metadata
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: SGPT-125M-weightedmean-msmarco-specb-bitfit
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 61.23880597014926
- type: ap
value: 25.854431650388644
- type: f1
value: 55.751862762818604
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (de)
config: de
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 56.88436830835117
- type: ap
value: 72.67279104379772
- type: f1
value: 54.449840243786404
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en-ext)
config: en-ext
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 58.27586206896551
- type: ap
value: 14.067357642500387
- type: f1
value: 48.172318518691334
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (ja)
config: ja
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 54.64668094218415
- type: ap
value: 11.776694555054965
- type: f1
value: 44.526622834078765
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
metrics:
- type: accuracy
value: 65.401225
- type: ap
value: 60.22809958678552
- type: f1
value: 65.0251824898292
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 31.165999999999993
- type: f1
value: 30.908870050167437
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (de)
config: de
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 24.79
- type: f1
value: 24.5833598854121
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (es)
config: es
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 26.643999999999995
- type: f1
value: 26.39012792213563
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (fr)
config: fr
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 26.386000000000003
- type: f1
value: 26.276867791454873
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (ja)
config: ja
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 22.078000000000003
- type: f1
value: 21.797960290226843
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 24.274
- type: f1
value: 23.887054434822627
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
metrics:
- type: map_at_1
value: 22.404
- type: map_at_10
value: 36.845
- type: map_at_100
value: 37.945
- type: map_at_1000
value: 37.966
- type: map_at_3
value: 31.78
- type: map_at_5
value: 34.608
- type: mrr_at_1
value: 22.902
- type: mrr_at_10
value: 37.034
- type: mrr_at_100
value: 38.134
- type: mrr_at_1000
value: 38.155
- type: mrr_at_3
value: 31.935000000000002
- type: mrr_at_5
value: 34.812
- type: ndcg_at_1
value: 22.404
- type: ndcg_at_10
value: 45.425
- type: ndcg_at_100
value: 50.354
- type: ndcg_at_1000
value: 50.873999999999995
- type: ndcg_at_3
value: 34.97
- type: ndcg_at_5
value: 40.081
- type: precision_at_1
value: 22.404
- type: precision_at_10
value: 7.303999999999999
- type: precision_at_100
value: 0.951
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 14.746
- type: precision_at_5
value: 11.337
- type: recall_at_1
value: 22.404
- type: recall_at_10
value: 73.044
- type: recall_at_100
value: 95.092
- type: recall_at_1000
value: 99.075
- type: recall_at_3
value: 44.239
- type: recall_at_5
value: 56.686
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
metrics:
- type: v_measure
value: 39.70858340673288
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
metrics:
- type: v_measure
value: 28.242847713721048
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
metrics:
- type: map
value: 55.83700395192393
- type: mrr
value: 70.3891307215407
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: 9ee918f184421b6bd48b78f6c714d86546106103
metrics:
- type: cos_sim_pearson
value: 79.25366801756223
- type: cos_sim_spearman
value: 75.20954502580506
- type: euclidean_pearson
value: 78.79900722991617
- type: euclidean_spearman
value: 77.79996549607588
- type: manhattan_pearson
value: 78.18408109480399
- type: manhattan_spearman
value: 76.85958262303106
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
metrics:
- type: accuracy
value: 77.70454545454545
- type: f1
value: 77.6929000113803
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
metrics:
- type: v_measure
value: 33.63260395543984
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
metrics:
- type: v_measure
value: 27.038042665369925
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 22.139
- type: map_at_10
value: 28.839
- type: map_at_100
value: 30.023
- type: map_at_1000
value: 30.153000000000002
- type: map_at_3
value: 26.521
- type: map_at_5
value: 27.775
- type: mrr_at_1
value: 26.466
- type: mrr_at_10
value: 33.495000000000005
- type: mrr_at_100
value: 34.416999999999994
- type: mrr_at_1000
value: 34.485
- type: mrr_at_3
value: 31.402
- type: mrr_at_5
value: 32.496
- type: ndcg_at_1
value: 26.466
- type: ndcg_at_10
value: 33.372
- type: ndcg_at_100
value: 38.7
- type: ndcg_at_1000
value: 41.696
- type: ndcg_at_3
value: 29.443
- type: ndcg_at_5
value: 31.121
- type: precision_at_1
value: 26.466
- type: precision_at_10
value: 6.037
- type: precision_at_100
value: 1.0670000000000002
- type: precision_at_1000
value: 0.16199999999999998
- type: precision_at_3
value: 13.782
- type: precision_at_5
value: 9.757
- type: recall_at_1
value: 22.139
- type: recall_at_10
value: 42.39
- type: recall_at_100
value: 65.427
- type: recall_at_1000
value: 86.04899999999999
- type: recall_at_3
value: 31.127
- type: recall_at_5
value: 35.717999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 20.652
- type: map_at_10
value: 27.558
- type: map_at_100
value: 28.473
- type: map_at_1000
value: 28.577
- type: map_at_3
value: 25.402
- type: map_at_5
value: 26.68
- type: mrr_at_1
value: 25.223000000000003
- type: mrr_at_10
value: 31.966
- type: mrr_at_100
value: 32.664
- type: mrr_at_1000
value: 32.724
- type: mrr_at_3
value: 30.074
- type: mrr_at_5
value: 31.249
- type: ndcg_at_1
value: 25.223000000000003
- type: ndcg_at_10
value: 31.694
- type: ndcg_at_100
value: 35.662
- type: ndcg_at_1000
value: 38.092
- type: ndcg_at_3
value: 28.294000000000004
- type: ndcg_at_5
value: 30.049
- type: precision_at_1
value: 25.223000000000003
- type: precision_at_10
value: 5.777
- type: precision_at_100
value: 0.9730000000000001
- type: precision_at_1000
value: 0.13999999999999999
- type: precision_at_3
value: 13.397
- type: precision_at_5
value: 9.605
- type: recall_at_1
value: 20.652
- type: recall_at_10
value: 39.367999999999995
- type: recall_at_100
value: 56.485
- type: recall_at_1000
value: 73.292
- type: recall_at_3
value: 29.830000000000002
