BatchSizeFinder throws KeyError: 'limit_eval_batches'

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### Bug description

Using the latest Lightning-AI v 2.1

I have added vanilla BatchSizeFinder as a callback to my lightningmodule. After it finishes finding the correct batchsize, it breaks while calling function batch_size_scaling. The error message is:
```
File ~/miniconda3/envs/dl/lib/python3.10/site-packages/lightning/pytorch/tuner/batch_size_scaling.py:155, in __scale_batch_restore_params(trainer, params)
153 stage = trainer.state.stage
154 assert stage is not None
--> 155 setattr(trainer, f"limit_{stage.dataloader_prefix}_batches", params["limit_eval_batches"])
157 loop.load_state_dict(deepcopy(params["loop_state_dict"]))
158 loop.restarting = False
```
On debugging the params variable only has the following keys:
```
dict_keys(['loggers', 'callbacks', 'max_steps', 'limit_train_batches', 'limit_val_batches', 'loop_state_dict'])
```
So indeed the limit_eval_batches key does not exist in my lightningmodule. Happy to provide more info if needed.

Thanks

### What version are you seeing the problem on?

v2.1

### How to reproduce the bug

_No response_

### Error messages and logs

```
# Error messages and logs here please
```

### Environment

_No response_

### More info

_No response_

Inspect lightning/pytorch/tuner/batch_size_scaling.py, starting at __scale_batch_restore_params where the traceback accesses limit_eval_batches. Reproduce the BatchSizeFinder callback flow and verify that scaling completes when the parameters contain only the listed train and validation limits, without raising KeyError.

Written by the indexing model from the issue text.