Name: BAAI/bge-large-en-v1.5
Author: BAAI

tags:

sentence-transformers
feature-extraction
sentence-similarity
transformers
mteb model-index:
name: bge-large-en-v1.5 results:
- task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
  - type: accuracy value: 75.8507462686567
  - type: ap value: 38.566457320228245
  - type: f1 value: 69.69386648043475
- task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics:
  - type: accuracy value: 92.416675
  - type: ap value: 89.1928861155922
  - type: f1 value: 92.39477019574215
- task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
  - type: accuracy value: 48.175999999999995
  - type: f1 value: 47.80712792870253
- task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics:
  - type: map_at_1 value: 40.184999999999995
  - type: map_at_10 value: 55.654
  - type: map_at_100 value: 56.25
  - type: map_at_1000 value: 56.255
  - type: map_at_3 value: 51.742999999999995
  - type: map_at_5 value: 54.129000000000005
  - type: mrr_at_1 value: 40.967
  - type: mrr_at_10 value: 55.96
  - type: mrr_at_100 value: 56.54900000000001
  - type: mrr_at_1000 value: 56.554
  - type: mrr_at_3 value: 51.980000000000004
  - type: mrr_at_5 value: 54.44
  - type: ndcg_at_1 value: 40.184999999999995
  - type: ndcg_at_10 value: 63.542
  - type: ndcg_at_100 value: 65.96499999999999
  - type: ndcg_at_1000 value: 66.08699999999999
  - type: ndcg_at_3 value: 55.582
  - type: ndcg_at_5 value: 59.855000000000004
  - type: precision_at_1 value: 40.184999999999995
  - type: precision_at_10 value: 8.841000000000001
  - type: precision_at_100 value: 0.987
  - type: precision_at_1000 value: 0.1
  - type: precision_at_3 value: 22.238
  - type: precision_at_5 value: 15.405
  - type: recall_at_1 value: 40.184999999999995
  - type: recall_at_10 value: 88.407
  - type: recall_at_100 value: 98.72
  - type: recall_at_1000 value: 99.644
  - type: recall_at_3 value: 66.714
  - type: recall_at_5 value: 77.027
- task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics:
  - type: v_measure value: 48.567077926750066
- task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics:
  - type: v_measure value: 43.19453389182364
- task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics:
  - type: map value: 64.46555939623092
  - type: mrr value: 77.82361605768807
- task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics:
  - type: cos_sim_pearson value: 84.9554128814735
  - type: cos_sim_spearman value: 84.65373612172036
  - type: euclidean_pearson value: 83.2905059954138
  - type: euclidean_spearman value: 84.52240782811128
  - type: manhattan_pearson value: 82.99533802997436
  - type: manhattan_spearman value: 84.20673798475734
- task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics:
  - type: accuracy value: 87.78896103896103
  - type: f1 value: 87.77189310964883
- task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics:
  - type: v_measure value: 39.714538337650495
- task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics:
  - type: v_measure value: 36.90108349284447
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 32.795
  - type: map_at_10 value: 43.669000000000004
  - type: map_at_100 value: 45.151
  - type: map_at_1000 value: 45.278
  - type: map_at_3 value: 40.006
  - type: map_at_5 value: 42.059999999999995
  - type: mrr_at_1 value: 39.771
  - type: mrr_at_10 value: 49.826
  - type: mrr_at_100 value: 50.504000000000005
  - type: mrr_at_1000 value: 50.549
  - type: mrr_at_3 value: 47.115
  - type: mrr_at_5 value: 48.832
  - type: ndcg_at_1 value: 39.771
  - type: ndcg_at_10 value: 50.217999999999996
  - type: ndcg_at_100 value: 55.454
  - type: ndcg_at_1000 value: 57.37
  - type: ndcg_at_3 value: 44.885000000000005
  - type: ndcg_at_5 value: 47.419
  - type: precision_at_1 value: 39.771
  - type: precision_at_10 value: 9.642000000000001
  - type: precision_at_100 value: 1.538
  - type: precision_at_1000 value: 0.198
  - type: precision_at_3 value: 21.268
  - type: precision_at_5 value: 15.536
  - type: recall_at_1 value: 32.795
  - type: recall_at_10 value: 62.580999999999996
  - type: recall_at_100 value: 84.438
  - type: recall_at_1000 value: 96.492
  - type: recall_at_3 value: 47.071000000000005
  - type: recall_at_5 value: 54.079
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 32.671
  - type: map_at_10 value: 43.334
  - type: map_at_100 value: 44.566
  - type: map_at_1000 value: 44.702999999999996
  - type: map_at_3 value: 40.343
  - type: map_at_5 value: 41.983
  - type: mrr_at_1 value: 40.764
  - type: mrr_at_10 value: 49.382
  - type: mrr_at_100 value: 49.988
  - type: mrr_at_1000 value: 50.03300000000001
  - type: mrr_at_3 value: 47.293
  - type: mrr_at_5 value: 48.51
  - type: ndcg_at_1 value: 40.764
  - type: ndcg_at_10 value: 49.039
  - type: ndcg_at_100 value: 53.259
  - type: ndcg_at_1000 value: 55.253
  - type: ndcg_at_3 value: 45.091
  - type: ndcg_at_5 value: 46.839999999999996
  - type: precision_at_1 value: 40.764
  - type: precision_at_10 value: 9.191
  - type: precision_at_100 value: 1.476
  - type: precision_at_1000 value: 0.19499999999999998
  - type: precision_at_3 value: 21.72
  - type: precision_at_5 value: 15.299
  - type: recall_at_1 value: 32.671
  - type: recall_at_10 value: 58.816
  - type: recall_at_100 value: 76.654
  - type: recall_at_1000 value: 89.05999999999999
  - type: recall_at_3 value: 46.743
  - type: recall_at_5 value: 51.783
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 40.328
  - type: map_at_10 value: 53.32599999999999
  - type: map_at_100 value: 54.37499999999999
  - type: map_at_1000 value: 54.429
  - type: map_at_3 value: 49.902
  - type: map_at_5 value: 52.002
  - type: mrr_at_1 value: 46.332
  - type: mrr_at_10 value: 56.858
  - type: mrr_at_100 value: 57.522
  - type: mrr_at_1000 value: 57.54899999999999
  - type: mrr_at_3 value: 54.472
  - type: mrr_at_5 value: 55.996
  - type: ndcg_at_1 value: 46.332
  - type: ndcg_at_10 value: 59.313
  - type: ndcg_at_100 value: 63.266999999999996
  - type: ndcg_at_1000 value: 64.36
  - type: ndcg_at_3 value: 53.815000000000005
  - type: ndcg_at_5 value: 56.814
  - type: precision_at_1 value: 46.332
  - type: precision_at_10 value: 9.53
  - type: precision_at_100 value: 1.238
  - type: precision_at_1000 value: 0.13699999999999998
  - type: precision_at_3 value: 24.054000000000002
  - type: precision_at_5 value: 16.589000000000002
  - type: recall_at_1 value: 40.328
  - type: recall_at_10 value: 73.421
  - type: recall_at_100 value: 90.059
  - type: recall_at_1000 value: 97.81
  - type: recall_at_3 value: 59.009
  - type: recall_at_5 value: 66.352
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 27.424
  - type: map_at_10 value: 36.332
  - type: map_at_100 value: 37.347
  - type: map_at_1000 value: 37.422
  - type: map_at_3 value: 33.743
  - type: map_at_5 value: 35.176
  - type: mrr_at_1 value: 29.153000000000002
  - type: mrr_at_10 value: 38.233
  - type: mrr_at_100 value: 39.109
  - type: mrr_at_1000 value: 39.164
  - type: mrr_at_3 value: 35.876000000000005
  - type: mrr_at_5 value: 37.169000000000004
  - type: ndcg_at_1 value: 29.153000000000002
  - type: ndcg_at_10 value: 41.439
  - type: ndcg_at_100 value: 46.42
  - type: ndcg_at_1000 value: 48.242000000000004
  - type: ndcg_at_3 value: 36.362
  - type: ndcg_at_5 value: 38.743
  - type: precision_at_1 value: 29.153000000000002
  - type: precision_at_10 value: 6.315999999999999
  - type: precision_at_100 value: 0.927
  - type: precision_at_1000 value: 0.11199999999999999
  - type: precision_at_3 value: 15.443000000000001
  - type: precision_at_5 value: 10.644
  - type: recall_at_1 value: 27.424
  - type: recall_at_10 value: 55.364000000000004
  - type: recall_at_100 value: 78.211
  - type: recall_at_1000 value: 91.74600000000001
  - type: recall_at_3 value: 41.379
  - type: recall_at_5 value: 47.14
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 19.601
  - type: map_at_10 value: 27.826
  - type: map_at_100 value: 29.017
  - type: map_at_1000 value: 29.137
  - type: map_at_3 value: 25.125999999999998
  - type: map_at_5 value: 26.765
  - type: mrr_at_1 value: 24.005000000000003
  - type: mrr_at_10 value: 32.716
  - type: mrr_at_100 value: 33.631
  - type: mrr_at_1000 value: 33.694
  - type: mrr_at_3 value: 29.934
  - type: mrr_at_5 value: 31.630999999999997
  - type: ndcg_at_1 value: 24.005000000000003
  - type: ndcg_at_10 value: 33.158
  - type: ndcg_at_100 value: 38.739000000000004
  - type: ndcg_at_1000 value: 41.495
  - type: ndcg_at_3 value: 28.185
  - type: ndcg_at_5 value: 30.796
  - type: precision_at_1 value: 24.005000000000003
  - type: precision_at_10 value: 5.908
  - type: precision_at_100 value: 1.005
  - type: precision_at_1000 value: 0.13899999999999998
  - type: precision_at_3 value: 13.391
  - type: precision_at_5 value: 9.876
  - type: recall_at_1 value: 19.601
  - type: recall_at_10 value: 44.746
  - type: recall_at_100 value: 68.82300000000001
  - type: recall_at_1000 value: 88.215
  - type: recall_at_3 value: 31.239
  - type: recall_at_5 value: 37.695
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 30.130000000000003
  - type: map_at_10 value: 40.96
  - type: map_at_100 value: 42.282
  - type: map_at_1000 value: 42.392
  - type: map_at_3 value: 37.889
  - type: map_at_5 value: 39.661
  - type: mrr_at_1 value: 36.958999999999996
  - type: mrr_at_10 value: 46.835
  - type: mrr_at_100 value: 47.644
  - type: mrr_at_1000 value: 47.688
  - type: mrr_at_3 value: 44.562000000000005
  - type: mrr_at_5 value: 45.938
  - type: ndcg_at_1 value: 36.958999999999996
  - type: ndcg_at_10 value: 47.06
  - type: ndcg_at_100 value: 52.345
  - type: ndcg_at_1000 value: 54.35
  - type: ndcg_at_3 value: 42.301
  - type: ndcg_at_5 value: 44.635999999999996
  - type: precision_at_1 value: 36.958999999999996
  - type: precision_at_10 value: 8.479000000000001
  - type: precision_at_100 value: 1.284
  - type: precision_at_1000 value: 0.163
  - type: precision_at_3 value: 20.244
  - type: precision_at_5 value: 14.224999999999998
  - type: recall_at_1 value: 30.130000000000003
  - type: recall_at_10 value: 59.27
  - type: recall_at_100 value: 81.195
  - type: recall_at_1000 value: 94.21199999999999
  - type: recall_at_3 value: 45.885
  - type: recall_at_5 value: 52.016
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 26.169999999999998
  - type: map_at_10 value: 36.451
  - type: map_at_100 value: 37.791000000000004
  - type: map_at_1000 value: 37.897
  - type: map_at_3 value: 33.109
  - type: map_at_5 value: 34.937000000000005
  - type: mrr_at_1 value: 32.877
  - type: mrr_at_10 value: 42.368
  - type: mrr_at_100 value: 43.201
  - type: mrr_at_1000 value: 43.259
  - type: mrr_at_3 value: 39.763999999999996
  - type: mrr_at_5 value: 41.260000000000005
  - type: ndcg_at_1 value: 32.877
  - type: ndcg_at_10 value: 42.659000000000006
  - type: ndcg_at_100 value: 48.161
  - type: ndcg_at_1000 value: 50.345
  - type: ndcg_at_3 value: 37.302
  - type: ndcg_at_5 value: 39.722
  - type: precision_at_1 value: 32.877
  - type: precision_at_10 value: 7.9
  - type: precision_at_100 value: 1.236
  - type: precision_at_1000 value: 0.158
  - type: precision_at_3 value: 17.846
  - type: precision_at_5 value: 12.9
  - type: recall_at_1 value: 26.169999999999998
  - type: recall_at_10 value: 55.35
  - type: recall_at_100 value: 78.755
  - type: recall_at_1000 value: 93.518
  - type: recall_at_3 value: 40.176
  - type: recall_at_5 value: 46.589000000000006
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 27.15516666666667
  - type: map_at_10 value: 36.65741666666667
  - type: map_at_100 value: 37.84991666666666
  - type: map_at_1000 value: 37.96316666666667
  - type: map_at_3 value: 33.74974999999999
  - type: map_at_5 value: 35.3765
  - type: mrr_at_1 value: 32.08233333333334
  - type: mrr_at_10 value: 41.033833333333334
  - type: mrr_at_100 value: 41.84524999999999
  - type: mrr_at_1000 value: 41.89983333333333
  - type: mrr_at_3 value: 38.62008333333333
  - type: mrr_at_5 value: 40.03441666666666
  - type: ndcg_at_1 value: 32.08233333333334
  - type: ndcg_at_10 value: 42.229
  - type: ndcg_at_100 value: 47.26716666666667
  - type: ndcg_at_1000 value: 49.43466666666667
  - type: ndcg_at_3 value: 37.36408333333333
  - type: ndcg_at_5 value: 39.6715
  - type: precision_at_1 value: 32.08233333333334
  - type: precision_at_10 value: 7.382583333333334
  - type: precision_at_100 value: 1.16625
  - type: precision_at_1000 value: 0.15408333333333332
  - type: precision_at_3 value: 17.218
  - type: precision_at_5 value: 12.21875
  - type: recall_at_1 value: 27.15516666666667
  - type: recall_at_10 value: 54.36683333333333
  - type: recall_at_100 value: 76.37183333333333
  - type: recall_at_1000 value: 91.26183333333333
  - type: recall_at_3 value: 40.769916666666674
  - type: recall_at_5 value: 46.702333333333335
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 25.749
  - type: map_at_10 value: 33.001999999999995
  - type: map_at_100 value: 33.891
  - type: map_at_1000 value: 33.993
  - type: map_at_3 value: 30.703999999999997
  - type: map_at_5 value: 31.959
  - type: mrr_at_1 value: 28.834
  - type: mrr_at_10 value: 35.955
  - type: mrr_at_100 value: 36.709
  - type: mrr_at_1000 value: 36.779
  - type: mrr_at_3 value: 33.947
  - type: mrr_at_5 value: 35.089
  - type: ndcg_at_1 value: 28.834
  - type: ndcg_at_10 value: 37.329
  - type: ndcg_at_100 value: 41.79
  - type: ndcg_at_1000 value: 44.169000000000004
  - type: ndcg_at_3 value: 33.184999999999995
  - type: ndcg_at_5 value: 35.107
  - type: precision_at_1 value: 28.834
  - type: precision_at_10 value: 5.7669999999999995
  - type: precision_at_100 value: 0.876
