B

Bert Base Uncased Emotion

Developed by bhadresh-savani
BERT-based sentiment analysis model fine-tuned on Twitter sentiment dataset for text emotion classification
Downloads 17.20k
Release Time : 3/2/2022

Model Overview

This model is a BERT-based pre-trained model specifically fine-tuned for sentiment analysis tasks, capable of identifying six basic emotions in text: sadness, joy, love, anger, fear, and surprise.

Model Features

High accuracy
Achieves 92.65% accuracy in emotion classification tasks
Multi-emotion recognition
Capable of identifying six different emotion categories
Transformer-based
Utilizes BERT bidirectional encoder architecture with strong contextual understanding capabilities

Model Capabilities

Text classification
Sentiment analysis
Natural language understanding

Use Cases

Social media analysis
Tweet sentiment analysis
Analyze the sentiment tendencies of Twitter users' tweets
Accurately identifies six basic emotions
Customer feedback analysis
Product review sentiment classification
Automatically classify customer reviews' sentiment towards products
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
Š 2025AIbase