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README.md

@@ -0,0 +1,526 @@
+---
+language:
+- da
+- fo
+- gmq
+- is
+- nb
+- nn
+- no
+- sv
+
+tags:
+- translation
+- opus-mt-tc
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-gmq-gmq
+  results:
+  - task:
+      name: Translation isl-swe
+      type: translation
+      args: isl-swe
+    dataset:
+      name: europeana2021
+      type: europeana2021
+      args: isl-swe
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.2
+       - name: chr-F
+         type: chrf
+         value: 0.45562
+  - task:
+      name: Translation nob-isl
+      type: translation
+      args: nob-isl
+    dataset:
+      name: europeana2021
+      type: europeana2021
+      args: nob-isl
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 29.7
+       - name: chr-F
+         type: chrf
+         value: 0.54171
+  - task:
+      name: Translation nob-swe
+      type: translation
+      args: nob-swe
+    dataset:
+      name: europeana2021
+      type: europeana2021
+      args: nob-swe
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 54.0
+       - name: chr-F
+         type: chrf
+         value: 0.73891
+  - task:
+      name: Translation dan-isl
+      type: translation
+      args: dan-isl
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan isl devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.2
+       - name: chr-F
+         type: chrf
+         value: 0.50227
+  - task:
+      name: Translation dan-nob
+      type: translation
+      args: dan-nob
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan nob devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.6
+       - name: chr-F
+         type: chrf
+         value: 0.58445
+  - task:
+      name: Translation dan-swe
+      type: translation
+      args: dan-swe
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan swe devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 38.5
+       - name: chr-F
+         type: chrf
+         value: 0.65000
+  - task:
+      name: Translation isl-dan
+      type: translation
+      args: isl-dan
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl dan devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 27.2
+       - name: chr-F
+         type: chrf
+         value: 0.53630
+  - task:
+      name: Translation isl-nob
+      type: translation
+      args: isl-nob
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl nob devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 20.5
+       - name: chr-F
+         type: chrf
+         value: 0.49434
+  - task:
+      name: Translation isl-swe
+      type: translation
+      args: isl-swe
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl swe devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 26.0
+       - name: chr-F
+         type: chrf
+         value: 0.53373
+  - task:
+      name: Translation nob-dan
+      type: translation
+      args: nob-dan
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob dan devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.7
+       - name: chr-F
+         type: chrf
+         value: 0.59657
+  - task:
+      name: Translation nob-isl
+      type: translation
+      args: nob-isl
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob isl devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 18.9
+       - name: chr-F
+         type: chrf
+         value: 0.47432
+  - task:
+      name: Translation nob-swe
+      type: translation
+      args: nob-swe
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob swe devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.3
+       - name: chr-F
+         type: chrf
+         value: 0.60030
+  - task:
+      name: Translation swe-dan
+      type: translation
+      args: swe-dan
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe dan devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 39.0
+       - name: chr-F
+         type: chrf
+         value: 0.64340
+  - task:
+      name: Translation swe-isl
+      type: translation
+      args: swe-isl
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe isl devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.7
+       - name: chr-F
+         type: chrf
+         value: 0.49590
+  - task:
+      name: Translation swe-nob
+      type: translation
+      args: swe-nob
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe nob devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.9
+       - name: chr-F
+         type: chrf
+         value: 0.58336
+  - task:
+      name: Translation dan-nob
+      type: translation
+      args: dan-nob
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-nob
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 78.2
+       - name: chr-F
+         type: chrf
+         value: 0.87556
+  - task:
+      name: Translation dan-swe
+      type: translation
+      args: dan-swe
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-swe
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 72.5
+       - name: chr-F
+         type: chrf
+         value: 0.83556
+  - task:
+      name: Translation nno-nob
+      type: translation
+      args: nno-nob
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nno-nob
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 78.9
+       - name: chr-F
+         type: chrf
+         value: 0.88349
+  - task:
+      name: Translation nob-dan
+      type: translation
+      args: nob-dan
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nob-dan
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 73.9
+       - name: chr-F
+         type: chrf
+         value: 0.85345
+  - task:
+      name: Translation nob-nno
+      type: translation
+      args: nob-nno
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nob-nno
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 55.2
+       - name: chr-F
+         type: chrf
+         value: 0.74571
+  - task:
+      name: Translation nob-swe
+      type: translation
+      args: nob-swe
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nob-swe
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 73.9
+       - name: chr-F
+         type: chrf
+         value: 0.84747
+  - task:
+      name: Translation swe-dan
+      type: translation
+      args: swe-dan
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-dan
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 72.6
+       - name: chr-F
+         type: chrf
+         value: 0.83392
+  - task:
+      name: Translation swe-nob
+      type: translation
+      args: swe-nob
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-nob
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 76.3
+       - name: chr-F
+         type: chrf
+         value: 0.85815
+---
+# opus-mt-tc-big-gmq-gmq
+
+## 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 North Germanic languages (gmq) to North Germanic languages (gmq).
+
+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**: 2022-07-29
+- **License:** CC-BY-4.0
+- **Language(s):**  
+  - Source Language(s): dan fao isl nno nob nor swe
+  - Target Language(s): dan isl nno nob nor swe
+  - Valid Target Language Labels: >>dan<< >>isl<< >>nno<< >>nob<< >>nor<< >>swe<<
+- **Original Model**: [opusTCv20210807_transformer-big_2022-07-29.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-gmq/opusTCv20210807_transformer-big_2022-07-29.zip)
+- **Resources for more information:**
+  - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+  - More information about released models for this language pair: [OPUS-MT gmq-gmq README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmq-gmq/README.md)
+  - [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/
+
+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. `>>dan<<`
+
+## 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 = [
+    ">>fao<< Jeg er bange for kakerlakker.",
+    ">>nob<< Vladivostok är en stad i Ryssland."
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-gmq-gmq"
+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:
+#     Tað eru uml.
+#     Vladivostok er en by i Russland.
+```
+
+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-gmq-gmq")
+print(pipe(">>fao<< Jeg er bange for kakerlakker."))
+
+# expected output: Tað eru uml.
+```
+
+## Training
+
+- **Data**: opusTCv20210807 ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+- **Pre-processing**: SentencePiece (spm32k,spm32k)
+- **Model Type:**  transformer-big
+- **Original MarianNMT Model**: [opusTCv20210807_transformer-big_2022-07-29.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-gmq/opusTCv20210807_transformer-big_2022-07-29.zip)
+- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+
+## Evaluation
+
+* test set translations: [opusTCv20210807_transformer-big_2022-07-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-gmq/opusTCv20210807_transformer-big_2022-07-29.test.txt)
+* test set scores: [opusTCv20210807_transformer-big_2022-07-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-gmq/opusTCv20210807_transformer-big_2022-07-29.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 |
+|----------|---------|-------|-------|-------|--------|
+| dan-nob | tatoeba-test-v2021-08-07 | 0.87556 | 78.2 | 1299 | 9620 |
+| dan-swe | tatoeba-test-v2021-08-07 | 0.83556 | 72.5 | 1549 | 10060 |
+| nno-nob | tatoeba-test-v2021-08-07 | 0.88349 | 78.9 | 467 | 3129 |
+| nob-dan | tatoeba-test-v2021-08-07 | 0.85345 | 73.9 | 1299 | 9794 |
+| nob-nno | tatoeba-test-v2021-08-07 | 0.74571 | 55.2 | 466 | 3141 |
+| nob-swe | tatoeba-test-v2021-08-07 | 0.84747 | 73.9 | 563 | 3698 |
+| swe-dan | tatoeba-test-v2021-08-07 | 0.83392 | 72.6 | 1549 | 10239 |
+| swe-nob | tatoeba-test-v2021-08-07 | 0.85815 | 76.3 | 563 | 3708 |
+| isl-swe | europeana2021 | 0.45562 | 22.2 | 563 | 10293 |
+| nob-isl | europeana2021 | 0.54171 | 29.7 | 538 | 9932 |
+| nob-swe | europeana2021 | 0.73891 | 54.0 | 538 | 9885 |
+| dan-isl | flores101-devtest | 0.50227 | 22.2 | 1012 | 22834 |
+| dan-nob | flores101-devtest | 0.58445 | 28.6 | 1012 | 23873 |
+| dan-swe | flores101-devtest | 0.65000 | 38.5 | 1012 | 23121 |
+| isl-dan | flores101-devtest | 0.53630 | 27.2 | 1012 | 24638 |
