sentence-transformers bert feature-extraction sentence-similarity transformers mteb inferentia2 neuron en license:mit model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
language:
- en
license: mit
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- mteb
- inferentia2
- neuron
model-index:
- name: bge-base-en-v1.5
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 76.14925373134328
    - type: ap
      value: 39.32336517995478
    - type: f1
      value: 70.16902252611425
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.386825
    - type: ap
      value: 90.21276917991995
    - type: f1
      value: 93.37741030006174
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.846000000000004
    - type: f1
      value: 48.14646269778261
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.754000000000005
    - type: map_at_10
      value: 55.761
    - type: map_at_100
      value: 56.330999999999996
    - type: map_at_1000
      value: 56.333999999999996
    - type: map_at_3
      value: 51.92
    - type: map_at_5
      value: 54.010999999999996
    - type: mrr_at_1
      value: 41.181
    - type: mrr_at_10
      value: 55.967999999999996
    - type: mrr_at_100
      value: 56.538
    - type: mrr_at_1000
      value: 56.542
    - type: mrr_at_3
      value: 51.980000000000004
    - type: mrr_at_5
      value: 54.208999999999996
    - type: ndcg_at_1
      value: 40.754000000000005
    - type: ndcg_at_10
      value: 63.605000000000004
    - type: ndcg_at_100
      value: 66.05199999999999
    - type: ndcg_at_1000
      value: 66.12
    - type: ndcg_at_3
      value: 55.708
    - type: ndcg_at_5
      value: 59.452000000000005
    - type: precision_at_1
      value: 40.754000000000005
    - type: precision_at_10
      value: 8.841000000000001
    - type: precision_at_100
      value: 0.991
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 22.238
    - type: precision_at_5
      value: 15.149000000000001
    - type: recall_at_1
      value: 40.754000000000005
    - type: recall_at_10
      value: 88.407
    - type: recall_at_100
      value: 99.14699999999999
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 66.714
    - type: recall_at_5
      value: 75.747
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 48.74884539679369
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 42.8075893810716
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 62.128470519187736
    - type: mrr
      value: 74.28065778481289
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 89.24629081484655
    - type: cos_sim_spearman
      value: 86.93752309911496
    - type: euclidean_pearson
      value: 87.58589628573816
    - type: euclidean_spearman
      value: 88.05622328825284
    - type: manhattan_pearson
      value: 87.5594959805773
    - type: manhattan_spearman
      value: 88.19658793233961
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 86.9512987012987
    - type: f1
      value: 86.92515357973708
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.10263762928872
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 36.69711517426737
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 32.327
    - type: map_at_10
      value: 44.099
    - type: map_at_100
      value: 45.525
    - type: map_at_1000
      value: 45.641999999999996
    - type: map_at_3
      value: 40.47
    - type: map_at_5
      value: 42.36
    - type: mrr_at_1
      value: 39.199
    - type: mrr_at_10
      value: 49.651
    - type: mrr_at_100
      value: 50.29
    - type: mrr_at_1000
      value: 50.329
    - type: mrr_at_3
      value: 46.924
    - type: mrr_at_5
      value: 48.548
    - type: ndcg_at_1
      value: 39.199
    - type: ndcg_at_10
      value: 50.773
    - type: ndcg_at_100
      value: 55.67999999999999
    - type: ndcg_at_1000
      value: 57.495
    - type: ndcg_at_3
      value: 45.513999999999996
    - type: ndcg_at_5
      value: 47.703
    - type: precision_at_1
      value: 39.199
    - type: precision_at_10
      value: 9.914000000000001
    - type: precision_at_100
      value: 1.5310000000000001
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 21.984
    - type: precision_at_5
      value: 15.737000000000002
    - type: recall_at_1
      value: 32.327
    - type: recall_at_10
      value: 63.743
    - type: recall_at_100
      value: 84.538
    - type: recall_at_1000
      value: 96.089
    - type: recall_at_3
      value: 48.065000000000005
    - type: recall_at_5
      value: 54.519
    - type: map_at_1
      value: 32.671
    - type: map_at_10
      value: 42.954
    - type: map_at_100
      value: 44.151
    - type: map_at_1000
      value: 44.287
    - type: map_at_3
      value: 39.912
    - type: map_at_5
      value: 41.798
    - type: mrr_at_1
      value: 41.465
    - type: mrr_at_10
      value: 49.351
    - type: mrr_at_100
      value: 49.980000000000004
    - type: mrr_at_1000
      value: 50.016000000000005
    - type: mrr_at_3
      value: 47.144000000000005
    - type: mrr_at_5
      value: 48.592999999999996
    - type: ndcg_at_1
      value: 41.465
    - type: ndcg_at_10
      value: 48.565999999999995
    - type: ndcg_at_100
      value: 52.76499999999999
    - type: ndcg_at_1000
      value: 54.749
    - type: ndcg_at_3
      value: 44.57
    - type: ndcg_at_5
      value: 46.759
    - type: precision_at_1
      value: 41.465
    - type: precision_at_10
      value: 9.107999999999999
    - type: precision_at_100
      value: 1.433
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 21.423000000000002
    - type: precision_at_5
      value: 15.414
    - type: recall_at_1
      value: 32.671
    - type: recall_at_10
      value: 57.738
    - type: recall_at_100
      value: 75.86500000000001
    - type: recall_at_1000
      value: 88.36
    - type: recall_at_3
      value: 45.626
    - type: recall_at_5
      value: 51.812000000000005
    - type: map_at_1
      value: 41.185
    - type: map_at_10
      value: 53.929
    - type: map_at_100
      value: 54.92
    - type: map_at_1000
      value: 54.967999999999996
    - type: map_at_3
      value: 50.70400000000001
    - type: map_at_5
      value: 52.673
    - type: mrr_at_1
      value: 47.398
    - type: mrr_at_10
      value: 57.303000000000004
    - type: mrr_at_100
