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622 Commits
Author SHA1 Message Date
thomwolf a28dfc8659 fix eval for wt103 2019-01-16 11:18:19 +01:00
thomwolf 8831c68803 fixing various parts of model conversion, loading and weights sharing 2019-01-16 10:31:16 +01:00
thomwolf bcd4aa8fe0 update evaluation example 2019-01-15 23:32:34 +01:00
thomwolf a69ec2c722 improved corpus and tokenization conversion - added evaluation script 2019-01-15 23:17:46 +01:00
Thomas Wolf 4e0cba1053 Merge pull request #191 from nhatchan/20190113_py35_finetune 
lm_finetuning compatibility with Python 3.5
 2019-01-14 09:40:07 +01:00
nhatchan 6c65cb2492 lm_finetuning compatibility with Python 3.5 
dicts are not ordered in Python 3.5 or prior, which is a cause of #175.
This PR replaces one with a list, to keep its order.
 2019-01-13 21:09:13 +09:00
Li Dong a2da2b4109 [bug fix] args.do_lower_case is always True 
The "default=True" makes args.do_lower_case always True.

```python
parser.add_argument("--do_lower_case",
                        default=True,
                        action='store_true')
```
 2019-01-13 19:51:11 +08:00
tholor 506e5bb0c8 add do_lower_case arg and adjust model saving for lm finetuning. 2019-01-11 08:32:46 +01:00
Thomas Wolf e485829a41 Merge pull request #174 from abeljim/master 
Added Squad 2.0
 2019-01-10 23:40:45 +01:00
Sang-Kil Park 64326dccfb Fix it to run properly even if without --do_train param. 
It was modified similar to `run_classifier.py`, and Fixed to run properly even if without `--do_train` param.
 2019-01-10 21:51:39 +09:00
thomwolf e5c78c6684 update readme and few typos 2019-01-10 01:40:00 +01:00
thomwolf fa5222c296 update readme 2019-01-10 01:25:28 +01:00
Unknown b3628f117e Added Squad 2.0 2019-01-08 15:13:13 -08:00
thomwolf ab90d4cddd adding docs and example for OpenAI GPT 2019-01-09 00:12:43 +01:00
thomwolf 2e4db64cab add do_lower_case tokenizer loading optino in run_squad and ine_tuning examples 2019-01-07 13:06:42 +01:00
thomwolf c9fd350567 remove default when action is store_true in arguments 2019-01-07 13:01:54 +01:00
Thomas Wolf d3d56f9a0b Merge pull request #166 from likejazz/patch-1 
Fix error when `bert_model` param is path or url.
 2019-01-07 12:40:55 +01:00
Thomas Wolf 766c6b2ce3 Merge pull request #159 from jaderabbit/master 
Allow do_eval to be used without do_train and to use the pretrained model in the output folder
 2019-01-07 12:31:06 +01:00
Thomas Wolf 77966a43a4 Merge pull request #156 from rodgzilla/cl_args_doc 
Adding new pretrained model to the help of the `bert_model` argument.
 2019-01-07 12:27:16 +01:00
Thomas Wolf 2e8c5c00ec Merge pull request #141 from SinghJasdeep/patch-1 
loading saved model when n_classes != 2
 2019-01-07 12:21:13 +01:00
Sang-Kil Park ca4e7aaa72 Fix error when bert_model param is path or url. 
Error occurs when `bert_model` param is path or url. Therefore, if it is path, specify the last path to prevent error.
 2019-01-05 11:42:54 +09:00
Jade Abbott 193e2df8ba Remove rogue comment 2019-01-03 13:13:06 +02:00
Jade Abbott c64de50ea4 nb_tr_steps is not initialized 2019-01-03 12:34:57 +02:00
Jade Abbott b96149a19b Training loss is not initialized if only do_eval is specified 2019-01-03 10:32:10 +02:00
Jade Abbott be3b9bcf4d Allow one to use the pretrained model in evaluation when do_train is not selected 2019-01-03 09:02:33 +02:00
Grégory Châtel 186f75342e Adding new pretrained model to the help of the bert_model argument. 2019-01-02 14:00:59 +01:00
Jasdeep Singh 99709ee61d loading saved model when n_classes != 2 
Required to for: Assertion `t >= 0 && t < n_classes` failed,  if your default number of classes is not 2.
 2018-12-20 13:55:47 -08:00
tholor e5fc98c542 add exemplary training data. update to nvidia apex. refactor 'item -> line in doc' mapping. add warning for unknown word. 2018-12-20 18:30:52 +01:00
deepset a58361f197 Add example for fine tuning BERT language model (#1) 
Adds an example for loading a pre-trained BERT model and fine tune it as a language model (masked tokens & nextSentence) on your target corpus.
 2018-12-18 10:32:25 +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
thomwolf 0cf88ff084 make examples work without apex 2018-12-13 13:28:00 +01:00
thomwolf d3fcec1a3e add saving and loading model in examples 2018-12-13 12:50:44 +01:00
thomwolf b3caec5a56 adding save checkpoint and loading in examples 2018-12-13 12:48:13 +01:00
Thomas Wolf 91aab2a6d3 Merge pull request #116 from FDecaYed/deyuf/fp16_with_apex 
Change to use apex for better fp16 and multi-gpu support
 2018-12-13 12:32:37 +01:00
Thomas Wolf ffe9075f48 Merge pull request #96 from rodgzilla/multiple-choice-code 
BertForMultipleChoice and Swag dataset example.
 2018-12-13 12:05:11 +01:00
Deyu Fu c8ea286048 change to apex for better fp16 and multi-gpu support 2018-12-11 17:13:58 -08:00
Thomas Wolf e622790a93 Merge pull request #91 from rodgzilla/convert-examples-code-improvement 
run_classifier.py improvements
 2018-12-11 05:12:04 -05:00
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
Grégory Châtel fa7daa247d Fixing the commentary of the SquadExample class. 2018-12-06 13:14:33 +01:00
Grégory Châtel a994bf4076 Fixing related to issue #83. 2018-12-05 18:16:30 +01:00