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README.md

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+---
+license: cc-by-4.0
+language:
+- sv
+tags:
+- kraken
+- htr
+- ocr
+- fraktur
+- swedish
+- historical
+pipeline_tag: image-to-text
+---
+
+# Swedish Fraktur — Kraken OCR/HTR model
+
+A [Kraken](https://kraken.re) recognition model (`.mlmodel`) for **OCR of older
+Swedish text printed in Fraktur (blackletter)**. It produces a diplomatic
+transcription that keeps historical orthography, the long s (ſ) and period
+spelling, and works on scanned page images.
+
+- **File:** `svensk_fraktur.mlmodel`
+- **Type:** Kraken recognition model (baseline/HTR pipeline)
+- **DOI:** [10.5281/zenodo.20702142](https://doi.org/10.5281/zenodo.20702142)
+- **Best validation accuracy:** 0.9880 (≈ 1.2 % CER) on a held-out split
+- **Base model:** `german_print` (fine-tuned from it)
+- **Training data:** Språkbanken, *Svensk fraktur 1626–1816*
+
+## Usage
+
+Fetch the model directly from Zenodo: `kraken get 10.5281/zenodo.20702142`
+
+**Kraken (CLI):**
+
+```bash
+kraken -i page.jpg out.txt segment -bl ocr -m svensk_fraktur.mlmodel
+```
+
+For multi-page PDFs, render pages to images first (e.g. ~300 DPI) and pass them
+to Kraken. **eScriptorium:** import the `.mlmodel` under *Models*.
+
+## How it was trained
+
+Fine-tuned from `german_print` on the Språkbanken corpus *Svensk fraktur
+1626–1816* (199 page images with line-level diplomatic transcriptions). The page
+images were OCR-bootstrapped and the recognized lines aligned to the ground-truth
+line text (≈98 % coverage), producing PageXML for `ketos train`. A low learning
+rate (`-r 0.0001`) was decisive — it let the model improve steadily past epoch 0
+instead of drifting away from the strong starting point. See [`training/`](training/)
+for the scripts and exact commands.
+
+The validation accuracy is measured on a held-out split of the same corpus and is
+therefore optimistic relative to entirely new documents; on a real volume
+(1600s Swedish Fraktur) it produced a near-flawless body-text transcription with
+preserved long-s and period spelling and no systematic substitution errors.
+
+## Limitations
+
+- Trained on Swedish Fraktur print; not intended for handwriting or modern
+  (antiqua/roman) type.
+- Ornate/decorated title-page initials are read less reliably than body text.
+- Output is **diplomatic** (verbatim): historical spelling, long-s and printed
+  line-break hyphens are preserved. Modernisation/normalisation should happen in
+  a downstream step, not here.
+
+## Provenance, rights and attribution
+
+This is a derivative model. Full chain:
+
+| Layer | Resource | By | DOI | License |
+|-------|----------|----|-----|---------|
+| Base model | german_print (OCR model for German prints) | S. Weil, J. Kamlah, T. Schmidt (2023) | [10.5281/zenodo.10519596](https://doi.org/10.5281/zenodo.10519596) | **CC0-1.0** |
+| Training data | Svensk fraktur 1626–1816 | Språkbanken Text, University of Gothenburg | [10.23695/5sme-7437](https://doi.org/10.23695/5sme-7437) | **CC-BY-4.0** |
+
+The base model is **CC0** (no attribution legally required; cited as courtesy).
+The training data is **CC-BY-4.0**, which requires **attribution**. When you use
+or redistribute this model, please keep the following attribution:
+
+> Trained on *Svensk fraktur 1626–1816*, Språkbanken Text, University of
+> Gothenburg (digitisation: Gothenburg University Library; transcription:
+> GREPECT), [doi.org/10.23695/5sme-7437](https://doi.org/10.23695/5sme-7437),
+> licensed CC-BY-4.0.
+
+This model is released under **CC-BY-4.0** (see [`LICENSE`](LICENSE)).
+
+## Citation
+
+See [`CITATION.cff`](CITATION.cff).