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# Identifying and Analysing political quotes from the Danish Parliament related to climate change using NLP
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**KlimaBERT**, a sequence-classifier fine-tuned to predict whether political quotes are climate-related. When predicting the class 1, "climate-related", (positive class), the model achieves a F1-score of 0.97, Precision of 0.97, and Recall of 0.97. The negative class, 0, is defined as "non-climate-related".
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### Acknowledgements
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The resources are created through the work of my Master's thesis, so I would like to thank my supervisors [Leon Derczynski](https://www.derczynski.com/itu/) and [Vedran Sekara](https://vedransekara.github.io/) for the great support throughout the project! And a HUGE thanks to [Gustav Gyrst](https://github.com/Gyrst) for great sparring and co-development of the tools you find in this repo.
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language:
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- da
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- danish
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tags:
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- climate change
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- climate-classifier
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language:
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- da
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- danish
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tags:
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- climate change
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- climate-classifier
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- political quotes
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# Identifying and Analysing political quotes from the Danish Parliament related to climate change using NLP
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**KlimaBERT**, a sequence-classifier fine-tuned to predict whether political quotes are climate-related. When predicting the class 1, "climate-related", (positive class), the model achieves a F1-score of 0.97, Precision of 0.97, and Recall of 0.97. The negative class, 0, is defined as "non-climate-related".
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### Acknowledgements
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The resources are created through the work of my Master's thesis, so I would like to thank my supervisors [Leon Derczynski](https://www.derczynski.com/itu/) and [Vedran Sekara](https://vedransekara.github.io/) for the great support throughout the project! And a HUGE thanks to [Gustav Gyrst](https://github.com/Gyrst) for great sparring and co-development of the tools you find in this repo.
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