Initial commit
Browse files- .gitattributes +1 -0
- README.md +225 -0
- benchmark_results.txt +30 -0
- benchmark_translations.zip +3 -0
- config.json +45 -0
- pytorch_model.bin +3 -0
- source.spm +3 -0
- special_tokens_map.json +1 -0
- target.spm +3 -0
- tokenizer_config.json +1 -0
- vocab.json +0 -0
.gitattributes
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README.md
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1 |
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---
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language:
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- be
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- ru
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- uk
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- zle
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tags:
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- translation
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license: cc-by-4.0
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model-index:
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- name: opus-mt-tc-big-zle-zle
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results:
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- task:
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name: Translation rus-ukr
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type: translation
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args: rus-ukr
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dataset:
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name: flores101-devtest
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type: flores_101
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args: rus ukr devtest
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metrics:
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- name: BLEU
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type: bleu
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value: 25.5
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- task:
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name: Translation ukr-rus
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type: translation
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args: ukr-rus
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dataset:
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name: flores101-devtest
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type: flores_101
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args: ukr rus devtest
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metrics:
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- name: BLEU
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type: bleu
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value: 28.3
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+
- task:
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name: Translation bel-rus
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type: translation
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args: bel-rus
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dataset:
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name: tatoeba-test-v2021-08-07
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type: tatoeba_mt
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args: bel-rus
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metrics:
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- name: BLEU
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type: bleu
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value: 68.6
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- task:
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name: Translation bel-ukr
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type: translation
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args: bel-ukr
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dataset:
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name: tatoeba-test-v2021-08-07
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type: tatoeba_mt
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args: bel-ukr
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metrics:
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- name: BLEU
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type: bleu
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value: 65.5
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- task:
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name: Translation rus-bel
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type: translation
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args: rus-bel
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dataset:
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name: tatoeba-test-v2021-08-07
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type: tatoeba_mt
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args: rus-bel
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metrics:
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- name: BLEU
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type: bleu
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value: 50.3
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- task:
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name: Translation rus-ukr
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type: translation
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args: rus-ukr
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dataset:
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name: tatoeba-test-v2021-08-07
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type: tatoeba_mt
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args: rus-ukr
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metrics:
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- name: BLEU
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type: bleu
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value: 70.1
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- task:
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name: Translation ukr-bel
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type: translation
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args: ukr-bel
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dataset:
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name: tatoeba-test-v2021-08-07
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type: tatoeba_mt
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args: ukr-bel
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metrics:
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- name: BLEU
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type: bleu
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value: 58.9
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- task:
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name: Translation ukr-rus
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type: translation
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args: ukr-rus
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dataset:
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name: tatoeba-test-v2021-08-07
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type: tatoeba_mt
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args: ukr-rus
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metrics:
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- name: BLEU
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type: bleu
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value: 75.7
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---
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# opus-mt-tc-big-zle-zle
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Neural machine translation model for translating from East Slavic languages (zle) to East Slavic languages (zle).
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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).
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* Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
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```
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@inproceedings{tiedemann-thottingal-2020-opus,
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title = "{OPUS}-{MT} {--} Building open translation services for the World",
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author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh},
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booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
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month = nov,
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year = "2020",
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address = "Lisboa, Portugal",
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publisher = "European Association for Machine Translation",
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url = "https://aclanthology.org/2020.eamt-1.61",
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pages = "479--480",
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}
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@inproceedings{tiedemann-2020-tatoeba,
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title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
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author = {Tiedemann, J{\"o}rg},
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booktitle = "Proceedings of the Fifth Conference on Machine Translation",
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month = nov,
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year = "2020",
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address = "Online",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2020.wmt-1.139",
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pages = "1174--1182",
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}
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```
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## Model info
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* Release: 2022-03-07
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* source language(s): bel rus ukr
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* target language(s): bel rus ukr
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* valid target language labels: >>bel<< >>rus<< >>ukr<<
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* model: transformer-big
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* data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
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* tokenization: SentencePiece (spm32k,spm32k)
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* original model: [opusTCv20210807+bt_transformer-big_2022-03-07.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zle/opusTCv20210807+bt_transformer-big_2022-03-07.zip)
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* more information released models: [OPUS-MT zle-zle README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zle-zle/README.md)
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* more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian)
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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. `>>bel<<`
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## Usage
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A short example code:
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```python
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from transformers import MarianMTModel, MarianTokenizer
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src_text = [
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">>ukr<< Кот мёртвый.",
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">>bel<< Джон живе в Нью-Йорку."
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]
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model_name = "pytorch-models/opus-mt-tc-big-zle-zle"
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tokenizer = MarianTokenizer.from_pretrained(model_name)
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model = MarianMTModel.from_pretrained(model_name)
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translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
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for t in translated:
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print( tokenizer.decode(t, skip_special_tokens=True) )
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# expected output:
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# Кіт мертвий.
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# Джон жыве ў Нью-Йорку.
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```
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You can also use OPUS-MT models with the transformers pipelines, for example:
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```python
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from transformers import pipeline
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pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-zle-zle")
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print(pipe(">>ukr<< Кот мёртвый."))
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# expected output: Кіт мертвий.
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```
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## Benchmarks
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* test set translations: [opusTCv20210807+bt_transformer-big_2022-03-07.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zle/opusTCv20210807+bt_transformer-big_2022-03-07.test.txt)
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* test set scores: [opusTCv20210807+bt_transformer-big_2022-03-07.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zle/opusTCv20210807+bt_transformer-big_2022-03-07.eval.txt)
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* benchmark results: [benchmark_results.txt](benchmark_results.txt)
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* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
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| langpair | testset | chr-F | BLEU | #sent | #words |
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|----------|---------|-------|-------|-------|--------|
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| bel-rus | tatoeba-test-v2021-08-07 | 0.82526 | 68.6 | 2500 | 18895 |
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| bel-ukr | tatoeba-test-v2021-08-07 | 0.81036 | 65.5 | 2355 | 15179 |
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| rus-bel | tatoeba-test-v2021-08-07 | 0.66943 | 50.3 | 2500 | 18756 |
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| rus-ukr | tatoeba-test-v2021-08-07 | 0.83639 | 70.1 | 10000 | 60212 |
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| ukr-bel | tatoeba-test-v2021-08-07 | 0.75368 | 58.9 | 2355 | 15175 |
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| ukr-rus | tatoeba-test-v2021-08-07 | 0.86806 | 75.7 | 10000 | 60387 |
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| bel-rus | flores101-devtest | 0.47960 | 14.5 | 1012 | 23295 |
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| bel-ukr | flores101-devtest | 0.47335 | 12.8 | 1012 | 22810 |
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| rus-ukr | flores101-devtest | 0.55287 | 25.5 | 1012 | 22810 |
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| ukr-rus | flores101-devtest | 0.56224 | 28.3 | 1012 | 23295 |
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## Acknowledgements
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The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
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## Model conversion info
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* transformers version: 4.16.2
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* OPUS-MT git hash: 1bdabf7
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* port time: Thu Mar 24 00:15:39 EET 2022
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* port machine: LM0-400-22516.local
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benchmark_results.txt
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bel-rus flores101-dev 0.47944 13.8 997 22657
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bel-ukr flores101-dev 0.47149 12.2 997 21841
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rus-bel flores101-dev 0.31702 8.0 997 23996
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rus-ukr flores101-dev 0.54870 24.7 997 21841
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bel-rus flores101-devtest 0.47960 14.5 1012 23295
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bel-ukr flores101-devtest 0.47335 12.8 1012 22810
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rus-bel flores101-devtest 0.31398 8.4 1012 24829
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rus-ukr flores101-devtest 0.55287 25.5 1012 22810
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ukr-bel flores101-devtest 0.37165 10.6 1012 24829
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ukr-rus flores101-devtest 0.56224 28.3 1012 23295
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ukr-bel flores101-dev 0.37071 10.0 997 23996
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ukr-rus flores101-dev 0.55575 27.4 997 22657
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bel-rus tatoeba-test-v2020-07-28 0.82526 68.6 2500 18895
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bel-ukr tatoeba-test-v2020-07-28 0.81036 65.5 2355 15179
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rus-bel tatoeba-test-v2020-07-28 0.66942 50.3 2500 18756
