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yolov5 model #7879
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@jafar0892 👋 Hello! Thanks for asking about CUDA memory issues. YOLOv5 🚀 can be trained on CPU, single-GPU, or multi-GPU. When training on GPU it is important to keep your batch-size small enough that you do not use all of your GPU memory, otherwise you will see a CUDA Out Of Memory (OOM) Error and your training will crash. You can observe your CUDA memory utilization using either the CUDA Out of Memory SolutionsIf you encounter a CUDA OOM error, the steps you can take to reduce your memory usage are:
AutoBatchYou can use YOLOv5 AutoBatch (NEW) to find the best batch size for your training by passing Good luck 🍀 and let us know if you have any other questions! |
👋 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. Access additional YOLOv5 🚀 resources:
Access additional Ultralytics ⚡ resources:
Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed! Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐! |
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Hi, i would like train a yolov5 modell with large batch size, but unfortunately i am getting error that CUDA is out of memory. is it any solution to train it with large batch size to get better result and not getting the error ?
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