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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: 0.1742
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- Precision: 0.9650
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- Recall: 0.9650
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- F1: 0.9648
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- Accuracy: 0.965
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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: 2e-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 | 0.2068 | 0.9550 | 0.9536 | 0.9537 | 0.9544 |
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| No log | 2.0 | 450 | 0.1497 | 0.9583 | 0.9585 | 0.9582 | 0.9583 |
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| 0.445 | 3.0 | 675 | 0.1408 | 0.9628 | 0.9631 | 0.9627 | 0.9628 |
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| 0.445 | 4.0 | 900 | 0.1484 | 0.9630 | 0.9630 | 0.9626 | 0.9628 |
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| 0.0585 | 5.0 | 1125 | 0.1487 | 0.9675 | 0.9680 | 0.9676 | 0.9678 |
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| 0.0585 | 6.0 | 1350 | 0.1538 | 0.9665 | 0.9670 | 0.9665 | 0.9667 |
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| 0.0242 | 7.0 | 1575 | 0.1666 | 0.9644 | 0.9645 | 0.9642 | 0.9644 |
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| 0.0242 | 8.0 | 1800 | 0.1709 | 0.9672 | 0.9673 | 0.9671 | 0.9672 |
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| 0.0111 | 9.0 | 2025 | 0.1707 | 0.9670 | 0.9672 | 0.9670 | 0.9672 |
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| 0.0111 | 10.0 | 2250 | 0.1742 | 0.9650 | 0.9650 | 0.9648 | 0.965 |
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### Framework versions
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