sentence-transformers gguf mteb Sentence Transformers sentence-similarity llama-cpp gguf-my-repo en base_model:intfloat/e5-large-v2 base_model:quantized:intfloat/e5-large-v2 license:mit model-index autotrain_compatible endpoints_compatible region:us feature-extraction
---
base_model: intfloat/e5-large-v2
language:
- en
license: mit
tags:
- mteb
- Sentence Transformers
- sentence-similarity
- sentence-transformers
- llama-cpp
- gguf-my-repo
model-index:
- name: e5-large-v2
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 79.22388059701493
    - type: ap
      value: 43.20816505595132
    - type: f1
      value: 73.27811303522058
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.748325
    - type: ap
      value: 90.72534979701297
    - type: f1
      value: 93.73895874282185
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.612
    - type: f1
      value: 47.61157345898393
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 23.541999999999998
    - type: map_at_10
      value: 38.208
    - type: map_at_100
      value: 39.417
    - type: map_at_1000
      value: 39.428999999999995
    - type: map_at_3
      value: 33.95
    - type: map_at_5
      value: 36.329
    - type: mrr_at_1
      value: 23.755000000000003
    - type: mrr_at_10
      value: 38.288
    - type: mrr_at_100
      value: 39.511
    - type: mrr_at_1000
      value: 39.523
    - type: mrr_at_3
      value: 34.009
    - type: mrr_at_5
      value: 36.434
    - type: ndcg_at_1
      value: 23.541999999999998
    - type: ndcg_at_10
      value: 46.417
    - type: ndcg_at_100
      value: 51.812000000000005
    - type: ndcg_at_1000
      value: 52.137
    - type: ndcg_at_3
      value: 37.528
    - type: ndcg_at_5
      value: 41.81
    - type: precision_at_1
      value: 23.541999999999998
    - type: precision_at_10
      value: 7.269
    - type: precision_at_100
      value: 0.9690000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 15.979
    - type: precision_at_5
      value: 11.664
    - type: recall_at_1
      value: 23.541999999999998
    - type: recall_at_10
      value: 72.688
    - type: recall_at_100
      value: 96.871
    - type: recall_at_1000
      value: 99.431
    - type: recall_at_3
      value: 47.937000000000005
    - type: recall_at_5
      value: 58.321
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 45.546499570522094
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 41.01607489943561
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 59.616107510107774
    - type: mrr
      value: 72.75106626214661
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 84.33018094733868
    - type: cos_sim_spearman
      value: 83.60190492611737
    - type: euclidean_pearson
      value: 82.1492450218961
    - type: euclidean_spearman
      value: 82.70308926526991
    - type: manhattan_pearson
      value: 81.93959600076842
    - type: manhattan_spearman
      value: 82.73260801016369
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 84.54545454545455
    - type: f1
      value: 84.49582530928923
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 37.362725540120096
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 34.849509608178145
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.502999999999997
    - type: map_at_10
      value: 43.323
    - type: map_at_100
      value: 44.708999999999996
    - type: map_at_1000
      value: 44.838
    - type: map_at_3
      value: 38.987
    - type: map_at_5
      value: 41.516999999999996
    - type: mrr_at_1
      value: 38.769999999999996
    - type: mrr_at_10
      value: 49.13
    - type: mrr_at_100
      value: 49.697
    - type: mrr_at_1000
      value: 49.741
    - type: mrr_at_3
      value: 45.804
    - type: mrr_at_5
      value: 47.842
    - type: ndcg_at_1
      value: 38.769999999999996
    - type: ndcg_at_10
      value: 50.266999999999996
    - type: ndcg_at_100
      value: 54.967
    - type: ndcg_at_1000
      value: 56.976000000000006
    - type: ndcg_at_3
      value: 43.823
    - type: ndcg_at_5
      value: 47.12
    - type: precision_at_1
      value: 38.769999999999996
    - type: precision_at_10
      value: 10.057
    - type: precision_at_100
      value: 1.554
    - type: precision_at_1000
      value: 0.202
    - type: precision_at_3
      value: 21.125
    - type: precision_at_5
      value: 15.851
    - type: recall_at_1
      value: 31.502999999999997
    - type: recall_at_10
      value: 63.715999999999994
    - type: recall_at_100
      value: 83.61800000000001
    - type: recall_at_1000
      value: 96.63199999999999
    - type: recall_at_3
      value: 45.403
    - type: recall_at_5
      value: 54.481
    - type: map_at_1
      value: 27.833000000000002
    - type: map_at_10
      value: 37.330999999999996
    - type: map_at_100
      value: 38.580999999999996
    - type: map_at_1000
      value: 38.708
    - type: map_at_3
      value: 34.713
    - type: map_at_5
      value: 36.104
    - type: mrr_at_1
      value: 35.223
    - type: mrr_at_10
      value: 43.419000000000004
    - type: mrr_at_100
      value: 44.198
    - type: mrr_at_1000
      value: 44.249
    - type: mrr_at_3
      value: 41.614000000000004
    - type: mrr_at_5
      value: 42.553000000000004
    - type: ndcg_at_1
      value: 35.223
    - type: ndcg_at_10
      value: 42.687999999999995
    - type: ndcg_at_100
      value: 47.447
    - type: ndcg_at_1000
      value: 49.701
    - type: ndcg_at_3
      value: 39.162
    - type: ndcg_at_5
      value: 40.557
    - type: precision_at_1
      value: 35.223
    - type: precision_at_10
      value: 7.962
    - type: precision_at_100
      value: 1.304
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_3
      value: 19.023
    - type: precision_at_5
      value: 13.184999999999999
    - type: recall_at_1
      value: 27.833000000000002
    - type: recall_at_10
      value: 51.881
    - type: recall_at_100
      value: 72.04
    - type: recall_at_1000
      value: 86.644
    - type: recall_at_3
      value: 40.778
    - type: recall_at_5
      value: 45.176
    - type: map_at_1
      value: 38.175
    - type: map_at_10
      value: 51.174
    - type: map_at_100
      value: 52.26499999999999
    - type: map_at_1000
      value: 52.315999999999995
    - type: map_at_3
      value: 47.897
    - type: map_at_5
      value: 49.703
    - type: mrr_at_1
      value: 43.448
    - type: mrr_at_10
      value: 54.505
    - type: mrr_at_100
      value: 55.216
    - type: mrr_at_1000
      value: 55.242000000000004
    - type: mrr_at_3
      value: 51.98500000000001
    - type: mrr_at_5
      value: 53.434000000000005
    - type: ndcg_at_1
      value: 43.448
    - type: ndcg_at_10
      value: 57.282
    - type: ndcg_at_100
      value: 61.537
    - type: ndcg_at_1000
      value: 62.546
    - type: ndcg_at_3
      value: 51.73799999999999
    - type: ndcg_at_5
      value: 54.324
    - type: precision_at_1
      value: 43.448
    - type: precision_at_10
      value: 9.292
    - type: precision_at_100
      value: 1.233
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 23.218
    - type: precision_at_5
      value: 15.887
    - type: recall_at_1
      value: 38.175
    - type: recall_at_10
      value: 72.00999999999999
    - type: recall_at_100
      value: 90.155
    - type: recall_at_1000
      value: 97.257
    - type: recall_at_3
      value: 57.133
    - type: recall_at_5
      value: 63.424
    - type: map_at_1
      value: 22.405
    - type: map_at_10
      value: 30.043
    - type: map_at_100
      value: 31.191000000000003
    - type: map_at_1000
      value: 31.275
    - type: map_at_3
      value: 27.034000000000002
    - type: map_at_5
      value: 28.688000000000002
    - type: mrr_at_1
      value: 24.068
    - type: mrr_at_10
      value: 31.993
    - type: mrr_at_100
      value: 32.992
    - type: mrr_at_1000
      value: 33.050000000000004
    - type: mrr_at_3
      value: 28.964000000000002
    - type: mrr_at_5
      value: 30.653000000000002
    - type: ndcg_at_1
      value: 24.068
    - type: ndcg_at_10
      value: 35.198
    - type: ndcg_at_100
      value: 40.709
    - type: ndcg_at_1000
      value: 42.855
    - type: ndcg_at_3
      value: 29.139
    - type: ndcg_at_5
      value: 32.045
    - type: precision_at_1
      value: 24.068
    - type: precision_at_10
      value: 5.65
    - type: precision_at_100
      value: 0.885
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 12.279
    - type: precision_at_5
      value: 8.994
    - type: recall_at_1
      value: 22.405
    - type: recall_at_10
      value: 49.391
    - type: recall_at_100
      value: 74.53699999999999
    - type: recall_at_1000
      value: 90.605
    - type: recall_at_3
      value: 33.126
    - type: recall_at_5
      value: 40.073
    - type: map_at_1
      value: 13.309999999999999
    - type: map_at_10
      value: 20.688000000000002
    - type: map_at_100
      value: 22.022
    - type: map_at_1000
      value: 22.152
    - type: map_at_3
      value: 17.954
    - type: map_at_5
      value: 19.439
    - type: mrr_at_1
      value: 16.294
    - type: mrr_at_10
      value: 24.479
    - type: mrr_at_100
      value: 25.515
    - type: mrr_at_1000
      value: 25.593
    - type: mrr_at_3
      value: 21.642
    - type: mrr_at_5
      value: 23.189999999999998
    - type: ndcg_at_1
      value: 16.294
    - type: ndcg_at_10
      value: 25.833000000000002
    - type: ndcg_at_100
      value: 32.074999999999996
    - type: ndcg_at_1000
      value: 35.083
    - type: ndcg_at_3
      value: 20.493
    - type: ndcg_at_5
      value: 22.949
    - type: precision_at_1
      value: 16.294
    - type: precision_at_10
      value: 5.112
    - type: precision_at_100
      value: 0.96
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 9.908999999999999
    - type: precision_at_5
      value: 7.587000000000001
    - type: recall_at_1
      value: 13.309999999999999
    - type: recall_at_10
      value: 37.851
    - type: recall_at_100
      value: 64.835
    - type: recall_at_1000
      value: 86.334
    - type: recall_at_3
      value: 23.493
    - type: recall_at_5
      value: 29.528
    - type: map_at_1
      value: 25.857999999999997
    - type: map_at_10
      value: 35.503
    - type: map_at_100
      value: 36.957
    - type: map_at_1000
      value: 37.065
    - type: map_at_3
      value: 32.275999999999996
    - type: map_at_5
      value: 34.119
    - type: mrr_at_1
      value: 31.954
    - type: mrr_at_10
      value: 40.851
    - type: mrr_at_100
      value: 41.863
    - type: mrr_at_1000
      value: 41.900999999999996
    - type: mrr_at_3
      value: 38.129999999999995
    - type: mrr_at_5
      value: 39.737
    - type: ndcg_at_1
      value: 31.954
    - type: ndcg_at_10
      value: 41.343999999999994
    - type: ndcg_at_100
      value: 47.397
    - type: ndcg_at_1000
      value: 49.501
    - type: ndcg_at_3
      value: 36.047000000000004
    - type: ndcg_at_5
      value: 38.639
    - type: precision_at_1
      value: 31.954
    - type: precision_at_10
      value: 7.68
    - type: precision_at_100
      value: 1.247
    - type: precision_at_1000
      value: 0.16199999999999998
    - type: precision_at_3
      value: 17.132
    - type: precision_at_5
      value: 12.589
    - type: recall_at_1
      value: 25.857999999999997
    - type: recall_at_10
      value: 53.43599999999999
    - type: recall_at_100
      value: 78.82400000000001
    - type: recall_at_1000
      value: 92.78999999999999
    - type: recall_at_3
      value: 38.655
    - type: recall_at_5
      value: 45.216
    - type: map_at_1
      value: 24.709
    - type: map_at_10
      value: 34.318
    - type: map_at_100
      value: 35.657
    - type: map_at_1000
      value: 35.783
    - type: map_at_3
      value: 31.326999999999998
    - type: map_at_5
      value: 33.021
    - type: mrr_at_1
      value: 30.137000000000004
    - type: mrr_at_10
      value: 39.093
    - type: mrr_at_100
      value: 39.992
    - type: mrr_at_1000
      value: 40.056999999999995
    - type: mrr_at_3
      value: 36.606
    - type: mrr_at_5
      value: 37.861
    - type: ndcg_at_1
      value: 30.137000000000004
    - type: ndcg_at_10
      value: 39.974
    - type: ndcg_at_100
      value: 45.647999999999996
    - type: ndcg_at_1000
      value: 48.259
    - type: ndcg_at_3
      value: 35.028
    - type: ndcg_at_5
