--- language: - be - ca - es - fr - gl - it - pt - ro - ru - uk tags: - translation - opus-mt-tc license: cc-by-4.0 model-index: - name: opus-mt-tc-big-zle-itc results: - task: name: Translation bel-cat type: translation args: bel-cat dataset: name: flores101-devtest type: flores_101 args: bel cat devtest metrics: - name: BLEU type: bleu value: 16.8 - name: chr-F type: chrf value: 0.48374 - task: name: Translation bel-fra type: translation args: bel-fra dataset: name: flores101-devtest type: flores_101 args: bel fra devtest metrics: - name: BLEU type: bleu value: 19.4 - name: chr-F type: chrf value: 0.51278 - task: name: Translation bel-glg type: translation args: bel-glg dataset: name: flores101-devtest type: flores_101 args: bel glg devtest metrics: - name: BLEU type: bleu value: 15.3 - name: chr-F type: chrf value: 0.45665 - task: name: Translation bel-ita type: translation args: bel-ita dataset: name: flores101-devtest type: flores_101 args: bel ita devtest metrics: - name: BLEU type: bleu value: 14.6 - name: chr-F type: chrf value: 0.47204 - task: name: Translation bel-por type: translation args: bel-por dataset: name: flores101-devtest type: flores_101 args: bel por devtest metrics: - name: BLEU type: bleu value: 17.3 - name: chr-F type: chrf value: 0.49561 - task: name: Translation bel-ron type: translation args: bel-ron dataset: name: flores101-devtest type: flores_101 args: bel ron devtest metrics: - name: BLEU type: bleu value: 14.9 - name: chr-F type: chrf value: 0.46315 - task: name: Translation bel-spa type: translation args: bel-spa dataset: name: flores101-devtest type: flores_101 args: bel spa devtest metrics: - name: BLEU type: bleu value: 15.3 - name: chr-F type: chrf value: 0.46011 - task: name: Translation rus-ast type: translation args: rus-ast dataset: name: flores101-devtest type: flores_101 args: rus ast devtest metrics: - name: BLEU type: bleu value: 13.6 - name: chr-F type: chrf value: 0.45411 - task: name: Translation rus-cat type: translation args: rus-cat dataset: name: flores101-devtest type: flores_101 args: rus cat devtest metrics: - name: BLEU type: bleu value: 28.3 - name: chr-F type: chrf value: 0.55262 - task: name: Translation rus-fra type: translation args: rus-fra dataset: name: flores101-devtest type: flores_101 args: rus fra devtest metrics: - name: BLEU type: bleu value: 32.9 - name: chr-F type: chrf value: 0.59498 - task: name: Translation rus-glg type: translation args: rus-glg dataset: name: flores101-devtest type: flores_101 args: rus glg devtest metrics: - name: BLEU type: bleu value: 23.5 - name: chr-F type: chrf value: 0.51668 - task: name: Translation rus-ita type: translation args: rus-ita dataset: name: flores101-devtest type: flores_101 args: rus ita devtest metrics: - name: BLEU type: bleu value: 22.7 - name: chr-F type: chrf value: 0.52402 - task: name: Translation rus-oci type: translation args: rus-oci dataset: name: flores101-devtest type: flores_101 args: rus oci devtest metrics: - name: BLEU type: bleu value: 12.9 - name: chr-F type: chrf value: 0.42301 - task: name: Translation rus-por type: translation args: rus-por dataset: name: flores101-devtest type: flores_101 args: rus por devtest metrics: - name: BLEU type: bleu value: 31.4 - name: chr-F type: chrf value: 0.58045 - task: name: Translation rus-ron type: translation args: rus-ron dataset: name: flores101-devtest type: flores_101 args: rus ron devtest metrics: - name: BLEU type: bleu value: 24.7 - name: chr-F type: chrf value: 0.52560 - task: name: Translation rus-spa type: translation args: rus-spa dataset: name: flores101-devtest type: flores_101 args: rus spa devtest metrics: - name: BLEU type: bleu value: 21.8 - name: chr-F type: chrf value: 0.50622 - task: name: Translation ukr-ast type: translation args: ukr-ast dataset: name: flores101-devtest type: flores_101 args: ukr ast devtest metrics: - name: BLEU type: bleu value: 14.1 - name: chr-F type: chrf value: 0.45629 - task: name: Translation ukr-cat type: translation args: ukr-cat dataset: name: flores101-devtest type: flores_101 args: ukr cat devtest