metadata
tags:
- mteb
model-index:
- name: multi-qa-MiniLM-L6-cos-v1
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 61.791044776119406
- type: ap
value: 25.829130082463124
- type: f1
value: 56.00432262887535
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 62.36077499999999
- type: ap
value: 57.68938427410222
- type: f1
value: 62.247666843818436
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 29.59
- type: f1
value: 29.241975951560622
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.249
- type: map_at_10
value: 40.196
- type: map_at_100
value: 41.336
- type: map_at_1000
value: 41.343
- type: map_at_3
value: 34.934
- type: map_at_5
value: 37.871
- type: mrr_at_1
value: 26.031
- type: mrr_at_10
value: 40.488
- type: mrr_at_100
value: 41.628
- type: mrr_at_1000
value: 41.634
- type: mrr_at_3
value: 35.171
- type: mrr_at_5
value: 38.126
- type: ndcg_at_1
value: 25.249
- type: ndcg_at_10
value: 49.11
- type: ndcg_at_100
value: 53.827999999999996
- type: ndcg_at_1000
value: 53.993
- type: ndcg_at_3
value: 38.175
- type: ndcg_at_5
value: 43.488
- type: precision_at_1
value: 25.249
- type: precision_at_10
value: 7.788
- type: precision_at_100
value: 0.9820000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 15.861
- type: precision_at_5
value: 12.105
- type: recall_at_1
value: 25.249
- type: recall_at_10
value: 77.881
- type: recall_at_100
value: 98.222
- type: recall_at_1000
value: 99.502
- type: recall_at_3
value: 47.582
- type: recall_at_5
value: 60.526
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 37.75242616816114
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 27.70031808300247
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 63.09199068762668
- type: mrr
value: 76.08055225783757
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 80.83007234777145
- type: cos_sim_spearman
value: 79.76446808992547
- type: euclidean_pearson
value: 80.24418669808917
- type: euclidean_spearman
value: 79.76446808992547
- type: manhattan_pearson
value: 79.58896133042379
- type: manhattan_spearman
value: 78.9614377441415
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 78.6038961038961
- type: f1
value: 77.95572823168757
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 30.240388191413935
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 22.670413424756212
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.694
- type: map_at_10
value: 43.811
- type: map_at_100
value: 45.274
- type: map_at_1000
value: 45.393
- type: map_at_3
value: 40.043
- type: map_at_5
value: 41.983
- type: mrr_at_1
value: 39.628
- type: mrr_at_10
value: 49.748
- type: mrr_at_100
value: 50.356
- type: mrr_at_1000
value: 50.39900000000001
- type: mrr_at_3
value: 46.924
- type: mrr_at_5
value: 48.598
- type: ndcg_at_1
value: 39.628
- type: ndcg_at_10
value: 50.39
- type: ndcg_at_100
value: 55.489
- type: ndcg_at_1000
value: 57.291000000000004
- type: ndcg_at_3
value: 44.849
- type: ndcg_at_5
value: 47.195
- type: precision_at_1
value: 39.628
- type: precision_at_10
value: 9.714
- type: precision_at_100
value: 1.591
- type: precision_at_1000
value: 0.2
- type: precision_at_3
value: 21.507
- type: precision_at_5
value: 15.393
- type: recall_at_1
value: 32.694
- type: recall_at_10
value: 63.031000000000006
- type: recall_at_100
value: 84.49
- type: recall_at_1000
value: 96.148
- type: recall_at_3
value: 46.851
- type: recall_at_5
value: 53.64
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.183000000000003
- type: map_at_10
value: 38.796
- type: map_at_100
value: 40.117000000000004
- type: map_at_1000
value: 40.251
- type: map_at_3
value: 35.713
- type: map_at_5
value: 37.446
- type: mrr_at_1
value: 35.605
- type: mrr_at_10
value: 44.824000000000005
- type: mrr_at_100
value: 45.544000000000004
- type: mrr_at_1000
value: 45.59
- type: mrr_at_3
value: 42.452
- type: mrr_at_5
value: 43.891999999999996
- type: ndcg_at_1
value: 35.605
- type: ndcg_at_10
value: 44.857
- type: ndcg_at_100
value: 49.68
- type: ndcg_at_1000
value: 51.841
- type: ndcg_at_3
value: 40.445
- type: ndcg_at_5
value: 42.535000000000004
- type: precision_at_1
value: 35.605
- type: precision_at_10
value: 8.624
- type: precision_at_100
value: 1.438
- type: precision_at_1000
value: 0.193
- type: precision_at_3
value: 19.808999999999997
- type: precision_at_5
value: 14.191
- type: recall_at_1
value: 28.183000000000003
- type: recall_at_10
value: 55.742000000000004
- type: recall_at_100
value: 76.416
- type: recall_at_1000
value: 90.20899999999999
- type: recall_at_3
value: 42.488
- type: recall_at_5
value: 48.431999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.156
- type: map_at_10
value: 47.677
- type: map_at_100
value: 48.699999999999996
- type: map_at_1000
value: 48.756
- type: map_at_3
value: 44.467
- type: map_at_5
value: 46.132
- type: mrr_at_1
value: 41.567
- type: mrr_at_10
value: 51.06699999999999
- type: mrr_at_100
value: 51.800000000000004
- type: mrr_at_1000
value: 51.827999999999996
- type: mrr_at_3
