metadata
tags:
- mteb
model-index:
- name: andersonbcdefg/bge-small-4096
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 68.74626865671641
- type: ap
value: 31.113961861085855
- type: f1
value: 62.628656720790275
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 81.30347499999999
- type: ap
value: 76.05639977935193
- type: f1
value: 81.23180016825499
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 38.566
- type: f1
value: 38.014543974125615
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.445
- type: map_at_10
value: 44.157999999999994
- type: map_at_100
value: 45.169
- type: map_at_1000
value: 45.178000000000004
- type: map_at_3
value: 39.545
- type: map_at_5
value: 42.233
- type: mrr_at_1
value: 29.445
- type: mrr_at_10
value: 44.157999999999994
- type: mrr_at_100
value: 45.169
- type: mrr_at_1000
value: 45.178000000000004
- type: mrr_at_3
value: 39.545
- type: mrr_at_5
value: 42.233
- type: ndcg_at_1
value: 29.445
- type: ndcg_at_10
value: 52.446000000000005
- type: ndcg_at_100
value: 56.782
- type: ndcg_at_1000
value: 56.989999999999995
- type: ndcg_at_3
value: 42.935
- type: ndcg_at_5
value: 47.833999999999996
- type: precision_at_1
value: 29.445
- type: precision_at_10
value: 7.8950000000000005
- type: precision_at_100
value: 0.979
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 17.591
- type: precision_at_5
value: 12.959000000000001
- type: recall_at_1
value: 29.445
- type: recall_at_10
value: 78.947
- type: recall_at_100
value: 97.937
- type: recall_at_1000
value: 99.502
- type: recall_at_3
value: 52.774
- type: recall_at_5
value: 64.794
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 43.85187820924144
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 29.5939502757938
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 58.539409343284674
- type: mrr
value: 71.58982983775228
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 82.31440765254087
- type: cos_sim_spearman
value: 81.59884723689632
- type: euclidean_pearson
value: 80.65818473893147
- type: euclidean_spearman
value: 81.40004752638717
- type: manhattan_pearson
value: 80.52256901536644
- type: manhattan_spearman
value: 80.57292024599603
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 79.98376623376623
- type: f1
value: 79.91981901371503
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 37.79541356345093
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 26.760513681350375
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.794
- type: map_at_10
value: 33.361000000000004
- type: map_at_100
value: 34.86
- type: map_at_1000
value: 35
- type: map_at_3
value: 30.579
- type: map_at_5
value: 31.996000000000002
- type: mrr_at_1
value: 30.186
- type: mrr_at_10
value: 39.681
- type: mrr_at_100
value: 40.616
- type: mrr_at_1000
value: 40.669
- type: mrr_at_3
value: 37.244
- type: mrr_at_5
value: 38.588
- type: ndcg_at_1
value: 30.186
- type: ndcg_at_10
value: 39.34
- type: ndcg_at_100
value: 45.266
- type: ndcg_at_1000
value: 47.9
- type: ndcg_at_3
value: 35.164
- type: ndcg_at_5
value: 36.854
- type: precision_at_1
value: 30.186
- type: precision_at_10
value: 7.639
- type: precision_at_100
value: 1.328
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 17.31
- type: precision_at_5
value: 12.275
- type: recall_at_1
value: 23.794
- type: recall_at_10
value: 50.463
- type: recall_at_100
value: 75.268
- type: recall_at_1000
value: 93.138
- type: recall_at_3
value: 37.797
- type: recall_at_5
value: 42.985
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.968999999999998
- type: map_at_10
value: 23.846999999999998
- type: map_at_100
value: 24.712999999999997
- type: map_at_1000
value: 24.833
- type: map_at_3
value: 22.024
- type: map_at_5
value: 23.087
- type: mrr_at_1
value: 22.038
- type: mrr_at_10
value: 27.808
- type: mrr_at_100
value: 28.532999999999998
- type: mrr_at_1000
value: 28.604000000000003
- type: mrr_at_3
value: 26.029999999999998
- type: mrr_at_5
value: 27.122
- type: ndcg_at_1
value: 22.038
- type: ndcg_at_10
value: 27.559
- type: ndcg_at_100
value: 31.541999999999998
- type: ndcg_at_1000
value: 34.343
- type: ndcg_at_3
value: 24.585
- type: ndcg_at_5
value: 26.026
- type: precision_at_1
value: 22.038
- type: precision_at_10
value: 5.019
- type: precision_at_100
value: 0.8920000000000001
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 11.423
- type: precision_at_5
value: 8.28
- type: recall_at_1
value: 17.968999999999998
- type: recall_at_10
value: 34.583000000000006
- type: recall_at_100
value: 51.849000000000004
- type: recall_at_1000
value: 70.832
- type: recall_at_3
value: 26.057000000000002
- type: recall_at_5
value: 29.816
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.183999999999997
- type: map_at_10
value: 40.245
- type: map_at_100
value: 41.324
- type: map_at_1000
value: 41.402
- type: map_at_3
value: 37.395
- type: map_at_5
value: 38.964999999999996
- type: mrr_at_1
value: 33.981
- type: mrr_at_10
value: 43.471
- type: mrr_at_100
value: 44.303
