| language: | |
| - uk | |
| # ukr-roberta-base | |
| ## Pre-training corpora | |
| Below is the list of corpora used along with the output of wc command (counting lines, words and characters). These corpora were concatenated and tokenized with HuggingFace Roberta Tokenizer. | |
| | Tables | Lines | Words | Characters | | |
| | ------------- |--------------:| -----:| -----:| | |
| | [Ukrainian Wikipedia - May 2020](https://dumps.wikimedia.org/ukwiki/latest/ukwiki-latest-pages-articles.xml.bz2) | 18 001 466| 201 207 739 | 2 647 891 947 | | |
| | [Ukrainian OSCAR deduplicated dataset](https://oscar-public.huma-num.fr/shuffled/uk_dedup.txt.gz) | 56 560 011 | 2 250 210 650 | 29 705 050 592 | | |
| | Sampled mentions from social networks | 11 245 710 | 128 461 796 | 1 632 567 763 | | |
| | Total | 85 807 187 | 2 579 880 185 | 33 985 510 302 | | |
| ## Pre-training details | |
| * Ukrainian Roberta was trained with code provided in [HuggingFace tutorial](https://huggingface.co/blog/how-to-train) | |
| * Currently released model follows roberta-base-cased model architecture (12-layer, 768-hidden, 12-heads, 125M parameters) | |
| * The model was trained on 4xV100 (85 hours) | |
| * Training configuration you can find in the [original repository](https://github.com/youscan/language-models) | |
| ## Author | |
| Vitalii Radchenko - contact me on Twitter [@vitaliradchenko](https://twitter.com/vitaliradchenko) | |