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Training complete

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@@ -20,11 +20,11 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0616
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- - Precision: 0.9350
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- - Recall: 0.9510
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- - F1: 0.9429
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- - Accuracy: 0.9866
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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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- | 0.073 | 1.0 | 1756 | 0.0665 | 0.9079 | 0.9327 | 0.9201 | 0.9808 |
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- | 0.0333 | 2.0 | 3512 | 0.0639 | 0.9359 | 0.9488 | 0.9423 | 0.9862 |
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- | 0.0211 | 3.0 | 5268 | 0.0616 | 0.9350 | 0.9510 | 0.9429 | 0.9866 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0610
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+ - Precision: 0.9355
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+ - Recall: 0.9522
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+ - F1: 0.9438
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+ - Accuracy: 0.9868
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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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+ | 0.0744 | 1.0 | 1756 | 0.0636 | 0.9123 | 0.9362 | 0.9241 | 0.9829 |
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+ | 0.035 | 2.0 | 3512 | 0.0633 | 0.9358 | 0.9492 | 0.9424 | 0.9862 |
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+ | 0.0211 | 3.0 | 5268 | 0.0610 | 0.9355 | 0.9522 | 0.9438 | 0.9868 |
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  ### Framework versions