| setting: | |
| seed: 20000812 | |
| os_environ: | |
| WANDB_API_KEY: ~ | |
| WANDB_RUN_ID: ~ | |
| CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7 | |
| MASTER_ADDR: localhost | |
| MASTER_PORT: 12315 | |
| WORLD_SIZE: 1 | |
| NODE_RANK: 0 | |
| wandb_config: | |
| project: EC | |
| name: esm2_t33_650M_UR50D | |
| model: | |
| # Which model to use | |
| model_py_path: saprot/saprot_annotation_model | |
| kwargs: | |
| # Arguments to initialize the specific class | |
| config_path: weight/PLMs/esm2_t33_650M_UR50D | |
| load_pretrained: True | |
| anno_type: EC | |
| # Arguments to initialize the basic class AbstractModel | |
| lr_scheduler_kwargs: | |
| last_epoch: -1 | |
| init_lr: 2.0e-5 | |
| # Weather to use this scheduler or not | |
| on_use: false | |
| optimizer_kwargs: | |
| betas: [0.9, 0.98] | |
| weight_decay: 0.01 | |
| save_path: weight/EC/esm2_t33_650M_UR50D.pt | |
| dataset: | |
| # Arguments to initialize the basic class LMDBDataset | |
| dataset_py_path: saprot/saprot_annotation_dataset | |
| dataloader_kwargs: | |
| batch_size: 8 | |
| num_workers: 8 | |
| train_lmdb: scripts/LMDB/EC/AF2/normal/train | |
| valid_lmdb: scripts/LMDB/EC/AF2/normal/valid | |
| test_lmdb: scripts/LMDB/EC/AF2/normal/test | |
| # Arguments to initialize the specific class | |
| kwargs: | |
| tokenizer: weight/PLMs/esm2_t33_650M_UR50D | |
| # Arguments to initialize Pytorch Lightning Trainer | |
| Trainer: | |
| max_epochs: 100 | |
| log_every_n_steps: 1 | |
| strategy: | |
| find_unused_parameters: True | |
| logger: True | |
| enable_checkpointing: false | |
| val_check_interval: 0.1 | |
| accelerator: gpu | |
| devices: 8 | |
| num_nodes: 1 | |
| accumulate_grad_batches: 1 | |
| precision: 16 | |
| num_sanity_val_steps: 0 |