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1_train.sh
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1_train.sh
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# cifar
python train.py --dataset cifar10 --method rmcos --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1 --m 0.15 --s 10
python train.py --dataset cifar10 --method rals --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cifar10 --method ls --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cifar10 --method s --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cifar10 --method rs --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cifar10 --method ras --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cifar10 --method hinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cifar10 --method rahinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
# mnist
python train.py --dataset mnist --method rmcos --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1 --m 0.15 --s 10
python train.py --dataset mnist --method rals --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset mnist --method ls --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset mnist --method s --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset mnist --method rs --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset mnist --method ras --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset mnist --method hinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset mnist --method rahinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
# stl10
python train.py --dataset stl10 --method rmcos --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1 --m 0.15 --s 10
python train.py --dataset stl10 --method rals --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset stl10 --method ls --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset stl10 --method s --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset stl10 --method rs --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset stl10 --method ras --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset stl10 --method hinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset stl10 --method rahinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
# cat
python train.py --dataset cat --method rmcos --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1 --m 0.15 --s 10
python train.py --dataset cat --method rals --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cat --method ls --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cat --method s --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cat --method rs --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cat --method ras --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cat --method hinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1
python train.py --dataset cat --method rahinge --n_iter 100000 --save_every 5000 --valid_images 10000 --seed 1