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UIT-xlnet-large-cased-finetuned

Text Classification
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xlnet
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  1. README.md +24 -24
  2. model.safetensors +1 -1
  3. tokenizer.json +16 -2
README.md CHANGED
@@ -19,10 +19,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7374
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- - F1: 0.7190
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- - Roc Auc: 0.7861
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- - Accuracy: 0.4368
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  ## Model description
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@@ -54,26 +54,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | 0.6144 | 1.0 | 139 | 0.5899 | 0.0858 | 0.5045 | 0.1245 |
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- | 0.55 | 2.0 | 278 | 0.5547 | 0.2409 | 0.5430 | 0.1625 |
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- | 0.5049 | 3.0 | 417 | 0.4514 | 0.5298 | 0.6834 | 0.3574 |
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- | 0.4 | 4.0 | 556 | 0.4586 | 0.5030 | 0.6732 | 0.3538 |
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- | 0.3206 | 5.0 | 695 | 0.4345 | 0.6371 | 0.7279 | 0.3827 |
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- | 0.2969 | 6.0 | 834 | 0.4264 | 0.6807 | 0.7627 | 0.4170 |
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- | 0.2036 | 7.0 | 973 | 0.4564 | 0.6871 | 0.7633 | 0.4495 |
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- | 0.1986 | 8.0 | 1112 | 0.4918 | 0.6930 | 0.7632 | 0.4170 |
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- | 0.1437 | 9.0 | 1251 | 0.5499 | 0.7021 | 0.7861 | 0.3953 |
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- | 0.1066 | 10.0 | 1390 | 0.5774 | 0.7028 | 0.7725 | 0.4224 |
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- | 0.0674 | 11.0 | 1529 | 0.6038 | 0.7145 | 0.7824 | 0.4585 |
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- | 0.038 | 12.0 | 1668 | 0.6528 | 0.7020 | 0.7797 | 0.4458 |
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- | 0.0341 | 13.0 | 1807 | 0.6681 | 0.7092 | 0.7781 | 0.4477 |
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- | 0.0308 | 14.0 | 1946 | 0.6986 | 0.7085 | 0.7796 | 0.4260 |
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- | 0.0109 | 15.0 | 2085 | 0.7297 | 0.7087 | 0.7796 | 0.4332 |
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- | 0.0224 | 16.0 | 2224 | 0.7307 | 0.7156 | 0.7838 | 0.4440 |
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- | 0.0097 | 17.0 | 2363 | 0.7358 | 0.7155 | 0.7816 | 0.4440 |
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- | 0.0103 | 18.0 | 2502 | 0.7374 | 0.7190 | 0.7861 | 0.4368 |
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- | 0.0116 | 19.0 | 2641 | 0.7381 | 0.7150 | 0.7829 | 0.4368 |
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- | 0.0077 | 20.0 | 2780 | 0.7383 | 0.7130 | 0.7817 | 0.4350 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7544
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+ - F1: 0.7191
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+ - Roc Auc: 0.7866
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+ - Accuracy: 0.4765
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.6047 | 1.0 | 139 | 0.5968 | 0.1435 | 0.5 | 0.1300 |
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+ | 0.551 | 2.0 | 278 | 0.5818 | 0.1393 | 0.4981 | 0.1318 |
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+ | 0.549 | 3.0 | 417 | 0.5342 | 0.3274 | 0.5764 | 0.1931 |
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+ | 0.4438 | 4.0 | 556 | 0.5083 | 0.4820 | 0.6362 | 0.3105 |
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+ | 0.3647 | 5.0 | 695 | 0.4219 | 0.6477 | 0.7325 | 0.4043 |
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+ | 0.3083 | 6.0 | 834 | 0.4281 | 0.6663 | 0.7489 | 0.4079 |
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+ | 0.2307 | 7.0 | 973 | 0.4171 | 0.6962 | 0.7756 | 0.4404 |
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+ | 0.1962 | 8.0 | 1112 | 0.4786 | 0.6985 | 0.7706 | 0.4242 |
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+ | 0.1404 | 9.0 | 1251 | 0.5594 | 0.6960 | 0.7769 | 0.4152 |
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+ | 0.0739 | 10.0 | 1390 | 0.5989 | 0.7033 | 0.7768 | 0.4567 |
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+ | 0.0604 | 11.0 | 1529 | 0.6251 | 0.7028 | 0.7758 | 0.4603 |
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+ | 0.0357 | 12.0 | 1668 | 0.6687 | 0.7077 | 0.7822 | 0.4531 |
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+ | 0.0198 | 13.0 | 1807 | 0.7097 | 0.6973 | 0.7701 | 0.4422 |
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+ | 0.0339 | 14.0 | 1946 | 0.7104 | 0.6992 | 0.7732 | 0.4531 |
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+ | 0.0228 | 15.0 | 2085 | 0.7339 | 0.7150 | 0.7842 | 0.4765 |
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+ | 0.0147 | 16.0 | 2224 | 0.7418 | 0.6941 | 0.7734 | 0.4711 |
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+ | 0.0078 | 17.0 | 2363 | 0.7514 | 0.7130 | 0.7833 | 0.4765 |
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+ | 0.0069 | 18.0 | 2502 | 0.7544 | 0.7191 | 0.7866 | 0.4765 |
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+ | 0.0067 | 19.0 | 2641 | 0.7570 | 0.7146 | 0.7845 | 0.4693 |
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+ | 0.005 | 20.0 | 2780 | 0.7579 | 0.7134 | 0.7834 | 0.4729 |
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  ### Framework versions
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