readme: 
  ---
  license: cc-by-4.0
  metrics:
  - bleu4
  - meteor
  - rouge-l
  - bertscore
  - moverscore
  language: en
  datasets:
  - lmqg/qg_squad
  pipeline_tag: text2text-generation
  tags:
  - answer extraction
  widget:
  - text: "extract answers: <hl> Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress."
    example_title: "Answering Extraction Example 1" 
  - text: "extract answers: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress. <hl>"
    example_title: "Answering Extraction Example 2" 
  model-index:
  - name: lmqg/t5-base-squad-ae
    results:
    - task:
        name: Text2text Generation
        type: text2text-generation
      dataset:
        name: lmqg/qg_squad
        type: default
        args: default
      metrics:
      - name: BLEU4 (Answer Extraction)
        type: bleu4_answer_extraction
        value: 54.28
      - name: ROUGE-L (Answer Extraction)
        type: rouge_l_answer_extraction
        value: 69.72
      - name: METEOR (Answer Extraction)
        type: meteor_answer_extraction
        value: 43.62
      - name: BERTScore (Answer Extraction)
        type: bertscore_answer_extraction
        value: 91.87
      - name: MoverScore (Answer Extraction)
        type: moverscore_answer_extraction
        value: 82.69
      - name: AnswerF1Score (Answer Extraction)
        type: answer_f1_score__answer_extraction
        value: 70.32
      - name: AnswerExactMatch (Answer Extraction)
        type: answer_exact_match_answer_extraction
        value: 59.48
  ---
  
  # Model Card of `lmqg/t5-base-squad-ae`
  This model is fine-tuned version of [t5-base](https://huggingface.co/t5-base) for answer extraction on the [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
  
  
  ### Overview
  - **Language model:** [t5-base](https://huggingface.co/t5-base)   
  - **Language:** en  
  - **Training data:** [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (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-generation#lmqg-language-model-for-question-generation-)
  ```python
  from lmqg import TransformersQG
  
  # initialize model
  model = TransformersQG(language="en", model="lmqg/t5-base-squad-ae")
  
  # model prediction
  answers = model.generate_a("William Turner was an English painter who specialised in watercolour landscapes")
  
  ```
  
  - With `transformers`
  ```python
  from transformers import pipeline
  
  pipe = pipeline("text2text-generation", "lmqg/t5-base-squad-ae")
  output = pipe("extract answers: <hl> Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress.")
  
  ```
  
  ## Evaluation
  
  
  - ***Metric (Answer Extraction)***: [raw metric file](https://huggingface.co/lmqg/t5-base-squad-ae/raw/main/eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_squad.default.json) 
  
  |                  |   Score | Type    | Dataset                                                        |
  |:-----------------|--------:|:--------|:---------------------------------------------------------------|
  | AnswerExactMatch |   59.48 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | AnswerF1Score    |   70.32 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | BERTScore        |   91.87 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | Bleu_1           |   64.27 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | Bleu_2           |   60.78 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | Bleu_3           |   57.35 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | Bleu_4           |   54.28 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
  | METEOR           |   43.