for their adsorption on closed-packed metal surfaces. The data is employed to train a proposed graph neural network architecture. The 5-fold cross validation revealed a mean absolute error of 0.17 eV when applied to the FG-dataset. Once trained, the human time required to obtain the energy estimation from GNN is at least six orders of magnitude lower than DFT.