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Distilbert Base Uncased Go Emotion
D
Distilbert Base Uncased Go Emotion
Developed by bhadresh-savani
A text classification model based on DistilBERT for multi-label sentiment classification tasks
Downloads 17
Release Time : 3/2/2022
Model Overview
This model is a lightweight text classification model based on the DistilBERT architecture, specifically designed for multi-label sentiment classification tasks, capable of identifying multiple emotions in text.
Model Features
Lightweight Architecture
Based on the DistilBERT architecture, it is more lightweight than standard BERT models and offers faster inference speed.
Multi-label Classification
Capable of identifying multiple emotions in text simultaneously.
High Accuracy
Achieves 96.2% accuracy on evaluation datasets.
Model Capabilities
Text Sentiment Analysis
Multi-label Classification
Use Cases
Sentiment Analysis
Social Media Sentiment Monitoring
Analyze sentiment tendencies in social media posts
Can identify multiple emotion labels
Customer Feedback Analysis
Analyze sentiment tendencies in customer reviews
Helps understand customer satisfaction
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