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WIP WIP: remap tagger and classifier onto Trainer oops fix issue with span F1 aggregation in Trainer adds support for other loss functions like KLDiv this is useful for cases like distillation where we can have soft targets. pass kwargs into target use forward function option whether to rm wrapper support overriding the train target This should fix multiworker mismatch on reload feelgood types fix first batch accum allow no early stopping global_step fix, clean examples, factor up more cleanup fix includes in addon rm dist code outside 8mi trainer, WIP dataset use native loaders via mead pseudo fix for showing examples fix default and backend arg in paired reader bye six + tmp working non-native LM loader add backend option LM is TF native fix test remove and simplify tf trainers and fix trim issue be a little tricky with TF native we cant switch it on with TF 1.x . explore more modular refactoring WIP WIP: remap tagger and classifier onto Trainer oops fix issue with span F1 aggregation in Trainer adds support for other loss functions like KLDiv this is useful for cases like distillation where we can have soft targets. pass kwargs into target use forward function option whether to rm wrapper support overriding the train target This should fix multiworker mismatch on reload feelgood types fix first batch accum allow no early stopping global_step fix, clean examples, factor up more cleanup fix includes in addon rm dist code outside 8mi trainer, WIP dataset use native loaders via mead pseudo fix for showing examples fix default and backend arg in paired reader bye six + tmp working non-native LM loader add backend option LM is TF native fix test remove and simplify tf trainers and fix trim issue .
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mead3_pytorch, supports future (distributed) training using 8mi viafit_func=mead3sixneg_log_loss