A single accuracy rate is not that useful when looking at ML problems. There is always a tradeoff between false positives and false negatives depending on the threshold selected. Amazon is guilty of this in this article, saying 0% false positive rate when you set the threshold to 99%. However, it doesn't say how many faces it successfully matched, it's easy to have a 0% false positive rate if you just say "no match" for every photo.

The best practice is to show a ROC curve, which shows the tradeoffs of selecting a given threshold: https://en.wikipedia.org/wiki/Receiver_operating_characteris...