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Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.

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SayamAlt/Financial-News-Sentiment-Analysis

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About Dataset

Context

This dataset (FinancialPhraseBank) contains the sentiments for financial news headlines from the perspective of a retail investor.

Content

The dataset contains two columns, "Sentiment" and "News Headline". The sentiment can be negative, neutral or positive.

Acknowledgements

Malo, P., Sinha, A., Korhonen, P., Wallenius, J., & Takala, P. (2014). Good debt or bad debt: Detecting semantic orientations in economic texts. Journal of the Association for Information Science and Technology, 65(4), 782-796.

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