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cwe-parent-vulnerability-classification-roberta-base
CIRCL/cwe-parent-vulnerability-classification-roberta-base
cwe-parent-vulnerability-classification-roberta-base is a text classification model from CIRCL. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Aug 13, 2025
- Updated
- Jul 13, 2026
- SHA
- 95c7ad5d
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Base models
Model card
From the Hugging Face model README
<!-- 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 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2511
- Accuracy: 0.5683
- F1 Macro: 0.2101
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|
| 5.6204 | 1.0 | 101 | 5.5246 | 0.0189 | 0.0004 |
| 5.4605 | 2.0 | 202 | 5.4081 | 0.0068 | 0.0005 |
| 5.4306 | 3.0 | 303 | 5.3191 | 0.0447 | 0.0045 |
| 5.3366 | 4.0 | 404 | 5.2692 | 0.0717 | 0.0049 |
| 5.2705 | 5.0 | 505 | 5.2310 | 0.0704 | 0.0096 |
| 5.1530 | 6.0 | 606 | 5.1756 | 0.0934 | 0.0136 |
| 4.9916 | 7.0 | 707 | 5.1084 | 0.2097 | 0.0299 |
| 4.8387 | 8.0 | 808 | 5.0626 | 0.2341 | 0.0419 |
| 4.7198 | 9.0 | 909 | 5.0164 | 0.2503 | 0.0616 |
| 4.6754 | 10.0 | 1010 | 4.9531 | 0.2963 | 0.0674 |
| 4.4443 | 11.0 | 1111 | 4.9144 | 0.3194 | 0.0714 |
| 4.3628 | 12.0 | 1212 | 4.8954 | 0.3315 | 0.0811 |
| 4.2481 | 13.0 | 1313 | 4.8476 | 0.3654 | 0.1104 |
| 4.1578 | 14.0 | 1414 | 4.7984 | 0.3775 | 0.1155 |
| 3.9924 | 15.0 | 1515 | 4.7600 | 0.4181 | 0.1226 |
| 3.9078 | 16.0 | 1616 | 4.7190 | 0.4263 | 0.1215 |
| 3.8065 | 17.0 | 1717 | 4.6783 | 0.4506 | 0.1442 |
| 3.7696 | 18.0 | 1818 | 4.6424 | 0.4696 | 0.1503 |
| 3.7075 | 19.0 | 1919 | 4.6157 | 0.4696 | 0.1438 |
| 3.5318 | 20.0 | 2020 | 4.5766 | 0.4736 | 0.1489 |
| 3.5248 | 21.0 | 2121 | 4.5494 | 0.4831 | 0.1463 |
| 3.5334 | 22.0 | 2222 | 4.5183 | 0.5101 | 0.1718 |
| 3.3713 | 23.0 | 2323 | 4.4923 | 0.5183 | 0.1595 |
| 3.2803 | 24.0 | 2424 | 4.4588 | 0.5223 | 0.1758 |
| 3.2246 | 25.0 | 2525 | 4.4311 | 0.5250 | 0.1932 |
| 3.1723 | 26.0 | 2626 | 4.4115 | 0.5359 | 0.1911 |
| 3.0648 | 27.0 | 2727 | 4.3898 | 0.5359 | 0.1986 |
| 2.9372 | 28.0 | 2828 | 4.3769 | 0.5426 | 0.1994 |
| 3.0113 | 29.0 | 2929 | 4.3596 | 0.5494 | 0.1968 |
| 2.9797 | 30.0 | 3030 | 4.3321 | 0.5413 | 0.1882 |
| 2.9339 | 31.0 | 3131 | 4.3254 | 0.5453 | 0.1944 |
| 2.8733 | 32.0 | 3232 | 4.3052 | 0.5521 | 0.1934 |
| 2.8051 | 33.0 | 3333 | 4.2951 | 0.5629 | 0.2121 |
| 2.8297 | 34.0 | 3434 | 4.2923 | 0.5589 | 0.2049 |
| 2.7814 | 35.0 | 3535 | 4.2770 | 0.5616 | 0.2079 |
| 2.7509 | 36.0 | 3636 | 4.2605 | 0.5670 | 0.2107 |
| 2.7396 | 37.0 | 3737 | 4.2677 | 0.5670 | 0.2128 |
| 2.7384 | 38.0 | 3838 | 4.2520 | 0.5670 | 0.2099 |
| 2.7081 | 39.0 | 3939 | 4.2548 | 0.5670 | 0.2115 |
| 2.7587 | 40.0 | 4040 | 4.2511 | 0.5683 | 0.2101 |
Framework versions
- Transformers 5.13.0
- Pytorch 2.12.1+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Aug 13, 2025
- Updated
- Jul 13, 2026