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t5-base-tweetqa-qag

Text2Text Generation
Transformers
PyTorch
English
t5
questions and answers generation
Eval Results
text-generation-inference
Model card Files Community
1
asahi417 commited on
Commit
0ffb71d
·
1 Parent(s): 5c1359c

model update

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  1. README.md +5 -5
README.md CHANGED
@@ -27,19 +27,19 @@ model-index:
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  type: default
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  args: default
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  metrics:
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- - name: BLEU4 ((Question & Answer Generation))
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  type: bleu4_question_answer_generation
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  value: 12.93
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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: 36.54
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- - name: METEOR ((Question & Answer Generation))
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  type: meteor_question_answer_generation
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  value: 30.35
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- - name: BERTScore ((Question & Answer Generation))
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  type: bertscore_question_answer_generation
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  value: 90.55
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- - name: MoverScore ((Question & Answer Generation))
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  type: moverscore_question_answer_generation
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  value: 61.82
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  - name: QAAlignedF1Score-BERTScore
 
27
  type: default
28
  args: default
29
  metrics:
30
+ - name: BLEU4 (Question & Answer Generation)
31
  type: bleu4_question_answer_generation
32
  value: 12.93
33
+ - name: ROUGE-L (Question & Answer Generation)
34
  type: rouge_l_question_answer_generation
35
  value: 36.54
36
+ - name: METEOR (Question & Answer Generation)
37
  type: meteor_question_answer_generation
38
  value: 30.35
39
+ - name: BERTScore (Question & Answer Generation)
40
  type: bertscore_question_answer_generation
41
  value: 90.55
42
+ - name: MoverScore (Question & Answer Generation)
43
  type: moverscore_question_answer_generation
44
  value: 61.82
45
  - name: QAAlignedF1Score-BERTScore