asahi417 commited on
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fddf19c
1 Parent(s): 5e835d9

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/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob
@@ -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).
161
  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/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob/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/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob/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/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob/raw/main/relation_mapping.json)):
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- - Accuracy on Relation Mapping: None
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  ### Usage
 
14
  metrics:
15
  - name: Accuracy
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  type: accuracy
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+ value: 0.9633333333333334
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  - 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: 0.6550802139037433
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  - task:
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  name: Analogy Questions (SAT)
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  type: multiple-choice-qa
 
36
  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.6528189910979229
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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: 0.8226792662590328
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  - task:
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  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: 0.936
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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: 0.6666666666666666
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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: 0.6712962962962963
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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: 0.9234593943046557
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.9180602208649703
98
  - task:
99
  name: Lexical Relation Classification (CogALexV)
100
  type: classification
 
105
  metrics:
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  - name: F1
107
  type: f1
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+ value: 0.8690140845070422
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  - name: F1 (macro)
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  type: f1_macro
111
+ value: 0.7117308070284601
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: 0.695557963163597
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.6823770398712694
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  - 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: 0.9635528969882451
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.8903933273008022
140
  - task:
141
  name: Lexical Relation Classification (ROOT09)
142
  type: classification
 
147
  metrics:
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  - name: F1
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  type: f1
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+ value: 0.9088060169225948
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.9056193124925707
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  ---
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  # relbert/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob
 
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/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob/raw/main/analogy.json)):
163
+ - Accuracy on SAT (full): 0.6550802139037433
164
+ - Accuracy on SAT: 0.6528189910979229
165
+ - Accuracy on BATS: 0.8226792662590328
166
+ - Accuracy on U2: 0.6666666666666666
167
+ - Accuracy on U4: 0.6712962962962963
168
+ - Accuracy on Google: 0.936
169
  - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob/raw/main/classification.json)):
170
+ - Micro F1 score on BLESS: 0.9234593943046557
171
+ - Micro F1 score on CogALexV: 0.8690140845070422
172
+ - Micro F1 score on EVALution: 0.695557963163597
173
+ - Micro F1 score on K&H+N: 0.9635528969882451
174
+ - Micro F1 score on ROOT09: 0.9088060169225948
175
  - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/relbert-roberta-large-semeval2012-average-no-mask-prompt-c-loob/raw/main/relation_mapping.json)):
176
+ - Accuracy on Relation Mapping: 0.9633333333333334
177
 
178
 
179
  ### Usage