sentence-transformers gguf mteb Sentence Transformers sentence-similarity llama-cpp gguf-my-repo en base_model:intfloat/e5-small-v2 base_model:quantized:intfloat/e5-small-v2 license:mit model-index autotrain_compatible endpoints_compatible region:us feature-extraction
---
base_model: intfloat/e5-small-v2
language:
- en
license: mit
tags:
- mteb
- Sentence Transformers
- sentence-similarity
- sentence-transformers
- llama-cpp
- gguf-my-repo
model-index:
- name: e5-small-v2
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 77.59701492537313
    - type: ap
      value: 41.67064885731708
    - type: f1
      value: 71.86465946398573
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 91.265875
    - type: ap
      value: 87.67633085349644
    - type: f1
      value: 91.24297521425744
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 45.882000000000005
    - type: f1
      value: 45.08058870381236
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 20.697
    - type: map_at_10
      value: 33.975
    - type: map_at_100
      value: 35.223
    - type: map_at_1000
      value: 35.260000000000005
    - type: map_at_3
      value: 29.776999999999997
    - type: map_at_5
      value: 32.035000000000004
    - type: mrr_at_1
      value: 20.982
    - type: mrr_at_10
      value: 34.094
    - type: mrr_at_100
      value: 35.343
    - type: mrr_at_1000
      value: 35.38
    - type: mrr_at_3
      value: 29.884
    - type: mrr_at_5
      value: 32.141999999999996
    - type: ndcg_at_1
      value: 20.697
    - type: ndcg_at_10
      value: 41.668
    - type: ndcg_at_100
      value: 47.397
    - type: ndcg_at_1000
      value: 48.305
    - type: ndcg_at_3
      value: 32.928000000000004
    - type: ndcg_at_5
      value: 36.998999999999995
    - type: precision_at_1
      value: 20.697
    - type: precision_at_10
      value: 6.636
    - type: precision_at_100
      value: 0.924
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.035
    - type: precision_at_5
      value: 10.398
    - type: recall_at_1
      value: 20.697
    - type: recall_at_10
      value: 66.35799999999999
    - type: recall_at_100
      value: 92.39
    - type: recall_at_1000
      value: 99.36
    - type: recall_at_3
      value: 42.105
    - type: recall_at_5
      value: 51.991
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 42.1169517447068
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 34.79553720107097
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 58.10811337308168
    - type: mrr
      value: 71.56410763751482
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.46834918248696
    - type: cos_sim_spearman
      value: 79.4289182755206
    - type: euclidean_pearson
      value: 76.26662973727008
    - type: euclidean_spearman
      value: 78.11744260952536
    - type: manhattan_pearson
      value: 76.08175262609434
    - type: manhattan_spearman
      value: 78.29395265552289
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 81.63636363636364
    - type: f1
      value: 81.55779952376953
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.88541137137571
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 30.05205685274407
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 30.293999999999997
    - type: map_at_10
      value: 39.876
    - type: map_at_100
      value: 41.315000000000005
    - type: map_at_1000
      value: 41.451
    - type: map_at_3
      value: 37.194
    - type: map_at_5
      value: 38.728
    - type: mrr_at_1
      value: 37.053000000000004
    - type: mrr_at_10
      value: 45.281
    - type: mrr_at_100
      value: 46.188
    - type: mrr_at_1000
      value: 46.245999999999995
    - type: mrr_at_3
      value: 43.228
    - type: mrr_at_5
      value: 44.366
    - type: ndcg_at_1
      value: 37.053000000000004
    - type: ndcg_at_10
      value: 45.086
    - type: ndcg_at_100
      value: 50.756
    - type: ndcg_at_1000
      value: 53.123
    - type: ndcg_at_3
      value: 41.416
    - type: ndcg_at_5
      value: 43.098
    - type: precision_at_1
      value: 37.053000000000004
    - type: precision_at_10
      value: 8.34
    - type: precision_at_100
      value: 1.346
    - type: precision_at_1000
      value: 0.186
    - type: precision_at_3
      value: 19.647000000000002
    - type: precision_at_5
      value: 13.877
    - type: recall_at_1
      value: 30.293999999999997
    - type: recall_at_10
      value: 54.309
    - type: recall_at_100
      value: 78.59
    - type: recall_at_1000
      value: 93.82300000000001
    - type: recall_at_3
      value: 43.168
    - type: recall_at_5
      value: 48.192
    - type: map_at_1
      value: 28.738000000000003
    - type: map_at_10
      value: 36.925999999999995
    - type: map_at_100
      value: 38.017
    - type: map_at_1000
      value: 38.144
    - type: map_at_3
      value: 34.446
    - type: map_at_5
      value: 35.704
    - type: mrr_at_1
      value: 35.478
    - type: mrr_at_10
      value: 42.786
    - type: mrr_at_100
      value: 43.458999999999996
    - type: mrr_at_1000
      value: 43.507
    - type: mrr_at_3
      value: 40.648
    - type: mrr_at_5
      value: 41.804
    - type: ndcg_at_1
      value: 35.478
    - type: ndcg_at_10
      value: 42.044
    - type: ndcg_at_100
      value: 46.249
    - type: ndcg_at_1000
      value: 48.44
    - type: ndcg_at_3
      value: 38.314
    - type: ndcg_at_5
      value: 39.798
    - type: precision_at_1
      value: 35.478
    - type: precision_at_10
      value: 7.764
    - type: precision_at_100
      value: 1.253
    - type: precision_at_1000
      value: 0.174
    - type: precision_at_3
      value: 18.047
    - type: precision_at_5
      value: 12.637
    - type: recall_at_1
      value: 28.738000000000003
    - type: recall_at_10
      value: 50.659
    - type: recall_at_100
      value: 68.76299999999999
    - type: recall_at_1000
      value: 82.811
    - type: recall_at_3
      value: 39.536
    - type: recall_at_5
      value: 43.763999999999996
    - type: map_at_1
      value: 38.565
    - type: map_at_10
      value: 50.168
    - type: map_at_100
      value: 51.11
    - type: map_at_1000
      value: 51.173
    - type: map_at_3
