|
--- |
|
library_name: transformers |
|
language: |
|
- bru |
|
- cmo |
|
- de |
|
- en |
|
- es |
|
- fr |
|
- kha |
|
- km |
|
- kxm |
|
- mnw |
|
- ngt |
|
- pt |
|
- vi |
|
- wbm |
|
|
|
tags: |
|
- translation |
|
- opus-mt-tc-bible |
|
|
|
license: apache-2.0 |
|
model-index: |
|
- name: opus-mt-tc-bible-big-deu_eng_fra_por_spa-mkh |
|
results: |
|
- task: |
|
name: Translation deu-vie |
|
type: translation |
|
args: deu-vie |
|
dataset: |
|
name: flores200-devtest |
|
type: flores200-devtest |
|
args: deu-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 33.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53535 |
|
- task: |
|
name: Translation eng-vie |
|
type: translation |
|
args: eng-vie |
|
dataset: |
|
name: flores200-devtest |
|
type: flores200-devtest |
|
args: eng-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 42.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.60021 |
|
- task: |
|
name: Translation fra-vie |
|
type: translation |
|
args: fra-vie |
|
dataset: |
|
name: flores200-devtest |
|
type: flores200-devtest |
|
args: fra-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 34.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.54168 |
|
- task: |
|
name: Translation por-vie |
|
type: translation |
|
args: por-vie |
|
dataset: |
|
name: flores200-devtest |
|
type: flores200-devtest |
|
args: por-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 35.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.55046 |
|
- task: |
|
name: Translation spa-vie |
|
type: translation |
|
args: spa-vie |
|
dataset: |
|
name: flores200-devtest |
|
type: flores200-devtest |
|
args: spa-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 28.1 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.50262 |
|
- task: |
|
name: Translation deu-vie |
|
type: translation |
|
args: deu-vie |
|
dataset: |
|
name: flores101-devtest |
|
type: flores_101 |
|
args: deu vie devtest |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 33.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53623 |
|
- task: |
|
name: Translation eng-vie |
|
type: translation |
|
args: eng-vie |
|
dataset: |
|
name: flores101-devtest |
|
type: flores_101 |
|
args: eng vie devtest |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 42.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59986 |
|
- task: |
|
name: Translation por-vie |
|
type: translation |
|
args: por-vie |
|
dataset: |
|
name: flores101-devtest |
|
type: flores_101 |
|
args: por vie devtest |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 35.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.54819 |
|
- task: |
|
name: Translation deu-vie |
|
type: translation |
|
args: deu-vie |
|
dataset: |
|
name: ntrex128 |
|
type: ntrex128 |
|
args: deu-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 31.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.51996 |
|
- task: |
|
name: Translation eng-vie |
|
type: translation |
|
args: eng-vie |
|
dataset: |
|
name: ntrex128 |
|
type: ntrex128 |
|
args: eng-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 42.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.60050 |
|
- task: |
|
name: Translation fra-vie |
|
type: translation |
|
args: fra-vie |
|
dataset: |
|
name: ntrex128 |
|
type: ntrex128 |
|
args: fra-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 31.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.51988 |
|
- task: |
|
name: Translation por-vie |
|
type: translation |
|
args: por-vie |
|
dataset: |
|
name: ntrex128 |
|
type: ntrex128 |
|
args: por-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 33.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.52931 |
|
- task: |
|
name: Translation spa-vie |
|
type: translation |
|
args: spa-vie |
|
dataset: |
|
name: ntrex128 |
|
type: ntrex128 |
|
args: spa-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 33.1 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53347 |
|
- task: |
|
name: Translation deu-vie |
|
type: translation |
|
args: deu-vie |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: deu-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 25.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.45222 |
|
- task: |
|
name: Translation eng-vie |
|
type: translation |
|
args: eng-vie |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: eng-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 39.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.56413 |
|
- task: |
|
name: Translation fra-vie |
|
type: translation |
|
args: fra-vie |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: fra-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 35.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53078 |
|
- 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: 24.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.43068 |
|
- task: |
|
name: Translation spa-vie |
|
