metadata
tags:
- mteb
- feature-extraction
- sentence-similarity
model-index:
- name: v2
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 76.56716417910448
- type: ap
value: 39.864746145463656
- type: f1
value: 70.60275403114987
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 93.46427500000001
- type: ap
value: 90.36283359936121
- type: f1
value: 93.45329322673612
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 48.77199999999999
- type: f1
value: 48.16695258838576
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.184999999999995
- type: map_at_10
value: 56.114
- type: map_at_100
value: 56.676
- type: map_at_1000
value: 56.68
- type: map_at_3
value: 51.968
- type: map_at_5
value: 54.642
- type: mrr_at_1
value: 40.896
- type: mrr_at_10
value: 56.388000000000005
- type: mrr_at_100
value: 56.95099999999999
- type: mrr_at_1000
value: 56.95400000000001
- type: mrr_at_3
value: 52.251999999999995
- type: mrr_at_5
value: 54.879999999999995
- type: ndcg_at_1
value: 40.184999999999995
- type: ndcg_at_10
value: 64.253
- type: ndcg_at_100
value: 66.47
- type: ndcg_at_1000
value: 66.549
- type: ndcg_at_3
value: 55.945
- type: ndcg_at_5
value: 60.742
- type: precision_at_1
value: 40.184999999999995
- type: precision_at_10
value: 8.982999999999999
- type: precision_at_100
value: 0.991
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 22.499
- type: precision_at_5
value: 15.817999999999998
- type: recall_at_1
value: 40.184999999999995
- type: recall_at_10
value: 89.82900000000001
- type: recall_at_100
value: 99.075
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 67.496
- type: recall_at_5
value: 79.09
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 49.64684811204023
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 43.6640710523389
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 63.71316367624821
- type: mrr
value: 77.02534845886647
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 88.96786300506704
- type: cos_sim_spearman
value: 88.08212749295554
- type: euclidean_pearson
value: 87.1561534920524
- type: euclidean_spearman
value: 88.016463346151
- type: manhattan_pearson
value: 87.19359910450564
- type: manhattan_spearman
value: 88.10803169765825
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 87.46103896103897
- type: f1
value: 87.4315144014101
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 41.03554871732576
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 37.974813344124264
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 34.174
- type: map_at_10
value: 45.728
- type: map_at_100
value: 47.266999999999996
- type: map_at_1000
value: 47.39
- type: map_at_3
value: 41.667
- type: map_at_5
value: 44.028
- type: mrr_at_1
value: 41.202
- type: mrr_at_10
value: 51.49
- type: mrr_at_100
value: 52.159
- type: mrr_at_1000
value: 52.197
- type: mrr_at_3
value: 48.379
- type: mrr_at_5
value: 50.331
- type: ndcg_at_1
value: 41.202
- type: ndcg_at_10
value: 52.38699999999999
- type: ndcg_at_100
value: 57.611999999999995
- type: ndcg_at_1000
value: 59.318000000000005
- type: ndcg_at_3
value: 46.516000000000005
- type: ndcg_at_5
value: 49.519000000000005
- type: precision_at_1
value: 41.202
- type: precision_at_10
value: 9.971
- type: precision_at_100
value: 1.5879999999999999
- type: precision_at_1000
value: 0.20500000000000002
- type: precision_at_3
value: 22.031
- type: precision_at_5
value: 16.309
- type: recall_at_1
value: 34.174
- type: recall_at_10
value: 65.32900000000001
- type: recall_at_100
value: 86.64
- type: recall_at_1000
value: 97.069
- type: recall_at_3
value: 48.607
- type: recall_at_5
value: 56.615
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 34.73
- type: map_at_10
value: 45.617999999999995
- type: map_at_100
value: 46.888000000000005
- type: map_at_1000
value: 47.016999999999996
- type: map_at_3
value: 42.425000000000004
- type: map_at_5
value: 44.214999999999996
- type: mrr_at_1
value: 43.631
- type: mrr_at_10
value: 52.014
- type: mrr_at_100
value: 52.6
- type: mrr_at_1000
value: 52.637
- type: mrr_at_3
value: 50.021
- type: mrr_at_5
value: 51.23799999999999
- type: ndcg_at_1
value: 43.631
- type: ndcg_at_10
value: 51.458000000000006
- type: ndcg_at_100
value: 55.61000000000001
- type: ndcg_at_1000
value: 57.462
- type: ndcg_at_3
value: 47.461
- type: ndcg_at_5
value: 49.312
- type: precision_at_1
value: 43.631
- type: precision_at_10
value: 9.661999999999999
- type: precision_at_100
value: 1.5270000000000001
- type: precision_at_1000
value: 0.198
- type: precision_at_3
value: 22.823999999999998
- type: precision_at_5
value: 16.075999999999997
- type: recall_at_1
value: 34.73
- type: recall_at_10
value: 61.041999999999994
- type: recall_at_100
value: 78.658
- type: recall_at_1000
value: 90.215
- type: recall_at_3
value: 48.952
- type: recall_at_5
value: 54.422000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 42.047000000000004
- type: map_at_10
value: 55.669999999999995
- type: map_at_100
value: 56.676
- type: map_at_1000
value: 56.728
- type: map_at_3
