sentence-transformers gguf feature-extraction mteb sentence-similarity transformers llama-cpp gguf-my-repo en base_model:avsolatorio/NoInstruct-small-Embedding-v0 base_model:quantized:avsolatorio/NoInstruct-small-Embedding-v0 license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: avsolatorio/NoInstruct-small-Embedding-v0
language:
- en
library_name: sentence-transformers
license: mit
pipeline_tag: sentence-similarity
tags:
- feature-extraction
- mteb
- sentence-similarity
- sentence-transformers
- transformers
- llama-cpp
- gguf-my-repo
model-index:
- name: NoInstruct-small-Embedding-v0
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.76119402985074
    - type: ap
      value: 39.03628777559392
    - type: f1
      value: 69.85860402259618
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.29920000000001
    - type: ap
      value: 90.03479490717608
    - type: f1
      value: 93.28554395248467
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 49.98799999999999
    - type: f1
      value: 49.46151232451642
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 31.935000000000002
    - type: map_at_10
      value: 48.791000000000004
    - type: map_at_100
      value: 49.619
    - type: map_at_1000
      value: 49.623
    - type: map_at_3
      value: 44.334
    - type: map_at_5
      value: 46.908
    - type: mrr_at_1
      value: 32.93
    - type: mrr_at_10
      value: 49.158
    - type: mrr_at_100
      value: 50.00599999999999
    - type: mrr_at_1000
      value: 50.01
    - type: mrr_at_3
      value: 44.618
    - type: mrr_at_5
      value: 47.325
    - type: ndcg_at_1
      value: 31.935000000000002
    - type: ndcg_at_10
      value: 57.593
    - type: ndcg_at_100
      value: 60.841
    - type: ndcg_at_1000
      value: 60.924
    - type: ndcg_at_3
      value: 48.416
    - type: ndcg_at_5
      value: 53.05
    - type: precision_at_1
      value: 31.935000000000002
    - type: precision_at_10
      value: 8.549
    - type: precision_at_100
      value: 0.9900000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 20.081
    - type: precision_at_5
      value: 14.296000000000001
    - type: recall_at_1
      value: 31.935000000000002
    - type: recall_at_10
      value: 85.491
    - type: recall_at_100
      value: 99.004
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 60.242
    - type: recall_at_5
      value: 71.479
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 47.78438534940855
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 40.12916178519471
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 62.125361608299855
    - type: mrr
      value: 74.92525172580574
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 88.64322910336641
    - type: cos_sim_spearman
      value: 87.20138453306345
    - type: euclidean_pearson
      value: 87.08547818178234
    - type: euclidean_spearman
      value: 87.17066094143931
    - type: manhattan_pearson
      value: 87.30053110771618
    - type: manhattan_spearman
      value: 86.86824441211934
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 86.3961038961039
    - type: f1
      value: 86.3669961645295
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.40291404289857
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 35.102356817746816
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 31.013
    - type: map_at_10
      value: 42.681999999999995
    - type: map_at_100
      value: 44.24
    - type: map_at_1000
      value: 44.372
    - type: map_at_3
      value: 39.181
    - type: map_at_5
      value: 41.071999999999996
    - type: mrr_at_1
      value: 38.196999999999996
    - type: mrr_at_10
      value: 48.604
    - type: mrr_at_100
      value: 49.315
    - type: mrr_at_1000
      value: 49.363
    - type: mrr_at_3
      value: 45.756
    - type: mrr_at_5
      value: 47.43
    - type: ndcg_at_1
      value: 38.196999999999996
    - type: ndcg_at_10
      value: 49.344
    - type: ndcg_at_100
      value: 54.662
    - type: ndcg_at_1000
      value: 56.665
    - type: ndcg_at_3
      value: 44.146
    - type: ndcg_at_5
      value: 46.514
    - type: precision_at_1
      value: 38.196999999999996
    - type: precision_at_10
      value: 9.571
    - type: precision_at_100
      value: 1.542
    - type: precision_at_1000
      value: 0.202
    - type: precision_at_3
      value: 21.364
    - type: precision_at_5
      value: 15.336
    - type: recall_at_1
      value: 31.013
    - type: recall_at_10
      value: 61.934999999999995
    - type: recall_at_100
      value: 83.923
    - type: recall_at_1000
      value: 96.601
    - type: recall_at_3
      value: 46.86
    - type: recall_at_5
      value: 53.620000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 29.84
    - type: map_at_10
      value: 39.335
    - type: map_at_100
      value: 40.647
    - type: map_at_1000
      value: 40.778
    - type: map_at_3
      value: 36.556
    - type: map_at_5
      value: 38.048
    - type: mrr_at_1
      value: 36.815
    - type: mrr_at_10
      value: 45.175
    - type: mrr_at_100
      value: 45.907
    - type: mrr_at_1000
      value: 45.946999999999996
    - type: mrr_at_3
      value: 42.909000000000006
    - type: mrr_at_5
      value: 44.227
    - type: ndcg_at_1
      value: 36.815
    - type: ndcg_at_10
      value: 44.783
    - type: ndcg_at_100
      value: 49.551
    - type: ndcg_at_1000
      value: 51.612
    - type: ndcg_at_3
      value: 40.697
    - type: ndcg_at_5
      value: 42.558
    - type: precision_at_1
      value: 36.815
    - type: precision_at_10
      value: 8.363
    - type: precision_at_100
      value: 1.385
    - type: precision_at_1000
      value: 0.186
    - type: precision_at_3
      value: 19.342000000000002
    - type: precision_at_5
      value: 13.706999999999999
    - type: recall_at_1
      value: 29.84
    - type: recall_at_10
      value: 54.164
    - type: recall_at_100
      value: 74.36
    - type: recall_at_1000
      value: 87.484
    - type: recall_at_3
      value: 42.306
    - type: recall_at_5
      value: 47.371
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 39.231
    - type: map_at_10
      value: 51.44800000000001
    - type: map_at_100
      value: 52.574
    - type: map_at_1000
      value: 52.629999999999995
    - type: map_at_3
      value: 48.077
    - type: map_at_5
      value: 50.019000000000005
    - type: mrr_at_1
      value: 44.89
    - type: mrr_at_10
      value: 54.803000000000004
    - type: mrr_at_100
      value: 55.556000000000004
    - type: mrr_at_1000
      value: 55.584
    - type: mrr_at_3
      value: 52.32
    - type: mrr_at_5
      value: 53.846000000000004
    - type: ndcg_at_1
      value: 44.89
    - type: ndcg_at_10
      value: 57.228
    - type: ndcg_at_100
      value: 61.57
    - type: ndcg_at_1000
      value: 62.613
    - type: ndcg_at_3
      value: 51.727000000000004
    - type: ndcg_at_5
      value: 54.496
    - type: precision_at_1
      value: 44.89
    - type: precision_at_10
      value: 9.266
    - type: precision_at_100
      value: 1.2309999999999999
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 23.051
    - type: precision_at_5
      value: 15.987000000000002
    - type: recall_at_1
      value: 39.231
    - type: recall_at_10
      value: 70.82000000000001
    - type: recall_at_100
      value: 89.446
    - type: recall_at_1000
      value: 96.665
    - type: recall_at_3
      value: 56.40500000000001
    - type: recall_at_5
      value: 62.993
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 25.296000000000003
    - type: map_at_10
      value: 34.021
    - type: map_at_100
      value: 35.158
    - type: map_at_1000
      value: 35.233
    - type: map_at_3
      value: 31.424999999999997
    - type: map_at_5
      value: 33.046
    - type: mrr_at_1
      value: 27.232
    - type: mrr_at_10
      value: 36.103
    - type: mrr_at_100
      value: 37.076
    - type: mrr_at_1000
      value: 37.135
    - type: mrr_at_3
      value: 33.635
    - type: mrr_at_5
      value: 35.211
    - type: ndcg_at_1
      value: 27.232
    - type: ndcg_at_10
      value: 38.878
    - type: ndcg_at_100
      value: 44.284
    - type: ndcg_at_1000
      value: 46.268
    - type: ndcg_at_3
      value: 33.94
    - type: ndcg_at_5
      value: 36.687
    - type: precision_at_1
      value: 27.232
    - type: precision_at_10
      value: 5.921
    - type: precision_at_100
      value: 0.907
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 14.426
