Analyze Financial Text
Analysis Result
Enter text and click Analyze to see sentiment results
Trusted by financial institutions worldwide
What is FinBERT
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification.
- Financial Domain TrainingFurther trained on a large financial corpus to understand the unique language and terminology of finance.
- Three-Class SentimentClassifies text into Positive, Negative, or Neutral sentiment with softmax probability outputs.
- Easy IntegrationAvailable on Hugging Face model hub for seamless integration into your applications.
Trusted by the Financial Community
Join thousands using FinBERT for sentiment analysis.
Hugging Face Downloads
10M+
Model downloads
GitHub Stars
5k+
Community stars
Accuracy
89%
On Financial PhraseBank
What Professionals Say About FinBERT
Hear from financial analysts and developers leveraging FinBERT.
Sarah Chen
Quantitative Analyst
FinBERT has transformed our news analysis workflow. The financial domain understanding is exceptional compared to generic sentiment models.
Michael Park
Fintech Developer
Integration was seamless through Hugging Face. We added financial sentiment analysis to our platform in hours.
Emily Rodriguez
Investment Manager
We use FinBERT to process thousands of earnings reports. The sentiment scores help us make better investment decisions.
David Kim
Data Scientist
The softmax outputs give us granular sentiment insights. We've built powerful trading signals on top of FinBERT.
Jessica Williams
Financial Reporter
I use FinBERT to analyze market sentiment from news articles. It's become an essential tool in my research.
Robert Taylor
Portfolio Manager
FinBERT helps us track market sentiment shifts in real-time. It's invaluable for our risk management strategy.
Frequently Asked Questions
Got questions about FinBERT? We have answers.
What is FinBERT?
FinBERT is a pre-trained NLP model specialized for financial sentiment analysis. It is built by further training the BERT language model on a large financial corpus and fine-tuning it for sentiment classification using Financial PhraseBank.
How accurate is FinBERT?
FinBERT achieves high accuracy on financial sentiment tasks, particularly when evaluated on the Financial PhraseBank dataset. Its domain-specific training makes it significantly more accurate than generic sentiment models for financial text.
What type of text can FinBERT analyze?
FinBERT is designed for financial text including news articles, earnings reports, financial statements, analyst reports, and social media posts about financial markets.
How do I integrate FinBERT?
FinBERT is available on the Hugging Face model hub. You can easily load it using the transformers library with just a few lines of code. Check the GitHub repository for detailed examples.
Is FinBERT free to use?
Yes, FinBERT is open source and freely available for both research and commercial use. The model can be downloaded from Hugging Face or the GitHub repository.
What sentiment classes does FinBERT predict?
FinBERT classifies text into three sentiment categories: Positive, Negative, and Neutral. It provides softmax probability outputs for all three classes along with an overall sentiment score.
Start Analyzing Financial Sentiment
Join the community of financial professionals and developers leveraging FinBERT for smarter sentiment analysis.