      value: 47.044000000000004
    - type: map_at_5
      value: 48.838
    - type: mrr_at_1
      value: 44.201
    - type: mrr_at_10
      value: 53.596999999999994
    - type: mrr_at_100
      value: 54.211
    - type: mrr_at_1000
      value: 54.247
    - type: mrr_at_3
      value: 51.202000000000005
    - type: mrr_at_5
      value: 52.608999999999995
    - type: ndcg_at_1
      value: 44.201
    - type: ndcg_at_10
      value: 55.694
    - type: ndcg_at_100
      value: 59.518
    - type: ndcg_at_1000
      value: 60.907
    - type: ndcg_at_3
      value: 50.395999999999994
    - type: ndcg_at_5
      value: 53.022999999999996
    - type: precision_at_1
      value: 44.201
    - type: precision_at_10
      value: 8.84
    - type: precision_at_100
      value: 1.162
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 22.153
    - type: precision_at_5
      value: 15.260000000000002
    - type: recall_at_1
      value: 38.565
    - type: recall_at_10
      value: 68.65
    - type: recall_at_100
      value: 85.37400000000001
    - type: recall_at_1000
      value: 95.37400000000001
    - type: recall_at_3
      value: 54.645999999999994
    - type: recall_at_5
      value: 60.958
    - type: map_at_1
      value: 23.945
    - type: map_at_10
      value: 30.641000000000002
    - type: map_at_100
      value: 31.599
    - type: map_at_1000
      value: 31.691000000000003
    - type: map_at_3
      value: 28.405
    - type: map_at_5
      value: 29.704000000000004
    - type: mrr_at_1
      value: 25.537
    - type: mrr_at_10
      value: 32.22
    - type: mrr_at_100
      value: 33.138
    - type: mrr_at_1000
      value: 33.214
    - type: mrr_at_3
      value: 30.151
    - type: mrr_at_5
      value: 31.298
    - type: ndcg_at_1
      value: 25.537
    - type: ndcg_at_10
      value: 34.638000000000005
    - type: ndcg_at_100
      value: 39.486
    - type: ndcg_at_1000
      value: 41.936
    - type: ndcg_at_3
      value: 30.333
    - type: ndcg_at_5
      value: 32.482
    - type: precision_at_1
      value: 25.537
    - type: precision_at_10
      value: 5.153
    - type: precision_at_100
      value: 0.7929999999999999
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 12.429
    - type: precision_at_5
      value: 8.723
    - type: recall_at_1
      value: 23.945
    - type: recall_at_10
      value: 45.412
    - type: recall_at_100
      value: 67.836
    - type: recall_at_1000
      value: 86.467
    - type: recall_at_3
      value: 34.031
    - type: recall_at_5
      value: 39.039
    - type: map_at_1
      value: 14.419
    - type: map_at_10
      value: 20.858999999999998
    - type: map_at_100
      value: 22.067999999999998
    - type: map_at_1000
      value: 22.192
    - type: map_at_3
      value: 18.673000000000002
    - type: map_at_5
      value: 19.968
    - type: mrr_at_1
      value: 17.785999999999998
    - type: mrr_at_10
      value: 24.878
    - type: mrr_at_100
      value: 26.021
    - type: mrr_at_1000
      value: 26.095000000000002
    - type: mrr_at_3
      value: 22.616
    - type: mrr_at_5
      value: 23.785
    - type: ndcg_at_1
      value: 17.785999999999998
    - type: ndcg_at_10
      value: 25.153
    - type: ndcg_at_100
      value: 31.05
    - type: ndcg_at_1000
      value: 34.052
    - type: ndcg_at_3
      value: 21.117
    - type: ndcg_at_5
      value: 23.048
    - type: precision_at_1
      value: 17.785999999999998
    - type: precision_at_10
      value: 4.590000000000001
    - type: precision_at_100
      value: 0.864
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 9.908999999999999
    - type: precision_at_5
      value: 7.313
    - type: recall_at_1
      value: 14.419
    - type: recall_at_10
      value: 34.477999999999994
    - type: recall_at_100
      value: 60.02499999999999
    - type: recall_at_1000
      value: 81.646
    - type: recall_at_3
      value: 23.515
    - type: recall_at_5
      value: 28.266999999999996
    - type: map_at_1
      value: 26.268
    - type: map_at_10
      value: 35.114000000000004
    - type: map_at_100
      value: 36.212
    - type: map_at_1000
      value: 36.333
    - type: map_at_3
      value: 32.436
    - type: map_at_5
      value: 33.992
    - type: mrr_at_1
      value: 31.761
    - type: mrr_at_10
      value: 40.355999999999995
    - type: mrr_at_100
      value: 41.125
    - type: mrr_at_1000
      value: 41.186
    - type: mrr_at_3
      value: 37.937
    - type: mrr_at_5
      value: 39.463
    - type: ndcg_at_1
      value: 31.761
    - type: ndcg_at_10
      value: 40.422000000000004
    - type: ndcg_at_100
      value: 45.458999999999996
    - type: ndcg_at_1000
      value: 47.951
    - type: ndcg_at_3
      value: 35.972
    - type: ndcg_at_5
      value: 38.272
    - type: precision_at_1
      value: 31.761
    - type: precision_at_10
      value: 7.103
    - type: precision_at_100
      value: 1.133
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 16.779
    - type: precision_at_5
      value: 11.877
    - type: recall_at_1
      value: 26.268
    - type: recall_at_10
      value: 51.053000000000004
    - type: recall_at_100
      value: 72.702
    - type: recall_at_1000
      value: 89.521
    - type: recall_at_3
      value: 38.619
    - type: recall_at_5
      value: 44.671
    - type: map_at_1
      value: 25.230999999999998
    - type: map_at_10
      value: 34.227000000000004
    - type: map_at_100
      value: 35.370000000000005
    - type: map_at_1000
      value: 35.488
    - type: map_at_3
      value: 31.496000000000002
    - type: map_at_5
      value: 33.034
    - type: mrr_at_1
      value: 30.822
    - type: mrr_at_10
      value: 39.045
    - type: mrr_at_100
      value: 39.809
    - type: mrr_at_1000
      value: 39.873
    - type: mrr_at_3
      value: 36.663000000000004
    - type: mrr_at_5
      value: 37.964
    - type: ndcg_at_1
      value: 30.822
    - type: ndcg_at_10
      value: 39.472
    - type: ndcg_at_100
      value: 44.574999999999996
    - type: ndcg_at_1000
      value: 47.162
    - type: ndcg_at_3
      value: 34.929
    - type: ndcg_at_5
      value: 37.002
    - type: precision_at_1
      value: 30.822