- type: recall_at_5
value: 34.43
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 25.180000000000003
- type: map_at_10
value: 34.579
- type: map_at_100
value: 35.589999999999996
- type: map_at_1000
value: 35.68
- type: map_at_3
value: 31.735999999999997
- type: map_at_5
value: 33.479
- type: mrr_at_1
value: 29.467
- type: mrr_at_10
value: 37.967
- type: mrr_at_100
value: 38.800000000000004
- type: mrr_at_1000
value: 38.858
- type: mrr_at_3
value: 35.465
- type: mrr_at_5
value: 37.057
- type: ndcg_at_1
value: 29.467
- type: ndcg_at_10
value: 39.796
- type: ndcg_at_100
value: 44.531
- type: ndcg_at_1000
value: 46.666000000000004
- type: ndcg_at_3
value: 34.676
- type: ndcg_at_5
value: 37.468
- type: precision_at_1
value: 29.467
- type: precision_at_10
value: 6.601999999999999
- type: precision_at_100
value: 0.9900000000000001
- type: precision_at_1000
value: 0.124
- type: precision_at_3
value: 15.568999999999999
- type: precision_at_5
value: 11.172
- type: recall_at_1
value: 25.180000000000003
- type: recall_at_10
value: 52.269
- type: recall_at_100
value: 73.574
- type: recall_at_1000
value: 89.141
- type: recall_at_3
value: 38.522
- type: recall_at_5
value: 45.323
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 16.303
- type: map_at_10
value: 21.629
- type: map_at_100
value: 22.387999999999998
- type: map_at_1000
value: 22.489
- type: map_at_3
value: 19.608
- type: map_at_5
value: 20.774
- type: mrr_at_1
value: 17.740000000000002
- type: mrr_at_10
value: 23.214000000000002
- type: mrr_at_100
value: 23.97
- type: mrr_at_1000
value: 24.054000000000002
- type: mrr_at_3
value: 21.243000000000002
- type: mrr_at_5
value: 22.322
- type: ndcg_at_1
value: 17.740000000000002
- type: ndcg_at_10
value: 25.113000000000003
- type: ndcg_at_100
value: 29.287999999999997
- type: ndcg_at_1000
value: 32.204
- type: ndcg_at_3
value: 21.111
- type: ndcg_at_5
value: 23.061999999999998
- type: precision_at_1
value: 17.740000000000002
- type: precision_at_10
value: 3.955
- type: precision_at_100
value: 0.644
- type: precision_at_1000
value: 0.093
- type: precision_at_3
value: 8.851
- type: precision_at_5
value: 6.418
- type: recall_at_1
value: 16.303
- type: recall_at_10
value: 34.487
- type: recall_at_100
value: 54.413999999999994
- type: recall_at_1000
value: 77.158
- type: recall_at_3
value: 23.733
- type: recall_at_5
value: 28.381
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 10.133000000000001
- type: map_at_10
value: 15.665999999999999
- type: map_at_100
value: 16.592000000000002
- type: map_at_1000
value: 16.733999999999998
- type: map_at_3
value: 13.625000000000002
- type: map_at_5
value: 14.721
- type: mrr_at_1
value: 12.562000000000001
- type: mrr_at_10
value: 18.487000000000002
- type: mrr_at_100
value: 19.391
- type: mrr_at_1000
value: 19.487
- type: mrr_at_3
value: 16.418
- type: mrr_at_5
value: 17.599999999999998
- type: ndcg_at_1
value: 12.562000000000001
- type: ndcg_at_10
value: 19.43
- type: ndcg_at_100
value: 24.546
- type: ndcg_at_1000
value: 28.193
- type: ndcg_at_3
value: 15.509999999999998
- type: ndcg_at_5
value: 17.322000000000003
- type: precision_at_1
value: 12.562000000000001
- type: precision_at_10
value: 3.794
- type: precision_at_100
value: 0.74
- type: precision_at_1000
value: 0.122
- type: precision_at_3
value: 7.546
- type: precision_at_5
value: 5.721
- type: recall_at_1
value: 10.133000000000001
- type: recall_at_10
value: 28.261999999999997
- type: recall_at_100
value: 51.742999999999995
- type: recall_at_1000
value: 78.075
- type: recall_at_3
value: 17.634
- type: recall_at_5
value: 22.128999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 19.991999999999997
- type: map_at_10
value: 27.346999999999998
- type: map_at_100
value: 28.582
- type: map_at_1000
value: 28.716
- type: map_at_3
value: 24.907
- type: map_at_5
value: 26.1
- type: mrr_at_1
value: 23.773
- type: mrr_at_10
value: 31.647
- type: mrr_at_100
value: 32.639
- type: mrr_at_1000
value: 32.706
- type: mrr_at_3
value: 29.195
- type: mrr_at_5
value: 30.484
- type: ndcg_at_1
value: 23.773
- type: ndcg_at_10
value: 32.322
- type: ndcg_at_100
value: 37.996
- type: ndcg_at_1000
value: 40.819
- type: ndcg_at_3
value: 27.876
- type: ndcg_at_5
value: 29.664
- type: precision_at_1
value: 23.773
- type: precision_at_10
value: 5.976999999999999
- type: precision_at_100
value: 1.055
- type: precision_at_1000
value: 0.15
- type: precision_at_3
value: 13.122
- type: precision_at_5
value: 9.451
- type: recall_at_1
value: 19.991999999999997
- type: recall_at_10
value: 43.106
- type: recall_at_100
value: 67.264
- type: recall_at_1000
value: 86.386
- type: recall_at_3
value: 30.392000000000003
- type: recall_at_5
value: 34.910999999999994
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 17.896
- type: map_at_10
value: 24.644
- type: map_at_100
value: 25.790000000000003
- type: map_at_1000
value: 25.913999999999998
- type: map_at_3
value: 22.694
- type: map_at_5
value: 23.69
- type: mrr_at_1
value: 21.346999999999998
- type: mrr_at_10
value: 28.594
- type: mrr_at_100
value: 29.543999999999997
- type: mrr_at_1000
value: 29.621
- type: mrr_at_3
value: 26.807
- type: mrr_at_5
value: 27.669
- type: ndcg_at_1
value: 21.346999999999998
- type: ndcg_at_10
value: 28.833
- type: ndcg_at_100
value: 34.272000000000006
- type: ndcg_at_1000
value: 37.355
- type: ndcg_at_3
value: 25.373
- type: ndcg_at_5
value: 26.756
- type: precision_at_1
value: 21.346999999999998
- type: precision_at_10
value: 5.2170000000000005
- type: precision_at_100
value: 0.954
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 11.948
- type: precision_at_5
value: 8.425
- type: recall_at_1
value: 17.896
- type: recall_at_10
value: 37.291000000000004
- type: recall_at_100
value: 61.138000000000005
- type: recall_at_1000
value: 83.212
- type: recall_at_3
value: 27.705999999999996
- type: recall_at_5
value: 31.234
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 17.195166666666665
- type: map_at_10
value: 23.329083333333333
- type: map_at_100
value: 24.30308333333333
- type: map_at_1000
value: 24.422416666666667
- type: map_at_3
value: 21.327416666666664
- type: map_at_5
value: 22.419999999999998
- type: mrr_at_1
value: 19.999916666666667
- type: mrr_at_10
value: 26.390166666666666
- type: mrr_at_100
value: 27.230999999999998
- type: mrr_at_1000
value: 27.308333333333334
- type: mrr_at_3
value: 24.4675
- type: mrr_at_5
value: 25.541083333333336
- type: ndcg_at_1
