| data: | |
| manifest_train: <path redacted for release> | |
| manifest_val: <path redacted for release> | |
| modality: ecg | |
| weights: temperature:0.5 | |
| model: | |
| channel_embed_dim: 64 | |
| channel_encoding: id | |
| channel_injection: token | |
| channel_token_gate_init: 0.0 | |
| depth: 9 | |
| dropout: 0.0 | |
| embed_dim: 512 | |
| ffn: swiglu | |
| fold_gamma: 0.1 | |
| fold_synthesis: 3 | |
| importance_ratio: 0.6 | |
| lead_group_masking: true | |
| mask_ratio: 0.7 | |
| masking_strategy: frequency_guided | |
| max_level: 3 | |
| mlp_ratio: 4.0 | |
| norm: rmsnorm | |
| num_heads: 8 | |
| qk_norm: true | |
| scale_fold: dynamic | |
| use_separate_channel: true | |
| wave_init_mode: pad | |
| wave_kernel_size: 16 | |
| wavelet_names: | |
| - db4 | |
| - db6 | |
| - sym4 | |
| - sym8 | |
| - coif2 | |
| objective: | |
| fold_kl: 0.001 | |
| mask_before_frontend: true | |
| normalize_spec_target: true | |
| raw_beta: 0.5 | |
| raw_weight: 0.5 | |
| spec_weight: 0.5 | |
| output_dir: <path redacted for release> | |
| run_name: pretrain_ecg_c1_moe | |
| seed: 42 | |
| train: | |
| batch_size_by_route: | |
| L12_500: 96 | |
| L1_250: 1024 | |
| clip_grad_norm: 1.0 | |
| epochs: 60 | |
| grad_accumulation_steps: 1 | |
| lr: 0.0003 | |
| min_lr_ratio: 0.01 | |
| precision: bf16 | |
| steps_per_epoch: 1000 | |
| val_mask_seed: 1234 | |
| val_max_batches_per_dataset: 100 | |
| warmup_epochs: 2 | |
| weight_decay: 0.05 | |
| trainer: ecg_c1_moe | |