README.md

---
library_name: transformers
language:
- chm
- de
- en
- es
- et
- fi
- fkv
- fr
- hu
- izh
- krl
- kv
- liv
- mdf
- mrj
- myv
- pt
- se
- sma
- smn
- udm
- vep
- vot

tags:
- translation
- opus-mt-tc-bible

license: apache-2.0
model-index:
- name: opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa
  results:
  - task:
      name: Translation est-deu
      type: translation
      args: est-deu
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: est-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 26.3
       - name: chr-F
         type: chrf
         value: 0.55825
  - task:
      name: Translation est-eng
      type: translation
      args: est-eng
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: est-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 35.4
       - name: chr-F
         type: chrf
         value: 0.62404
  - task:
      name: Translation est-fra
      type: translation
      args: est-fra
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: est-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 31.7
       - name: chr-F
         type: chrf
         value: 0.58580
  - task:
      name: Translation est-por
      type: translation
      args: est-por
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: est-por
    metrics:
       - name: BLEU
         type: bleu
         value: 27.3
       - name: chr-F
         type: chrf
         value: 0.55070
  - task:
      name: Translation est-spa
      type: translation
      args: est-spa
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: est-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 21.5
       - name: chr-F
         type: chrf
         value: 0.50188
  - task:
      name: Translation fin-deu
      type: translation
      args: fin-deu
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: fin-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 24.0
       - name: chr-F
         type: chrf
         value: 0.54281
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 33.1
       - name: chr-F
         type: chrf
         value: 0.60642
  - task:
      name: Translation fin-fra
      type: translation
      args: fin-fra
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: fin-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 30.5
       - name: chr-F
         type: chrf
         value: 0.57540
  - task:
      name: Translation fin-por
      type: translation
      args: fin-por
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: fin-por
    metrics:
       - name: BLEU
         type: bleu
         value: 27.4
       - name: chr-F
         type: chrf
         value: 0.55497
  - task:
      name: Translation fin-spa
      type: translation
      args: fin-spa
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: fin-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 21.4
       - name: chr-F
         type: chrf
         value: 0.49847
  - task:
      name: Translation hun-deu
      type: translation
      args: hun-deu
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: hun-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 25.1
       - name: chr-F
         type: chrf
         value: 0.55180
  - task:
      name: Translation hun-eng
      type: translation
      args: hun-eng
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: hun-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 34.0
       - name: chr-F
         type: chrf
         value: 0.61466
  - task:
      name: Translation hun-fra
      type: translation
      args: hun-fra
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: hun-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 30.6
       - name: chr-F
         type: chrf
         value: 0.57670
  - task:
      name: Translation hun-por
      type: translation
      args: hun-por
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: hun-por
    metrics:
       - name: BLEU
         type: bleu
         value: 28.9
       - name: chr-F
         type: chrf
         value: 0.56510
  - task:
      name: Translation hun-spa
      type: translation
      args: hun-spa
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: hun-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 21.3
       - name: chr-F
         type: chrf
         value: 0.49681
  - task:
      name: Translation est-deu
      type: translation
      args: est-deu
    dataset:
      name: flores101-devtest
      type: flores_101
      args: est deu devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 25.7
       - name: chr-F
         type: chrf
         value: 0.55353
  - task:
      name: Translation est-eng
      type: translation
      args: est-eng
    dataset:
      name: flores101-devtest
