metadata
tags:
- mteb
model-index:
- name: e5-small
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 76.22388059701493
- type: ap
value: 40.27466219523129
- type: f1
value: 70.60533006025108
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 87.525775
- type: ap
value: 83.51063993897611
- type: f1
value: 87.49342736805572
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 42.611999999999995
- type: f1
value: 42.05088045932892
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.826
- type: map_at_10
value: 38.269
- type: map_at_100
value: 39.322
- type: map_at_1000
value: 39.344
- type: map_at_3
value: 33.428000000000004
- type: map_at_5
value: 36.063
- type: mrr_at_1
value: 24.253
- type: mrr_at_10
value: 38.425
- type: mrr_at_100
value: 39.478
- type: mrr_at_1000
value: 39.5
- type: mrr_at_3
value: 33.606
- type: mrr_at_5
value: 36.195
- type: ndcg_at_1
value: 23.826
- type: ndcg_at_10
value: 46.693
- type: ndcg_at_100
value: 51.469
- type: ndcg_at_1000
value: 52.002
- type: ndcg_at_3
value: 36.603
- type: ndcg_at_5
value: 41.365
- type: precision_at_1
value: 23.826
- type: precision_at_10
value: 7.383000000000001
- type: precision_at_100
value: 0.9530000000000001
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 15.268
- type: precision_at_5
value: 11.479000000000001
- type: recall_at_1
value: 23.826
- type: recall_at_10
value: 73.82600000000001
- type: recall_at_100
value: 95.306
- type: recall_at_1000
value: 99.431
- type: recall_at_3
value: 45.804
- type: recall_at_5
value: 57.397
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 44.13995374767436
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 37.13950072624313
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 59.35843292105327
- type: mrr
value: 73.72312359846987
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 84.55140418324174
- type: cos_sim_spearman
value: 84.21637675860022
- type: euclidean_pearson
value: 81.26069614610006
- type: euclidean_spearman
value: 83.25069210421785
- type: manhattan_pearson
value: 80.17441422581014
- type: manhattan_spearman
value: 81.87596198487877
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.87337662337661
- type: f1
value: 81.76647866926402
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 35.80600542614507
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 31.86321613256603
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.054
- type: map_at_10
value: 40.699999999999996
- type: map_at_100
value: 41.818
- type: map_at_1000
value: 41.959999999999994
- type: map_at_3
value: 37.742
- type: map_at_5
value: 39.427
- type: mrr_at_1
value: 38.769999999999996
- type: mrr_at_10
value: 46.150000000000006
- type: mrr_at_100
value: 46.865
- type: mrr_at_1000
value: 46.925
- type: mrr_at_3
value: 43.705
- type: mrr_at_5
value: 45.214999999999996
- type: ndcg_at_1
value: 38.769999999999996
- type: ndcg_at_10
value: 45.778
- type: ndcg_at_100
value: 50.38
- type: ndcg_at_1000
value: 52.922999999999995
- type: ndcg_at_3
value: 41.597
- type: ndcg_at_5
value: 43.631
- type: precision_at_1
value: 38.769999999999996
- type: precision_at_10
value: 8.269
- type: precision_at_100
value: 1.278
- type: precision_at_1000
value: 0.178
- type: precision_at_3
value: 19.266
- type: precision_at_5
value: 13.705
- type: recall_at_1
value: 32.054
- type: recall_at_10
value: 54.947
- type: recall_at_100
value: 74.79599999999999
- type: recall_at_1000
value: 91.40899999999999
- type: recall_at_3
value: 42.431000000000004
- type: recall_at_5
value: 48.519
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.035
- type: map_at_10
value: 38.007000000000005
- type: map_at_100
value: 39.125
- type: map_at_1000
value: 39.251999999999995
- type: map_at_3
value: 35.77
- type: map_at_5
value: 37.057
- type: mrr_at_1
value: 36.497
- type: mrr_at_10
value: 44.077
- type: mrr_at_100
value: 44.743
- type: mrr_at_1000
value: 44.79
- type: mrr_at_3
value: 42.123
- type: mrr_at_5
value: 43.308
- type: ndcg_at_1
value: 36.497
- type: ndcg_at_10
value: 42.986000000000004
- type: ndcg_at_100
value: 47.323
- type: ndcg_at_1000
value: 49.624
- type: ndcg_at_3
value: 39.805
- type: ndcg_at_5
value: 41.286
- type: precision_at_1
value: 36.497
- type: precision_at_10
value: 7.8340000000000005
- type: precision_at_100
value: 1.269
- type: precision_at_1000
value: 0.178
- type: precision_at_3
value: 19.023
- type: precision_at_5
value: 13.248
- type: recall_at_1
value: 29.035
- type: recall_at_10
value: 51.06
- type: recall_at_100
value: 69.64099999999999
- type: recall_at_1000
value: 84.49
- type: recall_at_3
value: 41.333999999999996
- type: recall_at_5
value: 45.663
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.239
- type: map_at_10
value: 47.873
- type: map_at_100
value: 48.842999999999996
- type: map_at_1000
value: 48.913000000000004
- type: map_at_3
value: 45.050000000000004
- type: map_at_5
value: 46.498
- type: mrr_at_1
value: 42.508
- type: mrr_at_10
value: 51.44
- type: mrr_at_100
value: 52.087
- type: mrr_at_1000
