Trainer: Model: classpath: Model:UNetpp UNetpp: schedulers: StepLR: step_size: 10 gamma: 0.75 last_epoch: -1 verbose: deprecated nb_step: 0 outputs_criterions: Head:Tanh: targets_criterions: CT: criterions_loader: MAE: schedulers: Constant: nb_step: 0 value: 1 is_loss: true group: 0 start: 0 stop: None accumulation: false reduction: mean IMPACTSynth: is_loss: true group: 0 start: 0 stop: None accumulation: false model_name: SAM2.1/Tiny_3_Layers.pt shape: - 0 - 0 in_channels: 3 losses: torch:nn:L1Loss: weights: - 1 - 1 - 1 size_average: None reduce: None reduction: mean schedulers: Constant: nb_step: 0 value: 1 pretrained: false Optimizer: name: AdamW lr: 0.001 betas: - 0.9 - 0.999 eps: 1e-08 weight_decay: 0.001 amsgrad: false maximize: false foreach: None capturable: false differentiable: false fused: None Dataset: groups_src: CT: groups_dest: CT: transforms: Clip: min_value: -1024 max_value: 3071 save_clip_min: true save_clip_max: true mask: None Normalize: lazy: false channels: None min_value: -1 max_value: 1 inverse: true patch_transforms: None is_input: false CBCT: groups_dest: CBCT: transforms: Clip: min_value: min max_value: percentile:99.5 save_clip_min: false save_clip_max: false mask: None Normalize: lazy: false channels: None min_value: -1 max_value: 1 inverse: true patch_transforms: None is_input: true augmentations: DataAugmentation_0: data_augmentations: Flip: f_prob: - 0 - 0.5 - 0.5 prob: 1 nb: 1 Patch: patch_size: - 1 - 320 - 320 overlap: None mask: None pad_value: -1 extend_slice: 2 subset: None shuffle: true filter: None dataset_filenames: - ./Dataset/:a:mha inline_augmentations: true use_cache: true batch_size: 1 validation: None train_name: FT_0 manual_seed: 32 epochs: 100 it_validation: 2500 autocast: false gradient_checkpoints: None gpu_checkpoints: None ema_decay: 0 data_log: - CT/IMAGES/5 - CBCT/IMAGES/5 - Head:Tanh/IMAGES/5 save_checkpoint_mode: ALL EarlyStopping: monitor: [] patience: 30 min_delta: 0.0 mode: min