Rubert Base Russian Emotion Detection
R
Rubert Base Russian Emotion Detection
Developed by MaxKazak
A Russian multi-label emotion classification model fine-tuned on ruBert-base, trained on the ru_goemotions dataset, supporting 9 emotion categories
Downloads 1,288
Release Time : 5/28/2023
Model Overview
This model is specifically designed for sentiment analysis of Russian texts, capable of identifying multiple emotions expressed in text, including joy, interest, surprise, sadness, anger, disgust, fear, guilt, and neutral emotions.
Model Features
Multi-label Emotion Classification
Capable of identifying multiple emotions expressed in text simultaneously, rather than a single emotion
High Accuracy
Achieves 92.4% AUC on the evaluation set, demonstrating excellent classification performance
Broad Emotion Coverage
Supports classification of 9 different emotions, covering a wide range of human emotional expressions
Model Capabilities
Russian text sentiment analysis
Multi-label classification
Emotion recognition
Use Cases
Social Media Analysis
User Comment Sentiment Analysis
Analyze the emotions in Russian user comments on social media
Accurately identifies multiple compound emotions
Customer Service
Customer Feedback Emotion Classification
Automatically classify emotional tendencies in Russian customer feedback
Helps quickly identify negative emotional feedback
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