metadata
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: SGPT-1.3B-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: 65.20895522388061
- type: ap
value: 29.59212705444778
- type: f1
value: 59.97099864321921
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
metrics:
- type: accuracy
value: 73.20565
- type: ap
value: 67.36680643550963
- type: f1
value: 72.90420520325125
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 34.955999999999996
- type: f1
value: 34.719324437696955
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
metrics:
- type: map_at_1
value: 26.101999999999997
- type: map_at_10
value: 40.958
- type: map_at_100
value: 42.033
- type: map_at_1000
value: 42.042
- type: map_at_3
value: 36.332
- type: map_at_5
value: 38.608
- type: mrr_at_1
value: 26.387
- type: mrr_at_10
value: 41.051
- type: mrr_at_100
value: 42.118
- type: mrr_at_1000
value: 42.126999999999995
- type: mrr_at_3
value: 36.415
- type: mrr_at_5
value: 38.72
- type: ndcg_at_1
value: 26.101999999999997
- type: ndcg_at_10
value: 49.68
- type: ndcg_at_100
value: 54.257999999999996
- type: ndcg_at_1000
value: 54.486000000000004
- type: ndcg_at_3
value: 39.864
- type: ndcg_at_5
value: 43.980000000000004
- type: precision_at_1
value: 26.101999999999997
- type: precision_at_10
value: 7.781000000000001
- type: precision_at_100
value: 0.979
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 16.714000000000002
- type: precision_at_5
value: 12.034
- type: recall_at_1
value: 26.101999999999997
- type: recall_at_10
value: 77.809
- type: recall_at_100
value: 97.866
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 50.141999999999996
- type: recall_at_5
value: 60.171
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
metrics:
- type: v_measure
value: 43.384194916953774
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
metrics:
- type: v_measure
value: 33.70962633433912
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
metrics:
- type: map
value: 58.133058996870076
- type: mrr
value: 72.10922041946972
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: 9ee918f184421b6bd48b78f6c714d86546106103
metrics:
- type: cos_sim_pearson
value: 86.62153841660047
- type: cos_sim_spearman
value: 83.01514456843276
- type: euclidean_pearson
value: 86.00431518427241
- type: euclidean_spearman
value: 83.85552516285783
- type: manhattan_pearson
value: 85.83025803351181
- type: manhattan_spearman
value: 83.86636878343106
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
metrics:
- type: accuracy
value: 82.05844155844156
- type: f1
value: 82.0185837884764
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
metrics:
- type: v_measure
value: 35.05918333141837
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
metrics:
- type: v_measure
value: 30.71055028830579
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 26.519
- type: map_at_10
value: 35.634
- type: map_at_100
value: 36.961
- type: map_at_1000
value: 37.088
- type: map_at_3
value: 32.254
- type: map_at_5
value: 34.22
- type: mrr_at_1
value: 32.332
- type: mrr_at_10
value: 41.168
- type: mrr_at_100
value: 41.977
- type: mrr_at_1000
value: 42.028999999999996
- type: mrr_at_3
value: 38.196999999999996
- type: mrr_at_5
value: 40.036
- type: ndcg_at_1
value: 32.332
- type: ndcg_at_10
value: 41.471000000000004
- type: ndcg_at_100
value: 46.955999999999996
- type: ndcg_at_1000
value: 49.262
- type: ndcg_at_3
value: 35.937999999999995
- type: ndcg_at_5
value: 38.702999999999996
- type: precision_at_1
value: 32.332
- type: precision_at_10
value: 7.7829999999999995
- type: precision_at_100
value: 1.29
- type: precision_at_1000
value: 0.178
- type: precision_at_3
value: 16.834
- type: precision_at_5
value: 12.418
- type: recall_at_1
value: 26.519
- type: recall_at_10
value: 53.190000000000005
- type: recall_at_100
value: 76.56500000000001
- type: recall_at_1000
value: 91.47800000000001
- type: recall_at_3
value: 38.034
- type: recall_at_5
value: 45.245999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 25.356
- type: map_at_10
value: 34.596
- type: map_at_100
value: 35.714
- type: map_at_1000
value: 35.839999999999996
- type: map_at_3
value: 32.073
- type: map_at_5
value: 33.475
- type: mrr_at_1
value: 31.274
- type: mrr_at_10
value: 39.592
- type: mrr_at_100
value: 40.284
- type: mrr_at_1000
value: 40.339999999999996
- type: mrr_at_3
value: 37.378
- type: mrr_at_5
value: 38.658
- type: ndcg_at_1
value: 31.274
- type: ndcg_at_10
value: 39.766
- type: ndcg_at_100
value: 44.028
- type: ndcg_at_1000
value: 46.445
- type: ndcg_at_3
value: 35.934
- type: ndcg_at_5
value: 37.751000000000005
- type: precision_at_1
value: 31.274
- type: precision_at_10
value: 7.452
- type: precision_at_100
value: 1.217
- type: precision_at_1000
value: 0.16999999999999998
- type: precision_at_3
value: 17.431
- type: precision_at_5
value: 12.306000000000001
- type: recall_at_1
value: 25.356
- type: recall_at_10
value: 49.344
- type: recall_at_100
value: 67.497
- type: recall_at_1000
value: 83.372
- type: recall_at_3
value: 38.227
- type: recall_at_5
value: 43.187999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 32.759
- type: map_at_10
value: 43.937
- type: map_at_100
value: 45.004
- type: map_at_1000
value: 45.07
- type: map_at_3
value: 40.805
- type: map_at_5
value: 42.497