value: 48.620999999999995
- type: mrr_at_5
value: 50.013
- type: ndcg_at_1
value: 41.567
- type: ndcg_at_10
value: 53.418
- type: ndcg_at_100
value: 57.743
- type: ndcg_at_1000
value: 58.940000000000005
- type: ndcg_at_3
value: 47.923
- type: ndcg_at_5
value: 50.352
- type: precision_at_1
value: 41.567
- type: precision_at_10
value: 8.74
- type: precision_at_100
value: 1.1809999999999998
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 21.337999999999997
- type: precision_at_5
value: 14.646
- type: recall_at_1
value: 36.156
- type: recall_at_10
value: 67.084
- type: recall_at_100
value: 86.299
- type: recall_at_1000
value: 94.82000000000001
- type: recall_at_3
value: 52.209
- type: recall_at_5
value: 58.175
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.513
- type: map_at_10
value: 32.699
- type: map_at_100
value: 33.788000000000004
- type: map_at_1000
value: 33.878
- type: map_at_3
value: 30.044999999999998
- type: map_at_5
value: 31.506
- type: mrr_at_1
value: 25.311
- type: mrr_at_10
value: 34.457
- type: mrr_at_100
value: 35.443999999999996
- type: mrr_at_1000
value: 35.504999999999995
- type: mrr_at_3
value: 31.902
- type: mrr_at_5
value: 33.36
- type: ndcg_at_1
value: 25.311
- type: ndcg_at_10
value: 37.929
- type: ndcg_at_100
value: 43.1
- type: ndcg_at_1000
value: 45.275999999999996
- type: ndcg_at_3
value: 32.745999999999995
- type: ndcg_at_5
value: 35.235
- type: precision_at_1
value: 25.311
- type: precision_at_10
value: 6.034
- type: precision_at_100
value: 0.8959999999999999
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 14.237
- type: precision_at_5
value: 10.034
- type: recall_at_1
value: 23.513
- type: recall_at_10
value: 52.312999999999995
- type: recall_at_100
value: 75.762
- type: recall_at_1000
value: 91.85799999999999
- type: recall_at_3
value: 38.222
- type: recall_at_5
value: 44.316
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.333000000000002
- type: map_at_10
value: 24.605
- type: map_at_100
value: 25.924000000000003
- type: map_at_1000
value: 26.039
- type: map_at_3
value: 21.907
- type: map_at_5
value: 23.294999999999998
- type: mrr_at_1
value: 20.647
- type: mrr_at_10
value: 29.442
- type: mrr_at_100
value: 30.54
- type: mrr_at_1000
value: 30.601
- type: mrr_at_3
value: 26.802999999999997
- type: mrr_at_5
value: 28.147
- type: ndcg_at_1
value: 20.647
- type: ndcg_at_10
value: 30.171999999999997
- type: ndcg_at_100
value: 36.466
- type: ndcg_at_1000
value: 39.095
- type: ndcg_at_3
value: 25.134
- type: ndcg_at_5
value: 27.211999999999996
- type: precision_at_1
value: 20.647
- type: precision_at_10
value: 5.659
- type: precision_at_100
value: 1.012
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 12.148
- type: precision_at_5
value: 8.881
- type: recall_at_1
value: 16.333000000000002
- type: recall_at_10
value: 42.785000000000004
- type: recall_at_100
value: 70.282
- type: recall_at_1000
value: 88.539
- type: recall_at_3
value: 28.307
- type: recall_at_5
value: 33.751
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.821
- type: map_at_10
value: 37.188
- type: map_at_100
value: 38.516
- type: map_at_1000
value: 38.635000000000005
- type: map_at_3
value: 33.821
- type: map_at_5
value: 35.646
- type: mrr_at_1
value: 33.109
- type: mrr_at_10
value: 43.003
- type: mrr_at_100
value: 43.849
- type: mrr_at_1000
value: 43.889
- type: mrr_at_3
value: 40.263
- type: mrr_at_5
value: 41.957
- type: ndcg_at_1
value: 33.109
- type: ndcg_at_10
value: 43.556
- type: ndcg_at_100
value: 49.197
- type: ndcg_at_1000
value: 51.269
- type: ndcg_at_3
value: 38.01
- type: ndcg_at_5
value: 40.647
- type: precision_at_1
value: 33.109
- type: precision_at_10
value: 8.085
- type: precision_at_100
value: 1.286
- type: precision_at_1000
value: 0.166
- type: precision_at_3
value: 18.191
- type: precision_at_5
value: 13.050999999999998
- type: recall_at_1
value: 26.821
- type: recall_at_10
value: 56.818000000000005
- type: recall_at_100
value: 80.63
- type: recall_at_1000
value: 94.042
- type: recall_at_3
value: 41.266000000000005
- type: recall_at_5
value: 48.087999999999994
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.169
- type: map_at_10
value: 31.682
- type: map_at_100
value: 32.988
- type: map_at_1000
value: 33.097
- type: map_at_3
value: 28.708
- type: map_at_5
value: 30.319000000000003
- type: mrr_at_1
value: 27.854
- type: mrr_at_10
value: 36.814
- type: mrr_at_100
value: 37.741
- type: mrr_at_1000
value: 37.798
- type: mrr_at_3
value: 34.418
- type: mrr_at_5
value: 35.742000000000004
- type: ndcg_at_1
value: 27.854
- type: ndcg_at_10
value: 37.388
- type: ndcg_at_100
value: 43.342999999999996
- type: ndcg_at_1000
value: 45.829
- type: ndcg_at_3
value: 32.512
- type: ndcg_at_5
value: 34.613
- type: precision_at_1
value: 27.854
- type: precision_at_10
value: 7.031999999999999
- type: precision_at_100
value: 1.18
- type: precision_at_1000
value: 0.158
- type: precision_at_3
value: 15.753
- type: precision_at_5
value: 11.301
- type: recall_at_1
