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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: 0.4811
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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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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - seed: 42
 
 
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 50
 
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  ### Training results
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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
 
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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: 0.5888
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+ - Accuracy: 0.8783
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+ - F1: 0.8783
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+ - Bleu4: 0.8598
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 42
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+ - eval_batch_size: 42
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  - seed: 42
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+ - gradient_accumulation_steps: 3
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+ - total_train_batch_size: 126
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 50
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+ - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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+ | No log | 1.0 | 236 | 0.8706 | 0.8253 | 0.8253 | 0.7764 |
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+ | No log | 2.0 | 472 | 0.7296 | 0.8503 | 0.8503 | 0.8287 |
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+ | 1.0825 | 3.0 | 708 | 0.6826 | 0.8594 | 0.8594 | 0.8123 |
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+ | 1.0825 | 4.0 | 944 | 0.6655 | 0.8645 | 0.8645 | 0.8480 |
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+ | 0.755 | 5.0 | 1180 | 0.6317 | 0.8696 | 0.8696 | 0.9028 |
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+ | 0.755 | 6.0 | 1416 | 0.6333 | 0.8699 | 0.8699 | 0.8870 |
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+ | 0.6948 | 7.0 | 1652 | 0.6147 | 0.8738 | 0.8738 | 0.9187 |
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+ | 0.6948 | 8.0 | 1888 | 0.6110 | 0.8738 | 0.8738 | 0.8080 |
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+ | 0.6633 | 9.0 | 2124 | 0.5987 | 0.8770 | 0.8770 | 0.8903 |
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+ | 0.6633 | 10.0 | 2360 | 0.5888 | 0.8783 | 0.8783 | 0.8598 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions