sentence-transformers gguf feature-extraction sentence-similarity mteb llama-cpp gguf-my-repo en dataset:jinaai/negation-dataset base_model:jinaai/jina-embeddings-v2-small-en base_model:quantized:jinaai/jina-embeddings-v2-small-en license:apache-2.0 model-index autotrain_compatible region:us
---
base_model: jinaai/jina-embeddings-v2-small-en
datasets:
- jinaai/negation-dataset
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-s-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: 71.35820895522387
    - type: ap
      value: 33.99931933598115
    - type: f1
      value: 65.3853685535555
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 82.90140000000001
    - type: ap
      value: 78.01434597815617
    - type: f1
      value: 82.83357802722676
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 40.88999999999999
    - type: f1
      value: 39.209432767163456
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 23.257
    - type: map_at_10
      value: 37.946000000000005
    - type: map_at_100
      value: 39.17
    - type: map_at_1000
      value: 39.181
    - type: map_at_3
      value: 32.99
    - type: map_at_5
      value: 35.467999999999996
    - type: mrr_at_1
      value: 23.541999999999998
    - type: mrr_at_10
      value: 38.057
    - type: mrr_at_100
      value: 39.289
    - type: mrr_at_1000
      value: 39.299
    - type: mrr_at_3
      value: 33.096
    - type: mrr_at_5
      value: 35.628
    - type: ndcg_at_1
      value: 23.257
    - type: ndcg_at_10
      value: 46.729
    - type: ndcg_at_100
      value: 51.900999999999996
    - type: ndcg_at_1000
      value: 52.16
    - type: ndcg_at_3
      value: 36.323
    - type: ndcg_at_5
      value: 40.766999999999996
    - type: precision_at_1
      value: 23.257
    - type: precision_at_10
      value: 7.510999999999999
    - type: precision_at_100
      value: 0.976
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.339
    - type: precision_at_5
      value: 11.350999999999999
    - type: recall_at_1
      value: 23.257
    - type: recall_at_10
      value: 75.107
    - type: recall_at_100
      value: 97.58200000000001
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 46.017
    - type: recall_at_5
      value: 56.757000000000005
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 44.02420878391967
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 35.16136856000258
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 59.61809790513646
    - type: mrr
      value: 73.07215406938397
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.0167350090749
    - type: cos_sim_spearman
      value: 80.51569002630401
    - type: euclidean_pearson
      value: 81.46820525099726
    - type: euclidean_spearman
      value: 80.51569002630401
    - type: manhattan_pearson
      value: 81.35596555056757
    - type: manhattan_spearman
      value: 80.12592210903303
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 78.25
    - type: f1
      value: 77.34950913540605
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.57238596005698
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 29.066444306196683
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.891000000000002
    - type: map_at_10
      value: 42.772
    - type: map_at_100
      value: 44.108999999999995
    - type: map_at_1000
      value: 44.236
    - type: map_at_3
      value: 39.289
    - type: map_at_5
      value: 41.113
    - type: mrr_at_1
      value: 39.342
    - type: mrr_at_10
      value: 48.852000000000004
    - type: mrr_at_100
      value: 49.534
    - type: mrr_at_1000
      value: 49.582
    - type: mrr_at_3
      value: 46.089999999999996
    - type: mrr_at_5
      value: 47.685
    - type: ndcg_at_1
      value: 39.342
    - type: ndcg_at_10
      value: 48.988
    - type: ndcg_at_100
      value: 53.854
    - type: ndcg_at_1000
      value: 55.955
    - type: ndcg_at_3
      value: 43.877
    - type: ndcg_at_5
      value: 46.027
    - type: precision_at_1
      value: 39.342
    - type: precision_at_10
      value: 9.285
    - type: precision_at_100
      value: 1.488
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 20.696
    - type: precision_at_5
      value: 14.878
    - type: recall_at_1
      value: 31.891000000000002
    - type: recall_at_10
      value: 60.608
    - type: recall_at_100
      value: 81.025
    - type: recall_at_1000
      value: 94.883
    - type: recall_at_3
      value: 45.694
    - type: recall_at_5
      value: 51.684
    - type: map_at_1
      value: 28.778
    - type: map_at_10
      value: 37.632
    - type: map_at_100
      value: 38.800000000000004
    - type: map_at_1000
      value: 38.934999999999995
    - type: map_at_3
      value: 35.293
    - type: map_at_5
      value: 36.547000000000004
    - type: mrr_at_1
      value: 35.35
    - type: mrr_at_10
      value: 42.936
    - type: mrr_at_100
      value: 43.69
    - type: mrr_at_1000
      value: 43.739
    - type: mrr_at_3
      value: 41.062
    - type: mrr_at_5
      value: 42.097
    - type: ndcg_at_1
      value: 35.35
    - type: ndcg_at_10
      value: 42.528
    - type: ndcg_at_100
      value: 46.983000000000004
    - type: ndcg_at_1000
      value: 49.187999999999995
    - type: ndcg_at_3
      value: 39.271
    - type: ndcg_at_5
      value: 40.654
    - type: precision_at_1
      value: 35.35
    - type: precision_at_10
      value: 7.828
    - type: precision_at_100
      value: 1.3010000000000002
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 18.96
    - type: precision_at_5
      value: 13.120999999999999
    - type: recall_at_1
      value: 28.778
    - type: recall_at_10
      value: 50.775000000000006
    - type: recall_at_100
      value: 69.66799999999999
    - type: recall_at_1000
      value: 83.638
    - type: recall_at_3
      value: 40.757
    - type: recall_at_5
      value: 44.86
    - type: map_at_1
      value: 37.584
    - type: map_at_10
      value: 49.69
    - type: map_at_100
      value: 50.639
    - type: map_at_1000
      value: 50.702999999999996
    - type: map_at_3
      value: 46.61
    - type: map_at_5
      value: 48.486000000000004