value: 52.129999999999995
- type: mrr_at_3
value: 49.164
- type: mrr_at_5
value: 50.343
- type: ndcg_at_1
value: 42.508
- type: ndcg_at_10
value: 53.31399999999999
- type: ndcg_at_100
value: 57.245000000000005
- type: ndcg_at_1000
value: 58.794000000000004
- type: ndcg_at_3
value: 48.295
- type: ndcg_at_5
value: 50.415
- type: precision_at_1
value: 42.508
- type: precision_at_10
value: 8.458
- type: precision_at_100
value: 1.133
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 21.191
- type: precision_at_5
value: 14.307
- type: recall_at_1
value: 37.239
- type: recall_at_10
value: 65.99000000000001
- type: recall_at_100
value: 82.99499999999999
- type: recall_at_1000
value: 94.128
- type: recall_at_3
value: 52.382
- type: recall_at_5
value: 57.648999999999994
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.039
- type: map_at_10
value: 29.694
- type: map_at_100
value: 30.587999999999997
- type: map_at_1000
value: 30.692999999999998
- type: map_at_3
value: 27.708
- type: map_at_5
value: 28.774
- type: mrr_at_1
value: 24.633
- type: mrr_at_10
value: 31.478
- type: mrr_at_100
value: 32.299
- type: mrr_at_1000
value: 32.381
- type: mrr_at_3
value: 29.435
- type: mrr_at_5
value: 30.446
- type: ndcg_at_1
value: 24.633
- type: ndcg_at_10
value: 33.697
- type: ndcg_at_100
value: 38.080000000000005
- type: ndcg_at_1000
value: 40.812
- type: ndcg_at_3
value: 29.654000000000003
- type: ndcg_at_5
value: 31.474000000000004
- type: precision_at_1
value: 24.633
- type: precision_at_10
value: 5.0729999999999995
- type: precision_at_100
value: 0.753
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 12.279
- type: precision_at_5
value: 8.452
- type: recall_at_1
value: 23.039
- type: recall_at_10
value: 44.275999999999996
- type: recall_at_100
value: 64.4
- type: recall_at_1000
value: 85.135
- type: recall_at_3
value: 33.394
- type: recall_at_5
value: 37.687
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 13.594999999999999
- type: map_at_10
value: 19.933999999999997
- type: map_at_100
value: 20.966
- type: map_at_1000
value: 21.087
- type: map_at_3
value: 17.749000000000002
- type: map_at_5
value: 19.156000000000002
- type: mrr_at_1
value: 17.662
- type: mrr_at_10
value: 24.407
- type: mrr_at_100
value: 25.385
- type: mrr_at_1000
value: 25.465
- type: mrr_at_3
value: 22.056
- type: mrr_at_5
value: 23.630000000000003
- type: ndcg_at_1
value: 17.662
- type: ndcg_at_10
value: 24.391
- type: ndcg_at_100
value: 29.681
- type: ndcg_at_1000
value: 32.923
- type: ndcg_at_3
value: 20.271
- type: ndcg_at_5
value: 22.621
- type: precision_at_1
value: 17.662
- type: precision_at_10
value: 4.44
- type: precision_at_100
value: 0.8200000000000001
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 9.577
- type: precision_at_5
value: 7.313
- type: recall_at_1
value: 13.594999999999999
- type: recall_at_10
value: 33.976
- type: recall_at_100
value: 57.43000000000001
- type: recall_at_1000
value: 80.958
- type: recall_at_3
value: 22.897000000000002
- type: recall_at_5
value: 28.714000000000002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.683
- type: map_at_10
value: 35.068
- type: map_at_100
value: 36.311
- type: map_at_1000
value: 36.436
- type: map_at_3
value: 32.371
- type: map_at_5
value: 33.761
- type: mrr_at_1
value: 32.435
- type: mrr_at_10
value: 40.721000000000004
- type: mrr_at_100
value: 41.535
- type: mrr_at_1000
value: 41.593
- type: mrr_at_3
value: 38.401999999999994
- type: mrr_at_5
value: 39.567
- type: ndcg_at_1
value: 32.435
- type: ndcg_at_10
value: 40.538000000000004
- type: ndcg_at_100
value: 45.963
- type: ndcg_at_1000
value: 48.400999999999996
- type: ndcg_at_3
value: 36.048
- type: ndcg_at_5
value: 37.899
- type: precision_at_1
value: 32.435
- type: precision_at_10
value: 7.1129999999999995
- type: precision_at_100
value: 1.162
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 16.683
- type: precision_at_5
value: 11.684
- type: recall_at_1
value: 26.683
- type: recall_at_10
value: 51.517
- type: recall_at_100
value: 74.553
- type: recall_at_1000
value: 90.649
- type: recall_at_3
value: 38.495000000000005
- type: recall_at_5
value: 43.495
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.186
- type: map_at_10
value: 31.972
- type: map_at_100
value: 33.117000000000004
- type: map_at_1000
value: 33.243
- type: map_at_3
value: 29.423
- type: map_at_5
value: 30.847
- type: mrr_at_1
value: 29.794999999999998
- type: mrr_at_10
value: 36.767
- type: mrr_at_100
value: 37.645
- type: mrr_at_1000
value: 37.716
- type: mrr_at_3
value: 34.513
- type: mrr_at_5
value: 35.791000000000004
- type: ndcg_at_1
value: 29.794999999999998
- type: ndcg_at_10
value: 36.786
- type: ndcg_at_100
value: 41.94
- type: ndcg_at_1000
value: 44.830999999999996
- type: ndcg_at_3
value: 32.504
- type: ndcg_at_5
value: 34.404
- type: precision_at_1
value: 29.794999999999998
- type: precision_at_10
value: 6.518
- type: precision_at_100
value: 1.0659999999999998
- type: precision_at_1000
value: 0.149
- type: precision_at_3
value: 15.296999999999999
