sentence-transformers gguf feature-extraction sentence-similarity transformers mteb llama-cpp gguf-my-repo en base_model:BAAI/bge-large-en-v1.5 base_model:quantized:BAAI/bge-large-en-v1.5 license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: BAAI/bge-large-en-v1.5
language:
- en
license: mit
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- mteb
- llama-cpp
- gguf-my-repo
model-index:
- name: bge-large-en-v1.5
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.8507462686567
    - type: ap
      value: 38.566457320228245
    - type: f1
      value: 69.69386648043475
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 92.416675
    - type: ap
      value: 89.1928861155922
    - type: f1
      value: 92.39477019574215
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.175999999999995
    - type: f1
      value: 47.80712792870253
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.184999999999995
    - type: map_at_10
      value: 55.654
    - type: map_at_100
      value: 56.25
    - type: map_at_1000
      value: 56.255
    - type: map_at_3
      value: 51.742999999999995
    - type: map_at_5
      value: 54.129000000000005
    - type: mrr_at_1
      value: 40.967
    - type: mrr_at_10
      value: 55.96
    - type: mrr_at_100
      value: 56.54900000000001
    - type: mrr_at_1000
      value: 56.554
    - type: mrr_at_3
      value: 51.980000000000004
    - type: mrr_at_5
      value: 54.44
    - type: ndcg_at_1
      value: 40.184999999999995
    - type: ndcg_at_10
      value: 63.542
    - type: ndcg_at_100
      value: 65.96499999999999
    - type: ndcg_at_1000
      value: 66.08699999999999
    - type: ndcg_at_3
      value: 55.582
    - type: ndcg_at_5
      value: 59.855000000000004
    - type: precision_at_1
      value: 40.184999999999995
    - type: precision_at_10
      value: 8.841000000000001
    - type: precision_at_100
      value: 0.987
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 22.238
    - type: precision_at_5
      value: 15.405
    - type: recall_at_1
      value: 40.184999999999995
    - type: recall_at_10
      value: 88.407
    - type: recall_at_100
      value: 98.72
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 66.714
    - type: recall_at_5
      value: 77.027
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 48.567077926750066
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 43.19453389182364
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 64.46555939623092
    - type: mrr
      value: 77.82361605768807
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 84.9554128814735
    - type: cos_sim_spearman
      value: 84.65373612172036
    - type: euclidean_pearson
      value: 83.2905059954138
    - type: euclidean_spearman
      value: 84.52240782811128
    - type: manhattan_pearson
      value: 82.99533802997436
    - type: manhattan_spearman
      value: 84.20673798475734
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 87.78896103896103
    - type: f1
      value: 87.77189310964883
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.714538337650495
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 36.90108349284447
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 32.795
    - type: map_at_10
      value: 43.669000000000004
    - type: map_at_100
      value: 45.151
    - type: map_at_1000
      value: 45.278
    - type: map_at_3
      value: 40.006
    - type: map_at_5
      value: 42.059999999999995
    - type: mrr_at_1
      value: 39.771
    - type: mrr_at_10
      value: 49.826
    - type: mrr_at_100
      value: 50.504000000000005
    - type: mrr_at_1000
      value: 50.549
    - type: mrr_at_3
      value: 47.115
    - type: mrr_at_5
      value: 48.832
    - type: ndcg_at_1
      value: 39.771
    - type: ndcg_at_10
      value: 50.217999999999996
    - type: ndcg_at_100
      value: 55.454
    - type: ndcg_at_1000
      value: 57.37
    - type: ndcg_at_3
      value: 44.885000000000005
    - type: ndcg_at_5
      value: 47.419
    - type: precision_at_1
      value: 39.771
    - type: precision_at_10
      value: 9.642000000000001
    - type: precision_at_100
      value: 1.538
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 21.268
    - type: precision_at_5
      value: 15.536
    - type: recall_at_1
      value: 32.795
    - type: recall_at_10
      value: 62.580999999999996
    - type: recall_at_100
      value: 84.438
    - type: recall_at_1000
      value: 96.492
    - type: recall_at_3
      value: 47.071000000000005
    - type: recall_at_5
      value: 54.079
    - type: map_at_1
      value: 32.671
    - type: map_at_10
      value: 43.334
    - type: map_at_100
      value: 44.566
    - type: map_at_1000
      value: 44.702999999999996
    - type: map_at_3
      value: 40.343
    - type: map_at_5
      value: 41.983
    - type: mrr_at_1
      value: 40.764
    - type: mrr_at_10
      value: 49.382
    - type: mrr_at_100
      value: 49.988
    - type: mrr_at_1000
      value: 50.03300000000001
    - type: mrr_at_3
      value: 47.293
    - type: mrr_at_5
      value: 48.51
    - type: ndcg_at_1
      value: 40.764
    - type: ndcg_at_10
      value: 49.039
    - type: ndcg_at_100
      value: 53.259
    - type: ndcg_at_1000
      value: 55.253
    - type: ndcg_at_3
      value: 45.091
    - type: ndcg_at_5
      value: 46.839999999999996
    - type: precision_at_1
      value: 40.764
    - type: precision_at_10
      value: 9.191
    - type: precision_at_100
      value: 1.476
    - type: precision_at_1000
      value: 0.19499999999999998
    - type: precision_at_3
      value: 21.72
    - type: precision_at_5
      value: 15.299
    - type: recall_at_1
      value: 32.671
    - type: recall_at_10
      value: 58.816
    - type: recall_at_100
      value: 76.654
    - type: recall_at_1000
      value: 89.05999999999999
    - type: recall_at_3
      value: 46.743
    - type: recall_at_5
      value: 51.783
    - type: map_at_1
      value: 40.328
    - type: map_at_10
      value: 53.32599999999999
    - type: map_at_100
      value: 54.37499999999999
    - type: map_at_1000
      value: 54.429
    - type: map_at_3
      value: 49.902
    - type: map_at_5
      value: 52.002
    - type: mrr_at_1
      value: 46.332
    - type: mrr_at_10
      value: 56.858
    - type: mrr_at_100
      value: 57.522
    - type: mrr_at_1000
      value: 57.54899999999999
    - type: mrr_at_3
      value: 54.472
    - type: mrr_at_5
      value: 55.996
    - type: ndcg_at_1
      value: 46.332
    - type: ndcg_at_10
      value: 59.313
    - type: ndcg_at_100
      value: 63.266999999999996
    - type: ndcg_at_1000
      value: 64.36
    - type: ndcg_at_3
      value: 53.815000000000005
    - type: ndcg_at_5
      value: 56.814
    - type: precision_at_1
      value: 46.332
    - type: precision_at_10
      value: 9.53
    - type: precision_at_100
      value: 1.238
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 24.054000000000002
    - type: precision_at_5
      value: 16.589000000000002
    - type: recall_at_1
      value: 40.328
    - type: recall_at_10
      value: 73.421
    - type: recall_at_100
      value: 90.059
    - type: recall_at_1000
      value: 97.81
    - type: recall_at_3
      value: 59.009
    - type: recall_at_5
      value: 66.352
    - type: map_at_1
      value: 27.424
    - type: map_at_10
      value: 36.332
    - type: map_at_100
      value: 37.347
    - type: map_at_1000
      value: 37.422
    - type: map_at_3
      value: 33.743
    - type: map_at_5
      value: 35.176
    - type: mrr_at_1
      value: 29.153000000000002
    - type: mrr_at_10
      value: 38.233
    - type: mrr_at_100
      value: 39.109
    - type: mrr_at_1000
      value: 39.164
    - type: mrr_at_3
      value: 35.876000000000005
    - type: mrr_at_5
      value: 37.169000000000004
    - type: ndcg_at_1
      value: 29.153000000000002
    - type: ndcg_at_10
      value: 41.439
    - type: ndcg_at_100
      value: 46.42
    - type: ndcg_at_1000
      value: 48.242000000000004
    - type: ndcg_at_3
      value: 36.362
    - type: ndcg_at_5
      value: 38.743
    - type: precision_at_1
      value: 29.153000000000002
    - type: precision_at_10
      value: 6.315999999999999
    - type: precision_at_100
      value: 0.927
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 15.443000000000001
    - type: precision_at_5
      value: 10.644
    - type: recall_at_1
      value: 27.424
    - type: recall_at_10
      value: 55.364000000000004
    - type: recall_at_100
      value: 78.211
    - type: recall_at_1000
      value: 91.74600000000001
    - type: recall_at_3
      value: 41.379
    - type: recall_at_5
      value: 47.14
    - type: map_at_1
      value: 19.601
    - type: map_at_10
      value: 27.826
    - type: map_at_100
      value: 29.017
    - type: map_at_1000
      value: 29.137
    - type: map_at_3
      value: 25.125999999999998
    - type: map_at_5
      value: 26.765
    - type: mrr_at_1
      value: 24.005000000000003
    - type: mrr_at_10
      value: 32.716
    - type: mrr_at_100
      value: 33.631
    - type: mrr_at_1000
      value: 33.694
    - type: mrr_at_3
      value: 29.934
    - type: mrr_at_5
      value: 31.630999999999997
    - type: ndcg_at_1
      value: 24.005000000000003
    - type: ndcg_at_10
      value: 33.158
    - type: ndcg_at_100
      value: 38.739000000000004
    - type: ndcg_at_1000
      value: 41.495
    - type: ndcg_at_3
      value: 28.185
    - type: ndcg_at_5
      value: 30.796
    - type: precision_at_1
      value: 24.005000000000003
    - type: precision_at_10
      value: 5.908
    - type: precision_at_100
      value: 1.005
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 13.391
    - type: precision_at_5
      value: 9.876
    - type: recall_at_1
      value: 19.601
    - type: recall_at_10
      value: 44.746
    - type: recall_at_100
      value: 68.82300000000001
    - type: recall_at_1000
      value: 88.215
    - type: recall_at_3
      value: 31.239
    - type: recall_at_5
      value: 37.695
    - type: map_at_1
      value: 30.130000000000003
    - type: map_at_10
      value: 40.96
    - type: map_at_100
      value: 42.282
    - type: map_at_1000
      value: 42.392
    - type: map_at_3
      value: 37.889
    - type: map_at_5
      value: 39.661
    - type: mrr_at_1
      value: 36.958999999999996
    - type: mrr_at_10
      value: 46.835
    - type: mrr_at_100
      value: 47.644
    - type: mrr_at_1000
      value: 47.688
    - type: mrr_at_3
      value: 44.562000000000005
    - type: mrr_at_5
      value: 45.938
    - type: ndcg_at_1
      value: 36.958999999999996
    - type: ndcg_at_10
      value: 47.06
    - type: ndcg_at_100
      value: 52.345
    - type: ndcg_at_1000
      value: 54.35
    - type: ndcg_at_3
      value: 42.301
    - type: ndcg_at_5
      value: 44.635999999999996
    - type: precision_at_1
      value: 36.958999999999996
    - type: precision_at_10
      value: 8.479000000000001
    - type: precision_at_100
      value: 1.284
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 20.244
    - type: precision_at_5
      value: 14.224999999999998
    - type: recall_at_1
      value: 30.130000000000003
    - type: recall_at_10
      value: 59.27
    - type: recall_at_100
      value: 81.195
    - type: recall_at_1000
      value: 94.21199999999999
    - type: recall_at_3
      value: 45.885
    - type: recall_at_5
      value: 52.016
    - type: map_at_1
      value: 26.169999999999998
    - type: map_at_10
      value: 36.451
    - type: map_at_100
      value: 37.791000000000004
    - type: map_at_1000
      value: 37.897
    - type: map_at_3
      value: 33.109
    - type: map_at_5
      value: 34.937000000000005
    - type: mrr_at_1
      value: 32.877
    - type: mrr_at_10
      value: 42.368
    - type: mrr_at_100
      value: 43.201
    - type: mrr_at_1000
      value: 43.259
    - type: mrr_at_3
      value: 39.763999999999996
    - type: mrr_at_5
      value: 41.260000000000005
    - type: ndcg_at_1
      value: 32.877
    - type: ndcg_at_10
      value: 42.659000000000006
    - type: ndcg_at_100
      value: 48.161
    - type: ndcg_at_1000
      value: 50.345
    - type: ndcg_at_3
      value: 37.302
    - type: ndcg_at_5
      value: 39.722
    - type: precision_at_1
      value: 32.877
    - type: precision_at_10
      value: 7.9
