[logging] Turn off loss logging, while keeping progress bar and logging to third-party application
### Feature request

I would like to add a training argument to the `TrainingArguments` class to turn off the loss logging to stdout while keeping the progress bar and logging to a third-party application like Weights and Biases.

### Motivation

I am working on a project that trains a model with the Trainer class. I need to log the losses at every epoch to Weights and Biases. Here is my code:
```
training_arguments = TrainingArguments(
    output_dir="./logging_dir",
    num_train_epochs=epochs,
    per_device_train_batch_size=batch_size,
    per_device_eval_batch_size=batch_size,
    report_to="wandb",
    logging_strategy="epoch",
)

trainer = Trainer(
    model=model,
    args=training_arguments,
    tokenizer=tokenizer,
    train_dataset=train_dataset,
    eval_dataset=eval_dataset,
)
```
This code is contained in a python file `train.py` and is launched in the terminal via the command `python train.py`.
However, I don’t want to have the loss printed because it breaks my progress bar as you can see in the image below and I need the progress bar to give some feedback on the training time.

<img width="1155" alt="cut_progress_bar" src="https://user-images.githubusercontent.com/48316195/178239258-ad61d97f-d851-4c31-a4da-c653aa17db3b.png">



### Your contribution

I think that I could add a `disable_on_log` argument to `TrainingArguments`. Then in the `on_log` of the `ProgressCallback`, a condition should be added like this:

```
def on_log(self, args, state, control, logs=None, **kwargs):
    if state.is_local_process_zero and self.training_bar is not None and args.disable_on_log:
         _ = logs.pop("total_flos", None)
         self.training_bar.write(str(logs))
```
You should be able to disable logging while keeping progress bars active. Have you tried setting the log level manually?

```python
from transformers.utils.logging import set_verbosity_error

set_verbosity_error()
```<|||||>Yes, I've tried that, but this makes my progress bar disappear and keeps the loss logging. I want to do the opposite, keep my progress bar and remove the loss logging.<|||||>Ah, understood. Then in that case providing the training argument `logging_strategy` should do what you want: `logging_strategy="no"` will not output these logs. Did that solve your problem?
<|||||>Thank you for your answer @LysandreJik. I also tried that, but I want to keep the logs in my third-party application (Weights and Biases here). If I use `logging_strategy="no"`, no more logs are reported to Weights and Biases.<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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