The WS22 dataset is a recent collection focused on molecular systems generated using harmonicoscillator Wigner sampling and geodesic interpolation between trans and cis conformations. This dataset spans a wider range of the configurational space, presenting a significant challenge for out-ofdistribution predictions. Energies and forces for the dataset were computed at the PBE0/6 -311G* level of theory. Specifically, the acrolein dataset is composed of 120,000 geometries, distributed as (1) 50,000 geometries in the trans conformation; (2) 50,000 geometries in the cis conformation; (3) 20,000 geometries derived from the geodesic interpolation connecting the two conformers. For model training, we considered only the trans conformers, leveraging ANI deep ensembles, with a train-validation split of 90:10.