Hugging Face's logo

sharoz
/
codeparrot-small-custom-functions-dataset-python

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
text-generation-inference
Model card Files Community
2
sharoz commited on
Commit
bcb84c5
·
1 Parent(s): 08fb591

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +82 -42
README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
14
 
15
  This model is a fine-tuned version of [codeparrot/codeparrot-small](https://huggingface.co/codeparrot/codeparrot-small) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 0.4934
18
 
19
  ## Model description
20
 
@@ -39,52 +39,92 @@ The following hyperparameters were used during training:
39
  - seed: 42
40
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
41
  - lr_scheduler_type: linear
42
- - num_epochs: 5
43
 
44
  ### Training results
45
 
46
  | Training Loss | Epoch | Step | Validation Loss |
47
  |:-------------:|:-----:|:----:|:---------------:|
48
- | 1.2357 | 0.12 | 1 | 0.9450 |
49
- | 1.0585 | 0.25 | 2 | 0.8835 |
50
- | 0.9853 | 0.38 | 3 | 0.8324 |
51
- | 0.9877 | 0.5 | 4 | 0.7932 |
52
- | 1.0075 | 0.62 | 5 | 0.7623 |
53
- | 0.8744 | 0.75 | 6 | 0.7335 |
54
- | 0.8627 | 0.88 | 7 | 0.7091 |
55
- | 0.8615 | 1.0 | 8 | 0.6893 |
56
- | 0.8016 | 1.12 | 9 | 0.6706 |
57
- | 0.7458 | 1.25 | 10 | 0.6540 |
58
- | 0.7335 | 1.38 | 11 | 0.6378 |
59
- | 0.7754 | 1.5 | 12 | 0.6243 |
60
- | 0.7684 | 1.62 | 13 | 0.6107 |
61
- | 0.7335 | 1.75 | 14 | 0.5985 |
62
- | 0.7418 | 1.88 | 15 | 0.5878 |
63
- | 0.5644 | 2.0 | 16 | 0.5792 |
64
- | 0.6464 | 2.12 | 17 | 0.5711 |
65
- | 0.7304 | 2.25 | 18 | 0.5622 |
66
- | 0.6848 | 2.38 | 19 | 0.5545 |
67
- | 0.7221 | 2.5 | 20 | 0.5480 |
68
- | 0.6053 | 2.62 | 21 | 0.5420 |
69
- | 0.6168 | 2.75 | 22 | 0.5370 |
70
- | 0.5823 | 2.88 | 23 | 0.5323 |
71
- | 0.7512 | 3.0 | 24 | 0.5279 |
72
- | 0.5745 | 3.12 | 25 | 0.5241 |
73
- | 0.674 | 3.25 | 26 | 0.5202 |
74
- | 0.5441 | 3.38 | 27 | 0.5167 |
75
- | 0.6236 | 3.5 | 28 | 0.5134 |
76
- | 0.6006 | 3.62 | 29 | 0.5102 |
77
- | 0.6279 | 3.75 | 30 | 0.5072 |
78
- | 0.6257 | 3.88 | 31 | 0.5046 |
79
- | 0.5408 | 4.0 | 32 | 0.5025 |
80
- | 0.5855 | 4.12 | 33 | 0.5004 |
81
- | 0.594 | 4.25 | 34 | 0.4984 |
82
- | 0.5985 | 4.38 | 35 | 0.4970 |
83
- | 0.6279 | 4.5 | 36 | 0.4958 |
84
- | 0.6151 | 4.62 | 37 | 0.4949 |
85
- | 0.5629 | 4.75 | 38 | 0.4942 |
86
- | 0.5148 | 4.88 | 39 | 0.4937 |
87
- | 0.4823 | 5.0 | 40 | 0.4934 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
88
 
89
 
90
  ### Framework versions
 
14
 
15
  This model is a fine-tuned version of [codeparrot/codeparrot-small](https://huggingface.co/codeparrot/codeparrot-small) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.4238
18
 
19
  ## Model description
20
 
 
39
  - seed: 42
40
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
41
  - lr_scheduler_type: linear
42
+ - num_epochs: 10
43
 
