mteb model-index region:us
---
tags:
- mteb
model-index:
- name: neural-embedding-v1
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 93.10447761194031
    - type: ap
      value: 72.52673607512206
    - type: f1
      value: 89.6752355529259
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 97.536525
    - type: ap
      value: 96.46802431780014
    - type: f1
      value: 97.53623627430422
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 61.17399999999999
    - type: f1
      value: 60.40485236445537
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 44.452000000000005
    - type: map_at_10
      value: 59.563
    - type: map_at_100
      value: 60.014
    - type: map_at_1000
      value: 60.016000000000005
    - type: map_at_20
      value: 59.923
    - type: map_at_3
      value: 55.915000000000006
    - type: map_at_5
      value: 58.056
    - type: mrr_at_1
      value: 45.804
    - type: mrr_at_10
      value: 60.089999999999996
    - type: mrr_at_100
      value: 60.541
    - type: mrr_at_1000
      value: 60.543
    - type: mrr_at_20
      value: 60.45
    - type: mrr_at_3
      value: 56.294
    - type: mrr_at_5
      value: 58.54899999999999
    - type: ndcg_at_1
      value: 44.452000000000005
    - type: ndcg_at_10
      value: 67.208
    - type: ndcg_at_100
      value: 69.074
    - type: ndcg_at_1000
      value: 69.122
    - type: ndcg_at_20
      value: 68.474
    - type: ndcg_at_3
      value: 59.758
    - type: ndcg_at_5
      value: 63.621
    - type: precision_at_1
      value: 44.452000000000005
    - type: precision_at_10
      value: 9.125
    - type: precision_at_100
      value: 0.993
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.808
    - type: precision_at_3
      value: 23.637
    - type: precision_at_5
      value: 16.06
    - type: recall_at_1
      value: 44.452000000000005
    - type: recall_at_10
      value: 91.252
    - type: recall_at_100
      value: 99.289
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_20
      value: 96.15899999999999
    - type: recall_at_3
      value: 70.91
    - type: recall_at_5
      value: 80.29899999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 53.445166004781356
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 48.82101672589653
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 68.44973588765177
    - type: mrr
      value: 80.355274150288
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 90.06690068909613
    - type: cos_sim_spearman
      value: 87.97730582741434
    - type: euclidean_pearson
      value: 86.04185393610108
    - type: euclidean_spearman
      value: 85.91340337831018
    - type: manhattan_pearson
      value: 86.05913485565931
    - type: manhattan_spearman
      value: 85.70195277713228
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 88.73376623376623
    - type: f1
      value: 88.67733851784945
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 48.822459956481474
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 45.068617486695764
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 36.980000000000004
    - type: map_at_10
      value: 51.151
    - type: map_at_100
      value: 52.852
    - type: map_at_1000
      value: 52.957
    - type: map_at_20
      value: 52.196
    - type: map_at_3
      value: 46.537
    - type: map_at_5
      value: 49.025999999999996
    - type: mrr_at_1
      value: 45.494
    - type: mrr_at_10
      value: 56.765
    - type: mrr_at_100
      value: 57.483
    - type: mrr_at_1000
      value: 57.508
    - type: mrr_at_20
      value: 57.255
    - type: mrr_at_3
      value: 53.815000000000005
    - type: mrr_at_5
      value: 55.725
    - type: ndcg_at_1
      value: 45.494
    - type: ndcg_at_10
      value: 58.435
    - type: ndcg_at_100
      value: 63.318
    - type: ndcg_at_1000
      value: 64.498
    - type: ndcg_at_20
      value: 60.88
    - type: ndcg_at_3
      value: 52.307
    - type: ndcg_at_5
      value: 55.103
    - type: precision_at_1
      value: 45.494
    - type: precision_at_10
      value: 11.488
    - type: precision_at_100
      value: 1.735
    - type: precision_at_1000
      value: 0.215
    - type: precision_at_20
      value: 6.8309999999999995
    - type: precision_at_3
      value: 25.513
    - type: precision_at_5
      value: 18.282999999999998
    - type: recall_at_1
      value: 36.980000000000004
    - type: recall_at_10
      value: 72.82300000000001
    - type: recall_at_100
      value: 91.525
    - type: recall_at_1000
      value: 98.44800000000001
    - type: recall_at_20
      value: 81.345
    - type: recall_at_3
      value: 55.044000000000004
    - type: recall_at_5
      value: 63.441
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 37.489
    - type: map_at_10
      value: 50.708
    - type: map_at_100
      value: 52.101
    - type: map_at_1000
      value: 52.22
    - type: map_at_20
      value: 51.514
    - type: map_at_3
      value: 46.915
    - type: map_at_5
      value: 49.185
    - type: mrr_at_1
      value: 47.643
    - type: mrr_at_10
      value: 56.806
    - type: mrr_at_100
      value: 57.369
    - type: mrr_at_1000
      value: 57.399
    - type: mrr_at_20
      value: 57.141
    - type: mrr_at_3
      value: 54.437000000000005
    - type: mrr_at_5
      value: 55.955999999999996
    - type: ndcg_at_1
      value: 47.643
    - type: ndcg_at_10
      value: 56.989000000000004
    - type: ndcg_at_100
      value: 60.995999999999995
    - type: ndcg_at_1000
      value: 62.668
    - type: ndcg_at_20
      value: 58.63699999999999
    - type: ndcg_at_3
      value: 52.26499999999999
    - type: ndcg_at_5
      value: 54.684999999999995
    - type: precision_at_1
      value: 47.643
    - type: precision_at_10
      value: 10.879
    - type: precision_at_100
      value: 1.6320000000000001
    - type: precision_at_1000
      value: 0.211
    - type: precision_at_20
      value: 6.338000000000001
    - type: precision_at_3
      value: 25.52
    - type: precision_at_5
      value: 18.229
    - type: recall_at_1
      value: 37.489
    - type: recall_at_10
      value: 68.10300000000001
    - type: recall_at_100
      value: 84.497
    - type: recall_at_1000
      value: 94.402
    - type: recall_at_20
      value: 73.849
    - type: recall_at_3
      value: 53.925
    - type: recall_at_5
      value: 60.878
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 45.044000000000004
    - type: map_at_10
      value: 59.804
    - type: map_at_100
      value: 60.841
    - type: map_at_1000
      value: 60.870999999999995
    - type: map_at_20
      value: 60.478
    - type: map_at_3
      value: 56.169000000000004
    - type: map_at_5
      value: 58.331999999999994
    - type: mrr_at_1
      value: 51.849999999999994
    - type: mrr_at_10
      value: 63.249
    - type: mrr_at_100
      value: 63.786
    - type: mrr_at_1000
      value: 63.797000000000004
    - type: mrr_at_20
      value: 63.592999999999996
    - type: mrr_at_3
      value: 60.721000000000004
    - type: mrr_at_5
