Defining vocabulary size and output dimension is required in an Embedding layer. Other arguments are optional. You can experiment and see if they make a difference in your case.
If the targets are represented by a one-hot encoded matrix, the loss is categorical crossentropy. If the targets are just one column with various labels, the loss is sparse categorical crossentropy.
BatchNormalization is most often used in convolutional neural networks. It is also used between a dense layer with linear activation and following non-linear activation function.