--- language: - orv - cu tags: - masked-language-modeling - old-slavonic - old-russian - birchbark - historical-nlp - dual-embeddings license: apache-2.0 --- # DualEmbLM A masked language model trained from scratch on Old East Slavic and Old Church Slavonic texts, with dual character-level + word-level embeddings. ## Architecture DualEmbLM combines: - **Character-level tokenisation** (1 character = 1 token) — enables precise lacuna restoration at the character level - **Word-level context embeddings** — provides morphological and lexical context via a 50k word vocabulary - **Transformer encoder** (BERT architecture, trained from scratch) — 6 layers, hidden size 512, 8 attention heads The dual embeddings are concatenated and projected into the shared hidden space before being passed to the transformer encoder. ## Training The model was trained on a corpus of Old Russian and Church Slavonic texts assembled from the following sources: | Source | Language | Word Tokens | Link | |--------|----------|--------|------| | Birchbark manuscripts | Old Novgorodian (mostly) | 21,464 | [gramoty.ru](https://gramoty.ru) | | Epigraphy | Old Church Slavonic (mostly) | 8,102 | [epigraphica.ru](https://epigraphica.ru) | | DIACU | Old Church Slavonic; Church Slavonic (Old Russian, Middle Bulgarian, Serbian, Resava recensions); Middle Russian | 1,683,307 | [ACL Anthology](https://aclanthology.org/2025.bsnlp-1.12/) | | TOROT | Old Russian; Church Slavonic | 682,430 | [torottreebank.github.io](https://torottreebank.github.io) | | Bible (Ponomar) | Church Slavonic | 603,047 | [GitHub](https://github.com/typiconman/ponomar/tree/master/Ponomar/languages/cu/bible/elis) | | Byliny | Old Russian (XI–XVII c.) | 430,103 | [rusneb.ru](https://rusneb.ru/catalog/000199_000009_003636356/) | | Pushkin House | Old Russian | 256,503 | [lib2.pushkinskijdom.ru](https://lib2.pushkinskijdom.ru) | | Military Statute (Part 2) | Old Russian | 49,787 | [rusneb.ru](https://rusneb.ru/catalog/000199_000009_004093983/) | | NKRYA (historical) | Old Russian; Old Rus (XI–XVIII c.) | 42,412 | [ruscorpora.ru](https://ruscorpora.ru) | Masking details: MLM probability 8%, span masking, edge masking, random gap augmentation. ## Usage ```python from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained( "MaximEremeev/DualEmb-slav", trust_remote_code=True, ) ``` ## Tasks - **Generated lacunae restoration** (Test A Hit@1: 0.817, CER: 0.183) - **Real lacunae restoration** (Test B char Hit@1: 0.466, span Hit@1: 0.222) ## Contact Maxim Eremeev, maeremeev@edu.hse.ru