readme: ---
  language:
  - cs
  - da
  - nb
  - pl
  - sv
  
  tags:
  - translation
  - opus-mt-tc
  
  license: cc-by-4.0
  model-index:
  - name: opus-mt-tc-big-gmq-zlw
    results:
    - task:
        name: Translation dan-ces
        type: translation
        args: dan-ces
      dataset:
        name: flores101-devtest
        type: flores_101
        args: dan ces devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 26.7
         - name: chr-F
           type: chrf
           value: 0.54065
    - task:
        name: Translation dan-pol
        type: translation
        args: dan-pol
      dataset:
        name: flores101-devtest
        type: flores_101
        args: dan pol devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 18.8
         - name: chr-F
           type: chrf
           value: 0.48389
    - task:
        name: Translation isl-ces
        type: translation
        args: isl-ces
      dataset:
        name: flores101-devtest
        type: flores_101
        args: isl ces devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 17.7
         - name: chr-F
           type: chrf
           value: 0.43582
    - task:
        name: Translation isl-pol
        type: translation
        args: isl-pol
      dataset:
        name: flores101-devtest
        type: flores_101
        args: isl pol devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 13.9
         - name: chr-F
           type: chrf
           value: 0.41929
    - task:
        name: Translation nob-ces
        type: translation
        args: nob-ces
      dataset:
        name: flores101-devtest
        type: flores_101
        args: nob ces devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 22.3
         - name: chr-F
           type: chrf
           value: 0.50336
    - task:
        name: Translation nob-pol
        type: translation
        args: nob-pol
      dataset:
        name: flores101-devtest
        type: flores_101
        args: nob pol devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 16.3
         - name: chr-F
           type: chrf
           value: 0.46130
    - task:
        name: Translation swe-ces
        type: translation
        args: swe-ces
      dataset:
        name: flores101-devtest
        type: flores_101
        args: swe ces devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 25.7
         - name: chr-F
           type: chrf
           value: 0.53188
    - task:
        name: Translation swe-pol
        type: translation
        args: swe-pol
      dataset:
        name: flores101-devtest
        type: flores_101
        args: swe pol devtest
      metrics:
         - name: BLEU
           type: bleu
           value: 18.6
         - name: chr-F
           type: chrf
           value: 0.48163
    - task:
        name: Translation swe-pol
        type: translation
        args: swe-pol
      dataset:
        name: tatoeba-test-v2021-08-07
        type: tatoeba_mt
        args: swe-pol
      metrics:
         - name: BLEU
           type: bleu
           value: 46.2
         - name: chr-F
           type: chrf
           value: 0.66326
  ---
  # opus-mt-tc-big-gmq-zlw
  
  ## 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 West Slavic languages (zlw).
  
  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**: 2022-08-03
  - **License:** CC-BY-4.0
  - **Language(s):**  
    - Source Language(s): dan nob nor swe
    - Target Language(s): ces pol
    - Language Pair(s): dan-ces nob-ces swe-ces swe-pol
    - Valid Target Language Labels: >>ces<< >>csb<< >>czk<< >>dsb<< >>hsb<< >>pol<< >>pox<< >>slk<< >>szl<<
  - **Original Model**: [opusTCv20210807_transformer-big_2022-08-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmq-zlw/opusTCv20210807_transformer-big_2022-08-03.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-zlw README](h