metadata
tags:
- mteb
- arctic
- arctic-embed
model-index:
- name: snowflake-arctic-embed-s
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 71.17910447761193
- type: ap
value: 33.15833652904991
- type: f1
value: 64.86214791591543
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 78.750325
- type: ap
value: 72.83242788470943
- type: f1
value: 78.63968044029453
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 38.264
- type: f1
value: 37.140269688532825
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 32.646
- type: map_at_10
value: 48.372
- type: map_at_100
value: 49.207
- type: map_at_1000
value: 49.214
- type: map_at_3
value: 43.611
- type: map_at_5
value: 46.601
- type: mrr_at_1
value: 33.144
- type: mrr_at_10
value: 48.557
- type: mrr_at_100
value: 49.385
- type: mrr_at_1000
value: 49.392
- type: mrr_at_3
value: 43.777
- type: mrr_at_5
value: 46.792
- type: ndcg_at_1
value: 32.646
- type: ndcg_at_10
value: 56.874
- type: ndcg_at_100
value: 60.307
- type: ndcg_at_1000
value: 60.465999999999994
- type: ndcg_at_3
value: 47.339999999999996
- type: ndcg_at_5
value: 52.685
- type: precision_at_1
value: 32.646
- type: precision_at_10
value: 8.378
- type: precision_at_100
value: 0.984
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 19.393
- type: precision_at_5
value: 14.210999999999999
- type: recall_at_1
value: 32.646
- type: recall_at_10
value: 83.784
- type: recall_at_100
value: 98.43499999999999
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 58.179
- type: recall_at_5
value: 71.053
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 44.94353025039141
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 35.870836103029156
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 61.149290266979236
- type: mrr
value: 73.8448093919008
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.055571064151
- type: cos_sim_spearman
value: 86.2652186235749
- type: euclidean_pearson
value: 85.82039272282503
- type: euclidean_spearman
value: 86.2652186235749
- type: manhattan_pearson
value: 85.95825392094812
- type: manhattan_spearman
value: 86.6742640885316
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 79.11688311688312
- type: f1
value: 78.28328901613885
- task:
type: Clustering
dataset:
type: jinaai/big-patent-clustering
name: MTEB BigPatentClustering
config: default
split: test
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
metrics:
- type: v_measure
value: 19.147523589859325
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 35.68369864124274
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 30.474958792950872
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-android
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 33.183
- type: map_at_10
value: 43.989
- type: map_at_100
value: 45.389
- type: map_at_1000
value: 45.517
- type: map_at_3
value: 40.275
- type: map_at_5
value: 42.306
- type: mrr_at_1
value: 40.486
- type: mrr_at_10
value: 49.62
- type: mrr_at_100
value: 50.351
- type: mrr_at_1000
value: 50.393
- type: mrr_at_3
value: 46.805
- type: mrr_at_5
value: 48.429
- type: ndcg_at_1
value: 40.486
- type: ndcg_at_10
value: 50.249
- type: ndcg_at_100
value: 55.206
- type: ndcg_at_1000
value: 57.145
- type: ndcg_at_3
value: 44.852
- type: ndcg_at_5
value: 47.355000000000004
- type: precision_at_1
value: 40.486
- type: precision_at_10
value: 9.571
- type: precision_at_100
value: 1.4949999999999999
- type: precision_at_1000
value: 0.196
- type: precision_at_3
value: 21.173000000000002
- type: precision_at_5
value: 15.622
- type: recall_at_1
value: 33.183
- type: recall_at_10
value: 62.134
- type: recall_at_100
value: 82.73
- type: recall_at_1000
value: 94.93599999999999
- type: recall_at_3
value: 46.497
- type: recall_at_5
value: 53.199
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-english
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 32.862
- type: map_at_10
value: 42.439
- type: map_at_100
value: 43.736999999999995
- type: map_at_1000
value: 43.864
- type: map_at_3
value: 39.67
- type: map_at_5
value: 41.202
- type: mrr_at_1
value: 40.892
- type: mrr_at_10
value: 48.61
- type: mrr_at_100
value: 49.29
- type: mrr_at_1000
value: 49.332
- type: mrr_at_3
value: 46.688
- type: mrr_at_5
value: 47.803000000000004
- type: ndcg_at_1
value: 40.892
- type: ndcg_at_10
value: 47.797
- type: ndcg_at_100
value: 52.17699999999999
- type: ndcg_at_1000
value: 54.127
- type: ndcg_at_3
value: 44.189
- type: ndcg_at_5
value: 45.821
- type: precision_at_1
value: 40.892
- type: precision_at_10
value: 8.841000000000001
- type: precision_at_100
value: 1.419
- type: precision_at_1000
value: 0.188
- type: precision_at_3
value: 21.104
- type: precision_at_5
value: 14.777000000000001
- type: recall_at_1
value: 32.862
- type: recall_at_10
value: 56.352999999999994
- type: recall_at_100
value: 74.795
- type: recall_at_1000
value: 86.957
- type: recall_at_3
value: 45.269999999999996
- type: recall_at_5
value: 50.053000000000004
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gaming
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 42.998999999999995
- type: map_at_10
value: 54.745
- type: map_at_100
value: 55.650999999999996
- type: map_at_1000
value: 55.703
- type: map_at_3
value: 51.67
- type: map_at_5
value: 53.503
- type: mrr_at_1
value: 49.028
- type: mrr_at_10
value: 58.172000000000004
- type: mrr_at_100
value: 58.744
- type: mrr_at_1000
value: 58.769000000000005
