metadata
license: apache-2.0
tags:
- mteb
- arctic
model-index:
- name: arctic-embed-xs
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 65.08955223880598
- type: ap
value: 28.514291209445364
- type: f1
value: 59.2604580112738
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 70.035375
- type: ap
value: 64.29444264250405
- type: f1
value: 69.78382333907138
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 35.343999999999994
- type: f1
value: 34.69618251902858
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 28.592000000000002
- type: map_at_10
value: 43.597
- type: map_at_100
value: 44.614
- type: map_at_1000
value: 44.624
- type: map_at_3
value: 38.928000000000004
- type: map_at_5
value: 41.453
- type: mrr_at_1
value: 29.232000000000003
- type: mrr_at_10
value: 43.829
- type: mrr_at_100
value: 44.852
- type: mrr_at_1000
value: 44.862
- type: mrr_at_3
value: 39.118
- type: mrr_at_5
value: 41.703
- type: ndcg_at_1
value: 28.592000000000002
- type: ndcg_at_10
value: 52.081
- type: ndcg_at_100
value: 56.37
- type: ndcg_at_1000
value: 56.598000000000006
- type: ndcg_at_3
value: 42.42
- type: ndcg_at_5
value: 46.965
- type: precision_at_1
value: 28.592000000000002
- type: precision_at_10
value: 7.922999999999999
- type: precision_at_100
value: 0.979
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 17.52
- type: precision_at_5
value: 12.717
- type: recall_at_1
value: 28.592000000000002
- type: recall_at_10
value: 79.232
- type: recall_at_100
value: 97.866
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 52.559999999999995
- type: recall_at_5
value: 63.585
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 43.50220588953974
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 32.08725826118282
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 60.25381587694928
- type: mrr
value: 73.79776194873148
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 85.47489332445278
- type: cos_sim_spearman
value: 84.05432487336698
- type: euclidean_pearson
value: 84.5108222177219
- type: euclidean_spearman
value: 84.05432487336698
- type: manhattan_pearson
value: 84.20440618321464
- type: manhattan_spearman
value: 83.9290208134097
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 76.37337662337663
- type: f1
value: 75.33296834885043
- task:
type: Clustering
dataset:
type: jinaai/big-patent-clustering
name: MTEB BigPatentClustering
config: default
split: test
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
metrics:
- type: v_measure
value: 21.31174373264835
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 34.481973521597844
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 26.14094256567341
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-android
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 32.527
- type: map_at_10
value: 43.699
- type: map_at_100
value: 45.03
- type: map_at_1000
value: 45.157000000000004
- type: map_at_3
value: 39.943
- type: map_at_5
value: 42.324
- type: mrr_at_1
value: 39.771
- type: mrr_at_10
value: 49.277
- type: mrr_at_100
value: 49.956
- type: mrr_at_1000
value: 50.005
- type: mrr_at_3
value: 46.304
- type: mrr_at_5
value: 48.493
- type: ndcg_at_1
value: 39.771
- type: ndcg_at_10
value: 49.957
- type: ndcg_at_100
value: 54.678000000000004
- type: ndcg_at_1000
value: 56.751
- type: ndcg_at_3
value: 44.608
- type: ndcg_at_5
value: 47.687000000000005
- type: precision_at_1
value: 39.771
- type: precision_at_10
value: 9.557
- type: precision_at_100
value: 1.5010000000000001
- type: precision_at_1000
value: 0.194
- type: precision_at_3
value: 21.173000000000002
- type: precision_at_5
value: 15.794
- type: recall_at_1
value: 32.527
- type: recall_at_10
value: 61.791
- type: recall_at_100
value: 81.49300000000001
- type: recall_at_1000
value: 95.014
- type: recall_at_3
value: 46.605000000000004
- type: recall_at_5
value: 54.83
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-english
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 29.424
- type: map_at_10
value: 38.667
- type: map_at_100
value: 39.771
- type: map_at_1000
value: 39.899
- type: map_at_3
value: 35.91
- type: map_at_5
value: 37.45
- type: mrr_at_1
value: 36.687999999999995
- type: mrr_at_10
value: 44.673
- type: mrr_at_100
value: 45.289
- type: mrr_at_1000
value: 45.338
- type: mrr_at_3
value: 42.601
- type: mrr_at_5
value: 43.875
- type: ndcg_at_1
value: 36.687999999999995
- type: ndcg_at_10
value: 44.013000000000005
- type: ndcg_at_100
value: 48.13
- type: ndcg_at_1000
value: 50.294000000000004
- type: ndcg_at_3
value: 40.056999999999995
- type: ndcg_at_5
value: 41.902
- type: precision_at_1
value: 36.687999999999995
- type: precision_at_10
value: 8.158999999999999
- type: precision_at_100
value: 1.321
- type: precision_at_1000
value: 0.179
- type: precision_at_3
value: 19.045
- type: precision_at_5
value: 13.427
- type: recall_at_1
value: 29.424
- type: recall_at_10
value: 53.08500000000001
- type: recall_at_100
value: 70.679
- type: recall_at_1000
value: 84.66
- type: recall_at_3
value: 41.399
- type: recall_at_5
value: 46.632
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gaming
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 39.747
- type: map_at_10
value: 51.452
- type: map_at_100
value: 52.384
- type: map_at_1000
value: 52.437
- type: map_at_3
value: 48.213
- type: map_at_5
value: 50.195
- type: mrr_at_1
value: 45.391999999999996
- type: mrr_at_10
value: 54.928
- type: mrr_at_100
value: 55.532000000000004
- type: mrr_at_1000
value: 55.565
- type: mrr_at_3
value: 52.456
- type: mrr_at_5
value: 54.054
- type: ndcg_at_1
value: 45.391999999999996
- type: ndcg_at_10
value: 57.055
- type: ndcg_at_100
value: 60.751999999999995
- type: ndcg_at_1000
value: 61.864
- type: ndcg_at_3
value: 51.662
- type: ndcg_at_5
value: 54.613
- type: precision_at_1
value: 45.391999999999996
- type: precision_at_10
value: 9.103
- type: precision_at_100
value: 1.1780000000000002
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 22.717000000000002
- type: precision_at_5
value: 15.812000000000001
- type: recall_at_1
value: 39.747
- type: recall_at_10
value: 70.10499999999999
- type: recall_at_100
value: 86.23100000000001
- type: recall_at_1000
value: 94.025
- type: recall_at_3
value: 55.899
- type: recall_at_5
value: 63.05500000000001
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gis
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 27.168999999999997
- type: map_at_10
value: 34.975
- type: map_at_100
value: 35.94
- type: map_at_1000
value: 36.021
- type: map_at_3
value: 32.35
- type: map_at_5
value: 33.831
- type: mrr_at_1
value: 28.701
- type: mrr_at_10
value: 36.698
- type: mrr_at_100
value: 37.546
- type: mrr_at_1000
value: 37.613
- type: mrr_at_3
value: 34.256
- type: mrr_at_5
value: 35.685
- type: ndcg_at_1
value: 28.701
- type: ndcg_at_10
value: 39.639
- type: ndcg_at_100
value: 44.389
- type: ndcg_at_1000
value: 46.46
- type: ndcg_at_3
value: 34.52
- type: ndcg_at_5
value: 37.076
- type: precision_at_1
value: 28.701
- type: precision_at_10
value: 5.955
- type: precision_at_100
value: 0.8880000000000001
- type: precision_at_1000
value: 0.109
- type: precision_at_3
value: 14.274999999999999
- type: precision_at_5
value: 10.011000000000001
- type: recall_at_1
value: 27.168999999999997
- type: recall_at_10
value: 52.347
- type: recall_at_100
value: 74.1
- type: recall_at_1000
value: 89.739
- type: recall_at_3
value: 38.567
- type: recall_at_5
value: 44.767
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-mathematica
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 15.872
- type: map_at_10
value: 23.153000000000002
- type: map_at_100
value: 24.311
- type: map_at_1000
value: 24.432000000000002
- type: map_at_3
value: 20.707
- type: map_at_5
value: 21.921
- type: mrr_at_1
value: 19.776
- type: mrr_at_10
value: 27.755999999999997
- type: mrr_at_100
value: 28.709
- type: mrr_at_1000
value: 28.778
- type: mrr_at_3
value: 25.186999999999998
- type: mrr_at_5
value: 26.43
- type: ndcg_at_1
value: 19.776
- type: ndcg_at_10
value: 28.288999999999998
- type: ndcg_at_100
value: 34.011
- type: ndcg_at_1000
value: 36.916
- type: ndcg_at_3
value: 23.551
- type: ndcg_at_5
value: 25.429000000000002
- type: precision_at_1
value: 19.776
- type: precision_at_10
value: 5.311
- type: precision_at_100
value: 0.9440000000000001
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 11.360000000000001
- type: precision_at_5
value: 8.209
- type: recall_at_1
value: 15.872
- type: recall_at_10
value: 39.726
- type: recall_at_100
value: 65.035
- type: recall_at_1000
value: 85.846
- type: recall_at_3
value: 26.432
- type: recall_at_5
value: 31.22
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-physics
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 28.126
- type: map_at_10
value: 37.537
- type: map_at_100
value: 38.807
- type: map_at_1000
value: 38.923
- type: map_at_3
value: 34.65
- type: map_at_5
value: 36.248000000000005
- type: mrr_at_1
value: 34.649
- type: mrr_at_10
value: 42.893
- type: mrr_at_100
value: 43.721
- type: mrr_at_1000
value: 43.775999999999996
- type: mrr_at_3
value: 40.488
- type: mrr_at_5
value: 41.729
- type: ndcg_at_1
value: 34.649
- type: ndcg_at_10
value: 43.072
- type: ndcg_at_100
value: 48.464
- type: ndcg_at_1000
value: 50.724000000000004
- type: ndcg_at_3
value: 38.506
- type: ndcg_at_5
value: 40.522000000000006
- type: precision_at_1
value: 34.649
- type: precision_at_10
value: 7.68
- type: precision_at_100
value: 1.214
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 18.029999999999998
- type: precision_at_5
value: 12.666
- type: recall_at_1
value: 28.126
- type: recall_at_10
value: 54.396
- type: recall_at_100
value: 76.988
- type: recall_at_1000
value: 91.85799999999999
- type: recall_at_3
value: 41.169
- type: recall_at_5
value: 46.658
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-programmers
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 26.68
- type: map_at_10
value: 35.702
- type: map_at_100
value: 36.864999999999995
- type: map_at_1000
value: 36.977
- type: map_at_3
value: 32.828
- type: map_at_5
value: 34.481
- type: mrr_at_1
value: 32.991
- type: mrr_at_10
value: 40.993
- type: mrr_at_100
value: 41.827
- type: mrr_at_1000
value: 41.887
- type: mrr_at_3
value: 38.623000000000005
- type: mrr_at_5
value: 40.021
- type: ndcg_at_1
value: 32.991
- type: ndcg_at_10
value: 41.036
- type: ndcg_at_100
value: 46.294000000000004
- type: ndcg_at_1000
value: 48.644
- type: ndcg_at_3
value: 36.419000000000004
- type: ndcg_at_5
value: 38.618
- type: precision_at_1
value: 32.991
- type: precision_at_10
value: 7.385999999999999
- type: precision_at_100
value: 1.176
- type: precision_at_1000
value: 0.151
- type: precision_at_3
value: 17.122999999999998
- type: precision_at_5
value: 12.215
- type: recall_at_1
value: 26.68
- type: recall_at_10
value: 51.644
- type: recall_at_100
value: 74.55000000000001
- type: recall_at_1000
value: 90.825
- type: recall_at_3
value: 38.579
- type: recall_at_5
value: 44.512
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 26.30825
- type: map_at_10
value: 34.97866666666666
- type: map_at_100
value: 36.109249999999996
- type: map_at_1000
value: 36.22508333333333
- type: map_at_3
value: 32.239083333333326
- type: map_at_5
value: 33.75933333333334
- type: mrr_at_1
value: 31.05308333333333
- type: mrr_at_10
value: 39.099833333333336
- type: mrr_at_100
value: 39.92008333333334
- type: mrr_at_1000
value: 39.980000000000004
- type: mrr_at_3
value: 36.75958333333333
- type: mrr_at_5
value: 38.086416666666665
- type: ndcg_at_1
value: 31.05308333333333
- type: ndcg_at_10
value: 40.11558333333334
- type: ndcg_at_100
value: 45.05966666666667
- type: ndcg_at_1000
value: 47.36516666666667
- type: ndcg_at_3
value: 35.490833333333335
- type: ndcg_at_5
value: 37.64541666666666
- type: precision_at_1
value: 31.05308333333333
- type: precision_at_10
value: 6.968416666666666
- type: precision_at_100
value: 1.1156666666666666
- type: precision_at_1000
value: 0.14950000000000002
- type: precision_at_3
value: 16.123
- type: precision_at_5
value: 11.451166666666666
- type: recall_at_1
value: 26.30825
- type: recall_at_10
value: 51.19283333333333
- type: recall_at_100
value: 73.0285
- type: recall_at_1000
value: 89.11133333333333
- type: recall_at_3
value: 38.26208333333333
- type: recall_at_5
value: 43.855916666666666
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-stats
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 23.363999999999997
- type: map_at_10
value: 30.606
- type: map_at_100
value: 31.491999999999997
- type: map_at_1000
value: 31.578
- type: map_at_3
value: 28.610000000000003
- type: map_at_5
value: 29.602
- type: mrr_at_1
value: 26.38
- type: mrr_at_10
value: 33.472
- type: mrr_at_100
value: 34.299
- type: mrr_at_1000
value: 34.361999999999995
- type: mrr_at_3
value: 31.696999999999996
- type: mrr_at_5
value: 32.503
- type: ndcg_at_1
value: 26.38
- type: ndcg_at_10
value: 34.772999999999996
- type: ndcg_at_100
value: 39.334
- type: ndcg_at_1000
value: 41.676
- type: ndcg_at_3
value: 31.097
- type: ndcg_at_5
value: 32.561
- type: precision_at_1
value: 26.38
- type: precision_at_10
value: 5.475
- type: precision_at_100
value: 0.84
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 13.395000000000001
- type: precision_at_5
value: 9.11
- type: recall_at_1
value: 23.363999999999997
- type: recall_at_10
value: 44.656
- type: recall_at_100
value: 65.77199999999999
- type: recall_at_1000
value: 83.462
- type: recall_at_3
value: 34.213
- type: recall_at_5
value: 38.091
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-tex
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 17.971999999999998
- type: map_at_10
value: 24.913
- type: map_at_100
value: 25.916
- type: map_at_1000
value: 26.049
- type: map_at_3
value: 22.569
- type: map_at_5
value: 23.858999999999998
- type: mrr_at_1
value: 21.748
- type: mrr_at_10
value: 28.711
- type: mrr_at_100
value: 29.535
- type: mrr_at_1000
value: 29.621
- type: mrr_at_3
value: 26.484999999999996
- type: mrr_at_5
value: 27.701999999999998
- type: ndcg_at_1
value: 21.748
- type: ndcg_at_10
value: 29.412
- type: ndcg_at_100
value: 34.204
- type: ndcg_at_1000
value: 37.358000000000004
- type: ndcg_at_3
value: 25.202
- type: ndcg_at_5
value: 27.128000000000004
- type: precision_at_1
value: 21.748
- type: precision_at_10
value: 5.279
- type: precision_at_100
value: 0.902
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 11.551
- type: precision_at_5
value: 8.437999999999999
- type: recall_at_1
value: 17.971999999999998
- type: recall_at_10
value: 39.186
- type: recall_at_100
value: 60.785999999999994
- type: recall_at_1000
value: 83.372
- type: recall_at_3
value: 27.584999999999997
- type: recall_at_5
value: 32.448
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-unix
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 26.684
- type: map_at_10
value: 35.188
- type: map_at_100
value: 36.379
- type: map_at_1000
value: 36.481
- type: map_at_3
value: 32.401
- type: map_at_5
value: 34.132
- type: mrr_at_1
value: 31.063000000000002
- type: mrr_at_10
value: 39.104
- type: mrr_at_100
value: 40.062999999999995
- type: mrr_at_1000
value: 40.119
- type: mrr_at_3
value: 36.692
- type: mrr_at_5
value: 38.161
- type: ndcg_at_1
value: 31.063000000000002
- type: ndcg_at_10
value: 40.096
- type: ndcg_at_100
value: 45.616
- type: ndcg_at_1000
value: 47.869
- type: ndcg_at_3
value: 35.256
- type: ndcg_at_5
value: 37.826
- type: precision_at_1
value: 31.063000000000002
- type: precision_at_10
value: 6.622999999999999
- type: precision_at_100
value: 1.046
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 15.641
- type: precision_at_5
value: 11.231
- type: recall_at_1
value: 26.684
- type: recall_at_10
value: 51.092999999999996
- type: recall_at_100
value: 75.099
- type: recall_at_1000
value: 90.644
- type: recall_at_3
value: 38.063
- type: recall_at_5
value: 44.518
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-webmasters
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 26.249
- type: map_at_10
value: 34.694
- type: map_at_100
value: 36.208
- type: map_at_1000
value: 36.443
- type: map_at_3
value: 31.868000000000002
- type: map_at_5
value: 33.018
- type: mrr_at_1
value: 31.818
- type: mrr_at_10
value: 39.416000000000004
- type: mrr_at_100
value: 40.327
- type: mrr_at_1000
value: 40.388000000000005
- type: mrr_at_3
value: 37.120999999999995
- type: mrr_at_5
value: 38.07
- type: ndcg_at_1
value: 31.818
- type: ndcg_at_10
value: 40.405
- type: ndcg_at_100
value: 45.816
- type: ndcg_at_1000
value: 48.403
- type: ndcg_at_3
value: 35.823
- type: ndcg_at_5
value: 37.191
- type: precision_at_1
value: 31.818
- type: precision_at_10
value: 7.806
- type: precision_at_100
value: 1.518
- type: precision_at_1000
value: 0.241
- type: precision_at_3
value: 16.535
- type: precision_at_5
value: 11.738999999999999
- type: recall_at_1
value: 26.249
- type: recall_at_10
value: 50.928
- type: recall_at_100
value: 75.271
- type: recall_at_1000
value: 91.535
- type: recall_at_3
value: 37.322
- type: recall_at_5
value: 41.318
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-wordpress
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 21.884999999999998
- type: map_at_10
value: 29.158
- type: map_at_100
value: 30.208000000000002
- type: map_at_1000
value: 30.304
- type: map_at_3
value: 26.82
- type: map_at_5
value: 28.051
- type: mrr_at_1
value: 23.66
- type: mrr_at_10
value: 31.277
- type: mrr_at_100
value: 32.237
- type: mrr_at_1000
value: 32.308
- type: mrr_at_3
value: 29.205
- type: mrr_at_5
value: 30.314000000000004
- type: ndcg_at_1
value: 23.66
- type: ndcg_at_10
value: 33.64
- type: ndcg_at_100
value: 39.028
- type: ndcg_at_1000
value: 41.423
- type: ndcg_at_3
value: 29.189
- type: ndcg_at_5
value: 31.191999999999997
- type: precision_at_1
value: 23.66
- type: precision_at_10
value: 5.287
- type: precision_at_100
value: 0.86
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 12.631
- type: precision_at_5
value: 8.762
- type: recall_at_1
value: 21.884999999999998
- type: recall_at_10
value: 45.357
- type: recall_at_100
value: 70.338
- type: recall_at_1000
value: 88.356
- type: recall_at_3
value: 33.312000000000005
- type: recall_at_5
value: 38.222
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 13.058
- type: map_at_10
value: 21.549
- type: map_at_100
value: 23.287
- type: map_at_1000
value: 23.444000000000003
- type: map_at_3
value: 18.18
- type: map_at_5
value: 19.886
- type: mrr_at_1
value: 28.73
- type: mrr_at_10
value: 40.014
- type: mrr_at_100
value: 40.827000000000005
- type: mrr_at_1000
value: 40.866
- type: mrr_at_3
value: 36.602000000000004
- type: mrr_at_5
value: 38.702
- type: ndcg_at_1
value: 28.73
- type: ndcg_at_10
value: 29.881
- type: ndcg_at_100
value: 36.662
- type: ndcg_at_1000
value: 39.641999999999996
- type: ndcg_at_3
value: 24.661
- type: ndcg_at_5
value: 26.548
- type: precision_at_1
value: 28.73
- type: precision_at_10
value: 9.094
- type: precision_at_100
value: 1.6480000000000001
- type: precision_at_1000
value: 0.22100000000000003
- type: precision_at_3
value: 17.98
- type: precision_at_5
value: 13.811000000000002
- type: recall_at_1
value: 13.058
- type: recall_at_10
value: 35.458
- type: recall_at_100
value: 58.719
- type: recall_at_1000
value: 75.495
- type: recall_at_3
value: 22.607
- type: recall_at_5
value: 28.067999999999998
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 8.811
- type: map_at_10
value: 19.134999999999998
- type: map_at_100
value: 26.905
- type: map_at_1000
value: 28.503
- type: map_at_3
value: 13.863
- type: map_at_5
value: 16.062
- type: mrr_at_1
value: 67
- type: mrr_at_10
value: 74.607
- type: mrr_at_100
value: 74.941
- type: mrr_at_1000
value: 74.954
- type: mrr_at_3
value: 73.042
- type: mrr_at_5
value: 73.992
- type: ndcg_at_1
value: 52.87500000000001
- type: ndcg_at_10
value: 40.199
- type: ndcg_at_100
value: 44.901
- type: ndcg_at_1000
value: 52.239999999999995
- type: ndcg_at_3
value: 44.983000000000004
- type: ndcg_at_5
value: 42.137
- type: precision_at_1
value: 67
- type: precision_at_10
value: 31.8
- type: precision_at_100
value: 10.315000000000001
- type: precision_at_1000
value: 2.0420000000000003
- type: precision_at_3
value: 48.667
- type: precision_at_5
value: 40.9
- type: recall_at_1
value: 8.811
- type: recall_at_10
value: 24.503
- type: recall_at_100
value: 51.288999999999994
- type: recall_at_1000
value: 74.827
- type: recall_at_3
value: 15.254999999999999
- type: recall_at_5
value: 18.698999999999998
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 41.839999999999996
- type: f1
value: 37.78718146306379
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 68.47999999999999
- type: map_at_10
value: 78.782
- type: map_at_100
value: 79.021
- type: map_at_1000
value: 79.035
- type: map_at_3
value: 77.389
- type: map_at_5
value: 78.347
- type: mrr_at_1
value: 73.837
- type: mrr_at_10
value: 83.41499999999999
- type: mrr_at_100
value: 83.53399999999999
- type: mrr_at_1000
value: 83.535
- type: mrr_at_3
value: 82.32300000000001
- type: mrr_at_5
value: 83.13000000000001
- type: ndcg_at_1
value: 73.837
- type: ndcg_at_10
value: 83.404
- type: ndcg_at_100
value: 84.287
- type: ndcg_at_1000
value: 84.52199999999999
- type: ndcg_at_3
value: 81.072
- type: ndcg_at_5
value: 82.537
- type: precision_at_1
value: 73.837
- type: precision_at_10
value: 10.254000000000001
- type: precision_at_100
value: 1.088
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 31.538
- type: precision_at_5
value: 19.811
- type: recall_at_1
value: 68.47999999999999
- type: recall_at_10
value: 92.98100000000001
- type: recall_at_100
value: 96.50800000000001
- type: recall_at_1000
value: 97.925
- type: recall_at_3
value: 86.764
- type: recall_at_5
value: 90.39
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 16.786
- type: map_at_10
value: 26.97
- type: map_at_100
value: 28.488000000000003
- type: map_at_1000
value: 28.665000000000003
- type: map_at_3
value: 23.3
- type: map_at_5
value: 25.249
- type: mrr_at_1
value: 33.025
- type: mrr_at_10
value: 41.86
- type: mrr_at_100
value: 42.673
- type: mrr_at_1000
value: 42.714
- type: mrr_at_3
value: 39.403
- type: mrr_at_5
value: 40.723
- type: ndcg_at_1
value: 33.025
- type: ndcg_at_10
value: 34.522999999999996
- type: ndcg_at_100
value: 40.831
- type: ndcg_at_1000
value: 44.01
- type: ndcg_at_3
value: 30.698999999999998
- type: ndcg_at_5
value: 31.832
- type: precision_at_1
value: 33.025
- type: precision_at_10
value: 9.583
- type: precision_at_100
value: 1.619
- type: precision_at_1000
value: 0.22100000000000003
- type: precision_at_3
value: 20.216
- type: precision_at_5
value: 15.031
- type: recall_at_1
value: 16.786
- type: recall_at_10
value: 41.969
- type: recall_at_100
value: 66.353
- type: recall_at_1000
value: 85.299
- type: recall_at_3
value: 28.111000000000004
- type: recall_at_5
value: 33.645
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 37.346000000000004
- type: map_at_10
value: 56.184999999999995
- type: map_at_100
value: 57.062000000000005
- type: map_at_1000
value: 57.126999999999995
- type: map_at_3
value: 52.815
- type: map_at_5
value: 54.893
- type: mrr_at_1
value: 74.693
- type: mrr_at_10
value: 81.128
- type: mrr_at_100
value: 81.356
- type: mrr_at_1000
value: 81.363
- type: mrr_at_3
value: 80.05600000000001
- type: mrr_at_5
value: 80.74
- type: ndcg_at_1
value: 74.693
- type: ndcg_at_10
value: 65.249
- type: ndcg_at_100
value: 68.357
- type: ndcg_at_1000
value: 69.64200000000001
- type: ndcg_at_3
value: 60.377
- type: ndcg_at_5
value: 63.044
- type: precision_at_1
value: 74.693
- type: precision_at_10
value: 13.630999999999998
- type: precision_at_100
value: 1.606
- type: precision_at_1000
value: 0.178
- type: precision_at_3
value: 38.222
- type: precision_at_5
value: 25.040000000000003
- type: recall_at_1
value: 37.346000000000004
- type: recall_at_10
value: 68.157
- type: recall_at_100
value: 80.297
- type: recall_at_1000
value: 88.832
- type: recall_at_3
value: 57.333
- type: recall_at_5
value: 62.6
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 62.80240000000001
- type: ap
value: 58.22949464075975
- type: f1
value: 62.55694937343487
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 20.918
- type: map_at_10
value: 32.732
- type: map_at_100
value: 33.922000000000004
- type: map_at_1000
value: 33.976
- type: map_at_3
value: 29.051
- type: map_at_5
value: 31.101
- type: mrr_at_1
value: 21.418
- type: mrr_at_10
value: 33.284000000000006
- type: mrr_at_100
value: 34.426
- type: mrr_at_1000
value: 34.473
- type: mrr_at_3
value: 29.644
- type: mrr_at_5
value: 31.691000000000003
- type: ndcg_at_1
value: 21.418
- type: ndcg_at_10
value: 39.427
- type: ndcg_at_100
value: 45.190999999999995
- type: ndcg_at_1000
value: 46.544000000000004
- type: ndcg_at_3
value: 31.885
- type: ndcg_at_5
value: 35.555
- type: precision_at_1
value: 21.418
- type: precision_at_10
value: 6.254999999999999
- type: precision_at_100
value: 0.915
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 13.591000000000001
- type: precision_at_5
value: 10.011000000000001
- type: recall_at_1
value: 20.918
- type: recall_at_10
value: 60.074000000000005
- type: recall_at_100
value: 86.726
- type: recall_at_1000
value: 97.116
- type: recall_at_3
value: 39.506
- type: recall_at_5
value: 48.319
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 90.79799361605106
- type: f1
value: 90.0757957511057
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 58.00501595987233
- type: f1
value: 39.85731569133947
- task:
type: Classification
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClassification (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: accuracy
value: 77.10970464135022
- type: f1
value: 76.12037616356896
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringP2P (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 69.81323966287493
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringS2S (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 33.112774215788455
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 63.51042367182246
- type: f1
value: 60.99310361578824
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 71.0053799596503
- type: f1
value: 69.7794673003686
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 30.56899174856954
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.21848014733929
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.256308756916646
- type: mrr
value: 31.123872086825656
- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 5.07
- type: map_at_10
value: 11.286999999999999
- type: map_at_100
value: 13.630999999999998
- type: map_at_1000
value: 14.844
- type: map_at_3
value: 8.395
- type: map_at_5
value: 9.721
- type: mrr_at_1
value: 41.486000000000004
- type: mrr_at_10
value: 51.041000000000004
- type: mrr_at_100
value: 51.661
- type: mrr_at_1000
value: 51.7
- type: mrr_at_3
value: 49.226
- type: mrr_at_5
value: 50.526
- type: ndcg_at_1
value: 39.783
- type: ndcg_at_10
value: 30.885
- type: ndcg_at_100
value: 27.459
- type: ndcg_at_1000
value: 35.988
- type: ndcg_at_3
value: 36.705
- type: ndcg_at_5
value: 34.156
- type: precision_at_1
value: 41.486000000000004
