train_sup_us_template.yaml 1.8 KB

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  1. trainer:
  2. name: supervised_segmentation
  3. train:
  4. seed: 42
  5. epochs: 200
  6. batch_size: 4
  7. val_batch_size: 4
  8. amp: true
  9. num_workers: 4
  10. pin_memory: true
  11. persistent_workers: true
  12. prefetch_factor: 2
  13. device: cuda
  14. grad_clip:
  15. enabled: true
  16. max_norm: 1.0
  17. norm_type: 2.0
  18. auto_batch_size:
  19. enabled: false
  20. target_memory_fraction: 0.75
  21. reference_gpu_gb: 8.0
  22. reference_batch_size: 4
  23. min_batch_size: 1
  24. max_batch_size: 8
  25. metrics:
  26. task_mode: binary
  27. metrics:
  28. - name: dice
  29. - name: iou
  30. validation:
  31. enabled: true
  32. interval: 1
  33. threshold: 0.5
  34. early_stopping: true
  35. early_stopping_patience: 40
  36. early_stopping_min_delta: 0.0
  37. metrics:
  38. task_mode: binary
  39. metrics:
  40. - name: dice
  41. - name: iou
  42. dataset:
  43. name: ultrasound_sup_seg
  44. dataset_name: BUSI
  45. root: data/BUSI
  46. split: train
  47. split_file: null
  48. val_split: val
  49. val_split_file: null
  50. image_size: [256, 256]
  51. in_channels: 3
  52. num_classes: 1
  53. model:
  54. model_name: swinv2_tiny_patch4_window8_256
  55. load_weights: false
  56. decoder_channels: [384, 192, 96, 96]
  57. fwta_wavelet: haar
  58. fwta_level: 1
  59. fwta_sigma_ratio: 0.35
  60. fwta_tau_fourier: 0.15
  61. fwta_gate_temperature: 1.0
  62. use_multiscale_features: true
  63. include_patch_embed: true
  64. optimizer:
  65. name: adamw
  66. lr: 1.0e-4
  67. weight_decay: 0.05
  68. scheduler:
  69. name: cosine
  70. warmup:
  71. name: linear
  72. params:
  73. start_factor: 0.1
  74. total_iters: 10
  75. params:
  76. T_max: 190
  77. eta_min: 1.0e-6
  78. checkpoint:
  79. dir: outputs/supervised_segmentation/train_sup_us_template
  80. save: true
  81. save_last: true
  82. monitor: dice
  83. monitor_mode: max
  84. resume: null
  85. resume_strict: true
  86. resume_training: true
  87. logging:
  88. log_interval: 10
  89. print_training_setup: true
  90. use_swanlab: true
  91. project: X_SSL_Net
  92. experiment_name: supervised_segmentation
  93. swanlab_mode: null