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34 lines
1.5 KiB
Markdown
34 lines
1.5 KiB
Markdown
---
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title: XGBoost Metric Reporting
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---
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The [xgboost_metrics.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/xgboost/xgboost_metrics.py)
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example demonstrates the integration of ClearML into code that uses XGBoost to train a network on the scikit-learn [iris](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html#sklearn.datasets.load_iris)
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classification dataset. ClearML automatically captures models and scalars logged with XGBoost.
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When the script runs, it creates a ClearML experiment named `xgboost metric auto reporting`, which is associated with
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the `examples` project.
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## Scalars
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ClearML automatically captures scalars logged with XGBoost, which can be visualized in plots in the
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ClearML WebApp, in the experiment's **SCALARS** tab.
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## Models
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ClearML automatically captures the model logged using the `xgboost.save` method, and saves it as an artifact.
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View saved snapshots in the experiment's **ARTIFACTS** tab.
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To view the model details, click the model name in the **ARTIFACTS** page, which will open the model's info tab. Alternatively, download the model.
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## Console
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All console output during the script’s execution appears in the experiment’s **CONSOLE** page.
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