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Rubert Tiny2 Russian Emotion Detection
A fine-tuned Russian text multi-label emotion classification model based on rubert-tiny2, capable of recognizing 9 emotional spectra.
Downloads 721
Release Time : 4/8/2023
Model Overview
This model is used for multi-label emotion classification of Russian texts, capable of identifying 9 emotional categories including joy, sadness, anger, etc., based on Izard's emotion scale theory.
Model Features
Multi-label emotion classification
Can simultaneously identify multiple emotions in text, not just a single emotion.
Russian language optimization
Specifically optimized for Russian text, accurately identifying emotional expressions in Russian.
Broad emotional spectrum
Supports recognition of 9 different emotional categories, including neutral, joy, sadness, etc.
Model Capabilities
Russian text sentiment analysis
Multi-label emotion classification
Emotion detection
Use Cases
Social media analysis
User comment sentiment analysis
Analyze the emotional tendencies of user comments on social media to understand user feelings about products or services.
Can identify emotions such as joy and anger in comments, helping to improve products or services.
Market research
Consumer feedback analysis
Analyze consumer feedback on marketing campaigns to understand emotional responses.
Identify consumer emotions such as interest and surprise towards campaigns, optimizing marketing strategies.
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