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our experiments have shown that, when using data augmentation, a two step training approach is sensible:
train on all available lines (real + augmented).
refine the models resulting from 1 by training on real lines only and use the outcome of 1 as a starting point.
it would be nice if these training steps could be automatically performed by calamari without requiring any futher input by the user. the auto config proposed in #33 might be helpful :-).
The text was updated successfully, but these errors were encountered:
our experiments have shown that, when using data augmentation, a two step training approach is sensible:
it would be nice if these training steps could be automatically performed by calamari without requiring any futher input by the user. the auto config proposed in #33 might be helpful :-).
The text was updated successfully, but these errors were encountered: