metadata
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: SGPT-5.8B-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: 69.22388059701493
- type: ap
value: 32.04724673950256
- type: f1
value: 63.25719825770428
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
metrics:
- type: accuracy
value: 71.26109999999998
- type: ap
value: 66.16336378255403
- type: f1
value: 70.89719145825303
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 39.19199999999999
- type: f1
value: 38.580766731113826
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
metrics:
- type: map_at_1
value: 27.311999999999998
- type: map_at_10
value: 42.620000000000005
- type: map_at_100
value: 43.707
- type: map_at_1000
value: 43.714999999999996
- type: map_at_3
value: 37.624
- type: map_at_5
value: 40.498
- type: mrr_at_1
value: 27.667
- type: mrr_at_10
value: 42.737
- type: mrr_at_100
value: 43.823
- type: mrr_at_1000
value: 43.830999999999996
- type: mrr_at_3
value: 37.743
- type: mrr_at_5
value: 40.616
- type: ndcg_at_1
value: 27.311999999999998
- type: ndcg_at_10
value: 51.37500000000001
- type: ndcg_at_100
value: 55.778000000000006
- type: ndcg_at_1000
value: 55.96600000000001
- type: ndcg_at_3
value: 41.087
- type: ndcg_at_5
value: 46.269
- type: precision_at_1
value: 27.311999999999998
- type: precision_at_10
value: 7.945
- type: precision_at_100
value: 0.9820000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 17.046
- type: precision_at_5
value: 12.745000000000001
- type: recall_at_1
value: 27.311999999999998
- type: recall_at_10
value: 79.445
- type: recall_at_100
value: 98.151
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 51.13799999999999
- type: recall_at_5
value: 63.727000000000004
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
metrics:
- type: v_measure
value: 45.59037428592033
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
metrics:
- type: v_measure
value: 38.86371701986363
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
metrics:
- type: map
value: 61.625568691427766
- type: mrr
value: 75.83256386580486
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: 9ee918f184421b6bd48b78f6c714d86546106103
metrics:
- type: cos_sim_pearson
value: 89.96074355094802
- type: cos_sim_spearman
value: 86.2501580394454
- type: euclidean_pearson
value: 82.18427440380462
- type: euclidean_spearman
value: 80.14760935017947
- type: manhattan_pearson
value: 82.24621578156392
- type: manhattan_spearman
value: 80.00363016590163
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
metrics:
- type: accuracy
value: 84.49350649350649
- type: f1
value: 84.4249343233736
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
metrics:
- type: v_measure
value: 36.551459722989385
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
metrics:
- type: v_measure
value: 33.69901851846774
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 30.499
- type: map_at_10
value: 41.208
- type: map_at_100
value: 42.638
- type: map_at_1000
value: 42.754
- type: map_at_3
value: 37.506
- type: map_at_5
value: 39.422000000000004
- type: mrr_at_1
value: 37.339
- type: mrr_at_10
value: 47.051
- type: mrr_at_100
value: 47.745
- type: mrr_at_1000
value: 47.786
- type: mrr_at_3
value: 44.086999999999996
- type: mrr_at_5
value: 45.711
- type: ndcg_at_1
value: 37.339
- type: ndcg_at_10
value: 47.666
- type: ndcg_at_100
value: 52.994
- type: ndcg_at_1000
value: 54.928999999999995
- type: ndcg_at_3
value: 41.982
- type: ndcg_at_5
value: 44.42
- type: precision_at_1
value: 37.339
- type: precision_at_10
value: 9.127
- type: precision_at_100
value: 1.4749999999999999
- type: precision_at_1000
value: 0.194
- type: precision_at_3
value: 20.076
- type: precision_at_5
value: 14.449000000000002
- type: recall_at_1
value: 30.499
- type: recall_at_10
value: 60.328
- type: recall_at_100
value: 82.57900000000001
- type: recall_at_1000
value: 95.074
- type: recall_at_3
value: 44.17
- type: recall_at_5
value: 50.94
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 30.613
- type: map_at_10
value: 40.781
- type: map_at_100
value: 42.018
- type: map_at_1000
value: 42.132999999999996
- type: map_at_3
value: 37.816
- type: map_at_5
value: 39.389
- type: mrr_at_1
value: 38.408
- type: mrr_at_10
value: 46.631
- type: mrr_at_100
value: 47.332
- type: mrr_at_1000
value: 47.368
- type: mrr_at_3
value: 44.384
- type: mrr_at_5
value: 45.661
- type: ndcg_at_1
value: 38.408
- type: ndcg_at_10
value: 46.379999999999995
- type: ndcg_at_100
value: 50.81
- type: ndcg_at_1000
value: 52.663000000000004
- type: ndcg_at_3
value: 42.18
- type: ndcg_at_5
value: 43.974000000000004
- type: precision_at_1
value: 38.408
- type: precision_at_10
value: 8.656
- type: precision_at_100
value: 1.3860000000000001
- type: precision_at_1000
value: 0.184
- type: precision_at_3
value: 20.276
- type: precision_at_5
value: 14.241999999999999
- type: recall_at_1
value: 30.613
- type: recall_at_10
value: 56.44
- type: recall_at_100
value: 75.044
- type: recall_at_1000
value: 86.426
- type: recall_at_3
value: 43.766
- type: recall_at_5
value: 48.998000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 37.370999999999995
- type: map_at_10
value: 49.718
- type: map_at_100
value: 50.737
- type: map_at_1000
value: 50.79
- type: map_at_3
value: 46.231
- type: map_at_5
value: 48.329
- type: mrr_at_1
value: 42.884
- type: mrr_at_10