      value: 37.175999999999995
    - type: precision_at_1
      value: 30.137000000000004
    - type: precision_at_10
      value: 7.363
    - type: precision_at_100
      value: 1.184
    - type: precision_at_1000
      value: 0.161
    - type: precision_at_3
      value: 16.857
    - type: precision_at_5
      value: 11.963
    - type: recall_at_1
      value: 24.709
    - type: recall_at_10
      value: 52.087
    - type: recall_at_100
      value: 76.125
    - type: recall_at_1000
      value: 93.82300000000001
    - type: recall_at_3
      value: 38.149
    - type: recall_at_5
      value: 43.984
    - type: map_at_1
      value: 23.40791666666667
    - type: map_at_10
      value: 32.458083333333335
    - type: map_at_100
      value: 33.691916666666664
    - type: map_at_1000
      value: 33.81191666666666
    - type: map_at_3
      value: 29.51625
    - type: map_at_5
      value: 31.168083333333335
    - type: mrr_at_1
      value: 27.96591666666666
    - type: mrr_at_10
      value: 36.528583333333344
    - type: mrr_at_100
      value: 37.404
    - type: mrr_at_1000
      value: 37.464333333333336
    - type: mrr_at_3
      value: 33.92883333333333
    - type: mrr_at_5
      value: 35.41933333333333
    - type: ndcg_at_1
      value: 27.96591666666666
    - type: ndcg_at_10
      value: 37.89141666666666
    - type: ndcg_at_100
      value: 43.23066666666666
    - type: ndcg_at_1000
      value: 45.63258333333333
    - type: ndcg_at_3
      value: 32.811249999999994
    - type: ndcg_at_5
      value: 35.22566666666667
    - type: precision_at_1
      value: 27.96591666666666
    - type: precision_at_10
      value: 6.834083333333332
    - type: precision_at_100
      value: 1.12225
    - type: precision_at_1000
      value: 0.15241666666666667
    - type: precision_at_3
      value: 15.264333333333335
    - type: precision_at_5
      value: 11.039416666666666
    - type: recall_at_1
      value: 23.40791666666667
    - type: recall_at_10
      value: 49.927083333333336
    - type: recall_at_100
      value: 73.44641666666668
    - type: recall_at_1000
      value: 90.19950000000001
    - type: recall_at_3
      value: 35.88341666666667
    - type: recall_at_5
      value: 42.061249999999994
    - type: map_at_1
      value: 19.592000000000002
    - type: map_at_10
      value: 26.895999999999997
    - type: map_at_100
      value: 27.921000000000003
    - type: map_at_1000
      value: 28.02
    - type: map_at_3
      value: 24.883
    - type: map_at_5
      value: 25.812
    - type: mrr_at_1
      value: 22.698999999999998
    - type: mrr_at_10
      value: 29.520999999999997
    - type: mrr_at_100
      value: 30.458000000000002
    - type: mrr_at_1000
      value: 30.526999999999997
    - type: mrr_at_3
      value: 27.633000000000003
    - type: mrr_at_5
      value: 28.483999999999998
    - type: ndcg_at_1
      value: 22.698999999999998
    - type: ndcg_at_10
      value: 31.061
    - type: ndcg_at_100
      value: 36.398
    - type: ndcg_at_1000
      value: 38.89
    - type: ndcg_at_3
      value: 27.149
    - type: ndcg_at_5
      value: 28.627000000000002
    - type: precision_at_1
      value: 22.698999999999998
    - type: precision_at_10
      value: 5.106999999999999
    - type: precision_at_100
      value: 0.857
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 11.963
    - type: precision_at_5
      value: 8.221
    - type: recall_at_1
      value: 19.592000000000002
    - type: recall_at_10
      value: 41.329
    - type: recall_at_100
      value: 66.094
    - type: recall_at_1000
      value: 84.511
    - type: recall_at_3
      value: 30.61
    - type: recall_at_5
      value: 34.213
    - type: map_at_1
      value: 14.71
    - type: map_at_10
      value: 20.965
    - type: map_at_100
      value: 21.994
    - type: map_at_1000
      value: 22.133
    - type: map_at_3
      value: 18.741
    - type: map_at_5
      value: 19.951
    - type: mrr_at_1
      value: 18.307000000000002
    - type: mrr_at_10
      value: 24.66
    - type: mrr_at_100
      value: 25.540000000000003
    - type: mrr_at_1000
      value: 25.629
    - type: mrr_at_3
      value: 22.511
    - type: mrr_at_5
      value: 23.72
    - type: ndcg_at_1
      value: 18.307000000000002
    - type: ndcg_at_10
      value: 25.153
    - type: ndcg_at_100
      value: 30.229
    - type: ndcg_at_1000
      value: 33.623
    - type: ndcg_at_3
      value: 21.203
    - type: ndcg_at_5
      value: 23.006999999999998
    - type: precision_at_1
      value: 18.307000000000002
    - type: precision_at_10
      value: 4.725
    - type: precision_at_100
      value: 0.8659999999999999
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 10.14
    - type: precision_at_5
      value: 7.481
    - type: recall_at_1
      value: 14.71
    - type: recall_at_10
      value: 34.087
    - type: recall_at_100
      value: 57.147999999999996
    - type: recall_at_1000
      value: 81.777
    - type: recall_at_3
      value: 22.996
    - type: recall_at_5
      value: 27.73
    - type: map_at_1
      value: 23.472
    - type: map_at_10
      value: 32.699
    - type: map_at_100
      value: 33.867000000000004
    - type: map_at_1000
      value: 33.967000000000006
    - type: map_at_3
      value: 29.718
    - type: map_at_5
      value: 31.345
    - type: mrr_at_1
      value: 28.265
    - type: mrr_at_10
      value: 36.945
    - type: mrr_at_100
      value: 37.794
    - type: mrr_at_1000
      value: 37.857
    - type: mrr_at_3
      value: 34.266000000000005
    - type: mrr_at_5
      value: 35.768
    - type: ndcg_at_1
      value: 28.265
    - type: ndcg_at_10
      value: 38.35
    - type: ndcg_at_100
      value: 43.739
    - type: ndcg_at_1000
      value: 46.087
    - type: ndcg_at_3
      value: 33.004
    - type: ndcg_at_5
      value: 35.411
    - type: precision_at_1
      value: 28.265
    - type: precision_at_10
      value: 6.715999999999999
    - type: precision_at_100
      value: 1.059
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 15.299
    - type: precision_at_5
      value: 10.951
    - type: recall_at_1
      value: 23.472
    - type: recall_at_10
      value: 51.413
    - type: recall_at_100
