| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: mangsense/codebert_java |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: codebert-java-vul4j-ft |
| 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. --> |
|
|
| # codebert-java-vul4j-ft |
|
|
| This model is a fine-tuned version of [mangsense/codebert_java](https://huggingface.co/mangsense/codebert_java) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5547 |
| - Accuracy: 0.7143 |
| - F1: 0.4286 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | No log | 1.0 | 66 | 0.4762 | 0.6988 | 0.3243 | |
| | No log | 2.0 | 132 | 0.3536 | 0.8313 | 0.125 | |
| | No log | 3.0 | 198 | 0.4353 | 0.8434 | 0.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.4.2 |
| - Tokenizers 0.22.1 |
| |
