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Beto Sentiment Analysis Es

Developed by edumunozsala
A fine-tuned model optimized for Spanish sentiment analysis, based on BETO (a Spanish pre-trained BERT model), suitable for text sentiment classification tasks such as movie reviews.
Downloads 135
Release Time : 4/25/2025

Model Overview

This model was trained using Amazon SageMaker and the new Hugging Face deep learning container, with BETO as the base model—a BERT-base model pre-trained on Spanish corpus. Designed specifically for sentiment analysis of Spanish documents, it is optimized for movie reviews but can be extended to other types of reviews.

Model Features

Spanish Optimization
Based on the BETO model pre-trained on Spanish corpus, using whole-word masking for better understanding of Spanish text.
High-Performance Sentiment Analysis
Achieves 91.01% accuracy and 90.88% F1 score on the Spanish IMDb movie review dataset, demonstrating excellent performance.
Easy Integration
Provides a compatible interface with the Hugging Face transformers library, allowing seamless integration into existing NLP pipelines.

Model Capabilities

Spanish Text Classification
Sentiment Analysis
Movie Review Sentiment Polarity Judgment

Use Cases

Entertainment
Movie Review Sentiment Analysis
Analyze the sentiment polarity (positive/negative) of Spanish movie reviews.
91.01% accuracy
Customer Feedback Analysis
Product Review Sentiment Analysis
Analyze the sentiment polarity of Spanish product reviews.
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