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PRE-xlnet-large-cased-finetuned-augmentation

Text Classification
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xlnet
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  2. model.safetensors +1 -1
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-large-cased](https://huggingface.co/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: 0.2352
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- - F1: 0.7259
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- - Roc Auc: 0.8541
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- - Accuracy: 0.7651
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  ## Model description
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@@ -54,17 +54,22 @@ 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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- | 0.3178 | 1.0 | 389 | 0.2986 | 0.1377 | 0.5618 | 0.5450 |
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- | 0.2612 | 2.0 | 778 | 0.2526 | 0.4274 | 0.6840 | 0.6403 |
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- | 0.227 | 3.0 | 1167 | 0.2321 | 0.5028 | 0.7297 | 0.6802 |
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- | 0.2361 | 4.0 | 1556 | 0.2019 | 0.5561 | 0.7528 | 0.7124 |
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- | 0.1625 | 5.0 | 1945 | 0.1900 | 0.6209 | 0.7815 | 0.7381 |
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- | 0.1104 | 6.0 | 2334 | 0.2038 | 0.6265 | 0.7640 | 0.7523 |
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- | 0.0932 | 7.0 | 2723 | 0.2238 | 0.6613 | 0.7915 | 0.7561 |
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- | 0.076 | 8.0 | 3112 | 0.2352 | 0.7259 | 0.8541 | 0.7651 |
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- | 0.0495 | 9.0 | 3501 | 0.2470 | 0.7151 | 0.8311 | 0.7716 |
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- | 0.0349 | 10.0 | 3890 | 0.2762 | 0.7032 | 0.8280 | 0.7664 |
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- | 0.025 | 11.0 | 4279 | 0.3078 | 0.7066 | 0.8268 | 0.7793 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/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: 0.3555
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+ - F1: 0.7303
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+ - Roc Auc: 0.8500
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+ - Accuracy: 0.7773
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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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+ | 0.34 | 1.0 | 389 | 0.3108 | 0.1424 | 0.5799 | 0.5386 |
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+ | 0.2957 | 2.0 | 778 | 0.2733 | 0.3070 | 0.6420 | 0.5637 |
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+ | 0.2697 | 3.0 | 1167 | 0.2241 | 0.4578 | 0.6995 | 0.6525 |
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+ | 0.2248 | 4.0 | 1556 | 0.1944 | 0.5903 | 0.7595 | 0.7239 |
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+ | 0.1689 | 5.0 | 1945 | 0.1793 | 0.6729 | 0.8127 | 0.7561 |
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+ | 0.1052 | 6.0 | 2334 | 0.1961 | 0.6682 | 0.7962 | 0.7600 |
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+ | 0.0964 | 7.0 | 2723 | 0.2035 | 0.6728 | 0.7989 | 0.7613 |
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+ | 0.0885 | 8.0 | 3112 | 0.2315 | 0.7185 | 0.8404 | 0.7593 |
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+ | 0.0497 | 9.0 | 3501 | 0.2608 | 0.7264 | 0.8476 | 0.7593 |
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+ | 0.0411 | 10.0 | 3890 | 0.2688 | 0.7212 | 0.8363 | 0.7831 |
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+ | 0.0182 | 11.0 | 4279 | 0.3081 | 0.7300 | 0.8558 | 0.7709 |
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+ | 0.0186 | 12.0 | 4668 | 0.3179 | 0.7216 | 0.8452 | 0.7754 |
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+ | 0.0131 | 13.0 | 5057 | 0.3312 | 0.7328 | 0.8488 | 0.7773 |
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+ | 0.0069 | 14.0 | 5446 | 0.3464 | 0.7272 | 0.8472 | 0.7716 |
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+ | 0.0069 | 15.0 | 5835 | 0.3522 | 0.7316 | 0.8481 | 0.7793 |
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+ | 0.0027 | 16.0 | 6224 | 0.3555 | 0.7303 | 0.8500 | 0.7773 |
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  ### Framework versions
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