sentence-transformers gguf mteb transformers.js transformers llama-cpp gguf-my-repo feature-extraction en base_model:mixedbread-ai/mxbai-embed-large-v1 base_model:quantized:mixedbread-ai/mxbai-embed-large-v1 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: mixedbread-ai/mxbai-embed-large-v1
language:
- en
library_name: sentence-transformers
license: apache-2.0
pipeline_tag: feature-extraction
tags:
- mteb
- transformers.js
- transformers
- llama-cpp
- gguf-my-repo
model-index:
- name: mxbai-angle-large-v1
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.044776119403
    - type: ap
      value: 37.7362433623053
    - type: f1
      value: 68.92736573359774
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.84025000000001
    - type: ap
      value: 90.93190875404055
    - type: f1
      value: 93.8297833897293
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 49.184
    - type: f1
      value: 48.74163227751588
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 41.252
    - type: map_at_10
      value: 57.778
    - type: map_at_100
      value: 58.233000000000004
    - type: map_at_1000
      value: 58.23700000000001
    - type: map_at_3
      value: 53.449999999999996
    - type: map_at_5
      value: 56.376000000000005
    - type: mrr_at_1
      value: 41.679
    - type: mrr_at_10
      value: 57.92699999999999
    - type: mrr_at_100
      value: 58.389
    - type: mrr_at_1000
      value: 58.391999999999996
    - type: mrr_at_3
      value: 53.651
    - type: mrr_at_5
      value: 56.521
    - type: ndcg_at_1
      value: 41.252
    - type: ndcg_at_10
      value: 66.018
    - type: ndcg_at_100
      value: 67.774
    - type: ndcg_at_1000
      value: 67.84400000000001
    - type: ndcg_at_3
      value: 57.372
    - type: ndcg_at_5
      value: 62.646
    - type: precision_at_1
      value: 41.252
    - type: precision_at_10
      value: 9.189
    - type: precision_at_100
      value: 0.991
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 22.902
    - type: precision_at_5
      value: 16.302
    - type: recall_at_1
      value: 41.252
    - type: recall_at_10
      value: 91.892
    - type: recall_at_100
      value: 99.14699999999999
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 68.706
    - type: recall_at_5
      value: 81.50800000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 48.97294504317859
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 42.98071077674629
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 65.16477858490782
    - type: mrr
      value: 78.23583080508287
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 89.6277629421789
    - type: cos_sim_spearman
      value: 88.4056288400568
    - type: euclidean_pearson
      value: 87.94871847578163
    - type: euclidean_spearman
      value: 88.4056288400568
    - type: manhattan_pearson
      value: 87.73271254229648
    - type: manhattan_spearman
      value: 87.91826833762677
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 87.81818181818181
    - type: f1
      value: 87.79879337316918
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.91773608582761
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 36.73059477462478
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 32.745999999999995
    - type: map_at_10
      value: 43.632
    - type: map_at_100
      value: 45.206
    - type: map_at_1000
      value: 45.341
    - type: map_at_3
      value: 39.956
    - type: map_at_5
      value: 42.031
    - type: mrr_at_1
      value: 39.485
    - type: mrr_at_10
      value: 49.537
    - type: mrr_at_100
      value: 50.249
    - type: mrr_at_1000
      value: 50.294000000000004
    - type: mrr_at_3
      value: 46.757
    - type: mrr_at_5
      value: 48.481
    - type: ndcg_at_1
      value: 39.485
    - type: ndcg_at_10
      value: 50.058
    - type: ndcg_at_100
      value: 55.586
    - type: ndcg_at_1000
      value: 57.511
    - type: ndcg_at_3
      value: 44.786
    - type: ndcg_at_5
      value: 47.339999999999996
    - type: precision_at_1
      value: 39.485
    - type: precision_at_10
      value: 9.557
    - type: precision_at_100
      value: 1.552
    - type: precision_at_1000
      value: 0.202
    - type: precision_at_3
      value: 21.412
    - type: precision_at_5
      value: 15.479000000000001
    - type: recall_at_1
      value: 32.745999999999995
    - type: recall_at_10
      value: 62.056
    - type: recall_at_100
      value: 85.088
    - type: recall_at_1000
      value: 96.952
    - type: recall_at_3
      value: 46.959
    - type: recall_at_5
      value: 54.06999999999999
    - type: map_at_1
      value: 31.898
    - type: map_at_10
      value: 42.142
    - type: map_at_100
      value: 43.349
    - type: map_at_1000
      value: 43.483
    - type: map_at_3
      value: 39.18
    - type: map_at_5
      value: 40.733000000000004
    - type: mrr_at_1
      value: 39.617999999999995
    - type: mrr_at_10
      value: 47.922
    - type: mrr_at_100
      value: 48.547000000000004
    - type: mrr_at_1000
      value: 48.597
    - type: mrr_at_3
      value: 45.86
    - type: mrr_at_5
      value: 46.949000000000005
    - type: ndcg_at_1
      value: 39.617999999999995
    - type: ndcg_at_10
      value: 47.739
    - type: ndcg_at_100
      value: 51.934999999999995
    - type: ndcg_at_1000
      value: 54.007000000000005
    - type: ndcg_at_3
      value: 43.748
    - type: ndcg_at_5
      value: 45.345
    - type: precision_at_1
      value: 39.617999999999995
    - type: precision_at_10
      value: 8.962
    - type: precision_at_100
      value: 1.436
    - type: precision_at_1000
      value: 0.192
    - type: precision_at_3
      value: 21.083
    - type: precision_at_5
      value: 14.752
    - type: recall_at_1
      value: 31.898
    - type: recall_at_10
      value: 57.587999999999994
    - type: recall_at_100
      value: 75.323
    - type: recall_at_1000
      value: 88.304
    - type: recall_at_3
      value: 45.275
    - type: recall_at_5
      value: 49.99
    - type: map_at_1
      value: 40.458
    - type: map_at_10
      value: 52.942
    - type: map_at_100
      value: 53.974
    - type: map_at_1000
