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Low training accuracy using pre-trained model
Hello, I am trying to evaluate a pre-trained mobilenetv2 model from torchvision on the ImageNet training dataset using this script. To do so, I modify lines 235-237 to perform validation on the train loader instead of the val loader:
if args.evaluate:
validate(train_loader, model, criterion, args)
return
Everything else is left untouched. The command I use to run is:
python imagenet_train_example.py -a mobilenet_v2 -j 16 -b 1024 -e --pretrained /data/ImageNet
However, the results are lower than expected:
Acc@1 2.926 Acc@5 15.079 Loss 11.795791
Have you solved this problem? I had the same situation.
Did you try to train for one epoch with learning rate = 0 (--lr 0
)?