    - type: precision_at_10
      value: 7.055
    - type: precision_at_100
      value: 1.124
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 16.591
    - type: precision_at_5
      value: 11.667
    - type: recall_at_1
      value: 25.230999999999998
    - type: recall_at_10
      value: 50.42100000000001
    - type: recall_at_100
      value: 72.685
    - type: recall_at_1000
      value: 90.469
    - type: recall_at_3
      value: 37.503
    - type: recall_at_5
      value: 43.123
    - type: map_at_1
      value: 24.604166666666664
    - type: map_at_10
      value: 32.427166666666665
    - type: map_at_100
      value: 33.51474999999999
    - type: map_at_1000
      value: 33.6345
    - type: map_at_3
      value: 30.02366666666667
    - type: map_at_5
      value: 31.382333333333328
    - type: mrr_at_1
      value: 29.001166666666666
    - type: mrr_at_10
      value: 36.3315
    - type: mrr_at_100
      value: 37.16683333333333
    - type: mrr_at_1000
      value: 37.23341666666668
    - type: mrr_at_3
      value: 34.19916666666667
    - type: mrr_at_5
      value: 35.40458333333334
    - type: ndcg_at_1
      value: 29.001166666666666
    - type: ndcg_at_10
      value: 37.06883333333334
    - type: ndcg_at_100
      value: 41.95816666666666
    - type: ndcg_at_1000
      value: 44.501583333333336
    - type: ndcg_at_3
      value: 32.973499999999994
    - type: ndcg_at_5
      value: 34.90833333333334
    - type: precision_at_1
      value: 29.001166666666666
    - type: precision_at_10
      value: 6.336
    - type: precision_at_100
      value: 1.0282499999999999
    - type: precision_at_1000
      value: 0.14391666666666664
    - type: precision_at_3
      value: 14.932499999999996
    - type: precision_at_5
      value: 10.50825
    - type: recall_at_1
      value: 24.604166666666664
    - type: recall_at_10
      value: 46.9525
    - type: recall_at_100
      value: 68.67816666666667
    - type: recall_at_1000
      value: 86.59783333333334
    - type: recall_at_3
      value: 35.49783333333333
    - type: recall_at_5
      value: 40.52525000000001
    - type: map_at_1
      value: 23.559
    - type: map_at_10
      value: 29.023
    - type: map_at_100
      value: 29.818
    - type: map_at_1000
      value: 29.909000000000002
    - type: map_at_3
      value: 27.037
    - type: map_at_5
      value: 28.225
    - type: mrr_at_1
      value: 26.994
    - type: mrr_at_10
      value: 31.962000000000003
    - type: mrr_at_100
      value: 32.726
    - type: mrr_at_1000
      value: 32.800000000000004
    - type: mrr_at_3
      value: 30.266
    - type: mrr_at_5
      value: 31.208999999999996
    - type: ndcg_at_1
      value: 26.994
    - type: ndcg_at_10
      value: 32.53
    - type: ndcg_at_100
      value: 36.758
    - type: ndcg_at_1000
      value: 39.362
    - type: ndcg_at_3
      value: 28.985
    - type: ndcg_at_5
      value: 30.757
    - type: precision_at_1
      value: 26.994
    - type: precision_at_10
      value: 4.968999999999999
    - type: precision_at_100
      value: 0.759
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 12.219
    - type: precision_at_5
      value: 8.527999999999999
    - type: recall_at_1
      value: 23.559
    - type: recall_at_10
      value: 40.585
    - type: recall_at_100
      value: 60.306000000000004
    - type: recall_at_1000
      value: 80.11
    - type: recall_at_3
      value: 30.794
    - type: recall_at_5
      value: 35.186
    - type: map_at_1
      value: 16.384999999999998
    - type: map_at_10
      value: 22.142
    - type: map_at_100
      value: 23.057
    - type: map_at_1000
      value: 23.177
    - type: map_at_3
      value: 20.29
    - type: map_at_5
      value: 21.332
    - type: mrr_at_1
      value: 19.89
    - type: mrr_at_10
      value: 25.771
    - type: mrr_at_100
      value: 26.599
    - type: mrr_at_1000
      value: 26.680999999999997
    - type: mrr_at_3
      value: 23.962
    - type: mrr_at_5
      value: 24.934
    - type: ndcg_at_1
      value: 19.89
    - type: ndcg_at_10
      value: 25.97
    - type: ndcg_at_100
      value: 30.605
    - type: ndcg_at_1000
      value: 33.619
    - type: ndcg_at_3
      value: 22.704
    - type: ndcg_at_5
      value: 24.199
    - type: precision_at_1
      value: 19.89
    - type: precision_at_10
      value: 4.553
    - type: precision_at_100
      value: 0.8049999999999999
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 10.541
    - type: precision_at_5
      value: 7.46
    - type: recall_at_1
      value: 16.384999999999998
    - type: recall_at_10
      value: 34.001
    - type: recall_at_100
      value: 55.17100000000001
    - type: recall_at_1000
      value: 77.125
    - type: recall_at_3
      value: 24.618000000000002
    - type: recall_at_5
      value: 28.695999999999998
    - type: map_at_1
      value: 23.726
    - type: map_at_10
      value: 31.227
    - type: map_at_100
      value: 32.311
    - type: map_at_1000
      value: 32.419
    - type: map_at_3
      value: 28.765
    - type: map_at_5
      value: 30.229
    - type: mrr_at_1
      value: 27.705000000000002
    - type: mrr_at_10
      value: 35.085
    - type: mrr_at_100
      value: 35.931000000000004
    - type: mrr_at_1000
      value: 36
    - type: mrr_at_3
      value: 32.603
    - type: mrr_at_5
      value: 34.117999999999995
    - type: ndcg_at_1
      value: 27.705000000000002
    - type: ndcg_at_10
      value: 35.968
    - type: ndcg_at_100
      value: 41.197
    - type: ndcg_at_1000
      value: 43.76
    - type: ndcg_at_3
      value: 31.304
    - type: ndcg_at_5
      value: 33.661
    - type: precision_at_1
      value: 27.705000000000002
    - type: precision_at_10
      value: 5.942
    - type: precision_at_100
      value: 0.964
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 13.868
    - type: precision_at_5
      value: 9.944
    - type: recall_at_1
      value: 23.726
    - type: recall_at_10
      value: 46.786
    - type: recall_at_100
      value: 70.072
    - type: recall_at_1000
      value: 88.2
    - type: recall_at_3
      value: 33.981
    - type: recall_at_5
      value: 39.893
    - type: map_at_1
      value: 23.344
    - type: map_at_10
