175,
-0.07196114957332611,
-0.03254105895757675,
-0.01547172199934721,
0.009743290953338146,
-0.05094056576490402,
-0.23752011358737946,
-0.021084511652588844,
-0.0554598905146122,
0.14978623390197754,
-0.22872553765773773,
0.03972625732421875,
0.04129142314195633,
0.12734706699848175,
0.0021993080154061317,
-0.0596797838807106,
0.027768824249505997,
-0.07154082506895065,
-0.022692902013659477,
-0.07238355278968811,
-0.004847003147006035,
-0.001676840358413756,
-0.04038437828421593,
0.016839073970913887,
-0.11187786608934402,
-0.0447884164750576,
0.10195057839155197,
0.06268775463104248,
-0.17277465760707855,
-0.02041766420006752,
-0.04777924343943596,
-0.06872023642063141,
-0.09030480682849884,
-0.05886688455939293,
0.09846045076847076,
0.04916569963097572,
0.03816893696784973,
-0.07307842373847961,
-0.06809652596712112,
0.010012323036789894,
-0.017745092511177063,
-0.025862621143460274,
0.11348828673362732,
0.06857994943857193,
-0.11471354216337204,
0.09571298211812973,
0.06638070940971375,
0.026577377691864967,
0.07707730680704117,
-0.025765812024474144,
-0.10656370222568512,
-0.0275901909917593,
0.04605529084801674,
0.012250564992427826,
0.16212764382362366,
-0.07695270329713821,
0.0528617724776268,
0.04372003301978111,
-0.034936483949422836,
0.04988601431250572,
-0.09815118461847305,
0.010052197612822056,
0.005698662716895342,
-0.015340845100581646,
0.016503745689988136,
-0.01996779255568981,
0.010818221606314182,
0.08451361209154129,
0.05374802649021149,
0.034732699394226074,
0.03416459634900093,
-0.027584291994571686,
-0.13143029808998108,
0.1801474541425705,
-0.09626327455043793,
-0.23413608968257904,
-0.15353670716285706,
0.05498236417770386,
0.05599696934223175,
-0.018610401079058647,
0.027064653113484383,
-0.05219969525933266,
-0.10190703719854355,
-0.07922445982694626,
-0.004773293621838093,
0.028319185599684715,
-0.060163792222738266,
-0.0763615071773529,
0.05326016992330551,
0.04257733002305031,
-0.11543019115924835,
0.04015215486288071,
0.06237921118736267,
-0.007595696486532688,
0.006950370967388153,
0.052949290722608566,
0.0827041044831276,
0.1778176873922348,
-0.012662996537983418,
-0.001374164829030633,
0.05132483318448067,
0.28036999702453613,
-0.15926094353199005,
0.11483950167894363,
0.11827429383993149,
-0.061905838549137115,
0.07703997194766998,
0.18894267082214355,
0.031426820904016495,
-0.10071038454771042,
0.03919421136379242,
0.0339176207780838,
-0.026562854647636414,
-0.2736181616783142,
-0.04572368040680885,
-0.010000117123126984,
-0.09846661984920502,
0.08148844540119171,
0.09112165868282318,
0.09233558923006058,
0.03964434936642647,
-0.06323430687189102,
-0.09103947132825851,
0.03861045092344284,
0.099139004945755,
-0.016542939469218254,
0.004856142681092024,
0.08154811710119247,
-0.028960175812244415,
0.009979736059904099,
0.09486377984285355,
-0.018665187060832977,
0.1644057333469391,
0.04859054088592529,
0.10418574512004852,
0.07721724361181259,
0.09577159583568573,
-0.00678221695125103,
0.024683605879545212,
0.019262781366705894,
0.023546066135168076,
0.016479844227433205,
-0.0836954340338707,
0.035068731755018234,
0.10865435749292374,
0.03942868858575821,
0.02600918337702751,
0.013191206380724907,
-0.044774990528821945,
0.0474453829228878,
0.18922826647758484,
0.009999711997807026,
-0.20108447968959808,
-0.08201143890619278,
0.05267728865146637,
-0.07563731074333191,
-0.14131365716457367,
-0.017839588224887848,
0.028532851487398148,
-0.16847741603851318,
0.015154414810240269,
-0.044349510222673416,
0.10102768242359161,
-0.06610823422670364,
-0.04040110483765602,
0.10356244444847107,
0.0725359171628952,
-0.02740391157567501,
0.06083453819155693,
-0.20365430414676666,
0.12665313482284546,
0.024027224630117416,
0.07074165344238281,
-0.08825352787971497,
0.0968342199921608,
0.0011091300984844565,
-0.00461592897772789,
0.16639287769794464,
0.002134338952600956,
-0.07097217440605164,
-0.05354686081409454,
-0.0921424999833107,
-0.013771062716841698,
0.10175586491823196,
-0.1249750629067421,
0.06322869658470154,
-0.016876481473445892,
-0.03235099837183952,
0.006789884530007839,
-0.0761876031756401,
-0.13253721594810486,
-0.17009471356868744,
0.05461978167295456,
-0.10156451165676117,
0.03955043852329254,
-0.09254651516675949,
-0.06745260208845139,
0.004009621683508158,
0.17828625440597534,
-0.17609639465808868,
-0.09290038049221039,
-0.14633356034755707,
-0.08385132253170013,
0.16673745214939117,
-0.03696591779589653,
0.08714164793491364,
0.0008085340959951282,
0.1633509248495102,
0.014043261297047138,
-0.0004224503063596785,
0.09846942126750946,
-0.08807885646820068,
-0.19665396213531494,
-0.058461662381887436,
0.1666961908340454,
0.14166374504566193,
0.03869305178523064,
-0.010088405571877956,
0.021535715088248253,
-0.05324366316199303,
-0.11172157526016235,
0.025243619456887245,
0.12963053584098816,
0.08552177995443344,
-0.016120724380016327,
-0.03886369988322258,
-0.09494185447692871,
-0.0650559812784195,
-0.06025339663028717,
0.001782225794158876,
0.18376830220222473,
-0.07549230009317398,
0.16126713156700134,
0.11873925477266312,
-0.054935604333877563,
-0.20435717701911926,
0.051667653024196625,
0.057001613080501556,
0.01535657700151205,
0.03362317755818367,
-0.19608907401561737,
0.08624274283647537,
-0.00034414982656016946,
-0.07186609506607056,
0.16279858350753784,
-0.16888505220413208,
-0.14565519988536835,
0.09902361035346985,
0.0366116538643837,
-0.236861914396286,
-0.13917239010334015,
-0.09933043271303177,
-0.018550176173448563,
-0.11035100370645523,
0.062390539795160294,
0.00021574481797870249,
0.011819778941571712,
0.03125092014670372,
0.01891767606139183,
0.02876076102256775,
-0.04887833073735237,
0.20177625119686127,
-0.02594452165067196,
0.010557923465967178,
-0.05068642273545265,
-0.09157499670982361,
0.033935029059648514,
-0.0506705567240715,
0.1028408408164978,
0.00432779174298048,
0.02938619628548622,
-0.1420229971408844,
-0.04426152631640434,
-0.06219794973731041,
0.03049236349761486,
-0.09847007691860199,
-0.08974216133356094,
-0.04626361280679703,
0.09782198816537857,
0.09823662042617798,
-0.03223685920238495,
0.005748902913182974,
-0.08590634912252426,
0.0708165094256401,
0.20846675336360931,
0.1880311667919159,
0.07307461649179459,
-0.06206341087818146,
0.021826045587658882,
-0.034976597875356674,
0.04174673557281494,
-0.22437147796154022,
0.043028511106967926,
0.056297581642866135,
0.024020612239837646,
0.08573832362890244,
-0.00941250380128622,
-0.1538187861442566,
-0.07839273661375046,
0.0795898586511612,
-0.04730746150016785,
-0.16308970749378204,
-0.027136368677020073,
0.03949432820081711,
-0.21053273975849152,
-0.04798044264316559,
0.015552849508821964,
-0.02477485127747059,
-0.04049832746386528,
0.02438291907310486,
0.07634059339761734,
-0.01943463273346424,
0.11085540056228638,
0.09432967007160187,
0.09200961887836456,
-0.09735818207263947,
0.08124689757823944,
0.07701282203197479,
-0.04806763306260109,
0.021812697872519493,
0.11117840558290482,
-0.050739508122205734,
-0.037840310484170914,
0.09233005344867706,
0.08607760071754456,
0.02519970014691353,
-0.05105016753077507,
0.015625236555933952,
-0.05509917065501213,
0.06538805365562439,
0.12310566008090973,
0.028020475059747696,
-0.00401606410741806,
0.05817234516143799,
0.036317672580480576,
-0.10091570764780045,
0.11022966355085373,
0.060984570533037186,
0.022640034556388855,
-0.04285145550966263,
-0.025664152577519417,
-0.010606732219457626,
-0.00946447066962719,
-0.019042406231164932,
-0.005740757565945387,
-0.09020785242319107,
-0.008166715502738953,
-0.1037309393286705,
0.03222903981804848,
-0.07299622148275375,
0.010693063028156757,
0.026414508000016212,
-0.05268304422497749,
0.009201978333294392,
0.0049271248281002045,
-0.07451415061950684,
-0.051883138716220856,
-0.014390280470252037,
0.08451662957668304,
-0.12997590005397797,
0.03118613176047802,
0.07371551543474197,
-0.1054111048579216,
0.07181970775127411,
0.0018193931318819523,
0.007645344827324152,
0.012531098909676075,
-0.1657782346010208,
0.056539472192525864,
-0.024776315316557884,
-0.014173267409205437,
0.01549680344760418,
-0.2142029106616974,
-0.011480376124382019,
-0.04960622265934944,
-0.05262897163629532,
0.012350749224424362,
-0.02797774039208889,
-0.12506969273090363,
0.09995295107364655,
-0.005099916830658913,
-0.07048572599887848,
-0.017425669357180595,
0.038649704307317734,
0.09460994601249695,
-0.022369757294654846,
0.12504130601882935,
-0.028333604335784912,
0.07363194227218628,
-0.17342032492160797,
-0.0020430213771760464,
-0.016072485595941544,
0.04032069072127342,
-0.022196732461452484,
-0.022031286731362343,
0.05816557630896568,
-0.01751047931611538,
0.17629386484622955,
-0.021942971274256706,
0.07332462072372437,
0.0549980029463768,
0.00522792199626565,
0.005346484947949648,
0.08542075008153915,
0.06342078000307083,
-0.008526364341378212,
-0.004864741116762161,
0.04174121841788292,
-0.006167198531329632,
-0.04359015077352524,
-0.1550811231136322,
0.07007448375225067,
0.16129887104034424,
0.04683932289481163,
0.02103545516729355,
0.03010541759431362,
-0.12103217840194702,
-0.06719450652599335,
0.132915198802948,
-0.007291777525097132,
-0.035461392253637314,
-0.07875702530145645,
0.1820414662361145,
0.12919233739376068,
-0.19846510887145996,
0.0785851925611496,
-0.062020812183618546,
-0.055078864097595215,
-0.12649577856063843,
-0.1544293910264969,
-0.06379027664661407,
-0.04223756864666939,
-0.021467499434947968,
-0.06189240515232086,
0.050444722175598145,
0.04895254969596863,
0.004684585612267256,
-0.019241079688072205,
0.10444451123476028,
0.012044665403664112,
-0.023837493732571602,
0.04863271489739418,
0.06281875818967819,
0.03184809163212776,
-0.09782924503087997,
0.00889611430466175,
-0.003255242481827736,
0.01744062267243862,
0.06000742316246033,
0.016260197386145592,
-0.05058757960796356,
0.013521446846425533,
-0.014316970482468605,
-0.11267974227666855,
0.04368726164102554,
-0.017312193289399147,
-0.034139636904001236,
0.13907207548618317,
0.029180752113461494,
0.008199350908398628,
-0.020409412682056427,
0.2393750250339508,
-0.07374456524848938,
-0.07687947899103165,
-0.15254373848438263,
0.0597771592438221,
-0.06916273385286331,
0.0306389182806015,
0.03442620113492012,
-0.11679217219352722,
0.020971601828932762,
0.16349677741527557,
0.13074807822704315,
-0.010041698813438416,
0.01111083198338747,
0.05241261422634125,
0.0017416616901755333,
-0.030621716752648354,
0.014367358759045601,
0.05457673966884613,
0.13300518691539764,
-0.07221394777297974,
0.0668054074048996,
-0.012110509909689426,
-0.0727691724896431,
-0.017204321920871735,
0.10875110328197479,
-0.00115925632417202,
0.001458446611650288,
-0.07169950008392334,
0.14218659698963165,
-0.0870911106467247,
-0.23450365662574768,
0.05871950089931488,
-0.06713622808456421,
-0.14922666549682617,
-0.0495445616543293,
0.009493282064795494,
-0.01419214066118002,
0.014483078382909298,
0.07484103739261627,
-0.04558661952614784,
0.17140412330627441,
0.04358278587460518,
-0.05350765213370323,
-0.08261451125144958,
0.060234762728214264,
-0.12359639257192612,
0.28447747230529785,
0.018942512571811676,
0.05022856965661049,
0.10444867610931396,
-0.01699936017394066,
-0.14132224023342133,
0.012299301102757454,
0.10720779746770859,
-0.06784209609031677,
0.06262636929750443,
0.17135582864284515,
-0.000842442037537694,
0.1268947869539261,
0.05236613005399704,
-0.05412169173359871,
0.03930345177650452,
-0.08381089568138123,
-0.05141802504658699,
-0.11254512518644333,
0.07955029606819153,
-0.08164326846599579,
0.16071252524852753,
0.13219253718852997,
-0.0665043368935585,
-0.004091443493962288,
-0.0223674438893795,
0.08265941590070724,
0.007208789233118296,
0.11081504821777344,
0.008757385425269604,
-0.1851312816143036,
0.03756987303495407,
0.011224213056266308,
0.09999052435159683,
-0.2103920876979828,
-0.06459777057170868,
0.051976144313812256,
-0.021772118285298347,
-0.07437668740749359,
0.11798278242349625,
0.04241457208991051,
0.03347695991396904,
-0.03955359011888504,
-0.046107664704322815,
0.002645334228873253,
0.15035350620746613,
-0.11573656648397446,
-0.009015773423016071
] |
null | null | adapter-transformers |
# Adapter `tawfikgh/xsum_summary_adapter-v2` for gpt2
An [adapter](https://adapterhub.ml) for the `gpt2` model that was trained on the [summary/xsum](https://adapterhub.ml/explore/summary/xsum/) dataset.
This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library.
## Usage
First, install `adapters`:
```
pip install -U adapters
```
Now, the adapter can be loaded and activated like this:
```python
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("gpt2")
adapter_name = model.load_adapter("tawfikgh/xsum_summary_adapter-v2", source="hf", set_active=True)
```
## Architecture & Training
<!-- Add some description here -->
## Evaluation results
<!-- Add some description here -->
## Citation
<!-- Add some description here --> | {"tags": ["adapter-transformers", "adapterhub:summary/xsum", "gpt2"], "datasets": ["xsum"]} | null | tawfikgh/xsum_summary_adapter-v2 | [
"adapter-transformers",
"gpt2",
"adapterhub:summary/xsum",
"dataset:xsum",
"region:us"
] | 2024-02-09T01:47:30+00:00 | [] | [] | TAGS
#adapter-transformers #gpt2 #adapterhub-summary/xsum #dataset-xsum #region-us
|
# Adapter 'tawfikgh/xsum_summary_adapter-v2' for gpt2
An adapter for the 'gpt2' model that was trained on the summary/xsum dataset.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'adapters':
Now, the adapter can be loaded and activated like this:
## Architecture & Training
## Evaluation results
| [
"# Adapter 'tawfikgh/xsum_summary_adapter-v2' for gpt2\n\nAn adapter for the 'gpt2' model that was trained on the summary/xsum dataset.\n\nThis adapter was created for usage with the Adapters library.",
"## Usage\n\nFirst, install 'adapters':\n\n\n\nNow, the adapter can be loaded and activated like this:",
"## Architecture & Training",
"## Evaluation results"
] | [
"TAGS\n#adapter-transformers #gpt2 #adapterhub-summary/xsum #dataset-xsum #region-us \n",
"# Adapter 'tawfikgh/xsum_summary_adapter-v2' for gpt2\n\nAn adapter for the 'gpt2' model that was trained on the summary/xsum dataset.\n\nThis adapter was created for usage with the Adapters library.",
"## Usage\n\nFirst, install 'adapters':\n\n\n\nNow, the adapter can be loaded and activated like this:",
"## Architecture & Training",
"## Evaluation results"
] | [
30,
60,
25,
5,
4
] | [
"passage: TAGS\n#adapter-transformers #gpt2 #adapterhub-summary/xsum #dataset-xsum #region-us \n# Adapter 'tawfikgh/xsum_summary_adapter-v2' for gpt2\n\nAn adapter for the 'gpt2' model that was trained on the summary/xsum dataset.\n\nThis adapter was created for usage with the Adapters library.## Usage\n\nFirst, install 'adapters':\n\n\n\nNow, the adapter can be loaded and activated like this:## Architecture & Training## Evaluation results"
] | [
-0.06675992906093597,
-0.13657359778881073,
-0.0035921367816627026,
0.046100176870822906,
0.1578325778245926,
0.08794385194778442,
0.1517506241798401,
0.04721982404589653,
0.19045887887477875,
-0.055965907871723175,
0.06404192000627518,
0.12163811177015305,
0.09319371730089188,
0.13640782237052917,
0.07888025045394897,
-0.13105477392673492,
0.010140744037926197,
0.06675992161035538,
-0.21477344632148743,
0.12856218218803406,
0.12325343489646912,
-0.008464482612907887,
0.13607725501060486,
0.08973893523216248,
-0.11282509565353394,
0.04581274837255478,
0.09778879582881927,
-0.11655081063508987,
0.11606085300445557,
0.09243006259202957,
0.0929744690656662,
0.09272055327892303,
0.03419538214802742,
-0.11613806337118149,
-0.0025518410839140415,
0.07098107784986496,
-0.01592663861811161,
0.02370224893093109,
0.025620369240641594,
0.06699821352958679,
0.11661914736032486,
0.07177603989839554,
0.02436794526875019,
0.06880024820566177,
-0.10354165732860565,
-0.2598526179790497,
0.00412419717758894,
0.09244179725646973,
0.05263781547546387,
0.02214794047176838,
0.029560474678874016,
0.03405086696147919,
0.0340782031416893,
0.011275415308773518,
0.16265234351158142,
-0.2825221121311188,
0.014760182239115238,
0.025239478796720505,
0.06297758966684341,
0.07066894322633743,
0.06001448631286621,
0.07057693600654602,
-0.016919871792197227,
0.047038692981004715,
0.10953269898891449,
-0.06048768013715744,
-0.019567469134926796,
0.05711131542921066,
-0.1891549974679947,
-0.08871755748987198,
0.30755406618118286,
-0.07112739235162735,
-0.0745544284582138,
-0.012699862010776997,
-0.05686074495315552,
0.05930526182055473,
0.05443734675645828,
-0.1399327963590622,
-0.030379043892025948,
0.09584247320890427,
-0.0158743467181921,
-0.19341635704040527,
-0.12486488372087479,
-0.15828797221183777,
-0.15894997119903564,
0.2900383174419403,
-0.020280860364437103,
0.09070821106433868,
-0.0407070629298687,
0.11016914248466492,
-0.08655610680580139,
-0.0052614156156778336,
-0.041178856045007706,
-0.09709835797548294,
-0.020929494872689247,
0.0067377397790551186,
0.002795576583594084,
-0.2149384319782257,
0.047364428639411926,
0.043385736644268036,
0.1303962767124176,
0.023897361010313034,
0.05808474123477936,
0.08053513616323471,
-0.009952358901500702,
0.17089037597179413,
-0.09901971369981766,
0.013148792088031769,
0.004630186129361391,
-0.0435900054872036,
-0.07495800405740738,
-0.07795456796884537,
-0.1065046414732933,
-0.055703770369291306,
-0.03785436972975731,
0.058869123458862305,
0.02470262534916401,
0.11289028078317642,
-0.08458048105239868,
-0.07168973237276077,
0.03321247547864914,
-0.05740439519286156,
-0.029145749285817146,
-0.06003604829311371,
-0.017270393669605255,
0.004774696659296751,
0.1318962275981903,
-0.025167934596538544,
-0.014357764273881912,
-0.02800118178129196,
-0.06109246239066124,
-0.060051724314689636,
-0.013333452865481377,
-0.07722318172454834,
-0.017658531665802002,
-0.041325267404317856,
0.006640536244958639,
-0.1801925152540207,
-0.09791072458028793,
0.04912208393216133,
0.07947004586458206,
0.02161942422389984,
0.06444031000137329,
0.07305265218019485,
0.07017029821872711,
0.01846112310886383,
-0.06219302490353584,
0.05572063848376274,
-0.037096571177244186,
0.08027610927820206,
0.005806572735309601,
0.07983905076980591,
-0.11251488327980042,
0.05268200486898422,
-0.06433522701263428,
0.03700709342956543,
-0.10909272730350494,
0.07472073286771774,
-0.0970023050904274,
-0.06593887507915497,
-0.12710706889629364,
0.009453941136598587,
0.005307853687554598,
0.05408556014299393,
0.059498030692338943,
0.07390183210372925,
-0.09167730808258057,
-0.08271492272615433,
0.1804615706205368,
-0.22619971632957458,
-0.17793238162994385,
0.032770786434412,
0.06749329715967178,
0.16788388788700104,
0.04334896057844162,
0.09754514694213867,
0.09008806198835373,
-0.07568375021219254,
-0.01765032671391964,
0.09357482939958572,
-0.17826968431472778,
-0.048480018973350525,
0.0811053067445755,
0.06313642114400864,
-0.23562566936016083,
-0.003395866835489869,
-0.0855553075671196,
0.14348071813583374,
-0.023729173466563225,
-0.02835095301270485,
-0.06189258396625519,
-0.052113279700279236,
0.09428790956735611,
-0.04389443248510361,
-0.0804084911942482,
0.04983692988753319,
-0.10514549165964127,
0.05569799616932869,
0.08514133095741272,
-0.03553638234734535,
-0.012268705293536186,
-0.18137170374393463,
0.08358637988567352,
-0.12353802472352982,
0.033578645437955856,
-0.06091071665287018,
0.013679087162017822,
-0.01050265971571207,
0.02479344978928566,
0.03410585969686508,
0.127003476023674,
0.12193144857883453,
-0.011778141371905804,
-0.01084896083921194,
-0.01222914457321167,
-0.041018661111593246,
0.05152342841029167,
0.0016628861194476485,
-0.09375673532485962,
-0.02916720137000084,
-0.02000543661415577,
0.035987723618745804,
-0.039320845156908035,
0.03864986076951027,
0.16877441108226776,
0.0006637814221903682,
0.02566922828555107,
-0.007016688585281372,
-0.02923828363418579,
-0.045270998030900955,
0.0009574774303473532,
-0.08918674290180206,
0.03690919280052185,
0.007516868412494659,
-0.08083225041627884,
0.20412954688072205,
-0.09803903847932816,
0.11000768095254898,
0.10611823946237564,
-0.04118837043642998,
-0.020301934331655502,
0.02775782160460949,
-0.011134607717394829,
-0.03371728956699371,
0.03600263223052025,
-0.07141582667827606,
0.20813313126564026,
-0.008641846477985382,
0.017980942502617836,
-0.037593647837638855,
0.01941327564418316,
0.057439252734184265,
-0.04763064533472061,
0.016491012647747993,
-0.03976176679134369,
0.16152650117874146,
-0.22317251563072205,
0.06391286849975586,
0.2381782829761505,
0.054893773049116135,
0.06830351799726486,
0.043366145342588425,
-0.06744846701622009,
-0.054242994636297226,
-0.04644065350294113,
0.032354533672332764,
0.10105026513338089,
-0.17828331887722015,
0.018951645120978355,
0.06294345110654831,
-0.008843974210321903,
0.06527093052864075,
-0.11712126433849335,
0.013804685324430466,
0.0597820058465004,
-0.05665116757154465,
-0.007801665458828211,
0.04326926916837692,
-0.0345320962369442,
0.07600720226764679,
0.010569492354989052,
0.10673253238201141,
0.06951046735048294,
0.04744328558444977,
-0.07518427073955536,
0.13686802983283997,
-0.0692865327000618,
-0.3092379868030548,
-0.127572700381279,
-0.06615705788135529,
0.04319744557142258,
0.06689934432506561,
0.06950344145298004,
-0.08387348055839539,
-0.036033421754837036,
0.021134721115231514,
0.2363806962966919,
-0.06096379831433296,
0.0844060406088829,
-0.02905281074345112,
-0.013800402171909809,
0.07563075423240662,
-0.10983449220657349,
-0.019218644127249718,
0.04434889927506447,
-0.1925707906484604,
0.07643629610538483,
-0.03938186168670654,
0.02049664966762066,
0.13996657729148865,
-0.01688157208263874,
0.042085740715265274,
-0.02797253429889679,
0.12324564903974533,
-0.08092378824949265,
0.00535998959094286,
0.18507300317287445,
-0.07403182238340378,
0.01754763536155224,
-0.004115515388548374,
-0.012910796329379082,
-0.07135391235351562,
-0.032481953501701355,
-0.052841585129499435,
-0.13625462353229523,
-0.22620746493339539,
-0.03426993638277054,
-0.023705942556262016,
0.08466698229312897,
0.13132691383361816,
0.044104091823101044,
-0.013449521735310555,
0.18806198239326477,
0.04554768651723862,
0.011685481294989586,
-0.06563067436218262,
-0.006566921249032021,
0.1569199562072754,
-0.028630411252379417,
0.08289968967437744,
-0.09097777307033539,
0.016417158767580986,
0.1696184277534485,
0.06539837270975113,
0.17767469584941864,
0.005322551820427179,
-0.012074952013790607,
0.0849456936120987,
-0.0518416203558445,
0.03581321984529495,
0.18154899775981903,
-0.014863184653222561,
-0.035141948610544205,
-0.0180695578455925,
0.0029467218555510044,
-0.14398664236068726,
0.08333835005760193,
0.08272018283605576,
-0.15368486940860748,
-0.01900056190788746,
0.06911125779151917,
0.07040610164403915,
0.01310839131474495,
-0.0014531846391037107,
-0.2018308937549591,
-0.07986483722925186,
-0.03235644847154617,
-0.005880830809473991,
-0.09196450561285019,
0.012660859152674675,
0.1333627700805664,
-0.09552278369665146,
0.03935622423887253,
-0.005986498668789864,
0.0508098229765892,
-0.1565217226743698,
-0.06581403315067291,
0.06651125848293304,
0.03816433623433113,
0.0012971581891179085,
0.10869456082582474,
-0.2513369917869568,
0.12552830576896667,
0.019181791692972183,
-0.02841007336974144,
-0.11370353400707245,
0.040265895426273346,
0.03185497596859932,
0.08774243295192719,
0.10311706364154816,
0.06778435409069061,
-0.09747195243835449,
-0.17716127634048462,
-0.09427031129598618,
0.08380233496427536,
0.037272628396749496,
-0.06687162071466446,
-0.014798899181187153,
-0.06459204107522964,
0.08430155366659164,
0.030552078038454056,
-0.03280051425099373,
-0.06356166303157806,
-0.153102844953537,
0.1020115464925766,
0.07540430873632431,
0.028613658621907234,
-0.09915626794099808,
-0.03422196954488754,
0.07713144272565842,
0.2032470554113388,
-0.051011260598897934,
-0.11281327158212662,
-0.13199029862880707,
0.005820533726364374,
0.0930083766579628,
-0.05835150182247162,
0.08503542095422745,
0.0407184436917305,
0.0068719773553311825,
0.027786796912550926,
-0.12242007255554199,
0.14275403320789337,
-0.09135133773088455,
-0.015148019418120384,
-0.022026438266038895,
0.031877096742391586,
0.043074753135442734,
0.028740225359797478,
0.01982632651925087,
-0.04397444427013397,
0.03413282707333565,
-0.11772806942462921,
0.06808680295944214,
-0.05919970944523811,
-0.15566329658031464,
0.007862882688641548,
0.08405289053916931,
0.11627912521362305,
-0.003845899598672986,
-0.0688529908657074,
0.16400860249996185,
0.06438015401363373,
-0.04787904769182205,
0.13607239723205566,
0.0018609414109960198,
-0.05596918612718582,
-0.274492084980011,
-0.0870756283402443,
0.020341750234365463,
-0.014180101454257965,
0.03659089282155037,
-0.25763893127441406,
0.10406331717967987,
0.03359837085008621,
-0.03164512664079666,
0.14691531658172607,
-0.14714527130126953,
-0.0559237115085125,
0.15473489463329315,
0.07225590199232101,
0.13715128600597382,
-0.09649896621704102,
-0.06884485483169556,
0.008380210027098656,
-0.17087140679359436,
0.1391577273607254,
-0.056480396538972855,
0.0919775441288948,
-0.04782792553305626,
0.0756203681230545,
0.02663440816104412,
-0.014668138697743416,
0.12836933135986328,
-0.06638267636299133,
-0.05765752121806145,
-0.09982502460479736,
0.003945378120988607,
0.16597682237625122,
0.014633056707680225,
0.014355892315506935,
-0.09459388256072998,
0.03304201737046242,
-0.08865458518266678,
-0.10285720974206924,
-0.007453416474163532,
0.08391323685646057,
0.04512952268123627,
-0.1478261798620224,
-0.026160798966884613,
-0.026104552671313286,
-0.05848062038421631,
-0.05318407341837883,
-0.16040097177028656,
-0.0396663174033165,
-0.0014929687604308128,
0.09862960129976273,
0.03872702643275261,
-0.08417590707540512,
-0.10748716443777084,
-0.015793798491358757,
-0.009222745895385742,
0.11115361750125885,
-0.169760599732399,
0.10896401107311249,
0.037520308047533035,
-0.03711053729057312,
0.0639175996184349,
0.0763142853975296,
-0.05906105786561966,
0.010941630229353905,
0.14041095972061157,
-0.10814759880304337,
-0.04832020401954651,
-0.03949355334043503,
0.11901935935020447,
0.010397501289844513,
0.0772794708609581,
0.1686963438987732,
-0.0013749470235779881,
-0.015004092827439308,
-0.011866245418787003,
0.0010002248454838991,
-0.14378531277179718,
0.13761954009532928,
0.029354354366660118,
0.046997085213661194,
-0.05341968685388565,
0.0375833734869957,
-0.0016453824937343597,
-0.09059719741344452,
0.03291232883930206,
-0.08668487519025803,
-0.08608626574277878,
-0.06029241159558296,
-0.03678521886467934,
-0.04815835878252983,
-0.12624645233154297,
-0.13559949398040771,
0.02578362450003624,
-0.08929426223039627,
0.01849690079689026,
0.03219177573919296,
0.040070246905088425,
0.06454487890005112,
-0.009349939413368702,
0.017421506345272064,
-0.033878546208143234,
-0.011991389095783234,
-0.03817388042807579,
0.0413103923201561,
-0.16977597773075104,
0.015390443615615368,
0.04064485803246498,
0.08452312648296356,
-0.08994197100400925,
-0.00984166283160448,
-0.09734984487295151,
0.008239354938268661,
-0.11432304978370667,
-0.012967982329428196,
-0.04695281758904457,
-0.01787249743938446,
0.08656944334506989,
-0.10457446426153183,
-0.11225198209285736,
0.05430060997605324,
-0.0907677412033081,
0.01743757352232933,
0.015605106018483639,
0.03682996705174446,
-0.05013364925980568,
-0.0336209200322628,
0.08597896248102188,
-0.04230877384543419,
0.11610910296440125,
0.10387788712978363,
-0.03369499742984772,
0.03672121837735176,
-0.06274008750915527,
0.021367276087403297,
0.03820199519395828,
0.05633576586842537,
-0.037895362824201584,
-0.10724223405122757,
0.09812603145837784,
0.0009139683097600937,
-0.030524659901857376,
0.014774061739444733,
0.22400270402431488,
-0.018370365723967552,
0.04267747327685356,
-0.08131449669599533,
0.018523113802075386,
0.0005255966098047793,
0.016979437321424484,
0.07573531568050385,
0.13314133882522583,
0.051313187927007675,
-0.05134949833154678,
0.02267463319003582,
-0.11277349293231964,
0.049893368035554886,
0.0072080534882843494,
-0.013608011417090893,
0.2077043354511261,
-0.07526583969593048,
-0.009768731892108917,
-0.003112088656052947,
0.36083564162254333,
-0.034666407853364944,
-0.03376642242074013,
0.000465915392851457,
0.016256744042038918,
0.05648653581738472,
-0.06306079030036926,
0.23824024200439453,
0.028231561183929443,
0.030255554243922234,
-0.04577591270208359,
0.07749976217746735,
0.036635514348745346,
0.01669408567249775,
0.10603845864534378,
-0.05808128044009209,
-0.07760416716337204,
0.03970145806670189,
0.012111656367778778,
-0.05816066265106201,
-0.161248117685318,
-0.09607157856225967,
-0.09987155348062515,
0.03369636833667755,
0.013538738712668419,
0.1808355748653412,
0.09688396751880646,
0.03088225983083248,
0.0339193157851696,
0.04344287887215614,
-0.019781870767474174,
-0.1162072941660881,
-0.10624467581510544,
-0.06749890744686127,
-0.24412725865840912,
-0.02009386569261551,
-0.016805298626422882,
-0.04051859676837921,
0.1113271713256836,
0.001640179194509983,
0.03201226517558098,
0.192895770072937,
-0.03430657461285591,
-0.06153768301010132,
-0.0305166132748127,
-0.044359542429447174,
-0.05417879298329353,
-0.08034614473581314,
-0.0010217109229415655,
-0.004034008365124464,
0.13532304763793945,
0.04256109520792961,
0.013991465792059898,
-0.0719253420829773,
0.05953070893883705,
-0.03242471441626549,
-0.04506436735391617,
-0.1416979283094406,
-0.00007400053436867893,
-0.11387494206428528,
0.00706803984940052,
-0.04959471523761749,
0.003615243826061487,
0.014523904770612717,
0.10057854652404785,
-0.04907883703708649,
-0.15226063132286072,
-0.09844882786273956,
0.08741224557161331,
-0.08303111046552658,
0.043519213795661926,
-0.006024984642863274,
0.00725935772061348,
-0.033455926924943924,
0.17929689586162567,
0.133993461728096,
-0.02445192076265812,
0.04140666127204895,
0.042995233088731766,
0.02013833075761795,
-0.009035882540047169,
0.13636474311351776,
-0.018853701651096344,
0.07535595446825027,
-0.02727932669222355,
-0.11975201964378357,
-0.07198779284954071,
0.014934112317860126,
0.11415768414735794,
0.09386886656284332,
0.014842405915260315,
0.0009056030539795756,
-0.05491631478071213,
0.07425936311483383,
-0.035430487245321274,
-0.03909620642662048,
0.003171120071783662,
0.002464970573782921,
-0.04410826787352562,
-0.023154687136411667,
0.07525777816772461,
-0.04212452098727226,
0.02803291380405426,
-0.013432411476969719,
-0.03930728882551193,
-0.018439652398228645,
0.105523481965065,
-0.26596778631210327,
0.03616221621632576,
0.09113956242799759,
-0.0059331245720386505,
0.23815934360027313,
-0.04731179401278496,
0.06976741552352905,
0.04006616771221161,
0.02872423641383648,
-0.1250135898590088,
0.019844181835651398,
-0.01698189787566662,
-0.10425154864788055,
-0.049639202654361725,
-0.02519950456917286,
-0.05851484090089798,
0.0033931813668459654,
0.020182520151138306,
-0.08656173944473267,
-0.004628954920917749,
0.04170332849025726,
0.0014320964692160487,
0.008981285616755486,
-0.08083963394165039,
-0.09752882272005081,
0.13121864199638367,
0.01053079403936863,
0.0032636222895234823,
-0.05401932820677757,
-0.132967010140419,
0.07453274726867676,
0.031301334500312805,
0.09914060682058334,
-0.03052557446062565,
-0.07773081958293915,
-0.08458292484283447,
0.004530272446572781,
0.008183400146663189,
-0.12061181664466858,
-0.004628451075404882,
-0.0405157208442688,
-0.032058317214250565,
-0.045705486088991165,
0.12546095252037048,
0.0761043131351471,
0.07262150943279266,
-0.02546737901866436,
-0.015054026618599892,
0.006061524618417025,
0.08699921518564224,
-0.1896948367357254,
-0.048750173300504684
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# result
This model is a fine-tuned version of [microsoft/xtremedistil-l6-h384-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h384-uncased) on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
### Training results
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
| {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/xtremedistil-l6-h384-uncased", "model-index": [{"name": "result", "results": []}]} | question-answering | JingqiuChen/Jingqiu_H6_NLP4WEB | [
"transformers",
"safetensors",
"bert",
"question-answering",
"generated_from_trainer",
"base_model:microsoft/xtremedistil-l6-h384-uncased",
"license:mit",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:49:27+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #question-answering #generated_from_trainer #base_model-microsoft/xtremedistil-l6-h384-uncased #license-mit #endpoints_compatible #region-us
|
# result
This model is a fine-tuned version of microsoft/xtremedistil-l6-h384-uncased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
### Training results
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
| [
"# result\n\nThis model is a fine-tuned version of microsoft/xtremedistil-l6-h384-uncased on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 3e-05\n- train_batch_size: 12\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 2.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #bert #question-answering #generated_from_trainer #base_model-microsoft/xtremedistil-l6-h384-uncased #license-mit #endpoints_compatible #region-us \n",
"# result\n\nThis model is a fine-tuned version of microsoft/xtremedistil-l6-h384-uncased on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 3e-05\n- train_batch_size: 12\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 2.0",
"### Training results",
"### Framework versions\n\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.0"
] | [
63,
37,
6,
12,
8,
3,
90,
4,
38
] | [
"passage: TAGS\n#transformers #safetensors #bert #question-answering #generated_from_trainer #base_model-microsoft/xtremedistil-l6-h384-uncased #license-mit #endpoints_compatible #region-us \n# result\n\nThis model is a fine-tuned version of microsoft/xtremedistil-l6-h384-uncased on an unknown dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 3e-05\n- train_batch_size: 12\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 2.0### Training results### Framework versions\n\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.0"
] | [
-0.1100233867764473,
0.10157838463783264,
-0.001336683752015233,
0.06775525212287903,
0.1502802073955536,
0.022166116163134575,
0.11974061280488968,
0.09736083447933197,
-0.10983449220657349,
0.07483021169900894,
0.07829976081848145,
0.061494339257478714,
0.022762900218367577,
0.12222829461097717,
-0.053140655159950256,
-0.20922744274139404,
0.037464793771505356,
-0.012650701217353344,
-0.08387602865695953,
0.08551066368818283,
0.08780508488416672,
-0.12302927672863007,
0.06475374847650528,
0.01572588086128235,
-0.15151791274547577,
0.03178597241640091,
-0.012007241137325764,
-0.03502660617232323,
0.09048603475093842,
0.01763381063938141,
0.11941500008106232,
0.026656998321413994,
0.13676166534423828,
-0.22244788706302643,
0.0006460099830292165,
0.08029286563396454,
0.020938942208886147,
0.05371227487921715,
0.03857685253024101,
-0.0047077639028429985,
0.08827848732471466,
-0.11830032616853714,
0.0831248015165329,
0.039185479283332825,
-0.07169103622436523,
-0.17632755637168884,
-0.10082343220710754,
0.04645292088389397,
0.08647028356790543,
0.11064201593399048,
-0.005390793085098267,
0.16295774281024933,
-0.09920129925012589,
0.06867308169603348,
0.19238239526748657,
-0.27927693724632263,
-0.06952715665102005,
0.06340804696083069,
0.04756554961204529,
0.05742431432008743,
-0.10665712505578995,
-0.010308590717613697,
0.08268272131681442,
0.02684202790260315,
0.07633490115404129,
0.002086851978674531,
-0.04402390867471695,
-0.013550849631428719,
-0.13657398521900177,
-0.001373912557028234,
0.1742737591266632,
0.07585020363330841,
-0.06095794588327408,
-0.05388680472970009,
-0.04518793150782585,
-0.07380596548318863,
0.002742512384429574,
-0.0562618151307106,
0.047203779220581055,
-0.057342447340488434,
-0.07904758304357529,
-0.03488396480679512,
-0.08505410701036453,
-0.07735636830329895,
0.01417904905974865,
0.12524248659610748,
0.05072569102048874,
0.015173256397247314,
-0.02842879481613636,
0.10694990307092667,
0.0031963903456926346,
-0.10967931896448135,
-0.0345299206674099,
-0.000670919194817543,
-0.03940732404589653,
-0.054387569427490234,
-0.05636247247457504,
-0.007622897159308195,
0.013477453030645847,
0.1279722899198532,
-0.10117797553539276,
0.05317322909832001,
0.006838162429630756,
0.00656947260722518,
-0.06323514878749847,
0.10640823841094971,
-0.05068695917725563,
-0.020143132656812668,
0.008556184358894825,
0.12007875740528107,
0.01942671276628971,
0.005302614066749811,
-0.07011110335588455,
0.00011812899901997298,
0.08604612946510315,
0.050272077322006226,
-0.08084525913000107,
0.038050856441259384,
-0.039240043610334396,
-0.0060957674868404865,
-0.02255968749523163,
-0.11618974804878235,
0.03688511997461319,
0.019164349883794785,
-0.0771407037973404,
-0.04183637723326683,
0.05338122695684433,
0.015307573601603508,
-0.007795032579451799,
0.0830266922712326,
-0.09282942116260529,
0.0029475181363523006,
-0.10497783124446869,
-0.08239433914422989,
0.004576064180582762,
-0.04220793768763542,
-0.006936247926205397,
-0.08824129402637482,
-0.19225189089775085,
-0.04774055629968643,
0.03596675395965576,
-0.017686624079942703,
0.009964743629097939,
-0.07085520774126053,
-0.08092373609542847,
-0.006838273722678423,
-0.00763680087402463,
0.06275779753923416,
-0.04699302837252617,
0.07896595448255539,
0.021579958498477936,
0.03216654062271118,
-0.01717778667807579,
0.02428487129509449,
-0.08974020183086395,
0.029317833483219147,
-0.09162541478872299,
0.04343835636973381,
-0.09089909493923187,
0.04097209498286247,
-0.06746629625558853,
-0.1199076846241951,
-0.021628109738230705,
0.0007564169936813414,
0.07198667526245117,
0.11437219381332397,
-0.17823457717895508,
-0.017542609944939613,
0.17923606932163239,
-0.10196512937545776,
-0.1267477124929428,
0.0783412829041481,
-0.044365763664245605,
0.07171628624200821,
0.06075051799416542,
0.1314420849084854,
0.0674872100353241,
-0.1337796300649643,
-0.026458967477083206,
-0.03375193849205971,
0.061281777918338776,
0.028355712071061134,
0.03982286527752876,
-0.021702159196138382,
0.004640668630599976,
0.010738306678831577,
-0.07831620424985886,
-0.033628515899181366,
-0.10708601772785187,
-0.08806704729795456,
-0.05248462036252022,
-0.11509408056735992,
0.03396565839648247,
0.03128863126039505,
0.060530513525009155,
-0.09964371472597122,
-0.1027621477842331,
0.1504138559103012,
0.122909314930439,
-0.07445072382688522,
0.009558753110468388,
-0.08597283065319061,
0.027001651003956795,
-0.014464777894318104,
-0.03539710119366646,
-0.16722452640533447,
-0.1257695108652115,
0.01896524243056774,
-0.04972109571099281,
0.00646549928933382,
0.02969273366034031,
0.05489793419837952,
0.10091498494148254,
-0.05797979235649109,
-0.037659890949726105,
-0.11092305183410645,
0.02405393123626709,
-0.08850107342004776,
-0.18365879356861115,
-0.036570966243743896,
-0.01619049347937107,
0.16300641000270844,
-0.2651507556438446,
0.04506601393222809,
-0.022324832156300545,
0.13480040431022644,
0.032493606209754944,
-0.0502866692841053,
-0.02886812761425972,
0.057298943400382996,
-0.014976131729781628,
-0.07229297608137131,
0.04368291422724724,
-0.00004626777081284672,
-0.0963798388838768,
-0.10094194114208221,
-0.16040967404842377,
0.10019871592521667,
0.09109687805175781,
0.018176423385739326,
-0.0805492177605629,
0.011988979764282703,
-0.06780026108026505,
-0.04235471785068512,
-0.08069455623626709,
-0.01158544048666954,
0.11377478390932083,
-0.0182722769677639,
0.12025070935487747,
-0.0690264031291008,
-0.041826359927654266,
-0.003841280471533537,
-0.02614027075469494,
0.001278568059206009,
0.06008823961019516,
0.05102485045790672,
-0.1236521378159523,
0.09494352340698242,
0.11208874732255936,
-0.07781390100717545,
0.14306475222110748,
-0.048614658415317535,
-0.07085676491260529,
-0.025334006175398827,
0.024106990545988083,
0.005319943185895681,
0.1309889405965805,
-0.07483011484146118,
0.03176594153046608,
0.00020590188796631992,
0.031252942979335785,
0.03955388814210892,
-0.20921921730041504,
-0.018854651600122452,
0.013054382055997849,
-0.040497563779354095,
-0.059172727167606354,
-0.019565802067518234,
0.018861178308725357,
0.0746496319770813,
0.000729883904568851,
-0.0007349010556936264,
0.029461227357387543,
-0.01704441010951996,
-0.1081000342965126,
0.19347348809242249,
-0.12778839468955994,
-0.10221162438392639,
-0.10089597851037979,
0.08014550805091858,
-0.05166269466280937,
-0.014570514671504498,
0.046719200909137726,
-0.08346527814865112,
-0.04763203114271164,
-0.10009925067424774,
-0.030647963285446167,
0.00478872237727046,
-0.01704658754169941,
0.06843530386686325,
0.027097387239336967,
0.11750846356153488,
-0.13730546832084656,
0.005681621842086315,
-0.036780696362257004,
-0.1182422935962677,
0.014873534440994263,
0.03784789517521858,
0.11715935915708542,
0.09582863003015518,
-0.020437143743038177,
0.019809577614068985,
-0.025742536410689354,
0.2234279364347458,
-0.05131959542632103,
-0.04959119111299515,
0.11657567322254181,
0.001699973945505917,
0.046702902764081955,
0.09824081510305405,
0.038319386541843414,
-0.12938697636127472,
0.05009213462471962,
0.07676774263381958,
-0.007856173440814018,
-0.2255735844373703,
-0.031158339232206345,
-0.018659641966223717,
-0.06501501053571701,
0.05855230242013931,
0.030265241861343384,
0.004991002846509218,
0.03836241737008095,
-0.012193611823022366,
0.019833795726299286,
-0.009349670261144638,
0.07840275019407272,
0.06267929822206497,
0.03528571128845215,
0.10095593333244324,
-0.03221847862005234,
-0.014052730053663254,
0.044309962540864944,
-0.036069054156541824,
0.29095935821533203,
-0.005847201216965914,
0.029443752020597458,
0.08483079075813293,
0.15782208740711212,
-0.02935142256319523,
0.03942127525806427,
0.02493217960000038,
-0.028835631906986237,
0.020150629803538322,
-0.07179763913154602,
-0.031497206538915634,
0.046822212636470795,
-0.06939256191253662,
0.09264031797647476,
-0.12831023335456848,
0.06886351853609085,
0.05406556650996208,
0.23120594024658203,
0.04505274444818497,
-0.295708030462265,
-0.10062173753976822,
0.0063294353894889355,
-0.014753395691514015,
-0.04483466222882271,
0.02123469114303589,
0.13650764524936676,
-0.11468765139579773,
0.06051794812083244,
-0.05616956204175949,
0.08045808225870132,
0.027989575639367104,
0.029109422117471695,
0.04245557636022568,
0.11597161740064621,
-0.012038223445415497,
0.07131119072437286,
-0.22093196213245392,
0.23121243715286255,
0.010715928860008717,
0.15028683841228485,
-0.024640407413244247,
-0.005763052962720394,
0.031010732054710388,
0.10587822645902634,
0.08983304351568222,
-0.0036633056588470936,
-0.041137754917144775,
-0.15955589711666107,
-0.031153837218880653,
0.0607491172850132,
0.13252437114715576,
-0.014946862123906612,
0.10090567171573639,
-0.03229662403464317,
0.021737968549132347,
0.06938403099775314,
-0.03952513635158539,
-0.21214647591114044,
-0.0935242772102356,
0.0017451019957661629,
-0.00374680757522583,
0.012281161732971668,
-0.11822846531867981,
-0.1030329242348671,
-0.047858431935310364,
0.15740293264389038,
-0.016698604449629784,
-0.01581372320652008,
-0.11495556682348251,
0.09432096779346466,
0.07797477394342422,
-0.049046169966459274,
0.027364056557416916,
0.03718329593539238,
0.09644446521997452,
0.04456980898976326,
-0.05080975592136383,
0.06009163707494736,
-0.07807669788599014,
-0.18749256432056427,
-0.0590791217982769,
0.11171974241733551,
0.06733287870883942,
0.03924653306603432,
0.0037782255094498396,
0.006729655899107456,
0.028840890154242516,
-0.08930792659521103,
0.006807786878198385,
0.09925849735736847,
0.092893585562706,
0.0688103660941124,
-0.09749887138605118,
0.0061364625580608845,
-0.03739521652460098,
-0.038172196596860886,
0.10088532418012619,
0.2517474591732025,
-0.08251257985830307,
0.016991255804896355,
0.04875204712152481,
-0.07596388459205627,
-0.18429063260555267,
0.10060998797416687,
0.10200601816177368,
0.016441870480775833,
0.06201722472906113,
-0.14057831466197968,
0.11601965129375458,
0.13270126283168793,
-0.022300805896520615,
0.07299040257930756,
-0.29430150985717773,
-0.13668489456176758,
0.06799786537885666,
0.15417054295539856,
0.057577818632125854,
-0.14089800417423248,
-0.03078075684607029,
-0.03886780887842178,
-0.14321079850196838,
0.10436634719371796,
-0.1485746055841446,
0.09602867066860199,
0.003438860410824418,
0.05789640545845032,
0.016419192776083946,
-0.04188322648406029,
0.15145283937454224,
0.0072928559966385365,
0.11349108070135117,
-0.04299430921673775,
0.03342834487557411,
0.08354214578866959,
-0.06826967746019363,
0.03866492584347725,
-0.02349180541932583,
0.07517404854297638,
-0.0637412741780281,
-0.017772119492292404,
-0.07663403451442719,
0.0654297024011612,
-0.07059130072593689,
-0.05531662702560425,
-0.0430615171790123,
0.05658204108476639,
0.0660674124956131,
-0.02183731272816658,
0.06430451571941376,
0.0056783524341881275,
0.14607185125350952,
0.07229021191596985,
0.1058175265789032,
-0.024062372744083405,
-0.02812633290886879,
0.0008967705653049052,
-0.02138146013021469,
0.06619291752576828,
-0.10405407100915909,
0.040393467992544174,
0.12958404421806335,
0.04029505327343941,
0.15477605164051056,
0.053899556398391724,
-0.05420371890068054,
0.010147729888558388,
0.056979674845933914,
-0.10510143637657166,
-0.16971014440059662,
-0.008504738099873066,
-0.027630988508462906,
-0.12212739139795303,
0.06869889795780182,
0.099204421043396,
-0.0738690048456192,
0.009555096738040447,
-0.03293631225824356,
0.012864281423389912,
-0.03943236917257309,
0.18032518029212952,
0.05239362269639969,
0.05931781232357025,
-0.06781487166881561,
0.1302301287651062,
0.02380833588540554,
-0.05850444734096527,
0.03724700212478638,
0.027455495670437813,
-0.09983523190021515,
-0.019390782341361046,
0.0399777889251709,
0.17435172200202942,
-0.04534531757235527,
-0.07000544667243958,
-0.12174674868583679,
-0.09534619748592377,
0.018916726112365723,
0.1401289701461792,
0.05748417228460312,
-0.009494973346590996,
-0.002787782344967127,
0.052028756588697433,
-0.1350756734609604,
0.0995161309838295,
0.03790472075343132,
0.07143501192331314,
-0.1704200953245163,
0.14469772577285767,
0.025497950613498688,
0.009081568568944931,
-0.008045361377298832,
0.03629128262400627,
-0.10524717718362808,
-0.017255643382668495,
-0.16649740934371948,
-0.015307345427572727,
-0.03342841565608978,
-0.007826404646039009,
0.010910844430327415,
-0.048237886279821396,
-0.06603053957223892,
0.06464306265115738,
-0.06999139487743378,
-0.053164441138505936,
0.02947462722659111,
0.055077750235795975,
-0.13222245872020721,
-0.00941269751638174,
0.01767701655626297,
-0.09274306893348694,
0.05741904303431511,
0.05664088577032089,
0.02683587372303009,
0.055920179933309555,
-0.14709866046905518,
0.0010909136617556214,
0.04812614992260933,
0.022150885313749313,
0.05405211076140404,
-0.08322857320308685,
-0.029010938480496407,
-0.009081031195819378,
0.05568614602088928,
0.014516890048980713,
0.0656852051615715,
-0.10777918994426727,
-0.03388381004333496,
-0.050323229283094406,
-0.022805562242865562,
-0.05416230112314224,
0.01580745540559292,
0.0761084333062172,
0.02522149309515953,
0.18843626976013184,
-0.10027749836444855,
0.025595685467123985,
-0.1926531046628952,
-0.03807087242603302,
0.004435187671333551,
-0.024601204320788383,
-0.08008170872926712,
-0.01113832462579012,
0.06957503408193588,
-0.06990835070610046,
0.09301309287548065,
-0.059143513441085815,
0.08884172886610031,
0.036942631006240845,
-0.09406544268131256,
-0.012756569311022758,
0.008053954690694809,
0.21219970285892487,
0.03645271807909012,
-0.0003105232899542898,
0.049866512417793274,
-0.0111162681132555,
0.055817145854234695,
0.001961897127330303,
0.23255957663059235,
0.15802909433841705,
-0.07846105843782425,
0.07997274398803711,
0.06977925449609756,
-0.0945875495672226,
-0.14641229808330536,
0.06394515931606293,
-0.007759940344840288,
0.08728967607021332,
-0.040013253688812256,
0.12388858944177628,
0.133086159825325,
-0.16219377517700195,
0.02013394795358181,
-0.07590128481388092,
-0.10417352616786957,
-0.12329240888357162,
-0.007119464688003063,
-0.08580254763364792,
-0.14862418174743652,
0.03463798016309738,
-0.13313235342502594,
0.030373262241482735,
0.07781659066677094,
0.006502335891127586,
0.007890576496720314,
0.20572271943092346,
-0.056889042258262634,
0.028550466522574425,
0.021732376888394356,
-0.0031598201021552086,
-0.015232840552926064,
-0.04498402029275894,
-0.07126883417367935,
0.058476053178310394,
-0.019844600930809975,
0.06093661114573479,
-0.050524428486824036,
-0.03560876473784447,
0.027212638407945633,
-0.0002896978403441608,
-0.0549362450838089,
0.03127007186412811,
0.03325118497014046,
0.03651205450296402,
0.04022907093167305,
0.058443184942007065,
-0.008543466217815876,
-0.023719724267721176,
0.26010408997535706,
-0.09018593281507492,
-0.09542331099510193,
-0.13724066317081451,
0.23545923829078674,
0.06157183647155762,
0.010490873828530312,
0.05362444370985031,
-0.13194863498210907,
0.02457851730287075,
0.15570054948329926,
0.1377951204776764,
-0.07090245187282562,
-0.008484863676130772,
-0.021864959970116615,
-0.02349115163087845,
-0.08278875052928925,
0.09798528254032135,
0.10745646059513092,
0.037513695657253265,
-0.030862707644701004,
-0.030348243191838264,
-0.017209913581609726,
-0.01108712051063776,
-0.07495089620351791,
0.04638238996267319,
0.015103458426892757,
0.009596860967576504,
-0.030295293778181076,
0.059253059327602386,
0.018833287060260773,
-0.1789458692073822,
0.06536998599767685,
-0.13175716996192932,
-0.14956073462963104,
-0.02172730676829815,
0.08088251203298569,
-0.029009107500314713,
0.05042801797389984,
-0.03412759304046631,
-0.02404467761516571,
0.13785392045974731,
-0.01829497702419758,
-0.0324099138379097,
-0.09886292368173599,
0.053738925606012344,
-0.07288268953561783,
0.23454593122005463,
-0.00683304900303483,
0.0683123767375946,
0.106732077896595,
0.025534650310873985,
-0.09947600215673447,
0.0971020832657814,
0.06382070481777191,
-0.08159777522087097,
0.015179029665887356,
0.12743833661079407,
-0.055866606533527374,
0.12256321310997009,
0.04393451660871506,
-0.1737045794725418,
0.000004897104190604296,
0.026169823482632637,
-0.07731817662715912,
-0.06818386912345886,
-0.0005991476937197149,
-0.06211473047733307,
0.1436750590801239,
0.2025197446346283,
-0.047457218170166016,
0.03287782892584801,
-0.049667712301015854,
0.0623396597802639,
0.05496763437986374,
0.08442634344100952,
-0.005024905316531658,
-0.2396300733089447,
0.05194876343011856,
0.02045808918774128,
-0.008956190198659897,
-0.24687406420707703,
-0.08641873300075531,
0.04187929257750511,
-0.057744525372982025,
-0.04728369787335396,
0.09276445209980011,
0.09639917314052582,
0.04848640412092209,
-0.04841297119855881,
-0.1417265087366104,
-0.06945059448480606,
0.16820208728313446,
-0.12471645325422287,
-0.08567792922258377
] |
null | null | null | import json
import sagemaker
import boto3
from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri
try:
role = sagemaker.get_execution_role()
except ValueError:
iam = boto3.client('iam')
role = iam.get_role(RoleName='sagemaker_execution_role')['Role']['Arn']
# Hub Model configuration. https://huggingface.co/models
hub = {
'HF_MODEL_ID':'mistralai/Mixtral-8x7B-Instruct-v0.1',
'SM_NUM_GPUS': json.dumps(8)
}
# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
image_uri=get_huggingface_llm_image_uri("huggingface",version="1.1.0"),
env=hub,
role=role,
)
# deploy model to SageMaker Inference
predictor = huggingface_model.deploy(
initial_instance_count=1,
instance_type="ml.g5.48xlarge",
container_startup_health_check_timeout=300,
)
# send request
predictor.predict({
"inputs": "Digital Deviance Detective",
}) | {} | null | Vicious-Vineyards/Q2 | [
"region:us"
] | 2024-02-09T01:49:35+00:00 | [] | [] | TAGS
#region-us
| import json
import sagemaker
import boto3
from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri
try:
role = sagemaker.get_execution_role()
except ValueError:
iam = URL('iam')
role = iam.get_role(RoleName='sagemaker_execution_role')['Role']['Arn']
# Hub Model configuration. URL
hub = {
'HF_MODEL_ID':'mistralai/Mixtral-8x7B-Instruct-v0.1',
'SM_NUM_GPUS': URL(8)
}
# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
image_uri=get_huggingface_llm_image_uri("huggingface",version="1.1.0"),
env=hub,
role=role,
)
# deploy model to SageMaker Inference
predictor = huggingface_model.deploy(
initial_instance_count=1,
instance_type="ml.g5.48xlarge",
container_startup_health_check_timeout=300,
)
# send request
predictor.predict({
"inputs": "Digital Deviance Detective",
}) | [
"# Hub Model configuration. URL\nhub = {\n\t'HF_MODEL_ID':'mistralai/Mixtral-8x7B-Instruct-v0.1',\n\t'SM_NUM_GPUS': URL(8)\n}",
"# create Hugging Face Model Class\nhuggingface_model = HuggingFaceModel(\n\timage_uri=get_huggingface_llm_image_uri(\"huggingface\",version=\"1.1.0\"),\n\tenv=hub,\n\trole=role, \n)",
"# deploy model to SageMaker Inference\npredictor = huggingface_model.deploy(\n\tinitial_instance_count=1,\n\tinstance_type=\"ml.g5.48xlarge\",\n\tcontainer_startup_health_check_timeout=300,\n )",
"# send request\npredictor.predict({\n\t\"inputs\": \"Digital Deviance Detective\",\n})"
] | [
"TAGS\n#region-us \n",
"# Hub Model configuration. URL\nhub = {\n\t'HF_MODEL_ID':'mistralai/Mixtral-8x7B-Instruct-v0.1',\n\t'SM_NUM_GPUS': URL(8)\n}",
"# create Hugging Face Model Class\nhuggingface_model = HuggingFaceModel(\n\timage_uri=get_huggingface_llm_image_uri(\"huggingface\",version=\"1.1.0\"),\n\tenv=hub,\n\trole=role, \n)",
"# deploy model to SageMaker Inference\npredictor = huggingface_model.deploy(\n\tinitial_instance_count=1,\n\tinstance_type=\"ml.g5.48xlarge\",\n\tcontainer_startup_health_check_timeout=300,\n )",
"# send request\npredictor.predict({\n\t\"inputs\": \"Digital Deviance Detective\",\n})"
] | [
6,
51,
58,
63,
25
] | [
"passage: TAGS\n#region-us \n# Hub Model configuration. URL\nhub = {\n\t'HF_MODEL_ID':'mistralai/Mixtral-8x7B-Instruct-v0.1',\n\t'SM_NUM_GPUS': URL(8)\n}# create Hugging Face Model Class\nhuggingface_model = HuggingFaceModel(\n\timage_uri=get_huggingface_llm_image_uri(\"huggingface\",version=\"1.1.0\"),\n\tenv=hub,\n\trole=role, \n)# deploy model to SageMaker Inference\npredictor = huggingface_model.deploy(\n\tinitial_instance_count=1,\n\tinstance_type=\"ml.g5.48xlarge\",\n\tcontainer_startup_health_check_timeout=300,\n )# send request\npredictor.predict({\n\t\"inputs\": \"Digital Deviance Detective\",\n})"
] | [
-0.06220461055636406,
-0.024007881060242653,
-0.0015265985857695341,
0.017991967499256134,
0.14303548634052277,
0.08724305033683777,
0.18058177828788757,
0.04993319511413574,
0.24824069440364838,
0.08053111284971237,
0.10977791994810104,
-0.05994778499007225,
0.06290684640407562,
0.15046268701553345,
-0.006538306828588247,
-0.11599808931350708,
0.05671873316168785,
-0.055326513946056366,
0.015311429277062416,
0.03620905056595802,
0.04213178902864456,
-0.007201308850198984,
0.16450135409832,
-0.00037456394056789577,
-0.2023169845342636,
0.013970321044325829,
-0.01755417324602604,
0.12987373769283295,
0.026872839778661728,
0.0022461179178208113,
0.053356438875198364,
0.0039420402608811855,
0.05298958346247673,
-0.16353954374790192,
0.021362077444791794,
0.04358620569109917,
-0.007803806569427252,
0.04958571121096611,
0.06718911230564117,
-0.02493107318878174,
0.08783075958490372,
-0.10371170192956924,
-0.015630343928933144,
0.05268266424536705,
-0.06367983669042587,
0.05340339243412018,
-0.11852739751338959,
0.11069271713495255,
0.06906165927648544,
0.0149086220189929,
0.016706570982933044,
0.1256505846977234,
-0.1101420596241951,
0.054258815944194794,
0.10363589972257614,
-0.07760602980852127,
0.01125942263752222,
0.13121359050273895,
-0.0010537725174799562,
-0.023191921412944794,
-0.05181075260043144,
0.04732026532292366,
0.01586817391216755,
0.00958319939672947,
-0.03424675762653351,
-0.04400501772761345,
-0.04016321524977684,
0.00658962968736887,
-0.07019292563199997,
-0.05212943255901337,
0.21192322671413422,
0.11166463792324066,
-0.05230966582894325,
-0.04301726445555687,
-0.041720882058143616,
0.10536252707242966,
-0.04192482680082321,
0.02719983085989952,
0.047278910875320435,
0.012131982482969761,
0.001394121558405459,
-0.04357638955116272,
-0.014690215699374676,
-0.13881240785121918,
-0.03086659125983715,
0.0860166847705841,
-0.0031210046727210283,
0.04974177107214928,
-0.09157025814056396,
0.042807165533304214,
-0.0371786393225193,
-0.07762576639652252,
-0.04281257838010788,
-0.05907079949975014,
-0.06631215661764145,
0.03800682723522186,
-0.03472594916820526,
0.038497865200042725,
0.15082310140132904,
0.07053961604833603,
-0.10916709154844284,
0.0640534833073616,
-0.030148720368742943,
0.05616339296102524,
0.016693854704499245,
0.1331447809934616,
-0.10503385961055756,
-0.0990409106016159,
0.03356111794710159,
0.11500857025384903,
0.11326443403959274,
-0.01909974403679371,
-0.04369693249464035,
-0.08198953419923782,
0.0002535665116738528,
-0.014311748556792736,
-0.0127281304448843,
0.12990844249725342,
-0.018700120970606804,
-0.03677878528833389,
0.2265034168958664,
-0.03191067650914192,
0.009725447744131088,
0.07404735684394836,
-0.0651734322309494,
-0.029329678043723106,
0.1633012443780899,
-0.019774803891777992,
-0.05789204314351082,
-0.054299093782901764,
-0.13243481516838074,
0.04552774876356125,
-0.007082196418195963,
-0.07137688249349594,
0.015712397173047066,
-0.1483343094587326,
0.01289081759750843,
-0.1104125827550888,
-0.1313028633594513,
-0.032597821205854416,
0.0032878906931728125,
-0.031074436381459236,
0.06943487375974655,
-0.06110731139779091,
-0.01741691678762436,
-0.07109913229942322,
0.04995018616318703,
-0.12253344058990479,
-0.07763123512268066,
-0.04393482580780983,
-0.013212951831519604,
0.09745347499847412,
-0.08478136360645294,
0.01716889813542366,
-0.07613267004489899,
0.09684182703495026,
-0.1330184042453766,
0.10726524889469147,
-0.10449811071157455,
0.18562817573547363,
-0.026258694007992744,
0.04337369650602341,
-0.0051714396104216576,
0.0278952494263649,
0.11490040272474289,
0.23169702291488647,
-0.0028790475334972143,
-0.06599953025579453,
0.18308943510055542,
-0.06768254935741425,
-0.26037272810935974,
0.08332501351833344,
0.022026706486940384,
0.00303209968842566,
0.021868852898478508,
0.25591474771499634,
0.036908697336912155,
-0.22515679895877838,
0.049084823578596115,
0.06200861185789108,
-0.15778903663158417,
-0.0909641683101654,
-0.031022710725665092,
-0.025727592408657074,
-0.191234290599823,
0.08302592486143112,
-0.10002584755420685,
0.1949676126241684,
-0.011425377801060677,
0.0025925603695213795,
-0.058773815631866455,
-0.11499633640050888,
-0.08050894737243652,
-0.029913876205682755,
0.0003405210445635021,
-0.005555808078497648,
0.010571245104074478,
-0.023102058097720146,
0.1114126592874527,
-0.027889195829629898,
-0.0030432194471359253,
-0.02504040114581585,
0.08760194480419159,
-0.052092041820287704,
0.016606638208031654,
-0.04590684920549393,
-0.13960865139961243,
0.009753872640430927,
0.04759156331419945,
0.024957306683063507,
-0.022903595119714737,
0.07104161381721497,
0.030337631702423096,
0.03732368350028992,
-0.08987931907176971,
0.09241186827421188,
0.0021449567284435034,
-0.021959636360406876,
-0.10108586400747299,
0.014071614481508732,
-0.06278010457754135,
0.2099045217037201,
-0.08598534762859344,
0.02073035202920437,
-0.1650128960609436,
0.07218276709318161,
0.027904747053980827,
-0.022885538637638092,
0.100140780210495,
-0.08220674097537994,
0.024970708414912224,
-0.05784239619970322,
0.05618280544877052,
0.01049883384257555,
-0.05948310345411301,
0.08641716837882996,
-0.14089098572731018,
-0.03849571570754051,
0.08436381816864014,
0.009080869145691395,
-0.039837151765823364,
-0.15261319279670715,
-0.07553956657648087,
0.019968127831816673,
0.0746673196554184,
-0.006019489839673042,
-0.04062884673476219,
0.007626963313668966,
0.09018929302692413,
-0.044555019587278366,
0.012389381416141987,
0.02665906958281994,
-0.09391172975301743,
-0.11406704038381577,
0.024330629035830498,
0.02575824409723282,
-0.03162810578942299,
-0.012483627535402775,
-0.00971048604696989,
-0.07741191238164902,
0.16935916244983673,
0.021490272134542465,
-0.025437036529183388,
-0.0409587100148201,
0.0743643194437027,
-0.02924320288002491,
0.10461744666099548,
-0.2093380242586136,
-0.03442620486021042,
0.038428399711847305,
-0.04757166653871536,
0.09726627916097641,
-0.08953993767499924,
-0.03279406204819679,
-0.06872551888227463,
-0.052821993827819824,
-0.08524879068136215,
0.08197898417711258,
-0.019767720252275467,
0.02069408819079399,
-0.001518041011877358,
-0.022152045741677284,
0.022794479504227638,
-0.03899794816970825,
-0.12483494728803635,
0.12756377458572388,
-0.07196325063705444,
-0.1465165913105011,
-0.14628742635250092,
-0.07721355557441711,
-0.22195756435394287,
0.023930508643388748,
-0.020111272111535072,
-0.0975799635052681,
-0.04947112873196602,
-0.14211511611938477,
0.011233190074563026,
0.10851307213306427,
-0.05221479386091232,
-0.00680947070941329,
-0.0007326441118493676,
0.13088896870613098,
-0.08060195297002792,
-0.07296112179756165,
-0.09509091079235077,
0.05344953387975693,
0.058969322592020035,
-0.12049707025289536,
0.09676598012447357,
0.10364140570163727,
0.014740598388016224,
0.08962327986955643,
0.057904910296201706,
0.2740342915058136,
0.012823648750782013,
0.05702541023492813,
0.13217197358608246,
0.0815528854727745,
0.07145947962999344,
0.1818370223045349,
-0.004174706060439348,
-0.08897809684276581,
0.05153525993227959,
0.01919877529144287,
-0.010308346711099148,
-0.06590402871370316,
-0.11228769272565842,
-0.0977349504828453,
-0.03976241871714592,
0.012431987561285496,
0.041308075189590454,
0.05753125622868538,
0.08662274479866028,
0.005639331415295601,
0.0099723432213068,
-0.04219783470034599,
0.06240340694785118,
-0.03972768038511276,
-0.02440180443227291,
-0.004479800816625357,
-0.038006942719221115,
-0.014918661676347256,
0.06250403821468353,
0.021077636629343033,
0.12217399477958679,
-0.057593002915382385,
-0.09411094337701797,
0.09868121147155762,
0.0674445629119873,
-0.0273894090205431,
0.046272918581962585,
0.008800333365797997,
-0.062869593501091,
0.011477738618850708,
-0.0578436404466629,
-0.11771940439939499,
0.0388277992606163,
0.04378867149353027,
-0.049097687005996704,
-0.059046536684036255,
0.031232820823788643,
0.05300648882985115,
0.00806077104061842,
0.10104645043611526,
-0.29654550552368164,
0.0010501613141968846,
0.051866140216588974,
0.16859856247901917,
-0.08970057964324951,
-0.0312113668769598,
0.04904194176197052,
0.02076881378889084,
0.08935332298278809,
0.04483316093683243,
0.09050222486257553,
0.06874233484268188,
0.04695536568760872,
-0.05994776636362076,
0.1867087334394455,
-0.01298343762755394,
-0.006462328601628542,
-0.003504440886899829,
0.15576963126659393,
0.0005353700835257769,
0.02284245938062668,
-0.008231554180383682,
0.014565495774149895,
0.12414928525686264,
0.273855984210968,
0.09100920706987381,
0.09213775396347046,
0.025145189836621284,
-0.1404174566268921,
0.01573091931641102,
0.034339550882577896,
0.014055597595870495,
0.040368083864450455,
0.019119231030344963,
-0.033123716711997986,
-0.04685988277196884,
0.00897515844553709,
0.07400821894407272,
-0.177103653550148,
-0.07428637146949768,
-0.05260228365659714,
-0.02200334146618843,
-0.03864988684654236,
-0.022902261465787888,
0.06117737665772438,
-0.01996264047920704,
0.07450339943170547,
0.2117634266614914,
-0.02469533681869507,
-0.11765499413013458,
0.004524907562881708,
0.03997977823019028,
-0.08869427442550659,
-0.09810440242290497,
-0.10987982153892517,
0.009443067945539951,
-0.03142540156841278,
-0.13108773529529572,
0.054482825100421906,
-0.07156454771757126,
0.05208346247673035,
-0.03951502963900566,
0.07258375734090805,
-0.002785180229693651,
-0.07090149819850922,
0.0052184960804879665,
-0.05039520934224129,
-0.03323855996131897,
-0.09428592771291733,
0.14251959323883057,
0.18633511662483215,
-0.05802387371659279,
0.16308240592479706,
-0.07239644974470139,
-0.03366175666451454,
0.01014090608805418,
0.16174648702144623,
0.0055029201321303844,
0.22569942474365234,
0.012021953240036964,
0.04908464103937149,
0.19718818366527557,
0.018253987655043602,
-0.2589627206325531,
0.011149401776492596,
0.02668294869363308,
0.007191310171037912,
-0.019045794382691383,
-0.027843017131090164,
0.12890967726707458,
-0.053292952477931976,
-0.0004049929848406464,
0.10026484727859497,
0.004627325106412172,
-0.06061466783285141,
0.1057649776339531,
0.12233506888151169,
0.21502240002155304,
-0.04721471667289734,
-0.048782818019390106,
-0.0832367017865181,
-0.19149059057235718,
0.0528935082256794,
-0.005224648397415876,
0.07766471803188324,
-0.06597163528203964,
0.0910065621137619,
0.050979599356651306,
-0.053677935153245926,
0.1434757560491562,
-0.011519613675773144,
0.13398733735084534,
-0.09477164596319199,
-0.03560208901762962,
0.06360955536365509,
-0.13895702362060547,
0.2295597791671753,
-0.15041105449199677,
0.0707014948129654,
-0.07767459005117416,
-0.0038632669020444155,
-0.11940006166696548,
0.07657189667224884,
0.034108925610780716,
-0.008515605702996254,
-0.027709228917956352,
0.04690857604146004,
0.0600472129881382,
0.04533514007925987,
0.059843242168426514,
-0.042674049735069275,
-0.017243564128875732,
0.13061068952083588,
-0.04687078297138214,
-0.19249902665615082,
0.024974266067147255,
0.025558996945619583,
-0.025153284892439842,
0.06295105069875717,
-0.22000229358673096,
0.030691156163811684,
-0.007286486215889454,
-0.007966828532516956,
0.13041676580905914,
0.02843739651143551,
-0.06111181899905205,
-0.05430155619978905,
0.0875154361128807,
-0.09561126679182053,
-0.11044320464134216,
-0.06731991469860077,
-0.20791158080101013,
-0.09631617367267609,
0.017951523885130882,
0.11989349126815796,
0.04547972232103348,
0.05347521975636482,
-0.031454287469387054,
0.06936530023813248,
-0.09309854358434677,
0.0185969527810812,
0.10933100432157516,
0.0066337198950350285,
-0.09615816175937653,
0.08943916857242584,
-0.03623747453093529,
0.03500981256365776,
0.035835590213537216,
0.08508728444576263,
-0.12929238379001617,
-0.0739581361413002,
-0.08142103999853134,
0.3003562390804291,
0.012729333713650703,
-0.03630942106246948,
-0.0999193862080574,
-0.07567451149225235,
-0.031323496252298355,
-0.07833882421255112,
0.02719579078257084,
-0.007286268286406994,
-0.011970605701208115,
-0.02211686410009861,
-0.08969151973724365,
0.05239872261881828,
0.046585142612457275,
0.03492525964975357,
-0.10746931284666061,
-0.004181073047220707,
-0.010982577688992023,
0.14755180478096008,
-0.03767205774784088,
-0.02558853290975094,
-0.19027502834796906,
-0.05322791263461113,
-0.29807326197624207,
0.038478221744298935,
-0.08226922899484634,
0.015635855495929718,
-0.001102754846215248,
0.002286473987624049,
-0.06569354236125946,
0.06059732660651207,
-0.07217112928628922,
-0.030156441032886505,
0.02374124340713024,
0.07680817693471909,
-0.044197503477334976,
-0.05309789255261421,
0.026654019951820374,
-0.07816027104854584,
0.08597739785909653,
0.10938438028097153,
-0.07374061644077301,
-0.02905934490263462,
-0.18089169263839722,
-0.12912578880786896,
0.06401506066322327,
-0.020596930757164955,
0.07247944921255112,
-0.031986698508262634,
-0.005797513294965029,
-0.004779601003974676,
-0.01824600249528885,
-0.02819485403597355,
0.15777985751628876,
-0.002843614900484681,
0.0942021980881691,
-0.051771748811006546,
-0.050209857523441315,
-0.09696808457374573,
0.03368383273482323,
0.08605119585990906,
0.10192593932151794,
0.0014471671311184764,
-0.05530039593577385,
-0.02058882638812065,
-0.17583176493644714,
-0.061429232358932495,
0.05311625823378563,
-0.037274595350027084,
-0.04766355827450752,
-0.051801640540361404,
0.0622054859995842,
-0.00858856551349163,
0.13978950679302216,
0.06802348047494888,
-0.05005272477865219,
-0.04211825504899025,
0.2699684798717499,
0.1474313735961914,
-0.04412592574954033,
0.013969332911074162,
-0.07621981203556061,
-0.018152253702282906,
0.024572862312197685,
0.01677802763879299,
0.08598779141902924,
-0.09618152678012848,
0.06220691651105881,
0.02289077267050743,
-0.09558539092540741,
0.1060529574751854,
0.09393186867237091,
-0.041890066117048264,
0.05362740904092789,
0.018439307808876038,
-0.06027185916900635,
0.045037370175123215,
-0.08192809671163559,
0.06274428218603134,
0.12508954107761383,
-0.06561031192541122,
0.029479285702109337,
0.048668764531612396,
-0.09192008525133133,
-0.039754755795001984,
-0.1763005405664444,
-0.04476403072476387,
-0.2157789170742035,
0.056594084948301315,
-0.01447981409728527,
-0.06896931678056717,
0.07371881604194641,
-0.046487465500831604,
-0.01932583749294281,
0.09675579518079758,
0.011440051719546318,
0.007778697647154331,
0.01183804776519537,
-0.04728386923670769,
-0.0731339082121849,
0.11082200706005096,
-0.014543361961841583,
0.13256153464317322,
0.028202490881085396,
0.030367741361260414,
0.02060593105852604,
0.06699147820472717,
0.0646665021777153,
-0.023224055767059326,
-0.07166147232055664,
-0.019370147958397865,
0.03389687463641167,
-0.08533268421888351,
0.0848342701792717,
0.08161504566669464,
0.014335053972899914,
-0.02585269883275032,
0.05160224065184593,
-0.06000224128365517,
-0.03252840042114258,
-0.12491767108440399,
0.11241409927606583,
-0.055864784866571426,
0.03829103335738182,
-0.05585429444909096,
-0.11705763638019562,
-0.11361157149076462,
0.2612229585647583,
0.23353350162506104,
-0.13475964963436127,
-0.008116055279970169,
-0.05390399321913719,
0.009823291562497616,
-0.028147445991635323,
0.14055542647838593,
0.013878857716917992,
0.023570604622364044,
0.04227793961763382,
0.043644726276397705,
-0.016611071303486824,
-0.1224840059876442,
-0.03846147656440735,
-0.021075472235679626,
0.040026042610406876,
-0.0778874009847641,
-0.06979947537183762,
0.006606408394873142,
-0.16284841299057007,
0.01094918791204691,
0.07013841718435287,
-0.0748937651515007,
0.001456406433135271,
-0.07193081825971603,
0.012557082809507847,
0.03268295153975487,
0.10568487644195557,
-0.06235853210091591,
0.05642489343881607,
0.2348087728023529,
-0.1021195724606514,
-0.19145160913467407,
-0.0658218190073967,
-0.03089599311351776,
-0.08876095712184906,
0.13063791394233704,
0.017807133495807648,
-0.006002407521009445,
0.04098188132047653,
0.005457605700939894,
-0.10237690806388855,
0.07419421523809433,
-0.04349172115325928,
-0.06719641387462616,
-0.047130800783634186,
0.09083056449890137,
-0.04338517785072327,
-0.16814705729484558,
0.01193378958851099,
-0.07470017671585083,
-0.03539833426475525,
0.04592907801270485,
-0.053954701870679855,
-0.1074899286031723,
-0.028339378535747528,
-0.08329802751541138,
0.09195183217525482,
0.11660458147525787,
0.02261885441839695,
0.028941186144948006,
-0.02964087203145027,
0.06326460093259811,
0.04746675863862038,
-0.02826591208577156,
-0.03328685089945793,
-0.0673489198088646,
0.052520330995321274,
0.05756426230072975,
-0.017572999000549316,
-0.21948465704917908,
-0.023464486002922058,
-0.13237042725086212,
0.04400458186864853,
0.07444138079881668,
0.17156779766082764,
0.09167388081550598,
0.06162191554903984,
0.010161790065467358,
-0.19876378774642944,
0.09352758526802063,
0.12732510268688202,
-0.012376450002193451,
-0.11272266507148743
] |
null | null | transformers |
## MiquMaid v2
Check out our blogpost about this model series [Here!](https://ikaridevgit.github.io/index.html?blog=blogid-6&bo=true#Miqu-base) - Join our Discord server [Here!](https://discord.gg/Bb8pRUXy3Z)
<center>[<a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B">V2-70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B-DPO">V2-70B-DPO</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B">V2-2x70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B-DPO">V2-2x70B-DPO</a>]
</br>
<div style="width: 100%;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/1ziZ_5Rl7bsQKFrgH6ZCf.png" style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca **prompting format**
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: [FP16](https://huggingface.co/NeverSleep/MiquMaid-v2-70B) - [GGUF](https://huggingface.co/NeverSleep/MiquMaid-v2-70B-GGUF)
## Training data used:
- [Aesir datasets](https://huggingface.co/MinervaAI)
- [NoRobots](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt)
- [limarp](https://huggingface.co/datasets/lemonilia/LimaRP)
- [toxic-dpo-v0.1-sharegpt](https://huggingface.co/datasets/Undi95/toxic-dpo-v0.1-sharegpt)
- [ToxicQAFinal](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAFinal)
### Custom format:
```
### Instruction:
{system prompt}
### Input:
{input}
### Response:
{reply}
```
## Others
Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).
IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | text-generation | LoneStriker/MiquMaid-v2-70B-4.65bpw-h6-exl2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T01:51:05+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## MiquMaid v2
Check out our blogpost about this model series Here! - Join our Discord server Here!
<center>[<a href="URL - <a href="URL - <a href="URL - <a href="URL
</br>
<div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: FP16 - GGUF
## Training data used:
- Aesir datasets
- NoRobots
- limarp
- toxic-dpo-v0.1-sharegpt
- ToxicQAFinal
### Custom format:
## Others
Undi: If you want to support us, you can here.
IkariDev: Visit my retro/neocities style website please kek | [
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
75,
121,
11,
30,
40,
5,
32
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.## Credits:\n- Undi\n- IkariDev## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal### Custom format:## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
-0.09447834640741348,
0.17205014824867249,
-0.005602731369435787,
0.01779203675687313,
0.11820747703313828,
0.045264896005392075,
0.11447285860776901,
0.15961068868637085,
0.06829394400119781,
0.05906902998685837,
0.0005873226327821612,
0.11407624930143356,
0.07548845559358597,
0.22948826849460602,
-0.006628913804888725,
-0.14427904784679413,
0.046850357204675674,
-0.026289891451597214,
-0.02635573409497738,
0.09569915384054184,
0.07466454803943634,
-0.04618130251765251,
0.0709284171462059,
0.010442404076457024,
-0.10720876604318619,
-0.017348533496260643,
0.0019323929445818067,
-0.05718233436346054,
0.04780259355902672,
0.04367207735776901,
0.0479082316160202,
0.05087536945939064,
0.00845402292907238,
-0.22662657499313354,
0.047140758484601974,
0.07308577746152878,
-0.025127466768026352,
0.07861552387475967,
0.10886233299970627,
-0.04211974889039993,
0.02646409347653389,
-0.03574787452816963,
-0.02210289053618908,
0.09350186586380005,
-0.11214648932218552,
-0.12319593131542206,
-0.11320719122886658,
0.13006889820098877,
0.06314875930547714,
0.08198896050453186,
0.0033554788678884506,
0.1101357564330101,
-0.07631256431341171,
0.07790177315473557,
0.20335930585861206,
-0.16871041059494019,
-0.02322721853852272,
0.05624805763363838,
-0.015333202667534351,
-0.05565005913376808,
-0.09832000732421875,
0.011083890683948994,
0.010926350019872189,
-0.019533375278115273,
-0.0038207839243113995,
-0.041167840361595154,
0.004284780006855726,
-0.06099749729037285,
-0.059463758021593094,
-0.016264086589217186,
0.24300093948841095,
0.0361378937959671,
-0.07370094209909439,
-0.0026136080268770456,
-0.006493517197668552,
0.11463554203510284,
-0.05098545923829079,
0.030949248000979424,
0.005614427383989096,
-0.0010702924337238073,
-0.0032837465405464172,
-0.04595240205526352,
-0.10275456309318542,
-0.05733378976583481,
-0.014142698608338833,
0.14566513895988464,
0.017552156001329422,
0.00008401479135500267,
-0.004768410697579384,
0.051651932299137115,
-0.10471507161855698,
-0.12298901379108429,
-0.06133059412240982,
-0.10231878608465195,
-0.005009785760194063,
-0.042668018490076065,
-0.022182224318385124,
-0.06640303134918213,
0.12371482700109482,
0.1403876692056656,
-0.04801563546061516,
-0.0030525391921401024,
-0.025033647194504738,
0.00783479306846857,
0.005412905476987362,
-0.00017629309149924666,
-0.07161558419466019,
-0.023959118872880936,
0.07290422171354294,
0.025751972571015358,
0.004980665165930986,
0.010289043188095093,
-0.044097792357206345,
-0.07064660638570786,
-0.04732796177268028,
0.05287690833210945,
0.07054515182971954,
0.06856327503919601,
-0.07649759203195572,
-0.047711774706840515,
0.22618921101093292,
-0.10658138245344162,
0.029063958674669266,
0.05863291397690773,
-0.007088409271091223,
0.10424129664897919,
0.06771936267614365,
-0.0006956448778510094,
-0.06505299359560013,
0.016184480860829353,
-0.041465580463409424,
0.03125211223959923,
-0.08675958216190338,
-0.05394180864095688,
0.0855826810002327,
0.0812700167298317,
-0.03331775963306427,
-0.1366315633058548,
-0.10328203439712524,
-0.01740688644349575,
0.02815520204603672,
-0.023310357704758644,
0.0012498353607952595,
0.04892998933792114,
-0.05491432547569275,
0.01405452098697424,
0.01705477572977543,
0.00629244651645422,
-0.05887370929121971,
0.07736124843358994,
0.022486159577965736,
0.09428157657384872,
0.019443463534116745,
0.025946028530597687,
-0.035123471170663834,
0.002149750478565693,
-0.23019294440746307,
0.05012257769703865,
-0.10595361143350601,
0.0038321600295603275,
-0.0922209694981575,
0.0014835012843832374,
-0.027800843119621277,
-0.009975400753319263,
0.0055687217973172665,
0.20525269210338593,
-0.14585432410240173,
-0.05596565082669258,
0.304247111082077,
-0.15955102443695068,
-0.09778694808483124,
0.09222670644521713,
0.03642375022172928,
-0.07440096139907837,
0.06239297613501549,
0.08249494433403015,
0.1056317463517189,
-0.16265460848808289,
-0.09710903465747833,
-0.011078423820436,
-0.022652560845017433,
-0.024000728502869606,
0.0878278836607933,
-0.018813995644450188,
0.03245491161942482,
0.019763432443141937,
-0.03379102423787117,
0.07007033377885818,
-0.025310136377811432,
-0.022386055439710617,
-0.03589578717947006,
-0.06099054589867592,
0.05183964595198631,
-0.002879094798117876,
-0.0388391874730587,
-0.006428318098187447,
-0.04584600031375885,
-0.06035709008574486,
0.13202428817749023,
-0.004858740605413914,
-0.020473629236221313,
-0.07851582020521164,
0.09554000943899155,
-0.05498090013861656,
0.03728895261883736,
-0.13830018043518066,
-0.06243045628070831,
0.0036350893788039684,
-0.0796012431383133,
0.02157106250524521,
-0.0041148848831653595,
0.05950147658586502,
0.038105957210063934,
-0.04352330043911934,
-0.028907326981425285,
-0.0057363444939255714,
0.004301073960959911,
-0.025426069274544716,
-0.1666073054075241,
-0.0007695230888202786,
-0.0551750548183918,
0.1374220848083496,
-0.16868118941783905,
0.05043652653694153,
0.05925111472606659,
0.16357283294200897,
0.03616755083203316,
-0.031011521816253662,
0.11654403805732727,
-0.03804580122232437,
-0.006411012262105942,
-0.03725241497159004,
0.0044607375748455524,
0.002538213739171624,
-0.011939228512346745,
0.10659566521644592,
-0.06065728887915611,
0.054277852177619934,
0.12642189860343933,
-0.01595868356525898,
-0.05425528809428215,
-0.06506265699863434,
-0.01521784346550703,
-0.006736948620527983,
-0.048000186681747437,
-0.047349583357572556,
0.02513136900961399,
0.0662446990609169,
0.07768423110246658,
-0.03797391429543495,
-0.008253731764853,
0.0011901968391612172,
-0.0948609709739685,
-0.0020795518066734076,
0.0409865640103817,
0.05132393538951874,
-0.14333368837833405,
0.09081240743398666,
0.09744595736265182,
-0.015339801087975502,
0.14312495291233063,
0.008754834532737732,
-0.1070873811841011,
-0.003728162497282028,
0.027940761297941208,
0.05264529958367348,
0.0774049460887909,
-0.03596934303641319,
0.02683958038687706,
0.08106063306331635,
-0.05121877044439316,
0.007932554930448532,
-0.09500398486852646,
-0.022678673267364502,
-0.013256699778139591,
-0.0758146122097969,
-0.04612674191594124,
0.03610261529684067,
0.030104612931609154,
0.0918031707406044,
-0.015134556218981743,
0.07633049786090851,
-0.0010367896175011992,
-0.02394755184650421,
-0.09206201136112213,
0.1670486181974411,
-0.0899675041437149,
-0.27366867661476135,
-0.1188458725810051,
-0.07167717814445496,
-0.04199657961726189,
0.004022621084004641,
0.02857130952179432,
-0.12134306877851486,
-0.07081691175699234,
-0.03115151636302471,
-0.0038425917737185955,
0.06778023391962051,
-0.03805195540189743,
-0.02431504614651203,
0.05526971071958542,
0.09138014912605286,
-0.07273191213607788,
-0.002759605646133423,
0.06194623187184334,
-0.037675220519304276,
0.08085193485021591,
0.008549315854907036,
0.10605848580598831,
0.04739413037896156,
0.03012051060795784,
0.0015264216344803572,
0.04311876371502876,
0.17313145101070404,
-0.10127022117376328,
0.09718520194292068,
0.20746180415153503,
0.0394415408372879,
0.08480402082204819,
0.15171074867248535,
0.05122246593236923,
-0.013119645416736603,
-0.005120322108268738,
0.04244927689433098,
0.011746162548661232,
-0.2427690476179123,
-0.061469703912734985,
-0.05656198412179947,
-0.054776955395936966,
0.022767482325434685,
0.047591015696525574,
0.0650729089975357,
0.1047578752040863,
-0.10416096448898315,
-0.016062086448073387,
0.022997045889496803,
0.09911724179983139,
0.047439564019441605,
0.022038234397768974,
0.061993930488824844,
-0.04141371324658394,
0.015599393285810947,
0.12155410647392273,
0.06473620980978012,
0.11147889494895935,
-0.023897795006632805,
0.08020832389593124,
0.06728237122297287,
0.0892438217997551,
0.0530114471912384,
0.06319621205329895,
0.04218849167227745,
-0.014131366275250912,
-0.0013301256112754345,
-0.08454640209674835,
-0.04801497980952263,
0.023290416225790977,
0.013235284946858883,
-0.057533953338861465,
-0.0392376184463501,
-0.01914895512163639,
0.07390332221984863,
0.1574147492647171,
0.04597143456339836,
-0.20930512249469757,
-0.05056460201740265,
0.033859558403491974,
-0.0003397460968699306,
-0.06584210693836212,
-0.033550359308719635,
0.05652978643774986,
-0.12203755974769592,
0.1039382740855217,
-0.02658943273127079,
0.09946075826883316,
-0.07054278254508972,
0.000789299956522882,
0.00494906771928072,
0.12713035941123962,
-0.023788869380950928,
0.09413742274045944,
-0.24859566986560822,
0.14139194786548615,
0.04770104959607124,
0.06752338260412216,
-0.05309014022350311,
0.028258029371500015,
0.0961327999830246,
0.12656870484352112,
0.10434279590845108,
0.020785793662071228,
0.06395822018384933,
-0.15350443124771118,
-0.11799371987581253,
0.006164612248539925,
0.02960512787103653,
-0.04779611900448799,
0.07287964969873428,
-0.0005067483871243894,
-0.06341438740491867,
-0.04712821915745735,
0.03289221227169037,
-0.19348879158496857,
-0.12983499467372894,
0.07045576721429825,
0.052490055561065674,
0.090853750705719,
-0.06709475815296173,
-0.03205195814371109,
-0.043046124279499054,
0.18290454149246216,
-0.03442198783159256,
-0.08606650680303574,
-0.1285882145166397,
-0.0006686998531222343,
0.09258218854665756,
-0.08165017515420914,
-0.005991893354803324,
-0.052048277109861374,
0.1894829422235489,
-0.035209737718105316,
-0.08786994218826294,
0.01570327952504158,
-0.15995244681835175,
-0.1281605362892151,
-0.0414857491850853,
0.12103712558746338,
-0.021659180521965027,
0.02213156595826149,
0.05526252090930939,
-0.020805859938263893,
0.008410685695707798,
-0.1123393177986145,
0.02350648306310177,
0.09350050985813141,
0.08948540687561035,
0.08400450646877289,
-0.11930029839277267,
-0.11843101680278778,
-0.10216961801052094,
-0.022528614848852158,
0.06181072071194649,
0.24282413721084595,
-0.02235415205359459,
0.037382837384939194,
0.13085247576236725,
-0.04928212612867355,
-0.19814851880073547,
-0.06996271014213562,
-0.00017375701281707734,
-0.037472743541002274,
0.02159503661096096,
-0.21408295631408691,
0.08694717288017273,
0.09358245879411697,
-0.030445247888565063,
0.09161640703678131,
-0.07194696366786957,
-0.06843597441911697,
0.04065357893705368,
0.07071772962808609,
0.0037067674566060305,
-0.1683196723461151,
-0.07113704830408096,
-0.06764888018369675,
-0.12663458287715912,
0.08166584372520447,
-0.1314810812473297,
0.08971400558948517,
-0.005421672947704792,
0.0671011433005333,
0.025563575327396393,
-0.06707208603620529,
0.11356908828020096,
-0.020757906138896942,
0.009567689150571823,
-0.07924797385931015,
0.012899143621325493,
0.022010432556271553,
-0.050428662449121475,
0.09034649282693863,
-0.02925287000834942,
0.01692429557442665,
-0.091850645840168,
-0.0007856881711632013,
-0.10224597156047821,
0.0437864288687706,
-0.038862090557813644,
-0.017533548176288605,
-0.008498632349073887,
0.07837546616792679,
0.03536466881632805,
0.010669435374438763,
-0.009266866371035576,
-0.04946504905819893,
0.10181041061878204,
0.17810481786727905,
0.10491631180047989,
0.0006870499346405268,
-0.07857012748718262,
-0.036821771413087845,
-0.053213875740766525,
0.050082918256521225,
-0.08183137327432632,
0.06681650131940842,
0.029605142772197723,
0.010572184808552265,
0.12429390102624893,
-0.0033586653880774975,
-0.12030913680791855,
-0.003338087350130081,
0.10895328968763351,
-0.12868796288967133,
-0.07275929301977158,
-0.020934229716658592,
0.05516009032726288,
-0.10196569561958313,
0.0011667415965348482,
0.1428048461675644,
-0.028892088681459427,
-0.028331711888313293,
0.014776935800909996,
0.07020314782857895,
-0.012796786613762379,
0.10238455981016159,
0.07413777709007263,
0.049551427364349365,
-0.12031137198209763,
0.05704139545559883,
0.03181569650769234,
-0.03592713922262192,
-0.0024339298252016306,
0.05667674541473389,
-0.10612429678440094,
-0.1119871735572815,
0.03397342190146446,
0.06045559421181679,
-0.015471268445253372,
-0.06184658035635948,
-0.020792635157704353,
-0.04714902117848396,
0.02126099169254303,
0.07590576261281967,
0.00995138380676508,
-0.008162305690348148,
0.08148860931396484,
-0.017391547560691833,
-0.08959554880857468,
0.06402577459812164,
0.010443227365612984,
0.03571965917944908,
-0.13038720190525055,
0.07408680766820908,
-0.015041174367070198,
0.006071531679481268,
-0.022530831396579742,
0.003641687100753188,
-0.10074226558208466,
-0.04254826903343201,
-0.07885435223579407,
0.06230726093053818,
-0.1484614759683609,
-0.020241795107722282,
-0.026183132082223892,
-0.022612975910305977,
0.015071062371134758,
0.019551774486899376,
-0.07782812416553497,
-0.04559153690934181,
-0.010346274822950363,
0.08449862152338028,
-0.16007104516029358,
-0.008523115888237953,
0.03327300027012825,
-0.06084582209587097,
0.0670776516199112,
0.08543620258569717,
-0.010745981708168983,
-0.011400423012673855,
-0.24030931293964386,
-0.05429427698254585,
0.060920946300029755,
0.04178236424922943,
0.015297153033316135,
-0.10723429918289185,
0.0352109931409359,
-0.01898287609219551,
-0.023456763476133347,
0.005050045438110828,
0.031953055411577225,
-0.08434974402189255,
0.024241402745246887,
-0.019039491191506386,
-0.04014326632022858,
-0.051917847245931625,
0.04262912645936012,
0.17145587503910065,
-0.014532416127622128,
0.1174297034740448,
-0.080752432346344,
0.054420918226242065,
-0.13401885330677032,
0.029829595237970352,
-0.001078542205505073,
-0.039962440729141235,
-0.02863360196352005,
-0.010570892132818699,
0.06349045038223267,
-0.010899520479142666,
0.09258676320314407,
-0.0552545003592968,
0.06722300499677658,
0.0190583486109972,
-0.09725376963615417,
0.007986992597579956,
-0.026470135897397995,
0.03294571489095688,
0.0396236926317215,
-0.006473933346569538,
0.009316735900938511,
0.00238132756203413,
0.02042953483760357,
-0.0582701601088047,
0.07976511865854263,
0.16147081553936005,
0.02053176984190941,
0.022807525470852852,
0.054943084716796875,
-0.07234697043895721,
-0.036924149841070175,
-0.04578930139541626,
-0.077462337911129,
0.06634023785591125,
-0.021255100145936012,
0.07374273985624313,
0.15307408571243286,
-0.12218204140663147,
0.038187239319086075,
-0.005237263161689043,
-0.03132057934999466,
-0.08196348696947098,
-0.1581864356994629,
-0.06715912371873856,
-0.08088500797748566,
0.011959434486925602,
-0.11438815295696259,
0.06888450682163239,
0.04325690120458603,
0.019395047798752785,
-0.017880942672491074,
0.13543029129505157,
0.03472369909286499,
-0.07543140649795532,
0.060917001217603683,
-0.02095349319279194,
-0.031358812004327774,
0.04272241145372391,
0.0006400952115654945,
0.06196298450231552,
-0.010582057759165764,
0.044258568435907364,
0.0559408999979496,
0.02938593178987503,
0.05811672285199165,
-0.06726688146591187,
-0.12517108023166656,
0.006359596271067858,
0.005888449959456921,
0.04039566218852997,
0.15003027021884918,
0.05136363208293915,
0.007397872861474752,
0.014586303383111954,
0.16361239552497864,
-0.038274187594652176,
-0.0431714691221714,
-0.15419889986515045,
0.011273895390331745,
-0.02001452073454857,
-0.009176031686365604,
-0.03663250058889389,
-0.10866829752922058,
-0.028140606358647346,
0.20135445892810822,
0.08363344520330429,
-0.049736183136701584,
0.026926010847091675,
-0.006478144787251949,
0.0070541067980229855,
0.006099193822592497,
0.08733457326889038,
0.05982113629579544,
0.11233042925596237,
-0.03476639464497566,
0.04225286468863487,
0.008952682837843895,
-0.042931120842695236,
-0.100910983979702,
0.05160531401634216,
-0.04183126986026764,
-0.029043002054095268,
-0.0207699965685606,
0.12725666165351868,
-0.06002918258309364,
-0.12053494155406952,
-0.05984590947628021,
-0.05843505263328552,
-0.09186802059412003,
-0.04533113166689873,
-0.021347900852560997,
0.08330697566270828,
0.03736959397792816,
-0.008225626312196255,
-0.006564581301063299,
0.18599693477153778,
-0.004363450221717358,
-0.06833065301179886,
-0.047022756189107895,
0.03228268772363663,
-0.009685746394097805,
0.13331912457942963,
0.02237250655889511,
0.06835850328207016,
0.08902639895677567,
-0.04617135971784592,
-0.13351397216320038,
0.05768809840083122,
0.01893182285130024,
-0.16012974083423615,
0.03900958225131035,
0.1735668033361435,
-0.019399257376790047,
0.004258662927895784,
0.07070906460285187,
-0.07974739372730255,
0.021498262882232666,
0.05192280188202858,
-0.017278648912906647,
-0.07030515372753143,
0.08999960869550705,
-0.09391003847122192,
0.11678098142147064,
0.17506007850170135,
-0.024389326572418213,
-0.013276796787977219,
-0.03903545066714287,
0.05904215946793556,
0.06406354159116745,
-0.016790268942713737,
-0.07218509912490845,
-0.10399819910526276,
0.01415897998958826,
-0.01502299215644598,
0.07969480007886887,
-0.13121938705444336,
-0.019862104207277298,
-0.05875250697135925,
-0.03522523120045662,
-0.09029058367013931,
0.07942423224449158,
0.06178797036409378,
0.053517896682024,
-0.021183528006076813,
-0.09516715258359909,
0.007413235958665609,
0.11255256831645966,
-0.14081521332263947,
-0.0646120086312294
] |
null | null | null |
Quantized using 200 samples of 8192 tokens from an RP-oriented [PIPPA](https://huggingface.co/datasets/royallab/PIPPA-cleaned) dataset.
Branches:
- `main` -- `measurement.json`
- `2.25b6h` -- 2.25bpw, 6bit lm_head
- `3.5b6h` -- 3.5bpw, 6bit lm_head
- `3.7b6h` -- 3.7bpw, 6bit lm_head
- `5b6h` -- 5bpw, 6bit lm_head
- `6b6h` -- 6bpw, 6bit lm_head
Requires ExllamaV2 version 0.0.12 and up.
Original model link: [Envoid/Fish-8x7B](https://huggingface.co/Envoid/Fish-8x7B)
# This quant was broken. It is fixed now.
Original model README below.
***
# Caution: This model may output adult content.
# FISH - Fusion of Intuitive Semantic Heuristics
For this model I took the following LoRAs
[SeanWu25/Mixtral_8x7b_Medicine](https://huggingface.co/SeanWu25/Mixtral_8x7b_Medicine)
[SeanWu25/Mixtral_8x7b_WuKurtz](https://huggingface.co/SeanWu25/Mixtral_8x7b_WuKurtz)
and
[wandb/Mixtral-8x7b-Remixtral](https://huggingface.co/wandb/Mixtral-8x7b-Remixtral)
And merged them onto their base model.
I then did a simple linear merge between them, an experimental unreleased 8x7B model, and an unreleased model that was a intermediate step in creating [Envoid/BondBurger-8x7B](https://huggingface.co/Envoid/BondBurger-8x7B?not-for-all-audiences=true)
The end results are a surprisingly good model for role palying style entertainment.
At first I was disappointed with the results but ended up settling on the following sampler parameters which really bring it to life.
## It does eccentuate characters that have particularly aggressive personalities.
## Because this is part of the whole SensualNousInstruct family of models it still suffers from the same tokenizer/special tokens weirdness.
## This model has only been tested in Q8 GGUF form due to hardware limitations.
It responds well to [INST] do a thing [/INST] instruct style formatting (although uses the ChatML special tokens) | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences"]} | null | rAIfle/Fish-8x7B-exl2-rpcal | [
"not-for-all-audiences",
"license:cc-by-nc-4.0",
"region:us"
] | 2024-02-09T01:54:05+00:00 | [] | [] | TAGS
#not-for-all-audiences #license-cc-by-nc-4.0 #region-us
|
Quantized using 200 samples of 8192 tokens from an RP-oriented PIPPA dataset.
Branches:
- 'main' -- 'URL'
- '2.25b6h' -- 2.25bpw, 6bit lm_head
- '3.5b6h' -- 3.5bpw, 6bit lm_head
- '3.7b6h' -- 3.7bpw, 6bit lm_head
- '5b6h' -- 5bpw, 6bit lm_head
- '6b6h' -- 6bpw, 6bit lm_head
Requires ExllamaV2 version 0.0.12 and up.
Original model link: Envoid/Fish-8x7B
# This quant was broken. It is fixed now.
Original model README below.
*
# Caution: This model may output adult content.
 | [
"# This quant was broken. It is fixed now.\n\nOriginal model README below.\n\n*",
"# Caution: This model may output adult content.\n\n\n![](URL",
"# FISH - Fusion of Intuitive Semantic Heuristics \n\nFor this model I took the following LoRAs\n\nSeanWu25/Mixtral_8x7b_Medicine\n\nSeanWu25/Mixtral_8x7b_WuKurtz\n\nand\n\nwandb/Mixtral-8x7b-Remixtral\n\nAnd merged them onto their base model. \n\nI then did a simple linear merge between them, an experimental unreleased 8x7B model, and an unreleased model that was a intermediate step in creating Envoid/BondBurger-8x7B\n\nThe end results are a surprisingly good model for role palying style entertainment. \n\nAt first I was disappointed with the results but ended up settling on the following sampler parameters which really bring it to life. \n\n\n![](URL",
"## It does eccentuate characters that have particularly aggressive personalities.",
"## Because this is part of the whole SensualNousInstruct family of models it still suffers from the same tokenizer/special tokens weirdness.",
"## This model has only been tested in Q8 GGUF form due to hardware limitations. \n\nIt responds well to [INST] do a thing [/INST] instruct style formatting (although uses the ChatML special tokens)"
] | [
"TAGS\n#not-for-all-audiences #license-cc-by-nc-4.0 #region-us \n",
"# This quant was broken. It is fixed now.\n\nOriginal model README below.\n\n*",
"# Caution: This model may output adult content.\n\n\n![](URL",
"# FISH - Fusion of Intuitive Semantic Heuristics \n\nFor this model I took the following LoRAs\n\nSeanWu25/Mixtral_8x7b_Medicine\n\nSeanWu25/Mixtral_8x7b_WuKurtz\n\nand\n\nwandb/Mixtral-8x7b-Remixtral\n\nAnd merged them onto their base model. \n\nI then did a simple linear merge between them, an experimental unreleased 8x7B model, and an unreleased model that was a intermediate step in creating Envoid/BondBurger-8x7B\n\nThe end results are a surprisingly good model for role palying style entertainment. \n\nAt first I was disappointed with the results but ended up settling on the following sampler parameters which really bring it to life. \n\n\n![](URL",
"## It does eccentuate characters that have particularly aggressive personalities.",
"## Because this is part of the whole SensualNousInstruct family of models it still suffers from the same tokenizer/special tokens weirdness.",
"## This model has only been tested in Q8 GGUF form due to hardware limitations. \n\nIt responds well to [INST] do a thing [/INST] instruct style formatting (although uses the ChatML special tokens)"
] | [
26,
18,
16,
178,
15,
34,
55
] | [
"passage: TAGS\n#not-for-all-audiences #license-cc-by-nc-4.0 #region-us \n# This quant was broken. It is fixed now.\n\nOriginal model README below.\n\n*# Caution: This model may output adult content.\n\n\n"
] | [
-0.0513567291200161,
0.04432480037212372,
-0.0017353086732327938,
0.041925959289073944,
0.07790271192789078,
0.03496892377734184,
0.03770136460661888,
0.14105847477912903,
0.09180675446987152,
0.11091167479753494,
0.060392528772354126,
-0.018715975806117058,
0.04440372809767723,
0.16252081096172333,
0.023575851693749428,
-0.09173700213432312,
0.0818367525935173,
-0.07021082937717438,
0.0944548100233078,
0.044183842837810516,
0.0659543052315712,
-0.03952952101826668,
0.07952499389648438,
0.03856253996491432,
-0.02115381322801113,
-0.029134053736925125,
-0.0004369891539681703,
0.059542734175920486,
0.06188715249300003,
0.031775228679180145,
0.028623711317777634,
0.014583601616322994,
-0.0034036850556731224,
-0.13646897673606873,
0.037937089800834656,
0.053142745047807693,
0.031117770820856094,
0.05929867550730705,
0.05081993341445923,
0.026953428983688354,
0.09441240131855011,
-0.022709928452968597,
-0.016262421384453773,
0.07159248739480972,
-0.0927460789680481,
-0.06730961054563522,
-0.2013152837753296,
0.1374504417181015,
0.01990499533712864,
0.034362196922302246,
-0.04079641401767731,
0.16831722855567932,
0.053115759044885635,
0.06014085188508034,
0.17209340631961823,
-0.15717768669128418,
0.010695323348045349,
0.13052180409431458,
0.11408603191375732,
-0.028239155188202858,
-0.03562100976705551,
-0.011337694711983204,
0.020201614126563072,
-0.0056049395352602005,
-0.1143740862607956,
-0.038672465831041336,
0.0795743316411972,
-0.01127941720187664,
-0.09730684757232666,
-0.0356731191277504,
0.06584102660417557,
0.06733298301696777,
-0.09361594915390015,
-0.096877820789814,
-0.06429534405469894,
-0.10410431027412415,
0.015785355120897293,
-0.011809675954282284,
-0.00040131073910743,
0.049747053533792496,
0.12395458668470383,
-0.11666762828826904,
-0.041890982538461685,
0.0013091160217300057,
-0.09866559505462646,
0.117755226790905,
0.01134276483207941,
0.08165635168552399,
-0.019799035042524338,
0.04945426061749458,
-0.24536511301994324,
-0.02725718729197979,
-0.14062659442424774,
-0.09192785620689392,
-0.10450472682714462,
-0.05378323793411255,
-0.04232170432806015,
-0.012795071117579937,
0.0510324127972126,
0.16073673963546753,
-0.1436459720134735,
0.06597433984279633,
0.013974236324429512,
0.009994234889745712,
0.08691726624965668,
0.09843949973583221,
-0.0696176290512085,
0.030833806842565536,
0.09923424571752548,
0.0680345892906189,
0.01867878995835781,
-0.037959616631269455,
-0.03758570924401283,
0.03248026967048645,
0.03384653478860855,
0.01800897717475891,
0.08538930863142014,
0.03541816771030426,
-0.06443911790847778,
-0.028868617489933968,
0.1773153394460678,
-0.05046013370156288,
0.016819573938846588,
0.05221021920442581,
-0.07219492644071579,
0.07640014588832855,
0.06129181757569313,
-0.016754047945141792,
-0.046079568564891815,
0.03657523915171623,
-0.06900380551815033,
-0.03574739396572113,
-0.06023639068007469,
-0.08819800615310669,
0.07023432850837708,
-0.06827142834663391,
-0.04738088324666023,
-0.07093268632888794,
-0.21652169525623322,
-0.06088065728545189,
-0.0036476675886660814,
-0.053240370005369186,
0.03129381313920021,
0.01846495270729065,
-0.04362819716334343,
0.05266427993774414,
-0.006503930315375328,
-0.12509185075759888,
-0.022011028602719307,
-0.005216661840677261,
-0.0003279561933595687,
0.04117210954427719,
-0.1172577366232872,
0.002860395237803459,
-0.11907254904508591,
0.06908059120178223,
-0.11025425791740417,
0.0914166048169136,
-0.04914557561278343,
-0.019139928743243217,
-0.06987980753183365,
-0.014617501758038998,
-0.03748046234250069,
-0.02339307963848114,
0.0977868139743805,
0.19176146388053894,
-0.12756040692329407,
-0.01111583225429058,
0.07575555145740509,
-0.07333913445472717,
-0.09427811205387115,
0.098882295191288,
-0.003967232070863247,
0.005559053272008896,
0.024431554600596428,
0.15675704181194305,
0.0013398340670391917,
-0.0680825412273407,
-0.17764030396938324,
-0.03828362002968788,
-0.04378782957792282,
0.10236737132072449,
0.012775471433997154,
-0.08595570176839828,
0.03683657571673393,
0.00233482220210135,
-0.05100551247596741,
-0.034416474401950836,
-0.04748448356986046,
-0.033432625234127045,
-0.0889478325843811,
0.015454272739589214,
0.0319429449737072,
-0.025517083704471588,
-0.010664359666407108,
-0.04648984596133232,
-0.11815866082906723,
-0.0009167938842438161,
0.15726175904273987,
0.01575370319187641,
0.045536935329437256,
-0.12027953565120697,
0.20044955611228943,
-0.043945107609033585,
0.03931804746389389,
-0.13769784569740295,
-0.13201472163200378,
0.052813876420259476,
-0.11569609493017197,
0.016531549394130707,
-0.023766089230775833,
0.03993033245205879,
-0.0164333563297987,
0.004692193120718002,
-0.07307782024145126,
-0.005590746644884348,
-0.023802831768989563,
-0.03994929790496826,
-0.1530839055776596,
-0.03057892806828022,
-0.08411011844873428,
0.13897444307804108,
-0.07634828239679337,
-0.019458329305052757,
-0.0017348644323647022,
0.11108548939228058,
-0.005650719627737999,
-0.11989652365446091,
0.04717216268181801,
-0.022452564910054207,
-0.05584738031029701,
-0.05444704741239548,
0.03017757460474968,
0.008257907815277576,
-0.1011115238070488,
0.09385325014591217,
-0.20184999704360962,
-0.22113096714019775,
0.08007858693599701,
0.10806544125080109,
-0.06686452031135559,
0.04528672248125076,
-0.001988540170714259,
-0.018099457025527954,
-0.012441755272448063,
-0.04841598868370056,
0.08930857479572296,
0.04830799251794815,
0.06086421757936478,
-0.042041659355163574,
-0.0068902806378901005,
0.002070038113743067,
-0.06317370384931564,
-0.024273814633488655,
0.035489462316036224,
-0.0826190710067749,
-0.1603585183620453,
0.016406042501330376,
-0.0076428744941949844,
0.041471827775239944,
0.08628930151462555,
0.018409239128232002,
-0.04700600728392601,
-0.09393797069787979,
0.06346297264099121,
0.03256949409842491,
0.07515773177146912,
-0.06137959286570549,
0.06020801141858101,
0.031168118119239807,
0.028602665290236473,
0.013440784998238087,
-0.051798149943351746,
0.03591688349843025,
0.03187251091003418,
-0.04592990130186081,
-0.0438070148229599,
0.11160396039485931,
0.004552565049380064,
0.05804713815450668,
0.04297828674316406,
0.04366203397512436,
-0.0033238783944398165,
-0.05353011563420296,
-0.1358584612607956,
0.1283683478832245,
-0.11597564071416855,
-0.14871814846992493,
-0.14689654111862183,
-0.04583720490336418,
-0.1090768426656723,
-0.008609206415712833,
0.03767189010977745,
-0.06386936455965042,
-0.06766411662101746,
-0.10980820655822754,
-0.04057379066944122,
0.024793969467282295,
-0.011661428026854992,
0.04606319218873978,
-0.10180123895406723,
0.07495143264532089,
-0.08083683252334595,
-0.03180956095457077,
-0.006682634353637695,
-0.002019505714997649,
0.020975040271878242,
0.042414963245391846,
0.037918753921985626,
0.14050672948360443,
-0.010166761465370655,
-0.0035893325693905354,
0.022108444944024086,
0.2604904770851135,
-0.04535110667347908,
0.0756019651889801,
0.17022059857845306,
0.0011266121873632073,
0.08814115077257156,
0.10698414593935013,
-0.013481581583619118,
-0.03619654104113579,
0.026581941172480583,
0.04775841534137726,
-0.06017875298857689,
-0.18211165070533752,
-0.0711011290550232,
-0.06899302452802658,
0.015415843576192856,
-0.04526805877685547,
0.04821399226784706,
0.032780639827251434,
-0.0029668810311704874,
-0.058801908046007156,
-0.061030250042676926,
-0.07364891469478607,
0.1020968109369278,
0.1133602112531662,
0.009237694554030895,
0.05527142062783241,
-0.025941435247659683,
0.06594572961330414,
0.12690602242946625,
0.012191858142614365,
0.13546738028526306,
-0.03956232964992523,
0.1639433205127716,
0.05259282514452934,
0.06411673873662949,
-0.003295415546745062,
-0.02626008540391922,
-0.0445699542760849,
-0.014952726662158966,
-0.0019808108918368816,
-0.09136270731687546,
-0.007124544121325016,
0.07790029793977737,
0.024888204410672188,
0.04565408453345299,
-0.09151721000671387,
0.04100927338004112,
0.03800849989056587,
0.11114281415939331,
0.07730276882648468,
-0.1296965330839157,
-0.09510476142168045,
0.06061939150094986,
0.014145378023386002,
-0.040581777691841125,
-0.05484296754002571,
0.0498323068022728,
-0.10061420500278473,
0.06120633706450462,
-0.02105611190199852,
0.07957510650157928,
0.023494264110922813,
-0.0053337025456130505,
-0.02913193590939045,
0.0769817903637886,
-0.0254498478025198,
0.01908104680478573,
-0.0391203872859478,
0.10099136829376221,
0.03356413170695305,
0.043265022337436676,
0.04889987036585808,
0.02226240560412407,
0.07427147030830383,
0.07244259864091873,
0.10029494762420654,
0.07352938503026962,
-0.11873245984315872,
-0.07643893361091614,
-0.02995801530778408,
-0.023923376575112343,
0.02791442722082138,
0.12323897331953049,
0.09389360249042511,
-0.05844604969024658,
0.016857735812664032,
-0.004701986908912659,
0.10198360681533813,
-0.09102711826562881,
-0.06642556190490723,
0.05448365956544876,
0.03728983551263809,
-0.04566885530948639,
-0.06676186621189117,
-0.009254277683794498,
-0.025002993643283844,
0.1707143932580948,
0.039427924901247025,
-0.05181783065199852,
-0.09701789170503616,
-0.02275068871676922,
0.12101191282272339,
-0.08216357231140137,
-0.009841280058026314,
-0.06686937808990479,
0.02192108891904354,
-0.015548712573945522,
-0.11216063797473907,
0.04135384410619736,
-0.09148071706295013,
-0.16829156875610352,
-0.05584161356091499,
0.06410622596740723,
0.004472603090107441,
0.0346870981156826,
-0.01639416068792343,
0.0013588271103799343,
-0.06746525317430496,
-0.09888815879821777,
0.05131833627820015,
0.19689172506332397,
-0.08880696445703506,
0.129707932472229,
0.03479180485010147,
-0.016040915623307228,
-0.042498357594013214,
-0.040195923298597336,
0.08612406253814697,
0.35743987560272217,
-0.0511443130671978,
0.13086073100566864,
0.08513631671667099,
-0.09750553965568542,
-0.18206200003623962,
0.01347434800118208,
0.011411109007894993,
-0.008092910051345825,
-0.009817469865083694,
-0.011992127634584904,
0.026552844792604446,
0.04809128865599632,
-0.024578914046287537,
0.05430922284722328,
-0.24452181160449982,
-0.08114803582429886,
0.015294879674911499,
-0.013704365119338036,
0.19218425452709198,
-0.13348500430583954,
-0.08970718830823898,
0.008018286898732185,
-0.14964233338832855,
0.0035891993902623653,
0.007980595342814922,
0.08789153397083282,
-0.038853853940963745,
0.09545715898275375,
0.06346834450960159,
-0.061645038425922394,
0.16179580986499786,
-0.033692192286252975,
0.007534245494753122,
-0.05144401639699936,
-0.011672044172883034,
0.017390837892889977,
-0.0914444550871849,
0.12253311276435852,
0.027592068538069725,
0.07551959156990051,
-0.14784735441207886,
0.010269814170897007,
-0.09593626856803894,
0.10626900941133499,
-0.031066052615642548,
-0.03519859537482262,
-0.11208467930555344,
0.08879438787698746,
0.08093036711215973,
0.0049986690282821655,
0.03064000979065895,
-0.04743941128253937,
0.03566381335258484,
0.21598517894744873,
0.015636960044503212,
-0.04079906642436981,
-0.08376140892505646,
0.057374730706214905,
-0.03850937634706497,
0.04255085065960884,
-0.08061105757951736,
-0.0072312247939407825,
0.09664656966924667,
0.009503638371825218,
0.1074904203414917,
0.02727392688393593,
-0.1638653427362442,
0.038334865123033524,
0.04747001454234123,
-0.11421596258878708,
-0.15077172219753265,
-0.014752507209777832,
0.0676501989364624,
-0.0893704891204834,
-0.005499775055795908,
0.12148125469684601,
-0.002433426445350051,
-0.014852945692837238,
0.016312459483742714,
0.0587051585316658,
-0.005852829199284315,
0.08881286531686783,
-0.001424995600245893,
0.045718029141426086,
-0.07233665883541107,
0.07004251331090927,
0.004076244309544563,
-0.05969289690256119,
0.0713580995798111,
0.10396498441696167,
-0.06404707580804825,
-0.03508749231696129,
-0.06600144505500793,
0.05707084387540817,
-0.17154261469841003,
-0.02572900429368019,
-0.033819686621427536,
0.0018643751973286271,
0.019929904490709305,
0.12114202976226807,
0.011547135189175606,
0.028713881969451904,
0.029581386595964432,
-0.010233160108327866,
-0.06790921092033386,
0.046201225370168686,
0.04332863166928291,
0.05598628893494606,
-0.12258750200271606,
0.02136891894042492,
-0.048018988221883774,
0.07821418344974518,
-0.009713283739984035,
-0.049302250146865845,
-0.11980877816677094,
-0.05571998283267021,
-0.1291058212518692,
0.023020369932055473,
-0.09998426586389542,
-0.03768434002995491,
0.008343313820660114,
0.004600773099809885,
0.01971929520368576,
0.029395274817943573,
-0.05348086357116699,
-0.081048384308815,
-0.009549807757139206,
0.04070904850959778,
-0.12708544731140137,
-0.020784176886081696,
0.03500257059931755,
-0.020081061869859695,
0.07764650881290436,
0.048945553600788116,
-0.014230971224606037,
-0.010496886447072029,
-0.10895857214927673,
-0.01997777260839939,
-0.010581489652395248,
0.03825962170958519,
0.035650454461574554,
-0.15042948722839355,
0.013430891558527946,
-0.005778692662715912,
-0.04336360841989517,
0.011781534180045128,
0.07508400082588196,
-0.08381042629480362,
-0.07376202940940857,
-0.05267699435353279,
0.06135310232639313,
-0.07370948046445847,
0.016311032697558403,
0.045702580362558365,
0.09835117310285568,
0.1122317686676979,
-0.06770399957895279,
0.0448196716606617,
-0.13708581030368805,
-0.0020886934362351894,
0.03198884055018425,
0.0026421407237648964,
-0.038917023688554764,
0.02474238909780979,
0.02048899605870247,
-0.026469433680176735,
0.06456751376390457,
-0.0900372639298439,
-0.06495402753353119,
0.03953398019075394,
0.009125283919274807,
0.0014388575218617916,
-0.06179274991154671,
0.036506012082099915,
-0.006248858757317066,
-0.05686277523636818,
0.009364504367113113,
0.0017491652397438884,
-0.008073247037827969,
-0.0809396430850029,
0.19059328734874725,
0.00822678953409195,
0.0882783830165863,
0.11498378217220306,
0.028501184657216072,
-0.047466930001974106,
0.000602405983954668,
-0.02686677873134613,
-0.05368390306830406,
0.07912225276231766,
-0.03970729187130928,
0.14026698470115662,
0.11849424988031387,
-0.09190982580184937,
0.13339614868164062,
-0.08316313475370407,
-0.03276241198182106,
-0.09670747071504593,
-0.11118174344301224,
-0.04912106320261955,
-0.11281957477331161,
0.02014778181910515,
-0.09790212661027908,
0.12071176618337631,
0.017839912325143814,
0.011389603838324547,
-0.0680634081363678,
0.06948410719633102,
-0.12424808740615845,
-0.019071578979492188,
-0.0038669921923428774,
0.0011305682128295302,
-0.022286545485258102,
0.114601269364357,
-0.010186792351305485,
0.07695302367210388,
-0.006558113731443882,
0.06126037612557411,
0.07987213879823685,
0.10869941860437393,
0.07648692280054092,
-0.014557999558746815,
-0.10933853685855865,
-0.006882661487907171,
0.06081712245941162,
0.03398764133453369,
0.12462463974952698,
0.06118069589138031,
0.021725602447986603,
-0.0475919134914875,
0.16458140313625336,
-0.0511445626616478,
0.04174448549747467,
-0.11773475259542465,
0.13486331701278687,
-0.030845187604427338,
-0.03197432681918144,
-0.006425335071980953,
-0.13923999667167664,
-0.0031923502683639526,
0.09369990974664688,
0.11105924099683762,
-0.04517468437552452,
-0.02537286840379238,
-0.05256091058254242,
-0.010089716874063015,
-0.020923350006341934,
0.08522805571556091,
0.030472883954644203,
0.1297788918018341,
-0.03694453835487366,
0.09528505802154541,
-0.03069368004798889,
0.023604411631822586,
-0.04586357995867729,
0.04068821296095848,
0.01763748750090599,
0.01337256096303463,
-0.0482800155878067,
0.018425988033413887,
-0.1315222531557083,
-0.1702672690153122,
0.03518245369195938,
-0.07312273234128952,
-0.06833832710981369,
-0.037651270627975464,
0.02630997821688652,
0.022081071510910988,
0.10006608814001083,
-0.031670451164245605,
0.02261470817029476,
0.13539361953735352,
-0.04942586272954941,
-0.10215497016906738,
-0.11585056036710739,
0.029107093811035156,
-0.05380162596702576,
0.16376768052577972,
0.04616066813468933,
0.03319157660007477,
0.1118178740143776,
-0.0018722701352089643,
-0.14232827723026276,
0.0334840826690197,
0.004904172383248806,
-0.10627643018960953,
-0.021796269342303276,
0.15236252546310425,
0.016067171469330788,
0.08735790848731995,
0.0486750565469265,
-0.06113455817103386,
0.009661030024290085,
0.02847488410770893,
0.033115290105342865,
-0.14878836274147034,
0.05394503474235535,
-0.08906246721744537,
0.16263583302497864,
0.15331678092479706,
-0.04628103971481323,
-0.004620762541890144,
-0.029802896082401276,
-0.006602721754461527,
0.029022566974163055,
0.13206148147583008,
-0.0002244010684080422,
-0.09227822721004486,
0.1252899318933487,
-0.06009463220834732,
0.07331199198961258,
-0.28357362747192383,
-0.07934822887182236,
-0.05065026506781578,
-0.0037879585288465023,
0.028049759566783905,
0.14506718516349792,
0.054623108357191086,
0.02885652333498001,
-0.010484003461897373,
0.03700435534119606,
-0.0036855919752269983,
0.09956890344619751,
-0.035033971071243286,
-0.06861656904220581
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SMIDS_3x_beit_large_Adamax_lr0001_fold4
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4418
- Accuracy: 0.895
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.204 | 1.0 | 450 | 0.3436 | 0.8833 |
| 0.1469 | 2.0 | 900 | 0.5296 | 0.8583 |
| 0.0667 | 3.0 | 1350 | 0.6067 | 0.8817 |
| 0.0324 | 4.0 | 1800 | 0.7174 | 0.885 |
| 0.032 | 5.0 | 2250 | 0.9357 | 0.8817 |
| 0.0045 | 6.0 | 2700 | 0.9206 | 0.8867 |
| 0.0 | 7.0 | 3150 | 1.0053 | 0.8917 |
| 0.0001 | 8.0 | 3600 | 0.9862 | 0.9017 |
| 0.0088 | 9.0 | 4050 | 0.7925 | 0.8867 |
| 0.0007 | 10.0 | 4500 | 1.0261 | 0.89 |
| 0.0 | 11.0 | 4950 | 0.9270 | 0.8967 |
| 0.0437 | 12.0 | 5400 | 0.9783 | 0.89 |
| 0.0167 | 13.0 | 5850 | 1.1590 | 0.8867 |
| 0.0397 | 14.0 | 6300 | 1.0434 | 0.88 |
| 0.0351 | 15.0 | 6750 | 1.1694 | 0.88 |
| 0.0 | 16.0 | 7200 | 1.2189 | 0.8833 |
| 0.0 | 17.0 | 7650 | 1.1687 | 0.89 |
| 0.0 | 18.0 | 8100 | 1.1997 | 0.8983 |
| 0.0001 | 19.0 | 8550 | 1.2204 | 0.8917 |
| 0.0 | 20.0 | 9000 | 1.2786 | 0.8817 |
| 0.0 | 21.0 | 9450 | 1.2705 | 0.88 |
| 0.0 | 22.0 | 9900 | 1.1773 | 0.8917 |
| 0.0 | 23.0 | 10350 | 1.1889 | 0.9 |
| 0.0509 | 24.0 | 10800 | 1.2585 | 0.9033 |
| 0.0 | 25.0 | 11250 | 1.3099 | 0.9 |
| 0.0 | 26.0 | 11700 | 1.3168 | 0.8933 |
| 0.0 | 27.0 | 12150 | 1.3139 | 0.895 |
| 0.0 | 28.0 | 12600 | 1.2973 | 0.8983 |
| 0.0 | 29.0 | 13050 | 1.3711 | 0.8933 |
| 0.0 | 30.0 | 13500 | 1.3739 | 0.89 |
| 0.0 | 31.0 | 13950 | 1.3210 | 0.9017 |
| 0.0 | 32.0 | 14400 | 1.3119 | 0.9067 |
| 0.0 | 33.0 | 14850 | 1.4197 | 0.8917 |
| 0.0 | 34.0 | 15300 | 1.4157 | 0.8983 |
| 0.0 | 35.0 | 15750 | 1.4289 | 0.8967 |
| 0.0 | 36.0 | 16200 | 1.3327 | 0.905 |
| 0.0 | 37.0 | 16650 | 1.3348 | 0.9033 |
| 0.0059 | 38.0 | 17100 | 1.3487 | 0.8983 |
| 0.0 | 39.0 | 17550 | 1.4891 | 0.89 |
| 0.0 | 40.0 | 18000 | 1.4854 | 0.8917 |
| 0.0 | 41.0 | 18450 | 1.4777 | 0.8917 |
| 0.0 | 42.0 | 18900 | 1.4627 | 0.895 |
| 0.0 | 43.0 | 19350 | 1.4712 | 0.8883 |
| 0.0 | 44.0 | 19800 | 1.4608 | 0.8883 |
| 0.0 | 45.0 | 20250 | 1.4561 | 0.8883 |
| 0.0 | 46.0 | 20700 | 1.4599 | 0.8933 |
| 0.0 | 47.0 | 21150 | 1.4534 | 0.8933 |
| 0.0 | 48.0 | 21600 | 1.4498 | 0.8933 |
| 0.0 | 49.0 | 22050 | 1.4473 | 0.8933 |
| 0.0 | 50.0 | 22500 | 1.4418 | 0.895 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_3x_beit_large_Adamax_lr0001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.895, "name": "Accuracy"}]}]}]} | image-classification | onizukal/SMIDS_3x_beit_large_Adamax_lr0001_fold4 | [
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-large-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:55:05+00:00 | [] | [] | TAGS
#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| SMIDS\_3x\_beit\_large\_Adamax\_lr0001\_fold4
=============================================
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4418
* Accuracy: 0.895
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.2
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
"TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
81,
115,
4,
30
] | [
"passage: TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
-0.12968555092811584,
0.17251011729240417,
-0.0023243443574756384,
0.1362919956445694,
0.1120586097240448,
0.015268749557435513,
0.14003369212150574,
0.16890837252140045,
-0.08239254355430603,
0.046998485922813416,
0.14023225009441376,
0.13628867268562317,
0.046756189316511154,
0.19432850182056427,
-0.052493587136268616,
-0.26022207736968994,
0.04113864526152611,
0.032812196761369705,
-0.020441479980945587,
0.1235608458518982,
0.09337224811315536,
-0.13087525963783264,
0.11667836457490921,
0.0301132183521986,
-0.20004093647003174,
-0.036873914301395416,
-0.007245634216815233,
-0.06722474098205566,
0.10533155500888824,
-0.0034045001957565546,
0.0691065788269043,
0.03768180310726166,
0.08387713134288788,
-0.13018712401390076,
0.002076903358101845,
0.042768821120262146,
0.0062860166653990746,
0.10383369028568268,
0.054196570068597794,
-0.015545758418738842,
0.0701410248875618,
-0.06851525604724884,
0.0672622099518776,
0.009240911342203617,
-0.11321496963500977,
-0.2700493633747101,
-0.10203396528959274,
0.07240316271781921,
0.08221714198589325,
0.06822962313890457,
0.008172801695764065,
0.16417047381401062,
-0.014714903198182583,
0.10454332083463669,
0.23100516200065613,
-0.26415953040122986,
-0.05532161891460419,
0.029576225206255913,
0.015004046261310577,
0.06490366160869598,
-0.10617698729038239,
-0.01859438419342041,
0.020827138796448708,
0.04436356946825981,
0.1411312073469162,
-0.010821618139743805,
-0.028378209099173546,
-0.021572042256593704,
-0.10856294631958008,
-0.08875563740730286,
0.18566860258579254,
0.05809066444635391,
-0.048288628458976746,
-0.07735078781843185,
-0.07127056270837784,
-0.17220835387706757,
-0.041861895471811295,
0.009548050351440907,
0.041730549186468124,
-0.04684269055724144,
-0.10686429589986801,
-0.031055882573127747,
-0.078252874314785,
-0.051669858396053314,
-0.023303553462028503,
0.13525931537151337,
0.03357808664441109,
0.05729198828339577,
-0.03593141585588455,
0.09915280342102051,
0.006841922644525766,
-0.17527513206005096,
-0.028045548126101494,
-0.0016165260458365083,
0.01563161052763462,
-0.020048104226589203,
-0.03057136945426464,
-0.06562764942646027,
-0.0016239769756793976,
0.149040088057518,
-0.06106079742312431,
0.06079873815178871,
-0.0069216229021549225,
0.04031313583254814,
-0.0486484132707119,
0.18668954074382782,
-0.028643600642681122,
-0.016713637858629227,
0.02057800441980362,
0.08857519924640656,
0.06818821281194687,
-0.03644402697682381,
-0.12566283345222473,
0.03087625838816166,
0.1283741444349289,
0.0027549222577363253,
-0.021953243762254715,
0.053039632737636566,
-0.06444176286458969,
-0.05842158570885658,
0.09141092747449875,
-0.08884678035974503,
0.03514961525797844,
-0.01055920124053955,
-0.08416686952114105,
-0.06807748228311539,
0.02709859050810337,
0.018840007483959198,
-0.00014874596672598273,
0.07201956957578659,
-0.09116632491350174,
0.015490563586354256,
-0.06551176309585571,
-0.10091431438922882,
0.01564670167863369,
-0.11040772497653961,
0.012323775328695774,
-0.09688954800367355,
-0.1969451904296875,
0.006960712838917971,
0.07738039642572403,
-0.05607226490974426,
-0.06792453676462173,
-0.03661259636282921,
-0.07637017965316772,
0.04143770784139633,
-0.01186586357653141,
0.07317496836185455,
-0.07456725090742111,
0.09119440615177155,
0.02237127535045147,
0.08760105073451996,
-0.056383248418569565,
0.04597126320004463,
-0.10241573303937912,
0.04992371052503586,
-0.19877833127975464,
0.07988634705543518,
-0.049189720302820206,
0.06190093979239464,
-0.09581396728754044,
-0.10568851977586746,
0.033553607761859894,
-0.04994693025946617,
0.068512924015522,
0.09739063680171967,
-0.17317676544189453,
-0.05787286534905434,
0.13517500460147858,
-0.09691634029150009,
-0.14840039610862732,
0.10115666687488556,
-0.05093328654766083,
0.019768450409173965,
0.04739697277545929,
0.21447287499904633,
0.062935970723629,
-0.0910891741514206,
-0.025994082912802696,
-0.03333966061472893,
0.044677652418613434,
-0.06483115255832672,
0.101903036236763,
0.027484174817800522,
0.0531504862010479,
0.02367355115711689,
-0.03332329913973808,
0.03818739578127861,
-0.08385370671749115,
-0.10085898637771606,
-0.05038752406835556,
-0.08557170629501343,
0.039683446288108826,
0.05594057962298393,
0.059847064316272736,
-0.10873348265886307,
-0.09023979306221008,
0.041734639555215836,
0.09406744688749313,
-0.07396076619625092,
0.02903648279607296,
-0.0904788002371788,
0.11622294038534164,
-0.08363831788301468,
-0.02404896728694439,
-0.17903628945350647,
-0.0417308546602726,
0.04055763781070709,
-0.01668366603553295,
-0.006775525398552418,
-0.0494389571249485,
0.07092705368995667,
0.087753064930439,
-0.05281677842140198,
-0.052284084260463715,
-0.05530114471912384,
0.008562305010855198,
-0.11059658974409103,
-0.1778055727481842,
-0.080107681453228,
-0.03797448053956032,
0.15019145607948303,
-0.15246915817260742,
0.0224970243871212,
0.0616903156042099,
0.12470164895057678,
0.05992257222533226,
-0.0469760037958622,
-0.007631834130734205,
0.0217386856675148,
-0.05561714619398117,
-0.0865136981010437,
0.05727535858750343,
0.035165008157491684,
-0.07172347605228424,
-0.019373787567019463,
-0.10040221363306046,
0.15015454590320587,
0.13185308873653412,
-0.0021352346520870924,
-0.045590728521347046,
-0.012053865939378738,
-0.06572475284337997,
-0.030354894697666168,
-0.04096601903438568,
0.01860888861119747,
0.1020345464348793,
0.017360014840960503,
0.14407898485660553,
-0.09213681519031525,
-0.037007302045822144,
0.053231216967105865,
-0.028658904135227203,
-0.03313332051038742,
0.0737093985080719,
0.021478038281202316,
-0.14289474487304688,
0.1502111405134201,
0.14915579557418823,
-0.04949729144573212,
0.12371271848678589,
-0.03663388267159462,
-0.06141006201505661,
-0.04545919969677925,
-0.03777514770627022,
0.01429951936006546,
0.1407921016216278,
-0.08363746106624603,
-0.006257671397179365,
0.05626929551362991,
0.018998416140675545,
-0.007220869418233633,
-0.1808812916278839,
0.0005758196348324418,
0.03530525416135788,
-0.04614398628473282,
-0.022574707865715027,
-0.014720434322953224,
0.000520858506206423,
0.09188775718212128,
0.02001834660768509,
-0.07113038748502731,
0.05185159295797348,
0.010694033466279507,
-0.056145116686820984,
0.16459684073925018,
-0.07884351164102554,
-0.19753409922122955,
-0.11793240904808044,
-0.08745986223220825,
-0.10736268758773804,
0.013000035658478737,
0.067270427942276,
-0.050670597702264786,
-0.04932181537151337,
-0.1026671901345253,
-0.044550344347953796,
0.021845674142241478,
0.024347107857465744,
0.053595975041389465,
-0.00796813890337944,
0.08411940932273865,
-0.09194666892290115,
-0.03317512199282646,
-0.014813165180385113,
0.01894056238234043,
0.0670066773891449,
0.01914203353226185,
0.11091019958257675,
0.08160436898469925,
-0.0286879725754261,
0.05666669085621834,
-0.01685662567615509,
0.26526889204978943,
-0.06748054921627045,
-0.006749235559254885,
0.1391732543706894,
-0.013490693643689156,
0.0842166393995285,
0.12729591131210327,
0.04176322743296623,
-0.0955888107419014,
-0.01310211792588234,
-0.0005005627172067761,
-0.05257550999522209,
-0.1536482274532318,
-0.04132819548249245,
-0.04548354819417,
-0.0018228141125291586,
0.13951772451400757,
0.038064174354076385,
0.02505229413509369,
0.07843583822250366,
0.020602436736226082,
0.05678323283791542,
-0.0175874512642622,
0.10429482907056808,
0.08156884461641312,
0.06449971348047256,
0.13376133143901825,
-0.036523740738630295,
-0.019790813326835632,
0.05638623237609863,
0.042081572115421295,
0.20467498898506165,
-0.025362396612763405,
0.14717818796634674,
0.026553483679890633,
0.19327539205551147,
0.017808275297284126,
0.07306244969367981,
-0.014873637817800045,
0.0007499073399230838,
-0.019323905929923058,
-0.04713669419288635,
-0.0638502836227417,
0.03312433883547783,
-0.016851995140314102,
0.05682634562253952,
-0.09328699111938477,
0.03906902298331261,
0.05959288775920868,
0.30634987354278564,
0.0654144361615181,
-0.4125381410121918,
-0.09821337461471558,
0.012344546616077423,
0.0008716733427718282,
-0.05509618669748306,
-0.007402430288493633,
0.0980701595544815,
-0.09973937273025513,
0.0819711834192276,
-0.09416680037975311,
0.08507230132818222,
-0.0846736952662468,
0.020382488146424294,
0.07683569937944412,
0.055889930576086044,
0.012921135872602463,
0.05964238941669464,
-0.21880683302879333,
0.2499670386314392,
0.01837102696299553,
0.04415145888924599,
-0.08875706046819687,
0.009965145029127598,
0.03320525959134102,
0.05923061817884445,
0.08590700477361679,
0.0061045982874929905,
-0.09025654941797256,
-0.18889141082763672,
-0.12562422454357147,
0.000394518458051607,
0.06176565960049629,
-0.03729195147752762,
0.09444484859704971,
-0.018019067123532295,
-0.012201022356748581,
0.02127370797097683,
0.0009904175531119108,
-0.035084888339042664,
-0.10356581956148148,
0.02010609768331051,
0.03430531173944473,
-0.011726552620530128,
-0.06489048153162003,
-0.11480618268251419,
-0.035277001559734344,
0.16168422996997833,
0.05518770217895508,
-0.07543513178825378,
-0.14076673984527588,
0.0721859410405159,
0.0775376707315445,
-0.08563373237848282,
0.03936640918254852,
-0.016648126766085625,
0.14995604753494263,
0.020845195278525352,
-0.0889848992228508,
0.10199198871850967,
-0.05838112160563469,
-0.17863209545612335,
-0.04141612723469734,
0.09901762008666992,
0.007052883040159941,
0.05273612216114998,
0.004226623103022575,
0.06022334843873978,
-0.03518751636147499,
-0.05844981223344803,
0.06672939658164978,
-0.007545650005340576,
0.10645230114459991,
-0.014578265137970448,
0.008669902570545673,
0.028680432587862015,
-0.046410609036684036,
0.00012374592188280076,
0.1686571091413498,
0.24114695191383362,
-0.10427109152078629,
0.060499124228954315,
0.03038850799202919,
-0.030858036130666733,
-0.18259160220623016,
0.01086394116282463,
0.07622820883989334,
-0.00013084696547593921,
0.04143662750720978,
-0.1601918637752533,
0.05532059073448181,
0.10498367995023727,
-0.043228019028902054,
0.08107142895460129,
-0.27694207429885864,
-0.1185181736946106,
0.09238865971565247,
0.13856256008148193,
0.06877914071083069,
-0.13106170296669006,
-0.043299052864313126,
-0.041688259690999985,
-0.17338812351226807,
0.13653364777565002,
-0.057192787528038025,
0.1145344004034996,
-0.039500072598457336,
0.08082033693790436,
0.014952262863516808,
-0.056017596274614334,
0.14574900269508362,
0.0056154001504182816,
0.08686088770627975,
-0.07213473320007324,
-0.0020430299919098616,
0.10663212835788727,
-0.10254329442977905,
0.07232339680194855,
-0.08735590428113937,
0.0618043914437294,
-0.10790637135505676,
-0.003900582902133465,
-0.07402003556489944,
0.013697824440896511,
-0.01366274245083332,
-0.04917207732796669,
-0.04516566917300224,
0.03515308350324631,
0.0627121776342392,
-0.01822420209646225,
0.20940853655338287,
0.06430324167013168,
0.08635561168193817,
0.1727360188961029,
0.054769597947597504,
-0.10558480769395828,
-0.09403572231531143,
-0.043973103165626526,
-0.029537810012698174,
0.05986782908439636,
-0.1372820883989334,
0.0528247207403183,
0.11996810883283615,
0.013451187871396542,
0.12858225405216217,
0.055897701531648636,
-0.030677761882543564,
0.03560479357838631,
0.062153734266757965,
-0.17216050624847412,
-0.08662130683660507,
-0.009840693324804306,
0.030872231349349022,
-0.13055209815502167,
0.0458756685256958,
0.12116101384162903,
-0.05953402817249298,
-0.015017039142549038,
-0.004467411432415247,
0.03673877567052841,
-0.00978675577789545,
0.15920081734657288,
0.048089753836393356,
0.055168475955724716,
-0.11802823096513748,
0.11332250386476517,
0.05730176344513893,
-0.07302459329366684,
0.03206014260649681,
0.05020790174603462,
-0.1039617657661438,
-0.021727759391069412,
0.03114185482263565,
0.15037071704864502,
-0.06283780187368393,
-0.045329563319683075,
-0.1358855813741684,
-0.09226331859827042,
0.06643375009298325,
0.07981554418802261,
0.09349396824836731,
0.016502337530255318,
-0.03525979816913605,
-0.013309485279023647,
-0.10845191776752472,
0.11000601947307587,
0.04338005557656288,
0.09121100604534149,
-0.17974577844142914,
0.05434896796941757,
-0.001805671607144177,
0.07240304350852966,
-0.02173563651740551,
-0.00018242778605781496,
-0.08797106891870499,
0.0035262287128716707,
-0.10818753391504288,
0.024682866409420967,
-0.052850391715765,
0.006376184988766909,
-0.020511267706751823,
-0.05819518491625786,
-0.06372886151075363,
0.024663057178258896,
-0.1193968653678894,
-0.05304655060172081,
0.02193489298224449,
0.03176874667406082,
-0.11983832716941833,
-0.04395153746008873,
0.02043171599507332,
-0.08966860175132751,
0.09786758571863174,
0.06017395853996277,
-0.00797541905194521,
0.007467431016266346,
0.0038150406908243895,
-0.022212069481611252,
0.06630469858646393,
0.0074848150834441185,
0.08584009110927582,
-0.11553936451673508,
-0.022143544629216194,
0.016299601644277573,
-0.004447818733751774,
0.018147116526961327,
0.1585858017206192,
-0.12092386186122894,
0.00018621055642142892,
-0.014765054918825626,
-0.06592588871717453,
-0.06358986347913742,
0.0692417323589325,
0.10919524729251862,
0.02367839775979519,
0.2122299075126648,
-0.054594267159700394,
0.015877852216362953,
-0.21000300347805023,
-0.011462570168077946,
0.005311926826834679,
-0.13887609541416168,
-0.10537440329790115,
-0.032787878066301346,
0.0637630894780159,
-0.07039659470319748,
0.1177176982164383,
0.03537357598543167,
0.020886771380901337,
0.02911887876689434,
0.024869181215763092,
-0.002677198965102434,
0.013766518794000149,
0.1633930504322052,
0.014011929742991924,
-0.02872646041214466,
0.1283825933933258,
0.029096294194459915,
0.09337089955806732,
0.11805824935436249,
0.1763046532869339,
0.11451227962970734,
0.0477789007127285,
0.09043081104755402,
0.0520024336874485,
-0.02513159066438675,
-0.22147811949253082,
0.036259569227695465,
-0.039764102548360825,
0.1483127623796463,
-0.0033327124547213316,
0.15980194509029388,
0.09223487228155136,
-0.18392090499401093,
0.040660299360752106,
-0.037005215883255005,
-0.07937940210103989,
-0.08421849459409714,
-0.12178675830364227,
-0.1033017709851265,
-0.1509413868188858,
0.0028559700585901737,
-0.10428426414728165,
0.022927863523364067,
0.11217869818210602,
-0.008710348978638649,
-0.010019375011324883,
0.11695955693721771,
-0.026584560051560402,
0.026202335953712463,
0.03870072960853577,
0.00616151699796319,
-0.05987776443362236,
-0.04411191865801811,
-0.08036603778600693,
0.014018801040947437,
0.03200533241033554,
0.055842287838459015,
-0.03226681798696518,
-0.007200593128800392,
0.03782269358634949,
-0.009845683351159096,
-0.12363012880086899,
0.013544945046305656,
0.004753641318529844,
0.05189259722828865,
0.0008605605689808726,
0.01290043629705906,
0.03187544271349907,
-0.015199882909655571,
0.193119078874588,
-0.07321906089782715,
-0.02744952403008938,
-0.12274995446205139,
0.17869888246059418,
0.0023205638863146305,
-0.049724213778972626,
0.05292708799242973,
-0.09127075970172882,
-0.020290102809667587,
0.1547212302684784,
0.18941837549209595,
-0.07176556438207626,
-0.01638839766383171,
-0.017501909285783768,
-0.01388427522033453,
-0.022741587832570076,
0.09889717400074005,
0.09887372702360153,
-0.007504772394895554,
-0.07518953084945679,
-0.028498217463493347,
-0.06611054390668869,
-0.03444022685289383,
-0.03838160261511803,
0.06909165531396866,
-0.004605968948453665,
0.007089514285326004,
-0.0751754567027092,
0.04334408789873123,
-0.02207781746983528,
-0.060899440199136734,
0.06262887269258499,
-0.21282166242599487,
-0.17796695232391357,
0.006926008500158787,
0.07579630613327026,
0.0016649233875796199,
0.04621230810880661,
-0.010005760937929153,
0.018681904301047325,
0.07549776136875153,
-0.022177988663315773,
-0.0866948589682579,
-0.09604813903570175,
0.1083223819732666,
-0.1344224065542221,
0.25299492478370667,
-0.03893125429749489,
0.035907670855522156,
0.12175600975751877,
0.041717030107975006,
-0.13353091478347778,
0.033571965992450714,
0.03969275578856468,
-0.03212675452232361,
0.005746500100940466,
0.14248594641685486,
-0.037242501974105835,
0.07988674938678741,
0.04599026218056679,
-0.10243327170610428,
-0.039464809000492096,
-0.04960913211107254,
-0.011240639723837376,
-0.024744588881731033,
-0.05439573898911476,
-0.03649099916219711,
0.13208730518817902,
0.17168967425823212,
-0.04232889041304588,
-0.023784559220075607,
-0.06460724771022797,
0.030773790553212166,
0.0774260088801384,
-0.033050306141376495,
-0.05197038874030113,
-0.23585109412670135,
0.0024181774351745844,
0.05249672383069992,
-0.013345940038561821,
-0.20789918303489685,
-0.11062979698181152,
0.006115853786468506,
-0.05795856565237045,
-0.07630864530801773,
0.09230074286460876,
0.06326484680175781,
0.035358402878046036,
-0.06319575011730194,
0.03810267895460129,
-0.07874377071857452,
0.1419457346200943,
-0.1448507308959961,
-0.07860494405031204
] |
null | null | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: Jack51003/ppo-Huggy
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
| {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | reinforcement-learning | Jack51003/ppo-Huggy | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | 2024-02-09T01:58:38+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
browser: URL
- A *longer tutorial* to understand how works ML-Agents:
URL
### Resume the training
### Watch your Agent play
You can watch your agent playing directly in your browser
1. If the environment is part of ML-Agents official environments, go to URL
2. Step 1: Find your model_id: Jack51003/ppo-Huggy
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play
| [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: Jack51003/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n",
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: Jack51003/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
44,
199
] | [
"passage: TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: Jack51003/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
0.010951711796224117,
0.016299601644277573,
-0.004121433012187481,
0.04120408371090889,
0.1317567080259323,
0.008388412185013294,
0.17355412244796753,
0.13817386329174042,
0.11327388137578964,
0.08615383505821228,
0.08975845575332642,
0.06366035342216492,
0.05181408300995827,
0.19016215205192566,
0.06166312098503113,
-0.19863122701644897,
-0.00937559548765421,
-0.07262855768203735,
0.046174172312021255,
0.09127230942249298,
0.03899025171995163,
-0.03819293528795242,
0.06763341277837753,
0.020528843626379967,
-0.05167827755212784,
-0.007103846408426762,
-0.07026732712984085,
-0.027338290587067604,
0.0408022440969944,
0.011723335832357407,
-0.02699386142194271,
-0.03168274834752083,
0.06183122098445892,
-0.21873439848423004,
0.03178448602557182,
0.06471087038516998,
-0.017809147015213966,
0.02060106210410595,
0.1050843596458435,
0.04643384739756584,
0.08325093239545822,
-0.08294104039669037,
0.07389725744724274,
0.06240231171250343,
-0.07138726860284805,
-0.026050301268696785,
-0.12211982905864716,
0.061838820576667786,
0.23519544303417206,
0.10509747266769409,
0.0019241382833570242,
0.10692664235830307,
-0.06921225786209106,
0.038202546536922455,
0.18833069503307343,
-0.22301077842712402,
-0.06779446452856064,
0.09216228127479553,
0.0758761614561081,
0.009067618288099766,
-0.03225816786289215,
0.03506842255592346,
-0.018997790291905403,
0.039447229355573654,
0.0822209045290947,
-0.043745145201683044,
0.23444628715515137,
-0.018642690032720566,
-0.07291167229413986,
-0.08567299693822861,
0.05740007013082504,
0.07861941307783127,
-0.058492280542850494,
-0.22619736194610596,
0.027288487181067467,
0.1199941411614418,
-0.02899736352264881,
0.0037249813321977854,
0.06661776453256607,
-0.01893758215010166,
-0.054726697504520416,
-0.11157748848199844,
-0.05130092799663544,
-0.0745704248547554,
0.09234912693500519,
0.16909901797771454,
-0.0007751706871204078,
-0.02012123167514801,
0.05702439695596695,
0.06115412339568138,
0.05137602239847183,
-0.02948755957186222,
-0.01993567869067192,
-0.02134273387491703,
-0.1013471931219101,
-0.0002904660359490663,
0.0016417807200923562,
0.0696171298623085,
0.050987064838409424,
0.11234935373067856,
0.014480202458798885,
0.023404616862535477,
0.03578638285398483,
0.05979251116514206,
-0.0030660657212138176,
0.12076123058795929,
0.017652073875069618,
0.051699697971343994,
0.050661589950323105,
0.06283809244632721,
0.05008373036980629,
-0.05696573853492737,
-0.10225756466388702,
0.08902734518051147,
-0.10048434883356094,
0.0941912829875946,
0.08619756251573563,
0.02090930938720703,
-0.0822904035449028,
-0.03355257958173752,
-0.01035449281334877,
-0.1376810520887375,
0.08877095580101013,
0.053740520030260086,
-0.042399827390909195,
-0.10776399821043015,
-0.0011792373843491077,
-0.0012270888546481729,
-0.09546373039484024,
0.023159051313996315,
-0.01952843740582466,
0.045220643281936646,
-0.008893330581486225,
-0.04453885182738304,
0.09611102938652039,
-0.02895505167543888,
-0.02253788895905018,
-0.14911296963691711,
-0.08904169499874115,
-0.06376256048679352,
0.05770551413297653,
-0.04133100435137749,
-0.13417948782444,
-0.04716605693101883,
0.01910949870944023,
-0.09614821523427963,
-0.0004047768306918442,
-0.012252549640834332,
-0.05959068983793259,
-0.010586154647171497,
-0.029361162334680557,
0.07031691819429398,
0.17001183331012726,
0.0343814343214035,
-0.012012038379907608,
0.07244302332401276,
-0.17055785655975342,
0.10761736333370209,
-0.11398565769195557,
0.17534182965755463,
-0.05947805941104889,
0.010501573793590069,
0.0375107079744339,
0.019312946125864983,
0.01637752540409565,
0.17470361292362213,
-0.04785507544875145,
-0.11974682658910751,
0.14735932648181915,
-0.02859509550035,
-0.13283120095729828,
0.049205631017684937,
0.027067596092820168,
0.0810350775718689,
0.027377953752875328,
0.22978384792804718,
0.09821640700101852,
-0.27317601442337036,
0.07227910310029984,
0.03468503803014755,
-0.1476028561592102,
0.009079067967832088,
0.14619626104831696,
-0.06352967023849487,
-0.01657821424305439,
-0.004629844333976507,
-0.1421428918838501,
0.06827612221240997,
-0.011286155320703983,
-0.02743060700595379,
0.04147796705365181,
-0.023110365495085716,
-0.05700767785310745,
-0.005851940717548132,
-0.0007667004829272628,
-0.053742535412311554,
-0.09821116179227829,
-0.06907004863023758,
0.07143117487430573,
-0.02036689966917038,
0.07684784382581711,
-0.06146373599767685,
0.11585447192192078,
0.023324761539697647,
0.05446698144078255,
-0.08396786451339722,
-0.08690572530031204,
0.008582410402595997,
0.02852778322994709,
0.09250348806381226,
-0.09514559060335159,
0.05802399292588234,
0.0656236857175827,
0.007099605165421963,
-0.08117331564426422,
-0.10807615518569946,
-0.017009245231747627,
-0.0719638392329216,
-0.12045135349035263,
-0.06564343720674515,
-0.06754882633686066,
0.12269226461648941,
-0.07207266986370087,
0.06931111961603165,
-0.10547489672899246,
0.02985461615025997,
-0.015047317370772362,
-0.04320715740323067,
0.05651688948273659,
-0.00010890673729591072,
0.03284960240125656,
-0.06969659775495529,
0.10450711101293564,
0.031322725117206573,
-0.08896534889936447,
0.08012480288743973,
-0.06330080330371857,
-0.053455520421266556,
0.10024011135101318,
0.0449923500418663,
-0.017752939835190773,
-0.039034225046634674,
-0.09543517976999283,
0.0193073358386755,
-0.08697563409805298,
0.006383312400430441,
0.16212104260921478,
0.10618340969085693,
0.1217174232006073,
-0.0823076069355011,
-0.06988099962472916,
-0.011216556653380394,
-0.10978775471448898,
-0.06109340861439705,
0.15956199169158936,
0.046691685914993286,
0.07734280824661255,
0.04749095439910889,
0.05592361465096474,
0.08644775301218033,
0.08076728880405426,
0.021710095927119255,
-0.11773481220006943,
-0.02429944835603237,
0.06752081215381622,
0.05476471781730652,
0.01880711317062378,
0.021268226206302643,
-0.005308330524712801,
0.020845036953687668,
-0.04529053717851639,
-0.0059545692056417465,
-0.14437367022037506,
-0.07551459223031998,
0.015974510461091995,
-0.03575318306684494,
0.04688139259815216,
-0.024938231334090233,
-0.04307914897799492,
0.05744658783078194,
0.09582357853651047,
0.031939759850502014,
0.006590073928236961,
-0.043987955898046494,
-0.12273012846708298,
0.07484636455774307,
-0.0794360414147377,
-0.3144942820072174,
-0.125722274184227,
-0.11481064558029175,
-0.05524488538503647,
0.02029374986886978,
0.06106836721301079,
-0.1615390032529831,
-0.020475998520851135,
-0.11795534193515778,
-0.038953132927417755,
0.028844503685832024,
-0.06365054845809937,
0.20111869275569916,
0.10446037352085114,
0.025038104504346848,
-0.07196524739265442,
-0.025005793198943138,
0.011583518236875534,
-0.03942254185676575,
0.035536449402570724,
0.034043435007333755,
0.048945147544145584,
0.12099164724349976,
0.06599632650613785,
0.05821076035499573,
-0.03567900136113167,
0.08113888651132584,
-0.06039554998278618,
-0.02181403711438179,
0.10622461885213852,
-0.017828309908509254,
0.07917602360248566,
0.03223242610692978,
0.03343767300248146,
-0.0370786227285862,
0.046719446778297424,
0.00869170855730772,
-0.06525608897209167,
-0.19809305667877197,
-0.08786812424659729,
-0.023261599242687225,
0.2515510618686676,
0.10443675518035889,
0.08822118490934372,
-0.058223556727170944,
-0.02710074558854103,
-0.0011571792419999838,
-0.04363400116562843,
0.14959818124771118,
0.12998203933238983,
-0.05090118199586868,
-0.08103325963020325,
-0.0024683591909706593,
-0.036792904138565063,
0.0242005605250597,
0.09259545058012009,
-0.0077543254010379314,
0.03684074804186821,
0.04908636957406998,
0.00665584672242403,
0.02641325257718563,
-0.043321117758750916,
-0.07077158242464066,
0.07329682260751724,
0.042799212038517,
-0.0006972734117880464,
-0.03131571039557457,
-0.08626371622085571,
-0.03644726425409317,
0.09639040380716324,
0.1276095062494278,
-0.058753106743097305,
-0.10135392099618912,
0.07222820818424225,
0.08899791538715363,
0.0872003361582756,
0.01987622305750847,
-0.13323169946670532,
-0.04730452224612236,
0.008117789402604103,
-0.12448879331350327,
0.02213914506137371,
-0.008047468960285187,
0.029679086059331894,
-0.18031509220600128,
0.06347687542438507,
0.017789408564567566,
0.13425712287425995,
0.07133534550666809,
0.0015531618846580386,
0.027639545500278473,
0.07514425367116928,
-0.02089676260948181,
0.06195048242807388,
-0.18784287571907043,
0.06361713260412216,
-0.003416895167902112,
0.07746180146932602,
-0.06234454736113548,
0.013024887070059776,
0.07229484617710114,
-0.033518411219120026,
0.17818546295166016,
0.03551881015300751,
0.05837109684944153,
-0.06914257258176804,
-0.1798458993434906,
-0.040732841938734055,
-0.012328644283115864,
-0.09384594857692719,
0.06609226763248444,
-0.000638292811345309,
-0.03270372375845909,
-0.09655790776014328,
0.16449357569217682,
0.002392918337136507,
-0.06742919981479645,
-0.0026104405988007784,
-0.046375665813684464,
-0.010137802921235561,
-0.0563943088054657,
-0.03572400286793709,
-0.027058806270360947,
0.23149731755256653,
0.12503990530967712,
-0.011510122567415237,
-0.09585466235876083,
-0.030814126133918762,
-0.04788346588611603,
-0.016123799607157707,
-0.02851984277367592,
-0.0145029341802001,
0.1370435208082199,
-0.09377751499414444,
-0.04212542623281479,
-0.014610680751502514,
-0.09930752217769623,
-0.11575333774089813,
-0.01432426180690527,
0.26030173897743225,
-0.025452302768826485,
0.0934203565120697,
-0.02524171769618988,
0.01319582387804985,
-0.009775003418326378,
-0.08433865755796432,
0.16690309345722198,
0.16968271136283875,
0.03319433331489563,
0.05106956511735916,
-0.10576744377613068,
0.047470301389694214,
-0.1132434830069542,
-0.022503431886434555,
0.19208784401416779,
0.3283122181892395,
-0.026674386113882065,
0.19444017112255096,
0.04723110422492027,
-0.055913906544446945,
-0.20796982944011688,
-0.07521330565214157,
0.0379001758992672,
-0.003040859941393137,
0.1382409930229187,
-0.1389220952987671,
0.02048615925014019,
0.0332779698073864,
-0.01086906436830759,
-0.0032069801818579435,
-0.15268787741661072,
-0.09918832033872604,
-0.014892013743519783,
0.08620373904705048,
0.03323394060134888,
-0.10358179360628128,
-0.04665965586900711,
-0.03397040814161301,
-0.07967641204595566,
0.08698152005672455,
-0.16590799391269684,
0.08238048106431961,
-0.0013453857973217964,
0.0395226813852787,
0.04667241871356964,
-0.03474580496549606,
0.1306760311126709,
-0.08299708366394043,
-0.034395623952150345,
-0.0828484520316124,
-0.012277747504413128,
0.02019978128373623,
-0.11875185370445251,
0.07349622994661331,
-0.08284717798233032,
-0.04845335707068443,
-0.19439566135406494,
-0.048103928565979004,
-0.028844915330410004,
0.045678723603487015,
-0.02104499191045761,
-0.009689145721495152,
-0.007287087384611368,
0.0575811006128788,
0.08114423602819443,
0.035736504942178726,
0.07543759047985077,
-0.02090257965028286,
-0.007241289131343365,
0.1171502023935318,
0.08195774257183075,
0.022412536665797234,
-0.08511769771575928,
-0.03344579413533211,
-0.04932323470711708,
-0.014279124327003956,
-0.10383936017751694,
-0.0001746306661516428,
0.029205774888396263,
0.013263056054711342,
0.06445292383432388,
0.05702461674809456,
-0.09826146811246872,
-0.03856382891535759,
0.07345721870660782,
-0.11941447108983994,
-0.14354808628559113,
-0.04672877863049507,
-0.08251536637544632,
-0.054461847990751266,
-0.07950843125581741,
0.03604332357645035,
-0.03409317880868912,
-0.006528693251311779,
0.0428319089114666,
0.044053561985492706,
-0.07713489979505539,
0.04264092817902565,
-0.022642608731985092,
0.025647791102528572,
-0.06287334859371185,
0.15126001834869385,
0.012706352397799492,
-0.06656727939844131,
0.04079359397292137,
0.2007761001586914,
-0.04684588313102722,
-0.07646217197179794,
-0.0055865016765892506,
0.08344762027263641,
0.1893407106399536,
-0.031113531440496445,
-0.044139716774225235,
-0.06722403317689896,
0.08544252067804337,
-0.10111180692911148,
-0.006289706099778414,
-0.09375517070293427,
0.032784827053546906,
0.08537010103464127,
-0.12611429393291473,
0.09480715543031693,
-0.0026681567542254925,
-0.07418312132358551,
-0.1124558225274086,
0.10662254691123962,
0.053818732500076294,
0.1609441488981247,
-0.017027487978339195,
-0.034673113375902176,
-0.15427182614803314,
-0.0008771401480771601,
0.0036471367347985506,
-0.006807864643633366,
-0.16363690793514252,
-0.017067179083824158,
-0.0161574836820364,
0.06155533716082573,
-0.014047869481146336,
0.038809191435575485,
-0.05099989473819733,
-0.07671250402927399,
-0.05513327941298485,
0.07616174966096878,
-0.03572332113981247,
-0.03226560726761818,
0.01857299916446209,
-0.07827189564704895,
0.09052382409572601,
0.08117081969976425,
-0.029543699696660042,
-0.06080722063779831,
-0.05759252607822418,
-0.02078748308122158,
0.028748389333486557,
-0.045167647302150726,
0.02983585186302662,
-0.17479468882083893,
0.012755568139255047,
-0.037827927619218826,
-0.09957793354988098,
0.01855490542948246,
0.1231357604265213,
-0.07234907895326614,
0.057391874492168427,
0.014622258022427559,
-0.13111014664173126,
-0.07781635969877243,
0.010251968167722225,
0.008848817087709904,
0.06750461459159851,
0.08143309503793716,
-0.07504386454820633,
0.18138472735881805,
-0.14178194105625153,
-0.00864903349429369,
0.009995406493544579,
0.02091890387237072,
0.011909655295312405,
-0.09392800182104111,
0.03538760542869568,
-0.013837330043315887,
0.1428997814655304,
0.09714478999376297,
-0.04393317550420761,
0.032260868698358536,
0.00014811621804255992,
0.1280842423439026,
0.004334805533289909,
0.03871653974056244,
-0.036139536648988724,
-0.0015708270948380232,
0.0523054301738739,
-0.005373071879148483,
0.08117423206567764,
-0.127013698220253,
0.09168046712875366,
0.0796080082654953,
0.12159588932991028,
0.05533066391944885,
0.0702723041176796,
-0.10803837329149246,
-0.133082777261734,
-0.042789410799741745,
0.009073781780898571,
0.03600718826055527,
-0.07067130506038666,
0.24221879243850708,
0.09555720537900925,
-0.20585495233535767,
0.06720106303691864,
0.004006851464509964,
0.01772160641849041,
-0.09788713604211807,
-0.11774292588233948,
-0.0024224587250500917,
-0.22370187938213348,
0.0765923410654068,
-0.06252335757017136,
0.0032768668606877327,
-0.07463710755109787,
-0.029733560979366302,
-0.010460137389600277,
0.06395062059164047,
-0.10755113512277603,
-0.053852953016757965,
0.08160009235143661,
-0.039058584719896317,
0.004429420456290245,
-0.0240325890481472,
-0.018292048946022987,
-0.029262885451316833,
-0.08558007329702377,
0.06493157148361206,
0.05600171908736229,
0.004222765099257231,
0.06418664008378983,
-0.0631883516907692,
-0.06978234648704529,
0.029763182625174522,
-0.0148788932710886,
0.023080995306372643,
0.13419926166534424,
0.047744959592819214,
-0.10632075369358063,
-0.0009012579685077071,
0.20193222165107727,
-0.05590503662824631,
0.007056370377540588,
-0.08750388771295547,
0.14967893064022064,
-0.025343799963593483,
-0.059256263077259064,
-0.042582377791404724,
-0.09133205562829971,
-0.08670468628406525,
0.22550593316555023,
0.11850060522556305,
-0.0467115081846714,
0.01667105033993721,
-0.030979830771684647,
0.024457992985844612,
0.006767016835510731,
0.11054094135761261,
0.07343778014183044,
0.10697007179260254,
-0.05796612799167633,
-0.019779138267040253,
-0.0028649424202740192,
-0.0701652318239212,
-0.16204418241977692,
-0.017918473109602928,
0.026195067912340164,
-0.04343224689364433,
-0.021727602928876877,
0.051420386880636215,
-0.10375915467739105,
-0.11273138225078583,
0.11639508605003357,
-0.09992333501577377,
-0.06119273230433464,
-0.020655447617173195,
0.0226278118789196,
0.01641680672764778,
0.13265667855739594,
0.06317204236984253,
0.042489856481552124,
0.09104341268539429,
-0.032137103378772736,
-0.07837434113025665,
0.02503899112343788,
0.07583244144916534,
-0.11828272044658661,
0.2039654552936554,
-0.03388315066695213,
0.04838676005601883,
0.052824899554252625,
0.018357807770371437,
-0.14021745324134827,
0.06681328266859055,
0.022287622094154358,
-0.1572522521018982,
0.002744763158261776,
0.07392442226409912,
-0.07190587371587753,
-0.048862043768167496,
0.07103366404771805,
-0.040309395641088486,
-0.013146169483661652,
0.08421193063259125,
-0.004190445877611637,
-0.047241486608982086,
0.07726100087165833,
-0.1567981243133545,
0.09120087325572968,
0.14823156595230103,
-0.06466105580329895,
-0.0038896084297448397,
-0.05421504005789757,
0.043406564742326736,
0.041267719119787216,
0.06716226786375046,
-0.01042165607213974,
-0.15229590237140656,
0.014446944929659367,
-0.004468714352697134,
0.02070426754653454,
-0.30787527561187744,
-0.11823934316635132,
-0.0441201813519001,
-0.047385867685079575,
-0.05359990894794464,
0.10159812867641449,
0.10401607304811478,
-0.0073676202446222305,
-0.010432087816298008,
-0.1956283152103424,
0.051303476095199585,
0.17714227735996246,
-0.0724354162812233,
-0.00260770320892334
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_qa_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7895
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 250 | 2.4602 |
| 2.7592 | 2.0 | 500 | 1.8869 |
| 2.7592 | 3.0 | 750 | 1.7895 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "my_awesome_qa_model", "results": []}]} | question-answering | Gekyume/my_awesome_qa_model | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"question-answering",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-09T01:58:51+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us
| my\_awesome\_qa\_model
======================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7895
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
### Training results
### Framework versions
* Transformers 4.37.2
* Pytorch 2.1.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
65,
98,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3### Training results### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.10754022747278214,
0.0872088298201561,
-0.0019671760965138674,
0.1031731516122818,
0.12662118673324585,
0.021355096250772476,
0.1408969759941101,
0.11246659606695175,
-0.08133538067340851,
0.057961370795965195,
0.13372007012367249,
0.11614994704723358,
-0.0014247855870053172,
0.08982254564762115,
-0.061164114624261856,
-0.2010907679796219,
0.003977024462074041,
0.03876778483390808,
-0.09058649092912674,
0.11504953354597092,
0.08734682947397232,
-0.1371190845966339,
0.07674644887447357,
-0.005596425384283066,
-0.1737377941608429,
0.026906685903668404,
0.006826930213719606,
-0.037051573395729065,
0.12136603146791458,
0.0230260007083416,
0.13227041065692902,
0.02333933487534523,
0.0793963223695755,
-0.196542888879776,
0.01602010242640972,
0.060070548206567764,
-0.002640089485794306,
0.07753213495016098,
0.02531961351633072,
0.005987960379570723,
0.08444834500551224,
-0.08038125932216644,
0.06219916418194771,
0.029776426032185555,
-0.12545451521873474,
-0.24519887566566467,
-0.10116704553365707,
0.051408927887678146,
0.0966176986694336,
0.09681490063667297,
-0.012700347229838371,
0.14112670719623566,
-0.07637529820203781,
0.08486101031303406,
0.23750220239162445,
-0.31353721022605896,
-0.07489734143018723,
0.04096661135554314,
0.03493848443031311,
0.07171598076820374,
-0.10224577784538269,
-0.03190091252326965,
0.07607397437095642,
0.027257679030299187,
0.0994802862405777,
-0.038040176033973694,
-0.08011651039123535,
0.02577739953994751,
-0.14543692767620087,
-0.011226446367800236,
0.1627172976732254,
0.06518334150314331,
-0.04557962715625763,
-0.03410733863711357,
-0.0633695125579834,
-0.11915940791368484,
-0.02995401807129383,
-0.0380680151283741,
0.0424710214138031,
-0.036184631288051605,
-0.07862924039363861,
-0.016081467270851135,
-0.10214227437973022,
-0.09918496757745743,
-0.05076071619987488,
0.15744060277938843,
0.04198051244020462,
0.016190266236662865,
-0.02350858971476555,
0.10177965462207794,
-0.03384663164615631,
-0.14484857022762299,
0.0024046897888183594,
0.021458955481648445,
-0.005758507642894983,
-0.050115786492824554,
-0.04637562111020088,
-0.052851658314466476,
0.03599225729703903,
0.18847452104091644,
-0.07970503717660904,
0.041432641446590424,
0.027523746713995934,
0.0380459800362587,
-0.09761705249547958,
0.14816364645957947,
-0.06221051886677742,
-0.01686052232980728,
-0.0029129774775356054,
0.08140425384044647,
0.03265586495399475,
0.004203749354928732,
-0.08984926342964172,
0.02056715078651905,
0.08919528126716614,
0.01930347830057144,
-0.046131402254104614,
0.05462510138750076,
-0.05041464418172836,
-0.0005283366190269589,
0.015836670994758606,
-0.08075949549674988,
0.027119319885969162,
0.00893267709761858,
-0.06047888100147247,
-0.04047316685318947,
0.024507436901330948,
0.022057097405195236,
0.021197395399212837,
0.09375954419374466,
-0.09806183725595474,
0.008306441828608513,
-0.09094735234975815,
-0.10549817979335785,
0.023201627656817436,
-0.06500817835330963,
0.03355498984456062,
-0.09217902272939682,
-0.16941078007221222,
-0.013662878423929214,
0.059947557747364044,
-0.030940692871809006,
-0.01525961048901081,
-0.03910168260335922,
-0.09016554057598114,
0.0009216953185386956,
-0.012680569663643837,
0.09024128317832947,
-0.059013087302446365,
0.10169555991888046,
0.06154852733016014,
0.07004418969154358,
-0.035339780151844025,
0.031310662627220154,
-0.10968378186225891,
0.04157831519842148,
-0.1881045401096344,
0.0035691731609404087,
-0.08658526837825775,
0.07263000309467316,
-0.09194281697273254,
-0.08529951423406601,
-0.015897924080491066,
0.0065759834833443165,
0.08774163573980331,
0.10238122195005417,
-0.15060362219810486,
-0.058375559747219086,
0.14854946732521057,
-0.0916307345032692,
-0.17658990621566772,
0.12464495748281479,
-0.04764088615775108,
0.06110212951898575,
0.04747612029314041,
0.1688666194677353,
0.06240369379520416,
-0.11748392134904861,
-0.018450764939188957,
0.0029422699008136988,
0.05978998914361,
-0.027692565694451332,
0.0696604996919632,
-0.016603343188762665,
0.0040199002251029015,
0.008382067084312439,
-0.06427277624607086,
0.03453504294157028,
-0.0991661325097084,
-0.08979807049036026,
-0.05383786931633949,
-0.10882444679737091,
0.042241550981998444,
0.0675349235534668,
0.0566316656768322,
-0.11444703489542007,
-0.10052404552698135,
0.07673750072717667,
0.08780394494533539,
-0.07150858640670776,
0.01940763182938099,
-0.07852360606193542,
0.08087373524904251,
-0.07315631955862045,
-0.02881830744445324,
-0.15680795907974243,
-0.05398312211036682,
0.0033115961123257875,
-0.0041090501472353935,
0.006784244440495968,
0.014990421012043953,
0.08412253856658936,
0.06640032678842545,
-0.07332167029380798,
-0.04576760157942772,
-0.051735326647758484,
0.013590930961072445,
-0.1145736426115036,
-0.20971156656742096,
-0.02697254717350006,
-0.03321443870663643,
0.10919281095266342,
-0.2133859097957611,
0.043050676584243774,
-0.0025097085162997246,
0.09291014075279236,
0.03587590903043747,
-0.00906140636652708,
-0.04618086293339729,
0.06455862522125244,
-0.030895015224814415,
-0.06066613644361496,
0.03962242603302002,
0.002527279779314995,
-0.09484441578388214,
-0.07630803436040878,
-0.11597920209169388,
0.17350180447101593,
0.127400740981102,
-0.09140199422836304,
-0.08008186519145966,
-0.0028887377120554447,
-0.062414612621068954,
-0.040404368191957474,
-0.03816961124539375,
0.005219210404902697,
0.11494540423154831,
-0.014149335213005543,
0.11723906546831131,
-0.08390787243843079,
-0.038299474865198135,
0.010298023000359535,
-0.0515727624297142,
0.018823470920324326,
0.10837116837501526,
0.11342985183000565,
-0.07977816462516785,
0.14699909090995789,
0.1864837408065796,
-0.11061282455921173,
0.11605632305145264,
-0.06608447432518005,
-0.08707202225923538,
-0.03326261043548584,
0.022869903594255447,
0.0094345947727561,
0.1462448537349701,
-0.1375555545091629,
0.019221829250454903,
0.014804026111960411,
0.010623825713992119,
0.020948216319084167,
-0.21576392650604248,
-0.04512815177440643,
0.027307314798235893,
-0.04526031017303467,
-0.013538723811507225,
-0.010150794871151447,
-0.00849916972219944,
0.08756443113088608,
-0.011840506456792355,
-0.06235578656196594,
0.03935393691062927,
-0.0025962560903280973,
-0.0744098424911499,
0.21098926663398743,
-0.07420121878385544,
-0.08200941979885101,
-0.11245210468769073,
-0.02759879268705845,
-0.03650389611721039,
0.012413174845278263,
0.0685945525765419,
-0.0794384628534317,
-0.03466860577464104,
-0.09250249713659286,
0.01404531765729189,
0.03528460115194321,
0.027681471779942513,
0.03334531933069229,
0.0014535520458593965,
0.09460670500993729,
-0.11132674664258957,
0.0075415135361254215,
-0.043146394193172455,
-0.06780698150396347,
0.03262129798531532,
0.04199261590838432,
0.12941695749759674,
0.13265378773212433,
-0.006396770011633635,
-0.0036451786290854216,
-0.018812229856848717,
0.2462620884180069,
-0.0701012834906578,
-0.02562822960317135,
0.1327432096004486,
-0.00934448279440403,
0.045374151319265366,
0.13343611359596252,
0.07260828465223312,
-0.09806742519140244,
0.02695016749203205,
0.05859442800283432,
-0.01879209093749523,
-0.22799763083457947,
-0.014946097508072853,
-0.036103375256061554,
0.00017798735643737018,
0.07723827660083771,
0.031197788193821907,
0.041374944150447845,
0.07591672986745834,
0.02014058828353882,
0.04597941040992737,
-0.03432952240109444,
0.06358829140663147,
0.09360753744840622,
0.03752100467681885,
0.11666940152645111,
-0.04900801181793213,
-0.05267270281910896,
0.029014257714152336,
0.002763900440186262,
0.22789396345615387,
0.011255329474806786,
0.1371438354253769,
0.07875244319438934,
0.1797742247581482,
-0.01924898847937584,
0.06642983853816986,
-0.014175193384289742,
-0.06580395251512527,
0.0012462690938264132,
-0.05528007075190544,
0.0009468859061598778,
0.042813561856746674,
-0.08875363320112228,
0.0854770839214325,
-0.0987762063741684,
0.024964507669210434,
0.07110821455717087,
0.2448822557926178,
0.05719033256173134,
-0.29439353942871094,
-0.09927351027727127,
0.01800156943500042,
-0.02515226975083351,
-0.017252624034881592,
0.029358526691794395,
0.13120627403259277,
-0.03831953927874565,
0.01098579354584217,
-0.06211010366678238,
0.08191756159067154,
0.012059354223310947,
0.03951543569564819,
0.06852395087480545,
0.08924319595098495,
-0.01122487336397171,
0.07268134504556656,
-0.28448915481567383,
0.272459477186203,
0.018972858786582947,
0.0934230238199234,
-0.044366348534822464,
-0.004519992042332888,
0.01813541352748871,
0.0663079023361206,
0.0914369747042656,
-0.027176814153790474,
-0.04179193452000618,
-0.17258413136005402,
-0.044324446469545364,
0.037697747349739075,
0.09677491337060928,
-0.02932387962937355,
0.10808562487363815,
-0.019586896523833275,
0.011918356642127037,
0.09101119637489319,
-0.011990528553724289,
-0.10777638107538223,
-0.07809612900018692,
-0.01626713015139103,
0.005407590884715319,
-0.040826465934515,
-0.09735313057899475,
-0.09844731539487839,
-0.10964060574769974,
0.13508397340774536,
-0.044469162821769714,
-0.021420955657958984,
-0.10091753304004669,
0.06940682232379913,
0.09142360836267471,
-0.07604418694972992,
0.03983999788761139,
0.02169332467019558,
0.05464531108736992,
0.039615582674741745,
-0.04734743759036064,
0.11966588348150253,
-0.08116480708122253,
-0.1758660227060318,
-0.06190548464655876,
0.10878608375787735,
0.037817250937223434,
0.04540368169546127,
-0.012194614857435226,
0.004530956503003836,
-0.024012960493564606,
-0.09166499227285385,
0.026148255914449692,
-0.028555134311318398,
0.0717635452747345,
0.015510495752096176,
-0.047505252063274384,
0.044708382338285446,
-0.04898872971534729,
-0.020703110843896866,
0.1352609395980835,
0.29611048102378845,
-0.08448396623134613,
-0.01659068651497364,
0.06274762004613876,
-0.048611197620630264,
-0.19541625678539276,
0.061884962022304535,
0.032812606543302536,
-0.00480179488658905,
0.05772661790251732,
-0.14161238074302673,
0.14518676698207855,
0.11124126613140106,
-0.026899203658103943,
0.11125051230192184,
-0.3069438934326172,
-0.1252088099718094,
0.13041289150714874,
0.15494249761104584,
0.10125724971294403,
-0.1743493378162384,
-0.03473003953695297,
-0.01293216273188591,
-0.1473151296377182,
0.08080080896615982,
-0.15396808087825775,
0.09482841938734055,
-0.014168016612529755,
0.050069522112607956,
0.0039480761624872684,
-0.07067329436540604,
0.14702914655208588,
0.000025108622139669023,
0.11905081570148468,
-0.04664415493607521,
-0.013178437948226929,
0.07161860913038254,
-0.0440300814807415,
0.03244471177458763,
-0.0891299843788147,
0.05371810495853424,
-0.05257681757211685,
-0.026219379156827927,
-0.06334623694419861,
0.04367275536060333,
-0.051738444715738297,
-0.06737174838781357,
-0.04562317207455635,
0.03158135339617729,
0.026293084025382996,
-0.012044468894600868,
0.14366362988948822,
0.019449502229690552,
0.152317613363266,
0.11604864150285721,
0.07753553241491318,
-0.06884285062551498,
-0.05426878109574318,
0.011056793853640556,
-0.03131050989031792,
0.07339060306549072,
-0.15634511411190033,
0.041423697024583817,
0.13064169883728027,
0.03229861333966255,
0.1391829252243042,
0.07008695602416992,
-0.04683050885796547,
0.011576784774661064,
0.05696919932961464,
-0.16273337602615356,
-0.13527855277061462,
0.00021811471378896385,
-0.047389205545186996,
-0.1403459757566452,
0.0831863135099411,
0.09662125259637833,
-0.05798669531941414,
0.008472267538309097,
-0.0012196851894259453,
0.0035157862585037947,
-0.060666583478450775,
0.1914328783750534,
0.08576805144548416,
0.05076095461845398,
-0.07330186665058136,
0.08382532000541687,
0.02582845650613308,
-0.08156295120716095,
0.002931449329480529,
0.030454691499471664,
-0.0607781745493412,
-0.04764287918806076,
0.05753647908568382,
0.1763560175895691,
-0.018948348239064217,
-0.0515202097594738,
-0.15352745354175568,
-0.10358528792858124,
0.05325846001505852,
0.1758543699979782,
0.09900858998298645,
0.011282788589596748,
-0.016000112518668175,
0.037973884493112564,
-0.1204606145620346,
0.11462428420782089,
0.03907671943306923,
0.08269350230693817,
-0.15165305137634277,
0.10580801218748093,
-0.005053582135587931,
0.01481167133897543,
-0.02161414362490177,
0.053746651858091354,
-0.12387795001268387,
0.004668783862143755,
-0.16138239204883575,
-0.032673731446266174,
-0.04265699163079262,
0.00005815786789753474,
0.016311179846525192,
-0.07793152332305908,
-0.07630777359008789,
0.023686107248067856,
-0.10321642458438873,
-0.014211473986506462,
0.060817066580057144,
0.05188564211130142,
-0.14652001857757568,
-0.03198054060339928,
0.04170604422688484,
-0.06967003643512726,
0.062211405485868454,
0.033013585954904556,
0.030022205784916878,
0.05169149860739708,
-0.18481411039829254,
0.023730415850877762,
0.05416363105177879,
0.008681408129632473,
0.05330634489655495,
-0.09254615753889084,
-0.029685689136385918,
-0.005393489729613066,
0.05531492456793785,
0.008712153881788254,
0.04758720099925995,
-0.12232216447591782,
-0.006295136176049709,
-0.041359737515449524,
-0.06729541718959808,
-0.06066310405731201,
0.011773567646741867,
0.10576893389225006,
0.005918055307120085,
0.20029444992542267,
-0.08028514683246613,
0.020565306767821312,
-0.21805761754512787,
0.006317377556115389,
0.0007933637243695557,
-0.07833169400691986,
-0.09523365646600723,
-0.04047353193163872,
0.05296748876571655,
-0.06669023633003235,
0.13136978447437286,
-0.039475083351135254,
0.032888516783714294,
0.036545608192682266,
-0.05694027617573738,
0.06205161288380623,
0.027511926367878914,
0.25957661867141724,
0.017801513895392418,
-0.02665003389120102,
0.013341514393687248,
0.038759756833314896,
0.09329363703727722,
0.07672693580389023,
0.17791050672531128,
0.1838202327489853,
-0.051772985607385635,
0.08835951238870621,
0.05498681217432022,
-0.06097180396318436,
-0.11591967940330505,
0.06870200484991074,
-0.02460589073598385,
0.0692383274435997,
-0.015031394548714161,
0.21054156124591827,
0.11571332067251205,
-0.1587776094675064,
0.013516302220523357,
-0.05546863004565239,
-0.08683730661869049,
-0.10038408637046814,
-0.03010096400976181,
-0.08513257652521133,
-0.17593449354171753,
0.01682654581964016,
-0.12717175483703613,
0.0011617710115388036,
0.1000027060508728,
0.010899942368268967,
-0.0146885234862566,
0.2165999859571457,
0.030869025737047195,
0.05439092963933945,
0.03300661966204643,
-0.002652120776474476,
-0.03749638795852661,
-0.07248247414827347,
-0.07315754145383835,
0.015457108616828918,
-0.03426345810294151,
0.01978936232626438,
-0.05645136907696724,
-0.058194950222969055,
0.040037963539361954,
-0.004322974942624569,
-0.09796334058046341,
0.002814878011122346,
0.029437480494379997,
0.04828823357820511,
0.05667335167527199,
0.015311364084482193,
0.024760449305176735,
-0.011826446279883385,
0.21926701068878174,
-0.08337228745222092,
-0.07075966149568558,
-0.12012887001037598,
0.19813168048858643,
0.024691103026270866,
0.013258158229291439,
0.016685867682099342,
-0.10104376822710037,
0.03041871264576912,
0.20654979348182678,
0.15984123945236206,
-0.08086302131414413,
-0.0010668282629922032,
0.006114286370575428,
-0.010101964697241783,
-0.0754731297492981,
0.05709870159626007,
0.126203253865242,
0.02435288578271866,
-0.08202887326478958,
-0.07048694789409637,
-0.04507356882095337,
-0.01839148998260498,
-0.04224643111228943,
0.04067235812544823,
0.045371025800704956,
0.0077260928228497505,
-0.04650203138589859,
0.061570558696985245,
-0.0334857776761055,
-0.12720145285129547,
0.07758667320013046,
-0.17434673011302948,
-0.14375357329845428,
-0.018271489068865776,
0.1253378838300705,
-0.01291586272418499,
0.05312430486083031,
-0.04152625799179077,
-0.012125733308494091,
0.07907934486865997,
-0.01956496201455593,
-0.06455861777067184,
-0.08845704793930054,
0.08270423859357834,
-0.09279841929674149,
0.23132441937923431,
-0.0317649245262146,
0.06611967086791992,
0.14015908539295197,
0.034617822617292404,
-0.08410044759511948,
0.08451349288225174,
0.0667501837015152,
-0.10692247003316879,
0.011461373418569565,
0.07861605286598206,
-0.030612345784902573,
0.12119600921869278,
0.0594371035695076,
-0.15289843082427979,
0.00562914926558733,
-0.037805818021297455,
-0.07244839519262314,
-0.07971753925085068,
-0.03157307952642441,
-0.06536655873060226,
0.1324981302022934,
0.18955989181995392,
-0.04640680551528931,
0.01593819074332714,
-0.043855950236320496,
0.046381864696741104,
0.0714418888092041,
0.051799334585666656,
-0.03114747442305088,
-0.22789253294467926,
0.05559372529387474,
0.0580841563642025,
-0.023901915177702904,
-0.2410161942243576,
-0.09315819293260574,
0.021904300898313522,
-0.05920616537332535,
-0.07647330313920975,
0.06275112926959991,
0.13186587393283844,
0.06379792839288712,
-0.05905836448073387,
-0.10927333682775497,
-0.08591727167367935,
0.1586615890264511,
-0.13418279588222504,
-0.09488654136657715
] |
null | null | null |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` | {"license": "other", "tags": ["autotrain", "text-generation"], "widget": [{"text": "I love AutoTrain because "}]} | text-generation | TuringsSolutions/BatMistral | [
"safetensors",
"autotrain",
"text-generation",
"license:other",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:02:07+00:00 | [] | [] | TAGS
#safetensors #autotrain #text-generation #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
"TAGS\n#safetensors #autotrain #text-generation #license-other #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
33,
29,
3
] | [
"passage: TAGS\n#safetensors #autotrain #text-generation #license-other #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.# Usage"
] | [
-0.03320549428462982,
0.03780708089470863,
-0.0005784488166682422,
0.037439193576574326,
0.13256101310253143,
-0.02594633586704731,
0.22870999574661255,
0.04971681907773018,
-0.04270017519593239,
-0.08776232600212097,
0.19642603397369385,
0.16802352666854858,
-0.04566871374845505,
0.18935616314411163,
-0.02990073338150978,
-0.2414124757051468,
0.021885043010115623,
-0.025850016623735428,
0.1327640414237976,
0.11522045731544495,
0.14238014817237854,
-0.07779128849506378,
0.06120644509792328,
0.04086628183722496,
-0.20404933393001556,
0.03463415056467056,
0.07968573272228241,
-0.11895040422677994,
0.18004877865314484,
0.032886918634176254,
0.13635416328907013,
0.01931498385965824,
0.14652439951896667,
-0.12186150997877121,
0.014377960003912449,
0.01464270893484354,
-0.015491045080125332,
0.055415596812963486,
0.08804452419281006,
-0.038794226944446564,
0.09763352572917938,
0.177653506398201,
0.10883878171443939,
0.04911845549941063,
-0.10558086633682251,
-0.014727416448295116,
-0.03310466557741165,
0.018835384398698807,
0.12075160443782806,
0.1193094402551651,
-0.01845790445804596,
0.20021599531173706,
-0.14986595511436462,
0.07329507917165756,
-0.0995626449584961,
-0.27255508303642273,
-0.0038277229759842157,
0.21143054962158203,
0.07346842437982559,
-0.025004452094435692,
-0.12620827555656433,
0.06475763022899628,
0.12761425971984863,
0.0030757547356188297,
0.06504988670349121,
-0.015198786742985249,
-0.055105701088905334,
-0.0015243350062519312,
-0.07397002726793289,
-0.004598719999194145,
0.18640007078647614,
-0.07974611967802048,
-0.031184203922748566,
-0.12737500667572021,
-0.019428882747888565,
0.04709514603018761,
0.011552144773304462,
-0.09352482110261917,
-0.0217994824051857,
0.11079124361276627,
-0.007622338831424713,
-0.02531961165368557,
-0.15207529067993164,
-0.05755603685975075,
-0.08864409476518631,
0.04077286645770073,
0.0017509139142930508,
0.011538662947714329,
-0.09947098046541214,
0.12073534727096558,
-0.029350996017456055,
-0.0943499282002449,
0.052897434681653976,
-0.1107030138373375,
0.04635190963745117,
-0.11982002854347229,
-0.03970254212617874,
-0.10856737196445465,
0.013430505990982056,
0.22841021418571472,
0.1669083684682846,
-0.015314205549657345,
-0.08587565273046494,
0.039016176015138626,
0.02371702343225479,
0.09614221751689911,
0.06376225501298904,
-0.015822242945432663,
0.06775996834039688,
-0.04785482585430145,
-0.017039362341165543,
-0.025495992973446846,
-0.1726902425289154,
0.032083623111248016,
0.01997307874262333,
0.07117509841918945,
-0.0760226845741272,
0.06040170043706894,
-0.01951628364622593,
0.055283352732658386,
0.05161101743578911,
-0.031190861016511917,
0.03744623437523842,
-0.052504897117614746,
0.01617865450680256,
-0.09791388362646103,
0.0286922138184309,
0.1180110052227974,
0.03286140412092209,
0.1336720734834671,
-0.09649777412414551,
-0.026225421577692032,
-0.1056324690580368,
-0.03878350928425789,
0.018166208639740944,
-0.0019215025240555406,
0.0628642737865448,
-0.19663763046264648,
-0.30395275354385376,
-0.027070891112089157,
0.053043100982904434,
-0.019671862944960594,
-0.05561401695013046,
-0.07015043497085571,
0.016289202496409416,
0.059536442160606384,
-0.02920805849134922,
0.054385289549827576,
-0.022419849410653114,
0.03813159465789795,
-0.07676586508750916,
-0.02052054926753044,
-0.06291672587394714,
0.006658008787781,
-0.14841435849666595,
-0.03448035567998886,
-0.030017102137207985,
0.006548900622874498,
-0.03775618225336075,
0.16895608603954315,
-0.011088937520980835,
0.047757651656866074,
-0.05747115612030029,
0.05074193328619003,
0.007877329364418983,
0.1440490484237671,
-0.1335235834121704,
0.005429679993540049,
0.1511751264333725,
-0.11302075535058975,
-0.10663392394781113,
0.09467647224664688,
-0.10317569971084595,
0.23649843037128448,
0.10416192561388016,
0.13955152034759521,
0.05125761032104492,
-0.12630151212215424,
0.11601320654153824,
0.03282208740711212,
-0.08780468255281448,
-0.062369491904973984,
-0.0006791196065023541,
-0.034443121403455734,
-0.22099432349205017,
0.031658004969358444,
0.11068084836006165,
0.07476310431957245,
-0.03403317928314209,
-0.08304393291473389,
-0.02895026095211506,
-0.058612581342458725,
0.03986813873052597,
0.016017582267522812,
0.12599535286426544,
-0.07699156552553177,
-0.02858225256204605,
0.032077912241220474,
0.038467586040496826,
0.07923582941293716,
-0.054815541952848434,
-0.057291675359010696,
-0.01996961608529091,
-0.023569827899336815,
-0.00915558822453022,
-0.0898597314953804,
-0.0620407834649086,
-0.006840218789875507,
0.1304454207420349,
0.03466487303376198,
0.07167287915945053,
0.0362425372004509,
0.052633073180913925,
-0.028641145676374435,
0.002677651820704341,
0.1629824936389923,
0.04459667578339577,
-0.12675853073596954,
-0.08582112193107605,
0.10815013945102692,
-0.07446087151765823,
0.1071702167391777,
-0.2590586841106415,
0.028333326801657677,
-0.11371348798274994,
0.08611167222261429,
-0.013308924622833729,
0.06491301208734512,
-0.08320876955986023,
0.024355897679924965,
-0.08930765837430954,
-0.008432179689407349,
0.05678462237119675,
0.04953930526971817,
-0.02282531000673771,
0.12372811883687973,
-0.1432238668203354,
0.21934939920902252,
0.1198250874876976,
-0.09310522675514221,
-0.11077594012022018,
-0.0739443302154541,
0.009118417277932167,
-0.005148864816874266,
-0.1179550290107727,
0.005491754971444607,
0.076014444231987,
-0.04686584323644638,
0.1847466230392456,
-0.034107014536857605,
-0.03428659960627556,
-0.015382813289761543,
-0.08532355725765228,
-0.009268855676054955,
-0.02073976956307888,
0.09649215638637543,
-0.2238936424255371,
0.1325010061264038,
0.16212041676044464,
-0.015046309679746628,
0.1718226969242096,
0.01847519353032112,
0.013679388910531998,
0.006052343640476465,
-0.04082776978611946,
-0.00007846848893677816,
0.02128027006983757,
0.0015916629927232862,
0.0011914868373423815,
0.007707077544182539,
0.02131907269358635,
0.030305195599794388,
-0.14438240230083466,
-0.05413905158638954,
0.010167223401367664,
0.052466847002506256,
0.00018202696810476482,
0.0614926852285862,
-0.08105885237455368,
0.05735839903354645,
-0.0333511158823967,
-0.11407014727592468,
0.12527471780776978,
0.0140310637652874,
-0.12375999987125397,
0.1809239387512207,
-0.09875242412090302,
-0.177916020154953,
-0.19897617399692535,
-0.11664178967475891,
0.025174645707011223,
0.09509945660829544,
0.06778308749198914,
-0.06591268628835678,
-0.0677633062005043,
-0.013884147629141808,
-0.13205823302268982,
0.015237858518958092,
-0.0303916335105896,
-0.10815607011318207,
0.06643082201480865,
0.002197817200794816,
-0.1106930822134018,
-0.04751880466938019,
0.012397545389831066,
-0.05212624743580818,
0.06534521281719208,
-0.032029394060373306,
0.06015416979789734,
0.12733860313892365,
-0.009645693004131317,
0.014830506406724453,
-0.03892328962683678,
0.1736617386341095,
-0.07863081991672516,
0.0028175772167742252,
0.11224561184644699,
-0.04382455348968506,
0.03531843051314354,
0.2027312070131302,
0.03458266332745552,
-0.07247956842184067,
0.06938916444778442,
-0.03509911522269249,
-0.05979844182729721,
-0.202435702085495,
-0.10123657435178757,
-0.007523522712290287,
-0.02823515795171261,
0.08373580127954483,
0.0565473809838295,
0.25448861718177795,
0.1288231760263443,
0.060374923050403595,
0.03997355327010155,
0.024889161810278893,
0.0913970097899437,
0.1029813289642334,
-0.027027886360883713,
0.16222402453422546,
-0.08429007232189178,
-0.14650671184062958,
0.048164136707782745,
-0.022769063711166382,
0.07281020283699036,
0.17174853384494781,
-0.06210782378911972,
0.04705783352255821,
0.11571547389030457,
0.13094793260097504,
0.12702703475952148,
0.07746905833482742,
-0.061997704207897186,
-0.006629003677517176,
0.0010869213147088885,
-0.04415592923760414,
0.14652740955352783,
-0.060009948909282684,
-0.06889448314905167,
-0.04306207224726677,
-0.003198902355507016,
0.04323491454124451,
0.05818231403827667,
0.026216039434075356,
-0.28657910227775574,
0.042942874133586884,
0.04888097196817398,
-0.05969006195664406,
-0.11467164009809494,
0.09232109785079956,
-0.027857046574354172,
-0.18361465632915497,
0.03563778102397919,
-0.033283449709415436,
0.09147034585475922,
0.062072351574897766,
0.04841171205043793,
-0.06585943698883057,
-0.0609852597117424,
-0.045712124556303024,
0.15376420319080353,
-0.33846980333328247,
0.20756816864013672,
-0.011205663904547691,
0.08115556091070175,
-0.10785048454999924,
0.010794016532599926,
0.08773794025182724,
0.19103488326072693,
0.12050216645002365,
-0.049261946231126785,
-0.19848455488681793,
-0.11937171965837479,
-0.08363119512796402,
-0.015415008179843426,
0.02001480758190155,
-0.008096402511000633,
0.0008919041720218956,
-0.11757626384496689,
0.0014032695908099413,
0.04126403480768204,
-0.0069845812395215034,
-0.17894983291625977,
-0.15384836494922638,
-0.03538630157709122,
0.030474675819277763,
0.10934672504663467,
-0.04776112735271454,
-0.0534328930079937,
-0.06292759627103806,
0.13548673689365387,
0.026695549488067627,
0.008182995021343231,
-0.1301279366016388,
-0.053804632276296616,
-0.044131867587566376,
-0.023950019851326942,
0.07710648328065872,
0.009424211457371712,
0.11959850043058395,
-0.08615647256374359,
-0.06447352468967438,
0.09218238294124603,
-0.12910714745521545,
-0.042984966188669205,
-0.12177132815122604,
0.03449074551463127,
-0.045684002339839935,
-0.01073586754500866,
0.11459703743457794,
0.04736353084445,
-0.07455705851316452,
-0.06686578691005707,
-0.016151487827301025,
-0.0162202138453722,
0.052238523960113525,
-0.10140960663557053,
-0.11989933252334595,
-0.12391869723796844,
-0.023699220269918442,
-0.11985665559768677,
0.1933230459690094,
0.14995472133159637,
-0.08873795717954636,
0.15256796777248383,
0.2099498212337494,
-0.11413656920194626,
-0.29302918910980225,
-0.05128840357065201,
-0.06601350009441376,
0.004299632739275694,
0.06156041473150253,
-0.10058135539293289,
0.1023014560341835,
0.016915474086999893,
-0.08869403600692749,
-0.016260353848338127,
-0.10926515609025955,
-0.16224952042102814,
0.22960300743579865,
-0.0020108406897634268,
0.18459931015968323,
-0.07568172365427017,
-0.05459576100111008,
-0.12268339842557907,
0.05030543729662895,
0.043312136083841324,
-0.06949128210544586,
0.04921199381351471,
0.045118432492017746,
0.04848489910364151,
0.02309754677116871,
-0.04944291338324547,
0.05402865633368492,
-0.07527824491262436,
0.09563448280096054,
-0.16834798455238342,
-0.019022751599550247,
0.05676575005054474,
-0.027846379205584526,
0.11607834696769714,
-0.040225449949502945,
0.045501600950956345,
-0.05838647112250328,
-0.07079911977052689,
0.02105431631207466,
0.07136379927396774,
-0.007516450714319944,
-0.11632271111011505,
0.009460309520363808,
0.0020681610330939293,
-0.007515698205679655,
-0.07468903809785843,
0.01720641367137432,
-0.009510648436844349,
0.14864802360534668,
0.13830016553401947,
0.2062399536371231,
-0.06995580345392227,
0.06706579029560089,
-0.03199863061308861,
-0.11711113899946213,
0.07805433124303818,
-0.07166967540979385,
0.004296483471989632,
0.05220668390393257,
-0.0538930743932724,
0.14611311256885529,
0.06082209199666977,
0.003751826472580433,
-0.01890469156205654,
0.16250212490558624,
-0.16876746714115143,
0.04684048146009445,
-0.0843876302242279,
0.1279323697090149,
0.04778100550174713,
-0.03293748199939728,
0.09026376903057098,
-0.07791304588317871,
-0.03329215198755264,
-0.0002585914626251906,
0.006090222392231226,
-0.038581836968660355,
0.06518552452325821,
0.04536600783467293,
0.02252393215894699,
-0.06704199314117432,
0.0445764996111393,
0.07239795476198196,
0.016518399119377136,
0.041721411049366,
0.015846284106373787,
-0.09952405095100403,
-0.09522253274917603,
0.04372299090027809,
0.26397231221199036,
-0.1863422393798828,
-0.09990737587213516,
0.004564397502690554,
-0.09345841407775879,
0.004960347898304462,
0.08620705455541611,
0.0809662714600563,
0.04341237619519234,
-0.03603934869170189,
-0.02565331570804119,
-0.11602527648210526,
0.08217493444681168,
-0.015696978196501732,
0.05509110167622566,
-0.16319575905799866,
0.06676459312438965,
-0.030968010425567627,
-0.008549565449357033,
-0.08279257267713547,
-0.010031647980213165,
-0.11571928858757019,
0.026098787784576416,
-0.10430167615413666,
-0.03189973905682564,
-0.041006896644830704,
-0.011233619414269924,
0.05850789323449135,
-0.011018243618309498,
-0.013110441155731678,
-0.01927962154150009,
-0.08805359154939651,
0.02887921780347824,
-0.0008198951254598796,
0.04547540098428726,
-0.05460818111896515,
-0.024217726662755013,
0.037278566509485245,
0.004562355112284422,
0.046250831335783005,
0.012032478116452694,
-0.0011190201621502638,
0.049139540642499924,
-0.14732354879379272,
0.009436994791030884,
0.06159417703747749,
-0.0016145178815349936,
0.0070913624949753284,
-0.028678715229034424,
0.005330502521246672,
0.09783722460269928,
0.018718764185905457,
0.04128317907452583,
-0.0048657008446753025,
-0.1091027706861496,
0.014511657878756523,
0.10307195782661438,
-0.14174701273441315,
-0.03145497664809227,
-0.052812907844781876,
0.01100962609052658,
-0.05524790287017822,
0.23351503908634186,
-0.11669892817735672,
0.04470064863562584,
-0.02692001312971115,
0.030550040304660797,
-0.05822846665978432,
-0.10757116973400116,
-0.12190251797437668,
-0.0954190194606781,
-0.042861051857471466,
0.007703589275479317,
0.2689315676689148,
0.1459355354309082,
-0.008143693208694458,
0.0415508970618248,
0.07256698608398438,
0.09993022680282593,
0.001325596240349114,
0.22187061607837677,
0.09407079964876175,
-0.011255222372710705,
-0.12900875508785248,
0.0802748054265976,
0.027718892320990562,
-0.10550516843795776,
0.0003671931044664234,
0.017833324149250984,
-0.07709381729364395,
0.05998256057500839,
0.04779348149895668,
-0.04618219658732414,
-0.11530262231826782,
-0.1887446641921997,
-0.1010153517127037,
0.01362328790128231,
-0.09494820982217789,
-0.00841664057224989,
0.17340072989463806,
-0.07381404936313629,
-0.020257510244846344,
-0.08453129231929779,
-0.042230453342199326,
-0.21403644979000092,
-0.1685105264186859,
-0.09951409697532654,
-0.07172851264476776,
0.054574232548475266,
-0.01444533746689558,
0.051937036216259,
0.0384058877825737,
0.03334033116698265,
-0.0690227821469307,
0.10118697583675385,
-0.11317354440689087,
0.006825347896665335,
-0.007538147736340761,
-0.042660877108573914,
0.007157159503549337,
-0.17031751573085785,
-0.023363124579191208,
-0.1397811770439148,
-0.04669688642024994,
-0.031707603484392166,
-0.04375086724758148,
0.0007692996296100318,
-0.003963754046708345,
-0.03139100596308708,
-0.009807240217924118,
-0.01006900705397129,
0.03744599595665932,
0.023235660046339035,
0.05043753236532211,
0.022183645516633987,
0.01541586872190237,
0.043549589812755585,
0.21836970746517181,
-0.03527946025133133,
-0.18426218628883362,
-0.12376350164413452,
0.24631790816783905,
0.03293769061565399,
0.11490416526794434,
-0.07057193666696548,
-0.01361043006181717,
0.07598087936639786,
0.31235218048095703,
0.2598150074481964,
-0.03414434567093849,
0.010121017694473267,
-0.03132476285099983,
-0.014958096668124199,
-0.0064048562198877335,
0.18490195274353027,
0.008828791789710522,
0.16826002299785614,
-0.0621221587061882,
0.059055350720882416,
-0.016177164390683174,
-0.07808512449264526,
-0.06689254939556122,
0.14256809651851654,
-0.036333873867988586,
-0.02151089534163475,
-0.01796986348927021,
0.08792226016521454,
-0.0589551106095314,
0.17949369549751282,
-0.09007178992033005,
-0.009130639024078846,
-0.04809116572141647,
0.053617071360349655,
0.11827872693538666,
-0.02074413187801838,
0.03285614401102066,
-0.03567332774400711,
-0.018393725156784058,
0.0029441264923661947,
-0.04050283133983612,
-0.07413910329341888,
-0.04345672205090523,
0.06311136484146118,
0.02551795169711113,
0.25671228766441345,
-0.009337767027318478,
0.05477561056613922,
0.07988451421260834,
-0.0020537625532597303,
-0.10351628065109253,
0.11267323791980743,
0.00224103475920856,
-0.029008302837610245,
0.12491703033447266,
-0.015443749725818634,
0.007564615458250046,
-0.01867114193737507,
-0.01239294558763504,
-0.15698960423469543,
0.14728498458862305,
-0.10142818093299866,
-0.08940913528203964,
-0.05584051460027695,
0.12545742094516754,
-0.032320525497198105,
0.16258437931537628,
0.05726946145296097,
-0.026426637545228004,
0.0021389273460954428,
-0.0331779383122921,
0.08067825436592102,
0.009919043630361557,
-0.09914126992225647,
-0.02203422784805298,
-0.17707498371601105,
-0.016973769292235374,
0.12876249849796295,
-0.02544221095740795,
-0.24601322412490845,
-0.07971391826868057,
-0.06824030727148056,
-0.04311496391892433,
-0.1386985182762146,
0.07398401945829391,
0.2028772532939911,
0.019287997856736183,
-0.01476763840764761,
-0.1369636058807373,
-0.021961720660328865,
0.019149890169501305,
-0.026857441291213036,
-0.10799262672662735
] |
null | null | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 4.993301990907639e-05
f1: 1.0
precision: 1.0
recall: 1.0
auc: 1.0
accuracy: 1.0
| {"tags": ["autotrain", "image-classification"], "datasets": ["autotrain-87jyh-cly3l/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]} | image-classification | tferreira6/AIButterflyDetectorModel | [
"transformers",
"safetensors",
"vit",
"image-classification",
"autotrain",
"dataset:autotrain-87jyh-cly3l/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | 2024-02-09T02:03:51+00:00 | [] | [] | TAGS
#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-87jyh-cly3l/autotrain-data #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 4.993301990907639e-05
f1: 1.0
precision: 1.0
recall: 1.0
auc: 1.0
accuracy: 1.0
| [
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 4.993301990907639e-05\n\nf1: 1.0\n\nprecision: 1.0\n\nrecall: 1.0\n\nauc: 1.0\n\naccuracy: 1.0"
] | [
"TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-87jyh-cly3l/autotrain-data #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 4.993301990907639e-05\n\nf1: 1.0\n\nprecision: 1.0\n\nrecall: 1.0\n\nauc: 1.0\n\naccuracy: 1.0"
] | [
67,
16,
38
] | [
"passage: TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-87jyh-cly3l/autotrain-data #autotrain_compatible #endpoints_compatible #has_space #region-us \n# Model Trained Using AutoTrain\n\n- Problem type: Image Classification## Validation Metricsg\nloss: 4.993301990907639e-05\n\nf1: 1.0\n\nprecision: 1.0\n\nrecall: 1.0\n\nauc: 1.0\n\naccuracy: 1.0"
] | [
-0.1320050209760666,
0.0964435338973999,
0.0015729796141386032,
0.11147987097501755,
0.13260972499847412,
0.003909244667738676,
0.025856733322143555,
0.0954318419098854,
-0.060394641011953354,
0.06385184079408646,
0.20841245353221893,
0.09496507048606873,
0.00985621940344572,
0.17696337401866913,
-0.1382109522819519,
-0.20323501527309418,
0.06766481697559357,
0.00831559207290411,
0.10388949513435364,
0.09482120722532272,
0.07853130996227264,
-0.13777031004428864,
0.11767850071191788,
0.016172591596841812,
-0.2959916591644287,
0.01324157603085041,
0.13016657531261444,
-0.13617244362831116,
0.12182591110467911,
0.07213159650564194,
0.13189776241779327,
0.024520687758922577,
0.15166530013084412,
-0.02486836165189743,
-0.0063832467421889305,
0.026119058951735497,
-0.008670277893543243,
0.05615716800093651,
0.08681369572877884,
0.0017135088564828038,
-0.0876392275094986,
0.03155914694070816,
0.06491915881633759,
0.0051137967966496944,
-0.08708874881267548,
-0.040302176028490067,
-0.04819739982485771,
0.031273264437913895,
0.12851250171661377,
0.0789145827293396,
-0.0002865046262741089,
0.1962972730398178,
-0.1023382768034935,
0.08495742082595825,
-0.005491191986948252,
-0.24755418300628662,
-0.06721659749746323,
0.15659628808498383,
-0.015317113138735294,
-0.0638924315571785,
-0.11697208136320114,
0.09952778369188309,
0.14269544184207916,
-0.006573852151632309,
0.04416617006063461,
-0.0248279869556427,
-0.09665615856647491,
0.01820739544928074,
-0.09165813773870468,
-0.005727085284888744,
0.20234841108322144,
0.002190670697018504,
-0.034362103790044785,
-0.06785809248685837,
-0.06244148313999176,
-0.0999998226761818,
-0.04995153471827507,
-0.0620979443192482,
-0.031727585941553116,
-0.03323197737336159,
-0.07400350272655487,
0.08557742834091187,
-0.1155889704823494,
-0.05473526567220688,
-0.13609325885772705,
0.02109934389591217,
0.006740996614098549,
0.0659884586930275,
-0.03885437920689583,
0.08360453695058823,
-0.10388670861721039,
-0.08519915491342545,
0.029333075508475304,
-0.06453096121549606,
-0.0898229330778122,
-0.07718251645565033,
-0.013293148949742317,
-0.05434555560350418,
-0.015362701378762722,
0.08619782328605652,
0.11968319118022919,
0.011989404447376728,
-0.04515336826443672,
0.035499099642038345,
-0.011758756823837757,
0.24077042937278748,
-0.13371670246124268,
-0.021034464240074158,
0.034619878977537155,
0.0033213018905371428,
0.012836294248700142,
-0.01637754961848259,
-0.1063733696937561,
-0.07334472239017487,
0.1866122931241989,
0.019331254065036774,
-0.03930027782917023,
0.042441438883543015,
-0.045477889478206635,
0.02621932327747345,
0.008843916468322277,
-0.028618725016713142,
0.05267992988228798,
-0.08035890758037567,
-0.06428898125886917,
-0.03023458831012249,
0.06822460144758224,
0.03499482199549675,
0.005201693158596754,
0.11640623211860657,
-0.115327849984169,
0.013638339005410671,
-0.03768286854028702,
-0.10431541502475739,
0.0024936639238148928,
-0.05150357261300087,
0.015694214031100273,
-0.19352687895298004,
-0.16134408116340637,
0.00008710320253157988,
-0.00563894584774971,
-0.10239703953266144,
-0.023199869319796562,
-0.02443932369351387,
-0.07115153968334198,
0.0921740010380745,
0.003336285939440131,
0.02991442196071148,
-0.024271249771118164,
0.04414527863264084,
-0.0024972213432192802,
0.09506674855947495,
-0.07465977221727371,
0.027791207656264305,
-0.09102671593427658,
0.0035690604709088802,
-0.16705916821956635,
0.01161686610430479,
-0.03715793788433075,
0.06490571051836014,
-0.0642617717385292,
-0.027714809402823448,
0.08064091205596924,
-0.012828870676457882,
0.036289725452661514,
0.16732437908649445,
-0.14611268043518066,
0.015863141044974327,
0.03014282137155533,
-0.08135686069726944,
-0.07891219109296799,
0.12095792591571808,
-0.041507989168167114,
0.024567430838942528,
0.04436543956398964,
0.07887546718120575,
0.020132895559072495,
-0.12480270117521286,
-0.013255102559924126,
-0.023386213928461075,
-0.07526974380016327,
-0.054364144802093506,
0.017589615657925606,
0.07963849604129791,
-0.18607741594314575,
0.02056078240275383,
0.02303778938949108,
0.05386080965399742,
-0.10133624821901321,
-0.07958811521530151,
-0.06328634917736053,
-0.06170103698968887,
0.06791410595178604,
0.02312338538467884,
0.10341369360685349,
-0.07523267716169357,
-0.05387719348073006,
-0.012035318650305271,
0.06677182763814926,
0.017814185470342636,
-0.04952973872423172,
-0.08069103211164474,
0.11387786269187927,
-0.21757158637046814,
-0.03238776698708534,
-0.10186120867729187,
-0.06896553933620453,
-0.005750209093093872,
0.11180679500102997,
-0.05327850580215454,
0.030458688735961914,
0.05899927392601967,
0.05352277308702469,
-0.05520404130220413,
-0.06461840867996216,
0.11194755882024765,
0.038529638200998306,
-0.14213219285011292,
-0.09951306879520416,
0.053802479058504105,
-0.04332318529486656,
0.16748036444187164,
-0.20909535884857178,
-0.05666455253958702,
0.0008293704595416784,
0.12046751379966736,
0.047635529190301895,
0.05918360874056816,
-0.032569486647844315,
0.008381832391023636,
-0.0894622802734375,
-0.06305897980928421,
0.030923856422305107,
-0.009530168026685715,
-0.030011652037501335,
0.11168850213289261,
-0.18674109876155853,
0.24669773876667023,
0.1617150604724884,
-0.10525580495595932,
-0.12928402423858643,
0.016693953424692154,
0.01755361817777157,
-0.033564694225788116,
-0.11102039366960526,
0.009354599751532078,
-0.04969291761517525,
-0.05666455626487732,
0.1630513072013855,
-0.04181491583585739,
-0.018971392884850502,
0.06916067749261856,
-0.03535833954811096,
-0.12242244184017181,
0.061920881271362305,
0.0349218025803566,
-0.19089676439762115,
0.1374938040971756,
0.18169525265693665,
-0.09279151260852814,
0.08444024622440338,
0.07994136214256287,
-0.04828820750117302,
-0.01142119336873293,
-0.07320425659418106,
-0.0016811236273497343,
0.14625637233257294,
0.002470441395416856,
-0.03705458715558052,
0.04300546646118164,
-0.0116723058745265,
-0.034033920615911484,
-0.14330990612506866,
-0.02529759518802166,
0.013374718837440014,
0.06192585453391075,
0.041711948812007904,
0.01987481117248535,
0.02662065252661705,
0.1558026224374771,
-0.008904739283025265,
-0.15562930703163147,
0.08437930047512054,
0.0216792244464159,
-0.05065203085541725,
0.17159120738506317,
-0.10218150913715363,
-0.2981201410293579,
-0.15263217687606812,
-0.06275319308042526,
-0.08997175842523575,
0.05705647170543671,
0.014335043728351593,
-0.09836576133966446,
-0.12258726358413696,
-0.0460532046854496,
-0.060404784977436066,
-0.020423008129000664,
0.0266214981675148,
-0.03662209212779999,
-0.03298797458410263,
0.04655608534812927,
-0.043321236968040466,
-0.050508346408605576,
-0.017892537638545036,
-0.040380146354436874,
0.18272081017494202,
-0.005046079866588116,
0.11814708262681961,
0.14226701855659485,
-0.08418049663305283,
0.030892370268702507,
-0.017711028456687927,
0.16858845949172974,
-0.06697829067707062,
0.025516187772154808,
0.13002456724643707,
0.0017612525261938572,
0.00971185602247715,
0.21123063564300537,
-0.026435524225234985,
-0.09280769526958466,
0.01842714287340641,
0.00717845419421792,
-0.03586249426007271,
-0.06790820509195328,
-0.11057079583406448,
-0.008081641979515553,
0.011142125353217125,
0.13783733546733856,
0.03731692582368851,
0.14547200500965118,
0.1363433450460434,
0.034432169049978256,
0.07978807389736176,
-0.03837410733103752,
0.07240646332502365,
0.1278822422027588,
-0.027173500508069992,
0.20151011645793915,
-0.027838824316859245,
-0.10482439398765564,
0.061884403228759766,
-0.016176365315914154,
0.11849241703748703,
0.04580960422754288,
-0.18612244725227356,
-0.022287676110863686,
0.15774892270565033,
0.11594881862401962,
0.06273435801267624,
0.05972906947135925,
-0.07829409837722778,
-0.0012191543355584145,
-0.03386819735169411,
-0.0073935650289058685,
0.07774822413921356,
0.04684751108288765,
0.016109513118863106,
-0.10734318941831589,
0.058221060782670975,
0.05130169913172722,
0.05676732584834099,
0.1865433007478714,
-0.43272921442985535,
-0.008748444728553295,
0.03876010328531265,
0.00739370146766305,
-0.16207081079483032,
0.04794875159859657,
0.05705176666378975,
-0.10820847749710083,
0.019585054367780685,
-0.0645727887749672,
0.06509844213724136,
-0.008049985393881798,
0.002914471086114645,
-0.017005084082484245,
-0.03513994812965393,
-0.03823348134756088,
0.06381379067897797,
-0.21717648208141327,
0.22112619876861572,
0.03129829466342926,
0.011445061303675175,
-0.08465168625116348,
-0.002523314906284213,
0.07928048819303513,
0.1861942857503891,
0.18048778176307678,
-0.016474099829792976,
-0.06367690861225128,
-0.24910679459571838,
-0.07545652240514755,
-0.025217242538928986,
0.019426928833127022,
0.055922556668519974,
0.04522234946489334,
-0.08111640065908432,
-0.039453767240047455,
0.038182470947504044,
0.020590996369719505,
-0.14328035712242126,
-0.06113247945904732,
-0.0021968684159219265,
0.10619284957647324,
0.02576957270503044,
-0.03795035555958748,
-0.09387122094631195,
-0.13296163082122803,
0.09315142035484314,
0.08285684883594513,
0.017619645223021507,
-0.15964266657829285,
0.11251258850097656,
0.05352645739912987,
-0.04761887714266777,
0.09093422442674637,
-0.04083200544118881,
0.1239188015460968,
0.026597019284963608,
-0.09725033491849899,
0.1332649141550064,
-0.10242529958486557,
-0.060427453368902206,
-0.0695042610168457,
0.0029559016693383455,
-0.06930549442768097,
-0.0011241917964071035,
0.07255979627370834,
0.10804445296525955,
-0.035934872925281525,
-0.03759855031967163,
0.0885319709777832,
-0.021710235625505447,
0.10872984677553177,
0.06473749876022339,
-0.013654033653438091,
-0.2032601684331894,
-0.027759144082665443,
0.0007966867997311056,
0.14936546981334686,
0.1728937178850174,
-0.1348000317811966,
-0.007905587553977966,
0.06174921244382858,
-0.0033595855347812176,
-0.3700328767299652,
0.08373172581195831,
-0.033447179943323135,
0.05317060649394989,
-0.04645541310310364,
0.058037884533405304,
0.1376136988401413,
0.08644901216030121,
-0.060326188802719116,
0.030765004456043243,
-0.16337700188159943,
-0.11613792926073074,
0.23836170136928558,
0.07951993495225906,
0.2148960381746292,
-0.07703369855880737,
-0.008902961388230324,
-0.10445208847522736,
-0.06962532550096512,
0.028775537386536598,
0.020447492599487305,
0.07001294940710068,
-0.05211220681667328,
0.03506042808294296,
0.05088294669985771,
-0.05886368826031685,
0.11742928624153137,
-0.0685519352555275,
0.12949396669864655,
-0.10991595685482025,
-0.09442836046218872,
0.025484053418040276,
-0.07853198796510696,
0.10368958115577698,
0.09238481521606445,
0.07853846997022629,
-0.08890324085950851,
0.003262970829382539,
-0.027113713324069977,
0.07644834369421005,
-0.0000015044259953356232,
-0.056146860122680664,
-0.04374917224049568,
0.045481450855731964,
-0.03236670047044754,
-0.0855071097612381,
0.0573333241045475,
0.006283662747591734,
0.04194983094930649,
0.13423912227153778,
0.01142116915434599,
-0.08547955751419067,
0.03293450549244881,
-0.0009496986749581993,
-0.07566029578447342,
0.13392513990402222,
-0.0812968760728836,
0.09716163575649261,
0.10258973389863968,
-0.02945389412343502,
0.15293224155902863,
0.07282054424285889,
0.034028682857751846,
0.00048158588469959795,
0.11517296731472015,
-0.1481626033782959,
0.021843835711479187,
-0.054477445781230927,
0.017049061134457588,
0.05836257338523865,
0.0317097082734108,
0.11184398084878922,
-0.10671061277389526,
0.0034433994442224503,
-0.0055794427171349525,
0.03321577236056328,
0.0239284448325634,
0.18891729414463043,
0.04826944321393967,
0.0027750623412430286,
-0.10907091945409775,
0.09308233112096786,
0.07986456155776978,
-0.1053013876080513,
0.006697244010865688,
-0.047021858394145966,
-0.08835756778717041,
-0.07142993062734604,
0.05400805547833443,
0.1975754052400589,
-0.1960982233285904,
-0.025141306221485138,
-0.042123809456825256,
-0.14048799872398376,
0.050629597157239914,
0.17664602398872375,
0.08655690401792526,
0.02249990403652191,
-0.003848331281915307,
-0.08060018718242645,
-0.12160082161426544,
0.11026166379451752,
0.10532831400632858,
0.10791566967964172,
-0.2652375400066376,
0.07311280816793442,
-0.05285022035241127,
0.07531387358903885,
-0.08500192314386368,
0.0025960076600313187,
-0.14130422472953796,
0.0027612007688730955,
-0.15942376852035522,
0.03878893330693245,
0.008934247307479382,
-0.004092846997082233,
0.04035404697060585,
-0.03957192599773407,
-0.05845468491315842,
0.004302802495658398,
-0.07268156856298447,
0.011647704988718033,
0.029037917032837868,
0.024909265339374542,
-0.05148833990097046,
-0.1165342926979065,
0.01809733361005783,
-0.009548265486955643,
0.06167957931756973,
0.05819043889641762,
0.012853499501943588,
0.007886137813329697,
-0.07623568177223206,
-0.09854385256767273,
0.11932259798049927,
-0.015940872952342033,
0.09484442323446274,
-0.06499309837818146,
0.04228295758366585,
0.04735390841960907,
0.00948904175311327,
0.03744716942310333,
0.09172206372022629,
-0.09550628066062927,
-0.07669197767972946,
-0.09953180700540543,
-0.10533061623573303,
-0.07649583369493484,
0.058258023113012314,
0.11345750093460083,
-0.010642657987773418,
0.1450250893831253,
-0.10537444800138474,
0.0008919182000681758,
-0.10234703868627548,
0.01180714275687933,
-0.06642398238182068,
-0.13117501139640808,
-0.11383896321058273,
-0.008864488452672958,
0.055892378091812134,
-0.04136474058032036,
0.07749893516302109,
0.09790180623531342,
0.035149525851011276,
0.03402860090136528,
0.10744660347700119,
-0.020776335150003433,
0.036682434380054474,
0.14776869118213654,
0.0720352903008461,
-0.013820868916809559,
-0.031205279752612114,
0.10369662940502167,
0.1595471352338791,
0.028553662821650505,
-0.005539273843169212,
0.038107581436634064,
-0.06946299970149994,
0.15231524407863617,
0.01887451484799385,
-0.08631326258182526,
-0.07096242904663086,
0.009358653798699379,
-0.20703153312206268,
0.09601575136184692,
-0.03193600848317146,
-0.052638087421655655,
0.15928371250629425,
-0.06899692118167877,
-0.03303385525941849,
-0.1338178515434265,
-0.08446285128593445,
-0.12309250235557556,
-0.11896613240242004,
-0.16266170144081116,
-0.10882562398910522,
0.02365798130631447,
-0.06467549502849579,
0.03676794469356537,
0.0940278097987175,
0.06103748083114624,
-0.035782668739557266,
0.1499224752187729,
-0.1432434767484665,
0.0006608229596167803,
0.08369085192680359,
0.005349588580429554,
-0.008745397441089153,
-0.046583518385887146,
-0.01049333531409502,
-0.0037672817707061768,
0.022867679595947266,
-0.011993082240223885,
-0.027489962056279182,
0.025337953120470047,
0.05789019167423248,
0.0007868751999922097,
-0.0946841686964035,
-0.019911643117666245,
0.01791646145284176,
0.029243404045701027,
0.0005123780574649572,
-0.0034921267069876194,
0.0754028707742691,
-0.004794702865183353,
0.2594046890735626,
-0.12352462857961655,
-0.022744832560420036,
-0.1403522491455078,
0.21974441409111023,
-0.010851564817130566,
0.11172614246606827,
-0.016827121376991272,
-0.07883895188570023,
0.04457340016961098,
0.21918581426143646,
0.1581614762544632,
-0.081664077937603,
-0.017680367454886436,
-0.025384215638041496,
-0.01858830451965332,
-0.06276383250951767,
0.09058725088834763,
0.03173503279685974,
0.03918282687664032,
-0.07803261280059814,
0.016871202737092972,
-0.030735837295651436,
-0.05806322023272514,
-0.010770300403237343,
0.0713338553905487,
0.007623058278113604,
-0.0022286707535386086,
-0.10737813264131546,
0.0495864637196064,
0.049573641270399094,
0.11050111800432205,
0.10619289427995682,
-0.11463672667741776,
-0.11898758262395859,
0.05250517651438713,
0.08012460172176361,
-0.05225037783384323,
0.03972786292433739,
-0.1024775430560112,
0.02629995532333851,
-0.015247403644025326,
-0.003605624893680215,
-0.11053907871246338,
-0.10544513165950775,
0.023402610793709755,
0.08425650745630264,
0.26813817024230957,
-0.0015643282094970345,
0.059220850467681885,
0.09636080265045166,
-0.013669140636920929,
-0.13024146854877472,
0.06563983857631683,
-0.020972207188606262,
-0.08354313671588898,
0.09101174026727676,
0.13091446459293365,
0.003813851857557893,
0.0880960002541542,
0.00840036105364561,
-0.16746124625205994,
0.020451141521334648,
-0.11434514820575714,
-0.040336545556783676,
-0.06157713010907173,
0.05710338056087494,
-0.0299193374812603,
0.13958153128623962,
0.07851602137088776,
-0.025460151955485344,
0.0074645462445914745,
-0.059743668884038925,
0.019913917407393456,
0.043240007013082504,
-0.020163098350167274,
0.03873152658343315,
-0.11168283969163895,
0.05953068286180496,
-0.06697549670934677,
0.009027083404362202,
-0.20611749589443207,
-0.06812622398138046,
-0.07354293018579483,
-0.06803802400827408,
-0.08379846811294556,
0.13672052323818207,
0.12674887478351593,
0.022880390286445618,
-0.040065597742795944,
-0.09839915484189987,
0.026665199548006058,
0.09008928388357162,
-0.011215892620384693,
-0.1026654988527298
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-cased-bn-adapter-895K-squad-model3
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 71
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-base-cased-bn-adapter-895K-squad-model3", "results": []}]} | null | varun-v-rao/bert-base-cased-bn-adapter-895K-squad-model3 | [
"tensorboard",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:bert-base-cased",
"license:apache-2.0",
"region:us"
] | 2024-02-09T02:06:04+00:00 | [] | [] | TAGS
#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-bert-base-cased #license-apache-2.0 #region-us
|
# bert-base-cased-bn-adapter-895K-squad-model3
This model is a fine-tuned version of bert-base-cased on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 71
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# bert-base-cased-bn-adapter-895K-squad-model3\n\nThis model is a fine-tuned version of bert-base-cased on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 71\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-bert-base-cased #license-apache-2.0 #region-us \n",
"# bert-base-cased-bn-adapter-895K-squad-model3\n\nThis model is a fine-tuned version of bert-base-cased on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 71\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
49,
45,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-bert-base-cased #license-apache-2.0 #region-us \n# bert-base-cased-bn-adapter-895K-squad-model3\n\nThis model is a fine-tuned version of bert-base-cased on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 71\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.08991832286119461,
0.03241715580224991,
-0.0006316642393358052,
0.07234687358140945,
0.17247939109802246,
0.012831277213990688,
0.1309572160243988,
0.09355566650629044,
-0.11990545690059662,
0.033204689621925354,
0.0501396581530571,
0.04333381727337837,
0.03598729148507118,
0.09284596890211105,
-0.016951140016317368,
-0.23830115795135498,
-0.0006945532513782382,
0.03428926318883896,
-0.11766258627176285,
0.08920159190893173,
0.11132951825857162,
-0.12157729268074036,
0.06496404856443405,
0.0254445169121027,
-0.2207881063222885,
0.05557632073760033,
-0.012358617037534714,
-0.03722739592194557,
0.10486005991697311,
0.022697823122143745,
0.13872940838336945,
-0.008341489359736443,
0.1468343585729599,
-0.1634671539068222,
0.007793613243848085,
0.09205693751573563,
0.03493936359882355,
0.08901812881231308,
0.02015575021505356,
0.043439555913209915,
0.07957979291677475,
-0.08447331190109253,
0.08748248219490051,
0.03427534177899361,
-0.07528530806303024,
-0.2037905752658844,
-0.07561750710010529,
0.0404755063354969,
0.10379444062709808,
0.07208595424890518,
-0.005122858099639416,
0.13296382129192352,
-0.06071002781391144,
0.06162884458899498,
0.1997150033712387,
-0.29124003648757935,
-0.09132134169340134,
0.09350114315748215,
0.05746019259095192,
0.07759624719619751,
-0.0980871245265007,
-0.012427213601768017,
0.06352021545171738,
0.04918420687317848,
0.10525915771722794,
-0.014285675249993801,
-0.11165383458137512,
0.010168589651584625,
-0.14476895332336426,
0.032381538301706314,
0.14820946753025055,
0.03861253708600998,
-0.06223204731941223,
-0.019973337650299072,
-0.055632930248975754,
-0.07152649015188217,
-0.05517357587814331,
-0.04828300327062607,
0.06650255620479584,
-0.03532138094305992,
-0.09062442928552628,
-0.08077462017536163,
-0.0845140665769577,
-0.0969851016998291,
-0.020873820409178734,
0.13012610375881195,
0.0371149517595768,
0.02302374877035618,
-0.06318893283605576,
0.10310521721839905,
-0.07251793891191483,
-0.11135964840650558,
0.010291360318660736,
0.01218071486800909,
-0.05028543621301651,
-0.06679796427488327,
-0.06919723004102707,
-0.05679873004555702,
0.0077737378887832165,
0.13569656014442444,
-0.04945290833711624,
0.0647100955247879,
-0.02041659690439701,
0.021079227328300476,
-0.049166955053806305,
0.15591244399547577,
-0.06308053433895111,
-0.02423929236829281,
0.02134963683784008,
0.07954396307468414,
0.01300560962408781,
0.006373915821313858,
-0.11570588499307632,
0.01703319326043129,
0.06385806947946548,
0.012161128222942352,
-0.08242621272802353,
0.03126436844468117,
-0.02351340465247631,
-0.028187137097120285,
-0.002255761530250311,
-0.09896684437990189,
0.028603460639715195,
-0.017781715840101242,
-0.09024681150913239,
-0.031164346262812614,
0.022355303168296814,
0.01486117485910654,
0.006587326060980558,
0.08912213146686554,
-0.10546045750379562,
0.012072833254933357,
-0.127691388130188,
-0.10913674533367157,
0.006333678495138884,
-0.08679987490177155,
0.0024387575685977936,
-0.06865154206752777,
-0.17725500464439392,
-0.007125223986804485,
0.05359340459108353,
-0.058181919157505035,
-0.030564984306693077,
-0.02889847382903099,
-0.07474066317081451,
0.0022699865512549877,
-0.011254553683102131,
0.17547467350959778,
-0.04187440127134323,
0.05816224217414856,
0.040503766387701035,
0.03187745809555054,
-0.07556252181529999,
0.04318484291434288,
-0.06796275079250336,
0.025204045698046684,
-0.21056054532527924,
0.04118116572499275,
-0.1048080325126648,
0.04370706155896187,
-0.11084466427564621,
-0.08079810440540314,
0.009719728492200375,
0.00376563286408782,
0.1055048480629921,
0.07590625435113907,
-0.19017305970191956,
-0.043026603758335114,
0.10699476301670074,
-0.07333710044622421,
-0.09769269824028015,
0.08188199251890182,
-0.05491955950856209,
0.0738571435213089,
0.06652311235666275,
0.1473722755908966,
0.044387225061655045,
-0.13462212681770325,
-0.0019289158517494798,
0.022776151075959206,
0.10974254459142685,
-0.03434204310178757,
0.048103321343660355,
-0.00732839573174715,
-0.005343579221516848,
0.023650744929909706,
-0.07046087086200714,
-0.006847682874649763,
-0.09362597018480301,
-0.06737790256738663,
-0.050037357956171036,
-0.10112296789884567,
0.009133441373705864,
0.03534283488988876,
0.055081456899642944,
-0.07777576893568039,
-0.10307701677083969,
0.21371430158615112,
0.11861271411180496,
-0.051992081105709076,
0.025385217741131783,
-0.09336653351783752,
0.0730181410908699,
-0.07418126612901688,
-0.018222961574792862,
-0.20316877961158752,
-0.11096435785293579,
0.019519614055752754,
-0.023099573329091072,
0.05932816118001938,
0.038366928696632385,
0.058352041989564896,
0.0692780390381813,
-0.062307439744472504,
0.021772710606455803,
-0.0937783420085907,
-0.00737800495699048,
-0.12972195446491241,
-0.21308790147304535,
-0.07398587465286255,
-0.02548276260495186,
0.15635980665683746,
-0.2227647453546524,
0.030858270823955536,
-0.01771959289908409,
0.12042941153049469,
0.026514161378145218,
-0.034329604357481,
-0.05245677009224892,
0.07234157621860504,
-0.005521952640265226,
-0.07181859016418457,
0.050969596952199936,
0.018753143027424812,
-0.07335200905799866,
-0.09540867805480957,
-0.10605723410844803,
0.06486990302801132,
0.10400697588920593,
-0.028476187959313393,
-0.07244206219911575,
0.0007859994075261056,
-0.056045737117528915,
-0.027314769104123116,
-0.06438490748405457,
-0.022118955850601196,
0.16938208043575287,
-0.0006420335848815739,
0.1437119096517563,
-0.08323776721954346,
-0.057601816952228546,
0.007360775023698807,
-0.0061981347389519215,
0.03266208991408348,
0.05847044661641121,
0.104901023209095,
-0.06376798450946808,
0.09148526936769485,
0.11669854074716568,
-0.11064862459897995,
0.13372556865215302,
-0.050028979778289795,
-0.07378019392490387,
-0.016074109822511673,
-0.027872160077095032,
-0.017608383670449257,
0.17171074450016022,
-0.14908751845359802,
-0.007402020040899515,
0.012593379244208336,
0.012700268998742104,
0.046363286674022675,
-0.1989312320947647,
0.006580509711056948,
0.011470385827124119,
-0.030770136043429375,
-0.02875480428338051,
-0.03906913474202156,
0.0036575295962393284,
0.09506066143512726,
0.02672569453716278,
-0.0355316624045372,
0.01404382474720478,
-0.0013353850226849318,
-0.06650044023990631,
0.20489172637462616,
-0.11351172626018524,
-0.06200198456645012,
-0.12705251574516296,
-0.017233261838555336,
-0.074172742664814,
-0.015913812443614006,
0.013676499016582966,
-0.10335159301757812,
-0.046243976801633835,
-0.07929277420043945,
0.03938114270567894,
0.0032000578939914703,
-0.00169644586276263,
0.039113227277994156,
-0.0022113248705863953,
0.12338878214359283,
-0.15472571551799774,
0.01753797009587288,
-0.055328015238046646,
-0.12659277021884918,
-0.040041547268629074,
0.0709269568324089,
0.09755226969718933,
0.13606782257556915,
-0.03187873587012291,
0.004809380508959293,
-0.027220062911510468,
0.25172996520996094,
-0.05460646376013756,
-0.011657114140689373,
0.11374473571777344,
-0.003405489958822727,
0.03029416687786579,
0.11801818758249283,
0.07608937472105026,
-0.10732701420783997,
0.025696536526083946,
0.10271114856004715,
-0.027278754860162735,
-0.24000263214111328,
-0.020436331629753113,
-0.025107132270932198,
-0.08472815901041031,
0.061348073184490204,
0.04175496846437454,
-0.021915730088949203,
0.07283656299114227,
0.021281417459249496,
0.09540878981351852,
-0.04480907693505287,
0.0803680419921875,
0.10965485870838165,
0.032937418669462204,
0.1295868456363678,
-0.03878156840801239,
-0.03134707733988762,
0.054278191179037094,
0.02192455530166626,
0.255103200674057,
-0.006675987038761377,
0.08019045740365982,
0.07621444761753082,
0.13684339821338654,
-0.027386873960494995,
0.047916170209646225,
-0.022693153470754623,
-0.03084952011704445,
-0.0036548965144902468,
-0.06293240189552307,
0.0075132944621145725,
0.001334098051302135,
-0.08116628229618073,
0.07425674051046371,
-0.07286680489778519,
0.000742289237678051,
0.031874578446149826,
0.2706313133239746,
0.027134571224451065,
-0.2852729260921478,
-0.09160492569208145,
0.012392740696668625,
-0.022871894761919975,
-0.0576169528067112,
0.014975113794207573,
0.12073833495378494,
-0.07544822245836258,
0.03353289142251015,
-0.0590190552175045,
0.10505849123001099,
0.01223665103316307,
0.013979305513203144,
0.09139226377010345,
0.17817477881908417,
-0.009717545472085476,
0.06042347848415375,
-0.22617501020431519,
0.22615137696266174,
0.039148733019828796,
0.1261046826839447,
-0.029790930449962616,
0.02770289033651352,
0.022808674722909927,
0.0938112884759903,
0.038904640823602676,
-0.0171852745115757,
-0.012562190182507038,
-0.191922128200531,
-0.025328604504466057,
0.0615694522857666,
0.10468757897615433,
-0.026210153475403786,
0.09732551127672195,
-0.030346276238560677,
0.019442982971668243,
0.06915141642093658,
-0.03677967190742493,
-0.17883823812007904,
-0.08173064142465591,
-0.03653908520936966,
0.007526838220655918,
-0.06388115137815475,
-0.08440013229846954,
-0.10246867686510086,
-0.04828328266739845,
0.12306004017591476,
0.008882565423846245,
-0.032140858471393585,
-0.11684371531009674,
0.119914710521698,
0.09479178488254547,
-0.04004848003387451,
0.02626504749059677,
0.011647866107523441,
0.12702380120754242,
0.04164153337478638,
-0.08271848410367966,
0.08132185786962509,
-0.07753883302211761,
-0.14315587282180786,
-0.05342108756303787,
0.08633676916360855,
0.06565777212381363,
0.04233817383646965,
-0.0010507008992135525,
0.011171093210577965,
0.016614949330687523,
-0.08878384530544281,
-0.008667618036270142,
0.00792138185352087,
0.05909324437379837,
0.02515370585024357,
-0.10337725281715393,
0.023243805393576622,
-0.021773310378193855,
0.01039810199290514,
0.08968092501163483,
0.21275126934051514,
-0.07214810699224472,
0.007289268542081118,
0.11328785866498947,
-0.09786597639322281,
-0.18110354244709015,
0.13334505259990692,
0.1132907122373581,
0.013385861180722713,
0.04581424966454506,
-0.22017483413219452,
0.18551892042160034,
0.12650729715824127,
-0.032424941658973694,
0.07319456338882446,
-0.26526695489883423,
-0.14740043878555298,
0.10167635977268219,
0.15205265581607819,
0.054973114281892776,
-0.14617092907428741,
-0.024999301880598068,
-0.05109398066997528,
-0.1447352170944214,
0.14060567319393158,
-0.19104500114917755,
0.08919627219438553,
0.01456006895750761,
0.09409352391958237,
0.006074618082493544,
-0.024767285212874413,
0.13154159486293793,
0.026970447972416878,
0.10858508944511414,
-0.035126011818647385,
0.03473716601729393,
0.1332794725894928,
-0.04002779349684715,
0.017176413908600807,
-0.029700888320803642,
0.039719175547361374,
-0.11327198892831802,
-0.008954320102930069,
-0.06221563741564751,
0.04680450260639191,
-0.05508769303560257,
-0.06681736558675766,
-0.04606826603412628,
0.045901838690042496,
-0.0036869263276457787,
-0.033427644520998,
0.09991877526044846,
0.00642292620614171,
0.15119685232639313,
0.10120035707950592,
0.10704735666513443,
-0.0674217939376831,
-0.05819102004170418,
0.04523743316531181,
-0.02224735915660858,
0.08724521100521088,
-0.16250675916671753,
0.01655735820531845,
0.10994080454111099,
0.03853251785039902,
0.12019606679677963,
0.061944399029016495,
-0.06544239073991776,
0.02261624112725258,
0.05800527334213257,
-0.09270965307950974,
-0.14201658964157104,
0.006305714137852192,
-0.01481435913592577,
-0.1414005309343338,
0.07812690734863281,
0.11174497753381729,
-0.07082198560237885,
-0.009144607000052929,
0.003222791710868478,
-0.01266195997595787,
-0.07237663865089417,
0.1970731019973755,
0.07186015695333481,
0.05734354257583618,
-0.09147629886865616,
0.1047343760728836,
0.05188519507646561,
-0.03782310336828232,
0.02635199762880802,
0.04259614273905754,
-0.07340525835752487,
-0.005162050947546959,
0.0638083964586258,
0.2137107253074646,
-0.062125541269779205,
-0.05343235656619072,
-0.11552601307630539,
-0.10138105601072311,
0.029214223846793175,
0.17316552996635437,
0.07457759231328964,
-0.04046593979001045,
-0.04759569838643074,
0.07300136983394623,
-0.13014645874500275,
0.08852771669626236,
0.010483309626579285,
0.0900496244430542,
-0.11499543488025665,
0.10109081864356995,
0.01787341944873333,
0.02149486541748047,
-0.027778029441833496,
0.031389269977808,
-0.10913721472024918,
-0.013135939836502075,
-0.20571649074554443,
-0.03664741292595863,
0.004172755405306816,
0.007567481603473425,
-0.003986123949289322,
-0.04827539250254631,
-0.07473935186862946,
0.04670524597167969,
-0.09779828041791916,
-0.033461038023233414,
0.05050626024603844,
0.03873986378312111,
-0.1374436914920807,
0.020214494317770004,
0.013575343415141106,
-0.07371117919683456,
0.05789060890674591,
0.02918052300810814,
0.04071545973420143,
0.07410542666912079,
-0.1221616119146347,
-0.005814526230096817,
0.016963854432106018,
0.030421681702136993,
0.09103426337242126,
-0.041812509298324585,
-0.009093699045479298,
-0.027817288413643837,
0.09737756103277206,
0.002254922641441226,
0.08672566711902618,
-0.11141890287399292,
-0.025934061035513878,
-0.053312137722969055,
-0.04201190173625946,
-0.047445815056562424,
0.038815535604953766,
0.09719842672348022,
0.07695644348859787,
0.16095291078090668,
-0.07539786398410797,
-0.016709107905626297,
-0.20394733548164368,
-0.02362946607172489,
-0.0038591513875871897,
-0.04794774577021599,
-0.08873254060745239,
-0.05900071561336517,
0.06218017265200615,
-0.07081669569015503,
0.1223141998052597,
0.012795251794159412,
0.10552705079317093,
0.0496549978852272,
-0.01985067129135132,
-0.01655787229537964,
0.014831372536718845,
0.20019222795963287,
0.05468568950891495,
0.0036592755932360888,
0.05775506794452667,
0.03486631065607071,
0.07784084230661392,
0.08297461271286011,
0.18302704393863678,
0.1309679001569748,
-0.052293810993433,
0.0800272598862648,
0.10402155667543411,
-0.072128064930439,
-0.1288057267665863,
0.13633419573307037,
-0.030686819925904274,
0.11030390113592148,
-0.06600462645292282,
0.2035875916481018,
0.09209620207548141,
-0.16146914660930634,
0.03920378163456917,
-0.073744997382164,
-0.09702570736408234,
-0.12078770250082016,
-0.012986717745661736,
-0.06653350591659546,
-0.1672823280096054,
0.01670641452074051,
-0.14060336351394653,
0.005562386941164732,
0.1499626338481903,
0.00528974924236536,
0.009310142137110233,
0.17588497698307037,
-0.03514532744884491,
0.028750022873282433,
0.04710766673088074,
0.00034852817771025,
-0.016986267641186714,
-0.08889035880565643,
-0.06972778588533401,
0.04493378475308418,
0.00964890792965889,
0.052343375980854034,
-0.061198972165584564,
-0.026478925719857216,
0.03234502673149109,
0.007349600084125996,
-0.06340833753347397,
0.02259654365479946,
0.027531059458851814,
0.04897094517946243,
0.04224226623773575,
0.01239379309117794,
0.003709634533151984,
-0.03746318817138672,
0.27050185203552246,
-0.08066999912261963,
-0.08001770824193954,
-0.13940228521823883,
0.20324112474918365,
0.008412591181695461,
-0.008017247542738914,
0.042141418904066086,
-0.1099686324596405,
-0.028516126796603203,
0.18169009685516357,
0.14947491884231567,
-0.09657970070838928,
-0.03328831493854523,
0.0020163876470178366,
-0.029725095257163048,
-0.10140176117420197,
0.15476743876934052,
0.10923294723033905,
0.019966503605246544,
-0.06310476362705231,
-0.039981964975595474,
-0.018237128853797913,
-0.0242946594953537,
-0.04824573174118996,
0.04976899176836014,
0.041739292442798615,
0.002581553300842643,
-0.036026403307914734,
0.058206599205732346,
-0.00589382741600275,
-0.21879427134990692,
0.03746689856052399,
-0.12899282574653625,
-0.17960695922374725,
-0.042414937168359756,
0.07874681055545807,
-0.023082220926880836,
0.05491691827774048,
-0.042901553213596344,
0.013096929527819157,
0.12579642236232758,
-0.04145953804254532,
-0.01480498444288969,
-0.15845191478729248,
0.13478845357894897,
-0.1021287813782692,
0.22517718374729156,
-0.028726166114211082,
0.06258270144462585,
0.11933057010173798,
0.019404524937272072,
-0.10207687318325043,
0.03554023802280426,
0.04735368862748146,
-0.10629250109195709,
-0.0014214318944141269,
0.1264479160308838,
-0.05284491926431656,
0.0986357182264328,
0.022945493459701538,
-0.13462160527706146,
0.004919642582535744,
-0.07432343810796738,
-0.05581370368599892,
-0.0794471725821495,
-0.019179975613951683,
-0.11019724607467651,
0.1296554058790207,
0.20604902505874634,
-0.02556982822716236,
0.0031470542307943106,
-0.08831722289323807,
0.04083099588751793,
0.061240825802087784,
0.08845991641283035,
-0.0383429192006588,
-0.2405964881181717,
0.027605412527918816,
0.07146625965833664,
-0.03414890542626381,
-0.27183791995048523,
-0.0636051818728447,
0.07059359550476074,
-0.03585837036371231,
-0.05105914920568466,
0.08757288008928299,
0.11317431181669235,
0.05548226088285446,
-0.05870887264609337,
-0.16380536556243896,
-0.07704249024391174,
0.14517250657081604,
-0.1435452401638031,
-0.07004247605800629
] |
null | null | null |
<img src="data:image/svg+xml;base64,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" />
These are GGUF quantized versions of [01-ai/Yi-34B](https://huggingface.co/01-ai/Yi-34B).
The importance matrix was trained for 100K tokens (200 batches of 512 tokens) using `wiki.train.raw`.
The IQ2_XXS and IQ2_XS versions are compatible with llama.cpp, version `147b17a` or later. The IQ3_XXS requires version `f4d7e54` or later.
Some model files above 50GB are split into smaller files. To concatenate them, use the `cat` command (on Windows, use PowerShell): `cat foo-Q6_K.gguf.* > foo-Q6_K.gguf` | {"language": ["en"], "license": "other", "license_name": "yi-license", "license_link": "https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE"} | null | Artefact2/Yi-34B-GGUF | [
"gguf",
"en",
"license:other",
"region:us"
] | 2024-02-09T02:06:26+00:00 | [] | [
"en"
] | TAGS
#gguf #en #license-other #region-us
|
<img src="data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iNjAwIiBoZWlnaHQ9IjYwMCIgdmlld0JveD0iMCAwIDYwMCA2MDAiIGZpbGw9Im5vbmUiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CjxjaXJjbGUgY3g9IjMwMCIgY3k9IjMwMCIgcj0iMzAwIiBmaWxsPSIjMDAzNDI1Ii8+CjxyZWN0IHg9IjQwOS43MzMiIHk9IjM0MC4wMzEiIHdpZHRoPSI0Mi4zODYyIiBoZWlnaHQ9IjE1MS42NDgiIHJ4PSIyMS4xOTMxIiBmaWxsPSJ3aGl0ZSIvPgo8cGF0aCBmaWxsLXJ1bGU9ImV2ZW5vZGQiIGNsaXAtcnVsZT0iZXZlbm9kZCIgZD0iTTQyMi4wMDUgMTMzLjM1NEM0MTMuMDg5IDEyNS43NzEgMzk5LjcxNCAxMjYuODUxIDM5Mi4xMzEgMTM1Ljc2N0wyNzMuNjk5IDI3NS4wMjFDMjcwLjY0MyAyNzguNjE0IDI2OC45OTQgMjgyLjkzMiAyNjguNjk4IDI4Ny4zMDJDMjY4LjUzMiAyODguMzcxIDI2OC40NDYgMjg5LjQ2NiAyNjguNDQ2IDI5MC41ODFWNDY4LjYwM0MyNjguNDQ2IDQ4MC4zMDggMjc3LjkzNCA0ODkuNzk2IDI4OS42MzkgNDg5Ljc5NkMzMDEuMzQ0IDQ4OS43OTYgMzEwLjgzMiA0ODAuMzA4IDMxMC44MzIgNDY4LjYwM1YyOTYuNzg0TDQyNC40MTkgMTYzLjIyOEM0MzIuMDAyIDE1NC4zMTIgNDMwLjkyMSAxNDAuOTM3IDQyMi4wMDUgMTMzLjM1NFoiIGZpbGw9IndoaXRlIi8+CjxyZWN0IHg9IjExMy45NzIiIHk9IjEzNC4yNSIgd2lkdGg9IjQyLjM4NjIiIGhlaWdodD0iMTc0Ljc0NSIgcng9IjIxLjE5MzEiIHRyYW5zZm9ybT0icm90YXRlKC0zOS4zNDQxIDExMy45NzIgMTM0LjI1KSIgZmlsbD0id2hpdGUiLz4KPGNpcmNsZSBjeD0iNDYwLjEyNiIgY3k9IjI3OS4yNzgiIHI9IjI1LjkwMjciIGZpbGw9IiMwMEZGMjUiLz4KPC9zdmc+" />
These are GGUF quantized versions of 01-ai/Yi-34B.
The importance matrix was trained for 100K tokens (200 batches of 512 tokens) using 'URL'.
The IQ2_XXS and IQ2_XS versions are compatible with URL, version '147b17a' or later. The IQ3_XXS requires version 'f4d7e54' or later.
Some model files above 50GB are split into smaller files. To concatenate them, use the 'cat' command (on Windows, use PowerShell): 'cat foo-Q6_K.gguf.* > foo-Q6_K.gguf' | [] | [
"TAGS\n#gguf #en #license-other #region-us \n"
] | [
16
] | [
"passage: TAGS\n#gguf #en #license-other #region-us \n"
] | [
0.03707072511315346,
0.09913434088230133,
-0.00870874710381031,
-0.006532791070640087,
0.02293686382472515,
0.0556492805480957,
0.16533252596855164,
0.026876205578446388,
0.21608202159404755,
-0.032441556453704834,
0.12898358702659607,
0.04598511755466461,
0.012529212050139904,
0.007846599444746971,
0.041737303137779236,
-0.18633735179901123,
0.048099420964717865,
-0.06315776705741882,
0.05767900496721268,
0.012780582532286644,
0.0027143582701683044,
-0.030916865915060043,
0.00782254058867693,
-0.01654396578669548,
-0.09744243323802948,
0.024717526510357857,
0.006332659628242254,
-0.03149033710360527,
0.11124551296234131,
0.10425955057144165,
0.04378674179315567,
0.03815523535013199,
-0.02466847375035286,
-0.20687055587768555,
0.02283935621380806,
-0.08458584547042847,
-0.14280137419700623,
0.019482720643281937,
0.05214528366923332,
-0.030664842575788498,
0.07043583691120148,
0.20295269787311554,
-0.06924128532409668,
0.07273276150226593,
-0.24455030262470245,
-0.28113284707069397,
-0.07284314930438995,
0.022639891132712364,
-0.04829562455415726,
0.026769358664751053,
0.050944793969392776,
0.07210956513881683,
-0.16636137664318085,
-0.027252789586782455,
0.06467224657535553,
-0.33928385376930237,
0.07719913125038147,
0.23049084842205048,
-0.018195848912000656,
0.024345379322767258,
-0.07941575348377228,
0.14156785607337952,
0.05595522001385689,
-0.021348094567656517,
-0.170192688703537,
-0.03651909902691841,
0.03110424242913723,
0.1515502780675888,
-0.03728824108839035,
-0.11180154979228973,
0.1988488882780075,
0.024112720042467117,
-0.05478258058428764,
0.07490848004817963,
0.015539479441940784,
0.05218236893415451,
0.03461619094014168,
0.06404586136341095,
0.018138710409402847,
0.19708873331546783,
0.17624306678771973,
-0.04278828948736191,
-0.154348224401474,
-0.021052416414022446,
-0.2794322669506073,
0.17879757285118103,
-0.008359337225556374,
0.11986379325389862,
-0.1268564611673355,
0.037871893495321274,
-0.23507924377918243,
0.0028968178667128086,
-0.0863402783870697,
-0.05190429091453552,
0.05541776865720749,
0.00543129350990057,
-0.023668652400374413,
0.15287761390209198,
0.13709783554077148,
0.20476531982421875,
-0.0487593375146389,
0.012193934991955757,
-0.07930681854486465,
0.1648673564195633,
0.051104046404361725,
0.02957593835890293,
0.07084663212299347,
0.12891848385334015,
-0.016990788280963898,
-0.2427830696105957,
-0.011736532673239708,
-0.022418852895498276,
-0.13689281046390533,
-0.0013825849164277315,
-0.21752817928791046,
0.1317770928144455,
-0.06287607550621033,
-0.061442889273166656,
-0.0811508446931839,
0.09571166336536407,
0.10132642835378647,
0.0162770114839077,
-0.03808150067925453,
0.00015837261162232608,
0.0402861014008522,
-0.1028558760881424,
-0.10531554371118546,
0.04306234046816826,
0.14895254373550415,
0.0824551209807396,
-0.13035544753074646,
-0.014355354011058807,
0.018414195626974106,
0.07607357203960419,
0.07746485620737076,
-0.049382902681827545,
0.07497074455022812,
-0.08463262766599655,
-0.09665708243846893,
0.054311346262693405,
0.0371808223426342,
-0.033255331218242645,
0.10388050973415375,
0.054723650217056274,
0.0569649338722229,
-0.05687669664621353,
-0.049843914806842804,
-0.05000610277056694,
-0.09253983199596405,
0.09869556874036789,
-0.014610394835472107,
-0.03381931409239769,
-0.23860959708690643,
-0.04261936992406845,
-0.07669617235660553,
0.05112037807703018,
0.008460232987999916,
-0.04243912547826767,
-0.13307586312294006,
0.08202113211154938,
0.02035420387983322,
0.049710534512996674,
-0.12722520530223846,
0.04092121869325638,
-0.11449091136455536,
0.06741079688072205,
-0.05956871435046196,
-0.10071046650409698,
0.23611541092395782,
-0.11747753620147705,
-0.06711654365062714,
0.05001597851514816,
-0.0004607744631357491,
0.026372719556093216,
0.04431591182947159,
0.4017326235771179,
-0.11036475747823715,
-0.13162553310394287,
0.0709901675581932,
0.19989311695098877,
-0.1660463511943817,
-0.09470213204622269,
0.13887405395507812,
-0.16411903500556946,
-0.15765458345413208,
0.047148674726486206,
-0.03221829608082771,
0.13244767487049103,
-0.05283188819885254,
-0.058641064912080765,
0.03900634124875069,
-0.008719583973288536,
0.004720295779407024,
0.006151197943836451,
0.09074875712394714,
-0.049566738307476044,
0.0608414001762867,
-0.08672793954610825,
0.009903655387461185,
0.137020081281662,
-0.05136384814977646,
-0.056930094957351685,
0.04177753999829292,
0.04532494395971298,
0.00759313628077507,
-0.014326329343020916,
-0.11638158559799194,
0.017076486721634865,
-0.029707109555602074,
0.11008353531360626,
0.17215272784233093,
0.04094656556844711,
0.009484009817242622,
0.026899725198745728,
0.06012634187936783,
0.05053353309631348,
0.017436105757951736,
0.03529953584074974,
-0.06985928863286972,
0.09083253145217896,
-0.01925588957965374,
-0.014371025376021862,
-0.08802919089794159,
-0.022946996614336967,
0.17620158195495605,
-0.05343780666589737,
-0.03432536870241165,
0.00703984871506691,
-0.01919323392212391,
-0.018056627362966537,
0.03874822333455086,
-0.003933070693165064,
0.10187046229839325,
-0.021847933530807495,
-0.07071863114833832,
0.17464883625507355,
0.01170051284134388,
0.280329167842865,
0.12196532636880875,
-0.03523655980825424,
-0.0207778699696064,
-0.13703250885009766,
-0.041307784616947174,
0.0180890504270792,
0.04169600084424019,
0.03473615646362305,
0.08813917636871338,
-0.059023868292570114,
-0.0036130682565271854,
-0.011652974411845207,
0.006800753064453602,
-0.011547734029591084,
-0.042970526963472366,
-0.11366625130176544,
0.0723700299859047,
0.1692550629377365,
-0.1727157086133957,
0.1808074563741684,
0.30376964807510376,
0.207925945520401,
0.22116689383983612,
-0.12354481220245361,
-0.008339437656104565,
-0.06789418309926987,
0.040305979549884796,
-0.01828787848353386,
0.1746981292963028,
-0.11960001289844513,
-0.0017093814676627517,
0.0434332899749279,
0.017006823793053627,
0.06174436956644058,
-0.1708451211452484,
-0.173806294798851,
-0.013877293094992638,
-0.0572902150452137,
-0.11994562298059464,
0.10235270112752914,
-0.12415038049221039,
-0.002862074878066778,
0.015812695026397705,
-0.04051988571882248,
0.15664422512054443,
0.004043010529130697,
-0.03851764276623726,
0.0964646264910698,
-0.13567957282066345,
-0.14725999534130096,
-0.11847718805074692,
-0.12006006389856339,
0.0017712715780362487,
0.04444988816976547,
0.07353704422712326,
-0.0664912685751915,
-0.06110849231481552,
0.0959787368774414,
-0.054156698286533356,
-0.1644153594970703,
0.0004255145904608071,
-0.010358463041484356,
0.08730333298444748,
-0.10147397220134735,
-0.07209630310535431,
-0.0714225322008133,
-0.034551750868558884,
-0.07123490422964096,
0.0672914981842041,
-0.021150046959519386,
0.0766846239566803,
0.0790790393948555,
0.08403180539608002,
0.10705170780420303,
-0.05586308240890503,
0.19203230738639832,
-0.0831461250782013,
-0.15166102349758148,
0.06541042029857635,
0.0025085583329200745,
0.017986740916967392,
0.13642311096191406,
0.11150933802127838,
-0.12297306209802628,
-0.059162162244319916,
-0.05666736885905266,
-0.12409559637308121,
-0.1431649774312973,
-0.03875110298395157,
-0.060808319598436356,
0.12870259582996368,
-0.040503405034542084,
0.12747254967689514,
0.11530451476573944,
0.026162952184677124,
0.1064586415886879,
-0.045539017766714096,
0.0009773761266842484,
0.009370943531394005,
0.16740553081035614,
-0.05502437427639961,
-0.024779796600341797,
-0.1123647689819336,
-0.004709287546575069,
0.14779368042945862,
0.1247730627655983,
0.07946296036243439,
0.2667333483695984,
0.07306987047195435,
0.16145917773246765,
0.09411006420850754,
0.1378425657749176,
-0.03975855931639671,
0.013624911196529865,
-0.053862012922763824,
-0.04385434091091156,
-0.02451021783053875,
0.03478463739156723,
0.018845288082957268,
0.05268947035074234,
-0.25283318758010864,
0.05022969841957092,
-0.30606210231781006,
0.01675148494541645,
-0.1536426842212677,
0.044248901307582855,
0.08336745947599411,
0.07068635523319244,
0.0553569570183754,
0.050602518022060394,
-0.014362310990691185,
0.10349621623754501,
0.007920617237687111,
-0.1038089171051979,
0.002073726151138544,
0.05707991123199463,
0.039045996963977814,
0.07746882736682892,
0.08595159649848938,
-0.11737370491027832,
-0.11746356636285782,
0.03630317002534866,
0.14930908381938934,
-0.20555606484413147,
0.2752450406551361,
0.03566871955990791,
-0.08208291232585907,
-0.060893844813108444,
-0.04629513621330261,
0.007495981641113758,
0.12003673613071442,
0.1640256643295288,
0.047734927386045456,
-0.1636718064546585,
-0.11054249852895737,
0.029373232275247574,
0.02400711178779602,
0.08380864560604095,
-0.05081288143992424,
-0.15420782566070557,
-0.03561089560389519,
0.05233263969421387,
-0.016919976100325584,
0.09054641425609589,
-0.10054632276296616,
-0.14526037871837616,
0.032289762049913406,
0.0038042895030230284,
0.019397668540477753,
-0.0754971131682396,
0.060452401638031006,
-0.09803897142410278,
0.05884842947125435,
-0.10496555268764496,
0.03802559897303581,
-0.0989333987236023,
-0.09990286827087402,
0.010825848206877708,
-0.05395609140396118,
-0.01177919376641512,
-0.0863160714507103,
-0.136220321059227,
-0.12202873080968857,
-0.17823442816734314,
0.09259717911481857,
-0.04322099685668945,
0.018780533224344254,
-0.03741255775094032,
0.11696173995733261,
-0.04411688819527626,
0.013500282540917397,
-0.01961599849164486,
0.003633953630924225,
-0.00252980412915349,
-0.1722572296857834,
0.1214660033583641,
-0.1300552785396576,
0.02962683141231537,
0.0387859120965004,
0.004418859723955393,
0.04458159580826759,
0.0760180726647377,
-0.1503572165966034,
0.14990133047103882,
0.36869800090789795,
-0.022152086719870567,
0.25915512442588806,
0.3015614151954651,
-0.10700029134750366,
-0.19661566615104675,
-0.157291442155838,
-0.24609506130218506,
-0.08220653235912323,
0.17097190022468567,
-0.22228482365608215,
0.028470521792769432,
0.19982631504535675,
-0.11045118421316147,
0.312420517206192,
-0.22749821841716766,
-0.011291366070508957,
0.1327848732471466,
-0.0323665626347065,
0.4960802495479584,
-0.12470163404941559,
-0.13243889808654785,
0.055538080632686615,
-0.2096228301525116,
0.14421285688877106,
0.03143521398305893,
0.09708862751722336,
0.007189074065536261,
-0.05461630970239639,
-0.008974945172667503,
-0.034533172845840454,
0.21353097259998322,
-0.03306026756763458,
0.08593323081731796,
-0.08824195712804794,
-0.10901951789855957,
0.20765957236289978,
0.06144010275602341,
-0.0390445813536644,
-0.057282160967588425,
-0.04017835855484009,
-0.003639906644821167,
-0.013522764667868614,
-0.039224181324243546,
0.10339038074016571,
0.04469681158661842,
-0.10329683870077133,
-0.09871399402618408,
0.039328206330537796,
-0.14950338006019592,
-0.02720668353140354,
0.21246102452278137,
-0.03417665883898735,
0.0940234512090683,
-0.02277623862028122,
-0.059586357325315475,
-0.1681186705827713,
-0.012412729673087597,
-0.12649782001972198,
-0.052329689264297485,
0.041062962263822556,
-0.09535970538854599,
-0.03919892758131027,
0.10066425800323486,
-0.008734060451388359,
0.10091360658407211,
0.09755267202854156,
-0.07603789120912552,
0.05827255919575691,
0.1500721275806427,
-0.1204209104180336,
-0.22255448997020721,
-0.006342706270515919,
-0.07704376429319382,
0.2278909981250763,
0.001249095075763762,
0.0026227720081806183,
0.09534045308828354,
0.011155654676258564,
0.015511450357735157,
-0.016088025644421577,
-0.11261533200740814,
-0.0648309737443924,
0.013643793761730194,
-0.03600359708070755,
-0.11108417809009552,
0.12356878817081451,
0.06297626346349716,
0.0462312176823616,
-0.052626729011535645,
0.07573143392801285,
-0.05773498862981796,
-0.07696305215358734,
-0.25197702646255493,
0.05752129480242729,
-0.17979930341243744,
-0.04953151196241379,
0.06076458841562271,
-0.04063965380191803,
-0.03002467192709446,
0.08162586390972137,
0.020177006721496582,
0.16746297478675842,
0.013570504263043404,
0.0263554397970438,
0.15255732834339142,
-0.0746016725897789,
-0.2136504203081131,
0.003952421247959137,
-0.08720260113477707,
-0.05998463183641434,
-0.008728348650038242,
0.10650327056646347,
-0.06286515295505524,
-0.11074919998645782,
-0.2350994050502777,
0.05503427982330322,
-0.08024920523166656,
-0.06046639010310173,
-0.08042675256729126,
-0.0203123576939106,
0.08146075904369354,
-0.07456455379724503,
0.015918781980872154,
-0.009469340555369854,
-0.16577067971229553,
0.04455071687698364,
0.09140848368406296,
0.10072939097881317,
-0.054288674145936966,
-0.016181273385882378,
0.12617537379264832,
0.07629241049289703,
0.15032875537872314,
0.1041000708937645,
0.08961451053619385,
0.17898936569690704,
-0.259509414434433,
-0.022952144965529442,
0.09653044492006302,
-0.03759537264704704,
-0.015558628365397453,
0.12960101664066315,
-0.010128485038876534,
0.012862449511885643,
-0.0474281832575798,
0.0732109472155571,
-0.09790993481874466,
-0.13646139204502106,
-0.09241211414337158,
0.05681770294904709,
-0.1457071602344513,
0.0383298359811306,
-0.14987115561962128,
0.1547280251979828,
0.012495440430939198,
0.042524002492427826,
0.0552576407790184,
-0.013549959287047386,
0.0239860899746418,
-0.012850327417254448,
-0.008016789332032204,
-0.11221142113208771,
-0.017056912183761597,
-0.07532713562250137,
-0.09230168163776398,
-0.005918577313423157,
0.42094191908836365,
0.008515188470482826,
-0.14552606642246246,
0.0016086995601654053,
0.10093127191066742,
0.1419597864151001,
-0.01497360598295927,
0.23296737670898438,
0.07300929725170135,
-0.006262333132326603,
-0.1512821614742279,
0.0850784033536911,
-0.09492291510105133,
-0.2781663239002228,
0.019712844863533974,
-0.018073130398988724,
-0.03813077136874199,
-0.030870795249938965,
0.10086806118488312,
-0.10356926918029785,
0.012786483392119408,
-0.08364287763834,
0.06606979668140411,
-0.04137106612324715,
-0.05532634258270264,
0.01133950799703598,
0.1770588755607605,
-0.010892098769545555,
0.0675579383969307,
-0.016579624265432358,
0.01003966759890318,
-0.125335693359375,
-0.18584518134593964,
0.050541408360004425,
-0.04510089010000229,
0.1133074015378952,
0.0263381265103817,
0.09308065474033356,
0.1739671528339386,
0.05835092067718506,
-0.026027822867035866,
-0.02574620582163334,
-0.04304280877113342,
-0.06649071723222733,
-0.046312104910612106,
-0.03690152242779732,
0.0049730101600289345,
-0.14115925133228302,
-0.06736520677804947,
-0.06653659790754318,
-0.1447371542453766,
-0.0516405925154686,
0.007244284264743328,
-0.00044751277891919017,
-0.09227447211742401,
-0.15173721313476562,
-0.004440557211637497,
-0.05165013670921326,
0.09725359082221985,
-0.05296783894300461,
0.1458471119403839,
-0.0038076601922512054,
0.020168034359812737,
0.061291180551052094,
0.0994514673948288,
0.051403678953647614,
-0.05351099371910095,
0.01782672479748726,
0.10832910239696503,
-0.04533472657203674,
0.14927537739276886,
-0.07987771928310394,
0.018611501902341843,
0.03343478590250015,
0.16792631149291992,
0.2514605224132538,
-0.05921171233057976,
0.01660630851984024,
0.024549836292862892,
0.009084249846637249,
0.1428922563791275,
0.14046522974967957,
-0.037003763020038605,
0.28605955839157104,
-0.10683460533618927,
0.017663540318608284,
0.019125524908304214,
0.061227329075336456,
-0.10314376652240753,
0.0965065136551857,
0.03534840792417526,
-0.049024373292922974,
-0.07821030914783478,
0.1190011277794838,
-0.17773878574371338,
0.14023908972740173,
0.06587310880422592,
-0.11146829277276993,
0.01650065742433071,
-0.029415199533104897,
0.032449960708618164,
-0.008791141211986542,
0.07037851959466934,
-0.10150372982025146,
-0.08109822124242783,
-0.11457161605358124,
0.045897550880908966,
-0.36754530668258667,
-0.14420150220394135,
0.05234571173787117,
0.16850221157073975,
0.19665957987308502,
-0.03589048981666565,
0.057210274040699005,
0.022655168548226357,
0.06664685159921646,
-0.03933526203036308,
0.08553989231586456,
0.01381595153361559,
-0.018895668908953667,
-0.18651318550109863,
-0.17101770639419556,
0.05743609741330147,
-0.11223907768726349,
0.004588886629790068,
0.05345524102449417,
0.04061000421643257,
0.11923589557409286,
-0.05329148843884468,
0.011142456904053688,
0.032813675701618195,
-0.12949611246585846,
0.038910724222660065,
-0.05420905351638794,
0.04705159738659859,
-0.06694597750902176,
-0.05555694177746773,
0.026871394366025925,
0.12549877166748047,
-0.11961650848388672,
-0.08714471757411957,
0.16611872613430023,
-0.004710242617875338,
0.20622527599334717,
-0.040874190628528595,
-0.05218576267361641,
-0.013945507816970348,
-0.045050252228975296,
0.12845155596733093,
-0.04587571695446968,
0.04430215805768967,
0.18890777230262756,
0.022499820217490196,
0.0353832021355629,
-0.3115916848182678,
0.055461347103118896,
-0.07641594856977463,
-0.003848337335512042,
-0.022229772061109543
] |
null | null | transformers |
## MiquMaid v2
Check out our blogpost about this model series [Here!](https://ikaridevgit.github.io/index.html?blog=blogid-6&bo=true#Miqu-base) - Join our Discord server [Here!](https://discord.gg/Bb8pRUXy3Z)
<center>[<a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B">V2-70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B-DPO">V2-70B-DPO</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B">V2-2x70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B-DPO">V2-2x70B-DPO</a>]
</br>
<div style="width: 100%;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/1ziZ_5Rl7bsQKFrgH6ZCf.png" style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca **prompting format**
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: [FP16](https://huggingface.co/NeverSleep/MiquMaid-v2-70B) - [GGUF](https://huggingface.co/NeverSleep/MiquMaid-v2-70B-GGUF)
## Training data used:
- [Aesir datasets](https://huggingface.co/MinervaAI)
- [NoRobots](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt)
- [limarp](https://huggingface.co/datasets/lemonilia/LimaRP)
- [toxic-dpo-v0.1-sharegpt](https://huggingface.co/datasets/Undi95/toxic-dpo-v0.1-sharegpt)
- [ToxicQAFinal](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAFinal)
### Custom format:
```
### Instruction:
{system prompt}
### Input:
{input}
### Response:
{reply}
```
## Others
Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).
IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | text-generation | LoneStriker/MiquMaid-v2-70B-5.0bpw-h6-exl2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T02:08:31+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## MiquMaid v2
Check out our blogpost about this model series Here! - Join our Discord server Here!
<center>[<a href="URL - <a href="URL - <a href="URL - <a href="URL
</br>
<div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: FP16 - GGUF
## Training data used:
- Aesir datasets
- NoRobots
- limarp
- toxic-dpo-v0.1-sharegpt
- ToxicQAFinal
### Custom format:
## Others
Undi: If you want to support us, you can here.
IkariDev: Visit my retro/neocities style website please kek | [
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
75,
121,
11,
30,
40,
5,
32
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.## Credits:\n- Undi\n- IkariDev## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal### Custom format:## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
-0.09447834640741348,
0.17205014824867249,
-0.005602731369435787,
0.01779203675687313,
0.11820747703313828,
0.045264896005392075,
0.11447285860776901,
0.15961068868637085,
0.06829394400119781,
0.05906902998685837,
0.0005873226327821612,
0.11407624930143356,
0.07548845559358597,
0.22948826849460602,
-0.006628913804888725,
-0.14427904784679413,
0.046850357204675674,
-0.026289891451597214,
-0.02635573409497738,
0.09569915384054184,
0.07466454803943634,
-0.04618130251765251,
0.0709284171462059,
0.010442404076457024,
-0.10720876604318619,
-0.017348533496260643,
0.0019323929445818067,
-0.05718233436346054,
0.04780259355902672,
0.04367207735776901,
0.0479082316160202,
0.05087536945939064,
0.00845402292907238,
-0.22662657499313354,
0.047140758484601974,
0.07308577746152878,
-0.025127466768026352,
0.07861552387475967,
0.10886233299970627,
-0.04211974889039993,
0.02646409347653389,
-0.03574787452816963,
-0.02210289053618908,
0.09350186586380005,
-0.11214648932218552,
-0.12319593131542206,
-0.11320719122886658,
0.13006889820098877,
0.06314875930547714,
0.08198896050453186,
0.0033554788678884506,
0.1101357564330101,
-0.07631256431341171,
0.07790177315473557,
0.20335930585861206,
-0.16871041059494019,
-0.02322721853852272,
0.05624805763363838,
-0.015333202667534351,
-0.05565005913376808,
-0.09832000732421875,
0.011083890683948994,
0.010926350019872189,
-0.019533375278115273,
-0.0038207839243113995,
-0.041167840361595154,
0.004284780006855726,
-0.06099749729037285,
-0.059463758021593094,
-0.016264086589217186,
0.24300093948841095,
0.0361378937959671,
-0.07370094209909439,
-0.0026136080268770456,
-0.006493517197668552,
0.11463554203510284,
-0.05098545923829079,
0.030949248000979424,
0.005614427383989096,
-0.0010702924337238073,
-0.0032837465405464172,
-0.04595240205526352,
-0.10275456309318542,
-0.05733378976583481,
-0.014142698608338833,
0.14566513895988464,
0.017552156001329422,
0.00008401479135500267,
-0.004768410697579384,
0.051651932299137115,
-0.10471507161855698,
-0.12298901379108429,
-0.06133059412240982,
-0.10231878608465195,
-0.005009785760194063,
-0.042668018490076065,
-0.022182224318385124,
-0.06640303134918213,
0.12371482700109482,
0.1403876692056656,
-0.04801563546061516,
-0.0030525391921401024,
-0.025033647194504738,
0.00783479306846857,
0.005412905476987362,
-0.00017629309149924666,
-0.07161558419466019,
-0.023959118872880936,
0.07290422171354294,
0.025751972571015358,
0.004980665165930986,
0.010289043188095093,
-0.044097792357206345,
-0.07064660638570786,
-0.04732796177268028,
0.05287690833210945,
0.07054515182971954,
0.06856327503919601,
-0.07649759203195572,
-0.047711774706840515,
0.22618921101093292,
-0.10658138245344162,
0.029063958674669266,
0.05863291397690773,
-0.007088409271091223,
0.10424129664897919,
0.06771936267614365,
-0.0006956448778510094,
-0.06505299359560013,
0.016184480860829353,
-0.041465580463409424,
0.03125211223959923,
-0.08675958216190338,
-0.05394180864095688,
0.0855826810002327,
0.0812700167298317,
-0.03331775963306427,
-0.1366315633058548,
-0.10328203439712524,
-0.01740688644349575,
0.02815520204603672,
-0.023310357704758644,
0.0012498353607952595,
0.04892998933792114,
-0.05491432547569275,
0.01405452098697424,
0.01705477572977543,
0.00629244651645422,
-0.05887370929121971,
0.07736124843358994,
0.022486159577965736,
0.09428157657384872,
0.019443463534116745,
0.025946028530597687,
-0.035123471170663834,
0.002149750478565693,
-0.23019294440746307,
0.05012257769703865,
-0.10595361143350601,
0.0038321600295603275,
-0.0922209694981575,
0.0014835012843832374,
-0.027800843119621277,
-0.009975400753319263,
0.0055687217973172665,
0.20525269210338593,
-0.14585432410240173,
-0.05596565082669258,
0.304247111082077,
-0.15955102443695068,
-0.09778694808483124,
0.09222670644521713,
0.03642375022172928,
-0.07440096139907837,
0.06239297613501549,
0.08249494433403015,
0.1056317463517189,
-0.16265460848808289,
-0.09710903465747833,
-0.011078423820436,
-0.022652560845017433,
-0.024000728502869606,
0.0878278836607933,
-0.018813995644450188,
0.03245491161942482,
0.019763432443141937,
-0.03379102423787117,
0.07007033377885818,
-0.025310136377811432,
-0.022386055439710617,
-0.03589578717947006,
-0.06099054589867592,
0.05183964595198631,
-0.002879094798117876,
-0.0388391874730587,
-0.006428318098187447,
-0.04584600031375885,
-0.06035709008574486,
0.13202428817749023,
-0.004858740605413914,
-0.020473629236221313,
-0.07851582020521164,
0.09554000943899155,
-0.05498090013861656,
0.03728895261883736,
-0.13830018043518066,
-0.06243045628070831,
0.0036350893788039684,
-0.0796012431383133,
0.02157106250524521,
-0.0041148848831653595,
0.05950147658586502,
0.038105957210063934,
-0.04352330043911934,
-0.028907326981425285,
-0.0057363444939255714,
0.004301073960959911,
-0.025426069274544716,
-0.1666073054075241,
-0.0007695230888202786,
-0.0551750548183918,
0.1374220848083496,
-0.16868118941783905,
0.05043652653694153,
0.05925111472606659,
0.16357283294200897,
0.03616755083203316,
-0.031011521816253662,
0.11654403805732727,
-0.03804580122232437,
-0.006411012262105942,
-0.03725241497159004,
0.0044607375748455524,
0.002538213739171624,
-0.011939228512346745,
0.10659566521644592,
-0.06065728887915611,
0.054277852177619934,
0.12642189860343933,
-0.01595868356525898,
-0.05425528809428215,
-0.06506265699863434,
-0.01521784346550703,
-0.006736948620527983,
-0.048000186681747437,
-0.047349583357572556,
0.02513136900961399,
0.0662446990609169,
0.07768423110246658,
-0.03797391429543495,
-0.008253731764853,
0.0011901968391612172,
-0.0948609709739685,
-0.0020795518066734076,
0.0409865640103817,
0.05132393538951874,
-0.14333368837833405,
0.09081240743398666,
0.09744595736265182,
-0.015339801087975502,
0.14312495291233063,
0.008754834532737732,
-0.1070873811841011,
-0.003728162497282028,
0.027940761297941208,
0.05264529958367348,
0.0774049460887909,
-0.03596934303641319,
0.02683958038687706,
0.08106063306331635,
-0.05121877044439316,
0.007932554930448532,
-0.09500398486852646,
-0.022678673267364502,
-0.013256699778139591,
-0.0758146122097969,
-0.04612674191594124,
0.03610261529684067,
0.030104612931609154,
0.0918031707406044,
-0.015134556218981743,
0.07633049786090851,
-0.0010367896175011992,
-0.02394755184650421,
-0.09206201136112213,
0.1670486181974411,
-0.0899675041437149,
-0.27366867661476135,
-0.1188458725810051,
-0.07167717814445496,
-0.04199657961726189,
0.004022621084004641,
0.02857130952179432,
-0.12134306877851486,
-0.07081691175699234,
-0.03115151636302471,
-0.0038425917737185955,
0.06778023391962051,
-0.03805195540189743,
-0.02431504614651203,
0.05526971071958542,
0.09138014912605286,
-0.07273191213607788,
-0.002759605646133423,
0.06194623187184334,
-0.037675220519304276,
0.08085193485021591,
0.008549315854907036,
0.10605848580598831,
0.04739413037896156,
0.03012051060795784,
0.0015264216344803572,
0.04311876371502876,
0.17313145101070404,
-0.10127022117376328,
0.09718520194292068,
0.20746180415153503,
0.0394415408372879,
0.08480402082204819,
0.15171074867248535,
0.05122246593236923,
-0.013119645416736603,
-0.005120322108268738,
0.04244927689433098,
0.011746162548661232,
-0.2427690476179123,
-0.061469703912734985,
-0.05656198412179947,
-0.054776955395936966,
0.022767482325434685,
0.047591015696525574,
0.0650729089975357,
0.1047578752040863,
-0.10416096448898315,
-0.016062086448073387,
0.022997045889496803,
0.09911724179983139,
0.047439564019441605,
0.022038234397768974,
0.061993930488824844,
-0.04141371324658394,
0.015599393285810947,
0.12155410647392273,
0.06473620980978012,
0.11147889494895935,
-0.023897795006632805,
0.08020832389593124,
0.06728237122297287,
0.0892438217997551,
0.0530114471912384,
0.06319621205329895,
0.04218849167227745,
-0.014131366275250912,
-0.0013301256112754345,
-0.08454640209674835,
-0.04801497980952263,
0.023290416225790977,
0.013235284946858883,
-0.057533953338861465,
-0.0392376184463501,
-0.01914895512163639,
0.07390332221984863,
0.1574147492647171,
0.04597143456339836,
-0.20930512249469757,
-0.05056460201740265,
0.033859558403491974,
-0.0003397460968699306,
-0.06584210693836212,
-0.033550359308719635,
0.05652978643774986,
-0.12203755974769592,
0.1039382740855217,
-0.02658943273127079,
0.09946075826883316,
-0.07054278254508972,
0.000789299956522882,
0.00494906771928072,
0.12713035941123962,
-0.023788869380950928,
0.09413742274045944,
-0.24859566986560822,
0.14139194786548615,
0.04770104959607124,
0.06752338260412216,
-0.05309014022350311,
0.028258029371500015,
0.0961327999830246,
0.12656870484352112,
0.10434279590845108,
0.020785793662071228,
0.06395822018384933,
-0.15350443124771118,
-0.11799371987581253,
0.006164612248539925,
0.02960512787103653,
-0.04779611900448799,
0.07287964969873428,
-0.0005067483871243894,
-0.06341438740491867,
-0.04712821915745735,
0.03289221227169037,
-0.19348879158496857,
-0.12983499467372894,
0.07045576721429825,
0.052490055561065674,
0.090853750705719,
-0.06709475815296173,
-0.03205195814371109,
-0.043046124279499054,
0.18290454149246216,
-0.03442198783159256,
-0.08606650680303574,
-0.1285882145166397,
-0.0006686998531222343,
0.09258218854665756,
-0.08165017515420914,
-0.005991893354803324,
-0.052048277109861374,
0.1894829422235489,
-0.035209737718105316,
-0.08786994218826294,
0.01570327952504158,
-0.15995244681835175,
-0.1281605362892151,
-0.0414857491850853,
0.12103712558746338,
-0.021659180521965027,
0.02213156595826149,
0.05526252090930939,
-0.020805859938263893,
0.008410685695707798,
-0.1123393177986145,
0.02350648306310177,
0.09350050985813141,
0.08948540687561035,
0.08400450646877289,
-0.11930029839277267,
-0.11843101680278778,
-0.10216961801052094,
-0.022528614848852158,
0.06181072071194649,
0.24282413721084595,
-0.02235415205359459,
0.037382837384939194,
0.13085247576236725,
-0.04928212612867355,
-0.19814851880073547,
-0.06996271014213562,
-0.00017375701281707734,
-0.037472743541002274,
0.02159503661096096,
-0.21408295631408691,
0.08694717288017273,
0.09358245879411697,
-0.030445247888565063,
0.09161640703678131,
-0.07194696366786957,
-0.06843597441911697,
0.04065357893705368,
0.07071772962808609,
0.0037067674566060305,
-0.1683196723461151,
-0.07113704830408096,
-0.06764888018369675,
-0.12663458287715912,
0.08166584372520447,
-0.1314810812473297,
0.08971400558948517,
-0.005421672947704792,
0.0671011433005333,
0.025563575327396393,
-0.06707208603620529,
0.11356908828020096,
-0.020757906138896942,
0.009567689150571823,
-0.07924797385931015,
0.012899143621325493,
0.022010432556271553,
-0.050428662449121475,
0.09034649282693863,
-0.02925287000834942,
0.01692429557442665,
-0.091850645840168,
-0.0007856881711632013,
-0.10224597156047821,
0.0437864288687706,
-0.038862090557813644,
-0.017533548176288605,
-0.008498632349073887,
0.07837546616792679,
0.03536466881632805,
0.010669435374438763,
-0.009266866371035576,
-0.04946504905819893,
0.10181041061878204,
0.17810481786727905,
0.10491631180047989,
0.0006870499346405268,
-0.07857012748718262,
-0.036821771413087845,
-0.053213875740766525,
0.050082918256521225,
-0.08183137327432632,
0.06681650131940842,
0.029605142772197723,
0.010572184808552265,
0.12429390102624893,
-0.0033586653880774975,
-0.12030913680791855,
-0.003338087350130081,
0.10895328968763351,
-0.12868796288967133,
-0.07275929301977158,
-0.020934229716658592,
0.05516009032726288,
-0.10196569561958313,
0.0011667415965348482,
0.1428048461675644,
-0.028892088681459427,
-0.028331711888313293,
0.014776935800909996,
0.07020314782857895,
-0.012796786613762379,
0.10238455981016159,
0.07413777709007263,
0.049551427364349365,
-0.12031137198209763,
0.05704139545559883,
0.03181569650769234,
-0.03592713922262192,
-0.0024339298252016306,
0.05667674541473389,
-0.10612429678440094,
-0.1119871735572815,
0.03397342190146446,
0.06045559421181679,
-0.015471268445253372,
-0.06184658035635948,
-0.020792635157704353,
-0.04714902117848396,
0.02126099169254303,
0.07590576261281967,
0.00995138380676508,
-0.008162305690348148,
0.08148860931396484,
-0.017391547560691833,
-0.08959554880857468,
0.06402577459812164,
0.010443227365612984,
0.03571965917944908,
-0.13038720190525055,
0.07408680766820908,
-0.015041174367070198,
0.006071531679481268,
-0.022530831396579742,
0.003641687100753188,
-0.10074226558208466,
-0.04254826903343201,
-0.07885435223579407,
0.06230726093053818,
-0.1484614759683609,
-0.020241795107722282,
-0.026183132082223892,
-0.022612975910305977,
0.015071062371134758,
0.019551774486899376,
-0.07782812416553497,
-0.04559153690934181,
-0.010346274822950363,
0.08449862152338028,
-0.16007104516029358,
-0.008523115888237953,
0.03327300027012825,
-0.06084582209587097,
0.0670776516199112,
0.08543620258569717,
-0.010745981708168983,
-0.011400423012673855,
-0.24030931293964386,
-0.05429427698254585,
0.060920946300029755,
0.04178236424922943,
0.015297153033316135,
-0.10723429918289185,
0.0352109931409359,
-0.01898287609219551,
-0.023456763476133347,
0.005050045438110828,
0.031953055411577225,
-0.08434974402189255,
0.024241402745246887,
-0.019039491191506386,
-0.04014326632022858,
-0.051917847245931625,
0.04262912645936012,
0.17145587503910065,
-0.014532416127622128,
0.1174297034740448,
-0.080752432346344,
0.054420918226242065,
-0.13401885330677032,
0.029829595237970352,
-0.001078542205505073,
-0.039962440729141235,
-0.02863360196352005,
-0.010570892132818699,
0.06349045038223267,
-0.010899520479142666,
0.09258676320314407,
-0.0552545003592968,
0.06722300499677658,
0.0190583486109972,
-0.09725376963615417,
0.007986992597579956,
-0.026470135897397995,
0.03294571489095688,
0.0396236926317215,
-0.006473933346569538,
0.009316735900938511,
0.00238132756203413,
0.02042953483760357,
-0.0582701601088047,
0.07976511865854263,
0.16147081553936005,
0.02053176984190941,
0.022807525470852852,
0.054943084716796875,
-0.07234697043895721,
-0.036924149841070175,
-0.04578930139541626,
-0.077462337911129,
0.06634023785591125,
-0.021255100145936012,
0.07374273985624313,
0.15307408571243286,
-0.12218204140663147,
0.038187239319086075,
-0.005237263161689043,
-0.03132057934999466,
-0.08196348696947098,
-0.1581864356994629,
-0.06715912371873856,
-0.08088500797748566,
0.011959434486925602,
-0.11438815295696259,
0.06888450682163239,
0.04325690120458603,
0.019395047798752785,
-0.017880942672491074,
0.13543029129505157,
0.03472369909286499,
-0.07543140649795532,
0.060917001217603683,
-0.02095349319279194,
-0.031358812004327774,
0.04272241145372391,
0.0006400952115654945,
0.06196298450231552,
-0.010582057759165764,
0.044258568435907364,
0.0559408999979496,
0.02938593178987503,
0.05811672285199165,
-0.06726688146591187,
-0.12517108023166656,
0.006359596271067858,
0.005888449959456921,
0.04039566218852997,
0.15003027021884918,
0.05136363208293915,
0.007397872861474752,
0.014586303383111954,
0.16361239552497864,
-0.038274187594652176,
-0.0431714691221714,
-0.15419889986515045,
0.011273895390331745,
-0.02001452073454857,
-0.009176031686365604,
-0.03663250058889389,
-0.10866829752922058,
-0.028140606358647346,
0.20135445892810822,
0.08363344520330429,
-0.049736183136701584,
0.026926010847091675,
-0.006478144787251949,
0.0070541067980229855,
0.006099193822592497,
0.08733457326889038,
0.05982113629579544,
0.11233042925596237,
-0.03476639464497566,
0.04225286468863487,
0.008952682837843895,
-0.042931120842695236,
-0.100910983979702,
0.05160531401634216,
-0.04183126986026764,
-0.029043002054095268,
-0.0207699965685606,
0.12725666165351868,
-0.06002918258309364,
-0.12053494155406952,
-0.05984590947628021,
-0.05843505263328552,
-0.09186802059412003,
-0.04533113166689873,
-0.021347900852560997,
0.08330697566270828,
0.03736959397792816,
-0.008225626312196255,
-0.006564581301063299,
0.18599693477153778,
-0.004363450221717358,
-0.06833065301179886,
-0.047022756189107895,
0.03228268772363663,
-0.009685746394097805,
0.13331912457942963,
0.02237250655889511,
0.06835850328207016,
0.08902639895677567,
-0.04617135971784592,
-0.13351397216320038,
0.05768809840083122,
0.01893182285130024,
-0.16012974083423615,
0.03900958225131035,
0.1735668033361435,
-0.019399257376790047,
0.004258662927895784,
0.07070906460285187,
-0.07974739372730255,
0.021498262882232666,
0.05192280188202858,
-0.017278648912906647,
-0.07030515372753143,
0.08999960869550705,
-0.09391003847122192,
0.11678098142147064,
0.17506007850170135,
-0.024389326572418213,
-0.013276796787977219,
-0.03903545066714287,
0.05904215946793556,
0.06406354159116745,
-0.016790268942713737,
-0.07218509912490845,
-0.10399819910526276,
0.01415897998958826,
-0.01502299215644598,
0.07969480007886887,
-0.13121938705444336,
-0.019862104207277298,
-0.05875250697135925,
-0.03522523120045662,
-0.09029058367013931,
0.07942423224449158,
0.06178797036409378,
0.053517896682024,
-0.021183528006076813,
-0.09516715258359909,
0.007413235958665609,
0.11255256831645966,
-0.14081521332263947,
-0.0646120086312294
] |
null | null | null |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` | {"license": "other", "tags": ["autotrain", "text-generation"], "widget": [{"text": "I love AutoTrain because "}]} | text-generation | TuringsSolutions/BatPhi | [
"safetensors",
"autotrain",
"text-generation",
"license:other",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:11:50+00:00 | [] | [] | TAGS
#safetensors #autotrain #text-generation #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
"TAGS\n#safetensors #autotrain #text-generation #license-other #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
33,
29,
3
] | [
"passage: TAGS\n#safetensors #autotrain #text-generation #license-other #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.# Usage"
] | [
-0.03320549428462982,
0.03780708089470863,
-0.0005784488166682422,
0.037439193576574326,
0.13256101310253143,
-0.02594633586704731,
0.22870999574661255,
0.04971681907773018,
-0.04270017519593239,
-0.08776232600212097,
0.19642603397369385,
0.16802352666854858,
-0.04566871374845505,
0.18935616314411163,
-0.02990073338150978,
-0.2414124757051468,
0.021885043010115623,
-0.025850016623735428,
0.1327640414237976,
0.11522045731544495,
0.14238014817237854,
-0.07779128849506378,
0.06120644509792328,
0.04086628183722496,
-0.20404933393001556,
0.03463415056467056,
0.07968573272228241,
-0.11895040422677994,
0.18004877865314484,
0.032886918634176254,
0.13635416328907013,
0.01931498385965824,
0.14652439951896667,
-0.12186150997877121,
0.014377960003912449,
0.01464270893484354,
-0.015491045080125332,
0.055415596812963486,
0.08804452419281006,
-0.038794226944446564,
0.09763352572917938,
0.177653506398201,
0.10883878171443939,
0.04911845549941063,
-0.10558086633682251,
-0.014727416448295116,
-0.03310466557741165,
0.018835384398698807,
0.12075160443782806,
0.1193094402551651,
-0.01845790445804596,
0.20021599531173706,
-0.14986595511436462,
0.07329507917165756,
-0.0995626449584961,
-0.27255508303642273,
-0.0038277229759842157,
0.21143054962158203,
0.07346842437982559,
-0.025004452094435692,
-0.12620827555656433,
0.06475763022899628,
0.12761425971984863,
0.0030757547356188297,
0.06504988670349121,
-0.015198786742985249,
-0.055105701088905334,
-0.0015243350062519312,
-0.07397002726793289,
-0.004598719999194145,
0.18640007078647614,
-0.07974611967802048,
-0.031184203922748566,
-0.12737500667572021,
-0.019428882747888565,
0.04709514603018761,
0.011552144773304462,
-0.09352482110261917,
-0.0217994824051857,
0.11079124361276627,
-0.007622338831424713,
-0.02531961165368557,
-0.15207529067993164,
-0.05755603685975075,
-0.08864409476518631,
0.04077286645770073,
0.0017509139142930508,
0.011538662947714329,
-0.09947098046541214,
0.12073534727096558,
-0.029350996017456055,
-0.0943499282002449,
0.052897434681653976,
-0.1107030138373375,
0.04635190963745117,
-0.11982002854347229,
-0.03970254212617874,
-0.10856737196445465,
0.013430505990982056,
0.22841021418571472,
0.1669083684682846,
-0.015314205549657345,
-0.08587565273046494,
0.039016176015138626,
0.02371702343225479,
0.09614221751689911,
0.06376225501298904,
-0.015822242945432663,
0.06775996834039688,
-0.04785482585430145,
-0.017039362341165543,
-0.025495992973446846,
-0.1726902425289154,
0.032083623111248016,
0.01997307874262333,
0.07117509841918945,
-0.0760226845741272,
0.06040170043706894,
-0.01951628364622593,
0.055283352732658386,
0.05161101743578911,
-0.031190861016511917,
0.03744623437523842,
-0.052504897117614746,
0.01617865450680256,
-0.09791388362646103,
0.0286922138184309,
0.1180110052227974,
0.03286140412092209,
0.1336720734834671,
-0.09649777412414551,
-0.026225421577692032,
-0.1056324690580368,
-0.03878350928425789,
0.018166208639740944,
-0.0019215025240555406,
0.0628642737865448,
-0.19663763046264648,
-0.30395275354385376,
-0.027070891112089157,
0.053043100982904434,
-0.019671862944960594,
-0.05561401695013046,
-0.07015043497085571,
0.016289202496409416,
0.059536442160606384,
-0.02920805849134922,
0.054385289549827576,
-0.022419849410653114,
0.03813159465789795,
-0.07676586508750916,
-0.02052054926753044,
-0.06291672587394714,
0.006658008787781,
-0.14841435849666595,
-0.03448035567998886,
-0.030017102137207985,
0.006548900622874498,
-0.03775618225336075,
0.16895608603954315,
-0.011088937520980835,
0.047757651656866074,
-0.05747115612030029,
0.05074193328619003,
0.007877329364418983,
0.1440490484237671,
-0.1335235834121704,
0.005429679993540049,
0.1511751264333725,
-0.11302075535058975,
-0.10663392394781113,
0.09467647224664688,
-0.10317569971084595,
0.23649843037128448,
0.10416192561388016,
0.13955152034759521,
0.05125761032104492,
-0.12630151212215424,
0.11601320654153824,
0.03282208740711212,
-0.08780468255281448,
-0.062369491904973984,
-0.0006791196065023541,
-0.034443121403455734,
-0.22099432349205017,
0.031658004969358444,
0.11068084836006165,
0.07476310431957245,
-0.03403317928314209,
-0.08304393291473389,
-0.02895026095211506,
-0.058612581342458725,
0.03986813873052597,
0.016017582267522812,
0.12599535286426544,
-0.07699156552553177,
-0.02858225256204605,
0.032077912241220474,
0.038467586040496826,
0.07923582941293716,
-0.054815541952848434,
-0.057291675359010696,
-0.01996961608529091,
-0.023569827899336815,
-0.00915558822453022,
-0.0898597314953804,
-0.0620407834649086,
-0.006840218789875507,
0.1304454207420349,
0.03466487303376198,
0.07167287915945053,
0.0362425372004509,
0.052633073180913925,
-0.028641145676374435,
0.002677651820704341,
0.1629824936389923,
0.04459667578339577,
-0.12675853073596954,
-0.08582112193107605,
0.10815013945102692,
-0.07446087151765823,
0.1071702167391777,
-0.2590586841106415,
0.028333326801657677,
-0.11371348798274994,
0.08611167222261429,
-0.013308924622833729,
0.06491301208734512,
-0.08320876955986023,
0.024355897679924965,
-0.08930765837430954,
-0.008432179689407349,
0.05678462237119675,
0.04953930526971817,
-0.02282531000673771,
0.12372811883687973,
-0.1432238668203354,
0.21934939920902252,
0.1198250874876976,
-0.09310522675514221,
-0.11077594012022018,
-0.0739443302154541,
0.009118417277932167,
-0.005148864816874266,
-0.1179550290107727,
0.005491754971444607,
0.076014444231987,
-0.04686584323644638,
0.1847466230392456,
-0.034107014536857605,
-0.03428659960627556,
-0.015382813289761543,
-0.08532355725765228,
-0.009268855676054955,
-0.02073976956307888,
0.09649215638637543,
-0.2238936424255371,
0.1325010061264038,
0.16212041676044464,
-0.015046309679746628,
0.1718226969242096,
0.01847519353032112,
0.013679388910531998,
0.006052343640476465,
-0.04082776978611946,
-0.00007846848893677816,
0.02128027006983757,
0.0015916629927232862,
0.0011914868373423815,
0.007707077544182539,
0.02131907269358635,
0.030305195599794388,
-0.14438240230083466,
-0.05413905158638954,
0.010167223401367664,
0.052466847002506256,
0.00018202696810476482,
0.0614926852285862,
-0.08105885237455368,
0.05735839903354645,
-0.0333511158823967,
-0.11407014727592468,
0.12527471780776978,
0.0140310637652874,
-0.12375999987125397,
0.1809239387512207,
-0.09875242412090302,
-0.177916020154953,
-0.19897617399692535,
-0.11664178967475891,
0.025174645707011223,
0.09509945660829544,
0.06778308749198914,
-0.06591268628835678,
-0.0677633062005043,
-0.013884147629141808,
-0.13205823302268982,
0.015237858518958092,
-0.0303916335105896,
-0.10815607011318207,
0.06643082201480865,
0.002197817200794816,
-0.1106930822134018,
-0.04751880466938019,
0.012397545389831066,
-0.05212624743580818,
0.06534521281719208,
-0.032029394060373306,
0.06015416979789734,
0.12733860313892365,
-0.009645693004131317,
0.014830506406724453,
-0.03892328962683678,
0.1736617386341095,
-0.07863081991672516,
0.0028175772167742252,
0.11224561184644699,
-0.04382455348968506,
0.03531843051314354,
0.2027312070131302,
0.03458266332745552,
-0.07247956842184067,
0.06938916444778442,
-0.03509911522269249,
-0.05979844182729721,
-0.202435702085495,
-0.10123657435178757,
-0.007523522712290287,
-0.02823515795171261,
0.08373580127954483,
0.0565473809838295,
0.25448861718177795,
0.1288231760263443,
0.060374923050403595,
0.03997355327010155,
0.024889161810278893,
0.0913970097899437,
0.1029813289642334,
-0.027027886360883713,
0.16222402453422546,
-0.08429007232189178,
-0.14650671184062958,
0.048164136707782745,
-0.022769063711166382,
0.07281020283699036,
0.17174853384494781,
-0.06210782378911972,
0.04705783352255821,
0.11571547389030457,
0.13094793260097504,
0.12702703475952148,
0.07746905833482742,
-0.061997704207897186,
-0.006629003677517176,
0.0010869213147088885,
-0.04415592923760414,
0.14652740955352783,
-0.060009948909282684,
-0.06889448314905167,
-0.04306207224726677,
-0.003198902355507016,
0.04323491454124451,
0.05818231403827667,
0.026216039434075356,
-0.28657910227775574,
0.042942874133586884,
0.04888097196817398,
-0.05969006195664406,
-0.11467164009809494,
0.09232109785079956,
-0.027857046574354172,
-0.18361465632915497,
0.03563778102397919,
-0.033283449709415436,
0.09147034585475922,
0.062072351574897766,
0.04841171205043793,
-0.06585943698883057,
-0.0609852597117424,
-0.045712124556303024,
0.15376420319080353,
-0.33846980333328247,
0.20756816864013672,
-0.011205663904547691,
0.08115556091070175,
-0.10785048454999924,
0.010794016532599926,
0.08773794025182724,
0.19103488326072693,
0.12050216645002365,
-0.049261946231126785,
-0.19848455488681793,
-0.11937171965837479,
-0.08363119512796402,
-0.015415008179843426,
0.02001480758190155,
-0.008096402511000633,
0.0008919041720218956,
-0.11757626384496689,
0.0014032695908099413,
0.04126403480768204,
-0.0069845812395215034,
-0.17894983291625977,
-0.15384836494922638,
-0.03538630157709122,
0.030474675819277763,
0.10934672504663467,
-0.04776112735271454,
-0.0534328930079937,
-0.06292759627103806,
0.13548673689365387,
0.026695549488067627,
0.008182995021343231,
-0.1301279366016388,
-0.053804632276296616,
-0.044131867587566376,
-0.023950019851326942,
0.07710648328065872,
0.009424211457371712,
0.11959850043058395,
-0.08615647256374359,
-0.06447352468967438,
0.09218238294124603,
-0.12910714745521545,
-0.042984966188669205,
-0.12177132815122604,
0.03449074551463127,
-0.045684002339839935,
-0.01073586754500866,
0.11459703743457794,
0.04736353084445,
-0.07455705851316452,
-0.06686578691005707,
-0.016151487827301025,
-0.0162202138453722,
0.052238523960113525,
-0.10140960663557053,
-0.11989933252334595,
-0.12391869723796844,
-0.023699220269918442,
-0.11985665559768677,
0.1933230459690094,
0.14995472133159637,
-0.08873795717954636,
0.15256796777248383,
0.2099498212337494,
-0.11413656920194626,
-0.29302918910980225,
-0.05128840357065201,
-0.06601350009441376,
0.004299632739275694,
0.06156041473150253,
-0.10058135539293289,
0.1023014560341835,
0.016915474086999893,
-0.08869403600692749,
-0.016260353848338127,
-0.10926515609025955,
-0.16224952042102814,
0.22960300743579865,
-0.0020108406897634268,
0.18459931015968323,
-0.07568172365427017,
-0.05459576100111008,
-0.12268339842557907,
0.05030543729662895,
0.043312136083841324,
-0.06949128210544586,
0.04921199381351471,
0.045118432492017746,
0.04848489910364151,
0.02309754677116871,
-0.04944291338324547,
0.05402865633368492,
-0.07527824491262436,
0.09563448280096054,
-0.16834798455238342,
-0.019022751599550247,
0.05676575005054474,
-0.027846379205584526,
0.11607834696769714,
-0.040225449949502945,
0.045501600950956345,
-0.05838647112250328,
-0.07079911977052689,
0.02105431631207466,
0.07136379927396774,
-0.007516450714319944,
-0.11632271111011505,
0.009460309520363808,
0.0020681610330939293,
-0.007515698205679655,
-0.07468903809785843,
0.01720641367137432,
-0.009510648436844349,
0.14864802360534668,
0.13830016553401947,
0.2062399536371231,
-0.06995580345392227,
0.06706579029560089,
-0.03199863061308861,
-0.11711113899946213,
0.07805433124303818,
-0.07166967540979385,
0.004296483471989632,
0.05220668390393257,
-0.0538930743932724,
0.14611311256885529,
0.06082209199666977,
0.003751826472580433,
-0.01890469156205654,
0.16250212490558624,
-0.16876746714115143,
0.04684048146009445,
-0.0843876302242279,
0.1279323697090149,
0.04778100550174713,
-0.03293748199939728,
0.09026376903057098,
-0.07791304588317871,
-0.03329215198755264,
-0.0002585914626251906,
0.006090222392231226,
-0.038581836968660355,
0.06518552452325821,
0.04536600783467293,
0.02252393215894699,
-0.06704199314117432,
0.0445764996111393,
0.07239795476198196,
0.016518399119377136,
0.041721411049366,
0.015846284106373787,
-0.09952405095100403,
-0.09522253274917603,
0.04372299090027809,
0.26397231221199036,
-0.1863422393798828,
-0.09990737587213516,
0.004564397502690554,
-0.09345841407775879,
0.004960347898304462,
0.08620705455541611,
0.0809662714600563,
0.04341237619519234,
-0.03603934869170189,
-0.02565331570804119,
-0.11602527648210526,
0.08217493444681168,
-0.015696978196501732,
0.05509110167622566,
-0.16319575905799866,
0.06676459312438965,
-0.030968010425567627,
-0.008549565449357033,
-0.08279257267713547,
-0.010031647980213165,
-0.11571928858757019,
0.026098787784576416,
-0.10430167615413666,
-0.03189973905682564,
-0.041006896644830704,
-0.011233619414269924,
0.05850789323449135,
-0.011018243618309498,
-0.013110441155731678,
-0.01927962154150009,
-0.08805359154939651,
0.02887921780347824,
-0.0008198951254598796,
0.04547540098428726,
-0.05460818111896515,
-0.024217726662755013,
0.037278566509485245,
0.004562355112284422,
0.046250831335783005,
0.012032478116452694,
-0.0011190201621502638,
0.049139540642499924,
-0.14732354879379272,
0.009436994791030884,
0.06159417703747749,
-0.0016145178815349936,
0.0070913624949753284,
-0.028678715229034424,
0.005330502521246672,
0.09783722460269928,
0.018718764185905457,
0.04128317907452583,
-0.0048657008446753025,
-0.1091027706861496,
0.014511657878756523,
0.10307195782661438,
-0.14174701273441315,
-0.03145497664809227,
-0.052812907844781876,
0.01100962609052658,
-0.05524790287017822,
0.23351503908634186,
-0.11669892817735672,
0.04470064863562584,
-0.02692001312971115,
0.030550040304660797,
-0.05822846665978432,
-0.10757116973400116,
-0.12190251797437668,
-0.0954190194606781,
-0.042861051857471466,
0.007703589275479317,
0.2689315676689148,
0.1459355354309082,
-0.008143693208694458,
0.0415508970618248,
0.07256698608398438,
0.09993022680282593,
0.001325596240349114,
0.22187061607837677,
0.09407079964876175,
-0.011255222372710705,
-0.12900875508785248,
0.0802748054265976,
0.027718892320990562,
-0.10550516843795776,
0.0003671931044664234,
0.017833324149250984,
-0.07709381729364395,
0.05998256057500839,
0.04779348149895668,
-0.04618219658732414,
-0.11530262231826782,
-0.1887446641921997,
-0.1010153517127037,
0.01362328790128231,
-0.09494820982217789,
-0.00841664057224989,
0.17340072989463806,
-0.07381404936313629,
-0.020257510244846344,
-0.08453129231929779,
-0.042230453342199326,
-0.21403644979000092,
-0.1685105264186859,
-0.09951409697532654,
-0.07172851264476776,
0.054574232548475266,
-0.01444533746689558,
0.051937036216259,
0.0384058877825737,
0.03334033116698265,
-0.0690227821469307,
0.10118697583675385,
-0.11317354440689087,
0.006825347896665335,
-0.007538147736340761,
-0.042660877108573914,
0.007157159503549337,
-0.17031751573085785,
-0.023363124579191208,
-0.1397811770439148,
-0.04669688642024994,
-0.031707603484392166,
-0.04375086724758148,
0.0007692996296100318,
-0.003963754046708345,
-0.03139100596308708,
-0.009807240217924118,
-0.01006900705397129,
0.03744599595665932,
0.023235660046339035,
0.05043753236532211,
0.022183645516633987,
0.01541586872190237,
0.043549589812755585,
0.21836970746517181,
-0.03527946025133133,
-0.18426218628883362,
-0.12376350164413452,
0.24631790816783905,
0.03293769061565399,
0.11490416526794434,
-0.07057193666696548,
-0.01361043006181717,
0.07598087936639786,
0.31235218048095703,
0.2598150074481964,
-0.03414434567093849,
0.010121017694473267,
-0.03132476285099983,
-0.014958096668124199,
-0.0064048562198877335,
0.18490195274353027,
0.008828791789710522,
0.16826002299785614,
-0.0621221587061882,
0.059055350720882416,
-0.016177164390683174,
-0.07808512449264526,
-0.06689254939556122,
0.14256809651851654,
-0.036333873867988586,
-0.02151089534163475,
-0.01796986348927021,
0.08792226016521454,
-0.0589551106095314,
0.17949369549751282,
-0.09007178992033005,
-0.009130639024078846,
-0.04809116572141647,
0.053617071360349655,
0.11827872693538666,
-0.02074413187801838,
0.03285614401102066,
-0.03567332774400711,
-0.018393725156784058,
0.0029441264923661947,
-0.04050283133983612,
-0.07413910329341888,
-0.04345672205090523,
0.06311136484146118,
0.02551795169711113,
0.25671228766441345,
-0.009337767027318478,
0.05477561056613922,
0.07988451421260834,
-0.0020537625532597303,
-0.10351628065109253,
0.11267323791980743,
0.00224103475920856,
-0.029008302837610245,
0.12491703033447266,
-0.015443749725818634,
0.007564615458250046,
-0.01867114193737507,
-0.01239294558763504,
-0.15698960423469543,
0.14728498458862305,
-0.10142818093299866,
-0.08940913528203964,
-0.05584051460027695,
0.12545742094516754,
-0.032320525497198105,
0.16258437931537628,
0.05726946145296097,
-0.026426637545228004,
0.0021389273460954428,
-0.0331779383122921,
0.08067825436592102,
0.009919043630361557,
-0.09914126992225647,
-0.02203422784805298,
-0.17707498371601105,
-0.016973769292235374,
0.12876249849796295,
-0.02544221095740795,
-0.24601322412490845,
-0.07971391826868057,
-0.06824030727148056,
-0.04311496391892433,
-0.1386985182762146,
0.07398401945829391,
0.2028772532939911,
0.019287997856736183,
-0.01476763840764761,
-0.1369636058807373,
-0.021961720660328865,
0.019149890169501305,
-0.026857441291213036,
-0.10799262672662735
] |
null | null | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` | {"license": "other", "tags": ["autotrain", "text-generation"], "widget": [{"text": "I love AutoTrain because "}]} | text-generation | cti-ttp-18/autotrain-fine-tune-llama-7b-v2 | [
"transformers",
"tensorboard",
"safetensors",
"llama",
"text-generation",
"autotrain",
"conversational",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T02:13:35+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #llama #text-generation #autotrain #conversational #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
"TAGS\n#transformers #tensorboard #safetensors #llama #text-generation #autotrain #conversational #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
64,
29,
3
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #llama #text-generation #autotrain #conversational #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.# Usage"
] | [
-0.02613452635705471,
0.049413714557886124,
-0.001235937001183629,
0.057766400277614594,
0.11908803135156631,
-0.047180887311697006,
0.25978389382362366,
0.062040697783231735,
-0.06183041259646416,
-0.07097387313842773,
0.17655940353870392,
0.20011916756629944,
-0.034196529537439346,
0.14890672266483307,
-0.04465925320982933,
-0.25590524077415466,
0.012975475750863552,
0.004993412643671036,
0.047019220888614655,
0.10928612947463989,
0.13212309777736664,
-0.07878076285123825,
0.06832128763198853,
0.04493657499551773,
-0.20891742408275604,
0.04210423305630684,
0.060782670974731445,
-0.12605272233486176,
0.17248982191085815,
0.08152253180742264,
0.10901545733213425,
0.05683992803096771,
0.10586759448051453,
-0.10849345475435257,
0.029662592336535454,
0.020755331963300705,
-0.02078991010785103,
0.08820577710866928,
0.07470186799764633,
-0.035299722105264664,
0.07215429097414017,
0.14684215188026428,
0.10762351751327515,
0.040082842111587524,
-0.0852564349770546,
0.04254116490483284,
0.004651759285479784,
0.015854984521865845,
0.11901296675205231,
0.10350926220417023,
-0.012437925674021244,
0.1791660189628601,
-0.08964049071073532,
0.10806751251220703,
-0.043071042746305466,
-0.29939407110214233,
-0.03488517925143242,
0.18661688268184662,
0.0795476958155632,
0.010262852534651756,
-0.11835269629955292,
0.08963320404291153,
0.10412883758544922,
-0.012406714260578156,
0.07920694351196289,
-0.03449423238635063,
-0.06096579134464264,
-0.01133757084608078,
-0.09482002258300781,
0.053951624780893326,
0.16490447521209717,
-0.0752190351486206,
-0.005785335320979357,
-0.13045313954353333,
-0.04518674686551094,
0.0017910542665049434,
-0.008256753906607628,
-0.10972216725349426,
-0.024494245648384094,
0.07761058211326599,
-0.05755041539669037,
-0.051851361989974976,
-0.13915690779685974,
-0.04620703309774399,
-0.11440865695476532,
0.06710169464349747,
0.0016483352519571781,
-0.013026080094277859,
-0.12166047096252441,
0.09898441284894943,
0.041326556354761124,
-0.11274014413356781,
0.057468824088573456,
-0.06516207754611969,
0.007476082071661949,
-0.09524328261613846,
-0.01807548478245735,
-0.19157704710960388,
0.03322979435324669,
0.16156306862831116,
0.1720125824213028,
0.012935069389641285,
-0.09024287015199661,
0.05059973895549774,
0.004662597086280584,
0.13109496235847473,
0.020487379282712936,
-0.04061729088425636,
0.059230297803878784,
-0.03793470188975334,
-0.0032177686225622892,
-0.04360566288232803,
-0.21140706539154053,
0.053157076239585876,
0.02168825827538967,
0.045824479311704636,
-0.04998764023184776,
0.11030521243810654,
-0.025786373764276505,
0.021637380123138428,
0.0030263878870755434,
-0.048484575003385544,
0.040920186787843704,
-0.062069252133369446,
0.0042768921703100204,
-0.04237591102719307,
0.0567755363881588,
0.10066397488117218,
0.013421964831650257,
0.09718544781208038,
-0.07870227843523026,
-0.030314423143863678,
-0.10590091347694397,
-0.07626785337924957,
0.015162419527769089,
0.009757984429597855,
0.03571130335330963,
-0.18597133457660675,
-0.24962984025478363,
-0.02256452850997448,
0.05791530758142471,
-0.03063207119703293,
-0.0764627531170845,
-0.09304165095090866,
0.008293465711176395,
0.06075836345553398,
-0.03050735779106617,
0.06672713160514832,
-0.008851977996528149,
0.02706000581383705,
-0.06739524006843567,
0.04266677424311638,
-0.06249029189348221,
0.017498567700386047,
-0.10887601971626282,
-0.015602605417370796,
-0.02508353628218174,
0.048516370356082916,
-0.029804324731230736,
0.1375165432691574,
-0.02747293934226036,
0.04733441770076752,
-0.047279294580221176,
0.06538859009742737,
0.02304733730852604,
0.13786961138248444,
-0.162993922829628,
-0.04079555347561836,
0.14967569708824158,
-0.10233389586210251,
-0.1233963593840599,
0.11895162612199783,
-0.0959591493010521,
0.2498241364955902,
0.11483573168516159,
0.11121290177106857,
0.059587880969047546,
-0.0951211228966713,
0.09306998550891876,
0.029441511258482933,
-0.07866691797971725,
-0.05151381343603134,
-0.014814753085374832,
0.021744931116700172,
-0.15207351744174957,
0.032542139291763306,
0.1431044638156891,
0.07062506675720215,
-0.03470105677843094,
-0.08242109417915344,
-0.015910295769572258,
-0.05577618256211281,
0.060617972165346146,
0.008810481987893581,
0.14027662575244904,
-0.050112005323171616,
-0.049846310168504715,
0.08761004358530045,
0.03891126811504364,
0.014146309345960617,
-0.03182167932391167,
-0.09861091524362564,
-0.02235225960612297,
-0.05870905518531799,
0.01835584081709385,
-0.10523350536823273,
-0.06770681589841843,
-0.0344700962305069,
0.09944247454404831,
0.05938608571887016,
0.11463836580514908,
0.04611844941973686,
0.029390277341008186,
-0.01915644481778145,
0.03533774986863136,
0.18898840248584747,
0.031926229596138,
-0.14074572920799255,
-0.13996204733848572,
0.1156575009226799,
-0.09007788449525833,
0.1366654336452484,
-0.2408461570739746,
0.03996214270591736,
-0.07400106638669968,
0.0970928743481636,
0.0123940110206604,
0.06945404410362244,
-0.07163877785205841,
0.020932242274284363,
-0.11331301927566528,
-0.0037883282639086246,
0.06664266437292099,
0.0443410761654377,
-0.07635367661714554,
0.14723819494247437,
-0.18433347344398499,
0.2403380423784256,
0.12688855826854706,
-0.1313813328742981,
-0.08398402482271194,
-0.08870822191238403,
0.006813773885369301,
-0.023224353790283203,
-0.08838945627212524,
-0.010349818505346775,
0.12145121395587921,
-0.027707122266292572,
0.19904427230358124,
-0.023625297471880913,
-0.043538883328437805,
-0.005801444873213768,
-0.09306485950946808,
-0.011083913967013359,
0.033344805240631104,
0.10330363363027573,
-0.1977260559797287,
0.13565437495708466,
0.126370370388031,
-0.055930040776729584,
0.22625941038131714,
0.035821374505758286,
0.02718956023454666,
0.004748769570142031,
-0.050658464431762695,
0.020439933985471725,
-0.0007788225775584579,
-0.05567781627178192,
-0.04657468944787979,
0.01069801114499569,
-0.021309632807970047,
0.03768882900476456,
-0.1359213888645172,
-0.020793022587895393,
0.024789517745375633,
0.046894460916519165,
0.0794321596622467,
0.06370214372873306,
-0.08579982072114944,
0.0899532213807106,
-0.048366278409957886,
-0.1485423892736435,
0.1104399710893631,
0.008902136236429214,
-0.11655057221651077,
0.18044152855873108,
-0.06813055276870728,
-0.24840429425239563,
-0.18865229189395905,
-0.17377185821533203,
-0.01987111009657383,
0.05849945917725563,
0.055650971829891205,
-0.07216355949640274,
-0.06927336752414703,
-0.02213755063712597,
-0.06990166008472443,
0.011719576083123684,
0.002937101060524583,
-0.07580936700105667,
0.03829486295580864,
-0.009913301095366478,
-0.10666188597679138,
-0.03095516748726368,
-0.0082400506362319,
-0.05293632671236992,
0.05686712637543678,
-0.04920686408877373,
0.06362558901309967,
0.18969987332820892,
-0.017353497445583344,
0.025612402707338333,
-0.03593987599015236,
0.11464431881904602,
-0.08138527721166611,
0.01926834136247635,
0.09883652627468109,
-0.07179801911115646,
0.036658622324466705,
0.19957512617111206,
0.031201956793665886,
-0.06814595311880112,
0.07802021503448486,
-0.014282328076660633,
-0.08411948382854462,
-0.21063955128192902,
-0.08798232674598694,
-0.018082905560731888,
0.024205610156059265,
0.08105771988630295,
0.06365582346916199,
0.271727591753006,
0.13060413300991058,
0.08174886554479599,
0.07187239825725555,
0.028079472482204437,
0.08038744330406189,
0.15744641423225403,
-0.03873995691537857,
0.1927422732114792,
-0.07775282114744186,
-0.1839926540851593,
0.03508535027503967,
-0.006642169319093227,
0.055999793112277985,
0.15288497507572174,
0.03252122178673744,
0.03128522261977196,
0.06457684934139252,
0.13949453830718994,
0.11479554325342178,
0.05405056104063988,
-0.0646790936589241,
-0.0010256996611133218,
-0.024587802588939667,
-0.025985216721892357,
0.11569429188966751,
-0.03199762478470802,
-0.05976906791329384,
-0.0052961730398237705,
0.06857618689537048,
0.034007083624601364,
0.08258669078350067,
0.008592521771788597,
-0.297897607088089,
0.030249791219830513,
0.034858688712120056,
-0.07019975036382675,
-0.08513922989368439,
0.07109247893095016,
0.01635856181383133,
-0.1417742222547531,
0.019820986315608025,
-0.05749262496829033,
0.08601444214582443,
-0.021465325728058815,
0.06457336246967316,
-0.06669881194829941,
-0.01087320689111948,
-0.04573184996843338,
0.1286919265985489,
-0.38256508111953735,
0.19894777238368988,
-0.004020556341856718,
0.04042098671197891,
-0.11443748325109482,
0.019342930987477303,
0.0794905349612236,
0.14754587411880493,
0.10299526154994965,
-0.07041158527135849,
-0.11419450491666794,
-0.08860345184803009,
-0.108334019780159,
-0.012815619818866253,
0.020658791065216064,
-0.0071265907026827335,
0.01699085906147957,
-0.1017988994717598,
-0.017107557505369186,
0.05590512603521347,
-0.021086184307932854,
-0.11169766634702682,
-0.17701654136180878,
0.019230814650654793,
0.06162974238395691,
0.03728805482387543,
-0.0187192615121603,
-0.10412058979272842,
-0.12321512401103973,
0.2071624994277954,
0.018307644873857498,
-0.005237394943833351,
-0.1327933669090271,
-0.014151807874441147,
-0.05788804963231087,
-0.0388125479221344,
0.06623958796262741,
0.006339598447084427,
0.13703660666942596,
-0.0804799273610115,
-0.09800254553556442,
0.11590903997421265,
-0.11205103248357773,
-0.05204203724861145,
-0.11310744285583496,
0.029481299221515656,
-0.02533668465912342,
0.0017588507616892457,
0.09917452186346054,
0.030039267614483833,
-0.06435361504554749,
-0.058203477412462234,
-0.02380383014678955,
-0.005192129407078028,
-0.036690853536129,
-0.13227355480194092,
-0.10268548876047134,
-0.09113359451293945,
-0.020639801397919655,
-0.09743643552064896,
0.22499017417430878,
0.12181546539068222,
-0.09502962976694107,
0.13431377708911896,
0.18462873995304108,
-0.11420831084251404,
-0.32409247756004333,
-0.051731761544942856,
-0.036175042390823364,
0.022371893748641014,
0.044371481984853745,
-0.11967993527650833,
0.11708766967058182,
-0.004343600012362003,
-0.08226039260625839,
-0.013063148595392704,
-0.16041503846645355,
-0.17445823550224304,
0.2506617307662964,
0.028199229389429092,
0.22578518092632294,
-0.10632815957069397,
-0.06400556862354279,
-0.12734049558639526,
0.055893588811159134,
0.08170850574970245,
-0.11447708308696747,
0.07301059365272522,
0.05139289051294327,
0.06946814805269241,
0.034994129091501236,
-0.03212907165288925,
0.04435929283499718,
-0.05343679338693619,
0.05734099820256233,
-0.16260609030723572,
-0.031971052289009094,
0.04125194251537323,
-0.029259517788887024,
0.09094668179750443,
-0.08482377976179123,
0.012384120374917984,
-0.029457222670316696,
-0.07048147171735764,
0.033714886754751205,
0.0730753242969513,
0.0007500774227082729,
-0.10785745829343796,
-0.002392529509961605,
-0.01334359310567379,
0.0016578871291130781,
-0.05249679461121559,
0.0893378034234047,
-0.03819749504327774,
0.14314784109592438,
0.20726068317890167,
0.2469717264175415,
-0.04905981197953224,
0.061357930302619934,
-0.028249530121684074,
-0.11064134538173676,
0.08322218805551529,
-0.0830935388803482,
0.02912459895014763,
0.08418910950422287,
-0.03933535888791084,
0.1527082324028015,
0.06387831270694733,
-0.009888025932013988,
-0.009597230702638626,
0.1505560427904129,
-0.15615659952163696,
-0.0023331553675234318,
-0.07422249764204025,
0.10101985931396484,
0.02556183561682701,
0.02513941377401352,
0.14359448850154877,
-0.08335942029953003,
-0.005354918073862791,
0.043020498007535934,
-0.0012960387393832207,
-0.0191207118332386,
0.11358597874641418,
0.044929660856723785,
0.019113775342702866,
-0.07136465609073639,
0.022879086434841156,
0.07399597018957138,
-0.0046704052947461605,
0.05170837789773941,
0.03170456737279892,
-0.07824999839067459,
-0.10350322723388672,
0.02261495031416416,
0.2746606767177582,
-0.17664207518100739,
-0.08488890528678894,
-0.0501452311873436,
-0.12236138433218002,
0.01740502566099167,
0.13434366881847382,
0.07369136810302734,
0.037752341479063034,
-0.0809975415468216,
-0.020611241459846497,
-0.12210399657487869,
0.11721852421760559,
0.018459374085068703,
0.06112320348620415,
-0.1607562005519867,
0.08074508607387543,
-0.02028442919254303,
0.012837857007980347,
-0.09941032528877258,
-0.02627645432949066,
-0.12859836220741272,
0.02130647748708725,
-0.12115710228681564,
-0.03664113208651543,
-0.032076966017484665,
-0.017877457663416862,
0.05427646264433861,
-0.008721619844436646,
-0.03480428084731102,
-0.03161484748125076,
-0.08914840966463089,
0.03519104793667793,
0.004910000134259462,
0.03630561754107475,
-0.04848231002688408,
-0.027261164039373398,
0.01869961805641651,
-0.007818866521120071,
0.06680544465780258,
-0.017561109736561775,
-0.02122385799884796,
0.042821016162633896,
-0.16887645423412323,
0.044391728937625885,
0.07952035218477249,
0.010515812784433365,
0.0349714569747448,
-0.013000770471990108,
-0.00848341267555952,
0.08842522650957108,
0.05512119457125664,
0.044395171105861664,
-0.005570038687437773,
-0.0880206972360611,
0.06344640254974365,
0.029702799394726753,
-0.11368881911039352,
-0.04019291698932648,
-0.0032389771658927202,
-0.013973087072372437,
-0.01581406407058239,
0.20918111503124237,
-0.12089811265468597,
0.045476749539375305,
-0.06408795714378357,
0.04510820284485817,
-0.015165659599006176,
-0.13142997026443481,
-0.055747900158166885,
-0.11939580738544464,
-0.018719490617513657,
-0.018146933987736702,
0.23903241753578186,
0.15278510749340057,
-0.0293132234364748,
0.03286408260464668,
0.06214509531855583,
0.06287726759910583,
0.016978124156594276,
0.18268707394599915,
0.08955860137939453,
0.018569383770227432,
-0.126549631357193,
0.07263866066932678,
0.053632788360118866,
-0.022315610200166702,
0.019800836220383644,
-0.024462418630719185,
-0.11333486437797546,
0.08702895045280457,
0.079722560942173,
-0.0038163939025253057,
-0.0800442099571228,
-0.0884753167629242,
-0.14484558999538422,
0.05706819146871567,
-0.08547622710466385,
0.028176909312605858,
0.17262034118175507,
-0.03843715041875839,
-0.020216524600982666,
-0.03778230398893356,
-0.0627548024058342,
-0.22062307596206665,
-0.1840049922466278,
-0.1206788569688797,
-0.07601361721754074,
0.017178917303681374,
-0.04573162645101547,
0.042503513395786285,
0.014858824200928211,
0.07572535425424576,
-0.052833884954452515,
0.09751356393098831,
-0.07262639701366425,
0.00536007946357131,
0.027256036177277565,
-0.04671723023056984,
0.007862678728997707,
-0.20632827281951904,
0.003197787096723914,
-0.13907958567142487,
0.050043243914842606,
-0.03950429707765579,
-0.0245398860424757,
0.026373226195573807,
0.012478252872824669,
-0.029755668714642525,
-0.038004424422979355,
-0.017076868563890457,
0.03111935593187809,
0.028504783287644386,
0.035327259451150894,
0.012455487623810768,
-0.014540745876729488,
0.022681936621665955,
0.19050279259681702,
-0.051909707486629486,
-0.1470593363046646,
-0.13373933732509613,
0.1955510526895523,
-0.008017889223992825,
0.1170470118522644,
-0.06801515072584152,
-0.013752876780927181,
0.0331222228705883,
0.33613693714141846,
0.28134045004844666,
-0.06478410959243774,
0.017970405519008636,
-0.01393724326044321,
-0.002432035282254219,
-0.020601071417331696,
0.14792956411838531,
0.017218085005879402,
0.19390888512134552,
-0.05038122087717056,
0.015712467953562737,
-0.011443168856203556,
-0.08882667869329453,
-0.053111616522073746,
0.11841052025556564,
-0.0028693557251244783,
0.001059003290720284,
-0.02115878090262413,
0.07066109031438828,
-0.10890578478574753,
0.0980864018201828,
-0.14048123359680176,
-0.0635903999209404,
-0.07845725119113922,
0.035359855741262436,
0.12233898043632507,
-0.02201191708445549,
0.036815837025642395,
-0.026241952553391457,
-0.009932389482855797,
0.018695034086704254,
-0.038696445524692535,
-0.0994165688753128,
0.01826048456132412,
0.06768028438091278,
-0.044120125472545624,
0.18223965167999268,
-0.024770641699433327,
0.04789729416370392,
0.09007851779460907,
-0.001134435529820621,
-0.07955122739076614,
0.07831089198589325,
-0.012214750051498413,
-0.06741352379322052,
0.12816116213798523,
0.0036960330326110125,
0.0141795314848423,
-0.0014137336984276772,
0.010959620587527752,
-0.1342262178659439,
0.12145137041807175,
-0.14872406423091888,
-0.08933082222938538,
-0.05189753696322441,
0.09975093603134155,
-0.025115031749010086,
0.15273165702819824,
0.07925892621278763,
-0.012564110569655895,
0.013181307353079319,
-0.018889326602220535,
0.03741481900215149,
-0.028454123064875603,
-0.10128913074731827,
-0.032859254628419876,
-0.20255762338638306,
-0.02189943566918373,
0.032317206263542175,
-0.017749721184372902,
-0.29072636365890503,
-0.07636001706123352,
-0.08474932610988617,
-0.042441561818122864,
-0.13664405047893524,
0.05837016925215721,
0.25358763337135315,
0.03147624805569649,
-0.020409738644957542,
-0.09107930213212967,
-0.005107259377837181,
0.03582623600959778,
-0.06879168748855591,
-0.09328535199165344
] |
null | null | transformers |
<div align="center">
<h1>
MiniCPM
</h1>
</div>
<p align="center">
<a href="https://shengdinghu.notion.site/MiniCPM-c805a17c5c8046398914e47f0542095a?pvs=4" target="_blank">MiniCPM 技术报告</a><a href="https://shengdinghu.notion.site/MiniCPM-Unveiling-the-Potential-of-End-side-Large-Language-Models-d4d3a8c426424654a4e80e42a711cb20?pvs=4" target="_blank"> Technical Report</a> |
<a href="https://github.com/OpenBMB/OmniLMM/" target="_blank">OmniLMM 多模态模型 Multi-modal Model</a> |
<a href="https://luca.cn/" target="_blank">CPM-C 千亿模型试用 ~100B Model Trial </a>
</p>
MiniCPM 是面壁与清华大学自然语言处理实验室共同开源的系列端侧语言大模型，主体语言模型 MiniCPM-2B 仅有 24亿（2.4B）的非词嵌入参数量。
- 经过 SFT 后，MiniCPM 在公开综合性评测集上，MiniCPM 与 Mistral-7B相近（中文、数学、代码能力更优），整体性能超越 Llama2-13B、MPT-30B、Falcon-40B 等模型。
- 经过 DPO 后，MiniCPM 在当前最接近用户体感的评测集 MTBench上，MiniCPM-2B 也超越了 Llama2-70B-Chat、Vicuna-33B、Mistral-7B-Instruct-v0.1、Zephyr-7B-alpha 等众多代表性开源大模型。
- 以 MiniCPM-2B 为基础构建端侧多模态大模型 MiniCPM-V，整体性能在同规模模型中实现最佳，超越基于 Phi-2 构建的现有多模态大模型，在部分评测集上达到与 9.6B Qwen-VL-Chat 相当甚至更好的性能。
- 经过 Int4 量化后，MiniCPM 可在手机上进行部署推理，流式输出速度略高于人类说话速度。MiniCPM-V 也首次跑通了多模态大模型在手机上的部署。
- 一张1080/2080可高效参数微调，一张3090/4090可全参数微调，一台机器可持续训练 MiniCPM，二次开发成本较低。
我们将完全开源MiniCPM-2B的模型参数供学术研究和有限商用，以及训练过程中的所有Checkpoint和大部分非专有数据供模型机理研究。
- 基于MiniCPM-2B的指令微调与人类偏好对**MiniCPM-2B-SFT/DPO。**
- 基于MiniCPM-2B的多模态模型**MiniCPM-V**，能力超越基于Phi-2的同参数级别多模态模型**。**
- MiniCPM-2B-SFT/DPO的Int4量化版**MiniCPM-2B-SFT/DPO-Int4。**
- 基于MLC-LLM、LLMFarm开发的MiniCPM手机端程序，**文本及多模态模型均可在手机端进行推理。**
MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
- MiniCPM has very close performance compared with Mistral-7B on open-sourced general benchmarks with better ability on Chinese, Mathmetics and Coding after SFT. The overall performance exceeds Llama2-13B, MPT-30B, Falcon-40B, etc.
- After DPO, MiniCPM outperforms Llama2-70B-Chat, Vicuna-33B, Mistral-7B-Instruct-v0.1, Zephyr-7B-alpha, etc. on MTBench.
- MiniCPM-V, based on MiniCPM-2B, achieves the best overall performance among multimodel models of the same scale, surpassing existing multimodal large models built on Phi-2 and achieving performance comparable to or even better than 9.6B Qwen-VL-Chat on some tasks.
- MiniCPM can be deployed and infer on smartphones, and the speed of streaming output is relatively higher than the verbal speed of human. MiniCPM-V is the first multi-modal models that can be deployed on smartphones.
- The cost of developing based on MiniCPM is low. Parameter efficient finetuning can be conducted with a single 1080/2080 GPU and full parameter finetuning can be conducted with a 3090/4090 GPU.
We release all model parameters for research and limited commercial use. We also release all the checkpoint during training and most public training data for research on model mechanism.
- SFT and DPO version based on MiniCPM-2B and human preference: **MiniCPM-2B-SFT/DPO**
- The multi-modal model **MiniCPM-V** based on MiniCPM-2B, which outperforms models with similar size, i.e., Phi-2
- The INT4 quantized version **MiniCPM-2B-SFT/DPO-Int4** based on MiniCPM-2B-SFT/DPO
- Mobile phone application based on MLC-LLM and LLMFarm. Both language model and multimodel model can conduct inference on smartphones.
### 评测结果 Evaluation Results
详细的评测结果位于[github仓库](https://github.com/OpenBMB/MiniCPM?tab=readme-ov-file#%E8%AF%84%E6%B5%8B%E7%BB%93%E6%9E%9C)
Detailed evaluation results are in [github repo](https://github.com/OpenBMB/MiniCPM/blob/main/README-en.md#evaluation-results)
注意：我们发现使用Huggingface生成质量略差于vLLM，因此推荐使用vLLM进行测试。我们正在排查原因。
Notice: We discovered that the quality of Huggingface generation is slightly lower than vLLM, thus benchmarking using vLLM is recommended.
We are investigating the cause now.
### 局限性 Limitations
- 受限于模型规模，模型可能出现幻觉性问题。其中由于DPO模型生成的回复内容更长，更容易出现幻觉。我们也将持续进行MiniCPM模型的迭代改进；
- 为了保证在学术研究用途上模型的通用性，我们未对模型进行任何身份认同训练。同时由于我们用ShareGPT开源语料作为部分训练数据，模型可能会输出类似GPT系列模型的身份认同信息；
- 受限于模型规模，模型的输出受到提示词（prompt）的影响较大，可能多次尝试产生不一致的结果；
- 受限于模型容量，模型的知识记忆较不准确，后续我们将结合RAG方法来增强模型的知识记忆能力。
- Due to limitations in model size, the model may experience hallucinatory issues. As DPO model tend to generate longer response, hallucinations are more likely to occur. We will also continue to iterate and improve the MiniCPM model.
- To ensure the universality of the model for academic research purposes, we did not conduct any identity training on the model. Meanwhile, as we use ShareGPT open-source corpus as part of the training data, the model may output identity information similar to the GPT series models.
- Due to the limitation of model size, the output of the model is greatly influenced by prompt words, which may result in inconsistent results from multiple attempts.
- Due to limited model capacity, the model's knowledge memory is not accurate. In the future, we will combine the RAG method to enhance the model's knowledge memory ability.
## 模型下载 Download
| HuggingFace | ModelScope | WiseModel |
|-------------|------------|-----------|
|[sft-bf16](https://huggingface.co/openbmb/MiniCPM-2B-sft-bf16)|[sft-bf16](https://modelscope.cn/models/OpenBMB/miniCPM-bf16)|[sft-bf16](https://wisemodel.cn/models/OpenBMB/miniCPM-bf16)
|[sft-fp32](https://huggingface.co/openbmb/MiniCPM-2B-sft-fp32)|[sft-fp32](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-sft-fp32)|[sft-fp32](https://wisemodel.cn/models/OpenBMB/miniCPM-dpo-fp32)
|[dpo-bf16](https://huggingface.co/openbmb/MiniCPM-2B-dpo-bf16)|[dpo-bf16](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-dpo-bf16/summary)|[dpo-bf16](https://wisemodel.cn/models/OpenBMB/MiniCPM-2B-dpo-bf16)
|[dpo-fp16](https://huggingface.co/openbmb/MiniCPM-2B-dpo-fp16)|[dpo-fp16](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-dpo-fp16/)|[dpo-fp16](https://wisemodel.cn/models/OpenBMB/MiniCPM-2B-dpo-fp16)
|[dpo-fp32](https://huggingface.co/openbmb/MiniCPM-2B-dpo-fp32)|[dpo-fp32](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-dpo-fp32)|[dpo-fp32](https://wisemodel.cn/models/OpenBMB/miniCPM-dpo-fp32)
## 模型使用 Usage
* 安装`transformers>=4.36.0`以及`accelerate`后，运行以下代码
* 注意：需要在`from_pretrained`中明确指明模型的数据类型，否则会引起较大计算误差
* Run the following code after install `transformers>=4.36.0` and `accelerate`
* Warning: It is necessary to specify the data type of the model clearly in 'from_pretrained', otherwise large calculation errors will be caused
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
torch.manual_seed(0)
path = 'openbmb/MiniCPM-2B-sft-bf16'
tokenizer = AutoTokenizer.from_pretrained(path)
model = AutoModelForCausalLM.from_pretrained(path, torch_dtype=torch.bfloat16, device_map='cuda', trust_remote_code=True)
responds, history = model.chat(tokenizer, "山东省最高的山是哪座山, 它比黄山高还是矮？差距多少？", temperature=0.8, top_p=0.8)
print(responds)
```
* 期望输出 Expected Output
```shell
山东省最高的山是泰山，海拔1545米。
相对于黄山（海拔1864米），泰山海拔较低，相差约319米。
```
## 开源协议 LICENSE
#### 模型协议 Model LICENSE
* 本仓库中代码依照 [Apache-2.0](https://github.com/OpenBMB/MiniCPM/blob/main/LICENSE) 协议开源
* MiniCPM 模型权重的使用则需要遵循 [“通用模型许可协议-来源说明-宣传限制-商业授权”](https://github.com/OpenBMB/General-Model-License/blob/main/%E9%80%9A%E7%94%A8%E6%A8%A1%E5%9E%8B%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE-%E6%9D%A5%E6%BA%90%E8%AF%B4%E6%98%8E-%E5%AE%A3%E4%BC%A0%E9%99%90%E5%88%B6-%E5%95%86%E4%B8%9A%E6%8E%88%E6%9D%83.md)。
* MiniCPM 模型权重对学术研究完全开放。
* 如需将模型用于商业用途，请联系[email protected]来获取书面授权，在登记后亦允许免费商业使用。
* This repository is released under the [Apache-2.0](https://github.com/OpenBMB/MiniCPM/blob/main/LICENSE) License.
* The usage of MiniCPM model weights must strictly follow [the General Model License (GML)](https://github.com/OpenBMB/General-Model-License/blob/main/%E9%80%9A%E7%94%A8%E6%A8%A1%E5%9E%8B%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE-%E6%9D%A5%E6%BA%90%E8%AF%B4%E6%98%8E-%E5%AE%A3%E4%BC%A0%E9%99%90%E5%88%B6-%E5%95%86%E4%B8%9A%E6%8E%88%E6%9D%83.md).
* The models and weights of MiniCPM are completely free for academic research.
* If you intend to utilize the model for commercial purposes, please reach out to [email protected] to obtain the certificate of authorization.
#### 声明 Statement
* 作为一个语言模型，MiniCPM 通过学习大量的文本来生成内容，但它无法理解、表达个人观点或价值判断，它所输出的任何内容都不代表模型开发者的观点和立场。
* 因此用户在使用 MiniCPM 生成的内容时，应自行负责对其进行评估和验证。
* 如果由于使用 MinCPM 开源模型而导致的任何问题，包括但不限于数据安全问题、公共舆论风险，或模型被误导、滥用、传播或不当利用所带来的任何风险和问题，我们将不承担任何责任。
* As a language model, MiniCPM generates content by learning from a vast amount of text.
* However, it does not possess the ability to comprehend or express personal opinions or value judgments.
* Any content generated by MiniCPM does not represent the viewpoints or positions of the model developers.
* Therefore, when using content generated by MiniCPM, users should take full responsibility for evaluating and verifying it on their own.
<p id="8"></p>
## 工作引用 Citation
* 如果觉得MiniCPM有助于您的工作，请考虑引用下列[技术报告](https://shengdinghu.notion.site/MiniCPM-c805a17c5c8046398914e47f0542095a?pvs=4)
* Please cite our [techinical report](https://shengdinghu.notion.site/MiniCPM-Unveiling-the-Potential-of-End-side-Large-Language-Models-d4d3a8c426424654a4e80e42a711cb20?pvs=4) if you find our work valuable.
```
@inproceedings{minicpm2024,
title={MiniCPM：Unveiling the Potential of End-side Large Language Models},
booktitle={OpenBMB Blog},
year={2024}
}
```
| {"language": ["en", "zh"], "tags": ["MiniCPM", "ModelBest", "THUNLP"]} | text-generation | openbmb/MiniCPM-2B-sft-bf16-llama-format | [
"transformers",
"pytorch",
"text-generation",
"MiniCPM",
"ModelBest",
"THUNLP",
"conversational",
"en",
"zh",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:15:15+00:00 | [] | [
"en",
"zh"
] | TAGS
#transformers #pytorch #text-generation #MiniCPM #ModelBest #THUNLP #conversational #en #zh #autotrain_compatible #endpoints_compatible #region-us
|
MiniCPM
=========
[MiniCPM 技术报告](URL target=) [Technical Report](URL target=) |
[OmniLMM 多模态模型 Multi-modal Model](URL target=) |
[CPM-C 千亿模型试用 ~100B Model Trial](URL target=)
MiniCPM 是面壁与清华大学自然语言处理实验室共同开源的系列端侧语言大模型，主体语言模型 MiniCPM-2B 仅有 24亿（2.4B）的非词嵌入参数量。
* 经过 SFT 后，MiniCPM 在公开综合性评测集上，MiniCPM 与 Mistral-7B相近（中文、数学、代码能力更优），整体性能超越 Llama2-13B、MPT-30B、Falcon-40B 等模型。
* 经过 DPO 后，MiniCPM 在当前最接近用户体感的评测集 MTBench上，MiniCPM-2B 也超越了 Llama2-70B-Chat、Vicuna-33B、Mistral-7B-Instruct-v0.1、Zephyr-7B-alpha 等众多代表性开源大模型。
* 以 MiniCPM-2B 为基础构建端侧多模态大模型 MiniCPM-V，整体性能在同规模模型中实现最佳，超越基于 Phi-2 构建的现有多模态大模型，在部分评测集上达到与 9.6B Qwen-VL-Chat 相当甚至更好的性能。
* 经过 Int4 量化后，MiniCPM 可在手机上进行部署推理，流式输出速度略高于人类说话速度。MiniCPM-V 也首次跑通了多模态大模型在手机上的部署。
* 一张1080/2080可高效参数微调，一张3090/4090可全参数微调，一台机器可持续训练 MiniCPM，二次开发成本较低。
我们将完全开源MiniCPM-2B的模型参数供学术研究和有限商用，以及训练过程中的所有Checkpoint和大部分非专有数据供模型机理研究。
* 基于MiniCPM-2B的指令微调与人类偏好对MiniCPM-2B-SFT/DPO。
* 基于MiniCPM-2B的多模态模型MiniCPM-V，能力超越基于Phi-2的同参数级别多模态模型。
* MiniCPM-2B-SFT/DPO的Int4量化版MiniCPM-2B-SFT/DPO-Int4。
* 基于MLC-LLM、LLMFarm开发的MiniCPM手机端程序，文本及多模态模型均可在手机端进行推理。
MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
* MiniCPM has very close performance compared with Mistral-7B on open-sourced general benchmarks with better ability on Chinese, Mathmetics and Coding after SFT. The overall performance exceeds Llama2-13B, MPT-30B, Falcon-40B, etc.
* After DPO, MiniCPM outperforms Llama2-70B-Chat, Vicuna-33B, Mistral-7B-Instruct-v0.1, Zephyr-7B-alpha, etc. on MTBench.
* MiniCPM-V, based on MiniCPM-2B, achieves the best overall performance among multimodel models of the same scale, surpassing existing multimodal large models built on Phi-2 and achieving performance comparable to or even better than 9.6B Qwen-VL-Chat on some tasks.
* MiniCPM can be deployed and infer on smartphones, and the speed of streaming output is relatively higher than the verbal speed of human. MiniCPM-V is the first multi-modal models that can be deployed on smartphones.
* The cost of developing based on MiniCPM is low. Parameter efficient finetuning can be conducted with a single 1080/2080 GPU and full parameter finetuning can be conducted with a 3090/4090 GPU.
We release all model parameters for research and limited commercial use. We also release all the checkpoint during training and most public training data for research on model mechanism.
* SFT and DPO version based on MiniCPM-2B and human preference: MiniCPM-2B-SFT/DPO
* The multi-modal model MiniCPM-V based on MiniCPM-2B, which outperforms models with similar size, i.e., Phi-2
* The INT4 quantized version MiniCPM-2B-SFT/DPO-Int4 based on MiniCPM-2B-SFT/DPO
* Mobile phone application based on MLC-LLM and LLMFarm. Both language model and multimodel model can conduct inference on smartphones.
### 评测结果 Evaluation Results
详细的评测结果位于github仓库
Detailed evaluation results are in github repo
注意：我们发现使用Huggingface生成质量略差于vLLM，因此推荐使用vLLM进行测试。我们正在排查原因。
Notice: We discovered that the quality of Huggingface generation is slightly lower than vLLM, thus benchmarking using vLLM is recommended.
We are investigating the cause now.
### 局限性 Limitations
* 受限于模型规模，模型可能出现幻觉性问题。其中由于DPO模型生成的回复内容更长，更容易出现幻觉。我们也将持续进行MiniCPM模型的迭代改进；
* 为了保证在学术研究用途上模型的通用性，我们未对模型进行任何身份认同训练。同时由于我们用ShareGPT开源语料作为部分训练数据，模型可能会输出类似GPT系列模型的身份认同信息；
* 受限于模型规模，模型的输出受到提示词（prompt）的影响较大，可能多次尝试产生不一致的结果；
* 受限于模型容量，模型的知识记忆较不准确，后续我们将结合RAG方法来增强模型的知识记忆能力。
* Due to limitations in model size, the model may experience hallucinatory issues. As DPO model tend to generate longer response, hallucinations are more likely to occur. We will also continue to iterate and improve the MiniCPM model.
* To ensure the universality of the model for academic research purposes, we did not conduct any identity training on the model. Meanwhile, as we use ShareGPT open-source corpus as part of the training data, the model may output identity information similar to the GPT series models.
* Due to the limitation of model size, the output of the model is greatly influenced by prompt words, which may result in inconsistent results from multiple attempts.
* Due to limited model capacity, the model's knowledge memory is not accurate. In the future, we will combine the RAG method to enhance the model's knowledge memory ability.
模型下载 Download
-------------
HuggingFace: sft-bf16, ModelScope: sft-bf16, WiseModel: sft-bf16
HuggingFace: sft-fp32, ModelScope: sft-fp32, WiseModel: sft-fp32
HuggingFace: dpo-bf16, ModelScope: dpo-bf16, WiseModel: dpo-bf16
HuggingFace: dpo-fp16, ModelScope: dpo-fp16, WiseModel: dpo-fp16
HuggingFace: dpo-fp32, ModelScope: dpo-fp32, WiseModel: dpo-fp32
模型使用 Usage
----------
* 安装'transformers>=4.36.0'以及'accelerate'后，运行以下代码
* 注意：需要在'from\_pretrained'中明确指明模型的数据类型，否则会引起较大计算误差
* Run the following code after install 'transformers>=4.36.0' and 'accelerate'
* Warning: It is necessary to specify the data type of the model clearly in 'from\_pretrained', otherwise large calculation errors will be caused
* 期望输出 Expected Output
开源协议 LICENSE
------------
#### 模型协议 Model LICENSE
* 本仓库中代码依照 Apache-2.0 协议开源
* MiniCPM 模型权重的使用则需要遵循 “通用模型许可协议-来源说明-宣传限制-商业授权”。
* MiniCPM 模型权重对学术研究完全开放。
* 如需将模型用于商业用途，请联系[email protected]来获取书面授权，在登记后亦允许免费商业使用。
* This repository is released under the Apache-2.0 License.
* The usage of MiniCPM model weights must strictly follow the General Model License (GML).
* The models and weights of MiniCPM are completely free for academic research.
* If you intend to utilize the model for commercial purposes, please reach out to cpm@URL to obtain the certificate of authorization.
#### 声明 Statement
* 作为一个语言模型，MiniCPM 通过学习大量的文本来生成内容，但它无法理解、表达个人观点或价值判断，它所输出的任何内容都不代表模型开发者的观点和立场。
* 因此用户在使用 MiniCPM 生成的内容时，应自行负责对其进行评估和验证。
* 如果由于使用 MinCPM 开源模型而导致的任何问题，包括但不限于数据安全问题、公共舆论风险，或模型被误导、滥用、传播或不当利用所带来的任何风险和问题，我们将不承担任何责任。
* As a language model, MiniCPM generates content by learning from a vast amount of text.
* However, it does not possess the ability to comprehend or express personal opinions or value judgments.
* Any content generated by MiniCPM does not represent the viewpoints or positions of the model developers.
* Therefore, when using content generated by MiniCPM, users should take full responsibility for evaluating and verifying it on their own.
工作引用 Citation
-------------
* 如果觉得MiniCPM有助于您的工作，请考虑引用下列技术报告
* Please cite our techinical report if you find our work valuable.
| [
"### 评测结果 Evaluation Results\n\n\n详细的评测结果位于github仓库\n\n\nDetailed evaluation results are in github repo\n\n\n注意：我们发现使用Huggingface生成质量略差于vLLM，因此推荐使用vLLM进行测试。我们正在排查原因。\n\n\nNotice: We discovered that the quality of Huggingface generation is slightly lower than vLLM, thus benchmarking using vLLM is recommended.\nWe are investigating the cause now.",
"### 局限性 Limitations\n\n\n* 受限于模型规模，模型可能出现幻觉性问题。其中由于DPO模型生成的回复内容更长，更容易出现幻觉。我们也将持续进行MiniCPM模型的迭代改进；\n* 为了保证在学术研究用途上模型的通用性，我们未对模型进行任何身份认同训练。同时由于我们用ShareGPT开源语料作为部分训练数据，模型可能会输出类似GPT系列模型的身份认同信息；\n* 受限于模型规模，模型的输出受到提示词（prompt）的影响较大，可能多次尝试产生不一致的结果；\n* 受限于模型容量，模型的知识记忆较不准确，后续我们将结合RAG方法来增强模型的知识记忆能力。\n* Due to limitations in model size, the model may experience hallucinatory issues. As DPO model tend to generate longer response, hallucinations are more likely to occur. We will also continue to iterate and improve the MiniCPM model.\n* To ensure the universality of the model for academic research purposes, we did not conduct any identity training on the model. Meanwhile, as we use ShareGPT open-source corpus as part of the training data, the model may output identity information similar to the GPT series models.\n* Due to the limitation of model size, the output of the model is greatly influenced by prompt words, which may result in inconsistent results from multiple attempts.\n* Due to limited model capacity, the model's knowledge memory is not accurate. In the future, we will combine the RAG method to enhance the model's knowledge memory ability.\n\n\n模型下载 Download\n-------------\n\n\nHuggingFace: sft-bf16, ModelScope: sft-bf16, WiseModel: sft-bf16\nHuggingFace: sft-fp32, ModelScope: sft-fp32, WiseModel: sft-fp32\nHuggingFace: dpo-bf16, ModelScope: dpo-bf16, WiseModel: dpo-bf16\nHuggingFace: dpo-fp16, ModelScope: dpo-fp16, WiseModel: dpo-fp16\nHuggingFace: dpo-fp32, ModelScope: dpo-fp32, WiseModel: dpo-fp32\n\n\n模型使用 Usage\n----------\n\n\n* 安装'transformers>=4.36.0'以及'accelerate'后，运行以下代码\n* 注意：需要在'from\\_pretrained'中明确指明模型的数据类型，否则会引起较大计算误差\n* Run the following code after install 'transformers>=4.36.0' and 'accelerate'\n* Warning: It is necessary to specify the data type of the model clearly in 'from\\_pretrained', otherwise large calculation errors will be caused\n* 期望输出 Expected Output\n\n\n开源协议 LICENSE\n------------",
"#### 模型协议 Model LICENSE\n\n\n* 本仓库中代码依照 Apache-2.0 协议开源\n* MiniCPM 模型权重的使用则需要遵循 “通用模型许可协议-来源说明-宣传限制-商业授权”。\n* MiniCPM 模型权重对学术研究完全开放。\n* 如需将模型用于商业用途，请联系[email protected]来获取书面授权，在登记后亦允许免费商业使用。\n* This repository is released under the Apache-2.0 License.\n* The usage of MiniCPM model weights must strictly follow the General Model License (GML).\n* The models and weights of MiniCPM are completely free for academic research.\n* If you intend to utilize the model for commercial purposes, please reach out to cpm@URL to obtain the certificate of authorization.",
"#### 声明 Statement\n\n\n* 作为一个语言模型，MiniCPM 通过学习大量的文本来生成内容，但它无法理解、表达个人观点或价值判断，它所输出的任何内容都不代表模型开发者的观点和立场。\n* 因此用户在使用 MiniCPM 生成的内容时，应自行负责对其进行评估和验证。\n* 如果由于使用 MinCPM 开源模型而导致的任何问题，包括但不限于数据安全问题、公共舆论风险，或模型被误导、滥用、传播或不当利用所带来的任何风险和问题，我们将不承担任何责任。\n* As a language model, MiniCPM generates content by learning from a vast amount of text.\n* However, it does not possess the ability to comprehend or express personal opinions or value judgments.\n* Any content generated by MiniCPM does not represent the viewpoints or positions of the model developers.\n* Therefore, when using content generated by MiniCPM, users should take full responsibility for evaluating and verifying it on their own.\n\n\n\n工作引用 Citation\n-------------\n\n\n* 如果觉得MiniCPM有助于您的工作，请考虑引用下列技术报告\n* Please cite our techinical report if you find our work valuable."
] | [
"TAGS\n#transformers #pytorch #text-generation #MiniCPM #ModelBest #THUNLP #conversational #en #zh #autotrain_compatible #endpoints_compatible #region-us \n",
"### 评测结果 Evaluation Results\n\n\n详细的评测结果位于github仓库\n\n\nDetailed evaluation results are in github repo\n\n\n注意：我们发现使用Huggingface生成质量略差于vLLM，因此推荐使用vLLM进行测试。我们正在排查原因。\n\n\nNotice: We discovered that the quality of Huggingface generation is slightly lower than vLLM, thus benchmarking using vLLM is recommended.\nWe are investigating the cause now.",
"### 局限性 Limitations\n\n\n* 受限于模型规模，模型可能出现幻觉性问题。其中由于DPO模型生成的回复内容更长，更容易出现幻觉。我们也将持续进行MiniCPM模型的迭代改进；\n* 为了保证在学术研究用途上模型的通用性，我们未对模型进行任何身份认同训练。同时由于我们用ShareGPT开源语料作为部分训练数据，模型可能会输出类似GPT系列模型的身份认同信息；\n* 受限于模型规模，模型的输出受到提示词（prompt）的影响较大，可能多次尝试产生不一致的结果；\n* 受限于模型容量，模型的知识记忆较不准确，后续我们将结合RAG方法来增强模型的知识记忆能力。\n* Due to limitations in model size, the model may experience hallucinatory issues. As DPO model tend to generate longer response, hallucinations are more likely to occur. We will also continue to iterate and improve the MiniCPM model.\n* To ensure the universality of the model for academic research purposes, we did not conduct any identity training on the model. Meanwhile, as we use ShareGPT open-source corpus as part of the training data, the model may output identity information similar to the GPT series models.\n* Due to the limitation of model size, the output of the model is greatly influenced by prompt words, which may result in inconsistent results from multiple attempts.\n* Due to limited model capacity, the model's knowledge memory is not accurate. In the future, we will combine the RAG method to enhance the model's knowledge memory ability.\n\n\n模型下载 Download\n-------------\n\n\nHuggingFace: sft-bf16, ModelScope: sft-bf16, WiseModel: sft-bf16\nHuggingFace: sft-fp32, ModelScope: sft-fp32, WiseModel: sft-fp32\nHuggingFace: dpo-bf16, ModelScope: dpo-bf16, WiseModel: dpo-bf16\nHuggingFace: dpo-fp16, ModelScope: dpo-fp16, WiseModel: dpo-fp16\nHuggingFace: dpo-fp32, ModelScope: dpo-fp32, WiseModel: dpo-fp32\n\n\n模型使用 Usage\n----------\n\n\n* 安装'transformers>=4.36.0'以及'accelerate'后，运行以下代码\n* 注意：需要在'from\\_pretrained'中明确指明模型的数据类型，否则会引起较大计算误差\n* Run the following code after install 'transformers>=4.36.0' and 'accelerate'\n* Warning: It is necessary to specify the data type of the model clearly in 'from\\_pretrained', otherwise large calculation errors will be caused\n* 期望输出 Expected Output\n\n\n开源协议 LICENSE\n------------",
"#### 模型协议 Model LICENSE\n\n\n* 本仓库中代码依照 Apache-2.0 协议开源\n* MiniCPM 模型权重的使用则需要遵循 “通用模型许可协议-来源说明-宣传限制-商业授权”。\n* MiniCPM 模型权重对学术研究完全开放。\n* 如需将模型用于商业用途，请联系[email protected]来获取书面授权，在登记后亦允许免费商业使用。\n* This repository is released under the Apache-2.0 License.\n* The usage of MiniCPM model weights must strictly follow the General Model License (GML).\n* The models and weights of MiniCPM are completely free for academic research.\n* If you intend to utilize the model for commercial purposes, please reach out to cpm@URL to obtain the certificate of authorization.",
"#### 声明 Statement\n\n\n* 作为一个语言模型，MiniCPM 通过学习大量的文本来生成内容，但它无法理解、表达个人观点或价值判断，它所输出的任何内容都不代表模型开发者的观点和立场。\n* 因此用户在使用 MiniCPM 生成的内容时，应自行负责对其进行评估和验证。\n* 如果由于使用 MinCPM 开源模型而导致的任何问题，包括但不限于数据安全问题、公共舆论风险，或模型被误导、滥用、传播或不当利用所带来的任何风险和问题，我们将不承担任何责任。\n* As a language model, MiniCPM generates content by learning from a vast amount of text.\n* However, it does not possess the ability to comprehend or express personal opinions or value judgments.\n* Any content generated by MiniCPM does not represent the viewpoints or positions of the model developers.\n* Therefore, when using content generated by MiniCPM, users should take full responsibility for evaluating and verifying it on their own.\n\n\n\n工作引用 Citation\n-------------\n\n\n* 如果觉得MiniCPM有助于您的工作，请考虑引用下列技术报告\n* Please cite our techinical report if you find our work valuable."
] | [
53,
101,
655,
180,
262
] | [
"passage: TAGS\n#transformers #pytorch #text-generation #MiniCPM #ModelBest #THUNLP #conversational #en #zh #autotrain_compatible #endpoints_compatible #region-us \n### 评测结果 Evaluation Results\n\n\n详细的评测结果位于github仓库\n\n\nDetailed evaluation results are in github repo\n\n\n注意：我们发现使用Huggingface生成质量略差于vLLM，因此推荐使用vLLM进行测试。我们正在排查原因。\n\n\nNotice: We discovered that the quality of Huggingface generation is slightly lower than vLLM, thus benchmarking using vLLM is recommended.\nWe are investigating the cause now."
] | [
-0.012041576206684113,
-0.17306528985500336,
-0.005423421505838633,
0.0412234328687191,
0.12012123316526413,
-0.0013297442346811295,
0.0630730539560318,
0.12710997462272644,
0.001967189135029912,
0.008368625305593014,
0.14500227570533752,
0.07811778783798218,
0.02991710789501667,
0.032769594341516495,
-0.01100046094506979,
-0.14143450558185577,
0.06286749988794327,
0.04651982709765434,
0.004565810319036245,
0.09587398916482925,
0.16862188279628754,
-0.06725110858678818,
0.13815298676490784,
0.04727271944284439,
-0.1692403256893158,
0.005503055173903704,
0.04614584520459175,
0.014270780608057976,
0.0843590572476387,
0.05999916419386864,
-0.04125315696001053,
0.047944046556949615,
-0.025348521769046783,
-0.08415411412715912,
0.04981321468949318,
0.058366890996694565,
0.02226879633963108,
0.02243657037615776,
-0.0039905100129544735,
0.02264879085123539,
0.18685483932495117,
-0.015096279792487621,
-0.03529636561870575,
0.06114925816655159,
-0.03316779434680939,
-0.039811670780181885,
-0.06639444082975388,
-0.0035198780242353678,
-0.003083794144913554,
0.0411263071000576,
0.008474135771393776,
0.2886279821395874,
-0.130380779504776,
0.11442007124423981,
0.23111136257648468,
-0.20332802832126617,
-0.06621184945106506,
0.2206989973783493,
0.0905771404504776,
-0.05267082899808884,
-0.04831335321068764,
0.1073639914393425,
0.09240660816431046,
0.015986168757081032,
0.016957012936472893,
0.0018665504176169634,
-0.027889272198081017,
-0.008225708268582821,
-0.0518561489880085,
-0.05171787366271019,
0.21863552927970886,
-0.0017704556230455637,
0.001812653848901391,
-0.11802772432565689,
-0.08302648365497589,
-0.00809558667242527,
0.02644859440624714,
-0.030757931992411613,
-0.03809734061360359,
0.019589519128203392,
0.015890734270215034,
-0.06661680340766907,
-0.03903871774673462,
-0.054577652364969254,
-0.04695836082100868,
0.05889936536550522,
0.029830386862158775,
0.06455299258232117,
-0.11476194113492966,
0.09560688585042953,
0.0518440417945385,
-0.10540705174207687,
-0.04277677461504936,
-0.13894903659820557,
0.09285875409841537,
0.05823250114917755,
-0.0050173234194517136,
-0.049689747393131256,
0.14110924303531647,
0.06505978852510452,
0.047685541212558746,
0.008814618922770023,
-0.013269969262182713,
0.0020550915505737066,
0.035375457257032394,
0.16257059574127197,
-0.060592662543058395,
-0.041253235191106796,
0.12829729914665222,
0.016979673877358437,
0.049650706350803375,
-0.0373949371278286,
0.008281771093606949,
-0.10270453244447708,
0.13245679438114166,
0.08298145234584808,
0.014349494129419327,
0.12658534944057465,
-0.04858553409576416,
-0.07783547788858414,
-0.11770942807197571,
-0.07005496323108673,
-0.017810488119721413,
-0.00544792041182518,
-0.028596479445695877,
0.1237068772315979,
0.04494211822748184,
-0.006404855754226446,
-0.11509907245635986,
-0.01525888592004776,
-0.05364953354001045,
-0.06436917930841446,
-0.08488952368497849,
-0.07797754555940628,
0.03527848795056343,
-0.14458662271499634,
0.01339002512395382,
-0.0814577266573906,
-0.12333410978317261,
-0.06233471259474754,
-0.017572659999132156,
0.001468359725549817,
-0.06181802600622177,
0.022425444796681404,
-0.05147789046168327,
-0.0019156091148033738,
-0.0210970900952816,
0.09911452978849411,
-0.047557346522808075,
0.05318806320428848,
0.004390534944832325,
0.04231104627251625,
-0.0878949910402298,
-0.003471412928774953,
-0.04998128116130829,
0.03311353549361229,
0.06343575567007065,
-0.0005915469373576343,
-0.09381334483623505,
0.11334405094385147,
-0.045687247067689896,
-0.06714794039726257,
-0.024931101128458977,
0.0038972035981714725,
0.03026571124792099,
0.14996352791786194,
-0.10288990288972855,
-0.04877953976392746,
0.09875019639730453,
-0.10377205163240433,
-0.1112067922949791,
0.1744367778301239,
-0.017740415409207344,
0.044388920068740845,
0.12062321603298187,
0.052278030663728714,
0.07133281975984573,
-0.16525284945964813,
-0.008469953201711178,
0.02790532447397709,
-0.11010783165693283,
0.07411373406648636,
0.008409898728132248,
0.09669714421033859,
-0.13739950954914093,
0.10656656324863434,
-0.005012495443224907,
-0.00761538976803422,
-0.08259267359972,
-0.03550761193037033,
-0.1269558221101761,
-0.012140399776399136,
-0.046517807990312576,
0.03659087046980858,
0.004835695959627628,
-0.06111522763967514,
-0.0396670363843441,
-0.12258103489875793,
0.05821710824966431,
-0.05171796306967735,
0.009969858452677727,
-0.12657783925533295,
0.14205054938793182,
0.04821918532252312,
0.060012854635715485,
-0.04828257858753204,
-0.026217153295874596,
0.011709954589605331,
0.09574993699789047,
0.0015263421228155494,
0.13563863933086395,
0.01300012320280075,
-0.05509395897388458,
0.005051575601100922,
0.027540426701307297,
0.005631564185023308,
-0.051546886563301086,
-0.0033797682262957096,
-0.1557578593492508,
0.026755115017294884,
-0.04652092605829239,
-0.062198325991630554,
-0.02568444050848484,
-0.0012089081574231386,
0.080357626080513,
0.16800618171691895,
0.019731102511286736,
0.024924878031015396,
0.03495868295431137,
-0.03079851157963276,
-0.04088008403778076,
-0.04775739461183548,
0.06110534816980362,
-0.02499789372086525,
-0.04357493668794632,
0.130564346909523,
-0.0017886946443468332,
0.18021094799041748,
0.13176004588603973,
-0.077214315533638,
0.07732152193784714,
0.009911061264574528,
-0.05850088596343994,
0.035826217383146286,
-0.02997432090342045,
-0.06850644946098328,
0.13606135547161102,
-0.008008693344891071,
0.08203424513339996,
-0.0975809320807457,
-0.020444247871637344,
0.0098617784678936,
-0.0514347217977047,
-0.02269909158349037,
0.09585268050432205,
0.05578908324241638,
0.01172302570194006,
0.021128639578819275,
0.020467903465032578,
0.023792652413249016,
0.23454949259757996,
-0.04680071026086807,
0.045801468193531036,
0.027367854490876198,
-0.027568792924284935,
-0.04623908922076225,
0.01316177099943161,
-0.217410609126091,
-0.04361977428197861,
0.06643500179052353,
-0.026893066242337227,
0.08534650504589081,
-0.10343143343925476,
0.006402985192835331,
-0.008499260060489178,
-0.017631717026233673,
0.04959944263100624,
0.16777856647968292,
0.035074129700660706,
0.10797393321990967,
-0.06237276270985603,
0.06414423137903214,
-0.055241990834474564,
-0.03474891185760498,
-0.07624322921037674,
0.11593987792730331,
-0.05653247982263565,
-0.2350115031003952,
-0.10475151240825653,
0.0010152371833100915,
-0.18481551110744476,
-0.02754807472229004,
0.007564762141555548,
-0.1581612229347229,
-0.07127375900745392,
-0.03253509849309921,
0.2350156456232071,
0.002941955579444766,
0.04656582698225975,
0.14030198752880096,
0.04851154610514641,
0.002018240513280034,
-0.19114495813846588,
-0.07174283266067505,
-0.03722342476248741,
-0.09444919228553772,
0.08539843559265137,
-0.0662921816110611,
0.07349148392677307,
0.04712729901075363,
0.0013258547987788916,
0.05350495129823685,
-0.024602647870779037,
0.3198085129261017,
-0.035992495715618134,
-0.018550032749772072,
0.32673290371894836,
0.04017343372106552,
-0.0201023668050766,
0.0784171000123024,
-0.028046149760484695,
-0.12612977623939514,
0.007388388738036156,
0.01278578769415617,
-0.08270186185836792,
-0.14370010793209076,
-0.10012412071228027,
-0.08735613524913788,
0.03663092851638794,
-0.014703494496643543,
0.03611346334218979,
-0.039711322635412216,
0.02641797624528408,
-0.061123352497816086,
0.07336897403001785,
0.014881090261042118,
0.05397140979766846,
0.13779300451278687,
-0.06412909924983978,
0.1215447187423706,
-0.022147607058286667,
-0.05308264121413231,
0.11080634593963623,
-0.0011185697512701154,
0.14460064470767975,
-0.09571781754493713,
-0.03353708237409592,
0.13384023308753967,
0.07290609180927277,
0.056452345103025436,
0.05776350572705269,
-0.10554657876491547,
-0.02563147246837616,
-0.02670998126268387,
-0.03498886898159981,
-0.1271432787179947,
-0.027674475684762,
-0.023369571194052696,
-0.01888252981007099,
-0.08449911326169968,
0.1445365995168686,
0.10121521353721619,
0.1514013111591339,
0.01646769978106022,
-0.14907069504261017,
-0.0445612333714962,
0.025242865085601807,
-0.02075096219778061,
-0.09428364783525467,
0.017258737236261368,
-0.0002571991353761405,
-0.12195686250925064,
0.06966893374919891,
-0.032882045954465866,
0.12386024743318558,
-0.06477229297161102,
0.093997523188591,
-0.12904995679855347,
0.06455915421247482,
0.020705508068203926,
0.08613000065088272,
-0.23500287532806396,
0.1285199075937271,
0.005224231164902449,
0.07644294947385788,
-0.10995025932788849,
-0.01029803417623043,
0.05167360603809357,
0.13055124878883362,
0.05448029935359955,
-0.0008814808097667992,
0.06697290390729904,
0.03257967159152031,
-0.05295000225305557,
0.10109902918338776,
0.028283212333917618,
0.05891256779432297,
0.04932119697332382,
-0.11101848632097244,
0.07341565191745758,
-0.0014485915889963508,
0.024948252364993095,
-0.1597406417131424,
-0.025949710980057716,
0.02647472359240055,
0.023446427658200264,
0.008563980460166931,
-0.07205909490585327,
-0.03574857488274574,
-0.0003822891158051789,
0.20273925364017487,
-0.009449574165046215,
-0.059170857071876526,
-0.09824619442224503,
0.12116198241710663,
0.04880622774362564,
-0.037675391882658005,
-0.05225604772567749,
-0.09323538839817047,
0.11175838857889175,
-0.01635262556374073,
-0.16750910878181458,
-0.04521789774298668,
-0.09812474250793457,
-0.1488247662782669,
0.028358424082398415,
0.15575644373893738,
-0.12068270146846771,
0.015197372063994408,
0.07355780899524689,
-0.04805264249444008,
-0.08848033845424652,
-0.13683049380779266,
0.021687908098101616,
0.18921886384487152,
-0.11664211004972458,
0.0303568784147501,
-0.009279737249016762,
-0.05426528677344322,
-0.00044666399480775,
-0.03776675835251808,
0.11164551973342896,
0.21722832322120667,
-0.021184712648391724,
0.1349806934595108,
0.000023335594960371964,
-0.04024425148963928,
-0.3032006323337555,
-0.05312112718820572,
0.030403101816773415,
0.07061487436294556,
-0.11393516510725021,
0.015322198159992695,
0.08248046040534973,
-0.08909136801958084,
0.01642145961523056,
-0.008205090649425983,
-0.24321813881397247,
-0.1325308084487915,
0.05832463130354881,
0.026367533951997757,
0.39483895897865295,
-0.006305711343884468,
-0.013711717911064625,
-0.08911329507827759,
-0.2488856315612793,
0.07472796738147736,
-0.07193471491336823,
0.09528373181819916,
-0.09544526040554047,
0.027810730040073395,
0.0638531744480133,
-0.05403687804937363,
0.13775330781936646,
-0.1278660148382187,
0.07097037881612778,
-0.08119554072618484,
-0.04318161681294441,
0.03030886873602867,
-0.034863099455833435,
0.1170090064406395,
-0.06312378495931625,
0.09084362536668777,
-0.12138006091117859,
-0.05461288243532181,
-0.12308456003665924,
0.11142736673355103,
-0.011123293079435825,
-0.0613940991461277,
-0.13148485124111176,
0.017163045704364777,
0.0271842572838068,
0.003944768570363522,
0.06857966631650925,
-0.03231434151530266,
0.027513820677995682,
0.15131427347660065,
0.12368369102478027,
-0.27449288964271545,
0.03321032226085663,
0.034964669495821,
0.03794107213616371,
0.11302755028009415,
-0.09868153184652328,
0.060318030416965485,
0.11127489060163498,
-0.014959503896534443,
0.022536596283316612,
0.04223174601793289,
-0.04297272488474846,
0.0024958690628409386,
0.1149367168545723,
-0.20190882682800293,
-0.03281770274043083,
-0.054951801896095276,
-0.0728362575173378,
0.04267723858356476,
0.027897585183382034,
0.22292432188987732,
-0.023401111364364624,
0.006119216326624155,
0.011090376414358616,
0.029444055631756783,
-0.021184692159295082,
0.12377536296844482,
0.020297933369874954,
0.026660287752747536,
-0.14806781709194183,
0.050147175788879395,
-0.075998954474926,
0.050737906247377396,
0.025972016155719757,
-0.023280641064047813,
-0.11747658252716064,
-0.02771631069481373,
-0.005925072357058525,
0.1167292520403862,
-0.03018140234053135,
-0.0366852842271328,
-0.13916344940662384,
-0.1515641212463379,
0.009978842921555042,
0.005807365290820599,
0.0805787667632103,
0.09914808720350266,
-0.055956773459911346,
-0.04165932163596153,
-0.04544702172279358,
0.03928147256374359,
0.08055905252695084,
-0.011326931416988373,
-0.17374925315380096,
0.0936940386891365,
0.01645699329674244,
0.11606723815202713,
-0.0970708429813385,
-0.0031815017573535442,
-0.12650041282176971,
-0.007098662666976452,
-0.17066316306591034,
-0.04980909824371338,
0.04808872565627098,
-0.019487258046865463,
0.03982498496770859,
-0.05306154116988182,
-0.12017703056335449,
0.07589789479970932,
-0.06453850865364075,
0.0017519225366413593,
-0.039343077689409256,
0.043174874037504196,
-0.02286495268344879,
0.005552811548113823,
0.1182781308889389,
-0.054492972791194916,
0.09858082979917526,
0.014841422438621521,
-0.06341664493083954,
0.022824827581644058,
-0.17697595059871674,
-0.07488957792520523,
0.10524825751781464,
0.058501701802015305,
-0.01590939797461033,
0.0259566493332386,
0.06152660772204399,
0.04358411580324173,
-0.0002930971677415073,
0.04565538465976715,
0.10126908123493195,
-0.07497803121805191,
-0.03380323201417923,
-0.007830834947526455,
-0.019142769277095795,
0.015000910498201847,
0.00862963404506445,
0.022895025089383125,
0.12879842519760132,
0.11387906223535538,
-0.011861070990562439,
0.002764081582427025,
-0.17577968537807465,
0.00969113688915968,
0.02070978283882141,
-0.12795718014240265,
-0.05119390785694122,
-0.007846405729651451,
0.0806637704372406,
-0.01819346472620964,
0.2611583471298218,
0.15638965368270874,
-0.02850610390305519,
0.006295189261436462,
0.18055805563926697,
-0.04809131845831871,
-0.016696138307452202,
0.08330986648797989,
-0.00582207553088665,
0.10666073113679886,
-0.0406375378370285,
-0.05065103620290756,
0.06729482114315033,
-0.07125896960496902,
0.1628037840127945,
0.03156827390193939,
0.00399547815322876,
0.07461906969547272,
0.05788462236523628,
0.040365658700466156,
-0.002787478733807802,
-0.018573766574263573,
-0.05123700946569443,
0.15040016174316406,
-0.04014421999454498,
-0.07972094416618347,
0.14322122931480408,
-0.05842873454093933,
0.027944408357143402,
-0.0311273206025362,
-0.03880659490823746,
-0.15876638889312744,
-0.10663416236639023,
-0.08895990252494812,
-0.17422616481781006,
0.08444791287183762,
-0.13484033942222595,
0.004093908239156008,
-0.10722740739583969,
0.05937885493040085,
-0.09144376218318939,
0.08989180624485016,
-0.07196935266256332,
-0.12665551900863647,
0.0926973968744278,
-0.021941734477877617,
-0.0782194584608078,
-0.0225577000528574,
0.03650622442364693,
-0.04659340903162956,
0.05714433267712593,
0.008215117268264294,
0.052726998925209045,
-0.007898569107055664,
-0.06817437708377838,
-0.042123377323150635,
-0.037964098155498505,
-0.0552033893764019,
-0.022657383233308792,
-0.058664340525865555,
0.15724387764930725,
-0.005558132193982601,
-0.010029207915067673,
-0.01925608143210411,
0.19497627019882202,
0.028653524816036224,
-0.09042851626873016,
-0.11981602013111115,
0.03604769706726074,
-0.03987421467900276,
0.017520204186439514,
-0.007376867812126875,
0.028946975246071815,
-0.06811822950839996,
0.31822073459625244,
0.20531509816646576,
-0.09783336520195007,
-0.005969519726932049,
-0.09563238173723221,
0.028582042083144188,
-0.01794850453734398,
0.1958857923746109,
0.05049983784556389,
0.1581651270389557,
-0.03658413514494896,
0.052546512335538864,
-0.047069206833839417,
-0.020278004929423332,
-0.07424662262201309,
0.0834006667137146,
0.07263767719268799,
-0.052947599440813065,
-0.03419528901576996,
0.02575763501226902,
-0.07319007813930511,
-0.029212892055511475,
-0.04401495307683945,
-0.16775721311569214,
-0.07351382821798325,
-0.017973773181438446,
0.02883092686533928,
-0.06976012140512466,
0.07762473076581955,
-0.05979100987315178,
0.05015180632472038,
0.05064471811056137,
-0.030776100233197212,
-0.12027501314878464,
-0.008715573698282242,
0.11086076498031616,
0.03626920282840729,
0.07909857481718063,
-0.02322724275290966,
0.01676502637565136,
0.05646523833274841,
-0.08004547655582428,
-0.06507373601198196,
-0.004378459416329861,
-0.015796151012182236,
-0.09439942985773087,
-0.01663690060377121,
0.07747728377580643,
0.037152912467718124,
-0.0541045106947422,
0.04685864597558975,
-0.0004546974378172308,
-0.019693253561854362,
0.0727117657661438,
0.014842134900391102,
-0.04834957793354988,
0.12889014184474945,
-0.12104983627796173,
0.08800652623176575,
0.13818760216236115,
-0.03742275759577751,
-0.01470973715186119,
-0.10753654688596725,
0.10287948697805405,
-0.03846394270658493,
-0.04525461047887802,
-0.0003296649956610054,
-0.15100178122520447,
-0.0039954050444066525,
0.15307219326496124,
-0.07295624166727066,
-0.07406628876924515,
-0.10786087810993195,
-0.06190088763833046,
-0.012562060728669167,
-0.0390118770301342,
0.14109644293785095,
0.03829704225063324,
0.024775784462690353,
0.04737255722284317,
-0.1442311853170395,
0.061796870082616806,
0.024713510647416115,
-0.067190021276474,
-0.0917118638753891
] |
null | null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral7b_instruct_generation
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8017
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 0.03
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8552 | 0.0 | 20 | 1.8246 |
| 1.9103 | 0.01 | 40 | 1.7950 |
| 1.8802 | 0.01 | 60 | 1.7918 |
| 1.7641 | 0.01 | 80 | 1.7952 |
| 1.8434 | 0.01 | 100 | 1.7969 |
| 1.8108 | 0.02 | 120 | 1.7955 |
| 1.8556 | 0.02 | 140 | 1.7928 |
| 1.8986 | 0.02 | 160 | 1.7948 |
| 1.8581 | 0.03 | 180 | 1.8270 |
| 1.7897 | 0.03 | 200 | 1.7943 |
| 1.7806 | 0.03 | 220 | 1.7922 |
| 1.8261 | 0.03 | 240 | 1.7956 |
| 1.8138 | 0.04 | 260 | 1.7988 |
| 1.8244 | 0.04 | 280 | 1.7902 |
| 1.8769 | 0.04 | 300 | 1.7977 |
| 1.896 | 0.04 | 320 | 1.7932 |
| 1.9111 | 0.05 | 340 | 1.7987 |
| 1.8624 | 0.05 | 360 | 1.7998 |
| 1.9663 | 0.05 | 380 | 1.7964 |
| 1.9383 | 0.06 | 400 | 1.7989 |
| 1.8478 | 0.06 | 420 | 1.7924 |
| 1.9117 | 0.06 | 440 | 1.7899 |
| 1.8742 | 0.06 | 460 | 1.7920 |
| 1.7778 | 0.07 | 480 | 1.8015 |
| 1.9523 | 0.07 | 500 | 1.8017 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "mistral7b_instruct_generation", "results": []}]} | null | 4ndr3w/mistral7b_instruct_generation | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | 2024-02-09T02:15:58+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us
| mistral7b\_instruct\_generation
===============================
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8017
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0002
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_steps: 0.03
* training\_steps: 500
### Training results
### Framework versions
* PEFT 0.8.2
* Transformers 4.37.2
* Pytorch 2.1.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_steps: 0.03\n* training\\_steps: 500",
"### Training results",
"### Framework versions\n\n\n* PEFT 0.8.2\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_steps: 0.03\n* training\\_steps: 500",
"### Training results",
"### Framework versions\n\n\n* PEFT 0.8.2\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
61,
115,
4,
39
] | [
"passage: TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_steps: 0.03\n* training\\_steps: 500### Training results### Framework versions\n\n\n* PEFT 0.8.2\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.12655259668827057,
0.08907678723335266,
-0.0028333819936960936,
0.12002138793468475,
0.12202506512403488,
0.012428714893758297,
0.10774524509906769,
0.1329633593559265,
-0.05796525627374649,
0.0853806659579277,
0.1411277949810028,
0.1019122526049614,
0.032589368522167206,
0.1658523678779602,
-0.05366137996315956,
-0.21294143795967102,
0.006064490880817175,
-0.009025642648339272,
-0.05992205813527107,
0.12067462503910065,
0.08130650967359543,
-0.1261579394340515,
0.08505404740571976,
-0.034818343818187714,
-0.1510097086429596,
0.00004669619374908507,
0.016084523871541023,
-0.021714631468057632,
0.13250616192817688,
0.010170171037316322,
0.09958454221487045,
0.02959561161696911,
0.11105221509933472,
-0.2023097276687622,
0.012373360805213451,
0.07924298942089081,
0.021113086491823196,
0.0877227783203125,
0.055344801396131516,
-0.002523955889046192,
0.09570126235485077,
-0.09101927280426025,
0.045554861426353455,
0.024521825835108757,
-0.13567426800727844,
-0.20643775165081024,
-0.1146480143070221,
0.035313256084918976,
0.0916590690612793,
0.08076410740613937,
-0.0037058377638459206,
0.11184903234243393,
-0.04220021888613701,
0.09002625942230225,
0.2708457410335541,
-0.2825262248516083,
-0.07663946598768234,
0.062332961708307266,
0.03682784363627434,
0.10285111516714096,
-0.11898189783096313,
-0.014525293372571468,
0.05303526669740677,
0.04205472394824028,
0.1471991091966629,
-0.014592967927455902,
-0.06656983494758606,
0.017859693616628647,
-0.1415601670742035,
-0.026471780613064766,
0.10810854285955429,
0.038743309676647186,
-0.039704713970422745,
-0.03844236955046654,
-0.08221342414617538,
-0.1749003678560257,
-0.04806199669837952,
-0.012442260980606079,
0.05110832303762436,
-0.02624613046646118,
-0.03243733197450638,
-0.023663224652409554,
-0.0917624905705452,
-0.09578616917133331,
-0.035082053393125534,
0.10391578078269958,
0.042400605976581573,
0.014097856357693672,
-0.011678050272166729,
0.12048616260290146,
-0.023591583594679832,
-0.14607703685760498,
0.008120400831103325,
0.03043351322412491,
-0.033406853675842285,
-0.03278816491365433,
-0.026197051629424095,
-0.03106215037405491,
0.03855760395526886,
0.13395880162715912,
-0.10541674494743347,
0.06484406441450119,
0.026988768950104713,
0.03590334951877594,
-0.12221841514110565,
0.13048674166202545,
-0.07050258666276932,
-0.04816795513033867,
0.01882232539355755,
0.11528560519218445,
0.04596392437815666,
-0.00773793738335371,
-0.07522047311067581,
0.026788176968693733,
0.07661419361829758,
0.03260671719908714,
-0.036909256130456924,
0.0402994379401207,
-0.060658834874629974,
0.013697639107704163,
0.026986951008439064,
-0.1020180881023407,
0.02504362352192402,
0.019244695082306862,
-0.07319702953100204,
-0.06981531530618668,
0.011560743674635887,
-0.0019498898182064295,
0.010763904079794884,
0.08599154651165009,
-0.09174560755491257,
0.016398241743445396,
-0.09076926857233047,
-0.1118386909365654,
0.01632138527929783,
-0.08697438985109329,
-0.008735429495573044,
-0.06994204968214035,
-0.19261863827705383,
-0.03138917684555054,
0.05875756964087486,
-0.060841020196676254,
-0.017543770372867584,
-0.053544119000434875,
-0.10411909967660904,
0.021451013162732124,
-0.005113399587571621,
0.13510483503341675,
-0.0786614716053009,
0.11208058893680573,
0.010548916645348072,
0.06601561605930328,
-0.028870925307273865,
0.03253467008471489,
-0.08473377674818039,
0.05231025442481041,
-0.17705848813056946,
0.02149585820734501,
-0.07631748914718628,
0.057162512093782425,
-0.1243847981095314,
-0.06583517044782639,
-0.01364020723849535,
-0.010668310336768627,
0.111235111951828,
0.13017135858535767,
-0.23274165391921997,
-0.028106195852160454,
0.1526937633752823,
-0.0745835229754448,
-0.11133113503456116,
0.11471797525882721,
-0.04036830738186836,
0.03426719456911087,
0.04596804454922676,
0.20541219413280487,
0.0648505687713623,
-0.120878666639328,
0.0031174365431070328,
-0.006873628590255976,
0.06372865289449692,
-0.029545625671744347,
0.06277743726968765,
-0.014995008707046509,
0.026671741157770157,
0.018629426136612892,
-0.07077322155237198,
0.0383850559592247,
-0.09522421658039093,
-0.07969474792480469,
-0.05112062022089958,
-0.10149185359477997,
0.0214106272906065,
0.05466414988040924,
0.02546703815460205,
-0.1053866595029831,
-0.08524854481220245,
0.043304987251758575,
0.10451269894838333,
-0.06877454370260239,
0.022289790213108063,
-0.05705411732196808,
0.09591475129127502,
-0.03922336921095848,
-0.01995806396007538,
-0.15991376340389252,
-0.06172236427664757,
0.013642527163028717,
-0.0020748174283653498,
-0.019665800034999847,
-0.01760793663561344,
0.08652159571647644,
0.07776123285293579,
-0.06626386195421219,
-0.03366897255182266,
-0.023323198780417442,
0.00330065144225955,
-0.12222705781459808,
-0.23861902952194214,
-0.028704583644866943,
-0.03832286223769188,
0.11329744756221771,
-0.22838714718818665,
0.035956971347332,
0.00447676470503211,
0.08830360323190689,
0.03807765990495682,
-0.04481896385550499,
-0.012268037535250187,
0.04998859018087387,
-0.030813368037343025,
-0.08771736174821854,
0.05347101390361786,
-0.007529336493462324,
-0.06416741758584976,
-0.01970559172332287,
-0.1381787806749344,
0.1322815716266632,
0.1065688505768776,
0.05204543098807335,
-0.09777582436800003,
-0.0014243735931813717,
-0.06094231829047203,
-0.03719929978251457,
-0.05204778164625168,
0.02714937925338745,
0.10334008932113647,
0.014972753822803497,
0.12160864472389221,
-0.08313353359699249,
-0.04660304635763168,
0.03108944743871689,
-0.02134341187775135,
0.024307310581207275,
0.13961605727672577,
0.09525861591100693,
-0.0521845780313015,
0.13774962723255157,
0.1456996500492096,
-0.06970631331205368,
0.11827142536640167,
-0.05464531481266022,
-0.08124439418315887,
-0.03483419492840767,
0.04705005884170532,
0.012306716293096542,
0.16675667464733124,
-0.03349120914936066,
0.026979967951774597,
0.0012119906023144722,
0.018539514392614365,
0.004375076852738857,
-0.2219819277524948,
-0.041992902755737305,
0.015306769870221615,
-0.08644957840442657,
-0.020437462255358696,
-0.01426317822188139,
-0.01564548723399639,
0.10498810559511185,
-0.009552262723445892,
-0.09379836916923523,
0.0017423707759007812,
0.005117814056575298,
-0.067715585231781,
0.20216117799282074,
-0.0976172462105751,
-0.08211835473775864,
-0.08984621614217758,
-0.002546180272474885,
-0.03371206298470497,
-0.003566521918401122,
0.051140885800123215,
-0.06237836927175522,
-0.025596609339118004,
-0.1244613453745842,
-0.018291721120476723,
0.04195291921496391,
0.015356827527284622,
-0.003329047467559576,
-0.012421537190675735,
0.08541569113731384,
-0.10918194055557251,
0.0037455405108630657,
-0.04405210539698601,
-0.04993356764316559,
0.03141167759895325,
0.0566430389881134,
0.11670290678739548,
0.13817331194877625,
0.007486517075449228,
0.005817870609462261,
-0.02427847310900688,
0.23104070127010345,
-0.06815838813781738,
0.02360529638826847,
0.11943764984607697,
0.023575235158205032,
0.05827954784035683,
0.15948911011219025,
0.05752918869256973,
-0.1094389259815216,
0.007643640507012606,
0.05150483548641205,
-0.03412238880991936,
-0.21081209182739258,
-0.02782110497355461,
-0.03904718905687332,
-0.0074045248329639435,
0.07086494565010071,
0.04594289883971214,
-0.03856794163584709,
0.036130283027887344,
0.020357217639684677,
0.001296398346312344,
-0.007682792842388153,
0.05085073411464691,
0.03251863270998001,
0.034273236989974976,
0.10622958093881607,
-0.042507145553827286,
-0.007654769346117973,
0.04584355279803276,
0.014499792829155922,
0.24023647606372833,
-0.03555525839328766,
0.1286027580499649,
0.05667442828416824,
0.19650855660438538,
-0.026665814220905304,
0.04771718755364418,
-0.00978587195277214,
-0.04593191668391228,
-0.013304623775184155,
-0.05816547945141792,
-0.002849849173799157,
0.01892862468957901,
-0.07790501415729523,
0.062313199043273926,
-0.08060025423765182,
0.02702639438211918,
0.06164715439081192,
0.29297152161598206,
0.06904725730419159,
-0.32397526502609253,
-0.08579325675964355,
0.011129677295684814,
-0.013671711087226868,
-0.03239324316382408,
0.02361924573779106,
0.17999222874641418,
-0.040093500167131424,
0.02582157403230667,
-0.07064161449670792,
0.0753355324268341,
-0.0008315295563079417,
0.03296169266104698,
0.07251786440610886,
0.1359485238790512,
-0.01937549188733101,
0.04052889347076416,
-0.2678285539150238,
0.2977093458175659,
0.023277418687939644,
0.09903720766305923,
-0.02896147221326828,
-0.010953482240438461,
0.03352464362978935,
0.06043971702456474,
0.09858375787734985,
-0.007764453999698162,
-0.07928444445133209,
-0.1933586448431015,
-0.09776362776756287,
0.030285730957984924,
0.09596789628267288,
-0.03090490587055683,
0.09683098644018173,
-0.029728788882493973,
-0.004492514301091433,
0.06225603073835373,
-0.056407630443573,
-0.08599669486284256,
-0.06227659434080124,
-0.01756896823644638,
0.024003151804208755,
-0.05438666790723801,
-0.08208341151475906,
-0.08903983235359192,
-0.07950487732887268,
0.10036250948905945,
-0.0659317746758461,
-0.02803577110171318,
-0.12358181178569794,
0.05334499105811119,
0.11415597051382065,
-0.07726175338029861,
0.027329934760928154,
0.01757107302546501,
0.06449948996305466,
0.02880631387233734,
-0.043656811118125916,
0.11633756756782532,
-0.0734226256608963,
-0.1895834505558014,
-0.0655737817287445,
0.11656193435192108,
0.043573785573244095,
0.05479305982589722,
-0.017465345561504364,
0.03735078498721123,
-0.008130645379424095,
-0.0885307788848877,
0.04194621369242668,
0.030649537220597267,
0.057866670191287994,
-0.0013241247506812215,
-0.05717729404568672,
0.02070881985127926,
-0.0464647002518177,
-0.04784415662288666,
0.11128373444080353,
0.3165912330150604,
-0.10091520845890045,
0.05401626601815224,
0.0431610569357872,
-0.06624951213598251,
-0.2110350877046585,
0.05317796394228935,
0.057292185723781586,
0.00944624561816454,
0.07934844493865967,
-0.14733049273490906,
0.06935887038707733,
0.12904010713100433,
-0.026387551799416542,
0.13819167017936707,
-0.3653810918331146,
-0.1298687756061554,
0.0777997151017189,
0.1484985649585724,
0.0765797570347786,
-0.16338707506656647,
-0.03505514934659004,
-0.00031720998231321573,
-0.09929274022579193,
0.0594271756708622,
-0.1307573765516281,
0.11123164743185043,
-0.019210638478398323,
0.036895304918289185,
0.009169877506792545,
-0.06329719722270966,
0.1442103087902069,
-0.012525679543614388,
0.12426826357841492,
-0.03454165533185005,
0.013486433774232864,
0.051088541746139526,
-0.06274411082267761,
0.0360642671585083,
-0.11270566284656525,
0.05316305533051491,
-0.04752416908740997,
-0.0024050285574048758,
-0.08503555506467819,
0.031483158469200134,
-0.03847875818610191,
-0.052597567439079285,
-0.03933410346508026,
0.04158793017268181,
0.052434369921684265,
-0.026240313425660133,
0.11199025809764862,
0.0012424973538145423,
0.142497256398201,
0.1271665245294571,
0.031218145042657852,
-0.05520399287343025,
-0.06267303228378296,
0.014296610839664936,
-0.020738359540700912,
0.04245840758085251,
-0.17076855897903442,
0.021988525986671448,
0.13167734444141388,
0.030260376632213593,
0.1182013526558876,
0.057232704013586044,
-0.04858441278338432,
0.011522487737238407,
0.06544078886508942,
-0.1520419865846634,
-0.15278367698192596,
0.01931631565093994,
-0.03037109784781933,
-0.11561942100524902,
0.04584755748510361,
0.10947838425636292,
-0.07167188823223114,
0.00564573472365737,
-0.0055548688396811485,
0.04894018545746803,
-0.03421716019511223,
0.23335112631320953,
0.04978657886385918,
0.05315309762954712,
-0.09309332817792892,
0.08600326627492905,
0.026377705857157707,
-0.0751553475856781,
0.02226826921105385,
0.07389935106039047,
-0.08790519088506699,
-0.030594872310757637,
0.1087450310587883,
0.14016103744506836,
-0.007267711218446493,
-0.03361114487051964,
-0.14961254596710205,
-0.10295584797859192,
0.06319976598024368,
0.18594613671302795,
0.07232091575860977,
0.028088219463825226,
-0.01142170000821352,
-0.0004273106169421226,
-0.1077888011932373,
0.11143232882022858,
0.05939944460988045,
0.07519795000553131,
-0.13884593546390533,
0.13399280607700348,
-0.008318349719047546,
0.000004055003955727443,
-0.01933150552213192,
0.05508235841989517,
-0.1102074384689331,
0.0033531959634274244,
-0.1419214904308319,
-0.009538445621728897,
-0.02977212704718113,
-0.004262569360435009,
-0.002263697562739253,
-0.05721515417098999,
-0.05914054811000824,
0.025882529094815254,
-0.10900639742612839,
-0.03197014331817627,
0.01091773808002472,
0.04999880492687225,
-0.13958796858787537,
-0.031508635729551315,
0.025791864842176437,
-0.07303023338317871,
0.07131104916334152,
0.024270018562674522,
0.023599034175276756,
0.048110198229551315,
-0.17900638282299042,
0.01476525329053402,
0.04191206023097038,
-0.007897238247096539,
0.05060102790594101,
-0.10529312491416931,
-0.02460097335278988,
-0.02669571340084076,
0.03193880245089531,
0.015160322189331055,
0.08005944639444351,
-0.12946480512619019,
0.009567144326865673,
-0.044400688260793686,
-0.04531795158982277,
-0.053945913910865784,
0.02905193343758583,
0.0877954438328743,
0.034218594431877136,
0.17164772748947144,
-0.09716492146253586,
0.014724423177540302,
-0.2161412090063095,
-0.010035015642642975,
-0.00955839641392231,
-0.09779966622591019,
-0.13008102774620056,
-0.016868287697434425,
0.08722960948944092,
-0.05934382602572441,
0.08020825684070587,
-0.008857585489749908,
0.022234804928302765,
0.036636944860219955,
-0.05669756978750229,
0.00368353258818388,
0.02745288796722889,
0.17556655406951904,
0.004753472749143839,
-0.028491416946053505,
0.04847134277224541,
0.037426695227622986,
0.08403347432613373,
0.10732100903987885,
0.20725318789482117,
0.16764000058174133,
0.01386652234941721,
0.09273742884397507,
0.03279196098446846,
-0.10058239847421646,
-0.11777705699205399,
0.11827380955219269,
-0.06942548602819443,
0.1022256389260292,
-0.0401417538523674,
0.20384016633033752,
0.1099783405661583,
-0.1858300119638443,
0.030774010345339775,
-0.0650506243109703,
-0.0909532681107521,
-0.11344882845878601,
-0.05035523325204849,
-0.08097639679908752,
-0.14904995262622833,
-0.0012602743227034807,
-0.1039901152253151,
0.04893392696976662,
0.12802331149578094,
0.016032176092267036,
0.020693710073828697,
0.16204652190208435,
0.04141627252101898,
0.03343015909194946,
0.038848746567964554,
0.02830597758293152,
-0.03468387573957443,
-0.06629651039838791,
-0.09557923674583435,
0.02882026694715023,
-0.05601926147937775,
0.0290061105042696,
-0.041154202073812485,
-0.032721925526857376,
0.049812451004981995,
-0.013246762566268444,
-0.09120294451713562,
0.01953435316681862,
0.01906321384012699,
0.04986604303121567,
0.053639598190784454,
0.04487088695168495,
0.0030044771265238523,
-0.009918495081365108,
0.2688262462615967,
-0.08254087716341019,
-0.06256882101297379,
-0.1108451634645462,
0.25629085302352905,
0.03303191810846329,
-0.0025333778467029333,
0.01468147523701191,
-0.09293311834335327,
0.007462908048182726,
0.17917382717132568,
0.1768927127122879,
-0.10005885362625122,
-0.01069665513932705,
-0.02620324306190014,
-0.010104803368449211,
-0.05587133392691612,
0.10349943488836288,
0.11023712903261185,
0.046936288475990295,
-0.09241914004087448,
-0.04307785630226135,
-0.04246474802494049,
-0.021913964301347733,
-0.06467383354902267,
0.05789680778980255,
0.00454884534701705,
0.01757507584989071,
-0.05166321247816086,
0.06437616795301437,
-0.025414464995265007,
-0.1534799188375473,
0.05716896429657936,
-0.18962158262729645,
-0.1650739461183548,
-0.0243960190564394,
0.1034087985754013,
-0.0012020122958347201,
0.04733884334564209,
-0.030923157930374146,
0.017596973106265068,
0.07070256024599075,
-0.03870224952697754,
-0.0533783994615078,
-0.11317222565412521,
0.06907147914171219,
-0.09126577526330948,
0.23792113363742828,
-0.037606120109558105,
0.0209263376891613,
0.12004803866147995,
0.02666371501982212,
-0.12303250283002853,
0.08844810724258423,
0.06071237474679947,
-0.09374338388442993,
0.012211923487484455,
0.09909026324748993,
-0.04769185930490494,
0.09829112142324448,
0.044738758355379105,
-0.0927252545952797,
0.007994379848241806,
-0.04540664702653885,
-0.06305988132953644,
-0.05053095892071724,
-0.04129107668995857,
-0.044011496007442474,
0.13888181746006012,
0.18741343915462494,
-0.03780386596918106,
0.03328244388103485,
-0.06391502171754837,
0.02869391068816185,
0.057761840522289276,
0.07105231285095215,
-0.02237936109304428,
-0.23827925324440002,
0.04287334904074669,
0.04258336126804352,
-0.016140300780534744,
-0.2225101888179779,
-0.09668194502592087,
0.007813404314219952,
-0.048947472125291824,
-0.08030106872320175,
0.10199730098247528,
0.10810016840696335,
0.059131260961294174,
-0.054657552391290665,
-0.07793007791042328,
-0.06256451457738876,
0.1610645204782486,
-0.12877638638019562,
-0.08582086861133575
] |
null | null | transformers |
注意：此模型的结构为Qwen2.
注意2：由于qwen2的llama.cpp支持（转换gguf或推理部分）存在问题（质量严重下滑，退化等），使用transformers/vllm推理则没有这个问题，因此在llama.cpp解决这个问题之前，先只发布hf格式的全量模型 | {"license": "gpl-3.0"} | text-generation | SakuraLLM/Sakura-1B8-Qwen2beta-v0.9 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"license:gpl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:18:22+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us
|
注意：此模型的结构为Qwen2.
注意2：由于qwen2的llama.cpp支持（转换gguf或推理部分）存在问题（质量严重下滑，退化等），使用transformers/vllm推理则没有这个问题，因此在llama.cpp解决这个问题之前，先只发布hf格式的全量模型 | [] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us \n"
] | [
51
] | [
"passage: TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us \n"
] | [
-0.03477787598967552,
0.075380839407444,
-0.004925156943500042,
0.025683850049972534,
0.07712317258119583,
-0.0252146627753973,
0.1696764975786209,
0.10786139219999313,
0.030668020248413086,
-0.06683797389268875,
0.16204047203063965,
0.1682228446006775,
-0.021553101018071175,
0.09187246114015579,
-0.10045748949050903,
-0.1744309663772583,
0.1029253676533699,
-0.0032071059104055166,
0.0076133920811116695,
0.08735236525535583,
0.11980511993169785,
-0.048379652202129364,
0.07232208549976349,
-0.02114902436733246,
-0.11894071847200394,
0.004727814346551895,
0.06479175388813019,
-0.12040004134178162,
0.10823138058185577,
0.07677730917930603,
0.06349777430295944,
0.1327531337738037,
-0.0055161649361252785,
-0.24388115108013153,
0.02913178689777851,
-0.04176304116845131,
-0.10808764398097992,
0.010235046036541462,
0.03972037136554718,
-0.00456297118216753,
-0.007828802801668644,
0.0769670158624649,
-0.03419465199112892,
0.09288904070854187,
-0.10364923626184464,
-0.06196272000670433,
-0.08391312509775162,
0.0724562406539917,
0.06319436430931091,
0.07438966631889343,
-0.0003128639655187726,
0.16686944663524628,
-0.06766875088214874,
0.09464821219444275,
0.0961150974035263,
-0.4631839394569397,
0.02337581291794777,
0.13381581008434296,
0.098186194896698,
0.006782762706279755,
-0.04175495728850365,
0.08549120277166367,
0.05994658172130585,
-0.020902767777442932,
-0.008156043477356434,
-0.07282650470733643,
-0.07202853262424469,
0.03787025064229965,
-0.05595618858933449,
-0.006453802343457937,
0.19670085608959198,
0.004246714524924755,
-0.006807350087910891,
-0.0694989264011383,
-0.06174640730023384,
0.005508250556886196,
0.0052517675794661045,
0.001329958438873291,
-0.01247912086546421,
0.10085568577051163,
-0.034428671002388,
-0.04162449389696121,
-0.1449207216501236,
-0.0032910965383052826,
-0.20273125171661377,
0.16335098445415497,
0.013963096775114536,
0.0581454373896122,
-0.14440199732780457,
0.04803965613245964,
-0.05079994723200798,
-0.10682810842990875,
-0.0664772316813469,
-0.1289064884185791,
0.0823211744427681,
0.007002169266343117,
-0.021460913121700287,
0.027535168454051018,
0.1663585901260376,
0.19630125164985657,
-0.0023236474953591824,
0.02664228342473507,
-0.029716171324253082,
0.0838610902428627,
-0.02853134274482727,
0.0684279277920723,
0.07655566930770874,
-0.058254171162843704,
0.12771089375019073,
-0.09612803906202316,
0.059056345373392105,
-0.030634108930826187,
-0.1759064644575119,
-0.00994843989610672,
-0.025971556082367897,
0.13015685975551605,
0.02585999108850956,
0.09506205469369888,
-0.0195968858897686,
0.058890245854854584,
0.14374051988124847,
-0.02290198765695095,
-0.02716846950352192,
0.005225758999586105,
0.05897535756230354,
-0.02496372163295746,
0.021164387464523315,
0.08989336341619492,
-0.014180527999997139,
0.018863394856452942,
-0.02150571718811989,
-0.06219681724905968,
0.016358111053705215,
-0.03818078339099884,
0.05815279856324196,
0.008529236540198326,
0.06636368483304977,
-0.21762803196907043,
-0.14782947301864624,
0.03419014811515808,
-0.002234199084341526,
0.008266948163509369,
-0.06963492929935455,
-0.017274701967835426,
-0.019174130633473396,
0.011162935756146908,
-0.09088680893182755,
-0.09803617000579834,
-0.08257977664470673,
0.08174166828393936,
0.01594681851565838,
0.031122392043471336,
-0.22489336133003235,
0.01861736923456192,
-0.0976838544011116,
0.0035010227002203465,
0.037904273718595505,
0.019510652869939804,
-0.07281716912984848,
0.1500920057296753,
0.012791221961379051,
0.0024369703605771065,
-0.014191088266670704,
0.040020834654569626,
-0.03491278365254402,
0.16337984800338745,
-0.07791659981012344,
-0.032530661672353745,
0.2767113447189331,
-0.12555746734142303,
-0.25826433300971985,
0.10617199540138245,
0.0009032915695570409,
0.02340700849890709,
0.09156516939401627,
0.21251976490020752,
0.05746015906333923,
-0.09369057416915894,
0.01977658085525036,
0.12656529247760773,
-0.11487043648958206,
-0.11431402713060379,
0.032441094517707825,
-0.0006642975495196879,
-0.10077694803476334,
0.04505832493305206,
0.015668023377656937,
0.08849336206912994,
-0.03169703111052513,
-0.0696944147348404,
-0.06823120266199112,
-0.07208036631345749,
0.029472757130861282,
-0.05077680945396423,
0.044692620635032654,
-0.10354061424732208,
-0.011846495792269707,
-0.06316403299570084,
-0.0004604141286108643,
0.0132211372256279,
0.017587952315807343,
-0.12129629403352737,
0.07021187245845795,
0.018073370680212975,
0.044619183987379074,
-0.05232618376612663,
-0.1277010589838028,
0.0034739424008876085,
0.04909585788846016,
0.0368802584707737,
0.06088985130190849,
0.05051443353295326,
0.007477947045117617,
-0.021875424310564995,
-0.03981034830212593,
0.15011616051197052,
0.053846824914216995,
-0.05719911679625511,
-0.06312774866819382,
0.08654089272022247,
-0.06056858226656914,
0.005224333144724369,
-0.07328779995441437,
0.012911439873278141,
0.08543684333562851,
0.06126375123858452,
-0.002113532042130828,
0.08123568445444107,
-0.029220517724752426,
-0.0014730144757777452,
-0.06439177691936493,
0.013122170232236385,
0.10484325885772705,
0.047869373112916946,
-0.12368318438529968,
0.2369868904352188,
-0.1836749017238617,
0.30796223878860474,
0.18129384517669678,
-0.16509808599948883,
0.0548420250415802,
-0.09742695093154907,
-0.027254100888967514,
0.0034573294688016176,
0.017969464883208275,
0.018013373017311096,
0.02843068540096283,
-0.01362807396799326,
0.1494215875864029,
-0.07360633462667465,
-0.03048701211810112,
-0.006242403294891119,
-0.07018519937992096,
-0.03502665087580681,
0.04556170850992203,
0.0745590478181839,
-0.19742894172668457,
0.15247680246829987,
0.2631102204322815,
0.06126914918422699,
0.13604453206062317,
-0.01254183053970337,
0.06123607978224754,
0.02174469642341137,
0.03673897683620453,
-0.011964050121605396,
0.021085422486066818,
-0.11497893184423447,
-0.00157431501429528,
0.06188856437802315,
0.03735492751002312,
0.06213715672492981,
-0.13718067109584808,
-0.08937511593103409,
-0.0023691279347985983,
-0.054294392466545105,
-0.06627121567726135,
0.08828293532133102,
-0.032965969294309616,
0.1013750359416008,
-0.020433615893125534,
-0.05254491791129112,
0.131333127617836,
-0.022621609270572662,
-0.10458570718765259,
0.15192505717277527,
-0.13435803353786469,
-0.23767074942588806,
-0.15296360850334167,
-0.17409253120422363,
-0.08230128139257431,
0.0346016027033329,
0.17100790143013,
-0.06331802159547806,
-0.06711482256650925,
-0.015224729664623737,
-0.03784117102622986,
0.002011164790019393,
0.0198834128677845,
-0.018812866881489754,
0.05428006127476692,
-0.021194441244006157,
-0.12691530585289001,
-0.054282452911138535,
0.009157848544418812,
-0.08762309700250626,
0.11042331159114838,
-0.08800576627254486,
0.11669266223907471,
0.07563412934541702,
0.0012368251336738467,
0.03269580006599426,
-0.07083343714475632,
0.222764790058136,
-0.04243571683764458,
-0.013745598495006561,
0.19310735166072845,
-0.046605583280324936,
0.06281875818967819,
0.1785007119178772,
0.02018776349723339,
-0.0972200334072113,
0.05444023758172989,
-0.06178564205765724,
-0.09017198532819748,
-0.23226602375507355,
-0.09536495059728622,
-0.06461729854345322,
0.09995260834693909,
-0.036344096064567566,
0.07779534161090851,
0.09939759969711304,
0.09775533527135849,
-0.017659271135926247,
-0.03609027341008186,
0.04971528425812721,
0.10465560108423233,
0.25405895709991455,
-0.008440121077001095,
0.12582528591156006,
-0.11658471077680588,
-0.05265821889042854,
0.10760747641324997,
0.13092032074928284,
0.09663581103086472,
0.12601721286773682,
0.041699521243572235,
0.090172179043293,
0.1915346086025238,
0.14916415512561798,
0.07147964835166931,
0.047092072665691376,
-0.06434515863656998,
-0.0034559352789074183,
-0.023183878511190414,
-0.023419089615345,
0.054368142038583755,
-0.03576182574033737,
-0.12040235847234726,
-0.03973892331123352,
0.003580685006454587,
0.08672498911619186,
0.13803327083587646,
0.02543417364358902,
-0.10390164703130722,
-0.009004618972539902,
0.10688769072294235,
-0.006667027715593576,
-0.0385887511074543,
0.13463786244392395,
0.03114037960767746,
-0.10268715769052505,
0.11010716110467911,
-0.027475902810692787,
0.10277921706438065,
0.0026011462323367596,
0.0658898577094078,
-0.04711614549160004,
-0.11992933601140976,
0.026462381705641747,
0.13654479384422302,
-0.3340284824371338,
0.22229522466659546,
0.0032724428456276655,
0.011578175239264965,
-0.04240744188427925,
-0.023397527635097504,
0.02134457230567932,
0.1813199818134308,
0.1517971158027649,
-0.00752233387902379,
-0.09426873922348022,
-0.0865020602941513,
-0.014830529689788818,
0.06972215324640274,
0.1045079156756401,
0.0575295090675354,
-0.009186705574393272,
-0.06519388407468796,
0.0006505576311610639,
0.005630281288176775,
0.01729523576796055,
-0.08598408102989197,
-0.15067943930625916,
0.018290206789970398,
0.1235104352235794,
0.12540431320667267,
-0.06766389310359955,
0.018098773434758186,
-0.21205247938632965,
0.1813422441482544,
-0.16436193883419037,
-0.07602637261152267,
-0.08616180717945099,
-0.15374736487865448,
-0.0383852943778038,
-0.06574037671089172,
0.05674424767494202,
-0.06965754181146622,
0.01921004429459572,
-0.0984550416469574,
-0.18740308284759521,
0.11249858140945435,
-0.13781243562698364,
-0.09185820817947388,
-0.02826118841767311,
0.13947948813438416,
-0.09589826315641403,
-0.0026655823457986116,
0.07271509617567062,
-0.005489434115588665,
-0.09110986441373825,
-0.1567102074623108,
-0.007027891464531422,
-0.05790967866778374,
0.003318357514217496,
-0.05047530680894852,
-0.06936408579349518,
-0.07958617806434631,
-0.005701088346540928,
-0.08853266388177872,
0.265679270029068,
0.2771230638027191,
-0.08953061699867249,
0.16490188241004944,
0.2090049535036087,
-0.06037890538573265,
-0.32374337315559387,
-0.14937029778957367,
-0.15898078680038452,
-0.0758841261267662,
0.0011303696082904935,
-0.029659084975719452,
0.07524031400680542,
0.046423494815826416,
-0.06292913109064102,
0.047539081424474716,
-0.15159563720226288,
-0.10403411090373993,
0.14490287005901337,
0.019816016778349876,
0.31212517619132996,
-0.15993855893611908,
-0.09591855853796005,
-0.07121311873197556,
-0.23752273619174957,
0.15442825853824615,
-0.12137580662965775,
0.06968454271554947,
0.019034145399928093,
0.05755418911576271,
-0.011216566897928715,
-0.039770811796188354,
0.10868906229734421,
-0.04325666278600693,
0.03456064686179161,
-0.11783688515424728,
-0.023648694157600403,
0.0407126285135746,
-0.016336601227521896,
0.02493460476398468,
-0.11927549540996552,
0.051981206983327866,
-0.04396025463938713,
-0.038126543164253235,
-0.051509249955415726,
0.05424115061759949,
-0.003319773357361555,
-0.08308763802051544,
-0.019910506904125214,
-0.06705647706985474,
0.02961535006761551,
-0.007782287430018187,
0.24282115697860718,
-0.06126224622130394,
0.12712445855140686,
0.1627480387687683,
0.15564113855361938,
-0.18523311614990234,
0.06343525648117065,
-0.06919697672128677,
-0.1072561964392662,
0.0493166446685791,
-0.09104228764772415,
0.058254484087228775,
0.0952334776520729,
-0.06336076557636261,
0.06499653309583664,
0.08012430369853973,
0.0341145396232605,
0.053125929087400436,
0.13667261600494385,
-0.206730917096138,
-0.07998621463775635,
-0.04326091706752777,
0.10851586610078812,
0.10117363184690475,
0.12258068472146988,
0.1450648158788681,
0.000010371208190917969,
-0.021233119070529938,
-0.0167893934994936,
0.027695879340171814,
-0.07198478281497955,
0.02287096530199051,
0.05266718566417694,
0.016385922208428383,
-0.12730146944522858,
0.10011983662843704,
-0.03768235817551613,
-0.12076350301504135,
-0.003046375000849366,
0.09821408241987228,
-0.1586715579032898,
-0.12255062907934189,
-0.06637824326753616,
0.08737394213676453,
-0.20430609583854675,
-0.11205244809389114,
-0.021988162770867348,
-0.1629742681980133,
0.011331320740282536,
0.19786301255226135,
0.060461729764938354,
0.08343962579965591,
0.032579176127910614,
-0.028505586087703705,
-0.005486614070832729,
0.021245064213871956,
-0.07707379013299942,
0.04402177408337593,
-0.14075669646263123,
-0.038885269314050674,
-0.0345708429813385,
0.1262652575969696,
-0.08313530683517456,
-0.02576720155775547,
-0.15049469470977783,
0.022081119939684868,
-0.18761731684207916,
0.0049351355992257595,
-0.10117068886756897,
0.015946682542562485,
-0.013194771483540535,
-0.07940071821212769,
-0.038355834782123566,
-0.0024219637271016836,
-0.09262367337942123,
0.01325409859418869,
-0.006941735744476318,
0.030686283484101295,
-0.09720687568187714,
-0.011717895045876503,
0.04394155368208885,
0.009145562537014484,
0.14200396835803986,
0.04042861983180046,
-0.09307955205440521,
0.08786641061306,
-0.19873154163360596,
-0.0478888675570488,
0.0850069671869278,
0.01067102700471878,
0.03734318166971207,
0.0790848359465599,
-0.00011062242992920801,
0.12400440126657486,
-0.015698250383138657,
0.06396082788705826,
0.09209812432527542,
-0.11565764993429184,
0.010515561327338219,
-0.03934178873896599,
-0.08366337418556213,
-0.01753235049545765,
-0.10462284088134766,
0.07639560848474503,
-0.020471997559070587,
0.18205344676971436,
-0.09938120096921921,
0.021016893908381462,
-0.040300071239471436,
0.01893310248851776,
0.031042208895087242,
-0.147023543715477,
-0.16907158493995667,
-0.05588752031326294,
-0.022120937705039978,
-0.00533290347084403,
0.30519139766693115,
-0.05908031761646271,
-0.029506897553801537,
0.08774411678314209,
0.018484914675354958,
0.007747679017484188,
-0.014717936515808105,
0.2595593333244324,
0.0632062777876854,
-0.010576861910521984,
-0.12011208385229111,
0.04045820236206055,
0.0043406118638813496,
-0.18243330717086792,
0.08283229917287827,
0.056318070739507675,
-0.028465721756219864,
0.0849573165178299,
0.08005692064762115,
0.02338164858520031,
-0.08780499547719955,
-0.16855980455875397,
-0.05092160776257515,
0.026855936273932457,
-0.04841485619544983,
0.022297140210866928,
0.18772652745246887,
-0.0172745268791914,
-0.023635603487491608,
-0.05442046746611595,
-0.020168405026197433,
-0.17997977137565613,
-0.10915927588939667,
-0.11644235253334045,
-0.13117597997188568,
0.037146586924791336,
-0.08106116205453873,
0.02823769487440586,
0.023845624178647995,
0.06710821390151978,
-0.0679633840918541,
0.05166193097829819,
-0.06457974016666412,
-0.0314398817718029,
0.007983716204762459,
-0.02113492786884308,
0.03429330512881279,
0.019572574645280838,
-0.03133684769272804,
-0.07482488453388214,
-0.03611236438155174,
-0.04434259608387947,
0.08908895403146744,
-0.009426972828805447,
0.0348144993185997,
-0.12478519231081009,
-0.05536596104502678,
-0.05209506303071976,
0.10413568466901779,
-0.00030074172536842525,
0.1540076732635498,
0.012039356864988804,
0.00967292208224535,
0.08880288898944855,
0.20087291300296783,
-0.05621742457151413,
-0.15707747638225555,
-0.0552852489054203,
0.12194255739450455,
0.009342169389128685,
0.14207710325717926,
-0.031810689717531204,
-0.0015448792837560177,
-0.022786155343055725,
0.3484848737716675,
0.2724304497241974,
-0.08009026199579239,
0.052659772336483,
-0.04034177213907242,
0.0428108386695385,
0.07240435481071472,
0.13193802535533905,
0.09534380584955215,
0.2841408848762512,
-0.06770218908786774,
-0.05742249637842178,
-0.01139766164124012,
0.02403719164431095,
-0.10622616112232208,
0.10849850624799728,
-0.02641632780432701,
-0.03860248997807503,
-0.05317287892103195,
0.09551717340946198,
-0.15669699013233185,
0.17980533838272095,
-0.09534482657909393,
-0.10988982766866684,
-0.013406404294073582,
0.006524990778416395,
0.16398756206035614,
0.00509880343452096,
0.02230658568441868,
-0.01697954349219799,
-0.056173551827669144,
0.06045127287507057,
-0.013207479380071163,
-0.18918056786060333,
0.03382077440619469,
0.05058916285634041,
0.03532322496175766,
0.10823970288038254,
0.01664798893034458,
0.06968185305595398,
0.08248968422412872,
0.04947509244084358,
-0.07605055719614029,
0.167915478348732,
0.03022458590567112,
-0.1258201152086258,
-0.005162604618817568,
-0.07666230946779251,
0.002814072882756591,
0.01211383007466793,
0.0434877872467041,
-0.11577143520116806,
0.07345353811979294,
0.03488503769040108,
-0.07987688481807709,
-0.04741011932492256,
0.07391106337308884,
-0.05424671992659569,
0.08279623836278915,
-0.006832799408584833,
-0.032168198376894,
-0.011500255204737186,
-0.018862061202526093,
0.03094382770359516,
0.014128531329333782,
-0.10356061160564423,
-0.02410450577735901,
-0.09910768270492554,
-0.025552896782755852,
0.10533769428730011,
0.011912774294614792,
-0.18324778974056244,
-0.017734451219439507,
-0.11202482134103775,
0.07814271748065948,
-0.1466473489999771,
0.08421602845191956,
0.18313293159008026,
0.011649399064481258,
-0.02042359486222267,
-0.11944251507520676,
0.030459698289632797,
0.049708109349012375,
-0.0704386904835701,
-0.13651061058044434
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# german-party-sentiment-bert-complete-synonyms-5e-5
This model is a fine-tuned version of [mdraw/german-news-sentiment-bert](https://huggingface.co/mdraw/german-news-sentiment-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8769
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 20
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 120
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9596 | 1.0 | 70 | 0.9676 |
| 0.9122 | 2.0 | 140 | 0.8769 |
| 0.7382 | 3.0 | 210 | 0.9984 |
| 0.5708 | 4.0 | 280 | 1.1080 |
| 0.3579 | 5.0 | 350 | 1.4137 |
| 0.3066 | 6.0 | 420 | 1.8204 |
| 0.1716 | 7.0 | 490 | 1.8167 |
| 0.1974 | 8.0 | 560 | 2.1479 |
| 0.1164 | 9.0 | 630 | 2.3899 |
| 0.0878 | 10.0 | 700 | 2.5266 |
| 0.07 | 11.0 | 770 | 2.7014 |
| 0.0604 | 12.0 | 840 | 2.7048 |
| 0.0278 | 13.0 | 910 | 2.8119 |
| 0.0376 | 14.0 | 980 | 2.8799 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Tokenizers 0.15.1
| {"tags": ["generated_from_trainer"], "base_model": "mdraw/german-news-sentiment-bert", "model-index": [{"name": "german-party-sentiment-bert-complete-synonyms-5e-5", "results": []}]} | text-classification | Commandante/german-party-sentiment-bert-complete-synonyms-5e-5 | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:mdraw/german-news-sentiment-bert",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:21:11+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-mdraw/german-news-sentiment-bert #autotrain_compatible #endpoints_compatible #region-us
| german-party-sentiment-bert-complete-synonyms-5e-5
==================================================
This model is a fine-tuned version of mdraw/german-news-sentiment-bert on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8769
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 20
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 120
* num\_epochs: 14
### Training results
### Framework versions
* Transformers 4.37.2
* Pytorch 2.2.0+cu121
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 20\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 120\n* num\\_epochs: 14",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.2.0+cu121\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-mdraw/german-news-sentiment-bert #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 20\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 120\n* num\\_epochs: 14",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.2.0+cu121\n* Tokenizers 0.15.1"
] | [
61,
116,
4,
27
] | [
"passage: TAGS\n#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-mdraw/german-news-sentiment-bert #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 20\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 120\n* num\\_epochs: 14### Training results### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.2.0+cu121\n* Tokenizers 0.15.1"
] | [
-0.09882110357284546,
0.03095289319753647,
-0.0013701800489798188,
0.09915097802877426,
0.1508750021457672,
0.01300485897809267,
0.13450652360916138,
0.08011055737733841,
-0.06737196445465088,
0.041405901312828064,
0.12508103251457214,
0.1153736561536789,
-0.018169892951846123,
0.13068298995494843,
-0.06989467144012451,
-0.27178695797920227,
0.014945277944207191,
0.010073944926261902,
-0.05792444199323654,
0.1170424297451973,
0.08914732187986374,
-0.14049743115901947,
0.08904970437288284,
-0.02475779689848423,
-0.15378279983997345,
0.041594263166189194,
0.032282523810863495,
-0.046734120696783066,
0.15542802214622498,
0.01598723977804184,
0.11826572567224503,
0.029145628213882446,
0.10438433289527893,
-0.18832722306251526,
0.016472382470965385,
0.03538639098405838,
-0.0015459461137652397,
0.06744814664125443,
0.054405007511377335,
-0.03411222621798515,
0.1044975221157074,
-0.12003777921199799,
0.04677509143948555,
0.009089059196412563,
-0.1401752531528473,
-0.1968877762556076,
-0.05871716886758804,
0.03617937117815018,
0.08780772238969803,
0.11319185048341751,
-0.031023317947983742,
0.1290881335735321,
-0.09930222481489182,
0.10974520444869995,
0.24273863434791565,
-0.2749308943748474,
-0.0733996257185936,
0.014738856814801693,
0.01762736402451992,
0.08714518696069717,
-0.1218462884426117,
0.004451169166713953,
0.07419176399707794,
0.022245431318879128,
0.09371822327375412,
-0.03620259091258049,
-0.04429056867957115,
0.00401628203690052,
-0.1445140838623047,
-0.012772684916853905,
0.09981723129749298,
0.04959363490343094,
-0.04106200486421585,
-0.034409839659929276,
-0.05183999612927437,
-0.1365649253129959,
-0.05572427436709404,
-0.02601645141839981,
0.03252580389380455,
-0.0437786839902401,
-0.08716347068548203,
0.007919161580502987,
-0.10386720299720764,
-0.06986581534147263,
-0.03820972889661789,
0.2620742619037628,
0.025146938860416412,
-0.01493978314101696,
0.0005560921272262931,
0.1074930727481842,
-0.04266311973333359,
-0.1533111184835434,
0.02487920969724655,
0.024248827248811722,
-0.007587661035358906,
-0.05604957416653633,
-0.07010098546743393,
-0.03393755853176117,
-0.008555651642382145,
0.11931966245174408,
-0.0968913733959198,
0.04997427389025688,
0.03667775169014931,
0.01094589103013277,
-0.08737685531377792,
0.18118873238563538,
-0.046380601823329926,
-0.045993465930223465,
-0.01752495765686035,
0.08099141716957092,
0.02048547752201557,
0.002480353694409132,
-0.10209756344556808,
0.020263247191905975,
0.10576886683702469,
0.018117882311344147,
-0.11475653201341629,
0.10035991668701172,
-0.047360606491565704,
0.01852523535490036,
-0.005619404371827841,
-0.09779126942157745,
0.02367081120610237,
0.014393656514585018,
-0.07741876691579819,
-0.016265155747532845,
0.0012827941682189703,
0.015886547043919563,
0.011228391900658607,
0.15494567155838013,
-0.08504411578178406,
0.019504571333527565,
-0.08475644886493683,
-0.13636350631713867,
-0.004219468217343092,
-0.06281045079231262,
0.024348663166165352,
-0.11171810328960419,
-0.16937722265720367,
-0.014268595725297928,
0.04466213658452034,
-0.029795045033097267,
0.00285360193811357,
-0.08130982518196106,
-0.08015111088752747,
0.03243974596261978,
-0.0036129956133663654,
0.07069052010774612,
-0.07190769165754318,
0.09820921719074249,
0.04400976002216339,
0.08233747631311417,
-0.025756852701306343,
0.03462286666035652,
-0.13239231705665588,
0.016804536804556847,
-0.19859564304351807,
0.04942258819937706,
-0.07867753505706787,
0.07720353454351425,
-0.060220975428819656,
-0.08984139561653137,
0.016753774136304855,
0.032144445925951004,
0.0722760260105133,
0.14830155670642853,
-0.16261479258537292,
-0.09526167064905167,
0.15509450435638428,
-0.09472721815109253,
-0.08530779927968979,
0.11889590322971344,
-0.07278624176979065,
0.06357109546661377,
0.09776771813631058,
0.17095139622688293,
0.07060059905052185,
-0.11445704102516174,
0.010231678374111652,
-0.01765436679124832,
0.04319696128368378,
0.04309787601232529,
0.04000278189778328,
0.04204154387116432,
-0.06507696211338043,
0.02747020311653614,
-0.05133620277047157,
0.06342915445566177,
-0.09960997104644775,
-0.06846288591623306,
-0.015015915036201477,
-0.09752828627824783,
0.11237338930368423,
0.056339070200920105,
0.06711018085479736,
-0.14579631388187408,
-0.0867614895105362,
0.059305232018232346,
0.07708361744880676,
-0.05102216452360153,
0.0013452393468469381,
-0.05428343266248703,
0.021790264174342155,
-0.022597989067435265,
-0.012632278725504875,
-0.1532995104789734,
-0.046177592128515244,
0.003670354140922427,
0.03545154631137848,
0.0338425375521183,
0.029497768729925156,
0.09992073476314545,
0.07204332202672958,
-0.08331814408302307,
-0.053940799087285995,
-0.02430531196296215,
0.011361717246472836,
-0.10735374689102173,
-0.21793730556964874,
0.01681210845708847,
-0.03877658769488335,
0.13117919862270355,
-0.22665396332740784,
0.02650669403374195,
-0.004839188884943724,
0.08456788957118988,
0.04155007749795914,
0.007876892574131489,
-0.044252585619688034,
0.06568372994661331,
-0.03650834783911705,
-0.030568353831768036,
0.042088355869054794,
-0.02181975543498993,
-0.0714004635810852,
-0.0055990321561694145,
-0.145100399851799,
0.19159695506095886,
0.11660360544919968,
-0.10191678255796432,
-0.11786266416311264,
-0.0005521741113625467,
-0.051534585654735565,
-0.011629337444901466,
-0.05510466918349266,
0.0029954768251627684,
0.15811048448085785,
-0.021433843299746513,
0.13343043625354767,
-0.06509893387556076,
-0.032761819660663605,
0.022181499749422073,
-0.05013655871152878,
0.009711593389511108,
0.13918407261371613,
0.03438346087932587,
-0.11906686425209045,
0.14210861921310425,
0.174163818359375,
-0.10009484738111496,
0.17422835528850555,
-0.01521990168839693,
-0.05382995679974556,
-0.0174767654389143,
-0.013735148124396801,
-0.01456717774271965,
0.10817023366689682,
-0.08917218446731567,
-0.0020897851791232824,
-0.011953345499932766,
0.024099119007587433,
-0.006443502847105265,
-0.20127898454666138,
-0.051119279116392136,
0.040097687393426895,
-0.040956079959869385,
-0.007334851659834385,
-0.009478319436311722,
-0.00027477354160510004,
0.12406399101018906,
0.010587362572550774,
-0.09156223386526108,
0.022825196385383606,
0.00047005427768453956,
-0.08268309384584427,
0.2118985801935196,
-0.08184699714183807,
-0.1543368548154831,
-0.11714258790016174,
-0.06875213235616684,
-0.05878491327166557,
0.038407374173402786,
0.06026972457766533,
-0.13044379651546478,
-0.033984676003456116,
-0.08528496325016022,
0.04892868176102638,
0.052667293697595596,
0.04220195859670639,
-0.011573772877454758,
-0.010478510521352291,
0.06898809969425201,
-0.08675142377614975,
-0.01417272537946701,
-0.06579115241765976,
-0.042727530002593994,
0.03530745953321457,
0.028415247797966003,
0.11598517745733261,
0.1352011114358902,
-0.027157030999660492,
-0.00020114201470278203,
-0.028987685218453407,
0.24313336610794067,
-0.09349795430898666,
-0.008283033967018127,
0.10174436867237091,
-0.04220491647720337,
0.03507881239056587,
0.16259799897670746,
0.06060538440942764,
-0.10415546596050262,
0.04569842293858528,
0.04786719009280205,
-0.021781137213110924,
-0.18413519859313965,
-0.05346493422985077,
-0.015500478446483612,
0.0001003588258754462,
0.08911633491516113,
0.021868664771318436,
0.02411683462560177,
0.06686532497406006,
0.016091756522655487,
0.022664083167910576,
-0.011821756139397621,
0.05796827748417854,
0.09368335455656052,
0.03715356066823006,
0.1128171756863594,
-0.037430960685014725,
-0.11192384362220764,
0.04067714884877205,
-0.05208941549062729,
0.15537959337234497,
0.013049136847257614,
0.07565420866012573,
0.022787919268012047,
0.11968860775232315,
0.01101262029260397,
0.09622050821781158,
0.009212549775838852,
-0.08461889624595642,
-0.006782896816730499,
-0.051393669098615646,
-0.028565527871251106,
0.05316643416881561,
-0.07558039575815201,
0.071006178855896,
-0.13634875416755676,
-0.009483384899795055,
0.07726463675498962,
0.2327941209077835,
0.06658681482076645,
-0.3194001317024231,
-0.10653934627771378,
0.010486392304301262,
-0.04629029706120491,
-0.011683267541229725,
0.029451165348291397,
0.13288487493991852,
-0.0635068267583847,
0.052894119173288345,
-0.04176386073231697,
0.07154644280672073,
-0.042741794139146805,
0.07202523201704025,
0.026908939704298973,
0.08748289197683334,
-0.03519156202673912,
0.06501305848360062,
-0.27284204959869385,
0.3077945411205292,
0.007988929748535156,
0.06762850284576416,
-0.055956922471523285,
-0.03323391452431679,
0.05458154156804085,
0.10558563470840454,
0.06885241717100143,
-0.01587422750890255,
-0.06590566039085388,
-0.2228749543428421,
-0.04296116158366203,
0.02588389627635479,
0.14339029788970947,
-0.05942757800221443,
0.11700006574392319,
-0.03446042537689209,
-0.02231786958873272,
0.08490525931119919,
-0.05973157286643982,
-0.11212408542633057,
-0.05404696241021156,
-0.027707912027835846,
0.03338799998164177,
0.023769520223140717,
-0.0640229657292366,
-0.1272226870059967,
-0.12166781723499298,
0.13654665648937225,
0.00614931620657444,
-0.001977141946554184,
-0.12719044089317322,
0.06343900412321091,
0.039569735527038574,
-0.08415983617305756,
0.022712083533406258,
0.029100364074110985,
0.09287390112876892,
0.017693402245640755,
-0.05302254483103752,
0.14580459892749786,
-0.08877196907997131,
-0.1939607709646225,
-0.05619533360004425,
0.11578181385993958,
0.06997792422771454,
0.0493323989212513,
-0.0007687457255087793,
0.01298553217202425,
0.005406506825238466,
-0.08433207869529724,
0.04278979450464249,
-0.04579133912920952,
0.011338833719491959,
0.05229703336954117,
-0.06804884970188141,
-0.026090048253536224,
-0.06937187910079956,
-0.010481595993041992,
0.15469500422477722,
0.31516700983047485,
-0.09166613966226578,
-0.007448400370776653,
0.08603370189666748,
-0.03887958079576492,
-0.25227364897727966,
0.07175053656101227,
0.06051815673708916,
0.007879571989178658,
0.057103414088487625,
-0.12838387489318848,
0.11176000535488129,
0.08713134378194809,
-0.01599694974720478,
0.06873650848865509,
-0.24807119369506836,
-0.13750886917114258,
0.14124880731105804,
0.1471879929304123,
0.15574631094932556,
-0.1250249743461609,
-0.008174790069460869,
-0.03925326094031334,
-0.057722486555576324,
0.08772916346788406,
-0.1048404723405838,
0.10576868802309036,
0.008743688464164734,
0.08530960232019424,
0.020493432879447937,
-0.048262886703014374,
0.117836594581604,
0.007663079537451267,
0.13119909167289734,
-0.07550779730081558,
-0.041790902614593506,
0.0030973064713180065,
-0.04730604588985443,
0.031084813177585602,
-0.09459839761257172,
0.03368076682090759,
-0.039627205580472946,
-0.0320340134203434,
-0.08756446093320847,
0.04747674986720085,
-0.03939112275838852,
-0.08034177869558334,
-0.034918442368507385,
0.04158638417720795,
0.03548955172300339,
-0.019135762006044388,
0.12337957322597504,
-0.03246027231216431,
0.14650948345661163,
0.11291882395744324,
0.10564233362674713,
-0.03930342197418213,
0.0081447409465909,
0.020937327295541763,
-0.029988212510943413,
0.06211608275771141,
-0.12455493956804276,
0.04730844870209694,
0.12571825087070465,
0.016084181144833565,
0.1547127366065979,
0.07329284399747849,
-0.021180467680096626,
0.006964350119233131,
0.07571950554847717,
-0.19552810490131378,
-0.07363442331552505,
-0.04123459756374359,
-0.06805934756994247,
-0.08407505601644516,
0.06742747873067856,
0.1310495287179947,
-0.08320125192403793,
0.022242030128836632,
-0.020265134051442146,
-0.008552259765565395,
-0.04529904946684837,
0.19895392656326294,
0.05828928202390671,
0.04498172923922539,
-0.08743679523468018,
0.06510183960199356,
0.017218660563230515,
-0.11234904080629349,
0.01975569874048233,
0.09094494581222534,
-0.08750122785568237,
-0.050685781985521317,
0.06763571500778198,
0.20887109637260437,
-0.07271698862314224,
-0.04110918939113617,
-0.15652285516262054,
-0.13782818615436554,
0.0644773468375206,
0.21483059227466583,
0.1003178060054779,
-0.008975573815405369,
-0.04062149301171303,
0.034991033375263214,
-0.10951007902622223,
0.11801677197217941,
0.07059716433286667,
0.08030522614717484,
-0.13692225515842438,
0.1441587209701538,
-0.016570672392845154,
0.03087618015706539,
-0.04994405061006546,
0.022701771929860115,
-0.13553966581821442,
0.008301426656544209,
-0.16073574125766754,
-0.04671922326087952,
-0.011519117280840874,
0.012512866407632828,
-0.004005942028015852,
-0.07789679616689682,
-0.05564969405531883,
-0.008375835604965687,
-0.12008516490459442,
-0.0002434721973259002,
0.04104120284318924,
0.03838931769132614,
-0.11235059797763824,
-0.04417693242430687,
0.03490735590457916,
-0.0703234151005745,
0.0702424943447113,
0.04875488206744194,
0.009096026420593262,
0.08145944774150848,
-0.18396201729774475,
0.011939384043216705,
0.07625924795866013,
-0.02193831466138363,
0.06025298312306404,
-0.05129700526595116,
-0.006173533387482166,
-0.015927622094750404,
0.07552022486925125,
0.029534099623560905,
0.07402079552412033,
-0.10695014148950577,
0.06835861504077911,
0.009981897659599781,
-0.08699139207601547,
-0.06766262650489807,
0.015311403200030327,
0.05954020470380783,
-0.01733523979783058,
0.1970638781785965,
-0.12716391682624817,
0.03456667438149452,
-0.17293432354927063,
-0.00018094360711984336,
-0.00040138463373295963,
-0.14474649727344513,
-0.12938134372234344,
-0.06412992626428604,
0.07021887600421906,
-0.053785741329193115,
0.11962881684303284,
0.022744856774806976,
0.05799602344632149,
0.03879215195775032,
-0.05513511225581169,
0.040499068796634674,
0.039193522185087204,
0.17806614935398102,
0.03966333717107773,
-0.05091944709420204,
-0.008127545937895775,
0.060199491679668427,
0.11814707517623901,
0.07109593600034714,
0.2149970978498459,
0.1446777880191803,
-0.025533178821206093,
0.11608754098415375,
0.0395575612783432,
-0.044199347496032715,
-0.13727940618991852,
0.0012077527353540063,
-0.08498365432024002,
0.07879756391048431,
-0.02806798554956913,
0.20712529122829437,
0.10493268817663193,
-0.144741028547287,
0.02449186146259308,
-0.04925638437271118,
-0.06827455013990402,
-0.10051985830068588,
-0.03040226735174656,
-0.09938006848096848,
-0.17855983972549438,
0.00590541074052453,
-0.11146031320095062,
0.013994340784847736,
0.08219292014837265,
0.031700827181339264,
-0.018983693793416023,
0.22732600569725037,
-0.013044771738350391,
0.02546919882297516,
0.10105821490287781,
-0.005342207849025726,
-0.03660029545426369,
-0.07734604179859161,
-0.08644260466098785,
-0.013860582374036312,
-0.021797798573970795,
-0.00058909592917189,
-0.05787099152803421,
-0.08824902772903442,
0.022198010236024857,
-0.008425051346421242,
-0.10917199403047562,
0.017453515902161598,
0.033708155155181885,
0.06018010899424553,
0.007361509837210178,
0.006508827209472656,
0.0034772506915032864,
-0.00873299315571785,
0.22329950332641602,
-0.08855558931827545,
-0.07683862745761871,
-0.09077584743499756,
0.2835303843021393,
0.030199438333511353,
0.07084670662879944,
-0.005741542670875788,
-0.09273208677768707,
0.006391387898474932,
0.23593734204769135,
0.20000717043876648,
-0.10236432403326035,
0.021679941564798355,
-0.038703855127096176,
0.007739500142633915,
-0.022511042654514313,
0.09215907007455826,
0.09638938307762146,
0.05046406388282776,
-0.09344089031219482,
-0.034376077353954315,
-0.040346357971429825,
-0.024465002119541168,
-0.01777537912130356,
0.061907269060611725,
0.044819168746471405,
0.00927053950726986,
-0.08169809728860855,
0.08044102042913437,
-0.0562937930226326,
-0.10722551494836807,
0.03426282852888107,
-0.18168103694915771,
-0.14348724484443665,
-0.029602715745568275,
0.10853412002325058,
0.021389247849583626,
0.07497072964906693,
-0.018618730828166008,
-0.023781001567840576,
0.04126735031604767,
-0.022214939817786217,
-0.040633536875247955,
-0.12009446322917938,
0.07693444192409515,
-0.0815427154302597,
0.19838491082191467,
-0.045753974467515945,
0.03481103479862213,
0.12033895403146744,
0.024557985365390778,
-0.05333475023508072,
0.09895553439855576,
0.06232825294137001,
-0.13751265406608582,
0.01545203197747469,
0.12287458777427673,
-0.05121070146560669,
0.11619207262992859,
0.054180435836315155,
-0.20754249393939972,
0.04183431342244148,
-0.06612788140773773,
-0.09762059897184372,
-0.04994461312890053,
-0.016081692650914192,
-0.037593960762023926,
0.12945666909217834,
0.22140534222126007,
-0.01664750836789608,
0.03399364650249481,
-0.05435233190655708,
0.03625599667429924,
0.05335795506834984,
0.033612411469221115,
-0.026833252981305122,
-0.26548007130622864,
0.020493851974606514,
0.10101167857646942,
-0.020467102527618408,
-0.2752707898616791,
-0.08864987641572952,
-0.013235438615083694,
-0.019824763759970665,
-0.0718546062707901,
0.08156324177980423,
0.10180465131998062,
0.050879646092653275,
-0.03999485448002815,
-0.15903139114379883,
-0.05278244614601135,
0.17890822887420654,
-0.12379284203052521,
-0.0902535691857338
] |
null | null | transformers |
## MiquMaid v2
Check out our blogpost about this model series [Here!](https://ikaridevgit.github.io/index.html?blog=blogid-6&bo=true#Miqu-base) - Join our Discord server [Here!](https://discord.gg/Bb8pRUXy3Z)
<center>[<a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B">V2-70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-70B-DPO">V2-70B-DPO</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B">V2-2x70B</a> - <a href="https://huggingface.co/NeverSleep/MiquMaid-v2-2x70B-DPO">V2-2x70B-DPO</a>]
</br>
<div style="width: 100%;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/1ziZ_5Rl7bsQKFrgH6ZCf.png" style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca **prompting format**
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: [FP16](https://huggingface.co/NeverSleep/MiquMaid-v2-70B) - [GGUF](https://huggingface.co/NeverSleep/MiquMaid-v2-70B-GGUF)
## Training data used:
- [Aesir datasets](https://huggingface.co/MinervaAI)
- [NoRobots](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt)
- [limarp](https://huggingface.co/datasets/lemonilia/LimaRP)
- [toxic-dpo-v0.1-sharegpt](https://huggingface.co/datasets/Undi95/toxic-dpo-v0.1-sharegpt)
- [ToxicQAFinal](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAFinal)
### Custom format:
```
### Instruction:
{system prompt}
### Input:
{input}
### Response:
{reply}
```
## Others
Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).
IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | text-generation | LoneStriker/MiquMaid-v2-70B-6.0bpw-h6-exl2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T02:27:09+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## MiquMaid v2
Check out our blogpost about this model series Here! - Join our Discord server Here!
<center>[<a href="URL - <a href="URL - <a href="URL - <a href="URL
</br>
<div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce.
## Credits:
- Undi
- IkariDev
## Description
This repo contains FP16 files of MiquMaid-v2-70B.
Switch: FP16 - GGUF
## Training data used:
- Aesir datasets
- NoRobots
- limarp
- toxic-dpo-v0.1-sharegpt
- ToxicQAFinal
### Custom format:
## Others
Undi: If you want to support us, you can here.
IkariDev: Visit my retro/neocities style website please kek | [
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.",
"## Credits:\n- Undi\n- IkariDev",
"## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF",
"## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal",
"### Custom format:",
"## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
75,
121,
11,
30,
40,
5,
32
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## MiquMaid v2\n\nCheck out our blogpost about this model series Here! - Join our Discord server Here!\n\n<center>[<a href=\"URL - <a href=\"URL - <a href=\"URL - <a href=\"URL\n</br>\n<div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\n\nThis model uses the Alpaca prompting format\n\nModel trained for RP conversation on Miqu-70B with our magic sauce.## Credits:\n- Undi\n- IkariDev## Description\n\nThis repo contains FP16 files of MiquMaid-v2-70B.\n\nSwitch: FP16 - GGUF## Training data used:\n- Aesir datasets\n- NoRobots\n- limarp\n- toxic-dpo-v0.1-sharegpt\n- ToxicQAFinal### Custom format:## Others\n\nUndi: If you want to support us, you can here.\n\nIkariDev: Visit my retro/neocities style website please kek"
] | [
-0.09447834640741348,
0.17205014824867249,
-0.005602731369435787,
0.01779203675687313,
0.11820747703313828,
0.045264896005392075,
0.11447285860776901,
0.15961068868637085,
0.06829394400119781,
0.05906902998685837,
0.0005873226327821612,
0.11407624930143356,
0.07548845559358597,
0.22948826849460602,
-0.006628913804888725,
-0.14427904784679413,
0.046850357204675674,
-0.026289891451597214,
-0.02635573409497738,
0.09569915384054184,
0.07466454803943634,
-0.04618130251765251,
0.0709284171462059,
0.010442404076457024,
-0.10720876604318619,
-0.017348533496260643,
0.0019323929445818067,
-0.05718233436346054,
0.04780259355902672,
0.04367207735776901,
0.0479082316160202,
0.05087536945939064,
0.00845402292907238,
-0.22662657499313354,
0.047140758484601974,
0.07308577746152878,
-0.025127466768026352,
0.07861552387475967,
0.10886233299970627,
-0.04211974889039993,
0.02646409347653389,
-0.03574787452816963,
-0.02210289053618908,
0.09350186586380005,
-0.11214648932218552,
-0.12319593131542206,
-0.11320719122886658,
0.13006889820098877,
0.06314875930547714,
0.08198896050453186,
0.0033554788678884506,
0.1101357564330101,
-0.07631256431341171,
0.07790177315473557,
0.20335930585861206,
-0.16871041059494019,
-0.02322721853852272,
0.05624805763363838,
-0.015333202667534351,
-0.05565005913376808,
-0.09832000732421875,
0.011083890683948994,
0.010926350019872189,
-0.019533375278115273,
-0.0038207839243113995,
-0.041167840361595154,
0.004284780006855726,
-0.06099749729037285,
-0.059463758021593094,
-0.016264086589217186,
0.24300093948841095,
0.0361378937959671,
-0.07370094209909439,
-0.0026136080268770456,
-0.006493517197668552,
0.11463554203510284,
-0.05098545923829079,
0.030949248000979424,
0.005614427383989096,
-0.0010702924337238073,
-0.0032837465405464172,
-0.04595240205526352,
-0.10275456309318542,
-0.05733378976583481,
-0.014142698608338833,
0.14566513895988464,
0.017552156001329422,
0.00008401479135500267,
-0.004768410697579384,
0.051651932299137115,
-0.10471507161855698,
-0.12298901379108429,
-0.06133059412240982,
-0.10231878608465195,
-0.005009785760194063,
-0.042668018490076065,
-0.022182224318385124,
-0.06640303134918213,
0.12371482700109482,
0.1403876692056656,
-0.04801563546061516,
-0.0030525391921401024,
-0.025033647194504738,
0.00783479306846857,
0.005412905476987362,
-0.00017629309149924666,
-0.07161558419466019,
-0.023959118872880936,
0.07290422171354294,
0.025751972571015358,
0.004980665165930986,
0.010289043188095093,
-0.044097792357206345,
-0.07064660638570786,
-0.04732796177268028,
0.05287690833210945,
0.07054515182971954,
0.06856327503919601,
-0.07649759203195572,
-0.047711774706840515,
0.22618921101093292,
-0.10658138245344162,
0.029063958674669266,
0.05863291397690773,
-0.007088409271091223,
0.10424129664897919,
0.06771936267614365,
-0.0006956448778510094,
-0.06505299359560013,
0.016184480860829353,
-0.041465580463409424,
0.03125211223959923,
-0.08675958216190338,
-0.05394180864095688,
0.0855826810002327,
0.0812700167298317,
-0.03331775963306427,
-0.1366315633058548,
-0.10328203439712524,
-0.01740688644349575,
0.02815520204603672,
-0.023310357704758644,
0.0012498353607952595,
0.04892998933792114,
-0.05491432547569275,
0.01405452098697424,
0.01705477572977543,
0.00629244651645422,
-0.05887370929121971,
0.07736124843358994,
0.022486159577965736,
0.09428157657384872,
0.019443463534116745,
0.025946028530597687,
-0.035123471170663834,
0.002149750478565693,
-0.23019294440746307,
0.05012257769703865,
-0.10595361143350601,
0.0038321600295603275,
-0.0922209694981575,
0.0014835012843832374,
-0.027800843119621277,
-0.009975400753319263,
0.0055687217973172665,
0.20525269210338593,
-0.14585432410240173,
-0.05596565082669258,
0.304247111082077,
-0.15955102443695068,
-0.09778694808483124,
0.09222670644521713,
0.03642375022172928,
-0.07440096139907837,
0.06239297613501549,
0.08249494433403015,
0.1056317463517189,
-0.16265460848808289,
-0.09710903465747833,
-0.011078423820436,
-0.022652560845017433,
-0.024000728502869606,
0.0878278836607933,
-0.018813995644450188,
0.03245491161942482,
0.019763432443141937,
-0.03379102423787117,
0.07007033377885818,
-0.025310136377811432,
-0.022386055439710617,
-0.03589578717947006,
-0.06099054589867592,
0.05183964595198631,
-0.002879094798117876,
-0.0388391874730587,
-0.006428318098187447,
-0.04584600031375885,
-0.06035709008574486,
0.13202428817749023,
-0.004858740605413914,
-0.020473629236221313,
-0.07851582020521164,
0.09554000943899155,
-0.05498090013861656,
0.03728895261883736,
-0.13830018043518066,
-0.06243045628070831,
0.0036350893788039684,
-0.0796012431383133,
0.02157106250524521,
-0.0041148848831653595,
0.05950147658586502,
0.038105957210063934,
-0.04352330043911934,
-0.028907326981425285,
-0.0057363444939255714,
0.004301073960959911,
-0.025426069274544716,
-0.1666073054075241,
-0.0007695230888202786,
-0.0551750548183918,
0.1374220848083496,
-0.16868118941783905,
0.05043652653694153,
0.05925111472606659,
0.16357283294200897,
0.03616755083203316,
-0.031011521816253662,
0.11654403805732727,
-0.03804580122232437,
-0.006411012262105942,
-0.03725241497159004,
0.0044607375748455524,
0.002538213739171624,
-0.011939228512346745,
0.10659566521644592,
-0.06065728887915611,
0.054277852177619934,
0.12642189860343933,
-0.01595868356525898,
-0.05425528809428215,
-0.06506265699863434,
-0.01521784346550703,
-0.006736948620527983,
-0.048000186681747437,
-0.047349583357572556,
0.02513136900961399,
0.0662446990609169,
0.07768423110246658,
-0.03797391429543495,
-0.008253731764853,
0.0011901968391612172,
-0.0948609709739685,
-0.0020795518066734076,
0.0409865640103817,
0.05132393538951874,
-0.14333368837833405,
0.09081240743398666,
0.09744595736265182,
-0.015339801087975502,
0.14312495291233063,
0.008754834532737732,
-0.1070873811841011,
-0.003728162497282028,
0.027940761297941208,
0.05264529958367348,
0.0774049460887909,
-0.03596934303641319,
0.02683958038687706,
0.08106063306331635,
-0.05121877044439316,
0.007932554930448532,
-0.09500398486852646,
-0.022678673267364502,
-0.013256699778139591,
-0.0758146122097969,
-0.04612674191594124,
0.03610261529684067,
0.030104612931609154,
0.0918031707406044,
-0.015134556218981743,
0.07633049786090851,
-0.0010367896175011992,
-0.02394755184650421,
-0.09206201136112213,
0.1670486181974411,
-0.0899675041437149,
-0.27366867661476135,
-0.1188458725810051,
-0.07167717814445496,
-0.04199657961726189,
0.004022621084004641,
0.02857130952179432,
-0.12134306877851486,
-0.07081691175699234,
-0.03115151636302471,
-0.0038425917737185955,
0.06778023391962051,
-0.03805195540189743,
-0.02431504614651203,
0.05526971071958542,
0.09138014912605286,
-0.07273191213607788,
-0.002759605646133423,
0.06194623187184334,
-0.037675220519304276,
0.08085193485021591,
0.008549315854907036,
0.10605848580598831,
0.04739413037896156,
0.03012051060795784,
0.0015264216344803572,
0.04311876371502876,
0.17313145101070404,
-0.10127022117376328,
0.09718520194292068,
0.20746180415153503,
0.0394415408372879,
0.08480402082204819,
0.15171074867248535,
0.05122246593236923,
-0.013119645416736603,
-0.005120322108268738,
0.04244927689433098,
0.011746162548661232,
-0.2427690476179123,
-0.061469703912734985,
-0.05656198412179947,
-0.054776955395936966,
0.022767482325434685,
0.047591015696525574,
0.0650729089975357,
0.1047578752040863,
-0.10416096448898315,
-0.016062086448073387,
0.022997045889496803,
0.09911724179983139,
0.047439564019441605,
0.022038234397768974,
0.061993930488824844,
-0.04141371324658394,
0.015599393285810947,
0.12155410647392273,
0.06473620980978012,
0.11147889494895935,
-0.023897795006632805,
0.08020832389593124,
0.06728237122297287,
0.0892438217997551,
0.0530114471912384,
0.06319621205329895,
0.04218849167227745,
-0.014131366275250912,
-0.0013301256112754345,
-0.08454640209674835,
-0.04801497980952263,
0.023290416225790977,
0.013235284946858883,
-0.057533953338861465,
-0.0392376184463501,
-0.01914895512163639,
0.07390332221984863,
0.1574147492647171,
0.04597143456339836,
-0.20930512249469757,
-0.05056460201740265,
0.033859558403491974,
-0.0003397460968699306,
-0.06584210693836212,
-0.033550359308719635,
0.05652978643774986,
-0.12203755974769592,
0.1039382740855217,
-0.02658943273127079,
0.09946075826883316,
-0.07054278254508972,
0.000789299956522882,
0.00494906771928072,
0.12713035941123962,
-0.023788869380950928,
0.09413742274045944,
-0.24859566986560822,
0.14139194786548615,
0.04770104959607124,
0.06752338260412216,
-0.05309014022350311,
0.028258029371500015,
0.0961327999830246,
0.12656870484352112,
0.10434279590845108,
0.020785793662071228,
0.06395822018384933,
-0.15350443124771118,
-0.11799371987581253,
0.006164612248539925,
0.02960512787103653,
-0.04779611900448799,
0.07287964969873428,
-0.0005067483871243894,
-0.06341438740491867,
-0.04712821915745735,
0.03289221227169037,
-0.19348879158496857,
-0.12983499467372894,
0.07045576721429825,
0.052490055561065674,
0.090853750705719,
-0.06709475815296173,
-0.03205195814371109,
-0.043046124279499054,
0.18290454149246216,
-0.03442198783159256,
-0.08606650680303574,
-0.1285882145166397,
-0.0006686998531222343,
0.09258218854665756,
-0.08165017515420914,
-0.005991893354803324,
-0.052048277109861374,
0.1894829422235489,
-0.035209737718105316,
-0.08786994218826294,
0.01570327952504158,
-0.15995244681835175,
-0.1281605362892151,
-0.0414857491850853,
0.12103712558746338,
-0.021659180521965027,
0.02213156595826149,
0.05526252090930939,
-0.020805859938263893,
0.008410685695707798,
-0.1123393177986145,
0.02350648306310177,
0.09350050985813141,
0.08948540687561035,
0.08400450646877289,
-0.11930029839277267,
-0.11843101680278778,
-0.10216961801052094,
-0.022528614848852158,
0.06181072071194649,
0.24282413721084595,
-0.02235415205359459,
0.037382837384939194,
0.13085247576236725,
-0.04928212612867355,
-0.19814851880073547,
-0.06996271014213562,
-0.00017375701281707734,
-0.037472743541002274,
0.02159503661096096,
-0.21408295631408691,
0.08694717288017273,
0.09358245879411697,
-0.030445247888565063,
0.09161640703678131,
-0.07194696366786957,
-0.06843597441911697,
0.04065357893705368,
0.07071772962808609,
0.0037067674566060305,
-0.1683196723461151,
-0.07113704830408096,
-0.06764888018369675,
-0.12663458287715912,
0.08166584372520447,
-0.1314810812473297,
0.08971400558948517,
-0.005421672947704792,
0.0671011433005333,
0.025563575327396393,
-0.06707208603620529,
0.11356908828020096,
-0.020757906138896942,
0.009567689150571823,
-0.07924797385931015,
0.012899143621325493,
0.022010432556271553,
-0.050428662449121475,
0.09034649282693863,
-0.02925287000834942,
0.01692429557442665,
-0.091850645840168,
-0.0007856881711632013,
-0.10224597156047821,
0.0437864288687706,
-0.038862090557813644,
-0.017533548176288605,
-0.008498632349073887,
0.07837546616792679,
0.03536466881632805,
0.010669435374438763,
-0.009266866371035576,
-0.04946504905819893,
0.10181041061878204,
0.17810481786727905,
0.10491631180047989,
0.0006870499346405268,
-0.07857012748718262,
-0.036821771413087845,
-0.053213875740766525,
0.050082918256521225,
-0.08183137327432632,
0.06681650131940842,
0.029605142772197723,
0.010572184808552265,
0.12429390102624893,
-0.0033586653880774975,
-0.12030913680791855,
-0.003338087350130081,
0.10895328968763351,
-0.12868796288967133,
-0.07275929301977158,
-0.020934229716658592,
0.05516009032726288,
-0.10196569561958313,
0.0011667415965348482,
0.1428048461675644,
-0.028892088681459427,
-0.028331711888313293,
0.014776935800909996,
0.07020314782857895,
-0.012796786613762379,
0.10238455981016159,
0.07413777709007263,
0.049551427364349365,
-0.12031137198209763,
0.05704139545559883,
0.03181569650769234,
-0.03592713922262192,
-0.0024339298252016306,
0.05667674541473389,
-0.10612429678440094,
-0.1119871735572815,
0.03397342190146446,
0.06045559421181679,
-0.015471268445253372,
-0.06184658035635948,
-0.020792635157704353,
-0.04714902117848396,
0.02126099169254303,
0.07590576261281967,
0.00995138380676508,
-0.008162305690348148,
0.08148860931396484,
-0.017391547560691833,
-0.08959554880857468,
0.06402577459812164,
0.010443227365612984,
0.03571965917944908,
-0.13038720190525055,
0.07408680766820908,
-0.015041174367070198,
0.006071531679481268,
-0.022530831396579742,
0.003641687100753188,
-0.10074226558208466,
-0.04254826903343201,
-0.07885435223579407,
0.06230726093053818,
-0.1484614759683609,
-0.020241795107722282,
-0.026183132082223892,
-0.022612975910305977,
0.015071062371134758,
0.019551774486899376,
-0.07782812416553497,
-0.04559153690934181,
-0.010346274822950363,
0.08449862152338028,
-0.16007104516029358,
-0.008523115888237953,
0.03327300027012825,
-0.06084582209587097,
0.0670776516199112,
0.08543620258569717,
-0.010745981708168983,
-0.011400423012673855,
-0.24030931293964386,
-0.05429427698254585,
0.060920946300029755,
0.04178236424922943,
0.015297153033316135,
-0.10723429918289185,
0.0352109931409359,
-0.01898287609219551,
-0.023456763476133347,
0.005050045438110828,
0.031953055411577225,
-0.08434974402189255,
0.024241402745246887,
-0.019039491191506386,
-0.04014326632022858,
-0.051917847245931625,
0.04262912645936012,
0.17145587503910065,
-0.014532416127622128,
0.1174297034740448,
-0.080752432346344,
0.054420918226242065,
-0.13401885330677032,
0.029829595237970352,
-0.001078542205505073,
-0.039962440729141235,
-0.02863360196352005,
-0.010570892132818699,
0.06349045038223267,
-0.010899520479142666,
0.09258676320314407,
-0.0552545003592968,
0.06722300499677658,
0.0190583486109972,
-0.09725376963615417,
0.007986992597579956,
-0.026470135897397995,
0.03294571489095688,
0.0396236926317215,
-0.006473933346569538,
0.009316735900938511,
0.00238132756203413,
0.02042953483760357,
-0.0582701601088047,
0.07976511865854263,
0.16147081553936005,
0.02053176984190941,
0.022807525470852852,
0.054943084716796875,
-0.07234697043895721,
-0.036924149841070175,
-0.04578930139541626,
-0.077462337911129,
0.06634023785591125,
-0.021255100145936012,
0.07374273985624313,
0.15307408571243286,
-0.12218204140663147,
0.038187239319086075,
-0.005237263161689043,
-0.03132057934999466,
-0.08196348696947098,
-0.1581864356994629,
-0.06715912371873856,
-0.08088500797748566,
0.011959434486925602,
-0.11438815295696259,
0.06888450682163239,
0.04325690120458603,
0.019395047798752785,
-0.017880942672491074,
0.13543029129505157,
0.03472369909286499,
-0.07543140649795532,
0.060917001217603683,
-0.02095349319279194,
-0.031358812004327774,
0.04272241145372391,
0.0006400952115654945,
0.06196298450231552,
-0.010582057759165764,
0.044258568435907364,
0.0559408999979496,
0.02938593178987503,
0.05811672285199165,
-0.06726688146591187,
-0.12517108023166656,
0.006359596271067858,
0.005888449959456921,
0.04039566218852997,
0.15003027021884918,
0.05136363208293915,
0.007397872861474752,
0.014586303383111954,
0.16361239552497864,
-0.038274187594652176,
-0.0431714691221714,
-0.15419889986515045,
0.011273895390331745,
-0.02001452073454857,
-0.009176031686365604,
-0.03663250058889389,
-0.10866829752922058,
-0.028140606358647346,
0.20135445892810822,
0.08363344520330429,
-0.049736183136701584,
0.026926010847091675,
-0.006478144787251949,
0.0070541067980229855,
0.006099193822592497,
0.08733457326889038,
0.05982113629579544,
0.11233042925596237,
-0.03476639464497566,
0.04225286468863487,
0.008952682837843895,
-0.042931120842695236,
-0.100910983979702,
0.05160531401634216,
-0.04183126986026764,
-0.029043002054095268,
-0.0207699965685606,
0.12725666165351868,
-0.06002918258309364,
-0.12053494155406952,
-0.05984590947628021,
-0.05843505263328552,
-0.09186802059412003,
-0.04533113166689873,
-0.021347900852560997,
0.08330697566270828,
0.03736959397792816,
-0.008225626312196255,
-0.006564581301063299,
0.18599693477153778,
-0.004363450221717358,
-0.06833065301179886,
-0.047022756189107895,
0.03228268772363663,
-0.009685746394097805,
0.13331912457942963,
0.02237250655889511,
0.06835850328207016,
0.08902639895677567,
-0.04617135971784592,
-0.13351397216320038,
0.05768809840083122,
0.01893182285130024,
-0.16012974083423615,
0.03900958225131035,
0.1735668033361435,
-0.019399257376790047,
0.004258662927895784,
0.07070906460285187,
-0.07974739372730255,
0.021498262882232666,
0.05192280188202858,
-0.017278648912906647,
-0.07030515372753143,
0.08999960869550705,
-0.09391003847122192,
0.11678098142147064,
0.17506007850170135,
-0.024389326572418213,
-0.013276796787977219,
-0.03903545066714287,
0.05904215946793556,
0.06406354159116745,
-0.016790268942713737,
-0.07218509912490845,
-0.10399819910526276,
0.01415897998958826,
-0.01502299215644598,
0.07969480007886887,
-0.13121938705444336,
-0.019862104207277298,
-0.05875250697135925,
-0.03522523120045662,
-0.09029058367013931,
0.07942423224449158,
0.06178797036409378,
0.053517896682024,
-0.021183528006076813,
-0.09516715258359909,
0.007413235958665609,
0.11255256831645966,
-0.14081521332263947,
-0.0646120086312294
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | patruff/chucklesMistralTuneB | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:29:47+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
31,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06646376848220825,
0.2168014943599701,
-0.00225935154594481,
0.023818302899599075,
0.1271018385887146,
-0.001635765191167593,
0.04218708351254463,
0.13324736058712006,
-0.020175931975245476,
0.11144465953111649,
0.046588581055402756,
0.09377603232860565,
0.09928803145885468,
0.18404334783554077,
0.04859916493296623,
-0.2059975117444992,
0.007056170143187046,
-0.09090408682823181,
0.014076028019189835,
0.1116579994559288,
0.13719257712364197,
-0.10291384905576706,
0.08272874355316162,
-0.04045208916068077,
-0.02019004337489605,
0.00012576708104461432,
-0.09259183704853058,
-0.07032395154237747,
0.06885425746440887,
0.06264153122901917,
0.051234472543001175,
0.001456156256608665,
0.09140396863222122,
-0.2864592671394348,
0.017265573143959045,
0.08406311273574829,
0.0027674848679453135,
0.06290827691555023,
0.07236549258232117,
-0.07389893382787704,
0.11328595131635666,
-0.08021481335163116,
0.13019037246704102,
0.08625296503305435,
-0.062064990401268005,
-0.23071379959583282,
-0.07525765895843506,
0.0963398814201355,
0.12251301854848862,
0.06215599179267883,
-0.022921854630112648,
0.15455181896686554,
-0.06248689442873001,
0.012971068732440472,
0.1294165402650833,
-0.11526761949062347,
-0.05572471022605896,
0.061741601675748825,
0.11775490641593933,
0.10740239918231964,
-0.14110268652439117,
-0.0017287094378843904,
0.04900608956813812,
0.029121357947587967,
0.08589313924312592,
0.022661056369543076,
0.12003941088914871,
0.04652795568108559,
-0.13695219159126282,
-0.04037507623434067,
0.12011898308992386,
0.038862764835357666,
-0.06446044892072678,
-0.2168138176202774,
-0.006778308190405369,
-0.0601806715130806,
-0.014732478186488152,
-0.07019448280334473,
0.039128515869379044,
-0.02470310963690281,
0.07317749410867691,
-0.04465159401297569,
-0.1063927412033081,
-0.0421026237308979,
0.0892222449183464,
0.07748593389987946,
0.011527054943144321,
-0.02519804798066616,
0.04627908393740654,
0.13455867767333984,
0.05402068421244621,
-0.10399353504180908,
-0.07017925381660461,
-0.06942764669656754,
-0.09420394152402878,
-0.04035796597599983,
0.056760527193546295,
0.031942449510097504,
0.02665667235851288,
0.22703726589679718,
0.016653569415211678,
0.04155244305729866,
0.0224777739495039,
0.01032855175435543,
0.043662428855895996,
0.0955500528216362,
-0.05303520709276199,
-0.15660029649734497,
-0.04072032496333122,
0.09077946096658707,
-0.0027527001220732927,
-0.036689214408397675,
-0.03966725245118141,
0.03849169611930847,
0.06843466311693192,
0.13122352957725525,
0.07552056759595871,
-0.017929591238498688,
-0.04813180863857269,
-0.030096933245658875,
0.23523783683776855,
-0.1493375599384308,
0.04426715523004532,
-0.02271856553852558,
-0.01804111897945404,
-0.03908449783921242,
0.03597262129187584,
0.022118929773569107,
-0.000004518366949923802,
0.09706240892410278,
-0.058981191366910934,
-0.05378659814596176,
-0.10168042778968811,
-0.03272576630115509,
0.04088849574327469,
-0.013975566253066063,
-0.010589460842311382,
-0.09025166928768158,
-0.09490354359149933,
-0.04766594246029854,
0.05537205561995506,
-0.05123869329690933,
-0.03770573064684868,
0.009465423412621021,
-0.08151785284280777,
-0.005444355774670839,
-0.005417742300778627,
0.10699385404586792,
-0.03222226724028587,
0.04445803165435791,
-0.027600755915045738,
0.05225523188710213,
0.09919606149196625,
0.031576547771692276,
-0.0773419588804245,
0.0561848059296608,
-0.22559374570846558,
0.07503069192171097,
-0.11481974273920059,
0.04335082694888115,
-0.1704932004213333,
-0.042439818382263184,
0.005444696638733149,
0.0139949731528759,
0.013206101022660732,
0.12720820307731628,
-0.19255615770816803,
-0.01654396951198578,
0.13260798156261444,
-0.09212633967399597,
-0.118110790848732,
0.07884611934423447,
-0.029701577499508858,
0.1624738723039627,
0.04682036489248276,
-0.027025915682315826,
0.09224298596382141,
-0.16434773802757263,
-0.07092688232660294,
-0.00949116237461567,
-0.01727987825870514,
0.12109188735485077,
0.07512219995260239,
-0.05991523340344429,
0.046571120619773865,
0.02832140028476715,
-0.038078423589468,
-0.04424772411584854,
-0.050857074558734894,
-0.10884185880422592,
-0.01070026308298111,
-0.08987759798765182,
0.04065500199794769,
-0.01250192429870367,
-0.07916021347045898,
-0.029885273426771164,
-0.18612512946128845,
-0.0030564051121473312,
0.10038342326879501,
0.0035033065360039473,
-0.005652366206049919,
-0.08666291832923889,
0.026358824223279953,
-0.03112892620265484,
-0.008404186926782131,
-0.16764774918556213,
-0.04399421438574791,
0.046902090311050415,
-0.16094985604286194,
0.020117372274398804,
-0.06413903087377548,
0.06334125250577927,
0.03641495108604431,
-0.05590536445379257,
-0.0248766727745533,
-0.01730942726135254,
0.011945613659918308,
-0.05083848536014557,
-0.18994836509227753,
-0.056277405470609665,
-0.037882111966609955,
0.149809330701828,
-0.25956398248672485,
0.032966937869787216,
0.051140617579221725,
0.14649195969104767,
0.00406361510977149,
-0.05115427449345589,
0.01429014839231968,
-0.05360214412212372,
-0.054652128368616104,
-0.06746816635131836,
-0.006135428790003061,
-0.027576493099331856,
-0.05147203803062439,
0.019243421033024788,
-0.1755700707435608,
-0.021410830318927765,
0.09424154460430145,
0.12876708805561066,
-0.1486445665359497,
-0.018640631809830666,
-0.048725154250860214,
-0.06339836865663528,
-0.0715010017156601,
-0.07038594037294388,
0.10712739825248718,
0.0513901449739933,
0.04796046018600464,
-0.07435787469148636,
-0.07092321664094925,
0.02726263552904129,
0.006906150374561548,
-0.03382374346256256,
0.08727246522903442,
0.05199531093239784,
-0.09209315478801727,
0.0756213590502739,
0.1092359870672226,
0.07177663594484329,
0.09363535046577454,
0.01574566215276718,
-0.11756632477045059,
-0.028492970392107964,
0.036266472190618515,
0.02740776725113392,
0.1465986967086792,
-0.05952361226081848,
0.04016614332795143,
0.04494241625070572,
-0.04170418903231621,
0.022319864481687546,
-0.08787637203931808,
0.024075502529740334,
0.025203049182891846,
-0.0034381982404738665,
0.06284574419260025,
-0.02525499276816845,
-0.0050758360885083675,
0.07016654312610626,
0.047779910266399384,
0.04621000960469246,
0.009655474685132504,
-0.01720241829752922,
-0.1047825813293457,
0.16950392723083496,
-0.0951867327094078,
-0.269941508769989,
-0.17632324993610382,
0.026197833940386772,
0.04035249724984169,
-0.022378476336598396,
0.031619444489479065,
-0.07056326419115067,
-0.10630585998296738,
-0.1060405746102333,
-0.002429972169920802,
0.01714223250746727,
-0.06364088505506516,
-0.0741225928068161,
0.07348573952913284,
0.04382912442088127,
-0.14902326464653015,
0.038552410900592804,
0.055694397538900375,
-0.057955220341682434,
-0.0233661737293005,
0.09118817001581192,
0.12397737801074982,
0.14583967626094818,
-0.021366750821471214,
-0.028626007959246635,
0.029004426673054695,
0.19620531797409058,
-0.13469526171684265,
0.10371150821447372,
0.13814030587673187,
-0.04545360431075096,
0.08360563963651657,
0.1560150384902954,
0.029186224564909935,
-0.08317049592733383,
0.05044832453131676,
0.04082648828625679,
-0.043159641325473785,
-0.2666129767894745,
-0.0534592866897583,
0.012832709588110447,
-0.06255637854337692,
0.09786593168973923,
0.10183793306350708,
0.11542957276105881,
0.034910861402750015,
-0.07166364789009094,
-0.043925940990448,
-0.0058974819257855415,
0.11737963557243347,
-0.05490213260054588,
-0.012639665976166725,
0.07686592638492584,
-0.05086168646812439,
0.005355054512619972,
0.10266812145709991,
0.02973790094256401,
0.17442677915096283,
0.020399179309606552,
0.11231429129838943,
0.06195578724145889,
0.08633565157651901,
0.0007386076031252742,
0.02951662428677082,
0.05147615820169449,
0.017203815281391144,
-0.002300140680745244,
-0.10421168059110641,
-0.006156572140753269,
0.1449710875749588,
0.028103826567530632,
0.029669636860489845,
-0.0018948549404740334,
-0.005003341939300299,
0.05121048167347908,
0.1746254414319992,
-0.011592294089496136,
-0.22072425484657288,
-0.0845772922039032,
0.06936841458082199,
-0.06218599155545235,
-0.12968985736370087,
-0.026130788028240204,
0.045467354357242584,
-0.17519839107990265,
0.026703642681241035,
-0.027433741837739944,
0.0919293761253357,
-0.09345759451389313,
-0.02221956104040146,
0.03687324374914169,
0.084866963326931,
-0.014529162086546421,
0.08703910559415817,
-0.14498743414878845,
0.11886418610811234,
0.02978132851421833,
0.09024628251791,
-0.11081171780824661,
0.07909037172794342,
-0.007550720125436783,
0.009180475026369095,
0.19379350543022156,
-0.011335089802742004,
-0.03514958545565605,
-0.08774717897176743,
-0.11210042238235474,
-0.013537433929741383,
0.12687496840953827,
-0.1243172138929367,
0.08773399889469147,
-0.015198243781924248,
-0.044079482555389404,
0.00937260314822197,
-0.12100647389888763,
-0.17273177206516266,
-0.19628387689590454,
0.05585884302854538,
-0.09575839340686798,
0.025643249973654747,
-0.11914430558681488,
-0.07089093327522278,
-0.02952558360993862,
0.241120383143425,
-0.1745356321334839,
-0.06510113179683685,
-0.1468164622783661,
-0.046294767409563065,
0.1662203073501587,
-0.04437198117375374,
0.0718095526099205,
-0.0208172257989645,
0.20345525443553925,
0.005988610442727804,
-0.004939318168908358,
0.06724198162555695,
-0.08892562240362167,
-0.16873881220817566,
-0.06771010160446167,
0.1510489284992218,
0.11680185794830322,
0.04907919466495514,
-0.002248800592496991,
0.0011772146681323647,
-0.016943959519267082,
-0.1137804463505745,
-0.0033210667315870523,
0.16037839651107788,
0.03878779336810112,
0.025986969470977783,
-0.05243593826889992,
-0.08797456324100494,
-0.06899320334196091,
-0.06853509694337845,
0.06221301481127739,
0.19590823352336884,
-0.10376439243555069,
0.1700313836336136,
0.147536963224411,
-0.07305635511875153,
-0.23175598680973053,
0.035342130810022354,
0.04983805492520332,
0.0014306638622656465,
0.04886869341135025,
-0.18252557516098022,
0.10521943867206573,
0.019543392583727837,
-0.05505957826972008,
0.13485197722911835,
-0.1557481735944748,
-0.1552847921848297,
0.0722852572798729,
0.03904085233807564,
-0.22423844039440155,
-0.1354004591703415,
-0.09622503817081451,
-0.05825018882751465,
-0.14065024256706238,
0.06054598465561867,
-0.002136280992999673,
0.015948504209518433,
0.03500790148973465,
-0.0015643214574083686,
0.027123261243104935,
-0.058935679495334625,
0.18609118461608887,
-0.004065449349582195,
0.020676052197813988,
-0.060264769941568375,
-0.0478842556476593,
0.09839435666799545,
-0.06130504235625267,
0.12208222597837448,
0.004057085141539574,
0.01594383642077446,
-0.10362856835126877,
-0.048314861953258514,
-0.04328322783112526,
0.05154227837920189,
-0.07548051327466965,
-0.10070807486772537,
-0.043625857681035995,
0.08841723203659058,
0.07005169242620468,
-0.03383097052574158,
0.00549331633374095,
-0.07189501076936722,
0.10019614547491074,
0.17795267701148987,
0.17573626339435577,
0.009926567785441875,
-0.07241068035364151,
0.01677953451871872,
-0.04142116755247116,
0.044231921434402466,
-0.2513144314289093,
0.03756171092391014,
0.06098250672221184,
0.029438555240631104,
0.09217222779989243,
-0.020435843616724014,
-0.1820858269929886,
-0.04050002992153168,
0.08094815909862518,
-0.05452597141265869,
-0.22617179155349731,
-0.019085140898823738,
0.0954197570681572,
-0.2020406424999237,
-0.007372708059847355,
0.03995226323604584,
-0.048725228756666183,
-0.023169852793216705,
0.00010950004070764408,
0.06317184865474701,
0.002471912419423461,
0.09773622453212738,
0.0735151618719101,
0.09715340286493301,
-0.08337292820215225,
0.10562895983457565,
0.10150538384914398,
-0.09572599828243256,
0.03605884686112404,
0.06754924356937408,
-0.05300498008728027,
-0.043293699622154236,
0.03665391728281975,
0.033023297786712646,
0.005234600510448217,
-0.060321882367134094,
0.013913018628954887,
-0.036497246474027634,
0.044923391193151474,
0.08326134830713272,
0.03754979372024536,
-0.013354414142668247,
0.06462216377258301,
0.03401726484298706,
-0.10898099094629288,
0.10366570204496384,
0.01731540448963642,
0.04105307161808014,
-0.08384523540735245,
-0.019968897104263306,
0.035425446927547455,
0.030576206743717194,
-0.01765924133360386,
-0.02306121215224266,
-0.02860277332365513,
-0.01614218018949032,
-0.14299540221691132,
-0.023106401786208153,
-0.07243485748767853,
0.006181265693157911,
0.014656842686235905,
-0.031884219497442245,
-0.011233693920075893,
0.02475680410861969,
-0.06979699432849884,
-0.07426341623067856,
-0.006949664559215307,
0.09833318740129471,
-0.15115703642368317,
0.008848577737808228,
0.06907843053340912,
-0.11088496446609497,
0.08190931379795074,
-0.008411259390413761,
0.016245156526565552,
0.022527478635311127,
-0.15448406338691711,
0.05601610988378525,
0.0008648968650959432,
0.01916889287531376,
0.025886621326208115,
-0.16471809148788452,
0.004104440100491047,
-0.04661374166607857,
-0.02149827405810356,
-0.00004464812809601426,
-0.02647159807384014,
-0.12325995415449142,
0.06858719140291214,
-0.015622655861079693,
-0.035931166261434555,
-0.02701525390148163,
0.0539589487016201,
0.07888586074113846,
-0.027474910020828247,
0.10445091128349304,
-0.008690856397151947,
0.04941811040043831,
-0.16801609098911285,
-0.02470702864229679,
-0.04982255399227142,
0.019377702847123146,
0.009884213097393513,
-0.007693959400057793,
0.04183054715394974,
-0.00976533442735672,
0.21883612871170044,
-0.05075952783226967,
0.1607085019350052,
0.05847611650824547,
-0.017352959141135216,
-0.0007513365126214921,
0.06180921941995621,
0.05997028574347496,
0.04658793285489082,
0.009480604901909828,
0.023740366101264954,
-0.022450892254710197,
-0.006695089396089315,
-0.15932634472846985,
0.01890849508345127,
0.14999441802501678,
0.06301083415746689,
0.024745315313339233,
0.05866100639104843,
-0.12775006890296936,
-0.12135478109121323,
0.09311001747846603,
-0.026755332946777344,
0.00928465835750103,
-0.08245618641376495,
0.1358020007610321,
0.14980104565620422,
-0.14000412821769714,
0.05256148427724838,
-0.06134212389588356,
-0.05217423290014267,
-0.10388828068971634,
-0.12032219022512436,
-0.05887215584516525,
-0.053666237741708755,
0.002330566756427288,
-0.03760887682437897,
0.054546963423490524,
0.03344334661960602,
-0.009351172484457493,
-0.00022941511997487396,
0.13597318530082703,
-0.019751882180571556,
-0.0028988157864660025,
0.048313532024621964,
0.03693558648228645,
0.02373051457107067,
-0.05275435373187065,
0.02940409444272518,
0.02539868652820587,
0.032232340425252914,
0.06546790152788162,
0.033412106335163116,
-0.047448933124542236,
0.03804153576493263,
-0.0025254099164158106,
-0.11207924783229828,
0.019641218706965446,
-0.00460948096588254,
-0.0742158442735672,
0.1268945336341858,
0.0407399944961071,
0.010224059224128723,
-0.03741471841931343,
0.24361543357372284,
-0.06653323769569397,
-0.06378097087144852,
-0.13251738250255585,
0.10491154342889786,
-0.0027236645109951496,
0.06476365029811859,
0.023412218317389488,
-0.1284150779247284,
0.005243356805294752,
0.13858191668987274,
0.12181595712900162,
0.0045748427510261536,
0.009228081442415714,
0.0518609918653965,
0.0025186820421367884,
-0.06998204439878464,
0.054019294679164886,
0.06992026418447495,
0.12919506430625916,
-0.07847554981708527,
0.07680778950452805,
0.0006860480643808842,
-0.08370215445756912,
-0.02947772853076458,
0.11312682181596756,
-0.0409729965031147,
0.03491825982928276,
-0.047444481402635574,
0.10916327685117722,
-0.05787910893559456,
-0.29412412643432617,
0.02350960113108158,
-0.09588567912578583,
-0.15202060341835022,
-0.018367812037467957,
0.05944539234042168,
-0.02624768204987049,
0.018029648810625076,
0.06971040368080139,
-0.06011629104614258,
0.20098382234573364,
0.0335683599114418,
-0.07864278554916382,
-0.0664360448718071,
0.04837050288915634,
-0.06564252078533173,
0.2949807047843933,
0.008418165147304535,
0.02863333560526371,
0.10770907253026962,
-0.03253700211644173,
-0.18271861970424652,
0.010723991319537163,
0.1133992001414299,
-0.08056149631738663,
0.08200647681951523,
0.19000613689422607,
-0.012578671798110008,
0.1209007054567337,
0.05294662341475487,
-0.047376248985528946,
0.04217283055186272,
-0.03389401361346245,
-0.051268599927425385,
-0.10752558708190918,
0.058453381061553955,
-0.05909625440835953,
0.15447644889354706,
0.10152646154165268,
-0.05671518296003342,
-0.004550917539745569,
-0.05555408447980881,
0.04875178262591362,
0.01804669201374054,
0.12263146042823792,
0.02951994352042675,
-0.1865430772304535,
0.032826557755470276,
-0.01144319772720337,
0.10186848044395447,
-0.25588861107826233,
-0.08421015739440918,
0.08833149075508118,
-0.011924264021217823,
-0.05105875805020332,
0.10560628771781921,
0.057650718837976456,
0.04243382066488266,
-0.043439045548439026,
-0.10480839014053345,
-0.02186836116015911,
0.14663739502429962,
-0.1469624787569046,
-0.025013303384184837
] |
null | null | transformers |
# Uploaded model
- **Developed by:** devlocalhost
- **License:** apache-2.0
- **Finetuned from model :** unsloth/tinyllama-bnb-4bit
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "llama", "trl"], "widget": [{"text": "### Instruction: \u0906\u092a\u0915\u093e \u0928\u093e\u092e \u0915\u094d\u092f\u093e \u0939\u0948? ### Input:\n### Response:", "example_title": "what is your name?"}], "base_model": "unsloth/tinyllama-bnb-4bit"} | text-generation | devlocalhost/hi-tinylama-f16-3e | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"trl",
"en",
"base_model:unsloth/tinyllama-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | 2024-02-09T02:31:31+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #text-generation-inference #trl #en #base_model-unsloth/tinyllama-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# Uploaded model
- Developed by: devlocalhost
- License: apache-2.0
- Finetuned from model : unsloth/tinyllama-bnb-4bit
| [
"# Uploaded model\n\n- Developed by: devlocalhost\n- License: apache-2.0\n- Finetuned from model : unsloth/tinyllama-bnb-4bit"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #text-generation-inference #trl #en #base_model-unsloth/tinyllama-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# Uploaded model\n\n- Developed by: devlocalhost\n- License: apache-2.0\n- Finetuned from model : unsloth/tinyllama-bnb-4bit"
] | [
81,
38
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #text-generation-inference #trl #en #base_model-unsloth/tinyllama-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n# Uploaded model\n\n- Developed by: devlocalhost\n- License: apache-2.0\n- Finetuned from model : unsloth/tinyllama-bnb-4bit"
] | [
-0.03146393224596977,
0.032051824033260345,
-0.003618149319663644,
0.08558985590934753,
0.05020888149738312,
-0.02155516855418682,
0.1689489632844925,
0.08799520134925842,
-0.1583220660686493,
-0.021655522286891937,
0.14449235796928406,
0.06718456000089645,
-0.011630810797214508,
0.04116377606987953,
-0.021654335781931877,
-0.1191806048154831,
0.0712234377861023,
-0.024050330743193626,
-0.058582741767168045,
0.053072039037942886,
0.09587110579013824,
-0.04285665601491928,
0.08981321007013321,
-0.0643073171377182,
-0.026949768885970116,
0.03387003019452095,
0.01225118339061737,
-0.07112517207860947,
0.02321184240281582,
0.061182040721178055,
0.0020810572896152735,
0.05901645869016647,
0.03142726048827171,
-0.1436866819858551,
0.039239898324012756,
0.07439027726650238,
-0.043188467621803284,
0.0227418951690197,
0.007027549669146538,
-0.006092203315347433,
0.05518669635057449,
-0.026973159983754158,
-0.07221727818250656,
0.03920617699623108,
-0.02664932608604431,
-0.126733660697937,
-0.04789804294705391,
0.1090354472398758,
0.056445956230163574,
0.06004861369729042,
0.013615154661238194,
0.11525541543960571,
-0.0879276841878891,
0.07463745772838593,
0.11472675204277039,
-0.23163393139839172,
-0.05714592710137367,
0.14018648862838745,
0.04152970761060715,
0.0932227298617363,
-0.003792212111875415,
0.03622051700949669,
0.06485363841056824,
0.021644392982125282,
0.06375066936016083,
-0.06080406531691551,
-0.09128302335739136,
0.02236168272793293,
-0.07690798491239548,
-0.01408577710390091,
0.2598780393600464,
0.041797537356615067,
-0.024587208405137062,
-0.04106377437710762,
-0.08104297518730164,
0.004108182620257139,
-0.05445248261094093,
0.06745735555887222,
0.051856935024261475,
0.10336021333932877,
0.009522437117993832,
-0.05484580621123314,
-0.11138097941875458,
-0.017396939918398857,
-0.09786555171012878,
0.026141513139009476,
0.019052326679229736,
0.061294086277484894,
-0.1367843598127365,
0.05644216388463974,
0.0357879139482975,
-0.1304483711719513,
-0.0005643588374368846,
-0.06348546594381332,
0.18787916004657745,
0.07426664978265762,
-0.053980257362127304,
0.026859674602746964,
0.18121251463890076,
0.2143016904592514,
0.09080088138580322,
0.013352804817259312,
-0.0843147486448288,
0.06163349375128746,
-0.033634722232818604,
-0.02872900851070881,
-0.11568283289670944,
-0.083975650370121,
0.17720331251621246,
0.06068803369998932,
0.14029011130332947,
0.01689876802265644,
-0.09407331049442291,
0.022584574297070503,
0.04176865890622139,
0.07745832204818726,
0.15233664214611053,
0.08904854208230972,
-0.013616310432553291,
0.019003210589289665,
0.09059794992208481,
-0.08083776384592056,
-0.016415348276495934,
-0.0002172561507904902,
0.004791459999978542,
0.06319191306829453,
0.09721814841032028,
0.027920188382267952,
-0.035473499447107315,
-0.04900652915239334,
-0.04457169026136398,
-0.06897510588169098,
-0.0017507449956610799,
-0.062383536249399185,
0.09276381880044937,
-0.03713742271065712,
0.04660879820585251,
-0.19659368693828583,
-0.20637443661689758,
0.03428534418344498,
0.0894598588347435,
-0.027331793680787086,
-0.044981613755226135,
0.006583693902939558,
-0.08076265454292297,
0.030828244984149933,
-0.07213623076677322,
0.0005183665780350566,
-0.0815945714712143,
0.022075651213526726,
-0.0383116789162159,
0.07524707168340683,
-0.17243129014968872,
0.026078416034579277,
-0.11964159458875656,
0.03951701149344444,
-0.03173660486936569,
0.023912418633699417,
-0.05862925574183464,
0.14769257605075836,
-0.07754770666360855,
0.01315740030258894,
-0.05951089411973953,
0.033019330352544785,
0.023759741336107254,
0.16332168877124786,
-0.10468506067991257,
0.0025040721520781517,
0.14969517290592194,
-0.08915157616138458,
-0.17678916454315186,
0.11008669435977936,
0.03226592764258385,
0.07096608728170395,
0.08485130965709686,
0.11786685138940811,
0.11908465623855591,
-0.019312303513288498,
-0.004784663673490286,
0.10444505512714386,
0.001333483844064176,
-0.12539266049861908,
0.04279829189181328,
0.021376218646764755,
-0.10505680739879608,
0.0479622483253479,
0.008311822079122066,
0.09178446978330612,
0.02688783034682274,
-0.0724683627486229,
-0.09772475063800812,
-0.10489880293607712,
-0.015605483204126358,
-0.034467026591300964,
0.0057664234191179276,
-0.0800202265381813,
-0.0528232716023922,
0.004133148118853569,
0.10308019071817398,
-0.03903590887784958,
0.062157388776540756,
-0.07188984006643295,
0.07387598603963852,
-0.12971101701259613,
0.061407990753650665,
-0.05219312384724617,
-0.02071339450776577,
-0.025540664792060852,
0.015259265899658203,
0.03207626938819885,
0.03956272080540657,
0.06968750059604645,
-0.030736440792679787,
-0.05296369642019272,
-0.022512739524245262,
0.11889427155256271,
0.033682242035865784,
-0.05728011578321457,
-0.1646507978439331,
0.04860605672001839,
-0.014148728922009468,
0.10308665782213211,
-0.07105408608913422,
0.0244342889636755,
0.02315482310950756,
0.0891365259885788,
0.01124745886772871,
0.07647290080785751,
0.024548133835196495,
-0.04067855700850487,
-0.058761388063430786,
-0.04667888581752777,
0.0576145239174366,
0.037263717502355576,
-0.04824957251548767,
0.11209839582443237,
-0.08468890935182571,
0.18338221311569214,
0.2352171689271927,
-0.03856101632118225,
0.09588783979415894,
0.05318015068769455,
-0.011331833899021149,
-0.035770270973443985,
0.06038498505949974,
-0.052958302199840546,
-0.11154204607009888,
-0.01900191232562065,
0.11548598855733871,
-0.10042300820350647,
-0.0007168581360019743,
0.008264027535915375,
-0.09551254659891129,
-0.023266153410077095,
0.036513641476631165,
0.06595142185688019,
-0.051336608827114105,
0.13799473643302917,
0.286604642868042,
-0.07277129590511322,
0.0856037437915802,
-0.054796069860458374,
-0.006816753651946783,
0.03947904333472252,
-0.011358783580362797,
0.011141784489154816,
0.024127548560500145,
-0.03201616182923317,
0.03862245753407478,
0.059321023523807526,
0.018925843760371208,
0.0515064001083374,
-0.10010676831007004,
-0.007998224347829819,
0.02124997414648533,
-0.04842618480324745,
0.028598619624972343,
0.04385402798652649,
-0.07510917633771896,
0.0874146893620491,
-0.040437377989292145,
-0.05846363678574562,
0.06436600536108017,
0.007963919080793858,
-0.05661077797412872,
0.10768388211727142,
-0.14623908698558807,
-0.1891629844903946,
-0.15430599451065063,
-0.06221618875861168,
-0.13071230053901672,
0.02401788718998432,
0.11868397891521454,
-0.07390119880437851,
-0.0559515506029129,
-0.1589234173297882,
-0.038125377148389816,
0.0855410024523735,
0.02288527600467205,
0.002571169985458255,
0.04485950991511345,
0.06348959356546402,
-0.13508884608745575,
-0.012972219847142696,
0.06725781410932541,
-0.050015706568956375,
0.08411514014005661,
-0.04898882657289505,
0.0731150284409523,
0.08477282524108887,
0.044471655040979385,
-0.04488547146320343,
0.02605813555419445,
0.14016063511371613,
0.021385375410318375,
0.10716637969017029,
0.27038830518722534,
0.05310763791203499,
0.05360307916998863,
0.14645321667194366,
-0.0006846252363175154,
-0.05520608276128769,
0.045654769986867905,
-0.0003553122514858842,
-0.0762588158249855,
-0.1687871664762497,
-0.08354280889034271,
-0.052189186215400696,
0.10820410400629044,
0.0638062059879303,
0.0883922353386879,
0.03674556314945221,
0.16239729523658752,
-0.07712186127901077,
0.08341776579618454,
0.017962254583835602,
0.061248522251844406,
0.15721140801906586,
-0.02300448715686798,
0.10520138591527939,
-0.12263069301843643,
-0.0004647222231142223,
0.14199000597000122,
0.06507622450590134,
0.005710609722882509,
0.017732437700033188,
0.022324418649077415,
0.07431276887655258,
0.1511564552783966,
0.029911747202277184,
0.13859356939792633,
-0.028688697144389153,
-0.0037686810828745365,
-0.031344227492809296,
-0.0752824991941452,
-0.044336117804050446,
0.05411849915981293,
-0.11374664306640625,
-0.02791530452668667,
0.01524555403739214,
0.03430891036987305,
0.08332070708274841,
0.17802999913692474,
0.08140591531991959,
-0.216505229473114,
-0.006993627175688744,
0.1252078264951706,
0.0408116914331913,
-0.020037107169628143,
0.08189090341329575,
0.03363082930445671,
0.022126026451587677,
0.0417289212346077,
0.01402710098773241,
0.0977734625339508,
0.033785950392484665,
0.042336076498031616,
-0.02927195280790329,
0.017677899450063705,
0.01739584095776081,
0.09272617846727371,
-0.26092323660850525,
0.013475952669978142,
0.02416899986565113,
0.0017349119298160076,
-0.08174172043800354,
0.023271778598427773,
0.07229959219694138,
0.13189512491226196,
0.06577004492282867,
0.013317780569195747,
0.005312236957252026,
0.026511061936616898,
-0.13158933818340302,
0.07832600921392441,
0.0021375049836933613,
0.0028469713870435953,
0.04229776933789253,
-0.0837290957570076,
-0.00008880867972038686,
0.04968509078025818,
0.03448113426566124,
-0.12450768798589706,
-0.10085659474134445,
-0.012791204266250134,
0.2188323438167572,
-0.02339203841984272,
-0.0980505496263504,
0.007706332486122847,
-0.07094509899616241,
0.1359584778547287,
-0.05332016572356224,
-0.10236431658267975,
-0.06048772484064102,
-0.1056550145149231,
0.07513676583766937,
-0.04353707283735275,
0.05472402274608612,
-0.05808135122060776,
0.005000999663025141,
-0.004919731058180332,
-0.21132151782512665,
0.06908958405256271,
-0.14287324249744415,
-0.0754513293504715,
-0.005478765349835157,
0.0586044080555439,
-0.09450673311948776,
-0.008516592904925346,
0.02251921221613884,
-0.023219728842377663,
-0.09247662127017975,
-0.10325619578361511,
-0.08044496178627014,
0.09418238699436188,
0.015517487190663815,
0.011012370698153973,
-0.08706117421388626,
-0.04074566438794136,
0.0739535391330719,
-0.03777071088552475,
0.08617293834686279,
0.1867854744195938,
-0.0341942124068737,
0.05374329909682274,
0.22327345609664917,
-0.045626938343048096,
-0.3609531819820404,
-0.14203163981437683,
-0.1714751422405243,
-0.06742649525403976,
-0.022949693724513054,
-0.07925601303577423,
0.1853741556406021,
0.03472879156470299,
-0.07113885134458542,
0.11454227566719055,
-0.2247738391160965,
-0.09262143075466156,
0.1616658866405487,
0.037734776735305786,
0.27362948656082153,
-0.19604390859603882,
-0.039368435740470886,
-0.16697365045547485,
-0.14001114666461945,
0.05322093516588211,
-0.3212239444255829,
0.05595444515347481,
-0.02265971153974533,
-0.03152124956250191,
-0.02639772742986679,
-0.048053640872240067,
0.12309002131223679,
-0.03183414041996002,
0.07799699157476425,
-0.14199337363243103,
0.10358478128910065,
0.18084333837032318,
-0.06700976192951202,
0.12137454748153687,
-0.26917949318885803,
0.05201122537255287,
-0.06790901720523834,
0.0002427121071377769,
-0.02479572594165802,
0.018383491784334183,
-0.029548967257142067,
-0.07018294185400009,
-0.08543118834495544,
-0.02652568370103836,
0.061815325170755386,
0.013170485384762287,
0.09554839134216309,
-0.010247200727462769,
-0.01172731164842844,
0.27566877007484436,
0.07811162620782852,
-0.13766300678253174,
0.06953219324350357,
-0.030253281816840172,
-0.07656024396419525,
0.0776885598897934,
-0.2311355620622635,
0.07190506905317307,
0.024543454870581627,
-0.0781654492020607,
0.015649985522031784,
0.028243036940693855,
0.02572624571621418,
-0.0008402969688177109,
0.13783632218837738,
-0.12520922720432281,
-0.03315674513578415,
-0.005246132146567106,
0.049693647772073746,
-0.06037096679210663,
0.07073419541120529,
0.19125203788280487,
-0.05371943488717079,
0.017668835818767548,
-0.0061364686116576195,
0.06981924176216125,
-0.0910390317440033,
0.07681803405284882,
0.07207641005516052,
-0.004879475571215153,
-0.09214646369218826,
0.1532614827156067,
-0.0012559883762151003,
-0.02345338463783264,
0.00506917480379343,
0.031035007908940315,
-0.11655417829751968,
-0.13041861355304718,
0.07344160974025726,
-0.00020283606136217713,
-0.06448571383953094,
-0.09276407957077026,
-0.040606047958135605,
-0.11062527447938919,
0.009488836862146854,
0.006930751726031303,
0.0642218068242073,
0.05163180083036423,
0.03771384060382843,
-0.05165039002895355,
-0.04867711290717125,
0.06520602107048035,
0.02430904470384121,
0.060876745730638504,
-0.16610296070575714,
-0.05608309805393219,
-0.0338260754942894,
0.03202678635716438,
-0.042371153831481934,
0.05347117781639099,
-0.08599001169204712,
-0.004701667465269566,
-0.2905706763267517,
0.04411398246884346,
-0.07197058200836182,
0.019067635759711266,
0.0020703081972897053,
-0.009327300824224949,
-0.050946708768606186,
0.026823094114661217,
-0.043570131063461304,
-0.035460006445646286,
-0.021270666271448135,
0.058706823736429214,
-0.11180520057678223,
-0.045202892273664474,
0.025516893714666367,
-0.04206845909357071,
0.07868622988462448,
-0.0026882393285632133,
-0.10037343204021454,
0.04161982238292694,
-0.10719764977693558,
-0.057337336242198944,
0.0542740561068058,
0.03550659865140915,
-0.019539959728717804,
0.063497394323349,
-0.0178940761834383,
0.09890767186880112,
0.006439575459808111,
-0.0059572369791567326,
0.06738044321537018,
-0.07517164945602417,
-0.002087073167786002,
-0.09549794346094131,
0.0031686914153397083,
-0.019370663911104202,
-0.07102828472852707,
0.13327091932296753,
0.008368887938559055,
0.17197972536087036,
-0.05359221622347832,
-0.049266014248132706,
-0.1308465301990509,
0.025829358026385307,
-0.022601434960961342,
-0.1328180581331253,
-0.07593747228384018,
-0.04634260758757591,
-0.014250325970351696,
-0.017419278621673584,
0.17134645581245422,
0.026448260992765427,
-0.1466890424489975,
0.020937969908118248,
-0.011831293813884258,
0.06955926865339279,
0.01603664830327034,
0.3139246702194214,
0.04013114422559738,
-0.0048582167364656925,
-0.15589797496795654,
-0.028793949633836746,
0.14087006449699402,
-0.006762850563973188,
-0.02937251329421997,
0.15517699718475342,
-0.0092283571138978,
0.137692391872406,
0.032148197293281555,
-0.0010783267207443714,
0.02105925977230072,
0.011581463739275932,
-0.042735323309898376,
0.10687468200922012,
-0.03693203628063202,
0.06812000274658203,
0.18362738192081451,
-0.015204420313239098,
-0.05527421459555626,
-0.053457923233509064,
0.0012251423904672265,
-0.11953557282686234,
-0.18480032682418823,
-0.11321127414703369,
-0.1696227639913559,
-0.042637113481760025,
-0.07560523599386215,
-0.05129740759730339,
0.10609183460474014,
0.03542761504650116,
-0.02344590052962303,
0.08749611675739288,
-0.0645856261253357,
-0.03997563198208809,
0.038366954773664474,
-0.03688419237732887,
-0.07611262053251266,
0.09552957862615585,
-0.08275148272514343,
-0.002404420869424939,
-0.004788606893271208,
-0.017176615074276924,
0.07784675061702728,
0.03772473707795143,
0.11295784264802933,
-0.08172629773616791,
-0.07778435200452805,
-0.0625167116522789,
0.033300913870334625,
0.008823968470096588,
0.13384486734867096,
0.023113500326871872,
-0.04120281711220741,
0.06956102699041367,
0.15226168930530548,
-0.0676664486527443,
-0.16166628897190094,
-0.06361523270606995,
0.0350206196308136,
-0.06497712433338165,
0.05234811082482338,
-0.04474227502942085,
-0.05189081281423569,
-0.012510865926742554,
0.30458560585975647,
0.2888679504394531,
-0.08941489458084106,
0.03678987920284271,
-0.05337319150567055,
0.0058441245928406715,
-0.059265896677970886,
0.12699845433235168,
0.1183881163597107,
0.027691593393683434,
-0.0366043783724308,
0.0010004097130149603,
-0.029061894863843918,
-0.022911010310053825,
-0.15194658935070038,
0.028153909370303154,
-0.07289618998765945,
-0.053165826946496964,
-0.01754632405936718,
0.029324917122721672,
-0.062214940786361694,
0.053831081837415695,
0.003421528497710824,
-0.008730357512831688,
-0.006923608016222715,
-0.04494165629148483,
0.09051419794559479,
0.05284426361322403,
0.002270784694701433,
-0.07753345370292664,
0.0374872162938118,
0.046508897095918655,
-0.058355510234832764,
-0.1222565546631813,
-0.015523343347012997,
0.04844297096133232,
0.001187400659546256,
0.1666269451379776,
0.027670379728078842,
-0.020338095724582672,
0.09747537225484848,
-0.02612536959350109,
-0.1627255231142044,
0.11581140756607056,
-0.0034137764014303684,
-0.05142446979880333,
0.033840592950582504,
-0.08621691912412643,
-0.06252901256084442,
0.016390739008784294,
0.03750988468527794,
0.03900335729122162,
-0.01887388527393341,
0.09966131299734116,
-0.03561981022357941,
-0.078755684196949,
-0.020577838644385338,
-0.0892663449048996,
0.09442443400621414,
-0.0012482936726883054,
-0.08142432570457458,
-0.02228453755378723,
-0.04560784250497818,
0.049680452793836594,
-0.011476666666567326,
-0.12653809785842896,
0.03450152277946472,
-0.041960034519433975,
-0.0302377138286829,
0.028941882774233818,
0.06584790349006653,
-0.2328040450811386,
0.014337110333144665,
-0.07532259076833725,
-0.00844990648329258,
-0.12415196001529694,
0.071121446788311,
0.1776650846004486,
0.004937915131449699,
-0.03829115629196167,
-0.0820891484618187,
-0.028681457042694092,
0.06613849103450775,
-0.03490187227725983,
-0.12818829715251923
] |
null | null | transformers |
# Uploaded model
- **Developed by:** devlocalhost
- **License:** apache-2.0
- **Finetuned from model :** unsloth/tinyllama-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "gguf"], "base_model": "unsloth/tinyllama-bnb-4bit"} | null | devlocalhost/hi-tinylama-gguf-16bit-3e | [
"transformers",
"gguf",
"llama",
"text-generation-inference",
"unsloth",
"en",
"base_model:unsloth/tinyllama-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:34:20+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-unsloth/tinyllama-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: devlocalhost
- License: apache-2.0
- Finetuned from model : unsloth/tinyllama-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: devlocalhost\n- License: apache-2.0\n- Finetuned from model : unsloth/tinyllama-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
"TAGS\n#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-unsloth/tinyllama-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: devlocalhost\n- License: apache-2.0\n- Finetuned from model : unsloth/tinyllama-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
63,
77
] | [
"passage: TAGS\n#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-unsloth/tinyllama-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: devlocalhost\n- License: apache-2.0\n- Finetuned from model : unsloth/tinyllama-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
-0.0538182333111763,
0.08290159702301025,
-0.003552909940481186,
0.10400661826133728,
0.06262490153312683,
0.0209392998367548,
0.07172271609306335,
0.138449028134346,
-0.07810983806848526,
-0.010014447383582592,
0.11751418560743332,
0.10851263999938965,
0.03440818935632706,
-0.04280872270464897,
0.02756088227033615,
-0.16693463921546936,
0.08626529574394226,
-0.018009845167398453,
-0.13191670179367065,
0.02869298681616783,
0.06574010848999023,
-0.020178696140646935,
0.0907125174999237,
-0.04009813070297241,
-0.04183928668498993,
0.020637452602386475,
-0.0441109798848629,
-0.02541320212185383,
-0.009225201793015003,
0.08406883478164673,
-0.03431571274995804,
0.020233578979969025,
0.03746427595615387,
-0.13020940124988556,
0.03127383068203926,
0.04994894564151764,
0.01395532675087452,
0.05043729767203331,
-0.023561157286167145,
0.08439270406961441,
0.15438084304332733,
-0.01199878565967083,
-0.09138554334640503,
0.048122480511665344,
-0.00946433562785387,
-0.14949899911880493,
-0.038899172097444534,
0.1262323409318924,
0.004871254321187735,
0.048547644168138504,
0.03563090041279793,
0.05303877219557762,
-0.07921618223190308,
0.027076944708824158,
0.1380787491798401,
-0.25424396991729736,
-0.0843268483877182,
0.13268472254276276,
0.02652960829436779,
0.04423288628458977,
-0.030500710010528564,
0.05403297767043114,
0.056652434170246124,
0.011584908701479435,
0.026569919660687447,
-0.06168270856142044,
-0.12270066142082214,
0.06923934817314148,
-0.09368593245744705,
0.013736646622419357,
0.1572188436985016,
0.06454862654209137,
-0.033831704407930374,
0.010506252758204937,
-0.10356929153203964,
0.023136379197239876,
-0.07667750865221024,
0.06194937229156494,
0.08506999164819717,
0.10081296414136887,
-0.0026910321321338415,
-0.10378242284059525,
-0.055965621024370193,
-0.03335432708263397,
-0.09792344272136688,
0.05703955888748169,
0.07370080798864365,
0.1097823977470398,
-0.05340328440070152,
0.061170630156993866,
0.026326652616262436,
-0.13290126621723175,
-0.06096755713224411,
-0.0424998514354229,
0.132180318236351,
0.11112464964389801,
-0.05457163602113724,
0.08026473224163055,
0.1824835240840912,
0.15887004137039185,
0.13580338656902313,
0.0481351800262928,
0.01654859445989132,
0.03372551500797272,
-0.08058813214302063,
0.04438929259777069,
-0.16679653525352478,
-0.05739200860261917,
0.13822637498378754,
0.06630194932222366,
0.08471643179655075,
0.007997208274900913,
-0.08824044466018677,
-0.04274202138185501,
-0.05724648758769035,
0.053486429154872894,
0.07383488118648529,
0.08153709769248962,
0.012031719088554382,
-0.04702906310558319,
-0.018188174813985825,
-0.09660383313894272,
-0.043955300003290176,
-0.025341136381030083,
-0.06764958798885345,
0.1840471625328064,
0.08239538222551346,
-0.01042177900671959,
-0.05763706937432289,
-0.11342934519052505,
-0.07076792418956757,
-0.04571769759058952,
-0.022414082661271095,
0.01465998962521553,
0.0694245919585228,
-0.061445243656635284,
0.02225373312830925,
-0.14429409801959991,
-0.24331651628017426,
0.047399625182151794,
0.14956770837306976,
-0.03898663818836212,
-0.05144133046269417,
-0.025635533034801483,
-0.049764733761548996,
0.03622525930404663,
-0.056293971836566925,
0.04205700755119324,
-0.08766421675682068,
0.03901071473956108,
-0.017509371042251587,
0.08068910241127014,
-0.15019257366657257,
0.029461724683642387,
-0.08560577034950256,
0.04600431025028229,
-0.017111243680119514,
0.08621934056282043,
-0.06542417407035828,
0.13286419212818146,
-0.1070692166686058,
0.021339261904358864,
-0.08100564032793045,
0.03381248936057091,
0.033848896622657776,
0.13590914011001587,
-0.1297304332256317,
0.007631066720932722,
0.15785980224609375,
-0.02126423269510269,
-0.1181865781545639,
0.10575259476900101,
0.010121188126504421,
0.06737615913152695,
0.09902521222829819,
0.10461577028036118,
0.149929016828537,
-0.08338358253240585,
0.015492464415729046,
0.14698095619678497,
0.018794646486639977,
-0.14174588024616241,
0.07647053152322769,
0.02938821166753769,
-0.11149855703115463,
0.09654425829648972,
-0.08327916264533997,
0.1465301662683487,
0.023592809215188026,
-0.07289525866508484,
-0.12433089315891266,
-0.13359442353248596,
-0.07082552462816238,
-0.014549940824508667,
0.007580921985208988,
0.008968036621809006,
-0.06709820032119751,
-0.009587890468537807,
0.183336079120636,
-0.06945040822029114,
0.022840043529868126,
-0.06670399755239487,
0.07343971729278564,
-0.12054227292537689,
0.09125720709562302,
-0.05120346322655678,
0.006132433190941811,
-0.0345369353890419,
-0.052415162324905396,
0.09162615239620209,
0.05067715793848038,
0.0526522733271122,
-0.06259072571992874,
-0.016323622316122055,
0.04080308973789215,
0.06578874588012695,
-0.02703927457332611,
-0.04402797669172287,
-0.08870904892683029,
0.04622899740934372,
0.009830029681324959,
0.11210351437330246,
-0.04286408796906471,
0.038401588797569275,
-0.045951828360557556,
0.07203680276870728,
-0.04536517336964607,
0.06564685702323914,
0.031139135360717773,
-0.10449417680501938,
-0.017866889014840126,
-0.09118581563234329,
0.08121214061975479,
0.056991782039403915,
-0.061743538826704025,
0.07987556606531143,
0.012201470322906971,
0.11317674070596695,
0.17660795152187347,
0.032067134976387024,
0.0913555920124054,
0.041836388409137726,
-0.02936955913901329,
-0.0016761268489062786,
0.06195202097296715,
0.00006006513285683468,
-0.01692419871687889,
0.00004354761040303856,
0.12974070012569427,
-0.11307891458272934,
-0.009155935607850552,
0.01765945553779602,
-0.06604817509651184,
0.03084721229970455,
0.03518721088767052,
0.14206159114837646,
-0.04116450622677803,
0.06688693165779114,
0.2598881721496582,
-0.07629159837961197,
0.1193348690867424,
-0.08819326758384705,
-0.07118967175483704,
0.013397040776908398,
0.012615884654223919,
-0.010900674387812614,
0.012465547770261765,
-0.008685306645929813,
0.044735901057720184,
0.042281374335289,
-0.00253477250225842,
0.06447967141866684,
-0.12590886652469635,
-0.00983254425227642,
-0.006547464057803154,
-0.08814379572868347,
0.040059152990579605,
0.04321477562189102,
-0.0933871641755104,
0.06543612480163574,
-0.011016417294740677,
-0.06409236788749695,
0.04789765551686287,
0.0408671535551548,
-0.001878008246421814,
0.12023595720529556,
-0.08058622479438782,
-0.1545182466506958,
-0.1624288260936737,
-0.05769424885511398,
-0.133874773979187,
-0.00036501677823252976,
0.061144549399614334,
-0.0847906768321991,
-0.06537754088640213,
-0.07154424488544464,
0.013256380334496498,
0.02660081908106804,
0.03785242885351181,
0.07536838948726654,
0.03911186754703522,
0.08212277293205261,
-0.12694157660007477,
-0.005317917559295893,
0.028667351230978966,
-0.05855819955468178,
-0.04191293939948082,
-0.07626154273748398,
0.07850352674722672,
0.11742743104696274,
0.04510778933763504,
-0.02270747907459736,
0.08120819926261902,
0.13899320363998413,
0.027449091896414757,
0.06286995112895966,
0.26008525490760803,
0.07832811027765274,
0.07113412767648697,
0.08792766183614731,
0.006108679808676243,
-0.07856439799070358,
-0.013260112144052982,
0.038040000945329666,
-0.06873538345098495,
-0.17867709696292877,
0.002155161462724209,
-0.090294748544693,
0.03495632857084274,
0.06735449284315109,
0.08335282653570175,
-0.023377258330583572,
0.17734938859939575,
-0.047039858996868134,
0.12939152121543884,
-0.01989828795194626,
0.03919939696788788,
0.18735045194625854,
-0.0008583518210798502,
0.07462233304977417,
-0.13986876606941223,
-0.030400101095438004,
0.14662638306617737,
0.09080827981233597,
0.10477518290281296,
-0.010658332146704197,
0.02794375643134117,
0.046779535710811615,
0.1402815729379654,
-0.006271633785218,
0.08993937075138092,
-0.04092859476804733,
-0.007430294994264841,
-0.06764012575149536,
-0.05748097226023674,
-0.07192384451627731,
0.048590317368507385,
-0.09206285327672958,
-0.050619643181562424,
0.02172011509537697,
0.10529763251543045,
0.06290608644485474,
0.23591774702072144,
0.03556344285607338,
-0.2324485182762146,
-0.036995697766542435,
0.0745854452252388,
0.005633516702800989,
-0.033189933747053146,
0.08365516364574432,
0.0013251594500616193,
0.015228518284857273,
0.0537228137254715,
-0.021980876103043556,
0.12862174212932587,
0.025763018056750298,
0.04291045665740967,
0.012094127014279366,
0.12724357843399048,
0.07619430124759674,
0.10879398137331009,
-0.18463709950447083,
-0.029233571141958237,
0.01891155168414116,
0.035201024264097214,
-0.05628541484475136,
0.017111442983150482,
0.1242547407746315,
0.0749845802783966,
0.07366474717855453,
-0.0023390280548483133,
0.025125913321971893,
0.049677975475788116,
-0.16623488068580627,
0.1029273048043251,
-0.012669703923165798,
-0.006327481474727392,
0.07465031743049622,
-0.10457752645015717,
-0.00403459882363677,
0.018081560730934143,
0.05425344780087471,
-0.05546247214078903,
-0.13701602816581726,
-0.014112455770373344,
0.16923874616622925,
-0.07998581230640411,
-0.057612255215644836,
0.027010168880224228,
-0.06894711405038834,
0.14163938164710999,
-0.001997864106670022,
-0.09915059059858322,
-0.07354488968849182,
-0.0344863086938858,
0.1505253165960312,
-0.05823042616248131,
0.030193248763680458,
-0.1037050113081932,
-0.009145000949501991,
0.044497765600681305,
-0.22496363520622253,
0.0270835030823946,
-0.08897846937179565,
-0.018071062862873077,
0.017759645357728004,
0.03908388316631317,
-0.12589015066623688,
-0.023452499881386757,
0.01008730847388506,
-0.05606646090745926,
-0.10203052312135696,
-0.1302315890789032,
-0.10155139118432999,
0.1656174510717392,
-0.07350414991378784,
-0.008406121283769608,
-0.1082213744521141,
0.060880713164806366,
0.021483974531292915,
-0.005219536833465099,
0.04385041445493698,
0.16351431608200073,
-0.02633742056787014,
0.056649334728717804,
0.19366049766540527,
-0.05583959072828293,
-0.31515777111053467,
-0.14887258410453796,
-0.07110082358121872,
-0.038768470287323,
-0.07634780555963516,
-0.1457689255475998,
0.1952340006828308,
0.07921804487705231,
-0.043658290058374405,
0.1497403234243393,
-0.28862351179122925,
-0.0800158828496933,
0.11142953485250473,
-0.0006843531737104058,
0.3092193901538849,
-0.16951459646224976,
-0.052176814526319504,
-0.15671119093894958,
-0.21114452183246613,
0.08823588490486145,
-0.2650364637374878,
0.12920206785202026,
-0.05389447882771492,
0.02963831089437008,
-0.007925816811621189,
-0.016710873693227768,
0.1433100551366806,
0.001093667815439403,
0.05653093382716179,
-0.11143741011619568,
0.12480582296848297,
0.09655119478702545,
-0.07980645447969437,
0.1748618632555008,
-0.24165698885917664,
0.06632821261882782,
-0.10739423334598541,
-0.025977572426199913,
-0.011231601238250732,
-0.013317174278199673,
0.01923767477273941,
-0.025981388986110687,
-0.11505724489688873,
-0.014032406732439995,
0.07667161524295807,
0.02470247820019722,
0.09968064725399017,
0.03416077792644501,
-0.12197286635637283,
0.17475174367427826,
-0.01350673008710146,
-0.12370893359184265,
-0.015169456601142883,
-0.0951584056019783,
-0.03815879300236702,
0.08115680515766144,
-0.30057471990585327,
0.04648731276392937,
0.07209808379411697,
-0.06647428870201111,
0.0048974547535181046,
0.021136276423931122,
0.015820659697055817,
-0.01729232631623745,
0.0826842412352562,
-0.08456962555646896,
-0.07271087169647217,
-0.027722910046577454,
0.004770438652485609,
-0.0848885029554367,
0.03960064426064491,
0.15161551535129547,
-0.05769607797265053,
0.01619306392967701,
0.009382154792547226,
0.02901272289454937,
-0.08148360997438431,
0.0914563238620758,
0.09485998004674911,
-0.034703079611063004,
-0.11145695298910141,
0.16196005046367645,
-0.015757029876112938,
0.027900857850909233,
0.00275241257622838,
0.050231531262397766,
-0.10618248581886292,
-0.08286215364933014,
0.033468931913375854,
0.0375969335436821,
-0.1888454705476761,
-0.06176598742604256,
-0.08555832505226135,
-0.07373985648155212,
0.05055323988199234,
-0.037923142313957214,
0.0599035806953907,
0.026699520647525787,
-0.027662694454193115,
-0.024668773636221886,
-0.031927723437547684,
0.02928214520215988,
0.0498141385614872,
0.04742081090807915,
-0.1915077269077301,
-0.04415486752986908,
-0.006901704706251621,
0.05804622918367386,
-0.0385635644197464,
0.04587025195360184,
-0.07324910163879395,
0.003776178229600191,
-0.3527652323246002,
0.047541502863168716,
-0.03395943343639374,
0.03449365869164467,
0.014700088649988174,
-0.024384789168834686,
-0.07840330898761749,
0.04996233806014061,
-0.07288546860218048,
-0.04551819711923599,
-0.042428016662597656,
0.01055197138339281,
-0.08168195933103561,
-0.04992649331688881,
0.021306393668055534,
-0.054187893867492676,
0.023711828514933586,
0.023768877610564232,
-0.0685032457113266,
0.054031774401664734,
-0.09786994010210037,
-0.07932952791452408,
0.029794514179229736,
0.06680533289909363,
-0.029615722596645355,
0.091956727206707,
0.034011028707027435,
0.05668012797832489,
0.04795272648334503,
-0.047093465924263,
0.01713208109140396,
-0.08665694296360016,
-0.07994592189788818,
-0.10416200757026672,
0.03197150677442551,
-0.03274863213300705,
-0.052755508571863174,
0.12763439118862152,
0.1187969297170639,
0.16275523602962494,
-0.011811312288045883,
-0.05437662824988365,
-0.14327649772167206,
0.01638646610081196,
-0.013045072555541992,
-0.10845035314559937,
-0.019038796424865723,
-0.10092507302761078,
-0.006741214077919722,
-0.03608852997422218,
0.13222916424274445,
0.004525781609117985,
-0.07770650088787079,
-0.02157282643020153,
0.016060467809438705,
0.07532248646020889,
-0.03350021317601204,
0.30501070618629456,
0.09718248248100281,
0.05466604232788086,
-0.09150570631027222,
-0.02472038008272648,
0.13624924421310425,
0.023978425189852715,
-0.01976766251027584,
0.12248599529266357,
-0.007503865286707878,
0.19354432821273804,
0.04664965346455574,
0.04514395073056221,
0.03394847363233566,
0.115899957716465,
-0.03840126842260361,
0.08170685172080994,
-0.04400961473584175,
0.1422339677810669,
0.14814601838588715,
-0.054418474435806274,
-0.023423193022608757,
-0.031766071915626526,
-0.011211274191737175,
-0.13882941007614136,
-0.1395612508058548,
-0.09878131747245789,
-0.1725858896970749,
-0.0016558457864448428,
-0.04767872020602226,
0.018478918820619583,
0.11534523963928223,
0.012225834652781487,
0.01757095754146576,
0.05891679227352142,
-0.06413699686527252,
-0.08846864849328995,
0.07012316584587097,
-0.02279435656964779,
-0.1032460480928421,
0.11268001049757004,
-0.05735568702220917,
0.04396970570087433,
-0.005591657944023609,
0.004359664861112833,
0.037526145577430725,
0.0740584135055542,
0.07087462395429611,
-0.0815637856721878,
-0.023583658039569855,
-0.06192590296268463,
0.03931504860520363,
0.03375471010804176,
0.06763625890016556,
0.04003329575061798,
-0.05674163997173309,
0.03532559052109718,
0.1334165632724762,
-0.08218888193368912,
-0.13031835854053497,
-0.1027425229549408,
0.014621187001466751,
-0.07383321225643158,
0.027861740440130234,
-0.03883924335241318,
-0.022027619183063507,
-0.02842376008629799,
0.36063826084136963,
0.12117274850606918,
-0.16743454337120056,
-0.036549754440784454,
-0.020516561344265938,
0.008091629482805729,
-0.05040104687213898,
0.16580666601657867,
0.14371643960475922,
0.06771721690893173,
-0.04172668606042862,
-0.05369007959961891,
-0.02490939013659954,
-0.025922901928424835,
-0.16418981552124023,
0.03819159418344498,
-0.10239242017269135,
-0.021684905514121056,
-0.016444630920886993,
-0.009463989175856113,
-0.08996155858039856,
-0.009411143139004707,
0.023353692144155502,
0.039123427122831345,
-0.0399615503847599,
-0.10649742186069489,
0.002494317479431629,
0.06658399105072021,
-0.006290273740887642,
-0.10480567812919617,
0.059599075466394424,
0.11657772958278656,
-0.0490754060447216,
-0.17682434618473053,
-0.04875688627362251,
0.08107522130012512,
0.08963996171951294,
0.11247718334197998,
0.0459209643304348,
-0.006337487604469061,
0.08024483174085617,
-0.047892436385154724,
-0.15894939005374908,
0.07783827185630798,
-0.021496038883924484,
-0.04832546412944794,
0.018732866272330284,
-0.08479850739240646,
-0.07275092601776123,
-0.027716567739844322,
0.03453674539923668,
0.15165111422538757,
-0.06163845956325531,
0.11546234041452408,
-0.010215625166893005,
-0.08939334005117416,
-0.031009972095489502,
-0.10827548801898956,
0.09175753593444824,
0.07404708117246628,
-0.06458372622728348,
-0.04840179160237312,
-0.10092651844024658,
0.08998555690050125,
0.01717088744044304,
-0.12308524549007416,
0.023245930671691895,
0.01307748630642891,
-0.06899306923151016,
0.02651211805641651,
0.05498746037483215,
-0.1463969498872757,
-0.020588897168636322,
-0.0569230318069458,
-0.012792310677468777,
-0.06125134974718094,
0.11217144876718521,
0.15699714422225952,
0.04329914599657059,
-0.0293591246008873,
-0.12959496676921844,
-0.04029751196503639,
0.01603137142956257,
-0.03620908036828041,
-0.10421261191368103
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-960h-finetuned-ks
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9308
- Accuracy: 0.7752
- F1: 0.7749
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.3739 | 0.99 | 35 | 1.3646 | 0.3654 | 0.2858 |
| 1.3444 | 2.0 | 71 | 1.3366 | 0.3833 | 0.3172 |
| 1.3193 | 2.99 | 106 | 1.2654 | 0.4324 | 0.3350 |
| 1.2447 | 4.0 | 142 | 1.2093 | 0.4649 | 0.3611 |
| 1.2087 | 4.99 | 177 | 1.2030 | 0.4582 | 0.3714 |
| 1.1539 | 6.0 | 213 | 1.1419 | 0.4920 | 0.4317 |
| 1.0795 | 6.99 | 248 | 1.1794 | 0.4721 | 0.4207 |
| 1.0525 | 8.0 | 284 | 1.0922 | 0.5020 | 0.4684 |
| 1.0615 | 8.99 | 319 | 1.0459 | 0.5471 | 0.5158 |
| 0.9381 | 10.0 | 355 | 1.0080 | 0.5656 | 0.5464 |
| 0.8945 | 10.99 | 390 | 1.1166 | 0.5378 | 0.5108 |
| 0.8497 | 12.0 | 426 | 1.0068 | 0.5855 | 0.5772 |
| 0.7729 | 12.99 | 461 | 1.1214 | 0.5517 | 0.5406 |
| 0.6984 | 14.0 | 497 | 1.0416 | 0.5889 | 0.5729 |
| 0.6856 | 14.99 | 532 | 1.0135 | 0.6180 | 0.6185 |
| 0.6095 | 16.0 | 568 | 1.0088 | 0.6320 | 0.6299 |
| 0.5899 | 16.99 | 603 | 0.9208 | 0.6585 | 0.6612 |
| 0.5922 | 18.0 | 639 | 0.8657 | 0.6757 | 0.6749 |
| 0.537 | 18.99 | 674 | 0.8910 | 0.6850 | 0.6892 |
| 0.4767 | 20.0 | 710 | 1.0544 | 0.6525 | 0.6499 |
| 0.4864 | 20.99 | 745 | 0.8024 | 0.7255 | 0.7232 |
| 0.3546 | 22.0 | 781 | 0.8628 | 0.7168 | 0.7205 |
| 0.3567 | 22.99 | 816 | 0.8921 | 0.7168 | 0.7177 |
| 0.381 | 24.0 | 852 | 0.9130 | 0.7069 | 0.7081 |
| 0.3031 | 24.99 | 887 | 1.0026 | 0.7023 | 0.7039 |
| 0.412 | 26.0 | 923 | 0.8413 | 0.7420 | 0.7430 |
| 0.3175 | 26.99 | 958 | 0.8705 | 0.7294 | 0.7335 |
| 0.2581 | 28.0 | 994 | 0.8628 | 0.7387 | 0.7431 |
| 0.328 | 28.99 | 1029 | 0.9022 | 0.7414 | 0.7417 |
| 0.263 | 30.0 | 1065 | 0.9787 | 0.7248 | 0.7251 |
| 0.249 | 30.99 | 1100 | 0.8658 | 0.7454 | 0.7481 |
| 0.2242 | 32.0 | 1136 | 0.9386 | 0.7354 | 0.7380 |
| 0.2848 | 32.99 | 1171 | 0.8553 | 0.7633 | 0.7639 |
| 0.2457 | 34.0 | 1207 | 0.8789 | 0.7692 | 0.7674 |
| 0.1557 | 34.99 | 1242 | 0.8542 | 0.7553 | 0.7594 |
| 0.169 | 36.0 | 1278 | 0.9132 | 0.7573 | 0.7600 |
| 0.171 | 36.99 | 1313 | 0.9550 | 0.7467 | 0.7481 |
| 0.2209 | 38.0 | 1349 | 0.9843 | 0.7407 | 0.7408 |
| 0.1674 | 38.99 | 1384 | 0.9523 | 0.7460 | 0.7468 |
| 0.1998 | 40.0 | 1420 | 0.8683 | 0.7686 | 0.7697 |
| 0.1101 | 40.99 | 1455 | 1.0123 | 0.7354 | 0.7370 |
| 0.1466 | 42.0 | 1491 | 0.9332 | 0.7633 | 0.7651 |
| 0.1376 | 42.99 | 1526 | 0.9193 | 0.7739 | 0.7743 |
| 0.0939 | 44.0 | 1562 | 0.9234 | 0.7626 | 0.7634 |
| 0.1333 | 44.99 | 1597 | 0.9308 | 0.7752 | 0.7749 |
| 0.1183 | 46.0 | 1633 | 0.9375 | 0.7706 | 0.7712 |
| 0.1031 | 46.99 | 1668 | 0.9298 | 0.7739 | 0.7750 |
| 0.1154 | 48.0 | 1704 | 0.9373 | 0.7739 | 0.7745 |
| 0.1317 | 48.99 | 1739 | 0.9611 | 0.7646 | 0.7654 |
| 0.1132 | 49.3 | 1750 | 0.9606 | 0.7626 | 0.7635 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "facebook/wav2vec2-base-960h", "model-index": [{"name": "wav2vec2-base-960h-finetuned-ks", "results": []}]} | audio-classification | Rest970828/wav2vec2-base-960h-finetuned-ks | [
"transformers",
"safetensors",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"base_model:facebook/wav2vec2-base-960h",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:34:58+00:00 | [] | [] | TAGS
#transformers #safetensors #wav2vec2 #audio-classification #generated_from_trainer #base_model-facebook/wav2vec2-base-960h #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-960h-finetuned-ks
===============================
This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9308
* Accuracy: 0.7752
* F1: 0.7749
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.36.2
* Pytorch 2.1.1+cu121
* Datasets 2.16.1
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.36.2\n* Pytorch 2.1.1+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #wav2vec2 #audio-classification #generated_from_trainer #base_model-facebook/wav2vec2-base-960h #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.36.2\n* Pytorch 2.1.1+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.0"
] | [
65,
144,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #wav2vec2 #audio-classification #generated_from_trainer #base_model-facebook/wav2vec2-base-960h #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.36.2\n* Pytorch 2.1.1+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.0"
] | [
-0.14708378911018372,
0.0985463485121727,
-0.0016391176031902432,
0.08987800776958466,
0.14966905117034912,
0.016803201287984848,
0.1300368309020996,
0.09533407539129257,
-0.11827083677053452,
0.06785225123167038,
0.09430582076311111,
0.08899397403001785,
0.031177064403891563,
0.1263170689344406,
-0.03938843309879303,
-0.26096224784851074,
0.005422217771410942,
0.024082310497760773,
-0.14361004531383514,
0.133546382188797,
0.08593302965164185,
-0.13304151594638824,
0.056012555956840515,
0.012531482614576817,
-0.1789495348930359,
-0.004972628317773342,
0.0062230792827904224,
-0.07430313527584076,
0.12725870311260223,
0.007586182095110416,
0.11928614228963852,
0.044360291212797165,
0.11682792007923126,
-0.17273388803005219,
0.009704729542136192,
0.07504341751337051,
0.01601129025220871,
0.09779774397611618,
0.10067345947027206,
-0.00023082373081706464,
0.08049076050519943,
-0.07251892983913422,
0.055727049708366394,
0.03766936808824539,
-0.1148066520690918,
-0.2836698591709137,
-0.10001103579998016,
0.08691196143627167,
0.11162542551755905,
0.09386809915304184,
-0.01098658237606287,
0.10315766930580139,
-0.08121151477098465,
0.08539873361587524,
0.2768844962120056,
-0.2849601209163666,
-0.07352760434150696,
0.007686049211770296,
0.04223214089870453,
0.03998272493481636,
-0.12197991460561752,
-0.023047462105751038,
0.05922845005989075,
0.03415438532829285,
0.13141068816184998,
0.0014604012249037623,
-0.04229341447353363,
-0.005376417189836502,
-0.15077297389507294,
-0.04746000096201897,
0.11429018527269363,
0.063053660094738,
-0.053950969129800797,
-0.043036993592977524,
-0.05648018792271614,
-0.21969439089298248,
-0.03755486384034157,
0.01194750051945448,
0.027742939069867134,
-0.0710814967751503,
-0.10839749127626419,
0.033683691173791885,
-0.08515293151140213,
-0.11364385485649109,
0.01830335706472397,
0.19809061288833618,
0.05033816397190094,
0.010713138617575169,
-0.006457311101257801,
0.13822536170482635,
0.04145585745573044,
-0.1750314086675644,
0.03159357234835625,
0.029643073678016663,
-0.0541020892560482,
-0.012399252504110336,
-0.03526068851351738,
0.013437832705676556,
-0.0031845862977206707,
0.14547383785247803,
-0.11960186064243317,
0.027309628203511238,
0.04355749115347862,
0.038218267261981964,
-0.09789898246526718,
0.14743728935718536,
-0.08684132248163223,
-0.04561665654182434,
-0.00926190335303545,
0.11521228402853012,
0.02850235626101494,
-0.005568121559917927,
-0.08220577239990234,
0.008917116560041904,
0.10381294786930084,
0.03469623625278473,
-0.037097230553627014,
0.02447417750954628,
-0.05519324913620949,
-0.025379443541169167,
0.06032625585794449,
-0.08442717045545578,
0.020561717450618744,
0.02796923741698265,
-0.0747159868478775,
-0.0305599607527256,
0.0066667417995631695,
0.015554694458842278,
0.008562581613659859,
0.1604456901550293,
-0.0876716896891594,
-0.008227851241827011,
-0.09167300909757614,
-0.09301500022411346,
0.0260313767939806,
-0.07051530480384827,
0.014296245761215687,
-0.07978340983390808,
-0.13590440154075623,
-0.011818679049611092,
0.042989861220121384,
-0.032023560255765915,
-0.073391392827034,
-0.011571424081921577,
-0.11697200685739517,
0.03252959996461868,
-0.026286108419299126,
0.1528812199831009,
-0.06335607916116714,
0.13312749564647675,
0.0570099838078022,
0.060692302882671356,
0.02105940878391266,
0.051642317324876785,
-0.0795825943350792,
0.04002692177891731,
-0.1985582709312439,
0.013768954202532768,
-0.07443073391914368,
0.036788687109947205,
-0.089161217212677,
-0.135874405503273,
0.013555352576076984,
-0.011200646869838238,
0.09479054808616638,
0.1113467589020729,
-0.15211401879787445,
-0.10247605293989182,
0.13745559751987457,
-0.10618665814399719,
-0.12142450362443924,
0.12295892834663391,
-0.009097420610487461,
-0.0328495018184185,
0.02538006566464901,
0.12083401530981064,
0.0920097604393959,
-0.10885447263717651,
-0.03640211746096611,
-0.03942108526825905,
0.09483177959918976,
-0.02055799961090088,
0.10500679165124893,
0.0030792958568781614,
0.018417635932564735,
-0.0007941397489048541,
-0.0590185821056366,
0.05078753083944321,
-0.11806205660104752,
-0.08388470858335495,
-0.03858695551753044,
-0.10609561204910278,
0.0785011574625969,
0.06877715140581131,
0.02740875445306301,
-0.08958861231803894,
-0.11652122437953949,
0.044532790780067444,
0.12263289093971252,
-0.06189708411693573,
0.010823817923665047,
-0.06147058680653572,
0.08836361765861511,
-0.06373333185911179,
-0.03525925055146217,
-0.19233562052249908,
-0.030349167063832283,
0.015452496707439423,
-0.03298640251159668,
-0.008075681515038013,
-0.026282215490937233,
0.06827045232057571,
0.10671944916248322,
-0.07996590435504913,
-0.09933643043041229,
-0.10707352310419083,
-0.005026268772780895,
-0.08176492899656296,
-0.23858727514743805,
-0.09628043323755264,
-0.016743788495659828,
0.1240716502070427,
-0.19488897919654846,
0.019196074455976486,
0.01355009712278843,
0.1298176646232605,
0.042609211057424545,
-0.025067979469895363,
-0.019050216302275658,
0.0893855169415474,
-0.012678761966526508,
-0.060557447373867035,
0.029222333803772926,
0.0048756361939013,
-0.06658996641635895,
-0.03767312690615654,
-0.0926942303776741,
0.20355373620986938,
0.12012698501348495,
-0.02283102460205555,
-0.08877729624509811,
0.020299183204770088,
-0.09801854193210602,
-0.054674770683050156,
-0.05657382309436798,
0.007711096201092005,
0.12532193958759308,
0.020778043195605278,
0.12635836005210876,
-0.09175378084182739,
-0.045821983367204666,
0.052034784108400345,
-0.004075557924807072,
0.02168453112244606,
0.11499259620904922,
0.08443661779165268,
-0.05453206226229668,
0.14018435776233673,
0.15074001252651215,
-0.09826727211475372,
0.1435408592224121,
-0.08162334561347961,
-0.10346842557191849,
-0.01883224956691265,
-0.008191753178834915,
0.013230571523308754,
0.1638181060552597,
-0.08159595727920532,
0.015822432935237885,
0.022240955382585526,
0.01160737220197916,
0.006458629854023457,
-0.2226022183895111,
-0.025180818513035774,
0.015431931242346764,
