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Minimally: End training if a certain target accuracy isn't reached by some (early-ish) number of steps. This can be set manually to automatically catch jobs that fail due to a poor random seed.
Ideally: Integrate with some kind of experiment manager for hyperparameter tuning, so as to kill jobs that perform well below average early in tuning.
The text was updated successfully, but these errors were encountered:
Issue by sleepinyourhat
Thursday Apr 09, 2020 at 21:08 GMT
Originally opened as nyu-mll/jiant#1055
Inspired by: https://arxiv.org/abs/2002.06305
Minimally: End training if a certain target accuracy isn't reached by some (early-ish) number of steps. This can be set manually to automatically catch jobs that fail due to a poor random seed.
Ideally: Integrate with some kind of experiment manager for hyperparameter tuning, so as to kill jobs that perform well below average early in tuning.
The text was updated successfully, but these errors were encountered: