sentence-transformers gguf feature-extraction sentence-similarity mteb llama-cpp gguf-my-repo en dataset:allenai/c4 base_model:jinaai/jina-embeddings-v2-base-en base_model:quantized:jinaai/jina-embeddings-v2-base-en license:apache-2.0 model-index autotrain_compatible region:us
---
base_model: jinaai/jina-embeddings-v2-base-en
datasets:
- allenai/c4
language: en
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- llama-cpp
- gguf-my-repo
inference: false
model-index:
- name: jina-embedding-b-en-v2
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.73134328358209
    - type: ap
      value: 37.765427081831035
    - type: f1
      value: 68.79367444339518
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 88.544275
    - type: ap
      value: 84.61328675662887
    - type: f1
      value: 88.51879035862375
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 45.263999999999996
    - type: f1
      value: 43.778759656699435
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 21.693
    - type: map_at_10
      value: 35.487
    - type: map_at_100
      value: 36.862
    - type: map_at_1000
      value: 36.872
    - type: map_at_3
      value: 30.049999999999997
    - type: map_at_5
      value: 32.966
    - type: mrr_at_1
      value: 21.977
    - type: mrr_at_10
      value: 35.565999999999995
    - type: mrr_at_100
      value: 36.948
    - type: mrr_at_1000
      value: 36.958
    - type: mrr_at_3
      value: 30.121
    - type: mrr_at_5
      value: 33.051
    - type: ndcg_at_1
      value: 21.693
    - type: ndcg_at_10
      value: 44.181
    - type: ndcg_at_100
      value: 49.982
    - type: ndcg_at_1000
      value: 50.233000000000004
    - type: ndcg_at_3
      value: 32.830999999999996
    - type: ndcg_at_5
      value: 38.080000000000005
    - type: precision_at_1
      value: 21.693
    - type: precision_at_10
      value: 7.248
    - type: precision_at_100
      value: 0.9769999999999999
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 13.632
    - type: precision_at_5
      value: 10.725
    - type: recall_at_1
      value: 21.693
    - type: recall_at_10
      value: 72.475
    - type: recall_at_100
      value: 97.653
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 40.896
    - type: recall_at_5
      value: 53.627
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 45.39242428696777
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 36.675626784714
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 62.247725694904034
    - type: mrr
      value: 74.91359978894604
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.68003802970496
    - type: cos_sim_spearman
      value: 81.23438110096286
    - type: euclidean_pearson
      value: 81.87462986142582
    - type: euclidean_spearman
      value: 81.23438110096286
    - type: manhattan_pearson
      value: 81.61162566600755
    - type: manhattan_spearman
      value: 81.11329400456184
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 84.01298701298701
    - type: f1
      value: 83.31690714969382
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 37.050108150972086
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 30.15731442819715
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.391999999999996
    - type: map_at_10
      value: 42.597
    - type: map_at_100
      value: 44.07
    - type: map_at_1000
      value: 44.198
    - type: map_at_3
      value: 38.957
    - type: map_at_5
      value: 40.961
    - type: mrr_at_1
      value: 37.196
    - type: mrr_at_10
      value: 48.152
    - type: mrr_at_100
      value: 48.928
    - type: mrr_at_1000
      value: 48.964999999999996
    - type: mrr_at_3
      value: 45.446
    - type: mrr_at_5
      value: 47.205999999999996
    - type: ndcg_at_1
      value: 37.196
    - type: ndcg_at_10
      value: 49.089
    - type: ndcg_at_100
      value: 54.471000000000004
    - type: ndcg_at_1000
      value: 56.385
    - type: ndcg_at_3
      value: 43.699
    - type: ndcg_at_5
      value: 46.22
    - type: precision_at_1
      value: 37.196
    - type: precision_at_10
      value: 9.313
    - type: precision_at_100
      value: 1.478
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 20.839
    - type: precision_at_5
      value: 14.936
    - type: recall_at_1
      value: 31.391999999999996
    - type: recall_at_10
      value: 61.876
    - type: recall_at_100
      value: 84.214
    - type: recall_at_1000
      value: 95.985
    - type: recall_at_3
      value: 46.6
    - type: recall_at_5
      value: 53.588
    - type: map_at_1
      value: 29.083
    - type: map_at_10
      value: 38.812999999999995
    - type: map_at_100
      value: 40.053
    - type: map_at_1000
      value: 40.188
    - type: map_at_3
      value: 36.111
    - type: map_at_5
      value: 37.519000000000005
    - type: mrr_at_1
      value: 36.497
    - type: mrr_at_10
      value: 44.85
    - type: mrr_at_100
      value: 45.546
    - type: mrr_at_1000
      value: 45.593
    - type: mrr_at_3
      value: 42.686
    - type: mrr_at_5
      value: 43.909
    - type: ndcg_at_1
      value: 36.497
    - type: ndcg_at_10
      value: 44.443
    - type: ndcg_at_100
      value: 48.979
    - type: ndcg_at_1000
      value: 51.154999999999994
    - type: ndcg_at_3
      value: 40.660000000000004
    - type: ndcg_at_5
      value: 42.193000000000005
    - type: precision_at_1
      value: 36.497
    - type: precision_at_10
      value: 8.433
    - type: precision_at_100
      value: 1.369
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 19.894000000000002
    - type: precision_at_5
      value: 13.873
    - type: recall_at_1
      value: 29.083
    - type: recall_at_10
      value: 54.313
    - type: recall_at_100
      value: 73.792
    - type: recall_at_1000
      value: 87.629
    - type: recall_at_3
      value: 42.257
    - type: recall_at_5
      value: 47.066
    - type: map_at_1
      value: 38.556000000000004
    - type: map_at_10
      value: 50.698
    - type: map_at_100
      value: 51.705
    - type: map_at_1000
      value: 51.768
    - type: map_at_3
      value: 47.848
    - type: map_at_5
      value: 49.358000000000004
    - type: mrr_at_1
      value: 43.95
