If train resume_from_checkpoint, can't change trainerarguments?
restart train tihstrainer = transformers.Trainer(
    model=model,
    train_dataset=data["train"],
    args=transformers.TrainingArguments(
        save_steps = 100, # 500 -> 100 when restarting code with resume_from_checkpoint option
        ...
    ),
)

trainer.train(resume_from_checkpoint = '/checkpoint_path')try changing TrainerArguments ‘save_step’ = 500 to 100. but is not apply… Is it impossilbe?
2024-01-26T11:56:12Z
Hello!If I understand you’re question correctly, you are resuming from checkpoint and you want to to start saving checkpoints from there in increments of 100 instead of 500? Tell me if this example is what you want.Example of your directory:->checkpoint1 - 500->checkpoint2 - 1000->checkpoint3 - 1500->checkpoint4 - 2000Example of desired directory:->checkpoint1 - 500->checkpoint2 - 1000->checkpoint3 - 1500->checkpoint4 - 2000->checkpoint5 - 2100->checkpoint6 - 2200->checkpoint7 - 2300 …
2024-01-26T12:08:39Z
I want result->checkpoint1 - 500 (Frist train args)->checkpoint2 - 600 (restart train change args option save_step)->checkpoint3 - 700->checkpoint4 - 800…but still save_setp option is 500->checkpoint1 - 500->checkpoint2 - 1000…
2024-02-05T12:32:57Z
I’m running into this now! Have also posted it on stackoverflow:huggingface transformers - Cannot change training arguments when resuming from a checkpoint - Stack Overflow