Comments (2)
👋 Hello @majcheradam, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:
- Quickstart. Start training and deploying YOLO models with HUB in seconds.
- Datasets: Preparing and Uploading. Learn how to prepare and upload your datasets to HUB in YOLO format.
- Projects: Creating and Managing. Group your models into projects for improved organization.
- Models: Training and Exporting. Train YOLOv5 and YOLOv8 models on your custom datasets and export them to various formats for deployment.
- Integrations. Explore different integration options for your trained models, such as TensorFlow, ONNX, OpenVINO, CoreML, and PaddlePaddle.
- Ultralytics HUB App. Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
- Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.
If this is a 🐛 Bug Report, please provide screenshots and steps to reproduce 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!
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Hello @majcheradam!
Yes, it is possible to customize the number of epochs by opening the Advanced Model Configuration tile on the second step of the Train Model dialog (see screenshot below).
Regarding training a model for more than 100 epochs, it really depends on your dataset and the complexity of the model. In some cases, training for more epochs can improve model accuracy, especially with a large and varied dataset. However, beyond a certain point, you might encounter diminishing returns or even overfitting. Monitoring your model's performance on a validation set can help you determine the optimal number of epochs.
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