binary_paragraph_exp2

This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9220
• Classification Report: {'0': {'precision': 0.9416413373860182, 'recall': 0.9729899497487438, 'f1-score': 0.9570590052517763, 'support': 1592.0}, '1': {'precision': 0.7922705314009661, 'recall': 0.6307692307692307, 'f1-score': 0.702355460385439, 'support': 260.0}, 'accuracy': 0.9249460043196545, 'macro avg': {'precision': 0.8669559343934922, 'recall': 0.8018795902589873, 'f1-score': 0.8297072328186077, 'support': 1852.0}, 'weighted avg': {'precision': 0.9206713538244018, 'recall': 0.9249460043196545, 'f1-score': 0.9213014881539104, 'support': 1852.0}}

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Classification Report
0.4148	1.0	781	0.4646	{'0': {'precision': 0.8704209950792783, 'recall': 1.0, 'f1-score': 0.9307220111078632, 'support': 1592.0}, '1': {'precision': 1.0, 'recall': 0.08846153846153847, 'f1-score': 0.1625441696113074, 'support': 260.0}, 'accuracy': 0.8720302375809935, 'macro avg': {'precision': 0.9352104975396391, 'recall': 0.5442307692307692, 'f1-score': 0.5466330903595853, 'support': 1852.0}, 'weighted avg': {'precision': 0.8886124320551895, 'recall': 0.8720302375809935, 'f1-score': 0.8228784696450638, 'support': 1852.0}}
0.3363	2.0	1562	0.2247	{'0': {'precision': 0.940923076923077, 'recall': 0.960427135678392, 'f1-score': 0.9505750699409388, 'support': 1592.0}, '1': {'precision': 0.7224669603524229, 'recall': 0.6307692307692307, 'f1-score': 0.6735112936344969, 'support': 260.0}, 'accuracy': 0.9141468682505399, 'macro avg': {'precision': 0.8316950186377499, 'recall': 0.7955981832238114, 'f1-score': 0.8120431817877178, 'support': 1852.0}, 'weighted avg': {'precision': 0.9102542916593782, 'recall': 0.9141468682505399, 'f1-score': 0.9116784274789114, 'support': 1852.0}}
0.2633	3.0	2343	0.2125	{'0': {'precision': 0.9517543859649122, 'recall': 0.9541457286432161, 'f1-score': 0.9529485570890841, 'support': 1592.0}, '1': {'precision': 0.71484375, 'recall': 0.7038461538461539, 'f1-score': 0.7093023255813954, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8332990679824561, 'recall': 0.828995941244685, 'f1-score': 0.8311254413352398, 'support': 1852.0}, 'weighted avg': {'precision': 0.9184947934428404, 'recall': 0.9190064794816415, 'f1-score': 0.9187433626009637, 'support': 1852.0}}
0.231	4.0	3124	0.2109	{'0': {'precision': 0.9347958561852528, 'recall': 0.9635678391959799, 'f1-score': 0.9489638107021342, 'support': 1592.0}, '1': {'precision': 0.7251184834123223, 'recall': 0.5884615384615385, 'f1-score': 0.6496815286624203, 'support': 260.0}, 'accuracy': 0.9109071274298056, 'macro avg': {'precision': 0.8299571697987875, 'recall': 0.7760146888287591, 'f1-score': 0.7993226696822773, 'support': 1852.0}, 'weighted avg': {'precision': 0.9053595079557918, 'recall': 0.9109071274298056, 'f1-score': 0.9069479395734488, 'support': 1852.0}}
0.237	5.0	3905	0.2781	{'0': {'precision': 0.9408175716900549, 'recall': 0.9685929648241206, 'f1-score': 0.9545032497678737, 'support': 1592.0}, '1': {'precision': 0.7652582159624414, 'recall': 0.6269230769230769, 'f1-score': 0.6892177589852009, 'support': 260.0}, 'accuracy': 0.9206263498920086, 'macro avg': {'precision': 0.8530378938262482, 'recall': 0.7977580208735988, 'f1-score': 0.8218605043765372, 'support': 1852.0}, 'weighted avg': {'precision': 0.9161710098708435, 'recall': 0.9206263498920086, 'f1-score': 0.9172601463102631, 'support': 1852.0}}