      value: 54.031
    - type: map_at_3
      value: 49.559999999999995
    - type: map_at_5
      value: 51.408
    - type: mrr_at_1
      value: 46.27
    - type: mrr_at_10
      value: 56.31699999999999
    - type: mrr_at_100
      value: 56.95099999999999
    - type: mrr_at_1000
      value: 56.98
    - type: mrr_at_3
      value: 53.835
    - type: mrr_at_5
      value: 55.252
    - type: ndcg_at_1
      value: 46.27
    - type: ndcg_at_10
      value: 58.964000000000006
    - type: ndcg_at_100
      value: 62.875
    - type: ndcg_at_1000
      value: 63.969
    - type: ndcg_at_3
      value: 53.297000000000004
    - type: ndcg_at_5
      value: 55.938
    - type: precision_at_1
      value: 46.27
    - type: precision_at_10
      value: 9.549000000000001
    - type: precision_at_100
      value: 1.2409999999999999
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 23.762
    - type: precision_at_5
      value: 16.262999999999998
    - type: recall_at_1
      value: 40.458
    - type: recall_at_10
      value: 73.446
    - type: recall_at_100
      value: 90.12400000000001
    - type: recall_at_1000
      value: 97.795
    - type: recall_at_3
      value: 58.123000000000005
    - type: recall_at_5
      value: 64.68
    - type: map_at_1
      value: 27.443
    - type: map_at_10
      value: 36.081
    - type: map_at_100
      value: 37.163000000000004
    - type: map_at_1000
      value: 37.232
    - type: map_at_3
      value: 33.308
    - type: map_at_5
      value: 34.724
    - type: mrr_at_1
      value: 29.492
    - type: mrr_at_10
      value: 38.138
    - type: mrr_at_100
      value: 39.065
    - type: mrr_at_1000
      value: 39.119
    - type: mrr_at_3
      value: 35.593
    - type: mrr_at_5
      value: 36.785000000000004
    - type: ndcg_at_1
      value: 29.492
    - type: ndcg_at_10
      value: 41.134
    - type: ndcg_at_100
      value: 46.300999999999995
    - type: ndcg_at_1000
      value: 48.106
    - type: ndcg_at_3
      value: 35.77
    - type: ndcg_at_5
      value: 38.032
    - type: precision_at_1
      value: 29.492
    - type: precision_at_10
      value: 6.249
    - type: precision_at_100
      value: 0.9299999999999999
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 15.065999999999999
    - type: precision_at_5
      value: 10.373000000000001
    - type: recall_at_1
      value: 27.443
    - type: recall_at_10
      value: 54.80199999999999
    - type: recall_at_100
      value: 78.21900000000001
    - type: recall_at_1000
      value: 91.751
    - type: recall_at_3
      value: 40.211000000000006
    - type: recall_at_5
      value: 45.599000000000004
    - type: map_at_1
      value: 18.731
    - type: map_at_10
      value: 26.717999999999996
    - type: map_at_100
      value: 27.897
    - type: map_at_1000
      value: 28.029
    - type: map_at_3
      value: 23.91
    - type: map_at_5
      value: 25.455
    - type: mrr_at_1
      value: 23.134
    - type: mrr_at_10
      value: 31.769
    - type: mrr_at_100
      value: 32.634
    - type: mrr_at_1000
      value: 32.707
    - type: mrr_at_3
      value: 28.938999999999997
    - type: mrr_at_5
      value: 30.531000000000002
    - type: ndcg_at_1
      value: 23.134
    - type: ndcg_at_10
      value: 32.249
    - type: ndcg_at_100
      value: 37.678
    - type: ndcg_at_1000
      value: 40.589999999999996
    - type: ndcg_at_3
      value: 26.985999999999997
    - type: ndcg_at_5
      value: 29.457
    - type: precision_at_1
      value: 23.134
    - type: precision_at_10
      value: 5.8709999999999996
    - type: precision_at_100
      value: 0.988
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 12.852
    - type: precision_at_5
      value: 9.428
    - type: recall_at_1
      value: 18.731
    - type: recall_at_10
      value: 44.419
    - type: recall_at_100
      value: 67.851
    - type: recall_at_1000
      value: 88.103
    - type: recall_at_3
      value: 29.919
    - type: recall_at_5
      value: 36.230000000000004
    - type: map_at_1
      value: 30.324
    - type: map_at_10
      value: 41.265
    - type: map_at_100
      value: 42.559000000000005
    - type: map_at_1000
      value: 42.669000000000004
    - type: map_at_3
      value: 38.138
    - type: map_at_5
      value: 39.881
    - type: mrr_at_1
      value: 36.67
    - type: mrr_at_10
      value: 46.774
    - type: mrr_at_100
      value: 47.554
    - type: mrr_at_1000
      value: 47.593
    - type: mrr_at_3
      value: 44.338
    - type: mrr_at_5
      value: 45.723
    - type: ndcg_at_1
      value: 36.67
    - type: ndcg_at_10
      value: 47.367
    - type: ndcg_at_100
      value: 52.623
    - type: ndcg_at_1000
      value: 54.59
    - type: ndcg_at_3
      value: 42.323
    - type: ndcg_at_5
      value: 44.727
    - type: precision_at_1
      value: 36.67
    - type: precision_at_10
      value: 8.518
    - type: precision_at_100
      value: 1.2890000000000001
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 19.955000000000002
    - type: precision_at_5
      value: 14.11
    - type: recall_at_1
      value: 30.324
    - type: recall_at_10
      value: 59.845000000000006
    - type: recall_at_100
      value: 81.77499999999999
    - type: recall_at_1000
      value: 94.463
    - type: recall_at_3
      value: 46.019
    - type: recall_at_5
      value: 52.163000000000004
    - type: map_at_1
      value: 24.229
    - type: map_at_10
      value: 35.004000000000005
    - type: map_at_100
      value: 36.409000000000006
    - type: map_at_1000
      value: 36.521
    - type: map_at_3
      value: 31.793
    - type: map_at_5
      value: 33.432
    - type: mrr_at_1
      value: 30.365
    - type: mrr_at_10
      value: 40.502
    - type: mrr_at_100
      value: 41.372
    - type: mrr_at_1000
      value: 41.435
    - type: mrr_at_3
      value: 37.804
    - type: mrr_at_5
      value: 39.226
    - type: ndcg_at_1
      value: 30.365
    - type: ndcg_at_10
      value: 41.305
    - type: ndcg_at_100
      value: 47.028999999999996
    - type: ndcg_at_1000
      value: 49.375
    - type: ndcg_at_3
      value: 35.85
    - type: ndcg_at_5
      value: 38.12
    - type: precision_at_1
      value: 30.365
    - type: precision_at_10
      value: 7.808
    - type: precision_at_100
      value: 1.228
    - type: precision_at_1000
      value: 0.161
    - type: precision_at_3
      value: 17.352
    - type: precision_at_5
      value: 12.42
    - type: recall_at_1
      value: 24.229
    - type: recall_at_10
      value: 54.673
    - type: recall_at_100
      value: 78.766
    - type: recall_at_1000
      value: 94.625
    - type: recall_at_3
      value: 39.602
    - type: recall_at_5
      value: 45.558
    - type: map_at_1
      value: 26.695
    - type: map_at_10
      value: 36.0895
    - type: map_at_100
      value: 37.309416666666664
    - type: map_at_1000
      value: 37.42558333333334
    - type: map_at_3
      value: 33.19616666666666
    - type: map_at_5
      value: 34.78641666666667
    - type: mrr_at_1
      value: 31.486083333333337
    - type: mrr_at_10
      value: 40.34774999999999
    - type: mrr_at_100
      value: 41.17533333333333
    - type: mrr_at_1000
      value: 41.231583333333326
    - type: mrr_at_3
      value: 37.90075
    - type: mrr_at_5
      value: 39.266999999999996
    - type: ndcg_at_1
      value: 31.486083333333337
    - type: ndcg_at_10
      value: 41.60433333333334
    - type: ndcg_at_100
      value: 46.74525
    - type: ndcg_at_1000
      value: 48.96166666666667
    - type: ndcg_at_3
      value: 36.68825
    - type: ndcg_at_5
      value: 38.966499999999996
    - type: precision_at_1
      value: 31.486083333333337
    - type: precision_at_10
      value: 7.29675
    - type: precision_at_100
      value: 1.1621666666666666
    - type: precision_at_1000
      value: 0.1545
    - type: precision_at_3
      value: 16.8815
    - type: precision_at_5
      value: 11.974583333333333
    - type: recall_at_1
      value: 26.695
    - type: recall_at_10
      value: 53.651916666666665
    - type: recall_at_100
      value: 76.12083333333332
    - type: recall_at_1000
      value: 91.31191666666668
    - type: recall_at_3
      value: 40.03575
    - type: recall_at_5
      value: 45.876666666666665
    - type: map_at_1
      value: 25.668000000000003
    - type: map_at_10
      value: 32.486
    - type: map_at_100
      value: 33.371
    - type: map_at_1000
      value: 33.458
    - type: map_at_3
      value: 30.261
    - type: map_at_5
      value: 31.418000000000003
    - type: mrr_at_1
      value: 28.988000000000003
    - type: mrr_at_10
      value: 35.414
    - type: mrr_at_100
      value: 36.149
    - type: mrr_at_1000
      value: 36.215
    - type: mrr_at_3
      value: 33.333
    - type: mrr_at_5
      value: 34.43
    - type: ndcg_at_1
      value: 28.988000000000003
    - type: ndcg_at_10
      value: 36.732
    - type: ndcg_at_100
      value: 41.331
    - type: ndcg_at_1000
      value: 43.575
    - type: ndcg_at_3
      value: 32.413
    - type: ndcg_at_5
      value: 34.316
    - type: precision_at_1
      value: 28.988000000000003
    - type: precision_at_10
      value: 5.7059999999999995
    - type: precision_at_100
      value: 0.882
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 13.65
    - type: precision_at_5
      value: 9.417
    - type: recall_at_1
      value: 25.668000000000003
    - type: recall_at_10
      value: 47.147
    - type: recall_at_100
      value: 68.504
    - type: recall_at_1000
      value: 85.272
    - type: recall_at_3
      value: 35.19
    - type: recall_at_5
      value: 39.925
    - type: map_at_1
      value: 17.256
    - type: map_at_10
      value: 24.58
    - type: map_at_100
      value: 25.773000000000003
    - type: map_at_1000
      value: 25.899
    - type: map_at_3
      value: 22.236
    - type: map_at_5
      value: 23.507
    - type: mrr_at_1
      value: 20.957
    - type: mrr_at_10
      value: 28.416000000000004
    - type: mrr_at_100
      value: 29.447000000000003
    - type: mrr_at_1000
      value: 29.524
    - type: mrr_at_3
      value: 26.245
    - type: mrr_at_5
      value: 27.451999999999998
    - type: ndcg_at_1
      value: 20.957
    - type: ndcg_at_10
      value: 29.285
    - type: ndcg_at_100
      value: 35.003
    - type: ndcg_at_1000
      value: 37.881
    - type: ndcg_at_3
      value: 25.063000000000002
    - type: ndcg_at_5
      value: 26.983
    - type: precision_at_1
      value: 20.957
    - type: precision_at_10
      value: 5.344
    - type: precision_at_100
      value: 0.958
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 11.918
    - type: precision_at_5
      value: 8.596
    - type: recall_at_1
      value: 17.256
    - type: recall_at_10
      value: 39.644
    - type: recall_at_100
      value: 65.279
    - type: recall_at_1000
      value: 85.693
    - type: recall_at_3
      value: 27.825
    - type: recall_at_5
      value: 32.792
    - type: map_at_1
      value: 26.700000000000003
    - type: map_at_10
      value: 36.205999999999996
    - type: map_at_100
      value: 37.316
    - type: map_at_1000
      value: 37.425000000000004
    - type: map_at_3
      value: 33.166000000000004
    - type: map_at_5
      value: 35.032999999999994
    - type: mrr_at_1
      value: 31.436999999999998
    - type: mrr_at_10
      value: 40.61
    - type: mrr_at_100
      value: 41.415
    - type: mrr_at_1000
      value: 41.48
    - type: mrr_at_3
      value: 37.966
    - type: mrr_at_5
      value: 39.599000000000004
    - type: ndcg_at_1
      value: 31.436999999999998
    - type: ndcg_at_10
      value: 41.771
    - type: ndcg_at_100
      value: 46.784
    - type: ndcg_at_1000
      value: 49.183
    - type: ndcg_at_3
      value: 36.437000000000005
    - type: ndcg_at_5
      value: 39.291
    - type: precision_at_1
      value: 31.436999999999998
    - type: precision_at_10
      value: 6.987
    - type: precision_at_100
      value: 1.072
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 16.448999999999998
    - type: precision_at_5
      value: 11.866
    - type: recall_at_1
      value: 26.700000000000003
    - type: recall_at_10
      value: 54.301
    - type: recall_at_100
      value: 75.871
    - type: recall_at_1000
      value: 92.529
    - type: recall_at_3
      value: 40.201
    - type: recall_at_5
