The documentation for common ai packages is pretty good too. For example, pytorch docs, peft docs, timm docs.

Been reading a book by u/fpham "The Cranky mans guide to lora and qlora" and it's pretty great, writing quality isnt all there but the content is valuable for learning to make good finetunes

One problem with testing one change at a time is that if you can only run a small number of experiments because each one requires many GPU hours to get results, you can also only test a small number of changes. If you can come up with and implement new changes much more easily than you can test them, it would be more efficient to test multiple changes at a time and use some form of Bayesian optimization to find the best combination of changes with as few experiments as possible.