Hi Victor, I haven’t seen the guideline on NLP augmentation before.
Just want to note two potential augmentation codes.
As you may know, in vision, we have a lot of augmentation libraries, but one which really stands out is albumentations due to its speed and variety. (De facto choices for all Kaggle competitors)
Recently, there’s a creative guy who applied the basic Albumentations class to NLP task of Jigsaw’s multi-lingual toxic classification (of course with HuggingFace model) : https://www.kaggle.com/shonenkov/nlp-albumentations 4
I believe we can extend this class in the future.
Another worth-mentioning is nlpaug ( https://github.com/makcedward/nlpaug 5 ) where we can augment with simpler ideas like synonym / antonym word swapping via word suggestions from NLTK and Bert
BTW, do your team also attend ICML this week?