Model card

README.md

@@ -1 +1,39 @@
-## Multi-lingual sentiment prediction trained from COVID19-reated tweets
+---
+pipeline_tag: sentiment-analysis
+language: multilingual
+license: apache-2.0
+tags:
+- "sentiment-analysis"
+- "multilingual"
+---
+
+# Multi-lingual sentiment prediction trained from COVID19-related tweets
+
+Repository: [https://github.com/clampert/multilingual-sentiment-analysis/](https://github.com/clampert/multilingual-sentiment-analysis/)
+
+Model trained on a large-scale (18437530 examples) dataset of 
+multi-lingual tweets that was collected between March 2020 
+and November 2021 using Twitter’s Streaming API with varying
+COVID19-related keywords. Labels were auto-general based on 
+the presence of positive and negative emoticons. For details
+on the dataset, see our IEEE BigData 2021 publication. 
+
+Base model is [sentence-transformers/stsb-xlm-r-multilingual](https://huggingface.co/sentence-transformers/stsb-xlm-r-multilingual).
+It was finetuned for sequence classification with `positive` 
+and `negative` labels for two epochs (48 hours on 8xP100 GPUs). 
+
+## Citation
+
+If you use our model your work, please cite:
+
+```
+@inproceedings{lampert2021overcoming,
+  title={Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis},
+  author={Jasmin Lampert and Christoph H. Lampert},
+  booktitle={IEEE International Conference on Big Data (BigData)},
+  year={2021},
+  note={Special Session: Machine Learning on Big Data},
+}
+```
+
+Enjoy!