metadata
tags:
- mteb
model-index:
- name: conan-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: 56.613572467148856
- type: cos_sim_spearman
value: 60.66446211824284
- type: euclidean_pearson
value: 58.42080485872613
- type: euclidean_spearman
value: 59.82750030458164
- type: manhattan_pearson
value: 58.39885271199772
- type: manhattan_spearman
value: 59.817749720366734
- task:
type: STS
dataset:
type: C-MTEB/ATEC
name: MTEB ATEC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 56.60530380552331
- type: cos_sim_spearman
value: 58.63822441736707
- type: euclidean_pearson
value: 62.18551665180664
- type: euclidean_spearman
value: 58.23168804495912
- type: manhattan_pearson
value: 62.17191480770053
- type: manhattan_spearman
value: 58.22556219601401
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 50.308
- type: f1
value: 46.927458607895126
- task:
type: STS
dataset:
type: C-MTEB/BQ
name: MTEB BQ
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 72.6472074172711
- type: cos_sim_spearman
value: 74.50748447236577
- type: euclidean_pearson
value: 72.51833296451854
- type: euclidean_spearman
value: 73.9898922606105
- type: manhattan_pearson
value: 72.50184948939338
- type: manhattan_spearman
value: 73.97797921509638
- task:
type: Clustering
dataset:
type: C-MTEB/CLSClusteringP2P
name: MTEB CLSClusteringP2P
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 60.63545326048343
- task:
type: Clustering
dataset:
type: C-MTEB/CLSClusteringS2S
name: MTEB CLSClusteringS2S
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 52.64834762325994
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv1-reranking
name: MTEB CMedQAv1
config: default
split: test
revision: None
metrics:
- type: map
value: 91.38528814655234
- type: mrr
value: 93.35857142857144
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv2-reranking
name: MTEB CMedQAv2
config: default
split: test
revision: None
metrics:
- type: map
value: 89.72084678877096
- type: mrr
value: 91.74380952380953
- task:
type: Retrieval
dataset:
type: C-MTEB/CmedqaRetrieval
name: MTEB CmedqaRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 26.987
- type: map_at_10
value: 40.675
- type: map_at_100
value: 42.495
- type: map_at_1000
value: 42.596000000000004
- type: map_at_3
value: 36.195
- type: map_at_5
value: 38.704
- type: mrr_at_1
value: 41.21
- type: mrr_at_10
value: 49.816
- type: mrr_at_100
value: 50.743
- type: mrr_at_1000
value: 50.77700000000001
- type: mrr_at_3
value: 47.312
- type: mrr_at_5
value: 48.699999999999996
- type: ndcg_at_1
value: 41.21
- type: ndcg_at_10
value: 47.606
- type: ndcg_at_100
value: 54.457
- type: ndcg_at_1000
value: 56.16100000000001
- type: ndcg_at_3
value: 42.108000000000004
- type: ndcg_at_5
value: 44.393
- type: precision_at_1
value: 41.21
- type: precision_at_10
value: 10.593
- type: precision_at_100
value: 1.609
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 23.881
- type: precision_at_5
value: 17.339
- type: recall_at_1
value: 26.987
- type: recall_at_10
value: 58.875
- type: recall_at_100
value: 87.023
- type: recall_at_1000
value: 98.328
- type: recall_at_3
value: 42.265
- type: recall_at_5
value: 49.334
- task:
type: PairClassification
dataset:
type: C-MTEB/CMNLI
name: MTEB Cmnli
config: default
split: validation
revision: None
metrics:
- type: cos_sim_accuracy
value: 85.91701743836441
- type: cos_sim_ap
value: 92.53650618807644
- type: cos_sim_f1
value: 86.80265975431082
- type: cos_sim_precision
value: 83.79025239338556
- type: cos_sim_recall
value: 90.039747486556
- type: dot_accuracy
value: 77.17378232110643
- type: dot_ap
value: 85.40244368166546
- type: dot_f1
value: 79.03038001481951
- type: dot_precision
value: 72.20502901353966
- type: dot_recall
value: 87.2808043020809
- type: euclidean_accuracy
