Adjust default parameters to make even small samples do something

### Bug description

For regression testing, the 15 minute of data test case yielded 150 utterances from LJ, and that caused training to fail with this error:

```
2025-01-23 12:13:40.264 | ERROR | everyvoice.utils:filter_dataset_based_on_target_text_representation_level:96 - Sorry you do not have enough characters data in your current validation filelist to run the model with a batch size of 16.
```

This appears to be due to having just 15 samples in the validation set.

We should adjust the default wizard and training defaults so that if the data has <160 utterances, things are setup so training can proceed anyway.

### How to reproduce the bug

- Create a dataset with 150 samples
- run the wizard
- `everyvoice preprocess config/everyvoice-text-to-spec.yaml`
- `everyvoice train text-to-spec config/everyvoice-text-to-spec.yaml`

Or from the branch for #616 run `go.sh` and inspect the logs in regress-lj-150/

### Error messages and logs

```
2025-01-23 12:13:40.264 | ERROR | everyvoice.utils:filter_dataset_based_on_target_text_representation_level:96 - Sorry you do not have enough characters data in your current validation filelist to run the model with a batch size of 16.
```