- type: precision_at_5
value: 10.731
- type: recall_at_1
value: 24.186
- type: recall_at_10
value: 46.617
- type: recall_at_100
value: 68.75
- type: recall_at_1000
value: 88.864
- type: recall_at_3
value: 34.199
- type: recall_at_5
value: 39.462
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.22083333333333
- type: map_at_10
value: 31.606666666666662
- type: map_at_100
value: 32.6195
- type: map_at_1000
value: 32.739999999999995
- type: map_at_3
value: 29.37825
- type: map_at_5
value: 30.596083333333336
- type: mrr_at_1
value: 28.607916666666668
- type: mrr_at_10
value: 35.54591666666666
- type: mrr_at_100
value: 36.33683333333333
- type: mrr_at_1000
value: 36.40624999999999
- type: mrr_at_3
value: 33.526250000000005
- type: mrr_at_5
value: 34.6605
- type: ndcg_at_1
value: 28.607916666666668
- type: ndcg_at_10
value: 36.07966666666667
- type: ndcg_at_100
value: 40.73308333333333
- type: ndcg_at_1000
value: 43.40666666666666
- type: ndcg_at_3
value: 32.23525
- type: ndcg_at_5
value: 33.97083333333333
- type: precision_at_1
value: 28.607916666666668
- type: precision_at_10
value: 6.120333333333335
- type: precision_at_100
value: 0.9921666666666668
- type: precision_at_1000
value: 0.14091666666666666
- type: precision_at_3
value: 14.54975
- type: precision_at_5
value: 10.153166666666667
- type: recall_at_1
value: 24.22083333333333
- type: recall_at_10
value: 45.49183333333334
- type: recall_at_100
value: 66.28133333333332
- type: recall_at_1000
value: 85.16541666666667
- type: recall_at_3
value: 34.6485
- type: recall_at_5
value: 39.229749999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.842
- type: map_at_10
value: 27.573999999999998
- type: map_at_100
value: 28.410999999999998
- type: map_at_1000
value: 28.502
- type: map_at_3
value: 25.921
- type: map_at_5
value: 26.888
- type: mrr_at_1
value: 24.08
- type: mrr_at_10
value: 29.915999999999997
- type: mrr_at_100
value: 30.669
- type: mrr_at_1000
value: 30.746000000000002
- type: mrr_at_3
value: 28.349000000000004
- type: mrr_at_5
value: 29.246
- type: ndcg_at_1
value: 24.08
- type: ndcg_at_10
value: 30.898999999999997
- type: ndcg_at_100
value: 35.272999999999996
- type: ndcg_at_1000
value: 37.679
- type: ndcg_at_3
value: 27.881
- type: ndcg_at_5
value: 29.432000000000002
- type: precision_at_1
value: 24.08
- type: precision_at_10
value: 4.678
- type: precision_at_100
value: 0.744
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 11.860999999999999
- type: precision_at_5
value: 8.16
- type: recall_at_1
value: 21.842
- type: recall_at_10
value: 38.66
- type: recall_at_100
value: 59.169000000000004
- type: recall_at_1000
value: 76.887
- type: recall_at_3
value: 30.532999999999998
- type: recall_at_5
value: 34.354
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.145
- type: map_at_10
value: 22.729
- type: map_at_100
value: 23.574
- type: map_at_1000
value: 23.695
- type: map_at_3
value: 21.044
- type: map_at_5
value: 21.981
- type: mrr_at_1
value: 20.888
- type: mrr_at_10
value: 26.529000000000003
- type: mrr_at_100
value: 27.308
- type: mrr_at_1000
value: 27.389000000000003
- type: mrr_at_3
value: 24.868000000000002
- type: mrr_at_5
value: 25.825
- type: ndcg_at_1
value: 20.888
- type: ndcg_at_10
value: 26.457000000000004
- type: ndcg_at_100
value: 30.764000000000003
- type: ndcg_at_1000
value: 33.825
- type: ndcg_at_3
value: 23.483999999999998
- type: ndcg_at_5
value: 24.836
- type: precision_at_1
value: 20.888
- type: precision_at_10
value: 4.58
- type: precision_at_100
value: 0.784
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 10.874
- type: precision_at_5
value: 7.639
- type: recall_at_1
value: 17.145
- type: recall_at_10
value: 33.938
- type: recall_at_100
value: 53.672
- type: recall_at_1000
value: 76.023
- type: recall_at_3
value: 25.363000000000003
- type: recall_at_5
value: 29.023
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.275
- type: map_at_10
value: 30.438
- type: map_at_100
value: 31.489
- type: map_at_1000
value: 31.601000000000003
- type: map_at_3
value: 28.647
- type: map_at_5
value: 29.660999999999998
- type: mrr_at_1
value: 28.077999999999996
- type: mrr_at_10
value: 34.098
- type: mrr_at_100
value: 35.025
- type: mrr_at_1000
value: 35.109
- type: mrr_at_3
value: 32.4
- type: mrr_at_5
value: 33.379999999999995
- type: ndcg_at_1
value: 28.077999999999996
- type: ndcg_at_10
value: 34.271
- type: ndcg_at_100
value: 39.352
- type: ndcg_at_1000
value: 42.199
- type: ndcg_at_3
value: 30.978
- type: ndcg_at_5
value: 32.498
- type: precision_at_1
value: 28.077999999999996
- type: precision_at_10
value: 5.345
- type: precision_at_100
value: 0.897
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 13.526
- type: precision_at_5
value: 9.16
- type: recall_at_1
value: 24.275
- type: recall_at_10
value: 42.362
- type: recall_at_100
value: 64.461
- type: recall_at_1000
value: 84.981
- type: recall_at_3
value: 33.249
- type: recall_at_5
value: 37.214999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.358
