metadata
tags:
- mteb
- arctic
- arctic-embed
model-index:
- name: base
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 76.80597014925374
- type: ap
value: 39.31198155789558
- type: f1
value: 70.48198448222148
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 82.831525
- type: ap
value: 77.4474050181638
- type: f1
value: 82.77204845110204
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 38.93000000000001
- type: f1
value: 37.98013371053459
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 31.223
- type: map_at_10
value: 47.43
- type: map_at_100
value: 48.208
- type: map_at_1000
value: 48.211
- type: map_at_3
value: 42.579
- type: map_at_5
value: 45.263999999999996
- type: mrr_at_1
value: 31.65
- type: mrr_at_10
value: 47.573
- type: mrr_at_100
value: 48.359
- type: mrr_at_1000
value: 48.362
- type: mrr_at_3
value: 42.734
- type: mrr_at_5
value: 45.415
- type: ndcg_at_1
value: 31.223
- type: ndcg_at_10
value: 56.436
- type: ndcg_at_100
value: 59.657000000000004
- type: ndcg_at_1000
value: 59.731
- type: ndcg_at_3
value: 46.327
- type: ndcg_at_5
value: 51.178000000000004
- type: precision_at_1
value: 31.223
- type: precision_at_10
value: 8.527999999999999
- type: precision_at_100
value: 0.991
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 19.061
- type: precision_at_5
value: 13.797999999999998
- type: recall_at_1
value: 31.223
- type: recall_at_10
value: 85.277
- type: recall_at_100
value: 99.075
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 57.18299999999999
- type: recall_at_5
value: 68.99
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 47.23625429411296
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 37.433880471403654
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 60.53175025582013
- type: mrr
value: 74.51160796728664
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 88.93746103286769
- type: cos_sim_spearman
value: 86.62245567912619
- type: euclidean_pearson
value: 87.154173907501
- type: euclidean_spearman
value: 86.62245567912619
- type: manhattan_pearson
value: 87.17682026633462
- type: manhattan_spearman
value: 86.74775973908348
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 80.33766233766232
- type: f1
value: 79.64931422442245
- task:
type: Clustering
dataset:
type: jinaai/big-patent-clustering
name: MTEB BigPatentClustering
config: default
split: test
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
metrics:
- type: v_measure
value: 19.116028913890613
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 36.966921852810174
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 31.98019698537654
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-android
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 34.079
- type: map_at_10
value: 46.35
- type: map_at_100
value: 47.785
- type: map_at_1000
value: 47.903
- type: map_at_3
value: 42.620999999999995
- type: map_at_5
value: 44.765
- type: mrr_at_1
value: 41.345
- type: mrr_at_10
value: 52.032000000000004
- type: mrr_at_100
value: 52.690000000000005
- type: mrr_at_1000
value: 52.727999999999994
- type: mrr_at_3
value: 49.428
- type: mrr_at_5
value: 51.093999999999994
- type: ndcg_at_1
value: 41.345
- type: ndcg_at_10
value: 53.027
- type: ndcg_at_100
value: 57.962
- type: ndcg_at_1000
value: 59.611999999999995
- type: ndcg_at_3
value: 47.687000000000005
- type: ndcg_at_5
value: 50.367
- type: precision_at_1
value: 41.345
- type: precision_at_10
value: 10.157
- type: precision_at_100
value: 1.567
- type: precision_at_1000
value: 0.199
- type: precision_at_3
value: 23.081
- type: precision_at_5
value: 16.738
- type: recall_at_1
value: 34.079
- type: recall_at_10
value: 65.93900000000001
- type: recall_at_100
value: 86.42699999999999
- type: recall_at_1000
value: 96.61
- type: recall_at_3
value: 50.56699999999999
- type: recall_at_5
value: 57.82000000000001
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-english
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 33.289
- type: map_at_10
value: 43.681
- type: map_at_100
value: 45.056000000000004
- type: map_at_1000
value: 45.171
- type: map_at_3
value: 40.702
- type: map_at_5
value: 42.292
- type: mrr_at_1
value: 41.146
- type: mrr_at_10
value: 49.604
- type: mrr_at_100
value: 50.28399999999999
- type: mrr_at_1000
value: 50.322
- type: mrr_at_3
value: 47.611
- type: mrr_at_5
value: 48.717
- type: ndcg_at_1
value: 41.146
- type: ndcg_at_10
value: 49.43
- type: ndcg_at_100
value: 54.01899999999999
- type: ndcg_at_1000
value: 55.803000000000004
- type: ndcg_at_3
value: 45.503
- type: ndcg_at_5
value: 47.198
- type: precision_at_1
value: 41.146
- type: precision_at_10
value: 9.268
- type: precision_at_100
value: 1.4749999999999999
- type: precision_at_1000
value: 0.19
- type: precision_at_3
value: 21.932
- type: precision_at_5
value: 15.389
- type: recall_at_1
value: 33.289
- type: recall_at_10
value: 59.209999999999994
- type: recall_at_100
value: 78.676
- type: recall_at_1000
value: 89.84100000000001
- type: recall_at_3
value: 47.351
- type: recall_at_5
value: 52.178999999999995
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gaming
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 44.483
- type: map_at_10
value: 56.862
- type: map_at_100
value: 57.901
- type: map_at_1000
value: 57.948
- type: map_at_3
value: 53.737
- type: map_at_5
value: 55.64
- type: mrr_at_1
value: 50.658
- type: mrr_at_10
value: 60.281
- type: mrr_at_100
value: 60.946
- type: mrr_at_1000
value: 60.967000000000006
- type: mrr_at_3
value: 58.192
- type: mrr_at_5
value: 59.531
- type: ndcg_at_1
value: 50.658
- type: ndcg_at_10
value: 62.339
- type: ndcg_at_100
value: 66.28399999999999
- type: ndcg_at_1000
value: 67.166
- type: ndcg_at_3
value: 57.458
- type: ndcg_at_5
value: 60.112
- type: precision_at_1
value: 50.658
- type: precision_at_10
value: 9.762
- type: precision_at_100
value: 1.26
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 25.329
- type: precision_at_5
value: 17.254
- type: recall_at_1
value: 44.483
- type: recall_at_10
value: 74.819
- type: recall_at_100
value: 91.702
- type: recall_at_1000
value: 97.84
- type: recall_at_3
value: 62.13999999999999
- type: recall_at_5
value: 68.569
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gis
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 26.489
- type: map_at_10
value: 37.004999999999995
- type: map_at_100
value: 38.001000000000005
- type: map_at_1000
value: 38.085
- type: map_at_3
value: 34.239999999999995
- type: map_at_5
value: 35.934
- type: mrr_at_1
value: 28.362
- type: mrr_at_10
value: 38.807
- type: mrr_at_100
value: 39.671
- type: mrr_at_1000
value: 39.736
- type: mrr_at_3
value: 36.29
- type: mrr_at_5
value: 37.906
- type: ndcg_at_1
value: 28.362
- type: ndcg_at_10
value: 42.510999999999996
- type: ndcg_at_100
value: 47.226
- type: ndcg_at_1000
value: 49.226
- type: ndcg_at_3
value: 37.295
- type: ndcg_at_5
value: 40.165
- type: precision_at_1
value: 28.362
- type: precision_at_10
value: 6.633
- type: precision_at_100
value: 0.9490000000000001
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 16.234
- type: precision_at_5
value: 11.434999999999999
- type: recall_at_1
value: 26.489
- type: recall_at_10
value: 57.457
- type: recall_at_100
value: 78.712
- type: recall_at_1000
value: 93.565
- type: recall_at_3
value: 43.748
- type: recall_at_5
value: 50.589
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-mathematica
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 12.418999999999999
- type: map_at_10
value: 22.866
- type: map_at_100
value: 24.365000000000002
- type: map_at_1000
value: 24.479
- type: map_at_3
value: 19.965
- type: map_at_5
value: 21.684
- type: mrr_at_1
value: 14.677000000000001
- type: mrr_at_10
value: 26.316
- type: mrr_at_100
value: 27.514
- type: mrr_at_1000
value: 27.57
- type: mrr_at_3
value: 23.3
- type: mrr_at_5
value: 25.191000000000003
- type: ndcg_at_1
value: 14.677000000000001
- type: ndcg_at_10
value: 28.875
- type: ndcg_at_100
value: 35.607
- type: ndcg_at_1000
value: 38.237
- type: ndcg_at_3
value: 23.284
- type: ndcg_at_5
value: 26.226
- type: precision_at_1
value: 14.677000000000001
- type: precision_at_10
value: 5.771
- type: precision_at_100
value: 1.058
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_3
value: 11.940000000000001
- type: precision_at_5
value: 9.229
- type: recall_at_1
value: 12.418999999999999
- type: recall_at_10
value: 43.333
- type: recall_at_100
value: 71.942
- type: recall_at_1000
value: 90.67399999999999
- type: recall_at_3
value: 28.787000000000003
- type: recall_at_5
value: 35.638
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-physics
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 31.686999999999998
- type: map_at_10
value: 42.331
- type: map_at_100
value: 43.655
- type: map_at_1000
value: 43.771
- type: map_at_3
value: 38.944
- type: map_at_5
value: 40.991
- type: mrr_at_1
value: 37.921
- type: mrr_at_10
value: 47.534
- type: mrr_at_100
value: 48.362
- type: mrr_at_1000
value: 48.405
- type: mrr_at_3
value: 44.995000000000005
- type: mrr_at_5
value: 46.617
- type: ndcg_at_1
value: 37.921
- type: ndcg_at_10
value: 48.236000000000004
- type: ndcg_at_100
value: 53.705000000000005
- type: ndcg_at_1000
value: 55.596000000000004
- type: ndcg_at_3
value: 43.11
- type: ndcg_at_5
value: 45.862
- type: precision_at_1
value: 37.921
- type: precision_at_10
value: 8.643
- type: precision_at_100
value: 1.336
- type: precision_at_1000
value: 0.166
- type: precision_at_3
value: 20.308
- type: precision_at_5
value: 14.514
- type: recall_at_1
value: 31.686999999999998
- type: recall_at_10
value: 60.126999999999995
- type: recall_at_100
value: 83.10600000000001
- type: recall_at_1000
value: 95.15
- type: recall_at_3
value: 46.098
- type: recall_at_5
value: 53.179
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-programmers
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 28.686
- type: map_at_10
value: 39.146
- type: map_at_100
value: 40.543
- type: map_at_1000
value: 40.644999999999996
- type: map_at_3
value: 36.195
- type: map_at_5
value: 37.919000000000004
- type: mrr_at_1
value: 35.160000000000004
- type: mrr_at_10
value: 44.711
- type: mrr_at_100
value: 45.609
- type: mrr_at_1000
value: 45.655
- type: mrr_at_3
value: 42.409
- type: mrr_at_5
value: 43.779
- type: ndcg_at_1
value: 35.160000000000004
- type: ndcg_at_10
value: 44.977000000000004
- type: ndcg_at_100
value: 50.663000000000004
- type: ndcg_at_1000
value: 52.794
- type: ndcg_at_3
value: 40.532000000000004
- type: ndcg_at_5
value: 42.641
- type: precision_at_1
value: 35.160000000000004
- type: precision_at_10
value: 8.014000000000001
- type: precision_at_100
value: 1.269
- type: precision_at_1000
value: 0.163
- type: precision_at_3
value: 19.444
- type: precision_at_5
value: 13.653
- type: recall_at_1
value: 28.686
- type: recall_at_10
value: 56.801
