metadata
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- feature-extraction
- sentence-similarity
- mteb
- transformers
- transformers.js
license: apache-2.0
language:
- en
inference: false
model-index:
- name: epoch_0_model
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 76.98507462686568
- type: ap
value: 39.47222193126652
- type: f1
value: 70.5923611893019
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 87.540175
- type: ap
value: 83.16128207188409
- type: f1
value: 87.5231988227265
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 46.80799999999999
- type: f1
value: 46.2632547445265
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.583
- type: map_at_10
value: 46.17
- type: map_at_100
value: 47.115
- type: map_at_1000
value: 47.121
- type: map_at_3
value: 41.489
- type: map_at_5
value: 44.046
- type: mrr_at_1
value: 30.939
- type: mrr_at_10
value: 46.289
- type: mrr_at_100
value: 47.241
- type: mrr_at_1000
value: 47.247
- type: mrr_at_3
value: 41.596
- type: mrr_at_5
value: 44.149
- type: ndcg_at_1
value: 30.583
- type: ndcg_at_10
value: 54.812000000000005
- type: ndcg_at_100
value: 58.605
- type: ndcg_at_1000
value: 58.753
- type: ndcg_at_3
value: 45.095
- type: ndcg_at_5
value: 49.744
- type: precision_at_1
value: 30.583
- type: precision_at_10
value: 8.243
- type: precision_at_100
value: 0.984
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 18.516
- type: precision_at_5
value: 13.385
- type: recall_at_1
value: 30.583
- type: recall_at_10
value: 82.432
- type: recall_at_100
value: 98.43499999999999
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 55.547999999999995
- type: recall_at_5
value: 66.927
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 45.17830107652425
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 35.90561364087807
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 59.57222651819297
- type: mrr
value: 73.19241085169062
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 89.55181686367382
- type: cos_sim_spearman
value: 87.18933606575987
- type: euclidean_pearson
value: 87.78077503434338
- type: euclidean_spearman
value: 87.18933606575987
- type: manhattan_pearson
value: 87.75124980168601
- type: manhattan_spearman
value: 86.79113422137638
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.09415584415585
- type: f1
value: 80.60088693212091
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 36.57061229905462
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 32.05342946608653
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 34.376
- type: map_at_10
value: 45.214
- type: map_at_100
value: 46.635
- type: map_at_1000
value: 46.755
- type: map_at_3
value: 42.198
- type: map_at_5
value: 43.723
- type: mrr_at_1
value: 41.774
- type: mrr_at_10
value: 51.07000000000001
- type: mrr_at_100
value: 51.785000000000004
- type: mrr_at_1000
value: 51.824999999999996
- type: mrr_at_3
value: 48.808
- type: mrr_at_5
value: 50.11
- type: ndcg_at_1
value: 41.774
- type: ndcg_at_10
value: 51.105999999999995
- type: ndcg_at_100
value: 56.358
- type: ndcg_at_1000
value: 58.205
- type: ndcg_at_3
value: 46.965
- type: ndcg_at_5
value: 48.599
- type: precision_at_1
value: 41.774
- type: precision_at_10
value: 9.514
- type: precision_at_100
value: 1.508
- type: precision_at_1000
value: 0.196
- type: precision_at_3
value: 22.175
- type: precision_at_5
value: 15.508
- type: recall_at_1
value: 34.376
- type: recall_at_10
value: 61.748000000000005
- type: recall_at_100
value: 84.025
- type: recall_at_1000
value: 95.5
- type: recall_at_3
value: 49.378
- type: recall_at_5
value: 54.276
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.394
- type: map_at_10
value: 42.707
- type: map_at_100
value: 43.893
- type: map_at_1000
value: 44.019000000000005
- type: map_at_3
value: 39.51
- type: map_at_5
value: 41.381
- type: mrr_at_1
value: 41.019
- type: mrr_at_10
value: 49.042
- type: mrr_at_100
value: 49.669000000000004
- type: mrr_at_1000
value: 49.712
- type: mrr_at_3
value: 46.921
- type: mrr_at_5
value: 48.192
- type: ndcg_at_1
value: 41.019
- type: ndcg_at_10
value: 48.46
- type: ndcg_at_100
value: 52.537
- type: ndcg_at_1000
value: 54.491
- type: ndcg_at_3
value: 44.232
- type: ndcg_at_5
value: 46.305
- type: precision_at_1
value: 41.019
- type: precision_at_10
value: 9.134
- type: precision_at_100
value: 1.422
- type: precision_at_1000
value: 0.188
- type: precision_at_3
value: 21.38
- type: precision_at_5
value: 15.096000000000002
- type: recall_at_1
value: 32.394
- type: recall_at_10
value: 58.11500000000001
- type: recall_at_100
value: 75.509
- type: recall_at_1000
value: 87.812
- type: recall_at_3
value: 45.476
- type: recall_at_5
value: 51.549
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 43.47
- type: map_at_10
value: 55.871
- type: map_at_100
value: 56.745000000000005
- type: map_at_1000
value: 56.794
- type: map_at_3
value: 52.439
- type: map_at_5
value: 54.412000000000006
- type: mrr_at_1
value: 49.592000000000006
- type: mrr_at_10
value: 59.34199999999999
- type: mrr_at_100
value: 59.857000000000006
