* adapt wav2vec2
* add example
* add files
* adapt
* remove bogus file
* Apply suggestions from code review
* adapt files more
* upload changes
* del old files
* up
* up
* up
* up
* up
* correct gradient checkpoitning
* add readme
* finish
* finish
* up
* more fixes
* up
* up
* add demo run to readme
* up
* #12789 Replace assert statements with exceptions
* fix-copies: made copy changes to utils_qa.py in examples/pytorch/question-answering and examples/tensorflow/question-answering
* minor refactor for clarity
* Make gradient_checkpointing a training argument
* Update src/transformers/modeling_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Update src/transformers/configuration_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Fix tests
* Style
* document Gradient Checkpointing as a performance feature
* Small rename
* PoC for not using the config
* Adapt BC to new PoC
* Forgot to save
* Rollout changes to all other models
* Fix typo
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>
* examples: only use keep_linebreaks when reading TXT files for all CLM examples
* examples: only use keep_linebreaks when reading TXT files for all CLM examples
* examples: only use keep_linebreaks when reading TXT files for all CLM examples
* examples: add keep_linebreaks option to text dataset loader for all CLM examples
* examples: introduce new keep_linebreaks option as data argument in CLM examples
* Fix tied weights on TPU
* Manually tie weights in no trainer examples
* Fix for test
* One last missing
* Gettning owned by my scripts
* Address review comments
* Fix test
* Fix tests
* Fix reformer tests
* 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
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.
