Tuesday, August 11, 2020
Easy Data Augmentation 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! Thanks for watching! Please Subscribe! Paper Links Easy Data Augmentation: https://ift.tt/3fnqupG Conditional BERT: https://ift.tt/31DSSiE RandAugment: https://ift.tt/2VODOeX CheckList: https://ift.tt/3ktqTLj 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
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