Open-source Financial Text Sentiment Classification Model - Accurately Determine the Sentiment Tendency of Financial Texts

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.

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.

Financial Text Sentiment Classification

Sentence-Level Sentiment Analysis

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.

Property	Details
Model Type	Fine - tuned from [deepmind/language - perceiver](https://huggingface.co/deepmind/language - perceiver)
Training Data	financial_phrasebank
Metrics	Recall, Accuracy, Precision

Training Loss	Epoch	Step	Validation Loss	Recall	Accuracy	Precision
0.4481	1.0	273	0.4035	0.8526	0.8433	0.7955
0.4069	2.0	546	0.4478	0.8683	0.8289	0.8123
0.2225	3.0	819	0.3167	0.8747	0.8680	0.8387
0.1245	4.0	1092	0.3467	0.8840	0.8804	0.8604

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