      value: 75.17
    - type: recall_at_1000
      value: 91.577
    - type: recall_at_3
      value: 36.651
    - type: recall_at_5
      value: 42.814
    - type: map_at_1
      value: 23.666
    - type: map_at_10
      value: 32.963
    - type: map_at_100
      value: 34.544999999999995
    - type: map_at_1000
      value: 34.792
    - type: map_at_3
      value: 29.74
    - type: map_at_5
      value: 31.5
    - type: mrr_at_1
      value: 29.051
    - type: mrr_at_10
      value: 38.013000000000005
    - type: mrr_at_100
      value: 38.997
    - type: mrr_at_1000
      value: 39.055
    - type: mrr_at_3
      value: 34.947
    - type: mrr_at_5
      value: 36.815
    - type: ndcg_at_1
      value: 29.051
    - type: ndcg_at_10
      value: 39.361000000000004
    - type: ndcg_at_100
      value: 45.186
    - type: ndcg_at_1000
      value: 47.867
    - type: ndcg_at_3
      value: 33.797
    - type: ndcg_at_5
      value: 36.456
    - type: precision_at_1
      value: 29.051
    - type: precision_at_10
      value: 7.668
    - type: precision_at_100
      value: 1.532
    - type: precision_at_1000
      value: 0.247
    - type: precision_at_3
      value: 15.876000000000001
    - type: precision_at_5
      value: 11.779
    - type: recall_at_1
      value: 23.666
    - type: recall_at_10
      value: 51.858000000000004
    - type: recall_at_100
      value: 77.805
    - type: recall_at_1000
      value: 94.504
    - type: recall_at_3
      value: 36.207
    - type: recall_at_5
      value: 43.094
    - type: map_at_1
      value: 15.662
    - type: map_at_10
      value: 23.594
    - type: map_at_100
      value: 24.593999999999998
    - type: map_at_1000
      value: 24.694
    - type: map_at_3
      value: 20.925
    - type: map_at_5
      value: 22.817999999999998
    - type: mrr_at_1
      value: 17.375
    - type: mrr_at_10
      value: 25.734
    - type: mrr_at_100
      value: 26.586
    - type: mrr_at_1000
      value: 26.671
    - type: mrr_at_3
      value: 23.044
    - type: mrr_at_5
      value: 24.975
    - type: ndcg_at_1
      value: 17.375
    - type: ndcg_at_10
      value: 28.186
    - type: ndcg_at_100
      value: 33.436
    - type: ndcg_at_1000
      value: 36.203
    - type: ndcg_at_3
      value: 23.152
    - type: ndcg_at_5
      value: 26.397
    - type: precision_at_1
      value: 17.375
    - type: precision_at_10
      value: 4.677
    - type: precision_at_100
      value: 0.786
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 10.351
    - type: precision_at_5
      value: 7.985
    - type: recall_at_1
      value: 15.662
    - type: recall_at_10
      value: 40.066
    - type: recall_at_100
      value: 65.006
    - type: recall_at_1000
      value: 85.94000000000001
    - type: recall_at_3
      value: 27.400000000000002
    - type: recall_at_5
      value: 35.002
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.853
    - type: map_at_10
      value: 15.568000000000001
    - type: map_at_100
      value: 17.383000000000003
    - type: map_at_1000
      value: 17.584
    - type: map_at_3
      value: 12.561
    - type: map_at_5
      value: 14.056
    - type: mrr_at_1
      value: 18.958
    - type: mrr_at_10
      value: 28.288000000000004
    - type: mrr_at_100
      value: 29.432000000000002
    - type: mrr_at_1000
      value: 29.498
    - type: mrr_at_3
      value: 25.049
    - type: mrr_at_5
      value: 26.857
    - type: ndcg_at_1
      value: 18.958
    - type: ndcg_at_10
      value: 22.21
    - type: ndcg_at_100
      value: 29.596
    - type: ndcg_at_1000
      value: 33.583
    - type: ndcg_at_3
      value: 16.994999999999997
    - type: ndcg_at_5
      value: 18.95
    - type: precision_at_1
      value: 18.958
    - type: precision_at_10
      value: 7.192
    - type: precision_at_100
      value: 1.5
    - type: precision_at_1000
      value: 0.22399999999999998
    - type: precision_at_3
      value: 12.573
    - type: precision_at_5
      value: 10.202
    - type: recall_at_1
      value: 8.853
    - type: recall_at_10
      value: 28.087
    - type: recall_at_100
      value: 53.701
    - type: recall_at_1000
      value: 76.29899999999999
    - type: recall_at_3
      value: 15.913
    - type: recall_at_5
      value: 20.658
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.077
    - type: map_at_10
      value: 20.788999999999998
    - type: map_at_100
      value: 30.429000000000002
    - type: map_at_1000
      value: 32.143
    - type: map_at_3
      value: 14.692
    - type: map_at_5
      value: 17.139
    - type: mrr_at_1
      value: 70.75
    - type: mrr_at_10
      value: 78.036
    - type: mrr_at_100
      value: 78.401
    - type: mrr_at_1000
      value: 78.404
    - type: mrr_at_3
      value: 76.75
    - type: mrr_at_5
      value: 77.47500000000001
    - type: ndcg_at_1
      value: 58.12500000000001
    - type: ndcg_at_10
      value: 44.015
    - type: ndcg_at_100
      value: 49.247
    - type: ndcg_at_1000
      value: 56.211999999999996
    - type: ndcg_at_3
      value: 49.151
    - type: ndcg_at_5
      value: 46.195
    - type: precision_at_1
      value: 70.75
    - type: precision_at_10
      value: 35.5
    - type: precision_at_100
      value: 11.355
    - type: precision_at_1000
      value: 2.1950000000000003
    - type: precision_at_3
      value: 53.083000000000006
    - type: precision_at_5
      value: 44.800000000000004
    - type: recall_at_1
      value: 9.077
    - type: recall_at_10
      value: 26.259
    - type: recall_at_100
      value: 56.547000000000004
    - type: recall_at_1000
      value: 78.551
    - type: recall_at_3
      value: 16.162000000000003
    - type: recall_at_5
      value: 19.753999999999998
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 49.44500000000001
    - type: f1
      value: 44.67067691783401
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 68.182
    - type: map_at_10
      value: 78.223
    - type: map_at_100
      value: 78.498
    - type: map_at_1000
      value: 78.512
    - type: map_at_3
      value: 76.71
    - type: map_at_5
      value: 77.725
    - type: mrr_at_1
      value: 73.177
    - type: mrr_at_10
      value: 82.513
    - type: mrr_at_100
      value: 82.633
    - type: mrr_at_1000
      value: 82.635
    - type: mrr_at_3
      value: 81.376
    - type: mrr_at_5
      value: 82.182
    - type: ndcg_at_1
      value: 73.177
    - type: ndcg_at_10
      value: 82.829
    - type: ndcg_at_100
      value: 83.84
    - type: ndcg_at_1000
      value: 84.07900000000001
    - type: ndcg_at_3
      value: 80.303
    - type: ndcg_at_5
      value: 81.846
    - type: precision_at_1
      value: 73.177
    - type: precision_at_10
      value: 10.241999999999999
    - type: precision_at_100
      value: 1.099
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 31.247999999999998
    - type: precision_at_5
      value: 19.697
    - type: recall_at_1
      value: 68.182
    - type: recall_at_10
      value: 92.657
    - type: recall_at_100
      value: 96.709
    - type: recall_at_1000
      value: 98.184
    - type: recall_at_3
      value: 85.9
    - type: recall_at_5
      value: 89.755
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 21.108
    - type: map_at_10
      value: 33.342
    - type: map_at_100
      value: 35.281
    - type: map_at_1000
      value: 35.478
    - type: map_at_3
      value: 29.067
    - type: map_at_5
      value: 31.563000000000002
    - type: mrr_at_1
      value: 41.667
    - type: mrr_at_10
      value: 49.913000000000004
    - type: mrr_at_100
      value: 50.724000000000004
    - type: mrr_at_1000
      value: 50.766
    - type: mrr_at_3
      value: 47.504999999999995
    - type: mrr_at_5
      value: 49.033
    - type: ndcg_at_1
      value: 41.667
    - type: ndcg_at_10
      value: 41.144
    - type: ndcg_at_100
      value: 48.326
    - type: ndcg_at_1000
      value: 51.486
    - type: ndcg_at_3
      value: 37.486999999999995
    - type: ndcg_at_5
      value: 38.78
    - type: precision_at_1
      value: 41.667
    - type: precision_at_10
      value: 11.358
    - type: precision_at_100
      value: 1.873
    - type: precision_at_1000
      value: 0.244
    - type: precision_at_3
      value: 25
    - type: precision_at_5
      value: 18.519
    - type: recall_at_1
      value: 21.108
    - type: recall_at_10
      value: 47.249
    - type: recall_at_100
      value: 74.52
    - type: recall_at_1000
      value: 93.31
    - type: recall_at_3
      value: 33.271
    - type: recall_at_5
      value: 39.723000000000006
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.317
    - type: map_at_10
      value: 64.861
    - type: map_at_100
      value: 65.697
    - type: map_at_1000
      value: 65.755
    - type: map_at_3
      value: 61.258
    - type: map_at_5
      value: 63.590999999999994
    - type: mrr_at_1
      value: 80.635
    - type: mrr_at_10
      value: 86.528
    - type: mrr_at_100
      value: 86.66199999999999
    - type: mrr_at_1000
      value: 86.666
    - type: mrr_at_3
      value: 85.744
    - type: mrr_at_5
      value: 86.24300000000001
    - type: ndcg_at_1
      value: 80.635
    - type: ndcg_at_10
      value: 73.13199999999999
    - type: ndcg_at_100
      value: 75.927
    - type: ndcg_at_1000
      value: 76.976
    - type: ndcg_at_3
      value: 68.241
    - type: ndcg_at_5
      value: 71.071
    - type: precision_at_1
      value: 80.635
    - type: precision_at_10
      value: 15.326
    - type: precision_at_100
      value: 1.7500000000000002
    - type: precision_at_1000
      value: 0.189
    - type: precision_at_3
      value: 43.961
    - type: precision_at_5
      value: 28.599999999999998
    - type: recall_at_1
      value: 40.317
    - type: recall_at_10
      value: 76.631
    - type: recall_at_100
      value: 87.495
    - type: recall_at_1000
      value: 94.362
    - type: recall_at_3
      value: 65.94200000000001
    - type: recall_at_5
      value: 71.499
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 91.686
    - type: ap
      value: 87.5577120393173
    - type: f1
      value: 91.6629447355139
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 23.702
    - type: map_at_10
      value: 36.414
    - type: map_at_100
      value: 37.561
    - type: map_at_1000
      value: 37.605
    - type: map_at_3
      value: 32.456
    - type: map_at_5
      value: 34.827000000000005
    - type: mrr_at_1
      value: 24.355
    - type: mrr_at_10
      value: 37.01
    - type: mrr_at_100
      value: 38.085
    - type: mrr_at_1000
      value: 38.123000000000005
    - type: mrr_at_3
      value: 33.117999999999995
    - type: mrr_at_5
      value: 35.452
    - type: ndcg_at_1
      value: 24.384
    - type: ndcg_at_10
      value: 43.456
    - type: ndcg_at_100
      value: 48.892
    - type: ndcg_at_1000
      value: 49.964
    - type: ndcg_at_3
      value: 35.475
    - type: ndcg_at_5
      value: 39.711
    - type: precision_at_1
      value: 24.384
    - type: precision_at_10
      value: 6.7940000000000005
    - type: precision_at_100
      value: 0.951
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 15.052999999999999
    - type: precision_at_5
      value: 11.189
    - type: recall_at_1
      value: 23.702
    - type: recall_at_10
      value: 65.057
    - type: recall_at_100
      value: 90.021
    - type: recall_at_1000
      value: 98.142
    - type: recall_at_3
      value: 43.551
    - type: recall_at_5
      value: 53.738
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 94.62380300957591
    - type: f1
      value: 94.49871222100734
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 77.14090287277702
    - type: f1
      value: 60.32101258220515
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 73.84330867518494
    - type: f1
      value: 71.92248688515255
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 78.10692669804976
    - type: f1
      value: 77.9904839122866
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.822988923078444
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 30.38394880253403
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.82504612539082
    - type: mrr
      value: 32.84462298174977
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.029
    - type: map_at_10
      value: 14.088999999999999
    - type: map_at_100
      value: 17.601
    - type: map_at_1000
      value: 19.144
