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https://api.github.com/repos/huggingface/transformers/issues/423 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/423/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/423/comments | https://api.github.com/repos/huggingface/transformers/issues/423/events | https://github.com/huggingface/transformers/pull/423 | 426,614,853 | MDExOlB1bGxSZXF1ZXN0MjY1NDI5MDQx | 423 | making unconditional generation work | {
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"merged_at": "2019... | The unconditional generation works now but if the seed is fixed, the sample is the same every time.
n_samples > 1 will give different samples though.
I am giving the start token as '<|endoftext|>' for the unconditional generation. | {
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"Hi thanks for the PR.\r\nI think we still need to clean up the example a little more indeed.\r\nThese lines should be taken care off:\r\n```python\r\nwhile not args.unconditional:\r\n if not args.unconditional:\r\n```\r\nI will see if I can find time to refactor it next week or you can update your PR if you want... |
https://api.github.com/repos/huggingface/transformers/issues/480 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/480/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/480/comments | https://api.github.com/repos/huggingface/transformers/issues/480/events | https://github.com/huggingface/transformers/pull/480 | 432,692,428 | MDExOlB1bGxSZXF1ZXN0MjcwMTExMzc3 | 480 | Extend the BertForSequenceClassification docs to mention the special CLS token. | {
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"Ok, let's go for that @mboyanov!",
"Great!"
] | |
https://api.github.com/repos/huggingface/transformers/issues/412 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/412/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/412/comments | https://api.github.com/repos/huggingface/transformers/issues/412/events | https://github.com/huggingface/transformers/issues/412 | 425,663,361 | MDU6SXNzdWU0MjU2NjMzNjE= | 412 | Possible error in "pytorch-pretrained-BERT/examples/run_gpt2.py" unconditional | {
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First of all thanks for offering us those great NLP implementations.
I think there may be an error in the file pytorch-pretrained-BERT/examples/run_gpt2.py
The way it is implemented if we do unco... | {
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"This should be fixed by #462."
] |
https://api.github.com/repos/huggingface/transformers/issues/458 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/458/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/458/comments | https://api.github.com/repos/huggingface/transformers/issues/458/events | https://github.com/huggingface/transformers/issues/458 | 430,400,523 | MDU6SXNzdWU0MzA0MDA1MjM= | 458 | Suggestion: add warning when using BertForSequenceClassification without special [CLS] token | {
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As I understand it right now, it is the user's responsibility to add the special `CLS` and `SEP` tokens. People who haven't read the paper might miss this detail.
It would be nice to issue a warning in the tokenizer or the model itself if the input is missing these tokens. An alt... | {
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"I understand the issue but I'm not sure this would be very easy to implement as we would like to keep the model and tokenizer separated one from the other.\r\n\r\nDo you have a solution in mind?\r\n\r\nOtherwise, I'll guess people will have to continue to read the paper before using the model... 😉",
"I totally ... |
https://api.github.com/repos/huggingface/transformers/issues/485 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/485/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/485/comments | https://api.github.com/repos/huggingface/transformers/issues/485/events | https://github.com/huggingface/transformers/issues/485 | 432,830,533 | MDU6SXNzdWU0MzI4MzA1MzM= | 485 | UnboundLocalError: local variable 'i' referenced before assignment when using fine_tuning code | {
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I am using the lm_finetuning codes. Generated training data using generate_pretraining_data.py
When running finetune_on_pregenerated.py . I am getting this error.
logs
python finetune_on_pregenerated.py --pregenerated_data training_1/ --bert_model bert-base-uncased --do_lower_case --output_dir ... | {
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"I found out the issue. The text corpus I was using is just one document. So the code is for two or more documents only?",
"Yes only for multiple documents.\r\nWe have a test now to check that since #478 thanks to @Rocketknight1."
] |
https://api.github.com/repos/huggingface/transformers/issues/497 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/497/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/497/comments | https://api.github.com/repos/huggingface/transformers/issues/497/events | https://github.com/huggingface/transformers/issues/497 | 434,028,654 | MDU6SXNzdWU0MzQwMjg2NTQ= | 497 | UnboundLocalError: local variable 'special_tokens_file' referenced before assignment | {
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```enc = GPT2Tokenizer.from_pretrained('gpt2')```
```
File "example_lambada_prediction_difference.py", line 23, in <module>
enc = GPT2Tokenizer.from_pretrained(model_name)
File "/bflm/pytorch-pretrained-BERT/pytorch_pretrained_bert/tokenization_gpt2.py", line 134, in from_pretrained
... | {
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"Yes, this should be fixed by #498."
] |
https://api.github.com/repos/huggingface/transformers/issues/496 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/496/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/496/comments | https://api.github.com/repos/huggingface/transformers/issues/496/events | https://github.com/huggingface/transformers/pull/496 | 434,011,487 | MDExOlB1bGxSZXF1ZXN0MjcxMDk1Mjgw | 496 | [run_gpt2.py] temperature should be a float, not int | {
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"Indeed, thanks @8enmann!"
] | |
https://api.github.com/repos/huggingface/transformers/issues/382 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/382/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/382/comments | https://api.github.com/repos/huggingface/transformers/issues/382/events | https://github.com/huggingface/transformers/issues/382 | 421,646,528 | MDU6SXNzdWU0MjE2NDY1Mjg= | 382 | fp16 overflow in GPT-2 | {
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I noticed BERT multiplies by 1e4 (within fp16 range) instead, and the overflow problem doesn't occur and now it's training happily :)
I'm happ... | {
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"Hi @andrewPoulton, yes indeed we could update that for GPT-2, would be happy to get a PR.\r\nCan you check the generations are identical for a few seeds (it should be)?",
"Yeah, sure - what generations do you mean?",
"Fixed with #495"
] |
https://api.github.com/repos/huggingface/transformers/issues/494 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/494/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/494/comments | https://api.github.com/repos/huggingface/transformers/issues/494/events | https://github.com/huggingface/transformers/pull/494 | 433,917,699 | MDExOlB1bGxSZXF1ZXN0MjcxMDE5NTA3 | 494 | Fix indentation for unconditional generation | {
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"merged_at": "2019... | Hey guys, there was an issue with the example file for generating unconditional samples. I just fixed the indentation. Let me know if there is anything else I need to do! Thanks for the great work on this repo. | {
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"Thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/47 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/47/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/47/comments | https://api.github.com/repos/huggingface/transformers/issues/47/events | https://github.com/huggingface/transformers/issues/47 | 382,761,771 | MDU6SXNzdWUzODI3NjE3NzE= | 47 | Fine-Tuned BERT-base on Squad v1. | {
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I get 88.5 FM using these weights on SQuAD dev. (If I recall correctly I get roughly 82 EM).
I think it may be beneficial to have these weights here, so that people c... | {
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"Thanks for the details.\r\nThis PyTorch repo is starting to be used by a larger community so we would have to be a little more precise than just rough numbers if we want to include such pre-trained weights.\r\nIf you want to add your weights to the repo, you should convert the weights in the PyTorch repo model and... |
https://api.github.com/repos/huggingface/transformers/issues/484 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/484/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/484/comments | https://api.github.com/repos/huggingface/transformers/issues/484/events | https://github.com/huggingface/transformers/issues/484 | 432,826,407 | MDU6SXNzdWU0MzI4MjY0MDc= | 484 | KeyError: in convert_tokens_to_ids() | {
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```
for token in tokens:
i... | {
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"Hi @wasiahmad,\r\nThis should actually already been taken care of by the WordPieceTokenizer ([here](https://github.com/huggingface/pytorch-pretrained-BERT/blob/19666dcb3bee3e379f1458e295869957aac8590c/pytorch_pretrained_bert/tokenization.py#L357)).\r\nDo you have a simple example to share so I can try to reproduce... |
https://api.github.com/repos/huggingface/transformers/issues/445 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/445/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/445/comments | https://api.github.com/repos/huggingface/transformers/issues/445/events | https://github.com/huggingface/transformers/pull/445 | 428,837,798 | MDExOlB1bGxSZXF1ZXN0MjY3MTAzMTkx | 445 | Learning rate schedules improvement + extension | {
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"merged_at": "2019... | re: [PR#389](https://github.com/huggingface/pytorch-pretrained-BERT/pull/389)
- refactored learning rate schedules into objects
- added `WarmupCosineWithHardRestartsSchedule` for cosine schedule with hard restarts
- added `WarmupCosineWithWarmupRestartsSchedule` for cosine schedule with restarts where each restart u... | {
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"Sorry for the delay in reviewing this.\r\nThis is a great PR and it looks good to me.\r\nThanks for adding some tests also.\r\nI agree with the (mostly cosmetic) comments from @marpaia.\r\nDo you think you can fix them and then we can merge?",
"Fixed @marpaia 's comments.",
"Awesome @lukovnikov, I think it loo... |
https://api.github.com/repos/huggingface/transformers/issues/512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/512/comments | https://api.github.com/repos/huggingface/transformers/issues/512/events | https://github.com/huggingface/transformers/pull/512 | 435,529,853 | MDExOlB1bGxSZXF1ZXN0MjcyMjI5Mjg5 | 512 | Fix indentation weirdness in GPT-2 example. | {
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"Thanks @cynthia!"