  - type: precision_at_1000 value: 0.11399999999999999
  - type: precision_at_3 value: 14.213000000000001
  - type: precision_at_5 value: 9.754999999999999
  - type: recall_at_1 value: 25.749
  - type: recall_at_10 value: 47.791
  - type: recall_at_100 value: 68.255
  - type: recall_at_1000 value: 85.749
  - type: recall_at_3 value: 36.199
  - type: recall_at_5 value: 41.071999999999996
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 17.777
  - type: map_at_10 value: 25.201
  - type: map_at_100 value: 26.423999999999996
  - type: map_at_1000 value: 26.544
  - type: map_at_3 value: 22.869
  - type: map_at_5 value: 24.023
  - type: mrr_at_1 value: 21.473
  - type: mrr_at_10 value: 29.12
  - type: mrr_at_100 value: 30.144
  - type: mrr_at_1000 value: 30.215999999999998
  - type: mrr_at_3 value: 26.933
  - type: mrr_at_5 value: 28.051
  - type: ndcg_at_1 value: 21.473
  - type: ndcg_at_10 value: 30.003
  - type: ndcg_at_100 value: 35.766
  - type: ndcg_at_1000 value: 38.501000000000005
  - type: ndcg_at_3 value: 25.773000000000003
  - type: ndcg_at_5 value: 27.462999999999997
  - type: precision_at_1 value: 21.473
  - type: precision_at_10 value: 5.482
  - type: precision_at_100 value: 0.975
  - type: precision_at_1000 value: 0.13799999999999998
  - type: precision_at_3 value: 12.205
  - type: precision_at_5 value: 8.692
  - type: recall_at_1 value: 17.777
  - type: recall_at_10 value: 40.582
  - type: recall_at_100 value: 66.305
  - type: recall_at_1000 value: 85.636
  - type: recall_at_3 value: 28.687
  - type: recall_at_5 value: 33.089
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 26.677
  - type: map_at_10 value: 36.309000000000005
  - type: map_at_100 value: 37.403999999999996
  - type: map_at_1000 value: 37.496
  - type: map_at_3 value: 33.382
  - type: map_at_5 value: 34.98
  - type: mrr_at_1 value: 31.343
  - type: mrr_at_10 value: 40.549
  - type: mrr_at_100 value: 41.342
  - type: mrr_at_1000 value: 41.397
  - type: mrr_at_3 value: 38.029
  - type: mrr_at_5 value: 39.451
  - type: ndcg_at_1 value: 31.343
  - type: ndcg_at_10 value: 42.1
  - type: ndcg_at_100 value: 47.089999999999996
  - type: ndcg_at_1000 value: 49.222
  - type: ndcg_at_3 value: 36.836999999999996
  - type: ndcg_at_5 value: 39.21
  - type: precision_at_1 value: 31.343
  - type: precision_at_10 value: 7.164
  - type: precision_at_100 value: 1.0959999999999999
  - type: precision_at_1000 value: 0.13899999999999998
  - type: precision_at_3 value: 16.915
  - type: precision_at_5 value: 11.940000000000001
  - type: recall_at_1 value: 26.677
  - type: recall_at_10 value: 55.54599999999999
  - type: recall_at_100 value: 77.094
  - type: recall_at_1000 value: 92.01
  - type: recall_at_3 value: 41.191
  - type: recall_at_5 value: 47.006
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 24.501
  - type: map_at_10 value: 33.102
  - type: map_at_100 value: 34.676
  - type: map_at_1000 value: 34.888000000000005
  - type: map_at_3 value: 29.944
  - type: map_at_5 value: 31.613999999999997
  - type: mrr_at_1 value: 29.447000000000003
  - type: mrr_at_10 value: 37.996
  - type: mrr_at_100 value: 38.946
  - type: mrr_at_1000 value: 38.995000000000005
  - type: mrr_at_3 value: 35.079
  - type: mrr_at_5 value: 36.69
  - type: ndcg_at_1 value: 29.447000000000003
  - type: ndcg_at_10 value: 39.232
  - type: ndcg_at_100 value: 45.247
  - type: ndcg_at_1000 value: 47.613
  - type: ndcg_at_3 value: 33.922999999999995
  - type: ndcg_at_5 value: 36.284
  - type: precision_at_1 value: 29.447000000000003
  - type: precision_at_10 value: 7.648000000000001
  - type: precision_at_100 value: 1.516
  - type: precision_at_1000 value: 0.23900000000000002
  - type: precision_at_3 value: 16.008
  - type: precision_at_5 value: 11.779
  - type: recall_at_1 value: 24.501
  - type: recall_at_10 value: 51.18899999999999
  - type: recall_at_100 value: 78.437
  - type: recall_at_1000 value: 92.842
  - type: recall_at_3 value: 35.808
  - type: recall_at_5 value: 42.197
- task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 22.039
  - type: map_at_10 value: 30.377
  - type: map_at_100 value: 31.275
  - type: map_at_1000 value: 31.379
  - type: map_at_3 value: 27.98
  - type: map_at_5 value: 29.358
  - type: mrr_at_1 value: 24.03
  - type: mrr_at_10 value: 32.568000000000005
  - type: mrr_at_100 value: 33.403
  - type: mrr_at_1000 value: 33.475
  - type: mrr_at_3 value: 30.436999999999998
  - type: mrr_at_5 value: 31.796000000000003
  - type: ndcg_at_1 value: 24.03
  - type: ndcg_at_10 value: 35.198
  - type: ndcg_at_100 value: 39.668
  - type: ndcg_at_1000 value: 42.296
  - type: ndcg_at_3 value: 30.709999999999997
  - type: ndcg_at_5 value: 33.024
  - type: precision_at_1 value: 24.03
  - type: precision_at_10 value: 5.564
  - type: precision_at_100 value: 0.828
  - type: precision_at_1000 value: 0.117
  - type: precision_at_3 value: 13.309000000000001
  - type: precision_at_5 value: 9.39
  - type: recall_at_1 value: 22.039
  - type: recall_at_10 value: 47.746
  - type: recall_at_100 value: 68.23599999999999
  - type: recall_at_1000 value: 87.852
  - type: recall_at_3 value: 35.852000000000004
  - type: recall_at_5 value: 41.410000000000004
- task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics:
  - type: map_at_1 value: 15.692999999999998
  - type: map_at_10 value: 26.903
  - type: map_at_100 value: 28.987000000000002
  - type: map_at_1000 value: 29.176999999999996
  - type: map_at_3 value: 22.137
  - type: map_at_5 value: 24.758
  - type: mrr_at_1 value: 35.57
  - type: mrr_at_10 value: 47.821999999999996
  - type: mrr_at_100 value: 48.608000000000004
  - type: mrr_at_1000 value: 48.638999999999996
  - type: mrr_at_3 value: 44.452000000000005
  - type: mrr_at_5 value: 46.546
  - type: ndcg_at_1 value: 35.57
  - type: ndcg_at_10 value: 36.567
  - type: ndcg_at_100 value: 44.085
  - type: ndcg_at_1000 value: 47.24
  - type: ndcg_at_3 value: 29.964000000000002
  - type: ndcg_at_5 value: 32.511
  - type: precision_at_1 value: 35.57
  - type: precision_at_10 value: 11.485
  - type: precision_at_100 value: 1.9619999999999997
  - type: precision_at_1000 value: 0.256
  - type: precision_at_3 value: 22.237000000000002
  - type: precision_at_5 value: 17.471999999999998
  - type: recall_at_1 value: 15.692999999999998
  - type: recall_at_10 value: 43.056
  - type: recall_at_100 value: 68.628
  - type: recall_at_1000 value: 86.075
  - type: recall_at_3 value: 26.918999999999997
  - type: recall_at_5 value: 34.14
- task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics:
  - type: map_at_1 value: 9.53
  - type: map_at_10 value: 20.951
  - type: map_at_100 value: 30.136000000000003
  - type: map_at_1000 value: 31.801000000000002
  - type: map_at_3 value: 15.021
  - type: map_at_5 value: 17.471999999999998
  - type: mrr_at_1 value: 71.0
  - type: mrr_at_10 value: 79.176
  - type: mrr_at_100 value: 79.418
  - type: mrr_at_1000 value: 79.426
  - type: mrr_at_3 value: 78.125
  - type: mrr_at_5 value: 78.61200000000001
  - type: ndcg_at_1 value: 58.5
  - type: ndcg_at_10 value: 44.106
  - type: ndcg_at_100 value: 49.268
  - type: ndcg_at_1000 value: 56.711999999999996
  - type: ndcg_at_3 value: 48.934
  - type: ndcg_at_5 value: 45.826
  - type: precision_at_1 value: 71.0
  - type: precision_at_10 value: 35.0
  - type: precision_at_100 value: 11.360000000000001
  - type: precision_at_1000 value: 2.046
  - type: precision_at_3 value: 52.833
  - type: precision_at_5 value: 44.15
  - type: recall_at_1 value: 9.53
  - type: recall_at_10 value: 26.811
  - type: recall_at_100 value: 55.916999999999994
  - type: recall_at_1000 value: 79.973
  - type: recall_at_3 value: 16.413
  - type: recall_at_5 value: 19.980999999999998
- task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics:
  - type: accuracy value: 51.519999999999996
  - type: f1 value: 46.36601294761231
- task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics:
  - type: map_at_1 value: 74.413
  - type: map_at_10 value: 83.414
  - type: map_at_100 value: 83.621
  - type: map_at_1000 value: 83.635
  - type: map_at_3 value: 82.337
  - type: map_at_5 value: 83.039
  - type: mrr_at_1 value: 80.19800000000001
  - type: mrr_at_10 value: 87.715
  - type: mrr_at_100 value: 87.778
  - type: mrr_at_1000 value: 87.779
  - type: mrr_at_3 value: 87.106
  - type: mrr_at_5 value: 87.555
  - type: ndcg_at_1 value: 80.19800000000001
  - type: ndcg_at_10 value: 87.182
  - type: ndcg_at_100 value: 87.90299999999999
  - type: ndcg_at_1000 value: 88.143
  - type: ndcg_at_3 value: 85.60600000000001
  - type: ndcg_at_5 value: 86.541
  - type: precision_at_1 value: 80.19800000000001
  - type: precision_at_10 value: 10.531
  - type: precision_at_100 value: 1.113
  - type: precision_at_1000 value: 0.11499999999999999
  - type: precision_at_3 value: 32.933
  - type: precision_at_5 value: 20.429
  - type: recall_at_1 value: 74.413
  - type: recall_at_10 value: 94.363
  - type: recall_at_100 value: 97.165
  - type: recall_at_1000 value: 98.668
  - type: recall_at_3 value: 90.108
  - type: recall_at_5 value: 92.52
- task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics:
  - type: map_at_1 value: 22.701
  - type: map_at_10 value: 37.122
  - type: map_at_100 value: 39.178000000000004
  - type: map_at_1000 value: 39.326
  - type: map_at_3 value: 32.971000000000004
  - type: map_at_5 value: 35.332
  - type: mrr_at_1 value: 44.753
  - type: mrr_at_10 value: 53.452
  - type: mrr_at_100 value: 54.198
  - type: mrr_at_1000 value: 54.225
  - type: mrr_at_3 value: 50.952
  - type: mrr_at_5 value: 52.464
  - type: ndcg_at_1 value: 44.753
  - type: ndcg_at_10 value: 45.021
  - type: ndcg_at_100 value: 52.028
  - type: ndcg_at_1000 value: 54.596000000000004
  - type: ndcg_at_3 value: 41.622
  - type: ndcg_at_5 value: 42.736000000000004
  - type: precision_at_1 value: 44.753
  - type: precision_at_10 value: 12.284
  - type: precision_at_100 value: 1.955
  - type: precision_at_1000 value: 0.243
  - type: precision_at_3 value: 27.828999999999997
  - type: precision_at_5 value: 20.061999999999998
  - type: recall_at_1 value: 22.701
  - type: recall_at_10 value: 51.432
  - type: recall_at_100 value: 77.009
  - type: recall_at_1000 value: 92.511
  - type: recall_at_3 value: 37.919000000000004
  - type: recall_at_5 value: 44.131
- task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics:
  - type: map_at_1 value: 40.189
  - type: map_at_10 value: 66.24600000000001
  - type: map_at_100 value: 67.098
  - type: map_at_1000 value: 67.149
  - type: map_at_3 value: 62.684
  - type: map_at_5 value: 64.974
  - type: mrr_at_1 value: 80.378
  - type: mrr_at_10 value: 86.127
  - type: mrr_at_100 value: 86.29299999999999
  - type: mrr_at_1000 value: 86.297
  - type: mrr_at_3 value: 85.31400000000001
  - type: mrr_at_5 value: 85.858
  - type: ndcg_at_1 value: 80.378
  - type: ndcg_at_10 value: 74.101
  - type: ndcg_at_100 value: 76.993
  - type: ndcg_at_1000 value: 77.948
  - type: ndcg_at_3 value: 69.232
  - type: ndcg_at_5 value: 72.04599999999999
  - type: precision_at_1 value: 80.378
  - type: precision_at_10 value: 15.595999999999998
  - type: precision_at_100 value: 1.7840000000000003
  - type: precision_at_1000 value: 0.191
  - type: precision_at_3 value: 44.884
  - type: precision_at_5 value: 29.145
  - type: recall_at_1 value: 40.189
  - type: recall_at_10 value: 77.981
  - type: recall_at_100 value: 89.21
  - type: recall_at_1000 value: 95.48299999999999
  - type: recall_at_3 value: 67.326
  - type: recall_at_5 value: 72.863
- task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics:
  - type: accuracy value: 92.84599999999999
  - type: ap value: 89.4710787567357
  - type: f1 value: 92.83752676932258
- task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics:
  - type: map_at_1 value: 23.132
  - type: map_at_10 value: 35.543
  - type: map_at_100 value: 36.702
  - type: map_at_1000 value: 36.748999999999995
  - type: map_at_3 value: 31.737
  - type: map_at_5 value: 33.927
  - type: mrr_at_1 value: 23.782
  - type: mrr_at_10 value: 36.204
  - type: mrr_at_100 value: 37.29
  - type: mrr_at_1000 value: 37.330999999999996
  - type: mrr_at_3 value: 32.458999999999996
  - type: mrr_at_5 value: 34.631
  - type: ndcg_at_1 value: 23.782
  - type: ndcg_at_10 value: 42.492999999999995
  - type: ndcg_at_100 value: 47.985
  - type: ndcg_at_1000 value: 49.141
  - type: ndcg_at_3 value: 34.748000000000005
  - type: ndcg_at_5 value: 38.651
  - type: precision_at_1 value: 23.782
  - type: precision_at_10 value: 6.665
  - type: precision_at_100 value: 0.941
  - type: precision_at_1000 value: 0.104
  - type: precision_at_3 value: 14.776
  - type: precision_at_5 value: 10.84
  - type: recall_at_1 value: 23.132
  - type: recall_at_10 value: 63.794
  - type: recall_at_100 value: 89.027
  - type: recall_at_1000 value: 97.807
  - type: recall_at_3 value: 42.765
  - type: recall_at_5 value: 52.11
- task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
  - type: accuracy value: 94.59188326493388
  - type: f1 value: 94.3842594786827
- task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
  - type: accuracy value: 79.49384404924761
  - type: f1 value: 59.7580539534629
- task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
  - type: accuracy value: 77.56220578345663
  - type: f1 value: 75.27228165561478
- task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
  - type: accuracy value: 80.53463349024884
  - type: f1 value: 80.4893958236536
- task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics:
  - type: v_measure value: 32.56100273484962
- task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics:
  - type: v_measure value: 31.470380028839607
- task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics:
  - type: map value: 32.06102792457849
  - type: mrr value: 33.30709199672238
- task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics:
  - type: map_at_1 value: 6.776999999999999
  - type: map_at_10 value: 14.924000000000001
  - type: map_at_100 value: 18.955
  - type: map_at_1000 value: 20.538999999999998
  - type: map_at_3 value: 10.982
  - type: map_at_5 value: 12.679000000000002
  - type: mrr_at_1 value: 47.988
  - type: mrr_at_10 value: 57.232000000000006
  - type: mrr_at_100 value: 57.818999999999996
  - type: mrr_at_1000 value: 57.847
  - type: mrr_at_3 value: 54.901999999999994
  - type: mrr_at_5 value: 56.481
  - type: ndcg_at_1 value: 46.594
  - type: ndcg_at_10 value: 38.129000000000005
  - type: ndcg_at_100 value: 35.54
  - type: ndcg_at_1000 value: 44.172
  - type: ndcg_at_3 value: 43.025999999999996
  - type: ndcg_at_5 value: 41.052
  - type: precision_at_1 value: 47.988
  - type: precision_at_10 value: 28.111000000000004
  - type: precision_at_100 value: 8.929
  - type: precision_at_1000 value: 2.185
  - type: precision_at_3 value: 40.144000000000005
  - type: precision_at_5 value: 35.232
  - type: recall_at_1 value: 6.776999999999999
  - type: recall_at_10 value: 19.289
  - type: recall_at_100 value: 36.359
  - type: recall_at_1000 value: 67.54
  - type: recall_at_3 value: 11.869
  - type: recall_at_5 value: 14.999
- task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics:
  - type: map_at_1 value: 31.108000000000004
  - type: map_at_10 value: 47.126000000000005
  - type: map_at_100 value: 48.171
  - type: map_at_1000 value: 48.199
  - type: map_at_3 value: 42.734
  - type: map_at_5 value: 45.362
  - type: mrr_at_1 value: 34.936
  - type: mrr_at_10 value: 49.571
  - type: mrr_at_100 value: 50.345
  - type: mrr_at_1000 value: 50.363
  - type: mrr_at_3 value: 45.959
  - type: mrr_at_5 value: 48.165
  - type: ndcg_at_1 value: 34.936
  - type: ndcg_at_10 value: 55.028999999999996
  - type: ndcg_at_100 value: 59.244
  - type: ndcg_at_1000 value: 59.861
  - type: ndcg_at_3 value: 46.872
  - type: ndcg_at_5 value: 51.217999999999996
  - type: precision_at_1 value: 34.936
  - type: precision_at_10 value: 9.099
  - type: precision_at_100 value: 1.145
  - type: precision_at_1000 value: 0.12
  - type: precision_at_3 value: 21.456
  - type: precision_at_5 value: 15.411
  - type: recall_at_1 value: 31.108000000000004
  - type: recall_at_10 value: 76.53999999999999
  - type: recall_at_100 value: 94.39
  - type: recall_at_1000 value: 98.947
  - type: recall_at_3 value: 55.572
  - type: recall_at_5 value: 65.525
- task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics:
  - type: map_at_1 value: 71.56400000000001
  - type: map_at_10 value: 85.482
  - type: map_at_100 value: 86.114
  - type: map_at_1000 value: 86.13
  - type: map_at_3 value: 82.607
  - type: map_at_5 value: 84.405
  - type: mrr_at_1 value: 82.42
  - type: mrr_at_10 value: 88.304
  - type: mrr_at_100 value: 88.399
  - type: mrr_at_1000 value: 88.399
  - type: mrr_at_3 value: 87.37
  - type: mrr_at_5 value: 88.024
  - type: ndcg_at_1 value: 82.45
  - type: ndcg_at_10 value: 89.06500000000001
  - type: ndcg_at_100 value: 90.232
  - type: ndcg_at_1000 value: 90.305
  - type: ndcg_at_3 value: 86.375
  - type: ndcg_at_5 value: 87.85300000000001
  - type: precision_at_1 value: 82.45
  - type: precision_at_10 value: 13.486999999999998
  - type: precision_at_100 value: 1.534
  - type: precision_at_1000 value: 0.157
  - type: precision_at_3 value: 37.813
  - type: precision_at_5 value: 24.773999999999997
  - type: recall_at_1 value: 71.56400000000001
  - type: recall_at_10 value: 95.812
  - type: recall_at_100 value: 99.7
  - type: recall_at_1000 value: 99.979
  - type: recall_at_3 value: 87.966
  - type: recall_at_5 value: 92.268
- task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics:
  - type: v_measure value: 57.241876648614145
- task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics:
  - type: v_measure value: 64.66212576446223
- task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics:
  - type: map_at_1 value: 5.308
  - type: map_at_10 value: 13.803
  - type: map_at_100 value: 16.176
  - type: map_at_1000 value: 16.561
  - type: map_at_3 value: 9.761000000000001
  - type: map_at_5 value: 11.802
  - type: mrr_at_1 value: 26.200000000000003
  - type: mrr_at_10 value: 37.621
  - type: mrr_at_100 value: 38.767
  - type: mrr_at_1000 value: 38.815
  - type: mrr_at_3 value: 34.117
  - type: mrr_at_5 value: 36.107
