upstream-archive byte-perfect snapshot of Helsinki-NLP/opus-mt-tc-big-zle-zle (ADR-039 Phase D)
ce61c0d verified | language: | |
| - be | |
| - ru | |
| - uk | |
| - zle | |
| tags: | |
| - translation | |
| - opus-mt-tc | |
| license: cc-by-4.0 | |
| model-index: | |
| - name: opus-mt-tc-big-zle-zle | |
| results: | |
| - task: | |
| name: Translation rus-ukr | |
| type: translation | |
| args: rus-ukr | |
| dataset: | |
| name: flores101-devtest | |
| type: flores_101 | |
| args: rus ukr devtest | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 25.5 | |
| - task: | |
| name: Translation ukr-rus | |
| type: translation | |
| args: ukr-rus | |
| dataset: | |
| name: flores101-devtest | |
| type: flores_101 | |
| args: ukr rus devtest | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 28.3 | |
| - task: | |
| name: Translation bel-rus | |
| type: translation | |
| args: bel-rus | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: bel-rus | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 68.6 | |
| - task: | |
| name: Translation bel-ukr | |
| type: translation | |
| args: bel-ukr | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: bel-ukr | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 65.5 | |
| - task: | |
| name: Translation rus-bel | |
| type: translation | |
| args: rus-bel | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: rus-bel | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 50.3 | |
| - task: | |
| name: Translation rus-ukr | |
| type: translation | |
| args: rus-ukr | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: rus-ukr | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 70.1 | |
| - task: | |
| name: Translation ukr-bel | |
| type: translation | |
| args: ukr-bel | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: ukr-bel | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 58.9 | |
| - task: | |
| name: Translation ukr-rus | |
| type: translation | |
| args: ukr-rus | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: ukr-rus | |
| metrics: | |
| - name: BLEU | |
| type: bleu | |
| value: 75.7 | |
| # opus-mt-tc-big-zle-zle | |
| Neural machine translation model for translating from East Slavic languages (zle) to East Slavic languages (zle). | |
| This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). | |
| * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) | |
| ``` | |
| @inproceedings{tiedemann-thottingal-2020-opus, | |
| title = "{OPUS}-{MT} {--} Building open translation services for the World", | |
| author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, | |
| booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", | |
| month = nov, | |
| year = "2020", | |
| address = "Lisboa, Portugal", | |
| publisher = "European Association for Machine Translation", | |
| url = "https://aclanthology.org/2020.eamt-1.61", | |
| pages = "479--480", | |
| } | |
| @inproceedings{tiedemann-2020-tatoeba, | |
| title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", | |
| author = {Tiedemann, J{\"o}rg}, | |
| booktitle = "Proceedings of the Fifth Conference on Machine Translation", | |
| month = nov, | |
| year = "2020", | |
| address = "Online", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2020.wmt-1.139", | |
| pages = "1174--1182", | |
| } | |
| ``` | |
| ## Model info | |
| * Release: 2022-03-07 | |
| * source language(s): bel rus ukr | |
| * target language(s): bel rus ukr | |
| * valid target language labels: >>bel<< >>rus<< >>ukr<< | |
| * model: transformer-big | |
| * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) | |
| * tokenization: SentencePiece (spm32k,spm32k) | |
| * original model: [opusTCv20210807+bt_transformer-big_2022-03-07.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zle/opusTCv20210807+bt_transformer-big_2022-03-07.zip) | |
| * more information released models: [OPUS-MT zle-zle README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zle-zle/README.md) | |
| * more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian) | |
| This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>bel<<` | |
| ## Usage | |
| A short example code: | |
| ```python | |
| from transformers import MarianMTModel, MarianTokenizer | |
| src_text = [ | |
| ">>ukr<< Кот мёртвый.", | |
| ">>bel<< Джон живе в Нью-Йорку." | |
| ] | |
| model_name = "pytorch-models/opus-mt-tc-big-zle-zle" | |
| tokenizer = MarianTokenizer.from_pretrained(model_name) | |
| model = MarianMTModel.from_pretrained(model_name) | |
| translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) | |
| for t in translated: | |
| print( tokenizer.decode(t, skip_special_tokens=True) ) | |
| # expected output: | |
| # Кіт мертвий. | |
| # Джон жыве ў Нью-Йорку. | |
| ``` | |
| You can also use OPUS-MT models with the transformers pipelines, for example: | |
| ```python | |
| from transformers import pipeline | |
| pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-zle-zle") | |
| print(pipe(">>ukr<< Кот мёртвый.")) | |
| # expected output: Кіт мертвий. | |
| ``` | |
| ## Benchmarks | |
| * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-07.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zle/opusTCv20210807+bt_transformer-big_2022-03-07.test.txt) | |
| * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-07.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zle/opusTCv20210807+bt_transformer-big_2022-03-07.eval.txt) | |
| * benchmark results: [benchmark_results.txt](benchmark_results.txt) | |
| * benchmark output: [benchmark_translations.zip](benchmark_translations.zip) | |
| | langpair | testset | chr-F | BLEU | #sent | #words | | |
| |----------|---------|-------|-------|-------|--------| | |
| | bel-rus | tatoeba-test-v2021-08-07 | 0.82526 | 68.6 | 2500 | 18895 | | |
| | bel-ukr | tatoeba-test-v2021-08-07 | 0.81036 | 65.5 | 2355 | 15179 | | |
| | rus-bel | tatoeba-test-v2021-08-07 | 0.66943 | 50.3 | 2500 | 18756 | | |
| | rus-ukr | tatoeba-test-v2021-08-07 | 0.83639 | 70.1 | 10000 | 60212 | | |
| | ukr-bel | tatoeba-test-v2021-08-07 | 0.75368 | 58.9 | 2355 | 15175 | | |
| | ukr-rus | tatoeba-test-v2021-08-07 | 0.86806 | 75.7 | 10000 | 60387 | | |
| | bel-rus | flores101-devtest | 0.47960 | 14.5 | 1012 | 23295 | | |
| | bel-ukr | flores101-devtest | 0.47335 | 12.8 | 1012 | 22810 | | |
| | rus-ukr | flores101-devtest | 0.55287 | 25.5 | 1012 | 22810 | | |
| | ukr-rus | flores101-devtest | 0.56224 | 28.3 | 1012 | 23295 | | |
| ## Acknowledgements | |
| The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. | |
| ## Model conversion info | |
| * transformers version: 4.16.2 | |
| * OPUS-MT git hash: 1bdabf7 | |
| * port time: Thu Mar 24 00:15:39 EET 2022 | |
| * port machine: LM0-400-22516.local | |