configs/train_libero_goal.yaml

defaults:
  - _self_
  - encoder: resnet18_random
  - projector: inverse_dynamics_libero
  - ssl: dynamo_libero
  - env: libero_goal
  - env_vars: env_vars

# Dataset details
subset_fraction: null
train_fraction: 0.95
batch_size: 64  # across all processes
num_workers: 15  # per process
window_size: 5
goal_conditional: null
goal_seq_len: 0
min_future_sep: 0
num_extra_predicted_actions: 0

# Training details
ssl_lr: 1e-4
ssl_weight_decay: 0.0
betas:
  - 0.9
  - 0.999
clip_grad_norm: 0.1
seed: 42
timeout_seconds: 18000

sync_bn: True
use_lr_scheduling: False
warmup_epochs: 5
num_epochs: 40

save_every_epochs: 10

# Eval config
eval_offline: True

# Wandb config
project: dynamo-repro
experiment: train_libero_goal_dynamo

# hydra config
hydra:
  job:
    override_dirname: ${experiment}
    chdir: False
  run:
    dir: ./exp_local/${now:%Y.%m.%d}/${now:%H%M%S}_${experiment}
  sweep:
    dir: ./exp_local/${now:%Y.%m.%d}/sweep_${now:%H%M%S}_${experiment}
    subdir: ${hydra.job.num}