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Finance Sentiment Fr Base
A French financial news sentiment analysis model based on camembert-base, capable of identifying positive, negative, and neutral sentiment tendencies
Downloads 817
Release Time : 9/18/2023
Model Overview
This model is specifically designed to analyze sentiment tendencies in French financial texts. Trained on the Financial PhraseBank dataset, it is suitable for sentiment analysis tasks in the financial domain
Model Features
Financial Domain Optimization
Specially trained for financial texts, accurately identifying sentiment tendencies in financial news
Multi-sentiment Classification
Capable of identifying three sentiment labels: positive, negative, and neutral
Efficient Inference
Can process 140.8 samples per second on an RTX 3090 GPU
Model Capabilities
French financial text sentiment analysis
Three-class sentiment recognition
Financial news sentiment detection
Use Cases
Financial Analysis
Earnings Report Sentiment Analysis
Analyze positive or negative statements in company earnings reports
Accurately identify sentiment tendencies related to financial data growth or decline
Market News Monitoring
Real-time monitoring of sentiment changes in financial news
Help investors quickly understand market sentiment fluctuations
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