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hyperparameters #497

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berad1ar opened this issue Sep 11, 2019 · 2 comments
Closed

hyperparameters #497

berad1ar opened this issue Sep 11, 2019 · 2 comments

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@berad1ar
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berad1ar commented Sep 11, 2019

thanks for your work.I have a question need your help.
my dataset has 2000 images for training, and their objects are small.
I need to change hyperparameters to increase P and mAP. In your opinion, which hyperparameters should be changed and approximately how much should I increase or decrease them?

@glenn-jocher
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glenn-jocher commented Sep 11, 2019

@berad1ar its impossible to say. Start with the default hyps to establish a benchmark, then use hyperparameter evolution to automate the process.

Evolution command for coco_16img dataset for example:

while true
  do 
    python3 train.py --data data/coco_16img.data --img-size 320 --batch-size 16 --accumulate 1 --cache --evolve
done

See hyperparameter evolution: #392

@glenn-jocher
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@berad1ar closing as duplicate of #392, please post any comments there.

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