Trainer not logging into Tensorboard
Author: thomas-happify
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.5.0.dev0
- Platform: Ubuntu 18.04.5 LTS (x86_64)
- Python version: 3.7.0
- PyTorch version (GPU?): 1.7.1+cu101
- Tensorflow version (GPU?):
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Yes

### Who can help
@sgugger
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

Model hub:

- for issues with a model report at https://discuss.huggingface.co/ and tag the model's creator.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->

## Information

Model I am using (Bert, XLNet ...): EncoderDecoderModel

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

This is the tensorboard logs 
https://tensorboard.dev/experiment/caY7XIGGTbK2Zfr2DTeoJA/#scalars
1. go to the `Text` tab [here](https://tensorboard.dev/experiment/caY7XIGGTbK2Zfr2DTeoJA/#text), you can see that `"logging_first_step": true, "logging_steps": 2`
2. `epoch` graph is showing 75 total steps, but no scalars were logged except for the first_step
<img width="413" alt="Screen Shot 2021-04-02 at 10 14 49 AM" src="https://user-images.githubusercontent.com/66082334/113423326-48c54080-939c-11eb-9c61-b8fde0d62d12.png">

```
[INFO|trainer.py:402] 2021-04-02 10:05:50,085 >> Using amp fp16 backend
[INFO|trainer.py:1013] 2021-04-02 10:05:50,181 >> ***** Running training *****
[INFO|trainer.py:1014] 2021-04-02 10:05:50,182 >>   Num examples = 100
[INFO|trainer.py:1015] 2021-04-02 10:05:50,182 >>   Num Epochs = 3
[INFO|trainer.py:1016] 2021-04-02 10:05:50,182 >>   Instantaneous batch size per device = 1
[INFO|trainer.py:1017] 2021-04-02 10:05:50,182 >>   Total train batch size (w. parallel, distributed & accumulation) = 4
[INFO|trainer.py:1018] 2021-04-02 10:05:50,182 >>   Gradient Accumulation steps = 1
[INFO|trainer.py:1019] 2021-04-02 10:05:50,182 >>   Total optimization steps = 75
{'loss': 13.7546, 'learning_rate': 2.5000000000000002e-08, 'epoch': 0.04}
100%|█████████████████████████████████████████████████████████████████████████████████| 75/75 [01:03<00:00,  1.28it/s][INFO|trainer.py:1196] 2021-04-02 10:06:53,931 >>

Training completed. Do not forget to share your model on huggingface.co/models =)


{'train_runtime': 63.7497, 'train_samples_per_second': 1.176, 'epoch': 3.0}
100%|█████████████████████████████████████████████████████████████████████████████████| 75/75 [01:03<00:00,  1.18it/s]
[INFO|trainer.py:1648] 2021-04-02 10:06:54,265 >> Saving model checkpoint to ./pretrain_decoder/
```
<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior
It should log training loss very other `logging_steps` right? or did I misunderstood?
<!-- A clear and concise description of what you would expect to happen. -->


Comments:
Could you check if the bug persists with a [source install](https://huggingface.co/transformers/installation.html#installing-from-source)? I'm trying to reproduce but I have proper logs on my side.

@sgugger It only happened when I use `torch.distributed.launch`.
What might cause this problem?

I'm still not able to reproduce: I see logs for each logging step in a distributed training as well.

@sgugger  Ok.. probably only happens on my end.
Thanks