metadata
tags:
- mteb
model-index:
- name: bert_1b3_mixlang_newstep3
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 70.11940298507463
- type: ap
value: 32.37756187516329
- type: f1
value: 63.92312669545795
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 92.950675
- type: ap
value: 89.69186819088316
- type: f1
value: 92.94108521905532
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 50.522
- type: f1
value: 48.76020527037862
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.865
- type: map_at_10
value: 26.026
- type: map_at_100
value: 27.586
- type: map_at_1000
value: 27.622999999999998
- type: map_at_3
value: 21.859
- type: map_at_5
value: 24.049
- type: mrr_at_1
value: 15.504999999999999
- type: mrr_at_10
value: 26.265
- type: mrr_at_100
value: 27.810000000000002
- type: mrr_at_1000
value: 27.847
- type: mrr_at_3
value: 22.06
- type: mrr_at_5
value: 24.247
- type: ndcg_at_1
value: 14.865
- type: ndcg_at_10
value: 32.934999999999995
- type: ndcg_at_100
value: 40.627
- type: ndcg_at_1000
value: 41.524
- type: ndcg_at_3
value: 24.153
- type: ndcg_at_5
value: 28.133999999999997
- type: precision_at_1
value: 14.865
- type: precision_at_10
value: 5.541
- type: precision_at_100
value: 0.9159999999999999
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 10.266
- type: precision_at_5
value: 8.108
- type: recall_at_1
value: 14.865
- type: recall_at_10
value: 55.405
- type: recall_at_100
value: 91.607
- type: recall_at_1000
value: 98.506
- type: recall_at_3
value: 30.797
- type: recall_at_5
value: 40.541
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 47.028296913559814
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 38.38123118365735
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 58.9616553564134
- type: mrr
value: 72.16033504814668
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.00899493452621
- type: cos_sim_spearman
value: 83.85673000958819
- type: euclidean_pearson
value: 85.65567511199598
- type: euclidean_spearman
value: 83.90311660870698
- type: manhattan_pearson
value: 85.37147829428248
- type: manhattan_spearman
value: 83.74588411039522
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 75.5909090909091
- type: f1
value: 74.476632049175
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 38.981180962194216
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 34.9394829907367
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.277
- type: map_at_10
value: 42.153
- type: map_at_100
value: 43.683
- type: map_at_1000
value: 43.817
- type: map_at_3
value: 38.454
- type: map_at_5
value: 40.721000000000004
- type: mrr_at_1
value: 38.913
- type: mrr_at_10
value: 48.232
- type: mrr_at_100
value: 48.888
- type: mrr_at_1000
value: 48.929
- type: mrr_at_3
value: 45.279
- type: mrr_at_5
value: 47.089
- type: ndcg_at_1
value: 38.913
- type: ndcg_at_10
value: 48.518
- type: ndcg_at_100
value: 53.797
- type: ndcg_at_1000
value: 55.754999999999995
- type: ndcg_at_3
value: 43.122
- type: ndcg_at_5
value: 45.869
- type: precision_at_1
value: 38.913
- type: precision_at_10
value: 9.413
- type: precision_at_100
value: 1.567
- type: precision_at_1000
value: 0.20600000000000002
- type: precision_at_3
value: 20.791999999999998
- type: precision_at_5
value: 15.193000000000001
- type: recall_at_1
value: 31.277
- type: recall_at_10
value: 60.475
- type: recall_at_100
value: 82.675
- type: recall_at_1000
value: 95.298
- type: recall_at_3
value: 44.388
- type: recall_at_5
value: 52.242999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.593
- type: map_at_10
value: 35.089999999999996
- type: map_at_100
value: 36.269
- type: map_at_1000
value: 36.419000000000004
- type: map_at_3
value: 32.449
- type: map_at_5
value: 33.952
- type: mrr_at_1
value: 32.484
- type: mrr_at_10
value: 40.725
- type: mrr_at_100
value: 41.465999999999994
- type: mrr_at_1000
value: 41.521
- type: mrr_at_3
value: 38.757999999999996
- type: mrr_at_5
value: 39.869
- type: ndcg_at_1
value: 32.484
- type: ndcg_at_10
value: 40.384
- type: ndcg_at_100
value: 44.984
- type: ndcg_at_1000
value: 47.528
- type: ndcg_at_3
value: 36.77
- type: ndcg_at_5
value: 38.505
- type: precision_at_1
value: 32.484
- type: precision_at_10
value: 7.866
- type: precision_at_100
value: 1.2959999999999998
- type: precision_at_1000
value: 0.185
- type: precision_at_3
value: 18.195
- type: precision_at_5
value: 13.032
- type: recall_at_1
value: 25.593
- type: recall_at_10
value: 49.289
- type: recall_at_100
value: 69.84700000000001
- type: recall_at_1000
value: 86.329
- type: recall_at_3
value: 38.51
- type: recall_at_5
value: 43.349
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 35.116
- type: map_at_10
value: 45.908
- type: map_at_100
value: 46.979
- type: map_at_1000
value: 47.046
- type: map_at_3
value: 42.724000000000004
- type: map_at_5
value: 44.507999999999996
- type: mrr_at_1
value: 40.313
- type: mrr_at_10
value: 49.195
- type: mrr_at_100
value: 49.996
- type: mrr_at_1000
value: 50.03300000000001
