Models trained and tested on dataset 2 perform about 3nm better on average (MAE). Most probably this phenomenon is caused by better homogenity in compounds classes in dataset 2. The dataset of compounds composed only of C, O, N, F atoms also lacks maximum emission outliers which could affect the performance of prediction.