model update

README.md

@@ -46,6 +46,24 @@ model-index:
     - name: MoverScore (Question Generation)
       type: moverscore_question_generation
       value: 83.36
+    - name: QAAlignedF1Score-BERTScore (Question & Answer Generation) [Gold Answer]
+      type: qa_aligned_f1_score_bertscore_question_answer_generation_gold_answer
+      value: 88.8
+    - name: QAAlignedRecall-BERTScore (Question & Answer Generation) [Gold Answer]
+      type: qa_aligned_recall_bertscore_question_answer_generation_gold_answer
+      value: 88.76
+    - name: QAAlignedPrecision-BERTScore (Question & Answer Generation) [Gold Answer]
+      type: qa_aligned_precision_bertscore_question_answer_generation_gold_answer
+      value: 88.84
+    - name: QAAlignedF1Score-MoverScore (Question & Answer Generation) [Gold Answer]
+      type: qa_aligned_f1_score_moverscore_question_answer_generation_gold_answer
+      value: 85.93
+    - name: QAAlignedRecall-MoverScore (Question & Answer Generation) [Gold Answer]
+      type: qa_aligned_recall_moverscore_question_answer_generation_gold_answer
+      value: 85.87
+    - name: QAAlignedPrecision-MoverScore (Question & Answer Generation) [Gold Answer]
+      type: qa_aligned_precision_moverscore_question_answer_generation_gold_answer
+      value: 86.01
 ---
 
 # Model Card of `lmqg/mt5-base-koquad-qg`
@@ -99,6 +117,18 @@ output = pipe("1990년 영화 《 <hl> 남부군 <hl> 》에서 단역으로 영
 | ROUGE_L    |   28.57 | 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/mt5-base-koquad-qg/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_koquad.default.json)
+
+|                                 |   Score | Type    | Dataset                                                          |
+|:--------------------------------|--------:|:--------|:-----------------------------------------------------------------|
+| QAAlignedF1Score (BERTScore)    |   88.8  | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| QAAlignedF1Score (MoverScore)   |   85.93 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| QAAlignedPrecision (BERTScore)  |   88.84 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| QAAlignedPrecision (MoverScore) |   86.01 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| QAAlignedRecall (BERTScore)     |   88.76 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+| QAAlignedRecall (MoverScore)    |   85.87 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
+
+
 
 ## Training hyperparameters