

TITLE
MLflowCallback to log run_name argument

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# 🚀 Feature request

When using the MLflowCallback (set as default for Trainer), I would like to log the `run_name` argument passed to TrainingArguments as the Run Name on the MLflow dashboard. Currently runs are being logged as nameless.
E.g. see below.
![Screenshot 2020-11-13 at 10 29 32](https://user-images.githubusercontent.com/2844109/99062592-21abd500-259b-11eb-9caf-c43d2bcb31dc.png)


## Motivation

Trainer makes training 🤗  models so easy and MLflow is great for organising experiments/caching artifacts. I would like to make it easier to organise experimental runs and make research easier, particularly for larger teams. This feature would be a very simple patch on the original PR #8016 

example usage
```
training_args = TrainingArguments(
    label_names=['labels_t1', 'labels_t2'],
    output_dir='./runs,          # output directory
    run_name='multitask_clf_<run_name>',
)
trainer = Trainer(
    model=model,        # the instantiated 🤗 Transformers model to be trained
    args=training_args,        # training arguments, defined above
    train_dataset=train_dataset,        # training dataset
)
```

## Your contribution

I can submit a PR