    - type: precision_at_100
      value: 1.236
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 17.846
    - type: precision_at_5
      value: 12.9
    - type: recall_at_1
      value: 26.169999999999998
    - type: recall_at_10
      value: 55.35
    - type: recall_at_100
      value: 78.755
    - type: recall_at_1000
      value: 93.518
    - type: recall_at_3
      value: 40.176
    - type: recall_at_5
      value: 46.589000000000006
    - type: map_at_1
      value: 27.15516666666667
    - type: map_at_10
      value: 36.65741666666667
    - type: map_at_100
      value: 37.84991666666666
    - type: map_at_1000
      value: 37.96316666666667
    - type: map_at_3
      value: 33.74974999999999
    - type: map_at_5
      value: 35.3765
    - type: mrr_at_1
      value: 32.08233333333334
    - type: mrr_at_10
      value: 41.033833333333334
    - type: mrr_at_100
      value: 41.84524999999999
    - type: mrr_at_1000
      value: 41.89983333333333
    - type: mrr_at_3
      value: 38.62008333333333
    - type: mrr_at_5
      value: 40.03441666666666
    - type: ndcg_at_1
      value: 32.08233333333334
    - type: ndcg_at_10
      value: 42.229
    - type: ndcg_at_100
      value: 47.26716666666667
    - type: ndcg_at_1000
      value: 49.43466666666667
    - type: ndcg_at_3
      value: 37.36408333333333
    - type: ndcg_at_5
      value: 39.6715
    - type: precision_at_1
      value: 32.08233333333334
    - type: precision_at_10
      value: 7.382583333333334
    - type: precision_at_100
      value: 1.16625
    - type: precision_at_1000
      value: 0.15408333333333332
    - type: precision_at_3
      value: 17.218
    - type: precision_at_5
      value: 12.21875
    - type: recall_at_1
      value: 27.15516666666667
    - type: recall_at_10
      value: 54.36683333333333
    - type: recall_at_100
      value: 76.37183333333333
    - type: recall_at_1000
      value: 91.26183333333333
    - type: recall_at_3
      value: 40.769916666666674
    - type: recall_at_5
      value: 46.702333333333335
    - type: map_at_1
      value: 25.749
    - type: map_at_10
      value: 33.001999999999995
    - type: map_at_100
      value: 33.891
    - type: map_at_1000
      value: 33.993
    - type: map_at_3
      value: 30.703999999999997
    - type: map_at_5
      value: 31.959
    - type: mrr_at_1
      value: 28.834
    - type: mrr_at_10
      value: 35.955
    - type: mrr_at_100
      value: 36.709
    - type: mrr_at_1000
      value: 36.779
    - type: mrr_at_3
      value: 33.947
    - type: mrr_at_5
      value: 35.089
    - type: ndcg_at_1
      value: 28.834
    - type: ndcg_at_10
      value: 37.329
    - type: ndcg_at_100
      value: 41.79
    - type: ndcg_at_1000
      value: 44.169000000000004
    - type: ndcg_at_3
      value: 33.184999999999995
    - type: ndcg_at_5
      value: 35.107
    - type: precision_at_1
      value: 28.834
    - type: precision_at_10
      value: 5.7669999999999995
    - type: precision_at_100
      value: 0.876
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 14.213000000000001
    - type: precision_at_5
      value: 9.754999999999999
    - type: recall_at_1
      value: 25.749
    - type: recall_at_10
      value: 47.791
    - type: recall_at_100
      value: 68.255
    - type: recall_at_1000
      value: 85.749
    - type: recall_at_3
      value: 36.199
    - type: recall_at_5
      value: 41.071999999999996
    - type: map_at_1
      value: 17.777
    - type: map_at_10
      value: 25.201
    - type: map_at_100
      value: 26.423999999999996
    - type: map_at_1000
      value: 26.544
    - type: map_at_3
      value: 22.869
    - type: map_at_5
      value: 24.023
    - type: mrr_at_1
      value: 21.473
    - type: mrr_at_10
      value: 29.12
    - type: mrr_at_100
      value: 30.144
    - type: mrr_at_1000
      value: 30.215999999999998
    - type: mrr_at_3
      value: 26.933
    - type: mrr_at_5
      value: 28.051
    - type: ndcg_at_1
      value: 21.473
    - type: ndcg_at_10
      value: 30.003
    - type: ndcg_at_100
      value: 35.766
    - type: ndcg_at_1000
      value: 38.501000000000005
    - type: ndcg_at_3
      value: 25.773000000000003
    - type: ndcg_at_5
      value: 27.462999999999997
    - type: precision_at_1
      value: 21.473
    - type: precision_at_10
      value: 5.482
    - type: precision_at_100
      value: 0.975
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 12.205
    - type: precision_at_5
      value: 8.692
    - type: recall_at_1
      value: 17.777
    - type: recall_at_10
      value: 40.582
    - type: recall_at_100
      value: 66.305
    - type: recall_at_1000
      value: 85.636
    - type: recall_at_3
      value: 28.687
    - type: recall_at_5
      value: 33.089
    - type: map_at_1
      value: 26.677
    - type: map_at_10
      value: 36.309000000000005
    - type: map_at_100
      value: 37.403999999999996
    - type: map_at_1000
      value: 37.496
    - type: map_at_3
      value: 33.382
    - type: map_at_5
      value: 34.98
    - type: mrr_at_1
      value: 31.343
    - type: mrr_at_10
      value: 40.549
    - type: mrr_at_100
      value: 41.342
    - type: mrr_at_1000
      value: 41.397
    - type: mrr_at_3
      value: 38.029
    - type: mrr_at_5
      value: 39.451
    - type: ndcg_at_1
      value: 31.343
    - type: ndcg_at_10
      value: 42.1
    - type: ndcg_at_100
      value: 47.089999999999996
    - type: ndcg_at_1000
      value: 49.222
    - type: ndcg_at_3
      value: 36.836999999999996
    - type: ndcg_at_5
      value: 39.21
    - type: precision_at_1
      value: 31.343
    - type: precision_at_10
      value: 7.164
    - type: precision_at_100
      value: 1.0959999999999999
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 16.915
    - type: precision_at_5
      value: 11.940000000000001
    - type: recall_at_1
      value: 26.677
    - type: recall_at_10
      value: 55.54599999999999
    - type: recall_at_100
      value: 77.094
    - type: recall_at_1000
      value: 92.01
    - type: recall_at_3
      value: 41.191
    - type: recall_at_5
      value: 47.006
    - type: map_at_1
      value: 24.501
    - type: map_at_10
      value: 33.102
