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model update

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README.md ADDED
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+ ---
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+ datasets:
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+ - relbert/semeval2012_relational_similarity_v6
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+ model-index:
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+ - name: relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical
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+ results:
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+ - task:
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+ name: Relation Mapping
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+ type: sorting-task
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+ dataset:
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+ name: Relation Mapping
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+ args: relbert/relation_mapping
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+ type: relation-mapping
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8518253968253968
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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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+ dataset:
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+ name: SAT full
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+ args: relbert/analogy_questions
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+ type: analogy-questions
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.4679144385026738
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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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+ dataset:
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+ name: SAT
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+ args: relbert/analogy_questions
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+ type: analogy-questions
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.4688427299703264
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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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+ dataset:
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+ name: BATS
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+ args: relbert/analogy_questions
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+ type: analogy-questions
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7204002223457476
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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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+ dataset:
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+ name: Google
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+ args: relbert/analogy_questions
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+ type: analogy-questions
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.85
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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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+ dataset:
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+ name: U2
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+ args: relbert/analogy_questions
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+ type: analogy-questions
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.39473684210526316
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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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+ dataset:
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+ name: U4
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+ args: relbert/analogy_questions
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+ type: analogy-questions
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.48842592592592593
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+ - task:
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+ name: Lexical Relation Classification (BLESS)
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+ type: classification
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+ dataset:
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+ name: BLESS
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+ args: relbert/lexical_relation_classification
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+ type: relation-classification
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.9138164833509116
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+ - name: F1 (macro)
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+ type: f1_macro
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+ value: 0.9081465241563919
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+ - task:
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+ name: Lexical Relation Classification (CogALexV)
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+ type: classification
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+ dataset:
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+ name: CogALexV
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+ args: relbert/lexical_relation_classification
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+ type: relation-classification
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.8429577464788731
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+ - name: F1 (macro)
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+ type: f1_macro
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+ value: 0.6602643050400394
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+ - task:
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+ name: Lexical Relation Classification (EVALution)
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+ type: classification
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+ dataset:
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+ name: BLESS
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+ args: relbert/lexical_relation_classification
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+ type: relation-classification
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.6500541711809318
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+ - name: F1 (macro)
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+ type: f1_macro
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+ value: 0.6453765088165551
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+ - task:
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+ name: Lexical Relation Classification (K&H+N)
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+ type: classification
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+ dataset:
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+ name: K&H+N
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+ args: relbert/lexical_relation_classification
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+ type: relation-classification
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.9563886763580719
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+ - name: F1 (macro)
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+ type: f1_macro
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+ value: 0.8746878565965688
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+ - task:
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+ name: Lexical Relation Classification (ROOT09)
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+ type: classification
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+ dataset:
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+ name: ROOT09
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+ args: relbert/lexical_relation_classification
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+ type: relation-classification
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.8921968035098715
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+ - name: F1 (macro)
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+ type: f1_macro
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+ value: 0.8885486080562698
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+
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+ ---
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+ # relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical
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+
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+ RelBERT fine-tuned from [roberta-base](https://huggingface.co/roberta-base) on
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+ [relbert/semeval2012_relational_similarity_v6](https://huggingface.co/datasets/relbert/semeval2012_relational_similarity_v6).
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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/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical/raw/main/analogy.json)):
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+ - Accuracy on SAT (full): 0.4679144385026738
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+ - Accuracy on SAT: 0.4688427299703264
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+ - Accuracy on BATS: 0.7204002223457476
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+ - Accuracy on U2: 0.39473684210526316
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+ - Accuracy on U4: 0.48842592592592593
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+ - Accuracy on Google: 0.85
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+ - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical/raw/main/classification.json)):
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+ - Micro F1 score on BLESS: 0.9138164833509116
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+ - Micro F1 score on CogALexV: 0.8429577464788731
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+ - Micro F1 score on EVALution: 0.6500541711809318
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+ - Micro F1 score on K&H+N: 0.9563886763580719
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+ - Micro F1 score on ROOT09: 0.8921968035098715
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+ - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical/raw/main/relation_mapping.json)):
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+ - Accuracy on Relation Mapping: 0.8518253968253968
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+
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+
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+ ### Usage
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+ This model can be used through the [relbert library](https://github.com/asahi417/relbert). Install the library via pip
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+ ```shell
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+ pip install relbert
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+ ```
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+ and activate model as below.
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+ ```python
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+ from relbert import RelBERT
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+ model = RelBERT("relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical")
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+ vector = model.get_embedding(['Tokyo', 'Japan']) # shape of (1024, )
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+ ```
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - model: roberta-base
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+ - max_length: 64
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+ - mode: mask
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+ - data: relbert/semeval2012_relational_similarity_v6
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+ - split: train
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+ - split_eval: validation
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+ - template_mode: manual
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+ - loss_function: nce_logout
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+ - classification_loss: False
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+ - temperature_nce_constant: 0.05
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+ - temperature_nce_rank: {'min': 0.01, 'max': 0.05, 'type': 'linear'}
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+ - epoch: 8
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+ - batch: 128
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+ - lr: 5e-06
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+ - lr_decay: False
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+ - lr_warmup: 1
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+ - weight_decay: 0
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+ - random_seed: 0
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+ - exclude_relation: None
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+ - n_sample: 320
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+ - gradient_accumulation: 8
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+ - relation_level: None
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+ - data_level: child_prototypical
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+
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+ The full configuration can be found at [fine-tuning parameter file](https://huggingface.co/relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-b-nce-0-child-prototypical/raw/main/trainer_config.json).
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+
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+ ### Reference
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+ If you use any resource from RelBERT, please consider to cite our [paper](https://aclanthology.org/2021.eacl-demos.7/).
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+
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+ ```
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+
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+ @inproceedings{ushio-etal-2021-distilling-relation-embeddings,
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+ title = "{D}istilling {R}elation {E}mbeddings from {P}re-trained {L}anguage {M}odels",
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+ author = "Ushio, Asahi and
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+ Schockaert, Steven and
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+ Camacho-Collados, Jose",
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+ booktitle = "EMNLP 2021",
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+ year = "2021",
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+ address = "Online",
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+ publisher = "Association for Computational Linguistics",
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+ }
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+
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+ ```
analogy.json ADDED
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+ {"distance_function": "cosine_similarity", "sat/test": 0.4688427299703264, "sat/valid": 0.4594594594594595, "u2/test": 0.39473684210526316, "u2/valid": 0.375, "u4/test": 0.48842592592592593, "u4/valid": 0.4583333333333333, "google/test": 0.85, "google/valid": 0.9, "bats/test": 0.7204002223457476, "bats/valid": 0.7487437185929648, "sat_full": 0.4679144385026738}
classification.json ADDED
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+ {"lexical_relation_classification/BLESS": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.9138164833509116, "test/f1_macro": 0.9081465241563919, "test/f1_micro": 0.9138164833509116, "test/p_macro": 0.9081264819628446, "test/p_micro": 0.9138164833509116, "test/r_macro": 0.9086472654852402, "test/r_micro": 0.9138164833509116}, "lexical_relation_classification/CogALexV": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.8429577464788732, "test/f1_macro": 0.6602643050400394, "test/f1_micro": 0.8429577464788731, "test/p_macro": 0.6918108068181256, "test/p_micro": 0.8429577464788732, "test/r_macro": 0.6366330120771996, "test/r_micro": 0.8429577464788732}, "lexical_relation_classification/EVALution": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.6500541711809318, "test/f1_macro": 0.6453765088165551, "test/f1_micro": 0.6500541711809318, "test/p_macro": 0.6566393060903872, "test/p_micro": 0.6500541711809318, "test/r_macro": 0.6420851983369568, "test/r_micro": 0.6500541711809318}, "lexical_relation_classification/K&H+N": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.9563886763580719, "test/f1_macro": 0.8746878565965688, "test/f1_micro": 0.9563886763580719, "test/p_macro": 0.8902991066461602, "test/p_micro": 0.9563886763580719, "test/r_macro": 0.8626095096779203, "test/r_micro": 0.9563886763580719}, "lexical_relation_classification/ROOT09": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.8921968035098715, "test/f1_macro": 0.8885486080562698, "test/f1_micro": 0.8921968035098715, "test/p_macro": 0.8892467034481256, "test/p_micro": 0.8921968035098715, "test/r_macro": 0.8889553514188181, "test/r_micro": 0.8921968035098715}}
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relation_mapping.json ADDED
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+ {"accuracy": 0.8518253968253968, "prediction": [{"source": ["solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity"], "true": ["atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism"], "pred": ["nucleus", "electron", "atom", "charge", "attracts", "revolves", "electromagnetism"], "alignment_match": false, "accuracy": 0.5714285714285714, "similarity": 0.9157185269611691, "similarity_true": 0.9079788403612111}, {"source": ["water", "flows", "pressure", "water tower", "bucket", "filling", "emptying", "hydrodynamics"], "true": ["heat", "transfers", "temperature", "burner", "kettle", "heating", "cooling", "thermodynamics"], "pred": ["heat", "transfers", "temperature", "burner", "kettle", "heating", "cooling", "thermodynamics"], "alignment_match": true, "accuracy": 1, "similarity": 0.8502064218862899, "similarity_true": 0.8502064218862899}, {"source": ["waves", "shore", "reflects", "water", "breakwater", "rough", "calm", "crashing"], "true": 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"similarity_true": 0.7694393850521096}, {"source": ["war", "soldier", "destroy", "fighting", "defeat", "attacks", "weapon"], "true": ["argument", "debater", "refute", "arguing", "acceptance", "criticizes", "logic"], "pred": ["argument", "debater", "refute", "arguing", "acceptance", "criticizes", "logic"], "alignment_match": true, "accuracy": 