value: 22.169
- type: recall_at_10
value: 49.44
- type: recall_at_100
value: 75.644
- type: recall_at_1000
value: 92.919
- type: recall_at_3
value: 35.528999999999996
- type: recall_at_5
value: 41.271
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.20158333333334
- type: map_at_10
value: 33.509
- type: map_at_100
value: 34.76525
- type: map_at_1000
value: 34.885999999999996
- type: map_at_3
value: 30.594333333333335
- type: map_at_5
value: 32.160666666666664
- type: mrr_at_1
value: 28.803833333333333
- type: mrr_at_10
value: 37.61358333333333
- type: mrr_at_100
value: 38.5105
- type: mrr_at_1000
value: 38.56841666666667
- type: mrr_at_3
value: 35.090666666666664
- type: mrr_at_5
value: 36.49575
- type: ndcg_at_1
value: 28.803833333333333
- type: ndcg_at_10
value: 39.038333333333334
- type: ndcg_at_100
value: 44.49175
- type: ndcg_at_1000
value: 46.835499999999996
- type: ndcg_at_3
value: 34.011916666666664
- type: ndcg_at_5
value: 36.267
- type: precision_at_1
value: 28.803833333333333
- type: precision_at_10
value: 6.974583333333334
- type: precision_at_100
value: 1.1565
- type: precision_at_1000
value: 0.15533333333333332
- type: precision_at_3
value: 15.78025
- type: precision_at_5
value: 11.279583333333333
- type: recall_at_1
value: 24.20158333333334
- type: recall_at_10
value: 51.408
- type: recall_at_100
value: 75.36958333333334
- type: recall_at_1000
value: 91.5765
- type: recall_at_3
value: 37.334500000000006
- type: recall_at_5
value: 43.14666666666667
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.394
- type: map_at_10
value: 28.807
- type: map_at_100
value: 29.851
- type: map_at_1000
value: 29.959999999999997
- type: map_at_3
value: 26.694000000000003
- type: map_at_5
value: 27.805999999999997
- type: mrr_at_1
value: 23.773
- type: mrr_at_10
value: 30.895
- type: mrr_at_100
value: 31.894
- type: mrr_at_1000
value: 31.971
- type: mrr_at_3
value: 28.988000000000003
- type: mrr_at_5
value: 29.908
- type: ndcg_at_1
value: 23.773
- type: ndcg_at_10
value: 32.976
- type: ndcg_at_100
value: 38.109
- type: ndcg_at_1000
value: 40.797
- type: ndcg_at_3
value: 28.993999999999996
- type: ndcg_at_5
value: 30.659999999999997
- type: precision_at_1
value: 23.773
- type: precision_at_10
value: 5.2299999999999995
- type: precision_at_100
value: 0.857
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 12.73
- type: precision_at_5
value: 8.741999999999999
- type: recall_at_1
value: 21.394
- type: recall_at_10
value: 43.75
- type: recall_at_100
value: 66.765
- type: recall_at_1000
value: 86.483
- type: recall_at_3
value: 32.542
- type: recall_at_5
value: 36.689
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.266
- type: map_at_10
value: 23.639
- type: map_at_100
value: 24.814
- type: map_at_1000
value: 24.948
- type: map_at_3
value: 21.401999999999997
- type: map_at_5
value: 22.581
- type: mrr_at_1
value: 19.718
- type: mrr_at_10
value: 27.276
- type: mrr_at_100
value: 28.252
- type: mrr_at_1000
value: 28.33
- type: mrr_at_3
value: 25.086000000000002
- type: mrr_at_5
value: 26.304
- type: ndcg_at_1
value: 19.718
- type: ndcg_at_10
value: 28.254
- type: ndcg_at_100
value: 34.022999999999996
- type: ndcg_at_1000
value: 37.031
- type: ndcg_at_3
value: 24.206
- type: ndcg_at_5
value: 26.009
- type: precision_at_1
value: 19.718
- type: precision_at_10
value: 5.189
- type: precision_at_100
value: 0.9690000000000001
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_3
value: 11.551
- type: precision_at_5
value: 8.362
- type: recall_at_1
value: 16.266
- type: recall_at_10
value: 38.550000000000004
- type: recall_at_100
value: 64.63499999999999
- type: recall_at_1000
value: 86.059
- type: recall_at_3
value: 27.156000000000002
- type: recall_at_5
value: 31.829
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.124000000000002
- type: map_at_10
value: 35.099000000000004
- type: map_at_100
value: 36.269
- type: map_at_1000
value: 36.388999999999996
- type: map_at_3
value: 32.017
- type: map_at_5
value: 33.614
- type: mrr_at_1
value: 31.25
- type: mrr_at_10
value: 39.269999999999996
- type: mrr_at_100
value: 40.134
- type: mrr_at_1000
value: 40.197
- type: mrr_at_3
value: 36.536
- type: mrr_at_5
value: 37.842
- type: ndcg_at_1
value: 31.25
- type: ndcg_at_10
value: 40.643
- type: ndcg_at_100
value: 45.967999999999996
- type: ndcg_at_1000
value: 48.455999999999996
- type: ndcg_at_3
value: 34.954
- type: ndcg_at_5
value: 37.273
- type: precision_at_1
value: 31.25
- type: precision_at_10
value: 6.894
- type: precision_at_100
value: 1.086
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_3
value: 15.672
- type: precision_at_5
value: 11.082
- type: recall_at_1
value: 26.124000000000002
- type: recall_at_10
value: 53.730999999999995
- type: recall_at_100
value: 76.779
- type: recall_at_1000
value: 93.908
- type: recall_at_3
value: 37.869
- type: recall_at_5
value: 43.822
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.776
- type: map_at_10
value: 31.384
- type: map_at_100
value: 33.108
- type: map_at_1000
value: 33.339
- type: map_at_3
value: 28.269
- type: map_at_5
value: 30.108
- type: mrr_at_1
value: 26.482
- type: mrr_at_10
value: 35.876000000000005
- type: mrr_at_100
value: 36.887
- type: mrr_at_1000
value: 36.949
- type: mrr_at_3
value: 32.971000000000004
- type: mrr_at_5
value: 34.601
- type: ndcg_at_1
value: 26.482
- type: ndcg_at_10
value: 37.403999999999996
- type: ndcg_at_100
value: 43.722
- type: ndcg_at_1000
value: 46.417
- type: ndcg_at_3
value: 32.149
- type: ndcg_at_5
value: 34.818
- type: precision_at_1
value: 26.482
- type: precision_at_10
value: 7.411
- type: precision_at_100
value: 1.532
- type: precision_at_1000
value: 0.24
- type: precision_at_3
value: 15.152
- type: precision_at_5
value: 11.501999999999999
- type: recall_at_1
value: 21.776
- type: recall_at_10
value: 49.333
- type: recall_at_100
value: 76.753
- type: recall_at_1000
value: 93.762
- type: recall_at_3
value: 35.329
- type: recall_at_5
value: 41.82
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.990000000000002
- type: map_at_10
value: 26.721
- type: map_at_100
value: 27.833999999999996
- type: map_at_1000
value: 27.947
- type: map_at_3
value: 24.046
- type: map_at_5
value: 25.491999999999997
- type: mrr_at_1
value: 20.702
- type: mrr_at_10
value: 28.691
- type: mrr_at_100
value: 29.685
- type: mrr_at_1000
value: 29.764000000000003
- type: mrr_at_3
value: 26.124000000000002
- type: mrr_at_5
value: 27.584999999999997
- type: ndcg_at_1
value: 20.702
- type: ndcg_at_10
value: 31.473000000000003
- type: ndcg_at_100
value: 37.061
- type: ndcg_at_1000
value: 39.784000000000006
- type: ndcg_at_3
value: 26.221
- type: ndcg_at_5
value: 28.655
- type: precision_at_1
value: 20.702
- type: precision_at_10
value: 5.083
- type: precision_at_100
value: 0.8500000000000001
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 11.275
- type: precision_at_5
value: 8.17
- type: recall_at_1
value: 18.990000000000002
- type: recall_at_10
value: 44.318999999999996
- type: recall_at_100
value: 69.98
- type: recall_at_1000
value: 90.171
- type: recall_at_3
value: 30.246000000000002
- type: recall_at_5
value: 35.927
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.584
- type: map_at_10
value: 16.148
- type: map_at_100
value: 17.727
- type: map_at_1000
value: 17.913999999999998
- type: map_at_3
value: 13.456000000000001
- type: map_at_5
value: 14.841999999999999
- type: mrr_at_1
value: 21.564
- type: mrr_at_10
value: 31.579
- type: mrr_at_100
value: 32.586999999999996
- type: mrr_at_1000
value: 32.638
- type: mrr_at_3
value: 28.294999999999998
- type: mrr_at_5
value: 30.064
- type: ndcg_at_1
value: 21.564
- type: ndcg_at_10
value: 23.294999999999998
- type: ndcg_at_100
value: 29.997
- type: ndcg_at_1000
value: 33.517
- type: ndcg_at_3
value: 18.759
- type: ndcg_at_5
value: 20.324
- type: precision_at_1
value: 21.564
- type: precision_at_10
value: 7.362
- type: precision_at_100
value: 1.451
- type: precision_at_1000
value: 0.21
- type: precision_at_3
value: 13.919999999999998
- type: precision_at_5
value: 10.879
- type: recall_at_1
value: 9.584
- type: recall_at_10
value: 28.508
- type: recall_at_100
value: 51.873999999999995
- type: recall_at_1000
value: 71.773
- type: recall_at_3
value: 17.329
- type: recall_at_5
value: 21.823
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.034
- type: map_at_10
value: 14.664
- type: map_at_100
value: 19.652
- type: map_at_1000
value: 20.701
- type: map_at_3
value: 10.626
- type: map_at_5
value: 12.334
- type: mrr_at_1
value: 54
- type: mrr_at_10
value: 63.132
- type: mrr_at_100
value: 63.639
- type: mrr_at_1000
value: 63.663000000000004
- type: mrr_at_3
value: 61.083
- type: mrr_at_5
value: 62.483
- type: ndcg_at_1
value: 42.875
- type: ndcg_at_10
value: 32.04
- type: ndcg_at_100
value: 35.157
- type: ndcg_at_1000
value: 41.4
- type: ndcg_at_3
value: 35.652
- type: ndcg_at_5
value: 33.617000000000004
- type: precision_at_1
value: 54
- type: precision_at_10
value: 25.55
- type: precision_at_100
value: 7.5600000000000005
- type: precision_at_1000
value: 1.577
- type: precision_at_3
value: 38.833
- type: precision_at_5
value: 33.15
- type: recall_at_1
value: 7.034
- type: recall_at_10
value: 19.627
- type: recall_at_100
value: 40.528
- type: recall_at_1000
value: 60.789
- type: recall_at_3
value: 11.833
- type: recall_at_5
value: 14.804
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 39.6
- type: f1
value: 35.3770765501984
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 35.098
- type: map_at_10
value: 46.437
- type: map_at_100
value: 47.156
- type: map_at_1000
value: 47.193000000000005
- type: map_at_3
value: 43.702000000000005
- type: map_at_5
value: 45.326
- type: mrr_at_1
value: 37.774
- type: mrr_at_10
value: 49.512
- type: mrr_at_100
value: 50.196
- type: mrr_at_1000
value: 50.224000000000004
- type: mrr_at_3
value: 46.747
- type: mrr_at_5
value: 48.415
- type: ndcg_at_1
value: 37.774
- type: ndcg_at_10
value: 52.629000000000005
- type: ndcg_at_100
value: 55.995
- type: ndcg_at_1000
value: 56.962999999999994
- type: ndcg_at_3
value: 47.188
- type: ndcg_at_5
value: 50.019000000000005
- type: precision_at_1
value: 37.774
- type: precision_at_10
value: 7.541
- type: precision_at_100
value: 0.931
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 19.572
- type: precision_at_5
value: 13.288
- type: recall_at_1
value: 35.098
- type: recall_at_10
value: 68.818
- type: recall_at_100
value: 84.004
- type: recall_at_1000
value: 91.36800000000001
- type: recall_at_3
value: 54.176
- type: recall_at_5
value: 60.968999999999994
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.982
- type: map_at_10
value: 28.994999999999997
- type: map_at_100
value: 30.868000000000002
- type: map_at_1000
value: 31.045
- type: map_at_3
value: 25.081999999999997
- type: map_at_5
value: 27.303
- type: mrr_at_1
value: 35.031
- type: mrr_at_10
value: 43.537
- type: mrr_at_100
value: 44.422
- type: mrr_at_1000
value: 44.471
- type: mrr_at_3
value: 41.024
- type: mrr_at_5
value: 42.42
- type: ndcg_at_1
value: 35.031
- type: ndcg_at_10
value: 36.346000000000004
- type: ndcg_at_100
value: 43.275000000000006
- type: ndcg_at_1000
value: 46.577
- type: ndcg_at_3
value: 32.42
- type: ndcg_at_5
value: 33.841
- type: precision_at_1
value: 35.031
- type: precision_at_10
value: 10.231
- type: precision_at_100
value: 1.728
- type: precision_at_1000
value: 0.231
- type: precision_at_3
value: 21.553
- type: precision_at_5
value: 16.204
- type: recall_at_1
value: 17.982
- type: recall_at_10
value: 43.169000000000004
- type: recall_at_100
value: 68.812
- type: recall_at_1000
value: 89.008
- type: recall_at_3
value: 29.309
- type: recall_at_5
value: 35.514
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.387
- type: map_at_10
value: 36.931000000000004
- type: map_at_100
value: 37.734
- type: map_at_1000
value: 37.818000000000005
- type: map_at_3
value: 34.691
- type: map_at_5
value: 36.016999999999996
- type: mrr_at_1
value: 54.774
- type: mrr_at_10
value: 62.133
- type: mrr_at_100
value: 62.587
- type: mrr_at_1000
value: 62.61600000000001
- type: mrr_at_3
value: 60.49099999999999
- type: mrr_at_5
value: 61.480999999999995
- type: ndcg_at_1
value: 54.774
- type: ndcg_at_10
value: 45.657
- type: ndcg_at_100
value: 48.954
- type: ndcg_at_1000
value: 50.78
- type: ndcg_at_3
value: 41.808
- type: ndcg_at_5
value: 43.816
- type: precision_at_1
value: 54.774
- type: precision_at_10
value: 9.479
- type: precision_at_100
value: 1.208
- type: precision_at_1000
value: 0.145
- type: precision_at_3
value: 25.856
- type: precision_at_5
value: 17.102
- type: recall_at_1
value: 27.387
- type: recall_at_10
value: 47.394
- type: recall_at_100
value: 60.397999999999996
- type: recall_at_1000
value: 72.54599999999999
- type: recall_at_3
value: 38.785
- type: recall_at_5
value: 42.754999999999995
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 61.217999999999996
- type: ap
value: 56.84286974948407
- type: f1
value: 60.99211195455131
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 19.224
- type: map_at_10
value: 30.448999999999998
- type: map_at_100
value: 31.663999999999998
- type: map_at_1000
value: 31.721
- type: map_at_3
value: 26.922
- type: map_at_5
value: 28.906
- type: mrr_at_1
value: 19.756
- type: mrr_at_10
value: 30.994
- type: mrr_at_100
value: 32.161
- type: mrr_at_1000
value: 32.213
- type: mrr_at_3
value: 27.502
- type: mrr_at_5
value: 29.48
- type: ndcg_at_1
value: 19.742
- type: ndcg_at_10
value: 36.833
- type: ndcg_at_100
value: 42.785000000000004
- type: ndcg_at_1000
value: 44.291000000000004
- type: ndcg_at_3
value: 29.580000000000002
- type: ndcg_at_5
value: 33.139
- type: precision_at_1
value: 19.742
- type: precision_at_10
value: 5.894
- type: precision_at_100
value: 0.889
- type: precision_at_1000
value: 0.10200000000000001
- type: precision_at_3
value: 12.665000000000001
- type: precision_at_5
value: 9.393
- type: recall_at_1
value: 19.224
- type: recall_at_10
value: 56.538999999999994
- type: recall_at_100
value: 84.237
- type: recall_at_1000
value: 95.965
- type: recall_at_3
value: 36.71
- type: recall_at_5
value: 45.283
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 89.97264021887824
- type: f1
value: 89.53607318488027
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 59.566803465572285
- type: f1
value: 40.94003955225124
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 66.7787491593813
- type: f1
value: 64.51190971513093
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 73.7794216543376
- type: f1
value: 72.71852261076475
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 28.40883054472429
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.144338339113617
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.894071459751267
- type: mrr
value: 31.965886150526256
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.024
- type: map_at_10
value: 10.533
- type: map_at_100
value: 12.97
- type: map_at_1000
value: 14.163
