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README.md

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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.
  
 # Training data
-**FinancialBERT** model was fine-tuned on Financial PhraseBank, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive).
+FinancialBERT model was fine-tuned on Financial PhraseBank, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive).
 
  # How to use 
 Our model can be used thanks to Transformers pipeline for sentiment analysis.