- type: recall_at_100
value: 80.559
- type: recall_at_1000
value: 95.052
- type: recall_at_3
value: 43.675999999999995
- type: recall_at_5
value: 49.703
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 28.173833333333338
- type: map_at_10
value: 38.202083333333334
- type: map_at_100
value: 39.47475
- type: map_at_1000
value: 39.586499999999994
- type: map_at_3
value: 35.17308333333334
- type: map_at_5
value: 36.914
- type: mrr_at_1
value: 32.92958333333333
- type: mrr_at_10
value: 42.16758333333333
- type: mrr_at_100
value: 43.04108333333333
- type: mrr_at_1000
value: 43.092499999999994
- type: mrr_at_3
value: 39.69166666666666
- type: mrr_at_5
value: 41.19458333333333
- type: ndcg_at_1
value: 32.92958333333333
- type: ndcg_at_10
value: 43.80583333333333
- type: ndcg_at_100
value: 49.060916666666664
- type: ndcg_at_1000
value: 51.127250000000004
- type: ndcg_at_3
value: 38.80383333333333
- type: ndcg_at_5
value: 41.29658333333333
- type: precision_at_1
value: 32.92958333333333
- type: precision_at_10
value: 7.655666666666666
- type: precision_at_100
value: 1.2094166666666668
- type: precision_at_1000
value: 0.15750000000000003
- type: precision_at_3
value: 17.87975
- type: precision_at_5
value: 12.741833333333332
- type: recall_at_1
value: 28.173833333333338
- type: recall_at_10
value: 56.219249999999995
- type: recall_at_100
value: 79.01416666666665
- type: recall_at_1000
value: 93.13425000000001
- type: recall_at_3
value: 42.39241666666667
- type: recall_at_5
value: 48.764833333333335
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-stats
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 25.625999999999998
- type: map_at_10
value: 32.808
- type: map_at_100
value: 33.951
- type: map_at_1000
value: 34.052
- type: map_at_3
value: 30.536
- type: map_at_5
value: 31.77
- type: mrr_at_1
value: 28.374
- type: mrr_at_10
value: 35.527
- type: mrr_at_100
value: 36.451
- type: mrr_at_1000
value: 36.522
- type: mrr_at_3
value: 33.410000000000004
- type: mrr_at_5
value: 34.537
- type: ndcg_at_1
value: 28.374
- type: ndcg_at_10
value: 37.172
- type: ndcg_at_100
value: 42.474000000000004
- type: ndcg_at_1000
value: 44.853
- type: ndcg_at_3
value: 32.931
- type: ndcg_at_5
value: 34.882999999999996
- type: precision_at_1
value: 28.374
- type: precision_at_10
value: 5.813
- type: precision_at_100
value: 0.928
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 14.008000000000001
- type: precision_at_5
value: 9.754999999999999
- type: recall_at_1
value: 25.625999999999998
- type: recall_at_10
value: 47.812
- type: recall_at_100
value: 71.61800000000001
- type: recall_at_1000
value: 88.881
- type: recall_at_3
value: 35.876999999999995
- type: recall_at_5
value: 40.839
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-tex
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 18.233
- type: map_at_10
value: 26.375999999999998
- type: map_at_100
value: 27.575
- type: map_at_1000
value: 27.706999999999997
- type: map_at_3
value: 23.619
- type: map_at_5
value: 25.217
- type: mrr_at_1
value: 22.023
- type: mrr_at_10
value: 30.122
- type: mrr_at_100
value: 31.083
- type: mrr_at_1000
value: 31.163999999999998
- type: mrr_at_3
value: 27.541
- type: mrr_at_5
value: 29.061999999999998
- type: ndcg_at_1
value: 22.023
- type: ndcg_at_10
value: 31.476
- type: ndcg_at_100
value: 37.114000000000004
- type: ndcg_at_1000
value: 39.981
- type: ndcg_at_3
value: 26.538
- type: ndcg_at_5
value: 29.016
- type: precision_at_1
value: 22.023
- type: precision_at_10
value: 5.819
- type: precision_at_100
value: 1.018
- type: precision_at_1000
value: 0.14300000000000002
- type: precision_at_3
value: 12.583
- type: precision_at_5
value: 9.36
- type: recall_at_1
value: 18.233
- type: recall_at_10
value: 43.029
- type: recall_at_100
value: 68.253
- type: recall_at_1000
value: 88.319
- type: recall_at_3
value: 29.541
- type: recall_at_5
value: 35.783
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-unix
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 28.923
- type: map_at_10
value: 39.231
- type: map_at_100
value: 40.483000000000004
- type: map_at_1000
value: 40.575
- type: map_at_3
value: 35.94
- type: map_at_5
value: 37.683
- type: mrr_at_1
value: 33.955
- type: mrr_at_10
value: 43.163000000000004
- type: mrr_at_100
value: 44.054
- type: mrr_at_1000
value: 44.099
- type: mrr_at_3
value: 40.361000000000004
- type: mrr_at_5
value: 41.905
- type: ndcg_at_1
value: 33.955
- type: ndcg_at_10
value: 45.068000000000005
- type: ndcg_at_100
value: 50.470000000000006
- type: ndcg_at_1000
value: 52.349000000000004
- type: ndcg_at_3
value: 39.298
- type: ndcg_at_5
value: 41.821999999999996
- type: precision_at_1
value: 33.955
- type: precision_at_10
value: 7.649
- type: precision_at_100
value: 1.173
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_3
value: 17.817
- type: precision_at_5
value: 12.537
- type: recall_at_1
value: 28.923
- type: recall_at_10
value: 58.934
- type: recall_at_100
value: 81.809
- type: recall_at_1000
value: 94.71300000000001
- type: recall_at_3
value: 42.975
- type: recall_at_5
value: 49.501
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-webmasters
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 28.596
- type: map_at_10
value: 38.735
- type: map_at_100
value: 40.264
- type: map_at_1000
value: 40.48
- type: map_at_3
value: 35.394999999999996
- type: map_at_5
value: 37.099
- type: mrr_at_1
value: 33.992
- type: mrr_at_10
value: 43.076
- type: mrr_at_100
value: 44.005
- type: mrr_at_1000
value: 44.043
- type: mrr_at_3
value: 40.415
- type: mrr_at_5
value: 41.957
- type: ndcg_at_1
value: 33.992
- type: ndcg_at_10
value: 44.896
- type: ndcg_at_100
value: 50.44499999999999
- type: ndcg_at_1000
value: 52.675000000000004
- type: ndcg_at_3
value: 39.783
- type: ndcg_at_5
value: 41.997
- type: precision_at_1
value: 33.992
- type: precision_at_10
value: 8.498
- type: precision_at_100
value: 1.585
- type: precision_at_1000
value: 0.248
- type: precision_at_3
value: 18.511
- type: precision_at_5
value: 13.241
- type: recall_at_1
value: 28.596
- type: recall_at_10
value: 56.885
- type: recall_at_100
value: 82.306
- type: recall_at_1000
value: 95.813
- type: recall_at_3
value: 42.168
- type: recall_at_5
value: 48.32
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-wordpress
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 25.576
- type: map_at_10
value: 33.034
- type: map_at_100
value: 34.117999999999995
- type: map_at_1000
value: 34.222
- type: map_at_3
value: 30.183
- type: map_at_5
value: 31.974000000000004
- type: mrr_at_1
value: 27.542
- type: mrr_at_10
value: 34.838
- type: mrr_at_100
value: 35.824
- type: mrr_at_1000
value: 35.899
- type: mrr_at_3
value: 32.348
- type: mrr_at_5
value: 34.039
- type: ndcg_at_1
value: 27.542
- type: ndcg_at_10
value: 37.663000000000004
- type: ndcg_at_100
value: 42.762
- type: ndcg_at_1000
value: 45.235
- type: ndcg_at_3
value: 32.227
- type: ndcg_at_5
value: 35.27
- type: precision_at_1
value: 27.542
- type: precision_at_10
value: 5.840999999999999
- type: precision_at_100
value: 0.895
- type: precision_at_1000
value: 0.123
- type: precision_at_3
value: 13.370000000000001
- type: precision_at_5
value: 9.797
- type: recall_at_1
value: 25.576
- type: recall_at_10
value: 50.285000000000004
- type: recall_at_100
value: 73.06
- type: recall_at_1000
value: 91.15299999999999
- type: recall_at_3
value: 35.781
- type: recall_at_5
value: 43.058
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 17.061
- type: map_at_10
value: 29.464000000000002
- type: map_at_100
value: 31.552999999999997
- type: map_at_1000
value: 31.707
- type: map_at_3
value: 24.834999999999997
- type: map_at_5
value: 27.355
- type: mrr_at_1
value: 38.958
- type: mrr_at_10
value: 51.578
- type: mrr_at_100
value: 52.262
- type: mrr_at_1000
value: 52.283
- type: mrr_at_3
value: 48.599
- type: mrr_at_5
value: 50.404
- type: ndcg_at_1
value: 38.958
- type: ndcg_at_10
value: 39.367999999999995
- type: ndcg_at_100
value: 46.521
- type: ndcg_at_1000
value: 49.086999999999996
- type: ndcg_at_3
value: 33.442
- type: ndcg_at_5
value: 35.515
- type: precision_at_1
value: 38.958
- type: precision_at_10
value: 12.110999999999999
- type: precision_at_100
value: 1.982
- type: precision_at_1000
value: 0.247
- type: precision_at_3
value: 25.102999999999998
- type: precision_at_5
value: 18.971
- type: recall_at_1
value: 17.061
- type: recall_at_10
value: 45.198
- type: recall_at_100
value: 69.18900000000001
- type: recall_at_1000
value: 83.38499999999999
- type: recall_at_3
value: 30.241
- type: recall_at_5
value: 36.851
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 9.398
- type: map_at_10
value: 21.421
- type: map_at_100
value: 31.649
- type: map_at_1000
value: 33.469
- type: map_at_3
value: 15.310000000000002
- type: map_at_5
value: 17.946
- type: mrr_at_1
value: 71
- type: mrr_at_10
value: 78.92099999999999
- type: mrr_at_100
value: 79.225
- type: mrr_at_1000
value: 79.23
- type: mrr_at_3
value: 77.792
- type: mrr_at_5
value: 78.467
- type: ndcg_at_1
value: 57.99999999999999
- type: ndcg_at_10
value: 44.733000000000004
- type: ndcg_at_100
value: 50.646
- type: ndcg_at_1000
value: 57.903999999999996
- type: ndcg_at_3
value: 49.175999999999995
- type: ndcg_at_5
value: 46.800999999999995
- type: precision_at_1
value: 71
- type: precision_at_10
value: 36.25
- type: precision_at_100
value: 12.135
- type: precision_at_1000
value: 2.26
- type: precision_at_3
value: 52.75
- type: precision_at_5
value: 45.65
- type: recall_at_1
value: 9.398
- type: recall_at_10
value: 26.596999999999998
- type: recall_at_100
value: 57.943
- type: recall_at_1000
value: 81.147
- type: recall_at_3
value: 16.634
- type: recall_at_5
value: 20.7
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 46.535000000000004
- type: f1
value: 42.53702746452163
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 77.235
- type: map_at_10
value: 85.504
- type: map_at_100
value: 85.707
- type: map_at_1000
value: 85.718
- type: map_at_3
value: 84.425
- type: map_at_5
value: 85.13
- type: mrr_at_1
value: 83.363
- type: mrr_at_10
value: 89.916
- type: mrr_at_100
value: 89.955
- type: mrr_at_1000
value: 89.956
- type: mrr_at_3
value: 89.32600000000001
- type: mrr_at_5
value: 89.79
- type: ndcg_at_1
value: 83.363
- type: ndcg_at_10
value: 89.015
- type: ndcg_at_100
value: 89.649
- type: ndcg_at_1000
value: 89.825
- type: ndcg_at_3
value: 87.45100000000001
- type: ndcg_at_5
value: 88.39399999999999
- type: precision_at_1
value: 83.363
- type: precision_at_10
value: 10.659
- type: precision_at_100
value: 1.122
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 33.338
- type: precision_at_5
value: 20.671999999999997
- type: recall_at_1
value: 77.235
- type: recall_at_10
value: 95.389
- type: recall_at_100
value: 97.722
- type: recall_at_1000
value: 98.744
- type: recall_at_3
