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End of training

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@@ -20,15 +20,15 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.5273
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- - Accuracy: 0.79
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- - Precision: {'precision': 0.7951807228915663}
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- - Recall: {'recall': 0.7252747252747253}
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- - F1: {'f1': 0.7586206896551725}
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- - Tp: 66
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- - Fp: 17
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- - Tn: 92
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- - Fn: 25
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  ## Model description
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@@ -57,6 +57,9 @@ The following hyperparameters were used during training:
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  ### Training results
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.5336
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+ - Accuracy: 0.765
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+ - Precision: {'precision': 0.7894736842105263}
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+ - Recall: {'recall': 0.6593406593406593}
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+ - F1: {'f1': 0.7185628742514969}
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+ - Tp: 60
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+ - Fp: 16
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+ - Tn: 93
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+ - Fn: 31
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Tp | Fp | Tn | Fn |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------------------------:|:------------------------------:|:--------------------------:|:--:|:--:|:--:|:--:|
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+ | 0.6134 | 2.0 | 18 | 0.5336 | 0.765 | {'precision': 0.7894736842105263} | {'recall': 0.6593406593406593} | {'f1': 0.7185628742514969} | 60 | 16 | 93 | 31 |
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  ### Framework versions