metadata
tags:
- mteb
model-index:
- name: NV-Embed-v1
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 95.11940298507461
- type: ap
value: 79.21521293687752
- type: f1
value: 92.45575440759485
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 97.143125
- type: ap
value: 95.28635983806933
- type: f1
value: 97.1426073127198
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 55.465999999999994
- type: f1
value: 52.70196166254287
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 44.879000000000005
- type: map_at_10
value: 60.146
- type: map_at_100
value: 60.533
- type: map_at_1000
value: 60.533
- type: map_at_3
value: 55.725
- type: map_at_5
value: 58.477999999999994
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 44.879000000000005
- type: ndcg_at_10
value: 68.205
- type: ndcg_at_100
value: 69.646
- type: ndcg_at_1000
value: 69.65599999999999
- type: ndcg_at_3
value: 59.243
- type: ndcg_at_5
value: 64.214
- type: precision_at_1
value: 44.879000000000005
- type: precision_at_10
value: 9.374
- type: precision_at_100
value: 0.996
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 23.139000000000003
- type: precision_at_5
value: 16.302
- type: recall_at_1
value: 44.879000000000005
- type: recall_at_10
value: 93.741
- type: recall_at_100
value: 99.57300000000001
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 69.417
- type: recall_at_5
value: 81.50800000000001
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 53.76391569504432
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 49.589284930659005
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 67.49860736554155
- type: mrr
value: 80.77771182341819
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.87900681188576
- type: cos_sim_spearman
value: 85.5905044545741
- type: euclidean_pearson
value: 86.80150192033507
- type: euclidean_spearman
value: 85.5905044545741
- type: manhattan_pearson
value: 86.79080500635683
- type: manhattan_spearman
value: 85.69351885001977
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 90.33766233766235
- type: f1
value: 90.20736178753944
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 48.152262077598465
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 44.742970683037235
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 31.825333333333326
- type: map_at_10
value: 44.019999999999996
- type: map_at_100
value: 45.37291666666667
- type: map_at_1000
value: 45.46991666666666
- type: map_at_3
value: 40.28783333333333
- type: map_at_5
value: 42.39458333333334
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 37.79733333333333
- type: ndcg_at_10
value: 50.50541666666667
- type: ndcg_at_100
value: 55.59125
- type: ndcg_at_1000
value: 57.06325
- type: ndcg_at_3
value: 44.595666666666666
- type: ndcg_at_5
value: 47.44875
- type: precision_at_1
value: 37.79733333333333
- type: precision_at_10
value: 9.044083333333333
- type: precision_at_100
value: 1.3728333333333336
- type: precision_at_1000
value: 0.16733333333333333
- type: precision_at_3
value: 20.842166666666667
- type: precision_at_5
value: 14.921916666666668
- type: recall_at_1
value: 31.825333333333326
- type: recall_at_10
value: 65.11916666666666
- type: recall_at_100
value: 86.72233333333335
- type: recall_at_1000
value: 96.44200000000001
- type: recall_at_3
value: 48.75691666666667
- type: recall_at_5
value: 56.07841666666666
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 14.698
- type: map_at_10
value: 25.141999999999996
- type: map_at_100
value: 27.1
- type: map_at_1000
value: 27.277
- type: map_at_3
value: 21.162
- type: map_at_5
value: 23.154
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 32.704
- type: ndcg_at_10
value: 34.715
- type: ndcg_at_100
value: 41.839
- type: ndcg_at_1000
value: 44.82
- type: ndcg_at_3
value: 28.916999999999998
- type: ndcg_at_5
value: 30.738
- type: precision_at_1
value: 32.704
- type: precision_at_10
value: 10.795
- type: precision_at_100
value: 1.8530000000000002
- type: precision_at_1000
value: 0.241
- type: precision_at_3
value: 21.564
- type: precision_at_5
value: 16.261
- type: recall_at_1
value: 14.698
- type: recall_at_10
value: 41.260999999999996
- type: recall_at_100
value: 65.351
- type: recall_at_1000
value: 81.759
- type: recall_at_3
value: 26.545999999999996
- type: recall_at_5
value: 32.416
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 9.959
- type: map_at_10
value: 23.104
- type: map_at_100
value: 33.202
- type: map_at_1000
value: 35.061
- type: map_at_3
value: 15.911
- type: map_at_5
value: 18.796
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 63.5
- type: ndcg_at_10
value: 48.29
- type: ndcg_at_100
value: 52.949999999999996
- type: ndcg_at_1000
value: 60.20100000000001
- type: ndcg_at_3
value: 52.92
- type: ndcg_at_5
value: 50.375
- type: precision_at_1
value: 73.75
- type: precision_at_10
value: 38.65
- type: precision_at_100
value: 12.008000000000001
- type: precision_at_1000
value: 2.409
- type: precision_at_3
value: 56.083000000000006
- type: precision_at_5
value: 48.449999999999996
- type: recall_at_1
value: 9.959
- type: recall_at_10
value: 28.666999999999998
- type: recall_at_100
value: 59.319
- type: recall_at_1000
value: 81.973
- type: recall_at_3
value: 17.219
- type: recall_at_5
value: 21.343999999999998
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 91.705
- type: f1
value: 87.98464515154814
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 74.297
- type: map_at_10
value: 83.931
- type: map_at_100
value: 84.152
- type: map_at_1000
value: 84.164
- type: map_at_3
value: 82.708
- type: map_at_5
value: 83.536
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 80.048
- type: ndcg_at_10
value: 87.77000000000001
- type: ndcg_at_100
value: 88.467
- type: ndcg_at_1000
value: 88.673
- type: ndcg_at_3
value: 86.003
- type: ndcg_at_5
value: 87.115
- type: precision_at_1
value: 80.048
- type: precision_at_10
value: 10.711
- type: precision_at_100
value: 1.1320000000000001
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 33.248
- type: precision_at_5
value: 20.744
- type: recall_at_1
value: 74.297
- type: recall_at_10
value: 95.402
- type: recall_at_100
value: 97.97
- type: recall_at_1000
value: 99.235
- type: recall_at_3
value: 90.783
- type: recall_at_5
value: 93.55499999999999
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 32.986
- type: map_at_10
value: 55.173
- type: map_at_100
value: 57.077
- type: map_at_1000
value: 57.176
- type: map_at_3
value: 48.182
- type: map_at_5
value: 52.303999999999995
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 62.037
- type: ndcg_at_10
value: 63.096
- type: ndcg_at_100
value: 68.42200000000001
- type: ndcg_at_1000
value: 69.811
- type: ndcg_at_3
value: 58.702
- type: ndcg_at_5
value: 60.20100000000001
- type: precision_at_1
value: 62.037
- type: precision_at_10
value: 17.269000000000002
- type: precision_at_100
value: 2.309
- type: precision_at_1000
value: 0.256
- type: precision_at_3
value: 38.992
- type: precision_at_5
value: 28.610999999999997
- type: recall_at_1
value: 32.986
- type: recall_at_10
value: 70.61800000000001
- type: recall_at_100
value: 89.548
- type: recall_at_1000
value: 97.548
- type: recall_at_3
value: 53.400000000000006
- type: recall_at_5
value: 61.29599999999999
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 41.357
- type: map_at_10
value: 72.91499999999999
- type: map_at_100
value: 73.64699999999999
- type: map_at_1000
value: 73.67899999999999
- type: map_at_3
value: 69.113
- type: map_at_5
value: 71.68299999999999
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 82.714
- type: ndcg_at_10
value: 79.92
- type: ndcg_at_100
value: 82.232
- type: ndcg_at_1000
value: 82.816
- type: ndcg_at_3
value: 74.875
- type: ndcg_at_5
value: 77.969
- type: precision_at_1
value: 82.714
- type: precision_at_10
value: 17.037
- type: precision_at_100
value: 1.879
- type: precision_at_1000
value: 0.196
- type: precision_at_3
value: 49.471
- type: precision_at_5
value: 32.124
- type: recall_at_1
value: 41.357
- type: recall_at_10
value: 85.18599999999999
- type: recall_at_100
value: 93.964
- type: recall_at_1000
value: 97.765
- type: recall_at_3
value: 74.207
- type: recall_at_5
value: 80.31099999999999
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 97.05799999999998
- type: ap
value: 95.51324940484382
- type: f1
value: 97.05788617110184
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: test
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 25.608999999999998
- type: map_at_10
value: 39.098
- type: map_at_100
value: 0
- type: map_at_1000
value: 0
- type: map_at_3
value: 0
- type: map_at_5
value: 37.383
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 26.404
- type: ndcg_at_10
value: 46.493
- type: ndcg_at_100
value: 0
- type: ndcg_at_1000
value: 0
- type: ndcg_at_3
value: 0
- type: ndcg_at_5
value: 42.459
- type: precision_at_1
value: 26.404
- type: precision_at_10
value: 7.249
- type: precision_at_100
value: 0
- type: precision_at_1000
value: 0
- type: precision_at_3
value: 0
- type: precision_at_5
value: 11.874
- type: recall_at_1
value: 25.608999999999998
- type: recall_at_10
value: 69.16799999999999
- type: recall_at_100
value: 0
- type: recall_at_1000
value: 0
- type: recall_at_3
value: 0
- type: recall_at_5
value: 56.962
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 96.50706794345645
- type: f1
value: 96.3983656000426
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 89.77428180574556
- type: f1
value: 70.47378359921777
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 80.07061197041023
- type: f1
value: 77.8633288994029
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 81.74176193678547
- type: f1
value: 79.8943810025071
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 39.239199736486334
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 36.98167653792483
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.815595271130718
- type: mrr
value: 31.892823243368795
- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 6.214
- type: map_at_10
value: 14.393
- type: map_at_100
value: 18.163999999999998
- type: map_at_1000
value: 19.753999999999998
- type: map_at_3
value: 10.737
- type: map_at_5
value: 12.325
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 48.297000000000004
- type: ndcg_at_10
value: 38.035000000000004
- type: ndcg_at_100
value: 34.772
- type: ndcg_at_1000
value: 43.631
- type: ndcg_at_3
value: 44.252
- type: ndcg_at_5
value: 41.307
- type: precision_at_1
value: 50.15500000000001
- type: precision_at_10
value: 27.647
- type: precision_at_100
value: 8.824
- type: precision_at_1000
value: 2.169
- type: precision_at_3
value: 40.97
- type: precision_at_5
value: 35.17
- type: recall_at_1
value: 6.214
- type: recall_at_10
value: 18.566
- type: recall_at_100
value: 34.411
- type: recall_at_1000
value: 67.331
- type: recall_at_3
value: 12.277000000000001
- type: recall_at_5
value: 14.734
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 47.11
- type: map_at_10
value: 64.404
- type: map_at_100
value: 65.005
- type: map_at_1000
value: 65.01400000000001
- type: map_at_3
value: 60.831
- type: map_at_5
value: 63.181
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 52.983999999999995
- type: ndcg_at_10
value: 71.219
- type: ndcg_at_100
value: 73.449
- type: ndcg_at_1000
value: 73.629
- type: ndcg_at_3
value: 65.07
- type: ndcg_at_5
value: 68.715
- type: precision_at_1
value: 52.983999999999995
- type: precision_at_10
value: 10.756
- type: precision_at_100
value: 1.198
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 28.977999999999998
- type: precision_at_5
value: 19.583000000000002
- type: recall_at_1
value: 47.11
- type: recall_at_10
value: 89.216
- type: recall_at_100
value: 98.44500000000001
- type: recall_at_1000
value: 99.744
- type: recall_at_3
value: 73.851
- type: recall_at_5
value: 82.126
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 71.641
- type: map_at_10
value: 85.687
- type: map_at_100
value: 86.304
- type: map_at_1000
value: 86.318
- type: map_at_3
value: 82.811
- type: map_at_5
