Using specific metrics to evaluate a predictive model on a given data set is not the same as using those metrics to compare the performance of that model on two or more distinct data sets.

The metrics are primarily useful for comparing the performance of two or more models on the SAME data set.

The metrics used may be dependent on the proportions of each binary category ( Good, Bad ) within the data set and as such if the two data sets that are used for the comparison have significantly different Good/Bad ratios then the use of these metrics may be misleading.