metadata
tags:
- mteb
model-index:
- name: epoch_0_model
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 78.67164179104476
- type: ap
value: 42.7379383648841
- type: f1
value: 72.79997373883408
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 90.413775
- type: ap
value: 87.08812293673202
- type: f1
value: 90.39246586225426
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 47.80799999999999
- type: f1
value: 47.25679462673503
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.37
- type: map_at_10
value: 45.748
- type: map_at_100
value: 46.617
- type: map_at_1000
value: 46.622
- type: map_at_3
value: 40.564
- type: map_at_5
value: 43.69
- type: mrr_at_1
value: 30.868000000000002
- type: mrr_at_10
value: 45.905
- type: mrr_at_100
value: 46.787
- type: mrr_at_1000
value: 46.792
- type: mrr_at_3
value: 40.717999999999996
- type: mrr_at_5
value: 43.851
- type: ndcg_at_1
value: 30.37
- type: ndcg_at_10
value: 54.662
- type: ndcg_at_100
value: 58.23700000000001
- type: ndcg_at_1000
value: 58.373
- type: ndcg_at_3
value: 44.069
- type: ndcg_at_5
value: 49.728
- type: precision_at_1
value: 30.37
- type: precision_at_10
value: 8.321000000000002
- type: precision_at_100
value: 0.985
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 18.089
- type: precision_at_5
value: 13.613
- type: recall_at_1
value: 30.37
- type: recall_at_10
value: 83.21499999999999
- type: recall_at_100
value: 98.506
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 54.266999999999996
- type: recall_at_5
value: 68.065
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 45.85329429748079
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 36.12666783330692
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 57.58783867794241
- type: mrr
value: 71.84078617596622
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.92453139507079
- type: cos_sim_spearman
value: 85.37122234964886
- type: euclidean_pearson
value: 86.19345621799168
- type: euclidean_spearman
value: 85.37122234964886
- type: manhattan_pearson
value: 86.4685290616604
- type: manhattan_spearman
value: 85.91400580167537
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 83.81818181818181
- type: f1
value: 83.76155217378863
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 38.46362764203256
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 33.13807021168658
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.725
- type: map_at_10
value: 39.654
- type: map_at_100
value: 41.022
- type: map_at_1000
value: 41.144999999999996
- type: map_at_3
value: 36.819
- type: map_at_5
value: 38.376
- type: mrr_at_1
value: 36.195
- type: mrr_at_10
value: 45.171
- type: mrr_at_100
value: 45.987
- type: mrr_at_1000
value: 46.033
- type: mrr_at_3
value: 43.038
- type: mrr_at_5
value: 44.196000000000005
- type: ndcg_at_1
value: 36.195
- type: ndcg_at_10
value: 45.194
- type: ndcg_at_100
value: 50.516000000000005
- type: ndcg_at_1000
value: 52.739000000000004
- type: ndcg_at_3
value: 41.142
- type: ndcg_at_5
value: 42.973
- type: precision_at_1
value: 36.195
- type: precision_at_10
value: 8.312
- type: precision_at_100
value: 1.346
- type: precision_at_1000
value: 0.182
- type: precision_at_3
value: 19.599
- type: precision_at_5
value: 13.847999999999999
- type: recall_at_1
value: 29.725
- type: recall_at_10
value: 55.51199999999999
- type: recall_at_100
value: 78.182
- type: recall_at_1000
value: 92.727
- type: recall_at_3
value: 43.287
- type: recall_at_5
value: 48.732
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.23
- type: map_at_10
value: 40.091
- type: map_at_100
value: 41.251
- type: map_at_1000
value: 41.384
- type: map_at_3
value: 37.247
- type: map_at_5
value: 38.865
- type: mrr_at_1
value: 38.279999999999994
- type: mrr_at_10
value: 46.288000000000004
- type: mrr_at_100
value: 47.022999999999996
- type: mrr_at_1000
value: 47.068
- type: mrr_at_3
value: 44.395
- type: mrr_at_5
value: 45.446
- type: ndcg_at_1
value: 38.279999999999994
- type: ndcg_at_10
value: 45.647
- type: ndcg_at_100
value: 49.851
- type: ndcg_at_1000
value: 51.991
- type: ndcg_at_3
value: 41.795
- type: ndcg_at_5
value: 43.578
- type: precision_at_1
value: 38.279999999999994
- type: precision_at_10
value: 8.522
- type: precision_at_100
value: 1.361
- type: precision_at_1000
value: 0.185
- type: precision_at_3
value: 20.297
- type: precision_at_5
value: 14.255
- type: recall_at_1
value: 30.23
- type: recall_at_10
value: 55.094
- type: recall_at_100
value: 72.887
- type: recall_at_1000
value: 86.295
- type: recall_at_3
value: 43.244
- type: recall_at_5
value: 48.507
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.854
- type: map_at_10
value: 52.232
- type: map_at_100
value: 53.129000000000005
- type: map_at_1000
value: 53.185
- type: map_at_3
value: 49.094
- type: map_at_5
value: 50.834999999999994
- type: mrr_at_1
value: 46.708
- type: mrr_at_10
value: 56.021
- type: mrr_at_100
value: 56.584
- type: mrr_at_1000
value: 56.611999999999995
