model update

README.md

@@ -91,7 +91,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5531135531135531
+      value: 0.3145973154362416
   - task:
       name: Analogy Questions (TREX Analogy)
       type: multiple-choice-qa
@@ -102,7 +102,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8288690476190477
+      value: 0.5683060109289617
+  - 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: 0.61
   - task:
       name: Lexical Relation Classification (BLESS)
       type: classification
@@ -186,8 +197,9 @@ This model achieves the following results on the relation understanding tasks:
     - Accuracy on U2: 0.618421052631579
     - Accuracy on U4: 0.5949074074074074
     - Accuracy on Google: 0.902
-    - Accuracy on ConceptNet Analogy: 0.5531135531135531
-    - Accuracy on T-Rex Analogy: 0.8288690476190477
+    - Accuracy on ConceptNet Analogy: 0.3145973154362416
+    - Accuracy on T-Rex Analogy: 0.5683060109289617
+    - Accuracy on NELL-ONE Analogy: 0.61
 - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/relbert-roberta-large-triplet-e-semeval2012/raw/main/classification.json)):
     - Micro F1 score on BLESS: 0.9026668675606448
     - Micro F1 score on CogALexV: 0.8607981220657277