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End of training

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  1. README.md +11 -11
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2248
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- - Rmse: 0.2928
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- - Accuracy: 0.9143
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- - Precision: 0.9299
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- - Recall: 0.9143
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- - F1: 0.9220
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:------:|
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- | 0.3656 | 1.0 | 1073 | 0.2248 | 0.2928 | 0.9143 | 0.9299 | 0.9143 | 0.9220 |
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- | 0.2432 | 2.0 | 2146 | 0.3105 | 0.2912 | 0.9152 | 0.9158 | 0.9328 | 0.9242 |
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- | 0.1649 | 3.0 | 3219 | 0.3818 | 0.2696 | 0.9273 | 0.9176 | 0.9546 | 0.9357 |
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- | 0.1075 | 4.0 | 4292 | 0.4398 | 0.2798 | 0.9217 | 0.9049 | 0.9597 | 0.9315 |
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- | 0.0788 | 5.0 | 5365 | 0.4655 | 0.2847 | 0.9189 | 0.9110 | 0.9462 | 0.9283 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2964
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+ - Rmse: 0.2828
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+ - Accuracy: 0.92
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+ - Precision: 0.9236
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+ - Recall: 0.9329
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+ - F1: 0.9282
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:------:|
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+ | 0.3798 | 1.0 | 1075 | 0.2964 | 0.2828 | 0.92 | 0.9236 | 0.9329 | 0.9282 |
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+ | 0.2507 | 2.0 | 2150 | 0.3791 | 0.2973 | 0.9116 | 0.8824 | 0.9698 | 0.9241 |
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+ | 0.1734 | 3.0 | 3225 | 0.3779 | 0.3080 | 0.9051 | 0.8847 | 0.9530 | 0.9176 |
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+ | 0.1157 | 4.0 | 4300 | 0.4796 | 0.2861 | 0.9181 | 0.9456 | 0.9044 | 0.9245 |
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+ | 0.0762 | 5.0 | 5375 | 0.4729 | 0.2762 | 0.9237 | 0.9341 | 0.9279 | 0.9310 |
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  ### Framework versions
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