value: 52.275000000000006
- type: map_at_5
value: 54.254000000000005
- type: mrr_at_1
value: 48.15
- type: mrr_at_10
value: 59.036
- type: mrr_at_100
value: 59.650999999999996
- type: mrr_at_1000
value: 59.675
- type: mrr_at_3
value: 56.760999999999996
- type: mrr_at_5
value: 58.087
- type: ndcg_at_1
value: 48.15
- type: ndcg_at_10
value: 61.709
- type: ndcg_at_100
value: 65.446
- type: ndcg_at_1000
value: 66.388
- type: ndcg_at_3
value: 56.333
- type: ndcg_at_5
value: 59.028000000000006
- type: precision_at_1
value: 48.15
- type: precision_at_10
value: 9.893
- type: precision_at_100
value: 1.265
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 25.266
- type: precision_at_5
value: 17.204
- type: recall_at_1
value: 42.047000000000004
- type: recall_at_10
value: 76.004
- type: recall_at_100
value: 91.727
- type: recall_at_1000
value: 98.213
- type: recall_at_3
value: 61.82
- type: recall_at_5
value: 68.42200000000001
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.985
- type: map_at_10
value: 38.763999999999996
- type: map_at_100
value: 39.835
- type: map_at_1000
value: 39.900000000000006
- type: map_at_3
value: 35.826
- type: map_at_5
value: 37.403
- type: mrr_at_1
value: 32.202999999999996
- type: mrr_at_10
value: 40.94
- type: mrr_at_100
value: 41.861
- type: mrr_at_1000
value: 41.909
- type: mrr_at_3
value: 38.267
- type: mrr_at_5
value: 39.748
- type: ndcg_at_1
value: 32.202999999999996
- type: ndcg_at_10
value: 43.909
- type: ndcg_at_100
value: 49.028
- type: ndcg_at_1000
value: 50.714999999999996
- type: ndcg_at_3
value: 38.239000000000004
- type: ndcg_at_5
value: 40.854
- type: precision_at_1
value: 32.202999999999996
- type: precision_at_10
value: 6.621
- type: precision_at_100
value: 0.964
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 15.781999999999998
- type: precision_at_5
value: 10.96
- type: recall_at_1
value: 29.985
- type: recall_at_10
value: 57.727
- type: recall_at_100
value: 80.833
- type: recall_at_1000
value: 93.625
- type: recall_at_3
value: 42.396
- type: recall_at_5
value: 48.624
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.249
- type: map_at_10
value: 28.565
- type: map_at_100
value: 29.753
- type: map_at_1000
value: 29.881
- type: map_at_3
value: 25.778000000000002
- type: map_at_5
value: 27.21
- type: mrr_at_1
value: 23.632
- type: mrr_at_10
value: 33.51
- type: mrr_at_100
value: 34.372
- type: mrr_at_1000
value: 34.443
- type: mrr_at_3
value: 30.784
- type: mrr_at_5
value: 32.301
- type: ndcg_at_1
value: 23.632
- type: ndcg_at_10
value: 34.42
- type: ndcg_at_100
value: 39.823
- type: ndcg_at_1000
value: 42.558
- type: ndcg_at_3
value: 29.237000000000002
- type: ndcg_at_5
value: 31.465
- type: precision_at_1
value: 23.632
- type: precision_at_10
value: 6.331
- type: precision_at_100
value: 1.042
- type: precision_at_1000
value: 0.14100000000000001
- type: precision_at_3
value: 14.179
- type: precision_at_5
value: 10.299
- type: recall_at_1
value: 19.249
- type: recall_at_10
value: 47.539
- type: recall_at_100
value: 70.612
- type: recall_at_1000
value: 89.633
- type: recall_at_3
value: 33.082
- type: recall_at_5
value: 38.622
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.599
- type: map_at_10
value: 42.948
- type: map_at_100
value: 44.244
- type: map_at_1000
value: 44.352000000000004
- type: map_at_3
value: 39.352
- type: map_at_5
value: 41.397
- type: mrr_at_1
value: 38.21
- type: mrr_at_10
value: 48.347
- type: mrr_at_100
value: 49.132999999999996
- type: mrr_at_1000
value: 49.171
- type: mrr_at_3
value: 45.653
- type: mrr_at_5
value: 47.323
- type: ndcg_at_1
value: 38.21
- type: ndcg_at_10
value: 49.225
- type: ndcg_at_100
value: 54.422000000000004
- type: ndcg_at_1000
value: 56.27799999999999
- type: ndcg_at_3
value: 43.482
- type: ndcg_at_5
value: 46.321
- type: precision_at_1
value: 38.21
- type: precision_at_10
value: 8.921999999999999
- type: precision_at_100
value: 1.333
- type: precision_at_1000
value: 0.169
- type: precision_at_3
value: 20.372
- type: precision_at_5
value: 14.629
- type: recall_at_1
value: 31.599
- type: recall_at_10
value: 62.364
- type: recall_at_100
value: 83.91199999999999
- type: recall_at_1000
value: 95.743
- type: recall_at_3
value: 46.671
- type: recall_at_5
value: 53.772
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.641
- type: map_at_10
value: 37.604
- type: map_at_100
value: 38.897
- type: map_at_1000
value: 39.001000000000005
- type: map_at_3
value: 34.04
- type: map_at_5
value: 35.684
- type: mrr_at_1
value: 32.991
- type: mrr_at_10
value: 43.029
- type: mrr_at_100
value: 43.782
- type: mrr_at_1000
value: 43.830999999999996
- type: mrr_at_3
value: 40.164
- type: mrr_at_5
value: 41.619
- type: ndcg_at_1
value: 32.991
- type: ndcg_at_10
value: 44.217
- type: ndcg_at_100
value: 49.497
- type: ndcg_at_1000
value: 51.598
- type: ndcg_at_3
value: 38.208999999999996
- type: ndcg_at_5
value: 40.444
- type: precision_at_1
value: 32.991
- type: precision_at_10
value: 8.436
- type: precision_at_100
value: 1.279
- type: precision_at_1000
