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: 2.0377
- Accuracy: 0.8151
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 |
|---|---|---|---|---|
| 2.5673 | 1.0 | 15312 | 2.5667 | 0.7330 |
| 2.2339 | 2.0 | 30624 | 2.2996 | 0.7678 |
| 1.9288 | 3.0 | 45936 | 2.1713 | 0.7870 |
| 1.6486 | 4.0 | 61248 | 2.0764 | 0.8027 |
| 1.4956 | 5.0 | 76560 | 2.0377 | 0.8151 |
Framework versions
- Transformers 5.1.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2