      value: 47.208
    - type: map_at_1
      value: 24.296
    - type: map_at_10
      value: 33.116
    - type: map_at_100
      value: 34.81
    - type: map_at_1000
      value: 35.032000000000004
    - type: map_at_3
      value: 30.105999999999998
    - type: map_at_5
      value: 31.839000000000002
    - type: mrr_at_1
      value: 29.051
    - type: mrr_at_10
      value: 37.803
    - type: mrr_at_100
      value: 38.856
    - type: mrr_at_1000
      value: 38.903999999999996
    - type: mrr_at_3
      value: 35.211
    - type: mrr_at_5
      value: 36.545
    - type: ndcg_at_1
      value: 29.051
    - type: ndcg_at_10
      value: 39.007
    - type: ndcg_at_100
      value: 45.321
    - type: ndcg_at_1000
      value: 47.665
    - type: ndcg_at_3
      value: 34.1
    - type: ndcg_at_5
      value: 36.437000000000005
    - type: precision_at_1
      value: 29.051
    - type: precision_at_10
      value: 7.668
    - type: precision_at_100
      value: 1.542
    - type: precision_at_1000
      value: 0.24
    - type: precision_at_3
      value: 16.14
    - type: precision_at_5
      value: 11.897
    - type: recall_at_1
      value: 24.296
    - type: recall_at_10
      value: 49.85
    - type: recall_at_100
      value: 78.457
    - type: recall_at_1000
      value: 92.618
    - type: recall_at_3
      value: 36.138999999999996
    - type: recall_at_5
      value: 42.223
    - type: map_at_1
      value: 20.591
    - type: map_at_10
      value: 28.902
    - type: map_at_100
      value: 29.886000000000003
    - type: map_at_1000
      value: 29.987000000000002
    - type: map_at_3
      value: 26.740000000000002
    - type: map_at_5
      value: 27.976
    - type: mrr_at_1
      value: 22.366
    - type: mrr_at_10
      value: 30.971
    - type: mrr_at_100
      value: 31.865
    - type: mrr_at_1000
      value: 31.930999999999997
    - type: mrr_at_3
      value: 28.927999999999997
    - type: mrr_at_5
      value: 30.231
    - type: ndcg_at_1
      value: 22.366
    - type: ndcg_at_10
      value: 33.641
    - type: ndcg_at_100
      value: 38.477
    - type: ndcg_at_1000
      value: 41.088
    - type: ndcg_at_3
      value: 29.486
    - type: ndcg_at_5
      value: 31.612000000000002
    - type: precision_at_1
      value: 22.366
    - type: precision_at_10
      value: 5.3420000000000005
    - type: precision_at_100
      value: 0.828
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 12.939
    - type: precision_at_5
      value: 9.094
    - type: recall_at_1
      value: 20.591
    - type: recall_at_10
      value: 46.052
    - type: recall_at_100
      value: 68.193
    - type: recall_at_1000
      value: 87.638
    - type: recall_at_3
      value: 34.966
    - type: recall_at_5
      value: 40.082
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.091
    - type: map_at_10
      value: 26.38
    - type: map_at_100
      value: 28.421999999999997
    - type: map_at_1000
      value: 28.621999999999996
    - type: map_at_3
      value: 21.597
    - type: map_at_5
      value: 24.12
    - type: mrr_at_1
      value: 34.266999999999996
    - type: mrr_at_10
      value: 46.864
    - type: mrr_at_100
      value: 47.617
    - type: mrr_at_1000
      value: 47.644
    - type: mrr_at_3
      value: 43.312
    - type: mrr_at_5
      value: 45.501000000000005
    - type: ndcg_at_1
      value: 34.266999999999996
    - type: ndcg_at_10
      value: 36.095
    - type: ndcg_at_100
      value: 43.447
    - type: ndcg_at_1000
      value: 46.661
    - type: ndcg_at_3
      value: 29.337999999999997
    - type: ndcg_at_5
      value: 31.824
    - type: precision_at_1
      value: 34.266999999999996
    - type: precision_at_10
      value: 11.472
    - type: precision_at_100
      value: 1.944
    - type: precision_at_1000
      value: 0.255
    - type: precision_at_3
      value: 21.933
    - type: precision_at_5
      value: 17.224999999999998
    - type: recall_at_1
      value: 15.091
    - type: recall_at_10
      value: 43.022
    - type: recall_at_100
      value: 68.075
    - type: recall_at_1000
      value: 85.76
    - type: recall_at_3
      value: 26.564
    - type: recall_at_5
      value: 33.594
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.252
    - type: map_at_10
      value: 20.923
    - type: map_at_100
      value: 30.741000000000003
    - type: map_at_1000
      value: 32.542
    - type: map_at_3
      value: 14.442
    - type: map_at_5
      value: 17.399
    - type: mrr_at_1
      value: 70.25
    - type: mrr_at_10
      value: 78.17
    - type: mrr_at_100
      value: 78.444
    - type: mrr_at_1000
      value: 78.45100000000001
    - type: mrr_at_3
      value: 76.958
    - type: mrr_at_5
      value: 77.571
    - type: ndcg_at_1
      value: 58.375
    - type: ndcg_at_10
      value: 44.509
    - type: ndcg_at_100
      value: 49.897999999999996
    - type: ndcg_at_1000
      value: 57.269999999999996
    - type: ndcg_at_3
      value: 48.64
    - type: ndcg_at_5
      value: 46.697
    - type: precision_at_1
      value: 70.25
    - type: precision_at_10
      value: 36.05
    - type: precision_at_100
      value: 11.848
    - type: precision_at_1000
      value: 2.213
    - type: precision_at_3
      value: 52.917
    - type: precision_at_5
      value: 45.7
    - type: recall_at_1
      value: 9.252
    - type: recall_at_10
      value: 27.006999999999998
    - type: recall_at_100
      value: 57.008
    - type: recall_at_1000
      value: 80.697
    - type: recall_at_3
      value: 15.798000000000002
    - type: recall_at_5
      value: 20.4
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 50.88
    - type: f1
      value: 45.545495028653384
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 75.424
    - type: map_at_10
      value: 83.435
    - type: map_at_100
      value: 83.66900000000001
    - type: map_at_1000
      value: 83.685
    - type: map_at_3
      value: 82.39800000000001
    - type: map_at_5
      value: 83.07
    - type: mrr_at_1
      value: 81.113
    - type: mrr_at_10
      value: 87.77199999999999
    - type: mrr_at_100
      value: 87.862
    - type: mrr_at_1000
      value: 87.86500000000001
    - type: mrr_at_3
      value: 87.17099999999999
    - type: mrr_at_5
      value: 87.616
    - type: ndcg_at_1
      value: 81.113
    - type: ndcg_at_10
      value: 86.909
    - type: ndcg_at_100
      value: 87.746
    - type: ndcg_at_1000
      value: 88.017
    - type: ndcg_at_3
      value: 85.368
    - type: ndcg_at_5
      value: 86.28099999999999
    - type: precision_at_1
      value: 81.113
    - type: precision_at_10
      value: 10.363
    - type: precision_at_100
      value: 1.102
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 32.507999999999996
    - type: precision_at_5
      value: 20.138
    - type: recall_at_1
      value: 75.424
    - type: recall_at_10
      value: 93.258
    - type: recall_at_100
      value: 96.545
    - type: recall_at_1000
      value: 98.284
    - type: recall_at_3
      value: 89.083
    - type: recall_at_5
      value: 91.445
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.532
    - type: map_at_10
      value: 37.141999999999996
    - type: map_at_100
      value: 39.162
    - type: map_at_1000
      value: 39.322
    - type: map_at_3
      value: 32.885
    - type: map_at_5
      value: 35.093999999999994
    - type: mrr_at_1
      value: 44.29
    - type: mrr_at_10
      value: 53.516
    - type: mrr_at_100
      value: 54.24
    - type: mrr_at_1000
      value: 54.273
    - type: mrr_at_3
      value: 51.286
    - type: mrr_at_5
      value: 52.413
    - type: ndcg_at_1
      value: 44.29
    - type: ndcg_at_10
      value: 45.268
    - type: ndcg_at_100
      value: 52.125
    - type: ndcg_at_1000
      value: 54.778000000000006
    - type: ndcg_at_3
      value: 41.829
    - type: ndcg_at_5
      value: 42.525
    - type: precision_at_1
      value: 44.29
    - type: precision_at_10
      value: 12.5
    - type: precision_at_100
      value: 1.9720000000000002
    - type: precision_at_1000
      value: 0.245
    - type: precision_at_3
      value: 28.035
    - type: precision_at_5
      value: 20.093
    - type: recall_at_1
      value: 22.532
    - type: recall_at_10
      value: 52.419000000000004
    - type: recall_at_100
      value: 77.43299999999999
    - type: recall_at_1000
      value: 93.379
    - type: recall_at_3
      value: 38.629000000000005
    - type: recall_at_5
      value: 43.858000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 39.359
    - type: map_at_10
      value: 63.966
    - type: map_at_100
      value: 64.87
    - type: map_at_1000
      value: 64.92599999999999
    - type: map_at_3
      value: 60.409
    - type: map_at_5
      value: 62.627
    - type: mrr_at_1
      value: 78.717
    - type: mrr_at_10
      value: 84.468
    - type: mrr_at_100
      value: 84.655
    - type: mrr_at_1000
      value: 84.661
    - type: mrr_at_3
      value: 83.554
    - type: mrr_at_5
      value: 84.133
    - type: ndcg_at_1
      value: 78.717
    - type: ndcg_at_10
      value: 72.03399999999999
    - type: ndcg_at_100
      value: 75.158
    - type: ndcg_at_1000
      value: 76.197
    - type: ndcg_at_3
      value: 67.049
    - type: ndcg_at_5
      value: 69.808
    - type: precision_at_1
      value: 78.717
    - type: precision_at_10
      value: 15.201
    - type: precision_at_100
      value: 1.764
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 43.313
    - type: precision_at_5
      value: 28.165000000000003
    - type: recall_at_1
      value: 39.359
    - type: recall_at_10
      value: 76.003
    - type: recall_at_100
      value: 88.197
    - type: recall_at_1000
      value: 95.003
    - type: recall_at_3
      value: 64.97
    - type: recall_at_5
      value: 70.41199999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 92.83200000000001
    - type: ap
      value: 89.33560571859861
    - type: f1
      value: 92.82322915005167
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 21.983
    - type: map_at_10
      value: 34.259
    - type: map_at_100
      value: 35.432
    - type: map_at_1000
      value: 35.482
    - type: map_at_3
      value: 30.275999999999996
    - type: map_at_5
      value: 32.566
    - type: mrr_at_1
      value: 22.579
    - type: mrr_at_10
      value: 34.882999999999996
    - type: mrr_at_100
      value: 35.984
    - type: mrr_at_1000
      value: 36.028
    - type: mrr_at_3
      value: 30.964999999999996
    - type: mrr_at_5
      value: 33.245000000000005
    - type: ndcg_at_1
      value: 22.564
    - type: ndcg_at_10
      value: 41.258
    - type: ndcg_at_100
      value: 46.824
    - type: ndcg_at_1000
      value: 48.037
    - type: ndcg_at_3
      value: 33.17
    - type: ndcg_at_5
      value: 37.263000000000005
    - type: precision_at_1
      value: 22.564
    - type: precision_at_10
      value: 6.572
    - type: precision_at_100
      value: 0.935
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.130999999999998
    - type: precision_at_5
      value: 10.544
    - type: recall_at_1
      value: 21.983
    - type: recall_at_10
      value: 62.775000000000006
    - type: recall_at_100
      value: 88.389
    - type: recall_at_1000
      value: 97.603
    - type: recall_at_3
      value: 40.878
    - type: recall_at_5
      value: 50.690000000000005
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 93.95120839033288
    - type: f1
      value: 93.73824125055208
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 76.78978568171455
    - type: f1
      value: 57.50180552858304
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 76.24411566913248
    - type: f1
      value: 74.37851403532832
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 79.94620040349699
    - type: f1
      value: 80.21293397970435
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 33.44403096245675
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 31.659594631336812
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.53833075108798
    - type: mrr
      value: 33.78840823218308
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.185999999999999
    - type: map_at_10
      value: 15.193999999999999
    - type: map_at_100
      value: 19.538
    - type: map_at_1000
      value: 21.178
    - type: map_at_3
      value: 11.208
