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Locations Classifier

Developed by christopherxzyx
A lightweight text classification model based on DistilBERT for location classification tasks
Text Classification
Transformers
Open Source License:Apache-2.0#Lightweight BERT#Location Classification#Efficient Fine-tuning
Downloads 28
Release Time : 3/25/2025

Model Overview

This model is a text classifier fine-tuned from DistilBERT-base-uncased, specifically designed for location-related classification tasks. It achieved 78.95% accuracy on the evaluation set.

Model Features

Lightweight and Efficient
Based on the DistilBERT architecture, it is 40% smaller than standard BERT models while retaining 97% of the language understanding capability
Fast Inference
The distilled model design makes its inference speed 60% faster than the original BERT model
Transfer Learning
Fine-tuned on general language understanding, suitable for domain-specific classification tasks

Model Capabilities

Text Classification
Location Recognition
Short Text Analysis

Use Cases

Geographic Information Processing
Location Name Classification
Identify and classify location names mentioned in text
Achieved 78.95% accuracy on the test set
Content Moderation
Geographic Location Identification
Identify and classify geographic location information from user-generated content
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