metadata
license: apache-2.0
tags:
- mteb
- arctic
- arctic-embed
model-index:
- name: med
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 74.80597014925374
- type: ap
value: 37.911466766189875
- type: f1
value: 68.88606927542106
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 78.402275
- type: ap
value: 73.03294793248114
- type: f1
value: 78.3147786132161
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 36.717999999999996
- type: f1
value: 35.918044248787766
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 34.495
- type: map_at_10
value: 50.236000000000004
- type: map_at_100
value: 50.944
- type: map_at_1000
value: 50.94499999999999
- type: map_at_3
value: 45.341
- type: map_at_5
value: 48.286
- type: mrr_at_1
value: 35.135
- type: mrr_at_10
value: 50.471
- type: mrr_at_100
value: 51.185
- type: mrr_at_1000
value: 51.187000000000005
- type: mrr_at_3
value: 45.602
- type: mrr_at_5
value: 48.468
- type: ndcg_at_1
value: 34.495
- type: ndcg_at_10
value: 59.086000000000006
- type: ndcg_at_100
value: 61.937
- type: ndcg_at_1000
value: 61.966
- type: ndcg_at_3
value: 49.062
- type: ndcg_at_5
value: 54.367
- type: precision_at_1
value: 34.495
- type: precision_at_10
value: 8.734
- type: precision_at_100
value: 0.9939999999999999
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 19.962
- type: precision_at_5
value: 14.552000000000001
- type: recall_at_1
value: 34.495
- type: recall_at_10
value: 87.33999999999999
- type: recall_at_100
value: 99.431
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 59.885999999999996
- type: recall_at_5
value: 72.76
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 47.46440874635501
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 38.28720154213723
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 60.34614226394902
- type: mrr
value: 75.05628105351096
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.41072716728198
- type: cos_sim_spearman
value: 86.34534093114372
- type: euclidean_pearson
value: 85.34009667750838
- type: euclidean_spearman
value: 86.34534093114372
- type: manhattan_pearson
value: 85.2158833586889
- type: manhattan_spearman
value: 86.60920236509224
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 80.06493506493507
- type: f1
value: 79.28108600339833
- task:
type: Clustering
dataset:
type: jinaai/big-patent-clustering
name: MTEB BigPatentClustering
config: default
split: test
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
metrics:
- type: v_measure
value: 20.545049432417287
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 37.54369718479804
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 32.64941588219162
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-android
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 37.264
- type: map_at_10
value: 49.43
- type: map_at_100
value: 50.967
- type: map_at_1000
value: 51.08200000000001
- type: map_at_3
value: 45.742
- type: map_at_5
value: 47.764
- type: mrr_at_1
value: 44.921
- type: mrr_at_10
value: 54.879999999999995
- type: mrr_at_100
value: 55.525000000000006
- type: mrr_at_1000
value: 55.565
- type: mrr_at_3
value: 52.480000000000004
- type: mrr_at_5
value: 53.86
- type: ndcg_at_1
value: 44.921
- type: ndcg_at_10
value: 55.664
- type: ndcg_at_100
value: 60.488
- type: ndcg_at_1000
value: 62.138000000000005
- type: ndcg_at_3
value: 50.797000000000004
- type: ndcg_at_5
value: 52.94799999999999
- type: precision_at_1
value: 44.921
- type: precision_at_10
value: 10.587
- type: precision_at_100
value: 1.629
- type: precision_at_1000
value: 0.203
- type: precision_at_3
value: 24.034
- type: precision_at_5
value: 17.224999999999998
- type: recall_at_1
value: 37.264
- type: recall_at_10
value: 67.15
- type: recall_at_100
value: 86.811
- type: recall_at_1000
value: 97.172
- type: recall_at_3
value: 53.15800000000001
- type: recall_at_5
value: 59.116
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-english
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 36.237
- type: map_at_10
value: 47.941
- type: map_at_100
value: 49.131
- type: map_at_1000
value: 49.26
- type: map_at_3
value: 44.561
- type: map_at_5
value: 46.28
- type: mrr_at_1
value: 45.605000000000004
- type: mrr_at_10
value: 54.039
- type: mrr_at_100
value: 54.653
- type: mrr_at_1000
value: 54.688
- type: mrr_at_3
value: 52.006
- type: mrr_at_5
value: 53.096
- type: ndcg_at_1
value: 45.605000000000004
- type: ndcg_at_10
value: 53.916
- type: ndcg_at_100
value: 57.745999999999995
- type: ndcg_at_1000
value: 59.492999999999995
- type: ndcg_at_3
value: 49.774
- type: ndcg_at_5
value: 51.434999999999995
- type: precision_at_1
value: 45.605000000000004
- type: precision_at_10
value: 10.229000000000001
- type: precision_at_100
value: 1.55
- type: precision_at_1000
value: 0.2
- type: precision_at_3
value: 24.098
- type: precision_at_5
value: 16.726
- type: recall_at_1
value: 36.237
- type: recall_at_10
value: 64.03
- type: recall_at_100
value: 80.423
- type: recall_at_1000
value: 91.03
- type: recall_at_3
value: 51.20400000000001
- type: recall_at_5
value: 56.298
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gaming
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 47.278
- type: map_at_10
value: 59.757000000000005
- type: map_at_100
value: 60.67
- type: map_at_1000
value: 60.714
- type: map_at_3
value: 56.714
- type: map_at_5
value: 58.453
- type: mrr_at_1
value: 53.73
- type: mrr_at_10
value: 62.970000000000006
