Created
August 17, 2020 01:12
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model1 = Sequential([ | |
Dense(512, activation='tanh', input_shape = X_train[0].shape), | |
Dense(512//2, activation='tanh'), | |
Dense(512//4, activation='tanh'), | |
Dense(512//8, activation='tanh'), | |
Dense(32, activation='relu'), | |
Dense(3, activation='softmax') | |
]) | |
print(model1.summary()) | |
model1.compile(optimizer='sgd',loss='categorical_crossentropy', metrics=['acc', 'mse']) | |
hist = model1.fit(X_train, y_train, epochs=350, batch_size=128, validation_data=(X_test,y_test)) |
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