DistilBERT Phishing Classifier — Phishing Email Dataset
Fine-tuned distilbert-base-uncased for binary phishing/spam classification,
trained on the Phishing Email Dataset 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)
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