    - type: mrr_at_10
      value: 54.191
    - type: mrr_at_100
      value: 54.852999999999994
    - type: mrr_at_1000
      value: 54.885
    - type: mrr_at_3
      value: 51.954
    - type: mrr_at_5
      value: 53.13
    - type: ndcg_at_1
      value: 43.95
    - type: ndcg_at_10
      value: 56.516
    - type: ndcg_at_100
      value: 60.477000000000004
    - type: ndcg_at_1000
      value: 61.746
    - type: ndcg_at_3
      value: 51.601
    - type: ndcg_at_5
      value: 53.795
    - type: precision_at_1
      value: 43.95
    - type: precision_at_10
      value: 9.009
    - type: precision_at_100
      value: 1.189
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 22.989
    - type: precision_at_5
      value: 15.473
    - type: recall_at_1
      value: 38.556000000000004
    - type: recall_at_10
      value: 70.159
    - type: recall_at_100
      value: 87.132
    - type: recall_at_1000
      value: 96.16
    - type: recall_at_3
      value: 56.906
    - type: recall_at_5
      value: 62.332
    - type: map_at_1
      value: 24.238
    - type: map_at_10
      value: 32.5
    - type: map_at_100
      value: 33.637
    - type: map_at_1000
      value: 33.719
    - type: map_at_3
      value: 30.026999999999997
    - type: map_at_5
      value: 31.555
    - type: mrr_at_1
      value: 26.328000000000003
    - type: mrr_at_10
      value: 34.44
    - type: mrr_at_100
      value: 35.455999999999996
    - type: mrr_at_1000
      value: 35.521
    - type: mrr_at_3
      value: 32.034
    - type: mrr_at_5
      value: 33.565
    - type: ndcg_at_1
      value: 26.328000000000003
    - type: ndcg_at_10
      value: 37.202
    - type: ndcg_at_100
      value: 42.728
    - type: ndcg_at_1000
      value: 44.792
    - type: ndcg_at_3
      value: 32.368
    - type: ndcg_at_5
      value: 35.008
    - type: precision_at_1
      value: 26.328000000000003
    - type: precision_at_10
      value: 5.7059999999999995
    - type: precision_at_100
      value: 0.8880000000000001
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 13.672
    - type: precision_at_5
      value: 9.74
    - type: recall_at_1
      value: 24.238
    - type: recall_at_10
      value: 49.829
    - type: recall_at_100
      value: 75.21
    - type: recall_at_1000
      value: 90.521
    - type: recall_at_3
      value: 36.867
    - type: recall_at_5
      value: 43.241
    - type: map_at_1
      value: 15.378
    - type: map_at_10
      value: 22.817999999999998
    - type: map_at_100
      value: 23.977999999999998
    - type: map_at_1000
      value: 24.108
    - type: map_at_3
      value: 20.719
    - type: map_at_5
      value: 21.889
    - type: mrr_at_1
      value: 19.03
    - type: mrr_at_10
      value: 27.022000000000002
    - type: mrr_at_100
      value: 28.011999999999997
    - type: mrr_at_1000
      value: 28.096
    - type: mrr_at_3
      value: 24.855
    - type: mrr_at_5
      value: 26.029999999999998
    - type: ndcg_at_1
      value: 19.03
    - type: ndcg_at_10
      value: 27.526
    - type: ndcg_at_100
      value: 33.040000000000006
    - type: ndcg_at_1000
      value: 36.187000000000005
    - type: ndcg_at_3
      value: 23.497
    - type: ndcg_at_5
      value: 25.334
    - type: precision_at_1
      value: 19.03
    - type: precision_at_10
      value: 4.963
    - type: precision_at_100
      value: 0.893
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 11.360000000000001
    - type: precision_at_5
      value: 8.134
    - type: recall_at_1
      value: 15.378
    - type: recall_at_10
      value: 38.061
    - type: recall_at_100
      value: 61.754
    - type: recall_at_1000
      value: 84.259
    - type: recall_at_3
      value: 26.788
    - type: recall_at_5
      value: 31.326999999999998
    - type: map_at_1
      value: 27.511999999999997
    - type: map_at_10
      value: 37.429
    - type: map_at_100
      value: 38.818000000000005
    - type: map_at_1000
      value: 38.924
    - type: map_at_3
      value: 34.625
    - type: map_at_5
      value: 36.064
    - type: mrr_at_1
      value: 33.300999999999995
    - type: mrr_at_10
      value: 43.036
    - type: mrr_at_100
      value: 43.894
    - type: mrr_at_1000
      value: 43.936
    - type: mrr_at_3
      value: 40.825
    - type: mrr_at_5
      value: 42.028
    - type: ndcg_at_1
      value: 33.300999999999995
    - type: ndcg_at_10
      value: 43.229
    - type: ndcg_at_100
      value: 48.992000000000004
    - type: ndcg_at_1000
      value: 51.02100000000001
    - type: ndcg_at_3
      value: 38.794000000000004
    - type: ndcg_at_5
      value: 40.65
    - type: precision_at_1
      value: 33.300999999999995
    - type: precision_at_10
      value: 7.777000000000001
    - type: precision_at_100
      value: 1.269
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 18.351
    - type: precision_at_5
      value: 12.762
    - type: recall_at_1
      value: 27.511999999999997
    - type: recall_at_10
      value: 54.788000000000004
    - type: recall_at_100
      value: 79.105
    - type: recall_at_1000
      value: 92.49199999999999
    - type: recall_at_3
      value: 41.924
    - type: recall_at_5
      value: 47.026
    - type: map_at_1
      value: 24.117
    - type: map_at_10
      value: 33.32
    - type: map_at_100
      value: 34.677
    - type: map_at_1000
      value: 34.78
    - type: map_at_3
      value: 30.233999999999998
    - type: map_at_5
      value: 31.668000000000003
    - type: mrr_at_1
      value: 29.566
    - type: mrr_at_10
      value: 38.244
    - type: mrr_at_100
      value: 39.245000000000005
    - type: mrr_at_1000
      value: 39.296
    - type: mrr_at_3
      value: 35.864000000000004
    - type: mrr_at_5
      value: 36.919999999999995
    - type: ndcg_at_1
      value: 29.566
    - type: ndcg_at_10
      value: 39.127
    - type: ndcg_at_100
      value: 44.989000000000004
    - type: ndcg_at_1000
      value: 47.189
    - type: ndcg_at_3
      value: 34.039
    - type: ndcg_at_5
      value: 35.744
    - type: precision_at_1
      value: 29.566
    - type: precision_at_10
      value: 7.385999999999999
    - type: precision_at_100
      value: 1.204
