output_dir=/data/eval_results/fulltune_10step_caps_k-mscoco/
eps=2
step_size=0.5
num_iters=10

eval_batch_size=16

# python3 eval.py \
#     --config ./configs/Retrieval_coco_train_clip.yaml \
#     --model CLIP_ViT-B-16 \
#     --output_dir $output_dir \
#     --epsilon $eps \
#     --step_size $step_size \
#     --num_iters $num_iters \
#     --eval_train_subset \
#     --model_train_name Sup-cap1 \
#     --eval_ckpt_path /data/train_results/0408-PGD2-ep5/flickr30k/CLIP_ViT-B-16/UseCaps=1-_bs64sgd_lr0.0001_ep5_wd0.0001_warmup0.3/MMA-iters2-step1.0-scale0-img-unsup0.0-sup1.0/2024-04-08_09-28-57/checkpoint_last.pth

python3 eval.py \
    --config ./configs/Retrieval_coco_train_clip.yaml \
    --model CLIP_ViT-B-16 \
    --output_dir $output_dir \
    --epsilon $eps \
    --step_size $step_size \
    --num_iters $num_iters \
    --model_train_name Sup-cap5 \
    --eval_batch_size $eval_batch_size \
    --eval_ckpt_path /data/train_results/0408-PGD2-ep5/flickr30k/CLIP_ViT-B-16/_bs128sgd_lr0.0001_ep5_wd0.0001_warmup0.3/MMA-iters2-step1.0-scale0-txtSup1-sr0.1-ri0.1-rs0.1-rd0.1-img-unsup0.0-sup1.0/2024-04-20_15-15-20/checkpoint_last.pth

python3 eval.py \
    --config ./configs/Retrieval_coco_train_clip.yaml \
    --model CLIP_ViT-B-16 \
    --output_dir $output_dir \
    --epsilon $eps \
    --step_size $step_size \
    --num_iters $num_iters \
    --model_train_name Sup-cap5-llama-chatgpt \
    --eval_batch_size $eval_batch_size \
    --eval_ckpt_path /data/train_results/0408-PGD2-ep5/flickr30k/CLIP_ViT-B-16/ADD-ma_chatgpt-_bs128sgd_lr0.0001_ep5_wd0.0001_warmup0.3/MMA-iters2-step1.0-scale0-txtSup1-sr0.1-ri0.1-rs0.1-rd0.1-img-unsup0.0-sup1.0/2024-04-19_10-15-21/checkpoint_last.pth