- type: map_at_10
value: 30.062
- type: map_at_100
value: 31.189
- type: map_at_1000
value: 31.386999999999997
- type: map_at_3
value: 27.672
- type: map_at_5
value: 28.76
- type: mrr_at_1
value: 26.877000000000002
- type: mrr_at_10
value: 33.948
- type: mrr_at_100
value: 34.746
- type: mrr_at_1000
value: 34.816
- type: mrr_at_3
value: 31.884
- type: mrr_at_5
value: 33.001000000000005
- type: ndcg_at_1
value: 26.877000000000002
- type: ndcg_at_10
value: 34.977000000000004
- type: ndcg_at_100
value: 39.753
- type: ndcg_at_1000
value: 42.866
- type: ndcg_at_3
value: 30.956
- type: ndcg_at_5
value: 32.381
- type: precision_at_1
value: 26.877000000000002
- type: precision_at_10
value: 6.7
- type: precision_at_100
value: 1.287
- type: precision_at_1000
value: 0.215
- type: precision_at_3
value: 14.360999999999999
- type: precision_at_5
value: 10.119
- type: recall_at_1
value: 22.358
- type: recall_at_10
value: 44.183
- type: recall_at_100
value: 67.14
- type: recall_at_1000
value: 87.53999999999999
- type: recall_at_3
value: 32.79
- type: recall_at_5
value: 36.829
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.198999999999998
- type: map_at_10
value: 25.229000000000003
- type: map_at_100
value: 26.003
- type: map_at_1000
value: 26.111
- type: map_at_3
value: 23.442
- type: map_at_5
value: 24.343
- type: mrr_at_1
value: 21.072
- type: mrr_at_10
value: 27.02
- type: mrr_at_100
value: 27.735
- type: mrr_at_1000
value: 27.815
- type: mrr_at_3
value: 25.416
- type: mrr_at_5
value: 26.173999999999996
- type: ndcg_at_1
value: 21.072
- type: ndcg_at_10
value: 28.862
- type: ndcg_at_100
value: 33.043
- type: ndcg_at_1000
value: 36.003
- type: ndcg_at_3
value: 25.35
- type: ndcg_at_5
value: 26.773000000000003
- type: precision_at_1
value: 21.072
- type: precision_at_10
value: 4.436
- type: precision_at_100
value: 0.713
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 10.659
- type: precision_at_5
value: 7.32
- type: recall_at_1
value: 19.198999999999998
- type: recall_at_10
value: 38.376
- type: recall_at_100
value: 58.36900000000001
- type: recall_at_1000
value: 80.92099999999999
- type: recall_at_3
value: 28.715000000000003
- type: recall_at_5
value: 32.147
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.9319999999999995
- type: map_at_10
value: 10.483
- type: map_at_100
value: 11.97
- type: map_at_1000
value: 12.171999999999999
- type: map_at_3
value: 8.477
- type: map_at_5
value: 9.495000000000001
- type: mrr_at_1
value: 13.094
- type: mrr_at_10
value: 21.282
- type: mrr_at_100
value: 22.556
- type: mrr_at_1000
value: 22.628999999999998
- type: mrr_at_3
value: 18.218999999999998
- type: mrr_at_5
value: 19.900000000000002
- type: ndcg_at_1
value: 13.094
- type: ndcg_at_10
value: 15.811
- type: ndcg_at_100
value: 23.035
- type: ndcg_at_1000
value: 27.089999999999996
- type: ndcg_at_3
value: 11.905000000000001
- type: ndcg_at_5
value: 13.377
- type: precision_at_1
value: 13.094
- type: precision_at_10
value: 5.225
- type: precision_at_100
value: 1.2970000000000002
- type: precision_at_1000
value: 0.203
- type: precision_at_3
value: 8.86
- type: precision_at_5
value: 7.309
- type: recall_at_1
value: 5.9319999999999995
- type: recall_at_10
value: 20.305
- type: recall_at_100
value: 46.314
- type: recall_at_1000
value: 69.612
- type: recall_at_3
value: 11.21
- type: recall_at_5
value: 14.773
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.674
- type: map_at_10
value: 17.822
- type: map_at_100
value: 24.794
- type: map_at_1000
value: 26.214
- type: map_at_3
value: 12.690999999999999
- type: map_at_5
value: 15.033
- type: mrr_at_1
value: 61.75000000000001
- type: mrr_at_10
value: 71.58
- type: mrr_at_100
value: 71.923
- type: mrr_at_1000
value: 71.932
- type: mrr_at_3
value: 70.125
- type: mrr_at_5
value: 71.038
- type: ndcg_at_1
value: 51
- type: ndcg_at_10
value: 38.637
- type: ndcg_at_100
value: 42.398
- type: ndcg_at_1000
value: 48.962
- type: ndcg_at_3
value: 43.29
- type: ndcg_at_5
value: 40.763
- type: precision_at_1
value: 61.75000000000001
- type: precision_at_10
value: 30.125
- type: precision_at_100
value: 9.53
- type: precision_at_1000
value: 1.9619999999999997
- type: precision_at_3
value: 45.583
- type: precision_at_5
value: 38.95
- type: recall_at_1
value: 8.674
- type: recall_at_10
value: 23.122
- type: recall_at_100
value: 47.46
- type: recall_at_1000
value: 67.662
- type: recall_at_3
value: 13.946
- type: recall_at_5
value: 17.768
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 46.86000000000001
- type: f1
value: 41.343580452760776
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.609
- type: map_at_10
value: 47.552
- type: map_at_100
value: 48.283
- type: map_at_1000
value: 48.321
- type: map_at_3
value: 44.869
- type: map_at_5
value: 46.509
- type: mrr_at_1
value: 39.214
- type: mrr_at_10
value: 50.434999999999995
- type: mrr_at_100
value: 51.122
- type: mrr_at_1000
value: 51.151
- type: mrr_at_3
value: 47.735
- type: mrr_at_5
value: 49.394
- type: ndcg_at_1
value: 39.214
- type: ndcg_at_10
