but out of that in the as you seen in the previous slide that the mix-up seems to be the most important factor contributing to this a mix-up again is a tuning hyperparameter and if you tune it further you probably might get in better results if you don't tune it as much you might get in less results so these were the positives that i could get or we could see in the paper however there is a bit of a negative or that that comes out through this algorithm that the time and cost needed to generate all the transformations the mix up