      value: 31.636999999999997
    - type: map_at_100
      value: 33.065
    - type: map_at_1000
      value: 33.300000000000004
    - type: map_at_3
      value: 29.351
    - type: map_at_5
      value: 30.432
    - type: mrr_at_1
      value: 27.866000000000003
    - type: mrr_at_10
      value: 35.587
    - type: mrr_at_100
      value: 36.52
    - type: mrr_at_1000
      value: 36.597
    - type: mrr_at_3
      value: 33.696
    - type: mrr_at_5
      value: 34.713
    - type: ndcg_at_1
      value: 27.866000000000003
    - type: ndcg_at_10
      value: 36.61
    - type: ndcg_at_100
      value: 41.88
    - type: ndcg_at_1000
      value: 45.105000000000004
    - type: ndcg_at_3
      value: 33.038000000000004
    - type: ndcg_at_5
      value: 34.331
    - type: precision_at_1
      value: 27.866000000000003
    - type: precision_at_10
      value: 6.917
    - type: precision_at_100
      value: 1.3599999999999999
    - type: precision_at_1000
      value: 0.233
    - type: precision_at_3
      value: 15.547
    - type: precision_at_5
      value: 10.791
    - type: recall_at_1
      value: 23.344
    - type: recall_at_10
      value: 45.782000000000004
    - type: recall_at_100
      value: 69.503
    - type: recall_at_1000
      value: 90.742
    - type: recall_at_3
      value: 35.160000000000004
    - type: recall_at_5
      value: 39.058
    - type: map_at_1
      value: 20.776
    - type: map_at_10
      value: 27.285999999999998
    - type: map_at_100
      value: 28.235
    - type: map_at_1000
      value: 28.337
    - type: map_at_3
      value: 25.147000000000002
    - type: map_at_5
      value: 26.401999999999997
    - type: mrr_at_1
      value: 22.921
    - type: mrr_at_10
      value: 29.409999999999997
    - type: mrr_at_100
      value: 30.275000000000002
    - type: mrr_at_1000
      value: 30.354999999999997
    - type: mrr_at_3
      value: 27.418
    - type: mrr_at_5
      value: 28.592000000000002
    - type: ndcg_at_1
      value: 22.921
    - type: ndcg_at_10
      value: 31.239
    - type: ndcg_at_100
      value: 35.965
    - type: ndcg_at_1000
      value: 38.602
    - type: ndcg_at_3
      value: 27.174
    - type: ndcg_at_5
      value: 29.229
    - type: precision_at_1
      value: 22.921
    - type: precision_at_10
      value: 4.806
    - type: precision_at_100
      value: 0.776
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 11.459999999999999
    - type: precision_at_5
      value: 8.022
    - type: recall_at_1
      value: 20.776
    - type: recall_at_10
      value: 41.294
    - type: recall_at_100
      value: 63.111
    - type: recall_at_1000
      value: 82.88600000000001
    - type: recall_at_3
      value: 30.403000000000002
    - type: recall_at_5
      value: 35.455999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.376
    - type: map_at_10
      value: 15.926000000000002
    - type: map_at_100
      value: 17.585
    - type: map_at_1000
      value: 17.776
    - type: map_at_3
      value: 13.014000000000001
    - type: map_at_5
      value: 14.417
    - type: mrr_at_1
      value: 20.195
    - type: mrr_at_10
      value: 29.95
    - type: mrr_at_100
      value: 31.052000000000003
    - type: mrr_at_1000
      value: 31.108000000000004
    - type: mrr_at_3
      value: 26.667
    - type: mrr_at_5
      value: 28.458
    - type: ndcg_at_1
      value: 20.195
    - type: ndcg_at_10
      value: 22.871
    - type: ndcg_at_100
      value: 29.921999999999997
    - type: ndcg_at_1000
      value: 33.672999999999995
    - type: ndcg_at_3
      value: 17.782999999999998
    - type: ndcg_at_5
      value: 19.544
    - type: precision_at_1
      value: 20.195
    - type: precision_at_10
      value: 7.394
    - type: precision_at_100
      value: 1.493
    - type: precision_at_1000
      value: 0.218
    - type: precision_at_3
      value: 13.073
    - type: precision_at_5
      value: 10.436
    - type: recall_at_1
      value: 9.376
    - type: recall_at_10
      value: 28.544999999999998
    - type: recall_at_100
      value: 53.147999999999996
    - type: recall_at_1000
      value: 74.62
    - type: recall_at_3
      value: 16.464000000000002
    - type: recall_at_5
      value: 21.004
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.415000000000001
    - type: map_at_10
      value: 18.738
    - type: map_at_100
      value: 27.291999999999998
    - type: map_at_1000
      value: 28.992
    - type: map_at_3
      value: 13.196
    - type: map_at_5
      value: 15.539
    - type: mrr_at_1
      value: 66.5
    - type: mrr_at_10
      value: 74.518
    - type: mrr_at_100
      value: 74.86
    - type: mrr_at_1000
      value: 74.87
    - type: mrr_at_3
      value: 72.375
    - type: mrr_at_5
      value: 73.86200000000001
    - type: ndcg_at_1
      value: 54.37499999999999
    - type: ndcg_at_10
      value: 41.317
    - type: ndcg_at_100
      value: 45.845
    - type: ndcg_at_1000
      value: 52.92
    - type: ndcg_at_3
      value: 44.983000000000004
    - type: ndcg_at_5
      value: 42.989
    - type: precision_at_1
      value: 66.5
    - type: precision_at_10
      value: 33.6
    - type: precision_at_100
      value: 10.972999999999999
    - type: precision_at_1000
      value: 2.214
    - type: precision_at_3
      value: 48.583
    - type: precision_at_5
      value: 42.15
    - type: recall_at_1
      value: 8.415000000000001
    - type: recall_at_10
      value: 24.953
    - type: recall_at_100
      value: 52.48199999999999
    - type: recall_at_1000
      value: 75.093
    - type: recall_at_3
      value: 14.341000000000001
    - type: recall_at_5
      value: 18.468
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 47.06499999999999
    - type: f1
      value: 41.439327599975385
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 66.02
    - type: map_at_10
      value: 76.68599999999999
    - type: map_at_100
      value: 76.959
    - type: map_at_1000
      value: 76.972
    - type: map_at_3
      value: 75.024
    - type: map_at_5
      value: 76.153
    - type: mrr_at_1
      value: 71.197
    - type: mrr_at_10
      value: 81.105
    - type: mrr_at_100
      value: 81.232
    - type: mrr_at_1000
