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---
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description: Learn how to set up and customize MLflow logging for Ultralytics YOLO. Log metrics, parameters, and model artifacts easily.
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keywords: MLflow, Ultralytics YOLO, logging, metrics, parameters, model artifacts, setup, tracking, customization
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---
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# Reference for `ultralytics/utils/callbacks/mlflow.py`
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!!! note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/mlflow.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/mlflow.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/utils/callbacks/mlflow.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.utils.callbacks.mlflow.sanitize_dict
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<br><br><hr><br>
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## ::: ultralytics.utils.callbacks.mlflow.on_pretrain_routine_end
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<br><br><hr><br>
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## ::: ultralytics.utils.callbacks.mlflow.on_train_epoch_end
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<br><br><hr><br>
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## ::: ultralytics.utils.callbacks.mlflow.on_fit_epoch_end
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<br><br><hr><br>
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## ::: ultralytics.utils.callbacks.mlflow.on_train_end
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<br><br>
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