value: 19.999916666666667
- type: ndcg_at_10
value: 27.248666666666665
- type: ndcg_at_100
value: 32.00258333333334
- type: ndcg_at_1000
value: 34.9465
- type: ndcg_at_3
value: 23.58566666666667
- type: ndcg_at_5
value: 25.26341666666666
- type: precision_at_1
value: 19.999916666666667
- type: precision_at_10
value: 4.772166666666666
- type: precision_at_100
value: 0.847
- type: precision_at_1000
value: 0.12741666666666668
- type: precision_at_3
value: 10.756166666666669
- type: precision_at_5
value: 7.725416666666667
- type: recall_at_1
value: 17.195166666666665
- type: recall_at_10
value: 35.99083333333334
- type: recall_at_100
value: 57.467999999999996
- type: recall_at_1000
value: 78.82366666666667
- type: recall_at_3
value: 25.898499999999995
- type: recall_at_5
value: 30.084333333333333
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 16.779
- type: map_at_10
value: 21.557000000000002
- type: map_at_100
value: 22.338
- type: map_at_1000
value: 22.421
- type: map_at_3
value: 19.939
- type: map_at_5
value: 20.903
- type: mrr_at_1
value: 18.404999999999998
- type: mrr_at_10
value: 23.435
- type: mrr_at_100
value: 24.179000000000002
- type: mrr_at_1000
value: 24.25
- type: mrr_at_3
value: 21.907
- type: mrr_at_5
value: 22.781000000000002
- type: ndcg_at_1
value: 18.404999999999998
- type: ndcg_at_10
value: 24.515
- type: ndcg_at_100
value: 28.721000000000004
- type: ndcg_at_1000
value: 31.259999999999998
- type: ndcg_at_3
value: 21.508
- type: ndcg_at_5
value: 23.01
- type: precision_at_1
value: 18.404999999999998
- type: precision_at_10
value: 3.834
- type: precision_at_100
value: 0.641
- type: precision_at_1000
value: 0.093
- type: precision_at_3
value: 9.151
- type: precision_at_5
value: 6.503
- type: recall_at_1
value: 16.779
- type: recall_at_10
value: 31.730000000000004
- type: recall_at_100
value: 51.673
- type: recall_at_1000
value: 71.17599999999999
- type: recall_at_3
value: 23.518
- type: recall_at_5
value: 27.230999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 9.279
- type: map_at_10
value: 13.822000000000001
- type: map_at_100
value: 14.533
- type: map_at_1000
value: 14.649999999999999
- type: map_at_3
value: 12.396
- type: map_at_5
value: 13.214
- type: mrr_at_1
value: 11.149000000000001
- type: mrr_at_10
value: 16.139
- type: mrr_at_100
value: 16.872
- type: mrr_at_1000
value: 16.964000000000002
- type: mrr_at_3
value: 14.613000000000001
- type: mrr_at_5
value: 15.486
- type: ndcg_at_1
value: 11.149000000000001
- type: ndcg_at_10
value: 16.82
- type: ndcg_at_100
value: 20.73
- type: ndcg_at_1000
value: 23.894000000000002
- type: ndcg_at_3
value: 14.11
- type: ndcg_at_5
value: 15.404000000000002
- type: precision_at_1
value: 11.149000000000001
- type: precision_at_10
value: 3.063
- type: precision_at_100
value: 0.587
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 6.699
- type: precision_at_5
value: 4.928
- type: recall_at_1
value: 9.279
- type: recall_at_10
value: 23.745
- type: recall_at_100
value: 41.873
- type: recall_at_1000
value: 64.982
- type: recall_at_3
value: 16.152
- type: recall_at_5
value: 19.409000000000002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 16.36
- type: map_at_10
value: 21.927
- type: map_at_100
value: 22.889
- type: map_at_1000
value: 22.994
- type: map_at_3
value: 20.433
- type: map_at_5
value: 21.337
- type: mrr_at_1
value: 18.75
- type: mrr_at_10
value: 24.859
- type: mrr_at_100
value: 25.746999999999996
- type: mrr_at_1000
value: 25.829
- type: mrr_at_3
value: 23.383000000000003
- type: mrr_at_5
value: 24.297
- type: ndcg_at_1
value: 18.75
- type: ndcg_at_10
value: 25.372
- type: ndcg_at_100
value: 30.342999999999996
- type: ndcg_at_1000
value: 33.286
- type: ndcg_at_3
value: 22.627
- type: ndcg_at_5
value: 24.04
- type: precision_at_1
value: 18.75
- type: precision_at_10
value: 4.1419999999999995
- type: precision_at_100
value: 0.738
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 10.261000000000001
- type: precision_at_5
value: 7.164
- type: recall_at_1
value: 16.36
- type: recall_at_10
value: 32.949
- type: recall_at_100
value: 55.552
- type: recall_at_1000
value: 77.09899999999999
- type: recall_at_3
value: 25.538
- type: recall_at_5
value: 29.008
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 17.39
- type: map_at_10
value: 23.058
- type: map_at_100
value: 24.445
- type: map_at_1000
value: 24.637999999999998
- type: map_at_3
value: 21.037
- type: map_at_5
value: 21.966
- type: mrr_at_1
value: 19.96
- type: mrr_at_10
value: 26.301000000000002
- type: mrr_at_100
value: 27.297
- type: mrr_at_1000
value: 27.375
- type: mrr_at_3
value: 24.340999999999998
- type: mrr_at_5
value: 25.339
- type: ndcg_at_1
value: 19.96
- type: ndcg_at_10
value: 27.249000000000002
- type: ndcg_at_100
value: 32.997
- type: ndcg_at_1000
value: 36.359
- type: ndcg_at_3
value: 23.519000000000002
- type: ndcg_at_5
value: 24.915000000000003
- type: precision_at_1
value: 19.96
- type: precision_at_10
value: 5.356000000000001
- type: precision_at_100
value: 1.198
- type: precision_at_1000
value: 0.20400000000000001
- type: precision_at_3
value: 10.738
- type: precision_at_5
value: 7.904999999999999
- type: recall_at_1
value: 17.39
- type: recall_at_10
value: 35.254999999999995
- type: recall_at_100
value: 61.351
- type: recall_at_1000
value: 84.395
- type: recall_at_3
value: 25.194
- type: recall_at_5
value: 28.546
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 14.238999999999999
- type: map_at_10
value: 19.323
- type: map_at_100
value: 19.994
- type: map_at_1000
value: 20.102999999999998
- type: map_at_3
value: 17.631
- type: map_at_5
value: 18.401
- type: mrr_at_1
value: 15.157000000000002
- type: mrr_at_10
value: 20.578
- type: mrr_at_100
value: 21.252
- type: mrr_at_1000
value: 21.346999999999998
- type: mrr_at_3
value: 18.762
- type: mrr_at_5
value: 19.713
- type: ndcg_at_1
value: 15.157000000000002
- type: ndcg_at_10
value: 22.468
- type: ndcg_at_100
value: 26.245
- type: ndcg_at_1000
value: 29.534
- type: ndcg_at_3
value: 18.981
- type: ndcg_at_5
value: 20.349999999999998
- type: precision_at_1
value: 15.157000000000002
- type: precision_at_10
value: 3.512
- type: precision_at_100
value: 0.577
- type: precision_at_1000
value: 0.091
- type: precision_at_3
value: 8.01
- type: precision_at_5
value: 5.656
- type: recall_at_1
value: 14.238999999999999
- type: recall_at_10
value: 31.038
- type: recall_at_100
value: 49.122
- type: recall_at_1000
