jstephencorey/pythia-14m-embedding

tags:

mteb model-index:
name: pythia-14m_mean results:
- task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
  - type: accuracy value: 70.73134328358208
  - type: ap value: 32.35996836729783
  - type: f1 value: 64.2137087561157
- task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (de) config: de split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
  - type: accuracy value: 62.291220556745174
  - type: ap value: 76.5427302441011
  - type: f1 value: 60.37703210343267
- task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en-ext) config: en-ext split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
  - type: accuracy value: 67.57871064467767
  - type: ap value: 17.03033311712744
  - type: f1 value: 54.821750631894986
- task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (ja) config: ja split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
  - type: accuracy value: 62.51605995717344
  - type: ap value: 14.367489440317666
  - type: f1 value: 50.48473578289779
- task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics:
  - type: accuracy value: 57.567425000000014
  - type: ap value: 54.53026421737829
  - type: f1 value: 56.60093061259046
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 29.172000000000004
  - type: f1 value: 28.264998641170465
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (de) config: de split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 25.157999999999998
  - type: f1 value: 23.033533062569987
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (es) config: es split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 26.840000000000003
  - type: f1 value: 25.693413738086402
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (fr) config: fr split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 26.491999999999997
  - type: f1 value: 25.6252880863665
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (ja) config: ja split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 24.448000000000004
  - type: f1 value: 23.86460242225935
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 26.412000000000003
  - type: f1 value: 25.779710231390755
- task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics:
  - type: map_at_1 value: 5.761
  - type: map_at_10 value: 10.267
  - type: map_at_100 value: 11.065999999999999
  - type: map_at_1000 value: 11.16
  - type: map_at_3 value: 8.642
  - type: map_at_5 value: 9.474
  - type: mrr_at_1 value: 6.046
  - type: mrr_at_10 value: 10.365
  - type: mrr_at_100 value: 11.178
  - type: mrr_at_1000 value: 11.272
  - type: mrr_at_3 value: 8.713
  - type: mrr_at_5 value: 9.587
  - type: ndcg_at_1 value: 5.761
  - type: ndcg_at_10 value: 13.055
  - type: ndcg_at_100 value: 17.526
  - type: ndcg_at_1000 value: 20.578
  - type: ndcg_at_3 value: 9.616
  - type: ndcg_at_5 value: 11.128
  - type: precision_at_1 value: 5.761
  - type: precision_at_10 value: 2.212
  - type: precision_at_100 value: 0.44400000000000006
  - type: precision_at_1000 value: 0.06999999999999999
  - type: precision_at_3 value: 4.149
  - type: precision_at_5 value: 3.229
  - type: recall_at_1 value: 5.761
  - type: recall_at_10 value: 22.119
  - type: recall_at_100 value: 44.381
  - type: recall_at_1000 value: 69.70100000000001
  - type: recall_at_3 value: 12.447
  - type: recall_at_5 value: 16.145
- task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics:
  - type: v_measure value: 25.92658946113241
- task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics:
  - type: v_measure value: 13.902183567893395
- task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics:
  - type: map value: 47.93210378051478
  - type: mrr value: 60.70318339708921
- task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics:
  - type: cos_sim_pearson value: 49.57650220181508
  - type: cos_sim_spearman value: 51.842145113866636
  - type: euclidean_pearson value: 41.2188173176347
  - type: euclidean_spearman value: 41.16840792962046
  - type: manhattan_pearson value: 42.73893519020435
  - type: manhattan_spearman value: 44.384746276312534
- task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics:
  - type: accuracy value: 46.03896103896104
  - type: f1 value: 44.54083818845286
- task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics:
  - type: v_measure value: 23.113393015706908
- task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics:
  - type: v_measure value: 12.624675113307488
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 10.105
  - type: map_at_10 value: 13.364
  - type: map_at_100 value: 13.987
  - type: map_at_1000 value: 14.08
  - type: map_at_3 value: 12.447
  - type: map_at_5 value: 12.992999999999999
  - type: mrr_at_1 value: 12.876000000000001
  - type: mrr_at_10 value: 16.252
  - type: mrr_at_100 value: 16.926
  - type: mrr_at_1000 value: 17.004
  - type: mrr_at_3 value: 15.235999999999999
  - type: mrr_at_5 value: 15.744
  - type: ndcg_at_1 value: 12.876000000000001
  - type: ndcg_at_10 value: 15.634999999999998
  - type: ndcg_at_100 value: 19.173000000000002
  - type: ndcg_at_1000 value: 22.168
  - type: ndcg_at_3 value: 14.116999999999999
  - type: ndcg_at_5 value: 14.767
  - type: precision_at_1 value: 12.876000000000001
  - type: precision_at_10 value: 2.761
  - type: precision_at_100 value: 0.5579999999999999
  - type: precision_at_1000 value: 0.101
  - type: precision_at_3 value: 6.676
  - type: precision_at_5 value: 4.635
  - type: recall_at_1 value: 10.105
  - type: recall_at_10 value: 19.767000000000003
  - type: recall_at_100 value: 36.448
  - type: recall_at_1000 value: 58.623000000000005
  - type: recall_at_3 value: 15.087
  - type: recall_at_5 value: 17.076
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 7.249999999999999
  - type: map_at_10 value: 9.41
  - type: map_at_100 value: 9.903
  - type: map_at_1000 value: 9.993
  - type: map_at_3 value: 8.693
  - type: map_at_5 value: 9.052
  - type: mrr_at_1 value: 9.299
  - type: mrr_at_10 value: 11.907
  - type: mrr_at_100 value: 12.424
  - type: mrr_at_1000 value: 12.503
  - type: mrr_at_3 value: 10.945
  - type: mrr_at_5 value: 11.413
  - type: ndcg_at_1 value: 9.299
  - type: ndcg_at_10 value: 11.278
  - type: ndcg_at_100 value: 13.904
  - type: ndcg_at_1000 value: 16.642000000000003
  - type: ndcg_at_3 value: 9.956
  - type: ndcg_at_5 value: 10.488
  - type: precision_at_1 value: 9.299
  - type: precision_at_10 value: 2.166
  - type: precision_at_100 value: 0.45399999999999996
  - type: precision_at_1000 value: 0.089
  - type: precision_at_3 value: 4.798
  - type: precision_at_5 value: 3.427
  - type: recall_at_1 value: 7.249999999999999
  - type: recall_at_10 value: 14.285
  - type: recall_at_100 value: 26.588
  - type: recall_at_1000 value: 46.488
  - type: recall_at_3 value: 10.309
  - type: recall_at_5 value: 11.756
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 11.57
  - type: map_at_10 value: 15.497
  - type: map_at_100 value: 16.036
  - type: map_at_1000 value: 16.122
  - type: map_at_3 value: 14.309
  - type: map_at_5 value: 14.895
  - type: mrr_at_1 value: 13.354
  - type: mrr_at_10 value: 17.408
  - type: mrr_at_100 value: 17.936
  - type: mrr_at_1000 value: 18.015
  - type: mrr_at_3 value: 16.123
  - type: mrr_at_5 value: 16.735
  - type: ndcg_at_1 value: 13.354
  - type: ndcg_at_10 value: 18.071
  - type: ndcg_at_100 value: 21.017
  - type: ndcg_at_1000 value: 23.669999999999998
  - type: ndcg_at_3 value: 15.644
  - type: ndcg_at_5 value: 16.618
  - type: precision_at_1 value: 13.354
  - type: precision_at_10 value: 2.94
  - type: precision_at_100 value: 0.481
  - type: precision_at_1000 value: 0.076
  - type: precision_at_3 value: 7.001
  - type: precision_at_5 value: 4.765
  - type: recall_at_1 value: 11.57
  - type: recall_at_10 value: 24.147
  - type: recall_at_100 value: 38.045
  - type: recall_at_1000 value: 58.648
  - type: recall_at_3 value: 17.419999999999998
  - type: recall_at_5 value: 19.875999999999998
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 4.463
  - type: map_at_10 value: 6.091
  - type: map_at_100 value: 6.548
  - type: map_at_1000 value: 6.622
  - type: map_at_3 value: 5.461
  - type: map_at_5 value: 5.768
  - type: mrr_at_1 value: 4.746
  - type: mrr_at_10 value: 6.431000000000001
  - type: mrr_at_100 value: 6.941
  - type: mrr_at_1000 value: 7.016
  - type: mrr_at_3 value: 5.763
  - type: mrr_at_5 value: 6.101999999999999
  - type: ndcg_at_1 value: 4.746
  - type: ndcg_at_10 value: 7.19
  - type: ndcg_at_100 value: 9.604
  - type: ndcg_at_1000 value: 12.086
  - type: ndcg_at_3 value: 5.88
  - type: ndcg_at_5 value: 6.429
  - type: precision_at_1 value: 4.746
  - type: precision_at_10 value: 1.141
  - type: precision_at_100 value: 0.249
  - type: precision_at_1000 value: 0.049
  - type: precision_at_3 value: 2.448
  - type: precision_at_5 value: 1.7850000000000001
  - type: recall_at_1 value: 4.463
  - type: recall_at_10 value: 10.33
  - type: recall_at_100 value: 21.578
  - type: recall_at_1000 value: 41.404
  - type: recall_at_3 value: 6.816999999999999
  - type: recall_at_5 value: 8.06
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 1.521
  - type: map_at_10 value: 2.439
  - type: map_at_100 value: 2.785
  - type: map_at_1000 value: 2.858
  - type: map_at_3 value: 2.091
  - type: map_at_5 value: 2.2560000000000002
  - type: mrr_at_1 value: 2.114
  - type: mrr_at_10 value: 3.216
  - type: mrr_at_100 value: 3.6319999999999997
  - type: mrr_at_1000 value: 3.712
  - type: mrr_at_3 value: 2.778
  - type: mrr_at_5 value: 2.971
  - type: ndcg_at_1 value: 2.114
  - type: ndcg_at_10 value: 3.1910000000000003
  - type: ndcg_at_100 value: 5.165
  - type: ndcg_at_1000 value: 7.607
  - type: ndcg_at_3 value: 2.456
  - type: ndcg_at_5 value: 2.7439999999999998
  - type: precision_at_1 value: 2.114
  - type: precision_at_10 value: 0.634
  - type: precision_at_100 value: 0.189
  - type: precision_at_1000 value: 0.049
  - type: precision_at_3 value: 1.202
  - type: precision_at_5 value: 0.8959999999999999
  - type: recall_at_1 value: 1.521
  - type: recall_at_10 value: 4.8
  - type: recall_at_100 value: 13.877
  - type: recall_at_1000 value: 32.1
  - type: recall_at_3 value: 2.806
  - type: recall_at_5 value: 3.5520000000000005
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 7.449999999999999
  - type: map_at_10 value: 10.065
  - type: map_at_100 value: 10.507
  - type: map_at_1000 value: 10.599
  - type: map_at_3 value: 9.017
  - type: map_at_5 value: 9.603
  - type: mrr_at_1 value: 9.336
  - type: mrr_at_10 value: 12.589
  - type: mrr_at_100 value: 13.086
  - type: mrr_at_1000 value: 13.161000000000001
  - type: mrr_at_3 value: 11.373
  - type: mrr_at_5 value: 12.084999999999999
  - type: ndcg_at_1 value: 9.336
  - type: ndcg_at_10 value: 12.299
  - type: ndcg_at_100 value: 14.780999999999999
  - type: ndcg_at_1000 value: 17.632
  - type: ndcg_at_3 value: 10.302
  - type: ndcg_at_5 value: 11.247
  - type: precision_at_1 value: 9.336
  - type: precision_at_10 value: 2.271
  - type: precision_at_100 value: 0.42300000000000004
  - type: precision_at_1000 value: 0.08099999999999999
  - type: precision_at_3 value: 4.909
  - type: precision_at_5 value: 3.5999999999999996
  - type: recall_at_1 value: 7.449999999999999
  - type: recall_at_10 value: 16.891000000000002
  - type: recall_at_100 value: 28.050000000000004
  - type: recall_at_1000 value: 49.267
  - type: recall_at_3 value: 11.187999999999999
  - type: recall_at_5 value: 13.587
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 4.734
  - type: map_at_10 value: 7.045999999999999
  - type: map_at_100 value: 7.564
  - type: map_at_1000 value: 7.6499999999999995
  - type: map_at_3 value: 6.21
  - type: map_at_5 value: 6.617000000000001
  - type: mrr_at_1 value: 5.936
  - type: mrr_at_10 value: 8.624
  - type: mrr_at_100 value: 9.193
  - type: mrr_at_1000 value: 9.28
  - type: mrr_at_3 value: 7.725
  - type: mrr_at_5 value: 8.147
  - type: ndcg_at_1 value: 5.936
  - type: ndcg_at_10 value: 8.81
  - type: ndcg_at_100 value: 11.694
  - type: ndcg_at_1000 value: 14.526
  - type: ndcg_at_3 value: 7.140000000000001
  - type: ndcg_at_5 value: 7.8020000000000005
  - type: precision_at_1 value: 5.936
  - type: precision_at_10 value: 1.701
  - type: precision_at_100 value: 0.366
  - type: precision_at_1000 value: 0.07200000000000001
  - type: precision_at_3 value: 3.463
  - type: precision_at_5 value: 2.557
  - type: recall_at_1 value: 4.734
  - type: recall_at_10 value: 12.733
  - type: recall_at_100 value: 25.982
  - type: recall_at_1000 value: 47.233999999999995
  - type: recall_at_3 value: 8.018
  - type: recall_at_5 value: 9.762
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 4.293
  - type: map_at_10 value: 6.146999999999999
  - type: map_at_100 value: 6.487
  - type: map_at_1000 value: 6.544999999999999
  - type: map_at_3 value: 5.6930000000000005
  - type: map_at_5 value: 5.869
  - type: mrr_at_1 value: 5.061
  - type: mrr_at_10 value: 7.1690000000000005
  - type: mrr_at_100 value: 7.542
  - type: mrr_at_1000 value: 7.5969999999999995
  - type: mrr_at_3 value: 6.646000000000001
  - type: mrr_at_5 value: 6.8229999999999995
  - type: ndcg_at_1 value: 5.061
  - type: ndcg_at_10 value: 7.396
  - type: ndcg_at_100 value: 9.41
  - type: ndcg_at_1000 value: 11.386000000000001
  - type: ndcg_at_3 value: 6.454
  - type: ndcg_at_5 value: 6.718
  - type: precision_at_1 value: 5.061
  - type: precision_at_10 value: 1.319
  - type: precision_at_100 value: 0.262
  - type: precision_at_1000 value: 0.047
  - type: precision_at_3 value: 3.0669999999999997
  - type: precision_at_5 value: 1.994
  - type: recall_at_1 value: 4.293
  - type: recall_at_10 value: 10.221
  - type: recall_at_100 value: 19.744999999999997
  - type: recall_at_1000 value: 35.399
  - type: recall_at_3 value: 7.507999999999999
  - type: recall_at_5 value: 8.275
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 3.519
  - type: map_at_10 value: 4.768
  - type: map_at_100 value: 5.034000000000001
  - type: map_at_1000 value: 5.087
  - type: map_at_3 value: 4.308
  - type: map_at_5 value: 4.565
  - type: mrr_at_1 value: 4.474
  - type: mrr_at_10 value: 6.045
  - type: mrr_at_100 value: 6.361999999999999
  - type: mrr_at_1000 value: 6.417000000000001
  - type: mrr_at_3 value: 5.483
  - type: mrr_at_5 value: 5.81
  - type: ndcg_at_1 value: 4.474
  - type: ndcg_at_10 value: 5.799
  - type: ndcg_at_100 value: 7.344
  - type: ndcg_at_1000 value: 9.141
  - type: ndcg_at_3 value: 4.893
  - type: ndcg_at_5 value: 5.309
  - type: precision_at_1 value: 4.474
  - type: precision_at_10 value: 1.06
  - type: precision_at_100 value: 0.217
  - type: precision_at_1000 value: 0.045
  - type: precision_at_3 value: 2.306
  - type: precision_at_5 value: 1.7000000000000002
  - type: recall_at_1 value: 3.519
  - type: recall_at_10 value: 7.75
  - type: recall_at_100 value: 15.049999999999999
  - type: recall_at_1000 value: 28.779
  - type: recall_at_3 value: 5.18
  - type: recall_at_5 value: 6.245
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 6.098
  - type: map_at_10 value: 7.918
  - type: map_at_100 value: 8.229000000000001
  - type: map_at_1000 value: 8.293000000000001
  - type: map_at_3 value: 7.138999999999999
  - type: map_at_5 value: 7.646
  - type: mrr_at_1 value: 7.090000000000001
  - type: mrr_at_10 value: 9.293
  - type: mrr_at_100 value: 9.669
  - type: mrr_at_1000 value: 9.734
  - type: mrr_at_3 value: 8.364
  - type: mrr_at_5 value: 8.956999999999999
  - type: ndcg_at_1 value: 7.090000000000001
  - type: ndcg_at_10 value: 9.411999999999999
  - type: ndcg_at_100 value: 11.318999999999999
  - type: ndcg_at_1000 value: 13.478000000000002
  - type: ndcg_at_3 value: 7.837
  - type: ndcg_at_5 value: 8.73
  - type: precision_at_1 value: 7.090000000000001
  - type: precision_at_10 value: 1.558
  - type: precision_at_100 value: 0.28400000000000003
  - type: precision_at_1000 value: 0.053
  - type: precision_at_3 value: 3.42
  - type: precision_at_5 value: 2.5749999999999997
  - type: recall_at_1 value: 6.098
  - type: recall_at_10 value: 12.764000000000001
  - type: recall_at_100 value: 21.747
  - type: recall_at_1000 value: 38.279999999999994
  - type: recall_at_3 value: 8.476
  - type: recall_at_5 value: 10.707
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 8.607
  - type: map_at_10 value: 10.835
  - type: map_at_100 value: 11.285
  - type: map_at_1000 value: 11.383000000000001
  - type: map_at_3 value: 10.111
  - type: map_at_5 value: 10.334999999999999
  - type: mrr_at_1 value: 10.671999999999999
  - type: mrr_at_10 value: 13.269
  - type: mrr_at_100 value: 13.729
  - type: mrr_at_1000 value: 13.813
  - type: mrr_at_3 value: 12.385
  - type: mrr_at_5 value: 12.701
  - type: ndcg_at_1 value: 10.671999999999999
  - type: ndcg_at_10 value: 12.728
  - type: ndcg_at_100 value: 15.312999999999999
  - type: ndcg_at_1000 value: 18.160999999999998
  - type: ndcg_at_3 value: 11.355
  - type: ndcg_at_5 value: 11.605
  - type: precision_at_1 value: 10.671999999999999
  - type: precision_at_10 value: 2.154
  - type: precision_at_100 value: 0.455
  - type: precision_at_1000 value: 0.098
  - type: precision_at_3 value: 4.941
  - type: precision_at_5 value: 3.2809999999999997
  - type: recall_at_1 value: 8.607
  - type: recall_at_10 value: 16.398
  - type: recall_at_100 value: 28.92
  - type: recall_at_1000 value: 49.761
  - type: recall_at_3 value: 11.844000000000001
  - type: recall_at_5 value: 12.792
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 3.826
  - type: map_at_10 value: 5.6419999999999995
  - type: map_at_100 value: 5.943
  - type: map_at_1000 value: 6.005
  - type: map_at_3 value: 5.1049999999999995
  - type: map_at_5 value: 5.437
  - type: mrr_at_1 value: 4.436
  - type: mrr_at_10 value: 6.413
  - type: mrr_at_100 value: 6.752
  - type: mrr_at_1000 value: 6.819999999999999
  - type: mrr_at_3 value: 5.884
  - type: mrr_at_5 value: 6.18
  - type: ndcg_at_1 value: 4.436
  - type: ndcg_at_10 value: 6.7989999999999995
  - type: ndcg_at_100 value: 8.619
  - type: ndcg_at_1000 value: 10.842
  - type: ndcg_at_3 value: 5.739
  - type: ndcg_at_5 value: 6.292000000000001
  - type: precision_at_1 value: 4.436
  - type: precision_at_10 value: 1.109
  - type: precision_at_100 value: 0.214
  - type: precision_at_1000 value: 0.043
  - type: precision_at_3 value: 2.588
  - type: precision_at_5 value: 1.848
  - type: recall_at_1 value: 3.826
  - type: recall_at_10 value: 9.655
  - type: recall_at_100 value: 18.611
  - type: recall_at_1000 value: 36.733
  - type: recall_at_3 value: 6.784
  - type: recall_at_5 value: 8.17
- task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics:
  - type: map_at_1 value: 2.09
  - type: map_at_10 value: 3.469
  - type: map_at_100 value: 3.93
  - type: map_at_1000 value: 4.018
  - type: map_at_3 value: 2.8209999999999997
  - type: map_at_5 value: 3.144
  - type: mrr_at_1 value: 4.756
  - type: mrr_at_10 value: 7.853000000000001
  - type: mrr_at_100 value: 8.547
  - type: mrr_at_1000 value: 8.631
  - type: mrr_at_3 value: 6.569
  - type: mrr_at_5 value: 7.249999999999999
  - type: ndcg_at_1 value: 4.756
  - type: ndcg_at_10 value: 5.494000000000001
  - type: ndcg_at_100 value: 8.275
  - type: ndcg_at_1000 value: 10.892
  - type: ndcg_at_3 value: 4.091
  - type: ndcg_at_5 value: 4.588
  - type: precision_at_1 value: 4.756
  - type: precision_at_10 value: 1.8370000000000002
  - type: precision_at_100 value: 0.475
  - type: precision_at_1000 value: 0.094
  - type: precision_at_3 value: 3.018
  - type: precision_at_5 value: 2.528
  - type: recall_at_1 value: 2.09
  - type: recall_at_10 value: 7.127
  - type: recall_at_100 value: 17.483999999999998
  - type: recall_at_1000 value: 33.353
  - type: recall_at_3 value: 3.742
  - type: recall_at_5 value: 5.041
- task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics:
  - type: map_at_1 value: 0.573
  - type: map_at_10 value: 1.282
  - type: map_at_100 value: 1.625
  - type: map_at_1000 value: 1.71
  - type: map_at_3 value: 1.0
  - type: map_at_5 value: 1.135
  - type: mrr_at_1 value: 7.000000000000001
  - type: mrr_at_10 value: 11.084
  - type: mrr_at_100 value: 11.634
  - type: mrr_at_1000 value: 11.715
  - type: mrr_at_3 value: 9.792
  - type: mrr_at_5 value: 10.404
  - type: ndcg_at_1 value: 4.375
  - type: ndcg_at_10 value: 3.7800000000000002
  - type: ndcg_at_100 value: 4.353
  - type: ndcg_at_1000 value: 6.087
  - type: ndcg_at_3 value: 4.258
  - type: ndcg_at_5 value: 3.988
  - type: precision_at_1 value: 7.000000000000001
  - type: precision_at_10 value: 3.35
  - type: precision_at_100 value: 1.057
  - type: precision_at_1000 value: 0.243
  - type: precision_at_3 value: 5.75
  - type: precision_at_5 value: 4.6
  - type: recall_at_1 value: 0.573
  - type: recall_at_10 value: 2.464
  - type: recall_at_100 value: 5.6770000000000005
  - type: recall_at_1000 value: 12.516
  - type: recall_at_3 value: 1.405
  - type: recall_at_5 value: 1.807
- task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics:
  - type: accuracy value: 23.279999999999998
  - type: f1 value: 19.87865985032945
- task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics:
  - type: map_at_1 value: 3.145
  - type: map_at_10 value: 4.721
  - type: map_at_100 value: 5.086
  - type: map_at_1000 value: 5.142
  - type: map_at_3 value: 4.107
  - type: map_at_5 value: 4.45
  - type: mrr_at_1 value: 3.27
  - type: mrr_at_10 value: 4.958
  - type: mrr_at_100 value: 5.35
  - type: mrr_at_1000 value: 5.409
  - type: mrr_at_3 value: 4.303
  - type: mrr_at_5 value: 4.6739999999999995
  - type: ndcg_at_1 value: 3.27
  - type: ndcg_at_10 value: 5.768
  - type: ndcg_at_100 value: 7.854
  - type: ndcg_at_1000 value: 9.729000000000001
  - type: ndcg_at_3 value: 4.476
  - type: ndcg_at_5 value: 5.102
  - type: precision_at_1 value: 3.27
  - type: precision_at_10 value: 0.942
  - type: precision_at_100 value: 0.20600000000000002
  - type: precision_at_1000 value: 0.038
  - type: precision_at_3 value: 1.8849999999999998
  - type: precision_at_5 value: 1.455
  - type: recall_at_1 value: 3.145
  - type: recall_at_10 value: 8.889
  - type: recall_at_100 value: 19.092000000000002
  - type: recall_at_1000 value: 34.35
  - type: recall_at_3 value: 5.353
  - type: recall_at_5 value: 6.836
- task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics:
  - type: map_at_1 value: 1.166
  - type: map_at_10 value: 2.283
  - type: map_at_100 value: 2.564
  - type: map_at_1000 value: 2.6519999999999997
  - type: map_at_3 value: 1.867
  - type: map_at_5 value: 2.0500000000000003
  - type: mrr_at_1 value: 2.932
  - type: mrr_at_10 value: 4.852
  - type: mrr_at_100 value: 5.306
  - type: mrr_at_1000 value: 5.4
  - type: mrr_at_3 value: 4.141
  - type: mrr_at_5 value: 4.457
  - type: ndcg_at_1 value: 2.932
  - type: ndcg_at_10 value: 3.5709999999999997
  - type: ndcg_at_100 value: 5.489
  - type: ndcg_at_1000 value: 8.309999999999999
  - type: ndcg_at_3 value: 2.773
  - type: ndcg_at_5 value: 2.979
  - type: precision_at_1 value: 2.932
  - type: precision_at_10 value: 1.049
  - type: precision_at_100 value: 0.306
  - type: precision_at_1000 value: 0.077
  - type: precision_at_3 value: 1.8519999999999999
  - type: precision_at_5 value: 1.389
  - type: recall_at_1 value: 1.166
  - type: recall_at_10 value: 5.178
  - type: recall_at_100 value: 13.056999999999999
  - type: recall_at_1000 value: 31.708
  - type: recall_at_3 value: 2.714
  - type: recall_at_5 value: 3.4909999999999997
- task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics:
  - type: map_at_1 value: 6.138
  - type: map_at_10 value: 8.212
  - type: map_at_100 value: 8.548
  - type: map_at_1000 value: 8.604000000000001
  - type: map_at_3 value: 7.555000000000001
  - type: map_at_5 value: 7.881
  - type: mrr_at_1 value: 12.275
  - type: mrr_at_10 value: 15.49
  - type: mrr_at_100 value: 15.978
  - type: mrr_at_1000 value: 16.043
  - type: mrr_at_3 value: 14.488000000000001
  - type: mrr_at_5 value: 14.975
  - type: ndcg_at_1 value: 12.275
  - type: ndcg_at_10 value: 11.078000000000001
  - type: ndcg_at_100 value: 13.081999999999999
  - type: ndcg_at_1000 value: 14.906
  - type: ndcg_at_3 value: 9.574
  - type: ndcg_at_5 value: 10.206999999999999
  - type: precision_at_1 value: 12.275
  - type: precision_at_10 value: 2.488
  - type: precision_at_100 value: 0.41200000000000003
  - type: precision_at_1000 value: 0.066
  - type: precision_at_3 value: 5.991
  - type: precision_at_5 value: 4.0969999999999995
  - type: recall_at_1 value: 6.138
  - type: recall_at_10 value: 12.438
  - type: recall_at_100 value: 20.601
  - type: recall_at_1000 value: 32.984
  - type: recall_at_3 value: 8.987
  - type: recall_at_5 value: 10.242999999999999
- task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics:
  - type: accuracy value: 56.96359999999999
  - type: ap value: 54.16760114570921
  - type: f1 value: 56.193845361069116
- task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics:
  - type: map_at_1 value: 1.34
  - type: map_at_10 value: 2.2190000000000003
  - type: map_at_100 value: 2.427
  - type: map_at_1000 value: 2.461
  - type: map_at_3 value: 1.8610000000000002
  - type: map_at_5 value: 2.0340000000000003
  - type: mrr_at_1 value: 1.375
  - type: mrr_at_10 value: 2.284
  - type: mrr_at_100 value: 2.5
  - type: mrr_at_1000 value: 2.535
  - type: mrr_at_3 value: 1.913
  - type: mrr_at_5 value: 2.094
  - type: ndcg_at_1 value: 1.375
  - type: ndcg_at_10 value: 2.838
  - type: ndcg_at_100 value: 4.043
  - type: ndcg_at_1000 value: 5.205
  - type: ndcg_at_3 value: 2.0629999999999997
  - type: ndcg_at_5 value: 2.387
  - type: precision_at_1 value: 1.375
  - type: precision_at_10 value: 0.496
  - type: precision_at_100 value: 0.11399999999999999
  - type: precision_at_1000 value: 0.022000000000000002
  - type: precision_at_3 value: 0.898
  - type: precision_at_5 value: 0.705
  - type: recall_at_1 value: 1.34
  - type: recall_at_10 value: 4.787
  - type: recall_at_100 value: 10.759
  - type: recall_at_1000 value: 20.362
  - type: recall_at_3 value: 2.603
  - type: recall_at_5 value: 3.398
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 64.39808481532147
  - type: f1 value: 63.468270818712625
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (de) config: de split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 53.961679346294744
  - type: f1 value: 51.6707117653683
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (es) config: es split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 57.018012008005336
  - type: f1 value: 54.23413458037234
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (fr) config: fr split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 48.84434700908236
  - type: f1 value: 46.48494180527987
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (hi) config: hi split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 39.7669415561133
  - type: f1 value: 35.50974325529877
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (th) config: th split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 42.589511754068724
  - type: f1 value: 40.47244422785889
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 34.01276789785682
  - type: f1 value: 21.256775922291286
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (de) config: de split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 33.285432516201745
  - type: f1 value: 19.841703666811565
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (es) config: es split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 32.121414276184126
  - type: f1 value: 19.34706868150749
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (fr) config: fr split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 26.088318196053866
  - type: f1 value: 17.22608011891254
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (hi) config: hi split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 15.320903549659375
  - type: f1 value: 9.62002916015258
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (th) config: th split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 16.426763110307412
  - type: f1 value: 11.023799171137183
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (af) config: af split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 27.347007397444518
  - type: f1 value: 25.503551916252842
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (am) config: am split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 10.655682582380631
  - type: f1 value: 9.141696317946996
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ar) config: ar split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 17.347007397444518
  - type: f1 value: 15.345346511499534
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (az) config: az split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 20.39004707464694
  - type: f1 value: 21.129515472610237
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (bn) config: bn split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 14.082044384667114
  - type: f1 value: 12.169922201279885
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (cy) config: cy split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 27.108271687962336
  - type: f1 value: 25.449222444030063
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (da) config: da split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 27.780766644250164
  - type: f1 value: 26.96237025531764
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (de) config: de split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 21.768661735036986
  - type: f1 value: 22.377462868662263
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (el) config: el split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 21.967047747141898
  - type: f1 value: 22.427583602797057
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 33.221250840618694
  - type: f1 value: 32.627621011904495
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (es) config: es split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 27.047747141896426
  - type: f1 value: 25.244455827652786
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fa) config: fa split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 18.850033624747812
  - type: f1 value: 16.532690247057452
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fi) config: fi split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 25.934767989240083
  - type: f1 value: 24.126974912341858
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fr) config: fr split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 25.59179556153329
  - type: f1 value: 23.97686173045838
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (he) config: he split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 17.683254875588432
  - type: f1 value: 15.217082232778534
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (hi) config: hi split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 14.277067921990588
  - type: f1 value: 13.06156794974721
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (hu) config: hu split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 25.817081371889717
  - type: f1 value: 24.79443526877249
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (hy) config: hy split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 12.326832548755885
  - type: f1 value: 10.850963544530288
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (id) config: id split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 28.244788164088764
  - type: f1 value: 27.442212153664336
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (is) config: is split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 26.0390047074647
  - type: f1 value: 24.29180485465988
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- task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (tr) config: tr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
  - type: accuracy value: 28.60457296570275
  - type: f1 value: 26.98989368733863
- task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ur) config: ur split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
  - type: accuracy value: 23.345662407531943
  - type: f1 value: 19.75032390408514
- task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (vi) config: vi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
  - type: accuracy value: 29.71082716879624
  - type: f1 value: 26.675920460240782
- task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-CN) config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
  - type: accuracy value: 44.09549428379288
  - type: f1 value: 41.275350430825675
- task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-TW) config: zh-TW split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
  - type: accuracy value: 37.24277067921991
  - type: f1 value: 35.65629114113254
- task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics:
  - type: v_measure value: 22.08508717069763
- task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics:
  - type: v_measure value: 16.58582885790446
- task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics:
  - type: map value: 26.730268595233923
  - type: mrr value: 27.065185919114704
- task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics:
  - type: map_at_1 value: 1.2
  - type: map_at_10 value: 1.6400000000000001
  - type: map_at_100 value: 1.9789999999999999
  - type: map_at_1000 value: 2.554
  - type: map_at_3 value: 1.4449999999999998
  - type: map_at_5 value: 1.533
  - type: mrr_at_1 value: 6.811
  - type: mrr_at_10 value: 11.068999999999999
  - type: mrr_at_100 value: 12.454
  - type: mrr_at_1000 value: 12.590000000000002
  - type: mrr_at_3 value: 9.751999999999999
  - type: mrr_at_5 value: 10.31
  - type: ndcg_at_1 value: 6.3469999999999995
  - type: ndcg_at_10 value: 4.941
  - type: ndcg_at_100 value: 6.524000000000001
  - type: ndcg_at_1000 value: 15.918
  - type: ndcg_at_3 value: 5.959
  - type: ndcg_at_5 value: 5.395
  - type: precision_at_1 value: 6.811
  - type: precision_at_10 value: 3.375
  - type: precision_at_100 value: 2.0709999999999997
  - type: precision_at_1000 value: 1.313
  - type: precision_at_3 value: 5.47
  - type: precision_at_5 value: 4.396
  - type: recall_at_1 value: 1.2
  - type: recall_at_10 value: 2.5909999999999997
  - type: recall_at_100 value: 9.443999999999999
  - type: recall_at_1000 value: 41.542
  - type: recall_at_3 value: 1.702
  - type: recall_at_5 value: 1.9879999999999998
- task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics:
  - type: map_at_1 value: 1.214
  - type: map_at_10 value: 2.067
  - type: map_at_100 value: 2.2399999999999998
  - type: map_at_1000 value: 2.2689999999999997
  - type: map_at_3 value: 1.691
  - type: map_at_5 value: 1.916
  - type: mrr_at_1 value: 1.506
  - type: mrr_at_10 value: 2.413
  - type: mrr_at_100 value: 2.587
  - type: mrr_at_1000 value: 2.616
  - type: mrr_at_3 value: 2.023
  - type: mrr_at_5 value: 2.246
  - type: ndcg_at_1 value: 1.506
  - type: ndcg_at_10 value: 2.703
  - type: ndcg_at_100 value: 3.66
  - type: ndcg_at_1000 value: 4.6
  - type: ndcg_at_3 value: 1.9300000000000002
  - type: ndcg_at_5 value: 2.33
  - type: precision_at_1 value: 1.506
  - type: precision_at_10 value: 0.539
  - type: precision_at_100 value: 0.11
  - type: precision_at_1000 value: 0.02
  - type: precision_at_3 value: 0.9369999999999999
  - type: precision_at_5 value: 0.7939999999999999
  - type: recall_at_1 value: 1.214
  - type: recall_at_10 value: 4.34
  - type: recall_at_100 value: 8.905000000000001
  - type: recall_at_1000 value: 16.416
  - type: recall_at_3 value: 2.3009999999999997
  - type: recall_at_5 value: 3.2489999999999997
- task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 45.708
  - type: map_at_10 value: 55.131
  - type: map_at_100 value: 55.935
  - type: map_at_1000 value: 55.993
  - type: map_at_3 value: 52.749
  - type: map_at_5 value: 54.166000000000004
  - type: mrr_at_1 value: 52.44
  - type: mrr_at_10 value: 59.99
  - type: mrr_at_100 value: 60.492999999999995
  - type: mrr_at_1000 value: 60.522
  - type: mrr_at_3 value: 58.285
  - type: mrr_at_5 value: 59.305
  - type: ndcg_at_1 value: 52.43
  - type: ndcg_at_10 value: 59.873
  - type: ndcg_at_100 value: 63.086
  - type: ndcg_at_1000 value: 64.291
  - type: ndcg_at_3 value: 56.291000000000004
  - type: ndcg_at_5 value: 58.071
  - type: precision_at_1 value: 52.43
  - type: precision_at_10 value: 8.973
  - type: precision_at_100 value: 1.161
  - type: precision_at_1000 value: 0.134
  - type: precision_at_3 value: 24.177
  - type: precision_at_5 value: 16.073999999999998
  - type: recall_at_1 value: 45.708
  - type: recall_at_10 value: 69.195
  - type: recall_at_100 value: 82.812
  - type: recall_at_1000 value: 91.136
  - type: recall_at_3 value: 58.938
  - type: recall_at_5 value: 63.787000000000006
- task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics:
  - type: v_measure value: 13.142048230676806
- task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics:
  - type: v_measure value: 26.06687178917052
- task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics:
  - type: map_at_1 value: 0.46499999999999997
  - type: map_at_10 value: 0.906
  - type: map_at_100 value: 1.127
  - type: map_at_1000 value: 1.203
  - type: map_at_3 value: 0.72
  - type: map_at_5 value: 0.814
  - type: mrr_at_1 value: 2.3
  - type: mrr_at_10 value: 3.733
  - type: mrr_at_100 value: 4.295999999999999
  - type: mrr_at_1000 value: 4.412
  - type: mrr_at_3 value: 3.183
  - type: mrr_at_5 value: 3.458
  - type: ndcg_at_1 value: 2.3
  - type: ndcg_at_10 value: 1.797
  - type: ndcg_at_100 value: 3.376
  - type: ndcg_at_1000 value: 6.143
  - type: ndcg_at_3 value: 1.763
  - type: ndcg_at_5 value: 1.5070000000000001
  - type: precision_at_1 value: 2.3
  - type: precision_at_10 value: 0.91
  - type: precision_at_100 value: 0.32399999999999995
  - type: precision_at_1000 value: 0.101
  - type: precision_at_3 value: 1.633
  - type: precision_at_5 value: 1.3
  - type: recall_at_1 value: 0.46499999999999997
  - type: recall_at_10 value: 1.8499999999999999
  - type: recall_at_100 value: 6.625
  - type: recall_at_1000 value: 20.587
  - type: recall_at_3 value: 0.9900000000000001
  - type: recall_at_5 value: 1.315
- task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics:
  - type: cos_sim_pearson value: 60.78961481918511
  - type: cos_sim_spearman value: 54.92014630234372
  - type: euclidean_pearson value: 54.91456364340953
  - type: euclidean_spearman value: 50.95537043206628
  - type: manhattan_pearson value: 55.0450005071106
  - type: manhattan_spearman value: 51.227579527791654
- task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics:
  - type: cos_sim_pearson value: 43.73124494569395
  - type: cos_sim_spearman value: 43.07629933550637
  - type: euclidean_pearson value: 37.2529484210563
  - type: euclidean_spearman value: 36.68421330216546
  - type: manhattan_pearson value: 37.41673219009712
  - type: manhattan_spearman value: 36.92073705702668
- task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics:
  - type: cos_sim_pearson value: 57.17534157059787
  - type: cos_sim_spearman value: 56.86679858348438
  - type: euclidean_pearson value: 54.51552371857776
  - type: euclidean_spearman value: 53.80989851917749
  - type: manhattan_pearson value: 54.44486043632584
  - type: manhattan_spearman value: 53.83487353949481
- task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics:
  - type: cos_sim_pearson value: 52.319034960820375
  - type: cos_sim_spearman value: 50.89512224974754
  - type: euclidean_pearson value: 49.19308209408045
  - type: euclidean_spearman value: 47.45736923614355
  - type: manhattan_pearson value: 48.82127080055118
  - type: manhattan_spearman value: 47.20185686489298
- task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics:
  - type: cos_sim_pearson value: 61.57602956458427
  - type: cos_sim_spearman value: 62.894640061838956
  - type: euclidean_pearson value: 53.86893407586029
  - type: euclidean_spearman value: 54.68528520514299
  - type: manhattan_pearson value: 53.689614981956815
  - type: manhattan_spearman value: 54.51172839699876
- task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics:
  - type: cos_sim_pearson value: 56.2305694109318
  - type: cos_sim_spearman value: 57.885939000786045
  - type: euclidean_pearson value: 50.486043353701994
  - type: euclidean_spearman value: 50.4463227974027
  - type: manhattan_pearson value: 50.73317560427465
  - type: manhattan_spearman value: 50.81397877006027
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ko-ko) config: ko-ko split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 55.52162058025664
  - type: cos_sim_spearman value: 59.02220327783535
  - type: euclidean_pearson value: 55.66332330866701
  - type: euclidean_spearman value: 56.829076266662206
  - type: manhattan_pearson value: 55.39181385186973
  - type: manhattan_spearman value: 56.607432176121144
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ar-ar) config: ar-ar split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 46.312186899914906
  - type: cos_sim_spearman value: 48.07172073934163
  - type: euclidean_pearson value: 46.957276350776695
  - type: euclidean_spearman value: 43.98800593212707
  - type: manhattan_pearson value: 46.910805787619914
  - type: manhattan_spearman value: 43.96662723946553
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-ar) config: en-ar split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 16.222172523403835
  - type: cos_sim_spearman value: 17.230258645779042
  - type: euclidean_pearson value: -6.781460243147299
  - type: euclidean_spearman value: -6.884123336780775
  - type: manhattan_pearson value: -4.369061881907372
  - type: manhattan_spearman value: -4.235845433380353
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-de) config: en-de split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 7.462476431657987
  - type: cos_sim_spearman value: 5.875270645234161
  - type: euclidean_pearson value: -10.79494346180473
  - type: euclidean_spearman value: -11.704529023304776
  - type: manhattan_pearson value: -11.465867974964997
  - type: manhattan_spearman value: -12.428424608287173
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 61.46601840758559
  - type: cos_sim_spearman value: 65.69667638887147
  - type: euclidean_pearson value: 49.531065525619866
  - type: euclidean_spearman value: 53.880480167479725
  - type: manhattan_pearson value: 50.25462221374689
  - type: manhattan_spearman value: 54.22205494276401
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-tr) config: en-tr split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: -12.769479370624031
  - type: cos_sim_spearman value: -12.161427312728382
  - type: euclidean_pearson value: -27.950593491756536
  - type: euclidean_spearman value: -24.925281959398585
  - type: manhattan_pearson value: -25.98778888167475
  - type: manhattan_spearman value: -22.861942388867234
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-en) config: es-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 2.1575763564561727
  - type: cos_sim_spearman value: 1.182204089411577
  - type: euclidean_pearson value: -10.389249806317189
  - type: euclidean_spearman value: -16.078659904264605
  - type: manhattan_pearson value: -9.674301846448607
  - type: manhattan_spearman value: -16.976576817518577
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-es) config: es-es split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 66.16718583059163
  - type: cos_sim_spearman value: 69.95156267898052
  - type: euclidean_pearson value: 64.93174777029739
  - type: euclidean_spearman value: 66.21292533974568
  - type: manhattan_pearson value: 65.2578109632889
  - type: manhattan_spearman value: 66.21830865759128
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (fr-en) config: fr-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 0.1540829683540524
  - type: cos_sim_spearman value: -2.4072834011003987
  - type: euclidean_pearson value: -18.951775877513473
  - type: euclidean_spearman value: -18.393605606817527
  - type: manhattan_pearson value: -19.609633839454542
  - type: manhattan_spearman value: -19.276064769117912
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (it-en) config: it-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: -4.22497246932717
  - type: cos_sim_spearman value: -5.747420352346977
  - type: euclidean_pearson value: -16.86351349130112
  - type: euclidean_spearman value: -16.555536618547382
  - type: manhattan_pearson value: -17.45445643482646
  - type: manhattan_spearman value: -17.97322953856309
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (nl-en) config: nl-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 8.559184021676034
  - type: cos_sim_spearman value: 5.600273352595882
  - type: euclidean_pearson value: -10.76482859283058
  - type: euclidean_spearman value: -9.575202768285926
  - type: manhattan_pearson value: -9.48508597350615
  - type: manhattan_spearman value: -9.33387861352172
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 30.260087169228978
  - type: cos_sim_spearman value: 43.264174903196015
  - type: euclidean_pearson value: 35.07785877281954
  - type: euclidean_spearman value: 43.41294719372452
  - type: manhattan_pearson value: 36.74996284702431
  - type: manhattan_spearman value: 43.53522851890142
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de) config: de split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 5.58694979115026
  - type: cos_sim_spearman value: 32.80692337371332
  - type: euclidean_pearson value: 10.53180875461474
  - type: euclidean_spearman value: 31.105269938654033
  - type: manhattan_pearson value: 10.559778015974826
  - type: manhattan_spearman value: 31.452204563072044
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es) config: es split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 10.593783873928478
  - type: cos_sim_spearman value: 50.397542574042006
  - type: euclidean_pearson value: 28.122179063209714
  - type: euclidean_spearman value: 50.72847867996529
  - type: manhattan_pearson value: 28.730690148465005
  - type: manhattan_spearman value: 51.019761292483366
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl) config: pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: -1.3049499265017876
  - type: cos_sim_spearman value: 16.347130048706084
  - type: euclidean_pearson value: 0.5710147274110128
  - type: euclidean_spearman value: 16.589843077857605
  - type: manhattan_pearson value: 1.1226404198336415
  - type: manhattan_spearman value: 16.410620108636557
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (tr) config: tr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: -10.96861909019159
  - type: cos_sim_spearman value: 24.536979219880724
  - type: euclidean_pearson value: -1.3040190807315306
  - type: euclidean_spearman value: 25.061584673761928
  - type: manhattan_pearson value: -0.06525719745037804
  - type: manhattan_spearman value: 25.979295538386893
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ar) config: ar split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 1.0599417065503314
  - type: cos_sim_spearman value: 52.055853787103345
  - type: euclidean_pearson value: 23.666828441081776
  - type: euclidean_spearman value: 52.38656753170069
  - type: manhattan_pearson value: 23.398080463967215
  - type: manhattan_spearman value: 52.23849717509109
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ru) config: ru split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: -2.847646040977239
  - type: cos_sim_spearman value: 40.5826838357407
  - type: euclidean_pearson value: 9.242304983683113
  - type: euclidean_spearman value: 40.35906851022345
  - type: manhattan_pearson value: 9.645663412799504
  - type: manhattan_spearman value: 40.78106154950966
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh) config: zh split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 17.761397832130992
  - type: cos_sim_spearman value: 59.98756452345925
  - type: euclidean_pearson value: 37.03125109036693
  - type: euclidean_spearman value: 59.58469212715707
  - type: manhattan_pearson value: 36.828102137170724
  - type: manhattan_spearman value: 59.07036501478588
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr) config: fr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 22.281212883400205
  - type: cos_sim_spearman value: 48.27687537627578
  - type: euclidean_pearson value: 30.531395629285324
  - type: euclidean_spearman value: 50.349143748970384
  - type: manhattan_pearson value: 30.48762081986554
  - type: manhattan_spearman value: 50.66037165529169
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-en) config: de-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 15.76679673990358
  - type: cos_sim_spearman value: 19.123349126370442
  - type: euclidean_pearson value: 19.21389203087116
  - type: euclidean_spearman value: 23.63276413160338
  - type: manhattan_pearson value: 18.789263824907053
  - type: manhattan_spearman value: 19.962703178974692
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-en) config: es-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 11.024970397289941
  - type: cos_sim_spearman value: 13.530951900755017
  - type: euclidean_pearson value: 13.473514585343645
  - type: euclidean_spearman value: 16.754702023734914
  - type: manhattan_pearson value: 13.72847275970385
  - type: manhattan_spearman value: 16.673001637012348
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (it) config: it split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 33.32761589409043
  - type: cos_sim_spearman value: 54.14305778960692
  - type: euclidean_pearson value: 45.30173241170555
  - type: euclidean_spearman value: 54.77422257007743
  - type: manhattan_pearson value: 45.41890064000217
  - type: manhattan_spearman value: 54.533788920795544
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl-en) config: pl-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 20.045210048995486
  - type: cos_sim_spearman value: 17.597101329633823
  - type: euclidean_pearson value: 32.531726142346145
  - type: euclidean_spearman value: 27.244772040848105
  - type: manhattan_pearson value: 32.74618458514601
  - type: manhattan_spearman value: 25.81220754539242
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh-en) config: zh-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: -13.832846350193021
  - type: cos_sim_spearman value: -8.406778050457863
  - type: euclidean_pearson value: -6.557254855697437
  - type: euclidean_spearman value: -3.5112770921588563
  - type: manhattan_pearson value: -6.493730738275641
  - type: manhattan_spearman value: -2.5922348401468365
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-it) config: es-it split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 26.357929743436664
  - type: cos_sim_spearman value: 37.3417709718339
  - type: euclidean_pearson value: 30.930792572341293
  - type: euclidean_spearman value: 36.061866364725795
  - type: manhattan_pearson value: 31.56982745863155
  - type: manhattan_spearman value: 37.18529502311113
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-fr) config: de-fr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 9.310102041071547
  - type: cos_sim_spearman value: 10.907002693108673
  - type: euclidean_pearson value: 7.361793742296021
  - type: euclidean_spearman value: 9.53967881391466
  - type: manhattan_pearson value: 8.017048631719996
  - type: manhattan_spearman value: 13.537860190039725
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-pl) config: de-pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: -5.534456407419709
  - type: cos_sim_spearman value: 17.552638994787724
  - type: euclidean_pearson value: -10.136558594355556
  - type: euclidean_spearman value: 11.055083156366303
  - type: manhattan_pearson value: -11.799223055640773
  - type: manhattan_spearman value: 1.416528760982869
- task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr-pl) config: fr-pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
  - type: cos_sim_pearson value: 48.64639760720344
  - type: cos_sim_spearman value: 39.440531887330785
  - type: euclidean_pearson value: 37.75527464173489
  - type: euclidean_spearman value: 39.440531887330785
  - type: manhattan_pearson value: 32.324715276369474
  - type: manhattan_spearman value: 28.17180849095055
- task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics:
  - type: cos_sim_pearson value: 44.667456983937
  - type: cos_sim_spearman value: 46.04327333618551
  - type: euclidean_pearson value: 44.583522824155104
  - type: euclidean_spearman value: 44.77184813864239
  - type: manhattan_pearson value: 44.54496373721756
  - type: manhattan_spearman value: 44.830873857115996
- task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics:
  - type: map value: 49.756063724243
  - type: mrr value: 75.29077585450135
- task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics:
  - type: map_at_1 value: 14.194
  - type: map_at_10 value: 18.756999999999998
  - type: map_at_100 value: 19.743
  - type: map_at_1000 value: 19.865
  - type: map_at_3 value: 16.986
  - type: map_at_5 value: 18.024
  - type: mrr_at_1 value: 15.0
  - type: mrr_at_10 value: 19.961000000000002
  - type: mrr_at_100 value: 20.875
  - type: mrr_at_1000 value: 20.982
  - type: mrr_at_3 value: 18.056
  - type: mrr_at_5 value: 19.406000000000002
  - type: ndcg_at_1 value: 15.0
  - type: ndcg_at_10 value: 21.775
  - type: ndcg_at_100 value: 26.8
  - type: ndcg_at_1000 value: 30.468
  - type: ndcg_at_3 value: 18.199
  - type: ndcg_at_5 value: 20.111
  - type: precision_at_1 value: 15.0
  - type: precision_at_10 value: 3.4000000000000004
  - type: precision_at_100 value: 0.607
  - type: precision_at_1000 value: 0.094
  - type: precision_at_3 value: 7.444000000000001
  - type: precision_at_5 value: 5.6000000000000005
  - type: recall_at_1 value: 14.194
  - type: recall_at_10 value: 30.0
  - type: recall_at_100 value: 53.911
  - type: recall_at_1000 value: 83.289
  - type: recall_at_3 value: 20.556
  - type: recall_at_5 value: 24.972
- task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics:
  - type: cos_sim_accuracy value: 99.35544554455446
  - type: cos_sim_ap value: 62.596006705300724
  - type: cos_sim_f1 value: 60.80283353010627
  - type: cos_sim_precision value: 74.20749279538906
  - type: cos_sim_recall value: 51.5
  - type: dot_accuracy value: 99.13564356435643
  - type: dot_ap value: 43.87589686325114
  - type: dot_f1 value: 46.99663623258049
  - type: dot_precision value: 45.235892691951896
  - type: dot_recall value: 48.9
  - type: euclidean_accuracy value: 99.2
  - type: euclidean_ap value: 43.44660755386079
  - type: euclidean_f1 value: 45.9016393442623
  - type: euclidean_precision value: 52.79583875162549
  - type: euclidean_recall value: 40.6
  - type: manhattan_accuracy value: 99.2
  - type: manhattan_ap value: 43.11790011749347
  - type: manhattan_f1 value: 45.11023176936122
  - type: manhattan_precision value: 51.88556566970091
  - type: manhattan_recall value: 39.900000000000006
  - type: max_accuracy value: 99.35544554455446
  - type: max_ap value: 62.596006705300724
  - type: max_f1 value: 60.80283353010627
- task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics:
  - type: v_measure value: 25.71674282500873
- task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics:
  - type: v_measure value: 25.465780711520985
- task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics:
  - type: map value: 35.35656209427094
  - type: mrr value: 35.10693860877685
- task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics:
  - type: map_at_1 value: 0.074
  - type: map_at_10 value: 0.47400000000000003
  - type: map_at_100 value: 1.825
  - type: map_at_1000 value: 4.056
  - type: map_at_3 value: 0.199
  - type: map_at_5 value: 0.301
  - type: mrr_at_1 value: 34.0
  - type: mrr_at_10 value: 46.06
  - type: mrr_at_100 value: 47.506
  - type: mrr_at_1000 value: 47.522999999999996
  - type: mrr_at_3 value: 44.0
  - type: mrr_at_5 value: 44.4
  - type: ndcg_at_1 value: 32.0
  - type: ndcg_at_10 value: 28.633999999999997
  - type: ndcg_at_100 value: 18.547
  - type: ndcg_at_1000 value: 16.142
  - type: ndcg_at_3 value: 32.48
  - type: ndcg_at_5 value: 31.163999999999998
  - type: precision_at_1 value: 34.0
  - type: precision_at_10 value: 30.4
  - type: precision_at_100 value: 18.54
  - type: precision_at_1000 value: 7.942
  - type: precision_at_3 value: 35.333
  - type: precision_at_5 value: 34.0
  - type: recall_at_1 value: 0.074
  - type: recall_at_10 value: 0.641
  - type: recall_at_100 value: 3.675
  - type: recall_at_1000 value: 15.706000000000001
  - type: recall_at_3 value: 0.231
  - type: recall_at_5 value: 0.367
- task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics:
  - type: map_at_1 value: 0.6799999999999999
  - type: map_at_10 value: 2.1420000000000003
  - type: map_at_100 value: 2.888
  - type: map_at_1000 value: 3.3779999999999997
  - type: map_at_3 value: 1.486
  - type: map_at_5 value: 1.7579999999999998
  - type: mrr_at_1 value: 12.245000000000001
  - type: mrr_at_10 value: 22.12
  - type: mrr_at_100 value: 23.407
  - type: mrr_at_1000 value: 23.483999999999998
  - type: mrr_at_3 value: 19.048000000000002
  - type: mrr_at_5 value: 20.986
  - type: ndcg_at_1 value: 10.204
  - type: ndcg_at_10 value: 7.374
  - type: ndcg_at_100 value: 10.524000000000001
  - type: ndcg_at_1000 value: 18.4
  - type: ndcg_at_3 value: 9.913
  - type: ndcg_at_5 value: 8.938
  - type: precision_at_1 value: 12.245000000000001
  - type: precision_at_10 value: 7.142999999999999
  - type: precision_at_100 value: 2.4490000000000003
  - type: precision_at_1000 value: 0.731
  - type: precision_at_3 value: 11.565
  - type: precision_at_5 value: 9.796000000000001
  - type: recall_at_1 value: 0.6799999999999999
  - type: recall_at_10 value: 4.038
  - type: recall_at_100 value: 14.151
  - type: recall_at_1000 value: 40.111999999999995
  - type: recall_at_3 value: 1.921
  - type: recall_at_5 value: 2.604
- task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics:
  - type: accuracy value: 54.625600000000006
  - type: ap value: 9.425323874806459
  - type: f1 value: 42.38724794017267
- task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics:
  - type: accuracy value: 42.8494623655914
  - type: f1 value: 42.66062148844617
- task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics:
  - type: v_measure value: 12.464890895237952
- task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics:
  - type: cos_sim_accuracy value: 79.97854205161829
  - type: cos_sim_ap value: 47.45175747605773
  - type: cos_sim_f1 value: 46.55775962660444
  - type: cos_sim_precision value: 41.73640167364017
  - type: cos_sim_recall value: 52.638522427440634
  - type: dot_accuracy value: 77.76718126005842
  - type: dot_ap value: 35.97737653101504
  - type: dot_f1 value: 41.1975475754439
  - type: dot_precision value: 29.50165355228646
  - type: dot_recall value: 68.25857519788919
  - type: euclidean_accuracy value: 79.34076414138403
  - type: euclidean_ap value: 45.309577778755134
  - type: euclidean_f1 value: 45.09938313913639
  - type: euclidean_precision value: 39.76631748589847
  - type: euclidean_recall value: 52.0844327176781
  - type: manhattan_accuracy value: 79.31692197651546
  - type: manhattan_ap value: 45.2433373222626
  - type: manhattan_f1 value: 45.04624986069319
  - type: manhattan_precision value: 38.99286127725256
  - type: manhattan_recall value: 53.324538258575195
  - type: max_accuracy value: 79.97854205161829
  - type: max_ap value: 47.45175747605773
  - type: max_f1 value: 46.55775962660444
- task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics:
  - type: cos_sim_accuracy value: 81.76737687740133
  - type: cos_sim_ap value: 64.59241956109807
  - type: cos_sim_f1 value: 57.83203629255339
  - type: cos_sim_precision value: 55.50442477876106
  - type: cos_sim_recall value: 60.363412380659064
  - type: dot_accuracy value: 78.96922420149805
  - type: dot_ap value: 56.11775087282065
  - type: dot_f1 value: 52.92134831460675
  - type: dot_precision value: 51.524212368728115
  - type: dot_recall value: 54.39636587619341
  - type: euclidean_accuracy value: 80.8611790274382
  - type: euclidean_ap value: 61.28070098354092
  - type: euclidean_f1 value: 54.58334971882497
  - type: euclidean_precision value: 55.783297162607504
  - type: euclidean_recall value: 53.43393902063443
  - type: manhattan_accuracy value: 80.72534637326814
  - type: manhattan_ap value: 61.18048430787254
  - type: manhattan_f1 value: 54.50978912822061
  - type: manhattan_precision value: 53.435396790178245
  - type: manhattan_recall value: 55.6282722513089
  - type: max_accuracy value: 81.76737687740133
  - type: max_ap value: 64.59241956109807
  - type: max_f1 value: 57.83203629255339