    - type: map_at_3
      value: 10.156
    - type: map_at_5
      value: 11.892
    - type: mrr_at_1
      value: 46.44
    - type: mrr_at_10
      value: 56.596999999999994
    - type: mrr_at_100
      value: 57.11000000000001
    - type: mrr_at_1000
      value: 57.14
    - type: mrr_at_3
      value: 54.334
    - type: mrr_at_5
      value: 55.774
    - type: ndcg_at_1
      value: 44.891999999999996
    - type: ndcg_at_10
      value: 37.134
    - type: ndcg_at_100
      value: 33.652
    - type: ndcg_at_1000
      value: 42.548
    - type: ndcg_at_3
      value: 41.851
    - type: ndcg_at_5
      value: 39.842
    - type: precision_at_1
      value: 46.44
    - type: precision_at_10
      value: 27.647
    - type: precision_at_100
      value: 8.309999999999999
    - type: precision_at_1000
      value: 2.146
    - type: precision_at_3
      value: 39.422000000000004
    - type: precision_at_5
      value: 34.675
    - type: recall_at_1
      value: 6.029
    - type: recall_at_10
      value: 18.907
    - type: recall_at_100
      value: 33.76
    - type: recall_at_1000
      value: 65.14999999999999
    - type: recall_at_3
      value: 11.584999999999999
    - type: recall_at_5
      value: 14.626
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 39.373000000000005
    - type: map_at_10
      value: 55.836
    - type: map_at_100
      value: 56.611999999999995
    - type: map_at_1000
      value: 56.63
    - type: map_at_3
      value: 51.747
    - type: map_at_5
      value: 54.337999999999994
    - type: mrr_at_1
      value: 44.147999999999996
    - type: mrr_at_10
      value: 58.42699999999999
    - type: mrr_at_100
      value: 58.902
    - type: mrr_at_1000
      value: 58.914
    - type: mrr_at_3
      value: 55.156000000000006
    - type: mrr_at_5
      value: 57.291000000000004
    - type: ndcg_at_1
      value: 44.119
    - type: ndcg_at_10
      value: 63.444
    - type: ndcg_at_100
      value: 66.40599999999999
    - type: ndcg_at_1000
      value: 66.822
    - type: ndcg_at_3
      value: 55.962
    - type: ndcg_at_5
      value: 60.228
    - type: precision_at_1
      value: 44.119
    - type: precision_at_10
      value: 10.006
    - type: precision_at_100
      value: 1.17
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 25.135
    - type: precision_at_5
      value: 17.59
    - type: recall_at_1
      value: 39.373000000000005
    - type: recall_at_10
      value: 83.78999999999999
    - type: recall_at_100
      value: 96.246
    - type: recall_at_1000
      value: 99.324
    - type: recall_at_3
      value: 64.71900000000001
    - type: recall_at_5
      value: 74.508
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 69.199
    - type: map_at_10
      value: 82.892
    - type: map_at_100
      value: 83.578
    - type: map_at_1000
      value: 83.598
    - type: map_at_3
      value: 79.948
    - type: map_at_5
      value: 81.779
    - type: mrr_at_1
      value: 79.67
    - type: mrr_at_10
      value: 86.115
    - type: mrr_at_100
      value: 86.249
    - type: mrr_at_1000
      value: 86.251
    - type: mrr_at_3
      value: 85.08200000000001
    - type: mrr_at_5
      value: 85.783
    - type: ndcg_at_1
      value: 79.67
    - type: ndcg_at_10
      value: 86.839
    - type: ndcg_at_100
      value: 88.252
    - type: ndcg_at_1000
      value: 88.401
    - type: ndcg_at_3
      value: 83.86200000000001
    - type: ndcg_at_5
      value: 85.473
    - type: precision_at_1
      value: 79.67
    - type: precision_at_10
      value: 13.19
    - type: precision_at_100
      value: 1.521
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 36.677
    - type: precision_at_5
      value: 24.118000000000002
    - type: recall_at_1
      value: 69.199
    - type: recall_at_10
      value: 94.321
    - type: recall_at_100
      value: 99.20400000000001
    - type: recall_at_1000
      value: 99.947
    - type: recall_at_3
      value: 85.787
    - type: recall_at_5
      value: 90.365
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 55.82810046856353
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 63.38132611783628
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.127000000000001
    - type: map_at_10
      value: 12.235
    - type: map_at_100
      value: 14.417
    - type: map_at_1000
      value: 14.75
    - type: map_at_3
      value: 8.906
    - type: map_at_5
      value: 10.591000000000001
    - type: mrr_at_1
      value: 25.2
    - type: mrr_at_10
      value: 35.879
    - type: mrr_at_100
      value: 36.935
    - type: mrr_at_1000
      value: 36.997
    - type: mrr_at_3
      value: 32.783
    - type: mrr_at_5
      value: 34.367999999999995
    - type: ndcg_at_1
      value: 25.2
    - type: ndcg_at_10
      value: 20.509
    - type: ndcg_at_100
      value: 28.67
    - type: ndcg_at_1000
      value: 34.42
    - type: ndcg_at_3
      value: 19.948
    - type: ndcg_at_5
      value: 17.166
    - type: precision_at_1
      value: 25.2
    - type: precision_at_10
      value: 10.440000000000001
    - type: precision_at_100
      value: 2.214
    - type: precision_at_1000
      value: 0.359
    - type: precision_at_3
      value: 18.533
    - type: precision_at_5
      value: 14.860000000000001
    - type: recall_at_1
      value: 5.127000000000001
    - type: recall_at_10
      value: 21.147
    - type: recall_at_100
      value: 44.946999999999996
    - type: recall_at_1000
      value: 72.89
    - type: recall_at_3
      value: 11.277
    - type: recall_at_5
      value: 15.042
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 83.0373011786213
    - type: cos_sim_spearman
      value: 79.27889560856613
    - type: euclidean_pearson
      value: 80.31186315495655
    - type: euclidean_spearman
      value: 79.41630415280811
    - type: manhattan_pearson
      value: 80.31755140442013
    - type: manhattan_spearman
      value: 79.43069870027611
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 84.8659751342045
    - type: cos_sim_spearman
      value: 76.95377612997667
    - type: euclidean_pearson
      value: 81.24552945497848
    - type: euclidean_spearman
      value: 77.18236963555253
    - type: manhattan_pearson
      value: 81.26477607759037