- type: mrr_at_100
value: 63.507999999999996
- type: mrr_at_1000
value: 63.53
- type: mrr_at_3
value: 60.909
- type: mrr_at_5
value: 62.172000000000004
- type: ndcg_at_1
value: 53.73
- type: ndcg_at_10
value: 64.97
- type: ndcg_at_100
value: 68.394
- type: ndcg_at_1000
value: 69.255
- type: ndcg_at_3
value: 60.228
- type: ndcg_at_5
value: 62.617999999999995
- type: precision_at_1
value: 53.73
- type: precision_at_10
value: 10.056
- type: precision_at_100
value: 1.265
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 26.332
- type: precision_at_5
value: 17.743000000000002
- type: recall_at_1
value: 47.278
- type: recall_at_10
value: 76.86500000000001
- type: recall_at_100
value: 91.582
- type: recall_at_1000
value: 97.583
- type: recall_at_3
value: 64.443
- type: recall_at_5
value: 70.283
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gis
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 29.702
- type: map_at_10
value: 39.463
- type: map_at_100
value: 40.508
- type: map_at_1000
value: 40.579
- type: map_at_3
value: 36.748999999999995
- type: map_at_5
value: 38.296
- type: mrr_at_1
value: 31.977
- type: mrr_at_10
value: 41.739
- type: mrr_at_100
value: 42.586
- type: mrr_at_1000
value: 42.636
- type: mrr_at_3
value: 39.096
- type: mrr_at_5
value: 40.695
- type: ndcg_at_1
value: 31.977
- type: ndcg_at_10
value: 44.855000000000004
- type: ndcg_at_100
value: 49.712
- type: ndcg_at_1000
value: 51.443000000000005
- type: ndcg_at_3
value: 39.585
- type: ndcg_at_5
value: 42.244
- type: precision_at_1
value: 31.977
- type: precision_at_10
value: 6.768000000000001
- type: precision_at_100
value: 0.9690000000000001
- type: precision_at_1000
value: 0.116
- type: precision_at_3
value: 16.761
- type: precision_at_5
value: 11.593
- type: recall_at_1
value: 29.702
- type: recall_at_10
value: 59.082
- type: recall_at_100
value: 80.92
- type: recall_at_1000
value: 93.728
- type: recall_at_3
value: 45.212
- type: recall_at_5
value: 51.449
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-mathematica
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 21.336
- type: map_at_10
value: 30.137999999999998
- type: map_at_100
value: 31.385
- type: map_at_1000
value: 31.495
- type: map_at_3
value: 27.481
- type: map_at_5
value: 28.772
- type: mrr_at_1
value: 25.871
- type: mrr_at_10
value: 34.686
- type: mrr_at_100
value: 35.649
- type: mrr_at_1000
value: 35.705
- type: mrr_at_3
value: 32.09
- type: mrr_at_5
value: 33.52
- type: ndcg_at_1
value: 25.871
- type: ndcg_at_10
value: 35.617
- type: ndcg_at_100
value: 41.272999999999996
- type: ndcg_at_1000
value: 43.725
- type: ndcg_at_3
value: 30.653999999999996
- type: ndcg_at_5
value: 32.714
- type: precision_at_1
value: 25.871
- type: precision_at_10
value: 6.4799999999999995
- type: precision_at_100
value: 1.0699999999999998
- type: precision_at_1000
value: 0.13999999999999999
- type: precision_at_3
value: 14.469000000000001
- type: precision_at_5
value: 10.274
- type: recall_at_1
value: 21.336
- type: recall_at_10
value: 47.746
- type: recall_at_100
value: 71.773
- type: recall_at_1000
value: 89.05199999999999
- type: recall_at_3
value: 34.172999999999995
- type: recall_at_5
value: 39.397999999999996
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-physics
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 34.424
- type: map_at_10
value: 45.647999999999996
- type: map_at_100
value: 46.907
- type: map_at_1000
value: 47.010999999999996
- type: map_at_3
value: 42.427
- type: map_at_5
value: 44.285000000000004
- type: mrr_at_1
value: 41.867
- type: mrr_at_10
value: 51.17699999999999
- type: mrr_at_100
value: 51.937
- type: mrr_at_1000
value: 51.975
- type: mrr_at_3
value: 48.941
- type: mrr_at_5
value: 50.322
- type: ndcg_at_1
value: 41.867
- type: ndcg_at_10
value: 51.534
- type: ndcg_at_100
value: 56.696999999999996
- type: ndcg_at_1000
value: 58.475
- type: ndcg_at_3
value: 46.835
- type: ndcg_at_5
value: 49.161
- type: precision_at_1
value: 41.867
- type: precision_at_10
value: 9.134
- type: precision_at_100
value: 1.362
- type: precision_at_1000
value: 0.17099999999999999
- type: precision_at_3
value: 22.073
- type: precision_at_5
value: 15.495999999999999
- type: recall_at_1
value: 34.424
- type: recall_at_10
value: 63.237
- type: recall_at_100
value: 84.774
- type: recall_at_1000
value: 95.987
- type: recall_at_3
value: 49.888
- type: recall_at_5
value: 55.940999999999995
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-programmers
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 30.72
- type: map_at_10
value: 41.327999999999996
- type: map_at_100
value: 42.651
- type: map_at_1000
value: 42.739
- type: map_at_3
value: 38.223
- type: map_at_5
value: 40.053
- type: mrr_at_1
value: 37.9
- type: mrr_at_10
value: 46.857
- type: mrr_at_100
value: 47.673
- type: mrr_at_1000
value: 47.711999999999996
- type: mrr_at_3
value: 44.292
- type: mrr_at_5
value: 45.845
- type: ndcg_at_1
value: 37.9
- type: ndcg_at_10
value: 47.105999999999995
- type: ndcg_at_100
value: 52.56999999999999
- type: ndcg_at_1000
value: 54.37800000000001
- type: ndcg_at_3
value: 42.282
- type: ndcg_at_5
value: 44.646
- type: precision_at_1
value: 37.9
- type: precision_at_10
value: 8.368
- type: precision_at_100
value: 1.283
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 20.015
- type: precision_at_5
value: 14.132
- type: recall_at_1
value: 30.72
- type: recall_at_10
value: 58.826
- type: recall_at_100
