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Optimizer selection #113

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lakyfarky opened this issue Nov 1, 2022 · 5 comments
Closed
1 task done

Optimizer selection #113

lakyfarky opened this issue Nov 1, 2022 · 5 comments
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question A HUB question that does not involve a bug Stale

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@lakyfarky
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Hi, is there a possibility to change the optimizer during the training via google colab API?

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@lakyfarky lakyfarky added the question A HUB question that does not involve a bug label Nov 1, 2022
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github-actions bot commented Nov 1, 2022

👋 Hello @lakyfarky, thank you for raising an issue about Ultralytics HUB 🚀! Please visit https://ultralytics.com/hub to learn more, and see our ⭐️ HUB Guidelines to quickly get started uploading datasets and training YOLOv5 models.

If this is a 🐛 Bug Report, please provide screenshots and steps to recreate your problem to help us get started working on a fix.

If this is a ❓ Question, please provide as much information as possible, including dataset, model, environment details etc. so that we might provide the most helpful response.

We try to respond to all issues as promptly as possible. Thank you for your patience!

@glenn-jocher
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@lakyfarky in any AI application training settings are defined prior to training start and are not modified once training starts.

@lakyfarky
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Oh my bad... I thought "before the training". I didn't see optimizer settings on the hub so I changed default optimizer in train.py before train with API in colab.

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github-actions bot commented Dec 2, 2022

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

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@github-actions github-actions bot added the Stale label Dec 2, 2022
@github-actions github-actions bot closed this as completed Dec 7, 2022
@UltralyticsAssistant
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@lakyfarky ah, I see—modifying the train.py file directly before initiating the training with the API is indeed one way to change the optimizer settings when using the Ultralytics HUB. Keep in mind that changing the default settings in this way requires a good understanding of how the changes might affect your model's training process. For future reference, you can usually find the most up-to-date information for setting up and configuring your training environment in our official documentation. If you have further questions or require assistance with specific configurations, the documentation is a good starting point.

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