metadata
license: apache-2.0
tags:
- mteb
- arctic
- arctic-embed
model-index:
- name: base-lc
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 78.4776119402985
- type: ap
value: 42.34374238166049
- type: f1
value: 72.51164234732224
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 78.7416
- type: ap
value: 73.12074819362377
- type: f1
value: 78.64057339708795
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 39.926
- type: f1
value: 39.35531993117573
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 34.851
- type: map_at_10
value: 51.473
- type: map_at_100
value: 52.103
- type: map_at_1000
value: 52.105000000000004
- type: map_at_3
value: 46.776
- type: map_at_5
value: 49.617
- type: mrr_at_1
value: 35.491
- type: mrr_at_10
value: 51.73799999999999
- type: mrr_at_100
value: 52.37500000000001
- type: mrr_at_1000
value: 52.378
- type: mrr_at_3
value: 46.965
- type: mrr_at_5
value: 49.878
- type: ndcg_at_1
value: 34.851
- type: ndcg_at_10
value: 60.364
- type: ndcg_at_100
value: 62.888999999999996
- type: ndcg_at_1000
value: 62.946000000000005
- type: ndcg_at_3
value: 50.807
- type: ndcg_at_5
value: 55.901
- type: precision_at_1
value: 34.851
- type: precision_at_10
value: 8.855
- type: precision_at_100
value: 0.992
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 20.839
- type: precision_at_5
value: 14.963999999999999
- type: recall_at_1
value: 34.851
- type: recall_at_10
value: 88.549
- type: recall_at_100
value: 99.21799999999999
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 62.517999999999994
- type: recall_at_5
value: 74.822
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 45.5554998405317
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 35.614248811397005
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 61.355489424753884
- type: mrr
value: 75.49443784900849
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 89.17311056578292
- type: cos_sim_spearman
value: 88.24237210809322
- type: euclidean_pearson
value: 87.3188065853646
- type: euclidean_spearman
value: 88.24237210809322
- type: manhattan_pearson
value: 86.89499710049658
- type: manhattan_spearman
value: 87.85441146091777
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 80.26298701298703
- type: f1
value: 79.68356764080303
- task:
type: Clustering
dataset:
type: jinaai/big-patent-clustering
name: MTEB BigPatentClustering
config: default
split: test
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
metrics:
- type: v_measure
value: 20.923883720813706
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 36.16058801465044
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 30.1402356118627
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-android
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 35.612
- type: map_at_10
value: 47.117
- type: map_at_100
value: 48.711
- type: map_at_1000
value: 48.826
- type: map_at_3
value: 43.858999999999995
- type: map_at_5
value: 45.612
- type: mrr_at_1
value: 42.918
- type: mrr_at_10
value: 52.806
- type: mrr_at_100
value: 53.564
- type: mrr_at_1000
value: 53.596999999999994
- type: mrr_at_3
value: 50.453
- type: mrr_at_5
value: 51.841
- type: ndcg_at_1
value: 42.918
- type: ndcg_at_10
value: 53.291999999999994
- type: ndcg_at_100
value: 58.711999999999996
- type: ndcg_at_1000
value: 60.317
- type: ndcg_at_3
value: 48.855
- type: ndcg_at_5
value: 50.778
- type: precision_at_1
value: 42.918
- type: precision_at_10
value: 9.927999999999999
- type: precision_at_100
value: 1.592
- type: precision_at_1000
value: 0.201
- type: precision_at_3
value: 23.366999999999997
- type: precision_at_5
value: 16.366
- type: recall_at_1
value: 35.612
- type: recall_at_10
value: 64.671
- type: recall_at_100
value: 86.97
- type: recall_at_1000
value: 96.99600000000001
- type: recall_at_3
value: 51.37199999999999
- type: recall_at_5
value: 57.094
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-english
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 33.742
- type: map_at_10
value: 44.49
- type: map_at_100
value: 45.781
- type: map_at_1000
value: 45.902
- type: map_at_3
value: 41.453
- type: map_at_5
value: 43.251
- type: mrr_at_1
value: 42.357
- type: mrr_at_10
value: 50.463
- type: mrr_at_100
value: 51.17
- type: mrr_at_1000
value: 51.205999999999996
- type: mrr_at_3
value: 48.397
- type: mrr_at_5
value: 49.649
- type: ndcg_at_1
value: 42.357
- type: ndcg_at_10
value: 50.175000000000004
- type: ndcg_at_100
value: 54.491
- type: ndcg_at_1000
value: 56.282
- type: ndcg_at_3
value: 46.159
- type: ndcg_at_5
value: 48.226
- type: precision_at_1
value: 42.357
- type: precision_at_10
value: 9.382
- type: precision_at_100
value: 1.473
- type: precision_at_1000
value: 0.191
- type: precision_at_3
value: 22.187
- type: precision_at_5
value: 15.758
- type: recall_at_1
value: 33.742
- type: recall_at_10
value: 59.760999999999996
- type: recall_at_100
value: 77.89500000000001
- type: recall_at_1000
value: 89.005
- type: recall_at_3
value: 47.872
- type: recall_at_5
value: 53.559
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gaming
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 43.883
- type: map_at_10
value: 56.464999999999996
- type: map_at_100
value: 57.394
- type: map_at_1000
value: 57.443999999999996
- type: map_at_3
value: 53.169
- type: map_at_5
value: 54.984
- type: mrr_at_1
value: 50.470000000000006
- type: mrr_at_10
value: 59.997
- type: mrr_at_100
value: 60.586
- type: mrr_at_1000
value: 60.61
- type: mrr_at_3
value: 57.837
- type: mrr_at_5
value: 59.019
- type: ndcg_at_1
value: 50.470000000000006
- type: ndcg_at_10