- type: mrr_at_1000
value: 59.88
- type: mrr_at_3
value: 56.897
- type: mrr_at_5
value: 58.339
- type: ndcg_at_1
value: 49.592000000000006
- type: ndcg_at_10
value: 61.67
- type: ndcg_at_100
value: 65.11099999999999
- type: ndcg_at_1000
value: 66.065
- type: ndcg_at_3
value: 56.071000000000005
- type: ndcg_at_5
value: 58.84700000000001
- type: precision_at_1
value: 49.592000000000006
- type: precision_at_10
value: 9.774
- type: precision_at_100
value: 1.2449999999999999
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 24.66
- type: precision_at_5
value: 16.878
- type: recall_at_1
value: 43.47
- type: recall_at_10
value: 75.387
- type: recall_at_100
value: 90.253
- type: recall_at_1000
value: 97.00800000000001
- type: recall_at_3
value: 60.616
- type: recall_at_5
value: 67.31899999999999
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.633000000000003
- type: map_at_10
value: 35.497
- type: map_at_100
value: 36.504
- type: map_at_1000
value: 36.574
- type: map_at_3
value: 33.115
- type: map_at_5
value: 34.536
- type: mrr_at_1
value: 28.927000000000003
- type: mrr_at_10
value: 37.778
- type: mrr_at_100
value: 38.634
- type: mrr_at_1000
value: 38.690000000000005
- type: mrr_at_3
value: 35.518
- type: mrr_at_5
value: 36.908
- type: ndcg_at_1
value: 28.927000000000003
- type: ndcg_at_10
value: 40.327
- type: ndcg_at_100
value: 45.321
- type: ndcg_at_1000
value: 47.214
- type: ndcg_at_3
value: 35.762
- type: ndcg_at_5
value: 38.153999999999996
- type: precision_at_1
value: 28.927000000000003
- type: precision_at_10
value: 6.045
- type: precision_at_100
value: 0.901
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 15.140999999999998
- type: precision_at_5
value: 10.485999999999999
- type: recall_at_1
value: 26.633000000000003
- type: recall_at_10
value: 52.99
- type: recall_at_100
value: 76.086
- type: recall_at_1000
value: 90.46300000000001
- type: recall_at_3
value: 40.738
- type: recall_at_5
value: 46.449
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.521
- type: map_at_10
value: 25.130000000000003
- type: map_at_100
value: 26.176
- type: map_at_1000
value: 26.289
- type: map_at_3
value: 22.829
- type: map_at_5
value: 24.082
- type: mrr_at_1
value: 21.766
- type: mrr_at_10
value: 29.801
- type: mrr_at_100
value: 30.682
- type: mrr_at_1000
value: 30.75
- type: mrr_at_3
value: 27.633000000000003
- type: mrr_at_5
value: 28.858
- type: ndcg_at_1
value: 21.766
- type: ndcg_at_10
value: 30.026000000000003
- type: ndcg_at_100
value: 35.429
- type: ndcg_at_1000
value: 38.236
- type: ndcg_at_3
value: 25.968000000000004
- type: ndcg_at_5
value: 27.785
- type: precision_at_1
value: 21.766
- type: precision_at_10
value: 5.498
- type: precision_at_100
value: 0.9450000000000001
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 12.687000000000001
- type: precision_at_5
value: 9.005
- type: recall_at_1
value: 17.521
- type: recall_at_10
value: 40.454
- type: recall_at_100
value: 64.828
- type: recall_at_1000
value: 84.83800000000001
- type: recall_at_3
value: 28.758
- type: recall_at_5
value: 33.617000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.564999999999998
- type: map_at_10
value: 40.664
- type: map_at_100
value: 41.995
- type: map_at_1000
value: 42.104
- type: map_at_3
value: 37.578
- type: map_at_5
value: 39.247
- type: mrr_at_1
value: 37.44
- type: mrr_at_10
value: 46.533
- type: mrr_at_100
value: 47.363
- type: mrr_at_1000
value: 47.405
- type: mrr_at_3
value: 44.224999999999994
- type: mrr_at_5
value: 45.549
- type: ndcg_at_1
value: 37.44
- type: ndcg_at_10
value: 46.574
- type: ndcg_at_100
value: 52.024
- type: ndcg_at_1000
value: 53.93900000000001
- type: ndcg_at_3
value: 41.722
- type: ndcg_at_5
value: 43.973
- type: precision_at_1
value: 37.44
- type: precision_at_10
value: 8.344999999999999
- type: precision_at_100
value: 1.278
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 19.442
- type: precision_at_5
value: 13.802
- type: recall_at_1
value: 30.564999999999998
- type: recall_at_10
value: 58.207
- type: recall_at_100
value: 81.137
- type: recall_at_1000
value: 93.506
- type: recall_at_3
value: 44.606
- type: recall_at_5
value: 50.373000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.892
- type: map_at_10
value: 37.251
- type: map_at_100
value: 38.606
- type: map_at_1000
value: 38.716
- type: map_at_3
value: 34.312
- type: map_at_5
value: 35.791000000000004
- type: mrr_at_1
value: 34.247
- type: mrr_at_10
value: 42.696
- type: mrr_at_100
value: 43.659
- type: mrr_at_1000
value: 43.711
- type: mrr_at_3
value: 40.563
- type: mrr_at_5
value: 41.625
- type: ndcg_at_1
value: 34.247
- type: ndcg_at_10
value: 42.709
- type: ndcg_at_100
value: 48.422
- type: ndcg_at_1000
value: 50.544
- type: ndcg_at_3
value: 38.105
- type: ndcg_at_5
value: 39.846
- type: precision_at_1
value: 34.247
- type: precision_at_10
value: 7.66
- type: precision_at_100
value: 1.2109999999999999
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 17.884
- type: precision_at_5
value: 12.489
- type: recall_at_1
value: 27.892
- type: recall_at_10
