Bert Base Uncased Yelp Polarity
This model is a fine-tuned version of bert-base-uncased on the yelp_polarity dataset for text classification tasks, achieving an accuracy of 95.16%.
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Release Time : 3/2/2022
Model Overview
A text classification model based on the BERT architecture, specifically optimized for sentiment analysis (positive/negative) of Yelp reviews.
Model Features
High accuracy
Achieves 95.16% accuracy on Yelp review sentiment analysis tasks
BERT architecture
Fine-tuned based on the powerful BERT-base-uncased model
Sentiment analysis
Specifically optimized for binary classification (positive/negative) of review sentiments
Model Capabilities
Text classification
Sentiment analysis
Review rating prediction
Use Cases
Business analysis
Restaurant review analysis
Analyze sentiment tendencies of restaurant reviews on platforms like Yelp
Accurately distinguishes over 95% of positive/negative reviews
Customer feedback analysis
Product review classification
Automatically classify sentiment of product reviews on e-commerce platforms
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