- type: mrr_at_1000
value: 44.352999999999994
- type: mrr_at_3
value: 41.149
- type: mrr_at_5
value: 42.466
- type: ndcg_at_1
value: 33.981
- type: ndcg_at_10
value: 45.776
- type: ndcg_at_100
value: 50.441
- type: ndcg_at_1000
value: 52.16
- type: ndcg_at_3
value: 40.756
- type: ndcg_at_5
value: 43.132
- type: precision_at_1
value: 33.981
- type: precision_at_10
value: 7.617999999999999
- type: precision_at_100
value: 1.083
- type: precision_at_1000
value: 0.129
- type: precision_at_3
value: 18.558
- type: precision_at_5
value: 12.915
- type: recall_at_1
value: 29.183999999999997
- type: recall_at_10
value: 59.114
- type: recall_at_100
value: 79.549
- type: recall_at_1000
value: 91.925
- type: recall_at_3
value: 45.551
- type: recall_at_5
value: 51.38399999999999
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.286
- type: map_at_10
value: 27.143
- type: map_at_100
value: 28.107
- type: map_at_1000
value: 28.212
- type: map_at_3
value: 25.149
- type: map_at_5
value: 26.179999999999996
- type: mrr_at_1
value: 22.034000000000002
- type: mrr_at_10
value: 28.875
- type: mrr_at_100
value: 29.785
- type: mrr_at_1000
value: 29.876
- type: mrr_at_3
value: 27.023999999999997
- type: mrr_at_5
value: 28.058
- type: ndcg_at_1
value: 22.034000000000002
- type: ndcg_at_10
value: 31.148999999999997
- type: ndcg_at_100
value: 35.936
- type: ndcg_at_1000
value: 38.682
- type: ndcg_at_3
value: 27.230999999999998
- type: ndcg_at_5
value: 29.034
- type: precision_at_1
value: 22.034000000000002
- type: precision_at_10
value: 4.836
- type: precision_at_100
value: 0.754
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 11.562999999999999
- type: precision_at_5
value: 8.068
- type: recall_at_1
value: 20.286
- type: recall_at_10
value: 41.827999999999996
- type: recall_at_100
value: 63.922000000000004
- type: recall_at_1000
value: 84.639
- type: recall_at_3
value: 31.227
- type: recall_at_5
value: 35.546
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 13.488
- type: map_at_10
value: 18.595
- type: map_at_100
value: 19.783
- type: map_at_1000
value: 19.918
- type: map_at_3
value: 16.274
- type: map_at_5
value: 17.558
- type: mrr_at_1
value: 16.791
- type: mrr_at_10
value: 22.53
- type: mrr_at_100
value: 23.651
- type: mrr_at_1000
value: 23.738999999999997
- type: mrr_at_3
value: 20.232
- type: mrr_at_5
value: 21.644
- type: ndcg_at_1
value: 16.791
- type: ndcg_at_10
value: 22.672
- type: ndcg_at_100
value: 28.663
- type: ndcg_at_1000
value: 31.954
- type: ndcg_at_3
value: 18.372
- type: ndcg_at_5
value: 20.47
- type: precision_at_1
value: 16.791
- type: precision_at_10
value: 4.2540000000000004
- type: precision_at_100
value: 0.8370000000000001
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 8.706
- type: precision_at_5
value: 6.666999999999999
- type: recall_at_1
value: 13.488
- type: recall_at_10
value: 31.451
- type: recall_at_100
value: 58.085
- type: recall_at_1000
value: 81.792
- type: recall_at_3
value: 19.811
- type: recall_at_5
value: 24.973
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.436
- type: map_at_10
value: 29.105999999999998
- type: map_at_100
value: 30.442000000000004
- type: map_at_1000
value: 30.567
- type: map_at_3
value: 26.430999999999997
- type: map_at_5
value: 27.866000000000003
- type: mrr_at_1
value: 26.083000000000002
- type: mrr_at_10
value: 33.975
- type: mrr_at_100
value: 35.014
- type: mrr_at_1000
value: 35.07
- type: mrr_at_3
value: 31.649
- type: mrr_at_5
value: 32.944
- type: ndcg_at_1
value: 26.083000000000002
- type: ndcg_at_10
value: 34.229
- type: ndcg_at_100
value: 40.439
- type: ndcg_at_1000
value: 43.081
- type: ndcg_at_3
value: 29.64
- type: ndcg_at_5
value: 31.704
- type: precision_at_1
value: 26.083000000000002
- type: precision_at_10
value: 6.246
- type: precision_at_100
value: 1.1199999999999999
- type: precision_at_1000
value: 0.155
- type: precision_at_3
value: 13.858999999999998
- type: precision_at_5
value: 10.01
- type: recall_at_1
value: 21.436
- type: recall_at_10
value: 44.938
- type: recall_at_100
value: 72.029
- type: recall_at_1000
value: 90.009
- type: recall_at_3
value: 31.954
- type: recall_at_5
value: 37.303
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.217
- type: map_at_10
value: 25.16
- type: map_at_100
value: 26.490000000000002
- type: map_at_1000
value: 26.619
- type: map_at_3
value: 22.926
- type: map_at_5
value: 24.251
- type: mrr_at_1
value: 22.831000000000003
- type: mrr_at_10
value: 30.009000000000004
- type: mrr_at_100
value: 31.045
- type: mrr_at_1000
value: 31.122
- type: mrr_at_3
value: 28.025
- type: mrr_at_5
value: 29.07
- type: ndcg_at_1
value: 22.831000000000003
- type: ndcg_at_10
value: 29.664
- type: ndcg_at_100
value: 35.900999999999996
- type: ndcg_at_1000
value: 38.932
- type: ndcg_at_3
value: 26.051000000000002
- type: ndcg_at_5
value: 27.741
- type: precision_at_1
value: 22.831000000000003
- type: precision_at_10
value: 5.479
- type: precision_at_100
value: 1.027
- type: precision_at_1000
value: 0.146