- type: mrr_at_3
value: 55.977
- type: mrr_at_5
value: 57.38799999999999
- type: ndcg_at_1
value: 49.028
- type: ndcg_at_10
value: 60.161
- type: ndcg_at_100
value: 63.806
- type: ndcg_at_1000
value: 64.821
- type: ndcg_at_3
value: 55.199
- type: ndcg_at_5
value: 57.830999999999996
- type: precision_at_1
value: 49.028
- type: precision_at_10
value: 9.455
- type: precision_at_100
value: 1.216
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 24.242
- type: precision_at_5
value: 16.614
- type: recall_at_1
value: 42.998999999999995
- type: recall_at_10
value: 72.542
- type: recall_at_100
value: 88.605
- type: recall_at_1000
value: 95.676
- type: recall_at_3
value: 59.480999999999995
- type: recall_at_5
value: 65.886
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gis
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 27.907
- type: map_at_10
value: 35.975
- type: map_at_100
value: 36.985
- type: map_at_1000
value: 37.063
- type: map_at_3
value: 33.467999999999996
- type: map_at_5
value: 34.749
- type: mrr_at_1
value: 30.056
- type: mrr_at_10
value: 38.047
- type: mrr_at_100
value: 38.932
- type: mrr_at_1000
value: 38.991
- type: mrr_at_3
value: 35.705999999999996
- type: mrr_at_5
value: 36.966
- type: ndcg_at_1
value: 30.056
- type: ndcg_at_10
value: 40.631
- type: ndcg_at_100
value: 45.564
- type: ndcg_at_1000
value: 47.685
- type: ndcg_at_3
value: 35.748000000000005
- type: ndcg_at_5
value: 37.921
- type: precision_at_1
value: 30.056
- type: precision_at_10
value: 6.079
- type: precision_at_100
value: 0.898
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 14.727
- type: precision_at_5
value: 10.056
- type: recall_at_1
value: 27.907
- type: recall_at_10
value: 52.981
- type: recall_at_100
value: 75.53999999999999
- type: recall_at_1000
value: 91.759
- type: recall_at_3
value: 39.878
- type: recall_at_5
value: 45.077
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-mathematica
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 16.764000000000003
- type: map_at_10
value: 24.294
- type: map_at_100
value: 25.507999999999996
- type: map_at_1000
value: 25.64
- type: map_at_3
value: 21.807000000000002
- type: map_at_5
value: 23.21
- type: mrr_at_1
value: 20.771
- type: mrr_at_10
value: 28.677000000000003
- type: mrr_at_100
value: 29.742
- type: mrr_at_1000
value: 29.816
- type: mrr_at_3
value: 26.327
- type: mrr_at_5
value: 27.639000000000003
- type: ndcg_at_1
value: 20.771
- type: ndcg_at_10
value: 29.21
- type: ndcg_at_100
value: 34.788000000000004
- type: ndcg_at_1000
value: 37.813
- type: ndcg_at_3
value: 24.632
- type: ndcg_at_5
value: 26.801000000000002
- type: precision_at_1
value: 20.771
- type: precision_at_10
value: 5.373
- type: precision_at_100
value: 0.923
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 12.065
- type: precision_at_5
value: 8.706
- type: recall_at_1
value: 16.764000000000003
- type: recall_at_10
value: 40.072
- type: recall_at_100
value: 63.856
- type: recall_at_1000
value: 85.141
- type: recall_at_3
value: 27.308
- type: recall_at_5
value: 32.876
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-physics
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 31.194
- type: map_at_10
value: 40.731
- type: map_at_100
value: 42.073
- type: map_at_1000
value: 42.178
- type: map_at_3
value: 37.726
- type: map_at_5
value: 39.474
- type: mrr_at_1
value: 37.729
- type: mrr_at_10
value: 46.494
- type: mrr_at_100
value: 47.368
- type: mrr_at_1000
value: 47.407
- type: mrr_at_3
value: 44.224999999999994
- type: mrr_at_5
value: 45.582
- type: ndcg_at_1
value: 37.729
- type: ndcg_at_10
value: 46.312999999999995
- type: ndcg_at_100
value: 51.915
- type: ndcg_at_1000
value: 53.788000000000004
- type: ndcg_at_3
value: 41.695
- type: ndcg_at_5
value: 43.956
- type: precision_at_1
value: 37.729
- type: precision_at_10
value: 8.181
- type: precision_at_100
value: 1.275
- type: precision_at_1000
value: 0.16199999999999998
- type: precision_at_3
value: 19.41
- type: precision_at_5
value: 13.648
- type: recall_at_1
value: 31.194
- type: recall_at_10
value: 57.118
- type: recall_at_100
value: 80.759
- type: recall_at_1000
value: 92.779
- type: recall_at_3
value: 44.083
- type: recall_at_5
value: 50.044999999999995
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-programmers
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 28.047
- type: map_at_10
value: 37.79
- type: map_at_100
value: 39.145
- type: map_at_1000
value: 39.254
- type: map_at_3
value: 34.857
- type: map_at_5
value: 36.545
- type: mrr_at_1
value: 35.388
- type: mrr_at_10
value: 43.475
- type: mrr_at_100
value: 44.440000000000005
- type: mrr_at_1000
value: 44.494
- type: mrr_at_3
value: 41.286
- type: mrr_at_5
value: 42.673
- type: ndcg_at_1
value: 35.388
- type: ndcg_at_10
value: 43.169000000000004
- type: ndcg_at_100
value: 48.785000000000004
- type: ndcg_at_1000
value: 51.029
- type: ndcg_at_3
value: 38.801
- type: ndcg_at_5
value: 40.9
- type: precision_at_1
value: 35.388
- type: precision_at_10
value: 7.7509999999999994
- type: precision_at_100
value: 1.212
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 18.455
- type: precision_at_5
value: 13.014000000000001
- type: recall_at_1
value: 28.047
- type: recall_at_10
value: 53.53099999999999
- type: recall_at_100
value: 77.285
- type: recall_at_1000
value: 92.575
- type: recall_at_3
value: 40.949000000000005
- type: recall_at_5
