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  ## Model Description
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- As an extension to [this paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4622514), this is the EnvironmentalBERT-action language model. A language model that is trained to better classify action texts in the ESG domain.
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  Using the [EnvironmentalBERT-base](https://huggingface.co/ESGBERT/EnvironmentalBERT-base) model as a starting point, the EnvironmentalBERT-action Language Model is additionally fine-trained on a dataset with 500 sentences to detect action text samples. The underlying dataset is comparatively small, so if you would like to contribute to it, feel free to reach out. :)
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  While this dataset does not originate from the paper, it is a extension of it and the base models are described in it.
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  ```bibtex
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- @article{Schimanski23ESGBERT,
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- title={{Bridiging the Gap in ESG Measurement: Using NLP to Quantify Environmental, Social, and Governance Communication}},
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- author={Tobias Schimanski and Andrin Reding and Nico Reding and Julia Bingler and Mathias Kraus and Markus Leippold},
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- year={2023},
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- journal={Available on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4622514},
 
 
 
 
 
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  }
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  ```
 
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  ## Model Description
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+ As an extension to [this paper](https://www.sciencedirect.com/science/article/pii/S1544612324000096), this is the EnvironmentalBERT-action language model. A language model that is trained to better classify action texts in the ESG domain.
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  Using the [EnvironmentalBERT-base](https://huggingface.co/ESGBERT/EnvironmentalBERT-base) model as a starting point, the EnvironmentalBERT-action Language Model is additionally fine-trained on a dataset with 500 sentences to detect action text samples. The underlying dataset is comparatively small, so if you would like to contribute to it, feel free to reach out. :)
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  While this dataset does not originate from the paper, it is a extension of it and the base models are described in it.
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  ```bibtex
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+ @article{schimanski_ESGBERT_2024,
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+ title = {Bridging the gap in ESG measurement: Using NLP to quantify environmental, social, and governance communication},
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+ journal = {Finance Research Letters},
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+ volume = {61},
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+ pages = {104979},
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+ year = {2024},
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+ issn = {1544-6123},
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+ doi = {https://doi.org/10.1016/j.frl.2024.104979},
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+ url = {https://www.sciencedirect.com/science/article/pii/S1544612324000096},
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+ author = {Tobias Schimanski and Andrin Reding and Nico Reding and Julia Bingler and Mathias Kraus and Markus Leippold},
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  }
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  ```