value: 62.134
- type: ndcg_at_100
value: 65.69500000000001
- type: ndcg_at_1000
value: 66.674
- type: ndcg_at_3
value: 56.916999999999994
- type: ndcg_at_5
value: 59.312
- type: precision_at_1
value: 50.470000000000006
- type: precision_at_10
value: 9.812
- type: precision_at_100
value: 1.25
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 25.119999999999997
- type: precision_at_5
value: 17.016000000000002
- type: recall_at_1
value: 43.883
- type: recall_at_10
value: 75.417
- type: recall_at_100
value: 90.545
- type: recall_at_1000
value: 97.44500000000001
- type: recall_at_3
value: 61.306000000000004
- type: recall_at_5
value: 67.244
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gis
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 29.813000000000002
- type: map_at_10
value: 38.627
- type: map_at_100
value: 39.735
- type: map_at_1000
value: 39.806000000000004
- type: map_at_3
value: 36.283
- type: map_at_5
value: 37.491
- type: mrr_at_1
value: 32.316
- type: mrr_at_10
value: 40.752
- type: mrr_at_100
value: 41.699000000000005
- type: mrr_at_1000
value: 41.749
- type: mrr_at_3
value: 38.531
- type: mrr_at_5
value: 39.706
- type: ndcg_at_1
value: 32.316
- type: ndcg_at_10
value: 43.524
- type: ndcg_at_100
value: 48.648
- type: ndcg_at_1000
value: 50.405
- type: ndcg_at_3
value: 38.928000000000004
- type: ndcg_at_5
value: 40.967
- type: precision_at_1
value: 32.316
- type: precision_at_10
value: 6.451999999999999
- type: precision_at_100
value: 0.9490000000000001
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 16.384
- type: precision_at_5
value: 11.006
- type: recall_at_1
value: 29.813000000000002
- type: recall_at_10
value: 56.562999999999995
- type: recall_at_100
value: 79.452
- type: recall_at_1000
value: 92.715
- type: recall_at_3
value: 43.985
- type: recall_at_5
value: 49.001
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-mathematica
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 19.961000000000002
- type: map_at_10
value: 28.026
- type: map_at_100
value: 29.212
- type: map_at_1000
value: 29.332
- type: map_at_3
value: 25.296999999999997
- type: map_at_5
value: 26.832
- type: mrr_at_1
value: 24.627
- type: mrr_at_10
value: 33.045
- type: mrr_at_100
value: 33.944
- type: mrr_at_1000
value: 34.013
- type: mrr_at_3
value: 30.307000000000002
- type: mrr_at_5
value: 31.874000000000002
- type: ndcg_at_1
value: 24.627
- type: ndcg_at_10
value: 33.414
- type: ndcg_at_100
value: 39.061
- type: ndcg_at_1000
value: 41.795
- type: ndcg_at_3
value: 28.377000000000002
- type: ndcg_at_5
value: 30.781999999999996
- type: precision_at_1
value: 24.627
- type: precision_at_10
value: 6.02
- type: precision_at_100
value: 1.035
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 13.516
- type: precision_at_5
value: 9.851
- type: recall_at_1
value: 19.961000000000002
- type: recall_at_10
value: 45.174
- type: recall_at_100
value: 69.69
- type: recall_at_1000
value: 89.24600000000001
- type: recall_at_3
value: 31.062
- type: recall_at_5
value: 37.193
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-physics
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 32.080999999999996
- type: map_at_10
value: 42.177
- type: map_at_100
value: 43.431999999999995
- type: map_at_1000
value: 43.533
- type: map_at_3
value: 38.721
- type: map_at_5
value: 40.669
- type: mrr_at_1
value: 38.787
- type: mrr_at_10
value: 47.762
- type: mrr_at_100
value: 48.541000000000004
- type: mrr_at_1000
value: 48.581
- type: mrr_at_3
value: 45.123999999999995
- type: mrr_at_5
value: 46.639
- type: ndcg_at_1
value: 38.787
- type: ndcg_at_10
value: 48.094
- type: ndcg_at_100
value: 53.291
- type: ndcg_at_1000
value: 55.21
- type: ndcg_at_3
value: 42.721
- type: ndcg_at_5
value: 45.301
- type: precision_at_1
value: 38.787
- type: precision_at_10
value: 8.576
- type: precision_at_100
value: 1.306
- type: precision_at_1000
value: 0.164
- type: precision_at_3
value: 19.698
- type: precision_at_5
value: 14.013
- type: recall_at_1
value: 32.080999999999996
- type: recall_at_10
value: 59.948
- type: recall_at_100
value: 81.811
- type: recall_at_1000
value: 94.544
- type: recall_at_3
value: 44.903999999999996
- type: recall_at_5
value: 51.763999999999996
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-programmers
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 28.869
- type: map_at_10
value: 38.954
- type: map_at_100
value: 40.233000000000004
- type: map_at_1000
value: 40.332
- type: map_at_3
value: 35.585
- type: map_at_5
value: 37.476
- type: mrr_at_1
value: 35.959
- type: mrr_at_10
value: 44.800000000000004
- type: mrr_at_100
value: 45.609
- type: mrr_at_1000
value: 45.655
- type: mrr_at_3
value: 42.333
- type: mrr_at_5
value: 43.68
- type: ndcg_at_1
value: 35.959
- type: ndcg_at_10
value: 44.957
- type: ndcg_at_100
value: 50.275000000000006
- type: ndcg_at_1000
value: 52.29899999999999
- type: ndcg_at_3
value: 39.797
- type: ndcg_at_5
value: 42.128
- type: precision_at_1
value: 35.959
- type: precision_at_10
value: 8.185
- type: precision_at_100
value: 1.261
- type: precision_at_1000
value: 0.159
- type: precision_at_3
value: 18.988
- type: precision_at_5
value: 13.516
- type: recall_at_1
value: 28.869
- type: recall_at_10
value: 57.154
- type: recall_at_100
value: 79.764
- type: recall_at_1000
value: 93.515
- type: recall_at_3
value: 42.364000000000004
- type: recall_at_5
value: 48.756
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 29.31008333333333
- type: map_at_10
value: 38.81849999999999
- type: map_at_100
value: 40.05058333333334
- type: map_at_1000
