• Single-label model: one hidden layer with 1024 nodes and it has a dropout layer with dropoutrate 0.60 between each layer. It uses ReLU as its activation layer between layers, except for the final layer which uses a softmax activation. The single-label model was trained using categorical cross-entropy loss, and Adam optimizer with a learning rate of 6.1*10 -4 . It was trained for 10 epochs using a batch size of 64.