Chiraag-P-V/E-commerce-customer-query-classifier

🛍️ E-commerce Customer Support Classification

Model Description

This model is a fine-tuned version of distilbert-base-uncased for classifying e-commerce customer complaints and queries into multiple categories. It was trained on the Ataur77/ecommerce-customer-support dataset and can identify a wide range of e-commerce support issues.

The goal is to help customer service teams automatically route tickets to the correct department for faster resolution.

Categories

The model can classify queries into the following 15 categories:

Intended Uses

• —Customer Support Automation: Automatically route customer support tickets.
• —CRM Integration: Enhance ticket management systems.
• —Analytics: Categorize historical support data for insights.

Limitations

• —Works best with English-language customer queries.
• —Performance depends on dataset quality — the training dataset is small, so real-world accuracy may vary.

Quick Usage

from transformers import pipeline

# Load the model from Hugging Face
classifier = pipeline(
    "text-classification",
    model="Chiraag-P-V/E-commerce-customer-query-classifier"
)

# Example query
query = "I have not received my delivery yet."
result = classifier(query)

print(result)