value: 53.559
- type: recall_at_100
value: 78.018
- type: recall_at_1000
value: 92.07300000000001
- type: recall_at_3
value: 40.154
- type: recall_at_5
value: 45.078
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.29375
- type: map_at_10
value: 36.19533333333334
- type: map_at_100
value: 37.33183333333334
- type: map_at_1000
value: 37.44616666666667
- type: map_at_3
value: 33.49125
- type: map_at_5
value: 34.94166666666667
- type: mrr_at_1
value: 32.336666666666666
- type: mrr_at_10
value: 40.45983333333333
- type: mrr_at_100
value: 41.26533333333334
- type: mrr_at_1000
value: 41.321583333333336
- type: mrr_at_3
value: 38.23416666666667
- type: mrr_at_5
value: 39.48491666666666
- type: ndcg_at_1
value: 32.336666666666666
- type: ndcg_at_10
value: 41.39958333333333
- type: ndcg_at_100
value: 46.293
- type: ndcg_at_1000
value: 48.53425
- type: ndcg_at_3
value: 36.88833333333333
- type: ndcg_at_5
value: 38.90733333333333
- type: precision_at_1
value: 32.336666666666666
- type: precision_at_10
value: 7.175916666666667
- type: precision_at_100
value: 1.1311666666666669
- type: precision_at_1000
value: 0.15141666666666667
- type: precision_at_3
value: 16.841166666666666
- type: precision_at_5
value: 11.796583333333334
- type: recall_at_1
value: 27.29375
- type: recall_at_10
value: 52.514583333333334
- type: recall_at_100
value: 74.128
- type: recall_at_1000
value: 89.64125
- type: recall_at_3
value: 39.83258333333333
- type: recall_at_5
value: 45.126416666666664
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.62
- type: map_at_10
value: 31.517
- type: map_at_100
value: 32.322
- type: map_at_1000
value: 32.422000000000004
- type: map_at_3
value: 29.293999999999997
- type: map_at_5
value: 30.403999999999996
- type: mrr_at_1
value: 27.607
- type: mrr_at_10
value: 34.294999999999995
- type: mrr_at_100
value: 35.045
- type: mrr_at_1000
value: 35.114000000000004
- type: mrr_at_3
value: 32.311
- type: mrr_at_5
value: 33.369
- type: ndcg_at_1
value: 27.607
- type: ndcg_at_10
value: 35.853
- type: ndcg_at_100
value: 39.919
- type: ndcg_at_1000
value: 42.452
- type: ndcg_at_3
value: 31.702
- type: ndcg_at_5
value: 33.47
- type: precision_at_1
value: 27.607
- type: precision_at_10
value: 5.598
- type: precision_at_100
value: 0.83
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 13.700999999999999
- type: precision_at_5
value: 9.325
- type: recall_at_1
value: 24.62
- type: recall_at_10
value: 46.475
- type: recall_at_100
value: 64.891
- type: recall_at_1000
value: 83.524
- type: recall_at_3
value: 34.954
- type: recall_at_5
value: 39.471000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.858999999999998
- type: map_at_10
value: 23.746000000000002
- type: map_at_100
value: 24.731
- type: map_at_1000
value: 24.86
- type: map_at_3
value: 21.603
- type: map_at_5
value: 22.811999999999998
- type: mrr_at_1
value: 20.578
- type: mrr_at_10
value: 27.618
- type: mrr_at_100
value: 28.459
- type: mrr_at_1000
value: 28.543000000000003
- type: mrr_at_3
value: 25.533
- type: mrr_at_5
value: 26.730999999999998
- type: ndcg_at_1
value: 20.578
- type: ndcg_at_10
value: 28.147
- type: ndcg_at_100
value: 32.946999999999996
- type: ndcg_at_1000
value: 36.048
- type: ndcg_at_3
value: 24.32
- type: ndcg_at_5
value: 26.131999999999998
- type: precision_at_1
value: 20.578
- type: precision_at_10
value: 5.061999999999999
- type: precision_at_100
value: 0.8789999999999999
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 11.448
- type: precision_at_5
value: 8.251999999999999
- type: recall_at_1
value: 16.858999999999998
- type: recall_at_10
value: 37.565
- type: recall_at_100
value: 59.239
- type: recall_at_1000
value: 81.496
- type: recall_at_3
value: 26.865
- type: recall_at_5
value: 31.581
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.11
- type: map_at_10
value: 34.214
- type: map_at_100
value: 35.291
- type: map_at_1000
value: 35.400999999999996
- type: map_at_3
value: 31.541000000000004
- type: map_at_5
value: 33.21
- type: mrr_at_1
value: 30.97
- type: mrr_at_10
value: 38.522
- type: mrr_at_100
value: 39.37
- type: mrr_at_1000
value: 39.437
- type: mrr_at_3
value: 36.193999999999996
- type: mrr_at_5
value: 37.691
- type: ndcg_at_1
value: 30.97
- type: ndcg_at_10
value: 39.2
- type: ndcg_at_100
value: 44.267
- type: ndcg_at_1000
value: 46.760000000000005
- type: ndcg_at_3
value: 34.474
- type: ndcg_at_5
value: 37.016
- type: precision_at_1
value: 30.97
- type: precision_at_10
value: 6.521000000000001
- type: precision_at_100
value: 1.011
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 15.392
- type: precision_at_5
value: 11.026
- type: recall_at_1
value: 26.11
- type: recall_at_10
value: 50.14999999999999
- type: recall_at_100
value: 72.398
- type: recall_at_1000
value: 89.764
- type: recall_at_3
value: 37.352999999999994
- type: recall_at_5
value: 43.736000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.514
- type: map_at_10
value: 34.278999999999996
- type: map_at_100
value: 35.847
- type: map_at_1000
value: 36.086
- type: map_at_3
value: 31.563999999999997