- type: precision_at_3
value: 12.481
- type: precision_at_5
value: 8.973
- type: recall_at_1
value: 18.217
- type: recall_at_10
value: 38.336
- type: recall_at_100
value: 65.854
- type: recall_at_1000
value: 87.498
- type: recall_at_3
value: 28.158
- type: recall_at_5
value: 32.841
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.100666666666665
- type: map_at_10
value: 26.22883333333333
- type: map_at_100
value: 27.34241666666667
- type: map_at_1000
value: 27.468416666666666
- type: map_at_3
value: 23.953916666666668
- type: map_at_5
value: 25.20125
- type: mrr_at_1
value: 22.729249999999997
- type: mrr_at_10
value: 29.86491666666667
- type: mrr_at_100
value: 30.76925
- type: mrr_at_1000
value: 30.846333333333337
- type: mrr_at_3
value: 27.733999999999998
- type: mrr_at_5
value: 28.94058333333333
- type: ndcg_at_1
value: 22.729249999999997
- type: ndcg_at_10
value: 30.708250000000003
- type: ndcg_at_100
value: 35.89083333333333
- type: ndcg_at_1000
value: 38.75891666666666
- type: ndcg_at_3
value: 26.661083333333334
- type: ndcg_at_5
value: 28.54
- type: precision_at_1
value: 22.729249999999997
- type: precision_at_10
value: 5.433833333333333
- type: precision_at_100
value: 0.9486666666666665
- type: precision_at_1000
value: 0.13808333333333334
- type: precision_at_3
value: 12.292166666666668
- type: precision_at_5
value: 8.825
- type: recall_at_1
value: 19.100666666666665
- type: recall_at_10
value: 40.54208333333334
- type: recall_at_100
value: 63.67975
- type: recall_at_1000
value: 84.13574999999999
- type: recall_at_3
value: 29.311000000000003
- type: recall_at_5
value: 34.1105
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.762
- type: map_at_10
value: 23.905
- type: map_at_100
value: 24.663
- type: map_at_1000
value: 24.765
- type: map_at_3
value: 22.032
- type: map_at_5
value: 23.025000000000002
- type: mrr_at_1
value: 20.244999999999997
- type: mrr_at_10
value: 26.162999999999997
- type: mrr_at_100
value: 26.907999999999998
- type: mrr_at_1000
value: 26.987
- type: mrr_at_3
value: 24.361
- type: mrr_at_5
value: 25.326999999999998
- type: ndcg_at_1
value: 20.244999999999997
- type: ndcg_at_10
value: 27.577
- type: ndcg_at_100
value: 31.473000000000003
- type: ndcg_at_1000
value: 34.217999999999996
- type: ndcg_at_3
value: 24.092
- type: ndcg_at_5
value: 25.657000000000004
- type: precision_at_1
value: 20.244999999999997
- type: precision_at_10
value: 4.433
- type: precision_at_100
value: 0.692
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 10.634
- type: precision_at_5
value: 7.362
- type: recall_at_1
value: 17.762
- type: recall_at_10
value: 36.661
- type: recall_at_100
value: 54.581999999999994
- type: recall_at_1000
value: 75.28099999999999
- type: recall_at_3
value: 27.084999999999997
- type: recall_at_5
value: 31.064999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 12.998000000000001
- type: map_at_10
value: 18.926000000000002
- type: map_at_100
value: 19.836000000000002
- type: map_at_1000
value: 19.96
- type: map_at_3
value: 16.932
- type: map_at_5
value: 17.963
- type: mrr_at_1
value: 15.692
- type: mrr_at_10
value: 22.206
- type: mrr_at_100
value: 23.021
- type: mrr_at_1000
value: 23.108999999999998
- type: mrr_at_3
value: 20.114
- type: mrr_at_5
value: 21.241
- type: ndcg_at_1
value: 15.692
- type: ndcg_at_10
value: 22.997999999999998
- type: ndcg_at_100
value: 27.541
- type: ndcg_at_1000
value: 30.758000000000003
- type: ndcg_at_3
value: 19.117
- type: ndcg_at_5
value: 20.778
- type: precision_at_1
value: 15.692
- type: precision_at_10
value: 4.277
- type: precision_at_100
value: 0.774
- type: precision_at_1000
value: 0.122
- type: precision_at_3
value: 9.027000000000001
- type: precision_at_5
value: 6.641
- type: recall_at_1
value: 12.998000000000001
- type: recall_at_10
value: 32.135999999999996
- type: recall_at_100
value: 52.937
- type: recall_at_1000
value: 76.348
- type: recall_at_3
value: 21.292
- type: recall_at_5
value: 25.439
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.219
- type: map_at_10
value: 27.306
- type: map_at_100
value: 28.337
- type: map_at_1000
value: 28.459
- type: map_at_3
value: 25.423000000000002
- type: map_at_5
value: 26.375999999999998
- type: mrr_at_1
value: 23.787
- type: mrr_at_10
value: 30.977
- type: mrr_at_100
value: 31.85
- type: mrr_at_1000
value: 31.939
- type: mrr_at_3
value: 29.073
- type: mrr_at_5
value: 30.095
- type: ndcg_at_1
value: 23.787
- type: ndcg_at_10
value: 31.615
- type: ndcg_at_100
value: 36.641
- type: ndcg_at_1000
value: 39.707
- type: ndcg_at_3
value: 27.994000000000003
- type: ndcg_at_5
value: 29.508000000000003
- type: precision_at_1
value: 23.787
- type: precision_at_10
value: 5.271
- type: precision_at_100
value: 0.865
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 12.748999999999999
- type: precision_at_5
value: 8.806
- type: recall_at_1
value: 20.219
- type: recall_at_10
value: 41.108
- type: recall_at_100
value: 63.596
- type: recall_at_1000
value: 85.54899999999999
- type: recall_at_3
