Model.py

from keras.models import Sequential, load_model
from keras.layers import *
from keras.callbacks import ModelCheckpoint, EarlyStopping

model = Sequential()
model.add( LSTM(units=512,
               input_shape = (normalised_network_input.shape[1], normalised_network_input.shape[2]),
               return_sequences = True) )
model.add( Dropout(0.3) )
model.add( LSTM(512, return_sequences=True) )
model.add( Dropout(0.3) )
model.add( LSTM(512) )
model.add( Dense(256) )
model.add( Dropout(0.3) )
model.add( Dense(n_vocab, activation="softmax") )

model.compile(loss="categorical_crossentropy", optimizer="adam")

model.summary()

checkpoint = ModelCheckpoint("model.hdf5", monitor='loss', verbose=0, save_best_only=True, mode='min')


model_his = model.fit(normalised_network_input, network_output, epochs=100, batch_size=64, callbacks=[checkpoint])