Text sequence to integer with many integer classes in Keras
Maybe you can formulate it as sequence prediction problem using RNN or regression problem with N digit output nodes.
I am getting strings ex. "one hundred twenty three", or "nine hundred ninety nine", and encoding it into a sequence of word tokens of length 4 using the Keras text preprocessing tokenizer and using it as my input with 4 nodes, and having many integer classes as my output ex. 0 1 2 ... 1000 with 1001 output nodes with a tensorflow backend.
I'm using an embedding input layer and then a flatten layer and then a dense output layer with softmax activation to classify the input sequence to a number. 
This approach works well for numbers from 0-1000 etc. but scaling up to 100,000 numbers with strings like "eighty seven thousand four hundred twenty three" proves to be a problem with very long training times as there's 100,000 output neurons.
Is there a better way to structure the NN for possibly millions of numbers without sacrificing efficiency?