I'm using a deep hashing model to search most similar images in a database (most similar to the image given as a query). I'm doing this on the coco dataset which has multiple labels per image. I'd like to evaluate the performance of the model but I'm not sure what type of metric should be used here.
If it was just a single label per image, I'd go for something like mean average precision (given a query image of a dog, check how many dog images the system retrieved, evaluate MAP). But this obviously cannot be used on the multi label task (given a query image of three classes, system retrieved image with just one of them, it's not totally correct but it's not incorrect either). So are there any commonly used metrics to evaluate this kind of tasks? If so, please refer me to them. Or do I have to come up with something own (maybe some kind of a weighted MAP)?