tobischimanski
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README.md
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## Model Description
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Using the [EnvRoBERTa-base](https://huggingface.co/ESGBERT/EnvRoBERTa-base) model as a starting point, the EnvRoBERTa-environmental Language Model is additionally fine-trained on a 2k environmental dataset to detect environmental text samples.
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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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}
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```
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## Model Description
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Based on [this paper](https://huggingface.co/ESGBERT/GovRoBERTa-base), this is the EnvRoBERTa-environmental language model. A language model that is trained to better classify environmental texts in the ESG domain.
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Using the [EnvRoBERTa-base](https://huggingface.co/ESGBERT/EnvRoBERTa-base) model as a starting point, the EnvRoBERTa-environmental Language Model is additionally fine-trained on a 2k environmental dataset to detect environmental text samples.
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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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