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--- |
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license: apache-2.0 |
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base_model: Salesforce/codet5-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CodeT5ForCodeSummary |
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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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# CodeT5ForCodeSummary |
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This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8891 |
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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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| 1.0295 | 1.0 | 750 | 0.7786 | |
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| 0.7481 | 2.0 | 1500 | 0.6092 | |
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| 0.6274 | 3.0 | 2250 | 0.5648 | |
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| 0.5562 | 4.0 | 3000 | 0.5395 | |
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| 0.479 | 5.0 | 3750 | 0.5328 | |
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| 0.4297 | 6.0 | 4500 | 0.5227 | |
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| 0.3519 | 7.0 | 5250 | 0.5505 | |
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| 0.3148 | 8.0 | 6000 | 0.5607 | |
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| 0.2535 | 9.0 | 6750 | 0.5909 | |
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| 0.2152 | 10.0 | 7500 | 0.6145 | |
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| 0.1801 | 11.0 | 8250 | 0.6458 | |
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| 0.1635 | 12.0 | 9000 | 0.6921 | |
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| 0.1474 | 13.0 | 9750 | 0.7425 | |
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| 0.1236 | 14.0 | 10500 | 0.7537 | |
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| 0.1075 | 15.0 | 11250 | 0.8059 | |
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| 0.1039 | 16.0 | 12000 | 0.8050 | |
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| 0.0888 | 17.0 | 12750 | 0.8645 | |
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| 0.0857 | 18.0 | 13500 | 0.8714 | |
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| 0.0763 | 19.0 | 14250 | 0.9016 | |
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| 0.048 | 20.0 | 15000 | 0.8891 | |
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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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