---
tags:
- mteb
model-index:
- name: mlm
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 82.97014925373135
- type: ap
value: 49.6288385893607
- type: f1
value: 77.58957447993662
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 90.975425
- type: ap
value: 87.57349835900825
- type: f1
value: 90.96732416386632
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 48.708
- type: f1
value: 47.736228936979586
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.006
- type: map_at_10
value: 49.268
- type: map_at_100
value: 49.903999999999996
- type: map_at_1000
value: 49.909
- type: map_at_3
value: 44.334
- type: map_at_5
value: 47.374
- type: mrr_at_1
value: 32.788000000000004
- type: mrr_at_10
value: 49.707
- type: mrr_at_100
value: 50.346999999999994
- type: mrr_at_1000
value: 50.352
- type: mrr_at_3
value: 44.95
- type: mrr_at_5
value: 47.766999999999996
- type: ndcg_at_1
value: 32.006
- type: ndcg_at_10
value: 58.523
- type: ndcg_at_100
value: 61.095
- type: ndcg_at_1000
value: 61.190999999999995
- type: ndcg_at_3
value: 48.431000000000004
- type: ndcg_at_5
value: 53.94
- type: precision_at_1
value: 32.006
- type: precision_at_10
value: 8.791
- type: precision_at_100
value: 0.989
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 20.104
- type: precision_at_5
value: 14.751
- type: recall_at_1
value: 32.006
- type: recall_at_10
value: 87.909
- type: recall_at_100
value: 98.86200000000001
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 60.313
- type: recall_at_5
value: 73.75500000000001
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 47.01500173547629
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 43.52209238193538
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 64.1348784470504
- type: mrr
value: 76.93762916062083
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.8322696692348
- type: cos_sim_spearman
value: 86.53751398463592
- type: euclidean_pearson
value: 86.1435544054336
- type: euclidean_spearman
value: 86.70799979698164
- type: manhattan_pearson
value: 86.1206703865016
- type: manhattan_spearman
value: 86.47004256773585
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 88.1461038961039
- type: f1
value: 88.09877611214092
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 35.53021718892608
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 35.34236915611622
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.435
- type: map_at_10
value: 49.437999999999995
- type: map_at_100
value: 51.105999999999995
- type: map_at_1000
value: 51.217999999999996
- type: map_at_3
value: 44.856
- type: map_at_5
value: 47.195
- type: mrr_at_1
value: 45.78
- type: mrr_at_10
value: 56.302
- type: mrr_at_100
value: 56.974000000000004
- type: mrr_at_1000
value: 57.001999999999995
- type: mrr_at_3
value: 53.6
- type: mrr_at_5
value: 55.059999999999995
- type: ndcg_at_1
value: 44.921
- type: ndcg_at_10
value: 56.842000000000006
- type: ndcg_at_100
value: 61.586
- type: ndcg_at_1000
value: 63.039
- type: ndcg_at_3
value: 50.612
- type: ndcg_at_5
value: 53.181
- type: precision_at_1
value: 44.921
- type: precision_at_10
value: 11.245
- type: precision_at_100
value: 1.7069999999999999
- type: precision_at_1000
value: 0.216
- type: precision_at_3
value: 24.224999999999998
- type: precision_at_5
value: 17.511
- type: recall_at_1
value: 36.435
- type: recall_at_10
value: 70.998
- type: recall_at_100
value: 89.64
- type: recall_at_1000
value: 98.654
- type: recall_at_3
value: 53.034000000000006
- type: recall_at_5
value: 60.41
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 33.371
- type: map_at_10
value: 45.301
- type: map_at_100
value: 46.663
- type: map_at_1000
value: 46.791
- type: map_at_3
value: 41.79
- type: map_at_5
value: 43.836999999999996
- type: mrr_at_1
value: 42.611
- type: mrr_at_10
value: 51.70400000000001
- type: mrr_at_100
value: 52.342
- type: mrr_at_1000
value: 52.38
- type: mrr_at_3
value: 49.374
- type: mrr_at_5
value: 50.82
- type: ndcg_at_1
value: 42.166
- type: ndcg_at_10
value: 51.49
- type: ndcg_at_100
value: 56.005
- type: ndcg_at_1000
value: 57.748
- type: ndcg_at_3
value: 46.769
- type: ndcg_at_5
value: 49.155
- type: precision_at_1
value: 42.166
- type: precision_at_10
value: 9.841
- type: precision_at_100
value: 1.569
- type: precision_at_1000
value: 0.202
- type: precision_at_3
value: 22.803
- type: precision_at_5
value: 16.229
- type: recall_at_1
value: 33.371
- type: recall_at_10
value: 62.52799999999999
- type: recall_at_100
value: 81.269
- type: recall_at_1000
value: 91.824
- type: recall_at_3
value: 48.759
- type: recall_at_5
value: 55.519
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 41.421
- type: map_at_10
value: 55.985
- type: map_at_100
value: 56.989999999999995
- type: map_at_1000
value: 57.028
- type: map_at_3
value: 52.271
- type: map_at_5
value: 54.517
- type: mrr_at_1
value: 47.272999999999996
- type: mrr_at_10
value: 59.266
- type: mrr_at_100
value: 59.821999999999996
- type: mrr_at_1000
value: 59.839
- type: mrr_at_3
value: 56.677
- type: mrr_at_5
value: 58.309999999999995
- type: ndcg_at_1
value: 47.147
- type: ndcg_at_10
value: 62.596
- type: ndcg_at_100
value: 66.219
- type: ndcg_at_1000
value: 66.886
- type: ndcg_at_3
value: 56.558
- type: ndcg_at_5
value: 59.805
- type: precision_at_1
value: 47.147
- type: precision_at_10
value: 10.245
- type: precision_at_100
value: 1.302
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 25.663999999999998
- type: precision_at_5
value: 17.793
- type: recall_at_1
value: 41.421
- type: recall_at_10
value: 78.77499999999999
- type: recall_at_100
value: 93.996
- type: recall_at_1000
value: 98.60600000000001
- type: recall_at_3
value: 62.891
- type: recall_at_5
value: 70.819
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.517999999999997
- type: map_at_10
value: 37.468
- type: map_at_100
value: 38.667
- type: map_at_1000
value: 38.743
- type: map_at_3
value: 34.524
- type: map_at_5
value: 36.175000000000004
- type: mrr_at_1
value: 29.378999999999998
- type: mrr_at_10
value: 39.54
- type: mrr_at_100
value: 40.469
- type: mrr_at_1000
value: 40.522000000000006
- type: mrr_at_3
value: 36.685
- type: mrr_at_5
value: 38.324000000000005
- type: ndcg_at_1
value: 29.718
- type: ndcg_at_10
value: 43.091
- type: ndcg_at_100
value: 48.44
- type: ndcg_at_1000
value: 50.181
- type: ndcg_at_3
value: 37.34
- type: ndcg_at_5
value: 40.177
- type: precision_at_1
value: 29.718
- type: precision_at_10
value: 6.723
- type: precision_at_100
value: 0.992
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 16.083
- type: precision_at_5
value: 11.322000000000001
- type: recall_at_1
value: 27.517999999999997
- type: recall_at_10
value: 58.196999999999996
- type: recall_at_100
value: 82.07799999999999
- type: recall_at_1000
value: 94.935
- type: recall_at_3
value: 42.842
- type: recall_at_5
value: 49.58
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.621
- type: map_at_10
value: 30.175
- type: map_at_100
value: 31.496000000000002
- type: map_at_1000
value: 31.602000000000004
- type: map_at_3
value: 26.753
- type: map_at_5
value: 28.857
- type: mrr_at_1
value: 25.497999999999998
- type: mrr_at_10
value: 35.44
- type: mrr_at_100
value: 36.353
- type: mrr_at_1000
value: 36.412
- type: mrr_at_3
value: 32.275999999999996
- type: mrr_at_5
value: 34.434
- type: ndcg_at_1
value: 24.502
- type: ndcg_at_10
value: 36.423
- type: ndcg_at_100
value: 42.289
- type: ndcg_at_1000
value: 44.59
- type: ndcg_at_3
value: 30.477999999999998
- type: ndcg_at_5
value: 33.787
- type: precision_at_1
value: 24.502
- type: precision_at_10
value: 6.978
- type: precision_at_100
value: 1.139
- type: precision_at_1000
value: 0.145
- type: precision_at_3
value: 15.008
- type: precision_at_5
value: 11.468
- type: recall_at_1
value: 19.621
- type: recall_at_10
value: 50.516000000000005
- type: recall_at_100
value: 75.721
- type: recall_at_1000
value: 91.77199999999999
- type: recall_at_3
value: 34.695
- type: recall_at_5
value: 42.849
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 33.525
- type: map_at_10
value: 46.153
- type: map_at_100
value: 47.61
- type: map_at_1000
value: 47.715
- type: map_at_3
value: 42.397
- type: map_at_5
value: 44.487
- type: mrr_at_1
value: 42.445
- type: mrr_at_10
value: 52.174
- type: mrr_at_100
value: 52.986999999999995
- type: mrr_at_1000
value: 53.016
- type: mrr_at_3
value: 49.647000000000006
- type: mrr_at_5
value: 51.215999999999994
- type: ndcg_at_1
value: 42.156
- type: ndcg_at_10
value: 52.698
- type: ndcg_at_100
value: 58.167
- type: ndcg_at_1000
value: 59.71300000000001
- type: ndcg_at_3
value: 47.191
- type: ndcg_at_5
value: 49.745
- type: precision_at_1
value: 42.156
- type: precision_at_10
value: 9.682
- type: precision_at_100
value: 1.469
- type: precision_at_1000
value: 0.17700000000000002
- type: precision_at_3
value: 22.682
- type: precision_at_5
value: 16.035
- type: recall_at_1
value: 33.525
- type: recall_at_10
value: 66.142
- type: recall_at_100
value: 88.248
- type: recall_at_1000
value: 97.806
- type: recall_at_3
value: 50.541000000000004
- type: recall_at_5
value: 57.275
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.249000000000002
- type: map_at_10
value: 41.659
- type: map_at_100
value: 43.001
- type: map_at_1000
value: 43.094
- type: map_at_3
value: 37.607
- type: map_at_5
value: 39.662
- type: mrr_at_1
value: 36.301
- type: mrr_at_10
value: 47.482
- type: mrr_at_100
value: 48.251
- type: mrr_at_1000
value: 48.288
- type: mrr_at_3
value: 44.444
- type: mrr_at_5
value: 46.013999999999996
- type: ndcg_at_1
value: 35.616
- type: ndcg_at_10
value: 49.021
- type: ndcg_at_100
value: 54.362
- type: ndcg_at_1000
value: 55.864999999999995
- type: ndcg_at_3
value: 42.515
- type: ndcg_at_5
value: 45.053
- type: precision_at_1
value: 35.616
- type: precision_at_10
value: 9.372
- type: precision_at_100
value: 1.4120000000000001
- type: precision_at_1000
value: 0.172
- type: precision_at_3
value: 21.043
- type: precision_at_5
value: 14.84
- type: recall_at_1
value: 28.249000000000002
- type: recall_at_10
value: 65.514
- type: recall_at_100
