model update
Browse files- README.md +118 -0
- eval/{metric.first.answer.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.first.answer.paragraph_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.first.answer.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.first.answer.paragraph_sentence.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.first.answer.sentence_answer.question.asahi417_qg_itquad.default.json → metric.first.answer.sentence_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.first.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.first.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.first.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.first.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.first.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.first.sentence.sentence_answer.question.lmqg_qg_itquad.default.json} +0 -0
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- eval/{metric.last.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.last.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.last.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.last.sentence.sentence_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.long.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.long.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.long.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.long.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.long.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.long.sentence.sentence_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.middle.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.middle.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.middle.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.middle.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.middle.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.middle.sentence.sentence_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.short.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.short.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.short.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.short.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{metric.short.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.short.sentence.sentence_answer.question.lmqg_qg_itquad.default.json} +0 -0
- eval/{samples.test.hyp.paragraph_answer.question.asahi417_qg_itquad.default.txt → samples.test.hyp.paragraph_answer.question.lmqg_qg_itquad.default.txt} +0 -0
- eval/{samples.test.hyp.paragraph_sentence.question.asahi417_qg_itquad.default.txt → samples.test.hyp.paragraph_sentence.question.lmqg_qg_itquad.default.txt} +0 -0
- eval/{samples.test.hyp.sentence_answer.question.asahi417_qg_itquad.default.txt → samples.test.hyp.sentence_answer.question.lmqg_qg_itquad.default.txt} +0 -0
- eval/{samples.validation.hyp.paragraph_answer.question.asahi417_qg_itquad.default.txt → samples.validation.hyp.paragraph_answer.question.lmqg_qg_itquad.default.txt} +0 -0
- eval/{samples.validation.hyp.paragraph_sentence.question.asahi417_qg_itquad.default.txt → samples.validation.hyp.paragraph_sentence.question.lmqg_qg_itquad.default.txt} +0 -0
- eval/{samples.validation.hyp.sentence_answer.question.asahi417_qg_itquad.default.txt → samples.validation.hyp.sentence_answer.question.lmqg_qg_itquad.default.txt} +0 -0
- trainer_config.json +1 -1
README.md
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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: it
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datasets:
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- lmqg/qg_itquad
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pipeline_tag: text2text-generation
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tags:
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- question generation
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- answer extraction
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widget:
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- text: "generate question: <hl> Dopo il 1971 <hl> , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento."
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example_title: "Question Generation Example 1"
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- text: "generate question: L' individuazione del petrolio e lo sviluppo di nuovi giacimenti richiedeva in genere <hl> da cinque a dieci anni <hl> prima di una produzione significativa."
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example_title: "Question Generation Example 2"
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- text: "generate question: il <hl> Giappone <hl> è stato il paese più dipendente dal petrolio arabo."
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example_title: "Question Generation Example 3"
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- text: "<hl> Il 6 ottobre 1973 , la Siria e l' Egitto, con il sostegno di altre nazioni arabe, lanciarono un attacco a sorpresa su Israele, su Yom Kippur. <hl> Questo rinnovo delle ostilità nel conflitto arabo-israeliano ha liberato la pressione economica sottostante sui prezzi del petrolio. All' epoca, l' Iran era il secondo esportatore mondiale di petrolio e un vicino alleato degli Stati Uniti. Settimane più tardi, lo scià d' Iran ha detto in un' intervista: Naturalmente[il prezzo del petrolio] sta andando a salire Certamente! E come! Avete[Paesi occidentali] aumentato il prezzo del grano che ci vendete del 300 per cento, e lo stesso per zucchero e cemento."
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example_title: "Answer Extraction Example 1"
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- text: "<hl> Furono introdotti autocarri compatti, come la Toyota Hilux e il Datsun Truck, seguiti dal camion Mazda (venduto come il Ford Courier), e l' Isuzu costruito Chevrolet LUV. <hl> Mitsubishi rebranded il suo Forte come Dodge D-50 pochi anni dopo la crisi petrolifera. Mazda, Mitsubishi e Isuzu avevano partnership congiunte rispettivamente con Ford, Chrysler e GM. In seguito i produttori americani introdussero le loro sostituzioni nazionali (Ford Ranger, Dodge Dakota e la Chevrolet S10/GMC S-15), ponendo fine alla loro politica di importazione vincolata."
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example_title: "Answer Extraction Example 2"
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model-index:
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- name: lmqg/mt5-small-itquad-multitask
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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_itquad
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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: 0.07247588693912974
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- name: ROUGE-L
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type: rouge-l
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value: 0.2183840870793931
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- name: METEOR
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type: meteor
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value: 0.17495288244686244
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- name: BERTScore
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type: bertscore
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value: 0.8061110932516495
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- name: MoverScore
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type: moverscore
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value: 0.5662580131358668
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---
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# Language Models Fine-tuning on Question Generation: `lmqg/mt5-small-itquad-multitask`
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This model is fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) for question generation task on the
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[lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default).
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This model is fine-tuned on the answer extraction task as well as the question generation.
