transformers pytorch safetensors marian text2text-generation translation opus-mt-tc-bible anp as awa bal bho bn bpy de diq dv en es fa fr gbm glk gu hi hif hne hns jdt kok ks ku lah lrc mag mai mr mzn ne or os pa pal pi ps pt rhg rmy rom sa sd si skr syl tg tly ur zza license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
language:
- anp
- as
- awa
- bal
- bho
- bn
- bpy
- de
- diq
- dv
- en
- es
- fa
- fr
- gbm
- glk
- gu
- hi
- hif
- hne
- hns
- jdt
- kok
- ks
- ku
- lah
- lrc
- mag
- mai
- mr
- mzn
- ne
- or
- os
- pa
- pal
- pi
- ps
- pt
- rhg
- rmy
- rom
- sa
- sd
- si
- skr
- syl
- tg
- tly
- ur
- zza
library_name: transformers
license: apache-2.0
tags:
- translation
- opus-mt-tc-bible
model-index:
- name: opus-mt-tc-bible-big-deu_eng_fra_por_spa-iir
  results:
  - task:
      type: translation
      name: Translation deu-ben
    dataset:
      name: flores200-devtest
      type: flores200-devtest
      args: deu-ben
    metrics:
    - type: bleu
      value: 10.6
      name: BLEU
    - type: chrf
      value: 0.44005
      name: chr-F
    - type: bleu
      value: 11.1
      name: BLEU
    - type: chrf
      value: 0.39522
      name: chr-F
    - type: bleu
      value: 22.3
      name: BLEU
    - type: chrf
      value: 0.48448
      name: chr-F
    - type: bleu
      value: 13.8
      name: BLEU
    - type: chrf
      value: 0.42659
      name: chr-F
    - type: bleu
      value: 14.0
      name: BLEU
    - type: chrf
      value: 0.42477
      name: chr-F
    - type: bleu
      value: 11.3
      name: BLEU
    - type: chrf
      value: 0.37308
      name: chr-F
    - type: bleu
      value: 14.9
      name: BLEU
    - type: chrf
      value: 0.42726
      name: chr-F
    - type: bleu
      value: 12.9
      name: BLEU
    - type: chrf
      value: 0.3883
      name: chr-F
    - type: bleu
      value: 12.9
      name: BLEU
    - type: chrf
      value: 0.40932
      name: chr-F
    - type: bleu
      value: 14.4
      name: BLEU
    - type: chrf
      value: 0.4125
      name: chr-F
    - type: bleu
      value: 17.1
      name: BLEU
    - type: chrf
      value: 0.51361
      name: chr-F
    - type: bleu
      value: 12.1
      name: BLEU
    - type: chrf
      value: 0.38188
      name: chr-F
    - type: bleu
      value: 22.4
      name: BLEU
    - type: chrf
      value: 0.54231
      name: chr-F
    - type: bleu
      value: 33.7
      name: BLEU
    - type: chrf
      value: 0.58371
      name: chr-F
    - type: bleu
      value: 19.9
      name: BLEU
    - type: chrf
      value: 0.47591
      name: chr-F
    - type: bleu
      value: 22.2
      name: BLEU
    - type: chrf
      value: 0.5107
      name: chr-F
    - type: bleu
      value: 10.0
      name: BLEU
    - type: chrf
      value: 0.39249
      name: chr-F
    - type: bleu
      value: 14.8
      name: BLEU
    - type: chrf
      value: 0.48733
      name: chr-F
    - type: bleu
      value: 18.1
      name: BLEU
    - type: chrf
      value: 0.45015
      name: chr-F
    - type: bleu
      value: 21.1
      name: BLEU
    - type: chrf
      value: 0.48588
      name: chr-F
    - type: bleu
      value: 24.5
      name: BLEU
    - type: chrf
      value: 0.51879
      name: chr-F
    - type: bleu
      value: 10.6
      name: BLEU
    - type: chrf
      value: 0.43823
      name: chr-F
    - type: bleu
      value: 17.8
      name: BLEU
    - type: chrf
      value: 0.47323
      name: chr-F
    - type: bleu
      value: 20.4
      name: BLEU
    - type: chrf
      value: 0.48212
      name: chr-F
    - type: bleu
      value: 11.0
      name: BLEU
    - type: chrf
      value: 0.44029
      name: chr-F
    - type: bleu
      value: 11.0
      name: BLEU
    - type: chrf
      value: 0.38634
      name: chr-F
    - type: bleu
      value: 22.6
      name: BLEU
