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/bart-base-squadshifts-nyt`
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This model is fine-tuned version of [lmqg/bart-base-squad](https://huggingface.co/lmqg/bart-base-squad) for question generation task on the
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[lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) (dataset_name: nyt) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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This model is continuously fine-tuned with [lmqg/bart-base-squad](https://huggingface.co/lmqg/bart-base-squad).
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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:** [lmqg/bart-base-squad](https://huggingface.co/lmqg/bart-base-squad)
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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/bart-base-squadshifts-nyt')
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# question generation
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question = pipe('<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_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | nyt | 0.088 | 0.248 | 0.251 | 0.929 | 0.65 | [link](https://huggingface.co/lmqg/bart-base-squadshifts-nyt/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.nyt.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: 8.78
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- name: ROUGE-L
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type: rouge-l
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value: 24.85
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- name: METEOR
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type: meteor
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value: 25.13
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- name: BERTScore
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type: bertscore
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value: 92.86
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- name: MoverScore
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type: moverscore
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value: 64.99
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---
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# Model Card of `lmqg/bart-base-squadshifts-nyt`
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This model is fine-tuned version of [lmqg/bart-base-squad](https://huggingface.co/lmqg/bart-base-squad) for question generation task on the [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) (dataset_name: nyt) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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This model is continuously fine-tuned with [lmqg/bart-base-squad](https://huggingface.co/lmqg/bart-base-squad).
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### Overview
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- **Language model:** [lmqg/bart-base-squad](https://huggingface.co/lmqg/bart-base-squad)
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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/bart-base-squadshifts-nyt")
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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/bart-base-squadshifts-nyt")
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output = pipe("<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/bart-base-squadshifts-nyt/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.nyt.json)
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| | Score | Type | Dataset |
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|:-----------|--------:|:-------|:---------------------------------------------------------------------------|
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| BERTScore | 92.86 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| Bleu_1 | 25.26 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| Bleu_2 | 16.85 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| Bleu_3 | 11.93 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| Bleu_4 | 8.78 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| METEOR | 25.13 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| MoverScore | 64.99 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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| ROUGE_L | 24.85 | nyt | [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
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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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