Rajveerx11/email-classifier

📧 Email Classifier (Phi-3 Mini Fine-Tuned GGUF)

🧠 Model Overview

This model is a fine-tuned version of Phi-3 Mini (4K Instruct) optimized for email classification tasks such as spam detection and categorization.

• Base Model: Phi-3 Mini 4K Instruct
• Fine-tuning: Supervised fine-tuning on email dataset
• Format: GGUF (for efficient local inference)
• Quantization: Q5_K_M

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📚 Dataset

The model was trained on:

• Dataset: json22322/email-classifier
• Contains labeled email samples for classification tasks (e.g., spam vs non-spam)

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🎯 Task

• Email classification
• Spam detection
• Priority categorization

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⚙️ Usage

Using llama.cpp

./main -m Phi-3-mini-4k-instruct-Q5_K_M.gguf -p "Classify this email: Subject: ... Body: ..."

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🧪 Example

Input:

Subject: Win a free iPhone now!!!
Body: Click here to claim your reward.

Output:

Spam

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⚠️ Limitations

• Performance depends on dataset quality
• May not generalize to unseen domains
• Sensitive to prompt phrasing

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📦 Files

File	Description
*.gguf	Quantized fine-tuned model

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📌 Notes

• Optimized for local inference (CPU-friendly)
• Compatible with llama.cpp and GGUF runtimes

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📜 License

Same as base model (Phi-3).

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🙌 Acknowledgements

• Microsoft for Phi-3
• Hugging Face
• llama.cpp

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