1. A method of training a machine learning system to determine photoresist parameters of a wafer application to fabricate a structure on a wafer using optical metrology, the method comprising: a) obtaining a set of different values of one or more photoresist parameters, wherein the one or more photoresist parameters characterize behavior of photoresist when the photoresist undergoes processing steps in the wafer application; b) obtaining a set of diffraction signals using the set of different values of the one or more photoresist parameters; and c) training a machine learning system using the set of diffraction signals as inputs to the machine learning system and the set of different values of the one or more photoresist parameters as expected outputs of the machine learning system, wherein the one or more photoresist parameters comprise change of inhibitor concentration, surface inhibition, diffusion during the photoresist baking process, development rate parameters, labile absorptivity, non-labile absorptivity, and/or intrinsic sensitivity of the photoresist.