    - type: chrf
      value: 0.48406
      name: chr-F
    - type: bleu
      value: 13.9
      name: BLEU
    - type: chrf
      value: 0.42353
      name: chr-F
    - type: bleu
      value: 14.3
      name: BLEU
    - type: chrf
      value: 0.42678
      name: chr-F
    - type: bleu
      value: 10.6
      name: BLEU
    - type: chrf
      value: 0.3698
      name: chr-F
    - type: bleu
      value: 15.5
      name: BLEU
    - type: chrf
      value: 0.43526
      name: chr-F
    - type: bleu
      value: 12.8
      name: BLEU
    - type: chrf
      value: 0.37985
      name: chr-F
    - type: bleu
      value: 13.7
      name: BLEU
    - type: chrf
      value: 0.42982
      name: chr-F
    - type: bleu
      value: 14.2
      name: BLEU
    - type: chrf
      value: 0.41438
      name: chr-F
    - type: bleu
      value: 10.4
      name: BLEU
    - type: chrf
      value: 0.4339
      name: chr-F
    - type: bleu
      value: 10.6
      name: BLEU
    - type: chrf
      value: 0.37374
      name: chr-F
    - type: bleu
      value: 23.6
      name: BLEU
    - type: chrf
      value: 0.49524
      name: chr-F
    - type: bleu
      value: 13.9
      name: BLEU
    - type: chrf
      value: 0.42269
      name: chr-F
    - type: bleu
      value: 15.0
      name: BLEU
    - type: chrf
      value: 0.42753
      name: chr-F
    - type: bleu
      value: 10.7
      name: BLEU
    - type: chrf
      value: 0.36653
      name: chr-F
    - type: bleu
      value: 15.4
      name: BLEU
    - type: chrf
      value: 0.43194
      name: chr-F
    - type: bleu
      value: 12.1
      name: BLEU
    - type: chrf
      value: 0.36411
      name: chr-F
    - type: bleu
      value: 13.2
      name: BLEU
    - type: chrf
      value: 0.4186
      name: chr-F
    - type: bleu
      value: 14.8
      name: BLEU
    - type: chrf
      value: 0.41799
      name: chr-F
    - type: bleu
      value: 16.4
      name: BLEU
    - type: chrf
      value: 0.43777
      name: chr-F
    - type: bleu
      value: 11.2
      name: BLEU
    - type: chrf
      value: 0.39492
      name: chr-F
    - type: bleu
      value: 11.4
      name: BLEU
    - type: chrf
      value: 0.39882
      name: chr-F
    - type: bleu
      value: 12.2
      name: BLEU
    - type: chrf
      value: 0.40856
      name: chr-F
    - type: bleu
      value: 12.8
      name: BLEU
    - type: chrf
      value: 0.40361
      name: chr-F
    - type: bleu
      value: 10.8
      name: BLEU
    - type: chrf
      value: 0.401
      name: chr-F
    - type: bleu
      value: 10.9
      name: BLEU
    - type: chrf
      value: 0.38539
      name: chr-F
  - task:
      type: translation
      name: Translation deu-pan
    dataset:
      name: flores101-devtest
      type: flores_101
      args: deu pan devtest
    metrics:
    - type: bleu
      value: 10.9
      name: BLEU
    - type: chrf
      value: 0.36883
      name: chr-F
    - type: bleu
      value: 17.0
      name: BLEU
    - type: chrf
      value: 0.51055
      name: chr-F
    - type: bleu
      value: 22.3
      name: BLEU
    - type: chrf
      value: 0.53972
      name: chr-F
    - type: bleu
      value: 33.4
      name: BLEU
    - type: chrf
      value: 0.5798
      name: chr-F
    - type: bleu
      value: 14.3
      name: BLEU
    - type: chrf
      value: 0.48206
      name: chr-F
    - type: bleu
      value: 11.9
      name: BLEU
    - type: chrf
      value: 0.37264
      name: chr-F
    - type: bleu
      value: 20.5
      name: BLEU
    - type: chrf
      value: 0.4805
      name: chr-F
    - type: bleu
      value: 10.9
      name: BLEU
    - type: chrf
      value: 0.43806
      name: chr-F
    - type: bleu
      value: 11.0
      name: BLEU
    - type: chrf
      value: 0.37066
      name: chr-F
    - type: bleu
      value: 10.0
