Global step reset when restoring checkpoints with trainer.validate

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### Bug description

When restoring checkpoints with trainer.validate, global_step and epoch are overwritten with 0.

It should keep the same global_step and epoch otherwise, it messes with the loggers.

This issue prevents to correctly validate checkpoints of a model as a postprocessing.

### How to reproduce the bug

run a model with
```python

trainer.validate(model, datamodule, cpt_path=ckpt_path

```

and log a metric, the result will be logged at step 0.

### Environment

Current environment

```
#- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow):
#- PyTorch Lightning Version (e.g., 1.5.0): 1.9
#- Lightning App Version (e.g., 0.5.2):
#- PyTorch Version (e.g., 2.0): 1.13
#- Python version (e.g., 3.9): 3.10
#- OS (e.g., Linux): Linux
#- CUDA/cuDNN version: 11.7
#- GPU models and configuration:
#- How you installed Lightning(`conda`, `pip`, source):
#- Running environment of LightningApp (e.g. local, cloud):
```

### More info

_No response_

cc @borda @awaelchli @carmocca @justusschock

Start at the trainer.validate checkpoint-restoration path and reproduce the issue with the provided Python call, logging the resulting step and epoch. Trace where checkpoint state is restored during validation; done means validation preserves the checkpoint's global_step and epoch so logged metrics use the restored step.

Written by the indexing model from the issue text.