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  *FinancialBERT* is a BERT model pre-trained on a large corpora of financial texts. The purpose is to enhance financial NLP research and practice in financial domain, we hope financial practitioners and researchers can benefit from our model without the necessity of the significant computational resources required to train the model.
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- We fine-tuned our model on Sentiment Analysis task using _FinancialPhraseBank_ dataset, experiments show that our model outperforms the general BERT and other financial domain-specific models.
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  ### Training data
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  FinancialBERT model was fine-tuned on Financial PhraseBank, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive).
 
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  *FinancialBERT* is a BERT model pre-trained on a large corpora of financial texts. The purpose is to enhance financial NLP research and practice in financial domain, we hope financial practitioners and researchers can benefit from our model without the necessity of the significant computational resources required to train the model.
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+ Our model was fine-tuned for Sentiment Analysis task on _FinancialPhraseBank_ dataset, experiments show that our model outperforms the general BERT and other financial domain-specific models.
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  ### Training data
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  FinancialBERT model was fine-tuned on Financial PhraseBank, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive).