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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.
iOS. Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
Android. Explore TFLite acceleration on mobile devices.
Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.
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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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Hi, I have not found the possibility of setting a custom number of epochs,
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