Multiple classification algorithms are predicting always exactly with the same scores. Is that normal? If not, what should I suspect?
Same accuracies and losses for multilabel classification usually refer to the fact that model just chooses majority class. Please check the confusion matrix. Definitely, it is not a normal occurrence and you need to deal with it.