0.1888	6.0	4686	0.2870	{'0': {'precision': 0.9324162679425837, 'recall': 0.9792713567839196, 'f1-score': 0.9552696078431373, 'support': 1592.0}, '1': {'precision': 0.8166666666666667, 'recall': 0.5653846153846154, 'f1-score': 0.6681818181818182, 'support': 260.0}, 'accuracy': 0.9211663066954644, 'macro avg': {'precision': 0.8745414673046252, 'recall': 0.7723279860842676, 'f1-score': 0.8117257130124778, 'support': 1852.0}, 'weighted avg': {'precision': 0.9161663239189668, 'recall': 0.9211663066954644, 'f1-score': 0.9149657064867965, 'support': 1852.0}}
0.1606	7.0	5467	0.2999	{'0': {'precision': 0.950345694531741, 'recall': 0.949748743718593, 'f1-score': 0.9500471253534402, 'support': 1592.0}, '1': {'precision': 0.6934865900383141, 'recall': 0.6961538461538461, 'f1-score': 0.6948176583493282, 'support': 260.0}, 'accuracy': 0.9141468682505399, 'macro avg': {'precision': 0.8219161422850276, 'recall': 0.8229512949362195, 'f1-score': 0.8224323918513842, 'support': 1852.0}, 'weighted avg': {'precision': 0.9142855610715407, 'recall': 0.9141468682505399, 'f1-score': 0.9142157746941156, 'support': 1852.0}}
0.1251	8.0	6248	0.3801	{'0': {'precision': 0.9427527405602923, 'recall': 0.9723618090452262, 'f1-score': 0.9573283858998145, 'support': 1592.0}, '1': {'precision': 0.7904761904761904, 'recall': 0.6384615384615384, 'f1-score': 0.7063829787234043, 'support': 260.0}, 'accuracy': 0.9254859611231101, 'macro avg': {'precision': 0.8666144655182414, 'recall': 0.8054116737533823, 'f1-score': 0.8318556823116094, 'support': 1852.0}, 'weighted avg': {'precision': 0.9213748231618764, 'recall': 0.9254859611231101, 'f1-score': 0.9220984691255885, 'support': 1852.0}}
0.1189	9.0	7029	0.4351	{'0': {'precision': 0.9186658864833236, 'recall': 0.9861809045226131, 'f1-score': 0.9512269009391093, 'support': 1592.0}, '1': {'precision': 0.8461538461538461, 'recall': 0.4653846153846154, 'f1-score': 0.6004962779156328, 'support': 260.0}, 'accuracy': 0.9130669546436285, 'macro avg': {'precision': 0.8824098663185849, 'recall': 0.7257827599536142, 'f1-score': 0.775861589427371, 'support': 1852.0}, 'weighted avg': {'precision': 0.9084860104111506, 'recall': 0.9130669546436285, 'f1-score': 0.9019882605578436, 'support': 1852.0}}
0.0996	10.0	7810	0.4013	{'0': {'precision': 0.9452980946527351, 'recall': 0.9660804020100503, 'f1-score': 0.9555762659210935, 'support': 1592.0}, '1': {'precision': 0.76, 'recall': 0.6576923076923077, 'f1-score': 0.7051546391752578, 'support': 260.0}, 'accuracy': 0.9227861771058316, 'macro avg': {'precision': 0.8526490473263675, 'recall': 0.811886354851179, 'f1-score': 0.8303654525481756, 'support': 1852.0}, 'weighted avg': {'precision': 0.919284323265202, 'recall': 0.9227861771058316, 'f1-score': 0.9204198820366889, 'support': 1852.0}}
0.0829	11.0	8591	0.4406	{'0': {'precision': 0.9397443700547778, 'recall': 0.9698492462311558, 'f1-score': 0.9545595054095827, 'support': 1592.0}, '1': {'precision': 0.7703349282296651, 'recall': 0.6192307692307693, 'f1-score': 0.6865671641791045, 'support': 260.0}, 'accuracy': 0.9206263498920086, 'macro avg': {'precision': 0.8550396491422214, 'recall': 0.7945400077309626, 'f1-score': 0.8205633347943435, 'support': 1852.0}, 'weighted avg': {'precision': 0.9159611870771702, 'recall': 0.9206263498920086, 'f1-score': 0.9169363905500123, 'support': 1852.0}}
0.0674	12.0	9372	0.4446	{'0': {'precision': 0.9490999379267536, 'recall': 0.960427135678392, 'f1-score': 0.9547299406806119, 'support': 1592.0}, '1': {'precision': 0.7385892116182573, 'recall': 0.6846153846153846, 'f1-score': 0.7105788423153693, 'support': 260.0}, 'accuracy': 0.92170626349892, 'macro avg': {'precision': 0.8438445747725054, 'recall': 0.8225212601468883, 'f1-score': 0.8326543914979906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9195465962203773, 'recall': 0.92170626349892, 'f1-score': 0.9204538685559018, 'support': 1852.0}}
