observability-logging-gradient-acc-logged-loss-values-during-training-with-gradient-a-6dac7a5b

THEN Modify the `_maybe_log_save_evaluate` method in the Trainer to accept the gradient accumulation steps parameter and divide the accumulated loss by that value before logging. Specifically, change the log line to `logs["loss"] = round(tr_loss_scalar / ga_steps / (self.state.global_step - self._globalstep_last_logged), 4)`, and pass `self.args.gradient_accumulation_steps` (or the number of batches processed) from the training loop.

In `_maybe_log_save_evaluate`, add `ga_steps` parameter. Replace:
`logs["loss"] = round(tr_loss_scalar / (self.state.global_step - self._globalstep_last_logged), 4)`
with:
`logs["loss"] = round(tr_loss_scalar / ga_steps / (self.state.global_step - self._globalstep_last_logged), 4)`
Then pass `num_batches` or `self.args.gradient_accumulation_steps` when calling `_maybe_log_save_evaluate`.