dnn-tuning

dnn-tuning is a Model training & evaluation skill for AI agents, published by aliyun in the qwen-dianjin repository on GitHub. Skillspace rates dnn-tuning D (65/100) and it passed the safety scan; the rating is based on static analysis only.

【DNN调参】当用户说"DNN调参"、"深度学习调参"、"调整网络结构"、"调整dropout"、"DNN过拟合"时使用。基于 Optuna TPE 贝叶斯优化，搜索网络架构（层数、宽度、dropout）和训练参数（learning_rate、weight_decay、batch_size），诊断驱动约束搜索空间。前置条件：需先用 dnn-modeling 训练出基线模型。

Grade
D
Quality
65 / 100
Safety
Passed
GitHub stars
612

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubaliyun/qwen-dianjin

Our review

Architecture
94 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
Not declared. Check the repository before reusing it.

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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