- type: mrr_at_3
value: 46.708
- type: mrr_at_5
value: 48.187999999999995
- type: ndcg_at_1
value: 40.313
- type: ndcg_at_10
value: 51.43600000000001
- type: ndcg_at_100
value: 55.873
- type: ndcg_at_1000
value: 57.288
- type: ndcg_at_3
value: 46.038000000000004
- type: ndcg_at_5
value: 48.729
- type: precision_at_1
value: 40.313
- type: precision_at_10
value: 8.382000000000001
- type: precision_at_100
value: 1.145
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 20.480999999999998
- type: precision_at_5
value: 14.219000000000001
- type: recall_at_1
value: 35.116
- type: recall_at_10
value: 64.524
- type: recall_at_100
value: 83.859
- type: recall_at_1000
value: 93.977
- type: recall_at_3
value: 50.102999999999994
- type: recall_at_5
value: 56.818000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.488
- type: map_at_10
value: 25.667
- type: map_at_100
value: 26.541999999999998
- type: map_at_1000
value: 26.637
- type: map_at_3
value: 23.483
- type: map_at_5
value: 24.667
- type: mrr_at_1
value: 20
- type: mrr_at_10
value: 27.178
- type: mrr_at_100
value: 27.989000000000004
- type: mrr_at_1000
value: 28.07
- type: mrr_at_3
value: 25.122
- type: mrr_at_5
value: 26.275
- type: ndcg_at_1
value: 20
- type: ndcg_at_10
value: 29.736
- type: ndcg_at_100
value: 34.358
- type: ndcg_at_1000
value: 37.036
- type: ndcg_at_3
value: 25.405
- type: ndcg_at_5
value: 27.441
- type: precision_at_1
value: 20
- type: precision_at_10
value: 4.712000000000001
- type: precision_at_100
value: 0.751
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 10.885
- type: precision_at_5
value: 7.706
- type: recall_at_1
value: 18.488
- type: recall_at_10
value: 40.83
- type: recall_at_100
value: 62.707
- type: recall_at_1000
value: 83.41199999999999
- type: recall_at_3
value: 29.21
- type: recall_at_5
value: 34.009
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.532
- type: map_at_10
value: 15.193000000000001
- type: map_at_100
value: 16.381
- type: map_at_1000
value: 16.524
- type: map_at_3
value: 13.386000000000001
- type: map_at_5
value: 14.261
- type: mrr_at_1
value: 11.940000000000001
- type: mrr_at_10
value: 18.285
- type: mrr_at_100
value: 19.373
- type: mrr_at_1000
value: 19.467000000000002
- type: mrr_at_3
value: 16.252
- type: mrr_at_5
value: 17.26
- type: ndcg_at_1
value: 11.940000000000001
- type: ndcg_at_10
value: 19.095000000000002
- type: ndcg_at_100
value: 25.214
- type: ndcg_at_1000
value: 28.619
- type: ndcg_at_3
value: 15.482000000000001
- type: ndcg_at_5
value: 16.892
- type: precision_at_1
value: 11.940000000000001
- type: precision_at_10
value: 3.744
- type: precision_at_100
value: 0.815
- type: precision_at_1000
value: 0.124
- type: precision_at_3
value: 7.710999999999999
- type: precision_at_5
value: 5.647
- type: recall_at_1
value: 9.532
- type: recall_at_10
value: 28.026
- type: recall_at_100
value: 55.253
- type: recall_at_1000
value: 79.86999999999999
- type: recall_at_3
value: 18.084
- type: recall_at_5
value: 21.553
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.416
- type: map_at_10
value: 32.649
- type: map_at_100
value: 33.983000000000004
- type: map_at_1000
value: 34.107
- type: map_at_3
value: 29.254
- type: map_at_5
value: 31.339
- type: mrr_at_1
value: 28.778
- type: mrr_at_10
value: 37.513999999999996
- type: mrr_at_100
value: 38.458999999999996
- type: mrr_at_1000
value: 38.517
- type: mrr_at_3
value: 34.585
- type: mrr_at_5
value: 36.514
- type: ndcg_at_1
value: 28.778
- type: ndcg_at_10
value: 38.233
- type: ndcg_at_100
value: 44.14
- type: ndcg_at_1000
value: 46.583000000000006
- type: ndcg_at_3
value: 32.718
- type: ndcg_at_5
value: 35.778999999999996
- type: precision_at_1
value: 28.778
- type: precision_at_10
value: 7.2090000000000005
- type: precision_at_100
value: 1.194
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 15.495999999999999
- type: precision_at_5
value: 11.781
- type: recall_at_1
value: 23.416
- type: recall_at_10
value: 50.063
- type: recall_at_100
value: 75.4
- type: recall_at_1000
value: 91.74799999999999
- type: recall_at_3
value: 35.113
- type: recall_at_5
value: 42.620999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.891
- type: map_at_10
value: 28.000000000000004
- type: map_at_100
value: 29.354999999999997
- type: map_at_1000
value: 29.453000000000003
- type: map_at_3
value: 24.551000000000002
- type: map_at_5
value: 26.383000000000003
- type: mrr_at_1
value: 23.402
- type: mrr_at_10
value: 32.308
- type: mrr_at_100
value: 33.242
- type: mrr_at_1000
value: 33.294000000000004
- type: mrr_at_3
value: 29.262
- type: mrr_at_5
value: 30.997000000000003
- type: ndcg_at_1
value: 23.402
- type: ndcg_at_10
value: 33.932
- type: ndcg_at_100
value: 39.925
- type: ndcg_at_1000
value: 42.126999999999995
- type: ndcg_at_3
value: 27.816999999999997
- type: ndcg_at_5
value: 30.554
- type: precision_at_1
value: 23.402
- type: precision_at_10
value: 6.747
- type: precision_at_100
value: 1.147
- type: precision_at_1000
value: 0.15
