model update

README.md

@@ -46,23 +46,38 @@ model-index:
     - name: MoverScore (Question Generation)
       type: moverscore_question_generation
       value: 62.49
-    - 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: 18.61
+    - name: ROUGE-L (Question & Answer Generation (with Gold Answer))
+      type: rouge_l_question_answer_generation_with_gold_answer
+      value: 51.04
+    - name: METEOR (Question & Answer Generation (with Gold Answer))
+      type: meteor_question_answer_generation_with_gold_answer
+      value: 43.1
+    - name: BERTScore (Question & Answer Generation (with Gold Answer))
+      type: bertscore_question_answer_generation_with_gold_answer
+      value: 90.03
+    - name: MoverScore (Question & Answer Generation (with Gold Answer))
+      type: moverscore_question_answer_generation_with_gold_answer
+      value: 67.82
+    - 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: 90.17
-    - 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: 90.16
-    - 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: 90.17
-    - 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: 68.22
-    - 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: 68.21
-    - 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: 68.23
 ---
 
@@ -117,16 +132,24 @@ output = pipe("Нелишним будет отметить, что, разви
 | ROUGE_L    |   31.39 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 
 
-- ***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-small-ruquad-qg/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_ruquad.default.json)
+- ***Metric (Question & Answer Generation, Reference Answer)***: Each question is generated from *the gold answer*. [raw metric file](https://huggingface.co/lmqg/mt5-small-ruquad-qg/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_ruquad.default.json)
 
 |                                 |   Score | Type    | Dataset                                                          |
 |:--------------------------------|--------:|:--------|:-----------------------------------------------------------------|
+| BERTScore                       |   90.03 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_1                          |   45.81 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_2                          |   34.13 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_3                          |   25.81 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_4                          |   18.61 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| METEOR                          |   43.1  | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| MoverScore                      |   67.82 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 | QAAlignedF1Score (BERTScore)    |   90.17 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 | QAAlignedF1Score (MoverScore)   |   68.22 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 | QAAlignedPrecision (BERTScore)  |   90.17 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 | QAAlignedPrecision (MoverScore) |   68.23 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 | QAAlignedRecall (BERTScore)     |   90.16 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 | QAAlignedRecall (MoverScore)    |   68.21 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| ROUGE_L                         |   51.04 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |