Keras: Very high loss for Autoencoder
You should not use the categorical cross-entropy loss, but the binary cross-entropy.
The categorical cross-entropy is meant for categorical probability distribution. In your scenario, this means that only one label would be active at the same time. If multiple labels can be active at the same time, then they are independent, and you need to compute the binary cross-entropy.