] |
https://api.github.com/repos/huggingface/transformers/issues/515 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/515/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/515/comments | https://api.github.com/repos/huggingface/transformers/issues/515/events | https://github.com/huggingface/transformers/pull/515 | 435,719,517 | MDExOlB1bGxSZXF1ZXN0MjcyMzY3ODIy | 515 | Fix --reduce_memory in finetune_on_pregenerated | {
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"merged_at": "2019... | On reviewing the code I realized the --reduce_memory code path in `finetune_on_pregenerated.py` had a bug, but also wasn't getting used because the relevant argument wasn't getting passed correctly. The bugs have been fixed and the argument is now passed correctly. Performance still seems good, so now it should be poss... | {
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"Good catch!"
] |
https://api.github.com/repos/huggingface/transformers/issues/475 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/475/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/475/comments | https://api.github.com/repos/huggingface/transformers/issues/475/events | https://github.com/huggingface/transformers/issues/475 | 432,341,853 | MDU6SXNzdWU0MzIzNDE4NTM= | 475 | Non-Determinism Behavior that cannot reproduce result when evaluate on each epoch | {
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"There is some non-determinism in cuDNN. Try setting `torch.backends.cudnn.deterministic = True` in your code: with that plus the RNG seeding, you should be able to get deterministic results.",
"Yes go with @Rocketknight1 suggestion.\r\nAlso check that you set model in eval mode to disable the DropOut modules bef... |
https://api.github.com/repos/huggingface/transformers/issues/508 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/508/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/508/comments | https://api.github.com/repos/huggingface/transformers/issues/508/events | https://github.com/huggingface/transformers/pull/508 | 435,037,149 | MDExOlB1bGxSZXF1ZXN0MjcxODk2MzYx | 508 | Fix python syntax in examples/run_gpt2.py | {
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... | As the title, we will never reach the code from line 115 to 131 because the space before `if args.unconditional` is not enough. | {
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"Thanks for the PR. This is fixed now."
] |
https://api.github.com/repos/huggingface/transformers/issues/519 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/519/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/519/comments | https://api.github.com/repos/huggingface/transformers/issues/519/events | https://github.com/huggingface/transformers/issues/519 | 436,109,381 | MDU6SXNzdWU0MzYxMDkzODE= | 519 | No GPT2 model | {
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```
Model name 'gpt2' was not found in model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese). We assumed 'gpt2' was a ... | {
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"Do you have a working internet connection?\r\nWe should probably improve the error messages here, 2 different error are bundled in this error (no internet connection and wrong model name)",
"Yes, I have an internet connection. I am able to download the other models.",
"Oh wait, you are mixing two models here.\... |
https://api.github.com/repos/huggingface/transformers/issues/504 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/504/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/504/comments | https://api.github.com/repos/huggingface/transformers/issues/504/events | https://github.com/huggingface/transformers/issues/504 | 434,469,616 | MDU6SXNzdWU0MzQ0Njk2MTY= | 504 | Init BertForTokenClassification from from_pretrained | {
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model = BertForTokenClassification.from_pretrained('bert-base-uncased', 2)
```
will complain about missing positional arg for `num_labels`.
The root cause is here the function signature should actually be
https://github.com/huggingface/pytorch-pretrained-BERT/blob/19666dcb3bee3e379f1458e295869957aac8590c/pyt... | {
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"actually this is related to my current work, I will send a fix along with my PR."
] |
https://api.github.com/repos/huggingface/transformers/issues/506 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/506/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/506/comments | https://api.github.com/repos/huggingface/transformers/issues/506/events | https://github.com/huggingface/transformers/pull/506 | 434,515,106 | MDExOlB1bGxSZXF1ZXN0MjcxNDkyNjg0 | 506 | Hubconf | {
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"merged_at": "2019... | fixes #504
Also add hubconf for bert related tokenizer & models.
There're a few GPT models and transformer models, but would like to send this out to get a review first.
Also there's possibility to unify the cache dir with pytorch one. | {
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"Hi @ailzhang,\r\nThis is great! I went through it and it looks good to me.\r\n\r\nI guess we should update the `from_pretrained` method of the other models as well (like [here](https://github.com/huggingface/pytorch-pretrained-BERT/blob/19666dcb3bee3e379f1458e295869957aac8590c/pytorch_pretrained_bert/modeling_open... |
https://api.github.com/repos/huggingface/transformers/issues/536 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/536/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/536/comments | https://api.github.com/repos/huggingface/transformers/issues/536/events | https://github.com/huggingface/transformers/pull/536 | 437,348,950 | MDExOlB1bGxSZXF1ZXN0MjczNjQzNjM2 | 536 | Fix missing warmup_linear in run_classifier.py example | {
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... | Replaced warmup_linear function call with WarmupLinearSchedule | {
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"I see there is already a PR to fix this, I will close this."
] |
https://api.github.com/repos/huggingface/transformers/issues/531 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/531/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/531/comments | https://api.github.com/repos/huggingface/transformers/issues/531/events | https://github.com/huggingface/transformers/pull/531 | 437,178,066 | MDExOlB1bGxSZXF1ZXN0MjczNTA3OTY3 | 531 | fixed new LR API in examples | {
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https://api.github.com/repos/huggingface/transformers/issues/518 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/518/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/518/comments | https://api.github.com/repos/huggingface/transformers/issues/518/events | https://github.com/huggingface/transformers/pull/518 | 436,083,794 | MDExOlB1bGxSZXF1ZXN0MjcyNjQ4Mjkz | 518 | Fix training schedules in examples to match new API | {
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"merged_at": "2019... | Re #445:
- update examples to work with the new optimizer API | {
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"@lukovnikov do you want to give this PR a look and confirm it's fine?\r\n\r\nAlso, we should document a bit the new optimizer API in the README. Do you want to use this PR to copy a few docstring in the README (we currently don't have auto-generated doc)?",
"Hi. Sorry, forgot about the examples.\r\nDid a couple ... |
https://api.github.com/repos/huggingface/transformers/issues/488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/488/comments | https://api.github.com/repos/huggingface/transformers/issues/488/events | https://github.com/huggingface/transformers/pull/488 | 433,161,099 | MDExOlB1bGxSZXF1ZXN0MjcwNDIxODM2 | 488 | fixed BertForMultipleChoice model init and forward pass | {
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"merged_at": "2019... | the number of choices is not respected because you've hardcoded '1' into the classifier layer. also `token_type_ids` and `attention_mask` will cause an error if `None` because `None` does not have a `view` method. | {
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"Indeed, it looks better.\r\nDo you want to have a look and confirm @rodgzilla?",
"@thomwolf any word on this?",
"Oh yes sorry. Looking at it and reading Alec Radford's paper on GPT (section 3.3) again, I think @rodgzilla was actually right in the original implementation.\r\n\r\nSo I guess we should close this ... |
https://api.github.com/repos/huggingface/transformers/issues/532 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/532/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/532/comments | https://api.github.com/repos/huggingface/transformers/issues/532/events | https://github.com/huggingface/transformers/issues/532 | 437,219,614 | MDU6SXNzdWU0MzcyMTk2MTQ= | 532 | [Feature request] Support configurable BertLayerNorm epsilon | {
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"Hi, I'm closing this in favor of #514 to gather all the discussion on ERNIE."
] |
https://api.github.com/repos/huggingface/transformers/issues/533 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/533/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/533/comments | https://api.github.com/repos/huggingface/transformers/issues/533/events | https://github.com/huggingface/transformers/pull/533 | 437,224,702 | MDExOlB1bGxSZXF1ZXN0MjczNTQ1Mjcx | 533 | Docs for new learning rate code | {
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"merged_at": "2019... | - Added documentation for learning rate schedules in main README
- added some pictures for the README in docs/imgs/ (not sure if it's the best place)
- updated some docs in code for optimization | {
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"Great thanks!",
"The curves plot in the README are beautiful (and perfect size), awesome!"