- type: mrr_at_3
value: 53.657
- type: mrr_at_5
value: 55.027
- type: ndcg_at_1
value: 46.708
- type: ndcg_at_10
value: 57.89
- type: ndcg_at_100
value: 61.541999999999994
- type: ndcg_at_1000
value: 62.754
- type: ndcg_at_3
value: 52.632
- type: ndcg_at_5
value: 55.104
- type: precision_at_1
value: 46.708
- type: precision_at_10
value: 9.122
- type: precision_at_100
value: 1.187
- type: precision_at_1000
value: 0.134
- type: precision_at_3
value: 23.072
- type: precision_at_5
value: 15.661
- type: recall_at_1
value: 40.854
- type: recall_at_10
value: 70.98
- type: recall_at_100
value: 86.947
- type: recall_at_1000
value: 95.62
- type: recall_at_3
value: 56.782999999999994
- type: recall_at_5
value: 62.980000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.366
- type: map_at_10
value: 33.674
- type: map_at_100
value: 34.58
- type: map_at_1000
value: 34.662
- type: map_at_3
value: 31.596999999999998
- type: map_at_5
value: 32.596000000000004
- type: mrr_at_1
value: 28.588
- type: mrr_at_10
value: 35.912
- type: mrr_at_100
value: 36.696
- type: mrr_at_1000
value: 36.760999999999996
- type: mrr_at_3
value: 33.823
- type: mrr_at_5
value: 34.829
- type: ndcg_at_1
value: 28.588
- type: ndcg_at_10
value: 38.031
- type: ndcg_at_100
value: 42.678
- type: ndcg_at_1000
value: 44.871
- type: ndcg_at_3
value: 33.815
- type: ndcg_at_5
value: 35.531
- type: precision_at_1
value: 28.588
- type: precision_at_10
value: 5.638
- type: precision_at_100
value: 0.8380000000000001
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 13.974
- type: precision_at_5
value: 9.401
- type: recall_at_1
value: 26.366
- type: recall_at_10
value: 49.353
- type: recall_at_100
value: 71.194
- type: recall_at_1000
value: 87.842
- type: recall_at_3
value: 37.829
- type: recall_at_5
value: 41.976
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.634
- type: map_at_10
value: 23.271
- type: map_at_100
value: 24.366
- type: map_at_1000
value: 24.484
- type: map_at_3
value: 21.075
- type: map_at_5
value: 22.364
- type: mrr_at_1
value: 20.522000000000002
- type: mrr_at_10
value: 27.735
- type: mrr_at_100
value: 28.691
- type: mrr_at_1000
value: 28.762999999999998
- type: mrr_at_3
value: 25.518
- type: mrr_at_5
value: 26.762000000000004
- type: ndcg_at_1
value: 20.522000000000002
- type: ndcg_at_10
value: 27.791
- type: ndcg_at_100
value: 33.101
- type: ndcg_at_1000
value: 36.075
- type: ndcg_at_3
value: 23.74
- type: ndcg_at_5
value: 25.691000000000003
- type: precision_at_1
value: 20.522000000000002
- type: precision_at_10
value: 4.963
- type: precision_at_100
value: 0.873
- type: precision_at_1000
value: 0.128
- type: precision_at_3
value: 11.111
- type: precision_at_5
value: 8.01
- type: recall_at_1
value: 16.634
- type: recall_at_10
value: 37.498
- type: recall_at_100
value: 60.598
- type: recall_at_1000
value: 81.828
- type: recall_at_3
value: 26.136
- type: recall_at_5
value: 31.211
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.200999999999997
- type: map_at_10
value: 37.619
- type: map_at_100
value: 38.834999999999994
- type: map_at_1000
value: 38.951
- type: map_at_3
value: 35.119
- type: map_at_5
value: 36.559999999999995
- type: mrr_at_1
value: 33.782000000000004
- type: mrr_at_10
value: 43.033
- type: mrr_at_100
value: 43.761
- type: mrr_at_1000
value: 43.818
- type: mrr_at_3
value: 40.727999999999994
- type: mrr_at_5
value: 42.129
- type: ndcg_at_1
value: 33.782000000000004
- type: ndcg_at_10
value: 43.178
- type: ndcg_at_100
value: 48.27
- type: ndcg_at_1000
value: 50.559
- type: ndcg_at_3
value: 38.974
- type: ndcg_at_5
value: 41.019
- type: precision_at_1
value: 33.782000000000004
- type: precision_at_10
value: 7.575
- type: precision_at_100
value: 1.1820000000000002
- type: precision_at_1000
value: 0.154
- type: precision_at_3
value: 18.223
- type: precision_at_5
value: 12.742999999999999
- type: recall_at_1
value: 28.200999999999997
- type: recall_at_10
value: 54.089
- type: recall_at_100
value: 75.57000000000001
- type: recall_at_1000
value: 90.827
- type: recall_at_3
value: 42.435
- type: recall_at_5
value: 47.652
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.313000000000002
- type: map_at_10
value: 34.329
- type: map_at_100
value: 35.445
- type: map_at_1000
value: 35.556
- type: map_at_3
value: 31.659
- type: map_at_5
value: 32.981
- type: mrr_at_1
value: 30.822
- type: mrr_at_10
value: 39.084
- type: mrr_at_100
value: 39.97
- type: mrr_at_1000
value: 40.025
- type: mrr_at_3
value: 36.815
- type: mrr_at_5
value: 38.002
- type: ndcg_at_1
value: 30.822
- type: ndcg_at_10
value: 39.512
- type: ndcg_at_100
value: 44.925
- type: ndcg_at_1000
value: 47.274
- type: ndcg_at_3
value: 35.055
- type: ndcg_at_5
value: 36.788
- type: precision_at_1
value: 30.822
- type: precision_at_10
value: 7.1
- type: precision_at_100
value: 1.15
- type: precision_at_1000
value: 0.151
- type: precision_at_3
value: 16.476
- type: precision_at_5
value: 11.461
- type: recall_at_1
value: 25.313000000000002
- type: recall_at_10
value: 50.178
- type: recall_at_100
value: 74.312
- type: recall_at_1000
value: 90.50200000000001
- type: recall_at_3
value: 37.626
- type: recall_at_5
value: 42.34
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.502250000000004
- type: map_at_10
value: 33.655166666666666
- type: map_at_100
value: 34.72833333333333
- type: map_at_1000
value: 34.84375
- type: map_at_3
value: 31.253999999999998
- type: map_at_5
value: 32.55075
- type: mrr_at_1
value: 29.91975
- type: mrr_at_10
value: 37.65441666666667
- type: mrr_at_100
value: 38.464416666666665
- type: mrr_at_1000
value: 38.52591666666667
- type: mrr_at_3
value: 35.57858333333333
- type: mrr_at_5
value: 36.71083333333333
- type: ndcg_at_1
value: 29.91975
- type: ndcg_at_10
value: 38.47316666666667
- type: ndcg_at_100
value: 43.256416666666674
- type: ndcg_at_1000
value: 45.70658333333333
- type: ndcg_at_3
value: 34.350833333333334
- type: ndcg_at_5
value: 36.184583333333336
- type: precision_at_1
value: 29.91975
- type: precision_at_10
value: 6.5489999999999995
- type: precision_at_100
value: 1.0553333333333332
- type: precision_at_1000
value: 0.14516666666666667
- type: precision_at_3
value: 15.579083333333333
- type: precision_at_5
value: 10.851083333333332
- type: recall_at_1
value: 25.502250000000004
- type: recall_at_10
value: 48.7965
- type: recall_at_100
value: 69.93500000000002
- type: recall_at_1000
value: 87.17049999999999
- type: recall_at_3
value: 37.20433333333333
- type: recall_at_5
value: 42.00783333333333
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.777
- type: map_at_10
value: 29.932
- type: map_at_100
value: 30.778
- type: map_at_1000
value: 30.879
- type: map_at_3
value: 27.898
- type: map_at_5
value: 29.086000000000002
- type: mrr_at_1
value: 26.227
- type: mrr_at_10
value: 32.443
- type: mrr_at_100
value: 33.212
- type: mrr_at_1000
value: 33.29
- type: mrr_at_3
value: 30.419
- type: mrr_at_5
value: 31.616
- type: ndcg_at_1
value: 26.227
- type: ndcg_at_10
value: 33.774
- type: ndcg_at_100
value: 37.917
- type: ndcg_at_1000
value: 40.557
- type: ndcg_at_3
value: 29.875
- type: ndcg_at_5
value: 31.845000000000002
- type: precision_at_1
value: 26.227
- type: precision_at_10
value: 5.153
- type: precision_at_100
value: 0.784
- type: precision_at_1000
value: 0.108
- type: precision_at_3
value: 12.423
- type: precision_at_5
value: 8.773
- type: recall_at_1
value: 23.777
- type: recall_at_10
value: 43.142
- type: recall_at_100
value: 61.68900000000001
- type: recall_at_1000
value: 81.37100000000001
- type: recall_at_3
value: 32.582
- type: recall_at_5
value: 37.403
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.659
- type: map_at_10
value: 22.926
- type: map_at_100
value: 23.837
- type: map_at_1000
value: 23.953
- type: map_at_3
value: 21.029999999999998
- type: map_at_5
value: 22.019
- type: mrr_at_1
value: 19.649
- type: mrr_at_10
value: 26.32
- type: mrr_at_100
value: 27.143
- type: mrr_at_1000
value: 27.222
- type: mrr_at_3
value: 24.484
- type: mrr_at_5
value: 25.468000000000004
- type: ndcg_at_1
value: 19.649
- type: ndcg_at_10
value: 26.941
- type: ndcg_at_100
value: 31.522
- type: ndcg_at_1000
value: 34.538999999999994
- type: ndcg_at_3
value: 23.419999999999998
- type: ndcg_at_5
value: 24.927
- type: precision_at_1
value: 19.649
- type: precision_at_10
value: 4.7010000000000005
- type: precision_at_100
value: 0.8130000000000001
- type: precision_at_1000
value: 0.124
- type: precision_at_3
value: 10.735999999999999
- type: precision_at_5
value: 7.591
- type: recall_at_1
value: 16.659
- type: recall_at_10
value: 35.721000000000004
- type: recall_at_100
value: 56.43
- type: recall_at_1000
value: 78.464
- type: recall_at_3
value: 25.878
- type: recall_at_5
value: 29.731999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.309
- type: map_at_10
value: 31.990000000000002
- type: map_at_100
value: 32.895
- type: map_at_1000
value: 33
- type: map_at_3
value: 29.848999999999997
- type: map_at_5
value: 30.942999999999998
- type: mrr_at_1
value: 28.638
- type: mrr_at_10
value: 36.036
- type: mrr_at_100
value: 36.787
- type: mrr_at_1000
value: 36.855
- type: mrr_at_3
value: 34.08
- type: mrr_at_5
value: 35.073
- type: ndcg_at_1
value: 28.638
- type: ndcg_at_10
value: 36.588
- type: ndcg_at_100
value: 41.152
- type: ndcg_at_1000
value: 43.769999999999996
- type: ndcg_at_3
value: 32.632
- type: ndcg_at_5
value: 34.249
- type: precision_at_1
value: 28.638
- type: precision_at_10
value: 5.942
- type: precision_at_100
value: 0.9249999999999999
- type: precision_at_1000
value: 0.127
- type: precision_at_3
value: 14.582999999999998
- type: precision_at_5
value: 9.944
- type: recall_at_1
value: 24.309
- type: recall_at_10
value: 46.725
- type: recall_at_100
value: 67.11
- type: recall_at_1000
value: 85.91499999999999
- type: recall_at_3
value: 35.72
- type: recall_at_5
value: 39.854
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.997999999999998