value: 87.613
- type: recall_at_1000
value: 97.03
- type: recall_at_3
value: 47.21
- type: recall_at_5
value: 54.077
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.164583333333333
- type: map_at_10
value: 40.632000000000005
- type: map_at_100
value: 41.96875
- type: map_at_1000
value: 42.07508333333333
- type: map_at_3
value: 37.18458333333333
- type: map_at_5
value: 39.13700000000001
- type: mrr_at_1
value: 35.2035
- type: mrr_at_10
value: 45.28816666666666
- type: mrr_at_100
value: 46.11466666666667
- type: mrr_at_1000
value: 46.15741666666667
- type: mrr_at_3
value: 42.62925
- type: mrr_at_5
value: 44.18141666666667
- type: ndcg_at_1
value: 34.88958333333333
- type: ndcg_at_10
value: 46.90650000000001
- type: ndcg_at_100
value: 52.135333333333335
- type: ndcg_at_1000
value: 53.89766666666668
- type: ndcg_at_3
value: 41.32075
- type: ndcg_at_5
value: 44.02083333333333
- type: precision_at_1
value: 34.88958333333333
- type: precision_at_10
value: 8.392833333333332
- type: precision_at_100
value: 1.3085833333333334
- type: precision_at_1000
value: 0.16458333333333333
- type: precision_at_3
value: 19.361166666666666
- type: precision_at_5
value: 13.808416666666668
- type: recall_at_1
value: 29.164583333333333
- type: recall_at_10
value: 60.874666666666656
- type: recall_at_100
value: 83.21008333333334
- type: recall_at_1000
value: 95.09275000000001
- type: recall_at_3
value: 45.37591666666667
- type: recall_at_5
value: 52.367666666666665
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.682000000000002
- type: map_at_10
value: 37.913000000000004
- type: map_at_100
value: 39.037
- type: map_at_1000
value: 39.123999999999995
- type: map_at_3
value: 35.398
- type: map_at_5
value: 36.906
- type: mrr_at_1
value: 32.362
- type: mrr_at_10
value: 40.92
- type: mrr_at_100
value: 41.748000000000005
- type: mrr_at_1000
value: 41.81
- type: mrr_at_3
value: 38.701
- type: mrr_at_5
value: 39.936
- type: ndcg_at_1
value: 32.208999999999996
- type: ndcg_at_10
value: 42.84
- type: ndcg_at_100
value: 47.927
- type: ndcg_at_1000
value: 50.048
- type: ndcg_at_3
value: 38.376
- type: ndcg_at_5
value: 40.661
- type: precision_at_1
value: 32.208999999999996
- type: precision_at_10
value: 6.718
- type: precision_at_100
value: 1.012
- type: precision_at_1000
value: 0.127
- type: precision_at_3
value: 16.667
- type: precision_at_5
value: 11.503
- type: recall_at_1
value: 28.682000000000002
- type: recall_at_10
value: 54.872
- type: recall_at_100
value: 77.42999999999999
- type: recall_at_1000
value: 93.054
- type: recall_at_3
value: 42.577999999999996
- type: recall_at_5
value: 48.363
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.698
- type: map_at_10
value: 28.777
- type: map_at_100
value: 30.091
- type: map_at_1000
value: 30.209999999999997
- type: map_at_3
value: 25.874000000000002
- type: map_at_5
value: 27.438000000000002
- type: mrr_at_1
value: 24.295
- type: mrr_at_10
value: 33.077
- type: mrr_at_100
value: 34.036
- type: mrr_at_1000
value: 34.1
- type: mrr_at_3
value: 30.523
- type: mrr_at_5
value: 31.891000000000002
- type: ndcg_at_1
value: 24.535
- type: ndcg_at_10
value: 34.393
- type: ndcg_at_100
value: 40.213
- type: ndcg_at_1000
value: 42.748000000000005
- type: ndcg_at_3
value: 29.316
- type: ndcg_at_5
value: 31.588
- type: precision_at_1
value: 24.535
- type: precision_at_10
value: 6.483
- type: precision_at_100
value: 1.102
- type: precision_at_1000
value: 0.151
- type: precision_at_3
value: 14.201
- type: precision_at_5
value: 10.344000000000001
- type: recall_at_1
value: 19.698
- type: recall_at_10
value: 46.903
- type: recall_at_100
value: 72.624
- type: recall_at_1000
value: 90.339
- type: recall_at_3
value: 32.482
- type: recall_at_5
value: 38.452
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.56
- type: map_at_10
value: 41.993
- type: map_at_100
value: 43.317
- type: map_at_1000
value: 43.399
- type: map_at_3
value: 38.415
- type: map_at_5
value: 40.472
- type: mrr_at_1
value: 36.474000000000004
- type: mrr_at_10
value: 46.562
- type: mrr_at_100
value: 47.497
- type: mrr_at_1000
value: 47.532999999999994
- type: mrr_at_3
value: 43.905
- type: mrr_at_5
value: 45.379000000000005
- type: ndcg_at_1
value: 36.287000000000006
- type: ndcg_at_10
value: 48.262
- type: ndcg_at_100
value: 53.789
- type: ndcg_at_1000
value: 55.44
- type: ndcg_at_3
value: 42.358000000000004
- type: ndcg_at_5
value: 45.221000000000004
- type: precision_at_1
value: 36.287000000000006
- type: precision_at_10
value: 8.265
- type: precision_at_100
value: 1.24
- type: precision_at_1000
value: 0.148
- type: precision_at_3
value: 19.558
- type: precision_at_5
value: 13.880999999999998
- type: recall_at_1
value: 30.56
- type: recall_at_10
value: 62.891
- type: recall_at_100
value: 85.964
- type: recall_at_1000
value: 97.087
- type: recall_at_3
value: 46.755
- type: recall_at_5
value: 53.986000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.432000000000002
- type: map_at_10
value: 40.898
- type: map_at_100
value: 42.794
- type: map_at_1000
value: 43.029
- type: map_at_3
value: 37.658
- type: map_at_5
value: 39.519
- type: mrr_at_1
value: 36.364000000000004
- type: mrr_at_10
value: 46.9
- type: mrr_at_100
value: 47.819
- type: mrr_at_1000
value: 47.848
- type: mrr_at_3
value: 44.202999999999996
- type: mrr_at_5
value: 45.715
- type: ndcg_at_1
value: 35.573
- type: ndcg_at_10
value: 47.628
- type: ndcg_at_100
value: 53.88699999999999
- type: ndcg_at_1000
value: 55.584
- type: ndcg_at_3
value: 42.669000000000004
- type: ndcg_at_5
value: 45.036
- type: precision_at_1
value: 35.573
- type: precision_at_10
value: 8.933
- type: precision_at_100
value: 1.8159999999999998
- type: precision_at_1000
value: 0.256
- type: precision_at_3
value: 20.29
- type: precision_at_5
value: 14.387
- type: recall_at_1
value: 29.432000000000002
- type: recall_at_10
value: 60.388
- type: recall_at_100
value: 87.144
- type: recall_at_1000
value: 97.154
- type: recall_at_3
value: 45.675
- type: recall_at_5
value: 52.35300000000001
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.462999999999997
- type: map_at_10
value: 31.824
- type: map_at_100
value: 32.853
- type: map_at_1000
value: 32.948
- type: map_at_3
value: 28.671999999999997
- type: map_at_5
value: 30.579
- type: mrr_at_1
value: 23.66
- type: mrr_at_10
value: 34.091
- type: mrr_at_100
value: 35.077999999999996
- type: mrr_at_1000
value: 35.138999999999996
- type: mrr_at_3
value: 31.516
- type: mrr_at_5
value: 33.078
- type: ndcg_at_1
value: 23.845
- type: ndcg_at_10
value: 37.594
- type: ndcg_at_100
value: 42.74
- type: ndcg_at_1000
value: 44.93
- type: ndcg_at_3
value: 31.667
- type: ndcg_at_5
value: 34.841
- type: precision_at_1
value: 23.845
- type: precision_at_10
value: 6.229
- type: precision_at_100
value: 0.943
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 14.11
- type: precision_at_5
value: 10.388
- type: recall_at_1
value: 21.462999999999997
- type: recall_at_10
value: 52.772
- type: recall_at_100
value: 76.794
- type: recall_at_1000
value: 92.852
- type: recall_at_3
value: 37.049
- type: recall_at_5
value: 44.729
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.466
- type: map_at_10
value: 25.275
- type: map_at_100
value: 27.176000000000002
- type: map_at_1000
value: 27.374
- type: map_at_3
value: 21.438
- type: map_at_5
value: 23.366
- type: mrr_at_1
value: 35.699999999999996
- type: mrr_at_10
value: 47.238
- type: mrr_at_100
value: 47.99
- type: mrr_at_1000
value: 48.021
- type: mrr_at_3
value: 44.463
- type: mrr_at_5
value: 46.039
- type: ndcg_at_1
value: 35.244
- type: ndcg_at_10
value: 34.559
- type: ndcg_at_100
value: 41.74
- type: ndcg_at_1000
value: 45.105000000000004
- type: ndcg_at_3
value: 29.284
- type: ndcg_at_5
value: 30.903999999999996
- type: precision_at_1
value: 35.244
- type: precision_at_10
value: 10.463000000000001
- type: precision_at_100
value: 1.8259999999999998
- type: precision_at_1000
value: 0.246
- type: precision_at_3
value: 21.65
- type: precision_at_5
value: 16.078
- type: recall_at_1
value: 15.466
- type: recall_at_10
value: 39.782000000000004
- type: recall_at_100
value: 64.622
- type: recall_at_1000
value: 83.233
- type: recall_at_3
value: 26.398
- type: recall_at_5
value: 31.676
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.414
- type: map_at_10
value: 22.435
- type: map_at_100
value: 32.393
- type: map_at_1000
value: 34.454
- type: map_at_3
value: 15.346000000000002
- type: map_at_5
value: 18.282999999999998
- type: mrr_at_1
value: 71.5
- type: mrr_at_10
value: 78.795
- type: mrr_at_100
value: 79.046
- type: mrr_at_1000
value: 79.054
- type: mrr_at_3
value: 77.333
- type: mrr_at_5
value: 78.146
- type: ndcg_at_1
value: 60.75000000000001
- type: ndcg_at_10
value: 46.829
- type: ndcg_at_100
value: 52.370000000000005
- type: ndcg_at_1000
value: 59.943999999999996
- type: ndcg_at_3
value: 51.33
- type: ndcg_at_5
value: 48.814
- type: precision_at_1
value: 71.75
- type: precision_at_10
value: 37.525
- type: precision_at_100
value: 12.075
- type: precision_at_1000
value: 2.464
- type: precision_at_3
value: 54.75
- type: precision_at_5
value: 47.55
- type: recall_at_1
value: 9.414
- type: recall_at_10
value: 28.67
- type: recall_at_100
value: 59.924
- type: recall_at_1000
value: 83.921
- type: recall_at_3
value: 16.985
- type: recall_at_5
value: 21.372
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 52.18000000000001
- type: f1
value: 47.04613218997081
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 82.57900000000001
- type: map_at_10
value: 88.465
- type: map_at_100
value: 88.649
- type: map_at_1000
value: 88.661
- type: map_at_3
value: 87.709
- type: map_at_5
value: 88.191
- type: mrr_at_1
value: 88.899
- type: mrr_at_10
value: 93.35900000000001
- type: mrr_at_100
value: 93.38499999999999
- type: mrr_at_1000
value: 93.38499999999999
- type: mrr_at_3
value: 93.012
- type: mrr_at_5
value: 93.282
- type: ndcg_at_1
value: 88.98899999999999
- type: ndcg_at_10
value: 91.22
- type: ndcg_at_100
value: 91.806
- type: ndcg_at_1000
value: 92.013
- type: ndcg_at_3
