readme: ---
  language: "en"
  tags:
  - financial-text-analysis
  - esg
  - environmental-social-corporate-governance
  widget:
  - text: "Rhonda has been volunteering for several years for a variety of charitable community programs. "
  ---
  
  ESG analysis can help investors determine a business' long-term sustainability and identify associated risks. FinBERT-ESG is a FinBERT model fine-tuned on 2,000 manually annotated sentences from firms' ESG reports and annual reports.  
  
  **Input**: A financial text.
  
  **Output**: Environmental, Social, Governance or None.
  
  # How to use 
  You can use this model with Transformers pipeline for ESG classification.
  ```python
  # tested in transformers==4.18.0 
  from transformers import BertTokenizer, BertForSequenceClassification, pipeline
  
  finbert = BertForSequenceClassification.from_pretrained('yiyanghkust/finbert-esg',num_labels=4)
  tokenizer = BertTokenizer.from_pretrained('yiyanghkust/finbert-esg')
  nlp = pipeline("text-classification", model=finbert, tokenizer=tokenizer)
  results = nlp('Rhonda has been volunteering for several years for a variety of charitable community programs.')
  print(results) # [{'label': 'Social', 'score': 0.9906041026115417}]
  
  ```
  
  Visit [FinBERT.AI](https://finbert.ai/) for more details on the recent development of FinBERT.
  
  If you use the model in your academic work, please cite the following paper:
  
  Huang, Allen H., Hui Wang, and Yi Yang. "FinBERT: A Large Language Model for Extracting Information from Financial Text." *Contemporary Accounting Research* (2022).
  
  