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README.md

@@ -0,0 +1,803 @@
+---
+language:
+- da
+- es
+- fr
+- gmq
+- is
+- it
+- itc
+- la
+- nb
+- nn
+- no
+- pt
+- sv
+
+tags:
+- translation
+- opus-mt-tc
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-gmq-itc
+  results:
+  - task:
+      name: Translation dan-cat
+      type: translation
+      args: dan-cat
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan cat devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 33.4
+       - name: chr-F
+         type: chrf
+         value: 0.59224
+  - task:
+      name: Translation dan-fra
+      type: translation
+      args: dan-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 38.3
+       - name: chr-F
+         type: chrf
+         value: 0.63387
+  - task:
+      name: Translation dan-glg
+      type: translation
+      args: dan-glg
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan glg devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 26.4
+       - name: chr-F
+         type: chrf
+         value: 0.54446
+  - task:
+      name: Translation dan-ita
+      type: translation
+      args: dan-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.7
+       - name: chr-F
+         type: chrf
+         value: 0.55237
+  - task:
+      name: Translation dan-por
+      type: translation
+      args: dan-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 36.9
+       - name: chr-F
+         type: chrf
+         value: 0.62233
+  - task:
+      name: Translation dan-ron
+      type: translation
+      args: dan-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.8
+       - name: chr-F
+         type: chrf
+         value: 0.58235
+  - task:
+      name: Translation dan-spa
+      type: translation
+      args: dan-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: dan spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 24.3
+       - name: chr-F
+         type: chrf
+         value: 0.52453
+  - task:
+      name: Translation isl-cat
+      type: translation
+      args: isl-cat
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl cat devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.7
+       - name: chr-F
+         type: chrf
+         value: 0.48930
+  - task:
+      name: Translation isl-fra
+      type: translation
+      args: isl-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 26.2
+       - name: chr-F
+         type: chrf
+         value: 0.52704
+  - task:
+      name: Translation isl-glg
+      type: translation
+      args: isl-glg
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl glg devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 18.0
+       - name: chr-F
+         type: chrf
+         value: 0.45387
+  - task:
+      name: Translation isl-ita
+      type: translation
+      args: isl-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 18.6
+       - name: chr-F
+         type: chrf
+         value: 0.47303
+  - task:
+      name: Translation isl-por
+      type: translation
+      args: isl-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 24.9
+       - name: chr-F
+         type: chrf
+         value: 0.51381
+  - task:
+      name: Translation isl-ron
+      type: translation
+      args: isl-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.6
+       - name: chr-F
+         type: chrf
+         value: 0.48224
+  - task:
+      name: Translation isl-spa
+      type: translation
+      args: isl-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: isl spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 18.1
+       - name: chr-F
+         type: chrf
+         value: 0.45786
+  - task:
+      name: Translation nob-cat
+      type: translation
+      args: nob-cat
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob cat devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.9
+       - name: chr-F
+         type: chrf
+         value: 0.55984
+  - task:
+      name: Translation nob-fra
+      type: translation
+      args: nob-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 33.8
+       - name: chr-F
+         type: chrf
+         value: 0.60102
+  - task:
+      name: Translation nob-glg
+      type: translation
+      args: nob-glg
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob glg devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.4
+       - name: chr-F
+         type: chrf
+         value: 0.52145
+  - task:
+      name: Translation nob-ita
+      type: translation
+      args: nob-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.2
+       - name: chr-F
+         type: chrf
+         value: 0.52619
+  - task:
+      name: Translation nob-por
+      type: translation
+      args: nob-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.2
+       - name: chr-F
+         type: chrf
+         value: 0.58836
