Open xuuuluuu opened 3 years ago
python train.py \
--net_type resnet \
--dataset imagenet \
--batch_size 256 \
--lr 0.1 \
--depth 50 \
--epochs 300 \
--expname ResNet50 \
-j 40 \
--beta 1.0 \
--cutmix_prob 1.0 \
--no-verbose
I'm not 100% sure, but the PyramidNet (110 or 200) training on cifar also be same as in the README.
python train.py \
--net_type pyramidnet \
--dataset cifar100 \
--depth 200 \
--alpha 240 \
--batch_size 64 \
--lr 0.25 \
--expname PyraNet200 \
--epochs 300 \
--beta 1.0 \
--cutmix_prob 0.5 \
--no-verbose
cifar
and ImageNet
datasets is different. See https://github.com/clovaai/CutMix-PyTorch/blob/master/resnet.py#L87-L121Thanks a lot for the reply.
For the 3rd question, do you still have the code for fine-tuning the pre-trained models on the downstream datasets? I cannot find it in the current repo.
This repo does not have downstream training/testing code. The instructions to train/test on downstream tasks are described in our paper.
Hi, have you experienced any performance gap between using one and two GPUS?
Hi, thanks for this great repo!
I am new to this area and I have a few questions regarding the experiments:
Hope you can help me with this.
Thanks a lot!