    - type: mrr_at_1
      value: 43.009
    - type: mrr_at_10
      value: 52.949999999999996
    - type: mrr_at_100
      value: 53.618
    - type: mrr_at_1000
      value: 53.65299999999999
    - type: mrr_at_3
      value: 50.605999999999995
    - type: mrr_at_5
      value: 52.095
    - type: ndcg_at_1
      value: 43.009
    - type: ndcg_at_10
      value: 55.278000000000006
    - type: ndcg_at_100
      value: 59.134
    - type: ndcg_at_1000
      value: 60.528999999999996
    - type: ndcg_at_3
      value: 50.184
    - type: ndcg_at_5
      value: 52.919000000000004
    - type: precision_at_1
      value: 43.009
    - type: precision_at_10
      value: 8.821
    - type: precision_at_100
      value: 1.161
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 22.424
    - type: precision_at_5
      value: 15.436
    - type: recall_at_1
      value: 37.584
    - type: recall_at_10
      value: 68.514
    - type: recall_at_100
      value: 85.099
    - type: recall_at_1000
      value: 95.123
    - type: recall_at_3
      value: 55.007
    - type: recall_at_5
      value: 61.714999999999996
    - type: map_at_1
      value: 24.7
    - type: map_at_10
      value: 32.804
    - type: map_at_100
      value: 33.738
    - type: map_at_1000
      value: 33.825
    - type: map_at_3
      value: 30.639
    - type: map_at_5
      value: 31.781
    - type: mrr_at_1
      value: 26.328000000000003
    - type: mrr_at_10
      value: 34.679
    - type: mrr_at_100
      value: 35.510000000000005
    - type: mrr_at_1000
      value: 35.577999999999996
    - type: mrr_at_3
      value: 32.58
    - type: mrr_at_5
      value: 33.687
    - type: ndcg_at_1
      value: 26.328000000000003
    - type: ndcg_at_10
      value: 37.313
    - type: ndcg_at_100
      value: 42.004000000000005
    - type: ndcg_at_1000
      value: 44.232
    - type: ndcg_at_3
      value: 33.076
    - type: ndcg_at_5
      value: 34.966
    - type: precision_at_1
      value: 26.328000000000003
    - type: precision_at_10
      value: 5.627
    - type: precision_at_100
      value: 0.8410000000000001
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 14.011000000000001
    - type: precision_at_5
      value: 9.582
    - type: recall_at_1
      value: 24.7
    - type: recall_at_10
      value: 49.324
    - type: recall_at_100
      value: 71.018
    - type: recall_at_1000
      value: 87.905
    - type: recall_at_3
      value: 37.7
    - type: recall_at_5
      value: 42.281
    - type: map_at_1
      value: 14.350999999999999
    - type: map_at_10
      value: 21.745
    - type: map_at_100
      value: 22.731
    - type: map_at_1000
      value: 22.852
    - type: map_at_3
      value: 19.245
    - type: map_at_5
      value: 20.788
    - type: mrr_at_1
      value: 18.159
    - type: mrr_at_10
      value: 25.833000000000002
    - type: mrr_at_100
      value: 26.728
    - type: mrr_at_1000
      value: 26.802
    - type: mrr_at_3
      value: 23.383000000000003
    - type: mrr_at_5
      value: 24.887999999999998
    - type: ndcg_at_1
      value: 18.159
    - type: ndcg_at_10
      value: 26.518000000000004
    - type: ndcg_at_100
      value: 31.473000000000003
    - type: ndcg_at_1000
      value: 34.576
    - type: ndcg_at_3
      value: 21.907
    - type: ndcg_at_5
      value: 24.39
    - type: precision_at_1
      value: 18.159
    - type: precision_at_10
      value: 4.938
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 10.655000000000001
    - type: precision_at_5
      value: 7.985
    - type: recall_at_1
      value: 14.350999999999999
    - type: recall_at_10
      value: 37.284
    - type: recall_at_100
      value: 59.11300000000001
    - type: recall_at_1000
      value: 81.634
    - type: recall_at_3
      value: 24.753
    - type: recall_at_5
      value: 30.979
    - type: map_at_1
      value: 26.978
    - type: map_at_10
      value: 36.276
    - type: map_at_100
      value: 37.547000000000004
    - type: map_at_1000
      value: 37.678
    - type: map_at_3
      value: 33.674
    - type: map_at_5
      value: 35.119
    - type: mrr_at_1
      value: 32.916000000000004
    - type: mrr_at_10
      value: 41.798
    - type: mrr_at_100
      value: 42.72
    - type: mrr_at_1000
      value: 42.778
    - type: mrr_at_3
      value: 39.493
    - type: mrr_at_5
      value: 40.927
    - type: ndcg_at_1
      value: 32.916000000000004
    - type: ndcg_at_10
      value: 41.81
    - type: ndcg_at_100
      value: 47.284
    - type: ndcg_at_1000
      value: 49.702
    - type: ndcg_at_3
      value: 37.486999999999995
    - type: ndcg_at_5
      value: 39.597
    - type: precision_at_1
      value: 32.916000000000004
    - type: precision_at_10
      value: 7.411
    - type: precision_at_100
      value: 1.189
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 17.581
    - type: precision_at_5
      value: 12.397
    - type: recall_at_1
      value: 26.978
    - type: recall_at_10
      value: 52.869
    - type: recall_at_100
      value: 75.78399999999999
    - type: recall_at_1000
      value: 91.545
    - type: recall_at_3
      value: 40.717
    - type: recall_at_5
      value: 46.168
    - type: map_at_1
      value: 24.641
    - type: map_at_10
      value: 32.916000000000004
    - type: map_at_100
      value: 34.165
    - type: map_at_1000
      value: 34.286
    - type: map_at_3
      value: 30.335
    - type: map_at_5
      value: 31.569000000000003
    - type: mrr_at_1
      value: 30.593999999999998
    - type: mrr_at_10
      value: 38.448
    - type: mrr_at_100
      value: 39.299
    - type: mrr_at_1000
      value: 39.362
    - type: mrr_at_3
      value: 36.244
    - type: mrr_at_5
      value: 37.232
    - type: ndcg_at_1
      value: 30.593999999999998
    - type: ndcg_at_10
      value: 38.2
    - type: ndcg_at_100
      value: 43.742
    - type: ndcg_at_1000
      value: 46.217000000000006
    - type: ndcg_at_3
      value: 33.925
    - type: ndcg_at_5
      value: 35.394
    - type: precision_at_1
      value: 30.593999999999998
    - type: precision_at_10
      value: 6.895
    - type: precision_at_100
      value: 1.1320000000000001
