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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: CodeBERTa-commit-message-autocomplete |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# CodeBERTa-commit-message-autocomplete |
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This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7327 |
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- Accuracy: 0.6612 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 42 |
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- eval_batch_size: 42 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 126 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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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 | 325 | 2.6847 | 0.5185 | |
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| 3.367 | 2.0 | 650 | 2.4055 | 0.5573 | |
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| 3.367 | 3.0 | 975 | 2.2742 | 0.5766 | |
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| 2.4354 | 4.0 | 1300 | 2.1065 | 0.6057 | |
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| 2.1925 | 5.0 | 1625 | 2.0764 | 0.6053 | |
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| 2.1925 | 6.0 | 1950 | 2.0169 | 0.6172 | |
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| 2.0217 | 7.0 | 2275 | 1.9270 | 0.6209 | |
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| 1.9424 | 8.0 | 2600 | 1.9326 | 0.6318 | |
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| 1.9424 | 9.0 | 2925 | 1.8849 | 0.6321 | |
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| 1.8485 | 10.0 | 3250 | 1.8834 | 0.6422 | |
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| 1.7847 | 11.0 | 3575 | 1.8213 | 0.6481 | |
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| 1.7847 | 12.0 | 3900 | 1.8674 | 0.6374 | |
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| 1.719 | 13.0 | 4225 | 1.7865 | 0.6473 | |
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| 1.6847 | 14.0 | 4550 | 1.8005 | 0.6523 | |
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| 1.6847 | 15.0 | 4875 | 1.8039 | 0.6516 | |
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| 1.6274 | 16.0 | 5200 | 1.7457 | 0.6617 | |
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| 1.5833 | 17.0 | 5525 | 1.7456 | 0.6526 | |
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| 1.5833 | 18.0 | 5850 | 1.7314 | 0.6626 | |
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| 1.5485 | 19.0 | 6175 | 1.7605 | 0.6590 | |
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| 1.5448 | 20.0 | 6500 | 1.7694 | 0.6592 | |
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| 1.5448 | 21.0 | 6825 | 1.7327 | 0.6612 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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