From b6863385b571998984cc782d4d50ed34b9f631d0 Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Fri, 2 Jul 2021 12:23:09 +0200
Subject: [PATCH] Created using Colaboratory

---
 tutorial.ipynb | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tutorial.ipynb b/tutorial.ipynb
index d13680365..f2e35b3db 100644
--- a/tutorial.ipynb
+++ b/tutorial.ipynb
@@ -1074,7 +1074,7 @@
         "id": "7KN5ghjE6ZWh"
       },
       "source": [
-        "Training losses and performance metrics are also logged to [Tensorboard](https://www.tensorflow.org/tensorboard) and a custom `results.txt` logfile which is plotted as `results.png` (below) after training completes. Here we show YOLOv5s trained on COCO128 to 300 epochs, starting from scratch (blue), and from pretrained `--weights yolov5s.pt` (orange)."
+        "Training results are automatically logged to [Tensorboard](https://www.tensorflow.org/tensorboard) and `runs/train/exp/results.txt`, which is plotted as `results.png` (below) after training completes. You can also plot any `results.txt` file manually:"
       ]
     },
     {
@@ -1084,7 +1084,7 @@
       },
       "source": [
         "from utils.plots import plot_results \n",
-        "plot_results(save_dir='runs/train/exp')  # plot all results*.txt as results.png\n",
+        "plot_results(save_dir='runs/train/exp')  # plot all results*.txt files in 'runs/train/exp'\n",
         "Image(filename='runs/train/exp/results.png', width=800)"
       ],
       "execution_count": null,
@@ -1096,7 +1096,7 @@
         "id": "lfrEegCSW3fK"
       },
       "source": [
-        "<img src=\"https://user-images.githubusercontent.com/26833433/97808309-8182b180-1c66-11eb-8461-bffe1a79511d.png\" width=\"800\">\n"
+        "<p align=\"left\"><img width=\"800\" alt=\"COCO128 Training Results\" src=\"https://github.com/ultralytics/yolov5/releases/download/v1.0/results_COCO128.png\"></p>"
       ]
     },
     {