metadata
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: Dmeta-embedding
results:
- task:
type: STS
dataset:
type: C-MTEB/AFQMC
name: MTEB AFQMC
config: default
split: validation
revision: None
metrics:
- type: cos_sim_pearson
value: 65.60825224706932
- type: cos_sim_spearman
value: 71.12862586297193
- type: euclidean_pearson
value: 70.18130275750404
- type: euclidean_spearman
value: 71.12862586297193
- type: manhattan_pearson
value: 70.14470398075396
- type: manhattan_spearman
value: 71.05226975911737
- task:
type: STS
dataset:
type: C-MTEB/ATEC
name: MTEB ATEC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 65.52386345655479
- type: cos_sim_spearman
value: 64.64245253181382
- type: euclidean_pearson
value: 73.20157662981914
- type: euclidean_spearman
value: 64.64245253178956
- type: manhattan_pearson
value: 73.22837571756348
- type: manhattan_spearman
value: 64.62632334391418
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 44.925999999999995
- type: f1
value: 42.82555191308971
- task:
type: STS
dataset:
type: C-MTEB/BQ
name: MTEB BQ
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 71.35236446393156
- type: cos_sim_spearman
value: 72.29629643702184
- type: euclidean_pearson
value: 70.94570179874498
- type: euclidean_spearman
value: 72.29629297226953
- type: manhattan_pearson
value: 70.84463025501125
- type: manhattan_spearman
value: 72.24527021975821
- task:
type: Clustering
dataset:
type: C-MTEB/CLSClusteringP2P
name: MTEB CLSClusteringP2P
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 40.24232916894152
- task:
type: Clustering
dataset:
type: C-MTEB/CLSClusteringS2S
name: MTEB CLSClusteringS2S
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 39.167806226929706
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv1-reranking
name: MTEB CMedQAv1
config: default
split: test
revision: None
metrics:
- type: map
value: 88.48837920106357
- type: mrr
value: 90.36861111111111
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv2-reranking
name: MTEB CMedQAv2
config: default
split: test
revision: None
metrics:
- type: map
value: 89.17878171657071
- type: mrr
value: 91.35805555555555
- task:
type: Retrieval
dataset:
type: C-MTEB/CmedqaRetrieval
name: MTEB CmedqaRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 25.751
- type: map_at_10
value: 38.946
- type: map_at_100
value: 40.855000000000004
- type: map_at_1000
value: 40.953
- type: map_at_3
value: 34.533
- type: map_at_5
value: 36.905
- type: mrr_at_1
value: 39.235
- type: mrr_at_10
value: 47.713
- type: mrr_at_100
value: 48.71
- type: mrr_at_1000
value: 48.747
- type: mrr_at_3
value: 45.086
- type: mrr_at_5
value: 46.498
- type: ndcg_at_1
value: 39.235
- type: ndcg_at_10
value: 45.831
- type: ndcg_at_100
value: 53.162
- type: ndcg_at_1000
value: 54.800000000000004
- type: ndcg_at_3
value: 40.188
- type: ndcg_at_5
value: 42.387
- type: precision_at_1
value: 39.235
- type: precision_at_10
value: 10.273
- type: precision_at_100
value: 1.627
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 22.772000000000002
- type: precision_at_5
value: 16.524
- type: recall_at_1
value: 25.751
- type: recall_at_10
value: 57.411
- type: recall_at_100
value: 87.44
- type: recall_at_1000
value: 98.386
- type: recall_at_3
value: 40.416000000000004
- type: recall_at_5
value: 47.238
- task:
type: PairClassification
dataset:
type: C-MTEB/CMNLI
name: MTEB Cmnli
config: default
split: validation
revision: None
metrics:
- type: cos_sim_accuracy
value: 83.59591100420926
- type: cos_sim_ap
value: 90.65538153970263
- type: cos_sim_f1
value: 84.76466651795673
- type: cos_sim_precision
value: 81.04073363190446
- type: cos_sim_recall
value: 88.84732288987608
- type: dot_accuracy