] |
https://api.github.com/repos/huggingface/transformers/issues/523 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/523/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/523/comments | https://api.github.com/repos/huggingface/transformers/issues/523/events | https://github.com/huggingface/transformers/issues/523 | 436,177,142 | MDU6SXNzdWU0MzYxNzcxNDI= | 523 | ImportError: cannot import name 'WEIGHTS_NAME' from 'pytorch_pretrained_bert.file_utils' | {
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```
Traceback (most recent call last):
File "run_squad.py", line 37, in <module>
from pytorch_pretrained_bert.file_utils import PYTORCH_PRETRAINED_BERT_CACHE, WEIGHTS_NAME, CONFIG_NAME
ImportError: cannot import name 'WEIGHTS_NAME' from 'pyto... | {
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"Same is happening for `run_classifier.py` ",
"Yes the examples currently require to install from source (see the section in the readme).\r\nI'll release a new version tomorrow so the pip release will be in sync with `master` examples again.",
"Okay, thank you :)",
"Waiting for this; installing from source gi... |
https://api.github.com/repos/huggingface/transformers/issues/520 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/520/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/520/comments | https://api.github.com/repos/huggingface/transformers/issues/520/events | https://github.com/huggingface/transformers/issues/520 | 436,117,718 | MDU6SXNzdWU0MzYxMTc3MTg= | 520 | unable to load finetuned LM "No file bert_config.json" | {
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I think bert_config is not saved when finetuning a LM | {
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"Ok, this should be fixed in the new release v0.6.2. See #523."
] |
https://api.github.com/repos/huggingface/transformers/issues/390 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/390/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/390/comments | https://api.github.com/repos/huggingface/transformers/issues/390/events | https://github.com/huggingface/transformers/issues/390 | 422,725,827 | MDU6SXNzdWU0MjI3MjU4Mjc= | 390 | 'NoneType' object with constructor | {
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```python
model = BertModel.from_pretrained('bert-base-uncased')
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
``` | {
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"Me too.It is probably Network connection problem.",
"The network connection check has been relaxed in the now merged #500.\r\nIt will be included in the next PyPI release (probably next week).\r\nIn the meantime you can install from `master`.",
"@thomwolf Thank you.",
"The new release is on pypi!"
] |
https://api.github.com/repos/huggingface/transformers/issues/539 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/539/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/539/comments | https://api.github.com/repos/huggingface/transformers/issues/539/events | https://github.com/huggingface/transformers/issues/539 | 437,532,185 | MDU6SXNzdWU0Mzc1MzIxODU= | 539 | Can we use 'bert-base-uncased' to question_answer just for start, rather rather than run_squad pretraining? | {
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Can we use 'bert-base-uncased' to question_answer just for start, rather rather than run_squad pretraining?
model = BertForQuestionAnswering.from_pretrained('bert-base-uncased')
Thanks
Mahesh | {
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"Hi, no you need to fine tune the model on a question answering task like SQuAD before you can use it"
] |
https://api.github.com/repos/huggingface/transformers/issues/527 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/527/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/527/comments | https://api.github.com/repos/huggingface/transformers/issues/527/events | https://github.com/huggingface/transformers/pull/527 | 436,660,128 | MDExOlB1bGxSZXF1ZXN0MjczMTAxNzg4 | 527 | Update example files so that tr_loss is not affected by args.gradient… | {
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"merged_at": "2019... | Hi developpers!
Fix training loss value :
* if gradient_accumulation_steps > 1 then the batch loss value(which is a mean) is scaled by a factor 1/args.gradient_accumulation_steps.
To compare it to evaluation loss it is thus necessary to scale it back by multiplying by args.gradient_accumulation_steps (as done... | {
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"Hi @Mathieu-Prouveur, thanks for that.\r\nIndeed I think using `tr_loss/global_step` would be more easy to read.\r\nCan you update this? ",
"Sure, I've just done the update ",
"Great, thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/564 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/564/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/564/comments | https://api.github.com/repos/huggingface/transformers/issues/564/events | https://github.com/huggingface/transformers/pull/564 | 439,051,911 | MDExOlB1bGxSZXF1ZXN0Mjc0OTQ1MzM4 | 564 | Fix #537 | {
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"Thanks a lot for that @8enmann!"
] | |
https://api.github.com/repos/huggingface/transformers/issues/550 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/550/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/550/comments | https://api.github.com/repos/huggingface/transformers/issues/550/events | https://github.com/huggingface/transformers/pull/550 | 438,015,484 | MDExOlB1bGxSZXF1ZXN0Mjc0MTUzMTk5 | 550 | Fix GPT2 crash on special quotes in Python 3 | {
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... | In Python 3 the line
https://github.com/huggingface/pytorch-pretrained-BERT/blob/b832d5bb8a6dfc5965015b828e577677eace601e/pytorch_pretrained_bert/tokenization_gpt2.py#L224
splits `token` into full characters, not UTF-8 bytes, so for example the right single quote ’ gives `ord('’') == 8217`. That causes a crash since ... | {
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"Thanks, this is closed now with #564"
] |
https://api.github.com/repos/huggingface/transformers/issues/562 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/562/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/562/comments | https://api.github.com/repos/huggingface/transformers/issues/562/events | https://github.com/huggingface/transformers/pull/562 | 438,974,141 | MDExOlB1bGxSZXF1ZXN0Mjc0ODg0OTE1 | 562 | Small fix to remove shifting of lm labels during pre process of RocStories. | {
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"merged_at": "2019... | In reference to https://github.com/huggingface/pytorch-pretrained-BERT/issues/473, remove the one shifting of lm labels since this shift happens internally during the model's forward pass.
@thomwolf | {
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"Awesome, thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/540 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/540/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/540/comments | https://api.github.com/repos/huggingface/transformers/issues/540/events | https://github.com/huggingface/transformers/issues/540 | 437,549,824 | MDU6SXNzdWU0Mzc1NDk4MjQ= | 540 | no to_json_file(file) in BERT | {
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in the line 1035, I cannot use config.to_json_file(output_config_file) because there is no such function.
Instead I use
`file = model_to_save.config.to_json_string()`
`with open(file_path, "w") as f:`
` f.write(fi... | {
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"Are you using the latest release (0.6.2) ?",
"Yes I am.",
"Strange, `to_json_file` should be provided in 0.6.2 (cf code [here](https://github.com/huggingface/pytorch-pretrained-BERT/blob/e6cf62d49945e6277b5e4dc855f9186b3f789e35/pytorch_pretrained_bert/modeling.py#L222) and the associated test [here](https://gi... |
https://api.github.com/repos/huggingface/transformers/issues/441 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/441/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/441/comments | https://api.github.com/repos/huggingface/transformers/issues/441/events | https://github.com/huggingface/transformers/pull/441 | 428,369,581 | MDExOlB1bGxSZXF1ZXN0MjY2NzUzMzE2 | 441 | Fix bug in run_squad.py | {
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... | I fired an issue in Google's repo, https://github.com/google-research/bert/issues/540#issue-428344784
After testing, I found it is indeed a bug.
We should not put these chunks with `start_position==0` and `end_position==0` into training set.
Thanks for code review. | {
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"Hi @MottoX, sorry for the delay on reviewing this.\r\nIt seems to make sense to me.\r\nWhat kind of testing are you referring to? Could you share a bit more about them?",
"Hi, @thomwolf \r\nI was trying to train a BERT-based model on NewsQA, a document-level QA dataset, using `run_squad.py`. I used 384 for max_s... |
https://api.github.com/repos/huggingface/transformers/issues/569 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/569/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/569/comments | https://api.github.com/repos/huggingface/transformers/issues/569/events | https://github.com/huggingface/transformers/issues/569 | 439,365,268 | MDU6SXNzdWU0MzkzNjUyNjg= | 569 | License of the pretrained models | {
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"Just found it's under Apache v2 in the Google bert repo. Closing."
] |
https://api.github.com/repos/huggingface/transformers/issues/575 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/575/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/575/comments | https://api.github.com/repos/huggingface/transformers/issues/575/events | https://github.com/huggingface/transformers/issues/575 | 439,963,432 | MDU6SXNzdWU0Mzk5NjM0MzI= | 575 | Different BERT representations when text is with and without single quotes | {
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https://api.github.com/repos/huggingface/transformers/issues/507 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/507/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/507/comments | https://api.github.com/repos/huggingface/transformers/issues/507/events | https://github.com/huggingface/transformers/issues/507 | 434,994,568 | MDU6SXNzdWU0MzQ5OTQ1Njg= | 507 | GPT-2 FineTuning on Cloze/ ROC | {
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"Hi rohuns, I was wondering what padding value have you used for the lm_labels, since the -1 specified in the docs doesn't work for me on GPT2LMHead model. See #577. ",
"> Hi rohuns, I was wondering what padding value have you used for the lm_labels, since the -1 specified in the docs doesn't work for me on GPT2L... |
https://api.github.com/repos/huggingface/transformers/issues/545 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/545/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/545/comments | https://api.github.com/repos/huggingface/transformers/issues/545/events | https://github.com/huggingface/transformers/pull/545 | 437,968,723 | MDExOlB1bGxSZXF1ZXN0Mjc0MTIyOTkw | 545 | move pytroch_pretrained_bert cache folder under same path as torch | {
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"merged_at": "2019... | This PR does two things:
* Envs available:
PYTORCH_PRETRAINED_BERT_CACHE > TORCH_HOME > XDG_CACHE_HOME > `~/.cache`
* If no env is set, the default path is
`~/.cache/torch/pytorch_pretrained_bert` where `pytorch_pretrained_bert` is visible instead of hidden `.pytorch_pretrained_bert`. (since this is the cache ... | {
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"Ok, looks good, thanks @ailzhang!"
