Overall, the D-MPNN/FFNN model demonstrates fairly good predictive accuracy for pK a values in solvents where sufficient amount of training data was available, even when applied to acids not included in the training set. We emphasize that such training was done on a relatively small subset of training data: only 6,774 datapoints, owing to examining only mono-anions and the rigorous cleaning process. The number of training data here is much lower than other multi-solvent literature models, which have been trained on 20,000+ datapoints. Nonetheless, our model still achieves a comparably good predictive ability. Variations of our model trained on slightly smaller splits of data demonstrate worse performance, indicating that continuing to add data would improve the model (see SI).