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- train:
- seed: 42
- epochs: 100
- batch_size: 8
- accum_steps: 1
- amp: true
- num_workers: 8
- device: cuda
- dataset:
- name: lung_ultrasound_seg
- root: data/lung_ultrasound
- task_name: pe
- image_size: [256, 256]
- in_channels: 3
- num_classes: 1
- train_split: train
- val_split: val
- test_split: test
- mask_suffix: .png
- image_suffix: .png
- model:
- name: swin_unet
- encoder_name: swinv2_base_patch4_window12_192_22k
- in_channels: 3
- out_channels: 1
- img_size: 256
- drop_rate: 0.0
- drop_path_rate: 0.2
- pretrain:
- enabled: true
- source: imagenet22k
- checkpoint: weights/swinv2_base_patch4_window12_192_22k.pth
- strict: false
- loss:
- task_name: pe
- task_mode: binary
- metrics:
- task_mode: binary
- metrics:
- - name: dice
- - name: iou
- optimizer:
- name: adamw
- lr: 5.0e-5
- weight_decay: 0.05
- betas: [0.9, 0.999]
- scheduler:
- name: cosine
- warmup:
- name: linear
- params:
- start_factor: 0.1
- total_iters: 10
- params:
- T_max: 100
- eta_min: 1.0e-6
- augmentation:
- train:
- random_flip: true
- random_rotate_90: true
- random_resized_crop: false
- random_brightness_contrast: true
- random_gaussian_noise: true
- val:
- center_crop: false
- validation:
- enabled: true
- interval: 1
- metrics: [dice, iou]
- save_best: true
- monitor: dice
- mode: max
- checkpoint:
- dir: outputs/segmentation/train_seg_pe
- save_last: true
- save_best_only: false
- keep_top_k: 3
- logging:
- log_interval: 20
- use_tensorboard: true
- tensorboard_dir: outputs/tensorboard/train_seg_pe
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