John works at Yahoo and and trains a logistic regression classifier to find junk mail. He decides to use gradient descent to obtain the weights for the model. On the first go at it, he notices that the log likelihood decreases after every iteration. It continues decreasing and John then believes that the learning rate is not big enough. He decides he should increase the learning rate. Is this a correct or incorrect practice?