- type: precision_at_3
value: 13.469999999999999
- type: precision_at_5
value: 10.32
- type: recall_at_1
value: 18.891
- type: recall_at_10
value: 47.58
- type: recall_at_100
value: 73.668
- type: recall_at_1000
value: 88.77000000000001
- type: recall_at_3
value: 30.726
- type: recall_at_5
value: 37.547000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.303499999999996
- type: map_at_10
value: 28.263499999999997
- type: map_at_100
value: 29.431250000000002
- type: map_at_1000
value: 29.555166666666665
- type: map_at_3
value: 25.59133333333333
- type: map_at_5
value: 27.091500000000003
- type: mrr_at_1
value: 24.19725
- type: mrr_at_10
value: 31.803750000000004
- type: mrr_at_100
value: 32.691916666666664
- type: mrr_at_1000
value: 32.760083333333334
- type: mrr_at_3
value: 29.447749999999996
- type: mrr_at_5
value: 30.79858333333334
- type: ndcg_at_1
value: 24.19725
- type: ndcg_at_10
value: 33.11925000000001
- type: ndcg_at_100
value: 38.384916666666655
- type: ndcg_at_1000
value: 40.991499999999995
- type: ndcg_at_3
value: 28.5115
- type: ndcg_at_5
value: 30.718833333333333
- type: precision_at_1
value: 24.19725
- type: precision_at_10
value: 6.061666666666666
- type: precision_at_100
value: 1.0404166666666665
- type: precision_at_1000
value: 0.14583333333333337
- type: precision_at_3
value: 13.347083333333334
- type: precision_at_5
value: 9.747916666666667
- type: recall_at_1
value: 20.303499999999996
- type: recall_at_10
value: 43.93183333333334
- type: recall_at_100
value: 67.47800000000001
- type: recall_at_1000
value: 85.91425000000001
- type: recall_at_3
value: 31.160083333333333
- type: recall_at_5
value: 36.76633333333333
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 12.666
- type: map_at_10
value: 18.448999999999998
- type: map_at_100
value: 19.448
- type: map_at_1000
value: 19.54
- type: map_at_3
value: 16.581000000000003
- type: map_at_5
value: 17.485999999999997
- type: mrr_at_1
value: 14.11
- type: mrr_at_10
value: 19.796
- type: mrr_at_100
value: 20.785999999999998
- type: mrr_at_1000
value: 20.861
- type: mrr_at_3
value: 18.175
- type: mrr_at_5
value: 18.926000000000002
- type: ndcg_at_1
value: 14.11
- type: ndcg_at_10
value: 21.83
- type: ndcg_at_100
value: 27.017999999999997
- type: ndcg_at_1000
value: 29.520999999999997
- type: ndcg_at_3
value: 18.358
- type: ndcg_at_5
value: 19.719
- type: precision_at_1
value: 14.11
- type: precision_at_10
value: 3.819
- type: precision_at_100
value: 0.701
- type: precision_at_1000
value: 0.097
- type: precision_at_3
value: 8.384
- type: precision_at_5
value: 5.92
- type: recall_at_1
value: 12.666
- type: recall_at_10
value: 30.746000000000002
- type: recall_at_100
value: 54.675
- type: recall_at_1000
value: 73.57900000000001
- type: recall_at_3
value: 21.196
- type: recall_at_5
value: 24.552
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 12.53
- type: map_at_10
value: 17.881
- type: map_at_100
value: 18.923000000000002
- type: map_at_1000
value: 19.049
- type: map_at_3
value: 16.088
- type: map_at_5
value: 17
- type: mrr_at_1
value: 15.244
- type: mrr_at_10
value: 20.906
- type: mrr_at_100
value: 21.83
- type: mrr_at_1000
value: 21.913
- type: mrr_at_3
value: 19.104
- type: mrr_at_5
value: 19.994999999999997
- type: ndcg_at_1
value: 15.244
- type: ndcg_at_10
value: 21.541
- type: ndcg_at_100
value: 26.799
- type: ndcg_at_1000
value: 29.927
- type: ndcg_at_3
value: 18.208
- type: ndcg_at_5
value: 19.573999999999998
- type: precision_at_1
value: 15.244
- type: precision_at_10
value: 4.04
- type: precision_at_100
value: 0.808
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 8.672
- type: precision_at_5
value: 6.283999999999999
- type: recall_at_1
value: 12.53
- type: recall_at_10
value: 29.601
- type: recall_at_100
value: 53.615
- type: recall_at_1000
value: 76.344
- type: recall_at_3
value: 20.159
- type: recall_at_5
value: 23.746000000000002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.849
- type: map_at_10
value: 28.937
- type: map_at_100
value: 30.003999999999998
- type: map_at_1000
value: 30.122
- type: map_at_3
value: 26.150000000000002
- type: map_at_5
value: 27.744000000000003
- type: mrr_at_1
value: 25.093
- type: mrr_at_10
value: 32.143
- type: mrr_at_100
value: 33.053
- type: mrr_at_1000
value: 33.134
- type: mrr_at_3
value: 29.586000000000002
- type: mrr_at_5
value: 31.116
- type: ndcg_at_1
value: 25.093
- type: ndcg_at_10
value: 33.631
- type: ndcg_at_100
value: 38.893
- type: ndcg_at_1000
value: 41.692
- type: ndcg_at_3
value: 28.497
- type: ndcg_at_5
value: 31.028
- type: precision_at_1
value: 25.093
- type: precision_at_10
value: 5.765
- type: precision_at_100
value: 0.947
- type: precision_at_1000
value: 0.13
- type: precision_at_3
value: 12.623999999999999
- type: precision_at_5
value: 9.347
- type: recall_at_1
value: 21.849
- type: recall_at_10
value: 44.767
- type: recall_at_100
value: 68.298
- type: recall_at_1000
value: 88.107
- type: recall_at_3
value: 30.968
- type: recall_at_5
value: 37.19
