transformers pytorch safetensors marian text2text-generation translation opus-mt-tc-bible anp as awa bho bn bpy de dv en es fr gbm gu hi hif hne hns kok ks lah mag mai mr ne or pa pi pt rhg rmy rom sa sd si skr syl ur license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
language:
- anp
- as
- awa
- bho
- bn
- bpy
- de
- dv
- en
- es
- fr
- gbm
- gu
- hi
- hif
- hne
- hns
- kok
- ks
- lah
- mag
- mai
- mr
- ne
- or
- pa
- pi
- pt
- rhg
- rmy
- rom
- sa
- sd
- si
- skr
- syl
- ur
library_name: transformers
license: apache-2.0
tags:
- translation
- opus-mt-tc-bible
model-index:
- name: opus-mt-tc-bible-big-inc-deu_eng_fra_por_spa
  results:
  - task:
      type: translation
      name: Translation asm-eng
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: asm-eng
    metrics:
    - type: bleu
      value: 21.9
      name: BLEU
    - type: chrf
      value: 0.48584
      name: chr-F
    - type: bleu
      value: 10.1
      name: BLEU
    - type: chrf
      value: 0.35028
      name: chr-F
    - type: bleu
      value: 16.5
      name: BLEU
    - type: chrf
      value: 0.47173
      name: chr-F
    - type: bleu
      value: 24.5
      name: BLEU
    - type: chrf
      value: 0.50582
      name: chr-F
    - type: bleu
      value: 21.4
      name: BLEU
    - type: chrf
      value: 0.49682
      name: chr-F
    - type: bleu
      value: 21.5
      name: BLEU
    - type: chrf
      value: 0.49663
      name: chr-F
    - type: bleu
      value: 15.1
      name: BLEU
    - type: chrf
      value: 0.4374
      name: chr-F
    - type: bleu
      value: 16.6
      name: BLEU
    - type: chrf
      value: 0.4733
      name: chr-F
    - type: bleu
      value: 30.5
      name: BLEU
    - type: chrf
      value: 0.58077
      name: chr-F
    - type: bleu
      value: 22.6
      name: BLEU
    - type: chrf
      value: 0.50884
      name: chr-F
    - type: bleu
      value: 21.4
      name: BLEU
    - type: chrf
      value: 0.50054
      name: chr-F
    - type: bleu
      value: 15.2
      name: BLEU
    - type: chrf
      value: 0.44159
      name: chr-F
    - type: bleu
      value: 12.6
      name: BLEU
    - type: chrf
      value: 0.4266
      name: chr-F
    - type: bleu
      value: 22.7
      name: BLEU
    - type: chrf
      value: 0.50609
      name: chr-F
    - type: bleu
      value: 16.8
      name: BLEU
    - type: chrf
      value: 0.44889
      name: chr-F
    - type: bleu
      value: 16.9
      name: BLEU
    - type: chrf
      value: 0.44582
      name: chr-F
    - type: bleu
      value: 13.1
      name: BLEU
    - type: chrf
      value: 0.40581
      name: chr-F
    - type: bleu
      value: 16.8
      name: BLEU
    - type: chrf
      value: 0.46665
      name: chr-F
    - type: bleu
      value: 34.3
      name: BLEU
    - type: chrf
      value: 0.61383
      name: chr-F
    - type: bleu
      value: 22.3
      name: BLEU
    - type: chrf
      value: 0.5041
      name: chr-F
    - type: bleu
      value: 21.3
      name: BLEU
    - type: chrf
      value: 0.49257
      name: chr-F
    - type: bleu
      value: 15.6
      name: BLEU
    - type: chrf
      value: 0.44565
      name: chr-F
    - type: bleu
      value: 20.4
      name: BLEU
    - type: chrf
      value: 0.50226
      name: chr-F
    - type: bleu
      value: 37.3
      name: BLEU
    - type: chrf
      value: 0.63336
      name: chr-F
