ReduceLROnPlateu within configure_optimizers behave abnormally

Nobody has claimed this yet.

### Bug description

Got error
```[python]
File "c:\Users\sean\miniconda3\envs\keras+torch+pl\Lib\site-packages\lightning\pytorch\loops\training_epoch_loop.py", line 459, in _update_learning_rates
raise MisconfigurationException(
lightning.fabric.utilities.exceptions.MisconfigurationException: ReduceLROnPlateau conditioned on metric val/loss which is not available. Available metrics are: ['lr-AdamW/pg1', 'lr-AdamW/pg2', 'train/a_pcc', 'train/loss']. Condition can be set using `monitor` key in lr scheduler dict
```

Here is the `configure_optimizers` function:
```[python]
@final
def configure_optimizers(self):

decay, no_decay = [], []
for name, param in self.named_parameters():
if not param.requires_grad:
continue
if "bias" in name or "Norm" in name:
no_decay.append(param)
else:
decay.append(param)

grouped_params = [
{"params": decay, "weight_decay": self.weight_decay, "lr": self.lr * 0.3},
{
"params": no_decay,
"weight_decay": self.weight_decay,
"lr": self.lr * 1.7,
},
]

optimizer = self.optmizer_class(
grouped_params, lr=self.lr, weight_decay=self.weight_decay
)

scheduler = self.lr_scheduler_class(
optimizer, **self.lr_scheduler_args if self.lr_scheduler_args else {}
)
scheduler = {
"scheduler": self.lr_scheduler_class(
optimizer, **self.lr_scheduler_args if self.lr_scheduler_args else {}
),
"monitor": "val/loss",
"interval": "epoch",
"frequency": 1,
# "strict": False,
}
return {"optimizer": optimizer, "lr_scheduler": scheduler}
```

The `lr_scheduler_class` is passed in as
```[yaml]
lr_scheduler_class: torch.optim.lr_scheduler.ReduceLROnPlateau
lr_scheduler_args:
mode: min
factor: 0.5
patience: 10
threshold: 0.0001
threshold_mode: rel
cooldown: 5
min_lr: 1.e-9
eps: 1.e-08
```
(using yaml and CLI, which, I think, is not the case here)

It seems that I got the error at the end of the training epoch, as I just see the progress bar reports train/loss. The validation epoch is not finished, but the scheduler is called.

I am quite sure that val/loss is available after validation epoch is finished, because progress bar can correctly display it.

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

v2.5

### Reproduced in studio

_No response_

### How to reproduce the bug

```python

```

### Error messages and logs

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

### Environment

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### More info

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