Industry Classification
| Property | Value |
|---|---|
| Architecture | DistilBERT |
| Framework Support | PyTorch, TensorFlow |
| License | MIT |
| Training Data | 7000 Indian company descriptions |
What is industry-classification?
The industry-classification model is a specialized DistilBERT-based classifier designed to categorize business descriptions into one of 62 distinct industry tags. Developed by sampathkethineedi, this model leverages transformer architecture to provide accurate industry classification for business descriptions, particularly focused on Indian companies.
Implementation Details
The model is implemented using both PyTorch and TensorFlow frameworks, making it versatile for different development environments. It utilizes the DistilBERT architecture, a lightweight version of BERT that maintains good performance while reducing computational requirements.
- Multi-class classification capability across 62 industry categories
- Built on DistilBERT architecture for efficient processing
- Trained on 7,000 labeled business descriptions
- Supports both PyTorch and TensorFlow implementations
Core Capabilities
- Accurate classification of business descriptions into industry categories
- High-confidence predictions with score indicators
- Support for English language text processing
- Efficient processing through distilled BERT architecture
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in Indian business context classification, trained specifically on Indian company data, making it particularly effective for analyzing businesses in the Indian market context.
Q: What are the recommended use cases?
The model is ideal for automated industry classification of companies, market research, business analytics, and financial sector applications where understanding company classifications is crucial. However, it's important to note that its training focuses on Indian companies, which may limit its effectiveness for international business classifications.