- type: precision_at_10
value: 22.415
- type: precision_at_100
value: 6.819999999999999
- type: precision_at_1000
value: 1.8980000000000001
- type: precision_at_3
value: 34.572
- type: precision_at_5
value: 29.287999999999997
- type: recall_at_1
value: 5.07
- type: recall_at_10
value: 14.576
- type: recall_at_100
value: 27.112000000000002
- type: recall_at_1000
value: 57.995
- type: recall_at_3
value: 9.242
- type: recall_at_5
value: 11.668000000000001
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 32.263999999999996
- type: map_at_10
value: 47.219
- type: map_at_100
value: 48.209999999999994
- type: map_at_1000
value: 48.24
- type: map_at_3
value: 42.905
- type: map_at_5
value: 45.501000000000005
- type: mrr_at_1
value: 36.153
- type: mrr_at_10
value: 49.636
- type: mrr_at_100
value: 50.357
- type: mrr_at_1000
value: 50.378
- type: mrr_at_3
value: 46.094
- type: mrr_at_5
value: 48.233
- type: ndcg_at_1
value: 36.124
- type: ndcg_at_10
value: 54.764
- type: ndcg_at_100
value: 58.867999999999995
- type: ndcg_at_1000
value: 59.548
- type: ndcg_at_3
value: 46.717999999999996
- type: ndcg_at_5
value: 50.981
- type: precision_at_1
value: 36.124
- type: precision_at_10
value: 8.931000000000001
- type: precision_at_100
value: 1.126
- type: precision_at_1000
value: 0.11900000000000001
- type: precision_at_3
value: 21.051000000000002
- type: precision_at_5
value: 15.104000000000001
- type: recall_at_1
value: 32.263999999999996
- type: recall_at_10
value: 75.39099999999999
- type: recall_at_100
value: 93.038
- type: recall_at_1000
value: 98.006
- type: recall_at_3
value: 54.562999999999995
- type: recall_at_5
value: 64.352
- task:
type: Classification
dataset:
type: ag_news
name: MTEB NewsClassification
config: default
split: test
revision: eb185aade064a813bc0b7f42de02595523103ca4
metrics:
- type: accuracy
value: 77.75
- type: f1
value: 77.504243291547
- 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: 57.9482264289061
- type: cos_sim_f1
value: 62.444061962134256
- type: cos_sim_precision
value: 45.3953953953954
- type: cos_sim_recall
value: 100
- type: dot_accuracy
value: 61.75000000000001
- type: dot_ap
value: 57.94808038610475
- type: dot_f1
value: 62.444061962134256
- type: dot_precision
value: 45.3953953953954
- type: dot_recall
value: 100
- type: euclidean_accuracy
value: 61.75000000000001
- type: euclidean_ap
value: 57.94808038610475
- type: euclidean_f1
value: 62.444061962134256
- type: euclidean_precision
value: 45.3953953953954
- type: euclidean_recall
value: 100
- type: manhattan_accuracy
value: 61.7
- type: manhattan_ap
value: 57.996119308184966
- type: manhattan_f1
value: 62.46078773091669
- type: manhattan_precision
value: 45.66768603465851
- type: manhattan_recall
value: 98.78721058434398
- type: max_accuracy
value: 61.75000000000001
- type: max_ap
value: 57.996119308184966
- type: max_f1
value: 62.46078773091669
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 69.001
- type: map_at_10
value: 82.573
- type: map_at_100
value: 83.226
- type: map_at_1000
value: 83.246
- type: map_at_3
value: 79.625
- type: map_at_5
value: 81.491
- type: mrr_at_1
value: 79.44
- type: mrr_at_10
value: 85.928
- type: mrr_at_100
value: 86.05199999999999
- type: mrr_at_1000
value: 86.054
- type: mrr_at_3
value: 84.847
- type: mrr_at_5
value: 85.596
- type: ndcg_at_1
value: 79.41
- type: ndcg_at_10
value: 86.568
- type: ndcg_at_100
value: 87.965
- type: ndcg_at_1000
value: 88.134
- type: ndcg_at_3
value: 83.55900000000001
- type: ndcg_at_5
value: 85.244
- type: precision_at_1
value: 79.41
- type: precision_at_10
value: 13.108
- type: precision_at_100
value: 1.509
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.443
- type: precision_at_5
value: 24.03
- type: recall_at_1
value: 69.001
- type: recall_at_10
value: 94.132
- type: recall_at_100
value: 99.043
- type: recall_at_1000
value: 99.878
- type: recall_at_3
value: 85.492
- type: recall_at_5
value: 90.226
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 48.3161352736264
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 57.83784484156747
- task:
type: Retrieval
dataset:
type: mteb/scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
metrics:
- type: map_at_1
value: 4.403
- type: map_at_10
value: 10.922
- type: map_at_100
value: 12.626000000000001
- type: map_at_1000
value: 12.883
- type: map_at_3
value: 7.982
- type: map_at_5
value: 9.442
- type: mrr_at_1
value: 21.7
- type: mrr_at_10
value: 31.653
- type: mrr_at_100
value: 32.757999999999996
- type: mrr_at_1000
value: 32.824999999999996
- type: mrr_at_3
value: 28.266999999999996
- type: mrr_at_5
value: 30.127
- type: ndcg_at_1
value: 21.7
- type: ndcg_at_10
value: 18.355
- type: ndcg_at_100
value: 25.228
- type: ndcg_at_1000
value: 30.164
- type: ndcg_at_3
value: 17.549
- type: ndcg_at_5
value: 15.260000000000002
- type: precision_at_1
value: 21.7
- type: precision_at_10
value: 9.47
- type: precision_at_100
value: 1.9290000000000003
- type: precision_at_1000
value: 0.312
- type: precision_at_3
value: 16.3
- type: precision_at_5
value: 13.28
- type: recall_at_1
value: 4.403
- type: recall_at_10
value: 19.18
- type: recall_at_100
value: 39.182
- type: recall_at_1000
value: 63.378
- type: recall_at_3
value: 9.934999999999999
- type: recall_at_5
value: 13.459999999999999
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 76.90841073432534
- type: cos_sim_spearman
value: 69.2566375434526
- type: euclidean_pearson
