Moved logic of update of _best_ckpt_metrics before we build state dic…

…t for checkpoint

src/super_gradients/training/sg_trainer/sg_trainer.py

@@ -679,6 +679,15 @@ def _save_checkpoint(
             train_metrics_titles = get_metrics_titles(self.train_metrics)
             all_metrics["train"] = {metric_name: float(train_metrics_dict[metric_name]) for metric_name in train_metrics_titles}
 
+        best_checkpoint = (curr_tracked_metric > self.best_metric and self.greater_metric_to_watch_is_better) or (
+            curr_tracked_metric < self.best_metric and not self.greater_metric_to_watch_is_better
+        )
+
+        if best_checkpoint:
+            # STORE THE CURRENT metric AS BEST
+            self.best_metric = curr_tracked_metric
+            self._best_ckpt_metrics = all_metrics
+
         # BUILD THE state_dict
         state = {
             "net": unwrap_model(self.net).state_dict(),
@@ -713,13 +722,7 @@ def _save_checkpoint(
             self.sg_logger.add_checkpoint(tag=f"ckpt_epoch_{epoch}.pth", state_dict=state, global_step=epoch)
 
         # OVERRIDE THE BEST CHECKPOINT AND best_metric IF metric GOT BETTER THAN THE PREVIOUS BEST
-        if (curr_tracked_metric > self.best_metric and self.greater_metric_to_watch_is_better) or (
-            curr_tracked_metric < self.best_metric and not self.greater_metric_to_watch_is_better
-        ):
-            # STORE THE CURRENT metric AS BEST
-            self.best_metric = curr_tracked_metric
-
-            self._best_ckpt_metrics = all_metrics
+        if best_checkpoint:
             self.sg_logger.add_checkpoint(tag=self.ckpt_best_name, state_dict=state, global_step=epoch)
 
             # RUN PHASE CALLBACKS