---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vulnerability-severity-classification-roberta-base-expC
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vulnerability-severity-classification-roberta-base-expC

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: 0.4857
- Accuracy: 0.8246

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6425        | 1.0   | 14976 | 0.6224          | 0.7470   |
| 0.5791        | 2.0   | 29952 | 0.5606          | 0.7748   |
| 0.4643        | 3.0   | 44928 | 0.5173          | 0.7979   |
| 0.4282        | 4.0   | 59904 | 0.4955          | 0.8175   |
| 0.2652        | 5.0   | 74880 | 0.4857          | 0.8246   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1