value: 46.742
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 28.131999999999994
- type: map_at_10
value: 36.93333333333334
- type: map_at_100
value: 38.117250000000006
- type: map_at_1000
value: 38.23275
- type: map_at_3
value: 34.19708333333333
- type: map_at_5
value: 35.725166666666674
- type: mrr_at_1
value: 33.16116666666667
- type: mrr_at_10
value: 41.057833333333335
- type: mrr_at_100
value: 41.90033333333333
- type: mrr_at_1000
value: 41.95625
- type: mrr_at_3
value: 38.757333333333335
- type: mrr_at_5
value: 40.097333333333324
- type: ndcg_at_1
value: 33.16116666666667
- type: ndcg_at_10
value: 42.01983333333333
- type: ndcg_at_100
value: 46.99916666666667
- type: ndcg_at_1000
value: 49.21783333333334
- type: ndcg_at_3
value: 37.479916666666654
- type: ndcg_at_5
value: 39.6355
- type: precision_at_1
value: 33.16116666666667
- type: precision_at_10
value: 7.230249999999999
- type: precision_at_100
value: 1.1411666666666667
- type: precision_at_1000
value: 0.1520833333333333
- type: precision_at_3
value: 17.028166666666667
- type: precision_at_5
value: 12.046999999999999
- type: recall_at_1
value: 28.131999999999994
- type: recall_at_10
value: 52.825500000000005
- type: recall_at_100
value: 74.59608333333333
- type: recall_at_1000
value: 89.87916666666668
- type: recall_at_3
value: 40.13625
- type: recall_at_5
value: 45.699999999999996
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-stats
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 24.773999999999997
- type: map_at_10
value: 31.997999999999998
- type: map_at_100
value: 32.857
- type: map_at_1000
value: 32.957
- type: map_at_3
value: 30.041
- type: map_at_5
value: 31.119000000000003
- type: mrr_at_1
value: 27.607
- type: mrr_at_10
value: 34.538000000000004
- type: mrr_at_100
value: 35.308
- type: mrr_at_1000
value: 35.375
- type: mrr_at_3
value: 32.643
- type: mrr_at_5
value: 33.755
- type: ndcg_at_1
value: 27.607
- type: ndcg_at_10
value: 36.035000000000004
- type: ndcg_at_100
value: 40.351
- type: ndcg_at_1000
value: 42.684
- type: ndcg_at_3
value: 32.414
- type: ndcg_at_5
value: 34.11
- type: precision_at_1
value: 27.607
- type: precision_at_10
value: 5.6129999999999995
- type: precision_at_100
value: 0.8370000000000001
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 13.957
- type: precision_at_5
value: 9.571
- type: recall_at_1
value: 24.773999999999997
- type: recall_at_10
value: 45.717
- type: recall_at_100
value: 65.499
- type: recall_at_1000
value: 82.311
- type: recall_at_3
value: 35.716
- type: recall_at_5
value: 40.007999999999996
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-tex
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 19.227
- type: map_at_10
value: 26.649
- type: map_at_100
value: 27.711999999999996
- type: map_at_1000
value: 27.837
- type: map_at_3
value: 24.454
- type: map_at_5
value: 25.772000000000002
- type: mrr_at_1
value: 23.433999999999997
- type: mrr_at_10
value: 30.564999999999998
- type: mrr_at_100
value: 31.44
- type: mrr_at_1000
value: 31.513999999999996
- type: mrr_at_3
value: 28.435
- type: mrr_at_5
value: 29.744999999999997
- type: ndcg_at_1
value: 23.433999999999997
- type: ndcg_at_10
value: 31.104
- type: ndcg_at_100
value: 36.172
- type: ndcg_at_1000
value: 39.006
- type: ndcg_at_3
value: 27.248
- type: ndcg_at_5
value: 29.249000000000002
- type: precision_at_1
value: 23.433999999999997
- type: precision_at_10
value: 5.496
- type: precision_at_100
value: 0.9490000000000001
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 12.709000000000001
- type: precision_at_5
value: 9.209
- type: recall_at_1
value: 19.227
- type: recall_at_10
value: 40.492
- type: recall_at_100
value: 63.304
- type: recall_at_1000
value: 83.45
- type: recall_at_3
value: 29.713
- type: recall_at_5
value: 34.82
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-unix
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 29.199
- type: map_at_10
value: 37.617
- type: map_at_100
value: 38.746
- type: map_at_1000
value: 38.851
- type: map_at_3
value: 34.882000000000005
- type: map_at_5
value: 36.571999999999996
- type: mrr_at_1
value: 33.489000000000004
- type: mrr_at_10
value: 41.089999999999996
- type: mrr_at_100
value: 41.965
- type: mrr_at_1000
value: 42.028
- type: mrr_at_3
value: 38.666
- type: mrr_at_5
value: 40.159
- type: ndcg_at_1
value: 33.489000000000004
- type: ndcg_at_10
value: 42.487
- type: ndcg_at_100
value: 47.552
- type: ndcg_at_1000
value: 49.774
- type: ndcg_at_3
value: 37.623
- type: ndcg_at_5
value: 40.184999999999995
- type: precision_at_1
value: 33.489000000000004
- type: precision_at_10
value: 6.94
- type: precision_at_100
value: 1.0699999999999998
- type: precision_at_1000
value: 0.136
- type: precision_at_3
value: 16.667
- type: precision_at_5
value: 11.922
- type: recall_at_1
value: 29.199
- type: recall_at_10
value: 53.689
- type: recall_at_100
value: 75.374
- type: recall_at_1000
value: 90.64999999999999
- type: recall_at_3
value: 40.577999999999996
- type: recall_at_5
value: 46.909
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-webmasters
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 27.206999999999997
- type: map_at_10
value: 36.146
- type: map_at_100
value: 37.759
- type: map_at_1000
value: 37.979
- type: map_at_3
value: 32.967999999999996
- type: map_at_5
value: 34.809
- type: mrr_at_1
value: 32.806000000000004
- type: mrr_at_10
value: 40.449
- type: mrr_at_100
value: 41.404999999999994
- type: mrr_at_1000
value: 41.457
- type: mrr_at_3
value: 37.614999999999995
- type: mrr_at_5
value: 39.324999999999996
- type: ndcg_at_1
value: 32.806000000000004
- type: ndcg_at_10
value: 41.911
- type: ndcg_at_100
value: 47.576
- type: ndcg_at_1000
value: 50.072
- type: ndcg_at_3
value: 36.849
- type: ndcg_at_5
value: 39.475
- type: precision_at_1
value: 32.806000000000004
- type: precision_at_10
value: 8.103
- type: precision_at_100
value: 1.557
- type: precision_at_1000
value: 0.242
- type: precision_at_3
value: 17.26
- type: precision_at_5
value: 12.885
- type: recall_at_1
value: 27.206999999999997
- type: recall_at_10
value: 52.56999999999999
- type: recall_at_100
value: 78.302
- type: recall_at_1000
value: 94.121
- type: recall_at_3
value: 38.317
- type: recall_at_5
value: 45.410000000000004
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-wordpress
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 24.221
- type: map_at_10
value: 30.826999999999998
- type: map_at_100
value: 31.845000000000002
- type: map_at_1000
value: 31.95
- type: map_at_3
value: 28.547
- type: map_at_5
value: 29.441
- type: mrr_at_1
value: 26.247999999999998
- type: mrr_at_10
value: 32.957
- type: mrr_at_100
value: 33.819
- type: mrr_at_1000
value: 33.899
- type: mrr_at_3
value: 30.714999999999996
- type: mrr_at_5
value: 31.704
- type: ndcg_at_1
value: 26.247999999999998
- type: ndcg_at_10
value: 35.171
- type: ndcg_at_100
value: 40.098
- type: ndcg_at_1000
value: 42.67
- type: ndcg_at_3
value: 30.508999999999997
- type: ndcg_at_5
value: 32.022
- type: precision_at_1
value: 26.247999999999998
- type: precision_at_10
value: 5.36
- type: precision_at_100
value: 0.843
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 12.568999999999999
- type: precision_at_5
value: 8.540000000000001
- type: recall_at_1
value: 24.221
- type: recall_at_10
value: 46.707
- type: recall_at_100
value: 69.104
- type: recall_at_1000
value: 88.19500000000001
- type: recall_at_3
value: 33.845
- type: recall_at_5
value: 37.375
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 13.624
- type: map_at_10
value: 22.557
- type: map_at_100
value: 24.367
- type: map_at_1000
value: 24.54
- type: map_at_3
value: 18.988
- type: map_at_5
value: 20.785999999999998
- type: mrr_at_1
value: 30.619000000000003
- type: mrr_at_10
value: 42.019
- type: mrr_at_100
value: 42.818
- type: mrr_at_1000
value: 42.856
- type: mrr_at_3
value: 38.578
- type: mrr_at_5
value: 40.669
- type: ndcg_at_1
value: 30.619000000000003
- type: ndcg_at_10
value: 31.252999999999997
- type: ndcg_at_100
value: 38.238
- type: ndcg_at_1000
value: 41.368
- type: ndcg_at_3
value: 25.843
- type: ndcg_at_5
value: 27.638
- type: precision_at_1
value: 30.619000000000003
- type: precision_at_10
value: 9.687
- type: precision_at_100
value: 1.718
- type: precision_at_1000
value: 0.22999999999999998
- type: precision_at_3
value: 18.849
- type: precision_at_5
value: 14.463000000000001
- type: recall_at_1
value: 13.624
- type: recall_at_10
value: 36.693999999999996
- type: recall_at_100
value: 60.9
- type: recall_at_1000
value: 78.46
- type: recall_at_3
value: 23.354
- type: recall_at_5
value: 28.756999999999998
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 9.077
- type: map_at_10
value: 19.813
- type: map_at_100
value: 27.822999999999997
- type: map_at_1000
value: 29.485
- type: map_at_3
value: 14.255999999999998
- type: map_at_5
value: 16.836000000000002
- type: mrr_at_1
value: 69.25
- type: mrr_at_10
value: 77.059
- type: mrr_at_100
value: 77.41
- type: mrr_at_1000
value: 77.416
- type: mrr_at_3
value: 75.625
- type: mrr_at_5
value: 76.512
- type: ndcg_at_1
value: 55.75
- type: ndcg_at_10
value: 41.587
- type: ndcg_at_100
value: 46.048
- type: ndcg_at_1000
value: 53.172
- type: ndcg_at_3
value: 46.203
- type: ndcg_at_5
value: 43.696
- type: precision_at_1
value: 69.25
- type: precision_at_10
value: 32.95
- type: precision_at_100
value: 10.555
- type: precision_at_1000
value: 2.136
- type: precision_at_3
value: 49.667
- type: precision_at_5
value: 42.5
- type: recall_at_1
value: 9.077
- type: recall_at_10
value: 25.249
- type: recall_at_100
value: 51.964
- type: recall_at_1000
value: 74.51
- type: recall_at_3
value: 15.584000000000001
- type: recall_at_5
value: 19.717000000000002
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 45.769999999999996
- type: f1
value: 41.64144711933962
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 67.098
- type: map_at_10
value: 77.69800000000001
- type: map_at_100
value: 77.947
- type: map_at_1000
value: 77.961
- type: map_at_3
value: 76.278
- type: map_at_5
value: 77.217
- type: mrr_at_1
value: 72.532
- type: mrr_at_10
value: 82.41199999999999
- type: mrr_at_100
value: 82.527
- type: mrr_at_1000
value: 82.529
- type: mrr_at_3
value: 81.313
- type: mrr_at_5
value: 82.069
- type: ndcg_at_1
value: 72.532
- type: ndcg_at_10
value: 82.488
- type: ndcg_at_100
value: 83.382
- type: ndcg_at_1000
value: 83.622
- type: ndcg_at_3
value: 80.101
- type: ndcg_at_5
value: 81.52199999999999
- type: precision_at_1
value: 72.532
- type: precision_at_10
value: 10.203
- type: precision_at_100
value: 1.082
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 31.308000000000003
- type: precision_at_5
value: 19.652
- type: recall_at_1
value: 67.098
- type: recall_at_10
value: 92.511
- type: recall_at_100
value: 96.06099999999999