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 16.286
    - type: precision_at_5
      value: 11.484
    - type: recall_at_1
      value: 24.117
    - type: recall_at_10
      value: 51.559999999999995
    - type: recall_at_100
      value: 77.104
    - type: recall_at_1000
      value: 91.79899999999999
    - type: recall_at_3
      value: 36.82
    - type: recall_at_5
      value: 41.453
    - type: map_at_1
      value: 25.17625
    - type: map_at_10
      value: 34.063916666666664
    - type: map_at_100
      value: 35.255500000000005
    - type: map_at_1000
      value: 35.37275
    - type: map_at_3
      value: 31.351666666666667
    - type: map_at_5
      value: 32.80608333333333
    - type: mrr_at_1
      value: 29.59783333333333
    - type: mrr_at_10
      value: 38.0925
    - type: mrr_at_100
      value: 38.957249999999995
    - type: mrr_at_1000
      value: 39.01608333333333
    - type: mrr_at_3
      value: 35.77625
    - type: mrr_at_5
      value: 37.04991666666667
    - type: ndcg_at_1
      value: 29.59783333333333
    - type: ndcg_at_10
      value: 39.343666666666664
    - type: ndcg_at_100
      value: 44.488249999999994
    - type: ndcg_at_1000
      value: 46.83358333333334
    - type: ndcg_at_3
      value: 34.69708333333333
    - type: ndcg_at_5
      value: 36.75075
    - type: precision_at_1
      value: 29.59783333333333
    - type: precision_at_10
      value: 6.884083333333332
    - type: precision_at_100
      value: 1.114
    - type: precision_at_1000
      value: 0.15108333333333332
    - type: precision_at_3
      value: 15.965250000000003
    - type: precision_at_5
      value: 11.246500000000001
    - type: recall_at_1
      value: 25.17625
    - type: recall_at_10
      value: 51.015999999999984
    - type: recall_at_100
      value: 73.60174999999998
    - type: recall_at_1000
      value: 89.849
    - type: recall_at_3
      value: 37.88399999999999
    - type: recall_at_5
      value: 43.24541666666666
    - type: map_at_1
      value: 24.537
    - type: map_at_10
      value: 31.081999999999997
    - type: map_at_100
      value: 32.042
    - type: map_at_1000
      value: 32.141
    - type: map_at_3
      value: 29.137
    - type: map_at_5
      value: 30.079
    - type: mrr_at_1
      value: 27.454
    - type: mrr_at_10
      value: 33.694
    - type: mrr_at_100
      value: 34.579
    - type: mrr_at_1000
      value: 34.649
    - type: mrr_at_3
      value: 32.004
    - type: mrr_at_5
      value: 32.794000000000004
    - type: ndcg_at_1
      value: 27.454
    - type: ndcg_at_10
      value: 34.915
    - type: ndcg_at_100
      value: 39.641
    - type: ndcg_at_1000
      value: 42.105
    - type: ndcg_at_3
      value: 31.276
    - type: ndcg_at_5
      value: 32.65
    - type: precision_at_1
      value: 27.454
    - type: precision_at_10
      value: 5.337
    - type: precision_at_100
      value: 0.8250000000000001
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 13.241
    - type: precision_at_5
      value: 8.895999999999999
    - type: recall_at_1
      value: 24.537
    - type: recall_at_10
      value: 44.324999999999996
    - type: recall_at_100
      value: 65.949
    - type: recall_at_1000
      value: 84.017
    - type: recall_at_3
      value: 33.857
    - type: recall_at_5
      value: 37.316
    - type: map_at_1
      value: 17.122
    - type: map_at_10
      value: 24.32
    - type: map_at_100
      value: 25.338
    - type: map_at_1000
      value: 25.462
    - type: map_at_3
      value: 22.064
    - type: map_at_5
      value: 23.322000000000003
    - type: mrr_at_1
      value: 20.647
    - type: mrr_at_10
      value: 27.858
    - type: mrr_at_100
      value: 28.743999999999996
    - type: mrr_at_1000
      value: 28.819
    - type: mrr_at_3
      value: 25.769
    - type: mrr_at_5
      value: 26.964
    - type: ndcg_at_1
      value: 20.647
    - type: ndcg_at_10
      value: 28.849999999999998
    - type: ndcg_at_100
      value: 33.849000000000004
    - type: ndcg_at_1000
      value: 36.802
    - type: ndcg_at_3
      value: 24.799
    - type: ndcg_at_5
      value: 26.682
    - type: precision_at_1
      value: 20.647
    - type: precision_at_10
      value: 5.2170000000000005
    - type: precision_at_100
      value: 0.906
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 11.769
    - type: precision_at_5
      value: 8.486
    - type: recall_at_1
      value: 17.122
    - type: recall_at_10
      value: 38.999
    - type: recall_at_100
      value: 61.467000000000006
    - type: recall_at_1000
      value: 82.716
    - type: recall_at_3
      value: 27.601
    - type: recall_at_5
      value: 32.471
    - type: map_at_1
      value: 24.396
    - type: map_at_10
      value: 33.415
    - type: map_at_100
      value: 34.521
    - type: map_at_1000
      value: 34.631
    - type: map_at_3
      value: 30.703999999999997
    - type: map_at_5
      value: 32.166
    - type: mrr_at_1
      value: 28.825
    - type: mrr_at_10
      value: 37.397000000000006
    - type: mrr_at_100
      value: 38.286
    - type: mrr_at_1000
      value: 38.346000000000004
    - type: mrr_at_3
      value: 35.028
    - type: mrr_at_5
      value: 36.32
    - type: ndcg_at_1
      value: 28.825
    - type: ndcg_at_10
      value: 38.656
    - type: ndcg_at_100
      value: 43.856
    - type: ndcg_at_1000
      value: 46.31
    - type: ndcg_at_3
      value: 33.793
    - type: ndcg_at_5
      value: 35.909
    - type: precision_at_1
      value: 28.825
    - type: precision_at_10
      value: 6.567
    - type: precision_at_100
      value: 1.0330000000000001
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 15.516
    - type: precision_at_5
      value: 10.914
    - type: recall_at_1
      value: 24.396
    - type: recall_at_10
      value: 50.747
    - type: recall_at_100
      value: 73.477
    - type: recall_at_1000
      value: 90.801
    - type: recall_at_3
      value: 37.1
    - type: recall_at_5
      value: 42.589
    - type: map_at_1
      value: 25.072
    - type: map_at_10
      value: 34.307
    - type: map_at_100
      value: 35.725
    - type: map_at_1000
      value: 35.943999999999996
    - type: map_at_3
      value: 30.906
