GitLab

* Update run_translation_no_trainer.py

found an error in selecting `no_decay` parameters and some small modifications when the user continues to train from a checkpoint

* fixs `no_decay` and `resume_step` issue

1. change `no_decay` list
2. if use continue to train their model from provided checkpoint, the `resume_step` will not be initialized properly if `args.gradient_accumulation_steps != 1`

* Added accelerate gradient accumulation wrapper to run_image_classification_no_trainer.py example script

* make fixup changes

* PR comments

* changed input to Acceletor based on PR comment, ran make fixup

* Added comment explaining the sync_gradients statement

* Fixed lr scheduler max steps

* Changed run_clm_no_trainer.py script to use accelerate gradient accum wrapper

* Fixed all scripts except wav2vec2 pretraining to use accelerate gradient accum wrapper

* Added accelerate gradient accum wrapper for wav2vec2_pretraining_no_trainer.py script

* make fixup and lr_scheduler step inserted back into run_qa_beam_search_no_trainer.py

* removed changes to run_wav2vec2_pretraining_no_trainer.py script and fixed using wrong constant in qa_beam_search_no_trainer.py script

* zero chance anyone's using that constant no?

* `transformers-cli login` => `huggingface-cli login`

* `transformers-cli repo create` => `huggingface-cli repo create`

* `make style`

* Update no_trainer script for image-classification

* Update no_trainer scripts for language-modeling examples

* Remove unused variable

* Removing truncation from losses array for language modeling examples

* Fix ROUGE add example check and update README

* Stay consistent in values

* Migrate metric to Evaluate in pytorch examples

* Remove unused imports

Properly calculate the total train iterations and recalculate num epochs in no_trainer scripts (#17856)

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

* improve no-trainer examples

* Trigger CI

* adding comment to clarify tracker init on main process

* Trigger CI

* Trigger CI

* Trigger CI

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* Update all examples to properly calculate progress bar

* Propagate and fix imports

* Fixup all examples

* Fix multiple deletions of the same files in save_pretrained

* Add is_main_process argument

* Change tracking to store_true

* Remove step param and use it in the log dictionary directly

* use vars(args) when passing args to init_trackers

* Include tracking tests since tensorboard is already a dep

Adds checkpoint prefixes to the gitignore if `push_to_hub` is used along with `checkpointint_steps`

* Fixed some bugs involving saving during epochs
* Added tests mimicking the existing examples tests
* Added in json exporting to all `no_trainer` examples for consistency 

Adds logging and save/loading to the Accelerate scripts
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix formatting and remove use_auth

* Add use_auth_token to Flax examples

* [examples] max samples can't be bigger than then len of dataset

* do tf and flax

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Updates the default branch from master to main

* Links from `master` to `main`

* Typo

* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add preprocess_logits_for_metrics Trainer param

* Compute accuracy in LM examples

* Improve comments