model update

README.md

@@ -103,6 +103,17 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.45901639344262296
+  - task:
+      name: Analogy Questions (NELL-ONE Analogy)
+      type: multiple-choice-qa
+    dataset:
+      name: NELL-ONE Analogy
+      args: relbert/analogy_questions
+      type: analogy-questions
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6233333333333333
   - task:
       name: Lexical Relation Classification (BLESS)
       type: classification
@@ -188,6 +199,7 @@ This model achieves the following results on the relation understanding tasks:
     - Accuracy on Google: 0.92
     - Accuracy on ConceptNet Analogy: 0.3196308724832215
     - Accuracy on T-Rex Analogy: 0.45901639344262296
+    - Accuracy on NELL-ONE Analogy: 0.6233333333333333
 - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/relbert-roberta-large-triplet-c-semeval2012/raw/main/classification.json)):
     - Micro F1 score on BLESS: 0.9025161970769926
     - Micro F1 score on CogALexV: 0.8798122065727699