      value: 57.959
    - type: mrr_at_1000
      value: 57.985
    - type: mrr_at_3
      value: 54.932
    - type: mrr_at_5
      value: 56.464999999999996
    - type: ndcg_at_1
      value: 47.398
    - type: ndcg_at_10
      value: 59.653
    - type: ndcg_at_100
      value: 63.627
    - type: ndcg_at_1000
      value: 64.596
    - type: ndcg_at_3
      value: 54.455
    - type: ndcg_at_5
      value: 57.245000000000005
    - type: precision_at_1
      value: 47.398
    - type: precision_at_10
      value: 9.524000000000001
    - type: precision_at_100
      value: 1.243
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 24.389
    - type: precision_at_5
      value: 16.752
    - type: recall_at_1
      value: 41.185
    - type: recall_at_10
      value: 73.193
    - type: recall_at_100
      value: 90.357
    - type: recall_at_1000
      value: 97.253
    - type: recall_at_3
      value: 59.199999999999996
    - type: recall_at_5
      value: 66.118
    - type: map_at_1
      value: 27.27
    - type: map_at_10
      value: 36.223
    - type: map_at_100
      value: 37.218
    - type: map_at_1000
      value: 37.293
    - type: map_at_3
      value: 33.503
    - type: map_at_5
      value: 35.097
    - type: mrr_at_1
      value: 29.492
    - type: mrr_at_10
      value: 38.352000000000004
    - type: mrr_at_100
      value: 39.188
    - type: mrr_at_1000
      value: 39.247
    - type: mrr_at_3
      value: 35.876000000000005
    - type: mrr_at_5
      value: 37.401
    - type: ndcg_at_1
      value: 29.492
    - type: ndcg_at_10
      value: 41.239
    - type: ndcg_at_100
      value: 46.066
    - type: ndcg_at_1000
      value: 47.992000000000004
    - type: ndcg_at_3
      value: 36.11
    - type: ndcg_at_5
      value: 38.772
    - type: precision_at_1
      value: 29.492
    - type: precision_at_10
      value: 6.260000000000001
    - type: precision_at_100
      value: 0.914
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 15.104000000000001
    - type: precision_at_5
      value: 10.644
    - type: recall_at_1
      value: 27.27
    - type: recall_at_10
      value: 54.589
    - type: recall_at_100
      value: 76.70700000000001
    - type: recall_at_1000
      value: 91.158
    - type: recall_at_3
      value: 40.974
    - type: recall_at_5
      value: 47.327000000000005
    - type: map_at_1
      value: 17.848
    - type: map_at_10
      value: 26.207
    - type: map_at_100
      value: 27.478
    - type: map_at_1000
      value: 27.602
    - type: map_at_3
      value: 23.405
    - type: map_at_5
      value: 24.98
    - type: mrr_at_1
      value: 21.891
    - type: mrr_at_10
      value: 31.041999999999998
    - type: mrr_at_100
      value: 32.092
    - type: mrr_at_1000
      value: 32.151999999999994
    - type: mrr_at_3
      value: 28.358
    - type: mrr_at_5
      value: 29.969
    - type: ndcg_at_1
      value: 21.891
    - type: ndcg_at_10
      value: 31.585
    - type: ndcg_at_100
      value: 37.531
    - type: ndcg_at_1000
      value: 40.256
    - type: ndcg_at_3
      value: 26.508
    - type: ndcg_at_5
      value: 28.894
    - type: precision_at_1
      value: 21.891
    - type: precision_at_10
      value: 5.795999999999999
    - type: precision_at_100
      value: 0.9990000000000001
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 12.769
    - type: precision_at_5
      value: 9.279
    - type: recall_at_1
      value: 17.848
    - type: recall_at_10
      value: 43.452
    - type: recall_at_100
      value: 69.216
    - type: recall_at_1000
      value: 88.102
    - type: recall_at_3
      value: 29.18
    - type: recall_at_5
      value: 35.347
    - type: map_at_1
      value: 30.94
    - type: map_at_10
      value: 41.248000000000005
    - type: map_at_100
      value: 42.495
    - type: map_at_1000
      value: 42.602000000000004
    - type: map_at_3
      value: 37.939
    - type: map_at_5
      value: 39.924
    - type: mrr_at_1
      value: 37.824999999999996
    - type: mrr_at_10
      value: 47.041
    - type: mrr_at_100
      value: 47.83
    - type: mrr_at_1000
      value: 47.878
    - type: mrr_at_3
      value: 44.466
    - type: mrr_at_5
      value: 46.111999999999995
    - type: ndcg_at_1
      value: 37.824999999999996
    - type: ndcg_at_10
      value: 47.223
    - type: ndcg_at_100
      value: 52.394
    - type: ndcg_at_1000
      value: 54.432
    - type: ndcg_at_3
      value: 42.032000000000004
    - type: ndcg_at_5
      value: 44.772
    - type: precision_at_1
      value: 37.824999999999996
    - type: precision_at_10
      value: 8.393
    - type: precision_at_100
      value: 1.2890000000000001
    - type: precision_at_1000
      value: 0.164
    - type: precision_at_3
      value: 19.698
    - type: precision_at_5
      value: 14.013
    - type: recall_at_1
      value: 30.94
    - type: recall_at_10
      value: 59.316
    - type: recall_at_100
      value: 80.783
    - type: recall_at_1000
      value: 94.15400000000001
    - type: recall_at_3
      value: 44.712
    - type: recall_at_5
      value: 51.932
    - type: map_at_1
      value: 27.104
    - type: map_at_10
      value: 36.675999999999995
    - type: map_at_100
      value: 38.076
    - type: map_at_1000
      value: 38.189
    - type: map_at_3
      value: 33.733999999999995
    - type: map_at_5
      value: 35.287
    - type: mrr_at_1
      value: 33.904
    - type: mrr_at_10
      value: 42.55
    - type: mrr_at_100
      value: 43.434
    - type: mrr_at_1000
      value: 43.494
    - type: mrr_at_3
      value: 40.126
    - type: mrr_at_5
      value: 41.473
    - type: ndcg_at_1
      value: 33.904
    - type: ndcg_at_10
      value: 42.414
    - type: ndcg_at_100
      value: 48.203
    - type: ndcg_at_1000
      value: 50.437
    - type: ndcg_at_3
      value: 37.633
    - type: ndcg_at_5
      value: 39.67
    - type: precision_at_1
      value: 33.904
    - type: precision_at_10
      value: 7.82
    - type: precision_at_100
      value: 1.2409999999999999
    - type: precision_at_1000
      value: 0.159
    - type: precision_at_3
      value: 17.884
    - type: precision_at_5
      value: 12.648000000000001
    - type: recall_at_1
      value: 27.104
    - type: recall_at_10
      value: 53.563
    - type: recall_at_100
