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--- |
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base_model: microsoft/codebert-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CodeBertForCodeSummary |
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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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# CodeBertForCodeSummary |
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This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3533 |
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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: 5e-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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- lr_scheduler_warmup_steps: 14400.0 |
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- num_epochs: 20 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 5.051 | 1.0 | 750 | 4.6658 | |
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| 3.7963 | 2.0 | 1500 | 3.6102 | |
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| 3.2207 | 3.0 | 2250 | 2.9757 | |
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| 2.7558 | 4.0 | 3000 | 2.5950 | |
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| 2.4409 | 5.0 | 3750 | 2.3054 | |
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| 2.188 | 6.0 | 4500 | 2.0653 | |
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| 1.9616 | 7.0 | 5250 | 1.8439 | |
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| 1.7515 | 8.0 | 6000 | 1.6953 | |
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| 1.6408 | 9.0 | 6750 | 1.5872 | |
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| 1.4843 | 10.0 | 7500 | 1.5153 | |
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| 1.4453 | 11.0 | 8250 | 1.4662 | |
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| 1.3443 | 12.0 | 9000 | 1.4222 | |
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| 1.2826 | 13.0 | 9750 | 1.3990 | |
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| 1.2005 | 14.0 | 10500 | 1.3829 | |
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| 1.1559 | 15.0 | 11250 | 1.3678 | |
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| 1.0938 | 16.0 | 12000 | 1.3504 | |
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| 1.0285 | 17.0 | 12750 | 1.3493 | |
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| 0.9802 | 18.0 | 13500 | 1.3568 | |
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| 0.9333 | 19.0 | 14250 | 1.3549 | |
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| 0.8453 | 20.0 | 15000 | 1.3533 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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