| --- |
| license: other |
| license_name: nutrient-eval-restricted |
| pretty_name: Document Classification Benchmark (open-vocab, zero-shot) |
| task_categories: |
| - zero-shot-image-classification |
| - image-classification |
| language: |
| - en |
| tags: |
| - document-ai |
| - open-vocabulary |
| - zero-shot-image-classification |
| - document-image-classification |
| size_categories: |
| - 1K<n<10K |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: string |
| - name: candidate_labels |
| list: string |
| - name: source |
| dtype: string |
| - name: license_tag |
| dtype: string |
| - name: doc_id |
| dtype: string |
| - name: track |
| dtype: string |
| splits: |
| - name: test |
| num_bytes: 453775818 |
| num_examples: 1274 |
| download_size: 453674933 |
| dataset_size: 453775818 |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-* |
| --- |
| |
| # Document Classification Benchmark (open-vocab, zero-shot) |
|
|
| **Given a document image and an arbitrary set of text labels, which one is right?** A held-out, zero-shot, |
| *open-vocabulary* evaluation for document-type classification — labels are supplied at inference, not baked |
| into a head. Test split only; not for training. Every image is drawn from a **permissively-licensed, |
| redistributable** source. |
|
|
| Powers the |
| [document-classification-leaderboard](https://huggingface.co/spaces/nutrientdocs/document-classification-leaderboard) |
| and evaluates [`document-classification-v2`](https://huggingface.co/nutrientdocs/document-classification-v2) |
| (commercial) and the open-weight |
| [`document-classification-v1`](https://huggingface.co/nutrientdocs/document-classification-v1); try it live in |
| the [demo](https://huggingface.co/spaces/nutrientdocs/document-classification-demo). |
|
|
| ## Tracks (macro-F1) |
|
|
| - **DocLayNet** — document page categories (financial reports, scientific articles, manuals, patents, …). |
| - **Forms** — form vs non-form and fine form sub-types. |
| - **OOD** — document *types absent from training* (invoices, handwriting, charts, tables) — the open-vocab |
| stress test. |
| - **OOV** — an evaluation *protocol* (not extra rows): score the same images against never-seen synonym |
| paraphrases of each label ("invoice" → "bill") to measure concept-matching vs memorized wording. |
|
|
| ## Contents & sources |
|
|
| 897 test images (`track` column selects the slice). All sources are redistributable: |
|
|
| | Source | Track | License | |
| |---|---|---| |
| | DocLayNet (`ds4sd/DocLayNet`) | doclaynet | CDLA-Permissive-1.0 | |
| | synthetic IRS forms (public-domain templates + faked fields) | forms | public-domain | |
| | mixed permissive HF sources (invoice / handwriting / chart / table) | ood | per upstream source | |
|
|
| > **Tobacco3482 is deliberately excluded.** Its research-only license is not redistributable, so it is not |
| > part of this public benchmark (it is used only in internal evaluation). |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("nutrientdocs/document-classification-benchmark", split="test") |
| ``` |
|
|
| ## Schema |
|
|
| | field | meaning | |
| |---|---| |
| | `image` | the document image (RGB) | |
| | `label` | gold document-type label | |
| | `candidate_labels` | the open-vocab candidate set for the row's track | |
| | `source` | originating dataset | |
| | `license_tag` | redistribution tier of the source | |
| | `doc_id` | provenance id | |
| | `track` | doclaynet · forms · ood | |
|
|
| ## About the author |
|
|
| <a href="https://nutrient.io/"> |
| <img src="https://avatars2.githubusercontent.com/u/1527679?v=3&s=200" height="80" /> |
| </a> |
|
|
| This project is maintained and funded by [Nutrient](https://nutrient.io/) - The deterministic document infrastructure enterprises run their highest-stakes workflows on: replayable output, clear exceptions, and full audit trails on the messy, regulated documents where AI alone breaks. |
|
|