      value: 78.557
    - type: recall_at_1000
      value: 93.533
    - type: recall_at_3
      value: 39.92
    - type: recall_at_5
      value: 45.457
    - type: map_at_1
      value: 27.707749999999997
    - type: map_at_10
      value: 36.961
    - type: map_at_100
      value: 38.158833333333334
    - type: map_at_1000
      value: 38.270333333333326
    - type: map_at_3
      value: 34.07183333333334
    - type: map_at_5
      value: 35.69533333333334
    - type: mrr_at_1
      value: 32.81875
    - type: mrr_at_10
      value: 41.293
    - type: mrr_at_100
      value: 42.116499999999995
    - type: mrr_at_1000
      value: 42.170249999999996
    - type: mrr_at_3
      value: 38.83983333333333
    - type: mrr_at_5
      value: 40.29775
    - type: ndcg_at_1
      value: 32.81875
    - type: ndcg_at_10
      value: 42.355
    - type: ndcg_at_100
      value: 47.41374999999999
    - type: ndcg_at_1000
      value: 49.5805
    - type: ndcg_at_3
      value: 37.52825
    - type: ndcg_at_5
      value: 39.83266666666667
    - type: precision_at_1
      value: 32.81875
    - type: precision_at_10
      value: 7.382416666666666
    - type: precision_at_100
      value: 1.1640833333333334
    - type: precision_at_1000
      value: 0.15383333333333335
    - type: precision_at_3
      value: 17.134166666666665
    - type: precision_at_5
      value: 12.174833333333336
    - type: recall_at_1
      value: 27.707749999999997
    - type: recall_at_10
      value: 53.945
    - type: recall_at_100
      value: 76.191
    - type: recall_at_1000
      value: 91.101
    - type: recall_at_3
      value: 40.39083333333334
    - type: recall_at_5
      value: 46.40083333333333
    - type: map_at_1
      value: 26.482
    - type: map_at_10
      value: 33.201
    - type: map_at_100
      value: 34.107
    - type: map_at_1000
      value: 34.197
    - type: map_at_3
      value: 31.174000000000003
    - type: map_at_5
      value: 32.279
    - type: mrr_at_1
      value: 29.908
    - type: mrr_at_10
      value: 36.235
    - type: mrr_at_100
      value: 37.04
    - type: mrr_at_1000
      value: 37.105
    - type: mrr_at_3
      value: 34.355999999999995
    - type: mrr_at_5
      value: 35.382999999999996
    - type: ndcg_at_1
      value: 29.908
    - type: ndcg_at_10
      value: 37.325
    - type: ndcg_at_100
      value: 41.795
    - type: ndcg_at_1000
      value: 44.105
    - type: ndcg_at_3
      value: 33.555
    - type: ndcg_at_5
      value: 35.266999999999996
    - type: precision_at_1
      value: 29.908
    - type: precision_at_10
      value: 5.721
    - type: precision_at_100
      value: 0.8630000000000001
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 14.008000000000001
    - type: precision_at_5
      value: 9.754999999999999
    - type: recall_at_1
      value: 26.482
    - type: recall_at_10
      value: 47.072
    - type: recall_at_100
      value: 67.27
    - type: recall_at_1000
      value: 84.371
    - type: recall_at_3
      value: 36.65
    - type: recall_at_5
      value: 40.774
    - type: map_at_1
      value: 18.815
    - type: map_at_10
      value: 26.369999999999997
    - type: map_at_100
      value: 27.458
    - type: map_at_1000
      value: 27.588
    - type: map_at_3
      value: 23.990000000000002
    - type: map_at_5
      value: 25.345000000000002
    - type: mrr_at_1
      value: 22.953000000000003
    - type: mrr_at_10
      value: 30.342999999999996
    - type: mrr_at_100
      value: 31.241000000000003
    - type: mrr_at_1000
      value: 31.319000000000003
    - type: mrr_at_3
      value: 28.16
    - type: mrr_at_5
      value: 29.406
    - type: ndcg_at_1
      value: 22.953000000000003
    - type: ndcg_at_10
      value: 31.151
    - type: ndcg_at_100
      value: 36.309000000000005
    - type: ndcg_at_1000
      value: 39.227000000000004
    - type: ndcg_at_3
      value: 26.921
    - type: ndcg_at_5
      value: 28.938000000000002
    - type: precision_at_1
      value: 22.953000000000003
    - type: precision_at_10
      value: 5.602
    - type: precision_at_100
      value: 0.9530000000000001
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 12.606
    - type: precision_at_5
      value: 9.119
    - type: recall_at_1
      value: 18.815
    - type: recall_at_10
      value: 41.574
    - type: recall_at_100
      value: 64.84400000000001
    - type: recall_at_1000
      value: 85.406
    - type: recall_at_3
      value: 29.694
    - type: recall_at_5
      value: 34.935
    - type: map_at_1
      value: 27.840999999999998
    - type: map_at_10
      value: 36.797999999999995
    - type: map_at_100
      value: 37.993
    - type: map_at_1000
      value: 38.086999999999996
    - type: map_at_3
      value: 34.050999999999995
    - type: map_at_5
      value: 35.379
    - type: mrr_at_1
      value: 32.649
    - type: mrr_at_10
      value: 41.025
    - type: mrr_at_100
      value: 41.878
    - type: mrr_at_1000
      value: 41.929
    - type: mrr_at_3
      value: 38.573
    - type: mrr_at_5
      value: 39.715
    - type: ndcg_at_1
      value: 32.649
    - type: ndcg_at_10
      value: 42.142
    - type: ndcg_at_100
      value: 47.558
    - type: ndcg_at_1000
      value: 49.643
    - type: ndcg_at_3
      value: 37.12
    - type: ndcg_at_5
      value: 38.983000000000004
    - type: precision_at_1
      value: 32.649
    - type: precision_at_10
      value: 7.08
    - type: precision_at_100
      value: 1.1039999999999999
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 16.698
    - type: precision_at_5
      value: 11.511000000000001
    - type: recall_at_1
      value: 27.840999999999998
    - type: recall_at_10
      value: 54.245
    - type: recall_at_100
      value: 77.947
    - type: recall_at_1000
      value: 92.36999999999999
    - type: recall_at_3
      value: 40.146
    - type: recall_at_5
      value: 44.951
    - type: map_at_1
      value: 26.529000000000003
    - type: map_at_10
      value: 35.010000000000005
    - type: map_at_100
      value: 36.647
    - type: map_at_1000
      value: 36.857
    - type: map_at_3
      value: 31.968000000000004
    - type: map_at_5
      value: 33.554
    - type: mrr_at_1
      value: 31.818
    - type: mrr_at_10
      value: 39.550999999999995
