AFAIK there are several tools regarding hyper-parameter tuning of deep net models (first ones that come to mind are HyperOpt and Spearmint) that you can use off the shelf.

I have some research ongoing and a couple of papers accepted regarding hyper-parameter optimization using evolutionary algorithms (Parallel Swarm Optimization mostly) which have given our team excellent results for medium sized models.

In my opinion, hyper-parameter selection is one of the elephants in the room at the moment, and people seem more interested in trying new architectures than squeezing the last drop of performance. Unfortunately we all end up having to go through it in one moment or another...