Update tutorial.ipynb

tutorial.ipynb

@@ -1012,7 +1012,7 @@
       "source": [
         "## Weights & Biases Logging (🚀 NEW)\n",
         "\n",
-        "[Weights & Biases](https://www.wandb.com/) (W&B) is now integrated with YOLOv5 for real-time visualization and cloud logging of training runs. This allows for better run comparison and introspection, as well improved visibility and collaboration for teams. To enable W&B logging install `wandb`, and then train normally (you will be guided setup on first use).\n",
+        "[Weights & Biases](https://www.wandb.com/) (W&B) is now integrated with YOLOv5 for real-time visualization and cloud logging of training runs. This allows for better run comparison and introspection, as well improved visibility and collaboration for teams. To enable W&B logging install `wandb`, and then train normally (you will be guided through setup on first use).\n",
         "```bash\n",
         "$ pip install wandb\n",
         "```\n",
@@ -1030,7 +1030,7 @@
       "source": [
         "## Local Logging\n",
         "\n",
-        "All results are logged by default to `runs/train`, with a new experiment directory created for each new training as `runs/train/exp1`, `runs/train/exp2`, etc. View train and test jpgs to see mosaics, labels, predictions and augmentation effects. Note a **Mosaic Dataloader** is used for training (shown below), a new concept developed by Ultralytics and first featured in [YOLOv4](https://arxiv.org/abs/2004.10934)."
+        "All results are logged by default to `runs/train`, with a new experiment directory created for each new training as `runs/train/exp0`, `runs/train/exp1`, etc. View train and test jpgs to see mosaics, labels, predictions and augmentation effects. Note a **Mosaic Dataloader** is used for training (shown below), a new concept developed by Ultralytics and first featured in [YOLOv4](https://arxiv.org/abs/2004.10934)."
       ]
     },
     {
@@ -1182,4 +1182,4 @@
       "outputs": []
     }
   ]
-}
+}