RoBERTa Latin model
This is a Latin RoBERTa-based LM model.
The data it uses is the same as has been used to compute the text referenced HTR evaluation measures.
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.
The basis for the word unigram and character n-gram computations is the Latin part of the cc100 corpus.
The overall corpus contains 2.5G of text data.
Preprocessing
I undertook the following preprocessing steps:
- Removal of all "pseudo-Latin" text ("Lorem ipsum ...").
- Use of CLTK for sentence splitting and normalisation.
- Retaining only lines containing letters of the Latin alphabet, numerals, and certain punctuation (-->
grep -P '^[A-z0-9ÄÖÜäöüÆ挜ᵫĀāūōŌ.,;:?!\- Ęę]+$' la.nolorem.tok.txt - deduplication of the corpus
The result is a corpus of ~390 million tokens.
The dataset used to train this model is available HERE.
Contact
For contact, reach out to Phillip Ströbel via mail or via Twitter.
How to cite
If you use this model, pleas cite it as:
@online{stroebel-roberta-base-latin-cased1,
author = {Ströbel, Phillip Benjamin},
title = {RoBERTa Base Latin Cased V1},
year = 2022,
url = {https://huggingface.co/pstroe/roberta-base-latin-cased},
urldate = {YYYY-MM-DD}
}