0.0808	13.0	10153	0.4638	{'0': {'precision': 0.9528894472361809, 'recall': 0.9528894472361809, 'f1-score': 0.9528894472361809, 'support': 1592.0}, '1': {'precision': 0.7115384615384616, 'recall': 0.7115384615384616, 'f1-score': 0.7115384615384616, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8322139543873213, 'recall': 0.8322139543873213, 'f1-score': 0.8322139543873213, 'support': 1852.0}, 'weighted avg': {'precision': 0.9190064794816415, 'recall': 0.9190064794816415, 'f1-score': 0.9190064794816415, 'support': 1852.0}}
0.055	14.0	10934	0.5201	{'0': {'precision': 0.9522613065326633, 'recall': 0.9522613065326633, 'f1-score': 0.9522613065326633, 'support': 1592.0}, '1': {'precision': 0.7076923076923077, 'recall': 0.7076923076923077, 'f1-score': 0.7076923076923077, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8299768071124856, 'recall': 0.8299768071124856, 'f1-score': 0.8299768071124856, 'support': 1852.0}, 'weighted avg': {'precision': 0.91792656587473, 'recall': 0.91792656587473, 'f1-score': 0.91792656587473, 'support': 1852.0}}
0.0406	15.0	11715	0.5591	{'0': {'precision': 0.9627249357326478, 'recall': 0.9409547738693468, 'f1-score': 0.951715374841169, 'support': 1592.0}, '1': {'precision': 0.6824324324324325, 'recall': 0.7769230769230769, 'f1-score': 0.7266187050359713, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8225786840825402, 'recall': 0.8589389253962119, 'f1-score': 0.8391670399385701, 'support': 1852.0}, 'weighted avg': {'precision': 0.9233750162628552, 'recall': 0.91792656587473, 'f1-score': 0.9201143304840678, 'support': 1852.0}}
0.0194	16.0	12496	0.4841	{'0': {'precision': 0.9553739786297926, 'recall': 0.9547738693467337, 'f1-score': 0.9550738297203896, 'support': 1592.0}, '1': {'precision': 0.7241379310344828, 'recall': 0.7269230769230769, 'f1-score': 0.72552783109405, 'support': 260.0}, 'accuracy': 0.9227861771058316, 'macro avg': {'precision': 0.8397559548321376, 'recall': 0.8408484731349053, 'f1-score': 0.8403008304072197, 'support': 1852.0}, 'weighted avg': {'precision': 0.9229110345829348, 'recall': 0.9227861771058316, 'f1-score': 0.9228481495676637, 'support': 1852.0}}
0.0362	17.0	13277	0.5924	{'0': {'precision': 0.950778816199377, 'recall': 0.9585427135678392, 'f1-score': 0.9546449796684392, 'support': 1592.0}, '1': {'precision': 0.7327935222672065, 'recall': 0.6961538461538461, 'f1-score': 0.7140039447731755, 'support': 260.0}, 'accuracy': 0.92170626349892, 'macro avg': {'precision': 0.8417861692332917, 'recall': 0.8273482798608427, 'f1-score': 0.8343244622208074, 'support': 1852.0}, 'weighted avg': {'precision': 0.9201761291462646, 'recall': 0.92170626349892, 'f1-score': 0.920861681033035, 'support': 1852.0}}
0.0214	18.0	14058	0.7027	{'0': {'precision': 0.9521711768407803, 'recall': 0.9503768844221105, 'f1-score': 0.9512731845331657, 'support': 1592.0}, '1': {'precision': 0.6996197718631179, 'recall': 0.7076923076923077, 'f1-score': 0.7036328871892925, 'support': 260.0}, 'accuracy': 0.9163066954643628, 'macro avg': {'precision': 0.8258954743519491, 'recall': 0.8290345960572092, 'f1-score': 0.8274530358612291, 'support': 1852.0}, 'weighted avg': {'precision': 0.9167157960123828, 'recall': 0.9163066954643628, 'f1-score': 0.9165072680594037, 'support': 1852.0}}
