---
license: mit
datasets:
- Rishik001/URLs
metrics:
- accuracy
base_model:
- google-bert/bert-base-uncased
library_name: transformers
---
# Model Card: Fine-Tuned Phishing URL Classifier

## Model Details

**Model Name:** Fine-Tuned Phishing URL Classifier  
**Base Model:** BERT base uncased (Hugging Face Transformers)  
**Library Used:** Transformers  
**License:** MIT  
**Datasets:** [Rishik001/URLs](https://huggingface.co/datasets/Rishik001/URLs)  

## Model Description
This model has been fine-tuned for phishing URL classification. It is trained to classify URLs as either phishing or benign using a dataset of labeled URLs. The fine-tuning process leverages a pre-trained BERT model, adapting it to the domain-specific task of URL classification.

## Intended Use
This model is intended for cybersecurity applications, specifically for detecting phishing URLs. It can be used in security systems to filter out malicious links and protect users from cyber threats.

## Training Configuration
**Hyperparameters:**
- Learning Rate: 2e-5
- Per Device Train Batch Size: 16
- Per Device Eval Batch Size: 16
- Number of Training Epochs: 3
- Weight Decay: 0.01
- Evaluation Strategy: Epoch
- Save Strategy: Epoch
- Load Best Model at End: True

## Training Performance
| Epoch | Training Loss | Validation Loss | Accuracy | AUC |
|-------|--------------|----------------|----------|-----|
| 1     | 0.365300     | 0.315958       | 0.868000 | 0.941 |
| 2     | 0.344800     | 0.288597       | 0.882000 | 0.949 |
| 3     | 0.342000     | 0.284374       | 0.880000 | 0.951 |

## Evaluation Results
The model was evaluated on a test set, and the results are as follows:

- **Evaluation Loss:** 0.290662
- **Evaluation Accuracy:** 87.5%
- **Evaluation AUC:** 0.949
- **Evaluation Runtime:** 60.608 seconds
- **Evaluation Samples per Second:** 164.995
- **Evaluation Steps per Second:** 10.312

## Citation
If you use this model in your work, please cite it appropriately:
```
@misc{phishingurlclassifier,
  title={Fine-Tuned Phishing URL Classifier},
  authors={S Adhit and M Rishikesh},
  year={2025},
  publisher={Hugging Face Transformers}
}
```