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Mdeberta V3 Base Sentiment

Developed by agentlans
A multilingual text sentiment classification model fine-tuned based on mDeBERTa-v3-base, supporting cross-language sentiment analysis
Downloads 101
Release Time : 10/12/2024

Model Overview

This model is fine-tuned for cross-language text sentiment evaluation tasks and can predict positive/neutral/negative sentiment tendencies in text

Model Features

Cross-language Sentiment Analysis
Supports sentiment evaluation of texts in multiple languages, maintaining prediction consistency for translated texts
Three-way Sentiment Classification
Outputs continuous sentiment scores (positive value = positive / zero value = neutral / negative value = negative)
Efficient Fine-tuning Architecture
Optimized based on the powerful multilingual understanding capabilities of mDeBERTa-v3-base

Model Capabilities

Multilingual text sentiment classification
Cross-language sentiment consistency evaluation
Continuous sentiment score prediction

Use Cases

Social Media Analysis
Multilingual Comment Sentiment Monitoring
Analyze sentiment tendencies in user comments across different languages
Achieved 0.4177 RMSE accuracy on the validation set
Market Research
Global Brand Sentiment Tracking
Compare user sentiment feedback for products in different language markets
Experiments show high prediction consistency for translated texts
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