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: 4.0524
- Accuracy: 0.3448
- F1: 0.0285
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 |
|---|---|---|---|---|---|
| 4.6485 | 1.0 | 20 | 4.3362 | 0.2184 | 0.0081 |
| 4.1158 | 2.0 | 40 | 4.2805 | 0.2184 | 0.0081 |
| 4.0339 | 3.0 | 60 | 4.2431 | 0.2299 | 0.0132 |
| 3.928 | 4.0 | 80 | 4.1519 | 0.3103 | 0.0257 |
| 3.7985 | 5.0 | 100 | 4.0524 | 0.3448 | 0.0285 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2