metadata
library_name: transformers
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: vuln-patch-cwe-guesser-model-microsoft-codebert-base
results: []
vuln-patch-cwe-guesser-model-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: 3.4697
- Accuracy: 0.4535
- F1: 0.0330
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: 3e-05
- train_batch_size: 40
- eval_batch_size: 40
- 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: 5
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 4.6623 | 1.0 | 20 | 4.0312 | 0.3023 | 0.0122 |
| 4.1733 | 2.0 | 40 | 3.9241 | 0.3721 | 0.0265 |
| 4.0474 | 3.0 | 60 | 3.8249 | 0.4419 | 0.0324 |
| 3.8755 | 4.0 | 80 | 3.5504 | 0.4651 | 0.0357 |
| 3.6768 | 5.0 | 100 | 3.4697 | 0.4535 | 0.0330 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2