umayer16/distilbert-phishing-spam-detection

DistilBERT Phishing Classifier — Spam Detection

Fine-tuned distilbert-base-uncased for binary phishing/spam classification, trained on the Spam Detection dataset as part of an empirical study on adversarial robustness (homoglyph substitution vs. synonym replacement attacks).

• Training: 3 epochs, batch size 32, AdamW, lr=2e-5
• Baseline accuracy: see paper Table/Fig. 1
• Part of: "Adversarial Robustness of NLP-Based Phishing Email Classifiers: A Multi-Dataset Empirical Study" (CJSJ 2026, Muktadir Arif)