---
library_name: transformers
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
model-index:
- name: Vulnerability_Detection_Using_CodeBERT
  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. -->

# Vulnerability_Detection_Using_CodeBERT

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0740
- Accuracy: 1.0
- Auc: 1.0
- Precision: 1.0

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|
| 0.2971        | 1.0   | 26   | 0.1815          | 0.925    | 1.0 | 0.81      |
| 0.2407        | 2.0   | 52   | 0.1349          | 0.981    | 1.0 | 0.944     |
| 0.2619        | 3.0   | 78   | 0.1668          | 0.887    | 1.0 | 0.739     |
| 0.2207        | 4.0   | 104  | 0.1081          | 1.0      | 1.0 | 1.0       |
| 0.1543        | 5.0   | 130  | 0.1037          | 0.981    | 1.0 | 1.0       |
| 0.1428        | 6.0   | 156  | 0.0974          | 0.981    | 1.0 | 0.944     |
| 0.1598        | 7.0   | 182  | 0.0916          | 0.981    | 1.0 | 1.0       |
| 0.1324        | 8.0   | 208  | 0.1024          | 0.981    | 1.0 | 0.944     |
| 0.1445        | 9.0   | 234  | 0.0726          | 1.0      | 1.0 | 1.0       |
| 0.1287        | 10.0  | 260  | 0.0740          | 1.0      | 1.0 | 1.0       |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1