In addition, while early stopping after around 2000 epochs did improve significantly validation performance of these larger models, the results still did not surpass those obtained with the chosen smaller architecture. Consequently, the simpler, shallower model (employing 4737 trainable parameters) was deemed more appropriate for our specific dataset (see Tables and in Supporting Information for different choices of the number of neurons and layers for the n-LMF based on a hyper-meta-GGA set of features; cf. also below).