Email Intent Classifier
NLP model automatically classifying emails based on intent

Problem

Email overload is a significant problem in businesses. Manually sorting and prioritizing emails takes valuable time from employees. Automatically categorizing emails by intent helps with -

Prioritization of urgent matters
Routing to appropriate departments
Providing quick responses
Managing workflow more efficiently

Solution

This app uses a fine-tuned DeBERTa transformer model to classify emails into different intent categories:

• Question: Emails asking for information Request: Emails asking for action or approval
• Information: Emails sharing knowledge or updates Scheduling: Emails about setting up meetings or events Other: Any other intent

How to Use

Enter or paste an email text into the input box with subject
Click "Submit"
View the predicted intent categories and their probability/confidence scores

Try the live demo: Email Classifier Demo

Model Details

This model was fine-tuned on an email dataset with the following specifications: Base Model: DistilBERT (base-uncased) Training Dataset: Synthetic dataset of categorized emails across 6 intent categories

Limitations

Very short or ambiguous emails may be classified with lower confidence Emails with multiple intents may be classified based on the dominant intent

Deployment

This application is deployed using Hugging Face Spaces with Gradio. The model weights are stored in the Hugging Face Model Hub.

Technologies Used

• Python
• Hugging Face Transformers
• PyTorch
• Pandas
• Numpy