value: 91.19800000000001
- type: recall_at_5
value: 93.635
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 20.835
- type: map_at_10
value: 34.459
- type: map_at_100
value: 36.335
- type: map_at_1000
value: 36.518
- type: map_at_3
value: 30.581000000000003
- type: map_at_5
value: 32.859
- type: mrr_at_1
value: 40.894999999999996
- type: mrr_at_10
value: 50.491
- type: mrr_at_100
value: 51.243
- type: mrr_at_1000
value: 51.286
- type: mrr_at_3
value: 47.994
- type: mrr_at_5
value: 49.429
- type: ndcg_at_1
value: 40.894999999999996
- type: ndcg_at_10
value: 42.403
- type: ndcg_at_100
value: 48.954
- type: ndcg_at_1000
value: 51.961
- type: ndcg_at_3
value: 39.11
- type: ndcg_at_5
value: 40.152
- type: precision_at_1
value: 40.894999999999996
- type: precision_at_10
value: 11.466
- type: precision_at_100
value: 1.833
- type: precision_at_1000
value: 0.23700000000000002
- type: precision_at_3
value: 25.874000000000002
- type: precision_at_5
value: 19.012
- type: recall_at_1
value: 20.835
- type: recall_at_10
value: 49.535000000000004
- type: recall_at_100
value: 73.39099999999999
- type: recall_at_1000
value: 91.01599999999999
- type: recall_at_3
value: 36.379
- type: recall_at_5
value: 42.059999999999995
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 40.945
- type: map_at_10
value: 65.376
- type: map_at_100
value: 66.278
- type: map_at_1000
value: 66.33
- type: map_at_3
value: 61.753
- type: map_at_5
value: 64.077
- type: mrr_at_1
value: 81.891
- type: mrr_at_10
value: 87.256
- type: mrr_at_100
value: 87.392
- type: mrr_at_1000
value: 87.395
- type: mrr_at_3
value: 86.442
- type: mrr_at_5
value: 86.991
- type: ndcg_at_1
value: 81.891
- type: ndcg_at_10
value: 73.654
- type: ndcg_at_100
value: 76.62299999999999
- type: ndcg_at_1000
value: 77.60000000000001
- type: ndcg_at_3
value: 68.71199999999999
- type: ndcg_at_5
value: 71.563
- type: precision_at_1
value: 81.891
- type: precision_at_10
value: 15.409
- type: precision_at_100
value: 1.77
- type: precision_at_1000
value: 0.19
- type: precision_at_3
value: 44.15
- type: precision_at_5
value: 28.732000000000003
- type: recall_at_1
value: 40.945
- type: recall_at_10
value: 77.04299999999999
- type: recall_at_100
value: 88.508
- type: recall_at_1000
value: 94.943
- type: recall_at_3
value: 66.226
- type: recall_at_5
value: 71.83
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 74.08200000000001
- type: ap
value: 68.10929101713998
- type: f1
value: 73.98447117652009
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 21.729000000000003
- type: map_at_10
value: 34.602
- type: map_at_100
value: 35.756
- type: map_at_1000
value: 35.803000000000004
- type: map_at_3
value: 30.619000000000003
- type: map_at_5
value: 32.914
- type: mrr_at_1
value: 22.364
- type: mrr_at_10
value: 35.183
- type: mrr_at_100
value: 36.287000000000006
- type: mrr_at_1000
value: 36.327999999999996
- type: mrr_at_3
value: 31.258000000000003
- type: mrr_at_5
value: 33.542
- type: ndcg_at_1
value: 22.364
- type: ndcg_at_10
value: 41.765
- type: ndcg_at_100
value: 47.293
- type: ndcg_at_1000
value: 48.457
- type: ndcg_at_3
value: 33.676
- type: ndcg_at_5
value: 37.783
- type: precision_at_1
value: 22.364
- type: precision_at_10
value: 6.662
- type: precision_at_100
value: 0.943
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.435999999999998
- type: precision_at_5
value: 10.764999999999999
- type: recall_at_1
value: 21.729000000000003
- type: recall_at_10
value: 63.815999999999995
- type: recall_at_100
value: 89.265
- type: recall_at_1000
value: 98.149
- type: recall_at_3
value: 41.898
- type: recall_at_5
value: 51.76500000000001
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 92.73141814865483
- type: f1
value: 92.17518476408004
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 65.18011855905152
- type: f1
value: 46.70999638311856
- task:
type: Classification
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClassification (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: accuracy
value: 75.24261603375525
- type: f1
value: 74.07895183913367
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringP2P (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 28.43855875387446
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringS2S (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 29.05331990256969
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 66.92333557498318
- type: f1
value: 64.29789389602692
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 72.74714189643578
- type: f1
value: 71.672585608315
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.503564225501613
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 28.410225127136457
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.170019896091908
- type: mrr
value: 29.881276831500976
- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 6.544
- type: map_at_10
value: 14.116999999999999
- type: map_at_100
value: 17.522
- type: map_at_1000
value: 19
- type: map_at_3
value: 10.369
- type: map_at_5
value: 12.189
- type: mrr_at_1
value: 47.988
- type: mrr_at_10
value: 56.84
- type: mrr_at_100
value: 57.367000000000004
- type: mrr_at_1000
value: 57.403000000000006
- type: mrr_at_3
value: 54.592
- type: mrr_at_5
value: 56.233
- type: ndcg_at_1
value: 45.82
- type: ndcg_at_10
value: 36.767
- type: ndcg_at_100
value: 33.356
- type: ndcg_at_1000
value: 42.062
- type: ndcg_at_3
value: 42.15
- type: ndcg_at_5
value: 40.355000000000004
- type: precision_at_1
value: 47.988
- type: precision_at_10
value: 27.121000000000002
- type: precision_at_100
value: 8.455
- type: precision_at_1000
value: 2.103
- type: precision_at_3
value: 39.628
- type: precision_at_5
value: 35.356
- type: recall_at_1
value: 6.544
- type: recall_at_10
value: 17.928
- type: recall_at_100
value: 32.843
- type: recall_at_1000
value: 65.752
- type: recall_at_3
value: 11.297
- type: recall_at_5
value: 14.357000000000001
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 39.262
- type: map_at_10
value: 55.095000000000006
- type: map_at_100
value: 55.93900000000001
- type: map_at_1000
value: 55.955999999999996
- type: map_at_3
value: 50.93
- type: map_at_5
value: 53.491
- type: mrr_at_1
value: 43.598
- type: mrr_at_10
value: 57.379999999999995
- type: mrr_at_100
value: 57.940999999999995
- type: mrr_at_1000
value: 57.952000000000005
- type: mrr_at_3
value: 53.998000000000005
- type: mrr_at_5
value: 56.128
- type: ndcg_at_1
value: 43.598
- type: ndcg_at_10
value: 62.427
- type: ndcg_at_100
value: 65.759
- type: ndcg_at_1000
value: 66.133
- type: ndcg_at_3
value: 54.745999999999995
- type: ndcg_at_5
value: 58.975
- type: precision_at_1
value: 43.598
- type: precision_at_10
value: 9.789
- type: precision_at_100
value: 1.171
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 24.295
- type: precision_at_5
value: 17.028
- type: recall_at_1
value: 39.262
- type: recall_at_10
value: 82.317
- type: recall_at_100
value: 96.391
- type: recall_at_1000
value: 99.116
- type: recall_at_3
value: 62.621
- type: recall_at_5
value: 72.357
- task:
type: Classification
dataset:
type: ag_news
name: MTEB NewsClassification
config: default
split: test
revision: eb185aade064a813bc0b7f42de02595523103ca4
metrics:
- type: accuracy
value: 78.17500000000001
- type: f1
value: 78.01940892857273
- 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
- type: cos_sim_ap
value: 59.630757252602464
- type: cos_sim_f1
value: 62.37521514629949
- type: cos_sim_precision
value: 45.34534534534534
- type: cos_sim_recall
value: 99.88974641675854
- type: dot_accuracy
value: 61
- type: dot_ap
value: 59.631527308059006
- type: dot_f1
value: 62.37521514629949
- type: dot_precision
value: 45.34534534534534
- type: dot_recall
value: 99.88974641675854
- type: euclidean_accuracy
value: 61
- type: euclidean_ap
value: 59.630757252602464
- type: euclidean_f1
value: 62.37521514629949
- type: euclidean_precision
value: 45.34534534534534
- type: euclidean_recall
value: 99.88974641675854
- type: manhattan_accuracy
value: 60.9
- type: manhattan_ap
value: 59.613947780462254
- type: manhattan_f1
value: 62.37521514629949
- type: manhattan_precision
value: 45.34534534534534
- type: manhattan_recall
value: 99.88974641675854
- type: max_accuracy
value: 61
- type: max_ap
value: 59.631527308059006
- type: max_f1
value: 62.37521514629949
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 69.963
- type: map_at_10
value: 83.59400000000001
- type: map_at_100
value: 84.236
- type: map_at_1000
value: 84.255
- type: map_at_3
value: 80.69800000000001
- type: map_at_5
value: 82.568
- type: mrr_at_1
value: 80.58999999999999
- type: mrr_at_10
value: 86.78200000000001
- type: mrr_at_100
value: 86.89099999999999
- type: mrr_at_1000
value: 86.893
- type: mrr_at_3
value: 85.757
- type: mrr_at_5
value: 86.507
- type: ndcg_at_1
value: 80.60000000000001
- type: ndcg_at_10
value: 87.41799999999999
- type: ndcg_at_100
value: 88.723
- type: ndcg_at_1000
value: 88.875
- type: ndcg_at_3
value: 84.565
- type: ndcg_at_5
value: 86.236
- type: precision_at_1
value: 80.60000000000001
- type: precision_at_10
value: 13.239
- type: precision_at_100
value: 1.5150000000000001
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.947
- type: precision_at_5
value: 24.354
- type: recall_at_1
value: 69.963
- type: recall_at_10
value: 94.553
- type: recall_at_100
value: 99.104
- type: recall_at_1000
value: 99.872
- type: recall_at_3
value: 86.317
- type: recall_at_5
value: 91.023
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 47.52890410998761
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 62.760692287940486
- 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: 12.695
- type: map_at_100
value: 14.824000000000002
- type: map_at_1000
value: 15.123000000000001
- type: map_at_3
value: 8.968
- type: map_at_5
value: 10.828
- type: mrr_at_1
value: 25.1
- type: mrr_at_10
value: 35.894999999999996
- type: mrr_at_100
value: 36.966
- type: mrr_at_1000
value: 37.019999999999996
- type: mrr_at_3
value: 32.467
- type: mrr_at_5
value: 34.416999999999994
- type: ndcg_at_1
value: 25.1
- type: ndcg_at_10
value: 21.096999999999998
- type: ndcg_at_100
value: 29.202
- type: ndcg_at_1000
value: 34.541
- type: ndcg_at_3
value: 19.875
- type: ndcg_at_5
value: 17.497
- type: precision_at_1
value: 25.1
- type: precision_at_10
value: 10.9
- type: precision_at_100
value: 2.255
- type: precision_at_1000
value: 0.35400000000000004
- type: precision_at_3
value: 18.367
- type: precision_at_5
value: 15.299999999999999
- type: recall_at_1
value: 5.093
- type: recall_at_10
value: 22.092
- type: recall_at_100
value: 45.778
- type: recall_at_1000
value: 71.985
- type: recall_at_3
value: 11.167
- type: recall_at_5
value: 15.501999999999999
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 74.04386981759481
- type: cos_sim_spearman
value: 69.12484963763646