- type: map_at_10
value: 30.564000000000004
- type: map_at_100
value: 32.06
- type: map_at_1000
value: 32.282
- type: map_at_3
value: 28.12
- type: map_at_5
value: 29.395
- type: mrr_at_1
value: 27.075
- type: mrr_at_10
value: 34.510999999999996
- type: mrr_at_100
value: 35.549
- type: mrr_at_1000
value: 35.616
- type: mrr_at_3
value: 32.444
- type: mrr_at_5
value: 33.589999999999996
- type: ndcg_at_1
value: 27.075
- type: ndcg_at_10
value: 35.582
- type: ndcg_at_100
value: 41.308
- type: ndcg_at_1000
value: 44.385999999999996
- type: ndcg_at_3
value: 31.467
- type: ndcg_at_5
value: 33.189
- type: precision_at_1
value: 27.075
- type: precision_at_10
value: 6.68
- type: precision_at_100
value: 1.427
- type: precision_at_1000
value: 0.231
- type: precision_at_3
value: 14.625
- type: precision_at_5
value: 10.356
- type: recall_at_1
value: 22.997999999999998
- type: recall_at_10
value: 45.196
- type: recall_at_100
value: 70.319
- type: recall_at_1000
value: 90.766
- type: recall_at_3
value: 33.487
- type: recall_at_5
value: 38.297
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.961
- type: map_at_10
value: 27.58
- type: map_at_100
value: 28.542
- type: map_at_1000
value: 28.644
- type: map_at_3
value: 25.541000000000004
- type: map_at_5
value: 26.589000000000002
- type: mrr_at_1
value: 22.551
- type: mrr_at_10
value: 29.298999999999996
- type: mrr_at_100
value: 30.17
- type: mrr_at_1000
value: 30.248
- type: mrr_at_3
value: 27.542
- type: mrr_at_5
value: 28.392
- type: ndcg_at_1
value: 22.551
- type: ndcg_at_10
value: 31.55
- type: ndcg_at_100
value: 36.295
- type: ndcg_at_1000
value: 38.964
- type: ndcg_at_3
value: 27.663
- type: ndcg_at_5
value: 29.321
- type: precision_at_1
value: 22.551
- type: precision_at_10
value: 4.88
- type: precision_at_100
value: 0.7779999999999999
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 11.83
- type: precision_at_5
value: 8.17
- type: recall_at_1
value: 20.961
- type: recall_at_10
value: 42.07
- type: recall_at_100
value: 63.982000000000006
- type: recall_at_1000
value: 83.889
- type: recall_at_3
value: 31.445
- type: recall_at_5
value: 35.410000000000004
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 11.314
- type: map_at_10
value: 18.983
- type: map_at_100
value: 20.851
- type: map_at_1000
value: 21.066
- type: map_at_3
value: 16.014
- type: map_at_5
value: 17.569000000000003
- type: mrr_at_1
value: 25.277
- type: mrr_at_10
value: 36.657000000000004
- type: mrr_at_100
value: 37.646
- type: mrr_at_1000
value: 37.686
- type: mrr_at_3
value: 33.17
- type: mrr_at_5
value: 35.232
- type: ndcg_at_1
value: 25.277
- type: ndcg_at_10
value: 27.011000000000003
- type: ndcg_at_100
value: 34.418
- type: ndcg_at_1000
value: 38.089
- type: ndcg_at_3
value: 22.026
- type: ndcg_at_5
value: 23.866
- type: precision_at_1
value: 25.277
- type: precision_at_10
value: 8.397
- type: precision_at_100
value: 1.6320000000000001
- type: precision_at_1000
value: 0.22999999999999998
- type: precision_at_3
value: 16.156000000000002
- type: precision_at_5
value: 12.612000000000002
- type: recall_at_1
value: 11.314
- type: recall_at_10
value: 32.474
- type: recall_at_100
value: 57.926
- type: recall_at_1000
value: 78.387
- type: recall_at_3
value: 20.415
- type: recall_at_5
value: 25.407999999999998
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.835999999999999
- type: map_at_10
value: 19.73
- type: map_at_100
value: 28.011000000000003
- type: map_at_1000
value: 29.519000000000002
- type: map_at_3
value: 14.249
- type: map_at_5
value: 16.472
- type: mrr_at_1
value: 67
- type: mrr_at_10
value: 74.632
- type: mrr_at_100
value: 74.97200000000001
- type: mrr_at_1000
value: 74.97500000000001
- type: mrr_at_3
value: 72.958
- type: mrr_at_5
value: 73.908
- type: ndcg_at_1
value: 55.875
- type: ndcg_at_10
value: 42.071999999999996
- type: ndcg_at_100
value: 46.091
- type: ndcg_at_1000
value: 52.737
- type: ndcg_at_3
value: 47.079
- type: ndcg_at_5
value: 43.788
- type: precision_at_1
value: 67
- type: precision_at_10
value: 33.45
- type: precision_at_100
value: 10.633
- type: precision_at_1000
value: 2.067
- type: precision_at_3
value: 49.583
- type: precision_at_5
value: 41.25
- type: recall_at_1
value: 8.835999999999999
- type: recall_at_10
value: 24.872
- type: recall_at_100
value: 51.427
- type: recall_at_1000
value: 72.17099999999999
- type: recall_at_3
value: 15.631999999999998
- type: recall_at_5
value: 18.956
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 48.80500000000001
- type: f1
value: 43.91955883597831
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 61.480999999999995
- type: map_at_10
value: 72.162
- type: map_at_100
value: 72.487
- type: map_at_1000
value: 72.504
- type: map_at_3
value: 70.354
- type: map_at_5
value: 71.509
- type: mrr_at_1
value: 66.262
- type: mrr_at_10
value: 76.605
- type: mrr_at_100
value: 76.833
- type: mrr_at_1000
value: 76.839
- type: mrr_at_3
value: 74.977
- type: mrr_at_5