value: 82.104
- type: recall_at_1000
value: 94.194
- type: recall_at_3
value: 44.962999999999994
- type: recall_at_5
value: 51.426
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 31.656583333333334
- type: map_at_10
value: 41.59883333333333
- type: map_at_100
value: 42.80350000000001
- type: map_at_1000
value: 42.91075
- type: map_at_3
value: 38.68908333333333
- type: map_at_5
value: 40.27733333333334
- type: mrr_at_1
value: 37.23483333333334
- type: mrr_at_10
value: 45.782000000000004
- type: mrr_at_100
value: 46.577083333333334
- type: mrr_at_1000
value: 46.62516666666667
- type: mrr_at_3
value: 43.480666666666664
- type: mrr_at_5
value: 44.79833333333333
- type: ndcg_at_1
value: 37.23483333333334
- type: ndcg_at_10
value: 46.971500000000006
- type: ndcg_at_100
value: 51.90125
- type: ndcg_at_1000
value: 53.86366666666667
- type: ndcg_at_3
value: 42.31791666666667
- type: ndcg_at_5
value: 44.458666666666666
- type: precision_at_1
value: 37.23483333333334
- type: precision_at_10
value: 8.044583333333332
- type: precision_at_100
value: 1.2334166666666666
- type: precision_at_1000
value: 0.15925
- type: precision_at_3
value: 19.240833333333327
- type: precision_at_5
value: 13.435083333333333
- type: recall_at_1
value: 31.656583333333334
- type: recall_at_10
value: 58.44758333333333
- type: recall_at_100
value: 79.93658333333332
- type: recall_at_1000
value: 93.32491666666668
- type: recall_at_3
value: 45.44266666666667
- type: recall_at_5
value: 50.99866666666666
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-stats
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 28.247
- type: map_at_10
value: 35.443999999999996
- type: map_at_100
value: 36.578
- type: map_at_1000
value: 36.675999999999995
- type: map_at_3
value: 33.276
- type: map_at_5
value: 34.536
- type: mrr_at_1
value: 31.747999999999998
- type: mrr_at_10
value: 38.413000000000004
- type: mrr_at_100
value: 39.327
- type: mrr_at_1000
value: 39.389
- type: mrr_at_3
value: 36.401
- type: mrr_at_5
value: 37.543
- type: ndcg_at_1
value: 31.747999999999998
- type: ndcg_at_10
value: 39.646
- type: ndcg_at_100
value: 44.861000000000004
- type: ndcg_at_1000
value: 47.197
- type: ndcg_at_3
value: 35.764
- type: ndcg_at_5
value: 37.635999999999996
- type: precision_at_1
value: 31.747999999999998
- type: precision_at_10
value: 6.12
- type: precision_at_100
value: 0.942
- type: precision_at_1000
value: 0.123
- type: precision_at_3
value: 15.235000000000001
- type: precision_at_5
value: 10.491
- type: recall_at_1
value: 28.247
- type: recall_at_10
value: 49.456
- type: recall_at_100
value: 73.02499999999999
- type: recall_at_1000
value: 89.898
- type: recall_at_3
value: 38.653999999999996
- type: recall_at_5
value: 43.259
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-tex
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 22.45
- type: map_at_10
value: 30.476999999999997
- type: map_at_100
value: 31.630999999999997
- type: map_at_1000
value: 31.755
- type: map_at_3
value: 27.989000000000004
- type: map_at_5
value: 29.410999999999998
- type: mrr_at_1
value: 26.979
- type: mrr_at_10
value: 34.316
- type: mrr_at_100
value: 35.272999999999996
- type: mrr_at_1000
value: 35.342
- type: mrr_at_3
value: 32.14
- type: mrr_at_5
value: 33.405
- type: ndcg_at_1
value: 26.979
- type: ndcg_at_10
value: 35.166
- type: ndcg_at_100
value: 40.583000000000006
- type: ndcg_at_1000
value: 43.282
- type: ndcg_at_3
value: 30.916
- type: ndcg_at_5
value: 32.973
- type: precision_at_1
value: 26.979
- type: precision_at_10
value: 6.132
- type: precision_at_100
value: 1.047
- type: precision_at_1000
value: 0.145
- type: precision_at_3
value: 14.360999999999999
- type: precision_at_5
value: 10.227
- type: recall_at_1
value: 22.45
- type: recall_at_10
value: 45.348
- type: recall_at_100
value: 69.484
- type: recall_at_1000
value: 88.628
- type: recall_at_3
value: 33.338
- type: recall_at_5
value: 38.746
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-unix
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 32.123000000000005
- type: map_at_10
value: 41.778
- type: map_at_100
value: 42.911
- type: map_at_1000
value: 42.994
- type: map_at_3
value: 38.558
- type: map_at_5
value: 40.318
- type: mrr_at_1
value: 37.687
- type: mrr_at_10
value: 45.889
- type: mrr_at_100
value: 46.672999999999995
- type: mrr_at_1000
value: 46.72
- type: mrr_at_3
value: 43.33
- type: mrr_at_5
value: 44.734
- type: ndcg_at_1
value: 37.687
- type: ndcg_at_10
value: 47.258
- type: ndcg_at_100
value: 52.331
- type: ndcg_at_1000
value: 54.152
- type: ndcg_at_3
value: 41.857
- type: ndcg_at_5
value: 44.283
- type: precision_at_1
value: 37.687
- type: precision_at_10
value: 7.892
- type: precision_at_100
value: 1.183
- type: precision_at_1000
value: 0.14300000000000002
- type: precision_at_3
value: 18.781
- type: precision_at_5
value: 13.134
- type: recall_at_1
value: 32.123000000000005
- type: recall_at_10
value: 59.760000000000005
- type: recall_at_100
value: 81.652
- type: recall_at_1000
value: 94.401
- type: recall_at_3
value: 44.996
- type: recall_at_5
value: 51.184
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-webmasters
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 33.196999999999996
- type: map_at_10
value: 42.012
- type: map_at_100
value: 43.663999999999994
- type: map_at_1000
value: 43.883
- type: map_at_3
value: 39.33
- type: map_at_5
value: 40.586
- type: mrr_at_1
value: 39.328
- type: mrr_at_10
