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Goemotions Bert

Developed by logasanjeev
Multilabel sentiment classification model fine-tuned from BERT-base-uncased, supporting 28 emotion recognitions
Downloads 55
Release Time : 4/12/2025

Model Overview

This model is specifically designed for multilabel sentiment classification of text, trained on Reddit comment data, capable of identifying multiple emotions expressed in text simultaneously

Model Features

Multilabel Emotion Recognition
Capable of identifying multiple emotions expressed in text simultaneously, rather than a single emotion
Optimized Prediction Threshold
Uses specially optimized classification thresholds to improve prediction accuracy
Focal Loss Function
Employs focal loss with gamma=2 to address class imbalance issues

Model Capabilities

Text Sentiment Analysis
Multilabel Classification
Emotion Recognition

Use Cases

Social Media Analysis
Comment Sentiment Analysis
Analyze emotions expressed in social media comments
Can identify 28 different emotions
Customer Feedback Analysis
Customer Feedback Classification
Perform sentiment classification on customer feedback
Can identify various emotions like gratitude, anger, etc.
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