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README.md
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This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-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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- F1: 0.
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- Bleu4: 0.
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## Model description
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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:
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- eval_batch_size:
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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| 0.
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| 0.0086 | 5.0 | 3435 | 0.0068 | 0.0126 | 0.0126 | 0.0363 |
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### Framework versions
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This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0001
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- Accuracy: 0.0211
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- F1: 0.0211
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- Bleu4: 0.1608
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## Model description
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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: 16
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- eval_batch_size: 16
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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| 0.0908 | 1.0 | 1373 | 0.0184 | 0.0257 | 0.0257 | 0.1931 |
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| 0.0169 | 2.0 | 2746 | 0.0007 | 0.0207 | 0.0207 | 0.1567 |
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| 0.0033 | 3.0 | 4119 | 0.0058 | 0.0138 | 0.0138 | 0.0759 |
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| 0.0025 | 4.0 | 5492 | 0.0001 | 0.0211 | 0.0211 | 0.1608 |
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### Framework versions
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