value: 31.129
- type: recall_at_5
value: 34.845
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.949
- type: map_at_10
value: 26.629
- type: map_at_100
value: 28.006999999999998
- type: map_at_1000
value: 28.221
- type: map_at_3
value: 24.099999999999998
- type: map_at_5
value: 25.487
- type: mrr_at_1
value: 24.111
- type: mrr_at_10
value: 30.592000000000002
- type: mrr_at_100
value: 31.448999999999998
- type: mrr_at_1000
value: 31.538
- type: mrr_at_3
value: 28.128999999999998
- type: mrr_at_5
value: 29.503
- type: ndcg_at_1
value: 24.111
- type: ndcg_at_10
value: 31.373
- type: ndcg_at_100
value: 36.897999999999996
- type: ndcg_at_1000
value: 40.288000000000004
- type: ndcg_at_3
value: 26.895000000000003
- type: ndcg_at_5
value: 29.009
- type: precision_at_1
value: 24.111
- type: precision_at_10
value: 6.067
- type: precision_at_100
value: 1.269
- type: precision_at_1000
value: 0.22
- type: precision_at_3
value: 12.385
- type: precision_at_5
value: 9.249
- type: recall_at_1
value: 19.949
- type: recall_at_10
value: 40.394000000000005
- type: recall_at_100
value: 65.812
- type: recall_at_1000
value: 88.247
- type: recall_at_3
value: 28.116000000000003
- type: recall_at_5
value: 33.4
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 13.905999999999999
- type: map_at_10
value: 20.523
- type: map_at_100
value: 21.547
- type: map_at_1000
value: 21.665
- type: map_at_3
value: 18.182000000000002
- type: map_at_5
value: 19.661
- type: mrr_at_1
value: 14.972
- type: mrr_at_10
value: 22.092
- type: mrr_at_100
value: 23.055999999999997
- type: mrr_at_1000
value: 23.150000000000002
- type: mrr_at_3
value: 19.778000000000002
- type: mrr_at_5
value: 21.229
- type: ndcg_at_1
value: 14.972
- type: ndcg_at_10
value: 24.547
- type: ndcg_at_100
value: 29.948999999999998
- type: ndcg_at_1000
value: 33.084
- type: ndcg_at_3
value: 20.036
- type: ndcg_at_5
value: 22.567
- type: precision_at_1
value: 14.972
- type: precision_at_10
value: 4.067
- type: precision_at_100
value: 0.743
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 8.811
- type: precision_at_5
value: 6.654
- type: recall_at_1
value: 13.905999999999999
- type: recall_at_10
value: 35.493
- type: recall_at_100
value: 60.67399999999999
- type: recall_at_1000
value: 84.371
- type: recall_at_3
value: 23.555
- type: recall_at_5
value: 29.729
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.529
- type: map_at_10
value: 12.794
- type: map_at_100
value: 14.315
- type: map_at_1000
value: 14.523
- type: map_at_3
value: 10.367999999999999
- type: map_at_5
value: 11.546
- type: mrr_at_1
value: 16.872999999999998
- type: mrr_at_10
value: 25.709
- type: mrr_at_100
value: 26.907999999999998
- type: mrr_at_1000
value: 26.962000000000003
- type: mrr_at_3
value: 22.486
- type: mrr_at_5
value: 24.245
- type: ndcg_at_1
value: 16.872999999999998
- type: ndcg_at_10
value: 19.005
- type: ndcg_at_100
value: 25.990999999999996
- type: ndcg_at_1000
value: 29.955
- type: ndcg_at_3
value: 14.573
- type: ndcg_at_5
value: 16.118
- type: precision_at_1
value: 16.872999999999998
- type: precision_at_10
value: 6.235
- type: precision_at_100
value: 1.374
- type: precision_at_1000
value: 0.21
- type: precision_at_3
value: 10.793
- type: precision_at_5
value: 8.73
- type: recall_at_1
value: 7.529
- type: recall_at_10
value: 24.007
- type: recall_at_100
value: 48.742000000000004
- type: recall_at_1000
value: 71.35000000000001
- type: recall_at_3
value: 13.467
- type: recall_at_5
value: 17.502000000000002
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.614
- type: map_at_10
value: 11.42
- type: map_at_100
value: 15.873000000000001
- type: map_at_1000
value: 17.021
- type: map_at_3
value: 8.495
- type: map_at_5
value: 9.790000000000001
- type: mrr_at_1
value: 42
- type: mrr_at_10
value: 52.477
- type: mrr_at_100
value: 53.095000000000006
- type: mrr_at_1000
value: 53.135
- type: mrr_at_3
value: 49.833
- type: mrr_at_5
value: 51.183
- type: ndcg_at_1
value: 31.374999999999996
- type: ndcg_at_10
value: 25.27
- type: ndcg_at_100
value: 29.709999999999997
- type: ndcg_at_1000
value: 36.975
- type: ndcg_at_3
value: 27.688000000000002
- type: ndcg_at_5
value: 25.987
- type: precision_at_1
value: 42
- type: precision_at_10
value: 21.2
- type: precision_at_100
value: 7.053
- type: precision_at_1000
value: 1.512
- type: precision_at_3
value: 32.333
- type: precision_at_5
value: 26.6
- type: recall_at_1
value: 5.614
- type: recall_at_10
value: 16.112000000000002
- type: recall_at_100
value: 36.165000000000006
- type: recall_at_1000
value: 60.362
- type: recall_at_3
value: 9.761000000000001
- type: recall_at_5
value: 12.279
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 40.085
- type: f1
value: 35.53934111316537
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 34.185
- type: map_at_10
value: 44.491
- type: map_at_100
value: 45.204
- type: map_at_1000
value: 45.254
- type: map_at_3
value: 42.006
- type: map_at_5
value: 43.516
- type: mrr_at_1
value: 37.024
- type: mrr_at_10
value: 47.524
- type: mrr_at_100
value: 48.185
- type: mrr_at_1000
value: 48.227
- type: mrr_at_3
value: 45.086999999999996
- type: mrr_at_5
value: 46.575
- type: ndcg_at_1
value: 37.024
- type: ndcg_at_10
value: 50.126000000000005
- type: ndcg_at_100
value: 53.577
- type: ndcg_at_1000
value: 54.906
- type: ndcg_at_3
value: 45.25
- type: ndcg_at_5
value: 47.842
- type: precision_at_1
value: 37.024
- type: precision_at_10
value: 7.132
- type: precision_at_100
value: 0.898
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 18.767
- type: precision_at_5
value: 12.676000000000002
- type: recall_at_1
value: 34.185
- type: recall_at_10
value: 64.703
- type: recall_at_100
value: 80.58
- type: recall_at_1000
value: 90.742
- type: recall_at_3
value: 51.483000000000004
- type: recall_at_5
value: 57.775
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.358
- type: map_at_10
value: 16.391
- type: map_at_100
value: 17.698
- type: map_at_1000
value: 17.912
- type: map_at_3
value: 13.831
- type: map_at_5
value: 15.187000000000001
- type: mrr_at_1
value: 18.673000000000002
- type: mrr_at_10
value: 26.907999999999998
- type: mrr_at_100
value: 27.842
- type: mrr_at_1000
value: 27.933000000000003
- type: mrr_at_3
value: 24.486
- type: mrr_at_5
value: 25.766
- type: ndcg_at_1
value: 18.673000000000002
- type: ndcg_at_10
value: 22.137
- type: ndcg_at_100
value: 28.126
- type: ndcg_at_1000
value: 32.489000000000004
- type: ndcg_at_3
value: 18.723
- type: ndcg_at_5
value: 19.858
- type: precision_at_1
value: 18.673000000000002
- type: precision_at_10
value: 6.389
- type: precision_at_100
value: 1.262
- type: precision_at_1000
value: 0.202
- type: precision_at_3
value: 12.757
- type: precision_at_5
value: 9.753
- type: recall_at_1
value: 9.358
- type: recall_at_10
value: 28.605000000000004
- type: recall_at_100
value: 51.713
- type: recall_at_1000
value: 78.408
- type: recall_at_3
value: 17.674
- type: recall_at_5
value: 21.97
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.997999999999998
- type: map_at_10
value: 32.957
- type: map_at_100
value: 33.972
- type: map_at_1000
value: 34.072
- type: map_at_3
value: 30.44
- type: map_at_5
value: 31.869999999999997
- type: mrr_at_1
value: 45.995999999999995
- type: mrr_at_10
value: 54.473000000000006
- type: mrr_at_100
value: 55.103
- type: mrr_at_1000
value: 55.139
- type: mrr_at_3
value: 52.349999999999994
- type: mrr_at_5
value: 53.61900000000001
- type: ndcg_at_1
value: 45.995999999999995
- type: ndcg_at_10
value: 41.333
- type: ndcg_at_100
value: 45.635999999999996
- type: ndcg_at_1000
value: 47.847
- type: ndcg_at_3
value: 36.825
- type: ndcg_at_5
value: 39.099000000000004
- type: precision_at_1
value: 45.995999999999995
- type: precision_at_10
value: 9.020999999999999
- type: precision_at_100
value: 1.244
- type: precision_at_1000
value: 0.154
- type: precision_at_3
value: 23.34
- type: precision_at_5
value: 15.8
- type: recall_at_1
value: 22.997999999999998
- type: recall_at_10
value: 45.105000000000004
- type: recall_at_100
value: 62.188
- type: recall_at_1000
value: 76.907
- type: recall_at_3
value: 35.010000000000005
- type: recall_at_5
value: 39.5
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 80.0944
- type: ap
value: 74.43301569395831
- type: f1
value: 80.04407647044388
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 10.171
- type: map_at_10
value: 17.558
- type: map_at_100
value: 18.694
- type: map_at_1000
value: 18.787000000000003
- type: map_at_3
value: 14.826
- type: map_at_5
value: 16.249
- type: mrr_at_1
value: 10.473
- type: mrr_at_10
value: 17.967
- type: mrr_at_100
value: 19.089
- type: mrr_at_1000
value: 19.177
- type: mrr_at_3
value: 15.222
- type: mrr_at_5
value: 16.655
- type: ndcg_at_1
value: 10.473
- type: ndcg_at_10
value: 22.148
- type: ndcg_at_100
value: 28.028
- type: ndcg_at_1000
value: 30.659
- type: ndcg_at_3
value: 16.474
- type: ndcg_at_5
value: 19.017
- type: precision_at_1
value: 10.473
- type: precision_at_10
value: 3.7969999999999997
- type: precision_at_100
value: 0.6779999999999999
- type: precision_at_1000
value: 0.09
- type: precision_at_3
value: 7.187
- type: precision_at_5
value: 5.599
- type: recall_at_1
value: 10.171
- type: recall_at_10
value: 36.459
- type: recall_at_100
value: 64.512
- type: recall_at_1000
value: 85.27900000000001
- type: recall_at_3
value: 20.868000000000002
- type: recall_at_5
value: 26.933
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 90.35795713634292
- type: f1
value: 89.72064544336776
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 66.4546283629731
- type: f1
value: 49.487271168215095
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 67.58238063214527
- type: f1
value: 65.54281371907213
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 73.47343644922664
- type: f1
value: 72.80522894672785
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 32.53600917473176
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 28.04699774280647
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.984352865575797