    - type: map_at_5
      value: 32.818000000000005
    - type: mrr_at_1
      value: 29.644
    - type: mrr_at_10
      value: 38.673
    - type: mrr_at_100
      value: 39.459
    - type: mrr_at_1000
      value: 39.527
    - type: mrr_at_3
      value: 35.771
    - type: mrr_at_5
      value: 37.332
    - type: ndcg_at_1
      value: 29.644
    - type: ndcg_at_10
      value: 40.548
    - type: ndcg_at_100
      value: 45.678999999999995
    - type: ndcg_at_1000
      value: 48.488
    - type: ndcg_at_3
      value: 34.887
    - type: ndcg_at_5
      value: 37.543
    - type: precision_at_1
      value: 29.644
    - type: precision_at_10
      value: 7.688000000000001
    - type: precision_at_100
      value: 1.482
    - type: precision_at_1000
      value: 0.23600000000000002
    - type: precision_at_3
      value: 16.206
    - type: precision_at_5
      value: 12.016
    - type: recall_at_1
      value: 25.072
    - type: recall_at_10
      value: 53.478
    - type: recall_at_100
      value: 76.07300000000001
    - type: recall_at_1000
      value: 93.884
    - type: recall_at_3
      value: 37.583
    - type: recall_at_5
      value: 44.464
    - type: map_at_1
      value: 20.712
    - type: map_at_10
      value: 27.467999999999996
    - type: map_at_100
      value: 28.502
    - type: map_at_1000
      value: 28.610000000000003
    - type: map_at_3
      value: 24.887999999999998
    - type: map_at_5
      value: 26.273999999999997
    - type: mrr_at_1
      value: 22.736
    - type: mrr_at_10
      value: 29.553
    - type: mrr_at_100
      value: 30.485
    - type: mrr_at_1000
      value: 30.56
    - type: mrr_at_3
      value: 27.078999999999997
    - type: mrr_at_5
      value: 28.401
    - type: ndcg_at_1
      value: 22.736
    - type: ndcg_at_10
      value: 32.023
    - type: ndcg_at_100
      value: 37.158
    - type: ndcg_at_1000
      value: 39.823
    - type: ndcg_at_3
      value: 26.951999999999998
    - type: ndcg_at_5
      value: 29.281000000000002
    - type: precision_at_1
      value: 22.736
    - type: precision_at_10
      value: 5.213
    - type: precision_at_100
      value: 0.832
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 11.459999999999999
    - type: precision_at_5
      value: 8.244
    - type: recall_at_1
      value: 20.712
    - type: recall_at_10
      value: 44.057
    - type: recall_at_100
      value: 67.944
    - type: recall_at_1000
      value: 87.925
    - type: recall_at_3
      value: 30.305
    - type: recall_at_5
      value: 36.071999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.181999999999999
    - type: map_at_10
      value: 16.66
    - type: map_at_100
      value: 18.273
    - type: map_at_1000
      value: 18.45
    - type: map_at_3
      value: 14.141
    - type: map_at_5
      value: 15.455
    - type: mrr_at_1
      value: 22.15
    - type: mrr_at_10
      value: 32.062000000000005
    - type: mrr_at_100
      value: 33.116
    - type: mrr_at_1000
      value: 33.168
    - type: mrr_at_3
      value: 28.827
    - type: mrr_at_5
      value: 30.892999999999997
    - type: ndcg_at_1
      value: 22.15
    - type: ndcg_at_10
      value: 23.532
    - type: ndcg_at_100
      value: 30.358
    - type: ndcg_at_1000
      value: 33.783
    - type: ndcg_at_3
      value: 19.222
    - type: ndcg_at_5
      value: 20.919999999999998
    - type: precision_at_1
      value: 22.15
    - type: precision_at_10
      value: 7.185999999999999
    - type: precision_at_100
      value: 1.433
    - type: precision_at_1000
      value: 0.207
    - type: precision_at_3
      value: 13.941
    - type: precision_at_5
      value: 10.906
    - type: recall_at_1
      value: 10.181999999999999
    - type: recall_at_10
      value: 28.104000000000003
    - type: recall_at_100
      value: 51.998999999999995
    - type: recall_at_1000
      value: 71.311
    - type: recall_at_3
      value: 17.698
    - type: recall_at_5
      value: 22.262999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.669
    - type: map_at_10
      value: 15.552
    - type: map_at_100
      value: 21.865000000000002
    - type: map_at_1000
      value: 23.268
    - type: map_at_3
      value: 11.309
    - type: map_at_5
      value: 13.084000000000001
    - type: mrr_at_1
      value: 55.50000000000001
    - type: mrr_at_10
      value: 66.46600000000001
    - type: mrr_at_100
      value: 66.944
    - type: mrr_at_1000
      value: 66.956
    - type: mrr_at_3
      value: 64.542
    - type: mrr_at_5
      value: 65.717
    - type: ndcg_at_1
      value: 44.75
    - type: ndcg_at_10
      value: 35.049
    - type: ndcg_at_100
      value: 39.073
    - type: ndcg_at_1000
      value: 46.208
    - type: ndcg_at_3
      value: 39.525
    - type: ndcg_at_5
      value: 37.156
    - type: precision_at_1
      value: 55.50000000000001
    - type: precision_at_10
      value: 27.800000000000004
    - type: precision_at_100
      value: 9.013
    - type: precision_at_1000
      value: 1.8800000000000001
    - type: precision_at_3
      value: 42.667
    - type: precision_at_5
      value: 36.0
    - type: recall_at_1
      value: 6.669
    - type: recall_at_10
      value: 21.811
    - type: recall_at_100
      value: 45.112
    - type: recall_at_1000
      value: 67.806
    - type: recall_at_3
      value: 13.373
    - type: recall_at_5
      value: 16.615
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 48.769999999999996
    - type: f1
      value: 42.91448356376592
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 54.013
    - type: map_at_10
      value: 66.239
    - type: map_at_100
      value: 66.62599999999999
    - type: map_at_1000
      value: 66.644
    - type: map_at_3
      value: 63.965
    - type: map_at_5
      value: 65.45400000000001
    - type: mrr_at_1
      value: 58.221000000000004
    - type: mrr_at_10
      value: 70.43700000000001
    - type: mrr_at_100
      value: 70.744
    - type: mrr_at_1000
      value: 70.75099999999999
    - type: mrr_at_3
      value: 68.284
    - type: mrr_at_5
      value: 69.721
    - type: ndcg_at_1
      value: 58.221000000000004
    - type: ndcg_at_10
      value: 72.327
    - type: ndcg_at_100
