README.md

---
pretty_name: EvalEng
language:
  - en
license: mit
task_categories:
  - text-classification
  - token-classification
  - summarization
task_ids:
  - multi-class-classification
  - multi-label-classification
tags:
  - software-engineering
  - evaluation-harness
  - github-issues
  - issue-classification
  - empirical-software-engineering
  - llm-evaluation
  - benchmark-engineering
  - mlops
  - dataset-mining
  - text
  - tabular
  - arxiv:2605.24213
size_categories:
  - 10K<n<100K
annotations_creators:
  - machine-generated
  - expert-generated
source_datasets:
  - original
homepage: https://github.com/zhimin-z/EvalEng
paperswithcode_id: null
dataset_info:
  features:
  - name: harness_name
    dtype: string
  - name: github_repo
    dtype: string
  - name: issue_title
    dtype: string
  - name: issue_body
    dtype: string
  - name: issue_url
    dtype: string
  - name: issue_created_at
    dtype: int64
  - name: issue_closed_at
    dtype: int64
  - name: is_related
    dtype: float64
  - name: stage
    dtype: float64
  - name: step
    dtype: string
  - name: strategy
    dtype: float64
  - name: root_cause_label
    dtype: string
  - name: issue_comments
    sequence: string
  - name: issue_labels
    sequence: string
  - name: issue_cross_referenced
    sequence: string
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl
viewer: true
---

# EvalEng Dataset

GitHub issues collected from 57 ML evaluation harnesses, annotated with workflow stage, root cause, and evaluation strategy labels.

## Dataset Details

- **Paper:** [Towards Evaluation Engineering](https://arxiv.org/abs/2605.24213)
- **Repository:** https://github.com/zhimin-z/EvalEng
- **License:** MIT

## Fields

| Field | Type | Description |
|-------|------|-------------|
| `harness_name` | string | Name of the ML evaluation harness |
| `github_repo` | string | GitHub repository (owner/repo) |
| `issue_title` | string | Issue title |
| `issue_body` | string | Issue body text |
| `issue_url` | string | Direct URL to the GitHub issue |
| `issue_created_at` | int64 | Creation timestamp (ms since epoch) |
| `issue_closed_at` | int64 | Closed timestamp (ms since epoch) |
| `is_related` | float64 | Whether the issue is related to evaluation (1.0 = yes) |
| `stage` | float64 | Workflow stage label (numeric) |
| `step` | string | Workflow step label |
| `strategy` | float64 | Evaluation strategy label (numeric) |
| `root_cause_label` | string | Root cause category |
| `issue_comments` | list[string] | Issue comment texts |
| `issue_labels` | list[string] | GitHub labels on the issue |
| `issue_cross_referenced` | list[string] | Cross-referenced issue/PR URLs |

## Citation

```bibtex
@article{zhao2025evaleng,
      title={Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild}, 
      author={Zhimin Zhao and Zehao Wang and Abdul Ali Bangash and Bram Adams and Ahmed E. Hassan},
      year={2026},
      eprint={2605.24213},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2605.24213}, 
}
```