0.017	19.0	14839	0.8658	{'0': {'precision': 0.94858934169279, 'recall': 0.9503768844221105, 'f1-score': 0.9494822717288987, 'support': 1592.0}, '1': {'precision': 0.6926070038910506, 'recall': 0.6846153846153846, 'f1-score': 0.688588007736944, 'support': 260.0}, 'accuracy': 0.9130669546436285, 'macro avg': {'precision': 0.8205981727919203, 'recall': 0.8174961345187476, 'f1-score': 0.8190351397329213, 'support': 1852.0}, 'weighted avg': {'precision': 0.9126522964290469, 'recall': 0.9130669546436285, 'f1-score': 0.9128556471943908, 'support': 1852.0}}
0.0131	20.0	15620	0.6128	{'0': {'precision': 0.9495327102803738, 'recall': 0.957286432160804, 'f1-score': 0.9533938066937754, 'support': 1592.0}, '1': {'precision': 0.7246963562753036, 'recall': 0.6884615384615385, 'f1-score': 0.7061143984220908, 'support': 260.0}, 'accuracy': 0.9195464362850972, 'macro avg': {'precision': 0.8371145332778387, 'recall': 0.8228739853111713, 'f1-score': 0.8297541025579331, 'support': 1852.0}, 'weighted avg': {'precision': 0.9179682113379773, 'recall': 0.9195464362850972, 'f1-score': 0.918678554992567, 'support': 1852.0}}
0.0146	21.0	16401	0.6882	{'0': {'precision': 0.954915466499687, 'recall': 0.9579145728643216, 'f1-score': 0.9564126685481342, 'support': 1592.0}, '1': {'precision': 0.7372549019607844, 'recall': 0.7230769230769231, 'f1-score': 0.7300970873786408, 'support': 260.0}, 'accuracy': 0.9249460043196545, 'macro avg': {'precision': 0.8460851842302357, 'recall': 0.8404957479706223, 'f1-score': 0.8432548779633875, 'support': 1852.0}, 'weighted avg': {'precision': 0.9243583678063205, 'recall': 0.9249460043196545, 'f1-score': 0.9246405027252033, 'support': 1852.0}}
0.0064	22.0	17182	0.6426	{'0': {'precision': 0.943327239488117, 'recall': 0.9723618090452262, 'f1-score': 0.957624497370863, 'support': 1592.0}, '1': {'precision': 0.7914691943127962, 'recall': 0.6423076923076924, 'f1-score': 0.7091295116772823, 'support': 260.0}, 'accuracy': 0.9260259179265659, 'macro avg': {'precision': 0.8673982169004566, 'recall': 0.8073347506764592, 'f1-score': 0.8333770045240727, 'support': 1852.0}, 'weighted avg': {'precision': 0.9220080754786227, 'recall': 0.9260259179265659, 'f1-score': 0.9227385922518938, 'support': 1852.0}}
0.0121	23.0	17963	0.8338	{'0': {'precision': 0.9361060880048222, 'recall': 0.9755025125628141, 'f1-score': 0.9553983389726238, 'support': 1592.0}, '1': {'precision': 0.7979274611398963, 'recall': 0.5923076923076923, 'f1-score': 0.6799116997792495, 'support': 260.0}, 'accuracy': 0.92170626349892, 'macro avg': {'precision': 0.8670167745723593, 'recall': 0.7839051024352532, 'f1-score': 0.8176550193759367, 'support': 1852.0}, 'weighted avg': {'precision': 0.9167073606911716, 'recall': 0.92170626349892, 'f1-score': 0.916723108848284, 'support': 1852.0}}
0.0066	24.0	18744	0.8498	{'0': {'precision': 0.951875, 'recall': 0.9566582914572864, 'f1-score': 0.9542606516290727, 'support': 1592.0}, '1': {'precision': 0.7261904761904762, 'recall': 0.7038461538461539, 'f1-score': 0.71484375, 'support': 260.0}, 'accuracy': 0.9211663066954644, 'macro avg': {'precision': 0.839032738095238, 'recall': 0.8302522226517202, 'f1-score': 0.8345522008145363, 'support': 1852.0}, 'weighted avg': {'precision': 0.9201914275429395, 'recall': 0.9211663066954644, 'f1-score': 0.9206492075558768, 'support': 1852.0}}
0.0115	25.0	19525	0.7286	{'0': {'precision': 0.9475632325724861, 'recall': 0.964824120603015, 'f1-score': 0.9561157796451915, 'support': 1592.0}, '1': {'precision': 0.7575757575757576, 'recall': 0.6730769230769231, 'f1-score': 0.7128309572301426, 'support': 260.0}, 'accuracy': 0.923866090712743, 'macro avg': {'precision': 0.8525694950741218, 'recall': 0.8189505218399691, 'f1-score': 0.8344733684376671, 'support': 1852.0}, 'weighted avg': {'precision': 0.9208911248515631, 'recall': 0.923866090712743, 'f1-score': 0.9219613229346555, 'support': 1852.0}}
0.0082	26.0	20306	0.7561	{'0': {'precision': 0.9424019607843137, 'recall': 0.9660804020100503, 'f1-score': 0.9540942928039702, 'support': 1592.0}, '1': {'precision': 0.7545454545454545, 'recall': 0.6384615384615384, 'f1-score': 0.6916666666666667, 'support': 260.0}, 'accuracy': 0.9200863930885529, 'macro avg': {'precision': 0.8484737076648841, 'recall': 0.8022709702357944, 'f1-score': 0.8228804797353184, 'support': 1852.0}, 'weighted avg': {'precision': 0.9160290171438691, 'recall': 0.9200863930885529, 'f1-score': 0.9172524014456014, 'support': 1852.0}}
0.0143	27.0	21087	0.7671	{'0': {'precision': 0.9468150896722325, 'recall': 0.9616834170854272, 'f1-score': 0.954191336865067, 'support': 1592.0}, '1': {'precision': 0.7404255319148936, 'recall': 0.6692307692307692, 'f1-score': 0.703030303030303, 'support': 260.0}, 'accuracy': 0.9206263498920086, 'macro avg': {'precision': 0.843620310793563, 'recall': 0.8154570931580982, 'f1-score': 0.8286108199476849, 'support': 1852.0}, 'weighted avg': {'precision': 0.9178403137451763, 'recall': 0.9206263498920086, 'f1-score': 0.9189311485297329, 'support': 1852.0}}
0.0092	28.0	21868	0.7840	{'0': {'precision': 0.9482120838471023, 'recall': 0.9660804020100503, 'f1-score': 0.9570628500311139, 'support': 1592.0}, '1': {'precision': 0.7652173913043478, 'recall': 0.676923076923077, 'f1-score': 0.7183673469387755, 'support': 260.0}, 'accuracy': 0.9254859611231101, 'macro avg': {'precision': 0.8567147375757251, 'recall': 0.8215017394665636, 'f1-score': 0.8377150984849446, 'support': 1852.0}, 'weighted avg': {'precision': 0.9225216842460677, 'recall': 0.9254859611231101, 'f1-score': 0.9235526822103752, 'support': 1852.0}}
0.0064	29.0	22649	0.7067	{'0': {'precision': 0.9501246882793017, 'recall': 0.957286432160804, 'f1-score': 0.9536921151439299, 'support': 1592.0}, '1': {'precision': 0.7258064516129032, 'recall': 0.6923076923076923, 'f1-score': 0.7086614173228346, 'support': 260.0}, 'accuracy': 0.9200863930885529, 'macro avg': {'precision': 0.8379655699461025, 'recall': 0.8247970622342482, 'f1-score': 0.8311767662333822, 'support': 1852.0}, 'weighted avg': {'precision': 0.9186329271922263, 'recall': 0.9200863930885529, 'f1-score': 0.9192925571344889, 'support': 1852.0}}
0.004	30.0	23430	0.7699	{'0': {'precision': 0.9486068111455108, 'recall': 0.9623115577889447, 'f1-score': 0.9554100405363268, 'support': 1592.0}, '1': {'precision': 0.7468354430379747, 'recall': 0.6807692307692308, 'f1-score': 0.7122736418511066, 'support': 260.0}, 'accuracy': 0.9227861771058316, 'macro avg': {'precision': 0.8477211270917427, 'recall': 0.8215403942790878, 'f1-score': 0.8338418411937167, 'support': 1852.0}, 'weighted avg': {'precision': 0.9202803771779301, 'recall': 0.9227861771058316, 'f1-score': 0.9212764208504968, 'support': 1852.0}}
0.0038	31.0	24211	0.8001	{'0': {'precision': 0.9517543859649122, 'recall': 0.9541457286432161, 'f1-score': 0.9529485570890841, 'support': 1592.0}, '1': {'precision': 0.71484375, 'recall': 0.7038461538461539, 'f1-score': 0.7093023255813954, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8332990679824561, 'recall': 0.828995941244685, 'f1-score': 0.8311254413352398, 'support': 1852.0}, 'weighted avg': {'precision': 0.9184947934428404, 'recall': 0.9190064794816415, 'f1-score': 0.9187433626009637, 'support': 1852.0}}