    - type: mrr_at_100
      value: 40.54
    - type: mrr_at_1000
      value: 40.596
    - type: mrr_at_3
      value: 36.726
    - type: mrr_at_5
      value: 38.416
    - type: ndcg_at_1
      value: 31.818
    - type: ndcg_at_10
      value: 40.675
    - type: ndcg_at_100
      value: 46.548
    - type: ndcg_at_1000
      value: 49.126
    - type: ndcg_at_3
      value: 35.829
    - type: ndcg_at_5
      value: 38.0
    - type: precision_at_1
      value: 31.818
    - type: precision_at_10
      value: 7.826
    - type: precision_at_100
      value: 1.538
    - type: precision_at_1000
      value: 0.24
    - type: precision_at_3
      value: 16.601
    - type: precision_at_5
      value: 12.095
    - type: recall_at_1
      value: 26.529000000000003
    - type: recall_at_10
      value: 51.03
    - type: recall_at_100
      value: 77.556
    - type: recall_at_1000
      value: 93.804
    - type: recall_at_3
      value: 36.986000000000004
    - type: recall_at_5
      value: 43.096000000000004
    - type: map_at_1
      value: 23.480999999999998
    - type: map_at_10
      value: 30.817
    - type: map_at_100
      value: 31.838
    - type: map_at_1000
      value: 31.932
    - type: map_at_3
      value: 28.011999999999997
    - type: map_at_5
      value: 29.668
    - type: mrr_at_1
      value: 25.323
    - type: mrr_at_10
      value: 33.072
    - type: mrr_at_100
      value: 33.926
    - type: mrr_at_1000
      value: 33.993
    - type: mrr_at_3
      value: 30.436999999999998
    - type: mrr_at_5
      value: 32.092
    - type: ndcg_at_1
      value: 25.323
    - type: ndcg_at_10
      value: 35.514
    - type: ndcg_at_100
      value: 40.489000000000004
    - type: ndcg_at_1000
      value: 42.908
    - type: ndcg_at_3
      value: 30.092000000000002
    - type: ndcg_at_5
      value: 32.989000000000004
    - type: precision_at_1
      value: 25.323
    - type: precision_at_10
      value: 5.545
    - type: precision_at_100
      value: 0.861
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 12.446
    - type: precision_at_5
      value: 9.131
    - type: recall_at_1
      value: 23.480999999999998
    - type: recall_at_10
      value: 47.825
    - type: recall_at_100
      value: 70.652
    - type: recall_at_1000
      value: 88.612
    - type: recall_at_3
      value: 33.537
    - type: recall_at_5
      value: 40.542
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 13.333999999999998
    - type: map_at_10
      value: 22.524
    - type: map_at_100
      value: 24.506
    - type: map_at_1000
      value: 24.715
    - type: map_at_3
      value: 19.022
    - type: map_at_5
      value: 20.693
    - type: mrr_at_1
      value: 29.186
    - type: mrr_at_10
      value: 41.22
    - type: mrr_at_100
      value: 42.16
    - type: mrr_at_1000
      value: 42.192
    - type: mrr_at_3
      value: 38.013000000000005
    - type: mrr_at_5
      value: 39.704
    - type: ndcg_at_1
      value: 29.186
    - type: ndcg_at_10
      value: 31.167
    - type: ndcg_at_100
      value: 38.879000000000005
    - type: ndcg_at_1000
      value: 42.376000000000005
    - type: ndcg_at_3
      value: 25.817
    - type: ndcg_at_5
      value: 27.377000000000002
    - type: precision_at_1
      value: 29.186
    - type: precision_at_10
      value: 9.693999999999999
    - type: precision_at_100
      value: 1.8030000000000002
    - type: precision_at_1000
      value: 0.246
    - type: precision_at_3
      value: 19.11
    - type: precision_at_5
      value: 14.344999999999999
    - type: recall_at_1
      value: 13.333999999999998
    - type: recall_at_10
      value: 37.092000000000006
    - type: recall_at_100
      value: 63.651
    - type: recall_at_1000
      value: 83.05
    - type: recall_at_3
      value: 23.74
    - type: recall_at_5
      value: 28.655
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.151
    - type: map_at_10
      value: 19.653000000000002
    - type: map_at_100
      value: 28.053
    - type: map_at_1000
      value: 29.709000000000003
    - type: map_at_3
      value: 14.191
    - type: map_at_5
      value: 16.456
    - type: mrr_at_1
      value: 66.25
    - type: mrr_at_10
      value: 74.4
    - type: mrr_at_100
      value: 74.715
    - type: mrr_at_1000
      value: 74.726
    - type: mrr_at_3
      value: 72.417
    - type: mrr_at_5
      value: 73.667
    - type: ndcg_at_1
      value: 54.25
    - type: ndcg_at_10
      value: 40.77
    - type: ndcg_at_100
      value: 46.359
    - type: ndcg_at_1000
      value: 54.193000000000005
    - type: ndcg_at_3
      value: 44.832
    - type: ndcg_at_5
      value: 42.63
    - type: precision_at_1
      value: 66.25
    - type: precision_at_10
      value: 32.175
    - type: precision_at_100
      value: 10.668
    - type: precision_at_1000
      value: 2.067
    - type: precision_at_3
      value: 47.667
    - type: precision_at_5
      value: 41.3
    - type: recall_at_1
      value: 9.151
    - type: recall_at_10
      value: 25.003999999999998
    - type: recall_at_100
      value: 52.976
    - type: recall_at_1000
      value: 78.315
    - type: recall_at_3
      value: 15.487
    - type: recall_at_5
      value: 18.999
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 51.89999999999999
    - type: f1
      value: 46.47777925067403
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 73.706
    - type: map_at_10
      value: 82.423
    - type: map_at_100
      value: 82.67999999999999
    - type: map_at_1000
      value: 82.694
    - type: map_at_3
      value: 81.328
    - type: map_at_5
      value: 82.001
    - type: mrr_at_1
      value: 79.613
    - type: mrr_at_10
      value: 87.07000000000001
    - type: mrr_at_100
      value: 87.169
    - type: mrr_at_1000
      value: 87.17
    - type: mrr_at_3
      value: 86.404
    - type: mrr_at_5
      value: 86.856
    - type: ndcg_at_1
      value: 79.613
    - type: ndcg_at_10
      value: 86.289
    - type: ndcg_at_100
      value: 87.201
    - type: ndcg_at_1000
      value: 87.428
    - type: ndcg_at_3
      value: 84.625
    - type: ndcg_at_5
      value: 85.53699999999999
    - type: precision_at_1
      value: 79.613
    - type: precision_at_10
      value: 10.399
    - type: precision_at_100
      value: 1.1079999999999999
