PhishLlama LoRA: A LoRA Fine-Tuned Model for Phishing URL Detection
Model Details
- Model Name: PhishLlama LoRA
- Developed by: Najmul Hasan
- Model Type: LoRA fine-tuned version of
meta-llama/Llama-3.2-1B
- Language: English
- License: Apache 2.0
- Base Model:
meta-llama/Llama-3.2-1B
- Pipeline Tag: Text Classification
- Library: Transformers
- Dataset Used: PhiUSIIL Phishing URL (Website) - Reduced Dataset
- Training Data Reduction: The dataset was balanced and reduced to 50,000 samples while maintaining class distribution.
Model Description
PhishLlama LoRA is a LoRA fine-tuned version of Llama-3.2-1B, designed for phishing URL detection. It classifies URLs as either legitimate (1) or phishing (0).
The model was trained using a reduced version of the PhiUSIIL Phishing URL dataset to improve training speed, computational efficiency, and maintain predictive performance.
Performance
- Accuracy: 59%
- Macro F1-score: 0.58
Confusion Matrix:
| Prediction / Actual | Phishing (0) | Legitimate (1) |
|---|
| Phishing (0) | 3668 (True Negative) | 2131 (False Negative) |
| Legitimate (1) | 1954 (False Positive) | 2247 (True Positive) |
- True Positive (TP): 2247 (Legitimate detected as Legitimate)
- False Positive (FP): 1954 (Phishing misclassified as Legitimate)
- True Negative (TN): 3668 (Phishing detected correctly)
- False Negative (FN): 2131 (Legitimate misclassified as Phishing)