- type: mrr_at_1
value: 37.367
- type: mrr_at_10
value: 47.237
- type: mrr_at_100
value: 47.973
- type: mrr_at_1000
value: 48.010999999999996
- type: mrr_at_3
value: 44.65
- type: mrr_at_5
value: 46.050999999999995
- type: ndcg_at_1
value: 37.367
- type: ndcg_at_10
value: 49.659
- type: ndcg_at_100
value: 54.069
- type: ndcg_at_1000
value: 55.552
- type: ndcg_at_3
value: 44.169000000000004
- type: ndcg_at_5
value: 46.726
- type: precision_at_1
value: 37.367
- type: precision_at_10
value: 8.163
- type: precision_at_100
value: 1.133
- type: precision_at_1000
value: 0.131
- type: precision_at_3
value: 19.707
- type: precision_at_5
value: 13.718
- type: recall_at_1
value: 32.759
- type: recall_at_10
value: 63.341
- type: recall_at_100
value: 82.502
- type: recall_at_1000
value: 93.259
- type: recall_at_3
value: 48.796
- type: recall_at_5
value: 54.921
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 18.962
- type: map_at_10
value: 25.863000000000003
- type: map_at_100
value: 26.817999999999998
- type: map_at_1000
value: 26.918
- type: map_at_3
value: 23.043
- type: map_at_5
value: 24.599
- type: mrr_at_1
value: 20.452
- type: mrr_at_10
value: 27.301
- type: mrr_at_100
value: 28.233000000000004
- type: mrr_at_1000
value: 28.310000000000002
- type: mrr_at_3
value: 24.539
- type: mrr_at_5
value: 26.108999999999998
- type: ndcg_at_1
value: 20.452
- type: ndcg_at_10
value: 30.354999999999997
- type: ndcg_at_100
value: 35.336
- type: ndcg_at_1000
value: 37.927
- type: ndcg_at_3
value: 24.705
- type: ndcg_at_5
value: 27.42
- type: precision_at_1
value: 20.452
- type: precision_at_10
value: 4.949
- type: precision_at_100
value: 0.7799999999999999
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 10.358
- type: precision_at_5
value: 7.774
- type: recall_at_1
value: 18.962
- type: recall_at_10
value: 43.056
- type: recall_at_100
value: 66.27300000000001
- type: recall_at_1000
value: 85.96000000000001
- type: recall_at_3
value: 27.776
- type: recall_at_5
value: 34.287
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 11.24
- type: map_at_10
value: 18.503
- type: map_at_100
value: 19.553
- type: map_at_1000
value: 19.689999999999998
- type: map_at_3
value: 16.150000000000002
- type: map_at_5
value: 17.254
- type: mrr_at_1
value: 13.806
- type: mrr_at_10
value: 21.939
- type: mrr_at_100
value: 22.827
- type: mrr_at_1000
value: 22.911
- type: mrr_at_3
value: 19.32
- type: mrr_at_5
value: 20.558
- type: ndcg_at_1
value: 13.806
- type: ndcg_at_10
value: 23.383000000000003
- type: ndcg_at_100
value: 28.834
- type: ndcg_at_1000
value: 32.175
- type: ndcg_at_3
value: 18.651999999999997
- type: ndcg_at_5
value: 20.505000000000003
- type: precision_at_1
value: 13.806
- type: precision_at_10
value: 4.714
- type: precision_at_100
value: 0.864
- type: precision_at_1000
value: 0.13
- type: precision_at_3
value: 9.328
- type: precision_at_5
value: 6.841
- type: recall_at_1
value: 11.24
- type: recall_at_10
value: 34.854
- type: recall_at_100
value: 59.50299999999999
- type: recall_at_1000
value: 83.25
- type: recall_at_3
value: 22.02
- type: recall_at_5
value: 26.715
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 23.012
- type: map_at_10
value: 33.048
- type: map_at_100
value: 34.371
- type: map_at_1000
value: 34.489
- type: map_at_3
value: 29.942999999999998
- type: map_at_5
value: 31.602000000000004
- type: mrr_at_1
value: 28.104000000000003
- type: mrr_at_10
value: 37.99
- type: mrr_at_100
value: 38.836
- type: mrr_at_1000
value: 38.891
- type: mrr_at_3
value: 35.226
- type: mrr_at_5
value: 36.693999999999996
- type: ndcg_at_1
value: 28.104000000000003
- type: ndcg_at_10
value: 39.037
- type: ndcg_at_100
value: 44.643
- type: ndcg_at_1000
value: 46.939
- type: ndcg_at_3
value: 33.784
- type: ndcg_at_5
value: 36.126000000000005
- type: precision_at_1
value: 28.104000000000003
- type: precision_at_10
value: 7.2669999999999995
- type: precision_at_100
value: 1.193
- type: precision_at_1000
value: 0.159
- type: precision_at_3
value: 16.298000000000002
- type: precision_at_5
value: 11.684
- type: recall_at_1
value: 23.012
- type: recall_at_10
value: 52.054
- type: recall_at_100
value: 75.622
- type: recall_at_1000
value: 90.675
- type: recall_at_3
value: 37.282
- type: recall_at_5
value: 43.307
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 21.624
- type: map_at_10
value: 30.209999999999997
- type: map_at_100
value: 31.52
- type: map_at_1000
value: 31.625999999999998
- type: map_at_3
value: 26.951000000000004
- type: map_at_5
value: 28.938999999999997
- type: mrr_at_1
value: 26.941
- type: mrr_at_10
value: 35.13
- type: mrr_at_100
value: 36.15
- type: mrr_at_1000
value: 36.204
- type: mrr_at_3
value: 32.42
- type: mrr_at_5
value: 34.155
- type: ndcg_at_1
value: 26.941
- type: ndcg_at_10
value: 35.726
- type: ndcg_at_100
value: 41.725
- type: ndcg_at_1000
value: 44.105
- type: ndcg_at_3
value: 30.184
- type: ndcg_at_5
value: 33.176
- type: precision_at_1
value: 26.941
- type: precision_at_10
value: 6.654999999999999
- type: precision_at_100
value: 1.1520000000000001
- type: precision_at_1000
value: 0.152
- type: precision_at_3
value: 14.346
- type: precision_at_5
value: 10.868
- type: recall_at_1
value: 21.624
- type: recall_at_10
value: 47.359
- type: recall_at_100
value: 73.436
- type: recall_at_1000
value: 89.988
