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cae_large_finetune.sh
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cae_large_finetune.sh
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tmp_my_name=${0##*/}
my_name=${tmp_my_name%.*}
OUTPUT_DIR='./output/'$my_name
DATA_PATH=/path/to/imagenet1k/
TOKENIZER_PATH=./tokenizer-weights
ADDRESS=ADDR_FOR_THIS_MACHINE
NNODES=4
RANK=RANK_FOR_THIS_MACHINE
MODEL_PATH=/path/to/pretrained/model
OMP_NUM_THREADS=1 python -m torch.distributed.launch \
--nproc_per_node=8 \
--nnodes=$NNODES \
--node_rank=$RANK \
--master_addr=$ADDRESS \
--master_port=8899 \
tools/run_class_finetuning.py \
--model cae_large_patch16_224 --data_path $DATA_PATH \
--finetune $MODEL_PATH \
--nb_classes 1000 --data_set IMNET \
--output_dir $OUTPUT_DIR \
--batch_size 64 \
--lr 2e-3 --update_freq 2 \
--warmup_epochs 5 --epochs 50 --layer_decay 0.75 --drop_path 0.2 \
--weight_decay 0.05 --mixup 0.8 --cutmix 1.0 \
--sin_pos_emb \
--dist_eval \
--no_auto_resume \
--exp_name $my_name \
--imagenet_default_mean_and_std