financial-sentiments-analysis-finbert

Financial sentiments Analysis

This workflow uses the FinBERT Model tailored specifically for financial sentiment analysis. It is designed to understand and analyze text data from the financial domain, making it particularly useful for tasks such as predicting sentiment in financial news articles, reports, and social media posts related to the financial markets.

FinBERT

FinBERT builds upon the foundation of BERT by further training it on a financial corpus, specifically the Reuters TRC2 dataset. This additional training allows FinBERT to better understand and interpret financial jargon and terminology, enhancing its performance for sentiment analysis within the financial domain.

How to use the Financial sentiments Analysis workflow? 

Using Clarifai SDK

Export your PAT as an environment variable. Then, import and initialize the API Client.

Find your PAT in your security settings.

export CLARIFAI_PAT={your personal access token}

Prediction with the workflow

from clarifai.client.workflow import Workflow

workflow_url = 'https://clarifai.com/clarifai/sentiment-analysis/workflows/financial-sentiments-analysis-finbert'

text = 'The company supports its global customers in developing new technologies and offers a fast route from product development to applications and volume production .'

prediction = Workflow(workflow_url).predict_by_bytes( text.encode(), input_type="text")

# Get workflow results
print(prediction.results[0].outputs[-1].data)

Using Workflow

To utilize the Financial sentiments Analysis workflow, you can input text through the Blue Plus Try your own Input button and it will provide whether the sentiment is positive, negative, or neutral towards a specific financial entity, event, or market trend, helping investors and analysts gauge market sentiment and make informed decisions.