    - type: precision_at_5
      value: 10.215
    - type: recall_at_1
      value: 25.296000000000003
    - type: recall_at_10
      value: 51.708
    - type: recall_at_100
      value: 76.36699999999999
    - type: recall_at_1000
      value: 91.306
    - type: recall_at_3
      value: 38.651
    - type: recall_at_5
      value: 45.201
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 16.24
    - type: map_at_10
      value: 24.696
    - type: map_at_100
      value: 25.945
    - type: map_at_1000
      value: 26.069
    - type: map_at_3
      value: 22.542
    - type: map_at_5
      value: 23.526
    - type: mrr_at_1
      value: 20.149
    - type: mrr_at_10
      value: 29.584
    - type: mrr_at_100
      value: 30.548
    - type: mrr_at_1000
      value: 30.618000000000002
    - type: mrr_at_3
      value: 27.301
    - type: mrr_at_5
      value: 28.563
    - type: ndcg_at_1
      value: 20.149
    - type: ndcg_at_10
      value: 30.029
    - type: ndcg_at_100
      value: 35.812
    - type: ndcg_at_1000
      value: 38.755
    - type: ndcg_at_3
      value: 26.008
    - type: ndcg_at_5
      value: 27.517000000000003
    - type: precision_at_1
      value: 20.149
    - type: precision_at_10
      value: 5.647
    - type: precision_at_100
      value: 0.968
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 12.934999999999999
    - type: precision_at_5
      value: 8.955
    - type: recall_at_1
      value: 16.24
    - type: recall_at_10
      value: 41.464
    - type: recall_at_100
      value: 66.781
    - type: recall_at_1000
      value: 87.85300000000001
    - type: recall_at_3
      value: 29.822
    - type: recall_at_5
      value: 34.096
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 29.044999999999998
    - type: map_at_10
      value: 39.568999999999996
    - type: map_at_100
      value: 40.831
    - type: map_at_1000
      value: 40.948
    - type: map_at_3
      value: 36.495
    - type: map_at_5
      value: 38.21
    - type: mrr_at_1
      value: 35.611
    - type: mrr_at_10
      value: 45.175
    - type: mrr_at_100
      value: 45.974
    - type: mrr_at_1000
      value: 46.025
    - type: mrr_at_3
      value: 42.765
    - type: mrr_at_5
      value: 44.151
    - type: ndcg_at_1
      value: 35.611
    - type: ndcg_at_10
      value: 45.556999999999995
    - type: ndcg_at_100
      value: 50.86000000000001
    - type: ndcg_at_1000
      value: 52.983000000000004
    - type: ndcg_at_3
      value: 40.881
    - type: ndcg_at_5
      value: 43.035000000000004
    - type: precision_at_1
      value: 35.611
    - type: precision_at_10
      value: 8.306
    - type: precision_at_100
      value: 1.276
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 19.57
    - type: precision_at_5
      value: 13.725000000000001
    - type: recall_at_1
      value: 29.044999999999998
    - type: recall_at_10
      value: 57.513999999999996
    - type: recall_at_100
      value: 80.152
    - type: recall_at_1000
      value: 93.982
    - type: recall_at_3
      value: 44.121
    - type: recall_at_5
      value: 50.007000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 22.349
    - type: map_at_10
      value: 33.434000000000005
    - type: map_at_100
      value: 34.8
    - type: map_at_1000
      value: 34.919
    - type: map_at_3
      value: 30.348000000000003
    - type: map_at_5
      value: 31.917
    - type: mrr_at_1
      value: 28.195999999999998
    - type: mrr_at_10
      value: 38.557
    - type: mrr_at_100
      value: 39.550999999999995
    - type: mrr_at_1000
      value: 39.607
    - type: mrr_at_3
      value: 36.035000000000004
    - type: mrr_at_5
      value: 37.364999999999995
    - type: ndcg_at_1
      value: 28.195999999999998
    - type: ndcg_at_10
      value: 39.656000000000006
    - type: ndcg_at_100
      value: 45.507999999999996
    - type: ndcg_at_1000
      value: 47.848
    - type: ndcg_at_3
      value: 34.609
    - type: ndcg_at_5
      value: 36.65
    - type: precision_at_1
      value: 28.195999999999998
    - type: precision_at_10
      value: 7.534000000000001
    - type: precision_at_100
      value: 1.217
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 17.085
    - type: precision_at_5