value: 76.06
- type: ndcg_at_1
value: 66.262
- type: ndcg_at_10
value: 77.323
- type: ndcg_at_100
value: 78.685
- type: ndcg_at_1000
value: 79.032
- type: ndcg_at_3
value: 74.015
- type: ndcg_at_5
value: 75.916
- type: precision_at_1
value: 66.262
- type: precision_at_10
value: 9.757
- type: precision_at_100
value: 1.059
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 29.032999999999998
- type: precision_at_5
value: 18.5
- type: recall_at_1
value: 61.480999999999995
- type: recall_at_10
value: 88.878
- type: recall_at_100
value: 94.719
- type: recall_at_1000
value: 97.066
- type: recall_at_3
value: 79.95100000000001
- type: recall_at_5
value: 84.691
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.925
- type: map_at_10
value: 31.621
- type: map_at_100
value: 33.282000000000004
- type: map_at_1000
value: 33.455
- type: map_at_3
value: 27.504
- type: map_at_5
value: 29.921999999999997
- type: mrr_at_1
value: 39.660000000000004
- type: mrr_at_10
value: 47.366
- type: mrr_at_100
value: 48.179
- type: mrr_at_1000
value: 48.219
- type: mrr_at_3
value: 45.062000000000005
- type: mrr_at_5
value: 46.404
- type: ndcg_at_1
value: 39.660000000000004
- type: ndcg_at_10
value: 39.019
- type: ndcg_at_100
value: 45.286
- type: ndcg_at_1000
value: 48.370000000000005
- type: ndcg_at_3
value: 35.421
- type: ndcg_at_5
value: 36.767
- type: precision_at_1
value: 39.660000000000004
- type: precision_at_10
value: 10.494
- type: precision_at_100
value: 1.7069999999999999
- type: precision_at_1000
value: 0.22599999999999998
- type: precision_at_3
value: 23.200000000000003
- type: precision_at_5
value: 17.253
- type: recall_at_1
value: 19.925
- type: recall_at_10
value: 45.48
- type: recall_at_100
value: 68.585
- type: recall_at_1000
value: 87.128
- type: recall_at_3
value: 31.913000000000004
- type: recall_at_5
value: 38.107
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.961
- type: map_at_10
value: 55.010000000000005
- type: map_at_100
value: 55.896
- type: map_at_1000
value: 55.962
- type: map_at_3
value: 52.03
- type: map_at_5
value: 53.866
- type: mrr_at_1
value: 75.922
- type: mrr_at_10
value: 81.655
- type: mrr_at_100
value: 81.879
- type: mrr_at_1000
value: 81.889
- type: mrr_at_3
value: 80.657
- type: mrr_at_5
value: 81.291
- type: ndcg_at_1
value: 75.922
- type: ndcg_at_10
value: 64.119
- type: ndcg_at_100
value: 67.25
- type: ndcg_at_1000
value: 68.55499999999999
- type: ndcg_at_3
value: 59.792
- type: ndcg_at_5
value: 62.165000000000006
- type: precision_at_1
value: 75.922
- type: precision_at_10
value: 13.155
- type: precision_at_100
value: 1.5599999999999998
- type: precision_at_1000
value: 0.173
- type: precision_at_3
value: 37.461
- type: precision_at_5
value: 24.351
- type: recall_at_1
value: 37.961
- type: recall_at_10
value: 65.77300000000001
- type: recall_at_100
value: 78.015
- type: recall_at_1000
value: 86.685
- type: recall_at_3
value: 56.192
- type: recall_at_5
value: 60.878
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 83.7804
- type: ap
value: 78.89508987851809
- type: f1
value: 83.72392373438922
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.807000000000002
- type: map_at_10
value: 36.411
- type: map_at_100
value: 37.574000000000005
- type: map_at_1000
value: 37.618
- type: map_at_3
value: 32.653
- type: map_at_5
value: 34.902
- type: mrr_at_1
value: 24.499000000000002
- type: mrr_at_10
value: 37.045
- type: mrr_at_100
value: 38.135999999999996
- type: mrr_at_1000
value: 38.175
- type: mrr_at_3
value: 33.326
- type: mrr_at_5
value: 35.561
- type: ndcg_at_1
value: 24.512999999999998
- type: ndcg_at_10
value: 43.328
- type: ndcg_at_100
value: 48.779
- type: ndcg_at_1000
value: 49.897999999999996
- type: ndcg_at_3
value: 35.713
- type: ndcg_at_5
value: 39.729
- type: precision_at_1
value: 24.512999999999998
- type: precision_at_10
value: 6.7379999999999995
- type: precision_at_100
value: 0.9450000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 15.196000000000002
- type: precision_at_5
value: 11.158
- type: recall_at_1
value: 23.807000000000002
- type: recall_at_10
value: 64.488
- type: recall_at_100
value: 89.386
- type: recall_at_1000
value: 97.968
- type: recall_at_3
value: 43.891000000000005
- type: recall_at_5
value: 53.535
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.47013223894209
- type: f1
value: 93.15020887152107
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 75.27131782945737
- type: f1
value: 58.45703758149779
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 72.76395427034298
- type: f1
value: 70.6084399610629
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 76.69804976462676
- type: f1
value: 76.61599181962723
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 32.7253797676744
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 30.547731924629424
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 31.286918745183772
- type: mrr
value: 32.47449315230336
