semi-supervised learning framework different model architectures from ResNet 18 and 50 up to the res next group convolution architectures and then you see up to the 80 4.8% accuracy when using the semi-weekly supervised learning framework with 193 million parameters on the res next 101 32 by 16 d architecture the first set of results they present shows the success of the semi-supervised learning framework with different student models so first we're looking at the resident 18 the resident 50 and then higher versions of the