| --- |
| license: apache-2.0 |
| base_model: neuralsentry/distilbert-git-commits-mlm |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: vulnfixClassification-DistilBERT-DCMB |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # vulnfixClassification-DistilBERT-DCMB |
|
|
| 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. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1769 |
| - Accuracy: 0.9713 |
| - Precision: 0.9778 |
| - Recall: 0.9667 |
| - F1: 0.9722 |
| - Roc Auc: 0.9715 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 256 |
| - eval_batch_size: 256 |
| - seed: 420 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
| | 0.2594 | 1.0 | 110 | 0.1452 | 0.9520 | 0.9672 | 0.9395 | 0.9532 | 0.9525 | |
| | 0.0966 | 2.0 | 220 | 0.1103 | 0.9644 | 0.9714 | 0.9599 | 0.9656 | 0.9646 | |
| | 0.0499 | 3.0 | 330 | 0.1193 | 0.9640 | 0.9679 | 0.9626 | 0.9653 | 0.9641 | |
| | 0.0251 | 4.0 | 440 | 0.1289 | 0.9623 | 0.9577 | 0.9703 | 0.9640 | 0.9619 | |
| | 0.0132 | 5.0 | 550 | 0.1495 | 0.9660 | 0.9660 | 0.9687 | 0.9673 | 0.9659 | |
| | 0.0086 | 6.0 | 660 | 0.1759 | 0.9684 | 0.9830 | 0.9558 | 0.9692 | 0.9689 | |
| | 0.0054 | 7.0 | 770 | 0.1568 | 0.9700 | 0.9788 | 0.9632 | 0.9709 | 0.9703 | |
| | 0.0023 | 8.0 | 880 | 0.1775 | 0.9707 | 0.9754 | 0.9681 | 0.9717 | 0.9708 | |
| | 0.0023 | 9.0 | 990 | 0.1752 | 0.9710 | 0.9794 | 0.9646 | 0.9719 | 0.9713 | |
| | 0.0011 | 10.0 | 1100 | 0.1769 | 0.9713 | 0.9778 | 0.9667 | 0.9722 | 0.9715 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.2 |
| - Tokenizers 0.13.3 |
|
|
