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Econosentiment

Developed by samchain
A financial domain sentiment analysis model fine-tuned based on econo-sentence-v2, achieving 96.2% accuracy on the Financial Phrase Bank dataset
Downloads 31
Release Time : 3/25/2025

Model Overview

A fine-grained sentiment analysis model specifically designed for financial texts, capable of identifying sentiment tendencies in financial news and reports

Model Features

Optimized for Financial Domain
Fine-tuned on professional financial corpora, accurately understanding economic terminology and financial contexts
High-Precision Classification
Achieves 96.2% accuracy and F1 score on the test set
Comprehensive Fine-Tuning Strategy
Uses full parameter fine-tuning instead of freezing the encoder for better task adaptability

Model Capabilities

Financial Text Sentiment Classification
Economic News Sentiment Analysis
Financial Report Sentiment Recognition

Use Cases

Financial Analysis
Earnings Report Sentiment Monitoring
Automatically analyzes the sentiment tendencies in listed companies' financial report texts
Can be integrated into investment analysis systems as a sentiment indicator
Market Sentiment Dashboard
Tracks sentiment changes in financial news and market commentary in real-time
Provides sentiment data support for trading strategies
Risk Management
Risk Warning System
Detects financial texts with concentrated negative sentiment
Identifies potential market risk events in advance
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