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 16.096
    - type: precision_at_5
      value: 11.05
    - type: recall_at_1
      value: 24.641
    - type: recall_at_10
      value: 48.588
    - type: recall_at_100
      value: 72.841
    - type: recall_at_1000
      value: 89.535
    - type: recall_at_3
      value: 36.087
    - type: recall_at_5
      value: 40.346
    - type: map_at_1
      value: 24.79425
    - type: map_at_10
      value: 33.12033333333333
    - type: map_at_100
      value: 34.221333333333334
    - type: map_at_1000
      value: 34.3435
    - type: map_at_3
      value: 30.636583333333338
    - type: map_at_5
      value: 31.974083333333326
    - type: mrr_at_1
      value: 29.242416666666664
    - type: mrr_at_10
      value: 37.11675
    - type: mrr_at_100
      value: 37.93783333333334
    - type: mrr_at_1000
      value: 38.003083333333336
    - type: mrr_at_3
      value: 34.904666666666664
    - type: mrr_at_5
      value: 36.12916666666667
    - type: ndcg_at_1
      value: 29.242416666666664
    - type: ndcg_at_10
      value: 38.03416666666667
    - type: ndcg_at_100
      value: 42.86674999999999
    - type: ndcg_at_1000
      value: 45.34550000000001
    - type: ndcg_at_3
      value: 33.76466666666666
    - type: ndcg_at_5
      value: 35.668666666666674
    - type: precision_at_1
      value: 29.242416666666664
    - type: precision_at_10
      value: 6.589833333333334
    - type: precision_at_100
      value: 1.0693333333333332
    - type: precision_at_1000
      value: 0.14641666666666667
    - type: precision_at_3
      value: 15.430749999999998
    - type: precision_at_5
      value: 10.833833333333333
    - type: recall_at_1
      value: 24.79425
    - type: recall_at_10
      value: 48.582916666666655
    - type: recall_at_100
      value: 69.88499999999999
    - type: recall_at_1000
      value: 87.211
    - type: recall_at_3
      value: 36.625499999999995
    - type: recall_at_5
      value: 41.553999999999995
    - type: map_at_1
      value: 22.767
    - type: map_at_10
      value: 28.450999999999997
    - type: map_at_100
      value: 29.332
    - type: map_at_1000
      value: 29.426000000000002
    - type: map_at_3
      value: 26.379
    - type: map_at_5
      value: 27.584999999999997
    - type: mrr_at_1
      value: 25.46
    - type: mrr_at_10
      value: 30.974
    - type: mrr_at_100
      value: 31.784000000000002
    - type: mrr_at_1000
      value: 31.857999999999997
    - type: mrr_at_3
      value: 28.962
    - type: mrr_at_5
      value: 30.066
    - type: ndcg_at_1
      value: 25.46
    - type: ndcg_at_10
      value: 32.041
    - type: ndcg_at_100
      value: 36.522
    - type: ndcg_at_1000
      value: 39.101
    - type: ndcg_at_3
      value: 28.152
    - type: ndcg_at_5
      value: 30.03
    - type: precision_at_1
      value: 25.46
    - type: precision_at_10
      value: 4.893
    - type: precision_at_100
      value: 0.77
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 11.605
    - type: precision_at_5
      value: 8.19
    - type: recall_at_1
      value: 22.767
    - type: recall_at_10
      value: 40.71
    - type: recall_at_100
      value: 61.334999999999994
    - type: recall_at_1000
      value: 80.567
    - type: recall_at_3
      value: 30.198000000000004
    - type: recall_at_5
      value: 34.803
    - type: map_at_1
      value: 16.722
    - type: map_at_10
      value: 22.794
    - type: map_at_100
      value: 23.7
    - type: map_at_1000
      value: 23.822
    - type: map_at_3
      value: 20.781
    - type: map_at_5
      value: 22.024
    - type: mrr_at_1
      value: 20.061999999999998
    - type: mrr_at_10
      value: 26.346999999999998
    - type: mrr_at_100
      value: 27.153
    - type: mrr_at_1000
      value: 27.233
    - type: mrr_at_3
      value: 24.375
    - type: mrr_at_5
      value: 25.593
    - type: ndcg_at_1
      value: 20.061999999999998
    - type: ndcg_at_10
      value: 26.785999999999998
    - type: ndcg_at_100
      value: 31.319999999999997
    - type: ndcg_at_1000
      value: 34.346
    - type: ndcg_at_3
      value: 23.219
    - type: ndcg_at_5
      value: 25.107000000000003
    - type: precision_at_1
      value: 20.061999999999998
    - type: precision_at_10
      value: 4.78
    - type: precision_at_100
      value: 0.83
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 10.874
    - type: precision_at_5
      value: 7.956
    - type: recall_at_1
      value: 16.722
    - type: recall_at_10
      value: 35.204
    - type: recall_at_100
      value: 55.797
    - type: recall_at_1000
      value: 77.689
    - type: recall_at_3
      value: 25.245
    - type: recall_at_5
      value: 30.115
    - type: map_at_1
      value: 24.842
    - type: map_at_10
      value: 32.917
    - type: map_at_100
      value: 33.961000000000006
    - type: map_at_1000
      value: 34.069
    - type: map_at_3
      value: 30.595
    - type: map_at_5
      value: 31.837
    - type: mrr_at_1
      value: 29.011
    - type: mrr_at_10
      value: 36.977
    - type: mrr_at_100
      value: 37.814
    - type: mrr_at_1000
      value: 37.885999999999996
    - type: mrr_at_3
      value: 34.966
    - type: mrr_at_5
      value: 36.043
    - type: ndcg_at_1
      value: 29.011
    - type: ndcg_at_10
      value: 37.735
    - type: ndcg_at_100
      value: 42.683
    - type: ndcg_at_1000
      value: 45.198
    - type: ndcg_at_3
      value: 33.650000000000006
    - type: ndcg_at_5
      value: 35.386
    - type: precision_at_1
      value: 29.011
    - type: precision_at_10
      value: 6.259
    - type: precision_at_100
      value: 0.984
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 15.329999999999998
    - type: precision_at_5
      value: 10.541
    - type: recall_at_1
      value: 24.842
    - type: recall_at_10
      value: 48.304
    - type: recall_at_100
      value: 70.04899999999999
    - type: recall_at_1000
      value: 87.82600000000001
    - type: recall_at_3
      value: 36.922
    - type: recall_at_5
      value: 41.449999999999996
    - type: map_at_1
      value: 24.252000000000002
    - type: map_at_10
      value: 32.293
