Before trying to interpret the rest of the results, first look at the best-fit value of each parameter in your model. First make sure you know what units each parameter is expressed in (if there are any units; some parameters are unitless constants). Next,  make sure each value makes biological or scientific sense. If a value doesn't make any sense, ask your self these questions:

•Does your data actually define all the parameters?

•Should you be constraining a parameter (or several) to constant values? If not, should you be constraining them to have a range of values (only positive numbers, perhaps)?

•Should you be fitting a family of datasets together using global nonlinear regression?