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README.md

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 license: apache-2.0
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+# GitHub issues classifier (using zero shot classification)
+
+This model was trained using the [**Zero-shot classifier distillation**](https://github.com/huggingface/transformers/tree/main/examples/research_projects/zero-shot-distillation) method
+with the [BART-large-mnli](https://huggingface.co/facebook/bart-large-mnli) model as teacher model, to train a classifier on Github issues from the [Github Issues Prediction dataset](https://www.kaggle.com/datasets/anmolkumar/github-bugs-prediction)
+
+## Labels
+
+As per the dataset Kaggle competition, the classifier predicts wether an issue is a bug, feature or question. After playing around with different labels pre-training I've used a different mapping
+of labels that yielded better predictions (see notebook [here](https://www.kaggle.com/code/antoinemacia/zero-shot-classifier-for-bug-analysis/edit) for details), labels being
+
+* issue
+* feature request
+* question 
+
+
+## Training data
+
+This model was trained on 5k titles (unlabelled, as per distillation requierements) from the train dataset of [Github Issues Prediction dataset](https://www.kaggle.com/datasets/anmolkumar/github-bugs-prediction)
+
+## Acknowledgements
+
+* Joe Davison and his article on [Zero-Shot Learning in Modern NLP](https://joeddav.github.io/blog/2020/05/29/ZSL.html)
+* Jeremy Evans and his notebook on [Iterate like a grandmaster](https://www.kaggle.com/code/antoinemacia/iterate-like-a-grandmaster)
+