      value: 62.251
    - type: ndcg_at_1
      value: 51.849999999999994
    - type: ndcg_at_10
      value: 66.122
    - type: ndcg_at_100
      value: 69.614
    - type: ndcg_at_1000
      value: 70.12
    - type: ndcg_at_20
      value: 67.805
    - type: ndcg_at_3
      value: 60.348
    - type: ndcg_at_5
      value: 63.33800000000001
    - type: precision_at_1
      value: 51.849999999999994
    - type: precision_at_10
      value: 10.539
    - type: precision_at_100
      value: 1.327
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_20
      value: 5.865
    - type: precision_at_3
      value: 27.084999999999997
    - type: precision_at_5
      value: 18.483
    - type: recall_at_1
      value: 45.044000000000004
    - type: recall_at_10
      value: 81.192
    - type: recall_at_100
      value: 95.597
    - type: recall_at_1000
      value: 98.97200000000001
    - type: recall_at_20
      value: 87.139
    - type: recall_at_3
      value: 65.713
    - type: recall_at_5
      value: 73.213
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 29.834
    - type: map_at_10
      value: 40.363
    - type: map_at_100
      value: 41.559000000000005
    - type: map_at_1000
      value: 41.626000000000005
    - type: map_at_20
      value: 41.160999999999994
    - type: map_at_3
      value: 36.958999999999996
    - type: map_at_5
      value: 38.897999999999996
    - type: mrr_at_1
      value: 32.429
    - type: mrr_at_10
      value: 42.604
    - type: mrr_at_100
      value: 43.54
    - type: mrr_at_1000
      value: 43.59
    - type: mrr_at_20
      value: 43.247
    - type: mrr_at_3
      value: 39.528999999999996
    - type: mrr_at_5
      value: 41.36
    - type: ndcg_at_1
      value: 32.429
    - type: ndcg_at_10
      value: 46.39
    - type: ndcg_at_100
      value: 51.561
    - type: ndcg_at_1000
      value: 53.071
    - type: ndcg_at_20
      value: 48.951
    - type: ndcg_at_3
      value: 39.796
    - type: ndcg_at_5
      value: 43.07
    - type: precision_at_1
      value: 32.429
    - type: precision_at_10
      value: 7.277
    - type: precision_at_100
      value: 1.038
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_20
      value: 4.249
    - type: precision_at_3
      value: 17.024
    - type: precision_at_5
      value: 12.113
    - type: recall_at_1
      value: 29.834
    - type: recall_at_10
      value: 62.808
    - type: recall_at_100
      value: 85.47200000000001
    - type: recall_at_1000
      value: 96.503
    - type: recall_at_20
      value: 72.246
    - type: recall_at_3
      value: 45.059
    - type: recall_at_5
      value: 52.907000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 22.121
    - type: map_at_10
      value: 33.217
    - type: map_at_100
      value: 34.671
    - type: map_at_1000
      value: 34.77
    - type: map_at_20
      value: 34.039
    - type: map_at_3
      value: 29.389
    - type: map_at_5
      value: 31.749
    - type: mrr_at_1
      value: 27.114
    - type: mrr_at_10
      value: 37.730999999999995
    - type: mrr_at_100
      value: 38.673
    - type: mrr_at_1000
      value: 38.725
    - type: mrr_at_20
      value: 38.279
    - type: mrr_at_3
      value: 34.494
    - type: mrr_at_5
      value: 36.609
    - type: ndcg_at_1
      value: 27.114
    - type: ndcg_at_10
      value: 39.723000000000006
    - type: ndcg_at_100
      value: 45.847
    - type: ndcg_at_1000
      value: 47.879
    - type: ndcg_at_20
      value: 42.129
    - type: ndcg_at_3
      value: 33.194
    - type: ndcg_at_5
      value: 36.763
    - type: precision_at_1
      value: 27.114
    - type: precision_at_10
      value: 7.575
    - type: precision_at_100
      value: 1.218
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_20
      value: 4.527
    - type: precision_at_3
      value: 16.252
    - type: precision_at_5
      value: 12.363
    - type: recall_at_1
      value: 22.121
    - type: recall_at_10
      value: 54.726
    - type: recall_at_100
      value: 80.662
    - type: recall_at_1000
      value: 94.645
    - type: recall_at_20
      value: 62.977000000000004
    - type: recall_at_3
      value: 37.348
    - type: recall_at_5
      value: 46.163
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 36.346000000000004
    - type: map_at_10
      value: 50.034
    - type: map_at_100
      value: 51.37500000000001
    - type: map_at_1000
      value: 51.464
    - type: map_at_20
      value: 50.739999999999995
    - type: map_at_3
      value: 45.948
    - type: map_at_5
      value: 48.421
    - type: mrr_at_1
      value: 45.043
    - type: mrr_at_10
      value: 55.642
    - type: mrr_at_100
      value: 56.335
    - type: mrr_at_1000
      value: 56.355999999999995
    - type: mrr_at_20
      value: 56.027
    - type: mrr_at_3
      value: 53.224000000000004
    - type: mrr_at_5
      value: 54.798
    - type: ndcg_at_1
      value: 45.043
    - type: ndcg_at_10
      value: 56.627
    - type: ndcg_at_100
      value: 61.751
    - type: ndcg_at_1000
      value: 62.873999999999995
    - type: ndcg_at_20
      value: 58.521
    - type: ndcg_at_3
      value: 50.995999999999995
    - type: ndcg_at_5
      value: 54.049
    - type: precision_at_1
      value: 45.043
    - type: precision_at_10
      value: 10.51
    - type: precision_at_100
      value: 1.521
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_20
      value: 5.958
    - type: precision_at_3
      value: 24.703
    - type: precision_at_5
      value: 17.671
    - type: recall_at_1
      value: 36.346000000000004
    - type: recall_at_10
      value: 69.95
    - type: recall_at_100
      value: 91.449
    - type: recall_at_1000
      value: 98.021
    - type: recall_at_20
      value: 76.522
    - type: recall_at_3
      value: 54.348
    - type: recall_at_5
      value: 62.271
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 28.754
    - type: map_at_10
      value: 42.921
    - type: map_at_100
      value: 44.440000000000005
    - type: map_at_1000
      value: 44.516
    - type: map_at_20
      value: 43.815
    - type: map_at_3
      value: 38.592999999999996
    - type: map_at_5
      value: 41.138999999999996
    - type: mrr_at_1
      value: 36.416
    - type: mrr_at_10
      value: 48.284
    - type: mrr_at_100
      value: 49.086
    - type: mrr_at_1000
      value: 49.116
    - type: mrr_at_20
      value: 48.741
    - type: mrr_at_3
      value: 45.301
    - type: mrr_at_5
      value: 47.104
    - type: ndcg_at_1
      value: 36.416
    - type: ndcg_at_10
      value: 50.257
    - type: ndcg_at_100
      value: 55.931
    - type: ndcg_at_1000
      value: 57.188
    - type: ndcg_at_20
      value: 52.607000000000006
    - type: ndcg_at_3
      value: 43.787
    - type: ndcg_at_5
      value: 46.941
    - type: precision_at_1
      value: 36.416
    - type: precision_at_10
      value: 9.783
    - type: precision_at_100
      value: 1.465
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_20
      value: 5.713
    - type: precision_at_3
      value: 21.804000000000002
