New `--log_level` feature introduces failures using 'passive' mode
## Environment info
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- `transformers` version: `nightly`
- Platform: PyTorch
- Python version: 3.6
- PyTorch version (GPU?): TPU
- Tensorflow version (GPU?): n/a
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: yes

### Who can help
@stas00 @sgugger 

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Models:

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- gpt2: @patrickvonplaten, @LysandreJik
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Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
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- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
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## Information

Model I am using (Bert, XLNet ...): XLNet

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

The tasks I am working on is:
* [x] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

This was captured by Cloud TPU tests (XLNet/MNLI/GLUE), but I think this behavior is model/dataset agnostic. Essentially, it seems that:
1. The `training_args`'s `__post_init__` method _should_ [convert the `log_level` to `-1`](https://github.com/huggingface/transformers/blob/dad414d5f9c20627ee6c16f62e8a2056916bf35b/src/transformers/training_args.py#L606) if it's set to 'passive' (which it is by default).
2. However in the end-to-end `run_glue.py` example, using [`parse_args_into_dataclasses()`](https://github.com/huggingface/transformers/blob/dad414d5f9c20627ee6c16f62e8a2056916bf35b/examples/pytorch/text-classification/run_glue.py#L199) seems to not call `__post_init__`, as our tests are failing with:
```
Traceback (most recent call last):
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 329, in _mp_start_fn
    _start_fn(index, pf_cfg, fn, args)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 323, in _start_fn
    fn(gindex, *args)
  File "/transformers/examples/pytorch/text-classification/run_glue.py", line 554, in _mp_fn
    main()
  File "/transformers/examples/pytorch/text-classification/run_glue.py", line 468, in main
    data_collator=data_collator,
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/trainer.py", line 295, in __init__
    logging.set_verbosity(log_level)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/transformers/utils/logging.py", line 161, in set_verbosity
    _get_library_root_logger().setLevel(verbosity)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/logging/__init__.py", line 1284, in setLevel
    self.level = _checkLevel(level)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/logging/__init__.py", line 195, in _checkLevel
    raise ValueError("Unknown level: %r" % level)
ValueError: Unknown level: 'passive'
```

## To reproduce

Steps to reproduce the behavior:

1. The command we're using is:
```
    git clone https://github.com/huggingface/transformers.git
    cd transformers && pip install .
    git log -1
    pip install datasets
    python examples/pytorch/xla_spawn.py \
      --num_cores 8 \
      examples/pytorch/text-classification/run_glue.py \
      --logging_dir=./tensorboard-metrics \
      --task_name MNLI \
      --cache_dir ./cache_dir \
      --do_train \
      --do_eval \
      --num_train_epochs 3 \
      --max_seq_length 128 \
      --learning_rate 3e-5 \
      --output_dir MNLI \
      --overwrite_output_dir \
      --logging_steps 30 \
      --save_steps 3000 \
      --overwrite_cache \
      --tpu_metrics_debug \
      --model_name_or_path xlnet-large-cased \
      --per_device_train_batch_size 32 \
      --per_device_eval_batch_size 16
```


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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

Thank you for the report, it will be fixed shortly via https://github.com/huggingface/transformers/pull/12309

I'm just working on a test - need another 10min or so<|||||>Thank you for fixing this so quickly!