Update example files so that tr_loss is not affected by args.gradient…
Hi developpers!

Fix training loss value : 

* if gradient_accumulation_steps > 1 then the batch loss value(which is a mean) is scaled by a factor 1/args.gradient_accumulation_steps.

To compare it to evaluation loss it is thus necessary to scale it back by multiplying by args.gradient_accumulation_steps (as done in finetuning script)

Another way to fix this would be to replace the lines with tr_loss/nb_tr_steps by tr_loss/global_step. I thought you might want to consider this alternative
Hi @Mathieu-Prouveur, thanks for that.
Indeed I think using `tr_loss/global_step` would be more easy to read.
Can you update this? <|||||>Sure, I've just done the update <|||||>Great, thanks!