Config directory: dp4-nothink/ with 28 per-bench YAMLs (aime repeats=12, judged, agent, long-context) + README

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
sora 2026-09-11 07:59:42 +00:00
parent 77b67f8bbc
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# 配置目录
每个模型/协议一个文件夹,内含逐 bench 的 YAML 配置。
```
config/
├── README.md ← 本文件
└── dp4-nothink/ ← 模型/协议名
├── default.yaml ← 协议级默认参数(所有 bench 继承)
├── aime24.yaml ← 逐 bench 覆盖
├── aime25.yaml
├── ...
└── swe_bench_verified.yaml
```
## 每个 YAML 的结构
```yaml
# generation: 传给模型的参数
generation:
temperature: 1.0
max_tokens: 8192
top_p: 1.0
# run: 运行方式
run:
repeats: 12 # 跑 12 遍取均值temp=1 方差测量用)
limit: null # 全量 / limit_per_task: 10 每子集 10 条
concurrency: 4
checkpoint: true
resume: true
# judge: LLM-judge 类 bench 需要
judge:
model: dp4-flash
api_url: http://174.1.51.4:30000/v1
```
## 优先级
```
DatasetSpec.gen_config < default.yaml < <bench>.yaml < 命令行显式参数
```
## 使用
```bash
# 单 bench
evalharness eval run aime25 --config dp4-nothink --api-url ... --model ...
# 多 bench自动读各自的 yaml
evalharness eval run aime24 aime25 aime26 hmmt26 --config dp4-nothink ...
# 查看某 bench 的生效配置
evalharness config show dp4-nothink aime25
```
## 新增模型配置
```bash
mkdir config/qwen3-es-parity
cp config/dp4-nothink/default.yaml config/qwen3-es-parity/
# 编辑 default.yaml然后按需添加逐 bench 覆盖
```

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# aime24: AIME/HMMT -- temp=1 sampling, 12 runs averaged
generation:
temperature: 1.0
max_tokens: 8192
top_p: 1.0
run:
repeats: 12
limit: null # full dataset (30 problems)
concurrency: 4

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# aime25: AIME/HMMT -- temp=1 sampling, 12 runs averaged
generation:
temperature: 1.0
max_tokens: 8192
top_p: 1.0
run:
repeats: 12
limit: null # full dataset (30 problems)
concurrency: 4

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# aime26: AIME/HMMT -- temp=1 sampling, 12 runs averaged
generation:
temperature: 1.0
max_tokens: 8192
top_p: 1.0
run:
repeats: 12
limit: null # full dataset (30 problems)
concurrency: 4

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# arc: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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# bbh: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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generation:
temperature: 0.0
max_tokens: 4096
top_p: 1.0
parallel_tool_calls: true
run:
limit_per_task: 20
concurrency: 8
env: bfcl_mock
extra:
is_fc_model: true
underscore_to_dot: true

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# bigcodebench: code generation (docker sandbox)
generation:
temperature: 1.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 4

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# cmmlu: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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# dp4-nothink: DeepSeek-V4-Flash nothinking protocol
# All benches inherit these unless overridden in their own <bench>.yaml
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
stream: true
run:
concurrency: 8
checkpoint: true
resume: true

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# drop: short-answer QA
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 8

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generation:
temperature: 0.0
max_tokens: 4096
top_p: 1.0
run:
limit: 400
concurrency: 8

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# gpqa_diamond: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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# gsm8k: short-answer QA
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 8

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# hellaswag: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 25
concurrency: 8
judge:
model: dp4-flash
api_url: http://174.1.51.4:30000/v1

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# hmmt26: AIME/HMMT -- temp=1 sampling, 12 runs averaged
generation:
temperature: 1.0
max_tokens: 8192
top_p: 1.0
run:
repeats: 12
limit: null # full dataset (30 problems)
concurrency: 4

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# humaneval: code generation (docker sandbox)
generation:
temperature: 1.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 4

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generation:
temperature: 1.0
max_tokens: 8192
top_p: 1.0
run:
limit_per_task: 25
concurrency: 8
judge:
model: dp4-flash
api_url: http://174.1.51.4:30000/v1

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# live_code_bench: code generation (docker sandbox)
generation:
temperature: 1.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 4

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generation:
temperature: 0.0
max_tokens: 8192
top_p: 1.0
run:
limit_per_task: 66
concurrency: 4
max_input_tokens: 120000

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# mmlu: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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# mmlu_pro: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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generation:
temperature: 0.0
max_tokens: 8192
top_p: 1.0
run:
limit: 200
concurrency: 4
max_input_tokens: 120000

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# simple_qa: short-answer QA
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 8

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generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit: 70
concurrency: 4

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generation:
temperature: 0.0
max_tokens: 16384
top_p: 1.0
run:
concurrency: 8
env: tau2_official
max_turns: 50

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# trivia_qa: short-answer QA
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit: 200
concurrency: 8

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# winogrande: knowledge/MCQ benchmark
generation:
temperature: 0.0
max_tokens: 32768
top_p: 1.0
run:
limit_per_task: 10
concurrency: 8

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# Generation-parameter profiles (YAML).
# Usage: evalharness eval run <bench> --model ... --profile <name>
# Resolution: DatasetSpec.gen_config < profile.default < profile.<bench> < gen_kwargs
dp4-nothink:
default: {temperature: 0.0, max_tokens: 32768, top_p: 1.0}
qwen3-es-parity:
default: {temperature: 0.0, max_tokens: 32768}
simple_qa: {max_tokens: 1024}
hle: {max_tokens: 8192}
gpqa_diamond: {temperature: 1.0, max_tokens: 8192}
aime24: {temperature: 1.0, max_tokens: 8192}
aime25: {temperature: 1.0, max_tokens: 8192}
aime26: {temperature: 1.0, max_tokens: 8192}
hmmt26: {temperature: 1.0, max_tokens: 8192}
imo_answerbench: {temperature: 1.0, max_tokens: 8192}
glm53-nothink:
default: {temperature: 0.0, max_tokens: 8192, top_p: 1.0}
aime24: {temperature: 1.0, max_tokens: 8192}
aime25: {temperature: 1.0, max_tokens: 8192}
aime26: {temperature: 1.0, max_tokens: 8192}
hmmt26: {temperature: 1.0, max_tokens: 8192}
imo_answerbench: {temperature: 1.0, max_tokens: 8192}
gpqa_diamond: {temperature: 1.0, max_tokens: 8192}
humaneval: {temperature: 1.0, max_tokens: 32768}
live_code_bench: {temperature: 1.0, max_tokens: 32768}
t1-short:
default: {temperature: 1.0, max_tokens: 8192, top_p: 1.0}