    - type: precision_at_5
      value: 16.05
    - type: recall_at_1
      value: 28.754
    - type: recall_at_10
      value: 66.31099999999999
    - type: recall_at_100
      value: 90.034
    - type: recall_at_1000
      value: 98.058
    - type: recall_at_20
      value: 74.411
    - type: recall_at_3
      value: 48.332
    - type: recall_at_5
      value: 56.548
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 30.579583333333332
    - type: map_at_10
      value: 42.696333333333335
    - type: map_at_100
      value: 44.078583333333334
    - type: map_at_1000
      value: 44.176333333333325
    - type: map_at_20
      value: 43.499833333333335
    - type: map_at_3
      value: 38.953583333333334
    - type: map_at_5
      value: 41.125583333333324
    - type: mrr_at_1
      value: 36.52666666666667
    - type: mrr_at_10
      value: 46.925666666666665
    - type: mrr_at_100
      value: 47.74333333333334
    - type: mrr_at_1000
      value: 47.78266666666667
    - type: mrr_at_20
      value: 47.42483333333333
    - type: mrr_at_3
      value: 44.068083333333334
    - type: mrr_at_5
      value: 45.82383333333333
    - type: ndcg_at_1
      value: 36.52666666666667
    - type: ndcg_at_10
      value: 49.1145
    - type: ndcg_at_100
      value: 54.340583333333335
    - type: ndcg_at_1000
      value: 55.90625
    - type: ndcg_at_20
      value: 51.32724999999999
    - type: ndcg_at_3
      value: 43.146
    - type: ndcg_at_5
      value: 46.146166666666666
    - type: precision_at_1
      value: 36.52666666666667
    - type: precision_at_10
      value: 8.866916666666667
    - type: precision_at_100
      value: 1.3526666666666667
    - type: precision_at_1000
      value: 0.1670833333333333
    - type: precision_at_20
      value: 5.199416666666667
    - type: precision_at_3
      value: 20.278333333333332
    - type: precision_at_5
      value: 14.614999999999997
    - type: recall_at_1
      value: 30.579583333333332
    - type: recall_at_10
      value: 63.618416666666675
    - type: recall_at_100
      value: 85.86858333333332
    - type: recall_at_1000
      value: 96.24825
    - type: recall_at_20
      value: 71.52533333333334
    - type: recall_at_3
      value: 47.18050000000001
    - type: recall_at_5
      value: 54.90683333333334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 26.180999999999997
    - type: map_at_10
      value: 36.4
    - type: map_at_100
      value: 37.464999999999996
    - type: map_at_1000
      value: 37.556
    - type: map_at_20
      value: 36.984
    - type: map_at_3
      value: 33.354
    - type: map_at_5
      value: 35.214
    - type: mrr_at_1
      value: 29.601
    - type: mrr_at_10
      value: 39.328
    - type: mrr_at_100
      value: 40.113
    - type: mrr_at_1000
      value: 40.176
    - type: mrr_at_20
      value: 39.751999999999995
    - type: mrr_at_3
      value: 36.58
    - type: mrr_at_5
      value: 38.313
    - type: ndcg_at_1
      value: 29.601
    - type: ndcg_at_10
      value: 42.037
    - type: ndcg_at_100
      value: 46.946
    - type: ndcg_at_1000
      value: 49.075
    - type: ndcg_at_20
      value: 43.827
    - type: ndcg_at_3
      value: 36.473
    - type: ndcg_at_5
      value: 39.482
    - type: precision_at_1
      value: 29.601
    - type: precision_at_10
      value: 7.009
    - type: precision_at_100
      value: 1.0290000000000001
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_20
      value: 4.018
    - type: precision_at_3
      value: 16.36
    - type: precision_at_5
      value: 11.779
    - type: recall_at_1
      value: 26.180999999999997
    - type: recall_at_10
      value: 56.275
    - type: recall_at_100
      value: 78.61200000000001
    - type: recall_at_1000
      value: 93.887
    - type: recall_at_20
      value: 62.798
    - type: recall_at_3
      value: 41.157
    - type: recall_at_5
      value: 48.49
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 20.205000000000002
    - type: map_at_10
      value: 29.947000000000003
    - type: map_at_100
      value: 31.342
    - type: map_at_1000
      value: 31.458000000000002
    - type: map_at_20
      value: 30.741000000000003
    - type: map_at_3
      value: 26.568
    - type: map_at_5
      value: 28.372999999999998
    - type: mrr_at_1
      value: 24.742
    - type: mrr_at_10
      value: 33.941
    - type: mrr_at_100
      value: 34.92
    - type: mrr_at_1000
      value: 34.981
    - type: mrr_at_20
      value: 34.509
    - type: mrr_at_3
      value: 31.097
    - type: mrr_at_5
      value: 32.631
    - type: ndcg_at_1
      value: 24.742
    - type: ndcg_at_10
      value: 35.884
    - type: ndcg_at_100
      value: 41.839999999999996
    - type: ndcg_at_1000
      value: 44.162
    - type: ndcg_at_20
      value: 38.273
    - type: ndcg_at_3
      value: 30.073
    - type: ndcg_at_5
      value: 32.617000000000004
    - type: precision_at_1
      value: 24.742
    - type: precision_at_10
      value: 6.958
    - type: precision_at_100
      value: 1.155
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_20
      value: 4.202
    - type: precision_at_3
      value: 14.568
    - type: precision_at_5
      value: 10.757
    - type: recall_at_1
      value: 20.205000000000002
    - type: recall_at_10
      value: 49.603
    - type: recall_at_100
      value: 75.77000000000001
    - type: recall_at_1000
      value: 91.767
    - type: recall_at_20
      value: 58.309
    - type: recall_at_3
      value: 33.353
    - type: recall_at_5
      value: 39.947
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 31.543
    - type: map_at_10
      value: 43.895
    - type: map_at_100
      value: 45.233000000000004
    - type: map_at_1000
      value: 45.314
    - type: map_at_20
      value: 44.707
    - type: map_at_3
      value: 40.165
    - type: map_at_5
      value: 42.353
    - type: mrr_at_1
      value: 37.5
    - type: mrr_at_10
      value: 47.814
    - type: mrr_at_100
      value: 48.701
    - type: mrr_at_1000
      value: 48.74
    - type: mrr_at_20
      value: 48.378
    - type: mrr_at_3
      value: 45.04
    - type: mrr_at_5
      value: 46.729
    - type: ndcg_at_1
      value: 37.5
    - type: ndcg_at_10
      value: 50.312999999999995
    - type: ndcg_at_100
      value: 55.696999999999996
    - type: ndcg_at_1000
      value: 57.135000000000005
    - type: ndcg_at_20
      value: 52.734
    - type: ndcg_at_3
      value: 44.263000000000005
    - type: ndcg_at_5
      value: 47.268
    - type: precision_at_1
      value: 37.5
    - type: precision_at_10
      value: 8.871
    - type: precision_at_100
      value: 1.278
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_20
      value: 5.117
    - type: precision_at_3
      value: 20.709
    - type: precision_at_5
      value: 14.832
    - type: recall_at_1
      value: 31.543
    - type: recall_at_10
      value: 65.694
    - type: recall_at_100
      value: 88.105
    - type: recall_at_1000
      value: 97.38
    - type: recall_at_20
      value: 74.307
    - type: recall_at_3
