model update

README.md

@@ -46,23 +46,38 @@ model-index:
     - name: MoverScore (Question Generation)
       type: moverscore_question_generation
       value: 82.95
-    - name: QAAlignedF1Score-BERTScore (Question & Answer Generation) [Gold Answer]
-      type: qa_aligned_f1_score_bertscore_question_answer_generation_gold_answer
+    - name: BLEU4 (Question & Answer Generation (with Gold Answer))
+      type: bleu4_question_answer_generation_with_gold_answer
+      value: 11.25
+    - name: ROUGE-L (Question & Answer Generation (with Gold Answer))
+      type: rouge_l_question_answer_generation_with_gold_answer
+      value: 47.9
+    - name: METEOR (Question & Answer Generation (with Gold Answer))
+      type: meteor_question_answer_generation_with_gold_answer
+      value: 39.03
+    - name: BERTScore (Question & Answer Generation (with Gold Answer))
+      type: bertscore_question_answer_generation_with_gold_answer
+      value: 87.88
+    - name: MoverScore (Question & Answer Generation (with Gold Answer))
+      type: moverscore_question_answer_generation_with_gold_answer
+      value: 84.85
+    - name: QAAlignedF1Score-BERTScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
+      type: qa_aligned_f1_score_bertscore_question_answer_generation_with_gold_answer_gold_answer
       value: 88.18
-    - name: QAAlignedRecall-BERTScore (Question & Answer Generation) [Gold Answer]
-      type: qa_aligned_recall_bertscore_question_answer_generation_gold_answer
+    - name: QAAlignedRecall-BERTScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
+      type: qa_aligned_recall_bertscore_question_answer_generation_with_gold_answer_gold_answer
       value: 88.15
-    - name: QAAlignedPrecision-BERTScore (Question & Answer Generation) [Gold Answer]
-      type: qa_aligned_precision_bertscore_question_answer_generation_gold_answer
+    - name: QAAlignedPrecision-BERTScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
+      type: qa_aligned_precision_bertscore_question_answer_generation_with_gold_answer_gold_answer
       value: 88.22
-    - name: QAAlignedF1Score-MoverScore (Question & Answer Generation) [Gold Answer]
-      type: qa_aligned_f1_score_moverscore_question_answer_generation_gold_answer
+    - name: QAAlignedF1Score-MoverScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
+      type: qa_aligned_f1_score_moverscore_question_answer_generation_with_gold_answer_gold_answer
       value: 85.53
-    - name: QAAlignedRecall-MoverScore (Question & Answer Generation) [Gold Answer]
-      type: qa_aligned_recall_moverscore_question_answer_generation_gold_answer
+    - name: QAAlignedRecall-MoverScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
+      type: qa_aligned_recall_moverscore_question_answer_generation_with_gold_answer_gold_answer
       value: 85.46
-    - name: QAAlignedPrecision-MoverScore (Question & Answer Generation) [Gold Answer]
-      type: qa_aligned_precision_moverscore_question_answer_generation_gold_answer
+    - name: QAAlignedPrecision-MoverScore (Question & Answer Generation (with Gold Answer)) [Gold Answer]
+      type: qa_aligned_precision_moverscore_question_answer_generation_with_gold_answer_gold_answer
       value: 85.62
 ---
 
@@ -117,16 +132,24 @@ output = pipe("1990년 영화 《 <hl> 남부군 <hl> 》에서 단역으로 영
 | ROUGE_L    |   27.76 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 
 
-- ***Metric (Question & Answer Generation)***: QAG metrics are computed with *the gold answer* and generated question on it for this model, as the model cannot provide an answer. [raw metric file](https://huggingface.co/lmqg/mbart-large-cc25-koquad-qg/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_koquad.default.json)
+- ***Metric (Question & Answer Generation, Reference Answer)***: Each question is generated from *the gold answer*. [raw metric file](https://huggingface.co/lmqg/mbart-large-cc25-koquad-qg/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_koquad.default.json)
 
 |                                 |   Score | Type    | Dataset                                                          |
 |:--------------------------------|--------:|:--------|:-----------------------------------------------------------------|
+| BERTScore                       |   87.88 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| Bleu_1                          |   42.94 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| Bleu_2                          |   31.44 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| Bleu_3                          |   19.38 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| Bleu_4                          |   11.25 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| METEOR                          |   39.03 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| MoverScore                      |   84.85 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 | QAAlignedF1Score (BERTScore)    |   88.18 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 | QAAlignedF1Score (MoverScore)   |   85.53 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 | QAAlignedPrecision (BERTScore)  |   88.22 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 | QAAlignedPrecision (MoverScore) |   85.62 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 | QAAlignedRecall (BERTScore)     |   88.15 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
 | QAAlignedRecall (MoverScore)    |   85.46 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| ROUGE_L                         |   47.9  | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |