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RL4M / MRM-pytorch

An official implementation of Advancing Radiograph Representation Learning with Masked Record Modeling (ICLR'23)
MIT License
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How to define the percentage of training data used in segmentation tasks #10

Open SZUHvern opened 1 year ago

SZUHvern commented 1 year ago

I would like to know how to define the percentage of training data used in segmentation tasks? I couldn't find the relevant variables in the code.

Thanks again for sharing the code.

DopamineLcy commented 1 year ago

Please use the config https://github.com/RL4M/MRM-pytorch/blob/3730ba49a678eda870284205178bfe25627aaed8/Siim_Segmentation/configs/mrm/upernet_mrm-base_fp16_8x2_512x512_160k_siim_10per.py

SZUHvern commented 1 year ago

Please use the config https://github.com/RL4M/MRM-pytorch/blob/3730ba49a678eda870284205178bfe25627aaed8/Siim_Segmentation/configs/mrm/upernet_mrm-base_fp16_8x2_512x512_160k_siim_10per.py

Sorry, do you mean 'max_iters' here is the number of training dataset? https://github.com/RL4M/MRM-pytorch/blob/3730ba49a678eda870284205178bfe25627aaed8/Siim_Segmentation/configs/_base_/schedules/schedule_5k.py#L7

DopamineLcy commented 1 year ago

You could specify the config in https://github.com/RL4M/MRM-pytorch/blob/main/Siim_Segmentation/ft.sh If you want to use 10% of the training set data, you may set the config configs/mrm/upernet_mrm-base_fp16_8x2_512x512_160k_siim_10per.py. And If you want to use 100% of the training set data, you may set the config configs/mrm/upernet_mrm-base_fp16_8x2_512x512_160k_siim.py, which is set by default.