---
license: mit
language:
- en
- de
- fr
- fi
- sv
- nl
---

# hmByT5 - Preliminary Language Models

Preliminary Historic Multilingual and Monolingual ByT5 Models. Following languages are currently covered:

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

More details can be found in [our GitHub repository](https://github.com/stefan-it/hmByT5).

In this experiment we sample 4B bytes (~4GB of text) from each corpora (and upsample Swedish and Finnish) and train for another epoch (2 epochs in total).

# Pretraining

We use the official JAX/FLAX example in Hugging Face Transformers to pretrain a ByT5 model on a single v3-8 TPU.
Details about the training can be found [here](https://github.com/stefan-it/hmByT5/tree/main/hmbyt5-flax).

# Evaluation on Downstream Tasks (NER)

We evaluated the hmByT5 model on downstream tasks:

| Model                                                                                                                                                                           | English AjMC | German AjMC  | French AjMC  | Finnish NewsEye | Swedish NewsEye | Dutch ICDAR  | French ICDAR | Avg. |
|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|--------------|--------------|-----------------|-----------------|--------------|--------------|------|
| [`hmbyt5-preliminary/byt5-small-multilingual-4g-2e`](https://huggingface.co/hmbyt5-preliminary/byt5-small-multilingual-4g-2e)                                                   | 83.86 ± 0.61 | 87.54 ± 0.19 | 84.29 ± 0.41 |                 |                 |              |              |      |

# Acknowledgements

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 ❤️