      value: 49.254999999999995
    - type: recall_at_5
      value: 56.85
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 29.325000000000003
    - type: map_at_10
      value: 40.653
    - type: map_at_100
      value: 42.568
    - type: map_at_1000
      value: 42.782
    - type: map_at_20
      value: 41.638999999999996
    - type: map_at_3
      value: 36.726
    - type: map_at_5
      value: 38.911
    - type: mrr_at_1
      value: 34.98
    - type: mrr_at_10
      value: 45.281
    - type: mrr_at_100
      value: 46.255
    - type: mrr_at_1000
      value: 46.29
    - type: mrr_at_20
      value: 45.94
    - type: mrr_at_3
      value: 41.831
    - type: mrr_at_5
      value: 44.045
    - type: ndcg_at_1
      value: 34.98
    - type: ndcg_at_10
      value: 47.629
    - type: ndcg_at_100
      value: 53.912000000000006
    - type: ndcg_at_1000
      value: 55.48
    - type: ndcg_at_20
      value: 50.281
    - type: ndcg_at_3
      value: 41.211999999999996
    - type: ndcg_at_5
      value: 44.529
    - type: precision_at_1
      value: 34.98
    - type: precision_at_10
      value: 9.229
    - type: precision_at_100
      value: 1.854
    - type: precision_at_1000
      value: 0.258
    - type: precision_at_20
      value: 5.8500000000000005
    - type: precision_at_3
      value: 19.631
    - type: precision_at_5
      value: 14.506
    - type: recall_at_1
      value: 29.325000000000003
    - type: recall_at_10
      value: 61.894000000000005
    - type: recall_at_100
      value: 88.684
    - type: recall_at_1000
      value: 97.83800000000001
    - type: recall_at_20
      value: 71.758
    - type: recall_at_3
      value: 44.265
    - type: recall_at_5
      value: 53.051
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 23.133
    - type: map_at_10
      value: 33.263
    - type: map_at_100
      value: 34.496
    - type: map_at_1000
      value: 34.582
    - type: map_at_20
      value: 33.983999999999995
    - type: map_at_3
      value: 30.12
    - type: map_at_5
      value: 31.906000000000002
    - type: mrr_at_1
      value: 25.507999999999996
    - type: mrr_at_10
      value: 35.663
    - type: mrr_at_100
      value: 36.659000000000006
    - type: mrr_at_1000
      value: 36.714
    - type: mrr_at_20
      value: 36.236000000000004
    - type: mrr_at_3
      value: 32.748
    - type: mrr_at_5
      value: 34.365
    - type: ndcg_at_1
      value: 25.507999999999996
    - type: ndcg_at_10
      value: 38.968
    - type: ndcg_at_100
      value: 44.674
    - type: ndcg_at_1000
      value: 46.725
    - type: ndcg_at_20
      value: 41.282000000000004
    - type: ndcg_at_3
      value: 33.038000000000004
    - type: ndcg_at_5
      value: 35.909
    - type: precision_at_1
      value: 25.507999999999996
    - type: precision_at_10
      value: 6.285
    - type: precision_at_100
      value: 0.98
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_20
      value: 3.7249999999999996
    - type: precision_at_3
      value: 14.171
    - type: precision_at_5
      value: 10.314
    - type: recall_at_1
      value: 23.133
    - type: recall_at_10
      value: 54.042
    - type: recall_at_100
      value: 80.01599999999999
    - type: recall_at_1000
      value: 95.05799999999999
    - type: recall_at_20
      value: 62.643
    - type: recall_at_3
      value: 38.367000000000004
    - type: recall_at_5
      value: 45.123000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 13.923
    - type: map_at_10
      value: 23.415
    - type: map_at_100
      value: 25.389
    - type: map_at_1000
      value: 25.539
    - type: map_at_20
      value: 24.462
    - type: map_at_3
      value: 19.719
    - type: map_at_5
      value: 21.75
    - type: mrr_at_1
      value: 31.205
    - type: mrr_at_10
      value: 43.196
    - type: mrr_at_100
      value: 44.039
    - type: mrr_at_1000
      value: 44.071
    - type: mrr_at_20
      value: 43.744
    - type: mrr_at_3
      value: 40.033
    - type: mrr_at_5
      value: 41.967
    - type: ndcg_at_1
      value: 31.205
    - type: ndcg_at_10
      value: 32.304
    - type: ndcg_at_100
      value: 39.717
    - type: ndcg_at_1000
      value: 42.559999999999995
    - type: ndcg_at_20
      value: 35.166
    - type: ndcg_at_3
      value: 26.955000000000002
    - type: ndcg_at_5
      value: 28.967
    - type: precision_at_1
      value: 31.205
    - type: precision_at_10
      value: 9.948
    - type: precision_at_100
      value: 1.7870000000000001
    - type: precision_at_1000
      value: 0.233
    - type: precision_at_20
      value: 6.205
    - type: precision_at_3
      value: 20.108999999999998
    - type: precision_at_5
      value: 15.453
    - type: recall_at_1
      value: 13.923
    - type: recall_at_10
      value: 37.885000000000005
    - type: recall_at_100
      value: 63.352
    - type: recall_at_1000
      value: 79.372
    - type: recall_at_20
      value: 45.954
    - type: recall_at_3
      value: 24.511
    - type: recall_at_5
      value: 30.451
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 9.584
    - type: map_at_10
      value: 23.432
    - type: map_at_100
      value: 32.513
    - type: map_at_1000
      value: 34.27
    - type: map_at_20
      value: 27.18
    - type: map_at_3
      value: 16.145
    - type: map_at_5
      value: 19.405
    - type: mrr_at_1
      value: 74.5
    - type: mrr_at_10
      value: 81.233
    - type: mrr_at_100
      value: 81.463
    - type: mrr_at_1000
      value: 81.46900000000001
    - type: mrr_at_20
      value: 81.394
    - type: mrr_at_3
      value: 79.958
    - type: mrr_at_5
      value: 80.808
    - type: ndcg_at_1
      value: 62.125
    - type: ndcg_at_10
      value: 48.047000000000004
    - type: ndcg_at_100
      value: 52.251999999999995
    - type: ndcg_at_1000
      value: 59.353
    - type: ndcg_at_20
      value: 47.264
    - type: ndcg_at_3
      value: 52.891999999999996
    - type: ndcg_at_5
      value: 50.766999999999996
    - type: precision_at_1
      value: 74.5
    - type: precision_at_10
      value: 38.15
    - type: precision_at_100
      value: 11.51
    - type: precision_at_1000
      value: 2.183
    - type: precision_at_20
      value: 28.749999999999996
    - type: precision_at_3
      value: 56.25
    - type: precision_at_5
      value: 49.1
    - type: recall_at_1
      value: 9.584
    - type: recall_at_10
      value: 29.215999999999998
    - type: recall_at_100
      value: 57.914
    - type: recall_at_1000
      value: 80.67699999999999
    - type: recall_at_20
      value: 37.358000000000004
    - type: recall_at_3
      value: 17.422
    - type: recall_at_5
      value: 22.345000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 91.36000000000001
    - type: f1
      value: 87.72724279223316
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 78.81700000000001
    - type: map_at_10
      value: 86.392
    - type: map_at_100
      value: 86.6
    - type: map_at_1000
      value: 86.611
    - type: map_at_20
      value: 86.521
    - type: map_at_3