- type: map_at_5
value: 32.903999999999996
- type: mrr_at_1
value: 30.830000000000002
- type: mrr_at_10
value: 38.719
- type: mrr_at_100
value: 39.678999999999995
- type: mrr_at_1000
value: 39.741
- type: mrr_at_3
value: 36.265
- type: mrr_at_5
value: 37.599
- type: ndcg_at_1
value: 30.830000000000002
- type: ndcg_at_10
value: 39.997
- type: ndcg_at_100
value: 45.537
- type: ndcg_at_1000
value: 48.296
- type: ndcg_at_3
value: 35.429
- type: ndcg_at_5
value: 37.3
- type: precision_at_1
value: 30.830000000000002
- type: precision_at_10
value: 7.747
- type: precision_at_100
value: 1.516
- type: precision_at_1000
value: 0.24
- type: precision_at_3
value: 16.601
- type: precision_at_5
value: 11.818
- type: recall_at_1
value: 25.514
- type: recall_at_10
value: 50.71600000000001
- type: recall_at_100
value: 75.40299999999999
- type: recall_at_1000
value: 93.10300000000001
- type: recall_at_3
value: 37.466
- type: recall_at_5
value: 42.677
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.571
- type: map_at_10
value: 28.254
- type: map_at_100
value: 29.237000000000002
- type: map_at_1000
value: 29.334
- type: map_at_3
value: 25.912000000000003
- type: map_at_5
value: 26.798
- type: mrr_at_1
value: 23.29
- type: mrr_at_10
value: 30.102
- type: mrr_at_100
value: 30.982
- type: mrr_at_1000
value: 31.051000000000002
- type: mrr_at_3
value: 27.942
- type: mrr_at_5
value: 28.848000000000003
- type: ndcg_at_1
value: 23.29
- type: ndcg_at_10
value: 32.726
- type: ndcg_at_100
value: 37.644
- type: ndcg_at_1000
value: 40.161
- type: ndcg_at_3
value: 27.91
- type: ndcg_at_5
value: 29.461
- type: precision_at_1
value: 23.29
- type: precision_at_10
value: 5.213
- type: precision_at_100
value: 0.828
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 11.583
- type: precision_at_5
value: 7.8740000000000006
- type: recall_at_1
value: 21.571
- type: recall_at_10
value: 44.809
- type: recall_at_100
value: 67.74900000000001
- type: recall_at_1000
value: 86.60799999999999
- type: recall_at_3
value: 31.627
- type: recall_at_5
value: 35.391
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.953
- type: map_at_10
value: 17.183
- type: map_at_100
value: 18.926000000000002
- type: map_at_1000
value: 19.105
- type: map_at_3
value: 14.308000000000002
- type: map_at_5
value: 15.738
- type: mrr_at_1
value: 22.02
- type: mrr_at_10
value: 33.181
- type: mrr_at_100
value: 34.357
- type: mrr_at_1000
value: 34.398
- type: mrr_at_3
value: 29.793999999999997
- type: mrr_at_5
value: 31.817
- type: ndcg_at_1
value: 22.02
- type: ndcg_at_10
value: 24.712
- type: ndcg_at_100
value: 32.025
- type: ndcg_at_1000
value: 35.437000000000005
- type: ndcg_at_3
value: 19.852
- type: ndcg_at_5
value: 21.565
- type: precision_at_1
value: 22.02
- type: precision_at_10
value: 7.779
- type: precision_at_100
value: 1.554
- type: precision_at_1000
value: 0.219
- type: precision_at_3
value: 14.832
- type: precision_at_5
value: 11.453000000000001
- type: recall_at_1
value: 9.953
- type: recall_at_10
value: 30.375000000000004
- type: recall_at_100
value: 55.737
- type: recall_at_1000
value: 75.071
- type: recall_at_3
value: 18.529999999999998
- type: recall_at_5
value: 23.313
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.651
- type: map_at_10
value: 19.674
- type: map_at_100
value: 27.855999999999998
- type: map_at_1000
value: 29.348000000000003
- type: map_at_3
value: 14.247000000000002
- type: map_at_5
value: 16.453
- type: mrr_at_1
value: 61.75000000000001
- type: mrr_at_10
value: 71.329
- type: mrr_at_100
value: 71.69200000000001
- type: mrr_at_1000
value: 71.699
- type: mrr_at_3
value: 69.042
- type: mrr_at_5
value: 70.679
- type: ndcg_at_1
value: 50.125
- type: ndcg_at_10
value: 40.199
- type: ndcg_at_100
value: 45.378
- type: ndcg_at_1000
value: 52.376999999999995
- type: ndcg_at_3
value: 44.342
- type: ndcg_at_5
value: 41.730000000000004
- type: precision_at_1
value: 61.75000000000001
- type: precision_at_10
value: 32.2
- type: precision_at_100
value: 10.298
- type: precision_at_1000
value: 1.984
- type: precision_at_3
value: 48.667
- type: precision_at_5
value: 40.5
- type: recall_at_1
value: 8.651
- type: recall_at_10
value: 25.607000000000003
- type: recall_at_100
value: 53.062
- type: recall_at_1000
value: 74.717
- type: recall_at_3
value: 15.661
- type: recall_at_5
value: 19.409000000000002
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 47.64500000000001
- type: f1
value: 43.71011316507787
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 54.613
- type: map_at_10
value: 68.02
- type: map_at_100
value: 68.366
- type: map_at_1000
value: 68.379
- type: map_at_3
value: 65.753
- type: map_at_5
value: 67.242
- type: mrr_at_1
value: 59.001000000000005
- type: mrr_at_10
value: 72.318
- type: mrr_at_100
value: 72.558
- type: mrr_at_1000
value: 72.56099999999999
- type: mrr_at_3
value: 70.22699999999999
- type: mrr_at_5
value: 71.655
- type: ndcg_at_1
value: 59.001000000000005
- type: ndcg_at_10
value: 74.386
- type: ndcg_at_100
value: 75.763
- type: ndcg_at_1000
value: 76.03
- type: ndcg_at_3