value: 73.00183878559413
- type: euclidean_spearman
value: 69.25664656235413
- type: manhattan_pearson
value: 72.89594756197533
- type: manhattan_spearman
value: 69.23247111043545
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 69.60878511794063
- type: cos_sim_spearman
value: 65.89916377105551
- type: euclidean_pearson
value: 66.90761876557181
- type: euclidean_spearman
value: 65.89915018368384
- type: manhattan_pearson
value: 66.78502575257721
- type: manhattan_spearman
value: 65.79977053467938
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 77.2869334987418
- type: cos_sim_spearman
value: 77.86961921643416
- type: euclidean_pearson
value: 77.43179820479914
- type: euclidean_spearman
value: 77.86961921643416
- type: manhattan_pearson
value: 77.18900647348373
- type: manhattan_spearman
value: 77.61209060062608
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 76.26453932960364
- type: cos_sim_spearman
value: 72.81574657995401
- type: euclidean_pearson
value: 75.0708953437423
- type: euclidean_spearman
value: 72.81574657995401
- type: manhattan_pearson
value: 74.88396609999512
- type: manhattan_spearman
value: 72.65437562156805
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 82.37827653919395
- type: cos_sim_spearman
value: 83.4885552472602
- type: euclidean_pearson
value: 82.89377087926749
- type: euclidean_spearman
value: 83.4885552472602
- type: manhattan_pearson
value: 82.82440771787735
- type: manhattan_spearman
value: 83.41449537888975
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 78.7995043673964
- type: cos_sim_spearman
value: 80.57804447517638
- type: euclidean_pearson
value: 80.03013884278195
- type: euclidean_spearman
value: 80.57804447517638
- type: manhattan_pearson
value: 80.13406111544424
- type: manhattan_spearman
value: 80.65354602648962
- 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: 83.63565989937278
- type: cos_sim_spearman
value: 84.4948593656943
- type: euclidean_pearson
value: 84.68743074820951
- type: euclidean_spearman
value: 84.4948593656943
- type: manhattan_pearson
value: 84.43639397781811
- type: manhattan_spearman
value: 84.32595552115242
- 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: 65.06382649277246
- type: cos_sim_spearman
value: 66.28447782018655
- type: euclidean_pearson
value: 67.09895930908392
- type: euclidean_spearman
value: 66.28447782018655
- type: manhattan_pearson
value: 66.96342453888376
- type: manhattan_spearman
value: 66.33876259551842
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 78.43883428940346
- type: cos_sim_spearman
value: 79.18395553127085
- type: euclidean_pearson
value: 79.22986635457109
- type: euclidean_spearman
value: 79.18395553127085
- type: manhattan_pearson
value: 79.10921229934691
- type: manhattan_spearman
value: 79.02283553930171
- 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: 78.43883433444418
- type: cos_sim_spearman
value: 79.18395553127085
- type: euclidean_pearson
value: 79.22986642351681
- type: euclidean_spearman
value: 79.18395553127085
- type: manhattan_pearson
value: 79.10921236746302
- type: manhattan_spearman
value: 79.02283553930171
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 76.9361627171417
- type: mrr
value: 93.06577046773126
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 50.693999999999996
- type: map_at_10
value: 59.784000000000006
- type: map_at_100
value: 60.443000000000005
- type: map_at_1000
value: 60.480000000000004
- type: map_at_3
value: 57.028
- type: map_at_5
value: 58.306999999999995
- type: mrr_at_1
value: 53.333
- type: mrr_at_10
value: 61.565000000000005
- type: mrr_at_100
value: 62.095
- type: mrr_at_1000
value: 62.131
- type: mrr_at_3
value: 59.721999999999994
- type: mrr_at_5
value: 60.589000000000006
- type: ndcg_at_1
value: 53.333
- type: ndcg_at_10
value: 64.512
- type: ndcg_at_100
value: 67.366
- type: ndcg_at_1000
value: 68.46799999999999
- type: ndcg_at_3
value: 59.748999999999995
- type: ndcg_at_5
value: 61.526
- type: precision_at_1
value: 53.333
- type: precision_at_10
value: 8.733
- type: precision_at_100
value: 1.027
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 23.222
- type: precision_at_5
value: 15.2
- type: recall_at_1
value: 50.693999999999996
- type: recall_at_10
value: 77.333
- type: recall_at_100
value: 90.10000000000001
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 64.39399999999999
- type: recall_at_5
value: 68.7
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81386138613861
- type: cos_sim_ap
value: 94.96375600031361
- type: cos_sim_f1
value: 90.36885245901641
- type: cos_sim_precision
value: 92.64705882352942
- type: cos_sim_recall
value: 88.2
- type: dot_accuracy
value: 99.81386138613861
- type: dot_ap
value: 94.96375600031361
- type: dot_f1
value: 90.36885245901641
- type: dot_precision
value: 92.64705882352942
- type: dot_recall
value: 88.2
- type: euclidean_accuracy
value: 99.81386138613861
- type: euclidean_ap
value: 94.96375600031361
- type: euclidean_f1
value: 90.36885245901641
- type: euclidean_precision
value: 92.64705882352942
- type: euclidean_recall
value: 88.2
- type: manhattan_accuracy
value: 99.81287128712871
- type: manhattan_ap
value: 94.92563500640084
- type: manhattan_f1
value: 90.27277406073082
- type: manhattan_precision
value: 93.00106044538707
- type: manhattan_recall
value: 87.7
- type: max_accuracy
value: 99.81386138613861
- type: max_ap
value: 94.96375600031361
- type: max_f1
