Tibo De Peuter
f31436bccd
- Add default_ppo.yaml template for training configurations - Create configs/README.md with usage documentation - Enable per-researcher configuration without code changes - Support YAML config files with CLI parameter overrides - Document how to set personal WandB credentials safely This allows researchers to maintain personal configs without committing credentials to the repository. |
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| .. | ||
| .gitkeep | ||
| default_ppo.yaml | ||
| README.md | ||
Configuration Files
This directory contains configuration files for training experiments.
Usage
Configuration files use YAML format and allow you to specify all training parameters in one place.
Quick Start
Copy the default configuration template:
cp configs/default_ppo.yaml configs/my_experiment.yaml
Edit my_experiment.yaml to customize your experiment settings, particularly:
wandb_entity: Your WandB username or team nametrack: Set totrueto enable WandB logging- Training hyperparameters as needed
Run training with your config:
python src/train.py --config configs/my_experiment.yaml
Override Parameters
You can override any parameter from the command line:
python src/train.py --config configs/my_experiment.yaml --learning-rate 0.001 --num-envs 32
Configuration for Different Users
Each researcher should create their own config file with their WandB settings:
# configs/researcher_name.yaml
exp_name: "researcher_name_experiment"
track: true
wandb_project_name: "PPO-Modularity"
wandb_entity: "your-wandb-username" # Change this!
This approach allows everyone to use the codebase without modifying source files.
Available Configurations
default_ppo.yaml- Default PPO training configuration template