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t5-base-tweetqa-qag-np

Text2Text Generation
Transformers
PyTorch
English
t5
questions and answers generation
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
asahi417 commited on
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1 Parent(s): 0bd2368

model update

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  1. README.md +12 -12
README.md CHANGED
@@ -42,23 +42,23 @@ model-index:
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  - name: MoverScore (Question & Answer Generation)
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  type: moverscore_question_answer_generation
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  value: 62.26
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- - name: QAAlignedF1Score-BERTScore
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- type: qa_aligned_f1_score_bertscore
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  value: 92.4
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- - name: QAAlignedRecall-BERTScore
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- type: qa_aligned_recall_bertscore
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  value: 92.03
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- - name: QAAlignedPrecision-BERTScore
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- type: qa_aligned_precision_bertscore
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  value: 92.78
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- - name: QAAlignedF1Score-MoverScore
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- type: qa_aligned_f1_score_moverscore
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  value: 64.83
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- - name: QAAlignedRecall-MoverScore
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- type: qa_aligned_recall_moverscore
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  value: 64.07
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- - name: QAAlignedPrecision-MoverScore
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- type: qa_aligned_precision_moverscore
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  value: 65.68
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  ---
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42
  - name: MoverScore (Question & Answer Generation)
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  type: moverscore_question_answer_generation
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  value: 62.26
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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: 92.4
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+ - name: QAAlignedRecall-BERTScore (Question & Answer Generation)
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+ type: qa_aligned_recall_bertscore_question_answer_generation
50
  value: 92.03
51
+ - name: QAAlignedPrecision-BERTScore (Question & Answer Generation)
52
+ type: qa_aligned_precision_bertscore_question_answer_generation
53
  value: 92.78
54
+ - name: QAAlignedF1Score-MoverScore (Question & Answer Generation)
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+ type: qa_aligned_f1_score_moverscore_question_answer_generation
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  value: 64.83
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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: 64.07
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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: 65.68
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  ---
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