value: 0.163
- type: precision_at_3
value: 18.379
- type: precision_at_5
value: 13.196
- type: recall_at_1
value: 26.641
- type: recall_at_10
value: 58.50300000000001
- type: recall_at_100
value: 81.228
- type: recall_at_1000
value: 95.345
- type: recall_at_3
value: 41.6
- type: recall_at_5
value: 47.425
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.678083333333333
- type: map_at_10
value: 38.63366666666666
- type: map_at_100
value: 39.84708333333333
- type: map_at_1000
value: 39.959583333333335
- type: map_at_3
value: 35.49
- type: map_at_5
value: 37.23125
- type: mrr_at_1
value: 33.813916666666664
- type: mrr_at_10
value: 42.955500000000015
- type: mrr_at_100
value: 43.75541666666667
- type: mrr_at_1000
value: 43.80616666666666
- type: mrr_at_3
value: 40.40191666666667
- type: mrr_at_5
value: 41.88358333333333
- type: ndcg_at_1
value: 33.813916666666664
- type: ndcg_at_10
value: 44.361666666666665
- type: ndcg_at_100
value: 49.37991666666667
- type: ndcg_at_1000
value: 51.432583333333326
- type: ndcg_at_3
value: 39.12949999999999
- type: ndcg_at_5
value: 41.60183333333333
- type: precision_at_1
value: 33.813916666666664
- type: precision_at_10
value: 7.759250000000002
- type: precision_at_100
value: 1.2108333333333332
- type: precision_at_1000
value: 0.158
- type: precision_at_3
value: 17.90716666666667
- type: precision_at_5
value: 12.765333333333334
- type: recall_at_1
value: 28.678083333333333
- type: recall_at_10
value: 56.92716666666667
- type: recall_at_100
value: 78.74991666666668
- type: recall_at_1000
value: 92.73875000000001
- type: recall_at_3
value: 42.459916666666665
- type: recall_at_5
value: 48.76258333333333
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.282
- type: map_at_10
value: 34.458
- type: map_at_100
value: 35.44
- type: map_at_1000
value: 35.536
- type: map_at_3
value: 31.912000000000003
- type: map_at_5
value: 33.495000000000005
- type: mrr_at_1
value: 30.675
- type: mrr_at_10
value: 37.563
- type: mrr_at_100
value: 38.374
- type: mrr_at_1000
value: 38.444
- type: mrr_at_3
value: 35.276
- type: mrr_at_5
value: 36.718
- type: ndcg_at_1
value: 30.675
- type: ndcg_at_10
value: 38.838
- type: ndcg_at_100
value: 43.527
- type: ndcg_at_1000
value: 45.891
- type: ndcg_at_3
value: 34.314
- type: ndcg_at_5
value: 36.789
- type: precision_at_1
value: 30.675
- type: precision_at_10
value: 6.012
- type: precision_at_100
value: 0.903
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 14.571000000000002
- type: precision_at_5
value: 10.306999999999999
- type: recall_at_1
value: 27.282
- type: recall_at_10
value: 49.198
- type: recall_at_100
value: 70.489
- type: recall_at_1000
value: 87.902
- type: recall_at_3
value: 36.966
- type: recall_at_5
value: 43.079
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.839000000000002
- type: map_at_10
value: 27.68
- type: map_at_100
value: 28.851
- type: map_at_1000
value: 28.977999999999998
- type: map_at_3
value: 25.062
- type: map_at_5
value: 26.389000000000003
- type: mrr_at_1
value: 23.813000000000002
- type: mrr_at_10
value: 31.628
- type: mrr_at_100
value: 32.58
- type: mrr_at_1000
value: 32.655
- type: mrr_at_3
value: 29.29
- type: mrr_at_5
value: 30.551000000000002
- type: ndcg_at_1
value: 23.813000000000002
- type: ndcg_at_10
value: 32.751000000000005
- type: ndcg_at_100
value: 38.218
- type: ndcg_at_1000
value: 40.979
- type: ndcg_at_3
value: 28.043000000000003
- type: ndcg_at_5
value: 30.043
- type: precision_at_1
value: 23.813000000000002
- type: precision_at_10
value: 5.936
- type: precision_at_100
value: 1.016
- type: precision_at_1000
value: 0.14400000000000002
- type: precision_at_3
value: 13.145000000000001
- type: precision_at_5
value: 9.443
- type: recall_at_1
value: 19.839000000000002
- type: recall_at_10
value: 44.072
- type: recall_at_100
value: 68.406
- type: recall_at_1000
value: 87.749
- type: recall_at_3
value: 30.906
- type: recall_at_5
value: 36.081
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.195999999999998
- type: map_at_10
value: 38.345
- type: map_at_100
value: 39.561
- type: map_at_1000
value: 39.65
- type: map_at_3
value: 35.382999999999996
- type: map_at_5
value: 37.023
- type: mrr_at_1
value: 33.022
- type: mrr_at_10
value: 42.504
- type: mrr_at_100
value: 43.376
- type: mrr_at_1000
value: 43.427
- type: mrr_at_3
value: 40.050000000000004
- type: mrr_at_5
value: 41.421
- type: ndcg_at_1
value: 33.022
- type: ndcg_at_10
value: 43.997
- type: ndcg_at_100
value: 49.370000000000005
- type: ndcg_at_1000
value: 51.38399999999999
- type: ndcg_at_3
value: 38.802
- type: ndcg_at_5
value: 41.209
- type: precision_at_1
value: 33.022
- type: precision_at_10
value: 7.351000000000001
- type: precision_at_100
value: 1.1440000000000001
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_3
value: 17.724
- type: precision_at_5
value: 12.443999999999999
- type: recall_at_1
value: 28.195999999999998
- type: recall_at_10
value: 57.011
- type: recall_at_100
value: 79.922
- type: recall_at_1000
value: 93.952
- type: recall_at_3
value: 42.857
- type: recall_at_5
value: 48.916
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.768
- type: map_at_10
value: 35.118
- type: map_at_100
value: 36.817
- type: map_at_1000
value: 37.037
- type: map_at_3
value: 31.997999999999998
- type: map_at_5
value: 33.697
- type: mrr_at_1
value: 31.621
- type: mrr_at_10
value: 40.228
- type: mrr_at_100
value: 41.239
- type: mrr_at_1000
value: 41.277
- type: mrr_at_3
value: 37.614999999999995
- type: mrr_at_5
value: 39.058
- type: ndcg_at_1
value: 31.621
- type: ndcg_at_10
value: 41.347
- type: ndcg_at_100
value: 47.620000000000005
- type: ndcg_at_1000
value: 49.759
- type: ndcg_at_3
value: 36.361
- type: ndcg_at_5
value: 38.635000000000005
- type: precision_at_1
value: 31.621
- type: precision_at_10
value: 8.024000000000001
- type: precision_at_100
value: 1.595
- type: precision_at_1000
value: 0.244
- type: precision_at_3
value: 16.996
- type: precision_at_5
value: 12.372
- type: recall_at_1
value: 25.768
- type: recall_at_10
value: 53.02
- type: recall_at_100
value: 81.329
- type: recall_at_1000
value: 94.025
- type: recall_at_3
value: 38.884
- type: recall_at_5
value: 45.057
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.627
- type: map_at_10
value: 33.106
- type: map_at_100
value: 33.936
- type: map_at_1000
value: 34.044999999999995
- type: map_at_3
value: 30.162
- type: map_at_5
value: 31.979999999999997
- type: mrr_at_1
value: 26.617
- type: mrr_at_10
value: 35.177
- type: mrr_at_100
value: 35.937999999999995
- type: mrr_at_1000
value: 36.008
- type: mrr_at_3
value: 32.562999999999995
- type: mrr_at_5
value: 34.208
- type: ndcg_at_1
value: 26.617
- type: ndcg_at_10
value: 38.082
- type: ndcg_at_100
value: 42.386
- type: ndcg_at_1000
value: 44.861000000000004
- type: ndcg_at_3
value: 32.557
- type: ndcg_at_5
value: 35.603
- type: precision_at_1
value: 26.617
- type: precision_at_10
value: 5.952
- type: precision_at_100
value: 0.874
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 13.617
- type: precision_at_5
value: 9.945
- type: recall_at_1
value: 24.627
- type: recall_at_10
value: 51.317
- type: recall_at_100
value: 71.243
- type: recall_at_1000
value: 89.39399999999999
- type: recall_at_3
value: 36.778
- type: recall_at_5
value: 44.116
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.631
- type: map_at_10
value: 28.069
- type: map_at_100
value: 30.130000000000003
- type: map_at_1000
value: 30.318
- type: map_at_3
value: 23.430999999999997
- type: map_at_5
value: 25.929000000000002
- type: mrr_at_1
value: 37.264
- type: mrr_at_10
value: 49.608999999999995
- type: mrr_at_100
value: 50.349
- type: mrr_at_1000
value: 50.373000000000005
- type: mrr_at_3
value: 46.515
- type: mrr_at_5
value: 48.41
- type: ndcg_at_1
value: 37.264
- type: ndcg_at_10
value: 37.688
- type: ndcg_at_100
value: 45.101
- type: ndcg_at_1000
value: 48.19
- type: ndcg_at_3
value: 31.471
- type: ndcg_at_5
value: 33.719
- type: precision_at_1
value: 37.264
- type: precision_at_10
value: 11.616
- type: precision_at_100
value: 1.9619999999999997
- type: precision_at_1000
value: 0.255
- type: precision_at_3
value: 23.214000000000002
- type: precision_at_5
value: 17.824
- type: recall_at_1
value: 16.631
- type: recall_at_10
value: 43.516
- type: recall_at_100
value: 68.681
- type: recall_at_1000
value: 85.751
- type: recall_at_3
value: 28.199
- type: recall_at_5
value: 34.826
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.971
- type: map_at_10
value: 22.274
- type: map_at_100
value: 32.61
- type: map_at_1000
value: 34.422000000000004
- type: map_at_3
value: 15.473999999999998
- type: map_at_5
value: 18.412
- type: mrr_at_1
value: 72.25
- type: mrr_at_10
value: 79.945
- type: mrr_at_100
value: 80.192
- type: mrr_at_1000
value: 80.199
- type: mrr_at_3
value: 78.667
- type: mrr_at_5
value: 79.49199999999999
- type: ndcg_at_1
value: 59.75
- type: ndcg_at_10
value: 45.689
- type: ndcg_at_100
value: 51.687000000000005
- type: ndcg_at_1000
value: 58.904999999999994
- type: ndcg_at_3
value: 49.675999999999995
- type: ndcg_at_5
value: 47.419
- type: precision_at_1
value: 72.25
- type: precision_at_10
value: 37.05
- type: precision_at_100
value: 12.183
- type: precision_at_1000
value: 2.2929999999999997
- type: precision_at_3
value: 53.417
- type: precision_at_5
value: 46.150000000000006
- type: recall_at_1
value: 9.971
- type: recall_at_10
value: 27.932000000000002
- type: recall_at_100
value: 58.85399999999999
- type: recall_at_1000
value: 81.728
- type: recall_at_3
value: 16.619999999999997
- type: recall_at_5
value: 21.082
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 52.83499999999999
- type: f1
value: 47.754076079187044
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 79.783
- type: map_at_10
value: 87.224
- type: map_at_100
value: 87.401
- type: map_at_1000
value: 87.413
- type: map_at_3
value: 86.29
- type: map_at_5
value: 86.896
- type: mrr_at_1
value: 86.09400000000001
- type: mrr_at_10
value: 91.789
- type: mrr_at_100
value: 91.814
- type: mrr_at_1000
value: 91.815
