| _target_: models.simplefold.simplefold.SimpleFold | |
| ema_decay: 0.999 | |
| clip_grad_norm_val: 2.0 | |
| use_rigid_align: True | |
| smooth_lddt_loss_weight: 1.0 | |
| lddt_cutoff: 15.0 | |
| esm_model: "esm2_3B" | |
| lddt_weight_schedule: False | |
| sample_dir: ${paths.sample_dir} | |
| architecture: | |
| esm_model: ${model.esm_model} | |
| path: | |
| _target_: models.simplefold.flow.LinearPath | |
| loss: | |
| _target_: torch.nn.MSELoss | |
| reduction: 'none' | |
| reduce: False | |
| optimizer: | |
| _target_: torch.optim.AdamW | |
| _partial_: true | |
| lr: 1e-4 | |
| weight_decay: 0.0 | |
| max_steps: ??? | |
| scheduler: | |
| _target_: onescience.utils.simplefold.lr_scheduler.LinearWarmup | |
| _partial_: true | |
| min_lr: 1e-6 | |
| max_lr: ${model.optimizer.lr} | |
| warmup_steps: 10 | |
| processor: | |
| scale: 16.0 | |
| ref_scale: 5.0 | |
| multiplicity: 16 | |