|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: roberta-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: cwe-parent-vulnerability-classification-roberta-base-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-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: 1.3755 |
|
|
- Accuracy: 0.6603 |
|
|
- F1 Macro: 0.4616 |
|
|
|
|
|
## 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_FUSED 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
|
|
| 2.9549 | 1.0 | 238 | 2.9056 | 0.0948 | 0.0729 | |
|
|
| 2.2865 | 2.0 | 476 | 1.9760 | 0.4946 | 0.3041 | |
|
|
| 1.8517 | 3.0 | 714 | 1.7010 | 0.5114 | 0.3522 | |
|
|
| 1.6439 | 4.0 | 952 | 1.5457 | 0.6074 | 0.3826 | |
|
|
| 1.3475 | 5.0 | 1190 | 1.5154 | 0.5894 | 0.3608 | |
|
|
| 1.1372 | 6.0 | 1428 | 1.4379 | 0.6327 | 0.4183 | |
|
|
| 1.0323 | 7.0 | 1666 | 1.3955 | 0.6411 | 0.4184 | |
|
|
| 0.8662 | 8.0 | 1904 | 1.3755 | 0.6603 | 0.4616 | |
|
|
| 0.8135 | 9.0 | 2142 | 1.4626 | 0.6807 | 0.4703 | |
|
|
| 0.632 | 10.0 | 2380 | 1.4197 | 0.6999 | 0.4439 | |
|
|
| 0.5727 | 11.0 | 2618 | 1.4083 | 0.6795 | 0.4878 | |
|
|
| 0.5429 | 12.0 | 2856 | 1.5234 | 0.6651 | 0.4823 | |
|
|
| 0.3597 | 13.0 | 3094 | 1.5866 | 0.7107 | 0.4995 | |
|
|
| 0.3076 | 14.0 | 3332 | 1.6262 | 0.7191 | 0.5243 | |
|
|
| 0.2458 | 15.0 | 3570 | 1.7271 | 0.6963 | 0.5259 | |
|
|
| 0.2052 | 16.0 | 3808 | 1.7799 | 0.7011 | 0.4556 | |
|
|
| 0.1801 | 17.0 | 4046 | 1.7717 | 0.7179 | 0.4983 | |
|
|
| 0.187 | 18.0 | 4284 | 2.0014 | 0.7239 | 0.5273 | |
|
|
| 0.1473 | 19.0 | 4522 | 1.9999 | 0.7419 | 0.5388 | |
|
|
| 0.1198 | 20.0 | 4760 | 1.9328 | 0.7275 | 0.5336 | |
|
|
| 0.152 | 21.0 | 4998 | 2.0637 | 0.7407 | 0.4759 | |
|
|
| 0.0692 | 22.0 | 5236 | 2.2153 | 0.7647 | 0.5553 | |
|
|
| 0.0632 | 23.0 | 5474 | 2.1253 | 0.7431 | 0.5381 | |
|
|
| 0.069 | 24.0 | 5712 | 2.2856 | 0.7587 | 0.5443 | |
|
|
| 0.0472 | 25.0 | 5950 | 2.3607 | 0.7611 | 0.5286 | |
|
|
| 0.0452 | 26.0 | 6188 | 2.4693 | 0.7539 | 0.5191 | |
|
|
| 0.0388 | 27.0 | 6426 | 2.4699 | 0.7587 | 0.5550 | |
|
|
| 0.0412 | 28.0 | 6664 | 2.5062 | 0.7659 | 0.5332 | |
|
|
| 0.0419 | 29.0 | 6902 | 2.4443 | 0.7551 | 0.5488 | |
|
|
| 0.0238 | 30.0 | 7140 | 2.5642 | 0.7479 | 0.5487 | |
|
|
| 0.0616 | 31.0 | 7378 | 2.5451 | 0.7623 | 0.5511 | |
|
|
| 0.0163 | 32.0 | 7616 | 2.6758 | 0.7599 | 0.5450 | |
|
|
| 0.028 | 33.0 | 7854 | 2.6806 | 0.7671 | 0.5432 | |
|
|
| 0.0147 | 34.0 | 8092 | 2.6815 | 0.7647 | 0.5518 | |
|
|
| 0.0251 | 35.0 | 8330 | 2.7046 | 0.7611 | 0.5470 | |
|
|
| 0.0151 | 36.0 | 8568 | 2.6610 | 0.7527 | 0.5440 | |
|
|
| 0.0128 | 37.0 | 8806 | 2.7269 | 0.7551 | 0.5426 | |
|
|
| 0.0421 | 38.0 | 9044 | 2.7759 | 0.7515 | 0.5437 | |
|
|
| 0.0259 | 39.0 | 9282 | 2.7239 | 0.7587 | 0.5444 | |
|
|
| 0.0046 | 40.0 | 9520 | 2.7196 | 0.7599 | 0.5448 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.57.1 |
|
|
- Pytorch 2.9.1+cu128 |
|
|
- Datasets 4.4.1 |
|
|
- Tokenizers 0.22.1 |
|
|
|