- type: recall_at_3
value: 32.34
- type: recall_at_5
value: 39.856
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 20.67566666666667
- type: map_at_10
value: 28.479333333333333
- type: map_at_100
value: 29.612249999999996
- type: map_at_1000
value: 29.731166666666663
- type: map_at_3
value: 25.884
- type: map_at_5
value: 27.298916666666667
- type: mrr_at_1
value: 24.402583333333332
- type: mrr_at_10
value: 32.07041666666667
- type: mrr_at_100
value: 32.95841666666667
- type: mrr_at_1000
value: 33.025416666666665
- type: mrr_at_3
value: 29.677749999999996
- type: mrr_at_5
value: 31.02391666666667
- type: ndcg_at_1
value: 24.402583333333332
- type: ndcg_at_10
value: 33.326166666666666
- type: ndcg_at_100
value: 38.51566666666667
- type: ndcg_at_1000
value: 41.13791666666667
- type: ndcg_at_3
value: 28.687749999999994
- type: ndcg_at_5
value: 30.84766666666667
- type: precision_at_1
value: 24.402583333333332
- type: precision_at_10
value: 5.943749999999999
- type: precision_at_100
value: 1.0098333333333334
- type: precision_at_1000
value: 0.14183333333333334
- type: precision_at_3
value: 13.211500000000001
- type: precision_at_5
value: 9.548416666666668
- type: recall_at_1
value: 20.67566666666667
- type: recall_at_10
value: 44.245583333333336
- type: recall_at_100
value: 67.31116666666667
- type: recall_at_1000
value: 85.87841666666665
- type: recall_at_3
value: 31.49258333333333
- type: recall_at_5
value: 36.93241666666667
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 18.34
- type: map_at_10
value: 23.988
- type: map_at_100
value: 24.895
- type: map_at_1000
value: 24.992
- type: map_at_3
value: 21.831
- type: map_at_5
value: 23
- type: mrr_at_1
value: 20.399
- type: mrr_at_10
value: 26.186
- type: mrr_at_100
value: 27.017999999999997
- type: mrr_at_1000
value: 27.090999999999998
- type: mrr_at_3
value: 24.08
- type: mrr_at_5
value: 25.230000000000004
- type: ndcg_at_1
value: 20.399
- type: ndcg_at_10
value: 27.799000000000003
- type: ndcg_at_100
value: 32.579
- type: ndcg_at_1000
value: 35.209
- type: ndcg_at_3
value: 23.684
- type: ndcg_at_5
value: 25.521
- type: precision_at_1
value: 20.399
- type: precision_at_10
value: 4.585999999999999
- type: precision_at_100
value: 0.755
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 10.276
- type: precision_at_5
value: 7.362
- type: recall_at_1
value: 18.34
- type: recall_at_10
value: 37.456
- type: recall_at_100
value: 59.86
- type: recall_at_1000
value: 79.703
- type: recall_at_3
value: 26.163999999999998
- type: recall_at_5
value: 30.652
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 12.327
- type: map_at_10
value: 17.572
- type: map_at_100
value: 18.534
- type: map_at_1000
value: 18.653
- type: map_at_3
value: 15.703
- type: map_at_5
value: 16.752
- type: mrr_at_1
value: 15.038000000000002
- type: mrr_at_10
value: 20.726
- type: mrr_at_100
value: 21.61
- type: mrr_at_1000
value: 21.695
- type: mrr_at_3
value: 18.829
- type: mrr_at_5
value: 19.885
- type: ndcg_at_1
value: 15.038000000000002
- type: ndcg_at_10
value: 21.241
- type: ndcg_at_100
value: 26.179000000000002
- type: ndcg_at_1000
value: 29.316
- type: ndcg_at_3
value: 17.762
- type: ndcg_at_5
value: 19.413
- type: precision_at_1
value: 15.038000000000002
- type: precision_at_10
value: 3.8920000000000003
- type: precision_at_100
value: 0.75
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 8.351
- type: precision_at_5
value: 6.187
- type: recall_at_1
value: 12.327
- type: recall_at_10
value: 29.342000000000002
- type: recall_at_100
value: 51.854
- type: recall_at_1000
value: 74.648
- type: recall_at_3
value: 19.596
- type: recall_at_5
value: 23.899
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 20.594
- type: map_at_10
value: 27.878999999999998
- type: map_at_100
value: 28.926000000000002
- type: map_at_1000
value: 29.041
- type: map_at_3
value: 25.668999999999997
- type: map_at_5
value: 26.773999999999997
- type: mrr_at_1
value: 23.694000000000003
- type: mrr_at_10
value: 31.335
- type: mrr_at_100
value: 32.218
- type: mrr_at_1000
value: 32.298
- type: mrr_at_3
value: 29.26
- type: mrr_at_5
value: 30.328
- type: ndcg_at_1
value: 23.694000000000003
- type: ndcg_at_10
value: 32.456
- type: ndcg_at_100
value: 37.667
- type: ndcg_at_1000
value: 40.571
- type: ndcg_at_3
value: 28.283
- type: ndcg_at_5
value: 29.986
- type: precision_at_1
value: 23.694000000000003
- type: precision_at_10
value: 5.448
- type: precision_at_100
value: 0.9119999999999999
- type: precision_at_1000
value: 0.127
- type: precision_at_3
value: 12.717999999999998
- type: precision_at_5
value: 8.843
- type: recall_at_1
value: 20.594
- type: recall_at_10
value: 43.004999999999995
- type: recall_at_100
value: 66.228
- type: recall_at_1000
value: 87.17099999999999
- type: recall_at_3
value: 31.554
- type: recall_at_5
value: 35.838
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 20.855999999999998
- type: map_at_10
value: 28.372000000000003
- type: map_at_100
value: 29.87
- type: map_at_1000
value: 30.075000000000003
- type: map_at_3
value: 26.054
- type: map_at_5
value: 27.128999999999998
- type: mrr_at_1
value: 25.494
- type: mrr_at_10
value: 32.735
- type: mrr_at_100
value: 33.794000000000004
- type: mrr_at_1000
value: 33.85
- type: mrr_at_3
value: 30.731
- type: mrr_at_5
value: 31.897
- type: ndcg_at_1
value: 25.494
- type: ndcg_at_10
value: 33.385
- type: ndcg_at_100
value: 39.436
- type: ndcg_at_1000
value: 42.313
- type: ndcg_at_3
value: 29.612
- type: ndcg_at_5
value: 31.186999999999998
- type: precision_at_1
value: 25.494
- type: precision_at_10
value: 6.422999999999999
- type: precision_at_100
value: 1.383
- type: precision_at_1000
value: 0.22399999999999998
- type: precision_at_3
value: 13.834
- type: precision_at_5
value: 10
- type: recall_at_1
value: 20.855999999999998
- type: recall_at_10
value: 42.678
- type: recall_at_100
value: 70.224
- type: recall_at_1000
value: 89.369
- type: recall_at_3
value: 31.957
- type: recall_at_5
value: 36.026
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 16.519000000000002
- type: map_at_10
value: 22.15
- type: map_at_100
value: 23.180999999999997
- type: map_at_1000
value: 23.291999999999998
- type: map_at_3
value: 20.132
- type: map_at_5
value: 21.346
- type: mrr_at_1
value: 17.93
- type: mrr_at_10
value: 23.506
- type: mrr_at_100
value: 24.581
- type: mrr_at_1000
value: 24.675
- type: mrr_at_3
value: 21.503
- type: mrr_at_5
value: 22.686
- type: ndcg_at_1
value: 17.93
- type: ndcg_at_10
value: 25.636
- type: ndcg_at_100
value: 30.736
- type: ndcg_at_1000
value: 33.841
- type: ndcg_at_3
value: 21.546000000000003
- type: ndcg_at_5
value: 23.658
- type: precision_at_1
value: 17.93
- type: precision_at_10
value: 3.993
- type: precision_at_100
value: 0.6890000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 9.057
- type: precision_at_5
value: 6.58
- type: recall_at_1
value: 16.519000000000002
- type: recall_at_10
value: 35.268
- type: recall_at_100
value: 58.17
- type: recall_at_1000
value: 81.66799999999999
- type: recall_at_3
value: 24.165
- type: recall_at_5
value: 29.254
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
metrics:
- type: map_at_1
value: 10.363
- type: map_at_10
value: 18.301000000000002
- type: map_at_100
value: 20.019000000000002
- type: map_at_1000
value: 20.207
- type: map_at_3
value: 14.877
- type: map_at_5
value: 16.544
- type: mrr_at_1
value: 22.866
- type: mrr_at_10
value: 34.935
- type: mrr_at_100
value: 35.802
- type: mrr_at_1000
value: 35.839999999999996
- type: mrr_at_3
value: 30.965999999999998
- type: mrr_at_5
value: 33.204
- type: ndcg_at_1
value: 22.866
- type: ndcg_at_10
value: 26.595000000000002
- type: ndcg_at_100
value: 33.513999999999996
- type: ndcg_at_1000
value: 36.872
- type: ndcg_at_3
value: 20.666999999999998
- type: ndcg_at_5
value: 22.728
- type: precision_at_1
value: 22.866
- type: precision_at_10
value: 8.632
- type: precision_at_100
value: 1.6119999999999999
- type: precision_at_1000
value: 0.22399999999999998
- type: precision_at_3
value: 15.504999999999999
- type: precision_at_5
value: 12.404
- type: recall_at_1
value: 10.363
- type: recall_at_10
value: 33.494
- type: recall_at_100
value: 57.593
- type: recall_at_1000
value: 76.342
- type: recall_at_3
value: 19.157
- type: recall_at_5
value: 24.637999999999998
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: f097057d03ed98220bc7309ddb10b71a54d667d6
metrics:
- type: map_at_1
value: 7.436
- type: map_at_10
value: 14.760000000000002
- type: map_at_100
value: 19.206
- type: map_at_1000
value: 20.267
- type: map_at_3
value: 10.894
- type: map_at_5
value: 12.828999999999999
- type: mrr_at_1
value: 54.25
- type: mrr_at_10
value: 63.769
- type: mrr_at_100
value: 64.193
- type: mrr_at_1000
value: 64.211
- type: mrr_at_3
value: 61.458
- type: mrr_at_5
value: 63.096
- type: ndcg_at_1
value: 42.875
- type: ndcg_at_10
value: 31.507
- type: ndcg_at_100
value: 34.559
- type: ndcg_at_1000
value: 41.246
- type: ndcg_at_3
value: 35.058
- type: ndcg_at_5
value: 33.396
- type: precision_at_1
value: 54.25
- type: precision_at_10
value: 24.45
- type: precision_at_100
value: 7.383000000000001
- type: precision_at_1000
value: 1.582
- type: precision_at_3
value: 38.083
- type: precision_at_5
value: 32.6
- type: recall_at_1
value: 7.436
- type: recall_at_10
value: 19.862
- type: recall_at_100
value: 38.981
- type: recall_at_1000
value: 61.038000000000004
- type: recall_at_3
value: 11.949
- type: recall_at_5
value: 15.562000000000001
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 829147f8f75a25f005913200eb5ed41fae320aa1
metrics:
- type: accuracy
value: 46.39
- type: f1
value: 42.26424885856703
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
metrics:
- type: map_at_1
value: 50.916
- type: map_at_10
value: 62.258
- type: map_at_100
value: 62.741
- type: map_at_1000
value: 62.763000000000005
- type: map_at_3
value: 60.01800000000001
- type: map_at_5
value: 61.419999999999995
- type: mrr_at_1
value: 54.964999999999996
- type: mrr_at_10
value: 66.554
- type: mrr_at_100
value: 66.96600000000001
- type: mrr_at_1000
value: 66.97800000000001
- type: mrr_at_3
value: 64.414
- type: mrr_at_5
value: 65.77
- type: ndcg_at_1
value: 54.964999999999996
- type: ndcg_at_10
value: 68.12
- type: ndcg_at_100
value: 70.282
- type: ndcg_at_1000
value: 70.788
- type: ndcg_at_3
value: 63.861999999999995
- type: ndcg_at_5
value: 66.216
- type: precision_at_1
value: 54.964999999999996
- type: precision_at_10
value: 8.998000000000001
- type: precision_at_100
value: 1.016
- type: precision_at_1000
value: 0.107
- type: precision_at_3
value: 25.618000000000002
