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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 clinc_oos dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.9161
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 4.2938 | 1.0 | 318 | 3.2905 | 0.
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| 2.6346 | 2.0 | 636 | 1.8833 | 0.
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| 1.5554 | 3.0 | 954 | 1.1650 | 0.
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| 1.0189 | 4.0 | 1272 | 0.8636 | 0.9110 |
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| 0.8028 | 5.0 | 1590 | 0.
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### Framework versions
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- Transformers 4.
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- Pytorch 1.11.0
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- Datasets 2.0.0
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- Tokenizers 0.
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7796
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- Accuracy: 0.9161
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 4.2938 | 1.0 | 318 | 3.2905 | 0.7410 |
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| 2.6346 | 2.0 | 636 | 1.8833 | 0.8326 |
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| 1.5554 | 3.0 | 954 | 1.1650 | 0.8926 |
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| 1.0189 | 4.0 | 1272 | 0.8636 | 0.9110 |
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| 0.8028 | 5.0 | 1590 | 0.7796 | 0.9161 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0
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- Datasets 2.0.0
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- Tokenizers 0.12.1
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