---
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: []
---

<!-- 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-expB

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: 0.5255
- Accuracy: 0.8184

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.6959        | 1.0   | 29819  | 0.6482          | 0.7331   |
| 0.6137        | 2.0   | 59638  | 0.5869          | 0.7681   |
| 0.48          | 3.0   | 89457  | 0.5544          | 0.7899   |
| 0.4657        | 4.0   | 119276 | 0.5210          | 0.8109   |
| 0.3649        | 5.0   | 149095 | 0.5255          | 0.8184   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1