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model update

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  1. README.md +7 -7
README.md CHANGED
@@ -18,7 +18,7 @@ widget:
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  example_title: "Question Generation Example 1"
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  - text: "generate question: Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
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  example_title: "Question Generation Example 2"
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- - text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, <hl> Cadillac Records <hl> ."
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  example_title: "Question Generation Example 3"
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  model-index:
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  - name: lmqg/t5-small-squad-no-paragraph
@@ -33,19 +33,19 @@ model-index:
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  metrics:
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  - name: BLEU4
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  type: bleu4
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- value: 0.23349926865772538
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  - name: ROUGE-L
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  type: rouge-l
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- value: 0.5051176301939
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  - name: METEOR
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  type: meteor
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- value: 0.2483120643455213
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  - name: BERTScore
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  type: bertscore
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- value: 0.9034379432252281
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  - name: MoverScore
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  type: moverscore
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- value: 0.6344747434744118
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  ---
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  # Language Models Fine-tuning on Question Generation: `lmqg/t5-small-squad-no-paragraph`
@@ -81,7 +81,7 @@ question = pipe(input_text)
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  | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
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  |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
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- | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.23349926865772538 | 0.5051176301939 | 0.2483120643455213 | 0.9034379432252281 | 0.6344747434744118 | [link](https://huggingface.co/lmqg/t5-small-squad-no-paragraph/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) |
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  example_title: "Question Generation Example 1"
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  - text: "generate question: Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
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  example_title: "Question Generation Example 2"
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+ - text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, <hl> Cadillac Records <hl> ."
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  example_title: "Question Generation Example 3"
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  model-index:
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  - name: lmqg/t5-small-squad-no-paragraph
 
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  metrics:
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  - name: BLEU4
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  type: bleu4
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+ value: 0.2323410628068291
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  - name: ROUGE-L
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  type: rouge-l
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+ value: 0.501778456335822
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  - name: METEOR
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  type: meteor
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+ value: 0.24803004691027772
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  - name: BERTScore
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  type: bertscore
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+ value: 0.9035977943342849
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  - name: MoverScore
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  type: moverscore
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+ value: 0.6318028738243845
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  ---
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  # Language Models Fine-tuning on Question Generation: `lmqg/t5-small-squad-no-paragraph`
 
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  | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
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  |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
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+ | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.2323410628068291 | 0.501778456335822 | 0.24803004691027772 | 0.9035977943342849 | 0.6318028738243845 | [link](https://huggingface.co/lmqg/t5-small-squad-no-paragraph/raw/main/eval/metric.first.sentence.sentence_answer.question.lmqg_qg_squad.default.json) |
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