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@glenn-jocher glenn-jocher commented Oct 18, 2021

πŸ› οΈ PR Summary

Made with ❀️ by Ultralytics Actions

🌟 Summary

Enhancements to training callbacks for COCO dataset evaluations and improved results logging.

πŸ“Š Key Changes

  • Added an additional callback condition specifically for the COCO dataset during the training phase.
  • Updated the on_train_end callback to include the results in its parameters.

🎯 Purpose & Impact

  • 🎲 Tailored Callbacks for COCO Dataset: The update enables custom behavior during training when the model is using the COCO dataset, likely to process evaluation results specifically for this common benchmark.
  • πŸ“ˆ Enhanced Results Logging: By including results in the on_train_end callback, more detailed information will be logged at the end of training, providing users with better insights into model performance.
  • Both changes should improve the user's insight and control over the training process, particularly when working with the well-known COCO dataset, potentially leading to more informed decision-making and streamlined workflows.

@glenn-jocher glenn-jocher merged commit 752d97d into master Oct 18, 2021
@glenn-jocher glenn-jocher deleted the update/callback branch October 18, 2021 12:28
BjarneKuehl pushed a commit to fhkiel-mlaip/yolov5 that referenced this pull request Aug 26, 2022
* Add `on_fit_epoch_end` callback

* Add results to train

* Update __init__.py
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