value: 46.57
- type: mrr_at_100
value: 47.508
- type: mrr_at_1000
value: 47.558
- type: mrr_at_3
value: 44.532
- type: mrr_at_5
value: 45.58
- type: ndcg_at_1
value: 39.328
- type: ndcg_at_10
value: 47.337
- type: ndcg_at_100
value: 52.989
- type: ndcg_at_1000
value: 55.224
- type: ndcg_at_3
value: 43.362
- type: ndcg_at_5
value: 44.866
- type: precision_at_1
value: 39.328
- type: precision_at_10
value: 8.577
- type: precision_at_100
value: 1.5789999999999997
- type: precision_at_1000
value: 0.25
- type: precision_at_3
value: 19.697
- type: precision_at_5
value: 13.755
- type: recall_at_1
value: 33.196999999999996
- type: recall_at_10
value: 56.635000000000005
- type: recall_at_100
value: 81.882
- type: recall_at_1000
value: 95.342
- type: recall_at_3
value: 44.969
- type: recall_at_5
value: 49.266
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-wordpress
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 26.901000000000003
- type: map_at_10
value: 35.77
- type: map_at_100
value: 36.638999999999996
- type: map_at_1000
value: 36.741
- type: map_at_3
value: 33.219
- type: map_at_5
value: 34.574
- type: mrr_at_1
value: 29.205
- type: mrr_at_10
value: 37.848
- type: mrr_at_100
value: 38.613
- type: mrr_at_1000
value: 38.682
- type: mrr_at_3
value: 35.551
- type: mrr_at_5
value: 36.808
- type: ndcg_at_1
value: 29.205
- type: ndcg_at_10
value: 40.589
- type: ndcg_at_100
value: 45.171
- type: ndcg_at_1000
value: 47.602
- type: ndcg_at_3
value: 35.760999999999996
- type: ndcg_at_5
value: 37.980000000000004
- type: precision_at_1
value: 29.205
- type: precision_at_10
value: 6.192
- type: precision_at_100
value: 0.922
- type: precision_at_1000
value: 0.123
- type: precision_at_3
value: 15.034
- type: precision_at_5
value: 10.424999999999999
- type: recall_at_1
value: 26.901000000000003
- type: recall_at_10
value: 53.236000000000004
- type: recall_at_100
value: 74.809
- type: recall_at_1000
value: 92.884
- type: recall_at_3
value: 40.314
- type: recall_at_5
value: 45.617999999999995
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 16.794999999999998
- type: map_at_10
value: 29.322
- type: map_at_100
value: 31.463
- type: map_at_1000
value: 31.643
- type: map_at_3
value: 24.517
- type: map_at_5
value: 27.237000000000002
- type: mrr_at_1
value: 37.655
- type: mrr_at_10
value: 50.952
- type: mrr_at_100
value: 51.581999999999994
- type: mrr_at_1000
value: 51.61
- type: mrr_at_3
value: 47.991
- type: mrr_at_5
value: 49.744
- type: ndcg_at_1
value: 37.655
- type: ndcg_at_10
value: 39.328
- type: ndcg_at_100
value: 46.358
- type: ndcg_at_1000
value: 49.245
- type: ndcg_at_3
value: 33.052
- type: ndcg_at_5
value: 35.407
- type: precision_at_1
value: 37.655
- type: precision_at_10
value: 12.202
- type: precision_at_100
value: 1.9789999999999999
- type: precision_at_1000
value: 0.252
- type: precision_at_3
value: 24.973
- type: precision_at_5
value: 19.075
- type: recall_at_1
value: 16.794999999999998
- type: recall_at_10
value: 45.716
- type: recall_at_100
value: 68.919
- type: recall_at_1000
value: 84.71600000000001
- type: recall_at_3
value: 30.135
- type: recall_at_5
value: 37.141999999999996
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 9.817
- type: map_at_10
value: 22.058
- type: map_at_100
value: 31.805
- type: map_at_1000
value: 33.562999999999995
- type: map_at_3
value: 15.537
- type: map_at_5
value: 18.199
- type: mrr_at_1
value: 72.75
- type: mrr_at_10
value: 79.804
- type: mrr_at_100
value: 80.089
- type: mrr_at_1000
value: 80.09100000000001
- type: mrr_at_3
value: 78.75
- type: mrr_at_5
value: 79.325
- type: ndcg_at_1
value: 59.875
- type: ndcg_at_10
value: 45.972
- type: ndcg_at_100
value: 51.092999999999996
- type: ndcg_at_1000
value: 58.048
- type: ndcg_at_3
value: 50.552
- type: ndcg_at_5
value: 47.672
- type: precision_at_1
value: 72.75
- type: precision_at_10
value: 37.05
- type: precision_at_100
value: 12.005
- type: precision_at_1000
value: 2.221
- type: precision_at_3
value: 54.083000000000006
- type: precision_at_5
value: 46.2
- type: recall_at_1
value: 9.817
- type: recall_at_10
value: 27.877000000000002
- type: recall_at_100
value: 57.974000000000004
- type: recall_at_1000
value: 80.085
- type: recall_at_3
value: 16.911
- type: recall_at_5
value: 20.689
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 46.464999999999996
- type: f1
value: 42.759588662873796
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 75.82900000000001
- type: map_at_10
value: 84.613
- type: map_at_100
value: 84.845
- type: map_at_1000
value: 84.855
- type: map_at_3
value: 83.498
- type: map_at_5
value: 84.29299999999999
- type: mrr_at_1
value: 81.69800000000001
- type: mrr_at_10
value: 88.84100000000001
- type: mrr_at_100
value: 88.887
- type: mrr_at_1000
value: 88.888
- type: mrr_at_3
value: 88.179
- type: mrr_at_5
value: 88.69200000000001
- type: ndcg_at_1
value: 81.69800000000001
- type: ndcg_at_10
value: 88.21799999999999
- type: ndcg_at_100
value: 88.961
- type: ndcg_at_1000
value: 89.131
- type: ndcg_at_3
value: 86.591
- type: ndcg_at_5
value: 87.666
- type: precision_at_1
value: 81.69800000000001
- type: precision_at_10
value: 10.615
- type: precision_at_100
value: 1.125
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 33.208
- type: precision_at_5
value: 20.681
- type: recall_at_1
value: 75.82900000000001
- type: recall_at_10
value: 94.97
- type: recall_at_100
value: 97.786
- type: recall_at_1000
value: 98.809
- type: recall_at_3
value: 90.625
- type: recall_at_5
value: 93.345
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 22.788
- type: map_at_10
value: 36.71
- type: map_at_100
value: 38.527
- type: map_at_1000
value: 38.701
- type: map_at_3
value: 32.318999999999996
- type: map_at_5
value: 34.809
- type: mrr_at_1
value: 44.444
- type: mrr_at_10
value: 52.868
- type: mrr_at_100
value: 53.52400000000001
- type: mrr_at_1000
value: 53.559999999999995
- type: mrr_at_3
value: 50.153999999999996
- type: mrr_at_5
value: 51.651
- type: ndcg_at_1
value: 44.444
- type: ndcg_at_10
value: 44.707
- type: ndcg_at_100
value: 51.174
- type: ndcg_at_1000
value: 53.996
- type: ndcg_at_3
value: 40.855999999999995
- type: ndcg_at_5
value: 42.113
- type: precision_at_1
value: 44.444
- type: precision_at_10
value: 12.021999999999998
- type: precision_at_100
value: 1.8950000000000002
- type: precision_at_1000
value: 0.241
- type: precision_at_3
value: 26.8
- type: precision_at_5
value: 19.66
- type: recall_at_1
value: 22.788
- type: recall_at_10
value: 51.793
- type: recall_at_100
value: 75.69500000000001
- type: recall_at_1000
value: 92.292
- type: recall_at_3
value: 37.375
- type: recall_at_5
value: 43.682
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 41.276
- type: map_at_10
value: 67.245
- type: map_at_100
value: 68.061
- type: map_at_1000
value: 68.11399999999999
- type: map_at_3
value: 63.693
- type: map_at_5
value: 65.90899999999999
- type: mrr_at_1
value: 82.552
- type: mrr_at_10
value: 87.741
- type: mrr_at_100
value: 87.868
- type: mrr_at_1000
value: 87.871
- type: mrr_at_3
value: 86.98599999999999
- type: mrr_at_5
value: 87.469
- type: ndcg_at_1
value: 82.552
- type: ndcg_at_10
value: 75.176
- type: ndcg_at_100
value: 77.902
- type: ndcg_at_1000
value: 78.852
- type: ndcg_at_3
value: 70.30499999999999
- type: ndcg_at_5
value: 73.00999999999999
- type: precision_at_1
value: 82.552
- type: precision_at_10
value: 15.765
- type: precision_at_100
value: 1.788
- type: precision_at_1000
value: 0.191
- type: precision_at_3
value: 45.375
- type: precision_at_5
value: 29.360999999999997
- type: recall_at_1
value: 41.276
- type: recall_at_10
value: 78.825
- type: recall_at_100
value: 89.41900000000001
- type: recall_at_1000
value: 95.625
- type: recall_at_3
value: 68.062
- type: recall_at_5
value: 73.40299999999999
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 72.876
- type: ap
value: 67.15477852410164
- type: f1
value: 72.65147370025373
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 21.748
- type: map_at_10
value: 34.626000000000005
- type: map_at_100
value: 35.813
- type: map_at_1000
value: 35.859
- type: map_at_3
value: 30.753000000000004
- type: map_at_5
value: 33.049
- type: mrr_at_1
value: 22.35
- type: mrr_at_10
value: 35.23
- type: mrr_at_100
value: 36.359
- type: mrr_at_1000
value: 36.399
- type: mrr_at_3
value: 31.436999999999998
- type: mrr_at_5
value: 33.687
- type: ndcg_at_1
value: 22.364
- type: ndcg_at_10
value: 41.677
- type: ndcg_at_100
value: 47.355999999999995
- type: ndcg_at_1000
value: 48.494
- type: ndcg_at_3
value: 33.85
- type: ndcg_at_5
value: 37.942
- type: precision_at_1
value: 22.364
- type: precision_at_10
value: 6.6000000000000005
- type: precision_at_100
value: 0.9450000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.527000000000001
- type: precision_at_5
value: 10.796999999999999
- type: recall_at_1
value: 21.748
- type: recall_at_10
value: 63.292
- type: recall_at_100
value: 89.427
- type: recall_at_1000
value: 98.13499999999999
- type: recall_at_3
value: 42.126000000000005
- type: recall_at_5
value: 51.968
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 92.62425900592795
- type: f1
value: 92.08497761553683
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 64.51436388508893
- type: f1
value: 45.884016531912906
- task:
type: Classification
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClassification (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: accuracy
value: 76.57172995780591
- type: f1
value: 75.52979910878491
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringP2P (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 44.84052695201612
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringS2S (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 21.443971229936494
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 65.79354404841965
- type: f1
value: 63.17260074126185
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 71.09616677874916
- type: f1
value: 69.74285784421075
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.474709231086184
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 28.93630367824217
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.08234393834005
- type: mrr
value: 29.740466971605432
- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 6.2059999999999995
- type: map_at_10
value: 14.442
- type: map_at_100
value: 18.005
- type: map_at_1000
value: 19.488
- type: map_at_3
value: 10.666
- type: map_at_5
value: 12.45
- type: mrr_at_1
value: 47.678
- type: mrr_at_10
value: 57.519
- type: mrr_at_100
value: 58.13700000000001
- type: mrr_at_1000
value: 58.167
- type: mrr_at_3
value: 55.779
- type: mrr_at_5
value: 56.940000000000005
- type: ndcg_at_1
value: 45.82
- type: ndcg_at_10
value: 37.651
- type: ndcg_at_100
value: 34.001999999999995
- type: ndcg_at_1000
value: 42.626
- type: ndcg_at_3
value: 43.961
- type: ndcg_at_5
