--- 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: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. 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. 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 2" model-index: - name: lmqg/t5-small-squad-answer-extraction results: - task: name: Text2text Generation type: text2text-generation dataset: name: lmqg/qg_squad type: default args: default metrics: - name: BLEU4 type: bleu4 value: 39.23 - name: ROUGE-L type: rouge-l value: 67.58 - name: METEOR type: meteor value: 42.5 - name: BERTScore type: bertscore value: 91.2 - name: MoverScore type: moverscore value: 80.92 - name: AnswerF1Score (Answer Extraction) type: answer_f1_score_answer_extraction value: 68.06 - name: AnswerExactMatch (Answer Extraction) type: answer_exact_match_answer_extraction value: 56.15 --- # Model Card of `lmqg/t5-small-squad-answer-extraction` This model is fine-tuned version of [t5-small](https://huggingface.co/t5-small) 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-small](https://huggingface.co/t5-small) - **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-small-squad-answer-extraction") # 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-small-squad-answer-extraction") output = pipe("extract answers: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. 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-small-squad-answer-extraction/raw/main/eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_squad.default.json) | | Score | Type | Dataset | |:-----------------|--------:|:--------|:---------------------------------------------------------------| | AnswerExactMatch | 56.15 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | AnswerF1Score | 68.06 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | BERTScore | 91.2 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | Bleu_1 | 52.42 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | Bleu_2 | 47.81 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | Bleu_3 | 43.22 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | Bleu_4 | 39.23 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | METEOR | 42.5 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | MoverScore | 80.92 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | | ROUGE_L | 67.58 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | ## Training hyperparameters The following hyperparameters were used during fine-tuning: - dataset_path: lmqg/qg_squad - dataset_name: default - input_types: ['paragraph_sentence'] - output_types: ['answer'] - prefix_types: ['ae'] - model: t5-small - max_length: 512 - max_length_output: 32 - epoch: 7 - batch: 64 - lr: 0.0001 - fp16: False - random_seed: 1 - gradient_accumulation_steps: 1 - label_smoothing: 0.15 The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/t5-small-squad-answer-extraction/raw/main/trainer_config.json). ## 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", } ```