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I trained for 300 epochs and the test acc1 is 0.094 and test acc5 is 1.338 which is very poor performance.
How can I train for classification on Imagenet with only one GPU?
Is there any learning rate and batch size for training with only one GPU?
I'd appreciate any help.
Thank you,
The text was updated successfully, but these errors were encountered:
I am using one GPU so I ran the command like following.
python -m torch.distributed.launch --nproc_per_node=1 --master_port 12346 --use_env main.py --model repvit_m0_9 --data-path /media/iipl/DATA/DAT-main/imagenet --dist-eval
I trained for 300 epochs and the test acc1 is 0.094 and test acc5 is 1.338 which is very poor performance.
How can I train for classification on Imagenet with only one GPU?
Is there any learning rate and batch size for training with only one GPU?
I'd appreciate any help.
Thank you,
The text was updated successfully, but these errors were encountered: