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Fpsentiment Model
DistilBERT is a lightweight distilled version of BERT, retaining 97% of BERT's performance while being 40% smaller and 60% faster in inference.
Downloads 16
Release Time : 1/10/2025
Model Overview
A distilled model based on BERT for text classification tasks, particularly suitable for sentiment analysis on the Rotten Tomatoes movie review dataset.
Model Features
Efficient and Lightweight
Through knowledge distillation, the model is 40% smaller than the original BERT and 60% faster in inference.
High Performance
Retains 97% of the original BERT model's performance.
Specialized for Text Classification
Specially optimized for text classification tasks such as sentiment analysis.
Model Capabilities
Text Classification
Sentiment Analysis
Natural Language Understanding
Use Cases
Movie Review Analysis
Rotten Tomatoes Review Sentiment Analysis
Analyze sentiment tendencies (positive/negative) in movie reviews
Achieves high accuracy on the Rotten Tomatoes dataset
Social Media Monitoring
User Comment Sentiment Analysis
Automatically classify sentiment in user comments on social media
Can process large volumes of text data in real-time
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