0.0029	32.0	24992	0.7972	{'0': {'precision': 0.9561904761904761, 'recall': 0.9459798994974874, 'f1-score': 0.9510577833912219, 'support': 1592.0}, '1': {'precision': 0.6895306859205776, 'recall': 0.7346153846153847, 'f1-score': 0.7113594040968343, 'support': 260.0}, 'accuracy': 0.9163066954643628, 'macro avg': {'precision': 0.822860581055527, 'recall': 0.8402976420564361, 'f1-score': 0.8312085937440281, 'support': 1852.0}, 'weighted avg': {'precision': 0.9187544365197561, 'recall': 0.9163066954643628, 'f1-score': 0.91740682301512, 'support': 1852.0}}
0.0018	33.0	25773	0.7795	{'0': {'precision': 0.9525593008739076, 'recall': 0.9585427135678392, 'f1-score': 0.9555416405760802, 'support': 1592.0}, '1': {'precision': 0.736, 'recall': 0.7076923076923077, 'f1-score': 0.7215686274509804, 'support': 260.0}, 'accuracy': 0.9233261339092873, 'macro avg': {'precision': 0.8442796504369539, 'recall': 0.8331175106300734, 'f1-score': 0.8385551340135302, 'support': 1852.0}, 'weighted avg': {'precision': 0.9221568072307024, 'recall': 0.9233261339092873, 'f1-score': 0.9226944573079775, 'support': 1852.0}}
0.0061	34.0	26554	0.8124	{'0': {'precision': 0.9469463294262801, 'recall': 0.9641959798994975, 'f1-score': 0.9554933084344849, 'support': 1592.0}, '1': {'precision': 0.7532467532467533, 'recall': 0.6692307692307692, 'f1-score': 0.7087576374745418, 'support': 260.0}, 'accuracy': 0.9227861771058316, 'macro avg': {'precision': 0.8500965413365167, 'recall': 0.8167133745651334, 'f1-score': 0.8321254729545133, 'support': 1852.0}, 'weighted avg': {'precision': 0.9197530843902774, 'recall': 0.9227861771058316, 'f1-score': 0.9208543913450761, 'support': 1852.0}}
0.002	35.0	27335	0.8639	{'0': {'precision': 0.9521144278606966, 'recall': 0.9616834170854272, 'f1-score': 0.956875, 'support': 1592.0}, '1': {'precision': 0.75, 'recall': 0.7038461538461539, 'f1-score': 0.7261904761904762, 'support': 260.0}, 'accuracy': 0.9254859611231101, 'macro avg': {'precision': 0.8510572139303483, 'recall': 0.8327647854657905, 'f1-score': 0.8415327380952381, 'support': 1852.0}, 'weighted avg': {'precision': 0.9237398321567111, 'recall': 0.9254859611231101, 'f1-score': 0.924489483698447, 'support': 1852.0}}
0.0017	36.0	28116	0.9146	{'0': {'precision': 0.9436619718309859, 'recall': 0.967964824120603, 'f1-score': 0.9556589147286821, 'support': 1592.0}, '1': {'precision': 0.7671232876712328, 'recall': 0.6461538461538462, 'f1-score': 0.7014613778705637, 'support': 260.0}, 'accuracy': 0.9227861771058316, 'macro avg': {'precision': 0.8553926297511094, 'recall': 0.8070593351372246, 'f1-score': 0.8285601462996229, 'support': 1852.0}, 'weighted avg': {'precision': 0.9188779232988391, 'recall': 0.9227861771058316, 'f1-score': 0.9199724354721429, 'support': 1852.0}}
0.0008	37.0	28897	0.8441	{'0': {'precision': 0.9477244772447725, 'recall': 0.967964824120603, 'f1-score': 0.9577377252952144, 'support': 1592.0}, '1': {'precision': 0.7743362831858407, 'recall': 0.6730769230769231, 'f1-score': 0.720164609053498, 'support': 260.0}, 'accuracy': 0.9265658747300216, 'macro avg': {'precision': 0.8610303802153065, 'recall': 0.820520873598763, 'f1-score': 0.8389511671743561, 'support': 1852.0}, 'weighted avg': {'precision': 0.9233827221393069, 'recall': 0.9265658747300216, 'f1-score': 0.9243851279826624, 'support': 1852.0}}
