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!python3 prepare_data.py --data-dir data/raw

!python3 train.py --model-name 'ECA_NFNetL2' --img-size 360 640 --batch-size 32 --scheduler 'cosine' --loss 'Huber'
!python3 train.py --model-name 'ECA_NFNetL2' --img-size 450 800 --batch-size 24 --scheduler 'cosine' --loss 'Huber'
!python3 train.py --model-name 'ECA_NFNetL2' --img-size 576 1024 --batch-size 12 --scheduler 'cosine' --loss 'Huber'
!python3 train.py --model-name 'ECA_NFNetL2' --img-size 720 1280 --batch-size 8 --scheduler 'cosine' --loss 'Huber'
!python3 train.py --model-name 'ECA_NFNetL2' --img-size 900 1600 --batch-size 4 --scheduler 'cosine' --loss 'Huber'

!python3 train.py --model-name 'ResNest200' --img-size 360 640 --batch-size 16 --scheduler 'step' --loss 'MAE'
!python3 train.py --model-name 'ResNest200' --img-size 576 1024 --batch-size 8 --scheduler 'step' --loss 'MAE'

!python3 train.py --model-name 'EfficientNetB7' --img-size 360 640 --batch-size 32 --scheduler 'cosine' --loss 'MAE'
!python3 train.py --model-name 'EfficientNetB7' --img-size 450 800 --batch-size 24 --scheduler 'cosine' --loss 'MAE'

!python3 train.py --model-name 'EfficientNetV2M' --img-size 450 800 --batch-size 24 --scheduler 'exp' --loss 'Huber'
!python3 train.py --model-name 'EfficientNetV2M' --img-size 576 1024 --batch-size 12 --scheduler 'exp' --loss 'Huber'

!python predict_soln.py

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