metadata
tags:
- mteb
model-index:
- name: bge_finetuned
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 61.64179104477612
- type: ap
value: 25.20497978200253
- type: f1
value: 55.51169205110252
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 58.6114
- type: ap
value: 55.013881977883706
- type: f1
value: 58.0798269108889
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 27.009999999999994
- type: f1
value: 26.230644551993027
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.011000000000001
- type: map_at_10
value: 24.082
- type: map_at_100
value: 25.273
- type: map_at_1000
value: 25.336
- type: map_at_3
value: 20.341
- type: map_at_5
value: 22.155
- type: mrr_at_1
value: 14.651
- type: mrr_at_10
value: 24.306
- type: mrr_at_100
value: 25.503999999999998
- type: mrr_at_1000
value: 25.566
- type: mrr_at_3
value: 20.59
- type: mrr_at_5
value: 22.400000000000002
- type: ndcg_at_1
value: 14.011000000000001
- type: ndcg_at_10
value: 30.316
- type: ndcg_at_100
value: 36.146
- type: ndcg_at_1000
value: 37.972
- type: ndcg_at_3
value: 22.422
- type: ndcg_at_5
value: 25.727
- type: precision_at_1
value: 14.011000000000001
- type: precision_at_10
value: 5.0569999999999995
- type: precision_at_100
value: 0.7799999999999999
- type: precision_at_1000
value: 0.093
- type: precision_at_3
value: 9.483
- type: precision_at_5
value: 7.312
- type: recall_at_1
value: 14.011000000000001
- type: recall_at_10
value: 50.568999999999996
- type: recall_at_100
value: 77.952
- type: recall_at_1000
value: 92.674
- type: recall_at_3
value: 28.449999999999996
- type: recall_at_5
value: 36.558
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 21.580787107217457
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 12.755947651867459
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 50.36895415359604
- type: mrr
value: 62.93244075100032
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 54.84190098866484
- type: cos_sim_spearman
value: 52.065644182348144
- type: euclidean_pearson
value: 54.181073661388034
- type: euclidean_spearman
value: 52.065644182348144
- type: manhattan_pearson
value: 54.98368207013862
- type: manhattan_spearman
value: 53.66387337016872
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 63.48051948051948
- type: f1
value: 61.45740352513437
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 16.23123129183937
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 6.846095550717324
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.587
- type: map_at_10
value: 20.032
- type: map_at_100
value: 21.2
- type: map_at_1000
value: 21.351
- type: map_at_3
value: 18.224
- type: map_at_5
value: 19.028
- type: mrr_at_1
value: 18.312
- type: mrr_at_10
value: 24.343999999999998
- type: mrr_at_100
value: 25.302000000000003
- type: mrr_at_1000
value: 25.385
- type: mrr_at_3
value: 22.461000000000002
- type: mrr_at_5
value: 23.219
- type: ndcg_at_1
value: 18.312
- type: ndcg_at_10
value: 24.05
- type: ndcg_at_100
value: 29.512
- type: ndcg_at_1000
value: 33.028999999999996
- type: ndcg_at_3
value: 20.947
- type: ndcg_at_5
value: 21.807000000000002
- type: precision_at_1
value: 18.312
- type: precision_at_10
value: 4.664
- type: precision_at_100
value: 0.9570000000000001
- type: precision_at_1000
value: 0.155
- type: precision_at_3
value: 10.11
- type: precision_at_5
value: 7.066999999999999
- type: recall_at_1
value: 14.587
- type: recall_at_10
value: 31.865
- type: recall_at_100
value: 55.922000000000004
- type: recall_at_1000
value: 80.878
- type: recall_at_3
value: 22.229
- type: recall_at_5
value: 25.09
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.456
- type: map_at_10
value: 11.429
- type: map_at_100
value: 11.956
- type: map_at_1000
value: 12.04
- type: map_at_3
value: 10.309
- type: map_at_5
value: 11.006
- type: mrr_at_1
value: 10.637
- type: mrr_at_10
value: 14.047
- type: mrr_at_100
value: 14.591999999999999
- type: mrr_at_1000
value: 14.66
- type: mrr_at_3
value: 12.876999999999999
- type: mrr_at_5
value: 13.644
- type: ndcg_at_1
value: 10.637
- type: ndcg_at_10
value: 13.623
- type: ndcg_at_100
value: 16.337
- type: ndcg_at_1000
value: 18.881
- type: ndcg_at_3
value: 11.76
- type: ndcg_at_5
value: 12.803
- type: precision_at_1
value: 10.637
- type: precision_at_10
value: 2.611
- type: precision_at_100
value: 0.49899999999999994
- type: precision_at_1000
value: 0.08800000000000001
- type: precision_at_3
value: 5.7540000000000004
- type: precision_at_5
value: 4.306
- type: recall_at_1
value: 8.456
- type: recall_at_10
value: 17.543
- type: recall_at_100
value: 29.696
- type: recall_at_1000
value: 48.433
- type: recall_at_3
value: 12.299
- type: recall_at_5
value: 15.126000000000001
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.517999999999999
- type: map_at_10
value: 14.924999999999999
- type: map_at_100
value: 15.716
- type: map_at_1000
value: 15.804000000000002
- type: map_at_3
value: 13.228000000000002
- type: map_at_5
value: 14.155999999999999
- type: mrr_at_1
value: 12.790000000000001
- type: mrr_at_10
value: 17.122999999999998
- type: mrr_at_100
value: 17.874000000000002
- type: mrr_at_1000
value: 17.947
- type: mrr_at_3
value: 15.528
- type: mrr_at_5
value: 16.421
- type: ndcg_at_1
value: 12.790000000000001
- type: ndcg_at_10
value: 17.967
- type: ndcg_at_100
value: 22.016
- type: ndcg_at_1000
value: 24.57
- type: ndcg_at_3
value: 14.745
- type: ndcg_at_5
value: 16.247
- type: precision_at_1
value: 12.790000000000001
- type: precision_at_10
value: 3.229
- type: precision_at_100
value: 0.592
- type: precision_at_1000
value: 0.087
- type: precision_at_3
value: 6.792
- type: precision_at_5
value: 5.066
- type: recall_at_1
value: 10.517999999999999
- type: recall_at_10
value: 25.194
- type: recall_at_100
value: 43.858999999999995
- type: recall_at_1000
value: 63.410999999999994
- type: recall_at_3
value: 16.384999999999998
- type: recall_at_5
value: 20.09
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.325000000000001
- type: map_at_10
value: 12.262
- type: map_at_100
value: 13.003
- type: map_at_1000
value: 13.126999999999999
- type: map_at_3
value: 10.946
- type: map_at_5
value: 11.581
- type: mrr_at_1
value: 9.379
- type: mrr_at_10
value: 13.527000000000001
- type: mrr_at_100
value: 14.249999999999998
- type: mrr_at_1000
value: 14.365
- type: mrr_at_3
value: 12.166
- type: mrr_at_5
value: 12.798000000000002
- type: ndcg_at_1
value: 9.379
- type: ndcg_at_10
value: 14.878
- type: ndcg_at_100
value: 19.17
- type: ndcg_at_1000
value: 22.861
- type: ndcg_at_3
value: 12.136
- type: ndcg_at_5
value: 13.209000000000001
- type: precision_at_1
value: 9.379
- type: precision_at_10
value: 2.5309999999999997
- type: precision_at_100
value: 0.505
- type: precision_at_1000
value: 0.086
- type: precision_at_3
value: 5.386
- type: precision_at_5
value: 3.887
- type: recall_at_1
value: 8.325000000000001
- type: recall_at_10
value: 21.886
- type: recall_at_100
value: 42.977
- type: recall_at_1000
value: 71.946
- type: recall_at_3
value: 14.123
- type: recall_at_5
value: 16.747
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.982
- type: map_at_10
value: 9.249
- type: map_at_100
value: 10
- type: map_at_1000
value: 10.127
- type: map_at_3
value: 7.913
- type: map_at_5
value: 8.540000000000001
- type: mrr_at_1
value: 7.960000000000001
- type: mrr_at_10
value: 11.703
- type: mrr_at_100
value: 12.43
- type: mrr_at_1000
value: 12.534999999999998
- type: mrr_at_3
value: 10.344000000000001
- type: mrr_at_5
value: 11.022
- type: ndcg_at_1
value: 7.960000000000001
- type: ndcg_at_10
value: 11.863
- type: ndcg_at_100
value: 16.086
- type: ndcg_at_1000
value: 19.738
- type: ndcg_at_3
value: 9.241000000000001
- type: ndcg_at_5
value: 10.228
- type: precision_at_1
value: 7.960000000000001
- type: precision_at_10
value: 2.4
- type: precision_at_100
value: 0.534
- type: precision_at_1000
value: 0.097
- type: precision_at_3
value: 4.561
- type: precision_at_5
value: 3.408
- type: recall_at_1
value: 5.982
- type: recall_at_10
value: 17.669999999999998
- type: recall_at_100
value: 37.261
- type: recall_at_1000
value: 64.416
- type: recall_at_3
value: 10.376000000000001
- type: recall_at_5
value: 12.933
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.068
- type: map_at_10
value: 12.101
- type: map_at_100
value: 12.828000000000001
- type: map_at_1000
value: 12.953000000000001
- type: map_at_3
value: 11.047
- type: map_at_5
value: 11.542
- type: mrr_at_1
value: 10.972
- type: mrr_at_10
value: 14.873
- type: mrr_at_100
value: 15.584000000000001
- type: mrr_at_1000
value: 15.681999999999999
- type: mrr_at_3
value: 13.523
- type: mrr_at_5
value: 14.254
- type: ndcg_at_1
value: 10.972
- type: ndcg_at_10
value: 14.557999999999998
- type: ndcg_at_100
value: 18.56
- type: ndcg_at_1000
value: 21.975
- type: ndcg_at_3
value: 12.436
- type: ndcg_at_5
value: 13.270999999999999
- type: precision_at_1
value: 10.972
- type: precision_at_10
value: 2.714
- type: precision_at_100
value: 0.5720000000000001
- type: precision_at_1000
value: 0.10200000000000001
- type: precision_at_3
value: 5.711
- type: precision_at_5
value: 4.1579999999999995
- type: recall_at_1
value: 9.068
- type: recall_at_10
value: 19.381999999999998
- type: recall_at_100
value: 37.602999999999994
- type: recall_at_1000
value: 62.376
- type: recall_at_3
value: 13.48
- type: recall_at_5
value: 15.506
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.206
- type: map_at_10
value: 12.032
- type: map_at_100
value: 12.992
- type: map_at_1000
value: 13.135
- type: map_at_3
value: 10.741
- type: map_at_5
value: 11.392
- type: mrr_at_1
value: 10.502
- type: mrr_at_10
value: 14.818999999999999
- type: mrr_at_100
value: 15.716
- type: mrr_at_1000
value: 15.823
- type: mrr_at_3
value: 13.375
- type: mrr_at_5
value: 14.169
- type: ndcg_at_1
value: 10.502
- type: ndcg_at_10
value: 14.790000000000001
- type: ndcg_at_100
value: 19.881999999999998
- type: ndcg_at_1000
value: 23.703
- type: ndcg_at_3
value: 12.281
- type: ndcg_at_5
value: 13.33
- type: precision_at_1
value: 10.502
- type: precision_at_10
value: 2.911
- type: precision_at_100
value: 0.668
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 6.012
- type: precision_at_5
value: 4.475
- type: recall_at_1
value: 8.206
- type: recall_at_10
value: 20.508000000000003
- type: recall_at_100
value: 43.568
- type: recall_at_1000
value: 71.56400000000001
- type: recall_at_3
value: 13.607
- type: recall_at_5
value: 16.211000000000002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 6.4159999999999995
- type: map_at_10
value: 9.581000000000001
- type: map_at_100
value: 10.123999999999999
- type: map_at_1000
value: 10.226
- type: map_at_3
value: 8.51
- type: map_at_5
value: 9.078999999999999
- type: mrr_at_1
value: 7.515
- type: mrr_at_10
value: 10.801
- type: mrr_at_100
value: 11.373
- type: mrr_at_1000
value: 11.466999999999999
- type: mrr_at_3
value: 9.637
- type: mrr_at_5
value: 10.197000000000001
- type: ndcg_at_1
value: 7.515
- type: ndcg_at_10
value: 11.776
- type: ndcg_at_100
value: 14.776
- type: ndcg_at_1000
value: 17.7
- type: ndcg_at_3
value: 9.515
- type: ndcg_at_5
value: 10.511
- type: precision_at_1
value: 7.515
- type: precision_at_10
value: 2.086
- type: precision_at_100
value: 0.402
- type: precision_at_1000
value: 0.07100000000000001
- type: precision_at_3
value: 4.397
- type: precision_at_5
value: 3.19
- type: recall_at_1
value: 6.4159999999999995
- type: recall_at_10
value: 17.468
- type: recall_at_100
value: 31.398
- type: recall_at_1000
value: 53.686
- type: recall_at_3
value: 11.379999999999999
- type: recall_at_5
value: 13.745
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.646
- type: map_at_10
value: 7.047000000000001
- type: map_at_100
value: 7.697
- type: map_at_1000
value: 7.806
- type: map_at_3
value: 6.258
- type: map_at_5
value: 6.628
- type: mrr_at_1
value: 5.919
- type: mrr_at_10
value: 8.767999999999999
- type: mrr_at_100
value: 9.434
- type: mrr_at_1000
value: 9.524000000000001
- type: mrr_at_3
value: 7.8
- type: mrr_at_5
value: 8.275
- type: ndcg_at_1
value: 5.919
- type: ndcg_at_10
value: 8.927999999999999
- type: ndcg_at_100
value: 12.467
- type: ndcg_at_1000
value: 15.674
- type: ndcg_at_3
value: 7.3260000000000005
- type: ndcg_at_5
value: 7.931000000000001
- type: precision_at_1
value: 5.919
- type: precision_at_10
value: 1.7760000000000002
- type: precision_at_100
value: 0.438
- type: precision_at_1000
value: 0.086
- type: precision_at_3
value: 3.6249999999999996
- type: precision_at_5
value: 2.657
- type: recall_at_1
value: 4.646
- type: recall_at_10
value: 12.973
- type: recall_at_100
value: 29.444
- type: recall_at_1000
value: 53.413999999999994
- type: recall_at_3
value: 8.378
- type: recall_at_5
value: 9.957
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.202
- type: map_at_10
value: 13.402
- type: map_at_100
value: 14.330000000000002
- type: map_at_1000
value: 14.455000000000002
- type: map_at_3
value: 11.916
- type: map_at_5
value: 12.828000000000001
- type: mrr_at_1
value: 10.634
- type: mrr_at_10
value: 15.528
- type: mrr_at_100
value: 16.393
- type: mrr_at_1000
value: 16.497999999999998
- type: mrr_at_3
value: 13.837
- type: mrr_at_5
value: 14.821000000000002
- type: ndcg_at_1
value: 10.634
- type: ndcg_at_10
value: 16.267
- type: ndcg_at_100
value: 21.149
- type: ndcg_at_1000
value: 24.509
- type: ndcg_at_3
value: 13.320000000000002
- type: ndcg_at_5
value: 14.857000000000001
- type: precision_at_1
value: 10.634
- type: precision_at_10
value: 2.948
- type: precision_at_100
value: 0.618
- type: precision_at_1000
value: 0.10200000000000001
- type: precision_at_3
value: 6.188
- type: precision_at_5
value: 4.7010000000000005
- type: recall_at_1
value: 9.202
- type: recall_at_10
value: 22.921
- type: recall_at_100
value: 45.292
- type: recall_at_1000
value: 69.853
- type: recall_at_3
value: 15.126000000000001
- type: recall_at_5
value: 18.863
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 11.278
- type: map_at_10
value: 15.72
- type: map_at_100
value: 16.832
- type: map_at_1000
value: 17.025000000000002
- type: map_at_3
value: 13.852999999999998
- type: map_at_5
value: 14.654
- type: mrr_at_1
value: 14.822
- type: mrr_at_10
value: 19.564
- type: mrr_at_100
value: 20.509
- type: mrr_at_1000
value: 20.607
- type: mrr_at_3
value: 17.721
- type: mrr_at_5
value: 18.451999999999998
- type: ndcg_at_1
value: 14.822
- type: ndcg_at_10
value: 19.548
- type: ndcg_at_100
value: 24.734
- type: ndcg_at_1000
value: 28.832
- type: ndcg_at_3
value: 16.14
- type: ndcg_at_5
value: 17.253
- type: precision_at_1
value: 14.822
- type: precision_at_10
value: 3.972
- type: precision_at_100
value: 0.943
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 7.642
- type: precision_at_5
value: 5.6129999999999995
- type: recall_at_1
value: 11.278
- type: recall_at_10
value: 27.006999999999998
- type: recall_at_100
value: 51.012
- type: recall_at_1000
value: 79.833
- type: recall_at_3
value: 16.785
- type: recall_at_5
value: 19.82
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.305
- type: map_at_10
value: 9.099
- type: map_at_100
value: 9.927999999999999
- type: map_at_1000
value: 10.027
- type: map_at_3
value: 7.7700000000000005
- type: map_at_5
value: 8.333
- type: mrr_at_1
value: 6.1
- type: mrr_at_10
value: 10.227
- type: mrr_at_100
value: 11.057
- type: mrr_at_1000
value: 11.151
- type: mrr_at_3
value: 8.842
- type: mrr_at_5
value: 9.442
- type: ndcg_at_1
value: 6.1
- type: ndcg_at_10
value: 11.769
- type: ndcg_at_100
value: 16.378999999999998
- type: ndcg_at_1000
value: 19.517
- type: ndcg_at_3
value: 8.936
- type: ndcg_at_5
value: 9.907
- type: precision_at_1
value: 6.1
- type: precision_at_10
value: 2.181
- type: precision_at_100
value: 0.481
- type: precision_at_1000
value: 0.08099999999999999
- type: precision_at_3
value: 4.19
- type: precision_at_5
value: 3.031
- type: recall_at_1
value: 5.305
- type: recall_at_10
value: 19.236
- type: recall_at_100
value: 41.333999999999996
- type: recall_at_1000
value: 65.96600000000001
- type: recall_at_3
value: 11.189
- type: recall_at_5
value: 13.592
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.882
- type: map_at_10
value: 1.6
- type: map_at_100
value: 1.894
- type: map_at_1000
value: 1.9640000000000002
- type: map_at_3
value: 1.345
- type: map_at_5
value: 1.444
- type: mrr_at_1
value: 2.2800000000000002
- type: mrr_at_10
value: 3.8510000000000004
- type: mrr_at_100
value: 4.401
- type: mrr_at_1000
value: 4.472
- type: mrr_at_3
value: 3.2359999999999998
- type: mrr_at_5
value: 3.519
- type: ndcg_at_1
value: 2.2800000000000002
- type: ndcg_at_10
value: 2.5829999999999997
- type: ndcg_at_100
value: 4.629
- type: ndcg_at_1000
value: 6.709
- type: ndcg_at_3
value: 1.978
- type: ndcg_at_5
value: 2.133
- type: precision_at_1
value: 2.2800000000000002
- type: precision_at_10
value: 0.86
- type: precision_at_100
value: 0.298
- type: precision_at_1000
value: 0.065
- type: precision_at_3
value: 1.52
- type: precision_at_5
value: 1.173
- type: recall_at_1
value: 0.882
- type: recall_at_10
value: 3.273
- type: recall_at_100
value: 11.254
- type: recall_at_1000
value: 23.988
- type: recall_at_3
value: 1.818
- type: recall_at_5
value: 2.236
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.057
- type: map_at_10
value: 2.289
- type: map_at_100
value: 2.844
- type: map_at_1000
value: 3.026
- type: map_at_3
value: 1.661
- type: map_at_5
value: 1.931
- type: mrr_at_1
value: 12.75
- type: mrr_at_10
value: 17.645
- type: mrr_at_100
value: 18.312
- type: mrr_at_1000
value: 18.385
- type: mrr_at_3
value: 15.958
- type: mrr_at_5
value: 17.046
- type: ndcg_at_1
value: 10
- type: ndcg_at_10
value: 6.890000000000001
- type: ndcg_at_100
value: 7.131
- type: ndcg_at_1000
value: 9.725
- type: ndcg_at_3
value: 8.222
- type: ndcg_at_5
value: 7.536
- type: precision_at_1
value: 12.75
- type: precision_at_10
value: 5.925
- type: precision_at_100
value: 1.6469999999999998
- type: precision_at_1000
value: 0.40299999999999997
- type: precision_at_3
value: 9.667
- type: precision_at_5
value: 8
- type: recall_at_1
value: 1.057
- type: recall_at_10
value: 3.8580000000000005
- type: recall_at_100
value: 8.685
- type: recall_at_1000
value: 17.605
- type: recall_at_3
value: 2.041
- type: recall_at_5
value: 2.811
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 20.674999999999997
- type: f1
value: 17.79184478487413
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.637
- type: map_at_10
value: 3.9730000000000003
- type: map_at_100
value: 4.228
- type: map_at_1000
value: 4.268000000000001
- type: map_at_3
value: 3.542
- type: map_at_5
value: 3.763
- type: mrr_at_1
value: 2.7449999999999997
- type: mrr_at_10
value: 4.146
- type: mrr_at_100
value: 4.42
- type: mrr_at_1000
value: 4.460999999999999
- type: mrr_at_3
value: 3.695
- type: mrr_at_5
value: 3.925
- type: ndcg_at_1
value: 2.7449999999999997
- type: ndcg_at_10
value: 4.801
- type: ndcg_at_100
value: 6.198
- type: ndcg_at_1000
value: 7.468
- type: ndcg_at_3
value: 3.882
- type: ndcg_at_5
value: 4.283
- type: precision_at_1
value: 2.7449999999999997
- type: precision_at_10
value: 0.771
- type: precision_at_100
value: 0.152
- type: precision_at_1000
value: 0.027
- type: precision_at_3
value: 1.6549999999999998
- type: precision_at_5
value: 1.206
- type: recall_at_1
value: 2.637
- type: recall_at_10
value: 7.2669999999999995
- type: recall_at_100
value: 13.982
- type: recall_at_1000
value: 24.192
- type: recall_at_3
value: 4.712000000000001
- type: recall_at_5
value: 5.6739999999999995
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.91
- type: map_at_10
value: 5.721
- type: map_at_100
value: 6.489000000000001
- type: map_at_1000
value: 6.642
- type: map_at_3
value: 4.797
- type: map_at_5
value: 5.292
- type: mrr_at_1
value: 6.481000000000001
- type: mrr_at_10
value: 10.624
- type: mrr_at_100
value: 11.498999999999999
- type: mrr_at_1000
value: 11.599
- type: mrr_at_3
value: 9.285
- type: mrr_at_5
value: 10.003
- type: ndcg_at_1
value: 6.481000000000001
- type: ndcg_at_10
value: 8.303
- type: ndcg_at_100
value: 12.512
- type: ndcg_at_1000
value: 16.665
- type: ndcg_at_3
value: 6.827
- type: ndcg_at_5
value: 7.367
- type: precision_at_1
value: 6.481000000000001
- type: precision_at_10
value: 2.485
- type: precision_at_100
value: 0.668
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 4.733
- type: precision_at_5
value: 3.642
- type: recall_at_1
value: 2.91
- type: recall_at_10
value: 11.239
- type: recall_at_100
value: 27.877999999999997
- type: recall_at_1000
value: 54.507000000000005
- type: recall_at_3
value: 6.683
- type: recall_at_5
value: 8.591
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.073
- type: map_at_10
value: 2.919
- type: map_at_100
value: 3.107
- type: map_at_1000
value: 3.143
- type: map_at_3
value: 2.6100000000000003
- type: map_at_5
value: 2.773
- type: mrr_at_1
value: 4.146
- type: mrr_at_10
value: 5.657
- type: mrr_at_100
value: 5.970000000000001
- type: mrr_at_1000
value: 6.022
- type: mrr_at_3
value: 5.116
- type: mrr_at_5
value: 5.411
- type: ndcg_at_1
value: 4.146
- type: ndcg_at_10
value: 4.115
- type: ndcg_at_100
value: 5.319
- type: ndcg_at_1000
value: 6.584
- type: ndcg_at_3
value: 3.3709999999999996
- type: ndcg_at_5
value: 3.7159999999999997
- type: precision_at_1
value: 4.146
- type: precision_at_10
value: 0.983
- type: precision_at_100
value: 0.197
- type: precision_at_1000
value: 0.037
- type: precision_at_3
value: 2.152
- type: precision_at_5
value: 1.564
- type: recall_at_1
value: 2.073
- type: recall_at_10
value: 4.916
- type: recall_at_100
value: 9.844999999999999
- type: recall_at_1000
value: 18.454
- type: recall_at_3
value: 3.228
- type: recall_at_5
value: 3.91
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 53.28480000000001
- type: ap
value: 51.81084207241404
- type: f1
value: 52.83683146513476
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 2.613
- type: map_at_10
value: 4.33
- type: map_at_100
value: 4.681
- type: map_at_1000
value: 4.731
- type: map_at_3
value: 3.7560000000000002
- type: map_at_5
value: 4.035
- type: mrr_at_1
value: 2.665
- type: mrr_at_10
value: 4.436
- type: mrr_at_100
value: 4.797
- type: mrr_at_1000
value: 4.848
- type: mrr_at_3
value: 3.83
- type: mrr_at_5
value: 4.123
- type: ndcg_at_1
value: 2.665
- type: ndcg_at_10
value: 5.399
- type: ndcg_at_100
value: 7.402
- type: ndcg_at_1000
value: 9.08
- type: ndcg_at_3
value: 4.1579999999999995
- type: ndcg_at_5
value: 4.664
- type: precision_at_1
value: 2.665
- type: precision_at_10
value: 0.907
- type: precision_at_100
value: 0.19499999999999998
- type: precision_at_1000
value: 0.034
- type: precision_at_3
value: 1.791
- type: precision_at_5
value: 1.3299999999999998
- type: recall_at_1
value: 2.613
- type: recall_at_10
value: 8.729000000000001
- type: recall_at_100
value: 18.668000000000003
- type: recall_at_1000
value: 32.387
- type: recall_at_3
value: 5.25
- type: recall_at_5
value: 6.465
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 73.57729138166896
- type: f1
value: 71.0267308110663
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 38.76652986776106
- type: f1
value: 24.385724192837007
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 43.43308675184936
- type: f1
value: 39.072401899805016
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 55.225285810356425
- type: f1
value: 49.81719052485716
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 20.583405653329283
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 17.155646378261917
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 24.26316550665883
- type: mrr
value: 23.951621402458755
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.4040000000000001
- type: map_at_10
value: 2.199
- type: map_at_100
value: 2.597
- type: map_at_1000
value: 3.15
- type: map_at_3
value: 1.7850000000000001
- type: map_at_5
value: 2.005
- type: mrr_at_1
value: 13.932
- type: mrr_at_10
value: 19.529
- type: mrr_at_100
value: 20.53
- type: mrr_at_1000
value: 20.635
- type: mrr_at_3
value: 17.647
- type: mrr_at_5
value: 18.731
- type: ndcg_at_1
value: 12.539
- type: ndcg_at_10
value: 8.676
- type: ndcg_at_100
value: 8.092
- type: ndcg_at_1000
value: 16.375999999999998
- type: ndcg_at_3
value: 10.615
- type: ndcg_at_5
value: 9.690999999999999
- type: precision_at_1
value: 13.622
- type: precision_at_10
value: 6.315999999999999
- type: precision_at_100
value: 2.486
- type: precision_at_1000
value: 1.317
- type: precision_at_3
value: 10.113999999999999
- type: precision_at_5
value: 8.235000000000001
- type: recall_at_1
value: 1.4040000000000001
- type: recall_at_10
value: 3.794
- type: recall_at_100
value: 9.71
- type: recall_at_1000
value: 37.476
- type: recall_at_3
value: 2.197
- type: recall_at_5
value: 2.929
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.299
- type: map_at_10
value: 2.7279999999999998
- type: map_at_100
value: 3.065
- type: map_at_1000
value: 3.118
- type: map_at_3
value: 2.182
- type: map_at_5
value: 2.48
- type: mrr_at_1
value: 1.6219999999999999
- type: mrr_at_10
value: 3.237
- type: mrr_at_100
value: 3.5749999999999997
- type: mrr_at_1000
value: 3.626
- type: mrr_at_3
value: 2.6550000000000002
- type: mrr_at_5
value: 2.9770000000000003
- type: ndcg_at_1
value: 1.6219999999999999
- type: ndcg_at_10
value: 3.768
- type: ndcg_at_100
value: 5.721
- type: ndcg_at_1000
value: 7.346
- type: ndcg_at_3
value: 2.604
- type: ndcg_at_5
value: 3.1530000000000005
- type: precision_at_1
value: 1.6219999999999999
- type: precision_at_10
value: 0.776
- type: precision_at_100
value: 0.194
- type: precision_at_1000
value: 0.034999999999999996
- type: precision_at_3
value: 1.371
- type: precision_at_5
value: 1.1119999999999999
- type: recall_at_1
value: 1.299
- type: recall_at_10
value: 6.54
- type: recall_at_100
value: 16.014999999999997
- type: recall_at_1000
value: 28.776000000000003
- type: recall_at_3
value: 3.37
- type: recall_at_5
value: 4.676
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 50.827
- type: map_at_10
value: 60.903
- type: map_at_100
value: 61.67700000000001
- type: map_at_1000
value: 61.729
- type: map_at_3
value: 58.411
- type: map_at_5
value: 59.854
- type: mrr_at_1
value: 58.52
- type: mrr_at_10
value: 65.53999999999999
- type: mrr_at_100
value: 65.94
- type: mrr_at_1000
value: 65.962
- type: mrr_at_3
value: 63.905
- type: mrr_at_5
value: 64.883
- type: ndcg_at_1
value: 58.51
- type: ndcg_at_10
value: 65.458
- type: ndcg_at_100
value: 68.245
- type: ndcg_at_1000
value: 69.244
- type: ndcg_at_3
value: 61.970000000000006
- type: ndcg_at_5
value: 63.664
- type: precision_at_1
value: 58.51
- type: precision_at_10
value: 9.873999999999999
- type: precision_at_100
value: 1.24
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 26.650000000000002
- type: precision_at_5
value: 17.666
- type: recall_at_1
value: 50.827
- type: recall_at_10
value: 74.13300000000001
- type: recall_at_100
value: 85.724
- type: recall_at_1000
value: 92.551
- type: recall_at_3
value: 64.122
- type: recall_at_5
value: 68.757
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 15.106948858308094
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 30.968103547012337
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.4749999999999999
- type: map_at_10
value: 3.434
- type: map_at_100
value: 4.139
- type: map_at_1000
value: 4.312
- type: map_at_3
value: 2.554
- type: map_at_5
value: 2.999
- type: mrr_at_1
value: 7.3
- type: mrr_at_10
value: 12.031
- type: mrr_at_100
value: 12.97
- type: mrr_at_1000
value: 13.092
- type: mrr_at_3
value: 10.217
- type: mrr_at_5
value: 11.172
- type: ndcg_at_1
value: 7.3
- type: ndcg_at_10
value: 6.406000000000001
- type: ndcg_at_100
value: 10.302999999999999
- type: ndcg_at_1000
value: 14.791000000000002
- type: ndcg_at_3
value: 5.982
- type: ndcg_at_5
value: 5.274
- type: precision_at_1
value: 7.3
- type: precision_at_10
value: 3.37
- type: precision_at_100
value: 0.914
- type: precision_at_1000
value: 0.201
- type: precision_at_3
value: 5.567
- type: precision_at_5
value: 4.68
- type: recall_at_1
value: 1.4749999999999999
- type: recall_at_10
value: 6.79
- type: recall_at_100
value: 18.55
- type: recall_at_1000
value: 40.842
- type: recall_at_3
value: 3.36
- type: recall_at_5
value: 4.72
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 59.464420082440526
- type: cos_sim_spearman
value: 54.319988337451704
- type: euclidean_pearson
value: 57.042312873314295
- type: euclidean_spearman
value: 54.31996388571784
- type: manhattan_pearson
value: 57.078786802338435
- type: manhattan_spearman
value: 54.323312153757456
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 60.08105871689929
- type: cos_sim_spearman
value: 57.53293836132526
- type: euclidean_pearson
value: 57.69984777047449
- type: euclidean_spearman
value: 57.534154476967345
- type: manhattan_pearson
value: 57.661519973840946
- type: manhattan_spearman
value: 57.447636234309854
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 57.12692049687197
- type: cos_sim_spearman
value: 57.4759438730368
- type: euclidean_pearson
value: 58.41782334532981
- type: euclidean_spearman
value: 57.47613008122331
- type: manhattan_pearson
value: 58.41335837274888
- type: manhattan_spearman
value: 57.465936751045746
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 53.84165004759765
- type: cos_sim_spearman
value: 52.32112048731462
- type: euclidean_pearson
value: 52.790405817119094
- type: euclidean_spearman
value: 52.32112268628659
- type: manhattan_pearson
value: 52.804939090733804
- type: manhattan_spearman
value: 52.31750678935915
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 63.555819199866036
- type: cos_sim_spearman
value: 64.05841117331784
- type: euclidean_pearson
value: 63.659991414541786
- type: euclidean_spearman
value: 64.05841071779129
- type: manhattan_pearson
value: 63.6915442281397
- type: manhattan_spearman
value: 64.07728265258595
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 63.03024268207247
- type: cos_sim_spearman
value: 63.53003651570799
- type: euclidean_pearson
value: 64.09620752390686
- type: euclidean_spearman
value: 63.530036058718096
- type: manhattan_pearson
value: 64.07468313413827
- type: manhattan_spearman
value: 63.526415746516285
- 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: 70.18862439704168
- type: cos_sim_spearman
value: 70.97966882821095
- type: euclidean_pearson
value: 71.04858522892525
- type: euclidean_spearman
value: 70.97966882821095
- type: manhattan_pearson
value: 71.0777838495318
- type: manhattan_spearman
value: 71.08141859528023
- 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: 49.680993011354964
- type: cos_sim_spearman
value: 55.990646519065734
- type: euclidean_pearson
value: 52.53309325175639
- type: euclidean_spearman
value: 55.990646519065734
- type: manhattan_pearson
value: 52.55809108662631
- type: manhattan_spearman
value: 55.65236114980215
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 61.18394695826386
- type: cos_sim_spearman
value: 60.77402126712771
- type: euclidean_pearson
value: 61.202070794992736
- type: euclidean_spearman
value: 60.77402126712771
- type: manhattan_pearson
value: 61.2505175850885
- type: manhattan_spearman
value: 60.77213463387346
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 58.251838750265804
- type: mrr
value: 81.27406090641384
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.833
- type: map_at_10
value: 11.219999999999999
- type: map_at_100
value: 12.086
- type: map_at_1000
value: 12.200999999999999
- type: map_at_3
value: 10.056
- type: map_at_5
value: 10.664
- type: mrr_at_1
value: 9
- type: mrr_at_10
value: 11.875
- type: mrr_at_100
value: 12.757
- type: mrr_at_1000
value: 12.864
- type: mrr_at_3
value: 10.722
- type: mrr_at_5
value: 11.322000000000001
- type: ndcg_at_1
value: 9
- type: ndcg_at_10
value: 13.001
- type: ndcg_at_100
value: 17.784
- type: ndcg_at_1000
value: 21.695
- type: ndcg_at_3
value: 10.63
- type: ndcg_at_5
value: 11.693000000000001
- type: precision_at_1
value: 9
- type: precision_at_10
value: 2
- type: precision_at_100
value: 0.46299999999999997
- type: precision_at_1000
value: 0.083
- type: precision_at_3
value: 4.222
- type: precision_at_5
value: 3.1329999999999996
- type: recall_at_1
value: 8.833
- type: recall_at_10
value: 18
- type: recall_at_100
value: 41.211
- type: recall_at_1000
value: 73.14399999999999
- type: recall_at_3
value: 11.5
- type: recall_at_5
value: 14.083000000000002
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.44455445544554
- type: cos_sim_ap
value: 68.76115592640271
- type: cos_sim_f1
value: 67.29805013927577
- type: cos_sim_precision
value: 75.9748427672956
- type: cos_sim_recall
value: 60.4
- type: dot_accuracy
value: 99.44455445544554
- type: dot_ap
value: 68.76115778951738
- type: dot_f1
value: 67.29805013927577
- type: dot_precision
value: 75.9748427672956
- type: dot_recall
value: 60.4
- type: euclidean_accuracy
value: 99.44455445544554
- type: euclidean_ap
value: 68.76115530286063
- type: euclidean_f1
value: 67.29805013927577
- type: euclidean_precision
value: 75.9748427672956
- type: euclidean_recall
value: 60.4
- type: manhattan_accuracy
value: 99.44653465346535
- type: manhattan_ap
value: 68.76446446842253
- type: manhattan_f1
value: 67.34926052332196
- type: manhattan_precision
value: 78.10026385224275
- type: manhattan_recall
value: 59.199999999999996
- type: max_accuracy
value: 99.44653465346535
- type: max_ap
value: 68.76446446842253
- type: max_f1
value: 67.34926052332196
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 28.486032726226675
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 29.654061810103283
