Mid-epoch resume causes a single unwanted validation step (which is not a sanity check)

Nobody has claimed this yet.

### Bug description

This is an issue created from the discussion in this thread: https://github.com/Lightning-AI/pytorch-lightning/discussions/18110#discussioncomment-10115118 which seems to affect a few people.

When resuming from a checkpoint using mid-epoch checkpointing (in my case I use the ModelCheckpoint callback with `train_time_interval` every 1 hour), two primary cases arise:
- The checkpoint was in mid-epoch and the training resumes without issues.
- The checkpoint was at end of epoch, just before validation, in which case the model loads and performs a single validation step which causes an evaluation with a single batch, and alters metrics at this point.

Certain relevant elements:
- Validation is only performed once every epoch (at the end)
- I use two checkpoint callbacks: one with time interval and one at the end of epoch during training.
- This seems to happen when an error occurs during validation.

Do you know if this issue can be solved or bypassed ? What are the reasons this happens ?

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

v2.2

### How to reproduce the bug

_No response_

### Error messages and logs

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

### Environment

Current environment

```
- PyTorch Lightning Version: 2.2.0
- PyTorch Version: 2.0.0
- Python version: 3.11.8
```

### More info

Don't have a minimal working example, but if need be I can try to make one.

cc @awaelchli

Start with the ModelCheckpoint callback and resume flow using train_time_interval alongside end-of-epoch validation, reproducing the reported v2.2 setup if possible. A complete fix should resume from an end-of-epoch checkpoint without performing an unwanted single-batch validation or altering metrics.

Written by the indexing model from the issue text.