fix number of steps of training in readme to 10M

unit3/unit3.ipynb

@@ -3,8 +3,8 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "colab_type": "text",
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/unit3/unit3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -278,7 +278,7 @@
         "Here we see that:\n",
         "- We use the Atari Wrapper that preprocess the input (Frame reduction ,grayscale, stack 4 frames)\n",
         "- We use `CnnPolicy`, since we use Convolutional layers to process the frames\n",
-        "- We train it for 1 million `n_timesteps` \n",
+        "- We train it for 10 million `n_timesteps` \n",
         "- Memory (Experience Replay) size is 100000"
       ]
     },
@@ -712,12 +712,12 @@
   ],
   "metadata": {
     "colab": {
+      "authorship_tag": "ABX9TyPwiHKn+ccCskGi3ZMw9yH2",
       "collapsed_sections": [],
+      "include_colab_link": true,
       "name": "Copie de Unit 3: Deep Q-Learning with Space Invaders.ipynb",
       "private_outputs": true,
-      "provenance": [],
-      "authorship_tag": "ABX9TyPwiHKn+ccCskGi3ZMw9yH2",
-      "include_colab_link": true
+      "provenance": []
     },
     "kernelspec": {
       "display_name": "Python 3",
@@ -729,4 +729,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}