smart-category-detector-v1

Lightweight Transformer-based classifier for short text categorization (60 categories)

smart-category-detector-v1 is a multi-class text classification model designed to predict one of 60 categories from short text inputs such as:

• product titles
• marketplace listings
• event announcements
• restaurant menu items with prices

The model is optimized for fast inference and practical categorization tasks.

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Model Details

Field Value

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Developer Salim Al Sazu Hugging Face salimalsazu Model Type DistilBERT Fine-tuned Base Model distilbert-base-uncased Task Multi-class Text Classification Categories 60 Training Samples ~600,000 Language English License MIT

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Training Dataset

The model was trained on a curated dataset of approximately 600,000 samples containing short text entries mapped to one of 60 categories.

Dataset Structure

Column Description

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text Short input text category Target classification label

Example:

Samsung Galaxy S24 Ultra 512GB Mobile -> smartphones
Dhaka International Book Fair 2026 -> book_fair
Jamboo Burger Tk 220 -> burgers
Lenovo ThinkPad X1 Carbon Laptop -> laptops
Chicken Biryani Tk 180 -> biryani

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Dataset Distribution

The dataset is divided into three main groups, each containing 20 categories.

Event Categories (20) --- ~200,000 samples

sports
music
tech_conference
education_seminar
business_summit
startup_pitch
job_fair
art_exhibition
cultural_festival
religious_event
political_rally
charity_event
workshop
webinar
networking_event
book_fair
food_festival
fashion_show
award_ceremony
hackathon

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Product Categories (20) --- ~200,000 samples

electronics
smartphones
laptops
fashion_clothing
shoes
beauty_cosmetics
grocery_food
furniture
home_appliances
kitchen_items
sports_equipment
books
toys
baby_products
health_supplements
automotive
gaming
jewelry
office_supplies
pet_products

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Restaurant / Menu Categories (20) --- ~200,000 samples

burgers
pizza
sandwich_wraps
fries_sides
fried_snacks
street_food
biryani
rice_dishes
noodles_pasta
curries
bbq_grill
seafood_dishes
breakfast_items
soups_salads
cakes_pastries
ice_cream
traditional_sweets
coffee_tea
soft_drinks
shakes_smoothies

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Example Predictions

Input Prediction

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Samsung Galaxy S24 Ultra 512GB Mobile smartphones Dhaka International Book Fair 2026 book_fair Jamboo Burger Tk 220 burgers HP Pavilion RTX 4060 Gaming Laptop laptops Beef Burger Combo Tk 350 burgers

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Quick Start

from transformers import pipeline

clf = pipeline(
    "text-classification",
    model="salimalsazu/smart-category-detector-v1",
    top_k=5
)

print(clf("Samsung Galaxy S24 Ultra 512GB Mobile"))
print(clf("Dhaka International Book Fair 2026"))
print(clf("Jamboo Burger Tk 220"))

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Limitations

• Works best with short text
• Designed primarily for English text
• Mixed-language inputs may reduce accuracy
• Limited to 60 predefined categories
• Unknown categories may be mapped to the closest label

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Future Improvements

Potential improvements include:

• adding real-world marketplace data
• improving Bangla language support
• increasing spelling robustness
• adding an "unknown" label
• publishing benchmark evaluation metrics

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Citation

Salim Al Sazu
smart-category-detector-v1