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README.md
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## RoBERTa Latin model, version 3 --> model card not finished yet
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This is a Latin RoBERTa-based LM model, version 3.
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The intention of the Transformer-based LM is twofold: on the one hand, it will be used for the evaluation of HTR results; on the other, it should be used as a decoder for the TrOCR architecture.
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The training data differs from the one used in the RoBERTa Bas Latin Cased V1 and V2, and therefore also by what is used by [Bamman and Burns (2020)](https://arxiv.org/pdf/2009.10053.pdf). We exclusively used the text from the [Corpus Corporum](https://www.mlat.uzh.ch).
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The overall corpus contains 1.5G of text data (3x as much as has been used for V2 and very likely of better quality).
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### Preprocessing
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I undertook the following preprocessing steps:
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- Normalisation of all lines with [CLTK](http://www.cltk.org) incl. sentence splitting.
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- Language identification with [langid](https://github.com/saffsd/langid.py)
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- Retaining only Latin lines.
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The result is a corpus of ~232 million tokens.
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The dataset used to train this will be available on Hugging Face later [HERE (does not work yet)]().
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### Contact
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For contact, reach out to Phillip Ströbel [via mail](mailto:pstroebel@cl.uzh.ch) or [via Twitter](https://twitter.com/CLingophil).
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### How to cite
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If you use this model, pleas cite it as:
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@online{stroebel-roberta-base-latin-cased3,
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author = {Ströbel, Phillip Benjamin},
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title = {RoBERTa Base Latin Cased V2},
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year = 2022,
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url = {https://huggingface.co/pstroe/roberta-base-latin-cased3},
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urldate = {YYYY-MM-DD}
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}
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