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 32.473
    - type: precision_at_5
      value: 20.132
    - type: recall_at_1
      value: 73.706
    - type: recall_at_10
      value: 93.559
    - type: recall_at_100
      value: 97.188
    - type: recall_at_1000
      value: 98.555
    - type: recall_at_3
      value: 88.98700000000001
    - type: recall_at_5
      value: 91.373
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 19.841
    - type: map_at_10
      value: 32.643
    - type: map_at_100
      value: 34.575
    - type: map_at_1000
      value: 34.736
    - type: map_at_3
      value: 28.317999999999998
    - type: map_at_5
      value: 30.964000000000002
    - type: mrr_at_1
      value: 39.660000000000004
    - type: mrr_at_10
      value: 48.620000000000005
    - type: mrr_at_100
      value: 49.384
    - type: mrr_at_1000
      value: 49.415
    - type: mrr_at_3
      value: 45.988
    - type: mrr_at_5
      value: 47.361
    - type: ndcg_at_1
      value: 39.660000000000004
    - type: ndcg_at_10
      value: 40.646
    - type: ndcg_at_100
      value: 47.657
    - type: ndcg_at_1000
      value: 50.428
    - type: ndcg_at_3
      value: 36.689
    - type: ndcg_at_5
      value: 38.211
    - type: precision_at_1
      value: 39.660000000000004
    - type: precision_at_10
      value: 11.235000000000001
    - type: precision_at_100
      value: 1.8530000000000002
    - type: precision_at_1000
      value: 0.23600000000000002
    - type: precision_at_3
      value: 24.587999999999997
    - type: precision_at_5
      value: 18.395
    - type: recall_at_1
      value: 19.841
    - type: recall_at_10
      value: 48.135
    - type: recall_at_100
      value: 74.224
    - type: recall_at_1000
      value: 90.826
    - type: recall_at_3
      value: 33.536
    - type: recall_at_5
      value: 40.311
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.358
    - type: map_at_10
      value: 64.497
    - type: map_at_100
      value: 65.362
    - type: map_at_1000
      value: 65.41900000000001
    - type: map_at_3
      value: 61.06700000000001
    - type: map_at_5
      value: 63.317
    - type: mrr_at_1
      value: 80.716
    - type: mrr_at_10
      value: 86.10799999999999
    - type: mrr_at_100
      value: 86.265
    - type: mrr_at_1000
      value: 86.27
    - type: mrr_at_3
      value: 85.271
    - type: mrr_at_5
      value: 85.82499999999999
    - type: ndcg_at_1
      value: 80.716
    - type: ndcg_at_10
      value: 72.597
    - type: ndcg_at_100
      value: 75.549
    - type: ndcg_at_1000
      value: 76.61
    - type: ndcg_at_3
      value: 67.874
    - type: ndcg_at_5
      value: 70.655
    - type: precision_at_1
      value: 80.716
    - type: precision_at_10
      value: 15.148
    - type: precision_at_100
      value: 1.745
    - type: precision_at_1000
      value: 0.188
    - type: precision_at_3
      value: 43.597
    - type: precision_at_5
      value: 28.351
    - type: recall_at_1
      value: 40.358
    - type: recall_at_10
      value: 75.739
    - type: recall_at_100
      value: 87.259
    - type: recall_at_1000
      value: 94.234
    - type: recall_at_3
      value: 65.39500000000001
    - type: recall_at_5
      value: 70.878
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 90.80799999999998
    - type: ap
      value: 86.81350378180757
    - type: f1
      value: 90.79901248314215
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 22.096
    - type: map_at_10
      value: 34.384
    - type: map_at_100
      value: 35.541
    - type: map_at_1000
      value: 35.589999999999996
    - type: map_at_3
      value: 30.496000000000002
    - type: map_at_5
      value: 32.718
    - type: mrr_at_1
      value: 22.750999999999998
    - type: mrr_at_10
      value: 35.024
    - type: mrr_at_100
      value: 36.125
    - type: mrr_at_1000
      value: 36.168
    - type: mrr_at_3
      value: 31.225
    - type: mrr_at_5
      value: 33.416000000000004
    - type: ndcg_at_1
      value: 22.750999999999998
    - type: ndcg_at_10
      value: 41.351
    - type: ndcg_at_100
      value: 46.92
    - type: ndcg_at_1000
      value: 48.111
    - type: ndcg_at_3
      value: 33.439
    - type: ndcg_at_5
      value: 37.407000000000004
    - type: precision_at_1
      value: 22.750999999999998
    - type: precision_at_10
      value: 6.564
    - type: precision_at_100
      value: 0.935
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.288
    - type: precision_at_5
      value: 10.581999999999999
    - type: recall_at_1
      value: 22.096
    - type: recall_at_10
      value: 62.771
    - type: recall_at_100
      value: 88.529
    - type: recall_at_1000
      value: 97.55
    - type: recall_at_3
      value: 41.245
    - type: recall_at_5
      value: 50.788
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 94.16780665754673
    - type: f1
      value: 93.96331194859894
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 76.90606475148198
    - type: f1
      value: 58.58344986604187
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 76.14660390047075
    - type: f1
      value: 74.31533923533614
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 80.16139878950908
    - type: f1
      value: 80.18532656824924
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.949880906135085
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 31.56300351524862
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.196521894371315
    - type: mrr
      value: 32.22644231694389
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.783
    - type: map_at_10
      value: 14.549000000000001
    - type: map_at_100
      value: 18.433
    - type: map_at_1000
      value: 19.949
    - type: map_at_3
      value: 10.936
    - type: map_at_5
      value: 12.514
    - type: mrr_at_1
      value: 47.368
    - type: mrr_at_10
      value: 56.42
    - type: mrr_at_100
      value: 56.908
    - type: mrr_at_1000
      value: 56.95
    - type: mrr_at_3
      value: 54.283
    - type: mrr_at_5
      value: 55.568
    - type: ndcg_at_1
      value: 45.666000000000004
    - type: ndcg_at_10
      value: 37.389
    - type: ndcg_at_100
      value: 34.253
    - type: ndcg_at_1000
      value: 43.059999999999995
    - type: ndcg_at_3
      value: 42.725