] |
https://api.github.com/repos/huggingface/transformers/issues/585 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/585/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/585/comments | https://api.github.com/repos/huggingface/transformers/issues/585/events | https://github.com/huggingface/transformers/pull/585 | 440,463,287 | MDExOlB1bGxSZXF1ZXN0Mjc2MDA4ODEy | 585 | Make the epsilon of LayerNorm configurable. | {
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#514 related | {
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"Ok, good to go, thanks @huntzhan!"
] |
https://api.github.com/repos/huggingface/transformers/issues/570 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/570/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/570/comments | https://api.github.com/repos/huggingface/transformers/issues/570/events | https://github.com/huggingface/transformers/pull/570 | 439,538,398 | MDExOlB1bGxSZXF1ZXN0Mjc1MzIxMzAx | 570 | Create optimizer only when args.do_train is True | {
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"merged_at": "2019... | I am facing the same problem as #544 . When only setting args.do_eval to evaluate a trained model, there will be an error due to optimizer initialization. I think it is unnecessary to create an optimizer if args.do_train is False. Thanks for your review. | {
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"Great, thanks @MottoX!"
] |
https://api.github.com/repos/huggingface/transformers/issues/571 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/571/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/571/comments | https://api.github.com/repos/huggingface/transformers/issues/571/events | https://github.com/huggingface/transformers/pull/571 | 439,542,506 | MDExOlB1bGxSZXF1ZXN0Mjc1MzI0NjE1 | 571 | Fix documentation typo | {
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"Thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/588 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/588/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/588/comments | https://api.github.com/repos/huggingface/transformers/issues/588/events | https://github.com/huggingface/transformers/issues/588 | 440,677,033 | MDU6SXNzdWU0NDA2NzcwMzM= | 588 | installation error | {
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My output's error message is here:
> error: command '/usr/bin/nvcc' failed with exit status 1
> error
> Cleaning up...
> Removing source in /tmp/pip-req-build-837wsq53
> Removed build tracker '/tmp/pip-req-tracker-txkm... | {
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"Which commands are you running?",
"I am so sorry that I took your time, I accidentally posted this here. "
] |
https://api.github.com/repos/huggingface/transformers/issues/596 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/596/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/596/comments | https://api.github.com/repos/huggingface/transformers/issues/596/events | https://github.com/huggingface/transformers/issues/596 | 441,715,398 | MDU6SXNzdWU0NDE3MTUzOTg= | 596 | [Question] Cross-lingual sentence representations | {
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Would it be possible to integrate also a BERT model for cross-lingual sentence representations?
Something like, for example, the `XNLI-15` model in [https://github.com/facebookresearch/XLM](https://github.com/facebookresearch/XLM).
Thanks! | {
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"Hi @shoegazerstella well XLM is already pretty much as powerful as BERT and focused on cross-lingual sentence representations so I would go directly for it instead of BERT.",
"Thanks @thomwolf, \r\nAre you considering integrating something for cross-lingual representations in the `pytorch-pretrained-BERT` librar... |
https://api.github.com/repos/huggingface/transformers/issues/566 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/566/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/566/comments | https://api.github.com/repos/huggingface/transformers/issues/566/events | https://github.com/huggingface/transformers/issues/566 | 439,085,421 | MDU6SXNzdWU0MzkwODU0MjE= | 566 | Bug in run_classifier.py fp16 learning rate | {
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https://github.com/huggingface/pytorch-pretrained-BERT/blob/2dee86319dbad575352358b8f2fb4129940e381a/examples/run_classifier.py#L857-L858
I think the right code is: lr_this_step = args.learning_rate * warmup_linear.get_lr(glo... | {
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"I'm asking the same question",
"I had been dealing with the issue of low and decreasing accuracy when I use fp16, as shown below,\r\n\r\n```\r\nEpoch 1 - Batch 1600/287417 - Training Acc. 0.106250 - Training Loss 2.295977\r\nEpoch 1 - Batch 3200/287417 - Training Acc. 0.098125 - Training Loss 2.299707\r\nEpoch 1... |
https://api.github.com/repos/huggingface/transformers/issues/598 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/598/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/598/comments | https://api.github.com/repos/huggingface/transformers/issues/598/events | https://github.com/huggingface/transformers/pull/598 | 442,291,837 | MDExOlB1bGxSZXF1ZXN0Mjc3NDM2MTQz | 598 | Updating learning rate with special warm up in examples | {
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"merged_at": "2019... | Updating examples by removing division to num_train_optimization_steps for new WarmupLinearSchedule.
Fixes #566 | {
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"Oh great thanks Burc!"
] |
https://api.github.com/repos/huggingface/transformers/issues/495 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/495/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/495/comments | https://api.github.com/repos/huggingface/transformers/issues/495/events | https://github.com/huggingface/transformers/pull/495 | 433,929,690 | MDExOlB1bGxSZXF1ZXN0MjcxMDI5MDQx | 495 | Fix gradient overflow issue during attention mask | {
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"merged_at": "2019... | This fix is in reference to issue #382. GPT2 can now be trained in mixed precision, which I've confirmed with testing. I also tested unconditional generation on multiple seeds before and after changing 1e10 to 1e4 and there was no difference. Please let me know if there is anything else I can do to make this pull reque... | {
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"Ok, great, thanks @SudoSharma!",
"While the outputs are the same between 1e10 and 1e4, I shouldn't expect the outputs between fp32 and fp16 to be the same, should I? I get different outputs between the two when doing unconditional/conditional generation with top_k=40 but even with top_k=1. Usually they're the sa... |
https://api.github.com/repos/huggingface/transformers/issues/285 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/285/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/285/comments | https://api.github.com/repos/huggingface/transformers/issues/285/events | https://github.com/huggingface/transformers/issues/285 | 411,074,179 | MDU6SXNzdWU0MTEwNzQxNzk= | 285 | Anyone tried this model to write a next sentence? | {
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"Closing for now.",
"Why ? @thomwolf ",
"I'm trying to clean up the issues to get a better view of what needs to be fixed.\r\nBut you are right opening/closing issue is too binary. Let's add labels instead.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be... | |
https://api.github.com/repos/huggingface/transformers/issues/271 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/271/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/271/comments | https://api.github.com/repos/huggingface/transformers/issues/271/events | https://github.com/huggingface/transformers/issues/271 | 409,585,974 | MDU6SXNzdWU0MDk1ODU5NzQ= | 271 | Transformer-XL: wrong encoding in the vocab | {
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E.g.:
```
In [1]: import pytorch_pretrained_bert
In [2]: tokenizer = pytorch_pretrained_bert.TransfoXLTokenizer.from_pretrained('transfo-xl-wt103')
In [4]: print(tokenizer.idx2sym[224178])
'Enquête... | {
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"Yeah, the re-encoding seems to fix the bug:\r\n```\r\nIn [6]: \"'Enquêtes\".encode('latin1').decode('utf8')\r\nOut[6]: \"'Enquêtes\"\r\n```",
"which version of python are you using?",
"It's python3.6. Does the snippet above gives different result on other version?\r\n\r\nJFYI: I'm using the script below to cr... |
https://api.github.com/repos/huggingface/transformers/issues/238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/238/comments | https://api.github.com/repos/huggingface/transformers/issues/238/events | https://github.com/huggingface/transformers/issues/238 | 404,624,962 | MDU6SXNzdWU0MDQ2MjQ5NjI= | 238 | padded positions are ignored when embedding position ids | {
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```
seq_length = input_ids.size(1)
position_ids = torch.arange(seq_length, dtype=torch.long, device=input_ids.device)
```
This is different from most transformer implementations.
Should it be
```
position_ids = np.array([
[pos_i+1 if w_i != ... | {
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https://api.github.com/repos/huggingface/transformers/issues/313 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/313/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/313/comments | https://api.github.com/repos/huggingface/transformers/issues/313/events | https://github.com/huggingface/transformers/issues/313 | 413,241,264 | MDU6SXNzdWU0MTMyNDEyNjQ= | 313 | run_lm_finetuning | {
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... | closed | false | [] | null | 2 | 2019-02-22T04:42:39Z | 2019-05-12T13:18:46Z | 2019-05-12T13:18:46Z | null | NONE | [] | null | null | null | null | When I run_lm_finetuning with the exemplary training corpus (small_wiki_sentence_corpus.txt), I printed the tr_loss every 20 steps. I found that the tr_loss increases very fast. I wonder what the reason is.
