End of training
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README.md
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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.
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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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| No log | 1.0 | 55 | 0.
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| No log | 2.0 | 110 | 0.
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| No log | 3.0 | 165 | 0.
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| No log | 4.0 | 220 | 0.
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| No log | 5.0 | 275 | 0.
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### Framework versions
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- Transformers 4.33.
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.
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- Tokenizers 0.13.3
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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: 0.0834
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- Precision: 0.5329
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- Recall: 0.6129
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- F1: 0.5701
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- Accuracy: 0.9689
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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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| No log | 1.0 | 55 | 0.1363 | 0.2460 | 0.2987 | 0.2698 | 0.9436 |
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| No log | 2.0 | 110 | 0.0926 | 0.3943 | 0.4656 | 0.4270 | 0.9636 |
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| No log | 3.0 | 165 | 0.0823 | 0.4937 | 0.6059 | 0.5441 | 0.9683 |
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| No log | 4.0 | 220 | 0.0802 | 0.5187 | 0.5849 | 0.5498 | 0.9696 |
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| No log | 5.0 | 275 | 0.0834 | 0.5329 | 0.6129 | 0.5701 | 0.9689 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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