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.409
- type: map_at_10
value: 27.750999999999998
- type: map_at_100
value: 29.241
- type: map_at_1000
value: 29.467
- type: map_at_3
value: 24.29
- type: map_at_5
value: 26.448
- type: mrr_at_1
value: 22.53
- type: mrr_at_10
value: 31.887999999999998
- type: mrr_at_100
value: 32.89
- type: mrr_at_1000
value: 32.956
- type: mrr_at_3
value: 28.854000000000003
- type: mrr_at_5
value: 30.751
- type: ndcg_at_1
value: 22.53
- type: ndcg_at_10
value: 33.827
- type: ndcg_at_100
value: 39.749
- type: ndcg_at_1000
value: 42.677
- type: ndcg_at_3
value: 28.101
- type: ndcg_at_5
value: 31.380999999999997
- type: precision_at_1
value: 22.53
- type: precision_at_10
value: 6.976
- type: precision_at_100
value: 1.443
- type: precision_at_1000
value: 0.23700000000000002
- type: precision_at_3
value: 13.966000000000001
- type: precision_at_5
value: 10.909
- type: recall_at_1
value: 18.409
- type: recall_at_10
value: 46.217000000000006
- type: recall_at_100
value: 72.882
- type: recall_at_1000
value: 91.625
- type: recall_at_3
value: 30.64
- type: recall_at_5
value: 38.948
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.875
- type: map_at_10
value: 21.484
- type: map_at_100
value: 22.367
- type: map_at_1000
value: 22.481
- type: map_at_3
value: 19.686
- type: map_at_5
value: 20.589
- type: mrr_at_1
value: 17.560000000000002
- type: mrr_at_10
value: 23.474999999999998
- type: mrr_at_100
value: 24.331
- type: mrr_at_1000
value: 24.426000000000002
- type: mrr_at_3
value: 21.688
- type: mrr_at_5
value: 22.603
- type: ndcg_at_1
value: 17.560000000000002
- type: ndcg_at_10
value: 25.268
- type: ndcg_at_100
value: 29.869
- type: ndcg_at_1000
value: 33.145
- type: ndcg_at_3
value: 21.622
- type: ndcg_at_5
value: 23.155
- type: precision_at_1
value: 17.560000000000002
- type: precision_at_10
value: 4.067
- type: precision_at_100
value: 0.6709999999999999
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 9.489
- type: precision_at_5
value: 6.617000000000001
- type: recall_at_1
value: 15.875
- type: recall_at_10
value: 35.064
- type: recall_at_100
value: 56.857
- type: recall_at_1000
value: 81.91199999999999
- type: recall_at_3
value: 24.823999999999998
- type: recall_at_5
value: 28.62
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.637
- type: map_at_10
value: 18.401999999999997
- type: map_at_100
value: 20.121
- type: map_at_1000
value: 20.305999999999997
- type: map_at_3
value: 15.348
- type: map_at_5
value: 16.841
- type: mrr_at_1
value: 23.909
- type: mrr_at_10
value: 34.512
- type: mrr_at_100
value: 35.485
- type: mrr_at_1000
value: 35.528999999999996
- type: mrr_at_3
value: 31.368000000000002
- type: mrr_at_5
value: 33.137
- type: ndcg_at_1
value: 23.909
- type: ndcg_at_10
value: 25.94
- type: ndcg_at_100
value: 33.116
- type: ndcg_at_1000
value: 36.502
- type: ndcg_at_3
value: 21.046
- type: ndcg_at_5
value: 22.715
- type: precision_at_1
value: 23.909
- type: precision_at_10
value: 8.195
- type: precision_at_100
value: 1.593
- type: precision_at_1000
value: 0.22200000000000003
- type: precision_at_3
value: 15.744
- type: precision_at_5
value: 12.142999999999999
- type: recall_at_1
value: 10.637
- type: recall_at_10
value: 31.251
- type: recall_at_100
value: 56.477999999999994
- type: recall_at_1000
value: 75.52600000000001
- type: recall_at_3
value: 19.482
- type: recall_at_5
value: 24.145
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.786999999999999
- type: map_at_10
value: 16.182
- type: map_at_100
value: 22.698
- type: map_at_1000
value: 24.192
- type: map_at_3
value: 11.84
- type: map_at_5
value: 13.602
- type: mrr_at_1
value: 56.99999999999999
- type: mrr_at_10
value: 66.702
- type: mrr_at_100
value: 67.291
- type: mrr_at_1000
value: 67.301
- type: mrr_at_3
value: 64.708
- type: mrr_at_5
value: 65.946
- type: ndcg_at_1
value: 46.75
- type: ndcg_at_10
value: 35.469
- type: ndcg_at_100
value: 40.077
- type: ndcg_at_1000
value: 47.252
- type: ndcg_at_3
value: 39.096
- type: ndcg_at_5
value: 36.766
- type: precision_at_1
value: 56.99999999999999
- type: precision_at_10
value: 28.175
- type: precision_at_100
value: 9.423
- type: precision_at_1000
value: 2.017
- type: precision_at_3
value: 41.667
- type: precision_at_5
value: 35.199999999999996
- type: recall_at_1
value: 7.786999999999999
- type: recall_at_10
value: 21.428
- type: recall_at_100
value: 45.86
- type: recall_at_1000
value: 68.83
- type: recall_at_3
value: 12.992
- type: recall_at_5
value: 16.091
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 45.985
- type: f1
value: 39.52034839578244
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.141999999999996
- type: map_at_10
value: 50.255
- type: map_at_100
value: 50.938
- type: map_at_1000
value: 50.975
- type: map_at_3
value: 47.4
- type: map_at_5
value: 49.172
- type: mrr_at_1
value: 41.794
- type: mrr_at_10
value: 53.198
- type: mrr_at_100
value: 53.82900000000001
- type: mrr_at_1000
value: 53.857
- type: mrr_at_3
value: 50.32
- type: mrr_at_5
value: 52.105999999999995
- type: ndcg_at_1
value: 41.794
- type: ndcg_at_10
value: 56.411
- type: ndcg_at_100
value: 59.663
- type: ndcg_at_1000
value: 60.590999999999994
- type: ndcg_at_3
value: 50.73
- type: ndcg_at_5
value: 53.823
- type: precision_at_1
value: 41.794
- type: precision_at_10
value: 7.9159999999999995
- type: precision_at_100
value: 0.968
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 20.627000000000002
- type: precision_at_5
value: 14.038
- type: recall_at_1
value: 39.141999999999996
- type: recall_at_10
value: 72.695
- type: recall_at_100
value: 87.44800000000001
- type: recall_at_1000
value: 94.313
- type: recall_at_3
value: 57.415000000000006
- type: recall_at_5
value: 64.851
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.715
- type: map_at_10
value: 30.253999999999998
- type: map_at_100
value: 32.123000000000005
- type: map_at_1000
value: 32.303
- type: map_at_3
value: 26.203
- type: map_at_5
value: 28.585
- type: mrr_at_1
value: 36.42
- type: mrr_at_10
value: 45.456
- type: mrr_at_100
value: 46.314
- type: mrr_at_1000
value: 46.356
- type: mrr_at_3
value: 42.798
- type: mrr_at_5
value: 44.365
- type: ndcg_at_1
value: 36.42
- type: ndcg_at_10
value: 37.747
- type: ndcg_at_100
value: 44.714999999999996
- type: ndcg_at_1000
value: 47.866
- type: ndcg_at_3
value: 34.166999999999994
- type: ndcg_at_5
value: 35.54
- type: precision_at_1
value: 36.42
- type: precision_at_10
value: 10.602
- type: precision_at_100
value: 1.773
- type: precision_at_1000
value: 0.234
- type: precision_at_3
value: 22.84
- type: precision_at_5
value: 17.315
- type: recall_at_1
value: 18.715
- type: recall_at_10
value: 44.199
- type: recall_at_100
value: 70.097
- type: recall_at_1000
value: 89.13600000000001
- type: recall_at_3
value: 30.543
- type: recall_at_5
value: 36.705
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.608
- type: map_at_10
value: 45.829
- type: map_at_100
value: 46.786
- type: map_at_1000
value: 46.869
- type: map_at_3
value: 42.834
- type: map_at_5
value: 44.566
- type: mrr_at_1
value: 61.214999999999996
- type: mrr_at_10
value: 69.072
- type: mrr_at_100
value: 69.492
- type: mrr_at_1000
value: 69.512
- type: mrr_at_3
value: 67.553
- type: mrr_at_5
value: 68.446
- type: ndcg_at_1
value: 61.214999999999996
- type: ndcg_at_10
value: 54.66
- type: ndcg_at_100
value: 58.342000000000006
- type: ndcg_at_1000
value: 60.101000000000006
- type: ndcg_at_3
value: 49.932
- type: ndcg_at_5
value: 52.342999999999996
- type: precision_at_1
value: 61.214999999999996
- type: precision_at_10
value: 11.65
- type: precision_at_100
value: 1.4529999999999998
- type: precision_at_1000
value: 0.169
- type: precision_at_3
value: 31.78
- type: precision_at_5
value: 20.979999999999997
- type: recall_at_1
value: 30.608
- type: recall_at_10
value: 58.251
- type: recall_at_100
value: 72.667
- type: recall_at_1000
value: 84.396
- type: recall_at_3
value: 47.67
- type: recall_at_5
value: 52.451
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 90.21999999999998
- type: ap
value: 85.88889163834975
- type: f1
value: 90.20542534971861
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 19.785
- type: map_at_10
value: 31.596000000000004
- type: map_at_100
value: 32.849000000000004
- type: map_at_1000
value: 32.903999999999996
- type: map_at_3
value: 27.772000000000002
- type: map_at_5
value: 29.952
- type: mrr_at_1
value: 20.344
- type: mrr_at_10
value: 32.146
- type: mrr_at_100
value: 33.349000000000004
- type: mrr_at_1000
value: 33.396
- type: mrr_at_3
value: 28.403
- type: mrr_at_5
value: 30.542
- type: ndcg_at_1
value: 20.358
- type: ndcg_at_10
value: 38.288
- type: ndcg_at_100
value: 44.383
- type: ndcg_at_1000
value: 45.714
- type: ndcg_at_3
value: 30.525999999999996
- type: ndcg_at_5
value: 34.393
- type: precision_at_1
value: 20.358
- type: precision_at_10
value: 6.16
- type: precision_at_100
value: 0.9209999999999999
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 13.08
- type: precision_at_5
value: 9.799
- type: recall_at_1
value: 19.785
- type: recall_at_10
value: 58.916000000000004
- type: recall_at_100
value: 87.24
- type: recall_at_1000
value: 97.37599999999999
- type: recall_at_3
value: 37.872
- type: recall_at_5
value: 47.116
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 88.63429092567262
- type: f1
value: 88.58612904162257
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 58.080255357957135
- type: f1
value: 39.561402859935
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 65.03026227303296
- type: f1
value: 61.10334739098155
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 71.05245460659046
- type: f1
value: 69.96280851244295
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 33.9762359299763
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 31.670044418802444
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.32330726926572
- type: mrr
value: 30.16727607430052
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.552
- type: map_at_10
value: 10.692
- type: map_at_100
value: 13.835
- type: map_at_1000
value: 15.305
- type: map_at_3
value: 7.5009999999999994
- type: map_at_5
value: 8.988
- type: mrr_at_1
value: 39.318999999999996
- type: mrr_at_10
value: 48.809000000000005
- type: mrr_at_100
value: 49.382
- type: mrr_at_1000
value: 49.442
- type: mrr_at_3
value: 46.078
- type: mrr_at_5
value: 48.091
- type: ndcg_at_1
value: 37.152
- type: ndcg_at_10
value: 30.159000000000002
- type: ndcg_at_100
value: 28.371000000000002
- type: ndcg_at_1000
value: 37.632
- type: ndcg_at_3
value: 34.662
- type: ndcg_at_5
value: 32.814
- type: precision_at_1
value: 38.7
- type: precision_at_10
value: 23.034
- type: precision_at_100
value: 7.588
- type: precision_at_1000
value: 2.0709999999999997
- type: precision_at_3
value: 33.024
- type: precision_at_5
value: 29.164
- type: recall_at_1
value: 4.552
- type: recall_at_10
value: 14.827000000000002
- type: recall_at_100
value: 29.256
- type: recall_at_1000
value: 61.739
- type: recall_at_3
value: 8.38
- type: recall_at_5
value: 11.123
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.424999999999997
- type: map_at_10
value: 39.972
- type: map_at_100
value: 41.163
- type: map_at_1000
value: 41.202
- type: map_at_3
value: 35.546
- type: map_at_5
value: 38.146
- type: mrr_at_1
value: 28.794999999999998
- type: mrr_at_10
value: 42.315999999999995
- type: mrr_at_100
value: 43.253
- type: mrr_at_1000
value: 43.282
- type: mrr_at_3
value: 38.649
- type: mrr_at_5
value: 40.858
- type: ndcg_at_1
value: 28.766000000000002
- type: ndcg_at_10
value: 47.614000000000004
- type: ndcg_at_100
value: 52.676
- type: ndcg_at_1000
value: 53.574
- type: ndcg_at_3
value: 39.292
- type: ndcg_at_5
value: 43.633
- type: precision_at_1
value: 28.766000000000002
- type: precision_at_10
value: 8.201
- type: precision_at_100
value: 1.099
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 18.201999999999998
- type: precision_at_5
value: 13.447000000000001
- type: recall_at_1
value: 25.424999999999997
- type: recall_at_10
value: 68.586
- type: recall_at_100
value: 90.556
- type: recall_at_1000
value: 97.197
- type: recall_at_3
value: 47.033
- type: recall_at_5
value: 57.044
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 70.054
- type: map_at_10
value: 83.991
- type: map_at_100
value: 84.63000000000001
- type: map_at_1000
value: 84.648
- type: map_at_3
value: 80.982
- type: map_at_5
value: 82.857
- type: mrr_at_1
value: 80.76
- type: mrr_at_10
value: 87.079
- type: mrr_at_100
value: 87.185
- type: mrr_at_1000
value: 87.18599999999999
- type: mrr_at_3
value: 86.03
- type: mrr_at_5
value: 86.771
- type: ndcg_at_1
value: 80.75
- type: ndcg_at_10
value: 87.85300000000001
- type: ndcg_at_100
value: 89.105
- type: ndcg_at_1000
value: 89.213
- type: ndcg_at_3
value: 84.87400000000001
- type: ndcg_at_5
value: 86.51299999999999
- type: precision_at_1
value: 80.75
- type: precision_at_10
value: 13.352
- type: precision_at_100
value: 1.528
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.113
- type: precision_at_5
value: 24.424
- type: recall_at_1
value: 70.054
- type: recall_at_10
value: 95.209
- type: recall_at_100
value: 99.497
- type: recall_at_1000
value: 99.973
- type: recall_at_3
value: 86.654
- type: recall_at_5
value: 91.313
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 42.71909082787674
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 56.92567540870805
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.225
- type: map_at_10
value: 5.785
- type: map_at_100
value: 7.6240000000000006
- type: map_at_1000
value: 8.094999999999999
- type: map_at_3
value: 3.882
- type: map_at_5
value: 4.715
- type: mrr_at_1
value: 11
- type: mrr_at_10
value: 18.049
- type: mrr_at_100
value: 19.475
- type: mrr_at_1000
value: 19.599
- type: mrr_at_3
value: 15.082999999999998
- type: mrr_at_5
value: 16.583000000000002
- type: ndcg_at_1
value: 11
- type: ndcg_at_10
value: 10.59
- type: ndcg_at_100
value: 18.68
- type: ndcg_at_1000
value: 27.327
- type: ndcg_at_3
value: 8.932
- type: ndcg_at_5
value: 8.126
- type: precision_at_1
value: 11
- type: precision_at_10
value: 5.89
- type: precision_at_100
value: 1.778
- type: precision_at_1000
value: 0.385
- type: precision_at_3
value: 8.333
- type: precision_at_5
value: 7.3
- type: recall_at_1
value: 2.225
- type: recall_at_10
value: 11.948
- type: recall_at_100
value: 36.097
- type: recall_at_1000
value: 78.145
- type: recall_at_3
value: 5.078
- type: recall_at_5
value: 7.4079999999999995
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 83.87898494199837
- type: cos_sim_spearman
value: 79.3815141247343
- type: euclidean_pearson
value: 80.984944764735
- type: euclidean_spearman
value: 79.37984688714191
- type: manhattan_pearson
value: 80.96139326762788
- type: manhattan_spearman
value: 79.34882764221987
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 82.94123934276303
- type: cos_sim_spearman
value: 73.64821774752144