- type: mrr_at_3
value: 91.39399999999999
- type: mrr_at_5
value: 91.684
- type: ndcg_at_1
value: 86.09400000000001
- type: ndcg_at_10
value: 90.36999999999999
- type: ndcg_at_100
value: 90.95299999999999
- type: ndcg_at_1000
value: 91.13799999999999
- type: ndcg_at_3
value: 89.13799999999999
- type: ndcg_at_5
value: 89.845
- type: precision_at_1
value: 86.09400000000001
- type: precision_at_10
value: 10.671
- type: precision_at_100
value: 1.123
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 33.698
- type: precision_at_5
value: 20.788999999999998
- type: recall_at_1
value: 79.783
- type: recall_at_10
value: 95.50999999999999
- type: recall_at_100
value: 97.68900000000001
- type: recall_at_1000
value: 98.79400000000001
- type: recall_at_3
value: 92.14099999999999
- type: recall_at_5
value: 94
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.526
- type: map_at_10
value: 38.135999999999996
- type: map_at_100
value: 40.221000000000004
- type: map_at_1000
value: 40.394000000000005
- type: map_at_3
value: 33.548
- type: map_at_5
value: 35.975
- type: mrr_at_1
value: 47.068
- type: mrr_at_10
value: 55.224
- type: mrr_at_100
value: 56.038
- type: mrr_at_1000
value: 56.066
- type: mrr_at_3
value: 53.00899999999999
- type: mrr_at_5
value: 54.306
- type: ndcg_at_1
value: 47.068
- type: ndcg_at_10
value: 46.399
- type: ndcg_at_100
value: 53.312000000000005
- type: ndcg_at_1000
value: 55.946
- type: ndcg_at_3
value: 42.954
- type: ndcg_at_5
value: 43.765
- type: precision_at_1
value: 47.068
- type: precision_at_10
value: 12.824
- type: precision_at_100
value: 1.986
- type: precision_at_1000
value: 0.246
- type: precision_at_3
value: 28.807
- type: precision_at_5
value: 20.772
- type: recall_at_1
value: 23.526
- type: recall_at_10
value: 53.242999999999995
- type: recall_at_100
value: 78.309
- type: recall_at_1000
value: 93.92099999999999
- type: recall_at_3
value: 38.716
- type: recall_at_5
value: 44.921
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 41.641
- type: map_at_10
value: 67.24
- type: map_at_100
value: 68.108
- type: map_at_1000
value: 68.157
- type: map_at_3
value: 63.834999999999994
- type: map_at_5
value: 65.995
- type: mrr_at_1
value: 83.282
- type: mrr_at_10
value: 88.22
- type: mrr_at_100
value: 88.35499999999999
- type: mrr_at_1000
value: 88.358
- type: mrr_at_3
value: 87.571
- type: mrr_at_5
value: 88.01299999999999
- type: ndcg_at_1
value: 83.282
- type: ndcg_at_10
value: 75.066
- type: ndcg_at_100
value: 77.952
- type: ndcg_at_1000
value: 78.878
- type: ndcg_at_3
value: 70.482
- type: ndcg_at_5
value: 73.098
- type: precision_at_1
value: 83.282
- type: precision_at_10
value: 15.608
- type: precision_at_100
value: 1.7840000000000003
- type: precision_at_1000
value: 0.191
- type: precision_at_3
value: 45.324999999999996
- type: precision_at_5
value: 29.256
- type: recall_at_1
value: 41.641
- type: recall_at_10
value: 78.042
- type: recall_at_100
value: 89.223
- type: recall_at_1000
value: 95.341
- type: recall_at_3
value: 67.988
- type: recall_at_5
value: 73.14
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 93.50520000000002
- type: ap
value: 90.36560251927821
- type: f1
value: 93.50064413170799
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.355999999999998
- type: map_at_10
value: 36.082
- type: map_at_100
value: 37.239
- type: map_at_1000
value: 37.285000000000004
- type: map_at_3
value: 32.16
- type: map_at_5
value: 34.469
- type: mrr_at_1
value: 23.968
- type: mrr_at_10
value: 36.708
- type: mrr_at_100
value: 37.795
- type: mrr_at_1000
value: 37.836
- type: mrr_at_3
value: 32.865
- type: mrr_at_5
value: 35.154
- type: ndcg_at_1
value: 23.968
- type: ndcg_at_10
value: 43.152
- type: ndcg_at_100
value: 48.615
- type: ndcg_at_1000
value: 49.714000000000006
- type: ndcg_at_3
value: 35.208
- type: ndcg_at_5
value: 39.342
- type: precision_at_1
value: 23.968
- type: precision_at_10
value: 6.784
- type: precision_at_100
value: 0.951
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.995
- type: precision_at_5
value: 11.092
- type: recall_at_1
value: 23.355999999999998
- type: recall_at_10
value: 64.828
- type: recall_at_100
value: 89.888
- type: recall_at_1000
value: 98.181
- type: recall_at_3
value: 43.336000000000006
- type: recall_at_5
value: 53.274
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 94.97948016415869
- type: f1
value: 94.77285510790911
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 78.49749202006383
- type: f1
value: 59.36772995632707
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 77.64290517821117
- type: f1
value: 75.33296771580456
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 80.76664425016811
- type: f1
value: 80.79147962348141
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 35.158637354708034
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 32.39319499403552
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.19460802526735
- type: mrr
value: 33.39458959690712
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.225
- type: map_at_10