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.894
- type: map_at_10
value: 13.405000000000001
- type: map_at_100
value: 16.586000000000002
- type: map_at_1000
value: 17.919
- type: map_at_3
value: 10.066
- type: map_at_5
value: 11.679
- type: mrr_at_1
value: 45.201
- type: mrr_at_10
value: 54.018
- type: mrr_at_100
value: 54.581999999999994
- type: mrr_at_1000
value: 54.623
- type: mrr_at_3
value: 51.6
- type: mrr_at_5
value: 53.473000000000006
- type: ndcg_at_1
value: 43.189
- type: ndcg_at_10
value: 35.306
- type: ndcg_at_100
value: 31.505
- type: ndcg_at_1000
value: 39.991
- type: ndcg_at_3
value: 41.108
- type: ndcg_at_5
value: 39.039
- type: precision_at_1
value: 44.582
- type: precision_at_10
value: 26.161
- type: precision_at_100
value: 7.867
- type: precision_at_1000
value: 2.043
- type: precision_at_3
value: 39.112
- type: precision_at_5
value: 34.18
- type: recall_at_1
value: 5.894
- type: recall_at_10
value: 16.88
- type: recall_at_100
value: 30.671
- type: recall_at_1000
value: 61.42999999999999
- type: recall_at_3
value: 11.022
- type: recall_at_5
value: 13.697999999999999
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 38.440999999999995
- type: map_at_10
value: 54.187
- type: map_at_100
value: 55.022000000000006
- type: map_at_1000
value: 55.044000000000004
- type: map_at_3
value: 50.174
- type: map_at_5
value: 52.61
- type: mrr_at_1
value: 42.903000000000006
- type: mrr_at_10
value: 56.699
- type: mrr_at_100
value: 57.31
- type: mrr_at_1000
value: 57.325
- type: mrr_at_3
value: 53.63099999999999
- type: mrr_at_5
value: 55.596000000000004
- type: ndcg_at_1
value: 42.903000000000006
- type: ndcg_at_10
value: 61.434
- type: ndcg_at_100
value: 64.852
- type: ndcg_at_1000
value: 65.36
- type: ndcg_at_3
value: 54.193000000000005
- type: ndcg_at_5
value: 58.15
- type: precision_at_1
value: 42.903000000000006
- type: precision_at_10
value: 9.623
- type: precision_at_100
value: 1.1560000000000001
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 24.034
- type: precision_at_5
value: 16.779
- type: recall_at_1
value: 38.440999999999995
- type: recall_at_10
value: 80.72399999999999
- type: recall_at_100
value: 95.329
- type: recall_at_1000
value: 99.059
- type: recall_at_3
value: 62.343
- type: recall_at_5
value: 71.304
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 70.85000000000001
- type: map_at_10
value: 84.54
- type: map_at_100
value: 85.148
- type: map_at_1000
value: 85.168
- type: map_at_3
value: 81.631
- type: map_at_5
value: 83.45700000000001
- type: mrr_at_1
value: 81.58
- type: mrr_at_10
value: 87.732
- type: mrr_at_100
value: 87.825
- type: mrr_at_1000
value: 87.82600000000001
- type: mrr_at_3
value: 86.783
- type: mrr_at_5
value: 87.437
- type: ndcg_at_1
value: 81.56
- type: ndcg_at_10
value: 88.32900000000001
- type: ndcg_at_100
value: 89.513
- type: ndcg_at_1000
value: 89.63799999999999
- type: ndcg_at_3
value: 85.51100000000001
- type: ndcg_at_5
value: 87.062
- type: precision_at_1
value: 81.56
- type: precision_at_10
value: 13.349
- type: precision_at_100
value: 1.518
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 37.293
- type: precision_at_5
value: 24.502
- type: recall_at_1
value: 70.85000000000001
- type: recall_at_10
value: 95.351
- type: recall_at_100
value: 99.405
- type: recall_at_1000
value: 99.958
- type: recall_at_3
value: 87.184
- type: recall_at_5
value: 91.625
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 56.81818576893834
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 61.57033658868022
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.468
- type: map_at_10
value: 11.109
- type: map_at_100
value: 12.921
- type: map_at_1000
value: 13.187999999999999
- type: map_at_3
value: 8.094999999999999
- type: map_at_5
value: 9.664
- type: mrr_at_1
value: 22.1
- type: mrr_at_10
value: 32.482
- type: mrr_at_100
value: 33.558
- type: mrr_at_1000
value: 33.623999999999995
- type: mrr_at_3
value: 29.25
- type: mrr_at_5
value: 31.080000000000002
- type: ndcg_at_1
value: 22.1
- type: ndcg_at_10
value: 18.695999999999998
- type: ndcg_at_100
value: 25.749
- type: ndcg_at_1000
value: 30.711
- type: ndcg_at_3
value: 17.974
- type: ndcg_at_5
value: 15.684000000000001
- type: precision_at_1
value: 22.1
- type: precision_at_10
value: 9.56
- type: precision_at_100
value: 1.966
- type: precision_at_1000
value: 0.316
- type: precision_at_3
value: 16.667
- type: precision_at_5
value: 13.68
- type: recall_at_1
value: 4.468
- type: recall_at_10
value: 19.373
- type: recall_at_100
value: 39.853
- type: recall_at_1000
value: 64.118
- type: recall_at_3
value: 10.133000000000001
- type: recall_at_5
value: 13.877999999999998
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 80.11452150923512
- type: cos_sim_spearman
value: 77.3007421887329
- type: euclidean_pearson
value: 78.2493681078981
- type: euclidean_spearman
value: 77.3007432741821
- type: manhattan_pearson
value: 78.19716818242554
- type: manhattan_spearman
value: 77.26439033199102
