Adaptive Training

Adaptive-training focuses to adjust the number of iterations or interval for the validation to achieve the fast training. In the small data regime, we don’t need to validate the model at every epoch since there are a few iterations at a single epoch. To handle this, we have implemented module named AdaptiveTrainScheduling. This callback controls the interval of the validation to do faster training.

Note

AdaptiveTrainScheduling changes the interval of the validation, evaluation and updating learning rate by checking the number of dataset.

API

from otx.algo.callbacks.adaptive_train_scheduling import AdaptiveTrainScheduling

engine.train(callbacks=[AdaptiveTrainScheduling()])

CLI

(otx) ...$ otx train ... --callbacks otx.algo.callbacks.adaptive_train_scheduling.AdaptiveTrainScheduling