value: 84.641
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 82.48
- type: ndcg_at_10
value: 89.212
- type: ndcg_at_100
value: 90.321
- type: ndcg_at_1000
value: 90.405
- type: ndcg_at_3
value: 86.573
- type: ndcg_at_5
value: 88.046
- type: precision_at_1
value: 82.48
- type: precision_at_10
value: 13.522
- type: precision_at_100
value: 1.536
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.95
- type: precision_at_5
value: 24.932000000000002
- type: recall_at_1
value: 71.641
- type: recall_at_10
value: 95.91499999999999
- type: recall_at_100
value: 99.63300000000001
- type: recall_at_1000
value: 99.994
- type: recall_at_3
value: 88.248
- type: recall_at_5
value: 92.428
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 63.19631707795757
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 68.01353074322002
- task:
type: Retrieval
dataset:
type: mteb/scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
metrics:
- type: map_at_1
value: 4.67
- type: map_at_10
value: 11.991999999999999
- type: map_at_100
value: 14.263
- type: map_at_1000
value: 14.59
- type: map_at_3
value: 8.468
- type: map_at_5
value: 10.346
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 23.1
- type: ndcg_at_10
value: 20.19
- type: ndcg_at_100
value: 28.792
- type: ndcg_at_1000
value: 34.406
- type: ndcg_at_3
value: 19.139
- type: ndcg_at_5
value: 16.916
- type: precision_at_1
value: 23.1
- type: precision_at_10
value: 10.47
- type: precision_at_100
value: 2.2849999999999997
- type: precision_at_1000
value: 0.363
- type: precision_at_3
value: 17.9
- type: precision_at_5
value: 14.979999999999999
- type: recall_at_1
value: 4.67
- type: recall_at_10
value: 21.21
- type: recall_at_100
value: 46.36
- type: recall_at_1000
value: 73.72999999999999
- type: recall_at_3
value: 10.865
- type: recall_at_5
value: 15.185
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 84.31392081916142
- type: cos_sim_spearman
value: 82.80375234068289
- type: euclidean_pearson
value: 81.4159066418654
- type: euclidean_spearman
value: 82.80377112831907
- type: manhattan_pearson
value: 81.48376861134983
- type: manhattan_spearman
value: 82.86696725667119
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 84.1940844467158
- type: cos_sim_spearman
value: 76.22474792649982
- type: euclidean_pearson
value: 79.87714243582901
- type: euclidean_spearman
value: 76.22462054296349
- type: manhattan_pearson
value: 80.19242023327877
- type: manhattan_spearman
value: 76.53202564089719
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 85.58028303401805
- type: cos_sim_spearman
value: 86.30355131725051
- type: euclidean_pearson
value: 85.9027489087145
- type: euclidean_spearman
value: 86.30352515906158
- type: manhattan_pearson
value: 85.74953930990678
- type: manhattan_spearman
value: 86.21878393891001
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 82.92370135244734
- type: cos_sim_spearman
value: 82.09196894621044
- type: euclidean_pearson
value: 81.83198023906334
- type: euclidean_spearman
value: 82.09196482328333
- type: manhattan_pearson
value: 81.8951479497964
- type: manhattan_spearman
value: 82.2392819738236
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 87.05662816919057
- type: cos_sim_spearman
value: 87.24083005603993
- type: euclidean_pearson
value: 86.54673655650183
- type: euclidean_spearman
value: 87.24083428218053
- type: manhattan_pearson
value: 86.51248710513431
- type: manhattan_spearman
value: 87.24796986335883
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 84.06330254316376
- type: cos_sim_spearman
value: 84.76788840323285
- type: euclidean_pearson
value: 84.15438606134029
- type: euclidean_spearman
value: 84.76788840323285
- type: manhattan_pearson
value: 83.97986968570088
- type: manhattan_spearman
value: 84.52468572953663
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 88.08627867173213
- type: cos_sim_spearman
value: 87.41531216247836
- type: euclidean_pearson
value: 87.92912483282956
- type: euclidean_spearman
value: 87.41531216247836
- type: manhattan_pearson
value: 87.85418528366228
- type: manhattan_spearman
value: 87.32655499883539
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 70.74143864859911
- type: cos_sim_spearman
value: 69.84863549051433
- type: euclidean_pearson
value: 71.07346533903932
- type: euclidean_spearman
value: 69.84863549051433
- type: manhattan_pearson
value: 71.32285810342451
- type: manhattan_spearman
value: 70.13063960824287
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 86.05702492574339
- type: cos_sim_spearman
value: 86.13895001731495
- type: euclidean_pearson
value: 85.86694514265486
- type: euclidean_spearman
value: 86.13895001731495
- type: manhattan_pearson
value: 85.96382530570494
- type: manhattan_spearman
value: 86.30950247235928
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 87.26225076335467
- type: mrr
value: 96.60696329813977
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 64.494
- type: map_at_10
value: 74.102
- type: map_at_100
value: 74.571
- type: map_at_1000
value: 74.58
- type: map_at_3
value: 71.111
- type: map_at_5
value: 73.184
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 67.667
- type: ndcg_at_10
value: 78.427
- type: ndcg_at_100
value: 80.167
- type: ndcg_at_1000
value: 80.41
- type: ndcg_at_3
value: 73.804
- type: ndcg_at_5
value: 76.486
- type: precision_at_1
value: 67.667
- type: precision_at_10
value: 10.167
- type: precision_at_100
value: 1.107
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 28.222
- type: precision_at_5
value: 18.867
- type: recall_at_1
value: 64.494
- type: recall_at_10
value: 90.422
- type: recall_at_100
value: 97.667
- type: recall_at_1000
value: 99.667
- type: recall_at_3
value: 78.278
- type: recall_at_5
value: 84.828
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.82772277227723
- type: cos_sim_ap
value: 95.93881941923254
- type: cos_sim_f1
value: 91.12244897959184
- type: cos_sim_precision
value: 93.02083333333333
- type: cos_sim_recall
value: 89.3
- type: dot_accuracy
value: 99.82772277227723
- type: dot_ap
value: 95.93886287716076
- type: dot_f1
value: 91.12244897959184
- type: dot_precision
value: 93.02083333333333
- type: dot_recall
value: 89.3
- type: euclidean_accuracy
value: 99.82772277227723
- type: euclidean_ap
value: 95.93881941923253
- type: euclidean_f1
value: 91.12244897959184
- type: euclidean_precision
value: 93.02083333333333
- type: euclidean_recall
value: 89.3
- type: manhattan_accuracy
value: 99.83366336633664
- type: manhattan_ap
value: 96.07286531485964
- type: manhattan_f1
value: 91.34912461380021
- type: manhattan_precision
value: 94.16135881104034
- type: manhattan_recall
value: 88.7
- type: max_accuracy
value: 99.83366336633664
- type: max_ap
value: 96.07286531485964
- type: max_f1
value: 91.34912461380021
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 74.98877944689897
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 42.0365286267706
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 56.5797777961647
- type: mrr
value: 57.57701754944402
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.673216240991756
- type: cos_sim_spearman
value: 31.198648165051225
- type: dot_pearson
value: 30.67321511262982
- type: dot_spearman
value: 31.198648165051225
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.23500000000000001
- type: map_at_10
value: 2.274
- type: map_at_100
value: 14.002
- type: map_at_1000
value: 34.443
- type: map_at_3
value: 0.705
- type: map_at_5
value: 1.162
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 88
- type: ndcg_at_10
value: 85.883
- type: ndcg_at_100
value: 67.343
- type: ndcg_at_1000
value: 59.999
- type: ndcg_at_3
value: 87.70400000000001
- type: ndcg_at_5
value: 85.437
- type: precision_at_1
value: 92
- type: precision_at_10
value: 91.2
- type: precision_at_100
value: 69.19999999999999
- type: precision_at_1000
value: 26.6
- type: precision_at_3
value: 92.667
- type: precision_at_5
value: 90.8
- type: recall_at_1
value: 0.23500000000000001
- type: recall_at_10
value: 2.409