      value: 12.169
    - type: recall_at_1
      value: 22.349
    - type: recall_at_10
      value: 53.127
    - type: recall_at_100
      value: 77.884
    - type: recall_at_1000
      value: 93.705
    - type: recall_at_3
      value: 38.611000000000004
    - type: recall_at_5
      value: 44.182
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 25.215749999999996
    - type: map_at_10
      value: 34.332750000000004
    - type: map_at_100
      value: 35.58683333333333
    - type: map_at_1000
      value: 35.70458333333333
    - type: map_at_3
      value: 31.55441666666667
    - type: map_at_5
      value: 33.100833333333334
    - type: mrr_at_1
      value: 29.697250000000004
    - type: mrr_at_10
      value: 38.372249999999994
    - type: mrr_at_100
      value: 39.26708333333334
    - type: mrr_at_1000
      value: 39.3265
    - type: mrr_at_3
      value: 35.946083333333334
    - type: mrr_at_5
      value: 37.336999999999996
    - type: ndcg_at_1
      value: 29.697250000000004
    - type: ndcg_at_10
      value: 39.64575
    - type: ndcg_at_100
      value: 44.996833333333335
    - type: ndcg_at_1000
      value: 47.314499999999995
    - type: ndcg_at_3
      value: 34.93383333333334
    - type: ndcg_at_5
      value: 37.15291666666667
    - type: precision_at_1
      value: 29.697250000000004
    - type: precision_at_10
      value: 6.98825
    - type: precision_at_100
      value: 1.138
    - type: precision_at_1000
      value: 0.15283333333333332
    - type: precision_at_3
      value: 16.115583333333333
    - type: precision_at_5
      value: 11.460916666666666
    - type: recall_at_1
      value: 25.215749999999996
    - type: recall_at_10
      value: 51.261250000000004
    - type: recall_at_100
      value: 74.67258333333334
    - type: recall_at_1000
      value: 90.72033333333334
    - type: recall_at_3
      value: 38.1795
    - type: recall_at_5
      value: 43.90658333333334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 24.352
    - type: map_at_10
      value: 30.576999999999998
    - type: map_at_100
      value: 31.545
    - type: map_at_1000
      value: 31.642
    - type: map_at_3
      value: 28.605000000000004
    - type: map_at_5
      value: 29.828
    - type: mrr_at_1
      value: 26.994
    - type: mrr_at_10
      value: 33.151
    - type: mrr_at_100
      value: 33.973
    - type: mrr_at_1000
      value: 34.044999999999995
    - type: mrr_at_3
      value: 31.135
    - type: mrr_at_5
      value: 32.262
    - type: ndcg_at_1
      value: 26.994
    - type: ndcg_at_10
      value: 34.307
    - type: ndcg_at_100
      value: 39.079
    - type: ndcg_at_1000
      value: 41.548
    - type: ndcg_at_3
      value: 30.581000000000003
    - type: ndcg_at_5
      value: 32.541
    - type: precision_at_1
      value: 26.994
    - type: precision_at_10
      value: 5.244999999999999
    - type: precision_at_100
      value: 0.831
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 12.781
    - type: precision_at_5
      value: 9.017999999999999
    - type: recall_at_1
      value: 24.352
    - type: recall_at_10
      value: 43.126999999999995
    - type: recall_at_100
      value: 64.845
    - type: recall_at_1000
      value: 83.244
    - type: recall_at_3
      value: 33.308
    - type: recall_at_5
      value: 37.984
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 16.592000000000002
    - type: map_at_10
      value: 23.29
    - type: map_at_100
      value: 24.423000000000002
    - type: map_at_1000
      value: 24.554000000000002
    - type: map_at_3
      value: 20.958
    - type: map_at_5
      value: 22.267
    - type: mrr_at_1
      value: 20.061999999999998
    - type: mrr_at_10
      value: 26.973999999999997
    - type: mrr_at_100
      value: 27.944999999999997
    - type: mrr_at_1000
      value: 28.023999999999997
    - type: mrr_at_3
      value: 24.839
    - type: mrr_at_5
      value: 26.033
    - type: ndcg_at_1
      value: 20.061999999999998
    - type: ndcg_at_10
      value: 27.682000000000002
    - type: ndcg_at_100
      value: 33.196
    - type: ndcg_at_1000
      value: 36.246
    - type: ndcg_at_3
      value: 23.559
    - type: ndcg_at_5
      value: 25.507
    - type: precision_at_1
      value: 20.061999999999998
