sync: eqbench-ja-run/README.md
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eqbench-ja-run/README.md
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# EQ-Bench3 ローカル評価セットアップ
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TeenEmo-LFM2.5-1.2B-DPO を EQ-Bench3 日本語版で評価するセットアップ。
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受験者・採点者ともに同一A100インスタンス上のローカルvLLMを使用。
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## モデル構成
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| 役割 | モデル | VRAM | ポート |
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|------|--------|------|--------|
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| 受験者 | `YUGOROU/TeenEmo-LFM2.5-1.2B-DPO` | ~3GB | 8000 |
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| 採点者 | `Qwen/Qwen3.5-35B-A3B` | ~70GB | 8001 |
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## セットアップ
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```bash
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export HF_TOKEN="hf_xxxx" && export HF_USERNAME="YUGOROU"
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curl -fL -H "Authorization: Bearer ${HF_TOKEN}" \
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"https://huggingface.co/datasets/YUGOROU/Test-2/resolve/main/eqbench-ja-run/setup_eqbench_run.sh" \
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-o /tmp/setup_eqbench_run.sh && bash /tmp/setup_eqbench_run.sh
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```
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## 同時起動モード(推奨)
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A100 80GBで両モデルを同時起動する。TeenEmoのGPU_UTIL=0.10で約3GBに抑える。
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```bash
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# Step 1: TeenEmo起動(port 8000)
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tmux new-session -d -s eq_run
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tmux new-window -t eq_run -n test
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tmux send-keys -t eq_run:test "cd /workspace/eqbench-run && export HF_TOKEN='hf_xxxx' && ./serve_test.sh" Enter
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# Step 2: 採点者起動(port 8001)
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tmux new-window -t eq_run -n judge
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tmux send-keys -t eq_run:judge "cd /workspace/eqbench-run && ./serve_judge.sh" Enter
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# Step 3: 起動確認
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tmux capture-pane -t eq_run:test -p | grep "startup complete"
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tmux capture-pane -t eq_run:judge -p | grep "startup complete"
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# Step 4: 評価実行
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cd /workspace/eqbench-run/eqbench3
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python eqbench3.py \
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--test-model YUGOROU/TeenEmo-LFM2.5-1.2B-DPO \
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--model-name TeenEmo-DPO \
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--judge-model Qwen/Qwen3.5-35B-A3B \
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--no-elo \
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--iterations 1
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```
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## 順次実行モード(OOM対策)
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同時起動でOOMが発生した場合。
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```bash
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# Phase 1: TeenEmoで全応答を生成
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./serve_test.sh & # port 8000
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# (起動待機)
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cd /workspace/eqbench-run/eqbench3
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python eqbench3.py \
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--test-model YUGOROU/TeenEmo-LFM2.5-1.2B-DPO \
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--model-name TeenEmo-DPO \
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--judge-model Qwen/Qwen3.5-35B-A3B \
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--no-elo --iterations 1
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# → 採点時にjudge APIが返せずエラーになるが応答データは保存される
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# Phase 2: TeenEmoを停止してJudgeで採点
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kill $(lsof -t -i:8000)
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JUDGE_GPU_UTIL=0.90 ./serve_judge.sh & # port 8001
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# (起動待機後、再実行で既存応答を再利用し採点のみ行う)
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python eqbench3.py \
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--test-model YUGOROU/TeenEmo-LFM2.5-1.2B-DPO \
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--model-name TeenEmo-DPO \
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--judge-model Qwen/Qwen3.5-35B-A3B \
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--no-elo --iterations 1
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```
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## 結果の確認
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```bash
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cat /workspace/eqbench-run/eqbench3/eqbench3_runs.json | python3 -c "
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import json, sys
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data = json.load(sys.stdin)
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for run_id, run in data.items():
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if 'TeenEmo' in run_id:
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print(f'Run: {run_id}')
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print(f'Score: {run.get(\"eq_bench_score\", \"N/A\")}')
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"
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```
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