Soleimanian

financial-roberta-large-sentiment

The financial-roberta-large-sentiment model is a text classification model specifically designed for sentiment analysis in the financial domain. It is based on the RoBERTa architecture and has been fine-tuned on a large dataset of financial texts. The model takes in a piece of text and predicts the sentiment associated with it, classifying it as positive, negative, or neutral. This model can be used to analyze sentiment in financial news articles, social media posts, or other financial texts, providing valuable insights for investment decision-making and market analysis.

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