- type: mrr
value: 32.02736001972659
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.666
- type: map_at_10
value: 10.066
- type: map_at_100
value: 12.794
- type: map_at_1000
value: 14.184
- type: map_at_3
value: 7.622
- type: map_at_5
value: 8.587
- type: mrr_at_1
value: 39.318999999999996
- type: mrr_at_10
value: 47.678
- type: mrr_at_100
value: 48.355
- type: mrr_at_1000
value: 48.400999999999996
- type: mrr_at_3
value: 45.82
- type: mrr_at_5
value: 46.656
- type: ndcg_at_1
value: 37.926
- type: ndcg_at_10
value: 29.049999999999997
- type: ndcg_at_100
value: 26.826
- type: ndcg_at_1000
value: 35.841
- type: ndcg_at_3
value: 33.513
- type: ndcg_at_5
value: 31.227
- type: precision_at_1
value: 39.318999999999996
- type: precision_at_10
value: 21.424000000000003
- type: precision_at_100
value: 7.231999999999999
- type: precision_at_1000
value: 2.012
- type: precision_at_3
value: 30.857
- type: precision_at_5
value: 26.378
- type: recall_at_1
value: 4.666
- type: recall_at_10
value: 13.898
- type: recall_at_100
value: 26.983
- type: recall_at_1000
value: 59.485
- type: recall_at_3
value: 8.953
- type: recall_at_5
value: 10.496
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.26
- type: map_at_10
value: 17.907999999999998
- type: map_at_100
value: 19.245
- type: map_at_1000
value: 19.339000000000002
- type: map_at_3
value: 14.634
- type: map_at_5
value: 16.386
- type: mrr_at_1
value: 10.574
- type: mrr_at_10
value: 19.438
- type: mrr_at_100
value: 20.638
- type: mrr_at_1000
value: 20.715
- type: mrr_at_3
value: 16.276
- type: mrr_at_5
value: 17.971999999999998
- type: ndcg_at_1
value: 10.574
- type: ndcg_at_10
value: 23.451
- type: ndcg_at_100
value: 29.982
- type: ndcg_at_1000
value: 32.449
- type: ndcg_at_3
value: 16.817
- type: ndcg_at_5
value: 19.867
- type: precision_at_1
value: 10.574
- type: precision_at_10
value: 4.609
- type: precision_at_100
value: 0.8330000000000001
- type: precision_at_1000
value: 0.107
- type: precision_at_3
value: 8.266
- type: precision_at_5
value: 6.6739999999999995
- type: recall_at_1
value: 9.26
- type: recall_at_10
value: 39.224
- type: recall_at_100
value: 69.107
- type: recall_at_1000
value: 87.908
- type: recall_at_3
value: 21.490000000000002
- type: recall_at_5
value: 28.560999999999996
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 65.655
- type: map_at_10
value: 79.199
- type: map_at_100
value: 79.937
- type: map_at_1000
value: 79.964
- type: map_at_3
value: 76.19399999999999
- type: map_at_5
value: 78.08800000000001
- type: mrr_at_1
value: 75.53999999999999
- type: mrr_at_10
value: 82.89
- type: mrr_at_100
value: 83.074
- type: mrr_at_1000
value: 83.077
- type: mrr_at_3
value: 81.577
- type: mrr_at_5
value: 82.452
- type: ndcg_at_1
value: 75.53999999999999
- type: ndcg_at_10
value: 83.62899999999999
- type: ndcg_at_100
value: 85.411
- type: ndcg_at_1000
value: 85.646
- type: ndcg_at_3
value: 80.23700000000001
- type: ndcg_at_5
value: 82.107
- type: precision_at_1
value: 75.53999999999999
- type: precision_at_10
value: 12.695
- type: precision_at_100
value: 1.493
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 34.983
- type: precision_at_5
value: 23.164
- type: recall_at_1
value: 65.655
- type: recall_at_10
value: 92.269
- type: recall_at_100
value: 98.598
- type: recall_at_1000
value: 99.815
- type: recall_at_3
value: 82.616
- type: recall_at_5
value: 87.75800000000001
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 43.67844919460687
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 54.32866004447611
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.238
- type: map_at_10
value: 8.539
- type: map_at_100
value: 10.267
- type: map_at_1000
value: 10.552999999999999
- type: map_at_3
value: 6.165
- type: map_at_5
value: 7.22
- type: mrr_at_1
value: 15.9
- type: mrr_at_10
value: 25.557999999999996
- type: mrr_at_100
value: 26.867
- type: mrr_at_1000
value: 26.939
- type: mrr_at_3
value: 22.633
- type: mrr_at_5
value: 24.233
- type: ndcg_at_1
value: 15.9
- type: ndcg_at_10
value: 14.954
- type: ndcg_at_100
value: 22.486
- type: ndcg_at_1000
value: 27.986
- type: ndcg_at_3
value: 14.069
- type: ndcg_at_5
value: 12.200999999999999
- type: precision_at_1
value: 15.9
- type: precision_at_10
value: 7.9399999999999995
- type: precision_at_100
value: 1.8929999999999998
- type: precision_at_1000
value: 0.32299999999999995
- type: precision_at_3
value: 13.5
- type: precision_at_5
value: 10.9
- type: recall_at_1
value: 3.238
- type: recall_at_10
value: 16.1
- type: recall_at_100
value: 38.427
- type: recall_at_1000
value: 65.498
- type: recall_at_3
value: 8.212
- type: recall_at_5
value: 11.032
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 80.7612029200118
- type: cos_sim_spearman
value: 74.17706899450974
- type: euclidean_pearson
value: 78.6240925347838
- type: euclidean_spearman
value: 74.22104652352341
- type: manhattan_pearson
value: 78.49956480878576
- type: manhattan_spearman
value: 74.0528957569391
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 80.0377294417705
- type: cos_sim_spearman
value: 72.19570903733732
- type: euclidean_pearson
value: 77.060604990743
- type: euclidean_spearman
value: 71.54251658956483
- type: manhattan_pearson
value: 77.28301977645965
- type: manhattan_spearman
value: 71.77449045278667
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 79.69841558517969
- type: cos_sim_spearman
value: 80.54022353649157
- type: euclidean_pearson
value: 80.03651743688496
- type: euclidean_spearman
value: 80.45116824930123
- type: manhattan_pearson
value: 79.89688370680031
- type: manhattan_spearman
value: 80.27208259746283
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 79.92235427443056
- type: cos_sim_spearman
value: 76.20243980748161
- type: euclidean_pearson
value: 79.28031963400572
- type: euclidean_spearman
value: 76.3568261868673
- type: manhattan_pearson
value: 79.24527845959733
- type: manhattan_spearman
value: 76.39886696744185
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 84.2762365324788
- type: cos_sim_spearman
value: 85.19929628214842
- type: euclidean_pearson
value: 84.82568872953075
- type: euclidean_spearman
value: 85.11039387706913
- type: manhattan_pearson
value: 84.72922084197847
- type: manhattan_spearman
value: 85.04448532444505
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 80.23256564746382
- type: cos_sim_spearman
value: 81.92968415429543
- type: euclidean_pearson
value: 81.12612888308936
- type: euclidean_spearman
value: 81.97396557448675
- type: manhattan_pearson
value: 81.15685601512081
- type: manhattan_spearman
value: 82.01929408689
- 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: 85.35057935029289
- type: cos_sim_spearman
value: 86.60658025867397
- type: euclidean_pearson
value: 86.48666975508912
- type: euclidean_spearman
value: 86.70310223264862
- type: manhattan_pearson
value: 86.23959282751626
- type: manhattan_spearman
value: 86.48318896577922
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 63.15375299804011
- type: cos_sim_spearman
value: 65.4588500819246
- type: euclidean_pearson
value: 65.60180021985416
- type: euclidean_spearman
value: 65.55596512146833
- type: manhattan_pearson
value: 66.12421335157649
- type: manhattan_spearman
value: 66.05163838991123
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 81.82391915730462
- type: cos_sim_spearman
value: 81.93942545767499
- type: euclidean_pearson
value: 83.16752744889406
- type: euclidean_spearman
value: 82.31380947581034
- type: manhattan_pearson
value: 82.98915741609575
- type: manhattan_spearman
value: 82.16585239338073
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 77.19504204180527
- type: mrr
value: 92.85429983959396
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 49.528
- type: map_at_10
value: 57.62199999999999
- type: map_at_100
value: 58.544
- type: map_at_1000
value: 58.573
- type: map_at_3
value: 54.56999999999999
- type: map_at_5
value: 56.552
- type: mrr_at_1
value: 52
- type: mrr_at_10
value: 58.939
- type: mrr_at_100
value: 59.653
- type: mrr_at_1000
value: 59.68
- type: mrr_at_3
value: 56.389
- type: mrr_at_5
value: 57.989000000000004
- type: ndcg_at_1
value: 52
- type: ndcg_at_10
value: 61.964
- type: ndcg_at_100
value: 65.871
- type: ndcg_at_1000
value: 66.724
- type: ndcg_at_3
value: 56.621
- type: ndcg_at_5
value: 59.551
- type: precision_at_1
value: 52
- type: precision_at_10
value: 8.333
- type: precision_at_100
value: 1.04
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 21.778
- type: precision_at_5
value: 14.933
- type: recall_at_1
value: 49.528
- type: recall_at_10
value: 74.2
- type: recall_at_100
value: 91.5
- type: recall_at_1000
value: 98.333
- type: recall_at_3
value: 60.06700000000001
- type: recall_at_5
value: 67.133
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81287128712871
- type: cos_sim_ap
value: 95.15039468118793
- type: cos_sim_f1
value: 90.48817312531455
- type: cos_sim_precision
value: 91.08409321175279
- type: cos_sim_recall
value: 89.9
- type: dot_accuracy
value: 99.78019801980199
- type: dot_ap
value: 93.60256835857994
- type: dot_f1
value: 88.73096446700508
- type: dot_precision
value: 90.10309278350516
- type: dot_recall
value: 87.4
- type: euclidean_accuracy
value: 99.81188118811882
- type: euclidean_ap
value: 95.15954231276913
- type: euclidean_f1
value: 90.48096192384769
- type: euclidean_precision
value: 90.66265060240963
- type: euclidean_recall
value: 90.3
- type: manhattan_accuracy
value: 99.81188118811882
- type: manhattan_ap
value: 95.17107000565468
- type: manhattan_f1
value: 90.5
- type: manhattan_precision
value: 90.5
- type: manhattan_recall
value: 90.5
- type: max_accuracy
value: 99.81287128712871
- type: max_ap
value: 95.17107000565468
- type: max_f1
value: 90.5
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 51.77488276525734
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.30657214418171
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 47.84571922992432