    - type: map_at_100
      value: 34.676
    - type: map_at_1000
      value: 34.888000000000005
    - type: map_at_3
      value: 29.944
    - type: map_at_5
      value: 31.613999999999997
    - type: mrr_at_1
      value: 29.447000000000003
    - type: mrr_at_10
      value: 37.996
    - type: mrr_at_100
      value: 38.946
    - type: mrr_at_1000
      value: 38.995000000000005
    - type: mrr_at_3
      value: 35.079
    - type: mrr_at_5
      value: 36.69
    - type: ndcg_at_1
      value: 29.447000000000003
    - type: ndcg_at_10
      value: 39.232
    - type: ndcg_at_100
      value: 45.247
    - type: ndcg_at_1000
      value: 47.613
    - type: ndcg_at_3
      value: 33.922999999999995
    - type: ndcg_at_5
      value: 36.284
    - type: precision_at_1
      value: 29.447000000000003
    - type: precision_at_10
      value: 7.648000000000001
    - type: precision_at_100
      value: 1.516
    - type: precision_at_1000
      value: 0.23900000000000002
    - type: precision_at_3
      value: 16.008
    - type: precision_at_5
      value: 11.779
    - type: recall_at_1
      value: 24.501
    - type: recall_at_10
      value: 51.18899999999999
    - type: recall_at_100
      value: 78.437
    - type: recall_at_1000
      value: 92.842
    - type: recall_at_3
      value: 35.808
    - type: recall_at_5
      value: 42.197
    - type: map_at_1
      value: 22.039
    - type: map_at_10
      value: 30.377
    - type: map_at_100
      value: 31.275
    - type: map_at_1000
      value: 31.379
    - type: map_at_3
      value: 27.98
    - type: map_at_5
      value: 29.358
    - type: mrr_at_1
      value: 24.03
    - type: mrr_at_10
      value: 32.568000000000005
    - type: mrr_at_100
      value: 33.403
    - type: mrr_at_1000
      value: 33.475
    - type: mrr_at_3
      value: 30.436999999999998
    - type: mrr_at_5
      value: 31.796000000000003
    - type: ndcg_at_1
      value: 24.03
    - type: ndcg_at_10
      value: 35.198
    - type: ndcg_at_100
      value: 39.668
    - type: ndcg_at_1000
      value: 42.296
    - type: ndcg_at_3
      value: 30.709999999999997
    - type: ndcg_at_5
      value: 33.024
    - type: precision_at_1
      value: 24.03
    - type: precision_at_10
      value: 5.564
    - type: precision_at_100
      value: 0.828
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 13.309000000000001
    - type: precision_at_5
      value: 9.39
    - type: recall_at_1
      value: 22.039
    - type: recall_at_10
      value: 47.746
    - type: recall_at_100
      value: 68.23599999999999
    - type: recall_at_1000
      value: 87.852
    - type: recall_at_3
      value: 35.852000000000004
    - type: recall_at_5
      value: 41.410000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.692999999999998
    - type: map_at_10
      value: 26.903
    - type: map_at_100
      value: 28.987000000000002
    - type: map_at_1000
      value: 29.176999999999996
    - type: map_at_3
      value: 22.137
    - type: map_at_5
      value: 24.758
    - type: mrr_at_1
      value: 35.57
    - type: mrr_at_10
      value: 47.821999999999996
    - type: mrr_at_100
      value: 48.608000000000004
    - type: mrr_at_1000
      value: 48.638999999999996
    - type: mrr_at_3
      value: 44.452000000000005
    - type: mrr_at_5
      value: 46.546
    - type: ndcg_at_1
      value: 35.57
    - type: ndcg_at_10
      value: 36.567
    - type: ndcg_at_100
      value: 44.085
    - type: ndcg_at_1000
      value: 47.24
    - type: ndcg_at_3
      value: 29.964000000000002
    - type: ndcg_at_5
      value: 32.511
    - type: precision_at_1
      value: 35.57
    - type: precision_at_10
      value: 11.485
    - type: precision_at_100
      value: 1.9619999999999997
    - type: precision_at_1000
      value: 0.256
    - type: precision_at_3
      value: 22.237000000000002
    - type: precision_at_5
      value: 17.471999999999998
    - type: recall_at_1
      value: 15.692999999999998
    - type: recall_at_10
      value: 43.056
    - type: recall_at_100
      value: 68.628
    - type: recall_at_1000
      value: 86.075
    - type: recall_at_3
      value: 26.918999999999997
    - type: recall_at_5
      value: 34.14
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.53
    - type: map_at_10
      value: 20.951
    - type: map_at_100
      value: 30.136000000000003
    - type: map_at_1000
      value: 31.801000000000002
    - type: map_at_3
      value: 15.021
    - type: map_at_5
      value: 17.471999999999998
    - type: mrr_at_1
      value: 71.0
    - type: mrr_at_10
      value: 79.176
    - type: mrr_at_100
      value: 79.418
    - type: mrr_at_1000
      value: 79.426
    - type: mrr_at_3
      value: 78.125
    - type: mrr_at_5
      value: 78.61200000000001
    - type: ndcg_at_1
      value: 58.5
    - type: ndcg_at_10
      value: 44.106
    - type: ndcg_at_100
      value: 49.268
    - type: ndcg_at_1000
      value: 56.711999999999996
    - type: ndcg_at_3
      value: 48.934
    - type: ndcg_at_5
      value: 45.826
    - type: precision_at_1
      value: 71.0
    - type: precision_at_10
      value: 35.0
    - type: precision_at_100
      value: 11.360000000000001
    - type: precision_at_1000
      value: 2.046
    - type: precision_at_3
      value: 52.833
    - type: precision_at_5
      value: 44.15
    - type: recall_at_1
      value: 9.53
    - type: recall_at_10
      value: 26.811
    - type: recall_at_100
      value: 55.916999999999994
    - type: recall_at_1000
      value: 79.973
    - type: recall_at_3
      value: 16.413
    - type: recall_at_5
      value: 19.980999999999998
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 51.519999999999996
    - type: f1
      value: 46.36601294761231
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 74.413
    - type: map_at_10
      value: 83.414
    - type: map_at_100
      value: 83.621
    - type: map_at_1000
      value: 83.635
    - type: map_at_3
      value: 82.337
    - type: map_at_5
      value: 83.039
    - type: mrr_at_1
      value: 80.19800000000001
    - type: mrr_at_10
      value: 87.715
    - type: mrr_at_100
      value: 87.778
    - type: mrr_at_1000
      value: 87.779
