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Reviews Sentiment Analysis
R
Reviews Sentiment Analysis
Developed by juliensimon
This is a lightweight model based on the DistilBERT architecture, specifically fine-tuned for sentiment analysis tasks on English product reviews.
Downloads 114
Release Time : 3/2/2022
Model Overview
This model is a distilled version of BERT, retaining most of BERT's performance while significantly reducing the model size, making it suitable for sentiment analysis tasks, especially sentiment classification of product reviews.
Model Features
Lightweight and Efficient
40% smaller in size compared to the original BERT model while retaining 95% of its performance.
Optimized for Sentiment Analysis
Fine-tuned specifically for product review data, excelling in sentiment analysis tasks.
Fast Inference
The distilled architecture enables faster inference, making it suitable for production deployment.
Model Capabilities
Text Classification
Sentiment Analysis
Product Review Understanding
Use Cases
E-commerce
Product Review Sentiment Analysis
Automatically analyze whether user reviews of products are positive or negative.
Helps merchants quickly understand market feedback on products.
Review Quality Assessment
Identify the sentiment and usefulness of reviews.
Assists in filtering high-quality user feedback.
Market Research
Consumer Sentiment Monitoring
Large-scale analysis of consumer attitudes towards brands or products.
Provides insights into market trends.
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