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 82.70293570563516
- type: cos_sim_spearman
value: 77.97040896962338
- type: euclidean_pearson
value: 77.98827330337348
- type: euclidean_spearman
value: 77.9704358930525
- type: manhattan_pearson
value: 78.06991702207395
- type: manhattan_spearman
value: 78.03857843100195
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 77.81236960157503
- type: cos_sim_spearman
value: 79.38801416063187
- type: euclidean_pearson
value: 79.35003045476847
- type: euclidean_spearman
value: 79.38797289536578
- type: manhattan_pearson
value: 79.33155563344724
- type: manhattan_spearman
value: 79.3858955436803
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 77.35604880089507
- type: cos_sim_spearman
value: 78.17327332594571
- type: euclidean_pearson
value: 77.30302038209295
- type: euclidean_spearman
value: 78.17327332594571
- type: manhattan_pearson
value: 77.31323781935417
- type: manhattan_spearman
value: 78.20141256686921
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 84.29348597583
- type: cos_sim_spearman
value: 85.50877410088334
- type: euclidean_pearson
value: 85.22367284169081
- type: euclidean_spearman
value: 85.50877410088334
- type: manhattan_pearson
value: 85.17979979737612
- type: manhattan_spearman
value: 85.46459282596254
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 83.16190794761513
- type: cos_sim_spearman
value: 84.94610605287254
- type: euclidean_pearson
value: 83.95587174131369
- type: euclidean_spearman
value: 84.94610605287254
- type: manhattan_pearson
value: 83.99025745366798
- type: manhattan_spearman
value: 84.98123107148953
- 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: 85.3047190687711
- type: cos_sim_spearman
value: 85.86642469958113
- type: euclidean_pearson
value: 86.74377658528041
- type: euclidean_spearman
value: 85.86642469958113
- type: manhattan_pearson
value: 86.56967885987439
- type: manhattan_spearman
value: 85.63613272583275
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 64.8298932792099
- type: cos_sim_spearman
value: 64.27626667878636
- type: euclidean_pearson
value: 66.01603861201576
- type: euclidean_spearman
value: 64.27626667878636
- type: manhattan_pearson
value: 66.31232809448106
- type: manhattan_spearman
value: 64.46190921631559
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 82.73696291316243
- type: cos_sim_spearman
value: 83.41508337893958
- type: euclidean_pearson
value: 82.8827053024064
- type: euclidean_spearman
value: 83.41508337893958
- type: manhattan_pearson
value: 82.85613329045803
- type: manhattan_spearman
value: 83.40522047443645
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 75.51490079179645
- type: mrr
value: 92.6809655486126
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 58.594
- type: map_at_10
value: 67.208
- type: map_at_100
value: 67.702
- type: map_at_1000
value: 67.73
- type: map_at_3
value: 64.815
- type: map_at_5
value: 65.946
- type: mrr_at_1
value: 61.667
- type: mrr_at_10
value: 68.52000000000001
- type: mrr_at_100
value: 68.888
- type: mrr_at_1000
value: 68.911
- type: mrr_at_3
value: 66.833
- type: mrr_at_5
value: 67.617
- type: ndcg_at_1
value: 61.667
- type: ndcg_at_10
value: 71.511
- type: ndcg_at_100
value: 73.765
- type: ndcg_at_1000
value: 74.40299999999999
- type: ndcg_at_3
value: 67.411
- type: ndcg_at_5
value: 68.88
- type: precision_at_1
value: 61.667
- type: precision_at_10
value: 9.433
- type: precision_at_100
value: 1.0670000000000002
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 26.222
- type: precision_at_5
value: 16.866999999999997
- type: recall_at_1
value: 58.594
- type: recall_at_10
value: 83.439
- type: recall_at_100
value: 94.1
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 71.922
- type: recall_at_5
value: 75.678
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.7990099009901
- type: cos_sim_ap
value: 94.8316184070519
- type: cos_sim_f1
value: 89.75265017667844
- type: cos_sim_precision
value: 90.62181447502549
- type: cos_sim_recall
value: 88.9
- type: dot_accuracy
value: 99.7990099009901
- type: dot_ap
value: 94.831611518794
- type: dot_f1
value: 89.75265017667844
- type: dot_precision
value: 90.62181447502549
- type: dot_recall
value: 88.9
- type: euclidean_accuracy
value: 99.7990099009901
- type: euclidean_ap
value: 94.83161335144017
- type: euclidean_f1
value: 89.75265017667844
- type: euclidean_precision
value: 90.62181447502549
- type: euclidean_recall
value: 88.9
- type: manhattan_accuracy
value: 99.8
- type: manhattan_ap
value: 94.84210829841739
- type: manhattan_f1
value: 89.60905349794238
- type: manhattan_precision
value: 92.26694915254238
- type: manhattan_recall
value: 87.1
- type: max_accuracy
value: 99.8
- type: max_ap
value: 94.84210829841739
- type: max_f1
value: 89.75265017667844
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 63.18343792633894
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.50944549814364