    - type: bleu
      value: 25.9
      name: BLEU
    - type: chrf
      value: 0.53701
      name: chr-F
    - type: bleu
      value: 25.5
      name: BLEU
    - type: chrf
      value: 0.53448
      name: chr-F
    - type: bleu
      value: 17.2
      name: BLEU
    - type: chrf
      value: 0.46171
      name: chr-F
    - type: bleu
      value: 19.0
      name: BLEU
    - type: chrf
      value: 0.49698
      name: chr-F
    - type: bleu
      value: 38.5
      name: BLEU
    - type: chrf
      value: 0.63936
      name: chr-F
    - type: bleu
      value: 25.3
      name: BLEU
    - type: chrf
      value: 0.52835
      name: chr-F
    - type: bleu
      value: 25.0
      name: BLEU
    - type: chrf
      value: 0.52788
      name: chr-F
    - type: bleu
      value: 16.7
      name: BLEU
    - type: chrf
      value: 0.45443
      name: chr-F
    - type: bleu
      value: 19.7
      name: BLEU
    - type: chrf
      value: 0.50359
      name: chr-F
    - type: bleu
      value: 38.0
      name: BLEU
    - type: chrf
      value: 0.63906
      name: chr-F
    - type: bleu
      value: 25.8
      name: BLEU
    - type: chrf
      value: 0.53616
      name: chr-F
    - type: bleu
      value: 25.9
      name: BLEU
    - type: chrf
      value: 0.53537
      name: chr-F
    - type: bleu
      value: 16.9
      name: BLEU
    - type: chrf
      value: 0.45822
      name: chr-F
    - type: bleu
      value: 16.2
      name: BLEU
    - type: chrf
      value: 0.46791
      name: chr-F
    - type: bleu
      value: 30.4
      name: BLEU
    - type: chrf
      value: 0.57461
      name: chr-F
    - type: bleu
      value: 22.1
      name: BLEU
    - type: chrf
      value: 0.50585
      name: chr-F
    - type: bleu
      value: 22.0
      name: BLEU
    - type: chrf
      value: 0.5049
      name: chr-F
    - type: bleu
      value: 15.3
      name: BLEU
    - type: chrf
      value: 0.44366
      name: chr-F
    - type: bleu
      value: 14.5
      name: BLEU
    - type: chrf
      value: 0.44725
      name: chr-F
    - type: bleu
      value: 31.4
      name: BLEU
    - type: chrf
      value: 0.585
      name: chr-F
    - type: bleu
      value: 19.5
      name: BLEU
    - type: chrf
      value: 0.47027
      name: chr-F
    - type: bleu
      value: 19.3
      name: BLEU
    - type: chrf
      value: 0.47216
      name: chr-F
    - type: bleu
      value: 14.2
      name: BLEU
    - type: chrf
      value: 0.42178
      name: chr-F
    - type: bleu
      value: 16.4
      name: BLEU
    - type: chrf
      value: 0.46631
      name: chr-F
    - type: bleu
      value: 32.3
      name: BLEU
    - type: chrf
      value: 0.59776
      name: chr-F
    - type: bleu
      value: 22.5
      name: BLEU
    - type: chrf
      value: 0.50548
      name: chr-F
    - type: bleu
      value: 21.7
      name: BLEU
    - type: chrf
      value: 0.50202
      name: chr-F
    - type: bleu
      value: 15.3
      name: BLEU
    - type: chrf
      value: 0.43804
      name: chr-F
    - type: bleu
      value: 18.7
      name: BLEU
    - type: chrf
      value: 0.48421
      name: chr-F
    - type: bleu
      value: 33.8
      name: BLEU
    - type: chrf
      value: 0.60676
      name: chr-F
    - type: bleu
      value: 23.5
      name: BLEU
    - type: chrf
      value: 0.51368
      name: chr-F
    - type: bleu
      value: 22.7
      name: BLEU
