Hi @aclifton314,



 aclifton314:


It looks like wandb is charting the loss, learning rate, and epoch for a given run of Trainer.train() . Are there other things that would be useful to have charted for a finetuning run?



It also logs validation loss and all the task dependent metrics defined against your validation dataset.
Then you can decide to log losses/metrics against epoch using it as x-axis in W&B interface (instead of the step) if it makes more sense for your use case.



 aclifton314:


It also looks like wandb is using the logging_steps value in TrainerArguments . Is this right?



That is correct. It can also log evaluation loss/metrics at the end of training if the evaluate loop is called at the end of your script (usually the case when you use one of the “examples” script from the library).



 aclifton314:


Is it preferred to set wandb behavior through the environment variables or in the finetuning script directly?



There is no preferred way. When I write my own fine-tuning script, I like to pass explicitly my variables as the code looks more clear to me but either way should work perfectly fine.