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* Add _determine_best_metric and new saving logic. 1. Logic to determine the best logic was separated out from `_save_checkpoint`. 2. In `_maybe_log_save_evaluate`, whether or not a new best metric was achieved is determined after each evaluation, and if the save strategy is "best' then the TrainerControl is updated accordingly. * Added SaveStrategy. Same as IntervalStrategy, but with a new attribute called BEST. * IntervalStrategy -> SaveStrategy * IntervalStratgy -> SaveStrategy for save_strat. * Interval -> Save in docstring. * Updated docstring for save_strategy. * Added SaveStrategy and made according changes. `save_strategy` previously followed `IntervalStrategy` but now follows `SaveStrategy`. Changes were made accordingly to the code and the docstring. * Changes from `make fixup`. * Removed redundant metrics argument. * Added new test_save_best_checkpoint test. 1. Checks for both cases where `metric_for_best_model` is explicitly provided and when it's not provided. 2. The first case should have two checkpoints saved, whereas the second should have three saved. * Changed should_training_end saving logic. The Trainer saves a checkpoints at the end of training by default as long as `save_strategy != SaveStrategy.NO`. This condition was modified to include `SaveStrategy.BEST` because it would be counterintuitive that we'd only want the best checkpoint to be saved but the last one is as well. * `args.metric_for_best_model` default to loss. * Undo metric_for_best_model update. * Remove checking metric_for_best_model. * Added test cases for loss and no metric. * Added error for metric and changed default best_metric. * Removed unused import. * `new_best_metric` -> `is_new_best_metric` Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Applied `is_new_best_metric` to all. Changes were made for consistency and also to fix a potential bug. --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Zach Mueller <muellerzr@gmail.com> |
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| .. | ||
| agents | ||
| benchmark | ||
| bettertransformer | ||
| deepspeed | ||
| extended | ||
| fixtures | ||
| fsdp | ||
| generation | ||
| models | ||
| optimization | ||
| peft_integration | ||
| pipelines | ||
| quantization | ||
| repo_utils | ||
| sagemaker | ||
| tokenization | ||
| trainer | ||
| utils | ||
| __init__.py | ||
| test_backbone_common.py | ||
| test_configuration_common.py | ||
| test_feature_extraction_common.py | ||
| test_image_processing_common.py | ||
| test_image_transforms.py | ||
| test_modeling_common.py | ||
| test_modeling_flax_common.py | ||
| test_modeling_tf_common.py | ||
| test_pipeline_mixin.py | ||
| test_processing_common.py | ||
| test_sequence_feature_extraction_common.py | ||
| test_tokenization_common.py | ||