

TITLE
how to finetune mT5 on XGLUE-NTG task

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# 📚 Migration

## Information

<!-- Important information -->

Model I am using (Bert, XLNet ...): google/mt5-base

Language I am using the model on (English, Chinese ...): multi-language

The problem arises when using:
* [ ] the official example scripts: (give details below)
* my own modified scripts: (give details below)

Just a little change in ./examples/pytorch/summarization/run_summarization_no_trainer.py to suit for NTG task and bleu evaluation metric.

The tasks I am working on is:
* an official GLUE/SQUaD task: (give the name): XGLUE-NTG
* [ ] my own task or dataset: (give details below)

## Details

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When training MT5 with multilingual data, do I need to add the "--source_prefix" argument like T5?  If so, " --source_prefix=' Summarize: ' " Is that right?  But when this was added, the results were poor in all language but English.  Is there a problem with my parameter setting?  

![image](https://user-images.githubusercontent.com/30341159/130722965-4911b07b-aee5-4651-8516-be3b8d4a8d0a.png)

Also, the result with the parameter "--source_prefix" above is actually the same as the result without the parameter below:
![image](https://user-images.githubusercontent.com/30341159/130723118-a50ae07e-c541-48dc-ab34-839562b7d309.png)

Should we set different --source_prefix for different languages, and how to set that?

## Environment info
<!-- You can run the command `python transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
 
- `transformers` version:
- Platform:
- Python version: 3.6
- PyTorch version (GPU?): 
- Tensorflow version (GPU?):
- Using GPU in script?:
- Using distributed or parallel set-up in script?:

<!-- IMPORTANT: which version of the former library do you use? -->
* `pytorch-transformers` or `pytorch-pretrained-bert` version (or branch):


## Checklist

-  I have read the migration guide in the readme.
 ([pytorch-transformers](https://github.com/huggingface/transformers#migrating-from-pytorch-transformers-to-transformers);
  [pytorch-pretrained-bert](https://github.com/huggingface/transformers#migrating-from-pytorch-pretrained-bert-to-transformers))
- I checked if a related official extension example runs on my machine.
