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fine-tuned-NLI-idk-mrc-nli-keep-with-xlm-roberta-large

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xlm-roberta
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update model card README.md

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@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1080
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- - Accuracy: 0.9830
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- - F1: 0.9830
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.3752 | 0.49 | 39 | 0.6866 | 0.5183 | 0.3749 |
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- | 0.7598 | 0.99 | 78 | 0.2098 | 0.9332 | 0.9331 |
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- | 0.3228 | 1.49 | 117 | 0.1063 | 0.9634 | 0.9633 |
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- | 0.1461 | 1.99 | 156 | 0.0813 | 0.9725 | 0.9725 |
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- | 0.1461 | 2.49 | 195 | 0.0719 | 0.9777 | 0.9777 |
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- | 0.1154 | 2.99 | 234 | 0.0704 | 0.9777 | 0.9777 |
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- | 0.0881 | 3.49 | 273 | 0.0625 | 0.9830 | 0.9830 |
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- | 0.0551 | 3.99 | 312 | 0.0738 | 0.9817 | 0.9817 |
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- | 0.0474 | 4.49 | 351 | 0.0779 | 0.9843 | 0.9843 |
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- | 0.0474 | 4.99 | 390 | 0.0860 | 0.9791 | 0.9791 |
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- | 0.0425 | 5.49 | 429 | 0.0801 | 0.9856 | 0.9856 |
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- | 0.0316 | 5.99 | 468 | 0.0947 | 0.9817 | 0.9817 |
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- | 0.0185 | 6.49 | 507 | 0.0953 | 0.9856 | 0.9856 |
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- | 0.0185 | 6.99 | 546 | 0.0979 | 0.9817 | 0.9817 |
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- | 0.0264 | 7.49 | 585 | 0.0923 | 0.9830 | 0.9830 |
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- | 0.0156 | 7.99 | 624 | 0.1080 | 0.9830 | 0.9830 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1224
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+ - Accuracy: 0.9751
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+ - F1: 0.9751
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.3634 | 0.49 | 39 | 0.6900 | 0.5052 | 0.3515 |
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+ | 0.7309 | 0.99 | 78 | 0.2791 | 0.9202 | 0.9202 |
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+ | 0.4815 | 1.49 | 117 | 0.0854 | 0.9738 | 0.9738 |
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+ | 0.145 | 1.99 | 156 | 0.0903 | 0.9699 | 0.9699 |
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+ | 0.145 | 2.49 | 195 | 0.0931 | 0.9738 | 0.9738 |
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+ | 0.0937 | 2.99 | 234 | 0.0875 | 0.9751 | 0.9751 |
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+ | 0.0752 | 3.49 | 273 | 0.1164 | 0.9738 | 0.9738 |
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+ | 0.0538 | 3.99 | 312 | 0.1386 | 0.9673 | 0.9673 |
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+ | 0.0379 | 4.49 | 351 | 0.0893 | 0.9791 | 0.9791 |
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+ | 0.0379 | 4.99 | 390 | 0.1002 | 0.9777 | 0.9777 |
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+ | 0.0397 | 5.49 | 429 | 0.1214 | 0.9764 | 0.9764 |
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+ | 0.031 | 5.99 | 468 | 0.1224 | 0.9751 | 0.9751 |
 
 
 
 
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  ### Framework versions