Resetting of high scores, scheduler and optimizer for fine-tuning/domain adaptation

[juliakreutzer]

In the case of fine-tuning or domain adaptation, one might want to overwrite the existing scheduler or optimizer or the previously tracked high score.
This is specifically relevant when fine-tuning with a different metric or a data where the validation score is in a different range than the loaded model (e.g. pre-training on BLEU and fine-tuning on PPL would result in never storing a new checkpoint). When the data is much smaller than the previous training data, one might want to reduce the patience.

We can also think about modeling this as "load_x_from_ckpt" rather than "reset_x", but for now, it seems that in the default case we want to load everything.

[dwhitena]

This works for me. When the flags are set, I can see the checkpoints being saved in the filesystem and logged properly. Thanks for updating this!

[juliakreutzer]

Awesome, thanks for confirming this so quickly @dwhitena! And an official welcome as collaborator! 🎉