Comments (2)
Dear Mobulan,
On which dataset did you train and did you use the same parameters as specified in the paper? It might also be the case that you had a bad random seed or unfortunate weight initialization, which you could verify by training it again.
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yes, i will run it again today.
python main_tree.py --epochs 100 --log_dir /DATA/linjing/Mobulan/ProtoTree/runs/protoree_cub_11.27 --dataset CUB-200-2011 --lr 0.001 --lr_block 0.001 --lr_net 1e-5 --num_features 256 --depth 9 --net resnet50_inat --freeze_epochs 30 --milestones 60,70,80,90,100
i change the num_wokers to 4 by editing
trainloader = torch.utils.data.DataLoader(trainset,
batch_size=args.batch_size,
shuffle=True,
pin_memory=cuda,
num_workers = 4
)
projectloader = torch.utils.data.DataLoader(projectset,
# batch_size=args.batch_size,
batch_size=int(args.batch_size/4), #make batch size smaller to prevent out of memory errors during projection
shuffle=False,
pin_memory=cuda,
num_workers = 4
)
testloader = torch.utils.data.DataLoader(testset,
batch_size=args.batch_size,
shuffle=False,
pin_memory=cuda,
num_workers = 4
)
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