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rus-ukr tatoeba-test-v2020-07-28 0.83639 70.1 10000 60212
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ukr-bel tatoeba-test-v2020-07-28 0.75362 58.9 2355 15175
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ukr-rus tatoeba-test-v2020-07-28 0.86806 75.7 10000 60387
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bel-rus tatoeba-test-v2021-03-30 0.82526 68.6 2500 18895
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bel-ukr tatoeba-test-v2021-03-30 0.81036 65.5 2355 15179
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rus-bel tatoeba-test-v2021-03-30 0.66942 50.3 2500 18756
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rus-ukr tatoeba-test-v2021-03-30 0.83639 70.1 10000 60212
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ukr-bel tatoeba-test-v2021-03-30 0.75362 58.9 2355 15175
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ukr-rus tatoeba-test-v2021-03-30 0.86806 75.7 10000 60387
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bel-rus tatoeba-test-v2021-08-07 0.82526 68.6 2500 18895
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bel-ukr tatoeba-test-v2021-08-07 0.81036 65.5 2355 15179
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rus-bel tatoeba-test-v2021-08-07 0.66943 50.3 2500 18756
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rus-ukr tatoeba-test-v2021-08-07 0.83639 70.1 10000 60212
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+
ukr-bel tatoeba-test-v2021-08-07 0.75368 58.9 2355 15175
|
30 |
+
ukr-rus tatoeba-test-v2021-08-07 0.86806 75.7 10000 60387
|
benchmark_translations.zip
ADDED
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1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:b71500515d5512f8a8a40f6de36212f3aac0607a128f420d4f7c7d8c4792a05b
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3 |
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size 6062613
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config.json
ADDED
@@ -0,0 +1,45 @@
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{
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2 |
+
"activation_dropout": 0.0,
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3 |
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"activation_function": "relu",
|
4 |
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"architectures": [
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5 |
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"MarianMTModel"
|
6 |
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],
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"bad_words_ids": [
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9 |
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[
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10 |
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36262
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|
12 |
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"d_model": 1024,
|
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"decoder_attention_heads": 16,
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17 |
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|
20 |
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26 |
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27 |
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"eos_token_id": 2171,
|
28 |
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"forced_eos_token_id": 2171,
|
29 |
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"init_std": 0.02,
|
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"is_encoder_decoder": true,
|
31 |
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"max_length": 512,
|
32 |
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"max_position_embeddings": 1024,
|
33 |
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"model_type": "marian",
|
34 |
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"normalize_embedding": false,
|
35 |
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"num_beams": 4,
|
36 |
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"num_hidden_layers": 6,
|
37 |
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"pad_token_id": 36262,
|
38 |
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"scale_embedding": true,
|
39 |
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"share_encoder_decoder_embeddings": true,
|
40 |
+
"static_position_embeddings": true,
|
41 |
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"torch_dtype": "float16",
|
42 |
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"transformers_version": "4.18.0.dev0",
|
43 |
+
"use_cache": true,
|
44 |
+
"vocab_size": 36263
|
45 |
+
}
|
pytorch_model.bin
ADDED
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:8935f9beb8f15e2ba68a3e06f5be58e2629ed90bcc758f545ca6860a8dd5ff05
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size 501412227
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source.spm
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:9b49b740c96c0d82a918f7986274b4352cce26420bf166db9dddd9a2e96e40aa
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3 |
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size 1012800
|
special_tokens_map.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}
|
target.spm
ADDED
@@ -0,0 +1,3 @@
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:4c5be1deafcea3cd0a23b164ea9645df09e394a91959e35bfd5140db879c5ff9
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3 |
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size 1012444
|
tokenizer_config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"source_lang": "zle", "target_lang": "zle", "unk_token": "<unk>", "eos_token": "</s>", "pad_token": "<pad>", "model_max_length": 512, "sp_model_kwargs": {}, "separate_vocabs": false, "special_tokens_map_file": null, "name_or_path": "marian-models/opusTCv20210807+bt_transformer-big_2022-03-07/zle-zle", "tokenizer_class": "MarianTokenizer"}
|
vocab.json
ADDED
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