    - type: chrf
      value: 0.50586
      name: chr-F
    - type: bleu
      value: 16.5
      name: BLEU
    - type: chrf
      value: 0.44653
      name: chr-F
    - type: bleu
      value: 11.8
      name: BLEU
    - type: chrf
      value: 0.36887
      name: chr-F
    - type: bleu
      value: 14.2
      name: BLEU
    - type: chrf
      value: 0.44676
      name: chr-F
    - type: bleu
      value: 26.8
      name: BLEU
    - type: chrf
      value: 0.54777
      name: chr-F
    - type: bleu
      value: 19.0
      name: BLEU
    - type: chrf
      value: 0.47283
      name: chr-F
    - type: bleu
      value: 18.4
      name: BLEU
    - type: chrf
      value: 0.46935
      name: chr-F
    - type: bleu
      value: 13.7
      name: BLEU
    - type: chrf
      value: 0.42143
      name: chr-F
    - type: bleu
      value: 17.1
      name: BLEU
    - type: chrf
      value: 0.46542
      name: chr-F
    - type: bleu
      value: 29.3
      name: BLEU
    - type: chrf
      value: 0.56935
      name: chr-F
    - type: bleu
      value: 22.3
      name: BLEU
    - type: chrf
      value: 0.50276
      name: chr-F
    - type: bleu
      value: 20.3
      name: BLEU
    - type: chrf
      value: 0.4801
      name: chr-F
    - type: bleu
      value: 14.7
      name: BLEU
    - type: chrf
      value: 0.43032
      name: chr-F
  - task:
      type: translation
      name: Translation asm-por
    dataset:
      name: flores101-devtest
      type: flores_101
      args: asm por devtest
    metrics:
    - type: bleu
      value: 10.0
      name: BLEU
    - type: chrf
      value: 0.34689
      name: chr-F
    - type: bleu
      value: 30.4
      name: BLEU
    - type: chrf
      value: 0.57906
      name: chr-F
    - type: bleu
      value: 21.9
      name: BLEU
    - type: chrf
      value: 0.50109
      name: chr-F
    - type: bleu
      value: 15.2
      name: BLEU
    - type: chrf
      value: 0.44065
      name: chr-F
    - type: bleu
      value: 13.8
      name: BLEU
    - type: chrf
      value: 0.44067
      name: chr-F
    - type: bleu
      value: 18.6
      name: BLEU
    - type: chrf
      value: 0.46685
      name: chr-F
    - type: bleu
      value: 14.0
      name: BLEU
    - type: chrf
      value: 0.41662
      name: chr-F
    - type: bleu
      value: 33.0
      name: BLEU
    - type: chrf
      value: 0.59922
      name: chr-F
    - type: bleu
      value: 21.9
      name: BLEU
    - type: chrf
      value: 0.49373
      name: chr-F
    - type: bleu
      value: 15.4
      name: BLEU
    - type: chrf
      value: 0.4391
      name: chr-F
  - task:
      type: translation
      name: Translation ben-deu
    dataset:
      name: ntrex128
      type: ntrex128
      args: ben-deu
    metrics:
    - type: bleu
      value: 14.6
      name: BLEU
    - type: chrf
      value: 0.4518
      name: chr-F
    - type: bleu
      value: 29.5
      name: BLEU
    - type: chrf
      value: 0.57247
      name: chr-F
    - type: bleu
      value: 18.0
      name: BLEU
    - type: chrf
      value: 0.46475
      name: chr-F
    - type: bleu
      value: 16.8
      name: BLEU
    - type: chrf
      value: 0.45486
      name: chr-F
    - type: bleu
      value: 21.1
      name: BLEU
    - type: chrf
      value: 0.48738
      name: chr-F
    - type: bleu
      value: 13.9
      name: BLEU
    - type: chrf
      value: 0.43539
