In Sec. 3.1 we demonstrated that our multitask procedure is a simplified, but viable alternative to the transfer learning procedure of Smith et al. Next we turn to study the behavior of the procedure when we train to more than two datasets. We now include the OrbNet Denali and SPICE datasets. Here we will use the HCNO subset of a test set of torsion scans of neutral druglike molecules reported previously to probe torsion profiles over a broader re- gion of chemical space than that probed by the Sellers dataset studied in Section 3.1. We have relabeled this test set with the ωB97X-D3/def2-TZVP level of theory and use that as the reference. We believe this reference is sufficient for our purposes and the error between this level of theory and CCSD(T)/CBS for these relative conformational energies are likely to be much smaller than the errors between the models and CCSD(T)/CBS results. This dataset contains 369 torsion scans and covers a much more significant sample of chemical space, representing a stronger test of transferability.