+  - task:
+      name: Translation nob-ron
+      type: translation
+      args: nob-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 27.6
+       - name: chr-F
+         type: chrf
+         value: 0.54845
+  - task:
+      name: Translation nob-spa
+      type: translation
+      args: nob-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: nob spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.8
+       - name: chr-F
+         type: chrf
+         value: 0.50661
+  - task:
+      name: Translation swe-cat
+      type: translation
+      args: swe-cat
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe cat devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.4
+       - name: chr-F
+         type: chrf
+         value: 0.58542
+  - task:
+      name: Translation swe-fra
+      type: translation
+      args: swe-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 39.3
+       - name: chr-F
+         type: chrf
+         value: 0.63688
+  - task:
+      name: Translation swe-glg
+      type: translation
+      args: swe-glg
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe glg devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 26.0
+       - name: chr-F
+         type: chrf
+         value: 0.53989
+  - task:
+      name: Translation swe-ita
+      type: translation
+      args: swe-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.9
+       - name: chr-F
+         type: chrf
+         value: 0.55232
+  - task:
+      name: Translation swe-por
+      type: translation
+      args: swe-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 36.5
+       - name: chr-F
+         type: chrf
+         value: 0.61882
+  - task:
+      name: Translation swe-ron
+      type: translation
+      args: swe-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.0
+       - name: chr-F
+         type: chrf
+         value: 0.57419
+  - task:
+      name: Translation swe-spa
+      type: translation
+      args: swe-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: swe spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.8
+       - name: chr-F
+         type: chrf
+         value: 0.52175
+  - task:
+      name: Translation dan-fra
+      type: translation
+      args: dan-fra
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-fra
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 63.8
+       - name: chr-F
+         type: chrf
+         value: 0.76671
+  - task:
+      name: Translation dan-ita
+      type: translation
+      args: dan-ita
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-ita
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 56.2
+       - name: chr-F
+         type: chrf
+         value: 0.74658
+  - task:
+      name: Translation dan-por
+      type: translation
+      args: dan-por
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-por
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 57.8
+       - name: chr-F
+         type: chrf
+         value: 0.74944
+  - task:
+      name: Translation dan-spa
+      type: translation
+      args: dan-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: dan-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 54.8
+       - name: chr-F
+         type: chrf
+         value: 0.72328
+  - task:
+      name: Translation isl-ita
+      type: translation
+      args: isl-ita
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: isl-ita
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 51.0
+       - name: chr-F
+         type: chrf
+         value: 0.69354
+  - task:
+      name: Translation isl-spa
+      type: translation
+      args: isl-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: isl-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 49.2
+       - name: chr-F
+         type: chrf
+         value: 0.66008
+  - task:
+      name: Translation nob-fra
+      type: translation
+      args: nob-fra
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nob-fra
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 54.4
+       - name: chr-F
+         type: chrf
+         value: 0.70854
+  - task:
+      name: Translation nob-spa
+      type: translation
+      args: nob-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: nob-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 55.9
+       - name: chr-F
+         type: chrf
+         value: 0.73672
+  - task:
+      name: Translation swe-fra
+      type: translation
+      args: swe-fra
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-fra
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 59.2
+       - name: chr-F
+         type: chrf
+         value: 0.73014
+  - task:
+      name: Translation swe-ita
+      type: translation
+      args: swe-ita
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-ita
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 56.6
+       - name: chr-F
+         type: chrf
+         value: 0.73211
+  - task:
+      name: Translation swe-por
+      type: translation
+      args: swe-por
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-por
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 48.7
+       - name: chr-F
+         type: chrf
+         value: 0.68146
+  - task:
+      name: Translation swe-spa
+      type: translation
+      args: swe-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: swe-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 55.3
+       - name: chr-F
+         type: chrf
+         value: 0.71373
+---
+# opus-mt-tc-big-gmq-itc
+
+## 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 Italic languages (itc).
+
+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**: 2022-08-09
+- **License:** CC-BY-4.0
+- **Language(s):**  
+  - Source Language(s): dan isl nno nob nor swe
+  - Target Language(s): fra ita lat por spa
+  - Valid Target Language Labels: >>fra<< >>ita<< >>lat<< >>por<< >>spa<<
+- **Original Model**: [opusTCv20210807_transformer-big_2022-08-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-itc/opusTCv20210807_transformer-big_2022-08-09.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-itc README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmq-itc/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. `>>fra<<`
+
+## 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 = [
+    ">>spa<< Jag är inte religiös.",
+    ">>por<< Livet er for kort til å lære seg tysk."
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-gmq-itc"
+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:
+#     No soy religioso.
+#     A vida é muito curta para aprender alemão.
+```
+
+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-itc")
+print(pipe(">>spa<< Jag är inte religiös."))
+
+# expected output: No soy religioso.
+```
+
+## 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_2022-08-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-itc/opusTCv20210807_transformer-big_2022-08-09.zip)
+- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+
+## Evaluation
+
+* test set translations: [opusTCv20210807_transformer-big_2022-08-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-itc/opusTCv20210807_transformer-big_2022-08-09.test.txt)
+* test set scores: [opusTCv20210807_transformer-big_2022-08-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-itc/opusTCv20210807_transformer-big_2022-08-09.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-fra | tatoeba-test-v2021-08-07 | 0.76671 | 63.8 | 1731 | 11882 |
+| dan-ita | tatoeba-test-v2021-08-07 | 0.74658 | 56.2 | 284 | 2226 |
+| dan-por | tatoeba-test-v2021-08-07 | 0.74944 | 57.8 | 873 | 5360 |
+| dan-spa | tatoeba-test-v2021-08-07 | 0.72328 | 54.8 | 5000 | 35528 |
+| isl-ita | tatoeba-test-v2021-08-07 | 0.69354 | 51.0 | 236 | 1450 |
+| isl-spa | tatoeba-test-v2021-08-07 | 0.66008 | 49.2 | 238 | 1229 |
+| nob-fra | tatoeba-test-v2021-08-07 | 0.70854 | 54.4 | 323 | 2269 |
+| nob-spa | tatoeba-test-v2021-08-07 | 0.73672 | 55.9 | 885 | 6866 |
+| swe-fra | tatoeba-test-v2021-08-07 | 0.73014 | 59.2 | 1407 | 9580 |
+| swe-ita | tatoeba-test-v2021-08-07 | 0.73211 | 56.6 | 715 | 4711 |
+| swe-por | tatoeba-test-v2021-08-07 | 0.68146 | 48.7 | 320 | 2032 |
+| swe-spa | tatoeba-test-v2021-08-07 | 0.71373 | 55.3 | 1351 | 8235 |
+| dan-cat | flores101-devtest | 0.59224 | 33.4 | 1012 | 27304 |
+| dan-fra | flores101-devtest | 0.63387 | 38.3 | 1012 | 28343 |
+| dan-glg | flores101-devtest | 0.54446 | 26.4 | 1012 | 26582 |
+| dan-ita | flores101-devtest | 0.55237 | 25.7 | 1012 | 27306 |
+| dan-por | flores101-devtest | 0.62233 | 36.9 | 1012 | 26519 |
+| dan-ron | flores101-devtest | 0.58235 | 31.8 | 1012 | 26799 |
+| dan-spa | flores101-devtest | 0.52453 | 24.3 | 1012 | 29199 |
+| isl-cat | flores101-devtest | 0.48930 | 22.7 | 1012 | 27304 |
+| isl-fra | flores101-devtest | 0.52704 | 26.2 | 1012 | 28343 |
+| isl-glg | flores101-devtest | 0.45387 | 18.0 | 1012 | 26582 |
+| isl-ita | flores101-devtest | 0.47303 | 18.6 | 1012 | 27306 |
+| isl-por | flores101-devtest | 0.51381 | 24.9 | 1012 | 26519 |
+| isl-ron | flores101-devtest | 0.48224 | 21.6 | 1012 | 26799 |
+| isl-spa | flores101-devtest | 0.45786 | 18.1 | 1012 | 29199 |
+| nob-cat | flores101-devtest | 0.55984 | 28.9 | 1012 | 27304 |
+| nob-fra | flores101-devtest | 0.60102 | 33.8 | 1012 | 28343 |
+| nob-glg | flores101-devtest | 0.52145 | 23.4 | 1012 | 26582 |
+| nob-ita | flores101-devtest | 0.52619 | 22.2 | 1012 | 27306 |
+| nob-por | flores101-devtest | 0.58836 | 32.2 | 1012 | 26519 |
+| nob-ron | flores101-devtest | 0.54845 | 27.6 | 1012 | 26799 |
+| nob-spa | flores101-devtest | 0.50661 | 21.8 | 1012 | 29199 |
+| swe-cat | flores101-devtest | 0.58542 | 32.4 | 1012 | 27304 |
+| swe-fra | flores101-devtest | 0.63688 | 39.3 | 1012 | 28343 |