value: 83.59591100420926
- type: dot_ap
value: 90.64355541781003
- type: dot_f1
value: 84.76466651795673
- type: dot_precision
value: 81.04073363190446
- type: dot_recall
value: 88.84732288987608
- type: euclidean_accuracy
value: 83.59591100420926
- type: euclidean_ap
value: 90.6547878194287
- type: euclidean_f1
value: 84.76466651795673
- type: euclidean_precision
value: 81.04073363190446
- type: euclidean_recall
value: 88.84732288987608
- type: manhattan_accuracy
value: 83.51172579675286
- type: manhattan_ap
value: 90.59941589844144
- type: manhattan_f1
value: 84.51827242524917
- type: manhattan_precision
value: 80.28613507258574
- type: manhattan_recall
value: 89.22141688099134
- type: max_accuracy
value: 83.59591100420926
- type: max_ap
value: 90.65538153970263
- type: max_f1
value: 84.76466651795673
- task:
type: Retrieval
dataset:
type: C-MTEB/CovidRetrieval
name: MTEB CovidRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 63.251000000000005
- type: map_at_10
value: 72.442
- type: map_at_100
value: 72.79299999999999
- type: map_at_1000
value: 72.80499999999999
- type: map_at_3
value: 70.293
- type: map_at_5
value: 71.571
- type: mrr_at_1
value: 63.541000000000004
- type: mrr_at_10
value: 72.502
- type: mrr_at_100
value: 72.846
- type: mrr_at_1000
value: 72.858
- type: mrr_at_3
value: 70.39
- type: mrr_at_5
value: 71.654
- type: ndcg_at_1
value: 63.541000000000004
- type: ndcg_at_10
value: 76.774
- type: ndcg_at_100
value: 78.389
- type: ndcg_at_1000
value: 78.678
- type: ndcg_at_3
value: 72.47
- type: ndcg_at_5
value: 74.748
- type: precision_at_1
value: 63.541000000000004
- type: precision_at_10
value: 9.115
- type: precision_at_100
value: 0.9860000000000001
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 26.379
- type: precision_at_5
value: 16.965
- type: recall_at_1
value: 63.251000000000005
- type: recall_at_10
value: 90.253
- type: recall_at_100
value: 97.576
- type: recall_at_1000
value: 99.789
- type: recall_at_3
value: 78.635
- type: recall_at_5
value: 84.141
- task:
type: Retrieval
dataset:
type: C-MTEB/DuRetrieval
name: MTEB DuRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.597
- type: map_at_10
value: 72.411
- type: map_at_100
value: 75.58500000000001
- type: map_at_1000
value: 75.64800000000001
- type: map_at_3
value: 49.61
- type: map_at_5
value: 62.527
- type: mrr_at_1
value: 84.65
- type: mrr_at_10
value: 89.43900000000001
- type: mrr_at_100
value: 89.525
- type: mrr_at_1000
value: 89.529
- type: mrr_at_3
value: 89
- type: mrr_at_5
value: 89.297
- type: ndcg_at_1
value: 84.65
- type: ndcg_at_10
value: 81.47
- type: ndcg_at_100
value: 85.198
- type: ndcg_at_1000
value: 85.828
- type: ndcg_at_3
value: 79.809
- type: ndcg_at_5
value: 78.55
- type: precision_at_1
value: 84.65
- type: precision_at_10
value: 39.595
- type: precision_at_100
value: 4.707
- type: precision_at_1000
value: 0.485
- type: precision_at_3
value: 71.61699999999999
- type: precision_at_5
value: 60.45
- type: recall_at_1
value: 23.597
- type: recall_at_10
value: 83.34
- type: recall_at_100
value: 95.19800000000001
- type: recall_at_1000
value: 98.509
- type: recall_at_3
value: 52.744
- type: recall_at_5
value: 68.411
- task:
type: Retrieval
dataset:
type: C-MTEB/EcomRetrieval
name: MTEB EcomRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 53.1
- type: map_at_10
value: 63.359
- type: map_at_100
value: 63.9
- type: map_at_1000
value: 63.909000000000006
- type: map_at_3
value: 60.95
- type: map_at_5
value: 62.305
- type: mrr_at_1
value: 53.1
- type: mrr_at_10
value: 63.359
- type: mrr_at_100
value: 63.9
- type: mrr_at_1000
value: 63.909000000000006
- type: mrr_at_3
value: 60.95
- type: mrr_at_5
value: 62.305
- type: ndcg_at_1
value: 53.1
- type: ndcg_at_10