    - type: ndcg_at_5
      value: 40.193
    - type: precision_at_1
      value: 47.368
    - type: precision_at_10
      value: 27.988000000000003
    - type: precision_at_100
      value: 8.672
    - type: precision_at_1000
      value: 2.164
    - type: precision_at_3
      value: 40.248
    - type: precision_at_5
      value: 34.737
    - type: recall_at_1
      value: 6.783
    - type: recall_at_10
      value: 17.838
    - type: recall_at_100
      value: 33.672000000000004
    - type: recall_at_1000
      value: 66.166
    - type: recall_at_3
      value: 11.849
    - type: recall_at_5
      value: 14.205000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.698999999999998
    - type: map_at_10
      value: 46.556
    - type: map_at_100
      value: 47.652
    - type: map_at_1000
      value: 47.68
    - type: map_at_3
      value: 42.492000000000004
    - type: map_at_5
      value: 44.763999999999996
    - type: mrr_at_1
      value: 35.747
    - type: mrr_at_10
      value: 49.242999999999995
    - type: mrr_at_100
      value: 50.052
    - type: mrr_at_1000
      value: 50.068
    - type: mrr_at_3
      value: 45.867000000000004
    - type: mrr_at_5
      value: 47.778999999999996
    - type: ndcg_at_1
      value: 35.717999999999996
    - type: ndcg_at_10
      value: 54.14600000000001
    - type: ndcg_at_100
      value: 58.672999999999995
    - type: ndcg_at_1000
      value: 59.279
    - type: ndcg_at_3
      value: 46.407
    - type: ndcg_at_5
      value: 50.181
    - type: precision_at_1
      value: 35.717999999999996
    - type: precision_at_10
      value: 8.844000000000001
    - type: precision_at_100
      value: 1.139
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 20.993000000000002
    - type: precision_at_5
      value: 14.791000000000002
    - type: recall_at_1
      value: 31.698999999999998
    - type: recall_at_10
      value: 74.693
    - type: recall_at_100
      value: 94.15299999999999
    - type: recall_at_1000
      value: 98.585
    - type: recall_at_3
      value: 54.388999999999996
    - type: recall_at_5
      value: 63.08200000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 71.283
    - type: map_at_10
      value: 85.24000000000001
    - type: map_at_100
      value: 85.882
    - type: map_at_1000
      value: 85.897
    - type: map_at_3
      value: 82.326
    - type: map_at_5
      value: 84.177
    - type: mrr_at_1
      value: 82.21000000000001
    - type: mrr_at_10
      value: 88.228
    - type: mrr_at_100
      value: 88.32
    - type: mrr_at_1000
      value: 88.32
    - type: mrr_at_3
      value: 87.323
    - type: mrr_at_5
      value: 87.94800000000001
    - type: ndcg_at_1
      value: 82.17999999999999
    - type: ndcg_at_10
      value: 88.9
    - type: ndcg_at_100
      value: 90.079
    - type: ndcg_at_1000
      value: 90.158
    - type: ndcg_at_3
      value: 86.18299999999999
    - type: ndcg_at_5
      value: 87.71799999999999
    - type: precision_at_1
      value: 82.17999999999999
    - type: precision_at_10
      value: 13.464
    - type: precision_at_100
      value: 1.533
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.693
    - type: precision_at_5
      value: 24.792
    - type: recall_at_1
      value: 71.283
    - type: recall_at_10
      value: 95.742
    - type: recall_at_100
      value: 99.67200000000001
    - type: recall_at_1000
      value: 99.981
    - type: recall_at_3
      value: 87.888
    - type: recall_at_5
      value: 92.24
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 56.24267063669042
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 62.88056988932578
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.903
    - type: map_at_10
      value: 13.202
    - type: map_at_100
      value: 15.5
    - type: map_at_1000
      value: 15.870999999999999
    - type: map_at_3
      value: 9.407
    - type: map_at_5
      value: 11.238
    - type: mrr_at_1
      value: 24.2
    - type: mrr_at_10
      value: 35.867
    - type: mrr_at_100
      value: 37.001
    - type: mrr_at_1000
      value: 37.043
    - type: mrr_at_3
      value: 32.5
    - type: mrr_at_5
      value: 34.35
    - type: ndcg_at_1
      value: 24.2
    - type: ndcg_at_10
      value: 21.731
    - type: ndcg_at_100
      value: 30.7
    - type: ndcg_at_1000
      value: 36.618
    - type: ndcg_at_3
      value: 20.72
    - type: ndcg_at_5
      value: 17.954
    - type: precision_at_1
      value: 24.2
    - type: precision_at_10
      value: 11.33
    - type: precision_at_100
      value: 2.4410000000000003
    - type: precision_at_1000
      value: 0.386
    - type: precision_at_3
      value: 19.667
    - type: precision_at_5
      value: 15.86
    - type: recall_at_1
      value: 4.903
    - type: recall_at_10
      value: 22.962
    - type: recall_at_100
      value: 49.563
    - type: recall_at_1000
      value: 78.238
    - type: recall_at_3
      value: 11.953
    - type: recall_at_5
      value: 16.067999999999998
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 84.12694254604078
    - type: cos_sim_spearman
      value: 80.30141815181918
    - type: euclidean_pearson
      value: 81.34015449877128
    - type: euclidean_spearman
      value: 80.13984197010849
    - type: manhattan_pearson
      value: 81.31767068124086
    - type: manhattan_spearman
      value: 80.11720513114103
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 86.13112984010417
    - type: cos_sim_spearman
      value: 78.03063573402875
    - type: euclidean_pearson
      value: 83.51928418844804
    - type: euclidean_spearman
      value: 78.4045235411144
    - type: manhattan_pearson
      value: 83.49981637388689
    - type: manhattan_spearman
      value: 78.4042575139372
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 82.50327987379504
    - type: cos_sim_spearman
      value: 84.18556767756205
    - type: euclidean_pearson
      value: 82.69684424327679
    - type: euclidean_spearman
      value: 83.5368106038335
    - type: manhattan_pearson
      value: 82.57967581007374
    - type: manhattan_spearman
      value: 83.43009053133697
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 82.50756863007814
    - type: cos_sim_spearman
      value: 82.27204331279108
    - type: euclidean_pearson