value: 53.52400000000001
- type: ndcg_at_100
value: 56.997
- type: ndcg_at_1000
value: 57.975
- type: ndcg_at_3
value: 48.173
- type: ndcg_at_5
value: 51.05800000000001
- type: precision_at_1
value: 39.214
- type: precision_at_10
value: 7.573
- type: precision_at_100
value: 0.9440000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 19.782
- type: precision_at_5
value: 13.453000000000001
- type: recall_at_1
value: 36.609
- type: recall_at_10
value: 69.247
- type: recall_at_100
value: 84.99600000000001
- type: recall_at_1000
value: 92.40899999999999
- type: recall_at_3
value: 54.856
- type: recall_at_5
value: 61.797000000000004
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.466
- type: map_at_10
value: 27.060000000000002
- type: map_at_100
value: 28.511999999999997
- type: map_at_1000
value: 28.693
- type: map_at_3
value: 22.777
- type: map_at_5
value: 25.086000000000002
- type: mrr_at_1
value: 32.716
- type: mrr_at_10
value: 41.593999999999994
- type: mrr_at_100
value: 42.370000000000005
- type: mrr_at_1000
value: 42.419000000000004
- type: mrr_at_3
value: 38.143
- type: mrr_at_5
value: 40.288000000000004
- type: ndcg_at_1
value: 32.716
- type: ndcg_at_10
value: 34.795
- type: ndcg_at_100
value: 40.58
- type: ndcg_at_1000
value: 43.993
- type: ndcg_at_3
value: 29.573
- type: ndcg_at_5
value: 31.583
- type: precision_at_1
value: 32.716
- type: precision_at_10
value: 9.937999999999999
- type: precision_at_100
value: 1.585
- type: precision_at_1000
value: 0.22
- type: precision_at_3
value: 19.496
- type: precision_at_5
value: 15.247
- type: recall_at_1
value: 16.466
- type: recall_at_10
value: 42.886
- type: recall_at_100
value: 64.724
- type: recall_at_1000
value: 85.347
- type: recall_at_3
value: 26.765
- type: recall_at_5
value: 33.603
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 33.025
- type: map_at_10
value: 47.343
- type: map_at_100
value: 48.207
- type: map_at_1000
value: 48.281
- type: map_at_3
value: 44.519
- type: map_at_5
value: 46.217000000000006
- type: mrr_at_1
value: 66.05
- type: mrr_at_10
value: 72.94699999999999
- type: mrr_at_100
value: 73.289
- type: mrr_at_1000
value: 73.30499999999999
- type: mrr_at_3
value: 71.686
- type: mrr_at_5
value: 72.491
- type: ndcg_at_1
value: 66.05
- type: ndcg_at_10
value: 56.338
- type: ndcg_at_100
value: 59.599999999999994
- type: ndcg_at_1000
value: 61.138000000000005
- type: ndcg_at_3
value: 52.034000000000006
- type: ndcg_at_5
value: 54.352000000000004
- type: precision_at_1
value: 66.05
- type: precision_at_10
value: 11.693000000000001
- type: precision_at_100
value: 1.425
- type: precision_at_1000
value: 0.163
- type: precision_at_3
value: 32.613
- type: precision_at_5
value: 21.401999999999997
- type: recall_at_1
value: 33.025
- type: recall_at_10
value: 58.467
- type: recall_at_100
value: 71.242
- type: recall_at_1000
value: 81.452
- type: recall_at_3
value: 48.92
- type: recall_at_5
value: 53.504
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 75.5492
- type: ap
value: 69.42911637216271
- type: f1
value: 75.39113704261024
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.173
- type: map_at_10
value: 35.453
- type: map_at_100
value: 36.573
- type: map_at_1000
value: 36.620999999999995
- type: map_at_3
value: 31.655
- type: map_at_5
value: 33.823
- type: mrr_at_1
value: 23.868000000000002
- type: mrr_at_10
value: 36.085
- type: mrr_at_100
value: 37.15
- type: mrr_at_1000
value: 37.193
- type: mrr_at_3
value: 32.376
- type: mrr_at_5
value: 34.501
- type: ndcg_at_1
value: 23.854
- type: ndcg_at_10
value: 42.33
- type: ndcg_at_100
value: 47.705999999999996
- type: ndcg_at_1000
value: 48.91
- type: ndcg_at_3
value: 34.604
- type: ndcg_at_5
value: 38.473
- type: precision_at_1
value: 23.854
- type: precision_at_10
value: 6.639
- type: precision_at_100
value: 0.932
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.685
- type: precision_at_5
value: 10.782
- type: recall_at_1
value: 23.173
- type: recall_at_10
value: 63.441
- type: recall_at_100
value: 88.25
- type: recall_at_1000
value: 97.438
- type: recall_at_3
value: 42.434
- type: recall_at_5
value: 51.745
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 92.05426356589147
- type: f1
value: 91.88068588063942
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 73.23985408116735
- type: f1
value: 55.858906745287506
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 72.21923335574984
- type: f1
value: 70.0174116204253
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 75.77673167451245
- type: f1
value: 75.44811354778666
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.340414710728737
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 28.196676760061578
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.564149683482206
- type: mrr
value: 30.28995474250486
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.93
- type: map_at_10
value: 12.828000000000001
- type: map_at_100
value: 15.501000000000001
- type: map_at_1000
value: 16.791
- type: map_at_3
value: 9.727
- type: map_at_5
