Add `on_fit_epoch_end` callback (#5232)

* Add `on_fit_epoch_end` callback

* Add results to train

* Update __init__.py

train.py

                                             plots=True,
                                             callbacks=callbacks,
                                             compute_loss=compute_loss)  # val best model with plots
+                    if is_coco:
+                        callbacks.run('on_fit_epoch_end', list(mloss) + list(results) + lr, epoch, best_fitness, fi)
 
-        callbacks.run('on_train_end', last, best, plots, epoch)
+        callbacks.run('on_train_end', last, best, plots, epoch, results)
         LOGGER.info(f"Results saved to {colorstr('bold', save_dir)}")
 
     torch.cuda.empty_cache()

utils/loggers/__init__.py

             if ((epoch + 1) % self.opt.save_period == 0 and not final_epoch) and self.opt.save_period != -1:
                 self.wandb.log_model(last.parent, self.opt, epoch, fi, best_model=best_fitness == fi)
 
-    def on_train_end(self, last, best, plots, epoch):
+    def on_train_end(self, last, best, plots, epoch, results):
         # Callback runs on training end
         if plots:
             plot_results(file=self.save_dir / 'results.csv')  # save results.png