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Twitter Xlm Roberta Emotion Es

Developed by daveni
A model based on the XLM-roBERTa-base architecture, fine-tuned for sentiment analysis on Spanish tweets, capable of classifying text into seven emotions
Downloads 5,638
Release Time : 3/2/2022

Model Overview

This model is designed for sentiment analysis of Spanish tweets, identifying seven emotion categories including anger, disgust, fear, happiness, sadness, surprise, and others.

Model Features

Multi-emotion Classification
Capable of identifying seven different emotion categories, including basic emotions and an 'other' category
Spanish Language Optimization
Specifically fine-tuned for Spanish tweets, ideal for analyzing Spanish social media content
Competition-validated Performance
Achieved first place in the EmoEvalEs competition at IberLEF 2021, with a macro-average F1 score of 71.70%

Model Capabilities

Spanish Text Classification
Social Media Sentiment Analysis
Multi-category Emotion Recognition

Use Cases

Social Media Analysis
Tweet Sentiment Monitoring
Analyze emotional tendencies in Spanish user tweets
Can identify seven different emotional states
Brand Sentiment Analysis
Assess public sentiment towards brands or products in Spanish-speaking markets
Academic Research
Affective Computing Research
Used for research related to Spanish-language affective computing
Performance validated in the EmoEvalEs competition
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