Add rounding error check to _maybe_log_save_evaluate

Author: marcndo

src/transformers/trainer.py

@@ -3077,7 +3077,11 @@ def _maybe_log_save_evaluate(
             # reset tr_loss to zero
             tr_loss -= tr_loss
 
-            logs["loss"] = round(tr_loss_scalar / (self.state.global_step - self._globalstep_last_logged), 4)
+            log_eval = tr_loss_scalar / (self.state.global_step - self._globalstep_last_logged)
+            if log_eval > 1e-4:
+                logs["loss"] = str(round(log_eval))
+            else:
+                logs["loss"] = "{:e}".format(log_eval)
             if grad_norm is not None:
                 logs["grad_norm"] = grad_norm.item() if isinstance(grad_norm, torch.Tensor) else grad_norm
             if learning_rate is not None: