(iii) We demonstrate that the actively acquired training datasets can be utilized as small, surrogate training sets with a 5x-40x compression for training large, deep text classification models.
we can train the ULMFiT (Howard and Ruder, 2018) model to state of the art accuracy at 25x-200x speedups.