metadata
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: sgpt-bloom-7b1-msmarco
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 68.05970149253731
- type: ap
value: 31.640363460776193
- type: f1
value: 62.50025574145796
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (de)
config: de
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 61.34903640256959
- type: ap
value: 75.18797161500426
- type: f1
value: 59.04772570730417
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en-ext)
config: en-ext
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 67.78110944527737
- type: ap
value: 19.218916023322706
- type: f1
value: 56.24477391445512
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (ja)
config: ja
split: test
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
metrics:
- type: accuracy
value: 58.23340471092078
- type: ap
value: 13.20222967424681
- type: f1
value: 47.511718095460296
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
metrics:
- type: accuracy
value: 68.97232499999998
- type: ap
value: 63.53632885535693
- type: f1
value: 68.62038513152868
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 33.855999999999995
- type: f1
value: 33.43468222830134
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (de)
config: de
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 29.697999999999997
- type: f1
value: 29.39935388885501
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (es)
config: es
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 35.974000000000004
- type: f1
value: 35.25910820714383
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (fr)
config: fr
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 35.922
- type: f1
value: 35.38637028933444
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (ja)
config: ja
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 27.636
- type: f1
value: 27.178349955978266
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: c379a6705fec24a2493fa68e011692605f44e119
metrics:
- type: accuracy
value: 32.632
- type: f1
value: 32.08014766494587
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
metrics:
- type: map_at_1
value: 23.684
- type: map_at_10
value: 38.507999999999996
- type: map_at_100
value: 39.677
- type: map_at_1000
value: 39.690999999999995
- type: map_at_3
value: 33.369
- type: map_at_5
value: 36.15
- type: mrr_at_1
value: 24.04
- type: mrr_at_10
value: 38.664
- type: mrr_at_100
value: 39.833
- type: mrr_at_1000
value: 39.847
- type: mrr_at_3
value: 33.476
- type: mrr_at_5
value: 36.306
- type: ndcg_at_1
value: 23.684
- type: ndcg_at_10
value: 47.282000000000004
- type: ndcg_at_100
value: 52.215
- type: ndcg_at_1000
value: 52.551
- type: ndcg_at_3
value: 36.628
- type: ndcg_at_5
value: 41.653
- type: precision_at_1
value: 23.684
- type: precision_at_10
value: 7.553
- type: precision_at_100
value: 0.97
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 15.363
- type: precision_at_5
value: 11.664
- type: recall_at_1
value: 23.684
- type: recall_at_10
value: 75.533
- type: recall_at_100
value: 97.013
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 46.088
- type: recall_at_5
value: 58.321
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
metrics:
- type: v_measure
value: 44.59375023881131
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
metrics:
- type: v_measure
value: 38.02921907752556
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
metrics:
- type: map
value: 59.97321570342109
- type: mrr
value: 73.18284746955106
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: 9ee918f184421b6bd48b78f6c714d86546106103
metrics:
- type: cos_sim_pearson
value: 89.09091435741429
- type: cos_sim_spearman
value: 85.31459455332202
- type: euclidean_pearson
value: 79.3587681410798
- type: euclidean_spearman
value: 76.8174129874685
- type: manhattan_pearson
value: 79.57051762121769
- type: manhattan_spearman
value: 76.75837549768094
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (de-en)
config: de-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 54.27974947807933
- type: f1
value: 54.00144411132214
- type: precision
value: 53.87119374071357
- type: recall
value: 54.27974947807933
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (fr-en)
config: fr-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 97.3365617433414
- type: f1
value: 97.06141316310809
- type: precision
value: 96.92567319685965
- type: recall
value: 97.3365617433414
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (ru-en)
config: ru-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 46.05472809144441
- type: f1
value: 45.30319274690595
- type: precision
value: 45.00015469655234
- type: recall
value: 46.05472809144441
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (zh-en)
config: zh-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 98.10426540284361
- type: f1
value: 97.96384061786905
- type: precision
value: 97.89362822538178
- type: recall
value: 98.10426540284361
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
metrics:
- type: accuracy
value: 84.33441558441558
- type: f1
value: 84.31653077470322
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
metrics:
- type: v_measure
value: 36.025318694698086
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
metrics:
- type: v_measure
value: 32.484889034590346
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 30.203999999999997
- type: map_at_10
value: 41.314
- type: map_at_100
value: 42.66
- type: map_at_1000
value: 42.775999999999996
- type: map_at_3
value: 37.614999999999995
- type: map_at_5
value: 39.643
- type: mrr_at_1
value: 37.482
- type: mrr_at_10
value: 47.075
- type: mrr_at_100
value: 47.845
- type: mrr_at_1000
value: 47.887
- type: mrr_at_3
value: 44.635000000000005
- type: mrr_at_5
value: 45.966
- type: ndcg_at_1
value: 37.482
- type: ndcg_at_10
value: 47.676
- type: ndcg_at_100
value: 52.915
- type: ndcg_at_1000
value: 54.82900000000001
- type: ndcg_at_3
value: 42.562
- type: ndcg_at_5
value: 44.852
- type: precision_at_1
value: 37.482
- type: precision_at_10
value: 9.142
- type: precision_at_100
value: 1.436
- type: precision_at_1000
value: 0.189
- type: precision_at_3
value: 20.458000000000002
- type: precision_at_5
value: 14.821000000000002
- type: recall_at_1
value: 30.203999999999997
- type: recall_at_10
value: 60.343
- type: recall_at_100
value: 82.58
- type: recall_at_1000
value: 94.813
- type: recall_at_3
value: 45.389
- type: recall_at_5
value: 51.800999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 30.889
- type: map_at_10
value: 40.949999999999996
- type: map_at_100
value: 42.131
- type: map_at_1000
value: 42.253
- type: map_at_3
value: 38.346999999999994
- type: map_at_5
value: 39.782000000000004
- type: mrr_at_1
value: 38.79
- type: mrr_at_10
value: 46.944
- type: mrr_at_100
value: 47.61
- type: mrr_at_1000
value: 47.650999999999996
- type: mrr_at_3
value: 45.053
- type: mrr_at_5
value: 46.101
- type: ndcg_at_1
value: 38.79
- type: ndcg_at_10
value: 46.286
- type: ndcg_at_100
value: 50.637
- type: ndcg_at_1000
value: 52.649
- type: ndcg_at_3
value: 42.851
- type: ndcg_at_5
value: 44.311
- type: precision_at_1
value: 38.79
- type: precision_at_10
value: 8.516
- type: precision_at_100
value: 1.3679999999999999
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 20.637
- type: precision_at_5
value: 14.318
- type: recall_at_1
value: 30.889
- type: recall_at_10
value: 55.327000000000005
- type: recall_at_100
value: 74.091
- type: recall_at_1000
value: 86.75500000000001
- type: recall_at_3
value: 44.557
- type: recall_at_5
value: 49.064
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 39.105000000000004
- type: map_at_10
value: 50.928
- type: map_at_100
value: 51.958000000000006
- type: map_at_1000
value: 52.017
- type: map_at_3
value: 47.638999999999996
- type: map_at_5
value: 49.624
- type: mrr_at_1
value: 44.639
- type: mrr_at_10
value: 54.261
- type: mrr_at_100
value: 54.913999999999994
- type: mrr_at_1000
value: 54.945
- type: mrr_at_3
value: 51.681999999999995
- type: mrr_at_5
value: 53.290000000000006
- type: ndcg_at_1
value: 44.639
- type: ndcg_at_10
value: 56.678
- type: ndcg_at_100
value: 60.649
- type: ndcg_at_1000
value: 61.855000000000004
- type: ndcg_at_3
value: 51.092999999999996
- type: ndcg_at_5
value: 54.096999999999994
- type: precision_at_1
value: 44.639
- type: precision_at_10
value: 9.028
- type: precision_at_100
value: 1.194
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 22.508
- type: precision_at_5
value: 15.661
- type: recall_at_1
value: 39.105000000000004
- type: recall_at_10
value: 70.367
- type: recall_at_100
value: 87.359
- type: recall_at_1000
value: 95.88
- type: recall_at_3
value: 55.581
- type: recall_at_5
value: 62.821000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 23.777
- type: map_at_10
value: 32.297
- type: map_at_100
value: 33.516
- type: map_at_1000
value: 33.592
- type: map_at_3
value: 30.001
- type: map_at_5
value: 31.209999999999997
- type: mrr_at_1
value: 25.989
- type: mrr_at_10
value: 34.472
- type: mrr_at_100
value: 35.518
- type: mrr_at_1000
value: 35.577
- type: mrr_at_3
value: 32.185
- type: mrr_at_5
value: 33.399
- type: ndcg_at_1
value: 25.989
- type: ndcg_at_10
value: 37.037
- type: ndcg_at_100
value: 42.699
- type: ndcg_at_1000
value: 44.725
- type: ndcg_at_3
value: 32.485
- type: ndcg_at_5
value: 34.549
- type: precision_at_1
value: 25.989
- type: precision_at_10
value: 5.718
- type: precision_at_100
value: 0.89
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 14.049
- type: precision_at_5
value: 9.672
- type: recall_at_1
value: 23.777
- type: recall_at_10
value: 49.472
- type: recall_at_100
value: 74.857
- type: recall_at_1000
value: 90.289
- type: recall_at_3
value: 37.086000000000006
- type: recall_at_5
value: 42.065999999999995
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 13.377
- type: map_at_10
value: 21.444
- type: map_at_100
value: 22.663
- type: map_at_1000
value: 22.8
- type: map_at_3
value: 18.857
- type: map_at_5
value: 20.426
- type: mrr_at_1
value: 16.542
- type: mrr_at_10
value: 25.326999999999998
- type: mrr_at_100
value: 26.323
- type: mrr_at_1000
value: 26.406000000000002
- type: mrr_at_3
value: 22.823
- type: mrr_at_5
value: 24.340999999999998
- type: ndcg_at_1
value: 16.542
- type: ndcg_at_10
value: 26.479000000000003
- type: ndcg_at_100
value: 32.29
- type: ndcg_at_1000