    - type: map_at_5
      value: 12.745999999999999
    - type: mrr_at_1
      value: 48.916
    - type: mrr_at_10
      value: 58.141
    - type: mrr_at_100
      value: 58.656
    - type: mrr_at_1000
      value: 58.684999999999995
    - type: mrr_at_3
      value: 55.521
    - type: mrr_at_5
      value: 57.239
    - type: ndcg_at_1
      value: 47.059
    - type: ndcg_at_10
      value: 38.644
    - type: ndcg_at_100
      value: 36.272999999999996
    - type: ndcg_at_1000
      value: 44.996
    - type: ndcg_at_3
      value: 43.293
    - type: ndcg_at_5
      value: 40.819
    - type: precision_at_1
      value: 48.916
    - type: precision_at_10
      value: 28.607
    - type: precision_at_100
      value: 9.195
    - type: precision_at_1000
      value: 2.225
    - type: precision_at_3
      value: 40.454
    - type: precision_at_5
      value: 34.985
    - type: recall_at_1
      value: 7.185999999999999
    - type: recall_at_10
      value: 19.654
    - type: recall_at_100
      value: 37.224000000000004
    - type: recall_at_1000
      value: 68.663
    - type: recall_at_3
      value: 12.158
    - type: recall_at_5
      value: 14.674999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.552000000000003
    - type: map_at_10
      value: 47.75
    - type: map_at_100
      value: 48.728
    - type: map_at_1000
      value: 48.754
    - type: map_at_3
      value: 43.156
    - type: map_at_5
      value: 45.883
    - type: mrr_at_1
      value: 35.66
    - type: mrr_at_10
      value: 50.269
    - type: mrr_at_100
      value: 50.974
    - type: mrr_at_1000
      value: 50.991
    - type: mrr_at_3
      value: 46.519
    - type: mrr_at_5
      value: 48.764
    - type: ndcg_at_1
      value: 35.632000000000005
    - type: ndcg_at_10
      value: 55.786
    - type: ndcg_at_100
      value: 59.748999999999995
    - type: ndcg_at_1000
      value: 60.339
    - type: ndcg_at_3
      value: 47.292
    - type: ndcg_at_5
      value: 51.766999999999996
    - type: precision_at_1
      value: 35.632000000000005
    - type: precision_at_10
      value: 9.267
    - type: precision_at_100
      value: 1.149
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 21.601
    - type: precision_at_5
      value: 15.539
    - type: recall_at_1
      value: 31.552000000000003
    - type: recall_at_10
      value: 77.62400000000001
    - type: recall_at_100
      value: 94.527
    - type: recall_at_1000
      value: 98.919
    - type: recall_at_3
      value: 55.898
    - type: recall_at_5
      value: 66.121
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 71.414
    - type: map_at_10
      value: 85.37400000000001
    - type: map_at_100
      value: 86.01100000000001
    - type: map_at_1000
      value: 86.027
    - type: map_at_3
      value: 82.562
    - type: map_at_5
      value: 84.284
    - type: mrr_at_1
      value: 82.24000000000001
    - type: mrr_at_10
      value: 88.225
    - type: mrr_at_100
      value: 88.324
    - type: mrr_at_1000
      value: 88.325
    - type: mrr_at_3
      value: 87.348
    - type: mrr_at_5
      value: 87.938
    - type: ndcg_at_1
      value: 82.24000000000001
    - type: ndcg_at_10
      value: 88.97699999999999
    - type: ndcg_at_100
      value: 90.16
    - type: ndcg_at_1000
      value: 90.236
    - type: ndcg_at_3
      value: 86.371
    - type: ndcg_at_5
      value: 87.746
    - type: precision_at_1
      value: 82.24000000000001
    - type: precision_at_10
      value: 13.481000000000002
    - type: precision_at_100
      value: 1.534
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.86
    - type: precision_at_5
      value: 24.738
    - type: recall_at_1
      value: 71.414
    - type: recall_at_10
      value: 95.735
    - type: recall_at_100
      value: 99.696
    - type: recall_at_1000
      value: 99.979
    - type: recall_at_3
      value: 88.105
    - type: recall_at_5
      value: 92.17999999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 60.22146692057259
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 65.29273320614578
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.023
    - type: map_at_10
      value: 14.161000000000001
    - type: map_at_100
      value: 16.68
    - type: map_at_1000
      value: 17.072000000000003
    - type: map_at_3
      value: 9.763
    - type: map_at_5
      value: 11.977
    - type: mrr_at_1
      value: 24.8
    - type: mrr_at_10
      value: 37.602999999999994
    - type: mrr_at_100
      value: 38.618
    - type: mrr_at_1000
      value: 38.659
    - type: mrr_at_3
      value: 34.117
    - type: mrr_at_5
      value: 36.082
    - type: ndcg_at_1
      value: 24.8
    - type: ndcg_at_10
      value: 23.316
    - type: ndcg_at_100
      value: 32.613
    - type: ndcg_at_1000
      value: 38.609
    - type: ndcg_at_3
      value: 21.697
    - type: ndcg_at_5
      value: 19.241
    - type: precision_at_1
      value: 24.8
    - type: precision_at_10
      value: 12.36
    - type: precision_at_100
      value: 2.593
    - type: precision_at_1000
      value: 0.402
    - type: precision_at_3
      value: 20.767
    - type: precision_at_5
      value: 17.34
    - type: recall_at_1
      value: 5.023
    - type: recall_at_10
      value: 25.069999999999997
    - type: recall_at_100
      value: 52.563
    - type: recall_at_1000
      value: 81.525
    - type: recall_at_3
      value: 12.613
    - type: recall_at_5
      value: 17.583
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 87.71506247604255
    - type: cos_sim_spearman
      value: 82.91813463738802
    - type: euclidean_pearson
      value: 85.5154616194479
    - type: euclidean_spearman
      value: 82.91815254466314
    - type: manhattan_pearson
      value: 85.5280917850374
    - type: manhattan_spearman
      value: 82.92276537286398
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 87.43772054228462
    - type: cos_sim_spearman
      value: 78.75750601716682
    - type: euclidean_pearson
      value: 85.76074482955764
    - type: euclidean_spearman
      value: 78.75651057223058
    - type: manhattan_pearson
      value: 85.73390291701668
    - type: manhattan_spearman
      value: 78.72699385957797