44
  ### Training results
45
 
46
  | Training Loss | Epoch | Step | Validation Loss |
47
  |:-------------:|:-----:|:----:|:---------------:|
48
+ | 1.216 | 0.12 | 1 | 1.0747 |
49
+ | 1.051 | 0.25 | 2 | 1.0005 |
50
+ | 0.9855 | 0.38 | 3 | 0.9462 |
51
+ | 0.9259 | 0.5 | 4 | 0.9042 |
52
+ | 0.9236 | 0.62 | 5 | 0.8675 |
53
+ | 0.8644 | 0.75 | 6 | 0.8331 |
54
+ | 0.8148 | 0.88 | 7 | 0.8030 |
55
+ | 0.7554 | 1.0 | 8 | 0.7800 |
56
+ | 0.7815 | 1.12 | 9 | 0.7600 |
57
+ | 0.784 | 1.25 | 10 | 0.7440 |
58
+ | 0.635 | 1.38 | 11 | 0.7309 |
59
+ | 0.6666 | 1.5 | 12 | 0.7170 |
60
+ | 0.7676 | 1.62 | 13 | 0.6993 |
61
+ | 0.6608 | 1.75 | 14 | 0.6835 |
62
+ | 0.6885 | 1.88 | 15 | 0.6696 |
63
+ | 0.69 | 2.0 | 16 | 0.6582 |
64
+ | 0.6343 | 2.12 | 17 | 0.6463 |
65
+ | 0.709 | 2.25 | 18 | 0.6324 |
66
+ | 0.5446 | 2.38 | 19 | 0.6206 |
67
+ | 0.5298 | 2.5 | 20 | 0.6102 |
68
+ | 0.6478 | 2.62 | 21 | 0.6016 |
69
+ | 0.546 | 2.75 | 22 | 0.5941 |
70
+ | 0.6297 | 2.88 | 23 | 0.5871 |
71
+ | 0.4518 | 3.0 | 24 | 0.5814 |
72
+ | 0.566 | 3.12 | 25 | 0.5769 |
73
+ | 0.6285 | 3.25 | 26 | 0.5702 |
74
+ | 0.5938 | 3.38 | 27 | 0.5631 |
75
+ | 0.514 | 3.5 | 28 | 0.5568 |
76
+ | 0.5113 | 3.62 | 29 | 0.5504 |
77
+ | 0.512 | 3.75 | 30 | 0.5451 |
78
+ | 0.4392 | 3.88 | 31 | 0.5407 |
79
+ | 0.5097 | 4.0 | 32 | 0.5370 |
80
+ | 0.4866 | 4.12 | 33 | 0.5326 |
81
+ | 0.5028 | 4.25 | 34 | 0.5285 |
82
+ | 0.5438 | 4.38 | 35 | 0.5228 |
83
+ | 0.5424 | 4.5 | 36 | 0.5166 |
84
+ | 0.5156 | 4.62 | 37 | 0.5108 |
85
+ | 0.4335 | 4.75 | 38 | 0.5056 |
86
+ | 0.4298 | 4.88 | 39 | 0.5013 |
87
+ | 0.5268 | 5.0 | 40 | 0.4978 |
88
+ | 0.4714 | 5.12 | 41 | 0.4938 |
89
+ | 0.4659 | 5.25 | 42 | 0.4907 |
90
+ | 0.4573 | 5.38 | 43 | 0.4874 |
91
+ | 0.4689 | 5.5 | 44 | 0.4847 |
92
+ | 0.4346 | 5.62 | 45 | 0.4824 |
93
+ | 0.4563 | 5.75 | 46 | 0.4794 |
94
+ | 0.4505 | 5.88 | 47 | 0.4761 |
95
+ | 0.7359 | 6.0 | 48 | 0.4732 |
96
+ | 0.4704 | 6.12 | 49 | 0.4706 |
97
+ | 0.4223 | 6.25 | 50 | 0.4685 |
98
+ | 0.4789 | 6.38 | 51 | 0.4651 |
99
+ | 0.4402 | 6.5 | 52 | 0.4624 |
100
+ | 0.4454 | 6.62 | 53 | 0.4597 |
101
+ | 0.4496 | 6.75 | 54 | 0.4566 |
102
+ | 0.3942 | 6.88 | 55 | 0.4539 |
103
+ | 0.2915 | 7.0 | 56 | 0.4515 |
104
+ | 0.3926 | 7.12 | 57 | 0.4496 |
105
+ | 0.4102 | 7.25 | 58 | 0.4474 |
106
+ | 0.4235 | 7.38 | 59 | 0.4456 |
107
+ | 0.4841 | 7.5 | 60 | 0.4441 |
108
+ | 0.3914 | 7.62 | 61 | 0.4423 |
109
+ | 0.4417 | 7.75 | 62 | 0.4404 |
110
+ | 0.4212 | 7.88 | 63 | 0.4384 |
111
+ | 0.4343 | 8.0 | 64 | 0.4369 |
112
+ | 0.4159 | 8.12 | 65 | 0.4355 |
113
+ | 0.4193 | 8.25 | 66 | 0.4343 |
114
+ | 0.4393 | 8.38 | 67 | 0.4333 |
115
+ | 0.4507 | 8.5 | 68 | 0.4319 |
116
+ | 0.3855 | 8.62 | 69 | 0.4305 |
117
+ | 0.4064 | 8.75 | 70 | 0.4293 |
118
+ | 0.4044 | 8.88 | 71 | 0.4283 |
119
+ | 0.2957 | 9.0 | 72 | 0.4275 |
120
+ | 0.4442 | 9.12 | 73 | 0.4266 |
121
+ | 0.4142 | 9.25 | 74 | 0.4260 |
122
+ | 0.4022 | 9.38 | 75 | 0.4253 |
123
+ | 0.4161 | 9.5 | 76 | 0.4248 |
124
+ | 0.3828 | 9.62 | 77 | 0.4244 |
125
+ | 0.384 | 9.75 | 78 | 0.4241 |
126
+ | 0.3985 | 9.88 | 79 | 0.4239 |
127
+ | 0.4912 | 10.0 | 80 | 0.4238 |
128
 
129
 
130
  ### Framework versions