+| isl-nob | flores101-devtest | 0.49434 | 20.5 | 1012 | 23873 |
+| isl-swe | flores101-devtest | 0.53373 | 26.0 | 1012 | 23121 |
+| nob-dan | flores101-devtest | 0.59657 | 31.7 | 1012 | 24638 |
+| nob-isl | flores101-devtest | 0.47432 | 18.9 | 1012 | 22834 |
+| nob-swe | flores101-devtest | 0.60030 | 31.3 | 1012 | 23121 |
+| swe-dan | flores101-devtest | 0.64340 | 39.0 | 1012 | 24638 |
+| swe-isl | flores101-devtest | 0.49590 | 21.7 | 1012 | 22834 |
+| swe-nob | flores101-devtest | 0.58336 | 28.9 | 1012 | 23873 |
+
+## Citation Information
+
+* 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",
+}
+```
+
+## 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: 8b9f0b0
+* port time: Fri Aug 12 13:30:22 EEST 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,47 @@
+isl-swe	europeana2021	0.45562	22.2	563	10293
+nob-isl	europeana2021	0.54171	29.7	538	9932
+nob-swe	europeana2021	0.73891	54.0	538	9885
+dan-isl	flores101-dev	0.50526	22.6	997	21857
+dan-nob	flores101-dev	0.58258	29.0	997	23157
+dan-swe	flores101-dev	0.64830	38.5	997	22417
+isl-dan	flores101-dev	0.53960	27.5	997	23685
+isl-nob	flores101-dev	0.49502	20.9	997	23157
+isl-swe	flores101-dev	0.53173	26.1	997	22417
+nob-dan	flores101-dev	0.59954	32.4	997	23685
+nob-isl	flores101-dev	0.48147	19.7	997	21857
+nob-swe	flores101-dev	0.59719	30.6	997	22417
+swe-dan	flores101-dev	0.64216	38.8	997	23685
+swe-isl	flores101-dev	0.49997	22.4	997	21857
+swe-nob	flores101-dev	0.57853	28.7	997	23157
+dan-isl	flores101-devtest	0.50227	22.2	1012	22834
+dan-nob	flores101-devtest	0.58445	28.6	1012	23873
+dan-swe	flores101-devtest	0.65000	38.5	1012	23121
+isl-dan	flores101-devtest	0.53630	27.2	1012	24638
+isl-nob	flores101-devtest	0.49434	20.5	1012	23873
+isl-swe	flores101-devtest	0.53373	26.0	1012	23121
+nob-dan	flores101-devtest	0.59657	31.7	1012	24638
+nob-isl	flores101-devtest	0.47432	18.9	1012	22834
+nob-swe	flores101-devtest	0.60030	31.3	1012	23121
+swe-dan	flores101-devtest	0.64340	39.0	1012	24638
+swe-isl	flores101-devtest	0.49590	21.7	1012	22834
+swe-nob	flores101-devtest	0.58336	28.9	1012	23873
+dan-swe	tatoeba-test-v2020-07-28	0.83565	72.6	1550	10082
+nno-nob	tatoeba-test-v2020-07-28	0.88417	79.1	474	3167
+nob-nno	tatoeba-test-v2020-07-28	0.74642	55.3	474	3184
+nob-swe	tatoeba-test-v2020-07-28	0.85123	74.5	560	3661
+swe-dan	tatoeba-test-v2020-07-28	0.83413	72.7	1550	10261
+swe-nob	tatoeba-test-v2020-07-28	0.86040	76.7	560	3672
+dan-swe	tatoeba-test-v2021-03-30	0.83565	72.6	1550	10082
+nno-nob	tatoeba-test-v2021-03-30	0.88607	79.2	500	3314
+nob-nno	tatoeba-test-v2021-03-30	0.74623	55.3	488	3321
+nob-swe	tatoeba-test-v2021-03-30	0.84518	73.4	570	3756
+swe-dan	tatoeba-test-v2021-03-30	0.83413	72.7	1550	10261
+swe-nob	tatoeba-test-v2021-03-30	0.85670	76.2	570	3765
+dan-nob	tatoeba-test-v2021-08-07	0.87556	78.2	1299	9620
+dan-swe	tatoeba-test-v2021-08-07	0.83556	72.5	1549	10060
+nno-nob	tatoeba-test-v2021-08-07	0.88349	78.9	467	3129
+nob-dan	tatoeba-test-v2021-08-07	0.85345	73.9	1299	9794
+nob-nno	tatoeba-test-v2021-08-07	0.74571	55.2	466	3141
+nob-swe	tatoeba-test-v2021-08-07	0.84747	73.9	563	3698
+swe-dan	tatoeba-test-v2021-08-07	0.83392	72.6	1549	10239
+swe-nob	tatoeba-test-v2021-08-07	0.85815	76.3	563	3708

benchmark_translations.zip

@@ -0,0 +1,3 @@
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