    - type: manhattan_spearman
      value: 77.13821753062756
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 83.34597139044875
    - type: cos_sim_spearman
      value: 84.124169425592
    - type: euclidean_pearson
      value: 83.68590721511401
    - type: euclidean_spearman
      value: 84.18846190846398
    - type: manhattan_pearson
      value: 83.57630235061498
    - type: manhattan_spearman
      value: 84.10244043726902
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 82.67641885599572
    - type: cos_sim_spearman
      value: 80.46450725650428
    - type: euclidean_pearson
      value: 81.61645042715865
    - type: euclidean_spearman
      value: 80.61418394236874
    - type: manhattan_pearson
      value: 81.55712034928871
    - type: manhattan_spearman
      value: 80.57905670523951
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 88.86650310886782
    - type: cos_sim_spearman
      value: 89.76081629222328
    - type: euclidean_pearson
      value: 89.1530747029954
    - type: euclidean_spearman
      value: 89.80990657280248
    - type: manhattan_pearson
      value: 89.10640563278132
    - type: manhattan_spearman
      value: 89.76282108434047
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 83.93864027911118
    - type: cos_sim_spearman
      value: 85.47096193999023
    - type: euclidean_pearson
      value: 85.03141840870533
    - type: euclidean_spearman
      value: 85.43124029598181
    - type: manhattan_pearson
      value: 84.99002664393512
    - type: manhattan_spearman
      value: 85.39169195120834
  - 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: 88.7045343749832
    - type: cos_sim_spearman
      value: 89.03262221146677
    - type: euclidean_pearson
      value: 89.56078218264365
    - type: euclidean_spearman
      value: 89.17827006466868
    - type: manhattan_pearson
      value: 89.52717595468582
    - type: manhattan_spearman
      value: 89.15878115952923
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 64.20191302875551
    - type: cos_sim_spearman
      value: 64.11446552557646
    - type: euclidean_pearson
      value: 64.6918197393619
    - type: euclidean_spearman
      value: 63.440182631197764
    - type: manhattan_pearson
      value: 64.55692904121835
    - type: manhattan_spearman
      value: 63.424877742756266
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 86.37793104662344
    - type: cos_sim_spearman
      value: 87.7357802629067
    - type: euclidean_pearson
      value: 87.4286301545109
    - type: euclidean_spearman
      value: 87.78452920777421
    - type: manhattan_pearson
      value: 87.42445169331255
    - type: manhattan_spearman
      value: 87.78537677249598
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 84.31465405081792
    - type: mrr
      value: 95.7173781193389
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 57.760999999999996
    - type: map_at_10
      value: 67.904
    - type: map_at_100
      value: 68.539
    - type: map_at_1000
      value: 68.562
    - type: map_at_3
      value: 65.415
    - type: map_at_5
      value: 66.788
    - type: mrr_at_1
      value: 60.333000000000006
    - type: mrr_at_10
      value: 68.797
    - type: mrr_at_100
      value: 69.236
    - type: mrr_at_1000
      value: 69.257
    - type: mrr_at_3
      value: 66.667
    - type: mrr_at_5
      value: 67.967
    - type: ndcg_at_1
      value: 60.333000000000006
    - type: ndcg_at_10
      value: 72.24199999999999
    - type: ndcg_at_100
      value: 74.86
    - type: ndcg_at_1000
      value: 75.354
    - type: ndcg_at_3
      value: 67.93400000000001
    - type: ndcg_at_5
      value: 70.02199999999999
    - type: precision_at_1
      value: 60.333000000000006
    - type: precision_at_10
      value: 9.533
    - type: precision_at_100
      value: 1.09
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 26.778000000000002
    - type: precision_at_5
      value: 17.467
    - type: recall_at_1
      value: 57.760999999999996
    - type: recall_at_10
      value: 84.383
    - type: recall_at_100
      value: 96.267
    - type: recall_at_1000
      value: 100
    - type: recall_at_3
      value: 72.628
    - type: recall_at_5
      value: 78.094
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.8029702970297
    - type: cos_sim_ap
      value: 94.9210324173411
    - type: cos_sim_f1
      value: 89.8521162672106
    - type: cos_sim_precision
      value: 91.67533818938605
    - type: cos_sim_recall
      value: 88.1
    - type: dot_accuracy
      value: 99.69504950495049
    - type: dot_ap
      value: 90.4919719146181
    - type: dot_f1
      value: 84.72289156626506
    - type: dot_precision
      value: 81.76744186046511
    - type: dot_recall
      value: 87.9
    - type: euclidean_accuracy
      value: 99.79702970297029
    - type: euclidean_ap
      value: 94.87827463795753
    - type: euclidean_f1
      value: 89.55680081507896
    - type: euclidean_precision
      value: 91.27725856697819
    - type: euclidean_recall
      value: 87.9
    - type: manhattan_accuracy
      value: 99.7990099009901
    - type: manhattan_ap
      value: 94.87587025149682
    - type: manhattan_f1
      value: 89.76298537569339
    - type: manhattan_precision
      value: 90.53916581892166
    - type: manhattan_recall
      value: 89
    - type: max_accuracy
      value: 99.8029702970297
    - type: max_ap
      value: 94.9210324173411
    - type: max_f1
      value: 89.8521162672106
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 65.92385753948724
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 33.671756975431144
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 50.677928036739004
    - type: mrr
      value: 51.56413133435193
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.523589340819683
    - type: cos_sim_spearman
      value: 30.187407518823235
    - type: dot_pearson
      value: 29.039713969699015
    - type: dot_spearman
      value: 29.114740651155508
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.211
    - type: map_at_10
      value: 1.6199999999999999
    - type: map_at_100
      value: 8.658000000000001
    - type: map_at_1000
      value: 21.538