... | {
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"What tr_loss are you exactly printing here? Is it possible that you just print this one here? https://github.com/huggingface/pytorch-pretrained-BERT/blob/2152bfeae82439600dc5b5deab057a3c4331c62d/examples/run_lm_finetuning.py#L600 If yes, you should divide it by the number of training steps (nb_tr_steps) first to g... |
https://api.github.com/repos/huggingface/transformers/issues/343 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/343/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/343/comments | https://api.github.com/repos/huggingface/transformers/issues/343/events | https://github.com/huggingface/transformers/issues/343 | 417,107,904 | MDU6SXNzdWU0MTcxMDc5MDQ= | 343 | Tokenizer defaults lowercase even when bert_model is cased | {
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A more clear behavior would be to use whether or not 'uncased' is in bert_model, and set the default behavior of do_lower_case accordingly. | {
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https://api.github.com/repos/huggingface/transformers/issues/349 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/349/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/349/comments | https://api.github.com/repos/huggingface/transformers/issues/349/events | https://github.com/huggingface/transformers/issues/349 | 417,596,167 | MDU6SXNzdWU0MTc1OTYxNjc= | 349 | Unable to train (fine-tuning) BERT with small training set | {
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... | closed | false | [] | null | 2 | 2019-03-06T02:44:27Z | 2019-05-12T13:18:48Z | 2019-05-12T13:18:48Z | null | NONE | [] | null | null | null | null | I am trying to train BERT with 1 context and 1 answer in the train.json, I am getting the below error.
_lr_this_step = args.learning_rate * warmup_linear(global_step/t_total, args.warmup_proportion)
ZeroDivisionError: division by zero_
After training with 1 context and 5 answers, the error is avoided, but I do not s... | {
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"Probably an issue with `t_total` and the number of training optimization steps similarly to #329.\r\nCould you check the number of total training step sent to the optimizer? Which example script are you using?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be... |
https://api.github.com/repos/huggingface/transformers/issues/329 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/329/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/329/comments | https://api.github.com/repos/huggingface/transformers/issues/329/events | https://github.com/huggingface/transformers/issues/329 | 415,449,361 | MDU6SXNzdWU0MTU0NDkzNjE= | 329 | run_lm_finetuning - ZeroDivisionError | {
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... | closed | false | [] | null | 3 | 2019-02-28T05:05:55Z | 2019-05-12T14:18:40Z | 2019-05-12T14:18:40Z | null | NONE | [] | null | null | null | null | Trying to get run_lm_finetunning example on working on below GPU machine but finding getting zeroDivisonError.Any idea what could be causing this error?
python /home/ec2-user/SageMaker/bert_pytorch/pyt... | {
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"Seems like an error with `t_total`. `t_total` is the number of training optimization steps of the optimizer defined [here](num_train_optimization_steps) in the `run_lm_finetuning` example.\r\nCan you make sure it's not zero?",
"Your `batch_size` of 32 is too big for such a small `train_file`, i.e. sample_text.tx... |
https://api.github.com/repos/huggingface/transformers/issues/448 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/448/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/448/comments | https://api.github.com/repos/huggingface/transformers/issues/448/events | https://github.com/huggingface/transformers/issues/448 | 429,145,745 | MDU6SXNzdWU0MjkxNDU3NDU= | 448 | pretrain for chinese dataset | {
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and what is the format for vocab.txt ? thanks a lot | {
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"Hi, you should probably turn to the TensorFlow version for pre-training.\r\nThis package is mostly intended to be used for fine-tuning pre-trained models.\r\nAnother option for BERT-like pre-training is to use Facebook's [XLM](https://github.com/facebookresearch/XLM)"
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https://api.github.com/repos/huggingface/transformers/issues/514 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/514/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/514/comments | https://api.github.com/repos/huggingface/transformers/issues/514/events | https://github.com/huggingface/transformers/issues/514 | 435,672,972 | MDU6SXNzdWU0MzU2NzI5NzI= | 514 | ADD ERNIE | {
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] | closed | false | [] | null | 2 | 2019-04-22T09:57:29Z | 2019-05-13T06:51:39Z | 2019-05-13T06:51:38Z | null | CONTRIBUTOR | [] | null | null | null | null | Can we add a new model ERNIE?
ERNIE is based on the Bert model and has better performance on Chinese NLP tasks.
Github address: https://github.com/PaddlePaddle/LARK/tree/develop/ERNIE
paper: https://arxiv.org/abs/1904.09223
Thanks | {
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"Hi @nghuyong, I won't convert ERNIE but I'm open to welcome a PR if somebody want to give it a try.\r\n\r\nAlso, note that unlike examples, a PR with a new model should have a configuration class, tests, a conversion script and be documented like the other models in the library.\r\n",
"I do implement that conver... |
https://api.github.com/repos/huggingface/transformers/issues/355 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/355/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/355/comments | https://api.github.com/repos/huggingface/transformers/issues/355/events | https://github.com/huggingface/transformers/issues/355 | 417,981,275 | MDU6SXNzdWU0MTc5ODEyNzU= | 355 | [Question] Best choice for Sentence Compression model? | {
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I'm thinking using the BertforTokenClassification module. Will it work with a large datas... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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... | Examples had wrongly computed t_total, resulting in warning messages (Issue #556 )
Added fixes in several examples but:
- only tested MRPC in `run_classifier.py` so far
- `finetune_on_pregenerated.py` still needs fixing (not sure why lines 221-227 are as they are) | {
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"Closed in favour of #604 "
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https://api.github.com/repos/huggingface/transformers/issues/32 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/32/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/32/comments | https://api.github.com/repos/huggingface/transformers/issues/32/events | https://github.com/huggingface/transformers/pull/32 | 381,939,230 | MDExOlB1bGxSZXF1ZXN0MjMxNzc1MTI1 | 32 | Fix ineffective no_decay bug when using BERTAdam | {
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"thanks!",
"Question - wouldn't `.named_parameters()` for the model return a tuple `(name, param_tensor)`, where name looks similar to these\r\n```\r\n['bert.embeddings.word_embeddings.weight',\r\n 'bert.embeddings.position_embeddings.weight',\r\n 'bert.embeddings.token_type_embeddings.weight',\r\n 'bert.embeddin... |
https://api.github.com/repos/huggingface/transformers/issues/609 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/609/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/609/comments | https://api.github.com/repos/huggingface/transformers/issues/609/events | https://github.com/huggingface/transformers/issues/609 | 444,313,756 | MDU6SXNzdWU0NDQzMTM3NTY= | 609 | t_total | {
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File "finetune_on_pregenerated.py", line 333, in <module>
main()
File "finetune_on_pregenerated.py", line 321, in main
optimizer.step()
File "/home/py36/lib/python3.6/site-packages/pytorch_pretrained_bert/optimization.py", line 290, in step
lr_scheduled *= grou... | {
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"\r\nI found the reason. When the data is relatively small, this happens. After I added the data, it is normal now."
] |
https://api.github.com/repos/huggingface/transformers/issues/363 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/363/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/363/comments | https://api.github.com/repos/huggingface/transformers/issues/363/events | https://github.com/huggingface/transformers/issues/363 | 419,139,787 | MDU6SXNzdWU0MTkxMzk3ODc= | 363 | Separator token for custom QA input (multi paragraph, longer than 512) | {
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},... | closed | false | [] | null | 1 | 2019-03-10T02:56:29Z | 2019-05-17T09:11:31Z | 2019-05-17T09:11:31Z | null | NONE | [] | null | null | null | null | Hello!
I'm trying to extract features for a QA task where the document is composed of multiple disparate paragraphs. So my input is:
question ||| document
where document is {para1 SEP para2 SEP para3 SEP}, so overall, it's something like:
question ||| para1 SEP para2 SEP para3 SEP
My question is: Is it okay to u... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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https://api.github.com/repos/huggingface/transformers/issues/351 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/351/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/351/comments | https://api.github.com/repos/huggingface/transformers/issues/351/events | https://github.com/huggingface/transformers/issues/351 | 417,721,684 | MDU6SXNzdWU0MTc3MjE2ODQ= | 351 | Little training has no impact | {
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"id": 1108... | closed | false | [] | null | 1 | 2019-03-06T10:09:43Z | 2019-05-17T12:11:31Z | 2019-05-17T12:11:31Z | null | NONE | [] | null | null | null | null | When tried to enter few training data in trainxx.json (few questions and few answers) and ran the training, then new pytorch_model.bin file got generated ( = uncased + squad training + few my questions).
