model update
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- relation_mapping.json +1 -0
README.md
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datasets:
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- relbert/semeval2012_relational_similarity
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model-index:
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- name: relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification
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results:
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- task:
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name: 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.
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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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value: 0.8885946595123109
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---
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# relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification
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RelBERT fine-tuned from [roberta-large](https://huggingface.co/roberta-large) on
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[relbert/semeval2012_relational_similarity](https://huggingface.co/datasets/relbert/semeval2012_relational_similarity).
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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): 0.5133689839572193
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- Accuracy on SAT: 0.516320474777448
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- Accuracy on BATS: 0.5958866036687048
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- Accuracy on U2: 0.4605263157894737
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- Accuracy on U4: 0.5231481481481481
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- Accuracy on Google: 0.748
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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: 0.9025161970769926
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- Micro F1 score on CogALexV: 0.8328638497652581
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- Micro F1 score on EVALution: 0.6630552546045504
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- Micro F1 score on K&H+N: 0.9562495652778744
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- Micro F1 score on ROOT09: 0.8906298965841429
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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: 0.
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### Usage
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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/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification")
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vector = model.get_embedding(['Tokyo', 'Japan']) # shape of (1024, )
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```
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- n_sample: 640
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- gradient_accumulation: 8
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The full configuration can be found at [fine-tuning parameter file](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification/raw/main/trainer_config.json).
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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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datasets:
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- relbert/semeval2012_relational_similarity
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model-index:
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- name: relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification-conceptnet-validated
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results:
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- task:
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name: Relation Mapping
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7637698412698413
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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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value: 0.8885946595123109
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---
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# relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification-conceptnet-validated
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RelBERT fine-tuned from [roberta-large](https://huggingface.co/roberta-large) on
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[relbert/semeval2012_relational_similarity](https://huggingface.co/datasets/relbert/semeval2012_relational_similarity).
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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-conceptnet-validated/raw/main/analogy.json)):
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- Accuracy on SAT (full): 0.5133689839572193
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- Accuracy on SAT: 0.516320474777448
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- Accuracy on BATS: 0.5958866036687048
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- Accuracy on U2: 0.4605263157894737
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- Accuracy on U4: 0.5231481481481481
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- Accuracy on Google: 0.748
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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-conceptnet-validated/raw/main/classification.json)):
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- Micro F1 score on BLESS: 0.9025161970769926
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- Micro F1 score on CogALexV: 0.8328638497652581
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- Micro F1 score on EVALution: 0.6630552546045504
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- Micro F1 score on K&H+N: 0.9562495652778744
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- Micro F1 score on ROOT09: 0.8906298965841429
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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-conceptnet-validated/raw/main/relation_mapping.json)):
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- Accuracy on Relation Mapping: 0.7637698412698413
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### Usage
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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/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification-conceptnet-validated")
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vector = model.get_embedding(['Tokyo', 'Japan']) # shape of (1024, )
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```
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- n_sample: 640
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- gradient_accumulation: 8
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The full configuration can be found at [fine-tuning parameter file](https://huggingface.co/relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-classification-conceptnet-validated/raw/main/trainer_config.json).
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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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relation_mapping.json
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{"accuracy": 0.7637698412698413, "prediction": [{"source": ["solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity"], "true": ["atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism"], "pred": ["atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism"], "alignment_match": true, "accuracy": 1, "similarity": 0.999999999806734, "similarity_true": 0.999999999806734}, {"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": 0.9639594292257277, "similarity_true": 0.9639594292257277}, {"source": ["waves", "shore", "reflects", "water", "breakwater", "rough", "calm", "crashing"], "true": ["sounds", "wall", "echoes", "air", "insulation", "loud", "quiet", "vibrating"], "pred": ["sounds", "wall", "echoes", "air", "insulation", "loud", "quiet", "vibrating"], "alignment_match": true, "accuracy": 1, "similarity": 0.8934108385956929, "similarity_true": 0.8934108385956929}, {"source": ["combustion", "fire", "fuel", "burning", "hot", "intense", "oxygen", "carbon dioxide"], "true": ["respiration", "animal", "food", "breathing", "living", "vigorous", "oxygen", "carbon dioxide"], "pred": ["respiration", "animal", "food", "breathing", "living", "vigorous", "oxygen", "carbon dioxide"], "alignment_match": true, "accuracy": 1, "similarity": 0.9999999998052076, "similarity_true": 0.9999999998052076}, {"source": ["sound", "low", "high", "echoes", "loud", "quiet", "horn"], "true": ["light", "red", "violet", "reflects", "bright", "dim", "lens"], "pred": ["light", "bright", "red", "reflects", "dim", "violet", "lens"], "alignment_match": false, "accuracy": 0.42857142857142855, "similarity": 0.931271210323597, "similarity_true": 0.9272962916448915}, {"source": ["projectile", "trajectory", "earth", "parabolic", "air", "gravity", "attracts"], "true": ["planet", "orbit", "sun", "elliptical", "space", "gravity", "attracts"], "pred": ["sun", "orbit", "planet", "elliptical", "space", "gravity", "attracts"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9999999997817971, "similarity_true": 0.9999999997817971}, {"source": ["breeds", "selection", "conformance", "artificial", "popularity", "breeding", "domesticated"], "true": ["species", "competition", "adaptation", "natural", "fitness", "mating", "wild"], "pred": ["species", "adaptation", "fitness", "natural", "competition", "mating", "wild"], "alignment_match": false, "accuracy": 0.5714285714285714, "similarity": 0.9028503246617249, "similarity_true": 0.8924045879804939}, {"source": ["ball", "billiards", "speed", "table", "bouncing", "moving", "slow", "fast"], "true": ["molecules", "gas", "temperature", "container", "pressing", "moving", "cold", "hot"], "pred": ["gas", "molecules", "temperature", "container", "pressing", "moving", "cold", "hot"], "alignment_match": false, "accuracy": 0.75, "similarity": 0.9452767458664261, "similarity_true": 0.9452767458664261}, {"source": ["computer", "processing", "erasing", "write", "read", "memory", "outputs", "inputs", "bug"], "true": ["mind", "thinking", "forgetting", "memorize", "remember", "memory", "muscles", "senses", "mistake"], "pred": ["mind", "thinking", "forgetting", "memorize", "remember", "memory", "senses", "muscles", "mistake"], "alignment_match": false, "accuracy": 0.7777777777777778, "similarity": 0.8903844256635752, "similarity_true": 0.8903844256635752}, {"source": ["slot machines", "reels", "spinning", "winning", "losing"], "true": ["bacteria", "genes", "mutating", "reproducing", "dying"], "pred": ["bacteria", "genes", "mutating", "dying", "reproducing"], "alignment_match": false, "accuracy": 0.6, "similarity": 0.8874331552976258, "similarity_true": 0.8869484981035648}, {"source": ["war", "soldier", "destroy", "fighting", "defeat", "attacks", "weapon"], "true": ["argument", "debater", "refute", "arguing", "acceptance", "criticizes", "logic"], "pred": ["logic", "debater", "refute", "arguing", "acceptance", "criticizes", "argument"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.8813501529914167, "similarity_true": 0.8813501529914167}, {"source": ["buyer", "merchandise", "buying", "selling", "returning", "valuable", "worthless"], "true": ["believer", "belief", "accepting", "advocating", "rejecting", "true", "false"], "pred": ["believer", "belief", "advocating", "rejecting", "accepting", "true", "false"], "alignment_match": false, "accuracy": 0.5714285714285714, "similarity": 0.8800199339587258, "similarity_true": 0.8800199339587258}, {"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": 0.8847022242564093, "similarity_true": 0.8847022242564093}, {"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": 0.8509583232289993, "similarity_true": 0.8509583232289993}, {"source": ["money", "allocate", "budget", "effective", "cheap", "expansive"], "true": ["time", "invest", "schedule", "efficient", "quick", "slow"], "pred": ["time", "invest", "schedule", "quick", "efficient", "slow"], "alignment_match": false, "accuracy": 0.6666666666666666, "similarity": 0.9358579932911557, "similarity_true": 0.9270276082844308}, {"source": ["seeds", "planted", "fruitful", "fruit", "grow", "wither", "blossom"], "true": ["ideas", "inspired", "productive", "product", "develop", "fail", "succeed"], "pred": ["ideas", "inspired", "productive", "product", "succeed", "fail", "develop"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9168286231457263, "similarity_true": 0.9051934505112551}, {"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": 0.8336174802085505, "similarity_true": 0.8336174802085505}, {"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": 0.8351602353464301, "similarity_true": 0.8351602353464301}, {"source": ["follow", "leader", "path", "follower", "lost", "wanders", "twisted", "straight"], "true": ["understand", "speaker", "argument", "listener", "misunderstood", "digresses", "complicated", "simple"], "pred": ["speaker", "listener", "argument", "complicated", "misunderstood", "digresses", "understand", "simple"], "alignment_match": false, "accuracy": 0.5, "similarity": 0.9002186536342802, "similarity_true": 0.8918285277114261}, {"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": 0.8778624406629346, "similarity_true": 0.8778624406629346}]}
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