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

<!-- 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

This model is a fine-tuned version of [RoBERTa-base](https://huggingface.co/FacebookAI/roberta-base) on the dataset [CIRCL/vulnerability-scores](https://huggingface.co/datasets/CIRCL/vulnerability-scores).

It achieves the following results on the evaluation set:
- Loss: 0.6501
- Accuracy: 0.7607

## Model description

It is a classification model and is aimed to assist in classifying vulnerabilities by severity based on their descriptions.

## 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 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5993        | 1.0   | 14930 | 0.6907          | 0.7245   |
| 0.5952        | 2.0   | 29860 | 0.6572          | 0.7416   |
| 0.6602        | 3.0   | 44790 | 0.6146          | 0.7513   |
| 0.4305        | 4.0   | 59720 | 0.6159          | 0.7615   |
| 0.3855        | 5.0   | 74650 | 0.6501          | 0.7607   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0