- type: euclidean_pearson
value: 71.49384353291062
- type: euclidean_spearman
value: 69.12484548317074
- type: manhattan_pearson
value: 71.49828173987272
- type: manhattan_spearman
value: 69.08350274367014
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 66.95372527615659
- type: cos_sim_spearman
value: 66.96821894433991
- type: euclidean_pearson
value: 64.675348002074
- type: euclidean_spearman
value: 66.96821894433991
- type: manhattan_pearson
value: 64.5965887073831
- type: manhattan_spearman
value: 66.88569076794741
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 77.34698437961983
- type: cos_sim_spearman
value: 79.1153001117325
- type: euclidean_pearson
value: 78.53562874696966
- type: euclidean_spearman
value: 79.11530018205724
- type: manhattan_pearson
value: 78.46484988944093
- type: manhattan_spearman
value: 79.01416027493104
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 68.81220371935373
- type: cos_sim_spearman
value: 68.50538405089604
- type: euclidean_pearson
value: 68.69204272683749
- type: euclidean_spearman
value: 68.50534223912419
- type: manhattan_pearson
value: 68.67300120149523
- type: manhattan_spearman
value: 68.45404301623115
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 78.2464678879813
- type: cos_sim_spearman
value: 79.92003940566667
- type: euclidean_pearson
value: 79.8080778793964
- type: euclidean_spearman
value: 79.92003940566667
- type: manhattan_pearson
value: 79.80153621444681
- type: manhattan_spearman
value: 79.91293261418134
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 76.31179207708662
- type: cos_sim_spearman
value: 78.65597349856115
- type: euclidean_pearson
value: 78.76937027472678
- type: euclidean_spearman
value: 78.65597349856115
- type: manhattan_pearson
value: 78.77129513300605
- type: manhattan_spearman
value: 78.62640467680775
- 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: 79.43158429552561
- type: cos_sim_spearman
value: 81.46108646565362
- type: euclidean_pearson
value: 81.47071791452292
- type: euclidean_spearman
value: 81.46108646565362
- type: manhattan_pearson
value: 81.56920643846031
- type: manhattan_spearman
value: 81.42226241399516
- 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: 66.89546474141514
- type: cos_sim_spearman
value: 65.8393752170531
- type: euclidean_pearson
value: 67.2580522762307
- type: euclidean_spearman
value: 65.8393752170531
- type: manhattan_pearson
value: 67.45157729300522
- type: manhattan_spearman
value: 66.19470854403802
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 71.39566306334434
- type: cos_sim_spearman
value: 74.0981396086974
- type: euclidean_pearson
value: 73.7834496259745
- type: euclidean_spearman
value: 74.09803741302046
- type: manhattan_pearson
value: 73.79958138780945
- type: manhattan_spearman
value: 74.09894837555905
- 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: 71.39566311006806
- type: cos_sim_spearman
value: 74.0981396086974
- type: euclidean_pearson
value: 73.78344970897099
- type: euclidean_spearman
value: 74.09803741302046
- type: manhattan_pearson
value: 73.79958147136705
- type: manhattan_spearman
value: 74.09894837555905
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 80.81059564334683
- type: mrr
value: 94.62696617108381
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 57.760999999999996
- type: map_at_10
value: 68.614
- type: map_at_100
value: 69.109
- type: map_at_1000
value: 69.134
- type: map_at_3
value: 65.735
- type: map_at_5
value: 67.42099999999999
- type: mrr_at_1
value: 60.667
- type: mrr_at_10
value: 69.94200000000001
- type: mrr_at_100
value: 70.254
- type: mrr_at_1000
value: 70.28
- type: mrr_at_3
value: 67.72200000000001
- type: mrr_at_5
value: 69.18900000000001
- type: ndcg_at_1
value: 60.667
- type: ndcg_at_10
value: 73.548
- type: ndcg_at_100
value: 75.381
- type: ndcg_at_1000
value: 75.991
- type: ndcg_at_3
value: 68.685
- type: ndcg_at_5
value: 71.26
- type: precision_at_1
value: 60.667
- type: precision_at_10
value: 9.833
- type: precision_at_100
value: 1.08
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 26.889000000000003
- type: precision_at_5
value: 17.8
- type: recall_at_1
value: 57.760999999999996
- type: recall_at_10
value: 87.13300000000001
- type: recall_at_100
value: 95
- type: recall_at_1000
value: 99.667
- type: recall_at_3
value: 74.211
- type: recall_at_5
value: 80.63900000000001
- 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: 95.21196473745837
- type: cos_sim_f1
value: 90.69767441860465
- type: cos_sim_precision
value: 91.71779141104295
- type: cos_sim_recall
value: 89.7
- type: dot_accuracy
value: 99.81881188118813
- type: dot_ap
value: 95.21196473745837
- type: dot_f1
value: 90.69767441860465
- type: dot_precision
value: 91.71779141104295
- type: dot_recall
value: 89.7
- type: euclidean_accuracy
value: 99.81881188118813
- type: euclidean_ap
value: 95.21196473745839
- type: euclidean_f1
value: 90.69767441860465
- type: euclidean_precision
value: 91.71779141104295
- type: euclidean_recall
value: 89.7
- type: manhattan_accuracy
value: 99.81287128712871
- type: manhattan_ap
value: 95.16667174835017
- type: manhattan_f1
value: 90.41095890410959
- type: manhattan_precision
value: 91.7610710607621
- type: manhattan_recall
value: 89.1
- type: max_accuracy
value: 99.81881188118813
- type: max_ap
value: 95.21196473745839
- type: max_f1
value: 90.69767441860465