    - type: mrr_at_3
      value: 87.106
    - type: mrr_at_5
      value: 87.555
    - type: ndcg_at_1
      value: 80.19800000000001
    - type: ndcg_at_10
      value: 87.182
    - type: ndcg_at_100
      value: 87.90299999999999
    - type: ndcg_at_1000
      value: 88.143
    - type: ndcg_at_3
      value: 85.60600000000001
    - type: ndcg_at_5
      value: 86.541
    - type: precision_at_1
      value: 80.19800000000001
    - type: precision_at_10
      value: 10.531
    - type: precision_at_100
      value: 1.113
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 32.933
    - type: precision_at_5
      value: 20.429
    - type: recall_at_1
      value: 74.413
    - type: recall_at_10
      value: 94.363
    - type: recall_at_100
      value: 97.165
    - type: recall_at_1000
      value: 98.668
    - type: recall_at_3
      value: 90.108
    - type: recall_at_5
      value: 92.52
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.701
    - type: map_at_10
      value: 37.122
    - type: map_at_100
      value: 39.178000000000004
    - type: map_at_1000
      value: 39.326
    - type: map_at_3
      value: 32.971000000000004
    - type: map_at_5
      value: 35.332
    - type: mrr_at_1
      value: 44.753
    - type: mrr_at_10
      value: 53.452
    - type: mrr_at_100
      value: 54.198
    - type: mrr_at_1000
      value: 54.225
    - type: mrr_at_3
      value: 50.952
    - type: mrr_at_5
      value: 52.464
    - type: ndcg_at_1
      value: 44.753
    - type: ndcg_at_10
      value: 45.021
    - type: ndcg_at_100
      value: 52.028
    - type: ndcg_at_1000
      value: 54.596000000000004
    - type: ndcg_at_3
      value: 41.622
    - type: ndcg_at_5
      value: 42.736000000000004
    - type: precision_at_1
      value: 44.753
    - type: precision_at_10
      value: 12.284
    - type: precision_at_100
      value: 1.955
    - type: precision_at_1000
      value: 0.243
    - type: precision_at_3
      value: 27.828999999999997
    - type: precision_at_5
      value: 20.061999999999998
    - type: recall_at_1
      value: 22.701
    - type: recall_at_10
      value: 51.432
    - type: recall_at_100
      value: 77.009
    - type: recall_at_1000
      value: 92.511
    - type: recall_at_3
      value: 37.919000000000004
    - type: recall_at_5
      value: 44.131
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.189
    - type: map_at_10
      value: 66.24600000000001
    - type: map_at_100
      value: 67.098
    - type: map_at_1000
      value: 67.149
    - type: map_at_3
      value: 62.684
    - type: map_at_5
      value: 64.974
    - type: mrr_at_1
      value: 80.378
    - type: mrr_at_10
      value: 86.127
    - type: mrr_at_100
      value: 86.29299999999999
    - type: mrr_at_1000
      value: 86.297
    - type: mrr_at_3
      value: 85.31400000000001
    - type: mrr_at_5
      value: 85.858
    - type: ndcg_at_1
      value: 80.378
    - type: ndcg_at_10
      value: 74.101
    - type: ndcg_at_100
      value: 76.993
    - type: ndcg_at_1000
      value: 77.948
    - type: ndcg_at_3
      value: 69.232
    - type: ndcg_at_5
      value: 72.04599999999999
    - type: precision_at_1
      value: 80.378
    - type: precision_at_10
      value: 15.595999999999998
    - type: precision_at_100
      value: 1.7840000000000003
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 44.884
    - type: precision_at_5
      value: 29.145
    - type: recall_at_1
      value: 40.189
    - type: recall_at_10
      value: 77.981
    - type: recall_at_100
      value: 89.21
    - type: recall_at_1000
      value: 95.48299999999999
    - type: recall_at_3
      value: 67.326
    - type: recall_at_5
      value: 72.863
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 92.84599999999999
    - type: ap
      value: 89.4710787567357
    - type: f1
      value: 92.83752676932258
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 23.132
    - type: map_at_10
      value: 35.543
    - type: map_at_100
      value: 36.702
    - type: map_at_1000
      value: 36.748999999999995
    - type: map_at_3
      value: 31.737
    - type: map_at_5
      value: 33.927
    - type: mrr_at_1
      value: 23.782
    - type: mrr_at_10
      value: 36.204
    - type: mrr_at_100
      value: 37.29
    - type: mrr_at_1000
      value: 37.330999999999996
    - type: mrr_at_3
      value: 32.458999999999996
    - type: mrr_at_5
      value: 34.631
    - type: ndcg_at_1
      value: 23.782
    - type: ndcg_at_10
      value: 42.492999999999995
    - type: ndcg_at_100
      value: 47.985
    - type: ndcg_at_1000
      value: 49.141
    - type: ndcg_at_3
      value: 34.748000000000005
    - type: ndcg_at_5
      value: 38.651
    - type: precision_at_1
      value: 23.782
    - type: precision_at_10
      value: 6.665
    - type: precision_at_100
      value: 0.941
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.776
    - type: precision_at_5
      value: 10.84
    - type: recall_at_1
      value: 23.132
    - type: recall_at_10
      value: 63.794
    - type: recall_at_100
      value: 89.027
    - type: recall_at_1000
      value: 97.807
    - type: recall_at_3
      value: 42.765
    - type: recall_at_5
      value: 52.11
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 94.59188326493388
    - type: f1
      value: 94.3842594786827
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 79.49384404924761
    - type: f1
      value: 59.7580539534629
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 77.56220578345663
    - type: f1
      value: 75.27228165561478
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 80.53463349024884
    - type: f1
      value: 80.4893958236536
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.56100273484962
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 31.470380028839607
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.06102792457849
    - type: mrr
      value: 33.30709199672238
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.776999999999999
    - type: map_at_10
      value: 14.924000000000001
    - type: map_at_100
      value: 18.955
    - type: map_at_1000
      value: 20.538999999999998
    - type: map_at_3