value: 74.919
- type: recall_at_3
value: 21.436
- type: recall_at_5
value: 24.692
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
metrics:
- type: map_at_1
value: 8.828
- type: map_at_10
value: 14.982000000000001
- type: map_at_100
value: 16.495
- type: map_at_1000
value: 16.658
- type: map_at_3
value: 12.366000000000001
- type: map_at_5
value: 13.655000000000001
- type: mrr_at_1
value: 19.088
- type: mrr_at_10
value: 29.29
- type: mrr_at_100
value: 30.291
- type: mrr_at_1000
value: 30.342000000000002
- type: mrr_at_3
value: 25.907000000000004
- type: mrr_at_5
value: 27.840999999999998
- type: ndcg_at_1
value: 19.088
- type: ndcg_at_10
value: 21.858
- type: ndcg_at_100
value: 28.323999999999998
- type: ndcg_at_1000
value: 31.561
- type: ndcg_at_3
value: 17.175
- type: ndcg_at_5
value: 18.869
- type: precision_at_1
value: 19.088
- type: precision_at_10
value: 6.9190000000000005
- type: precision_at_100
value: 1.376
- type: precision_at_1000
value: 0.197
- type: precision_at_3
value: 12.703999999999999
- type: precision_at_5
value: 9.993
- type: recall_at_1
value: 8.828
- type: recall_at_10
value: 27.381
- type: recall_at_100
value: 50
- type: recall_at_1000
value: 68.355
- type: recall_at_3
value: 16.118
- type: recall_at_5
value: 20.587
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: f097057d03ed98220bc7309ddb10b71a54d667d6
metrics:
- type: map_at_1
value: 5.586
- type: map_at_10
value: 10.040000000000001
- type: map_at_100
value: 12.55
- type: map_at_1000
value: 13.123999999999999
- type: map_at_3
value: 7.75
- type: map_at_5
value: 8.835999999999999
- type: mrr_at_1
value: 42.25
- type: mrr_at_10
value: 51.205999999999996
- type: mrr_at_100
value: 51.818
- type: mrr_at_1000
value: 51.855
- type: mrr_at_3
value: 48.875
- type: mrr_at_5
value: 50.488
- type: ndcg_at_1
value: 32.25
- type: ndcg_at_10
value: 22.718
- type: ndcg_at_100
value: 24.359
- type: ndcg_at_1000
value: 29.232000000000003
- type: ndcg_at_3
value: 25.974000000000004
- type: ndcg_at_5
value: 24.291999999999998
- type: precision_at_1
value: 42.25
- type: precision_at_10
value: 17.75
- type: precision_at_100
value: 5.032
- type: precision_at_1000
value: 1.117
- type: precision_at_3
value: 28.833
- type: precision_at_5
value: 24.25
- type: recall_at_1
value: 5.586
- type: recall_at_10
value: 14.16
- type: recall_at_100
value: 28.051
- type: recall_at_1000
value: 45.157000000000004
- type: recall_at_3
value: 8.758000000000001
- type: recall_at_5
value: 10.975999999999999
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 829147f8f75a25f005913200eb5ed41fae320aa1
metrics:
- type: accuracy
value: 39.075
- type: f1
value: 35.01420354708222
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
metrics:
- type: map_at_1
value: 43.519999999999996
- type: map_at_10
value: 54.368
- type: map_at_100
value: 54.918
- type: map_at_1000
value: 54.942
- type: map_at_3
value: 51.712
- type: map_at_5
value: 53.33599999999999
- type: mrr_at_1
value: 46.955000000000005
- type: mrr_at_10
value: 58.219
- type: mrr_at_100
value: 58.73500000000001
- type: mrr_at_1000
value: 58.753
- type: mrr_at_3
value: 55.518
- type: mrr_at_5
value: 57.191
- type: ndcg_at_1
value: 46.955000000000005
- type: ndcg_at_10
value: 60.45
- type: ndcg_at_100
value: 63.047
- type: ndcg_at_1000
value: 63.712999999999994
- type: ndcg_at_3
value: 55.233
- type: ndcg_at_5
value: 58.072
- type: precision_at_1
value: 46.955000000000005
- type: precision_at_10
value: 8.267
- type: precision_at_100
value: 0.962
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 22.326999999999998
- type: precision_at_5
value: 14.940999999999999
- type: recall_at_1
value: 43.519999999999996
- type: recall_at_10
value: 75.632
- type: recall_at_100
value: 87.41600000000001
- type: recall_at_1000
value: 92.557
- type: recall_at_3
value: 61.597
- type: recall_at_5
value: 68.518
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
metrics:
- type: map_at_1
value: 9.549000000000001
- type: map_at_10
value: 15.762
- type: map_at_100
value: 17.142
- type: map_at_1000
value: 17.329
- type: map_at_3
value: 13.575000000000001
- type: map_at_5
value: 14.754000000000001
- type: mrr_at_1
value: 19.753
- type: mrr_at_10
value: 26.568
- type: mrr_at_100
value: 27.606
- type: mrr_at_1000
value: 27.68
- type: mrr_at_3
value: 24.203
- type: mrr_at_5
value: 25.668999999999997
- type: ndcg_at_1
value: 19.753
- type: ndcg_at_10
value: 21.118000000000002
- type: ndcg_at_100
value: 27.308
- type: ndcg_at_1000
value: 31.304
- type: ndcg_at_3
value: 18.319
- type: ndcg_at_5
value: 19.414
- type: precision_at_1
value: 19.753
- type: precision_at_10
value: 6.08
- type: precision_at_100
value: 1.204
- type: precision_at_1000
value: 0.192
- type: precision_at_3
value: 12.191
- type: precision_at_5
value: 9.383
- type: recall_at_1
value: 9.549000000000001
- type: recall_at_10
value: 26.131
- type: recall_at_100
value: 50.544999999999995
- type: recall_at_1000
value: 74.968
- type: recall_at_3
value: 16.951
- type: recall_at_5
value: 20.95
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
metrics:
- type: map_at_1
value: 25.544
- type: map_at_10
value: 32.62
- type: map_at_100
value: 33.275
- type: map_at_1000
value: 33.344
- type: map_at_3
value: 30.851
- type: map_at_5
value: 31.868999999999996
- type: mrr_at_1
value: 51.087
- type: mrr_at_10
value: 57.704
- type: mrr_at_100
value: 58.175
- type: mrr_at_1000
value: 58.207
- type: mrr_at_3
value: 56.106
- type: mrr_at_5
value: 57.074000000000005
- type: ndcg_at_1
value: 51.087
- type: ndcg_at_10
value: 40.876000000000005
- type: ndcg_at_100
value: 43.762
- type: ndcg_at_1000
value: 45.423
- type: ndcg_at_3
value: 37.65
- type: ndcg_at_5
value: 39.305
- type: precision_at_1
value: 51.087
- type: precision_at_10
value: 8.304
- type: precision_at_100
value: 1.059
- type: precision_at_1000
value: 0.128
- type: precision_at_3
value: 22.875999999999998
- type: precision_at_5
value: 15.033
- type: recall_at_1
value: 25.544
- type: recall_at_10
value: 41.519
- type: recall_at_100
value: 52.957
- type: recall_at_1000
value: 64.132
- type: recall_at_3
value: 34.315
- type: recall_at_5
value: 37.583
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
metrics:
- type: accuracy
value: 58.6696
- type: ap
value: 55.3644880984279
- type: f1
value: 58.07942097405652
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: validation
revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
