Model: blemond/0910a
Author: blemond
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, xlm-roberta, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:43318, loss:MultipleNegativesRankingLoss, arxiv:1908.10084, arxiv:1705.00652, base_model:intfloat/multilingual-e5-large, base_model:finetune:intfloat/multilingual-e5-large, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: intfloat/multilingual-e5-large
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:43318, loss:MultipleNegativesRankingLoss
base_model: intfloat/multilingual-e5-large
widget: source_sentence: query: 3PL 사용 시의 비용 절감 메커니즘은 어떤 것이 있나요?
sentences: passage: 3 Dimension-Through Silicon Via (Technical), passage: Third Party Logistics (상업), passage: Authorization Account Answer (Technical), source_sentence: query: How can ACE be utilized?
sentences: passage: Audio Connecting Equipment (Applicational), passage: Access Class-Barring (활용), passage: Abort Accept (기술), source_sentence: query: What makes the 1x RTT technology significant?
sentences: passage: Ab Wire Test (Conceptual), passage: CDMA2000 1x Radio Transmission Technology (Conceptual), passage: Authentication, Authorization, Accounting (기술), source_sentence: query: 2WPD의 전력 분배 방식은 어떻게 이루어지나요?
sentences: passage: Triple Digital Encryption Standard (기술), passage: Air Baffle (Conceptual), passage: 2 Way Power Divider (기술), source_sentence: query: 3D-TSV가 반도체 설계에 미치는 영향은 무엇인가요?
sentences: passage: Available Bit Rate (Applicational), passage: Average Bouncing Busy Hour (개념), passage: 3 Dimension-Through Silicon Via (기술)
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: cosine_accuracy@1, cosine_accuracy@3, cosine_accuracy@5, cosine_accuracy@10, cosine_precision@1, cosine_precision@3, cosine_precision@5, cosine_precision@10, cosine_recall@1, cosine_recall@3, cosine_recall@5, cosine_recall@10, cosine_ndcg@10, cosine_mrr@10, cosine_map@100
model-index: name: SentenceTransformer based on intfloat/multilingual-e5-large
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: e5 eval real
type: e5-eval-real
metrics: type: cosine_accuracy@1
value: 0.9683
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.9981
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.9997
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.9999
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.9683
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.3326999999999999
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.19994000000000006
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.09999000000000001
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.9683
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.9981
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.9997
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.9999
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.9873905751741222
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.9830366666666664
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.9830414285714285
name: Cosine Map@100
verified: no
Likes: 0 | All-time downloads: 305
Created: 2025-09-17 04:16:02