code: def on_train_end(self, **kwargs):
          "Load the best model."
          if self.every=="improvement" and (self.learn.path/f'{self.learn.model_dir}/{self.name}.pth').is_file():
              self.learn.load(f'{self.name}', purge=Falsef on_train_end(self, **kwargs):
          "Load the best model."
          if self.every=="improvement" and (self.learn.path/f'{self.learn.model_dir}/{self.name}.pth').is_file():
              self.learn.load(f'{self.name}', purge=False)
docs: Load the best model.