48 lines
1.1 KiB
YAML
48 lines
1.1 KiB
YAML
# PPO Training Configuration Template
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#
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# This file provides an example configuration for PPO training.
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# Copy this file and modify it for your specific experiments.
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#
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# Usage:
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# python src/train.py --config-path configs/my_config.yaml
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# Or override specific parameters:
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# python src/train.py --learning-rate 0.001 --num-envs 32
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# Experiment settings
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exp_name: "brittle_star_ppo"
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seed: 1
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# Tracking settings
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track: false # Set to true to enable WandB logging
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wandb_project_name: "PPO-Modularity"
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wandb_entity: "SEL3-2026-Groep-4" # Set to your WandB username or team name
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# Model saving
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save_model: true
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checkpoint_frequency: 100 # Save checkpoint every N iterations (0 = no checkpoints)
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# Environment settings
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num_envs: 16
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# Training hyperparameters
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total_timesteps: 10000000
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learning_rate: 0.00025
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num_steps: 128
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anneal_lr: true
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# PPO specific
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gamma: 0.99
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gae_lambda: 0.95
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num_minibatches: 4
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update_epochs: 4
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norm_adv: true
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clip_coef: 0.1
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clip_vloss: true
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ent_coef: 0.01
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vf_coef: 0.5
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max_grad_norm: 0.5
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target_kl: null
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# Hardware
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cuda: true
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torch_deterministic: true
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