value: 90.236
- type: ndcg_at_5
value: 90.798
- type: precision_at_1
value: 88.98899999999999
- type: precision_at_10
value: 10.537
- type: precision_at_100
value: 1.106
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 33.598
- type: precision_at_5
value: 20.618
- type: recall_at_1
value: 82.57900000000001
- type: recall_at_10
value: 94.95400000000001
- type: recall_at_100
value: 97.14
- type: recall_at_1000
value: 98.407
- type: recall_at_3
value: 92.203
- type: recall_at_5
value: 93.747
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.871000000000002
- type: map_at_10
value: 46.131
- type: map_at_100
value: 48.245
- type: map_at_1000
value: 48.361
- type: map_at_3
value: 40.03
- type: map_at_5
value: 43.634
- type: mrr_at_1
value: 52.932
- type: mrr_at_10
value: 61.61299999999999
- type: mrr_at_100
value: 62.205
- type: mrr_at_1000
value: 62.224999999999994
- type: mrr_at_3
value: 59.388
- type: mrr_at_5
value: 60.760999999999996
- type: ndcg_at_1
value: 53.395
- type: ndcg_at_10
value: 54.506
- type: ndcg_at_100
value: 61.151999999999994
- type: ndcg_at_1000
value: 62.882000000000005
- type: ndcg_at_3
value: 49.903999999999996
- type: ndcg_at_5
value: 51.599
- type: precision_at_1
value: 53.395
- type: precision_at_10
value: 15.247
- type: precision_at_100
value: 2.221
- type: precision_at_1000
value: 0.255
- type: precision_at_3
value: 33.539
- type: precision_at_5
value: 24.722
- type: recall_at_1
value: 27.871000000000002
- type: recall_at_10
value: 62.074
- type: recall_at_100
value: 86.531
- type: recall_at_1000
value: 96.574
- type: recall_at_3
value: 45.003
- type: recall_at_5
value: 53.00899999999999
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.513
- type: map_at_10
value: 69.066
- type: map_at_100
value: 69.903
- type: map_at_1000
value: 69.949
- type: map_at_3
value: 65.44200000000001
- type: map_at_5
value: 67.784
- type: mrr_at_1
value: 80.891
- type: mrr_at_10
value: 86.42699999999999
- type: mrr_at_100
value: 86.577
- type: mrr_at_1000
value: 86.58200000000001
- type: mrr_at_3
value: 85.6
- type: mrr_at_5
value: 86.114
- type: ndcg_at_1
value: 81.026
- type: ndcg_at_10
value: 76.412
- type: ndcg_at_100
value: 79.16
- type: ndcg_at_1000
value: 79.989
- type: ndcg_at_3
value: 71.45
- type: ndcg_at_5
value: 74.286
- type: precision_at_1
value: 81.026
- type: precision_at_10
value: 16.198999999999998
- type: precision_at_100
value: 1.831
- type: precision_at_1000
value: 0.194
- type: precision_at_3
value: 46.721000000000004
- type: precision_at_5
value: 30.266
- type: recall_at_1
value: 40.513
- type: recall_at_10
value: 80.99300000000001
- type: recall_at_100
value: 91.526
- type: recall_at_1000
value: 96.935
- type: recall_at_3
value: 70.081
- type: recall_at_5
value: 75.665
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 87.42320000000001
- type: ap
value: 83.59975323233843
- type: f1
value: 87.38669942597816
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 22.676
- type: map_at_10
value: 35.865
- type: map_at_100
value: 37.019000000000005
- type: map_at_1000
value: 37.062
- type: map_at_3
value: 31.629
- type: map_at_5
value: 34.050999999999995
- type: mrr_at_1
value: 23.023
- type: mrr_at_10
value: 36.138999999999996
- type: mrr_at_100
value: 37.242
- type: mrr_at_1000
value: 37.28
- type: mrr_at_3
value: 32.053
- type: mrr_at_5
value: 34.383
- type: ndcg_at_1
value: 23.308999999999997
- type: ndcg_at_10
value: 43.254
- type: ndcg_at_100
value: 48.763
- type: ndcg_at_1000
value: 49.788
- type: ndcg_at_3
value: 34.688
- type: ndcg_at_5
value: 38.973
- type: precision_at_1
value: 23.308999999999997
- type: precision_at_10
value: 6.909999999999999
- type: precision_at_100
value: 0.967
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 14.818999999999999
- type: precision_at_5
value: 11.072
- type: recall_at_1
value: 22.676
- type: recall_at_10
value: 66.077
- type: recall_at_100
value: 91.4
- type: recall_at_1000
value: 99.143
- type: recall_at_3
value: 42.845
- type: recall_at_5
value: 53.08500000000001
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 96.16279069767444
- type: f1
value: 96.02183835878418
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 85.74783401732788
- type: f1
value: 70.59661579230463
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 79.67047747141895
- type: f1
value: 77.06311183471965
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 82.82447881640887
- type: f1
value: 82.37598020010746
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 30.266131881264467
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 29.673653452453998
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.91846122902102
- type: mrr
value: 34.2557300204471
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 6.762
- type: map_at_10
value: 15.134
- type: map_at_100
value: 19.341
- type: map_at_1000
value: 20.961
- type: map_at_3
value: 10.735999999999999
- type: map_at_5
value: 12.751999999999999
- type: mrr_at_1
value: 52.941
- type: mrr_at_10
value: 60.766
- type: mrr_at_100