value: 11.318999999999999
- type: mrr_at_1
value: 47.678
- type: mrr_at_10
value: 55.893
- type: mrr_at_100
value: 56.491
- type: mrr_at_1000
value: 56.53
- type: mrr_at_3
value: 54.386
- type: mrr_at_5
value: 55.516
- type: ndcg_at_1
value: 45.975
- type: ndcg_at_10
value: 33.928999999999995
- type: ndcg_at_100
value: 30.164
- type: ndcg_at_1000
value: 38.756
- type: ndcg_at_3
value: 41.077000000000005
- type: ndcg_at_5
value: 38.415
- type: precision_at_1
value: 47.678
- type: precision_at_10
value: 24.365000000000002
- type: precision_at_100
value: 7.344
- type: precision_at_1000
value: 1.994
- type: precision_at_3
value: 38.184000000000005
- type: precision_at_5
value: 33.003
- type: recall_at_1
value: 5.93
- type: recall_at_10
value: 16.239
- type: recall_at_100
value: 28.782999999999998
- type: recall_at_1000
value: 60.11
- type: recall_at_3
value: 10.700999999999999
- type: recall_at_5
value: 13.584
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.163000000000004
- type: map_at_10
value: 51.520999999999994
- type: map_at_100
value: 52.449
- type: map_at_1000
value: 52.473000000000006
- type: map_at_3
value: 47.666
- type: map_at_5
value: 50.043000000000006
- type: mrr_at_1
value: 40.266999999999996
- type: mrr_at_10
value: 54.074
- type: mrr_at_100
value: 54.722
- type: mrr_at_1000
value: 54.739000000000004
- type: mrr_at_3
value: 51.043000000000006
- type: mrr_at_5
value: 52.956
- type: ndcg_at_1
value: 40.238
- type: ndcg_at_10
value: 58.73199999999999
- type: ndcg_at_100
value: 62.470000000000006
- type: ndcg_at_1000
value: 63.083999999999996
- type: ndcg_at_3
value: 51.672
- type: ndcg_at_5
value: 55.564
- type: precision_at_1
value: 40.238
- type: precision_at_10
value: 9.279
- type: precision_at_100
value: 1.139
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 23.078000000000003
- type: precision_at_5
value: 16.176
- type: recall_at_1
value: 36.163000000000004
- type: recall_at_10
value: 77.88199999999999
- type: recall_at_100
value: 93.83399999999999
- type: recall_at_1000
value: 98.465
- type: recall_at_3
value: 59.857000000000006
- type: recall_at_5
value: 68.73599999999999
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 70.344
- type: map_at_10
value: 83.907
- type: map_at_100
value: 84.536
- type: map_at_1000
value: 84.557
- type: map_at_3
value: 80.984
- type: map_at_5
value: 82.844
- type: mrr_at_1
value: 81.02000000000001
- type: mrr_at_10
value: 87.158
- type: mrr_at_100
value: 87.268
- type: mrr_at_1000
value: 87.26899999999999
- type: mrr_at_3
value: 86.17
- type: mrr_at_5
value: 86.87
- type: ndcg_at_1
value: 81.02000000000001
- type: ndcg_at_10
value: 87.70700000000001
- type: ndcg_at_100
value: 89.004
- type: ndcg_at_1000
value: 89.139
- type: ndcg_at_3
value: 84.841
- type: ndcg_at_5
value: 86.455
- type: precision_at_1
value: 81.02000000000001
- type: precision_at_10
value: 13.248999999999999
- type: precision_at_100
value: 1.516
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.963
- type: precision_at_5
value: 24.33
- type: recall_at_1
value: 70.344
- type: recall_at_10
value: 94.75099999999999
- type: recall_at_100
value: 99.30499999999999
- type: recall_at_1000
value: 99.928
- type: recall_at_3
value: 86.506
- type: recall_at_5
value: 91.083
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 42.873718018378305
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 56.39477366450528
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.868
- type: map_at_10
value: 9.611
- type: map_at_100
value: 11.087
- type: map_at_1000
value: 11.332
- type: map_at_3
value: 6.813
- type: map_at_5
value: 8.233
- type: mrr_at_1
value: 19
- type: mrr_at_10
value: 28.457
- type: mrr_at_100
value: 29.613
- type: mrr_at_1000
value: 29.695
- type: mrr_at_3
value: 25.55
- type: mrr_at_5
value: 27.29
- type: ndcg_at_1
value: 19
- type: ndcg_at_10
value: 16.419
- type: ndcg_at_100
value: 22.817999999999998
- type: ndcg_at_1000
value: 27.72
- type: ndcg_at_3
value: 15.379000000000001
- type: ndcg_at_5
value: 13.645
- type: precision_at_1
value: 19
- type: precision_at_10
value: 8.540000000000001
- type: precision_at_100
value: 1.7819999999999998
- type: precision_at_1000
value: 0.297
- type: precision_at_3
value: 14.267
- type: precision_at_5
value: 12.04
- type: recall_at_1
value: 3.868
- type: recall_at_10
value: 17.288
- type: recall_at_100
value: 36.144999999999996
- type: recall_at_1000
value: 60.199999999999996
- type: recall_at_3
value: 8.688
- type: recall_at_5
value: 12.198
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 83.96614722598582
- type: cos_sim_spearman
value: 78.9003023008781
- type: euclidean_pearson
value: 81.01829384436505
- type: euclidean_spearman
value: 78.93248416788914
- type: manhattan_pearson
value: 81.1665428926402
- type: manhattan_spearman
value: 78.93264116287453
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 83.54613363895993
- type: cos_sim_spearman
value: 75.1883451602451
- type: euclidean_pearson
value: 79.70320886899894
- type: euclidean_spearman
