Dear computer vision community,
I have to find a suitable model for recognizing different events within video clips. I am a little bit confused in considering my task as a multilabel-multiclass classification or multitask classification problem and how should this be implemented
Explanation of the task: From a video clip I need to know if :


an Event A occured or not


was it successful, not successful, or out


was it performed using right or left hand


Which type of event was it (there are 6 types)


was it done while running, walking, jumping or standing-up


So the 5 labels need to be returned and each returned label can have one of the subclasses.

Should 5 different output layers for 5 different outputs be implemented? Each one of them has n_classes = subclasses

self.fc1 = nn.Linear(block_inplanes[3] * block.expansion, n_classes1)
self.fc2 = nn.Linear(block_inplanes[3] * block.expansion, n_classes2)
self.fc3 = nn.Linear(block_inplanes[3] * block.expansion, n_classes3)
self.fc4 = nn.Linear(block_inplanes[3] * block.expansion, n_classes4)
self.fc5 = nn.Linear(block_inplanes[3] * block.expansion, n_classes5)
or

should I have only one output layer ;

self.fc = nn.Linear(block_inplanes[3] * block.expansion, n_classes)
If the 2nd one is the right answer, how could this be implemented?
I would be very thankful for your precious help.