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### Overview
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- **Language model:** [google/mt5-small](https://huggingface.co/google/mt5-small)
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- **Language:** it
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- **Training data:** [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (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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### Usage
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```python
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from transformers import pipeline
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model_path = 'lmqg/mt5-small-itquad-multitask'
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pipe = pipeline("text2text-generation", model_path)
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# Question Generation
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input_text = 'generate question: <hl> Dopo il 1971 <hl> , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento.'
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question = pipe(input_text)
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# Answer Extraction
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answer = pipe('extract answers: <hl> Il 6 ottobre 1973 , la Siria e l' Egitto, con il sostegno di altre nazioni arabe, lanciarono un attacco a sorpresa su Israele, su Yom Kippur. <hl> Questo rinnovo delle ostilità nel conflitto arabo-israeliano ha liberato la pressione economica sottostante sui prezzi del petrolio. All' epoca, l' Iran era il secondo esportatore mondiale di petrolio e un vicino alleato degli Stati Uniti. Settimane più tardi, lo scià d' Iran ha detto in un' intervista: Naturalmente[il prezzo del petrolio] sta andando a salire Certamente! E come! Avete[Paesi occidentali] aumentato il prezzo del grano che ci vendete del 300 per cento, e lo stesso per zucchero e cemento.')
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```
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## Evaluation Metrics
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### Metrics
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| Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
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|:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
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| [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) | default | 0.07247588693912974 | 0.2183840870793931 | 0.17495288244686244 | 0.8061110932516495 | 0.5662580131358668 | [link](https://huggingface.co/lmqg/mt5-small-itquad-multitask/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json) |
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## Training hyperparameters
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The following hyperparameters were used during fine-tuning:
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- dataset_path: lmqg/qg_itquad
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- dataset_name: default
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- input_types: ['paragraph_answer', 'paragraph_sentence']
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- output_types: ['question', 'answer']
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- prefix_types: ['qg', 'ae']
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- model: google/mt5-small
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- max_length: 512
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- max_length_output: 32
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- epoch: 13
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- batch: 16
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- lr: 0.001
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- fp16: False
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- random_seed: 1
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- gradient_accumulation_steps: 4
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- label_smoothing: 0.15
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The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/mt5-small-itquad-multitask/raw/main/trainer_config.json).
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## Citation
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TBA
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eval/{metric.first.answer.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.first.answer.paragraph_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.first.answer.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.first.answer.paragraph_sentence.question.lmqg_qg_itquad.default.json}
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eval/{metric.first.answer.sentence_answer.question.asahi417_qg_itquad.default.json → metric.first.answer.sentence_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.first.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.first.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.first.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.first.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json}
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eval/{metric.first.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.first.sentence.sentence_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.last.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.last.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.last.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.last.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json}
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eval/{metric.last.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.last.sentence.sentence_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.long.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.long.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.long.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.long.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json}
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eval/{metric.long.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.long.sentence.sentence_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.middle.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.middle.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.middle.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.middle.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json}
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eval/{metric.middle.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.middle.sentence.sentence_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.short.sentence.paragraph_answer.question.asahi417_qg_itquad.default.json → metric.short.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json}
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eval/{metric.short.sentence.paragraph_sentence.question.asahi417_qg_itquad.default.json → metric.short.sentence.paragraph_sentence.question.lmqg_qg_itquad.default.json}
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eval/{metric.short.sentence.sentence_answer.question.asahi417_qg_itquad.default.json → metric.short.sentence.sentence_answer.question.lmqg_qg_itquad.default.json}
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eval/{samples.test.hyp.paragraph_answer.question.asahi417_qg_itquad.default.txt → samples.test.hyp.paragraph_answer.question.lmqg_qg_itquad.default.txt}
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eval/{samples.test.hyp.paragraph_sentence.question.asahi417_qg_itquad.default.txt → samples.test.hyp.paragraph_sentence.question.lmqg_qg_itquad.default.txt}
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eval/{samples.test.hyp.sentence_answer.question.asahi417_qg_itquad.default.txt → samples.test.hyp.sentence_answer.question.lmqg_qg_itquad.default.txt}
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eval/{samples.validation.hyp.paragraph_answer.question.asahi417_qg_itquad.default.txt → samples.validation.hyp.paragraph_answer.question.lmqg_qg_itquad.default.txt}
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eval/{samples.validation.hyp.paragraph_sentence.question.asahi417_qg_itquad.default.txt → samples.validation.hyp.paragraph_sentence.question.lmqg_qg_itquad.default.txt}
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eval/{samples.validation.hyp.sentence_answer.question.asahi417_qg_itquad.default.txt → samples.validation.hyp.sentence_answer.question.lmqg_qg_itquad.default.txt}
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trainer_config.json
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{"dataset_path": "
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{"dataset_path": "lmqg/qg_itquad", "dataset_name": "default", "input_types": ["paragraph_answer", "paragraph_sentence"], "output_types": ["question", "answer"], "prefix_types": ["qg", "ae"], "model": "google/mt5-small", "max_length": 512, "max_length_output": 32, "epoch": 13, "batch": 16, "lr": 0.001, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 4, "label_smoothing": 0.15}
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