Financial Sentiment Model
This model is a financial text sentiment classification model fine-tuned on the financial_phrasebank dataset based on deepmind/language-perceiver.
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Release Time : 3/2/2022
Model Overview
This model is specifically designed for sentiment analysis of financial texts, capable of classifying sentiments in finance-related sentences.
Model Features
High Accuracy
Achieves 88.04% accuracy on the financial_phrasebank dataset.
Domain-Specific Optimization
Fine-tuned specifically for financial texts, ideal for financial sentiment analysis.
Efficient Training
Requires only 4 training epochs to achieve good performance.
Model Capabilities
Financial Text Sentiment Classification
Sentence-Level Sentiment Analysis
Use Cases
Financial Analysis
Earnings Report Sentiment Analysis
Analyze sentiment tendencies in company earnings reports.
Can identify positive or negative expressions in earnings reports.
News Sentiment Monitoring
Monitor sentiment changes in financial news.
Helps investors understand market sentiment.
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