run_seq2seq.py meet bug in using huggingface datasets billsum
run code below
```shell
python examples/seq2seq/run_seq2seq_tune.py --model_name_or_path /home2/zhenggo1/checkpoint/pegasus_billsum --do_eval --task summarization_billsum --dataset_name billsum --output_dir /home2/zhenggo1/checkpoint/pegasus_billsum --per_device_train_batch_size=8 --per_device_eval_batch_size=8 --predict_with_generate --tune --tuned_checkpoint="/home2/zhenggo1/checkpoint/pegasus_billsum" --max_source_length 1024 --max_target_length=256 --val_max_target_length=256 --do_calibration
```
bug below,in my opinion,is that the newest dataset process module don't match the billsum?
```python
Traceback (most recent call last):
  File "examples/seq2seq/run_seq2seq_tune.py", line 694, in <module>
    main()
  File "examples/seq2seq/run_seq2seq_tune.py", line 374, in main
    column_names = datasets["validation"].column_names
KeyError: 'validation'
```
using `dataset_name` and print() it show as below
```
DatasetDict({
    train: Dataset({
        features: ['text', 'summary', 'title'],
        num_rows: 18949
    })
    test: Dataset({
        features: ['text', 'summary', 'title'],
        num_rows: 3269
    })
    ca_test: Dataset({
        features: ['text', 'summary', 'title'],
        num_rows: 1237
    })
})
```
I want to try another way to load the local dataset,but the dataset's oldest version is below
```
train.source
train.target
val.source
val.target
test.source
test.target
```
which can be process by the oldest code:
```python
train_dataset = (
        dataset_class(
            tokenizer,
            type_path="train",
            data_dir=data_args.data_dir,
            n_obs=data_args.n_train,
            max_target_length=data_args.max_target_length,
            max_source_length=data_args.max_source_length,
            prefix=model.config.prefix or "",
        )
        if training_args.do_train
        else None
    )
```
but not the newest code:
```python
if data_args.dataset_name is not None:
        # Downloading and loading a dataset from the hub.
        datasets = load_dataset(data_args.dataset_name, data_args.dataset_config_name)
    else:
        data_files = {}
        if data_args.train_file is not None:
            data_files["train"] = data_args.train_file
            extension = data_args.train_file.split(".")[-1]
        if data_args.validation_file is not None:
            data_files["validation"] = data_args.validation_file
            extension = data_args.validation_file.split(".")[-1]
        if data_args.test_file is not None:
            data_files["test"] = data_args.test_file
            extension = data_args.test_file.split(".")[-1]
        datasets = load_dataset(extension, data_files=data_files)
```
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