value: 61.196
- type: mrr_at_1000
value: 61.227
- type: mrr_at_3
value: 58.720000000000006
- type: mrr_at_5
value: 59.866
- type: ndcg_at_1
value: 50.929
- type: ndcg_at_10
value: 39.554
- type: ndcg_at_100
value: 36.307
- type: ndcg_at_1000
value: 44.743
- type: ndcg_at_3
value: 44.157000000000004
- type: ndcg_at_5
value: 42.142
- type: precision_at_1
value: 52.322
- type: precision_at_10
value: 29.412
- type: precision_at_100
value: 9.365
- type: precision_at_1000
value: 2.2159999999999997
- type: precision_at_3
value: 40.557
- type: precision_at_5
value: 35.913000000000004
- type: recall_at_1
value: 6.762
- type: recall_at_10
value: 19.689999999999998
- type: recall_at_100
value: 36.687
- type: recall_at_1000
value: 67.23
- type: recall_at_3
value: 11.773
- type: recall_at_5
value: 15.18
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.612
- type: map_at_10
value: 54.208
- type: map_at_100
value: 55.056000000000004
- type: map_at_1000
value: 55.069
- type: map_at_3
value: 49.45
- type: map_at_5
value: 52.556000000000004
- type: mrr_at_1
value: 41.976
- type: mrr_at_10
value: 56.972
- type: mrr_at_100
value: 57.534
- type: mrr_at_1000
value: 57.542
- type: mrr_at_3
value: 53.312000000000005
- type: mrr_at_5
value: 55.672999999999995
- type: ndcg_at_1
value: 41.338
- type: ndcg_at_10
value: 62.309000000000005
- type: ndcg_at_100
value: 65.557
- type: ndcg_at_1000
value: 65.809
- type: ndcg_at_3
value: 53.74100000000001
- type: ndcg_at_5
value: 58.772999999999996
- type: precision_at_1
value: 41.338
- type: precision_at_10
value: 10.107
- type: precision_at_100
value: 1.1900000000000002
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 24.488
- type: precision_at_5
value: 17.596
- type: recall_at_1
value: 36.612
- type: recall_at_10
value: 84.408
- type: recall_at_100
value: 97.929
- type: recall_at_1000
value: 99.725
- type: recall_at_3
value: 62.676
- type: recall_at_5
value: 74.24199999999999
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 71.573
- type: map_at_10
value: 85.81
- type: map_at_100
value: 86.434
- type: map_at_1000
value: 86.446
- type: map_at_3
value: 82.884
- type: map_at_5
value: 84.772
- type: mrr_at_1
value: 82.53
- type: mrr_at_10
value: 88.51299999999999
- type: mrr_at_100
value: 88.59700000000001
- type: mrr_at_1000
value: 88.598
- type: mrr_at_3
value: 87.595
- type: mrr_at_5
value: 88.266
- type: ndcg_at_1
value: 82.39999999999999
- type: ndcg_at_10
value: 89.337
- type: ndcg_at_100
value: 90.436
- type: ndcg_at_1000
value: 90.498
- type: ndcg_at_3
value: 86.676
- type: ndcg_at_5
value: 88.241
- type: precision_at_1
value: 82.39999999999999
- type: precision_at_10
value: 13.58
- type: precision_at_100
value: 1.543
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 38.04
- type: precision_at_5
value: 25.044
- type: recall_at_1
value: 71.573
- type: recall_at_10
value: 96.066
- type: recall_at_100
value: 99.73100000000001
- type: recall_at_1000
value: 99.991
- type: recall_at_3
value: 88.34
- type: recall_at_5
value: 92.79899999999999
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 61.767168063971724
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 66.00502775826037
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.718
- type: map_at_10
value: 12.13
- type: map_at_100
value: 14.269000000000002
- type: map_at_1000
value: 14.578
- type: map_at_3
value: 8.605
- type: map_at_5
value: 10.483
- type: mrr_at_1
value: 23.7
- type: mrr_at_10
value: 34.354
- type: mrr_at_100
value: 35.522
- type: mrr_at_1000
value: 35.571999999999996
- type: mrr_at_3
value: 31.15
- type: mrr_at_5
value: 32.98
- type: ndcg_at_1
value: 23.3
- type: ndcg_at_10
value: 20.171
- type: ndcg_at_100
value: 28.456
- type: ndcg_at_1000
value: 33.826
- type: ndcg_at_3
value: 19.104
- type: ndcg_at_5
value: 16.977999999999998
- type: precision_at_1
value: 23.3
- type: precision_at_10
value: 10.45
- type: precision_at_100
value: 2.239
- type: precision_at_1000
value: 0.35300000000000004
- type: precision_at_3
value: 17.933
- type: precision_at_5
value: 15.1
- type: recall_at_1
value: 4.718
- type: recall_at_10
value: 21.221999999999998
- type: recall_at_100
value: 45.42
- type: recall_at_1000
value: 71.642
- type: recall_at_3
value: 10.922
- type: recall_at_5
value: 15.322
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 85.2065344862739
- type: cos_sim_spearman
value: 83.2276569587515
- type: euclidean_pearson
value: 83.42726762105312
- type: euclidean_spearman
value: 83.31396596997742
- type: manhattan_pearson
value: 83.41123401762816
- type: manhattan_spearman
value: 83.34393052682026
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 81.28253173719754
- type: cos_sim_spearman
value: 76.12995701324436
- type: euclidean_pearson
value: 75.30693691794121
- type: euclidean_spearman
value: 75.12472789129536
- type: manhattan_pearson
value: 75.35860808729171
- type: manhattan_spearman
value: 75.30445827952794
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 82.09358031005694
- type: cos_sim_spearman