- type: recall_at_1000
value: 97.548
- type: recall_at_3
value: 86.105
- type: recall_at_5
value: 89.661
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 18.681
- type: map_at_10
value: 31.739
- type: map_at_100
value: 33.503
- type: map_at_1000
value: 33.69
- type: map_at_3
value: 27.604
- type: map_at_5
value: 29.993
- type: mrr_at_1
value: 37.5
- type: mrr_at_10
value: 46.933
- type: mrr_at_100
value: 47.771
- type: mrr_at_1000
value: 47.805
- type: mrr_at_3
value: 44.239
- type: mrr_at_5
value: 45.766
- type: ndcg_at_1
value: 37.5
- type: ndcg_at_10
value: 39.682
- type: ndcg_at_100
value: 46.127
- type: ndcg_at_1000
value: 48.994
- type: ndcg_at_3
value: 35.655
- type: ndcg_at_5
value: 37.036
- type: precision_at_1
value: 37.5
- type: precision_at_10
value: 11.08
- type: precision_at_100
value: 1.765
- type: precision_at_1000
value: 0.22999999999999998
- type: precision_at_3
value: 23.919999999999998
- type: precision_at_5
value: 17.809
- type: recall_at_1
value: 18.681
- type: recall_at_10
value: 47.548
- type: recall_at_100
value: 71.407
- type: recall_at_1000
value: 87.805
- type: recall_at_3
value: 32.979
- type: recall_at_5
value: 39.192
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 38.257999999999996
- type: map_at_10
value: 57.605
- type: map_at_100
value: 58.50300000000001
- type: map_at_1000
value: 58.568
- type: map_at_3
value: 54.172
- type: map_at_5
value: 56.323
- type: mrr_at_1
value: 76.51599999999999
- type: mrr_at_10
value: 82.584
- type: mrr_at_100
value: 82.78
- type: mrr_at_1000
value: 82.787
- type: mrr_at_3
value: 81.501
- type: mrr_at_5
value: 82.185
- type: ndcg_at_1
value: 76.51599999999999
- type: ndcg_at_10
value: 66.593
- type: ndcg_at_100
value: 69.699
- type: ndcg_at_1000
value: 70.953
- type: ndcg_at_3
value: 61.673
- type: ndcg_at_5
value: 64.42
- type: precision_at_1
value: 76.51599999999999
- type: precision_at_10
value: 13.857
- type: precision_at_100
value: 1.628
- type: precision_at_1000
value: 0.179
- type: precision_at_3
value: 38.956
- type: precision_at_5
value: 25.541999999999998
- type: recall_at_1
value: 38.257999999999996
- type: recall_at_10
value: 69.284
- type: recall_at_100
value: 81.391
- type: recall_at_1000
value: 89.689
- type: recall_at_3
value: 58.433
- type: recall_at_5
value: 63.856
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 69.48679999999999
- type: ap
value: 63.97638838971138
- type: f1
value: 69.22731638841675
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 20.916999999999998
- type: map_at_10
value: 32.929
- type: map_at_100
value: 34.1
- type: map_at_1000
value: 34.152
- type: map_at_3
value: 29.065
- type: map_at_5
value: 31.287
- type: mrr_at_1
value: 21.562
- type: mrr_at_10
value: 33.533
- type: mrr_at_100
value: 34.644000000000005
- type: mrr_at_1000
value: 34.69
- type: mrr_at_3
value: 29.735
- type: mrr_at_5
value: 31.928
- type: ndcg_at_1
value: 21.562
- type: ndcg_at_10
value: 39.788000000000004
- type: ndcg_at_100
value: 45.434999999999995
- type: ndcg_at_1000
value: 46.75
- type: ndcg_at_3
value: 31.942999999999998
- type: ndcg_at_5
value: 35.888
- type: precision_at_1
value: 21.562
- type: precision_at_10
value: 6.348
- type: precision_at_100
value: 0.918
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 13.682
- type: precision_at_5
value: 10.189
- type: recall_at_1
value: 20.916999999999998
- type: recall_at_10
value: 60.926
- type: recall_at_100
value: 87.03800000000001
- type: recall_at_1000
value: 97.085
- type: recall_at_3
value: 39.637
- type: recall_at_5
value: 49.069
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 90.93935248518011
- type: f1
value: 90.56439321844506
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 58.62517099863203
- type: f1
value: 40.69925681703197
- task:
type: Classification
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClassification (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: accuracy
value: 76.29746835443039
- type: f1
value: 75.31702672039506
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringP2P (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 43.05495067062023
- task:
type: Clustering
dataset:
type: masakhane/masakhanews
name: MTEB MasakhaNEWSClusteringS2S (eng)
config: eng
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure
value: 19.625272848173843
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 64.76126429051781
- type: f1
value: 62.60284261265268
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 70.05043712172159
- type: f1
value: 69.08340521169049
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 30.78969229005989
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 27.954325178520335
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.601827413968596
- type: mrr
value: 31.515372019474196
- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 5.4559999999999995
- type: map_at_10
value: 12.039
- type: map_at_100
value: 14.804999999999998
- type: map_at_1000
value: 16.081
- type: map_at_3
value: 8.996
- type: map_at_5
value: 10.357
- type: mrr_at_1
value: 45.82
- type: mrr_at_10
value: 53.583999999999996
- type: mrr_at_100
value: 54.330999999999996
- type: mrr_at_1000
value: 54.366
- type: mrr_at_3
value: 52.166999999999994
- type: mrr_at_5
value: 52.971999999999994
- type: ndcg_at_1
value: 44.427
- type: ndcg_at_10
value: 32.536
- type: ndcg_at_100
value: 29.410999999999998
