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  - Earnings Call Transcripts: 1.3B tokens
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  - Analyst Reports: 1.1B tokens
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- More details on `FinBERT`'s pre-training process can be found at: https://arxiv.org/abs/2006.08097
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- `FinBERT` can be further fine-tuned on downstream tasks. Specifically, we have fine-tuned `FinBERT` on an analyst sentiment classification task, and the fine-tuned model is shared at https://huggingface.co/yiyanghkust/finbert-tone
 
 
 
 
 
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  - Earnings Call Transcripts: 1.3B tokens
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  - Analyst Reports: 1.1B tokens
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+ If you use the model in your academic work, please cite the following papers:
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+ Huang, Allen H., Hui Wang, and Yi Yang. "FinBERT: A Large Language Model for Extracting Information from Financial Text." *Contemporary Accounting Research* (2022).
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+ Yang, Yi, Mark Christopher Siy Uy, and Allen Huang. "Finbert: A pretrained language model for financial communications." *arXiv preprint arXiv:2006.08097* (2020).
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+ `FinBERT` can be further fine-tuned on downstream tasks. Specifically, we have fine-tuned `FinBERT` for financial sentiment analysis, ESG classification, Forward-looking statement classification and etc. Visit [FinBERT.AI](https://finbert.ai/) for more details on these task-specific models and recent development of FinBERT.