Finbert Sentiment Ko
A Korean financial news sentiment analysis model fine-tuned based on BERT architecture, specifically designed for sentiment classification of exchange rate-related news summaries
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Release Time : 3/23/2025
Model Overview
This model is a sentiment analysis model optimized for the Korean financial domain (particularly exchange rate news), capable of classifying news summaries into three sentiment categories: negative, neutral, or positive
Model Features
Financial Domain Optimization
Specifically optimized and trained for Korean financial news (especially content related to exchange rates)
High Accuracy
Achieves an overall accuracy of 93% on the test set
Fine-grained Classification
Provides three-class sentiment analysis: negative (0), neutral (1), positive (2)
Model Capabilities
Korean text sentiment analysis
Financial news sentiment classification
Exchange rate-related text analysis
Use Cases
Financial Analysis
Exchange Rate News Sentiment Monitoring
Real-time analysis of sentiment trends in exchange rate-related news to provide references for investment decisions
Accurately identifies changes in market sentiment
Market Sentiment Dashboard
Build a financial news sentiment dashboard to visualize overall market sentiment trends
Helps investors grasp market sentiment fluctuations
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