- type: precision_at_5
value: 16.676
- type: recall_at_1
value: 50.916
- type: recall_at_10
value: 82.04
- type: recall_at_100
value: 91.689
- type: recall_at_1000
value: 95.34899999999999
- type: recall_at_3
value: 70.512
- type: recall_at_5
value: 76.29899999999999
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
metrics:
- type: map_at_1
value: 13.568
- type: map_at_10
value: 23.264000000000003
- type: map_at_100
value: 24.823999999999998
- type: map_at_1000
value: 25.013999999999996
- type: map_at_3
value: 19.724
- type: map_at_5
value: 21.772
- type: mrr_at_1
value: 27.315
- type: mrr_at_10
value: 35.935
- type: mrr_at_100
value: 36.929
- type: mrr_at_1000
value: 36.985
- type: mrr_at_3
value: 33.591
- type: mrr_at_5
value: 34.848
- type: ndcg_at_1
value: 27.315
- type: ndcg_at_10
value: 29.988
- type: ndcg_at_100
value: 36.41
- type: ndcg_at_1000
value: 40.184999999999995
- type: ndcg_at_3
value: 26.342
- type: ndcg_at_5
value: 27.68
- type: precision_at_1
value: 27.315
- type: precision_at_10
value: 8.565000000000001
- type: precision_at_100
value: 1.508
- type: precision_at_1000
value: 0.219
- type: precision_at_3
value: 17.849999999999998
- type: precision_at_5
value: 13.672999999999998
- type: recall_at_1
value: 13.568
- type: recall_at_10
value: 37.133
- type: recall_at_100
value: 61.475
- type: recall_at_1000
value: 84.372
- type: recall_at_3
value: 24.112000000000002
- type: recall_at_5
value: 29.507
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
metrics:
- type: map_at_1
value: 30.878
- type: map_at_10
value: 40.868
- type: map_at_100
value: 41.693999999999996
- type: map_at_1000
value: 41.775
- type: map_at_3
value: 38.56
- type: map_at_5
value: 39.947
- type: mrr_at_1
value: 61.756
- type: mrr_at_10
value: 68.265
- type: mrr_at_100
value: 68.671
- type: mrr_at_1000
value: 68.694
- type: mrr_at_3
value: 66.78399999999999
- type: mrr_at_5
value: 67.704
- type: ndcg_at_1
value: 61.756
- type: ndcg_at_10
value: 49.931
- type: ndcg_at_100
value: 53.179
- type: ndcg_at_1000
value: 54.94799999999999
- type: ndcg_at_3
value: 46.103
- type: ndcg_at_5
value: 48.147
- type: precision_at_1
value: 61.756
- type: precision_at_10
value: 10.163
- type: precision_at_100
value: 1.2710000000000001
- type: precision_at_1000
value: 0.151
- type: precision_at_3
value: 28.179
- type: precision_at_5
value: 18.528
- type: recall_at_1
value: 30.878
- type: recall_at_10
value: 50.817
- type: recall_at_100
value: 63.544999999999995
- type: recall_at_1000
value: 75.361
- type: recall_at_3
value: 42.269
- type: recall_at_5
value: 46.32
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
metrics:
- type: accuracy
value: 64.04799999999999
- type: ap
value: 59.185251455339284
- type: f1
value: 63.947123181349255
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: validation
revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
metrics:
- type: map_at_1
value: 18.9
- type: map_at_10
value: 29.748
- type: map_at_100
value: 30.976
- type: map_at_1000
value: 31.041
- type: map_at_3
value: 26.112999999999996
- type: map_at_5
value: 28.197
- type: mrr_at_1
value: 19.413
- type: mrr_at_10
value: 30.322
- type: mrr_at_100
value: 31.497000000000003
- type: mrr_at_1000
value: 31.555
- type: mrr_at_3
value: 26.729000000000003
- type: mrr_at_5
value: 28.788999999999998
- type: ndcg_at_1
value: 19.413
- type: ndcg_at_10
value: 36.048
- type: ndcg_at_100
value: 42.152
- type: ndcg_at_1000
value: 43.772
- type: ndcg_at_3
value: 28.642
- type: ndcg_at_5
value: 32.358
- type: precision_at_1
value: 19.413
- type: precision_at_10
value: 5.785
- type: precision_at_100
value: 0.8869999999999999
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 12.192
- type: precision_at_5
value: 9.189
- type: recall_at_1
value: 18.9
- type: recall_at_10
value: 55.457
- type: recall_at_100
value: 84.09100000000001
- type: recall_at_1000
value: 96.482
- type: recall_at_3
value: 35.359
- type: recall_at_5
value: 44.275
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 92.07706338349293
- type: f1
value: 91.56680443236652
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: 6299947a7777084cc2d4b64235bf7190381ce755
metrics:
- type: accuracy
value: 71.18559051527589
- type: f1
value: 52.42887061726789
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
metrics:
- type: accuracy
value: 68.64828513786148
- type: f1
value: 66.54281381596097
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 76.04236718224612
- type: f1
value: 75.89170458655639
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: dcefc037ef84348e49b0d29109e891c01067226b
metrics:
- type: v_measure
value: 32.0840369055247
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc
metrics:
- type: v_measure
value: 29.448729560244537
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 31.340856463122375
- type: mrr
value: 32.398547669840916
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610
metrics:
- type: map_at_1
value: 5.526
- type: map_at_10
value: 11.745
- type: map_at_100
value: 14.831
- type: map_at_1000
value: 16.235
- type: map_at_3
value: 8.716
- type: map_at_5
value: 10.101
- type: mrr_at_1
value: 43.653
- type: mrr_at_10
value: 51.06699999999999
- type: mrr_at_100
value: 51.881
- type: mrr_at_1000
value: 51.912000000000006
- type: mrr_at_3