      value: 85.31
    - type: map_at_5
      value: 86.047
    - type: mrr_at_1
      value: 84.878
    - type: mrr_at_10
      value: 90.359
    - type: mrr_at_100
      value: 90.426
    - type: mrr_at_1000
      value: 90.427
    - type: mrr_at_20
      value: 90.405
    - type: mrr_at_3
      value: 89.761
    - type: mrr_at_5
      value: 90.191
    - type: ndcg_at_1
      value: 84.878
    - type: ndcg_at_10
      value: 89.459
    - type: ndcg_at_100
      value: 90.171
    - type: ndcg_at_1000
      value: 90.349
    - type: ndcg_at_20
      value: 89.788
    - type: ndcg_at_3
      value: 87.908
    - type: ndcg_at_5
      value: 88.844
    - type: precision_at_1
      value: 84.878
    - type: precision_at_10
      value: 10.639
    - type: precision_at_100
      value: 1.123
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_20
      value: 5.427
    - type: precision_at_3
      value: 33.333
    - type: precision_at_5
      value: 20.696
    - type: recall_at_1
      value: 78.81700000000001
    - type: recall_at_10
      value: 94.959
    - type: recall_at_100
      value: 97.72800000000001
    - type: recall_at_1000
      value: 98.791
    - type: recall_at_20
      value: 96.036
    - type: recall_at_3
      value: 90.727
    - type: recall_at_5
      value: 93.12899999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 29.596
    - type: map_at_10
      value: 50.833
    - type: map_at_100
      value: 53.034000000000006
    - type: map_at_1000
      value: 53.135
    - type: map_at_20
      value: 52.195
    - type: map_at_3
      value: 44.247
    - type: map_at_5
      value: 48.107
    - type: mrr_at_1
      value: 57.87
    - type: mrr_at_10
      value: 65.566
    - type: mrr_at_100
      value: 66.15299999999999
    - type: mrr_at_1000
      value: 66.168
    - type: mrr_at_20
      value: 65.923
    - type: mrr_at_3
      value: 63.55499999999999
    - type: mrr_at_5
      value: 64.727
    - type: ndcg_at_1
      value: 57.87
    - type: ndcg_at_10
      value: 58.943999999999996
    - type: ndcg_at_100
      value: 65.283
    - type: ndcg_at_1000
      value: 66.706
    - type: ndcg_at_20
      value: 61.778999999999996
    - type: ndcg_at_3
      value: 54.554
    - type: ndcg_at_5
      value: 56.159000000000006
    - type: precision_at_1
      value: 57.87
    - type: precision_at_10
      value: 16.435
    - type: precision_at_100
      value: 2.307
    - type: precision_at_1000
      value: 0.256
    - type: precision_at_20
      value: 9.522
    - type: precision_at_3
      value: 36.986000000000004
    - type: precision_at_5
      value: 27.16
    - type: recall_at_1
      value: 29.596
    - type: recall_at_10
      value: 66.705
    - type: recall_at_100
      value: 89.45
    - type: recall_at_1000
      value: 97.758
    - type: recall_at_20
      value: 75.13300000000001
    - type: recall_at_3
      value: 49.689
    - type: recall_at_5
      value: 57.701
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 42.532
    - type: map_at_10
      value: 71.931
    - type: map_at_100
      value: 72.623
    - type: map_at_1000
      value: 72.662
    - type: map_at_20
      value: 72.355
    - type: map_at_3
      value: 68.72200000000001
    - type: map_at_5
      value: 70.813
    - type: mrr_at_1
      value: 85.064
    - type: mrr_at_10
      value: 89.69500000000001
    - type: mrr_at_100
      value: 89.792
    - type: mrr_at_1000
      value: 89.795
    - type: mrr_at_20
      value: 89.759
    - type: mrr_at_3
      value: 89.129
    - type: mrr_at_5
      value: 89.5
    - type: ndcg_at_1
      value: 85.064
    - type: ndcg_at_10
      value: 78.86999999999999
    - type: ndcg_at_100
      value: 81.134
    - type: ndcg_at_1000
      value: 81.862
    - type: ndcg_at_20
      value: 79.888
    - type: ndcg_at_3
      value: 74.579
    - type: ndcg_at_5
      value: 77.086
    - type: precision_at_1
      value: 85.064
    - type: precision_at_10
      value: 16.433
    - type: precision_at_100
      value: 1.818
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_20
      value: 8.545
    - type: precision_at_3
      value: 48.508
    - type: precision_at_5
      value: 31.084
    - type: recall_at_1
      value: 42.532
    - type: recall_at_10
      value: 82.167
    - type: recall_at_100
      value: 90.905
    - type: recall_at_1000
      value: 95.699
    - type: recall_at_20
      value: 85.449
    - type: recall_at_3
      value: 72.762
    - type: recall_at_5
      value: 77.711
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 96.91919999999999
    - type: ap
      value: 95.88443935380744
    - type: f1
      value: 96.91873838978964
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 21.747
    - type: map_at_10
      value: 34.764
    - type: map_at_100
      value: 35.981
    - type: map_at_1000
      value: 36.027
    - type: map_at_20
      value: 35.557
    - type: map_at_3
      value: 30.770999999999997
    - type: map_at_5
      value: 33.07
    - type: mrr_at_1
      value: 22.421
    - type: mrr_at_10
      value: 35.417
    - type: mrr_at_100
      value: 36.57
    - type: mrr_at_1000
      value: 36.61
    - type: mrr_at_20
      value: 36.174
    - type: mrr_at_3
      value: 31.516
    - type: mrr_at_5
      value: 33.783
    - type: ndcg_at_1
      value: 22.421
    - type: ndcg_at_10
      value: 42.003
    - type: ndcg_at_100
      value: 47.674
    - type: ndcg_at_1000
      value: 48.783
    - type: ndcg_at_20
      value: 44.789
    - type: ndcg_at_3
      value: 33.918
    - type: ndcg_at_5
      value: 38.011
    - type: precision_at_1
      value: 22.421
    - type: precision_at_10
      value: 6.712
    - type: precision_at_100
      value: 0.9520000000000001
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_20
      value: 3.9309999999999996
    - type: precision_at_3
      value: 14.632000000000001
    - type: precision_at_5
      value: 10.845
    - type: recall_at_1
      value: 21.747
    - type: recall_at_10
      value: 64.2
    - type: recall_at_100
      value: 90.04100000000001
    - type: recall_at_1000
      value: 98.41499999999999
    - type: recall_at_20
      value: 74.982
    - type: recall_at_3
      value: 42.303000000000004
    - type: recall_at_5
      value: 52.11
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 99.02872777017784
    - type: f1
      value: 98.8785703018425
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 90.93935248518011
    - type: f1
      value: 75.46510480635821
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 82.49831876260927
    - type: f1
      value: 79.43439001730579
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 84.50235373234702
    - type: f1
      value: 84.03906668934695
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 42.634572576984716
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 40.96861872930255
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.986207669202933
    - type: mrr
      value: 33.11375583060012
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 6.783