value: 41.461
- type: precision_at_1
value: 47.678
- type: precision_at_10
value: 27.584999999999997
- type: precision_at_100
value: 8.455
- type: precision_at_1000
value: 2.118
- type: precision_at_3
value: 41.692
- type: precision_at_5
value: 36.161
- type: recall_at_1
value: 6.2059999999999995
- type: recall_at_10
value: 18.599
- type: recall_at_100
value: 33.608
- type: recall_at_1000
value: 65.429
- type: recall_at_3
value: 12.126000000000001
- type: recall_at_5
value: 14.902000000000001
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 39.117000000000004
- type: map_at_10
value: 55.535000000000004
- type: map_at_100
value: 56.32899999999999
- type: map_at_1000
value: 56.34400000000001
- type: map_at_3
value: 51.439
- type: map_at_5
value: 53.89699999999999
- type: mrr_at_1
value: 43.714
- type: mrr_at_10
value: 58.05200000000001
- type: mrr_at_100
value: 58.582
- type: mrr_at_1000
value: 58.592
- type: mrr_at_3
value: 54.896
- type: mrr_at_5
value: 56.874
- type: ndcg_at_1
value: 43.685
- type: ndcg_at_10
value: 63.108
- type: ndcg_at_100
value: 66.231
- type: ndcg_at_1000
value: 66.583
- type: ndcg_at_3
value: 55.659000000000006
- type: ndcg_at_5
value: 59.681
- type: precision_at_1
value: 43.685
- type: precision_at_10
value: 9.962
- type: precision_at_100
value: 1.174
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 24.961
- type: precision_at_5
value: 17.352
- type: recall_at_1
value: 39.117000000000004
- type: recall_at_10
value: 83.408
- type: recall_at_100
value: 96.553
- type: recall_at_1000
value: 99.136
- type: recall_at_3
value: 64.364
- type: recall_at_5
value: 73.573
- task:
type: Classification
dataset:
type: ag_news
name: MTEB NewsClassification
config: default
split: test
revision: eb185aade064a813bc0b7f42de02595523103ca4
metrics:
- type: accuracy
value: 78.87763157894737
- type: f1
value: 78.69611753876177
- 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: 62
- type: cos_sim_ap
value: 62.26837791655737
- type: cos_sim_f1
value: 62.607449856733524
- type: cos_sim_precision
value: 46.36604774535809
- type: cos_sim_recall
value: 96.36163175303197
- type: dot_accuracy
value: 62
- type: dot_ap
value: 62.26736459439965
- type: dot_f1
value: 62.607449856733524
- type: dot_precision
value: 46.36604774535809
- type: dot_recall
value: 96.36163175303197
- type: euclidean_accuracy
value: 62
- type: euclidean_ap
value: 62.26826112548132
- type: euclidean_f1
value: 62.607449856733524
- type: euclidean_precision
value: 46.36604774535809
- type: euclidean_recall
value: 96.36163175303197
- type: manhattan_accuracy
value: 62
- type: manhattan_ap
value: 62.26223761507973
- type: manhattan_f1
value: 62.585034013605444
- type: manhattan_precision
value: 46.34146341463415
- type: manhattan_recall
value: 96.36163175303197
- type: max_accuracy
value: 62
- type: max_ap
value: 62.26837791655737
- type: max_f1
value: 62.607449856733524
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 69.90899999999999
- type: map_at_10
value: 83.56700000000001
- type: map_at_100
value: 84.19200000000001
- type: map_at_1000
value: 84.212
- type: map_at_3
value: 80.658
- type: map_at_5
value: 82.473
- type: mrr_at_1
value: 80.4
- type: mrr_at_10
value: 86.699
- type: mrr_at_100
value: 86.798
- type: mrr_at_1000
value: 86.80099999999999
- type: mrr_at_3
value: 85.677
- type: mrr_at_5
value: 86.354
- type: ndcg_at_1
value: 80.43
- type: ndcg_at_10
value: 87.41
- type: ndcg_at_100
value: 88.653
- type: ndcg_at_1000
value: 88.81599999999999
- type: ndcg_at_3
value: 84.516
- type: ndcg_at_5
value: 86.068
- type: precision_at_1
value: 80.43
- type: precision_at_10
value: 13.234000000000002
- type: precision_at_100
value: 1.513
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.93
- type: precision_at_5
value: 24.26
- type: recall_at_1
value: 69.90899999999999
- type: recall_at_10
value: 94.687
- type: recall_at_100
value: 98.96000000000001
- type: recall_at_1000
value: 99.79599999999999
- type: recall_at_3
value: 86.25699999999999
- type: recall_at_5
value: 90.70700000000001
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 46.02256865360266
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 62.43157528757563
- task:
type: Retrieval
dataset:
type: mteb/scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
metrics:
- type: map_at_1
value: 5.093
- type: map_at_10
value: 12.982
- type: map_at_100
value: 15.031
- type: map_at_1000
value: 15.334
- type: map_at_3
value: 9.339
- type: map_at_5
value: 11.183
- type: mrr_at_1
value: 25.1
- type: mrr_at_10
value: 36.257
- type: mrr_at_100
value: 37.351
- type: mrr_at_1000
value: 37.409
- type: mrr_at_3
value: 33.050000000000004
- type: mrr_at_5
value: 35.205
- type: ndcg_at_1
value: 25.1
- type: ndcg_at_10
value: 21.361
- type: ndcg_at_100
value: 29.396
- type: ndcg_at_1000
value: 34.849999999999994
- type: ndcg_at_3
value: 20.704
- type: ndcg_at_5
value: 18.086
- type: precision_at_1
value: 25.1
- type: precision_at_10
value: 10.94
- type: precision_at_100
value: 2.257
- type: precision_at_1000
value: 0.358
- type: precision_at_3
value: 19.467000000000002
- type: precision_at_5
value: 15.98
- type: recall_at_1
value: 5.093
- type: recall_at_10
value: 22.177
- type: recall_at_100
value: 45.842
- type: recall_at_1000
value: 72.598
- type: recall_at_3
value: 11.833
- type: recall_at_5
value: 16.173000000000002
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 73.56535226754596
