---
license: bigscience-openrail-m
base_model: ehsanaghaei/SecureBERT
tags:
- generated_from_trainer
- cybersecurity
metrics:
- accuracy
model-index:
- name: vuln-cat-secbert
  results: []
widget:
- text: A NULL pointer dereference flaw was found in KubeVirt.
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vuln-cat-secbert

This model is a fine-tuned version of [ehsanaghaei/SecureBERT](https://huggingface.co/ehsanaghaei/SecureBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6754
- Accuracy: 0.8977

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 110  | 0.5211          | 0.8886   |
| No log        | 2.0   | 220  | 0.5437          | 0.8932   |
| No log        | 3.0   | 330  | 0.5760          | 0.8909   |
| No log        | 4.0   | 440  | 0.6122          | 0.8955   |
| 0.103         | 5.0   | 550  | 0.6467          | 0.8932   |
| 0.103         | 6.0   | 660  | 0.6633          | 0.8977   |
| 0.103         | 7.0   | 770  | 0.6719          | 0.8977   |
| 0.103         | 8.0   | 880  | 0.6754          | 0.8977   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2