End of training
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README.md
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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.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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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.
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| 0.0007 | 2.0 | 2002 | 0.
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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
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