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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:
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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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- 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 | F1
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| 0.0011 | 5.0 | 6865 | 0.0002 | 0.0215 | 0.0215 | 0.1640 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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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: 14.6482
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- Accuracy: 0.0
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- F1: 0.0
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- Bleu4: 0.0592
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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: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:------:|
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| No log | 1.0 | 1 | 16.4835 | 0.0 | 0.0 | 0.1118 |
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| No log | 2.0 | 2 | 15.8217 | 0.0 | 0.0 | 0.0940 |
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| No log | 3.0 | 3 | 15.2096 | 0.0 | 0.0 | 0.0648 |
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| No log | 4.0 | 4 | 14.6482 | 0.0 | 0.0 | 0.0592 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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