metrics:
- type: map_at_1
value: 14.442
- type: map_at_10
value: 22.932
- type: map_at_100
value: 24.132
- type: map_at_1000
value: 24.213
- type: map_at_3
value: 20.002
- type: map_at_5
value: 21.636
- type: mrr_at_1
value: 14.841999999999999
- type: mrr_at_10
value: 23.416
- type: mrr_at_100
value: 24.593999999999998
- type: mrr_at_1000
value: 24.669
- type: mrr_at_3
value: 20.494
- type: mrr_at_5
value: 22.14
- type: ndcg_at_1
value: 14.841999999999999
- type: ndcg_at_10
value: 27.975
- type: ndcg_at_100
value: 34.143
- type: ndcg_at_1000
value: 36.370000000000005
- type: ndcg_at_3
value: 21.944
- type: ndcg_at_5
value: 24.881
- type: precision_at_1
value: 14.841999999999999
- type: precision_at_10
value: 4.537
- type: precision_at_100
value: 0.767
- type: precision_at_1000
value: 0.096
- type: precision_at_3
value: 9.322
- type: precision_at_5
value: 7.074
- type: recall_at_1
value: 14.442
- type: recall_at_10
value: 43.557
- type: recall_at_100
value: 72.904
- type: recall_at_1000
value: 90.40700000000001
- type: recall_at_3
value: 27.088
- type: recall_at_5
value: 34.144000000000005
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 86.95622435020519
- type: f1
value: 86.58363130708494
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (de)
config: de
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 62.73034657650043
- type: f1
value: 60.78623915840713
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (es)
config: es
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 67.54503002001334
- type: f1
value: 65.34879794116112
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (fr)
config: fr
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 65.35233322893829
- type: f1
value: 62.994001882446646
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (hi)
config: hi
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 45.37110075295806
- type: f1
value: 44.26285860740745
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (th)
config: th
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 55.276672694394215
- type: f1
value: 53.28388179869587
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: 6299947a7777084cc2d4b64235bf7190381ce755
metrics:
- type: accuracy
value: 62.25262197902417
- type: f1
value: 43.44084037148853
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- type: recall_at_100
value: 28.975
- type: recall_at_1000
value: 54.038
- type: recall_at_3
value: 6.912999999999999
- type: recall_at_5
value: 8.883000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 76.62983928119752
- type: cos_sim_spearman
value: 65.92910683118656
- type: euclidean_pearson
value: 71.10290039690963
- type: euclidean_spearman
value: 64.80076622426652
- type: manhattan_pearson
value: 70.8944726230188
- type: manhattan_spearman
value: 64.75082576033986
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
metrics:
- type: cos_sim_pearson
value: 74.42679147085553
- type: cos_sim_spearman
value: 66.52980061546658
- type: euclidean_pearson
value: 74.87039477408763
- type: euclidean_spearman
value: 70.63397666902786
- type: manhattan_pearson
value: 74.97015137513088
- type: manhattan_spearman
value: 70.75951355434326
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9
metrics:
- type: cos_sim_pearson
value: 75.62472426599543
- type: cos_sim_spearman
value: 76.1662886374236
- type: euclidean_pearson
value: 76.3297128081315
- type: euclidean_spearman
value: 77.19385151966563
- type: manhattan_pearson
value: 76.50363291423257
- type: manhattan_spearman
value: 77.37081896355399
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b
metrics:
- type: cos_sim_pearson
value: 74.48227705407035
- type: cos_sim_spearman
value: 69.04572664009687
- type: euclidean_pearson
value: 71.76138185714849
- type: euclidean_spearman
value: 68.93415452043307
- type: manhattan_pearson
value: 71.68010915543306
- type: manhattan_spearman
value: 68.99176321262806
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
metrics:
- type: cos_sim_pearson
value: 78.1566527175902
- type: cos_sim_spearman
value: 79.23677712825851
- type: euclidean_pearson
value: 76.29138438696417
- type: euclidean_spearman
value: 77.20108266215374
- type: manhattan_pearson
value: 76.27464935799118
- type: manhattan_spearman
value: 77.15286174478099
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
metrics:
- type: cos_sim_pearson
value: 75.068454465977
- type: cos_sim_spearman
value: 76.06792422441929
- type: euclidean_pearson
value: 70.64605440627699
- type: euclidean_spearman
value: 70.21776051117844
- type: manhattan_pearson
value: 70.32479295054918
- type: manhattan_spearman
value: 69.89782458638528
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (ko-ko)
config: ko-ko
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 39.43327289939437
- type: cos_sim_spearman
value: 52.386010275505654
- type: euclidean_pearson
value: 46.40999904885745
- type: euclidean_spearman
value: 51.00333465175934
- type: manhattan_pearson
value: 46.55753533133655
- type: manhattan_spearman
value: 51.07550440519388
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (ar-ar)
config: ar-ar
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 55.54431928210687
- type: cos_sim_spearman
value: 55.61674586076298
- type: euclidean_pearson
value: 58.07442713714088
- type: euclidean_spearman
value: 55.74066216931719
- type: manhattan_pearson
value: 57.84021675638542
- type: manhattan_spearman
value: 55.20365812536853
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-ar)
config: en-ar
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 11.378463868809098
- type: cos_sim_spearman
value: 8.209569244801065
- type: euclidean_pearson
value: 1.07041700730406
- type: euclidean_spearman
value: 2.2052197108931892
- type: manhattan_pearson
value: 0.7671300251104268
- type: manhattan_spearman
value: 3.430645020535567
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-de)
config: en-de
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 32.71403560929013
- type: cos_sim_spearman
value: 30.18181775929109
- type: euclidean_pearson
value: 25.57368595910298
- type: euclidean_spearman
value: 23.316649115731376
- type: manhattan_pearson
value: 24.144200325329614
- type: manhattan_spearman
value: 21.64621546338457
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 83.36340470799158
- type: cos_sim_spearman
value: 84.95398260629699
- type: euclidean_pearson