value: 49.02
- type: mrr_at_5
value: 50.288999999999994
- type: ndcg_at_1
value: 41.949999999999996
- type: ndcg_at_10
value: 32.083
- type: ndcg_at_100
value: 30.049999999999997
- type: ndcg_at_1000
value: 38.661
- type: ndcg_at_3
value: 37.940000000000005
- type: ndcg_at_5
value: 35.455999999999996
- type: precision_at_1
value: 43.344
- type: precision_at_10
value: 23.437
- type: precision_at_100
value: 7.829999999999999
- type: precision_at_1000
value: 2.053
- type: precision_at_3
value: 35.501
- type: precision_at_5
value: 30.464000000000002
- type: recall_at_1
value: 5.526
- type: recall_at_10
value: 15.445999999999998
- type: recall_at_100
value: 31.179000000000002
- type: recall_at_1000
value: 61.578
- type: recall_at_3
value: 9.71
- type: recall_at_5
value: 12.026
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c
metrics:
- type: map_at_1
value: 23.467
- type: map_at_10
value: 36.041000000000004
- type: map_at_100
value: 37.268
- type: map_at_1000
value: 37.322
- type: map_at_3
value: 32.09
- type: map_at_5
value: 34.414
- type: mrr_at_1
value: 26.738
- type: mrr_at_10
value: 38.665
- type: mrr_at_100
value: 39.64
- type: mrr_at_1000
value: 39.681
- type: mrr_at_3
value: 35.207
- type: mrr_at_5
value: 37.31
- type: ndcg_at_1
value: 26.709
- type: ndcg_at_10
value: 42.942
- type: ndcg_at_100
value: 48.296
- type: ndcg_at_1000
value: 49.651
- type: ndcg_at_3
value: 35.413
- type: ndcg_at_5
value: 39.367999999999995
- type: precision_at_1
value: 26.709
- type: precision_at_10
value: 7.306
- type: precision_at_100
value: 1.0290000000000001
- type: precision_at_1000
value: 0.116
- type: precision_at_3
value: 16.348
- type: precision_at_5
value: 12.068
- type: recall_at_1
value: 23.467
- type: recall_at_10
value: 61.492999999999995
- type: recall_at_100
value: 85.01100000000001
- type: recall_at_1000
value: 95.261
- type: recall_at_3
value: 41.952
- type: recall_at_5
value: 51.105999999999995
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: 6205996560df11e3a3da9ab4f926788fc30a7db4
metrics:
- type: map_at_1
value: 67.51700000000001
- type: map_at_10
value: 81.054
- type: map_at_100
value: 81.727
- type: map_at_1000
value: 81.75200000000001
- type: map_at_3
value: 78.018
- type: map_at_5
value: 79.879
- type: mrr_at_1
value: 77.52
- type: mrr_at_10
value: 84.429
- type: mrr_at_100
value: 84.58200000000001
- type: mrr_at_1000
value: 84.584
- type: mrr_at_3
value: 83.268
- type: mrr_at_5
value: 84.013
- type: ndcg_at_1
value: 77.53
- type: ndcg_at_10
value: 85.277
- type: ndcg_at_100
value: 86.80499999999999
- type: ndcg_at_1000
value: 87.01
- type: ndcg_at_3
value: 81.975
- type: ndcg_at_5
value: 83.723
- type: precision_at_1
value: 77.53
- type: precision_at_10
value: 12.961
- type: precision_at_100
value: 1.502
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 35.713
- type: precision_at_5
value: 23.574
- type: recall_at_1
value: 67.51700000000001
- type: recall_at_10
value: 93.486
- type: recall_at_100
value: 98.9
- type: recall_at_1000
value: 99.92999999999999
- type: recall_at_3
value: 84.17999999999999
- type: recall_at_5
value: 88.97500000000001
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: b2805658ae38990172679479369a78b86de8c390
metrics:
- type: v_measure
value: 48.225994608749915
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 53.17635557157765
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5
metrics:
- type: map_at_1
value: 3.988
- type: map_at_10
value: 9.4
- type: map_at_100
value: 10.968
- type: map_at_1000
value: 11.257
- type: map_at_3
value: 7.123
- type: map_at_5
value: 8.221
- type: mrr_at_1
value: 19.7
- type: mrr_at_10
value: 29.098000000000003
- type: mrr_at_100
value: 30.247
- type: mrr_at_1000
value: 30.318
- type: mrr_at_3
value: 26.55
- type: mrr_at_5
value: 27.915
- type: ndcg_at_1
value: 19.7
- type: ndcg_at_10
value: 16.176
- type: ndcg_at_100
value: 22.931
- type: ndcg_at_1000
value: 28.301
- type: ndcg_at_3
value: 16.142
- type: ndcg_at_5
value: 13.633999999999999
- type: precision_at_1
value: 19.7
- type: precision_at_10
value: 8.18
- type: precision_at_100
value: 1.8010000000000002
- type: precision_at_1000
value: 0.309
- type: precision_at_3
value: 15.1
- type: precision_at_5
value: 11.74
- type: recall_at_1
value: 3.988
- type: recall_at_10
value: 16.625
- type: recall_at_100
value: 36.61
- type: recall_at_1000
value: 62.805
- type: recall_at_3
value: 9.168
- type: recall_at_5
value: 11.902
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 77.29330379162072
- type: cos_sim_spearman
value: 67.22953551111448
- type: euclidean_pearson
value: 71.44682700059415
- type: euclidean_spearman
value: 66.33178012153247
- type: manhattan_pearson
value: 71.46941734657887
- type: manhattan_spearman
value: 66.43234359835814
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
metrics:
- type: cos_sim_pearson
value: 75.40943196466576
- type: cos_sim_spearman
value: 66.59241013465915
- type: euclidean_pearson
value: 71.32500540796616
- type: euclidean_spearman
value: 67.86667467202591
- type: manhattan_pearson
value: 71.48209832089134
- type: manhattan_spearman
value: 67.94511626964879
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9
metrics:
- type: cos_sim_pearson
value: 77.08302398877518
- type: cos_sim_spearman
value: 77.33151317062642
