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End of training

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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 [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0011
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- - Precision: 0.9996
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- - Recall: 0.9998
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- - F1: 0.9997
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- - Accuracy: 0.9998
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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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- | 0.0015 | 1.0 | 1001 | 0.0012 | 0.9996 | 0.9998 | 0.9997 | 0.9998 |
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- | 0.0007 | 2.0 | 2002 | 0.0011 | 0.9996 | 0.9998 | 0.9997 | 0.9998 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0005
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+ - Precision: 0.9998
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+ - Recall: 0.9999
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+ - F1: 0.9998
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+ - Accuracy: 0.9999
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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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+ | 0.0015 | 1.0 | 1001 | 0.0009 | 0.9996 | 0.9998 | 0.9997 | 0.9998 |
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+ | 0.0007 | 2.0 | 2002 | 0.0005 | 0.9998 | 0.9999 | 0.9998 | 0.9999 |
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  ### Framework versions