In principle, when you are generating starting positions for umbrella sampling, you can use a fairly high pull rate, in most cases. What you need to keep in mind though, is that a high pull rate means that you are pulling far from equilibrium. This may in turn mean that you need to discard more data in the beginning of each of your umbrella sampling windows to get stable and reliable results. Pulling for a few more ns might save you a significant amount of time if you use many umbrella windows.
You can’t get the free energy barrier, at least not reliably, just from the pull force of a single pulling simulation. You should have a look at Jarzynski’s equality and Crooks’ fluctuation theorem. With Jarzynski’s equality you pull multiple times (very many times) in one direction to get the PMF, but the friction is not properly accounted for. With Crooks’ fluctuation theorem you pull in both the forward and reverse direction, which means that you can get a better estimate of the PMF by accounting for the friction (dissipated work). Unless you know what you are doing, I would recommend sticking to umbrella sampling, or possibly consider AWH or metadynamics etc.