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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0080
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- - Accuracy: 0.7264
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  ## Model description
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@@ -43,13 +43,32 @@ The following hyperparameters were used during training:
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  - distributed_type: multi-GPU
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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: 1
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.8103 | 1.0 | 2355 | 1.0080 | 0.7264 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.2660
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+ - Accuracy: 0.7504
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  ## Model description
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  - distributed_type: multi-GPU
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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: 20
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 1.2373 | 1.0 | 2355 | 1.1927 | 0.6802 |
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+ | 0.9192 | 2.0 | 4710 | 1.0538 | 0.7118 |
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+ | 0.6782 | 3.0 | 7065 | 0.9921 | 0.7288 |
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+ | 0.5687 | 4.0 | 9420 | 1.0542 | 0.7421 |
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+ | 0.4598 | 5.0 | 11775 | 1.2043 | 0.7384 |
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+ | 0.3557 | 6.0 | 14130 | 1.2833 | 0.7459 |
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+ | 0.3126 | 7.0 | 16485 | 1.4286 | 0.7459 |
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+ | 0.2541 | 8.0 | 18840 | 1.5076 | 0.7419 |
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+ | 0.1948 | 9.0 | 21195 | 1.6771 | 0.7371 |
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+ | 0.1576 | 10.0 | 23550 | 1.8419 | 0.7429 |
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+ | 0.1071 | 11.0 | 25905 | 1.9164 | 0.7467 |
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+ | 0.0977 | 12.0 | 28260 | 1.9773 | 0.7466 |
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+ | 0.0652 | 13.0 | 30615 | 2.0582 | 0.7486 |
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+ | 0.0752 | 14.0 | 32970 | 2.1108 | 0.7482 |
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+ | 0.0594 | 15.0 | 35325 | 2.1406 | 0.7492 |
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+ | 0.049 | 16.0 | 37680 | 2.1958 | 0.7485 |
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+ | 0.0267 | 17.0 | 40035 | 2.1858 | 0.7499 |
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+ | 0.0339 | 18.0 | 42390 | 2.2162 | 0.7503 |
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+ | 0.0137 | 19.0 | 44745 | 2.2699 | 0.7503 |
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+ | 0.0083 | 20.0 | 47100 | 2.2660 | 0.7504 |
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  ### Framework versions