    - type: map_at_100
      value: 33.816
    - type: map_at_1000
      value: 34.053
    - type: map_at_3
      value: 29.781999999999996
    - type: map_at_5
      value: 31.008000000000003
    - type: mrr_at_1
      value: 29.051
    - type: mrr_at_10
      value: 36.722
    - type: mrr_at_100
      value: 37.663000000000004
    - type: mrr_at_1000
      value: 37.734
    - type: mrr_at_3
      value: 34.354
    - type: mrr_at_5
      value: 35.609
    - type: ndcg_at_1
      value: 29.051
    - type: ndcg_at_10
      value: 37.775999999999996
    - type: ndcg_at_100
      value: 43.221
    - type: ndcg_at_1000
      value: 46.116
    - type: ndcg_at_3
      value: 33.403
    - type: ndcg_at_5
      value: 35.118
    - type: precision_at_1
      value: 29.051
    - type: precision_at_10
      value: 7.332
    - type: precision_at_100
      value: 1.49
    - type: precision_at_1000
      value: 0.23600000000000002
    - type: precision_at_3
      value: 15.415000000000001
    - type: precision_at_5
      value: 11.107
    - type: recall_at_1
      value: 24.252000000000002
    - type: recall_at_10
      value: 47.861
    - type: recall_at_100
      value: 72.21600000000001
    - type: recall_at_1000
      value: 90.886
    - type: recall_at_3
      value: 35.533
    - type: recall_at_5
      value: 39.959
    - type: map_at_1
      value: 20.025000000000002
    - type: map_at_10
      value: 27.154
    - type: map_at_100
      value: 28.118
    - type: map_at_1000
      value: 28.237000000000002
    - type: map_at_3
      value: 25.017
    - type: map_at_5
      value: 25.832
    - type: mrr_at_1
      value: 21.627
    - type: mrr_at_10
      value: 28.884999999999998
    - type: mrr_at_100
      value: 29.741
    - type: mrr_at_1000
      value: 29.831999999999997
    - type: mrr_at_3
      value: 26.741
    - type: mrr_at_5
      value: 27.628000000000004
    - type: ndcg_at_1
      value: 21.627
    - type: ndcg_at_10
      value: 31.436999999999998
    - type: ndcg_at_100
      value: 36.181000000000004
    - type: ndcg_at_1000
      value: 38.986
    - type: ndcg_at_3
      value: 27.025
    - type: ndcg_at_5
      value: 28.436
    - type: precision_at_1
      value: 21.627
    - type: precision_at_10
      value: 5.009
    - type: precision_at_100
      value: 0.7929999999999999
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 11.522
    - type: precision_at_5
      value: 7.763000000000001
    - type: recall_at_1
      value: 20.025000000000002
    - type: recall_at_10
      value: 42.954
    - type: recall_at_100
      value: 64.67500000000001
    - type: recall_at_1000
      value: 85.301
    - type: recall_at_3
      value: 30.892999999999997
    - type: recall_at_5
      value: 34.288000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.079
    - type: map_at_10
      value: 16.930999999999997
    - type: map_at_100
      value: 18.398999999999997
    - type: map_at_1000
      value: 18.561
    - type: map_at_3
      value: 14.294
    - type: map_at_5
      value: 15.579
    - type: mrr_at_1
      value: 22.606
    - type: mrr_at_10
      value: 32.513
    - type: mrr_at_100
      value: 33.463
    - type: mrr_at_1000
      value: 33.513999999999996
    - type: mrr_at_3
      value: 29.479
    - type: mrr_at_5
      value: 31.3
    - type: ndcg_at_1
      value: 22.606
    - type: ndcg_at_10
      value: 24.053
    - type: ndcg_at_100
      value: 30.258000000000003
    - type: ndcg_at_1000
      value: 33.516
    - type: ndcg_at_3
      value: 19.721
    - type: ndcg_at_5
      value: 21.144
    - type: precision_at_1
      value: 22.606
    - type: precision_at_10
      value: 7.55
    - type: precision_at_100
      value: 1.399
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 14.701
    - type: precision_at_5
      value: 11.192
    - type: recall_at_1
      value: 10.079
    - type: recall_at_10
      value: 28.970000000000002
    - type: recall_at_100
      value: 50.805
    - type: recall_at_1000
      value: 69.378
    - type: recall_at_3
      value: 18.199
    - type: recall_at_5
      value: 22.442
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.794
    - type: map_at_10
      value: 15.165999999999999
    - type: map_at_100
      value: 20.508000000000003
    - type: map_at_1000
      value: 21.809
    - type: map_at_3
      value: 11.568000000000001
    - type: map_at_5
      value: 13.059000000000001
    - type: mrr_at_1
      value: 56.49999999999999
    - type: mrr_at_10
      value: 65.90899999999999
    - type: mrr_at_100
      value: 66.352
    - type: mrr_at_1000
      value: 66.369
    - type: mrr_at_3
      value: 64.0
    - type: mrr_at_5
      value: 65.10000000000001
    - type: ndcg_at_1
      value: 44.25
    - type: ndcg_at_10
      value: 32.649
    - type: ndcg_at_100
      value: 36.668
    - type: ndcg_at_1000
      value: 43.918
    - type: ndcg_at_3
      value: 37.096000000000004
    - type: ndcg_at_5
      value: 34.048
    - type: precision_at_1
      value: 56.49999999999999
    - type: precision_at_10
      value: 25.45
    - type: precision_at_100
      value: 8.055
    - type: precision_at_1000
      value: 1.7489999999999999
    - type: precision_at_3
      value: 41.0
    - type: precision_at_5
      value: 32.85
    - type: recall_at_1
      value: 7.794
    - type: recall_at_10
      value: 20.101
    - type: recall_at_100
      value: 42.448
    - type: recall_at_1000
      value: 65.88000000000001
    - type: recall_at_3
      value: 12.753
    - type: recall_at_5
      value: 15.307
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.01
    - type: f1
      value: 38.659680951114964
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 49.713
    - type: map_at_10
      value: 61.79
    - type: map_at_100
      value: 62.28
    - type: map_at_1000
      value: 62.297000000000004
    - type: map_at_3
      value: 59.361
    - type: map_at_5
      value: 60.92100000000001
    - type: mrr_at_1
      value: 53.405
    - type: mrr_at_10
      value: 65.79899999999999
    - type: mrr_at_100
      value: 66.219
    - type: mrr_at_1000
      value: 66.227
    - type: mrr_at_3
