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DanielPFlorian

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Transformers-Github-Issues

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1610?src=pr&el=h1) Report\n> Merging [#1610](https://codecov.io/gh/huggingface/transformers/pull/1610?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef1b8b2ae5ad1057154a126879f7eb8de685f862?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1610?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1610 +/- ##\n=======================================\n Coverage 86.17% 86.17% \n=======================================\n Files 91 91 \n Lines 13595 13595 \n=======================================\n Hits 11715 11715 \n Misses 1880 1880\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1610?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1610?src=pr&el=footer). Last update [ef1b8b2...2248c6b](https://codecov.io/gh/huggingface/transformers/pull/1610?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Why should we change this?" ]

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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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=h1) Report\n> Merging [#1608](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef1b8b2ae5ad1057154a126879f7eb8de685f862?src=pr&el=desc) will **increase** coverage by `0.02%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1608 +/- ##\n=========================================\n+ Coverage 86.17% 86.2% +0.02% \n=========================================\n Files 91 91 \n Lines 13595 13595 \n=========================================\n+ Hits 11715 11719 +4 \n+ Misses 1880 1876 -4\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1608/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2ZpbGVfdXRpbHMucHk=) | `76.37% <0%> (+2.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=footer). Last update [ef1b8b2...bd847ce](https://codecov.io/gh/huggingface/transformers/pull/1608?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks @focox!" ]

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[ "Hi, this seems to be a network error. Are you sure you have access to the internet on this machine, or is it behind a firewall?", "I had exactly the same problem Yesterday and s3.amazonaws.com just was not reachable. We also had the same problem with another service as well. After trying for some time it just started working again." ]

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[ "I feel that this would clutter the README, leading to a bad experience for 99.99% of users. But you can always submit a PR and see what the maintainers think.", "Just make a PR." ]

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[ "As far as I know pytorch-pretrained-bert development has been discontinued. That makes sense. If you want the new features, you have to upgrade.", "Well technically what I'm asking for isn't a new feature, it's just backwards-compatibility for the above three model artifacts.\r\n\r\nI can manually add them to the `modeling_gpt2.py` in my conda environment containing pytorch-pretrained-bert 0.6.2 and verify if these model artifacts work with the old package by invoking the `from_pretrained()` method with each of these three artifact names. I am guessing they would work, but I haven't tried yet.\r\n\r\nI feel like this dictionary containing pre-trained artifact names should itself reside in S3, and in `modeling_gpt2.py`, the dictionary should be pulled from S3. Then you could continually add new artifact sizes to that dictionary in S3 and it will work with all versions of this repo, not just some versions. Does that make sense?", "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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=h1) Report\n> Merging [#1604](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef1b8b2ae5ad1057154a126879f7eb8de685f862?src=pr&el=desc) will **decrease** coverage by `<.01%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1604 +/- ##\n==========================================\n- Coverage 86.17% 86.16% -0.01% \n==========================================\n Files 91 91 \n Lines 13595 13593 -2 \n==========================================\n- Hits 11715 11713 -2 \n Misses 1880 1880\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/tokenization\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1604/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl9jdHJsLnB5) | `96.03% <0%> (-0.08%)` | :arrow_down: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=footer). Last update [ef1b8b2...6e85bcc](https://codecov.io/gh/huggingface/transformers/pull/1604?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Ready to merge", "Awesome!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=h1) Report\n> Merging [#1603](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e16d46843a19ab289b82138e4eccec5610a76de7?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1603 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/tokenization\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1603/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl9jdHJsLnB5) | `96.03% <0%> (ø)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=footer). Last update [e16d468...b0af23c](https://codecov.io/gh/huggingface/transformers/pull/1603?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "In my script, I take another approach for this. I assume that distributed training can only be instantiated by using torch's launch script 'or that at least the WORLD_SIZE env variable is set). `local_rank` will be used for the GPU id, even when not in distributed mode.\r\n\r\n```python\r\n# torch.distributed.launch adds a world_size environment variable\r\ndistributed = int(os.environ['WORLD_SIZE']) > 1 if 'WORLD_SIZE' in os.environ else False\r\n```\r\n\r\nBased on that, you can decide what you want to do with `local_rank`. If we're in distributed mode, start the process group, if we're not: use the `local_rank` cuda device.\r\n\r\n```python\r\nif local_rank == -1 or not torch.cuda.is_available():\r\n device = torch.device('cpu')\r\nelse:\r\n device = torch.device(f\"cuda:{local_rank}\")\r\n if distributed:\r\n dist.init_process_group(backend='nccl', init_method='env://')\r\n```\r\n\r\nAs a bonus, to ensure that all processes such as validating only happen on the main device, even if that's not cuda:0 (even though personally I do that on all devices, too):\r\n\r\n```python\r\nis_first_process = not distributed or local_rank in [0, -1]\r\n# ...\r\nif args.do_eval and is_first_process:\r\n # do eval\r\n```\r\n\r\nI merely post this for possible inspiration, of course!", "Sounds good to me let's add this to all the examples (and the template in `templates/adding_a_new_example_script`)", "> Sounds good to me let's add this to all the examples\r\n\r\nThe other scripts maybe make less sense as you would want to train on all available devices? Not 100% sure yet.", "Ok I see, then maybe let's have the device flag on `run_generation` instead of `run_squad` (as currently proposed in the PR)?", "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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[ "Great, thanks!", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1602?src=pr&el=h1) Report\n> Merging [#1602](https://codecov.io/gh/huggingface/transformers/pull/1602?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1cfd9748683db43af2c98da1a19d39f0efc8cc3b?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1602?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1602 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1602?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1602?src=pr&el=footer). Last update [1cfd974...25d32f4](https://codecov.io/gh/huggingface/transformers/pull/1602?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=h1) Report\n> Merging [#1601](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c?src=pr&el=desc) will **decrease** coverage by `0.01%`.\n> The diff coverage is `100%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1601 +/- ##\n==========================================\n- Coverage 85.9% 85.88% -0.02% \n==========================================\n Files 91 91 \n Lines 13653 13640 -13 \n==========================================\n- Hits 11728 11715 -13 \n Misses 1925 1925\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3JvYmVydGEucHk=) | `70.55% <ø> (-0.71%)` | :arrow_down: |\n| [transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3JvYmVydGEucHk=) | `89.9% <ø> (-0.77%)` | :arrow_down: |\n| [transformers/tests/tokenization\\_bert\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl9iZXJ0X3Rlc3QucHk=) | `98.66% <100%> (ø)` | :arrow_up: |\n| [transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl91dGlscy5weQ==) | `91.43% <100%> (ø)` | :arrow_up: |\n| [transformers/tests/tokenization\\_roberta\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl9yb2JlcnRhX3Rlc3QucHk=) | `92.45% <100%> (ø)` | :arrow_up: |\n| [transformers/tests/tokenization\\_xlnet\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl94bG5ldF90ZXN0LnB5) | `97.91% <100%> (ø)` | :arrow_up: |\n| [transformers/tests/tokenization\\_tests\\_commons.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl90ZXN0c19jb21tb25zLnB5) | `100% <100%> (ø)` | :arrow_up: |\n| [transformers/tests/tokenization\\_xlm\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl94bG1fdGVzdC5weQ==) | `97.72% <100%> (ø)` | :arrow_up: |\n| [transformers/tests/tokenization\\_distilbert\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1601/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl9kaXN0aWxiZXJ0X3Rlc3QucHk=) | `95.23% <100%> (ø)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=footer). Last update [079bfb3...3617469](https://codecov.io/gh/huggingface/transformers/pull/1601?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Great, LGTM" ]