value: 53.176
- type: mrr_at_100
value: 53.81700000000001
- type: mrr_at_1000
value: 53.845
- type: mrr_at_3
value: 50.199000000000005
- type: mrr_at_5
value: 52.129999999999995
- type: ndcg_at_1
value: 42.884
- type: ndcg_at_10
value: 55.826
- type: ndcg_at_100
value: 59.93000000000001
- type: ndcg_at_1000
value: 61.013
- type: ndcg_at_3
value: 49.764
- type: ndcg_at_5
value: 53.025999999999996
- type: precision_at_1
value: 42.884
- type: precision_at_10
value: 9.046999999999999
- type: precision_at_100
value: 1.212
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 22.131999999999998
- type: precision_at_5
value: 15.524
- type: recall_at_1
value: 37.370999999999995
- type: recall_at_10
value: 70.482
- type: recall_at_100
value: 88.425
- type: recall_at_1000
value: 96.03399999999999
- type: recall_at_3
value: 54.43
- type: recall_at_5
value: 62.327999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 22.875999999999998
- type: map_at_10
value: 31.715
- type: map_at_100
value: 32.847
- type: map_at_1000
value: 32.922000000000004
- type: map_at_3
value: 29.049999999999997
- type: map_at_5
value: 30.396
- type: mrr_at_1
value: 24.52
- type: mrr_at_10
value: 33.497
- type: mrr_at_100
value: 34.455000000000005
- type: mrr_at_1000
value: 34.510000000000005
- type: mrr_at_3
value: 30.791
- type: mrr_at_5
value: 32.175
- type: ndcg_at_1
value: 24.52
- type: ndcg_at_10
value: 36.95
- type: ndcg_at_100
value: 42.238
- type: ndcg_at_1000
value: 44.147999999999996
- type: ndcg_at_3
value: 31.435000000000002
- type: ndcg_at_5
value: 33.839000000000006
- type: precision_at_1
value: 24.52
- type: precision_at_10
value: 5.9319999999999995
- type: precision_at_100
value: 0.901
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 13.446
- type: precision_at_5
value: 9.469
- type: recall_at_1
value: 22.875999999999998
- type: recall_at_10
value: 51.38
- type: recall_at_100
value: 75.31099999999999
- type: recall_at_1000
value: 89.718
- type: recall_at_3
value: 36.26
- type: recall_at_5
value: 42.248999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 14.984
- type: map_at_10
value: 23.457
- type: map_at_100
value: 24.723
- type: map_at_1000
value: 24.846
- type: map_at_3
value: 20.873
- type: map_at_5
value: 22.357
- type: mrr_at_1
value: 18.159
- type: mrr_at_10
value: 27.431
- type: mrr_at_100
value: 28.449
- type: mrr_at_1000
value: 28.52
- type: mrr_at_3
value: 24.979000000000003
- type: mrr_at_5
value: 26.447
- type: ndcg_at_1
value: 18.159
- type: ndcg_at_10
value: 28.627999999999997
- type: ndcg_at_100
value: 34.741
- type: ndcg_at_1000
value: 37.516
- type: ndcg_at_3
value: 23.902
- type: ndcg_at_5
value: 26.294
- type: precision_at_1
value: 18.159
- type: precision_at_10
value: 5.485
- type: precision_at_100
value: 0.985
- type: precision_at_1000
value: 0.136
- type: precision_at_3
value: 11.774
- type: precision_at_5
value: 8.731
- type: recall_at_1
value: 14.984
- type: recall_at_10
value: 40.198
- type: recall_at_100
value: 67.11500000000001
- type: recall_at_1000
value: 86.497
- type: recall_at_3
value: 27.639000000000003
- type: recall_at_5
value: 33.595000000000006
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 29.067
- type: map_at_10
value: 39.457
- type: map_at_100
value: 40.83
- type: map_at_1000
value: 40.94
- type: map_at_3
value: 35.995
- type: map_at_5
value: 38.159
- type: mrr_at_1
value: 34.937000000000005
- type: mrr_at_10
value: 44.755
- type: mrr_at_100
value: 45.549
- type: mrr_at_1000
value: 45.589
- type: mrr_at_3
value: 41.947
- type: mrr_at_5
value: 43.733
- type: ndcg_at_1
value: 34.937000000000005
- type: ndcg_at_10
value: 45.573
- type: ndcg_at_100
value: 51.266999999999996
- type: ndcg_at_1000
value: 53.184
- type: ndcg_at_3
value: 39.961999999999996
- type: ndcg_at_5
value: 43.02
- type: precision_at_1
value: 34.937000000000005
- type: precision_at_10
value: 8.296000000000001
- type: precision_at_100
value: 1.32
- type: precision_at_1000
value: 0.167
- type: precision_at_3
value: 18.8
- type: precision_at_5
value: 13.763
- type: recall_at_1
value: 29.067
- type: recall_at_10
value: 58.298
- type: recall_at_100
value: 82.25099999999999
- type: recall_at_1000
value: 94.476
- type: recall_at_3
value: 42.984
- type: recall_at_5
value: 50.658
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 25.985999999999997
- type: map_at_10
value: 35.746
- type: map_at_100
value: 37.067
- type: map_at_1000
value: 37.191
- type: map_at_3
value: 32.599000000000004
- type: map_at_5
value: 34.239000000000004
- type: mrr_at_1
value: 31.735000000000003
- type: mrr_at_10
value: 40.515
- type: mrr_at_100
value: 41.459
- type: mrr_at_1000
value: 41.516
- type: mrr_at_3
value: 37.938
- type: mrr_at_5
value: 39.25
- type: ndcg_at_1
value: 31.735000000000003
- type: ndcg_at_10
value: 41.484
- type: ndcg_at_100
value: 47.047
- type: ndcg_at_1000
value: 49.427
- type: ndcg_at_3
value: 36.254999999999995
- type: ndcg_at_5
value: 38.375
- type: precision_at_1
value: 31.735000000000003
- type: precision_at_10
value: 7.66
- type: precision_at_100
value: 1.234
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 17.427999999999997
- type: precision_at_5
value: 12.328999999999999
- type: recall_at_1
value: 25.985999999999997
- type: recall_at_10
value: 53.761
- type: recall_at_100
value: 77.149
- type: recall_at_1000
value: 93.342