      name: chr-F
    - type: bleu
      value: 31.6
      name: BLEU
    - type: chrf
      value: 0.58894
      name: chr-F
    - type: bleu
      value: 16.9
      name: BLEU
    - type: chrf
      value: 0.45075
      name: chr-F
    - type: bleu
      value: 15.2
      name: BLEU
    - type: chrf
      value: 0.43567
      name: chr-F
    - type: bleu
      value: 20.2
      name: BLEU
    - type: chrf
      value: 0.47525
      name: chr-F
    - type: bleu
      value: 15.0
      name: BLEU
    - type: chrf
      value: 0.46336
      name: chr-F
    - type: bleu
      value: 31.5
      name: BLEU
    - type: chrf
      value: 0.59842
      name: chr-F
    - type: bleu
      value: 19.2
      name: BLEU
    - type: chrf
      value: 0.48208
      name: chr-F
    - type: bleu
      value: 17.6
      name: BLEU
    - type: chrf
      value: 0.46509
      name: chr-F
    - type: bleu
      value: 21.8
      name: BLEU
    - type: chrf
      value: 0.49436
      name: chr-F
    - type: bleu
      value: 12.8
      name: BLEU
    - type: chrf
      value: 0.43119
      name: chr-F
    - type: bleu
      value: 27.3
      name: BLEU
    - type: chrf
      value: 0.55151
      name: chr-F
    - type: bleu
      value: 16.2
      name: BLEU
    - type: chrf
      value: 0.43957
      name: chr-F
    - type: bleu
      value: 15.4
      name: BLEU
    - type: chrf
      value: 0.43555
      name: chr-F
    - type: bleu
      value: 19.1
      name: BLEU
    - type: chrf
      value: 0.46271
      name: chr-F
    - type: bleu
      value: 13.0
      name: BLEU
    - type: chrf
      value: 0.4294
      name: chr-F
    - type: bleu
      value: 29.1
      name: BLEU
    - type: chrf
      value: 0.56277
      name: chr-F
    - type: bleu
      value: 16.5
      name: BLEU
    - type: chrf
      value: 0.44663
      name: chr-F
    - type: bleu
      value: 15.4
      name: BLEU
    - type: chrf
      value: 0.43686
      name: chr-F
    - type: bleu
      value: 19.3
      name: BLEU
    - type: chrf
      value: 0.46553
      name: chr-F
    - type: bleu
      value: 14.1
      name: BLEU
    - type: chrf
      value: 0.44036
      name: chr-F
    - type: bleu
      value: 31.6
      name: BLEU
    - type: chrf
      value: 0.58427
      name: chr-F
    - type: bleu
      value: 17.3
      name: BLEU
    - type: chrf
      value: 0.45593
      name: chr-F
    - type: bleu
      value: 15.9
      name: BLEU
    - type: chrf
      value: 0.44264
      name: chr-F
    - type: bleu
      value: 20.0
      name: BLEU
    - type: chrf
      value: 0.47199
      name: chr-F
    - type: bleu
      value: 12.4
      name: BLEU
    - type: chrf
      value: 0.4228
      name: chr-F
    - type: bleu
      value: 24.6
      name: BLEU
    - type: chrf
      value: 0.52576
      name: chr-F
    - type: bleu
      value: 15.6
      name: BLEU
    - type: chrf
      value: 0.43594
      name: chr-F
    - type: bleu
      value: 14.4
      name: BLEU
    - type: chrf
      value: 0.42751
      name: chr-F
    - type: bleu
      value: 18.3
      name: BLEU
    - type: chrf
      value: 0.4589
      name: chr-F
    - type: bleu
      value: 15.6
      name: BLEU
    - type: chrf
      value: 0.45737
      name: chr-F
    - type: bleu
      value: 28.6
      name: BLEU
    - type: chrf
      value: 0.56781
      name: chr-F
    - type: bleu
      value: 18.9