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 39.81455140801657
- type: mrr
value: 40.09712407690349
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.05
- type: map_at_10
value: 0.191
- type: map_at_100
value: 0.346
- type: map_at_1000
value: 0.553
- type: map_at_3
value: 0.11299999999999999
- type: map_at_5
value: 0.148
- type: mrr_at_1
value: 22
- type: mrr_at_10
value: 30.091
- type: mrr_at_100
value: 31.241999999999997
- type: mrr_at_1000
value: 31.298
- type: mrr_at_3
value: 28.000000000000004
- type: mrr_at_5
value: 28.999999999999996
- type: ndcg_at_1
value: 18
- type: ndcg_at_10
value: 12.501000000000001
- type: ndcg_at_100
value: 5.605
- type: ndcg_at_1000
value: 4.543
- type: ndcg_at_3
value: 17.531
- type: ndcg_at_5
value: 15.254999999999999
- type: precision_at_1
value: 22
- type: precision_at_10
value: 12.6
- type: precision_at_100
value: 5.06
- type: precision_at_1000
value: 2.028
- type: precision_at_3
value: 20.666999999999998
- type: precision_at_5
value: 16.8
- type: recall_at_1
value: 0.05
- type: recall_at_10
value: 0.267
- type: recall_at_100
value: 1.102
- type: recall_at_1000
value: 4.205
- type: recall_at_3
value: 0.134
- type: recall_at_5
value: 0.182
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.45199999999999996
- type: map_at_10
value: 1.986
- type: map_at_100
value: 3.887
- type: map_at_1000
value: 4.5809999999999995
- type: map_at_3
value: 0.9299999999999999
- type: map_at_5
value: 1.287
- type: mrr_at_1
value: 8.163
- type: mrr_at_10
value: 16.152
- type: mrr_at_100
value: 17.187
- type: mrr_at_1000
value: 17.301
- type: mrr_at_3
value: 11.224
- type: mrr_at_5
value: 12.653
- type: ndcg_at_1
value: 4.082
- type: ndcg_at_10
value: 6.687
- type: ndcg_at_100
value: 13.158
- type: ndcg_at_1000
value: 22.259
- type: ndcg_at_3
value: 5.039
- type: ndcg_at_5
value: 5.519
- type: precision_at_1
value: 8.163
- type: precision_at_10
value: 8.163
- type: precision_at_100
value: 3.51
- type: precision_at_1000
value: 0.9159999999999999
- type: precision_at_3
value: 7.483
- type: precision_at_5
value: 7.3469999999999995
- type: recall_at_1
value: 0.45199999999999996
- type: recall_at_10
value: 5.27
- type: recall_at_100
value: 20.75
- type: recall_at_1000
value: 49.236999999999995
- type: recall_at_3
value: 1.28
- type: recall_at_5
value: 2.045
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 57.08740000000001
- type: ap
value: 9.092681400063896
- type: f1
value: 43.966684273361125
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 42.314657611771366
- type: f1
value: 42.2349043058169
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 15.71319288909283
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 78.84007867914407
- type: cos_sim_ap
value: 42.2183603452187
- type: cos_sim_f1
value: 43.1781412906705
- type: cos_sim_precision
value: 32.74263904034896
- type: cos_sim_recall
value: 63.377308707124016
- type: dot_accuracy
value: 78.84007867914407
- type: dot_ap
value: 42.21836359699547
- type: dot_f1
value: 43.1781412906705
- type: dot_precision
value: 32.74263904034896
- type: dot_recall
value: 63.377308707124016
- type: euclidean_accuracy
value: 78.84007867914407
- type: euclidean_ap
value: 42.218363575958854
- type: euclidean_f1
value: 43.1781412906705
- type: euclidean_precision
value: 32.74263904034896
- type: euclidean_recall
value: 63.377308707124016
- type: manhattan_accuracy
value: 78.79239434940692
- type: manhattan_ap
value: 42.178124350579
- type: manhattan_f1
value: 43.16231513602337
- type: manhattan_precision
value: 32.99832495812395
- type: manhattan_recall
value: 62.37467018469657
- type: max_accuracy
value: 78.84007867914407
- type: max_ap
value: 42.21836359699547
- type: max_f1
value: 43.1781412906705
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 82.51445647533667
- type: cos_sim_ap
value: 69.65701766911302
- type: cos_sim_f1
value: 62.92060699362217
- type: cos_sim_precision
value: 60.046173219532676
- type: cos_sim_recall
value: 66.08407761010163
- type: dot_accuracy
value: 82.51445647533667
- type: dot_ap
value: 69.6569952654014
- type: dot_f1
value: 62.92060699362217
- type: dot_precision
value: 60.046173219532676
- type: dot_recall
value: 66.08407761010163
- type: euclidean_accuracy
value: 82.51445647533667
- type: euclidean_ap
value: 69.65697749857492
- type: euclidean_f1
value: 62.92060699362217
- type: euclidean_precision
value: 60.046173219532676
- type: euclidean_recall
value: 66.08407761010163
- type: manhattan_accuracy
value: 82.52221834128925
- type: manhattan_ap
value: 69.65965534790995
- type: manhattan_f1
value: 62.865817064991006
- type: manhattan_precision
value: 58.04811265401917
- type: manhattan_recall
value: 68.55558977517708
- type: max_accuracy
value: 82.52221834128925
- type: max_ap
value: 69.65965534790995
- type: max_f1
value: 62.92060699362217