Training
Configure experiments, launch reproducible runs, and monitor progress in real time. Every run is versioned and traceable.
Experiment configuration
Create experiments and define your RL setup before you run. All configuration is explicit and versioned.
- Environment: symbols, timeframe, and market data from your broker
- Policy: algorithm and hyperparameters (e.g. PPO)
- Actions, observations, and reward: full control over the RL loop
- Validation: schema and server-side checks before execution
Reproducible runs
Launch training runs tied to an experiment. Config and execution are versioned so you can reproduce results every time.
Each run is linked to an experiment and records the configuration at launch time. Resume from checkpoints when you need to extend training or recover from interruptions.
Real-time monitoring
Watch training progress, key metrics, and failures live from the dashboard. No polling—updates stream as they happen.
Progress and metrics are pushed over a real-time connection so you see updates as soon as they’re available. Track episodes, rewards, and failures without refreshing.
Traceable artifacts
Every run logs metrics and artifacts. Compare runs, manage models, and keep experiments auditable.
Models and metrics are stored per run. Use them to compare runs, pick the best model for promotion to live, and keep a clear audit trail of what was trained and when.