In the bottom-up force field development, we need to fit the energies or the forces to ab initio results. The object functions are typically the root mean square error (RMSE) or weighted RMSE of energies and forces, which can be directly computed using the DMFF force field calculator. The JAX implementation of the molecular force fields enables us to utilize the state-of-the-art optimizers developed in the ML community, designed to perform robustly when fitting a large number of nonlinear parameters. Here, we show a complicated energy fitting example, the goal of which is to fit the short-range and damping parts of an ab initio potential. The total energy is decomposed into several physically meaningful terms, including exchange (ex), electrostatic (es), dispersion (disp), polarization (pol), and dHF (dhf) interactions. All these terms can be computed using the ab initio Symmetry Adapted Perturbation Theory (SAPT) method, and the short-range parts of them are then fitted using the following functions: