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--- |
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license: bsd-3-clause |
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base_model: Salesforce/codet5p-770m |
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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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- precision |
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- recall |
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model-index: |
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- name: Salesforce-codet5p-770m-finetuned-defect-detection |
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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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# Salesforce-codet5p-770m-finetuned-defect-detection |
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This model is a fine-tuned version of [Salesforce/codet5p-770m](https://huggingface.co/Salesforce/codet5p-770m) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5699 |
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- Accuracy: 0.7505 |
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- Roc Auc: 0.7509 |
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- Precision: 0.7343 |
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- Recall: 0.7667 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 4711 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 5 |
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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 | Roc Auc | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:---------:|:------:| |
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| 0.6826 | 1.0 | 996 | 0.5735 | 0.6923 | 0.6925 | 0.6791 | 0.7014 | |
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| 0.528 | 2.0 | 1993 | 0.4960 | 0.7191 | 0.7211 | 0.6785 | 0.8078 | |
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| 0.4308 | 3.0 | 2989 | 0.4821 | 0.7415 | 0.7419 | 0.7234 | 0.7621 | |
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| 0.3495 | 4.0 | 3986 | 0.5010 | 0.7455 | 0.7463 | 0.7217 | 0.7795 | |
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| 0.2731 | 5.0 | 4980 | 0.5699 | 0.7505 | 0.7509 | 0.7343 | 0.7667 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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