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[ "Are you using the GPT tokenizer? If not try\r\n\r\n```\r\ntokenizer = transformers.OpenAIGTPTTokenizer()\r\ninput_ids = tokenizer.encode(your_text)\r\n```\r\n\r\n", "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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[ "Hi @anandhperumal. Remember that you train GPT-2 by doing next-token prediction, therefore you need to compare the i-th input label--the truth--with what the model predicted: the (i-1)th output. Hence the indices shift.", "@rlouf oh yeah. Thanks for the input.\r\nif you don't mind can you answer this question as well [transformers](https://github.com/huggingface/transfer-learning-conv-ai/issues/43) it's not directly related to transformers.\r\nThanks again.", "You're welcome. I haven't worked on the other codebase, but I'll try to help if I can." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=h1) Report\n> Merging [#1598](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b8c9ea0010a09cca8173e5bdf4af855123aebfc7?src=pr&el=desc) will **decrease** coverage by `4.94%`.\n> The diff coverage is `100%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1598 +/- ##\n==========================================\n- Coverage 86.16% 81.22% -4.95% \n==========================================\n Files 91 57 -34 \n Lines 13593 8028 -5565 \n==========================================\n- Hits 11713 6521 -5192 \n+ Misses 1880 1507 -373\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [pytorch\\_transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-cHl0b3JjaF90cmFuc2Zvcm1lcnMvbW9kZWxpbmdfdXRpbHMucHk=) | `90.3% <100%> (ø)` | |\n| [transformers/modeling\\_tf\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3hsbS5weQ==) | | |\n| [transformers/configuration\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fZGlzdGlsYmVydC5weQ==) | | |\n| [transformers/configuration\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fYmVydC5weQ==) | | |\n| [transformers/tests/tokenization\\_transfo\\_xl\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl90cmFuc2ZvX3hsX3Rlc3QucHk=) | | |\n| [transformers/tests/modeling\\_bert\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX2JlcnRfdGVzdC5weQ==) | | |\n| [transformers/tests/tokenization\\_utils\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl91dGlsc190ZXN0LnB5) | | |\n| [transformers/tests/modeling\\_tf\\_ctrl\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2N0cmxfdGVzdC5weQ==) | | |\n| [transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3hsbmV0LnB5) | | |\n| [transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl91dGlscy5weQ==) | | |\n| ... and [139 more](https://codecov.io/gh/huggingface/transformers/pull/1598/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=footer). Last update [b8c9ea0...9388320](https://codecov.io/gh/huggingface/transformers/pull/1598?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks you for this, I actually had this fix included in #1721" ]

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[ "Hi @BramVanroy, thanks for reporting this. There was an issue in the docstring. It does not use prefix spaces and it does not use a byte-level BPE like GPT-2 does. The docstring should be fixed now." ]

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[ "I'm a bit confused: you're basically defining the broad case of named entity recognition. Is it not enough to have a binary NER (token-level classification) task for entity vs non-entity?", "Assuming you have 3-class (PER, ORG, LOC) data with labels:\r\nB-PER, I-PER, B-ORG, I-ORG, B-LOC, I-LOC, as well as O\r\n\r\nReplace PER, ORG, LOC with ENT.\r\nThis leaves you with these labels:\r\nB-ENT, I-ENT, O\r\n\r\nYou can do this before training, and then train a model specifically for 1-class named entity detection only.\r\nOr you can do this as a post-processing step on the output of the normal 3-class model.", "@bheinzerling Thank you!!\r\n I will try this." ]

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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", "I faced the same problem:I solved it by passing the size of your vocabulary (from your custom tokenizer) as a parameter.\r\nI proceeded as follows:\r\n`vocabulary_size = tokenizer.vocab_size`\r\n```\r\nconfiguration = tf.TransfoXLConfig(vocab_size_or_config_json_file=vocabulary_size, cutoffs=cutoffs,\r\n d_model=512, d_embed=512, n_head=8, d_head=64, n_layer=12, d_inner=2048)\r\n```\r\nI hope that helped :)", "P.s. What do you pass as inputs and labels?\r\nFor now, I create a batch as follows:\r\n\"The quick brown fox jumps over the lazy dog\"\r\nIf I have batch_size=2, and sequence length=4:\r\n[\"The quick brown fox\",\r\n\"jumps over the lazy\"]\r\n\r\nWhat do you feed to the Transformer-XL as input?" ]

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[ "I believe a quick workaround is to just install the pre-built, CPU version of TensorFlow 2.0. If you won't be running the TF benchmarks, it wouldn't affect anything.", "True, but still not quite flexible. Since the goal of the benchmark script is to, I believe, encourage the community to add there runtimes, it's a good to make this as easy-to-use as possible.", "You're right that we shouldn't require to have both libraries installed in order to benchmark only one of them. I've updated the Benchmark code so that you can run it with only a single library installed.", "That's great, Lysandre. Thanks for pushing out changes so quickly!" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=h1) Report\n> Merging [#1593](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/702f589848baba97ea4897aa3f0bb937e1ec3bcf?src=pr&el=desc) will **decrease** coverage by `0.77%`.\n> The diff coverage is `82.23%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1593 +/- ##\n==========================================\n- Coverage 84.73% 83.95% -0.78% \n==========================================\n Files 84 94 +10 \n Lines 12573 13951 +1378 \n==========================================\n+ Hits 10654 11713 +1059 \n- Misses 1919 2238 +319\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3RyYW5zZm9feGwucHk=) | `92.21% <ø> (+0.97%)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX2JlcnQucHk=) | `96.6% <ø> (+0.89%)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX2dwdDIucHk=) | `94.79% <ø> (+1.31%)` | :arrow_up: |\n| [transformers/tokenization\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl9ncHQyLnB5) | `96.72% <ø> (ø)` | :arrow_up: |\n| [transformers/configuration\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fZ3B0Mi5weQ==) | `88.63% <ø> (ø)` | :arrow_up: |\n| [transformers/configuration\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fcm9iZXJ0YS5weQ==) | `100% <ø> (ø)` | :arrow_up: |\n| [transformers/configuration\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fYmVydC5weQ==) | `87.09% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX29wZW5haS5weQ==) | `96.04% <ø> (+1.43%)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX2Rpc3RpbGJlcnQucHk=) | `98.59% <ø> (+1.98%)` | :arrow_up: |\n| [transformers/tests/modeling\\_tf\\_gpt2\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2dwdDJfdGVzdC5weQ==) | `94.73% <0%> (ø)` | :arrow_up: |\n| ... and [79 more](https://codecov.io/gh/huggingface/transformers/pull/1593/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=footer). Last update [702f589...3408e84](https://codecov.io/gh/huggingface/transformers/pull/1593?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "I just realized that it's better to try to import AdamW in optimization, and if not available define the custom AdamW class." ]