value: 80.69876969911644
- type: euclidean_spearman
value: 80.97451731130427
- type: manhattan_pearson
value: 80.65869354146945
- type: manhattan_spearman
value: 80.8540858718528
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-tr)
config: en-tr
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 1.9200044163754912
- type: cos_sim_spearman
value: 1.0393399782021342
- type: euclidean_pearson
value: 1.1376003191297994
- type: euclidean_spearman
value: 1.8947106671763914
- type: manhattan_pearson
value: 3.8362564474484335
- type: manhattan_spearman
value: 4.242750882792888
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (es-en)
config: es-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 26.561262451099577
- type: cos_sim_spearman
value: 28.776666666659906
- type: euclidean_pearson
value: 14.640410196999088
- type: euclidean_spearman
value: 16.10557011701786
- type: manhattan_pearson
value: 15.019405495911272
- type: manhattan_spearman
value: 15.37192083104197
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (es-es)
config: es-es
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 69.7544202001433
- type: cos_sim_spearman
value: 71.88444295144646
- type: euclidean_pearson
value: 73.84934185952773
- type: euclidean_spearman
value: 73.26911108021089
- type: manhattan_pearson
value: 74.04354196954574
- type: manhattan_spearman
value: 73.37650787943872
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (fr-en)
config: fr-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 27.70511842301491
- type: cos_sim_spearman
value: 26.339466714066447
- type: euclidean_pearson
value: 9.323158236506385
- type: euclidean_spearman
value: 7.32083231520273
- type: manhattan_pearson
value: 7.807399527573071
- type: manhattan_spearman
value: 5.525546663067113
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (it-en)
config: it-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 24.226521799447692
- type: cos_sim_spearman
value: 20.72992940458968
- type: euclidean_pearson
value: 6.753378617205011
- type: euclidean_spearman
value: 6.281654679029505
- type: manhattan_pearson
value: 7.087180250449323
- type: manhattan_spearman
value: 6.41611659259516
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (nl-en)
config: nl-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 29.131412364061234
- type: cos_sim_spearman
value: 25.053429612793547
- type: euclidean_pearson
value: 10.657141303962
- type: euclidean_spearman
value: 9.712124819778452
- type: manhattan_pearson
value: 12.481782693315688
- type: manhattan_spearman
value: 11.287958480905973
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 64.04750650962879
- type: cos_sim_spearman
value: 65.66183708171826
- type: euclidean_pearson
value: 66.90887604405887
- type: euclidean_spearman
value: 66.89814072484552
- type: manhattan_pearson
value: 67.31627110509089
- type: manhattan_spearman
value: 67.01048176165322
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de)
config: de
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 19.26519187000913
- type: cos_sim_spearman
value: 21.987647321429005
- type: euclidean_pearson
value: 17.850618752342946
- type: euclidean_spearman
value: 22.86669392885474
- type: manhattan_pearson
value: 18.16183594260708
- type: manhattan_spearman
value: 23.637510352837907
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es)
config: es
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 34.221261828226936
- type: cos_sim_spearman
value: 49.811823238907664
- type: euclidean_pearson
value: 44.50394399762147
- type: euclidean_spearman
value: 50.959184495072876
- type: manhattan_pearson
value: 45.83191034038624
- type: manhattan_spearman
value: 50.190409866117946
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (pl)
config: pl
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 3.620381732096531
- type: cos_sim_spearman
value: 23.30843951799194
- type: euclidean_pearson
value: 0.965453312113125
- type: euclidean_spearman
value: 24.235967620790316
- type: manhattan_pearson
value: 1.4408922275701606
- type: manhattan_spearman
value: 25.161920137046096
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (tr)
config: tr
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 16.69489628726267
- type: cos_sim_spearman
value: 34.66348380997687
- type: euclidean_pearson
value: 29.415825529188606
- type: euclidean_spearman
value: 38.33011033170646
- type: manhattan_pearson
value: 31.23273195263394
- type: manhattan_spearman
value: 39.10055785755795
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (ar)
config: ar
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 9.134927430889528
- type: cos_sim_spearman
value: 28.18922448944151
- type: euclidean_pearson
value: 19.86814169549051
- type: euclidean_spearman
value: 27.519588644948627
- type: manhattan_pearson
value: 21.80949221238945
- type: manhattan_spearman
value: 28.25217200494078
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (ru)
config: ru
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 3.6386482942352085
- type: cos_sim_spearman
value: 9.068119621940966
- type: euclidean_pearson
value: 0.8123129118737714
- type: euclidean_spearman
value: 9.173672890166147
- type: manhattan_pearson
value: 0.754518899822658
- type: manhattan_spearman
value: 8.431719541986524
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh)
config: zh
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 2.972091574908432
- type: cos_sim_spearman
value: 25.48511383289232
- type: euclidean_pearson
value: 12.751569670148918
- type: euclidean_spearman
value: 24.940721642439286
- type: manhattan_pearson
value: 14.310238482989826
- type: manhattan_spearman
value: 24.69821216148647
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (fr)
config: fr
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 54.4745185734135
- type: cos_sim_spearman
value: 67.66493409568727
- type: euclidean_pearson
value: 60.13580336797049
- type: euclidean_spearman
value: 66.12319300814538
- type: manhattan_pearson
value: 60.816210368708155
- type: manhattan_spearman
value: 65.70010026716766
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-en)
config: de-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 49.37865412588201
- type: cos_sim_spearman
value: 53.07135629778897
- type: euclidean_pearson
value: 49.29201416711091
- type: euclidean_spearman
value: 50.54523702399645
- type: manhattan_pearson
