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Complaints Classifier
C
Complaints Classifier
Developed by jpsteinhafel
A text classification model fine-tuned on distilbert-base-uncased for complaint content classification, achieving 94.2% accuracy
Downloads 41
Release Time : 2/7/2024
Model Overview
This model is a text classifier specifically designed for classifying complaint content. Based on the DistilBERT architecture and fine-tuned on a specific dataset, it delivers high classification accuracy.
Model Features
High Accuracy
Achieves 94.2% classification accuracy on the evaluation set
Lightweight
Based on DistilBERT architecture, more lightweight than standard BERT models
Fast Inference
Distilled model design enables faster inference speed
Model Capabilities
Text Classification
Complaint Content Analysis
Natural Language Understanding
Use Cases
Customer Service
Automatic Complaint Classification
Automatically categorizes customer complaints into predefined categories
94.2% accuracy
Data Analysis
Complaint Trend Analysis
Analyzes complaint type distribution and trends through classification results
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