[D] With which objective do I get a more desirable Precision-Recall-Threshold?

[Higher auc-roc, but undesirable](https://preview.redd.it/5ezth9kxrj8d1.png?width=1000&format=png&auto=webp&s=31731c249c17f69aaa3c5da41d1894ceaf7cfe9d)

[Lower auc-roc, but desirable](https://preview.redd.it/gv9wmv8zrj8d1.png?width=1000&format=png&auto=webp&s=165c5981fc418b302a7284a23402dcbfe2382ac2)

I have an unbalanced binary classification dataset (60/40). However, I do apply class balancing (using BinaryFocalCrossentropy). For the tuning process I have both tried optimising for AUC-PR and AUC-ROC, but keep getting these results as seen in the images, whereby the first image has a higher score, but is more undesirable. What is the advice here for the choice of objective metric? I would have used F1 Score, but I really don't …

advice apply auc binary class classification dataset however image images machinelearning process results roc tuning