# define model | |
model = Sequential() | |
model.add(Embedding(vocab, 50, input_length=30, trainable=True)) | |
model.add(GRU(150, recurrent_dropout=0.1, dropout=0.1)) | |
model.add(Dense(vocab, activation='softmax')) | |
print(model.summary()) | |
# compile the model | |
model.compile(loss='categorical_crossentropy', metrics=['acc'], optimizer='adam') | |
# fit the model | |
model.fit(X_tr, y_tr, epochs=100, verbose=2, validation_data=(X_val, y_val)) |
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