34 Commits

Author	SHA1	Message	Date
burcturkoglu	00c7fd2b79	Division to num_train_optimizer of global_step in lr_this_step is removed.	2019-05-09 10:57:03 +03:00
burcturkoglu	fa37b4da77	Merge branch 'master' of https://github.com/huggingface/pytorch-pretrained-BERT	2019-05-09 10:55:24 +03:00
burcturkoglu	5289b4b9e0	Division to num_train_optimizer of global_step in lr_this_step is removed.	2019-05-09 10:51:38 +03:00
MottoX	74dbba64bc	Prepare optimizer only when args.do_train is True	2019-05-02 19:09:29 +08:00
Thomas Wolf	2dee86319d	Merge pull request #527 from Mathieu-Prouveur/fix_value_training_loss ... Update example files so that tr_loss is not affected by args.gradient…	2019-04-30 11:12:55 +02:00
Mathieu Prouveur	87b9ec3843	Fix tr_loss rescaling factor using global_step	2019-04-29 12:58:29 +02:00
Mathieu Prouveur	ed8fad7390	Update example files so that tr_loss is not affected by args.gradient_accumulation_step	2019-04-24 14:07:00 +02:00
thomwolf	d94c6b0144	fix training schedules in examples to match new API	2019-04-23 11:17:06 +02:00
thomwolf	60ea6c59d2	added best practices for serialization in README and examples	2019-04-15 15:00:33 +02:00
thomwolf	179a2c2ff6	update example to work with new serialization semantic	2019-04-15 14:33:23 +02:00
Yuqiang Xie	77944d1b31	add tqdm to the process of eval ... Maybe better.	2019-03-21 20:59:33 +08:00
tseretelitornike	83857ffeaa	Added missing imports.	2019-03-15 12:45:48 +01:00
thomwolf	994d86609b	fixing PYTORCH_PRETRAINED_BERT_CACHE use in examples	2019-03-06 10:21:24 +01:00
thomwolf	5c85fc3977	fix typo - logger info	2019-03-06 10:05:21 +01:00
thomwolf	eebc8abbe2	clarify and unify model saving logic in examples	2019-02-11 14:04:19 +01:00
Thomas Wolf	848aae49e1	Merge branch 'master' into python_2	2019-02-06 00:13:20 +01:00
thomwolf	448937c00d	python 2 compatibility	2019-02-06 00:07:46 +01:00
thomwolf	1579c53635	more explicit notation: num_train_step => num_train_optimization_steps	2019-02-05 15:36:33 +01:00
Matej Svejda	5169069997	make examples consistent, revert error in num_train_steps calculation	2019-01-30 11:47:25 +01:00
Matej Svejda	9c6a48c8c3	fix learning rate/fp16 and warmup problem for all examples	2019-01-27 14:07:24 +01:00
thomwolf	c9fd350567	remove default when action is store_true in arguments	2019-01-07 13:01:54 +01:00
Grégory Châtel	186f75342e	Adding new pretrained model to the help of the bert_model argument.	2019-01-02 14:00:59 +01:00
thomwolf	ae88eb88a4	set encoding to 'utf-8' in calls to open	2018-12-14 13:48:58 +01:00
thomwolf	e1eab59aac	no fp16 on evaluation	2018-12-13 14:54:02 +01:00
thomwolf	087798b7fa	fix reloading model for evaluation in examples	2018-12-13 14:48:12 +01:00
thomwolf	0f544625f4	fix swag example for work with apex	2018-12-13 13:35:59 +01:00
Grégory Châtel	df34f22854	Removing the dependency to pandas and using the csv module to load data.	2018-12-10 17:45:23 +01:00
Grégory Châtel	d429c15f25	Removing old code from copy-paste.	2018-12-06 19:19:21 +01:00
Grégory Châtel	63c45056aa	Finishing the code for the Swag task.	2018-12-06 18:53:05 +01:00
Grégory Châtel	c45d8ac554	Storing the feature of each choice as a dict for readability.	2018-12-06 16:01:28 +01:00
Grégory Châtel	0812aee2c3	Fixing problems in convert_examples_to_features.	2018-12-06 15:53:07 +01:00
Grégory Châtel	f2b873e995	convert_examples_to_features code and small improvements.	2018-12-06 15:40:47 +01:00
Grégory Châtel	83fdbd6043	Adding read_swag_examples to load the dataset.	2018-12-06 14:02:46 +01:00
Grégory Châtel	7183cded4e	SwagExample class.	2018-12-06 13:39:44 +01:00