If you are dealing with a multi-class classification use case, your target should contain the class index for each sample, which seems to be the case.
However, the output of your model seems still to have an additional dimension (probably the sequence length), which needs to be reduced.
You could apply an average pooling layer or any other operation, which creates an output of shape [batch_size, nb_classes].