    - type: map_at_10
      value: 16.276
    - type: map_at_100
      value: 21.324
    - type: map_at_1000
      value: 23.166
    - type: map_at_20
      value: 18.383
    - type: map_at_3
      value: 11.296000000000001
    - type: map_at_5
      value: 13.504
    - type: mrr_at_1
      value: 53.559999999999995
    - type: mrr_at_10
      value: 61.589000000000006
    - type: mrr_at_100
      value: 62.11600000000001
    - type: mrr_at_1000
      value: 62.158
    - type: mrr_at_20
      value: 61.976
    - type: mrr_at_3
      value: 59.855999999999995
    - type: mrr_at_5
      value: 60.877
    - type: ndcg_at_1
      value: 50.15500000000001
    - type: ndcg_at_10
      value: 42.598
    - type: ndcg_at_100
      value: 39.15
    - type: ndcg_at_1000
      value: 47.888999999999996
    - type: ndcg_at_20
      value: 39.956
    - type: ndcg_at_3
      value: 46.836
    - type: ndcg_at_5
      value: 45.001000000000005
    - type: precision_at_1
      value: 52.322
    - type: precision_at_10
      value: 32.601
    - type: precision_at_100
      value: 10.145999999999999
    - type: precision_at_1000
      value: 2.358
    - type: precision_at_20
      value: 24.025
    - type: precision_at_3
      value: 44.169000000000004
    - type: precision_at_5
      value: 39.628
    - type: recall_at_1
      value: 6.783
    - type: recall_at_10
      value: 21.175
    - type: recall_at_100
      value: 40.097
    - type: recall_at_1000
      value: 71.65
    - type: recall_at_20
      value: 26.465
    - type: recall_at_3
      value: 12.589
    - type: recall_at_5
      value: 15.867999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 43.376
    - type: map_at_10
      value: 60.968
    - type: map_at_100
      value: 61.614999999999995
    - type: map_at_1000
      value: 61.626000000000005
    - type: map_at_20
      value: 61.441
    - type: map_at_3
      value: 56.858
    - type: map_at_5
      value: 59.476
    - type: mrr_at_1
      value: 48.841
    - type: mrr_at_10
      value: 63.366
    - type: mrr_at_100
      value: 63.79
    - type: mrr_at_1000
      value: 63.797000000000004
    - type: mrr_at_20
      value: 63.682
    - type: mrr_at_3
      value: 60.535000000000004
    - type: mrr_at_5
      value: 62.348000000000006
    - type: ndcg_at_1
      value: 48.841
    - type: ndcg_at_10
      value: 68.362
    - type: ndcg_at_100
      value: 70.799
    - type: ndcg_at_1000
      value: 71.004
    - type: ndcg_at_20
      value: 69.804
    - type: ndcg_at_3
      value: 61.251
    - type: ndcg_at_5
      value: 65.28500000000001
    - type: precision_at_1
      value: 48.841
    - type: precision_at_10
      value: 10.588000000000001
    - type: precision_at_100
      value: 1.194
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_20
      value: 5.646
    - type: precision_at_3
      value: 27.298000000000002
    - type: precision_at_5
      value: 18.841
    - type: recall_at_1
      value: 43.376
    - type: recall_at_10
      value: 88.053
    - type: recall_at_100
      value: 98.194
    - type: recall_at_1000
      value: 99.67200000000001
    - type: recall_at_20
      value: 93.318
    - type: recall_at_3
      value: 70.281
    - type: recall_at_5
      value: 79.28
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 71.477
    - type: map_at_10
      value: 85.548
    - type: map_at_100
      value: 86.187
    - type: map_at_1000
      value: 86.199
    - type: map_at_20
      value: 85.971
    - type: map_at_3
      value: 82.50999999999999
    - type: map_at_5
      value: 84.447
    - type: mrr_at_1
      value: 82.35
    - type: mrr_at_10
      value: 88.039
    - type: mrr_at_100
      value: 88.14699999999999
    - type: mrr_at_1000
      value: 88.14699999999999
    - type: mrr_at_20
      value: 88.12100000000001
    - type: mrr_at_3
      value: 87.048
    - type: mrr_at_5
      value: 87.73100000000001
    - type: ndcg_at_1
      value: 82.35
    - type: ndcg_at_10
      value: 89.024
    - type: ndcg_at_100
      value: 90.18599999999999
    - type: ndcg_at_1000
      value: 90.245
    - type: ndcg_at_20
      value: 89.67399999999999
    - type: ndcg_at_3
      value: 86.167
    - type: ndcg_at_5
      value: 87.779
    - type: precision_at_1
      value: 82.35
    - type: precision_at_10
      value: 13.565
    - type: precision_at_100
      value: 1.544
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_20
      value: 7.2010000000000005
    - type: precision_at_3
      value: 37.773
    - type: precision_at_5
      value: 24.924
    - type: recall_at_1
      value: 71.477
    - type: recall_at_10
      value: 95.821
    - type: recall_at_100
      value: 99.737
    - type: recall_at_1000
      value: 99.98599999999999
    - type: recall_at_20
      value: 97.90100000000001
    - type: recall_at_3
      value: 87.61
    - type: recall_at_5
      value: 92.135
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 66.43811157811552
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 69.56403346330322
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 6.253
    - type: map_at_10
      value: 17.379
    - type: map_at_100
      value: 20.51
    - type: map_at_1000
      value: 20.881
    - type: map_at_20
      value: 18.983
    - type: map_at_3
      value: 12.061
    - type: map_at_5
      value: 14.546000000000001
    - type: mrr_at_1
      value: 30.8
    - type: mrr_at_10
      value: 43.814
    - type: mrr_at_100
      value: 44.883
    - type: mrr_at_1000
      value: 44.906
    - type: mrr_at_20
      value: 44.555
    - type: mrr_at_3
      value: 40.416999999999994
    - type: mrr_at_5
      value: 42.482
    - type: ndcg_at_1
      value: 30.8
    - type: ndcg_at_10
      value: 27.694999999999997
    - type: ndcg_at_100
      value: 38.248
    - type: ndcg_at_1000
      value: 43.547000000000004
    - type: ndcg_at_20
      value: 31.573
    - type: ndcg_at_3
      value: 26.239
    - type: ndcg_at_5
      value: 22.817999999999998
    - type: precision_at_1
      value: 30.8
    - type: precision_at_10
      value: 14.540000000000001
    - type: precision_at_100
      value: 2.9690000000000003
    - type: precision_at_1000
      value: 0.422
    - type: precision_at_20
      value: 9.5
    - type: precision_at_3
      value: 24.967
    - type: precision_at_5
      value: 20.22
    - type: recall_at_1
      value: 6.253
    - type: recall_at_10
      value: 29.465000000000003
    - type: recall_at_100
      value: 60.28
    - type: recall_at_1000
      value: 85.712
    - type: recall_at_20
      value: 38.578
    - type: recall_at_3
      value: 15.201999999999998
    - type: recall_at_5
      value: 20.507
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 86.88263045065128
    - type: cos_sim_spearman
      value: 83.2199052396249
    - type: euclidean_pearson
      value: 83.89316748784084
    - type: euclidean_spearman
      value: 82.80089923470608
    - type: manhattan_pearson
      value: 83.79340504513027
    - type: manhattan_spearman
