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metadata
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
          - 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
          - 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
          - 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
          - 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
          - type: mrr_at_5
            value: 91.8
          - type: ndcg_at_1
            value: 82
          - 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
          - type: precision_at_10
            value: 83
          - 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

This repository contains are AWS Inferentia2 and neuronx compatible checkpoint for BAAI/bge-base-en-v1.5. You can find detailed information about the base model on its Model Card.

Usage on Amazon SageMaker

coming soon

Usage with optimum-neuron


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

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