value: 90.36885245901641
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 57.486984956276274
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 34.58453023612073
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 50.16317315282306
- type: mrr
value: 50.82617137764197
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.2927995133324
- type: cos_sim_spearman
value: 30.09648622523191
- type: dot_pearson
value: 30.29279853541771
- type: dot_spearman
value: 30.09648622523191
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.23500000000000001
- type: map_at_10
value: 2.01
- type: map_at_100
value: 12.064
- type: map_at_1000
value: 27.437
- type: map_at_3
value: 0.6649999999999999
- type: map_at_5
value: 1.0959999999999999
- type: mrr_at_1
value: 88
- type: mrr_at_10
value: 92.667
- type: mrr_at_100
value: 92.667
- type: mrr_at_1000
value: 92.667
- type: mrr_at_3
value: 91.667
- type: mrr_at_5
value: 92.667
- type: ndcg_at_1
value: 84
- type: ndcg_at_10
value: 79.431
- type: ndcg_at_100
value: 60.914
- type: ndcg_at_1000
value: 52.005
- type: ndcg_at_3
value: 82.285
- type: ndcg_at_5
value: 81.565
- type: precision_at_1
value: 88
- type: precision_at_10
value: 84.8
- type: precision_at_100
value: 62.32
- type: precision_at_1000
value: 23.014000000000003
- type: precision_at_3
value: 86.667
- type: precision_at_5
value: 87.2
- type: recall_at_1
value: 0.23500000000000001
- type: recall_at_10
value: 2.19
- type: recall_at_100
value: 14.904
- type: recall_at_1000
value: 47.875
- type: recall_at_3
value: 0.695
- type: recall_at_5
value: 1.165
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 3.639
- type: map_at_10
value: 14.184
- type: map_at_100
value: 20.61
- type: map_at_1000
value: 22.377
- type: map_at_3
value: 9.163
- type: map_at_5
value: 10.773000000000001
- type: mrr_at_1
value: 46.939
- type: mrr_at_10
value: 59.345000000000006
- type: mrr_at_100
value: 60.07599999999999
- type: mrr_at_1000
value: 60.07599999999999
- type: mrr_at_3
value: 55.782
- type: mrr_at_5
value: 58.231
- type: ndcg_at_1
value: 41.837
- type: ndcg_at_10
value: 32.789
- type: ndcg_at_100
value: 42.232
- type: ndcg_at_1000
value: 53.900999999999996
- type: ndcg_at_3
value: 41.963
- type: ndcg_at_5
value: 35.983
- type: precision_at_1
value: 46.939
- type: precision_at_10
value: 28.163
- type: precision_at_100
value: 8.102
- type: precision_at_1000
value: 1.59
- type: precision_at_3
value: 44.897999999999996
- type: precision_at_5
value: 34.694
- type: recall_at_1
value: 3.639
- type: recall_at_10
value: 19.308
- type: recall_at_100
value: 48.992000000000004
- type: recall_at_1000
value: 84.59400000000001
- type: recall_at_3
value: 9.956
- type: recall_at_5
value: 12.33
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 64.305
- type: ap
value: 11.330746746072599
- type: f1
value: 49.290704382387865
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 56.1941143180532
- type: f1
value: 56.40189765095578
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 36.28189332526842
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.1912737676581
- type: cos_sim_ap
value: 64.31536990146257
- type: cos_sim_f1
value: 61.095167030191696
- type: cos_sim_precision
value: 54.074375127006704
- type: cos_sim_recall
value: 70.21108179419525
- type: dot_accuracy
value: 83.1912737676581
- type: dot_ap
value: 64.31539216162541
- type: dot_f1
value: 61.095167030191696
- type: dot_precision
value: 54.074375127006704
- type: dot_recall
value: 70.21108179419525
- type: euclidean_accuracy
value: 83.1912737676581
- type: euclidean_ap
value: 64.31538391358727
- type: euclidean_f1
value: 61.095167030191696
- type: euclidean_precision
value: 54.074375127006704
- type: euclidean_recall
value: 70.21108179419525
- type: manhattan_accuracy
value: 83.07206294331525
- type: manhattan_ap
value: 64.14646315556838
- type: manhattan_f1
value: 61.194029850746254
- type: manhattan_precision
value: 54.166666666666664
- type: manhattan_recall
value: 70.31662269129288
- type: max_accuracy
value: 83.1912737676581
- type: max_ap
value: 64.31539216162541
- type: max_f1
value: 61.194029850746254
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.38242713548337
- type: cos_sim_ap
value: 84.70041255196017
- type: cos_sim_f1
value: 77.13222561986515
- type: cos_sim_precision
value: 73.95266690215472
- type: cos_sim_recall
value: 80.59747459193102
- type: dot_accuracy
value: 88.38242713548337
- type: dot_ap
value: 84.7004118720222
- type: dot_f1
value: 77.13222561986515
- type: dot_precision
value: 73.95266690215472
- type: dot_recall
value: 80.59747459193102
- type: euclidean_accuracy
value: 88.38242713548337
- type: euclidean_ap
value: 84.70041593996575
- type: euclidean_f1
value: 77.13222561986515
- type: euclidean_precision
value: 73.95266690215472
- type: euclidean_recall
value: 80.59747459193102
- type: manhattan_accuracy
value: 88.36108200411378
- type: manhattan_ap
value: 84.66897701572054
- type: manhattan_f1
value: 77.00707640360645
- type: manhattan_precision
value: 72.17695778062082
- type: manhattan_recall
value: 82.53002771789343
- type: max_accuracy
value: 88.38242713548337
- type: max_ap
value: 84.70041593996575
- type: max_f1
value: 77.13222561986515
- task:
type: Clustering
dataset:
type: jinaai/cities_wiki_clustering
name: MTEB WikiCitiesClustering
config: default
split: test
revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
metrics:
- type: v_measure
value: 81.46426354153643