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During your training setup, try to set a random seed:
From Ulytralytics:
seed | int | default value is 0 | Sets the random seed for training, ensuring the reproducibility of results across runs with the same configurations.
e.g yolo detect train data=data.yaml model=yolov8n.pt epochs=100 imgsz=640 seed=42
With the seed value set at the same integer value, you can reproduce the same training result with the same code.
I hope this helps you.
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Notebook name
https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/train-rt-detr-on-custom-dataset-with-transformers.ipynb?ref=blog.roboflow.com#scrollTo=Fh5y-l8LJLIR
Bug
I RUN SAME CODE BUT I GET DIFFERENT ACCURACY
Environment
Minimal Reproducible Example
No response
Additional
No response
Are you willing to submit a PR?
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