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---
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 ❤️
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