However, when same question was put in devxx.json the answer is not same which was put in training.
Why is... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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https://api.github.com/repos/huggingface/transformers/issues/360 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/360/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/360/comments | https://api.github.com/repos/huggingface/transformers/issues/360/events | https://github.com/huggingface/transformers/issues/360 | 418,882,345 | MDU6SXNzdWU0MTg4ODIzNDU= | 360 | Ranking predictions with BertForQuestionAnswering | {
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},... | closed | false | [] | null | 2 | 2019-03-08T17:26:03Z | 2019-05-18T09:44:38Z | 2019-05-18T09:44:38Z | null | NONE | [] | null | null | null | null | I am using `BertForQuestionAnswering`
I am trying to make a prediction from the same question asked on different paragraphs. It outputs an `OrderedDict` of tuples with format `(paragraphID, answer)`. How can I rank those predictions to get the most probable answer across all paragraphs?
Thanks for great repo! | {
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"I am also interested in this, it looks like we would have to append the prediction probability to the `all_predictions` JSON output.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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https://api.github.com/repos/huggingface/transformers/issues/618 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/618/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/618/comments | https://api.github.com/repos/huggingface/transformers/issues/618/events | https://github.com/huggingface/transformers/issues/618 | 445,703,262 | MDU6SXNzdWU0NDU3MDMyNjI= | 618 | Loss function of run_classifier.py takes in 2 inputs of different dimensions. | {
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In this line, `loss = loss_fct(logits.view(-1, num_labels), label_ids.view(-1))`, suppose we have 2 labels (entailment vs. not_entailment like QNLI task), then,
`logits` is already in dime... | {
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"Closing issue, because I pass in the num_labels as 1 instead of 2 for the QNLI task. I was thinking that giving 1 label is enough because the 2nd label can be inferred from the 1st one. "
] |
https://api.github.com/repos/huggingface/transformers/issues/365 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/365/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/365/comments | https://api.github.com/repos/huggingface/transformers/issues/365/events | https://github.com/huggingface/transformers/issues/365 | 419,473,116 | MDU6SXNzdWU0MTk0NzMxMTY= | 365 | BERT accuracy reduced after providing custom training..The answer is also not correct | {
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"id": 1108... | closed | false | [] | null | 2 | 2019-03-11T13:36:58Z | 2019-05-18T14:44:34Z | 2019-05-18T14:44:34Z | null | NONE | [] | null | null | null | null | I have trained Google BERT with a custom training.
I have included the exact question and answer along with the context from the input document in the training file and trained BERT.
With new generated checkpoints (ckpt) I am still getting the same wrong answer as obtained before training. However it is observed th... | {
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"Can you give a simple self-contained script to reproduce your issue?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] |
https://api.github.com/repos/huggingface/transformers/issues/366 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/366/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/366/comments | https://api.github.com/repos/huggingface/transformers/issues/366/events | https://github.com/huggingface/transformers/issues/366 | 419,689,340 | MDU6SXNzdWU0MTk2ODkzNDA= | 366 | Vocabularly file not available for Squad predictions | {
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"id": 1314... | closed | false | [] | null | 2 | 2019-03-11T21:21:06Z | 2019-05-18T14:44:35Z | 2019-05-18T14:44:35Z | null | NONE | [] | null | null | null | null | There appears to be a bug in the way the vocabulary file is handled.
For example, if we execute [`run_squad.py`](https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/examples/run_squad.py) with `--do_train`, and set the `--output_dir` to `/tmp/debug_squad/`, we successfully build a model and the result... | {
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"Indeed, this example could be improved. I would happy to welcome a PR on that.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] |
https://api.github.com/repos/huggingface/transformers/issues/364 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/364/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/364/comments | https://api.github.com/repos/huggingface/transformers/issues/364/events | https://github.com/huggingface/transformers/issues/364 | 419,292,310 | MDU6SXNzdWU0MTkyOTIzMTA= | 364 | Potential redundancy in run_classifier.py example script | {
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},... | closed | false | [] | null | 5 | 2019-03-11T04:44:38Z | 2019-05-18T14:44:36Z | 2019-05-18T14:44:36Z | null | CONTRIBUTOR | [] | null | null | null | null | https://github.com/huggingface/pytorch-pretrained-BERT/blob/7cc35c31040d8bdfcadc274c087d6a73c2036210/examples/run_classifier.py#L641-L642
Here we are calling the model twice. I understand that the model returns different things depending on the presence of `label_ids`, but this could actually be quite expensive. I t... | {
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"I agree with you, this part of the API could be improved.\r\n\r\nThe BERT model is now used in several third-party libraries like AllenNLP and FLAIR so we have to be careful not to make any breaking change on this model.\r\n\r\nWe could add a flag to get full output maybe.",
"Mind if I submit a PR adding a flag ... |
https://api.github.com/repos/huggingface/transformers/issues/592 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/592/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/592/comments | https://api.github.com/repos/huggingface/transformers/issues/592/events | https://github.com/huggingface/transformers/issues/592 | 441,030,704 | MDU6SXNzdWU0NDEwMzA3MDQ= | 592 | Can the use of [SEP] reduce the information extraction between the sentences? | {
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If I have 2 sentences, which are s1 and s2, and our fine-tuning task is the same. In one way, I ad... | {
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"I think so. Ultimately you should have s1 and s2 in input, your [CLS] + s1 + s2 + [SEP] will be equivalent to `[CLS] + s1 + [SEP]` in `[CLS] + s1 + [SEP] + s2 + [SEP]` where `s1` now is the concatenation of `s1` and `s2`. I don't think that's what you want to do."
] |
https://api.github.com/repos/huggingface/transformers/issues/591 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/591/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/591/comments | https://api.github.com/repos/huggingface/transformers/issues/591/events | https://github.com/huggingface/transformers/issues/591 | 441,018,048 | MDU6SXNzdWU0NDEwMTgwNDg= | 591 | What is the use of [SEP]? | {
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If I have 2 sentences, which are s1 and s2., and our fine-tuning task is the same. In one way, I a... | {
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"@RomanShen What is your observation on your question"
] |
https://api.github.com/repos/huggingface/transformers/issues/387 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/387/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/387/comments | https://api.github.com/repos/huggingface/transformers/issues/387/events | https://github.com/huggingface/transformers/issues/387 | 421,899,003 | MDU6SXNzdWU0MjE4OTkwMDM= | 387 | run_squad.py cannot predict only | {
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https://github.com/huggingface/pytorch-pretrained-BERT/blob/f3e5404880902a1bdfed2b1d47d10a6c672dc430/examples/run_squad.py#L1011-L1025 | {
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"It is better to imitate original Bert repo to add separate argument `args.vocab_file`, and during prediction, argument `bert_model` is the directory containing the fine-tuned model. ",
"Make sense indeed. Would you like to submit a PR on that?",
"This issue has been automatically marked as stale because it ... |
https://api.github.com/repos/huggingface/transformers/issues/384 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/384/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/384/comments | https://api.github.com/repos/huggingface/transformers/issues/384/events | https://github.com/huggingface/transformers/issues/384 | 421,794,835 | MDU6SXNzdWU0MjE3OTQ4MzU= | 384 | Incrementally Train BERT with minimum QnA records - to get improved results | {
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https://datascience.stackexchange.com/questions/47406/incrementally-train-bert-with-minimum-qna-records
Question is after training on my data on some new questions and answers, new checkpoints are generated. With new checkpoints, when as... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Wondering Noone is replying\n\nOn Sat, 25 May, 2019, 4:09 PM stale[bot], <notifications@github.com> wrote:\n\n> Closed #384\n> <https:/... |
https://api.github.com/repos/huggingface/transformers/issues/638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/638/comments | https://api.github.com/repos/huggingface/transformers/issues/638/events | https://github.com/huggingface/transformers/issues/638 | 448,020,154 | MDU6SXNzdWU0NDgwMjAxNTQ= | 638 | GPT-2 Tokenizer error! | {
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"Maybe you can find the solution at #537 ",
"> Maybe you can find the solution at #537\r\n\r\nThank for your support! It works for me!"
