Delete config.yaml with huggingface_hub

config.yaml

@@ -1,105 +0,0 @@
-datamodule:
-  _target_: megascale
-  batch_size: 1
-  num_workers: 8
-  pin_memory: true
-  alphabet:
-    name: esm
-    featurizer: megascale
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: auto
-  min_epochs: 1
-  max_epochs: 200
-  enable_progress_bar: true
-  log_every_n_steps: 10
-  resume_from_checkpoint: null
-  strategy: ddp_sharded_fbo
-  precision: 32
-  gradient_clip_val: 0.0
-  num_sanity_val_steps: 0
-  check_val_every_n_epoch: 1
-  reload_dataloaders_every_n_epochs: 100000
-  replace_sampler_ddp: false
-  max_steps: 200000
-name: megascale/spurs
-model:
-  _target_: spurs
-  encoder:
-    d_model: 128
-    n_enc_layers: 3
-    n_dec_layers: 3
-    tune: true
-    use_input_decoding_order: true
-  adapter_layer_indices:
-  - -3
-  mlp:
-    flat_dim: 128
-    input_dim: 256
-    hidden_dim: 1024
-    num_layers: 2
-    output_dim: 21
-    dropout: 0.1
-  dropout: 0.5
-task:
-  _target_: stability/megascale
-  criterion:
-    _target_: spurs.modules.mseloss.MSELoss
-  optimizer:
-    type: adamw
-    _partial_: true
-    lr: 0.0001
-    betas:
-    - 0.9
-    - 0.98
-    weight_decay: 0.001
-  lr_scheduler:
-    type: plateau
-    lr: ${train.lr}
-    factor: 0.2
-    mode: min
-    monitor: val/rho_avg_mse
-train:
-  seed: 45
-  lr: 0.001
-  monitor: val/rho_avg_spearman
-  mode: max
-  patience: 30
-optimized_metric: val/rho_avg_spearman
-experiment: mpnn
-callbacks:
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  model_checkpoint:
-    _target_: spurs.utils.callbacks.ModelCheckpoint
-    monitor: ${train.monitor}
-    mode: ${train.mode}
-    save_top_k: 1
-    save_last: true
-    verbose: true
-    dirpath: checkpoints
-    filename: step_{global_step}-${train.monitor}_{${train.monitor}:.2f}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: ${train.monitor}
-    mode: ${train.mode}
-    patience: ${train.patience}
-    min_delta: 0
-    check_on_train_epoch_end: false
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-paths:
-  root_dir: ${oc.env:PROJECT_ROOT}
-  data_dir: ${paths.root_dir}/data/
-  log_dir: ${paths.root_dir}/logs/${name}
-  ckpt_dir: ${paths.log_dir}/checkpoints
-  psnetdata: ${paths.root_dir}/PSNet/data