value: 15.609
- type: map_at_100
value: 20.067
- type: map_at_1000
value: 21.709999999999997
- type: map_at_3
value: 11.518
- type: map_at_5
value: 13.469999999999999
- type: mrr_at_1
value: 50.15500000000001
- type: mrr_at_10
value: 58.711
- type: mrr_at_100
value: 59.333000000000006
- type: mrr_at_1000
value: 59.362
- type: mrr_at_3
value: 56.65599999999999
- type: mrr_at_5
value: 57.972
- type: ndcg_at_1
value: 48.452
- type: ndcg_at_10
value: 38.845
- type: ndcg_at_100
value: 36.597
- type: ndcg_at_1000
value: 45.472
- type: ndcg_at_3
value: 43.947
- type: ndcg_at_5
value: 42.097
- type: precision_at_1
value: 49.845
- type: precision_at_10
value: 28.638
- type: precision_at_100
value: 9.229
- type: precision_at_1000
value: 2.234
- type: precision_at_3
value: 40.867
- type: precision_at_5
value: 36.285000000000004
- type: recall_at_1
value: 7.225
- type: recall_at_10
value: 19.272
- type: recall_at_100
value: 37.299
- type: recall_at_1000
value: 68.757
- type: recall_at_3
value: 12.350999999999999
- type: recall_at_5
value: 15.369
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 34.453
- type: map_at_10
value: 50.748000000000005
- type: map_at_100
value: 51.666000000000004
- type: map_at_1000
value: 51.687000000000005
- type: map_at_3
value: 46.300000000000004
- type: map_at_5
value: 49.032
- type: mrr_at_1
value: 38.673
- type: mrr_at_10
value: 53.11
- type: mrr_at_100
value: 53.772
- type: mrr_at_1000
value: 53.784
- type: mrr_at_3
value: 49.483
- type: mrr_at_5
value: 51.751999999999995
- type: ndcg_at_1
value: 38.673
- type: ndcg_at_10
value: 58.60300000000001
- type: ndcg_at_100
value: 62.302
- type: ndcg_at_1000
value: 62.763999999999996
- type: ndcg_at_3
value: 50.366
- type: ndcg_at_5
value: 54.888999999999996
- type: precision_at_1
value: 38.673
- type: precision_at_10
value: 9.522
- type: precision_at_100
value: 1.162
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 22.779
- type: precision_at_5
value: 16.256999999999998
- type: recall_at_1
value: 34.453
- type: recall_at_10
value: 80.074
- type: recall_at_100
value: 95.749
- type: recall_at_1000
value: 99.165
- type: recall_at_3
value: 58.897999999999996
- type: recall_at_5
value: 69.349
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 71.80499999999999
- type: map_at_10
value: 85.773
- type: map_at_100
value: 86.4
- type: map_at_1000
value: 86.414
- type: map_at_3
value: 82.919
- type: map_at_5
value: 84.70299999999999
- type: mrr_at_1
value: 82.69999999999999
- type: mrr_at_10
value: 88.592
- type: mrr_at_100
value: 88.682
- type: mrr_at_1000
value: 88.683
- type: mrr_at_3
value: 87.705
- type: mrr_at_5
value: 88.30799999999999
- type: ndcg_at_1
value: 82.69
- type: ndcg_at_10
value: 89.316
- type: ndcg_at_100
value: 90.45100000000001
- type: ndcg_at_1000
value: 90.525
- type: ndcg_at_3
value: 86.68
- type: ndcg_at_5
value: 88.113
- type: precision_at_1
value: 82.69
- type: precision_at_10
value: 13.507
- type: precision_at_100
value: 1.5350000000000001
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.927
- type: precision_at_5
value: 24.823999999999998
- type: recall_at_1
value: 71.80499999999999
- type: recall_at_10
value: 95.965
- type: recall_at_100
value: 99.70400000000001
- type: recall_at_1000
value: 99.992
- type: recall_at_3
value: 88.268
- type: recall_at_5
value: 92.45
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 60.24178219867024
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 64.99552099515469
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.4879999999999995
- type: map_at_10
value: 14.774999999999999
- type: map_at_100
value: 17.285
- type: map_at_1000
value: 17.648
- type: map_at_3
value: 10.4
- type: map_at_5
value: 12.552
- type: mrr_at_1
value: 27.1
- type: mrr_at_10
value: 39.251000000000005
- type: mrr_at_100
value: 40.335
- type: mrr_at_1000
value: 40.367
- type: mrr_at_3
value: 35.683
- type: mrr_at_5
value: 37.733
- type: ndcg_at_1
value: 27.1
- type: ndcg_at_10
value: 23.974
- type: ndcg_at_100
value: 33.161
- type: ndcg_at_1000
value: 38.853
- type: ndcg_at_3
value: 22.695999999999998
- type: ndcg_at_5
value: 19.881
- type: precision_at_1
value: 27.1
- type: precision_at_10
value: 12.479999999999999
- type: precision_at_100
value: 2.571
- type: precision_at_1000
value: 0.393
- type: precision_at_3
value: 21.367
- type: precision_at_5
value: 17.560000000000002
- type: recall_at_1
value: 5.4879999999999995
- type: recall_at_10
value: 25.290000000000003
- type: recall_at_100
value: 52.222
- type: recall_at_1000
value: 79.77300000000001
- type: recall_at_3
value: 13.001999999999999
- type: recall_at_5
value: 17.812
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 85.3407705934785
- type: cos_sim_spearman
value: 81.28145766913589
- type: euclidean_pearson
value: 82.69277819943873
- type: euclidean_spearman
value: 81.26097565088551
- type: manhattan_pearson
value: 82.73440374725746
- type: manhattan_spearman
value: 81.25376873901254
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 87.23415639286914
