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Roberta Base Finetuned Yelp Polarity
This model is a binary sentiment analysis model fine-tuned on the RoBERTa base version, specifically designed for sentiment polarity classification of Yelp reviews.
Downloads 294
Release Time : 3/2/2022
Model Overview
This model is based on the RoBERTa architecture, fine-tuned on the Yelp polarity dataset, and used to determine the sentiment polarity (positive or negative) of Yelp reviews, achieving a test set accuracy of 98.08%.
Model Features
High accuracy
Achieves 98.08% accuracy on the Yelp polarity test set
Based on RoBERTa
Leverages RoBERTa's powerful language understanding capabilities for fine-tuning
Binary sentiment analysis
Specifically designed for classifying positive and negative sentiments in Yelp reviews
Model Capabilities
Text sentiment classification
Natural language understanding
Review sentiment analysis
Use Cases
Business analysis
Yelp review sentiment analysis
Automatically analyzes the sentiment tendencies of user reviews on the Yelp platform
Accurately identifies positive and negative reviews
Customer feedback analysis
Customer satisfaction assessment
Evaluates service quality by analyzing customer reviews
Quickly understands customer satisfaction trends
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