incl unbalance comment

README.md

@@ -1,3 +1,57 @@
 ---
 license: mit
+pipeline_tag: token-classification
 ---
+
+# Description:
+
+climateattention-10k classifies if a given sequence is related to climate topics. 
+As a fine-tuned classifier based on climatebert/distilroberta-base-climate-f (Webersinke et al., 2021), 
+it is using the following ClimaText dataset (Varini et al., 2020):
+
+* AL-10Ks.tsv : 3000 (58 positives, 2942 negatives)
+
+The training set is highly unbalanced. You might want to check the upscaling version: 'kruthof/climateattention-10k-upscaled'
+
+# How to use:
+```python
+from transformers import AutoTokenizer, pipeline,RobertaForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("climatebert/distilroberta-base-climate-f")
+climateattention = RobertaForSequenceClassification.from_pretrained('kruthof/climateattention-10k',num_labels=2)
+
+ClimateAttention = pipeline("text-classification", model=climateattention, tokenizer=tokenizer)
+
+ClimateAttention('Emissions have increased during the last several months')
+
+>> [{'label': 'Yes', 'score': 0.9993829727172852}]
+
+```
+ # Performance:
+
+Performance tested on the balanced ClimaText 10K test set, featuring 300 samples (67 positives, 233 negatives)  (Varini et al., 2020)
+
+|Accuracy|  Precision | Recall  |   F1   |  
+|----|-----|-----|-----|
+| 0.9633   |  1    |  0.8358 | 0.9106 |  
+
+
+# Cite:
+```bibtex
+@misc{kruthof2023,
+        title={ClimateAttention: A Fine-Tuned Climate Attention Classifier},
+        author={Kruthof, Garvin},
+        url={https://huggingface.co/kruthof/climateattention-ctw},
+        year={2023}
+```
+
+# References:
+
+Varini, F. S., Boyd-Graber, J., Ciaramita, M., & Leippold, M. (2020). 
+ClimaText: A dataset for climate change topic detection. arXiv preprint arXiv:2012.00483.
+
+Webersinke, N., Kraus, M., Bingler, J. A., & Leippold, M. (2021). 
+Climatebert: A pretrained language model for climate-related text. arXiv preprint arXiv:2110.12010.
+
+------------------------------
+https://kruthof.github.io