Allow resuming of logging to WANDB with the Trainer
### Feature request

As far as I can tell, it is currently not possible to resume a training run and continue logging to the same run on WANDB when using the Trainer. The reason is that WANDB would [require](https://github.com/wandb/wandb/blob/a32638cb1c6ab775e9ed431d9a9b4b8a30685453/wandb/sdk/wandb_init.py#L1036-L1053) you to set `resume=True` and a run `id` in `wandb.init` (or env `WANDB_RUN_ID`) for this to work.

The Trainer currently does not allow for these options as far as I can see

https://github.com/huggingface/transformers/blob/c9a82be592ca305180a7ab6a36e884bca1d426b8/src/transformers/integrations.py#L726-L737
### 

### Motivation

Make it easy to resume logging to wandb without any code changes, directly through a config or CLI (TrainingArguments).

### Your contribution

I can work on this. I would update TrainingArguments to add two new arguments:

- `wandb_resume`
- `wandb_id` (which backs off to the environment variable `WANDB_RUN_ID`)

which would then be passed to the `wandb` integration Callback as part of `args`

https://github.com/huggingface/transformers/blob/c9a82be592ca305180a7ab6a36e884bca1d426b8/src/transformers/integrations.py#L684

which can then be used in `init`

https://github.com/huggingface/transformers/blob/c9a82be592ca305180a7ab6a36e884bca1d426b8/src/transformers/integrations.py#L725-L737

cc @parambharat who has done a lot of work on the Wandb integration<|||||>Hi @BramVanroy , Thanks for bringing this up. If I understood the issue correctly, you want to resume a wandb run while resuming training. There are two solutions I can think of that don't require changing `TrainingArguments`. Can you try these instead ?


1. Set the env vars `WANDB_RESUME="must"` and `WANDB_RUN_ID=<run_id_you_want_to_resume>` before running your training script.  wandb should read these env vars upon initialization and should resume your training run. [W&B Env Vars Reference](https://docs.wandb.ai/guides/track/environment-variables)
2. Initialize a `run` with `wandb.init(resume=must, id=<run_id_you_want_to_resume>` before initializing the `Trainer`. The trainer will [not initialize a new run](https://github.com/huggingface/transformers/blob/8f1f0bf50f402881c0aa53b18f21736a151adf5b/src/transformers/integrations.py#L733C16-L733C38) if a run already exists. Here's a [colab](https://colab.research.google.com/github/wandb/examples/blob/master/colabs/huggingface/wandb_hf_example.ipynb#scrollTo=RK5HRy1JQ0yX) example of this from the wandb examples repo.<|||||>@parambharat  Oh, I was not aware of the resume environment variable! That would make life indeed much easier in combination with the wandb run ID!

A run's ID is the alphanumeric part of the URL, right? So in this example

> https://wandb.ai/username/projectname/runs/phup4zp1/

it would be `phup4zp1`?

If it's that easy then I am a happy man! <|||||>@BramVanroy , Yes, that's the `run_id` 👍 