-0.05131922662258148,
-0.05013637617230415,
-0.014356082305312157,
0.018109429627656937,
0.10480935871601105,
-0.008614142425358295,
-0.07432755827903748,
0.015272454358637333,
0.006894636433571577,
-0.06521760672330856,
0.19953833520412445,
-0.07232674211263657,
-0.1311473250389099,
-0.13670341670513153,
0.00992570724338293,
-0.04642711207270622,
-0.010106125846505165,
0.051322195678949356,
-0.10001714527606964,
-0.027890965342521667,
-0.03286777809262276,
0.052222903817892075,
0.01813117042183876,
0.04626478627324104,
0.025197407230734825,
0.024376146495342255,
0.09233938157558441,
-0.09853862971067429,
0.027786169201135635,
-0.03116789646446705,
-0.04772602394223213,
0.022530436515808105,
0.08336810767650604,
0.09714008122682571,
0.156881645321846,
0.00500982953235507,
-0.0006024707690812647,
-0.014929192140698433,
0.19590239226818085,
-0.10495008528232574,
-0.02234989032149315,
0.16162490844726562,
-0.007975473068654537,
0.04738253727555275,
0.13361257314682007,
0.07691089808940887,
-0.07165835797786713,
0.007382646203041077,
0.0438404344022274,
-0.023001952096819878,
-0.2377937138080597,
-0.040432579815387726,
-0.0358741395175457,
0.003957213368266821,
0.09002895653247833,
0.025154590606689453,
0.003901989897713065,
0.05354548245668411,
-0.026577219367027283,
0.02341012842953205,
-0.03348026052117348,
0.055685751140117645,
0.03303591534495354,
0.05409018322825432,
0.12981584668159485,
-0.03002883307635784,
-0.04165999963879585,
0.024815402925014496,
-0.01311578694730997,
0.2145831137895584,
-0.0310647152364254,
0.09832333773374557,
0.060006607323884964,
0.17866250872612,
0.01753312163054943,
0.10387358069419861,
0.00995428953319788,
-0.04231660068035126,
0.02031964622437954,
-0.06399445980787277,
-0.011056983843445778,
0.011885760352015495,
-0.02592087723314762,
0.08786774426698685,
-0.147064670920372,
0.008116190321743488,
0.03185117617249489,
0.33248215913772583,
0.0691945031285286,
-0.32466384768486023,
-0.12726891040802002,
-0.012549014762043953,
-0.04084031656384468,
-0.04045049473643303,
0.02669428288936615,
0.13597851991653442,
-0.08338712155818939,
0.0508931428194046,
-0.0724959447979927,
0.08015147596597672,
-0.02277895249426365,
0.021166447550058365,
0.11627301573753357,
0.09565363079309464,
-0.0023534889332950115,
0.05089270696043968,
-0.22369475662708282,
0.2992841601371765,
0.013423916883766651,
0.0863838866353035,
-0.03432689234614372,
0.014760797843337059,
0.025022076442837715,
0.043055228888988495,
0.06880880892276764,
-0.018954841420054436,
-0.04746190086007118,
-0.20461739599704742,
-0.0850229263305664,
0.009155603125691414,
0.12585626542568207,
-0.06512729078531265,
0.11813722550868988,
-0.021552909165620804,
-0.029752546921372414,
0.054806217551231384,
-0.07023293524980545,
-0.09978274255990982,
-0.056759607046842575,
0.01441122405230999,
0.012465988285839558,
0.04717647656798363,
-0.11487211287021637,
-0.13843406736850739,
-0.07883948087692261,
0.13841816782951355,
-0.08971802890300751,
-0.0410999171435833,
-0.1291845738887787,
0.08086434006690979,
0.15628832578659058,
-0.06346395611763,
0.0679033100605011,
0.019455237314105034,
0.12398719787597656,
0.012149200774729252,
-0.03878035768866539,
0.09880336374044418,
-0.10095597058534622,
-0.2619297504425049,
-0.04649738967418671,
0.17497976124286652,
0.03074393980205059,
0.06025253236293793,
-0.03210463747382164,
0.030776608735322952,
0.004829511512070894,
-0.08523446321487427,
0.03936599940061569,
-0.04560909792780876,
0.07196580618619919,
0.03254111483693123,
-0.026526497676968575,
-0.014073668047785759,
-0.041510265320539474,
-0.04208429530262947,
0.1072094514966011,
0.2984161674976349,
-0.09151472896337509,
0.011129661463201046,
0.08141785115003586,
-0.023121165111660957,
-0.1778130680322647,
0.03849131613969803,
0.12123321741819382,
0.018353216350078583,
0.03369272127747536,
-0.18305547535419464,
0.10226951539516449,
0.0857580155134201,
-0.044432442635297775,
0.10314160585403442,
-0.2945651412010193,
-0.12470486015081406,
0.09247007966041565,
0.1252860128879547,
0.028744591400027275,
-0.15465299785137177,
-0.04314287379384041,
-0.014201442711055279,
-0.14431390166282654,
0.10909852385520935,
-0.10682225227355957,
0.11240196973085403,
-0.022379182279109955,
0.040151745080947876,
0.01582062803208828,
-0.06474542617797852,
0.12431377917528152,
-0.002186582190915942,
0.09212959557771683,
-0.005886056926101446,
0.011663686484098434,
0.0810026153922081,
-0.04238465800881386,
-0.00025003671180456877,
-0.05881229043006897,
0.04886558651924133,
-0.06030145287513733,
-0.012247627601027489,
-0.10953805595636368,
0.03301793709397316,
-0.06374598294496536,
-0.0580596923828125,
-0.00993439182639122,
0.04764328896999359,
0.006730018183588982,
-0.03019692748785019,
0.1346265971660614,
0.028992844745516777,
0.171869695186615,
0.13084067404270172,
0.07248149067163467,
-0.022986747324466705,
-0.09574371576309204,
-0.014812607318162918,
-0.03340449929237366,
0.08061051368713379,
-0.13206498324871063,
0.025901976972818375,
0.12859807908535004,
0.06770119816064835,
0.0952039510011673,
0.07294241338968277,
-0.05827876925468445,
0.0013901578495278955,
0.08543027192354202,
-0.15840654075145721,
-0.07479291409254074,
-0.027500856667757034,
0.0022738652769476175,
-0.1374332308769226,
0.07592515647411346,
0.10485181212425232,
-0.0746946781873703,
-0.01335877738893032,
0.007681856397539377,
0.013242870569229126,
-0.05168190598487854,
0.24150623381137848,
0.06519816815853119,
0.10047271847724915,
-0.10919731855392456,
0.08876721560955048,
0.038432735949754715,
-0.13424335420131683,
-0.009907311759889126,
0.07683561742305756,
-0.07595399767160416,
-0.017016934230923653,
0.04919901490211487,
0.07610577344894409,
-0.03526971489191055,
-0.06402384489774704,
-0.15230290591716766,
-0.14101994037628174,
0.06461180001497269,
0.161017045378685,
0.06670617312192917,
0.030349552631378174,
-0.01592259481549263,
0.037432216107845306,
-0.1338447779417038,
0.12617892026901245,
0.06446191668510437,
0.09146551787853241,
-0.18872784078121185,
0.15006417036056519,
0.015070391818881035,
0.03976236283779144,
-0.014957742765545845,
0.04359877482056618,
-0.1081007868051529,
0.014285984449088573,
-0.11811285465955734,
-0.04463199898600578,
-0.02372588962316513,
-0.006008451338857412,
-0.02487809583544731,
-0.05403011664748192,
-0.06522473692893982,
0.039153821766376495,
-0.10501962900161743,
-0.02634449489414692,
0.016314741224050522,
0.03388373553752899,
-0.12982569634914398,
-0.011468194425106049,
0.04694410413503647,
-0.10955405235290527,
0.09247877448797226,
0.055576350539922714,
0.04765881970524788,
0.052796702831983566,
-0.10393939912319183,
-0.012713027186691761,
0.058409981429576874,
-0.00956442579627037,
0.053474754095077515,
-0.13802890479564667,
-0.003579413751140237,
-0.04321218654513359,
0.03633247688412666,
-0.0024152484256774187,
0.06204194203019142,
-0.13862794637680054,
-0.005866211373358965,
-0.018667036667466164,
-0.038410916924476624,
-0.05970068648457527,
0.018659086897969246,
0.10487378388643265,
0.009018899872899055,
0.18232256174087524,
-0.0792732983827591,
0.03449377045035362,
-0.2271202802658081,
0.0008368045091629028,
-0.03722821921110153,
-0.10405581444501877,
-0.12265776097774506,
-0.014285529963672161,
0.08090328425168991,
-0.057090166956186295,
0.07740233093500137,
-0.039883702993392944,
0.08718416839838028,
0.03068532980978489,
-0.05582498759031296,
0.012162106111645699,
0.055383723229169846,
0.1945456862449646,
0.0280360858887434,
-0.01978808082640171,
0.04092847555875778,
0.02568412944674492,
0.07112149149179459,
0.09459105879068375,
0.18867085874080658,
0.1457398235797882,
0.0023503201082348824,
0.07117057591676712,
0.0747341439127922,
-0.11008372902870178,
-0.18237163126468658,
0.05303157866001129,
-0.05846262723207474,
0.10799265652894974,
-0.014833790250122547,
0.18731814622879028,
0.1081274002790451,
-0.17273110151290894,
0.038230303674936295,
-0.04416593536734581,
-0.0690363422036171,
-0.09010916948318481,
0.01075886283069849,
-0.0625716969370842,
-0.176125168800354,
0.018717017024755478,
-0.12016525119543076,
0.018827013671398163,
0.09257259964942932,
0.007968711666762829,
0.007672101259231567,
0.18947595357894897,
0.06692518293857574,
0.033595796674489975,
0.07621457427740097,
0.03661337122321129,
-0.026581918820738792,
-0.0272279791533947,
-0.08462405949831009,
0.030304066836833954,
-0.04107128828763962,
0.031252436339855194,
-0.075959712266922,
-0.12709768116474152,
0.06827408075332642,
0.04176418110728264,
-0.10405625402927399,
0.03454846516251564,
-0.009227347560226917,
0.08612038195133209,
0.06782073527574539,
-0.0021729383151978254,
0.03225461393594742,
-0.02292836271226406,
0.24200914800167084,
-0.10435465723276138,
-0.06227739155292511,
-0.1181657537817955,
0.25057029724121094,
0.0031605814583599567,
-0.02236214466392994,
0.05024236813187599,
-0.08842340111732483,
-0.02231782302260399,
0.15732556581497192,
0.15152201056480408,
-0.036440521478652954,
-0.00963541492819786,
0.015309900045394897,
-0.019193340092897415,
-0.07189065963029861,
0.08611449599266052,
0.1389872431755066,
0.10575009137392044,
-0.09203486889600754,
-0.04321487620472908,
-0.06181018799543381,
-0.039818692952394485,
-0.010620222426950932,
0.07678645104169846,
0.010895995423197746,
-0.01837555132806301,
-0.0401829294860363,
0.08487523347139359,
-0.045934926718473434,
-0.14585892856121063,
0.06853524595499039,
-0.1972375512123108,
-0.18665611743927002,
-0.033702071756124496,
0.09741418063640594,
0.0175225418061018,
0.05838540941476822,
-0.007983917370438576,
-0.03226522356271744,
0.07708116620779037,
-0.005754994694143534,
-0.035021521151065826,
-0.11972590535879135,
0.07911156862974167,
-0.08185607939958572,
0.20262181758880615,
-0.04898800328373909,
0.07196959853172302,
0.11122800409793854,
0.04973505809903145,
-0.10773061215877533,
0.0367560051381588,
0.0728725716471672,
-0.1659751981496811,
0.008241123519837856,
0.18281373381614685,
-0.03767695277929306,
0.10114370286464691,
0.01503605768084526,
-0.15729373693466187,
-0.00652959942817688,
-0.04638656601309776,
-0.04672094061970711,
-0.053491558879613876,
-0.02126210927963257,
-0.03270389512181282,
0.12588989734649658,
0.1974325180053711,
-0.05631411820650101,
-0.003497400553897023,
-0.06420721113681793,
0.041975267231464386,
0.07751717418432236,
0.08134283125400543,
-0.009675699286162853,
-0.28832098841667175,
0.046433061361312866,
0.03736361116170883,
-0.009493867866694927,
-0.24465395510196686,
-0.08024567365646362,
0.04209452494978905,
-0.06612566858530045,
-0.10620865970849991,
0.07162978500127792,
0.06145646423101425,
0.050339747220277786,
-0.0461246520280838,
-0.058794036507606506,
-0.08419332653284073,
0.17186374962329865,
-0.19427338242530823,
-0.08692415803670883
] |
null | null | null | import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
# Download NLTK resources (only need to run once)
nltk.download('vader_lexicon')
# Sample text for sentiment analysis
with open("lks.txt", 'r') as file:
fl = file.read()
contactId = fl.split("|")[0]
transcript=fl.split("|")[1]
transcript=transcript.replace("'",'')
# Initialize the sentiment analyzer
sia = SentimentIntensityAnalyzer()
print(transcript)
# Analyze sentiment
sentiment_score = sia.polarity_scores(transcript)
# Initialize dictionary to store tone counts
tones = {
'analytical': 0,
'anger': 0,
'confident': 0,
'fear': 0,
'joy': 0,
'sadness': 0,
'tentative': 0
}
# Apply thresholds and count tones
if sentiment_score['compound'] >= 0.05: # Threshold for positive sentiment
tones['joy'] += 1
elif sentiment_score['compound'] <= -0.05: # Threshold for negative sentiment
tones['anger'] += 1
elif sentiment_score['neg'] >= 0.5: # Threshold for high negativity
tones['sadness'] += 1
elif sentiment_score['pos'] <= 0.2: # Threshold for low positivity
tones['fear'] += 1
elif sentiment_score['neu'] >= 0.5: # Threshold for high neutrality
tones['tentative'] += 1
else: # Otherwise, consider it analytical or confident
tones['analytical'] += 1
tones['confident'] += 1
# Print tone counts
print("Tone Counts:", tones)
# sample output
#Tone Counts: {'analytical': 0, 'anger': 0, 'confident': 0, 'fear': 0, 'joy': 1, 'sadness': 0, 'tentative': 0} | {"language": ["en"], "tags": ["nltk", "swntiment", "tone", "nlp"]} | null | kishanj97/nltk_tone_analyzer | [
"nltk",
"swntiment",
"tone",
"nlp",
"en",
"region:us"
] | 2024-02-09T02:38:31+00:00 | [] | [
"en"
] | TAGS
#nltk #swntiment #tone #nlp #en #region-us
| import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
# Download NLTK resources (only need to run once)
nltk.download('vader_lexicon')
# Sample text for sentiment analysis
with open("URL", 'r') as file:
fl = URL()
contactId = URL("|")[0]
transcript=URL("|")[1]
transcript=transcript.replace("'",'')
# Initialize the sentiment analyzer
sia = SentimentIntensityAnalyzer()
print(transcript)
# Analyze sentiment
sentiment_score = sia.polarity_scores(transcript)
# Initialize dictionary to store tone counts
tones = {
'analytical': 0,
'anger': 0,
'confident': 0,
'fear': 0,
'joy': 0,
'sadness': 0,
'tentative': 0
}
# Apply thresholds and count tones
if sentiment_score['compound'] >= 0.05: # Threshold for positive sentiment
tones['joy'] += 1
elif sentiment_score['compound'] <= -0.05: # Threshold for negative sentiment
tones['anger'] += 1
elif sentiment_score['neg'] >= 0.5: # Threshold for high negativity
tones['sadness'] += 1
elif sentiment_score['pos'] <= 0.2: # Threshold for low positivity
tones['fear'] += 1
elif sentiment_score['neu'] >= 0.5: # Threshold for high neutrality
tones['tentative'] += 1
else: # Otherwise, consider it analytical or confident
tones['analytical'] += 1
tones['confident'] += 1
# Print tone counts
print("Tone Counts:", tones)
# sample output
#Tone Counts: {'analytical': 0, 'anger': 0, 'confident': 0, 'fear': 0, 'joy': 1, 'sadness': 0, 'tentative': 0} | [
"# Download NLTK resources (only need to run once)\nnltk.download('vader_lexicon')",
"# Sample text for sentiment analysis\nwith open(\"URL\", 'r') as file:\n fl = URL()\n \ncontactId = URL(\"|\")[0]\ntranscript=URL(\"|\")[1]\ntranscript=transcript.replace(\"'\",'')",
"# Initialize the sentiment analyzer\nsia = SentimentIntensityAnalyzer()\nprint(transcript)",
"# Analyze sentiment\nsentiment_score = sia.polarity_scores(transcript)",
"# Initialize dictionary to store tone counts\ntones = {\n 'analytical': 0,\n 'anger': 0,\n 'confident': 0,\n 'fear': 0,\n 'joy': 0,\n 'sadness': 0,\n 'tentative': 0\n}",
"# Apply thresholds and count tones\nif sentiment_score['compound'] >= 0.05: # Threshold for positive sentiment\n tones['joy'] += 1\nelif sentiment_score['compound'] <= -0.05: # Threshold for negative sentiment\n tones['anger'] += 1\nelif sentiment_score['neg'] >= 0.5: # Threshold for high negativity\n tones['sadness'] += 1\nelif sentiment_score['pos'] <= 0.2: # Threshold for low positivity\n tones['fear'] += 1\nelif sentiment_score['neu'] >= 0.5: # Threshold for high neutrality\n tones['tentative'] += 1\nelse: # Otherwise, consider it analytical or confident\n tones['analytical'] += 1\n tones['confident'] += 1",
"# Print tone counts\nprint(\"Tone Counts:\", tones)",
"# sample output"
] | [
"TAGS\n#nltk #swntiment #tone #nlp #en #region-us \n",
"# Download NLTK resources (only need to run once)\nnltk.download('vader_lexicon')",
"# Sample text for sentiment analysis\nwith open(\"URL\", 'r') as file:\n fl = URL()\n \ncontactId = URL(\"|\")[0]\ntranscript=URL(\"|\")[1]\ntranscript=transcript.replace(\"'\",'')",
"# Initialize the sentiment analyzer\nsia = SentimentIntensityAnalyzer()\nprint(transcript)",
"# Analyze sentiment\nsentiment_score = sia.polarity_scores(transcript)",
"# Initialize dictionary to store tone counts\ntones = {\n 'analytical': 0,\n 'anger': 0,\n 'confident': 0,\n 'fear': 0,\n 'joy': 0,\n 'sadness': 0,\n 'tentative': 0\n}",
"# Apply thresholds and count tones\nif sentiment_score['compound'] >= 0.05: # Threshold for positive sentiment\n tones['joy'] += 1\nelif sentiment_score['compound'] <= -0.05: # Threshold for negative sentiment\n tones['anger'] += 1\nelif sentiment_score['neg'] >= 0.5: # Threshold for high negativity\n tones['sadness'] += 1\nelif sentiment_score['pos'] <= 0.2: # Threshold for low positivity\n tones['fear'] += 1\nelif sentiment_score['neu'] >= 0.5: # Threshold for high neutrality\n tones['tentative'] += 1\nelse: # Otherwise, consider it analytical or confident\n tones['analytical'] += 1\n tones['confident'] += 1",
"# Print tone counts\nprint(\"Tone Counts:\", tones)",
"# sample output"
] | [
22,
29,
60,
26,
22,
62,
218,
18,
3
] | [
"passage: TAGS\n#nltk #swntiment #tone #nlp #en #region-us \n# Download NLTK resources (only need to run once)\nnltk.download('vader_lexicon')# Sample text for sentiment analysis\nwith open(\"URL\", 'r') as file:\n fl = URL()\n \ncontactId = URL(\"|\")[0]\ntranscript=URL(\"|\")[1]\ntranscript=transcript.replace(\"'\",'')# Initialize the sentiment analyzer\nsia = SentimentIntensityAnalyzer()\nprint(transcript)# Analyze sentiment\nsentiment_score = sia.polarity_scores(transcript)# Initialize dictionary to store tone counts\ntones = {\n 'analytical': 0,\n 'anger': 0,\n 'confident': 0,\n 'fear': 0,\n 'joy': 0,\n 'sadness': 0,\n 'tentative': 0\n}# Apply thresholds and count tones\nif sentiment_score['compound'] >= 0.05: # Threshold for positive sentiment\n tones['joy'] += 1\nelif sentiment_score['compound'] <= -0.05: # Threshold for negative sentiment\n tones['anger'] += 1\nelif sentiment_score['neg'] >= 0.5: # Threshold for high negativity\n tones['sadness'] += 1\nelif sentiment_score['pos'] <= 0.2: # Threshold for low positivity\n tones['fear'] += 1\nelif sentiment_score['neu'] >= 0.5: # Threshold for high neutrality\n tones['tentative'] += 1\nelse: # Otherwise, consider it analytical or confident\n tones['analytical'] += 1\n tones['confident'] += 1# Print tone counts\nprint(\"Tone Counts:\", tones)# sample output"
] | [
-0.029256071895360947,
0.0915779322385788,
-0.011845837347209454,
0.03456497937440872,
-0.0020632802043110132,
0.010031802579760551,
0.062351249158382416,
0.11313199251890182,
0.07093209028244019,
0.14861954748630524,
0.010558112524449825,
0.08447090536355972,
0.03719692304730415,
0.05503634735941887,
-0.12039043754339218,
-0.12153640389442444,
-0.012263613753020763,
-0.018753569573163986,
0.235550656914711,
0.13162367045879364,
0.06499990075826645,
-0.003911283798515797,
0.05801958963274956,
-0.012969803996384144,
0.03404087573289871,
0.0457381047308445,
-0.0225383248180151,
-0.012928671203553677,
0.035419512540102005,
0.008716742508113384,
0.018499579280614853,
0.006002841517329216,
-0.01337897963821888,
-0.32966527342796326,
0.02688208967447281,
0.03441694378852844,
0.020116938278079033,
0.02563493140041828,
0.20146873593330383,
-0.18273156881332397,
0.2316197156906128,
-0.13301430642604828,
0.03642500191926956,
0.06945411115884781,
-0.10450495779514313,
-0.11192770302295685,
-0.12391362339258194,
-0.00960826687514782,
0.11869129538536072,
0.04079119861125946,
-0.09079273790121078,
0.19116570055484772,
-0.12289591133594513,
0.11583343148231506,
0.22227856516838074,
-0.14442604780197144,
-0.04093516245484352,
-0.04487159848213196,
-0.08926897495985031,
-0.01062624342739582,
-0.12698301672935486,
-0.007279036566615105,
0.01942744292318821,
0.033355630934238434,
-0.052758604288101196,
-0.020631177350878716,
0.041071511805057526,
-0.026326846331357956,
-0.0685875341296196,
-0.09813202172517776,
0.13519498705863953,
0.1272987574338913,
-0.062468841671943665,
-0.046510569751262665,
-0.0115001006051898,
-0.13706769049167633,
0.003714208025485277,
-0.01593148335814476,
0.007307462859898806,
0.0237440038472414,
0.05487538129091263,
0.1137426495552063,
-0.10391008108854294,
0.04815405234694481,
-0.08462409675121307,
0.06658211350440979,
-0.03821873664855957,
-0.030963826924562454,
0.05942821875214577,
0.01560105662792921,
-0.03562508895993233,
-0.11842329055070877,
-0.009568894281983376,
0.01122337393462658,
-0.10053201019763947,
0.0010366537608206272,
-0.05803272873163223,
-0.018460216000676155,
0.0950448289513588,
0.06605568528175354,
-0.1037120521068573,
0.06275433301925659,
-0.06550779193639755,
0.0031467704102396965,
0.09560976922512054,
0.028575485572218895,
0.051163509488105774,
-0.1316402554512024,
-0.0665508285164833,
-0.006255635526031256,
0.09969563037157059,
0.026302440091967583,
0.07115793228149414,
-0.0023746497463434935,
0.049372658133506775,
0.00460395822301507,
0.025213507935404778,
0.04551959037780762,
-0.17647913098335266,
0.024019693955779076,
-0.026727117598056793,
-0.1531863659620285,
0.012414099648594856,
0.09949091076850891,
-0.03012099675834179,
0.12014731019735336,
-0.002303481800481677,
-0.004070953465998173,
-0.061405912041664124,
0.06036406382918358,
0.012910558842122555,
0.01910831592977047,
-0.05843362584710121,
-0.07566513121128082,
0.10123846679925919,
0.03855344280600548,
-0.02108762226998806,
-0.04791627079248428,
-0.09997256845235825,
-0.031929053366184235,
0.03318250551819801,
-0.12387798726558685,
-0.03561193495988846,
-0.07850811630487442,
-0.09514251351356506,
0.011407365091145039,
0.027343647554516792,
-0.010052531026303768,
-0.051165491342544556,
0.04727059230208397,
0.05866038426756859,
0.07583945989608765,
0.14934036135673523,
-0.042809803038835526,
-0.11798061430454254,
0.036041826009750366,
-0.18027204275131226,
0.16392816603183746,
-0.09854402393102646,
0.007960546761751175,
-0.1332576423883438,
-0.06234649196267128,
-0.025700729340314865,
0.006108323112130165,
0.010105661116540432,
0.16762253642082214,
-0.1471162736415863,
-0.031293366104364395,
0.07520662248134613,
-0.1150418221950531,
0.008863070048391819,
0.19868649542331696,
-0.020513271912932396,
-0.011122356168925762,
0.06178466975688934,
0.22774171829223633,
-0.006998010911047459,
-0.15146715939044952,
-0.09314844757318497,
0.07076842337846756,
-0.05404500290751457,
0.19782523810863495,
0.04036809504032135,
0.006400333251804113,
0.05013875290751457,
0.02272423915565014,
0.028356753289699554,
0.004719650838524103,
-0.01243346743285656,
-0.01748645305633545,
0.011513195931911469,
-0.007193009369075298,
0.10051232576370239,
-0.018411071971058846,
-0.10991795361042023,
-0.07967007905244827,
-0.10930337756872177,
-0.10739107429981232,
0.08526723086833954,
-0.015825381502509117,
0.020368965342640877,
-0.14275918900966644,
-0.011330009438097477,
-0.00028543444932438433,
-0.024296913295984268,
-0.15330196917057037,
0.025649789720773697,
-0.009260700084269047,
-0.13665130734443665,
0.06726115196943283,
0.13980987668037415,
0.02377988211810589,
-0.045333776623010635,
-0.025018073618412018,
0.01669992320239544,
-0.00506731728091836,
-0.008196854963898659,
-0.029901953414082527,
-0.20039783418178558,
0.05459572374820709,
-0.04969541355967522,
0.16453132033348083,
-0.1704045981168747,
0.03005368635058403,
0.2414017915725708,
0.06527764350175858,
-0.019040819257497787,
-0.01339662354439497,
0.04519582539796829,
0.03386605903506279,
-0.03659450635313988,
0.010056127794086933,
-0.01590757630765438,
0.020544124767184258,
-0.0883064866065979,
0.008658032864332199,
-0.19096729159355164,
-0.10481350868940353,
0.08571586012840271,
-0.05891337990760803,
-0.12979352474212646,
-0.03625376895070076,
-0.024681275710463524,
0.0005269377143122256,
-0.05772196128964424,
0.008503815159201622,
0.11755436658859253,
0.11896618455648422,
0.0064325714483857155,
-0.06350590288639069,
-0.05196806788444519,
0.002308842958882451,
-0.10668791830539703,
0.004010253585875034,
0.18184486031532288,
-0.12458425015211105,
-0.09567490965127945,
0.03479553014039993,
0.044761382043361664,
-0.0955890342593193,
-0.024294614791870117,
0.022233812138438225,
-0.06948785483837128,
-0.11420819908380508,
0.10599832236766815,
0.011634476482868195,
0.010684484615921974,
-0.0952611044049263,
0.03852534294128418,
0.03236377611756325,
-0.04676373302936554,
-0.055895622819662094,
-0.05774961784482002,
0.024987582117319107,
0.05122724175453186,
-0.03277301415801048,
-0.017733467742800713,
-0.00446481304243207,
0.06732914596796036,
0.0634598582983017,
-0.05882914736866951,
0.005749334581196308,
-0.029021915048360825,
-0.05729558691382408,
-0.1060190498828888,
0.1348589062690735,
-0.028758931905031204,
-0.20931990444660187,
-0.028584199026226997,
0.020376650616526604,
-0.07052931189537048,
-0.017341984435915947,
0.07558493316173553,
-0.1608942598104477,
-0.09184562414884567,
-0.11580158025026321,
0.012734499759972095,
0.055625010281801224,
-0.06133246049284935,
-0.019368307664990425,
0.05810035392642021,
0.0811215192079544,
-0.0699760690331459,
-0.00144442159216851,
-0.01894996501505375,
-0.039301738142967224,
0.05444522574543953,
0.0012887426419183612,
0.033244237303733826,
0.07178188115358353,
0.005180711857974529,
0.018546778708696365,
-0.029984120279550552,
0.165280282497406,
-0.09449588507413864,
0.0004948294372297823,
0.11480651050806046,
-0.023454133421182632,
0.10488022118806839,
0.12555663287639618,
0.03117261454463005,
-0.06745925545692444,
0.05705268681049347,
0.11638942360877991,
0.009073452092707157,
-0.26101425290107727,
-0.061399195343256,
-0.01488605234771967,
0.01233618427067995,
0.018247464671730995,
0.015727637335658073,
-0.016662675887346268,
0.07132593542337418,
-0.0004287961928639561,
-0.07530748099088669,
-0.007663258351385593,
0.10925041139125824,
0.23156382143497467,
0.01650260016322136,
0.02744162455201149,
-0.042809490114450455,
-0.02520863153040409,
0.09499669820070267,
-0.011178490705788136,
0.0418647900223732,
-0.09262995421886444,
0.20691023766994476,
0.06303486227989197,
0.1921440064907074,
-0.006709138862788677,
-0.033088263124227524,
0.01253134198486805,
0.038019951432943344,
-0.03430556878447533,
-0.05669453740119934,
-0.14988607168197632,
0.002754373475909233,
-0.0033794990740716457,
0.06928203254938126,
0.03847649320960045,
0.025083286687731743,
0.154599130153656,
0.1602144092321396,
0.009148371405899525,
-0.20191386342048645,
-0.021545324474573135,
0.020372193306684494,
-0.025598393753170967,
0.007659949827939272,
-0.03298114612698555,
0.018454698845744133,
-0.032874949276447296,
0.14387962222099304,
0.013221239671111107,
0.05780409649014473,
-0.2101188749074936,
0.0714683011174202,
-0.056098390370607376,
0.035871680825948715,
0.04408779740333557,
0.06351453810930252,
-0.06452164053916931,
0.21565023064613342,
0.022891147062182426,
0.04373425990343094,
-0.02270752750337124,
0.00040708627784624696,
0.03851860389113426,
-0.07488805800676346,
0.1270751655101776,
-0.019687777385115623,
0.06808149069547653,
-0.08933781087398529,
-0.08694998919963837,
0.006625264883041382,
0.042785950005054474,
-0.03086501732468605,
0.11473362892866135,
0.014280547387897968,
-0.02089710906147957,
-0.05247163772583008,
-0.017272543162107468,
-0.15133735537528992,
-0.10725302994251251,
0.049009472131729126,
-0.048309169709682465,
-0.010485927574336529,
0.0044655404053628445,
-0.04225461184978485,
-0.08761583268642426,
0.23292765021324158,
-0.12619180977344513,
-0.03215043246746063,
-0.08156569302082062,
0.08418887108564377,
0.05334816873073578,
-0.07017792761325836,
-0.14768821001052856,
0.039133720099925995,
0.1325044333934784,
-0.012162853963673115,
0.018432658165693283,
0.028709029778838158,
-0.026123400777578354,
-0.12158581614494324,
-0.023282453417778015,
0.060544926673173904,
0.08478742092847824,
0.054506566375494,
0.05695245414972305,
-0.02078220807015896,
0.0137248570099473,
-0.11007499694824219,
0.02864149585366249,
-0.015771126374602318,
-0.022309111431241035,
0.02801484987139702,
0.07269344478845596,
-0.11775404959917068,
-0.1448703110218048,
-0.015661682933568954,
-0.0008563757874071598,
0.3354744017124176,
-0.04859372600913048,
0.03641194477677345,
0.10107699781656265,
-0.10657777637243271,
-0.11811348795890808,
-0.010064402595162392,
0.10987474024295807,
-0.03757214918732643,
0.20421399176120758,
-0.06074482947587967,
0.10262960940599442,
0.12518560886383057,
0.0067139072343707085,
-0.19683630764484406,
-0.1092115119099617,
-0.02548837661743164,
0.05669436603784561,
0.05512552335858345,
-0.06654486060142517,
-0.14305388927459717,
-0.049649953842163086,
-0.03679553046822548,
-0.10896605253219604,
0.047614362090826035,
-0.03445027768611908,
0.03025672771036625,
0.03803008049726486,
0.21109260618686676,
0.08441124856472015,
-0.004505017772316933,
0.1941995918750763,
0.017694242298603058,
0.06248226389288902,
-0.10424400120973587,
0.02940414287149906,
0.08856871724128723,
-0.08104225993156433,
0.07566700875759125,
-0.0800679475069046,
-0.035120174288749695,
-0.0814976617693901,
-0.021998656913638115,
-0.05849539116024971,
0.05418700352311134,
-0.06441456079483032,
0.007209693547338247,
-0.03261993080377579,
-0.028825078159570694,
0.11366172134876251,
-0.0260090883821249,
0.03724915534257889,
-0.08288199454545975,
0.00846510287374258,
0.2585649788379669,
0.18657538294792175,
0.12110693007707596,
-0.13523970544338226,
0.033450618386268616,
-0.0110399154946208,
-0.03789586201310158,
-0.12688353657722473,
0.005340303760021925,
0.10409168899059296,
-0.003780588274821639,
0.11355076730251312,
-0.022893493995070457,
-0.08172035217285156,
0.07799194008111954,
0.049711111932992935,
-0.042936358600854874,
-0.10686759650707245,
0.042484357953071594,
0.047081541270017624,
-0.14674492180347443,
-0.09600766003131866,
0.15051424503326416,
0.008687278255820274,
-0.003931290935724974,
0.02964089624583721,
0.07180513441562653,
-0.010368641465902328,
0.019312340766191483,
-0.10560455173254013,
0.04069191589951515,
-0.07169810682535172,
0.003900588024407625,
0.07832616567611694,
-0.2909899353981018,
0.05909644812345505,
0.10235478729009628,
-0.031420640647411346,
-0.06209355220198631,
-0.022203819826245308,
0.11510581523180008,
-0.006879536435008049,
0.023770270869135857,
-0.03346473351120949,
-0.13593626022338867,
0.028144853189587593,
0.1463899314403534,
0.0721830427646637,
0.08209525793790817,
-0.012105369009077549,
0.007048086263239384,
-0.04706544801592827,
0.09158804267644882,
0.20070618391036987,
-0.014483480714261532,
-0.0630444809794426,
-0.010697084479033947,
0.0013105041580274701,
-0.040039874613285065,
0.011693167500197887,
-0.05429886654019356,
-0.03359995782375336,
0.017159486189484596,
-0.12131649255752563,
0.14352308213710785,
-0.1000666618347168,
0.06301166117191315,
0.04385381564497948,
0.03211423382163048,
-0.030149346217513084,
-0.006376167759299278,
-0.08975762873888016,
-0.021870099008083344,
0.0495530404150486,
0.13761547207832336,
-0.1165483221411705,
-0.0062836757861077785,
0.07551269978284836,
-0.11471854150295258,
0.05124110355973244,
0.030498867854475975,
-0.07570217549800873,
-0.023345472291111946,
-0.23306693136692047,
-0.0161922425031662,
0.10349421203136444,
0.03274013102054596,
-0.0056066932156682014,
-0.11311067640781403,
-0.002141115954145789,
0.011860675178468227,
-0.0034784809686243534,
0.00018417347746435553,
0.148106187582016,
-0.12707339227199554,
0.09675205498933792,
0.09411916881799698,
-0.07334502786397934,
-0.10394492000341415,
0.015021412633359432,
0.12799185514450073,
-0.0013436912558972836,
0.12740278244018555,
-0.06445306539535522,
0.01506280992180109,
-0.16611246764659882,
0.0021150936372578144,
0.06404320895671844,
0.052858155220746994,
-0.14769534766674042,
-0.02424635738134384,
0.10498984158039093,
-0.00914129801094532,
0.030108721926808357,
0.0028462205082178116,
0.043649885803461075,
0.021767277270555496,
-0.04579903185367584,
-0.036010369658470154,
-0.03371666371822357,
-0.04922076314687729,
-0.012052283622324467,
-0.028080647811293602,
0.022447766736149788,
-0.08727949857711792,
0.03529166802763939,
-0.0829109251499176,
0.04260486736893654,
0.1213284283876419,
0.12585444748401642,
0.024624289944767952,
-0.05038919299840927,
0.022907836362719536,
0.022364221513271332,
0.18655195832252502,
-0.11706860363483429,
0.09177658706903458,
-0.019546516239643097,
0.08116758614778519,
0.16818496584892273,
-0.0118552902713418,
0.08984377980232239,
-0.05237460508942604,
-0.06283623725175858,
-0.11032858490943909,
-0.254366934299469,
-0.10097835958003998,
-0.05398639291524887,
0.035667985677719116,
-0.14074677228927612,
0.07382144033908844,
0.08576387912034988,
0.06974717974662781,
0.00397711293771863,
-0.05737431347370148,
-0.030297519639134407,
-0.06485731899738312,
0.06339821964502335,
-0.04374540224671364,
-0.03336136043071747,
0.015045437961816788,
0.04685894399881363,
0.06313490122556686,
0.09171765297651291,
0.09334106743335724,
0.11212391406297684,
0.05271472781896591,
-0.0329493023455143,
-0.12635941803455353,
-0.10879442095756531,
0.03889864310622215,
0.004026898182928562,
-0.037254150956869125,
0.18494440615177155,
0.05307910218834877,
-0.017797864973545074,
-0.006162077188491821,
0.13646598160266876,
-0.0820251852273941,
-0.06590136140584946,
-0.12958765029907227,
0.12204401940107346,
-0.007639715448021889,
0.06701627373695374,
-0.02794005163013935,
-0.08894653618335724,
0.001056864857673645,
0.04435194656252861,
0.0531127005815506,
0.03828287124633789,
0.007020391058176756,
-0.011046281084418297,
0.014507772400975227,
-0.01284779328852892,
-0.08204479515552521,
0.06258661299943924,
0.12146241217851639,
-0.11273471266031265,
0.16159483790397644,
-0.03198754042387009,
-0.0197018850594759,
-0.03506290540099144,
-0.002525817835703492,
-0.10142475366592407,
0.044786617159843445,
-0.08012501150369644,
0.18120285868644714,
-0.10018596798181534,
-0.18288195133209229,
0.09360215067863464,
-0.10406260937452316,
-0.07964497059583664,
0.06071062758564949,
0.11528307944536209,
0.08716249465942383,
0.07175246626138687,
-0.0029386284295469522,
-0.05615989863872528,
0.1412406861782074,
-0.037622276693582535,
-0.08996377140283585,
0.005750518292188644,
0.05395692214369774,
-0.15968845784664154,
0.08919470757246017,
0.01404605619609356,
0.0745554193854332,
0.10698526352643967,
-0.05938555300235748,
-0.11360344290733337,
0.08417274057865143,
0.06817746162414551,
-0.11548510938882828,
0.07589077204465866,
0.16190657019615173,
0.0014265079516917467,
0.15341509878635406,
0.10694853216409683,
-0.11723947525024414,
0.030157150700688362,
0.030910689383745193,
0.030842525884509087,
-0.07537131756544113,
0.031718067824840546,
-0.07234714180231094,
-0.009522509761154652,
0.12261573225259781,
0.022545289248228073,
0.028243357315659523,
-0.04555146396160126,
-0.038732025772333145,
-0.02938101999461651,
-0.019681131467223167,
0.046076226979494095,
-0.11475414037704468,
0.04501033574342728,
0.19714286923408508,
0.1032913401722908,
-0.1268632560968399,
-0.06257160007953644,
0.03667006269097328,
0.029653223231434822,
-0.0285644493997097,
0.048508379608392715,
0.03053896501660347,
0.04115620255470276,
-0.026751814410090446,
-0.2981525957584381,
0.08708894997835159,
0.1822570562362671,
-0.024162055924534798,
-0.03736245632171631
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-large-bn-adapter-3.17M-squad-model2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 98
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "roberta-large", "model-index": [{"name": "roberta-large-bn-adapter-3.17M-squad-model2", "results": []}]} | null | varun-v-rao/roberta-large-bn-adapter-3.17M-squad-model2 | [
"tensorboard",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:roberta-large",
"license:mit",
"region:us"
] | 2024-02-09T02:47:33+00:00 | [] | [] | TAGS
#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-roberta-large #license-mit #region-us
|
# roberta-large-bn-adapter-3.17M-squad-model2
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 98
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# roberta-large-bn-adapter-3.17M-squad-model2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 98\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-roberta-large #license-mit #region-us \n",
"# roberta-large-bn-adapter-3.17M-squad-model2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 98\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
45,
42,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#tensorboard #generated_from_trainer #dataset-varun-v-rao/squad #base_model-roberta-large #license-mit #region-us \n# roberta-large-bn-adapter-3.17M-squad-model2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 4\n- seed: 98\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.09754420071840286,
0.08475632220506668,
-0.002429765649139881,
0.08253579586744308,
0.1683940440416336,
0.026871461421251297,
0.13405132293701172,
0.10536665469408035,
-0.12229356914758682,
0.045643460005521774,
0.07935084402561188,
0.030750688165426254,
0.032697878777980804,
0.12299175560474396,
-0.00869996938854456,
-0.2618621289730072,
-0.0074153682217001915,
0.026069119572639465,
-0.1237412765622139,
0.09699109941720963,
0.12700355052947998,
-0.10863638669252396,
0.0643458142876625,
0.0221774410456419,
-0.2300180196762085,
0.024251354858279228,
-0.004101091995835304,
-0.0778789222240448,
0.09706447273492813,
0.007166001014411449,
0.11605313420295715,
-0.0060288915410637856,
0.12009679526090622,
-0.115598663687706,
0.010618858970701694,
0.04576048627495766,
0.043364040553569794,
0.10978171974420547,
0.030587049201130867,
0.034546416252851486,
0.124949611723423,
-0.08095930516719818,
0.08476325869560242,
0.03224795311689377,
-0.07510058581829071,
-0.2366773784160614,
-0.08863873779773712,
0.0996035784482956,
0.04864353686571121,
0.08931349962949753,
0.005408297758549452,
0.16001860797405243,
-0.09736719727516174,
0.05792494863271713,
0.22765742242336273,
-0.2782544493675232,
-0.0802895650267601,
0.06149259954690933,
0.06936346739530563,
0.06481161713600159,
-0.10713951289653778,
-0.03239522874355316,
0.04126841947436333,
0.04537498578429222,
0.1006937026977539,
-0.016878686845302582,
-0.05580233037471771,
-0.0018466259352862835,
-0.12856248021125793,
-0.029915954917669296,
0.22060996294021606,
0.025365211069583893,
-0.05242510885000229,
-0.056602153927087784,
-0.04064253345131874,
-0.06631659716367722,
-0.029996179044246674,
-0.024449309334158897,
0.021003857254981995,
-0.06731054931879044,
-0.12927596271038055,
-0.08209763467311859,
-0.09691290557384491,
-0.07964542508125305,
-0.007301480043679476,
0.16882817447185516,
0.05380010977387428,
0.03955172002315521,
-0.08404221385717392,
0.11257664859294891,
0.0038171184714883566,
-0.11734288185834885,
0.004695152398198843,
-0.014785142615437508,
-0.03506476804614067,
-0.03333209827542305,
-0.050415173172950745,
-0.01691015623509884,
0.021957524120807648,
0.18542422354221344,
-0.07462923228740692,
0.022331157699227333,
0.02428204007446766,
0.03602900728583336,
-0.027836589142680168,
0.1530725508928299,
-0.08065196126699448,
-0.017308181151747704,
0.03120947629213333,
0.08843675255775452,
0.020268958061933517,
0.006590112112462521,
-0.10401736199855804,
-0.03847615793347359,
0.09152903407812119,
0.04438081383705139,
-0.038584575057029724,
0.01707170158624649,
0.00883046817034483,
-0.043583206832408905,
0.029155775904655457,
-0.1030520424246788,
0.014542937278747559,
-0.0019221777329221368,
-0.09820079058408737,
-0.012412120588123798,
0.017286157235503197,
-0.01505826972424984,
-0.016641460359096527,
0.06837866455316544,
-0.1063055545091629,
-0.02223292924463749,
-0.09625136107206345,
-0.07762166112661362,
0.0076684048399329185,
-0.08398006856441498,
0.02256557159125805,
-0.09867580980062485,
-0.13780274987220764,
0.003257109085097909,
0.014771542511880398,
-0.06052039936184883,
-0.05986616387963295,
0.005210453644394875,
-0.08781038969755173,
0.0016214707866311073,
-0.007490929681807756,
0.16777819395065308,
-0.017239240929484367,
0.10420332849025726,
0.061691947281360626,
0.027365485206246376,
-0.030232368037104607,
0.04163962975144386,
-0.08617300540208817,
0.018061421811580658,
-0.15135662257671356,
0.017487091943621635,
-0.08132191747426987,
0.029086489230394363,
-0.10694742202758789,
-0.11832752078771591,
0.008298162370920181,
-0.015569382347166538,
0.08817265927791595,
0.07965931296348572,
-0.08566198498010635,
-0.057277336716651917,
0.14447352290153503,
-0.07850909978151321,
-0.08200523257255554,
0.09907951951026917,
-0.03908529505133629,
0.0530305877327919,
0.038546156138181686,
0.14532150328159332,
0.09997765719890594,
-0.08406121283769608,
-0.028589187189936638,
0.01152379997074604,
0.06144682690501213,
-0.07231555879116058,
0.09974686801433563,
0.01464372780174017,
0.0002339594066143036,
0.04112761467695236,
-0.06445594877004623,
0.04029904305934906,
-0.10309746116399765,
-0.07131693512201309,
-0.055328186601400375,
-0.09356050193309784,
0.03968723490834236,
0.046942297369241714,
0.05652396008372307,
-0.06438732892274857,
-0.09743025153875351,
0.11543279141187668,
0.1655237376689911,
-0.03770054876804352,
0.0056526632979512215,
-0.08923487365245819,
0.10758227854967117,
-0.10143772512674332,
-0.021521396934986115,
-0.20761819183826447,
-0.07209373265504837,
0.02786092646420002,
-0.00013354372640606016,
0.0479465052485466,
0.01339570339769125,
0.06493185460567474,
0.06201138347387314,
-0.05413009598851204,
-0.0219754446297884,
-0.12898388504981995,
-0.03004167601466179,
-0.0820930153131485,
-0.16966736316680908,
-0.09361656755208969,
-0.034005794674158096,
0.160646453499794,
-0.19831931591033936,
0.023676728829741478,
-0.01125429105013609,
0.13153375685214996,
0.034210436046123505,
-0.03176090121269226,
-0.01721356064081192,
0.04641583189368248,
-0.013790395110845566,
-0.07656512409448624,
0.037521690130233765,
0.01444954238831997,
-0.06269066035747528,
-0.07192754745483398,
-0.09353131800889969,
0.0891733467578888,
0.10596911609172821,
0.04540005698800087,
-0.07217022776603699,
0.012192760594189167,
-0.0895715206861496,
-0.02952374704182148,
-0.04477544501423836,
-0.01077762246131897,
0.11235912144184113,
-0.0013492127181962132,
0.14385543763637543,
-0.08097496628761292,
-0.05359628424048424,
0.033320941030979156,
-0.011631420813500881,
0.015045803971588612,
0.07689781486988068,
0.10835865885019302,
-0.10419424623250961,
0.09098294377326965,
0.09331449866294861,
-0.10634233802556992,
0.17005831003189087,
-0.06330974400043488,
-0.0975319892168045,
-0.03938262537121773,
-0.014085478149354458,
0.007531574461609125,
0.16389423608779907,
-0.07022950053215027,
-0.0014985318994149566,
0.04802978038787842,
-0.004570361226797104,
0.048511721193790436,
-0.1694387048482895,
-0.014282649382948875,
-0.003300267970189452,
-0.01659364439547062,
0.0026570355985313654,
0.015696678310632706,
0.02404572255909443,
0.10171127319335938,
0.029341403394937515,
-0.03209315240383148,
0.027633022516965866,
0.012288114987313747,
-0.052449941635131836,
0.19749635457992554,
-0.07231315225362778,
-0.11472827196121216,
-0.15929074585437775,
0.04746530205011368,
-0.06665828824043274,
-0.029891610145568848,
0.012613202445209026,
-0.08013173192739487,
-0.025088798254728317,
-0.05744108185172081,
0.04551812633872032,
-0.050866078585386276,
0.010824686847627163,
0.005341443233191967,
0.04324198141694069,
0.08780772984027863,
-0.1471504122018814,
0.025673937052488327,
-0.05114991217851639,
-0.11939100921154022,
-0.0028191900346428156,
0.06325873732566833,
0.10958430916070938,
0.09918563812971115,
-0.03134748712182045,
0.013985387049615383,
-0.033333875238895416,
0.2093830406665802,
-0.07140738517045975,
-0.021501636132597923,
0.16399060189723969,
0.027826128527522087,
0.034874480217695236,
0.07450416684150696,
0.054529715329408646,
-0.058615341782569885,
0.013279488310217857,
0.04344767704606056,
-0.031943537294864655,
-0.2515064477920532,
-0.03193312883377075,
-0.0427682064473629,
-0.03692033514380455,
0.09268860518932343,
0.05437994748353958,
-0.008277044631540775,
0.0822640135884285,
-0.02002294547855854,
0.07525432854890823,
-0.05620027706027031,
0.09863196313381195,
0.09770002961158752,
0.03600291535258293,
0.10663540661334991,
-0.052262138575315475,
-0.05496664717793465,
0.06094574183225632,
0.02812603861093521,
0.29295673966407776,
-0.04812447354197502,
0.09081114828586578,
0.05040435492992401,
0.1485881209373474,
-0.014476866461336613,
0.06397660821676254,
-0.006239024922251701,
-0.004697263706475496,
-0.007549828849732876,
-0.05025482922792435,
-0.0025135446339845657,
-0.00944435503333807,
-0.021047096699476242,
0.09253395348787308,
-0.09762341529130936,
0.022091325372457504,
0.014212219044566154,
0.2488841414451599,
0.017644742503762245,
-0.29547205567359924,
-0.12253697216510773,
0.0010291626676917076,
-0.014188962057232857,
-0.055131394416093826,
0.01942724548280239,
0.12289481610059738,
-0.11436627060174942,
-0.005966251716017723,
-0.06551365554332733,
0.07403251528739929,
-0.01987784542143345,
-0.005979653913527727,
0.039696577936410904,
0.1772008240222931,
0.010492930188775063,
0.09655704349279404,
-0.19638198614120483,
0.2223164141178131,
0.016967911273241043,
0.10445205122232437,
-0.046204276382923126,
0.027199462056159973,
0.01624072715640068,
0.0518687441945076,
0.0620470754802227,
-0.012723283842206001,
0.0015739565715193748,
-0.167976975440979,
-0.062182627618312836,
0.03731875121593475,
0.0994289442896843,
-0.04242626205086708,
0.1047048270702362,
-0.05170323699712753,
0.019775159657001495,
0.03871309757232666,
-0.08408430218696594,
-0.13311181962490082,
-0.10193901509046555,
0.00028308984474278986,
0.0022222271654754877,
-0.09051734209060669,
-0.09956780076026917,
-0.10005241632461548,
0.005557079333811998,
0.13743619620800018,
-0.022735392674803734,
-0.04148907959461212,
-0.1305479258298874,
0.12237272411584854,
0.1399267464876175,
-0.07329373061656952,
0.023930484429001808,
-0.0016422285698354244,
0.13405553996562958,
0.0036594157572835684,
-0.0820583701133728,
0.04351992532610893,
-0.0694592073559761,
-0.18315313756465912,
-0.024381911382079124,
0.1268623173236847,
0.02169954590499401,
0.04701388254761696,
-0.013066589832305908,
0.013152710162103176,
-0.00945028942078352,
-0.09274397045373917,
0.0073448182083666325,
0.018721522763371468,
0.04069148749113083,
0.031774211674928665,
-0.06687718629837036,
0.019271915778517723,
-0.02057364396750927,
-0.0024654241278767586,
0.13454632461071014,
0.21680764853954315,
-0.09022866189479828,
0.03906063362956047,
0.08416103571653366,
-0.04956098645925522,
-0.1764441877603531,
0.04944348335266113,
0.09506546705961227,
0.02080395445227623,
0.04828883334994316,
-0.2009802907705307,
0.12071651965379715,
0.09537024796009064,
-0.03284255787730217,
0.05086645856499672,
-0.29586461186408997,
-0.10974238067865372,
0.08764775842428207,
0.1342744082212448,
0.06666047126054764,
-0.13808047771453857,
-0.02901330217719078,
-0.02060410939157009,
-0.13672903180122375,
0.11360576003789902,
-0.14730806648731232,
0.11739730834960938,
-0.03454136848449707,
0.1207665428519249,
0.014009964652359486,
-0.05091176927089691,
0.12791119515895844,
-0.0046410588547587395,
0.07603359967470169,
-0.03655969351530075,
-0.046836160123348236,
0.18456639349460602,
-0.03387966752052307,
0.05468735843896866,
-0.02245151437819004,
0.0720723494887352,
-0.1470232456922531,
-0.023892903700470924,
-0.08998914062976837,
0.06865768879652023,
-0.05194469168782234,
-0.06603237986564636,
-0.06026455760002136,
0.07369700074195862,
-0.02475782483816147,
-0.02835734188556671,
0.08562687784433365,
0.04889591038227081,
0.0923435166478157,
0.08968821167945862,
0.08056201040744781,
0.03332867473363876,
-0.08465319126844406,
-0.003772065509110689,
-0.028114579617977142,
0.08913581818342209,
-0.1535455882549286,
-0.0014690086245536804,
0.09281203150749207,
0.049990762025117874,
0.0971185564994812,
0.06118341535329819,
-0.09067294001579285,
0.03835597634315491,
0.06077073514461517,
-0.11331146955490112,
-0.1449732631444931,
-0.03217187896370888,
-0.0036760892253369093,
-0.15964120626449585,
0.07323424518108368,
0.10946305841207504,
-0.08161024749279022,
-0.035719119012355804,
-0.010226425714790821,
-0.008127548731863499,
-0.04752719774842262,
0.17852535843849182,
0.09498103708028793,
0.06795306503772736,
-0.0887429490685463,
0.10784647613763809,
0.08301011472940445,
-0.019451964646577835,
0.03316850587725639,
0.07818403840065002,
-0.07634814828634262,
-0.017379600554704666,
0.016779540106654167,
0.14085149765014648,
-0.07063375413417816,
-0.04914228990674019,
-0.13618357479572296,
-0.08799047768115997,
0.04652627930045128,
0.07589437812566757,
0.06534624844789505,
-0.02370510995388031,
-0.05251820385456085,
0.04867062345147133,
-0.17277398705482483,
0.09784183651208878,
0.028017466887831688,
0.07932811230421066,
-0.14474141597747803,
0.09350499510765076,
0.004967825021594763,
0.05369367450475693,
-0.021133191883563995,
0.008427138440310955,
-0.10911976546049118,
-0.00471061747521162,
-0.119178906083107,
-0.02792896144092083,
0.0003085604403167963,
0.006338875275105238,
-0.027962571009993553,
-0.054868221282958984,
-0.06383790820837021,
0.057862285524606705,
-0.08427966386079788,
-0.04072773829102516,
0.027351493015885353,
0.046933017671108246,
-0.1251041293144226,
0.017953431233763695,
0.016602452844381332,
-0.0855884775519371,
0.09595432132482529,
0.06194377318024635,
0.0537087582051754,
0.04604918137192726,
-0.06421402841806412,
-0.032251015305519104,
-0.000137308074044995,
0.013127979822456837,
0.06927134096622467,
-0.07007718086242676,
0.011747688986361027,
-0.03834070265293121,
0.06529979407787323,
0.00323494547046721,
0.0555758997797966,
-0.1394427865743637,
-0.01115130353718996,
-0.06502055376768112,
-0.042136479169130325,
-0.08060827851295471,
0.046355392783880234,
0.07200264185667038,
0.0590519979596138,
0.15020059049129486,
-0.0626632496714592,
0.016125155612826347,
-0.20809127390384674,
-0.015474100597202778,
-0.029699016362428665,
-0.05925866216421127,
-0.10362627357244492,
-0.025623928755521774,
0.05445535108447075,
-0.05050650238990784,
0.09696951508522034,
-0.0002672515984158963,
0.07603910565376282,
0.03857026249170303,
-0.025332147255539894,
-0.008679934777319431,
0.009598184376955032,
0.19209405779838562,
0.06300899386405945,
-0.000796677777543664,
0.0648321732878685,
0.008695635013282299,
0.060403332114219666,
0.0853831097483635,
0.14691345393657684,
0.15275819599628448,
-0.018104754388332367,
0.05700221285223961,
0.11380582302808762,
-0.05936908349394798,
-0.12623941898345947,
0.10067307204008102,
0.010286718606948853,
0.06620179861783981,
-0.044461868703365326,
0.15518637001514435,
0.16971337795257568,
-0.14114603400230408,
0.028357580304145813,
-0.05022720247507095,
-0.07596658170223236,
-0.0875965803861618,
-0.029141347855329514,
-0.07619732618331909,
-0.11528550088405609,
0.03676733002066612,
-0.12444896250963211,
-0.03107168897986412,
0.10255143791437149,
-0.0003083404735662043,
-0.016703912988305092,
0.14437030255794525,
0.02398441918194294,
0.015730058774352074,
0.0463065430521965,
0.0034113978035748005,
-0.021954385563731194,
-0.053397420793771744,
-0.05412866175174713,
0.03931539133191109,
0.0021758300717920065,
0.07909844070672989,
-0.04843466728925705,
-0.03732087090611458,
0.03349361941218376,
-0.004119501914829016,
-0.0705229714512825,
0.01894625462591648,
0.022540219128131866,
0.05685299262404442,
0.029078271239995956,
0.016725102439522743,
-0.009936205111443996,
-0.047559697180986404,
0.2669473886489868,
-0.06793110072612762,
-0.09497741609811783,
-0.11864744126796722,
0.18247149884700775,
0.017827406525611877,
-0.03937484696507454,
0.051626697182655334,
-0.10867471247911453,
-0.0329737551510334,
0.17208057641983032,
0.19244679808616638,
-0.03631790354847908,
-0.02483849786221981,
0.02791818417608738,
-0.029579488560557365,
-0.08482065051794052,
0.14328975975513458,
0.09643998742103577,
0.0727459117770195,
-0.06394080817699432,
-0.016661876812577248,
-0.02870633453130722,
-0.013570365495979786,
-0.050605736672878265,
0.07604772597551346,
0.032809920608997345,
-0.0006677961209788918,
-0.048810988664627075,
0.048833079636096954,
-0.013047629036009312,
-0.18649174273014069,
0.04683653637766838,
-0.1385786235332489,
-0.18822820484638214,
-0.038891300559043884,
0.07095758616924286,
-0.01884979009628296,
0.07664736360311508,
-0.03644812852144241,
0.003959102556109428,
0.08307905495166779,
-0.012449770234525204,
-0.07317490130662918,
-0.09796765446662903,
0.12910495698451996,
-0.04377370700240135,
0.20704536139965057,
-0.038130875676870346,
0.08321063965559006,
0.12194253504276276,
0.004139169584959745,
-0.14771904051303864,
0.01111642923206091,
0.06436415761709213,
-0.05987004190683365,
0.01619040034711361,
0.169560968875885,
-0.033227261155843735,
0.08477742969989777,
0.019164524972438812,
-0.12136945873498917,
-0.026622852310538292,
-0.046475183218717575,
-0.001304615056142211,
-0.08089467138051987,
0.0034875788260251284,
-0.0725008174777031,
0.14662057161331177,
0.19327017664909363,
-0.05045313760638237,
-0.031000085175037384,
-0.1027929037809372,
0.055044986307621,
0.09222669154405594,
0.06821697950363159,
-0.019267065450549126,
-0.1952277570962906,
-0.006141484249383211,
0.034305233508348465,
-0.005497874692082405,
-0.3038184344768524,
-0.05894649401307106,
0.039255086332559586,
-0.04634229466319084,
-0.07123734056949615,
0.08992303907871246,
0.09006232023239136,
0.05305977910757065,
-0.040802694857120514,
-0.0771670788526535,
-0.09490816295146942,
0.12404990941286087,
-0.18565350770950317,
-0.06078154221177101
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# marian-finetuned-kde4-zh-to-en-local
This model is a fine-tuned version of [charliealex123/marian-finetuned-kde4-zh-to-en](https://huggingface.co/charliealex123/marian-finetuned-kde4-zh-to-en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5666
- Bleu: 67.9677
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log | 1.0 | 57 | 0.6232 | 64.5453 |
| No log | 2.0 | 114 | 0.5666 | 67.9677 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| {"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "charliealex123/marian-finetuned-kde4-zh-to-en", "model-index": [{"name": "marian-finetuned-kde4-zh-to-en-local", "results": []}]} | text2text-generation | charliealex123/marian-finetuned-kde4-zh-to-en-local | [
"transformers",
"tensorboard",
"safetensors",
"marian",
"text2text-generation",
"generated_from_trainer",
"base_model:charliealex123/marian-finetuned-kde4-zh-to-en",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:50:07+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #base_model-charliealex123/marian-finetuned-kde4-zh-to-en #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us
| marian-finetuned-kde4-zh-to-en-local
====================================
This model is a fine-tuned version of charliealex123/marian-finetuned-kde4-zh-to-en on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5666
* Bleu: 67.9677
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #base_model-charliealex123/marian-finetuned-kde4-zh-to-en #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
86,
113,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #base_model-charliealex123/marian-finetuned-kde4-zh-to-en #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.14974084496498108,
0.128411203622818,
-0.002186035504564643,
0.09594079852104187,
0.11395392566919327,
0.012068022042512894,
0.15874798595905304,
0.11894015222787857,
-0.06733808666467667,
0.09059606492519379,
0.14190655946731567,
0.0972708910703659,
0.039838775992393494,
0.174835667014122,
-0.0651467964053154,
-0.21580810844898224,
0.0250061247497797,
0.03395634889602661,
-0.08501608669757843,
0.11937513202428818,
0.0948202982544899,
-0.1252593696117401,
0.08111698180437088,
0.01276102289557457,
-0.17536358535289764,
-0.02977241948246956,
0.0037931445986032486,
-0.048494040966033936,
0.12346748262643814,
0.045644283294677734,
0.12765051424503326,
0.07875989377498627,
0.07572316378355026,
-0.17402106523513794,
0.01457105204463005,
0.034879423677921295,
-0.002894133096560836,
0.09468743205070496,
0.06752428412437439,
0.0008810010040178895,
0.039652250707149506,
-0.11780265718698502,
0.03691703453660011,
0.009724149480462074,
-0.1210579052567482,
-0.18167519569396973,
-0.1070435494184494,
0.05077686905860901,
0.0775357112288475,
0.06553623825311661,
-0.007504103239625692,
0.11781763285398483,
-0.025879299268126488,
0.08080390095710754,
0.23998811841011047,
-0.3004714250564575,
-0.06576011329889297,
0.014699996449053288,
0.05416193976998329,
0.0816541463136673,
-0.08064109086990356,
-0.02144487202167511,
0.057638537138700485,
0.0007000530604273081,
0.11811764538288116,
-0.013199570588767529,
0.0024162856861948967,
-0.01595362462103367,
-0.1506122499704361,
-0.05565090477466583,
0.17444023489952087,
0.05500921979546547,
-0.05133653059601784,
-0.062136877328157425,
-0.06421568244695663,
-0.16285111010074615,
-0.029360152781009674,
0.004688451066613197,
0.014601843431591988,
-0.04820147529244423,
-0.10075104236602783,
-0.01747521571815014,
-0.10792410373687744,
-0.08080970495939255,
-0.010055184364318848,
0.14557166397571564,
0.051896508783102036,
-0.001107682241126895,
-0.006806365679949522,
0.10256750881671906,
0.008283691480755806,
-0.1610700935125351,
0.0033896579407155514,
0.010917266830801964,
-0.023081768304109573,
-0.038266781717538834,
-0.05114433914422989,
-0.04840395227074623,
0.02149980142712593,
0.13699506223201752,
-0.05842771753668785,
0.05171055719256401,
0.028650708496570587,
0.03968162462115288,
-0.0949690192937851,
0.1383354514837265,
-0.05671956017613411,
-0.00459551066160202,
0.02889503724873066,
0.12254639714956284,
0.02959483489394188,
-0.025189675390720367,
-0.1015266701579094,
-0.01056522224098444,
0.1327103227376938,
0.026041610166430473,
-0.030918989330530167,
0.05068187415599823,
-0.07272959500551224,
-0.03192272409796715,
0.0664382129907608,
-0.08996754139661789,
0.008940615691244602,
0.026325257495045662,
-0.06564337015151978,
-0.07085267454385757,
0.016667773947119713,
0.018913133069872856,
0.006167599931359291,
0.06569825857877731,
-0.08618276566267014,
-0.013531782664358616,
-0.06624829769134521,
-0.11802500486373901,
0.02266690507531166,
-0.07737535238265991,
0.010947699658572674,
-0.10041382908821106,
-0.12869809567928314,
-0.03721940144896507,
0.03236282616853714,
-0.033039893954992294,
-0.0744243636727333,
-0.05590679496526718,
-0.07698525488376617,
0.03733920305967331,
-0.012857195921242237,
0.09352052211761475,
-0.0546574741601944,
0.10807272791862488,
0.04721774160861969,
0.06933003664016724,
-0.02291497401893139,
0.038698479533195496,
-0.06260892748832703,
0.05508420988917351,
-0.13779127597808838,
0.06195036321878433,
-0.06216529384255409,
0.035169992595911026,
-0.10836709290742874,
-0.08500517159700394,
0.0033262630458921194,
-0.023941460996866226,
0.10919690132141113,
0.11214695125818253,
-0.16908076405525208,
-0.05415099486708641,
0.1961921751499176,
-0.08301837742328644,
-0.134640172123909,
0.12542188167572021,
-0.045524414628744125,
0.019002048298716545,
0.03718017041683197,
0.14719855785369873,
0.1074334904551506,
-0.07913615554571152,
-0.003966389689594507,
-0.028280718252062798,
0.09777176380157471,
-0.05964628607034683,
0.11221121996641159,
0.0017699101008474827,
-0.007693094667047262,
0.001030901912599802,
-0.09636437147855759,
0.03832003101706505,
-0.09920922666788101,
-0.09209207445383072,
-0.02619660459458828,
-0.0987677350640297,
0.06492756307125092,
0.03821771964430809,
0.062473364174366,
-0.09520483762025833,
-0.08766941726207733,
0.01941250078380108,
0.09944106638431549,
-0.09777749329805374,
0.017154565081000328,
-0.06846068799495697,
0.09963999688625336,
-0.08142417669296265,
-0.02417442575097084,
-0.1630810648202896,
-0.05951090529561043,
0.03556431829929352,
-0.012641172856092453,
0.005363300442695618,
-0.0065668849274516106,
0.0555693693459034,
0.09002887457609177,
-0.03814150393009186,
-0.05908924341201782,
-0.04579435661435127,
-0.0024459240958094597,
-0.10810981690883636,
-0.2064158320426941,
-0.04606951028108597,
-0.03112083300948143,
0.19714131951332092,
-0.22764061391353607,
0.03525187820196152,
0.04147491976618767,
0.10230088979005814,
0.022909164428710938,
-0.02126031182706356,
-0.01338244415819645,
0.07379837334156036,
-0.035347457975149155,
-0.059317633509635925,
0.06878162920475006,
0.030073439702391624,
-0.11232456564903259,
0.03283682465553284,
-0.15548647940158844,
0.1220206543803215,
0.11126083135604858,
0.001017423695884645,
-0.06260691583156586,
-0.03687552362680435,
-0.05111194774508476,
-0.04397202283143997,
-0.025104064494371414,
0.00041180712287314236,
0.13324199616909027,
0.0070074088871479034,
0.15314671397209167,
-0.09837950021028519,
-0.04870767518877983,
0.03752707690000534,
-0.02343100495636463,
-0.013495882973074913,
0.12197470664978027,
0.06001926213502884,
-0.121351458132267,
0.1275034099817276,
0.1281614899635315,
-0.06390753388404846,
0.13874009251594543,
-0.056247446686029434,
-0.08072396367788315,
-0.0448090024292469,
0.03821872919797897,
0.04107221961021423,
0.12856948375701904,
-0.07858052849769592,
-0.018227891996502876,
0.025049878284335136,
0.0010398015147075057,
0.01794261857867241,
-0.22324077785015106,
-0.016674892976880074,
0.04464096948504448,
-0.05544455349445343,
-0.004943888634443283,
-0.008994647301733494,
-0.007992873899638653,
0.0981389507651329,
0.0023311609402298927,
-0.06304774433374405,
0.033834122121334076,
-0.009786432608962059,
-0.09408101439476013,
0.20906519889831543,
-0.07247055321931839,
-0.1370927095413208,
-0.14562350511550903,
-0.032532699406147,
-0.04162987321615219,
0.013561430387198925,
0.0443425290286541,
-0.044524915516376495,
-0.02197159081697464,
-0.09001030027866364,
-0.02076779119670391,
0.00254518399015069,
0.03425665944814682,
0.027777547016739845,
-0.00906364619731903,
0.07832835614681244,
-0.09672821313142776,
0.005287512205541134,
-0.021491799503564835,
-0.027407854795455933,
0.06332693248987198,
0.006188129540532827,
0.13087767362594604,
0.12716010212898254,
-0.021691065281629562,
0.007611372973769903,
-0.03361457958817482,
0.2144131362438202,
-0.05830514430999756,
-0.029191628098487854,
0.1125807911157608,
-0.03179359436035156,
0.07259369641542435,
0.13772182166576385,
0.0416671447455883,
-0.07724294066429138,
0.01666177809238434,
0.0008456875220872462,
-0.028368284925818443,
-0.22729986906051636,
-0.0350143238902092,
-0.04884162172675133,
-0.008433118462562561,
0.11558420211076736,
0.019727589562535286,
0.010252900421619415,
0.08032884448766708,
-0.01679397001862526,
0.0659579411149025,
-0.012933959253132343,
0.07813622802495956,
0.0895662009716034,
0.05538363382220268,
0.1308986097574234,
-0.037150789052248,
-0.040072109550237656,
0.029939191415905952,
0.013683467172086239,
0.2364695519208908,
-0.021597454324364662,
0.2224079668521881,
0.06048687919974327,
0.19254308938980103,
0.03550088033080101,
0.06314296275377274,
0.005822027567774057,
-0.008111974224448204,
-0.005738022271543741,
-0.05159488692879677,
-0.046831611543893814,
0.024471208453178406,
-0.041479624807834625,
0.036632996052503586,
-0.13734553754329681,
0.048521172255277634,
0.013056267984211445,
0.2622772753238678,
0.0670618936419487,
-0.35072949528694153,
-0.0936778113245964,
0.006958063691854477,
0.01008567400276661,
-0.026374060660600662,
-0.006923386361449957,
0.15661877393722534,
-0.07310094684362411,
0.035344913601875305,
-0.08632902801036835,
0.08042854815721512,
-0.07077386975288391,
0.009087708778679371,
0.04302303493022919,
0.08233083039522171,
-0.0034318757243454456,
0.06430742889642715,
-0.25813916325569153,
0.29065433144569397,
0.009814837947487831,
0.04934268444776535,
-0.060632821172475815,
-0.005965543445199728,
0.017410147935152054,
0.018349388614296913,
0.07099439203739166,
-0.010661027394235134,
-0.0987321212887764,
-0.20306909084320068,
-0.12292176485061646,
0.023282552137970924,
0.10558703541755676,
-0.04792318865656853,
0.12768177688121796,
-0.020959114655852318,
-0.005252022296190262,
0.05090697109699249,
0.017724579200148582,
-0.09212114661931992,
-0.1140829548239708,
0.027751272544264793,
0.02282007224857807,
-0.012248954735696316,
-0.10207995772361755,
-0.12111586332321167,
-0.08039300888776779,
0.1433085948228836,
-0.053615752607584,
-0.03431819751858711,
-0.11454638093709946,
0.08021102845668793,
0.1021362915635109,
-0.11133010685443878,
0.04217296466231346,
0.008076963014900684,
0.13575947284698486,
-0.0009336143266409636,
-0.047216806560754776,
0.08869320899248123,
-0.06798363476991653,
-0.1998342126607895,
-0.0587896890938282,
0.13503092527389526,
0.03298193961381912,
0.05692485719919205,
-0.0012116654543206096,
0.020721785724163055,
-0.009095209650695324,
-0.07134538888931274,
0.026158085092902184,
-0.007653229869902134,
0.058125581592321396,
0.00021062177256681025,
-0.043479517102241516,
-0.009253592230379581,
-0.06767050176858902,
-0.046402670443058014,
0.17617961764335632,
0.2932865023612976,
-0.0919937938451767,
0.009140823036432266,
0.04744400456547737,
-0.051504310220479965,
-0.18808580935001373,
0.016660159453749657,
0.09244739264249802,
0.04416057839989662,
0.005727862007915974,
-0.16034437716007233,
0.025193840265274048,
0.09064530581235886,
-0.023083772510290146,
0.06898574531078339,
-0.3011784255504608,
-0.14019623398780823,
0.08844492584466934,
0.15526163578033447,
0.10203540325164795,
-0.15883684158325195,
-0.06844881176948547,
-0.01010571513324976,
-0.12249719351530075,
0.11965829879045486,
-0.0803925171494484,
0.11085929721593857,
-0.018532324582338333,
0.025248762220144272,
0.007202653214335442,
-0.05722719803452492,
0.1449681520462036,
-0.0014813814777880907,
0.06703510880470276,
-0.04043939709663391,
-0.020120013505220413,
0.08703126758337021,
-0.07686488330364227,
0.008581360802054405,
-0.08531033992767334,
0.054186414927244186,
-0.10014671087265015,
-0.019762545824050903,
-0.07139430940151215,
0.01751863770186901,
-0.049964480102062225,
-0.02279101312160492,
-0.029163645580410957,
0.03325933218002319,
0.05461473390460014,
0.00018760887905955315,
0.1115521639585495,
0.02539926767349243,
0.10793812572956085,
0.12328231334686279,
0.09060104191303253,
-0.016093239188194275,
-0.010972260497510433,
-0.015775881707668304,
-0.02600874938070774,
0.05523953586816788,
-0.12484994530677795,
0.02788994088768959,
0.13263581693172455,
0.026817509904503822,
0.12693051993846893,
0.0542643703520298,
-0.06770123541355133,
0.022960394620895386,
0.0703376904129982,
-0.15228019654750824,
-0.12002688646316528,
-0.02731735073029995,
0.020027777180075645,
-0.13302412629127502,
0.023908551782369614,
0.12424491345882416,
-0.056215498596429825,
-0.02167886309325695,
-0.021442836150527,
-0.005736963357776403,
-0.009879612363874912,
0.20341920852661133,
0.06555994600057602,
0.07365718483924866,
-0.08499401062726974,
0.05612829700112343,
0.06324248760938644,
-0.0848178043961525,
0.023615136742591858,
0.04243624582886696,
-0.09372702986001968,
-0.03250553831458092,
0.050629399716854095,
0.139071524143219,
-0.046224016696214676,
-0.05461414158344269,
-0.1492009460926056,
-0.10288652032613754,
0.05832917243242264,
0.16473078727722168,
0.07871624827384949,
0.028500666841864586,
0.010049192234873772,
-0.011358669959008694,
-0.1134006455540657,
0.12031484395265579,
0.07097289711236954,
0.09390819072723389,
-0.13723188638687134,
0.13163669407367706,
-0.017269594594836235,
0.03606913611292839,
-0.008239829912781715,
0.03588823974132538,
-0.1016804650425911,
-0.01919572614133358,
-0.1148524209856987,
0.026945432648062706,
-0.039558663964271545,
-0.01376911997795105,
-0.021971995010972023,
-0.053215865045785904,
-0.04791416972875595,
0.02917630411684513,
-0.08857851475477219,
-0.0393943265080452,
-0.006348376628011465,
0.05102396011352539,
-0.10870367288589478,
-0.03808091953396797,
0.03279146924614906,
-0.10239244252443314,
0.08048169314861298,
0.027836665511131287,
0.03743821382522583,
0.01647515594959259,
-0.09764227271080017,
0.018448716029524803,
0.03548930585384369,
0.016824230551719666,
0.04362836107611656,
-0.14012697339057922,
-0.0021134675480425358,
-0.00641448050737381,
0.0274849534034729,
0.00030861858977004886,
0.08815012127161026,
-0.118187315762043,
-0.019175846129655838,
-0.026806943118572235,
-0.0279620960354805,
-0.06777621060609818,
0.05237799882888794,
0.0718582347035408,
0.027452092617750168,
0.17706575989723206,
-0.08720213919878006,
0.031464725732803345,
-0.20860694348812103,
-0.0010680592386052012,
-0.00829552486538887,
-0.10096360743045807,
-0.10164101421833038,
-0.048190806061029434,
0.07466483116149902,
-0.05426294356584549,
0.09489776939153671,
-0.04380087926983833,
0.02121368795633316,
0.018327394500374794,
-0.023332519456744194,
0.04152347147464752,
0.04201953485608101,
0.21656499803066254,
0.028426261618733406,
-0.02479240484535694,
0.05327540263533592,
0.039267271757125854,
0.08765826374292374,
0.10410737246274948,
0.1782321184873581,
0.14898580312728882,
0.021984709426760674,
0.07920525223016739,
0.07437581568956375,
-0.05148094892501831,
-0.1299036294221878,
0.05491624027490616,
-0.05093323066830635,
0.07824070751667023,
-0.0002496866218280047,
0.19639718532562256,
0.1062161847949028,
-0.19161349534988403,
0.014338498935103416,
-0.03657536208629608,
-0.09708540141582489,
-0.09330858290195465,
-0.09101918339729309,
-0.10509106516838074,
-0.1143084242939949,
-0.005220181308686733,
-0.1195378378033638,
-0.00887706782668829,
0.0863475576043129,
0.005188429728150368,
0.0017002193490043283,
0.14505866169929504,
0.05651156231760979,
0.010722924023866653,
0.06415542960166931,
0.010042199864983559,
-0.003542251419275999,
-0.05069280415773392,
-0.09547856450080872,
0.037912093102931976,
-0.010465705767273903,
0.04951292276382446,
-0.046089980751276016,
-0.011289674788713455,
0.06007961183786392,
0.011277931742370129,
-0.11796380579471588,
0.0060499622486531734,
0.01096330676227808,
0.0820663645863533,
0.05520318076014519,
0.02281733974814415,
0.008711855858564377,
-0.006344588007777929,
0.18458931148052216,
-0.04033411294221878,
-0.05512011796236038,
-0.11070495843887329,
0.15423332154750824,
0.013130536302924156,
-0.020373575389385223,
0.05471132695674896,
-0.09041984379291534,
0.041366152465343475,
0.17905031144618988,
0.15988196432590485,
-0.06663341820240021,
0.005342095624655485,
0.011593278497457504,
-0.008617157116532326,
-0.020062411203980446,
0.085729219019413,
0.1058284193277359,
0.03954223915934563,
-0.08877650648355484,
-0.06794451177120209,
-0.05016881600022316,
-0.00044389194226823747,
-0.029925519600510597,
0.06473346799612045,
0.015666866675019264,
0.001784150255843997,
-0.04140390828251839,
0.046250808984041214,
-0.015634195879101753,
-0.07782917469739914,
0.03450419381260872,
-0.2036474198102951,
-0.1705566644668579,
-0.03435436636209488,
0.06590273976325989,
-0.0017457460053265095,
0.050743915140628815,
-0.03170430287718773,
0.011961049400269985,
0.06848497688770294,
-0.01717018149793148,
-0.06520434468984604,
-0.04102059081196785,
0.06795378029346466,
-0.0804985836148262,
0.18776929378509521,
-0.037521861493587494,
0.08556606620550156,
0.13550376892089844,
0.051641594618558884,
-0.11452212929725647,
0.055346470326185226,
0.06336852163076401,
-0.051030032336711884,
0.04591601341962814,
0.12519487738609314,
-0.03968201205134392,
0.09657313674688339,
0.05949295312166214,
-0.12293723970651627,
0.0161854550242424,
-0.0435662679374218,
-0.026937609538435936,
-0.05376953259110451,
-0.019703462719917297,
-0.05697272717952728,
0.14477680623531342,
0.1803881675004959,
-0.06280747801065445,
-0.01022779755294323,
-0.034658800810575485,
0.004838608670979738,
0.06631478667259216,
0.09261856228113174,
-0.02844887226819992,
-0.2518268823623657,
0.010435142554342747,
0.02636052295565605,
0.017446231096982956,
-0.28108546137809753,
-0.08919313549995422,
-0.008519914932549,
-0.060147110372781754,
-0.08390398323535919,
0.11281464993953705,
0.08425021171569824,
0.05255282297730446,
-0.06204710155725479,
-0.04662474989891052,
-0.09263697266578674,
0.1475362330675125,
-0.15036258101463318,
-0.0976165384054184
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] | {"library_name": "transformers", "tags": []} | automatic-speech-recognition | spsither/wav2vec2_run9.25 | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:52:09+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #wav2vec2 #automatic-speech-recognition #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #wav2vec2 #automatic-speech-recognition #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
47,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #wav2vec2 #automatic-speech-recognition #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06877388060092926,
0.1546701192855835,
-0.0037609888240695,
0.013798683881759644,
0.11170210689306259,
0.0049477447755634785,
0.07622946053743362,
0.1076156347990036,
-0.024175573140382767,
0.12644733488559723,
0.04164152219891548,
0.09870775043964386,
0.11074616760015488,
0.18980292975902557,
0.0015578214079141617,
-0.20271944999694824,
0.06667982041835785,
-0.11557482928037643,
0.02210802026093006,
0.12125445902347565,
0.14131462574005127,
-0.10717527568340302,
0.06805222481489182,
-0.03453851491212845,
-0.022604284808039665,
-0.03256304934620857,
-0.06200181692838669,
-0.0628168061375618,
0.06936536729335785,
0.060818396508693695,
0.06474827229976654,
0.023958178237080574,
0.07868874818086624,
-0.2985154092311859,
0.020363550633192062,
0.07747753709554672,
0.005190075840801001,
0.0596587099134922,
0.07716850191354752,
-0.06847380846738815,
0.11357854306697845,
-0.0553223080933094,
0.15529125928878784,
0.07729580253362656,
-0.09200245141983032,
-0.18732582032680511,
-0.08171983063220978,
0.09086527675390244,
0.16344711184501648,
0.05807739868760109,
-0.035454582422971725,
0.14257195591926575,
-0.08119463175535202,
0.015228749252855778,
0.06432900577783585,
-0.07448869198560715,
-0.04995284602046013,
0.044303327798843384,
0.07393822818994522,
0.09027253836393356,
-0.12936420738697052,
-0.005840824451297522,
0.04285894334316254,
0.01751609519124031,
0.1045890524983406,
0.0271924901753664,
0.10937820374965668,
0.030452799052000046,
-0.13982591032981873,
-0.06308452039957047,
0.12294159829616547,
0.03608649969100952,
-0.05978325754404068,
-0.24299637973308563,
-0.007494248915463686,
-0.030862024053931236,
-0.022421855479478836,
-0.0449565127491951,
0.040200937539339066,
-0.03043903410434723,
0.0803007185459137,
0.005218773614615202,
-0.07346875220537186,
-0.0566013865172863,
0.08528164029121399,
0.0660456046462059,
0.024965541437268257,
-0.02511134371161461,
0.022877119481563568,
0.11602471768856049,
0.09200266003608704,
-0.11191211640834808,
-0.07020656764507294,
-0.06118712201714516,
-0.09110330045223236,
-0.04440220445394516,
0.03338851034641266,
0.07138838618993759,
0.04954010248184204,
0.19076436758041382,
0.006971653085201979,
0.05134076997637749,
0.026316070929169655,
0.018496420234441757,
0.061533693224191666,
0.06859898567199707,
-0.05315755307674408,
-0.12085959315299988,
-0.043275654315948486,
0.1195915937423706,
0.008576745167374611,
-0.03422791138291359,
-0.034871865063905716,
0.05920550227165222,
0.05124519392848015,
0.11922229826450348,
0.06299308687448502,
0.015805674716830254,
-0.06944610923528671,
-0.041848812252283096,
0.17807698249816895,
-0.15696440637111664,
0.01886504516005516,
0.019594965502619743,
-0.05179493874311447,
-0.028022583574056625,
0.01927095092833042,
0.011918062344193459,
-0.028684133663773537,
0.09848573058843613,
-0.06384129822254181,
-0.037289999425411224,
-0.10494036227464676,
-0.051826175302267075,
0.03436095267534256,
-0.01885044015944004,
-0.030469300225377083,
-0.04276524484157562,
-0.11668366193771362,
-0.07342278957366943,
0.06446365267038345,
-0.06070359796285629,
-0.06312011927366257,
-0.04004829749464989,
-0.05974921956658363,
0.01184001937508583,
-0.0018999426392838359,
0.12804386019706726,
-0.03126852586865425,
0.04724927991628647,
-0.05154479295015335,
0.07010733336210251,
0.13001501560211182,
0.0328618623316288,
-0.06312436610460281,
0.06317896395921707,
-0.20583610236644745,
0.10645388811826706,
-0.0948607325553894,
0.026716187596321106,
-0.16420963406562805,
-0.024270139634609222,
0.02872021123766899,
0.03977278992533684,
-0.014035328291356564,
0.13902691006660461,
-0.1889396458864212,
-0.037479519844055176,
0.1823769360780716,
-0.1340419203042984,
-0.09025664627552032,
0.06442771852016449,
-0.056058306246995926,
0.1311984360218048,
0.051679398864507675,
-0.016549112275242805,
0.050827931612730026,
-0.14181455969810486,
-0.021199021488428116,
-0.05750836804509163,
-0.01345672644674778,
0.14918801188468933,
0.06591099500656128,
-0.060217004269361496,
0.03262941166758537,
0.02008114755153656,
-0.02076314203441143,
-0.052245598286390305,
-0.03416990861296654,
-0.09862805157899857,
0.003799794940277934,
-0.08055862784385681,
0.018423959612846375,
-0.026528598740696907,
-0.08738208562135696,
-0.0410190187394619,
-0.1575777381658554,
-0.001173238386400044,
0.1026405617594719,
0.0026203012093901634,
-0.02646641992032528,
-0.10305316001176834,
0.001408840762451291,
0.015838710591197014,
-0.010245922021567822,
-0.14677146077156067,
-0.04217318072915077,
0.026863576844334602,
-0.16719304025173187,
0.031281016767024994,
-0.045817263424396515,
0.03617605194449425,
0.042714666575193405,
-0.04341552406549454,
-0.026187991723418236,
0.011214246973395348,
0.01926763355731964,
-0.01759723760187626,
-0.24584431946277618,
-0.01623428985476494,
-0.05088721215724945,
0.17665798962116241,
-0.2476477026939392,
0.04387471452355385,
0.07402390241622925,
0.1185368224978447,
0.006659833248704672,
-0.0473252609372139,
0.03859061002731323,
-0.04956425726413727,
-0.039547327905893326,
-0.06162410229444504,
-0.002731422893702984,
-0.034249331802129745,
-0.04925791174173355,
0.04766050726175308,
-0.19274261593818665,
-0.0254798773676157,
0.1145588755607605,
0.07196282595396042,
-0.16417020559310913,
-0.0721944123506546,
-0.03388380631804466,
-0.060263555496931076,
-0.0855790227651596,
-0.05511211231350899,
0.10627889633178711,
0.042532145977020264,
0.053568705916404724,
-0.07193132489919662,
-0.0538090355694294,
0.014475145377218723,
-0.008023109287023544,
-0.03674730286002159,
0.08616615831851959,
0.07892905920743942,
-0.111492820084095,
0.0967666357755661,
0.06781410425901413,
0.06170906499028206,
0.10836543887853622,
0.0035758649464696646,
-0.09838994592428207,
-0.013410377316176891,
0.028753211721777916,
0.013008177280426025,
0.1445195972919464,
-0.08268706500530243,
0.02993486076593399,
0.04475158452987671,
-0.029572229832410812,
0.014260980300605297,
-0.10948343575000763,
0.020612964406609535,
0.03188888356089592,
-0.01410164125263691,
0.016051514074206352,
-0.05129382014274597,
0.013738108798861504,
0.10363461822271347,
0.031123731285333633,
0.025897923856973648,
0.016665659844875336,
-0.04273077845573425,
-0.12888197600841522,
0.17441782355308533,
-0.09573886543512344,
-0.24906472861766815,
-0.13649064302444458,
0.0033230632543563843,
0.04450872540473938,
-0.01420661062002182,
0.019941311329603195,
-0.06085766479372978,
-0.10865217447280884,
-0.10793688893318176,
0.02346382476389408,
0.04952440410852432,
-0.08567548543214798,
-0.05095811188220978,
0.05441328510642052,
0.03898037597537041,
-0.12600500881671906,
0.024548007175326347,
0.04095667228102684,
-0.07147589325904846,
0.005656755063682795,
0.061115942895412445,
0.08382482826709747,
0.1812773495912552,
0.012779363431036472,
-0.015533777885138988,
0.01035984791815281,
0.21022020280361176,
-0.14754468202590942,
0.08923394232988358,
0.142924964427948,
-0.06379926204681396,
0.07994367927312851,
0.20067699253559113,
0.030222468078136444,
-0.0959763154387474,
0.0354040265083313,
0.03157598897814751,
-0.03929230570793152,
-0.24485765397548676,
-0.07799134403467178,
0.004727535881102085,
-0.06941798329353333,
0.0999692752957344,
0.08970286697149277,
0.11357339471578598,
0.04878859966993332,
-0.10688808560371399,
-0.07536104321479797,
0.04997042194008827,
0.11770502477884293,
-0.025654911994934082,
0.0004288276832085103,
0.09490229189395905,
-0.032173965126276016,
0.024045821279287338,
0.09091470390558243,
0.01785297878086567,
0.1891387403011322,
0.045389045029878616,
0.13416282832622528,
0.08966030925512314,
0.05892613157629967,
0.02283613197505474,
0.020396918058395386,
0.022836502641439438,
0.028627371415495872,
-0.02071341499686241,
-0.08800762891769409,
-0.01406664215028286,
0.1445012241601944,
0.03501417487859726,
0.03224355727434158,
0.005818283185362816,
-0.03822546452283859,
0.07026989012956619,
0.16923215985298157,
0.01291902456432581,
-0.22557523846626282,
-0.06553208827972412,
0.07285686582326889,
-0.07819344103336334,
-0.10939628630876541,
-0.00628721434623003,
0.039236925542354584,
-0.1781243532896042,
0.0453440323472023,
-0.016895415261387825,
0.09935811161994934,
-0.11019659787416458,
-0.022818224504590034,
0.03339223191142082,
0.06351818144321442,
-0.033710017800331116,
0.07605454325675964,
-0.20844414830207825,
0.14833855628967285,
0.007355031557381153,
0.06984888762235641,
-0.10627210140228271,
0.07959222793579102,
0.018262188881635666,
0.0005360859213396907,
0.16532482206821442,
-0.0075689139775931835,
-0.07650822401046753,
-0.08155251294374466,
-0.07923656702041626,
-0.010918287560343742,
0.10160883516073227,
-0.10205793380737305,
0.08789419382810593,
-0.006757213734090328,
-0.030893130227923393,
-0.00026032759342342615,
-0.11519953608512878,
-0.1342930644750595,
-0.18055365979671478,
0.04992220178246498,
-0.10558607429265976,
0.04552379995584488,
-0.11181014776229858,
-0.062069665640592575,
-0.04111560434103012,
0.18840233981609344,
-0.20550832152366638,
-0.07671810686588287,
-0.14316488802433014,
-0.08166468888521194,
0.11773297190666199,
-0.036535169929265976,
0.08007847517728806,
0.008441719226539135,
0.20702308416366577,
-0.00666013965383172,
0.002528243465349078,
0.08686443418264389,
-0.09668374806642532,
-0.2072489857673645,
-0.09340810775756836,
0.14340825378894806,
0.12398830056190491,
0.045563604682683945,
-0.0001787850633263588,
0.021285003051161766,
-0.004406071733683348,
-0.11160994321107864,
0.036765191704034805,
0.1599014699459076,
0.08414851129055023,
0.041826896369457245,
-0.023910723626613617,
-0.15188267827033997,
-0.1039518192410469,
-0.06143968924880028,
0.022748636081814766,
0.18740743398666382,
-0.06844107806682587,
0.17012163996696472,
0.157639279961586,
-0.061386726796627045,
-0.20854754745960236,
0.031976643949747086,
0.03363525867462158,
-0.008795025758445263,
0.0332365483045578,
-0.20113597810268402,
0.06802120804786682,
0.01531505398452282,
-0.057996444404125214,
0.1332528293132782,
-0.16826434433460236,
-0.15160627663135529,
0.08843177556991577,
0.07692008465528488,
-0.20126505196094513,
-0.12921905517578125,
-0.09711465984582901,
-0.05218008533120155,
-0.10807206481695175,
0.08772927522659302,
-0.006655422504991293,
0.007214459590613842,
0.037578340619802475,
0.02635364979505539,
0.015357093885540962,
-0.05328182876110077,
0.19721722602844238,
0.0011987579055130482,
0.044046565890312195,
-0.07511261850595474,
-0.077226422727108,
0.034381043165922165,
-0.06312628090381622,
0.07982822507619858,
-0.020660031586885452,
0.0017429457511752844,
-0.11481664329767227,
-0.06663372367620468,
-0.05009456351399422,
0.029989875853061676,
-0.08466581255197525,
-0.09467059373855591,
-0.051657307893037796,
0.09798348695039749,
0.09048279374837875,
-0.03396918624639511,
-0.06807554513216019,
-0.10042613744735718,
0.06601390987634659,
0.22872091829776764,
0.18910692632198334,
0.06991440057754517,
-0.06895517557859421,
-0.0038870053831487894,
-0.026509825140237808,
0.05879383906722069,
-0.20851773023605347,
0.044600993394851685,
0.036500073969364166,
0.032537586987018585,
0.13215065002441406,
-0.02442602440714836,
-0.16357013583183289,
-0.043075863271951675,
0.056227099150419235,
-0.06633396446704865,
-0.16863006353378296,
0.005107434932142496,
0.09075167030096054,
-0.15091724693775177,
-0.04752274975180626,
0.030901111662387848,
-0.03220430761575699,
-0.02397167682647705,
0.00030637482996098697,
0.08078145235776901,
0.020850084722042084,
0.1107739508152008,
0.06640642136335373,
0.11335843801498413,
-0.10278842598199844,
0.08162284642457962,
0.08386309444904327,
-0.11347422748804092,
0.04244251549243927,
0.05978094041347504,
-0.06325716525316238,
-0.03386267274618149,
0.016484335064888,
0.0787876546382904,
0.03214597329497337,
-0.08122093230485916,
0.0026990212500095367,
-0.11556044965982437,
0.06788678467273712,
0.14209748804569244,
0.03322440758347511,
0.007564007304608822,
0.04558844491839409,
0.031089849770069122,
-0.09967122226953506,
0.10952559113502502,
0.0327114500105381,
0.03264835476875305,
-0.052766215056180954,
0.007493352517485619,
0.044093240052461624,
-0.012370331212878227,
-0.01659340038895607,
-0.04159332811832428,
-0.062125492841005325,
-0.004501889459788799,
-0.15752804279327393,
0.029296958819031715,
-0.06990371644496918,
0.009181820787489414,
0.0195058211684227,
-0.03118128329515457,
0.001035416848026216,
0.014971627853810787,
-0.0777391716837883,
-0.03601877763867378,
-0.00462498189881444,
0.10573451966047287,
-0.15904870629310608,
0.012398114427924156,
0.0838126391172409,
-0.12594857811927795,
0.0813586562871933,
-0.0006106876535341144,
-0.01206875778734684,
0.022131776437163353,
-0.14767099916934967,
0.06096983700990677,
-0.00651735020801425,
0.005330943502485752,
0.022080490365624428,
-0.20231451094150543,
0.0010611782781779766,
-0.046166326850652695,
-0.0580565482378006,
-0.006821162533015013,
-0.034208331257104874,
-0.10881488770246506,
0.10119375586509705,
0.01840946450829506,
-0.0807829275727272,
-0.019118202850222588,
0.049314580857753754,
0.10984907299280167,
-0.05423201248049736,
0.13843025267124176,
-0.022093484178185463,
0.05561875179409981,
-0.17508383095264435,
-0.015010466799139977,
-0.01884511485695839,
0.01675039529800415,
-0.032699406147003174,
-0.0063448576256632805,
0.053761400282382965,
-0.021795762702822685,
0.23006084561347961,
-0.03329315781593323,
0.022746775299310684,
0.0662616565823555,
-0.007395898457616568,
-0.02466614730656147,
0.09141410142183304,
0.05831921473145485,
0.019823938608169556,
0.023462723940610886,
0.009678727947175503,
-0.051977336406707764,
-0.011846045032143593,
-0.1287335902452469,
0.08032830059528351,
0.17006289958953857,
0.0832807645201683,
-0.0011417492059990764,
0.05661620944738388,
-0.11824764311313629,
-0.08884397894144058,
0.10315068811178207,
-0.03696487843990326,
-0.008325101807713509,
-0.05479050800204277,
0.14003127813339233,
0.16284166276454926,
-0.1792466789484024,
0.06529472023248672,
-0.06703231483697891,
-0.054111137986183167,
-0.1079135313630104,
-0.1702733039855957,
-0.06385406106710434,
-0.04134172946214676,
-0.003200325183570385,
-0.056672241538763046,
0.07026970386505127,
0.10425727069377899,
0.015394158661365509,
0.007145122159272432,
0.08924684673547745,
-0.034410521388053894,
0.003967431839555502,
0.04615078866481781,
0.05031316727399826,
0.015370454639196396,
-0.06289559602737427,
0.003805057378485799,
0.012086667120456696,
0.03619912639260292,
0.05767577514052391,
0.03358588367700577,
-0.015441972762346268,
0.00826429296284914,
-0.019517268985509872,
-0.0962890237569809,
0.0407244898378849,
-0.028659315779805183,
-0.04762914776802063,
0.14599058032035828,
0.023316938430070877,
-0.005744231399148703,
-0.019850272685289383,
0.22833019495010376,
-0.06841307878494263,
-0.08293036371469498,
-0.13890130817890167,
0.1406106948852539,
-0.04129096865653992,
0.054532211273908615,
0.048289187252521515,
-0.10287833213806152,
0.031274814158678055,
0.14709845185279846,
0.14302049577236176,
-0.028337303549051285,
0.01196619775146246,
0.009999874047935009,
0.005250520538538694,
-0.026724260300397873,
0.052909236401319504,
0.049603480845689774,
0.12155342847108841,
-0.06124946475028992,
0.09144628793001175,
-0.0038096080534160137,
-0.08695073425769806,
-0.01940424181520939,
0.13583695888519287,
-0.001434069243259728,
0.020704632624983788,
-0.08129720389842987,
0.11675985902547836,
-0.06527755409479141,
-0.2561015188694,
0.060353249311447144,
-0.06762448698282242,
-0.14944049715995789,
-0.018578823655843735,
0.027211744338274002,
0.0003355915832798928,
0.021279368549585342,
0.06146527826786041,
-0.06275594234466553,
0.15064457058906555,
0.03758588433265686,
-0.07729688286781311,
-0.07095571607351303,
0.07545747607946396,
-0.0798204317688942,
0.2952599823474884,
0.007051850203424692,
0.05692324787378311,
0.09223286807537079,
-0.033274851739406586,
-0.1323377937078476,
0.049896061420440674,
0.09064158797264099,
-0.06194010376930237,
0.06410481035709381,
0.20840007066726685,
-0.011975160799920559,
0.12260035425424576,
0.07416624575853348,
-0.08735647797584534,
0.05223854258656502,
-0.07405798882246017,
-0.09430453926324844,
-0.08655916899442673,
0.08934324234724045,
-0.06278510391712189,
0.15317323803901672,
0.12562185525894165,
-0.04725475609302521,
0.0027636797167360783,
-0.025733815506100655,
0.054841578006744385,
-0.0038393251597881317,
0.11300427466630936,
0.026762498542666435,
-0.19724777340888977,
0.03347480297088623,
-0.01826278306543827,
0.10099007189273834,
-0.2592698633670807,
-0.08135145157575607,
0.039587851613759995,
-0.009570525959134102,
-0.05378785356879234,
0.11855222284793854,
0.06144152209162712,
0.04968099668622017,
-0.0558135025203228,
-0.05388732627034187,
0.0009833982912823558,
0.1646765172481537,
-0.10682281851768494,
-0.0031281758565455675
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-lora-1.77M-squad-model1
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 67
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "t5-base", "model-index": [{"name": "t5-base-lora-1.77M-squad-model1", "results": []}]} | question-answering | varun-v-rao/t5-base-lora-1.77M-squad-model1 | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"question-answering",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:t5-base",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T02:52:55+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us
|
# t5-base-lora-1.77M-squad-model1
This model is a fine-tuned version of t5-base on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 67
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# t5-base-lora-1.77M-squad-model1\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 67\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us \n",
"# t5-base-lora-1.77M-squad-model1\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 67\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
80,
37,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us \n# t5-base-lora-1.77M-squad-model1\n\nThis model is a fine-tuned version of t5-base on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 67\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.08530748635530472,
0.1453900784254074,
-0.0027867709286510944,
0.09697535634040833,
0.11275944858789444,
0.017081232741475105,
0.11294884234666824,
0.15932400524616241,
-0.10101774334907532,
0.0746476948261261,
0.06123688817024231,
0.047666650265455246,
0.060323331505060196,
0.12312732636928558,
-0.028816500678658485,
-0.2148274928331375,
0.006919967941939831,
-0.018343115225434303,
-0.0653180256485939,
0.10498302429914474,
0.11038815975189209,
-0.08530043065547943,
0.08303094655275345,
-0.016885291785001755,
-0.10695616900920868,
0.05440085753798485,
-0.019475309178233147,
-0.05627257749438286,
0.09911399334669113,
0.013669046573340893,
0.05867670476436615,
0.009302672930061817,
0.13083888590335846,
-0.24376115202903748,
0.0035663170274347067,
0.0899844542145729,
0.007009139750152826,
0.0764152854681015,
0.03816627711057663,
0.0033200145699083805,
0.08897934854030609,
-0.17451411485671997,
0.0971154272556305,
0.0339093953371048,
-0.07373842597007751,
-0.1543528288602829,
-0.10393235087394714,
0.08886633813381195,
0.09634748846292496,
0.09397093206644058,
0.009889524430036545,
0.16860131919384003,
-0.05312857776880264,
0.09340091049671173,
0.21568748354911804,
-0.2909335494041443,
-0.05446247011423111,
0.05851748213171959,
0.05537218227982521,
0.09119343012571335,
-0.09919791668653488,
-0.0017361849313601851,
0.05430377274751663,
0.02083686739206314,
0.10225117206573486,
-0.01647922769188881,
-0.10494738072156906,
0.019469507038593292,
-0.12921187281608582,
-0.03916085138916969,
0.19394205510616302,
0.06014885753393173,
-0.04182472825050354,
-0.08607117831707001,
-0.06407596170902252,
-0.0794268250465393,
0.007336998358368874,
-0.07169242203235626,
0.04564257338643074,
-0.04827134311199188,
-0.05265525355935097,
-0.06873754411935806,
-0.08429897576570511,
-0.07661938667297363,
0.004121963866055012,
0.046553242951631546,
0.05816022679209709,
0.028329387307167053,
-0.04599905386567116,
0.09695930033922195,
-0.02462855912744999,
-0.12602846324443817,
-0.037794943898916245,
0.014537978917360306,
-0.10144732147455215,
-0.0587618313729763,
-0.008497909642755985,
-0.04704884812235832,
0.012391431257128716,
0.16949087381362915,
-0.05697385221719742,
0.04942570999264717,
-0.00609412370249629,
-0.00846723560243845,
-0.023083116859197617,
0.12622645497322083,
-0.056189052760601044,
-0.04624025523662567,
0.01811971142888069,
0.08311262726783752,
0.02703585848212242,
-0.0027430718764662743,
-0.07504155486822128,
-0.030671674758195877,
0.0971488431096077,
0.08018843084573746,
-0.022811222821474075,
0.02924140729010105,
-0.014515544287860394,
-0.021729229018092155,
0.002444636542350054,
-0.14423637092113495,
0.0348629429936409,
-0.02805897407233715,
-0.07336818426847458,
-0.05508286878466606,
0.045360174030065536,
0.0000027793346362159355,
-0.04180923476815224,
0.03292696923017502,
-0.06829389184713364,
-0.019226467236876488,
-0.06518668681383133,
-0.05315946787595749,
0.03986678645014763,
-0.08201771974563599,
-0.010544771328568459,
-0.0675172433257103,
-0.23156695067882538,
-0.024235181510448456,
0.02637937292456627,
-0.06276344507932663,
-0.04188449680805206,
-0.031801220029592514,
-0.06664644926786423,
-0.003225094173103571,
-0.01170259341597557,
0.1055382713675499,
-0.045829303562641144,
0.06789027899503708,
0.013465785421431065,
0.03606119751930237,
0.03628404811024666,
0.030806411057710648,
-0.08691910654306412,
0.03121175616979599,
-0.11539537459611893,
0.05095742642879486,
-0.08638972789049149,
0.027634071186184883,
-0.14108067750930786,
-0.08922238647937775,
0.0008808309212327003,
-0.033560723066329956,
0.05650583282113075,
0.12050116807222366,
-0.17233875393867493,
0.000566564267501235,
0.16827455163002014,
-0.09461155533790588,
-0.12836769223213196,
0.11014986038208008,
-0.04135071486234665,
0.036896150559186935,
0.06521172821521759,
0.1472642421722412,
0.10706104338169098,
-0.1725277304649353,
-0.02327505312860012,
0.007889977656304836,
0.04027821868658066,
0.013178283348679543,
0.07411490380764008,
-0.006175342947244644,
0.04725038260221481,
0.005652462597936392,
-0.08207769691944122,
-0.020841216668486595,
-0.06809378415346146,
-0.09381803870201111,
-0.07504414767026901,
-0.08583993464708328,
0.015270538628101349,
0.03925161063671112,
0.02191399596631527,
-0.07859738916158676,
-0.12371604144573212,
0.07932915538549423,
0.1311483085155487,
-0.04872394725680351,
0.020538408309221268,
-0.08777264505624771,
0.04711425304412842,
-0.04226722940802574,
-0.023876145482063293,
-0.17423060536384583,
-0.11767356097698212,
0.037205323576927185,
-0.04642750322818756,
0.043459415435791016,
0.01659407652914524,
0.06811101734638214,
0.05482322350144386,
-0.06634064018726349,
-0.02252805046737194,
-0.08866141736507416,
0.005920315161347389,
-0.0839567482471466,
-0.19393771886825562,
-0.043702129274606705,
-0.0326286256313324,
0.116739422082901,
-0.21239769458770752,
0.029401831328868866,
0.0246291384100914,
0.1507115662097931,
0.03577077016234398,
-0.039449453353881836,
0.007406551856547594,
0.010854726657271385,
-0.014108151197433472,
-0.09702669084072113,
0.012912796810269356,
-0.011730758473277092,
-0.07689601927995682,
-0.05760054290294647,
-0.12150657176971436,
0.0752548947930336,
0.06867709010839462,
0.08314333111047745,
-0.09085363894701004,
-0.004950936883687973,
-0.05864817276597023,
-0.047868844121694565,
-0.0924518033862114,
-0.0314381867647171,
0.14718185365200043,
0.005852397531270981,
0.11065589636564255,
-0.08198335021734238,
-0.0813983827829361,
-0.0010615987703204155,
0.004328545182943344,
-0.013731918297708035,
0.08164829760789871,
0.04815884307026863,
-0.1255921572446823,
0.10614726692438126,
0.09971088916063309,
-0.03003809228539467,
0.12756291031837463,
-0.07565820962190628,
-0.10340031236410141,
-0.042203232645988464,
0.036347825080156326,
-0.002615983597934246,
0.14280858635902405,
-0.07577819377183914,
0.005997858475893736,
0.02795114368200302,
0.007243284955620766,
0.017401257529854774,
-0.1614202857017517,
-0.012363762594759464,
0.03170134499669075,
-0.06928383558988571,
0.0016366556519642472,
-0.01691526733338833,
0.022313088178634644,
0.09450975805521011,
0.010794198140501976,
-0.014879763126373291,
0.024458657950162888,
-0.014219568111002445,
-0.0983489453792572,
0.17078454792499542,
-0.09887628257274628,
-0.13588815927505493,
-0.11860860139131546,
0.08486413955688477,
-0.044630762189626694,
-0.03824538737535477,
0.025393737480044365,
-0.07743673771619797,
-0.057314224541187286,
-0.11587268114089966,
-0.02750016376376152,
-0.01922227442264557,
-0.011936568655073643,
0.03951678425073624,
0.0370514802634716,
0.08960236608982086,
-0.1410641074180603,
0.020448625087738037,
0.00032057843054644763,
-0.09869848191738129,
-0.02305597811937332,
0.036155566573143005,
0.12017923593521118,
0.09799067676067352,
-0.027807554230093956,
0.0352315828204155,
-0.04460854083299637,
0.2045055329799652,
-0.07015446573495865,
0.023481860756874084,
0.1272733509540558,
0.009328026324510574,
0.055782750248909,
0.1258988380432129,
0.014041079208254814,
-0.08134312927722931,
0.037327829748392105,
0.0765811949968338,
-0.021389126777648926,
-0.27606630325317383,
-0.013746406883001328,
-0.021334746852517128,
-0.0380609892308712,
0.07625693082809448,
0.07173647731542587,
0.05656250938773155,
0.03877634555101395,
-0.02200370468199253,
0.021864933893084526,
-0.0018252760637551546,
0.08585777878761292,
0.08277453482151031,
0.025954673066735268,
0.07882536202669144,
-0.0534137599170208,
-0.029070960357785225,
0.06863709539175034,
0.052661821246147156,
0.26339101791381836,
-0.022670691832900047,
0.1369771957397461,
0.030556585639715195,
0.17154830694198608,
-0.053656432777643204,
0.035185858607292175,
0.005671211052685976,
0.01477317325770855,
0.010197021998465061,
-0.07374563813209534,
0.00879098940640688,
0.06417468190193176,
-0.04885128140449524,
0.053823765367269516,
-0.059572163969278336,
0.06525512784719467,
0.04093514755368233,
0.28284716606140137,
0.03394082188606262,
-0.2664276361465454,
-0.0681305080652237,
0.023621071130037308,
-0.04205816239118576,
-0.03681882098317146,
0.017835654318332672,
0.13413438200950623,
-0.10749661922454834,
0.06366244703531265,
-0.05380956456065178,
0.08893298357725143,
-0.014755711890757084,
-0.01324598677456379,
0.05487198010087013,
0.0927523821592331,
-0.003859251504763961,
0.10073469579219818,
-0.20974844694137573,
0.2183978408575058,
0.027956077829003334,
0.11260595172643661,
-0.07168393582105637,
0.0404999814927578,
0.004801273811608553,
0.07610756903886795,
0.155735582113266,
-0.00941837765276432,
-0.0936717614531517,
-0.13235853612422943,
-0.08635439723730087,
0.030630527064204216,
0.10488806664943695,
-0.03825931251049042,
0.08709754794836044,
-0.051789045333862305,
-0.006746801547706127,
0.0515391044318676,
-0.05061855539679527,
-0.1698600798845291,
-0.1086668148636818,
0.017046160995960236,
-0.0017698873998597264,
-0.05119358375668526,
-0.08961882442235947,
-0.09612132608890533,
-0.03857848793268204,
0.15357252955436707,
-0.03041476383805275,
-0.04683682695031166,
-0.1391247808933258,
0.06433932483196259,
0.12116994708776474,
-0.06949302554130554,
0.01306095439940691,
0.03182018920779228,
0.11559033393859863,
0.041738737374544144,
-0.09176008403301239,
0.050960928201675415,
-0.06131739541888237,
-0.17252086102962494,
-0.05174235999584198,
0.14299602806568146,
0.041046250611543655,
0.04444350674748421,
0.01493463758379221,
0.014971014112234116,
0.024645715951919556,
-0.08345814049243927,
0.01953888311982155,
0.06208067759871483,
0.08312734216451645,
0.04048681631684303,
-0.07946500182151794,
-0.00018834788352251053,
-0.05284908786416054,
-0.030404580757021904,
0.11900122463703156,
0.18816077709197998,
-0.09008299559354782,
0.08464168012142181,
0.05088069662451744,
-0.08689100295305252,
-0.1608574092388153,
0.05801839753985405,
0.06485835462808609,
0.00487499451264739,
0.08390293270349503,
-0.14635269343852997,
0.10361963510513306,
0.09428562223911285,
-0.025516178458929062,
0.027074970304965973,
-0.31662824749946594,
-0.13585776090621948,
0.07133886963129044,
0.11417315900325775,
-0.028249140828847885,
-0.15968626737594604,
-0.04076299071311951,
-0.004450656473636627,
-0.13728563487529755,
0.10199063271284103,
-0.1484135091304779,
0.07788487523794174,
-0.007630475331097841,
0.08392064273357391,
0.02205122634768486,
-0.038264282047748566,
0.12063280493021011,
0.041600942611694336,
0.08928502351045609,
-0.06318022310733795,
0.01776040717959404,
0.12593547999858856,
-0.07708599418401718,
0.10116660594940186,
-0.052684228867292404,
0.08837823569774628,
-0.1524764448404312,
-0.01614305190742016,
-0.05496592074632645,
0.05694275721907616,
-0.062244903296232224,
-0.06306210160255432,
-0.06192650645971298,
0.06244239583611488,
0.06890008598566055,
-0.04727906361222267,
0.09510777145624161,
0.02977112866938114,
0.09981381148099899,
0.13305139541625977,
0.10202842205762863,
0.024525633081793785,
-0.107132688164711,
0.005143808666616678,
-0.024011662229895592,
0.04770773649215698,
-0.1451885998249054,
0.0402640663087368,
0.12466833740472794,
0.04934205487370491,
0.13726000487804413,
0.010784762911498547,
-0.07005023211240768,
-0.015409104526042938,
0.02699888125061989,
-0.11958900094032288,
-0.19674745202064514,
-0.01172634121030569,
-0.04202009364962578,
-0.1447964608669281,
0.045202068984508514,
0.10152604430913925,
-0.06497856974601746,
-0.010246803052723408,
-0.013673066161572933,
0.03677309304475784,
-0.01904859021306038,
0.16500000655651093,
0.06293331831693649,
0.06330255419015884,
-0.06379009783267975,
0.13192956149578094,
0.07724619656801224,
-0.07268603146076202,
0.06548795849084854,
0.07572101056575775,
-0.0788479670882225,
-0.02434685453772545,
0.06846312433481216,
0.15336032211780548,
-0.02661067061126232,
-0.05635712668299675,
-0.10155391693115234,
-0.0722026526927948,
0.04269545525312424,
0.15090546011924744,
0.035973746329545975,
-0.004531252663582563,
-0.007606470491737127,
0.023747680708765984,
-0.1257879137992859,
0.12491555511951447,
0.04825357347726822,
0.06104728579521179,
-0.1549094021320343,
0.07282821089029312,
0.0013345543993636966,
0.047682955861091614,
-0.022927941754460335,
0.0347466841340065,
-0.08143589645624161,
-0.013888014480471611,
-0.12771517038345337,
0.004395888652652502,
-0.029365453869104385,
0.009791147895157337,
-0.005561776924878359,
-0.08430758118629456,
-0.041733916848897934,
0.0659361183643341,
-0.05247609689831734,
-0.05159009248018265,
0.022766774520277977,
0.0658482238650322,
-0.16858696937561035,
-0.026624253019690514,
0.026815805584192276,
-0.08558270335197449,
0.08573814481496811,
0.03514169156551361,
0.01605674810707569,
0.02359900064766407,
-0.10693269968032837,
0.023271990939974785,
0.012009426951408386,
0.03929804265499115,
0.05009850859642029,
-0.11829082667827606,
-0.007357135880738497,
-0.024969322606921196,
0.02279028296470642,
0.02406522072851658,
0.034260060638189316,
-0.11346990615129471,
-0.022087931632995605,
-0.06951899826526642,
-0.046973273158073425,
-0.05281677842140198,
0.047962602227926254,
0.11347027868032455,
0.0039155264385044575,
0.1463339775800705,
-0.07630231976509094,
0.046712666749954224,
-0.2240721434354782,
-0.021797293797135353,
0.01572723500430584,
-0.02334960736334324,
-0.08040180057287216,
-0.02183537185192108,
0.06459417939186096,
-0.07401197403669357,
0.10285983979701996,
-0.01690896786749363,
0.1045004278421402,
0.054541539400815964,
-0.03913740813732147,
0.0005981827853247523,
0.00465507572516799,
0.16260136663913727,
0.025227705016732216,
-0.015718698501586914,
0.07035957276821136,
-0.050700943917036057,
0.048159364610910416,
-0.006272982340306044,
0.15808449685573578,
0.15735210478305817,
-0.02968681789934635,
0.059078559279441833,
0.0955156460404396,
-0.10453164577484131,
-0.12636272609233856,
0.08704283088445663,
-0.009918386116623878,
0.09187926352024078,
-0.04922293871641159,
0.13331389427185059,
0.1431024819612503,
-0.1735789030790329,
0.042130615562200546,
-0.05179476737976074,
-0.10363536328077316,
-0.11541754752397537,
-0.07159237563610077,
-0.08559877425432205,
-0.11819516867399216,
0.029735662043094635,
-0.12693211436271667,
0.0332932211458683,
0.06942783296108246,
0.0158219076693058,
0.0013793442631140351,
0.16036608815193176,
-0.020441213622689247,
0.026123307645320892,
0.04612307995557785,
0.02699723094701767,
0.00361843965947628,
-0.04627841338515282,
-0.030435658991336823,
0.05938053876161575,
0.005866481456905603,
0.05830436199903488,
-0.03652162104845047,
0.03338180482387543,
0.02718595415353775,
-0.01902289316058159,
-0.0609360970556736,
0.015191995538771152,
0.02014869637787342,
0.02247842587530613,
0.06136129051446915,
0.061975568532943726,
0.003430006094276905,
-0.03223569318652153,
0.2658251225948334,
-0.07548054307699203,
-0.07860813289880753,
-0.14174331724643707,
0.14635910093784332,
0.030499139800667763,
-0.013277328573167324,
0.07602758705615997,
-0.13089878857135773,
0.006925188470631838,
0.1530826836824417,
0.12892967462539673,
-0.015765292569994926,
-0.009414388798177242,
-0.0236763097345829,
-0.011924948543310165,
-0.04588698968291283,
0.07239596545696259,
0.09755104035139084,
0.032905463129282,
-0.05091632530093193,
-0.006983250379562378,
0.009562860243022442,
-0.02684105932712555,
-0.06997324526309967,
0.075871542096138,
0.004902207758277655,
0.015355314128100872,
-0.010859581641852856,
0.0847315788269043,
0.013734075240790844,
-0.20402437448501587,
0.048178207129240036,
-0.16199789941310883,
-0.1704254150390625,
-0.009485804475843906,
0.10212536156177521,
-0.025703448802232742,
0.0220886692404747,
-0.00872769020497799,
0.004285566508769989,
0.13228553533554077,
-0.0010918941115960479,
-0.08942512422800064,
-0.09877276420593262,
0.09287328273057938,
-0.09733958542346954,
0.23534217476844788,
-0.005405775737017393,
0.07737987488508224,
0.10793851315975189,
-0.01855231449007988,
-0.15382982790470123,
0.042662762105464935,
0.07841889560222626,
-0.047151029109954834,
0.015255854465067387,
0.15163905918598175,
-0.03724389895796776,
0.11547201126813889,
0.05041833966970444,
-0.08935113251209259,
-0.03287245333194733,
-0.00790014024823904,
-0.009069361723959446,
-0.10893313586711884,
0.01901267282664776,
-0.07069794088602066,
0.16204409301280975,
0.17231722176074982,
-0.05001790076494217,
0.030907345935702324,
-0.0831938236951828,
0.031667474657297134,
0.061181265860795975,
0.0556173250079155,
0.013318208046257496,
-0.17371445894241333,
0.03573370724916458,
0.010205895639955997,
0.029298599809408188,
-0.22512172162532806,
-0.10946111381053925,
0.06286121159791946,
-0.04866650700569153,
-0.06973807513713837,
0.10646510124206543,
0.1178709864616394,
0.04448052495718002,
-0.029673336073756218,
-0.13021934032440186,
-0.04586132615804672,
0.13824330270290375,
-0.16385599970817566,
-0.040376365184783936
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SMIDS_3x_beit_large_SGD_lr001_fold5
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2835
- Accuracy: 0.9033
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5357 | 1.0 | 450 | 0.5366 | 0.79 |
| 0.3977 | 2.0 | 900 | 0.3950 | 0.845 |
| 0.358 | 3.0 | 1350 | 0.3415 | 0.8517 |
| 0.2661 | 4.0 | 1800 | 0.3198 | 0.865 |
| 0.3233 | 5.0 | 2250 | 0.3001 | 0.8733 |
| 0.346 | 6.0 | 2700 | 0.2867 | 0.8867 |
| 0.2205 | 7.0 | 3150 | 0.2820 | 0.885 |
| 0.2571 | 8.0 | 3600 | 0.2769 | 0.8983 |
| 0.3024 | 9.0 | 4050 | 0.2719 | 0.8967 |
| 0.2738 | 10.0 | 4500 | 0.2681 | 0.8967 |
| 0.299 | 11.0 | 4950 | 0.2693 | 0.9017 |
| 0.1694 | 12.0 | 5400 | 0.2623 | 0.8983 |
| 0.2638 | 13.0 | 5850 | 0.2636 | 0.9 |
| 0.2005 | 14.0 | 6300 | 0.2661 | 0.9 |
| 0.2349 | 15.0 | 6750 | 0.2672 | 0.9017 |
| 0.2995 | 16.0 | 7200 | 0.2624 | 0.8967 |
| 0.1968 | 17.0 | 7650 | 0.2699 | 0.8983 |
| 0.2241 | 18.0 | 8100 | 0.2653 | 0.9017 |
| 0.1952 | 19.0 | 8550 | 0.2667 | 0.9033 |
| 0.1522 | 20.0 | 9000 | 0.2648 | 0.9033 |
| 0.2518 | 21.0 | 9450 | 0.2673 | 0.9067 |
| 0.1624 | 22.0 | 9900 | 0.2682 | 0.9067 |
| 0.206 | 23.0 | 10350 | 0.2688 | 0.9033 |
| 0.1813 | 24.0 | 10800 | 0.2711 | 0.9033 |
| 0.1668 | 25.0 | 11250 | 0.2754 | 0.9067 |
| 0.1958 | 26.0 | 11700 | 0.2755 | 0.9067 |
| 0.1062 | 27.0 | 12150 | 0.2709 | 0.9033 |
| 0.1357 | 28.0 | 12600 | 0.2745 | 0.905 |
| 0.1048 | 29.0 | 13050 | 0.2747 | 0.9017 |
| 0.1734 | 30.0 | 13500 | 0.2736 | 0.9067 |
| 0.1554 | 31.0 | 13950 | 0.2773 | 0.9067 |
| 0.1206 | 32.0 | 14400 | 0.2750 | 0.905 |
| 0.1325 | 33.0 | 14850 | 0.2767 | 0.9033 |
| 0.2242 | 34.0 | 15300 | 0.2773 | 0.9083 |
| 0.114 | 35.0 | 15750 | 0.2774 | 0.9083 |
| 0.1279 | 36.0 | 16200 | 0.2790 | 0.905 |
| 0.1132 | 37.0 | 16650 | 0.2811 | 0.9033 |
| 0.1187 | 38.0 | 17100 | 0.2817 | 0.9067 |
| 0.2173 | 39.0 | 17550 | 0.2806 | 0.905 |
| 0.1909 | 40.0 | 18000 | 0.2818 | 0.905 |
| 0.1122 | 41.0 | 18450 | 0.2795 | 0.905 |
| 0.1996 | 42.0 | 18900 | 0.2815 | 0.9033 |
| 0.1429 | 43.0 | 19350 | 0.2813 | 0.9067 |
| 0.1008 | 44.0 | 19800 | 0.2826 | 0.905 |
| 0.1257 | 45.0 | 20250 | 0.2835 | 0.905 |
| 0.0847 | 46.0 | 20700 | 0.2831 | 0.9033 |
| 0.1355 | 47.0 | 21150 | 0.2830 | 0.9033 |
| 0.1508 | 48.0 | 21600 | 0.2839 | 0.9033 |
| 0.1845 | 49.0 | 22050 | 0.2835 | 0.9033 |
| 0.1784 | 50.0 | 22500 | 0.2835 | 0.9033 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_3x_beit_large_SGD_lr001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9033333333333333, "name": "Accuracy"}]}]}]} | image-classification | onizukal/SMIDS_3x_beit_large_SGD_lr001_fold5 | [
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-large-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T02:54:15+00:00 | [] | [] | TAGS
#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| SMIDS\_3x\_beit\_large\_SGD\_lr001\_fold5
=========================================
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2835
* Accuracy: 0.9033
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.2
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
"TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
81,
115,
4,
30
] | [
"passage: TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
-0.1293599158525467,
0.1724882274866104,
-0.0023454553447663784,
0.13587836921215057,
0.11250235140323639,
0.015344180166721344,
0.13944171369075775,
0.16905122995376587,
-0.08231265097856522,
0.04725457355380058,
0.1399839073419571,
0.13659004867076874,
0.046719420701265335,
0.19427457451820374,
-0.05236957222223282,
-0.2601667046546936,
0.04119328409433365,
0.03234807401895523,
-0.02075078710913658,
0.12314869463443756,
0.09301083534955978,
-0.13055187463760376,
0.11641614139080048,
0.030263151973485947,
-0.1994711011648178,
-0.03690062463283539,
-0.00742433313280344,
-0.06729142367839813,
0.10523199290037155,
-0.003170925425365567,
0.06897550076246262,
0.03744976967573166,
0.0835329070687294,
-0.13024620711803436,
0.0019813377875834703,
0.043246712535619736,
0.0064185261726379395,
0.10353662818670273,
0.05471734330058098,
-0.015182994306087494,
0.07030405849218369,
-0.06875743716955185,
0.06702885776758194,
0.009385199286043644,
-0.11313743144273758,
-0.26980340480804443,
-0.10223843902349472,
0.07157823443412781,
0.08217991888523102,
0.068179190158844,
0.008332090452313423,
0.1646922081708908,
-0.015027978457510471,
0.10447341948747635,
0.23090173304080963,
-0.2640359699726105,
-0.055165741592645645,
0.0294360164552927,
0.014914325438439846,
0.06473758071660995,
-0.10603974759578705,
-0.018760167062282562,
0.02059783600270748,
0.044390130788087845,
0.1409236192703247,
-0.010635782033205032,
-0.02811739780008793,
-0.021928580477833748,
-0.10847067832946777,
-0.08875154703855515,
0.18579065799713135,
0.058072153478860855,
-0.04802494868636131,
-0.07736620306968689,
-0.07186304777860641,
-0.17165552079677582,
-0.041741833090782166,
0.009797174483537674,
0.04154014587402344,
-0.04674985632300377,
-0.10634559392929077,
-0.030910290777683258,
-0.07805538177490234,
-0.051461391150951385,
-0.023120464757084846,
0.1351369321346283,
0.03383360058069229,
0.05723920464515686,
-0.03597215935587883,
0.09929350018501282,
0.0073938071727752686,
-0.17543649673461914,
-0.028137801215052605,
-0.0017277015140280128,
0.015125435777008533,
-0.01991228759288788,
-0.030262885615229607,
-0.06523662805557251,
-0.001314454828388989,
0.1489848643541336,
-0.06082969531416893,
0.060913555324077606,
-0.007318461779505014,
0.04020942002534866,
-0.048562191426754,
0.1864238679409027,
-0.02870783396065235,
-0.01659870520234108,
0.0207351166754961,
0.08822518587112427,
0.06836054474115372,
-0.036532942205667496,
-0.12525734305381775,
0.03098621405661106,
0.12811045348644257,
0.0029374780133366585,
-0.021369412541389465,
0.05286439135670662,
-0.0643334686756134,
-0.0587083138525486,
0.09228596836328506,
-0.08908151835203171,
0.034838590770959854,
-0.010374085046350956,
-0.084370456635952,
-0.06779533624649048,
0.027354132384061813,
0.01850878819823265,
-0.0004323708708398044,
0.07165450602769852,
-0.09108522534370422,
0.014963540248572826,
-0.06533985584974289,
-0.10081785917282104,
0.016071073710918427,
-0.1107335016131401,
0.012424856424331665,
-0.09663169085979462,
-0.19710472226142883,
0.006891206838190556,
0.07721206545829773,
-0.05610070005059242,
-0.06814593821763992,
-0.03639180585741997,
-0.07652068138122559,
0.04154945909976959,
-0.011949662119150162,
0.07310567051172256,
-0.0747697651386261,
0.0913747176527977,
0.022405456751585007,
0.08734618872404099,
-0.05631003528833389,
0.0460691936314106,
-0.1024455726146698,
0.04984736442565918,
-0.19827407598495483,
0.0799676924943924,
-0.0493633896112442,
0.0617455318570137,
-0.09557844698429108,
-0.10542625933885574,
0.03370443359017372,
-0.05006959289312363,
0.06861566007137299,
0.0974634513258934,
-0.1729826033115387,
-0.057957619428634644,
0.1353495568037033,
-0.09663163125514984,
-0.14797286689281464,
0.10109983384609222,
-0.050693199038505554,
0.01928282529115677,
0.047161467373371124,
0.21422064304351807,
0.06321150809526443,
-0.09143578261137009,
-0.02580295503139496,
-0.03329068049788475,
0.04440530762076378,
-0.06494591385126114,
0.10175396502017975,
0.027680888772010803,
0.05365157872438431,
0.023984158411622047,
-0.032899804413318634,
0.03856229409575462,
-0.08387355506420135,
-0.10054522752761841,
-0.05070185661315918,
-0.08565592765808105,
0.039397966116666794,
0.05604296177625656,
0.05994046851992607,
-0.10856401175260544,
-0.09017187356948853,
0.04204317927360535,
0.0943065956234932,
-0.07395226508378983,
0.028962817043066025,
-0.09000826627016068,
0.11608705669641495,
-0.08325600624084473,
-0.02390553615987301,
-0.1791052222251892,
-0.04241684824228287,
0.040629271417856216,
-0.01629319041967392,
-0.006912850774824619,
-0.048891667276620865,
0.07074255496263504,
0.08783093094825745,
-0.05235742777585983,
-0.05203414335846901,
-0.05522594600915909,
0.008213330060243607,
-0.1105295866727829,
-0.1776295155286789,
-0.08015653491020203,
-0.0380605012178421,
0.14977632462978363,
-0.15268713235855103,
0.022225622087717056,
0.061116840690374374,
0.12500962615013123,
0.059797611087560654,
-0.04723487049341202,
-0.007436409126967192,
0.021452799439430237,
-0.05571167171001434,
-0.08678608387708664,
0.05719248577952385,
0.03528200834989548,
-0.07155010849237442,
-0.019102152436971664,
-0.10049699991941452,
0.1498662531375885,
0.13190734386444092,
-0.0015375686343759298,
-0.04512632265686989,
-0.01160994078963995,
-0.06610778719186783,
-0.030441991984844208,
-0.04081778973340988,
0.018804829567670822,
0.10142559558153152,
0.01744643971323967,
0.14419154822826385,
-0.09178037941455841,
-0.036961425095796585,
0.053544968366622925,
-0.028453968465328217,
-0.0331195667386055,
0.07361359149217606,
0.02190210297703743,
-0.14263916015625,
0.15015269815921783,
0.14882412552833557,
-0.04894813522696495,
0.12402692437171936,
-0.036747027188539505,
-0.0615357980132103,
-0.044876549392938614,
-0.037704430520534515,
0.014213677495718002,
0.1403394341468811,
-0.08333314955234528,
-0.005919712595641613,
0.05630137771368027,
0.019257593899965286,
-0.007085299585014582,
-0.18072617053985596,
0.0006808378966525197,
0.03521978110074997,
-0.04604950174689293,
-0.02278841845691204,
-0.014470276422798634,
0.0007941273506730795,
0.09172741323709488,
0.019804218783974648,
-0.07102026045322418,
0.05166372284293175,
0.010580740869045258,
-0.05623085796833038,
0.16415521502494812,
-0.07910753041505814,
-0.19727325439453125,
-0.11776646971702576,
-0.08754957467317581,
-0.10735819488763809,
0.013021474704146385,
0.06737184524536133,
-0.050448641180992126,
-0.04938974231481552,
-0.10206248611211777,
-0.04453543201088905,
0.021900271996855736,
0.02429220825433731,
0.05370878055691719,
-0.008031168952584267,
0.08405356109142303,
-0.09224440902471542,
-0.03291117399930954,
-0.014789600856602192,
0.018657125532627106,
0.06682770699262619,
0.018715238198637962,
0.11069032549858093,
0.08161229640245438,
-0.02844928205013275,
0.05646483600139618,
-0.01682325080037117,
0.2655041813850403,
-0.06765957176685333,
-0.006789656355977058,
0.13932959735393524,
-0.013368978165090084,
0.08428963273763657,
0.1268712729215622,
0.04151352122426033,
-0.09555158019065857,
-0.013173693791031837,
-0.00024822441628202796,
-0.05275752767920494,
-0.1537386178970337,
-0.04163756221532822,
-0.045641690492630005,
-0.0021682933438569307,
0.13930507004261017,
0.03818075731396675,
0.02474883571267128,
0.07807637751102448,
0.020041609182953835,
0.05664918199181557,
-0.017527885735034943,
0.10406769812107086,
0.08156019449234009,
0.06448414921760559,
0.13368317484855652,
-0.03653626888990402,
-0.019387291744351387,
0.05662747099995613,
0.04215037450194359,
0.20423758029937744,
-0.02541770040988922,
0.14701254665851593,
0.02641657367348671,
0.19307395815849304,
0.017521383240818977,
0.0728468969464302,
-0.014410126954317093,
0.0009393728105351329,
-0.019274147227406502,
-0.04702805355191231,
-0.06427313387393951,
0.03288881108164787,
-0.016649875789880753,
0.05632343888282776,
-0.09356046468019485,
0.039105307310819626,
0.059592608362436295,
0.30666422843933105,
0.06539998203516006,
-0.4122132360935211,
-0.09836560487747192,
0.012291035614907742,
0.0009865236934274435,
-0.055195607244968414,
-0.0072626820765435696,
0.0979013666510582,
-0.09949664771556854,
0.08215389400720596,
-0.09418605268001556,
0.08514873683452606,
-0.0845724418759346,
0.020298872143030167,
0.07689075917005539,
0.056060366332530975,
0.013226890936493874,
0.05964293330907822,
-0.21821673214435577,
0.24971400201320648,
0.018467964604496956,
0.04422129690647125,
-0.08908867090940475,
0.010060982778668404,
0.033364444971084595,
0.059161990880966187,
0.08554306626319885,
0.005977867171168327,
-0.09024009108543396,
-0.18880225718021393,
-0.1258762925863266,
0.0005427713040262461,
0.06169470399618149,
-0.036699384450912476,
0.09451829642057419,
-0.018175894394516945,
-0.012127134948968887,
0.021332256495952606,
0.0005201056483201683,
-0.03501477465033531,
-0.103630930185318,
0.02024604007601738,
0.034688886255025864,
-0.012138742953538895,
-0.06473075598478317,
-0.11475593596696854,
-0.03554871678352356,
0.16192500293254852,
0.05505121126770973,
-0.07524240761995316,
-0.1408705860376358,
0.07218684256076813,
0.07781627029180527,
-0.0855332687497139,
0.039305757731199265,
-0.016779718920588493,
0.14986851811408997,
0.020937321707606316,
-0.08943228423595428,
0.10178638249635696,
-0.05869165062904358,
-0.17860572040081024,
-0.041185978800058365,
0.09929849207401276,
0.007366738747805357,
0.05263189971446991,
0.004192214459180832,
0.06014186516404152,
-0.035002902150154114,
-0.0584394596517086,
0.06681792438030243,
-0.0073097143322229385,
0.10614755749702454,
-0.014883637428283691,
0.00864378735423088,
0.029195772483944893,
-0.04613848030567169,
0.00009839441918302327,
0.1684505194425583,
0.24079899489879608,
-0.10403203964233398,
0.060546230524778366,
0.03012177161872387,
-0.030879246070981026,
-0.18261685967445374,
0.010319743305444717,
0.07656802982091904,
-0.0001991603203350678,
0.04173794388771057,
-0.16060468554496765,
0.055176541209220886,
0.10514935851097107,
-0.043303944170475006,
0.08152011036872864,
-0.2768779397010803,
-0.11840421706438065,
0.0923023670911789,
0.138164222240448,
0.0691317543387413,
-0.13107311725616455,
-0.04327763617038727,
-0.041234806180000305,
-0.17335952818393707,
0.13665583729743958,
-0.05704028159379959,
0.11501350998878479,
-0.039327461272478104,
0.08051838725805283,
0.014901114627718925,
-0.056082114577293396,
0.14561402797698975,
0.005515002179890871,
0.08661133795976639,
-0.07185279577970505,
-0.0014093852369114757,
0.10643326491117477,
-0.10252601653337479,
0.07192501425743103,
-0.0869532898068428,
0.06187514215707779,
-0.10810889303684235,
-0.0037693935446441174,
-0.07425615191459656,
0.013987713493406773,
-0.013397954404354095,
-0.048907287418842316,
-0.0448833703994751,
0.03488645330071449,
0.06301422417163849,
-0.018155096098780632,
0.20988906919956207,
0.06445588916540146,
0.0862940326333046,
0.1728745847940445,
0.05397673323750496,
-0.10576145350933075,
-0.09408308565616608,
-0.04430058225989342,
-0.029343122616410255,
0.059755485504865646,
-0.13705183565616608,
0.053009506314992905,
0.12004052102565765,
0.013443393632769585,
0.1280696988105774,
0.05582417547702789,
-0.030783196911215782,
0.035687193274497986,
0.06206676363945007,
-0.1721130907535553,
-0.08640376478433609,
-0.010029762983322144,
0.030597826465964317,
-0.13003188371658325,
0.045725177973508835,
0.12137939780950546,
-0.0593545101583004,
-0.014887568540871143,
-0.004342919681221247,
0.03682979568839073,
-0.009421703405678272,
0.15946903824806213,
0.047883741557598114,
0.05509158596396446,
-0.11808934807777405,
0.11348052322864532,
0.057328153401613235,
-0.0728185623884201,
0.032391179352998734,
0.05030714347958565,
-0.10392948985099792,
-0.021465230733156204,
0.031419817358255386,
0.14932547509670258,
-0.06275127828121185,
-0.045640427619218826,
-0.13568063080310822,
-0.091814324259758,
0.06645428389310837,
0.07967224717140198,
0.0933644250035286,
0.01663324609398842,
-0.03539150580763817,
-0.013165266253054142,
-0.10855977237224579,
0.10982618480920792,
0.04324139654636383,
0.09105362743139267,
-0.17992232739925385,
0.054193608462810516,
-0.0015555275604128838,
0.07246194779872894,
-0.021836427971720695,
-0.00042325531831011176,
-0.08788467198610306,
0.003508437890559435,
-0.10813499987125397,
0.02464236691594124,
-0.052905477583408356,
0.006243168842047453,
-0.02064651995897293,
-0.0580705925822258,
-0.06364380568265915,
0.024784497916698456,
-0.11918067932128906,
-0.053243763744831085,
0.02146504819393158,
0.031834639608860016,
-0.12016978859901428,
-0.04392008110880852,
0.020345089957118034,
-0.08986733108758926,
0.09774119406938553,
0.06029992923140526,
-0.008077923208475113,
0.00773270707577467,
0.0036002967972308397,
-0.02274298295378685,
0.0666942149400711,
0.007561622653156519,
0.08597277849912643,
-0.1152612566947937,
-0.0221384409815073,
0.01634843461215496,
-0.004547150805592537,
0.017726117745041847,
0.15840598940849304,
-0.12086156010627747,
-0.0003179961640853435,
-0.014678256586194038,
-0.06600851565599442,
-0.06344839930534363,
0.06893838196992874,
0.10903503000736237,
0.02346671372652054,
0.21181334555149078,
-0.054371658712625504,
0.015811823308467865,
-0.20995409786701202,
-0.011581460013985634,
0.005185890011489391,
-0.1388559192419052,
-0.10497695952653885,
-0.03237957879900932,
0.06376256048679352,
-0.07031478732824326,
0.11765085160732269,
0.03525954857468605,
0.02161695808172226,
0.02906344085931778,
0.025029366835951805,
-0.0031726681627333164,
0.013450034894049168,
0.16309522092342377,
0.014403261244297028,
-0.028442582115530968,
0.12852592766284943,
0.028986822813749313,
0.09334488213062286,
0.11778779327869415,
0.17672526836395264,
0.11388354748487473,
0.04729508236050606,
0.09055530279874802,
0.05202596262097359,
-0.025968270376324654,
-0.22174733877182007,
0.03601896017789841,
-0.03978736698627472,
0.1488790065050125,
-0.0030294209718704224,
0.15902450680732727,
0.0920415073633194,
-0.18360793590545654,
0.040488436818122864,
-0.03700747340917587,
-0.0790853351354599,
-0.08454839885234833,
-0.12155362963676453,
-0.10311590880155563,
-0.15089921653270721,
0.002945262473076582,
-0.1040843203663826,
0.023338600993156433,
0.11202728003263474,
-0.008582104928791523,
-0.009919910691678524,
0.116677425801754,
-0.02631515823304653,
0.026041926816105843,
0.03836518153548241,
0.00608045794069767,
-0.059937771409749985,
-0.044151950627565384,
-0.08065995573997498,
0.014101422391831875,
0.032313644886016846,
0.05599058046936989,
-0.03235676884651184,
-0.007023791316896677,
0.03841041401028633,
-0.010091220960021019,
-0.12353866547346115,
0.01347822230309248,
0.005028906278312206,
0.05164548382163048,
0.0008541525457985699,
0.012780209071934223,
0.03201600909233093,
-0.015217483974993229,
0.19341084361076355,
-0.07325411587953568,
-0.027416478842496872,
-0.1228807121515274,
0.17896701395511627,
0.0026140701957046986,
-0.04994320869445801,
0.05295133590698242,
-0.09137362241744995,
-0.020702529698610306,
0.15485265851020813,
0.1892986297607422,
-0.07158271223306656,
-0.016520513221621513,
-0.017527583986520767,
-0.013897030614316463,
-0.022615507245063782,
0.09919055551290512,
0.0991419330239296,
-0.0069245584309101105,
-0.0751221776008606,
-0.028980256989598274,
-0.06606413424015045,
-0.034512959420681,
-0.03850788250565529,
0.06925404816865921,
-0.004570751916617155,
0.0070457919500768185,
-0.07483471930027008,
0.04310325160622597,
-0.02210995741188526,
-0.06085818260908127,
0.06226903945207596,
-0.21256737411022186,
-0.17790570855140686,
0.006773421075195074,
0.07538973540067673,
0.0015973751433193684,
0.0461571104824543,
-0.009913075715303421,
0.018662674352526665,
0.07594356685876846,
-0.02225665934383869,
-0.08672447502613068,
-0.09593749046325684,
0.10812120139598846,
-0.13375911116600037,
0.2528570294380188,
-0.03883460536599159,
0.03583916276693344,
0.12127543240785599,
0.041867125779390335,
-0.1335451751947403,
0.03351692110300064,
0.03981999680399895,
-0.032485269010066986,
0.00548918079584837,
0.14240407943725586,
-0.03740047290921211,
0.07958021014928818,
0.0458458811044693,
-0.1027912050485611,
-0.03964604437351227,
-0.04966754838824272,
-0.011354409158229828,
-0.024445757269859314,
-0.054610975086688995,
-0.036348532885313034,
0.13227923214435577,
0.17175258696079254,
-0.042096637189388275,
-0.023690558969974518,
-0.06475082784891129,
0.030860183760523796,
0.07729368656873703,
-0.03295742720365524,
-0.052064236253499985,
-0.23603148758411407,
0.0024359924718737602,
0.05229694023728371,
-0.013576737605035305,
-0.20701472461223602,
-0.110505111515522,
0.0060418094508349895,
-0.05801977962255478,
-0.07628542929887772,
0.09231390058994293,
0.06255589425563812,
0.035103797912597656,
-0.06320928037166595,
0.038133736699819565,
-0.07872021943330765,
0.14179112017154694,
-0.14508864283561707,
-0.07859515398740768
] |
null | null | timm | # Model card for resnet18_lensless
| {"license": "apache-2.0", "library_name": "timm", "tags": ["image-classification", "timm"]} | image-classification | inria-chile/resnet18_lensless | [
"timm",
"pytorch",
"image-classification",
"license:apache-2.0",
"region:us"
] | 2024-02-09T03:03:43+00:00 | [] | [] | TAGS
#timm #pytorch #image-classification #license-apache-2.0 #region-us
| # Model card for resnet18_lensless
| [
"# Model card for resnet18_lensless"
] | [
"TAGS\n#timm #pytorch #image-classification #license-apache-2.0 #region-us \n",
"# Model card for resnet18_lensless"
] | [
26,
11
] | [
"passage: TAGS\n#timm #pytorch #image-classification #license-apache-2.0 #region-us \n# Model card for resnet18_lensless"
] | [
-0.09205368906259537,
0.040155280381441116,
-0.005849248729646206,
0.07223878800868988,
0.05248767510056496,
0.07367672771215439,
0.17500345408916473,
0.04238832741975784,
-0.020581860095262527,
-0.11070840060710907,
0.09729684889316559,
0.11751440167427063,
0.04606504738330841,
0.03277139365673065,
0.00486753461882472,
-0.16332252323627472,
0.07220109552145004,
0.013772804290056229,
0.030452309176325798,
0.10738696157932281,
0.039168644696474075,
-0.009576652199029922,
0.07212499529123306,
-0.02844194322824478,
-0.11230786144733429,
0.02126360312104225,
0.06462457776069641,
-0.031067533418536186,
0.04728199914097786,
-0.022687535732984543,
0.07841420918703079,
0.024933526292443275,
0.03986314311623573,
-0.10069452971220016,
0.03908839449286461,
0.07363633066415787,
-0.12846499681472778,
0.026893984526395798,
0.1032974049448967,
-0.030989833176136017,
0.153550386428833,
0.0831410214304924,
-0.040434256196022034,
0.019343359395861626,
-0.014093142934143543,
-0.18022210896015167,
-0.06213449686765671,
0.1589505523443222,
-0.014349839650094509,
0.012737239710986614,
0.06657183170318604,
0.11965975910425186,
-0.10330148041248322,
0.06016911566257477,
0.12314178049564362,
-0.12389751523733139,
-0.04406058415770531,
0.15855193138122559,
-0.06224856898188591,
0.06305793672800064,
0.0005185611080378294,
0.04509977623820305,
0.0556013248860836,
0.01574910804629326,
-0.03664182871580124,
0.012768841348588467,
0.05071736127138138,
-0.027815068140625954,
-0.022900143638253212,
-0.09992725402116776,
0.09908659011125565,
0.07526005804538727,
-0.014821684919297695,
0.025925584137439728,
-0.1116899773478508,
0.08251169323921204,
-0.09010980278253555,
0.13010315597057343,
0.05767673999071121,
0.05704323202371597,
0.03451116383075714,
-0.027045872062444687,
-0.09596538543701172,
-0.07770567387342453,
-0.14374545216560364,
-0.030497629195451736,
0.07499004155397415,
0.20611460506916046,
-0.14789026975631714,
-0.000530088844243437,
0.04111197590827942,
-0.049284543842077255,
0.003990601282566786,
-0.1025770902633667,
0.12245544791221619,
0.1271732896566391,
-0.029137181118130684,
0.06066872924566269,
0.08822115510702133,
0.16756084561347961,
-0.025074636563658714,
0.03195270895957947,
0.009690721519291401,
0.14163565635681152,
-0.05193779990077019,
-0.15501411259174347,
0.018617942929267883,
0.1255798041820526,
0.03271187096834183,
-0.07202088832855225,
0.056997161358594894,
-0.0781487226486206,
-0.05200100690126419,
0.055180538445711136,
-0.012906449846923351,
-0.003295010654255748,
0.03344299644231796,
-0.037264999002218246,
-0.0011508159805089235,
-0.07999900728464127,
0.27750569581985474,
-0.0027456225361675024,
-0.04964403808116913,
-0.028071124106645584,
-0.002238419372588396,
0.15387770533561707,
0.11218468844890594,
-0.1003803163766861,
-0.016535278409719467,
0.039010535925626755,
-0.024207986891269684,
-0.03453758731484413,
-0.02492707595229149,
0.02572394348680973,
0.05802987888455391,
-0.041171588003635406,
0.024491216987371445,
-0.15691785514354706,
-0.18085971474647522,
0.0653628259897232,
0.12866443395614624,
0.011891260743141174,
-0.028007378801703453,
0.10833431035280228,
-0.017110558226704597,
0.0023364657536149025,
0.008009067736566067,
0.025356018915772438,
-0.0361640565097332,
0.07039177417755127,
-0.05648168548941612,
0.09758060425519943,
-0.1846366673707962,
0.01761583238840103,
-0.10209676623344421,
0.006718078628182411,
-0.03940016031265259,
-0.009721045382320881,
-0.11597142368555069,
0.024739183485507965,
-0.008892670273780823,
-0.07244682312011719,
-0.036100324243307114,
0.03524333983659744,
-0.06594773381948471,
-0.007588609121739864,
-0.1581360399723053,
-0.0800611823797226,
0.2132079005241394,
-0.2273193895816803,
-0.09242016077041626,
0.011544971726834774,
0.016925113275647163,
-0.1378519982099533,
-0.019203631207346916,
0.16229330003261566,
0.08989890664815903,
-0.05118687078356743,
0.01237134262919426,
0.05936644226312637,
-0.1319749504327774,
-0.24605053663253784,
0.03853897750377655,
0.08360783755779266,
-0.11673761904239655,
0.036539316177368164,
-0.08392815291881561,
0.028371537104249,
-0.01642555743455887,
-0.12556585669517517,
-0.05810106173157692,
-0.0723860040307045,
-0.0020019575022161007,
0.03205273300409317,
-0.01001828908920288,
-0.039136581122875214,
0.004335806705057621,
-0.054713863879442215,
0.10488654673099518,
0.014835363253951073,
0.026637408882379532,
-0.0780804231762886,
0.17171147465705872,
-0.06273283809423447,
0.01742429845035076,
-0.06726647913455963,
-0.0083489203825593,
-0.048771679401397705,
-0.2018505483865738,
0.07237915694713593,
0.05227719992399216,
0.039208974689245224,
0.017524821683764458,
-0.0796637088060379,
0.005906151607632637,
0.00896026287227869,
-0.011399202980101109,
0.077695831656456,
-0.17524677515029907,
0.03292200714349747,
0.030869873240590096,
0.05429297685623169,
-0.09187395870685577,
-0.02934044785797596,
0.04945141449570656,
0.052803341299295425,
-0.041128113865852356,
0.027911679819226265,
-0.05968431755900383,
-0.08519836515188217,
0.004001590423285961,
-0.040878668427467346,
0.10584884881973267,
0.008607813157141209,
0.07986609637737274,
0.0831105187535286,
-0.02126111462712288,
0.06544111669063568,
0.23226265609264374,
-0.2644989788532257,
-0.00467545073479414,
0.08802597224712372,
-0.015348022803664207,
-0.017514187842607498,
-0.019902696833014488,
0.16385525465011597,
-0.09693454951047897,
-0.055667027831077576,
0.06705576181411743,
-0.07119344174861908,
0.058079302310943604,
0.06269548088312149,
-0.02604367397725582,
-0.019833972677588463,
0.0012767023872584105,
0.2790573537349701,
-0.16109347343444824,
0.08347901701927185,
0.26833003759384155,
-0.03917369619011879,
0.01864214427769184,
-0.0345487967133522,
-0.047897160053253174,
0.05748646333813667,
-0.024500451982021332,
-0.006298907101154327,
0.21475005149841309,
0.0055747078731656075,
-0.009561626240611076,
0.08082184195518494,
-0.06135572865605354,
0.043298251926898956,
-0.14732138812541962,
-0.018737876787781715,
0.03628088906407356,
-0.014659375883638859,
-0.12450006604194641,
0.029216885566711426,
-0.050661928951740265,
0.07019510865211487,
-0.07742815464735031,
-0.14267627894878387,
0.09134311228990555,
-0.02206917479634285,
-0.04793568328022957,
0.10686793923377991,
-0.0338568352162838,
-0.24489617347717285,
-0.036128249019384384,
0.04527944698929787,
-0.07405983656644821,
-0.02414877526462078,
0.05024734511971474,
-0.0773022323846817,
-0.02097442001104355,
-0.0005211227107793093,
-0.23758837580680847,
0.0257277712225914,
0.00023208885977510363,
-0.0735970214009285,
0.0007563589606434107,
0.059751689434051514,
-0.07615986466407776,
-0.03130932152271271,
-0.02384001389145851,
-0.04719484969973564,
0.14335931837558746,
-0.08477695286273956,
0.07797258347272873,
0.08538328856229782,
-0.0725085511803627,
0.03826335445046425,
0.02870342507958412,
0.1122002825140953,
-0.05668612942099571,
0.03553353250026703,
0.17553597688674927,
0.0982852354645729,
0.08338357508182526,
0.0036928129848092794,
0.025830332189798355,
-0.031503669917583466,
-0.07579503953456879,
0.06687171012163162,
-0.1568146049976349,
-0.1559930145740509,
-0.1001642718911171,
-0.03453397378325462,
0.06900029629468918,
0.10840030759572983,
0.11299041658639908,
0.1979343146085739,
0.1575370579957962,
-0.029957232996821404,
-0.009584984742105007,
-0.020267851650714874,
0.04995296150445938,
0.035141997039318085,
0.04073260352015495,
0.0817410871386528,
-0.17136552929878235,
0.054551053792238235,
0.17936426401138306,
0.11277613043785095,
0.21765530109405518,
0.08125627040863037,
-0.10420067608356476,
0.14011266827583313,
0.20466431975364685,
0.1416919231414795,
0.10915420949459076,
-0.0014764433726668358,
0.01265015359967947,
-0.06086187809705734,
-0.026163656264543533,
-0.006488100625574589,
0.0101922070607543,
-0.11040867865085602,
-0.10155464708805084,
0.03639468550682068,
0.01981760747730732,
0.029227079823613167,
0.1374811977148056,
0.031237823888659477,
-0.17988303303718567,
0.07134690880775452,
-0.010545746423304081,
0.05724295601248741,
-0.008805084973573685,
0.11559649556875229,
-0.042033422738313675,
-0.052113573998212814,
0.19326843321323395,
-0.051898758858442307,
0.09399603307247162,
-0.06280063092708588,
-0.00016434644930996,
0.06153090298175812,
-0.09676902741193771,
0.09030687808990479,
0.09108231961727142,
-0.13565590977668762,
0.1598590463399887,
-0.03168302774429321,
-0.0671333447098732,
-0.0983174741268158,
-0.09386803209781647,
0.09819555282592773,
0.08577229082584381,
0.1498471051454544,
0.08434636890888214,
-0.10455016046762466,
0.0702538937330246,
-0.010521892458200455,
0.030354395508766174,
0.01949700526893139,
0.10100273787975311,
-0.12654896080493927,
-0.01489143818616867,
0.009497701190412045,
-0.013522331602871418,
0.018623152747750282,
-0.05104010924696922,
-0.07332436740398407,
0.037689208984375,
0.07447195053100586,
-0.2551100552082062,
-0.06776999682188034,
-0.05953073501586914,
-0.08147216588258743,
0.10693436115980148,
-0.0366225428879261,
-0.06116463989019394,
-0.04130178689956665,
-0.14878559112548828,
0.008072146214544773,
-0.03967434912919998,
0.07695362716913223,
-0.06178626790642738,
0.015039295889437199,
-0.06102021038532257,
-0.24520106613636017,
0.0950012281537056,
-0.09378591924905777,
0.01987488754093647,
0.0028916059527546167,
0.005311205517500639,
-0.09062574803829193,
0.021169845014810562,
-0.014023247174918652,
0.004498718772083521,
-0.08418628573417664,
-0.09214940667152405,
0.10101218521595001,
-0.11321230977773666,
-0.07947427779436111,
0.07021638751029968,
0.12082162499427795,
-0.04756131395697594,
0.05311048403382301,
0.022879708558321,
0.01381127443164587,
0.1488831341266632,
-0.07033886760473251,
0.0963607057929039,
0.17619729042053223,
-0.03271373733878136,
-0.2747422158718109,
-0.11332681775093079,
-0.15864866971969604,
-0.1446865051984787,
0.0164677444845438,
-0.1126420646905899,
0.11289674788713455,
0.09316480904817581,
-0.08650338649749756,
0.19581907987594604,
-0.09538105875253677,
-0.06714729219675064,
0.17561456561088562,
0.13960646092891693,
0.24250856041908264,
-0.14236578345298767,
-0.024829309433698654,
-0.11464405059814453,
-0.08912952989339828,
0.11183987557888031,
-0.14650501310825348,
0.02871866337954998,
-0.025371648371219635,
0.07021491974592209,
-0.09462559223175049,
-0.06423775851726532,
0.11684925109148026,
-0.01405345555394888,
0.11263967305421829,
-0.12274067848920822,
0.036712467670440674,
0.17993122339248657,
0.01584332436323166,
-0.011322911828756332,
-0.10580357909202576,
0.09619700163602829,
-0.0049026114866137505,
0.007965381257236004,
-0.060361020267009735,
-0.018020229414105415,
0.013870214112102985,
-0.017186373472213745,
-0.0407709926366806,
-0.0011616923147812486,
0.00016161563689820468,
0.020481443032622337,
0.038681287318468094,
0.045461490750312805,
-0.006200346164405346,
0.10667970776557922,
-0.037814170122146606,
-0.10421982407569885,
-0.17155639827251434,
-0.18883313238620758,
-0.07841993868350983,
0.12809999287128448,
-0.22590379416942596,
0.029381368309259415,
0.0575219988822937,
0.008550201542675495,
-0.012543137185275555,
0.041554734110832214,
0.012384459376335144,
-0.02395903691649437,
0.12432751804590225,
-0.09868058562278748,
-0.07917222380638123,
0.02735287882387638,
0.12371114641427994,
0.11937586963176727,
0.10367970168590546,
0.028142694383859634,
-0.06621142476797104,
0.019232353195548058,
0.01573934219777584,
0.04903401806950569,
-0.08794776350259781,
0.017141446471214294,
0.145246684551239,
0.019825413823127747,
-0.159038245677948,
0.16445252299308777,
0.000991802429780364,
-0.09346643090248108,
-0.07052838057279587,
0.06124785915017128,
-0.059266939759254456,
-0.12960562109947205,
0.09113569557666779,
0.026359662413597107,
-0.27182984352111816,
-0.14480926096439362,
0.007921944372355938,
-0.08365646004676819,
0.0550561286509037,
0.013812914490699768,
0.11528971046209335,
0.012483267113566399,
0.03929733484983444,
-0.052314288914203644,
0.009281045757234097,
-0.06447066366672516,
-0.05588322877883911,
0.08444062620401382,
-0.14572344720363617,
-0.18851472437381744,
0.06392117589712143,
0.1110399067401886,
-0.07888559252023697,
0.014633302576839924,
0.0023980517871677876,
0.06972813606262207,
-0.22282184660434723,
0.10137920826673508,
0.028189053758978844,
0.04573724791407585,
0.02160446159541607,
-0.0027598512824624777,
-0.01570911519229412,
0.04233402758836746,
-0.09769795835018158,
-0.0029618325643241405,
0.07928343117237091,
0.0019408793887123466,
-0.10273285955190659,
0.014577020891010761,
0.02584652416408062,
0.05621655285358429,
0.02581598609685898,
0.04801920801401138,
-0.07608097046613693,
0.048348043113946915,
-0.10380914807319641,
-0.15915721654891968,
0.056006092578172684,
0.0847485288977623,
-0.07042749971151352,
0.14529919624328613,
0.050397418439388275,
0.09292733669281006,
-0.04535258561372757,
0.017255093902349472,
-0.03698049858212471,
-0.09743352234363556,
-0.0024152479600161314,
-0.15939971804618835,
-0.08787037432193756,
-0.02935684099793434,
-0.028001058846712112,
0.12014374881982803,
0.020127296447753906,
0.08310558646917343,
-0.008501656353473663,
0.009643086232244968,
-0.10860923677682877,
-0.0072731738910079,
-0.020393336191773415,
-0.11479555815458298,
-0.07728306204080582,
0.003982230089604855,
-0.008654954843223095,
-0.07559691369533539,
0.2517906725406647,
0.0013542785309255123,
-0.11674914509057999,
-0.0025637440849095583,
0.18527834117412567,
-0.05604610964655876,
-0.015781357884407043,
0.21537110209465027,
0.05914686992764473,
0.02166488766670227,
0.01685263216495514,
0.0022825838532298803,
0.016714947298169136,
0.007982876151800156,
0.011226887814700603,
0.18366070091724396,
-0.03351566940546036,
0.004885430913418531,
0.1314060091972351,
0.05097923055291176,
-0.0316925011575222,
-0.02496606856584549,
0.0159189123660326,
0.0643819123506546,
0.019534200429916382,
0.04645627737045288,
0.1886477768421173,
0.0016035932349041104,
0.05265626683831215,
0.019997674971818924,
-0.012322049587965012,
-0.10188477486371994,
-0.289469450712204,
-0.07976336777210236,
-0.11824769526720047,
0.04763993248343468,
0.06917313486337662,
-0.054775163531303406,
0.2639976441860199,
0.0645919069647789,
-0.08258865773677826,
0.012643396854400635,
-0.1100398376584053,
0.054362379014492035,
0.049458544701337814,
-0.014564933255314827,
-0.11468422412872314,
0.06631752103567123,
-0.06532905995845795,
0.07167033851146698,
0.041634250432252884,
-0.02284282073378563,
-0.028385749086737633,
0.04611250385642052,
0.10964569449424744,
-0.023704472929239273,
-0.08124209195375443,
-0.05672681704163551,
-0.019086431711912155,
-0.005230075679719448,
0.12592969834804535,
-0.054540012031793594,
0.09799592941999435,
0.03168052062392235,
0.0762908011674881,
-0.05094616487622261,
-0.17180246114730835,
0.018961869180202484,
0.004676098003983498,
-0.1361042559146881,
0.05169122293591499,
0.020022479817271233,
-0.01712578348815441,
-0.02750462479889393,
0.24495676159858704,
0.328960657119751,
-0.08092837035655975,
0.009802303276956081,
0.04961248114705086,
0.015581672079861164,
0.004061675630509853,
0.10362476110458374,
0.015354380011558533,
0.12041755020618439,
-0.054160457104444504,
-0.057214830070734024,
-0.05219515413045883,
-0.010919271036982536,
-0.06347011029720306,
0.030579427257180214,
0.052369292825460434,
-0.0641472190618515,
-0.09710925817489624,
0.06891842186450958,
-0.034506168216466904,
0.1032944917678833,
0.16188572347164154,
0.05434246361255646,
-0.02673751302063465,
-0.036690451204776764,
0.13645046949386597,
0.10847510397434235,
-0.07822439074516296,
-0.1145809069275856,
0.027310334146022797,
-0.02454538084566593,
0.01060981024056673,
-0.3033277094364166,
-0.16629648208618164,
-0.00023093110939953476,
-0.045726027339696884,
0.23620718717575073,
0.016553862020373344,
0.057534974068403244,
0.026589475572109222,
0.03209134563803673,
-0.03802208974957466,
0.06261289864778519,
-0.05535819008946419,
-0.11506953090429306,
-0.001443038578145206,
0.02337615005671978,
-0.06459243595600128,
-0.14430397748947144,
0.052307531237602234,
-0.004133313894271851,
-0.0758199542760849,
0.08126148581504822,
-0.06229908764362335,
-0.0056818085722625256,
0.053054019808769226,
-0.09448029845952988,
0.02253349870443344,
0.02620808407664299,
0.011277095414698124,
-0.07030022889375687,
-0.11008446663618088,
-0.006361660547554493,
0.06367964297533035,
-0.2623732388019562,
0.02940778248012066,
0.122320257127285,
-0.05457819998264313,
-0.17848707735538483,
0.0666855052113533,
-0.06089065596461296,
0.005222576204687357,
-0.10783319920301437,
-0.004696447867900133,
-0.09740327298641205,
0.029279885813593864,
0.11712646484375,
0.026735777035355568,
-0.04737855866551399,
0.06234244629740715,
0.008710384368896484,
0.007831293158233166,
-0.020915837958455086,
-0.07162484526634216
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec_RTSplit0209_1
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-japanese](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-japanese) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0108
- Wer: 0.1863
- Cer: 0.1112
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 5.6863 | 1.0 | 120 | 4.8921 | 1.0 | 0.8906 |
| 1.3062 | 2.0 | 240 | 1.0561 | 0.9970 | 0.6363 |
| 0.8239 | 3.0 | 360 | 0.6832 | 0.8210 | 0.5206 |
| 0.7072 | 4.0 | 480 | 0.6368 | 0.8210 | 0.4940 |
| 0.657 | 5.0 | 600 | 0.5983 | 0.8210 | 0.5058 |
| 0.5694 | 6.0 | 720 | 0.5007 | 0.8013 | 0.4322 |
| 0.5048 | 7.0 | 840 | 0.4137 | 0.7115 | 0.3596 |
| 0.4403 | 8.0 | 960 | 0.3105 | 0.5295 | 0.2739 |
| 0.3738 | 9.0 | 1080 | 0.1929 | 0.4222 | 0.1945 |
| 0.2421 | 10.0 | 1200 | 0.1232 | 0.3094 | 0.1819 |
| 0.2205 | 11.0 | 1320 | 0.0879 | 0.2604 | 0.1439 |
| 0.1691 | 12.0 | 1440 | 0.0408 | 0.2146 | 0.0996 |
| 0.1355 | 13.0 | 1560 | 0.0278 | 0.2004 | 0.0941 |
| 0.1023 | 14.0 | 1680 | 0.0237 | 0.1972 | 0.1117 |
| 0.1152 | 15.0 | 1800 | 0.0191 | 0.1941 | 0.1167 |
| 0.115 | 16.0 | 1920 | 0.0154 | 0.1898 | 0.1229 |
| 0.0798 | 17.0 | 2040 | 0.0135 | 0.1881 | 0.1175 |
| 0.0799 | 18.0 | 2160 | 0.0115 | 0.1870 | 0.1072 |
| 0.0792 | 19.0 | 2280 | 0.0113 | 0.1872 | 0.1101 |
| 0.0869 | 20.0 | 2400 | 0.0108 | 0.1863 | 0.1112 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "jonatasgrosman/wav2vec2-large-xlsr-53-japanese", "model-index": [{"name": "wav2vec_RTSplit0209_1", "results": []}]} | automatic-speech-recognition | tndklab/wav2vec_RTSplit0209_1 | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:jonatasgrosman/wav2vec2-large-xlsr-53-japanese",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-09T03:16:57+00:00 | [] | [] | TAGS
#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-jonatasgrosman/wav2vec2-large-xlsr-53-japanese #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec\_RTSplit0209\_1
=======================
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-japanese on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0108
* Wer: 0.1863
* Cer: 0.1112
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.14.6
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 4\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 1000\n* num\\_epochs: 20",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.6\n* Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-jonatasgrosman/wav2vec2-large-xlsr-53-japanese #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 4\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 1000\n* num\\_epochs: 20",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.6\n* Tokenizers 0.15.0"
] | [
80,
116,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-jonatasgrosman/wav2vec2-large-xlsr-53-japanese #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 4\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 1000\n* num\\_epochs: 20### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.6\n* Tokenizers 0.15.0"
] | [
-0.14125153422355652,
0.15196993947029114,
-0.0005096179665997624,
0.09910103678703308,
0.11762437969446182,
0.008136923424899578,
0.17595644295215607,
0.15003347396850586,
-0.041509028524160385,
0.11163437366485596,
0.11358251422643661,
0.061053063720464706,
0.05535566061735153,
0.19844815135002136,
-0.0821583941578865,
-0.22069455683231354,
0.07650025188922882,
-0.003520418656989932,
0.009394848719239235,
0.11246301978826523,
0.07096446305513382,
-0.11871502548456192,
0.09019626677036285,
-0.007087480276823044,
-0.14438480138778687,
-0.04156386852264404,
0.01643381081521511,
-0.11012612283229828,
0.10884256660938263,
0.010122951120138168,
0.06624047458171844,
0.03506539762020111,
0.08954091370105743,
-0.18697157502174377,
0.002065089764073491,
0.01709642820060253,
0.014176598750054836,
0.0745033249258995,
0.04328455030918121,
-0.0012422389118000865,
0.00437670573592186,
-0.11527440696954727,
0.03663405403494835,
0.01465702522546053,
-0.1166890561580658,
-0.1994403600692749,
-0.07800198346376419,
0.01781792938709259,
0.09923684597015381,
0.08443353325128555,
-0.020961089059710503,
0.12325669825077057,
0.0014254958368837833,
0.07970765978097916,
0.19862909615039825,
-0.31377795338630676,
-0.05488074943423271,
-0.01812855713069439,
0.03781460225582123,
0.08243285864591599,
-0.10096623748540878,
-0.018317921087145805,
0.05009109526872635,
0.02134917862713337,
0.09211244434118271,
-0.03155193105340004,
-0.033802393823862076,
-0.010962148196995258,
-0.12077207863330841,
-0.03909025713801384,
0.19074618816375732,
0.0728745087981224,
-0.06322785466909409,
-0.08110848069190979,
-0.06431447714567184,
-0.12107501924037933,
-0.05483274161815643,
-0.008241765201091766,
0.02698177844285965,
-0.039166659116744995,
-0.09999217092990875,
-0.004302267450839281,
-0.08024033904075623,
-0.0909392237663269,
-0.01783766970038414,
0.17623271048069,
0.010930151678621769,
0.013578737154603004,
-0.012951282784342766,
0.05406586825847626,
-0.02449834905564785,
-0.1848858892917633,
-0.021786607801914215,
0.027511080726981163,
-0.032205864787101746,
-0.014576558955013752,
-0.04426860436797142,
-0.03540217503905296,
0.04405122995376587,
0.11755815893411636,
-0.020655475556850433,
0.06546316295862198,
-0.025179298594594002,
0.0015108666848391294,
-0.08450498431921005,
0.1817910224199295,
-0.06465786695480347,
-0.06891614198684692,
0.019686095416545868,
0.12623198330402374,
0.0630890354514122,
-0.02338474802672863,
-0.0985686182975769,
-0.008597072213888168,
0.14660581946372986,
0.03534100577235222,
-0.04243125393986702,
0.04969576746225357,
-0.03865012153983116,
-0.013795911334455013,
0.056127794086933136,
-0.12151429057121277,
0.025600135326385498,
0.021416792646050453,
-0.0628436803817749,
-0.02213444747030735,
-0.011552567593753338,
0.012529374100267887,
0.012874079868197441,
0.05217357352375984,
-0.08271631598472595,
0.0038196020759642124,
-0.02298075519502163,
-0.09222802519798279,
0.02663276717066765,
-0.06636116653680801,
-0.00009894903632812202,
-0.10773251205682755,
-0.17834560573101044,
-0.017645472660660744,
0.023874744772911072,
-0.049300774931907654,
-0.01028616912662983,
-0.11223874241113663,
-0.09690869599580765,
0.04734962061047554,
-0.022548899054527283,
0.03530019521713257,
-0.07921339571475983,
0.10768070071935654,
0.07966849207878113,
0.08712813258171082,
-0.03981523960828781,
0.02647586725652218,
-0.09469880908727646,
0.032625555992126465,
-0.1757422387599945,
0.07457476854324341,
-0.05392616614699364,
0.03370068222284317,
-0.12032784521579742,
-0.06718988716602325,
0.020194316282868385,
-0.022188080474734306,
0.06995049118995667,
0.14245401322841644,
-0.1904195100069046,
-0.05764715000987053,
0.19828735291957855,
-0.12032623589038849,
-0.1422257125377655,
0.12767471373081207,
-0.036098308861255646,
0.03811813145875931,
0.07031863927841187,
0.2228860855102539,
0.029074236750602722,
-0.10606653988361359,
-0.03957075998187065,
-0.06341684609651566,
0.08373894542455673,
-0.0368381030857563,
0.11153890192508698,
0.0047129117883741856,
-0.0018239254131913185,
0.015954168513417244,
-0.08078019320964813,
0.032347630709409714,
-0.07132356613874435,
-0.1002269983291626,
-0.04445602744817734,
-0.10569128394126892,
0.027701860293745995,
0.015272905118763447,
0.0561961829662323,
-0.0987728163599968,
-0.07059375941753387,
0.012023349292576313,
0.10849296301603317,
-0.11696513742208481,
0.012858877889811993,
-0.10422658175230026,
0.09366480261087418,
-0.11325295269489288,
-0.019966352730989456,
-0.15474918484687805,
-0.0043707131408154964,
0.05357925221323967,
0.01917894370853901,
0.014559420756995678,
-0.0756562352180481,
0.08223055303096771,
0.07709704339504242,
-0.048854369670152664,
-0.07365778833627701,
-0.004984020721167326,
0.018000300973653793,
-0.06257152557373047,
-0.17463570833206177,
-0.028350982815027237,
-0.053802479058504105,
0.16169367730617523,
-0.16553054749965668,
0.0009540295577608049,
0.009854848496615887,
0.09111765772104263,
0.04365720972418785,
-0.022938955575227737,
0.019627349451184273,
0.048140086233615875,
-0.02593155950307846,
-0.07134630531072617,
0.028554461896419525,
0.015161865390837193,
-0.10378418117761612,
0.019476864486932755,
-0.16712172329425812,
0.15066201984882355,
0.1392187476158142,
0.04162779822945595,
-0.053390126675367355,
0.019608836621046066,
-0.014209994114935398,
-0.04226040467619896,
-0.054557181894779205,
-0.01496588159352541,
0.10122998803853989,
0.008508378639817238,
0.12130646407604218,
-0.10252140462398529,
0.01536150835454464,
0.06468397378921509,
-0.027483394369482994,
-0.02868824265897274,
0.08121438324451447,
0.010782327502965927,
-0.1411331295967102,
0.13063719868659973,
0.11258848756551743,
-0.07198533415794373,
0.12639571726322174,
-0.0614188015460968,
-0.08544658124446869,
-0.0505715012550354,
0.03447146713733673,
0.03407841548323631,
0.13749052584171295,
-0.08110443502664566,
-0.02277352288365364,
0.021551011130213737,
0.021524038165807724,
-0.016043122857809067,
-0.1930161714553833,
-0.019647520035505295,
0.014874700456857681,
-0.0945306345820427,
-0.008648199960589409,
0.006200041621923447,
-0.017801737412810326,
0.09444939345121384,
-0.0002227611985290423,
-0.1136024221777916,
0.023740500211715698,
-0.014891540631651878,
-0.0878107026219368,
0.17227071523666382,
-0.09247516095638275,
-0.17502637207508087,
-0.13546505570411682,
-0.0711088553071022,
-0.05636181682348251,
0.037064079195261,
0.060293782502412796,
-0.0658404603600502,
-0.0411604568362236,
-0.11497455835342407,
-0.0476309172809124,
0.03197001293301582,
0.04592474550008774,
0.050641659647226334,
-0.009051329456269741,
0.06650891900062561,
-0.08168910443782806,
-0.005200598388910294,
-0.01415317878127098,
-0.007429053075611591,
0.029025480151176453,
0.0008445620769634843,
0.12627847492694855,
0.1213156208395958,
0.0065246326848864555,
0.02487906813621521,
-0.03746205195784569,
0.22717353701591492,
-0.06961655616760254,
-0.01986483484506607,
0.12328777462244034,
-0.027265748009085655,
0.04553432762622833,
0.1771840900182724,
0.030941173434257507,
-0.10738599300384521,
0.0016122678061947227,
-0.04966747760772705,
-0.015232213772833347,
-0.18889711797237396,
-0.03380108252167702,
-0.04794025421142578,
0.013247009366750717,
0.10157947242259979,
0.029904436320066452,
0.0159853994846344,
0.04765588417649269,
0.02188735455274582,
0.04662126675248146,
0.004234179388731718,
0.08129806071519852,
0.09686854481697083,
0.0761241763830185,
0.10789462178945541,
-0.03187083825469017,
-0.049142494797706604,
0.033232636749744415,
0.019864896312355995,
0.202481210231781,
0.030914682894945145,
0.19326941668987274,
0.0009126043296419084,
0.1547553688287735,
0.026017507538199425,
0.07976194471120834,
0.019675564020872116,
0.00996070634573698,
-0.021061889827251434,
-0.07878586649894714,
-0.05362928286194801,
0.05601036176085472,
-0.014737914316356182,
0.060522112995386124,
-0.10523321479558945,
0.02068718895316124,
0.050251320004463196,
0.27305272221565247,
0.08646926283836365,
-0.3681713938713074,
-0.08654031902551651,
0.02093161642551422,
-0.03737780451774597,
-0.019559089094400406,
0.01657257415354252,
0.15368205308914185,
-0.061814479529857635,
0.06849710643291473,
-0.07176604121923447,
0.0633578822016716,
-0.06497307121753693,
0.019202830269932747,
0.022835852578282356,
0.04778813198208809,
0.0030505124013870955,
0.030672650784254074,
-0.24178652465343475,
0.2874431908130646,
0.03589886054396629,
0.09421420097351074,
-0.0569322295486927,
-0.00357251288369298,
0.039468660950660706,
-0.005897740833461285,
0.11819354444742203,
-0.024643326178193092,
-0.11200551688671112,
-0.17883141338825226,
-0.13464680314064026,
0.04883519187569618,
0.10588953644037247,
-0.0074752564541995525,
0.1153174415230751,
-0.013706614263355732,
-0.04431004449725151,
0.04493009299039841,
-0.022703494876623154,
-0.08027070015668869,
-0.07499056309461594,
0.009748728945851326,
0.11410743743181229,
0.04501901939511299,
-0.05019683763384819,
-0.09624215960502625,
-0.08832626789808273,
0.09084278345108032,
0.002722937148064375,
-0.006283976137638092,
-0.10572609305381775,
0.019583921879529953,
0.1496136337518692,
-0.09170612692832947,
0.05291745439171791,
0.009555297903716564,
0.1114538162946701,
0.02668704092502594,
-0.04957491159439087,
0.09101761132478714,
-0.06227915734052658,
-0.17828553915023804,
-0.050509415566921234,
0.13855043053627014,
-0.006674335338175297,
0.04255940392613411,
0.02045295573771,
0.05173122510313988,
-0.005654301960021257,
-0.06711788475513458,
0.03225403651595116,
0.027320457622408867,
0.040724337100982666,
0.019080648198723793,
-0.01177731528878212,
-0.09052799642086029,
-0.09241806715726852,
-0.0234029870480299,
0.15053130686283112,
0.29826709628105164,
-0.06612488627433777,
0.018267611041665077,
0.08654861897230148,
-0.017332985997200012,
-0.151014044880867,
-0.0044801668263971806,
0.04356582835316658,
0.04462878778576851,
-0.004940017592161894,
-0.12330197542905807,
0.04589373990893364,
0.0616580955684185,
-0.0449066162109375,
0.07601486146450043,
-0.24877819418907166,
-0.1275302916765213,
0.0895995944738388,
0.133384570479393,
0.1245466023683548,
-0.15245915949344635,
-0.06739960610866547,
-0.023983130231499672,
-0.10674285888671875,
0.10438309609889984,
-0.07404301315546036,
0.1326197236776352,
-0.002160007366910577,
0.06533220410346985,
0.007238437887281179,
-0.0509224496781826,
0.1501586139202118,
0.022545842453837395,
0.05333742871880531,
-0.021989990025758743,
-0.016098318621516228,
0.04646014794707298,
-0.0750277042388916,
0.06907732784748077,
-0.08598868548870087,
0.04982045665383339,
-0.05952443182468414,
-0.02498140186071396,
-0.06149646267294884,
-0.005611171014606953,
0.003486855188384652,
-0.03507950156927109,
-0.010422157123684883,
0.03645242005586624,
0.058325234800577164,
0.0034232998732477427,
0.13312268257141113,
0.012208027765154839,
0.08213723450899124,
0.14704978466033936,
0.08823084831237793,
-0.039760831743478775,
0.014484667219221592,
-0.006313697434961796,
-0.056337807327508926,
0.05416826158761978,
-0.13201552629470825,
0.04815923422574997,
0.09654116630554199,
0.018687166273593903,
0.16074210405349731,
0.046562641859054565,
-0.04975597932934761,
0.03745123744010925,
0.06957907974720001,
-0.15992295742034912,
-0.11167877167463303,
0.0030021732673048973,
-0.01186772994697094,
-0.11019180715084076,
0.048999518156051636,
0.13900502026081085,
-0.07014594972133636,
-0.006949229631572962,
-0.017866848036646843,
0.021123474463820457,
-0.0397300161421299,
0.20019923150539398,
0.04152362421154976,
0.05123975872993469,
-0.10993373394012451,
0.08054223656654358,
0.0570816844701767,
-0.08722361922264099,
0.04992043599486351,
0.03850547596812248,
-0.11531060934066772,
-0.02240585908293724,
0.00003842521255137399,
0.14411461353302002,
0.004215383902192116,
-0.07663226127624512,
-0.137697234749794,
-0.0886649563908577,
0.03492627292871475,
0.1777021586894989,
0.06819020211696625,
0.03625902533531189,
-0.018345236778259277,
-0.002072784351184964,
-0.10311992466449738,
0.09386821836233139,
0.07408457249403,
0.07508492469787598,
-0.14941833913326263,
0.08311134576797485,
-0.007839291356503963,
0.026438046246767044,
-0.020600801333785057,
0.016960112378001213,
-0.10999862104654312,
0.005012352950870991,
-0.09816557168960571,
0.05667472630739212,
-0.07845596969127655,
-0.016208991408348083,
-0.0015018136473372579,
-0.08166708797216415,
-0.06176602095365524,
0.01176134031265974,
-0.08715321868658066,
-0.026074524968862534,
0.003415917046368122,
0.043616894632577896,
-0.13680465519428253,
-0.03731467202305794,
0.022870592772960663,
-0.0979870930314064,
0.08365924656391144,
0.0868551954627037,
-0.01907014288008213,
0.047005750238895416,
-0.09452186524868011,
-0.021653279662132263,
0.0823376327753067,
0.0022182571701705456,
0.051462527364492416,
-0.14541393518447876,
-0.014215817674994469,
0.0315285362303257,
0.04986303672194481,
0.021504336968064308,
0.14721673727035522,
-0.09683036059141159,
0.0056404368951916695,
-0.06776165217161179,
-0.011539564467966557,
-0.056822922080755234,
0.021521134302020073,
0.14240053296089172,
0.0030657516326755285,
0.18262432515621185,
-0.09499452263116837,
0.02252662181854248,
-0.1972416639328003,
0.0011507939780130982,
-0.03704344481229782,
-0.12580347061157227,
-0.14708679914474487,
-0.027334922924637794,
0.07801265269517899,
-0.06274133175611496,
0.09577324241399765,
-0.061526812613010406,
0.06918186694383621,
0.013386853970587254,
-0.059092216193675995,
-0.0013609114103019238,
0.04014180600643158,
0.24866798520088196,
0.058431822806596756,
-0.035736922174692154,
0.07698313146829605,
0.010418841615319252,
0.09413561224937439,
0.12436730414628983,
0.12373945862054825,
0.15680478513240814,
0.03193293884396553,
0.14303919672966003,
0.08376245200634003,
-0.025116145610809326,
-0.11938551813364029,
0.059341397136449814,
-0.06797483563423157,
0.08984821289777756,
0.025740332901477814,
0.20986129343509674,
0.09953925013542175,
-0.1640893816947937,
0.004485063720494509,
-0.03601297736167908,
-0.08489023894071579,
-0.09578442573547363,
-0.0612788163125515,
-0.13108332455158234,
-0.14509078860282898,
0.010749326087534428,
-0.10683873295783997,
0.03462059423327446,
0.06881961971521378,
0.014675730839371681,
0.00022742393775843084,
0.14133231341838837,
0.01544282678514719,
0.029067734256386757,
0.09554934501647949,
0.008729403838515282,
-0.04032512754201889,
-0.0013154544867575169,
-0.1037578284740448,
0.02381155453622341,
0.005197292659431696,
0.05644603818655014,
-0.02187400870025158,
-0.025180848315358162,
0.06880489736795425,
-0.025567352771759033,
-0.12494207173585892,
0.011241186410188675,
0.019990084692835808,
0.059927936643362045,
0.04253486171364784,
0.05635620281100273,
-0.017752110958099365,
0.024863488972187042,
0.20689493417739868,
-0.08919373154640198,
-0.07660328596830368,
-0.13318517804145813,
0.14917951822280884,
-0.014670039527118206,
-0.007395995315164328,
0.009302129969000816,
-0.10561878979206085,
0.0014640478184446692,
0.1934189647436142,
0.14886318147182465,
-0.07316035032272339,
-0.000621120969299227,
-0.027442099526524544,
-0.006490211933851242,
-0.038507480174303055,
0.06437768042087555,
0.0785442367196083,
0.035581037402153015,
-0.05986148118972778,
-0.06036505103111267,
-0.058567993342876434,
-0.04111696779727936,
-0.022993089631199837,
0.04017707705497742,
-0.03109791688621044,
-0.022745227441191673,
-0.04977179691195488,
0.0783529058098793,
-0.08197082579135895,
-0.09805622696876526,
0.007538431324064732,
-0.2169453650712967,
-0.17371806502342224,
-0.001783187733963132,
0.07489483058452606,
0.03511296957731247,
0.025993308052420616,
-0.03329768776893616,
0.025347674265503883,
0.05635211989283562,
-0.01332924049347639,
-0.05744485184550285,
-0.06003412976861,
0.04317265748977661,
-0.08277393132448196,
0.17367669939994812,
-0.004546391777694225,
0.06618756055831909,
0.10399951785802841,
0.08164743334054947,
-0.10676847398281097,
0.10381152480840683,
0.061149146407842636,
-0.07399465888738632,
0.05525686964392662,
0.15225888788700104,
-0.05610305443406105,
0.14341101050376892,
0.05205845087766647,
-0.10318749397993088,
0.0005951290368102491,
0.00926982145756483,
-0.02823072113096714,
-0.0751638114452362,
-0.06558346748352051,
-0.04624539613723755,
0.1467822790145874,
0.13456816971302032,
-0.06614606827497482,
0.0016618965892121196,
-0.01697814092040062,
0.05680086091160774,
0.06295444071292877,
0.021999862045049667,
-0.061175309121608734,
-0.2838469445705414,
-0.016154825687408447,
0.03894461691379547,
0.022162849083542824,
-0.2418304830789566,
-0.08981732279062271,
-0.010499806143343449,
-0.0455985851585865,
-0.07411003112792969,
0.09332647919654846,
0.08025132864713669,
0.031043171882629395,
-0.054696954786777496,
-0.0514439195394516,
-0.02890656888484955,
0.17264892160892487,
-0.16266079246997833,
-0.11448425054550171
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# opt-350m-squad-model2
This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 68
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "other", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "facebook/opt-350m", "model-index": [{"name": "opt-350m-squad-model2", "results": []}]} | question-answering | varun-v-rao/opt-350m-squad-model2 | [
"transformers",
"tensorboard",
"safetensors",
"opt",
"question-answering",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:facebook/opt-350m",
"license:other",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:17:11+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #opt #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-facebook/opt-350m #license-other #endpoints_compatible #text-generation-inference #region-us
|
# opt-350m-squad-model2
This model is a fine-tuned version of facebook/opt-350m on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 68
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# opt-350m-squad-model2\n\nThis model is a fine-tuned version of facebook/opt-350m on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 68\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #opt #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-facebook/opt-350m #license-other #endpoints_compatible #text-generation-inference #region-us \n",
"# opt-350m-squad-model2\n\nThis model is a fine-tuned version of facebook/opt-350m on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 68\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
81,
35,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #opt #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-facebook/opt-350m #license-other #endpoints_compatible #text-generation-inference #region-us \n# opt-350m-squad-model2\n\nThis model is a fine-tuned version of facebook/opt-350m on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 68\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.10833881050348282,
0.1310877501964569,
-0.0020622883457690477,
0.08175748586654663,
0.13908374309539795,
0.01016643363982439,
0.09932327270507812,
0.13366274535655975,
-0.05010765418410301,
0.07703894376754761,
0.064348503947258,
-0.001022245967760682,
0.05735015869140625,
0.16227568686008453,
-0.0422452874481678,
-0.18669219315052032,
0.014142254367470741,
-0.02394174598157406,
-0.07933924347162247,
0.0968480184674263,
0.08154818415641785,
-0.09690968692302704,
0.09923488646745682,
-0.014875566586852074,
-0.13137798011302948,
0.05796564742922783,
-0.012420304119586945,
-0.04579576477408409,
0.09122893959283829,
0.03947199508547783,
0.06746651977300644,
0.012245791964232922,
0.12162303924560547,
-0.23373520374298096,
0.009125057607889175,
0.08861053735017776,
-0.0028269237373024225,
0.06485529243946075,
0.03136103227734566,
0.0064702872186899185,
0.10609167069196701,
-0.17760144174098969,
0.09311218559741974,
0.02923782914876938,
-0.08300504833459854,
-0.14767831563949585,
-0.07894758135080338,
0.09016713500022888,
0.09956107288599014,
0.10325650125741959,
-0.005464537069201469,
0.13262377679347992,
-0.055551279336214066,
0.08209528774023056,
0.18870598077774048,
-0.2622639834880829,
-0.06918276101350784,
0.036131467670202255,
0.05455749109387398,
0.07685408741235733,
-0.11508429795503616,
0.016889464110136032,
0.05532200634479523,
0.027747510001063347,
0.0915173590183258,
-0.026953257620334625,
-0.0433463454246521,
-0.014060436747968197,
-0.1305205225944519,
-0.02347269281744957,
0.16598299145698547,
0.078370600938797,
-0.045499857515096664,
-0.10106489062309265,
-0.05565723031759262,
-0.03734079375863075,
-0.008650589734315872,
-0.07036080956459045,
0.03015424869954586,
-0.0481104850769043,
-0.06273511052131653,
-0.07805101573467255,
-0.08211283385753632,
-0.06762900948524475,
0.02544642798602581,
0.04649483039975166,
0.03591339290142059,
0.02857421338558197,
-0.04158652573823929,
0.0805371105670929,
-0.023403508588671684,
-0.12333536148071289,
-0.020185619592666626,
-0.0007155904313549399,
-0.11534261703491211,
-0.06745803356170654,
-0.005381304305046797,
-0.04349689930677414,
0.007073824759572744,
0.1256863921880722,
-0.08099266141653061,
0.06845097243785858,
-0.012178818695247173,
-0.0049683223478496075,
-0.01757705956697464,
0.10731163620948792,
-0.05571939796209335,
-0.06388434022665024,
0.011541955173015594,
0.1102965921163559,
0.006462979596108198,
0.0018219414632767439,
-0.06759218126535416,
-0.02564830146729946,
0.08848001807928085,
0.06382454186677933,
-0.03943725675344467,
0.023402497172355652,
-0.01728501170873642,
-0.017222348600625992,
0.04602906480431557,
-0.11997054517269135,
0.05859958380460739,
-0.006147462874650955,
-0.06795260310173035,
-0.06743364036083221,
0.04828369989991188,
-0.021531203761696815,
-0.020693911239504814,
0.04390718415379524,
-0.06855912506580353,
-0.008886139839887619,
-0.05909954756498337,
-0.05099887773394585,
0.03106890805065632,
-0.03483422473073006,
-0.01555087324231863,
-0.07425884157419205,
-0.21114619076251984,
-0.04018726944923401,
0.01808065176010132,
-0.06453553587198257,
-0.02897377498447895,
-0.030394619330763817,
-0.06115160137414932,
-0.001264182268641889,
-0.018100691959261894,
0.09660520404577255,
-0.046639129519462585,
0.06406385451555252,
0.027013344690203667,
0.035182952880859375,
0.05106738954782486,
0.03544801101088524,
-0.08085328340530396,
0.037873655557632446,
-0.13948237895965576,
0.06654654443264008,
-0.09429334104061127,
0.02037610486149788,
-0.11460598558187485,
-0.09590355306863785,
-0.013625958934426308,
-0.011135414242744446,
0.05508602038025856,
0.14178667962551117,
-0.16356544196605682,
-0.04180888831615448,
0.17322753369808197,
-0.1127583310008049,
-0.11580637097358704,
0.11831597238779068,
-0.04502502828836441,
0.019663726910948753,
0.07474593073129654,
0.1287815421819687,
0.13461893796920776,
-0.17941169440746307,
-0.03641725704073906,
0.005397789645940065,
0.029790500178933144,
-0.0008409072761423886,
0.04545653983950615,
0.008229545317590237,
0.04323875159025192,
0.0019191538449376822,
-0.0674174576997757,
0.005019824020564556,
-0.07403089851140976,
-0.0804269015789032,
-0.05860714241862297,
-0.09049902856349945,
0.027990128844976425,
0.05592561885714531,
0.011068622581660748,
-0.08144277334213257,
-0.10905753821134567,
0.1064186617732048,
0.11775670200586319,
-0.04961949586868286,
-0.0007435991428792477,
-0.07149486988782883,
0.045003216713666916,
-0.0550205372273922,
-0.02205490693449974,
-0.1777789443731308,
-0.1346701681613922,
0.02723510190844536,
-0.06484320759773254,
0.035640303045511246,
0.055100757628679276,
0.07318681478500366,
0.06107112765312195,
-0.07239528745412827,
-0.02769758552312851,
-0.08857833594083786,
-0.001533625298179686,
-0.08870023488998413,
-0.17442335188388824,
-0.04523059353232384,
-0.04309174790978432,
0.1317528635263443,
-0.2603492736816406,
0.033939115703105927,
0.01874842680990696,
0.14451804757118225,
0.027365174144506454,
-0.0387161560356617,
0.0060884072445333,
0.016607603058218956,
0.01962486281991005,
-0.08968210965394974,
0.02657761611044407,
-0.007016101852059364,
-0.0703488439321518,
-0.08572589606046677,
-0.11855160444974899,
0.1053454726934433,
0.06550872325897217,
0.07356052845716476,
-0.10306613147258759,
-0.016097746789455414,
-0.057543445378541946,
-0.04772654175758362,
-0.10741040110588074,
-0.030403543263673782,
0.19364722073078156,
0.026057584211230278,
0.10933739691972733,
-0.07209310680627823,
-0.05616338178515434,
0.008611549623310566,
0.0028495765291154385,
-0.027529733255505562,
0.07540322840213776,
0.05037817358970642,
-0.1613522469997406,
0.10615358501672745,
0.09185250848531723,
0.0020530486945062876,
0.1444617658853531,
-0.04902098700404167,
-0.08741352707147598,
-0.03678623586893082,
0.04171766713261604,
-0.021132009103894234,
0.14447981119155884,
-0.08715109527111053,
-0.006142250262200832,
0.006823285017162561,
-0.000919331272598356,
0.024760834872722626,
-0.1484612226486206,
-0.014055035077035427,
0.021241910755634308,
-0.06831064820289612,
0.017622681334614754,
-0.01178191788494587,
0.04086488112807274,
0.08733765780925751,
0.013115275651216507,
-0.023014012724161148,
0.026873867958784103,
-0.02156464010477066,
-0.09721700847148895,
0.17756474018096924,
-0.08343970775604248,
-0.21305911242961884,
-0.12094887346029282,
0.09893849492073059,
-0.05710182711482048,
-0.03394640237092972,
0.016240883618593216,
-0.0924098938703537,
-0.05433104187250137,
-0.0974060669541359,
-0.004324428737163544,
0.008138996548950672,
-0.019485417753458023,
0.037743303924798965,
0.02582511305809021,
0.11515501141548157,
-0.11492908746004105,
0.01114045549184084,
-0.013598121702671051,
-0.10066331177949905,
-0.03844549134373665,
0.05790112912654877,
0.10348671674728394,
0.06993988156318665,
-0.024153130128979683,
0.02977469004690647,
-0.03151015564799309,
0.2157374918460846,
-0.08160725235939026,
0.02279273234307766,
0.1351289302110672,
0.0176120363175869,
0.053736720234155655,
0.13641007244586945,
0.009959764778614044,
-0.10194911807775497,
0.04068489372730255,
0.08629608899354935,
-0.01212222594767809,
-0.2197725772857666,
-0.03729046881198883,
-0.023218266665935516,
-0.04136458784341812,
0.08737398684024811,
0.06594385951757431,
0.02118326723575592,
0.03112426958978176,
-0.02332107163965702,
-0.0018234597519040108,
-0.0035879325587302446,
0.06742698699235916,
0.08218616247177124,
0.03317538648843765,
0.08714278787374496,
-0.03924481198191643,
-0.03559001907706261,
0.0701741948723793,
-0.009624899365007877,
0.26050856709480286,
-0.01623474806547165,
0.06468973308801651,
0.0315219908952713,
0.1421971619129181,
-0.04131617769598961,
0.015896428376436234,
0.009458833374083042,
-0.015082046389579773,
0.013632495887577534,
-0.05119839310646057,
-0.014205851592123508,
0.04391908645629883,
-0.02679232880473137,
0.05382890626788139,
-0.10705816745758057,
0.06479934602975845,
0.03558124974370003,
0.24511682987213135,
0.05407099798321724,
-0.2566511929035187,
-0.0789247378706932,
0.016006391495466232,
-0.04849829524755478,
-0.05777003616094589,
0.010823325254023075,
0.17951229214668274,
-0.11994312703609467,
0.07838263362646103,
-0.07492769509553909,
0.08264082670211792,
-0.02123858779668808,
0.012674961239099503,
0.0530652217566967,
0.09057438373565674,
-0.008580304682254791,
0.09204820543527603,
-0.18510043621063232,
0.21881873905658722,
0.02599688619375229,
0.11980074644088745,
-0.06095212697982788,
0.03040241450071335,
0.015430915169417858,
0.09991273283958435,
0.1486911177635193,
-0.011314657516777515,
-0.08808760344982147,
-0.1395072489976883,
-0.07433751225471497,
0.03765552118420601,
0.08507782965898514,
-0.030578620731830597,
0.07354268431663513,
-0.035214364528656006,
-0.008403973653912544,
0.04618323966860771,
-0.03016676753759384,
-0.16566428542137146,
-0.112468421459198,
-0.006371976807713509,
-0.009911640547215939,
-0.049962736666202545,
-0.0915345698595047,
-0.09523358941078186,
-0.026133844628930092,
0.18246108293533325,
0.018828481435775757,
-0.04107876494526863,
-0.13580438494682312,
0.10064393281936646,
0.09979280084371567,
-0.07673179358243942,
0.006082095671445131,
0.04319151118397713,
0.13403713703155518,
0.03295382484793663,
-0.08861318975687027,
0.05261741578578949,
-0.06433653086423874,
-0.16479575634002686,
-0.03663042187690735,
0.15820817649364471,
0.07027561962604523,
0.034006595611572266,
0.023457083851099014,
0.0071318489499390125,
0.03668566793203354,
-0.09331853687763214,
0.03066238947212696,
0.03237498179078102,
0.08683351427316666,
0.06021226942539215,
-0.05921291559934616,
-0.02395658567547798,
-0.031184861436486244,
0.0015944610349833965,
0.0980696901679039,
0.22278322279453278,
-0.07673049718141556,
0.06695664674043655,
0.08590824156999588,
-0.08227523416280746,
-0.16924022138118744,
0.0822419598698616,
0.06299059092998505,
0.017577633261680603,
0.08398111909627914,
-0.15863816440105438,
0.10898850858211517,
0.09676800668239594,
-0.023184549063444138,
0.028581881895661354,
-0.28718534111976624,
-0.12559081614017487,
0.0847502201795578,
0.11321821808815002,
0.01732182875275612,
-0.14057840406894684,
-0.034326184540987015,
-0.022718265652656555,
-0.09860218316316605,
0.1056830883026123,
-0.1615871638059616,
0.07917949557304382,
-0.005128016229718924,
0.08042097091674805,
0.022800667211413383,
-0.033032745122909546,
0.11952760070562363,
0.029091356322169304,
0.11446794122457504,
-0.057973701506853104,
0.031455107033252716,
0.10064682364463806,
-0.07203570008277893,
0.08582023531198502,
-0.05739263817667961,
0.06270182132720947,
-0.1455727517604828,
-0.020745590329170227,
-0.08408305794000626,
0.08291755616664886,
-0.06459921598434448,
-0.03770875185728073,
-0.061794575303792953,
0.07991095632314682,
0.04866131767630577,
-0.029325244948267937,
0.050126273185014725,
0.007090473081916571,
0.11846268177032471,
0.13112995028495789,
0.11484694480895996,
0.011545205488801003,
-0.1037163957953453,
0.01038610190153122,
-0.016152366995811462,
0.04814242199063301,
-0.09975984692573547,
0.043789658695459366,
0.12076929211616516,
0.026648500934243202,
0.15953807532787323,
0.0035926615819334984,
-0.06740742921829224,
-0.008513196371495724,
0.03628784045577049,
-0.1222175732254982,
-0.1999734789133072,
-0.020794592797756195,
-0.06455911695957184,
-0.15737566351890564,
0.024905363097786903,
0.10776709020137787,
-0.0610673688352108,
-0.0050210487097501755,
-0.024436119943857193,
0.036295730620622635,
-0.02066301740705967,
0.1655992567539215,
0.05786743760108948,
0.06425189971923828,
-0.07256506383419037,
0.11662939935922623,
0.04726127162575722,
-0.0780353769659996,
0.0703519657254219,
0.07150602340698242,
-0.08021825551986694,
-0.032397735863924026,
0.06714925169944763,
0.21345584094524384,
0.005694035440683365,
-0.052899401634931564,
-0.09540696442127228,
-0.086796335875988,
0.039986684918403625,
0.15231956541538239,
0.03519638255238533,
-0.03216228261590004,
-0.006827701348811388,
0.018695956096053123,
-0.12975206971168518,
0.11345666646957397,
0.04992784932255745,
0.0372701995074749,
-0.1584218591451645,
0.08400869369506836,
0.0003686669806484133,
0.044392652809619904,
-0.031452253460884094,
0.039438359439373016,
-0.09836889803409576,
-0.02456694282591343,
-0.14122918248176575,
-0.013146495446562767,
-0.03269888460636139,
0.003111539874225855,
-0.01669497787952423,
-0.0745796486735344,
-0.0481029637157917,
0.04408353567123413,
-0.056719861924648285,
-0.044193875044584274,
0.03738720342516899,
0.057765182107686996,
-0.18154406547546387,
-0.028490513563156128,
0.021279485896229744,
-0.07666781544685364,
0.07232555001974106,
0.03689335286617279,
0.030845941975712776,
0.025730108842253685,
-0.0870569571852684,
0.007355962879955769,
0.0301425252109766,
0.02896038256585598,
0.05809425935149193,
-0.11082445085048676,
0.011803681030869484,
-0.017917999997735023,
0.026751836761832237,
0.03378579765558243,
0.030321933329105377,
-0.0995888039469719,
-0.01066103670746088,
-0.07190123200416565,
-0.039688218384981155,
-0.04634583741426468,
0.053340982645750046,
0.12142656743526459,
0.02393113635480404,
0.16074980795383453,
-0.1035778820514679,
0.04530693590641022,
-0.23626309633255005,
-0.03515433147549629,
0.021052099764347076,
-0.020930256694555283,
-0.015623335726559162,
-0.03814394399523735,
0.08558646589517593,
-0.05572964623570442,
0.10842695832252502,
-0.0023089656606316566,
0.13146960735321045,
0.05233960226178169,
-0.07914284616708755,
-0.005899257026612759,
0.009424642659723759,
0.10507959127426147,
0.027165867388248444,
-0.022604066878557205,
0.10510528087615967,
-0.0375211127102375,
0.0642184466123581,
0.012499590404331684,
0.19169756770133972,
0.15559302270412445,
-0.04512894153594971,
0.05636938288807869,
0.1022462472319603,
-0.1137225329875946,
-0.10686977952718735,
0.0526215024292469,
-0.04588816314935684,
0.08671959489583969,
-0.056211262941360474,
0.12015388906002045,
0.10880275070667267,
-0.1780143529176712,
0.054300930351018906,
-0.05639742314815521,
-0.1145913153886795,
-0.10617164522409439,
-0.05406265705823898,
-0.08432431519031525,
-0.11636720597743988,
0.03278511390089989,
-0.12261821329593658,
0.005532870069146156,
0.04185083508491516,
0.001163422828540206,
-0.022243821993470192,
0.19257083535194397,
-0.0181589312851429,
0.023894550278782845,
0.07480975240468979,
0.02102339267730713,
0.005254810675978661,
-0.041897330433130264,
-0.022162936627864838,
0.058808986097574234,
0.011292224749922752,
0.05691291019320488,
-0.03751281648874283,
0.006652704440057278,
0.03739624843001366,
-0.006752190180122852,
-0.07380782812833786,
0.011814271099865437,
0.019849402830004692,
0.02504471130669117,
0.05981315299868584,
0.06247668340802193,
0.009847947396337986,
-0.043183691799640656,
0.25101950764656067,
-0.07328920066356659,
-0.04260968044400215,
-0.14098390936851501,
0.1358543485403061,
0.021676912903785706,
0.0009517886210232973,
0.051190704107284546,
-0.1211145892739296,
0.008719679899513721,
0.14746613800525665,
0.12266533821821213,
-0.04997549206018448,
0.007644172292202711,
-0.035357434302568436,
-0.015798084437847137,
-0.03460610285401344,
0.08317878097295761,
0.08432924002408981,
0.01979626901447773,
-0.04581035301089287,
-0.0003142270725220442,
0.008656797930598259,
-0.04750474914908409,
-0.057726211845874786,
0.07145307213068008,
0.018427938222885132,
0.04876284301280975,
-0.02624399960041046,
0.09423527121543884,
0.013937094248831272,
-0.23803775012493134,
0.0488949790596962,
-0.16967351734638214,
-0.1698906123638153,
-0.012160411104559898,
0.06280957907438278,
-0.00685826875269413,
0.041883789002895355,
-0.01199787575751543,
0.010784892365336418,
0.13976313173770905,
-0.01398727297782898,
-0.0650411918759346,
-0.13373947143554688,
0.07707725465297699,
-0.11270497739315033,
0.22258694469928741,
-0.0022251259069889784,
0.040787503123283386,
0.10054327547550201,
-0.032104577869176865,
-0.13865862786769867,
0.034960824996232986,
0.0639863833785057,
-0.047929856926202774,
0.013319450430572033,
0.1688818484544754,
-0.03474559262394905,
0.10754486173391342,
0.05711633339524269,
-0.1050335168838501,
-0.03648533299565315,
-0.08700676262378693,
-0.011197748593986034,
-0.10209903120994568,
0.03145112097263336,
-0.06331411004066467,
0.1582791805267334,
0.18665140867233276,
-0.02980949357151985,
0.02737422101199627,
-0.0684601366519928,
0.040314968675374985,
0.06766850501298904,
0.10472618043422699,
0.0069620972499251366,
-0.19635739922523499,
0.027998972684144974,
0.03628029301762581,
0.03051118552684784,
-0.2509342432022095,
-0.10719756782054901,
0.05663298815488815,
-0.04813719168305397,
-0.049035824835300446,
0.11354466527700424,
0.06285998225212097,
0.046439673751592636,
-0.0314045250415802,
-0.1259668469429016,
-0.047861892729997635,
0.15680623054504395,
-0.15824073553085327,
-0.028601091355085373
] |
null | null | transformers |
# Vision Alignment for google/siglip-base-patch16-384 + mesolitica/malaysian-Qwen1.5-0.5B-16k-instructions
WanDB at https://wandb.ai/huseinzol05/vision-alignment-Qwen1.5-0.5B?workspace=user-huseinzol05 | {"library_name": "transformers", "tags": []} | null | mesolitica/malaysian-Qwen1.5-0.5B-siglip-base-384-vision-alignment | [
"transformers",
"pytorch",
"mm_llms",
"endpoints_compatible",
"region:us"
] | 2024-02-09T03:18:04+00:00 | [] | [] | TAGS
#transformers #pytorch #mm_llms #endpoints_compatible #region-us
|
# Vision Alignment for google/siglip-base-patch16-384 + mesolitica/malaysian-Qwen1.5-0.5B-16k-instructions
WanDB at URL | [
"# Vision Alignment for google/siglip-base-patch16-384 + mesolitica/malaysian-Qwen1.5-0.5B-16k-instructions\n\nWanDB at URL"
] | [
"TAGS\n#transformers #pytorch #mm_llms #endpoints_compatible #region-us \n",
"# Vision Alignment for google/siglip-base-patch16-384 + mesolitica/malaysian-Qwen1.5-0.5B-16k-instructions\n\nWanDB at URL"
] | [
26,
43
] | [
"passage: TAGS\n#transformers #pytorch #mm_llms #endpoints_compatible #region-us \n# Vision Alignment for google/siglip-base-patch16-384 + mesolitica/malaysian-Qwen1.5-0.5B-16k-instructions\n\nWanDB at URL"
] | [
-0.15528854727745056,
-0.08604541420936584,
-0.0032663734164088964,
0.07297763228416443,
0.11419492214918137,
-0.00035292073152959347,
0.08035193383693695,
0.02312692254781723,
0.04806581884622574,
-0.0035476640332490206,
0.042067885398864746,
-0.009622754529118538,
0.02590632252395153,
0.026519574224948883,
0.018977968022227287,
-0.29641738533973694,
-0.03862980380654335,
0.07857752591371536,
-0.12596487998962402,
0.08022896945476532,
0.000047117064241319895,
-0.027452485635876656,
0.12406858801841736,
-0.04196545481681824,
-0.151480570435524,
0.03006010502576828,
-0.07072076201438904,
-0.057105593383312225,
0.09018707275390625,
0.06966954469680786,
0.05363895371556282,
-0.022308072075247765,
-0.022296765819191933,
-0.09295352548360825,
0.027668731287121773,
-0.030893754214048386,
-0.007464042864739895,
-0.008510060608386993,
0.0682605654001236,
0.08345013111829758,
-0.09799143671989441,
-0.031217582523822784,
-0.05631175637245178,
0.015982303768396378,
-0.11328347027301788,
0.05458465963602066,
-0.048038601875305176,
0.10198333114385605,
0.07018404453992844,
0.09425099194049835,
0.0312226340174675,
0.08230271935462952,
-0.038815777748823166,
0.10851439088582993,
0.2343776971101761,
-0.2740394175052643,
-0.01672041416168213,
0.12758682668209076,
-0.06676098704338074,
0.016622696071863174,
-0.025888651609420776,
0.07133349776268005,
0.015406393446028233,
0.04792903736233711,
-0.09755545854568481,
-0.09481624513864517,
-0.07896111160516739,
0.001170822768472135,
-0.02685384638607502,
-0.016497846692800522,
0.22508101165294647,
-0.002478355774655938,
-0.015982726588845253,
0.021705541759729385,
-0.12987911701202393,
-0.03502453863620758,
-0.06437328457832336,
0.0674731507897377,
0.039704084396362305,
0.03426894545555115,
0.0025345608592033386,
-0.13389798998832703,
-0.07476595044136047,
-0.040521152317523956,
-0.24025313556194305,
0.23101550340652466,
0.014592751860618591,
0.060056280344724655,
-0.13811731338500977,
0.0957392230629921,
0.046208348125219345,
-0.13143159449100494,
-0.04339531064033508,
-0.021750567480921745,
-0.01238251756876707,
0.0873941108584404,
-0.02795133925974369,
0.026386568322777748,
0.025305237621068954,
0.047346923500299454,
0.020326649770140648,
0.07782164961099625,
-0.02921323850750923,
0.1067173033952713,
-0.12143738567829132,
0.19213753938674927,
-0.13714520633220673,
0.047019027173519135,
0.12898023426532745,
-0.06335344910621643,
0.12549681961536407,
-0.008371970616281033,
-0.030782418325543404,
-0.13432396948337555,
-0.04608936980366707,
0.03512949496507645,
-0.0005134748062118888,
0.0934099555015564,
-0.06186062842607498,
-0.07186684012413025,
0.0811130478978157,
-0.11889917403459549,
-0.021257728338241577,
-0.044741615653038025,
-0.061588261276483536,
0.014034938998520374,
0.15909437835216522,
-0.013540145009756088,
-0.07087959349155426,
0.02466050162911415,
-0.009562204591929913,
0.09105744957923889,
-0.015429305844008923,
0.02159982919692993,
0.05317302793264389,
0.008801257237792015,
0.012439602054655552,
-0.16297589242458344,
-0.24847668409347534,
0.011932635679841042,
0.02084345556795597,
-0.036717258393764496,
-0.004125023726373911,
0.03489113971590996,
-0.04716716706752777,
-0.026284849271178246,
-0.028490854427218437,
0.04766155406832695,
0.0058445618487894535,
0.05707491934299469,
0.17158523201942444,
0.11208643764257431,
-0.11570769548416138,
0.057402413338422775,
-0.07551813125610352,
0.07809700816869736,
-0.22395126521587372,
0.17418722808361053,
-0.06790269911289215,
0.10995946824550629,
0.03285807743668556,
0.01149106863886118,
-0.13837279379367828,
0.0019306879257783294,
0.08426113426685333,
0.16333718597888947,
-0.1278805434703827,
-0.042134642601013184,
0.03887731581926346,
-0.09881692379713058,
-0.18031494319438934,
0.09664274007081985,
0.06938285380601883,
-0.02159450389444828,
0.0223043505102396,
0.1648588329553604,
0.14650210738182068,
-0.026258151978254318,
-0.014324383810162544,
0.038577303290367126,
-0.12248469144105911,
-0.22881661355495453,
-0.026297861710190773,
0.09110835194587708,
-0.03555241599678993,
0.05918951705098152,
-0.03260282799601555,
0.13429191708564758,
-0.03611338138580322,
-0.05074096471071243,
-0.08638375997543335,
-0.022034188732504845,
-0.06368082016706467,
0.0018936587730422616,
0.10534165799617767,
-0.07644470781087875,
0.07545793801546097,
-0.030530855059623718,
0.004738989751785994,
-0.019588036462664604,
0.07753893733024597,
-0.04953315109014511,
0.0023208169732242823,
-0.14837577939033508,
0.048065003007650375,
-0.13745784759521484,
-0.13039852678775787,
0.013314099982380867,
-0.03809961676597595,
0.07633322477340698,
-0.08960602432489395,
0.07342316955327988,
0.02281612530350685,
-0.06472387164831161,
-0.07318528741598129,
0.01153448037803173,
-0.022658726200461388,
-0.05466780439019203,
0.003637246787548065,
0.0661560446023941,
-0.0009788377210497856,
-0.058120597153902054,
0.037815749645233154,
0.020875295624136925,
0.10604774206876755,
0.12400335818529129,
-0.006528210826218128,
0.0507596880197525,
0.10425516217947006,
0.07411955296993256,
0.08652699738740921,
-0.06301546841859818,
0.09666062891483307,
0.010789696127176285,
-0.00011440637172199786,
0.2067696452140808,
-0.042865365743637085,
0.26772376894950867,
0.1830868422985077,
-0.29010501503944397,
0.0921696126461029,
0.035121455788612366,
-0.0005021424149163067,
-0.08317621797323227,
0.03737599030137062,
0.06291694939136505,
0.1337539404630661,
-0.027841391041874886,
0.1349237859249115,
-0.03458908945322037,
-0.02769503928720951,
0.02123209461569786,
-0.052328333258628845,
-0.08931612968444824,
0.05907251313328743,
0.044489990919828415,
-0.1264297068119049,
0.10028984397649765,
0.05790602043271065,
0.016390807926654816,
0.06291281431913376,
-0.03558693081140518,
0.033643610775470734,
-0.00873193982988596,
0.04073919728398323,
-0.05293916538357735,
0.1379508674144745,
-0.18878623843193054,
-0.058247290551662445,
0.004866164643317461,
0.010730776935815811,
0.16652590036392212,
-0.1796942502260208,
-0.014136292971670628,
-0.028393536806106567,
-0.040497735142707825,
-0.052842866629362106,
0.04583694413304329,
-0.027446087449789047,
0.03190317377448082,
-0.03043954260647297,
0.06406291574239731,
0.062170252203941345,
0.004986215848475695,
-0.07617918401956558,
0.0880744457244873,
-0.0636848658323288,
-0.29501858353614807,
-0.19945521652698517,
-0.07614679634571075,
-0.11481548845767975,
-0.009359563700854778,
0.03280448913574219,
-0.06842820346355438,
-0.006704735103994608,
0.028898034244775772,
0.024224888533353806,
0.028458481654524803,
0.02837984822690487,
0.050258975476026535,
-0.01904037781059742,
0.006172988563776016,
-0.07591261714696884,
-0.049303602427244186,
-0.02656211517751217,
0.09598390012979507,
0.08499614149332047,
-0.11305117607116699,
0.12816470861434937,
0.005554432049393654,
-0.016655374318361282,
0.05586433410644531,
0.011637385934591293,
0.1993069052696228,
-0.0704207643866539,
-0.00016515303286723793,
0.18675948679447174,
0.030815385282039642,
0.00782129168510437,
0.07117389142513275,
0.011402061209082603,
-0.13126181066036224,
-0.016505254432559013,
0.006796281784772873,
-0.08308815956115723,
-0.1429506242275238,
-0.05579567700624466,
-0.14720985293388367,
0.016904817894101143,
-0.0568215437233448,
0.03547681123018265,
-0.04781956225633621,
0.06904760003089905,
-0.019723128527402878,
0.1385893076658249,
-0.08925759792327881,
0.02308483235538006,
0.32197433710098267,
-0.009640008211135864,
0.027616895735263824,
-0.15040968358516693,
-0.006834439001977444,
0.029958529397845268,
0.14072881639003754,
0.1409117579460144,
-0.02440333552658558,
-0.017145242542028427,
0.016247808933258057,
0.10624091327190399,
0.15576927363872528,
0.05618910491466522,
-0.03076164983212948,
-0.027609113603830338,
0.02567482367157936,
-0.03362460806965828,
-0.09980237483978271,
-0.034691981971263885,
-0.014989763498306274,
-0.006344105117022991,
0.014861037954688072,
-0.01144643034785986,
0.03059876523911953,
0.19718579947948456,
-0.0031058217864483595,
-0.16199961304664612,
-0.040812402963638306,
0.03406750038266182,
0.08252447843551636,
-0.013737683184444904,
0.04193665832281113,
0.06805810332298279,
-0.047919608652591705,
0.09131453931331635,
-0.07735598832368851,
0.09633302688598633,
-0.11633113771677017,
0.0005796396289952099,
0.028435779735445976,
-0.05237883701920509,
0.02542165294289589,
0.015046492218971252,
-0.22652556002140045,
0.19625377655029297,
0.056370511651039124,
0.035181622952222824,
0.017331579700112343,
-0.0033266814425587654,
0.07959742844104767,
0.11313997209072113,
0.00770903192460537,
0.05441545322537422,
0.16190724074840546,
-0.10580697655677795,
-0.05022084712982178,
0.0723896324634552,
0.11426781862974167,
0.07802966237068176,
0.04059308022260666,
0.05308012291789055,
-0.01916169561445713,
-0.03646215423941612,
0.06791772693395615,
-0.054289810359478,
-0.0915420725941658,
0.024597596377134323,
0.05177793651819229,
0.0227603018283844,
-0.048233866691589355,
-0.022523444145917892,
-0.12276040762662888,
0.09147165715694427,
-0.07573345303535461,
-0.08009403944015503,
-0.07680610567331314,
0.0006619375199079514,
0.06829250603914261,
-0.09991836547851562,
0.028799017891287804,
-0.028187232092022896,
-0.13364115357398987,
0.006338649895042181,
-0.1599239856004715,
0.09330640733242035,
-0.09519702196121216,
0.025069091469049454,
0.031106187030673027,
0.18736238777637482,
-0.13514119386672974,
-0.025525324046611786,
-0.05981052666902542,
-0.025604724884033203,
-0.0007667796453461051,
-0.12542611360549927,
0.11064154654741287,
-0.0015326864086091518,
-0.01244487427175045,
0.15291938185691833,
-0.004051517229527235,
0.08921980857849121,
-0.020954450592398643,
-0.020983750000596046,
0.08191585540771484,
0.07441772520542145,
0.0510491244494915,
-0.01879975013434887,
0.13058574497699738,
-0.007288314867764711,
-0.18651767075061798,
0.008455327711999416,
-0.04398655518889427,
0.05385437235236168,
-0.14572536945343018,
-0.09783599525690079,
0.09193545579910278,
0.009111934341490269,
-0.004615870304405689,
0.07614482939243317,
-0.1771983504295349,
-0.1040782630443573,
0.014480244368314743,
0.07622405141592026,
0.25414344668388367,
-0.0795125737786293,
-0.09854783117771149,
0.012741418555378914,
-0.2808643877506256,
-0.018994508311152458,
0.09474126249551773,
0.17188791930675507,
-0.08049894124269485,
0.07301201671361923,
-0.012224527075886726,
-0.059104371815919876,
0.14054138958454132,
-0.05120187625288963,
0.06021235138177872,
-0.04587360844016075,
-0.06758618354797363,
0.0866166427731514,
0.006506856065243483,
0.0851660668849945,
0.1893828958272934,
0.09626130014657974,
-0.05778846889734268,
-0.02562907710671425,
-0.042083438485860825,
-0.017712289467453957,
0.05186283588409424,
0.012478466145694256,
-0.010427932254970074,
-0.028687741607427597,
-0.08568982034921646,
-0.014248586259782314,
0.027176138013601303,
0.04161838814616203,
-0.17888124287128448,
0.02944427914917469,
-0.018489310517907143,
-0.15794727206230164,
-0.14275574684143066,
-0.0800495445728302,
-0.03235890716314316,
0.07725919783115387,
-0.1006162241101265,
0.03324085846543312,
0.09492100030183792,
0.020464787259697914,
-0.007592757232487202,
0.07511050254106522,
-0.04150894656777382,
0.06531256437301636,
0.07421999424695969,
-0.08527906984090805,
-0.14356544613838196,
-0.10198322683572769,
-0.17268982529640198,
0.15154887735843658,
0.1263464242219925,
0.11230560392141342,
-0.07094621658325195,
0.024986300617456436,
0.0018990235403180122,
-0.026260631158947945,
-0.07745480537414551,
0.17356301844120026,
0.06875497847795486,
0.015365112572908401,
-0.14900849759578705,
0.19437627494335175,
-0.05218614265322685,
-0.10596076399087906,
-0.055415838956832886,
0.19612464308738708,
-0.12412218749523163,
-0.03500968590378761,
-0.10608478635549545,
0.10838799923658371,
-0.020682837814092636,
-0.06489671766757965,
-0.11132488399744034,
-0.07361526042222977,
0.08597445487976074,
0.1239805743098259,
0.08213718980550766,
0.01811695471405983,
-0.06389274448156357,
0.009716982953250408,
0.03421948850154877,
0.02699151448905468,
0.033053383231163025,
0.14679479598999023,
-0.1876940131187439,
-0.05453164130449295,
0.035167086869478226,
0.1960637867450714,
-0.059662386775016785,
-0.06789933890104294,
-0.10013435781002045,
0.041880711913108826,
-0.14203549921512604,
-0.022414475679397583,
-0.03491392359137535,
0.0049222251400351524,
-0.056698668748140335,
-0.109517902135849,
-0.10358504951000214,
0.05320749059319496,
-0.020358312875032425,
-0.06012243032455444,
-0.02480820193886757,
-0.0002359654026804492,
-0.053326986730098724,
-0.06090549752116203,
0.08561760187149048,
-0.017128657549619675,
0.06109389290213585,
0.16458235681056976,
-0.0640757828950882,
0.019404781982302666,
-0.020526785403490067,
-0.17998094856739044,
0.1469709426164627,
0.042146362364292145,
0.001616907655261457,
-0.008707087486982346,
0.05066618695855141,
0.017595207318663597,
0.07253984361886978,
0.017415650188922882,
0.30271655321121216,
-0.08480588346719742,
-0.0784006416797638,
-0.17065931856632233,
-0.029267432168126106,
-0.09370122104883194,
0.0010456537129357457,
0.10178417712450027,
0.1169205754995346,
0.010127672925591469,
-0.06950384378433228,
0.012089683674275875,
-0.10896392911672592,
-0.022542737424373627,
-0.029986120760440826,
-0.15570688247680664,
0.09307147562503815,
-0.06402043998241425,
0.0548022985458374,
-0.026114730164408684,
0.14133040606975555,
-0.03980299085378647,
-0.04139672592282295,
0.0017744720680639148,
0.08678659796714783,
-0.06636026501655579,
0.0009930158266797662,
0.19863881170749664,
0.054494552314281464,
0.017377546057105064,
0.09293410927057266,
0.16290193796157837,
0.06278406083583832,
0.1112687885761261,
-0.03498511016368866,
0.10427265614271164,
-0.0805690661072731,
0.1743854433298111,
0.12519603967666626,
0.001885371282696724,
-0.13480818271636963,
-0.16335351765155792,
-0.06800208985805511,
-0.0081985117867589,
-0.07434558123350143,
-0.11137881129980087,
0.1737462729215622,
-0.015570983290672302,
0.09422590583562851,
0.048041559755802155,
-0.05146114155650139,
-0.027474330738186836,
-0.13134951889514923,
-0.06742864847183228,
-0.07792248576879501,
0.011496179737150669,
-0.02214343287050724,
-0.05437566339969635,
0.20173844695091248,
0.0001430715637980029,
-0.014802904799580574,
0.25441649556159973,
-0.0567639097571373,
-0.06613526493310928,
0.03546394035220146,
-0.003628616454079747,
-0.0170049499720335,
0.051442358642816544,
0.030473140999674797,
-0.0012881061993539333,
-0.020474255084991455,
-0.013373768888413906,
0.05512818321585655,
-0.043921735137701035,
0.0391545295715332,
-0.05289892852306366,
-0.06056628003716469,
-0.07361622899770737,
0.05662575736641884,
0.02757645957171917,
0.03321587294340134,
0.019565919414162636,
-0.023021137341856956,
0.01842430979013443,
0.21960130333900452,
-0.10097533464431763,
-0.14428222179412842,
-0.02426944114267826,
-0.08903376758098602,
-0.0018806760199368,
0.05358535051345825,
-0.050501808524131775,
-0.05365286394953728,
-0.027480173856019974,
0.23626601696014404,
0.1883852481842041,
-0.13797393441200256,
0.0066426959820091724,
0.06758620589971542,
0.028783274814486504,
0.06035469099879265,
0.09719208627939224,
0.1610788255929947,
0.27286309003829956,
-0.041498929262161255,
-0.08473251760005951,
-0.06394360214471817,
-0.07269527018070221,
-0.07083363085985184,
0.07995889335870743,
0.05032551661133766,
-0.03500741720199585,
-0.12758603692054749,
0.0851428210735321,
-0.00868026539683342,
0.16413642466068268,
0.12885840237140656,
-0.16761571168899536,
-0.09330011904239655,
-0.022826876491308212,
0.008478591218590736,
0.0415789820253849,
0.007727408315986395,
-0.057997506111860275,
0.031130803748965263,
-0.015997983515262604,
0.06087828427553177,
-0.2508156895637512,
0.010348218493163586,
-0.0089009590446949,
0.025676948949694633,
-0.0267651230096817,
-0.03039243444800377,
0.09418386965990067,
0.04695994034409523,
0.06842133402824402,
-0.10325750708580017,
0.10125165432691574,
-0.0820523351430893,
-0.1258787214756012,
-0.01571580395102501,
0.03612327203154564,
0.016648586839437485,
-0.15208466351032257,
0.022767644375562668,
0.02580515667796135,
0.00801924616098404,
0.13399921357631683,
0.01224564854055643,
-0.07221630960702896,
-0.02658582292497158,
-0.10411552339792252,
0.06350229680538177,
0.011934570968151093,
0.008031736128032207,
0.005019105039536953,
-0.056735314428806305,
-0.007821167819201946,
0.036218758672475815,
-0.04066450893878937,
-0.03131510689854622,
-0.05857356637716293,
-0.11080104112625122,
-0.00924879964441061,
-0.031541403383016586,
-0.04114989563822746,
-0.08581259101629257,
-0.06746388971805573,
-0.0280930045992136,
-0.003453292651101947,
0.08483445644378662,
0.09143344312906265,
0.03240780159831047,
-0.013983390294015408,
-0.2321629673242569,
0.0305414330214262,
0.08069879561662674,
-0.12531106173992157,
-0.1229507252573967
] |
null | null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral-finetuned-specific-broad
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 250
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "model-index": [{"name": "mistral-finetuned-specific-broad", "results": []}]} | null | amaresh07877/mistral-finetuned-specific-broad | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ",
"license:apache-2.0",
"region:us"
] | 2024-02-09T03:18:18+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.1-GPTQ #license-apache-2.0 #region-us
|
# mistral-finetuned-specific-broad
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 250
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 | [
"# mistral-finetuned-specific-broad\n\nThis model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0002\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: cosine\n- training_steps: 250\n- mixed_precision_training: Native AMP",
"### Training results",
"### Framework versions\n\n- PEFT 0.8.2\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.1"
] | [
"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.1-GPTQ #license-apache-2.0 #region-us \n",
"# mistral-finetuned-specific-broad\n\nThis model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0002\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: cosine\n- training_steps: 250\n- mixed_precision_training: Native AMP",
"### Training results",
"### Framework versions\n\n- PEFT 0.8.2\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.1"
] | [
62,
47,
6,
12,
8,
3,
102,
4,
44
] | [
"passage: TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.1-GPTQ #license-apache-2.0 #region-us \n# mistral-finetuned-specific-broad\n\nThis model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0002\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: cosine\n- training_steps: 250\n- mixed_precision_training: Native AMP### Training results### Framework versions\n\n- PEFT 0.8.2\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0+cu121\n- Datasets 2.16.1\n- Tokenizers 0.15.1"
] | [
-0.11118513345718384,
0.09646748006343842,
-0.0032973007764667273,
0.0825679823756218,
0.10526523739099503,
0.03379175439476967,
0.10111929476261139,
0.1439255028963089,
-0.06236906349658966,
0.08492370694875717,
0.06271184235811234,
0.011651677079498768,
0.08167373389005661,
0.1810065060853958,
-0.01583678647875786,
-0.21506743133068085,
0.029325254261493683,
-0.03475206345319748,
-0.022210264578461647,
0.10599412024021149,
0.10726947337388992,
-0.10534530878067017,
0.046931084245443344,
-0.012358731590211391,
-0.14628097414970398,
-0.023012487217783928,
-0.023189734667539597,
-0.03569959104061127,
0.09644200652837753,
0.008331647142767906,
0.13282589614391327,
0.04198084771633148,
0.15021267533302307,
-0.22001104056835175,
0.00417829817160964,
0.07774598151445389,
0.049924079328775406,
0.09332624822854996,
0.05622342228889465,
0.01606009528040886,
0.022888267412781715,
-0.14882366359233856,
0.10652164369821548,
0.01615518517792225,
-0.096396304666996,
-0.11055031418800354,
-0.13494643568992615,
0.10896789282560349,
0.09920400381088257,
0.09657467901706696,
0.01603267528116703,
0.138518825173378,
-0.07939063012599945,
0.055970799177885056,
0.1996021717786789,
-0.22975559532642365,
-0.07029221951961517,
0.057067617774009705,
0.06487146019935608,
0.08816792815923691,
-0.11513391882181168,
-0.03381709009408951,
0.032318517565727234,
0.027988463640213013,
0.08761712163686752,
-0.009845870546996593,
-0.0937943309545517,
-0.016496755182743073,
-0.12426358461380005,
-0.05430108308792114,
0.1226617842912674,
0.031829435378313065,
-0.052957966923713684,
-0.08926088362932205,
-0.03308418393135071,
-0.14490751922130585,
-0.019612697884440422,
-0.05176074802875519,
0.03338395804166794,
-0.031692877411842346,
-0.0032027936540544033,
-0.06802783161401749,
-0.10867200046777725,
-0.0651642233133316,
-0.0021475483663380146,
0.017145752906799316,
0.03287679702043533,
0.015735773369669914,
-0.011839971877634525,
0.12727610766887665,
-0.013913152739405632,
-0.09861166775226593,
-0.02764826826751232,
-0.017435578629374504,
-0.1077762246131897,
-0.07511334866285324,
-0.01814364455640316,
0.00429524714127183,
-0.00948254019021988,
0.15276682376861572,
-0.10486604273319244,
0.06635333597660065,
-0.007462023291736841,
0.03369876369833946,
-0.038885973393917084,
0.12342888861894608,
-0.03959782049059868,
0.003319868817925453,
0.006460211705416441,
0.11510404944419861,
-0.0014229330699890852,
-0.01795901544392109,
-0.0753348246216774,
-0.032951176166534424,
0.08056801557540894,
0.0741758868098259,
-0.027834061533212662,
0.002839546650648117,
-0.07294785976409912,
-0.025118891149759293,
0.10005085170269012,
-0.12453518062829971,
0.05250391736626625,
0.005436605308204889,
-0.06259384751319885,
-0.03531717509031296,
0.037028148770332336,
0.015681341290473938,
-0.036582332104444504,
0.06792959570884705,
-0.06553305685520172,
0.014821830205619335,
-0.0773528590798378,
-0.07001450657844543,
0.044365301728248596,
-0.089270681142807,
-0.04300577566027641,
-0.07937303930521011,
-0.19166436791419983,
-0.06369809806346893,
0.020655972883105278,
-0.06235238537192345,
-0.044137753546237946,
-0.040621642023324966,
-0.06004893407225609,
0.014756085351109505,
-0.017332712188363075,
0.1260223239660263,
-0.04981497675180435,
0.07825010269880295,
-0.06649932265281677,
0.01135672815144062,
-0.004356982186436653,
0.029984042048454285,
-0.06695198267698288,
0.03422492742538452,
-0.13127027451992035,
0.06918394565582275,
-0.09753555804491043,
0.007685353513807058,
-0.13981342315673828,
-0.09480085223913193,
0.008653402328491211,
-0.04870855435729027,
0.07083608955144882,
0.11224041134119034,
-0.1925511211156845,
0.002543410286307335,
0.17487004399299622,
-0.08243412524461746,
-0.03730383515357971,
0.10449597984552383,
-0.039125364273786545,
0.020289089530706406,
0.05101142078638077,
0.15006783604621887,
0.13160809874534607,
-0.1688484102487564,
0.008576558902859688,
-0.0003908799262717366,
0.06345207989215851,
0.03105422668159008,
0.06355166435241699,
-0.024421581998467445,
0.04897724837064743,
0.0011024121195077896,
-0.07001576572656631,
-0.002600831910967827,
-0.07238565385341644,
-0.08947333693504333,
-0.044010479003190994,
-0.06860221177339554,
0.05491015315055847,
0.03144500032067299,
0.014127121306955814,
-0.05588527023792267,
-0.1162823885679245,
0.06496527791023254,
0.14255328476428986,
-0.03900352865457535,
0.01745297573506832,
-0.08029858022928238,
0.04415414109826088,
0.008024152368307114,
-0.03859700635075569,
-0.1928112953901291,
-0.12199800461530685,
0.0482138991355896,
-0.04199299216270447,
0.0248936265707016,
0.03410087898373604,
0.049309857189655304,
0.061682410538196564,
-0.04781821742653847,
-0.02025524713099003,
-0.09385064244270325,
-0.00047444752999581397,
-0.1096130982041359,
-0.19298484921455383,
-0.048889439553022385,
-0.037940677255392075,
0.20593933761119843,
-0.2261810302734375,
0.022068066522479057,
0.01708531379699707,
0.1344275325536728,
0.0239560604095459,
-0.06420489400625229,
0.003468241775408387,
0.07294415682554245,
0.013736837543547153,
-0.09968306869268417,
0.04745984449982643,
0.004342244938015938,
-0.06706458330154419,
-0.018167922273278236,
-0.1459321677684784,
-0.03111506998538971,
0.0692819356918335,
0.11682475358247757,
-0.1276184469461441,
-0.07246746867895126,
-0.06519722938537598,
-0.050858017057180405,
-0.07639812678098679,
0.00928200501948595,
0.16532595455646515,
0.029505804181098938,
0.10713087767362595,
-0.05687536671757698,
-0.06836877018213272,
0.006739228032529354,
0.01818890869617462,
0.00838096160441637,
0.07587286829948425,
0.05548369139432907,
-0.10639752447605133,
0.09370677918195724,
0.08181383460760117,
-0.04505437985062599,
0.11380138993263245,
-0.058294642716646194,
-0.0961378812789917,
-0.024756042286753654,
0.045608989894390106,
0.009886455722153187,
0.1362374722957611,
-0.014756298623979092,
0.01899958774447441,
0.03646925464272499,
0.013141943141818047,
0.01702907495200634,
-0.19852885603904724,
-0.009042787365615368,
0.013412915170192719,
-0.056243401020765305,
-0.014172231778502464,
-0.04444292187690735,
0.04647175222635269,
0.08071531355381012,
0.023615611717104912,
-0.019289402291178703,
0.004860032349824905,
-0.0037526339292526245,
-0.0981769934296608,
0.16336695849895477,
-0.14146356284618378,
-0.15652751922607422,
-0.11343122273683548,
0.09251751005649567,
0.01662396267056465,
-0.03369203954935074,
0.008951579220592976,
-0.04615141078829765,
-0.0353153795003891,
-0.10622940957546234,
-0.07100227475166321,
-0.02522558905184269,
-0.019428465515375137,
0.028708383440971375,
0.016935162246227264,
0.06557022780179977,
-0.11185061186552048,
0.0047199116088449955,
0.006474752444773912,
-0.08422816544771194,
0.02754509635269642,
0.03248507156968117,
0.08291149884462357,
0.1496395319700241,
-0.013864870183169842,
-0.011471840552985668,
-0.06583955138921738,
0.17254745960235596,
-0.09997601807117462,
0.02583068422973156,
0.09755673259496689,
0.0017408537678420544,
0.06372613459825516,
0.13327983021736145,
0.02327231876552105,
-0.07216756045818329,
0.011399230919778347,
0.04168657958507538,
-0.017157327383756638,
-0.25727441906929016,
-0.05304984375834465,
-0.02921401895582676,
-0.03294556215405464,
0.10032493621110916,
0.05392313376069069,
0.03477829694747925,
0.038511134684085846,
-0.03486863151192665,
0.016235120594501495,
0.027553902938961983,
0.07150233536958694,
0.04566385969519615,
0.0314469039440155,
0.09848994761705399,
-0.02026461623609066,
0.015041995793581009,
0.0748085081577301,
0.04595189541578293,
0.2667025923728943,
-0.03161870315670967,
0.1414986103773117,
0.03699527680873871,
0.1756974458694458,
-0.007767529226839542,
0.026330772787332535,
0.04835444688796997,
0.0063938782550394535,
0.0065809376537799835,
-0.05935182794928551,
-0.025569597259163857,
0.036210544407367706,
0.027770712971687317,
0.018438788130879402,
-0.07380594313144684,
0.018794871866703033,
0.009824380278587341,
0.29119595885276794,
0.039507679641246796,
-0.28597578406333923,
-0.08885501325130463,
0.010811246931552887,
-0.020616937428712845,
-0.06378767639398575,
-0.014376087114214897,
0.14818310737609863,
-0.1531413048505783,
0.04222842678427696,
-0.05273029953241348,
0.09420085698366165,
-0.04200175777077675,
-0.02011941559612751,
0.03838222101330757,
0.08622407168149948,
0.005347713362425566,
0.06941890716552734,
-0.20077522099018097,
0.21965615451335907,
0.013653519563376904,
0.10336919128894806,
-0.04634489864110947,
0.036263227462768555,
0.013797812163829803,
0.0938815027475357,
0.1310073286294937,
0.002067812718451023,
-0.05437140166759491,
-0.2059578001499176,
-0.12453612685203552,
0.011813079006969929,
0.09647642821073532,
-0.0315806046128273,
0.05934280529618263,
-0.035830460488796234,
0.005917529109865427,
0.026819000020623207,
-0.0847301185131073,
-0.17424504458904266,
-0.12486225366592407,
0.03992415964603424,
0.00442487932741642,
-0.023159658536314964,
-0.09557390958070755,
-0.09864480793476105,
-0.010852652601897717,
0.17038927972316742,
-0.0755716934800148,
-0.04034477099776268,
-0.1467112898826599,
0.07829837501049042,
0.12969531118869781,
-0.05286715552210808,
0.013946237042546272,
0.020085548982024193,
0.1317456215620041,
0.00018617235764395446,
-0.047792356461286545,
0.0428335964679718,
-0.06600971519947052,
-0.19526934623718262,
-0.07549405843019485,
0.1306217461824417,
0.08276282995939255,
0.07364808768033981,
0.005968782585114241,
0.02751564234495163,
0.02937990613281727,
-0.08836429566144943,
0.01618620567023754,
0.15373972058296204,
0.08347699791193008,
0.03305278718471527,
-0.06987614929676056,
0.0002475369838066399,
-0.05444743484258652,
-0.04009481891989708,
0.11750861257314682,
0.213740736246109,
-0.10564456135034561,
0.12791487574577332,
0.062216617166996,
-0.09182291477918625,
-0.1839868128299713,
0.05608205869793892,
0.13339585065841675,
0.03655238077044487,
0.022464165464043617,
-0.16844496130943298,
0.04716017469763756,
0.1469958871603012,
-0.028072906658053398,
0.05367496237158775,
-0.33866146206855774,
-0.1325514018535614,
0.053141769021749496,
0.06805744022130966,
-0.04350836202502251,
-0.12419123202562332,
-0.04507678374648094,
0.0014839564682915807,
-0.14575934410095215,
0.09099081158638,
-0.08631949871778488,
0.09220993518829346,
0.004049291834235191,
0.05916205048561096,
0.020711328834295273,
-0.03536422923207283,
0.1657591462135315,
0.014495305716991425,
0.06762518733739853,
-0.04969198629260063,
0.011309504508972168,
0.10187021642923355,
-0.07649089395999908,
0.04421267285943031,
-0.0007065507234074175,
0.053653471171855927,
-0.1290912628173828,
-0.009806973859667778,
-0.08000149577856064,
0.05895725265145302,
-0.05532711744308472,
-0.05075088143348694,
-0.05370675399899483,
0.08472862839698792,
0.044108401983976364,
-0.03801688551902771,
0.03900708630681038,
0.008965185843408108,
0.10835340619087219,
0.1105363741517067,
0.09577637165784836,
0.007242520805448294,
-0.10107774287462234,
-0.005703618284314871,
-0.041421543806791306,
0.0569155290722847,
-0.10052467882633209,
0.008068864233791828,
0.13936612010002136,
0.03452376648783684,
0.1336134374141693,
0.021297002211213112,
-0.07551391422748566,
0.014184542931616306,
0.030743462964892387,
-0.0931103304028511,
-0.1464918702840805,
0.02768077701330185,
0.05891476944088936,
-0.11745146661996841,
-0.035124532878398895,
0.13066452741622925,
-0.06293381750583649,
-0.03779524937272072,
0.004489412065595388,
0.029712049290537834,
-0.022183585911989212,
0.1948239654302597,
0.020799539983272552,
0.07805358618497849,
-0.07378491014242172,
0.10026843100786209,
0.10501492768526077,
-0.11961397528648376,
0.04567349702119827,
0.08839277178049088,
-0.10885554552078247,
-0.03538591414690018,
0.0876423791050911,
0.09922004491090775,
-0.01735685020685196,
-0.04436241462826729,
-0.040066421031951904,
-0.09203963726758957,
0.058316826820373535,
0.11164404451847076,
0.02127523347735405,
0.017950337380170822,
-0.0027126632630825043,
0.01699742302298546,
-0.12218962609767914,
0.07073651999235153,
0.035096392035484314,
0.0731741189956665,
-0.11142721772193909,
0.1474694013595581,
0.0056711845099925995,
0.03254030644893646,
-0.0064733633771538734,
0.01884920336306095,
-0.06973639130592346,
-0.011333728209137917,
-0.13149623572826385,
0.03353869542479515,
-0.033178143203258514,
-0.005026009865105152,
-0.0026519072707742453,
-0.037463001906871796,
0.0001528656284790486,
0.04657371714711189,
-0.06980431079864502,
-0.06250963360071182,
-0.02039503864943981,
0.06332551687955856,
-0.13696761429309845,
-0.022331515327095985,
0.028438594192266464,
-0.0819733664393425,
0.07784978300333023,
0.04429866001009941,
0.03616458177566528,
0.01541332621127367,
-0.12381192296743393,
-0.0024224526714533567,
0.026266733184456825,
0.032917238771915436,
0.05174598470330238,
-0.1020774394273758,
-0.019475504755973816,
-0.03700438514351845,
0.0050072683952748775,
0.03458966314792633,
0.05619223043322563,
-0.11265970021486282,
-0.04011049121618271,
-0.0329069048166275,
-0.05821715667843819,
-0.07234278321266174,
0.055850330740213394,
0.10888849943876266,
0.03956267982721329,
0.11051472276449203,
-0.08376281708478928,
0.06653618067502975,
-0.18926800787448883,
-0.03670452907681465,
-0.010150758549571037,
0.005144291557371616,
-0.05509290099143982,
-0.039333537220954895,
0.09619123488664627,
-0.04574304446578026,
0.05924403294920921,
-0.03366801142692566,
0.09507741779088974,
0.03276723995804787,
-0.08021990954875946,
-0.04268283024430275,
0.03809164837002754,
0.12301450967788696,
0.07020318508148193,
-0.032811239361763,
0.08377272635698318,
-0.037583887577056885,
0.032431572675704956,
0.03933726251125336,
0.2031385898590088,
0.1568818837404251,
0.04364185035228729,
0.055022627115249634,
0.05415249243378639,
-0.12332555651664734,
-0.12600666284561157,
0.1035667434334755,
-0.04382804036140442,
0.08891961723566055,
-0.07379040122032166,
0.17193584144115448,
0.08586473762989044,
-0.20022325217723846,
0.04974544048309326,
-0.06883934140205383,
-0.11705689132213593,
-0.09121959656476974,
-0.05876170098781586,
-0.0692429170012474,
-0.08783137053251266,
0.0030854095239192247,
-0.10596215724945068,
0.03503919765353203,
0.09105828404426575,
0.027324628084897995,
0.029531335458159447,
0.10786440223455429,
-0.01875442825257778,
0.008535555563867092,
0.062417689710855484,
0.036957886070013046,
0.025072135031223297,
-0.0886935219168663,
-0.07965733110904694,
0.06889552623033524,
0.0026702622417360544,
0.08476362377405167,
-0.03144841641187668,
0.049991022795438766,
0.026669485494494438,
-0.0018305990379303694,
-0.06563841551542282,
0.036717742681503296,
0.009998145513236523,
0.024375757202506065,
0.05873139202594757,
0.06091132014989853,
0.02004855126142502,
-0.028575953096151352,
0.26353174448013306,
-0.05495210736989975,
-0.09894654154777527,
-0.1509792059659958,
0.20360122621059418,
0.005040965508669615,
-0.018705230206251144,
0.0725492611527443,
-0.10647700726985931,
-0.003345433622598648,
0.12489604949951172,
0.1465885490179062,
-0.05042560026049614,
-0.003228848334401846,
0.0017792860744521022,
-0.016867240890860558,
-0.06779205054044724,
0.11704755574464798,
0.09284700453281403,
0.02924000285565853,
-0.0899372324347496,
0.004500879440456629,
0.011766469106078148,
-0.033749040216207504,
-0.0807323232293129,
0.03565305098891258,
-0.018215149641036987,
0.02391858585178852,
-0.05466826260089874,
0.07337407022714615,
0.0313107892870903,
-0.16275784373283386,
0.08553332090377808,
-0.16489006578922272,
-0.17745855450630188,
-0.005111627746373415,
0.06514027714729309,
-0.036590058356523514,
0.03288431465625763,
-0.014152374118566513,
-0.0014226343482732773,
0.16879010200500488,
-0.035781972110271454,
-0.04609550163149834,
-0.09098800271749496,
0.07557664811611176,
-0.04583923518657684,
0.2120165377855301,
-0.01402449980378151,
0.09566835314035416,
0.0926661342382431,
0.037185221910476685,
-0.13973161578178406,
0.017536185681819916,
0.08012617379426956,
-0.03451446816325188,
0.01686161197721958,
0.1651420146226883,
-0.04940235614776611,
0.0869373008608818,
0.06376169621944427,
-0.13203084468841553,
-0.008634895086288452,
-0.059944283217191696,
-0.00861961580812931,
-0.07232527434825897,
0.004834986291825771,
-0.06116744503378868,
0.15904922783374786,
0.17641392350196838,
-0.030709289014339447,
0.011728323996067047,
-0.05730297788977623,
0.011463425122201443,
0.041285064071416855,
0.10938151925802231,
-0.023884780704975128,
-0.17149107158184052,
0.031485795974731445,
0.0015524947084486485,
0.06270536035299301,
-0.20054955780506134,
-0.1101657897233963,
0.030826233327388763,
-0.058315303176641464,
-0.049024295061826706,
0.1382765918970108,
0.01812896504998207,
0.03177431598305702,
-0.02951662614941597,
-0.1439991444349289,
-0.027665141969919205,
0.13138382136821747,
-0.13376374542713165,
-0.03614669293165207
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | text-generation | gmonsoon/Qwenchana-0.5B | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T03:21:57+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
52,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06744060665369034,
0.1237388551235199,
-0.004114609677344561,
0.02991606667637825,
0.11460870504379272,
0.005568372085690498,
0.06294357031583786,
0.10971193760633469,
-0.026014693081378937,
0.11581014841794968,
0.018924949690699577,
0.10499268025159836,
0.10659246146678925,
0.1691424399614334,
-0.006015846040099859,
-0.21231532096862793,
0.044865865260362625,
-0.13380737602710724,
-0.025073938071727753,
0.11961860954761505,
0.13043774664402008,
-0.12202122807502747,
0.06986955553293228,
-0.03994565084576607,
-0.009295043535530567,
-0.0361013263463974,
-0.05820033326745033,
-0.04808541759848595,
0.06927672773599625,
0.0690578892827034,
0.06336662918329239,
0.01922842301428318,
0.10299910604953766,
-0.2810887396335602,
0.0236574187874794,
0.08111110329627991,
0.002226806478574872,
0.07000467926263809,
0.06337219476699829,
-0.07296913117170334,
0.06984713673591614,
-0.06522127240896225,
0.14495620131492615,
0.08224987238645554,
-0.0922221839427948,
-0.19323916733264923,
-0.08794740587472916,
0.09357348084449768,
0.19385994970798492,
0.05913294479250908,
-0.03049401193857193,
0.12686537206172943,
-0.07434657961130142,
0.01852177456021309,
0.06567037850618362,
-0.08194528520107269,
-0.053086262196302414,
0.06812959164381027,
0.07113085687160492,
0.10160701721906662,
-0.13397133350372314,
-0.0072817932814359665,
0.03036416508257389,
0.013016993179917336,
0.10258961468935013,
0.017448842525482178,
0.11838137358427048,
0.04335033521056175,
-0.14493173360824585,
-0.038016412407159805,
0.0884561613202095,
0.04341543838381767,
-0.05371417850255966,
-0.24333322048187256,
-0.021258622407913208,
-0.033045537769794464,
-0.03133222460746765,
-0.048901937901973724,
0.046065423637628555,
-0.018345197662711143,
0.0746571272611618,
-0.00905180536210537,
-0.077952079474926,
-0.047369781881570816,
0.07820919156074524,
0.06576532125473022,
0.026357414200901985,
-0.0243342574685812,
0.00772935152053833,
0.11627262830734253,
0.09934048354625702,
-0.11843404918909073,
-0.049750957638025284,
-0.06367483735084534,
-0.08425901085138321,
-0.04867105185985565,
0.029223250225186348,
0.03197961300611496,
0.05072800815105438,
0.2138856053352356,
-0.0016585314879193902,
0.04777570813894272,
0.0300018060952425,
0.01629858836531639,
0.0634123831987381,
0.09685925394296646,
-0.058943528681993484,
-0.12131623923778534,
-0.022760409861803055,
0.10975006967782974,
0.002361652674153447,
-0.03354809433221817,
-0.04929806664586067,
0.0689367800951004,
0.017635801807045937,
0.12228328734636307,
0.07093650102615356,
0.01461301650851965,
-0.07341200113296509,
-0.0643758624792099,
0.17208924889564514,
-0.1599913388490677,
0.033031485974788666,
0.027699848636984825,
-0.049781136214733124,
-0.016962584108114243,
0.0206128042191267,
0.030544809997081757,
-0.009477566927671432,
0.08983151614665985,
-0.051631052047014236,
-0.03264494985342026,
-0.11271350830793381,
-0.05229318514466286,
0.022805018350481987,
0.02329850196838379,
-0.029599839821457863,
-0.04297630116343498,
-0.10461901128292084,
-0.0702618658542633,
0.08274642378091812,
-0.06679617613554001,
-0.04588131234049797,
-0.034392643719911575,
-0.08036767691373825,
0.012772615067660809,
0.006944936700165272,
0.11524419486522675,
-0.024861354380846024,
0.04965236783027649,
-0.05080482363700867,
0.07076980918645859,
0.12968726456165314,
0.0256124809384346,
-0.052786268293857574,
0.05227842554450035,
-0.23543758690357208,
0.10626004636287689,
-0.07104437053203583,
0.04600486531853676,
-0.16222067177295685,
-0.019692296162247658,
0.04013443738222122,
0.022423196583986282,
-0.0052419379353523254,
0.13304713368415833,
-0.20579689741134644,
-0.03484721481800079,
0.1778334081172943,
-0.10716996341943741,
-0.08844240009784698,
0.05829978361725807,
-0.05727203190326691,
0.12106184661388397,
0.046658918261528015,
-0.015959804877638817,
0.030861597508192062,
-0.14105893671512604,
-0.012573265470564365,
-0.05725134164094925,
-0.027953004464507103,
0.1594742387533188,
0.06174226105213165,
-0.04975385218858719,
0.06329082697629929,
0.017857130616903305,
-0.014720242470502853,
-0.047373462468385696,
-0.03508519008755684,
-0.10099945217370987,
0.009225212968885899,
-0.0735674798488617,
0.025139320641756058,
-0.03237168863415718,
-0.09091918170452118,
-0.030487151816487312,
-0.15721407532691956,
0.006027343682944775,
0.09086263924837112,
-0.0028123122174292803,
-0.02166888304054737,
-0.10495693236589432,
-0.015849687159061432,
0.023717699572443962,
0.0010735627729445696,
-0.14732947945594788,
-0.052729055285453796,
0.01963592879474163,
-0.16102278232574463,
0.03527507185935974,
-0.032337408512830734,
0.046559423208236694,
0.04404491186141968,
-0.044810350984334946,
-0.03644292429089546,
0.01527401339262724,
0.01702694222331047,
-0.01812152937054634,
-0.2757890224456787,
-0.016599029302597046,
-0.037502363324165344,
0.16484688222408295,
-0.2536672055721283,
0.044451385736465454,
0.052858345210552216,
0.12650004029273987,
0.011718528345227242,
-0.026840604841709137,
0.02031077817082405,
-0.06778053194284439,
-0.03378141298890114,
-0.060537584125995636,
-0.0102090397849679,
-0.036261335015296936,
-0.05234677344560623,
0.03442572429776192,
-0.16672758758068085,
-0.04233158379793167,
0.11038065701723099,
0.03841483220458031,
-0.1514066904783249,
-0.046796903014183044,
-0.04655757546424866,
-0.05544671788811684,
-0.06981822848320007,
-0.05111313611268997,
0.10990618914365768,
0.0552663654088974,
0.054820816963911057,
-0.06279280036687851,
-0.06714518368244171,
0.008098754100501537,
-0.023038236424326897,
-0.01628015749156475,
0.08303935825824738,
0.07147926092147827,
-0.12255207449197769,
0.09013188630342484,
0.0958702489733696,
0.08535332977771759,
0.10111390799283981,
0.0031223141122609377,
-0.08790350705385208,
-0.02990630455315113,
0.029989181086421013,
0.01356097124516964,
0.150030717253685,
-0.026905570179224014,
0.049839962273836136,
0.03979787230491638,
-0.007262712344527245,
0.005843297578394413,
-0.0978906974196434,
0.029100263491272926,
0.024840185418725014,
-0.011728756129741669,
0.036994971334934235,
-0.05755846947431564,
0.016809193417429924,
0.10532841086387634,
0.040135741233825684,
0.051635969430208206,
0.008006487041711807,
-0.05116545408964157,
-0.11712050437927246,
0.1763288974761963,
-0.11831972748041153,
-0.23028700053691864,
-0.12128487974405289,
-0.012982514686882496,
0.03150848671793938,
-0.012953351251780987,
0.025938911363482475,
-0.07433073222637177,
-0.11664986610412598,
-0.0922725722193718,
0.04694730415940285,
0.059740062803030014,
-0.08346977084875107,
-0.062362488359212875,
0.06679393351078033,
0.0457296296954155,
-0.1380528211593628,
0.026153815910220146,
0.035679563879966736,
-0.09117627143859863,
0.005887721199542284,
0.08140957355499268,
0.06103856489062309,
0.1818755865097046,
0.012728521600365639,
-0.023938871920108795,
0.019584620371460915,
0.20903365314006805,
-0.136505126953125,
0.10589402914047241,
0.13493265211582184,
-0.0703483521938324,
0.08147261291742325,
0.2107224464416504,
0.0418342649936676,
-0.10617547482252121,
0.04455582797527313,
0.034235551953315735,
-0.0238803718239069,
-0.25054290890693665,
-0.07808786630630493,
0.007576430216431618,
-0.06175751984119415,
0.06809944659471512,
0.08130444586277008,
0.09570267051458359,
0.01984638161957264,
-0.10488120466470718,
-0.06586658954620361,
0.05113326013088226,
0.11108365654945374,
-0.007418854162096977,
-0.012006757780909538,
0.0969165563583374,
-0.020286425948143005,
0.028002621605992317,
0.09235991537570953,
0.0084880031645298,
0.18746548891067505,
0.05100390687584877,
0.14692288637161255,
0.09142749756574631,
0.06584213674068451,
0.015684716403484344,
0.006666323635727167,
0.015644695609807968,
0.02073444239795208,
-0.014378254301846027,
-0.0880797803401947,
-0.0017288135131821036,
0.12815876305103302,
0.020411469042301178,
0.050393857061862946,
0.005088018253445625,
-0.032580070197582245,
0.08683152496814728,
0.17358696460723877,
0.010363306850194931,
-0.1908130794763565,
-0.07101033627986908,
0.06939493864774704,
-0.08181700855493546,
-0.10146915167570114,
-0.02635601907968521,
0.04305123910307884,
-0.17831183969974518,
0.014033086597919464,
-0.022382382303476334,
0.10410568863153458,
-0.11462701857089996,
-0.012489398010075092,
0.04906824603676796,
0.07298072427511215,
-0.016658522188663483,
0.06773389875888824,
-0.18002092838287354,
0.1395270675420761,
0.01758507452905178,
0.07150158286094666,
-0.08825206011533737,
0.08410486578941345,
0.003178939688950777,
0.0013509939890354872,
0.14415407180786133,
0.0013785995543003082,
-0.0523817352950573,
-0.10979107022285461,
-0.08634650707244873,
-0.009079654701054096,
0.13044366240501404,
-0.12778301537036896,
0.10016698390245438,
-0.01834736578166485,
-0.045373477041721344,
0.005183245521038771,
-0.11240560561418533,
-0.14056962728500366,
-0.1725207269191742,
0.04330243170261383,
-0.13124029338359833,
0.04465160518884659,
-0.10545487701892853,
-0.048093315213918686,
-0.05306214094161987,
0.19742146134376526,
-0.22286871075630188,
-0.07013117522001266,
-0.1519971340894699,
-0.05761480703949928,
0.119932159781456,
-0.04775578901171684,
0.08312731981277466,
0.012994625605642796,
0.18674440681934357,
0.014313536696135998,
-0.013770169578492641,
0.11090241372585297,
-0.10466983169317245,
-0.21406547725200653,
-0.10291838645935059,
0.14246919751167297,
0.13924811780452728,
0.041273895651102066,
0.0022257522214204073,
0.02827414683997631,
-0.014804026111960411,
-0.11688549816608429,
0.020713498815894127,
0.1711113303899765,
0.11356078088283539,
0.031762681901454926,
-0.045852549374103546,
-0.12838490307331085,
-0.08528922498226166,
-0.04527286812663078,
0.01937401480972767,
0.1929924041032791,
-0.07334718853235245,
0.17354312539100647,
0.15734395384788513,
-0.05666225776076317,
-0.1967383325099945,
0.02808118239045143,
0.04254651814699173,
0.0018926940392702818,
0.058352239429950714,
-0.19716250896453857,
0.0960150957107544,
0.0021078127902001143,
-0.054582200944423676,
0.11626559495925903,
-0.18086016178131104,
-0.1472223997116089,
0.055250246077775955,
0.06544214487075806,
-0.1867036670446396,
-0.12468403577804565,
-0.09152166545391083,
-0.040479280054569244,
-0.12750375270843506,
0.08364081382751465,
-0.015219016931951046,
0.011511581018567085,
0.03329310938715935,
0.02034589648246765,
0.010542148724198341,
-0.043612707406282425,
0.18297483026981354,
-0.0074994368478655815,
0.04291056841611862,
-0.07745802402496338,
-0.06123793497681618,
0.04548247158527374,
-0.06682101637125015,
0.0688505694270134,
-0.012457388453185558,
0.01576600968837738,
-0.10679414868354797,
-0.05470338836312294,
-0.03223368898034096,
0.019370099529623985,
-0.08504306524991989,
-0.10194364190101624,
-0.036353081464767456,
0.09871356934309006,
0.09517461061477661,
-0.037792425602674484,
-0.056679584085941315,
-0.08485732227563858,
0.04062115028500557,
0.20317383110523224,
0.18020522594451904,
0.053560756146907806,
-0.06437430530786514,
-0.006059312727302313,
-0.013237647712230682,
0.049002740532159805,
-0.22129850089550018,
0.05923459306359291,
0.041168149560689926,
0.03180031478404999,
0.11860810965299606,
-0.023935925215482712,
-0.1587793081998825,
-0.0502057746052742,
0.05410148575901985,
-0.07425004243850708,
-0.1685684472322464,
0.010434879921376705,
0.08286356180906296,
-0.1552492380142212,
-0.022906674072146416,
0.04575012996792793,
-0.020043641328811646,
-0.03438226878643036,
0.00707294000312686,
0.07919111847877502,
0.009836919605731964,
0.08478374034166336,
0.057017721235752106,
0.0959276556968689,
-0.10216023027896881,
0.06617968529462814,
0.08096546679735184,
-0.09338610619306564,
0.03410530090332031,
0.07545924931764603,
-0.07126593589782715,
-0.037233464419841766,
0.04482624679803848,
0.0918767899274826,
0.031775590032339096,
-0.050642579793930054,
0.012327476404607296,
-0.10012588649988174,
0.05418751388788223,
0.11697539687156677,
0.03980601206421852,
0.0020653458777815104,
0.0349934883415699,
0.04598642885684967,
-0.09361135214567184,
0.12619003653526306,
0.03253564611077309,
0.024358928203582764,
-0.044029660522937775,
-0.027948984876275063,
0.033686719834804535,
-0.020634718239307404,
-0.014900618232786655,
-0.04131974279880524,
-0.06906769424676895,
-0.011919837445020676,
-0.17663416266441345,
-0.0006877299747429788,
-0.03835081309080124,
0.008035878650844097,
0.01438689511269331,
-0.03798643499612808,
0.008271864615380764,
0.015990857034921646,
-0.07275852560997009,
-0.05440134555101395,
-0.01070401445031166,
0.10120883584022522,
-0.16839949786663055,
0.013798215426504612,
0.0738481730222702,
-0.11845122277736664,
0.08829576522111893,
0.01660950295627117,
0.004566526506096125,
0.03947852551937103,
-0.12990154325962067,
0.0469437912106514,
-0.015183643437922001,
0.017251212149858475,
0.051821283996105194,
-0.20713716745376587,
-0.005219681188464165,
-0.053738780319690704,
-0.054747533053159714,
-0.008454185910522938,
-0.028378764167428017,
-0.11614704132080078,
0.10657370090484619,
0.006339828949421644,
-0.07519937306642532,
-0.027563083916902542,
0.034499529749155045,
0.07487460225820541,
-0.031029552221298218,
0.1542745679616928,
-0.014918236993253231,
0.06987065821886063,
-0.1874280571937561,
-0.023337583988904953,
-0.014252493157982826,
0.024976249784231186,
-0.03739270567893982,
-0.01777520589530468,
0.05066380277276039,
-0.025644395500421524,
0.1947220265865326,
-0.02277233451604843,
0.05517526715993881,
0.06517178565263748,
-0.015353423543274403,
-0.025753356516361237,
0.10341554135084152,
0.055761225521564484,
0.015996338799595833,
0.03251899033784866,
0.007716674357652664,
-0.03165765851736069,
-0.005552713759243488,
-0.167100191116333,
0.07967466861009598,
0.16496649384498596,
0.08635497838258743,
-0.014588052406907082,
0.06132662668824196,
-0.11290588229894638,
-0.11605644226074219,
0.09777160733938217,
-0.056159622967243195,
-0.01740921474993229,
-0.062441661953926086,
0.13894620537757874,
0.1522199958562851,
-0.19082458317279816,
0.06211152300238609,
-0.06795507669448853,
-0.0487544871866703,
-0.10746019333600998,
-0.16687791049480438,
-0.05764069780707359,
-0.05954143404960632,
-0.020104030147194862,
-0.05745544657111168,
0.06959457695484161,
0.07283110171556473,
0.017621422186493874,
0.012575851753354073,
0.07775423675775528,
-0.017673097550868988,
0.00843984168022871,
0.026977673172950745,
0.06567810475826263,
0.013495570048689842,
-0.04381807893514633,
0.016235843300819397,
-0.00015613723371643573,
0.034048307687044144,
0.047009509056806564,
0.039173372089862823,
-0.03012777306139469,
0.005396591499447823,
-0.03004968911409378,
-0.1132737398147583,
0.04056783393025398,
-0.0245139729231596,
-0.06442589312791824,
0.13803128898143768,
0.026449358090758324,
-0.006702050566673279,
-0.025474393740296364,
0.2641041576862335,
-0.07600386440753937,
-0.09474562108516693,
-0.13578693568706512,
0.13365262746810913,
-0.0308542363345623,
0.06413768976926804,
0.033664409071207047,
-0.11381697654724121,
0.027896301820874214,
0.145524263381958,
0.14766931533813477,
-0.059594202786684036,
0.018058648332953453,
0.023248950019478798,
0.0036677704192698,
-0.038663145154714584,
0.05093686655163765,
0.07642526924610138,
0.13084270060062408,
-0.057510439306497574,
0.07993458956480026,
-0.00528855761513114,
-0.09648048877716064,
-0.03070426546037197,
0.12046385556459427,
-0.005974611733108759,
0.018961863592267036,
-0.06711561232805252,
0.12644343078136444,
-0.043718259781599045,
-0.261628121137619,
0.05282887443900108,
-0.06905496120452881,
-0.14716462790966034,
-0.02855629473924637,
0.05909299477934837,
-0.00726199010387063,
0.02540661208331585,
0.06713409721851349,
-0.06904488801956177,
0.19428247213363647,
0.03470597416162491,
-0.044902503490448,
-0.06258992105722427,
0.07463990896940231,
-0.10928831994533539,
0.28889188170433044,
0.010627356357872486,
0.05702703818678856,
0.1010323017835617,
-0.02710605598986149,
-0.13230937719345093,
0.030603965744376183,
0.08569987118244171,
-0.08157077431678772,
0.049359869211912155,
0.2173999398946762,
-0.00799210648983717,
0.11221332848072052,
0.0741662085056305,
-0.09916665405035019,
0.052276816219091415,
-0.10220054537057877,
-0.09391136467456818,
-0.08265925943851471,
0.09803684055805206,
-0.05557653307914734,
0.14824360609054565,
0.12248145043849945,
-0.04785078391432762,
0.022196060046553612,
-0.022353654727339745,
0.04894673451781273,
0.006722010672092438,
0.12958186864852905,
0.013888917863368988,
-0.19708466529846191,
0.027539461851119995,
-0.004416270647197962,
0.09896787256002426,
-0.2124645709991455,
-0.10066045075654984,
0.05214649438858032,
0.00458158552646637,
-0.06152847036719322,
0.12505200505256653,
0.06458623707294464,
0.040626320987939835,
-0.045448239892721176,
-0.0330616720020771,
-0.008380461484193802,
0.1610291600227356,
-0.10901795327663422,
-0.004472559317946434
] |
null | null | transformers |
# Bangla LLaMA 13B Instruct v0.1
Welcome to the inaugural release of the Bangla LLaMA 13B instruct model – an important step in advancing LLMs for the Tamil language. This model is ready for immediate inference and is also primed for further fine-tuning to cater to your specific NLP tasks.
## Model description
The Bangla LLaMA models have been enhanced and tailored specifically with an extensive Bangla vocabulary of 16,000 tokens, building upon the foundation set by the original LLaMA-2.
- **Model type:** A 13B parameter GPT-like model fine-tuned on [Bangla-Alpaca-Orca](https://huggingface.co/datasets/banglallm/bangla-alpaca-orca) - a mix of Bangla-translated [Stanford-Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) and a subset of [OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) datasets.
- **Language(s):** Bangla and English
- **License:** GNU General Public License v3.0
- **Finetuned from model:** [BanglaLLM/bangla-llama-13b-base-v0.1](https://huggingface.co/banglallm/bangla-llama-13b-base-v0.1)
- **Training Precision:** `float16`
- **Code:** [GitHub](https://github.com/BanglaLLM/bangla-llama)
## Prompting Format
**Prompt Template Without Input**
```
{system_prompt}
### Instruction:
{instruction or query}
### Response:
{response}
```
**Prompt Template With Input**
```
{system_prompt}
### Instruction:
{instruction or query}
### Input:
{input}
### Response:
{response}
```
## Related Models
| Model | Type | Data | Base Model | # Params | Download Links |
|--------------------------|-----------------------------|-------------------|----------------------|------|------------------------------------------------------------------------|
| Bangla LLaMA 7B Base | Base model | 12GB | LLaMA 7B | 7B | [HF Hub](https://huggingface.co/banglallm/bangla-llama-7b-base-v0.1) |
| Bangla LLaMA 13B Base | Base model | 4GB | LLaMA 13B | 13B | [HF Hub](https://huggingface.co/banglallm/bangla-llama-13b-base-v0.1) |
| Bangla LLaMA 7B Instruct | Instruction following model | 145k instructions | Bangla LLaMA 7B Base | 7B | [HF Hub](https://huggingface.co/banglallm/bangla-llama-7b-instruct-v0.1) |
| Bangla LLaMA 13B Instruct | Instruction following model | 145k instructions | Bangla LLaMA 13B Base | 13B | [HF Hub](banglallm/bangla-llama-13b-instruct-v0.1) |
## Usage Note
It's important to note that the models have not undergone detoxification. Therefore, while they possess impressive linguistic capabilities, there is a possibility for them to generate content that could be deemed harmful or offensive. We urge users to exercise discretion and supervise the model's outputs closely, especially in public or sensitive applications.
## Meet the Developers
Get to know the creators behind this innovative model and follow their contributions to the field:
- [Abdullah Khan Zehady](https://www.linkedin.com/in/abdullah-khan-zehady-915ba024/)
## Citation
We hope this model serves as a valuable tool in your NLP toolkit and look forward to seeing the advancements it will enable in the understanding and generation of the Bangla language. | {"language": ["bn", "en"], "license": "llama2"} | text-generation | BanglaLLM/bangla-llama-13b-instruct-v0.1 | [
"transformers",
"pytorch",
"tensorboard",
"llama",
"text-generation",
"bn",
"en",
"license:llama2",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:26:55+00:00 | [] | [
"bn",
"en"
] | TAGS
#transformers #pytorch #tensorboard #llama #text-generation #bn #en #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Bangla LLaMA 13B Instruct v0.1
==============================
Welcome to the inaugural release of the Bangla LLaMA 13B instruct model – an important step in advancing LLMs for the Tamil language. This model is ready for immediate inference and is also primed for further fine-tuning to cater to your specific NLP tasks.
Model description
-----------------
The Bangla LLaMA models have been enhanced and tailored specifically with an extensive Bangla vocabulary of 16,000 tokens, building upon the foundation set by the original LLaMA-2.
* Model type: A 13B parameter GPT-like model fine-tuned on Bangla-Alpaca-Orca - a mix of Bangla-translated Stanford-Alpaca and a subset of OpenOrca datasets.
* Language(s): Bangla and English
* License: GNU General Public License v3.0
* Finetuned from model: BanglaLLM/bangla-llama-13b-base-v0.1
* Training Precision: 'float16'
* Code: GitHub
Prompting Format
----------------
Prompt Template Without Input
Prompt Template With Input
Related Models
--------------
Usage Note
----------
It's important to note that the models have not undergone detoxification. Therefore, while they possess impressive linguistic capabilities, there is a possibility for them to generate content that could be deemed harmful or offensive. We urge users to exercise discretion and supervise the model's outputs closely, especially in public or sensitive applications.