- type: euclidean_pearson
value: 76.77020279715008
- type: euclidean_spearman
value: 77.13893776083225
- type: manhattan_pearson
value: 76.76732290707477
- type: manhattan_spearman
value: 77.14500877396631
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b
metrics:
- type: cos_sim_pearson
value: 77.46886184932168
- type: cos_sim_spearman
value: 71.82815265534886
- type: euclidean_pearson
value: 75.19783284299076
- type: euclidean_spearman
value: 71.36479611710412
- type: manhattan_pearson
value: 75.30375233959337
- type: manhattan_spearman
value: 71.46280266488021
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
metrics:
- type: cos_sim_pearson
value: 80.093017609484
- type: cos_sim_spearman
value: 80.65931167868882
- type: euclidean_pearson
value: 80.36786337117047
- type: euclidean_spearman
value: 81.30521389642827
- type: manhattan_pearson
value: 80.37922433220973
- type: manhattan_spearman
value: 81.30496664496285
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
metrics:
- type: cos_sim_pearson
value: 77.98998347238742
- type: cos_sim_spearman
value: 78.91151365939403
- type: euclidean_pearson
value: 76.40510899217841
- type: euclidean_spearman
value: 76.8551459824213
- type: manhattan_pearson
value: 76.3986079603294
- type: manhattan_spearman
value: 76.8848053254288
- 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: 85.63510653472044
- type: cos_sim_spearman
value: 86.98674844768605
- type: euclidean_pearson
value: 85.205080538809
- type: euclidean_spearman
value: 85.53630494151886
- type: manhattan_pearson
value: 85.48612469885626
- type: manhattan_spearman
value: 85.81741413931921
- 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: 66.7257987615171
- type: cos_sim_spearman
value: 67.30387805090024
- type: euclidean_pearson
value: 69.46877227885867
- type: euclidean_spearman
value: 69.33161798704344
- type: manhattan_pearson
value: 69.82773311626424
- type: manhattan_spearman
value: 69.57199940498796
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: 8913289635987208e6e7c72789e4be2fe94b6abd
metrics:
- type: cos_sim_pearson
value: 79.37322139418472
- type: cos_sim_spearman
value: 77.5887175717799
- type: euclidean_pearson
value: 78.23006410562164
- type: euclidean_spearman
value: 77.18470385673044
- type: manhattan_pearson
value: 78.40868369362455
- type: manhattan_spearman
value: 77.36675823897656
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: 56a6d0140cf6356659e2a7c1413286a774468d44
metrics:
- type: map
value: 77.21233007730808
- type: mrr
value: 93.0502386139641
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: a75ae049398addde9b70f6b268875f5cbce99089
metrics:
- type: map_at_1
value: 54.567
- type: map_at_10
value: 63.653000000000006
- type: map_at_100
value: 64.282
- type: map_at_1000
value: 64.31099999999999
- type: map_at_3
value: 60.478
- type: map_at_5
value: 62.322
- type: mrr_at_1
value: 56.99999999999999
- type: mrr_at_10
value: 64.759
- type: mrr_at_100
value: 65.274
- type: mrr_at_1000
value: 65.301
- type: mrr_at_3
value: 62.333000000000006
- type: mrr_at_5
value: 63.817
- type: ndcg_at_1
value: 56.99999999999999
- type: ndcg_at_10
value: 68.28699999999999
- type: ndcg_at_100
value: 70.98400000000001
- type: ndcg_at_1000
value: 71.695
- type: ndcg_at_3
value: 62.656
- type: ndcg_at_5
value: 65.523
- type: precision_at_1
value: 56.99999999999999
- type: precision_at_10
value: 9.232999999999999
- type: precision_at_100
value: 1.0630000000000002
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 24.221999999999998
- type: precision_at_5
value: 16.333000000000002
- type: recall_at_1
value: 54.567
- type: recall_at_10
value: 81.45599999999999
- type: recall_at_100
value: 93.5
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 66.228
- type: recall_at_5
value: 73.489
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
metrics:
- type: cos_sim_accuracy
value: 99.74455445544554
- type: cos_sim_ap
value: 92.57836032673468
- type: cos_sim_f1
value: 87.0471464019851
- type: cos_sim_precision
value: 86.4039408866995
- type: cos_sim_recall
value: 87.7
- type: dot_accuracy
value: 99.56039603960396
- type: dot_ap
value: 82.47233353407186
- type: dot_f1
value: 76.78207739307537
- type: dot_precision
value: 78.21576763485477
- type: dot_recall
value: 75.4
- type: euclidean_accuracy
value: 99.73069306930694
- type: euclidean_ap
value: 91.70507666665775
- type: euclidean_f1
value: 86.26262626262626
- type: euclidean_precision
value: 87.14285714285714
- type: euclidean_recall
value: 85.39999999999999
- type: manhattan_accuracy
value: 99.73861386138614
- type: manhattan_ap
value: 91.96809459281754
- type: manhattan_f1
value: 86.6
- type: manhattan_precision
value: 86.6
- type: manhattan_recall
value: 86.6
- type: max_accuracy
value: 99.74455445544554
- type: max_ap
value: 92.57836032673468
- type: max_f1
value: 87.0471464019851
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
metrics:
- type: v_measure
value: 60.85593925770172
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
metrics:
- type: v_measure
value: 32.356772998237496
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
metrics:
- type: map
value: 49.320607035290735
- type: mrr
value: 50.09196481622952
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
metrics:
- type: cos_sim_pearson
