| | --- |
| | language: |
| | - da |
| | - en |
| | - fo |
| | - gmq |
| | - is |
| | - nb |
| | - nn |
| | - false |
| | - sv |
| | tags: |
| | - translation |
| | - opus-mt-tc |
| | license: cc-by-4.0 |
| | model-index: |
| | - name: opus-mt-tc-big-gmq-en |
| | results: |
| | - task: |
| | name: Translation dan-eng |
| | type: translation |
| | args: dan-eng |
| | dataset: |
| | name: flores101-devtest |
| | type: flores_101 |
| | args: dan eng devtest |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 49.3 |
| | - task: |
| | name: Translation isl-eng |
| | type: translation |
| | args: isl-eng |
| | dataset: |
| | name: flores101-devtest |
| | type: flores_101 |
| | args: isl eng devtest |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 34.2 |
| | - task: |
| | name: Translation nob-eng |
| | type: translation |
| | args: nob-eng |
| | dataset: |
| | name: flores101-devtest |
| | type: flores_101 |
| | args: nob eng devtest |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 44.2 |
| | - task: |
| | name: Translation swe-eng |
| | type: translation |
| | args: swe-eng |
| | dataset: |
| | name: flores101-devtest |
| | type: flores_101 |
| | args: swe eng devtest |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 49.8 |
| | - task: |
| | name: Translation isl-eng |
| | type: translation |
| | args: isl-eng |
| | dataset: |
| | name: newsdev2021.is-en |
| | type: newsdev2021.is-en |
| | args: isl-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 30.4 |
| | - task: |
| | name: Translation dan-eng |
| | type: translation |
| | args: dan-eng |
| | dataset: |
| | name: tatoeba-test-v2021-08-07 |
| | type: tatoeba_mt |
| | args: dan-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 65.9 |
| | - task: |
| | name: Translation fao-eng |
| | type: translation |
| | args: fao-eng |
| | dataset: |
| | name: tatoeba-test-v2021-08-07 |
| | type: tatoeba_mt |
| | args: fao-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 30.1 |
| | - task: |
| | name: Translation isl-eng |
| | type: translation |
| | args: isl-eng |
| | dataset: |
| | name: tatoeba-test-v2021-08-07 |
| | type: tatoeba_mt |
| | args: isl-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 53.3 |
| | - task: |
| | name: Translation nno-eng |
| | type: translation |
| | args: nno-eng |
| | dataset: |
| | name: tatoeba-test-v2021-08-07 |
| | type: tatoeba_mt |
| | args: nno-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 56.1 |
| | - task: |
| | name: Translation nob-eng |
| | type: translation |
| | args: nob-eng |
| | dataset: |
| | name: tatoeba-test-v2021-08-07 |
| | type: tatoeba_mt |
| | args: nob-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 60.2 |
| | - task: |
| | name: Translation swe-eng |
| | type: translation |
| | args: swe-eng |
| | dataset: |
| | name: tatoeba-test-v2021-08-07 |
| | type: tatoeba_mt |
| | args: swe-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 66.4 |
| | - task: |
| | name: Translation isl-eng |
| | type: translation |
| | args: isl-eng |
| | dataset: |
| | name: newstest2021.is-en |
| | type: wmt-2021-news |
| | args: isl-eng |
| | metrics: |
| | - name: BLEU |
| | type: bleu |
| | value: 34.4 |
| | --- |
| | # opus-mt-tc-big-gmq-en |
| |
|
| | Neural machine translation model for translating from North Germanic languages (gmq) to English (en). |
| |
|
| | 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: 2022-03-09 |
| | * source language(s): dan fao isl nno nob nor swe |
| | * target language(s): eng |
| | * model: transformer-big |
| | * data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) |
| | * tokenization: SentencePiece (spm32k,spm32k) |
| | * original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-eng/opusTCv20210807+bt_transformer-big_2022-03-09.zip) |
| | * more information released models: [OPUS-MT gmq-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmq-eng/README.md) |
| |
|
| | ## Usage |
| |
|
| | A short example code: |
| |
|
| | ```python |
| | from transformers import MarianMTModel, MarianTokenizer |
| | |
| | src_text = [ |
| | "Han var synligt nervøs.", |
| | "Inte ens Tom själv var övertygad." |
| | ] |
| | |
| | model_name = "pytorch-models/opus-mt-tc-big-gmq-en" |
| | 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: |
| | # He was visibly nervous. |
| | # Even Tom was not convinced. |
| | ``` |
| |
|
| | 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-gmq-en") |
| | print(pipe("Han var synligt nervøs.")) |
| | |
| | # expected output: He was visibly nervous. |
| | ``` |
| |
|
| | ## Benchmarks |
| |
|
| | * test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-eng/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt) |
| | * test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-eng/opusTCv20210807+bt_transformer-big_2022-03-09.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 | |
| | |----------|---------|-------|-------|-------|--------| |
| | | dan-eng | tatoeba-test-v2021-08-07 | 0.78292 | 65.9 | 10795 | 79684 | |
| | | fao-eng | tatoeba-test-v2021-08-07 | 0.47467 | 30.1 | 294 | 1984 | |
| | | isl-eng | tatoeba-test-v2021-08-07 | 0.68346 | 53.3 | 2503 | 19788 | |
| | | nno-eng | tatoeba-test-v2021-08-07 | 0.69788 | 56.1 | 460 | 3524 | |
| | | nob-eng | tatoeba-test-v2021-08-07 | 0.73524 | 60.2 | 4539 | 36823 | |
| | | swe-eng | tatoeba-test-v2021-08-07 | 0.77665 | 66.4 | 10362 | 68513 | |
| | | dan-eng | flores101-devtest | 0.72322 | 49.3 | 1012 | 24721 | |
| | | isl-eng | flores101-devtest | 0.59616 | 34.2 | 1012 | 24721 | |
| | | nob-eng | flores101-devtest | 0.68224 | 44.2 | 1012 | 24721 | |
| | | swe-eng | flores101-devtest | 0.72042 | 49.8 | 1012 | 24721 | |
| | | isl-eng | newsdev2021.is-en | 0.56709 | 30.4 | 2004 | 46383 | |
| | | isl-eng | newstest2021.is-en | 0.57756 | 34.4 | 1000 | 22529 | |
| |
|
| | ## 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: 3405783 |
| | * port time: Wed Apr 13 19:13:11 EEST 2022 |
| | * port machine: LM0-400-22516.local |
| |
|