      value: 63.431000000000004
    - type: mrr_at_5
      value: 64.98
    - type: ndcg_at_1
      value: 53.405
    - type: ndcg_at_10
      value: 68.01899999999999
    - type: ndcg_at_100
      value: 70.197
    - type: ndcg_at_1000
      value: 70.571
    - type: ndcg_at_3
      value: 63.352
    - type: ndcg_at_5
      value: 66.018
    - type: precision_at_1
      value: 53.405
    - type: precision_at_10
      value: 9.119
    - type: precision_at_100
      value: 1.03
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 25.602999999999998
    - type: precision_at_5
      value: 16.835
    - type: recall_at_1
      value: 49.713
    - type: recall_at_10
      value: 83.306
    - type: recall_at_100
      value: 92.92
    - type: recall_at_1000
      value: 95.577
    - type: recall_at_3
      value: 70.798
    - type: recall_at_5
      value: 77.254
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.310000000000002
    - type: map_at_10
      value: 26.204
    - type: map_at_100
      value: 27.932000000000002
    - type: map_at_1000
      value: 28.121000000000002
    - type: map_at_3
      value: 22.481
    - type: map_at_5
      value: 24.678
    - type: mrr_at_1
      value: 29.784
    - type: mrr_at_10
      value: 39.582
    - type: mrr_at_100
      value: 40.52
    - type: mrr_at_1000
      value: 40.568
    - type: mrr_at_3
      value: 37.114000000000004
    - type: mrr_at_5
      value: 38.596000000000004
    - type: ndcg_at_1
      value: 29.784
    - type: ndcg_at_10
      value: 33.432
    - type: ndcg_at_100
      value: 40.281
    - type: ndcg_at_1000
      value: 43.653999999999996
    - type: ndcg_at_3
      value: 29.612
    - type: ndcg_at_5
      value: 31.223
    - type: precision_at_1
      value: 29.784
    - type: precision_at_10
      value: 9.645
    - type: precision_at_100
      value: 1.645
    - type: precision_at_1000
      value: 0.22499999999999998
    - type: precision_at_3
      value: 20.165
    - type: precision_at_5
      value: 15.401000000000002
    - type: recall_at_1
      value: 15.310000000000002
    - type: recall_at_10
      value: 40.499
    - type: recall_at_100
      value: 66.643
    - type: recall_at_1000
      value: 87.059
    - type: recall_at_3
      value: 27.492
    - type: recall_at_5
      value: 33.748
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 33.599000000000004
    - type: map_at_10
      value: 47.347
    - type: map_at_100
      value: 48.191
    - type: map_at_1000
      value: 48.263
    - type: map_at_3
      value: 44.698
    - type: map_at_5
      value: 46.278999999999996
    - type: mrr_at_1
      value: 67.19800000000001
    - type: mrr_at_10
      value: 74.054
    - type: mrr_at_100
      value: 74.376
    - type: mrr_at_1000
      value: 74.392
    - type: mrr_at_3
      value: 72.849
    - type: mrr_at_5
      value: 73.643
    - type: ndcg_at_1
      value: 67.19800000000001
    - type: ndcg_at_10
      value: 56.482
    - type: ndcg_at_100
      value: 59.694
    - type: ndcg_at_1000
      value: 61.204
    - type: ndcg_at_3
      value: 52.43299999999999
    - type: ndcg_at_5
      value: 54.608000000000004
    - type: precision_at_1
      value: 67.19800000000001
    - type: precision_at_10
      value: 11.613999999999999
    - type: precision_at_100
      value: 1.415
    - type: precision_at_1000
      value: 0.16199999999999998
    - type: precision_at_3
      value: 32.726
    - type: precision_at_5
      value: 21.349999999999998
    - type: recall_at_1
      value: 33.599000000000004
    - type: recall_at_10
      value: 58.069
    - type: recall_at_100
      value: 70.736
    - type: recall_at_1000
      value: 80.804
    - type: recall_at_3
      value: 49.088
    - type: recall_at_5
      value: 53.376000000000005
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 73.64359999999999
    - type: ap
      value: 67.54685976014599
    - type: f1
      value: 73.55148707559482
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 19.502
    - type: map_at_10
      value: 30.816
    - type: map_at_100
      value: 32.007999999999996
    - type: map_at_1000
      value: 32.067
    - type: map_at_3
      value: 27.215
    - type: map_at_5
      value: 29.304000000000002
    - type: mrr_at_1
      value: 20.072000000000003
    - type: mrr_at_10
      value: 31.406
    - type: mrr_at_100
      value: 32.549
    - type: mrr_at_1000
      value: 32.602
    - type: mrr_at_3
      value: 27.839000000000002
    - type: mrr_at_5
      value: 29.926000000000002
    - type: ndcg_at_1
      value: 20.086000000000002
    - type: ndcg_at_10
      value: 37.282
    - type: ndcg_at_100
      value: 43.206
    - type: ndcg_at_1000
      value: 44.690000000000005
    - type: ndcg_at_3
      value: 29.932
    - type: ndcg_at_5
      value: 33.668
    - type: precision_at_1
      value: 20.086000000000002
    - type: precision_at_10
      value: 5.961
    - type: precision_at_100
      value: 0.898
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 12.856000000000002
    - type: precision_at_5
      value: 9.596
    - type: recall_at_1
      value: 19.502
    - type: recall_at_10
      value: 57.182
    - type: recall_at_100
      value: 84.952
    - type: recall_at_1000
      value: 96.34700000000001
    - type: recall_at_3
      value: 37.193
    - type: recall_at_5
      value: 46.157
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 93.96488828089375
    - type: f1
      value: 93.32119260543482
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 72.4965800273598
    - type: f1
      value: 49.34896217536082
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 67.60928043039678
    - type: f1
      value: 64.34244712074538
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.75453934095493
    - type: f1
      value: 68.39224867489249
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.862573504920082
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.511123551196803
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.99145104942086
    - type: mrr
      value: 32.03606480418627
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.015