- type: map_at_3
value: 7.971
- type: map_at_5
value: 9.15
- type: mrr_at_1
value: 40.867
- type: mrr_at_10
value: 48.837
- type: mrr_at_100
value: 49.464999999999996
- type: mrr_at_1000
value: 49.509
- type: mrr_at_3
value: 46.800999999999995
- type: mrr_at_5
value: 47.745
- type: ndcg_at_1
value: 38.854
- type: ndcg_at_10
value: 29.674
- type: ndcg_at_100
value: 26.66
- type: ndcg_at_1000
value: 35.088
- type: ndcg_at_3
value: 34.838
- type: ndcg_at_5
value: 32.423
- type: precision_at_1
value: 40.248
- type: precision_at_10
value: 21.826999999999998
- type: precision_at_100
value: 6.78
- type: precision_at_1000
value: 1.889
- type: precision_at_3
value: 32.405
- type: precision_at_5
value: 27.74
- type: recall_at_1
value: 5.024
- type: recall_at_10
value: 13.996
- type: recall_at_100
value: 26.636
- type: recall_at_1000
value: 57.816
- type: recall_at_3
value: 9.063
- type: recall_at_5
value: 10.883
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.088
- type: map_at_10
value: 36.915
- type: map_at_100
value: 38.141999999999996
- type: map_at_1000
value: 38.191
- type: map_at_3
value: 32.458999999999996
- type: map_at_5
value: 35.004999999999995
- type: mrr_at_1
value: 26.101000000000003
- type: mrr_at_10
value: 39.1
- type: mrr_at_100
value: 40.071
- type: mrr_at_1000
value: 40.106
- type: mrr_at_3
value: 35.236000000000004
- type: mrr_at_5
value: 37.43
- type: ndcg_at_1
value: 26.072
- type: ndcg_at_10
value: 44.482
- type: ndcg_at_100
value: 49.771
- type: ndcg_at_1000
value: 50.903
- type: ndcg_at_3
value: 35.922
- type: ndcg_at_5
value: 40.178000000000004
- type: precision_at_1
value: 26.072
- type: precision_at_10
value: 7.795000000000001
- type: precision_at_100
value: 1.072
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 16.725
- type: precision_at_5
value: 12.468
- type: recall_at_1
value: 23.088
- type: recall_at_10
value: 65.534
- type: recall_at_100
value: 88.68
- type: recall_at_1000
value: 97.101
- type: recall_at_3
value: 43.161
- type: recall_at_5
value: 52.959999999999994
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 69.612
- type: map_at_10
value: 83.292
- type: map_at_100
value: 83.96000000000001
- type: map_at_1000
value: 83.978
- type: map_at_3
value: 80.26299999999999
- type: map_at_5
value: 82.11500000000001
- type: mrr_at_1
value: 80.21000000000001
- type: mrr_at_10
value: 86.457
- type: mrr_at_100
value: 86.58500000000001
- type: mrr_at_1000
value: 86.587
- type: mrr_at_3
value: 85.452
- type: mrr_at_5
value: 86.101
- type: ndcg_at_1
value: 80.21000000000001
- type: ndcg_at_10
value: 87.208
- type: ndcg_at_100
value: 88.549
- type: ndcg_at_1000
value: 88.683
- type: ndcg_at_3
value: 84.20400000000001
- type: ndcg_at_5
value: 85.768
- type: precision_at_1
value: 80.21000000000001
- type: precision_at_10
value: 13.29
- type: precision_at_100
value: 1.5230000000000001
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.767
- type: precision_at_5
value: 24.2
- type: recall_at_1
value: 69.612
- type: recall_at_10
value: 94.651
- type: recall_at_100
value: 99.297
- type: recall_at_1000
value: 99.95100000000001
- type: recall_at_3
value: 86.003
- type: recall_at_5
value: 90.45100000000001
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 46.28945925252077
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 50.954446620859684
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.888
- type: map_at_10
value: 9.21
- type: map_at_100
value: 10.629
- type: map_at_1000
value: 10.859
- type: map_at_3
value: 6.743
- type: map_at_5
value: 7.982
- type: mrr_at_1
value: 19.1
- type: mrr_at_10
value: 28.294000000000004
- type: mrr_at_100
value: 29.326999999999998
- type: mrr_at_1000
value: 29.414
- type: mrr_at_3
value: 25.367
- type: mrr_at_5
value: 27.002
- type: ndcg_at_1
value: 19.1
- type: ndcg_at_10
value: 15.78
- type: ndcg_at_100
value: 21.807000000000002
- type: ndcg_at_1000
value: 26.593
- type: ndcg_at_3
value: 15.204999999999998
- type: ndcg_at_5
value: 13.217
- type: precision_at_1
value: 19.1
- type: precision_at_10
value: 7.9799999999999995
- type: precision_at_100
value: 1.667
- type: precision_at_1000
value: 0.28300000000000003
- type: precision_at_3
value: 13.933000000000002
- type: precision_at_5
value: 11.379999999999999
- type: recall_at_1
value: 3.888
- type: recall_at_10
value: 16.17
- type: recall_at_100
value: 33.848
- type: recall_at_1000
value: 57.345
- type: recall_at_3
value: 8.468
- type: recall_at_5
value: 11.540000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 79.05803116288386
- type: cos_sim_spearman
value: 70.0403855402571
- type: euclidean_pearson
value: 75.59006280166072
- type: euclidean_spearman
value: 70.04038926247613
- type: manhattan_pearson
value: 75.48136278078455
- type: manhattan_spearman
value: 69.9608897701754
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 68.56836430603597
- type: cos_sim_spearman
value: 64.38407759822387
- type: euclidean_pearson
value: 65.93619045541732
