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---
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: 1.3447
- Accuracy: 0.7727
- F1 Macro: 0.4235
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.263 | 1.0 | 25 | 3.2313 | 0.2614 | 0.0345 |
| 3.1726 | 2.0 | 50 | 2.9923 | 0.1818 | 0.0431 |
| 3.1008 | 3.0 | 75 | 2.8828 | 0.0 | 0.0 |
| 2.9805 | 4.0 | 100 | 2.8858 | 0.0114 | 0.0019 |
| 3.0021 | 5.0 | 125 | 2.8257 | 0.4432 | 0.0626 |
| 2.8775 | 6.0 | 150 | 2.7730 | 0.0795 | 0.0462 |
| 2.8805 | 7.0 | 175 | 2.6421 | 0.2841 | 0.1362 |
| 2.6602 | 8.0 | 200 | 2.6462 | 0.3864 | 0.1366 |
| 2.5303 | 9.0 | 225 | 2.5584 | 0.3523 | 0.1461 |
| 2.5236 | 10.0 | 250 | 2.4933 | 0.4205 | 0.1209 |
| 2.3221 | 11.0 | 275 | 2.3458 | 0.5909 | 0.2232 |
| 2.1446 | 12.0 | 300 | 2.2679 | 0.625 | 0.2521 |
| 1.9937 | 13.0 | 325 | 2.1932 | 0.625 | 0.2736 |
| 1.8521 | 14.0 | 350 | 2.0372 | 0.6477 | 0.2881 |
| 1.7899 | 15.0 | 375 | 1.9494 | 0.6364 | 0.2679 |
| 1.5273 | 16.0 | 400 | 1.8457 | 0.6705 | 0.3205 |
| 1.4178 | 17.0 | 425 | 1.8276 | 0.6477 | 0.2931 |
| 1.335 | 18.0 | 450 | 1.7690 | 0.6591 | 0.3004 |
| 1.2685 | 19.0 | 475 | 1.6681 | 0.6705 | 0.3577 |
| 1.112 | 20.0 | 500 | 1.6399 | 0.6818 | 0.3152 |
| 1.01 | 21.0 | 525 | 1.5561 | 0.6932 | 0.3255 |
| 0.9637 | 22.0 | 550 | 1.5008 | 0.7159 | 0.4218 |
| 0.9571 | 23.0 | 575 | 1.5387 | 0.7045 | 0.3385 |
| 0.8213 | 24.0 | 600 | 1.5366 | 0.7159 | 0.4043 |
| 0.7538 | 25.0 | 625 | 1.4691 | 0.75 | 0.3942 |
| 0.7228 | 26.0 | 650 | 1.4826 | 0.7273 | 0.3872 |
| 0.7244 | 27.0 | 675 | 1.4789 | 0.7386 | 0.3915 |
| 0.6746 | 28.0 | 700 | 1.4439 | 0.7727 | 0.4322 |
| 0.5959 | 29.0 | 725 | 1.4202 | 0.7614 | 0.3942 |
| 0.5788 | 30.0 | 750 | 1.4339 | 0.7727 | 0.4002 |
| 0.5718 | 31.0 | 775 | 1.3723 | 0.7955 | 0.4431 |
| 0.5358 | 32.0 | 800 | 1.4186 | 0.7727 | 0.3812 |
| 0.5094 | 33.0 | 825 | 1.3722 | 0.7841 | 0.4579 |
| 0.5003 | 34.0 | 850 | 1.3955 | 0.7614 | 0.3786 |
| 0.4973 | 35.0 | 875 | 1.3733 | 0.8068 | 0.4635 |
| 0.4721 | 36.0 | 900 | 1.3447 | 0.7727 | 0.4235 |
| 0.4457 | 37.0 | 925 | 1.3622 | 0.7955 | 0.4573 |
| 0.4232 | 38.0 | 950 | 1.3736 | 0.7614 | 0.3986 |
| 0.4405 | 39.0 | 975 | 1.3683 | 0.7727 | 0.4235 |
| 0.437 | 40.0 | 1000 | 1.3642 | 0.7614 | 0.3986 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
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