GitLab

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* 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

* Add preprocess_logits_for_metrics Trainer param

* Compute accuracy in LM examples

* Improve comments

* Replace outdated model tags with their now-canonical pipeline types

* spam the CI till it's green

* remove sum for list flattening

* change to chain(*)

* make chain object a list

* delete empty lines

per sgugger's suggestions
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Nicholas Broad <nicholas@nmbroad.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add test for --config_overrides

* remove unneeded parts of the test

Updated masked-language modeling examples in pytorch
with convention defined by #12789

* Update run_glue.py

* Update run_glue.py

* Add model creation snippet to other scripts

* Fix style

* Validation split percentage to be used for custom data files also

Issue same as https://github.com/huggingface/transformers/issues/12406 fixed for pytorch branch run_mlm.py

* Validation split added in the right place

* Update run_clm.py

* validation split added for custom files

* Validation split added for custom files

* Update run_plm.py

* fixed validation split for custom files as input for pytorch examples in lm

* Update run_clm_no_trainer.py

* args modified

* added cotext manager to datasets map

* fixed style and spaces

* fixed warning of deprecation

* changed desc

Before the code could not be used for validation only because of this line:
extension = data_args.train_file.split(".")[-1]
was assuming that extension must be extracted from the training dataset. This line would run regardless of the training or validation options of the user. This would lead to an error if the user only wants to run an evaluation only and does not want to do train (because the training file does not exist). I modified it to extract extension from the training file if the user wants to do train and extract it from the validation file if the user wants to run eval. This way the code can be used for both training and validation separately.

* added log_level

* fix comment

* fixed log_level

* Trigger CI

* Unfied logging

* simplified args for log_level