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Financial Sentiment Model

Developed by oandreae
This model is a financial text sentiment classification model fine-tuned on the financial_phrasebank dataset based on deepmind/language-perceiver.
Downloads 15
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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