---
license: mit
language:
- en
---

# hmByT5 - Preliminary Language Models

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

* English (British Library Corpus - Books)

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

# 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 Base model on English AjMC dataset:

| Configuration                            |   Run 1 |   Run 2 |   Run 3 |   Run 4 |   Run 5 | Avg.         |
|------------------------------------------|---------|---------|---------|---------|---------|--------------|
| `wsFalse-bs4-e10-lr0.00015-poolingfirst` |   86.78 |   87.46 |   85.75 |   88.41 |   86.6  | 87.0 ± 0.89  |
| `wsFalse-bs8-e10-lr0.00016-poolingfirst` |   86.79 |   86.29 |   86.67 |   87.14 |   85.82 | 86.54 ± 0.45 |
| `wsFalse-bs4-e10-lr0.00016-poolingfirst` |   87.04 |   87.34 |   86.63 |   84.09 |   87.04 | 86.43 ± 1.19 |
| `wsFalse-bs8-e10-lr0.00015-poolingfirst` |   86.87 |   86.43 |   86.88 |   85.15 |   85.25 | 86.12 ± 0.77 |

The ByT5 Small [model](https://huggingface.co/hmbyt5/byt5-small-english) achieves 85.65 ± 1.21 on this dataset.

# 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 ❤️