- type: euclidean_spearman
value: 64.38184049884836
- type: manhattan_pearson
value: 65.97148637646873
- type: manhattan_spearman
value: 64.48011982438929
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 75.990362280318
- type: cos_sim_spearman
value: 76.40621890996734
- type: euclidean_pearson
value: 76.01739766577184
- type: euclidean_spearman
value: 76.4062736496846
- type: manhattan_pearson
value: 76.04738378838042
- type: manhattan_spearman
value: 76.44991409719592
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 74.8516957692617
- type: cos_sim_spearman
value: 69.325199098278
- type: euclidean_pearson
value: 73.37922793254768
- type: euclidean_spearman
value: 69.32520119670215
- type: manhattan_pearson
value: 73.3795212376615
- type: manhattan_spearman
value: 69.35306787926315
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 78.644002190612
- type: cos_sim_spearman
value: 80.18337978181648
- type: euclidean_pearson
value: 79.7628642371887
- type: euclidean_spearman
value: 80.18337906907526
- type: manhattan_pearson
value: 79.68810722704522
- type: manhattan_spearman
value: 80.10664518173466
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 77.8303940874723
- type: cos_sim_spearman
value: 79.56812599677549
- type: euclidean_pearson
value: 79.38928950396344
- type: euclidean_spearman
value: 79.56812556750812
- type: manhattan_pearson
value: 79.41057583507681
- type: manhattan_spearman
value: 79.57604428731142
- 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: 78.90792116013353
- type: cos_sim_spearman
value: 81.18059230233499
- type: euclidean_pearson
value: 80.2622631297375
- type: euclidean_spearman
value: 81.18059230233499
- type: manhattan_pearson
value: 80.23946026135997
- type: manhattan_spearman
value: 81.11947325071426
- 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: 64.46850619973324
- type: cos_sim_spearman
value: 65.50839374141563
- type: euclidean_pearson
value: 66.60130812260707
- type: euclidean_spearman
value: 65.50839374141563
- type: manhattan_pearson
value: 66.58871918195092
- type: manhattan_spearman
value: 65.7347325297592
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 75.71536124107834
- type: cos_sim_spearman
value: 75.98365906208434
- type: euclidean_pearson
value: 76.64573753881218
- type: euclidean_spearman
value: 75.98365906208434
- type: manhattan_pearson
value: 76.63637189172626
- type: manhattan_spearman
value: 75.9660207821009
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 74.27669440147513
- type: mrr
value: 91.7729356699945
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 41.028
- type: map_at_10
value: 49.919000000000004
- type: map_at_100
value: 50.91
- type: map_at_1000
value: 50.955
- type: map_at_3
value: 47.785
- type: map_at_5
value: 49.084
- type: mrr_at_1
value: 43.667
- type: mrr_at_10
value: 51.342
- type: mrr_at_100
value: 52.197
- type: mrr_at_1000
value: 52.236000000000004
- type: mrr_at_3
value: 49.667
- type: mrr_at_5
value: 50.766999999999996
- type: ndcg_at_1
value: 43.667
- type: ndcg_at_10
value: 54.029
- type: ndcg_at_100
value: 58.909
- type: ndcg_at_1000
value: 60.131
- type: ndcg_at_3
value: 50.444
- type: ndcg_at_5
value: 52.354
- type: precision_at_1
value: 43.667
- type: precision_at_10
value: 7.432999999999999
- type: precision_at_100
value: 1
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 20.444000000000003
- type: precision_at_5
value: 13.533000000000001
- type: recall_at_1
value: 41.028
- type: recall_at_10
value: 65.011
- type: recall_at_100
value: 88.033
- type: recall_at_1000
value: 97.667
- type: recall_at_3
value: 55.394
- type: recall_at_5
value: 60.183
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.76534653465346
- type: cos_sim_ap
value: 93.83756773536699
- type: cos_sim_f1
value: 87.91097622660598
- type: cos_sim_precision
value: 88.94575230296827
- type: cos_sim_recall
value: 86.9
- type: dot_accuracy
value: 99.76534653465346
- type: dot_ap
value: 93.83756773536699
- type: dot_f1
value: 87.91097622660598
- type: dot_precision
value: 88.94575230296827
- type: dot_recall
value: 86.9
- type: euclidean_accuracy
value: 99.76534653465346
- type: euclidean_ap
value: 93.837567735367
- type: euclidean_f1
value: 87.91097622660598
- type: euclidean_precision
value: 88.94575230296827
- type: euclidean_recall
value: 86.9
- type: manhattan_accuracy
value: 99.76633663366337
- type: manhattan_ap
value: 93.84480825492724
- type: manhattan_f1
value: 87.97145769622833
- type: manhattan_precision
value: 89.70893970893971
- type: manhattan_recall
value: 86.3
- type: max_accuracy
value: 99.76633663366337
- type: max_ap
value: 93.84480825492724
- type: max_f1
value: 87.97145769622833
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 48.078155553339585
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.34857297824906
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 50.06219491505384
- type: mrr
value: 50.77479097699686
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.48401937651373
