two things you can do are early stopping + using a subset of your dataset.
In my experience, hyperparams that have the best convergence at 3~5 epochs will generalize to pretty good convergence on a full training run. It won't guarantee the best performance, but if you're on a budget it's a great compromise.
techlos t1_ir131zp wrote
Reply to [D] How do you go about hyperparameter tuning when network takes a long time to train? by twocupv60
two things you can do are early stopping + using a subset of your dataset.
In my experience, hyperparams that have the best convergence at 3~5 epochs will generalize to pretty good convergence on a full training run. It won't guarantee the best performance, but if you're on a budget it's a great compromise.