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---
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: []
---
<!-- 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](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6858
- Accuracy: 0.6126
- F1 Macro: 0.3737
## 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_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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.078 | 1.0 | 237 | 3.0510 | 0.1776 | 0.0529 |
| 2.4726 | 2.0 | 474 | 2.2886 | 0.4398 | 0.2407 |
| 2.2031 | 3.0 | 711 | 1.9511 | 0.5185 | 0.3141 |
| 1.7872 | 4.0 | 948 | 1.7893 | 0.5638 | 0.3511 |
| 1.4324 | 5.0 | 1185 | 1.7492 | 0.6305 | 0.3805 |
| 1.2675 | 6.0 | 1422 | 1.6858 | 0.6126 | 0.3737 |
| 1.0437 | 7.0 | 1659 | 1.7359 | 0.6675 | 0.4296 |
| 0.8699 | 8.0 | 1896 | 1.7641 | 0.6746 | 0.4246 |
| 0.8832 | 9.0 | 2133 | 1.8097 | 0.6746 | 0.4444 |
| 0.8027 | 10.0 | 2370 | 1.8753 | 0.6698 | 0.4380 |
| 0.4583 | 11.0 | 2607 | 1.8919 | 0.6830 | 0.4473 |
| 0.5493 | 12.0 | 2844 | 1.8456 | 0.7080 | 0.4915 |
| 0.4808 | 13.0 | 3081 | 1.9593 | 0.6841 | 0.4555 |
| 0.4466 | 14.0 | 3318 | 2.0736 | 0.6865 | 0.4454 |
| 0.2989 | 15.0 | 3555 | 2.1972 | 0.6961 | 0.4474 |
| 0.255 | 16.0 | 3792 | 2.2513 | 0.7008 | 0.4638 |
| 0.2474 | 17.0 | 4029 | 2.2991 | 0.7223 | 0.4609 |
| 0.1648 | 18.0 | 4266 | 2.4582 | 0.7128 | 0.4614 |
| 0.2112 | 19.0 | 4503 | 2.5944 | 0.7247 | 0.4714 |
| 0.1185 | 20.0 | 4740 | 2.5292 | 0.7128 | 0.4557 |
| 0.1453 | 21.0 | 4977 | 2.6173 | 0.7104 | 0.4466 |
| 0.1126 | 22.0 | 5214 | 2.7072 | 0.7104 | 0.4461 |
| 0.0872 | 23.0 | 5451 | 2.8997 | 0.7235 | 0.4577 |
| 0.0768 | 24.0 | 5688 | 2.8199 | 0.7294 | 0.4623 |
| 0.0643 | 25.0 | 5925 | 2.9228 | 0.7211 | 0.4587 |
| 0.0828 | 26.0 | 6162 | 3.0185 | 0.7330 | 0.4774 |
| 0.0407 | 27.0 | 6399 | 3.1037 | 0.7211 | 0.4586 |
| 0.0386 | 28.0 | 6636 | 3.1938 | 0.7235 | 0.4622 |
| 0.0321 | 29.0 | 6873 | 3.2786 | 0.7318 | 0.4612 |
| 0.0189 | 30.0 | 7110 | 3.4453 | 0.7330 | 0.4559 |
| 0.0223 | 31.0 | 7347 | 3.3558 | 0.7366 | 0.4583 |
| 0.0255 | 32.0 | 7584 | 3.3787 | 0.7354 | 0.4682 |
| 0.0123 | 33.0 | 7821 | 3.4288 | 0.7306 | 0.4633 |
| 0.0128 | 34.0 | 8058 | 3.4361 | 0.7366 | 0.4645 |
| 0.0201 | 35.0 | 8295 | 3.6213 | 0.7235 | 0.4559 |
| 0.014 | 36.0 | 8532 | 3.7080 | 0.7247 | 0.4554 |
| 0.0159 | 37.0 | 8769 | 3.6249 | 0.7330 | 0.4622 |
| 0.027 | 38.0 | 9006 | 3.6598 | 0.7294 | 0.4604 |
| 0.0086 | 39.0 | 9243 | 3.7176 | 0.7342 | 0.4637 |
| 0.0096 | 40.0 | 9480 | 3.7223 | 0.7306 | 0.4614 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
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