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End of training

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@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1117
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- - Precision: 0.9060
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- - Recall: 0.9201
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- - F1: 0.9130
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- - Accuracy: 0.9833
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0451 | 1.0 | 878 | 0.0398 | 0.9261 | 0.9378 | 0.9319 | 0.9892 |
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- | 0.0201 | 2.0 | 1756 | 0.0375 | 0.9440 | 0.9463 | 0.9451 | 0.9907 |
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- | 0.0118 | 3.0 | 2634 | 0.0364 | 0.9445 | 0.9518 | 0.9481 | 0.9913 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1125
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+ - Precision: 0.9051
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+ - Recall: 0.9192
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+ - F1: 0.9121
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+ - Accuracy: 0.9827
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0473 | 1.0 | 878 | 0.0407 | 0.9256 | 0.9390 | 0.9323 | 0.9891 |
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+ | 0.0199 | 2.0 | 1756 | 0.0386 | 0.9433 | 0.9481 | 0.9457 | 0.9909 |
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+ | 0.0126 | 3.0 | 2634 | 0.0367 | 0.9444 | 0.9527 | 0.9485 | 0.9914 |
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  ### Framework versions