GitLab

* added log_level

* fix comment

* fixed log_level

* Trigger CI

* Unfied logging

* simplified args for log_level

* Don't log anything before logging is setup in examples

* Last example

* add relevant `desc` in examples

* require_version datasets>=1.8.0

* Add option to long only once in multinode training

* Use an alternate property

* Split checkpoint from model_name_or_path in examples

* Address review comments

* Address review comments

* added changes for uniformity

* modified files

* corrected typo

* fixed qa scripts

* fix typos

* fixed predict typo in qa no trainer

* fixed test file

* reverted trainer changes

* reverted trainer changes in custom exmaples

* updated readme

* added changes in deepspeed test

* added changes for predict and eval

* Base move

* Examples reorganization

* Update references

* Put back test data

* Move conftest

* More fixes

* Move test data to test fixtures

* Update path

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

* Address review comments and clean
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* model_path is refered as the path of the trainer, and should be ignored as the checkpoint path.

* Improved according to Sgugger's comment.

* added predict stage

* added test keyword in exception message

* removed example specific saving predictions

* fixed f-string error

* removed extra line
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Add minimum version check in examples

* Style

* No need for new line maybe?

* Add helpful comment

* reverted changes of logging and saving metrics

* added max_sample arguments

* fixed code

* white space diff

* reformetting code

* reformatted code

* updated logging and saving metrics

* space removal

* remove xnli_compute_metrics, add load_dataset, load_metric, set_seed,metric.compute,load_metric

* fix

* fix

* fix

* push

* fix

* everything works

* fix init

* fix

* special treatment for sepconv1d

* style

* 🙏🏽

* add doc and cleanup


* fix doc

* fix doc again

* fix doc again

* Apply suggestions from code review

* make style

* Proposal that should work

* Remove needless code

* Fix test

* Apply suggestions from code review

* remove xnli_compute_metrics, add load_dataset, load_metric, set_seed,metric.compute,load_metric

* amend README

* removed data_args.task_name and replaced with task_name = "xnli"; use split function to load train and validation dataset separately; remove __post_init__; remove flag --task_name from README.

* removed dict task_to_keys, use str "xnli" instead of variable task_name, change preprocess_function to use examples["premise"], examples["hypothesis"] directly, remove sentence1_key and sentence2_key, change compute_metrics function to cater only to accuracy metric, add condition for train_langauge is None when using dataset.load_dataset()

* removed `torch.distributed.barrier()` and `import torch` as `from_pretrained` is able to do the work; amend README

* make executable

* make executable

* same for the template

* cleanup

* <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>

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

* 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

* Created using Colaboratory

* [examples] reorganize files

* remove run_tpu_glue.py as superseded by TPU support in Trainer

* Bugfix: int, not tuple

* move files around

* Big cleanup of `glue_convert_examples_to_features`

* Use batch_encode_plus

* Cleaner wrapping of glue_convert_examples_to_features for TF

@lysandrejik

* Cleanup syntax, thanks to @mfuntowicz

* Raise explicit error in case of user error

* Start cleaning examples

* Fixup

* fix n_gpu count when no_cuda flag is activated

* someone was left behind