# ──────────────────────────────────────────────────
# SkillOpt Config Template — <Your Benchmark Name>
# ──────────────────────────────────────────────────
# Copy this file to configs/<your_benchmark>/default.yaml
# and customize the values below.

# Inherit global defaults
_base_: ../_base_/default.yaml

# ── Environment ──────────────────────────────────
env:
  name: your_benchmark            # Must match _ENV_REGISTRY key in scripts/train.py
  data_path: data/your_benchmark  # Path to your data
  split_mode: ratio               # "ratio" or "split_dir"
  split_ratio: "2:1:7"            # train:val:test
  exec_timeout: 120               # Per-task timeout (seconds)

# ── Training ─────────────────────────────────────
train:
  num_epochs: 4                   # Number of epochs
  batch_size: 40                  # Tasks per step (batch size)
  seed: 42

# ── Gradient (Reflection) ───────────────────────
gradient:
  analyst_workers: 16             # Parallel reflection workers
  minibatch_size: 8

# ── Optimizer ────────────────────────────────────
optimizer:
  learning_rate: 4                # Max edits per step (edit budget)
  lr_scheduler: cosine            # cosine | linear | constant | autonomous
  use_slow_update: true           # Epoch-boundary momentum
  use_meta_skill: true            # Cross-epoch optimizer memory

# ── Evaluation ───────────────────────────────────
evaluation:
  use_gate: true                  # Validation gating
  eval_test: true                 # Run test eval after training

# ── Model ────────────────────────────────────────
model:
  backend: azure_openai           # azure_openai | openai_chat | claude_code_exec | qwen
  optimizer: gpt-4o
  target: gpt-4o