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Finance Sentiment Classification

Developed by RashidNLP
Financial sentiment classification model based on Deberta-v2 architecture, fine-tuned on multiple financial sentiment datasets
Downloads 418
Release Time : 5/14/2023

Model Overview

This model is specifically designed for sentiment analysis of financial texts, capable of identifying positive, neutral, and negative emotions in the text.

Model Features

Specialized for Financial Domain
Optimized specifically for financial texts, accurately identifying sentiment tendencies in financial news and reports
Multi-dataset Fine-tuning
Fine-tuned on 4 different financial sentiment datasets, improving the model's generalization capability
Three-class Sentiment Analysis
Capable of identifying positive, neutral, and negative sentiments

Model Capabilities

Financial text sentiment analysis
News sentiment classification
Market sentiment monitoring

Use Cases

Financial Market Analysis
Stock Market News Sentiment Analysis
Analyzing sentiment tendencies in stock market-related news
Helps predict market sentiment changes
Corporate Earnings Report Sentiment Analysis
Evaluating language sentiment in corporate earnings reports
Assists in investment decision-making
Social Media Monitoring
Financial Tweet Sentiment Analysis
Analyzing sentiment on financial topics from social media platforms like Twitter
Real-time public sentiment monitoring
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