value: 83.18811147636619
- type: euclidean_pearson
value: 82.65513459991631
- type: euclidean_spearman
value: 82.71085530442987
- type: manhattan_pearson
value: 82.67700926821576
- type: manhattan_spearman
value: 82.73815539380426
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 81.51365440223137
- type: cos_sim_spearman
value: 80.59933905019179
- type: euclidean_pearson
value: 80.56660025433806
- type: euclidean_spearman
value: 80.27926539084027
- type: manhattan_pearson
value: 80.64632724055481
- type: manhattan_spearman
value: 80.43616365139444
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 86.8590461417506
- type: cos_sim_spearman
value: 87.16337291721602
- type: euclidean_pearson
value: 85.8847725068404
- type: euclidean_spearman
value: 86.12602873624066
- type: manhattan_pearson
value: 86.04095861363909
- type: manhattan_spearman
value: 86.35535645007629
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 83.61371557181502
- type: cos_sim_spearman
value: 85.16330754442785
- type: euclidean_pearson
value: 84.20831431260608
- type: euclidean_spearman
value: 84.33191523212125
- type: manhattan_pearson
value: 84.34911007642411
- type: manhattan_spearman
value: 84.49670164290394
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 90.54452933158781
- type: cos_sim_spearman
value: 90.88214621695892
- type: euclidean_pearson
value: 91.38488015281216
- type: euclidean_spearman
value: 91.01822259603908
- type: manhattan_pearson
value: 91.36449776198687
- type: manhattan_spearman
value: 90.90478717381717
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 68.00941643037453
- type: cos_sim_spearman
value: 67.03588472081898
- type: euclidean_pearson
value: 67.35224911601603
- type: euclidean_spearman
value: 66.35544831459266
- type: manhattan_pearson
value: 67.35080066508304
- type: manhattan_spearman
value: 66.07893473733782
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 85.18291011086279
- type: cos_sim_spearman
value: 85.66913777481429
- type: euclidean_pearson
value: 84.81115930027242
- type: euclidean_spearman
value: 85.07133983924173
- type: manhattan_pearson
value: 84.88932120524983
- type: manhattan_spearman
value: 85.176903109055
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 83.67543572266588
- type: mrr
value: 95.9468146232852
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 59.633
- type: map_at_10
value: 69.801
- type: map_at_100
value: 70.504
- type: map_at_1000
value: 70.519
- type: map_at_3
value: 67.72500000000001
- type: map_at_5
value: 68.812
- type: mrr_at_1
value: 62.333000000000006
- type: mrr_at_10
value: 70.956
- type: mrr_at_100
value: 71.489
- type: mrr_at_1000
value: 71.504
- type: mrr_at_3
value: 69.44399999999999
- type: mrr_at_5
value: 70.244
- type: ndcg_at_1
value: 62.0
- type: ndcg_at_10
value: 73.98599999999999
- type: ndcg_at_100
value: 76.629
- type: ndcg_at_1000
value: 77.054
- type: ndcg_at_3
value: 70.513
- type: ndcg_at_5
value: 71.978
- type: precision_at_1
value: 62.0
- type: precision_at_10
value: 9.633
- type: precision_at_100
value: 1.097
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 27.556000000000004
- type: precision_at_5
value: 17.666999999999998
- type: recall_at_1
value: 59.633
- type: recall_at_10
value: 85.52199999999999
- type: recall_at_100
value: 96.667
- type: recall_at_1000
value: 100.0
- type: recall_at_3
value: 75.767
- type: recall_at_5
value: 79.76100000000001
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.77821782178218
- type: cos_sim_ap
value: 94.58684455008866
- type: cos_sim_f1
value: 88.51282051282053
- type: cos_sim_precision
value: 90.84210526315789
- type: cos_sim_recall
value: 86.3
- type: dot_accuracy
value: 99.77623762376237
- type: dot_ap
value: 94.86277541733045
- type: dot_f1
value: 88.66897575457693
- type: dot_precision
value: 87.75710088148874
- type: dot_recall
value: 89.60000000000001
- type: euclidean_accuracy
value: 99.76732673267327
- type: euclidean_ap
value: 94.12114402691984
- type: euclidean_f1
value: 87.96804792810784
- type: euclidean_precision
value: 87.83649052841476
- type: euclidean_recall
value: 88.1
- type: manhattan_accuracy
value: 99.77227722772277
- type: manhattan_ap
value: 94.33665105240306
- type: manhattan_f1
value: 88.25587206396803
- type: manhattan_precision
value: 88.21178821178822
- type: manhattan_recall
value: 88.3
- type: max_accuracy
value: 99.77821782178218
- type: max_ap
value: 94.86277541733045
- type: max_f1
value: 88.66897575457693
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 72.03943478268592
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 35.285037897356496
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 51.83578447913503
- type: mrr
value: 52.69070696460402
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.89437612567638
- type: cos_sim_spearman
value: 30.7277819987126
- type: dot_pearson
value: 30.999783674122526
- type: dot_spearman
value: 30.992168551124905
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.22699999999999998
- type: map_at_10
