650 K and so on and you can see how the performance especially when you use word fine-tune is on par with the birth large that strain on all the label data points so the performance you get from taking birth large and fine-tuning on the fully supervised baseline is actually on par with what do you get from you da plus using bird fine-tune but just on like thousand x few labels which is incredible so it means that the consistency loss is using back translation is actually working really well secondly they have this idea called