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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 glue 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: 0.9025
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| No log | 1.0 | 132 | 0.
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| No log | 2.0 | 264 | 0.
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| No log | 3.0 | 396 | 0.
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### Framework versions
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- Transformers 4.
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- Pytorch 1.12.1+cu116
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- Datasets 2.
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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 glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2817
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- Accuracy: 0.9025
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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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| No log | 1.0 | 132 | 0.2534 | 0.8956 |
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| No log | 2.0 | 264 | 0.2679 | 0.9002 |
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| No log | 3.0 | 396 | 0.2817 | 0.9025 |
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| 0.1896 | 4.0 | 528 | 0.2933 | 0.9002 |
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| 0.1896 | 5.0 | 660 | 0.3008 | 0.9002 |
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### Framework versions
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- Transformers 4.23.1
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- Pytorch 1.12.1+cu116
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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