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.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+*.spm filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- be
+- en
+- ru
+- uk
+- zle
+
+tags:
+- translation
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-en-zle
+  results:
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng rus devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.7
+  - task:
+      name: Translation eng-ukr
+      type: translation
+      args: eng-ukr
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng ukr devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.1
+  - task:
+      name: Translation eng-bel
+      type: translation
+      args: eng-bel
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-bel
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 24.9
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 45.5
+  - task:
+      name: Translation eng-ukr
+      type: translation
+      args: eng-ukr
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-ukr
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 37.7
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 33.7
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2012
+      type: wmt-2012-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 36.8
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2013
+      type: wmt-2013-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 26.9
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2014
+      type: wmt-2014-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 43.5
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2015
+      type: wmt-2015-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 34.9
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2016
+      type: wmt-2016-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 33.1
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2017
+      type: wmt-2017-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 37.3
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2018
+      type: wmt-2018-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.9
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2019
+      type: wmt-2019-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.8
+  - task:
+      name: Translation eng-rus
+      type: translation
+      args: eng-rus
+    dataset:
+      name: newstest2020
+      type: wmt-2020-news
+      args: eng-rus
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.5
+---
+# opus-mt-tc-big-en-zle
+
+Neural machine translation model for translating from English (en) to East Slavic languages (zle).
+
+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).
+
+* 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.)
+
+```
+@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",
+}
+```
+
+## Model info
+
+* Release: 2022-03-13
+* source language(s): eng
+* target language(s): bel rus ukr
+* valid target language labels: >>bel<< >>rus<< >>ukr<<
+* model: transformer-big
+* data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+* tokenization: SentencePiece (spm32k,spm32k)
+* original model: [opusTCv20210807+bt_transformer-big_2022-03-13.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zle/opusTCv20210807+bt_transformer-big_2022-03-13.zip)
+* more information released models: [OPUS-MT eng-zle README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-zle/README.md)
+* more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian)
+
+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<<`
+
+## Usage
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>rus<< Are they coming as well?",
+    ">>rus<< I didn't let Tom do what he wanted to do."
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-en-zle"
+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) )
+
+# expected output:
+#     Они тоже приедут?
+#     Я не позволил Тому сделать то, что он хотел.
+```
+
+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-big-en-zle")
+print(pipe(">>rus<< Are they coming as well?"))
+
+# expected output: Они тоже приедут?
+```
+
+## Benchmarks
+
+* test set translations: [opusTCv20210807+bt_transformer-big_2022-03-13.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zle/opusTCv20210807+bt_transformer-big_2022-03-13.test.txt)
+* test set scores: [opusTCv20210807+bt_transformer-big_2022-03-13.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zle/opusTCv20210807+bt_transformer-big_2022-03-13.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 |
+|----------|---------|-------|-------|-------|--------|
+| eng-bel | tatoeba-test-v2021-08-07 | 0.50345 | 24.9 | 2500 | 16237 |
+| eng-rus | tatoeba-test-v2021-08-07 | 0.66182 | 45.5 | 19425 | 134296 |
+| eng-ukr | tatoeba-test-v2021-08-07 | 0.60175 | 37.7 | 13127 | 80998 |
+| eng-bel | flores101-devtest | 0.42078 | 11.2 | 1012 | 24829 |
+| eng-rus | flores101-devtest | 0.59654 | 32.7 | 1012 | 23295 |
+| eng-ukr | flores101-devtest | 0.60131 | 32.1 | 1012 | 22810 |
+| eng-rus | newstest2012 | 0.62842 | 36.8 | 3003 | 64790 |
+| eng-rus | newstest2013 | 0.54627 | 26.9 | 3000 | 58560 |
+| eng-rus | newstest2014 | 0.68348 | 43.5 | 3003 | 61603 |
+| eng-rus | newstest2015 | 0.62621 | 34.9 | 2818 | 55915 |
+| eng-rus | newstest2016 | 0.60595 | 33.1 | 2998 | 62014 |
+| eng-rus | newstest2017 | 0.64249 | 37.3 | 3001 | 60253 |
+| eng-rus | newstest2018 | 0.61219 | 32.9 | 3000 | 61907 |
+| eng-rus | newstest2019 | 0.57902 | 31.8 | 1997 | 48147 |
+| eng-rus | newstest2020 | 0.52939 | 25.5 | 2002 | 47083 |
+| eng-rus | tico19-test | 0.59314 | 33.7 | 2100 | 55843 |
+
+## Acknowledgements
+
+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.
+
+## Model conversion info
+
+* transformers version: 4.16.2
+* OPUS-MT git hash: 1bdabf7
+* port time: Thu Mar 24 01:58:40 EET 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,25 @@
+eng-bel	flores101-dev	0.40686	9.9	997	23996
+eng-rus	flores101-dev	0.59726	32.8	997	22657
+eng-ukr	flores101-dev	0.59100	30.8	997	21841
+eng-bel	flores101-devtest	0.42078	11.2	1012	24829
+eng-rus	flores101-devtest	0.59654	32.7	1012	23295
+eng-ukr	flores101-devtest	0.60131	32.1	1012	22810
+eng-rus	newstest2012	0.62842	36.8	3003	64790
+eng-rus	newstest2013	0.54627	26.9	3000	58560
+eng-rus	newstest2014	0.68348	43.5	3003	61603
+eng-rus	newstest2015	0.62621	34.9	2818	55915
+eng-rus	newstest2016	0.60595	33.1	2998	62014
+eng-rus	newstest2017	0.64249	37.3	3001	60253
+eng-rus	newstest2018	0.61219	32.9	3000	61907
+eng-rus	newstest2019	0.57902	31.8	1997	48147
+eng-rus	newstest2020	0.52939	25.5	2002	47083
+eng-bel	tatoeba-test-v2020-07-28	0.50348	24.9	2500	16237
+eng-rus	tatoeba-test-v2020-07-28	0.66185	46.3	10000	66872
+eng-ukr	tatoeba-test-v2020-07-28	0.59540	37.4	10000	60756
+eng-bel	tatoeba-test-v2021-03-30	0.50348	24.9	2500	16237
+eng-rus	tatoeba-test-v2021-03-30	0.65983	45.2	15118	101983
+eng-ukr	tatoeba-test-v2021-03-30	0.60091	37.7	11969	73416
+eng-bel	tatoeba-test-v2021-08-07	0.50345	24.9	2500	16237
+eng-rus	tatoeba-test-v2021-08-07	0.66182	45.5	19425	134296
+eng-ukr	tatoeba-test-v2021-08-07	0.60175	37.7	13127	80998
+eng-rus	tico19-test	0.59314	33.7	2100	55843

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+  "scale_embedding": true,
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+  "static_position_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.18.0.dev0",
+  "use_cache": true,
+  "vocab_size": 61577
+}

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special_tokens_map.json

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tokenizer_config.json

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