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--- |
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library_name: transformers |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: cwe-parent-vulnerability-classification-roberta-base |
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results: [] |
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datasets: |
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- CIRCL/vulnerability-cwe-patch |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# cwe-parent-vulnerability-classification-roberta-base |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base). |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2078 |
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- Accuracy: 0.875 |
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- F1 Macro: 0.6248 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 40 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| 3.2699 | 1.0 | 25 | 3.1492 | 0.0341 | 0.0055 | |
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| 3.1972 | 2.0 | 50 | 2.9909 | 0.0114 | 0.0064 | |
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| 3.1211 | 3.0 | 75 | 3.0017 | 0.0341 | 0.0140 | |
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| 3.0888 | 4.0 | 100 | 3.0223 | 0.2841 | 0.0463 | |
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| 2.9467 | 5.0 | 125 | 2.9608 | 0.0114 | 0.0018 | |
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| 2.9851 | 6.0 | 150 | 2.8743 | 0.1932 | 0.0641 | |
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| 2.9083 | 7.0 | 175 | 2.7687 | 0.375 | 0.0963 | |
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| 2.7652 | 8.0 | 200 | 2.7049 | 0.4318 | 0.1953 | |
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| 2.6893 | 9.0 | 225 | 2.5547 | 0.4886 | 0.1952 | |
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| 2.5636 | 10.0 | 250 | 2.4970 | 0.5682 | 0.3314 | |
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| 2.477 | 11.0 | 275 | 2.3499 | 0.6136 | 0.3790 | |
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| 2.2936 | 12.0 | 300 | 2.2659 | 0.6364 | 0.3949 | |
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| 2.1369 | 13.0 | 325 | 2.1758 | 0.625 | 0.4002 | |
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| 2.0615 | 14.0 | 350 | 2.1015 | 0.6477 | 0.4169 | |
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| 1.9548 | 15.0 | 375 | 1.9444 | 0.6932 | 0.3972 | |
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| 1.7943 | 16.0 | 400 | 1.8892 | 0.6818 | 0.4210 | |
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| 1.6619 | 17.0 | 425 | 1.8439 | 0.6818 | 0.4149 | |
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| 1.5391 | 18.0 | 450 | 1.7247 | 0.7159 | 0.4848 | |
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| 1.4415 | 19.0 | 475 | 1.6650 | 0.7273 | 0.4749 | |
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| 1.2834 | 20.0 | 500 | 1.5743 | 0.7727 | 0.5574 | |
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| 1.2245 | 21.0 | 525 | 1.5396 | 0.7614 | 0.5373 | |
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| 1.1629 | 22.0 | 550 | 1.5005 | 0.7614 | 0.5350 | |
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| 1.0894 | 23.0 | 575 | 1.4478 | 0.7614 | 0.5383 | |
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| 0.9755 | 24.0 | 600 | 1.4335 | 0.7841 | 0.5599 | |
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| 0.9271 | 25.0 | 625 | 1.4195 | 0.7841 | 0.5562 | |
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| 0.8761 | 26.0 | 650 | 1.3740 | 0.8182 | 0.6015 | |
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| 0.8312 | 27.0 | 675 | 1.3479 | 0.8295 | 0.6086 | |
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| 0.7523 | 28.0 | 700 | 1.3379 | 0.8295 | 0.5948 | |
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| 0.718 | 29.0 | 725 | 1.2991 | 0.8295 | 0.5948 | |
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| 0.6819 | 30.0 | 750 | 1.3059 | 0.8409 | 0.6047 | |
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| 0.6771 | 31.0 | 775 | 1.2650 | 0.8636 | 0.6167 | |
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| 0.6267 | 32.0 | 800 | 1.2905 | 0.8523 | 0.6252 | |
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| 0.6068 | 33.0 | 825 | 1.2559 | 0.875 | 0.6248 | |
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| 0.5811 | 34.0 | 850 | 1.2371 | 0.875 | 0.6248 | |
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| 0.5579 | 35.0 | 875 | 1.2231 | 0.875 | 0.6248 | |
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| 0.5385 | 36.0 | 900 | 1.2342 | 0.875 | 0.6248 | |
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| 0.5334 | 37.0 | 925 | 1.2255 | 0.875 | 0.6248 | |
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| 0.4868 | 38.0 | 950 | 1.2223 | 0.875 | 0.6248 | |
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| 0.5228 | 39.0 | 975 | 1.2078 | 0.875 | 0.6248 | |
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| 0.5325 | 40.0 | 1000 | 1.2101 | 0.875 | 0.6248 | |
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### Framework versions |
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- Transformers 4.55.4 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
