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

<!-- 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. -->

# cwe-parent-vulnerability-classification-roberta-base

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base).

It achieves the following results on the evaluation set:
- Loss: 1.2078
- Accuracy: 0.875
- F1 Macro: 0.6248

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.2699        | 1.0   | 25   | 3.1492          | 0.0341   | 0.0055   |
| 3.1972        | 2.0   | 50   | 2.9909          | 0.0114   | 0.0064   |
| 3.1211        | 3.0   | 75   | 3.0017          | 0.0341   | 0.0140   |
| 3.0888        | 4.0   | 100  | 3.0223          | 0.2841   | 0.0463   |
| 2.9467        | 5.0   | 125  | 2.9608          | 0.0114   | 0.0018   |
| 2.9851        | 6.0   | 150  | 2.8743          | 0.1932   | 0.0641   |
| 2.9083        | 7.0   | 175  | 2.7687          | 0.375    | 0.0963   |
| 2.7652        | 8.0   | 200  | 2.7049          | 0.4318   | 0.1953   |
| 2.6893        | 9.0   | 225  | 2.5547          | 0.4886   | 0.1952   |
| 2.5636        | 10.0  | 250  | 2.4970          | 0.5682   | 0.3314   |
| 2.477         | 11.0  | 275  | 2.3499          | 0.6136   | 0.3790   |
| 2.2936        | 12.0  | 300  | 2.2659          | 0.6364   | 0.3949   |
| 2.1369        | 13.0  | 325  | 2.1758          | 0.625    | 0.4002   |
| 2.0615        | 14.0  | 350  | 2.1015          | 0.6477   | 0.4169   |
| 1.9548        | 15.0  | 375  | 1.9444          | 0.6932   | 0.3972   |
| 1.7943        | 16.0  | 400  | 1.8892          | 0.6818   | 0.4210   |
| 1.6619        | 17.0  | 425  | 1.8439          | 0.6818   | 0.4149   |
| 1.5391        | 18.0  | 450  | 1.7247          | 0.7159   | 0.4848   |
| 1.4415        | 19.0  | 475  | 1.6650          | 0.7273   | 0.4749   |
| 1.2834        | 20.0  | 500  | 1.5743          | 0.7727   | 0.5574   |
| 1.2245        | 21.0  | 525  | 1.5396          | 0.7614   | 0.5373   |
| 1.1629        | 22.0  | 550  | 1.5005          | 0.7614   | 0.5350   |
| 1.0894        | 23.0  | 575  | 1.4478          | 0.7614   | 0.5383   |
| 0.9755        | 24.0  | 600  | 1.4335          | 0.7841   | 0.5599   |
| 0.9271        | 25.0  | 625  | 1.4195          | 0.7841   | 0.5562   |
| 0.8761        | 26.0  | 650  | 1.3740          | 0.8182   | 0.6015   |
| 0.8312        | 27.0  | 675  | 1.3479          | 0.8295   | 0.6086   |
| 0.7523        | 28.0  | 700  | 1.3379          | 0.8295   | 0.5948   |
| 0.718         | 29.0  | 725  | 1.2991          | 0.8295   | 0.5948   |
| 0.6819        | 30.0  | 750  | 1.3059          | 0.8409   | 0.6047   |
| 0.6771        | 31.0  | 775  | 1.2650          | 0.8636   | 0.6167   |
| 0.6267        | 32.0  | 800  | 1.2905          | 0.8523   | 0.6252   |
| 0.6068        | 33.0  | 825  | 1.2559          | 0.875    | 0.6248   |
| 0.5811        | 34.0  | 850  | 1.2371          | 0.875    | 0.6248   |
| 0.5579        | 35.0  | 875  | 1.2231          | 0.875    | 0.6248   |
| 0.5385        | 36.0  | 900  | 1.2342          | 0.875    | 0.6248   |
| 0.5334        | 37.0  | 925  | 1.2255          | 0.875    | 0.6248   |
| 0.4868        | 38.0  | 950  | 1.2223          | 0.875    | 0.6248   |
| 0.5228        | 39.0  | 975  | 1.2078          | 0.875    | 0.6248   |
| 0.5325        | 40.0  | 1000 | 1.2101          | 0.875    | 0.6248   |


### Framework versions

- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2