Model: research-backup/relbert-roberta-base-semeval2012-v6-mask-prompt-c-nce-2
Author: research-backup
Pipeline: feature-extraction
Library: transformers
Tags: transformers, pytorch, roberta, feature-extraction, dataset:relbert/semeval2012_relational_similarity_v6, model-index, text-embeddings-inference, endpoints_compatible, region:us
Card metadata: datasets: relbert/semeval2012_relational_similarity_v6
model-index: name: relbert/relbert-roberta-base-semeval2012-v6-mask-prompt-c-nce-2
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: 0.5858333333333333
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: 0.3235294117647059
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: 0.3264094955489614
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: 0.40355753196220123
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: 0.454
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: 0.3991228070175439
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: 0.3680555555555556
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: 0.8927226156395962
verified: no, name: F1 (macro)
type: f1_macro
value: 0.8860530490594479
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: 0.7772300469483568
verified: no, name: F1 (macro)
type: f1_macro
value: 0.49603297373551636
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: 0.5910075839653305
verified: no, name: F1 (macro)
type: f1_macro
value: 0.5855884123582632
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: 0.9483897892467135
verified: no, name: F1 (macro)
type: f1_macro
value: 0.8589949863564919
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: 0.8614854277655907
verified: no, name: F1 (macro)
type: f1_macro
value: 0.8600976443012404
verified: no
Likes: 0 | All-time downloads: 280
Created: 2022-11-22 07:26:54