56 lines
2.9 KiB
YAML
56 lines
2.9 KiB
YAML
# ──────────────────────────────────────────────────
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# SkillOpt Config Template — <Your Benchmark Name>
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# ──────────────────────────────────────────────────
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# Copy this file to configs/<your_benchmark>/default.yaml
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# and customize the values below.
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# Inherit global defaults.
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# NOTE: `_base_` is a string path, not a list.
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_base_: ../_base_/default.yaml
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# ── Environment ──────────────────────────────────
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env:
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name: your_benchmark # Must match the key registered in scripts/train.py
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# Optional: a seed skill document. Create this file yourself before the
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# first run, or omit the key to start from an empty skill.
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# skill_init: skillopt/envs/your_benchmark/skills/initial.md
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data_path: data/your_benchmark # Path to your data (for split_mode: ratio)
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split_dir: "" # Set this and use split_mode: split_dir for pre-split data
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split_mode: ratio # "ratio" or "split_dir"
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split_ratio: "2:1:7" # train:val:test (used when split_mode: ratio)
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workers: 4 # Parallel rollout workers
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max_completion_tokens: 4096 # Cap per target-model call
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limit: 0 # 0 = no limit; small int = debug sample
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# ── Training ─────────────────────────────────────
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train:
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num_epochs: 4
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batch_size: 40
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accumulation: 1
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seed: 42
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# ── Gradient (Reflection) ───────────────────────
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gradient:
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analyst_workers: 16 # Parallel reflection workers
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minibatch_size: 8
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merge_batch_size: 8
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# ── Optimizer ────────────────────────────────────
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optimizer:
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learning_rate: 4 # Max edits per step (edit budget)
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lr_scheduler: cosine # cosine | linear | constant | autonomous
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use_slow_update: true # Epoch-boundary momentum
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use_meta_skill: true # Cross-epoch optimizer memory
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# ── Evaluation ───────────────────────────────────
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evaluation:
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use_gate: true # Validation gating
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eval_test: true # Run test eval after training
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# ── Model ────────────────────────────────────────
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# Override only what differs from the inherited defaults.
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model:
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optimizer_backend: openai_chat # openai_chat | claude_chat | qwen_chat | minimax_chat
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target_backend: openai_chat # … plus codex_exec / claude_code_exec for target only
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reasoning_effort: medium
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