    - type: map_at_10
      value: 11.054
    - type: map_at_100
      value: 13.773
    - type: map_at_1000
      value: 15.082999999999998
    - type: map_at_3
      value: 8.253
    - type: map_at_5
      value: 9.508999999999999
    - type: mrr_at_1
      value: 42.105
    - type: mrr_at_10
      value: 50.44499999999999
    - type: mrr_at_100
      value: 51.080000000000005
    - type: mrr_at_1000
      value: 51.129999999999995
    - type: mrr_at_3
      value: 48.555
    - type: mrr_at_5
      value: 49.84
    - type: ndcg_at_1
      value: 40.402
    - type: ndcg_at_10
      value: 30.403000000000002
    - type: ndcg_at_100
      value: 28.216
    - type: ndcg_at_1000
      value: 37.021
    - type: ndcg_at_3
      value: 35.53
    - type: ndcg_at_5
      value: 33.202999999999996
    - type: precision_at_1
      value: 42.105
    - type: precision_at_10
      value: 22.353
    - type: precision_at_100
      value: 7.266
    - type: precision_at_1000
      value: 2.011
    - type: precision_at_3
      value: 32.921
    - type: precision_at_5
      value: 28.297
    - type: recall_at_1
      value: 5.015
    - type: recall_at_10
      value: 14.393
    - type: recall_at_100
      value: 28.893
    - type: recall_at_1000
      value: 60.18
    - type: recall_at_3
      value: 9.184000000000001
    - type: recall_at_5
      value: 11.39
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 29.524
    - type: map_at_10
      value: 44.182
    - type: map_at_100
      value: 45.228
    - type: map_at_1000
      value: 45.265
    - type: map_at_3
      value: 39.978
    - type: map_at_5
      value: 42.482
    - type: mrr_at_1
      value: 33.256
    - type: mrr_at_10
      value: 46.661
    - type: mrr_at_100
      value: 47.47
    - type: mrr_at_1000
      value: 47.496
    - type: mrr_at_3
      value: 43.187999999999995
    - type: mrr_at_5
      value: 45.330999999999996
    - type: ndcg_at_1
      value: 33.227000000000004
    - type: ndcg_at_10
      value: 51.589
    - type: ndcg_at_100
      value: 56.043
    - type: ndcg_at_1000
      value: 56.937000000000005
    - type: ndcg_at_3
      value: 43.751
    - type: ndcg_at_5
      value: 47.937000000000005
    - type: precision_at_1
      value: 33.227000000000004
    - type: precision_at_10
      value: 8.556999999999999
    - type: precision_at_100
      value: 1.103
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 19.921
    - type: precision_at_5
      value: 14.396999999999998
    - type: recall_at_1
      value: 29.524
    - type: recall_at_10
      value: 71.615
    - type: recall_at_100
      value: 91.056
    - type: recall_at_1000
      value: 97.72800000000001
    - type: recall_at_3
      value: 51.451
    - type: recall_at_5
      value: 61.119
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 69.596
    - type: map_at_10
      value: 83.281
    - type: map_at_100
      value: 83.952
    - type: map_at_1000
      value: 83.97200000000001
    - type: map_at_3
      value: 80.315
    - type: map_at_5
      value: 82.223
    - type: mrr_at_1
      value: 80.17
    - type: mrr_at_10
      value: 86.522
    - type: mrr_at_100
      value: 86.644
    - type: mrr_at_1000
      value: 86.64500000000001
    - type: mrr_at_3
      value: 85.438
    - type: mrr_at_5
      value: 86.21799999999999
    - type: ndcg_at_1
      value: 80.19
    - type: ndcg_at_10
      value: 87.19
    - type: ndcg_at_100
      value: 88.567
    - type: ndcg_at_1000
      value: 88.70400000000001
    - type: ndcg_at_3
      value: 84.17999999999999
    - type: ndcg_at_5
      value: 85.931
    - type: precision_at_1
      value: 80.19
    - type: precision_at_10
      value: 13.209000000000001
    - type: precision_at_100
      value: 1.518
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 36.717
    - type: precision_at_5
      value: 24.248
    - type: recall_at_1
      value: 69.596
    - type: recall_at_10
      value: 94.533
    - type: recall_at_100
      value: 99.322
    - type: recall_at_1000
      value: 99.965
    - type: recall_at_3
      value: 85.911
    - type: recall_at_5
      value: 90.809
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 49.27650627571912
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 57.08550946534183
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.568
    - type: map_at_10
      value: 10.862
    - type: map_at_100
      value: 12.757
    - type: map_at_1000
      value: 13.031
    - type: map_at_3
      value: 7.960000000000001
    - type: map_at_5
      value: 9.337
    - type: mrr_at_1
      value: 22.5
    - type: mrr_at_10
      value: 32.6
    - type: mrr_at_100
      value: 33.603
    - type: mrr_at_1000
      value: 33.672000000000004
    - type: mrr_at_3
      value: 29.299999999999997
    - type: mrr_at_5
      value: 31.25
    - type: ndcg_at_1
      value: 22.5
    - type: ndcg_at_10
      value: 18.605
    - type: ndcg_at_100
      value: 26.029999999999998
    - type: ndcg_at_1000
      value: 31.256
    - type: ndcg_at_3
      value: 17.873
    - type: ndcg_at_5
      value: 15.511
    - type: precision_at_1
      value: 22.5
    - type: precision_at_10
      value: 9.58
    - type: precision_at_100
      value: 2.033
    - type: precision_at_1000
      value: 0.33
    - type: precision_at_3
      value: 16.633
    - type: precision_at_5
      value: 13.54
    - type: recall_at_1
      value: 4.568
    - type: recall_at_10
      value: 19.402
    - type: recall_at_100
      value: 41.277
    - type: recall_at_1000
      value: 66.963
    - type: recall_at_3
      value: 10.112
    - type: recall_at_5
      value: 13.712
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 83.31992291680787
    - type: cos_sim_spearman
      value: 76.7212346922664
    - type: euclidean_pearson
      value: 80.42189271706478
    - type: euclidean_spearman
      value: 76.7212342532493
    - type: manhattan_pearson
      value: 80.33171093031578
    - type: manhattan_spearman
      value: 76.63192883074694
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 83.16654278886763
    - type: cos_sim_spearman
      value: 73.66390263429565
