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Co-authored-by: Pavel Tarashkevich <Pavel.Tarashkievich@orange.com>

* Allow example to use a revision and work with private models

* Copy to other examples and template

* Styling

* Update the README of the text classification example

* Update examples/README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Adapt comment from review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add speed metrics

* suggestions

* Reorganize example folder

* Continue reorganization

* Change requirements for tests

* Final cleanup

* Finish regroup with tests all passing

* Copyright

* Requirements and readme

* Make a full link for the documentation

* Address review comments

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add symlink

* Reorg again

* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Adapt title

* Update to new strucutre

* Remove test

* Update READMEs
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

Without this fix, training a `BARTForSequenceClassification` model with `run_pl_glue.py` gives `TypeError: forward() got an unexpected keyword argument 'token_type_ids'`, because BART does not have token_type_ids. I've solved this issue in the same way as it's solved for the "distilbert" model, and I can train BART models on SNLI without errors now.

* <small>tiny typo</small>

* Tokenizers: ability to load from model subfolder

* use subfolder for local files as well

* Uniformize model shortcut name => model id

* from s3 => from huggingface.co
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

* Finish the cleanup of the language-modeling examples

* Update main README

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Propagate changes
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* New run_clm script

* Formatting

* More comments

* Remove unused imports

* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Address review comments

* Change link to the hub
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Start simplification

* More progress

* Finished script

* Address comments and update tests instructions

* Wrong test

* Accept files as inputs and fix test

* Update src/transformers/trainer_utils.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Fix labels and add combined score

* Add special labels

* Update TPU command

* Revert to old label strategy

* Use model labels

* Fix for STT-B

* Styling

* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Code styling

* Fix review comments
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Don't use `store_xxx` on optional bools

* Refine test

* Refine test

* Fix test

* fix generic text classification

* fix test

* Fix tests

* Fix test

* Fix cardinality issue

* Fix test

* Add new example with nlp

* Update README

* replace nlp by datasets

* Update examples/text-classification/README.md

Add Lysandre's suggestion.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* fix compute_metrics_fn

* p.predictions -> preds

* apply suggestions

* add pl_glue example test

* for now just test that it runs, next validate results of eval or predict?

* complete the run_pl_glue test to validate the actual outcome

* worked on my machine, CI gets less accuracy - trying higher epochs

* match run_pl.sh hparms

* more epochs?

* trying higher lr

* for now just test that the script runs to a completion

* correct the comment

* if cuda is available, add --fp16 --gpus=1 to cover more bases

* style

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Fully rework training/prediction loops

* fix method name

* Fix variable name

* Fix property name

* Fix scope

* Fix method name

* Fix tuple index

* Fix tuple index

* Fix indentation

* Fix variable name

* fix eval before log

* Add drop remainder for test dataset

* Fix step number + fix logging datetime

* fix eval loss value

* use global step instead of step + fix logging at step 0

* Fix logging datetime

* Fix global_step usage

* Fix breaking loop + logging datetime

* Fix step in prediction loop

* Fix step breaking

* Fix train/test loops

* Force TF at least 2.2 for the trainer

* Use assert_cardinality to facilitate the dataset size computation

* Log steps per epoch

* Make tfds compliant with TPU

* Make tfds compliant with TPU

* Use TF dataset enumerate instead of the Python one

* revert previous commit

* Fix data_dir

* Apply style

* rebase on master

* Address Sylvain's comments

* Address Sylvain's and Lysandre comments

* Trigger CI

* Remove unused import

* Cleanup and unify Trainer/TFTrainer

* Forgot to adapt TFTrainingArgs

* In tf scripts n_gpu -> n_replicas

* Update src/transformers/training_args.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Address review comments

* Formatting

* Fix typo
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* all save_pretrained methods mkdir if not os.path.exists

* Glue task cleaup

* Enable writing cache to cache_dir in case dataset lives in readOnly
filesystem.
* Differentiate match vs mismatch for MNLI metrics.

* Style

* Fix pytype

* Fix type

* Use cache_dir in mnli mismatch eval dataset

* Small Tweaks
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Kill model archive maps

* Fixup

* Also kill model_archive_map for MaskedBertPreTrainedModel

* Unhook config_archive_map

* Tokenizers: align with model id changes

* make style && make quality

* Fix CI