value: 68.418
- type: ndcg_at_100
value: 70.88499999999999
- type: ndcg_at_1000
value: 71.135
- type: ndcg_at_3
value: 63.50599999999999
- type: ndcg_at_5
value: 65.92
- type: precision_at_1
value: 53.1
- type: precision_at_10
value: 8.43
- type: precision_at_100
value: 0.955
- type: precision_at_1000
value: 0.098
- type: precision_at_3
value: 23.633000000000003
- type: precision_at_5
value: 15.340000000000002
- type: recall_at_1
value: 53.1
- type: recall_at_10
value: 84.3
- type: recall_at_100
value: 95.5
- type: recall_at_1000
value: 97.5
- type: recall_at_3
value: 70.89999999999999
- type: recall_at_5
value: 76.7
- task:
type: Classification
dataset:
type: C-MTEB/IFlyTek-classification
name: MTEB IFlyTek
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 48.303193535975375
- type: f1
value: 35.96559358693866
- task:
type: Classification
dataset:
type: C-MTEB/JDReview-classification
name: MTEB JDReview
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 85.06566604127579
- type: ap
value: 52.0596483757231
- type: f1
value: 79.5196835127668
- task:
type: STS
dataset:
type: C-MTEB/LCQMC
name: MTEB LCQMC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 74.48499423626059
- type: cos_sim_spearman
value: 78.75806756061169
- type: euclidean_pearson
value: 78.47917601852879
- type: euclidean_spearman
value: 78.75807199272622
- type: manhattan_pearson
value: 78.40207586289772
- type: manhattan_spearman
value: 78.6911776964119
- task:
type: Reranking
dataset:
type: C-MTEB/Mmarco-reranking
name: MTEB MMarcoReranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 24.75987466552363
- type: mrr
value: 23.40515873015873
- task:
type: Retrieval
dataset:
type: C-MTEB/MMarcoRetrieval
name: MTEB MMarcoRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 58.026999999999994
- type: map_at_10
value: 67.50699999999999
- type: map_at_100
value: 67.946
- type: map_at_1000
value: 67.96600000000001
- type: map_at_3
value: 65.503
- type: map_at_5
value: 66.649
- type: mrr_at_1
value: 60.20100000000001
- type: mrr_at_10
value: 68.271
- type: mrr_at_100
value: 68.664
- type: mrr_at_1000
value: 68.682
- type: mrr_at_3
value: 66.47800000000001
- type: mrr_at_5
value: 67.499
- type: ndcg_at_1
value: 60.20100000000001
- type: ndcg_at_10
value: 71.697
- type: ndcg_at_100
value: 73.736
- type: ndcg_at_1000
value: 74.259
- type: ndcg_at_3
value: 67.768
- type: ndcg_at_5
value: 69.72
- type: precision_at_1
value: 60.20100000000001
- type: precision_at_10
value: 8.927999999999999
- type: precision_at_100
value: 0.9950000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 25.883
- type: precision_at_5
value: 16.55
- type: recall_at_1
value: 58.026999999999994
- type: recall_at_10
value: 83.966
- type: recall_at_100
value: 93.313
- type: recall_at_1000
value: 97.426
- type: recall_at_3
value: 73.342
- type: recall_at_5
value: 77.997
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (zh-CN)
config: zh-CN
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 71.1600537995965
- type: f1
value: 68.8126216609964
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (zh-CN)
config: zh-CN
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 73.54068594485541
- type: f1
value: 73.46845879869848
- task:
type: Retrieval
dataset:
type: C-MTEB/MedicalRetrieval
name: MTEB MedicalRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 54.900000000000006
- type: map_at_10
value: 61.363
- type: map_at_100
value: 61.924
- type: map_at_1000
value: 61.967000000000006
- type: map_at_3
value: 59.767
- type: map_at_5
value: 60.802
- type: mrr_at_1
value: 55.1
- type: mrr_at_10
value: 61.454
- type: mrr_at_100
value: 62.016000000000005
- type: mrr_at_1000
value: 62.059
- type: mrr_at_3