      value: 82.57647453394455
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 87.23417612553622
    - type: cos_sim_spearman
      value: 79.40077017685032
    - type: euclidean_pearson
      value: 82.98069591415172
    - type: euclidean_spearman
      value: 77.72626690650102
    - type: manhattan_pearson
      value: 83.2549008896714
    - type: manhattan_spearman
      value: 77.97517379409553
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 89.94319057478221
    - type: cos_sim_spearman
      value: 89.57673217959568
    - type: euclidean_pearson
      value: 88.52164819479393
    - type: euclidean_spearman
      value: 89.28792930444656
    - type: manhattan_pearson
      value: 88.63748131889201
    - type: manhattan_spearman
      value: 89.5337354128652
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 87.0002285020644
    - type: cos_sim_spearman
      value: 84.85558709405255
    - type: euclidean_pearson
      value: 85.76743275817024
    - type: euclidean_spearman
      value: 84.7900299161083
    - type: manhattan_pearson
      value: 85.81372778099167
    - type: manhattan_spearman
      value: 84.88975144080597
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 89.90992300865088
    - type: cos_sim_spearman
      value: 89.89952259773258
    - type: euclidean_pearson
      value: 88.95472170794739
    - type: euclidean_spearman
      value: 89.79840257558794
    - type: manhattan_pearson
      value: 89.00903847816028
    - type: manhattan_spearman
      value: 89.99292271664685
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 85.75044299994977
    - type: cos_sim_spearman
      value: 86.31137676221347
    - type: euclidean_pearson
      value: 85.03198959400133
    - type: euclidean_spearman
      value: 85.62611072515675
    - type: manhattan_pearson
      value: 85.11681545306745
    - type: manhattan_spearman
      value: 85.75766564037835
  - 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: 91.85595137809975
    - type: cos_sim_spearman
      value: 91.19454529401669
    - type: euclidean_pearson
      value: 90.88727698604517
    - type: euclidean_spearman
      value: 90.93184869101279
    - type: manhattan_pearson
      value: 90.79591587599141
    - type: manhattan_spearman
      value: 90.75783237234161
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 71.60579944207497
    - type: cos_sim_spearman
      value: 70.08286575049202
    - type: euclidean_pearson
      value: 71.83195353568124
    - type: euclidean_spearman
      value: 70.3030975376705
    - type: manhattan_pearson
      value: 71.80222200714064
    - type: manhattan_spearman
      value: 70.04005646739672
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 89.65716781275425
    - type: cos_sim_spearman
      value: 89.90701888074334
    - type: euclidean_pearson
      value: 88.50498754631819
    - type: euclidean_spearman
      value: 88.88763469318933
    - type: manhattan_pearson
      value: 88.58398429591064
    - type: manhattan_spearman
      value: 89.0138386837653
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 89.26199160020026
    - type: mrr
      value: 96.86981772766087
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 62.827999999999996
    - type: map_at_10
      value: 74.028
    - type: map_at_100
      value: 74.264
    - type: map_at_1000
      value: 74.274
    - type: map_at_20
      value: 74.18599999999999
    - type: map_at_3
      value: 70.787
    - type: map_at_5
      value: 72.87
    - type: mrr_at_1
      value: 66.333
    - type: mrr_at_10
      value: 74.894
    - type: mrr_at_100
      value: 75.09599999999999
    - type: mrr_at_1000
      value: 75.105
    - type: mrr_at_20
      value: 75.024
    - type: mrr_at_3
      value: 72.833
    - type: mrr_at_5
      value: 73.917
    - type: ndcg_at_1
      value: 66.333
    - type: ndcg_at_10
      value: 78.82000000000001
    - type: ndcg_at_100
      value: 79.95
    - type: ndcg_at_1000
      value: 80.207
    - type: ndcg_at_20
      value: 79.324
    - type: ndcg_at_3
      value: 73.87899999999999
    - type: ndcg_at_5
      value: 76.399
    - type: precision_at_1
      value: 66.333
    - type: precision_at_10
      value: 10.5
    - type: precision_at_100
      value: 1.11
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 5.367
    - type: precision_at_3
      value: 29.110999999999997
    - type: precision_at_5
      value: 19.333
    - type: recall_at_1
      value: 62.827999999999996
    - type: recall_at_10
      value: 92.667
    - type: recall_at_100
      value: 98.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 94.5
    - type: recall_at_3
      value: 79.5
    - type: recall_at_5
      value: 85.739
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.85940594059406
    - type: cos_sim_ap
      value: 96.72065839344104
    - type: cos_sim_f1
      value: 92.85714285714286
    - type: cos_sim_precision
      value: 93.42105263157895
    - type: cos_sim_recall
      value: 92.30000000000001
    - type: dot_accuracy
      value: 99.84752475247525
    - type: dot_ap
      value: 96.41536649209695
    - type: dot_f1
      value: 92.24572004028197
    - type: dot_precision
      value: 92.90060851926978
    - type: dot_recall
      value: 91.60000000000001
    - type: euclidean_accuracy
      value: 99.86039603960396
    - type: euclidean_ap
      value: 96.63078081708719
    - type: euclidean_f1
      value: 92.87518948964124
    - type: euclidean_precision
      value: 93.87129724208376
    - type: euclidean_recall
      value: 91.9
    - type: manhattan_accuracy
      value: 99.86435643564356
    - type: manhattan_ap
      value: 96.71272943532432
    - type: manhattan_f1
      value: 93.05625950329447
    - type: manhattan_precision
      value: 94.34737923946557
    - type: manhattan_recall
      value: 91.8
    - type: max_accuracy
      value: 99.86435643564356
    - type: max_ap
      value: 96.72065839344104
    - type: max_f1
      value: 93.05625950329447
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 75.95483275621876
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 46.20364113200157
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 56.2577092438525
    - type: mrr
      value: 57.40251782531194
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.492357459875645
    - type: cos_sim_spearman
      value: 30.868968719156825
    - type: dot_pearson
      value: 29.44619482351129
    - type: dot_spearman
      value: 31.295984532577215
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.22200000000000003
    - type: map_at_10
      value: 1.9290000000000003
    - type: map_at_100
      value: 12.435
    - type: map_at_1000
      value: 32.352
    - type: map_at_20
      value: 3.496
    - type: map_at_3
      value: 0.637
    - type: map_at_5
      value: 1.016
    - type: mrr_at_1
      value: 86.0
    - type: mrr_at_10
      value: 92.333
    - type: mrr_at_100
      value: 92.333
    - type: mrr_at_1000
      value: 92.333
    - type: mrr_at_20
      value: 92.333
