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model update

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README.md ADDED
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+
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+ ---
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+ license: cc-by-4.0
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+ metrics:
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+ - bleu4
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+ - meteor
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+ - rouge-l
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+ - bertscore
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+ - moverscore
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+ language: ko
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+ datasets:
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+ - lmqg/qg_koquad
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+ pipeline_tag: text2text-generation
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+ tags:
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+ - question generation
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+ widget:
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+ - text: "generate question: 1990년 영화 《 <hl> 남부군 <hl> 》에서 단역으로 영화배우 첫 데뷔에 이어 같은 해 KBS 드라마 《지구인》에서 단역으로 출연하였고 이듬해 MBC 《여명의 눈동자》를 통해 단역으로 출연하였다."
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+ example_title: "Question Generation Example 1"
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+ - text: "generate question: 백신이 없기때문에 예방책은 <hl> 살충제 <hl> 를 사용하면서 서식 장소(찻찬 받침, 배수로, 고인 물의 열린 저장소, 버려진 타이어 등)의 수를 줄임으로써 매개체를 통제할 수 있다."
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+ example_title: "Question Generation Example 2"
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+ - text: "generate question: <hl> 원테이크 촬영 <hl> 이기 때문에 한 사람이 실수를 하면 처음부터 다시 찍어야 하는 상황이 발생한다."
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+ example_title: "Question Generation Example 3"
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+ model-index:
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+ - name: lmqg/mt5-base-koquad
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+ results:
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+ - task:
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+ name: Text2text Generation
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+ type: text2text-generation
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+ dataset:
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+ name: lmqg/qg_koquad
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+ type: default
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+ args: default
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+ metrics:
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+ - name: BLEU4
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+ type: bleu4
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+ value: 0.12184665382055122
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+ - name: ROUGE-L
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+ type: rouge-l
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+ value: 0.2856948017709817
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+ - name: METEOR
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+ type: meteor
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+ value: 0.29623847263524816
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+ - name: BERTScore
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+ type: bertscore
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+ value: 0.8451586993172961
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+ - name: MoverScore
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+ type: moverscore
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+ value: 0.8335888774638588
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+ ---
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+
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+ # Language Models Fine-tuning on Question Generation: `lmqg/mt5-base-koquad`
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+ This model is fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) for question generation task on the
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+ [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) (dataset_name: default).
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+
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+
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+ ### Overview
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+ - **Language model:** [google/mt5-base](https://huggingface.co/google/mt5-base)
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+ - **Language:** ko
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+ - **Training data:** [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) (default)
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+ - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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+ - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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+ - **Paper:** [TBA](TBA)
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+
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+ ### Usage
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+ ```python
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+
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+ from transformers import pipeline
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+
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+ model_path = 'lmqg/mt5-base-koquad'
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+ pipe = pipeline("text2text-generation", model_path)
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+
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+ # Question Generation
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+ question = pipe('generate question: 1990년 영화 《 <hl> 남부군 <hl> 》에서 단역으로 영화배우 첫 데뷔에 이어 같은 해 KBS 드라마 《지구인》에서 단역으로 출연하였고 이듬해 MBC 《여명의 눈동자》를 통해 단역으로 출연하였다.')
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+ ```
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+
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+ ## Evaluation Metrics
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+
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+
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+ ### Metrics
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+
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+ | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
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+ |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
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+ | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) | default | 0.12184665382055122 | 0.2856948017709817 | 0.29623847263524816 | 0.8451586993172961 | 0.8335888774638588 | [link](https://huggingface.co/lmqg/mt5-base-koquad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_koquad.default.json) |
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+
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+
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+
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+
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+ ## Training hyperparameters
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+
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+ The following hyperparameters were used during fine-tuning:
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+ - dataset_path: lmqg/qg_koquad
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+ - dataset_name: default
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+ - input_types: ['paragraph_answer']
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+ - output_types: ['question']
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+ - prefix_types: None
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+ - model: google/mt5-base
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+ - max_length: 512
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+ - max_length_output: 32
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+ - epoch: 11
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+ - batch: 4
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+ - lr: 0.0005
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+ - fp16: False
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+ - random_seed: 1
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+ - gradient_accumulation_steps: 16
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+ - label_smoothing: 0.15
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+
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+ The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/mt5-base-koquad/raw/main/trainer_config.json).
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+
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+ ## Citation
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+ TBA
eval/{metric.first.answer.paragraph_answer.question.asahi417_qg_koquad.default.json → metric.first.answer.paragraph_answer.question.lmqg_qg_koquad.default.json} RENAMED
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eval/{metric.first.sentence.paragraph_answer.question.asahi417_qg_koquad.default.json → metric.first.sentence.paragraph_answer.question.lmqg_qg_koquad.default.json} RENAMED
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eval/{samples.test.hyp.paragraph_answer.question.asahi417_qg_koquad.default.txt → samples.test.hyp.paragraph_answer.question.lmqg_qg_koquad.default.txt} RENAMED
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eval/{samples.validation.hyp.paragraph_answer.question.asahi417_qg_koquad.default.txt → samples.validation.hyp.paragraph_answer.question.lmqg_qg_koquad.default.txt} RENAMED
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trainer_config.json CHANGED
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- {"dataset_path": "asahi417/qg_koquad", "dataset_name": "default", "input_types": ["paragraph_answer"], "output_types": ["question"], "prefix_types": null, "model": "google/mt5-base", "max_length": 512, "max_length_output": 32, "epoch": 11, "batch": 4, "lr": 0.0005, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 16, "label_smoothing": 0.15}
 
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+ {"dataset_path": "lmqg/qg_koquad", "dataset_name": "default", "input_types": ["paragraph_answer"], "output_types": ["question"], "prefix_types": null, "model": "google/mt5-base", "max_length": 512, "max_length_output": 32, "epoch": 11, "batch": 4, "lr": 0.0005, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 16, "label_smoothing": 0.15}