    - type: precision_at_10
      value: 5.086
    - type: precision_at_100
      value: 0.9249999999999999
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 11.046
    - type: precision_at_5
      value: 8.149000000000001
    - type: recall_at_1
      value: 16.592000000000002
    - type: recall_at_10
      value: 37.181999999999995
    - type: recall_at_100
      value: 62.224999999999994
    - type: recall_at_1000
      value: 84.072
    - type: recall_at_3
      value: 25.776
    - type: recall_at_5
      value: 30.680000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 26.035999999999998
    - type: map_at_10
      value: 34.447
    - type: map_at_100
      value: 35.697
    - type: map_at_1000
      value: 35.802
    - type: map_at_3
      value: 31.64
    - type: map_at_5
      value: 33.056999999999995
    - type: mrr_at_1
      value: 29.851
    - type: mrr_at_10
      value: 38.143
    - type: mrr_at_100
      value: 39.113
    - type: mrr_at_1000
      value: 39.175
    - type: mrr_at_3
      value: 35.665
    - type: mrr_at_5
      value: 36.901
    - type: ndcg_at_1
      value: 29.851
    - type: ndcg_at_10
      value: 39.554
    - type: ndcg_at_100
      value: 45.091
    - type: ndcg_at_1000
      value: 47.504000000000005
    - type: ndcg_at_3
      value: 34.414
    - type: ndcg_at_5
      value: 36.508
    - type: precision_at_1
      value: 29.851
    - type: precision_at_10
      value: 6.614000000000001
    - type: precision_at_100
      value: 1.051
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 15.329999999999998
    - type: precision_at_5
      value: 10.671999999999999
    - type: recall_at_1
      value: 26.035999999999998
    - type: recall_at_10
      value: 51.396
    - type: recall_at_100
      value: 75.09
    - type: recall_at_1000
      value: 91.904
    - type: recall_at_3
      value: 37.378
    - type: recall_at_5
      value: 42.69
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 23.211000000000002
    - type: map_at_10
      value: 32.231
    - type: map_at_100
      value: 33.772999999999996
    - type: map_at_1000
      value: 33.982
    - type: map_at_3
      value: 29.128
    - type: map_at_5
      value: 31.002999999999997
    - type: mrr_at_1
      value: 27.668
    - type: mrr_at_10
      value: 36.388
    - type: mrr_at_100
      value: 37.384
    - type: mrr_at_1000
      value: 37.44
    - type: mrr_at_3
      value: 33.762
    - type: mrr_at_5
      value: 35.234
    - type: ndcg_at_1
      value: 27.668
    - type: ndcg_at_10
      value: 38.043
    - type: ndcg_at_100
      value: 44.21
    - type: ndcg_at_1000
      value: 46.748
    - type: ndcg_at_3
      value: 32.981
    - type: ndcg_at_5
      value: 35.58
    - type: precision_at_1
      value: 27.668
    - type: precision_at_10
      value: 7.352
    - type: precision_at_100
      value: 1.5
    - type: precision_at_1000
      value: 0.23700000000000002
    - type: precision_at_3
      value: 15.613
    - type: precision_at_5
      value: 11.501999999999999
    - type: recall_at_1
      value: 23.211000000000002
    - type: recall_at_10
      value: 49.851
    - type: recall_at_100
      value: 77.596
    - type: recall_at_1000
      value: 93.683
    - type: recall_at_3
      value: 35.403
    - type: recall_at_5
      value: 42.485
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 19.384
    - type: map_at_10
      value: 26.262999999999998
    - type: map_at_100
      value: 27.409
    - type: map_at_1000
      value: 27.526
    - type: map_at_3
      value: 23.698
    - type: map_at_5
      value: 25.217
    - type: mrr_at_1
      value: 20.702
    - type: mrr_at_10
      value: 27.810000000000002
    - type: mrr_at_100
      value: 28.863
    - type: mrr_at_1000
      value: 28.955
    - type: mrr_at_3
      value: 25.230999999999998
    - type: mrr_at_5
      value: 26.821
    - type: ndcg_at_1
      value: 20.702
    - type: ndcg_at_10
      value: 30.688
    - type: ndcg_at_100
      value: 36.138999999999996
    - type: ndcg_at_1000
      value: 38.984
    - type: ndcg_at_3
      value: 25.663000000000004
    - type: ndcg_at_5
      value: 28.242
    - type: precision_at_1
      value: 20.702
    - type: precision_at_10
