run_lm_finetuning.py on bert-base-uncased with wikitext-2-raw does not work
# 🐛 Bug

## Running run_lm_finetuning.py on bert-base-uncased with wikitext-2-raw does not work. 

Model I am using (Bert, XLNet ...): Bert - bert-base-uncased

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [*] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [*] an official GLUE/SQUaD task: train language model on wikitext
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. Installed Transformers from the source (git pull and then pip install). Downloaded Wikitext-2 raw dataset.
2. Ran this command ""python run_lm_finetuning.py --output_dir=output --model_type=bert --model_name_or_path=bert-base-uncased --do_train  --train_data_file=E:\\Code\\data\\wikitext-2-raw\\wiki.train.raw --do_eval --eval_data_file=E:\\Code\\data\\wikitext-2-raw\\wiki.test.raw --mlm""
3. This fails in train() method. I haven't touched the code. Stacktraces below:

python run_lm_finetuning.py --output_dir=output --model_type=bert --model_name_or_path=bert-base-uncased --do_train  --train_data_file=E:\\Code\\data\\wikitext-2-raw\\wiki.train.raw --do_eval --eval_data_file=E:\\Code\\data\\wikitext-2-raw\\wiki.test.raw --mlm
2020-01-31 21:51:38.831236: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
01/31/2020 21:51:40 - WARNING - __main__ -   Process rank: -1, device: cuda, n_gpu: 1, distributed training: False, 16-bits training: False
01/31/2020 21:51:40 - INFO - transformers.file_utils -   https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-config.json not found in cache or force_download set to True, downloading to C:\Users\athre\AppData\Local\Temp\tmp91_kkef0
01/31/2020 21:51:40 - INFO - transformers.file_utils -   copying C:\Users\athre\AppData\Local\Temp\tmp91_kkef0 to cache at C:\Users\athre\.cache\torch\transformers\4dad0251492946e18ac39290fcfe91b89d370fee250efe9521476438fe8ca185.8f56353af4a709bf5ff0fbc915d8f5b42bfff892cbb6ac98c3c45f481a03c685
01/31/2020 21:51:40 - INFO - transformers.file_utils -   creating metadata file for C:\Users\athre\.cache\torch\transformers\4dad0251492946e18ac39290fcfe91b89d370fee250efe9521476438fe8ca185.8f56353af4a709bf5ff0fbc915d8f5b42bfff892cbb6ac98c3c45f481a03c685
01/31/2020 21:51:40 - INFO - transformers.file_utils -   removing temp file C:\Users\athre\AppData\Local\Temp\tmp91_kkef0
01/31/2020 21:51:40 - INFO - transformers.configuration_utils -   loading configuration file https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-config.json from cache at C:\Users\athre\.cache\torch\transformers\4dad0251492946e18ac39290fcfe91b89d370fee250efe9521476438fe8ca185.8f56353af4a709bf5ff0fbc915d8f5b42bfff892cbb6ac98c3c45f481a03c685
01/31/2020 21:51:40 - INFO - transformers.configuration_utils -   Model config {
  "architectures": [
    "BertForMaskedLM"
  ],
  "attention_probs_dropout_prob": 0.1,
  "finetuning_task": null,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "id2label": {
    "0": "LABEL_0",
    "1": "LABEL_1"
  },
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "is_decoder": false,
  "label2id": {
    "LABEL_0": 0,
    "LABEL_1": 1
  },
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "num_labels": 2,
  "output_attentions": false,
  "output_hidden_states": false,
  "output_past": true,
  "pruned_heads": {},
  "torchscript": false,
  "type_vocab_size": 2,
  "use_bfloat16": false,
  "vocab_size": 30522
}

