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2026SEL3-project-Brittle_St.../configs/production_training.yaml

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YAML

# Production Training Configuration
#
# Full-scale training configuration for production runs
# with wandb logging enabled.
# Experiment settings
exp_name: "brittle_star_production"
seed: 42
# Tracking settings - IMPORTANT: Set your own wandb_entity!
track: true
wandb_project_name: "PPO-Modularity"
wandb_entity: null # ⚠️ SET THIS TO YOUR WANDB USERNAME OR TEAM
# Model saving
save_model: true
checkpoint_frequency: 100 # Save checkpoint every 100 iterations
# Environment settings
num_envs: 32 # Increased for production
# Training hyperparameters - Production scale
total_timesteps: 50000000 # 50M timesteps for full training
learning_rate: 0.00025
num_steps: 256 # Longer rollouts
anneal_lr: true
# PPO specific - Fine-tuned
gamma: 0.99
gae_lambda: 0.95
num_minibatches: 8 # More minibatches for stability
update_epochs: 4
norm_adv: true
clip_coef: 0.2
clip_vloss: true
ent_coef: 0.01
vf_coef: 0.5
max_grad_norm: 0.5
target_kl: null
# Hardware
cuda: true
torch_deterministic: true