+| swe-glg | flores101-devtest | 0.53989 | 26.0 | 1012 | 26582 |
+| swe-ita | flores101-devtest | 0.55232 | 25.9 | 1012 | 27306 |
+| swe-por | flores101-devtest | 0.61882 | 36.5 | 1012 | 26519 |
+| swe-ron | flores101-devtest | 0.57419 | 31.0 | 1012 | 26799 |
+| swe-spa | flores101-devtest | 0.52175 | 23.8 | 1012 | 29199 |
+
+## 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 14:15:19 EEST 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,85 @@
+dan-cat	flores101-dev	0.58904	32.3	997	25962
+dan-fra	flores101-dev	0.63627	38.7	997	26706
+dan-glg	flores101-dev	0.53965	26.5	997	25265
+dan-ita	flores101-dev	0.54662	25.0	997	25840
+dan-por	flores101-dev	0.61581	36.3	997	25287
+dan-ron	flores101-dev	0.57907	31.9	997	25616
+dan-spa	flores101-dev	0.51873	24.1	997	27793
+isl-cat	flores101-dev	0.48721	22.7	997	25962
+isl-fra	flores101-dev	0.52986	26.4	997	26706
+isl-glg	flores101-dev	0.45577	18.5	997	25265
+isl-ita	flores101-dev	0.47766	18.7	997	25840
+isl-por	flores101-dev	0.51411	25.2	997	25287
+isl-ron	flores101-dev	0.48374	22.1	997	25616
+isl-spa	flores101-dev	0.45296	18.5	997	27793
+nob-cat	flores101-dev	0.55963	28.5	997	25962
+nob-fra	flores101-dev	0.59978	34.3	997	26706
+nob-glg	flores101-dev	0.51661	23.7	997	25265
+nob-ita	flores101-dev	0.52610	22.5	997	25840
+nob-por	flores101-dev	0.58589	31.8	997	25287
+nob-ron	flores101-dev	0.54908	27.6	997	25616
+nob-spa	flores101-dev	0.49895	21.4	997	27793
+swe-cat	flores101-dev	0.58623	32.4	997	25962
+swe-fra	flores101-dev	0.63855	39.4	997	26706
+swe-glg	flores101-dev	0.53654	26.2	997	25265
+swe-ita	flores101-dev	0.54976	25.3	997	25840
+swe-por	flores101-dev	0.61208	36.2	997	25287
+swe-ron	flores101-dev	0.58319	32.6	997	25616
+swe-spa	flores101-dev	0.51446	23.7	997	27793
+dan-cat	flores101-devtest	0.59224	33.4	1012	27304
+dan-fra	flores101-devtest	0.63387	38.3	1012	28343
+dan-glg	flores101-devtest	0.54446	26.4	1012	26582
+dan-ita	flores101-devtest	0.55237	25.7	1012	27306
+dan-por	flores101-devtest	0.62233	36.9	1012	26519
+dan-ron	flores101-devtest	0.58235	31.8	1012	26799
+dan-spa	flores101-devtest	0.52453	24.3	1012	29199
+isl-cat	flores101-devtest	0.48930	22.7	1012	27304
+isl-fra	flores101-devtest	0.52704	26.2	1012	28343
+isl-glg	flores101-devtest	0.45387	18.0	1012	26582
+isl-ita	flores101-devtest	0.47303	18.6	1012	27306
+isl-por	flores101-devtest	0.51381	24.9	1012	26519
+isl-ron	flores101-devtest	0.48224	21.6	1012	26799
+isl-spa	flores101-devtest	0.45786	18.1	1012	29199
+nob-cat	flores101-devtest	0.55984	28.9	1012	27304
+nob-fra	flores101-devtest	0.60102	33.8	1012	28343
+nob-glg	flores101-devtest	0.52145	23.4	1012	26582
+nob-ita	flores101-devtest	0.52619	22.2	1012	27306
+nob-por	flores101-devtest	0.58836	32.2	1012	26519
+nob-ron	flores101-devtest	0.54845	27.6	1012	26799
+nob-spa	flores101-devtest	0.50661	21.8	1012	29199
+swe-cat	flores101-devtest	0.58542	32.4	1012	27304
+swe-fra	flores101-devtest	0.63688	39.3	1012	28343
+swe-glg	flores101-devtest	0.53989	26.0	1012	26582
+swe-ita	flores101-devtest	0.55232	25.9	1012	27306
+swe-por	flores101-devtest	0.61882	36.5	1012	26519
+swe-ron	flores101-devtest	0.57419	31.0	1012	26799
+swe-spa	flores101-devtest	0.52175	23.8	1012	29199
+dan-fra	tatoeba-test-v2020-07-28	0.76678	63.8	1742	11929
+dan-ita	tatoeba-test-v2020-07-28	0.74650	56.2	280	2202
+dan-por	tatoeba-test-v2020-07-28	0.74906	57.8	871	5351
+nob-fra	tatoeba-test-v2020-07-28	0.70768	54.2	322	2261
+swe-fra	tatoeba-test-v2020-07-28	0.73024	59.2	1409	9585
+swe-ita	tatoeba-test-v2020-07-28	0.72267	55.2	673	4420
+swe-por	tatoeba-test-v2020-07-28	0.67926	48.2	299	1878
+dan-fra	tatoeba-test-v2021-03-30	0.76678	63.8	1742	11929
+dan-ita	tatoeba-test-v2021-03-30	0.74688	56.1	291	2289
+dan-por	tatoeba-test-v2021-03-30	0.75007	57.9	880	5406
+isl-ita	tatoeba-test-v2021-03-30	0.69485	51.2	237	1455
+isl-spa	tatoeba-test-v2021-03-30	0.66114	49.4	239	1233
+nob-fra	tatoeba-test-v2021-03-30	0.70983	54.6	326	2286
+nob-spa	tatoeba-test-v2021-03-30	0.73669	55.9	894	6934
+swe-fra	tatoeba-test-v2021-03-30	0.73024	59.2	1409	9585
+swe-ita	tatoeba-test-v2021-03-30	0.72795	55.8	723	4741
+swe-por	tatoeba-test-v2021-03-30	0.68052	48.2	319	1996
+dan-fra	tatoeba-test-v2021-08-07	0.76671	63.8	1731	11882
+dan-ita	tatoeba-test-v2021-08-07	0.74658	56.2	284	2226
+dan-por	tatoeba-test-v2021-08-07	0.74944	57.8	873	5360
+dan-spa	tatoeba-test-v2021-08-07	0.72328	54.8	5000	35528
+isl-ita	tatoeba-test-v2021-08-07	0.69354	51.0	236	1450
+isl-spa	tatoeba-test-v2021-08-07	0.66008	49.2	238	1229
+nob-fra	tatoeba-test-v2021-08-07	0.70854	54.4	323	2269
+nob-spa	tatoeba-test-v2021-08-07	0.73672	55.9	885	6866
+swe-fra	tatoeba-test-v2021-08-07	0.73014	59.2	1407	9580
+swe-ita	tatoeba-test-v2021-08-07	0.73211	56.6	715	4711
+swe-por	tatoeba-test-v2021-08-07	0.68146	48.7	320	2032
+swe-spa	tatoeba-test-v2021-08-07	0.71373	55.3	1351	8235