    - type: mrr_at_3
      value: 92.0
    - type: mrr_at_5
      value: 92.0
    - type: ndcg_at_1
      value: 81.0
    - type: ndcg_at_10
      value: 75.32900000000001
    - type: ndcg_at_100
      value: 62.756
    - type: ndcg_at_1000
      value: 59.232
    - type: ndcg_at_20
      value: 73.393
    - type: ndcg_at_3
      value: 78.469
    - type: ndcg_at_5
      value: 76.953
    - type: precision_at_1
      value: 86.0
    - type: precision_at_10
      value: 79.4
    - type: precision_at_100
      value: 64.94
    - type: precision_at_1000
      value: 26.332
    - type: precision_at_20
      value: 77.3
    - type: precision_at_3
      value: 82.667
    - type: precision_at_5
      value: 80.4
    - type: recall_at_1
      value: 0.22200000000000003
    - type: recall_at_10
      value: 2.113
    - type: recall_at_100
      value: 16.02
    - type: recall_at_1000
      value: 57.227
    - type: recall_at_20
      value: 4.036
    - type: recall_at_3
      value: 0.6689999999999999
    - type: recall_at_5
      value: 1.076
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.83
    - type: map_at_10
      value: 8.981
    - type: map_at_100
      value: 14.796000000000001
    - type: map_at_1000
      value: 16.451999999999998
    - type: map_at_20
      value: 11.361
    - type: map_at_3
      value: 5.143
    - type: map_at_5
      value: 6.537
    - type: mrr_at_1
      value: 36.735
    - type: mrr_at_10
      value: 50.99399999999999
    - type: mrr_at_100
      value: 51.775000000000006
    - type: mrr_at_1000
      value: 51.775000000000006
    - type: mrr_at_20
      value: 51.39
    - type: mrr_at_3
      value: 47.278999999999996
    - type: mrr_at_5
      value: 49.626
    - type: ndcg_at_1
      value: 34.694
    - type: ndcg_at_10
      value: 24.061
    - type: ndcg_at_100
      value: 35.832
    - type: ndcg_at_1000
      value: 47.875
    - type: ndcg_at_20
      value: 25.022
    - type: ndcg_at_3
      value: 27.939999999999998
    - type: ndcg_at_5
      value: 25.246000000000002
    - type: precision_at_1
      value: 36.735
    - type: precision_at_10
      value: 20.204
    - type: precision_at_100
      value: 7.224
    - type: precision_at_1000
      value: 1.516
    - type: precision_at_20
      value: 15.714
    - type: precision_at_3
      value: 27.211000000000002
    - type: precision_at_5
      value: 23.265
    - type: recall_at_1
      value: 2.83
    - type: recall_at_10
      value: 14.564
    - type: recall_at_100
      value: 45.251000000000005
    - type: recall_at_1000
      value: 81.849
    - type: recall_at_20
      value: 22.31
    - type: recall_at_3
      value: 6.065
    - type: recall_at_5
      value: 8.588
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 91.17320000000001
    - type: ap
      value: 41.18509354980418
    - type: f1
      value: 77.77470860794351
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 77.92869269949067
    - type: f1
      value: 78.23271267071486
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 59.59735858830448
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.81069321094355
    - type: cos_sim_ap
      value: 79.1522153826438
    - type: cos_sim_f1
      value: 72.83363802559415
    - type: cos_sim_precision
      value: 67.678369195923
    - type: cos_sim_recall
      value: 78.83905013192613
    - type: dot_accuracy
      value: 87.369613160875
    - type: dot_ap
      value: 78.51617049363121
    - type: dot_f1
      value: 71.89735998026153
    - type: dot_precision
      value: 67.516218721038
    - type: dot_recall
      value: 76.88654353562005
    - type: euclidean_accuracy
      value: 87.72724563390356
    - type: euclidean_ap
      value: 78.45799796334607
    - type: euclidean_f1
      value: 72.7159880834161
    - type: euclidean_precision
      value: 68.65916549460853
    - type: euclidean_recall
      value: 77.28232189973615
    - type: manhattan_accuracy
      value: 87.57823210347499
    - type: manhattan_ap
      value: 78.24705251626389
    - type: manhattan_f1
      value: 72.34365129500948
    - type: manhattan_precision
      value: 69.4060606060606
    - type: manhattan_recall
      value: 75.54089709762533
    - type: max_accuracy
      value: 87.81069321094355
    - type: max_ap
      value: 79.1522153826438
    - type: max_f1
      value: 72.83363802559415
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.76597974152986
    - type: cos_sim_ap
      value: 87.15717597277224
    - type: cos_sim_f1
      value: 79.71815316150567
    - type: cos_sim_precision
      value: 76.89776060671103
    - type: cos_sim_recall
      value: 82.75331074838313
    - type: dot_accuracy
      value: 89.49237396670159
    - type: dot_ap
      value: 86.69824401657353
    - type: dot_f1
      value: 79.39796433985418
    - type: dot_precision
      value: 74.7316211441772
    - type: dot_recall
      value: 84.68586387434554
    - type: euclidean_accuracy
      value: 89.65149221872937
    - type: euclidean_ap
      value: 86.98932847862545
    - type: euclidean_f1
      value: 79.65759212314929
    - type: euclidean_precision
      value: 76.17876466868105
    - type: euclidean_recall
      value: 83.46935632891899
    - type: manhattan_accuracy
      value: 89.63402802033609
    - type: manhattan_ap
      value: 86.99550128469285
    - type: manhattan_f1
      value: 79.61443655494647
    - type: manhattan_precision
      value: 76.23476361586697
    - type: manhattan_recall
      value: 83.30766861718509
    - type: max_accuracy
      value: 89.76597974152986
    - type: max_ap
      value: 87.15717597277224
    - type: max_f1
      value: 79.71815316150567
---

## Model Details:

This embedding model is a fine-tuned 10.7B parameter LLM on the Intel Gaudi 2 processor using the [upstage/SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0).

## Date

July, 2024

## Training Details

Two stage training: 
- General Text Embedding Training
- Specific domains Emebedding Training


More technical details will be updated later.


## Evaluation

The results of (MTEB)[https://huggingface.co/spaces/mteb/leaderboard] (English):

| Model Name | MTEB(56)  || 
|:----:|:---------:|:----------:| 
| [bge-base-en-1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) |   64.23   | 
| [bge-large-en-1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) |   63.55   |
| [gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   65.39   |
| [gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   64.11   |
| [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) |   64.68   |
| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) |   59.45   | 
| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) |   61.50   |
| [e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |   66.63   |
| [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) |   67.34   |
| [NV-Embed-v1](https://huggingface.co/nvidia/NV-Embed-v1) |   69.32   |
| [**neural-embedding-v1**](https://huggingface.co/Intel/neural-embedding-v1) | **69.94** |
 

