model = Sequential()
model.add(pretrained_embedding_layer(word_to_vec_map, word_to_index))
model.add(GRU(128, dropout=0.2, return_sequences=True))
model.add(GRU(128, dropout=0.2))
model.add(Dense(1))
model.add(Activation('sigmoid'))

model.compile(loss='binary_crossentropy',
              optimizer='adam',
              metrics=['accuracy'])