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3.4.0 - 2023-06-19
Added
every_n_train_steps parameter now controls the frequency of both validation epochs and model checkpointing during training.
Changed
We now log steps rather than epochs as units of progress during training.
Validation performance metrics are logged (and added to tensorboard) at the validation epoch, and training loss is logged at the end of training epoch, i.e. training and validation metrics are logged asynchronously.
Fixed
Correctly refer to input peak files by their full file path.