Update tutorial.ipynb
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tutorial.ipynb
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"source": [
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"## Weights & Biases Logging (π NEW)\n",
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"\n",
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"[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",
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"```bash\n",
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"$ pip install wandb\n",
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"```\n",
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"source": [
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"## Local Logging\n",
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"\n",
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"All results are logged by default to `runs/train`, with a new experiment directory created for each new training as `runs/train/
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"outputs": []
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}
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"source": [
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"## Weights & Biases Logging (π NEW)\n",
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"\n",
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+
"[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",
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"```bash\n",
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"$ pip install wandb\n",
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"```\n",
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"source": [
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"## Local Logging\n",
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"\n",
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"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)."
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]
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},
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{
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"outputs": []
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}
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]
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}
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