value: 84.65423932651834
- type: euclidean_ap
value: 91.47775530034588
- type: euclidean_f1
value: 85.64471499723298
- type: euclidean_precision
value: 81.31567885666246
- type: euclidean_recall
value: 90.46060322656068
- type: manhattan_accuracy
value: 84.58208057726999
- type: manhattan_ap
value: 91.46228709402014
- type: manhattan_f1
value: 85.6631626034444
- type: manhattan_precision
value: 82.10075026795283
- type: manhattan_recall
value: 89.5487491232172
- type: max_accuracy
value: 85.91701743836441
- type: max_ap
value: 92.53650618807644
- type: max_f1
value: 86.80265975431082
- task:
type: Retrieval
dataset:
type: C-MTEB/CovidRetrieval
name: MTEB CovidRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 83.693
- type: map_at_10
value: 90.098
- type: map_at_100
value: 90.145
- type: map_at_1000
value: 90.146
- type: map_at_3
value: 89.445
- type: map_at_5
value: 89.935
- type: mrr_at_1
value: 83.878
- type: mrr_at_10
value: 90.007
- type: mrr_at_100
value: 90.045
- type: mrr_at_1000
value: 90.046
- type: mrr_at_3
value: 89.34
- type: mrr_at_5
value: 89.835
- type: ndcg_at_1
value: 84.089
- type: ndcg_at_10
value: 92.351
- type: ndcg_at_100
value: 92.54599999999999
- type: ndcg_at_1000
value: 92.561
- type: ndcg_at_3
value: 91.15299999999999
- type: ndcg_at_5
value: 91.968
- type: precision_at_1
value: 84.089
- type: precision_at_10
value: 10.011000000000001
- type: precision_at_100
value: 1.009
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 32.28
- type: precision_at_5
value: 19.789
- type: recall_at_1
value: 83.693
- type: recall_at_10
value: 99.05199999999999
- type: recall_at_100
value: 99.895
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 95.917
- type: recall_at_5
value: 97.893
- task:
type: Retrieval
dataset:
type: C-MTEB/DuRetrieval
name: MTEB DuRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 26.924
- type: map_at_10
value: 81.392
- type: map_at_100
value: 84.209
- type: map_at_1000
value: 84.237
- type: map_at_3
value: 56.998000000000005
- type: map_at_5
value: 71.40100000000001
- type: mrr_at_1
value: 91.75
- type: mrr_at_10
value: 94.45
- type: mrr_at_100
value: 94.503
- type: mrr_at_1000
value: 94.505
- type: mrr_at_3
value: 94.258
- type: mrr_at_5
value: 94.381
- type: ndcg_at_1
value: 91.75
- type: ndcg_at_10
value: 88.53
- type: ndcg_at_100
value: 91.13900000000001
- type: ndcg_at_1000
value: 91.387
- type: ndcg_at_3
value: 87.925
- type: ndcg_at_5
value: 86.461
- type: precision_at_1
value: 91.75
- type: precision_at_10
value: 42.05
- type: precision_at_100
value: 4.827
- type: precision_at_1000
value: 0.48900000000000005
- type: precision_at_3
value: 78.55
- type: precision_at_5
value: 65.82000000000001
- type: recall_at_1
value: 26.924
- type: recall_at_10
value: 89.338
- type: recall_at_100
value: 97.856
- type: recall_at_1000
value: 99.11
- type: recall_at_3
value: 59.202999999999996
- type: recall_at_5
value: 75.642
- task:
type: Retrieval
dataset:
type: C-MTEB/EcomRetrieval
name: MTEB EcomRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 54.800000000000004
- type: map_at_10
value: 65.613
- type: map_at_100
value: 66.185
- type: map_at_1000
value: 66.191
- type: map_at_3
value: 62.8
- type: map_at_5
value: 64.535
- type: mrr_at_1
value: 54.800000000000004
- type: mrr_at_10
value: 65.613
- type: mrr_at_100
value: 66.185
- type: mrr_at_1000
value: 66.191
- type: mrr_at_3
value: 62.8
- type: mrr_at_5
value: 64.535
- type: ndcg_at_1
value: 54.800000000000004
- type: ndcg_at_10
value: 70.991
- type: ndcg_at_100
value: 73.434
- type: ndcg_at_1000
value: 73.587
- type: ndcg_at_3
value: 65.324
- type: ndcg_at_5
value: 68.431
- type: precision_at_1
value: 54.800000000000004
- type: precision_at_10
value: 8.790000000000001
- type: precision_at_100