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[ "this lgtm but let's wait for @thomwolf and @LysandreJik to chime in", "I'd also like to improve the test cases. I'll try to find some time for that this weekend", "Nice improvement, it would be even better with tests for DistilBERT and XLNet as both those models make use of the `do_lower_case` argument. TransfoXL also uses the `lower_case` argument and XLM the `do_lowercase_and_remove_accent` argument so it might be a good idea to test that those models have the correct behavior.\r\n\r\nPutting tests in the `tokenization_tests_common` would probably be cleaner than in each model's test file, if we test all models rather than a single one.", "@LysandreJik good points.\r\n\r\n~Now that I'm thinking about it, it seems like it would make more sense to do the lowercasing/accent removal directly in the subclasses (`BertTokenizer`, `XLMtokenizer`, etc.) by overriding the `tokenize()` method from `PreTrainedTokenizer`, performing the normalization there, then calling the super `tokenize()` with the now-normalized text.~\r\n\r\nNever mind, this would result in some silly code duplication.", "Alright that looks good to me!", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=h1) Report\n> Merging [#1592](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/de2696f68e20019fef3a5e1b54de10351abb4145?src=pr&el=desc) will **decrease** coverage by `1.22%`.\n> The diff coverage is `100%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1592 +/- ##\n==========================================\n- Coverage 84.26% 83.03% -1.23% \n==========================================\n Files 104 104 \n Lines 15431 15456 +25 \n==========================================\n- Hits 13003 12834 -169 \n- Misses 2428 2622 +194\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/tests/tokenization\\_tests\\_commons.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL3Rva2VuaXphdGlvbl90ZXN0c19jb21tb25zLnB5) | `100% <100%> (ø)` | :arrow_up: |\n| [transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl91dGlscy5weQ==) | `92.21% <100%> (+0.07%)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3B5dG9yY2hfdXRpbHMucHk=) | `9.85% <0%> (-83.1%)` | :arrow_down: |\n| [transformers/tests/modeling\\_tf\\_common\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2NvbW1vbl90ZXN0LnB5) | `81.55% <0%> (-15.54%)` | :arrow_down: |\n| [transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3JvYmVydGEucHk=) | `59.41% <0%> (-12.36%)` | :arrow_down: |\n| [transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3hsbmV0LnB5) | `71.18% <0%> (-2.44%)` | :arrow_down: |\n| [transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2N0cmwucHk=) | `94.24% <0%> (-2.22%)` | :arrow_down: |\n| [transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1592/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX29wZW5haS5weQ==) | `80.66% <0%> (-1.34%)` | :arrow_down: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=footer). Last update [de2696f...21637d4](https://codecov.io/gh/huggingface/transformers/pull/1592?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Ok merging!" ]

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[ "The same error occurs with the library installed with `git clone` (_master_ version) + torch v1.3.0 + python v3.6.8.\r\n[Here](https://colab.research.google.com/drive/1nawWX6Lrfh9ZVKyRfTLgFSIG355xkPRy#scrollTo=n93UZjq5EIE_) is a more verbose version of the Colab Notebook posted by @bkkaggle with Google Colab.", "I've just pushed a fix on the branch `fix-ctrl-past`. It should be in the next release.", "Thanks, closing" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1590?src=pr&el=h1) Report\n> Merging [#1590](https://codecov.io/gh/huggingface/transformers/pull/1590?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4d456542e9d381090f9a00b2bcc5a4cb07f6f3f7?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1590?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1590 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1590?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1590?src=pr&el=footer). Last update [4d45654...0322842](https://codecov.io/gh/huggingface/transformers/pull/1590?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Fixing TF Roberta and TF XLNet seem to be much trickier than XLM. **I will open a separate PR for XLM alone since that works fine.** \r\n\r\nFor TF Roberta and TF XLNet, the solution might be to simply run them eagerly at a rather severe performance penalty. `tf.function` speeds it up a lot but seems to introduce some inconsistency in the weight saving, which might be a TensorFlow issue and I don't yet have the time to investigate.", "@tlkh did you look into the shape errors any further? I'm getting similar errors in eager mode on tf-nightly, didn't try 2.0 (need some other fixes in 2.1)\r\n\r\n```\r\ntensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [91,91,64,12] vs. [91,181,64,12]\r\n\t [[node model/tfxl_net_lm_head_model/transformer/layer_._0/rel_attn/add_2 (defined at .../transformers/modeling_tf_xlnet.py:148) ]] [Op:__inference_distributed_function_17027]\r\n```", "@NathanHowell sorry, I don't have any ideas about that! Seems to be the same error, but oddly running it in eager mode fixed it for me.", "Thanks a lot @tlkh\r\n\r\nSo I think RoBERTa is now fixed on master (removed the faulty check in the forward pass) and XLM as well (with your other PR).\r\n\r\nDo you want to make a new PR with fixes for XLNet and we close the present one maybe?", "@thomwolf thanks, I'll close the current PR and open a new one for XLNet after I validate it again. " ]

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[ "Hi! Actually, if we count DistilGPT-2 as a standalone architecture, it should be 10. Do you think you could update it to 10 before we merge? Thanks." ]

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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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[ "We are currently working on implementing seq2seq for most models in the library (see https://github.com/huggingface/transformers/pull/1455). I won't be ready before a week or two.", "I'm closing this issue, but feel free to reply in #1506 that we leave open for comments on this implementation." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=h1) Report\n> Merging [#1586](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/82f6abd98aaa691ca0adfe21e85a17dc6f386497?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1586 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2dwdDIucHk=) | `84.19% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX29wZW5haS5weQ==) | `96.04% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3RyYW5zZm9feGwucHk=) | `92.21% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3JvYmVydGEucHk=) | `80.57% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RyYW5zZm9feGwucHk=) | `75.16% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX2N0cmwucHk=) | `97.75% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3hsbS5weQ==) | `88.42% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2JlcnQucHk=) | `88.17% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2N0cmwucHk=) | `95.45% <ø> (ø)` | :arrow_up: |\n| [transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX29wZW5haS5weQ==) | `81.75% <ø> (ø)` | :arrow_up: |\n| ... and [7 more](https://codecov.io/gh/huggingface/transformers/pull/1586/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=footer). Last update [82f6abd...d36680d](https://codecov.io/gh/huggingface/transformers/pull/1586?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "This is great thanks. Actually we should be adding this to all the examples for all the models...", "@thomwolf Would be happy to make the changes for the rest of the models.", "@thomwolf added changes for the rest of the pytorch model examples and all the tensorflow model examples\r\n\r\nI used the two bash scripts below to identify files to edit:\r\n```\r\n# Pytorch model examples\r\ngrep -iR \"input_ids = torch.tensor(tokenizer.encode(\" .\r\n\r\n# Tensorflow model examples\r\ngrep -iR \"input_ids = tf.constant(tokenizer.encode(\" .\r\n```\r\n\r\n**UPDATE:** Example documentation changes were implemented for all tensorflow models except for ```modeling_tf_distilbert.py``` since ```TFDistilBertModelTest.test_pt_tf_model_equivalence``` would fail under **build_py3_torch_and_tf** (details in error [logs](https://circleci.com/gh/huggingface/transformers/5245?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link) for commit: ec276d6abad7eae800f1a1a039ddc78fde406009)", "Thanks for that.\r\n\r\n@LysandreJik even though we will have special tokens added by default in the coming release, maybe we still want to update the doc for the current release with this? (not sure this is possible)", "I agree that the necessity to add special tokens should be explicit. However, the documentation is based on previous commits so changing the previous documentation would require to change the commit history of the repo (which we should not do). \r\n\r\nWe might need to think of a way to work around that to update the misleading documentation of previous versions like in this case." ]

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[ "I don't think that's right. AdamW is implemented in transformers.optimization\r\n\r\nhttps://github.com/huggingface/transformers/blob/82f6abd98aaa691ca0adfe21e85a17dc6f386497/transformers/optimization.py#L107\r\n\r\nAs far as I can see that does not require anything specific to torch 1.2. _However_, if you are trying to import [AdamW from torch ](https://pytorch.org/docs/stable/optim.html#torch.optim.AdamW), you may indeed be required to use torch 1.2.\r\n\r\nI haven't compared the implementation in torch vs. transformers, but I'd go with torch's native implementation if you can and otherwise fallback to transformers' implementation.", "sorry, I didn't show the details:\r\nthe error is from 29 line in transformers/examples/distillation/distiller.py\r\nfrom torch.optim import AdamW\r\nthis AdamW is imported from torch.optim", "does this really need torch >=1.2? I met this problem", "my torch version is 1.1", "No. Importing AdamW from transformers should work with earlier versions. If you're trying to import it directly from torch, then you'll need 1.2+.", "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", "Unstale. ", "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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=h1) Report\n> Merging [#1584](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/82f6abd98aaa691ca0adfe21e85a17dc6f386497?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1584 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/1584/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2JlcnQucHk=) | `88.17% <ø> (ø)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=footer). Last update [82f6abd...1972e0e](https://codecov.io/gh/huggingface/transformers/pull/1584?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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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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[ "Hello @evehsu,\r\n\r\nBERT uses an additional non-linearity before the vocabulary projection (see [here](https://github.com/huggingface/transformers/blob/master/transformers/modeling_bert.py#L381)).\r\nIt's a design choice, as far as I know, XLM doesn't a non-linearity right before the vocab projection (the language modeling head).\r\n\r\nI left this option because I experimented with it, but if you want to keep the BERT architecture as unchanged as possible, you should use the `--vocab_transform` to ensure you also extract the pre-trained weights for this non-linearity.\r\n\r\nVictor", "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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[ "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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1580?src=pr&el=h1) Report\n> Merging [#1580](https://codecov.io/gh/huggingface/transformers/pull/1580?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/82f6abd98aaa691ca0adfe21e85a17dc6f386497?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1580?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1580 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1580?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1580?src=pr&el=footer). Last update [82f6abd...abd7110](https://codecov.io/gh/huggingface/transformers/pull/1580?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Oh yes, great, thanks, Pasquale. Would you mind fixing the `run_glue` and `run_ner` examples as well?", "@thomwolf done! what's the best way to check this code before merging?", "Thanks a lot!\r\nIt should be fine, we have continuous integration tests on `run_glue` and `run_squad` so if it passed at least the code run." ]

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[ "Merging with #1506" ]

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[ "Hi, DistilGPT-2 is considered to be a checkpoint of GPT-2 in our library (differently to DistilBERT). You can already use DistilGPT-2 for both of these scripts with the following:\r\n```bash\r\npython run_generation --model_type=gpt2 --model_name_or_path=distilgpt2\r\n```" ]

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[ "Please note that main() now returns a list with ```num_samples``` elements inside.\r\n\r\nBecause of this, the test for run_generation.py should be updated to test for ```length``` for each element within the list. This explains why **build_py3_torch** test failed.\r\n\r\nI will update ```ExamplesTests.test_generation``` to reflect the new output format.", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1577?src=pr&el=h1) Report\n> Merging [#1577](https://codecov.io/gh/huggingface/transformers/pull/1577?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef1b8b2ae5ad1057154a126879f7eb8de685f862?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1577?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1577 +/- ##\n=======================================\n Coverage 86.17% 86.17% \n=======================================\n Files 91 91 \n Lines 13595 13595 \n=======================================\n Hits 11715 11715 \n Misses 1880 1880\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1577?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1577?src=pr&el=footer). Last update [ef1b8b2...17dd64e](https://codecov.io/gh/huggingface/transformers/pull/1577?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Latest commit 17dd64e now applies repetition penalty and ```top_k_top_p_filtering``` to each candidate sequence separately.", "Thanks @enzoampil \r\n\r\nSuperseded by https://github.com/huggingface/transformers/pull/1333 which was just merged to master.\r\n\r\nLet me know if this works for your use case." ]

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[ "Do you get any improvement? \r\nThe ACC of eval and test has a huge gap.\r\n", " --classification-head when converting the models ", "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", "I am unable to reproduce the results on the RACE dataset. If anyone has been able to reproduce it, could you kindly share the weights of the fine-tuned model ?" ]

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[ "Merging with #1506" ]

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[ "Hello, could you provide a script so that we may better understand the problem here?", "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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[ "Closing this because I found my answer", "Hi, would you mind sharing what the answer you found is? Thank you so much!", "Sorry for the delay. Gpt2 was trained as a CLM model with a fixed block size of data. So there was no need for attention mask. (That is what I understood). " ]

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[ "@zhaoxy92 I happen to have a use case for this as well. I'll add in this feature to the ```run_generation.py```", "@zhaoxy92 Added this functionality in ```run_generation.py```. You can set the number of candidates generated by setting the argument ```num_samples``` which is set to 1 by default.", "I think you need to change `top_k_top_p_filtering()` as well.", "@s-js not sure why we'd have to change```top_k_top_p_filtering()``` since the sampling only happens at ```sample_sequence()```. ```top_k_top_p_filtering()``` only filters the logits, so we can still generate multiple candidate sequences (independent of the filtered distribution).", "@enzoampil Sorry, I meant repetition penalty (https://github.com/enzoampil/transformers/blob/7facbbe9871fe458b530ae8ce1b4bfefabd47c74/examples/run_generation.py#L142). Each sample has a different set of seen tokens.\r\nAt first I thought you were doing it inside `top_k_top_p_filtering()`.", "Hi, thanks very much for adding this functionality – I'm trying to implement this into my own notebook and hitting a tensor mismatch error I can't figure out. I hope this is the right forum to post this question, since I'm using the new functionality you created.\r\n\r\nAt line 150: `generated = torch.cat((generated, next_token.unsqueeze(0)), dim=1)`\r\n\r\nI'm getting this error:\r\n```RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 1. Got 1 and 3 in dimension 0 at /opt/conda/conda-bld/pytorch_1556653114079/work/aten/src/THC/generic/THCTensorMath.cu:71```\r\n\r\nThe debugger shows me the sizes:\r\ngenerated = (3,37)\r\nnext_token.unsqueeze(0) = (1,3)\r\n\r\nSo I figure that next_token tensor shape ought to be (3,1) instead, so I tried changing the line to `next_token.unsqueeze(1)` instead. When I do that I get a `CUDA error: device-side assert triggered`. Did that change fix my problem or just cause a new one?\r\n\r\nAny ideas are greatly appreciated, thank you!", "hi @buttchurch , did you run ```run_generation.py``` (with the multiple sentence functionality) as a CLI? It should work if you run it from my [fork](https://github.com/enzoampil/transformers/blob/7facbbe9871fe458b530ae8ce1b4bfefabd47c74/examples/run_generation.py#L142). Can you please post here the exact script you ran and the complete error message. \r\n\r\nAlso, my pull [request](https://github.com/enzoampil/transformers/blob/7facbbe9871fe458b530ae8ce1b4bfefabd47c74/examples/run_generation.py#L142) shows ```generated = torch.cat((generated, next_token.unsqueeze(1)), dim=1)``` in the last line of ```sample_sequence``` so I'm not sure where you got that line 150 code snippet.", "@s-js noted on repetition penalty support. I'll try to find time for this within the next week.", "hi @enzoampil, thanks for such a quick response! I still don't understand navigating git forks and branches and the different versions of git projects very well, so I have been just going off the main code I find in the transformers github.\r\n\r\nIt's probably not the 'right' way to do it, but I've pulled my own jupyter notebook together from a couple of the transformer example.py files, rather than using the run_generation.py. I think it might be way too long to post here, but I will now try implementing the changes in your fork to my notebook. I'll report back – thanks again for your help, and for creating this new functionality :)\r\n\r\nEdit: It works! Seems like the important bit I was missing was `replacement=True` on the previous line.", "@buttchurch glad it works for you :) Very welcome!", "@s-js Latest [commit](https://github.com/huggingface/transformers/commit/17dd64ed939e09c1c9b1fa666390dd69a4731387) now implements _repetition penalty_ and ```top_k_top_p_filtering``` separately per candidate sequence generated.", "We just merged https://github.com/huggingface/transformers/pull/1333 to master (+ subsequent fixes), can you check that it does what you guys want?\r\n\r\nI'll close the issue for now, re-open if needed." ]

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[ "`from_pretrained` expects the following files: `vocab.txt`, `config.json` and `pytorch_model.bin`. \r\n\r\nThus, you only need to extract the `weights.tar.gz` archive. \r\n\r\nThen rename `bert_config.json` to `config.json` and pass the path name to the `from_pretrained` method: this should be `/content/scibert_scivocab_uncased` in your example :)" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=h1) Report\n> Merging [#1570](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/82f6abd98aaa691ca0adfe21e85a17dc6f386497?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `100%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1570 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1570/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3JvYmVydGEucHk=) | `100% <100%> (ø)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=footer). Last update [82f6abd...55c3ae1](https://codecov.io/gh/huggingface/transformers/pull/1570?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Hum this situation is a bit annoying because we switched from `logger.error` to `tf.print` to solve #1350", "Is there a specific reason why we have such a warning message for Roberta but not for other models? All models based on BERT are require the special tokens.\r\nI was having the same issues as #1350 on my end using the logger (lots of zmq , operationnotallowed errors) . The solution for me was to remove the entire warning message altogether.\r\nIs that viable in this scenario? ", "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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[ "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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=h1) Report\n> Merging [#1568](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/82f6abd98aaa691ca0adfe21e85a17dc6f386497?src=pr&el=desc) will **decrease** coverage by `0.02%`.\n> The diff coverage is `100%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1568 +/- ##\n==========================================\n- Coverage 86.16% 86.14% -0.03% \n==========================================\n Files 91 91 \n Lines 13593 13593 \n==========================================\n- Hits 11713 11710 -3 \n- Misses 1880 1883 +3\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1568/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2ZpbGVfdXRpbHMucHk=) | `74.17% <100%> (ø)` | :arrow_up: |\n| [transformers/tests/modeling\\_tf\\_common\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1568/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2NvbW1vbl90ZXN0LnB5) | `95.21% <0%> (-1.6%)` | :arrow_down: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=footer). Last update [82f6abd...a2c8c8e](https://codecov.io/gh/huggingface/transformers/pull/1568?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Ok, LGTM thanks" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1567?src=pr&el=h1) Report\n> Merging [#1567](https://codecov.io/gh/huggingface/transformers/pull/1567?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1567?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1567 +/- ##\n======================================\n Coverage 85.9% 85.9% \n======================================\n Files 91 91 \n Lines 13653 13653 \n======================================\n Hits 11728 11728 \n Misses 1925 1925\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1567?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1567?src=pr&el=footer). Last update [079bfb3...079bfb3](https://codecov.io/gh/huggingface/transformers/pull/1567?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Any reason why you kept the batch sizes so small? With a V100, you should be able to easily pull of a batch size of 64 for seq len 64. (Perhaps that's what the benchmark script uses as default, I don't know EDIT: yes, those are the values from the benchmark script. Not sure why, though.) I'm a bit surprised by the relatively small speed up. I've experienced **much** greater speed ups when using AMP, but that was on PyTorch with apex.", "@BramVanroy this is for **inference** hence the emphasis on low batch size.", "Oh, my bad. I was under the impression that the benchmark script included training profiling with PyProf. " ]

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[ "I don't understand when you get this error?", "In order to understand when you've encountered this bug, as suggested by @iedmrc , you've to write down the source code that generates the bug! And please show your environment (Python, Transformers, PyTorch, TensorFlow versions) too! \r\n\r\n> Error content:\r\n> OSError: Error no file named ['pytorch_model.bin', 'tf_model.h5', 'model.ckpt.index'] found in directory ./uncased_L-12_H-768_A-12_transformers or `from_tf` set to False\r\n> but file exists\r\n> ", "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", "I got the same error when loading a TF BERT model: \r\n```\r\ndir = \"/Users/danielk/ideaProjects/farsi-language-models/src/models/perbert_L-12_H-768_A-12/\"\r\ntokenizer = BertTokenizer.from_pretrained(dir)\r\nconfig = BertConfig.from_json_file(dir + '/bert_config.json')\r\nmodel = TFBertForMaskedLM.from_pretrained(dir, config=config)\r\n```\r\nThe error happens in the last line. \r\n```\r\nTraceback (most recent call last):\r\n File \"6.2.try_tf_bert_transformers.py\", line 8, in <module>\r\n model = TFBertForMaskedLM.from_pretrained(dir, config=config)\r\n File \"/Users/danielk/opt/anaconda3/lib/python3.7/site-packages/transformers/modeling_tf_utils.py\", line 353, in from_pretrained\r\n [WEIGHTS_NAME, TF2_WEIGHTS_NAME], pretrained_model_name_or_path\r\nOSError: Error no file named ['pytorch_model.bin', 'tf_model.h5'] found in directory /Users/danielk/ideaProjects/farsi-language-models/src/models/perbert_L-12_H-768_A-12/ or `from_pt` set to False\r\n```" ]

