Automix

This repository contains the code to use Fast AutoAugment algorithm to generate and pick automatic augmentations for a given task.

For the set of combinations, we used {4 EDA Augmentations, inter lada, intra lada, adverserial augmentation}

The way FAA Algorithm works is as follows -

• Create a model (M) on Train, and formulate a method to pick augmentations
• Repeat
  • Sample augmentations and created augmented val data
  • Find loss of augmented val data on M
  • Save the augmentations with lowest loss (call this ‘aug val loss’)
• Best augmentations are the one with least loss
• Using saved augmentations, create the final model M’ on Train.
• Use M’ to find out ‘final val accuracy’ and test accuracy

Directions to run the code

• yahoo_with_mixtext/train_*/ - Train a FAA policy using the chosen augmentation on the yahoo dataset.
• yahoo_with_mixtext/evaluate_any_model.py - Once train generates a policy, run this to evaluate the policy