0.0018	38.0	29678	0.8533	{'0': {'precision': 0.9468215158924206, 'recall': 0.9729899497487438, 'f1-score': 0.959727385377943, 'support': 1592.0}, '1': {'precision': 0.8009259259259259, 'recall': 0.6653846153846154, 'f1-score': 0.726890756302521, 'support': 260.0}, 'accuracy': 0.9298056155507559, 'macro avg': {'precision': 0.8738737209091733, 'recall': 0.8191872825666795, 'f1-score': 0.843309070840232, 'support': 1852.0}, 'weighted avg': {'precision': 0.9263394136293057, 'recall': 0.9298056155507559, 'f1-score': 0.9270397376675706, 'support': 1852.0}}
0.0039	39.0	30459	0.8169	{'0': {'precision': 0.9459791282995703, 'recall': 0.967964824120603, 'f1-score': 0.9568457000931387, 'support': 1592.0}, '1': {'precision': 0.7713004484304933, 'recall': 0.6615384615384615, 'f1-score': 0.7122153209109731, 'support': 260.0}, 'accuracy': 0.9249460043196545, 'macro avg': {'precision': 0.8586397883650319, 'recall': 0.8147516428295323, 'f1-score': 0.834530510502056, 'support': 1852.0}, 'weighted avg': {'precision': 0.9214562034799374, 'recall': 0.9249460043196545, 'f1-score': 0.9225023423245841, 'support': 1852.0}}
0.0012	40.0	31240	0.8379	{'0': {'precision': 0.9449877750611247, 'recall': 0.9711055276381909, 'f1-score': 0.9578686493184635, 'support': 1592.0}, '1': {'precision': 0.7870370370370371, 'recall': 0.6538461538461539, 'f1-score': 0.7142857142857143, 'support': 260.0}, 'accuracy': 0.9265658747300216, 'macro avg': {'precision': 0.8660124060490809, 'recall': 0.8124758407421724, 'f1-score': 0.8360771818020889, 'support': 1852.0}, 'weighted avg': {'precision': 0.9228132654033154, 'recall': 0.9265658747300216, 'f1-score': 0.9236723409445354, 'support': 1852.0}}
0.0008	41.0	32021	0.8383	{'0': {'precision': 0.9422492401215805, 'recall': 0.9736180904522613, 'f1-score': 0.9576768612913191, 'support': 1592.0}, '1': {'precision': 0.7971014492753623, 'recall': 0.6346153846153846, 'f1-score': 0.7066381156316917, 'support': 260.0}, 'accuracy': 0.9260259179265659, 'macro avg': {'precision': 0.8696753446984714, 'recall': 0.804116737533823, 'f1-score': 0.8321574884615054, 'support': 1852.0}, 'weighted avg': {'precision': 0.9218721204563447, 'recall': 0.9260259179265659, 'f1-score': 0.9224338408423433, 'support': 1852.0}}
0.0019	42.0	32802	0.8564	{'0': {'precision': 0.9433617539585871, 'recall': 0.9729899497487438, 'f1-score': 0.9579468150896723, 'support': 1592.0}, '1': {'precision': 0.7952380952380952, 'recall': 0.6423076923076924, 'f1-score': 0.7106382978723405, 'support': 260.0}, 'accuracy': 0.9265658747300216, 'macro avg': {'precision': 0.8692999245983412, 'recall': 0.807648821028218, 'f1-score': 0.8342925564810064, 'support': 1852.0}, 'weighted avg': {'precision': 0.9225668558660776, 'recall': 0.9265658747300216, 'f1-score': 0.9232274768194204, 'support': 1852.0}}
0.0006	43.0	33583	0.8631	{'0': {'precision': 0.944954128440367, 'recall': 0.9704773869346733, 'f1-score': 0.9575457080880074, 'support': 1592.0}, '1': {'precision': 0.783410138248848, 'recall': 0.6538461538461539, 'f1-score': 0.7127882599580713, 'support': 260.0}, 'accuracy': 0.9260259179265659, 'macro avg': {'precision': 0.8641821333446075, 'recall': 0.8121617703904136, 'f1-score': 0.8351669840230393, 'support': 1852.0}, 'weighted avg': {'precision': 0.9222751665344302, 'recall': 0.9260259179265659, 'f1-score': 0.9231845112663101, 'support': 1852.0}}
0.0	44.0	34364	0.8741	{'0': {'precision': 0.9421084704448507, 'recall': 0.9711055276381909, 'f1-score': 0.9563872564181874, 'support': 1592.0}, '1': {'precision': 0.7819905213270142, 'recall': 0.6346153846153846, 'f1-score': 0.7006369426751592, 'support': 260.0}, 'accuracy': 0.923866090712743, 'macro avg': {'precision': 0.8620494958859324, 'recall': 0.8028604561267878, 'f1-score': 0.8285120995466733, 'support': 1852.0}, 'weighted avg': {'precision': 0.9196297086896468, 'recall': 0.923866090712743, 'f1-score': 0.9204827847264017, 'support': 1852.0}}