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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", "I think you can see [here](https://jalammar.github.io/a-visual-guide-to-using-bert-for-the-first-time/). In more details, this tutorial uses **BERT** as **feature extractor** and on-top they have used a **Logistic Regression** model from [Scikit-learn](https://scikit-learn.org/stable/) for the **sentiment analysis** task. \r\n\r\nQuestion: which is the problem in details? Are you not able to connect the feature vector extracted by BERT to a custom classifier on-top? Is the shape of the feature vector fixed?\r\n\r\n> ## Questions & Help\r\n> Hello, I am a student who is learning nlp.\r\n> Now I want to use the word vector output by bert to apply to my model, but **I can't connect the word vector to the network**. Could you give me an example program or tutorial about this which use textCNN or LSTM. You can sent e-mail to **[[email protected]](mailto:[email protected])** or reply me, please.\r\n> Thank you for your kind cooperation!", "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://github.com/brightmart/albert_zh", "Please direct all your questions to the main albert topic. https://github.com/huggingface/transformers/issues/1370 \r\n\r\nPlease close this current topic. It does not add anything.", "... We should extend the issue template and redirect all ALBERT questions to #1370 😂" ]

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[ "This should be fixed in https://github.com/huggingface/transformers/pull/1580", "yeah @yangyiben please let me know if that merge fixes it", "#1580 is now merged" ]

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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", "There's a newer [approach](https://github.com/mandarjoshi90/coref) using BERT but it's using tensorflow 1.14. I wish if we could get this into hugginface.\r\n" ]

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[ "@hawkeoni [CLS] and [SEP] tokens are added automatically as long as you use the tokenizer, ```BertTokenizer```", "@enzoampil It doesn't seem to work.\r\nThe following code\r\n```python\r\nfrom transformers import BertTokenizer\r\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\r\nsentence = \"Hello there, General Kenobi!\"\r\nprint(tokenizer.encode(sentence))\r\nprint(tokenizer.cls_token_id, tokenizer.sep_token_id)\r\n```\r\nproduces the next output: \r\n\r\n[7592, 2045, 1010, 2236, 6358, 16429, 2072, 999]\r\n101 102\r\n\r\nAs you can see, cls and sep tokens are not in the list.", "@hawkeoni please try ```print(tokenizer.encode(sentence, add_special_tokens=True))```", "@enzoampil I'm sorry, but you're missing the point that the documentation is plainly wrong and misleading. That's why I asked whether the tokens should be added at all.", "@hawkeoni Apologies, yes I did miss your point.\r\n\r\nIs this intentional or just a typo? **Looks like a typo since special tokens weren't added. Setting ```add_special_tokens=True``` should make this correct (will add this in).**\r\n\r\nDo I need to add [CLS] & [SEP] tokens when I fine tune base bert for sequence classification or token classification? **Yes, I believe this is currently handled by ```load_and_cache_examples``` in the sample training scripts (e.g. ```run_ner.py```)**", "@enzoampil Thanks for your answer! If you plan on fixing this typo, please, fix it everywhere, so this issue never occurs again.\r\nYou can find it with \r\n```bash\r\ngrep -iR \"input_ids = torch.tensor(tokenizer.encode(\" .\r\n```\r\n", "@hawkeoni thanks for the bash script reco. Ended up using it :)", "Thank you both for that.\r\nPlease note that the special tokens will be added by default from now on (already on master and in the coming release)." ]

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[ "Hello, if you want to try and fine-tune GPT-2 to another language, you can just give the `run_lm_finetuning` script your text in the other language on which you want to fine-tune your model. \r\n\r\nHowever, please be aware that according to the language and its distance to the English language (language on which GPT-2 was pre-trained), you may find it hard to obtain good results. ", "@0x01h\r\n\r\nGPT-2 can produce great results given a proper vocabulary. If you just run `run_lm_finetuning` on your lang dataset it will give you poor results, regardless of language distance from English because the vocab. \r\n\r\nI'd suggest that you train your tokenizer model first and then fine-tune GPT-2 with it. I'm doing that here \r\nhttps://github.com/mgrankin/ru_transformers\r\n\r\n", "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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[ "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" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

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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", "Did you find a solution?", "> Did you find a solution?\r\n\r\nRename \"bert_config.json\" to \"config.json\"." ]

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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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[ "Could you specify what script you're running, with which parameters? Did you set a random seed?", "> Could you specify what script you're running, with which parameters? Did you set a random seed?\r\n\r\nfor SEEDS in 99\r\n\r\ndo\r\nCUDA_VISIBLE_DEVICES=2 python run_glue.py \\\r\n --data_dir '/data/transformers/data/RTE/' \\\r\n --model_type 'roberta' \\\r\n --model_name_or_path '/data/transformers/examples/pretrained_model/roberta-mnli/' \\\r\n --task_name 'rte' \\\r\n --output_dir ./$SEEDS \\\r\n --overwrite_output_dir \\\r\n --max_seq_length 128 \\\r\n --do_train \\\r\n --do_eval \\\r\n --evaluate_during_training \\\r\n --per_gpu_train_batch_size 8 \\\r\n --per_gpu_eval_batch_size 8 \\\r\n --gradient_accumulation_steps 2 \\\r\n --learning_rate 1e-5 \\\r\n --num_train_epochs 10 \\\r\n --logging_steps 50 \\\r\n --save_steps -1 \\\r\n --seed $SEEDS \\\r\n\r\ndone\r\n\r\n\r\n", "> Could you specify what script you're running, with which parameters? Did you set a random seed?\r\n\r\ni change 'roberta' to 'bert' and set the same seed, the result is also different, Is there any wrong with my shell script?" ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=h1) Report\n> Merging [#1555](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fd97761c5a977fd22df789d2851cf57c7c9c0930?src=pr&el=desc) will **increase** coverage by `1.42%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1555 +/- ##\n==========================================\n+ Coverage 84.74% 86.16% +1.42% \n==========================================\n Files 91 91 \n Lines 13593 13593 \n==========================================\n+ Hits 11519 11713 +194 \n+ Misses 2074 1880 -194\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1555/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX29wZW5haS5weQ==) | `81.75% <0%> (+1.35%)` | :arrow_up: |\n| [transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1555/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2N0cmwucHk=) | `95.45% <0%> (+2.27%)` | :arrow_up: |\n| [transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/1555/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3hsbmV0LnB5) | `73.28% <0%> (+2.46%)` | :arrow_up: |\n| [transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1555/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3JvYmVydGEucHk=) | `80.57% <0%> (+15.1%)` | :arrow_up: |\n| [transformers/tests/modeling\\_tf\\_common\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1555/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2NvbW1vbl90ZXN0LnB5) | `96.8% <0%> (+17.02%)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1555/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3B5dG9yY2hfdXRpbHMucHk=) | `92.95% <0%> (+83.09%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=footer). Last update [fd97761...090cbd6](https://codecov.io/gh/huggingface/transformers/pull/1555?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks @rakeshchada. Closing as superseded by #1814 " ]

