cwe-parent-vulnerability-classification-microsoft-codebert-base
This model is a fine-tuned version of microsoft/codebert-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6351
- Accuracy: 0.6517
- F1 Macro: 0.3129
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 |
3.2599 |
1.0 |
25 |
3.2873 |
0.0225 |
0.0037 |
3.1436 |
2.0 |
50 |
3.3011 |
0.0562 |
0.0216 |
3.1168 |
3.0 |
75 |
3.3439 |
0.0449 |
0.0113 |
3.0315 |
4.0 |
100 |
3.3314 |
0.1461 |
0.0645 |
3.0604 |
5.0 |
125 |
3.3334 |
0.0899 |
0.0581 |
2.9746 |
6.0 |
150 |
3.3430 |
0.1124 |
0.0546 |
2.9773 |
7.0 |
175 |
3.3535 |
0.4157 |
0.0990 |
2.8666 |
8.0 |
200 |
3.2720 |
0.4831 |
0.2052 |
2.8196 |
9.0 |
225 |
3.2289 |
0.4270 |
0.1442 |
2.6704 |
10.0 |
250 |
3.1301 |
0.2584 |
0.1440 |
2.6964 |
11.0 |
275 |
3.0508 |
0.2809 |
0.1197 |
2.5442 |
12.0 |
300 |
2.9618 |
0.3596 |
0.1644 |
2.4519 |
13.0 |
325 |
2.9271 |
0.3596 |
0.1637 |
2.4064 |
14.0 |
350 |
2.8342 |
0.3933 |
0.2154 |
2.2469 |
15.0 |
375 |
2.7950 |
0.3596 |
0.2097 |
2.1662 |
16.0 |
400 |
2.7928 |
0.3596 |
0.1926 |
2.126 |
17.0 |
425 |
2.6786 |
0.4157 |
0.2223 |
2.0579 |
18.0 |
450 |
2.7615 |
0.3820 |
0.1987 |
1.8908 |
19.0 |
475 |
2.6469 |
0.4157 |
0.2015 |
1.8119 |
20.0 |
500 |
2.7396 |
0.4157 |
0.2097 |
1.8234 |
21.0 |
525 |
2.7319 |
0.3933 |
0.2101 |
1.6483 |
22.0 |
550 |
2.7024 |
0.4607 |
0.2504 |
1.7195 |
23.0 |
575 |
2.6693 |
0.4944 |
0.2345 |
1.5326 |
24.0 |
600 |
2.6387 |
0.5169 |
0.2341 |
1.5649 |
25.0 |
625 |
2.6509 |
0.6180 |
0.2934 |
1.4294 |
26.0 |
650 |
2.7232 |
0.6292 |
0.3175 |
1.4872 |
27.0 |
675 |
2.6745 |
0.6404 |
0.3005 |
1.3451 |
28.0 |
700 |
2.6499 |
0.6517 |
0.3100 |
1.296 |
29.0 |
725 |
2.6788 |
0.6517 |
0.3290 |
1.2962 |
30.0 |
750 |
2.6351 |
0.6517 |
0.3129 |
1.2969 |
31.0 |
775 |
2.6432 |
0.6742 |
0.3226 |
1.1886 |
32.0 |
800 |
2.6496 |
0.6742 |
0.3226 |
1.1426 |
33.0 |
825 |
2.6603 |
0.6742 |
0.3230 |
1.1833 |
34.0 |
850 |
2.6660 |
0.6742 |
0.3253 |
1.14 |
35.0 |
875 |
2.6588 |
0.6854 |
0.3477 |
1.0947 |
36.0 |
900 |
2.6501 |
0.6854 |
0.3477 |
1.0714 |
37.0 |
925 |
2.6654 |
0.6854 |
0.3477 |
1.0678 |
38.0 |
950 |
2.6454 |
0.6854 |
0.3477 |
1.0535 |
39.0 |
975 |
2.6375 |
0.6854 |
0.3481 |
1.0273 |
40.0 |
1000 |
2.6422 |
0.6854 |
0.3481 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2