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#!/bin/bash
## Experiment for barlow twins
# nohup python train.py --config configs/barlow_twins.c10.yaml --gpu 2 --model resnet18 --epochs 350 --epochs_lin 100 --save_path bt.c10.r18.e350.pth > logs/bt.c10.r18.e350.log &
# nohup python train.py --config configs/barlow_twins.c100.yaml --gpu 3 --model resnet18 --epochs 350 --epochs_lin 100 --save_path bt.c100.r18.e350.pth > logs/bt.c100.r18.e350.log &
# nohup python train.py --config configs/barlow_twins.c10.yaml --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path bt.c10.r50.e350.pth > logs/bt.c10.r50.e350.log &
# nohup python train.py --config configs/barlow_twins.c100.yaml --gpu 5 --model resnet50 --epochs 350 --epochs_lin 100 --save_path bt.c100.r50.e350.pth > logs/bt.c100.r50.e350.log &
# # Experiment for byol
# nohup python train.py --config configs/byol.c10.yaml --gpu 3 --model resnet18 --epochs 350 --epochs_lin 100 --save_path byol.c10.r18.e350.pth > logs/byol.c10.r18.e350.log &
# nohup python train.py --config configs/byol.c100.yaml --gpu 3 --model resnet18 --epochs 350 --epochs_lin 100 --save_path byol.c100.r18.e350.pth > logs/byol.c100.r18.e350.log &
# nohup python train.py --config configs/byol.c10.yaml --gpu 3 --model resnet50 --epochs 350 --epochs_lin 100 --save_path byol.c10.r50.e350.pth > logs/byol.c10.r50.e350.log &
# nohup python train.py --config configs/byol.c100.yaml --gpu 2 --model resnet50 --epochs 350 --epochs_lin 100 --save_path byol.c100.r50.e350.pth > logs/byol.c100.r50.e350.log &
# Experiment for simsiam
# nohup python train.py --config configs/simsiam.c10.yaml --gpu 6 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simsiam.c10.r18.e350.pth > logs/simsiam.c10.r18.e350.log &
# nohup python train.py --config configs/simsiam.c100.yaml --gpu 6 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simsiam.c100.r18.e350.pth > logs/simsiam.c100.r18.e350.log &
# nohup python train.py --config configs/simsiam.c10.yaml --gpu 7 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simsiam.c10.r50.e350.pth > logs/simsiam.c10.r50.e350.log &
# nohup python train.py --config configs/simsiam.c100.yaml --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simsiam.c100.r50.e350.pth > logs/simsiam.c100.r50.e350.log &
# Experiment for simclr
# nohup python train.py --config configs/simclr.c10.yaml --mlp_type linear --gpu 2 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simclr.c10.r18.e350.pth > logs/simclr.c10.r18.e350.log &
# nohup python train.py --config configs/simclr.c100.yaml --mlp_type linear --gpu 2 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simclr.c100.r18.e350.pth > logs/simclr.c100.r18.e350.log &
# nohup python train.py --config configs/simclr.c10.yaml --mlp_type linear --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simclr.c10.r50.e350.pth > logs/simclr.c10.r50.e350.log &
# nohup python train.py --config configs/simclr.c100.yaml --mlp_type linear --gpu 6 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simclr.c100.r50.e350.pth > logs/simclr.c100.r50.e350.log &
## Test Experiment for barlow twins
# python train.py --config configs/barlow_twins.c10.yaml --gpu 2 --model resnet18 --epochs 350 --epochs_lin 100 --save_path bt.c10.r18.e350.pth --test --knn --lreg
# python train.py --config configs/barlow_twins.c100.yaml --gpu 3 --model resnet18 --epochs 350 --epochs_lin 100 --save_path bt.c100.r18.e350.pth --test --knn --lreg
# python train.py --config configs/barlow_twins.c10.yaml --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path bt.c10.r50.e350.pth --test --knn --lreg
# python train.py --config configs/barlow_twins.c100.yaml --gpu 5 --model resnet50 --epochs 350 --epochs_lin 100 --save_path bt.c100.r50.e350.pth --test --knn --lreg
## Experiment for byol
# python train.py --config configs/byol.c10.yaml --gpu 3 --model resnet18 --epochs 350 --epochs_lin 100 --save_path byol.c10.r18.e350.pth --test --knn --lreg
# python train.py --config configs/byol.c100.yaml --gpu 3 --model resnet18 --epochs 350 --epochs_lin 100 --save_path byol.c100.r18.e350.pth --test --knn --lreg
# python train.py --config configs/byol.c10.yaml --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path byol.c10.r50.e350.pth --test --knn --lreg
# python train.py --config configs/byol.c100.yaml --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path byol.c100.r50.e350.pth --test --knn --lreg
## Experiment for simsiam
# python train.py --config configs/simsiam.c10.yaml --gpu 6 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simsiam.c10.r18.e350.pth --test --knn --lreg
# python train.py --config configs/simsiam.c100.yaml --gpu 6 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simsiam.c100.r18.e350.pth --test --knn --lreg
# python train.py --config configs/simsiam.c10.yaml --gpu 7 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simsiam.c10.r50.e350.pth --test --knn --lreg
# python train.py --config configs/simsiam.c100.yaml --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simsiam.c100.r50.e350.pth --test --knn --lreg
## Experiment for simclr
# python train.py --config configs/simclr.c10.yaml --mlp_type linear --gpu 2 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simclr.c10.r18.e350.pth --test --knn --lreg
# python train.py --config configs/simclr.c100.yaml --mlp_type linear --gpu 2 --model resnet18 --epochs 350 --epochs_lin 100 --save_path simclr.c100.r18.e350.pth --test --knn --lreg
# python train.py --config configs/simclr.c10.yaml --mlp_type linear --gpu 4 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simclr.c10.r50.e350.pth --test --knn --lreg
# python train.py --config configs/simclr.c100.yaml --mlp_type linear --gpu 6 --model resnet50 --epochs 350 --epochs_lin 100 --save_path simclr.c100.r50.e350.pth --test --knn --lreg
########################### 800 epochs experiments ##############################
#################################################################################
# Experiment for simsiam
# nohup python train.py --config configs/simsiam.c10.yaml --gpu 6 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path simsiam.c10.r18.e800.pth > logs/simsiam.c10.r18.e800.log &
# nohup python train.py --config configs/simsiam.c100.yaml --gpu 7 --model resnet18 --epochs 800 --epochs_lin 100 --lr 0.08 --linear_lr 0.1 --mlp_type linear --save_path simsiam.c100.r18.e800.pth > logs/simsiam.c100.r18.e800.log &
# nohup python train.py --config configs/simsiam.c10.yaml --gpu 0 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path simsiam.c10.r50.e800.pth > logs/simsiam.c10.r50.e800.log &
# nohup python train.py --config configs/simsiam.c100.yaml --gpu 2 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path simsiam.c100.r50.e800.pth > logs/simsiam.c100.r50.e800.log &
# Experiment for simclr
# nohup python train.py --config configs/simclr.c10.yaml --mlp_type linear --gpu 5 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --save_path simclr.c10.r18.e800.pth > logs/simclr.c10.r18.e800.log &
# nohup python train.py --config configs/simclr.c100.yaml --mlp_type linear --gpu 5 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --save_path simclr.c100.r18.e800.pth > logs/simclr.c100.r18.e800.log &
# nohup python train.py --config configs/simclr.c10.yaml --mlp_type linear --gpu 6 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --save_path simclr.c10.r50.e800.pth > logs/simclr.c10.r50.e800.log &
# nohup python train.py --config configs/simclr.c100.yaml --mlp_type linear --gpu 7 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --save_path simclr.c100.r50.e800.pth > logs/simclr.c100.r50.e800.log &
# experiments for barlow twins
# nohup python train.py --config configs/barlow_twins.c10.yaml --gpu 2 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path bt.c10.r18.e800.pth > logs/bt.c10.r18.e800.log &
# nohup python train.py --config configs/barlow_twins.c100.yaml --gpu 2 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path bt.c100.r18.e800.pth > logs/bt.c100.r18.e800.log &
# nohup python train.py --config configs/barlow_twins.c10.yaml --gpu 3 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path bt.c10.r50.e800.pth > logs/bt.c10.r50.e800.log &
# nohup python train.py --config configs/barlow_twins.c100.yaml --gpu 6 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path bt.c100.r50.e800.pth > logs/bt.c100.r50.e800.log &
# experiments for byol
# nohup python train.py --config configs/byol.c10.yaml --gpu 6 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path byol.c10.r18.e800.pth > logs/byol.c10.r18.e800.log &
# nohup python train.py --config configs/byol.c100.yaml --gpu 7 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path byol.c100.r18.e800.pth > logs/byol.c100.r18.e800.log &
# nohup python train.py --config configs/byol.c10.yaml --gpu 6 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --save_path byol.c10.r50.e800.pth > logs/byol.c10.r50.e800.log &
# nohup python train.py --config configs/byol.c100.yaml --gpu 6 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --lr 0.2 --save_path byol.c100.r50.e800.pth > logs/byol.c100.r50.e800.log &
# experiments for vicreg
# nohup python train.py --config configs/vicreg.c10.yaml --gpu 3 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --opt LARS --save_path vicreg.c10.r18.e800.pth > logs/vicreg.c10.r18.e800.log &
nohup python train.py --config configs/vicreg.c100.yaml --gpu 2 --model resnet18 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --opt LARS --save_path vicreg.c100.r18.e800.pth > logs/vicreg.c100.r18.e800.log &
# nohup python train.py --config configs/vicreg.c10.yaml --gpu 6 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --opt LARS --save_path vicreg.c10.r50.e800.pth > logs/vicreg.c10.r50.e800.log &
nohup python train.py --config configs/vicreg.c100.yaml --gpu 3 --model resnet50 --epochs 800 --epochs_lin 100 --linear_lr 0.1 --mlp_type linear --opt LARS --save_path vicreg.c100.r50.e800.pth > logs/vicreg.c100.r50.e800.log &