Eval rouge = 100.0 on gem/wiki_lingua_english_en
Hey everyone!

I just tried the example code `transformers/examples/pytorch/summarization/run_summarization_no_trainer.py` but got 100.0 for eval rouge1, rouge2, and rougeL on a GEM dataset. Seems like there is something wrong here. Am I missing something? (Tagging @patil-suraj as it involves summarization)

My script

```
accelerate launch run_summarization_no_trainer.py \
    --model_name_or_path t5-small \
    --dataset_name "gem" \
    --dataset_config "wiki_lingua_english_en" \
    --source_prefix "summarize: " \
    --output_dir ~/tmp/tst-summarization
```

Training log

```
12/14/2021 18:51:04 - INFO - __main__ - ***** Running training *****
12/14/2021 18:51:04 - INFO - __main__ -   Num examples = 99020
12/14/2021 18:51:04 - INFO - __main__ -   Num Epochs = 3
12/14/2021 18:51:04 - INFO - __main__ -   Instantaneous batch size per device = 32
12/14/2021 18:51:04 - INFO - __main__ -   Total train batch size (w. parallel, distributed & accumulation) = 128
12/14/2021 18:51:04 - INFO - __main__ -   Gradient Accumulation steps = 1
12/14/2021 18:51:04 - INFO - __main__ -   Total optimization steps = 2322
  0%|          | 0/2322 [00:00<?, ?it/s]
  0%|          | 1/2322 [00:00<19:52,  1.95it/s]12/14/2021 18:51:05 - INFO - root - Reducer buckets have been rebuilt in this iteration.
12/14/2021 18:51:05 - INFO - root - Reducer buckets have been rebuilt in this iteration.
12/14/2021 18:51:05 - INFO - root - Reducer buckets have been rebuilt in this iteration.
12/14/2021 18:51:05 - INFO - root - Reducer buckets have been rebuilt in this iteration.
__main__ - {'rouge1': 100.0, 'rouge2': 100.0, 'rougeL': 100.0, 'rougeLsum': 100.0}
Configuration saved in ./output_dir/config.json
Model weights saved in ./output_dir/pytorch_model.bin
tokenizer config file saved in ./output_dir/tokenizer_config.json
Special tokens file saved in ./output_dir/special_tokens_map.json
Copy vocab file to ./output_dir/spiece.model
100%|██████████| 2322/2322 [07:28<00:00,  5.18it/s]
```
Hello, thanks for opening an issue! For an additional chance of getting your question answered, could you ask your question on the [forum](https://discuss.huggingface.co) as well, to involve the broader community?

Thanks!<|||||>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.