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roberta
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update model card README.md

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@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4812
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- - Accuracy: 0.8993
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- - F1: 0.8993
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- - Bleu4: 0.9483
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  ## Model description
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@@ -50,32 +50,32 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
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- | 1.1319 | 1.0 | 687 | 0.6982 | 0.8562 | 0.8562 | 0.8551 |
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- | 0.7784 | 2.0 | 1374 | 0.6501 | 0.8665 | 0.8665 | 0.8977 |
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- | 0.6779 | 3.0 | 2061 | 0.6229 | 0.8733 | 0.8733 | 0.8535 |
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- | 0.6579 | 4.0 | 2748 | 0.5978 | 0.8769 | 0.8769 | 0.9176 |
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- | 0.6319 | 5.0 | 3435 | 0.5833 | 0.8808 | 0.8808 | 0.8073 |
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- | 0.5988 | 6.0 | 4122 | 0.5627 | 0.8834 | 0.8834 | 0.9241 |
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- | 0.5939 | 7.0 | 4809 | 0.5533 | 0.8864 | 0.8864 | 0.9212 |
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- | 0.575 | 8.0 | 5496 | 0.5512 | 0.8860 | 0.8860 | 0.7943 |
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- | 0.5574 | 9.0 | 6183 | 0.5412 | 0.8879 | 0.8879 | 0.9396 |
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- | 0.553 | 10.0 | 6870 | 0.5276 | 0.8899 | 0.8899 | 0.8301 |
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- | 0.5371 | 11.0 | 7557 | 0.5341 | 0.8893 | 0.8893 | 0.9350 |
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- | 0.5302 | 12.0 | 8244 | 0.5236 | 0.8909 | 0.8909 | 0.8813 |
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- | 0.5245 | 13.0 | 8931 | 0.5153 | 0.8933 | 0.8933 | 0.8817 |
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- | 0.5165 | 14.0 | 9618 | 0.5138 | 0.8926 | 0.8926 | 0.9174 |
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- | 0.5122 | 15.0 | 10305 | 0.5144 | 0.8930 | 0.8930 | 0.8318 |
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- | 0.5007 | 16.0 | 10992 | 0.5007 | 0.8957 | 0.8957 | 0.9350 |
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- | 0.4954 | 17.0 | 11679 | 0.5041 | 0.8960 | 0.8960 | 0.9355 |
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- | 0.4894 | 18.0 | 12366 | 0.5000 | 0.8967 | 0.8967 | 0.7818 |
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- | 0.4851 | 19.0 | 13053 | 0.4915 | 0.8982 | 0.8982 | 0.9190 |
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- | 0.483 | 20.0 | 13740 | 0.4970 | 0.8962 | 0.8962 | 0.9359 |
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- | 0.4792 | 21.0 | 14427 | 0.4849 | 0.8971 | 0.8971 | 0.8458 |
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- | 0.4716 | 22.0 | 15114 | 0.4809 | 0.8990 | 0.8990 | 0.9367 |
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- | 0.4691 | 23.0 | 15801 | 0.4732 | 0.9006 | 0.9006 | 0.9478 |
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- | 0.4675 | 24.0 | 16488 | 0.4805 | 0.8989 | 0.8989 | 0.9412 |
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- | 0.4618 | 25.0 | 17175 | 0.4837 | 0.8997 | 0.8997 | 0.8373 |
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- | 0.4633 | 26.0 | 17862 | 0.4812 | 0.8993 | 0.8993 | 0.9483 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4811
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+ - Accuracy: 0.8991
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+ - F1: 0.8991
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+ - Bleu4: 0.9479
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
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+ | 1.143 | 1.0 | 687 | 0.6993 | 0.8563 | 0.8563 | 0.8531 |
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+ | 0.7772 | 2.0 | 1374 | 0.6482 | 0.8677 | 0.8677 | 0.9036 |
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+ | 0.6738 | 3.0 | 2061 | 0.6211 | 0.8734 | 0.8734 | 0.8189 |
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+ | 0.6544 | 4.0 | 2748 | 0.5942 | 0.8782 | 0.8782 | 0.9196 |
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+ | 0.6295 | 5.0 | 3435 | 0.5805 | 0.8815 | 0.8815 | 0.8079 |
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+ | 0.5966 | 6.0 | 4122 | 0.5609 | 0.8838 | 0.8838 | 0.8186 |
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+ | 0.5916 | 7.0 | 4809 | 0.5514 | 0.8870 | 0.8870 | 0.9103 |
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+ | 0.5732 | 8.0 | 5496 | 0.5492 | 0.8861 | 0.8861 | 0.8067 |
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+ | 0.5559 | 9.0 | 6183 | 0.5389 | 0.8881 | 0.8881 | 0.9353 |
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+ | 0.5511 | 10.0 | 6870 | 0.5257 | 0.8901 | 0.8901 | 0.9297 |
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+ | 0.5345 | 11.0 | 7557 | 0.5319 | 0.8905 | 0.8905 | 0.9363 |
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+ | 0.5287 | 12.0 | 8244 | 0.5220 | 0.8911 | 0.8911 | 0.8816 |
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+ | 0.5226 | 13.0 | 8931 | 0.5139 | 0.8938 | 0.8938 | 0.9438 |
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+ | 0.5147 | 14.0 | 9618 | 0.5124 | 0.8929 | 0.8929 | 0.9145 |
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+ | 0.511 | 15.0 | 10305 | 0.5131 | 0.8932 | 0.8932 | 0.8570 |
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+ | 0.4996 | 16.0 | 10992 | 0.4997 | 0.8964 | 0.8964 | 0.9287 |
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+ | 0.4949 | 17.0 | 11679 | 0.5033 | 0.8958 | 0.8958 | 0.9460 |
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+ | 0.4882 | 18.0 | 12366 | 0.5003 | 0.8971 | 0.8971 | 0.7739 |
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+ | 0.4837 | 19.0 | 13053 | 0.4914 | 0.8979 | 0.8979 | 0.9014 |
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+ | 0.4822 | 20.0 | 13740 | 0.4962 | 0.8963 | 0.8963 | 0.9330 |
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+ | 0.4778 | 21.0 | 14427 | 0.4844 | 0.8971 | 0.8971 | 0.8454 |
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+ | 0.4704 | 22.0 | 15114 | 0.4809 | 0.8988 | 0.8988 | 0.9274 |
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+ | 0.4676 | 23.0 | 15801 | 0.4735 | 0.9009 | 0.9009 | 0.9445 |
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+ | 0.4663 | 24.0 | 16488 | 0.4792 | 0.8990 | 0.8990 | 0.9001 |
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+ | 0.4605 | 25.0 | 17175 | 0.4826 | 0.8995 | 0.8995 | 0.8313 |
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+ | 0.4621 | 26.0 | 17862 | 0.4811 | 0.8991 | 0.8991 | 0.9479 |
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  ### Framework versions