The "60" refers to the length of the FIR filter. An FIR model typically has larger number of coefficients than a rational transfer function model. Hence the "large number" 60. The exact value of the filter length is not known in advance. You have to try out various values and evaluate the resulting quality of the model using tools such as COMPARE, RESID, and evaluating confidence bounds on impulse response and step response plots.
Note that the estimation is "regularized" unless you choose regularization kernel to be "none" (see IMPULSEESTOPTIONS). This means that choosing too large a value for the filter length would not adversely affect its quality too much. So go with a reasonably large number of coefficients (such as 1/10 of data length).