metrics: - name: BLEU type: bleu value: 29.5 - name: chr-F type: chrf value: 0.56383 - task: name: Translation ukr-fra type: translation args: ukr-fra dataset: name: flores101-devtest type: flores_101 args: ukr fra devtest metrics: - name: BLEU type: bleu value: 34.5 - name: chr-F type: chrf value: 0.60596 - task: name: Translation ukr-glg type: translation args: ukr-glg dataset: name: flores101-devtest type: flores_101 args: ukr glg devtest metrics: - name: BLEU type: bleu value: 24.2 - name: chr-F type: chrf value: 0.52217 - task: name: Translation ukr-ita type: translation args: ukr-ita dataset: name: flores101-devtest type: flores_101 args: ukr ita devtest metrics: - name: BLEU type: bleu value: 23.0 - name: chr-F type: chrf value: 0.52610 - task: name: Translation ukr-oci type: translation args: ukr-oci dataset: name: flores101-devtest type: flores_101 args: ukr oci devtest metrics: - name: BLEU type: bleu value: 13.7 - name: chr-F type: chrf value: 0.42937 - task: name: Translation ukr-por type: translation args: ukr-por dataset: name: flores101-devtest type: flores_101 args: ukr por devtest metrics: - name: BLEU type: bleu value: 32.5 - name: chr-F type: chrf value: 0.59036 - task: name: Translation ukr-ron type: translation args: ukr-ron dataset: name: flores101-devtest type: flores_101 args: ukr ron devtest metrics: - name: BLEU type: bleu value: 26.0 - name: chr-F type: chrf value: 0.53883 - task: name: Translation ukr-spa type: translation args: ukr-spa dataset: name: flores101-devtest type: flores_101 args: ukr spa devtest metrics: - name: BLEU type: bleu value: 22.5 - name: chr-F type: chrf value: 0.51018 - task: name: Translation bel-fra type: translation args: bel-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: bel-fra metrics: - name: BLEU type: bleu value: 49.1 - name: chr-F type: chrf value: 0.66784 - task: name: Translation bel-ita type: translation args: bel-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: bel-ita metrics: - name: BLEU type: bleu value: 47.6 - name: chr-F type: chrf value: 0.64145 - task: name: Translation bel-spa type: translation args: bel-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: bel-spa metrics: - name: BLEU type: bleu value: 46.9 - name: chr-F type: chrf value: 0.65485 - task: name: Translation rus-fra type: translation args: rus-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: rus-fra metrics: - name: BLEU type: bleu value: 52.1 - name: chr-F type: chrf value: 0.68174 - task: name: Translation rus-ita type: translation args: rus-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: rus-ita metrics: - name: BLEU type: bleu value: 42.7 - name: chr-F type: chrf value: 0.63277 - task: name: Translation rus-por type: translation args: rus-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: rus-por metrics: - name: BLEU type: bleu value: 42.6 - name: chr-F type: chrf value: 0.63606 - task: name: Translation rus-ron type: translation args: rus-ron dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: rus-ron metrics: - name: BLEU type: bleu value: 37.5 - name: chr-F type: chrf value: 0.60796 - task: name: Translation rus-spa type: translation args: rus-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: rus-spa metrics: - name: BLEU type: bleu value: 51.3 - name: chr-F type: chrf value: 0.69108 - task: name: Translation ukr-cat type: translation args: ukr-cat dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ukr-cat metrics: - name: BLEU type: bleu value: 52.9 - name: chr-F type: chrf value: 0.69275 - task: name: Translation ukr-fra type: translation args: ukr-fra dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ukr-fra metrics: - name: BLEU type: bleu value: 51.3 - name: chr-F type: chrf value: 0.67392 - task: name: Translation ukr-ita type: translation args: ukr-ita dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ukr-ita metrics: - name: BLEU type: bleu value: 49.6 - name: chr-F type: chrf value: 0.69157 - task: name: Translation ukr-por type: translation args: ukr-por dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ukr-por metrics: - name: BLEU type: bleu value: 45.0 - name: chr-F type: chrf value: 0.64722 - task: name: Translation ukr-spa type: translation args: ukr-spa dataset: name: tatoeba-test-v2021-08-07 type: tatoeba_mt args: ukr-spa metrics: - name: BLEU type: bleu value: 50.7 - name: chr-F type: chrf value: 0.68409 - task: name: Translation rus-fra type: translation args: rus-fra dataset: name: newstest2012 type: wmt-2012-news args: rus-fra metrics: - name: BLEU type: bleu value: 25.0 - name: chr-F type: chrf value: 0.53481 - task: name: Translation rus-spa type: translation args: rus-spa dataset: name: newstest2012 type: wmt-2012-news args: rus-spa metrics: - name: BLEU type: bleu value: 28.7 - name: chr-F type: chrf value: 0.54814 - task: name: Translation rus-fra type: translation args: rus-fra dataset: name: newstest2013 type: wmt-2013-news args: rus-fra metrics: - name: BLEU type: bleu value: 29.0 - name: chr-F type: chrf value: 0.55745 - task: name: Translation rus-spa type: translation args: rus-spa dataset: name: newstest2013 type: wmt-2013-news args: rus-spa metrics: - name: BLEU type: bleu value: 31.5 - name: chr-F type: chrf value: 0.56582 --- # opus-mt-tc-big-zle-itc ## Table of Contents - [Model Details](#model-details) - [Uses](#uses) - [Risks, Limitations and Biases](#risks-limitations-and-biases) - [How to Get Started With the Model](#how-to-get-started-with-the-model) - [Training](#training) - [Evaluation](#evaluation) - [Citation Information](#citation-information) - [Acknowledgements](#acknowledgements) ## Model Details Neural machine translation model for translating from East Slavic languages (zle) to Italic languages (itc). 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). **Model Description:** - **Developed by:** Language Technology Research Group at the University of Helsinki - **Model Type:** Translation (transformer-big) - **Release**: 2022-08-03 - **License:** CC-BY-4.0 - **Language(s):** - Source Language(s): bel rue rus ukr - Target Language(s): cat fra glg ita lad_Latn por ron spa - Language Pair(s): bel-fra bel-ita bel-spa rus-cat rus-fra rus-glg rus-ita rus-por rus-ron rus-spa ukr-cat ukr-fra ukr-glg ukr-ita ukr-por ukr-ron ukr-spa - Valid Target Language Labels: >>acf<< >>aoa<< >>arg<< >>ast<< >>cat<< >>cbk<< >>ccd<< >>cks<< >>cos<< >>cri<< >>crs<< >>dlm<< >>drc<< >>egl<< >>ext<< >>fab<< >>fax<< >>fra<< >>frc<< >>frm<< >>fro<< >>frp<< >>fur<< >>gcf<< >>gcf_Latn<< >>gcr<< >>glg<< >>hat<< >>idb<< >>ist<< >>ita<< >>itk<< >>kea<< >>kmv<< >>lad<< >>lad_Latn<< >>lat<< >>lat_Latn<< >>lij<< >>lld<< >>lmo<< >>lou<< >>mcm<< >>mfe<< >>mol<< >>mwl<< >>mxi<< >>mzs<< >>nap<< >>nrf<< >>oci<< >>osc<< >>osp<< >>osp_Latn<< >>pap<< >>pcd<< >>pln<< >>pms<< >>pob<< >>por<< >>pov<< >>pre<< >>pro<< >>qbb<< >>qhr<< >>rcf<< >>rgn<< >>roh<< >>ron<< >>ruo<< >>rup<< >>ruq<< >>scf<< >>scn<< >>sdc<< >>sdn<< >>spa<< >>spq<< >>spx<< >>src<< >>srd<< >>sro<< >>tmg<< >>tvy<< >>vec<< >>vkp<< >>wln<< >>xfa<< >>xum<< - **Original Model**: [opusTCv20210807_transformer-big_2022-08-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-itc/opusTCv20210807_transformer-big_2022-08-03.zip) - **Resources for more information:** - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) - More information about released models for this language pair: [OPUS-MT zle-itc README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zle-itc/README.md) - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian) - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/ 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. `>>cat<<` ## Uses This model can be used for translation and text-to-text generation. ## Risks, Limitations and Biases **CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.** Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). ## How to Get Started With the Model A short example code: ```python from transformers import MarianMTModel, MarianTokenizer src_text = [ ">>fra<< Вони не мої справжні батьки.", ">>por<< Мне нужно в школу." ] model_name = "pytorch-models/opus-mt-tc-big-zle-itc" 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: # Ce ne sont pas mes vrais parents. # Tenho de ir para a escola. ``` 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-itc") print(pipe(">>fra<< Вони не мої справжні батьки.")) # expected output: Ce ne sont pas mes vrais parents. ``` ## Training - **Data**: opusTCv20210807 ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) - **Pre-processing**: SentencePiece (spm32k,spm32k) - **Model Type:** transformer-big - **Original MarianNMT Model**: [opusTCv20210807_transformer-big_2022-08-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-itc/opusTCv20210807_transformer-big_2022-08-03.zip) - **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) ## Evaluation * test set translations: [opusTCv20210807_transformer-big_2022-08-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-itc/opusTCv20210807_transformer-big_2022-08-03.test.txt) * test set scores: [opusTCv20210807_transformer-big_2022-08-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-itc/opusTCv20210807_transformer-big_2022-08-03.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-fra | tatoeba-test-v2021-08-07 | 0.66784 | 49.1 | 283 | 2005 | | bel-ita | tatoeba-test-v2021-08-07 | 0.64145 | 47.6 | 264 | 1681 | | bel-spa | tatoeba-test-v2021-08-07 | 0.65485 | 46.9 | 205 | 1412 | | rus-fra | tatoeba-test-v2021-08-07 | 0.68174 | 52.1 | 11490 | 80579 | | rus-ita | tatoeba-test-v2021-08-07 | 0.63277 | 42.7 | 10045 | 71584 | | rus-por | tatoeba-test-v2021-08-07 | 0.63606 | 42.6 | 10000 | 74713 | | rus-ron | tatoeba-test-v2021-08-07 | 0.60796 | 37.5 | 782 | 4772 | | rus-spa | tatoeba-test-v2021-08-07 | 0.69108 | 51.3 | 10506 | 75246 | | ukr-cat | tatoeba-test-v2021-08-07 | 0.69275 | 52.9 | 456 | 2675 | | ukr-fra | tatoeba-test-v2021-08-07 | 0.67392 | 51.3 | 10035 | 63227 | | ukr-ita | tatoeba-test-v2021-08-07 | 0.69157 | 49.6 | 5000 | 27846 | | ukr-por | tatoeba-test-v2021-08-07 | 0.64722 | 45.0 | 3372 | 21315 | | ukr-spa | tatoeba-test-v2021-08-07 | 0.68409 | 50.7 | 10115 | 59284 | | bel-ast | flores101-devtest | 0.40942 | 8.7 | 1012 | 24572 | | bel-cat | flores101-devtest | 0.48374 | 16.8 | 1012 | 27304 | | bel-fra | flores101-devtest | 0.51278 | 19.4 | 1012 | 28343 | | bel-glg | flores101-devtest | 0.45665 | 15.3 | 1012 | 26582 | | bel-ita | flores101-devtest | 0.47204 | 14.6 | 1012 | 27306 | | bel-por | flores101-devtest | 0.49561 | 17.3 | 1012 | 26519 | | bel-ron | flores101-devtest | 0.46315 | 14.9 | 1012 | 26799 | | bel-spa | flores101-devtest | 0.46011 | 15.3 | 1012 | 29199 | | rus-ast | flores101-devtest | 0.45411 | 13.6 | 1012 | 24572 | | rus-cat | flores101-devtest | 0.55262 | 28.3 | 1012 | 27304 | | rus-fra | flores101-devtest | 0.59498 | 32.9 | 1012 | 28343 | | rus-glg | flores101-devtest | 0.51668 | 23.5 | 1012 | 26582 | | rus-ita | flores101-devtest | 0.52402 | 22.7 | 1012 | 27306 | | rus-oci | flores101-devtest | 0.42301 | 12.9 | 1012 | 27305 | | rus-por | flores101-devtest | 0.58045 | 31.4 | 1012 | 26519 | | rus-ron | flores101-devtest | 0.52560 | 24.7 | 1012 | 26799 | | rus-spa | flores101-devtest | 0.50622 | 21.8 | 1012 | 29199 | | ukr-ast | flores101-devtest | 0.45629 | 14.1 | 1012 | 24572 | | ukr-cat | flores101-devtest | 0.56383 | 29.5 | 1012 | 27304 | | ukr-fra | flores101-devtest | 0.60596 | 34.5 | 1012 | 28343 | | ukr-glg | flores101-devtest | 0.52217 | 24.2 | 1012 | 26582 | | ukr-ita | flores101-devtest | 0.52610 | 23.0 | 1012 | 27306 | | ukr-oci | flores101-devtest | 0.42937 | 13.7 | 1012 | 27305 | | ukr-por | flores101-devtest | 0.59036 | 32.5 | 1012 | 26519 | | ukr-ron | flores101-devtest | 0.53883 | 26.0 | 1012 | 26799 | | ukr-spa | flores101-devtest | 0.51018 | 22.5 | 1012 | 29199 | | rus-fra | newstest2012 | 0.53481 | 25.0 | 3003 | 78011 | | rus-spa | newstest2012 | 0.54814 | 28.7 | 3003 | 79006 | | rus-fra | newstest2013 | 0.55745 | 29.0 | 3000 | 70037 | | rus-spa | newstest2013 | 0.56582 | 31.5 | 3000 | 70528 | ## Citation Information * 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", } ``` ## 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: 8b9f0b0 * port time: Sat Aug 13 00:01:33 EEST 2022 * port machine: LM0-400-22516.local