模型:
lmqg/t5-large-squad-qg-ae
该模型是基于 t5-large 在 lmqg/qg_squad (数据集名称:default)上进行的问题生成和答案提取的联合微调版本。该模型使用 lmqg 进行训练。
from lmqg import TransformersQG # initialize model model = TransformersQG(language="en", model="lmqg/t5-large-squad-qg-ae") # 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-large-squad-qg-ae") # answer extraction answer = pipe("generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.") # question generation question = 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.")
Score | Type | Dataset | |
---|---|---|---|
BERTScore | 90.69 | default | 12313321 |
Bleu_1 | 59.93 | default | 12313321 |
Bleu_2 | 43.98 | default | 12313321 |
Bleu_3 | 34.19 | default | 12313321 |
Bleu_4 | 27.2 | default | 12313321 |
METEOR | 27.81 | default | 12313321 |
MoverScore | 65.29 | default | 12313321 |
ROUGE_L | 54.23 | default | 12313321 |
Score | Type | Dataset | |
---|---|---|---|
QAAlignedF1Score (BERTScore) | 92.87 | default | 12313321 |
QAAlignedF1Score (MoverScore) | 64.67 | default | 12313321 |
QAAlignedPrecision (BERTScore) | 92.72 | default | 12313321 |
QAAlignedPrecision (MoverScore) | 64.82 | default | 12313321 |
QAAlignedRecall (BERTScore) | 93.04 | default | 12313321 |
QAAlignedRecall (MoverScore) | 64.63 | default | 12313321 |
Score | Type | Dataset | |
---|---|---|---|
AnswerExactMatch | 59.26 | default | 12313321 |
AnswerF1Score | 70.3 | default | 12313321 |
BERTScore | 91.63 | default | 12313321 |
Bleu_1 | 60.87 | default | 12313321 |
Bleu_2 | 56.96 | default | 12313321 |
Bleu_3 | 53.12 | default | 12313321 |
Bleu_4 | 49.73 | default | 12313321 |
METEOR | 44.46 | default | 12313321 |
MoverScore | 82.48 | default | 12313321 |
ROUGE_L | 69.82 | default | 12313321 |
微调期间使用了以下超参数:
完整的配置可以在 fine-tuning config file 中找到。
@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", }