value: 35.504999999999995
- type: ndcg_at_3
value: 21.619
- type: ndcg_at_5
value: 24.19
- type: precision_at_1
value: 16.542
- type: precision_at_10
value: 5.075
- type: precision_at_100
value: 0.9339999999999999
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 10.697
- type: precision_at_5
value: 8.134
- type: recall_at_1
value: 13.377
- type: recall_at_10
value: 38.027
- type: recall_at_100
value: 63.439
- type: recall_at_1000
value: 86.354
- type: recall_at_3
value: 25
- type: recall_at_5
value: 31.306
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 28.368
- type: map_at_10
value: 39.305
- type: map_at_100
value: 40.637
- type: map_at_1000
value: 40.753
- type: map_at_3
value: 36.077999999999996
- type: map_at_5
value: 37.829
- type: mrr_at_1
value: 34.937000000000005
- type: mrr_at_10
value: 45.03
- type: mrr_at_100
value: 45.78
- type: mrr_at_1000
value: 45.827
- type: mrr_at_3
value: 42.348
- type: mrr_at_5
value: 43.807
- type: ndcg_at_1
value: 34.937000000000005
- type: ndcg_at_10
value: 45.605000000000004
- type: ndcg_at_100
value: 50.941
- type: ndcg_at_1000
value: 52.983000000000004
- type: ndcg_at_3
value: 40.366
- type: ndcg_at_5
value: 42.759
- type: precision_at_1
value: 34.937000000000005
- type: precision_at_10
value: 8.402
- type: precision_at_100
value: 1.2959999999999998
- type: precision_at_1000
value: 0.164
- type: precision_at_3
value: 19.217000000000002
- type: precision_at_5
value: 13.725000000000001
- type: recall_at_1
value: 28.368
- type: recall_at_10
value: 58.5
- type: recall_at_100
value: 80.67999999999999
- type: recall_at_1000
value: 93.925
- type: recall_at_3
value: 43.956
- type: recall_at_5
value: 50.065000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 24.851
- type: map_at_10
value: 34.758
- type: map_at_100
value: 36.081
- type: map_at_1000
value: 36.205999999999996
- type: map_at_3
value: 31.678
- type: map_at_5
value: 33.398
- type: mrr_at_1
value: 31.279
- type: mrr_at_10
value: 40.138
- type: mrr_at_100
value: 41.005
- type: mrr_at_1000
value: 41.065000000000005
- type: mrr_at_3
value: 37.519000000000005
- type: mrr_at_5
value: 38.986
- type: ndcg_at_1
value: 31.279
- type: ndcg_at_10
value: 40.534
- type: ndcg_at_100
value: 46.093
- type: ndcg_at_1000
value: 48.59
- type: ndcg_at_3
value: 35.473
- type: ndcg_at_5
value: 37.801
- type: precision_at_1
value: 31.279
- type: precision_at_10
value: 7.477
- type: precision_at_100
value: 1.2
- type: precision_at_1000
value: 0.159
- type: precision_at_3
value: 17.047
- type: precision_at_5
value: 12.306000000000001
- type: recall_at_1
value: 24.851
- type: recall_at_10
value: 52.528
- type: recall_at_100
value: 76.198
- type: recall_at_1000
value: 93.12
- type: recall_at_3
value: 38.257999999999996
- type: recall_at_5
value: 44.440000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 25.289833333333334
- type: map_at_10
value: 34.379333333333335
- type: map_at_100
value: 35.56916666666666
- type: map_at_1000
value: 35.68633333333333
- type: map_at_3
value: 31.63916666666666
- type: map_at_5
value: 33.18383333333334
- type: mrr_at_1
value: 30.081749999999996
- type: mrr_at_10
value: 38.53658333333333
- type: mrr_at_100
value: 39.37825
- type: mrr_at_1000
value: 39.43866666666666
- type: mrr_at_3
value: 36.19025
- type: mrr_at_5
value: 37.519749999999995
- type: ndcg_at_1
value: 30.081749999999996
- type: ndcg_at_10
value: 39.62041666666667
- type: ndcg_at_100
value: 44.74825
- type: ndcg_at_1000
value: 47.11366666666667
- type: ndcg_at_3
value: 35.000499999999995
- type: ndcg_at_5
value: 37.19283333333333
- type: precision_at_1
value: 30.081749999999996
- type: precision_at_10
value: 6.940249999999999
- type: precision_at_100
value: 1.1164166666666668
- type: precision_at_1000
value: 0.15025000000000002
- type: precision_at_3
value: 16.110416666666666
- type: precision_at_5
value: 11.474416666666668
- type: recall_at_1
value: 25.289833333333334
- type: recall_at_10
value: 51.01591666666667
- type: recall_at_100
value: 73.55275000000002
- type: recall_at_1000
value: 90.02666666666667
- type: recall_at_3
value: 38.15208333333334
- type: recall_at_5
value: 43.78458333333334
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 23.479
- type: map_at_10
value: 31.2
- type: map_at_100
value: 32.11
- type: map_at_1000
value: 32.214
- type: map_at_3
value: 29.093999999999998
- type: map_at_5
value: 30.415
- type: mrr_at_1
value: 26.840000000000003
- type: mrr_at_10
value: 34.153
- type: mrr_at_100
value: 34.971000000000004
- type: mrr_at_1000
value: 35.047
- type: mrr_at_3
value: 32.285000000000004
- type: mrr_at_5
value: 33.443
- type: ndcg_at_1
value: 26.840000000000003
- type: ndcg_at_10
value: 35.441
- type: ndcg_at_100
value: 40.150000000000006
- type: ndcg_at_1000
value: 42.74
- type: ndcg_at_3
value: 31.723000000000003
- type: ndcg_at_5
value: 33.71
- type: precision_at_1
value: 26.840000000000003
- type: precision_at_10
value: 5.552
- type: precision_at_100
value: 0.859
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 13.804
- type: precision_at_5
value: 9.600999999999999
- type: recall_at_1
value: 23.479
- type: recall_at_10
value: 45.442
- type: recall_at_100
value: 67.465
- type: recall_at_1000
value: 86.53
- type: recall_at_3
value: 35.315999999999995
- type: recall_at_5
value: 40.253
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 16.887
- type: map_at_10
value: 23.805
- type: map_at_100
value: 24.804000000000002
- type: map_at_1000
value: 24.932000000000002
- type: map_at_3
value: 21.632
- type: map_at_5
value: 22.845
- type: mrr_at_1
value: 20.75
- type: mrr_at_10
value: 27.686
- type: mrr_at_100
value: 28.522
- type: mrr_at_1000
value: 28.605000000000004
- type: mrr_at_3
value: 25.618999999999996
- type: mrr_at_5
value: 26.723999999999997
- type: ndcg_at_1
value: 20.75
- type: ndcg_at_10
value: 28.233000000000004
- type: ndcg_at_100
value: 33.065
- type: ndcg_at_1000
value: 36.138999999999996
- type: ndcg_at_3
value: 24.361
- type: ndcg_at_5
value: 26.111
- type: precision_at_1
value: 20.75
- type: precision_at_10
value: 5.124
- type: precision_at_100
value: 0.8750000000000001
- type: precision_at_1000
value: 0.131
- type: precision_at_3
value: 11.539000000000001
- type: precision_at_5
value: 8.273
- type: recall_at_1
value: 16.887
- type: recall_at_10
value: 37.774
- type: recall_at_100
value: 59.587
- type: recall_at_1000
value: 81.523
- type: recall_at_3
value: 26.837
- type: recall_at_5
value: 31.456
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 25.534000000000002
- type: map_at_10
value: 33.495999999999995
- type: map_at_100
value: 34.697
- type: map_at_1000
value: 34.805
- type: map_at_3
value: 31.22
- type: map_at_5
value: 32.277
- type: mrr_at_1
value: 29.944
- type: mrr_at_10
value: 37.723
- type: mrr_at_100
value: 38.645
- type: mrr_at_1000
value: 38.712999999999994
- type: mrr_at_3
value: 35.665
- type: mrr_at_5
value: 36.681999999999995
- type: ndcg_at_1
value: 29.944
- type: ndcg_at_10
value: 38.407000000000004
- type: ndcg_at_100
value: 43.877
- type: ndcg_at_1000
value: 46.312
- type: ndcg_at_3
value: 34.211000000000006
- type: ndcg_at_5
value: 35.760999999999996
- type: precision_at_1
value: 29.944
- type: precision_at_10
value: 6.343
- type: precision_at_100
value: 1.023
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 15.360999999999999
- type: precision_at_5
value: 10.428999999999998
- type: recall_at_1
value: 25.534000000000002
- type: recall_at_10
value: 49.204
- type: recall_at_100
value: 72.878
- type: recall_at_1000
value: 89.95
- type: recall_at_3
value: 37.533
- type: recall_at_5
value: 41.611
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 26.291999999999998
- type: map_at_10
value: 35.245
- type: map_at_100
value: 36.762
- type: map_at_1000
value: 36.983
- type: map_at_3
value: 32.439
- type: map_at_5
value: 33.964
- type: mrr_at_1
value: 31.423000000000002
- type: mrr_at_10
value: 39.98
- type: mrr_at_100
value: 40.791
- type: mrr_at_1000
value: 40.854
- type: mrr_at_3
value: 37.451
- type: mrr_at_5
value: 38.854
- type: ndcg_at_1
value: 31.423000000000002
- type: ndcg_at_10
value: 40.848
- type: ndcg_at_100
value: 46.35
- type: ndcg_at_1000
value: 49.166
- type: ndcg_at_3
value: 36.344
- type: ndcg_at_5
value: 38.36
- type: precision_at_1
value: 31.423000000000002
- type: precision_at_10
value: 7.767
- type: precision_at_100
value: 1.498
- type: precision_at_1000
value: 0.23700000000000002
- type: precision_at_3
value: 16.733
- type: precision_at_5
value: 12.213000000000001
- type: recall_at_1
value: 26.291999999999998
- type: recall_at_10
value: 51.184
- type: recall_at_100
value: 76.041
- type: recall_at_1000
value: 94.11500000000001
- type: recall_at_3
value: 38.257000000000005
- type: recall_at_5
value: 43.68
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
metrics:
- type: map_at_1
value: 20.715
- type: map_at_10
value: 27.810000000000002
- type: map_at_100
value: 28.810999999999996
- type: map_at_1000
value: 28.904999999999998
- type: map_at_3
value: 25.069999999999997
- type: map_at_5
value: 26.793
- type: mrr_at_1
value: 22.366
- type: mrr_at_10
value: 29.65
- type: mrr_at_100
value: 30.615
- type: mrr_at_1000
value: 30.686999999999998
- type: mrr_at_3
value: 27.017999999999997
- type: mrr_at_5
value: 28.644
- type: ndcg_at_1
value: 22.366
- type: ndcg_at_10
value: 32.221
- type: ndcg_at_100
value: 37.313
- type: ndcg_at_1000
value: 39.871
- type: ndcg_at_3
value: 26.918
- type: ndcg_at_5
value: 29.813000000000002
- type: precision_at_1
value: 22.366
- type: precision_at_10
value: 5.139
- type: precision_at_100
value: 0.8240000000000001
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 11.275
- type: precision_at_5
value: 8.540000000000001
- type: recall_at_1
value: 20.715
- type: recall_at_10
value: 44.023
- type: recall_at_100
value: 67.458
- type: recall_at_1000
value: 87.066
- type: recall_at_3
value: 30.055
- type: recall_at_5
value: 36.852000000000004
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
metrics:
- type: map_at_1
value: 11.859
- type: map_at_10
value: 20.625
- type: map_at_100
value: 22.5
- type: map_at_1000
value: 22.689
- type: map_at_3
value: 16.991
- type: map_at_5
value: 18.781
- type: mrr_at_1
value: 26.906000000000002
- type: mrr_at_10
value: 39.083
- type: mrr_at_100
value: 39.978
- type: mrr_at_1000
value: 40.014
- type: mrr_at_3
value: 35.44
- type: mrr_at_5
