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: 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