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This is a finetuning of the ESGBERT/EnvRoBERTa-base language model, trained to classify texts on climate adaptation in the ESG/climate domain.

Using the EnvironmentalBERT-base model as a starting point, the AdaptationBERT Language Model is additionally fine-trained on a 2k adaptation dataset to detect climate adaptation and resilience text samples.

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

See these tutorials from Tobias Schimanski on Medium for a guide on model usage, large-scale analysis, and fine-tuning.

It is highly recommended to first classify a sentence to be "environmental" or not with the EnvironmentalBERT-environmental model before classifying whether it is "forest" or not.

You can use the model with a pipeline for text classification:

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Training Details

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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