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metadata
license: cc-by-4.0
metrics:
  - bleu4
  - meteor
  - rouge-l
  - bertscore
  - moverscore
language: en
datasets:
  - lmqg/qg_subjqa
pipeline_tag: text2text-generation
tags:
  - question generation
widget:
  - text: >-
      generate question: <hl> Beyonce <hl> further expanded her acting career,
      starring as blues singer Etta James in the 2008 musical biopic, Cadillac
      Records.
    example_title: Question Generation Example 1
  - text: >-
      generate question: Beyonce further expanded her acting career, starring as
      blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac
      Records.
    example_title: Question Generation Example 2
  - text: >-
      generate question: Beyonce further expanded her acting career, starring as
      blues singer Etta James in the 2008 musical biopic,  <hl> Cadillac Records
      <hl> .
    example_title: Question Generation Example 3
model-index:
  - name: lmqg/t5-base-subjqa-vanilla-tripadvisor
    results:
      - task:
          name: Text2text Generation
          type: text2text-generation
        dataset:
          name: lmqg/qg_subjqa
          type: tripadvisor
          args: tripadvisor
        metrics:
          - name: BLEU4
            type: bleu4
            value: 3.780489342226055e-7
          - name: ROUGE-L
            type: rouge-l
            value: 0.02285469638718953
          - name: METEOR
            type: meteor
            value: 0.03164426479158904
          - name: BERTScore
            type: bertscore
            value: 0.7947235033105651
          - name: MoverScore
            type: moverscore
            value: 0.5109369869246486

Model Card of lmqg/t5-base-subjqa-vanilla-tripadvisor

This model is fine-tuned version of t5-base for question generation task on the lmqg/qg_subjqa (dataset_name: tripadvisor) via lmqg.

Please cite our paper if you use the model (https://arxiv.org/abs/2210.03992).


@inproceedings{ushio-etal-2022-generative,
    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
    author = "Ushio, Asahi  and
        Alva-Manchego, Fernando  and
        Camacho-Collados, Jose",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, U.A.E.",
    publisher = "Association for Computational Linguistics",
}

Overview

Usage


from lmqg import TransformersQG
# initialize model
model = TransformersQG(language='en', model='lmqg/t5-base-subjqa-vanilla-tripadvisor')
# model prediction
question = model.generate_q(list_context=["William Turner was an English painter who specialised in watercolour landscapes"], list_answer=["William Turner"])
  • With transformers

from transformers import pipeline
# initialize model
pipe = pipeline("text2text-generation", 'lmqg/t5-base-subjqa-vanilla-tripadvisor')
# question generation
question = pipe('generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')

Evaluation Metrics

Metrics

Dataset Type BLEU4 ROUGE-L METEOR BERTScore MoverScore Link
lmqg/qg_subjqa tripadvisor 0.0 0.023 0.032 0.795 0.511 link

Training hyperparameters

The following hyperparameters were used during fine-tuning:

  • dataset_path: lmqg/qg_subjqa
  • dataset_name: tripadvisor
  • input_types: ['paragraph_answer']
  • output_types: ['question']
  • prefix_types: ['qg']
  • model: t5-base
  • max_length: 512
  • max_length_output: 32
  • epoch: 1
  • batch: 16
  • lr: 1e-05
  • fp16: False
  • random_seed: 1
  • gradient_accumulation_steps: 4
  • label_smoothing: 0.15

The full configuration can be found at fine-tuning config file.

Citation


@inproceedings{ushio-etal-2022-generative,
    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
    author = "Ushio, Asahi  and
        Alva-Manchego, Fernando  and
        Camacho-Collados, Jose",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, U.A.E.",
    publisher = "Association for Computational Linguistics",
}