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model update

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  1. README.md +9 -9
  2. relation_mapping.json +1 -0
README.md CHANGED
@@ -2,7 +2,7 @@
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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-mask-prompt-a-nce-classification
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  results:
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  - task:
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  name: Relation Mapping
@@ -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: 0.932936507936508
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  - task:
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  name: Analogy Questions (SAT full)
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  type: multiple-choice-qa
@@ -153,27 +153,27 @@ model-index:
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  value: 0.9103620381025954
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  ---
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- # relbert/roberta-large-semeval2012-mask-prompt-a-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-mask-prompt-a-nce-classification/raw/main/analogy.json)):
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  - Accuracy on SAT (full): 0.6149732620320856
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  - Accuracy on SAT: 0.6201780415430267
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  - Accuracy on BATS: 0.7137298499166204
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  - Accuracy on U2: 0.5570175438596491
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  - Accuracy on U4: 0.5972222222222222
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  - Accuracy on Google: 0.892
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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-mask-prompt-a-nce-classification/raw/main/classification.json)):
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  - Micro F1 score on BLESS: 0.9245140876902215
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  - Micro F1 score on CogALexV: 0.8748826291079812
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  - Micro F1 score on EVALution: 0.6966413867822319
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  - Micro F1 score on K&H+N: 0.9568755651387633
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  - Micro F1 score on ROOT09: 0.9122532121591977
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- - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-a-nce-classification/raw/main/relation_mapping.json)):
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- - Accuracy on Relation Mapping: 0.932936507936508
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  ### Usage
@@ -184,7 +184,7 @@ pip install relbert
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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-mask-prompt-a-nce-classification")
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  vector = model.get_embedding(['Tokyo', 'Japan']) # shape of (1024, )
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  ```
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@@ -216,7 +216,7 @@ The following hyperparameters were used during training:
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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-mask-prompt-a-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-mask-prompt-a-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: 0.8409126984126984
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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: 0.9103620381025954
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  ---
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+ # relbert/roberta-large-semeval2012-mask-prompt-a-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-mask-prompt-a-nce-classification-conceptnet-validated/raw/main/analogy.json)):
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  - Accuracy on SAT (full): 0.6149732620320856
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  - Accuracy on SAT: 0.6201780415430267
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  - Accuracy on BATS: 0.7137298499166204
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  - Accuracy on U2: 0.5570175438596491
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  - Accuracy on U4: 0.5972222222222222
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  - Accuracy on Google: 0.892
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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-mask-prompt-a-nce-classification-conceptnet-validated/raw/main/classification.json)):
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  - Micro F1 score on BLESS: 0.9245140876902215
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  - Micro F1 score on CogALexV: 0.8748826291079812
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  - Micro F1 score on EVALution: 0.6966413867822319
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  - Micro F1 score on K&H+N: 0.9568755651387633
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  - Micro F1 score on ROOT09: 0.9122532121591977
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+ - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-a-nce-classification-conceptnet-validated/raw/main/relation_mapping.json)):
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+ - Accuracy on Relation Mapping: 0.8409126984126984
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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-mask-prompt-a-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-mask-prompt-a-nce-classification-conceptnet-validated/raw/main/trainer_config.json).
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221
  ### Reference
222
  If you use any resource from RelBERT, please consider to cite our [paper](https://aclanthology.org/2021.eacl-demos.7/).
