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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 hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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 | 225 | 0.
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| No log | 2.0 | 450 | 0.
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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: 0.1825
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- Precision: 0.9668
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- Recall: 0.9672
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- F1: 0.9669
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- Accuracy: 0.9672
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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 | 225 | 0.1820 | 0.9527 | 0.9500 | 0.9506 | 0.9511 |
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| No log | 2.0 | 450 | 0.1582 | 0.9583 | 0.9584 | 0.9578 | 0.9583 |
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| 0.3586 | 3.0 | 675 | 0.1369 | 0.9677 | 0.9678 | 0.9676 | 0.9678 |
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| 0.3586 | 4.0 | 900 | 0.1371 | 0.9702 | 0.9706 | 0.9703 | 0.9706 |
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| 0.0493 | 5.0 | 1125 | 0.1567 | 0.9686 | 0.9690 | 0.9687 | 0.9689 |
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| 0.0493 | 6.0 | 1350 | 0.1622 | 0.9680 | 0.9685 | 0.9681 | 0.9683 |
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| 0.0181 | 7.0 | 1575 | 0.1684 | 0.9640 | 0.9643 | 0.9640 | 0.9644 |
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| 0.0181 | 8.0 | 1800 | 0.1717 | 0.9663 | 0.9666 | 0.9664 | 0.9667 |
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| 0.0051 | 9.0 | 2025 | 0.1791 | 0.9674 | 0.9678 | 0.9675 | 0.9678 |
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| 0.0051 | 10.0 | 2250 | 0.1825 | 0.9668 | 0.9672 | 0.9669 | 0.9672 |
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### Framework versions
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