value: 51.265764141268534
- type: manhattan_spearman
value: 51.979086403193605
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es-en)
config: es-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 44.925652392562135
- type: cos_sim_spearman
value: 49.51253904767726
- type: euclidean_pearson
value: 48.79346518897415
- type: euclidean_spearman
value: 51.47957870101565
- type: manhattan_pearson
value: 49.51314553898044
- type: manhattan_spearman
value: 51.895207893189166
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (it)
config: it
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 45.241690321111875
- type: cos_sim_spearman
value: 48.24795739512037
- type: euclidean_pearson
value: 49.22719494399897
- type: euclidean_spearman
value: 49.64102442042809
- type: manhattan_pearson
value: 49.497887732970256
- type: manhattan_spearman
value: 49.940515338096304
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (pl-en)
config: pl-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 36.42138324083909
- type: cos_sim_spearman
value: 36.79867489417801
- type: euclidean_pearson
value: 27.760612942610084
- type: euclidean_spearman
value: 29.140966500287625
- type: manhattan_pearson
value: 28.456674031350115
- type: manhattan_spearman
value: 27.46356370924497
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh-en)
config: zh-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 26.55350664089358
- type: cos_sim_spearman
value: 28.681707196975008
- type: euclidean_pearson
value: 12.613577889195138
- type: euclidean_spearman
value: 13.589493311702933
- type: manhattan_pearson
value: 11.640157427420958
- type: manhattan_spearman
value: 10.345223941212415
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es-it)
config: es-it
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 38.54682179114309
- type: cos_sim_spearman
value: 45.782560880405704
- type: euclidean_pearson
value: 46.496857002368486
- type: euclidean_spearman
value: 48.21270426410012
- type: manhattan_pearson
value: 46.871839119374044
- type: manhattan_spearman
value: 47.556987773851525
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-fr)
config: de-fr
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 35.12956772546032
- type: cos_sim_spearman
value: 32.96920218281008
- type: euclidean_pearson
value: 34.23140384382136
- type: euclidean_spearman
value: 32.19303153191447
- type: manhattan_pearson
value: 34.189468276600635
- type: manhattan_spearman
value: 34.887065709732376
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-pl)
config: de-pl
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 30.507667380509634
- type: cos_sim_spearman
value: 20.447284723752716
- type: euclidean_pearson
value: 29.662041381794474
- type: euclidean_spearman
value: 20.939990379746757
- type: manhattan_pearson
value: 32.5112080506328
- type: manhattan_spearman
value: 23.773047901712495
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (fr-pl)
config: fr-pl
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 71.10820459712156
- type: cos_sim_spearman
value: 61.97797868009122
- type: euclidean_pearson
value: 60.30910689156633
- type: euclidean_spearman
value: 61.97797868009122
- type: manhattan_pearson
value: 66.3405176964038
- type: manhattan_spearman
value: 61.97797868009122
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: 8913289635987208e6e7c72789e4be2fe94b6abd
metrics:
- type: cos_sim_pearson
value: 76.53032504460737
- type: cos_sim_spearman
value: 75.33716094627373
- type: euclidean_pearson
value: 69.64662673290599
- type: euclidean_spearman
value: 67.30188896368857
- type: manhattan_pearson
value: 69.45096082050807
- type: manhattan_spearman
value: 67.0718727259371
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: 56a6d0140cf6356659e2a7c1413286a774468d44
metrics:
- type: map
value: 71.33941904192648
- type: mrr
value: 89.73766429648782
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: a75ae049398addde9b70f6b268875f5cbce99089
metrics:
- type: map_at_1
value: 43.333
- type: map_at_10
value: 52.364
- type: map_at_100
value: 53.184
- type: map_at_1000
value: 53.234
- type: map_at_3
value: 49.832
- type: map_at_5
value: 51.244
- type: mrr_at_1
value: 45.333
- type: mrr_at_10
value: 53.455
- type: mrr_at_100
value: 54.191
- type: mrr_at_1000
value: 54.235
- type: mrr_at_3
value: 51.556000000000004
- type: mrr_at_5
value: 52.622
- type: ndcg_at_1
value: 45.333
- type: ndcg_at_10
value: 56.899
- type: ndcg_at_100
value: 60.702
- type: ndcg_at_1000
value: 62.046
- type: ndcg_at_3
value: 52.451
- type: ndcg_at_5
value: 54.534000000000006
- type: precision_at_1
value: 45.333
- type: precision_at_10
value: 7.8
- type: precision_at_100
value: 0.987
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 20.778
- type: precision_at_5
value: 13.866999999999999
- type: recall_at_1
value: 43.333
- type: recall_at_10
value: 69.69999999999999
- type: recall_at_100
value: 86.9
- type: recall_at_1000
value: 97.6
- type: recall_at_3
value: 57.81699999999999
- type: recall_at_5
value: 62.827999999999996
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
metrics:
- type: cos_sim_accuracy
value: 99.7
- type: cos_sim_ap
value: 89.88577913120001
- type: cos_sim_f1
value: 84.62694041061593
- type: cos_sim_precision
value: 84.7542627883651
- type: cos_sim_recall
value: 84.5
- type: dot_accuracy
value: 99.24752475247524
- type: dot_ap
value: 56.81855467290009
- type: dot_f1
value: 56.084126189283936
- type: dot_precision
value: 56.16850551654965
- type: dot_recall
value: 56.00000000000001
- type: euclidean_accuracy
value: 99.7059405940594
- type: euclidean_ap
value: 90.12451226491524
- type: euclidean_f1
value: 84.44211629125196
- type: euclidean_precision
value: 88.66886688668868
- type: euclidean_recall
value: 80.60000000000001
- type: manhattan_accuracy
value: 99.7128712871287
- type: manhattan_ap
value: 90.67590584183216
- type: manhattan_f1
value: 84.85436893203884
- type: manhattan_precision
value: 82.45283018867924
- type: manhattan_recall
value: 87.4
- type: max_accuracy
value: 99.7128712871287
- type: max_ap
value: 90.67590584183216
- type: max_f1
value: 84.85436893203884
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
metrics:
- type: v_measure
value: 52.74481093815175
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
metrics:
- type: v_measure
value: 32.65999453562101
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
metrics:
