| --- |
| library_name: transformers |
| base_model: microsoft/codebert-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| model-index: |
| - name: Vulnerability_Detection_Using_CodeBERT |
| 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. --> |
|
|
| # Vulnerability_Detection_Using_CodeBERT |
| |
| This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0740 |
| - Accuracy: 1.0 |
| - Auc: 1.0 |
| - Precision: 1.0 |
| |
| ## 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: 0.0002 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:| |
| | 0.2971 | 1.0 | 26 | 0.1815 | 0.925 | 1.0 | 0.81 | |
| | 0.2407 | 2.0 | 52 | 0.1349 | 0.981 | 1.0 | 0.944 | |
| | 0.2619 | 3.0 | 78 | 0.1668 | 0.887 | 1.0 | 0.739 | |
| | 0.2207 | 4.0 | 104 | 0.1081 | 1.0 | 1.0 | 1.0 | |
| | 0.1543 | 5.0 | 130 | 0.1037 | 0.981 | 1.0 | 1.0 | |
| | 0.1428 | 6.0 | 156 | 0.0974 | 0.981 | 1.0 | 0.944 | |
| | 0.1598 | 7.0 | 182 | 0.0916 | 0.981 | 1.0 | 1.0 | |
| | 0.1324 | 8.0 | 208 | 0.1024 | 0.981 | 1.0 | 0.944 | |
| | 0.1445 | 9.0 | 234 | 0.0726 | 1.0 | 1.0 | 1.0 | |
| | 0.1287 | 10.0 | 260 | 0.0740 | 1.0 | 1.0 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.50.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
| |