      value: 73.953
    - type: ndcg_at_1000
      value: 74.312
    - type: ndcg_at_3
      value: 68.062
    - type: ndcg_at_5
      value: 70.56400000000001
    - type: precision_at_1
      value: 58.221000000000004
    - type: precision_at_10
      value: 9.521
    - type: precision_at_100
      value: 1.045
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 27.348
    - type: precision_at_5
      value: 17.794999999999998
    - type: recall_at_1
      value: 54.013
    - type: recall_at_10
      value: 86.957
    - type: recall_at_100
      value: 93.911
    - type: recall_at_1000
      value: 96.38
    - type: recall_at_3
      value: 75.555
    - type: recall_at_5
      value: 81.671
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 21.254
    - type: map_at_10
      value: 33.723
    - type: map_at_100
      value: 35.574
    - type: map_at_1000
      value: 35.730000000000004
    - type: map_at_3
      value: 29.473
    - type: map_at_5
      value: 31.543
    - type: mrr_at_1
      value: 41.358
    - type: mrr_at_10
      value: 49.498
    - type: mrr_at_100
      value: 50.275999999999996
    - type: mrr_at_1000
      value: 50.308
    - type: mrr_at_3
      value: 47.016000000000005
    - type: mrr_at_5
      value: 48.336
    - type: ndcg_at_1
      value: 41.358
    - type: ndcg_at_10
      value: 41.579
    - type: ndcg_at_100
      value: 48.455
    - type: ndcg_at_1000
      value: 51.165000000000006
    - type: ndcg_at_3
      value: 37.681
    - type: ndcg_at_5
      value: 38.49
    - type: precision_at_1
      value: 41.358
    - type: precision_at_10
      value: 11.543000000000001
    - type: precision_at_100
      value: 1.87
    - type: precision_at_1000
      value: 0.23600000000000002
    - type: precision_at_3
      value: 24.743000000000002
    - type: precision_at_5
      value: 17.994
    - type: recall_at_1
      value: 21.254
    - type: recall_at_10
      value: 48.698
    - type: recall_at_100
      value: 74.588
    - type: recall_at_1000
      value: 91.00200000000001
    - type: recall_at_3
      value: 33.939
    - type: recall_at_5
      value: 39.367000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 35.922
    - type: map_at_10
      value: 52.32599999999999
    - type: map_at_100
      value: 53.18000000000001
    - type: map_at_1000
      value: 53.245
    - type: map_at_3
      value: 49.294
    - type: map_at_5
      value: 51.202999999999996
    - type: mrr_at_1
      value: 71.843
    - type: mrr_at_10
      value: 78.24600000000001
    - type: mrr_at_100
      value: 78.515
    - type: mrr_at_1000
      value: 78.527
    - type: mrr_at_3
      value: 77.17500000000001
    - type: mrr_at_5
      value: 77.852
    - type: ndcg_at_1
      value: 71.843
    - type: ndcg_at_10
      value: 61.379
    - type: ndcg_at_100
      value: 64.535
    - type: ndcg_at_1000
      value: 65.888
    - type: ndcg_at_3
      value: 56.958
    - type: ndcg_at_5
      value: 59.434
    - type: precision_at_1
      value: 71.843
    - type: precision_at_10
      value: 12.686
    - type: precision_at_100
      value: 1.517
    - type: precision_at_1000
      value: 0.16999999999999998
    - type: precision_at_3
      value: 35.778
    - type: precision_at_5
      value: 23.422
    - type: recall_at_1
      value: 35.922
    - type: recall_at_10
      value: 63.43
    - type: recall_at_100
      value: 75.868
    - type: recall_at_1000
      value: 84.88900000000001
    - type: recall_at_3
      value: 53.666000000000004
    - type: recall_at_5
      value: 58.555
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 79.4408
    - type: ap
      value: 73.52820871620366
    - type: f1
      value: 79.36240238685001
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 21.826999999999998
    - type: map_at_10
      value: 34.04
    - type: map_at_100
      value: 35.226
    - type: map_at_1000
      value: 35.275
    - type: map_at_3
      value: 30.165999999999997
    - type: map_at_5
      value: 32.318000000000005
    - type: mrr_at_1
      value: 22.464000000000002
    - type: mrr_at_10
      value: 34.631
    - type: mrr_at_100
      value: 35.752
    - type: mrr_at_1000
      value: 35.795
    - type: mrr_at_3
      value: 30.798
    - type: mrr_at_5
      value: 32.946999999999996
    - type: ndcg_at_1
      value: 22.464000000000002
    - type: ndcg_at_10
      value: 40.919
    - type: ndcg_at_100
      value: 46.632
    - type: ndcg_at_1000
      value: 47.833
    - type: ndcg_at_3
      value: 32.992
    - type: ndcg_at_5
      value: 36.834
    - type: precision_at_1
      value: 22.464000000000002
    - type: precision_at_10
      value: 6.494
    - type: precision_at_100
      value: 0.9369999999999999
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.021
    - type: precision_at_5
      value: 10.347000000000001
    - type: recall_at_1
      value: 21.826999999999998
    - type: recall_at_10
      value: 62.132
    - type: recall_at_100
      value: 88.55199999999999
    - type: recall_at_1000
      value: 97.707
    - type: recall_at_3
      value: 40.541
    - type: recall_at_5
      value: 49.739
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 95.68399452804377
    - type: f1
      value: 95.25490609832268
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 83.15321477428182
    - type: f1
      value: 60.35476439087966
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 71.92669804976462
    - type: f1
      value: 69.22815107207565
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 74.4855413584398
    - type: f1
      value: 72.92107516103387
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.412679360205544
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 28.09211869875204
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.540919056982545
    - type: mrr
      value: 31.529904607063536
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.745
    - type: map_at_10
      value: 12.013
    - type: map_at_100
      value: 15.040000000000001
    - type: map_at_1000
      value: 16.427
    - type: map_at_3
      value: 8.841000000000001
    - type: map_at_5
      value: 10.289
    - type: mrr_at_1
      value: 45.201
