PhishLlama_QLoRA

PhishLlama QLoRA: A QLoRA Fine-Tuned Model for Phishing URL Detection

Model Details

• Model Name: PhishLlama QLoRA
• Developed by: Najmul Hasan
• Model Type: QLoRA 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 QLoRA is a QLoRA 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 enable fine-tuning with lower memory requirements while maintaining predictive capability.

Performance

• Accuracy: 40%
• Macro F1-score: 0.30

Confusion Matrix:

• True Positive (TP): 3842 (Legitimate detected as Legitimate)
• False Positive (FP): 5493 (Phishing misclassified as Legitimate)
• True Negative (TN): 129 (Phishing detected correctly)
• False Negative (FN): 536 (Legitimate misclassified as Phishing)

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