readme: 
  ---
  license: cc-by-4.0
  metrics:
  - bleu4
  - meteor
  - rouge-l
  - bertscore
  - moverscore
  language: fr
  datasets:
  - lmqg/qg_frquad
  pipeline_tag: text2text-generation
  tags:
  - question generation
  widget:
  - text: "Créateur » (Maker), lui aussi au singulier, « <hl> le Suprême Berger <hl> » (The Great Shepherd) ; de l'autre, des réminiscences de la théologie de l'Antiquité : le tonnerre, voix de Jupiter, « Et souvent ta voix gronde en un tonnerre terrifiant », etc."
    example_title: "Question Generation Example 1" 
  - text: "Ce black dog peut être lié à des évènements traumatisants issus du monde extérieur, tels que son renvoi de l'Amirauté après la catastrophe des Dardanelles, lors de la <hl> Grande Guerre <hl> de 14-18, ou son rejet par l'électorat en juillet 1945."
    example_title: "Question Generation Example 2" 
  - text: "contre <hl> Normie Smith <hl> et 15 000 dollars le 28 novembre 1938."
    example_title: "Question Generation Example 3" 
  model-index:
  - name: lmqg/mt5-base-frquad-qg
    results:
    - task:
        name: Text2text Generation
        type: text2text-generation
      dataset:
        name: lmqg/qg_frquad
        type: default
        args: default
      metrics:
      - name: BLEU4 (Question Generation)
        type: bleu4_question_generation
        value: 6.14
      - name: ROUGE-L (Question Generation)
        type: rouge_l_question_generation
        value: 25.88
      - name: METEOR (Question Generation)
        type: meteor_question_generation
        value: 15.55
      - name: BERTScore (Question Generation)
        type: bertscore_question_generation
        value: 77.81
      - name: MoverScore (Question Generation)
        type: moverscore_question_generation
        value: 54.58
      - name: QAAlignedF1Score-BERTScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
        type: qa_aligned_f1_score_bertscore_question_answer_generation_with_gold_answer_gold_answer
        value: 86.41
      - name: QAAlignedRecall-BERTScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
        type: qa_aligned_recall_bertscore_question_answer_generation_with_gold_answer_gold_answer
        value: 86.4
      - name: QAAlignedPrecision-BERTScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
        type: qa_aligned_precision_bertscore_question_answer_generation_with_gold_answer_gold_answer
        value: 86.42
      - name: QAAlignedF1Score-MoverScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
        type: qa_aligned_f1_score_moverscore_question_answer_generation_with_gold_answer_gold_answer
        value: 60.19
      - name: QAAlignedRecall-MoverScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
        type: qa_aligned_recall_moverscore_question_answer_generation_with_gold_answer_gold_answer
        value: 60.18
      - name: QAAlignedPrecision-MoverScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
        type: qa_aligned_precision_moverscore_question_answer_generation_with_gold_answer_gold_answer
        value: 60.19
      - name: QAAlignedF1Score-BERTScore (Question & Answer Generation) [Gold Answer]
        type: qa_aligned_f1_score_bertscore_question_answer_generation_gold_answer
        value: 68.59
      - name: QAAlignedRecall-BERTScore (Question & Answer Generation) [Gold Answer]
        type: qa_aligned_recall_bertscore_question_answer_generation_gold_answer
        value: 69.69
      - name: QAAlignedPrecision-BERTScore (Question & Answer Generation) [Gold Answer]
        type: qa_aligned_precision_bertscore_question_answer_generation_gold_answer
        value: 67.59
      - name: QAAlignedF1Score-MoverScore (Question & Answer Generation) [Gold Answer]
        type: qa_aligned_f1_score_moverscore_question_answer_generation_gold_answer
        value: 47.87
      - name: QAAlignedRecall-MoverScore (Question & Answer Generation) [Gold Answer]
        type: qa_aligned_recall_moverscore_question_answer_generation_gold_answer
        value: 48.36
      - name: QAAlignedPrecision-MoverScore (Question & Answer Generation) [Gold Answer]
        type: qa_aligned_precision_moverscore_question_answer_generation_gold_answer
        value: 47.42
  ---
  
  # Model Card of `lmqg/mt5-base-frquad-qg`
  This model is fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) for question generation task on the [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
  
  
  ### Overview
  - **Language model:** [google/mt5-base](https://huggingface.co/google/mt5-base)   
  - **Language:** fr  
  - **Training data:** [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) (default)
  - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
  - **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
  
  ### Usage
  - With [`lmqg`](https://github.com/asahi417/lm-question-gener