- type: recall_at_3
value: 39.068000000000005
- type: recall_at_5
value: 44.693
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 24.949749999999998
- type: map_at_10
value: 34.04991666666667
- type: map_at_100
value: 35.26825
- type: map_at_1000
value: 35.38316666666667
- type: map_at_3
value: 31.181333333333335
- type: map_at_5
value: 32.77391666666667
- type: mrr_at_1
value: 29.402833333333334
- type: mrr_at_10
value: 38.01633333333333
- type: mrr_at_100
value: 38.88033333333334
- type: mrr_at_1000
value: 38.938500000000005
- type: mrr_at_3
value: 35.5175
- type: mrr_at_5
value: 36.93808333333333
- type: ndcg_at_1
value: 29.402833333333334
- type: ndcg_at_10
value: 39.403166666666664
- type: ndcg_at_100
value: 44.66408333333333
- type: ndcg_at_1000
value: 46.96283333333333
- type: ndcg_at_3
value: 34.46633333333334
- type: ndcg_at_5
value: 36.78441666666667
- type: precision_at_1
value: 29.402833333333334
- type: precision_at_10
value: 6.965833333333333
- type: precision_at_100
value: 1.1330833333333334
- type: precision_at_1000
value: 0.15158333333333335
- type: precision_at_3
value: 15.886666666666665
- type: precision_at_5
value: 11.360416666666667
- type: recall_at_1
value: 24.949749999999998
- type: recall_at_10
value: 51.29325
- type: recall_at_100
value: 74.3695
- type: recall_at_1000
value: 90.31299999999999
- type: recall_at_3
value: 37.580083333333334
- type: recall_at_5
value: 43.529666666666664
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 22.081999999999997
- type: map_at_10
value: 29.215999999999998
- type: map_at_100
value: 30.163
- type: map_at_1000
value: 30.269000000000002
- type: map_at_3
value: 26.942
- type: map_at_5
value: 28.236
- type: mrr_at_1
value: 24.847
- type: mrr_at_10
value: 31.918999999999997
- type: mrr_at_100
value: 32.817
- type: mrr_at_1000
value: 32.897
- type: mrr_at_3
value: 29.831000000000003
- type: mrr_at_5
value: 31.019999999999996
- type: ndcg_at_1
value: 24.847
- type: ndcg_at_10
value: 33.4
- type: ndcg_at_100
value: 38.354
- type: ndcg_at_1000
value: 41.045
- type: ndcg_at_3
value: 29.236
- type: ndcg_at_5
value: 31.258000000000003
- type: precision_at_1
value: 24.847
- type: precision_at_10
value: 5.353
- type: precision_at_100
value: 0.853
- type: precision_at_1000
value: 0.116
- type: precision_at_3
value: 12.679000000000002
- type: precision_at_5
value: 8.988
- type: recall_at_1
value: 22.081999999999997
- type: recall_at_10
value: 43.505
- type: recall_at_100
value: 66.45400000000001
- type: recall_at_1000
value: 86.378
- type: recall_at_3
value: 32.163000000000004
- type: recall_at_5
value: 37.059999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 15.540000000000001
- type: map_at_10
value: 22.362000000000002
- type: map_at_100
value: 23.435
- type: map_at_1000
value: 23.564
- type: map_at_3
value: 20.143
- type: map_at_5
value: 21.324
- type: mrr_at_1
value: 18.892
- type: mrr_at_10
value: 25.942999999999998
- type: mrr_at_100
value: 26.883000000000003
- type: mrr_at_1000
value: 26.968999999999998
- type: mrr_at_3
value: 23.727
- type: mrr_at_5
value: 24.923000000000002
- type: ndcg_at_1
value: 18.892
- type: ndcg_at_10
value: 26.811
- type: ndcg_at_100
value: 32.066
- type: ndcg_at_1000
value: 35.166
- type: ndcg_at_3
value: 22.706
- type: ndcg_at_5
value: 24.508
- type: precision_at_1
value: 18.892
- type: precision_at_10
value: 4.942
- type: precision_at_100
value: 0.878
- type: precision_at_1000
value: 0.131
- type: precision_at_3
value: 10.748000000000001
- type: precision_at_5
value: 7.784000000000001
- type: recall_at_1
value: 15.540000000000001
- type: recall_at_10
value: 36.742999999999995
- type: recall_at_100
value: 60.525
- type: recall_at_1000
value: 82.57600000000001
- type: recall_at_3
value: 25.252000000000002
- type: recall_at_5
value: 29.872
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 24.453
- type: map_at_10
value: 33.363
- type: map_at_100
value: 34.579
- type: map_at_1000
value: 34.686
- type: map_at_3
value: 30.583
- type: map_at_5
value: 32.118
- type: mrr_at_1
value: 28.918
- type: mrr_at_10
value: 37.675
- type: mrr_at_100
value: 38.567
- type: mrr_at_1000
value: 38.632
- type: mrr_at_3
value: 35.260999999999996
- type: mrr_at_5
value: 36.576
- type: ndcg_at_1
value: 28.918
- type: ndcg_at_10
value: 38.736
- type: ndcg_at_100
value: 44.261
- type: ndcg_at_1000
value: 46.72
- type: ndcg_at_3
value: 33.81
- type: ndcg_at_5
value: 36.009
- type: precision_at_1
value: 28.918
- type: precision_at_10
value: 6.586
- type: precision_at_100
value: 1.047
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 15.360999999999999
- type: precision_at_5
value: 10.857999999999999
- type: recall_at_1
value: 24.453
- type: recall_at_10
value: 50.885999999999996
- type: recall_at_100
value: 75.03
- type: recall_at_1000
value: 92.123
- type: recall_at_3
value: 37.138
- type: recall_at_5
value: 42.864999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 24.57
- type: map_at_10
value: 33.672000000000004
- type: map_at_100
value: 35.244
- type: map_at_1000
value: 35.467
- type: map_at_3
value: 30.712
- type: map_at_5
value: 32.383
- type: mrr_at_1
value: 29.644
- type: mrr_at_10
value: 38.344
- type: mrr_at_100
value: 39.219
- type: mrr_at_1000
value: 39.282000000000004
- type: mrr_at_3
value: 35.771
- type: mrr_at_5
value: 37.273
- type: ndcg_at_1