      type: flores_101
      args: est eng devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 34.7
       - name: chr-F
         type: chrf
         value: 0.61930
  - task:
      name: Translation est-fra
      type: translation
      args: est-fra
    dataset:
      name: flores101-devtest
      type: flores_101
      args: est fra devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 31.3
       - name: chr-F
         type: chrf
         value: 0.58199
  - task:
      name: Translation est-por
      type: translation
      args: est-por
    dataset:
      name: flores101-devtest
      type: flores_101
      args: est por devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 26.5
       - name: chr-F
         type: chrf
         value: 0.54388
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: flores101-devtest
      type: flores_101
      args: fin eng devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 32.2
       - name: chr-F
         type: chrf
         value: 0.59914
  - task:
      name: Translation fin-por
      type: translation
      args: fin-por
    dataset:
      name: flores101-devtest
      type: flores_101
      args: fin por devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 27.1
       - name: chr-F
         type: chrf
         value: 0.55156
  - task:
      name: Translation hun-eng
      type: translation
      args: hun-eng
    dataset:
      name: flores101-devtest
      type: flores_101
      args: hun eng devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 33.5
       - name: chr-F
         type: chrf
         value: 0.61198
  - task:
      name: Translation hun-fra
      type: translation
      args: hun-fra
    dataset:
      name: flores101-devtest
      type: flores_101
      args: hun fra devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 30.8
       - name: chr-F
         type: chrf
         value: 0.57776
  - task:
      name: Translation hun-por
      type: translation
      args: hun-por
    dataset:
      name: flores101-devtest
      type: flores_101
      args: hun por devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 28.4
       - name: chr-F
         type: chrf
         value: 0.56263
  - task:
      name: Translation hun-spa
      type: translation
      args: hun-spa
    dataset:
      name: flores101-devtest
      type: flores_101
      args: hun spa devtest
    metrics:
       - name: BLEU
         type: bleu
         value: 20.7
       - name: chr-F
         type: chrf
         value: 0.49140
  - task:
      name: Translation est-deu
      type: translation
      args: est-deu
    dataset:
      name: ntrex128
      type: ntrex128
      args: est-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 21.4
       - name: chr-F
         type: chrf
         value: 0.51377
  - task:
      name: Translation est-eng
      type: translation
      args: est-eng
    dataset:
      name: ntrex128
      type: ntrex128
      args: est-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 29.9
       - name: chr-F
         type: chrf
         value: 0.58358
  - task:
      name: Translation est-fra
      type: translation
      args: est-fra
    dataset:
      name: ntrex128
      type: ntrex128
      args: est-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 24.9
       - name: chr-F
         type: chrf
         value: 0.52713
  - task:
      name: Translation est-por
      type: translation
      args: est-por
    dataset:
      name: ntrex128
      type: ntrex128
      args: est-por
    metrics:
       - name: BLEU
         type: bleu
         value: 22.2
       - name: chr-F
         type: chrf
         value: 0.50745
  - task:
      name: Translation est-spa
      type: translation
      args: est-spa
    dataset:
      name: ntrex128
      type: ntrex128
      args: est-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 27.5
       - name: chr-F
         type: chrf
         value: 0.54304
  - task:
      name: Translation fin-deu
      type: translation
      args: fin-deu
    dataset:
      name: ntrex128
      type: ntrex128
      args: fin-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 19.8
       - name: chr-F
         type: chrf
         value: 0.50282
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: ntrex128
      type: ntrex128
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 26.3
       - name: chr-F
         type: chrf
         value: 0.55545
  - task:
      name: Translation fin-fra
      type: translation
      args: fin-fra
    dataset:
      name: ntrex128
      type: ntrex128
      args: fin-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 22.9
       - name: chr-F
         type: chrf
