Optimizing multiple metrics - Weights & Biases Documentation

W&B Sweeps optimize a single objective metric. To optimize multiple metrics in a single run, combine them into a weighted sum and use that combined value as the sweep objective.

with wandb.init() as run:
  # Log individual metrics
  metric_a = run.summary.get("metric_a", 0.5)
  metric_b = run.summary.get("metric_b", 0.7)
  # ... log other metrics as needed
  metric_n = run.summary.get("metric_n", 0.9)

  # Combine metrics with weights
  # Adjust weights according to your optimization goals
  # For example, if you want to give more importance to metric_a and metric_n:
  metric_combined = 0.3 * metric_a + 0.2 * metric_b + ... + 1.5 * metric_n
  run.log({"metric_combined": metric_combined})

After you log the combined metric, set it as the optimization objective in your sweep configuration:

metric:
  name: metric_combined
  goal: minimize

Sweeps Metrics

⌘I