model update
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README.md
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metrics:
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- name: BLEU4
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type: bleu4
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value:
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- name: ROUGE-L
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type: rouge-l
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value:
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- name: METEOR
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type: meteor
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value:
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- name: BERTScore
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type: bertscore
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value:
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- name: MoverScore
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type: moverscore
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value:
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---
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# Model Card of `lmqg/t5-large-subjqa-vanilla-tripadvisor`
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This model is fine-tuned version of [t5-large](https://huggingface.co/t5-large) for question generation task on the
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[lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) (dataset_name: tripadvisor) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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Please cite our paper if you use the model ([https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)).
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```
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
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author = "Ushio, Asahi and
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Alva-Manchego, Fernando and
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Camacho-Collados, Jose",
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booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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year = "2022",
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address = "Abu Dhabi, U.A.E.",
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publisher = "Association for Computational Linguistics",
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}
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```
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### Overview
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- **Language model:** [t5-large](https://huggingface.co/t5-large)
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- **Language:** en
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### Usage
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- With [`lmqg`](https://github.com/asahi417/lm-question-generation#lmqg-language-model-for-question-generation-)
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```python
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from lmqg import TransformersQG
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# initialize model
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model = TransformersQG(language=
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# model prediction
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```
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- With `transformers`
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```python
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from transformers import pipeline
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# initialize model
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pipe = pipeline("text2text-generation", 'lmqg/t5-large-subjqa-vanilla-tripadvisor')
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# question generation
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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.')
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### Metrics
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|:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
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| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | tripadvisor | 0.0 | 0.038 | 0.039 | 0.784 | 0.49 | [link](https://huggingface.co/lmqg/t5-large-subjqa-vanilla-tripadvisor/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.tripadvisor.json) |
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## Citation
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```
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
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author = "Ushio, Asahi and
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metrics:
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- name: BLEU4
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type: bleu4
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value: 0.0
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- name: ROUGE-L
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type: rouge-l
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value: 3.81
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- name: METEOR
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type: meteor
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value: 3.86
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- name: BERTScore
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type: bertscore
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value: 78.39
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- name: MoverScore
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type: moverscore
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value: 49.03
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---
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# Model Card of `lmqg/t5-large-subjqa-vanilla-tripadvisor`
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This model is fine-tuned version of [t5-large](https://huggingface.co/t5-large) for question generation task on the [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) (dataset_name: tripadvisor) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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### Overview
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- **Language model:** [t5-large](https://huggingface.co/t5-large)
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- **Language:** en
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### Usage
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- With [`lmqg`](https://github.com/asahi417/lm-question-generation#lmqg-language-model-for-question-generation-)
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```python
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from lmqg import TransformersQG
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# initialize model
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model = TransformersQG(language="en", model="lmqg/t5-large-subjqa-vanilla-tripadvisor")
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# model prediction
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questions = model.generate_q(list_context="William Turner was an English painter who specialised in watercolour landscapes", list_answer="William Turner")
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```
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- With `transformers`
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```python
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from transformers import pipeline
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pipe = pipeline("text2text-generation", "lmqg/t5-large-subjqa-vanilla-tripadvisor")
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output = pipe("generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")
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```
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## Evaluation
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- ***Metric (Question Generation)***: [raw metric file](https://huggingface.co/lmqg/t5-large-subjqa-vanilla-tripadvisor/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.tripadvisor.json)
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| | Score | Type | Dataset |
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|:-----------|--------:|:------------|:-----------------------------------------------------------------|
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| BERTScore | 78.39 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| Bleu_1 | 2.95 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| Bleu_2 | 0.73 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| Bleu_3 | 0.23 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| Bleu_4 | 0 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| METEOR | 3.86 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| MoverScore | 49.03 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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| ROUGE_L | 3.81 | tripadvisor | [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) |
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## Citation
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```
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
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author = "Ushio, Asahi and
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