- type: ndcg_at_1000
value: 38.012
- type: ndcg_at_3
value: 38.674
- type: ndcg_at_5
value: 36.107
- type: precision_at_1
value: 45.82
- type: precision_at_10
value: 23.591
- type: precision_at_100
value: 7.35
- type: precision_at_1000
value: 1.9769999999999999
- type: precision_at_3
value: 36.016999999999996
- type: precision_at_5
value: 30.959999999999997
- type: recall_at_1
value: 5.4559999999999995
- type: recall_at_10
value: 15.387
- type: recall_at_100
value: 28.754999999999995
- type: recall_at_1000
value: 59.787
- type: recall_at_3
value: 10.137
- type: recall_at_5
value: 12.200999999999999
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 32.609
- type: map_at_10
value: 48.522
- type: map_at_100
value: 49.468
- type: map_at_1000
value: 49.497
- type: map_at_3
value: 44.327
- type: map_at_5
value: 46.937
- type: mrr_at_1
value: 36.616
- type: mrr_at_10
value: 50.943000000000005
- type: mrr_at_100
value: 51.626000000000005
- type: mrr_at_1000
value: 51.647
- type: mrr_at_3
value: 47.532999999999994
- type: mrr_at_5
value: 49.714000000000006
- type: ndcg_at_1
value: 36.586999999999996
- type: ndcg_at_10
value: 56.19499999999999
- type: ndcg_at_100
value: 60.014
- type: ndcg_at_1000
value: 60.707
- type: ndcg_at_3
value: 48.486000000000004
- type: ndcg_at_5
value: 52.791999999999994
- type: precision_at_1
value: 36.586999999999996
- type: precision_at_10
value: 9.139999999999999
- type: precision_at_100
value: 1.129
- type: precision_at_1000
value: 0.11900000000000001
- type: precision_at_3
value: 22.171
- type: precision_at_5
value: 15.787999999999998
- type: recall_at_1
value: 32.609
- type: recall_at_10
value: 77.011
- type: recall_at_100
value: 93.202
- type: recall_at_1000
value: 98.344
- type: recall_at_3
value: 57.286
- type: recall_at_5
value: 67.181
- task:
type: Classification
dataset:
type: ag_news
name: MTEB NewsClassification
config: default
split: test
revision: eb185aade064a813bc0b7f42de02595523103ca4
metrics:
- type: accuracy
value: 77.4421052631579
- type: f1
value: 77.23976860913628
- 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: 61.25000000000001
- type: cos_sim_ap
value: 59.23166242799505
- type: cos_sim_f1
value: 62.53016201309893
- type: cos_sim_precision
value: 45.486459378134406
- type: cos_sim_recall
value: 100
- type: dot_accuracy
value: 61.25000000000001
- type: dot_ap
value: 59.23109306756652
- type: dot_f1
value: 62.53016201309893
- type: dot_precision
value: 45.486459378134406
- type: dot_recall
value: 100
- type: euclidean_accuracy
value: 61.25000000000001
- type: euclidean_ap
value: 59.23166242799505
- type: euclidean_f1
value: 62.53016201309893
- type: euclidean_precision
value: 45.486459378134406
- type: euclidean_recall
value: 100
- type: manhattan_accuracy
value: 61.25000000000001
- type: manhattan_ap
value: 59.23015114712089
- type: manhattan_f1
value: 62.50861474844934
- type: manhattan_precision
value: 45.46365914786967
- type: manhattan_recall
value: 100
- type: max_accuracy
value: 61.25000000000001
- type: max_ap
value: 59.23166242799505
- type: max_f1
value: 62.53016201309893
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 69.919
- type: map_at_10
value: 83.636
- type: map_at_100
value: 84.27
- type: map_at_1000
value: 84.289
- type: map_at_3
value: 80.744
- type: map_at_5
value: 82.509
- type: mrr_at_1
value: 80.52
- type: mrr_at_10
value: 86.751
- type: mrr_at_100
value: 86.875
- type: mrr_at_1000
value: 86.876
- type: mrr_at_3
value: 85.798
- type: mrr_at_5
value: 86.414
- type: ndcg_at_1
value: 80.53
- type: ndcg_at_10
value: 87.465
- type: ndcg_at_100
value: 88.762
- type: ndcg_at_1000
value: 88.90599999999999
- type: ndcg_at_3
value: 84.634
- type: ndcg_at_5
value: 86.09400000000001
- type: precision_at_1
value: 80.53
- type: precision_at_10
value: 13.263
- type: precision_at_100
value: 1.517
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.973
- type: precision_at_5
value: 24.25
- type: recall_at_1
value: 69.919
- type: recall_at_10
value: 94.742
- type: recall_at_100
value: 99.221
- type: recall_at_1000
value: 99.917
- type: recall_at_3
value: 86.506
- type: recall_at_5
value: 90.736
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 50.47309147963901
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 60.53779561923047
- task:
type: Retrieval
dataset:
type: mteb/scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
metrics:
- type: map_at_1
value: 4.843
- type: map_at_10
value: 11.664
- type: map_at_100
value: 13.499
- type: map_at_1000
value: 13.771
- type: map_at_3
value: 8.602
- type: map_at_5
value: 10.164
- type: mrr_at_1
value: 23.9
- type: mrr_at_10
value: 34.018
- type: mrr_at_100
value: 35.099000000000004
- type: mrr_at_1000
value: 35.162
- type: mrr_at_3
value: 31.233
- type: mrr_at_5
value: 32.793
- type: ndcg_at_1
value: 23.9
- type: ndcg_at_10
value: 19.42
- type: ndcg_at_100
value: 26.715
- type: ndcg_at_1000
value: 31.776
- type: ndcg_at_3
value: 19.165
- type: ndcg_at_5
value: 16.46
- type: precision_at_1
value: 23.9
- type: precision_at_10
value: 9.82
- type: precision_at_100
value: 2.0340000000000003
- type: precision_at_1000
value: 0.325
- type: precision_at_3
value: 17.767
- type: precision_at_5
value: 14.24
- type: recall_at_1
value: 4.843
- type: recall_at_10
value: 19.895
- type: recall_at_100
value: 41.302
- type: recall_at_1000
value: 66.077
- type: recall_at_3
value: 10.803
- type: recall_at_5