      name: BLEU
    - type: chrf
      value: 0.47298
      name: chr-F
    - type: bleu
      value: 16.2
      name: BLEU
    - type: chrf
      value: 0.45273
      name: chr-F
    - type: bleu
      value: 21.0
      name: BLEU
    - type: chrf
      value: 0.48644
      name: chr-F
  - task:
      type: translation
      name: Translation awa-eng
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: awa-eng
    metrics:
    - type: bleu
      value: 40.8
      name: BLEU
    - type: chrf
      value: 0.6039
      name: chr-F
    - type: bleu
      value: 49.4
      name: BLEU
    - type: chrf
      value: 0.64078
      name: chr-F
    - type: bleu
      value: 49.1
      name: BLEU
    - type: chrf
      value: 0.64929
      name: chr-F
    - type: bleu
      value: 48.0
      name: BLEU
    - type: chrf
      value: 0.64074
      name: chr-F
    - type: bleu
      value: 44.6
      name: BLEU
    - type: chrf
      value: 0.6136
      name: chr-F
    - type: bleu
      value: 35.0
      name: BLEU
    - type: chrf
      value: 0.52963
      name: chr-F
  - task:
      type: translation
      name: Translation ben-eng
    dataset:
      name: tico19-test
      type: tico19-test
      args: ben-eng
    metrics:
    - type: bleu
      value: 38.2
      name: BLEU
    - type: chrf
      value: 0.64568
      name: chr-F
    - type: bleu
      value: 22.0
      name: BLEU
    - type: chrf
      value: 0.49799
      name: chr-F
    - type: bleu
      value: 27.2
      name: BLEU
    - type: chrf
      value: 0.55115
      name: chr-F
    - type: bleu
      value: 29.9
      name: BLEU
    - type: chrf
      value: 0.56847
      name: chr-F
    - type: bleu
      value: 46.6
      name: BLEU
    - type: chrf
      value: 0.70694
      name: chr-F
    - type: bleu
      value: 26.7
      name: BLEU
    - type: chrf
      value: 0.53932
      name: chr-F
    - type: bleu
      value: 33.4
      name: BLEU
    - type: chrf
      value: 0.60581
      name: chr-F
    - type: bleu
      value: 35.7
      name: BLEU
    - type: chrf
      value: 0.61585
      name: chr-F
    - type: bleu
      value: 31.8
      name: BLEU
    - type: chrf
      value: 0.59329
      name: chr-F
    - type: bleu
      value: 19.3
      name: BLEU
    - type: chrf
      value: 0.46574
      name: chr-F
    - type: bleu
      value: 23.6
      name: BLEU
    - type: chrf
      value: 0.51463
      name: chr-F
    - type: bleu
      value: 25.7
      name: BLEU
    - type: chrf
      value: 0.52551
      name: chr-F
    - type: bleu
      value: 40.7
      name: BLEU
    - type: chrf
      value: 0.66283
      name: chr-F
    - type: bleu
      value: 22.8
      name: BLEU
    - type: chrf
      value: 0.50397
      name: chr-F
    - type: bleu
      value: 28.1
      name: BLEU
    - type: chrf
      value: 0.55951
      name: chr-F
    - type: bleu
      value: 30.3
      name: BLEU
    - type: chrf
      value: 0.57272
      name: chr-F
    - type: bleu
      value: 30.5
      name: BLEU
    - type: chrf
      value: 0.57473
      name: chr-F
    - type: bleu
      value: 19.6
      name: BLEU
    - type: chrf
      value: 0.46725
      name: chr-F
    - type: bleu
      value: 23.5
      name: BLEU
    - type: chrf
      value: 0.50913
      name: chr-F
    - type: bleu
      value: 25.8
      name: BLEU
    - type: chrf
      value: 0.52387
      name: chr-F
