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I start a learning rate of 0.01, and reduce it to 0.001 when the accuracy on the evaluation set stops improving. which lr_policy should I choose? I am a beginner, thanks for your patience .
Dinesh
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Mar 26, 2015, 10:36:55 AM3/26/15
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When I find that optimizing learning schedule-related hyperparameters for a bunch of baselines is cumbersome in practice, I find that starting with a learning rate around 1e-3 and using a solver like ADAGRAD or NESTEROV that adapts the learning rate by itself does reasonably well and spares me the headache of huge grid searches.