relation_mapping.json ADDED
@@ -0,0 +1 @@
 
 
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+ {"accuracy": 0.8409126984126984, "prediction": [{"source": ["solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity"], "true": ["atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism"], "pred": ["atom", "electron", "nucleus", "charge", "attracts", "revolves", "electromagnetism"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9999999006338451, "similarity_true": 0.9999999006338451}, {"source": ["water", "flows", "pressure", "water tower", "bucket", "filling", "emptying", "hydrodynamics"], "true": ["heat", "transfers", "temperature", "burner", "kettle", "heating", "cooling", "thermodynamics"], "pred": ["heat", "transfers", "temperature", "kettle", "burner", "heating", "cooling", "thermodynamics"], "alignment_match": false, "accuracy": 0.75, "similarity": 0.9699565847405514, "similarity_true": 0.9699565847405514}, {"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": 0.9687495715212839, "similarity_true": 0.9687495715212839}, {"source": ["combustion", "fire", "fuel", "burning", "hot", "intense", "oxygen", "carbon dioxide"], "true": ["respiration", "animal", "food", "breathing", "living", "vigorous", "oxygen", "carbon dioxide"], "pred": ["breathing", "respiration", "food", "living", "animal", "vigorous", "oxygen", "carbon dioxide"], "alignment_match": false, "accuracy": 0.5, "similarity": 0.9999999002893707, "similarity_true": 0.9999999002893707}, {"source": ["sound", "low", "high", "echoes", "loud", "quiet", "horn"], "true": ["light", "red", "violet", "reflects", "bright", "dim", "lens"], "pred": ["light", "violet", "red", "reflects", "bright", "dim", "lens"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9807006292690847, "similarity_true": 0.9807006292690847}, {"source": ["projectile", "trajectory", "earth", "parabolic", "air", "gravity", "attracts"], "true": ["planet", "orbit", "sun", "elliptical", "space", "gravity", "attracts"], "pred": ["planet", "orbit", "sun", "elliptical", "space", "gravity", "attracts"], "alignment_match": true, "accuracy": 1, "similarity": 0.999999900411965, "similarity_true": 0.999999900411965}, {"source": ["breeds", "selection", "conformance", "artificial", "popularity", "breeding", "domesticated"], "true": ["species", "competition", "adaptation", "natural", "fitness", "mating", "wild"], "pred": ["species", "competition", "adaptation", "natural", "fitness", "mating", "wild"], "alignment_match": true, "accuracy": 1, "similarity": 0.9338756286360113, "similarity_true": 0.9338756286360113}, {"source": ["ball", "billiards", "speed", "table", "bouncing", "moving", "slow", "fast"], "true": ["molecules", "gas", "temperature", "container", "pressing", "moving", "cold", "hot"], "pred": ["molecules", "gas", "temperature", "container", "pressing", "moving", "cold", "hot"], "alignment_match": true, "accuracy": 1, "similarity": 0.9696948398780945, "similarity_true": 0.9696948398780945}, {"source": ["computer", "processing", "erasing", "write", "read", "memory", "outputs", "inputs", "bug"], "true": ["mind", "thinking", "forgetting", "memorize", "remember", "memory", "muscles", "senses", "mistake"], "pred": ["mind", "thinking", "forgetting", "remember", "memorize", "memory", "muscles", "senses", "mistake"], "alignment_match": false, "accuracy": 0.7777777777777778, "similarity": 0.9658390018310581, "similarity_true": 0.9527935841585946}, {"source": ["slot machines", "reels", "spinning", "winning", "losing"], "true": ["bacteria", "genes", "mutating", "reproducing", "dying"], "pred": ["bacteria", "genes", "mutating", "reproducing", "dying"], "alignment_match": true, "accuracy": 1, "similarity": 0.9053004837364593, "similarity_true": 0.9053004837364593}, {"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": 0.943215638246518, "similarity_true": 0.943215638246518}, {"source": ["buyer", "merchandise", "buying", "selling", "returning", "valuable", "worthless"], "true": ["believer", "belief", "accepting", "advocating", "rejecting", "true", "false"], "pred": ["believer", "belief", "accepting", "rejecting", "advocating", "true", "false"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.94883418455052, "similarity_true": 0.9468818428298434}, {"source": ["foundations", "buildings", "supporting", "solid", "weak", "crack"], "true": ["reasons", "theories", "confirming", "rational", "dubious", "flaw"], "pred": ["reasons", "theories", "confirming", "rational", "dubious", "flaw"], "alignment_match": true, "accuracy": 1, "similarity": 0.9559462173948704, "similarity_true": 0.9559462173948704}, {"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": 0.9226653159149564, "similarity_true": 0.9226653159149564}, {"source": ["money", "allocate", "budget", "effective", "cheap", "expansive"], "true": ["time", "invest", "schedule", "efficient", "quick", "slow"], "pred": ["time", "invest", "schedule", "efficient", "slow", "quick"], "alignment_match": false, "accuracy": 0.6666666666666666, "similarity": 0.9679066425869014, "similarity_true": 0.9550753869894802}, {"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": 0.9636833724321173, "similarity_true": 0.9636833724321173}, {"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": 0.965494782888032, "similarity_true": 0.965494782888032}, {"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": 0.9573161795870536, "similarity_true": 0.9573161795870536}, {"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": 0.9629473184303895, "similarity_true": 0.9629473184303895}, {"source": ["seeing", "light", "illuminating", "darkness", "view", "hidden"], "true": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"], "pred": ["explaining", "knowledge", "understanding", "confusion", "interpretation", "secret"], "alignment_match": false, "accuracy": 0.6666666666666666, "similarity": 0.9065766797824919, "similarity_true": 0.8963958652392428}]}