Since training single lipid membranes on their own would lead to non-transferable overfitted parameters to that specific lipid (see Supporting Information), in each epoch, we opt to train a set of them and apply the parameter update step only after all the lipids in the set have been simulated (Fig. ). This ensures that the parameters are transferable among the different lipids. We achieve this by computing a mean loss