Speech Commands v2 dataset doesn't match AST-v2 config
### Describe the bug

[According](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) to `MIT/ast-finetuned-speech-commands-v2`, the model was trained on the Speech Commands v2 dataset. However, while the model config says the model should have 35 class labels, the dataset itself has 36 class labels. Moreover, the class labels themselves don't match between the model config and the dataset. It is difficult to reproduce the data used to fine tune `MIT/ast-finetuned-speech-commands-v2`.

### Steps to reproduce the bug

```
>>> model = ASTForAudioClassification.from_pretrained("MIT/ast-finetuned-speech-commands-v2")
>>> model.config.id2label
{0: 'backward', 1: 'follow', 2: 'five', 3: 'bed', 4: 'zero', 5: 'on', 6: 'learn', 7: 'two', 8: 'house', 9: 'tree', 10: 'dog', 11: 'stop', 12: 'seven', 13: 'eight', 14: 'down', 15: 'six', 16: 'forward', 17: 'cat', 18: 'right', 19: 'visual', 20: 'four', 21: 'wow', 22: 'no', 23: 'nine', 24: 'off', 25: 'three', 26: 'left', 27: 'marvin', 28: 'yes', 29: 'up', 30: 'sheila', 31: 'happy', 32: 'bird', 33: 'go', 34: 'one'}

>>> dataset = load_dataset("speech_commands", "v0.02", split="test")
>>> torch.unique(torch.Tensor(dataset['label']))
tensor([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
        14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.,
        28., 29., 30., 31., 32., 33., 34., 35.])
```
If you try to explore the [dataset itself](https://huggingface.co/datasets/speech_commands/viewer/v0.02/test), you can see that the id to label does not match what is provided by `model.config.id2label`.


### Expected behavior

The labels should match completely and there should be the same number of label classes between the model config and the dataset itself.

### Environment info

datasets = 2.14.6, transformers =  4.33.3