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---
library_name: transformers
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cwe-parent-vulnerability-classification-huggingface-CodeBERTa-small-v1
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-huggingface-CodeBERTa-small-v1
This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3718
- Accuracy: 0.7753
- F1 Macro: 0.3835
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.2521 | 1.0 | 25 | 3.3015 | 0.0112 | 0.0057 |
| 3.037 | 2.0 | 50 | 3.2608 | 0.3258 | 0.1301 |
| 3.0191 | 3.0 | 75 | 3.3140 | 0.3146 | 0.0568 |
| 2.8876 | 4.0 | 100 | 3.2111 | 0.2472 | 0.2190 |
| 2.7888 | 5.0 | 125 | 3.1305 | 0.2360 | 0.2394 |
| 2.6762 | 6.0 | 150 | 3.1370 | 0.3146 | 0.1503 |
| 2.5905 | 7.0 | 175 | 3.0446 | 0.3933 | 0.2144 |
| 2.4173 | 8.0 | 200 | 2.9769 | 0.3933 | 0.1999 |
| 2.2706 | 9.0 | 225 | 2.9704 | 0.3708 | 0.1825 |
| 2.1355 | 10.0 | 250 | 2.9071 | 0.3820 | 0.2097 |
| 2.0722 | 11.0 | 275 | 2.9189 | 0.4382 | 0.1855 |
| 1.8111 | 12.0 | 300 | 2.7873 | 0.4157 | 0.2257 |
| 1.7056 | 13.0 | 325 | 2.7584 | 0.4607 | 0.2217 |
| 1.6693 | 14.0 | 350 | 2.7394 | 0.5169 | 0.2370 |
| 1.496 | 15.0 | 375 | 2.6647 | 0.5506 | 0.2630 |
| 1.3093 | 16.0 | 400 | 2.6477 | 0.5843 | 0.2644 |
| 1.251 | 17.0 | 425 | 2.6355 | 0.6067 | 0.2654 |
| 1.1316 | 18.0 | 450 | 2.5521 | 0.6404 | 0.3000 |
| 1.049 | 19.0 | 475 | 2.5236 | 0.6404 | 0.2951 |
| 0.9441 | 20.0 | 500 | 2.5538 | 0.6404 | 0.2957 |
| 0.8752 | 21.0 | 525 | 2.5020 | 0.6742 | 0.3259 |
| 0.7623 | 22.0 | 550 | 2.4927 | 0.6966 | 0.3339 |
| 0.7938 | 23.0 | 575 | 2.4595 | 0.7079 | 0.3413 |
| 0.6321 | 24.0 | 600 | 2.4564 | 0.7079 | 0.3369 |
| 0.6245 | 25.0 | 625 | 2.4537 | 0.7191 | 0.3631 |
| 0.5502 | 26.0 | 650 | 2.4470 | 0.7416 | 0.3764 |
| 0.5805 | 27.0 | 675 | 2.4588 | 0.7528 | 0.3849 |
| 0.5042 | 28.0 | 700 | 2.4243 | 0.7640 | 0.3930 |
| 0.464 | 29.0 | 725 | 2.4051 | 0.7640 | 0.3930 |
| 0.4349 | 30.0 | 750 | 2.4361 | 0.7753 | 0.4034 |
| 0.4347 | 31.0 | 775 | 2.4062 | 0.7640 | 0.3906 |
| 0.3953 | 32.0 | 800 | 2.3939 | 0.7753 | 0.3835 |
| 0.3775 | 33.0 | 825 | 2.4091 | 0.7865 | 0.3958 |
| 0.3948 | 34.0 | 850 | 2.4018 | 0.7865 | 0.3958 |
| 0.348 | 35.0 | 875 | 2.3718 | 0.7753 | 0.3835 |
| 0.3328 | 36.0 | 900 | 2.3843 | 0.7865 | 0.3947 |
| 0.3291 | 37.0 | 925 | 2.3843 | 0.7978 | 0.3965 |
| 0.3211 | 38.0 | 950 | 2.3764 | 0.7865 | 0.3958 |
| 0.307 | 39.0 | 975 | 2.3822 | 0.7978 | 0.3975 |
| 0.3055 | 40.0 | 1000 | 2.3855 | 0.7978 | 0.3965 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
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