Resuming training from a state that was resumed training from earlier state behaves weird

When resuming training from a training state that was also created from resuming training from a training state behaves weird.

Example: 5 epochs. Save state every epoch.
* Blue line: Normal training from start to finish.
* Red line: Resume from state of epoch 2. `resume = "E:/training/output/test_1-000002-state"`
* yellowline: Resumed from first saved state (epoch 3) of the previously resumed training `resume = "E:/training/output/test_2-000003-state"`

The first resumed training (redline) trains for 3 epochs and finishes at total of 2+3=5 epochs as expected.
The resumed-resumed training (yellowline) trains for 4 epochs resulting in of 2+1+4=7 epochs of training.

This may be as simple as the `"current_step"` being saved with wrong number in train_state.json. But I am not good enough to know if that is the problem.

Used training settings: [training_tomls.zip](https://github.com/user-attachments/files/21706249/training_tomls.zip)

Reproduce the nested-resume case using the training settings in training_tomls.zip: resume from epoch 2, then resume again from the saved epoch-3 state. Inspect train_state.json, especially current_step, and compare the resulting epoch counts with the reported 5, 5, and 7 epochs. Done means nested resume training stops at the expected total rather than adding extra epochs.

Written by the indexing model from the issue text.