] |
https://api.github.com/repos/huggingface/transformers/issues/647 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/647/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/647/comments | https://api.github.com/repos/huggingface/transformers/issues/647/events | https://github.com/huggingface/transformers/issues/647 | 450,256,737 | MDU6SXNzdWU0NTAyNTY3Mzc= | 647 | No softmax activation in BertForTokenClassification | {
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In the `forward` function, it treats it's out as probabilities (Cross Entropy for loss) but there's no softmax. Is there a reason for that? | {
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"It's because `nn.CrossEntropyLoss` already has a Softmax integrated in the module:\r\nhttps://pytorch.org/docs/stable/nn.html?highlight=crossentropy#torch.nn.CrossEntropyLoss",
"I see it now. Thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/641 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/641/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/641/comments | https://api.github.com/repos/huggingface/transformers/issues/641/events | https://github.com/huggingface/transformers/issues/641 | 449,349,557 | MDU6SXNzdWU0NDkzNDk1NTc= | 641 | The prediction accuracy for the masked token is ZERO when using the pretrained model. Does it make sense? | {
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I run the pretrained model BertForPreTraining and test it on my own text data. Because BERT has knowledge about language so I expect it to be able to predict the masked tokens with a reasonable accuracy,... | {
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https://api.github.com/repos/huggingface/transformers/issues/456 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/456/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/456/comments | https://api.github.com/repos/huggingface/transformers/issues/456/events | https://github.com/huggingface/transformers/issues/456 | 430,270,548 | MDU6SXNzdWU0MzAyNzA1NDg= | 456 | max_seq_length for squad | {
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"Then you're doomed for this answer. There are a possibility to do a sliding window approach but we didn't implemented it in the examples of pytorch-pretrained-bert.\r\nCheck this issue (and the linked TensorFlow issue) for a discussion on this: https://github.com/huggingface/pytorch-pretrained-BERT/issues/89"
] |
https://api.github.com/repos/huggingface/transformers/issues/395 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/395/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/395/comments | https://api.github.com/repos/huggingface/transformers/issues/395/events | https://github.com/huggingface/transformers/issues/395 | 423,581,764 | MDU6SXNzdWU0MjM1ODE3NjQ= | 395 | AttributeError: 'BertOnlyMLMHead' object has no attribute 'seq_relationship' | {
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```bash
Skipping cls/predictions/transform/dense/kernel/adam_m
Skipping cls/predictions/transform/dense/kernel/adam_v
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-11-5... | {
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"Hi,\r\nWhat command are you running to load the model?\r\nAre you loading your own model or one or our pre-trained one?\r\n\r\nIt's normal that there is no `seq_relationship` attribute in a `BertOnlyMLMHead` but our pre-trained model should load without error.",
"\r\nI was loading my own pre-trained model by \"c... |
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"Maybe you should ask in the AllenNLP repo as well?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] |
https://api.github.com/repos/huggingface/transformers/issues/402 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/402/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/402/comments | https://api.github.com/repos/huggingface/transformers/issues/402/events | https://github.com/huggingface/transformers/issues/402 | 424,585,953 | MDU6SXNzdWU0MjQ1ODU5NTM= | 402 | gpt2 tokenizer issue with ValueError: chr() arg not in range(256) in Python 2.X | {
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Here's a solution for python 2.X
```python
@lru_cache()
def bytes_to_unicode():
"""
Returns list of utf-8 byte and a corresponding list of unicode strings.
The reversi... | {
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"Indeed, I have added backward compatibility to python 2 for GPT-2.\r\nDo you want to submit a PR on this?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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https://api.github.com/repos/huggingface/transformers/issues/408 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/408/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/408/comments | https://api.github.com/repos/huggingface/transformers/issues/408/events | https://github.com/huggingface/transformers/issues/408 | 425,298,071 | MDU6SXNzdWU0MjUyOTgwNzE= | 408 | slow training speed even 20 steps | {
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I am running run_lm_finetuning.py code on a 1 million sentences .
It's taking more than 20 hours even for each epoch.
where as run_pretraining.py code from google-research/bert takes very less time.
What can be the reason?
How to resolve this? | {
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"We have new lm_fintetuning scripts thanks to @Rocketknight1 PR #392.\r\nMaybe you can try these ones.\r\nThey are in the `./examples/lm_finetuning/` folder.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for ... |
https://api.github.com/repos/huggingface/transformers/issues/410 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/410/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/410/comments | https://api.github.com/repos/huggingface/transformers/issues/410/events | https://github.com/huggingface/transformers/issues/410 | 425,411,023 | MDU6SXNzdWU0MjU0MTEwMjM= | 410 | something wrong in example | {
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... | closed | false | [] | null | 3 | 2019-03-26T13:15:19Z | 2019-06-03T08:37:46Z | 2019-06-03T08:37:46Z | null | NONE | [] | null | null | null | null |
the segmentation is wrong。。 | {
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"Do you have the latest `pytorch-pretrained-bert` ?\r\n```python\r\nimport pytorch_pretrained_bert\r\npytorch_pretrained_bert.__version__\r\n```",
"Thank you so much!!!!!!!",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occur... |
https://api.github.com/repos/huggingface/transformers/issues/377 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/377/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/377/comments | https://api.github.com/repos/huggingface/transformers/issues/377/events | https://github.com/huggingface/transformers/issues/377 | 420,722,840 | MDU6SXNzdWU0MjA3MjI4NDA= | 377 | Empty nbest_predictions.json for run_squad.py | {
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It should be outside of the "if else" loop. | {
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"Good catch! Do you want to submit a PR? Otherwise, I'll fix it in the next release.",
"Hi @thomwolf \r\nThe issue still persists, there were two extra indentations and you removed only one to move the line out of inner if-else but, one more indentation should be removed to bring [L620](https://github.com/hugging... |
https://api.github.com/repos/huggingface/transformers/issues/247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/247/comments | https://api.github.com/repos/huggingface/transformers/issues/247/events | https://github.com/huggingface/transformers/issues/247 | 405,757,654 | MDU6SXNzdWU0MDU3NTc2NTQ= | 247 | Multilabel classification and diverging loss | {
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I'm not sure I'm posting this at the right spot but I am trying to use your excellent implementation to do some multi label classification on some text. I basically adapted the run_classifier.py code to a Jupyter Notebook and change a little bit the BERT Sequence Classifier model so it can handle multilabel clas... | {
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"Hey, I am working on something similar. I feel like the original code might be incorrect. They seem to directly take the output of the model as 'loss' without applying any criteria. But I might be totally wrong. ",
"Hey! :)\r\n\r\nReally? What do you mean by criteria?\r\n\r\nI tried to artificially change my dat... |
https://api.github.com/repos/huggingface/transformers/issues/663 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/663/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/663/comments | https://api.github.com/repos/huggingface/transformers/issues/663/events | https://github.com/huggingface/transformers/issues/663 | 453,088,216 | MDU6SXNzdWU0NTMwODgyMTY= | 663 | Accumulation | {
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https://api.github.com/repos/huggingface/transformers/issues/416 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/416/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/416/comments | https://api.github.com/repos/huggingface/transformers/issues/416/events | https://github.com/huggingface/transformers/issues/416 | 426,242,746 | MDU6SXNzdWU0MjYyNDI3NDY= | 416 | Distributed Training Gets Stuck | {
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When I freeze the BERT layers, distributed training works just fine. However, when I unfreeze the BERT layers, the first node continues training, and all other nodes wait on the training step with 100% GPU utilization on the first GPU. Is this expected behavior, or am I doing something wrong?
I'm using PyTorc... | {
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"Hi,\r\nOne possible cause of this behavior may be the way you are freezing your parameters.\r\n\r\nPyTorch's `DistributedDataParallel` is a rather sensitive beast as you can juge by the number of warnings in [its doc](https://pytorch.org/docs/stable/nn.html#torch.nn.parallel.DistributedDataParallel).\r\n\r\nTwo fe... |
https://api.github.com/repos/huggingface/transformers/issues/434 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/434/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/434/comments | https://api.github.com/repos/huggingface/transformers/issues/434/events | https://github.com/huggingface/transformers/issues/434 | 427,743,495 | MDU6SXNzdWU0Mjc3NDM0OTU= | 434 | Model not training at all in Google Colab | {
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I am initiating training in the following way in a Colab notebook with GPU acceleration (with very small train batch size and max seq length to prove I'm not getting out of memory problems!):
!pip install pytorch-pretrained-bert
!rm -rf bert_output
!mkdir bert_output
!... | {
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"Try train_batch_size =1. Alternatively I propose to finetune with the tensorflow model using colabs TPUs as these have far more memory.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n... |
https://api.github.com/repos/huggingface/transformers/issues/421 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/421/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/421/comments | https://api.github.com/repos/huggingface/transformers/issues/421/events | https://github.com/huggingface/transformers/issues/421 | 426,549,937 | MDU6SXNzdWU0MjY1NDk5Mzc= | 421 | pytorch model to tensorflow checkpoint | {
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"Hi, there is no script to do that currently. I don't plan to add this feature in the short term but I would be happy to welcome a PR on that.",
"A PR for this would be great. It would allow a simple deployment via Han's bert-as-service\r\n https://github.com/hanxiao/bert-as-service/",
"This issue has been aut... |
https://api.github.com/repos/huggingface/transformers/issues/442 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/442/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/442/comments | https://api.github.com/repos/huggingface/transformers/issues/442/events | https://github.com/huggingface/transformers/issues/442 | 428,418,589 | MDU6SXNzdWU0Mjg0MTg1ODk= | 442 | Unable to incrementally train BERT with custom training | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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https://api.github.com/repos/huggingface/transformers/issues/439 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/439/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/439/comments | https://api.github.com/repos/huggingface/transformers/issues/439/events | https://github.com/huggingface/transformers/issues/439 | 428,321,776 | MDU6SXNzdWU0MjgzMjE3NzY= | 439 | DistributedDataParallel Not Working | {
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... | closed | false | [] | null | 2 | 2019-04-02T16:18:27Z | 2019-06-09T10:47:43Z | 2019-06-09T10:47:43Z | null | NONE | [] | null | null | null | null | Hi, I've been stuck on this for days, so I decided to make an issue.