value: 37.619
- type: ndcg_at_1
value: 26.906000000000002
- type: ndcg_at_10
value: 29.386000000000003
- type: ndcg_at_100
value: 36.510999999999996
- type: ndcg_at_1000
value: 39.814
- type: ndcg_at_3
value: 23.558
- type: ndcg_at_5
value: 25.557999999999996
- type: precision_at_1
value: 26.906000000000002
- type: precision_at_10
value: 9.342
- type: precision_at_100
value: 1.6969999999999998
- type: precision_at_1000
value: 0.231
- type: precision_at_3
value: 17.503
- type: precision_at_5
value: 13.655000000000001
- type: recall_at_1
value: 11.859
- type: recall_at_10
value: 35.929
- type: recall_at_100
value: 60.21300000000001
- type: recall_at_1000
value: 78.606
- type: recall_at_3
value: 21.727
- type: recall_at_5
value: 27.349
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: f097057d03ed98220bc7309ddb10b71a54d667d6
metrics:
- type: map_at_1
value: 8.627
- type: map_at_10
value: 18.248
- type: map_at_100
value: 25.19
- type: map_at_1000
value: 26.741
- type: map_at_3
value: 13.286000000000001
- type: map_at_5
value: 15.126000000000001
- type: mrr_at_1
value: 64.75
- type: mrr_at_10
value: 71.865
- type: mrr_at_100
value: 72.247
- type: mrr_at_1000
value: 72.255
- type: mrr_at_3
value: 69.958
- type: mrr_at_5
value: 71.108
- type: ndcg_at_1
value: 53.25
- type: ndcg_at_10
value: 39.035
- type: ndcg_at_100
value: 42.735
- type: ndcg_at_1000
value: 50.166
- type: ndcg_at_3
value: 43.857
- type: ndcg_at_5
value: 40.579
- type: precision_at_1
value: 64.75
- type: precision_at_10
value: 30.75
- type: precision_at_100
value: 9.54
- type: precision_at_1000
value: 2.035
- type: precision_at_3
value: 47.333
- type: precision_at_5
value: 39
- type: recall_at_1
value: 8.627
- type: recall_at_10
value: 23.413
- type: recall_at_100
value: 48.037
- type: recall_at_1000
value: 71.428
- type: recall_at_3
value: 14.158999999999999
- type: recall_at_5
value: 17.002
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 829147f8f75a25f005913200eb5ed41fae320aa1
metrics:
- type: accuracy
value: 44.865
- type: f1
value: 41.56625743266997
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
metrics:
- type: map_at_1
value: 57.335
- type: map_at_10
value: 68.29499999999999
- type: map_at_100
value: 68.69800000000001
- type: map_at_1000
value: 68.714
- type: map_at_3
value: 66.149
- type: map_at_5
value: 67.539
- type: mrr_at_1
value: 61.656
- type: mrr_at_10
value: 72.609
- type: mrr_at_100
value: 72.923
- type: mrr_at_1000
value: 72.928
- type: mrr_at_3
value: 70.645
- type: mrr_at_5
value: 71.938
- type: ndcg_at_1
value: 61.656
- type: ndcg_at_10
value: 73.966
- type: ndcg_at_100
value: 75.663
- type: ndcg_at_1000
value: 75.986
- type: ndcg_at_3
value: 69.959
- type: ndcg_at_5
value: 72.269
- type: precision_at_1
value: 61.656
- type: precision_at_10
value: 9.581000000000001
- type: precision_at_100
value: 1.054
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 27.743000000000002
- type: precision_at_5
value: 17.939
- type: recall_at_1
value: 57.335
- type: recall_at_10
value: 87.24300000000001
- type: recall_at_100
value: 94.575
- type: recall_at_1000
value: 96.75399999999999
- type: recall_at_3
value: 76.44800000000001
- type: recall_at_5
value: 82.122
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
metrics:
- type: map_at_1
value: 17.014000000000003
- type: map_at_10
value: 28.469
- type: map_at_100
value: 30.178
- type: map_at_1000
value: 30.369
- type: map_at_3
value: 24.63
- type: map_at_5
value: 26.891
- type: mrr_at_1
value: 34.259
- type: mrr_at_10
value: 43.042
- type: mrr_at_100
value: 43.91
- type: mrr_at_1000
value: 43.963
- type: mrr_at_3
value: 40.483999999999995
- type: mrr_at_5
value: 42.135
- type: ndcg_at_1
value: 34.259
- type: ndcg_at_10
value: 35.836
- type: ndcg_at_100
value: 42.488
- type: ndcg_at_1000
value: 45.902
- type: ndcg_at_3
value: 32.131
- type: ndcg_at_5
value: 33.697
- type: precision_at_1
value: 34.259
- type: precision_at_10
value: 10
- type: precision_at_100
value: 1.699
- type: precision_at_1000
value: 0.22999999999999998
- type: precision_at_3
value: 21.502
- type: precision_at_5
value: 16.296
- type: recall_at_1
value: 17.014000000000003
- type: recall_at_10
value: 42.832
- type: recall_at_100
value: 67.619
- type: recall_at_1000
value: 88.453
- type: recall_at_3
value: 29.537000000000003
- type: recall_at_5
value: 35.886
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
metrics:
- type: map_at_1
value: 34.558
- type: map_at_10
value: 48.039
- type: map_at_100
value: 48.867
- type: map_at_1000
value: 48.941
- type: map_at_3
value: 45.403
- type: map_at_5
value: 46.983999999999995
- type: mrr_at_1
value: 69.11500000000001
- type: mrr_at_10
value: 75.551
- type: mrr_at_100
value: 75.872
- type: mrr_at_1000
value: 75.887
- type: mrr_at_3
value: 74.447
- type: mrr_at_5
value: 75.113
- type: ndcg_at_1
value: 69.11500000000001
- type: ndcg_at_10
value: 57.25599999999999
- type: ndcg_at_100
value: 60.417
- type: ndcg_at_1000
value: 61.976
- type: ndcg_at_3
value: 53.258
- type: ndcg_at_5
value: 55.374
- type: precision_at_1
value: 69.11500000000001
- type: precision_at_10
value: 11.689
- type: precision_at_100
value: 1.418
- type: precision_at_1000
value: 0.163
- type: precision_at_3
value: 33.018
- type: precision_at_5
value: 21.488
- type: recall_at_1
value: 34.558
- type: recall_at_10
value: 58.447
- type: recall_at_100
value: 70.91199999999999
- type: recall_at_1000
value: 81.31
- type: recall_at_3
value: 49.527
- type: recall_at_5
value: 53.72
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
metrics:
- type: accuracy
value: 61.772000000000006
- type: ap
value: 57.48217702943605
- type: f1
value: 61.20495351356274
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: validation
revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
metrics:
- type: map_at_1
value: 22.044
- type: map_at_10
value: 34.211000000000006
- type: map_at_100
value: 35.394
- type: map_at_1000
value: 35.443000000000005
- type: map_at_3
value: 30.318
- type: map_at_5
value: 32.535
- type: mrr_at_1
value: 22.722
- type: mrr_at_10
value: 34.842
- type: mrr_at_100
value: 35.954
- type: mrr_at_1000
value: 35.997
- type: mrr_at_3
value: 30.991000000000003
- type: mrr_at_5
value: 33.2
- type: ndcg_at_1
value: 22.722
- type: ndcg_at_10
value: 41.121
- type: ndcg_at_100
value: 46.841
- type: ndcg_at_1000
value: 48.049
- type: ndcg_at_3
value: 33.173
- type: ndcg_at_5
value: 37.145
- type: precision_at_1
value: 22.722
- type: precision_at_10
value: 6.516
- type: precision_at_100
value: 0.9400000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.093
- type: precision_at_5
value: 10.473
- type: recall_at_1
value: 22.044
- type: recall_at_10
value: 62.382000000000005
- type: recall_at_100
value: 88.914
- type: recall_at_1000
value: 98.099
- type: recall_at_3
value: 40.782000000000004
- type: recall_at_5
value: 50.322
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 93.68217054263563
- type: f1
value: 93.25810075739523
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (de)
config: de
split: test
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
metrics:
- type: accuracy
value: 82.05409974640745
- type: f1
value: 80.42814140324903
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (es)
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dataset:
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metrics:
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metrics:
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metrics:
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metrics:
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split: test
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metrics:
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value: 62.476
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split: test
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metrics:
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value: 73.654
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value: 80.36
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type: Clustering
dataset:
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name: MTEB RedditClustering
config: default
split: test
revision: b2805658ae38990172679479369a78b86de8c390
metrics:
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dataset:
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name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
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dataset:
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name: MTEB SCIDOCS
config: default
split: test
revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5
metrics:
- type: map_at_1
value: 4.3229999999999995
- type: map_at_10
value: 10.979999999999999
- type: map_at_100
value: 12.867
- type: map_at_1000
value: 13.147
- type: map_at_3
value: 7.973
- type: map_at_5
value: 9.513
- type: mrr_at_1
value: 21.3
- type: mrr_at_10
value: 32.34
- type: mrr_at_100
value: 33.428999999999995
- type: mrr_at_1000
value: 33.489999999999995
- type: mrr_at_3
value: 28.999999999999996
- type: mrr_at_5
value: 31.019999999999996
- type: ndcg_at_1
value: 21.3
- type: ndcg_at_10
value: 18.619
- type: ndcg_at_100
value: 26.108999999999998
- type: ndcg_at_1000
value: 31.253999999999998
- type: ndcg_at_3
value: 17.842
- type: ndcg_at_5
value: 15.673
- type: precision_at_1
value: 21.3
- type: precision_at_10
value: 9.55
- type: precision_at_100
value: 2.0340000000000003
- type: precision_at_1000
value: 0.327
- type: precision_at_3
value: 16.667
- type: precision_at_5
value: 13.76
- type: recall_at_1
value: 4.3229999999999995
- type: recall_at_10
value: 19.387
- type: recall_at_100
value: 41.307
- type: recall_at_1000
value: 66.475
- type: recall_at_3
value: 10.143
- type: recall_at_5
value: 14.007
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 78.77975189382573
- type: cos_sim_spearman
value: 69.81522686267631
- type: euclidean_pearson
value: 71.37617936889518
- type: euclidean_spearman
value: 65.71738481148611
- type: manhattan_pearson
value: 71.58222165832424
- type: manhattan_spearman
value: 65.86851365286654
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
metrics:
- type: cos_sim_pearson
value: 77.75509450443367
- type: cos_sim_spearman
value: 69.66180222442091
- type: euclidean_pearson
value: 74.98512779786111
- type: euclidean_spearman
value: 69.5997451409469