Meet the Developers
-------------------
Get to know the creators behind this innovative model and follow their contributions to the field:
* Abdullah Khan Zehady
We hope this model serves as a valuable tool in your NLP toolkit and look forward to seeing the advancements it will enable in the understanding and generation of the Bangla language.
| [] | [
"TAGS\n#transformers #pytorch #tensorboard #llama #text-generation #bn #en #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] | [
61
] | [
"passage: TAGS\n#transformers #pytorch #tensorboard #llama #text-generation #bn #en #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] | [
-0.021583616733551025,
0.0419837161898613,
-0.0073033468797802925,
0.03225100785493851,
0.12277133762836456,
0.012326795607805252,
0.1723111867904663,
0.12695762515068054,
0.04005973041057587,
-0.005883583799004555,
0.1306232064962387,
0.2228497415781021,
-0.0031323048751801252,
-0.00848793238401413,
-0.07070004940032959,
-0.25125402212142944,
0.012457413598895073,
0.07926931232213974,
-0.017302600666880608,
0.10082059353590012,
0.0671292394399643,
-0.08502651751041412,
0.06893278658390045,
-0.021431267261505127,
-0.14725935459136963,
0.030943488702178,
0.02617737278342247,
-0.10811074078083038,
0.11165158450603485,
0.06871424615383148,
0.1095183715224266,
0.048554837703704834,
-0.046346720308065414,
-0.170292928814888,
0.0362987257540226,
-0.007548939436674118,
-0.08227908611297607,
0.08090232312679291,
0.08105053752660751,
-0.0695149227976799,
0.11233602464199066,
0.07323259115219116,
-0.02315366268157959,
0.043473996222019196,
-0.11061033606529236,
-0.03462153300642967,
-0.026977095752954483,
0.04667189344763756,
0.04070165753364563,
0.059056032449007034,
0.006346791982650757,
0.10253669321537018,
-0.059862155467271805,
0.09761897474527359,
0.16345888376235962,
-0.36860013008117676,
0.0007862618658691645,
0.11778637766838074,
0.09870313853025436,
0.054660677909851074,
-0.04871607944369316,
0.0805283859372139,
0.03409962356090546,
0.004394074901938438,
0.06577245891094208,
-0.08409154415130615,
-0.06898586452007294,
0.05935051292181015,
-0.0846790224313736,
-0.015498410910367966,
0.18740342557430267,
-0.04888560250401497,
0.0757015272974968,
-0.049953773617744446,
-0.07945667207241058,
-0.05143657699227333,
-0.020540768280625343,
0.026400217786431313,
-0.023386167362332344,
0.06247890740633011,
0.0269931647926569,
-0.08532048761844635,
-0.13834576308727264,
0.0020605693571269512,
-0.19807292520999908,
0.12352820485830307,
0.011650514788925648,
0.03674282133579254,
-0.18144559860229492,
0.07999645173549652,
0.05980347841978073,
-0.10951763391494751,
0.041610851883888245,
-0.03910386189818382,
0.070330910384655,
0.01981757953763008,
-0.040380410850048065,
-0.12031945586204529,
0.10176302492618561,
0.08147480338811874,
0.032027192413806915,
0.011700949631631374,
-0.07918345183134079,
0.13698752224445343,
0.0047468882985413074,
0.06250583380460739,
-0.027874013409018517,
-0.03171782195568085,
0.058565735816955566,
-0.07369709014892578,
0.047554466873407364,
-0.058724019676446915,
-0.19196657836437225,
-0.016008786857128143,
0.033481597900390625,
0.08764354884624481,
0.021878723055124283,
0.07816360145807266,
-0.04407656565308571,
-0.018069244921207428,
0.013549835421144962,
-0.08740220963954926,
0.010538431815803051,
0.009929201565682888,
0.009289917536079884,
0.08847224712371826,
0.03256500884890556,
0.0018955266568809748,
-0.08737330883741379,
0.07439503073692322,
-0.08204035460948944,
-0.006815681699663401,
-0.059667687863111496,
-0.07262624055147171,
0.06229345500469208,
-0.1407940685749054,
0.02699769102036953,
-0.13161203265190125,
-0.1605188250541687,
0.0316346250474453,
0.022565146908164024,
-0.0446152463555336,
-0.02739761210978031,
-0.013420281931757927,
-0.050572916865348816,
0.020248807966709137,
-0.07545020431280136,
0.0310643520206213,
-0.05756101757287979,
0.10620680451393127,
-0.05000791698694229,
0.06975923478603363,
-0.1509661078453064,
0.06508643925189972,
-0.07391299307346344,
0.018970925360918045,
-0.060576967895030975,
0.03417212516069412,
-0.03956945985555649,
0.10147465765476227,
-0.022351296618580818,
-0.010148097760975361,
-0.07239072024822235,
0.05704298987984657,
-0.009258124977350235,
0.13024207949638367,
-0.13872282207012177,
-0.11355190724134445,
0.19923193752765656,
-0.07899562269449234,
-0.1706131249666214,
0.08662554621696472,
-0.010102626867592335,
0.055965278297662735,
0.06593938916921616,
0.21275146305561066,
0.029589103534817696,
-0.03994648531079292,
0.04596531763672829,
0.10749343782663345,
-0.04645149037241936,
-0.15694257616996765,
0.006473641376942396,
-0.000129448133520782,
-0.029604537412524223,
0.046552810817956924,
0.08260082453489304,
0.07440320402383804,
-0.0381026566028595,
-0.06178881600499153,
-0.03692663088440895,
-0.023368405178189278,
0.028361225500702858,
0.026264186948537827,
0.10941185802221298,
-0.04368796944618225,
-0.02465987205505371,
0.09800278395414352,
-0.00581911439076066,
-0.03796641156077385,
0.04542528837919235,
-0.058621324598789215,
0.15614795684814453,
-0.05099298804998398,
0.029864761978387833,
-0.17848381400108337,
-0.06639307737350464,
-0.022460870444774628,
0.052250172942876816,
0.03934241458773613,
0.09689033031463623,
0.05072323605418205,
-0.018260449171066284,
-0.02760804072022438,
0.03699224442243576,
0.14560700953006744,
0.003700021654367447,
-0.07550010830163956,
-0.13255612552165985,
0.045372478663921356,
-0.06863734126091003,
-0.0271610077470541,
-0.10070756077766418,
0.03069392405450344,
0.06374623626470566,
0.10167740285396576,
0.013545428402721882,
0.05470077693462372,
-0.015406019985675812,
0.02855980023741722,
-0.0965871512889862,
0.026963666081428528,
0.12083212286233902,
-0.013340394012629986,
-0.11433803290128708,
0.1781643182039261,
-0.16780085861682892,
0.24299536645412445,
0.21378017961978912,
-0.23042739927768707,
0.048335663974285126,
-0.08854974061250687,
-0.027256662026047707,
-0.0057123880833387375,
0.04845528304576874,
-0.03066275827586651,
0.06812182068824768,
0.012585107237100601,
0.1807868331670761,
-0.0755884125828743,
-0.057743463665246964,
-0.002842934802174568,
-0.040922220796346664,
-0.034203846007585526,
0.09915397316217422,
0.17990247905254364,
-0.12080895900726318,
0.18131180107593536,
0.2136181890964508,
-0.0187664981931448,
0.22050108015537262,
-0.03142240643501282,
-0.022818759083747864,
0.04180309921503067,
-0.0032090237364172935,
-0.01274838112294674,
0.006307479925453663,
-0.1895150989294052,
-0.014035153202712536,
0.06689701229333878,
-0.011913341470062733,
0.09384778887033463,
-0.1552077829837799,
-0.05101930722594261,
-0.037699129432439804,
-0.019663747400045395,
0.039391592144966125,
0.08124172687530518,
0.031812168657779694,
0.12208834290504456,
-0.04661839082837105,
-0.05928774178028107,
0.08614734560251236,
-0.004382953979074955,
-0.07302988320589066,
0.18682646751403809,
-0.10603497922420502,
-0.2674848735332489,
-0.1701354831457138,
-0.14200833439826965,
-0.06311903893947601,
0.008422222919762135,
0.08918693661689758,
-0.03954741358757019,
-0.016054904088377953,
-0.026853803545236588,
0.05374393239617348,
-0.04823986440896988,
0.012043006718158722,
-0.059529926627874374,
0.05998793989419937,
-0.0780976414680481,
-0.1155306026339531,
-0.04701162874698639,
-0.04058144614100456,
-0.02874358929693699,
0.1136806383728981,
-0.07245152443647385,
0.07076387107372284,
0.20020240545272827,
0.026781843975186348,
0.03439171984791756,
-0.04106510803103447,
0.13019096851348877,
-0.059297263622283936,
0.023823311552405357,
0.1735464185476303,
-0.05421728640794754,
0.07473138719797134,
0.1314089447259903,
0.05662689730525017,
-0.08145204186439514,
-0.00048052871716208756,
-0.0006593711441382766,
-0.09941797703504562,
-0.25929608941078186,
-0.09664347767829895,
-0.11991097033023834,
0.0733126848936081,
0.022133177146315575,
0.07335460186004639,
0.1196858286857605,
0.07914132624864578,
0.014722142368555069,
0.009665056131780148,
0.008174872025847435,
0.061749957501888275,
0.25990980863571167,
-0.02548089064657688,
0.142116516828537,
-0.07433412969112396,
-0.11273180693387985,
0.0695681944489479,
0.13122814893722534,
0.153394877910614,
0.08103183656930923,
0.12285696715116501,
0.06209801882505417,
0.07858029007911682,
0.11671695113182068,
0.09741932153701782,
-0.020611267536878586,
-0.015919499099254608,
-0.025800423696637154,
-0.05295263230800629,
0.01356943417340517,
0.03070160001516342,
0.009916636161506176,
-0.10397949814796448,
-0.006368973292410374,
-0.10300444066524506,
0.057444699108600616,
0.09549005329608917,
0.0308675579726696,
-0.19970953464508057,
0.04103364422917366,
0.09517418593168259,
-0.018209023401141167,
-0.07512450963258743,
0.07722699642181396,
0.03344624489545822,
-0.06378717720508575,
0.05566800385713577,
-0.06746549904346466,
0.11480003595352173,
-0.06960969418287277,
0.06689628958702087,
-0.04307189956307411,
-0.06136232987046242,
0.032371699810028076,
0.09397926181554794,
-0.28681227564811707,
0.22561585903167725,
0.013667920604348183,
-0.04333243519067764,
-0.08301233500242233,
-0.0011588330380618572,
0.006653038319200277,
0.1030103862285614,
0.11303018778562546,
-0.027265451848506927,
0.018361205235123634,
-0.054037801921367645,
-0.03548423573374748,
0.021213741973042488,
0.09398521482944489,
-0.030529124662280083,
0.002707042032852769,
-0.019804250448942184,
-0.0002501686103641987,
0.0076782554388046265,
-0.004678367171436548,
0.018640784546732903,
-0.1858457326889038,
0.07316973805427551,
0.06511636823415756,
-0.026893025264143944,
0.0075868177227675915,
-0.060862574726343155,
-0.14162400364875793,
0.2048294097185135,
-0.14627887308597565,
-0.08891554921865463,
-0.09719330817461014,
-0.06967051327228546,
0.05368838459253311,
-0.06595151126384735,
0.028997143730521202,
-0.07048435509204865,
0.01062492560595274,
-0.09146594256162643,
-0.21682365238666534,
0.12715713679790497,
-0.07197821885347366,
-0.027382684871554375,
-0.05780750513076782,
0.16958126425743103,
-0.07463444769382477,
0.021526459604501724,
0.014435891062021255,
0.005359770730137825,
-0.07817381620407104,
-0.09916123747825623,
0.0025941464118659496,
0.016348451375961304,
0.04499430954456329,
-0.03890546038746834,
-0.13994061946868896,
-0.0011339260963723063,
-0.0008076258818618953,
-0.02894374169409275,
0.2707950472831726,
0.19640877842903137,
-0.06993817538022995,
0.16287170350551605,
0.14912724494934082,
-0.12483913451433182,
-0.3241073787212372,
-0.08855834603309631,
-0.11372748762369156,
-0.02921454608440399,
0.009007474407553673,
-0.1862119436264038,
0.10485691577196121,
0.03518575057387352,
-0.036973245441913605,
0.16918505728244781,
-0.3006094992160797,
-0.11365983635187149,
0.15205809473991394,
0.05139905586838722,
0.3040759265422821,
-0.18084333837032318,
-0.11102227866649628,
-0.036597512662410736,
-0.10540492832660675,
0.18613260984420776,
-0.0624525286257267,
0.12326253950595856,
-0.03574128821492195,
0.08644832670688629,
0.028214117512106895,
-0.05710498243570328,
0.09209669381380081,
0.004538797307759523,
0.02912387251853943,
-0.0933501198887825,
-0.05629643052816391,
0.08051818609237671,
0.007812660187482834,
0.017779922112822533,
-0.13750462234020233,
-0.004220831207931042,
-0.1241702139377594,
-0.04025445133447647,
-0.04797682911157608,
0.09110243618488312,
0.004456766881048679,
-0.07429155707359314,
-0.027677739039063454,
-0.03144904598593712,
-0.012959664687514305,
0.003112902631983161,
0.25645628571510315,
-0.04956479370594025,
0.13893328607082367,
0.21865038573741913,
0.11865241825580597,
-0.11857561022043228,
0.003408164717257023,
-0.07426141947507858,
-0.06379345804452896,
0.07272696495056152,
-0.11276883631944656,
0.02398213930428028,
0.13985766470432281,
-0.022750312462449074,
0.061466556042432785,
0.09294819831848145,
-0.022921781986951828,
0.0012248784769326448,
0.1356629580259323,
-0.20811370015144348,
-0.07657378166913986,
-0.030316196382045746,
-0.028128325939178467,
0.06275729089975357,
0.07604341208934784,
0.15752936899662018,
0.0014214948751032352,
-0.0026249277871102095,
0.03386493772268295,
0.006650147028267384,
-0.03330409526824951,
0.06936164200305939,
0.044951096177101135,
0.022129686549305916,
-0.1214214637875557,
0.08364838361740112,
0.03184809163212776,
-0.1340590864419937,
0.005458024330437183,
0.14486032724380493,
-0.09488833695650101,
-0.1212637647986412,
-0.05532204732298851,
0.13449321687221527,
-0.15203428268432617,
-0.03600247949361801,
-0.06537377089262009,
-0.15325216948986053,
0.07244660705327988,
0.23004642128944397,
0.06766367703676224,
0.0722167119383812,
-0.05576855316758156,
-0.037363357841968536,
-0.021482380107045174,
0.05143032222986221,
-0.038703784346580505,
0.029940683394670486,
-0.07899846881628036,
0.011966126039624214,
-0.008384913206100464,
0.11179425567388535,
-0.08318732678890228,
-0.03268550708889961,
-0.15345735847949982,
0.028401635587215424,
-0.16464559733867645,
-0.03010667860507965,
-0.07354193925857544,
-0.04273228347301483,
-0.010254187509417534,
-0.03200434148311615,
-0.06440943479537964,
-0.05187966302037239,
-0.11115317791700363,
0.018717437982559204,
-0.026717666536569595,
0.05414443835616112,
-0.10629753768444061,
-0.02479478530585766,
0.056412309408187866,
-0.024381373077630997,
0.11780981719493866,
0.05188882350921631,
-0.0643557757139206,
0.1006055474281311,
-0.14834536612033844,
-0.04084670543670654,
0.11034949868917465,
0.04234158620238304,
0.03706766292452812,
0.07794460654258728,
0.006999630481004715,
0.06890895217657089,
0.03245672211050987,
0.057455819100141525,
0.00458263885229826,
-0.13496269285678864,
0.012408832088112831,
-0.058697305619716644,
-0.12725429236888885,
-0.04473007842898369,
-0.01679570972919464,
0.045411448925733566,
0.021434012800455093,
0.12062337249517441,
-0.042200516909360886,
0.06068318337202072,
-0.08414644002914429,
0.037729017436504364,
0.012921998277306557,
-0.17059104144573212,
-0.026352936401963234,
-0.07622009515762329,
-0.002706872997805476,
-0.02803128771483898,
0.2630847096443176,
0.04381776973605156,
-0.08900124579668045,
0.03224717080593109,
0.05492182821035385,
-0.008363338187336922,
0.017516788095235825,
0.2484036087989807,
0.08249928802251816,
-0.022138342261314392,
-0.11759085208177567,
0.06178658455610275,
0.013385627418756485,
0.05200238898396492,
0.13279780745506287,
0.07695559412240982,
-0.052332937717437744,
0.09701516479253769,
0.08409374952316284,
0.0308678038418293,
-0.06917218118906021,
-0.022152358666062355,
0.004765098914504051,
0.09347886592149734,
-0.02393520064651966,
0.14019671082496643,
0.17846524715423584,
-0.03603784739971161,
0.04373898357152939,
-0.00621609203517437,
-0.050146084278821945,
-0.16855116188526154,
-0.19405977427959442,
-0.06456350535154343,
-0.06601566821336746,
0.012735612690448761,
-0.08550923317670822,
0.019592391327023506,
0.05895513668656349,
0.06941568106412888,
-0.0647730752825737,
0.07013055682182312,
0.052673619240522385,
-0.05570954084396362,
0.05110829323530197,
0.0010500869248062372,
0.029165305197238922,
-0.08896631747484207,
0.005618681199848652,
-0.08382841944694519,
-0.0042207855731248856,
-0.055005040019750595,
0.059182412922382355,
-0.010629219934344292,
0.019023792818188667,
-0.13699083030223846,
-0.0909036248922348,
-0.04093699902296066,
0.0483621247112751,
0.013117406517267227,
0.12795469164848328,
-0.0033036405220627785,
-0.040087636560201645,
0.02981376275420189,
0.1803569793701172,
-0.05351847782731056,
-0.05289231613278389,
0.01554904691874981,
0.1486639827489853,
0.011139431968331337,
0.09067005664110184,
-0.0248284712433815,
0.004626283887773752,
-0.06582119315862656,
0.3522948920726776,
0.3192991018295288,
-0.09400618076324463,
0.02935604937374592,
0.039314452558755875,
0.035863980650901794,
0.07748065143823624,
0.11704506725072861,
0.08235106617212296,
0.30268627405166626,
-0.06567348539829254,
-0.049142662435770035,
-0.050101637840270996,
0.0014299519825726748,
-0.11453582346439362,
0.11240015923976898,
0.05004330351948738,
-0.07186486572027206,
-0.042020924389362335,
0.06973446905612946,
-0.21906544268131256,
0.057811155915260315,
-0.03008376434445381,
-0.18736004829406738,
-0.0655287429690361,
-0.020010123029351234,
0.15890468657016754,
-0.026142751798033714,
0.04256435111165047,
-0.037668246775865555,
-0.06875821948051453,
0.002715082373470068,
0.010657360777258873,
-0.22895170748233795,
0.05085567384958267,
0.04231465235352516,
-0.036872051656246185,
0.01739424653351307,
-0.0255917739123106,
0.043597299605607986,
0.07961180061101913,
0.054578252136707306,
-0.0306621752679348,
0.06312068551778793,
0.030050603672862053,
-0.0598771758377552,
0.025385657325387,
0.0020102933049201965,
0.020546572282910347,
-0.06677628308534622,
0.06397807598114014,
-0.030454371124505997,
0.04771936684846878,
-0.08164738863706589,
-0.08050000667572021,
-0.01697513833642006,
0.011647358536720276,
-0.06275404244661331,
0.06098377704620361,
0.06221199780702591,
0.001119570224545896,
-0.025570278987288475,
-0.06892856955528259,
-0.02385849691927433,
0.017720503732562065,
-0.10769002884626389,
-0.07398076355457306,
-0.0925418809056282,
-0.07463579624891281,
0.06734909862279892,
0.00022357380657922477,
-0.26523536443710327,
-0.007066152524203062,
-0.08694779127836227,
0.03730125352740288,
-0.19184811413288116,
0.04853439703583717,
0.16445665061473846,
0.013154867105185986,
-0.020962286740541458,
-0.09718240797519684,
0.04145117476582527,
0.03852356597781181,
-0.13411840796470642,
-0.07231267541646957
] |
null | null | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
```
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarLander-v2"}, "metrics": [{"type": "mean_reward", "value": "258.86 +/- 34.40", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | tahsinkheya/ppo-LunarLander-v2 | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | 2024-02-09T03:30:38+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
39,
41,
17
] | [
"passage: TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
0.03942384943366051,
0.04900386184453964,
-0.005304091144353151,
0.026427261531352997,
0.107408307492733,
-0.026511888951063156,
0.11188238859176636,
0.0814051404595375,
0.10722193866968155,
0.04762078449130058,
0.08338645845651627,
0.06030960753560066,
0.05080918222665787,
0.2571701407432556,
0.04754156619310379,
-0.22987541556358337,
0.036159250885248184,
-0.04869936779141426,
0.12395193427801132,
0.07178173214197159,
-0.0038484656251966953,
-0.06485428661108017,
0.020415637642145157,
-0.013290755450725555,
0.05367108806967735,
0.04282612353563309,
-0.01716216839849949,
-0.08207534998655319,
0.07169748842716217,
-0.06345846503973007,
0.06986866891384125,
0.07677983492612839,
0.13218913972377777,
-0.17832116782665253,
0.029566360637545586,
0.02571309357881546,
-0.07189024239778519,
0.01342033501714468,
0.008019951172173023,
0.05120139941573143,
0.17303818464279175,
0.019879888743162155,
0.07844575494527817,
-0.0025605305563658476,
-0.15412317216396332,
-0.018950799480080605,
0.0436202734708786,
0.12546207010746002,
0.08808347582817078,
0.04605821147561073,
0.01970590092241764,
0.17503218352794647,
-0.054352790117263794,
-0.028833400458097458,
0.21759237349033356,
-0.2881564497947693,
-0.031460098922252655,
0.321048766374588,
0.06997483223676682,
0.09725230932235718,
-0.07540661096572876,
-0.03619609400629997,
0.007783263456076384,
-0.013137873262166977,
-0.028666524216532707,
-0.07447073608636856,
0.17313385009765625,
0.05152064561843872,
-0.05057951435446739,
-0.09541505575180054,
0.16948209702968597,
0.006921638268977404,
0.0018855923553928733,
-0.019282981753349304,
0.009060598909854889,
0.07402525842189789,
-0.016097044572234154,
-0.07255112379789352,
0.057438433170318604,
0.05330665782094002,
0.019649166613817215,
-0.1435653269290924,
-0.10762494057416916,
-0.022740179672837257,
-0.008012006990611553,
0.17786912620067596,
-0.009255532175302505,
0.042902372777462006,
0.003065188182517886,
0.10384012013673782,
-0.12480384111404419,
-0.03354184702038765,
-0.0454259067773819,
-0.07565800100564957,
-0.0223417766392231,
-0.02058211714029312,
-0.03580251708626747,
0.07184842973947525,
0.11971849203109741,
0.027368178591132164,
0.09350208193063736,
0.047715865075588226,
-0.03206788748502731,
0.06343851238489151,
0.05555703118443489,
0.14222665131092072,
0.05807621404528618,
0.012854371219873428,
0.13179877400398254,
0.055213116109371185,
0.033023182302713394,
-0.0613492950797081,
-0.18252409994602203,
0.07489913702011108,
-0.07031869143247604,
0.007941240444779396,
0.12051256000995636,
-0.04480670019984245,
-0.1183447614312172,
-0.037500523030757904,
-0.017392054200172424,
-0.06224250793457031,
-0.025395862758159637,
0.0547584593296051,
-0.02883218228816986,
-0.03973718360066414,
0.0011496668448671699,
0.09384800493717194,
0.00953749567270279,
-0.1752052903175354,
0.03303423151373863,
-0.025042934343218803,
-0.10782608389854431,
0.009975161403417587,
0.0022444494534283876,
0.03394931182265282,
0.04408763721585274,
-0.11822668462991714,
-0.30899152159690857,
-0.07652641832828522,
0.05490870401263237,
-0.06516939401626587,
-0.18425025045871735,
-0.13193942606449127,
0.02454492449760437,
-0.09037084132432938,
-0.044885024428367615,
-0.12759265303611755,
-0.028549788519740105,
0.01743689924478531,
0.011519349180161953,
0.10758619755506516,
-0.0106219332665205,
-0.012188062071800232,
-0.1571401208639145,
0.008273907005786896,
-0.20951123535633087,
0.0890483483672142,
-0.019150104373693466,
0.037884220480918884,
-0.032381169497966766,
-0.07404014468193054,
0.030707746744155884,
0.052499737590551376,
-0.01474119070917368,
0.13510210812091827,
-0.15592676401138306,
-0.03691192343831062,
-0.007996266707777977,
-0.13611900806427002,
-0.04786273464560509,
-0.10358831286430359,
-0.04357128217816353,
0.13354332745075226,
0.018664736300706863,
0.15356586873531342,
-0.08709818124771118,
-0.0722038671374321,
0.20489206910133362,
-0.010411538183689117,
-0.12820468842983246,
-0.076752208173275,
0.10165707021951675,
0.021510310471057892,
-0.056606587022542953,
-0.02523270808160305,
-0.1839766949415207,
-0.0152357779443264,
-0.04550420492887497,
-0.047039128839969635,
0.01796751655638218,
-0.010888241231441498,
0.13837894797325134,
0.08494598418474197,
0.05018039792776108,
-0.06086122244596481,
-0.006730288732796907,
0.10779471695423126,
0.08823856711387634,
0.008680110797286034,
0.023406028747558594,
-0.05774238705635071,
0.09552932530641556,
-0.04003755748271942,
-0.0142367510125041,
-0.08283266425132751,
-0.036246106028556824,
-0.026256313547492027,
0.17507147789001465,
0.09440762549638748,
0.2257927656173706,
0.09567736834287643,
0.039160262793302536,
0.031270865350961685,
-0.13181598484516144,
-0.1425403207540512,
-0.0017254541162401438,
0.09020978957414627,
-0.14270411431789398,
-0.04119925573468208,
-0.08974775671958923,
-0.17768175899982452,
-0.12202505767345428,
0.0006432619411498308,
-0.17960017919540405,
0.06390921026468277,
0.05408334732055664,
-0.035177867859601974,
0.03272094577550888,
0.13032332062721252,
-0.011533179320394993,
-0.03967514634132385,
0.0831870287656784,
0.0379033200442791,
-0.041234664618968964,
-0.021742934361100197,
0.11885567009449005,
0.15673065185546875,
0.13124459981918335,
-0.03511447086930275,
0.004914294462651014,
0.07076404243707657,
-0.02309088408946991,
0.06539414077997208,
0.0558244064450264,
0.20973342657089233,
0.188301220536232,
0.038996949791908264,
0.008822928182780743,
-0.07048165798187256,
0.0855446457862854,
-0.0742373839020729,
-0.14302679896354675,
-0.05579735338687897,
0.08729292452335358,
0.016605578362941742,
0.023469142615795135,
0.08711627870798111,
0.024545932188630104,
0.09132762253284454,
0.15968108177185059,
0.01990218088030815,
-0.09659269452095032,
-0.050218869000673294,
0.01175848301500082,
0.027713103219866753,
0.04794301092624664,
-0.04514073207974434,
-0.00937939714640379,
0.017020760104060173,
-0.10303554683923721,
0.031789086759090424,
-0.1413339376449585,
-0.1358717679977417,
0.044326696544885635,
0.003906996920704842,
0.010907664895057678,
0.02786896750330925,
-0.0038291432429105043,
0.019039705395698547,
0.04351753741502762,
-0.06975466758012772,
0.047416772693395615,
-0.024745507165789604,
-0.020031947642564774,
0.03340689837932587,
-0.057257164269685745,
-0.205775648355484,
-0.17696654796600342,
0.00013708483311347663,
-0.09910997003316879,
0.10194740444421768,
0.018308809027075768,
-0.12373185902833939,
0.047737859189510345,
-0.05822649225592613,
0.027574289590120316,
-0.01875593699514866,
-0.049130141735076904,
0.10507171601057053,
0.1525275856256485,
-0.016146350651979446,
0.018018173053860664,
-0.04865182936191559,
-0.10157987475395203,
-0.19632206857204437,
0.0691583976149559,
0.04680244252085686,
0.014610917307436466,
0.10669491440057755,
0.018072687089443207,
0.02367905154824257,
-0.007674071006476879,
-0.016521066427230835,
-0.011659215204417706,
-0.08781040459871292,
0.31909599900245667,
0.04510033503174782,
-0.025173069909214973,
0.02041010931134224,
-0.0043001663871109486,
-0.028083480894565582,
0.03263787180185318,
-0.0985708013176918,
-0.07548979669809341,
-0.08774089068174362,
-0.04367410019040108,
-0.09784720093011856,
0.053299110382795334,
0.05916472524404526,
0.003188040340319276,
-0.07727594673633575,
0.04221395403146744,
0.11369874328374863,
-0.0923808291554451,
-0.07137343287467957,
0.07477962225675583,
0.0972946360707283,
-0.07331304252147675,
0.00012658814375754446,
0.00874367356300354,
0.023951783776283264,
0.037102166563272476,
0.06778035312891006,
-0.03966575115919113,
0.08589404821395874,
-0.19917890429496765,
0.0372927263379097,
0.106058269739151,
0.023754918947815895,
0.0638108178973198,
0.07643651217222214,
-0.1058402881026268,
-0.008500572293996811,
-0.032518330961465836,
-0.21341575682163239,
0.1668180525302887,
0.1355515867471695,
0.06788124144077301,
-0.025637222453951836,
-0.00461410591378808,
-0.0649740919470787,
0.05773647129535675,
0.02723747305572033,
-0.14758841693401337,
0.004883295856416225,
0.06064270809292793,
0.026899009943008423,
0.01614922471344471,
0.07971042394638062,
0.014697225764393806,
-0.1801026314496994,
-0.014406266622245312,
0.10730406641960144,
0.002390873385593295,
0.0053148469887673855,
-0.03175045922398567,
-0.1755964607000351,
0.0751047357916832,
0.004285442177206278,
0.07233936339616776,
-0.1676585078239441,
0.14297930896282196,
-0.10089799761772156,
0.07726949453353882,
-0.004285062663257122,
-0.021311495453119278,
0.02507244050502777,
-0.0541163794696331,
0.15163759887218475,
0.01058570109307766,
-0.021810131147503853,
-0.1200498715043068,
-0.1717042326927185,
-0.019227758049964905,
-0.11788936704397202,
-0.11679866164922714,
0.050424277782440186,
0.062185097485780716,
0.04923136904835701,
-0.061147067695856094,
0.1518532931804657,
-0.047422297298908234,
0.060713399201631546,
-0.06893875449895859,
-0.06755045056343079,
0.03764858841896057,
-0.12588608264923096,
-0.08176055550575256,
0.05573027580976486,
0.19166934490203857,
0.15833087265491486,
-0.02816431224346161,
-0.03472423925995827,
-0.047419581562280655,
-0.006212298292666674,
-0.007802055217325687,
0.0275666993111372,
0.023223137483000755,
0.07315318286418915,
-0.07681374251842499,
-0.11649256944656372,
0.033787861466407776,
-0.06713802367448807,
-0.055589709430933,
-0.015439179725944996,
0.1513158082962036,
0.04671623185276985,
0.07720734924077988,
-0.018946662545204163,
0.03887668624520302,
-0.001724981120787561,
-0.056474871933460236,
0.16197094321250916,
0.03885216265916824,
-0.05193585529923439,
0.06837689876556396,
0.053174007683992386,
0.043745119124650955,
0.03011113777756691,
-0.026783017441630363,
0.206032395362854,
0.1980147808790207,
0.014206883497536182,
0.2175983190536499,
0.03177616000175476,
-0.03772832080721855,
-0.1300560086965561,
-0.065880686044693,
-0.006372632458806038,
0.03559038043022156,
0.08070417493581772,
-0.18207235634326935,
-0.015011128038167953,
-0.05689644813537598,
-0.034518610686063766,
-0.15059494972229004,
-0.28553900122642517,
-0.05957856774330139,
0.20075850188732147,
0.14706264436244965,
0.27519428730010986,
-0.10432573407888412,
0.035197313874959946,
0.02663275972008705,
-0.04912831634283066,
-0.006501141935586929,
0.00018665487004909664,
0.10268618166446686,
-0.15421873331069946,
0.1176437959074974,
0.08486983180046082,
-0.019002694636583328,
0.01058861706405878,
-0.1619086116552353,
0.00936629343777895,
-0.12191236019134521,
0.05354422330856323,
0.1400289237499237,
-0.048128653317689896,
-0.054873593151569366,
0.14033560454845428,
-0.024562934413552284,
-0.22685599327087402,
-0.04648222774267197,
-0.043600670993328094,
-0.010640020482242107,
0.026607351377606392,
-0.1013401448726654,
0.04101909324526787,
0.1330099105834961,
0.009380043484270573,
0.1147187277674675,
0.11749245226383209,
-0.052566803991794586,
0.10792597383260727,
0.2257719188928604,
-0.018785694614052773,
0.04689010605216026,
-0.12743118405342102,
-0.0012336712097749114,
-0.028270328417420387,
0.013657891191542149,
-0.09504974633455276,
-0.09938385337591171,
0.02366873063147068,
0.02872389927506447,
0.009118586778640747,
0.0921793207526207,
-0.029922157526016235,
0.0759170651435852,
0.06817561388015747,
-0.13014446198940277,
-0.16288450360298157,
0.015828335657715797,
-0.007344507612287998,
0.08354310691356659,
0.00027861111448146403,
0.08878035843372345,
-0.11932205408811569,
-0.018093237653374672,
-0.03153328225016594,
-0.03319635987281799,
-0.130486860871315,
-0.07138993591070175,
0.06156524643301964,
0.028095467016100883,
-0.06602972000837326,
0.1398407518863678,
0.026440169662237167,
0.15942534804344177,
0.049197953194379807,
0.012499804608523846,
0.07227300107479095,
-0.05345509201288223,
0.1283530443906784,
0.13818155229091644,
-0.00868943240493536,
-0.05460423603653908,
-0.1013643890619278,
-0.10236792266368866,
0.08925779908895493,
-0.05773641914129257,
0.07476430386304855,
-0.14885357022285461,
-0.06675903499126434,
0.015772046521306038,
0.016141414642333984,
-0.09562095999717712,
0.02571965754032135,
-0.01625603251159191,
-0.18119946122169495,
0.056570518761873245,
-0.048285093158483505,
0.0440407395362854,
-0.06347788125276566,
-0.1110161691904068,
-0.17226378619670868,
0.06091433763504028,
0.08593481779098511,
-0.053876690566539764,
-0.12229149043560028,
0.011023230850696564,
-0.00012518465518951416,
-0.06341652572154999,
-0.05023367330431938,
0.09722746908664703,
-0.11020902544260025,
0.031452205032110214,
-0.012567701749503613,
0.08853451162576675,
-0.03510405123233795,
-0.011538895778357983,
0.044220831245183945,
-0.08039166033267975,
-0.009481523185968399,
0.03534642979502678,
-0.026372017338871956,
-0.04127239063382149,
-0.2689029574394226,
0.0036654395516961813,
0.0341104120016098,
0.02497158572077751,
0.07856601476669312,
0.011906822212040424,
0.021174922585487366,
0.03993808850646019,
-0.15396519005298615,
-0.013395369984209538,
0.14574195444583893,
-0.07689505815505981,
-0.022186370566487312,
0.05703273415565491,
-0.09054436534643173,
0.013882770203053951,
-0.030287226662039757,
0.1345842480659485,
0.023923413828015327,
0.06404478847980499,
-0.0851147472858429,
0.10106813907623291,
-0.1451139897108078,
-0.04998219385743141,
-0.01244612317532301,
0.09761348366737366,
0.07019034773111343,
-0.10272270441055298,
0.014697125181555748,
0.04210108891129494,
0.19416837394237518,
0.016384804621338844,
-0.0356343574821949,
-0.03396720811724663,
0.004015897400677204,
0.22076453268527985,
0.03044266067445278,
0.10457023978233337,
0.07281364500522614,
-0.026583973318338394,
0.12624378502368927,
0.09929762035608292,
0.11280370503664017,
-0.055645186454057693,
0.13904185593128204,
0.04667386785149574,
0.038641396909952164,
0.0614289753139019,
0.06836545467376709,
0.09098632633686066,
-0.0008288522367365658,
0.1138714924454689,
0.013811973854899406,
-0.02422109805047512,
-0.021335409954190254,
0.17759373784065247,
0.10501719266176224,
-0.14769648015499115,
0.029047364369034767,
-0.01258957851678133,
0.039933037012815475,
-0.014194529503583908,
-0.15634691715240479,
-0.07240267097949982,
-0.3315149247646332,
0.1226184144616127,
-0.07119352370500565,
0.019930170848965645,
0.007913772016763687,
-0.037425633519887924,
-0.03296699747443199,
-0.04477746784687042,
0.13151589035987854,
-0.013641550205647945,
-0.006079165264964104,
-0.04815853759646416,
-0.015360191464424133,
-0.11607866734266281,
-0.11200575530529022,
-0.013207737356424332,
-0.13671602308750153,
-0.010119039565324783,
0.05595948174595833,
0.003977729007601738,
0.01821410097181797,
-0.03142618387937546,
0.0024383175186812878,
0.06541839241981506,
-0.05751744285225868,
0.056182678788900375,
0.12097269296646118,
0.08766137808561325,
-0.1058853268623352,
0.031048951670527458,
0.2011747509241104,
0.04359564557671547,
-0.12483977526426315,
0.01449228823184967,
0.1819491684436798,
0.004885740112513304,
0.017068125307559967,
-0.006097703706473112,
-0.0540788508951664,
-0.07554277032613754,
0.1251034289598465,
0.08296554535627365,
-0.09985227137804031,
0.015833314508199692,
-0.0726347416639328,
-0.01594804972410202,
-0.06374675035476685,
0.10130585730075836,
0.09538925439119339,
0.04440245032310486,
-0.10621760785579681,
-0.08487539738416672,
-0.10891728103160858,
0.040588874369859695,
-0.08629853278398514,
-0.07311757653951645,
0.09629398584365845,
-0.07057105004787445,
-0.07029950618743896,
0.025521177798509598,
-0.17978744208812714,
-0.009467960335314274,
0.1711762249469757,
-0.24654000997543335,
-0.0916430801153183,
-0.10857923328876495,
0.14477859437465668,
0.016497576609253883,
0.1013975441455841,
-0.006207061931490898,
-0.007889035157859325,
-0.20577777922153473,
0.024890204891562462,
-0.05293011665344238,
-0.02073732763528824,
0.07814782857894897,
-0.09476397186517715,
0.22629831731319427,
-0.08276885002851486,
0.020940175279974937,
0.012659613974392414,
0.0870661810040474,
-0.030675338581204414,
0.09283176809549332,
-0.03660329803824425,
-0.12576518952846527,
-0.03620953485369682,
0.03001813031733036,
0.013904244638979435,
0.10071761906147003,
0.09772487729787827,
-0.03414725139737129,
0.03389119729399681,
0.09747414290904999,
0.04172342270612717,
-0.023843804374337196,
0.0360250361263752,
-0.17077107727527618,
0.02182629331946373,
-0.018498148769140244,
-0.06935930997133255,
0.03687669709324837,
-0.06603235751390457,
0.1639697551727295,
0.04022442549467087,
0.0670473501086235,
-0.036152735352516174,
0.0073931049555540085,
-0.014454689808189869,
-0.013775371946394444,
-0.026180334389209747,
-0.17259705066680908,
-0.10422050207853317,
-0.1347656100988388,
-0.012701659463346004,
-0.034971047192811966,
0.04591470584273338,
0.023234914988279343,
-0.0003200018545612693,
-0.014577031135559082,
-0.12090865522623062,
0.04360328987240791,
0.11146783083677292,
-0.04631396010518074,
-0.026193076744675636
] |
null | null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BOLETIN_8bit_13
This model is a fine-tuned version of [bertin-project/BOLETIN](https://huggingface.co/bertin-project/BOLETIN) on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.41e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 | {"license": "openrail", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "bertin-project/BOLETIN", "model-index": [{"name": "BOLETIN_8bit_13", "results": []}]} | null | versae/BOLETIN_8bit_13 | [
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:bertin-project/BOLETIN",
"license:openrail",
"region:us"
] | 2024-02-09T03:32:49+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #base_model-bertin-project/BOLETIN #license-openrail #region-us
|
# BOLETIN_8bit_13
This model is a fine-tuned version of bertin-project/BOLETIN on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.41e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 | [
"# BOLETIN_8bit_13\n\nThis model is a fine-tuned version of bertin-project/BOLETIN on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1.41e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3\n- mixed_precision_training: Native AMP",
"### Training results",
"### Framework versions\n\n- PEFT 0.7.1\n- Transformers 4.37.2\n- Pytorch 2.2.0+cu121\n- Datasets 2.14.6\n- Tokenizers 0.15.1"
] | [
"TAGS\n#peft #tensorboard #safetensors #generated_from_trainer #base_model-bertin-project/BOLETIN #license-openrail #region-us \n",
"# BOLETIN_8bit_13\n\nThis model is a fine-tuned version of bertin-project/BOLETIN on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1.41e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3\n- mixed_precision_training: Native AMP",
"### Training results",
"### Framework versions\n\n- PEFT 0.7.1\n- Transformers 4.37.2\n- Pytorch 2.2.0+cu121\n- Datasets 2.14.6\n- Tokenizers 0.15.1"
] | [
44,
35,
6,
12,
8,
3,
104,
4,
39
] | [
"passage: TAGS\n#peft #tensorboard #safetensors #generated_from_trainer #base_model-bertin-project/BOLETIN #license-openrail #region-us \n# BOLETIN_8bit_13\n\nThis model is a fine-tuned version of bertin-project/BOLETIN on an unknown dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1.41e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3\n- mixed_precision_training: Native AMP### Training results### Framework versions\n\n- PEFT 0.7.1\n- Transformers 4.37.2\n- Pytorch 2.2.0+cu121\n- Datasets 2.14.6\n- Tokenizers 0.15.1"
] | [
-0.12494830787181854,
0.11085519939661026,
-0.0018354286439716816,
0.06741254776716232,
0.1299133002758026,
-0.010500965639948845,
0.11313387751579285,
0.09417149424552917,
-0.08437430113554001,
0.10026879608631134,
0.09201143682003021,
-0.003715852042660117,
0.05449405312538147,
0.15591663122177124,
-0.010537269525229931,
-0.2830413281917572,
0.019132142886519432,
0.019681284204125404,
-0.06127852946519852,
0.09063136577606201,
0.11485759913921356,
-0.08572383224964142,
0.04739495366811752,
0.043541599065065384,
-0.15168015658855438,
0.0363200418651104,
-0.031503792852163315,
-0.06794677674770355,
0.07738351076841354,
0.03941844403743744,
0.1252373307943344,
-0.002977862488478422,
0.09158031642436981,
-0.1863865852355957,
0.009761635214090347,
0.07714885473251343,
0.053336724638938904,
0.10304021090269089,
0.09575146436691284,
0.04728962853550911,
0.10531716048717499,
-0.09740518033504486,
0.09470982104539871,
0.03695479407906532,
-0.06860050559043884,
-0.19065521657466888,
-0.0967174544930458,
0.14577019214630127,
0.07132121175527573,
0.07166741043329239,
0.004597447346895933,
0.1400255560874939,
-0.06585423648357391,
0.058279529213905334,
0.21565914154052734,
-0.270227313041687,
-0.10169237107038498,
0.024533700197935104,
0.08046291023492813,
0.06532484292984009,
-0.11328276246786118,
-0.04500109702348709,
0.0852905884385109,
0.03153703734278679,
0.062196679413318634,
0.015375619754195213,
-0.014614276587963104,
-0.026818759739398956,
-0.16148348152637482,
-0.013997367583215237,
0.1789935976266861,
0.07521069794893265,
-0.07570470124483109,
-0.08732325583696365,
-0.030529357492923737,
-0.12963837385177612,
-0.026716044172644615,
-0.026246724650263786,
0.012204539962112904,
-0.03999004140496254,
-0.035755455493927,
-0.061142683029174805,
-0.0867101326584816,
-0.07075008749961853,
0.023271404206752777,
0.1452185958623886,
0.06461449712514877,
0.007582305930554867,
-0.03267647325992584,
0.09452984482049942,
-0.011539829894900322,
-0.09235300868749619,
-0.004478810355067253,
-0.0323789156973362,
-0.022099029272794724,
-0.06139492616057396,
-0.031229443848133087,
-0.023708676919341087,
0.007859993726015091,
0.1453375220298767,
-0.11663733422756195,
0.07099681347608566,
-0.0008833635365590453,
0.0374460369348526,
-0.035084642469882965,
0.12009891122579575,
-0.05853719636797905,
0.06072252243757248,
0.0037113234866410494,
0.10676747560501099,
0.000051828130381181836,
0.00875219888985157,
-0.07168810069561005,
-0.01185845397412777,
0.08640004694461823,
0.046150557696819305,
-0.04654381796717644,
-0.008038715459406376,
-0.0415789969265461,
-0.03191636502742767,
0.05773400142788887,
-0.10999405384063721,
0.0371650829911232,
-0.0025787947233766317,
-0.07266246527433395,
0.03687063977122307,
0.026531310752034187,
0.010109205730259418,
-0.024057554081082344,
0.08528179675340652,
-0.10710866004228592,
-0.019907791167497635,
-0.10238733887672424,
-0.06746137887239456,
0.03483423590660095,
-0.021720675751566887,
-0.004483726341277361,
-0.1067354679107666,
-0.1439170241355896,
-0.02466156706213951,
0.029384519904851913,
-0.053717128932476044,
-0.07931225001811981,
-0.005935767665505409,
-0.06526074558496475,
0.02029913105070591,
-0.026061540469527245,
0.14166072010993958,
-0.022402407601475716,
0.08974625915288925,
-0.0008179766591638327,
-0.0021722291130572557,
-0.024932462722063065,
0.02920197695493698,
-0.05904928594827652,
0.05370475351810455,
-0.10140251368284225,
0.02460346929728985,
-0.12188103049993515,
0.047855667769908905,
-0.1244010180234909,
-0.12030328065156937,
-0.039253123104572296,
-0.010461484082043171,
0.10892917215824127,
0.10463374853134155,
-0.10279158502817154,
-0.03360456973314285,
0.16698740422725677,
-0.1007004827260971,
-0.10129524022340775,
0.11037494242191315,
-0.021880390122532845,
0.02171105518937111,
0.04262484982609749,
0.14878466725349426,
0.10534441471099854,
-0.15260548889636993,
-0.017131101340055466,
0.013467480428516865,
0.10372614115476608,
-0.030096719041466713,
0.08510448783636093,
-0.022093521431088448,
-0.06551889330148697,
0.01620030216872692,
-0.017693640664219856,
0.02638782374560833,
-0.10513195395469666,
-0.06462497264146805,
-0.042693059891462326,
-0.09209080040454865,
0.04712771624326706,
0.02247493900358677,
0.046078506857156754,
-0.07095365971326828,
-0.11816249042749405,
0.13268853724002838,
0.14227741956710815,
-0.03358009085059166,
0.013180097565054893,
-0.07039808481931686,
0.074570432305336,
-0.05827679485082626,
-0.045249540358781815,
-0.1666516214609146,
-0.11102897673845291,
0.04802752286195755,
-0.08357067406177521,
0.010111721232533455,
-0.008225747384130955,
0.05376780033111572,
0.07823003828525543,
-0.027301684021949768,
-0.04067463427782059,
-0.1229475736618042,
-0.01585247553884983,
-0.11548519879579544,
-0.17370092868804932,
-0.07188499718904495,
-0.032639846205711365,
0.1335645467042923,
-0.2558857798576355,
0.023966174572706223,
-0.02428874373435974,
0.1537926197052002,
0.03562911972403526,
-0.05942615494132042,
-0.01330499816685915,
0.06981546431779861,
-0.00442956667393446,
-0.06890904903411865,
0.03710819035768509,
0.026521164923906326,
-0.07708760350942612,
-0.05176256224513054,
-0.09445478767156601,
0.07107758522033691,
0.06570107489824295,
0.07717423886060715,
-0.0902714729309082,
-0.09003695845603943,
-0.102544866502285,
-0.03836638480424881,
-0.05291295051574707,
-0.014891626313328743,
0.13061963021755219,
0.017054038122296333,
0.1473574936389923,
-0.09879623353481293,
-0.05728858709335327,
0.024843724444508553,
-0.027030544355511665,
-0.03239928558468819,
0.09776947647333145,
0.09292734414339066,
-0.04160507768392563,
0.09627871215343475,
0.06158631294965744,
-0.08730240911245346,
0.15765219926834106,
-0.06288226693868637,
-0.12346446514129639,
-0.005349212791770697,
0.05701437219977379,
0.011794022284448147,
0.14212413132190704,
-0.07754157483577728,
0.021979399025440216,
0.02467045933008194,
0.016176827251911163,
0.06571776419878006,
-0.17217768728733063,
-0.0136821698397398,
0.0009632366127334535,
-0.011954432353377342,
-0.011746424250304699,
0.004641811829060316,
0.013629513792693615,
0.08994191139936447,
0.03168168663978577,
-0.011687500402331352,
0.006576351821422577,
0.009271930903196335,
-0.08313179761171341,
0.18817457556724548,
-0.10519400984048843,
-0.12960204482078552,
-0.167192742228508,
0.0453546941280365,
-0.0413287878036499,
-0.043665286153554916,
0.018028419464826584,
-0.07874339073896408,
-0.04252349212765694,
-0.08682353794574738,
-0.024304863065481186,
-0.08394075185060501,
0.0034113219007849693,
0.04981716722249985,
0.008258458226919174,
0.12972548604011536,
-0.12362752854824066,
0.023179173469543457,
-0.009787673130631447,
-0.0636243000626564,
-0.0186129380017519,
0.037589091807603836,
0.09239695966243744,
0.11221495270729065,
-0.0015711805317550898,
0.018162833526730537,
-0.041444938629865646,
0.22769612073898315,
-0.04880483075976372,
-0.03177059814333916,
0.1243739202618599,
0.011564487591385841,
0.06955555081367493,
0.07499318569898605,
0.0601460263133049,
-0.07749967277050018,
0.049615681171417236,
0.07570772618055344,
-0.019033348187804222,
-0.25692933797836304,
-0.042474884539842606,
-0.031660474836826324,
-0.03479446470737457,
0.11516067385673523,
0.07065559178590775,
-0.002332919044420123,
0.0687294527888298,
-0.02878187969326973,
0.055139005184173584,
-0.05422035604715347,
0.11103254556655884,
0.07036255300045013,
0.021234605461359024,
0.08472202718257904,
-0.03059982880949974,
-0.026658104732632637,
0.06180934980511665,
0.0038832041900604963,
0.2474580854177475,
-0.008430268615484238,
0.06647802889347076,
0.06689488142728806,
0.17012310028076172,
0.007863695733249187,
0.04028501734137535,
-0.007810225710272789,
-0.018247943371534348,
0.02649664506316185,
-0.07012148946523666,
-0.006518655456602573,
0.03331685811281204,
-0.04196345806121826,
0.0905221551656723,
-0.1202620267868042,
-0.012119066901504993,
-0.020280689001083374,
0.2717815041542053,
0.028754809871315956,
-0.2933187484741211,
-0.0972050130367279,
0.0003195549361407757,
-0.0531616136431694,
-0.10366545617580414,
0.03871592506766319,
0.10728541016578674,
-0.11508982628583908,
0.027113527059555054,
-0.0663759633898735,
0.1167106181383133,
0.00674715731292963,
-0.02635612152516842,
0.044872164726257324,
0.1478094607591629,
-0.01928413100540638,
0.09011664986610413,
-0.1963978260755539,
0.22154471278190613,
0.0030298412311822176,
0.09932556003332138,
-0.011188370175659657,
0.04174407571554184,
0.0052161309868097305,
0.052752137184143066,
0.08035025745630264,
-0.004594616591930389,
0.010639036074280739,
-0.19946828484535217,
-0.10337264835834503,
0.029843294993042946,
0.09795840084552765,
-0.02280011773109436,
0.075673907995224,
-0.0334881953895092,
0.030250564217567444,
0.032079435884952545,
-0.054440297186374664,
-0.21863530576229095,
-0.10924824327230453,
0.016286272555589676,
0.032290223985910416,
0.00424896739423275,
-0.1277216523885727,
-0.11601096391677856,
-0.04192713648080826,
0.1190059632062912,
-0.03565409034490585,
-0.049777790904045105,
-0.1316516399383545,
0.10108845680952072,
0.13378913700580597,
-0.048629336059093475,
0.028846899047493935,
-0.010251144878566265,
0.1539442092180252,
0.007448385003954172,
-0.05345407500863075,
0.05360871180891991,
-0.08486821502447128,
-0.16787347197532654,
-0.05986059457063675,
0.15618674457073212,
0.06765131652355194,
0.034977987408638,
-0.014406091533601284,
-0.008418097160756588,
-0.00020516170479822904,
-0.09267102926969528,
-0.001619420712813735,
0.07308372855186462,
0.028653305023908615,
0.024782832711935043,
-0.09828238189220428,
0.07262814790010452,
-0.031242026016116142,
-0.04012628272175789,
0.10077798366546631,
0.22385093569755554,
-0.07912983745336533,
0.038685813546180725,
0.0894317626953125,
-0.07164640724658966,
-0.13999240100383759,
0.06535781919956207,
0.16799262166023254,
0.020422307774424553,
0.014273843728005886,
-0.20348358154296875,
0.10334073752164841,
0.13721419870853424,
-0.031270503997802734,
0.09278766065835953,
-0.3027383089065552,
-0.1112951710820198,
0.08581365644931793,
0.1122906357049942,
0.016540909186005592,
-0.15511056780815125,
-0.06486105918884277,
0.0036114854738116264,
-0.10809627920389175,
0.08621471375226974,
-0.07385723292827606,
0.07498782873153687,
-0.01052035577595234,
0.09324943274259567,
0.024056166410446167,
-0.03793717548251152,
0.159086674451828,
-0.02996707335114479,
0.05994074046611786,
-0.03101625107228756,
0.05188741162419319,
0.044002607464790344,
-0.06287985295057297,
0.05796903744339943,
-0.004143013618886471,
0.0643039271235466,
-0.16322709619998932,
-0.029158756136894226,
-0.07540711760520935,
0.0782504603266716,
-0.07000946998596191,
-0.05137922614812851,
-0.0409955233335495,
0.056913308799266815,
0.012707112357020378,
-0.015233075246214867,
0.07921290397644043,
0.013781516812741756,
0.15509828925132751,
0.10641197115182877,
0.0626940056681633,
-0.024993889033794403,
-0.10799328237771988,
0.00020325960940681398,
-0.036973737180233,
0.09167470782995224,
-0.11822712421417236,
-0.006193067412823439,
0.12145160883665085,
0.03480999916791916,
0.12459125369787216,
0.03464074805378914,
-0.09566740691661835,
-0.0026038242504000664,
0.05210062861442566,
-0.09680962562561035,
-0.12866681814193726,
-0.044774919748306274,
0.14787892997264862,
-0.16449777781963348,
0.02588191255927086,
0.09585558623075485,
-0.10394967347383499,
-0.0226534903049469,
-0.0065562305971980095,
-0.006794394459575415,
-0.025954412296414375,
0.15163227915763855,
0.07007535547018051,
0.06881901621818542,
-0.04873722419142723,
0.08056975156068802,
0.07792767882347107,
-0.10260009765625,
0.03644489869475365,
0.06929516792297363,
-0.05882585421204567,
-0.005027868784964085,
0.03697136044502258,
0.1247735247015953,
-0.04241681471467018,
-0.06632675975561142,
-0.06670842319726944,
-0.09465458989143372,
0.05433965101838112,
0.09082186222076416,
0.029884299263358116,
-0.017289090901613235,
-0.015858909115195274,
0.054786063730716705,
-0.1418595314025879,
0.09629926085472107,
0.05133631080389023,
0.09219767898321152,
-0.17317774891853333,
0.10454456508159637,
0.008394979871809483,
0.019720403477549553,
-0.002217767760157585,
0.009652750566601753,
-0.10148010402917862,
-0.019400950521230698,
-0.13249805569648743,
-0.0016684804577380419,
-0.03061951883137226,
0.008906313218176365,
-0.015279032289981842,
-0.0521218441426754,
-0.05235820263624191,
0.047131430357694626,
-0.06729371100664139,
-0.04285750910639763,
0.028375759720802307,
0.07583965361118317,
-0.1067192554473877,
0.017755424603819847,
0.031039593741297722,
-0.0846857875585556,
0.05971803516149521,
0.02805224433541298,
0.04280097782611847,
0.02895757555961609,
-0.09388620406389236,
0.04258497431874275,
0.013678021728992462,
0.014059005305171013,
0.039692290127277374,
-0.07610992342233658,
-0.0029975122306495905,
-0.033331822603940964,
0.0482996441423893,
-0.002266197232529521,
0.0083694439381361,
-0.15066184103488922,
-0.08220893144607544,
-0.012026765383780003,
-0.04083238169550896,
-0.06332948058843613,
0.0401001051068306,
0.05925808846950531,
0.06074056401848793,
0.12325839698314667,
-0.08956752717494965,
0.02321837842464447,
-0.1791347861289978,
-0.014936549589037895,
-0.01689181849360466,
0.01145777478814125,
-0.02433847449719906,
-0.0224316269159317,
0.05369725450873375,
-0.04860963299870491,
0.09434161335229874,
-0.0297875814139843,
0.06036366894841194,
0.04307357221841812,
-0.10007040202617645,
-0.004448065534234047,
0.014175022952258587,
0.24210263788700104,
0.05089111253619194,
0.013732018880546093,
0.05328725278377533,
-0.018892157822847366,
0.050673339515924454,
0.07828187197446823,
0.1451539546251297,
0.15479588508605957,
-0.05994608253240585,
0.057536717504262924,
0.06475179642438889,
-0.07733774930238724,
-0.10709589719772339,
0.06962569057941437,
0.009965470992028713,
0.0965835377573967,
-0.049927838146686554,
0.1883818507194519,
0.1395631730556488,
-0.14496082067489624,
0.02179691195487976,
-0.014365497045218945,
-0.09924053400754929,
-0.11181189864873886,
-0.05229909345507622,
-0.06233987212181091,
-0.1310976892709732,
0.018220851197838783,
-0.1302272081375122,
0.010167177766561508,
0.06127391755580902,
0.02207936905324459,
0.013913976028561592,
0.15830278396606445,
0.02410878799855709,
-0.001693044207058847,
0.07873201370239258,
0.007738860789686441,
0.00883958488702774,
-0.08731462806463242,
-0.0842658206820488,
0.05830491706728935,
-0.019031252712011337,
0.052898794412612915,
-0.044976383447647095,
-0.024668820202350616,
0.03060915321111679,
0.030509155243635178,
-0.061649587005376816,
0.02994854934513569,
0.0056571741588413715,
0.03390960395336151,
0.05847851186990738,
0.028196576982736588,
-0.008280174806714058,
-0.06652121245861053,
0.26997730135917664,
-0.07193328440189362,
-0.022170651704072952,
-0.13924428820610046,
0.19721826910972595,
0.007379037328064442,
-0.02044876478612423,
0.043190378695726395,
-0.10515791922807693,
-0.024327021092176437,
0.16455914080142975,
0.08939845114946365,
-0.01692250929772854,
-0.022705653682351112,
0.004024536814540625,
-0.023058613762259483,
-0.0870434045791626,
0.13751140236854553,
0.10513272881507874,
0.06517763435840607,
-0.047581154853105545,
-0.004034274723380804,
-0.04448674991726875,
0.001187857473269105,
-0.09577782452106476,
0.06064467132091522,
0.02881619706749916,
-0.014135312288999557,
-0.057533569633960724,
0.08760834485292435,
-0.008323071524500847,
-0.13254863023757935,
0.006916310638189316,
-0.10542567074298859,
-0.18067438900470734,
-0.03736722841858864,
0.05179496854543686,
-0.011845642700791359,
0.046095579862594604,
-0.033058714121580124,
-0.0022280483972281218,
0.1267726719379425,
-0.02237331122159958,
-0.021484019234776497,
-0.1327451765537262,
0.09052100032567978,
-0.02434747852385044,
0.24534791707992554,
0.003519858466461301,
0.06585364043712616,
0.10693719983100891,
0.011406194418668747,
-0.13806672394275665,
0.006085801403969526,
0.07643279433250427,
-0.08647126704454422,
0.010392150841653347,
0.15162386000156403,
-0.02761559560894966,
0.11300023645162582,
0.015006345696747303,
-0.15330618619918823,
-0.043883148580789566,
-0.06309928745031357,
-0.01061780285090208,
-0.09414424747228622,
0.04360567778348923,
-0.07783956825733185,
0.13473810255527496,
0.18000146746635437,
-0.06960366666316986,
-0.047287821769714355,
-0.07202943414449692,
0.050980065017938614,
0.047174181789159775,
0.08414146304130554,
0.009308774955570698,
-0.22220435738563538,
0.008107815869152546,
-0.013342030346393585,
0.01884499378502369,
-0.2970673441886902,
-0.05115435644984245,
0.020372221246361732,
-0.036166854202747345,
-0.06461647152900696,
0.10432995855808258,
0.06212101876735687,
0.034098681062459946,
-0.039384737610816956,
-0.11145289987325668,
-0.06643879413604736,
0.1467885971069336,
-0.12319080531597137,
-0.03679458424448967
] |
null | null | transformers | # Lao to Vietnamese Translation Model
In the domain of natural language processing (NLP), the development of translation models tailored for low-resource languages represents a critical endeavor to facilitate cross-cultural communication and knowledge exchange. In response to this challenge, we present a novel and impactful contribution: a translation model specifically designed to bridge the linguistic gap between Lao and Vietnamese.
Lao, a language spoken primarily in Laos and parts of Thailand, presents inherent challenges for machine translation due to its low-resource nature, characterized by limited parallel corpora and linguistic resources. Vietnamese, a language spoken by millions worldwide, shares some linguistic similarities with Lao, making it an ideal target language for translation purposes.
Leveraging the power of the Transformer-based T5 model, we have developed a robust translation system for the Lao-Vietnamese language pair. The T5 model, renowned for its versatility and effectiveness across various NLP tasks, serves as the cornerstone of our approach. Through fine-tuning on a curated dataset of Lao-Vietnamese parallel texts, we have endeavored to enhance translation accuracy and fluency, thus enabling smoother communication between speakers of these languages.
Our work represents a significant advancement in the field of machine translation, particularly for low-resource languages like Lao. By harnessing state-of-the-art NLP techniques and focusing on the specific linguistic nuances of the Lao-Vietnamese language pair, we aim to provide a valuable resource for facilitating cross-linguistic communication and cultural exchange.
## How to use
### On GPU
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
model.cuda()
src = "ຂ້ອຍຢາກຊື້ປຶ້ມາ"
tokenized_text = tokenizer.encode(src, return_tensors="pt").cuda()
model.eval()
translate_ids = model.generate(tokenized_text, max_length=200)
output = tokenizer.decode(translate_ids[0], skip_special_tokens=True)
output
```
'Tôi muốn mua một cuốn sách'
### On CPU
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
src = "ຂ້ອຍຢາກຊື້ປຶ້ມ"
input_ids = tokenizer(src, max_length=200, return_tensors="pt", padding="max_length", truncation=True).input_ids
outputs = model.generate(input_ids=input_ids, max_new_tokens=200)
output = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
output
```
'Tôi muốn mua một cuốn sách'
## Author
`
Phan Minh Toan
` | {"language": ["vi", "lo"], "license": "mit", "library_name": "transformers", "tags": ["translation"], "widget": [{"text": "\u0e82\u0ec9\u0ead\u0e8d\u0ea2\u0eb2\u0e81\u0e8a\u0eb7\u0ec9\u0e9b\u0eb6\u0ec9\u0ea1"}], "inference": {"parameters": {"max_length": 200}}, "pipeline_tag": "translation"} | translation | minhtoan/t5-translate-lao-vietnamese | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"translation",
"vi",
"lo",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:36:41+00:00 | [] | [
"vi",
"lo"
] | TAGS
#transformers #pytorch #mt5 #text2text-generation #translation #vi #lo #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Lao to Vietnamese Translation Model
In the domain of natural language processing (NLP), the development of translation models tailored for low-resource languages represents a critical endeavor to facilitate cross-cultural communication and knowledge exchange. In response to this challenge, we present a novel and impactful contribution: a translation model specifically designed to bridge the linguistic gap between Lao and Vietnamese.
Lao, a language spoken primarily in Laos and parts of Thailand, presents inherent challenges for machine translation due to its low-resource nature, characterized by limited parallel corpora and linguistic resources. Vietnamese, a language spoken by millions worldwide, shares some linguistic similarities with Lao, making it an ideal target language for translation purposes.
Leveraging the power of the Transformer-based T5 model, we have developed a robust translation system for the Lao-Vietnamese language pair. The T5 model, renowned for its versatility and effectiveness across various NLP tasks, serves as the cornerstone of our approach. Through fine-tuning on a curated dataset of Lao-Vietnamese parallel texts, we have endeavored to enhance translation accuracy and fluency, thus enabling smoother communication between speakers of these languages.
Our work represents a significant advancement in the field of machine translation, particularly for low-resource languages like Lao. By harnessing state-of-the-art NLP techniques and focusing on the specific linguistic nuances of the Lao-Vietnamese language pair, we aim to provide a valuable resource for facilitating cross-linguistic communication and cultural exchange.
## How to use
### On GPU
'Tôi muốn mua một cuốn sách'
### On CPU
'Tôi muốn mua một cuốn sách'
## Author
'
Phan Minh Toan
' | [
"# Lao to Vietnamese Translation Model\nIn the domain of natural language processing (NLP), the development of translation models tailored for low-resource languages represents a critical endeavor to facilitate cross-cultural communication and knowledge exchange. In response to this challenge, we present a novel and impactful contribution: a translation model specifically designed to bridge the linguistic gap between Lao and Vietnamese.\n\nLao, a language spoken primarily in Laos and parts of Thailand, presents inherent challenges for machine translation due to its low-resource nature, characterized by limited parallel corpora and linguistic resources. Vietnamese, a language spoken by millions worldwide, shares some linguistic similarities with Lao, making it an ideal target language for translation purposes.\n\nLeveraging the power of the Transformer-based T5 model, we have developed a robust translation system for the Lao-Vietnamese language pair. The T5 model, renowned for its versatility and effectiveness across various NLP tasks, serves as the cornerstone of our approach. Through fine-tuning on a curated dataset of Lao-Vietnamese parallel texts, we have endeavored to enhance translation accuracy and fluency, thus enabling smoother communication between speakers of these languages.\n\nOur work represents a significant advancement in the field of machine translation, particularly for low-resource languages like Lao. By harnessing state-of-the-art NLP techniques and focusing on the specific linguistic nuances of the Lao-Vietnamese language pair, we aim to provide a valuable resource for facilitating cross-linguistic communication and cultural exchange.",
"## How to use",
"### On GPU\n\n'Tôi muốn mua một cuốn sách'",
"### On CPU\n\n'Tôi muốn mua một cuốn sách'",
"## Author\n'\nPhan Minh Toan \n'"
] | [
"TAGS\n#transformers #pytorch #mt5 #text2text-generation #translation #vi #lo #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Lao to Vietnamese Translation Model\nIn the domain of natural language processing (NLP), the development of translation models tailored for low-resource languages represents a critical endeavor to facilitate cross-cultural communication and knowledge exchange. In response to this challenge, we present a novel and impactful contribution: a translation model specifically designed to bridge the linguistic gap between Lao and Vietnamese.\n\nLao, a language spoken primarily in Laos and parts of Thailand, presents inherent challenges for machine translation due to its low-resource nature, characterized by limited parallel corpora and linguistic resources. Vietnamese, a language spoken by millions worldwide, shares some linguistic similarities with Lao, making it an ideal target language for translation purposes.\n\nLeveraging the power of the Transformer-based T5 model, we have developed a robust translation system for the Lao-Vietnamese language pair. The T5 model, renowned for its versatility and effectiveness across various NLP tasks, serves as the cornerstone of our approach. Through fine-tuning on a curated dataset of Lao-Vietnamese parallel texts, we have endeavored to enhance translation accuracy and fluency, thus enabling smoother communication between speakers of these languages.\n\nOur work represents a significant advancement in the field of machine translation, particularly for low-resource languages like Lao. By harnessing state-of-the-art NLP techniques and focusing on the specific linguistic nuances of the Lao-Vietnamese language pair, we aim to provide a valuable resource for facilitating cross-linguistic communication and cultural exchange.",
"## How to use",
"### On GPU\n\n'Tôi muốn mua một cuốn sách'",
"### On CPU\n\n'Tôi muốn mua một cuốn sách'",
"## Author\n'\nPhan Minh Toan \n'"
] | [
61,
358,
4,
12,
12,
8
] | [
"passage: TAGS\n#transformers #pytorch #mt5 #text2text-generation #translation #vi #lo #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Lao to Vietnamese Translation Model\nIn the domain of natural language processing (NLP), the development of translation models tailored for low-resource languages represents a critical endeavor to facilitate cross-cultural communication and knowledge exchange. In response to this challenge, we present a novel and impactful contribution: a translation model specifically designed to bridge the linguistic gap between Lao and Vietnamese.\n\nLao, a language spoken primarily in Laos and parts of Thailand, presents inherent challenges for machine translation due to its low-resource nature, characterized by limited parallel corpora and linguistic resources. Vietnamese, a language spoken by millions worldwide, shares some linguistic similarities with Lao, making it an ideal target language for translation purposes.\n\nLeveraging the power of the Transformer-based T5 model, we have developed a robust translation system for the Lao-Vietnamese language pair. The T5 model, renowned for its versatility and effectiveness across various NLP tasks, serves as the cornerstone of our approach. Through fine-tuning on a curated dataset of Lao-Vietnamese parallel texts, we have endeavored to enhance translation accuracy and fluency, thus enabling smoother communication between speakers of these languages.\n\nOur work represents a significant advancement in the field of machine translation, particularly for low-resource languages like Lao. By harnessing state-of-the-art NLP techniques and focusing on the specific linguistic nuances of the Lao-Vietnamese language pair, we aim to provide a valuable resource for facilitating cross-linguistic communication and cultural exchange.## How to use### On GPU\n\n'Tôi muốn mua một cuốn sách'### On CPU\n\n'Tôi muốn mua một cuốn sách'## Author\n'\nPhan Minh Toan \n'"
] | [
0.03373567759990692,
0.020291296765208244,
-0.0065729995258152485,
0.03920796513557434,
0.06886783242225647,
-0.05793452635407448,
-0.03326995670795441,
0.06654826551675797,
-0.0728086605668068,
-0.009454844519495964,
-0.03735286742448807,
0.003793943440541625,
0.07366381585597992,
0.05085434392094612,
0.10230256617069244,
-0.3242424726486206,
0.04533737897872925,
-0.01757517084479332,
-0.020859982818365097,
0.08416911214590073,
0.08846123516559601,
0.007221575360745192,
0.1478462964296341,
0.07191141694784164,
-0.07076586037874222,
0.01168430782854557,
-0.007748572621494532,
0.006558445747941732,
0.08782648295164108,
0.049024637788534164,
0.08811523765325546,
0.005393979139626026,
-0.028193751350045204,
-0.15196789801120758,
-0.0018209980335086584,
0.05141793191432953,
-0.016176577657461166,
0.0002487458405084908,
0.023803839460015297,
0.0165045578032732,
0.2762458026409149,
-0.15410122275352478,
0.008693741634488106,
0.04319123178720474,
-0.09017611294984818,
-0.044992800801992416,
-0.07179956138134003,
-0.009380773641169071,
0.027526620775461197,
0.030966520309448242,
-0.02374844439327717,
0.1674058735370636,
-0.12273423373699188,
0.05928952246904373,
0.015708692371845245,
-0.33551159501075745,
-0.033850669860839844,
0.04033851623535156,
0.027222594246268272,
0.08532721549272537,
0.0037534553557634354,
0.042441949248313904,
-0.035272080451250076,
0.038057997822761536,
0.09447695314884186,
-0.0727766752243042,
0.03581562638282776,
-0.03957866132259369,
-0.13167023658752441,
-0.023719392716884613,
0.1834852397441864,
-0.010388013906776905,
-0.07606719434261322,
-0.07777218520641327,
-0.0664062350988388,
0.10310210287570953,
0.024598557502031326,
-0.15827900171279907,
0.05286768823862076,
0.017096804454922676,
0.1697988063097,
-0.08763287216424942,
-0.0636724904179573,
0.005942767485976219,
-0.0736818015575409,
-0.02927154116332531,
0.062275439500808716,
-0.03439849615097046,
0.039976440370082855,
0.06737380474805832,
-0.13123352825641632,
0.012594462372362614,
-0.042226195335388184,
-0.09215224534273148,
-0.06278753280639648,
0.00802758987993002,
0.06259890645742416,
-0.052639901638031006,
-0.028671231120824814,
0.02493373677134514,
-0.04956570267677307,
0.02611132524907589,
-0.06460399925708771,
0.014867153950035572,
0.029628533869981766,
0.11799760907888412,
-0.05491483211517334,
-0.12095291167497635,
0.016077274456620216,
-0.08055777847766876,
-0.03487800806760788,
0.021401356905698776,
-0.029419347643852234,
-0.03749489039182663,
-0.03467182442545891,
0.049990758299827576,
0.03769573196768761,
0.09189298003911972,
-0.0331273190677166,
-0.055669065564870834,
0.2053264081478119,
-0.06561924517154694,
-0.010269170626997948,
-0.05402957648038864,
-0.02302073873579502,
0.1670076996088028,
0.10643734782934189,
-0.002503445837646723,
-0.13582561910152435,
-0.04094165563583374,
-0.018650515004992485,
-0.023431146517395973,
-0.10871352255344391,
-0.15595774352550507,
0.032943692058324814,
-0.04886376112699509,
-0.050532858818769455,
-0.14491182565689087,
-0.05799788609147072,
-0.02900402434170246,
0.020406177267432213,
-0.04826592281460762,
-0.10320053994655609,
-0.04910432919859886,
-0.05789783224463463,
-0.02512793056666851,
0.04119091480970383,
-0.023462865501642227,
0.001934782019816339,
-0.0003414998354855925,
-0.04860725626349449,
0.05606108903884888,
-0.030389079824090004,
0.01925964653491974,
-0.07619418203830719,
0.0430804044008255,
-0.20604585111141205,
0.12548169493675232,
-0.06042976677417755,
0.007283203303813934,
-0.06732586026191711,
-0.039462003856897354,
-0.07325002551078796,
0.010372074320912361,
-0.03973749279975891,
0.10158718377351761,
-0.09721440821886063,
-0.030802659690380096,
0.1932360678911209,
-0.141928032040596,
-0.02037029340863228,
0.1614464372396469,
0.04724859818816185,
0.12772880494594574,
0.1279229074716568,
0.11953961104154587,
0.1634058803319931,
-0.08253762871026993,
-0.029362760484218597,
-0.0012018781853839755,
-0.17713147401809692,
0.04000367596745491,
0.07870388776063919,
-0.003363829106092453,
-0.021915094926953316,
0.012269026599824429,
-0.035971906036138535,
0.04873044043779373,
-0.03548308461904526,
-0.018987298011779785,
0.0036628879606723785,
0.008831363171339035,
0.0531412735581398,
0.011459160596132278,
0.006624426227062941,
0.019361009821295738,
-0.0903792753815651,
0.12659373879432678,
0.014833959750831127,
-0.00616376381367445,
0.06530040502548218,
-0.1260399967432022,
-0.009704392403364182,
-0.0245229359716177,
0.03532062843441963,
-0.09245868027210236,
-0.05463221296668053,
0.07834415137767792,
-0.054468367248773575,
0.12351703643798828,
0.019698018208146095,
0.0052451277151703835,
0.014902613125741482,
-0.059304412454366684,
0.021029703319072723,
-0.04394108057022095,
0.011059686541557312,
-0.03559127077460289,
-0.1088964119553566,
0.06826326996088028,
-0.007103698328137398,
-0.049558963626623154,
-0.07569955289363861,
-0.013889242894947529,
0.1071205884218216,
0.04814557731151581,
0.05445761978626251,
0.03892647475004196,
0.011027384549379349,
0.12173012644052505,
0.017340971156954765,
-0.008738228119909763,
0.0539708286523819,
-0.023317335173487663,
0.013573472388088703,
0.23690423369407654,
-0.09166115522384644,
0.05530476197600365,
0.08280637115240097,
-0.06040862575173378,
-0.04296577349305153,
0.05812434107065201,
0.002536368789151311,
-0.08149508386850357,
0.021956853568553925,
-0.0007717754924669862,
0.08838989585638046,
-0.0017653459217399359,
0.08848144859075546,
-0.080910824239254,
0.03979671746492386,
0.022153688594698906,
-0.021679053083062172,
0.006240886636078358,
0.07064027339220047,
0.05847657471895218,
-0.19395241141319275,
0.08048145473003387,
0.024627095088362694,
0.09660540521144867,
0.20186883211135864,
0.053169723600149155,
-0.054942306131124496,
-0.0546870082616806,
0.07627050578594208,
0.02317240834236145,
0.020878607407212257,
-0.09378406405448914,
-0.024865243583917618,
0.013156146742403507,
0.10408587008714676,
0.04804760217666626,
-0.026711806654930115,
0.06697140634059906,
0.04402269795536995,
-0.03027120977640152,
-0.02620624005794525,
0.038060616701841354,
-0.007302593905478716,
0.07108984887599945,
0.05730898678302765,
0.07236133515834808,
-0.007261460181325674,
0.007465668022632599,
-0.07978134602308273,
0.10363510251045227,
-0.12435593456029892,
-0.327176958322525,
-0.07225796580314636,
0.02543109655380249,
-0.004254372790455818,
-0.03721335157752037,
0.012343084439635277,
-0.059846047312021255,
-0.03438553586602211,
-0.03879280015826225,
0.08909234404563904,
-0.043047331273555756,
-0.08133770525455475,
-0.18454991281032562,
0.03802367299795151,
-0.02420876733958721,
-0.07544813305139542,
-0.033047232776880264,
-0.0041013238951563835,
-0.18249422311782837,
0.031406693160533905,
-0.11048126220703125,
0.07679706066846848,
0.027308084070682526,
-0.0042073591612279415,
-0.04124182090163231,
-0.04415221884846687,
0.09754318743944168,
-0.07658776640892029,
0.13793455064296722,
0.05370454117655754,
0.02829207479953766,
0.07612606883049011,
0.0850306898355484,
-0.017928583547472954,
-0.01403983123600483,
0.053605351597070694,
0.07847792655229568,
-0.05430812016129494,
-0.1790917068719864,
-0.13540774583816528,
-0.08754041790962219,
0.0551765002310276,
-0.06727202981710434,
0.031136568635702133,
0.03202151507139206,
0.0011818442726507783,
0.029575582593679428,
0.09096069633960724,
0.020189015194773674,
0.042862195521593094,
0.17375582456588745,
-0.04743071645498276,
0.0304313562810421,
-0.08503549546003342,
-0.012700258754193783,
0.09225281327962875,
0.06963871419429779,
0.25671857595443726,
0.03965606540441513,
0.13135060667991638,
0.15784958004951477,
0.2015121728181839,
0.09539370983839035,
0.05882422626018524,
-0.04917594790458679,
0.02529238909482956,
-0.022298110648989677,
-0.060872338712215424,
0.042442742735147476,
0.056807368993759155,
0.13236092031002045,
-0.03206793591380119,
0.031549692153930664,
0.06827412545681,
0.06484514474868774,
0.2160498946905136,
-0.04895024374127388,
-0.03412136435508728,
-0.0033152701798826456,
0.0020044974517077208,
-0.02708231471478939,
-0.05907562002539635,
0.0511644147336483,
0.15303616225719452,
-0.18280331790447235,
0.04060220718383789,
-0.006378024350851774,
0.08054982870817184,
-0.0903245210647583,
-0.009284461848437786,
-0.02199125662446022,
0.000637831399217248,
0.013193950988352299,
0.05961961671710014,
-0.2318459302186966,
0.16719664633274078,
0.003238845383748412,
0.03948310390114784,
-0.0067006624303758144,
0.004028966650366783,
0.019845835864543915,
0.09082332253456116,
0.1423933357000351,
0.07040319591760635,
0.04097425192594528,
-0.030279453843832016,
-0.0643816664814949,
0.03034239448606968,
0.04447183758020401,
0.02780580148100853,
0.033846233040094376,
0.0024310138542205095,
-0.02818438410758972,
-0.042409747838974,
0.045528803020715714,
-0.1864062249660492,
-0.11401978880167007,
0.03858274593949318,
-0.12354622781276703,
-0.002690836787223816,
-0.016106016933918,
-0.008272369392216206,
0.00022980902576819062,
0.19780656695365906,
-0.14638303220272064,
-0.09044772386550903,
-0.06542908400297165,
-0.1438237428665161,
0.05992904305458069,
-0.07964856922626495,
0.07063007354736328,
-0.01566825993359089,
0.0032984863501042128,
-0.011677625589072704,
-0.053207527846097946,
0.09334345906972885,
-0.031921397894620895,
-0.030277792364358902,
0.02011740766465664,
0.13487422466278076,
0.11188182979822159,
0.029105840250849724,
0.004245990887284279,
-0.006531660445034504,
0.0670112743973732,
-0.11288075149059296,
-0.02704704739153385,
0.11255443096160889,
-0.07361879199743271,
0.08275432884693146,
-0.08873333036899567,
-0.10443258285522461,
-0.07548633217811584,
-0.04955267161130905,
0.10892824828624725,
0.04496883973479271,
-0.05564163625240326,
0.18764477968215942,
0.11661358177661896,
-0.16194839775562286,
-0.1649555265903473,
-0.038735177367925644,
-0.013524573296308517,
0.04160459339618683,
0.04645891115069389,
-0.20704713463783264,
-0.024491848424077034,
-0.00545869255438447,
0.03174513205885887,
-0.05320488661527634,
-0.16752278804779053,
-0.09416170418262482,
-0.0030859780963510275,
-0.008774956688284874,
0.10641803592443466,
-0.030853187665343285,
-0.012671463191509247,
0.04482300952076912,
-0.10737702250480652,
0.19583038985729218,
-0.0976804569363594,
0.01935175433754921,
0.008673487231135368,
0.0360332690179348,
0.007409313693642616,
0.02096642553806305,
0.051121022552251816,
-0.038714032620191574,
-0.009217211045324802,
-0.06729033589363098,
-0.03805333375930786,
0.0674513727426529,
0.01595664769411087,
0.10722942650318146,
0.12132066488265991,
-0.03914041817188263,
-0.08986930549144745,
-0.0612049400806427,
-0.10234704613685608,
0.023186510428786278,
-0.04217666760087013,
-0.05403526872396469,
-0.07542506605386734,
0.0932413712143898,
0.05125471204519272,
0.028376273810863495,
-0.11150386929512024,
-0.07491163164377213,
-0.06563664227724075,
0.04139582812786102,
0.21942949295043945,
-0.07625927031040192,
0.01242850348353386,
-0.024482684209942818,
-0.00233056559227407,
0.08692598342895508,
-0.0926540195941925,
0.025356855243444443,
0.12875568866729736,
-0.049696579575538635,
0.05448406562209129,
-0.02180320955812931,
-0.16051244735717773,
0.03677387163043022,
0.057969070971012115,
-0.049794118851423264,
-0.26464810967445374,
-0.03983756899833679,
-0.16443794965744019,
0.11547558754682541,
-0.0771731361746788,
0.08482372015714645,
-0.12794175744056702,
-0.028168203309178352,
-0.016981106251478195,
0.020155414938926697,
-0.08134768158197403,
-0.009447009302675724,
-0.02651933580636978,
0.0029379979241639376,
-0.025020629167556763,
0.14021852612495422,
0.09089569002389908,
-0.2432989627122879,
-0.008602161891758442,
0.16475729644298553,
-0.14189420640468597,
-0.05236286669969559,
-0.04252567142248154,
0.040790390223264694,
0.03214498609304428,
-0.09357352554798126,
0.043234486132860184,
-0.11159355938434601,
0.00891087856143713,
0.15511858463287354,
0.022587716579437256,
0.05861812084913254,
-0.020620349794626236,
-0.006671683397144079,
-0.08108793199062347,
0.03605000674724579,
0.0440719835460186,
-0.07240836322307587,
-0.0724279135465622,
0.03700461983680725,
0.11862945556640625,
0.10619351267814636,
-0.03137888014316559,
-0.0722615122795105,
-0.08979704976081848,
-0.013585679233074188,
0.013399907387793064,
-0.02851550467312336,
-0.07601193338632584,
-0.032380085438489914,
-0.02246297150850296,
-0.035853222012519836,
-0.05032075196504593,
0.03323827683925629,
-0.054356493055820465,
0.02904460020363331,
-0.006578457076102495,
0.09093312919139862,
-0.046443771570920944,
-0.020186664536595345,
0.10051628947257996,
-0.008926420472562313,
0.04911760240793228,
-0.028137048706412315,
-0.046442072838544846,
0.03614155948162079,
-0.0596466064453125,
0.04578632116317749,
-0.017939617857336998,
0.003409908153116703,
0.048724520951509476,
-0.13749960064888,
0.01299123652279377,
0.047427013516426086,
0.04410574585199356,
-0.02097456529736519,
0.10204602777957916,
-0.063747838139534,
0.07885347306728363,
0.004978889599442482,
-0.06984664499759674,
-0.05402061715722084,
0.03465719521045685,
-0.00609572883695364,
0.023909393697977066,
0.01964930072426796,
-0.06366721540689468,
-0.0066256155259907246,
-0.0728292167186737,
-0.015825582668185234,
-0.0004385900974739343,
0.01714826188981533,
0.09214653074741364,
-0.01574834994971752,
0.006401488091796637,
0.019707567989826202,
0.14498798549175262,
0.002846759743988514,
-0.04153899848461151,
0.025794563814997673,
-0.07769642770290375,
-0.18751423060894012,
-0.003488637274131179,
-0.11931055039167404,
0.011817218735814095,
0.0018077063141390681,
-0.022935185581445694,
-0.0033308258280158043,
-0.10614637285470963,
0.04401405155658722,
0.09329777210950851,
0.10346057265996933,
0.16709434986114502,
0.03382524847984314,
-0.015394529327750206,
0.035930417478084564,
-0.21783709526062012,
-0.033601898699998856,
-0.08082657307386398,
0.07403818517923355,
-0.11346091330051422,
0.07660456001758575,
0.1458864063024521,
-0.08045592159032822,
0.14517612755298615,
0.029011882841587067,
-0.0659770667552948,
-0.07344679534435272,
-0.22528913617134094,
-0.05041342228651047,
-0.0639474093914032,
-0.054649364203214645,
-0.08261007815599442,
0.0642203539609909,
0.10073508322238922,
0.08388905227184296,
-0.03429734706878662,
0.12029185146093369,
-0.11656853556632996,
-0.1107916608452797,
0.059570156037807465,
-0.01966959796845913,
0.040228672325611115,
0.016872093081474304,
0.09276346117258072,
-0.06552831083536148,
0.04575509577989578,
-0.005595271475613117,
0.07883607596158981,
-0.02688785456120968,
0.042091816663742065,
-0.04608484357595444,
0.004333735443651676,
-0.03558763489127159,
0.021072570234537125,
-0.01993059180676937,
0.09938222169876099,
0.045840390026569366,
-0.13798931241035461,
0.007351738400757313,
0.1389370560646057,
0.01588582992553711,
-0.13442659378051758,
-0.16085703670978546,
0.18805056810379028,
-0.00378556945361197,
-0.015146148391067982,
0.02079859748482704,
0.021491622552275658,
0.008855193853378296,
0.1993885189294815,
0.1814245730638504,
0.08446746319532394,
-0.025678614154458046,
-0.013740654103457928,
0.008346124552190304,
0.012219076044857502,
0.1342744678258896,
0.013596991077065468,
0.33691471815109253,
-0.05716749280691147,
0.042056091129779816,
-0.11963357776403427,
-0.0013958358904346824,
-0.03254043683409691,
0.01275248546153307,
0.04346754029393196,
0.018144307658076286,
-0.017908548936247826,
0.08819031715393066,
-0.05161810666322708,
-0.00941412802785635,
0.03619329631328583,
-0.08805622905492783,
-0.03317968547344208,
-0.01430745329707861,
-0.028308730572462082,
0.020302090793848038,
0.017629465088248253,
0.009865683503448963,
-0.019766468554735184,
0.1449853926897049,
0.0653756707906723,
-0.11557723581790924,
-0.031251631677150726,
0.10187914222478867,
0.017115220427513123,
0.1459801346063614,
0.0007549987058155239,
0.04367385432124138,
0.06657689809799194,
0.03894766792654991,
-0.10712744295597076,
0.02150668576359749,
-0.03628913313150406,
-0.05347875878214836,
-0.03636535629630089,
0.059128664433956146,
0.03555182367563248,
0.133754163980484,
0.007524577435106039,
0.05383029580116272,
0.08985406905412674,
-0.022378897294402122,
0.03347589820623398,
-0.016388937830924988,
0.07838940620422363,
-0.12660352885723114,
0.086844302713871,
0.16083405911922455,
0.03197570517659187,
0.07502085715532303,
-0.11561360210180283,
-0.0016336555127054453,
-0.0227675698697567,
0.09495580196380615,
-0.07091769576072693,
-0.0375237800180912,
0.025843676179647446,
-0.022930031642317772,
0.03340133652091026,
-0.08950959891080856,
-0.09186549484729767,
-0.03943520039319992,
0.025132741779088974,
-0.09001830965280533,
0.08744962513446808,
-0.006423258688300848,
0.0585310198366642,
-0.016153302043676376,
-0.22122859954833984,
-0.009437561966478825,
0.09785893559455872,
-0.08969646692276001,
-0.046331677585840225
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral_gsm8k_sft
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3771
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3753 | 1.0 | 455 | 0.3771 |
### Framework versions
- Transformers 4.36.1
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "mistral_gsm8k_sft", "results": []}]} | text-generation | weijie210/mistral_gsm8k_sft | [
"transformers",
"tensorboard",
"safetensors",
"mistral",
"text-generation",
"trl",
"sft",
"generated_from_trainer",
"conversational",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:40:06+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #trl #sft #generated_from_trainer #conversational #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| mistral\_gsm8k\_sft
===================
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3771
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 16
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* total\_train\_batch\_size: 16
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 1
### Training results
### Framework versions
* Transformers 4.36.1
* Pytorch 2.0.1+cu117
* Datasets 2.16.1
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 16\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* total\\_train\\_batch\\_size: 16\n* total\\_eval\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* num\\_epochs: 1",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.36.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.16.1\n* Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #mistral #text-generation #trl #sft #generated_from_trainer #conversational #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 16\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* total\\_train\\_batch\\_size: 16\n* total\\_eval\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* num\\_epochs: 1",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.36.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.16.1\n* Tokenizers 0.15.0"
] | [
92,
148,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #mistral #text-generation #trl #sft #generated_from_trainer #conversational #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 16\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* total\\_train\\_batch\\_size: 16\n* total\\_eval\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* num\\_epochs: 1### Training results### Framework versions\n\n\n* Transformers 4.36.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.16.1\n* Tokenizers 0.15.0"
] | [
-0.08638639003038406,
0.10855191946029663,
-0.004766938276588917,
0.08835691213607788,
0.09174834936857224,
0.03253064304590225,
0.15181443095207214,
0.1512031853199005,
-0.07402492314577103,
0.12124720215797424,
0.1147225871682167,
0.06760511547327042,
0.05656915903091431,
0.15426014363765717,
-0.026277780532836914,
-0.21292035281658173,
0.03833554685115814,
-0.013308478519320488,
-0.11224468797445297,
0.10890661180019379,
0.08549466729164124,
-0.10417306423187256,
0.09608869254589081,
-0.019164694473147392,
-0.13219192624092102,
-0.018215570598840714,
-0.032565101981163025,
-0.02727845311164856,
0.08542054891586304,
0.05544181913137436,
0.07552751898765564,
0.026361960917711258,
0.06777994334697723,
-0.22185441851615906,
0.0007683503208681941,
0.07703627645969391,
0.0019198444206267595,
0.07173244655132294,
0.0846574604511261,
0.0235665924847126,
0.10335568338632584,
-0.08500514924526215,
0.0465577132999897,
0.035726435482501984,
-0.11217917501926422,
-0.1914007067680359,
-0.08659864217042923,
0.06632308661937714,
0.10278042405843735,
0.06885695457458496,
-0.010962709784507751,
0.10164713114500046,
-0.04180249944329262,
0.08665669709444046,
0.23772870004177094,
-0.2596032917499542,
-0.07027959823608398,
0.06265155971050262,
0.04417732357978821,
0.083089180290699,
-0.10410947352647781,
-0.022459127008914948,
0.04416317120194435,
0.022438418120145798,
0.10269376635551453,
-0.003811570582911372,
0.009341518394649029,
-0.004524439573287964,
-0.13166409730911255,
-0.0669059231877327,
0.17061612010002136,
0.06314278393983841,
-0.00974537804722786,
-0.10205361247062683,
-0.07335349917411804,
-0.17307023704051971,
-0.03511321544647217,
-0.0069356560707092285,
0.04411117359995842,
-0.028026161715388298,
-0.027843983843922615,
0.02306857332587242,
-0.07046571373939514,
-0.08618295937776566,
0.010819039307534695,
0.0843227356672287,
0.06238703429698944,
-0.003113840240985155,
-0.0017085929866880178,
0.10175234824419022,
0.008425615727901459,
-0.16109995543956757,
-0.029198117554187775,
0.02295519784092903,
-0.056273531168699265,
-0.0199876818805933,
0.00016280122508760542,
0.012573396787047386,
0.06511791795492172,
0.16462965309619904,
-0.05905681848526001,
0.07545056194067001,
0.03740890696644783,
0.019434981048107147,
-0.08166250586509705,
0.14083395898342133,
-0.07223158329725266,
-0.054114002734422684,
-0.014463269151747227,
0.11514236032962799,
0.04130077362060547,
-0.0022610106971114874,
-0.08451579511165619,
0.03270334377884865,
0.1004570722579956,
0.047854818403720856,
-0.006932089105248451,
0.06046239659190178,
-0.05586276948451996,
-0.015757162123918533,
0.1017170399427414,
-0.10880906879901886,
0.035251133143901825,
0.03006524220108986,
-0.05356409773230553,
-0.01983296312391758,
0.014927387237548828,
-0.022608166560530663,
-0.021662527695298195,
0.054872065782547,
-0.0919012725353241,
-0.026422644034028053,
-0.07830101996660233,
-0.09329957515001297,
0.04037037864327431,
-0.040812328457832336,
-0.011290493421256542,
-0.07996832579374313,
-0.13950327038764954,
-0.03692101687192917,
0.03206684812903404,
-0.06304814666509628,
-0.06710943579673767,
-0.05173331871628761,
-0.1081521064043045,
0.03933122381567955,
0.0007796582067385316,
0.1036490947008133,
-0.06593120843172073,
0.06812993437051773,
0.02937176451086998,
0.05519317835569382,
0.06126202642917633,
0.04294091835618019,
-0.06668529659509659,
0.07978890836238861,
-0.15238511562347412,
0.054683469235897064,
-0.08915093541145325,
0.0690506249666214,
-0.11637993156909943,
-0.09114357084035873,
-0.006172648165374994,
-0.016162309795618057,
0.06307177990674973,
0.1145709902048111,
-0.13632486760616302,
-0.0605425126850605,
0.19315725564956665,
-0.09748353064060211,
-0.1394423246383667,
0.12678200006484985,
-0.0030564728658646345,
-0.04708121716976166,
0.03079167567193508,
0.13843755424022675,
0.13282975554466248,
-0.09381089359521866,
-0.030088486149907112,
-0.005287072155624628,
0.08328120410442352,
0.013914113864302635,
0.09159654378890991,
-0.007504072040319443,
0.048653919249773026,
0.023265788331627846,
-0.04872865229845047,
0.023751916363835335,
-0.06822693347930908,
-0.07842466235160828,
-0.05418788269162178,
-0.07592549920082092,
-0.004891593009233475,
0.0429631769657135,
0.023560382425785065,
-0.08889571577310562,
-0.11935613304376602,
0.012693461030721664,
0.11537080258131027,
-0.08663368225097656,
0.014339761808514595,
-0.061528634279966354,
0.08549819886684418,
-0.03204002603888512,
0.017014330253005028,
-0.14199453592300415,
-0.0979386493563652,
0.06231832876801491,
-0.08642718940973282,
-0.00034748855978250504,
0.014705199748277664,
0.0673312395811081,
0.08187374472618103,
-0.05446904897689819,
-0.0538189597427845,
-0.02046091854572296,
-0.007907803170382977,
-0.07827605307102203,
-0.21733565628528595,
-0.04918912425637245,
-0.02902393974363804,
0.13085928559303284,
-0.21356011927127838,
0.04039682075381279,
0.05071176588535309,
0.12563127279281616,
0.020930156111717224,
-0.03508063033223152,
0.005378939677029848,
0.0346769243478775,
-0.05251952260732651,
-0.09209644794464111,
0.0269775390625,
-0.0027431570924818516,
-0.0837443545460701,
-0.005753902718424797,
-0.16287411749362946,
0.13571473956108093,
0.09465697407722473,
0.044374506920576096,
-0.08370915800333023,
-0.008874310180544853,
-0.05502966046333313,
-0.06833828240633011,
-0.016304992139339447,
-0.03427499532699585,
0.114946648478508,
-0.002218480221927166,
0.11755402386188507,
-0.08487141877412796,
-0.06662499159574509,
0.023592596873641014,
0.0008195194532163441,
-0.01903243362903595,
0.13639108836650848,
0.04758121818304062,
-0.10084468871355057,
0.1567986011505127,
0.11701136827468872,
-0.06477881222963333,
0.11558113992214203,
-0.07932735234498978,
-0.07052110135555267,
-0.04468381032347679,
0.05747275426983833,
0.03468981012701988,
0.08500941097736359,
-0.09550264477729797,
0.0052833412773907185,
0.0233700443059206,
0.018879279494285583,
0.017683617770671844,
-0.16745321452617645,
0.007062916643917561,
0.02961765229701996,
-0.09352155774831772,
0.056880537420511246,
-0.01468784362077713,
-0.012580189853906631,
0.09017083048820496,
-0.0069055743515491486,
-0.05162519961595535,
0.004138156305998564,
-0.016167661175131798,
-0.07860933989286423,
0.2052561491727829,
-0.09836708754301071,
-0.13097834587097168,
-0.15227021276950836,
0.01979614980518818,
-0.05540813133120537,
-0.0013339711586013436,
0.037641990929841995,
-0.062113117426633835,
-0.05780639126896858,
-0.107320636510849,
0.004124383442103863,
0.007908939383924007,
0.020039880648255348,
0.027197211980819702,
0.006330409087240696,
0.07951316237449646,
-0.11599459499120712,
0.005912721157073975,
0.02041034586727619,
-0.07314110547304153,
0.013227281160652637,
0.013230284675955772,
0.10770942270755768,
0.1427455097436905,
0.027359789237380028,
0.005832338239997625,
-0.013687344267964363,
0.18020914494991302,
-0.08070864528417587,
0.01731569878757,
0.08947145193815231,
0.025851542130112648,
0.06520029157400131,
0.15622632205486298,
0.03809835761785507,
-0.0762050449848175,
0.0018098399741575122,
0.03499056398868561,
-0.02107304148375988,
-0.22660347819328308,
-0.026981240138411522,
-0.04686807468533516,
0.038607824593782425,
0.10421142727136612,
0.05957772955298424,
0.03349313139915466,
0.04334373027086258,
-0.04017544910311699,
0.046588677912950516,
0.03578697144985199,
0.07573332637548447,
0.06932462006807327,
0.05434345081448555,
0.11011993139982224,
-0.050492290407419205,
-0.024380691349506378,
0.04696433246135712,
0.011883288621902466,
0.2198018729686737,
-0.021551787853240967,
0.23948489129543304,
0.04167060926556587,
0.1287941336631775,
0.0038415694143623114,
0.0496499128639698,
0.003667710116133094,
-0.0006944691995158792,
0.008190855383872986,
-0.06136641278862953,
0.00011828819697257131,
0.04336453974246979,
-0.006454960443079472,
0.046054333448410034,
-0.06972530484199524,
0.03729480504989624,
0.06760725378990173,
0.26910459995269775,
0.05620695278048515,
-0.31745535135269165,
-0.07834704220294952,
0.038309454917907715,
-0.034322477877140045,
-0.029800985008478165,
0.025345398113131523,
0.15832340717315674,
-0.06954645365476608,
0.07790835201740265,
-0.05462093651294708,
0.08109088242053986,
-0.055475447326898575,
0.00969129242002964,
0.10240856558084488,
0.11292944103479385,
0.009790798649191856,
0.07451064884662628,
-0.2485707849264145,
0.24100792407989502,
0.004182352218776941,
0.04113984480500221,
-0.04596973583102226,
0.04839581251144409,
0.014827384613454342,
0.05590791627764702,
0.07824712246656418,
-0.011780506931245327,
-0.1105850487947464,
-0.15471963584423065,
-0.12564072012901306,
0.005576563999056816,
0.09551303088665009,
-0.059397391974925995,
0.11147303879261017,
-0.033230092376470566,
-0.032665759325027466,
0.04493347555398941,
-0.05032123997807503,
-0.07042102515697479,
-0.10878932476043701,
0.034550439566373825,
0.0048112040385603905,
-0.013625934720039368,
-0.09292101114988327,
-0.0820692703127861,
-0.09731476753950119,
0.17423410713672638,
-0.11480522900819778,
-0.04884925112128258,
-0.1133517324924469,
0.04856472089886665,
0.1303892731666565,
-0.09141978621482849,
0.037241511046886444,
-0.013644018210470676,
0.1174091100692749,
0.03287702798843384,
-0.05285510793328285,
0.09517789632081985,
-0.0648178979754448,
-0.22185324132442474,
-0.041568558663129807,
0.13051868975162506,
0.0034808171913027763,
0.04965243861079216,
-0.030239347368478775,
0.022723587229847908,
-0.005534294992685318,
-0.10106870532035828,
0.022276293486356735,
0.0672735869884491,
0.048542194068431854,
0.03729905188083649,
-0.04459673911333084,
-0.01037455815821886,
-0.036997806280851364,
-0.032688360661268234,
0.0812053456902504,
0.2835148572921753,
-0.09174934774637222,
0.02561582438647747,
0.052613720297813416,
-0.07246725261211395,
-0.18464434146881104,
-0.027480121701955795,
0.060771770775318146,
0.01876462996006012,
-0.0009853781666606665,
-0.15405070781707764,
0.05388256534934044,
0.10721726715564728,
-0.022660166025161743,
0.10557635128498077,
-0.34547531604766846,
-0.14133259654045105,
0.0703423023223877,
0.09325367957353592,
-0.030805686488747597,
-0.2003103792667389,
-0.07254394143819809,
-0.01606382429599762,
-0.12009432911872864,
0.051542431116104126,
-0.05782376974821091,
0.11198030412197113,
-0.036497656255960464,
0.004728697240352631,
0.009186695329844952,
-0.05891413614153862,
0.1662573218345642,
0.012318120338022709,
0.08634404838085175,
-0.05363057926297188,
0.010396905243396759,
0.09904277324676514,
-0.0793839693069458,
0.052719373255968094,
-0.13184572756290436,
0.04606860876083374,
-0.07737857103347778,
-0.012834507040679455,
-0.05776993930339813,
0.01500011421740055,
-0.05515265464782715,
-0.016408313065767288,
-0.0654745101928711,
0.03261416405439377,
0.06508532911539078,
-0.014724495820701122,
0.14052055776119232,
0.022384172305464745,
0.1284281611442566,
0.17278848588466644,
0.07294026762247086,
0.00004624006396625191,
-0.10949085652828217,
-0.01051550917327404,
-0.0036032823845744133,
0.04202389717102051,
-0.14121343195438385,
0.03627244383096695,
0.13422253727912903,
0.016541222110390663,
0.12838608026504517,
0.048870641738176346,
-0.06796056032180786,
-0.009727484546601772,
0.06905028969049454,
-0.12590838968753815,
-0.17044506967067719,
-0.007826324552297592,
0.001162331784144044,
-0.15023913979530334,
0.02416517399251461,
0.10267484933137894,
-0.056390244513750076,
0.0055524795316159725,
0.00921436958014965,
0.05883539468050003,
-0.017943503335118294,
0.21205705404281616,
0.0308415275067091,
0.08385223895311356,
-0.09025716036558151,
0.09667174518108368,
0.06334005296230316,
-0.08185485750436783,
0.016744162887334824,
0.0918123871088028,
-0.08389303088188171,
-0.033255089074373245,
0.08817330002784729,
0.11827408522367477,
0.019456621259450912,
-0.04793064296245575,
-0.12028708308935165,
-0.13736391067504883,
0.0779041200876236,
0.09822939336299896,
0.0647699311375618,
0.06271862983703613,
0.008613175712525845,
0.011811777018010616,
-0.0861387774348259,
0.13539272546768188,
0.06424523890018463,
0.08926961570978165,
-0.1612275093793869,
0.07867739349603653,
0.0014712180709466338,
0.00043948192615062,
-0.009361610747873783,
0.045269738882780075,
-0.12305805832147598,
-0.026031654328107834,
-0.11543332785367966,
0.02811249904334545,
-0.051957592368125916,
0.0003408065822441131,
0.005980563350021839,
-0.041130390018224716,
-0.050730347633361816,
0.0269155390560627,
-0.08000264316797256,
-0.0584699921309948,
-0.02554992027580738,
0.08125662803649902,
-0.12423154711723328,
-0.030691301450133324,
0.03425402566790581,
-0.11291765421628952,
0.08313895016908646,
0.022984616458415985,
0.03010234422981739,
0.007353892084211111,
-0.08191770315170288,
0.03581717982888222,
0.04370805621147156,
0.02509140968322754,
0.02277195081114769,
-0.14494480192661285,
-0.009017453528940678,
-0.023260729387402534,
-0.005509767681360245,
0.0033990468364208937,
0.028655149042606354,
-0.12320098280906677,
0.02063034474849701,
-0.04888369143009186,
-0.05363916605710983,
-0.05454937368631363,
0.04655425623059273,
0.09932679682970047,
-0.017902491614222527,
0.16347092390060425,
-0.07943041622638702,
0.030333857983350754,
-0.23100756108760834,
-0.002304708119481802,
0.01877945102751255,
-0.09829198569059372,
-0.08156117051839828,
-0.020773207768797874,
0.07563038170337677,
-0.056383877992630005,
0.12364640831947327,
-0.04748819023370743,
-0.0038347213994711637,
0.033753424882888794,
-0.02906445786356926,
0.037248995155096054,
0.06062198802828789,
0.1371268630027771,
0.022482406347990036,
-0.030985554680228233,
0.050114553421735764,
-0.01619892194867134,
0.08010431379079819,
0.041836198419332504,
0.15875592827796936,
0.1379023641347885,
-0.023217543959617615,
0.08618108928203583,
0.061753883957862854,
-0.11362606287002563,
-0.12592457234859467,
0.1090511754155159,
-0.08128947019577026,
0.12697459757328033,
-0.029692701995372772,
0.1466040462255478,
0.11724668741226196,
-0.19054143130779266,
0.03717142716050148,
-0.04825568571686745,
-0.08899133652448654,
-0.09504158049821854,
-0.09092312306165695,
-0.09603462368249893,
-0.1573937088251114,
-0.008546951226890087,
-0.11631108820438385,
0.032402995973825455,
0.0764799490571022,
0.028717536479234695,
0.013392038643360138,
0.1534639596939087,
0.04680433124303818,
0.025871993973851204,
0.03138282522559166,
0.027152154594659805,
-0.025499384850263596,
-0.03757611662149429,
-0.07567480206489563,
0.025449011474847794,
-0.02244826965034008,
0.04736620560288429,
-0.016025574877858162,
-0.004024949390441179,
0.07188843935728073,
-0.005117161199450493,
-0.08352470397949219,
0.015815628692507744,
-0.004679795354604721,
0.01070111058652401,
0.03827540948987007,
0.023092538118362427,
-0.012111231684684753,
-0.013338252902030945,
0.16009095311164856,
-0.0725538581609726,
-0.065116286277771,
-0.11062733829021454,
0.1837311089038849,
-0.005035307724028826,
-0.007369701284915209,
0.04077675938606262,
-0.06248468533158302,
-0.011378836818039417,
0.1664552390575409,
0.17828038334846497,
-0.01778697595000267,
-0.015852125361561775,
0.005413363687694073,
-0.014316149055957794,
-0.006930391304194927,
0.07700255513191223,
0.09973793476819992,
0.047289907932281494,
-0.04786233231425285,
-0.021906418725848198,
-0.010027918964624405,
-0.029265686869621277,
-0.05801749974489212,
0.05659197270870209,
0.007456429302692413,
0.008997393772006035,
-0.029831763356924057,
0.043329257518053055,
-0.03551623970270157,
-0.08273636549711227,
0.061283260583877563,
-0.1857861429452896,
-0.15551674365997314,
-0.028765633702278137,
0.09274373203516006,
-0.002375344280153513,
0.047734592109918594,
-0.004005549941211939,
-0.023156579583883286,
0.10752364993095398,
-0.02605072781443596,
-0.10066525638103485,
-0.08579621464014053,
0.04786919802427292,
-0.10471346229314804,
0.19947153329849243,
-0.030069870874285698,
0.039884887635707855,
0.13060420751571655,
0.0008108649053610861,
-0.13129064440727234,
0.045071616768836975,
0.07320968061685562,
-0.08836716413497925,
0.02749757096171379,
0.11484649032354355,
-0.0374370776116848,
0.09936550259590149,
0.04542135074734688,
-0.06466123461723328,
-0.020833998918533325,
-0.024277539923787117,
-0.025918668136000633,
-0.06479281932115555,
-0.021553609520196915,
-0.045467983931303024,
0.15225477516651154,
0.2046227902173996,
-0.05376356095075607,
-0.017282191663980484,
-0.024584777653217316,
0.03379198908805847,
0.04212237149477005,
0.10343282669782639,
-0.00023020189837552607,
-0.2591414749622345,
0.031018434092402458,
-0.00028742128051817417,
0.04186080023646355,
-0.2045089602470398,
-0.10419043153524399,
0.021070705726742744,
-0.036284007132053375,
-0.09517154097557068,
0.12009435147047043,
0.08874557912349701,
0.05108955502510071,
-0.05705806612968445,
-0.10538603365421295,
-0.060743845999240875,
0.15800878405570984,
-0.14762786030769348,
-0.09083496034145355
] |
null | null | transformers | # wizard-tulu-dolphin-70b-v1.0-slerp
I used this blend as part of Midnight Rose v2.0.3. I haven't tested it much on its own, but I created this blend to be good at instruction following.
It's nothing fancy. I just figured that WizardLM, Tulu, and Dolphin 2.2 together would be a heavy hitter for smarts.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab
* /home/llm/mergequant/models/wizard-tulu-70b-v1.0
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: /home/llm/mergequant/models/wizard-tulu-70b-v1.0
- model: /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab
merge_method: slerp
base_model: /home/llm/mergequant/models/wizard-tulu-70b-v1.0
parameters:
t:
- value: 0.5
dtype: float16
```
```yaml
models:
- model: /home/llm/mergequant/models/BASE/NousResearch_Llama-2-70b-hf
# no parameters necessary for base model
- model: /home/llm/mergequant/models/BASE/allenai_tulu-2-dpo-70b
parameters:
density: 0.35
weight: 0.75
- model: /home/llm/mergequant/models/BASE/WizardLM_WizardLM-70B-V1.0
parameters:
density: 0.35
weight: 0.5
merge_method: dare_ties
base_model: /home/llm/mergequant/models/BASE/NousResearch_Llama-2-70b-hf
parameters:
normalize: true
int8_mask: true
dtype: float16
tokenzer_source: union
```
| {"tags": ["mergekit", "merge"], "base_model": []} | text-generation | sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:41:03+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #mergekit #merge #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # wizard-tulu-dolphin-70b-v1.0-slerp
I used this blend as part of Midnight Rose v2.0.3. I haven't tested it much on its own, but I created this blend to be good at instruction following.
It's nothing fancy. I just figured that WizardLM, Tulu, and Dolphin 2.2 together would be a heavy hitter for smarts.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab
* /home/llm/mergequant/models/wizard-tulu-70b-v1.0
### Configuration
The following YAML configuration was used to produce this model:
| [
"# wizard-tulu-dolphin-70b-v1.0-slerp\n\nI used this blend as part of Midnight Rose v2.0.3. I haven't tested it much on its own, but I created this blend to be good at instruction following.\nIt's nothing fancy. I just figured that WizardLM, Tulu, and Dolphin 2.2 together would be a heavy hitter for smarts.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the SLERP merge method.",
"### Models Merged\n\nThe following models were included in the merge:\n* /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab\n* /home/llm/mergequant/models/wizard-tulu-70b-v1.0",
"### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #mergekit #merge #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# wizard-tulu-dolphin-70b-v1.0-slerp\n\nI used this blend as part of Midnight Rose v2.0.3. I haven't tested it much on its own, but I created this blend to be good at instruction following.\nIt's nothing fancy. I just figured that WizardLM, Tulu, and Dolphin 2.2 together would be a heavy hitter for smarts.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the SLERP merge method.",
"### Models Merged\n\nThe following models were included in the merge:\n* /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab\n* /home/llm/mergequant/models/wizard-tulu-70b-v1.0",
"### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
54,
91,
4,
18,
71,
17
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #mergekit #merge #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# wizard-tulu-dolphin-70b-v1.0-slerp\n\nI used this blend as part of Midnight Rose v2.0.3. I haven't tested it much on its own, but I created this blend to be good at instruction following.\nIt's nothing fancy. I just figured that WizardLM, Tulu, and Dolphin 2.2 together would be a heavy hitter for smarts.## Merge Details### Merge Method\n\nThis model was merged using the SLERP merge method.### Models Merged\n\nThe following models were included in the merge:\n* /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab\n* /home/llm/mergequant/models/wizard-tulu-70b-v1.0### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
-0.05671406909823418,
-0.03620082885026932,
-0.0017332087736576796,
0.014973326586186886,
0.06796915084123611,
0.09363887459039688,
0.18207736313343048,
0.0572863332927227,
0.059966977685689926,
0.04727666452527046,
0.017179159447550774,
0.06373430043458939,
0.0848604366183281,
0.16582441329956055,
-0.003741517895832658,
-0.1124306172132492,
0.06087875738739967,
-0.010852789506316185,
-0.21780702471733093,
0.09856288880109787,
0.08036871254444122,
-0.08105312287807465,
0.1350061148405075,
0.028314892202615738,
-0.1483103185892105,
0.013598588295280933,
-0.05836601182818413,
0.011562432162463665,
0.08630195260047913,
0.07397828996181488,
0.11947981268167496,
0.055893365293741226,
0.02451489306986332,
-0.07712661474943161,
0.0571400448679924,
0.004488248378038406,
0.030593471601605415,
0.06104739010334015,
0.12429570406675339,
0.0012755811912938952,
0.16179122030735016,
-0.0557963065803051,
0.08976951241493225,
0.06500526517629623,
-0.04127413034439087,
-0.0714588314294815,
-0.17734725773334503,
0.09705699235200882,
0.12936541438102722,
-0.01421777531504631,
0.01297457329928875,
0.10095939040184021,
0.05504103749990463,
0.071591816842556,
0.07338134944438934,
-0.22912107408046722,
-0.025066129863262177,
0.09574540704488754,
0.08530233800411224,
-0.06670991331338882,
0.05606386438012123,
0.03134462982416153,
0.018351219594478607,
0.00401252182200551,
-0.00042385057895444334,
-0.020215913653373718,
0.22944045066833496,
-0.10091575235128403,
-0.12431646883487701,
0.0010643535060808063,
0.0728980228304863,
0.04232717677950859,
-0.03814161568880081,
-0.06537670642137527,
-0.0951947495341301,
0.018400048837065697,
-0.019076291471719742,
-0.021718068048357964,
0.00668846070766449,
-0.04237407073378563,
0.07823152095079422,
-0.06635207682847977,
-0.033789537847042084,
-0.07811091840267181,
-0.11941271275281906,
0.22738385200500488,
0.06275977194309235,
0.07714885473251343,
-0.09088669717311859,
0.059814807027578354,
-0.002358638448640704,
-0.059849921613931656,
0.051815420389175415,
-0.06329534202814102,
-0.064173124730587,
-0.017588453367352486,
-0.04128077253699303,
-0.20948359370231628,
0.09671831130981445,
0.14588019251823425,
0.006315640639513731,
0.06786049902439117,
0.04454505816102028,
0.044692669063806534,
-0.005504057742655277,
0.032939132302999496,
-0.11936500668525696,
-0.1942605972290039,
0.0862668827176094,
0.04456113651394844,
0.06192013621330261,
0.009003176353871822,
-0.10110670328140259,
-0.013998717069625854,
-0.07358292490243912,
-0.02131330594420433,
0.1160338893532753,
0.03269575536251068,
-0.04675744101405144,
-0.08881019055843353,
0.16598866879940033,
-0.07208839803934097,
0.07018285989761353,
0.022010562941432,
-0.01652079075574875,
0.0017481946852058172,
0.11056656390428543,
0.004176213871687651,
0.05120902135968208,
0.08032938838005066,
-0.023102447390556335,
-0.023790346458554268,
-0.06465692073106766,
-0.09670714288949966,
0.022013049572706223,
-0.012377794831991196,
-0.03584858030080795,
-0.1279982477426529,
-0.20306961238384247,
-0.033897433429956436,
0.033125150948762894,
-0.028561336919665337,
-0.019807875156402588,
-0.015482345595955849,
0.020760156214237213,
-0.0125216543674469,
0.036969143897295,
0.07568081468343735,
0.006071198265999556,
0.009710220620036125,
-0.004634043201804161,
0.05148443207144737,
-0.12215776741504669,
0.020454101264476776,
-0.026696080341935158,
0.11063322424888611,
-0.1005091443657875,
0.12421619892120361,
0.010746232233941555,
0.07695610076189041,
-0.10104360431432724,
-0.005021814722567797,
-0.0236976258456707,
-0.01733408309519291,
0.08868787437677383,
0.13997460901737213,
-0.1719193011522293,
-0.03414887934923172,
0.03015584498643875,
-0.14910146594047546,
-0.10765383392572403,
0.12641632556915283,
0.004784885793924332,
0.01889050006866455,
0.06559525430202484,
0.11223801225423813,
0.10968611389398575,
-0.012632840313017368,
-0.0023146162275224924,
-0.0835789293050766,
-0.03399088606238365,
-0.003529265057295561,
0.06689997017383575,
0.06164989247918129,
-0.23335546255111694,
0.030213309451937675,
0.005964178126305342,
0.14157477021217346,
-0.02465439960360527,
-0.05340518057346344,
-0.0663374662399292,
-0.0856478288769722,
0.10987520962953568,
-0.043688055127859116,
0.002079931553453207,
-0.058067966252565384,
-0.05845850706100464,
-0.04486781358718872,
0.11959762871265411,
-0.027188658714294434,
0.0055607883259654045,
-0.05066557601094246,
0.23601017892360687,
-0.12427610903978348,
0.04088663309812546,
-0.05953952297568321,
-0.00198694271966815,
-0.0070981490425765514,
0.002342888154089451,
0.09774846583604813,
-0.017796076834201813,
0.06595486402511597,
0.06322548538446426,
-0.025948766618967056,
-0.05626103654503822,
0.0611516609787941,
0.04910935461521149,
-0.03578401356935501,
-0.15690049529075623,
-0.06935795396566391,
-0.04434394836425781,
0.15018074214458466,
-0.04576844349503517,
0.06567854434251785,
-0.018501173704862595,
0.22738294303417206,
-0.049703508615493774,
-0.02021012082695961,
0.045224517583847046,
0.01568208634853363,
-0.015421830117702484,
-0.030042074620723724,
0.04449370875954628,
0.0239386148750782,
-0.19147343933582306,
0.022426243871450424,
-0.14302946627140045,
-0.07323242723941803,
0.0893169641494751,
0.07578511536121368,
-0.0641740933060646,
0.0021039729472249746,
-0.006272133439779282,
-0.047532085329294205,
0.048964470624923706,
-0.0129531379789114,
0.08766481280326843,
0.04285296052694321,
0.10991252958774567,
-0.045721132308244705,
-0.020616695284843445,
0.0196082666516304,
-0.005375418346375227,
-0.028671767562627792,
0.03858399763703346,
-0.014980155974626541,
-0.13124409317970276,
0.039472028613090515,
0.11217358708381653,
0.029386021196842194,
0.013251629658043385,
0.04700780287384987,
-0.0032594052609056234,
-0.07361958175897598,
-0.017734549939632416,
-0.0015959525480866432,
0.019394004717469215,
0.01989014632999897,
0.06450436264276505,
0.06748365610837936,
0.00025666592409834266,
0.03694213926792145,
-0.12992195785045624,
0.055913295596838,
0.0616779625415802,
0.025424780324101448,
0.04452335834503174,
0.06913942098617554,
0.03218153491616249,
0.06100587919354439,
0.03573289513587952,
-0.0048378934152424335,
0.014100293628871441,
-0.01226187963038683,
-0.0711735263466835,
0.1268487125635147,
-0.13995394110679626,
-0.21617013216018677,
-0.17937061190605164,
-0.05697111412882805,
-0.10021648555994034,
-0.04247276112437248,
0.04534170404076576,
-0.06048637256026268,
-0.07512237131595612,
-0.05117674916982651,
0.13821785151958466,
0.03319865092635155,
0.05506303906440735,
0.008028428070247173,
-0.01873924769461155,
0.036529961973428726,
-0.0494125634431839,
-0.01777116395533085,
0.015407871454954147,
0.018099382519721985,
0.04918643832206726,
0.022937925532460213,
0.06488856673240662,
0.138707235455513,
-0.09362980723381042,
-0.013814381323754787,
-0.004329252988100052,
0.19823208451271057,
-0.02294076234102249,
0.1135842576622963,
0.1588445007801056,
-0.06670502573251724,
0.05892324447631836,
0.16535715758800507,
0.027384625747799873,
-0.04001136124134064,
0.0045649162493646145,
-0.053004711866378784,
-0.06966656446456909,
-0.1998182088136673,
-0.11383991688489914,
-0.062114179134368896,
-0.04139922931790352,
0.0025662542320787907,
0.04478803277015686,
-0.03724134713411331,
0.07744985073804855,
-0.04575814679265022,
0.018785323947668076,
-0.007420465350151062,
0.07113528996706009,
0.2154325246810913,
0.011414648965001106,
0.04431382566690445,
-0.0667104572057724,
0.010314062237739563,
0.05352921411395073,
0.08898254483938217,
0.05205637961626053,
0.02917948178946972,
0.08943558484315872,
0.06818945705890656,
0.014556316658854485,
0.030679170042276382,
0.06304607540369034,
-0.023127250373363495,
0.05208098888397217,
-0.03873893991112709,
-0.06880415976047516,
-0.00638057803735137,
0.0588202178478241,
0.016527188941836357,
0.10368752479553223,
-0.056341808289289474,
0.08628383278846741,
0.007497921120375395,
0.14577357470989227,
-0.006459487602114677,
-0.2907450497150421,
-0.06207376718521118,
0.04587966576218605,
0.006992044392973185,
-0.053557317703962326,
-0.04386356472969055,
-0.0006920385640114546,
-0.05524666979908943,
0.18286341428756714,
-0.036945194005966187,
0.08366455137729645,
0.041230350732803345,
-0.048680782318115234,
-0.02579384483397007,
0.14191874861717224,
0.04036583751440048,
0.008627675473690033,
-0.04049045220017433,
0.10065487027168274,
0.003500694641843438,
0.011445616371929646,
0.04414454847574234,
0.06560840457677841,
0.054698310792446136,
0.1761244237422943,
0.021231889724731445,
0.030203303322196007,
-0.0008580386638641357,
-0.03395538777112961,
-0.1602063775062561,
-0.006226534489542246,
-0.06194894388318062,
0.002661126898601651,
0.08644881099462509,
-0.049242157489061356,
-0.07210977375507355,
-0.036911942064762115,
0.04112992808222771,
-0.05682360753417015,
-0.12268971651792526,
0.053950995206832886,
-0.010292448103427887,
-0.023308631032705307,
-0.0818372517824173,
-0.044697098433971405,
-0.10859180986881256,
0.20187193155288696,
-0.031594596803188324,
-0.10312607139348984,
-0.08148475736379623,
-0.04091400280594826,
0.18328845500946045,
-0.03411950170993805,
0.03855906426906586,
-0.06055229529738426,
0.09829706698656082,
-0.09695225208997726,
-0.14348958432674408,
-0.012034519575536251,
-0.09482427686452866,
-0.14399735629558563,
-0.053570374846458435,
0.11575203388929367,
-0.07325328886508942,
0.08147411048412323,
-0.002293652156367898,
0.04846139997243881,
-0.06380674242973328,
-0.01033035945147276,
-0.037959448993206024,
0.24613910913467407,
-0.05593421310186386,
0.08267299830913544,
0.03387843817472458,
-0.05877070873975754,
-0.05692532658576965,
-0.023924261331558228,
0.1279904991388321,
0.2561018764972687,
-0.0700264424085617,
0.14144015312194824,
0.05445471033453941,
-0.0956432893872261,
-0.14388726651668549,
-0.03119822032749653,
-0.00422859750688076,
0.06412287801504135,
-0.03062133863568306,
0.003445640904828906,
0.048977725207805634,
0.021242156624794006,
0.008110214956104755,
0.08123402297496796,
-0.2563614845275879,
-0.13894525170326233,
0.01766190305352211,
0.04410730302333832,
0.180242657661438,
-0.1290348917245865,
-0.08370088040828705,
-0.05624920874834061,
-0.11563427746295929,
0.03283752501010895,
0.030016779899597168,
0.05516760051250458,
-0.05165201425552368,
0.11420951038599014,
0.030294451862573624,
-0.04467661306262016,
0.14462421834468842,
-0.1294754594564438,
-0.0076849088072776794,
-0.0498553067445755,
-0.015103950165212154,
-0.036563973873853683,
-0.10064171254634857,
0.07385768741369247,
-0.060124438256025314,
0.015239913947880268,
-0.026780899614095688,
-0.02173556014895439,
-0.05042172223329544,
0.05309590697288513,
-0.01747511886060238,
0.00032283729524351656,
-0.09434863179922104,
-0.0001072628510883078,
0.08087457716464996,
-0.04160713776946068,
0.0532262921333313,
0.018972745165228844,
0.043375857174396515,
0.06557206064462662,
0.07657252252101898,
-0.0868556797504425,
-0.0945010706782341,
0.022732842713594437,
-0.0792422965168953,
0.04680690914392471,
-0.08204164355993271,
-0.013307704590260983,
0.1062571108341217,
-0.025269722566008568,
0.08431585878133774,
0.011264864355325699,
-0.06059573218226433,
-0.01865873672068119,
0.09316661953926086,
-0.11125826090574265,
-0.2289351522922516,
-0.011829863302409649,
0.08128318190574646,
-0.07673830538988113,
-0.05170571058988571,
0.13531945645809174,
-0.07518418878316879,
-0.0720762312412262,
0.021316727623343468,
0.023436708375811577,
-0.09379716962575912,
0.1067938357591629,
0.01573159731924534,
0.040653347969055176,
-0.11842251569032669,
0.04995395988225937,
0.047791142016649246,
-0.10484735667705536,
0.013449528254568577,
0.10766591876745224,
-0.051302094012498856,
-0.03934917226433754,
-0.005124896299093962,
0.22277428209781647,
-0.009246709756553173,
-0.04787985607981682,
-0.14878924190998077,
-0.12847748398780823,
0.007922450080513954,
0.09367980808019638,
0.05087769404053688,
0.03330408036708832,
-0.0005423541297204792,
-0.029295682907104492,
-0.09561051428318024,
0.0979778990149498,
0.0879732295870781,
0.11759033054113388,
-0.18801754713058472,
0.11383146792650223,
-0.018630430102348328,
0.04078790917992592,
-0.028645040467381477,
0.017291612923145294,
-0.0484958253800869,
-0.04613753408193588,
-0.20660142600536346,
0.05894916504621506,
-0.12745918333530426,
0.007680431008338928,
0.006993545684963465,
-0.005576149094849825,
-0.014239238575100899,
0.03464391082525253,
-0.053467512130737305,
-0.053627777844667435,
-0.06032141298055649,
-0.009060253389179707,
-0.018934492021799088,
-0.05490173026919365,
-0.0041587441228330135,
-0.0659060925245285,
-0.02181888185441494,
-0.015325583517551422,
-0.04151110723614693,
-0.09337016940116882,
-0.10027064383029938,
-0.08156446367502213,
0.025646880269050598,
0.022578829899430275,
0.03491313010454178,
-0.21224196255207062,
-0.004529144614934921,
0.001531926798634231,
-0.05659480392932892,
-0.05573707073926926,
0.14102622866630554,
-0.08288642764091492,
-0.03206103295087814,
-0.06876290589570999,
-0.016920870169997215,
-0.018819058313965797,
-0.07476969808340073,
0.04742728918790817,
0.10923933982849121,
0.14922374486923218,
-0.07746952027082443,
0.0710490420460701,
-0.14858120679855347,
-0.025232411921024323,
-0.04912090301513672,
-0.05338664725422859,
-0.1005258560180664,
-0.06500652432441711,
0.04093509912490845,
0.013950373977422714,
0.05408085882663727,
0.02334648370742798,
-0.11539265513420105,
0.018966296687722206,
0.04978351294994354,
-0.005833253730088472,
0.020342431962490082,
0.09378542006015778,
-0.05488308146595955,
0.024419700726866722,
-0.03513073921203613,
0.025548305362462997,
0.022164270281791687,
-0.006238322705030441,
0.07883177697658539,
0.05180761590600014,
0.08475692570209503,
0.07794804126024246,
0.12440800666809082,
0.06873160600662231,
-0.07275717705488205,
-0.12861290574073792,
-0.05382024124264717,
0.0487632229924202,
-0.04081081971526146,
0.17488829791545868,
0.03301504626870155,
-0.17357401549816132,
0.07458953559398651,
0.010054416954517365,
-0.021751750260591507,
-0.06495776027441025,
-0.02259049005806446,
-0.10471481829881668,
-0.10248305648565292,
-0.028079206123948097,
-0.03338364511728287,
-0.043118685483932495,
-0.11266501247882843,
-0.02095782570540905,
0.0012571044499054551,
0.15302205085754395,
-0.009126784279942513,
0.01003209687769413,
-0.0357789620757103,
0.03608804568648338,
-0.04732182249426842,
0.10072430968284607,
-0.05001077428460121,
0.06783252209424973,
-0.02300688810646534,
0.020802929997444153,
0.05476367101073265,
0.006674449425190687,
0.06767784804105759,
-0.0033452624920755625,
-0.12474659830331802,
0.005444250535219908,
0.014570904895663261,
0.12364312261343002,
0.04331827163696289,
0.049551062285900116,
-0.02925359085202217,
-0.030862469226121902,
-0.0025798066053539515,
-0.029860304668545723,
-0.06835261732339859,
-0.08985816687345505,
0.17900779843330383,
-0.11667706072330475,
-0.024766582995653152,
0.05357913672924042,
-0.06040818244218826,
-0.02104675956070423,
0.15714406967163086,
0.25522080063819885,
0.04624243080615997,
-0.05205480754375458,
0.028650587424635887,
0.016769375652074814,
-0.05365710332989693,
0.09769822657108307,
0.03339717537164688,
0.1376132369041443,
-0.04229773208498955,
0.06627675890922546,
-0.07574523985385895,
-0.058672137558460236,
-0.035235658288002014,
-0.056621287018060684,
-0.03191063925623894,
-0.012309323996305466,
0.06332691013813019,
0.07759558409452438,
-0.028691159561276436,
-0.12611310184001923,
0.12399682402610779,
-0.1509045511484146,
-0.09356068074703217,
-0.04626355320215225,
0.07680049538612366,
-0.010310275480151176,
0.0719895139336586,
-0.03847038745880127,
0.003681397996842861,
0.1460098922252655,
-0.05472424253821373,
-0.10180199146270752,
-0.06404491513967514,
0.06113848462700844,
-0.05338050052523613,
0.07305251806974411,
0.023468798026442528,
0.0953180268406868,
0.07647506147623062,
0.020010357722640038,
-0.15780146420001984,
-0.034980788826942444,
0.0054276431910693645,
-0.015315569937229156,
0.06010102108120918,
0.09314901381731033,
-0.016734065487980843,
0.020239179953932762,
0.010205790400505066,
-0.03363049775362015,
-0.003334798850119114,
-0.049816057085990906,
-0.03561755642294884,
-0.041072748601436615,
0.08479227870702744,
-0.05866523087024689,
0.156082421541214,
0.1647176444530487,
-0.027501516044139862,
0.012748247012495995,
-0.04059490188956261,
0.018407125025987625,
0.09035968035459518,
0.1480960100889206,
-0.006993625778704882,
-0.21971698105335236,
-0.011447629891335964,
0.004324150271713734,
0.07672344893217087,
-0.2671442925930023,
-0.15025927126407623,
-0.13100364804267883,
-0.031266361474990845,
-0.052343908697366714,
0.11133459210395813,
0.10859271883964539,
0.01988133043050766,
-0.005162734538316727,
-0.13028131425380707,
-0.036550942808389664,
0.07833748310804367,
-0.11692065000534058,
-0.05014590919017792
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SMIDS_3x_beit_large_Adamax_lr0001_fold5
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1085
- Accuracy: 0.9133
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1874 | 1.0 | 450 | 0.2642 | 0.9067 |
| 0.3866 | 2.0 | 900 | 0.3187 | 0.9017 |
| 0.0948 | 3.0 | 1350 | 0.4617 | 0.8867 |
| 0.0401 | 4.0 | 1800 | 0.5973 | 0.9033 |
| 0.1313 | 5.0 | 2250 | 0.7304 | 0.9 |
| 0.0588 | 6.0 | 2700 | 0.6472 | 0.9083 |
| 0.0001 | 7.0 | 3150 | 0.8444 | 0.885 |
| 0.0439 | 8.0 | 3600 | 0.8789 | 0.895 |
| 0.0001 | 9.0 | 4050 | 0.7443 | 0.9017 |
| 0.0 | 10.0 | 4500 | 0.8103 | 0.9 |
| 0.0005 | 11.0 | 4950 | 0.7976 | 0.9033 |
| 0.003 | 12.0 | 5400 | 0.8613 | 0.915 |
| 0.0282 | 13.0 | 5850 | 0.7804 | 0.9133 |
| 0.0014 | 14.0 | 6300 | 0.7984 | 0.905 |
| 0.0109 | 15.0 | 6750 | 0.9148 | 0.9 |
| 0.0137 | 16.0 | 7200 | 0.9900 | 0.9167 |
| 0.018 | 17.0 | 7650 | 0.9748 | 0.9033 |
| 0.0 | 18.0 | 8100 | 0.9534 | 0.9083 |
| 0.0 | 19.0 | 8550 | 1.0229 | 0.9 |
| 0.0 | 20.0 | 9000 | 1.0013 | 0.9083 |
| 0.0 | 21.0 | 9450 | 1.0294 | 0.9117 |
| 0.0 | 22.0 | 9900 | 1.0297 | 0.905 |
| 0.073 | 23.0 | 10350 | 0.8401 | 0.9083 |
| 0.0 | 24.0 | 10800 | 0.9954 | 0.8983 |
| 0.0 | 25.0 | 11250 | 0.9643 | 0.9 |
| 0.0001 | 26.0 | 11700 | 1.0231 | 0.9 |
| 0.0 | 27.0 | 12150 | 1.0523 | 0.8983 |
| 0.0 | 28.0 | 12600 | 1.0970 | 0.9033 |
| 0.0 | 29.0 | 13050 | 1.1122 | 0.9033 |
| 0.0 | 30.0 | 13500 | 1.0836 | 0.9067 |
| 0.0 | 31.0 | 13950 | 1.0762 | 0.9033 |
| 0.0 | 32.0 | 14400 | 1.0758 | 0.9067 |
| 0.0 | 33.0 | 14850 | 1.1027 | 0.9033 |
| 0.0 | 34.0 | 15300 | 1.1037 | 0.9017 |
| 0.0 | 35.0 | 15750 | 1.1210 | 0.9133 |
| 0.0 | 36.0 | 16200 | 1.1154 | 0.9083 |
| 0.0 | 37.0 | 16650 | 1.1432 | 0.91 |
| 0.0 | 38.0 | 17100 | 1.0947 | 0.9117 |
| 0.0 | 39.0 | 17550 | 1.1108 | 0.9117 |
| 0.0 | 40.0 | 18000 | 1.1310 | 0.9083 |
| 0.0 | 41.0 | 18450 | 1.1270 | 0.9083 |
| 0.0 | 42.0 | 18900 | 1.0919 | 0.9133 |
| 0.0 | 43.0 | 19350 | 1.1003 | 0.915 |
| 0.0 | 44.0 | 19800 | 1.1060 | 0.9133 |
| 0.0 | 45.0 | 20250 | 1.1151 | 0.9117 |
| 0.0 | 46.0 | 20700 | 1.1080 | 0.915 |
| 0.0 | 47.0 | 21150 | 1.1070 | 0.915 |
| 0.0 | 48.0 | 21600 | 1.1047 | 0.915 |
| 0.0 | 49.0 | 22050 | 1.1066 | 0.9133 |
| 0.0 | 50.0 | 22500 | 1.1085 | 0.9133 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_3x_beit_large_Adamax_lr0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9133333333333333, "name": "Accuracy"}]}]}]} | image-classification | onizukal/SMIDS_3x_beit_large_Adamax_lr0001_fold5 | [
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-large-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T03:45:17+00:00 | [] | [] | TAGS
#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| SMIDS\_3x\_beit\_large\_Adamax\_lr0001\_fold5
=============================================
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1085
* Accuracy: 0.9133
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.2
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
"TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
81,
115,
4,
30
] | [
"passage: TAGS\n#transformers #pytorch #beit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-microsoft/beit-large-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.1\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1\n* Datasets 2.12.0\n* Tokenizers 0.13.2"
] | [
-0.12968555092811584,
0.17251011729240417,
-0.0023243443574756384,
0.1362919956445694,
0.1120586097240448,
0.015268749557435513,
0.14003369212150574,
0.16890837252140045,
-0.08239254355430603,
0.046998485922813416,
0.14023225009441376,
0.13628867268562317,
0.046756189316511154,
0.19432850182056427,
-0.052493587136268616,
-0.26022207736968994,
0.04113864526152611,
0.032812196761369705,
-0.020441479980945587,
0.1235608458518982,
0.09337224811315536,
-0.13087525963783264,
0.11667836457490921,
0.0301132183521986,
-0.20004093647003174,
-0.036873914301395416,
-0.007245634216815233,
-0.06722474098205566,
0.10533155500888824,
-0.0034045001957565546,
0.0691065788269043,
0.03768180310726166,
0.08387713134288788,
-0.13018712401390076,
0.002076903358101845,
0.042768821120262146,
0.0062860166653990746,
0.10383369028568268,
0.054196570068597794,
-0.015545758418738842,
0.0701410248875618,
-0.06851525604724884,
0.0672622099518776,
0.009240911342203617,
-0.11321496963500977,
-0.2700493633747101,
-0.10203396528959274,
0.07240316271781921,
0.08221714198589325,
0.06822962313890457,
0.008172801695764065,
0.16417047381401062,
-0.014714903198182583,
0.10454332083463669,
0.23100516200065613,
-0.26415953040122986,
-0.05532161891460419,
0.029576225206255913,
0.015004046261310577,
0.06490366160869598,
-0.10617698729038239,
-0.01859438419342041,
0.020827138796448708,
0.04436356946825981,
0.1411312073469162,
-0.010821618139743805,
-0.028378209099173546,
-0.021572042256593704,
-0.10856294631958008,
-0.08875563740730286,
0.18566860258579254,
0.05809066444635391,
-0.048288628458976746,
-0.07735078781843185,
-0.07127056270837784,
-0.17220835387706757,
-0.041861895471811295,
0.009548050351440907,
0.041730549186468124,
-0.04684269055724144,
-0.10686429589986801,
-0.031055882573127747,
-0.078252874314785,
-0.051669858396053314,
-0.023303553462028503,
0.13525931537151337,
0.03357808664441109,
0.05729198828339577,
-0.03593141585588455,
0.09915280342102051,
0.006841922644525766,
-0.17527513206005096,
-0.028045548126101494,
-0.0016165260458365083,
0.01563161052763462,
-0.020048104226589203,
-0.03057136945426464,
-0.06562764942646027,
-0.0016239769756793976,
0.149040088057518,
-0.06106079742312431,
0.06079873815178871,
-0.0069216229021549225,
0.04031313583254814,
-0.0486484132707119,
0.18668954074382782,
-0.028643600642681122,
-0.016713637858629227,
0.02057800441980362,
0.08857519924640656,
0.06818821281194687,
-0.03644402697682381,
-0.12566283345222473,
0.03087625838816166,
0.1283741444349289,
0.0027549222577363253,
-0.021953243762254715,
0.053039632737636566,
-0.06444176286458969,
-0.05842158570885658,
0.09141092747449875,
-0.08884678035974503,
0.03514961525797844,
-0.01055920124053955,
-0.08416686952114105,
-0.06807748228311539,
0.02709859050810337,
0.018840007483959198,
-0.00014874596672598273,
0.07201956957578659,
-0.09116632491350174,
0.015490563586354256,
-0.06551176309585571,
-0.10091431438922882,
0.01564670167863369,
-0.11040772497653961,
0.012323775328695774,
-0.09688954800367355,
-0.1969451904296875,
0.006960712838917971,
0.07738039642572403,
-0.05607226490974426,
-0.06792453676462173,
-0.03661259636282921,
-0.07637017965316772,
0.04143770784139633,
-0.01186586357653141,
0.07317496836185455,
-0.07456725090742111,
0.09119440615177155,
0.02237127535045147,
0.08760105073451996,
-0.056383248418569565,
0.04597126320004463,
-0.10241573303937912,
0.04992371052503586,
-0.19877833127975464,
0.07988634705543518,
-0.049189720302820206,
0.06190093979239464,
-0.09581396728754044,
-0.10568851977586746,
0.033553607761859894,
-0.04994693025946617,
0.068512924015522,
0.09739063680171967,
-0.17317676544189453,
-0.05787286534905434,
0.13517500460147858,
-0.09691634029150009,
-0.14840039610862732,
0.10115666687488556,
-0.05093328654766083,
0.019768450409173965,
0.04739697277545929,
0.21447287499904633,
0.062935970723629,
-0.0910891741514206,
-0.025994082912802696,
-0.03333966061472893,
0.044677652418613434,
-0.06483115255832672,
0.101903036236763,
0.027484174817800522,
0.0531504862010479,
0.02367355115711689,
-0.03332329913973808,
0.03818739578127861,
-0.08385370671749115,
-0.10085898637771606,
-0.05038752406835556,
-0.08557170629501343,
0.039683446288108826,
0.05594057962298393,
0.059847064316272736,
-0.10873348265886307,
-0.09023979306221008,
0.041734639555215836,
0.09406744688749313,
-0.07396076619625092,
0.02903648279607296,
-0.0904788002371788,
0.11622294038534164,
-0.08363831788301468,
-0.02404896728694439,
-0.17903628945350647,
-0.0417308546602726,
0.04055763781070709,
-0.01668366603553295,
-0.006775525398552418,
-0.0494389571249485,
0.07092705368995667,
0.087753064930439,
-0.05281677842140198,
-0.052284084260463715,
-0.05530114471912384,
0.008562305010855198,
-0.11059658974409103,
-0.1778055727481842,
-0.080107681453228,
-0.03797448053956032,
0.15019145607948303,
-0.15246915817260742,
0.0224970243871212,
0.0616903156042099,
0.12470164895057678,
0.05992257222533226,
-0.0469760037958622,
-0.007631834130734205,
0.0217386856675148,
-0.05561714619398117,
-0.0865136981010437,
0.05727535858750343,
0.035165008157491684,
-0.07172347605228424,
-0.019373787567019463,
-0.10040221363306046,
0.15015454590320587,
0.13185308873653412,
-0.0021352346520870924,
-0.045590728521347046,
-0.012053865939378738,
-0.06572475284337997,
-0.030354894697666168,
-0.04096601903438568,
0.01860888861119747,
0.1020345464348793,
0.017360014840960503,
0.14407898485660553,
-0.09213681519031525,
-0.037007302045822144,
0.053231216967105865,
-0.028658904135227203,
-0.03313332051038742,
0.0737093985080719,
0.021478038281202316,
-0.14289474487304688,
0.1502111405134201,
0.14915579557418823,
-0.04949729144573212,
0.12371271848678589,
-0.03663388267159462,
-0.06141006201505661,
-0.04545919969677925,
-0.03777514770627022,
0.01429951936006546,
0.1407921016216278,
-0.08363746106624603,
-0.006257671397179365,
0.05626929551362991,
0.018998416140675545,
-0.007220869418233633,
-0.1808812916278839,
0.0005758196348324418,
0.03530525416135788,
-0.04614398628473282,
-0.022574707865715027,
-0.014720434322953224,
0.000520858506206423,
0.09188775718212128,
0.02001834660768509,
-0.07113038748502731,
0.05185159295797348,
0.010694033466279507,
-0.056145116686820984,
0.16459684073925018,
-0.07884351164102554,
-0.19753409922122955,
-0.11793240904808044,
-0.08745986223220825,
-0.10736268758773804,
0.013000035658478737,
0.067270427942276,
-0.050670597702264786,
-0.04932181537151337,
-0.1026671901345253,
-0.044550344347953796,
0.021845674142241478,
0.024347107857465744,
0.053595975041389465,
-0.00796813890337944,
0.08411940932273865,
-0.09194666892290115,
-0.03317512199282646,
-0.014813165180385113,
0.01894056238234043,
0.0670066773891449,
0.01914203353226185,
0.11091019958257675,
0.08160436898469925,
-0.0286879725754261,
0.05666669085621834,
-0.01685662567615509,
0.26526889204978943,
-0.06748054921627045,
-0.006749235559254885,
0.1391732543706894,
-0.013490693643689156,
0.0842166393995285,
0.12729591131210327,
0.04176322743296623,
-0.0955888107419014,
-0.01310211792588234,
-0.0005005627172067761,
-0.05257550999522209,
-0.1536482274532318,
-0.04132819548249245,
-0.04548354819417,
-0.0018228141125291586,
0.13951772451400757,
0.038064174354076385,
0.02505229413509369,
0.07843583822250366,
0.020602436736226082,
0.05678323283791542,
-0.0175874512642622,
0.10429482907056808,
0.08156884461641312,
0.06449971348047256,
0.13376133143901825,
-0.036523740738630295,
-0.019790813326835632,
0.05638623237609863,
0.042081572115421295,
0.20467498898506165,
-0.025362396612763405,
0.14717818796634674,
0.026553483679890633,
0.19327539205551147,
0.017808275297284126,
0.07306244969367981,
-0.014873637817800045,
0.0007499073399230838,
-0.019323905929923058,
-0.04713669419288635,
-0.0638502836227417,
0.03312433883547783,
-0.016851995140314102,
0.05682634562253952,
-0.09328699111938477,
0.03906902298331261,
0.05959288775920868,
0.30634987354278564,
0.0654144361615181,
-0.4125381410121918,
-0.09821337461471558,
0.012344546616077423,
0.0008716733427718282,
-0.05509618669748306,
-0.007402430288493633,
0.0980701595544815,
-0.09973937273025513,
0.0819711834192276,
-0.09416680037975311,
0.08507230132818222,
-0.0846736952662468,
0.020382488146424294,
0.07683569937944412,
0.055889930576086044,
0.012921135872602463,
0.05964238941669464,
-0.21880683302879333,
0.2499670386314392,
0.01837102696299553,
0.04415145888924599,
-0.08875706046819687,
0.009965145029127598,
0.03320525959134102,
0.05923061817884445,
0.08590700477361679,
0.0061045982874929905,
-0.09025654941797256,
-0.18889141082763672,
-0.12562422454357147,
0.000394518458051607,
0.06176565960049629,
-0.03729195147752762,
0.09444484859704971,
-0.018019067123532295,
-0.012201022356748581,
0.02127370797097683,
0.0009904175531119108,
-0.035084888339042664,
-0.10356581956148148,
0.02010609768331051,
0.03430531173944473,
-0.011726552620530128,
-0.06489048153162003,
-0.11480618268251419,
-0.035277001559734344,
0.16168422996997833,
0.05518770217895508,
-0.07543513178825378,
-0.14076673984527588,
0.0721859410405159,
0.0775376707315445,
-0.08563373237848282,
0.03936640918254852,
-0.016648126766085625,
0.14995604753494263,
0.020845195278525352,
-0.0889848992228508,
0.10199198871850967,
-0.05838112160563469,
-0.17863209545612335,
-0.04141612723469734,
0.09901762008666992,
0.007052883040159941,
0.05273612216114998,
0.004226623103022575,
0.06022334843873978,
-0.03518751636147499,
-0.05844981223344803,
0.06672939658164978,
-0.007545650005340576,
0.10645230114459991,
-0.014578265137970448,
0.008669902570545673,
0.028680432587862015,
-0.046410609036684036,
0.00012374592188280076,
0.1686571091413498,
0.24114695191383362,
-0.10427109152078629,
0.060499124228954315,
0.03038850799202919,
-0.030858036130666733,
-0.18259160220623016,
0.01086394116282463,
0.07622820883989334,
-0.00013084696547593921,
0.04143662750720978,
-0.1601918637752533,
0.05532059073448181,
0.10498367995023727,
-0.043228019028902054,
0.08107142895460129,
-0.27694207429885864,
-0.1185181736946106,
0.09238865971565247,
0.13856256008148193,
0.06877914071083069,
-0.13106170296669006,
-0.043299052864313126,
-0.041688259690999985,
-0.17338812351226807,
0.13653364777565002,
-0.057192787528038025,
0.1145344004034996,
-0.039500072598457336,
0.08082033693790436,
0.014952262863516808,
-0.056017596274614334,
0.14574900269508362,
0.0056154001504182816,
0.08686088770627975,
-0.07213473320007324,
-0.0020430299919098616,
0.10663212835788727,
-0.10254329442977905,
0.07232339680194855,
-0.08735590428113937,
0.0618043914437294,
-0.10790637135505676,
-0.003900582902133465,
-0.07402003556489944,
0.013697824440896511,
-0.01366274245083332,
-0.04917207732796669,
-0.04516566917300224,
0.03515308350324631,
0.0627121776342392,
-0.01822420209646225,
0.20940853655338287,
0.06430324167013168,
0.08635561168193817,
0.1727360188961029,
0.054769597947597504,
-0.10558480769395828,
-0.09403572231531143,
-0.043973103165626526,
-0.029537810012698174,
0.05986782908439636,
-0.1372820883989334,
0.0528247207403183,
0.11996810883283615,
0.013451187871396542,
0.12858225405216217,
0.055897701531648636,
-0.030677761882543564,
0.03560479357838631,
0.062153734266757965,
-0.17216050624847412,
-0.08662130683660507,
-0.009840693324804306,
0.030872231349349022,
-0.13055209815502167,
0.0458756685256958,
0.12116101384162903,
-0.05953402817249298,
-0.015017039142549038,
-0.004467411432415247,
0.03673877567052841,
-0.00978675577789545,
0.15920081734657288,
0.048089753836393356,
0.055168475955724716,
-0.11802823096513748,
0.11332250386476517,
0.05730176344513893,
-0.07302459329366684,
0.03206014260649681,
0.05020790174603462,
-0.1039617657661438,
-0.021727759391069412,
0.03114185482263565,
0.15037071704864502,
-0.06283780187368393,
-0.045329563319683075,
-0.1358855813741684,
-0.09226331859827042,
0.06643375009298325,
0.07981554418802261,
0.09349396824836731,
0.016502337530255318,
-0.03525979816913605,
-0.013309485279023647,
-0.10845191776752472,
0.11000601947307587,
0.04338005557656288,
0.09121100604534149,
-0.17974577844142914,
0.05434896796941757,
-0.001805671607144177,
0.07240304350852966,
-0.02173563651740551,
-0.00018242778605781496,
-0.08797106891870499,
0.0035262287128716707,
-0.10818753391504288,
0.024682866409420967,
-0.052850391715765,
0.006376184988766909,
-0.020511267706751823,
-0.05819518491625786,
-0.06372886151075363,
0.024663057178258896,
-0.1193968653678894,
-0.05304655060172081,
0.02193489298224449,
0.03176874667406082,
-0.11983832716941833,
-0.04395153746008873,
0.02043171599507332,
-0.08966860175132751,
0.09786758571863174,
0.06017395853996277,
-0.00797541905194521,
0.007467431016266346,
0.0038150406908243895,
-0.022212069481611252,
0.06630469858646393,
0.0074848150834441185,
0.08584009110927582,
-0.11553936451673508,
-0.022143544629216194,
0.016299601644277573,
-0.004447818733751774,
0.018147116526961327,
0.1585858017206192,
-0.12092386186122894,
0.00018621055642142892,
-0.014765054918825626,
-0.06592588871717453,
-0.06358986347913742,
0.0692417323589325,
0.10919524729251862,
0.02367839775979519,
0.2122299075126648,
-0.054594267159700394,
0.015877852216362953,
-0.21000300347805023,
-0.011462570168077946,
0.005311926826834679,
-0.13887609541416168,
-0.10537440329790115,
-0.032787878066301346,
0.0637630894780159,
-0.07039659470319748,
0.1177176982164383,
0.03537357598543167,
0.020886771380901337,
0.02911887876689434,
0.024869181215763092,
-0.002677198965102434,
0.013766518794000149,
0.1633930504322052,
0.014011929742991924,
-0.02872646041214466,
0.1283825933933258,
0.029096294194459915,
0.09337089955806732,
0.11805824935436249,
0.1763046532869339,
0.11451227962970734,
0.0477789007127285,
0.09043081104755402,
0.0520024336874485,
-0.02513159066438675,
-0.22147811949253082,
0.036259569227695465,
-0.039764102548360825,
0.1483127623796463,
-0.0033327124547213316,
0.15980194509029388,
0.09223487228155136,
-0.18392090499401093,
0.040660299360752106,
-0.037005215883255005,
-0.07937940210103989,
-0.08421849459409714,
-0.12178675830364227,
-0.1033017709851265,
-0.1509413868188858,
0.0028559700585901737,
-0.10428426414728165,
0.022927863523364067,
0.11217869818210602,
-0.008710348978638649,
-0.010019375011324883,
0.11695955693721771,
-0.026584560051560402,
0.026202335953712463,
0.03870072960853577,
0.00616151699796319,
-0.05987776443362236,
-0.04411191865801811,
-0.08036603778600693,
0.014018801040947437,
0.03200533241033554,
0.055842287838459015,
-0.03226681798696518,
-0.007200593128800392,
0.03782269358634949,
-0.009845683351159096,
-0.12363012880086899,
0.013544945046305656,
0.004753641318529844,
0.05189259722828865,
0.0008605605689808726,
0.01290043629705906,
0.03187544271349907,
-0.015199882909655571,
0.193119078874588,
-0.07321906089782715,
-0.02744952403008938,
-0.12274995446205139,
0.17869888246059418,
0.0023205638863146305,
-0.049724213778972626,
0.05292708799242973,
-0.09127075970172882,
-0.020290102809667587,
0.1547212302684784,
0.18941837549209595,
-0.07176556438207626,
-0.01638839766383171,
-0.017501909285783768,
-0.01388427522033453,
-0.022741587832570076,
0.09889717400074005,
0.09887372702360153,
-0.007504772394895554,
-0.07518953084945679,
-0.028498217463493347,
-0.06611054390668869,
-0.03444022685289383,
-0.03838160261511803,
0.06909165531396866,
-0.004605968948453665,
0.007089514285326004,
-0.0751754567027092,
0.04334408789873123,
-0.02207781746983528,
-0.060899440199136734,
0.06262887269258499,
-0.21282166242599487,
-0.17796695232391357,
0.006926008500158787,
0.07579630613327026,
0.0016649233875796199,
0.04621230810880661,
-0.010005760937929153,
0.018681904301047325,
0.07549776136875153,
-0.022177988663315773,
-0.0866948589682579,
-0.09604813903570175,
0.1083223819732666,
-0.1344224065542221,
0.25299492478370667,
-0.03893125429749489,
0.035907670855522156,
0.12175600975751877,
0.041717030107975006,
-0.13353091478347778,
0.033571965992450714,
0.03969275578856468,
-0.03212675452232361,
0.005746500100940466,
0.14248594641685486,
-0.037242501974105835,
0.07988674938678741,
0.04599026218056679,
-0.10243327170610428,
-0.039464809000492096,
-0.04960913211107254,
-0.011240639723837376,
-0.024744588881731033,
-0.05439573898911476,
-0.03649099916219711,
0.13208730518817902,
0.17168967425823212,
-0.04232889041304588,
-0.023784559220075607,
-0.06460724771022797,
0.030773790553212166,
0.0774260088801384,
-0.033050306141376495,
-0.05197038874030113,
-0.23585109412670135,
0.0024181774351745844,
0.05249672383069992,
-0.013345940038561821,
-0.20789918303489685,
-0.11062979698181152,
0.006115853786468506,
-0.05795856565237045,
-0.07630864530801773,
0.09230074286460876,
0.06326484680175781,
0.035358402878046036,
-0.06319575011730194,
0.03810267895460129,
-0.07874377071857452,
0.1419457346200943,
-0.1448507308959961,
-0.07860494405031204
] |
null | null | transformers |
## Model Summary
net5-base is a Nepali version of the mt5-base model. Unlike the mt5 model, the tokenizer in net5-base contains only the vocabulary of nepali and english words. This minimizes the cross language generation error. This model can be used for any text generation tasks on nepali language.
| {"language": ["ne", "en"], "library_name": "transformers", "datasets": ["Someman/news_nepali"], "metrics": ["rouge"], "pipeline_tag": "text2text-generation"} | text2text-generation | Angeldahal404/net5-base | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"ne",
"en",
"dataset:Someman/news_nepali",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:46:28+00:00 | [] | [
"ne",
"en"
] | TAGS
#transformers #safetensors #t5 #text2text-generation #ne #en #dataset-Someman/news_nepali #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
## Model Summary
net5-base is a Nepali version of the mt5-base model. Unlike the mt5 model, the tokenizer in net5-base contains only the vocabulary of nepali and english words. This minimizes the cross language generation error. This model can be used for any text generation tasks on nepali language.
| [
"## Model Summary\n\nnet5-base is a Nepali version of the mt5-base model. Unlike the mt5 model, the tokenizer in net5-base contains only the vocabulary of nepali and english words. This minimizes the cross language generation error. This model can be used for any text generation tasks on nepali language."
