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More technical details on `FinBERT`: [Click Link](https://github.com/yya518/FinBERT)
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Please check out our working paper [`FinBERT—A Deep Learning Approach to Extracting Textual Information`](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3910214).
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This released `finbert-tone` model is the `FinBERT` model fine-tuned on 10,000 manually annotated (positive, negative, neutral) sentences from analyst reports. This model achieves superior performance on financial tone analysis task. If you are simply interested in using `FinBERT` for financial tone analysis, give it a try.
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# How to use
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You can use this model with Transformers pipeline for sentiment analysis.
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```python
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More technical details on `FinBERT`: [Click Link](https://github.com/yya518/FinBERT)
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This released `finbert-tone` model is the `FinBERT` model fine-tuned on 10,000 manually annotated (positive, negative, neutral) sentences from analyst reports. This model achieves superior performance on financial tone analysis task. If you are simply interested in using `FinBERT` for financial tone analysis, give it a try.
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If you use the model in your academic work, please cite the following paper:
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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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# How to use
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You can use this model with Transformers pipeline for sentiment analysis.
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```python
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