  - task:
      type: translation
      name: Translation hin-eng
    dataset:
      name: newstest2014
      type: wmt-2014-news
      args: hin-eng
    metrics:
    - type: bleu
      value: 30.3
      name: BLEU
    - type: chrf
      value: 0.59329
      name: chr-F
  - task:
      type: translation
      name: Translation guj-eng
    dataset:
      name: newstest2019
      type: wmt-2019-news
      args: guj-eng
    metrics:
    - type: bleu
      value: 26.9
      name: BLEU
    - type: chrf
      value: 0.53383
      name: chr-F
---
# opus-mt-tc-bible-big-inc-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 Indic languages (inc) 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): anp asm awa ben bho bpy div dty gbm guj hif hin hne hns kas kok lah mag mai mar nep npi ori pan pli rhg rmy rom san sin skr snd syl urd
  - 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/inc-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/inc-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-inc-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-inc-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/inc-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/inc-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/inc-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/inc-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 |
|----------|---------|-------|-------|-------|--------|
| awa-eng | tatoeba-test-v2021-08-07 | 0.60390 | 40.8 | 279 | 1335 |
| ben-eng | tatoeba-test-v2021-08-07 | 0.64078 | 49.4 | 2500 | 13978 |
| hin-eng | tatoeba-test-v2021-08-07 | 0.64929 | 49.1 | 5000 | 33943 |
| mar-eng | tatoeba-test-v2021-08-07 | 0.64074 | 48.0 | 10396 | 67527 |
| urd-eng | tatoeba-test-v2021-08-07 | 0.52963 | 35.0 | 1663 | 12029 |
| ben-eng | flores101-devtest | 0.57906 | 30.4 | 1012 | 24721 |
| ben-fra | flores101-devtest | 0.50109 | 21.9 | 1012 | 28343 |
| guj-spa | flores101-devtest | 0.44065 | 15.2 | 1012 | 29199 |
| mar-deu | flores101-devtest | 0.44067 | 13.8 | 1012 | 25094 |
| mar-por | flores101-devtest | 0.46685 | 18.6 | 1012 | 26519 |
| mar-spa | flores101-devtest | 0.41662 | 14.0 | 1012 | 29199 |
| pan-eng | flores101-devtest | 0.59922 | 33.0 | 1012 | 24721 |
| pan-por | flores101-devtest | 0.49373 | 21.9 | 1012 | 26519 |
| pan-spa | flores101-devtest | 0.43910 | 15.4 | 1012 | 29199 |
| asm-eng | flores200-devtest | 0.48584 | 21.9 | 1012 | 24721 |
| awa-deu | flores200-devtest | 0.47173 | 16.5 | 1012 | 25094 |
| awa-eng | flores200-devtest | 0.50582 | 24.5 | 1012 | 24721 |
| awa-fra | flores200-devtest | 0.49682 | 21.4 | 1012 | 28343 |
| awa-por | flores200-devtest | 0.49663 | 21.5 | 1012 | 26519 |
| awa-spa | flores200-devtest | 0.43740 | 15.1 | 1012 | 29199 |
| ben-deu | flores200-devtest | 0.47330 | 16.6 | 1012 | 25094 |
| ben-eng | flores200-devtest | 0.58077 | 30.5 | 1012 | 24721 |
| ben-fra | flores200-devtest | 0.50884 | 22.6 | 1012 | 28343 |
| ben-por | flores200-devtest | 0.50054 | 21.4 | 1012 | 26519 |
| ben-spa | flores200-devtest | 0.44159 | 15.2 | 1012 | 29199 |
| bho-deu | flores200-devtest | 0.42660 | 12.6 | 1012 | 25094 |
| bho-eng | flores200-devtest | 0.50609 | 22.7 | 1012 | 24721 |
| bho-fra | flores200-devtest | 0.44889 | 16.8 | 1012 | 28343 |
| bho-por | flores200-devtest | 0.44582 | 16.9 | 1012 | 26519 |
| bho-spa | flores200-devtest | 0.40581 | 13.1 | 1012 | 29199 |