value: 70.216
- type: ndcg_at_5
value: 72.697
- type: precision_at_1
value: 59.001000000000005
- type: precision_at_10
value: 9.844
- type: precision_at_100
value: 1.068
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 28.523
- type: precision_at_5
value: 18.491
- type: recall_at_1
value: 54.613
- type: recall_at_10
value: 89.669
- type: recall_at_100
value: 95.387
- type: recall_at_1000
value: 97.129
- type: recall_at_3
value: 78.54100000000001
- type: recall_at_5
value: 84.637
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.348
- type: map_at_10
value: 32.464999999999996
- type: map_at_100
value: 34.235
- type: map_at_1000
value: 34.410000000000004
- type: map_at_3
value: 28.109
- type: map_at_5
value: 30.634
- type: mrr_at_1
value: 38.889
- type: mrr_at_10
value: 47.131
- type: mrr_at_100
value: 48.107
- type: mrr_at_1000
value: 48.138
- type: mrr_at_3
value: 44.599
- type: mrr_at_5
value: 46.181
- type: ndcg_at_1
value: 38.889
- type: ndcg_at_10
value: 39.86
- type: ndcg_at_100
value: 46.619
- type: ndcg_at_1000
value: 49.525999999999996
- type: ndcg_at_3
value: 35.768
- type: ndcg_at_5
value: 37.4
- type: precision_at_1
value: 38.889
- type: precision_at_10
value: 11.003
- type: precision_at_100
value: 1.796
- type: precision_at_1000
value: 0.233
- type: precision_at_3
value: 23.714
- type: precision_at_5
value: 17.901
- type: recall_at_1
value: 20.348
- type: recall_at_10
value: 46.781
- type: recall_at_100
value: 71.937
- type: recall_at_1000
value: 89.18599999999999
- type: recall_at_3
value: 32.16
- type: recall_at_5
value: 38.81
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.198
- type: map_at_10
value: 54.065
- type: map_at_100
value: 54.984
- type: map_at_1000
value: 55.05
- type: map_at_3
value: 50.758
- type: map_at_5
value: 52.758
- type: mrr_at_1
value: 74.396
- type: mrr_at_10
value: 81.352
- type: mrr_at_100
value: 81.562
- type: mrr_at_1000
value: 81.57
- type: mrr_at_3
value: 80.30199999999999
- type: mrr_at_5
value: 80.963
- type: ndcg_at_1
value: 74.396
- type: ndcg_at_10
value: 63.70099999999999
- type: ndcg_at_100
value: 66.874
- type: ndcg_at_1000
value: 68.171
- type: ndcg_at_3
value: 58.916999999999994
- type: ndcg_at_5
value: 61.495999999999995
- type: precision_at_1
value: 74.396
- type: precision_at_10
value: 13.228000000000002
- type: precision_at_100
value: 1.569
- type: precision_at_1000
value: 0.174
- type: precision_at_3
value: 37.007
- type: precision_at_5
value: 24.248
- type: recall_at_1
value: 37.198
- type: recall_at_10
value: 66.13799999999999
- type: recall_at_100
value: 78.45400000000001
- type: recall_at_1000
value: 87.04899999999999
- type: recall_at_3
value: 55.510000000000005
- type: recall_at_5
value: 60.621
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 86.32240000000002
- type: ap
value: 81.37708984744188
- type: f1
value: 86.29645005523952
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 16.402
- type: map_at_10
value: 28.097
- type: map_at_100
value: 29.421999999999997
- type: map_at_1000
value: 29.476999999999997
- type: map_at_3
value: 24.015
- type: map_at_5
value: 26.316
- type: mrr_at_1
value: 16.905
- type: mrr_at_10
value: 28.573999999999998
- type: mrr_at_100
value: 29.862
- type: mrr_at_1000
value: 29.912
- type: mrr_at_3
value: 24.589
- type: mrr_at_5
value: 26.851000000000003
- type: ndcg_at_1
value: 16.905
- type: ndcg_at_10
value: 34.99
- type: ndcg_at_100
value: 41.419
- type: ndcg_at_1000
value: 42.815999999999995
- type: ndcg_at_3
value: 26.695
- type: ndcg_at_5
value: 30.789
- type: precision_at_1
value: 16.905
- type: precision_at_10
value: 5.891
- type: precision_at_100
value: 0.91
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 11.724
- type: precision_at_5
value: 9.097
- type: recall_at_1
value: 16.402
- type: recall_at_10
value: 56.462999999999994
- type: recall_at_100
value: 86.246
- type: recall_at_1000
value: 96.926
- type: recall_at_3
value: 33.897
- type: recall_at_5
value: 43.718
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 92.35978112175103
- type: f1
value: 92.04704651024416
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 65.20063839489283
- type: f1
value: 45.34047546059121
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 67.74714189643578
- type: f1
value: 65.36156843270334
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 74.03160726294554
- type: f1
value: 73.42899064973165
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.347360980344476
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 29.56022733162805
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.60132765358296
- type: mrr
value: 31.710892632824468
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.827999999999999
- type: map_at_10
value: 13.547
- type: map_at_100
value: 16.869
- type: map_at_1000
value: 18.242
- type: map_at_3
value: 9.917
- type: map_at_5
value: 11.648
- type: mrr_at_1
value: 46.44
- type: mrr_at_10
value: 55.062
- type: mrr_at_100
value: 55.513999999999996
- type: mrr_at_1000
value: 55.564
- type: mrr_at_3
value: 52.735