type: translation |
|
args: spa-vie |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: spa-vie |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 34.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.51783 |
|
--- |
|
# opus-mt-tc-bible-big-deu_eng_fra_por_spa-mkh |
|
|
|
## 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 Mon-Khmer languages (mkh). |
|
|
|
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): bru cmo kha khm kxm mnw ngt vie wbm |
|
- Valid Target Language Labels: >>aem<< >>alk<< >>aml<< >>bbh<< >>bdq<< >>bgk<< >>bgl<< >>blr<< >>brb<< >>bru<< >>brv<< >>btq<< >>caq<< >>cbn<< >>cma<< >>cmo<< >>cog<< >>crv<< >>crw<< >>cua<< >>cwg<< >>dnu<< >>hal<< >>hld<< >>hnu<< >>hre<< >>huo<< >>jah<< >>jeh<< >>jhi<< >>kdt<< >>kha<< >>khf<< >>khm<< >>kjg<< >>kjm<< >>knq<< >>kns<< >>kpm<< >>krr<< >>krv<< >>kta<< >>ktv<< >>kuf<< >>kxm<< >>kxy<< >>lbn<< >>lbo<< >>lcp<< >>lnh<< >>lwl<< >>lyg<< >>mef<< >>mhe<< >>mlf<< >>mml<< >>mng<< >>mnn<< >>mnq<< >>mnw<< >>moo<< >>mqt<< >>mra<< >>mtq<< >>mzt<< >>ncb<< >>ncq<< >>nev<< >>ngt<< >>ngt_Latn<< >>nik<< >>nuo<< >>nyl<< >>omx<< >>oog<< >>oyb<< >>pac<< >>pbv<< >>pcb<< >>pce<< >>phg<< >>pkt<< >>pll<< >>ply<< >>pnx<< >>prk<< >>prt<< >>puo<< >>rbb<< >>ren<< >>ril<< >>rka<< >>rmx<< >>sbo<< >>scb<< >>scq<< >>sct<< >>sea<< >>sed<< >>sii<< >>smu<< >>spu<< >>sqq<< >>ssm<< >>sss<< >>stg<< >>sti<< >>stt<< >>stu<< >>syo<< >>sza<< >>szc<< >>tdf<< >>tdr<< >>tea<< >>tef<< >>thm<< >>tkz<< >>tlq<< >>tmo<< >>tnz<< >>tou<< >>tpu<< >>tth<< >>tto<< >>tyh<< >>uuu<< >>vie<< >>vwa<< >>wbm<< >>xao<< >>xkk<< >>xnh<< >>xxx<< >>yin<< >>zng<< |
|
- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-mkh/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-mkh/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. `>>bru<<` |
|
|
|
## 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 = [ |
|
">>bru<< Replace this with text in an accepted source language.", |
|
">>wbm<< This is the second sentence." |
|
] |
|
|
|
model_name = "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-mkh" |
|
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-mkh") |
|
print(pipe(">>bru<< 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-mkh/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-mkh/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-mkh/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-mkh/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-vie | tatoeba-test-v2021-08-07 | 0.45222 | 25.3 | 400 | 3768 | |
|
| eng-kha | tatoeba-test-v2021-08-07 | 9.076 | 0.4 | 1314 | 9269 | |
|
| eng-vie | tatoeba-test-v2021-08-07 | 0.56413 | 39.0 | 2500 | 24427 | |
|
| fra-vie | tatoeba-test-v2021-08-07 | 0.53078 | 35.6 | 1299 | 13219 | |
|
| spa-vie | tatoeba-test-v2021-08-07 | 0.51783 | 34.0 | 594 | 4740 | |
|
| deu-vie | flores101-devtest | 0.53623 | 33.9 | 1012 | 33331 | |
|
| eng-khm | flores101-devtest | 0.42022 | 1.4 | 1012 | 7006 | |
|
| eng-vie | flores101-devtest | 0.59986 | 42.7 | 1012 | 33331 | |
|
| por-vie | flores101-devtest | 0.54819 | 35.7 | 1012 | 33331 | |
|
| deu-vie | flores200-devtest | 0.53535 | 33.9 | 1012 | 33331 | |
|
| eng-khm | flores200-devtest | 0.41987 | 1.3 | 1012 | 7006 | |
|
| eng-vie | flores200-devtest | 0.60021 | 42.6 | 1012 | 33331 | |
|
| fra-khm | flores200-devtest | 0.40241 | 2.3 | 1012 | 7006 | |
|
| fra-vie | flores200-devtest | 0.54168 | 34.6 | 1012 | 33331 | |
|
| por-khm | flores200-devtest | 0.41582 | 2.3 | 1012 | 7006 | |
|
| por-vie | flores200-devtest | 0.55046 | 35.9 | 1012 | 33331 | |
|
| spa-vie | flores200-devtest | 0.50262 | 28.1 | 1012 | 33331 | |
|
| deu-khm | ntrex128 | 0.44917 | 3.2 | 1997 | 15866 | |
|
| deu-vie | ntrex128 | 0.51996 | 31.2 | 1997 | 64655 | |
|
| eng-khm | ntrex128 | 0.50215 | 1.6 | 1997 | 15866 | |
|
| eng-vie | ntrex128 | 0.60050 | 42.7 | 1997 | 64655 | |
|
| fra-khm | ntrex128 | 0.44024 | 2.3 | 1997 | 15866 | |
|
| fra-vie | ntrex128 | 0.51988 | 31.7 | 1997 | 64655 | |
|
| por-khm | ntrex128 | 0.46752 | 2.4 | 1997 | 15866 | |
|
| por-vie | ntrex128 | 0.52931 | 33.3 | 1997 | 64655 | |
|
| spa-khm | ntrex128 | 0.46166 | 2.5 | 1997 | 15866 | |
|
| spa-vie | ntrex128 | 0.53347 | 33.1 | 1997 | 64655 | |
|
| eng-khm | tico19-test | 0.54267 | 3.4 | 2100 | 15810 | |
|
| fra-khm | tico19-test | 0.45333 | 4.8 | 2100 | 15810 | |
|
| por-khm | tico19-test | 0.52339 | 6.8 | 2100 | 15810 | |
|
| spa-khm | tico19-test | 0.51848 | 6.8 | 2100 | 15810 | |
|
|
|
## 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 |
|
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* transformers version: 4.45.1 |
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* OPUS-MT git hash: 0882077 |
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* port time: Tue Oct 8 10:19:52 EEST 2024 |
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* port machine: LM0-400-22516.local |
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