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 89.58144067172472
    - type: cos_sim_spearman
      value: 90.3524512966946
    - type: euclidean_pearson
      value: 89.71365391594237
    - type: euclidean_spearman
      value: 90.35239632843408
    - type: manhattan_pearson
      value: 89.66905421746478
    - type: manhattan_spearman
      value: 90.31508211683513
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 87.77692637102102
    - type: cos_sim_spearman
      value: 85.45710562643485
    - type: euclidean_pearson
      value: 87.42456979928723
    - type: euclidean_spearman
      value: 85.45709386240908
    - type: manhattan_pearson
      value: 87.40754529526272
    - type: manhattan_spearman
      value: 85.44834854173303
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 88.28491331695997
    - type: cos_sim_spearman
      value: 89.62037029566964
    - type: euclidean_pearson
      value: 89.02479391362826
    - type: euclidean_spearman
      value: 89.62036733618466
    - type: manhattan_pearson
      value: 89.00394756040342
    - type: manhattan_spearman
      value: 89.60867744215236
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 85.08911381280191
    - type: cos_sim_spearman
      value: 86.5791780765767
    - type: euclidean_pearson
      value: 86.16063473577861
    - type: euclidean_spearman
      value: 86.57917745378766
    - type: manhattan_pearson
      value: 86.13677924604175
    - type: manhattan_spearman
      value: 86.56115615768685
  - 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: 89.58029496205235
    - type: cos_sim_spearman
      value: 89.49551253826998
    - type: euclidean_pearson
      value: 90.13714840963748
    - type: euclidean_spearman
      value: 89.49551253826998
    - type: manhattan_pearson
      value: 90.13039633601363
    - type: manhattan_spearman
      value: 89.4513453745516
  - 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: 69.01546399666435
    - type: cos_sim_spearman
      value: 69.33824484595624
    - type: euclidean_pearson
      value: 70.76511642998874
    - type: euclidean_spearman
      value: 69.33824484595624
    - type: manhattan_pearson
      value: 70.84320785047453
    - type: manhattan_spearman
      value: 69.54233632223537
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 87.26389196390119
    - type: cos_sim_spearman
      value: 89.09721478341385
    - type: euclidean_pearson
      value: 88.97208685922517
    - type: euclidean_spearman
      value: 89.09720927308881
    - type: manhattan_pearson
      value: 88.97513670502573
    - type: manhattan_spearman
      value: 89.07647853984004
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 87.53075025771936
    - type: mrr
      value: 96.24327651288436
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.428000000000004
    - type: map_at_10
      value: 70.088
    - type: map_at_100
      value: 70.589
    - type: map_at_1000
      value: 70.614
    - type: map_at_3
      value: 67.191
    - type: map_at_5
      value: 68.515
    - type: mrr_at_1
      value: 63.333
    - type: mrr_at_10
      value: 71.13000000000001
    - type: mrr_at_100
      value: 71.545
    - type: mrr_at_1000
      value: 71.569
    - type: mrr_at_3
      value: 68.944
    - type: mrr_at_5
      value: 70.078
    - type: ndcg_at_1
      value: 63.333
    - type: ndcg_at_10
      value: 74.72800000000001
    - type: ndcg_at_100
      value: 76.64999999999999
    - type: ndcg_at_1000
      value: 77.176
    - type: ndcg_at_3
      value: 69.659
    - type: ndcg_at_5
      value: 71.626
    - type: precision_at_1
      value: 63.333
    - type: precision_at_10
      value: 10
    - type: precision_at_100
      value: 1.09
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 27.111
    - type: precision_at_5
      value: 17.666999999999998
    - type: recall_at_1
      value: 60.428000000000004
    - type: recall_at_10
      value: 87.98899999999999
    - type: recall_at_100
      value: 96.167
    - type: recall_at_1000
      value: 100
    - type: recall_at_3
      value: 74.006
    - type: recall_at_5
      value: 79.05
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.87326732673267
    - type: cos_sim_ap
      value: 96.81770773701805
    - type: cos_sim_f1
      value: 93.6318407960199
    - type: cos_sim_precision
      value: 93.16831683168317
    - type: cos_sim_recall
      value: 94.1
    - type: dot_accuracy
      value: 99.87326732673267
    - type: dot_ap
      value: 96.8174218946665
    - type: dot_f1
      value: 93.6318407960199
    - type: dot_precision
      value: 93.16831683168317
    - type: dot_recall
      value: 94.1
    - type: euclidean_accuracy
      value: 99.87326732673267
    - type: euclidean_ap
      value: 96.81770773701807
    - type: euclidean_f1
      value: 93.6318407960199
    - type: euclidean_precision
      value: 93.16831683168317
    - type: euclidean_recall
      value: 94.1
    - type: manhattan_accuracy
      value: 99.87227722772278
    - type: manhattan_ap
      value: 96.83164126821747
    - type: manhattan_f1
      value: 93.54677338669335
    - type: manhattan_precision
      value: 93.5935935935936
    - type: manhattan_recall
      value: 93.5
    - type: max_accuracy
      value: 99.87326732673267
    - type: max_ap
      value: 96.83164126821747
    - type: max_f1
      value: 93.6318407960199
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 65.6212042420246
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 35.779230635982564
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 55.217701909036286
    - type: mrr
      value: 56.17658995416349
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.954206018888453
    - type: cos_sim_spearman
      value: 32.71062599450096
    - type: dot_pearson
      value: 30.95420929056943
    - type: dot_spearman
      value: 32.71062599450096
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.22699999999999998
    - type: map_at_10
      value: 1.924
    - type: map_at_100
      value: 10.525
    - type: map_at_1000
      value: 24.973
    - type: map_at_3
      value: 0.638
    - type: map_at_5
      value: 1.0659999999999998