- type: mrr_at_5
value: 54.391
- type: ndcg_at_1
value: 44.582
- type: ndcg_at_10
value: 35.684
- type: ndcg_at_100
value: 31.913999999999998
- type: ndcg_at_1000
value: 40.701
- type: ndcg_at_3
value: 40.819
- type: ndcg_at_5
value: 39.117000000000004
- type: precision_at_1
value: 46.129999999999995
- type: precision_at_10
value: 26.687
- type: precision_at_100
value: 8.062
- type: precision_at_1000
value: 2.073
- type: precision_at_3
value: 38.493
- type: precision_at_5
value: 34.241
- type: recall_at_1
value: 5.827999999999999
- type: recall_at_10
value: 17.391000000000002
- type: recall_at_100
value: 31.228
- type: recall_at_1000
value: 63.943000000000005
- type: recall_at_3
value: 10.81
- type: recall_at_5
value: 13.618
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.02
- type: map_at_10
value: 40.054
- type: map_at_100
value: 41.318
- type: map_at_1000
value: 41.343999999999994
- type: map_at_3
value: 35.221999999999994
- type: map_at_5
value: 38.057
- type: mrr_at_1
value: 27.230999999999998
- type: mrr_at_10
value: 42.315999999999995
- type: mrr_at_100
value: 43.254
- type: mrr_at_1000
value: 43.272
- type: mrr_at_3
value: 38.176
- type: mrr_at_5
value: 40.64
- type: ndcg_at_1
value: 27.230999999999998
- type: ndcg_at_10
value: 48.551
- type: ndcg_at_100
value: 53.737
- type: ndcg_at_1000
value: 54.313
- type: ndcg_at_3
value: 39.367999999999995
- type: ndcg_at_5
value: 44.128
- type: precision_at_1
value: 27.230999999999998
- type: precision_at_10
value: 8.578
- type: precision_at_100
value: 1.145
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 18.704
- type: precision_at_5
value: 13.927999999999999
- type: recall_at_1
value: 24.02
- type: recall_at_10
value: 72.258
- type: recall_at_100
value: 94.489
- type: recall_at_1000
value: 98.721
- type: recall_at_3
value: 48.373
- type: recall_at_5
value: 59.388
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 70.476
- type: map_at_10
value: 84.41300000000001
- type: map_at_100
value: 85.036
- type: map_at_1000
value: 85.055
- type: map_at_3
value: 81.45599999999999
- type: map_at_5
value: 83.351
- type: mrr_at_1
value: 81.07
- type: mrr_at_10
value: 87.408
- type: mrr_at_100
value: 87.509
- type: mrr_at_1000
value: 87.51
- type: mrr_at_3
value: 86.432
- type: mrr_at_5
value: 87.128
- type: ndcg_at_1
value: 81.13
- type: ndcg_at_10
value: 88.18599999999999
- type: ndcg_at_100
value: 89.401
- type: ndcg_at_1000
value: 89.515
- type: ndcg_at_3
value: 85.332
- type: ndcg_at_5
value: 86.97
- type: precision_at_1
value: 81.13
- type: precision_at_10
value: 13.361
- type: precision_at_100
value: 1.5230000000000001
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 37.31
- type: precision_at_5
value: 24.548000000000002
- type: recall_at_1
value: 70.476
- type: recall_at_10
value: 95.3
- type: recall_at_100
value: 99.46000000000001
- type: recall_at_1000
value: 99.96000000000001
- type: recall_at_3
value: 87.057
- type: recall_at_5
value: 91.739
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 55.36775089400664
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 60.05041008018361
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.743
- type: map_at_10
value: 12.171
- type: map_at_100
value: 14.174999999999999
- type: map_at_1000
value: 14.446
- type: map_at_3
value: 8.698
- type: map_at_5
value: 10.444
- type: mrr_at_1
value: 23.400000000000002
- type: mrr_at_10
value: 34.284
- type: mrr_at_100
value: 35.400999999999996
- type: mrr_at_1000
value: 35.451
- type: mrr_at_3
value: 31.167
- type: mrr_at_5
value: 32.946999999999996
- type: ndcg_at_1
value: 23.400000000000002
- type: ndcg_at_10
value: 20.169999999999998
- type: ndcg_at_100
value: 27.967
- type: ndcg_at_1000
value: 32.982
- type: ndcg_at_3
value: 19.308
- type: ndcg_at_5
value: 16.837
- type: precision_at_1
value: 23.400000000000002
- type: precision_at_10
value: 10.41
- type: precision_at_100
value: 2.162
- type: precision_at_1000
value: 0.338
- type: precision_at_3
value: 18.067
- type: precision_at_5
value: 14.78
- type: recall_at_1
value: 4.743
- type: recall_at_10
value: 21.098
- type: recall_at_100
value: 43.85
- type: recall_at_1000
value: 68.60000000000001
- type: recall_at_3
value: 10.993
- type: recall_at_5
value: 14.998000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 81.129376905658
- type: cos_sim_spearman
value: 74.18938626206575
- type: euclidean_pearson
value: 77.95192851803141
- type: euclidean_spearman
value: 74.18938626206575
- type: manhattan_pearson
value: 77.97718819383338
- type: manhattan_spearman
value: 74.20580317409417
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 78.36913772828827
- type: cos_sim_spearman
value: 73.22311186990363
- type: euclidean_pearson
value: 74.45263405031004
- type: euclidean_spearman
value: 73.22311186990363
- type: manhattan_pearson
value: 74.56201270071791
- type: manhattan_spearman
value: 73.26490493774821
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 84.79920796384403
- type: cos_sim_spearman
value: 84.77145185366201
- type: euclidean_pearson
value: 83.90638366191354