      value: 10.982
    - type: map_at_5
      value: 12.679000000000002
    - type: mrr_at_1
      value: 47.988
    - type: mrr_at_10
      value: 57.232000000000006
    - type: mrr_at_100
      value: 57.818999999999996
    - type: mrr_at_1000
      value: 57.847
    - type: mrr_at_3
      value: 54.901999999999994
    - type: mrr_at_5
      value: 56.481
    - type: ndcg_at_1
      value: 46.594
    - type: ndcg_at_10
      value: 38.129000000000005
    - type: ndcg_at_100
      value: 35.54
    - type: ndcg_at_1000
      value: 44.172
    - type: ndcg_at_3
      value: 43.025999999999996
    - type: ndcg_at_5
      value: 41.052
    - type: precision_at_1
      value: 47.988
    - type: precision_at_10
      value: 28.111000000000004
    - type: precision_at_100
      value: 8.929
    - type: precision_at_1000
      value: 2.185
    - type: precision_at_3
      value: 40.144000000000005
    - type: precision_at_5
      value: 35.232
    - type: recall_at_1
      value: 6.776999999999999
    - type: recall_at_10
      value: 19.289
    - type: recall_at_100
      value: 36.359
    - type: recall_at_1000
      value: 67.54
    - type: recall_at_3
      value: 11.869
    - type: recall_at_5
      value: 14.999
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.108000000000004
    - type: map_at_10
      value: 47.126000000000005
    - type: map_at_100
      value: 48.171
    - type: map_at_1000
      value: 48.199
    - type: map_at_3
      value: 42.734
    - type: map_at_5
      value: 45.362
    - type: mrr_at_1
      value: 34.936
    - type: mrr_at_10
      value: 49.571
    - type: mrr_at_100
      value: 50.345
    - type: mrr_at_1000
      value: 50.363
    - type: mrr_at_3
      value: 45.959
    - type: mrr_at_5
      value: 48.165
    - type: ndcg_at_1
      value: 34.936
    - type: ndcg_at_10
      value: 55.028999999999996
    - type: ndcg_at_100
      value: 59.244
    - type: ndcg_at_1000
      value: 59.861
    - type: ndcg_at_3
      value: 46.872
    - type: ndcg_at_5
      value: 51.217999999999996
    - type: precision_at_1
      value: 34.936
    - type: precision_at_10
      value: 9.099
    - type: precision_at_100
      value: 1.145
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 21.456
    - type: precision_at_5
      value: 15.411
    - type: recall_at_1
      value: 31.108000000000004
    - type: recall_at_10
      value: 76.53999999999999
    - type: recall_at_100
      value: 94.39
    - type: recall_at_1000
      value: 98.947
    - type: recall_at_3
      value: 55.572
    - type: recall_at_5
      value: 65.525
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 71.56400000000001
    - type: map_at_10
      value: 85.482
    - type: map_at_100
      value: 86.114
    - type: map_at_1000
      value: 86.13
    - type: map_at_3
      value: 82.607
    - type: map_at_5
      value: 84.405
    - type: mrr_at_1
      value: 82.42
    - type: mrr_at_10
      value: 88.304
    - type: mrr_at_100
      value: 88.399
    - type: mrr_at_1000
      value: 88.399
    - type: mrr_at_3
      value: 87.37
    - type: mrr_at_5
      value: 88.024
    - type: ndcg_at_1
      value: 82.45
    - type: ndcg_at_10
      value: 89.06500000000001
    - type: ndcg_at_100
      value: 90.232
    - type: ndcg_at_1000
      value: 90.305
    - type: ndcg_at_3
      value: 86.375
    - type: ndcg_at_5
      value: 87.85300000000001
    - type: precision_at_1
      value: 82.45
    - type: precision_at_10
      value: 13.486999999999998
    - type: precision_at_100
      value: 1.534
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.813
    - type: precision_at_5
      value: 24.773999999999997
    - type: recall_at_1
      value: 71.56400000000001
    - type: recall_at_10
      value: 95.812
    - type: recall_at_100
      value: 99.7
    - type: recall_at_1000
      value: 99.979
    - type: recall_at_3
      value: 87.966
    - type: recall_at_5
      value: 92.268
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 57.241876648614145
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 64.66212576446223
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.308
    - type: map_at_10
      value: 13.803
    - type: map_at_100
      value: 16.176
    - type: map_at_1000
      value: 16.561
    - type: map_at_3
      value: 9.761000000000001
    - type: map_at_5
      value: 11.802
    - type: mrr_at_1
      value: 26.200000000000003
    - type: mrr_at_10
      value: 37.621
    - type: mrr_at_100
      value: 38.767
    - type: mrr_at_1000
      value: 38.815
    - type: mrr_at_3
      value: 34.117
    - type: mrr_at_5
      value: 36.107
    - type: ndcg_at_1
      value: 26.200000000000003
    - type: ndcg_at_10
      value: 22.64
    - type: ndcg_at_100
      value: 31.567
    - type: ndcg_at_1000
      value: 37.623
    - type: ndcg_at_3
      value: 21.435000000000002
    - type: ndcg_at_5
      value: 18.87
    - type: precision_at_1
      value: 26.200000000000003
    - type: precision_at_10
      value: 11.74
    - type: precision_at_100
      value: 2.465
    - type: precision_at_1000
      value: 0.391
    - type: precision_at_3
      value: 20.033
    - type: precision_at_5
      value: 16.64
    - type: recall_at_1
      value: 5.308
    - type: recall_at_10
      value: 23.794999999999998
    - type: recall_at_100
      value: 50.015
    - type: recall_at_1000
      value: 79.283
    - type: recall_at_3
      value: 12.178
    - type: recall_at_5
      value: 16.882
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 84.93231134675553
    - type: cos_sim_spearman
      value: 81.68319292603205
    - type: euclidean_pearson
      value: 81.8396814380367
    - type: euclidean_spearman
      value: 81.24641903349945
    - type: manhattan_pearson
      value: 81.84698799204274
    - type: manhattan_spearman
      value: 81.24269997904105
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 86.73241671587446
    - type: cos_sim_spearman
      value: 79.05091082971826
    - type: euclidean_pearson
      value: 83.91146869578044
    - type: euclidean_spearman
      value: 79.87978465370936
    - type: manhattan_pearson
      value: 83.90888338917678