    - type: map_at_3
      value: 0.575
    - type: map_at_5
      value: 0.919
    - type: mrr_at_1
      value: 78
    - type: mrr_at_10
      value: 86.18599999999999
    - type: mrr_at_100
      value: 86.18599999999999
    - type: mrr_at_1000
      value: 86.18599999999999
    - type: mrr_at_3
      value: 85
    - type: mrr_at_5
      value: 85.9
    - type: ndcg_at_1
      value: 74
    - type: ndcg_at_10
      value: 66.542
    - type: ndcg_at_100
      value: 50.163999999999994
    - type: ndcg_at_1000
      value: 45.696999999999996
    - type: ndcg_at_3
      value: 71.531
    - type: ndcg_at_5
      value: 70.45
    - type: precision_at_1
      value: 78
    - type: precision_at_10
      value: 69.39999999999999
    - type: precision_at_100
      value: 51.06
    - type: precision_at_1000
      value: 20.022000000000002
    - type: precision_at_3
      value: 76
    - type: precision_at_5
      value: 74.8
    - type: recall_at_1
      value: 0.211
    - type: recall_at_10
      value: 1.813
    - type: recall_at_100
      value: 12.098
    - type: recall_at_1000
      value: 42.618
    - type: recall_at_3
      value: 0.603
    - type: recall_at_5
      value: 0.987
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.2079999999999997
    - type: map_at_10
      value: 7.777000000000001
    - type: map_at_100
      value: 12.825000000000001
    - type: map_at_1000
      value: 14.196
    - type: map_at_3
      value: 4.285
    - type: map_at_5
      value: 6.177
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 42.635
    - type: mrr_at_100
      value: 43.955
    - type: mrr_at_1000
      value: 43.955
    - type: mrr_at_3
      value: 38.435
    - type: mrr_at_5
      value: 41.088
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 20.666999999999998
    - type: ndcg_at_100
      value: 31.840000000000003
    - type: ndcg_at_1000
      value: 43.191
    - type: ndcg_at_3
      value: 23.45
    - type: ndcg_at_5
      value: 22.994
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 17.959
    - type: precision_at_100
      value: 6.755
    - type: precision_at_1000
      value: 1.4200000000000002
    - type: precision_at_3
      value: 23.810000000000002
    - type: precision_at_5
      value: 23.673
    - type: recall_at_1
      value: 2.2079999999999997
    - type: recall_at_10
      value: 13.144
    - type: recall_at_100
      value: 42.491
    - type: recall_at_1000
      value: 77.04299999999999
    - type: recall_at_3
      value: 5.3469999999999995
    - type: recall_at_5
      value: 9.139
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.9044
    - type: ap
      value: 14.625783489340755
    - type: f1
      value: 54.814936562590546
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 60.94227504244483
    - type: f1
      value: 61.22516038508854
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 49.602409155145864
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 86.94641473445789
    - type: cos_sim_ap
      value: 76.91572747061197
    - type: cos_sim_f1
      value: 70.14348097317529
    - type: cos_sim_precision
      value: 66.53254437869822
    - type: cos_sim_recall
      value: 74.1688654353562
    - type: dot_accuracy
      value: 84.80061989628658
    - type: dot_ap
      value: 70.7952548895177
    - type: dot_f1
      value: 65.44780728844965
    - type: dot_precision
      value: 61.53310104529617
    - type: dot_recall
      value: 69.89445910290237
    - type: euclidean_accuracy
      value: 86.94641473445789
    - type: euclidean_ap
      value: 76.80774009393652
    - type: euclidean_f1
      value: 70.30522503879979
    - type: euclidean_precision
      value: 68.94977168949772
    - type: euclidean_recall
      value: 71.71503957783642
    - type: manhattan_accuracy
      value: 86.8629671574179
    - type: manhattan_ap
      value: 76.76518632600317
    - type: manhattan_f1
      value: 70.16056518946692
    - type: manhattan_precision
      value: 68.360450563204
    - type: manhattan_recall
      value: 72.0580474934037
    - type: max_accuracy
      value: 86.94641473445789
    - type: max_ap
      value: 76.91572747061197
    - type: max_f1
      value: 70.30522503879979
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.10428066907285
    - type: cos_sim_ap
      value: 86.25114759921435
    - type: cos_sim_f1
      value: 78.37857884586856
    - type: cos_sim_precision
      value: 75.60818546078993
    - type: cos_sim_recall
      value: 81.35971666153372
    - type: dot_accuracy
      value: 87.41995575736406
    - type: dot_ap
      value: 81.51838010086782
    - type: dot_f1
      value: 74.77398015435503
    - type: dot_precision
      value: 71.53002390662354
    - type: dot_recall
      value: 78.32614721281182
    - type: euclidean_accuracy
      value: 89.12368533395428
    - type: euclidean_ap
      value: 86.33456799874504
    - type: euclidean_f1
      value: 78.45496750232127
    - type: euclidean_precision
      value: 75.78388462366364
    - type: euclidean_recall
      value: 81.32121958731136
    - type: manhattan_accuracy
      value: 89.10622113556099
    - type: manhattan_ap
      value: 86.31215061745333
    - type: manhattan_f1
      value: 78.40684906011539
    - type: manhattan_precision
      value: 75.89536643366722
    - type: manhattan_recall
      value: 81.09023714197721
    - type: max_accuracy
      value: 89.12368533395428
    - type: max_ap
      value: 86.33456799874504
    - type: max_f1
      value: 78.45496750232127
---

# Pekarnick/e5-large-v2-Q4_K_M-GGUF
This model was converted to GGUF format from [`intfloat/e5-large-v2`](https://huggingface.co/intfloat/e5-large-v2) 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/intfloat/e5-large-v2) 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 Pekarnick/e5-large-v2-Q4_K_M-GGUF --hf-file e5-large-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Pekarnick/e5-large-v2-Q4_K_M-GGUF --hf-file e5-large-v2-q4_k_m.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 Pekarnick/e5-large-v2-Q4_K_M-GGUF --hf-file e5-large-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Pekarnick/e5-large-v2-Q4_K_M-GGUF --hf-file e5-large-v2-q4_k_m.gguf -c 2048
```