    - type: euclidean_pearson
      value: 79.7485360086639
    - type: euclidean_spearman
      value: 73.66389870373436
    - type: manhattan_pearson
      value: 79.73652237443706
    - type: manhattan_spearman
      value: 73.65296117151647
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 82.40389689929246
    - type: cos_sim_spearman
      value: 83.29727595993955
    - type: euclidean_pearson
      value: 82.23970587854079
    - type: euclidean_spearman
      value: 83.29727595993955
    - type: manhattan_pearson
      value: 82.18823600831897
    - type: manhattan_spearman
      value: 83.20746192209594
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 81.73505246913413
    - type: cos_sim_spearman
      value: 79.1686548248754
    - type: euclidean_pearson
      value: 80.48889135993412
    - type: euclidean_spearman
      value: 79.16864112930354
    - type: manhattan_pearson
      value: 80.40720651057302
    - type: manhattan_spearman
      value: 79.0640155089286
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.3953512879065
    - type: cos_sim_spearman
      value: 87.29947322714338
    - type: euclidean_pearson
      value: 86.59759438529645
    - type: euclidean_spearman
      value: 87.29947511092824
    - type: manhattan_pearson
      value: 86.52097806169155
    - type: manhattan_spearman
      value: 87.22987242146534
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 82.48565753792056
    - type: cos_sim_spearman
      value: 83.6049720319893
    - type: euclidean_pearson
      value: 82.56452023172913
    - type: euclidean_spearman
      value: 83.60490168191697
    - type: manhattan_pearson
      value: 82.58079941137872
    - type: manhattan_spearman
      value: 83.60975807374051
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 88.18239976618212
    - type: cos_sim_spearman
      value: 88.23061724730616
    - type: euclidean_pearson
      value: 87.78482472776658
    - type: euclidean_spearman
      value: 88.23061724730616
    - type: manhattan_pearson
      value: 87.75059641730239
    - type: manhattan_spearman
      value: 88.22527413524622
  - 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: 63.42816418706765
    - type: cos_sim_spearman
      value: 63.4569864520124
    - type: euclidean_pearson
      value: 64.35405409953853
    - type: euclidean_spearman
      value: 63.4569864520124
    - type: manhattan_pearson
      value: 63.96649236073056
    - type: manhattan_spearman
      value: 63.01448583722708
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 83.41659638047614
    - type: cos_sim_spearman
      value: 84.03893866106175
    - type: euclidean_pearson
      value: 84.2251203953798
    - type: euclidean_spearman
      value: 84.03893866106175
    - type: manhattan_pearson
      value: 84.22733643205514
    - type: manhattan_spearman
      value: 84.06504411263612
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.75608022582414
    - type: mrr
      value: 94.0947732369301
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 50.161
    - type: map_at_10
      value: 59.458999999999996
    - type: map_at_100
      value: 60.156
    - type: map_at_1000
      value: 60.194
    - type: map_at_3
      value: 56.45400000000001
    - type: map_at_5
      value: 58.165
    - type: mrr_at_1
      value: 53.333
    - type: mrr_at_10
      value: 61.050000000000004
    - type: mrr_at_100
      value: 61.586
    - type: mrr_at_1000
      value: 61.624
    - type: mrr_at_3
      value: 58.889
    - type: mrr_at_5
      value: 60.122
    - type: ndcg_at_1
      value: 53.333
    - type: ndcg_at_10
      value: 63.888999999999996
    - type: ndcg_at_100
      value: 66.963
    - type: ndcg_at_1000
      value: 68.062
    - type: ndcg_at_3
      value: 59.01
    - type: ndcg_at_5
      value: 61.373999999999995
    - type: precision_at_1
      value: 53.333
    - type: precision_at_10
      value: 8.633000000000001
    - type: precision_at_100
      value: 1.027
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 23.111
    - type: precision_at_5
      value: 15.467
    - type: recall_at_1
      value: 50.161
    - type: recall_at_10
      value: 75.922
    - type: recall_at_100
      value: 90.0
    - type: recall_at_1000
      value: 98.667
    - type: recall_at_3
      value: 62.90599999999999
    - type: recall_at_5
      value: 68.828
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.81188118811882
    - type: cos_sim_ap
      value: 95.11619225962413
    - type: cos_sim_f1
      value: 90.35840484603736
    - type: cos_sim_precision
      value: 91.23343527013252
    - type: cos_sim_recall
      value: 89.5
    - type: dot_accuracy
      value: 99.81188118811882
    - type: dot_ap
      value: 95.11619225962413
    - type: dot_f1
      value: 90.35840484603736
    - type: dot_precision
      value: 91.23343527013252
    - type: dot_recall
      value: 89.5
    - type: euclidean_accuracy
      value: 99.81188118811882
    - type: euclidean_ap
      value: 95.11619225962413
    - type: euclidean_f1
      value: 90.35840484603736
    - type: euclidean_precision
      value: 91.23343527013252
    - type: euclidean_recall
      value: 89.5
    - type: manhattan_accuracy
      value: 99.80891089108911
    - type: manhattan_ap
      value: 95.07294266220966
    - type: manhattan_f1
      value: 90.21794221996959
    - type: manhattan_precision
      value: 91.46968139773895
    - type: manhattan_recall
      value: 89.0
    - type: max_accuracy
      value: 99.81188118811882
    - type: max_ap
      value: 95.11619225962413
    - type: max_f1
      value: 90.35840484603736
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 55.3481874105239
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 34.421291695525
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 49.98746633276634
    - type: mrr
      value: 50.63143249724133
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.009961979844036
    - type: cos_sim_spearman
      value: 30.558416108881044
    - type: dot_pearson
      value: 31.009964941134253
    - type: dot_spearman
      value: 30.545760761761393
