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update model card README.md

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  1. README.md +13 -13
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@@ -15,8 +15,8 @@ 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: 0.5015
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- - Accuracy: 0.8968
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  ## Model description
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@@ -35,7 +35,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2.8817627388443496e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -47,16 +47,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.7432 | 1.0 | 2440 | 0.6306 | 0.8726 |
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- | 0.6595 | 2.0 | 4880 | 0.5858 | 0.8803 |
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- | 0.6211 | 3.0 | 7320 | 0.5694 | 0.8834 |
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- | 0.5869 | 4.0 | 9760 | 0.5399 | 0.8887 |
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- | 0.551 | 5.0 | 12200 | 0.5253 | 0.8920 |
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- | 0.5417 | 6.0 | 14640 | 0.5185 | 0.8930 |
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- | 0.5388 | 7.0 | 17080 | 0.5180 | 0.8935 |
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- | 0.5149 | 8.0 | 19520 | 0.5064 | 0.8955 |
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- | 0.5157 | 9.0 | 21960 | 0.5047 | 0.8954 |
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- | 0.5143 | 10.0 | 24400 | 0.5015 | 0.8968 |
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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: 0.5238
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+ - Accuracy: 0.8925
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1.7636624471082695e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.7781 | 1.0 | 2440 | 0.6600 | 0.8638 |
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+ | 0.6881 | 2.0 | 4880 | 0.6070 | 0.8760 |
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+ | 0.6493 | 3.0 | 7320 | 0.5903 | 0.8794 |
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+ | 0.6173 | 4.0 | 9760 | 0.5597 | 0.8849 |
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+ | 0.5803 | 5.0 | 12200 | 0.5430 | 0.8888 |
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+ | 0.5735 | 6.0 | 14640 | 0.5380 | 0.8891 |
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+ | 0.575 | 7.0 | 17080 | 0.5392 | 0.8892 |
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+ | 0.5517 | 8.0 | 19520 | 0.5279 | 0.8912 |
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+ | 0.5552 | 9.0 | 21960 | 0.5283 | 0.8912 |
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+ | 0.5542 | 10.0 | 24400 | 0.5238 | 0.8925 |
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  ### Framework versions