         value: 0.50946
  - task:
      name: Translation fin-por
      type: translation
      args: fin-por
    dataset:
      name: ntrex128
      type: ntrex128
      args: fin-por
    metrics:
       - name: BLEU
         type: bleu
         value: 21.3
       - name: chr-F
         type: chrf
         value: 0.50404
  - task:
      name: Translation fin-spa
      type: translation
      args: fin-spa
    dataset:
      name: ntrex128
      type: ntrex128
      args: fin-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 25.5
       - name: chr-F
         type: chrf
         value: 0.52641
  - task:
      name: Translation hun-deu
      type: translation
      args: hun-deu
    dataset:
      name: ntrex128
      type: ntrex128
      args: hun-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 18.5
       - name: chr-F
         type: chrf
         value: 0.49322
  - task:
      name: Translation hun-eng
      type: translation
      args: hun-eng
    dataset:
      name: ntrex128
      type: ntrex128
      args: hun-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 23.3
       - name: chr-F
         type: chrf
         value: 0.52964
  - task:
      name: Translation hun-fra
      type: translation
      args: hun-fra
    dataset:
      name: ntrex128
      type: ntrex128
      args: hun-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 21.8
       - name: chr-F
         type: chrf
         value: 0.49800
  - task:
      name: Translation hun-por
      type: translation
      args: hun-por
    dataset:
      name: ntrex128
      type: ntrex128
      args: hun-por
    metrics:
       - name: BLEU
         type: bleu
         value: 20.5
       - name: chr-F
         type: chrf
         value: 0.48941
  - task:
      name: Translation hun-spa
      type: translation
      args: hun-spa
    dataset:
      name: ntrex128
      type: ntrex128
      args: hun-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 24.2
       - name: chr-F
         type: chrf
         value: 0.51123
  - task:
      name: Translation est-deu
      type: translation
      args: est-deu
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: est-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 53.9
       - name: chr-F
         type: chrf
         value: 0.69451
  - task:
      name: Translation est-eng
      type: translation
      args: est-eng
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: est-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 58.2
       - name: chr-F
         type: chrf
         value: 0.72437
  - task:
      name: Translation fin-deu
      type: translation
      args: fin-deu
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: fin-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 47.3
       - name: chr-F
         type: chrf
         value: 0.66025
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 53.7
       - name: chr-F
         type: chrf
         value: 0.69685
  - task:
      name: Translation fin-fra
      type: translation
      args: fin-fra
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: fin-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 48.3
       - name: chr-F
         type: chrf
         value: 0.65900
  - task:
      name: Translation fin-por
      type: translation
      args: fin-por
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: fin-por
    metrics:
       - name: BLEU
         type: bleu
         value: 54.0
       - name: chr-F
         type: chrf
         value: 0.72250
  - task:
      name: Translation fin-spa
      type: translation
      args: fin-spa
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: fin-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 52.1
       - name: chr-F
         type: chrf
         value: 0.69600
  - task:
      name: Translation hun-deu
      type: translation
      args: hun-deu
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: hun-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 41.1
       - name: chr-F
         type: chrf
         value: 0.62418
  - task:
      name: Translation hun-eng
      type: translation
      args: hun-eng
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: hun-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 48.7
       - name: chr-F
         type: chrf
         value: 0.65626
  - task:
      name: Translation hun-fra
      type: translation
      args: hun-fra
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: hun-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 50.3
       - name: chr-F
         type: chrf
         value: 0.66840
  - task:
      name: Translation hun-por
      type: translation
      args: hun-por
