Model: research-backup/relbert-roberta-large-nce-b-semeval2012-t-rex
Author: research-backup
Pipeline: feature-extraction
Library: transformers
Tags: transformers, pytorch, roberta, feature-extraction, dataset:relbert/relational_similarity, model-index, text-embeddings-inference, endpoints_compatible, region:us
Card metadata: datasets: relbert/relational_similarity
model-index: name: relbert/relbert-roberta-large-nce-b-semeval2012-t-rex
results: task: name: Relation Mapping
type: sorting-task
dataset: name: Relation Mapping
args: relbert/relation_mapping
type: relation-mapping
metrics: name: Accuracy
type: accuracy
value: 0.8576190476190476
verified: no, task: name: Analogy Questions (SAT full)
type: multiple-choice-qa
dataset: name: SAT full
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.6203208556149733
verified: no, task: name: Analogy Questions (SAT)
type: multiple-choice-qa
dataset: name: SAT
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.6201780415430267
verified: no, task: name: Analogy Questions (BATS)
type: multiple-choice-qa
dataset: name: BATS
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.8015564202334631
verified: no, task: name: Analogy Questions (Google)
type: multiple-choice-qa
dataset: name: Google
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.928
verified: no, task: name: Analogy Questions (U2)
type: multiple-choice-qa
dataset: name: U2
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.5614035087719298
verified: no, task: name: Analogy Questions (U4)
type: multiple-choice-qa
dataset: name: U4
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.5555555555555556
verified: no, task: name: Analogy Questions (ConceptNet Analogy)
type: multiple-choice-qa
dataset: name: ConceptNet Analogy
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.375
verified: no, task: name: Analogy Questions (TREX Analogy)
type: multiple-choice-qa
dataset: name: TREX Analogy
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.726775956284153
verified: no, task: name: Analogy Questions (NELL-ONE Analogy)
type: multiple-choice-qa
dataset: name: NELL-ONE Analogy
args: relbert/analogy_questions
type: analogy-questions
metrics: name: Accuracy
type: accuracy
value: 0.7383333333333333
verified: no, task: name: Lexical Relation Classification (BLESS)
type: classification
dataset: name: BLESS
args: relbert/lexical_relation_classification
type: relation-classification
metrics: name: F1
type: f1
value: 0.9056802772336899
verified: no, name: F1 (macro)
type: f1_macro
value: 0.903141776537122
verified: no, task: name: Lexical Relation Classification (CogALexV)
type: classification
dataset: name: CogALexV
args: relbert/lexical_relation_classification
type: relation-classification
metrics: name: F1
type: f1
value: 0.8457746478873239
verified: no, name: F1 (macro)
type: f1_macro
value: 0.6705724590559077
verified: no, task: name: Lexical Relation Classification (EVALution)
type: classification
dataset: name: BLESS
args: relbert/lexical_relation_classification
type: relation-classification
metrics: name: F1
type: f1
value: 0.6587215601300108
verified: no, name: F1 (macro)
type: f1_macro
value: 0.638574336791404
verified: no, task: name: Lexical Relation Classification (K&H+N)
type: classification
dataset: name: K&H+N
args: relbert/lexical_relation_classification
type: relation-classification
metrics: name: F1
type: f1
value: 0.9488071224873061
verified: no, name: F1 (macro)
type: f1_macro
value: 0.85501872585967
verified: no, task: name: Lexical Relation Classification (ROOT09)
type: classification
dataset: name: ROOT09
args: relbert/lexical_relation_classification
type: relation-classification
metrics: name: F1
type: f1
value: 0.8903165151989971
verified: no, name: F1 (macro)
type: f1_macro
value: 0.8865181925574306
verified: no
Likes: 0 | All-time downloads: 254
Created: 2023-02-17 19:08:32