GitLab

* Fix DeBERTa docs

* Tokenizer and config

* Fix a few docstrings

* More fixes

* Styling

* Fix comet_ml import and add ensure availability

* Make isort happy

* Make flake8 happy

* Don't show comet_ml warn if COMET_MODE=DISABLED

* Make isort happy

Signed-off-by: mymusise <mymusise1@gmail.com>

* Important files

* Styling them all

* Revert "Styling them all"

This reverts commit 7d029395fdae8513b8281cbc2a6c239f8093503e.

* Syling them for realsies

* Fix syntax error

* Fix benchmark_utils

* More fixes

* Fix modeling auto and script

* Remove new line

* Fixes

* More fixes

* Fix more files

* Style

* Add FSMT

* More fixes

* More fixes

* More fixes

* More fixes

* Fixes

* More fixes

* More fixes

* Last fixes

* Make sphinx happy

* Fixes in preparation for doc styling

* More fixes

* Better syntax

* Fixes

* Style

* More fixes

* More fixes

* mc for new cross lingual sentence model

* fat text

* url spelling fix

* more url spelling fixes

* slight thanks change

* small improvements in text

* multilingual word xchange

* change colab link

* xval fold number

* add model links

* line break in model names

* Update README.md

* Update README.md

* new examples link

* new examples link

* add evaluation dataset name

* add more about multi lingual

* typo fix

* typo

* typos

* hyperparameter typos

* hyperparameter typo

* add metadata

* add metadata

* Update README.md

* typo fix

* Small improvement

* make sure padding is implemented for non-padding tokens models as well

* add better error message

* add better warning

* remove results files

* Update examples/seq2seq/seq2seq_trainer.py

* remove unnecessary copy line

* correct usage of labels

* delete test files

--wwm cant be used as an argument given run_language_modeling.py and should be changed to --whole_word_mask

* Fix minor typos

Fix minor typos in the docs.

* Update docs/source/preprocessing.rst

Clearer data structure description.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add MLflow integration class

Add integration code for MLflow in integrations.py along with the code
that checks that MLflow is installed.

* Add MLflowCallback import

Add import of MLflowCallback in trainer.py

* Handle model argument

Allow the callback to handle model argument and store model config items as hyperparameters.

* Log parameters to MLflow in batches

MLflow cannot log more than a hundred parameters at once.
Code added to split the parameters into batches of 100 items and log the batches one by one.

* Fix style

* Add docs on MLflow callback

* Fix issue with unfinished runs

The "fluent" api used in MLflow integration allows only one run to be active at any given moment. If the Trainer is disposed off and a new one is created, but the training is not finished, it will refuse to log the results when the next trainer is created.

* Add MLflow integration class

Add integration code for MLflow in integrations.py along with the code
that checks that MLflow is installed.

* Add MLflowCallback import

Add import of MLflowCallback in trainer.py

* Handle model argument

Allow the callback to handle model argument and store model config items as hyperparameters.

* Log parameters to MLflow in batches

MLflow cannot log more than a hundred parameters at once.
Code added to split the parameters into batches of 100 items and log the batches one by one.

* Fix style

* Add docs on MLflow callback

* Fix issue with unfinished runs

The "fluent" api used in MLflow integration allows only one run to be active at any given moment. If the Trainer is disposed off and a new one is created, but the training is not finished, it will refuse to log the results when the next trainer is created.

* distributed training

* fix

* fix formatting

* wording

* Add mixed precision evaluation

* use original flag

Minor typo fixes to the tokenizer summary

* fixing #8001

* make T5 tokenizer serialization more robust - style

#8030

Close #8030

* Create README.md

* Update README.md

* Create README.md

* Update model_cards/ynie/roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Add Meta information for dataset identifier.
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Make Seq2Seq Trainer more similar to Trainer

* fix typo

* fix seq2seq trainer

* remove from tests

* remove lock

* remove train files

* delete test files

* correct typo

* check at init

* make sure trainer is not slowed down on TPU

* correct isort

* remove use cache

* fix use cache

* add last use chache = false

* Create README.md

* Update model_cards/sachaarbonel/bert-italian-cased-finetuned-pos/README.md

* Apply suggestions from code review
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

Co-authored-by: Jan Christian Blaise Cruz <jcblaise@Blaises-MacBook-Pro.local>

* model card German Sentence Embeddings V2

- for German RoBERTa for Sentence Embeddings V2
- marked old as outdated

* small correction

* small improvement in description

* small spelling fix

* spelling fix

* add evaluation results

* spearman explanation

* add number of trials

Updating the run_squad training script to handle the "longformer" `model_type`. The longformer is trained in the same was as RoBERTa, so I've added the "longformer" `model_type` (that's the right hugginface name for the LongFormer model, right?) everywhere there was a "roberta" `model_type` reference. The longformer (like RoBERTa) doesn't use `token_type_ids` (as I understand from looking at the [longformer notebook](https://github.com/patil-suraj/Notebooks/blob/master/longformer_qa_training.ipynb), which is what gets updated after this change.

This fix might be related to [this issue](https://github.com/huggingface/transformers/issues/7249) with SQuAD training when using run_squad.py