value: 74.5917140136796
- type: manhattan_pearson
value: 79.82157067185999
- type: manhattan_spearman
value: 74.74185720594735
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 81.30430156721782
- type: cos_sim_spearman
value: 81.79962989974364
- type: euclidean_pearson
value: 80.89058823224924
- type: euclidean_spearman
value: 81.35929372984597
- type: manhattan_pearson
value: 81.12204370487478
- type: manhattan_spearman
value: 81.6248963282232
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 81.13064504403134
- type: cos_sim_spearman
value: 78.48371403924872
- type: euclidean_pearson
value: 80.16794919665591
- type: euclidean_spearman
value: 78.29216082221699
- type: manhattan_pearson
value: 80.22308565207301
- type: manhattan_spearman
value: 78.37829229948022
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 86.52918899541099
- type: cos_sim_spearman
value: 87.49276894673142
- type: euclidean_pearson
value: 86.77440570164254
- type: euclidean_spearman
value: 87.5753295736756
- type: manhattan_pearson
value: 86.86098573892133
- type: manhattan_spearman
value: 87.65848591821947
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 82.86805307244882
- type: cos_sim_spearman
value: 84.58066253757511
- type: euclidean_pearson
value: 84.38377000876991
- type: euclidean_spearman
value: 85.1837278784528
- type: manhattan_pearson
value: 84.41903291363842
- type: manhattan_spearman
value: 85.19023736251052
- 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: 86.77218560282436
- type: cos_sim_spearman
value: 87.94243515296604
- type: euclidean_pearson
value: 88.22800939214864
- type: euclidean_spearman
value: 87.91106839439841
- type: manhattan_pearson
value: 88.17063269848741
- type: manhattan_spearman
value: 87.72751904126062
- 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: 60.40731554300387
- type: cos_sim_spearman
value: 63.76300532966479
- type: euclidean_pearson
value: 62.94727878229085
- type: euclidean_spearman
value: 63.678039531461216
- type: manhattan_pearson
value: 63.00661039863549
- type: manhattan_spearman
value: 63.6282591984376
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 84.92731569745344
- type: cos_sim_spearman
value: 86.36336704300167
- type: euclidean_pearson
value: 86.09122224841195
- type: euclidean_spearman
value: 86.2116149319238
- type: manhattan_pearson
value: 86.07879456717032
- type: manhattan_spearman
value: 86.2022069635119
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 79.75976311752326
- type: mrr
value: 94.15782837351466
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 51.193999999999996
- type: map_at_10
value: 61.224999999999994
- type: map_at_100
value: 62.031000000000006
- type: map_at_1000
value: 62.066
- type: map_at_3
value: 59.269000000000005
- type: map_at_5
value: 60.159
- type: mrr_at_1
value: 53.667
- type: mrr_at_10
value: 62.74999999999999
- type: mrr_at_100
value: 63.39399999999999
- type: mrr_at_1000
value: 63.425
- type: mrr_at_3
value: 61.389
- type: mrr_at_5
value: 61.989000000000004
- type: ndcg_at_1
value: 53.667
- type: ndcg_at_10
value: 65.596
- type: ndcg_at_100
value: 68.906
- type: ndcg_at_1000
value: 69.78999999999999
- type: ndcg_at_3
value: 62.261
- type: ndcg_at_5
value: 63.453
- type: precision_at_1
value: 53.667
- type: precision_at_10
value: 8.667
- type: precision_at_100
value: 1.04
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 24.556
- type: precision_at_5
value: 15.6
- type: recall_at_1
value: 51.193999999999996
- type: recall_at_10
value: 77.156
- type: recall_at_100
value: 91.43299999999999
- type: recall_at_1000
value: 98.333
- type: recall_at_3
value: 67.994
- type: recall_at_5
value: 71.14399999999999
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81485148514851
- type: cos_sim_ap
value: 95.28896513388551
- type: cos_sim_f1
value: 90.43478260869566
- type: cos_sim_precision
value: 92.56544502617801
- type: cos_sim_recall
value: 88.4
- type: dot_accuracy
value: 99.30594059405941
- type: dot_ap
value: 61.6432597455472
- type: dot_f1
value: 59.46481665014866
- type: dot_precision
value: 58.93909626719057
- type: dot_recall
value: 60
- type: euclidean_accuracy
value: 99.81980198019802
- type: euclidean_ap
value: 95.21411049527
- type: euclidean_f1
value: 91.06090373280944
- type: euclidean_precision
value: 89.47876447876449
- type: euclidean_recall
value: 92.7
- type: manhattan_accuracy
value: 99.81782178217821
- type: manhattan_ap
value: 95.32449994414968
- type: manhattan_f1
value: 90.86395233366436
- type: manhattan_precision
value: 90.23668639053254
- type: manhattan_recall
value: 91.5
- type: max_accuracy
value: 99.81980198019802
- type: max_ap
value: 95.32449994414968
- type: max_f1
value: 91.06090373280944
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 59.08045614613064
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 30.297802606804748
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 49.12801740706292
- type: mrr
value: 50.05592956879722