    - type: mrr_at_10
      value: 53.483999999999995
    - type: mrr_at_100
      value: 54.20700000000001
    - type: mrr_at_1000
      value: 54.252
    - type: mrr_at_3
      value: 51.29
    - type: mrr_at_5
      value: 52.73
    - type: ndcg_at_1
      value: 43.808
    - type: ndcg_at_10
      value: 32.445
    - type: ndcg_at_100
      value: 30.031000000000002
    - type: ndcg_at_1000
      value: 39.007
    - type: ndcg_at_3
      value: 37.204
    - type: ndcg_at_5
      value: 35.07
    - type: precision_at_1
      value: 45.201
    - type: precision_at_10
      value: 23.684
    - type: precision_at_100
      value: 7.600999999999999
    - type: precision_at_1000
      value: 2.043
    - type: precision_at_3
      value: 33.953
    - type: precision_at_5
      value: 29.412
    - type: recall_at_1
      value: 5.745
    - type: recall_at_10
      value: 16.168
    - type: recall_at_100
      value: 30.875999999999998
    - type: recall_at_1000
      value: 62.686
    - type: recall_at_3
      value: 9.75
    - type: recall_at_5
      value: 12.413
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 37.828
    - type: map_at_10
      value: 53.239000000000004
    - type: map_at_100
      value: 54.035999999999994
    - type: map_at_1000
      value: 54.067
    - type: map_at_3
      value: 49.289
    - type: map_at_5
      value: 51.784
    - type: mrr_at_1
      value: 42.497
    - type: mrr_at_10
      value: 55.916999999999994
    - type: mrr_at_100
      value: 56.495
    - type: mrr_at_1000
      value: 56.516999999999996
    - type: mrr_at_3
      value: 52.800000000000004
    - type: mrr_at_5
      value: 54.722
    - type: ndcg_at_1
      value: 42.468
    - type: ndcg_at_10
      value: 60.437
    - type: ndcg_at_100
      value: 63.731
    - type: ndcg_at_1000
      value: 64.41799999999999
    - type: ndcg_at_3
      value: 53.230999999999995
    - type: ndcg_at_5
      value: 57.26
    - type: precision_at_1
      value: 42.468
    - type: precision_at_10
      value: 9.47
    - type: precision_at_100
      value: 1.1360000000000001
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 23.724999999999998
    - type: precision_at_5
      value: 16.593
    - type: recall_at_1
      value: 37.828
    - type: recall_at_10
      value: 79.538
    - type: recall_at_100
      value: 93.646
    - type: recall_at_1000
      value: 98.72999999999999
    - type: recall_at_3
      value: 61.134
    - type: recall_at_5
      value: 70.377
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.548
    - type: map_at_10
      value: 84.466
    - type: map_at_100
      value: 85.10600000000001
    - type: map_at_1000
      value: 85.123
    - type: map_at_3
      value: 81.57600000000001
    - type: map_at_5
      value: 83.399
    - type: mrr_at_1
      value: 81.24
    - type: mrr_at_10
      value: 87.457
    - type: mrr_at_100
      value: 87.574
    - type: mrr_at_1000
      value: 87.575
    - type: mrr_at_3
      value: 86.507
    - type: mrr_at_5
      value: 87.205
    - type: ndcg_at_1
      value: 81.25
    - type: ndcg_at_10
      value: 88.203
    - type: ndcg_at_100
      value: 89.457
    - type: ndcg_at_1000
      value: 89.563
    - type: ndcg_at_3
      value: 85.465
    - type: ndcg_at_5
      value: 87.007
    - type: precision_at_1
      value: 81.25
    - type: precision_at_10
      value: 13.373
    - type: precision_at_100
      value: 1.5270000000000001
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.417
    - type: precision_at_5
      value: 24.556
    - type: recall_at_1
      value: 70.548
    - type: recall_at_10
      value: 95.208
    - type: recall_at_100
      value: 99.514
    - type: recall_at_1000
      value: 99.988
    - type: recall_at_3
      value: 87.214
    - type: recall_at_5
      value: 91.696
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 53.04822095496839
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 60.30778476474675
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.692
    - type: map_at_10
      value: 11.766
    - type: map_at_100
      value: 13.904
    - type: map_at_1000
      value: 14.216999999999999
    - type: map_at_3
      value: 8.245
    - type: map_at_5
      value: 9.92
    - type: mrr_at_1
      value: 23.0
    - type: mrr_at_10
      value: 33.78
    - type: mrr_at_100
      value: 34.922
    - type: mrr_at_1000
      value: 34.973
    - type: mrr_at_3
      value: 30.2
    - type: mrr_at_5
      value: 32.565
    - type: ndcg_at_1
      value: 23.0
    - type: ndcg_at_10
      value: 19.863
    - type: ndcg_at_100
      value: 28.141
    - type: ndcg_at_1000
      value: 33.549
    - type: ndcg_at_3
      value: 18.434
    - type: ndcg_at_5
      value: 16.384
    - type: precision_at_1
      value: 23.0
    - type: precision_at_10
      value: 10.39
    - type: precision_at_100
      value: 2.235
    - type: precision_at_1000
      value: 0.35300000000000004
    - type: precision_at_3
      value: 17.133000000000003
    - type: precision_at_5
      value: 14.44
    - type: recall_at_1
      value: 4.692
    - type: recall_at_10
      value: 21.025
    - type: recall_at_100
      value: 45.324999999999996
    - type: recall_at_1000
      value: 71.675
    - type: recall_at_3
      value: 10.440000000000001
    - type: recall_at_5
      value: 14.64
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 84.96178184892842
    - type: cos_sim_spearman
      value: 79.6487740813199
    - type: euclidean_pearson
      value: 82.06661161625023
    - type: euclidean_spearman
      value: 79.64876769031183
    - type: manhattan_pearson
      value: 82.07061164575131
    - type: manhattan_spearman
      value: 79.65197039464537
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 84.15305604100027
    - type: cos_sim_spearman
      value: 74.27447427941591
    - type: euclidean_pearson
      value: 80.52737337565307
    - type: euclidean_spearman
      value: 74.27416077132192
    - type: manhattan_pearson
      value: 80.53728571140387
    - type: manhattan_spearman
      value: 74.28853605753457
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 83.44386080639279
    - type: cos_sim_spearman