0.0003	45.0	35145	0.8963	{'0': {'precision': 0.9437996334758705, 'recall': 0.9704773869346733, 'f1-score': 0.9569526169092598, 'support': 1592.0}, '1': {'precision': 0.7813953488372093, 'recall': 0.6461538461538462, 'f1-score': 0.7073684210526315, 'support': 260.0}, 'accuracy': 0.9249460043196545, 'macro avg': {'precision': 0.8625974911565399, 'recall': 0.8083156165442598, 'f1-score': 0.8321605189809457, 'support': 1852.0}, 'weighted avg': {'precision': 0.9209998958916092, 'recall': 0.9249460043196545, 'f1-score': 0.9219137989164287, 'support': 1852.0}}
0.0017	46.0	35926	0.9038	{'0': {'precision': 0.9421437271619976, 'recall': 0.9717336683417085, 'f1-score': 0.9567099567099567, 'support': 1592.0}, '1': {'precision': 0.7857142857142857, 'recall': 0.6346153846153846, 'f1-score': 0.7021276595744681, 'support': 260.0}, 'accuracy': 0.9244060475161987, 'macro avg': {'precision': 0.8639290064381416, 'recall': 0.8031745264785466, 'f1-score': 0.8294188081422125, 'support': 1852.0}, 'weighted avg': {'precision': 0.9201827904576751, 'recall': 0.9244060475161987, 'f1-score': 0.9209694614317564, 'support': 1852.0}}
0.0013	47.0	36707	0.9121	{'0': {'precision': 0.9415702982349361, 'recall': 0.9717336683417085, 'f1-score': 0.9564142194744977, 'support': 1592.0}, '1': {'precision': 0.784688995215311, 'recall': 0.6307692307692307, 'f1-score': 0.6993603411513859, 'support': 260.0}, 'accuracy': 0.923866090712743, 'macro avg': {'precision': 0.8631296467251235, 'recall': 0.8012514495554697, 'f1-score': 0.8278872803129418, 'support': 1852.0}, 'weighted avg': {'precision': 0.9195459252408203, 'recall': 0.923866090712743, 'f1-score': 0.9203267419561343, 'support': 1852.0}}
0.0007	48.0	37488	0.9184	{'0': {'precision': 0.9416058394160584, 'recall': 0.9723618090452262, 'f1-score': 0.9567367119901112, 'support': 1592.0}, '1': {'precision': 0.7884615384615384, 'recall': 0.6307692307692307, 'f1-score': 0.7008547008547008, 'support': 260.0}, 'accuracy': 0.9244060475161987, 'macro avg': {'precision': 0.8650336889387984, 'recall': 0.8015655199072285, 'f1-score': 0.8287957064224061, 'support': 1852.0}, 'weighted avg': {'precision': 0.9201060995412337, 'recall': 0.9244060475161987, 'f1-score': 0.9208137514635417, 'support': 1852.0}}
0.0011	49.0	38269	0.9214	{'0': {'precision': 0.9416413373860182, 'recall': 0.9729899497487438, 'f1-score': 0.9570590052517763, 'support': 1592.0}, '1': {'precision': 0.7922705314009661, 'recall': 0.6307692307692307, 'f1-score': 0.702355460385439, 'support': 260.0}, 'accuracy': 0.9249460043196545, 'macro avg': {'precision': 0.8669559343934922, 'recall': 0.8018795902589873, 'f1-score': 0.8297072328186077, 'support': 1852.0}, 'weighted avg': {'precision': 0.9206713538244018, 'recall': 0.9249460043196545, 'f1-score': 0.9213014881539104, 'support': 1852.0}}
0.0015	50.0	39050	0.9220	{'0': {'precision': 0.9416413373860182, 'recall': 0.9729899497487438, 'f1-score': 0.9570590052517763, 'support': 1592.0}, '1': {'precision': 0.7922705314009661, 'recall': 0.6307692307692307, 'f1-score': 0.702355460385439, 'support': 260.0}, 'accuracy': 0.9249460043196545, 'macro avg': {'precision': 0.8669559343934922, 'recall': 0.8018795902589873, 'f1-score': 0.8297072328186077, 'support': 1852.0}, 'weighted avg': {'precision': 0.9206713538244018, 'recall': 0.9249460043196545, 'f1-score': 0.9213014881539104, 'support': 1852.0}}

Framework versions

• Transformers 4.51.1
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1