Save last epoch only

[DonggyuBan]

Context

What is the purpose of this PR? Is it to

• add a new feature
• fix a bug
• update tests and/or documentation
• other (please add here)

This PR adds the save_last_epoch_only configuration parameter to LoRA fine-tuning recipes, which allows users to save only the final epoch checkpoint instead of all intermediate checkpoints. This feature helps reduce storage usage during training while still preserving the final trained model.

Changelog

What are the changes made in this PR?

Feature Implementation:

• Added save_last_epoch_only configuration parameter to LoRA fine-tuning recipes
• Implemented checkpointing logic to skip intermediate epochs when enabled
• Feature works with both regular and async checkpointing modes

Test Coverage:

• Added test_save_last_epoch_only integration test for regular checkpointing mode
• Added test_save_last_epoch_only_with_async_checkpointing integration test for async checkpointing mode
• Tests verify correct epoch folder creation behavior when feature is enabled/disabled

Test plan

Please make sure to do each of the following if applicable to your PR. If you're unsure about any one of these just ask and we will happily help. We also have a contributing page for some guidance on contributing.

• run pre-commit hooks and linters (make sure you've first installed via pre-commit install)
• add unit tests for any new functionality
• update docstrings for any new or updated methods or classes
• run unit tests via pytest tests
• run recipe tests via pytest tests -m integration_test
• manually run any new or modified recipes with sufficient proof of correctness
• include relevant commands and any other artifacts in this summary (pastes of loss curves, eval results, etc.)

UX

If your function changed a public API, please add a dummy example of what the user experience will look like when calling it.
Here is a docstring example
and a tutorial example

• I did not change any public API
• I have added an example to docs or docstrings

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchtune/2854

• 📄 Preview Python docs built from this PR

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