asahi417 commited on
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1 Parent(s): d9324eb

model update

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  1. README.md +14 -14
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
@@ -160,12 +160,12 @@ 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-prompt-e-nce/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-prompt-e-nce/raw/main/classification.json)):
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  - Micro F1 score on BLESS: None
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  - Micro F1 score on CogALexV: None
@@ -173,7 +173,7 @@ It achieves the following results on the relation understanding tasks:
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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-prompt-e-nce/raw/main/relation_mapping.json)):
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- - Accuracy on Relation Mapping: None
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  ### Usage
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8967261904761905
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  - task:
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  name: Analogy Questions (SAT full)
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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: 0.6256684491978609
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  - task:
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  name: Analogy Questions (SAT)
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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: 0.6379821958456974
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  - task:
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  name: Analogy Questions (BATS)
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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: 0.7354085603112841
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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: 0.882
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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: 0.6403508771929824
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  - task:
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  name: Analogy Questions (U4)
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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: 0.6273148148148148
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  - task:
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  name: Lexical Relation Classification (BLESS)
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  type: classification
 
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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-prompt-e-nce/raw/main/analogy.json)):
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+ - Accuracy on SAT (full): 0.6256684491978609
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+ - Accuracy on SAT: 0.6379821958456974
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+ - Accuracy on BATS: 0.7354085603112841
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+ - Accuracy on U2: 0.6403508771929824
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+ - Accuracy on U4: 0.6273148148148148
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+ - Accuracy on Google: 0.882
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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-prompt-e-nce/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 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-prompt-e-nce/raw/main/relation_mapping.json)):
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+ - Accuracy on Relation Mapping: 0.8967261904761905
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  ### Usage