- type: manhattan_pearson
value: 75.50135090962459
- type: manhattan_spearman
value: 69.94984748475302
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9
metrics:
- type: cos_sim_pearson
value: 79.42363892383264
- type: cos_sim_spearman
value: 79.66529244176742
- type: euclidean_pearson
value: 79.50429208135942
- type: euclidean_spearman
value: 80.44767586416276
- type: manhattan_pearson
value: 79.58563944997708
- type: manhattan_spearman
value: 80.51452267103
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b
metrics:
- type: cos_sim_pearson
value: 79.2749401478149
- type: cos_sim_spearman
value: 74.6076920702392
- type: euclidean_pearson
value: 73.3302002952881
- type: euclidean_spearman
value: 70.67029803077013
- type: manhattan_pearson
value: 73.52699344010296
- type: manhattan_spearman
value: 70.8517556194297
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
metrics:
- type: cos_sim_pearson
value: 83.20884740785921
- type: cos_sim_spearman
value: 83.80600789090722
- type: euclidean_pearson
value: 74.9154089816344
- type: euclidean_spearman
value: 75.69243899592276
- type: manhattan_pearson
value: 75.0312832634451
- type: manhattan_spearman
value: 75.78324960357642
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
metrics:
- type: cos_sim_pearson
value: 79.63194141000497
- type: cos_sim_spearman
value: 80.40118418350866
- type: euclidean_pearson
value: 72.07354384551088
- type: euclidean_spearman
value: 72.28819150373845
- type: manhattan_pearson
value: 72.08736119834145
- type: manhattan_spearman
value: 72.28347083261288
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (ko-ko)
config: ko-ko
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 66.78512789499386
- type: cos_sim_spearman
value: 66.89125587193288
- type: euclidean_pearson
value: 58.74535708627959
- type: euclidean_spearman
value: 59.62103716794647
- type: manhattan_pearson
value: 59.00494529143961
- type: manhattan_spearman
value: 59.832257846799806
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (ar-ar)
config: ar-ar
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 75.48960503523992
- type: cos_sim_spearman
value: 76.4223037534204
- type: euclidean_pearson
value: 64.93966381820944
- type: euclidean_spearman
value: 62.39697395373789
- type: manhattan_pearson
value: 65.54480770061505
- type: manhattan_spearman
value: 62.944204863043105
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-ar)
config: en-ar
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 77.7331440643619
- type: cos_sim_spearman
value: 78.0748413292835
- type: euclidean_pearson
value: 38.533108233460304
- type: euclidean_spearman
value: 35.37638615280026
- type: manhattan_pearson
value: 41.0639726746513
- type: manhattan_spearman
value: 37.688161243671765
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-de)
config: en-de
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 58.4628923720782
- type: cos_sim_spearman
value: 59.10093128795948
- type: euclidean_pearson
value: 30.422902393436836
- type: euclidean_spearman
value: 27.837806030497457
- type: manhattan_pearson
value: 32.51576984630963
- type: manhattan_spearman
value: 29.181887010982514
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 86.87447904613737
- type: cos_sim_spearman
value: 87.06554974065622
- type: euclidean_pearson
value: 76.82669047851108
- type: euclidean_spearman
value: 75.45711985511991
- type: manhattan_pearson
value: 77.46644556452847
- type: manhattan_spearman
value: 76.0249120007112
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-tr)
config: en-tr
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 17.784495723497468
- type: cos_sim_spearman
value: 11.79629537128697
- type: euclidean_pearson
value: -4.354328445994008
- type: euclidean_spearman
value: -6.984566116230058
- type: manhattan_pearson
value: -4.166751901507852
- type: manhattan_spearman
value: -6.984143198323786
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (es-en)
config: es-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 76.9009642643449
- type: cos_sim_spearman
value: 78.21764726338341
- type: euclidean_pearson
value: 50.578959144342925
- type: euclidean_spearman
value: 51.664379260719606
- type: manhattan_pearson
value: 53.95690880393329
- type: manhattan_spearman
value: 54.910058464050785
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (es-es)
config: es-es
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 86.41638022270219
- type: cos_sim_spearman
value: 86.00477030366811
- type: euclidean_pearson
value: 79.7224037788285
- type: euclidean_spearman
value: 79.21417626867616
- type: manhattan_pearson
value: 80.29412412756984
- type: manhattan_spearman
value: 79.49460867616206
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (fr-en)
config: fr-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 79.90432664091082
- type: cos_sim_spearman
value: 80.46007940700204
- type: euclidean_pearson
value: 49.25348015214428
- type: euclidean_spearman
value: 47.13113020475859
- type: manhattan_pearson
value: 54.57291204043908
- type: manhattan_spearman
value: 51.98559736896087
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (it-en)
config: it-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 52.55164822309034
- type: cos_sim_spearman
value: 51.57629192137736
- type: euclidean_pearson
value: 16.63360593235354
- type: euclidean_spearman
value: 14.479679923782912
- type: manhattan_pearson
value: 18.524867185117472
- type: manhattan_spearman
value: 16.65940056664755
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (nl-en)
config: nl-en
split: test
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
metrics:
- type: cos_sim_pearson
value: 46.83690919715875
- type: cos_sim_spearman
value: 45.84993650002922
- type: euclidean_pearson
value: 6.173128686815117
- type: euclidean_spearman
value: 6.260781946306191
- type: manhattan_pearson
value: 7.328440452367316
- type: manhattan_spearman
value: 7.370842306497447
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 64.97916914277232
- type: cos_sim_spearman
value: 66.13392188807865
- type: euclidean_pearson
value: 65.3921146908468
- type: euclidean_spearman
value: 65.8381588635056
- type: manhattan_pearson
value: 65.8866165769975
- type: manhattan_spearman
value: 66.27774050472219
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de)
config: de
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 25.605130445111545
- type: cos_sim_spearman
value: 30.054844562369254
- type: euclidean_pearson
value: 23.890611005408196
- type: euclidean_spearman
value: 29.07902600726761
- type: manhattan_pearson
value: 24.239478426621833
- type: manhattan_spearman
value: 29.48547576782375
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es)
config: es
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 61.6665616159781
- type: cos_sim_spearman
value: 65.41310206289988
- type: euclidean_pearson
value: 68.38805493215008
- type: euclidean_spearman
value: 65.22777377603435
- type: manhattan_pearson
value: 69.37445390454346
- type: manhattan_spearman
value: 66.02437701858754
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (pl)
config: pl
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 15.302891825626372
- type: cos_sim_spearman
value: 31.134517255070097
- type: euclidean_pearson
value: 12.672592658843143
- type: euclidean_spearman
value: 29.14881036784207
- type: manhattan_pearson
value: 13.528545327757735
- type: manhattan_spearman
value: 29.56217928148797
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (tr)
config: tr
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 28.79299114515319
- type: cos_sim_spearman
value: 47.135864983626206
- type: euclidean_pearson
value: 40.66410787594309
- type: euclidean_spearman
value: 45.09585593138228
- type: manhattan_pearson
value: 42.02561630700308
- type: manhattan_spearman
value: 45.43979983670554
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (ar)
config: ar
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 46.00096625052943
- type: cos_sim_spearman
value: 58.67147426715496
- type: euclidean_pearson
value: 54.7154367422438
- type: euclidean_spearman
value: 59.003235142442634
- type: manhattan_pearson
value: 56.3116235357115
- type: manhattan_spearman
value: 60.12956331404423
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (ru)
config: ru
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 29.3396354650316
- type: cos_sim_spearman
value: 43.3632935734809
- type: euclidean_pearson
value: 31.18506539466593
- type: euclidean_spearman
value: 37.531745324803815
- type: manhattan_pearson
value: 32.829038232529015
- type: manhattan_spearman
value: 38.04574361589953
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh)
config: zh
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 62.9596148375188
- type: cos_sim_spearman
value: 66.77653412402461
- type: euclidean_pearson
value: 64.53156585980886
- type: euclidean_spearman
value: 66.2884373036083
- type: manhattan_pearson
value: 65.2831035495143
- type: manhattan_spearman
value: 66.83641945244322
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (fr)
config: fr
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 79.9138821493919
- type: cos_sim_spearman
value: 80.38097535004677
- type: euclidean_pearson
value: 76.2401499094322
- type: euclidean_spearman
value: 77.00897050735907
- type: manhattan_pearson
value: 76.69531453728563
- type: manhattan_spearman
value: 77.83189696428695
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-en)
config: de-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 51.27009640779202
- type: cos_sim_spearman
value: 51.16120562029285
- type: euclidean_pearson
value: 52.20594985566323
- type: euclidean_spearman
value: 52.75331049709882
- type: manhattan_pearson
value: 52.2725118792549
- type: manhattan_spearman
value: 53.614847968995115
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es-en)
config: es-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 70.46044814118835
- type: cos_sim_spearman
value: 75.05760236668672
- type: euclidean_pearson
value: 72.80128921879461
- type: euclidean_spearman
value: 73.81164755219257
- type: manhattan_pearson
value: 72.7863795809044
- type: manhattan_spearman
value: 73.65932033818906
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (it)
config: it
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 61.89276840435938
- type: cos_sim_spearman
value: 65.65042955732055
- type: euclidean_pearson
value: 61.22969491863841
- type: euclidean_spearman
value: 63.451215637904724
- type: manhattan_pearson
value: 61.16138956945465
- type: manhattan_spearman
value: 63.34966179331079
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (pl-en)
config: pl-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 56.377577221753626
- type: cos_sim_spearman
value: 53.31223653270353
- type: euclidean_pearson
value: 26.488793041564307
- type: euclidean_spearman
value: 19.524551741701472
- type: manhattan_pearson
value: 24.322868054606474
- type: manhattan_spearman
value: 19.50371443994939
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh-en)
config: zh-en
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 69.3634693673425
- type: cos_sim_spearman
value: 68.45051245419702
- type: euclidean_pearson
value: 56.1417414374769
- type: euclidean_spearman
value: 55.89891749631458
- type: manhattan_pearson
value: 57.266417430882925
- type: manhattan_spearman
value: 56.57927102744128
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es-it)
config: es-it
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 60.04169437653179
- type: cos_sim_spearman
value: 65.49531007553446
- type: euclidean_pearson
value: 58.583860732586324
- type: euclidean_spearman
value: 58.80034792537441
- type: manhattan_pearson
value: 59.02513161664622
- type: manhattan_spearman
value: 58.42942047904558
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-fr)
config: de-fr
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 48.81035211493999
- type: cos_sim_spearman
value: 53.27599246786967
- type: euclidean_pearson
value: 52.25710699032889
- type: euclidean_spearman
value: 55.22995695529873
- type: manhattan_pearson
value: 51.894901893217884
- type: manhattan_spearman
value: 54.95919975149795
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-pl)
config: de-pl
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 36.75993101477816
- type: cos_sim_spearman
value: 43.050156692479355
- type: euclidean_pearson
value: 51.49021084746248
- type: euclidean_spearman
value: 49.54771253090078
- type: manhattan_pearson
value: 54.68410760796417
- type: manhattan_spearman
value: 48.19277197691717
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (fr-pl)
config: fr-pl
split: test
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
metrics:
- type: cos_sim_pearson
value: 48.553763306386486
- type: cos_sim_spearman
value: 28.17180849095055
- type: euclidean_pearson
value: 17.50739087826514
- type: euclidean_spearman
value: 16.903085094570333
- type: manhattan_pearson
value: 20.750046512534112
- type: manhattan_spearman
value: 5.634361698190111
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: 8913289635987208e6e7c72789e4be2fe94b6abd
metrics:
- type: cos_sim_pearson
value: 82.17107190594417
- type: cos_sim_spearman
value: 80.89611873505183
- type: euclidean_pearson
value: 71.82491561814403
- type: euclidean_spearman
value: 70.33608835403274
- type: manhattan_pearson
value: 71.89538332420133
- type: manhattan_spearman
value: 70.36082395775944
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: 56a6d0140cf6356659e2a7c1413286a774468d44
metrics:
- type: map
value: 79.77047154974562
- type: mrr
value: 94.25887021475256
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: a75ae049398addde9b70f6b268875f5cbce99089
metrics:
- type: map_at_1
value: 56.328
- type: map_at_10
value: 67.167
- type: map_at_100
value: 67.721
- type: map_at_1000
value: 67.735
- type: map_at_3
value: 64.20400000000001
- type: map_at_5
value: 65.904
- type: mrr_at_1
value: 59.667
- type: mrr_at_10
value: 68.553
- type: mrr_at_100
value: 68.992
- type: mrr_at_1000
value: 69.004
- type: mrr_at_3
value: 66.22200000000001
- type: mrr_at_5
value: 67.739
- type: ndcg_at_1
value: 59.667
- type: ndcg_at_10
value: 72.111
- type: ndcg_at_100
value: 74.441
- type: ndcg_at_1000
value: 74.90599999999999
- type: ndcg_at_3
value: 67.11399999999999
- type: ndcg_at_5
value: 69.687
- type: precision_at_1
value: 59.667
- type: precision_at_10
value: 9.733
- type: precision_at_100
value: 1.09
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 26.444000000000003
- type: precision_at_5
value: 17.599999999999998
- type: recall_at_1
value: 56.328
- type: recall_at_10
value: 85.8
- type: recall_at_100
value: 96.167
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 72.433
- type: recall_at_5
value: 78.972
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
metrics:
- type: cos_sim_accuracy
value: 99.8019801980198
- type: cos_sim_ap
value: 94.92527097094644
- type: cos_sim_f1
value: 89.91935483870968
- type: cos_sim_precision
value: 90.65040650406505
- type: cos_sim_recall
value: 89.2
- type: dot_accuracy
value: 99.51782178217822
- type: dot_ap
value: 81.30756869559929
- type: dot_f1
value: 75.88235294117648
- type: dot_precision
value: 74.42307692307692
- type: dot_recall
value: 77.4
- type: euclidean_accuracy
value: 99.73069306930694
- type: euclidean_ap
value: 91.05040371796932
- type: euclidean_f1
value: 85.7889237199582
- type: euclidean_precision
value: 89.82494529540482
- type: euclidean_recall
value: 82.1
- type: manhattan_accuracy
value: 99.73762376237623
- type: manhattan_ap
value: 91.4823412839869
- type: manhattan_f1
value: 86.39836984207845
- type: manhattan_precision
value: 88.05815160955348
- type: manhattan_recall
value: 84.8
- type: max_accuracy
value: 99.8019801980198
- type: max_ap
value: 94.92527097094644
- type: max_f1
value: 89.91935483870968
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
metrics:
- type: v_measure
value: 55.13046832022158
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
metrics:
- type: v_measure
value: 34.31252463546675
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
metrics:
- type: map
value: 51.06639688231414
- type: mrr
value: 51.80205415499534
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
metrics:
- type: cos_sim_pearson
value: 31.963331462886956
- type: cos_sim_spearman
value: 33.59510652629926
- type: dot_pearson
value: 29.033733540882125
- type: dot_spearman
value: 31.550290638315506
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
metrics:
- type: map_at_1
value: 0.23600000000000002
- type: map_at_10
value: 2.09
- type: map_at_100
value: 12.466000000000001
- type: map_at_1000
value: 29.852
- type: map_at_3
value: 0.6859999999999999
- type: map_at_5
value: 1.099
- type: mrr_at_1
value: 88
- type: mrr_at_10
value: 94
- type: mrr_at_100
value: 94
- type: mrr_at_1000
value: 94
- type: mrr_at_3
value: 94
- type: mrr_at_5
value: 94
- type: ndcg_at_1
value: 86
- type: ndcg_at_10
value: 81.368
- type: ndcg_at_100
value: 61.879
- type: ndcg_at_1000
value: 55.282
- type: ndcg_at_3
value: 84.816
- type: ndcg_at_5
value: 82.503
- type: precision_at_1
value: 88
- type: precision_at_10
value: 85.6
- type: precision_at_100
value: 63.85999999999999
- type: precision_at_1000
value: 24.682000000000002
- type: precision_at_3
value: 88.667
- type: precision_at_5
value: 86
- type: recall_at_1
value: 0.23600000000000002
- type: recall_at_10
value: 2.25
- type: recall_at_100
value: 15.488
- type: recall_at_1000
value: 52.196
- type: recall_at_3
value: 0.721
- type: recall_at_5
value: 1.159
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (sqi-eng)
config: sqi-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 12.7
- type: f1
value: 10.384182044950325
- type: precision
value: 9.805277385275312
- type: recall
value: 12.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fry-eng)
config: fry-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 30.63583815028902
- type: f1
value: 24.623726947426373
- type: precision
value: 22.987809919828013
- type: recall
value: 30.63583815028902
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kur-eng)
config: kur-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 10.487804878048781
- type: f1
value: 8.255945048627975
- type: precision
value: 7.649047253615001
- type: recall
value: 10.487804878048781
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tur-eng)
config: tur-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 8.5
- type: f1
value: 6.154428783776609
- type: precision
value: 5.680727638128585
- type: recall
value: 8.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (deu-eng)
config: deu-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 73
- type: f1
value: 70.10046605876393
- type: precision
value: 69.0018253968254
- type: recall
value: 73
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nld-eng)
config: nld-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 32.7
- type: f1
value: 29.7428583868239
- type: precision
value: 28.81671359506905
- type: recall
value: 32.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ron-eng)
config: ron-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 31.5
- type: f1
value: 27.228675552174003
- type: precision
value: 25.950062299847747
- type: recall
value: 31.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ang-eng)
config: ang-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 35.82089552238806
- type: f1
value: 28.75836980510979
- type: precision
value: 26.971643613434658
- type: recall
value: 35.82089552238806
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ido-eng)
config: ido-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 49.8
- type: f1
value: 43.909237401451776
- type: precision
value: 41.944763440988936
- type: recall
value: 49.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (jav-eng)
config: jav-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 18.536585365853657
- type: f1
value: 15.020182570246751
- type: precision
value: 14.231108073213337
- type: recall
value: 18.536585365853657
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (isl-eng)
config: isl-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 8.7
- type: f1
value: 6.2934784902885355
- type: precision
value: 5.685926293425392
- type: recall
value: 8.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (slv-eng)
config: slv-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 12.879708383961116
- type: f1
value: 10.136118341751114
- type: precision
value: 9.571444036679436
- type: recall
value: 12.879708383961116
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cym-eng)
config: cym-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 9.217391304347826
- type: f1
value: 6.965003297761793
- type: precision
value: 6.476093529199119
- type: recall
value: 9.217391304347826
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kaz-eng)
config: kaz-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 4.3478260869565215
- type: f1
value: 3.3186971707677397
- type: precision
value: 3.198658632552104
- type: recall
value: 4.3478260869565215
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (est-eng)
config: est-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 6.9
- type: f1
value: 4.760708297894056
- type: precision
value: 4.28409511756074
- type: recall
value: 6.9
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (heb-eng)
config: heb-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 2.1999999999999997
- type: f1
value: 1.6862703878117107
- type: precision
value: 1.6048118233915603
- type: recall
value: 2.1999999999999997
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (gla-eng)
config: gla-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 3.0156815440289506
- type: f1
value: 2.0913257250659134
- type: precision
value: 1.9072775486461648
- type: recall
value: 3.0156815440289506
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mar-eng)
config: mar-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 49
- type: f1
value: 45.5254456536713
- type: precision
value: 44.134609250398725
- type: recall
value: 49
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lat-eng)
config: lat-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 33.5
- type: f1
value: 28.759893973182564
- type: precision
value: 27.401259116024836
- type: recall
value: 33.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bel-eng)
config: bel-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 10.2
- type: f1
value: 8.030039981676275
- type: precision
value: 7.548748077210127
- type: recall
value: 10.2
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pms-eng)
config: pms-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 38.095238095238095
- type: f1
value: 31.944999250262406
- type: precision
value: 30.04452690166976
- type: recall
value: 38.095238095238095
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (gle-eng)
config: gle-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 4.8
- type: f1
value: 3.2638960786708067
- type: precision
value: 3.0495382950729644
- type: recall
value: 4.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pes-eng)
config: pes-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 15.8
- type: f1
value: 12.131087470371275
- type: precision
value: 11.141304011547815
- type: recall
value: 15.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nob-eng)
config: nob-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 23.3
- type: f1
value: 21.073044636921384
- type: precision
value: 20.374220568287285
- type: recall
value: 23.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bul-eng)
config: bul-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 24.9
- type: f1
value: 20.091060685364987
- type: precision
value: 18.899700591081224
- type: recall
value: 24.9
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cbk-eng)
config: cbk-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 70.1
- type: f1
value: 64.62940836940835
- type: precision
value: 62.46559523809524
- type: recall
value: 70.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hun-eng)
config: hun-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 7.199999999999999
- type: f1
value: 5.06613460576115
- type: precision
value: 4.625224463391809
- type: recall
value: 7.199999999999999
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (uig-eng)
config: uig-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 1.7999999999999998
- type: f1
value: 1.2716249514772895
- type: precision
value: 1.2107445914723798
- type: recall
value: 1.7999999999999998
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (rus-eng)
config: rus-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 65.5
- type: f1
value: 59.84399711399712
- type: precision
value: 57.86349567099567
- type: recall
value: 65.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (spa-eng)
config: spa-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 95.7
- type: f1
value: 94.48333333333333
- type: precision
value: 93.89999999999999
- type: recall
value: 95.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hye-eng)
config: hye-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 0.8086253369272237
- type: f1
value: 0.4962046191492002
- type: precision
value: 0.47272438578554393
- type: recall
value: 0.8086253369272237
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tel-eng)
config: tel-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 69.23076923076923
- type: f1
value: 64.6227941099736
- type: precision
value: 63.03795877325289
- type: recall
value: 69.23076923076923
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (afr-eng)
config: afr-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 20.599999999999998
- type: f1
value: 16.62410040660465
- type: precision
value: 15.598352437967069
- type: recall
value: 20.599999999999998
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mon-eng)
config: mon-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 4.318181818181818
- type: f1
value: 2.846721192535661
- type: precision
value: 2.6787861417537147
- type: recall
value: 4.318181818181818
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (arz-eng)
config: arz-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 74.84276729559748
- type: f1
value: 70.6638714185884
- type: precision
value: 68.86792452830188
- type: recall
value: 74.84276729559748
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hrv-eng)
config: hrv-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 15.9
- type: f1
value: 12.793698974586706
- type: precision
value: 12.088118017657736
- type: recall
value: 15.9
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nov-eng)
config: nov-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 59.92217898832685
- type: f1
value: 52.23086900129701
- type: precision
value: 49.25853869433636
- type: recall
value: 59.92217898832685
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (gsw-eng)
config: gsw-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 27.350427350427353
- type: f1
value: 21.033781033781032
- type: precision
value: 19.337955491801644
- type: recall
value: 27.350427350427353
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nds-eng)
config: nds-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 29.299999999999997
- type: f1
value: 23.91597452425777
- type: precision
value: 22.36696598364942
- type: recall
value: 29.299999999999997
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ukr-eng)
config: ukr-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 27.3
- type: f1
value: 22.059393517688886
- type: precision
value: 20.503235534170887
- type: recall
value: 27.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (uzb-eng)
config: uzb-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 8.177570093457943
- type: f1
value: 4.714367017906037
- type: precision
value: 4.163882933965758
- type: recall
value: 8.177570093457943
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lit-eng)
config: lit-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 5.800000000000001
- type: f1
value: 4.4859357432293825
- type: precision
value: 4.247814465614043
- type: recall
value: 5.800000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ina-eng)
config: ina-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 78.4
- type: f1
value: 73.67166666666667
- type: precision
value: 71.83285714285714
- type: recall
value: 78.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lfn-eng)
config: lfn-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 50.3
- type: f1
value: 44.85221545883311
- type: precision
value: 43.04913026243909
- type: recall
value: 50.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (zsm-eng)
config: zsm-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 83.5
- type: f1
value: 79.95151515151515
- type: precision
value: 78.53611111111111
- type: recall
value: 83.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ita-eng)
config: ita-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 69.89999999999999
- type: f1
value: 65.03756269256269
- type: precision
value: 63.233519536019536
- type: recall
value: 69.89999999999999
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cmn-eng)
config: cmn-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 93.2
- type: f1
value: 91.44666666666666
- type: precision
value: 90.63333333333333
- type: recall
value: 93.2
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lvs-eng)
config: lvs-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 8.3
- type: f1
value: 6.553388144729963
- type: precision
value: 6.313497782829976
- type: recall
value: 8.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (glg-eng)
config: glg-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 83.6
- type: f1
value: 79.86243107769424
- type: precision
value: 78.32555555555555
- type: recall
value: 83.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ceb-eng)
config: ceb-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 9.166666666666666
- type: f1
value: 6.637753604420271
- type: precision
value: 6.10568253585495
- type: recall
value: 9.166666666666666
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bre-eng)
config: bre-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 7.3999999999999995
- type: f1
value: 4.6729483612322165
- type: precision
value: 4.103844520292658
- type: recall
value: 7.3999999999999995
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ben-eng)
config: ben-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 80.30000000000001
- type: f1
value: 75.97666666666667
- type: precision
value: 74.16
- type: recall
value: 80.30000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (swg-eng)
config: swg-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 23.214285714285715
- type: f1
value: 16.88988095238095
- type: precision
value: 15.364937641723353
- type: recall
value: 23.214285714285715
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (arq-eng)
config: arq-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 33.15038419319429
- type: f1
value: 27.747873024072415
- type: precision
value: 25.99320572578704
- type: recall
value: 33.15038419319429
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kab-eng)
config: kab-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 2.6
- type: f1
value: 1.687059048752127
- type: precision
value: 1.5384884521299
- type: recall
value: 2.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fra-eng)
config: fra-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 93.30000000000001
- type: f1
value: 91.44000000000001
- type: precision
value: 90.59166666666667
- type: recall
value: 93.30000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (por-eng)
config: por-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 94.1
- type: f1
value: 92.61666666666667
- type: precision
value: 91.88333333333333
- type: recall
value: 94.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tat-eng)
config: tat-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 5
- type: f1
value: 3.589591971281927
- type: precision
value: 3.3046491614532854
- type: recall
value: 5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (oci-eng)
config: oci-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 45.9
- type: f1
value: 40.171969141969136
- type: precision
value: 38.30764368870302
- type: recall
value: 45.9
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pol-eng)
config: pol-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 16.900000000000002
- type: f1
value: 14.094365204207351
- type: precision
value: 13.276519841269844
- type: recall
value: 16.900000000000002
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (war-eng)
config: war-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 12.8
- type: f1
value: 10.376574912567156
- type: precision
value: 9.758423963284509
- type: recall
value: 12.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (aze-eng)
config: aze-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 8.1
- type: f1
value: 6.319455355175778
- type: precision
value: 5.849948830628881
- type: recall
value: 8.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (vie-eng)
config: vie-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 95.5
- type: f1
value: 94.19666666666667
- type: precision
value: 93.60000000000001
- type: recall
value: 95.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nno-eng)
config: nno-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 19.1
- type: f1
value: 16.280080686081906
- type: precision
value: 15.451573089395668
- type: recall
value: 19.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cha-eng)
config: cha-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 30.656934306569344
- type: f1
value: 23.2568647897115
- type: precision
value: 21.260309034031664
- type: recall
value: 30.656934306569344
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mhr-eng)
config: mhr-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 2.1999999999999997
- type: f1
value: 1.556861047295521
- type: precision
value: 1.4555993437238521
- type: recall
value: 2.1999999999999997
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (dan-eng)
config: dan-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 27.500000000000004
- type: f1
value: 23.521682636223492
- type: precision
value: 22.345341306967683
- type: recall
value: 27.500000000000004
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ell-eng)
config: ell-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 7.3999999999999995
- type: f1
value: 5.344253880846173
- type: precision
value: 4.999794279068863
- type: recall
value: 7.3999999999999995
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (amh-eng)
config: amh-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 0.5952380952380952
- type: f1
value: 0.026455026455026457
- type: precision
value: 0.013528138528138528
- type: recall
value: 0.5952380952380952
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pam-eng)
config: pam-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 7.3
- type: f1
value: 5.853140211779251
- type: precision
value: 5.505563080945322
- type: recall
value: 7.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hsb-eng)
config: hsb-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 13.250517598343686
- type: f1
value: 9.676349506190704
- type: precision
value: 8.930392053553216
- type: recall
value: 13.250517598343686
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (srp-eng)
config: srp-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 14.499999999999998
- type: f1
value: 11.68912588067557
- type: precision
value: 11.024716513105519
- type: recall
value: 14.499999999999998
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (epo-eng)
config: epo-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 30.099999999999998
- type: f1
value: 26.196880936315146
- type: precision
value: 25.271714086169478
- type: recall
value: 30.099999999999998
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kzj-eng)
config: kzj-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 6.4
- type: f1
value: 5.1749445942023335
- type: precision
value: 4.975338142029625
- type: recall
value: 6.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (awa-eng)
config: awa-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 39.39393939393939
- type: f1
value: 35.005707393767096
- type: precision
value: 33.64342032053631
- type: recall
value: 39.39393939393939
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fao-eng)
config: fao-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 18.3206106870229
- type: f1
value: 12.610893447220345
- type: precision
value: 11.079228765297467
- type: recall
value: 18.3206106870229
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mal-eng)
config: mal-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 85.58951965065502
- type: f1
value: 83.30363944928548
- type: precision
value: 82.40026591554977
- type: recall
value: 85.58951965065502
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ile-eng)
config: ile-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 65.7
- type: f1
value: 59.589642857142856
- type: precision
value: 57.392826797385624
- type: recall
value: 65.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bos-eng)
config: bos-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 18.07909604519774
- type: f1
value: 13.65194306689995
- type: precision
value: 12.567953943826327
- type: recall
value: 18.07909604519774
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cor-eng)
config: cor-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 4.6
- type: f1
value: 2.8335386392505013
- type: precision
value: 2.558444143575722
- type: recall
value: 4.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cat-eng)
config: cat-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 90.7
- type: f1
value: 88.30666666666666
- type: precision
value: 87.195
- type: recall
value: 90.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (eus-eng)
config: eus-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 57.699999999999996
- type: f1
value: 53.38433067253876
- type: precision
value: 51.815451335350346
- type: recall
value: 57.699999999999996
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (yue-eng)
config: yue-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 80.60000000000001
- type: f1
value: 77.0290354090354
- type: precision
value: 75.61685897435898
- type: recall
value: 80.60000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (swe-eng)
config: swe-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 24.6
- type: f1
value: 19.52814960069739
- type: precision
value: 18.169084599880502
- type: recall
value: 24.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (dtp-eng)
config: dtp-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 5
- type: f1
value: 3.4078491753102376
- type: precision
value: 3.1757682319102387
- type: recall
value: 5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kat-eng)
config: kat-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 1.2064343163538873
- type: f1
value: 0.4224313053283095
- type: precision
value: 0.3360484946842894
- type: recall
value: 1.2064343163538873
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (jpn-eng)
config: jpn-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 76.1
- type: f1
value: 71.36246031746032
- type: precision
value: 69.5086544011544
- type: recall
value: 76.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (csb-eng)
config: csb-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 14.229249011857709
- type: f1
value: 10.026578603653704
- type: precision
value: 9.09171178352764
- type: recall
value: 14.229249011857709
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (xho-eng)
config: xho-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 8.450704225352112
- type: f1
value: 5.51214407186151
- type: precision
value: 4.928281812084629
- type: recall
value: 8.450704225352112
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (orv-eng)
config: orv-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 7.664670658682635
- type: f1
value: 5.786190079917295
- type: precision
value: 5.3643643579244
- type: recall
value: 7.664670658682635
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ind-eng)
config: ind-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 90.5
- type: f1
value: 88.03999999999999
- type: precision
value: 86.94833333333334
- type: recall
value: 90.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tuk-eng)
config: tuk-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 7.389162561576355
- type: f1
value: 5.482366349556517
- type: precision
value: 5.156814449917898
- type: recall
value: 7.389162561576355
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (max-eng)
config: max-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 41.54929577464789
- type: f1
value: 36.13520282534367
- type: precision
value: 34.818226488560995
- type: recall
value: 41.54929577464789
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (swh-eng)
config: swh-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 20.76923076923077
- type: f1
value: 16.742497560177643
- type: precision
value: 15.965759712090138
- type: recall
value: 20.76923076923077