      value: 84.17947648159536
    - type: euclidean_pearson
      value: 83.34145388129387
    - type: euclidean_spearman
      value: 84.17947648159536
    - type: manhattan_pearson
      value: 83.30699061927966
    - type: manhattan_spearman
      value: 84.18125737380451
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 81.57392220985612
    - type: cos_sim_spearman
      value: 78.80745014464101
    - type: euclidean_pearson
      value: 80.01660371487199
    - type: euclidean_spearman
      value: 78.80741240102256
    - type: manhattan_pearson
      value: 79.96810779507953
    - type: manhattan_spearman
      value: 78.75600400119448
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.85421063026625
    - type: cos_sim_spearman
      value: 87.55320285299192
    - type: euclidean_pearson
      value: 86.69750143323517
    - type: euclidean_spearman
      value: 87.55320284326378
    - type: manhattan_pearson
      value: 86.63379169960379
    - type: manhattan_spearman
      value: 87.4815029877984
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 84.31314130411842
    - type: cos_sim_spearman
      value: 85.3489588181433
    - type: euclidean_pearson
      value: 84.13240933463535
    - type: euclidean_spearman
      value: 85.34902871403281
    - type: manhattan_pearson
      value: 84.01183086503559
    - type: manhattan_spearman
      value: 85.19316703166102
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 89.09979781689536
    - type: cos_sim_spearman
      value: 88.87813323759015
    - type: euclidean_pearson
      value: 88.65413031123792
    - type: euclidean_spearman
      value: 88.87813323759015
    - type: manhattan_pearson
      value: 88.61818758256024
    - type: manhattan_spearman
      value: 88.81044100494604
  - 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: 62.30693258111531
    - type: cos_sim_spearman
      value: 62.195516523251946
    - type: euclidean_pearson
      value: 62.951283701049476
    - type: euclidean_spearman
      value: 62.195516523251946
    - type: manhattan_pearson
      value: 63.068322281439535
    - type: manhattan_spearman
      value: 62.10621171028406
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 84.27092833763909
    - type: cos_sim_spearman
      value: 84.84429717949759
    - type: euclidean_pearson
      value: 84.8516966060792
    - type: euclidean_spearman
      value: 84.84429717949759
    - type: manhattan_pearson
      value: 84.82203139242881
    - type: manhattan_spearman
      value: 84.8358503952945
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 83.10290863981409
    - type: mrr
      value: 95.31168450286097
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 52.161
    - type: map_at_10
      value: 62.138000000000005
    - type: map_at_100
      value: 62.769
    - type: map_at_1000
      value: 62.812
    - type: map_at_3
      value: 59.111000000000004
    - type: map_at_5
      value: 60.995999999999995
    - type: mrr_at_1
      value: 55.333
    - type: mrr_at_10
      value: 63.504000000000005
    - type: mrr_at_100
      value: 64.036
    - type: mrr_at_1000
      value: 64.08
    - type: mrr_at_3
      value: 61.278
    - type: mrr_at_5
      value: 62.778
    - type: ndcg_at_1
      value: 55.333
    - type: ndcg_at_10
      value: 66.678
    - type: ndcg_at_100
      value: 69.415
    - type: ndcg_at_1000
      value: 70.453
    - type: ndcg_at_3
      value: 61.755
    - type: ndcg_at_5
      value: 64.546
    - type: precision_at_1
      value: 55.333
    - type: precision_at_10
      value: 9.033
    - type: precision_at_100
      value: 1.043
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 24.221999999999998
    - type: precision_at_5
      value: 16.333000000000002
    - type: recall_at_1
      value: 52.161
    - type: recall_at_10
      value: 79.156
    - type: recall_at_100
      value: 91.333
    - type: recall_at_1000
      value: 99.333
    - type: recall_at_3
      value: 66.43299999999999
    - type: recall_at_5
      value: 73.272
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.81287128712871
    - type: cos_sim_ap
      value: 95.30034785910676
    - type: cos_sim_f1
      value: 90.28629856850716
    - type: cos_sim_precision
      value: 92.36401673640168
    - type: cos_sim_recall
      value: 88.3
    - type: dot_accuracy
      value: 99.81287128712871
    - type: dot_ap
      value: 95.30034785910676
    - type: dot_f1
      value: 90.28629856850716
    - type: dot_precision
      value: 92.36401673640168
    - type: dot_recall
      value: 88.3
    - type: euclidean_accuracy
      value: 99.81287128712871
    - type: euclidean_ap
      value: 95.30034785910676
    - type: euclidean_f1
      value: 90.28629856850716
    - type: euclidean_precision
      value: 92.36401673640168
    - type: euclidean_recall
      value: 88.3
    - type: manhattan_accuracy
      value: 99.80990099009901
    - type: manhattan_ap
      value: 95.26880751950654
    - type: manhattan_f1
      value: 90.22177419354838
    - type: manhattan_precision
      value: 90.95528455284553
    - type: manhattan_recall
      value: 89.5
    - type: max_accuracy
      value: 99.81287128712871
    - type: max_ap
      value: 95.30034785910676
    - type: max_f1
      value: 90.28629856850716
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 58.518662504351184
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 34.96168178378587
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 52.04862593471896
    - type: mrr
      value: 52.97238402936932
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.092545236479946
    - type: cos_sim_spearman
      value: 31.599851000175498
    - type: dot_pearson
      value: 30.092542723901676
    - type: dot_spearman
      value: 31.599851000175498
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.189
    - type: map_at_10
      value: 1.662
    - type: map_at_100
      value: 9.384
    - type: map_at_1000
      value: 22.669
    - type: map_at_3
      value: 0.5559999999999999
    - type: map_at_5
      value: 0.9039999999999999
    - type: mrr_at_1
      value: 68.0
    - type: mrr_at_10
      value: 81.01899999999999
