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Rubert Base Cased Sentiment Rusentiment
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Rubert Base Cased Sentiment Rusentiment

Developed by blanchefort
A sentiment analysis model based on DeepPavlov/rubert-base-cased-conversational architecture, trained on the RuSentiment dataset, capable of identifying neutral, positive, and negative emotions in Russian text.
Text Classification Other#Russian sentiment analysis#Social media text#Pre-training fine-tuning
Downloads 80.75k
Release Time : 3/2/2022

Model Overview

This model is specifically designed for sentiment analysis tasks in Russian text, capable of classifying input text into three emotional categories: neutral, positive, or negative.

Model Features

Russian Sentiment Analysis
Sentiment analysis capabilities optimized specifically for Russian social media and conversational text
Three-class Classification Model
Capable of identifying three emotional states: neutral, positive, and negative
BERT-based Architecture
Utilizes the powerful BERT architecture for context-aware sentiment analysis

Model Capabilities

Russian text sentiment classification
Social media sentiment analysis
Conversational sentiment recognition

Use Cases

Social media analysis
Russian social media comment sentiment analysis
Analyze sentiment tendencies in Russian social media user comments
Can identify positive, negative, or neutral emotions in comments
Customer feedback analysis
Russian customer feedback sentiment classification
Automated sentiment classification of Russian customer feedback
Helps businesses quickly understand customer satisfaction
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