    - type: manhattan_spearman
      value: 79.87482848584241
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 85.14970731146177
    - type: cos_sim_spearman
      value: 86.37363490084627
    - type: euclidean_pearson
      value: 83.02154218530433
    - type: euclidean_spearman
      value: 83.80258761957367
    - type: manhattan_pearson
      value: 83.01664495119347
    - type: manhattan_spearman
      value: 83.77567458007952
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 83.40474139886784
    - type: cos_sim_spearman
      value: 82.77768789165984
    - type: euclidean_pearson
      value: 80.7065877443695
    - type: euclidean_spearman
      value: 81.375940662505
    - type: manhattan_pearson
      value: 80.6507552270278
    - type: manhattan_spearman
      value: 81.32782179098741
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 87.08585968722274
    - type: cos_sim_spearman
      value: 88.03110031451399
    - type: euclidean_pearson
      value: 85.74012019602384
    - type: euclidean_spearman
      value: 86.13592849438209
    - type: manhattan_pearson
      value: 85.74404842369206
    - type: manhattan_spearman
      value: 86.14492318960154
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 84.95069052788875
    - type: cos_sim_spearman
      value: 86.4867991595147
    - type: euclidean_pearson
      value: 84.31013325754635
    - type: euclidean_spearman
      value: 85.01529258006482
    - type: manhattan_pearson
      value: 84.26995570085374
    - type: manhattan_spearman
      value: 84.96982104986162
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 87.54617647971897
    - type: cos_sim_spearman
      value: 87.49834181751034
    - type: euclidean_pearson
      value: 86.01015322577122
    - type: euclidean_spearman
      value: 84.63362652063199
    - type: manhattan_pearson
      value: 86.13807574475706
    - type: manhattan_spearman
      value: 84.7772370721132
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 67.20047755786615
    - type: cos_sim_spearman
      value: 67.05324077987636
    - type: euclidean_pearson
      value: 66.91930642976601
    - type: euclidean_spearman
      value: 65.21491856099105
    - type: manhattan_pearson
      value: 66.78756851976624
    - type: manhattan_spearman
      value: 65.12356257740728
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 86.19852871539686
    - type: cos_sim_spearman
      value: 87.5161895296395
    - type: euclidean_pearson
      value: 84.59848645207485
    - type: euclidean_spearman
      value: 85.26427328757919
    - type: manhattan_pearson
      value: 84.59747366996524
    - type: manhattan_spearman
      value: 85.24045855146915
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 87.63320317811032
    - type: mrr
      value: 96.26242947321379
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.928000000000004
    - type: map_at_10
      value: 70.112
    - type: map_at_100
      value: 70.59299999999999
    - type: map_at_1000
      value: 70.623
    - type: map_at_3
      value: 66.846
    - type: map_at_5
      value: 68.447
    - type: mrr_at_1
      value: 64.0
    - type: mrr_at_10
      value: 71.212
    - type: mrr_at_100
      value: 71.616
    - type: mrr_at_1000
      value: 71.64500000000001
    - type: mrr_at_3
      value: 68.77799999999999
    - type: mrr_at_5
      value: 70.094
    - type: ndcg_at_1
      value: 64.0
    - type: ndcg_at_10
      value: 74.607
    - type: ndcg_at_100
      value: 76.416
    - type: ndcg_at_1000
      value: 77.102
    - type: ndcg_at_3
      value: 69.126
    - type: ndcg_at_5
      value: 71.41300000000001
    - type: precision_at_1
      value: 64.0
    - type: precision_at_10
      value: 9.933
    - type: precision_at_100
      value: 1.077
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 26.556
    - type: precision_at_5
      value: 17.467
    - type: recall_at_1
      value: 60.928000000000004
    - type: recall_at_10
      value: 87.322
    - type: recall_at_100
      value: 94.833
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 72.628
    - type: recall_at_5
      value: 78.428
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.86237623762376
    - type: cos_sim_ap
      value: 96.72586477206649
    - type: cos_sim_f1
      value: 93.01858362631845
    - type: cos_sim_precision
      value: 93.4409687184662
    - type: cos_sim_recall
      value: 92.60000000000001
    - type: dot_accuracy
      value: 99.78019801980199
    - type: dot_ap
      value: 93.72748205246228
    - type: dot_f1
      value: 89.04109589041096
    - type: dot_precision
      value: 87.16475095785441
    - type: dot_recall
      value: 91.0
    - type: euclidean_accuracy
      value: 99.85445544554456
    - type: euclidean_ap
      value: 96.6661459876145
    - type: euclidean_f1
      value: 92.58337481333997
    - type: euclidean_precision
      value: 92.17046580773042
    - type: euclidean_recall
      value: 93.0
    - type: manhattan_accuracy
      value: 99.85445544554456
    - type: manhattan_ap
      value: 96.6883549244056
    - type: manhattan_f1
      value: 92.57598405580468
    - type: manhattan_precision
      value: 92.25422045680239
    - type: manhattan_recall
      value: 92.9
    - type: max_accuracy
      value: 99.86237623762376
    - type: max_ap
      value: 96.72586477206649
    - type: max_f1
      value: 93.01858362631845
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 66.39930057069995
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 34.96398659903402
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 55.946944700355395
    - type: mrr
      value: 56.97151398438164
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.541657650692905
    - type: cos_sim_spearman
      value: 31.605804192286303
    - type: dot_pearson
      value: 28.26905996736398
    - type: dot_spearman
      value: 27.864801765851187
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.22599999999999998
    - type: map_at_10
      value: 1.8870000000000002
    - type: map_at_100
      value: 9.78
    - type: map_at_1000
      value: 22.514
    - type: map_at_3
      value: 0.6669999999999999