benchmark_translations.zip

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config.json

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+  "activation_dropout": 0.0,
+  "activation_function": "relu",
+  "architectures": [
+    "MarianMTModel"
+  ],
+  "attention_dropout": 0.0,
+  "bad_words_ids": [
+    [
+      57968
+    ]
+  ],
+  "bos_token_id": 0,
+  "classifier_dropout": 0.0,
+  "d_model": 1024,
+  "decoder_attention_heads": 16,
+  "decoder_ffn_dim": 4096,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 6,
+  "decoder_start_token_id": 57968,
+  "decoder_vocab_size": 57969,
+  "dropout": 0.1,
+  "encoder_attention_heads": 16,
+  "encoder_ffn_dim": 4096,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 6,
+  "eos_token_id": 45463,
+  "forced_eos_token_id": 45463,
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "max_length": 512,
+  "max_position_embeddings": 1024,
+  "model_type": "marian",
+  "normalize_embedding": false,
+  "num_beams": 4,
+  "num_hidden_layers": 6,
+  "pad_token_id": 57968,
+  "scale_embedding": true,
+  "share_encoder_decoder_embeddings": true,
+  "static_position_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.18.0.dev0",
+  "use_cache": true,
+  "vocab_size": 57969
+}

pytorch_model.bin

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source.spm

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special_tokens_map.json

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target.spm

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tokenizer_config.json

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