      value: 81.39535251429741
    - type: euclidean_spearman
      value: 81.84386626336239
    - type: manhattan_pearson
      value: 81.34281737280695
    - type: manhattan_spearman
      value: 81.81149375673166
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.8727714856726
    - type: cos_sim_spearman
      value: 87.95738287792312
    - type: euclidean_pearson
      value: 86.62920602795887
    - type: euclidean_spearman
      value: 87.05207355381243
    - type: manhattan_pearson
      value: 86.53587918472225
    - type: manhattan_spearman
      value: 86.95382961029586
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 83.52240359769479
    - type: cos_sim_spearman
      value: 85.47685776238286
    - type: euclidean_pearson
      value: 84.25815333483058
    - type: euclidean_spearman
      value: 85.27415639683198
    - type: manhattan_pearson
      value: 84.29127757025637
    - type: manhattan_spearman
      value: 85.30226224917351
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 86.42501708915708
    - type: cos_sim_spearman
      value: 86.42276182795041
    - type: euclidean_pearson
      value: 86.5408207354761
    - type: euclidean_spearman
      value: 85.46096321750838
    - type: manhattan_pearson
      value: 86.54177303026881
    - type: manhattan_spearman
      value: 85.50313151916117
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 64.86521089250766
    - type: cos_sim_spearman
      value: 65.94868540323003
    - type: euclidean_pearson
      value: 67.16569626533084
    - type: euclidean_spearman
      value: 66.37667004134917
    - type: manhattan_pearson
      value: 67.1482365102333
    - type: manhattan_spearman
      value: 66.53240122580029
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 84.64746265365318
    - type: cos_sim_spearman
      value: 86.41888825906786
    - type: euclidean_pearson
      value: 85.27453642725811
    - type: euclidean_spearman
      value: 85.94095796602544
    - type: manhattan_pearson
      value: 85.28643660505334
    - type: manhattan_spearman
      value: 85.95028003260744
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 87.48903153618527
    - type: mrr
      value: 96.41081503826601
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 58.594
    - type: map_at_10
      value: 69.296
    - type: map_at_100
      value: 69.782
    - type: map_at_1000
      value: 69.795
    - type: map_at_3
      value: 66.23
    - type: map_at_5
      value: 68.293
    - type: mrr_at_1
      value: 61.667
    - type: mrr_at_10
      value: 70.339
    - type: mrr_at_100
      value: 70.708
    - type: mrr_at_1000
      value: 70.722
    - type: mrr_at_3
      value: 68.0
    - type: mrr_at_5
      value: 69.56700000000001
    - type: ndcg_at_1
      value: 61.667
    - type: ndcg_at_10
      value: 74.039
    - type: ndcg_at_100
      value: 76.103
    - type: ndcg_at_1000
      value: 76.47800000000001
    - type: ndcg_at_3
      value: 68.967
    - type: ndcg_at_5
      value: 71.96900000000001
    - type: precision_at_1
      value: 61.667
    - type: precision_at_10
      value: 9.866999999999999
    - type: precision_at_100
      value: 1.097
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 27.111
    - type: precision_at_5
      value: 18.2
    - type: recall_at_1
      value: 58.594
    - type: recall_at_10
      value: 87.422
    - type: recall_at_100
      value: 96.667
    - type: recall_at_1000
      value: 99.667
    - type: recall_at_3
      value: 74.217
    - type: recall_at_5
      value: 81.539
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.85049504950496
    - type: cos_sim_ap
      value: 96.33111544137081
    - type: cos_sim_f1
      value: 92.35443037974684
    - type: cos_sim_precision
      value: 93.53846153846153
    - type: cos_sim_recall
      value: 91.2
    - type: dot_accuracy
      value: 99.82376237623762
    - type: dot_ap
      value: 95.38082527310888
    - type: dot_f1
      value: 90.90909090909092
    - type: dot_precision
      value: 92.90187891440502
    - type: dot_recall
      value: 89.0
    - type: euclidean_accuracy
      value: 99.84851485148515
    - type: euclidean_ap
      value: 96.32316003996347
    - type: euclidean_f1
      value: 92.2071392659628
    - type: euclidean_precision
      value: 92.71991911021233
    - type: euclidean_recall
      value: 91.7
    - type: manhattan_accuracy
      value: 99.84851485148515
    - type: manhattan_ap
      value: 96.3655668249217
    - type: manhattan_f1
      value: 92.18356026222895
    - type: manhattan_precision
      value: 92.98067141403867
    - type: manhattan_recall
      value: 91.4
    - type: max_accuracy
      value: 99.85049504950496
    - type: max_ap
      value: 96.3655668249217
    - type: max_f1
      value: 92.35443037974684
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 65.94861371629051
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 35.009430451385
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 54.61164066427969
    - type: mrr
      value: 55.49710603938544
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.622620124907662
    - type: cos_sim_spearman
      value: 31.0678351356163
    - type: dot_pearson
      value: 30.863727693306814
    - type: dot_spearman
      value: 31.230306567021255
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.22
    - type: map_at_10
      value: 2.011
    - type: map_at_100
      value: 10.974
    - type: map_at_1000
      value: 25.819
    - type: map_at_3
      value: 0.6649999999999999
    - type: map_at_5
      value: 1.076
    - type: mrr_at_1
      value: 86.0
    - type: mrr_at_10
      value: 91.8
    - type: mrr_at_100
      value: 91.8
    - type: mrr_at_1000
      value: 91.8
    - type: mrr_at_3
      value: 91.0
    - type: mrr_at_5
      value: 91.8
    - type: ndcg_at_1
      value: 82.0
    - type: ndcg_at_10
      value: 78.07300000000001
    - type: ndcg_at_100
      value: 58.231
    - type: ndcg_at_1000
      value: 51.153000000000006
    - type: ndcg_at_3
      value: 81.123
    - type: ndcg_at_5
      value: 81.059
    - type: precision_at_1
      value: 86.0
    - type: precision_at_10
      value: 83.0
    - type: precision_at_100
      value: 59.38
    - type: precision_at_1000