| guj-deu | flores200-devtest | 0.46665 | 16.8 | 1012 | 25094 |
| guj-eng | flores200-devtest | 0.61383 | 34.3 | 1012 | 24721 |
| guj-fra | flores200-devtest | 0.50410 | 22.3 | 1012 | 28343 |
| guj-por | flores200-devtest | 0.49257 | 21.3 | 1012 | 26519 |
| guj-spa | flores200-devtest | 0.44565 | 15.6 | 1012 | 29199 |
| hin-deu | flores200-devtest | 0.50226 | 20.4 | 1012 | 25094 |
| hin-eng | flores200-devtest | 0.63336 | 37.3 | 1012 | 24721 |
| hin-fra | flores200-devtest | 0.53701 | 25.9 | 1012 | 28343 |
| hin-por | flores200-devtest | 0.53448 | 25.5 | 1012 | 26519 |
| hin-spa | flores200-devtest | 0.46171 | 17.2 | 1012 | 29199 |
| hne-deu | flores200-devtest | 0.49698 | 19.0 | 1012 | 25094 |
| hne-eng | flores200-devtest | 0.63936 | 38.5 | 1012 | 24721 |
| hne-fra | flores200-devtest | 0.52835 | 25.3 | 1012 | 28343 |
| hne-por | flores200-devtest | 0.52788 | 25.0 | 1012 | 26519 |
| hne-spa | flores200-devtest | 0.45443 | 16.7 | 1012 | 29199 |
| mag-deu | flores200-devtest | 0.50359 | 19.7 | 1012 | 25094 |
| mag-eng | flores200-devtest | 0.63906 | 38.0 | 1012 | 24721 |
| mag-fra | flores200-devtest | 0.53616 | 25.8 | 1012 | 28343 |
| mag-por | flores200-devtest | 0.53537 | 25.9 | 1012 | 26519 |
| mag-spa | flores200-devtest | 0.45822 | 16.9 | 1012 | 29199 |
| mai-deu | flores200-devtest | 0.46791 | 16.2 | 1012 | 25094 |
| mai-eng | flores200-devtest | 0.57461 | 30.4 | 1012 | 24721 |
| mai-fra | flores200-devtest | 0.50585 | 22.1 | 1012 | 28343 |
| mai-por | flores200-devtest | 0.50490 | 22.0 | 1012 | 26519 |
| mai-spa | flores200-devtest | 0.44366 | 15.3 | 1012 | 29199 |
| mar-deu | flores200-devtest | 0.44725 | 14.5 | 1012 | 25094 |
| mar-eng | flores200-devtest | 0.58500 | 31.4 | 1012 | 24721 |
| mar-fra | flores200-devtest | 0.47027 | 19.5 | 1012 | 28343 |
| mar-por | flores200-devtest | 0.47216 | 19.3 | 1012 | 26519 |
| mar-spa | flores200-devtest | 0.42178 | 14.2 | 1012 | 29199 |
| npi-deu | flores200-devtest | 0.46631 | 16.4 | 1012 | 25094 |
| npi-eng | flores200-devtest | 0.59776 | 32.3 | 1012 | 24721 |
| npi-fra | flores200-devtest | 0.50548 | 22.5 | 1012 | 28343 |
| npi-por | flores200-devtest | 0.50202 | 21.7 | 1012 | 26519 |
| npi-spa | flores200-devtest | 0.43804 | 15.3 | 1012 | 29199 |
| pan-deu | flores200-devtest | 0.48421 | 18.7 | 1012 | 25094 |
| pan-eng | flores200-devtest | 0.60676 | 33.8 | 1012 | 24721 |
| pan-fra | flores200-devtest | 0.51368 | 23.5 | 1012 | 28343 |
| pan-por | flores200-devtest | 0.50586 | 22.7 | 1012 | 26519 |
| pan-spa | flores200-devtest | 0.44653 | 16.5 | 1012 | 29199 |
| sin-deu | flores200-devtest | 0.44676 | 14.2 | 1012 | 25094 |
| sin-eng | flores200-devtest | 0.54777 | 26.8 | 1012 | 24721 |
| sin-fra | flores200-devtest | 0.47283 | 19.0 | 1012 | 28343 |
| sin-por | flores200-devtest | 0.46935 | 18.4 | 1012 | 26519 |
| sin-spa | flores200-devtest | 0.42143 | 13.7 | 1012 | 29199 |
| urd-deu | flores200-devtest | 0.46542 | 17.1 | 1012 | 25094 |
| urd-eng | flores200-devtest | 0.56935 | 29.3 | 1012 | 24721 |
| urd-fra | flores200-devtest | 0.50276 | 22.3 | 1012 | 28343 |
| urd-por | flores200-devtest | 0.48010 | 20.3 | 1012 | 26519 |
| urd-spa | flores200-devtest | 0.43032 | 14.7 | 1012 | 29199 |
| hin-eng | newstest2014 | 0.59329 | 30.3 | 2507 | 55571 |
| guj-eng | newstest2019 | 0.53383 | 26.9 | 1016 | 17757 |
| ben-deu | ntrex128 | 0.45180 | 14.6 | 1997 | 48761 |
