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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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- 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: 1.
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- train_batch_size: 4
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- eval_batch_size: 16
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- seed:
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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 | 60 | 0.
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| No log | 2.0 | 120 | 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: 0.5457
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- Accuracy: 0.8167
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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: 1.4354778271056715e-05
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- train_batch_size: 4
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- eval_batch_size: 16
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- seed: 7
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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: 4
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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 | 60 | 0.6582 | 0.5667 |
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| No log | 2.0 | 120 | 0.5764 | 0.8 |
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| No log | 3.0 | 180 | 0.5458 | 0.8167 |
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| No log | 4.0 | 240 | 0.5457 | 0.8167 |
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### Framework versions
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