- type: cos_sim_spearman
value: 79.80147936079915
- type: euclidean_pearson
value: 84.324220218071
- type: euclidean_spearman
value: 79.71794784987208
- type: manhattan_pearson
value: 84.27523842345964
- type: manhattan_spearman
value: 79.58070329781553
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 85.90966234413125
- type: cos_sim_spearman
value: 87.10742652814713
- type: euclidean_pearson
value: 86.28297063322286
- type: euclidean_spearman
value: 87.09425001932226
- type: manhattan_pearson
value: 86.19204338411774
- type: manhattan_spearman
value: 87.02046826723424
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 84.12351399124411
- type: cos_sim_spearman
value: 83.32955357808568
- type: euclidean_pearson
value: 83.81222384305896
- type: euclidean_spearman
value: 83.1836394454507
- type: manhattan_pearson
value: 83.79162945392092
- type: manhattan_spearman
value: 83.14306058903364
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 86.9345194840047
- type: cos_sim_spearman
value: 88.47286320653176
- type: euclidean_pearson
value: 87.72825182191445
- type: euclidean_spearman
value: 88.33484195475864
- type: manhattan_pearson
value: 87.75121043906692
- type: manhattan_spearman
value: 88.36695329548576
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 84.80215370816441
- type: cos_sim_spearman
value: 86.44917331470305
- type: euclidean_pearson
value: 85.3458573021962
- type: euclidean_spearman
value: 86.24853627058414
- type: manhattan_pearson
value: 85.38477148579328
- type: manhattan_spearman
value: 86.28201585857053
- 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: 87.20498617189688
- type: cos_sim_spearman
value: 87.61389142076317
- type: euclidean_pearson
value: 88.15430699740293
- type: euclidean_spearman
value: 87.35065666258774
- type: manhattan_pearson
value: 88.2994571119992
- type: manhattan_spearman
value: 87.60920178284005
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 68.27672577392406
- type: cos_sim_spearman
value: 68.31250175566586
- type: euclidean_pearson
value: 69.45016222616813
- type: euclidean_spearman
value: 67.93461301528046
- type: manhattan_pearson
value: 69.39774219739259
- type: manhattan_spearman
value: 67.78124856615536
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 85.31916148698113
- type: cos_sim_spearman
value: 87.45541524487057
- type: euclidean_pearson
value: 86.5845909408775
- type: euclidean_spearman
value: 87.2373331768082
- type: manhattan_pearson
value: 86.64467698948668
- type: manhattan_spearman
value: 87.26707857525533
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 88.0007930269447
- type: mrr
value: 96.52852594029063
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 60.99400000000001
- type: map_at_10
value: 70.923
- type: map_at_100
value: 71.299
- type: map_at_1000
value: 71.318
- type: map_at_3
value: 67.991
- type: map_at_5
value: 69.292
- type: mrr_at_1
value: 64.333
- type: mrr_at_10
value: 71.98400000000001
- type: mrr_at_100
value: 72.306
- type: mrr_at_1000
value: 72.32499999999999
- type: mrr_at_3
value: 69.833
- type: mrr_at_5
value: 70.783
- type: ndcg_at_1
value: 64.333
- type: ndcg_at_10
value: 75.729
- type: ndcg_at_100
value: 77.38199999999999
- type: ndcg_at_1000
value: 77.788
- type: ndcg_at_3
value: 70.774
- type: ndcg_at_5
value: 72.478
- type: precision_at_1
value: 64.333
- type: precision_at_10
value: 10.167
- type: precision_at_100
value: 1.0999999999999999
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 27.778000000000002
- type: precision_at_5
value: 17.867
- type: recall_at_1
value: 60.99400000000001
- type: recall_at_10
value: 89.48899999999999
- type: recall_at_100
value: 97
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 75.85
- type: recall_at_5
value: 80.328
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.86435643564356
- type: cos_sim_ap
value: 96.78001342960285
- type: cos_sim_f1
value: 93.07030854830552
- type: cos_sim_precision
value: 94.16581371545547
- type: cos_sim_recall
value: 92
- type: dot_accuracy
value: 99.74653465346535
- type: dot_ap
value: 92.80391251199522
- type: dot_f1
value: 87.36426456071075
- type: dot_precision
value: 86.25730994152046
- type: dot_recall
value: 88.5
- type: euclidean_accuracy
value: 99.86138613861387
- type: euclidean_ap
value: 96.77007810699926
- type: euclidean_f1
value: 92.95065458207452
- type: euclidean_precision
value: 93.6105476673428
- type: euclidean_recall
value: 92.30000000000001
- type: manhattan_accuracy
value: 99.86336633663366
- type: manhattan_ap
value: 96.78913160708261
- type: manhattan_f1
value: 93.03030303030305
- type: manhattan_precision
value: 93.9795918367347
- type: manhattan_recall
value: 92.10000000000001
- type: max_accuracy
value: 99.86435643564356
- type: max_ap
value: 96.78913160708261
- type: max_f1
value: 93.07030854830552
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 67.80798406371026
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 35.69251193913337
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 55.04250964616215