- type: mrr
value: 48.549107142857146
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 29.840750357585556
- type: cos_sim_spearman
value: 29.832953864936567
- type: dot_pearson
value: 30.499687946740657
- type: dot_spearman
value: 30.73436062481656
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.16999999999999998
- type: map_at_10
value: 1.014
- type: map_at_100
value: 5.623
- type: map_at_1000
value: 15.190999999999999
- type: map_at_3
value: 0.377
- type: map_at_5
value: 0.577
- type: mrr_at_1
value: 68
- type: mrr_at_10
value: 74.45
- type: mrr_at_100
value: 74.846
- type: mrr_at_1000
value: 74.846
- type: mrr_at_3
value: 71.333
- type: mrr_at_5
value: 73.533
- type: ndcg_at_1
value: 64
- type: ndcg_at_10
value: 47.52
- type: ndcg_at_100
value: 37.419999999999995
- type: ndcg_at_1000
value: 36.318
- type: ndcg_at_3
value: 51.13999999999999
- type: ndcg_at_5
value: 49.101
- type: precision_at_1
value: 68
- type: precision_at_10
value: 50.8
- type: precision_at_100
value: 39.160000000000004
- type: precision_at_1000
value: 16.948
- type: precision_at_3
value: 52
- type: precision_at_5
value: 51.6
- type: recall_at_1
value: 0.16999999999999998
- type: recall_at_10
value: 1.269
- type: recall_at_100
value: 8.937000000000001
- type: recall_at_1000
value: 35.036
- type: recall_at_3
value: 0.396
- type: recall_at_5
value: 0.6669999999999999
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.672
- type: map_at_10
value: 6.739000000000001
- type: map_at_100
value: 12.006
- type: map_at_1000
value: 13.474
- type: map_at_3
value: 2.617
- type: map_at_5
value: 4.329000000000001
- type: mrr_at_1
value: 20.408
- type: mrr_at_10
value: 30.764000000000003
- type: mrr_at_100
value: 32.457
- type: mrr_at_1000
value: 32.481
- type: mrr_at_3
value: 26.531
- type: mrr_at_5
value: 28.877999999999997
- type: ndcg_at_1
value: 18.367
- type: ndcg_at_10
value: 17.471999999999998
- type: ndcg_at_100
value: 29.341
- type: ndcg_at_1000
value: 41.005
- type: ndcg_at_3
value: 14.64
- type: ndcg_at_5
value: 17.039
- type: precision_at_1
value: 20.408
- type: precision_at_10
value: 17.551
- type: precision_at_100
value: 6.673
- type: precision_at_1000
value: 1.4160000000000001
- type: precision_at_3
value: 14.966
- type: precision_at_5
value: 18.776
- type: recall_at_1
value: 1.672
- type: recall_at_10
value: 12.795000000000002
- type: recall_at_100
value: 41.289
- type: recall_at_1000
value: 76.947
- type: recall_at_3
value: 3.334
- type: recall_at_5
value: 6.864000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 69.3424
- type: ap
value: 13.45149708639965
- type: f1
value: 53.278180518373574
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 57.60045274476513
- type: f1
value: 57.9395926195531
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 36.649067825169446
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.68599868868093
- type: cos_sim_ap
value: 65.7938550603812
- type: cos_sim_f1
value: 61.81946735800141
- type: cos_sim_precision
value: 55.85604770017035
- type: cos_sim_recall
value: 69.2084432717678
- type: dot_accuracy
value: 82.09453418370389
- type: dot_ap
value: 61.00867337905922
- type: dot_f1
value: 58.56196783349101
- type: dot_precision
value: 53.06472353193313
- type: dot_recall
value: 65.32981530343008
- type: euclidean_accuracy
value: 83.68599868868093
- type: euclidean_ap
value: 66.17065796133883
- type: euclidean_f1
value: 62.440610152538135
- type: euclidean_precision
value: 59.3393536121673
- type: euclidean_recall
value: 65.88390501319262
- type: manhattan_accuracy
value: 83.57870894677237
- type: manhattan_ap
value: 65.89925640001532
- type: manhattan_f1
value: 62.2255119664446
- type: manhattan_precision
value: 58.43373493975904
- type: manhattan_recall
value: 66.54353562005278
- type: max_accuracy
value: 83.68599868868093
- type: max_ap
value: 66.17065796133883
- type: max_f1
value: 62.440610152538135
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 87.68579966623976
- type: cos_sim_ap
value: 83.2666595805096
- type: cos_sim_f1
value: 75.11536297129996
- type: cos_sim_precision
value: 73.24943294065999
- type: cos_sim_recall
value: 77.07884200800738
- type: dot_accuracy
value: 86.76213761788334
- type: dot_ap
value: 80.85199640255004
- type: dot_f1
value: 73.27634898520165
- type: dot_precision
value: 71.70756872282409
- type: dot_recall
value: 74.91530643671081
- type: euclidean_accuracy
value: 87.79640625606395
- type: euclidean_ap
value: 83.52666327503474
- type: euclidean_f1
value: 75.37022886875523
- type: euclidean_precision
value: 71.4522249051397
- type: euclidean_recall
value: 79.74283954419464
- type: manhattan_accuracy
value: 87.80804905499282
- type: manhattan_ap
value: 83.4995899990913
- type: manhattan_f1
value: 75.44320420223242
- type: manhattan_precision
value: 71.68307223069458
- type: manhattan_recall
value: 79.6196489066831
- type: max_accuracy
value: 87.80804905499282
- type: max_ap
value: 83.52666327503474
- type: max_f1
value: 75.44320420223242