- type: recall_at_100
value: 16.706
- type: recall_at_1000
value: 56.396
- type: recall_at_3
value: 0.734
- type: recall_at_5
value: 1.213
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 2.4819999999999998
- type: map_at_10
value: 10.985
- type: map_at_100
value: 17.943
- type: map_at_1000
value: 19.591
- type: map_at_3
value: 5.86
- type: map_at_5
value: 8.397
- type: mrr_at_1
value: 0
- type: mrr_at_10
value: 0
- type: mrr_at_100
value: 0
- type: mrr_at_1000
value: 0
- type: mrr_at_3
value: 0
- type: mrr_at_5
value: 0
- type: ndcg_at_1
value: 37.755
- type: ndcg_at_10
value: 28.383000000000003
- type: ndcg_at_100
value: 40.603
- type: ndcg_at_1000
value: 51.469
- type: ndcg_at_3
value: 32.562000000000005
- type: ndcg_at_5
value: 31.532
- type: precision_at_1
value: 38.775999999999996
- type: precision_at_10
value: 24.898
- type: precision_at_100
value: 8.429
- type: precision_at_1000
value: 1.582
- type: precision_at_3
value: 31.973000000000003
- type: precision_at_5
value: 31.019999999999996
- type: recall_at_1
value: 2.4819999999999998
- type: recall_at_10
value: 17.079
- type: recall_at_100
value: 51.406
- type: recall_at_1000
value: 84.456
- type: recall_at_3
value: 6.802
- type: recall_at_5
value: 10.856
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 92.5984
- type: ap
value: 41.969971606260906
- type: f1
value: 78.95995145145926
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 80.63950198075835
- type: f1
value: 80.93345710055597
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 60.13491858535076
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.42325803182929
- type: cos_sim_ap
value: 78.72789856051176
- type: cos_sim_f1
value: 71.83879093198993
- type: cos_sim_precision
value: 68.72289156626506
- type: cos_sim_recall
value: 75.25065963060686
- type: dot_accuracy
value: 87.42325803182929
- type: dot_ap
value: 78.72789755269454
- type: dot_f1
value: 71.83879093198993
- type: dot_precision
value: 68.72289156626506
- type: dot_recall
value: 75.25065963060686
- type: euclidean_accuracy
value: 87.42325803182929
- type: euclidean_ap
value: 78.7278973892869
- type: euclidean_f1
value: 71.83879093198993
- type: euclidean_precision
value: 68.72289156626506
- type: euclidean_recall
value: 75.25065963060686
- type: manhattan_accuracy
value: 87.59015318590929
- type: manhattan_ap
value: 78.99631410090865
- type: manhattan_f1
value: 72.11323565929972
- type: manhattan_precision
value: 68.10506566604127
- type: manhattan_recall
value: 76.62269129287598
- type: max_accuracy
value: 87.59015318590929
- type: max_ap
value: 78.99631410090865
- type: max_f1
value: 72.11323565929972
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.15473279776458
- type: cos_sim_ap
value: 86.05463278065247
- type: cos_sim_f1
value: 78.63797449855686
- type: cos_sim_precision
value: 74.82444552596816
- type: cos_sim_recall
value: 82.86110255620572
- type: dot_accuracy
value: 89.15473279776458
- type: dot_ap
value: 86.05463366261054
- type: dot_f1
value: 78.63797449855686
- type: dot_precision
value: 74.82444552596816
- type: dot_recall
value: 82.86110255620572
- type: euclidean_accuracy
value: 89.15473279776458
- type: euclidean_ap
value: 86.05463195314907
- type: euclidean_f1
value: 78.63797449855686
- type: euclidean_precision
value: 74.82444552596816
- type: euclidean_recall
value: 82.86110255620572
- type: manhattan_accuracy
value: 89.15861373074087
- type: manhattan_ap
value: 86.08743411620402
- type: manhattan_f1
value: 78.70125023325248
- type: manhattan_precision
value: 76.36706018686174
- type: manhattan_recall
value: 81.18263012011087
- type: max_accuracy
value: 89.15861373074087
- type: max_ap
value: 86.08743411620402
- type: max_f1
value: 78.70125023325248
language:
- en
license: cc-by-nc-4.0
Model Details
We introduce the NV-Embed model with a variety of architectural designs and training procedures to significantly enhance the performance of LLM as a versatile embedding model. More details will be updated soon.
Paper
arxiv.org/abs/2405.17428