When I run DistributedDataParallel with the PyTorch launch module, I see that one machine will start training without waiting for the other one to start; this is different than if I run it without the launch module. WIthout the launch module, I am ... | {
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"Hi @moinnadeem,\r\nWhat is the hardware you are using and what is the exact command you are using to run DistributedDataParallel with the PyTorch launch module? ",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you... |
https://api.github.com/repos/huggingface/transformers/issues/668 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/668/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/668/comments | https://api.github.com/repos/huggingface/transformers/issues/668/events | https://github.com/huggingface/transformers/pull/668 | 453,981,634 | MDExOlB1bGxSZXF1ZXN0Mjg2NTI4MTYw | 668 | apply Whole Word Masking technique | {
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referred to [link](https://github.com/google-research/bert/blob/master/create_pretraining_data.py) | {
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"Nice, thanks @jeonsworld "
] |
https://api.github.com/repos/huggingface/transformers/issues/662 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/662/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/662/comments | https://api.github.com/repos/huggingface/transformers/issues/662/events | https://github.com/huggingface/transformers/issues/662 | 452,974,452 | MDU6SXNzdWU0NTI5NzQ0NTI= | 662 | MRPC / SQuAD stuck in "Running training" | {
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I am stuck since days.
ubuntu 19.04 (tried 18.04 also)
NVIDIA-SMI 418.74 Driver Version: 418.74
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
>>> impor... | {
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"Update: specify device works for at least 1 GPU\r\n\r\nexport CUDA_VISIBLE_DEVICES=0\r\npython run_classifier.py \\\r\n\r\n\r\nmore than 1 GPU still not working:\r\n\r\nexport CUDA_VISIBLE_DEVICES=0,1\r\npython run_classifier.py \\\r\n",
"@AndreasFdev Your distributed training setting is False.",
"Problem:\r\n... |
https://api.github.com/repos/huggingface/transformers/issues/670 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/670/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/670/comments | https://api.github.com/repos/huggingface/transformers/issues/670/events | https://github.com/huggingface/transformers/issues/670 | 454,491,144 | MDU6SXNzdWU0NTQ0OTExNDQ= | 670 | warmup for BertAdam | {
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BertAdam() can update learning rate by itself.
Why update learning rate manually here? | {
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"Because we don't use BertAdam in fp16 mode but the optimizer of NVIDIA's apex library.",
"OK thank you!"
] |
https://api.github.com/repos/huggingface/transformers/issues/301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/301/comments | https://api.github.com/repos/huggingface/transformers/issues/301/events | https://github.com/huggingface/transformers/issues/301 | 412,222,150 | MDU6SXNzdWU0MTIyMjIxNTA= | 301 | `train_dataset` and `eval_dataset` in run_openai_gpt.py | {
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```
$ python run_openai_gpt.py --output_dir tmp --do_eval
Traceback (most recent call last):
File "run_openai_gpt.py", line 259, in <module>
main()
File "run_openai_gpt.py", line 153, in main
train_dataset = load_rocstorie... | {
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"Hi Ben,\r\nPlease read the [relevant example section in the readme](https://github.com/huggingface/pytorch-pretrained-BERT#fine-tuning-openai-gpt-on-the-rocstories-dataset).",
"@thomwolf I see that the data is downloaded and cached in case of not providing the `train_dataset` and `eval_dataset` parameters: https... |
https://api.github.com/repos/huggingface/transformers/issues/283 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/283/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/283/comments | https://api.github.com/repos/huggingface/transformers/issues/283/events | https://github.com/huggingface/transformers/issues/283 | 410,723,439 | MDU6SXNzdWU0MTA3MjM0Mzk= | 283 | unicode | {
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python2.7 run_squad.py \
--bert_model bert-base-uncased \
--do_train \
--do_predict \
--do_lower_case \
--train_file $SQUAD_DIR/train-v1.1.json \
--predi... | {
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"Yes, the examples are not adapted for Python 2, only the library.\r\nI don't plan to adapt or maintain them but feel free to submit a PR!",
"env: python2.7\r\nline 662: writer.write(json.dumps(all_predictions, indent=4) + \"\\n\")\r\nchange as :writer.write(json.dumps(all_predictions, indent=4).decode('utf-8') +... |
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"Thanks @meetshah1995 "
] |
https://api.github.com/repos/huggingface/transformers/issues/461 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/461/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/461/comments | https://api.github.com/repos/huggingface/transformers/issues/461/events | https://github.com/huggingface/transformers/issues/461 | 430,686,503 | MDU6SXNzdWU0MzA2ODY1MDM= | 461 | Pooler weights not being updated for Multiple Choice models? | {
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"followers_url": "https://api.github.com/users/meetps/foll... | [] | closed | false | [] | null | 5 | 2019-04-08T22:29:35Z | 2019-06-12T17:40:47Z | 2019-06-12T17:40:47Z | null | CONTRIBUTOR | [] | null | null | null | null | I'm trying use pretrained BERT to finetune on a multiple choice dataset.
The parameters from `pooler` are excluded from the optimizer params [here](https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/pytorch_pretrained_bert/modeling.py#L1044-L1047), however, the MutlipleChoice model does indeed use `p... | {
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"Indeed this looks like a bug in the `run_swag.py` example.\r\nWhat do you think @rodgzilla?\r\nIsn't the exclusion of the pooler parameters from optimization ([line 392 of `run_swag.py`](https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/examples/run_swag.py#L392)) a typo?",
"This issue has been ... |
https://api.github.com/repos/huggingface/transformers/issues/375 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/375/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/375/comments | https://api.github.com/repos/huggingface/transformers/issues/375/events | https://github.com/huggingface/transformers/issues/375 | 420,557,663 | MDU6SXNzdWU0MjA1NTc2NjM= | 375 | How to input the fine-tuned model? | {
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python run_lm_finetuning.py \
--bert_model bert-base-uncased \ .
--output_dir models \
...
As a result the fine-tuned model is now in models/pytorch_model.bin
But how do I use it to classify? The example doesn't mention that.
I don't fi... | {
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"maybe you can take a look at the \"cache_dir\" argument. For the run_classifier.py file, it is located at line 498",
"I tried with --cache_dir , giving the fine-tunings output directory as cache_dir. \r\nI added these 2 files to the directory: bert_config.json and vocab.txt from the original bert_basic_uncased\r... |
https://api.github.com/repos/huggingface/transformers/issues/682 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/682/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/682/comments | https://api.github.com/repos/huggingface/transformers/issues/682/events | https://github.com/huggingface/transformers/issues/682 | 455,859,694 | MDU6SXNzdWU0NTU4NTk2OTQ= | 682 | Can't find gpt2 vocab file. | {
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```
tokenizer = GPT2Tokenizer.from_pretrained(pretrained_model_name_or_path='gpt2',cache_dir=None)
```
I am getting this
```
Model name 'gpt2' was not found in model name list (gpt2). We assumed 'gpt2' was a path or url but couldn't find files https://s3.amazonaws.com/models.huggingface.co/bert/... | {
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"I got the solution.\r\n"
] |
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https://api.github.com/repos/huggingface/transformers/issues/401 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/401/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/401/comments | https://api.github.com/repos/huggingface/transformers/issues/401/events | https://github.com/huggingface/transformers/issues/401 | 424,517,333 | MDU6SXNzdWU0MjQ1MTczMzM= | 401 | How can I generate new text after having fine-tuned BERT on a custom dataset ? | {
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Once I've fine-tuned the Language Model, how can I get it to generate new text ? Is there any example available ?
Thanks ! | {
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"Also interested in this! ",
"Hi,\r\nIt's quite difficult to use BERT to generate text as BERT is not a causal language model per se.\r\nHere is an example: https://github.com/nyu-dl/bert-gen by @W4ngatang and @kyunghyuncho.",
"Bert was not trained for text generation since it's not trained in the classical lm ... |
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