      value: 81.233
    - type: mrr_at_3
      value: 79.758
    - type: mrr_at_5
      value: 80.69
    - type: ndcg_at_1
      value: 71.197
    - type: ndcg_at_10
      value: 81.644
    - type: ndcg_at_100
      value: 82.645
    - type: ndcg_at_1000
      value: 82.879
    - type: ndcg_at_3
      value: 78.792
    - type: ndcg_at_5
      value: 80.528
    - type: precision_at_1
      value: 71.197
    - type: precision_at_10
      value: 10.206999999999999
    - type: precision_at_100
      value: 1.093
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 30.868000000000002
    - type: precision_at_5
      value: 19.559
    - type: recall_at_1
      value: 66.02
    - type: recall_at_10
      value: 92.50699999999999
    - type: recall_at_100
      value: 96.497
    - type: recall_at_1000
      value: 97.956
    - type: recall_at_3
      value: 84.866
    - type: recall_at_5
      value: 89.16199999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.948
    - type: map_at_10
      value: 29.833
    - type: map_at_100
      value: 31.487
    - type: map_at_1000
      value: 31.674000000000003
    - type: map_at_3
      value: 26.029999999999998
    - type: map_at_5
      value: 28.038999999999998
    - type: mrr_at_1
      value: 34.721999999999994
    - type: mrr_at_10
      value: 44.214999999999996
    - type: mrr_at_100
      value: 44.994
    - type: mrr_at_1000
      value: 45.051
    - type: mrr_at_3
      value: 41.667
    - type: mrr_at_5
      value: 43.032
    - type: ndcg_at_1
      value: 34.721999999999994
    - type: ndcg_at_10
      value: 37.434
    - type: ndcg_at_100
      value: 43.702000000000005
    - type: ndcg_at_1000
      value: 46.993
    - type: ndcg_at_3
      value: 33.56
    - type: ndcg_at_5
      value: 34.687
    - type: precision_at_1
      value: 34.721999999999994
    - type: precision_at_10
      value: 10.401
    - type: precision_at_100
      value: 1.7049999999999998
    - type: precision_at_1000
      value: 0.22799999999999998
    - type: precision_at_3
      value: 22.531000000000002
    - type: precision_at_5
      value: 16.42
    - type: recall_at_1
      value: 17.948
    - type: recall_at_10
      value: 45.062999999999995
    - type: recall_at_100
      value: 68.191
    - type: recall_at_1000
      value: 87.954
    - type: recall_at_3
      value: 31.112000000000002
    - type: recall_at_5
      value: 36.823
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 36.644
    - type: map_at_10
      value: 57.658
    - type: map_at_100
      value: 58.562000000000005
    - type: map_at_1000
      value: 58.62500000000001
    - type: map_at_3
      value: 54.022999999999996
    - type: map_at_5
      value: 56.293000000000006
    - type: mrr_at_1
      value: 73.288
    - type: mrr_at_10
      value: 80.51700000000001
    - type: mrr_at_100
      value: 80.72
    - type: mrr_at_1000
      value: 80.728
    - type: mrr_at_3
      value: 79.33200000000001
    - type: mrr_at_5
      value: 80.085
    - type: ndcg_at_1
      value: 73.288
    - type: ndcg_at_10
      value: 66.61
    - type: ndcg_at_100
      value: 69.723
    - type: ndcg_at_1000
      value: 70.96000000000001
    - type: ndcg_at_3
      value: 61.358999999999995
    - type: ndcg_at_5
      value: 64.277
    - type: precision_at_1
      value: 73.288
    - type: precision_at_10
      value: 14.17
    - type: precision_at_100
      value: 1.659
    - type: precision_at_1000
      value: 0.182
    - type: precision_at_3
      value: 39.487
    - type: precision_at_5
      value: 25.999
    - type: recall_at_1
      value: 36.644
    - type: recall_at_10
      value: 70.851
    - type: recall_at_100
      value: 82.94399999999999
    - type: recall_at_1000
      value: 91.134
    - type: recall_at_3
      value: 59.230000000000004
    - type: recall_at_5
      value: 64.997
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 86.00280000000001
    - type: ap
      value: 80.46302061021223
    - type: f1
      value: 85.9592921596419
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 22.541
    - type: map_at_10
      value: 34.625
    - type: map_at_100
      value: 35.785
    - type: map_at_1000
      value: 35.831
    - type: map_at_3
      value: 30.823
    - type: map_at_5
      value: 32.967999999999996
    - type: mrr_at_1
      value: 23.180999999999997
    - type: mrr_at_10
      value: 35.207
    - type: mrr_at_100
      value: 36.315
    - type: mrr_at_1000
      value: 36.355
    - type: mrr_at_3
      value: 31.483
    - type: mrr_at_5
      value: 33.589999999999996
    - type: ndcg_at_1
      value: 23.195
    - type: ndcg_at_10
      value: 41.461
    - type: ndcg_at_100
      value: 47.032000000000004
    - type: ndcg_at_1000
      value: 48.199999999999996
    - type: ndcg_at_3
      value: 33.702
    - type: ndcg_at_5
      value: 37.522
    - type: precision_at_1
      value: 23.195
    - type: precision_at_10
      value: 6.526999999999999
    - type: precision_at_100
      value: 0.932
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 14.308000000000002
    - type: precision_at_5
      value: 10.507
    - type: recall_at_1
      value: 22.541
    - type: recall_at_10
      value: 62.524
    - type: recall_at_100
      value: 88.228
    - type: recall_at_1000
      value: 97.243
    - type: recall_at_3
      value: 41.38
    - type: recall_at_5
      value: 50.55
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 92.69949840401279
    - type: f1
      value: 92.54141471311786
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 72.56041951664386
    - type: f1
      value: 55.88499977508287
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 71.62071284465365
    - type: f1
      value: 69.36717546572152
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 76.35843981170142
    - type: f1
      value: 76.15496453538884
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.33664956793118
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.883839621715524
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.096874986740758
    - type: mrr
      value: 30.97300481932132
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.4
    - type: map_at_10
      value: 11.852
    - type: map_at_100
      value: 14.758
    - type: map_at_1000
      value: 16.134
    - type: map_at_3
      value: 8.558
    - type: map_at_5
      value: 10.087
    - type: mrr_at_1
      value: 44.272
    - type: mrr_at_10
      value: 52.05800000000001
    - type: mrr_at_100
      value: 52.689
    - type: mrr_at_1000
      value: 52.742999999999995
    - type: mrr_at_3
      value: 50.205999999999996
    - type: mrr_at_5
      value: 51.367
    - type: ndcg_at_1
      value: 42.57
    - type: ndcg_at_10
      value: 32.449
    - type: ndcg_at_100
      value: 29.596
    - type: ndcg_at_1000
      value: 38.351
    - type: ndcg_at_3
      value: 37.044
    - type: ndcg_at_5
      value: 35.275
    - type: precision_at_1
      value: 44.272
    - type: precision_at_10
      value: 23.87
    - type: precision_at_100
      value: 7.625
    - type: precision_at_1000
      value: 2.045
    - type: precision_at_3
      value: 34.365
    - type: precision_at_5
      value: 30.341
    - type: recall_at_1
      value: 5.4
    - type: recall_at_10
      value: 15.943999999999999
    - type: recall_at_100
      value: 29.805
    - type: recall_at_1000
      value: 61.695
    - type: recall_at_3
      value: 9.539
    - type: recall_at_5
      value: 12.127
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 36.047000000000004
    - type: map_at_10
      value: 51.6
    - type: map_at_100
      value: 52.449999999999996
    - type: map_at_1000
      value: 52.476
    - type: map_at_3
      value: 47.452
    - type: map_at_5
      value: 49.964
    - type: mrr_at_1
      value: 40.382
    - type: mrr_at_10
      value: 54.273
    - type: mrr_at_100
      value: 54.859
    - type: mrr_at_1000
      value: 54.876000000000005
    - type: mrr_at_3
      value: 51.014
    - type: mrr_at_5
      value: 52.983999999999995
    - type: ndcg_at_1
      value: 40.353
    - type: ndcg_at_10
      value: 59.11300000000001
    - type: ndcg_at_100
      value: 62.604000000000006
    - type: ndcg_at_1000
      value: 63.187000000000005
    - type: ndcg_at_3
      value: 51.513
    - type: ndcg_at_5
      value: 55.576
    - type: precision_at_1
      value: 40.353
    - type: precision_at_10
      value: 9.418
    - type: precision_at_100
      value: 1.1440000000000001
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 23.078000000000003
    - type: precision_at_5
      value: 16.250999999999998
    - type: recall_at_1
      value: 36.047000000000004
    - type: recall_at_10
      value: 79.22200000000001
    - type: recall_at_100
      value: 94.23
    - type: recall_at_1000
      value: 98.51100000000001
    - type: recall_at_3
      value: 59.678
    - type: recall_at_5
      value: 68.967
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 68.232
    - type: map_at_10
      value: 81.674
    - type: map_at_100
      value: 82.338
    - type: map_at_1000
      value: 82.36099999999999
    - type: map_at_3
      value: 78.833
    - type: map_at_5
      value: 80.58
    - type: mrr_at_1
      value: 78.64
    - type: mrr_at_10
      value: 85.164
    - type: mrr_at_100
      value: 85.317
    - type: mrr_at_1000
      value: 85.319
    - type: mrr_at_3
      value: 84.127
    - type: mrr_at_5
      value: 84.789
    - type: ndcg_at_1
      value: 78.63
    - type: ndcg_at_10
      value: 85.711
    - type: ndcg_at_100
      value: 87.238
    - type: ndcg_at_1000
      value: 87.444
    - type: ndcg_at_3
      value: 82.788
    - type: ndcg_at_5
      value: 84.313
    - type: precision_at_1
      value: 78.63
    - type: precision_at_10
      value: 12.977
    - type: precision_at_100
      value: 1.503
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 36.113
    - type: precision_at_5
      value: 23.71
    - type: recall_at_1
      value: 68.232
    - type: recall_at_10
      value: 93.30199999999999
    - type: recall_at_100
      value: 98.799
    - type: recall_at_1000
      value: 99.885
    - type: recall_at_3
      value: 84.827
    - type: recall_at_5
      value: 89.188
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 45.71879170816294
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 59.65866311751794
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.218
    - type: map_at_10
      value: 10.337
    - type: map_at_100
      value: 12.131
    - type: map_at_1000
      value: 12.411
    - type: map_at_3
      value: 7.4270000000000005
    - type: map_at_5
      value: 8.913
    - type: mrr_at_1
      value: 20.8
    - type: mrr_at_10
      value: 30.868000000000002
    - type: mrr_at_100
      value: 31.903
    - type: mrr_at_1000
      value: 31.972
    - type: mrr_at_3
      value: 27.367
    - type: mrr_at_5
      value: 29.372
    - type: ndcg_at_1
      value: 20.8
    - type: ndcg_at_10
      value: 17.765
    - type: ndcg_at_100
      value: 24.914
    - type: ndcg_at_1000
      value: 30.206
    - type: ndcg_at_3
      value: 16.64
    - type: ndcg_at_5
      value: 14.712
    - type: precision_at_1
      value: 20.8
    - type: precision_at_10
      value: 9.24
    - type: precision_at_100
      value: 1.9560000000000002
    - type: precision_at_1000
      value: 0.32299999999999995
    - type: precision_at_3
      value: 15.467
    - type: precision_at_5
      value: 12.94
    - type: recall_at_1
      value: 4.218
    - type: recall_at_10
      value: 18.752
    - type: recall_at_100
      value: 39.7
    - type: recall_at_1000
      value: 65.57300000000001
    - type: recall_at_3
      value: 9.428
    - type: recall_at_5
      value: 13.133000000000001
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 83.04338850207233
    - type: cos_sim_spearman
      value: 78.5054651430423
    - type: euclidean_pearson
      value: 80.30739451228612
    - type: euclidean_spearman
      value: 78.48377464299097
    - type: manhattan_pearson
      value: 80.40795049052781
    - type: manhattan_spearman
      value: 78.49506205443114
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 84.11596224442962
    - type: cos_sim_spearman
      value: 76.20997388935461
    - type: euclidean_pearson
      value: 80.56858451349109