    - type: map_at_5
      value: 1.077
    - type: mrr_at_1
      value: 82.0
    - type: mrr_at_10
      value: 89.86699999999999
    - type: mrr_at_100
      value: 89.86699999999999
    - type: mrr_at_1000
      value: 89.86699999999999
    - type: mrr_at_3
      value: 89.667
    - type: mrr_at_5
      value: 89.667
    - type: ndcg_at_1
      value: 79.0
    - type: ndcg_at_10
      value: 74.818
    - type: ndcg_at_100
      value: 53.715999999999994
    - type: ndcg_at_1000
      value: 47.082
    - type: ndcg_at_3
      value: 82.134
    - type: ndcg_at_5
      value: 79.81899999999999
    - type: precision_at_1
      value: 82.0
    - type: precision_at_10
      value: 78.0
    - type: precision_at_100
      value: 54.48
    - type: precision_at_1000
      value: 20.518
    - type: precision_at_3
      value: 87.333
    - type: precision_at_5
      value: 85.2
    - type: recall_at_1
      value: 0.22599999999999998
    - type: recall_at_10
      value: 2.072
    - type: recall_at_100
      value: 13.013
    - type: recall_at_1000
      value: 43.462
    - type: recall_at_3
      value: 0.695
    - type: recall_at_5
      value: 1.139
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.328
    - type: map_at_10
      value: 9.795
    - type: map_at_100
      value: 15.801000000000002
    - type: map_at_1000
      value: 17.23
    - type: map_at_3
      value: 4.734
    - type: map_at_5
      value: 6.644
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 46.902
    - type: mrr_at_100
      value: 47.495
    - type: mrr_at_1000
      value: 47.495
    - type: mrr_at_3
      value: 41.156
    - type: mrr_at_5
      value: 44.218
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 24.806
    - type: ndcg_at_100
      value: 36.419000000000004
    - type: ndcg_at_1000
      value: 47.272999999999996
    - type: ndcg_at_3
      value: 25.666
    - type: ndcg_at_5
      value: 25.448999999999998
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 23.061
    - type: precision_at_100
      value: 7.714
    - type: precision_at_1000
      value: 1.484
    - type: precision_at_3
      value: 26.531
    - type: precision_at_5
      value: 26.122
    - type: recall_at_1
      value: 2.328
    - type: recall_at_10
      value: 16.524
    - type: recall_at_100
      value: 47.179
    - type: recall_at_1000
      value: 81.22200000000001
    - type: recall_at_3
      value: 5.745
    - type: recall_at_5
      value: 9.339
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.9142
    - type: ap
      value: 14.335574772555415
    - type: f1
      value: 54.62839595194111
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.94340690435768
    - type: f1
      value: 60.286487936731916
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 51.26597708987974
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.48882398521786
    - type: cos_sim_ap
      value: 79.04326607602204
    - type: cos_sim_f1
      value: 71.64566826860633
    - type: cos_sim_precision
      value: 70.55512918905092
    - type: cos_sim_recall
      value: 72.77044854881267
    - type: dot_accuracy
      value: 84.19264469213805
    - type: dot_ap
      value: 67.96360043562528
    - type: dot_f1
      value: 64.06418393006827
    - type: dot_precision
      value: 58.64941898706424
    - type: dot_recall
      value: 70.58047493403694
    - type: euclidean_accuracy
      value: 87.45902127913214
    - type: euclidean_ap
      value: 78.9742237648272
    - type: euclidean_f1
      value: 71.5553235908142
    - type: euclidean_precision
      value: 70.77955601445535
    - type: euclidean_recall
      value: 72.34828496042216
    - type: manhattan_accuracy
      value: 87.41729749061214
    - type: manhattan_ap
      value: 78.90073137580596
    - type: manhattan_f1
      value: 71.3942611553533
    - type: manhattan_precision
      value: 68.52705653967483
    - type: manhattan_recall
      value: 74.51187335092348
    - type: max_accuracy
      value: 87.48882398521786
    - type: max_ap
      value: 79.04326607602204
    - type: max_f1
      value: 71.64566826860633
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.68125897465751
    - type: cos_sim_ap
      value: 85.6003454431979
    - type: cos_sim_f1
      value: 77.6957163958641
    - type: cos_sim_precision
      value: 73.0110366307807
    - type: cos_sim_recall
      value: 83.02279026793964
    - type: dot_accuracy
      value: 87.7672992587418
    - type: dot_ap
      value: 82.4971301112899
    - type: dot_f1
      value: 75.90528233151184
    - type: dot_precision
      value: 72.0370626469368
    - type: dot_recall
      value: 80.21250384970742
    - type: euclidean_accuracy
      value: 88.4503434625684
    - type: euclidean_ap
      value: 84.91949884748384
    - type: euclidean_f1
      value: 76.92365018444684
    - type: euclidean_precision
      value: 74.53245721712759
    - type: euclidean_recall
      value: 79.47336002463813
    - type: manhattan_accuracy
      value: 88.47556952691427
    - type: manhattan_ap
      value: 84.8963689101517
    - type: manhattan_f1
      value: 76.85901249256395
    - type: manhattan_precision
      value: 74.31693989071039
    - type: manhattan_recall
      value: 79.58115183246073
    - type: max_accuracy
      value: 88.68125897465751
    - type: max_ap
      value: 85.6003454431979
    - type: max_f1
      value: 77.6957163958641
---

# archit28/bge-large-en-v1.5-Q4_K_S-GGUF
This model was converted to GGUF format from [`BAAI/bge-large-en-v1.5`](https://huggingface.co/BAAI/bge-large-en-v1.5) 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/BAAI/bge-large-en-v1.5) 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 archit28/bge-large-en-v1.5-Q4_K_S-GGUF --hf-file bge-large-en-v1.5-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo archit28/bge-large-en-v1.5-Q4_K_S-GGUF --hf-file bge-large-en-v1.5-q4_k_s.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 archit28/bge-large-en-v1.5-Q4_K_S-GGUF --hf-file bge-large-en-v1.5-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo archit28/bge-large-en-v1.5-Q4_K_S-GGUF --hf-file bge-large-en-v1.5-q4_k_s.gguf -c 2048
```