value: 40.16116666666667
- type: map_at_3
value: 35.91441666666667
- type: map_at_5
value: 37.526583333333335
- type: mrr_at_1
value: 34.60066666666667
- type: mrr_at_10
value: 43.08858333333333
- type: mrr_at_100
value: 43.927749999999996
- type: mrr_at_1000
value: 43.97866666666667
- type: mrr_at_3
value: 40.72775
- type: mrr_at_5
value: 42.067249999999994
- type: ndcg_at_1
value: 34.60066666666667
- type: ndcg_at_10
value: 44.20841666666667
- type: ndcg_at_100
value: 49.32866666666667
- type: ndcg_at_1000
value: 51.373999999999995
- type: ndcg_at_3
value: 39.452083333333334
- type: ndcg_at_5
value: 41.67
- type: precision_at_1
value: 34.60066666666667
- type: precision_at_10
value: 7.616583333333334
- type: precision_at_100
value: 1.20175
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 17.992
- type: precision_at_5
value: 12.658416666666666
- type: recall_at_1
value: 29.31008333333333
- type: recall_at_10
value: 55.81900000000001
- type: recall_at_100
value: 78.06308333333334
- type: recall_at_1000
value: 92.10641666666668
- type: recall_at_3
value: 42.50166666666667
- type: recall_at_5
value: 48.26108333333333
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-stats
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 26.773000000000003
- type: map_at_10
value: 34.13
- type: map_at_100
value: 35.113
- type: map_at_1000
value: 35.211
- type: map_at_3
value: 31.958
- type: map_at_5
value: 33.080999999999996
- type: mrr_at_1
value: 30.061
- type: mrr_at_10
value: 37.061
- type: mrr_at_100
value: 37.865
- type: mrr_at_1000
value: 37.939
- type: mrr_at_3
value: 34.995
- type: mrr_at_5
value: 36.092
- type: ndcg_at_1
value: 30.061
- type: ndcg_at_10
value: 38.391999999999996
- type: ndcg_at_100
value: 43.13
- type: ndcg_at_1000
value: 45.449
- type: ndcg_at_3
value: 34.411
- type: ndcg_at_5
value: 36.163000000000004
- type: precision_at_1
value: 30.061
- type: precision_at_10
value: 5.982
- type: precision_at_100
value: 0.911
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 14.673
- type: precision_at_5
value: 10.030999999999999
- type: recall_at_1
value: 26.773000000000003
- type: recall_at_10
value: 48.445
- type: recall_at_100
value: 69.741
- type: recall_at_1000
value: 86.59
- type: recall_at_3
value: 37.576
- type: recall_at_5
value: 41.948
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-tex
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 18.556
- type: map_at_10
value: 26.340999999999998
- type: map_at_100
value: 27.560000000000002
- type: map_at_1000
value: 27.685
- type: map_at_3
value: 24.136
- type: map_at_5
value: 25.34
- type: mrr_at_1
value: 22.368
- type: mrr_at_10
value: 30.192999999999998
- type: mrr_at_100
value: 31.183
- type: mrr_at_1000
value: 31.258000000000003
- type: mrr_at_3
value: 28.223
- type: mrr_at_5
value: 29.294999999999998
- type: ndcg_at_1
value: 22.368
- type: ndcg_at_10
value: 31.029
- type: ndcg_at_100
value: 36.768
- type: ndcg_at_1000
value: 39.572
- type: ndcg_at_3
value: 27.197
- type: ndcg_at_5
value: 28.912
- type: precision_at_1
value: 22.368
- type: precision_at_10
value: 5.606
- type: precision_at_100
value: 0.9979999999999999
- type: precision_at_1000
value: 0.14100000000000001
- type: precision_at_3
value: 12.892999999999999
- type: precision_at_5
value: 9.16
- type: recall_at_1
value: 18.556
- type: recall_at_10
value: 41.087
- type: recall_at_100
value: 66.92
- type: recall_at_1000
value: 86.691
- type: recall_at_3
value: 30.415
- type: recall_at_5
value: 34.813
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-unix
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 29.953999999999997
- type: map_at_10
value: 39.633
- type: map_at_100
value: 40.923
- type: map_at_1000
value: 41.016000000000005
- type: map_at_3
value: 36.609
- type: map_at_5
value: 38.443
- type: mrr_at_1
value: 35.354
- type: mrr_at_10
value: 43.718
- type: mrr_at_100
value: 44.651999999999994
- type: mrr_at_1000
value: 44.696000000000005
- type: mrr_at_3
value: 41.154
- type: mrr_at_5
value: 42.730000000000004
- type: ndcg_at_1
value: 35.354
- type: ndcg_at_10
value: 44.933
- type: ndcg_at_100
value: 50.577000000000005
- type: ndcg_at_1000
value: 52.428
- type: ndcg_at_3
value: 39.833
- type: ndcg_at_5
value: 42.465
- type: precision_at_1
value: 35.354
- type: precision_at_10
value: 7.416
- type: precision_at_100
value: 1.157
- type: precision_at_1000
value: 0.14100000000000001
- type: precision_at_3
value: 17.817
- type: precision_at_5
value: 12.687000000000001
- type: recall_at_1
value: 29.953999999999997
- type: recall_at_10
value: 56.932
- type: recall_at_100
value: 80.93900000000001
- type: recall_at_1000
value: 93.582
- type: recall_at_3
value: 43.192
- type: recall_at_5
value: 49.757
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-webmasters
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 27.85
- type: map_at_10
value: 37.68
- type: map_at_100
value: 39.295
- type: map_at_1000
value: 39.527
- type: map_at_3
value: 35.036
- type: map_at_5
value: 36.269
- type: mrr_at_1
value: 33.004
- type: mrr_at_10
value: 42.096000000000004
- type: mrr_at_100
value: 43.019
- type: mrr_at_1000
value: 43.071
- type: mrr_at_3
value: 39.987
- type: mrr_at_5
value: 40.995
- type: ndcg_at_1
value: 33.004
- type: ndcg_at_10
value: 43.461
- type: ndcg_at_100
value: 49.138
- type: ndcg_at_1000
value: 51.50900000000001
- type: ndcg_at_3
value: 39.317
- type: ndcg_at_5
value: 40.760999999999996
- type: precision_at_1
value: 33.004
- type: precision_at_10
value: 8.161999999999999
- type: precision_at_100
value: 1.583
- type: precision_at_1000
