Edit model card

Model Card for EnvironmentalBERT-base

Model Description

Based on this paper, this is the EnvironmentalBERT-base language model. A language model that is trained to better understand environmental texts in the ESG domain.

Using the DistilRoBERTa model as a starting point, the EnvironmentalBERT-base Language Model is additionally pre-trained on a text corpus comprising environmental-related annual reports, sustainability reports, and corporate and general news.

More details can be found in the paper

@article{Schimanski23ESGBERT,
    title={{Bridiging the Gap in ESG Measurement: Using NLP to Quantify Environmental, Social, and Governance Communication}},
    author={Tobias Schimanski and Andrin Reding and Nico Reding and Julia Bingler and Mathias Kraus and Markus Leippold},
    year={2023},
    journal={Available on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4622514},
}
Downloads last month
71
Inference Examples
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.