Model: quarkss/indobert-base-stsb
Author: quarkss
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:5749, loss:CosineSimilarityLoss, dataset:quarkss/stsb-indo-mt, arxiv:1908.10084, base_model:indobenchmark/indobert-base-p2, base_model:finetune:indobenchmark/indobert-base-p2, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: indobenchmark/indobert-base-p2
Card metadata: base_model: indobenchmark/indobert-base-p2
datasets: quarkss/stsb-indo-mt
library_name: sentence-transformers
metrics: pearson_cosine, spearman_cosine, pearson_manhattan, spearman_manhattan, pearson_euclidean, spearman_euclidean, pearson_dot, spearman_dot, pearson_max, spearman_max
pipeline_tag: sentence-similarity
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:5749, loss:CosineSimilarityLoss
widget: source_sentence: Dua ekor anjing berenang di kolam renang.
sentences: Anjing-anjing sedang berenang di kolam renang., Seekor binatang sedang berjalan di atas tanah., Seorang pria sedang menyeka pinggiran mangkuk., source_sentence: Seorang anak perempuan sedang mengiris mentega menjadi dua bagian.
sentences: Seorang wanita sedang mengiris tahu., Dua orang berkelahi., Seorang pria sedang menari., source_sentence: Seorang gadis sedang makan kue mangkuk.
sentences: Seorang pria sedang mengiris bawang putih dengan alat pengiris mandolin., Seorang pria sedang memotong dan memotong bawang., Seorang wanita sedang makan kue mangkuk., source_sentence: Sebuah helikopter mendarat di landasan helikopter.
sentences: Seorang pria sedang mengiris mentimun., Seorang pria sedang memotong batang pohon dengan kapak., Sebuah helikopter mendarat., source_sentence: Seorang pria sedang berjalan dengan seekor kuda.
sentences: Seorang pria sedang menuntun seekor kuda dengan tali kekang., Seorang pria sedang menembakkan pistol., Seorang wanita sedang memetik tomat.
model-index: name: SentenceTransformer based on indobenchmark/indobert-base-p2
results: task: type: semantic-similarity
name: Semantic Similarity
dataset: name: Unknown
type: unknown
metrics: type: pearson_cosine
value: 0.8577280779646681
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.8588776334781149
name: Spearman Cosine
verified: no, type: pearson_manhattan
value: 0.8315261521874587
name: Pearson Manhattan
verified: no, type: spearman_manhattan
value: 0.8355406849443783
name: Spearman Manhattan
verified: no, type: pearson_euclidean
value: 0.8318083198603524
name: Pearson Euclidean
verified: no, type: spearman_euclidean
value: 0.8359194889385243
name: Spearman Euclidean
verified: no, type: pearson_dot
value: 0.7767060276322824
name: Pearson Dot
verified: no, type: spearman_dot
value: 0.783607744137448
name: Spearman Dot
verified: no, type: pearson_max
value: 0.8577280779646681
name: Pearson Max
verified: no, type: spearman_max
value: 0.8588776334781149
name: Spearman Max
verified: no, type: pearson_cosine
value: 0.8122790124383042
name: Pearson Cosine
verified: no, type: spearman_cosine
value: 0.8123119892530147
name: Spearman Cosine
verified: no, type: pearson_manhattan
value: 0.7987643661729152
name: Pearson Manhattan
verified: no, type: spearman_manhattan
value: 0.7966661480553803
name: Spearman Manhattan
verified: no, type: pearson_euclidean
value: 0.7992882233155829
name: Pearson Euclidean
verified: no, type: spearman_euclidean
value: 0.797227936168015
name: Spearman Euclidean
verified: no, type: pearson_dot
value: 0.712195542080357
name: Pearson Dot
verified: no, type: spearman_dot
value: 0.7014898656834544
name: Spearman Dot
verified: no, type: pearson_max
value: 0.8122790124383042
name: Pearson Max
verified: no, type: spearman_max
value: 0.8123119892530147
name: Spearman Max
verified: no
Likes: 0 | All-time downloads: 172
Created: 2024-07-16 08:47:08