- type: euclidean_spearman
value: 84.77145185366201
- type: manhattan_pearson
value: 83.83788216629048
- type: manhattan_spearman
value: 84.70515987131665
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 83.18883765092875
- type: cos_sim_spearman
value: 79.9948128016449
- type: euclidean_pearson
value: 81.57436738666773
- type: euclidean_spearman
value: 79.9948128016449
- type: manhattan_pearson
value: 81.55274202648187
- type: manhattan_spearman
value: 79.99854975019382
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 86.89669110871021
- type: cos_sim_spearman
value: 87.26758456901442
- type: euclidean_pearson
value: 86.62614163641416
- type: euclidean_spearman
value: 87.26758456901442
- type: manhattan_pearson
value: 86.58584490012353
- type: manhattan_spearman
value: 87.20340001562076
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 81.983023415916
- type: cos_sim_spearman
value: 82.31169002657151
- type: euclidean_pearson
value: 81.52305092886222
- type: euclidean_spearman
value: 82.31169002657151
- type: manhattan_pearson
value: 81.63024996600281
- type: manhattan_spearman
value: 82.44579116264026
- 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: 89.27779520541694
- type: cos_sim_spearman
value: 89.54137104681308
- type: euclidean_pearson
value: 88.99136079955996
- type: euclidean_spearman
value: 89.54137104681308
- type: manhattan_pearson
value: 88.95980417618277
- type: manhattan_spearman
value: 89.55178819334718
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 66.50806758829178
- type: cos_sim_spearman
value: 65.92675365587571
- type: euclidean_pearson
value: 67.09216876696559
- type: euclidean_spearman
value: 65.92675365587571
- type: manhattan_pearson
value: 67.37398716891478
- type: manhattan_spearman
value: 66.34811143508206
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 84.557575753862
- type: cos_sim_spearman
value: 83.95859527071087
- type: euclidean_pearson
value: 83.77287626715369
- type: euclidean_spearman
value: 83.95859527071087
- type: manhattan_pearson
value: 83.7898033034244
- type: manhattan_spearman
value: 83.94860981294184
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 79.90679624144718
- type: mrr
value: 94.33150183150182
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 56.81699999999999
- type: map_at_10
value: 67.301
- type: map_at_100
value: 67.73599999999999
- type: map_at_1000
value: 67.757
- type: map_at_3
value: 64.865
- type: map_at_5
value: 66.193
- type: mrr_at_1
value: 59.667
- type: mrr_at_10
value: 68.324
- type: mrr_at_100
value: 68.66
- type: mrr_at_1000
value: 68.676
- type: mrr_at_3
value: 66.556
- type: mrr_at_5
value: 67.472
- type: ndcg_at_1
value: 59.667
- type: ndcg_at_10
value: 71.982
- type: ndcg_at_100
value: 74.149
- type: ndcg_at_1000
value: 74.60799999999999
- type: ndcg_at_3
value: 67.796
- type: ndcg_at_5
value: 69.64099999999999
- type: precision_at_1
value: 59.667
- type: precision_at_10
value: 9.633
- type: precision_at_100
value: 1.08
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 26.889000000000003
- type: precision_at_5
value: 17.467
- type: recall_at_1
value: 56.81699999999999
- type: recall_at_10
value: 85.18900000000001
- type: recall_at_100
value: 95.6
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 73.617
- type: recall_at_5
value: 78.444
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.83465346534653
- type: cos_sim_ap
value: 95.93387984443646
- type: cos_sim_f1
value: 91.49261334691798
- type: cos_sim_precision
value: 93.25025960539979
- type: cos_sim_recall
value: 89.8
- type: dot_accuracy
value: 99.83465346534653
- type: dot_ap
value: 95.93389375761485
- type: dot_f1
value: 91.49261334691798
- type: dot_precision
value: 93.25025960539979
- type: dot_recall
value: 89.8
- type: euclidean_accuracy
value: 99.83465346534653
- type: euclidean_ap
value: 95.93389375761487
- type: euclidean_f1
value: 91.49261334691798
- type: euclidean_precision
value: 93.25025960539979
- type: euclidean_recall
value: 89.8
- type: manhattan_accuracy
value: 99.83564356435643
- type: manhattan_ap
value: 95.89877504534601
- type: manhattan_f1
value: 91.53061224489795
- type: manhattan_precision
value: 93.4375
- type: manhattan_recall
value: 89.7
- type: max_accuracy
value: 99.83564356435643
- type: max_ap
value: 95.93389375761487
- type: max_f1
value: 91.53061224489795
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 62.2780055191805
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.94461701798904
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 49.865789666749535
- type: mrr
value: 50.61783804430863
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 29.97703436199298
- type: cos_sim_spearman
value: 30.71880290978946
- type: dot_pearson
value: 29.977036284086818
- type: dot_spearman
value: 30.71880290978946
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.22799999999999998
- type: map_at_10
value: 1.559
- type: map_at_100
value: 8.866
- type: map_at_1000
value: 23.071
- type: map_at_3
value: 0.592
- type: map_at_5
value: 0.906