value: 31.17573968015504
- type: cos_sim_spearman
value: 30.43371643155132
- type: dot_pearson
value: 30.164319483092743
- type: dot_spearman
value: 29.207082242868754
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
metrics:
- type: map_at_1
value: 0.22100000000000003
- type: map_at_10
value: 1.7229999999999999
- type: map_at_100
value: 9.195
- type: map_at_1000
value: 21.999
- type: map_at_3
value: 0.6479999999999999
- type: map_at_5
value: 0.964
- type: mrr_at_1
value: 86
- type: mrr_at_10
value: 90.667
- type: mrr_at_100
value: 90.858
- type: mrr_at_1000
value: 90.858
- type: mrr_at_3
value: 90.667
- type: mrr_at_5
value: 90.667
- type: ndcg_at_1
value: 82
- type: ndcg_at_10
value: 72.98
- type: ndcg_at_100
value: 52.868
- type: ndcg_at_1000
value: 46.541
- type: ndcg_at_3
value: 80.39699999999999
- type: ndcg_at_5
value: 76.303
- type: precision_at_1
value: 86
- type: precision_at_10
value: 75.8
- type: precision_at_100
value: 53.5
- type: precision_at_1000
value: 20.946
- type: precision_at_3
value: 85.333
- type: precision_at_5
value: 79.2
- type: recall_at_1
value: 0.22100000000000003
- type: recall_at_10
value: 1.9109999999999998
- type: recall_at_100
value: 12.437
- type: recall_at_1000
value: 43.606
- type: recall_at_3
value: 0.681
- type: recall_at_5
value: 1.023
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
metrics:
- type: map_at_1
value: 2.5
- type: map_at_10
value: 9.568999999999999
- type: map_at_100
value: 15.653
- type: map_at_1000
value: 17.188
- type: map_at_3
value: 5.335999999999999
- type: map_at_5
value: 6.522
- type: mrr_at_1
value: 34.694
- type: mrr_at_10
value: 49.184
- type: mrr_at_100
value: 50.512
- type: mrr_at_1000
value: 50.512
- type: mrr_at_3
value: 46.259
- type: mrr_at_5
value: 48.299
- type: ndcg_at_1
value: 30.612000000000002
- type: ndcg_at_10
value: 24.45
- type: ndcg_at_100
value: 35.870999999999995
- type: ndcg_at_1000
value: 47.272999999999996
- type: ndcg_at_3
value: 28.528
- type: ndcg_at_5
value: 25.768
- type: precision_at_1
value: 34.694
- type: precision_at_10
value: 21.429000000000002
- type: precision_at_100
value: 7.265000000000001
- type: precision_at_1000
value: 1.504
- type: precision_at_3
value: 29.252
- type: precision_at_5
value: 24.898
- type: recall_at_1
value: 2.5
- type: recall_at_10
value: 15.844
- type: recall_at_100
value: 45.469
- type: recall_at_1000
value: 81.148
- type: recall_at_3
value: 6.496
- type: recall_at_5
value: 8.790000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 68.7272
- type: ap
value: 13.156450706152686
- type: f1
value: 52.814703437064395
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: 62146448f05be9e52a36b8ee9936447ea787eede
metrics:
- type: accuracy
value: 55.6677985285795
- type: f1
value: 55.9373937514999
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
metrics:
- type: v_measure
value: 40.05809562275603
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 82.76807534124099
- type: cos_sim_ap
value: 62.37052608803734
- type: cos_sim_f1
value: 59.077414934916646
- type: cos_sim_precision
value: 52.07326892109501
- type: cos_sim_recall
value: 68.25857519788919
- type: dot_accuracy
value: 80.56267509089825
- type: dot_ap
value: 54.75349561321037
- type: dot_f1
value: 54.75483794372552
- type: dot_precision
value: 49.77336499028707
- type: dot_recall
value: 60.844327176781
- type: euclidean_accuracy
value: 82.476008821601
- type: euclidean_ap
value: 61.17417554210511
- type: euclidean_f1
value: 57.80318696022382
- type: euclidean_precision
value: 53.622207176709544
- type: euclidean_recall
value: 62.69129287598945
- type: manhattan_accuracy
value: 82.48792990403528
- type: manhattan_ap
value: 61.044816292966544
- type: manhattan_f1
value: 58.03033951360462
- type: manhattan_precision
value: 53.36581045172719
- type: manhattan_recall
value: 63.58839050131926
- type: max_accuracy
value: 82.76807534124099
- type: max_ap
value: 62.37052608803734
- type: max_f1
value: 59.077414934916646
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 87.97881010594946
- type: cos_sim_ap
value: 83.78748636891035
- type: cos_sim_f1
value: 75.94113995691386
- type: cos_sim_precision
value: 72.22029307590805
- type: cos_sim_recall
value: 80.06621496766245
- type: dot_accuracy
value: 85.69294058291614
- type: dot_ap
value: 78.15363722278026
- type: dot_f1
value: 72.08894926888564
- type: dot_precision
value: 67.28959487419075
- type: dot_recall
value: 77.62550046196489
- type: euclidean_accuracy
value: 87.73625179493149
- type: euclidean_ap
value: 83.19012184470559
- type: euclidean_f1
value: 75.5148064623461
- type: euclidean_precision
value: 72.63352535381551
- type: euclidean_recall
value: 78.6341238065907
- type: manhattan_accuracy
value: 87.74013272790779
- type: manhattan_ap
value: 83.23305405113403
- type: manhattan_f1
value: 75.63960775639607
- type: manhattan_precision
value: 72.563304569246
- type: manhattan_recall
value: 78.9882968894364
- type: max_accuracy
value: 87.97881010594946
- type: max_ap
value: 83.78748636891035
- type: max_f1
value: 75.94113995691386
SGPT-1.3B-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 62398 with parameters:
{'batch_size': 8, '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': 2048, '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}
}