value: 29.644
- type: ndcg_at_10
value: 39.567
- type: ndcg_at_100
value: 45.097
- type: ndcg_at_1000
value: 47.923
- type: ndcg_at_3
value: 34.768
- type: ndcg_at_5
value: 37.122
- type: precision_at_1
value: 29.644
- type: precision_at_10
value: 7.5889999999999995
- type: precision_at_100
value: 1.478
- type: precision_at_1000
value: 0.23500000000000001
- type: precision_at_3
value: 16.337
- type: precision_at_5
value: 12.055
- type: recall_at_1
value: 24.57
- type: recall_at_10
value: 51.00900000000001
- type: recall_at_100
value: 75.423
- type: recall_at_1000
value: 93.671
- type: recall_at_3
value: 36.925999999999995
- type: recall_at_5
value: 43.245
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 21.356
- type: map_at_10
value: 27.904
- type: map_at_100
value: 28.938000000000002
- type: map_at_1000
value: 29.036
- type: map_at_3
value: 25.726
- type: map_at_5
value: 26.935
- type: mrr_at_1
value: 22.551
- type: mrr_at_10
value: 29.259
- type: mrr_at_100
value: 30.272
- type: mrr_at_1000
value: 30.348000000000003
- type: mrr_at_3
value: 27.295
- type: mrr_at_5
value: 28.358
- type: ndcg_at_1
value: 22.551
- type: ndcg_at_10
value: 31.817
- type: ndcg_at_100
value: 37.164
- type: ndcg_at_1000
value: 39.82
- type: ndcg_at_3
value: 27.595999999999997
- type: ndcg_at_5
value: 29.568
- type: precision_at_1
value: 22.551
- type: precision_at_10
value: 4.917
- type: precision_at_100
value: 0.828
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 11.583
- type: precision_at_5
value: 8.133
- type: recall_at_1
value: 21.356
- type: recall_at_10
value: 42.489
- type: recall_at_100
value: 67.128
- type: recall_at_1000
value: 87.441
- type: recall_at_3
value: 31.165
- type: recall_at_5
value: 35.853
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
metrics:
- type: map_at_1
value: 12.306000000000001
- type: map_at_10
value: 21.523
- type: map_at_100
value: 23.358
- type: map_at_1000
value: 23.541
- type: map_at_3
value: 17.809
- type: map_at_5
value: 19.631
- type: mrr_at_1
value: 27.948
- type: mrr_at_10
value: 40.355000000000004
- type: mrr_at_100
value: 41.166000000000004
- type: mrr_at_1000
value: 41.203
- type: mrr_at_3
value: 36.819
- type: mrr_at_5
value: 38.958999999999996
- type: ndcg_at_1
value: 27.948
- type: ndcg_at_10
value: 30.462
- type: ndcg_at_100
value: 37.473
- type: ndcg_at_1000
value: 40.717999999999996
- type: ndcg_at_3
value: 24.646
- type: ndcg_at_5
value: 26.642
- type: precision_at_1
value: 27.948
- type: precision_at_10
value: 9.648
- type: precision_at_100
value: 1.7239999999999998
- type: precision_at_1000
value: 0.232
- type: precision_at_3
value: 18.48
- type: precision_at_5
value: 14.293
- type: recall_at_1
value: 12.306000000000001
- type: recall_at_10
value: 37.181
- type: recall_at_100
value: 61.148
- type: recall_at_1000
value: 79.401
- type: recall_at_3
value: 22.883
- type: recall_at_5
value: 28.59
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: f097057d03ed98220bc7309ddb10b71a54d667d6
metrics:
- type: map_at_1
value: 9.357
- type: map_at_10
value: 18.849
- type: map_at_100
value: 25.369000000000003
- type: map_at_1000
value: 26.950000000000003
- type: map_at_3
value: 13.625000000000002
- type: map_at_5
value: 15.956999999999999
- type: mrr_at_1
value: 67.75
- type: mrr_at_10
value: 74.734
- type: mrr_at_100
value: 75.1
- type: mrr_at_1000
value: 75.10900000000001
- type: mrr_at_3
value: 73.542
- type: mrr_at_5
value: 74.167
- type: ndcg_at_1
value: 55.375
- type: ndcg_at_10
value: 39.873999999999995
- type: ndcg_at_100
value: 43.098
- type: ndcg_at_1000
value: 50.69200000000001
- type: ndcg_at_3
value: 44.856
- type: ndcg_at_5
value: 42.138999999999996
- type: precision_at_1
value: 67.75
- type: precision_at_10
value: 31.1
- type: precision_at_100
value: 9.303
- type: precision_at_1000
value: 2.0060000000000002
- type: precision_at_3
value: 48.25
- type: precision_at_5
value: 40.949999999999996
- type: recall_at_1
value: 9.357
- type: recall_at_10
value: 23.832
- type: recall_at_100
value: 47.906
- type: recall_at_1000
value: 71.309
- type: recall_at_3
value: 14.512
- type: recall_at_5
value: 18.3
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 829147f8f75a25f005913200eb5ed41fae320aa1
metrics:
- type: accuracy
value: 49.655
- type: f1
value: 45.51976190938951
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
metrics:
- type: map_at_1
value: 62.739999999999995
- type: map_at_10
value: 73.07000000000001
- type: map_at_100
value: 73.398
- type: map_at_1000
value: 73.41
- type: map_at_3
value: 71.33800000000001
- type: map_at_5
value: 72.423
- type: mrr_at_1
value: 67.777
- type: mrr_at_10
value: 77.873
- type: mrr_at_100
value: 78.091
- type: mrr_at_1000
value: 78.094
- type: mrr_at_3
value: 76.375
- type: mrr_at_5
value: 77.316
- type: ndcg_at_1
value: 67.777
- type: ndcg_at_10
value: 78.24
- type: ndcg_at_100
value: 79.557
- type: ndcg_at_1000
value: 79.814
- type: ndcg_at_3
value: 75.125
- type: ndcg_at_5
value: 76.834
- type: precision_at_1
value: 67.777
- type: precision_at_10
value: 9.832
- type: precision_at_100
value: 1.061
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 29.433
- type: precision_at_5
value: 18.665000000000003
- type: recall_at_1
value: 62.739999999999995
- type: recall_at_10
value: 89.505
- type: recall_at_100
value: 95.102
- type: recall_at_1000
value: 96.825
