More informative EarlyStopping() message (ultralytics#5303)

utils/torch_utils.py

@@ -299,7 +299,10 @@ def __call__(self, epoch, fitness):
         self.possible_stop = delta >= (self.patience - 1)  # possible stop may occur next epoch
         stop = delta >= self.patience  # stop training if patience exceeded
         if stop:
-            LOGGER.info(f'EarlyStopping patience {self.patience} exceeded, stopping training.')
+            LOGGER.info(f'Stopping training early as no improvement observed in last {self.patience} epochs. '
+                        f'Best results observed at epoch {self.best_epoch}, best model saved as best.pt.\n'
+                        f'To update EarlyStopping(patience={self.patience}) pass a new patience value, '
+                        f'i.e. `python train.py --patience 300` or use `--patience 0` to disable EarlyStopping.')
         return stop