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Distilbert Base Uncased Sst5 All Train
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Distilbert Base Uncased Sst5 All Train
Developed by SetFit
This model is a text classification model fine-tuned on the SST5 dataset based on the DistilBERT base model, with an accuracy of 50.45%.
Downloads 131
Release Time : 3/2/2022
Model Overview
A lightweight BERT model for text classification, suitable for natural language processing tasks such as sentiment analysis.
Model Features
Lightweight Architecture
Based on the DistilBERT architecture, smaller and faster than standard BERT models
Sentiment Analysis Capability
Optimized for 5-level sentiment classification tasks (SST5)
Efficient Training
Uses mixed-precision training for high training efficiency
Model Capabilities
Text Classification
Sentiment Analysis
Use Cases
Sentiment Analysis
Product Review Analysis
Analyze the sentiment tendencies of user reviews
Can identify 5 different levels of sentiment
Social Media Monitoring
Monitor user sentiment on social media
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