01/31/2020 21:51:40 - INFO - transformers.file_utils -   https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt not found in cache or force_download set to True, downloading to C:\Users\athre\AppData\Local\Temp\tmpx8hth4qr
01/31/2020 21:51:41 - INFO - transformers.file_utils -   copying C:\Users\athre\AppData\Local\Temp\tmpx8hth4qr to cache at C:\Users\athre\.cache\torch\transformers\26bc1ad6c0ac742e9b52263248f6d0f00068293b33709fae12320c0e35ccfbbb.542ce4285a40d23a559526243235df47c5f75c197f04f37d1a0c124c32c9a084
01/31/2020 21:51:41 - INFO - transformers.file_utils -   creating metadata file for C:\Users\athre\.cache\torch\transformers\26bc1ad6c0ac742e9b52263248f6d0f00068293b33709fae12320c0e35ccfbbb.542ce4285a40d23a559526243235df47c5f75c197f04f37d1a0c124c32c9a084
01/31/2020 21:51:41 - INFO - transformers.file_utils -   removing temp file C:\Users\athre\AppData\Local\Temp\tmpx8hth4qr
01/31/2020 21:51:41 - INFO - transformers.tokenization_utils -   loading file https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt from cache at C:\Users\athre\.cache\torch\transformers\26bc1ad6c0ac742e9b52263248f6d0f00068293b33709fae12320c0e35ccfbbb.542ce4285a40d23a559526243235df47c5f75c197f04f37d1a0c124c32c9a084
01/31/2020 21:51:41 - INFO - transformers.file_utils -   https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-pytorch_model.bin not found in cache or force_download set to True, downloading to C:\Users\athre\AppData\Local\Temp\tmpy8kf8hkd
01/31/2020 21:54:14 - INFO - transformers.file_utils -   copying C:\Users\athre\AppData\Local\Temp\tmpy8kf8hkd to cache at C:\Users\athre\.cache\torch\transformers\aa1ef1aede4482d0dbcd4d52baad8ae300e60902e88fcb0bebdec09afd232066.36ca03ab34a1a5d5fa7bc3d03d55c4fa650fed07220e2eeebc06ce58d0e9a157
01/31/2020 21:54:14 - INFO - transformers.file_utils -   creating metadata file for C:\Users\athre\.cache\torch\transformers\aa1ef1aede4482d0dbcd4d52baad8ae300e60902e88fcb0bebdec09afd232066.36ca03ab34a1a5d5fa7bc3d03d55c4fa650fed07220e2eeebc06ce58d0e9a157
01/31/2020 21:54:14 - INFO - transformers.file_utils -   removing temp file C:\Users\athre\AppData\Local\Temp\tmpy8kf8hkd
01/31/2020 21:54:14 - INFO - transformers.modeling_utils -   loading weights file https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-pytorch_model.bin from cache at C:\Users\athre\.cache\torch\transformers\aa1ef1aede4482d0dbcd4d52baad8ae300e60902e88fcb0bebdec09afd232066.36ca03ab34a1a5d5fa7bc3d03d55c4fa650fed07220e2eeebc06ce58d0e9a157
01/31/2020 21:54:16 - INFO - transformers.modeling_utils -   Weights from pretrained model not used in BertForMaskedLM: ['cls.seq_relationship.weight', 'cls.seq_relationship.bias']
01/31/2020 21:54:18 - INFO - __main__ -   Training/evaluation parameters Namespace(adam_epsilon=1e-08, block_size=510, cache_dir=None, config_name=None, device=device(type='cuda'), do_eval=True, do_train=True, eval_all_checkpoints=False, eval_data_file='E:\\\\Code\\\\data\\\\wikitext-2-raw\\\\wiki.test.raw', evaluate_during_training=False, fp16=False, fp16_opt_level='O1', gradient_accumulation_steps=1, learning_rate=5e-05, line_by_line=False, local_rank=-1, logging_steps=500, max_grad_norm=1.0, max_steps=-1, mlm=True, mlm_probability=0.15, model_name_or_path='bert-base-uncased', model_type='bert', n_gpu=1, no_cuda=False, num_train_epochs=1.0, output_dir='output', overwrite_cache=False, overwrite_output_dir=False, per_gpu_eval_batch_size=4, per_gpu_train_batch_size=4, save_steps=500, save_total_limit=None, seed=42, server_ip='', server_port='', should_continue=False, tokenizer_name=None, train_data_file='E:\\\\Code\\\\data\\\\wikitext-2-raw\\\\wiki.train.raw', warmup_steps=0, weight_decay=0.0)
01/31/2020 21:54:18 - INFO - __main__ -   Loading features from cached file E:\\Code\\data\\wikitext-2-raw\bert_cached_lm_510_wiki.train.raw
01/31/2020 21:54:18 - INFO - __main__ -   ***** Running training *****
01/31/2020 21:54:18 - INFO - __main__ -     Num examples = 4664
01/31/2020 21:54:18 - INFO - __main__ -     Num Epochs = 1
01/31/2020 21:54:18 - INFO - __main__ -     Instantaneous batch size per GPU = 4
01/31/2020 21:54:18 - INFO - __main__ -     Total train batch size (w. parallel, distributed & accumulation) = 4
01/31/2020 21:54:18 - INFO - __main__ -     Gradient Accumulation steps = 1
01/31/2020 21:54:18 - INFO - __main__ -     Total optimization steps = 1166
Epoch:   0%|                                                                                                                                                                                                                                                                                          | 0/1 [00:00<?, ?it/s]C:/w/1/s/windows/pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:106: block: [0,0,0], thread: [0,0,0] Assertion `t >= 0 && t < n_classes` failed.                                                                                                                                                      | 0/1166 [00:00<?, ?it/s]
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C:/w/1/s/windows/pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:106: block: [0,0,0], thread: [31,0,0] Assertion `t >= 0 && t < n_classes` failed.
Traceback (most recent call last):
  File "run_lm_finetuning.py", line 790, in <module>
    main()
  File "run_lm_finetuning.py", line 740, in main
    global_step, tr_loss = train(args, train_dataset, model, tokenizer)
  File "run_lm_finetuning.py", line 356, in train
    loss.backward()
  File "E:\Code\torch_env\lib\site-packages\torch\tensor.py", line 195, in backward
    torch.autograd.backward(self, gradient, retain_graph, create_graph)
  File "E:\Code\torch_env\lib\site-packages\torch\autograd\__init__.py", line 99, in backward
    allow_unreachable=True)  # allow_unreachable flag
RuntimeError: CUDA error: device-side assert triggered
Epoch:   0%|                                                                                                                                                                                                                                                                                          | 0/1 [00:00<?, ?it/s]
Iteration:   0%|

## Expected behavior

Training should start. 

## Environment

* OS: Windows 10
* Python version:  3.7
* PyTorch version: 1.4 stable
* `transformers` version (or branch): Latest (Jan-31-2020)
* Using GPU ? Yes
* Distributed or parallel setup ? Only 1 GPU
* Any other relevant information:

Hi, did you manage to fix your issue?<|||||>Hi,
Yes, I took the latest build, and it worked without any changes. 