    - type: euclidean_spearman
      value: 75.92659183871186
    - type: manhattan_pearson
      value: 80.60246102203844
    - type: manhattan_spearman
      value: 76.03018971432664
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 81.34691640755737
    - type: cos_sim_spearman
      value: 82.4018369631579
    - type: euclidean_pearson
      value: 81.87673092245366
    - type: euclidean_spearman
      value: 82.3671489960678
    - type: manhattan_pearson
      value: 81.88222387719948
    - type: manhattan_spearman
      value: 82.3816590344736
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 81.2836092579524
    - type: cos_sim_spearman
      value: 78.99982781772064
    - type: euclidean_pearson
      value: 80.5184271010527
    - type: euclidean_spearman
      value: 78.89777392101904
    - type: manhattan_pearson
      value: 80.53585705018664
    - type: manhattan_spearman
      value: 78.92898405472994
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.7349907750784
    - type: cos_sim_spearman
      value: 87.7611234446225
    - type: euclidean_pearson
      value: 86.98759326731624
    - type: euclidean_spearman
      value: 87.58321319424618
    - type: manhattan_pearson
      value: 87.03483090370842
    - type: manhattan_spearman
      value: 87.63278333060288
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 81.75873694924825
    - type: cos_sim_spearman
      value: 83.80237999094724
    - type: euclidean_pearson
      value: 83.55023725861537
    - type: euclidean_spearman
      value: 84.12744338577744
    - type: manhattan_pearson
      value: 83.58816983036232
    - type: manhattan_spearman
      value: 84.18520748676501
  - 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: 87.21630882940174
    - type: cos_sim_spearman
      value: 87.72382883437031
    - type: euclidean_pearson
      value: 88.69933350930333
    - type: euclidean_spearman
      value: 88.24660814383081
    - type: manhattan_pearson
      value: 88.77331018833499
    - type: manhattan_spearman
      value: 88.26109989380632
  - 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: 61.11854063060489
    - type: cos_sim_spearman
      value: 63.14678634195072
    - type: euclidean_pearson
      value: 61.679090067000864
    - type: euclidean_spearman
      value: 62.28876589509653
    - type: manhattan_pearson
      value: 62.082324165511004
    - type: manhattan_spearman
      value: 62.56030932816679
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 84.00319882832645
    - type: cos_sim_spearman
      value: 85.94529772647257
    - type: euclidean_pearson
      value: 85.6661390122756
    - type: euclidean_spearman
      value: 85.97747815545827
    - type: manhattan_pearson
      value: 85.58422770541893
    - type: manhattan_spearman
      value: 85.9237139181532
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.16198731863916
    - type: mrr
      value: 94.25202702163487
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 54.761
    - type: map_at_10
      value: 64.396
    - type: map_at_100
      value: 65.07
    - type: map_at_1000
      value: 65.09899999999999
    - type: map_at_3
      value: 61.846000000000004
    - type: map_at_5
      value: 63.284
    - type: mrr_at_1
      value: 57.667
    - type: mrr_at_10
      value: 65.83099999999999
    - type: mrr_at_100
      value: 66.36800000000001
    - type: mrr_at_1000
      value: 66.39399999999999
    - type: mrr_at_3
      value: 64.056
    - type: mrr_at_5
      value: 65.206
    - type: ndcg_at_1
      value: 57.667
    - type: ndcg_at_10
      value: 68.854
    - type: ndcg_at_100
      value: 71.59100000000001
    - type: ndcg_at_1000
      value: 72.383
    - type: ndcg_at_3
      value: 64.671
    - type: ndcg_at_5
      value: 66.796
    - type: precision_at_1
      value: 57.667
    - type: precision_at_10
      value: 9.167
    - type: precision_at_100
      value: 1.053
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 25.444
    - type: precision_at_5
      value: 16.667
    - type: recall_at_1
      value: 54.761
    - type: recall_at_10
      value: 80.9
    - type: recall_at_100
      value: 92.767
    - type: recall_at_1000
      value: 99
    - type: recall_at_3
      value: 69.672
    - type: recall_at_5
      value: 75.083
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.8079207920792
    - type: cos_sim_ap
      value: 94.88470927617445
    - type: cos_sim_f1
      value: 90.08179959100204
    - type: cos_sim_precision
      value: 92.15481171548117
    - type: cos_sim_recall
      value: 88.1
    - type: dot_accuracy
      value: 99.58613861386138
    - type: dot_ap
      value: 82.94822578881316
    - type: dot_f1
      value: 77.33333333333333
    - type: dot_precision
      value: 79.36842105263158
    - type: dot_recall
      value: 75.4
    - type: euclidean_accuracy
      value: 99.8069306930693
    - type: euclidean_ap
      value: 94.81367858031837
    - type: euclidean_f1
      value: 90.01009081735621
    - type: euclidean_precision
      value: 90.83503054989816
    - type: euclidean_recall
      value: 89.2
    - type: manhattan_accuracy
      value: 99.81188118811882
    - type: manhattan_ap
      value: 94.91405337220161
    - type: manhattan_f1
      value: 90.2763561924258
    - type: manhattan_precision
      value: 92.45283018867924
    - type: manhattan_recall
      value: 88.2
    - type: max_accuracy
      value: 99.81188118811882
    - type: max_ap
      value: 94.91405337220161
    - type: max_f1
      value: 90.2763561924258
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 58.511599500053094
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 31.984728147814707
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 49.93428193939015
    - type: mrr
      value: 50.916557911043206
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.562500894537145
    - type: cos_sim_spearman
      value: 31.162587976726307
    - type: dot_pearson
      value: 22.633662187735762
    - type: dot_spearman
      value: 22.723000282378962
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.219
    - type: map_at_10
      value: 1.871
    - type: map_at_100
      value: 10.487