- type: recall_at_3
value: 81.028
- type: recall_at_5
value: 85.28099999999999
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
metrics:
- type: map_at_1
value: 18.467
- type: map_at_10
value: 30.020999999999997
- type: map_at_100
value: 31.739
- type: map_at_1000
value: 31.934
- type: map_at_3
value: 26.003
- type: map_at_5
value: 28.338
- type: mrr_at_1
value: 35.339999999999996
- type: mrr_at_10
value: 44.108999999999995
- type: mrr_at_100
value: 44.993
- type: mrr_at_1000
value: 45.042
- type: mrr_at_3
value: 41.667
- type: mrr_at_5
value: 43.14
- type: ndcg_at_1
value: 35.339999999999996
- type: ndcg_at_10
value: 37.202
- type: ndcg_at_100
value: 43.852999999999994
- type: ndcg_at_1000
value: 47.235
- type: ndcg_at_3
value: 33.5
- type: ndcg_at_5
value: 34.985
- type: precision_at_1
value: 35.339999999999996
- type: precision_at_10
value: 10.247
- type: precision_at_100
value: 1.7149999999999999
- type: precision_at_1000
value: 0.232
- type: precision_at_3
value: 22.222
- type: precision_at_5
value: 16.573999999999998
- type: recall_at_1
value: 18.467
- type: recall_at_10
value: 44.080999999999996
- type: recall_at_100
value: 68.72200000000001
- type: recall_at_1000
value: 89.087
- type: recall_at_3
value: 30.567
- type: recall_at_5
value: 36.982
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
metrics:
- type: map_at_1
value: 35.726
- type: map_at_10
value: 50.207
- type: map_at_100
value: 51.05499999999999
- type: map_at_1000
value: 51.12799999999999
- type: map_at_3
value: 47.576
- type: map_at_5
value: 49.172
- type: mrr_at_1
value: 71.452
- type: mrr_at_10
value: 77.41900000000001
- type: mrr_at_100
value: 77.711
- type: mrr_at_1000
value: 77.723
- type: mrr_at_3
value: 76.39399999999999
- type: mrr_at_5
value: 77.00099999999999
- type: ndcg_at_1
value: 71.452
- type: ndcg_at_10
value: 59.260999999999996
- type: ndcg_at_100
value: 62.424
- type: ndcg_at_1000
value: 63.951
- type: ndcg_at_3
value: 55.327000000000005
- type: ndcg_at_5
value: 57.416999999999994
- type: precision_at_1
value: 71.452
- type: precision_at_10
value: 12.061
- type: precision_at_100
value: 1.455
- type: precision_at_1000
value: 0.166
- type: precision_at_3
value: 34.36
- type: precision_at_5
value: 22.266
- type: recall_at_1
value: 35.726
- type: recall_at_10
value: 60.304
- type: recall_at_100
value: 72.75500000000001
- type: recall_at_1000
value: 82.978
- type: recall_at_3
value: 51.54
- type: recall_at_5
value: 55.665
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
metrics:
- type: accuracy
value: 66.63759999999999
- type: ap
value: 61.48938261286748
- type: f1
value: 66.35089269264965
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: validation
revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
metrics:
- type: map_at_1
value: 20.842
- type: map_at_10
value: 32.992
- type: map_at_100
value: 34.236
- type: map_at_1000
value: 34.286
- type: map_at_3
value: 29.049000000000003
- type: map_at_5
value: 31.391999999999996
- type: mrr_at_1
value: 21.375
- type: mrr_at_10
value: 33.581
- type: mrr_at_100
value: 34.760000000000005
- type: mrr_at_1000
value: 34.803
- type: mrr_at_3
value: 29.704000000000004
- type: mrr_at_5
value: 32.015
- type: ndcg_at_1
value: 21.375
- type: ndcg_at_10
value: 39.905
- type: ndcg_at_100
value: 45.843
- type: ndcg_at_1000
value: 47.083999999999996
- type: ndcg_at_3
value: 31.918999999999997
- type: ndcg_at_5
value: 36.107
- type: precision_at_1
value: 21.375
- type: precision_at_10
value: 6.393
- type: precision_at_100
value: 0.935
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 13.663
- type: precision_at_5
value: 10.324
- type: recall_at_1
value: 20.842
- type: recall_at_10
value: 61.17
- type: recall_at_100
value: 88.518
- type: recall_at_1000
value: 97.993
- type: recall_at_3
value: 39.571
- type: recall_at_5
value: 49.653999999999996
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 93.46557227542178
- type: f1
value: 92.87345917772146
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: 6299947a7777084cc2d4b64235bf7190381ce755
metrics:
- type: accuracy
value: 72.42134062927497
- type: f1
value: 55.03624810959269
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
metrics:
- type: accuracy
value: 70.3866845998655
- type: f1
value: 68.9674519872921
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 76.27774041694687
- type: f1
value: 76.72936190462792
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: dcefc037ef84348e49b0d29109e891c01067226b
metrics:
- type: v_measure
value: 31.511745925773337
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc
metrics:
- type: v_measure
value: 28.764235987575365
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.29353136386601
- type: mrr
value: 33.536774455851685
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610
metrics:
- type: map_at_1
value: 5.702
- type: map_at_10
value: 13.642000000000001
- type: map_at_100
value: 17.503
- type: map_at_1000
value: 19.126
- type: map_at_3
value: 9.748
- type: map_at_5
value: 11.642
- type: mrr_at_1
value: 45.82
- type: mrr_at_10
value: 54.821
- type: mrr_at_100
value: 55.422000000000004
- type: mrr_at_1000
value: 55.452999999999996
- type: mrr_at_3
value: 52.373999999999995
- type: mrr_at_5
value: 53.937000000000005
- type: ndcg_at_1
value: 44.272
- type: ndcg_at_10
value: 36.213
- type: ndcg_at_100
