| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: vulnerability-severity-classification-roberta-base |
| 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-severity-classification-roberta-base |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5002 |
| - Accuracy: 0.8264 |
|
|
| ## 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: 3e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - 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 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:| |
| | 0.6004 | 1.0 | 29952 | 0.6255 | 0.7471 | |
| | 0.5196 | 2.0 | 59904 | 0.5728 | 0.7776 | |
| | 0.4888 | 3.0 | 89856 | 0.5283 | 0.8019 | |
| | 0.3788 | 4.0 | 119808 | 0.5072 | 0.8179 | |
| | 0.2821 | 5.0 | 149760 | 0.5002 | 0.8264 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.1 |
| - Pytorch 2.9.1+cu128 |
| - Datasets 4.4.1 |
| - Tokenizers 0.22.1 |
| |
