when the epoch increased to a certain value, the loss increased rapidly

[C-hongfei]

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Question

When training the Yolov5 detection model, there was a strange problem, when the epoch increased to a certain value, the loss increased rapidly. The training commands are as follows, and the rest are the default parameters python train.py --img 640 --batch 128 --epoch 100 --data data/mydata.yaml --cfg models/yolov5s.yaml --weights weights/yolov5s.pt --device '0,1,2,3,4,5,6,7 There are about 12,000 datasets

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[glenn-jocher]

@C-hongfei it sounds like your model might be encountering overfitting. You could try adjusting the learning rate, introducing more data augmentation, or using a larger model.

Also, bear in mind that for larger datasets, you may require longer training times—impacted by factors like model size, image resolution, and dataset diversity.

For any further assistance, please refer to the YOLOv5 documentation at https://docs.ultralytics.com/yolov5/.

Hope this helps!

[C-hongfei]

@C-hongfei it sounds like your model might be encountering overfitting. You could try adjusting the learning rate, introducing more data augmentation, or using a larger model.

Also, bear in mind that for larger datasets, you may require longer training times—impacted by factors like model size, image resolution, and dataset diversity.

For any further assistance, please refer to the YOLOv5 documentation at https://docs.ultralytics.com/yolov5/.

Hope this helps! yes, I reduced the value of lr0 and this problem was solved, thank you

[glenn-jocher]

@C-hongfei glad to hear that reducing the learning rate solved the issue! If you have any more questions, feel free to ask. The YOLO community and the Ultralytics team are here to help. 👍