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.
# 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 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).
- Downloads last month
- 2,095
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.