  - type: ndcg_at_1 value: 26.200000000000003
  - type: ndcg_at_10 value: 22.64
  - type: ndcg_at_100 value: 31.567
  - type: ndcg_at_1000 value: 37.623
  - type: ndcg_at_3 value: 21.435000000000002
  - type: ndcg_at_5 value: 18.87
  - type: precision_at_1 value: 26.200000000000003
  - type: precision_at_10 value: 11.74
  - type: precision_at_100 value: 2.465
  - type: precision_at_1000 value: 0.391
  - type: precision_at_3 value: 20.033
  - type: precision_at_5 value: 16.64
  - type: recall_at_1 value: 5.308
  - type: recall_at_10 value: 23.794999999999998
  - type: recall_at_100 value: 50.015
  - type: recall_at_1000 value: 79.283
  - type: recall_at_3 value: 12.178
  - type: recall_at_5 value: 16.882
- task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics:
  - type: cos_sim_pearson value: 84.93231134675553
  - type: cos_sim_spearman value: 81.68319292603205
  - type: euclidean_pearson value: 81.8396814380367
  - type: euclidean_spearman value: 81.24641903349945
  - type: manhattan_pearson value: 81.84698799204274
  - type: manhattan_spearman value: 81.24269997904105
- task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics:
  - type: cos_sim_pearson value: 86.73241671587446
  - type: cos_sim_spearman value: 79.05091082971826
  - type: euclidean_pearson value: 83.91146869578044
  - type: euclidean_spearman value: 79.87978465370936
  - type: manhattan_pearson value: 83.90888338917678
  - type: manhattan_spearman value: 79.87482848584241
- task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics:
  - type: cos_sim_pearson value: 85.14970731146177
  - type: cos_sim_spearman value: 86.37363490084627
  - type: euclidean_pearson value: 83.02154218530433
  - type: euclidean_spearman value: 83.80258761957367
  - type: manhattan_pearson value: 83.01664495119347
  - type: manhattan_spearman value: 83.77567458007952
- task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics:
  - type: cos_sim_pearson value: 83.40474139886784
  - type: cos_sim_spearman value: 82.77768789165984
  - type: euclidean_pearson value: 80.7065877443695
  - type: euclidean_spearman value: 81.375940662505
  - type: manhattan_pearson value: 80.6507552270278
  - type: manhattan_spearman value: 81.32782179098741
- task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics:
  - type: cos_sim_pearson value: 87.08585968722274
  - type: cos_sim_spearman value: 88.03110031451399
  - type: euclidean_pearson value: 85.74012019602384
  - type: euclidean_spearman value: 86.13592849438209
  - type: manhattan_pearson value: 85.74404842369206
  - type: manhattan_spearman value: 86.14492318960154
- task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics:
  - type: cos_sim_pearson value: 84.95069052788875
  - type: cos_sim_spearman value: 86.4867991595147
  - type: euclidean_pearson value: 84.31013325754635
  - type: euclidean_spearman value: 85.01529258006482
  - type: manhattan_pearson value: 84.26995570085374
  - type: manhattan_spearman value: 84.96982104986162
- task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
  - type: cos_sim_pearson value: 87.54617647971897
  - type: cos_sim_spearman value: 87.49834181751034
  - type: euclidean_pearson value: 86.01015322577122
  - type: euclidean_spearman value: 84.63362652063199
  - type: manhattan_pearson value: 86.13807574475706
  - type: manhattan_spearman value: 84.7772370721132
- 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: 67.20047755786615
  - type: cos_sim_spearman value: 67.05324077987636
  - type: euclidean_pearson value: 66.91930642976601
  - type: euclidean_spearman value: 65.21491856099105
  - type: manhattan_pearson value: 66.78756851976624
  - type: manhattan_spearman value: 65.12356257740728
- task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics:
  - type: cos_sim_pearson value: 86.19852871539686
  - type: cos_sim_spearman value: 87.5161895296395
  - type: euclidean_pearson value: 84.59848645207485
  - type: euclidean_spearman value: 85.26427328757919
  - type: manhattan_pearson value: 84.59747366996524
  - type: manhattan_spearman value: 85.24045855146915
- task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics:
  - type: map value: 87.63320317811032
  - type: mrr value: 96.26242947321379
- task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics:
  - type: map_at_1 value: 60.928000000000004
  - type: map_at_10 value: 70.112
  - type: map_at_100 value: 70.5929

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BAAI/bge-large-en-v1.5

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