      value: 22.55
    - type: precision_at_3
      value: 87.333
    - type: precision_at_5
      value: 86.8
    - type: recall_at_1
      value: 0.22
    - type: recall_at_10
      value: 2.2079999999999997
    - type: recall_at_100
      value: 14.069
    - type: recall_at_1000
      value: 47.678
    - type: recall_at_3
      value: 0.7040000000000001
    - type: recall_at_5
      value: 1.161
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.809
    - type: map_at_10
      value: 10.394
    - type: map_at_100
      value: 16.598
    - type: map_at_1000
      value: 18.142
    - type: map_at_3
      value: 5.572
    - type: map_at_5
      value: 7.1370000000000005
    - type: mrr_at_1
      value: 32.653
    - type: mrr_at_10
      value: 46.564
    - type: mrr_at_100
      value: 47.469
    - type: mrr_at_1000
      value: 47.469
    - type: mrr_at_3
      value: 42.177
    - type: mrr_at_5
      value: 44.524
    - type: ndcg_at_1
      value: 30.612000000000002
    - type: ndcg_at_10
      value: 25.701
    - type: ndcg_at_100
      value: 37.532
    - type: ndcg_at_1000
      value: 48.757
    - type: ndcg_at_3
      value: 28.199999999999996
    - type: ndcg_at_5
      value: 25.987
    - type: precision_at_1
      value: 32.653
    - type: precision_at_10
      value: 23.469
    - type: precision_at_100
      value: 7.9799999999999995
    - type: precision_at_1000
      value: 1.5350000000000001
    - type: precision_at_3
      value: 29.932
    - type: precision_at_5
      value: 26.122
    - type: recall_at_1
      value: 2.809
    - type: recall_at_10
      value: 16.887
    - type: recall_at_100
      value: 48.67
    - type: recall_at_1000
      value: 82.89699999999999
    - type: recall_at_3
      value: 6.521000000000001
    - type: recall_at_5
      value: 9.609
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.57860000000001
    - type: ap
      value: 13.82629211536393
    - type: f1
      value: 54.59860966183956
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.38030560271647
    - type: f1
      value: 59.69685552567865
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 51.4736717043405
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 86.92853311080646
    - type: cos_sim_ap
      value: 77.67872502591382
    - type: cos_sim_f1
      value: 70.33941236068895
    - type: cos_sim_precision
      value: 67.63273258645884
    - type: cos_sim_recall
      value: 73.27176781002639
    - type: dot_accuracy
      value: 85.79603027954938
    - type: dot_ap
      value: 73.73786190233379
    - type: dot_f1
      value: 67.3437901774235
    - type: dot_precision
      value: 65.67201604814443
    - type: dot_recall
      value: 69.10290237467018
    - type: euclidean_accuracy
      value: 86.94045419324074
    - type: euclidean_ap
      value: 77.6687791535167
    - type: euclidean_f1
      value: 70.47209214023542
    - type: euclidean_precision
      value: 67.7207492094381
    - type: euclidean_recall
      value: 73.45646437994723
    - type: manhattan_accuracy
      value: 86.87488823985218
    - type: manhattan_ap
      value: 77.63373392430728
    - type: manhattan_f1
      value: 70.40920716112532
    - type: manhattan_precision
      value: 68.31265508684864
    - type: manhattan_recall
      value: 72.63852242744063
    - type: max_accuracy
      value: 86.94045419324074
    - type: max_ap
      value: 77.67872502591382
    - type: max_f1
      value: 70.47209214023542
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.67155664221679
    - type: cos_sim_ap
      value: 85.64591703003417
    - type: cos_sim_f1
      value: 77.59531005352656
    - type: cos_sim_precision
      value: 73.60967184801382
    - type: cos_sim_recall
      value: 82.03726516784724
    - type: dot_accuracy
      value: 88.41541506578181
    - type: dot_ap
      value: 84.6482788957769
    - type: dot_f1
      value: 77.04748541466657
    - type: dot_precision
      value: 74.02440754931176
    - type: dot_recall
      value: 80.3279950723745
    - type: euclidean_accuracy
      value: 88.63080684596576
    - type: euclidean_ap
      value: 85.44570045321562
    - type: euclidean_f1
      value: 77.28769403336106
    - type: euclidean_precision
      value: 72.90600040958427
    - type: euclidean_recall
      value: 82.22975053895904
    - type: manhattan_accuracy
      value: 88.59393798269105
    - type: manhattan_ap
      value: 85.40271361038187
    - type: manhattan_f1
      value: 77.17606419344392
    - type: manhattan_precision
      value: 72.4447747078295
    - type: manhattan_recall
      value: 82.5685247921158
    - type: max_accuracy
      value: 88.67155664221679
    - type: max_ap
      value: 85.64591703003417
    - type: max_f1
      value: 77.59531005352656
---
# Neuronx model for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)

This repository contains are  [**AWS Inferentia2**](https://aws.amazon.com/ec2/instance-types/inf2/) and [`neuronx`](https://awsdocs-neuron.readthedocs-hosted.com/en/latest/) compatible checkpoint for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5). You can find detailed information about the base model on its [Model Card](https://huggingface.co/BAAI/bge-base-en-v1.5).

## Usage on Amazon SageMaker

_coming soon_

## Usage with optimum-neuron

```python

from optimum.neuron import NeuronModelForFeatureExtraction
from transformers import AutoTokenizer
import torch
import torch_neuronx

# Load Model from Hugging Face repository
model = NeuronModelForFeatureExtraction.from_pretrained("aws-neuron/bge-base-en-v1-5-seqlen-384-bs-1")
tokenizer = AutoTokenizer.from_pretrained("aws-neuron/bge-base-en-v1-5-seqlen-384-bs-1")

# sentence input
inputs = "Hello, my dog is cute"

# Tokenize sentences
encoded_input = tokenizer(inputs,return_tensors="pt",truncation=True,max_length=model.config.neuron["static_sequence_length"])

# Compute embeddings
with torch.no_grad():
    model_output = model(*tuple(encoded_input.values()))

# Perform pooling. In this case, cls pooling.
sentence_embeddings = model_output[0][:, 0]
# normalize embeddings
sentence_embeddings = torch.nn.functional.normalize(sentence_embeddings, p=2, dim=1)   
```

**input_shapes**

```json
{
  "sequence_length": 384,
  "batch_size": 1
}
```