value: 0.245
- type: precision_at_3
value: 18.445
- type: precision_at_5
value: 12.885
- type: recall_at_1
value: 27.85
- type: recall_at_10
value: 54.419
- type: recall_at_100
value: 79.742
- type: recall_at_1000
value: 93.97
- type: recall_at_3
value: 42.149
- type: recall_at_5
value: 46.165
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-wordpress
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 24.627
- type: map_at_10
value: 32.182
- type: map_at_100
value: 33.217999999999996
- type: map_at_1000
value: 33.32
- type: map_at_3
value: 28.866999999999997
- type: map_at_5
value: 30.871
- type: mrr_at_1
value: 26.987
- type: mrr_at_10
value: 34.37
- type: mrr_at_100
value: 35.301
- type: mrr_at_1000
value: 35.369
- type: mrr_at_3
value: 31.391999999999996
- type: mrr_at_5
value: 33.287
- type: ndcg_at_1
value: 26.987
- type: ndcg_at_10
value: 37.096000000000004
- type: ndcg_at_100
value: 42.158
- type: ndcg_at_1000
value: 44.548
- type: ndcg_at_3
value: 30.913
- type: ndcg_at_5
value: 34.245
- type: precision_at_1
value: 26.987
- type: precision_at_10
value: 5.878
- type: precision_at_100
value: 0.906
- type: precision_at_1000
value: 0.123
- type: precision_at_3
value: 12.815999999999999
- type: precision_at_5
value: 9.612
- type: recall_at_1
value: 24.627
- type: recall_at_10
value: 50.257
- type: recall_at_100
value: 73.288
- type: recall_at_1000
value: 90.97800000000001
- type: recall_at_3
value: 33.823
- type: recall_at_5
value: 41.839
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 17.343
- type: map_at_10
value: 28.59
- type: map_at_100
value: 30.591
- type: map_at_1000
value: 30.759999999999998
- type: map_at_3
value: 24.197
- type: map_at_5
value: 26.433
- type: mrr_at_1
value: 39.609
- type: mrr_at_10
value: 51.107
- type: mrr_at_100
value: 51.87199999999999
- type: mrr_at_1000
value: 51.894
- type: mrr_at_3
value: 48.154
- type: mrr_at_5
value: 49.939
- type: ndcg_at_1
value: 39.609
- type: ndcg_at_10
value: 38.329
- type: ndcg_at_100
value: 45.573
- type: ndcg_at_1000
value: 48.405
- type: ndcg_at_3
value: 32.506
- type: ndcg_at_5
value: 34.331
- type: precision_at_1
value: 39.609
- type: precision_at_10
value: 11.668000000000001
- type: precision_at_100
value: 1.9539999999999997
- type: precision_at_1000
value: 0.249
- type: precision_at_3
value: 23.952
- type: precision_at_5
value: 17.902
- type: recall_at_1
value: 17.343
- type: recall_at_10
value: 43.704
- type: recall_at_100
value: 68.363
- type: recall_at_1000
value: 84.04599999999999
- type: recall_at_3
value: 29.028
- type: recall_at_5
value: 35.022
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 9.934999999999999
- type: map_at_10
value: 22.081
- type: map_at_100
value: 32.036
- type: map_at_1000
value: 33.803
- type: map_at_3
value: 15.687999999999999
- type: map_at_5
value: 18.357
- type: mrr_at_1
value: 70.75
- type: mrr_at_10
value: 78.506
- type: mrr_at_100
value: 78.874
- type: mrr_at_1000
value: 78.88300000000001
- type: mrr_at_3
value: 77.667
- type: mrr_at_5
value: 78.342
- type: ndcg_at_1
value: 57.25
- type: ndcg_at_10
value: 45.286
- type: ndcg_at_100
value: 50.791
- type: ndcg_at_1000
value: 58.021
- type: ndcg_at_3
value: 49.504
- type: ndcg_at_5
value: 47.03
- type: precision_at_1
value: 70.75
- type: precision_at_10
value: 36.425000000000004
- type: precision_at_100
value: 11.953
- type: precision_at_1000
value: 2.248
- type: precision_at_3
value: 53.25
- type: precision_at_5
value: 46.150000000000006
- type: recall_at_1
value: 9.934999999999999
- type: recall_at_10
value: 27.592
- type: recall_at_100
value: 58.089
- type: recall_at_1000
value: 81.025
- type: recall_at_3
value: 17.048
- type: recall_at_5
value: 20.834
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 47.25999999999999
- type: f1
value: 43.83371155132253
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 73.68900000000001
- type: map_at_10
value: 82.878
- type: map_at_100
value: 83.084
- type: map_at_1000
value: 83.097
- type: map_at_3
value: 81.528
- type: map_at_5
value: 82.432
- type: mrr_at_1
value: 79.49300000000001
- type: mrr_at_10
value: 87.24300000000001
- type: mrr_at_100
value: 87.3
- type: mrr_at_1000
value: 87.301
- type: mrr_at_3
value: 86.359
- type: mrr_at_5
value: 87.01
- type: ndcg_at_1
value: 79.49300000000001
- type: ndcg_at_10
value: 86.894
- type: ndcg_at_100
value: 87.6
- type: ndcg_at_1000
value: 87.79299999999999
- type: ndcg_at_3
value: 84.777
- type: ndcg_at_5
value: 86.08
- type: precision_at_1
value: 79.49300000000001
- type: precision_at_10
value: 10.578
- type: precision_at_100
value: 1.117
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 32.592999999999996
- type: precision_at_5
value: 20.423
- type: recall_at_1
value: 73.68900000000001
- type: recall_at_10
value: 94.833
- type: recall_at_100
value: 97.554
- type: recall_at_1000
value: 98.672
- type: recall_at_3
value: 89.236
- type: recall_at_5
value: 92.461
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 20.59
- type: map_at_10
value: 34.089000000000006
- type: map_at_100
value: 35.796
- type: map_at_1000
value: 35.988
- type: map_at_3
value: 29.877
- type: map_at_5
value: 32.202999999999996
- type: mrr_at_1
value: 41.049
- type: mrr_at_10
value: 50.370000000000005
- type: mrr_at_100
value: 51.209
- type: mrr_at_1000
value: 51.247
- type: mrr_at_3
value: 48.122
- type: mrr_at_5
value: 49.326
- type: ndcg_at_1
value: 41.049
- type: ndcg_at_10
value: 42.163000000000004
- type: ndcg_at_100
value: 48.638999999999996
- type: ndcg_at_1000
value: 51.775000000000006
- type: ndcg_at_3
value: 38.435
- type: ndcg_at_5
