incer_1

#baris ke 68
#train the model using the Adam optimizer
print("[INFO] training network...")
opt = Adam(lr=1e-3, decay=1e-3 / 50)
model.compile(loss="categorical_crossentropy", optimizer=opt
  metrics=["accuracy"])
H = model.fit(trainX, trainY, validation_data=(testX, testY),
  epochs=50, batch_size=32)

#evaluate the network
print("[INFO] evaluating network...")
predictions = model.predict(testX, batch_size=32)
print(classification_report(testY.argmax(axis=1),
  predictions.argmmax(axis=1), target_names=lb.classes_))