AI is happening. The future is updating.financial-roberta-large-sentiment
Financial-RoBERTa Financial-RoBERTa is a pre-trained NLP model to analyze sentiment of financial text including: Financial Statements, Earnings Announcements, Earnings Call Transcripts, Corporate Social Responsibility (CSR) Reports, Environmental, Social, and Governance (ESG) News, Financial News, Etc. Financial-RoBERTa is built by further training and fine-tuning the RoBERTa Large language model using a large corpus created from 10k, 10Q, 8K, Earnings Call Transcripts, CSR Reports, ESG News, and Financial News text. The model will give softmax outputs for three labels: Positive , Negative or Neutral . How to perform sentiment analysis: The easiest way to use the model for single predictions is Hugging Face's sentiment analysis pipeline, which only needs a couple lines of code as shown in the following example:
Financial-RoBERTa Financial-RoBERTa is a pre-trained NLP model to analyze sentiment of financial text including: Financial Statements, Earnings Announcements, Earnings Call Transcripts, Corporate Social Responsibility (CSR) Reports, Environmental, Social, and Governance (ESG) News, Financial News, Etc. Financial-RoBERTa is built by further training and fine-tuning the RoBERTa Large language model using a large corpus created from 10k, 10Q, 8K, Earnings Call Transcripts, CSR Reports, ESG News, and Financial News text. The model will give softmax outputs for three labels: Positive , Negative or Neutral . How to perform sentiment analysis: The easiest way to use the model for single predictions is Hugging Face's sentiment analysis pipeline, which only needs a couple lines of code as shown in the following example: