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lmqg/bart-base-squad-ae
bart-base-squad-ae is a text generation model from lmqg. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as cc-by-4.0.
This model is fine-tuned version of facebook/bart-base for answer extraction on the lmqg/qgsquad (datasetname: default) via lmqg.
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From the Hugging Face model README
lmqg/bart-base-squad-aeThis model is fine-tuned version of facebook/bart-base for answer extraction on the lmqg/qg_squad (dataset_name: default) via lmqg.
lmqgfrom lmqg import TransformersQG
# initialize model
model = TransformersQG(language="en", model="lmqg/bart-base-squad-ae")
# model prediction
answers = model.generate_a("William Turner was an English painter who specialised in watercolour landscapes")
transformersfrom transformers import pipeline
pipe = pipeline("text2text-generation", "lmqg/bart-base-squad-ae")
output = pipe("<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 | |
|---|---|---|---|
| AnswerExactMatch | 58.17 | default | lmqg/qg_squad |
| AnswerF1Score | 69.47 | default | lmqg/qg_squad |
| BERTScore | 91.96 | default | lmqg/qg_squad |
| Bleu_1 | 65.92 | default | lmqg/qg_squad |
| Bleu_2 | 63.24 | default | lmqg/qg_squad |
| Bleu_3 | 60.8 | default | lmqg/qg_squad |
| Bleu_4 | 58.72 | default | lmqg/qg_squad |
| METEOR | 41.71 | default | lmqg/qg_squad |
| MoverScore | 82.2 | default | lmqg/qg_squad |
| ROUGE_L | 68.7 | default | lmqg/qg_squad |
The following hyperparameters were used during fine-tuning:
The full configuration can be found at fine-tuning config file.
@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",
}