value: 14.418000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 76.94120735638143
- type: cos_sim_spearman
value: 69.66114097154585
- type: euclidean_pearson
value: 73.11242035696426
- type: euclidean_spearman
value: 69.66114271982464
- type: manhattan_pearson
value: 73.07993034858605
- type: manhattan_spearman
value: 69.6457893357314
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 74.72893353272778
- type: cos_sim_spearman
value: 68.78540928870311
- type: euclidean_pearson
value: 71.13907970605574
- type: euclidean_spearman
value: 68.78540928870311
- type: manhattan_pearson
value: 71.02709590547859
- type: manhattan_spearman
value: 68.71685896660532
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 79.30142652684971
- type: cos_sim_spearman
value: 79.61879435615303
- type: euclidean_pearson
value: 79.08730432883864
- type: euclidean_spearman
value: 79.61879435615303
- type: manhattan_pearson
value: 78.99621073156322
- type: manhattan_spearman
value: 79.53806342308278
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 78.99585233036139
- type: cos_sim_spearman
value: 75.57574519760183
- type: euclidean_pearson
value: 77.33835658613162
- type: euclidean_spearman
value: 75.57573873503655
- type: manhattan_pearson
value: 77.12175044789362
- type: manhattan_spearman
value: 75.41293517634836
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 83.9694268253376
- type: cos_sim_spearman
value: 84.64256921939338
- type: euclidean_pearson
value: 83.92322958711
- type: euclidean_spearman
value: 84.64257976421872
- type: manhattan_pearson
value: 83.93503107204337
- type: manhattan_spearman
value: 84.63611608236032
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 81.09041419790253
- type: cos_sim_spearman
value: 82.39869157752557
- type: euclidean_pearson
value: 82.04595698258301
- type: euclidean_spearman
value: 82.39869157752557
- type: manhattan_pearson
value: 81.97581168053004
- type: manhattan_spearman
value: 82.34255320578193
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 86.35210432821825
- type: cos_sim_spearman
value: 86.73200885328937
- type: euclidean_pearson
value: 86.8527089168747
- type: euclidean_spearman
value: 86.73200885328937
- type: manhattan_pearson
value: 86.95671235295457
- type: manhattan_spearman
value: 86.77713700838545
- 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: 68.91106612960657
- type: cos_sim_spearman
value: 69.48524490302286
- type: euclidean_pearson
value: 70.51347841618035
- type: euclidean_spearman
value: 69.48524490302286
- type: manhattan_pearson
value: 70.31770181334245
- type: manhattan_spearman
value: 69.12494700138238
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 81.54104342761988
- type: cos_sim_spearman
value: 81.18789220331483
- type: euclidean_pearson
value: 81.5895544590969
- type: euclidean_spearman
value: 81.18789220331483
- type: manhattan_pearson
value: 81.4738562449809
- type: manhattan_spearman
value: 81.06565101416024
- 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: 81.54104346197056
- type: cos_sim_spearman
value: 81.18789220331483
- type: euclidean_pearson
value: 81.58955451690102
- type: euclidean_spearman
value: 81.18789220331483
- type: manhattan_pearson
value: 81.47385630064072
- type: manhattan_spearman
value: 81.06565101416024
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 79.34107964300796
- type: mrr
value: 94.01917889662987
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 55.928
- type: map_at_10
value: 65.443
- type: map_at_100
value: 66.067
- type: map_at_1000
value: 66.091
- type: map_at_3
value: 62.629999999999995
- type: map_at_5
value: 64.35
- type: mrr_at_1
value: 59
- type: mrr_at_10
value: 66.845
- type: mrr_at_100
value: 67.31899999999999
- type: mrr_at_1000
value: 67.342
- type: mrr_at_3
value: 64.61099999999999
- type: mrr_at_5
value: 66.044
- type: ndcg_at_1
value: 59
- type: ndcg_at_10
value: 69.921
- type: ndcg_at_100
value: 72.365
- type: ndcg_at_1000
value: 73.055
- type: ndcg_at_3
value: 65.086
- type: ndcg_at_5
value: 67.62700000000001
- type: precision_at_1
value: 59
- type: precision_at_10
value: 9.3
- type: precision_at_100
value: 1.057
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 25.333
- type: precision_at_5
value: 16.866999999999997
- type: recall_at_1
value: 55.928
- type: recall_at_10
value: 82.289
- type: recall_at_100
value: 92.833
- type: recall_at_1000
value: 98.333
- type: recall_at_3
value: 69.172
- type: recall_at_5
value: 75.628
- 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: 95.2776439040401
- type: cos_sim_f1
value: 90.74355083459787
- type: cos_sim_precision
value: 91.81166837256909
- type: cos_sim_recall
value: 89.7
- type: dot_accuracy
value: 99.81881188118813
- type: dot_ap
value: 95.27764092100406
- type: dot_f1
value: 90.74355083459787
- type: dot_precision
value: 91.81166837256909
- type: dot_recall
value: 89.7
- type: euclidean_accuracy
value: 99.81881188118813
- type: euclidean_ap
value: 95.27764091101388
- type: euclidean_f1
value: 90.74355083459787
- type: euclidean_precision
value: 91.81166837256909
- type: euclidean_recall
value: 89.7
- type: manhattan_accuracy
value: 99.82079207920792
- type: manhattan_ap
value: 95.25081634689418
- type: manhattan_f1
value: 90.75114971895759
- type: manhattan_precision
value: 92.78996865203762
- type: manhattan_recall
value: 88.8
- type: max_accuracy
value: 99.82079207920792
- type: max_ap
