* 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 new run_swag example
* Add check
* Add sample
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Very important change to make Lysandre happy
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* 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>
* Add new SQUAD example
* Same with a task-specific Trainer
* Address review comment.
* Small fixes
* Initial work for XLNet
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Final clean up and working XLNet script
* Test and debug
* Final working version
* Add new SQUAD example
* Same with a task-specific Trainer
* Address review comment.
* Small fixes
* Initial work for XLNet
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Final clean up and working XLNet script
* Test and debug
* Final working version
* Add tick
* Update README
* Address review comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add new token classification example
* Remove txt file
* Add test
* With actual testing done
* Less warmup is better
* Update examples/token-classification/run_ner_new.py
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Address review comments
* Fix test
* Make Lysandre happy
* Last touches and rename
* Rename in tests
* Address review comments
* More run_ner -> run_ner_old
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.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>
* Support for Comet.ml
* Need to import comet first
* Log this model, not the one in the backprop step
* Log args as hyperparameters; use framework to allow fine control
* Log hyperparameters with context
* Apply black formatting
* isort fix integrations
* isort fix __init__
* Update src/transformers/trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/trainer_tf.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Address review comments
* Style + Quality, remove Tensorboard import test
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* 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
* Add QA trainer example for TF
* Make data_dir optional
* Fix parameter logic
* Fix feature convert
* Update the READMEs to add the question-answering task
* Apply style
* Change 'sequence-classification' to 'text-classification' and prefix with 'eval' all the metric names
* Apply style
* Apply style
* catch gpu len 1 set to gpu0
* Add mpc to trainer
* Add MPC for TF
* fix TF automodel for MPC and add Albert
* Apply style
* Fix import
* Note to self: double check
* Make shape None, None for datasetgenerator output shapes
* Add from_pt bool which doesnt seem to work
* Original checkpoint dir
* Fix docstrings for automodel
* Update readme and apply style
* Colab should probably not be from users
* Colabs should probably not be from users
* Add colab
* Update README.md
* Update README.md
* Cleanup __intit__
* Cleanup flake8 trailing comma
* Update src/transformers/training_args_tf.py
* Update src/transformers/modeling_tf_auto.py
Co-authored-by: Viktor Alm <viktoralm@pop-os.localdomain>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
* 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
* doc
* [tests] Add sample files for a regression task
* [HUGE] Trainer
* Feedback from @sshleifer
* Feedback from @thomwolf + logging tweak
* [file_utils] when downloading concurrently, get_from_cache will use the cached file for subsequent processes
* [glue] Use default max_seq_length of 128 like before
* [glue] move DataTrainingArguments around
* [ner] Change interface of InputExample, and align run_{tf,pl}
* Re-align the pl scripts a little bit
* ner
* [ner] Add integration test
* Fix language_modeling with API tweak
* [ci] Tweak loss target
* Don't break console output
* amp.initialize: model must be on right device before
* [multiple-choice] update for Trainer
* Re-align to 827d6d6ef0
* Initial commit to get BERT + run_glue.py on TPU
* Add README section for TPU and address comments.
* Cleanup TPU bits from run_glue.py (#3)
TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.
We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested.
* Cleanup TPU bits from run_glue.py
TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.
We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested.
* No need to call `xm.mark_step()` explicitly (#4)
Since for gradient accumulation we're accumulating on batches from
`ParallelLoader` instance which on next() marks the step itself.
* Resolve R/W conflicts from multiprocessing (#5)
* Add XLNet in list of models for `run_glue_tpu.py` (#6)
* Add RoBERTa to list of models in TPU GLUE (#7)
* Add RoBERTa and DistilBert to list of models in TPU GLUE (#8)
* Use barriers to reduce duplicate work/resources (#9)
* Shard eval dataset and aggregate eval metrics (#10)
* Shard eval dataset and aggregate eval metrics
Also, instead of calling `eval_loss.item()` every time do summation with
tensors on device.
* Change defaultdict to float
* Reduce the pred, label tensors instead of metrics
As brought up during review some metrics like f1 cannot be aggregated
via averaging. GLUE task metrics depends largely on the dataset, so
instead we sync the prediction and label tensors so that the metrics can
be computed accurately on those instead.
* Only use tb_writer from master (#11)
* Apply huggingface black code formatting
* Style
* Remove `--do_lower_case` as example uses cased
* Add option to specify tensorboard logdir
This is needed for our testing framework which checks regressions
against key metrics writtern by the summary writer.
* Using configuration for `xla_device`
* Prefix TPU specific comments.
* num_cores clarification and namespace eval metrics
* Cache features file under `args.cache_dir`
Instead of under `args.data_dir`. This is needed as our test infra uses
data_dir with a read-only filesystem.
* Rename `run_glue_tpu` to `run_tpu_glue`
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
