Multi-Task Evaluation Example

Configuring multi_task.yaml

• eval.defaults defines inference parameters shared by every dataset entry. Override them inside an individual dataset block if needed.
• eval.datasets enumerates the datasets to evaluate. Each entry should specify:
  • name: a short identifier that appears in logs and dashboards.
  • path: the path to the dataset JSONL file.
  • rm_type: which reward function to use for scoring.
  • n_samples_per_eval_prompt: how many candidate completions to generate per prompt.

IFBench Notes

• When ifbench is used, slime/rollout/rm_hub/ifbench.py will automatically prepares the scoring environment, so no additional manual setup is required beyond providing the dataset path.