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[ "Hey @tuhinjubcse gpt2 is a text generation model. If you look in the run_glue.py file you will see your options for model selection for using the run_glue.py script.\r\n```\r\nMODEL_CLASSES = {\r\n 'bert': (BertConfig, BertForSequenceClassification, BertTokenizer),\r\n 'xlnet': (XLNetConfig, XLNetForSequenceClassification, XLNetTokenizer),\r\n 'xlm': (XLMConfig, XLMForSequenceClassification, XLMTokenizer),\r\n 'roberta': (RobertaConfig, RobertaForSequenceClassification, RobertaTokenizer),\r\n 'distilbert': (DistilBertConfig, DistilBertForSequenceClassification, DistilBertTokenizer)\r\n}\r\n```", "gpt2 is a transformer model. Why would it be limited to only generation ??", "It's not that you can't use it for classification, etc. It's that you would need to make a few changes to the code and model. #1248 . Right now the changes are not made for gpt2. Generally speaking, people use gpt2 for text generation.", "Autoregressive models are not as good as mlms, at classification tasks. You should check masked language models (mlm) or similars. But it's not impossible, Open AI has shown some example use cases on original [GPT paper](https://s3-us-west-2.amazonaws.com/openai-assets/research-covers/language-unsupervised/language_understanding_paper.pdf). Check the figure 1 and page 6 for more details.\r\nAlso, this is not a bug but just not implemented. ", "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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=h1) Report\n> Merging [#1553](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fd97761c5a977fd22df789d2851cf57c7c9c0930?src=pr&el=desc) will **increase** coverage by `1.42%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1553 +/- ##\n==========================================\n+ Coverage 84.74% 86.16% +1.42% \n==========================================\n Files 91 91 \n Lines 13593 13593 \n==========================================\n+ Hits 11519 11713 +194 \n+ Misses 2074 1880 -194\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1553/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX29wZW5haS5weQ==) | `81.75% <0%> (+1.35%)` | :arrow_up: |\n| [transformers/modeling\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1553/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2N0cmwucHk=) | `95.45% <0%> (+2.27%)` | :arrow_up: |\n| [transformers/modeling\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/1553/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3hsbmV0LnB5) | `73.28% <0%> (+2.46%)` | :arrow_up: |\n| [transformers/modeling\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1553/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3JvYmVydGEucHk=) | `80.57% <0%> (+15.1%)` | :arrow_up: |\n| [transformers/tests/modeling\\_tf\\_common\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1553/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2NvbW1vbl90ZXN0LnB5) | `96.8% <0%> (+17.02%)` | :arrow_up: |\n| [transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1553/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3B5dG9yY2hfdXRpbHMucHk=) | `92.95% <0%> (+83.09%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=footer). Last update [fd97761...0919389](https://codecov.io/gh/huggingface/transformers/pull/1553?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "up ?", "Why not, indeed. Ok to merge it." ]

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[ "Can you show exactly how you ran ```run_generation.py```?", "@enzoampil thanks, this is my command:\r\n```python run_generation.py --model_type=gpt2 --model_name_or_path=gpt2_finetuned/ --top_k 10 --temperature 0.8 --top_p 0.0 --stop_token \"<|endoftext|>\" ```", "Can you try running ```python run_generation.py --model_type=gpt2 --model_name_or_path=gpt2_finetuned/ --top_k 10 --temperature 0.8 --top_p 0.0``` and post the output here. \r\n\r\nIf the output looks fine at this point, just exclude the ```stop_token``` argument when running ```run_generation.py```", "I see the problem. At the decoding step using ```tokenizer.decode```, we set ```skip_special_tokens=True```.\r\n\r\nIn other words, special tokens are removed at the decoding step, so you the ```stop_token``` argument should not be a special token.", "@enzoampil \r\n1) I tried without --stop_token and the output is the same.\r\n2) I don't think ``` skip_special_tokens=True ``` is the problem, since I had already set that to **False**.\r\nDid you mean --stop_token is a problem? Am I doing something wrong?", "Can you try to set ```clean_up_tokenization_spaces=False```", "Yeah I actually tried that one too and still the output doesn't change. @enzoampil ", "Would you mind sending over your model files? Can't seem to replicate the 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", "Is it solved?", "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", "I know this is old, but I'm having the same issue (and I've never had it before). It was introduced after I added a Tokenizers `BPEDecoder` to my tokenizer. I'm using special tokens as a way of logically parsing my (non-language) input, and I need the special tokens in the output so that another stage of processing can use them for understanding the structure of the prediction. But there are no spaces between my special tokens and the next word. It's not a huge deal, I suppose, because I could fix it in post-processing, but I'd like to know what's up.\r\n\r\n[EDIT] Just to note; in my case it has nothing to do with prediction. I'm just testing the encode/decode of my tokenizer and noticing these spaces missing in the decoded output." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1551?src=pr&el=h1) Report\n> Merging [#1551](https://codecov.io/gh/huggingface/transformers/pull/1551?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c5441946112e68441b46866d114bf8d3c29b0c1d?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1551?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1551 +/- ##\n=======================================\n Coverage 86.16% 86.16% \n=======================================\n Files 91 91 \n Lines 13593 13593 \n=======================================\n Hits 11713 11713 \n Misses 1880 1880\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1551?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1551?src=pr&el=footer). Last update [c544194...4f05239](https://codecov.io/gh/huggingface/transformers/pull/1551?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Hello! That's great, thank you!" ]

