| --- |
| license: other |
| language: |
| - en |
| task_categories: |
| - visual-question-answering |
| - automatic-speech-recognition |
| - text-generation |
| tags: |
| - evaluation |
| - benchmark |
| - multimodal |
| - edge-inference |
| - on-device |
| - litert-lm |
| - image |
| - audio |
| - text |
| - multi-turn |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test/metadata.jsonl |
| pretty_name: EdgeMMEval |
| --- |
| |
| # EdgeMMEval |
|
|
| Minimal multimodal evaluation dataset for on-device inference testing. |
| Covers functional correctness, accuracy, latency stress, and memory |
| pressure across image, audio, text, multi-turn, combination, structured |
| output, and tool-calling cases. |
|
|
| ## Dataset summary |
|
|
| The test split is defined in `data/test/metadata.jsonl` (**200** rows). Each |
| row has a `test_id` (for example `IMG-001`, `STO-020`) and a `modality`. |
|
|
| | Modality | Samples | Focus | |
| |----------------------|--------:|--------| |
| | Image | 34 | VQA, OCR, description, classification, resolution / loop stress | |
| | Audio | 27 | Transcription, spoken QA, translation, noise and edge cases | |
| | Text | 41 | QA, translation, summarization, reasoning-style prompts | |
| | Multi-turn | 24 | Context retention, KV-cache stress | |
| | Combination | 28 | Cross-modal alignment | |
| | Structured output | 32 | JSON schema, regex, grammar-style constraints (`constraint_type`) | |
| | Tool call | 14 | Correct tool name, arguments, or valid refusal text | |
| | **Total** | **200** | | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("CortexSwarm/EdgeMMEval", split="test") |
| print(ds[0]) |
| ``` |
|
|
| ## Scoring |
|
|
| Each sample includes a `reference` field and usually `reference_variants` for |
| automatic scoring. The scorer lives in this repo at `scripts/score.py`. |
|
|
| **Pipeline** |
|
|
| 1. Run your model on each `test_id` and collect the model’s output string. |
| 2. Write a JSON object to **`results.json`** at the repo root: keys are |
| `test_id` values, values are the raw model outputs (strings). |
| 3. Run `python scripts/score.py`. It reads `data/test/metadata.jsonl` and |
| `results.json`, then writes **`report.json`**. |
|
|
| **Metrics and pass rules** (see constants at the top of `score.py`) |
|
|
| - Most tasks: **BLEU-1** vs `reference_variants`; pass if score **≥ 0.5**. |
| - Summarization-style tasks (`task` in `summarization` / `summarize`): **ROUGE-L**; |
| pass if **≥ 0.4**. |
| - **Structured output**: format check (JSON Schema, regex, or grammar-style |
| heuristic) plus content BLEU; pass if format is valid and BLEU **≥ 0.3**. |
| - **Tool call**: compares expected tool/args or valid text-only refusal; |
| separate logic in `score_tool_call`. |
|
|
| **`report.json` shape** |
|
|
| - `summary`: `total_scored`, `total_passed`, `overall_avg`, `pass_rate_pct`, |
| `verdict` (`✓ INFERENCE WORKING` if pass rate ≥ 80%, else |
| `✗ ISSUES DETECTED`), and `skipped` (test IDs with **no** entry in |
| `results.json`). |
| - `by_modality`: average score and pass counts per modality (empty if nothing |
| was scored). |
| - `samples`: per-test rows with scores, metrics, and pass/fail. |
|
|
| If **`total_scored` is 0**, every test ID was skipped—typically **`results.json` |
| is missing or does not map test IDs to outputs**. Fix the results file and |
| re-run the scorer. |
| |
| ## License |
| |
| The majority of this dataset is **CC BY 4.0**. A small subset of image files |
| comes from [Unsplash](https://unsplash.com/) and is governed by the |
| **[Unsplash License](https://unsplash.com/license)** instead. |
| |
| ### CC BY 4.0 (metadata, text tasks, original media, tooling, and most images) |
| |
| The following are licensed under **Creative Commons Attribution 4.0** |
| ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)): |
| |
| - `data/test/metadata.jsonl` (prompts, references, labels, structure). |
| - All **text**, **multi-turn**, **combination**, **structured output**, and |
| **tool call** samples. |
| - **Audio** clips produced from project `samples/` recordings (see |
| `scripts/collect_all_audio.sh`). |
| - **Images** generated in-repo by `scripts/collect_all_images.py` using PIL— |
| synthetic shapes, UI mockups, charts, QR patterns, blank canvases, sequential |
| frames, and all derived images (blur, crop, rotation, collage, meme, watermark, |
| overexposed) whose source is a PIL-generated file rather than an Unsplash photo. |
| This covers `IMG-001`–`IMG-005`, `IMG-007`–`IMG-009`, `IMG-015`–`IMG-017`, |
| `IMG-021`–`IMG-024`, `IMG-026`–`IMG-033`. |
| - `IMG-020` (built from `samples/v2/real-receipt.webp`, author-provided). |
| - Scripts and scorer logic (`scripts/`, `upload.py`). |
| |
| Reuse requires **attribution** to **EdgeMMEval** and a link to this dataset or |
| source repository. |
| |
| ### Unsplash License (specific image files) |
| |
| The following files under `data/test/images/` are photographs downloaded from |
| [Unsplash](https://unsplash.com/) (URLs in `scripts/collect_all_images.py`) |
| and remain under the **[Unsplash License](https://unsplash.com/license)**: |
| |
| **Direct downloads:** `IMG-006.jpg` (4K mountain; if the download failed and |
| the script used its generated fallback, that copy is CC BY 4.0 instead), |
| `IMG-010.jpg`, `IMG-011.jpg`, `IMG-012.jpg`, `IMG-013.jpg`, `IMG-014.jpg`, |
| `IMG-025.jpg`, `IMG-034.jpg`. |
| |
| **Derivatives of those photos:** `IMG-018.jpg` (180° rotation of `IMG-010`), |
| `IMG-019.jpg` (JPEG-compressed from `IMG-010`). |
| |
| The Unsplash License permits free use and modification; you may not sell |
| unmodified copies or build a competing image-service from the content—see the |
| [full license text](https://unsplash.com/license) for details. |
| |
| ### Summary |
| |
| | Part | License | |
| |------|---------| |
| | Metadata, text tasks, scripts, audio, PIL-generated images, receipt | **CC BY 4.0** | |
| | Unsplash photos and two derivatives listed above | **[Unsplash License](https://unsplash.com/license)** | |
| |