value: 1.8950000000000002
- type: map_at_100
value: 11.712
- type: map_at_1000
value: 28.713
- type: map_at_3
value: 0.65
- type: map_at_5
value: 1.011
- type: mrr_at_1
value: 92.0
- type: mrr_at_10
value: 95.39999999999999
- type: mrr_at_100
value: 95.39999999999999
- type: mrr_at_1000
value: 95.39999999999999
- type: mrr_at_3
value: 95.0
- type: mrr_at_5
value: 95.39999999999999
- type: ndcg_at_1
value: 83.0
- type: ndcg_at_10
value: 76.658
- type: ndcg_at_100
value: 60.755
- type: ndcg_at_1000
value: 55.05
- type: ndcg_at_3
value: 82.961
- type: ndcg_at_5
value: 80.008
- type: precision_at_1
value: 90.0
- type: precision_at_10
value: 79.80000000000001
- type: precision_at_100
value: 62.019999999999996
- type: precision_at_1000
value: 24.157999999999998
- type: precision_at_3
value: 88.0
- type: precision_at_5
value: 83.6
- type: recall_at_1
value: 0.22699999999999998
- type: recall_at_10
value: 2.086
- type: recall_at_100
value: 15.262
- type: recall_at_1000
value: 51.800000000000004
- type: recall_at_3
value: 0.679
- type: recall_at_5
value: 1.0739999999999998
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.521
- type: map_at_10
value: 7.281
- type: map_at_100
value: 12.717
- type: map_at_1000
value: 14.266000000000002
- type: map_at_3
value: 3.62
- type: map_at_5
value: 4.7010000000000005
- type: mrr_at_1
value: 18.367
- type: mrr_at_10
value: 34.906
- type: mrr_at_100
value: 36.333
- type: mrr_at_1000
value: 36.348
- type: mrr_at_3
value: 29.592000000000002
- type: mrr_at_5
value: 33.367000000000004
- type: ndcg_at_1
value: 19.387999999999998
- type: ndcg_at_10
value: 18.523
- type: ndcg_at_100
value: 30.932
- type: ndcg_at_1000
value: 42.942
- type: ndcg_at_3
value: 18.901
- type: ndcg_at_5
value: 17.974999999999998
- type: precision_at_1
value: 20.408
- type: precision_at_10
value: 17.347
- type: precision_at_100
value: 6.898
- type: precision_at_1000
value: 1.482
- type: precision_at_3
value: 21.088
- type: precision_at_5
value: 19.184
- type: recall_at_1
value: 1.521
- type: recall_at_10
value: 13.406
- type: recall_at_100
value: 43.418
- type: recall_at_1000
value: 80.247
- type: recall_at_3
value: 4.673
- type: recall_at_5
value: 7.247000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 71.9084
- type: ap
value: 15.388385311898144
- type: f1
value: 55.760189174489426
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 62.399547255234864
- type: f1
value: 62.61398519525303
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 53.041094760846164
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.92394349406926
- type: cos_sim_ap
value: 79.93037248584875
- type: cos_sim_f1
value: 73.21063394683026
- type: cos_sim_precision
value: 70.99652949925633
- type: cos_sim_recall
value: 75.56728232189973
- type: dot_accuracy
value: 87.80473266972642
- type: dot_ap
value: 79.11055417163318
- type: dot_f1
value: 72.79587473273801
- type: dot_precision
value: 69.55058880076905
- type: dot_recall
value: 76.35883905013192
- type: euclidean_accuracy
value: 87.91202241163496
- type: euclidean_ap
value: 79.61955502404068
- type: euclidean_f1
value: 72.65956080647231
- type: euclidean_precision
value: 70.778083562672
- type: euclidean_recall
value: 74.64379947229551
- type: manhattan_accuracy
value: 87.7749299636407
- type: manhattan_ap
value: 79.33286131650932
- type: manhattan_f1
value: 72.44748412310699
- type: manhattan_precision
value: 67.43974533879036
- type: manhattan_recall
value: 78.25857519788919
- type: max_accuracy
value: 87.92394349406926
- type: max_ap
value: 79.93037248584875
- type: max_f1
value: 73.21063394683026
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.89987192921178
- type: cos_sim_ap
value: 87.49525152555509
- type: cos_sim_f1
value: 80.05039276715578
- type: cos_sim_precision
value: 77.15714285714286
- type: cos_sim_recall
value: 83.1690791499846
- type: dot_accuracy
value: 89.58163542515621
- type: dot_ap
value: 86.87353801172357
- type: dot_f1
value: 79.50204384986993
- type: dot_precision
value: 76.83522482401953
- type: dot_recall
value: 82.36064059131506
- type: euclidean_accuracy
value: 89.81255093724532
- type: euclidean_ap
value: 87.41058010369022
- type: euclidean_f1
value: 79.94095829233214
- type: euclidean_precision
value: 78.61396456751525
- type: euclidean_recall
value: 81.3135201724669
- type: manhattan_accuracy
value: 89.84553886754377
- type: manhattan_ap
value: 87.41173628281432
- type: manhattan_f1
value: 79.9051922079846
- type: manhattan_precision
value: 76.98016269444841
- type: manhattan_recall
value: 83.06128734216199
- type: max_accuracy
value: 89.89987192921178
- type: max_ap
value: 87.49525152555509
- type: max_f1
value: 80.05039276715578
---
# Repetition Improves Language Model Embeddings
Please refer to our paper: [https://arxiv.org/abs/2402.15449](https://arxiv.org/abs/2402.15449)
And our GitHub: [https://github.com/jakespringer/echo-embeddings](https://github.com/jakespringer/echo-embeddings)
We provide a description of the model as well as example usage in the above links.