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.207
    - type: map_at_10
      value: 1.6
    - type: map_at_100
      value: 8.594
    - type: map_at_1000
      value: 20.213
    - type: map_at_3
      value: 0.585
    - type: map_at_5
      value: 0.9039999999999999
    - type: mrr_at_1
      value: 78.0
    - type: mrr_at_10
      value: 87.4
    - type: mrr_at_100
      value: 87.4
    - type: mrr_at_1000
      value: 87.4
    - type: mrr_at_3
      value: 86.667
    - type: mrr_at_5
      value: 87.06700000000001
    - type: ndcg_at_1
      value: 73.0
    - type: ndcg_at_10
      value: 65.18
    - type: ndcg_at_100
      value: 49.631
    - type: ndcg_at_1000
      value: 43.498999999999995
    - type: ndcg_at_3
      value: 71.83800000000001
    - type: ndcg_at_5
      value: 69.271
    - type: precision_at_1
      value: 78.0
    - type: precision_at_10
      value: 69.19999999999999
    - type: precision_at_100
      value: 50.980000000000004
    - type: precision_at_1000
      value: 19.426
    - type: precision_at_3
      value: 77.333
    - type: precision_at_5
      value: 74.0
    - type: recall_at_1
      value: 0.207
    - type: recall_at_10
      value: 1.822
    - type: recall_at_100
      value: 11.849
    - type: recall_at_1000
      value: 40.492
    - type: recall_at_3
      value: 0.622
    - type: recall_at_5
      value: 0.9809999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.001
    - type: map_at_10
      value: 10.376000000000001
    - type: map_at_100
      value: 16.936999999999998
    - type: map_at_1000
      value: 18.615000000000002
    - type: map_at_3
      value: 5.335999999999999
    - type: map_at_5
      value: 7.374
    - type: mrr_at_1
      value: 20.408
    - type: mrr_at_10
      value: 38.29
    - type: mrr_at_100
      value: 39.33
    - type: mrr_at_1000
      value: 39.347
    - type: mrr_at_3
      value: 32.993
    - type: mrr_at_5
      value: 36.973
    - type: ndcg_at_1
      value: 17.347
    - type: ndcg_at_10
      value: 23.515
    - type: ndcg_at_100
      value: 37.457
    - type: ndcg_at_1000
      value: 49.439
    - type: ndcg_at_3
      value: 22.762999999999998
    - type: ndcg_at_5
      value: 22.622
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 22.448999999999998
    - type: precision_at_100
      value: 8.184
    - type: precision_at_1000
      value: 1.608
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 25.306
    - type: recall_at_1
      value: 2.001
    - type: recall_at_10
      value: 17.422
    - type: recall_at_100
      value: 51.532999999999994
    - type: recall_at_1000
      value: 87.466
    - type: recall_at_3
      value: 6.861000000000001
    - type: recall_at_5
      value: 10.502
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.54419999999999
    - type: ap
      value: 14.372170450843907
    - type: f1
      value: 54.94420257390529
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.402942840973395
    - type: f1
      value: 59.4166538875571
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 41.569064336457906
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 85.31322644096085
    - type: cos_sim_ap
      value: 72.14518894837381
    - type: cos_sim_f1
      value: 66.67489813557229
    - type: cos_sim_precision
      value: 62.65954977953121
    - type: cos_sim_recall
      value: 71.2401055408971
    - type: dot_accuracy
      value: 85.31322644096085
    - type: dot_ap
      value: 72.14521480685293
    - type: dot_f1
      value: 66.67489813557229
    - type: dot_precision
      value: 62.65954977953121
    - type: dot_recall
      value: 71.2401055408971
    - type: euclidean_accuracy
      value: 85.31322644096085
    - type: euclidean_ap
      value: 72.14520820485349
    - type: euclidean_f1
      value: 66.67489813557229
    - type: euclidean_precision
      value: 62.65954977953121
    - type: euclidean_recall
      value: 71.2401055408971
    - type: manhattan_accuracy
      value: 85.21785778148656
    - type: manhattan_ap
      value: 72.01177147657364
    - type: manhattan_f1
      value: 66.62594673833374
    - type: manhattan_precision
      value: 62.0336669699727
    - type: manhattan_recall
      value: 71.95250659630607
    - type: max_accuracy
      value: 85.31322644096085
    - type: max_ap
      value: 72.14521480685293
    - type: max_f1
      value: 66.67489813557229
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.12756626693057
    - type: cos_sim_ap
      value: 86.05430786440826
    - type: cos_sim_f1
      value: 78.27759692216631
    - type: cos_sim_precision
      value: 75.33466248931929
    - type: cos_sim_recall
      value: 81.45980905451185
    - type: dot_accuracy
      value: 89.12950673341872
    - type: dot_ap
      value: 86.05431161145492
    - type: dot_f1
      value: 78.27759692216631
    - type: dot_precision
      value: 75.33466248931929
    - type: dot_recall
      value: 81.45980905451185
    - type: euclidean_accuracy
      value: 89.12756626693057
    - type: euclidean_ap
      value: 86.05431303247397
    - type: euclidean_f1
      value: 78.27759692216631
    - type: euclidean_precision
      value: 75.33466248931929
    - type: euclidean_recall
      value: 81.45980905451185
    - type: manhattan_accuracy
      value: 89.04994760740482
    - type: manhattan_ap
      value: 86.00860610892074
    - type: manhattan_f1
      value: 78.1846776005392
    - type: manhattan_precision
      value: 76.10438839480975
    - type: manhattan_recall
      value: 80.3818909762858
    - type: max_accuracy
      value: 89.12950673341872
    - type: max_ap
      value: 86.05431303247397
    - type: max_f1
      value: 78.27759692216631
---

# Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF
This model was converted to GGUF format from [`jinaai/jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-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-small-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 Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-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 Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.gguf -c 2048
```