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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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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1549?src=pr&el=h1) Report\n> Merging [#1549](https://codecov.io/gh/huggingface/transformers/pull/1549?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8a62835577a2a93642546858b21372e43c1a1ff8?src=pr&el=desc) will **not change** coverage.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1549?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1549 +/- ##\n=======================================\n Coverage 85.14% 85.14% \n=======================================\n Files 94 94 \n Lines 13920 13920 \n=======================================\n Hits 11852 11852 \n Misses 2068 2068\n```\n\n\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1549?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1549?src=pr&el=footer). Last update [8a62835...9a3b173](https://codecov.io/gh/huggingface/transformers/pull/1549?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "This is great, thanks @hlums.\r\nI'm adding information on the runs/results in the example's readme and merging.", "@ShengeBelmendo I think we set them to the right values here as well (cf lines 309-310 in `run_squad`).", "Ok LGTM, merging this PR, thanks @hlums ", "@thomwolf oh, I'm sorry for missing that.\r\n\r\nAnd another small question. @hlums Have you tested whether set the `do_lower_case` option or not ? It seems that we shouldn't set this option cuz the model is the cased version and it also didn't be set in official code.\r\n\r\nI'm trying to reproduce the results of xlnet but obviously there are some problems especially for squad2.0, it's still a long way to go.", "> @thomwolf oh, I'm sorry for missing that.\r\n> \r\n> And another small question. @hlums Have you tested whether set the `do_lower_case` option or not ? It seems that we shouldn't set this option cuz the model is the cased version and it also didn't be set in official code.\r\n> \r\n> I'm trying to reproduce the results of xlnet but obviously there are some problems especially for squad2.0, it's still a long way to go.\r\n\r\nYou are right. I shouldn't have set the do_lower_case flag. I can give it a try some time this week. \r\nHave you tried the latest code on squad 2.0? I thought put the cls token at the right place would help a lot because it's used for unanswerable question classification. ", "> > @thomwolf oh, I'm sorry for missing that.\r\n> > And another small question. @hlums Have you tested whether set the `do_lower_case` option or not ? It seems that we shouldn't set this option cuz the model is the cased version and it also didn't be set in official code.\r\n> > I'm trying to reproduce the results of xlnet but obviously there are some problems especially for squad2.0, it's still a long way to go.\r\n> \r\n> You are right. I shouldn't have set the do_lower_case flag. I can give it a try some time this week.\r\n> Have you tried the latest code on squad 2.0? I thought put the cls token at the right place would help a lot because it's used for unanswerable question classification.\r\n\r\n@hlums Sorry for late reply. The latest code doesn't work, you will get a f1 score closed to 0 on unanswerable questions. But I have found the reason. \r\n\r\nThe following is a piece of code in forward function of xlnet model, which obviously is the key point of training the model on unanswerable questions using cls token representations. But the default value of tensor `is_impossible`(using to indicate whether this example is answerable) is none, and we also hadn't passed this tensor into forward function. That's the problem. \r\n\r\n``` \r\n if cls_index is not None and is_impossible is not None:\r\n # Predict answerability from the representation of CLS and START\r\n cls_logits = self.answer_class(hidden_states, start_positions=start_positions, cls_index=cls_index)\r\n loss_fct_cls = nn.BCEWithLogitsLoss()\r\n cls_loss = loss_fct_cls(cls_logits, is_impossible)\r\n total_loss += cls_loss * 0.5\r\n```\r\n\r\nI added the `is_impossible` tensor to TensorDataset and model inputs, and got a reasonable result, f1: 84, EM: 80. Maybe I can creat a PR for this, maybe after I find more discrepancies and get better results. I'm working hard to reproduce the results of xlnet on squad2.0, so I hope you can tell me if you have some new ideas or finds.Thanks! ", "@hlums before your fix:\r\n`xlnet-large-cased`, SQuAD 1.1, 2 epochs, MSL: 512, BS: 48\r\n{\r\n \"exact\": 75.01419110690634,\r\n \"f1\": 82.13017516396678,\r\n \"total\": 10570,\r\n \"HasAns_exact\": 75.01419110690634,\r\n \"HasAns_f1\": 82.13017516396678,\r\n \"HasAns_total\": 10570\r\n}\r\nPost fix, awesome:\r\n{\r\n \"exact\": 85.1371807000946,\r\n \"f1\": 92.24219729313499,\r\n \"total\": 10570,\r\n \"HasAns_exact\": 85.1371807000946,\r\n \"HasAns_f1\": 92.24219729313499,\r\n \"HasAns_total\": 10570\r\n}\r\nThanks again for your fix!\r\n\r\n`xlnet-large-cased`, SQuAD 2.0, max_steps: 8000, MSL: 512, BS: 48\r\n{\r\n \"exact\": 40.95005474606249,\r\n \"f1\": 45.305949189220875,\r\n \"total\": 11873,\r\n \"HasAns_exact\": 81.96693657219973,\r\n \"HasAns_f1\": 90.69121705864026,\r\n \"HasAns_total\": 5928,\r\n \"NoAns_exact\": 0.050462573591253154,\r\n \"NoAns_f1\": 0.050462573591253154,\r\n \"NoAns_total\": 5945\r\n}\r\n\r\nHopefully `xlnet-large-cased` on _SQuAD 2.0_ for the holidays: @ShengeBelmendo https://github.com/huggingface/transformers/pull/1803\r\nLimited what I can contribute to the code/logic, but I can run tests 24 x 7.", "@ShengeBelmendo I tried turning do_lower_case off, but the model performance didn't change much.\r\n\r\n\r\nSorry I'm not actively working QA anymore so probably won't be able to contribute to the improvement on squad 2.0\r\n\r\nAnother thing mentioned in the XLNet paper is layer-wise learning rate decay. I actually tried implementing it, but it didn't help with the performance on 1.1 for me. See #1198 \r\n\r\nThe pre-processing code in the XLNet repo also looks much more complicated than here. I'm not sure if it has anything to do with the performance discrepancy though. \r\n", "@hlums ok, tks again. I will check more carefully about the pre-processing part and maybe read all the official code for comparison." ]

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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=h1) Report\n> Merging [#1548](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/33adab2b91697b3e78af618a21ab9f1176281165?src=pr&el=desc) will **decrease** coverage by `1.44%`.\n> The diff coverage is `44.59%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #1548 +/- ##\n==========================================\n- Coverage 81.47% 80.03% -1.45% \n==========================================\n Files 122 128 +6 \n Lines 18342 19325 +983 \n==========================================\n+ Hits 14945 15467 +522 \n- Misses 3397 3858 +461\n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [transformers/commands/download.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbW1hbmRzL2Rvd25sb2FkLnB5) | `0% <0%> (ø)` | |\n| [transformers/commands/run.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbW1hbmRzL3J1bi5weQ==) | `0% <0%> (ø)` | |\n| [transformers/commands/train.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbW1hbmRzL3RyYWluLnB5) | `0% <0%> (ø)` | |\n| [transformers/commands/convert.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbW1hbmRzL2NvbnZlcnQucHk=) | `0% <0%> (ø)` | |\n| [transformers/tests/model\\_card\\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsX2NhcmRfdGVzdC5weQ==) | `97.5% <100%> (ø)` | :arrow_up: |\n| [transformers/data/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2RhdGEvX19pbml0X18ucHk=) | `100% <100%> (ø)` | :arrow_up: |\n| [transformers/data/processors/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2RhdGEvcHJvY2Vzc29ycy9fX2luaXRfXy5weQ==) | `100% <100%> (ø)` | :arrow_up: |\n| [transformers/modeling\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3V0aWxzLnB5) | `93.06% <100%> (+1.37%)` | :arrow_up: |\n| [transformers/data/processors/utils.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2RhdGEvcHJvY2Vzc29ycy91dGlscy5weQ==) | `19.37% <12.5%> (-25.53%)` | :arrow_down: |\n| [transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX2F1dG8ucHk=) | `32.55% <19.04%> (-5.08%)` | :arrow_down: |\n| ... and [34 more](https://codecov.io/gh/huggingface/transformers/pull/1548/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=footer). Last update [33adab2...db0795b](https://codecov.io/gh/huggingface/transformers/pull/1548?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

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[ "Hi @oligiles0, you can actually use ```run_lm_finetuning.py``` for this. You can find more details in the **RoBERTa/BERT and masked language modeling** section in the README", "> Hi @oligiles0, you can actually use `run_lm_finetuning.py` for this. You can find more details in the **RoBERTa/BERT and masked language modeling** section in the README\r\n\r\nThanks very much @enzoampil . Is there a reason this uses a single text file as opposed to taking a folder of text files? I wouldn't want to combine multiple documents because some chunks will then cross documents and interfere with training, but I also wouldn't want to rerun the script for individual documents. ", "> Thanks very much @enzoampil . Is there a reason this uses a single text file as opposed to taking a folder of text files? I wouldn't want to combine multiple documents because some chunks will then cross documents and interfere with training, but I also wouldn't want to rerun the script for individual documents.\r\n\r\nPlease check https://github.com/huggingface/transformers/issues/1896#issuecomment-557222822\r\n\r\n", "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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[ "If you play with the script a bit, you can see that the loss for BERT with the MLM head is actually quite high, as someone suggested elsewhere, this may be due to pre-training on different tasks than just MLM", "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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[ "Hmm looks like BertTokenizer's super class handles `.add_tokens()` and the first steps of `.tokenize()`, and doesn't really seem to consider whether the tokens should be made lowercase. I'm not sure whether it's intentional, but I'll make a PR and find out :smile: \r\n\r\nIn the meantime, it might be a good idea to manually lowercase your text before tokenization.", "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" ]