    - type: mrr_at_100
      value: 81.01899999999999
    - type: mrr_at_1000
      value: 81.01899999999999
    - type: mrr_at_3
      value: 79.333
    - type: mrr_at_5
      value: 80.733
    - type: ndcg_at_1
      value: 63.0
    - type: ndcg_at_10
      value: 65.913
    - type: ndcg_at_100
      value: 51.895
    - type: ndcg_at_1000
      value: 46.967
    - type: ndcg_at_3
      value: 65.49199999999999
    - type: ndcg_at_5
      value: 66.69699999999999
    - type: precision_at_1
      value: 68.0
    - type: precision_at_10
      value: 71.6
    - type: precision_at_100
      value: 53.66
    - type: precision_at_1000
      value: 21.124000000000002
    - type: precision_at_3
      value: 72.667
    - type: precision_at_5
      value: 74.0
    - type: recall_at_1
      value: 0.189
    - type: recall_at_10
      value: 1.913
    - type: recall_at_100
      value: 12.601999999999999
    - type: recall_at_1000
      value: 44.296
    - type: recall_at_3
      value: 0.605
    - type: recall_at_5
      value: 1.018
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.701
    - type: map_at_10
      value: 10.445
    - type: map_at_100
      value: 17.324
    - type: map_at_1000
      value: 19.161
    - type: map_at_3
      value: 5.497
    - type: map_at_5
      value: 7.278
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 45.534
    - type: mrr_at_100
      value: 45.792
    - type: mrr_at_1000
      value: 45.806999999999995
    - type: mrr_at_3
      value: 37.755
    - type: mrr_at_5
      value: 43.469
    - type: ndcg_at_1
      value: 26.531
    - type: ndcg_at_10
      value: 26.235000000000003
    - type: ndcg_at_100
      value: 39.17
    - type: ndcg_at_1000
      value: 51.038
    - type: ndcg_at_3
      value: 23.625
    - type: ndcg_at_5
      value: 24.338
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 24.285999999999998
    - type: precision_at_100
      value: 8.224
    - type: precision_at_1000
      value: 1.6179999999999999
    - type: precision_at_3
      value: 24.490000000000002
    - type: precision_at_5
      value: 24.898
    - type: recall_at_1
      value: 2.701
    - type: recall_at_10
      value: 17.997
    - type: recall_at_100
      value: 51.766999999999996
    - type: recall_at_1000
      value: 87.863
    - type: recall_at_3
      value: 6.295000000000001
    - type: recall_at_5
      value: 9.993
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 73.3474
    - type: ap
      value: 15.393431414459924
    - type: f1
      value: 56.466681887882416
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.062818336163
    - type: f1
      value: 62.11230840463252
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 42.464892820845115
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 86.15962329379508
    - type: cos_sim_ap
      value: 74.73674057919256
    - type: cos_sim_f1
      value: 68.81245642574947
    - type: cos_sim_precision
      value: 61.48255813953488
    - type: cos_sim_recall
      value: 78.12664907651715
    - type: dot_accuracy
      value: 86.15962329379508
    - type: dot_ap
      value: 74.7367634988281
    - type: dot_f1
      value: 68.81245642574947
    - type: dot_precision
      value: 61.48255813953488
    - type: dot_recall
      value: 78.12664907651715
    - type: euclidean_accuracy
      value: 86.15962329379508
    - type: euclidean_ap
      value: 74.7367761466634
    - type: euclidean_f1
      value: 68.81245642574947
    - type: euclidean_precision
      value: 61.48255813953488
    - type: euclidean_recall
      value: 78.12664907651715
    - type: manhattan_accuracy
      value: 86.21326816474935
    - type: manhattan_ap
      value: 74.64416473733951
    - type: manhattan_f1
      value: 68.80924855491331
    - type: manhattan_precision
      value: 61.23456790123457
    - type: manhattan_recall
      value: 78.52242744063325
    - type: max_accuracy
      value: 86.21326816474935
    - type: max_ap
      value: 74.7367761466634
    - type: max_f1
      value: 68.81245642574947
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.97620988085536
    - type: cos_sim_ap
      value: 86.08680845745758
    - type: cos_sim_f1
      value: 78.02793637114438
    - type: cos_sim_precision
      value: 73.11082699683736
    - type: cos_sim_recall
      value: 83.65414228518632
    - type: dot_accuracy
      value: 88.97620988085536
    - type: dot_ap
      value: 86.08681149437946
    - type: dot_f1
      value: 78.02793637114438
    - type: dot_precision
      value: 73.11082699683736
    - type: dot_recall
      value: 83.65414228518632
    - type: euclidean_accuracy
      value: 88.97620988085536
    - type: euclidean_ap
      value: 86.08681215460771
    - type: euclidean_f1
      value: 78.02793637114438
    - type: euclidean_precision
      value: 73.11082699683736
    - type: euclidean_recall
      value: 83.65414228518632
    - type: manhattan_accuracy
      value: 88.88888888888889
    - type: manhattan_ap
      value: 86.02916327562438
    - type: manhattan_f1
      value: 78.02063045516843
    - type: manhattan_precision
      value: 73.38851947346994
    - type: manhattan_recall
      value: 83.2768709578072
    - type: max_accuracy
      value: 88.97620988085536
    - type: max_ap
      value: 86.08681215460771
    - type: max_f1
      value: 78.02793637114438
---

# ngxson/jina-embeddings-v2-base-en-Q8_0-GGUF
This model was converted to GGUF format from [`jinaai/jina-embeddings-v2-base-en`](https://huggingface.co/jinaai/jina-embeddings-v2-base-en) 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/jinaai/jina-embeddings-v2-base-en) 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 ngxson/jina-embeddings-v2-base-en-Q8_0-GGUF --hf-file jina-embeddings-v2-base-en-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo ngxson/jina-embeddings-v2-base-en-Q8_0-GGUF --hf-file jina-embeddings-v2-base-en-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 ngxson/jina-embeddings-v2-base-en-Q8_0-GGUF --hf-file jina-embeddings-v2-base-en-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo ngxson/jina-embeddings-v2-base-en-Q8_0-GGUF --hf-file jina-embeddings-v2-base-en-q8_0.gguf -c 2048
```
