model update

README.md

@@ -14,7 +14,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8809523809523809
+      value: 0.8121428571428572
   - task:
       name: Analogy Questions (SAT full)
       type: multiple-choice-qa
@@ -91,10 +91,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.9352116920295314
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.9311260283995134
   - task:
       name: Lexical Relation Classification (CogALexV)
       type: classification
@@ -105,10 +105,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.8788732394366198
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.7379976930896036
   - task:
       name: Lexical Relation Classification (EVALution)
       type: classification
@@ -119,10 +119,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.7074756229685807
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.6987258653863991
   - task:
       name: Lexical Relation Classification (K&H+N)
       type: classification
@@ -133,10 +133,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.9649440077902205
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.8941098884351074
   - task:
       name: Lexical Relation Classification (ROOT09)
       type: classification
@@ -147,10 +147,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.9100595424631777
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.9083602075581158
 
 ---
 # relbert/roberta-large-semeval2012-mask-prompt-e-nce
@@ -167,13 +167,13 @@ It achieves the following results on the relation understanding tasks:
     - Accuracy on U4: 0.6412037037037037
     - Accuracy on Google: 0.868
 - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce/raw/main/classification.json)):
-    - Micro F1 score on BLESS: None
-    - Micro F1 score on CogALexV: None
-    - Micro F1 score on EVALution: None
-    - Micro F1 score on K&H+N: None
-    - Micro F1 score on ROOT09: None
+    - Micro F1 score on BLESS: 0.9352116920295314
+    - Micro F1 score on CogALexV: 0.8788732394366198
+    - Micro F1 score on EVALution: 0.7074756229685807
+    - Micro F1 score on K&H+N: 0.9649440077902205
+    - Micro F1 score on ROOT09: 0.9100595424631777
 - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce/raw/main/relation_mapping.json)):
-    - Accuracy on Relation Mapping: 0.8809523809523809 
+    - Accuracy on Relation Mapping: 0.8121428571428572 
 
 
 ### Usage