37 lines
1.8 KiB
Markdown
37 lines
1.8 KiB
Markdown
---
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language: "en"
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tags:
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- financial-sentiment-analysis
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- sentiment-analysis
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widget:
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- text: "Stocks rallied and the British pound gained."
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---
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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 PhraseBank](https://www.researchgate.net/publication/251231107_Good_Debt_or_Bad_Debt_Detecting_Semantic_Orientations_in_Economic_Texts) by Malo et al. (2014) is used for fine-tuning. For more details, please see the paper [FinBERT: Financial Sentiment Analysis with Pre-trained Language Models](https://arxiv.org/abs/1908.10063) and our related [blog post](https://medium.com/prosus-ai-tech-blog/finbert-financial-sentiment-analysis-with-bert-b277a3607101) on Medium.
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The model will give softmax outputs for three labels: positive, negative or neutral.
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---
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About Prosus
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Prosus is a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities. For more information, please visit www.prosus.com.
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Contact information
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Please contact Dogu Araci dogu.araci[at]prosus[dot]com and Zulkuf Genc zulkuf.genc[at]prosus[dot]com about any FinBERT related issues and questions.
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---
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FinBERT in Use (New!)
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We are delighted to hear the use of FinBERT at many other organisations. Please, let us know your use-case if you have FinBERT deployed and we add you to this list:
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- Prosus
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- Huggingface
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- Moodys Analytics
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- ING
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API Implementations
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- [Multilingual Rapid API](https://rapidapi.com/financial-sentiment-financial-sentiment-default/api/finbert3/) |