Added DagshubCallback
# What does this PR do?

Adds a Trainer Integration with [DagsHub](https://dagshub.com/). It extends the MLFlow integration that already currently exists to also track and push artifacts using DVC, into DagsHub repositories. The idea is to allow users to integrate an MLOps stack to their current setups with minimal effort.

Here's a colab notebook with a sample integration: https://colab.research.google.com/drive/1KEeQYp3jD8kmkMMhGKR1R1C6cEjnbJLZ

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts and @NielsRogge
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

Integrations:

- deepspeed: HF Trainer: @stas00, Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger, @stevhliu and @MKhalusova

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
- TensorFlow: @Rocketknight1

 -->

_The documentation is not available anymore as the PR was closed or merged._<|||||>Thank you so much for the lightning review, @sgugger!

I've made the relevant changes. I also added a check within `get_available_reporting_integrations` to ensure available integrations are reported accurately. 

Since `DagsHubCallback` subclasses `MLFlowCallback`, it's still separate. If both integrations are requested, it does not execute twice. This is what the `get_available_reporting_integrations` looks like when moving packages around:

![2023-02-01-095908_1920x606_scrot](https://user-images.githubusercontent.com/52078103/216080956-e57170a6-9a77-49e2-adff-e36e3b885909.png)

Hope this was helpful! :)<|||||>Thanks again for your contribution!<|||||>Thank you for your rapid responses!! Have an awesome rest of day 🙂