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 23.380995453661917
- type: cos_sim_spearman
value: 24.941761858688917
- type: dot_pearson
value: 24.930577961642413
- type: dot_spearman
value: 24.804715835064492
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.243
- type: map_at_10
value: 1.886
- type: map_at_100
value: 10.040000000000001
- type: map_at_1000
value: 23.768
- type: map_at_3
value: 0.674
- type: map_at_5
value: 1.079
- type: mrr_at_1
value: 88
- type: mrr_at_10
value: 93.667
- type: mrr_at_100
value: 93.667
- type: mrr_at_1000
value: 93.667
- type: mrr_at_3
value: 93.667
- type: mrr_at_5
value: 93.667
- type: ndcg_at_1
value: 83
- type: ndcg_at_10
value: 76.777
- type: ndcg_at_100
value: 55.153
- type: ndcg_at_1000
value: 47.912
- type: ndcg_at_3
value: 81.358
- type: ndcg_at_5
value: 80.74799999999999
- type: precision_at_1
value: 88
- type: precision_at_10
value: 80.80000000000001
- type: precision_at_100
value: 56.02
- type: precision_at_1000
value: 21.51
- type: precision_at_3
value: 86
- type: precision_at_5
value: 86
- type: recall_at_1
value: 0.243
- type: recall_at_10
value: 2.0869999999999997
- type: recall_at_100
value: 13.014000000000001
- type: recall_at_1000
value: 44.433
- type: recall_at_3
value: 0.6910000000000001
- type: recall_at_5
value: 1.1440000000000001
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.066
- type: map_at_10
value: 10.615
- type: map_at_100
value: 16.463
- type: map_at_1000
value: 17.815
- type: map_at_3
value: 5.7860000000000005
- type: map_at_5
value: 7.353999999999999
- type: mrr_at_1
value: 38.775999999999996
- type: mrr_at_10
value: 53.846000000000004
- type: mrr_at_100
value: 54.37
- type: mrr_at_1000
value: 54.37
- type: mrr_at_3
value: 48.980000000000004
- type: mrr_at_5
value: 51.735
- type: ndcg_at_1
value: 34.694
- type: ndcg_at_10
value: 26.811
- type: ndcg_at_100
value: 37.342999999999996
- type: ndcg_at_1000
value: 47.964
- type: ndcg_at_3
value: 30.906
- type: ndcg_at_5
value: 27.77
- type: precision_at_1
value: 38.775999999999996
- type: precision_at_10
value: 23.878
- type: precision_at_100
value: 7.632999999999999
- type: precision_at_1000
value: 1.469
- type: precision_at_3
value: 31.973000000000003
- type: precision_at_5
value: 26.939
- type: recall_at_1
value: 3.066
- type: recall_at_10
value: 17.112
- type: recall_at_100
value: 47.723
- type: recall_at_1000
value: 79.50500000000001
- type: recall_at_3
value: 6.825
- type: recall_at_5
value: 9.584
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 72.76460000000002
- type: ap
value: 14.944240012137053
- type: f1
value: 55.89805777266571
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 63.30503678551217
- type: f1
value: 63.57492701921179
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 37.51066495006874
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 86.07021517553794
- type: cos_sim_ap
value: 74.15520712370555
- type: cos_sim_f1
value: 68.64321608040201
- type: cos_sim_precision
value: 65.51558752997602
- type: cos_sim_recall
value: 72.0844327176781
- type: dot_accuracy
value: 80.23484532395541
- type: dot_ap
value: 54.298763810214176
- type: dot_f1
value: 53.22254659779924
- type: dot_precision
value: 46.32525410476936
- type: dot_recall
value: 62.532981530343015
- type: euclidean_accuracy
value: 86.04637301066937
- type: euclidean_ap
value: 73.85333854233123
- type: euclidean_f1
value: 68.77723660599845
- type: euclidean_precision
value: 66.87437686939182
- type: euclidean_recall
value: 70.79155672823218
- type: manhattan_accuracy
value: 85.98676759849795
- type: manhattan_ap
value: 73.56016090035973
- type: manhattan_f1
value: 68.48878539036647
- type: manhattan_precision
value: 63.9505607690547
- type: manhattan_recall
value: 73.7203166226913
- type: max_accuracy
value: 86.07021517553794
- type: max_ap
value: 74.15520712370555
- type: max_f1
value: 68.77723660599845
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.92769821865176
- type: cos_sim_ap
value: 85.78879502899773
- type: cos_sim_f1
value: 78.14414083990464
- type: cos_sim_precision
value: 74.61651607480563
- type: cos_sim_recall
value: 82.0218663381583
- type: dot_accuracy
value: 84.95750378390964
- type: dot_ap
value: 75.80219641857563
- type: dot_f1
value: 70.13966179585681
- type: dot_precision
value: 65.71140262361251
- type: dot_recall
value: 75.20788420080073
- type: euclidean_accuracy
value: 88.93546008460433
- type: euclidean_ap
value: 85.72056428301667
- type: euclidean_f1
value: 78.14387902598124
- type: euclidean_precision
value: 75.3376688344172
- type: euclidean_recall
value: 81.16723129042192
- type: manhattan_accuracy
value: 88.96262661543835
- type: manhattan_ap
value: 85.76605136314335
- type: manhattan_f1
value: 78.26696165191743
- type: manhattan_precision
value: 75.0990659496179
- type: manhattan_recall
value: 81.71388974437943
- type: max_accuracy
value: 88.96262661543835
- type: max_ap
value: 85.78879502899773
- type: max_f1
value: 78.26696165191743
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