metadata
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: []
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: 1.9131
- Accuracy: 0.7701
- F1 Macro: 0.4179
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 |
|---|---|---|---|---|---|
| 3.2726 | 1.0 | 25 | 3.1430 | 0.0230 | 0.0041 |
| 3.214 | 2.0 | 50 | 2.9861 | 0.0230 | 0.0041 |
| 3.1457 | 3.0 | 75 | 2.9949 | 0.0115 | 0.0019 |
| 3.0447 | 4.0 | 100 | 3.0090 | 0.1149 | 0.0265 |
| 3.0588 | 5.0 | 125 | 2.9652 | 0.0230 | 0.0039 |
| 2.9336 | 6.0 | 150 | 2.9089 | 0.4828 | 0.1081 |
| 2.9729 | 7.0 | 175 | 2.9005 | 0.1264 | 0.0606 |
| 2.812 | 8.0 | 200 | 2.9174 | 0.3563 | 0.1788 |
| 2.6587 | 9.0 | 225 | 2.8268 | 0.3563 | 0.1414 |
| 2.5464 | 10.0 | 250 | 2.8296 | 0.3103 | 0.1339 |
| 2.4379 | 11.0 | 275 | 2.7762 | 0.2989 | 0.1554 |
| 2.2741 | 12.0 | 300 | 2.7595 | 0.4598 | 0.1745 |
| 2.1793 | 13.0 | 325 | 2.7483 | 0.4943 | 0.1826 |
| 2.0085 | 14.0 | 350 | 2.6646 | 0.4713 | 0.2136 |
| 1.9313 | 15.0 | 375 | 2.6414 | 0.6092 | 0.2916 |
| 1.7534 | 16.0 | 400 | 2.5186 | 0.6552 | 0.3345 |
| 1.6187 | 17.0 | 425 | 2.3736 | 0.6552 | 0.3381 |
| 1.5568 | 18.0 | 450 | 2.2908 | 0.6667 | 0.3391 |
| 1.4627 | 19.0 | 475 | 2.4101 | 0.6437 | 0.3356 |
| 1.2964 | 20.0 | 500 | 2.2791 | 0.6782 | 0.3525 |
| 1.2236 | 21.0 | 525 | 2.1636 | 0.6667 | 0.3403 |
| 1.1237 | 22.0 | 550 | 2.1584 | 0.6897 | 0.3397 |
| 1.0589 | 23.0 | 575 | 2.1262 | 0.6782 | 0.3535 |
| 0.952 | 24.0 | 600 | 2.1252 | 0.6782 | 0.3504 |
| 0.9137 | 25.0 | 625 | 2.0899 | 0.6667 | 0.3656 |
| 0.878 | 26.0 | 650 | 1.9915 | 0.7126 | 0.4012 |
| 0.8073 | 27.0 | 675 | 1.9856 | 0.7356 | 0.3857 |
| 0.7588 | 28.0 | 700 | 1.9613 | 0.7356 | 0.3737 |
| 0.7114 | 29.0 | 725 | 1.9789 | 0.7701 | 0.4103 |
| 0.6728 | 30.0 | 750 | 1.9131 | 0.7701 | 0.4179 |
| 0.6651 | 31.0 | 775 | 2.0236 | 0.7701 | 0.4231 |
| 0.5979 | 32.0 | 800 | 2.0366 | 0.7701 | 0.4668 |
| 0.5946 | 33.0 | 825 | 2.0026 | 0.7931 | 0.4478 |
| 0.5395 | 34.0 | 850 | 2.0010 | 0.8046 | 0.4544 |
| 0.5301 | 35.0 | 875 | 1.9332 | 0.8046 | 0.4500 |
| 0.5216 | 36.0 | 900 | 1.9965 | 0.8161 | 0.4966 |
| 0.497 | 37.0 | 925 | 1.9930 | 0.8161 | 0.4639 |
| 0.5149 | 38.0 | 950 | 1.9813 | 0.8161 | 0.4582 |
| 0.5022 | 39.0 | 975 | 1.9775 | 0.8046 | 0.4667 |
| 0.4892 | 40.0 | 1000 | 1.9643 | 0.8161 | 0.4688 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2