| # Submit to the Doc-Split leaderboard |
|
|
| 1. **Predict** boundaries for every stream in each cut: `{stream_id: [0/1 per page, in position order]}` |
| (1 = page starts a new document; page 0 is a forced boundary). Cuts: `our200` (this repo) and the |
| OpenPSS SHORT/LONG cuts from [`openpss-mirror`](https://huggingface.co/datasets/nutrientdocs/openpss-mirror). |
| 2. **Score** per cut: `python score.py --pred preds.json --config our200` → `{f1, kappa, windowdiff, pk, ...}`. |
| 3. **Open a PR** on the [leaderboard Space](https://huggingface.co/spaces/nutrientdocs/doc-split-leaderboard) |
| adding `results/<model>-<cut>.json`: |
|
|
| ```json |
| { "name": "your-model", "model": "org/your-model", "cut": "openpss_short", |
| "open": true, "n": 108, "f1": 0.00, "kappa": 0.00, |
| "hardware": "A100", "inputs": "image+text" } |
| ``` |
|
|
| Report **κ alongside F1** — on the sparse cuts a degenerate predict-none/all scores κ ≈ 0 despite a |
| misleading F1. Note whether your model saw these domains in training (in-domain vs zero-shot). |
|
|
