| model: mage_vit_base_patch16 | |
| dataset: "imagenet" | |
| dataset_path: '/home/t2vg-a100-G4-10/project/qyp/datasets/imagenet' | |
| kodak_path: '/home/t2vg-a100-G4-10/project/qyp/datasets/kodak/' | |
| eval_path: '' | |
| batch_size: 64 # Batch size per GPU | |
| test_batch_size: 200 | |
| num_workers: 4 | |
| epochs: 400 | |
| blr: 2.e-4 # 1.5e-4 # base learning rate: absolute_lr = base_lr * total_batch_size / 256 | |
| min_lr: 5.e-6 | |
| accum_iter: 1 # Accumulate gradient iterations (for increasing the effective batch size under memory constraints) | |
| input_size: 256 | |
| weight_decay: 0.05 | |
| warmup_epochs: 20 | |
| mask_ratio_min: 0.5 | |
| mask_ratio_max: 0.9 | |
| mask_ratio_mu: 0.55 | |
| mask_ratio_std: 0.25 | |
| grad_clip: 3.0 | |
| device: "cuda" | |
| distributed: True | |
| seed: 0 | |
| resume: '/home/t2vg-a100-G4-10/project/qyp/lossless/checkpoint-330.pth' # Path to the checkpoint to resume from | |
| start_epoch: 0 | |
| pin_mem: True | |
| save: True | |
| name: "exp" | |
| exp_name: "MIM_vbr_eval_lossless" | |
| root: "/home/t2vg-a100-G4-10/project/qyp/mimc_rope" | |
| output_dir: "/home/t2vg-a100-G4-10/project/qyp/mimc_rope/MIM_vbr_eval_lossless" # path where to save, empty for no saving | |
| log_dir: "/home/t2vg-a100-G4-10/project/qyp/mimc_rope/MIM_vbr_eval_lossless/logs_eval" # path where to tensorboard log | |
| strart_epoch: 0 | |
| cuda: True | |