metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vulnerability-severity-classification-roberta-base
results: []
vulnerability-severity-classification-roberta-base
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0731
- Accuracy: 0.8134
- F1 Macro: 0.7445
- Low Precision: 0.6507
- Low Recall: 0.5058
- Low F1: 0.5692
- Medium Precision: 0.8479
- Medium Recall: 0.8626
- Medium F1: 0.8552
- High Precision: 0.8069
- High Recall: 0.8089
- High F1: 0.8079
- Critical Precision: 0.7441
- Critical Recall: 0.7472
- Critical F1: 0.7457
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: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Low Precision | Low Recall | Low F1 | Medium Precision | Medium Recall | Medium F1 | High Precision | High Recall | High F1 | Critical Precision | Critical Recall | Critical F1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.7651 | 1.0 | 15900 | 2.5756 | 0.7357 | 0.6295 | 0.6394 | 0.2587 | 0.3683 | 0.7911 | 0.8066 | 0.7988 | 0.7049 | 0.7369 | 0.7205 | 0.6314 | 0.6294 | 0.6304 |
| 2.3544 | 2.0 | 31800 | 2.3242 | 0.7640 | 0.6742 | 0.6876 | 0.3302 | 0.4461 | 0.8154 | 0.8253 | 0.8204 | 0.7468 | 0.7512 | 0.7490 | 0.6454 | 0.7212 | 0.6812 |
| 2.3762 | 3.0 | 47700 | 2.1947 | 0.7844 | 0.7118 | 0.5717 | 0.4992 | 0.5330 | 0.8218 | 0.8440 | 0.8328 | 0.7816 | 0.7704 | 0.7760 | 0.7109 | 0.7001 | 0.7055 |
| 1.5527 | 4.0 | 63600 | 2.0991 | 0.8034 | 0.7263 | 0.7186 | 0.4157 | 0.5267 | 0.8411 | 0.8543 | 0.8476 | 0.7886 | 0.8028 | 0.7956 | 0.7235 | 0.7472 | 0.7352 |
| 1.2645 | 5.0 | 79500 | 2.0731 | 0.8134 | 0.7445 | 0.6507 | 0.5058 | 0.5692 | 0.8479 | 0.8626 | 0.8552 | 0.8069 | 0.8089 | 0.8079 | 0.7441 | 0.7472 | 0.7457 |
Framework versions
- Transformers 5.5.4
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2