Senior Project Notice

This repository was created for a senior project in ENGT 375 Applied Machine Learning at Old Dominion University. It is provided for educational and research demonstration purposes only. It is not intended for production use, security filtering, or making real-world spam/phishing decisions. Always use established security tools for operational email protection.

Shared References

Papers and documentation that apply to more than one of the three spam-classifier projects live in this folder. Project-specific references live inside each project's own docs/references/ folder.

How to browse

Double-click how-to.html to open the full reference index in your browser. It has clickable links to every local PDF and HTML guide, plus online fallbacks.

What's in here

Papers

• papers/Attention_Vaswani2017.pdf — The original Transformer paper
• papers/LoRA_Hu2021.pdf — LoRA fine-tuning technique (used by MLX + Liquid)
• papers/QLoRA_Dettmers2023.pdf — Quantized LoRA (applies to the MLX project's 4-bit model)
• papers/PEFT_Survey.pdf — Han 2024 survey of parameter-efficient fine-tuning methods

Guides (HTML, open in browser)

• guides/HuggingFace_LLM_FullFineTune_Tutorial.html — LearnHuggingFace full fine-tune walkthrough
• guides/HuggingFace_PEFT_Quicktour.html — HF PEFT quickstart
• guides/HuggingFace_PEFT_LoRA_Conceptual.html — What LoRA r, alpha, target_modules mean
• guides/HuggingFace_TRL_SFTTrainer.html — TRL SFTTrainer reference (used by Liquid project)
• guides/HuggingFace_ChatTemplates.html — tokenizer.apply_chat_template() reference
• guides/Unsloth_LoRA_Hyperparameters.html — Practical LoRA hyperparameter advice

Per-project references

Each project has its own folder with project-specific material (model tech reports, library docs, XAI papers, etc.):

Project	Reference folder
MLX	../spam-classifier-mlx/docs/references/
Liquid	../spam-classifier-liquid/docs/references/
XAI	../spam-xai-project/docs/references/

Each contains its own how-to.html.

Re-downloading or updating

If you want to refresh any of the downloaded files (e.g., HuggingFace updated their docs), re-run the fetch script from the LLM Project root:

bash fetch_references.sh

The script is safe to re-run — it overwrites existing files.