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  3. 基于合成数据的大模型性能优化挑战赛
OpenAtomLLMIntermediateRegistration unverified

基于合成数据的大模型性能优化挑战赛

A intermediate llm competition requiring roughly 12–40 hours for an end-to-end practice run.

Difficulty
Intermediate
Estimated effort
12–40 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

适合已有大语言模型训练或微调经验、能围绕 API 定义构造合成指令数据的开发者或团队。参赛者还需要理解多轮对话中的工具调用时机、历史上下文和函数参数生成;个人和组织机构均可参赛。

Read the original official blurb
探索合成数据在真实任务重的有效性。通过任务定义合成相应数据,有效提高模型在真实任务的性能表现;提高合成数据有效性,在有限合成资源约束下,最大化合成出的数据对模型提升效果。 Official category: 实战竞技赛. Organizers: 华为技术有限公司. Participants: 5.

Preparation

From registration to a first submission

  1. 01

    大语言模型微调

  2. 02

    合成数据生成

  3. 03

    多轮对话建模

  4. 04

    函数调用(Function Calling)

  5. 05

    API 参数填充

  6. 06

    模型推理环境部署

Before you commit: 难点不只是生成对话数据,而是让模型在包含日常聊天的多轮上下文中,既能判断是否该调用工具,又能选对未见过的 API 并准确填全参数。决赛还要求提交可由统一接口测试的模型及环境,并提供代码、训练日志等完整方案。

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
OpenAtom
Last checked
Dec 5, 2024

Entry assessment

est.
48

Prepare before joining

Overall fit estimate

Beginner fit48/100
Learning value60/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

Open official pageSign in to saveOpen guide

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

View data stateClose
Source page verifiedMetric confirmedReviewed
Source published
Dec 5, 2024
Source created
Dec 5, 2024
Published on this site
Jul 21, 2026

Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.

reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.