      name: BLEU
    - type: chrf
      value: 0.4273
      name: chr-F
    - type: bleu
      value: 10.7
      name: BLEU
    - type: chrf
      value: 0.36551
      name: chr-F
    - type: bleu
      value: 16.0
      name: BLEU
    - type: chrf
      value: 0.43371
      name: chr-F
    - type: bleu
      value: 10.6
      name: BLEU
    - type: chrf
      value: 0.39762
      name: chr-F
  - task:
      type: translation
      name: Translation deu-fas
    dataset:
      name: ntrex128
      type: ntrex128
      args: deu-fas
    metrics:
    - type: bleu
      value: 13.8
      name: BLEU
    - type: chrf
      value: 0.41469
      name: chr-F
    - type: bleu
      value: 16.8
      name: BLEU
    - type: chrf
      value: 0.4294
      name: chr-F
    - type: bleu
      value: 11.0
      name: BLEU
    - type: chrf
      value: 0.36776
      name: chr-F
    - type: bleu
      value: 14.5
      name: BLEU
    - type: chrf
      value: 0.41881
      name: chr-F
    - type: bleu
      value: 16.6
      name: BLEU
    - type: chrf
      value: 0.51555
      name: chr-F
    - type: bleu
      value: 19.7
      name: BLEU
    - type: chrf
      value: 0.46895
      name: chr-F
    - type: bleu
      value: 17.1
      name: BLEU
    - type: chrf
      value: 0.4899
      name: chr-F
    - type: bleu
      value: 26.9
      name: BLEU
    - type: chrf
      value: 0.52307
      name: chr-F
    - type: bleu
      value: 10.4
      name: BLEU
    - type: chrf
      value: 0.4458
      name: chr-F
    - type: bleu
      value: 19.6
      name: BLEU
    - type: chrf
      value: 0.46141
      name: chr-F
    - type: bleu
      value: 12.9
      name: BLEU
    - type: chrf
      value: 0.39651
      name: chr-F
    - type: bleu
      value: 11.3
      name: BLEU
    - type: chrf
      value: 0.38524
      name: chr-F
    - type: bleu
      value: 22.1
      name: BLEU
    - type: chrf
      value: 0.49646
      name: chr-F
    - type: bleu
      value: 13.8
      name: BLEU
    - type: chrf
      value: 0.41282
      name: chr-F
    - type: bleu
      value: 17.1
      name: BLEU
    - type: chrf
      value: 0.42475
      name: chr-F
    - type: bleu
      value: 10.2
      name: BLEU
    - type: chrf
      value: 0.3612
      name: chr-F
    - type: bleu
      value: 14.8
      name: BLEU
    - type: chrf
      value: 0.41536
      name: chr-F
    - type: bleu
      value: 14.4
      name: BLEU
    - type: chrf
      value: 0.4201
      name: chr-F
    - type: bleu
      value: 17.6
      name: BLEU
    - type: chrf
      value: 0.43275
      name: chr-F
    - type: bleu
      value: 10.6
      name: BLEU
    - type: chrf
      value: 0.3636
      name: chr-F
    - type: bleu
      value: 15.2
      name: BLEU
    - type: chrf
      value: 0.42484
      name: chr-F
    - type: bleu
      value: 10.3
      name: BLEU
    - type: chrf
      value: 0.44905
      name: chr-F
    - type: bleu
      value: 14.1
      name: BLEU
    - type: chrf
      value: 0.42207
      name: chr-F
    - type: bleu
      value: 17.6
      name: BLEU
    - type: chrf
      value: 0.4338
      name: chr-F
    - type: bleu
      value: 11.1
      name: BLEU
    - type: chrf
      value: 0.37361
      name: chr-F
    - type: bleu
      value: 10.3
      name: BLEU
    - type: chrf
      value: 0.37448
      name: chr-F
    - type: bleu
      value: 15.0
      name: BLEU
    - type: chrf
      value: 0.42434
      name: chr-F
  - task:
      type: translation
      name: Translation deu-fas
    dataset:
      name: tatoeba-test-v2021-08-07
      type: tatoeba_mt
      args: deu-fas
    metrics:
    - type: bleu
      value: 20.3
      name: BLEU
    - type: chrf
      value: 0.45763
      name: chr-F
    - type: bleu
      value: 28.4
      name: BLEU
    - type: chrf