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 59.54942204515638
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 39.42892282672948
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 51.189033075914324
- type: mrr
value: 51.97014790764791
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.09466569775977
- type: cos_sim_spearman
value: 30.31058660775912
- type: dot_pearson
value: 30.09466438861689
- type: dot_spearman
value: 30.31058660775912
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.253
- type: map_at_10
value: 2.07
- type: map_at_100
value: 12.679000000000002
- type: map_at_1000
value: 30.412
- type: map_at_3
value: 0.688
- type: map_at_5
value: 1.079
- type: mrr_at_1
value: 96
- type: mrr_at_10
value: 98
- type: mrr_at_100
value: 98
- type: mrr_at_1000
value: 98
- type: mrr_at_3
value: 98
- type: mrr_at_5
value: 98
- type: ndcg_at_1
value: 89
- type: ndcg_at_10
value: 79.646
- type: ndcg_at_100
value: 62.217999999999996
- type: ndcg_at_1000
value: 55.13400000000001
- type: ndcg_at_3
value: 83.458
- type: ndcg_at_5
value: 80.982
- type: precision_at_1
value: 96
- type: precision_at_10
value: 84.6
- type: precision_at_100
value: 64.34
- type: precision_at_1000
value: 24.534
- type: precision_at_3
value: 88.667
- type: precision_at_5
value: 85.6
- type: recall_at_1
value: 0.253
- type: recall_at_10
value: 2.253
- type: recall_at_100
value: 15.606
- type: recall_at_1000
value: 51.595
- type: recall_at_3
value: 0.7100000000000001
- type: recall_at_5
value: 1.139
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 3.0540000000000003
- type: map_at_10
value: 13.078999999999999
- type: map_at_100
value: 19.468
- type: map_at_1000
value: 21.006
- type: map_at_3
value: 6.8629999999999995
- type: map_at_5
value: 9.187
- type: mrr_at_1
value: 42.857
- type: mrr_at_10
value: 56.735
- type: mrr_at_100
value: 57.352000000000004
- type: mrr_at_1000
value: 57.352000000000004
- type: mrr_at_3
value: 52.721
- type: mrr_at_5
value: 54.66
- type: ndcg_at_1
value: 38.775999999999996
- type: ndcg_at_10
value: 31.469
- type: ndcg_at_100
value: 42.016999999999996
- type: ndcg_at_1000
value: 52.60399999999999
- type: ndcg_at_3
value: 35.894
- type: ndcg_at_5
value: 33.873
- type: precision_at_1
value: 42.857
- type: precision_at_10
value: 27.346999999999998
- type: precision_at_100
value: 8.327
- type: precision_at_1000
value: 1.551
- type: precision_at_3
value: 36.735
- type: precision_at_5
value: 33.469
- type: recall_at_1
value: 3.0540000000000003
- type: recall_at_10
value: 19.185
- type: recall_at_100
value: 51.056000000000004
- type: recall_at_1000
value: 82.814
- type: recall_at_3
value: 7.961
- type: recall_at_5
value: 11.829
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 64.9346
- type: ap
value: 12.121605736777527
- type: f1
value: 50.169902005887955
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 56.72608941709111
- type: f1
value: 57.0702928875253
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 37.72671554400943
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 82.84556237706384
- type: cos_sim_ap
value: 63.28364215788651
- type: cos_sim_f1
value: 60.00000000000001
- type: cos_sim_precision
value: 54.45161290322581
- type: cos_sim_recall
value: 66.80738786279683
- type: dot_accuracy
value: 82.84556237706384
- type: dot_ap
value: 63.28364302860433
- type: dot_f1
value: 60.00000000000001
- type: dot_precision
value: 54.45161290322581
- type: dot_recall
value: 66.80738786279683
- type: euclidean_accuracy
value: 82.84556237706384
- type: euclidean_ap
value: 63.28363625097978
- type: euclidean_f1
value: 60.00000000000001
- type: euclidean_precision
value: 54.45161290322581
- type: euclidean_recall
value: 66.80738786279683
- type: manhattan_accuracy
value: 82.86940454193241
- type: manhattan_ap
value: 63.244773709836764
- type: manhattan_f1
value: 60.12680942696495
- type: manhattan_precision
value: 55.00109433136353
- type: manhattan_recall
value: 66.3060686015831
- type: max_accuracy
value: 82.86940454193241
- type: max_ap
value: 63.28364302860433
- type: max_f1
value: 60.12680942696495
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.32033220786278
- type: cos_sim_ap
value: 84.71928176006863
- type: cos_sim_f1
value: 76.51483333969684
- type: cos_sim_precision
value: 75.89184276300841
- type: cos_sim_recall
value: 77.14813674160764
- type: dot_accuracy
value: 88.32033220786278
- type: dot_ap
value: 84.71928330149228
- type: dot_f1
value: 76.51483333969684
- type: dot_precision
value: 75.89184276300841
- type: dot_recall
value: 77.14813674160764
- type: euclidean_accuracy
value: 88.32033220786278
- type: euclidean_ap
value: 84.71928045384345
- type: euclidean_f1
value: 76.51483333969684
- type: euclidean_precision
value: 75.89184276300841
- type: euclidean_recall
value: 77.14813674160764
- type: manhattan_accuracy
value: 88.27570147863545
- type: manhattan_ap
value: 84.68523541579755
- type: manhattan_f1
value: 76.51512269355146
- type: manhattan_precision
value: 75.62608107091825
- type: manhattan_recall
value: 77.42531567600862
- type: max_accuracy
value: 88.32033220786278
- type: max_ap
value: 84.71928330149228
- type: max_f1
value: 76.51512269355146
- task:
type: Clustering
dataset:
type: jinaai/cities_wiki_clustering
name: MTEB WikiCitiesClustering
config: default
split: test
revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
metrics:
- type: v_measure
value: 85.30624598674467
license: apache-2.0