1, "similarity": 0.8307318898839068, "similarity_true": 0.8307318898839068}, {"source": ["buyer", "merchandise", "buying", "selling", "returning", "valuable", "worthless"], "true": ["believer", "belief", "accepting", "advocating", "rejecting", "true", "false"], "pred": ["believer", "belief", "accepting", "advocating", "rejecting", "true", "false"], "alignment_match": true, "accuracy": 1, "similarity": 0.7779148131797036, "similarity_true": 0.7779148131797036}, {"source": ["foundations", "buildings", "supporting", "solid", "weak", "crack"], "true": ["reasons", "theories", "confirming", "rational", "dubious", "flaw"], "pred": ["theories", "reasons", "confirming", "rational", "dubious", "flaw"], "alignment_match": false, "accuracy": 0.6666666666666666, "similarity": 0.7843681687740658, "similarity_true": 0.7730991581607511}, {"source": ["obstructions", "destination", "route", "traveller", "traveling", "companion", "arriving"], "true": ["difficulties", "goal", "plan", "person", "problem solving", "partner", "succeeding"], "pred": ["difficulties", "goal", "plan", "person", "problem solving", "partner", "succeeding"], "alignment_match": true, "accuracy": 1, "similarity": 0.834965126127087, "similarity_true": 0.834965126127087}, {"source": ["money", "allocate", "budget", "effective", "cheap", "expansive"], "true": ["time", "invest", "schedule", "efficient", "quick", "slow"], "pred": ["time", "invest", "schedule", "efficient", "quick", "slow"], "alignment_match": true, "accuracy": 1, "similarity": 0.8263918676540627, "similarity_true": 0.8263918676540627}, {"source": ["seeds", "planted", "fruitful", "fruit", "grow", "wither", "blossom"], "true": ["ideas", "inspired", "productive", "product", "develop", "fail", "succeed"], "pred": ["ideas", "inspired", "productive", "product", "develop", "fail", "succeed"], "alignment_match": true, "accuracy": 1, "similarity": 0.8320528993707552, "similarity_true": 0.8320528993707552}, {"source": ["machine", "working", "turned on", "turned off", "broken", "power", "repair"], "true": ["mind", "thinking", "awake", "asleep", "confused", "intelligence", "therapy"], "pred": ["mind", "thinking", "awake", "asleep", "confused", "intelligence", "therapy"], "alignment_match": true, "accuracy": 1, "similarity": 0.7787864437693168, "similarity_true": 0.7787864437693168}, {"source": ["object", "hold", "weight", "heavy", "light"], "true": ["idea", "understand", "analyze", "important", "trivial"], "pred": ["idea", "analyze", "understand", "important", "trivial"], "alignment_match": false, "accuracy": 0.6, "similarity": 0.7721402088163256, "similarity_true": 0.7667976027040252}, {"source": ["follow", "leader", "path", "follower", "lost", "wanders", "twisted", "straight"], "true": ["understand", "speaker", "argument", "listener", "misunderstood", "digresses", "complicated", "simple"], "pred": ["understand", "speaker", "argument", "listener", "misunderstood", "digresses", "complicated", "simple"], "alignment_match": true, "accuracy": 1, "similarity": 0.8205316109348595, "similarity_true": 0.8205316109348595}, {"source": ["seeing", "light", "illuminating", "darkness", "view", "hidden"], "true": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"], "pred": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"], "alignment_match": true, "accuracy": 1, "similarity": 0.8097120780372777, "similarity_true": 0.8097120780372777}]}
tokenizer_config.json CHANGED
@@ -6,7 +6,7 @@
6
  "errors": "replace",
7
  "mask_token": "<mask>",
8
  "model_max_length": 512,
9
- "name_or_path": "relbert_output/models/semeval2012-v6-child_prototypical/nce_logout.mask.b.0",
10
  "pad_token": "<pad>",
11
  "sep_token": "</s>",
12
  "special_tokens_map_file": null,
 
6
  "errors": "replace",
7
  "mask_token": "<mask>",
8
  "model_max_length": 512,
9
+ "name_or_path": "roberta-base",
10
  "pad_token": "<pad>",
11
  "sep_token": "</s>",
12
  "special_tokens_map_file": null,
trainer_config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"model": "roberta-base", "max_length": 64, "mode": "mask", "data": "relbert/semeval2012_relational_similarity_v6", "split": "train", "split_eval": "validation", "template_mode": "manual", "template": "Today, I finally discovered the relation between <subj> and <obj> : <obj> is <subj>'s <mask>", "loss_function": "nce_logout", "classification_loss": false, "temperature_nce_constant": 0.05, "temperature_nce_rank": {"min": 0.01, "max": 0.05, "type": "linear"}, "epoch": 8, "batch": 128, "lr": 5e-06, "lr_decay": false, "lr_warmup": 1, "weight_decay": 0, "random_seed": 0, "exclude_relation": null, "n_sample": 320, "gradient_accumulation": 8, "relation_level": null, "data_level": "child_prototypical"}
validation_loss.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"split": "validation", "loss": 6.010371333456295, "data": "relbert/semeval2012_relational_similarity_v6", "exclude_relation": null, "relation_level": null, "level": "child_prototypical"}