- type: mrr_at_1
value: 84
- type: mrr_at_10
value: 88.567
- type: mrr_at_100
value: 88.748
- type: mrr_at_1000
value: 88.748
- type: mrr_at_3
value: 87.667
- type: mrr_at_5
value: 88.067
- type: ndcg_at_1
value: 73
- type: ndcg_at_10
value: 62.202999999999996
- type: ndcg_at_100
value: 49.66
- type: ndcg_at_1000
value: 48.760999999999996
- type: ndcg_at_3
value: 67.52
- type: ndcg_at_5
value: 64.80799999999999
- type: precision_at_1
value: 84
- type: precision_at_10
value: 65.4
- type: precision_at_100
value: 51.72
- type: precision_at_1000
value: 22.014
- type: precision_at_3
value: 74
- type: precision_at_5
value: 69.19999999999999
- type: recall_at_1
value: 0.22799999999999998
- type: recall_at_10
value: 1.7680000000000002
- type: recall_at_100
value: 12.581999999999999
- type: recall_at_1000
value: 46.883
- type: recall_at_3
value: 0.618
- type: recall_at_5
value: 0.9690000000000001
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.295
- type: map_at_10
value: 7.481
- type: map_at_100
value: 13.120999999999999
- type: map_at_1000
value: 14.863999999999999
- type: map_at_3
value: 3.266
- type: map_at_5
value: 4.662
- type: mrr_at_1
value: 14.285999999999998
- type: mrr_at_10
value: 31.995
- type: mrr_at_100
value: 33.415
- type: mrr_at_1000
value: 33.432
- type: mrr_at_3
value: 27.551
- type: mrr_at_5
value: 30.306
- type: ndcg_at_1
value: 11.224
- type: ndcg_at_10
value: 19.166
- type: ndcg_at_100
value: 31.86
- type: ndcg_at_1000
value: 44.668
- type: ndcg_at_3
value: 17.371
- type: ndcg_at_5
value: 18.567
- type: precision_at_1
value: 14.285999999999998
- type: precision_at_10
value: 18.98
- type: precision_at_100
value: 7.041
- type: precision_at_1000
value: 1.555
- type: precision_at_3
value: 19.728
- type: precision_at_5
value: 20.816000000000003
- type: recall_at_1
value: 1.295
- type: recall_at_10
value: 14.482000000000001
- type: recall_at_100
value: 45.149
- type: recall_at_1000
value: 84.317
- type: recall_at_3
value: 4.484
- type: recall_at_5
value: 7.7170000000000005
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 72.96340000000001
- type: ap
value: 15.62835559397026
- type: f1
value: 56.42561616707867
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 55.280135823429546
- type: f1
value: 55.61428067547153
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 45.426677723253555
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 84.57411933003517
- type: cos_sim_ap
value: 69.68254951354992
- type: cos_sim_f1
value: 65.05232416646386
- type: cos_sim_precision
value: 60.36585365853659
- type: cos_sim_recall
value: 70.52770448548813
- type: dot_accuracy
value: 84.57411933003517
- type: dot_ap
value: 69.68256519978905
- type: dot_f1
value: 65.05232416646386
- type: dot_precision
value: 60.36585365853659
- type: dot_recall
value: 70.52770448548813
- type: euclidean_accuracy
value: 84.57411933003517
- type: euclidean_ap
value: 69.6825655240522
- type: euclidean_f1
value: 65.05232416646386
- type: euclidean_precision
value: 60.36585365853659
- type: euclidean_recall
value: 70.52770448548813
- type: manhattan_accuracy
value: 84.5502771651666
- type: manhattan_ap
value: 69.61700491283233
- type: manhattan_f1
value: 64.83962148211872
- type: manhattan_precision
value: 60.68553025074765
- type: manhattan_recall
value: 69.6042216358839
- type: max_accuracy
value: 84.57411933003517
- type: max_ap
value: 69.6825655240522
- type: max_f1
value: 65.05232416646386
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.80350836341057
- type: cos_sim_ap
value: 85.41051415803449
- type: cos_sim_f1
value: 77.99305633329602
- type: cos_sim_precision
value: 75.70113776360607
- type: cos_sim_recall
value: 80.42808746535263
- type: dot_accuracy
value: 88.80350836341057
- type: dot_ap
value: 85.41051488820463
- type: dot_f1
value: 77.99305633329602
- type: dot_precision
value: 75.70113776360607
- type: dot_recall
value: 80.42808746535263
- type: euclidean_accuracy
value: 88.80350836341057
- type: euclidean_ap
value: 85.41051374760137
- type: euclidean_f1
value: 77.99305633329602
- type: euclidean_precision
value: 75.70113776360607
- type: euclidean_recall
value: 80.42808746535263
- type: manhattan_accuracy
value: 88.74529436876625
- type: manhattan_ap
value: 85.38380242074525
- type: manhattan_f1
value: 78.02957839746892
- type: manhattan_precision
value: 74.71466816964914
- type: manhattan_recall
value: 81.65229442562365
- type: max_accuracy
value: 88.80350836341057
- type: max_ap
value: 85.41051488820463
- type: max_f1
value: 78.02957839746892
nomic-embed-text-v1-unsupervised: A Reproducible Long Context (8192) Text Embedder
nomic-embed-text-v1-unsupervised is 8192 context length text encoder. This is a checkpoint after contrastive pretraining from multi-stage contrastive training of the
final model. The purpose of releasing this checkpoint is to open-source training artifacts from our Nomic Embed Text tech report here
If you want to use a model to extract embeddings, we suggest using nomic-embed-text-v1.
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