- type: euclidean_pearson
value: 79.09149672589201
- type: euclidean_spearman
value: 73.64174833442063
- type: manhattan_pearson
value: 79.05135129686983
- type: manhattan_spearman
value: 73.57858840270084
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 71.37047316191514
- type: cos_sim_spearman
value: 75.56797051373606
- type: euclidean_pearson
value: 74.59038333631109
- type: euclidean_spearman
value: 75.55966023907652
- type: manhattan_pearson
value: 74.56600039917967
- type: manhattan_spearman
value: 75.52139454559969
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 71.75410054949431
- type: cos_sim_spearman
value: 72.09826786050286
- type: euclidean_pearson
value: 72.30015801748517
- type: euclidean_spearman
value: 72.09347126863909
- type: manhattan_pearson
value: 72.2692656804079
- type: manhattan_spearman
value: 72.07403601010577
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 83.09663528706463
- type: cos_sim_spearman
value: 85.6296813586495
- type: euclidean_pearson
value: 84.14347920777777
- type: euclidean_spearman
value: 85.62948425849926
- type: manhattan_pearson
value: 84.08840896634038
- type: manhattan_spearman
value: 85.56264430897471
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 78.55984417539631
- type: cos_sim_spearman
value: 82.06700938579174
- type: euclidean_pearson
value: 80.92277218507344
- type: euclidean_spearman
value: 82.06297899287695
- type: manhattan_pearson
value: 80.89292734584946
- type: manhattan_spearman
value: 82.01121177547141
- 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: 88.70738419575085
- type: cos_sim_spearman
value: 88.99910283221313
- type: euclidean_pearson
value: 88.91458218447116
- type: euclidean_spearman
value: 88.97188755639708
- type: manhattan_pearson
value: 88.93397958768632
- type: manhattan_spearman
value: 89.0514960821245
- 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: 65.30101408630514
- type: cos_sim_spearman
value: 66.15672143838582
- type: euclidean_pearson
value: 66.61257552376895
- type: euclidean_spearman
value: 66.00319920690566
- type: manhattan_pearson
value: 66.81435622246758
- type: manhattan_spearman
value: 66.35221377631379
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 81.94191078286725
- type: cos_sim_spearman
value: 83.69085688689903
- type: euclidean_pearson
value: 83.28942607749994
- type: euclidean_spearman
value: 83.69370814043747
- type: manhattan_pearson
value: 83.3553242227074
- type: manhattan_spearman
value: 83.74306572840383
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 88.02503921524934
- type: mrr
value: 96.47891777793738
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 51.24999999999999
- type: map_at_10
value: 61.472
- type: map_at_100
value: 62.132
- type: map_at_1000
value: 62.161
- type: map_at_3
value: 58.18299999999999
- type: map_at_5
value: 60.246
- type: mrr_at_1
value: 54
- type: mrr_at_10
value: 62.395
- type: mrr_at_100
value: 62.936
- type: mrr_at_1000
value: 62.965
- type: mrr_at_3
value: 59.833000000000006
- type: mrr_at_5
value: 61.5
- type: ndcg_at_1
value: 54
- type: ndcg_at_10
value: 66.235
- type: ndcg_at_100
value: 69.279
- type: ndcg_at_1000
value: 70.044
- type: ndcg_at_3
value: 60.679
- type: ndcg_at_5
value: 63.80200000000001
- type: precision_at_1
value: 54
- type: precision_at_10
value: 9.167
- type: precision_at_100
value: 1.0699999999999998
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 24.111
- type: precision_at_5
value: 16.333000000000002
- type: recall_at_1
value: 51.24999999999999
- type: recall_at_10
value: 79.833
- type: recall_at_100
value: 94
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 65.267
- type: recall_at_5
value: 72.956
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.62673267326733
- type: cos_sim_ap
value: 87.07482534376774
- type: cos_sim_f1
value: 80.63687724704674
- type: cos_sim_precision
value: 82.89334741288279
- type: cos_sim_recall
value: 78.5
- type: dot_accuracy
value: 99.63564356435643
- type: dot_ap
value: 86.98432756163903
- type: dot_f1
value: 80.91286307053943
- type: dot_precision
value: 84.05172413793103
- type: dot_recall
value: 78
- type: euclidean_accuracy
value: 99.62673267326733
- type: euclidean_ap
value: 87.0756316041764
- type: euclidean_f1
value: 80.53553038105046
- type: euclidean_precision
value: 83.01486199575372
- type: euclidean_recall
value: 78.2
- type: manhattan_accuracy
value: 99.62574257425743
- type: manhattan_ap
value: 87.05953308523233
- type: manhattan_f1
value: 80.50632911392405
- type: manhattan_precision
value: 81.53846153846153
- type: manhattan_recall
value: 79.5
- type: max_accuracy
value: 99.63564356435643
- type: max_ap
value: 87.0756316041764
- type: max_f1
value: 80.91286307053943
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 53.59692640735744
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 32.86771187657918
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 45.705711066037644
- type: mrr
value: 46.25163133435192