| ben-eng | ntrex128 | 0.57247 | 29.5 | 1997 | 47673 |
| ben-fra | ntrex128 | 0.46475 | 18.0 | 1997 | 53481 |
| ben-por | ntrex128 | 0.45486 | 16.8 | 1997 | 51631 |
| ben-spa | ntrex128 | 0.48738 | 21.1 | 1997 | 54107 |
| guj-deu | ntrex128 | 0.43539 | 13.9 | 1997 | 48761 |
| guj-eng | ntrex128 | 0.58894 | 31.6 | 1997 | 47673 |
| guj-fra | ntrex128 | 0.45075 | 16.9 | 1997 | 53481 |
| guj-por | ntrex128 | 0.43567 | 15.2 | 1997 | 51631 |
| guj-spa | ntrex128 | 0.47525 | 20.2 | 1997 | 54107 |
| hin-deu | ntrex128 | 0.46336 | 15.0 | 1997 | 48761 |
| hin-eng | ntrex128 | 0.59842 | 31.5 | 1997 | 47673 |
| hin-fra | ntrex128 | 0.48208 | 19.2 | 1997 | 53481 |
| hin-por | ntrex128 | 0.46509 | 17.6 | 1997 | 51631 |
| hin-spa | ntrex128 | 0.49436 | 21.8 | 1997 | 54107 |
| mar-deu | ntrex128 | 0.43119 | 12.8 | 1997 | 48761 |
| mar-eng | ntrex128 | 0.55151 | 27.3 | 1997 | 47673 |
| mar-fra | ntrex128 | 0.43957 | 16.2 | 1997 | 53481 |
| mar-por | ntrex128 | 0.43555 | 15.4 | 1997 | 51631 |
| mar-spa | ntrex128 | 0.46271 | 19.1 | 1997 | 54107 |
| nep-deu | ntrex128 | 0.42940 | 13.0 | 1997 | 48761 |
| nep-eng | ntrex128 | 0.56277 | 29.1 | 1997 | 47673 |
| nep-fra | ntrex128 | 0.44663 | 16.5 | 1997 | 53481 |
| nep-por | ntrex128 | 0.43686 | 15.4 | 1997 | 51631 |
| nep-spa | ntrex128 | 0.46553 | 19.3 | 1997 | 54107 |
| pan-deu | ntrex128 | 0.44036 | 14.1 | 1997 | 48761 |
| pan-eng | ntrex128 | 0.58427 | 31.6 | 1997 | 47673 |
| pan-fra | ntrex128 | 0.45593 | 17.3 | 1997 | 53481 |
| pan-por | ntrex128 | 0.44264 | 15.9 | 1997 | 51631 |
| pan-spa | ntrex128 | 0.47199 | 20.0 | 1997 | 54107 |
| sin-deu | ntrex128 | 0.42280 | 12.4 | 1997 | 48761 |
| sin-eng | ntrex128 | 0.52576 | 24.6 | 1997 | 47673 |
| sin-fra | ntrex128 | 0.43594 | 15.6 | 1997 | 53481 |
| sin-por | ntrex128 | 0.42751 | 14.4 | 1997 | 51631 |
| sin-spa | ntrex128 | 0.45890 | 18.3 | 1997 | 54107 |
| urd-deu | ntrex128 | 0.45737 | 15.6 | 1997 | 48761 |
| urd-eng | ntrex128 | 0.56781 | 28.6 | 1997 | 47673 |
| urd-fra | ntrex128 | 0.47298 | 18.9 | 1997 | 53481 |
| urd-por | ntrex128 | 0.45273 | 16.2 | 1997 | 51631 |
| urd-spa | ntrex128 | 0.48644 | 21.0 | 1997 | 54107 |
| ben-eng | tico19-test | 0.64568 | 38.2 | 2100 | 56824 |
| ben-fra | tico19-test | 0.49799 | 22.0 | 2100 | 64661 |
| ben-por | tico19-test | 0.55115 | 27.2 | 2100 | 62729 |
| ben-spa | tico19-test | 0.56847 | 29.9 | 2100 | 66563 |
| hin-eng | tico19-test | 0.70694 | 46.6 | 2100 | 56323 |
| hin-fra | tico19-test | 0.53932 | 26.7 | 2100 | 64661 |
| hin-por | tico19-test | 0.60581 | 33.4 | 2100 | 62729 |
| hin-spa | tico19-test | 0.61585 | 35.7 | 2100 | 66563 |
| mar-eng | tico19-test | 0.59329 | 31.8 | 2100 | 56315 |
| mar-fra | tico19-test | 0.46574 | 19.3 | 2100 | 64661 |
| mar-por | tico19-test | 0.51463 | 23.6 | 2100 | 62729 |
| mar-spa | tico19-test | 0.52551 | 25.7 | 2100 | 66563 |
| nep-eng | tico19-test | 0.66283 | 40.7 | 2100 | 56824 |
| nep-fra | tico19-test | 0.50397 | 22.8 | 2100 | 64661 |
| nep-por | tico19-test | 0.55951 | 28.1 | 2100 | 62729 |
| nep-spa | tico19-test | 0.57272 | 30.3 | 2100 | 66563 |
| urd-eng | tico19-test | 0.57473 | 30.5 | 2100 | 56315 |
| urd-fra | tico19-test | 0.46725 | 19.6 | 2100 | 64661 |
| urd-por | tico19-test | 0.50913 | 23.5 | 2100 | 62729 |
| urd-spa | tico19-test | 0.52387 | 25.8 | 2100 | 66563 |

## 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 11:39:25 EEST 2024
* port machine: LM0-400-22516.local
