In this work, we present an accelerated force field parameterization scheme. We gain speed by avoiding significant amounts of molecular simulation, instead replacing these runs using reweight-ing observables estimated the observables with well-bounded statistical uncertainty. The reweighting formalism requires a re-evaluation of the energies with the new set of parameters using the configurations generated in simulations run with the initial guess set of parameters. In the proper contexts, the time required to estimate observables using re-evaluated energies is orders of magnitude less compared to a fresh at each of these parameter points. Reweighting works well to predict thermodynamic properties at unsampled states as long as there is sufficient phase space overlap between the sampled and the unsampled parameter sets. As the phase space overlap between the simulated and target ensemble decreases, however, the uncertainty in the estimated thermodynamic quantities increases. Not only do the larger uncertainties makes the comparison between the observables between two iterations difficult, requiring additional simulation data, for sufficiently low phase space overlap, the uncertainties become unreliable. To verify the calculations done using reweighting, one should at also perform occasional simulations to estimate observables using directly sampled configurations; for example, when reaching a minimum in the objective function computed from reweighted observables. These adaptively performed simulations will ensure that the predicted ensemble has not deviated too much from the true ensemble that would be generated with those same parameters.