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.066382997227624
- type: cos_sim_spearman
value: 31.00934876843689
- type: dot_pearson
value: 30.419206995727873
- type: dot_spearman
value: 31.046571150093747
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.173
- type: map_at_10
value: 1.154
- type: map_at_100
value: 5.8180000000000005
- type: map_at_1000
value: 14.892
- type: map_at_3
value: 0.415
- type: map_at_5
value: 0.641
- type: mrr_at_1
value: 68
- type: mrr_at_10
value: 76.869
- type: mrr_at_100
value: 77.264
- type: mrr_at_1000
value: 77.264
- type: mrr_at_3
value: 75.333
- type: mrr_at_5
value: 76.333
- type: ndcg_at_1
value: 62
- type: ndcg_at_10
value: 50.81
- type: ndcg_at_100
value: 37.659
- type: ndcg_at_1000
value: 37.444
- type: ndcg_at_3
value: 55.11200000000001
- type: ndcg_at_5
value: 51.858000000000004
- type: precision_at_1
value: 68
- type: precision_at_10
value: 54.800000000000004
- type: precision_at_100
value: 38.36
- type: precision_at_1000
value: 16.88
- type: precision_at_3
value: 57.99999999999999
- type: precision_at_5
value: 54.800000000000004
- type: recall_at_1
value: 0.173
- type: recall_at_10
value: 1.435
- type: recall_at_100
value: 9.259
- type: recall_at_1000
value: 36.033
- type: recall_at_3
value: 0.447
- type: recall_at_5
value: 0.74
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.228
- type: map_at_10
value: 4.633
- type: map_at_100
value: 9.171
- type: map_at_1000
value: 10.58
- type: map_at_3
value: 2.413
- type: map_at_5
value: 3.3640000000000003
- type: mrr_at_1
value: 16.326999999999998
- type: mrr_at_10
value: 27.071
- type: mrr_at_100
value: 28.454
- type: mrr_at_1000
value: 28.475
- type: mrr_at_3
value: 19.048000000000002
- type: mrr_at_5
value: 24.354
- type: ndcg_at_1
value: 14.285999999999998
- type: ndcg_at_10
value: 13.312
- type: ndcg_at_100
value: 25.587
- type: ndcg_at_1000
value: 37.879000000000005
- type: ndcg_at_3
value: 11.591
- type: ndcg_at_5
value: 12.536
- type: precision_at_1
value: 16.326999999999998
- type: precision_at_10
value: 13.264999999999999
- type: precision_at_100
value: 6.061
- type: precision_at_1000
value: 1.4040000000000001
- type: precision_at_3
value: 12.245000000000001
- type: precision_at_5
value: 13.877999999999998
- type: recall_at_1
value: 1.228
- type: recall_at_10
value: 9.759
- type: recall_at_100
value: 38.809
- type: recall_at_1000
value: 76.229
- type: recall_at_3
value: 2.738
- type: recall_at_5
value: 5.510000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 69.33179999999999
- type: ap
value: 14.379598043710034
- type: f1
value: 53.89665138084001
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 58.245614035087726
- type: f1
value: 58.3152945231724
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 38.38161204174159
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 82.60118018716099
- type: cos_sim_ap
value: 62.5064927795416
- type: cos_sim_f1
value: 59.50177935943061
- type: cos_sim_precision
value: 54.05172413793103
- type: cos_sim_recall
value: 66.17414248021109
- type: dot_accuracy
value: 82.52369315133814
- type: dot_ap
value: 62.36545569178682
- type: dot_f1
value: 59.5539204414808
- type: dot_precision
value: 52.77098614506927
- type: dot_recall
value: 68.33773087071239
- type: euclidean_accuracy
value: 82.62502235202956
- type: euclidean_ap
value: 62.51708062651598
- type: euclidean_f1
value: 59.48887837198297
- type: euclidean_precision
value: 53.925353925353924
- type: euclidean_recall
value: 66.33245382585751
- type: manhattan_accuracy
value: 82.57733802229242
- type: manhattan_ap
value: 62.4034159268756
- type: manhattan_f1
value: 59.42896615242921
- type: manhattan_precision
value: 52.716503267973856
- type: manhattan_recall
value: 68.10026385224275
- type: max_accuracy
value: 82.62502235202956
- type: max_ap
value: 62.51708062651598
- type: max_f1
value: 59.5539204414808
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 86.74079248651377
- type: cos_sim_ap
value: 81.11128912769627
- type: cos_sim_f1
value: 73.39903296054331
- type: cos_sim_precision
value: 70.49273307337823
- type: cos_sim_recall
value: 76.55528179858331
- type: dot_accuracy
value: 86.71362595567975
- type: dot_ap
value: 81.07587927324371
- type: dot_f1
value: 73.36112443280334
- type: dot_precision
value: 70.42283447836249
- type: dot_recall
value: 76.55528179858331
- type: euclidean_accuracy
value: 86.73109015407304
- type: euclidean_ap
value: 81.11249921439843
- type: euclidean_f1
value: 73.39903296054331
- type: euclidean_precision
value: 70.49273307337823
- type: euclidean_recall
value: 76.55528179858331
- type: manhattan_accuracy
value: 86.7252687546086
- type: manhattan_ap
value: 81.05990290681223
- type: manhattan_f1
value: 73.29173525245952
- type: manhattan_precision
value: 72.88161400837457
- type: manhattan_recall
value: 73.70649830612874
- type: max_accuracy
value: 86.74079248651377
- type: max_ap
value: 81.11249921439843
- type: max_f1
value: 73.39903296054331