Using bootstrapping to pick best sample based on model performance

Question

I'm trying to use bootstrapping to pick a good training sample for a model development based on the model performance(AUC of ROC curve) for each bootstrapped sample. Is this a good method to follow? . Because I always find a better AUC when doing a model while changing sample along the way.