- type: mrr
value: 55.92283125371361
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.05492162235311
- type: cos_sim_spearman
value: 30.90473006515039
- type: dot_pearson
value: 26.85480454105073
- type: dot_spearman
value: 27.02880537417923
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.246
- type: map_at_10
value: 2.125
- type: map_at_100
value: 12.892999999999999
- type: map_at_1000
value: 31.513999999999996
- type: map_at_3
value: 0.695
- type: map_at_5
value: 1.133
- type: mrr_at_1
value: 92
- type: mrr_at_10
value: 95.667
- type: mrr_at_100
value: 95.667
- type: mrr_at_1000
value: 95.667
- type: mrr_at_3
value: 95.667
- type: mrr_at_5
value: 95.667
- type: ndcg_at_1
value: 88
- type: ndcg_at_10
value: 82.464
- type: ndcg_at_100
value: 63.351
- type: ndcg_at_1000
value: 57.129
- type: ndcg_at_3
value: 85.87700000000001
- type: ndcg_at_5
value: 86.042
- type: precision_at_1
value: 92
- type: precision_at_10
value: 86.2
- type: precision_at_100
value: 65.10000000000001
- type: precision_at_1000
value: 25.044
- type: precision_at_3
value: 89.333
- type: precision_at_5
value: 89.60000000000001
- type: recall_at_1
value: 0.246
- type: recall_at_10
value: 2.2880000000000003
- type: recall_at_100
value: 15.853
- type: recall_at_1000
value: 54.05
- type: recall_at_3
value: 0.72
- type: recall_at_5
value: 1.196
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.322
- type: map_at_10
value: 11.673
- type: map_at_100
value: 18.655
- type: map_at_1000
value: 20.058999999999997
- type: map_at_3
value: 6.265
- type: map_at_5
value: 8.549
- type: mrr_at_1
value: 42.857
- type: mrr_at_10
value: 55.352999999999994
- type: mrr_at_100
value: 55.928999999999995
- type: mrr_at_1000
value: 55.928999999999995
- type: mrr_at_3
value: 50
- type: mrr_at_5
value: 53.571000000000005
- type: ndcg_at_1
value: 39.796
- type: ndcg_at_10
value: 28.225
- type: ndcg_at_100
value: 40.452
- type: ndcg_at_1000
value: 51.332
- type: ndcg_at_3
value: 32.308
- type: ndcg_at_5
value: 30.942999999999998
- type: precision_at_1
value: 42.857
- type: precision_at_10
value: 24.490000000000002
- type: precision_at_100
value: 8.366999999999999
- type: precision_at_1000
value: 1.5709999999999997
- type: precision_at_3
value: 32.653
- type: precision_at_5
value: 30.203999999999997
- type: recall_at_1
value: 3.322
- type: recall_at_10
value: 17.857
- type: recall_at_100
value: 51.169
- type: recall_at_1000
value: 85.382
- type: recall_at_3
value: 7.126
- type: recall_at_5
value: 11.186
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 72.1046
- type: ap
value: 14.84774372187047
- type: f1
value: 55.52709376912111
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 60.18958687040181
- type: f1
value: 60.53154943862625
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 54.61440440799667
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.34577099600644
- type: cos_sim_ap
value: 78.19613471607386
- type: cos_sim_f1
value: 71.30501144746884
- type: cos_sim_precision
value: 68.83595284872298
- type: cos_sim_recall
value: 73.95778364116094
- type: dot_accuracy
value: 82.89324670680098
- type: dot_ap
value: 63.02362697550343
- type: dot_f1
value: 59.69837587006961
- type: dot_precision
value: 53.2712215320911
- type: dot_recall
value: 67.8891820580475
- type: euclidean_accuracy
value: 87.24444179531503
- type: euclidean_ap
value: 78.38356749852895
- type: euclidean_f1
value: 71.42133265771471
- type: euclidean_precision
value: 68.68908382066277
- type: euclidean_recall
value: 74.37994722955145
- type: manhattan_accuracy
value: 87.24444179531503
- type: manhattan_ap
value: 78.27660966609476
- type: manhattan_f1
value: 71.42165173165415
- type: manhattan_precision
value: 66.00268576544315
- type: manhattan_recall
value: 77.81002638522428
- type: max_accuracy
value: 87.34577099600644
- type: max_ap
value: 78.38356749852895
- type: max_f1
value: 71.42165173165415
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.90829355377032
- type: cos_sim_ap
value: 85.79696678631824
- type: cos_sim_f1
value: 77.8494623655914
- type: cos_sim_precision
value: 76.32610786417105
- type: cos_sim_recall
value: 79.43486295041576
- type: dot_accuracy
value: 86.17223580548765
- type: dot_ap
value: 79.05804163697516
- type: dot_f1
value: 72.38855622089154
- type: dot_precision
value: 69.61467368121713
- type: dot_recall
value: 75.39267015706807
- type: euclidean_accuracy
value: 88.94128148406877
- type: euclidean_ap
value: 85.86615739743813
- type: euclidean_f1
value: 77.97001153402537
- type: euclidean_precision
value: 75.44099647202822
- type: euclidean_recall
value: 80.67446874037573
- type: manhattan_accuracy
value: 88.9781503473435
- type: manhattan_ap
value: 85.91093266751166
- type: manhattan_f1
value: 77.96835723791216
- type: manhattan_precision
value: 74.98577929465301
- type: manhattan_recall
value: 81.19802894979982
- type: max_accuracy
value: 88.9781503473435
- type: max_ap
value: 85.91093266751166
- type: max_f1
value: 77.97001153402537
language:
- en