questions and answers generation

Model Card of lmqg/t5-small-tweetqa-qag

This model is fine-tuned version of t5-small for question & answer pair generation task on the lmqg/qag_tweetqa (dataset_name: default) via lmqg.

Overview

Usage

from lmqg import TransformersQG

# initialize model
model = TransformersQG(language="en", model="lmqg/t5-small-tweetqa-qag")

# model prediction
question_answer_pairs = model.generate_qa("William Turner was an English painter who specialised in watercolour landscapes")

from transformers import pipeline

pipe = pipeline("text2text-generation", "lmqg/t5-small-tweetqa-qag")
output = pipe("generate question and answer: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")

Evaluation

Score Type Dataset
BERTScore 89.64 default lmqg/qag_tweetqa
Bleu_1 35.53 default lmqg/qag_tweetqa
Bleu_2 22.94 default lmqg/qag_tweetqa
Bleu_3 15.11 default lmqg/qag_tweetqa
Bleu_4 10.08 default lmqg/qag_tweetqa
METEOR 28.02 default lmqg/qag_tweetqa
MoverScore 60.47 default lmqg/qag_tweetqa
QAAlignedF1Score (BERTScore) 91.42 default lmqg/qag_tweetqa
QAAlignedF1Score (MoverScore) 63.08 default lmqg/qag_tweetqa
QAAlignedPrecision (BERTScore) 91.89 default lmqg/qag_tweetqa
QAAlignedPrecision (MoverScore) 64.08 default lmqg/qag_tweetqa
QAAlignedRecall (BERTScore) 90.98 default lmqg/qag_tweetqa
QAAlignedRecall (MoverScore) 62.16 default lmqg/qag_tweetqa
ROUGE_L 34.19 default lmqg/qag_tweetqa

Training hyperparameters

The following hyperparameters were used during fine-tuning:

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",
}