    - type: mrr_at_1
      value: 84
    - type: mrr_at_10
      value: 91.067
    - type: mrr_at_100
      value: 91.067
    - type: mrr_at_1000
      value: 91.067
    - type: mrr_at_3
      value: 90.667
    - type: mrr_at_5
      value: 91.067
    - type: ndcg_at_1
      value: 81
    - type: ndcg_at_10
      value: 75.566
    - type: ndcg_at_100
      value: 56.387
    - type: ndcg_at_1000
      value: 49.834
    - type: ndcg_at_3
      value: 80.899
    - type: ndcg_at_5
      value: 80.75099999999999
    - type: precision_at_1
      value: 84
    - type: precision_at_10
      value: 79
    - type: precision_at_100
      value: 57.56
    - type: precision_at_1000
      value: 21.8
    - type: precision_at_3
      value: 84.667
    - type: precision_at_5
      value: 85.2
    - type: recall_at_1
      value: 0.22699999999999998
    - type: recall_at_10
      value: 2.136
    - type: recall_at_100
      value: 13.861
    - type: recall_at_1000
      value: 46.299
    - type: recall_at_3
      value: 0.6649999999999999
    - type: recall_at_5
      value: 1.145
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.752
    - type: map_at_10
      value: 9.951
    - type: map_at_100
      value: 16.794999999999998
    - type: map_at_1000
      value: 18.251
    - type: map_at_3
      value: 5.288
    - type: map_at_5
      value: 6.954000000000001
    - type: mrr_at_1
      value: 38.775999999999996
    - type: mrr_at_10
      value: 50.458000000000006
    - type: mrr_at_100
      value: 51.324999999999996
    - type: mrr_at_1000
      value: 51.339999999999996
    - type: mrr_at_3
      value: 46.939
    - type: mrr_at_5
      value: 47.857
    - type: ndcg_at_1
      value: 36.735
    - type: ndcg_at_10
      value: 25.198999999999998
    - type: ndcg_at_100
      value: 37.938
    - type: ndcg_at_1000
      value: 49.145
    - type: ndcg_at_3
      value: 29.348000000000003
    - type: ndcg_at_5
      value: 25.804
    - type: precision_at_1
      value: 38.775999999999996
    - type: precision_at_10
      value: 22.041
    - type: precision_at_100
      value: 7.939
    - type: precision_at_1000
      value: 1.555
    - type: precision_at_3
      value: 29.932
    - type: precision_at_5
      value: 24.490000000000002
    - type: recall_at_1
      value: 2.752
    - type: recall_at_10
      value: 16.197
    - type: recall_at_100
      value: 49.166
    - type: recall_at_1000
      value: 84.18900000000001
    - type: recall_at_3
      value: 6.438000000000001
    - type: recall_at_5
      value: 9.093
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.47980000000001
    - type: ap
      value: 14.605194452178754
    - type: f1
      value: 55.07362924988948
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.708545557441994
    - type: f1
      value: 60.04751270975683
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 53.21105960597211
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.58419264469214
    - type: cos_sim_ap
      value: 78.55300004517404
    - type: cos_sim_f1
      value: 71.49673530889001
    - type: cos_sim_precision
      value: 68.20795400095831
    - type: cos_sim_recall
      value: 75.11873350923483
    - type: dot_accuracy
      value: 87.58419264469214
    - type: dot_ap
      value: 78.55297659559511
    - type: dot_f1
      value: 71.49673530889001
    - type: dot_precision
      value: 68.20795400095831
    - type: dot_recall
      value: 75.11873350923483
    - type: euclidean_accuracy
      value: 87.58419264469214
    - type: euclidean_ap
      value: 78.55300477331477
    - type: euclidean_f1
      value: 71.49673530889001
    - type: euclidean_precision
      value: 68.20795400095831
    - type: euclidean_recall
      value: 75.11873350923483
    - type: manhattan_accuracy
      value: 87.5663110210407
    - type: manhattan_ap
      value: 78.49982050876562
    - type: manhattan_f1
      value: 71.35488740722104
    - type: manhattan_precision
      value: 68.18946862226497
    - type: manhattan_recall
      value: 74.82849604221636
    - type: max_accuracy
      value: 87.58419264469214
    - type: max_ap
      value: 78.55300477331477
    - type: max_f1
      value: 71.49673530889001
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.09069740365584
    - type: cos_sim_ap
      value: 86.22749303724757
    - type: cos_sim_f1
      value: 78.36863452005407
    - type: cos_sim_precision
      value: 76.49560117302053
    - type: cos_sim_recall
      value: 80.33569448721897
    - type: dot_accuracy
      value: 89.09069740365584
    - type: dot_ap
      value: 86.22750233655673
    - type: dot_f1
      value: 78.36863452005407
    - type: dot_precision
      value: 76.49560117302053
    - type: dot_recall
      value: 80.33569448721897
    - type: euclidean_accuracy
      value: 89.09069740365584
    - type: euclidean_ap
      value: 86.22749355597347
    - type: euclidean_f1
      value: 78.36863452005407
    - type: euclidean_precision
      value: 76.49560117302053
    - type: euclidean_recall
      value: 80.33569448721897
    - type: manhattan_accuracy
      value: 89.08293553770326
    - type: manhattan_ap
      value: 86.21913616084771
    - type: manhattan_f1
      value: 78.3907031479847
    - type: manhattan_precision
      value: 75.0352013517319
    - type: manhattan_recall
      value: 82.06036341238065
    - type: max_accuracy
      value: 89.09069740365584
    - type: max_ap
      value: 86.22750233655673
    - type: max_f1
      value: 78.3907031479847
---

# smcleod/mxbai-embed-large-v1-Q8_0-GGUF
This model was converted to GGUF format from [`mixedbread-ai/mxbai-embed-large-v1`](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo smcleod/mxbai-embed-large-v1-Q8_0-GGUF --hf-file mxbai-embed-large-v1-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo smcleod/mxbai-embed-large-v1-Q8_0-GGUF --hf-file mxbai-embed-large-v1-q8_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo smcleod/mxbai-embed-large-v1-Q8_0-GGUF --hf-file mxbai-embed-large-v1-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo smcleod/mxbai-embed-large-v1-Q8_0-GGUF --hf-file mxbai-embed-large-v1-q8_0.gguf -c 2048
```