- type: map
value: 44.74498464555465
- type: mrr
value: 45.333879764026825
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
metrics:
- type: cos_sim_pearson
value: 29,603788751645216
- type: cos_sim_spearman
value: 29.705103354786033
- type: dot_pearson
value: 28.07425338095399
- type: dot_spearman
value: 26.841406359135366
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
metrics:
- type: map_at_1
value: 0.241
- type: map_at_10
value: 1.672
- type: map_at_100
value: 7.858999999999999
- type: map_at_1000
value: 17.616
- type: map_at_3
value: 0.631
- type: map_at_5
value: 0.968
- type: mrr_at_1
value: 90
- type: mrr_at_10
value: 92.952
- type: mrr_at_100
value: 93.036
- type: mrr_at_1000
value: 93.036
- type: mrr_at_3
value: 92.667
- type: mrr_at_5
value: 92.667
- type: ndcg_at_1
value: 83
- type: ndcg_at_10
value: 70.30199999999999
- type: ndcg_at_100
value: 48.149
- type: ndcg_at_1000
value: 40.709
- type: ndcg_at_3
value: 79.173
- type: ndcg_at_5
value: 75.347
- type: precision_at_1
value: 90
- type: precision_at_10
value: 72.6
- type: precision_at_100
value: 48.46
- type: precision_at_1000
value: 18.093999999999998
- type: precision_at_3
value: 84
- type: precision_at_5
value: 78.8
- type: recall_at_1
value: 0.241
- type: recall_at_10
value: 1.814
- type: recall_at_100
value: 11.141
- type: recall_at_1000
value: 37.708999999999996
- type: recall_at_3
value: 0.647
- type: recall_at_5
value: 1.015
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
metrics:
- type: map_at_1
value: 2.782
- type: map_at_10
value: 9.06
- type: map_at_100
value: 14.571000000000002
- type: map_at_1000
value: 16.006999999999998
- type: map_at_3
value: 5.037
- type: map_at_5
value: 6.63
- type: mrr_at_1
value: 34.694
- type: mrr_at_10
value: 48.243
- type: mrr_at_100
value: 49.065
- type: mrr_at_1000
value: 49.065
- type: mrr_at_3
value: 44.897999999999996
- type: mrr_at_5
value: 46.428999999999995
- type: ndcg_at_1
value: 31.633
- type: ndcg_at_10
value: 22.972
- type: ndcg_at_100
value: 34.777
- type: ndcg_at_1000
value: 45.639
- type: ndcg_at_3
value: 26.398
- type: ndcg_at_5
value: 24.418
- type: precision_at_1
value: 34.694
- type: precision_at_10
value: 19.796
- type: precision_at_100
value: 7.224
- type: precision_at_1000
value: 1.4449999999999998
- type: precision_at_3
value: 26.531
- type: precision_at_5
value: 23.265
- type: recall_at_1
value: 2.782
- type: recall_at_10
value: 14.841
- type: recall_at_100
value: 44.86
- type: recall_at_1000
value: 78.227
- type: recall_at_3
value: 5.959
- type: recall_at_5
value: 8.969000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 62.657999999999994
- type: ap
value: 10.96353161716344
- type: f1
value: 48.294226423442645
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: 62146448f05be9e52a36b8ee9936447ea787eede
metrics:
- type: accuracy
value: 52.40803621958121
- type: f1
value: 52.61009636022186
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
metrics:
- type: v_measure
value: 32.12697126747911
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 80.69976753889253
- type: cos_sim_ap
value: 54.74680676121268
- type: cos_sim_f1
value: 53.18923998590391
- type: cos_sim_precision
value: 47.93563413084904
- type: cos_sim_recall
value: 59.73614775725594
- type: dot_accuracy
value: 79.3348036001669
- type: dot_ap
value: 48.46902128933627
- type: dot_f1
value: 50.480109739369006
- type: dot_precision
value: 42.06084051345173
- type: dot_recall
value: 63.113456464379944
- type: euclidean_accuracy
value: 79.78780473266973
- type: euclidean_ap
value: 50.258327255164815
- type: euclidean_f1
value: 49.655838666827684
- type: euclidean_precision
value: 45.78044978846582
- type: euclidean_recall
value: 54.24802110817942
- type: manhattan_accuracy
value: 79.76992310901831
- type: manhattan_ap
value: 49.89892485714363
- type: manhattan_f1
value: 49.330433787341185
- type: manhattan_precision
value: 43.56175459874672
- type: manhattan_recall
value: 56.86015831134564
- type: max_accuracy
value: 80.69976753889253
- type: max_ap
value: 54.74680676121268
- type: max_f1
value: 53.18923998590391
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 86.90573213800597
- type: cos_sim_ap
value: 81.05760818661524
- type: cos_sim_f1
value: 73.64688856729379
- type: cos_sim_precision
value: 69.46491946491946
- type: cos_sim_recall
value: 78.3646442870342
- type: dot_accuracy
value: 83.80680715644041
- type: dot_ap
value: 72.49774005947461
- type: dot_f1
value: 68.68460650173216
- type: dot_precision
value: 62.954647507858105
- type: dot_recall
value: 75.56205728364644
- type: euclidean_accuracy
value: 85.97430822369697
- type: euclidean_ap
value: 78.86101740829326
- type: euclidean_f1
value: 71.07960824663695
- type: euclidean_precision
value: 70.36897306270279
- type: euclidean_recall
value: 71.8047428395442
- type: manhattan_accuracy
value: 85.94132029339853
- type: manhattan_ap
value: 78.77876711171923
- type: manhattan_f1
value: 71.07869075515912
- type: manhattan_precision
value: 69.80697847067557
- type: manhattan_recall
value: 72.39759778256852
- type: max_accuracy
value: 86.90573213800597
- type: max_ap
value: 81.05760818661524
- type: max_f1
value: 73.64688856729379
SGPT-125M-weightedmean-msmarco-specb-bitfit
Usage
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt
Evaluation Results
For eval results, refer to the eval folder or our paper: https://arxiv.org/abs/2202.08904
Training
The model was trained with the parameters:
DataLoader:
torch.utils.data.dataloader.DataLoader of length 15600 with parameters:
{'batch_size': 32, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
Loss:
sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss with parameters:
{'scale': 20.0, 'similarity_fct': 'cos_sim'}
Parameters of the fit()-Method:
{
"epochs": 10,
"evaluation_steps": 0,
"evaluator": "NoneType",
"max_grad_norm": 1,
"optimizer_class": "<class 'transformers.optimization.AdamW'>",
"optimizer_params": {
"lr": 0.0002
},
"scheduler": "WarmupLinear",
"steps_per_epoch": null,
"warmup_steps": 1000,
"weight_decay": 0.01
}
Full Model Architecture
SentenceTransformer(
(0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: GPTNeoModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False})
)
Citing & Authors
@article{muennighoff2022sgpt,
title={SGPT: GPT Sentence Embeddings for Semantic Search},
author={Muennighoff, Niklas},
journal={arXiv preprint arXiv:2202.08904},
year={2022}
}