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Bert Base Uncased Yelp Polarity

Developed by fabriceyhc
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%.
Downloads 76
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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