Model: research-backup/roberta-large-semeval2012-average-no-mask-prompt-d-triplet
Author: research-backup
Pipeline: feature-extraction
Library: transformers
Tags: transformers, pytorch, roberta, feature-extraction, dataset:semeval2012, model-index, text-embeddings-inference, endpoints_compatible, region:us
Card metadata: datasets: semeval2012
model-index: name: relbert/roberta-large-semeval2012-average-no-mask-prompt-d-triplet
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: 0.815952380952381
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: 0.6951871658
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: 0.706231454
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: 0.7882156754
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: 0.924
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: 0.6622807018
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: 0.6527777778
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: 0.9153231881874341
verified: no, name: F1 (macro)
type: f1_macro
value: 0.9098445625290479
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: 0.8725352112676056
verified: no, name: F1 (macro)
type: f1_macro
value: 0.7174660438773314
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: 0.6944745395449621
verified: no, name: F1 (macro)
type: f1_macro
value: 0.688951875758847
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: 0.9689782291159491
verified: no, name: F1 (macro)
type: f1_macro
value: 0.90395779327521
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: 0.9050454403008461
verified: no, name: F1 (macro)
type: f1_macro
value: 0.9062415320017446
verified: no
Likes: 0 | All-time downloads: 318
Created: 2022-07-22 16:52:00