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: hun-por
    metrics:
       - name: BLEU
         type: bleu
         value: 43.1
       - name: chr-F
         type: chrf
         value: 0.65281
  - task:
      name: Translation hun-spa
      type: translation
      args: hun-spa
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: hun-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 48.7
       - name: chr-F
         type: chrf
         value: 0.67467
  - task:
      name: Translation multi-multi
      type: translation
      args: multi-multi
    dataset:
      name: tatoeba-test-v2020-07-28-v2023-09-26
      type: tatoeba_mt
      args: multi-multi
    metrics:
       - name: BLEU
         type: bleu
         value: 44.6
       - name: chr-F
         type: chrf
         value: 0.63895
  - task:
      name: Translation hun-deu
      type: translation
      args: hun-deu
    dataset:
      name: newstest2008
      type: wmt-2008-news
      args: hun-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 19.0
       - name: chr-F
         type: chrf
         value: 0.50164
  - task:
      name: Translation hun-eng
      type: translation
      args: hun-eng
    dataset:
      name: newstest2008
      type: wmt-2008-news
      args: hun-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 20.4
       - name: chr-F
         type: chrf
         value: 0.49802
  - task:
      name: Translation hun-fra
      type: translation
      args: hun-fra
    dataset:
      name: newstest2008
      type: wmt-2008-news
      args: hun-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 21.6
       - name: chr-F
         type: chrf
         value: 0.51012
  - task:
      name: Translation hun-spa
      type: translation
      args: hun-spa
    dataset:
      name: newstest2008
      type: wmt-2008-news
      args: hun-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 22.3
       - name: chr-F
         type: chrf
         value: 0.50719
  - task:
      name: Translation hun-deu
      type: translation
      args: hun-deu
    dataset:
      name: newstest2009
      type: wmt-2009-news
      args: hun-deu
    metrics:
       - name: BLEU
         type: bleu
         value: 18.6
       - name: chr-F
         type: chrf
         value: 0.49902
  - task:
      name: Translation hun-eng
      type: translation
      args: hun-eng
    dataset:
      name: newstest2009
      type: wmt-2009-news
      args: hun-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 22.3
       - name: chr-F
         type: chrf
         value: 0.50950
  - task:
      name: Translation hun-fra
      type: translation
      args: hun-fra
    dataset:
      name: newstest2009
      type: wmt-2009-news
      args: hun-fra
    metrics:
       - name: BLEU
         type: bleu
         value: 21.6
       - name: chr-F
         type: chrf
         value: 0.50742
  - task:
      name: Translation hun-spa
      type: translation
      args: hun-spa
    dataset:
      name: newstest2009
      type: wmt-2009-news
      args: hun-spa
    metrics:
       - name: BLEU
         type: bleu
         value: 22.2
       - name: chr-F
         type: chrf
         value: 0.50788
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: newstest2015
      type: wmt-2015-news
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 27.0
       - name: chr-F
         type: chrf
         value: 0.55249
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: newstest2016
      type: wmt-2016-news
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 30.7
       - name: chr-F
         type: chrf
         value: 0.57961
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: newstest2017
      type: wmt-2017-news
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 33.2
       - name: chr-F
         type: chrf
         value: 0.59973
  - task:
      name: Translation est-eng
      type: translation
      args: est-eng
    dataset:
      name: newstest2018
      type: wmt-2018-news
      args: est-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 31.5
       - name: chr-F
         type: chrf
         value: 0.59190
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: newstest2018
      type: wmt-2018-news
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 24.4
       - name: chr-F
         type: chrf
         value: 0.52373
  - task:
      name: Translation fin-eng
      type: translation
      args: fin-eng
    dataset:
      name: newstest2019
      type: wmt-2019-news
      args: fin-eng
    metrics:
       - name: BLEU
         type: bleu
         value: 30.3
       - name: chr-F
         type: chrf
         value: 0.57079
---
# opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa

## 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 Finno-Ugrian languages (fiu) to unknown (deu+eng+fra+por+spa).

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**: 2024-05-30
- **License:** Apache-2.0
- **Language(s):**  
  - Source Language(s): chm est fin fkv hun izh koi kom kpv krl liv mdf mrj myv sma sme smn udm vep vot vro
  - Target Language(s): deu eng fra por spa
  - Valid Target Language Labels: >>deu<< >>eng<< >>fra<< >>por<< >>spa<< >>xxx<<
- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
- **Resources for more information:**
  -  [OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/fiu-deu%2Beng%2Bfra%2Bpor%2Bspa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
  - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
  - [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/)
  - [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
  - [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)

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. `>>deu<<`

## 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 = [
    ">>deu<< Replace this with text in an accepted source language.",
    ">>spa<< This is the second sentence."
]

model_name = "pytorch-models/opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa"
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) )
```

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-bible-big-fiu-deu_eng_fra_por_spa")
print(pipe(">>deu<< Replace this with text in an accepted source language."))
```

## Training

- **Data**: opusTCv20230926max50+bt+jhubc ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
- **Pre-processing**: SentencePiece (spm32k,spm32k)
- **Model Type:**  transformer-big
- **Original MarianNMT Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)

## Evaluation

* [Model scores at the OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/fiu-deu%2Beng%2Bfra%2Bpor%2Bspa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
* test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt)
* test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.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 |
|----------|---------|-------|-------|-------|--------|
| est-deu | tatoeba-test-v2021-08-07 | 0.69451 | 53.9 | 244 | 1611 |
| est-eng | tatoeba-test-v2021-08-07 | 0.72437 | 58.2 | 1359 | 8811 |
| fin-deu | tatoeba-test-v2021-08-07 | 0.66025 | 47.3 | 2647 | 19163 |
| fin-eng | tatoeba-test-v2021-08-07 | 0.69685 | 53.7 | 10690 | 80552 |
| fin-fra | tatoeba-test-v2021-08-07 | 0.65900 | 48.3 | 1920 | 12193 |
| fin-por | tatoeba-test-v2021-08-07 | 0.72250 | 54.0 | 477 | 3021 |
| fin-spa | tatoeba-test-v2021-08-07 | 0.69600 | 52.1 | 2513 | 16912 |
| hun-deu | tatoeba-test-v2021-08-07 | 0.62418 | 41.1 | 15342 | 127344 |
| hun-eng | tatoeba-test-v2021-08-07 | 0.65626 | 48.7 | 13037 | 94699 |
| hun-fra | tatoeba-test-v2021-08-07 | 0.66840 | 50.3 | 2494 | 16914 |
| hun-por | tatoeba-test-v2021-08-07 | 0.65281 | 43.1 | 2500 | 16563 |
| hun-spa | tatoeba-test-v2021-08-07 | 0.67467 | 48.7 | 2500 | 16670 |
| est-deu | flores101-devtest | 0.55353 | 25.7 | 1012 | 25094 |
| est-eng | flores101-devtest | 0.61930 | 34.7 | 1012 | 24721 |
| est-fra | flores101-devtest | 0.58199 | 31.3 | 1012 | 28343 |
| est-por | flores101-devtest | 0.54388 | 26.5 | 1012 | 26519 |
| fin-eng | flores101-devtest | 0.59914 | 32.2 | 1012 | 24721 |
| fin-por | flores101-devtest | 0.55156 | 27.1 | 1012 | 26519 |
| hun-eng | flores101-devtest | 0.61198 | 33.5 | 1012 | 24721 |
| hun-fra | flores101-devtest | 0.57776 | 30.8 | 1012 | 28343 |
| hun-por | flores101-devtest | 0.56263 | 28.4 | 1012 | 26519 |
| hun-spa | flores101-devtest | 0.49140 | 20.7 | 1012 | 29199 |
| est-deu | flores200-devtest | 0.55825 | 26.3 | 1012 | 25094 |
| est-eng | flores200-devtest | 0.62404 | 35.4 | 1012 | 24721 |
| est-fra | flores200-devtest | 0.58580 | 31.7 | 1012 | 28343 |
