model update
Browse files- README.md +46 -6
- config.json +1 -1
- eval/metric.first.answer.paragraph.questions_answers.lmqg_qag_koquad.default.json +1 -1
- pytorch_model.bin +2 -2
- tokenizer_config.json +1 -1
README.md
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@@ -30,6 +30,36 @@ model-index:
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- name: BLEU4 (Question & Answer Generation)
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type: bleu4_question_answer_generation
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value: 0.87
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---
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# Model Card of `lmqg/mt5-base-koquad-qag`
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- ***Metric (Question & Answer Generation)***: [raw metric file](https://huggingface.co/lmqg/mt5-base-koquad-qag/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qag_koquad.default.json)
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- name: BLEU4 (Question & Answer Generation)
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type: bleu4_question_answer_generation
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value: 0.87
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- name: ROUGE-L (Question & Answer Generation)
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type: rouge_l_question_answer_generation
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value: 8.97
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- name: METEOR (Question & Answer Generation)
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type: meteor_question_answer_generation
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value: 14.25
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- name: BERTScore (Question & Answer Generation)
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type: bertscore_question_answer_generation
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value: 59.63
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- name: MoverScore (Question & Answer Generation)
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type: moverscore_question_answer_generation
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value: 59.15
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- name: QAAlignedF1Score-BERTScore (Question & Answer Generation)
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type: qa_aligned_f1_score_bertscore_question_answer_generation
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value: 76.88
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- name: QAAlignedRecall-BERTScore (Question & Answer Generation)
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type: qa_aligned_recall_bertscore_question_answer_generation
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value: 76.69
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- name: QAAlignedPrecision-BERTScore (Question & Answer Generation)
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type: qa_aligned_precision_bertscore_question_answer_generation
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value: 77.1
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- name: QAAlignedF1Score-MoverScore (Question & Answer Generation)
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type: qa_aligned_f1_score_moverscore_question_answer_generation
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value: 77.95
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- name: QAAlignedRecall-MoverScore (Question & Answer Generation)
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type: qa_aligned_recall_moverscore_question_answer_generation
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value: 77.66
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- name: QAAlignedPrecision-MoverScore (Question & Answer Generation)
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type: qa_aligned_precision_moverscore_question_answer_generation
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value: 78.29
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---
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# Model Card of `lmqg/mt5-base-koquad-qag`
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- ***Metric (Question & Answer Generation)***: [raw metric file](https://huggingface.co/lmqg/mt5-base-koquad-qag/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qag_koquad.default.json)
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| | Score | Type | Dataset |
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|:--------------------------------|--------:|:--------|:-------------------------------------------------------------------|
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| BERTScore | 59.63 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| Bleu_1 | 4.66 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| Bleu_2 | 2.43 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| Bleu_3 | 1.4 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| Bleu_4 | 0.87 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| METEOR | 14.25 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| MoverScore | 59.15 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| QAAlignedF1Score (BERTScore) | 76.88 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| QAAlignedF1Score (MoverScore) | 77.95 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| QAAlignedPrecision (BERTScore) | 77.1 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| QAAlignedPrecision (MoverScore) | 78.29 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| QAAlignedRecall (BERTScore) | 76.69 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| QAAlignedRecall (MoverScore) | 77.66 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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| ROUGE_L | 8.97 | default | [lmqg/qag_koquad](https://huggingface.co/datasets/lmqg/qag_koquad) |
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config.json
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{
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"_name_or_path": "lmqg_output/mt5-base-koquad-qag/
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"add_prefix": false,
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"architectures": [
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"MT5ForConditionalGeneration"
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{
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"_name_or_path": "lmqg_output/mt5-base-koquad-qag/model_umlauj/epoch_17",
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"add_prefix": false,
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"architectures": [
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"MT5ForConditionalGeneration"
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eval/metric.first.answer.paragraph.questions_answers.lmqg_qag_koquad.default.json
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{"validation": {"Bleu_1": 0.22944459267164455, "Bleu_2": 0.14581809736110674, "Bleu_3": 0.09073762379558614, "Bleu_4": 0.060320148625246546}, "test": {"Bleu_1": 0.046633951117251785, "Bleu_2": 0.024267387176477355, "Bleu_3": 0.013983981210269144, "Bleu_4": 0.00865229909206871}}
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{"validation": {"Bleu_1": 0.22944459267164455, "Bleu_2": 0.14581809736110674, "Bleu_3": 0.09073762379558614, "Bleu_4": 0.060320148625246546, "METEOR": 0.21020536565003278, "ROUGE_L": 0.2466824670559609, "BERTScore": 0.7206163909596701, "MoverScore": 0.6696985735571672, "QAAlignedF1Score (BERTScore)": 0.7926473005991794, "QAAlignedRecall (BERTScore)": 0.7655120301171079, "QAAlignedPrecision (BERTScore)": 0.8227984495823168, "QAAlignedF1Score (MoverScore)": 0.8196813358976065, "QAAlignedRecall (MoverScore)": 0.7834570086693475, "QAAlignedPrecision (MoverScore)": 0.8610160754337751}, "test": {"Bleu_1": 0.046633951117251785, "Bleu_2": 0.024267387176477355, "Bleu_3": 0.013983981210269144, "Bleu_4": 0.00865229909206871, "METEOR": 0.14250042873681426, "ROUGE_L": 0.08972020374341763, "BERTScore": 0.5963447060618836, "MoverScore": 0.5914871388294957, "QAAlignedF1Score (BERTScore)": 0.7688378008310351, "QAAlignedRecall (BERTScore)": 0.7669275914942397, "QAAlignedPrecision (BERTScore)": 0.7709911078538925, "QAAlignedF1Score (MoverScore)": 0.7794858817862599, "QAAlignedRecall (MoverScore)": 0.7766280538644278, "QAAlignedPrecision (MoverScore)": 0.782938458908736}}
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pytorch_model.bin
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tokenizer_config.json
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"extra_ids": 0,
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"name_or_path": "lmqg_output/mt5-base-koquad-qag/model_umlauj/epoch_17",
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