• Materials Project which consists of crystal structures and DFT- calculated properties of inorganic compounds collected from the iCSD , predicted at GGA (Gneralised Gradient Approximation) level of theory. It is provided as a database snapshot, 2018.6.1, (MP18) containing 69,684 structures with calculated formation energy (E f ) and band gap (E g ). In line with previous studies , materials containing noble elements (He, Ne, Ar, Kr, Xn) were excluded due to their infrequency, bringing the dataset down to 69,239 datapoints. Here we use the same training split used in . • Matbench which is a collection of dataset benchmarks maintained by the Materials Project, containing both structure and non-structure datasets covering a variety of prediction targets. We use tasks with more than 10,000 available datapoints with structural information, namely formation energy (E f ), band gap(E g ), Metallicity Classification (IsMetal ), Perovskiteonly formation energy (Perovskites), log10 VRH-averaged bulk modulus (log(K)), and log10 VRH-averaged sheer modulus (log(G)). We use predefined splits for training and test and five-fold cross-validation to ensure proper comparison amongst models.