autophagycode_metrics_D_metrics_he_unsloth__Qwen3-14B-Base-unsloth-bnb-4bit_lr0.0001_gen4

该数据集包含164个训练样本，总大小为18,027字节，下载大小为15,955字节。数据集结构包含14个特征字段，主要涉及编程任务执行指标和代码复杂度分析：
1. 任务标识（task_index）与入口点（entry_point）
2. 执行状态（is_executable, is_correct）
3. 测试结果（tests_passed, tests_failed, test_run_time_ms）
4. 错误类型（error_type）
5. 代码复杂度指标（halstead_vocabulary/length/volume/difficulty/effort）
6. 可维护性指数（maintainability_index）

虽然未明确说明应用场景，但字段特征表明该数据集适用于代码质量评估、自动测试验证或软件工程研究，特别是与代码复杂度分析和测试覆盖率相关的任务。

This dataset contains 164 training samples, with a total size of 18,027 bytes and a download size of 15,955 bytes. The dataset structure includes 14 feature fields, mainly focusing on programming task execution metrics and code complexity analysis: 1. Task identifier (task_index) and entry point (entry_point); 2. Execution status (is_executable, is_correct); 3. Test results (tests_passed, tests_failed, test_run_time_ms); 4. Error type (error_type); 5. Code complexity metrics (halstead_vocabulary/length/volume/difficulty/effort); 6. Maintainability index (maintainability_index). Although the application scenario is not explicitly specified, the field characteristics indicate that this dataset is suitable for code quality assessment, automated test validation, or software engineering research, particularly tasks related to code complexity analysis and test coverage.