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Just Another Emotion Classifier

Developed by bdotloh
This is a Transformer-based emotion classification model capable of identifying 32 different emotions in input text.
Downloads 92
Release Time : 9/19/2022

Model Overview

This model is designed for emotion classification tasks, predicting probability distributions across 32 predefined emotions. Built upon a fine-tuned distilbert-base-uncased model trained on the go-emotions dataset.

Model Features

Multi-emotion Classification
Capable of recognizing 32 distinct emotion categories
Transformer-based
Utilizes efficient distilbert architecture to reduce computational requirements while maintaining performance
Cross-dataset Training
Trained on combined go-emotions and empathetic dialogue datasets

Model Capabilities

Text Sentiment Analysis
Multi-label Classification
Emotion Probability Prediction

Use Cases

Customer Service
Customer Feedback Analysis
Analyze emotional tendencies in customer feedback
Helps identify dissatisfied customers for priority handling
Social Media
Public Sentiment Monitoring
Track changes in public emotions on social media
Provides real-time emotional trend analysis
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