value: 39.561
- type: precision_at_1
value: 41.049
- type: precision_at_10
value: 11.481
- type: precision_at_100
value: 1.8239999999999998
- type: precision_at_1000
value: 0.24
- type: precision_at_3
value: 25.257
- type: precision_at_5
value: 18.519
- type: recall_at_1
value: 20.59
- type: recall_at_10
value: 49.547999999999995
- type: recall_at_100
value: 73.676
- type: recall_at_1000
value: 92.269
- type: recall_at_3
value: 35.656
- type: recall_at_5
value: 41.455
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 39.932
- type: map_at_10
value: 64.184
- type: map_at_100
value: 65.06
- type: map_at_1000
value: 65.109
- type: map_at_3
value: 60.27
- type: map_at_5
value: 62.732
- type: mrr_at_1
value: 79.865
- type: mrr_at_10
value: 85.99799999999999
- type: mrr_at_100
value: 86.13
- type: mrr_at_1000
value: 86.13300000000001
- type: mrr_at_3
value: 85.136
- type: mrr_at_5
value: 85.69200000000001
- type: ndcg_at_1
value: 79.865
- type: ndcg_at_10
value: 72.756
- type: ndcg_at_100
value: 75.638
- type: ndcg_at_1000
value: 76.589
- type: ndcg_at_3
value: 67.38199999999999
- type: ndcg_at_5
value: 70.402
- type: precision_at_1
value: 79.865
- type: precision_at_10
value: 15.387999999999998
- type: precision_at_100
value: 1.7610000000000001
- type: precision_at_1000
value: 0.189
- type: precision_at_3
value: 43.394
- type: precision_at_5
value: 28.424
- type: recall_at_1
value: 39.932
- type: recall_at_10
value: 76.941
- type: recall_at_100
value: 88.062
- type: recall_at_1000
value: 94.396
- type: recall_at_3
value: 65.091
- type: recall_at_5
value: 71.06
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 71.7904
- type: ap
value: 65.82899456730257
- type: f1
value: 71.56611877410202
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 21.931
- type: map_at_10
value: 34.849999999999994
- type: map_at_100
value: 36.033
- type: map_at_1000
value: 36.08
- type: map_at_3
value: 30.842000000000002
- type: map_at_5
value: 33.229
- type: mrr_at_1
value: 22.55
- type: mrr_at_10
value: 35.436
- type: mrr_at_100
value: 36.563
- type: mrr_at_1000
value: 36.604
- type: mrr_at_3
value: 31.507
- type: mrr_at_5
value: 33.851
- type: ndcg_at_1
value: 22.55
- type: ndcg_at_10
value: 41.969
- type: ndcg_at_100
value: 47.576
- type: ndcg_at_1000
value: 48.731
- type: ndcg_at_3
value: 33.894000000000005
- type: ndcg_at_5
value: 38.133
- type: precision_at_1
value: 22.55
- type: precision_at_10
value: 6.660000000000001
- type: precision_at_100
value: 0.946
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.532
- type: precision_at_5
value: 10.865
- type: recall_at_1
value: 21.931
- type: recall_at_10
value: 63.841
- type: recall_at_100
value: 89.47699999999999
- type: recall_at_1000
value: 98.259
- type: recall_at_3
value: 42.063
- type: recall_at_5
value: 52.21
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.03921568627452
- type: f1
value: 92.56400672314416
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 63.515731874145
- type: f1
value: 44.922310875523216
- task:
type: Classification
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClassification (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: accuracy
value: 77.57383966244727
- type: f1
value: 76.55222378218293
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringP2P (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 62.74836240280833
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringS2S (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 24.414348715238184
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 66.54673839946201
- type: f1
value: 64.61004101532164
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 73.11365164761264
- type: f1
value: 72.01684013680978
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.123671999617297
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.72684341430875
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.910228061734816
- type: mrr
value: 30.835255982532477
- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 5.6770000000000005
- type: map_at_10
value: 13.15
- type: map_at_100
value: 16.205
- type: map_at_1000
value: 17.580000000000002
- type: map_at_3
value: 9.651
- type: map_at_5
value: 11.142000000000001
- type: mrr_at_1
value: 47.678
- type: mrr_at_10
value: 56.257000000000005
- type: mrr_at_100
value: 56.708000000000006
- type: mrr_at_1000
value: 56.751
- type: mrr_at_3
value: 54.128
- type: mrr_at_5
value: 55.181000000000004
- type: ndcg_at_1
value: 45.511
- type: ndcg_at_10
value: 35.867
- type: ndcg_at_100
value: 31.566
- type: ndcg_at_1000
value: 40.077
- type: ndcg_at_3
value: 41.9
- type: ndcg_at_5
value: 39.367999999999995
- type: precision_at_1
value: 47.678
- type: precision_at_10
value: 26.842
- type: precision_at_100
value: 7.991
- type: precision_at_1000
value: 2.0469999999999997
- type: precision_at_3
value: 39.938
- type: precision_at_5
value: 34.613
- type: recall_at_1
value: 5.6770000000000005
- type: recall_at_10
value: 17.119999999999997
- type: recall_at_100
value: 30.828
- type: recall_at_1000
value: 62.082
- type: recall_at_3
value: 10.456
- type: recall_at_5
value: 12.903999999999998
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 39.021
- type: map_at_10
value: 54.976
- type: map_at_100
value: 55.793000000000006
- type: map_at_1000
value: 55.811
- type: map_at_3
value: 50.759
- type: map_at_5
value: 53.429
- type: mrr_at_1
value: 43.308
- type: mrr_at_10
value: 57.118
- type: mrr_at_100
value: 57.69499999999999
- type: mrr_at_1000
value: 57.704
- type: mrr_at_3
value: 53.848
- type: mrr_at_5
