I ran ten chains with uniform(0,0.0001) randomly select stepsize and nsteps random uniform(1,100). The only chains that moved at all had step sizes less than 0.002. These chains explored the posterior, but barely. Convergence diagnostics were far from acceptable after 10,000 iterations. Still no luck using HMC for complex models. Default metropolis sampling works much better for these problem, and, for those problems where I can get HMC to work, the default sampler works just fine.
Please share any experiences that you have with HMC!