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Beto Sentiment Analysis Spanish

Developed by ignacio-ave
A sentiment analysis model based on BETO (Spanish version of BERT), supporting sentiment classification for Spanish text.
Downloads 1,708
Release Time : 9/17/2023

Model Overview

This model is specifically designed for sentiment analysis of Spanish text, capable of classifying text into positive, neutral, or negative sentiments.

Model Features

Spanish Language Optimization
Optimized specifically for Spanish text based on the BETO architecture.
Three-class Sentiment Analysis
Accurately identifies positive, neutral, and negative sentiments in text.
High Accuracy
Achieves 67.59% accuracy in three-class tasks, with particularly excellent performance in identifying positive sentiments.

Model Capabilities

Spanish Text Processing
Sentiment Classification
Natural Language Understanding

Use Cases

Social Media Analysis
User Comment Sentiment Analysis
Analyzes sentiment tendencies in Spanish social media user comments
Can identify 77% of positive comments and 72% of negative comments
Customer Feedback Analysis
Product Review Classification
Automatically classifies sentiment tendencies in Spanish customer reviews
Helps quickly identify dissatisfied customers
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