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README.md

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-license: apache-2.0
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-
-# Model card for distilroberta-base-climate-adaptation-detector
-## Model description
-This model is a fine-tuned version of [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) that classifies chunks of climate policy texts as **Adaptation** or **Not adaptation**. 
-
-It is fine-tuned on a labelled dataset of 3,159 chunks with an average of 3,158 characters and 10 paragraphs per chunk. More details and the methodology can be found in the corresponding [research paper]() and on our [Git](https://git.wur.nl/bonen003/transforming-adaptation-tracking).
-
-## Model performance
-**Recall**: 0.871
-**F1 score**: 0.759
-**Precision**: 0.673
-
-## Citation information
-```bibtex
-@inproceedings{bonen2025transforming,
-    title={{Transforming adaptation tracking: Benchmarking Transformer-based NLP approaches to retrieve adaptation-relevant information from climate policy text}},
-    author={Bonenkamp, Jetske and Biesbroek, Robbert and Athanasiadis, Ioannis},
-    booktitle={Proceedings of The 2nd Workshop of Natural Language Processing meets Climate Change},
-    year={2025}
-}
+---
+license: apache-2.0
+---
+
+# Model card for distilroberta-base-climate-adaptation-detector
+## Model description
+This model is a fine-tuned version of [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) that classifies chunks of climate policy texts as **Adaptation** or **Not adaptation**. 
+
+It is fine-tuned on a labelled dataset of 3,159 chunks with an average of 3,158 characters and 10 paragraphs per chunk. More details and the methodology can be found in the corresponding [research paper](https://aclanthology.org/2025.climatenlp-1.19/) and on our [Git](https://git.wur.nl/bonen003/transforming-adaptation-tracking).
+
+## Model performance
+**Recall**: 0.871
+**F1 score**: 0.759
+**Precision**: 0.673
+
+## Citation information
+```bibtex
+@inproceedings{bonen2025transforming,
+    title={{Transforming adaptation tracking: Benchmarking Transformer-based NLP approaches to retrieve adaptation-relevant information from climate policy text}},
+    author={Bonenkamp, Jetske and Biesbroek, Robbert and Athanasiadis, Ioannis},
+    booktitle={Proceedings of The 2nd Workshop of Natural Language Processing meets Climate Change},
+    year={2025}
+}
 ```