      value: 0.52525
      name: chr-F
    - type: bleu
      value: 24.4
      name: BLEU
    - type: chrf
      value: 0.52549
      name: chr-F
  - task:
      type: translation
      name: Translation eng-ben
    dataset:
      name: tico19-test
      type: tico19-test
      args: eng-ben
    metrics:
    - type: bleu
      value: 17.9
      name: BLEU
    - type: chrf
      value: 0.51563
      name: chr-F
    - type: bleu
      value: 25.8
      name: BLEU
    - type: chrf
      value: 0.53182
      name: chr-F
    - type: bleu
      value: 41.6
      name: BLEU
    - type: chrf
      value: 0.63128
      name: chr-F
    - type: bleu
      value: 12.9
      name: BLEU
    - type: chrf
      value: 0.45619
      name: chr-F
    - type: bleu
      value: 17.6
      name: BLEU
    - type: chrf
      value: 0.53413
      name: chr-F
    - type: bleu
      value: 17.3
      name: BLEU
    - type: chrf
      value: 0.44101
      name: chr-F
    - type: bleu
      value: 20.5
      name: BLEU
    - type: chrf
      value: 0.47063
      name: chr-F
    - type: bleu
      value: 22.0
      name: BLEU
    - type: chrf
      value: 0.51054
      name: chr-F
    - type: bleu
      value: 17.9
      name: BLEU
    - type: chrf
      value: 0.43476
      name: chr-F
    - type: bleu
      value: 25.6
      name: BLEU
    - type: chrf
      value: 0.48625
      name: chr-F
    - type: bleu
      value: 11.6
      name: BLEU
    - type: chrf
      value: 0.3613
      name: chr-F
    - type: bleu
      value: 12.7
      name: BLEU
    - type: chrf
      value: 0.37217
      name: chr-F
    - type: bleu
      value: 14.4
      name: BLEU
    - type: chrf
      value: 0.40482
      name: chr-F
    - type: bleu
      value: 12.5
      name: BLEU
    - type: chrf
      value: 0.45814
      name: chr-F
    - type: bleu
      value: 21.3
      name: BLEU
    - type: chrf
      value: 0.49181
      name: chr-F
    - type: bleu
      value: 31.1
      name: BLEU
    - type: chrf
      value: 0.55759
      name: chr-F
    - type: bleu
      value: 12.1
      name: BLEU
    - type: chrf
      value: 0.47378
      name: chr-F
    - type: bleu
      value: 12.1
      name: BLEU
    - type: chrf
      value: 0.38725
      name: chr-F
    - type: bleu
      value: 15.9
      name: BLEU
    - type: chrf
      value: 0.42496
      name: chr-F
    - type: bleu
      value: 16.6
      name: BLEU
    - type: chrf
      value: 0.4556
      name: chr-F
    - type: bleu
      value: 12.7
      name: BLEU
    - type: chrf
      value: 0.45751
      name: chr-F
    - type: bleu
      value: 21.0
      name: BLEU
    - type: chrf
      value: 0.48974
      name: chr-F
    - type: bleu
      value: 30.9
      name: BLEU
    - type: chrf
      value: 0.55641
      name: chr-F
    - type: bleu
      value: 12.1
      name: BLEU
    - type: chrf
      value: 0.47164
      name: chr-F
    - type: bleu
      value: 14.3
      name: BLEU
    - type: chrf
      value: 0.41879
      name: chr-F
    - type: bleu
      value: 15.1
      name: BLEU
    - type: chrf
      value: 0.41714
      name: chr-F
    - type: bleu
      value: 15.3
      name: BLEU
    - type: chrf
      value: 0.44931
      name: chr-F
  - task:
      type: translation
      name: Translation eng-hin
    dataset:
      name: newstest2014
      type: wmt-2014-news
      args: eng-hin
    metrics:
    - type: bleu
      value: 23.6
      name: BLEU
    - type: chrf
      value: 0.51249
      name: chr-F
  - task:
      type: translation
      name: Translation eng-guj
    dataset:
      name: newstest2019
      type: wmt-2019-news
      args: eng-guj
    metrics:
    - type: bleu
      value: 25.5
      name: BLEU
    - type: chrf
      value: 0.57282
      name: chr-F
---
# opus-mt-tc-bible-big-deu_eng_fra_por_spa-iir