value: 33.829
- type: ndcg_at_1000
value: 42.557
- type: ndcg_at_3
value: 40.814
- type: ndcg_at_5
value: 39.562000000000005
- type: precision_at_1
value: 45.511
- type: precision_at_10
value: 27.214
- type: precision_at_100
value: 8.941
- type: precision_at_1000
value: 2.1870000000000003
- type: precision_at_3
value: 37.874
- type: precision_at_5
value: 34.489
- type: recall_at_1
value: 5.702
- type: recall_at_10
value: 17.638
- type: recall_at_100
value: 34.419
- type: recall_at_1000
value: 66.41
- type: recall_at_3
value: 10.914
- type: recall_at_5
value: 14.032
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c
metrics:
- type: map_at_1
value: 30.567
- type: map_at_10
value: 45.01
- type: map_at_100
value: 46.091
- type: map_at_1000
value: 46.126
- type: map_at_3
value: 40.897
- type: map_at_5
value: 43.301
- type: mrr_at_1
value: 34.56
- type: mrr_at_10
value: 47.725
- type: mrr_at_100
value: 48.548
- type: mrr_at_1000
value: 48.571999999999996
- type: mrr_at_3
value: 44.361
- type: mrr_at_5
value: 46.351
- type: ndcg_at_1
value: 34.531
- type: ndcg_at_10
value: 52.410000000000004
- type: ndcg_at_100
value: 56.999
- type: ndcg_at_1000
value: 57.830999999999996
- type: ndcg_at_3
value: 44.734
- type: ndcg_at_5
value: 48.701
- type: precision_at_1
value: 34.531
- type: precision_at_10
value: 8.612
- type: precision_at_100
value: 1.118
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 20.307
- type: precision_at_5
value: 14.519000000000002
- type: recall_at_1
value: 30.567
- type: recall_at_10
value: 72.238
- type: recall_at_100
value: 92.154
- type: recall_at_1000
value: 98.375
- type: recall_at_3
value: 52.437999999999995
- type: recall_at_5
value: 61.516999999999996
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: 6205996560df11e3a3da9ab4f926788fc30a7db4
metrics:
- type: map_at_1
value: 65.98
- type: map_at_10
value: 80.05600000000001
- type: map_at_100
value: 80.76299999999999
- type: map_at_1000
value: 80.786
- type: map_at_3
value: 76.848
- type: map_at_5
value: 78.854
- type: mrr_at_1
value: 75.86
- type: mrr_at_10
value: 83.397
- type: mrr_at_100
value: 83.555
- type: mrr_at_1000
value: 83.557
- type: mrr_at_3
value: 82.033
- type: mrr_at_5
value: 82.97
- type: ndcg_at_1
value: 75.88000000000001
- type: ndcg_at_10
value: 84.58099999999999
- type: ndcg_at_100
value: 86.151
- type: ndcg_at_1000
value: 86.315
- type: ndcg_at_3
value: 80.902
- type: ndcg_at_5
value: 82.953
- type: precision_at_1
value: 75.88000000000001
- type: precision_at_10
value: 12.986
- type: precision_at_100
value: 1.5110000000000001
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 35.382999999999996
- type: precision_at_5
value: 23.555999999999997
- type: recall_at_1
value: 65.98
- type: recall_at_10
value: 93.716
- type: recall_at_100
value: 99.21799999999999
- type: recall_at_1000
value: 99.97
- type: recall_at_3
value: 83.551
- type: recall_at_5
value: 88.998
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: b2805658ae38990172679479369a78b86de8c390
metrics:
- type: v_measure
value: 40.45148482612238
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 55.749490673039126
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5
metrics:
- type: map_at_1
value: 4.903
- type: map_at_10
value: 11.926
- type: map_at_100
value: 13.916999999999998
- type: map_at_1000
value: 14.215
- type: map_at_3
value: 8.799999999999999
- type: map_at_5
value: 10.360999999999999
- type: mrr_at_1
value: 24.099999999999998
- type: mrr_at_10
value: 34.482
- type: mrr_at_100
value: 35.565999999999995
- type: mrr_at_1000
value: 35.619
- type: mrr_at_3
value: 31.433
- type: mrr_at_5
value: 33.243
- type: ndcg_at_1
value: 24.099999999999998
- type: ndcg_at_10
value: 19.872999999999998
- type: ndcg_at_100
value: 27.606
- type: ndcg_at_1000
value: 32.811
- type: ndcg_at_3
value: 19.497999999999998
- type: ndcg_at_5
value: 16.813
- type: precision_at_1
value: 24.099999999999998
- type: precision_at_10
value: 10.08
- type: precision_at_100
value: 2.122
- type: precision_at_1000
value: 0.337
- type: precision_at_3
value: 18.2
- type: precision_at_5
value: 14.62
- type: recall_at_1
value: 4.903
- type: recall_at_10
value: 20.438000000000002
- type: recall_at_100
value: 43.043
- type: recall_at_1000
value: 68.41000000000001
- type: recall_at_3
value: 11.068
- type: recall_at_5
value: 14.818000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 78.58086597995997
- type: cos_sim_spearman
value: 69.63214182814991
- type: euclidean_pearson
value: 72.76175489042691
- type: euclidean_spearman
value: 67.84965161872971
- type: manhattan_pearson
value: 72.73812689782592
- type: manhattan_spearman
value: 67.83610439531277
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
metrics:
- type: cos_sim_pearson
value: 75.13970861325006
- type: cos_sim_spearman
value: 67.5020551515597
- type: euclidean_pearson
value: 66.33415412418276
- type: euclidean_spearman
value: 66.82145056673268
- type: manhattan_pearson
value: 66.55489484006415
- type: manhattan_spearman
value: 66.95147433279057
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9
metrics:
- type: cos_sim_pearson
value: 78.85850536483447
- type: cos_sim_spearman
value: 79.1633350177206
- type: euclidean_pearson
value: 72.74090561408477
- type: euclidean_spearman
value: 73.57374448302961
- type: manhattan_pearson
