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--- |
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license: apache-2.0 |
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base_model: neuralsentry/distilbert-git-commits-mlm |
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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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- f1 |
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model-index: |
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- name: vulnfixClassification-DistilBERT-DCMB |
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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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# vulnfixClassification-DistilBERT-DCMB |
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This model is a fine-tuned version of [neuralsentry/distilbert-git-commits-mlm](https://huggingface.co/neuralsentry/distilbert-git-commits-mlm) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1769 |
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- Accuracy: 0.9713 |
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- Precision: 0.9778 |
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- Recall: 0.9667 |
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- F1: 0.9722 |
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- Roc Auc: 0.9715 |
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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: 0.0001 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 420 |
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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: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
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| 0.2594 | 1.0 | 110 | 0.1452 | 0.9520 | 0.9672 | 0.9395 | 0.9532 | 0.9525 | |
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| 0.0966 | 2.0 | 220 | 0.1103 | 0.9644 | 0.9714 | 0.9599 | 0.9656 | 0.9646 | |
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| 0.0499 | 3.0 | 330 | 0.1193 | 0.9640 | 0.9679 | 0.9626 | 0.9653 | 0.9641 | |
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| 0.0251 | 4.0 | 440 | 0.1289 | 0.9623 | 0.9577 | 0.9703 | 0.9640 | 0.9619 | |
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| 0.0132 | 5.0 | 550 | 0.1495 | 0.9660 | 0.9660 | 0.9687 | 0.9673 | 0.9659 | |
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| 0.0086 | 6.0 | 660 | 0.1759 | 0.9684 | 0.9830 | 0.9558 | 0.9692 | 0.9689 | |
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| 0.0054 | 7.0 | 770 | 0.1568 | 0.9700 | 0.9788 | 0.9632 | 0.9709 | 0.9703 | |
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| 0.0023 | 8.0 | 880 | 0.1775 | 0.9707 | 0.9754 | 0.9681 | 0.9717 | 0.9708 | |
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| 0.0023 | 9.0 | 990 | 0.1752 | 0.9710 | 0.9794 | 0.9646 | 0.9719 | 0.9713 | |
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| 0.0011 | 10.0 | 1100 | 0.1769 | 0.9713 | 0.9778 | 0.9667 | 0.9722 | 0.9715 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
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