## 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 unknown (deu+eng+fra+por+spa) to Indo-Iranian languages (iir).

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): deu eng fra por spa
  - Target Language(s): anp asm awa bal ben bho bpy ckb diq div dty fas gbm glk guj hif hin hne hns jdt kas kmr kok kur lah lrc mag mai mar mzn nep npi ori oss pal pan pes pli prs pus rhg rmy rom san sdh sin skr snd syl tgk tly urd zza
  - Valid Target Language Labels: >>aee<< >>aeq<< >>aiq<< >>anp<< >>anr<< >>ask<< >>asm<< >>atn<< >>avd<< >>ave<< >>awa<< >>bal<< >>bal_Latn<< >>bdv<< >>ben<< >>bfb<< >>bfy<< >>bfz<< >>bgc<< >>bgd<< >>bge<< >>bgw<< >>bha<< >>bhb<< >>bhd<< >>bhe<< >>bhh<< >>bhi<< >>bho<< >>bht<< >>bhu<< >>bjj<< >>bjm<< >>bkk<< >>bmj<< >>bns<< >>bpx<< >>bpy<< >>bqi<< >>bra<< >>bsg<< >>bsh<< >>btv<< >>ccp<< >>cdh<< >>cdi<< >>cdj<< >>cih<< >>ckb<< >>clh<< >>ctg<< >>dcc<< >>def<< >>deh<< >>dhn<< >>dho<< >>diq<< >>div<< >>dmk<< >>dml<< >>doi<< >>dry<< >>dty<< >>dub<< >>duh<< >>dwz<< >>emx<< >>esh<< >>fas<< >>fay<< >>gas<< >>gbk<< >>gbl<< >>gbm<< >>gbz<< >>gdx<< >>ggg<< >>ghr<< >>gig<< >>gjk<< >>glh<< >>glk<< >>goz<< >>gra<< >>guj<< >>gwc<< >>gwf<< >>gwt<< >>gzi<< >>hac<< >>haj<< >>haz<< >>hca<< >>hif<< >>hif_Latn<< >>hii<< >>hin<< >>hin_Latn<< >>hlb<< >>hne<< >>hns<< >>hrz<< >>isk<< >>jdg<< >>jdt<< >>jdt_Cyrl<< >>jml<< >>jnd<< >>jns<< >>jpr<< >>kas<< >>kas_Arab<< >>kas_Deva<< >>kbu<< >>keq<< >>key<< >>kfm<< >>kfr<< >>kfs<< >>kft<< >>kfu<< >>kfv<< >>kfx<< >>kfy<< >>kgn<< >>khn<< >>kho<< >>khw<< >>kjo<< >>kls<< >>kmr<< >>kok<< >>kra<< >>ksy<< >>ktl<< >>kur<< >>kur_Arab<< >>kur_Cyrl<< >>kur_Latn<< >>kvx<< >>kxp<< >>kyw<< >>lah<< >>lbm<< >>lhl<< >>lki<< >>lmn<< >>lrc<< >>lrl<< >>lsa<< >>lss<< >>luv<< >>luz<< >>mag<< >>mai<< >>mar<< >>mby<< >>mjl<< >>mjz<< >>mkb<< >>mke<< >>mki<< >>mnj<< >>mvy<< >>mwr<< >>mzn<< >>nag<< >>nep<< >>nhh<< >>nli<< >>nlx<< >>noe<< >>noi<< >>npi<< >>ntz<< >>nyq<< >>odk<< >>okh<< >>omr<< >>oos<< >>ori<< >>ort<< >>oru<< >>oss<< >>pal<< >>pan<< >>pan_Guru<< >>paq<< >>pcl<< >>peo<< >>pes<< >>pgg<< >>phd<< >>phl<< >>phv<< >>pli<< >>plk<< >>plp<< >>pmh<< >>prc<< >>prn<< >>prs<< >>psh<< >>psi<< >>psu<< >>pus<< >>pwr<< >>raj<< >>rat<< >>rdb<< >>rei<< >>rhg<< >>rhg_Latn<< >>rjs<< >>rkt<< >>rmi<< >>rmq<< >>rmt<< >>rmy<< >>rom<< >>rtw<< >>san<< >>san_Deva<< >>saz<< >>sbn<< >>sck<< >>scl<< >>sdb<< >>sdf<< >>sdg<< >>sdh<< >>sdr<< >>sgh<< >>sgl<< >>sgr<< >>sgy<< >>shd<< >>shm<< >>sin<< >>siy<< >>sjp<< >>skr<< >>smm<< >>smv<< >>smy<< >>snd<< >>snd_Arab<< >>sog<< >>soi<< >>soj<< >>sqo<< >>srh<< >>srx<< >>srz<< >>ssi<< >>sts<< >>syl<< >>syl_Sylo<< >>tdb<< >>tgk<< >>tgk_Cyrl<< >>tgk_Latn<< >>the<< >>thl<< >>thq<< >>thr<< >>tkb<< >>tks<< >>tkt<< >>tly<< >>tly_Latn<< >>tnv<< >>tov<< >>tra<< >>trm<< >>trw<< >>ttt<< >>urd<< >>ush<< >>vaa<< >>vaf<< >>vah<< >>vas<< >>vav<< >>ved<< >>vgr<< >>vmh<< >>wbk<< >>wbl<< >>wne<< >>wsv<< >>wtm<< >>xbc<< >>xco<< >>xka<< >>xkc<< >>xkj<< >>xkp<< >>xpr<< >>xsc<< >>xtq<< >>xvi<< >>xxx<< >>yah<< >>yai<< >>ydg<< >>zum<< >>zza<<
- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-iir/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/deu%2Beng%2Bfra%2Bpor%2Bspa-iir/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. `>>anp<<`

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

model_name = "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-iir"
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-deu_eng_fra_por_spa-iir")
print(pipe(">>anp<< 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/deu+eng+fra+por+spa-iir/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/deu%2Beng%2Bfra%2Bpor%2Bspa-iir/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/deu+eng+fra+por+spa-iir/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/deu+eng+fra+por+spa-iir/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 |
|----------|---------|-------|-------|-------|--------|
| deu-fas | tatoeba-test-v2021-08-07 | 0.45763 | 20.3 | 3185 | 24941 |
| deu-kur_Latn | tatoeba-test-v2021-08-07 | 1.027 | 0.6 | 223 | 1249 |
| eng-ben | tatoeba-test-v2021-08-07 | 0.47927 | 17.6 | 2500 | 11654 |
| eng-fas | tatoeba-test-v2021-08-07 | 0.40192 | 17.1 | 3762 | 31110 |
| eng-hin | tatoeba-test-v2021-08-07 | 0.52525 | 28.4 | 5000 | 32904 |
| eng-kur_Latn | tatoeba-test-v2021-08-07 | 0.493 | 0.0 | 290 | 1682 |
| eng-mar | tatoeba-test-v2021-08-07 | 0.52549 | 24.4 | 10396 | 61140 |
| eng-pes | tatoeba-test-v2021-08-07 | 0.40401 | 17.3 | 3757 | 31044 |
| eng-urd | tatoeba-test-v2021-08-07 | 0.45764 | 18.1 | 1663 | 12155 |
| fra-fas | tatoeba-test-v2021-08-07 | 0.42414 | 18.9 | 376 | 3217 |
| deu-npi | flores101-devtest | 3.082 | 0.2 | 1012 | 19762 |
| eng-ben | flores101-devtest | 0.51055 | 17.0 | 1012 | 21155 |
| eng-ckb | flores101-devtest | 0.45337 | 7.1 | 1012 | 21159 |
| eng-guj | flores101-devtest | 0.53972 | 22.3 | 1012 | 23840 |
| eng-hin | flores101-devtest | 0.57980 | 33.4 | 1012 | 27743 |
| eng-mar | flores101-devtest | 0.48206 | 14.3 | 1012 | 21810 |
| eng-urd | flores101-devtest | 0.48050 | 20.5 | 1012 | 28098 |
| fra-ben | flores101-devtest | 0.43806 | 10.9 | 1012 | 21155 |
| fra-ckb | flores101-devtest | 0.41016 | 4.9 | 1012 | 21159 |
| por-ben | flores101-devtest | 0.42730 | 10.0 | 1012 | 21155 |
| por-npi | flores101-devtest | 2.084 | 0.2 | 1012 | 19762 |
| spa-hin | flores101-devtest | 0.43371 | 16.0 | 1012 | 27743 |
| deu-ben | flores200-devtest | 0.44005 | 10.6 | 1012 | 21155 |
| deu-hin | flores200-devtest | 0.48448 | 22.3 | 1012 | 27743 |
| deu-hne | flores200-devtest | 0.42659 | 13.8 | 1012 | 26582 |
| deu-mag | flores200-devtest | 0.42477 | 14.0 | 1012 | 26516 |
| deu-npi | flores200-devtest | 5.870 | 0.1 | 1012 | 19762 |
| deu-pes | flores200-devtest | 0.42726 | 14.9 | 1012 | 24986 |
| deu-tgk | flores200-devtest | 0.40932 | 12.9 | 1012 | 25530 |
| deu-urd | flores200-devtest | 0.41250 | 14.4 | 1012 | 28098 |
| eng-ben | flores200-devtest | 0.51361 | 17.1 | 1012 | 21155 |
