I can not save checkpoints in checkpoints epochs

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### Bug description

When I ran the program to train the model, I couldn't save checkpoints after a certain epoch, but instead of getting an error, the model skipped saving and continued training

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

v2.5

### How to reproduce the bug

```python
default_modelckpt_cfg = {
"target": "pytorch_lightning.callbacks.ModelCheckpoint",
"params": {
"dirpath": ckptdir,
"filename": "{epoch:04}",
"verbose": True,
"save_last": False,
"every_n_epochs": 1,
"save_top_k": -1, # save all checkpoints
}
}
modelckpt_cfg = lightning_config.modelcheckpoint
modelckpt_cfg = OmegaConf.merge(default_modelckpt_cfg, modelckpt_cfg)
default_callbacks_cfg["checkpoint_callback"] = modelckpt_cfg
if "callbacks" in lightning_config:
callbacks_cfg = lightning_config.callbacks
else:
callbacks_cfg = OmegaConf.create()
callbacks_cfg = OmegaConf.merge(default_callbacks_cfg, callbacks_cfg)

trainer_kwargs["callbacks"] = [
instantiate_from_config(callbacks_cfg[k]) for k in callbacks_cfg]
trainer = Trainer(**trainer_config, **trainer_kwargs, num_nodes=opt.num_nodes)
```

### Error messages and logs

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

### Environment

Current environment

```
#- PyTorch Lightning Version (e.g., 2.5.0):
#- PyTorch Version (e.g., 2.2.2):
#- Python version (e.g., 3.10):
#- OS (e.g., Linux):

```

### More info

_No response_

Start by reproducing the reported configuration with PyTorch Lightning's ModelCheckpoint, especially every_n_epochs=1 and save_top_k=-1, using the Trainer construction shown. Inspect how the checkpoint callback handles the first skipped save and compare the configured checkpoint directory and filename pattern. Done means checkpoint saves are attempted for the expected epochs and failures are reported instead of silently allowing training to continue.

Written by the indexing model from the issue text.