value: 72.92980654233226
- type: manhattan_spearman
value: 73.72777155112588
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b
metrics:
- type: cos_sim_pearson
value: 79.51125593897028
- type: cos_sim_spearman
value: 74.46048326701329
- type: euclidean_pearson
value: 70.87726087052985
- type: euclidean_spearman
value: 67.7721470654411
- type: manhattan_pearson
value: 71.05892792135637
- type: manhattan_spearman
value: 67.93472619779037
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
metrics:
- type: cos_sim_pearson
value: 83.8299348880489
- type: cos_sim_spearman
value: 84.47194637929275
- type: euclidean_pearson
value: 78.68768462480418
- type: euclidean_spearman
value: 79.80526323901917
- type: manhattan_pearson
value: 78.6810718151946
- type: manhattan_spearman
value: 79.7820584821254
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
metrics:
- type: cos_sim_pearson
value: 79.99206664843005
- type: cos_sim_spearman
value: 80.96089203722137
- type: euclidean_pearson
value: 71.31216213716365
- type: euclidean_spearman
value: 71.45258140049407
- type: manhattan_pearson
value: 71.26140340402836
- type: manhattan_spearman
value: 71.3896894666943
- 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: 87.35697089594868
- type: cos_sim_spearman
value: 87.78202647220289
- type: euclidean_pearson
value: 84.20969668786667
- type: euclidean_spearman
value: 83.91876425459982
- type: manhattan_pearson
value: 84.24429755612542
- type: manhattan_spearman
value: 83.98826315103398
- 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: 69.06962775868384
- type: cos_sim_spearman
value: 69.34889515492327
- type: euclidean_pearson
value: 69.28108180412313
- type: euclidean_spearman
value: 69.6437114853659
- type: manhattan_pearson
value: 69.39974983734993
- type: manhattan_spearman
value: 69.69057284482079
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: 8913289635987208e6e7c72789e4be2fe94b6abd
metrics:
- type: cos_sim_pearson
value: 82.42553734213958
- type: cos_sim_spearman
value: 81.38977341532744
- type: euclidean_pearson
value: 76.47494587945522
- type: euclidean_spearman
value: 75.92794860531089
- type: manhattan_pearson
value: 76.4768777169467
- type: manhattan_spearman
value: 75.9252673228599
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: 56a6d0140cf6356659e2a7c1413286a774468d44
metrics:
- type: map
value: 80.78825425914722
- type: mrr
value: 94.60017197762296
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: a75ae049398addde9b70f6b268875f5cbce99089
metrics:
- type: map_at_1
value: 60.633
- type: map_at_10
value: 70.197
- type: map_at_100
value: 70.758
- type: map_at_1000
value: 70.765
- type: map_at_3
value: 67.082
- type: map_at_5
value: 69.209
- type: mrr_at_1
value: 63.333
- type: mrr_at_10
value: 71.17
- type: mrr_at_100
value: 71.626
- type: mrr_at_1000
value: 71.633
- type: mrr_at_3
value: 68.833
- type: mrr_at_5
value: 70.6
- type: ndcg_at_1
value: 63.333
- type: ndcg_at_10
value: 74.697
- type: ndcg_at_100
value: 76.986
- type: ndcg_at_1000
value: 77.225
- type: ndcg_at_3
value: 69.527
- type: ndcg_at_5
value: 72.816
- type: precision_at_1
value: 63.333
- type: precision_at_10
value: 9.9
- type: precision_at_100
value: 1.103
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 26.889000000000003
- type: precision_at_5
value: 18.2
- type: recall_at_1
value: 60.633
- type: recall_at_10
value: 87.36699999999999
- type: recall_at_100
value: 97.333
- type: recall_at_1000
value: 99.333
- type: recall_at_3
value: 73.656
- type: recall_at_5
value: 82.083
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
metrics:
- type: cos_sim_accuracy
value: 99.76633663366337
- type: cos_sim_ap
value: 93.84024096781063
- type: cos_sim_f1
value: 88.08080808080808
- type: cos_sim_precision
value: 88.9795918367347
- type: cos_sim_recall
value: 87.2
- type: dot_accuracy
value: 99.46336633663367
- type: dot_ap
value: 75.78127156965245
- type: dot_f1
value: 71.41403865717193
- type: dot_precision
value: 72.67080745341616
- type: dot_recall
value: 70.19999999999999
- type: euclidean_accuracy
value: 99.67524752475248
- type: euclidean_ap
value: 88.61274955249769
- type: euclidean_f1
value: 82.30852211434735
- type: euclidean_precision
value: 89.34426229508196
- type: euclidean_recall
value: 76.3
- type: manhattan_accuracy
value: 99.67722772277227
- type: manhattan_ap
value: 88.77516158012779
- type: manhattan_f1
value: 82.36536430834212
- type: manhattan_precision
value: 87.24832214765101
- type: manhattan_recall
value: 78
- type: max_accuracy
value: 99.76633663366337
- type: max_ap
value: 93.84024096781063
- type: max_f1
value: 88.08080808080808
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
metrics:
- type: v_measure
value: 59.20812266121527
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
metrics:
- type: v_measure
value: 33.954248554638056
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
metrics:
- type: map
value: 51.52800990025549
- type: mrr
value: 52.360394915541974
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
metrics:
- type: cos_sim_pearson
value: 30.737881131277355
- type: cos_sim_spearman
value: 31.45979323917254
- type: dot_pearson
value: 26.24686017962023
- type: dot_spearman
value: 25.006732878791745
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
metrics:
- type: map_at_1
value: 0.253
