Easy Data Augmentation Techniques for Text Classification

This video explains a great baseline for exploring data augmentation in NLP and text classification particularly. Synonym replacement, random insertion/deletion/swapping can all be quickly implemented and don't require much overhead (compared to say back-translation or generative modeling). If you put this to use, please share your experience!
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Paper Links
Easy Data Augmentation: https://arxiv.org/abs/1901.11196
Conditional BERT: https://arxiv.org/abs/1812.06705
RandAugment: https://arxiv.org/abs/1909.13719
CheckList: https://arxiv.org/abs/2005.04118

Chapters
0:00 Beginning
1:08 4 Operations Explored
3:13 Results
4:55 Hyperparameters of Augmentation
6:10 Ablations on Isolated Augmentations
8:53 t-SNE viz of Label Preservation
9:45 Contrast with Conditional BERT
10:41 Issue with Test Set Evaluation of Data Aug
12:02 Connection with RandAugment
13:44 Quick Takeaways from EDA