value: 55.915000000000006
- type: ndcg_at_1
value: 43.308
- type: ndcg_at_10
value: 62.33800000000001
- type: ndcg_at_100
value: 65.61099999999999
- type: ndcg_at_1000
value: 65.995
- type: ndcg_at_3
value: 54.723
- type: ndcg_at_5
value: 59.026
- type: precision_at_1
value: 43.308
- type: precision_at_10
value: 9.803
- type: precision_at_100
value: 1.167
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 24.334
- type: precision_at_5
value: 17.144000000000002
- type: recall_at_1
value: 39.021
- type: recall_at_10
value: 82.37299999999999
- type: recall_at_100
value: 96.21499999999999
- type: recall_at_1000
value: 99.02499999999999
- type: recall_at_3
value: 63.031000000000006
- type: recall_at_5
value: 72.856
- task:
type: Classification
dataset:
type: ag_news
name: MTEB NewsClassification
config: default
split: test
revision: eb185aade064a813bc0b7f42de02595523103ca4
metrics:
- type: accuracy
value: 78.03289473684211
- type: f1
value: 77.89323745730803
- task:
type: PairClassification
dataset:
type: GEM/opusparcus
name: MTEB OpusparcusPC (en)
config: en
split: test
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
metrics:
- type: cos_sim_accuracy
value: 99.89816700610999
- type: cos_sim_ap
value: 100
- type: cos_sim_f1
value: 99.9490575649516
- type: cos_sim_precision
value: 100
- type: cos_sim_recall
value: 99.89816700610999
- type: dot_accuracy
value: 99.89816700610999
- type: dot_ap
value: 100
- type: dot_f1
value: 99.9490575649516
- type: dot_precision
value: 100
- type: dot_recall
value: 99.89816700610999
- type: euclidean_accuracy
value: 99.89816700610999
- type: euclidean_ap
value: 100
- type: euclidean_f1
value: 99.9490575649516
- type: euclidean_precision
value: 100
- type: euclidean_recall
value: 99.89816700610999
- type: manhattan_accuracy
value: 99.89816700610999
- type: manhattan_ap
value: 100
- type: manhattan_f1
value: 99.9490575649516
- type: manhattan_precision
value: 100
- type: manhattan_recall
value: 99.89816700610999
- type: max_accuracy
value: 99.89816700610999
- type: max_ap
value: 100
- type: max_f1
value: 99.9490575649516
- task:
type: PairClassification
dataset:
type: paws-x
name: MTEB PawsX (en)
config: en
split: test
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
metrics:
- type: cos_sim_accuracy
value: 61.75000000000001
- type: cos_sim_ap
value: 59.578879568280385
- type: cos_sim_f1
value: 62.50861474844934
- type: cos_sim_precision
value: 45.46365914786967
- type: cos_sim_recall
value: 100
- type: dot_accuracy
value: 61.75000000000001
- type: dot_ap
value: 59.57893088951573
- type: dot_f1
value: 62.50861474844934
- type: dot_precision
value: 45.46365914786967
- type: dot_recall
value: 100
- type: euclidean_accuracy
value: 61.75000000000001
- type: euclidean_ap
value: 59.578755624671686
- type: euclidean_f1
value: 62.50861474844934
- type: euclidean_precision
value: 45.46365914786967
- type: euclidean_recall
value: 100
- type: manhattan_accuracy
value: 61.75000000000001
- type: manhattan_ap
value: 59.58504334461159
- type: manhattan_f1
value: 62.50861474844934
- type: manhattan_precision
value: 45.46365914786967
- type: manhattan_recall
value: 100
- type: max_accuracy
value: 61.75000000000001
- type: max_ap
value: 59.58504334461159
- type: max_f1
value: 62.50861474844934
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 70.186
- type: map_at_10
value: 83.875
- type: map_at_100
value: 84.514
- type: map_at_1000
value: 84.53500000000001
- type: map_at_3
value: 80.926
- type: map_at_5
value: 82.797
- type: mrr_at_1
value: 80.82000000000001
- type: mrr_at_10
value: 87.068
- type: mrr_at_100
value: 87.178
- type: mrr_at_1000
value: 87.18
- type: mrr_at_3
value: 86.055
- type: mrr_at_5
value: 86.763
- type: ndcg_at_1
value: 80.84
- type: ndcg_at_10
value: 87.723
- type: ndcg_at_100
value: 88.98700000000001
- type: ndcg_at_1000
value: 89.13499999999999
- type: ndcg_at_3
value: 84.821
- type: ndcg_at_5
value: 86.441
- type: precision_at_1
value: 80.84
- type: precision_at_10
value: 13.270000000000001
- type: precision_at_100
value: 1.516
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 37.013
- type: precision_at_5
value: 24.37
- type: recall_at_1
value: 70.186
- type: recall_at_10
value: 94.948
- type: recall_at_100
value: 99.223
- type: recall_at_1000
value: 99.932
- type: recall_at_3
value: 86.57000000000001
- type: recall_at_5
value: 91.157
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 50.24198927949519
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 61.452073078765544
- task:
type: Retrieval
dataset:
type: mteb/scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
metrics:
- type: map_at_1
value: 4.972
- type: map_at_10
value: 12.314
- type: map_at_100
value: 14.333000000000002
- type: map_at_1000
value: 14.628
- type: map_at_3
value: 8.972
- type: map_at_5
value: 10.724
- type: mrr_at_1
value: 24.4
- type: mrr_at_10
value: 35.257
- type: mrr_at_100
value: 36.297000000000004
- type: mrr_at_1000
value: 36.363
- type: mrr_at_3
value: 32.267
- type: mrr_at_5
value: 33.942
- type: ndcg_at_1
value: 24.4
- type: ndcg_at_10
value: 20.47
- type: ndcg_at_100
value: 28.111000000000004
- type: ndcg_at_1000
value: 33.499
- type: ndcg_at_3
value: 19.975
- type: ndcg_at_5
value: 17.293
- type: precision_at_1
value: 24.4
- type: precision_at_10
value: 10.440000000000001
- type: precision_at_100
value: 2.136
- type: precision_at_1000
value: 0.34299999999999997
- type: precision_at_3
value: 18.733
- type: precision_at_5
value: 15.120000000000001
- type: recall_at_1
value: 4.972
- type: recall_at_10
value: 21.157