value: 95.2776439040401
- type: max_f1
value: 90.75114971895759
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 60.69855369728728
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.98191834367251
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 50.156163330429614
- type: mrr
value: 50.90145148968678
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.16938079808134
- type: cos_sim_spearman
value: 31.74655874538245
- type: dot_pearson
value: 31.169380299671705
- type: dot_spearman
value: 31.74655874538245
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.252
- type: map_at_10
value: 2.009
- type: map_at_100
value: 11.611
- type: map_at_1000
value: 27.811999999999998
- type: map_at_3
value: 0.685
- type: map_at_5
value: 1.08
- 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: 88
- type: ndcg_at_10
value: 81.388
- type: ndcg_at_100
value: 60.629
- type: ndcg_at_1000
value: 52.38
- type: ndcg_at_3
value: 86.827
- type: ndcg_at_5
value: 84.597
- type: precision_at_1
value: 94
- type: precision_at_10
value: 85.8
- type: precision_at_100
value: 62.419999999999995
- type: precision_at_1000
value: 23.31
- type: precision_at_3
value: 90.667
- type: precision_at_5
value: 88.4
- type: recall_at_1
value: 0.252
- type: recall_at_10
value: 2.164
- type: recall_at_100
value: 14.613999999999999
- type: recall_at_1000
value: 48.730000000000004
- type: recall_at_3
value: 0.7020000000000001
- type: recall_at_5
value: 1.122
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 3.476
- type: map_at_10
value: 13.442000000000002
- type: map_at_100
value: 20.618
- type: map_at_1000
value: 22.175
- type: map_at_3
value: 6.968000000000001
- type: map_at_5
value: 9.214
- type: mrr_at_1
value: 44.897999999999996
- type: mrr_at_10
value: 56.77100000000001
- type: mrr_at_100
value: 57.226
- type: mrr_at_1000
value: 57.226
- type: mrr_at_3
value: 52.381
- type: mrr_at_5
value: 54.523999999999994
- type: ndcg_at_1
value: 42.857
- type: ndcg_at_10
value: 32.507999999999996
- type: ndcg_at_100
value: 43.614000000000004
- type: ndcg_at_1000
value: 53.82
- type: ndcg_at_3
value: 36.818
- type: ndcg_at_5
value: 33.346
- type: precision_at_1
value: 44.897999999999996
- type: precision_at_10
value: 28.571
- type: precision_at_100
value: 8.652999999999999
- type: precision_at_1000
value: 1.5709999999999997
- type: precision_at_3
value: 38.095
- type: precision_at_5
value: 32.245000000000005
- type: recall_at_1
value: 3.476
- type: recall_at_10
value: 20.827
- type: recall_at_100
value: 53.04299999999999
- type: recall_at_1000
value: 84.221
- type: recall_at_3
value: 8.200000000000001
- type: recall_at_5
value: 11.651
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 61.96360000000001
- type: ap
value: 11.256160324436445
- type: f1
value: 48.07712827691349
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 58.90492359932088
- type: f1
value: 59.12542417513503
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 38.284935353315355
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.4714192048638
- type: cos_sim_ap
value: 65.77588263185375
- type: cos_sim_f1
value: 62.459508098380326
- type: cos_sim_precision
value: 57.27172717271727
- type: cos_sim_recall
value: 68.68073878627968
- type: dot_accuracy
value: 83.4714192048638
- type: dot_ap
value: 65.77588818364636
- type: dot_f1
value: 62.459508098380326
- type: dot_precision
value: 57.27172717271727
- type: dot_recall
value: 68.68073878627968
- type: euclidean_accuracy
value: 83.4714192048638
- type: euclidean_ap
value: 65.77587693431595
- type: euclidean_f1
value: 62.459508098380326
- type: euclidean_precision
value: 57.27172717271727
- type: euclidean_recall
value: 68.68073878627968
- type: manhattan_accuracy
value: 83.47737974608094
- type: manhattan_ap
value: 65.65957745829654
- type: manhattan_f1
value: 62.22760290556902
- type: manhattan_precision
value: 57.494407158836694
- type: manhattan_recall
value: 67.81002638522428
- type: max_accuracy
value: 83.47737974608094
- type: max_ap
value: 65.77588818364636
- type: max_f1
value: 62.459508098380326
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.64244964489463
- type: cos_sim_ap
value: 85.154122301394
- type: cos_sim_f1
value: 77.45617911327146
- type: cos_sim_precision
value: 74.23066064370413
- type: cos_sim_recall
value: 80.97474591931014
- type: dot_accuracy
value: 88.64244964489463
- type: dot_ap
value: 85.15411965587543
- type: dot_f1
value: 77.45617911327146
- type: dot_precision
value: 74.23066064370413
- type: dot_recall
value: 80.97474591931014
- type: euclidean_accuracy
value: 88.64244964489463
- type: euclidean_ap
value: 85.15414684113986
- type: euclidean_f1
value: 77.45617911327146
- type: euclidean_precision
value: 74.23066064370413
- type: euclidean_recall
value: 80.97474591931014
- type: manhattan_accuracy
value: 88.57841425078588
- type: manhattan_ap
value: 85.12472268567576
- type: manhattan_f1
value: 77.39497339937627
- type: manhattan_precision
value: 73.92584285413892
- type: manhattan_recall
value: 81.20572836464429
- type: max_accuracy
value: 88.64244964489463
- type: max_ap
value: 85.15414684113986
- type: max_f1
value: 77.45617911327146
- task:
type: Clustering
dataset:
type: jinaai/cities_wiki_clustering
name: MTEB WikiCitiesClustering
config: default
split: test
revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
metrics:
- type: v_measure
value: 79.58576208710117