value: 59.882999999999996
- type: mrr_at_5
value: 60.893
- type: ndcg_at_1
value: 54.900000000000006
- type: ndcg_at_10
value: 64.423
- type: ndcg_at_100
value: 67.35900000000001
- type: ndcg_at_1000
value: 68.512
- type: ndcg_at_3
value: 61.224000000000004
- type: ndcg_at_5
value: 63.083
- type: precision_at_1
value: 54.900000000000006
- type: precision_at_10
value: 7.3999999999999995
- type: precision_at_100
value: 0.882
- type: precision_at_1000
value: 0.097
- type: precision_at_3
value: 21.8
- type: precision_at_5
value: 13.98
- type: recall_at_1
value: 54.900000000000006
- type: recall_at_10
value: 74
- type: recall_at_100
value: 88.2
- type: recall_at_1000
value: 97.3
- type: recall_at_3
value: 65.4
- type: recall_at_5
value: 69.89999999999999
- task:
type: Classification
dataset:
type: C-MTEB/MultilingualSentiment-classification
name: MTEB MultilingualSentiment
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 75.15666666666667
- type: f1
value: 74.8306375354435
- task:
type: PairClassification
dataset:
type: C-MTEB/OCNLI
name: MTEB Ocnli
config: default
split: validation
revision: None
metrics:
- type: cos_sim_accuracy
value: 83.10774228478614
- type: cos_sim_ap
value: 87.17679348388666
- type: cos_sim_f1
value: 84.59302325581395
- type: cos_sim_precision
value: 78.15577439570276
- type: cos_sim_recall
value: 92.18585005279832
- type: dot_accuracy
value: 83.10774228478614
- type: dot_ap
value: 87.17679348388666
- type: dot_f1
value: 84.59302325581395
- type: dot_precision
value: 78.15577439570276
- type: dot_recall
value: 92.18585005279832
- type: euclidean_accuracy
value: 83.10774228478614
- type: euclidean_ap
value: 87.17679348388666
- type: euclidean_f1
value: 84.59302325581395
- type: euclidean_precision
value: 78.15577439570276
- type: euclidean_recall
value: 92.18585005279832
- type: manhattan_accuracy
value: 82.67460747157553
- type: manhattan_ap
value: 86.94296334435238
- type: manhattan_f1
value: 84.32327166504382
- type: manhattan_precision
value: 78.22944896115628
- type: manhattan_recall
value: 91.4466737064414
- type: max_accuracy
value: 83.10774228478614
- type: max_ap
value: 87.17679348388666
- type: max_f1
value: 84.59302325581395
- task:
type: Classification
dataset:
type: C-MTEB/OnlineShopping-classification
name: MTEB OnlineShopping
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 93.24999999999999
- type: ap
value: 90.98617641063584
- type: f1
value: 93.23447883650289
- task:
type: STS
dataset:
type: C-MTEB/PAWSX
name: MTEB PAWSX
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 41.071417937737856
- type: cos_sim_spearman
value: 45.049199344455424
- type: euclidean_pearson
value: 44.913450096830786
- type: euclidean_spearman
value: 45.05733424275291
- type: manhattan_pearson
value: 44.881623825912065
- type: manhattan_spearman
value: 44.989923561416596
- task:
type: STS
dataset:
type: C-MTEB/QBQTC
name: MTEB QBQTC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 41.38238052689359
- type: cos_sim_spearman
value: 42.61949690594399
- type: euclidean_pearson
value: 40.61261500356766
- type: euclidean_spearman
value: 42.619626605620724
- type: manhattan_pearson
value: 40.8886109204474
- type: manhattan_spearman
value: 42.75791523010463
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh)
config: zh
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 62.10977863727196
- type: cos_sim_spearman
value: 63.843727112473225
- type: euclidean_pearson
value: 63.25133487817196
- type: euclidean_spearman
value: 63.843727112473225
- type: manhattan_pearson
value: 63.58749018644103
- type: manhattan_spearman
value: 63.83820575456674
- task:
type: STS
dataset:
type: C-MTEB/STSB
name: MTEB STSB
