Beam search on BART seq2seq
## 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: 4.5.0.dev0
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: ?

### Who can help

@patrickvonplaten, @patil-suraj

## Information

Model I am using (Bert, XLNet ...): BART seq2seq

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:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1.  I'm attempting to use beam search and have the model output the 10 best possible predictions for each test item.
2. I found the parameter `num_beams`, which I am using though it does not appear to work by itself. No error occurs, but only 1 output per test item is produced.
3. I thought I should use the parameter `num_return_sequences` as well, but it does not appear to be a possible argument for this model and I have not been able to find anything comparable. 

Here is my command:
```
python transformers/examples/seq2seq/run_translation.py \
    --model_name_or_path facebook/bart-base \
    --do_train \
    --do_predict \
    --source_lang en \
    --target_lang lf \
    --source_prefix "translate English to Logical Forms: " \
    --train_file folds/0_train.json \
    --test_file folds/0_val.json \
    --num_train_epochs=5 \
    --num_beams=10 \
    --output_dir ./test_results_beam \
    --per_device_train_batch_size=4 \
    --per_device_eval_batch_size=4 \
    --overwrite_output_dir \
    --predict_with_generate
```

## Expected behavior

Outputting the 10 best predictions per test item. 

Hi @ashleylew 

The `run_translation.py` uses the `Seq2SeqTrainer` which does not pass the `num_return_sequences` argument to `generate`, this is because if multiple sequences are returned then its not clear what sequence should be used to compute the metrics. 

you could generate test set predictions by using the `generate` method and passing the `num_return_sequences` argument. But if you want to do this using `Seq2SeqTrainer` then you would need to modify it.<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.