value: 0.9860000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 24.2
- type: precision_at_5
value: 16.02
- type: recall_at_1
value: 54.800000000000004
- type: recall_at_10
value: 87.9
- type: recall_at_100
value: 98.6
- type: recall_at_1000
value: 99.8
- type: recall_at_3
value: 72.6
- type: recall_at_5
value: 80.10000000000001
- task:
type: Classification
dataset:
type: C-MTEB/IFlyTek-classification
name: MTEB IFlyTek
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 51.94305502116199
- type: f1
value: 39.82197338426721
- task:
type: Classification
dataset:
type: C-MTEB/JDReview-classification
name: MTEB JDReview
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 90.31894934333957
- type: ap
value: 63.89821836499594
- type: f1
value: 85.93687177603624
- task:
type: STS
dataset:
type: C-MTEB/LCQMC
name: MTEB LCQMC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 73.18906216730208
- type: cos_sim_spearman
value: 79.44570226735877
- type: euclidean_pearson
value: 78.8105072242798
- type: euclidean_spearman
value: 79.15605680863212
- type: manhattan_pearson
value: 78.80576507484064
- type: manhattan_spearman
value: 79.14625534068364
- task:
type: Reranking
dataset:
type: C-MTEB/Mmarco-reranking
name: MTEB MMarcoReranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 41.58107192600853
- type: mrr
value: 41.37063492063492
- task:
type: Retrieval
dataset:
type: C-MTEB/MMarcoRetrieval
name: MTEB MMarcoRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 68.33
- type: map_at_10
value: 78.261
- type: map_at_100
value: 78.522
- type: map_at_1000
value: 78.527
- type: map_at_3
value: 76.236
- type: map_at_5
value: 77.557
- type: mrr_at_1
value: 70.602
- type: mrr_at_10
value: 78.779
- type: mrr_at_100
value: 79.00500000000001
- type: mrr_at_1000
value: 79.01
- type: mrr_at_3
value: 77.037
- type: mrr_at_5
value: 78.157
- type: ndcg_at_1
value: 70.602
- type: ndcg_at_10
value: 82.254
- type: ndcg_at_100
value: 83.319
- type: ndcg_at_1000
value: 83.449
- type: ndcg_at_3
value: 78.46
- type: ndcg_at_5
value: 80.679
- type: precision_at_1
value: 70.602
- type: precision_at_10
value: 9.989
- type: precision_at_100
value: 1.05
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 29.598999999999997
- type: precision_at_5
value: 18.948
- type: recall_at_1
value: 68.33
- type: recall_at_10
value: 94.00800000000001
- type: recall_at_100
value: 98.589
- type: recall_at_1000
value: 99.60799999999999
- type: recall_at_3
value: 84.057
- type: recall_at_5
value: 89.32900000000001
- 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: 78.13718897108272
- type: f1
value: 74.07613180855328
- 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: 86.20040349697376
- type: f1
value: 85.05282136519973
- task:
type: Retrieval
dataset:
type: C-MTEB/MedicalRetrieval
name: MTEB MedicalRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 56.8
- type: map_at_10
value: 64.199
- type: map_at_100
value: 64.89
- type: map_at_1000
value: 64.917
- type: map_at_3
value: 62.383
- type: map_at_5
value: 63.378
- type: mrr_at_1
value: 56.8
- type: mrr_at_10
value: 64.199
- type: mrr_at_100
value: 64.89
- type: mrr_at_1000
value: 64.917
- type: mrr_at_3
value: 62.383
- type: mrr_at_5
value: 63.378
- type: ndcg_at_1
value: 56.8
- type: ndcg_at_10
value: 67.944
- type: ndcg_at_100
value: 71.286
- type: ndcg_at_1000
value: 71.879
- type: ndcg_at_3
value: 64.163
- type: ndcg_at_5
value: 65.96600000000001
- type: precision_at_1
value: 56.8
- type: precision_at_10
value: 7.9799999999999995
- type: precision_at_100
value: 0.954
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 23.1
- type: precision_at_5
value: 14.74
- type: recall_at_1
value: 56.8
- type: recall_at_10
value: 79.80000000000001
- type: recall_at_100
value: 95.39999999999999
- type: recall_at_1000
value: 99.8
