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 # Identifying and Analysing political quotes from the Danish Parliament related to climate change using NLP
-**KlimaBERT**, a sequence-classifier fine-tuned to predict whether 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".
+**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".
 
 KlimaBERT is fine-tuned using the pre-trained DaBERT-uncased model, on a training set of 1.000 manually labelled data-points. The training set contains both political quotes and summaries of bills from the [Danish Parliament](https://www.ft.dk/).