I was trying to think of how to implement the exercise mentioned here http://pytorch.org/tutorials/beginner/nlp/sequence_models_tutorial.html 16
To augment the POS tagger I would have to find charecter level representation of each word. So I was wondering how would the ground truth look like ? For example for the word The, if I passed that to nn.Embedding(number_of_unique_letters,embed_dim) and then passed that to an nn.LSTM and then finally to a fully connected layer, what would the loss compare against ?