asahi417 commited on
Commit
5c2636c
1 Parent(s): 2e4439a

model update

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  1. README.md +29 -29
README.md CHANGED
@@ -14,7 +14,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Analogy Questions (SAT full)
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  type: multiple-choice-qa
@@ -25,7 +25,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Analogy Questions (SAT)
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  type: multiple-choice-qa
@@ -36,7 +36,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Analogy Questions (BATS)
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  type: multiple-choice-qa
@@ -47,7 +47,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Analogy Questions (Google)
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  type: multiple-choice-qa
@@ -58,7 +58,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Analogy Questions (U2)
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  type: multiple-choice-qa
@@ -69,7 +69,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Analogy Questions (U4)
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  type: multiple-choice-qa
@@ -80,7 +80,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: None
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  - task:
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  name: Lexical Relation Classification (BLESS)
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  type: classification
@@ -91,10 +91,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: None
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  - name: F1 (macro)
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  type: f1_macro
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- value: None
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  - task:
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  name: Lexical Relation Classification (CogALexV)
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  type: classification
@@ -105,10 +105,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: None
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  - name: F1 (macro)
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  type: f1_macro
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- value: None
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  - task:
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  name: Lexical Relation Classification (EVALution)
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  type: classification
@@ -119,10 +119,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: None
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  - name: F1 (macro)
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  type: f1_macro
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- value: None
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  - task:
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  name: Lexical Relation Classification (K&H+N)
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  type: classification
@@ -133,10 +133,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: None
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  - name: F1 (macro)
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  type: f1_macro
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- value: None
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  - task:
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  name: Lexical Relation Classification (ROOT09)
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  type: classification
@@ -147,10 +147,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: None
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  - name: F1 (macro)
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  type: f1_macro
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- value: None
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  ---
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  # relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification
@@ -160,20 +160,20 @@ RelBERT fine-tuned from [roberta-large](https://huggingface.co/roberta-large) on
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  Fine-tuning is done via [RelBERT](https://github.com/asahi417/relbert) library (see the repository for more detail).
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  It achieves the following results on the relation understanding tasks:
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  - Analogy Question ([dataset](https://huggingface.co/datasets/relbert/analogy_questions), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/analogy.json)):
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- - Accuracy on SAT (full): None
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- - Accuracy on SAT: None
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- - Accuracy on BATS: None
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- - Accuracy on U2: None
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- - Accuracy on U4: None
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- - Accuracy on Google: None
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  - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/classification.json)):
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- - Micro F1 score on BLESS: None
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- - Micro F1 score on CogALexV: None
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- - Micro F1 score on EVALution: None
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- - Micro F1 score on K&H+N: None
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- - Micro F1 score on ROOT09: None
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  - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/relation_mapping.json)):
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- - Accuracy on Relation Mapping: None
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  ### Usage
 
14
  metrics:
15
  - name: Accuracy
16
  type: accuracy
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+ value: 0.7550595238095238
18
  - task:
19
  name: Analogy Questions (SAT full)
20
  type: multiple-choice-qa
 
25
  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.5133689839572193
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  - task:
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  name: Analogy Questions (SAT)
31
  type: multiple-choice-qa
 
36
  metrics:
37
  - name: Accuracy
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  type: accuracy
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+ value: 0.516320474777448
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  - task:
41
  name: Analogy Questions (BATS)
42
  type: multiple-choice-qa
 
47
  metrics:
48
  - name: Accuracy
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  type: accuracy
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+ value: 0.5958866036687048
51
  - task:
52
  name: Analogy Questions (Google)
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  type: multiple-choice-qa
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.748
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  - task:
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  name: Analogy Questions (U2)
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  type: multiple-choice-qa
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.4605263157894737
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  - task:
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  name: Analogy Questions (U4)
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  type: multiple-choice-qa
 
80
  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.5231481481481481
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  - task:
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  name: Lexical Relation Classification (BLESS)
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  type: classification
 
91
  metrics:
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  - name: F1
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  type: f1
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+ value: 0.9025161970769926
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.8979165451427438
98
  - task:
99
  name: Lexical Relation Classification (CogALexV)
100
  type: classification
 
105
  metrics:
106
  - name: F1
107
  type: f1
108
+ value: 0.8328638497652581
109
  - name: F1 (macro)
110
  type: f1_macro
111
+ value: 0.6469572777603673
112
  - task:
113
  name: Lexical Relation Classification (EVALution)
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  type: classification
 
119
  metrics:
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  - name: F1
121
  type: f1
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+ value: 0.6630552546045504
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.6493250582245075
126
  - task:
127
  name: Lexical Relation Classification (K&H+N)
128
  type: classification
 
133
  metrics:
134
  - name: F1
135
  type: f1
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+ value: 0.9562495652778744
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.8695137253747418
140
  - task:
141
  name: Lexical Relation Classification (ROOT09)
142
  type: classification
 
147
  metrics:
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  - name: F1
149
  type: f1
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+ value: 0.8906298965841429
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.8885946595123109
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155
  ---
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  # relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification
 
160
  Fine-tuning is done via [RelBERT](https://github.com/asahi417/relbert) library (see the repository for more detail).
161
  It achieves the following results on the relation understanding tasks:
162
  - Analogy Question ([dataset](https://huggingface.co/datasets/relbert/analogy_questions), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/analogy.json)):
163
+ - Accuracy on SAT (full): 0.5133689839572193
164
+ - Accuracy on SAT: 0.516320474777448
165
+ - Accuracy on BATS: 0.5958866036687048
166
+ - Accuracy on U2: 0.4605263157894737
167
+ - Accuracy on U4: 0.5231481481481481
168
+ - Accuracy on Google: 0.748
169
  - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/classification.json)):
170
+ - Micro F1 score on BLESS: 0.9025161970769926
171
+ - Micro F1 score on CogALexV: 0.8328638497652581
172
+ - Micro F1 score on EVALution: 0.6630552546045504
173
+ - Micro F1 score on K&H+N: 0.9562495652778744
174
+ - Micro F1 score on ROOT09: 0.8906298965841429
175
  - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/relation_mapping.json)):
176
+ - Accuracy on Relation Mapping: 0.7550595238095238
177
 
178
 
179
  ### Usage