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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_100.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_150.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_200.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_250.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_350.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_50.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/cifar10_sam_0.01wide_resnet_sn_3.0_mod_1_train_loss.json

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.01/sam_001_wrn_seed1_cifar10.txt

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+CUDA_VISIBLE_DEVICES=0 nohup python train_RC.py \
+    --seed 1 \
+    --dataset cifar10 \
+    --model wide_resnet \
+    --opt sam \
+    --rho 0.01 \
+    -sn -mod \
+    --coeff 3.0 \
+    --save-interval 50 \
+    --save-path cifar10 \
+    > train_0.01_0.log 2>&1 &

00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/cifar10_sam_0.02wide_resnet_sn_3.0_mod_1_100.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/cifar10_sam_0.02wide_resnet_sn_3.0_mod_1_150.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/cifar10_sam_0.02wide_resnet_sn_3.0_mod_1_200.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/cifar10_sam_0.02wide_resnet_sn_3.0_mod_1_250.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/cifar10_sam_0.02wide_resnet_sn_3.0_mod_1_50.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/cifar10_sam_0.02wide_resnet_sn_3.0_mod_1_train_loss.json

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.02/sam_002_wrn_seed1_cifar10.txt

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+CUDA_VISIBLE_DEVICES=1 nohup python train_RC.py \
+    --seed 1 \
+    --dataset cifar10 \
+    --model wide_resnet \
+    --opt sam \
+    --rho 0.02 \
+    -sn -mod \
+    --coeff 3.0 \
+    --save-interval 50 \
+    --save-path cifar10 \
+    > train_0.02_0.log 2>&1 &

00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_100.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_150.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_200.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_250.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_300.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_50.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/cifar10_sam_0.05wide_resnet_sn_3.0_mod_1_train_loss.json

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.05/sam_005_wrn_seed1_cifar10.txt

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+CUDA_VISIBLE_DEVICES=0 nohup python train_RC.py \
+    --seed 1 \
+    --dataset cifar10 \
+    --model wide_resnet \
+    --opt sam \
+    --rho 0.05 \
+    -sn -mod \
+    --coeff 3.0 \
+    --save-interval 50 \
+    --save-path cifar10 \
+    > train_0.05_0.log 2>&1 &

00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/cifar10_sam_0.1wide_resnet_sn_3.0_mod_1_100.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/cifar10_sam_0.1wide_resnet_sn_3.0_mod_1_150.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/cifar10_sam_0.1wide_resnet_sn_3.0_mod_1_250.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/cifar10_sam_0.1wide_resnet_sn_3.0_mod_1_300.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/cifar10_sam_0.1wide_resnet_sn_3.0_mod_1_50.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/cifar10_sam_0.1wide_resnet_sn_3.0_mod_1_train_loss.json

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.10/sam_01_wrn_seed1_cifar10.txt

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+CUDA_VISIBLE_DEVICES=0 nohup python train_RC.py \
+    --seed 1 \
+    --dataset cifar10 \
+    --model wide_resnet \
+    --opt sam \
+    --rho 0.1 \
+    -sn -mod \
+    --coeff 3.0 \
+    --save-interval 50 \
+    --save-path cifar10 \
+    > train_0.1_0.log 2>&1 &

00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/cifar10_sam_0.2wide_resnet_sn_3.0_mod_1_100.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/cifar10_sam_0.2wide_resnet_sn_3.0_mod_1_150.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/cifar10_sam_0.2wide_resnet_sn_3.0_mod_1_250.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/cifar10_sam_0.2wide_resnet_sn_3.0_mod_1_300.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/cifar10_sam_0.2wide_resnet_sn_3.0_mod_1_50.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/cifar10_sam_0.2wide_resnet_sn_3.0_mod_1_train_loss.json

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.20/sam_02_wrn_seed1_cifar10.txt

@@ -0,0 +1,11 @@
+CUDA_VISIBLE_DEVICES=1 nohup python train_RC.py \
+    --seed 1 \
+    --dataset cifar10 \
+    --model wide_resnet \
+    --opt sam \
+    --rho 0.2 \
+    -sn -mod \
+    --coeff 3.0 \
+    --save-interval 50 \
+    --save-path cifar10 \
+    > train_0.2_0.log 2>&1 &

00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.50/cifar10_sam_0.5wide_resnet_sn_3.0_mod_1_100.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.50/cifar10_sam_0.5wide_resnet_sn_3.0_mod_1_150.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.50/cifar10_sam_0.5wide_resnet_sn_3.0_mod_1_200.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.50/cifar10_sam_0.5wide_resnet_sn_3.0_mod_1_250.model

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00_JH_Final_archive/rc_models_wrn_cifar10_seed1/sam_0.50/cifar10_sam_0.5wide_resnet_sn_3.0_mod_1_300.model

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