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README.md
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) 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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- Accuracy: 0.
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 69 | 0.
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| No log | 2.0 | 138 | 0.
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### Framework versions
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- Transformers 4.
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0673
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- Accuracy: 0.9914
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 69 | 0.2353 | 0.9741 |
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| No log | 2.0 | 138 | 0.0894 | 0.9741 |
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| No log | 3.0 | 207 | 0.0673 | 0.9914 |
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### Framework versions
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- Transformers 4.29.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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