- type: recall_at_100
value: 43.335
- type: recall_at_1000
value: 69.652
- type: recall_at_3
value: 11.417
- type: recall_at_5
value: 15.317
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 76.70295978506286
- type: cos_sim_spearman
value: 70.91162732446628
- type: euclidean_pearson
value: 73.25693688746031
- type: euclidean_spearman
value: 70.91162556180127
- type: manhattan_pearson
value: 73.27735004735767
- type: manhattan_spearman
value: 70.8856787022704
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 67.55878682646774
- type: cos_sim_spearman
value: 66.10824660353681
- type: euclidean_pearson
value: 64.93937270068541
- type: euclidean_spearman
value: 66.10824660353681
- type: manhattan_pearson
value: 64.96325555978984
- type: manhattan_spearman
value: 66.12052481638577
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 79.79979774019496
- type: cos_sim_spearman
value: 79.82293444619499
- type: euclidean_pearson
value: 79.4830436509311
- type: euclidean_spearman
value: 79.82293444619499
- type: manhattan_pearson
value: 79.49785594799296
- type: manhattan_spearman
value: 79.8280390479434
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 76.36839628231121
- type: cos_sim_spearman
value: 73.63809739428072
- type: euclidean_pearson
value: 74.93718121215906
- type: euclidean_spearman
value: 73.63810227650436
- type: manhattan_pearson
value: 74.8737197659424
- type: manhattan_spearman
value: 73.57534688126572
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 82.67482138157656
- type: cos_sim_spearman
value: 83.23485786963107
- type: euclidean_pearson
value: 82.50847772197369
- type: euclidean_spearman
value: 83.23485786963107
- type: manhattan_pearson
value: 82.48916218377576
- type: manhattan_spearman
value: 83.19756483500014
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 81.11626268793967
- type: cos_sim_spearman
value: 81.58184691061507
- type: euclidean_pearson
value: 80.65900869004938
- type: euclidean_spearman
value: 81.58184691061507
- type: manhattan_pearson
value: 80.67912306966772
- type: manhattan_spearman
value: 81.59957593393145
- 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: 80.3140990821409
- type: cos_sim_spearman
value: 80.59196586367551
- type: euclidean_pearson
value: 80.73014029317672
- type: euclidean_spearman
value: 80.59196586367551
- type: manhattan_pearson
value: 80.5774325136987
- type: manhattan_spearman
value: 80.35102610546238
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 68.34450491529164
- type: cos_sim_spearman
value: 68.79451793414492
- type: euclidean_pearson
value: 68.75619738499324
- type: euclidean_spearman
value: 68.79451793414492
- type: manhattan_pearson
value: 68.75256119543882
- type: manhattan_spearman
value: 68.81836416978547
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 77.95580414975612
- type: cos_sim_spearman
value: 77.89671867168987
- type: euclidean_pearson
value: 77.61352097720862
- type: euclidean_spearman
value: 77.89671867168987
- type: manhattan_pearson
value: 77.65282228135632
- type: manhattan_spearman
value: 77.91730533156762
- task:
type: STS
dataset:
type: PhilipMay/stsb_multi_mt
name: MTEB STSBenchmarkMultilingualSTS (en)
config: en
split: test
revision: 93d57ef91790589e3ce9c365164337a8a78b7632
metrics:
- type: cos_sim_pearson
value: 77.95580421496413
- type: cos_sim_spearman
value: 77.89671867168987
- type: euclidean_pearson
value: 77.61352107168794
- type: euclidean_spearman
value: 77.89671867168987
- type: manhattan_pearson
value: 77.65282237231794
- type: manhattan_spearman
value: 77.91730533156762
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 79.22928110092924
- type: mrr
value: 94.46700902583257
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 56.011
- type: map_at_10
value: 65.544
- type: map_at_100
value: 66.034
- type: map_at_1000
value: 66.065
- type: map_at_3
value: 63.077000000000005
- type: map_at_5
value: 64.354
- type: mrr_at_1
value: 59
- type: mrr_at_10
value: 66.74900000000001
- type: mrr_at_100
value: 67.176
- type: mrr_at_1000
value: 67.203
- type: mrr_at_3
value: 65.056
- type: mrr_at_5
value: 65.956
- type: ndcg_at_1
value: 59
- type: ndcg_at_10
value: 69.95599999999999
- type: ndcg_at_100
value: 72.27
- type: ndcg_at_1000
value: 73.066
- type: ndcg_at_3
value: 65.837
- type: ndcg_at_5
value: 67.633
- type: precision_at_1
value: 59
- type: precision_at_10
value: 9.333
- type: precision_at_100
value: 1.053
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 26
- type: precision_at_5
value: 16.866999999999997
- type: recall_at_1
value: 56.011
- type: recall_at_10
value: 82.133
- type: recall_at_100
value: 92.767
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 70.95
- type: recall_at_5
value: 75.556
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81584158415842
- type: cos_sim_ap
value: 94.67482871230736
- type: cos_sim_f1
value: 90.67201604814443
- type: cos_sim_precision
value: 90.94567404426559
- type: cos_sim_recall
value: 90.4
- type: dot_accuracy
value: 99.81584158415842
- type: dot_ap
value: 94.67482871230737
- type: dot_f1
value: 90.67201604814443
- type: dot_precision
value: 90.94567404426559
- type: dot_recall
value: 90.4
- type: euclidean_accuracy
value: 99.81584158415842
- type: euclidean_ap
value: 94.67482871230737
- type: euclidean_f1
value: 90.67201604814443
- type: euclidean_precision
value: 90.94567404426559
- type: euclidean_recall
value: 90.4
- type: manhattan_accuracy
value: 99.81188118811882
- type: manhattan_ap
value: 94.6409082219286
- type: manhattan_f1
value: 90.50949050949052
- type: manhattan_precision
