---
title: README
emoji: 📚
colorFrom: indigo
colorTo: purple
sdk: static
pinned: false
---

# hmBERT

Historical Multilingual Language Models for Named Entity Recognition. The following languages are covered by hmBERT:

* English (British Library Corpus - Books)
* German (Europeana Newspaper)
* French (Europeana Newspaper)
* Finnish (Europeana Newspaper)
* Swedish (Europeana Newspaper)

More details can be found in [our GitHub repository](https://github.com/dbmdz/clef-hipe) and in our
[hmBERT paper](https://ceur-ws.org/Vol-3180/paper-87.pdf).

# Leaderboard

We test our pretrained language models on various datasets from HIPE-2020, HIPE-2022 and Europeana.
The following table shows an overview of used datasets:

| Language | Datasets                                                         |
|----------|------------------------------------------------------------------|
| English  | [AjMC] - [TopRes19th]                                            |
| German   | [AjMC] - [NewsEye] - [HIPE-2020]                                 |
| French   | [AjMC] - [ICDAR-Europeana] - [LeTemps] - [NewsEye] - [HIPE-2020] |
| Finnish  | [NewsEye]                                                        |
| Swedish  | [NewsEye]                                                        |
| Dutch    | [ICDAR-Europeana]                                                |

[AjMC]: https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-ajmc.md
[NewsEye]: https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-newseye.md
[TopRes19th]: https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-topres19th.md
[ICDAR-Europeana]: https://github.com/stefan-it/historic-domain-adaptation-icdar
[LeTemps]: https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-letemps.md
[HIPE-2020]: https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-hipe2020.md

Results:

| Model                                                                     | English AjMC | German AjMC  | French AjMC  | German NewsEye | French NewsEye | Finnish NewsEye | Swedish NewsEye | Dutch ICDAR  | French ICDAR | French LeTemps | English TopRes19th | German HIPE-2020 | French HIPE-2020 | Avg.      |
|---------------------------------------------------------------------------|--------------|--------------|--------------|----------------|----------------|-----------------|-----------------|--------------|--------------|----------------|--------------------|------------------|------------------|-----------|
| hmBERT (32k) [Schweter et al.](https://ceur-ws.org/Vol-3180/paper-87.pdf) | 85.36 ± 0.94 | 89.08 ± 0.09 | 85.10 ± 0.60 | 39.65 ± 1.01   | 81.47 ± 0.36   | 77.28 ± 0.37    | 82.85 ± 0.83    | 82.11 ± 0.61 | 77.21 ± 0.16 | 65.73 ± 0.56   | 80.94 ± 0.86       | 79.18 ± 0.38     | 83.47 ± 0.80     | 77.65     |
| [hmTEAMS](https://huggingface.co/hmteams)                                 | 86.41 ± 0.36 | 88.64 ± 0.42 | 85.41 ± 0.67 | 41.51 ± 2.82   | 83.20 ± 0.79   | 79.27 ± 1.88    | 82.78 ± 0.60    | 88.21 ± 0.39 | 78.03 ± 0.39 | 66.71 ± 0.46   | 81.36 ± 0.59       | 80.15 ± 0.60     | 86.07 ± 0.49     | **79.06** |

# Acknowledgements

We thank [Luisa März](https://github.com/LuisaMaerz), [Katharina Schmid](https://github.com/schmika) and
[Erion Çano](https://github.com/erionc) for their fruitful discussions about Historical Language Models.

Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC).
Many Thanks for providing access to the TPUs ❤️