- type: recall_at_3
value: 69.3
- type: recall_at_5
value: 73.7
- task:
type: Classification
dataset:
type: C-MTEB/MultilingualSentiment-classification
name: MTEB MultilingualSentiment
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 78.57666666666667
- type: f1
value: 78.23373528202681
- task:
type: PairClassification
dataset:
type: C-MTEB/OCNLI
name: MTEB Ocnli
config: default
split: validation
revision: None
metrics:
- type: cos_sim_accuracy
value: 85.43584190579317
- type: cos_sim_ap
value: 90.76665640338129
- type: cos_sim_f1
value: 86.5021770682148
- type: cos_sim_precision
value: 79.82142857142858
- type: cos_sim_recall
value: 94.40337909186906
- type: dot_accuracy
value: 78.66811044937737
- type: dot_ap
value: 85.84084363880804
- type: dot_f1
value: 80.10075566750629
- type: dot_precision
value: 76.58959537572254
- type: dot_recall
value: 83.9493136219641
- type: euclidean_accuracy
value: 84.46128857606931
- type: euclidean_ap
value: 88.62351100230491
- type: euclidean_f1
value: 85.7709469509172
- type: euclidean_precision
value: 80.8411214953271
- type: euclidean_recall
value: 91.34107708553326
- type: manhattan_accuracy
value: 84.51543042772063
- type: manhattan_ap
value: 88.53975607870393
- type: manhattan_f1
value: 85.75697211155378
- type: manhattan_precision
value: 81.14985862393968
- type: manhattan_recall
value: 90.91869060190075
- type: max_accuracy
value: 85.43584190579317
- type: max_ap
value: 90.76665640338129
- type: max_f1
value: 86.5021770682148
- task:
type: Classification
dataset:
type: C-MTEB/OnlineShopping-classification
name: MTEB OnlineShopping
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 95.06999999999998
- type: ap
value: 93.45104559324996
- type: f1
value: 95.06036329426092
- task:
type: STS
dataset:
type: C-MTEB/PAWSX
name: MTEB PAWSX
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 40.01998290519605
- type: cos_sim_spearman
value: 46.5989769986853
- type: euclidean_pearson
value: 45.37905883182924
- type: euclidean_spearman
value: 46.22213849806378
- type: manhattan_pearson
value: 45.40925124776211
- type: manhattan_spearman
value: 46.250705124226386
- task:
type: STS
dataset:
type: C-MTEB/QBQTC
name: MTEB QBQTC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 42.719516197112526
- type: cos_sim_spearman
value: 44.57507789581106
- type: euclidean_pearson
value: 35.73062264160721
- type: euclidean_spearman
value: 40.473523909913695
- type: manhattan_pearson
value: 35.69868964086357
- type: manhattan_spearman
value: 40.46349925372903
- 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: 62.340118285801104
- type: cos_sim_spearman
value: 67.72781908620632
- type: euclidean_pearson
value: 63.161965746091596
- type: euclidean_spearman
value: 67.36825684340769
- type: manhattan_pearson
value: 63.089863788261425
- type: manhattan_spearman
value: 67.40868898995384
- task:
type: STS
dataset:
type: C-MTEB/STSB
name: MTEB STSB
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 79.1646360962365
- type: cos_sim_spearman
value: 81.24426700767087
- type: euclidean_pearson
value: 79.43826409936123
- type: euclidean_spearman
value: 79.71787965300125
- type: manhattan_pearson
value: 79.43377784961737
- type: manhattan_spearman
value: 79.69348376886967
- task:
type: Reranking
dataset:
type: C-MTEB/T2Reranking
name: MTEB T2Reranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 68.35595092507496
- type: mrr
value: 79.00244892585788
- task:
type: Retrieval
dataset:
type: C-MTEB/T2Retrieval
name: MTEB T2Retrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 26.588
- type: map_at_10
value: 75.327
- type: map_at_100
value: 79.095
- type: map_at_1000
value: 79.163
- type: map_at_3
value: 52.637
- type: map_at_5
value: 64.802
- type: mrr_at_1
value: 88.103
- type: mrr_at_10
