Update SPURS_multi checkpoints

spurs_multi/.hydra/config.yaml

@@ -0,0 +1,115 @@
+datamodule:
+  _target_: megascale_multi
+  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_multi
+model:
+  _target_: spurs_multi
+  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: 4
+    output_dim: 21
+    dropout: 0.1
+  multi:
+    flat_dim: 128
+    input_dim: 384
+    hidden_dim: 768
+    num_layers: 4
+    output_dim: 1
+    dropout: 0.1
+  dropout: 0.5
+  agg_type: concate
+  agg_dim: 128
+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: 0.0001
+  lr_scheduler:
+    type: plateau
+    lr: ${train.lr}
+    factor: 0.2
+    mode: min
+    monitor: val/rho_avg_mse
+train:
+  seed: 49
+  lr: 0.001
+  monitor: val/rho_avg_spearman
+  mode: max
+  patience: 10
+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

spurs_multi/checkpoints/best.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:018081b900a77958f67355f0d323dfdc3e18d63f61c8764f0b268e7c1e32080c
+size 2697880281