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:

Prediction / Actual Phishing (0) Legitimate (1)
Phishing (0) 129 (True Negative) 5493 (False Positive)
Legitimate (1) 536 (False Negative) 3842 (True Positive)
  • 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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