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Twitter Sentiment Pl Base
Polish Twitter sentiment analysis model based on Herbert-base, capable of identifying positive, negative, and neutral sentiments
Downloads 107
Release Time : 12/1/2022
Model Overview
This model is specifically designed to analyze the sentiment tendencies of Polish Twitter posts, outputting three classification results: positive, negative, or neutral. It is based on the Herbert-base architecture and trained on a translated version of the TweetEval dataset.
Model Features
Polish Language Specialization
Sentiment analysis model optimized specifically for Polish Twitter content
Three-Class Sentiment Recognition
Accurately distinguishes between positive, negative, and neutral emotional states
Efficient Inference
Can process 129.9 samples per second on an RTX 3090
Model Capabilities
Polish text classification
Social media sentiment analysis
Short text sentiment recognition
Use Cases
Social Media Analysis
Brand Sentiment Monitoring
Analyze the sentiment tendencies of users towards brands or products on Twitter
Can identify users' positive or negative attitudes towards brands
Public Event Sentiment Analysis
Monitor public emotional reactions to trending events
Provides trends in public sentiment related to events
Market Research
Product Feedback Analysis
Extract sentiment from user tweets about products
Helps identify product strengths, weaknesses, and areas for improvement
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