---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cwe-parent-vulnerability-classification-bert-base-uncased
  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-bert-base-uncased

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9385
- Accuracy: 0.4270
- F1 Macro: 0.2048

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.2751        | 1.0   | 25   | 3.3057          | 0.0112   | 0.0019   |
| 3.1518        | 2.0   | 50   | 3.1378          | 0.0449   | 0.0337   |
| 3.0997        | 3.0   | 75   | 3.2138          | 0.0674   | 0.0376   |
| 2.9858        | 4.0   | 100  | 3.1921          | 0.1348   | 0.0806   |
| 2.9764        | 5.0   | 125  | 3.1470          | 0.2584   | 0.1308   |
| 2.8564        | 6.0   | 150  | 3.2075          | 0.3708   | 0.1465   |
| 2.8474        | 7.0   | 175  | 3.1799          | 0.3596   | 0.1653   |
| 2.7354        | 8.0   | 200  | 3.1618          | 0.3483   | 0.1412   |
| 2.6452        | 9.0   | 225  | 3.1248          | 0.3258   | 0.1531   |
| 2.5802        | 10.0  | 250  | 3.1154          | 0.3371   | 0.1488   |
| 2.5078        | 11.0  | 275  | 3.1547          | 0.3820   | 0.1712   |
| 2.4203        | 12.0  | 300  | 3.1410          | 0.3483   | 0.1549   |
| 2.3624        | 13.0  | 325  | 3.1409          | 0.4045   | 0.1776   |
| 2.3642        | 14.0  | 350  | 3.0964          | 0.2809   | 0.1496   |
| 2.2259        | 15.0  | 375  | 3.0960          | 0.3708   | 0.1904   |
| 2.1874        | 16.0  | 400  | 3.0170          | 0.3146   | 0.1653   |
| 2.15          | 17.0  | 425  | 3.0944          | 0.3146   | 0.1452   |
| 2.1051        | 18.0  | 450  | 3.0225          | 0.3258   | 0.1807   |
| 1.988         | 19.0  | 475  | 3.0687          | 0.3820   | 0.1539   |
| 1.9716        | 20.0  | 500  | 3.0054          | 0.3820   | 0.1675   |
| 1.9034        | 21.0  | 525  | 2.9834          | 0.3820   | 0.1985   |
| 1.8538        | 22.0  | 550  | 3.0251          | 0.3933   | 0.1942   |
| 1.8294        | 23.0  | 575  | 3.0231          | 0.3708   | 0.1579   |
| 1.7436        | 24.0  | 600  | 2.9719          | 0.4045   | 0.1976   |
| 1.7088        | 25.0  | 625  | 2.9701          | 0.4157   | 0.2138   |
| 1.7028        | 26.0  | 650  | 2.9724          | 0.4607   | 0.2250   |
| 1.6962        | 27.0  | 675  | 2.9385          | 0.4270   | 0.2048   |
| 1.5973        | 28.0  | 700  | 2.9636          | 0.4494   | 0.1904   |
| 1.5754        | 29.0  | 725  | 2.9441          | 0.5393   | 0.2116   |
| 1.5279        | 30.0  | 750  | 2.9785          | 0.5506   | 0.2373   |
| 1.5802        | 31.0  | 775  | 2.9711          | 0.5618   | 0.2346   |
| 1.4479        | 32.0  | 800  | 2.9884          | 0.5730   | 0.2335   |
| 1.484         | 33.0  | 825  | 3.0117          | 0.5730   | 0.2550   |
| 1.4243        | 34.0  | 850  | 2.9759          | 0.5843   | 0.2408   |
| 1.4473        | 35.0  | 875  | 2.9626          | 0.5955   | 0.2692   |
| 1.3875        | 36.0  | 900  | 2.9673          | 0.5843   | 0.2342   |
| 1.4214        | 37.0  | 925  | 2.9887          | 0.5843   | 0.2564   |
| 1.373         | 38.0  | 950  | 2.9894          | 0.6067   | 0.2728   |
| 1.3472        | 39.0  | 975  | 2.9805          | 0.5730   | 0.2311   |
| 1.336         | 40.0  | 1000 | 2.9836          | 0.5843   | 0.2439   |


### Framework versions

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