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End of training

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  1. README.md +13 -6
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@@ -20,8 +20,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the swag dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8483
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- - Accuracy: 0.6567
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  ## Model description
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@@ -46,15 +46,22 @@ The following hyperparameters were used during training:
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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: 3
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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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- | 1.012 | 1.0 | 4597 | 0.8999 | 0.6374 |
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- | 0.9634 | 2.0 | 9194 | 0.8617 | 0.6512 |
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- | 0.955 | 3.0 | 13791 | 0.8483 | 0.6567 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the swag dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7733
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+ - Accuracy: 0.6858
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  ## Model description
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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: 10
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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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+ | 1.0103 | 1.0 | 4597 | 0.8978 | 0.6370 |
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+ | 0.9591 | 2.0 | 9194 | 0.8498 | 0.6568 |
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+ | 0.9401 | 3.0 | 13791 | 0.8270 | 0.6626 |
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+ | 0.9265 | 4.0 | 18388 | 0.8105 | 0.6713 |
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+ | 0.9202 | 5.0 | 22985 | 0.8001 | 0.6759 |
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+ | 0.8921 | 6.0 | 27582 | 0.7894 | 0.6790 |
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+ | 0.894 | 7.0 | 32179 | 0.7836 | 0.6823 |
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+ | 0.8695 | 8.0 | 36776 | 0.7803 | 0.6835 |
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+ | 0.8684 | 9.0 | 41373 | 0.7753 | 0.6845 |
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+ | 0.8696 | 10.0 | 45970 | 0.7733 | 0.6858 |
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  ### Framework versions