The test set was held constant and used for all GNN models that were trained in this study. Because ionic solvation free energies were only constructed for overlapping gas-phase acidities and pK a data, and because pK a and solvation free energy data can be stratified by solvents whereas gas-phase acidities cannot, there were sometimes different amounts of data available for the pK a and gas-phase acidity data than that for the ionic solvation free energies. This resulted in different split proportions. In all cases, the train -validation ratio was maintained as 8:1. For gas-phase data, 8.6% of the data was held out as the test set, whereas for pK a , 7.5% was held out. This splitting strategy means that test performance is not indicative of extrapolation to new solvents or chemical classes (in which case we already expect that the model would not perform well, given the highly limited number of quality data in such solvents, unknown values of the proton's transfer energy, and strong dependence of solvation free energies on functional group), but rather to new solutes of existing classes, which presents a more realistic application of such models.