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hin-eng)
config: hin-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 88.1
- type: f1
value: 85.23176470588236
- type: precision
value: 84.04458333333334
- type: recall
value: 88.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (dsb-eng)
config: dsb-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 11.899791231732777
- type: f1
value: 8.776706659565102
- type: precision
value: 8.167815946521582
- type: recall
value: 11.899791231732777
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ber-eng)
config: ber-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 6.1
- type: f1
value: 4.916589537178435
- type: precision
value: 4.72523017415345
- type: recall
value: 6.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tam-eng)
config: tam-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 76.54723127035831
- type: f1
value: 72.75787187839306
- type: precision
value: 71.43338442869005
- type: recall
value: 76.54723127035831
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (slk-eng)
config: slk-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 11.700000000000001
- type: f1
value: 9.975679190026007
- type: precision
value: 9.569927715653522
- type: recall
value: 11.700000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tgl-eng)
config: tgl-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 13.100000000000001
- type: f1
value: 10.697335850115408
- type: precision
value: 10.113816082086341
- type: recall
value: 13.100000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ast-eng)
config: ast-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 76.37795275590551
- type: f1
value: 71.12860892388451
- type: precision
value: 68.89763779527559
- type: recall
value: 76.37795275590551
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mkd-eng)
config: mkd-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 13.700000000000001
- type: f1
value: 10.471861684067568
- type: precision
value: 9.602902567641697
- type: recall
value: 13.700000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (khm-eng)
config: khm-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 0.554016620498615
- type: f1
value: 0.37034084643642423
- type: precision
value: 0.34676040281208437
- type: recall
value: 0.554016620498615
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ces-eng)
config: ces-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 12.4
- type: f1
value: 9.552607451092534
- type: precision
value: 8.985175505050504
- type: recall
value: 12.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tzl-eng)
config: tzl-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 33.65384615384615
- type: f1
value: 27.820512820512818
- type: precision
value: 26.09432234432234
- type: recall
value: 33.65384615384615
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (urd-eng)
config: urd-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 74.5
- type: f1
value: 70.09686507936507
- type: precision
value: 68.3117857142857
- type: recall
value: 74.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ara-eng)
config: ara-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 88.3
- type: f1
value: 85.37333333333333
- type: precision
value: 84.05833333333334
- type: recall
value: 88.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kor-eng)
config: kor-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 25
- type: f1
value: 22.393124632031995
- type: precision
value: 21.58347686592367
- type: recall
value: 25
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (yid-eng)
config: yid-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 0.589622641509434
- type: f1
value: 0.15804980033762941
- type: precision
value: 0.1393275384872965
- type: recall
value: 0.589622641509434
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fin-eng)
config: fin-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 4.1000000000000005
- type: f1
value: 3.4069011332551775
- type: precision
value: 3.1784507042253516
- type: recall
value: 4.1000000000000005
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tha-eng)
config: tha-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 3.102189781021898
- type: f1
value: 2.223851811694751
- type: precision
value: 2.103465682299194
- type: recall
value: 3.102189781021898
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (wuu-eng)
config: wuu-eng
split: test
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
metrics:
- type: accuracy
value: 83.1
- type: f1
value: 79.58255835667599
- type: precision
value: 78.09708333333333
- type: recall
value: 83.1
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
metrics:
- type: map_at_1
value: 2.322
- type: map_at_10
value: 8.959999999999999
- type: map_at_100
value: 15.136
- type: map_at_1000
value: 16.694
- type: map_at_3
value: 4.837000000000001
- type: map_at_5
value: 6.196
- type: mrr_at_1
value: 28.571
- type: mrr_at_10
value: 47.589999999999996
- type: mrr_at_100
value: 48.166
- type: mrr_at_1000
value: 48.169000000000004
- type: mrr_at_3
value: 43.197
- type: mrr_at_5
value: 45.646
- type: ndcg_at_1
value: 26.531
- type: ndcg_at_10
value: 23.982
- type: ndcg_at_100
value: 35.519
- type: ndcg_at_1000
value: 46.878
- type: ndcg_at_3
value: 26.801000000000002
- type: ndcg_at_5
value: 24.879
- type: precision_at_1
value: 28.571
- type: precision_at_10
value: 22.041
- type: precision_at_100
value: 7.4079999999999995
- type: precision_at_1000
value: 1.492
- type: precision_at_3
value: 28.571
- type: precision_at_5
value: 25.306
- type: recall_at_1
value: 2.322
- type: recall_at_10
value: 15.443999999999999
- type: recall_at_100
value: 45.918
- type: recall_at_1000
value: 79.952
- type: recall_at_3
value: 6.143
- type: recall_at_5
value: 8.737
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 66.5452
- type: ap
value: 12.99191723223892
- type: f1
value: 51.667665096195734
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: 62146448f05be9e52a36b8ee9936447ea787eede
metrics:
- type: accuracy
value: 55.854555744199196
- type: f1
value: 56.131766302254185
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
metrics:
- type: v_measure
value: 37.27891385518074
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.53102461703523
- type: cos_sim_ap
value: 65.30753664579191
- type: cos_sim_f1
value: 61.739943872778305
- type: cos_sim_precision
value: 55.438891222175556
- type: cos_sim_recall
value: 69.65699208443272
- type: dot_accuracy
value: 80.38981939560112
- type: dot_ap
value: 53.52081118421347
- type: dot_f1
value: 54.232957844617346
- type: dot_precision
value: 48.43393486828459
- type: dot_recall
value: 61.60949868073878
- type: euclidean_accuracy
value: 82.23758717291531
- type: euclidean_ap
value: 60.361102792772535
- type: euclidean_f1
value: 57.50518791791561
- type: euclidean_precision
value: 51.06470106470107
- type: euclidean_recall
value: 65.8047493403694
- type: manhattan_accuracy
value: 82.14221851344102
- type: manhattan_ap
value: 60.341937223793366
- type: manhattan_f1
value: 57.53803596127247
- type: manhattan_precision
value: 51.08473188702415
- type: manhattan_recall
value: 65.85751978891821
- type: max_accuracy
value: 83.53102461703523
- type: max_ap
value: 65.30753664579191
- type: max_f1
value: 61.739943872778305
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.75305623471883
- type: cos_sim_ap
value: 85.46387153880272
- type: cos_sim_f1
value: 77.91527673159008
- type: cos_sim_precision
value: 72.93667315828353
- type: cos_sim_recall
value: 83.62334462580844
- type: dot_accuracy
value: 85.08169363915086
- type: dot_ap
value: 74.96808060965559
- type: dot_f1
value: 71.39685033990366
- type: dot_precision
value: 64.16948111759288
- type: dot_recall
value: 80.45888512473051
- type: euclidean_accuracy
value: 85.84235650250321
- type: euclidean_ap
value: 78.42045145247211
- type: euclidean_f1
value: 70.32669630775179
- type: euclidean_precision
value: 70.6298050788227
- type: euclidean_recall
value: 70.02617801047121
- type: manhattan_accuracy
value: 85.86176116738464
- type: manhattan_ap
value: 78.54012451558276
- type: manhattan_f1
value: 70.56508080693389
- type: manhattan_precision
value: 69.39626293456413
- type: manhattan_recall
value: 71.77394518016631
- type: max_accuracy
value: 88.75305623471883
- type: max_ap
value: 85.46387153880272
- type: max_f1
value: 77.91527673159008
Usage
For usage instructions, refer to: https://github.com/Muennighoff/sgpt#asymmetric-semantic-search-be
The model was trained with the command
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 accelerate launch examples/training/ms_marco/train_bi-encoder_mnrl.py --model_name bigscience/bloom-7b1 --train_batch_size 32 --eval_batch_size 16 --freezenonbias --specb --lr 4e-4 --wandb --wandbwatchlog gradients --pooling weightedmean --gradcache --chunksize 8
Evaluation Results
{"ndcgs": {"sgpt-bloom-7b1-msmarco": {"scifact": {"NDCG@10": 0.71824}, "nfcorpus": {"NDCG@10": 0.35748}, "arguana": {"NDCG@10": 0.47281}, "scidocs": {"NDCG@10": 0.18435}, "fiqa": {"NDCG@10": 0.35736}, "cqadupstack": {"NDCG@10": 0.3708525}, "quora": {"NDCG@10": 0.74655}, "trec-covid": {"NDCG@10": 0.82731}, "webis-touche2020": {"NDCG@10": 0.2365}}}
See the evaluation folder or MTEB for more results.
Training
The model was trained with the parameters:
DataLoader:
torch.utils.data.dataloader.DataLoader of length 15600 with parameters:
{'batch_size': 32, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
The model uses BitFit, weighted-mean pooling & GradCache, for details see: https://arxiv.org/abs/2202.08904
Loss:
sentence_transformers.losses.MultipleNegativesRankingLoss.MNRLGradCache
Parameters of the fit()-Method:
{
"epochs": 10,
"evaluation_steps": 0,
"evaluator": "NoneType",
"max_grad_norm": 1,
"optimizer_class": "<class 'transformers.optimization.AdamW'>",
"optimizer_params": {
"lr": 0.0004
},
"scheduler": "WarmupLinear",
"steps_per_epoch": null,
"warmup_steps": 1000,
"weight_decay": 0.01
}
Full Model Architecture
SentenceTransformer(
(0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: BloomModel
(1): Pooling({'word_embedding_dimension': 4096, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False})
)
Citing & Authors
@article{muennighoff2022sgpt,
title={SGPT: GPT Sentence Embeddings for Semantic Search},
author={Muennighoff, Niklas},
journal={arXiv preprint arXiv:2202.08904},
year={2022}
}