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README.md
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---
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license: mit
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language:
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- en
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- de
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- fr
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- fi
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- sv
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- nl
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---
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# hmByT5 - Preliminary Language Models
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Preliminary Historic Multilingual and Monolingual ByT5 Models. Following languages are currently covered:
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* English (British Library Corpus - Books)
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* German (Europeana Newspaper)
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* French (Europeana Newspaper)
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* Finnish (Europeana Newspaper)
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* Swedish (Europeana Newspaper)
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* Dutch (Delpher Corpus)
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More details can be found in [our GitHub repository](https://github.com/stefan-it/hmByT5).
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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).
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# Pretraining
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We use the official JAX/FLAX example in Hugging Face Transformers to pretrain a ByT5 model on a single v3-8 TPU.
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Details about the training can be found [here](https://github.com/stefan-it/hmByT5/tree/main/hmbyt5-flax).
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# Evaluation on Downstream Tasks (NER)
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We evaluated the hmByT5 model on downstream tasks:
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| Model | English AjMC | German AjMC | French AjMC | Finnish NewsEye | Swedish NewsEye | Dutch ICDAR | French ICDAR | Avg. |
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|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|--------------|--------------|-----------------|-----------------|--------------|--------------|------|
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| [`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 | | | | | |
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# Acknowledgements
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Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC).
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Many Thanks for providing access to the TPUs ❤️
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