- type: map_at_10
value: 2.1399999999999997
- type: map_at_100
value: 12.873000000000001
- type: map_at_1000
value: 31.002000000000002
- type: map_at_3
value: 0.711
- type: map_at_5
value: 1.125
- type: mrr_at_1
value: 96
- type: mrr_at_10
value: 98
- type: mrr_at_100
value: 98
- type: mrr_at_1000
value: 98
- type: mrr_at_3
value: 98
- type: mrr_at_5
value: 98
- type: ndcg_at_1
value: 94
- type: ndcg_at_10
value: 84.881
- type: ndcg_at_100
value: 64.694
- type: ndcg_at_1000
value: 56.85
- type: ndcg_at_3
value: 90.061
- type: ndcg_at_5
value: 87.155
- type: precision_at_1
value: 96
- type: precision_at_10
value: 88.8
- type: precision_at_100
value: 65.7
- type: precision_at_1000
value: 25.080000000000002
- type: precision_at_3
value: 92.667
- type: precision_at_5
value: 90
- type: recall_at_1
value: 0.253
- type: recall_at_10
value: 2.292
- type: recall_at_100
value: 15.78
- type: recall_at_1000
value: 53.015
- type: recall_at_3
value: 0.7270000000000001
- type: recall_at_5
value: 1.162
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
metrics:
- type: map_at_1
value: 2.116
- type: map_at_10
value: 9.625
- type: map_at_100
value: 15.641
- type: map_at_1000
value: 17.127
- type: map_at_3
value: 4.316
- type: map_at_5
value: 6.208
- type: mrr_at_1
value: 32.653
- type: mrr_at_10
value: 48.083999999999996
- type: mrr_at_100
value: 48.631
- type: mrr_at_1000
value: 48.649
- type: mrr_at_3
value: 42.857
- type: mrr_at_5
value: 46.224
- type: ndcg_at_1
value: 29.592000000000002
- type: ndcg_at_10
value: 25.430999999999997
- type: ndcg_at_100
value: 36.344
- type: ndcg_at_1000
value: 47.676
- type: ndcg_at_3
value: 26.144000000000002
- type: ndcg_at_5
value: 26.304
- type: precision_at_1
value: 32.653
- type: precision_at_10
value: 24.082
- type: precision_at_100
value: 7.714
- type: precision_at_1000
value: 1.5310000000000001
- type: precision_at_3
value: 26.531
- type: precision_at_5
value: 26.939
- type: recall_at_1
value: 2.116
- type: recall_at_10
value: 16.794
- type: recall_at_100
value: 47.452
- type: recall_at_1000
value: 82.312
- type: recall_at_3
value: 5.306
- type: recall_at_5
value: 9.306000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 67.709
- type: ap
value: 13.541535578501716
- type: f1
value: 52.569619919446794
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: 62146448f05be9e52a36b8ee9936447ea787eede
metrics:
- type: accuracy
value: 56.850594227504246
- type: f1
value: 57.233377364910574
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
metrics:
- type: v_measure
value: 39.463722986090474
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 84.09131549144662
- type: cos_sim_ap
value: 66.86677647503386
- type: cos_sim_f1
value: 62.94631710362049
- type: cos_sim_precision
value: 59.73933649289099
- type: cos_sim_recall
value: 66.51715039577837
- type: dot_accuracy
value: 80.27656911247541
- type: dot_ap
value: 54.291720398612085
- type: dot_f1
value: 54.77150537634409
- type: dot_precision
value: 47.58660957571039
- type: dot_recall
value: 64.5118733509235
- type: euclidean_accuracy
value: 82.76211480002385
- type: euclidean_ap
value: 62.430397690753296
- type: euclidean_f1
value: 59.191590539356774
- type: euclidean_precision
value: 56.296119971435374
- type: euclidean_recall
value: 62.401055408970976
- type: manhattan_accuracy
value: 82.7561542588067
- type: manhattan_ap
value: 62.41882051995577
- type: manhattan_f1
value: 59.32101002778785
- type: manhattan_precision
value: 54.71361711611321
- type: manhattan_recall
value: 64.77572559366754
- type: max_accuracy
value: 84.09131549144662
- type: max_ap
value: 66.86677647503386
- type: max_f1
value: 62.94631710362049
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.79574649745798
- type: cos_sim_ap
value: 85.28960532524223
- type: cos_sim_f1
value: 77.98460043358001
- type: cos_sim_precision
value: 75.78090948714224
- type: cos_sim_recall
value: 80.32029565753002
- type: dot_accuracy
value: 85.5939767920208
- type: dot_ap
value: 76.14131706694056
- type: dot_f1
value: 72.70246298696868
- type: dot_precision
value: 65.27012127894156
- type: dot_recall
value: 82.04496458269172
- type: euclidean_accuracy
value: 86.72332828812046
- type: euclidean_ap
value: 80.84854809178995
- type: euclidean_f1
value: 72.47657499809551
- type: euclidean_precision
value: 71.71717171717171
- type: euclidean_recall
value: 73.25223283030489
- type: manhattan_accuracy
value: 86.7563162184189
- type: manhattan_ap
value: 80.87598895575626
- type: manhattan_f1
value: 72.54617892068092
- type: manhattan_precision
value: 68.49268225960881
- type: manhattan_recall
value: 77.10963966738528
- type: max_accuracy
value: 88.79574649745798
- type: max_ap
value: 85.28960532524223
- type: max_f1
value: 77.98460043358001
SGPT-5.8B-weightedmean-msmarco-specb-bitfit
Usage
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt
Evaluation Results
For eval results, refer to our paper: https://arxiv.org/abs/2202.08904
Training
The model was trained with the parameters:
DataLoader:
torch.utils.data.dataloader.DataLoader of length 249592 with parameters:
{'batch_size': 2, '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": 5e-05
},
"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: GPTJModel
(1): Pooling({'word_embedding_dimension': 4096, '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}
}