---
library_name: transformers
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cwe-parent-vulnerability-classification-huggingface-CodeBERTa-small-v1
  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-huggingface-CodeBERTa-small-v1

This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3718
- Accuracy: 0.7753
- F1 Macro: 0.3835

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.2521        | 1.0   | 25   | 3.3015          | 0.0112   | 0.0057   |
| 3.037         | 2.0   | 50   | 3.2608          | 0.3258   | 0.1301   |
| 3.0191        | 3.0   | 75   | 3.3140          | 0.3146   | 0.0568   |
| 2.8876        | 4.0   | 100  | 3.2111          | 0.2472   | 0.2190   |
| 2.7888        | 5.0   | 125  | 3.1305          | 0.2360   | 0.2394   |
| 2.6762        | 6.0   | 150  | 3.1370          | 0.3146   | 0.1503   |
| 2.5905        | 7.0   | 175  | 3.0446          | 0.3933   | 0.2144   |
| 2.4173        | 8.0   | 200  | 2.9769          | 0.3933   | 0.1999   |
| 2.2706        | 9.0   | 225  | 2.9704          | 0.3708   | 0.1825   |
| 2.1355        | 10.0  | 250  | 2.9071          | 0.3820   | 0.2097   |
| 2.0722        | 11.0  | 275  | 2.9189          | 0.4382   | 0.1855   |
| 1.8111        | 12.0  | 300  | 2.7873          | 0.4157   | 0.2257   |
| 1.7056        | 13.0  | 325  | 2.7584          | 0.4607   | 0.2217   |
| 1.6693        | 14.0  | 350  | 2.7394          | 0.5169   | 0.2370   |
| 1.496         | 15.0  | 375  | 2.6647          | 0.5506   | 0.2630   |
| 1.3093        | 16.0  | 400  | 2.6477          | 0.5843   | 0.2644   |
| 1.251         | 17.0  | 425  | 2.6355          | 0.6067   | 0.2654   |
| 1.1316        | 18.0  | 450  | 2.5521          | 0.6404   | 0.3000   |
| 1.049         | 19.0  | 475  | 2.5236          | 0.6404   | 0.2951   |
| 0.9441        | 20.0  | 500  | 2.5538          | 0.6404   | 0.2957   |
| 0.8752        | 21.0  | 525  | 2.5020          | 0.6742   | 0.3259   |
| 0.7623        | 22.0  | 550  | 2.4927          | 0.6966   | 0.3339   |
| 0.7938        | 23.0  | 575  | 2.4595          | 0.7079   | 0.3413   |
| 0.6321        | 24.0  | 600  | 2.4564          | 0.7079   | 0.3369   |
| 0.6245        | 25.0  | 625  | 2.4537          | 0.7191   | 0.3631   |
| 0.5502        | 26.0  | 650  | 2.4470          | 0.7416   | 0.3764   |
| 0.5805        | 27.0  | 675  | 2.4588          | 0.7528   | 0.3849   |
| 0.5042        | 28.0  | 700  | 2.4243          | 0.7640   | 0.3930   |
| 0.464         | 29.0  | 725  | 2.4051          | 0.7640   | 0.3930   |
| 0.4349        | 30.0  | 750  | 2.4361          | 0.7753   | 0.4034   |
| 0.4347        | 31.0  | 775  | 2.4062          | 0.7640   | 0.3906   |
| 0.3953        | 32.0  | 800  | 2.3939          | 0.7753   | 0.3835   |
| 0.3775        | 33.0  | 825  | 2.4091          | 0.7865   | 0.3958   |
| 0.3948        | 34.0  | 850  | 2.4018          | 0.7865   | 0.3958   |
| 0.348         | 35.0  | 875  | 2.3718          | 0.7753   | 0.3835   |
| 0.3328        | 36.0  | 900  | 2.3843          | 0.7865   | 0.3947   |
| 0.3291        | 37.0  | 925  | 2.3843          | 0.7978   | 0.3965   |
| 0.3211        | 38.0  | 950  | 2.3764          | 0.7865   | 0.3958   |
| 0.307         | 39.0  | 975  | 2.3822          | 0.7978   | 0.3975   |
| 0.3055        | 40.0  | 1000 | 2.3855          | 0.7978   | 0.3965   |


### Framework versions

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