The pytorch example summarization/run_summarization.py do not work with MBart
Author: nicolalandro
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: git+https://github.com/huggingface/transformers
- Platform:
- Python version: 3.8
- PyTorch version (GPU?): 1.10.0
- Using GPU in script?: yes
- Using GPU in script?:
- Using distributed or parallel set-up in script?:

### Who can help

@sgugger @NielsRogge @Narsil @patrickvonplaten 

Models:

- MBart: facebook/mbart-large-cc25
- encoder-decoder models (For example, BlenderBot, BART, Marian, Pegasus, T5, ByT5): facebook/mbart-large-cc25
- Pytorch: 1.10.0

If the model isn't in the list, ping @LysandreJik who will redirect you to the correct contributor.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)


Examples:

- maintained examples (not research project or legacy): [summarization/run_summarization.py](https://github.com/huggingface/transformers/blob/master/examples/pytorch/summarization/run_summarization.py)


## Information

Model I am using (Bert, XLNet ...): MBart

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [x] an official GLUE/SQUaD task: (give the name): summarization
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. run the  [summarization/run_summarization.py](https://github.com/huggingface/transformers/blob/master/examples/pytorch/summarization/run_summarization.py) with facebook/mbart-large-cc25 as model
2. receive the error:
```
INFO|tokenization_utils_base.py:888] 2021-11-10 17:36:01,873 >> Assigning ['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN'] to the additional_special_tokens key of the tokenizer
[INFO|modeling_utils.py:1342] 2021-11-10 17:36:02,289 >> loading weights file https://huggingface.co/facebook/mbart-large-cc25/resolve/main/pytorch_model.bin from cache at /home/super/.cache/huggingface/transformers/58963b41815ac5618d9910411e018d60a3ae7d4540a66e6cf70adf29a748ca1b.bef0d2e3352d6c4bf1213c6207738ec5ecf458de355c65b2aead6671bc612138
[INFO|modeling_utils.py:1609] 2021-11-10 17:36:07,745 >> All model checkpoint weights were used when initializing MBartForConditionalGeneration.

 

[INFO|modeling_utils.py:1617] 2021-11-10 17:36:07,745 >> All the weights of MBartForConditionalGeneration were initialized from the model checkpoint at facebook/mbart-large-cc25.
If your task is similar to the task the model of the checkpoint was trained on, you can already use MBartForConditionalGeneration for predictions without further training.
Traceback (most recent call last):
  File "src/run_summarization_bart.py", line 645, in <module>
    main()
  File "src/run_summarization_bart.py", line 371, in main
    raise ValueError("Make sure that `config.decoder_start_token_id` is correctly defined")
ValueError: Make sure that `config.decoder_start_token_id` is correctly defined
```

MBart is in the list of model to use with this script, but this multilingual model seams different.

## Expected behavior

Train summarization with pre-trained MBart correctly.


Comments:
Good point! @patil-suraj - let's try to fix this :-)

@sgugger @patrickvonplaten  @patil-suraj  any news about the problem?

I also faced the same problem, @patrickvonplaten, @patil-suraj, any news? :)

Sorry about the super late response.

We will need to support the language codes for mBART as we do in the `run_translation.py` script. Will update the script in a couple of days or feel free to open a PR @nicolalandro @banda-larga  if you want, happy to help with it :) 

Hi @patrickvonplaten @patil-suraj 
Do you have any updates on the mbart compatibility? Appreciate that you are looking into this. Thank you very much. 

Sorry about being late here again, will try to add it this week :) Thanks!

Hi @patil-suraj . Is there an update on this? Thanks!

Hey @Nikoschenk, messed up my schedule again! Sorry about the delay. I will take a look at it this week for sure 

The `run_summarization.py` now supports `mBART` thanks to @banda-larga !
Fixed by #15125

@banda-larga @patil-suraj thank you very much! That‘s great.