- type: cos_sim_spearman
value: 31.048654273022606
- type: dot_pearson
value: 30.484020082707847
- type: dot_spearman
value: 31.048654273022606
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.183
- type: map_at_10
value: 1.32
- type: map_at_100
value: 7.01
- type: map_at_1000
value: 16.957
- type: map_at_3
value: 0.481
- type: map_at_5
value: 0.737
- type: mrr_at_1
value: 66
- type: mrr_at_10
value: 78.7
- type: mrr_at_100
value: 78.7
- type: mrr_at_1000
value: 78.7
- type: mrr_at_3
value: 76
- type: mrr_at_5
value: 78.7
- type: ndcg_at_1
value: 56.99999999999999
- type: ndcg_at_10
value: 55.846
- type: ndcg_at_100
value: 43.138
- type: ndcg_at_1000
value: 39.4
- type: ndcg_at_3
value: 57.306999999999995
- type: ndcg_at_5
value: 57.294
- type: precision_at_1
value: 66
- type: precision_at_10
value: 60
- type: precision_at_100
value: 44.6
- type: precision_at_1000
value: 17.8
- type: precision_at_3
value: 62
- type: precision_at_5
value: 62
- type: recall_at_1
value: 0.183
- type: recall_at_10
value: 1.583
- type: recall_at_100
value: 10.412
- type: recall_at_1000
value: 37.358999999999995
- type: recall_at_3
value: 0.516
- type: recall_at_5
value: 0.845
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.7420000000000002
- type: map_at_10
value: 6.4879999999999995
- type: map_at_100
value: 11.654
- type: map_at_1000
value: 13.23
- type: map_at_3
value: 3.148
- type: map_at_5
value: 4.825
- type: mrr_at_1
value: 18.367
- type: mrr_at_10
value: 30.258000000000003
- type: mrr_at_100
value: 31.570999999999998
- type: mrr_at_1000
value: 31.594
- type: mrr_at_3
value: 26.19
- type: mrr_at_5
value: 28.027
- type: ndcg_at_1
value: 15.306000000000001
- type: ndcg_at_10
value: 15.608
- type: ndcg_at_100
value: 28.808
- type: ndcg_at_1000
value: 41.603
- type: ndcg_at_3
value: 13.357
- type: ndcg_at_5
value: 15.306000000000001
- type: precision_at_1
value: 18.367
- type: precision_at_10
value: 15.101999999999999
- type: precision_at_100
value: 6.49
- type: precision_at_1000
value: 1.488
- type: precision_at_3
value: 14.966
- type: precision_at_5
value: 17.143
- type: recall_at_1
value: 1.7420000000000002
- type: recall_at_10
value: 12.267
- type: recall_at_100
value: 41.105999999999995
- type: recall_at_1000
value: 80.569
- type: recall_at_3
value: 4.009
- type: recall_at_5
value: 7.417999999999999
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 65.1178
- type: ap
value: 11.974961582206614
- type: f1
value: 50.24491996814835
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 51.63271080928127
- type: f1
value: 51.81589904316042
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 40.791709673552276
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.05418131966383
- type: cos_sim_ap
value: 64.72353098186304
- type: cos_sim_f1
value: 61.313330054107226
- type: cos_sim_precision
value: 57.415937356057114
- type: cos_sim_recall
value: 65.77836411609499
- type: dot_accuracy
value: 83.05418131966383
- type: dot_ap
value: 64.72352701424393
- type: dot_f1
value: 61.313330054107226
- type: dot_precision
value: 57.415937356057114
- type: dot_recall
value: 65.77836411609499
- type: euclidean_accuracy
value: 83.05418131966383
- type: euclidean_ap
value: 64.72353124585976
- type: euclidean_f1
value: 61.313330054107226
- type: euclidean_precision
value: 57.415937356057114
- type: euclidean_recall
value: 65.77836411609499
- type: manhattan_accuracy
value: 82.98861536627525
- type: manhattan_ap
value: 64.53981837182303
- type: manhattan_f1
value: 60.94911377930246
- type: manhattan_precision
value: 53.784056508577194
- type: manhattan_recall
value: 70.31662269129288
- type: max_accuracy
value: 83.05418131966383
- type: max_ap
value: 64.72353124585976
- type: max_f1
value: 61.313330054107226
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.06225016493966
- type: cos_sim_ap
value: 84.00829172423475
- type: cos_sim_f1
value: 76.1288446157202
- type: cos_sim_precision
value: 72.11737153877945
- type: cos_sim_recall
value: 80.61287342161995
- type: dot_accuracy
value: 88.06225016493966
- type: dot_ap
value: 84.00827913374181
- type: dot_f1
value: 76.1288446157202
- type: dot_precision
value: 72.11737153877945
- type: dot_recall
value: 80.61287342161995
- type: euclidean_accuracy
value: 88.06225016493966
- type: euclidean_ap
value: 84.00827099295034
- type: euclidean_f1
value: 76.1288446157202
- type: euclidean_precision
value: 72.11737153877945
- type: euclidean_recall
value: 80.61287342161995
- type: manhattan_accuracy
value: 88.05642876547523
- type: manhattan_ap
value: 83.9157542691417
- type: manhattan_f1
value: 76.09045667447307
- type: manhattan_precision
value: 72.50348675034869
- type: manhattan_recall
value: 80.05081613797351
- type: max_accuracy
value: 88.06225016493966
- type: max_ap
value: 84.00829172423475
- type: max_f1
value: 76.1288446157202
MTEB evaluation results on English language for 'multi-qa-MiniLM-L6-cos-v1' sbert model
Model and licence can be found here