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 79.30616496720054
- type: cos_sim_spearman
value: 80.767935782436
- type: euclidean_pearson
value: 80.4160642670106
- type: euclidean_spearman
value: 80.76820284024356
- type: manhattan_pearson
value: 80.27318714580251
- type: manhattan_spearman
value: 80.61030164164964
- task:
type: Reranking
dataset:
type: C-MTEB/T2Reranking
name: MTEB T2Reranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 66.26242871142425
- type: mrr
value: 76.20689863623174
- task:
type: Retrieval
dataset:
type: C-MTEB/T2Retrieval
name: MTEB T2Retrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 26.240999999999996
- type: map_at_10
value: 73.009
- type: map_at_100
value: 76.893
- type: map_at_1000
value: 76.973
- type: map_at_3
value: 51.339
- type: map_at_5
value: 63.003
- type: mrr_at_1
value: 87.458
- type: mrr_at_10
value: 90.44
- type: mrr_at_100
value: 90.558
- type: mrr_at_1000
value: 90.562
- type: mrr_at_3
value: 89.89
- type: mrr_at_5
value: 90.231
- type: ndcg_at_1
value: 87.458
- type: ndcg_at_10
value: 81.325
- type: ndcg_at_100
value: 85.61999999999999
- type: ndcg_at_1000
value: 86.394
- type: ndcg_at_3
value: 82.796
- type: ndcg_at_5
value: 81.219
- type: precision_at_1
value: 87.458
- type: precision_at_10
value: 40.534
- type: precision_at_100
value: 4.96
- type: precision_at_1000
value: 0.514
- type: precision_at_3
value: 72.444
- type: precision_at_5
value: 60.601000000000006
- type: recall_at_1
value: 26.240999999999996
- type: recall_at_10
value: 80.42
- type: recall_at_100
value: 94.118
- type: recall_at_1000
value: 98.02199999999999
- type: recall_at_3
value: 53.174
- type: recall_at_5
value: 66.739
- task:
type: Classification
dataset:
type: C-MTEB/TNews-classification
name: MTEB TNews
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 52.40899999999999
- type: f1
value: 50.68532128056062
- task:
type: Clustering
dataset:
type: C-MTEB/ThuNewsClusteringP2P
name: MTEB ThuNewsClusteringP2P
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 65.57616085176686
- task:
type: Clustering
dataset:
type: C-MTEB/ThuNewsClusteringS2S
name: MTEB ThuNewsClusteringS2S
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 58.844999922904925
- task:
type: Retrieval
dataset:
type: C-MTEB/VideoRetrieval
name: MTEB VideoRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 58.4
- type: map_at_10
value: 68.64
- type: map_at_100
value: 69.062
- type: map_at_1000
value: 69.073
- type: map_at_3
value: 66.567
- type: map_at_5
value: 67.89699999999999
- type: mrr_at_1
value: 58.4
- type: mrr_at_10
value: 68.64
- type: mrr_at_100
value: 69.062
- type: mrr_at_1000
value: 69.073
- type: mrr_at_3
value: 66.567
- type: mrr_at_5
value: 67.89699999999999
- type: ndcg_at_1
value: 58.4
- type: ndcg_at_10
value: 73.30600000000001
- type: ndcg_at_100
value: 75.276
- type: ndcg_at_1000
value: 75.553
- type: ndcg_at_3
value: 69.126
- type: ndcg_at_5
value: 71.519
- type: precision_at_1
value: 58.4
- type: precision_at_10
value: 8.780000000000001
- type: precision_at_100
value: 0.968
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 25.5
- type: precision_at_5
value: 16.46
- type: recall_at_1
value: 58.4
- type: recall_at_10
value: 87.8
- type: recall_at_100
value: 96.8
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 76.5
- type: recall_at_5
value: 82.3
- task:
type: Classification
dataset:
type: C-MTEB/waimai-classification
name: MTEB Waimai
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 86.21000000000001
- type: ap
value: 69.17460264576461
- type: f1
value: 84.68032984659226
Dmeta-embedding
Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('{MODEL_NAME}')
embeddings = model.encode(sentences)
print(embeddings)