In contrast to traditional, piece-wise parameterizations of classical potentials, AutoBADDIE operates using an ADAM optimizer 21 to directly learn all classical IP parameters based on the mean squared error (MSE) between DFT and classical IP forces and energies using the PyTorch package in Python, building on the well established paradigm of force-matching.