- type: cos_sim_spearman
value: 69.32425977603488
- type: euclidean_pearson
value: 71.32425703470898
- type: euclidean_spearman
value: 69.32425217267013
- type: manhattan_pearson
value: 71.25897281394246
- type: manhattan_spearman
value: 69.27132577049578
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 69.66387868726018
- type: cos_sim_spearman
value: 67.85470749045027
- type: euclidean_pearson
value: 66.62075098063795
- type: euclidean_spearman
value: 67.85470749045027
- type: manhattan_pearson
value: 66.61455061901262
- type: manhattan_spearman
value: 67.87229618498695
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 75.65731331392575
- type: cos_sim_spearman
value: 77.48991626780108
- type: euclidean_pearson
value: 77.19884738623692
- type: euclidean_spearman
value: 77.48985836619045
- type: manhattan_pearson
value: 77.0656684243772
- type: manhattan_spearman
value: 77.30289226582691
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 69.37003253666457
- type: cos_sim_spearman
value: 69.77157648098141
- type: euclidean_pearson
value: 69.39543876030432
- type: euclidean_spearman
value: 69.77157648098141
- type: manhattan_pearson
value: 69.29901600459745
- type: manhattan_spearman
value: 69.65074167527128
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 78.56777256540136
- type: cos_sim_spearman
value: 80.16458787843023
- type: euclidean_pearson
value: 80.16475730686916
- type: euclidean_spearman
value: 80.16458787843023
- type: manhattan_pearson
value: 80.12814463670401
- type: manhattan_spearman
value: 80.1357907984809
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 76.09572350919031
- type: cos_sim_spearman
value: 77.94490233429326
- type: euclidean_pearson
value: 78.36595251203524
- type: euclidean_spearman
value: 77.94490233429326
- type: manhattan_pearson
value: 78.41538768125166
- type: manhattan_spearman
value: 78.01244379569542
- 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: 80.7843552187951
- type: cos_sim_spearman
value: 82.28085055047386
- type: euclidean_pearson
value: 82.37373672515267
- type: euclidean_spearman
value: 82.28085055047386
- type: manhattan_pearson
value: 82.39387241346917
- type: manhattan_spearman
value: 82.36503339515906
- 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: 68.29963929962095
- type: cos_sim_spearman
value: 67.96868942546051
- type: euclidean_pearson
value: 68.93524903869285
- type: euclidean_spearman
value: 67.96868942546051
- type: manhattan_pearson
value: 68.79144468444811
- type: manhattan_spearman
value: 67.69311483884324
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 72.84789696700685
- type: cos_sim_spearman
value: 75.67875747588545
- type: euclidean_pearson
value: 75.07752300463038
- type: euclidean_spearman
value: 75.67875747588545
- type: manhattan_pearson
value: 74.97934248140928
- type: manhattan_spearman
value: 75.62525644178724
- 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: 72.84789702519309
- type: cos_sim_spearman
value: 75.67875747588545
- type: euclidean_pearson
value: 75.07752310061133
- type: euclidean_spearman
value: 75.67875747588545
- type: manhattan_pearson
value: 74.97934257159595
- type: manhattan_spearman
value: 75.62525644178724
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 81.55557720431086
- type: mrr
value: 94.91178665198272
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 59.260999999999996
- type: map_at_10
value: 69.36099999999999
- type: map_at_100
value: 69.868
- type: map_at_1000
value: 69.877
- type: map_at_3
value: 66.617
- type: map_at_5
value: 68.061
- type: mrr_at_1
value: 62.333000000000006
- type: mrr_at_10
value: 70.533
- type: mrr_at_100
value: 70.966
- type: mrr_at_1000
value: 70.975
- type: mrr_at_3
value: 68.667
- type: mrr_at_5
value: 69.717
- type: ndcg_at_1
value: 62.333000000000006
- type: ndcg_at_10
value: 73.82300000000001
- type: ndcg_at_100
value: 76.122
- type: ndcg_at_1000
value: 76.374
- type: ndcg_at_3
value: 69.27499999999999
- type: ndcg_at_5
value: 71.33
- type: precision_at_1
value: 62.333000000000006
- type: precision_at_10
value: 9.8
- type: precision_at_100
value: 1.097
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 26.889000000000003
- type: precision_at_5
value: 17.599999999999998
- type: recall_at_1
value: 59.260999999999996
- type: recall_at_10
value: 86.2
- type: recall_at_100
value: 96.667
- type: recall_at_1000
value: 98.667
- type: recall_at_3
value: 74.006
- type: recall_at_5
value: 79.167
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81881188118813
- type: cos_sim_ap
value: 95.20169041096409
- type: cos_sim_f1
value: 90.76224129227664
- type: cos_sim_precision
value: 91.64118246687055
- type: cos_sim_recall
value: 89.9
- type: dot_accuracy
value: 99.81881188118813
- type: dot_ap
value: 95.20169041096409
- type: dot_f1
value: 90.76224129227664
- type: dot_precision
value: 91.64118246687055
- type: dot_recall
value: 89.9
- type: euclidean_accuracy
value: 99.81881188118813
- type: euclidean_ap
value: 95.2016904109641
- type: euclidean_f1
value: 90.76224129227664
- type: euclidean_precision
value: 91.64118246687055
- type: euclidean_recall
value: 89.9
- type: manhattan_accuracy
value: 99.81881188118813
- type: manhattan_ap
value: 95.22680188132777
- type: manhattan_f1
value: 90.79013588324108
- type: manhattan_precision
value: 91.38804457953394
- type: manhattan_recall
value: 90.2
- type: max_accuracy
value: 99.81881188118813
- type: max_ap