| est-por | flores200-devtest | 0.55070 | 27.3 | 1012 | 26519 |
| est-spa | flores200-devtest | 0.50188 | 21.5 | 1012 | 29199 |
| fin-deu | flores200-devtest | 0.54281 | 24.0 | 1012 | 25094 |
| fin-eng | flores200-devtest | 0.60642 | 33.1 | 1012 | 24721 |
| fin-fra | flores200-devtest | 0.57540 | 30.5 | 1012 | 28343 |
| fin-por | flores200-devtest | 0.55497 | 27.4 | 1012 | 26519 |
| fin-spa | flores200-devtest | 0.49847 | 21.4 | 1012 | 29199 |
| hun-deu | flores200-devtest | 0.55180 | 25.1 | 1012 | 25094 |
| hun-eng | flores200-devtest | 0.61466 | 34.0 | 1012 | 24721 |
| hun-fra | flores200-devtest | 0.57670 | 30.6 | 1012 | 28343 |
| hun-por | flores200-devtest | 0.56510 | 28.9 | 1012 | 26519 |
| hun-spa | flores200-devtest | 0.49681 | 21.3 | 1012 | 29199 |
| hun-deu | newssyscomb2009 | 0.49819 | 17.9 | 502 | 11271 |
| hun-eng | newssyscomb2009 | 0.52063 | 24.4 | 502 | 11818 |
| hun-fra | newssyscomb2009 | 0.51589 | 22.0 | 502 | 12331 |
| hun-spa | newssyscomb2009 | 0.51508 | 22.7 | 502 | 12503 |
| hun-deu | newstest2008 | 0.50164 | 19.0 | 2051 | 47447 |
| hun-eng | newstest2008 | 0.49802 | 20.4 | 2051 | 49380 |
| hun-fra | newstest2008 | 0.51012 | 21.6 | 2051 | 52685 |
| hun-spa | newstest2008 | 0.50719 | 22.3 | 2051 | 52586 |
| hun-deu | newstest2009 | 0.49902 | 18.6 | 2525 | 62816 |
| hun-eng | newstest2009 | 0.50950 | 22.3 | 2525 | 65399 |
| hun-fra | newstest2009 | 0.50742 | 21.6 | 2525 | 69263 |
| hun-spa | newstest2009 | 0.50788 | 22.2 | 2525 | 68111 |
| fin-eng | newstest2015 | 0.55249 | 27.0 | 1370 | 27270 |
| fin-eng | newstest2016 | 0.57961 | 30.7 | 3000 | 62945 |
| fin-eng | newstest2017 | 0.59973 | 33.2 | 3002 | 61846 |
| est-eng | newstest2018 | 0.59190 | 31.5 | 2000 | 45405 |
| fin-eng | newstest2018 | 0.52373 | 24.4 | 3000 | 62325 |
| fin-eng | newstest2019 | 0.57079 | 30.3 | 1996 | 36215 |
| fin-eng | newstestB2017 | 0.56420 | 28.9 | 3002 | 61846 |
| est-deu | ntrex128 | 0.51377 | 21.4 | 1997 | 48761 |
| est-eng | ntrex128 | 0.58358 | 29.9 | 1997 | 47673 |
| est-fra | ntrex128 | 0.52713 | 24.9 | 1997 | 53481 |
| est-por | ntrex128 | 0.50745 | 22.2 | 1997 | 51631 |
| est-spa | ntrex128 | 0.54304 | 27.5 | 1997 | 54107 |
| fin-deu | ntrex128 | 0.50282 | 19.8 | 1997 | 48761 |
| fin-eng | ntrex128 | 0.55545 | 26.3 | 1997 | 47673 |
| fin-fra | ntrex128 | 0.50946 | 22.9 | 1997 | 53481 |
| fin-por | ntrex128 | 0.50404 | 21.3 | 1997 | 51631 |
| fin-spa | ntrex128 | 0.52641 | 25.5 | 1997 | 54107 |
| hun-deu | ntrex128 | 0.49322 | 18.5 | 1997 | 48761 |
| hun-eng | ntrex128 | 0.52964 | 23.3 | 1997 | 47673 |
| hun-fra | ntrex128 | 0.49800 | 21.8 | 1997 | 53481 |
| hun-por | ntrex128 | 0.48941 | 20.5 | 1997 | 51631 |
| hun-spa | ntrex128 | 0.51123 | 24.2 | 1997 | 54107 |

## Citation Information

* Publications: [Democratizing neural machine translation with OPUS-MT](https://doi.org/10.1007/s10579-023-09704-w) and [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.)

```bibtex
@article{tiedemann2023democratizing,
  title={Democratizing neural machine translation with {OPUS-MT}},
  author={Tiedemann, J{\"o}rg and Aulamo, Mikko and Bakshandaeva, Daria and Boggia, Michele and Gr{\"o}nroos, Stig-Arne and Nieminen, Tommi and Raganato, Alessandro and Scherrer, Yves and Vazquez, Raul and Virpioja, Sami},
  journal={Language Resources and Evaluation},
  number={58},
  pages={713--755},
  year={2023},
  publisher={Springer Nature},
  issn={1574-0218},
  doi={10.1007/s10579-023-09704-w}
}

@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 [HPLT project](https://hplt-project.org/), funded by the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland, and the [EuroHPC supercomputer LUMI](https://www.lumi-supercomputer.eu/).

## Model conversion info

* transformers version: 4.45.1
* OPUS-MT git hash: 0882077
* port time: Tue Oct  8 10:53:49 EEST 2024
* port machine: LM0-400-22516.local