| eng-ckb | flores200-devtest | 0.45750 | 7.7 | 1012 | 21152 |
| eng-guj | flores200-devtest | 0.54231 | 22.4 | 1012 | 23840 |
| eng-hin | flores200-devtest | 0.58371 | 33.7 | 1012 | 27743 |
| eng-hne | flores200-devtest | 0.47591 | 19.9 | 1012 | 26582 |
| eng-mag | flores200-devtest | 0.51070 | 22.2 | 1012 | 26516 |
| eng-mar | flores200-devtest | 0.48733 | 14.8 | 1012 | 21810 |
| eng-pan | flores200-devtest | 0.45015 | 18.1 | 1012 | 27451 |
| eng-pes | flores200-devtest | 0.48588 | 21.1 | 1012 | 24986 |
| eng-prs | flores200-devtest | 0.51879 | 24.5 | 1012 | 25885 |
| eng-sin | flores200-devtest | 0.43823 | 10.6 | 1012 | 23278 |
| eng-tgk | flores200-devtest | 0.47323 | 17.8 | 1012 | 25530 |
| eng-urd | flores200-devtest | 0.48212 | 20.4 | 1012 | 28098 |
| fra-ben | flores200-devtest | 0.44029 | 11.0 | 1012 | 21155 |
| fra-ckb | flores200-devtest | 0.41353 | 5.3 | 1012 | 21152 |
| fra-hin | flores200-devtest | 0.48406 | 22.6 | 1012 | 27743 |
| fra-hne | flores200-devtest | 0.42353 | 13.9 | 1012 | 26582 |
| fra-mag | flores200-devtest | 0.42678 | 14.3 | 1012 | 26516 |
| fra-npi | flores200-devtest | 6.525 | 0.1 | 1012 | 19762 |
| fra-pes | flores200-devtest | 0.43526 | 15.5 | 1012 | 24986 |
| fra-tgk | flores200-devtest | 0.42982 | 13.7 | 1012 | 25530 |
| fra-urd | flores200-devtest | 0.41438 | 14.2 | 1012 | 28098 |
| por-ben | flores200-devtest | 0.43390 | 10.4 | 1012 | 21155 |
| por-ckb | flores200-devtest | 0.42303 | 5.6 | 1012 | 21152 |
| por-hin | flores200-devtest | 0.49524 | 23.6 | 1012 | 27743 |
| por-hne | flores200-devtest | 0.42269 | 13.9 | 1012 | 26582 |
| por-mag | flores200-devtest | 0.42753 | 15.0 | 1012 | 26516 |
| por-npi | flores200-devtest | 6.737 | 0.1 | 1012 | 19762 |
| por-pes | flores200-devtest | 0.43194 | 15.4 | 1012 | 24986 |
| por-tgk | flores200-devtest | 0.41860 | 13.2 | 1012 | 25530 |
| por-urd | flores200-devtest | 0.41799 | 14.8 | 1012 | 28098 |
| spa-ben | flores200-devtest | 0.41893 | 8.3 | 1012 | 21155 |
| spa-hin | flores200-devtest | 0.43777 | 16.4 | 1012 | 27743 |
| spa-kas_Arab | flores200-devtest | 9.380 | 0.1 | 1012 | 23514 |
| spa-npi | flores200-devtest | 7.518 | 0.2 | 1012 | 19762 |
| spa-pes | flores200-devtest | 0.40856 | 12.2 | 1012 | 24986 |
| spa-prs | flores200-devtest | 0.40361 | 12.8 | 1012 | 25885 |
| spa-tgk | flores200-devtest | 0.40100 | 10.8 | 1012 | 25530 |
| eng-hin | newstest2014 | 0.51249 | 23.6 | 2507 | 60872 |
| eng-guj | newstest2019 | 0.57282 | 25.5 | 998 | 21924 |
| deu-ben | ntrex128 | 0.43971 | 9.6 | 1997 | 40095 |
| deu-fas | ntrex128 | 0.41469 | 13.8 | 1997 | 50525 |
| deu-hin | ntrex128 | 0.42940 | 16.8 | 1997 | 55219 |
| deu-snd_Arab | ntrex128 | 6.129 | 0.1 | 1997 | 49866 |
| deu-urd | ntrex128 | 0.41881 | 14.5 | 1997 | 54259 |
| eng-ben | ntrex128 | 0.51555 | 16.6 | 1997 | 40095 |
| eng-fas | ntrex128 | 0.46895 | 19.7 | 1997 | 50525 |
| eng-guj | ntrex128 | 0.48990 | 17.1 | 1997 | 45335 |
| eng-hin | ntrex128 | 0.52307 | 26.9 | 1997 | 55219 |
| eng-mar | ntrex128 | 0.44580 | 10.4 | 1997 | 42375 |
