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Roberta Base Emotion

Developed by bhadresh-savani
A sentiment analysis model based on the RoBERTa architecture, fine-tuned on Twitter sentiment datasets for text sentiment classification.
Downloads 703
Release Time : 3/2/2022

Model Overview

This model is an improved version based on the RoBERTa architecture, achieving more robust optimization during pre-training through better hyperparameter selection, specifically designed for sentiment analysis tasks.

Model Features

High-performance Sentiment Analysis
Performs exceptionally well on Twitter sentiment datasets, achieving an accuracy of 93.1%.
Based on RoBERTa Architecture
Utilizes the RoBERTa-base architecture with optimized hyperparameters for robust performance.
Multi-emotion Classification
Capable of identifying multiple emotion categories, including joy, sadness, anger, fear, love, and surprise.

Model Capabilities

Text Classification
Sentiment Analysis
Multi-emotion Recognition

Use Cases

Social Media Analysis
Twitter Sentiment Analysis
Analyze text content on Twitter to identify user sentiment tendencies.
Accuracy 93.1%, F1 score 93.1%
Customer Feedback Analysis
Product Review Sentiment Analysis
Analyze customer reviews of products to identify positive and negative sentiments.
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