    - type: map_at_1000
      value: 25.122
    - type: map_at_3
      value: 0.657
    - type: map_at_5
      value: 1.0699999999999998
    - type: mrr_at_1
      value: 84
    - type: mrr_at_10
      value: 89.567
    - type: mrr_at_100
      value: 89.748
    - type: mrr_at_1000
      value: 89.748
    - type: mrr_at_3
      value: 88.667
    - type: mrr_at_5
      value: 89.567
    - type: ndcg_at_1
      value: 80
    - type: ndcg_at_10
      value: 74.533
    - type: ndcg_at_100
      value: 55.839000000000006
    - type: ndcg_at_1000
      value: 49.748
    - type: ndcg_at_3
      value: 79.53099999999999
    - type: ndcg_at_5
      value: 78.245
    - type: precision_at_1
      value: 84
    - type: precision_at_10
      value: 78.4
    - type: precision_at_100
      value: 56.99999999999999
    - type: precision_at_1000
      value: 21.98
    - type: precision_at_3
      value: 85.333
    - type: precision_at_5
      value: 84.8
    - type: recall_at_1
      value: 0.219
    - type: recall_at_10
      value: 2.02
    - type: recall_at_100
      value: 13.555
    - type: recall_at_1000
      value: 46.739999999999995
    - type: recall_at_3
      value: 0.685
    - type: recall_at_5
      value: 1.13
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.5029999999999997
    - type: map_at_10
      value: 11.042
    - type: map_at_100
      value: 16.326999999999998
    - type: map_at_1000
      value: 17.836
    - type: map_at_3
      value: 6.174
    - type: map_at_5
      value: 7.979
    - type: mrr_at_1
      value: 42.857
    - type: mrr_at_10
      value: 52.617000000000004
    - type: mrr_at_100
      value: 53.351000000000006
    - type: mrr_at_1000
      value: 53.351000000000006
    - type: mrr_at_3
      value: 46.939
    - type: mrr_at_5
      value: 50.714000000000006
    - type: ndcg_at_1
      value: 38.775999999999996
    - type: ndcg_at_10
      value: 27.125
    - type: ndcg_at_100
      value: 35.845
    - type: ndcg_at_1000
      value: 47.377
    - type: ndcg_at_3
      value: 29.633
    - type: ndcg_at_5
      value: 28.378999999999998
    - type: precision_at_1
      value: 42.857
    - type: precision_at_10
      value: 24.082
    - type: precision_at_100
      value: 6.877999999999999
    - type: precision_at_1000
      value: 1.463
    - type: precision_at_3
      value: 29.932
    - type: precision_at_5
      value: 28.571
    - type: recall_at_1
      value: 3.5029999999999997
    - type: recall_at_10
      value: 17.068
    - type: recall_at_100
      value: 43.361
    - type: recall_at_1000
      value: 78.835
    - type: recall_at_3
      value: 6.821000000000001
    - type: recall_at_5
      value: 10.357
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.0954
    - type: ap
      value: 14.216844153511959
    - type: f1
      value: 54.63687418565117
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 61.46293152235427
    - type: f1
      value: 61.744177921638645
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 41.12708617788644
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 85.75430649102938
    - type: cos_sim_ap
      value: 73.34252536948081
    - type: cos_sim_f1
      value: 67.53758935173774
    - type: cos_sim_precision
      value: 63.3672525439408
    - type: cos_sim_recall
      value: 72.29551451187335
    - type: dot_accuracy
      value: 81.71305954580676
    - type: dot_ap
      value: 59.5532209082386
    - type: dot_f1
      value: 56.18466898954705
    - type: dot_precision
      value: 47.830923248053395
    - type: dot_recall
      value: 68.07387862796834
    - type: euclidean_accuracy
      value: 85.81987244441795
    - type: euclidean_ap
      value: 73.34325409809446
    - type: euclidean_f1
      value: 67.83451360417443
    - type: euclidean_precision
      value: 64.09955388588871
    - type: euclidean_recall
      value: 72.0316622691293
    - type: manhattan_accuracy
      value: 85.68277999642368
    - type: manhattan_ap
      value: 73.1535450121903
    - type: manhattan_f1
      value: 67.928237896289
    - type: manhattan_precision
      value: 63.56945722171113
    - type: manhattan_recall
      value: 72.9287598944591
    - type: max_accuracy
      value: 85.81987244441795
    - type: max_ap
      value: 73.34325409809446
    - type: max_f1
      value: 67.928237896289
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.90441262079403
    - type: cos_sim_ap
      value: 85.79331880741438
    - type: cos_sim_f1
      value: 78.31563529842548
    - type: cos_sim_precision
      value: 74.6683424102779
    - type: cos_sim_recall
      value: 82.33754234678165
    - type: dot_accuracy
      value: 84.89928978926534
    - type: dot_ap
      value: 75.25819218316
    - type: dot_f1
      value: 69.88730119720536
    - type: dot_precision
      value: 64.23362374959665
    - type: dot_recall
      value: 76.63227594702803
    - type: euclidean_accuracy
      value: 89.01695967710637
    - type: euclidean_ap
      value: 85.98986606038852
    - type: euclidean_f1
      value: 78.5277880014722
    - type: euclidean_precision
      value: 75.22211253701876
    - type: euclidean_recall
      value: 82.13735756082538
    - type: manhattan_accuracy
      value: 88.99561454573679
    - type: manhattan_ap
      value: 85.92262421793953
    - type: manhattan_f1
      value: 78.38866094740769
    - type: manhattan_precision
      value: 76.02373028505282
    - type: manhattan_recall
      value: 80.9054511857099
    - type: max_accuracy
      value: 89.01695967710637
    - type: max_ap
      value: 85.98986606038852
    - type: max_f1
      value: 78.5277880014722
---

# ggml-org/e5-small-v2-Q8_0-GGUF
This model was converted to GGUF format from [`intfloat/e5-small-v2`](https://huggingface.co/intfloat/e5-small-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-small-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 ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -c 2048
```

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

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

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

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -c 2048
```
