metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vulnerability-severity-classification-roberta-base-expB
results: []
vulnerability-severity-classification-roberta-base-expB
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4995
- Accuracy: 0.8421
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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6798 | 1.0 | 14844 | 0.6302 | 0.7400 |
| 0.5937 | 2.0 | 29688 | 0.6037 | 0.7617 |
| 0.5045 | 3.0 | 44532 | 0.5406 | 0.7846 |
| 0.5463 | 4.0 | 59376 | 0.4999 | 0.8103 |
| 0.3192 | 5.0 | 74220 | 0.4894 | 0.8257 |
| 0.2919 | 6.0 | 89064 | 0.4923 | 0.8384 |
| 0.3553 | 7.0 | 103908 | 0.4995 | 0.8421 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1