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 48.89100016028111
- type: mrr
value: 49.607630931160344
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.628145384101522
- type: cos_sim_spearman
value: 31.275306930726675
- type: dot_pearson
value: 30.62814883550051
- type: dot_spearman
value: 31.275306930726675
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.26
- type: map_at_10
value: 2.163
- type: map_at_100
value: 12.29
- type: map_at_1000
value: 29.221999999999998
- type: map_at_3
value: 0.729
- type: map_at_5
value: 1.161
- type: mrr_at_1
value: 96
- type: mrr_at_10
value: 98
- type: mrr_at_100
value: 98
- type: mrr_at_1000
value: 98
- type: mrr_at_3
value: 98
- type: mrr_at_5
value: 98
- type: ndcg_at_1
value: 89
- type: ndcg_at_10
value: 82.312
- type: ndcg_at_100
value: 61.971
- type: ndcg_at_1000
value: 54.065
- type: ndcg_at_3
value: 87.87700000000001
- type: ndcg_at_5
value: 85.475
- type: precision_at_1
value: 96
- type: precision_at_10
value: 87.4
- type: precision_at_100
value: 64.02
- type: precision_at_1000
value: 24.093999999999998
- type: precision_at_3
value: 94
- type: precision_at_5
value: 90.8
- type: recall_at_1
value: 0.26
- type: recall_at_10
value: 2.302
- type: recall_at_100
value: 15.148
- type: recall_at_1000
value: 50.55
- type: recall_at_3
value: 0.744
- type: recall_at_5
value: 1.198
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.217
- type: map_at_10
value: 11.378
- type: map_at_100
value: 18.022
- type: map_at_1000
value: 19.544
- type: map_at_3
value: 6.079
- type: map_at_5
value: 8.559
- type: mrr_at_1
value: 28.571
- type: mrr_at_10
value: 48.423
- type: mrr_at_100
value: 49.028
- type: mrr_at_1000
value: 49.028
- type: mrr_at_3
value: 44.897999999999996
- type: mrr_at_5
value: 46.531
- type: ndcg_at_1
value: 25.509999999999998
- type: ndcg_at_10
value: 27.860000000000003
- type: ndcg_at_100
value: 39.34
- type: ndcg_at_1000
value: 50.21
- type: ndcg_at_3
value: 30.968
- type: ndcg_at_5
value: 29.541
- type: precision_at_1
value: 28.571
- type: precision_at_10
value: 25.918000000000003
- type: precision_at_100
value: 8.184
- type: precision_at_1000
value: 1.545
- type: precision_at_3
value: 35.374
- type: precision_at_5
value: 31.837
- type: recall_at_1
value: 2.217
- type: recall_at_10
value: 18.511
- type: recall_at_100
value: 50.178
- type: recall_at_1000
value: 83.07600000000001
- type: recall_at_3
value: 7.811999999999999
- type: recall_at_5
value: 11.684
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 71.386
- type: ap
value: 14.58573366644018
- type: f1
value: 55.0170316975105
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 60.868704018109796
- type: f1
value: 61.175908652496624
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 48.72082824812323
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 85.43839780652083
- type: cos_sim_ap
value: 72.55258980537292
- type: cos_sim_f1
value: 66.4145419055752
- type: cos_sim_precision
value: 61.765373269798054
- type: cos_sim_recall
value: 71.82058047493403
- type: dot_accuracy
value: 85.43839780652083
- type: dot_ap
value: 72.55256370197756
- type: dot_f1
value: 66.4145419055752
- type: dot_precision
value: 61.765373269798054
- type: dot_recall
value: 71.82058047493403
- type: euclidean_accuracy
value: 85.43839780652083
- type: euclidean_ap
value: 72.55259011957311
- type: euclidean_f1
value: 66.4145419055752
- type: euclidean_precision
value: 61.765373269798054
- type: euclidean_recall
value: 71.82058047493403
- type: manhattan_accuracy
value: 85.40263455921799
- type: manhattan_ap
value: 72.47856062032
- type: manhattan_f1
value: 66.39413249969942
- type: manhattan_precision
value: 60.989617848464775
- type: manhattan_recall
value: 72.84960422163589
- type: max_accuracy
value: 85.43839780652083
- type: max_ap
value: 72.55259011957311
- type: max_f1
value: 66.4145419055752
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.24981565568363
- type: cos_sim_ap
value: 86.38437585690401
- type: cos_sim_f1
value: 78.79039565086076
- type: cos_sim_precision
value: 77.29629629629629
- type: cos_sim_recall
value: 80.34339390206344
- type: dot_accuracy
value: 89.24981565568363
- type: dot_ap
value: 86.38437587564587
- type: dot_f1
value: 78.79039565086076
- type: dot_precision
value: 77.29629629629629
- type: dot_recall
value: 80.34339390206344
- type: euclidean_accuracy
value: 89.24981565568363
- type: euclidean_ap
value: 86.38437691024106
- type: euclidean_f1
value: 78.79039565086076
- type: euclidean_precision
value: 77.29629629629629
- type: euclidean_recall
value: 80.34339390206344
- type: manhattan_accuracy
value: 89.25563705514806
- type: manhattan_ap
value: 86.35729146774388
- type: manhattan_f1
value: 78.7238059278837
- type: manhattan_precision
value: 77.23938653034007
- type: manhattan_recall
value: 80.26639975361873
- type: max_accuracy
value: 89.25563705514806
- type: max_ap
value: 86.38437691024106
- type: max_f1
value: 78.79039565086076