value: 95.22680188132777
- type: max_f1
value: 90.79013588324108
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 57.8638628701308
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 37.82028248106046
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 50.870860210170946
- type: mrr
value: 51.608084521687466
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.60384207444685
- type: cos_sim_spearman
value: 30.84047452209471
- type: dot_pearson
value: 31.60384104417333
- type: dot_spearman
value: 30.84047452209471
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.246
- type: map_at_10
value: 2.051
- type: map_at_100
value: 13.129
- type: map_at_1000
value: 31.56
- type: map_at_3
value: 0.681
- type: map_at_5
value: 1.105
- type: mrr_at_1
value: 94
- type: mrr_at_10
value: 97
- type: mrr_at_100
value: 97
- type: mrr_at_1000
value: 97
- type: mrr_at_3
value: 97
- type: mrr_at_5
value: 97
- type: ndcg_at_1
value: 87
- type: ndcg_at_10
value: 80.716
- type: ndcg_at_100
value: 63.83
- type: ndcg_at_1000
value: 56.215
- type: ndcg_at_3
value: 84.531
- type: ndcg_at_5
value: 84.777
- type: precision_at_1
value: 94
- type: precision_at_10
value: 84.6
- type: precision_at_100
value: 66.03999999999999
- type: precision_at_1000
value: 24.878
- type: precision_at_3
value: 88.667
- type: precision_at_5
value: 89.60000000000001
- type: recall_at_1
value: 0.246
- type: recall_at_10
value: 2.2079999999999997
- type: recall_at_100
value: 15.895999999999999
- type: recall_at_1000
value: 52.683
- type: recall_at_3
value: 0.7040000000000001
- type: recall_at_5
value: 1.163
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 3.852
- type: map_at_10
value: 14.316
- type: map_at_100
value: 20.982
- type: map_at_1000
value: 22.58
- type: map_at_3
value: 7.767
- type: map_at_5
value: 10.321
- type: mrr_at_1
value: 51.019999999999996
- type: mrr_at_10
value: 66.365
- type: mrr_at_100
value: 66.522
- type: mrr_at_1000
value: 66.522
- type: mrr_at_3
value: 62.925
- type: mrr_at_5
value: 64.762
- type: ndcg_at_1
value: 46.939
- type: ndcg_at_10
value: 34.516999999999996
- type: ndcg_at_100
value: 44.25
- type: ndcg_at_1000
value: 54.899
- type: ndcg_at_3
value: 40.203
- type: ndcg_at_5
value: 37.004
- type: precision_at_1
value: 51.019999999999996
- type: precision_at_10
value: 29.796
- type: precision_at_100
value: 8.633000000000001
- type: precision_at_1000
value: 1.584
- type: precision_at_3
value: 40.816
- type: precision_at_5
value: 35.918
- type: recall_at_1
value: 3.852
- type: recall_at_10
value: 20.891000000000002
- type: recall_at_100
value: 52.428
- type: recall_at_1000
value: 84.34899999999999
- type: recall_at_3
value: 8.834
- type: recall_at_5
value: 12.909
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 64.7092
- type: ap
value: 11.972915012305819
- type: f1
value: 49.91050149892115
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 56.737408036219584
- type: f1
value: 57.07235266246011
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 35.9147539025798
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 82.52369315133814
- type: cos_sim_ap
value: 62.34858091376534
- type: cos_sim_f1
value: 58.18225190839694
- type: cos_sim_precision
value: 53.09098824553766
- type: cos_sim_recall
value: 64.35356200527704
- type: dot_accuracy
value: 82.52369315133814
- type: dot_ap
value: 62.34857753814992
- type: dot_f1
value: 58.18225190839694
- type: dot_precision
value: 53.09098824553766
- type: dot_recall
value: 64.35356200527704
- type: euclidean_accuracy
value: 82.52369315133814
- type: euclidean_ap
value: 62.34857756663386
- type: euclidean_f1
value: 58.18225190839694
- type: euclidean_precision
value: 53.09098824553766
- type: euclidean_recall
value: 64.35356200527704
- type: manhattan_accuracy
value: 82.49389044525243
- type: manhattan_ap
value: 62.32245347238179
- type: manhattan_f1
value: 58.206309819213054
- type: manhattan_precision
value: 52.70704044511021
- type: manhattan_recall
value: 64.9868073878628
- type: max_accuracy
value: 82.52369315133814
- type: max_ap
value: 62.34858091376534
- type: max_f1
value: 58.206309819213054
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.34555827220863
- type: cos_sim_ap
value: 84.84152481680071
- type: cos_sim_f1
value: 76.860456739428
- type: cos_sim_precision
value: 72.21470150263978
- type: cos_sim_recall
value: 82.14505697566985
- type: dot_accuracy
value: 88.34555827220863
- type: dot_ap
value: 84.84152743322608
- type: dot_f1
value: 76.860456739428
- type: dot_precision
value: 72.21470150263978
- type: dot_recall
value: 82.14505697566985
- type: euclidean_accuracy
value: 88.34555827220863
- type: euclidean_ap
value: 84.84152589453169
- type: euclidean_f1
value: 76.860456739428
- type: euclidean_precision
value: 72.21470150263978
- type: euclidean_recall
value: 82.14505697566985
- type: manhattan_accuracy
value: 88.38242713548337
- type: manhattan_ap
value: 84.8112124970968
- type: manhattan_f1
value: 76.83599206057487
- type: manhattan_precision
value: 73.51244900829934
- type: manhattan_recall
value: 80.47428395441946
- type: max_accuracy
value: 88.38242713548337
- type: max_ap
value: 84.84152743322608
- type: max_f1
value: 76.860456739428
- task:
type: Clustering
dataset:
type: jinaai/cities_wiki_clustering
name: MTEB WikiCitiesClustering
config: default
split: test
revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
metrics:
- type: v_measure
value: 85.5314389263015