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Financial Sentiment Analysis
F
Financial Sentiment Analysis
Developed by Sigma
This model is a financial text sentiment analysis model fine-tuned based on FinancialBERT, performing excellently on the financial_phrasebank dataset.
Downloads 646
Release Time : 5/14/2022
Model Overview
Used to analyze the sentiment tendency of financial texts, capable of identifying positive, negative, or neutral emotions in the text.
Model Features
High Accuracy
Achieves 99.24% accuracy and F1 score on the financial_phrasebank dataset.
Financial Domain Optimization
Specifically fine-tuned for financial texts, better understanding financial terminology and context.
Efficient Training
Uses a linear learning rate scheduler, completing efficient training within 5 epochs.
Model Capabilities
Financial Text Sentiment Analysis
Three-Class Sentiment Recognition (Positive/Negative/Neutral)
High-Precision Text Classification
Use Cases
Financial Analysis
Earnings Report Sentiment Analysis
Analyze the sentiment tendency in company earnings report texts.
Accurately identifies positive or negative expressions in earnings reports.
News Sentiment Monitoring
Monitor market sentiment changes in financial news.
Helps investors understand market sentiment trends.
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