lmc-code / scripts /cifar100 /train_model.sh
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WANDB_MODE=online CUDA_VISIBLE_DEVICES=0 python src/imagenet/train_model.py \
--input-size 32 --data-set CIFAR10 --patch-size 4 --hidden-size 128 --num-hidden-layers 6 --warmup-epochs 5\
--num-attention-heads 4 --intermediate-size 512 --position-embeddings "learnable" --num-labels 10\
--lr 5e-3 --epochs 50 --batch-size 128 --seed 0 --num-shared-experts 1 --num-routed-experts 0 --topk 0\
--wandb-project "LMC-Attention" --wandb-group "ViT-CIFAR10-FFN" --wandb-entity "fpt-team"\
--save-dir /mnt/d/NCKH/weights/lmc/cifar10 --data-path /mnt/d/NCKH/datasets/cifar10
WANDB_MODE=online CUDA_VISIBLE_DEVICES=0 python src/imagenet/train_model.py \
--input-size 32 --data-set CIFAR10 --patch-size 4 --hidden-size 128 --num-hidden-layers 6 --warmup-epochs 5\
--num-attention-heads 4 --intermediate-size 512 --position-embeddings "learnable" --num-labels 10\
--lr 5e-4 --epochs 50 --batch-size 128 --seed 0 --num-shared-experts 1 --num-routed-experts 0 --topk 0\
--wandb-project "LMC-Attention" --wandb-group "ViT-CIFAR10-FFN" --wandb-entity "fpt-team"\
--save-dir /mnt/d/NCKH/weights/lmc/cifar10 --data-path /mnt/d/NCKH/datasets/cifar10