F1 Score vs ROC AUC

Question

I have the below F1 and AUC scores for 2 different cases

Model 1: Precision: 85.11 Recall: 99.04 F1: 91.55 AUC: 69.94

Model 2: Precision:

Answer 1

just adding my 2 cents here:

AUC does an implicit weighting of the samples, which F1 does not.

In my last use case comparing the effectiveness of drugs on patients, it's easy to learn which drugs are generally strong, and which are weak. The big question is whether you can hit the outliers (the few positives for a weak drug or the few negatives for a strong drug). To answer that, you have to specifically weigh the outliers up using F1, which you don't need to do with AUC.