value: 90.41916167664671
- type: manhattan_recall
value: 90.60000000000001
- type: max_accuracy
value: 99.81584158415842
- type: max_ap
value: 94.67482871230737
- type: max_f1
value: 90.67201604814443
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 62.63494511649264
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 37.165838327685755
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 51.384873075208084
- type: mrr
value: 52.196439181733304
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 32.13690355567596
- type: cos_sim_spearman
value: 31.38349778638125
- type: dot_pearson
value: 32.13689596691593
- type: dot_spearman
value: 31.38349778638125
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.26
- type: map_at_10
value: 2.08
- type: map_at_100
value: 12.598
- type: map_at_1000
value: 30.119
- type: map_at_3
value: 0.701
- type: map_at_5
value: 1.11
- type: mrr_at_1
value: 96
- type: mrr_at_10
value: 97.167
- type: mrr_at_100
value: 97.167
- type: mrr_at_1000
value: 97.167
- type: mrr_at_3
value: 96.667
- type: mrr_at_5
value: 97.167
- type: ndcg_at_1
value: 91
- type: ndcg_at_10
value: 81.69800000000001
- type: ndcg_at_100
value: 62.9
- type: ndcg_at_1000
value: 55.245999999999995
- type: ndcg_at_3
value: 86.397
- type: ndcg_at_5
value: 84.286
- type: precision_at_1
value: 96
- type: precision_at_10
value: 87
- type: precision_at_100
value: 64.86
- type: precision_at_1000
value: 24.512
- type: precision_at_3
value: 90.667
- type: precision_at_5
value: 88.8
- type: recall_at_1
value: 0.26
- type: recall_at_10
value: 2.238
- type: recall_at_100
value: 15.488
- type: recall_at_1000
value: 51.6
- type: recall_at_3
value: 0.716
- type: recall_at_5
value: 1.151
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 3.376
- type: map_at_10
value: 13.142000000000001
- type: map_at_100
value: 19.763
- type: map_at_1000
value: 21.319
- type: map_at_3
value: 6.805999999999999
- type: map_at_5
value: 8.952
- type: mrr_at_1
value: 46.939
- type: mrr_at_10
value: 61.082
- type: mrr_at_100
value: 61.45
- type: mrr_at_1000
value: 61.468999999999994
- type: mrr_at_3
value: 57.483
- type: mrr_at_5
value: 59.931999999999995
- type: ndcg_at_1
value: 44.897999999999996
- type: ndcg_at_10
value: 32.35
- type: ndcg_at_100
value: 42.719
- type: ndcg_at_1000
value: 53.30200000000001
- type: ndcg_at_3
value: 37.724999999999994
- type: ndcg_at_5
value: 34.79
- type: precision_at_1
value: 46.939
- type: precision_at_10
value: 28.366999999999997
- type: precision_at_100
value: 8.429
- type: precision_at_1000
value: 1.557
- type: precision_at_3
value: 38.095
- type: precision_at_5
value: 33.469
- type: recall_at_1
value: 3.376
- type: recall_at_10
value: 20.164
- type: recall_at_100
value: 50.668
- type: recall_at_1000
value: 83.159
- type: recall_at_3
value: 8.155
- type: recall_at_5
value: 11.872
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 66.739
- type: ap
value: 12.17931839228834
- type: f1
value: 51.05383188624636
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 56.72891907187323
- type: f1
value: 56.997614557150946
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 39.825318429345224
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.65619598259522
- type: cos_sim_ap
value: 66.17412885183877
- type: cos_sim_f1
value: 63.09125656951745
- type: cos_sim_precision
value: 57.63858577040594
- type: cos_sim_recall
value: 69.68337730870712
- type: dot_accuracy
value: 83.65619598259522
- type: dot_ap
value: 66.17413621964548
- type: dot_f1
value: 63.09125656951745
- type: dot_precision
value: 57.63858577040594
- type: dot_recall
value: 69.68337730870712
- type: euclidean_accuracy
value: 83.65619598259522
- type: euclidean_ap
value: 66.17412836413126
- type: euclidean_f1
value: 63.09125656951745
- type: euclidean_precision
value: 57.63858577040594
- type: euclidean_recall
value: 69.68337730870712
- type: manhattan_accuracy
value: 83.5548667819038
- type: manhattan_ap
value: 66.07998834521334
- type: manhattan_f1
value: 62.96433419721092
- type: manhattan_precision
value: 59.14676559239509
- type: manhattan_recall
value: 67.30870712401055
- type: max_accuracy
value: 83.65619598259522
- type: max_ap
value: 66.17413621964548
- type: max_f1
value: 63.09125656951745
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.55706911941631
- type: cos_sim_ap
value: 85.20971331546805
- type: cos_sim_f1
value: 77.28446050593702
- type: cos_sim_precision
value: 74.16135881104033
- type: cos_sim_recall
value: 80.6821681552202
- type: dot_accuracy
value: 88.55706911941631
- type: dot_ap
value: 85.2097154112633
- type: dot_f1
value: 77.28446050593702
- type: dot_precision
value: 74.16135881104033
- type: dot_recall
value: 80.6821681552202
- type: euclidean_accuracy
value: 88.55706911941631
- type: euclidean_ap
value: 85.20971719214488
- type: euclidean_f1
value: 77.28446050593702
- type: euclidean_precision
value: 74.16135881104033
- type: euclidean_recall
value: 80.6821681552202
- type: manhattan_accuracy
value: 88.52020025614158
- type: manhattan_ap
value: 85.17569799117058
- type: manhattan_f1
value: 77.27157773040933
- type: manhattan_precision
value: 72.79286638077734
- type: manhattan_recall
value: 82.33754234678165
- type: max_accuracy
value: 88.55706911941631
- type: max_ap
value: 85.20971719214488
- type: max_f1
value: 77.28446050593702
- task:
type: Clustering
dataset:
type: jinaai/cities_wiki_clustering
name: MTEB WikiCitiesClustering
config: default
split: test
revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
metrics:
- type: v_measure
value: 85.63474850264893