| eng-nep | ntrex128 | 0.42955 | 8.4 | 1997 | 40570 |
| eng-pan | ntrex128 | 0.46141 | 19.6 | 1997 | 54355 |
| eng-sin | ntrex128 | 0.42236 | 9.7 | 1997 | 44429 |
| eng-snd_Arab | ntrex128 | 1.932 | 0.1 | 1997 | 49866 |
| eng-urd | ntrex128 | 0.49646 | 22.1 | 1997 | 54259 |
| fra-ben | ntrex128 | 0.41716 | 8.9 | 1997 | 40095 |
| fra-fas | ntrex128 | 0.41282 | 13.8 | 1997 | 50525 |
| fra-hin | ntrex128 | 0.42475 | 17.1 | 1997 | 55219 |
| fra-snd_Arab | ntrex128 | 6.047 | 0.0 | 1997 | 49866 |
| fra-urd | ntrex128 | 0.41536 | 14.8 | 1997 | 54259 |
| por-ben | ntrex128 | 0.43855 | 9.9 | 1997 | 40095 |
| por-fas | ntrex128 | 0.42010 | 14.4 | 1997 | 50525 |
| por-hin | ntrex128 | 0.43275 | 17.6 | 1997 | 55219 |
| por-snd_Arab | ntrex128 | 6.336 | 0.1 | 1997 | 49866 |
| por-urd | ntrex128 | 0.42484 | 15.2 | 1997 | 54259 |
| spa-ben | ntrex128 | 0.44905 | 10.3 | 1997 | 40095 |
| spa-fas | ntrex128 | 0.42207 | 14.1 | 1997 | 50525 |
| spa-hin | ntrex128 | 0.43380 | 17.6 | 1997 | 55219 |
| spa-snd_Arab | ntrex128 | 5.551 | 0.0 | 1997 | 49866 |
| spa-urd | ntrex128 | 0.42434 | 15.0 | 1997 | 54259 |
| eng-ben | tico19-test | 0.51563 | 17.9 | 2100 | 51695 |
| eng-ckb | tico19-test | 0.46188 | 8.9 | 2100 | 50500 |
| eng-fas | tico19-test | 0.53182 | 25.8 | 2100 | 59779 |
| eng-hin | tico19-test | 0.63128 | 41.6 | 2100 | 62680 |
| eng-mar | tico19-test | 0.45619 | 12.9 | 2100 | 50872 |
| eng-nep | tico19-test | 0.53413 | 17.6 | 2100 | 48363 |
| eng-prs | tico19-test | 0.44101 | 17.3 | 2100 | 62972 |
| eng-pus | tico19-test | 0.47063 | 20.5 | 2100 | 66213 |
| eng-urd | tico19-test | 0.51054 | 22.0 | 2100 | 65312 |
| fra-fas | tico19-test | 0.43476 | 17.9 | 2100 | 59779 |
| fra-hin | tico19-test | 0.48625 | 25.6 | 2100 | 62680 |
| fra-nep | tico19-test | 0.41153 | 9.7 | 2100 | 48363 |
| fra-urd | tico19-test | 0.40482 | 14.4 | 2100 | 65312 |
| por-ben | tico19-test | 0.45814 | 12.5 | 2100 | 51695 |
| por-ckb | tico19-test | 0.41684 | 5.6 | 2100 | 50500 |
| por-fas | tico19-test | 0.49181 | 21.3 | 2100 | 59779 |
| por-hin | tico19-test | 0.55759 | 31.1 | 2100 | 62680 |
| por-mar | tico19-test | 0.40067 | 9.1 | 2100 | 50872 |
| por-nep | tico19-test | 0.47378 | 12.1 | 2100 | 48363 |
| por-pus | tico19-test | 0.42496 | 15.9 | 2100 | 66213 |
| por-urd | tico19-test | 0.45560 | 16.6 | 2100 | 65312 |
| spa-ben | tico19-test | 0.45751 | 12.7 | 2100 | 51695 |
| spa-ckb | tico19-test | 0.41568 | 5.4 | 2100 | 50500 |
| spa-fas | tico19-test | 0.48974 | 21.0 | 2100 | 59779 |
| spa-hin | tico19-test | 0.55641 | 30.9 | 2100 | 62680 |
| spa-mar | tico19-test | 0.40329 | 9.4 | 2100 | 50872 |
| spa-nep | tico19-test | 0.47164 | 12.1 | 2100 | 48363 |
| spa-prs | tico19-test | 0.41879 | 14.3 | 2100 | 62972 |
| spa-pus | tico19-test | 0.41714 | 15.1 | 2100 | 66213 |
| spa-urd | tico19-test | 0.44931 | 15.3 | 2100 | 65312 |

## 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 10:05:20 EEST 2024
* port machine: LM0-400-22516.local
