---
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: []
---

<!-- 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) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5419
- Accuracy: 0.8068
- F1 Macro: 0.3782

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.2546        | 1.0   | 25   | 3.1526          | 0.0682   | 0.0142   |
| 3.1769        | 2.0   | 50   | 2.9132          | 0.0795   | 0.0185   |
| 3.1105        | 3.0   | 75   | 2.8945          | 0.5      | 0.0752   |
| 3.0319        | 4.0   | 100  | 2.7792          | 0.0114   | 0.0027   |
| 3.0703        | 5.0   | 125  | 2.8108          | 0.0455   | 0.0130   |
| 2.9543        | 6.0   | 150  | 2.8282          | 0.0682   | 0.0235   |
| 2.9445        | 7.0   | 175  | 2.7967          | 0.125    | 0.0743   |
| 2.8502        | 8.0   | 200  | 2.7834          | 0.1818   | 0.0913   |
| 2.7131        | 9.0   | 225  | 2.6824          | 0.4205   | 0.1350   |
| 2.6082        | 10.0  | 250  | 2.6462          | 0.5227   | 0.1447   |
| 2.6341        | 11.0  | 275  | 2.6106          | 0.4545   | 0.1765   |
| 2.3253        | 12.0  | 300  | 2.5876          | 0.5455   | 0.1611   |
| 2.2511        | 13.0  | 325  | 2.6247          | 0.4773   | 0.1580   |
| 2.2056        | 14.0  | 350  | 2.5191          | 0.6136   | 0.1808   |
| 2.0981        | 15.0  | 375  | 2.3928          | 0.625    | 0.2183   |
| 1.8694        | 16.0  | 400  | 2.3963          | 0.6818   | 0.2353   |
| 1.7945        | 17.0  | 425  | 2.2359          | 0.6818   | 0.2290   |
| 1.7152        | 18.0  | 450  | 2.2076          | 0.7159   | 0.2540   |
| 1.6186        | 19.0  | 475  | 2.1035          | 0.7045   | 0.2388   |
| 1.4477        | 20.0  | 500  | 2.0271          | 0.6932   | 0.2464   |
| 1.4064        | 21.0  | 525  | 1.9818          | 0.7159   | 0.2478   |
| 1.2211        | 22.0  | 550  | 1.8832          | 0.7159   | 0.2517   |
| 1.2831        | 23.0  | 575  | 1.8892          | 0.7273   | 0.2712   |
| 1.1426        | 24.0  | 600  | 1.7992          | 0.7273   | 0.2644   |
| 1.054         | 25.0  | 625  | 1.8517          | 0.7386   | 0.2726   |
| 1.0345        | 26.0  | 650  | 1.7283          | 0.7273   | 0.2644   |
| 0.9516        | 27.0  | 675  | 1.7043          | 0.7045   | 0.2630   |
| 0.8861        | 28.0  | 700  | 1.6532          | 0.7386   | 0.2735   |
| 0.8477        | 29.0  | 725  | 1.6508          | 0.7614   | 0.2795   |
| 0.8804        | 30.0  | 750  | 1.6057          | 0.7386   | 0.2612   |
| 0.7854        | 31.0  | 775  | 1.5771          | 0.75     | 0.2902   |
| 0.7311        | 32.0  | 800  | 1.5838          | 0.7614   | 0.2662   |
| 0.7362        | 33.0  | 825  | 1.5649          | 0.7841   | 0.3463   |
| 0.7031        | 34.0  | 850  | 1.5553          | 0.7841   | 0.3361   |
| 0.7589        | 35.0  | 875  | 1.5546          | 0.7955   | 0.3545   |
| 0.6877        | 36.0  | 900  | 1.5557          | 0.7841   | 0.3361   |
| 0.6497        | 37.0  | 925  | 1.5419          | 0.8068   | 0.3782   |
| 0.6565        | 38.0  | 950  | 1.5496          | 0.7955   | 0.3663   |
| 0.6333        | 39.0  | 975  | 1.5531          | 0.7955   | 0.3458   |
| 0.653         | 40.0  | 1000 | 1.5501          | 0.7955   | 0.3458   |


### Framework versions

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