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---
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
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