value: 91.29899999999999
- type: mrr_at_100
value: 91.408
- type: mrr_at_1000
value: 91.411
- type: mrr_at_3
value: 90.801
- type: mrr_at_5
value: 91.12700000000001
- type: ndcg_at_1
value: 88.103
- type: ndcg_at_10
value: 83.314
- type: ndcg_at_100
value: 87.201
- type: ndcg_at_1000
value: 87.83999999999999
- type: ndcg_at_3
value: 84.408
- type: ndcg_at_5
value: 83.078
- type: precision_at_1
value: 88.103
- type: precision_at_10
value: 41.638999999999996
- type: precision_at_100
value: 5.006
- type: precision_at_1000
value: 0.516
- type: precision_at_3
value: 73.942
- type: precision_at_5
value: 62.056
- type: recall_at_1
value: 26.588
- type: recall_at_10
value: 82.819
- type: recall_at_100
value: 95.334
- type: recall_at_1000
value: 98.51299999999999
- type: recall_at_3
value: 54.74
- type: recall_at_5
value: 68.864
- task:
type: Classification
dataset:
type: C-MTEB/TNews-classification
name: MTEB TNews
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 55.029
- type: f1
value: 53.043617905026764
- task:
type: Clustering
dataset:
type: C-MTEB/ThuNewsClusteringP2P
name: MTEB ThuNewsClusteringP2P
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 77.83675116835911
- task:
type: Clustering
dataset:
type: C-MTEB/ThuNewsClusteringS2S
name: MTEB ThuNewsClusteringS2S
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 74.19701455865277
- task:
type: Retrieval
dataset:
type: C-MTEB/VideoRetrieval
name: MTEB VideoRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 64.7
- type: map_at_10
value: 75.593
- type: map_at_100
value: 75.863
- type: map_at_1000
value: 75.863
- type: map_at_3
value: 73.63300000000001
- type: map_at_5
value: 74.923
- type: mrr_at_1
value: 64.7
- type: mrr_at_10
value: 75.593
- type: mrr_at_100
value: 75.863
- type: mrr_at_1000
value: 75.863
- type: mrr_at_3
value: 73.63300000000001
- type: mrr_at_5
value: 74.923
- type: ndcg_at_1
value: 64.7
- type: ndcg_at_10
value: 80.399
- type: ndcg_at_100
value: 81.517
- type: ndcg_at_1000
value: 81.517
- type: ndcg_at_3
value: 76.504
- type: ndcg_at_5
value: 78.79899999999999
- type: precision_at_1
value: 64.7
- type: precision_at_10
value: 9.520000000000001
- type: precision_at_100
value: 1
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 28.266999999999996
- type: precision_at_5
value: 18.060000000000002
- type: recall_at_1
value: 64.7
- type: recall_at_10
value: 95.19999999999999
- type: recall_at_100
value: 100
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 84.8
- type: recall_at_5
value: 90.3
- task:
type: Classification
dataset:
type: C-MTEB/waimai-classification
name: MTEB Waimai
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 89.69999999999999
- type: ap
value: 75.91371640164184
- type: f1
value: 88.34067777698694
license: cc-by-nc-4.0
library_name: sentence-transformers
Conan-embedding-v1
Performance
| Model | Average | CLS | Clustering | Reranking | Retrieval | STS | Pair_CLS |
|---|---|---|---|---|---|---|---|
| gte-Qwen2-7B-instruct | 72.05 | 75.09 | 66.06 | 68.92 | 76.03 | 65.33 | 87.48 |
| xiaobu-embedding-v2 | 72.43 | 74.67 | 65.17 | 72.58 | 76.5 | 64.53 | 91.87 |
| Conan-embedding-v1 | 72.62 | 75.03 | 66.33 | 72.76 | 76.67 | 64.18 | 91.66 |
Methods and Training Detials
Please refer to our technical report.
Citation
If you find our models / papers useful in your research, please consider giving ❤️ and citations. Thanks!
@misc{li2024conanembeddinggeneraltextembedding,
title={Conan-embedding: General Text Embedding with More and Better Negative Samples},
author={Shiyu Li and Yang Tang and Shizhe Chen and Xi Chen},
year={2024},
eprint={2408.15710},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2408.15710},
}
About
Created by the Tencent BAC Group. All rights reserved.
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.