] | [
"TAGS\n#transformers #safetensors #t5 #text2text-generation #ne #en #dataset-Someman/news_nepali #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## Model Summary\n\nnet5-base is a Nepali version of the mt5-base model. Unlike the mt5 model, the tokenizer in net5-base contains only the vocabulary of nepali and english words. This minimizes the cross language generation error. This model can be used for any text generation tasks on nepali language."
] | [
65,
73
] | [
"passage: TAGS\n#transformers #safetensors #t5 #text2text-generation #ne #en #dataset-Someman/news_nepali #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n## Model Summary\n\nnet5-base is a Nepali version of the mt5-base model. Unlike the mt5 model, the tokenizer in net5-base contains only the vocabulary of nepali and english words. This minimizes the cross language generation error. This model can be used for any text generation tasks on nepali language."
] | [
0.0054865637794137,
-0.05430147051811218,
0.0005783721571788192,
0.034262314438819885,
0.09316693246364594,
-0.037178728729486465,
0.05976736173033714,
0.08109669387340546,
0.0013341802405193448,
-0.0012474036775529385,
0.18854956328868866,
0.05022754892706871,
0.004028439521789551,
0.1932584047317505,
-0.003929697908461094,
-0.25724121928215027,
0.09183492511510849,
0.015900220721960068,
0.047753702849149704,
0.0977761521935463,
0.12005443125963211,
-0.05221448838710785,
0.08033724874258041,
0.003356419736519456,
-0.08310714364051819,
0.11157618463039398,
0.0505383163690567,
-0.08708786219358444,
0.015599108301103115,
0.01916639320552349,
0.05839257687330246,
0.08242930471897125,
-0.043439336121082306,
-0.15071438252925873,
0.03400374576449394,
-0.0050749098882079124,
-0.011992783285677433,
-0.03921879827976227,
0.018336031585931778,
-0.0336625836789608,
0.15598250925540924,
-0.06297348439693451,
-0.03367587924003601,
0.0587536059319973,
-0.0514468178153038,
0.018312115222215652,
0.08630616217851639,
0.06666044145822525,
0.06023053824901581,
0.0627516657114029,
-0.033707693219184875,
0.21016916632652283,
-0.06616614013910294,
0.09892227500677109,
-0.014309055171906948,
-0.22882528603076935,
-0.033475808799266815,
0.19139432907104492,
-0.0649053081870079,
0.1778641790151596,
0.011461442336440086,
0.07951676845550537,
0.12101113051176071,
-0.011181549169123173,
0.06615015119314194,
-0.08287513256072998,
-0.11991522461175919,
-0.0004200102121103555,
-0.10634078085422516,
0.04200367256999016,
0.23283670842647552,
-0.046499524265527725,
0.03501613438129425,
0.006666462868452072,
-0.10250134021043777,
0.09193900227546692,
-0.0006603206275030971,
-0.07166565954685211,
-0.06317334622144699,
0.1158868595957756,
0.09750529378652573,
-0.05964924022555351,
-0.10184003412723541,
0.012169941328465939,
-0.07313034683465958,
-0.08960746228694916,
-0.012684949673712254,
0.04105981066823006,
-0.13997799158096313,
-0.014399915002286434,
-0.17352694272994995,
-0.09345129877328873,
0.002212249906733632,
-0.14885856211185455,
-0.0038219764828681946,
-0.007265691179782152,
0.017589854076504707,
-0.1883036196231842,
0.09289161115884781,
-0.06263592839241028,
0.03560110181570053,
0.11017504334449768,
-0.08216335624456406,
0.020922217518091202,
0.06192474812269211,
-0.01603698544204235,
-0.04558528959751129,
-0.08877689391374588,
0.06701432168483734,
-0.040967244654893875,
0.09262753278017044,
-0.06789485365152359,
-0.04132412001490593,
-0.02239166758954525,
0.046786971390247345,
0.05098695307970047,
-0.040881793946027756,
0.12431894242763519,
0.060588475316762924,
-0.03342821076512337,
0.10385734587907791,
-0.09882095456123352,
-0.09492536634206772,
-0.029054732993245125,
0.024369390681385994,
0.14098167419433594,
-0.027585355564951897,
0.04485204815864563,
-0.10431300848722458,
-0.14391978085041046,
-0.09876367449760437,
-0.07805351167917252,
-0.051978062838315964,
-0.03917549550533295,
0.003183870343491435,
-0.07345151901245117,
-0.006858444306999445,
-0.1554863154888153,
-0.2788185179233551,
0.019523296505212784,
0.0610593818128109,
-0.05427933111786842,
-0.025005122646689415,
-0.10700905323028564,
-0.0012491884408518672,
0.07202357053756714,
-0.07481856644153595,
0.03748325631022453,
-0.036467961966991425,
-0.03305666148662567,
0.00987714622169733,
0.10438518971204758,
-0.08735598623752594,
0.005920973606407642,
-0.1246061623096466,
0.046381253749132156,
-0.13799799978733063,
0.08427992463111877,
-0.07780324667692184,
0.10275611281394958,
-0.05339832976460457,
0.03365147486329079,
-0.031370747834444046,
0.008771136403083801,
-0.024284157902002335,
0.19317662715911865,
-0.16811470687389374,
-0.06711942702531815,
0.045279886573553085,
-0.21392324566841125,
-0.17403645813465118,
0.10448917746543884,
0.005994102917611599,
0.19442619383335114,
0.10693839937448502,
0.23034825921058655,
0.13644270598888397,
0.058835405856370926,
0.062265705317258835,
0.0323144905269146,
-0.06799165904521942,
-0.08554322272539139,
-0.029001524671912193,
0.07411965727806091,
-0.1981285661458969,
0.08457507193088531,
-0.01279503758996725,
0.0009529164526611567,
-0.028228716924786568,
-0.04099457338452339,
-0.09804026037454605,
-0.06949674338102341,
0.05561007559299469,
-0.004820001777261496,
0.1061469316482544,
-0.08471543341875076,
0.03634396195411682,
0.12541435658931732,
0.043426163494586945,
-0.07498877495527267,
0.05429667979478836,
-0.08910447359085083,
0.01911146007478237,
-0.10044922679662704,
0.026907553896307945,
-0.08044130355119705,
0.032894525676965714,
0.028661640360951424,
0.04088783636689186,
0.009601271711289883,
0.0582553967833519,
0.03578101843595505,
-0.07482042163610458,
-0.08350960165262222,
0.04030868038535118,
0.2098935842514038,
0.04285350814461708,
-0.030236361548304558,
-0.1279975026845932,
0.08532123267650604,
-0.06366250663995743,
-0.003995982464402914,
-0.18379426002502441,
0.004059651400893927,
-0.038894958794116974,
0.15064136683940887,
-0.025972148403525352,
0.08308373391628265,
0.06147478520870209,
0.030564429238438606,
-0.030619846656918526,
-0.010152691043913364,
0.0703946202993393,
0.040991783142089844,
-0.11698117107152939,
0.20786641538143158,
-0.08804214000701904,
0.03749381750822067,
0.1274137794971466,
-0.1435890942811966,
0.07612557709217072,
-0.011355247348546982,
0.038548197597265244,
-0.05560928210616112,
0.04292776808142662,
0.07740724831819534,
0.001384821953251958,
-0.06471037864685059,
0.12026714533567429,
-0.1145978569984436,
0.019736599177122116,
0.026203026995062828,
-0.055667176842689514,
-0.10149949043989182,
0.03425942361354828,
-0.0073111215606331825,
-0.28269004821777344,
0.12859442830085754,
0.09102772921323776,
-0.027648067101836205,
0.29898568987846375,
0.017294693738222122,
-0.03073604591190815,
0.020313149318099022,
0.0019293477525934577,
-0.0669713020324707,
-0.08300433307886124,
-0.23211632668972015,
-0.07089144736528397,
0.028539996594190598,
0.05110011249780655,
0.1251479536294937,
0.021226223558187485,
0.014272589236497879,
-0.0260942243039608,
-0.0038304151967167854,
-0.003563347039744258,
0.0796370655298233,
-0.08980679512023926,
0.054665904492139816,
-0.03968921676278114,
0.05558020621538162,
0.0539889857172966,
0.011169010773301125,
-0.17706888914108276,
0.1500409096479416,
-0.1429411768913269,
-0.33184385299682617,
-0.11731600761413574,
-0.02392786554992199,
-0.11694387346506119,
0.042377691715955734,
0.0264997910708189,
-0.1787349134683609,
-0.11100475490093231,
-0.13643863797187805,
-0.026056617498397827,
-0.04920963943004608,
0.03985128179192543,
0.02128939889371395,
0.012872924096882343,
-0.024635184556245804,
-0.0923963338136673,
-0.006030605640262365,
-0.001126633957028389,
-0.02898656390607357,
0.08090344816446304,
-0.22764375805854797,
-0.030246110633015633,
0.15555010735988617,
-0.018444892019033432,
0.046116821467876434,
-0.0010617764201015234,
0.14119932055473328,
-0.016610480844974518,
0.10108862817287445,
0.12369643151760101,
0.007325298152863979,
0.009679964743554592,
0.19549478590488434,
-0.05060466006398201,
-0.03142217919230461,
0.11491825431585312,
-0.01371315773576498,
-0.07877716422080994,
-0.2650017738342285,
-0.07822816073894501,
-0.08291424810886383,
0.035279348492622375,
-0.027897648513317108,
0.035180967301130295,
0.10581234097480774,
0.11039764434099197,
-0.009557293727993965,
-0.023448888212442398,
0.033158693462610245,
0.06420694291591644,
0.16048556566238403,
-0.02075980044901371,
0.13496501743793488,
-0.09817877411842346,
0.02040463127195835,
0.07590946555137634,
0.03669549897313118,
0.15831558406352997,
0.051998320966959,
0.04718196392059326,
0.08633602410554886,
0.09423080086708069,
0.1892547607421875,
0.06869083642959595,
-0.08335001766681671,
-0.05951067432761192,
0.016145752742886543,
-0.0494719073176384,
-0.037453021854162216,
0.07488863170146942,
-0.075163334608078,
-0.012942219153046608,
0.021304557099938393,
0.08925530314445496,
0.06972592324018478,
0.0864216610789299,
0.05910588055849075,
-0.10976741462945938,
-0.04466364532709122,
0.11546260118484497,
-0.008549017831683159,
-0.0624300055205822,
0.10225042700767517,
0.08151929825544357,
-0.03264274448156357,
0.14853113889694214,
0.04877784103155136,
0.09667857736349106,
0.028528451919555664,
0.028609221801161766,
-0.21169936656951904,
-0.062019381672143936,
-0.042553599923849106,
0.06809516251087189,
-0.26475316286087036,
0.19092711806297302,
0.05660906061530113,
0.009259657002985477,
-0.04942702502012253,
-0.05046581104397774,
-0.023394132032990456,
0.20620059967041016,
0.036217909306287766,
0.027736397460103035,
-0.18689973652362823,
0.051579564809799194,
0.01765088550746441,
0.06960266083478928,
0.04910895600914955,
0.18472200632095337,
0.01210295781493187,
-0.03150010481476784,
-0.004506148863583803,
0.014762035571038723,
0.08991851657629013,
-0.27729499340057373,
-0.09242671728134155,
-0.009685889817774296,
0.1252809762954712,
-0.06637152284383774,
-0.04009799286723137,
-0.04902009665966034,
0.021484287455677986,
0.21065416932106018,
-0.03006400167942047,
-0.12828870117664337,
-0.08818347007036209,
-0.059659890830516815,
0.09520000964403152,
-0.051629114896059036,
0.08312433212995529,
-0.050209891051054,
0.10898616909980774,
-0.013328008353710175,
-0.1371309459209442,
0.06249985098838806,
-0.0768626406788826,
0.003282218938693404,
0.007972666062414646,
0.06165073439478874,
0.07628853619098663,
-0.04233989492058754,
0.04547136276960373,
-0.004984579049050808,
-0.029831694439053535,
-0.09108265489339828,
-0.07870377600193024,
0.08927169442176819,
-0.07135685533285141,
-0.0331248976290226,
-0.05472899228334427,
-0.14795593917369843,
-0.010918197222054005,
-0.14924462139606476,
0.1622520536184311,
0.05646128207445145,
-0.011292124167084694,
0.13381759822368622,
0.35538965463638306,
-0.09092038124799728,
-0.22724047303199768,
-0.004731659311801195,
-0.0483822263777256,
0.008052668534219265,
-0.10540904104709625,
0.007412308361381292,
0.09072895348072052,
0.040725018829107285,
0.01092820055782795,
-0.11813902854919434,
-0.08346275240182877,
-0.12264939397573471,
0.11566941440105438,
0.062325116246938705,
0.3766547739505768,
-0.09654910117387772,
-0.07809984683990479,
-0.09376110881567001,
-0.11740431934595108,
0.1367863118648529,
-0.2576068341732025,
0.023950494825839996,
-0.026386909186840057,
-0.017111802473664284,
-0.001550118438899517,
-0.03875206038355827,
0.059573765844106674,
0.023361623287200928,
-0.015298383310437202,
-0.07391134649515152,
0.04090438410639763,
0.16291193664073944,
-0.03457333892583847,
0.08732522279024124,
-0.016480091959238052,
0.04852991923689842,
-0.0335005447268486,
-0.09588297456502914,
-0.07677183300256729,
-0.023264115676283836,
0.00046603192458860576,
-0.1141374334692955,
0.01876966468989849,
0.04287010431289673,
0.07819180935621262,
-0.002313744043931365,
0.17298151552677155,
-0.1432630866765976,
0.12572358548641205,
0.3213476538658142,
0.1567743569612503,
-0.29352402687072754,
0.2729860842227936,
0.03009898215532303,
-0.07314933836460114,
0.03639095649123192,
-0.26484182476997375,
0.053692542016506195,
0.02840537391602993,
-0.03300129249691963,
0.055576663464307785,
0.01249254122376442,
0.005346438381820917,
-0.002760714152827859,
0.10539507865905762,
-0.027244769036769867,
-0.06003913655877113,
-0.03366747871041298,
-0.06516144424676895,
0.03130725771188736,
0.059643544256687164,
0.12353044003248215,
-0.118938148021698,
0.008190419524908066,
0.0024248205590993166,
-0.052144136279821396,
-0.059869617223739624,
0.08639022707939148,
0.11590120941400528,
0.019398631528019905,
-0.06367054581642151,
0.14266403019428253,
0.04951348155736923,
-0.07997733354568481,
-0.0038130292668938637,
0.10724367946386337,
-0.213917538523674,
-0.09569422155618668,
0.003166093723848462,
0.06829790771007538,
-0.09244536608457565,
-0.10568684339523315,
-0.022312572225928307,
-0.1103401705622673,
0.03077537566423416,
0.1574707329273224,
0.01713443361222744,
0.00959851499646902,
-0.061542075127363205,
-0.0419328436255455,
-0.010995144955813885,
0.047712184488773346,
0.06174573674798012,
0.04472972825169563,
-0.12230252474546432,
-0.009383898228406906,
0.04278559237718582,
0.06120844930410385,
-0.10080666095018387,
-0.07747922837734222,
-0.11395607888698578,
0.05593409016728401,
-0.19270123541355133,
0.03597066551446915,
-0.12442317605018616,
-0.05664053186774254,
-0.028932077810168266,
-0.09825775772333145,
-0.1424129605293274,
0.042847901582717896,
-0.031843435019254684,
0.08762955665588379,
-0.015546560287475586,
0.06373348832130432,
0.00787319429218769,
-0.023252783343195915,
0.07063394039869308,
0.006014812737703323,
0.015689760446548462,
0.023709090426564217,
-0.12123113125562668,
0.16857589781284332,
-0.16218723356723785,
0.021756501868367195,
0.039564378559589386,
0.031489480286836624,
0.0456104502081871,
-0.004792434629052877,
-0.03382735699415207,
0.13682110607624054,
0.051343925297260284,
0.03372189402580261,
0.013860732316970825,
-0.014194139279425144,
0.030961036682128906,
-0.09346187859773636,
-0.05468316748738289,
-0.02324547991156578,
-0.016099700704216957,
0.0941285640001297,
0.023098237812519073,
0.07963184267282486,
-0.10075773298740387,
-0.06764467805624008,
-0.04688185453414917,
0.030057856813073158,
0.007564918138086796,
-0.09593477845191956,
0.0025235149078071117,
-0.028192630037665367,
-0.03536253795027733,
-0.07286056876182556,
0.24899432063102722,
-0.11875835061073303,
-0.020712343975901604,
0.05396801605820656,
-0.07193931192159653,
-0.012411794625222683,
0.01474860031157732,
0.310165137052536,
0.11355644464492798,
0.010259262286126614,
-0.03966311365365982,
0.028379490599036217,
0.027802549302577972,
0.12924790382385254,
0.01709332875907421,
0.013136690482497215,
-0.038990553468465805,
0.13309341669082642,
-0.04653949290513992,
0.11970565468072891,
0.05143136903643608,
0.03301909565925598,
-0.1325899213552475,
0.03254525363445282,
-0.013518331572413445,
-0.025612659752368927,
0.4190501272678375,
-0.06619522720575333,
-0.01099602784961462,
0.007223918568342924,
-0.09561480581760406,
-0.1256280541419983,
-0.24755866825580597,
-0.1566377580165863,
-0.18202407658100128,
0.02166423387825489,
-0.11517705023288727,
0.004001045599579811,
0.03453482687473297,
0.13025568425655365,
-0.04705752432346344,
0.08279415220022202,
0.19107744097709656,
-0.07056663930416107,
0.026196666061878204,
-0.04061608761548996,
0.007641979493200779,
-0.022721705958247185,
-0.007308055181056261,
-0.05389537662267685,
0.002828005002811551,
-0.09128601104021072,
0.041218046098947525,
0.04078678786754608,
0.016766158863902092,
-0.021983977407217026,
-0.020574551075696945,
-0.0631784126162529,
0.03404860943555832,
-0.03588007390499115,
0.0728776678442955,
0.013006082735955715,
-0.12072928249835968,
0.032713908702135086,
0.13894428312778473,
0.00789070874452591,
-0.18074482679367065,
-0.10550957918167114,
0.20417135953903198,
0.03182360902428627,
0.09629812836647034,
0.01478564366698265,
-0.03942344710230827,
-0.1079484075307846,
0.2537476718425751,
0.2319626361131668,
0.0633714497089386,
0.0196125116199255,
-0.07332154363393784,
0.015750523656606674,
-0.024860434234142303,
0.15984447300434113,
0.046063538640737534,
0.06923262029886246,
-0.016073064878582954,
0.04659236595034599,
-0.07420958578586578,
-0.02897375077009201,
-0.11778393387794495,
0.11766686290502548,
0.056119389832019806,
-0.05886378884315491,
-0.01508056279271841,
0.08423642069101334,
-0.16840748488903046,
0.17070938646793365,
-0.1728428304195404,
-0.04524246230721474,
-0.06986222416162491,
-0.0725531056523323,
-0.04363219439983368,
-0.05635293945670128,
-0.024549048393964767,
-0.0034004293847829103,
0.03171318769454956,
-0.0925074964761734,
0.06778168678283691,
-0.10925108194351196,
-0.1234193965792656,
0.0924287885427475,
0.05996409431099892,
0.06311710923910141,
0.025736359879374504,
-0.028331853449344635,
0.07669881731271744,
0.02935900166630745,
-0.055409226566553116,
0.1434190571308136,
0.021725639700889587,
0.057375725358724594,
0.013055107556283474,
0.007918871939182281,
0.005479048006236553,
0.07467535883188248,
0.04230835661292076,
-0.025031007826328278,
0.0314599834382534,
0.06038539484143257,
0.050633497536182404,
-0.07299533486366272,
0.05928729102015495,
-0.09551627188920975,
0.09316320717334747,
0.008294356055557728,
-0.02913067117333412,
-0.01593327522277832,
-0.08855732530355453,
0.0556623749434948,
-0.07432728260755539,
0.051474180072546005,
-0.007976362481713295,
-0.20645380020141602,
0.014402611181139946,
0.07417953014373779,
0.023092545568943024,
-0.24218261241912842,
0.0033315089531242847,
-0.11111005395650864,
0.02008432149887085,
-0.07406885176897049,
0.11180184781551361,
0.04484584927558899,
0.03935617208480835,
-0.01127120666205883,
-0.1541660875082016,
0.023189309984445572,
0.07123126834630966,
-0.07720153778791428,
-0.12649978697299957
] |
null | null | null | ## CantoneseLLM-6B-preview202402 with ExLlamaV2 Quantization
哩個係用 [/hon9kon9ize/CantoneseLLM-6B-preview202402](https://huggingface.co/hon9kon9ize/CantoneseLLM-6B-preview202402) 生成嘅exl2量化模型。<br>
This is a quantizated model from [/hon9kon9ize/CantoneseLLM-6B-preview202402](https://huggingface.co/hon9kon9ize/CantoneseLLM-6B-preview202402) in exl2 format.<br>
這是一個由 [/hon9kon9ize/CantoneseLLM-6B-preview202402](https://huggingface.co/hon9kon9ize/CantoneseLLM-6B-preview202402) 生成的exl2量化模型。
哩度係main branch, 只係放EvLlamaV2量化果陣用到嘅[measurement.json](measurement.json)檔案，請響下面揀量化程度。<br>
You are currently at the [main](https://huggingface.co/kennylam/CantoneseLLM-6B-preview202402-exl2/tree/main) branch, which provides only [measurement.json](measurement.json) used in the ExLlamaV2 quantization. Please take a look of your choices in following table of branches.<br>
這裡是main branch, 只提供EvLlamaV2量化時所用到的[measurement.json](measurement.json)檔案，請在下面選擇量化程度。。
[8.0bpw-h8](/kennylam/CantoneseLLM-6B-preview202402-exl2/tree/8.0bpw-h8) 8 bits per weight.
[6.0bpw-h6](/kennylam/CantoneseLLM-6B-preview202402-exl2/tree/6.0bpw-h6) 6 bits per weight.
[5.0bpw-h6](/kennylam/CantoneseLLM-6B-preview202402-exl2/tree/5.0bpw-h6) 4 bits per weight.
[4.0bpw-h6](/kennylam/CantoneseLLM-6B-preview202402-exl2/tree/4.0bpw-h6) 4 bits per weight.
[3.0bpw-h6](/kennylam/CantoneseLLM-6B-preview202402-exl2/tree/3.0bpw-h6) 3 bits per weight. | {"license": "other", "tags": ["Hong Kong", "\u9999\u6e2f", "Cantonese", "\u5ee3\u6771\u8a71", "\u7cb5\u8a9e"], "pipeline_tag": "text-generation", "license_name": "yi-license"} | text-generation | kennylam/CantoneseLLM-6B-preview202402-exl2 | [
"Hong Kong",
"香港",
"Cantonese",
"廣東話",
"粵語",
"text-generation",
"license:other",
"region:us"
] | 2024-02-09T03:47:17+00:00 | [] | [] | TAGS
#Hong Kong #香港 #Cantonese #廣東話 #粵語 #text-generation #license-other #region-us
| ## CantoneseLLM-6B-preview202402 with ExLlamaV2 Quantization
哩個係用 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成嘅exl2量化模型。<br>
This is a quantizated model from /hon9kon9ize/CantoneseLLM-6B-preview202402 in exl2 format.<br>
這是一個由 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成的exl2量化模型。
哩度係main branch, 只係放EvLlamaV2量化果陣用到嘅measurement.json檔案，請響下面揀量化程度。<br>
You are currently at the main branch, which provides only URL used in the ExLlamaV2 quantization. Please take a look of your choices in following table of branches.<br>
這裡是main branch, 只提供EvLlamaV2量化時所用到的measurement.json檔案，請在下面選擇量化程度。。
8.0bpw-h8 8 bits per weight.
6.0bpw-h6 6 bits per weight.
5.0bpw-h6 4 bits per weight.
4.0bpw-h6 4 bits per weight.
3.0bpw-h6 3 bits per weight. | [
"## CantoneseLLM-6B-preview202402 with ExLlamaV2 Quantization\n哩個係用 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成嘅exl2量化模型。<br>\nThis is a quantizated model from /hon9kon9ize/CantoneseLLM-6B-preview202402 in exl2 format.<br>\n這是一個由 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成的exl2量化模型。\n\n\n哩度係main branch, 只係放EvLlamaV2量化果陣用到嘅measurement.json檔案，請響下面揀量化程度。<br>\nYou are currently at the main branch, which provides only URL used in the ExLlamaV2 quantization. Please take a look of your choices in following table of branches.<br>\n這裡是main branch, 只提供EvLlamaV2量化時所用到的measurement.json檔案，請在下面選擇量化程度。。\n\n\n8.0bpw-h8 8 bits per weight.\n\n6.0bpw-h6 6 bits per weight.\n\n5.0bpw-h6 4 bits per weight.\n\n4.0bpw-h6 4 bits per weight.\n\n3.0bpw-h6 3 bits per weight."
] | [
"TAGS\n#Hong Kong #香港 #Cantonese #廣東話 #粵語 #text-generation #license-other #region-us \n",
"## CantoneseLLM-6B-preview202402 with ExLlamaV2 Quantization\n哩個係用 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成嘅exl2量化模型。<br>\nThis is a quantizated model from /hon9kon9ize/CantoneseLLM-6B-preview202402 in exl2 format.<br>\n這是一個由 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成的exl2量化模型。\n\n\n哩度係main branch, 只係放EvLlamaV2量化果陣用到嘅measurement.json檔案，請響下面揀量化程度。<br>\nYou are currently at the main branch, which provides only URL used in the ExLlamaV2 quantization. Please take a look of your choices in following table of branches.<br>\n這裡是main branch, 只提供EvLlamaV2量化時所用到的measurement.json檔案，請在下面選擇量化程度。。\n\n\n8.0bpw-h8 8 bits per weight.\n\n6.0bpw-h6 6 bits per weight.\n\n5.0bpw-h6 4 bits per weight.\n\n4.0bpw-h6 4 bits per weight.\n\n3.0bpw-h6 3 bits per weight."
] | [
32,
318
] | [
"passage: TAGS\n#Hong Kong #香港 #Cantonese #廣東話 #粵語 #text-generation #license-other #region-us \n## CantoneseLLM-6B-preview202402 with ExLlamaV2 Quantization\n哩個係用 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成嘅exl2量化模型。<br>\nThis is a quantizated model from /hon9kon9ize/CantoneseLLM-6B-preview202402 in exl2 format.<br>\n這是一個由 /hon9kon9ize/CantoneseLLM-6B-preview202402 生成的exl2量化模型。\n\n\n哩度係main branch, 只係放EvLlamaV2量化果陣用到嘅measurement.json檔案，請響下面揀量化程度。<br>\nYou are currently at the main branch, which provides only URL used in the ExLlamaV2 quantization. Please take a look of your choices in following table of branches.<br>\n這裡是main branch, 只提供EvLlamaV2量化時所用到的measurement.json檔案，請在下面選擇量化程度。。\n\n\n8.0bpw-h8 8 bits per weight.\n\n6.0bpw-h6 6 bits per weight.\n\n5.0bpw-h6 4 bits per weight.\n\n4.0bpw-h6 4 bits per weight.\n\n3.0bpw-h6 3 bits per weight."
] | [
0.020688535645604134,
0.17626291513442993,
-0.006908957380801439,
0.08736374974250793,
0.047785285860300064,
0.030994461849331856,
0.0835605040192604,
0.14666637778282166,
0.07534787058830261,
0.08562619984149933,
0.02421456202864647,
0.0022339853458106518,
0.04676199331879616,
-0.0032462109811604023,
0.010496758855879307,
-0.19153866171836853,
0.018124844878911972,
0.04388580098748207,
0.07939872145652771,
0.039496298879384995,
0.04870743304491043,
-0.08547522127628326,
0.09675709903240204,
-0.04098634421825409,
-0.040144968777894974,
0.05557373911142349,
-0.045185621827840805,
0.03751259669661522,
0.01823912188410759,
0.029953105375170708,
0.03816058114171028,
0.007171250879764557,
0.03427306190133095,
-0.18577134609222412,
-0.005862068384885788,
0.005335588939487934,
-0.054727014154195786,
0.03713598474860191,
-0.0721905305981636,
-0.03591742366552353,
0.059104908257722855,
-0.052229154855012894,
0.028519757091999054,
0.03773852437734604,
-0.03481348603963852,
-0.07541268318891525,
0.003550813300535083,
0.06264718621969223,
0.10843569785356522,
0.0909324437379837,
0.006437793839722872,
0.06413739174604416,
-0.0875764861702919,
0.043670520186424255,
0.17941944301128387,
-0.0976220890879631,
-0.01759091578423977,
0.1381153017282486,
-0.04348103329539299,
0.12445536255836487,
-0.12972378730773926,
-0.025741687044501305,
0.11064990609884262,
0.02322409301996231,
-0.012196694500744343,
-0.06684170663356781,
0.022964071482419968,
0.021649962291121483,
-0.06991767138242722,
-0.0005487008020281792,
0.1708276867866516,
0.035728421062231064,
-0.02408072166144848,
-0.018676267936825752,
-0.0641326904296875,
-0.1465684324502945,
-0.017909223213791847,
0.022112876176834106,
0.0731421560049057,
-0.024842876940965652,
0.056592635810375214,
0.027068017050623894,
-0.03963065892457962,
-0.033100299537181854,
-0.008260475471615791,
0.17227381467819214,
0.00012593467545229942,
0.03799989074468613,
0.012074373662471771,
0.05276006460189819,
-0.07983841747045517,
-0.1015627384185791,
-0.07482112944126129,
-0.0147544639185071,
0.012351952493190765,
0.048926640301942825,
0.05473959073424339,
0.058837879449129105,
0.06164107844233513,
0.10404013842344284,
-0.11004356294870377,
0.11661262065172195,
-0.007224732078611851,
0.012076148763298988,
0.048351556062698364,
0.037994153797626495,
-0.02789515070617199,
-0.035665418952703476,
-0.017228104174137115,
0.03047252632677555,
0.06569991260766983,
-0.032474786043167114,
-0.12239716947078705,
0.033249858766794205,
-0.06369055807590485,
0.0198668260127306,
-0.027204928919672966,
-0.016581902280449867,
-0.06740888208150864,
-0.08120565116405487,
0.1964406818151474,
-0.0809013843536377,
0.04437713325023651,
0.01786377653479576,
-0.026706917211413383,
0.11544036865234375,
0.04565322399139404,
-0.015240256674587727,
-0.046638790518045425,
0.10366252064704895,
-0.09699821472167969,
0.03403964638710022,
-0.041629672050476074,
-0.07643130421638489,
0.038790371268987656,
-0.03397876396775246,
0.039941754192113876,
-0.046517472714185715,
-0.03336118161678314,
-0.0494370199739933,
-0.006195054855197668,
-0.06895246356725693,
-0.004445004276931286,
-0.03651604801416397,
-0.02532084472477436,
-0.006866853684186935,
0.016212791204452515,
-0.05670011788606644,
-0.03525248542428017,
-0.0011949115432798862,
0.030702408403158188,
0.09940537810325623,
-0.12535206973552704,
0.027229972183704376,
-0.0501040555536747,
0.06886464357376099,
-0.03809734433889389,
0.06558963656425476,
-0.1274336278438568,
0.07331271469593048,
-0.06769885122776031,
-0.05599653348326683,
-0.030185380950570107,
-0.03049304708838463,
0.01173174288123846,
0.06144507974386215,
-0.12262415140867233,
-0.052148979157209396,
0.0681447684764862,
-0.11563187092542648,
-0.059837695211172104,
0.06312893331050873,
-0.003608199767768383,
-0.005340085364878178,
0.058974649757146835,
0.11498450487852097,
0.164235919713974,
-0.0760641023516655,
-0.10534714162349701,
0.05078849568963051,
0.0489693321287632,
0.01624849997460842,
0.07536755502223969,
0.035163514316082,
-0.005643862299621105,
0.053262025117874146,
-0.046740420162677765,
-0.08218242973089218,
0.010587004013359547,
-0.0438406877219677,
0.0044148690067231655,
-0.024315979331731796,
0.02984735555946827,
0.01530042476952076,
-0.013612509705126286,
0.014892708510160446,
0.0025965082459151745,
0.15842938423156738,
0.11789792031049728,
-0.05405106022953987,
0.012094476260244846,
-0.020627781748771667,
0.054054658859968185,
-0.024177629500627518,
-0.03544772043824196,
-0.0507749579846859,
0.03668138384819031,
0.06434252113103867,
-0.026813657954335213,
0.05787020921707153,
0.05085131898522377,
0.04935259744524956,
0.05609465390443802,
-0.07145427912473679,
0.021140417084097862,
0.014498414471745491,
0.003769628005102277,
-0.021520324051380157,
-0.07609321922063828,
-0.056494180113077164,
-0.047887496650218964,
-0.006941542029380798,
-0.0717395767569542,
-0.011358204297721386,
0.10694917291402817,
0.08083056658506393,
0.011040774174034595,
-0.02839595451951027,
0.01702170819044113,
0.0063260821625590324,
-0.028744341805577278,
-0.026966823264956474,
-0.02897385135293007,
-0.03161052614450455,
-0.09103559702634811,
0.025230396538972855,
-0.058083001524209976,
0.03524674102663994,
0.11023730784654617,
0.07006969302892685,
0.012194711714982986,
-0.05532281845808029,
-0.00711379200220108,
-0.029480813071131706,
-0.05549656227231026,
-0.01191814336925745,
0.15454912185668945,
-0.0074401842430233955,
0.04297951981425285,
-0.09950190782546997,
-0.007912359200417995,
0.002378758043050766,
0.02449861913919449,
-0.01505815889686346,
0.10671579837799072,
0.08393178880214691,
-0.10837426781654358,
0.02959791012108326,
-0.014444176107645035,
-0.07685916870832443,
0.16931788623332977,
0.03477075695991516,
-0.04345454275608063,
-0.08559960126876831,
0.00841220561414957,
-0.016674568876624107,
0.046463675796985626,
-0.12677732110023499,
0.043562378734350204,
0.020613912492990494,
-0.004355412442237139,
0.02062268927693367,
-0.10808597505092621,
-0.008357664570212364,
0.00433873338624835,
-0.0557616651058197,
-0.05818013474345207,
-0.07738479971885681,
-0.06466981023550034,
0.017986536026000977,
0.006431467831134796,
0.09835786372423172,
-0.04308568686246872,
-0.026920517906546593,
-0.07677251100540161,
0.1237066239118576,
-0.09612420946359634,
-0.14271943271160126,
-0.1106824278831482,
-0.08243812620639801,
-0.05311903357505798,
-0.009245557710528374,
0.02219923958182335,
-0.06404755264520645,
-0.07591911405324936,
-0.059379514306783676,
-0.03940786421298981,
-0.12472007423639297,
-0.009972920641303062,
0.03514168784022331,
0.020122529938817024,
0.00032711171661503613,
-0.12917041778564453,
-0.027182137593626976,
-0.020940329879522324,
0.0017794782761484385,
0.029077591374516487,
-0.09507463872432709,
0.03374827653169632,
0.11358022689819336,
0.0025185279082506895,
0.019956069067120552,
0.012736153788864613,
0.14394088089466095,
-0.028923138976097107,
0.028573373332619667,
0.04111089929938316,
0.05050749331712723,
0.09194272011518478,
0.14181379973888397,
0.08284055441617966,
-0.05951714888215065,
0.0009748777374625206,
0.045175809413194656,
-0.08492451161146164,
-0.16841934621334076,
-0.0571976900100708,
-0.06722567975521088,
0.04864403232932091,
0.1260593831539154,
0.084006167948246,
0.0060117063112556934,
0.055090758949518204,
-0.010879226960241795,
0.11830607056617737,
-0.03751266375184059,
0.06146707013249397,
0.04769549518823624,
0.015284517779946327,
0.02676323801279068,
-0.05379600450396538,
0.009996202774345875,
0.12148772925138474,
0.044763363897800446,
0.09118543565273285,
-0.01312523614615202,
0.1342734396457672,
0.058516792953014374,
0.0985640212893486,
0.05262937396764755,
0.0750749483704567,
-0.01776297017931938,
-0.023100296035408974,
-0.023465143516659737,
-0.09580930322408676,
-0.018297621980309486,
0.11438104510307312,
0.08180280774831772,
0.026869941502809525,
0.03172207996249199,
0.0728687047958374,
0.04370906949043274,
0.019197538495063782,
0.10265520960092545,
-0.17367909848690033,
-0.005306299775838852,
0.048725225031375885,
0.013671635650098324,
-0.00019030197290703654,
0.03874003514647484,
0.0789875015616417,
-0.005089388228952885,
0.1235790029168129,
0.035498227924108505,
0.08765889704227448,
-0.09322677552700043,
-0.03219607099890709,
0.006338258273899555,
-0.019497469067573547,
-0.011641502380371094,
0.056327901780605316,
-0.1792294979095459,
0.12083551287651062,
0.002103210426867008,
-0.022630270570516586,
-0.028455546125769615,
-0.007762771565467119,
0.013197391293942928,
0.00417683832347393,
0.09723103046417236,
0.0471540167927742,
-0.0089029585942626,
-0.03564460948109627,
-0.0746164619922638,
0.02025693468749523,
0.018709588795900345,
-0.06437547504901886,
0.06084759905934334,
0.03261227905750275,
-0.018009992316365242,
-0.02123933844268322,
-0.02268444187939167,
0.019726572558283806,
-0.08046767860651016,
0.025765419006347656,
0.0455218069255352,
-0.045410044491291046,
0.029349178075790405,
-0.05384061485528946,
0.07485263794660568,
0.13363085687160492,
-0.05773391202092171,
-0.09087161719799042,
-0.09311096370220184,
-0.006368235219269991,
0.15920884907245636,
-0.08170759677886963,
0.006644813809543848,
0.008941559121012688,
0.08265473693609238,
-0.03198119252920151,
-0.038441695272922516,
0.016465630382299423,
-0.013795544393360615,
-0.06505332887172699,
-0.008249999023973942,
0.13097625970840454,
-0.039671655744314194,
0.05208713561296463,
-0.02936883457005024,
-0.006450152024626732,
-0.006505143363028765,
-0.19899232685565948,
0.03497900068759918,
0.09103488177061081,
-0.018940435722470284,
0.1079418808221817,
0.022752029821276665,
0.015227646566927433,
-0.05583728104829788,
0.04011974856257439,
0.005426814779639244,
0.2212793529033661,
-0.05530676245689392,
0.058141693472862244,
0.09661966562271118,
-0.05159779638051987,
-0.13337674736976624,
-0.14933787286281586,
0.03349006921052933,
0.006355751771479845,
0.002059253165498376,
-0.10896050930023193,
0.09997469931840897,
0.02704751305282116,
0.00656103203073144,
0.036304887384176254,
-0.18985921144485474,
-0.11262620240449905,
-0.06972341239452362,
0.06904560327529907,
0.0041129095479846,
-0.05872883275151253,
-0.12370222806930542,
-0.07862795144319534,
-0.21506832540035248,
0.08605144917964935,
-0.0388241782784462,
0.07585807144641876,
-0.07197344303131104,
0.02619299665093422,
0.021664997562766075,
-0.0262290146201849,
0.14832134544849396,
0.07433783262968063,
0.0342785008251667,
-0.029054297134280205,
-0.1596953570842743,
0.027853768318891525,
-0.041804809123277664,
0.1383601278066635,
-0.05668406933546066,
0.04460792988538742,
-0.08652416616678238,
-0.03528626635670662,
-0.014284800738096237,
-0.04148358106613159,
-0.034012991935014725,
-0.06263715773820877,
-0.10465757548809052,
0.034460924565792084,
0.05836179852485657,
0.02139238454401493,
0.08251211792230606,
0.027412591502070427,
-0.01682417467236519,
0.36955195665359497,
0.02343917079269886,
-0.06878244876861572,
-0.029783548787236214,
-0.05041765794157982,
-0.02822449430823326,
0.04454837366938591,
-0.23392094671726227,
0.049911826848983765,
0.11780142039060593,
0.09629683941602707,
0.07932340353727341,
0.022103959694504738,
-0.05759216472506523,
0.011253067292273045,
0.09159588068723679,
-0.05798226594924927,
-0.1514981985092163,
-0.05651109293103218,
-0.09739773720502853,
-0.07140108197927475,
-0.018947964534163475,
0.09979576617479324,
-0.04429745674133301,
-0.003093851264566183,
0.023066474124789238,
0.0375223271548748,
-0.05540427938103676,
0.07938944548368454,
0.02077225036919117,
0.06218289956450462,
-0.13050930202007294,
0.09148616343736649,
0.08452335000038147,
0.03337326645851135,
-0.012286284938454628,
0.08295216411352158,
-0.0485725924372673,
-0.023678526282310486,
-0.054814279079437256,
-0.016322659328579903,
-0.04373733699321747,
0.00011560893472051248,
-0.05913255363702774,
-0.07736816257238388,
0.017651652917265892,
0.013389992527663708,
0.06181875988841057,
0.06358649581670761,
-0.022932274267077446,
-0.016975006088614464,
-0.06835944950580597,
0.0441683866083622,
-0.049132030457258224,
0.04073934629559517,
-0.12683328986167908,
0.037571508437395096,
0.05444711074233055,
0.032370325177907944,
-0.01837671361863613,
-0.024853158742189407,
-0.09908387064933777,
0.0030504148453474045,
-0.10228487849235535,
0.13524863123893738,
-0.08550754189491272,
0.014564961194992065,
-0.009701550006866455,
-0.008696477860212326,
-0.11870305240154266,
0.04778483882546425,
-0.0648576021194458,
-0.015953732654452324,
-0.008334995247423649,
0.060317713767290115,
-0.028337743133306503,
-0.01068340428173542,
0.07733042538166046,
-0.0413057841360569,
0.031160758808255196,
-0.014814913272857666,
-0.01655583456158638,
0.059167008846998215,
0.009224152192473412,
0.014633378013968468,
0.11321434378623962,
0.015314794145524502,
0.01867733709514141,
-0.04650903865695,
-0.035064756870269775,
0.011351044289767742,
-0.019547834992408752,
-0.002761844778433442,
-0.05924573913216591,
-0.09056591242551804,
-0.05797833204269409,
-0.09643439203500748,
-0.12262586504220963,
-0.045125409960746765,
0.029207056388258934,
0.10124387592077255,
0.0036789248697459698,
0.05020700767636299,
0.0005708892713300884,
0.047790348529815674,
-0.15858019888401031,
-0.025607844814658165,
0.004423526581376791,
-0.0283547043800354,
-0.11257006973028183,
-0.039235107600688934,
0.009900382719933987,
-0.015074324794113636,
0.20001858472824097,
-0.020102405920624733,
0.012925633229315281,
-0.030689874663949013,
0.009637171402573586,
-0.07898768037557602,
-0.014452080242335796,
0.2126193791627884,
-0.0036287247203290462,
-0.03582087531685829,
-0.056945737451314926,
-0.007909274660050869,
-0.0019624661654233932,
0.05133833736181259,
-0.00945235788822174,
0.05096431076526642,
0.08379027992486954,
0.03899213671684265,
0.05794476717710495,
0.017862463369965553,
-0.11584196984767914,
0.06060248985886574,
-0.050237905234098434,
0.01750480942428112,
0.012569613754749298,
-0.019783714786171913,
0.09242915362119675,
-0.13166962563991547,
0.0871017575263977,
0.04125464707612991,
-0.07487903535366058,
-0.0885685607790947,
-0.14952406287193298,
-0.10498380661010742,
-0.1992839276790619,
0.009150481782853603,
-0.1500043421983719,
0.03973552584648132,
0.04946098104119301,
0.027019253000617027,
0.009692595340311527,
0.06267573684453964,
-0.0253459420055151,
-0.036758143454790115,
0.030277930200099945,
0.006961912848055363,
-0.03434338420629501,
0.06630109995603561,
0.06079484149813652,
0.04529685154557228,
-0.05127850919961929,
0.009202012792229652,
0.00104305031709373,
0.06840196996927261,
0.01033095084130764,
-0.010563448071479797,
-0.049003202468156815,
-0.00016757665434852242,
-0.00917294342070818,
0.0196880754083395,
0.1684623807668686,
0.024092739447951317,
-0.03502259403467178,
-0.0013280697166919708,
0.1115499809384346,
-0.053504180163145065,
-0.021096086129546165,
-0.10819025337696075,
0.21396121382713318,
0.04118209704756737,
0.04792215675115585,
0.02275611087679863,
-0.047107428312301636,
0.006196633446961641,
0.10167243331670761,
0.05953243002295494,
0.008690590038895607,
0.0017911377362906933,
0.03463730961084366,
0.009893842041492462,
0.02402845397591591,
0.0010572633473202586,
-0.012097563594579697,
0.16627253592014313,
-0.012462528422474861,
-0.03636261075735092,
-0.021865155547857285,
-0.027326708659529686,
0.0002786345430649817,
-0.03281792625784874,
0.03309334069490433,
-0.06520606577396393,
-0.10739591717720032,
0.0315997377038002,
-0.08793521672487259,
-0.0463089682161808,
0.09722311794757843,
-0.1714114546775818,
-0.06106957420706749,
-0.011906669475138187,
-0.05957377701997757,
0.11827468872070312,
0.030360747128725052,
-0.023802967742085457,
-0.06093093007802963,
0.13979963958263397,
0.003458212362602353,
-0.22565454244613647,
0.009767483919858932,
0.04614561051130295,
-0.041668448597192764,
0.12965162098407745,
0.012188243679702282,
-0.011027252301573753,
0.05153903365135193,
0.02100694179534912,
-0.03564589098095894,
0.11997072398662567,
0.013098403811454773,
-0.0886320024728775,
-0.011146164499223232,
0.1303076595067978,
-0.020474573597311974,
0.07073935866355896,
0.040924329310655594,
-0.057778745889663696,
-0.01291600987315178,
0.14790329337120056,
0.03146061301231384,
-0.08791018277406693,
0.004910253453999758,
-0.07652260363101959,
0.1269514560699463,
0.183523491024971,
-0.03453555330634117,
-0.03910454735159874,
0.021205203607678413,
0.10040568560361862,
-0.05351739004254341,
0.04294291138648987,
-0.02810167334973812,
-0.0710408091545105,
0.038498129695653915,
0.05847690999507904,
0.03863516077399254,
-0.18056870996952057,
-0.02835669182240963,
0.0196442361921072,
-0.05580548197031021,
-0.0190403051674366,
0.08539482951164246,
0.07453267276287079,
0.015044508501887321,
-0.03795614093542099,
-0.2587573826313019,
0.018172593787312508,
0.050858426839113235,
-0.10480278730392456,
-0.09196887910366058
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lmind_hotpot_train8000_eval7405_v1_qa_tyzhu_lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl
This model is a fine-tuned version of [tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl](https://huggingface.co/tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl) on the tyzhu/lmind_hotpot_train8000_eval7405_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6534
- Accuracy: 0.6210
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 2.1559 | 1.0 | 500 | 0.6354 | 2.2169 |
| 1.4762 | 2.0 | 1000 | 0.6336 | 2.3629 |
| 0.9246 | 3.0 | 1500 | 0.6296 | 2.7018 |
| 0.6439 | 4.0 | 2000 | 0.6296 | 2.9545 |
| 0.513 | 5.0 | 2500 | 0.6287 | 3.0991 |
| 0.4503 | 6.0 | 3000 | 0.6273 | 3.1997 |
| 0.4296 | 7.0 | 3500 | 0.6271 | 3.2721 |
| 0.4019 | 8.0 | 4000 | 0.6269 | 3.3166 |
| 0.39 | 9.0 | 4500 | 0.6264 | 3.3584 |
| 0.3832 | 10.0 | 5000 | 0.6259 | 3.3952 |
| 0.3769 | 11.0 | 5500 | 0.6249 | 3.4601 |
| 0.3728 | 12.0 | 6000 | 0.6252 | 3.4679 |
| 0.3687 | 13.0 | 6500 | 0.6245 | 3.4742 |
| 0.3621 | 14.0 | 7000 | 0.6237 | 3.5181 |
| 0.3559 | 15.0 | 7500 | 0.6238 | 3.5468 |
| 0.357 | 16.0 | 8000 | 0.6232 | 3.5493 |
| 0.3515 | 17.0 | 8500 | 0.6229 | 3.5869 |
| 0.3527 | 18.0 | 9000 | 0.6221 | 3.6148 |
| 0.3475 | 19.0 | 9500 | 0.6216 | 3.6053 |
| 0.3418 | 20.0 | 10000 | 0.6210 | 3.6534 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/lmind_hotpot_train8000_eval7405_v1_qa"], "metrics": ["accuracy"], "base_model": "tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl", "model-index": [{"name": "lmind_hotpot_train8000_eval7405_v1_qa_tyzhu_lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_hotpot_train8000_eval7405_v1_qa", "type": "tyzhu/lmind_hotpot_train8000_eval7405_v1_qa"}, "metrics": [{"type": "accuracy", "value": 0.6210125187237576, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/lmind_hotpot_train8000_eval7405_v1_qa_tyzhu_lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/lmind_hotpot_train8000_eval7405_v1_qa",
"base_model:tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:50:30+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/lmind_hotpot_train8000_eval7405_v1_qa #base_model-tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| lmind\_hotpot\_train8000\_eval7405\_v1\_qa\_tyzhu\_lmind\_hotpot\_train8000\_eval7405\_v1\_docidx\_gpt2-xl
==========================================================================================================
This model is a fine-tuned version of tyzhu/lmind\_hotpot\_train8000\_eval7405\_v1\_docidx\_gpt2-xl on the tyzhu/lmind\_hotpot\_train8000\_eval7405\_v1\_qa dataset.
It achieves the following results on the evaluation set:
* Loss: 3.6534
* Accuracy: 0.6210
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 20.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/lmind_hotpot_train8000_eval7405_v1_qa #base_model-tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 20.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
125,
99,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/lmind_hotpot_train8000_eval7405_v1_qa #base_model-tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 20.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.09477300196886063,
0.054782435297966,
-0.003312005428597331,
0.08592977374792099,
0.13393700122833252,
0.05373074486851692,
0.14662529528141022,
0.13484135270118713,
-0.1247682198882103,
0.051954466849565506,
0.12080007046461105,
0.12580189108848572,
0.03681769594550133,
0.07790924608707428,
-0.01508363988250494,
-0.2453354001045227,
-0.011614418588578701,
0.031005093827843666,
-0.12624649703502655,
0.12532465159893036,
0.06849060207605362,
-0.12901395559310913,
0.08034585416316986,
0.011150166392326355,
-0.19047756493091583,
0.009838476777076721,
-0.027045974507927895,
-0.04767170175909996,
0.126966655254364,
0.025043310597538948,
0.0946473628282547,
0.021429317072033882,
0.10477109253406525,
-0.22559377551078796,
0.004696420393884182,
0.0719427689909935,
-0.005911193322390318,
0.05862513557076454,
0.04911670461297035,
-0.02420789934694767,
0.1741092950105667,
-0.06582366675138474,
0.07441910356283188,
0.018427127972245216,
-0.13101089000701904,
-0.22150832414627075,
-0.06840326637029648,
0.06623025238513947,
0.06161190941929817,
0.11324787139892578,
-0.020964885130524635,
0.10866478085517883,
-0.09512794017791748,
0.09449922293424606,
0.25311675667762756,
-0.24648505449295044,
-0.0912533551454544,
0.08287419378757477,
0.009858849458396435,
0.07326388359069824,
-0.11868230253458023,
-0.01657249592244625,
0.048334505409002304,
0.03181863948702812,
0.10270977020263672,
0.003140487940981984,
-0.03425724804401398,
0.04077817499637604,
-0.12678946554660797,
-0.028090644627809525,
0.12108367681503296,
0.0439922958612442,
-0.005566272884607315,
-0.04298805072903633,
-0.04367151856422424,
-0.21046195924282074,
-0.03426976129412651,
-0.037663690745830536,
0.051399171352386475,
-0.0296125840395689,
-0.09249351918697357,
0.02163986675441265,
-0.07447229325771332,
-0.09223497658967972,
0.010581773705780506,
0.10906492918729782,
0.0572398379445076,
-0.023323848843574524,
-0.030390532687306404,
0.13163362443447113,
0.008369754068553448,
-0.151988223195076,
-0.007026337087154388,
0.033775847405195236,
-0.023204347118735313,
-0.03906533867120743,
-0.051853761076927185,
-0.01949722319841385,
0.014193709008395672,
0.11956427246332169,
-0.038230717182159424,
0.07564882189035416,
0.034474100917577744,
0.008283056318759918,
-0.10204102098941803,
0.15779589116573334,
-0.04861394688487053,
-0.05103575065732002,
-0.028788691386580467,
0.08568917214870453,
-0.027679655700922012,
-0.012422027997672558,
-0.07959660142660141,
0.02612067386507988,
0.11569508165121078,
0.005530012771487236,
-0.06725388020277023,
0.0708276554942131,
-0.04365667700767517,
-0.014931343495845795,
-0.06304030865430832,
-0.0740770548582077,
0.032180581241846085,
0.021952690556645393,
-0.0856013298034668,
-0.00035578894312493503,
0.010813943110406399,
0.019175352528691292,
0.007368727587163448,
0.13369528949260712,
-0.10114198923110962,
0.013957169838249683,
-0.10811024159193039,
-0.09752391278743744,
-0.0033370456658303738,
-0.06087936833500862,
0.014378508552908897,
-0.06154034286737442,
-0.18279272317886353,
-0.05140301212668419,
0.060019295662641525,
-0.03869020193815231,
-0.03050564043223858,
-0.08654045313596725,
-0.10693134367465973,
0.03726748004555702,
0.019076816737651825,
0.1342083215713501,
-0.05886249244213104,
0.10281349718570709,
0.0277671217918396,
0.05225197225809097,
0.05916796997189522,
0.05154077336192131,
-0.07058702409267426,
0.015947019681334496,
-0.138673797249794,
0.05897894129157066,
-0.04447619616985321,
0.043920937925577164,
-0.07527496665716171,
-0.11822258681058884,
-0.031212614849209785,
0.003577574621886015,
0.07231152802705765,
0.11281877011060715,
-0.19901874661445618,
-0.09267494827508926,
0.19622839987277985,
-0.06536304950714111,
-0.12696897983551025,
0.08685120940208435,
-0.05739371478557587,
0.02417343109846115,
0.06799422949552536,
0.13846105337142944,
0.07104260474443436,
-0.08238179236650467,
-0.006451851222664118,
-0.06035064160823822,
0.09489171206951141,
0.04912523925304413,
0.04968487471342087,
0.007291859947144985,
0.04281329736113548,
0.015509639866650105,
-0.0474449060857296,
0.016132796183228493,
-0.12293229252099991,
-0.09344431757926941,
-0.041567638516426086,
-0.08272087574005127,
0.006221978459507227,
0.05887964740395546,
0.0673108771443367,
-0.09186971187591553,
-0.10667365044355392,
0.0905366763472557,
0.09876811504364014,
-0.08494960516691208,
0.007447684649378061,
-0.05734965577721596,
0.049150705337524414,
0.0010233389912173152,
-0.0033271389547735453,
-0.13564452528953552,
-0.05029840022325516,
0.008839115500450134,
0.020027678459882736,
0.005382698494940996,
0.05503275990486145,
0.09125837683677673,
0.08702238649129868,
-0.05925988033413887,
-0.04969958961009979,
-0.1062302216887474,
-0.004075414035469294,
-0.09853237867355347,
-0.24558408558368683,
-0.023657921701669693,
0.0016767621273174882,
0.17728547751903534,
-0.24509389698505402,
0.05126114562153816,
-0.0013786399504169822,
0.08014804869890213,
0.018182309344410896,
-0.05171329900622368,
-0.05212588235735893,
0.06917368620634079,
-0.04065446928143501,
-0.06725648045539856,
0.047056395560503006,
-0.009595290757715702,
-0.0801304429769516,
-0.06290258467197418,
-0.1330559253692627,
0.18556207418441772,
0.12660515308380127,
-0.06532850116491318,
-0.10919973999261856,
-0.001994835212826729,
-0.06833763420581818,
-0.04232216253876686,
-0.031729768961668015,
0.007169235963374376,
0.18611641228199005,
-0.012192019261419773,
0.12216772139072418,
-0.07196556776762009,
-0.0627322793006897,
0.019656863063573837,
-0.003658306784927845,
0.0383186936378479,
0.1368434727191925,
0.11527399718761444,
-0.008047986775636673,
0.14050671458244324,
0.06713715195655823,
-0.06023101136088371,
0.16548870503902435,
-0.031738027930259705,
-0.06776261329650879,
-0.04352249577641487,
0.001139333238825202,
0.0034759468398988247,
0.0872853547334671,
-0.16408628225326538,
-0.007975314743816853,
-0.005903642158955336,
0.03150951489806175,
0.02503848448395729,
-0.21738767623901367,
-0.052979037165641785,
0.06414483487606049,
-0.058251820504665375,
-0.016145532950758934,
-0.010900972411036491,
-0.007682077586650848,
0.10032510757446289,
-0.00485010864213109,
-0.040311142802238464,
-0.011799472384154797,
0.003150907112285495,
-0.08521444350481033,
0.21162061393260956,
-0.09085693210363388,
-0.07558336853981018,
-0.07544983178377151,
-0.02506117708981037,
-0.03527642413973808,
0.012927022762596607,
0.05878513306379318,
-0.13867387175559998,
-0.0039854408241808414,
-0.05619153007864952,
0.05476117879152298,
-0.03371472284197807,
0.025437872856855392,
0.025715135037899017,
0.0013743818271905184,
0.03359038755297661,
-0.12370320409536362,
-0.007678784430027008,
-0.04925653338432312,
-0.10505419224500656,
0.05869447812438011,
0.036860741674900055,
0.10436434298753738,
0.14282813668251038,
0.012127640657126904,
0.025133565068244934,
-0.01089828833937645,
0.23787003755569458,
-0.0773961991071701,
-0.019488221034407616,
0.09664254635572433,
0.03340057283639908,
0.03911934420466423,
0.08826423436403275,
0.07338543981313705,
-0.10529126971960068,
0.009058278985321522,
0.0691901296377182,
-0.027267228811979294,
-0.21446174383163452,
-0.001968730939552188,
-0.04355312138795853,
-0.04485132917761803,
0.08205918967723846,
0.02142786607146263,
0.0418412983417511,
0.07280635833740234,
0.007622251752763987,
0.08206862211227417,
-0.025109373033046722,
0.06986644864082336,
0.05353279411792755,
0.052730023860931396,
0.11500158905982971,
-0.01127931009978056,
-0.05796239897608757,
0.024211985990405083,
-0.04366209730505943,
0.24632805585861206,
0.0007815593271516263,
0.08021754771471024,
0.07917425781488419,
0.1435653269290924,
-0.011687585152685642,
0.04630327224731445,
-0.009416098706424236,
-0.05710335075855255,
-0.005356332752853632,
-0.0598127506673336,
-0.03404572978615761,
0.038604144006967545,
-0.0372559018433094,
0.07476475089788437,
-0.11067673563957214,
0.025090401992201805,
0.06465596705675125,
0.2476939857006073,
0.015253288671374321,
-0.3123498558998108,
-0.07751721143722534,
-0.006737475283443928,
-0.0025179993826895952,
-0.013994935899972916,
0.008927179500460625,
0.07644791901111603,
-0.1098153367638588,
0.028615765273571014,
-0.04697909951210022,
0.07993902266025543,
-0.044579993933439255,
0.03428510203957558,
0.05901271477341652,
0.08412900567054749,
-0.011701519601047039,
0.06598752737045288,
-0.3029457926750183,
0.25876134634017944,
-0.004462930373847485,
0.09853925555944443,
-0.05546475574374199,
0.016118058934807777,
0.031146088615059853,
0.029524482786655426,
0.04017777740955353,
-0.00657489150762558,
-0.01571437157690525,
-0.20105689764022827,
-0.041228629648685455,
0.03985079377889633,
0.11993066966533661,
-0.08636458963155746,
0.12531718611717224,
-0.014190015383064747,
0.006774271372705698,
0.07203545421361923,
0.0057028657756745815,
-0.10653935372829437,
-0.09507430344820023,
0.007334562484174967,
-0.03055143915116787,
0.021234611049294472,
-0.07721249014139175,
-0.10815127938985825,
-0.12332816421985626,
0.15315240621566772,
-0.033619143068790436,
-0.032525528222322464,
-0.1119375228881836,
0.09482019394636154,
0.0912507101893425,
-0.07360019534826279,
0.03469507396221161,
0.03654590621590614,
0.06614933907985687,
0.035659193992614746,
-0.03138578683137894,
0.09068126231431961,
-0.0806477889418602,
-0.2036808729171753,
-0.06941098719835281,
0.10721465200185776,
0.07302330434322357,
0.07146606594324112,
-0.02037731371819973,
0.027045439928770065,
-0.028459124267101288,
-0.10401569306850433,
0.05571998655796051,
0.034842535853385925,
0.06440497189760208,
0.00802779570221901,
-0.0764111578464508,
0.07011689245700836,
-0.04813222587108612,
-0.045374996960163116,
0.1220332682132721,
0.2746008038520813,
-0.0739205926656723,
0.018367186188697815,
-0.001528409542515874,
-0.08711300045251846,
-0.12033388018608093,
0.07345700263977051,
0.09669000655412674,
0.006731102243065834,
0.006175511982291937,
-0.24876195192337036,
0.10621155798435211,
0.11807946115732193,
0.0104701928794384,
0.11654771119356155,
-0.37933745980262756,
-0.12809009850025177,
0.07078151404857635,
0.13932430744171143,
0.0688290074467659,
-0.16680747270584106,
-0.03108006902039051,
-0.0072190952487289906,
-0.16115957498550415,
0.07952991873025894,
-0.08714219927787781,
0.11899390071630478,
-0.044688284397125244,
0.05259305238723755,
0.019977377727627754,
-0.05559765547513962,
0.12816759943962097,
0.026597879827022552,
0.10643983632326126,
-0.04908735677599907,
-0.004148375242948532,
0.04814145714044571,
-0.04196051508188248,
-0.01076933741569519,
-0.10228634625673294,
0.03528203070163727,
-0.09803316742181778,
-0.024892013520002365,
-0.08290307223796844,
0.020709967240691185,
-0.06624571979045868,
-0.0753287672996521,
-0.034931641072034836,
0.02460397221148014,
0.07841328531503677,
-0.02505963295698166,
0.07097434252500534,
-0.0033789488952606916,
0.1871306151151657,
0.019352151080965996,
0.035150352865457535,
-0.02076762169599533,
-0.07591864466667175,
-0.012317167595028877,
0.02091939188539982,
0.05504986643791199,
-0.13699239492416382,
0.00661440147086978,
0.149992898106575,
0.04009845480322838,
0.1585942953824997,
0.09757440537214279,
-0.045148104429244995,
0.008665520697832108,
0.06685306876897812,
-0.13279969990253448,
-0.08202148973941803,
-0.016250422224402428,
-0.07104673981666565,
-0.09197276085615158,
0.02206260710954666,
0.08734381943941116,
-0.0776841789484024,
-0.0005459922831505537,
-0.010039038956165314,
0.012817231938242912,
-0.034525565803050995,
0.2206401228904724,
0.024958031252026558,
0.06230134516954422,
-0.0935790166258812,
0.05325246602296829,
0.012273951433598995,
-0.058135613799095154,
0.03551672771573067,
0.06219565123319626,
-0.07384588569402695,
-0.009918777272105217,
0.10498659312725067,
0.2052329182624817,
-0.0505906380712986,
-0.011410021223127842,
-0.15110445022583008,
-0.1137990951538086,
0.08329452574253082,
0.1312113106250763,
0.07060277462005615,
0.017539799213409424,
-0.043105870485305786,
0.05494283139705658,
-0.10502345860004425,
0.08898625522851944,
0.05672236531972885,
0.07112204283475876,
-0.12279094010591507,
0.18351124227046967,
0.022482285276055336,
-0.018191354349255562,
0.0038055204786360264,
0.02274484373629093,
-0.13313324749469757,
0.009868881665170193,
-0.09383661299943924,
-0.04952944070100784,
-0.01232109684497118,
-0.00858093798160553,
-0.00856793113052845,
-0.0427611880004406,
-0.05573496222496033,
0.01831294223666191,
-0.10931163281202316,
-0.044891610741615295,
0.006803188938647509,
0.06442505866289139,
-0.12148191779851913,
-0.0036973978858441114,
0.032984454184770584,
-0.10145331174135208,
0.06708760559558868,
0.08166094869375229,
0.026765119284391403,
0.04694628715515137,
-0.15142808854579926,
0.03731677681207657,
0.035974763333797455,
-0.00009002159640658647,
0.04082505777478218,
-0.12860053777694702,
0.005662921350449324,
-0.04517858102917671,
0.03676844760775566,
0.022562207654118538,
0.03785761445760727,
-0.12680171430110931,
0.007901703007519245,
-0.036661166697740555,
-0.07296746969223022,
-0.055812686681747437,
0.04054391011595726,
0.08203534781932831,
0.004296817351132631,
0.16239047050476074,
-0.07510360330343246,
0.054728325456380844,
-0.24132651090621948,
-0.021607404574751854,
0.017106259241700172,
-0.0718391165137291,
-0.08227258920669556,
-0.05639030784368515,
0.0744706317782402,
-0.06730140745639801,
0.10789111256599426,
-0.024077724665403366,
0.00046577912871725857,
0.015042020007967949,
-0.06138654425740242,
0.00038245489122346044,
0.008845376782119274,
0.22036820650100708,
0.06144360452890396,
-0.028154423460364342,
0.05829872563481331,
0.051135241985321045,
0.09322599321603775,
0.08482010662555695,
0.1999259740114212,
0.126499742269516,
-0.02596382610499859,
0.08437057584524155,
0.046388037502765656,
-0.10759627819061279,
-0.14381161332130432,
0.08997810631990433,
-0.06803660839796066,
0.10769229382276535,
-0.032155994325876236,
0.2055012732744217,
0.1270451843738556,
-0.17752575874328613,
0.044266633689403534,
-0.0410727933049202,
-0.08378186821937561,
-0.10491866618394852,
-0.010646914131939411,
-0.08655868470668793,
-0.17595310509204865,
0.043097782880067825,
-0.1336832493543625,
0.04520101472735405,
0.07806985825300217,
0.04031355679035187,
0.02781524322926998,
0.16936548054218292,
0.06292497366666794,
0.011377396062016487,
0.037833765149116516,
0.01299294177442789,
-0.04499465599656105,
-0.1188875138759613,
-0.07226763665676117,
0.0025324318557977676,
-0.03991955891251564,
0.03734441474080086,
-0.048922665417194366,
-0.07188937067985535,
0.031854402273893356,
0.0031544151715934277,
-0.07744577527046204,
0.030482284724712372,
-0.01696343533694744,
0.06445829570293427,
0.03016740083694458,
0.004296890925616026,
0.0008601582376286387,
-0.022009357810020447,
0.23114515841007233,
-0.07139655947685242,
-0.08341707289218903,
-0.0983266606926918,
0.2126035839319229,
0.06619514524936676,
0.00018133582489099354,
0.04455636069178581,
-0.07182858884334564,
0.016965413466095924,
0.21115566790103912,
0.19215890765190125,
-0.06326818466186523,
-0.00536477891728282,
0.021562060341238976,
-0.01576334983110428,
-0.022991584613919258,
0.07510536164045334,
0.12250771373510361,
0.03672763705253601,
-0.0693189725279808,
-0.015383834950625896,
-0.054238129407167435,
-0.03303999453783035,
0.0005185225745663047,
0.08721503615379333,
0.05202881246805191,
-0.0019954873714596033,
-0.019259734079241753,
0.06125640124082565,
-0.05117595195770264,
-0.12335989624261856,
0.07139148563146591,
-0.19794906675815582,
-0.15845347940921783,
-0.021614916622638702,
0.0674840584397316,
0.0028665896970778704,
0.08122793585062027,
-0.009676369838416576,
-0.044689618051052094,
0.07364866137504578,
-0.007028070744127035,
-0.07300341129302979,
-0.12172903120517731,
0.08453316986560822,
-0.0662064179778099,
0.19502106308937073,
-0.05636981502175331,
0.04072515293955803,
0.13033974170684814,
0.0575828030705452,
-0.0569903701543808,
0.0545077882707119,
0.06333129107952118,
-0.11512493342161179,
-0.00998235959559679,
0.10159129649400711,
-0.04397887736558914,
0.07820240408182144,
0.05782148241996765,
-0.12153247743844986,
0.0333997942507267,
-0.01937037892639637,
-0.05099143087863922,
-0.05460586026310921,
-0.021011516451835632,
-0.045194875448942184,
0.13271863758563995,
0.24988320469856262,
-0.030728641897439957,
0.007182360161095858,
-0.06888817250728607,
0.04227109253406525,
0.04945176839828491,
0.082213394343853,
-0.0537806861102581,
-0.27372556924819946,
0.028325799852609634,
0.06983471661806107,
-0.005894496105611324,
-0.22209028899669647,
-0.11804774403572083,
0.05102972686290741,
-0.06752899289131165,
-0.07655531913042068,
0.08701152354478836,
0.10288073122501373,
0.0715576559305191,
-0.057674340903759,
-0.08247409760951996,
-0.0658208504319191,
0.1847076267004013,
-0.14739584922790527,
-0.09587068110704422
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# image_classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6440
- Accuracy: 0.4437
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 40 | 1.9509 | 0.3312 |
| No log | 2.0 | 80 | 1.7328 | 0.375 |
| No log | 3.0 | 120 | 1.6260 | 0.4562 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "image_classification", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.44375, "name": "Accuracy"}]}]}]} | image-classification | ppriatiningtyaz/image_classification | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-09T03:51:41+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| image\_classification
=====================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6440
* Accuracy: 0.4437
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
86,
98,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.11703837662935257,
0.13337396085262299,
-0.0026314614806324244,
0.12070085108280182,
0.14108110964298248,
0.004635666497051716,
0.13976868987083435,
0.13915185630321503,
-0.07275068759918213,
0.07987997680902481,
0.14880694448947906,
0.13123802840709686,
0.030614977702498436,
0.186843603849411,
-0.049425795674324036,
-0.22279761731624603,
0.02685735560953617,
0.04665452614426613,
-0.048514917492866516,
0.12098179757595062,
0.08884505927562714,
-0.13715827465057373,
0.11813674122095108,
0.025373730808496475,
-0.20166562497615814,
-0.007906285114586353,
0.028533801436424255,
-0.05778995901346207,
0.11590585857629776,
0.03695005550980568,
0.09109177440404892,
0.029183940961956978,
0.05279802158474922,
-0.15043242275714874,
0.010382969863712788,
0.07545940577983856,
-0.008873723447322845,
0.09604368358850479,
0.05648350343108177,
0.011809377931058407,
0.011960681527853012,
-0.09294059872627258,
0.04073645547032356,
0.02618785761296749,
-0.1126071959733963,
-0.23252299427986145,
-0.08630016446113586,
0.05883171036839485,
0.07816880941390991,
0.07029051333665848,
-0.002089416841045022,
0.14405477046966553,
-0.00737989554181695,
0.09751922637224197,
0.2301016002893448,
-0.27348390221595764,
-0.07743311673402786,
0.03915984183549881,
0.018593033775687218,
0.07816129922866821,
-0.10029579699039459,
0.013005148619413376,
0.05876810848712921,
0.015363712795078754,
0.15396012365818024,
-0.005486635956913233,
-0.012113339267671108,
-0.02576831355690956,
-0.12579193711280823,
-0.06398480385541916,
0.19302216172218323,
0.08900821954011917,
-0.04782756417989731,
-0.08186109364032745,
-0.07897835224866867,
-0.13923798501491547,
-0.045598313212394714,
-0.01130685769021511,
0.05696497857570648,
-0.03428177163004875,
-0.06387034803628922,
-0.03622199594974518,
-0.09861935675144196,
-0.0694071352481842,
-0.01417485624551773,
0.09747761487960815,
0.05392841622233391,
0.013733952306210995,
-0.01965475268661976,
0.08202629536390305,
-0.03903357684612274,
-0.14419008791446686,
-0.008073186501860619,
0.016317779198288918,
0.025416046380996704,
-0.031292639672756195,
-0.02456621825695038,
-0.11346811056137085,
0.021297236904501915,
0.10916416347026825,
-0.06965523958206177,
0.05674217268824577,
-0.020271146669983864,
0.05181616172194481,
-0.11094168573617935,
0.19113050401210785,
-0.04913107678294182,
0.016911955550312996,
0.040070004761219025,
0.10395632684230804,
0.05103425309062004,
-0.0021235921885818243,
-0.10635765641927719,
0.018188273534178734,
0.12026511132717133,
0.007220359053462744,
-0.034489840269088745,
0.08142359554767609,
-0.06266428530216217,
-0.0302606038749218,
0.07919827848672867,
-0.08607569336891174,
0.026211019605398178,
-0.00618899567052722,
-0.05342717096209526,
-0.05631585419178009,
0.046617813408374786,
-0.011000683531165123,
-0.013043655082583427,
0.041490864008665085,
-0.10070876032114029,
0.012835947796702385,
-0.06701703369617462,
-0.10771821439266205,
0.013119104318320751,
-0.11608368158340454,
0.014757844619452953,
-0.12414803355932236,
-0.1380673348903656,
-0.012368048541247845,
0.06022344157099724,
-0.03041667491197586,
-0.05152950808405876,
-0.041196927428245544,
-0.08038634061813354,
0.026152383536100388,
0.004225734621286392,
0.04650184512138367,
-0.05763401836156845,
0.08761324733495712,
0.04544827342033386,
0.07616794109344482,
-0.020994113758206367,
0.045899562537670135,
-0.08738765865564346,
0.05809153988957405,
-0.2045249044895172,
0.03679561987519264,
-0.05837831273674965,
0.08663726598024368,
-0.11987154185771942,
-0.08720742911100388,
0.0016014266293495893,
-0.02086605131626129,
0.06450971961021423,
0.10771549493074417,
-0.13847248256206512,
-0.05708669498562813,
0.1700592339038849,
-0.10256218165159225,
-0.15680526196956635,
0.1140514686703682,
-0.029748473316431046,
0.02859514206647873,
0.05555932968854904,
0.19654671847820282,
0.07996563613414764,
-0.11017503589391708,
-0.0066634067334234715,
-0.03167468309402466,
0.03426699712872505,
-0.053370796144008636,
0.07663652300834656,
-0.0009144639479927719,
-0.011858968064188957,
0.022494114935398102,
-0.09691387414932251,
0.06316110491752625,
-0.07301964610815048,
-0.08512462675571442,
-0.06534026563167572,
-0.08831242471933365,
0.042954590171575546,
0.058359675109386444,
0.0645759254693985,
-0.10121571272611618,
-0.09006785601377487,
0.027817653492093086,
0.08084576576948166,
-0.09410694986581802,
0.018196698278188705,
-0.08191899210214615,
0.1126723513007164,
-0.1093708872795105,
0.0004419925680849701,
-0.13329780101776123,
-0.03131695091724396,
0.04985025152564049,
-0.06135560944676399,
-0.009030998684465885,
-0.03844417631626129,
0.07354863733053207,
0.06243178993463516,
-0.06397026032209396,
-0.07401686161756516,
-0.039857376366853714,
-0.002541468245908618,
-0.09822724014520645,
-0.1930789202451706,
-0.02491181716322899,
-0.027390971779823303,
0.1042720228433609,
-0.2170361429452896,
0.04140092059969902,
0.051480215042829514,
0.10060609132051468,
0.059354208409786224,
-0.031083568930625916,
0.003881290787830949,
0.018517998978495598,
-0.040115389972925186,
-0.08943285048007965,
0.06251829862594604,
0.01465153694152832,
-0.0682663545012474,
0.007539455778896809,
-0.1002621054649353,
0.17529559135437012,
0.12993976473808289,
-0.034416016191244125,
-0.06298492103815079,
-0.00528334453701973,
-0.04372486099600792,
-0.035125672817230225,
-0.035741571336984634,
0.00796236377209425,
0.0818292573094368,
-0.009152678772807121,
0.16176961362361908,
-0.10541821271181107,
-0.02614610828459263,
0.05752480775117874,
-0.030310874804854393,
-0.03932845965027809,
0.0879305824637413,
0.0689462199807167,
-0.13795559108257294,
0.14652696251869202,
0.16725656390190125,
-0.06790488958358765,
0.12538579106330872,
-0.04648170992732048,
-0.061255231499671936,
-0.02388312853872776,
0.0413455031812191,
0.033161431550979614,
0.12936992943286896,
-0.11827138066291809,
-0.012466629967093468,
0.02318766713142395,
0.0034411177039146423,
-0.007749029900878668,
-0.20055235922336578,
-0.008930030278861523,
0.03852272033691406,
-0.06102276220917702,
0.027995122596621513,
-0.0059851473197340965,
-0.021226882934570312,
0.08483211696147919,
0.008784144185483456,
-0.04312850162386894,
0.047620926052331924,
0.011016378179192543,
-0.070640929043293,
0.1946350783109665,
-0.08425688743591309,
-0.21688829362392426,
-0.13184000551700592,
-0.02259995974600315,
-0.08116496354341507,
0.021704653277993202,
0.05834820121526718,
-0.0939188152551651,
-0.05737043544650078,
-0.1059584692120552,
-0.014644067734479904,
0.029605969786643982,
0.039716124534606934,
0.04239022359251976,
-0.0021739343646913767,
0.13141466677188873,
-0.09900851547718048,
-0.007951428182423115,
-0.009906016290187836,
-0.024484282359480858,
0.0484999381005764,
0.019389836117625237,
0.12063866853713989,
0.08635938912630081,
-0.026420699432492256,
0.034378863871097565,
-0.02176588401198387,
0.24209915101528168,
-0.07170218974351883,
-0.002313279313966632,
0.15088510513305664,
0.01899421401321888,
0.0680055096745491,
0.1311551034450531,
0.0380869098007679,
-0.1028253585100174,
0.00868341512978077,
0.02154296450316906,
-0.026541180908679962,
-0.18667645752429962,
-0.017275797203183174,
-0.039236802607774734,
-0.002954996656626463,
0.15129339694976807,
0.055661555379629135,
0.05976345017552376,
0.09332019090652466,
0.0007176376529969275,
0.08904192596673965,
-0.003959463443607092,
0.08775415271520615,
0.10959029197692871,
0.04645396023988724,
0.1098446249961853,
-0.04363267868757248,
-0.028399335220456123,
0.03291943296790123,
0.01738213188946247,
0.2241400182247162,
-0.00003631914296420291,
0.17261895537376404,
0.04836900904774666,
0.1900348961353302,
0.01713091880083084,
0.05570961907505989,
-0.021902672946453094,
-0.0266709141433239,
-0.009243522770702839,
-0.054415035992860794,
-0.020340489223599434,
0.035104844719171524,
-0.04811236634850502,
0.06586732715368271,
-0.09328407049179077,
0.04222632199525833,
0.0642194002866745,
0.26483941078186035,
0.03752564638853073,
-0.3791341185569763,
-0.0939597487449646,
-0.0049210237339138985,
-0.013265467248857021,
-0.062238745391368866,
0.002539258450269699,
0.14532248675823212,
-0.06168266385793686,
0.06027646362781525,
-0.1037464290857315,
0.08121387660503387,
-0.050712015479803085,
0.021209081634879112,
0.07831300795078278,
0.08860913664102554,
0.008514128625392914,
0.05597322806715965,
-0.2486269623041153,
0.2566283643245697,
0.01536697056144476,
0.06393660604953766,
-0.046393249183893204,
0.013083992525935173,
0.035263027995824814,
0.10594192892313004,
0.10975627601146698,
-0.005398198962211609,
-0.013294120319187641,
-0.1774248480796814,
-0.08987019956111908,
0.006320901680737734,
0.07202734053134918,
-0.04535548761487007,
0.08152179419994354,
-0.03076917491853237,
-0.023336147889494896,
0.05034853145480156,
-0.0023333407007157803,
-0.09037072211503983,
-0.0938434824347496,
-0.007769833784550428,
0.042169827967882156,
0.014453562907874584,
-0.09538816660642624,
-0.09747780859470367,
-0.1048489362001419,
0.1335330307483673,
-0.01618613675236702,
-0.04101753234863281,
-0.1197008490562439,
0.08539466559886932,
0.05789906159043312,
-0.09232202917337418,
0.07979302108287811,
-0.028646942228078842,
0.13591405749320984,
0.029946301132440567,
-0.06286513060331345,
0.108878493309021,
-0.060614846646785736,
-0.17376556992530823,
-0.04674529656767845,
0.10528187453746796,
-0.018827708438038826,
0.024799806997179985,
0.0014270436950027943,
0.027369540184736252,
-0.009907948784530163,
-0.0595303513109684,
0.058219511061906815,
0.013695329427719116,
0.05881156399846077,
-0.012535660527646542,
-0.02047077752649784,
0.0071998704224824905,
-0.06425852328538895,
-0.02980400249361992,
0.13548409938812256,
0.24640130996704102,
-0.09706414490938187,
0.00592033751308918,
0.01898462325334549,
-0.05172053724527359,
-0.19607172906398773,
0.04743197187781334,
0.06572196632623672,
0.0012101199245080352,
0.03240214288234711,
-0.15322856605052948,
0.0722271278500557,
0.08123486489057541,
-0.030632134526968002,
0.09312167763710022,
-0.26652154326438904,
-0.13317318260669708,
0.07914533466100693,
0.18482905626296997,
0.06634730100631714,
-0.14518675208091736,
-0.05395825579762459,
-0.011692943051457405,
-0.09194391965866089,
0.09448184818029404,
-0.05885150656104088,
0.10514575242996216,
-0.02882414683699608,
0.0015335388015955687,
0.00582722807303071,
-0.05773221328854561,
0.13027338683605194,
-0.03471249341964722,
0.10697836428880692,
-0.057575780898332596,
-0.009273887611925602,
0.07730783522129059,
-0.07756908237934113,
0.06389493495225906,
-0.09080985933542252,
0.06284743547439575,
-0.06249602884054184,
-0.01630096137523651,
-0.07085379213094711,
0.032720524817705154,
-0.018907397985458374,
-0.025998355820775032,
-0.05104759335517883,
0.02411961741745472,
0.05202407017350197,
-0.0008917939267121255,
0.19917307794094086,
0.049436453729867935,
0.08815135806798935,
0.13946491479873657,
0.04505709558725357,
-0.07640576362609863,
-0.09965261816978455,
-0.02794247306883335,
-0.028156407177448273,
0.08631274104118347,
-0.1821335107088089,
0.050633545964956284,
0.09562115371227264,
0.008786720223724842,
0.1437925398349762,
0.046659890562295914,
-0.033027566969394684,
0.019468659535050392,
0.0716174766421318,
-0.15473493933677673,
-0.16070124506950378,
-0.03147938475012779,
-0.01959877274930477,
-0.11593525856733322,
0.06277275830507278,
0.11234544962644577,
-0.08436606824398041,
0.003143449081107974,
-0.008115489035844803,
0.016445670276880264,
-0.002922833664342761,
0.1620379239320755,
0.08044344931840897,
0.04440523684024811,
-0.09107036888599396,
0.09909168630838394,
0.05257095769047737,
-0.10333825647830963,
0.022850388661026955,
0.026029350236058235,
-0.10419294983148575,
-0.03795844316482544,
0.06664425134658813,
0.14432570338249207,
0.00006186454265844077,
-0.05099732056260109,
-0.145272359251976,
-0.09429456293582916,
0.05694856867194176,
0.12373209744691849,
0.09292376786470413,
0.015423471108078957,
-0.01091066561639309,
-0.00009720020898384973,
-0.10389916598796844,
0.11914563179016113,
0.03167761489748955,
0.09743194282054901,
-0.21961945295333862,
0.05785536766052246,
0.018080802634358406,
0.03249455615878105,
-0.019513674080371857,
0.029373042285442352,
-0.09893912822008133,
-0.015827111899852753,
-0.062337394803762436,
0.042512133717536926,
-0.03638628125190735,
0.005922649521380663,
-0.006159887183457613,
-0.06887022405862808,
-0.0612044595181942,
0.04134524613618851,
-0.10006293654441833,
-0.04592924565076828,
0.036102935671806335,
0.07028134912252426,
-0.1017250046133995,
-0.02997429668903351,
0.025206606835126877,
-0.08065185695886612,
0.08027215301990509,
0.013028341345489025,
-0.0004450915439520031,
0.02310003526508808,
-0.10084504634141922,
0.010026423260569572,
0.08489544689655304,
0.0024503201711922884,
0.02952449768781662,
-0.10438298434019089,
0.0064419936388731,
-0.0005933578358963132,
0.001203361782245338,
-0.007561885751783848,
0.10678712278604507,
-0.13309365510940552,
-0.024426471441984177,
-0.03807325288653374,
-0.032700758427381516,
-0.05843300372362137,
0.06268969178199768,
0.08548111468553543,
-0.002174717141315341,
0.20140309631824493,
-0.08715260028839111,
0.00044914960744790733,
-0.22340458631515503,
0.004364042077213526,
-0.004667307715862989,
-0.13584661483764648,
-0.12687353789806366,
-0.02751031517982483,
0.05282249674201012,
-0.07272692024707794,
0.09648748487234116,
0.015602112747728825,
0.005482446402311325,
0.03584155812859535,
0.002860749838873744,
-0.00020455298363231122,
0.026773367077112198,
0.18494276702404022,
-0.008662721142172813,
-0.021410565823316574,
0.07181929796934128,
0.018126700073480606,
0.11767108738422394,
0.08362764120101929,
0.100187748670578,
0.16270700097084045,
-0.043137241154909134,
0.1047297790646553,
0.05020562559366226,
-0.02201724424958229,
-0.17260314524173737,
0.099579818546772,
-0.07432375103235245,
0.1438605636358261,
-0.01329872664064169,
0.16352100670337677,
0.12169411033391953,
-0.1587391346693039,
0.026834789663553238,
-0.0289441104978323,
-0.07310780137777328,
-0.07127818465232849,
-0.14489620923995972,
-0.11695800721645355,
-0.18523749709129333,
0.014706979505717754,
-0.09824713319540024,
0.006036174017935991,
0.07335814088582993,
-0.008756529539823532,
-0.02278182841837406,
0.20525194704532623,
0.05062941461801529,
-0.0015471938531845808,
0.06982497125864029,
0.0004000072949565947,
-0.06756534427404404,
-0.058266229927539825,
-0.08429080992937088,
0.03729024529457092,
-0.008315094746649265,
0.033800289034843445,
-0.029064588248729706,
-0.006984272971749306,
0.049001943320035934,
-0.0008032873156480491,
-0.1114795133471489,
0.017399339005351067,
0.015422964468598366,
0.0104808509349823,
0.004319962579756975,
0.005276380572468042,
0.006768873892724514,
-0.009149119257926941,
0.18285971879959106,
-0.054600365459918976,
-0.007288629654794931,
-0.118613101541996,
0.12515847384929657,
0.027603721246123314,
-0.015562397427856922,
0.028825828805565834,
-0.07919397950172424,
0.025804884731769562,
0.21893082559108734,
0.1471487581729889,
-0.019513681530952454,
-0.0012397143291309476,
-0.008512388914823532,
-0.020078860223293304,
-0.02962370589375496,
0.09381722658872604,
0.093077652156353,
-0.045276205986738205,
-0.055423036217689514,
-0.02287806011736393,
-0.04775697737932205,
-0.01556673739105463,
-0.037331387400627136,
0.03700118884444237,
0.018096478655934334,
0.01576288789510727,
-0.06422943621873856,
0.042788662016391754,
0.01872457005083561,
-0.06986422836780548,
0.08822456747293472,
-0.195314422249794,
-0.13894817233085632,
-0.033102765679359436,
0.10025840252637863,
-0.006814622785896063,
0.03010626882314682,
-0.021688636392354965,
0.015948232263326645,
0.06887423992156982,
-0.024077434092760086,
-0.08256082236766815,
-0.09813321381807327,
0.05134633928537369,
-0.13101309537887573,
0.24609622359275818,
-0.032189205288887024,
0.006966001819819212,
0.1118864119052887,
0.018069008365273476,
-0.11937997490167618,
0.051981233060359955,
0.02522706799209118,
-0.03701399639248848,
0.025646666064858437,
0.11088280379772186,
-0.020911220461130142,
0.10904537886381149,
0.034553103148937225,
-0.08759990334510803,
-0.01746610552072525,
-0.054005686193704605,
-0.04080064594745636,
-0.055988289415836334,
-0.024216534569859505,
-0.06890667229890823,
0.12402335554361343,
0.17284543812274933,
-0.04252352565526962,
-0.02652166597545147,
-0.06382237374782562,
0.03748849779367447,
0.09080575406551361,
0.016650447621941566,
-0.013948991894721985,
-0.22873233258724213,
0.017291316762566566,
0.022657809779047966,
-0.0036899205297231674,
-0.21419458091259003,
-0.1106068342924118,
-0.017107412219047546,
-0.052657902240753174,
-0.08919410407543182,
0.08719994127750397,
0.11713390052318573,
0.05087953433394432,
-0.06030537560582161,
-0.04394691064953804,
-0.06989791989326477,
0.1599205732345581,
-0.12348966300487518,
-0.08576145023107529
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tpot_train8000_eval7405_v1_reciteonly_qa_tyzhu_lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl
This model is a fine-tuned version of [tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl](https://huggingface.co/tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl) on the tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5168
- Accuracy: 0.7637
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.3474 | 1.0 | 500 | 0.7668 | 0.3134 |
| 0.265 | 2.0 | 1000 | 0.7670 | 0.3178 |
| 0.2013 | 3.0 | 1500 | 0.7666 | 0.3400 |
| 0.1485 | 4.0 | 2000 | 0.7664 | 0.3720 |
| 0.1107 | 5.0 | 2500 | 0.7662 | 0.4115 |
| 0.0862 | 6.0 | 3000 | 0.7660 | 0.4266 |
| 0.076 | 7.0 | 3500 | 0.7659 | 0.4406 |
| 0.0675 | 8.0 | 4000 | 0.7657 | 0.4507 |
| 0.0657 | 9.0 | 4500 | 0.7656 | 0.4580 |
| 0.0634 | 10.0 | 5000 | 0.7655 | 0.4654 |
| 0.0621 | 11.0 | 5500 | 0.7653 | 0.4671 |
| 0.0599 | 12.0 | 6000 | 0.7652 | 0.4750 |
| 0.0594 | 13.0 | 6500 | 0.7650 | 0.4783 |
| 0.0589 | 14.0 | 7000 | 0.7649 | 0.4857 |
| 0.0587 | 15.0 | 7500 | 0.7646 | 0.4915 |
| 0.0566 | 16.0 | 8000 | 0.7644 | 0.4973 |
| 0.0559 | 17.0 | 8500 | 0.7642 | 0.5036 |
| 0.0559 | 18.0 | 9000 | 0.7641 | 0.5051 |
| 0.0553 | 19.0 | 9500 | 0.7638 | 0.5052 |
| 0.0539 | 20.0 | 10000 | 0.7637 | 0.5168 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa"], "metrics": ["accuracy"], "base_model": "tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl", "model-index": [{"name": "tpot_train8000_eval7405_v1_reciteonly_qa_tyzhu_lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa", "type": "tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa"}, "metrics": [{"type": "accuracy", "value": 0.7636795552094134, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/tpot_train8000_eval7405_v1_reciteonly_qa_tyzhu_lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa",
"base_model:tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T03:51:59+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa #base_model-tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| tpot\_train8000\_eval7405\_v1\_reciteonly\_qa\_tyzhu\_lmind\_hotpot\_train8000\_eval7405\_v1\_docidx\_gpt2-xl
=============================================================================================================
This model is a fine-tuned version of tyzhu/lmind\_hotpot\_train8000\_eval7405\_v1\_docidx\_gpt2-xl on the tyzhu/lmind\_hotpot\_train8000\_eval7405\_v1\_reciteonly\_qa dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5168
* Accuracy: 0.7637
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 20.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 20.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa #base_model-tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 20.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
130,
99,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa #base_model-tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx_gpt2-xl #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 20.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.061983373016119,
0.05636639520525932,
-0.00319877197034657,
0.06579594314098358,
0.15748892724514008,
0.06269589066505432,
0.1654113531112671,
0.11545407027006149,
-0.13137349486351013,
0.05930829420685768,
0.10350944846868515,
0.125236377120018,
0.03910483047366142,
0.08626929670572281,
-0.021323470398783684,
-0.2294575572013855,
0.009004856459796429,
0.03336743637919426,
-0.11801902949810028,
0.12148141115903854,
0.051631081849336624,
-0.1347469538450241,
0.08407764136791229,
0.0009183891233988106,
-0.201316237449646,
0.013196965679526329,
-0.025733262300491333,
-0.03478138521313667,
0.12440642714500427,
0.02907724864780903,
0.11003568023443222,
0.036439698189496994,
0.11537829786539078,
-0.27196991443634033,
0.0008045981521718204,
0.0955546647310257,
-0.01180050615221262,
0.04415806010365486,
0.04768609255552292,
-0.030050257220864296,
0.17096927762031555,
-0.0720793753862381,
0.06605488061904907,
0.017878666520118713,
-0.1250731348991394,
-0.22355201840400696,
-0.066840261220932,
0.04182785004377365,
0.05445566400885582,
0.0957346111536026,
-0.012626196257770061,
0.12427666038274765,
-0.08919942378997803,
0.0871775895357132,
0.2636265456676483,
-0.2494848519563675,
-0.0816950872540474,
0.06918518990278244,
-0.016537025570869446,
0.07425441592931747,
-0.10289497673511505,
-0.011926858685910702,
0.038432441651821136,
0.02217113971710205,
0.1197100281715393,
0.0029689131770282984,
-0.05192328244447708,
0.028797835111618042,
-0.13003025949001312,
-0.008619379252195358,
0.09054109454154968,
0.037126027047634125,
0.009326075203716755,
-0.01789848506450653,
-0.06251105666160583,
-0.18151378631591797,
-0.04478202015161514,
-0.03565795719623566,
0.07353299111127853,
-0.03301159664988518,
-0.09125877916812897,
0.030226081609725952,
-0.06281564384698868,
-0.06620581448078156,
-0.0025269926991313696,
0.09765411168336868,
0.06124504283070564,
-0.020063966512680054,
-0.027254320681095123,
0.10534129291772842,
-0.005573899019509554,
-0.1396220326423645,
0.004388112109154463,
0.041104916483163834,
-0.0354745015501976,
-0.05333173647522926,
-0.05654025077819824,
-0.04132470116019249,
0.022819217294454575,
0.12809516489505768,
-0.04004410654306412,
0.07702536135911942,
0.0161372609436512,
0.0028354686219245195,
-0.10218139737844467,
0.161857470870018,
-0.05757957324385643,
-0.06363983452320099,
-0.021491147577762604,
0.06408468633890152,
-0.00868328008800745,
-0.015529018826782703,
-0.08467203378677368,
0.05435111001133919,
0.12896770238876343,
-0.0008061126573011279,
-0.05683733522891998,
0.08045277744531631,
-0.031842608004808426,
-0.012642127461731434,
-0.0780707597732544,
-0.0747242197394371,
0.044832635670900345,
0.029453733935952187,
-0.059076257050037384,
0.02987932786345482,
0.013045983389019966,
0.019027531147003174,
-0.00006467003549914807,
0.16103126108646393,
-0.10334108769893646,
0.03266320750117302,
-0.10943964123725891,
-0.11982251703739166,
0.006870423909276724,
-0.04780331999063492,
0.0003694747865665704,
-0.06089739874005318,
-0.1692178100347519,
-0.04513832554221153,
0.06705298274755478,
-0.02757801115512848,
-0.010898638516664505,
-0.08128578215837479,
-0.10852807015180588,
0.030965520069003105,
0.01641790196299553,
0.0881020575761795,
-0.06552527099847794,
0.091300368309021,
0.028965452685952187,
0.04973660409450531,
0.052102044224739075,
0.04722533002495766,
-0.07630286365747452,
0.013677839189767838,
-0.17022056877613068,
0.04119332134723663,
-0.048168931156396866,
0.05006703734397888,
-0.07820220291614532,
-0.12560245394706726,
-0.012412098236382008,
0.009155883453786373,
0.06324619054794312,
0.09376060962677002,
-0.19979695975780487,
-0.10252495855093002,
0.20505842566490173,
-0.07863272726535797,
-0.1250685751438141,
0.08534131944179535,
-0.04715203866362572,
-0.008715888485312462,
0.07124008238315582,
0.12938639521598816,
0.06610141694545746,
-0.08026943355798721,
-0.008224908262491226,
-0.08618459850549698,
0.10070272535085678,
0.03272608295083046,
0.02919589914381504,
0.007529178634285927,
0.05438326671719551,
0.01261328998953104,
-0.04292899742722511,
0.022683188319206238,
-0.12021812051534653,
-0.08875759690999985,
-0.03777587413787842,
-0.07649731636047363,
-0.012475511990487576,
0.05735442787408829,
0.06028159707784653,
-0.08128990232944489,
-0.10612126439809799,
0.14541637897491455,
0.07055716216564178,
-0.10211919993162155,
0.016242720186710358,
-0.046115562319755554,
0.03737467899918556,
-0.017458617687225342,
0.009203444235026836,
-0.13564720749855042,
-0.08413746953010559,
0.006133220158517361,
-0.0173990149050951,
0.020221451297402382,
0.05548248812556267,
0.08396382629871368,
0.08544152230024338,
-0.06606345623731613,
-0.02766750194132328,
-0.0688924640417099,
0.0030066664330661297,
-0.08859189599752426,
-0.2464200258255005,
-0.02122427150607109,
0.012189862318336964,
0.1720454841852188,
-0.24816299974918365,
0.046961333602666855,
-0.021362926810979843,
0.0821995660662651,
0.012736779637634754,
-0.04496883973479271,
-0.06477706134319305,
0.09335704892873764,
-0.04119061678647995,
-0.06391049921512604,
0.05154583603143692,
-0.024163896217942238,
-0.059213120490312576,
-0.06402777135372162,
-0.17146936058998108,
0.20207546651363373,
0.1317509263753891,
-0.07742168754339218,
-0.09848316758871078,
0.01379541214555502,
-0.059062980115413666,
-0.04168207198381424,
-0.02881411463022232,
0.02254077047109604,
0.15213608741760254,
-0.012415081262588501,
0.12306278944015503,
-0.06101735681295395,
-0.04814901575446129,
0.019216712564229965,
0.0006157094612717628,
0.031900156289339066,
0.11165786534547806,
0.1607050597667694,
-0.014633631333708763,
0.1401461809873581,
0.06215345486998558,
-0.0653388649225235,
0.1356402039527893,
-0.028051402419805527,
-0.05596509948372841,
-0.041513800621032715,
-0.014615669846534729,
0.00744886277243495,
0.07736946642398834,
-0.14064373075962067,
-0.006075349636375904,
-0.0085243359208107,
0.018293241038918495,
0.022668596357107162,
-0.2035062313079834,
-0.03046017698943615,
0.06661395728588104,
-0.05461134389042854,
-0.01329206395894289,
-0.03818020597100258,
0.012415384873747826,
0.10396917164325714,
-0.008795719593763351,
-0.04584145545959473,
-0.027185140177607536,
0.0017826908733695745,
-0.09032953530550003,
0.21405376493930817,
-0.10253126174211502,
-0.06504819542169571,
-0.0673908218741417,
-0.050671398639678955,
-0.0512973926961422,
0.008992554619908333,
0.058886487036943436,
-0.12636956572532654,
-0.029571399092674255,
-0.06640545278787613,
0.059300340712070465,
-0.01070884708315134,
0.031076598912477493,
0.02828143537044525,
-0.007277527824044228,
0.03891092538833618,
-0.11900675296783447,
-0.012865276075899601,
-0.05578197166323662,
-0.10953011363744736,
0.0639168918132782,
0.057410258799791336,
0.11444186419248581,
0.15021350979804993,
0.0006433788221329451,
0.01708894781768322,
-0.007893471047282219,
0.22521725296974182,
-0.059191152453422546,
-0.004123670049011707,
0.07878178358078003,
0.03331625834107399,
0.045826785266399384,
0.1122765764594078,
0.07788655906915665,
-0.11169930547475815,
0.004721751436591148,
0.07410374283790588,
-0.027709949761629105,
-0.19621244072914124,
-0.027485651895403862,
-0.03879648819565773,
-0.06174250319600105,
0.08125641942024231,
0.011657251045107841,
0.025226008147001266,
0.05094970017671585,
0.0047507393173873425,
0.09583873301744461,
-0.01321727316826582,
0.07285521179437637,
0.0880378857254982,
0.07256146520376205,
0.12277209013700485,
-0.015600261278450489,
-0.06482904404401779,
0.01618913747370243,
-0.0659332126379013,
0.2461610734462738,
0.007631612475961447,
0.07444336265325546,
0.07471518218517303,
0.1081397533416748,
-0.01751747354865074,
0.04835573211312294,
-0.0066546425223350525,
-0.049712054431438446,
0.000884869194123894,
-0.06251417845487595,
-0.025533974170684814,
0.03255153074860573,
-0.036780308932065964,
0.05336698889732361,
-0.08984783291816711,
0.011313606053590775,
0.07315200567245483,
0.23551835119724274,
0.012028774246573448,
-0.31220272183418274,
-0.0570409931242466,
0.0009880746947601438,
0.005219819024205208,
0.004538774024695158,
-0.001728913513943553,
0.06389892101287842,
-0.09137473255395889,
0.05426069349050522,
-0.053995806723833084,
0.08018060773611069,
-0.055907852947711945,
0.050579898059368134,
0.0637912005186081,
0.11854322999715805,
-0.0056502907536923885,
0.0552690364420414,
-0.29091569781303406,
0.2529100179672241,
0.006048697512596846,
0.0962657704949379,
-0.047209423035383224,
0.016154898330569267,
0.014272878877818584,
0.024006996303796768,
0.0065947482362389565,
-0.005040371790528297,
-0.021075129508972168,
-0.2091122567653656,
-0.03275260701775551,
0.0448637530207634,
0.12926098704338074,
-0.05487370491027832,
0.13399498164653778,
-0.014981182292103767,
-0.015377162024378777,
0.07775700837373734,
0.011512466706335545,
-0.10562141239643097,
-0.10720431059598923,
0.016765061765909195,
-0.01912826858460903,
-0.008144526742398739,
-0.07018985599279404,
-0.10947753489017487,
-0.14951753616333008,
0.19342540204524994,
-0.0217084102332592,
-0.026208195835351944,
-0.11026836186647415,
0.09016264230012894,
0.08540821820497513,
-0.07555095106363297,
0.03408247232437134,
0.027252888306975365,
0.06811079382896423,
0.02957208827137947,
-0.0637168139219284,
0.10323169827461243,
-0.07093114405870438,
-0.18507367372512817,
-0.07122466713190079,
0.08368736505508423,
0.057468123733997345,
0.06262370198965073,
-0.029416091740131378,
0.03989965841174126,
-0.012118721380829811,
-0.10515157133340836,
0.03005680814385414,
0.06423664838075638,
0.053565070033073425,
0.016393888741731644,
-0.09266558289527893,
0.05396803095936775,
-0.04123702645301819,
-0.02315450832247734,
0.10700560361146927,
0.28734779357910156,
-0.07576597481966019,
0.01747201941907406,
0.012294808402657509,
-0.09056823700666428,
-0.14113496243953705,
0.07487554848194122,
0.07117959856987,
-0.0199884120374918,
0.0068710967898368835,
-0.2410556674003601,
0.13493597507476807,
0.12318544089794159,
0.01587880402803421,
0.10548274964094162,
-0.36343052983283997,
-0.1375860869884491,
0.07137694954872131,
0.14294205605983734,
0.0868791937828064,
-0.17153598368167877,
-0.030185777693986893,
-0.040787603706121445,
-0.17548835277557373,
0.09616094827651978,
-0.0828344076871872,
0.11177236586809158,
-0.04196490719914436,
0.03952031955122948,
0.015518782660365105,
-0.0613262765109539,
0.11326717585325241,
0.027819102630019188,
0.10840540379285812,
-0.053251560777425766,
0.02840636856853962,
0.052122991532087326,
-0.03879910707473755,
-0.01478899922221899,
-0.10242541879415512,
0.022659629583358765,
-0.06982044130563736,
-0.025613782927393913,
-0.07677596807479858,
0.022030601277947426,
-0.0554916188120842,
-0.06427837163209915,
-0.03799349442124367,
0.011407128535211086,
0.09601738303899765,
-0.028683478012681007,
0.0768744945526123,
0.0061795697547495365,
0.197901651263237,
0.028950361534953117,
0.033817119896411896,
-0.052227992564439774,
-0.05636390671133995,
-0.013663992285728455,
0.015367355197668076,
0.04242103546857834,
-0.10416477918624878,
0.016178980469703674,
0.1552576869726181,
0.03249175846576691,
0.14890186488628387,
0.1005140095949173,
-0.04093130677938461,
-0.006044747307896614,
0.06810129433870316,
-0.13508690893650055,
-0.12459693849086761,
0.007892251014709473,
-0.08220265060663223,
-0.08767984807491302,
0.03293673321604729,
0.09401477873325348,
-0.07643761485815048,
0.003965754061937332,
-0.008291084319353104,
0.025850282981991768,
-0.01711023785173893,
0.21142764389514923,
0.012954151257872581,
0.060328349471092224,
-0.10413691401481628,
0.0662626251578331,
0.030035555362701416,
-0.05620170012116432,
0.03279461711645126,
0.053711261600255966,
-0.07238051295280457,
-0.005670708138495684,
0.14892175793647766,
0.2099195271730423,
-0.07212700694799423,
0.0020413289312273264,
-0.1492326855659485,
-0.12504780292510986,
0.07406985759735107,
0.18144570291042328,
0.06570147722959518,
0.010092201642692089,
-0.027624860405921936,
0.042414482682943344,
-0.11602935940027237,
0.0784757137298584,
0.04501110687851906,
0.09052793681621552,
-0.09984293580055237,
0.1721181720495224,
0.0197366401553154,
-0.02393682673573494,
-0.00146693445276469,
0.03213908150792122,
-0.1514531970024109,
-0.0038864666130393744,
-0.10370063781738281,
-0.06574919074773788,
-0.019166085869073868,
-0.013723082840442657,
0.005172360688447952,
-0.038799185305833817,
-0.06817309558391571,
0.01194370910525322,
-0.10663017630577087,
-0.05069343000650406,
0.003231367329135537,
0.06519366055727005,
-0.14526255428791046,
0.003206804860383272,
0.02789318934082985,
-0.10482414066791534,
0.059310223907232285,
0.0701475441455841,
0.024621041491627693,
0.05908406525850296,
-0.17447015643119812,
-0.0063165160827338696,
0.04415540024638176,
0.004166727419942617,
0.06193075701594353,
-0.12118463218212128,
0.006243267562240362,
-0.024500323459506035,
0.03881590813398361,
0.02349495328962803,
0.05252701789140701,
-0.11595148593187332,
0.025737861171364784,
-0.06436372548341751,
-0.07419270277023315,
-0.04247700795531273,
0.018516242504119873,
0.08206404000520706,
-0.018249809741973877,
0.16581444442272186,
-0.08583759516477585,
0.04633258283138275,
-0.2366485893726349,
-0.027289150282740593,
0.012470701709389687,
-0.08278979361057281,
-0.06742460280656815,
-0.04759761691093445,
0.06952839344739914,
-0.062375858426094055,
0.12884870171546936,
-0.03182827681303024,
0.01579258032143116,
0.02218642458319664,
-0.046638861298561096,
-0.04449158161878586,
0.018108859658241272,
0.20032398402690887,
0.07493029534816742,
-0.03442414477467537,
0.0563582144677639,
0.04770779237151146,
0.09560923278331757,
0.0738782063126564,
0.22124052047729492,
0.12459464371204376,
-0.03538145869970322,
0.07940851151943207,
0.051262207329273224,
-0.11641114205121994,
-0.13573399186134338,
0.09971993416547775,
-0.0856676697731018,
0.13629750907421112,
-0.024226969107985497,
0.2160179764032364,
0.12344074249267578,
-0.1652417927980423,
0.03814312443137169,
-0.05050782486796379,
-0.08255541324615479,
-0.11700394749641418,
0.003189795184880495,
-0.10207725316286087,
-0.17417947947978973,
0.04329182580113411,
-0.12801101803779602,
0.038930121809244156,
0.08865257352590561,
0.038882751017808914,
0.036347899585962296,
0.15521140396595,
0.06970321387052536,
0.014455600641667843,
0.013228881172835827,
0.01690719835460186,
-0.056140780448913574,
-0.08030907064676285,
-0.0668388307094574,
0.002239687368273735,
-0.02704395353794098,
0.049440138041973114,
-0.025157341733574867,
-0.059867724776268005,
0.05017693340778351,
-0.00999437551945448,
-0.09648574143648148,
0.04372188076376915,
-0.016393817961215973,
0.04885057359933853,
0.023143714293837547,
-0.002622281201183796,
-0.0035030266735702753,
-0.025510217994451523,
0.21340607106685638,
-0.06626836210489273,
-0.09424106776714325,
-0.0848611444234848,
0.26430514454841614,
0.08098014444112778,
0.010458665899932384,
0.0354660227894783,
-0.07242655754089355,
0.003407094394788146,
0.2029104381799698,
0.19808577001094818,
-0.06495485454797745,
-0.0006488658837042749,
0.016619930043816566,
-0.018129386007785797,
-0.01854543760418892,
0.08568765223026276,
0.11459605395793915,
0.03718018904328346,
-0.06053891032934189,
-0.01841488853096962,
-0.043531786650419235,
-0.031671494245529175,
-0.018628092482686043,
0.0779486745595932,
0.05363806337118149,
0.0033192934934049845,
-0.013978409580886364,
0.0597035214304924,
-0.04612774774432182,
-0.13647957146167755,
0.0790148451924324,
-0.20167306065559387,
-0.1584535837173462,
-0.010997802950441837,
0.09749285131692886,
-0.015940025448799133,
0.06790558993816376,
-0.011925220489501953,
-0.05686907097697258,
0.08478214591741562,
-0.01230013556778431,
-0.07151233404874802,
-0.11641892045736313,
0.05789817124605179,
-0.08596288412809372,
0.18632693588733673,
-0.04984377324581146,
0.025518300011754036,
0.1315181404352188,
0.06325536221265793,
-0.05421949177980423,
0.07109782099723816,
0.054012998938560486,
-0.14406947791576385,
-0.006522731855511665,
0.098042793571949,
-0.058584995567798615,
0.08122774213552475,
0.06654687970876694,
-0.1133267730474472,
0.03336816281080246,
-0.01739341765642166,
-0.060510650277137756,
-0.026792509481310844,
-0.046405285596847534,
-0.04289475828409195,
0.10673727840185165,
0.24044349789619446,
-0.018920505419373512,
0.022274330258369446,
-0.07402347773313522,
0.03197379782795906,
0.04295507073402405,
0.10624711215496063,
-0.06456875801086426,
-0.2798374891281128,
0.037295181304216385,
0.04465162009000778,
0.013195290230214596,
-0.20843975245952606,
-0.10003697872161865,
0.047523561865091324,
-0.057393040508031845,
-0.08800603449344635,
0.10719989240169525,
0.114299476146698,
0.06611817330121994,
-0.07328636944293976,
-0.12033773958683014,
-0.06407155841588974,
0.18754376471042633,
-0.16201581060886383,
-0.10159309953451157
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-lora-1.77M-squad-model2
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "t5-base", "model-index": [{"name": "t5-base-lora-1.77M-squad-model2", "results": []}]} | question-answering | varun-v-rao/t5-base-lora-1.77M-squad-model2 | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"question-answering",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:t5-base",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-09T04:04:59+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us
|
# t5-base-lora-1.77M-squad-model2
This model is a fine-tuned version of t5-base on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# t5-base-lora-1.77M-squad-model2\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 10\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us \n",
"# t5-base-lora-1.77M-squad-model2\n\nThis model is a fine-tuned version of t5-base on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 10\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
80,
37,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #t5 #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-t5-base #license-apache-2.0 #endpoints_compatible #text-generation-inference #region-us \n# t5-base-lora-1.77M-squad-model2\n\nThis model is a fine-tuned version of t5-base on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 64\n- eval_batch_size: 16\n- seed: 10\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.08529214560985565,
0.1450778841972351,
-0.002835290739312768,
0.09535643458366394,
0.11357235163450241,
0.017336200922727585,
0.11504044383764267,
0.1583092361688614,
-0.10131978243589401,
0.07437735050916672,
0.05988472327589989,
0.04653680697083473,
0.06065155193209648,
0.12298142164945602,
-0.028874902054667473,
-0.2150047868490219,
0.00814411323517561,
-0.01796775497496128,
-0.06588518619537354,
0.10506571829319,
0.11054985970258713,
-0.08620855957269669,
0.08280090987682343,
-0.015825526788830757,
-0.10795856267213821,
0.05343129485845566,
-0.019582873210310936,
-0.056785982102155685,
0.09963899850845337,
0.012753266841173172,
0.06008699908852577,
0.010874340310692787,
0.13189826905727386,
-0.24235248565673828,
0.0040224576368927956,
0.08969730138778687,
0.006745413411408663,
0.07699844241142273,
0.03837678208947182,
0.0023193995002657175,
0.08808444440364838,
-0.1736903041601181,
0.0982951670885086,
0.03385934978723526,
-0.07470736652612686,
-0.15477976202964783,
-0.10342196375131607,
0.08849982917308807,
0.09599535912275314,
0.09287960827350616,
0.009518740698695183,
0.16815483570098877,
-0.05488921329379082,
0.09207386523485184,
0.21724705398082733,
-0.2920584976673126,
-0.05428881570696831,
0.05950517579913139,
0.05712905153632164,
0.09213311225175858,
-0.09964215010404587,
-0.0024709641002118587,
0.054202016443014145,
0.02098953351378441,
0.10342386364936829,
-0.016814451664686203,
-0.10664015263319016,
0.019491638988256454,
-0.12898626923561096,
-0.03782579302787781,
0.1939268261194229,
0.05853893235325813,
-0.04118982329964638,
-0.08756508678197861,
-0.06367071717977524,
-0.0781480073928833,
0.007063872646540403,
-0.07179659605026245,
0.04572276398539543,
-0.04896710440516472,
-0.05190916359424591,
-0.06895358115434647,
-0.08482515066862106,
-0.07644522935152054,
0.005308119580149651,
0.04763537645339966,
0.05848998576402664,
0.027864880859851837,
-0.047125667333602905,
0.09765796363353729,
-0.023377740755677223,
-0.12720254063606262,
-0.03740070015192032,
0.013096618466079235,
-0.10162054747343063,
-0.059273988008499146,
-0.008757962845265865,
-0.047425832599401474,
0.012608323246240616,
0.16839240491390228,
-0.05438736826181412,
0.04854271560907364,
-0.005833745002746582,
-0.008844397962093353,
-0.022030845284461975,
0.12691129744052887,
-0.05497727170586586,
-0.04715742543339729,
0.01712612994015217,
0.08379872143268585,
0.026088662445545197,
-0.0023040943779051304,
-0.07574309408664703,
-0.03167227283120155,
0.0961681455373764,
0.08038482069969177,
-0.022986769676208496,
0.02999866008758545,
-0.01375618577003479,
-0.02269461564719677,
0.0026408275589346886,
-0.14490680396556854,
0.035138875246047974,
-0.026046983897686005,
-0.073950856924057,
-0.054324861615896225,
0.04430985078215599,
0.0008397456258535385,
-0.041001006960868835,
0.03443605452775955,
-0.06875286251306534,
-0.01855439692735672,
-0.0649767816066742,
-0.05511050671339035,
0.03956475108861923,
-0.0856395959854126,
-0.010586347430944443,
-0.06802552193403244,
-0.23098334670066833,
-0.023725541308522224,
0.026316437870264053,
-0.06231405586004257,
-0.040665533393621445,
-0.033493444323539734,
-0.06682122498750687,
-0.0043206531554460526,
-0.011933247558772564,
0.1040925532579422,
-0.045472901314496994,
0.06763658672571182,
0.011940643191337585,
0.03666558116674423,
0.03595159575343132,
0.031031077727675438,
-0.08667735755443573,
0.030405232682824135,
-0.11554281413555145,
0.050899334251880646,
-0.08569280803203583,
0.028948893770575523,
-0.14066486060619354,
-0.08974066376686096,
0.0011898597003892064,
-0.03327858820557594,
0.05577810853719711,
0.12119386345148087,
-0.17387939989566803,
-0.00013395812129601836,
0.17049850523471832,
-0.09555968642234802,
-0.12747645378112793,
0.10874991863965988,
-0.04216650873422623,
0.03988108038902283,
0.06736321747303009,
0.14906662702560425,
0.10692644119262695,
-0.17344099283218384,
-0.023493800312280655,
0.006424834486097097,
0.039915531873703,
0.014217239804565907,
0.07428620755672455,
-0.006342685781419277,
0.051117781549692154,
0.0060603381134569645,
-0.08323731273412704,
-0.02084135264158249,
-0.0672805979847908,
-0.09351217746734619,
-0.07374667376279831,
-0.08530845493078232,
0.01782872900366783,
0.03844485059380531,
0.0226217620074749,
-0.07869902998209,
-0.12253725528717041,
0.08396445214748383,
0.1314009577035904,
-0.04979454725980759,
0.019957048818469048,
-0.08836790919303894,
0.04770684242248535,
-0.042496759444475174,
-0.023932280018925667,
-0.1739572137594223,
-0.11776682734489441,
0.03766634687781334,
-0.05023655667901039,
0.043901942670345306,
0.019862836226820946,
0.06821617484092712,
0.05573849007487297,
-0.06575796008110046,
-0.02264174446463585,
-0.08838501572608948,
0.006535467691719532,
-0.08388128131628036,
-0.1943027824163437,
-0.04323675110936165,
-0.032849397510290146,
0.11707752197980881,
-0.21341963112354279,
0.031041914597153664,
0.025081386789679527,
0.15087249875068665,
0.036893781274557114,
-0.039541516453027725,
0.0069258674047887325,
0.009785771369934082,
-0.013966739177703857,
-0.09718544036149979,
0.012940991669893265,
-0.011325744912028313,
-0.0772615373134613,
-0.05759324133396149,
-0.12401352822780609,
0.07404864579439163,
0.06991689652204514,
0.08321934193372726,
-0.08932803571224213,
-0.004497866611927748,
-0.0589882954955101,
-0.04658843204379082,
-0.09137667715549469,
-0.0319005586206913,
0.14861220121383667,
0.00586733128875494,
0.11160662770271301,
-0.08252939581871033,
-0.08209364861249924,
-0.0017094346694648266,
0.004397471435368061,
-0.012889733538031578,
0.0804368406534195,
0.04660908877849579,
-0.12369845062494278,
0.10557505488395691,
0.10147389769554138,
-0.028413450345396996,
0.12695840001106262,
-0.07482359558343887,
-0.10358303785324097,
-0.04266069084405899,
0.035307031124830246,
-0.0034722033888101578,
0.14379356801509857,
-0.07681529223918915,
0.0043099732138216496,
0.028053445741534233,
0.007658813614398241,
0.017457224428653717,
-0.16186799108982086,
-0.011821441352367401,
0.031558748334646225,
-0.06849582493305206,
-0.0005446957657113671,
-0.017077503725886345,
0.022206991910934448,
0.09479919075965881,
0.010749902576208115,
-0.013509374111890793,
0.02305256761610508,
-0.014724242500960827,
-0.09861978888511658,
0.16934040188789368,
-0.09970369189977646,
-0.13674326241016388,
-0.11651896685361862,
0.08389555662870407,
-0.043863050639629364,
-0.037202656269073486,
0.025901956483721733,
-0.07784471660852432,
-0.05751065909862518,
-0.11522509902715683,
-0.025591086596250534,
-0.01842569373548031,
-0.012995836324989796,
0.0401155948638916,
0.03816786780953407,
0.08810324221849442,
-0.14191016554832458,
0.020557956770062447,
-0.00013582858082372695,
-0.098210409283638,
-0.02284766361117363,
0.03673490509390831,
0.11887051910161972,
0.0983300432562828,
-0.027579747140407562,
0.03499326482415199,
-0.04520357400178909,
0.20357240736484528,
-0.0709247961640358,
0.023655593395233154,
0.12790223956108093,
0.007355313282459974,
0.05521668121218681,
0.12806636095046997,
0.013983232900500298,
-0.08063656836748123,
0.03598441183567047,
0.07487037032842636,
-0.020345380529761314,
-0.27674171328544617,
-0.01408859621733427,
-0.021004164591431618,
-0.03914035111665726,
0.07657667249441147,
0.07100538164377213,
0.0587647408246994,
0.03918233886361122,
-0.021982481703162193,
0.02109619416296482,
0.0008542173309251666,
0.08692266792058945,
0.082368865609169,
0.026011649519205093,
0.07872169464826584,
-0.05353895574808121,
-0.029479818418622017,
0.06814879924058914,
0.05171741917729378,
0.26548823714256287,
-0.02162971906363964,
0.13748310506343842,
0.03153941035270691,
0.1692878156900406,
-0.05245283618569374,
0.035081397742033005,
0.0070383306592702866,
0.0151020847260952,
0.009690498001873493,
-0.07365893572568893,
0.00962157640606165,
0.06443701684474945,
-0.04876129329204559,
0.053271710872650146,
-0.05997795611619949,
0.06337977945804596,
0.04229554533958435,
0.28157860040664673,
0.03452576324343681,
-0.2674219012260437,
-0.06831587105989456,
0.024595357477664948,
-0.04233405739068985,
-0.03654231131076813,
0.017250752076506615,
0.13563181459903717,
-0.10820472240447998,
0.06394375115633011,
-0.05427185818552971,
0.08828876912593842,
-0.01335331704467535,
-0.012208978645503521,
0.054474133998155594,
0.09206803888082504,
-0.003824562067165971,
0.10039351135492325,
-0.21060070395469666,
0.2174653857946396,
0.027502505108714104,
0.11265973001718521,
-0.07164707034826279,
0.039781443774700165,
0.0050369743257761,
0.076124407351017,
0.15527647733688354,
-0.009896093048155308,
-0.09276045113801956,
-0.13069112598896027,
-0.08629963546991348,
0.031192254275083542,
0.10519210249185562,
-0.0392325334250927,
0.08816395699977875,
-0.051789216697216034,
-0.006810110993683338,
0.05113949254155159,
-0.053134843707084656,
-0.16916540265083313,
-0.1084822341799736,
0.017630772665143013,
-0.003966525197029114,
-0.04975022003054619,
-0.08981431275606155,
-0.09621994942426682,
-0.04101220518350601,
0.15265271067619324,
-0.030133411288261414,
-0.0477961041033268,
-0.13837890326976776,
0.06349430233240128,
0.12114705890417099,
-0.06893113255500793,
0.01354057714343071,
0.032908275723457336,
0.11761035770177841,
0.04153145104646683,
-0.0918969213962555,
0.050365548580884933,
-0.061141934245824814,
-0.17279556393623352,
-0.05221220478415489,
0.1445264220237732,
0.041425228118896484,
0.04496830329298973,
0.01582343317568302,
0.015640154480934143,
0.02477618120610714,
-0.08263324201107025,
0.018029728904366493,
0.06370481848716736,
0.08370065689086914,
0.04005102813243866,
-0.08037211745977402,
-0.004027842544019222,
-0.05379395931959152,
-0.028119215741753578,
0.11987865716218948,
0.1872074455022812,
-0.0905187726020813,
0.08678961545228958,
0.05156033858656883,
-0.08709808439016342,
-0.16052767634391785,
0.05932685732841492,
0.06480244547128677,
0.0047774179838597775,
0.08451905101537704,
-0.14597249031066895,
0.10255838930606842,
0.09327829629182816,
-0.02442033775150776,
0.02920384705066681,
-0.31870436668395996,
-0.13585065305233002,
0.07096514850854874,
0.11366348713636398,
-0.030011266469955444,
-0.15973606705665588,
-0.040700893849134445,
-0.004780569113790989,
-0.13844835758209229,
0.10180776566267014,
-0.14881573617458344,
0.07695276290178299,
-0.006896985694766045,
0.08317115902900696,
0.022347435355186462,
-0.03868882730603218,
0.12081876397132874,
0.04373439773917198,
0.08870689570903778,
-0.06363359093666077,
0.01403531152755022,
0.12843400239944458,
-0.0772850438952446,
0.10002917051315308,
-0.05105890333652496,
0.08703141659498215,
-0.15029433369636536,
-0.01586800068616867,
-0.05533881112933159,
0.05593528598546982,
-0.06206560507416725,
-0.06274528801441193,
-0.06196887791156769,
0.06284022331237793,
0.07008684426546097,
-0.045837365090847015,
0.09285978972911835,
0.028806397691369057,
0.10013805329799652,
0.12795498967170715,
0.10236271470785141,
0.025655802339315414,
-0.10719034075737,
0.005070855841040611,
-0.02309996448457241,
0.047031741589307785,
-0.14589180052280426,
0.041031040251255035,
0.12510395050048828,
0.04874809458851814,
0.13888397812843323,
0.010865564458072186,
-0.06969727575778961,
-0.014682739041745663,
0.027014179155230522,
-0.11976240575313568,
-0.19567283987998962,
-0.010908665135502815,
-0.04417620599269867,
-0.1449260264635086,
0.045938778668642044,
0.10203384608030319,
-0.0638279840350151,
-0.010908819735050201,
-0.014215129427611828,
0.03705423325300217,
-0.018986042588949203,
0.16369383037090302,
0.0619363933801651,
0.06304630637168884,
-0.06447900831699371,
0.13157697021961212,
0.07768159359693527,
-0.07150135934352875,
0.06436187773942947,
0.07440918684005737,
-0.07998254895210266,
-0.024001603946089745,
0.06685540080070496,
0.15306922793388367,
-0.023525375872850418,
-0.055814873427152634,
-0.10201112926006317,
-0.07369408756494522,
0.04146517813205719,
0.15100669860839844,
0.03567099571228027,
-0.004263145383447409,
-0.0076321884989738464,
0.025027364492416382,
-0.12577229738235474,
0.12520523369312286,
0.04798232391476631,
0.06104189530014992,
-0.1548566222190857,
0.07623247057199478,
0.0023477233480662107,
0.046633634716272354,
-0.022626975551247597,
0.03457818925380707,
-0.08043874800205231,
-0.01482062041759491,
-0.12949484586715698,
0.003523778636008501,
-0.030159326270222664,
0.00954938679933548,
-0.005327314138412476,
-0.08463022112846375,
-0.04157733544707298,
0.06421133875846863,
-0.05288918316364288,
-0.05064624175429344,
0.022776199504733086,
0.06651623547077179,
-0.16804881393909454,
-0.02663024142384529,
0.02619408629834652,
-0.08670169115066528,
0.08649700880050659,
0.03625750541687012,
0.015475657768547535,
0.024667153134942055,
-0.10502009093761444,
0.021420994773507118,
0.01248698215931654,
0.04012896493077278,
0.05050574243068695,
-0.11797146499156952,
-0.008206875063478947,
-0.025046639144420624,
0.0235067680478096,
0.023857736960053444,
0.03245885297656059,
-0.11220546066761017,
-0.021066982299089432,
-0.06915807723999023,
-0.04680345207452774,
-0.0523429773747921,
0.046858154237270355,
0.11256333440542221,
0.003557597054168582,
0.14708319306373596,
-0.07542397081851959,
0.04812028631567955,
-0.22436809539794922,
-0.02219473198056221,
0.015327555127441883,
-0.023063160479068756,
-0.08223257958889008,
-0.022925401106476784,
0.06456308811903,
-0.07408510148525238,
0.10292700678110123,
-0.01762310415506363,
0.10505221039056778,
0.05472332239151001,
-0.03733960911631584,
-0.0008233620319515467,
0.005954298190772533,
0.16177046298980713,
0.02526145987212658,
-0.01591840200126171,
0.0686267614364624,
-0.05149058997631073,
0.04785563051700592,
-0.012283406220376492,
0.1595173329114914,
0.15937457978725433,
-0.029711538925766945,
0.05830589309334755,
0.09602455794811249,
-0.10437485575675964,
-0.12687696516513824,
0.08812085539102554,
-0.010565998032689095,
0.09126122295856476,
-0.04849877208471298,
0.13663950562477112,
0.14294743537902832,
-0.17391793429851532,
0.04225657135248184,
-0.051958173513412476,
-0.10351507365703583,
-0.11434578895568848,
-0.07149583846330643,
-0.08563093096017838,
-0.11717914044857025,
0.029157737269997597,
-0.12705053389072418,
0.03328634425997734,
0.06891416013240814,
0.015660202130675316,
0.0006436648545786738,
0.16070643067359924,
-0.02172546088695526,
0.025069709867239,
0.04581471532583237,
0.027414783835411072,
0.004430670756846666,
-0.04731413722038269,
-0.02924633026123047,
0.05939176306128502,
0.008860128931701183,
0.05836555361747742,
-0.03665447607636452,
0.033761680126190186,
0.025616079568862915,
-0.020065346732735634,
-0.060682378709316254,
0.016097180545330048,
0.02031739242374897,
0.022179855033755302,
0.06054858863353729,
0.06256506592035294,
0.0030206390656530857,
-0.031989678740501404,
0.2651079595088959,
-0.07534389942884445,
-0.08085674047470093,
-0.14219483733177185,
0.1434289515018463,
0.030973581597208977,
-0.013464201241731644,
0.07688148319721222,
-0.13138045370578766,
0.006769264116883278,
0.15472662448883057,
0.13167482614517212,
-0.015991147607564926,
-0.009534681215882301,
-0.0233891811221838,
-0.011739320121705532,
-0.04603506624698639,
0.07156231999397278,
0.09702599793672562,
0.032944876700639725,
-0.05068308487534523,
-0.007026337087154388,
0.010053586214780807,
-0.025926480069756508,
-0.06977462023496628,
0.07636421918869019,
0.004240669310092926,
0.014913161285221577,
-0.010419053956866264,
0.08541352301836014,
0.015008840709924698,
-0.20547476410865784,
0.04584035649895668,
-0.16321244835853577,
-0.17056092619895935,
-0.009257332421839237,
0.10205542296171188,
-0.02481241337954998,
0.02282739244401455,
-0.008845261298120022,
0.002494453452527523,
0.1347171515226364,
-0.0010177434887737036,
-0.08873164653778076,
-0.09799906611442566,
0.09464025497436523,
-0.10164080560207367,
0.23593243956565857,
-0.006126732099801302,
0.07744014263153076,
0.10734846442937851,
-0.01823204569518566,
-0.1526828110218048,
0.04130150377750397,
0.07859165966510773,
-0.04717612266540527,
0.014963414520025253,
0.15088622272014618,
-0.0371331050992012,
0.11248135566711426,
0.05181343853473663,
-0.09040504693984985,
-0.03170091658830643,
-0.007285926956683397,
-0.010591637343168259,
-0.10828585922718048,
0.019389683380723,
-0.06951684504747391,
0.16151246428489685,
0.17132480442523956,
-0.05031689628958702,
0.031140945851802826,
-0.08257696032524109,
0.030822787433862686,
0.06202326714992523,
0.057081181555986404,
0.013513375073671341,
-0.17444400489330292,
0.03514157980680466,
0.007283831015229225,
0.03043326735496521,
-0.22484567761421204,
-0.10867467522621155,
0.06215015798807144,
-0.04894678667187691,
-0.07006452232599258,
0.10594019293785095,
0.11736735701560974,
0.04419320449233055,
-0.029390767216682434,
-0.12944220006465912,
-0.0459558367729187,
0.1395663321018219,
-0.16386668384075165,
-0.04013479873538017
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.