      value: 4.954
    - type: precision_at_100
      value: 0.823
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 10.844
    - type: precision_at_5
      value: 8.096
    - type: recall_at_1
      value: 19.384
    - type: recall_at_10
      value: 42.847
    - type: recall_at_100
      value: 67.402
    - type: recall_at_1000
      value: 88.145
    - type: recall_at_3
      value: 29.513
    - type: recall_at_5
      value: 35.57
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 14.915000000000001
    - type: map_at_10
      value: 25.846999999999998
    - type: map_at_100
      value: 27.741
    - type: map_at_1000
      value: 27.921000000000003
    - type: map_at_3
      value: 21.718
    - type: map_at_5
      value: 23.948
    - type: mrr_at_1
      value: 33.941
    - type: mrr_at_10
      value: 46.897
    - type: mrr_at_100
      value: 47.63
    - type: mrr_at_1000
      value: 47.658
    - type: mrr_at_3
      value: 43.919999999999995
    - type: mrr_at_5
      value: 45.783
    - type: ndcg_at_1
      value: 33.941
    - type: ndcg_at_10
      value: 35.202
    - type: ndcg_at_100
      value: 42.132
    - type: ndcg_at_1000
      value: 45.190999999999995
    - type: ndcg_at_3
      value: 29.68
    - type: ndcg_at_5
      value: 31.631999999999998
    - type: precision_at_1
      value: 33.941
    - type: precision_at_10
      value: 10.906
    - type: precision_at_100
      value: 1.8339999999999999
    - type: precision_at_1000
      value: 0.241
    - type: precision_at_3
      value: 22.606
    - type: precision_at_5
      value: 17.081
    - type: recall_at_1
      value: 14.915000000000001
    - type: recall_at_10
      value: 40.737
    - type: recall_at_100
      value: 64.42
    - type: recall_at_1000
      value: 81.435
    - type: recall_at_3
      value: 26.767000000000003
    - type: recall_at_5
      value: 32.895
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 8.665000000000001
    - type: map_at_10
      value: 19.087
    - type: map_at_100
      value: 26.555
    - type: map_at_1000
      value: 28.105999999999998
    - type: map_at_3
      value: 13.858999999999998
    - type: map_at_5
      value: 16.083
    - type: mrr_at_1
      value: 68.5
    - type: mrr_at_10
      value: 76.725
    - type: mrr_at_100
      value: 76.974
    - type: mrr_at_1000
      value: 76.981
    - type: mrr_at_3
      value: 75.583
    - type: mrr_at_5
      value: 76.208
    - type: ndcg_at_1
      value: 55.875
    - type: ndcg_at_10
      value: 41.018
    - type: ndcg_at_100
      value: 44.982
    - type: ndcg_at_1000
      value: 52.43
    - type: ndcg_at_3
      value: 46.534
    - type: ndcg_at_5
      value: 43.083
    - type: precision_at_1
      value: 68.5
    - type: precision_at_10
      value: 32.35
    - type: precision_at_100
      value: 10.078
    - type: precision_at_1000
      value: 1.957
    - type: precision_at_3
      value: 50.083
    - type: precision_at_5
      value: 41.3
    - type: recall_at_1
      value: 8.665000000000001
    - type: recall_at_10
      value: 24.596999999999998
    - type: recall_at_100
      value: 50.612
    - type: recall_at_1000
      value: 74.24
    - type: recall_at_3
      value: 15.337
    - type: recall_at_5
      value: 18.796
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 55.06500000000001
    - type: f1
      value: 49.827367590822035
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 76.059
    - type: map_at_10
      value: 83.625
    - type: map_at_100
      value: 83.845
    - type: map_at_1000
      value: 83.858
    - type: map_at_3
      value: 82.67099999999999
    - type: map_at_5
      value: 83.223
    - type: mrr_at_1
      value: 82.013
    - type: mrr_at_10
      value: 88.44800000000001
    - type: mrr_at_100
      value: 88.535
    - type: mrr_at_1000
      value: 88.537
    - type: mrr_at_3
      value: 87.854
    - type: mrr_at_5
      value: 88.221
    - type: ndcg_at_1
      value: 82.013
    - type: ndcg_at_10
      value: 87.128
    - type: ndcg_at_100
      value: 87.922
    - type: ndcg_at_1000
      value: 88.166
    - type: ndcg_at_3
      value: 85.648
    - type: ndcg_at_5
      value: 86.366
    - type: precision_at_1
      value: 82.013
    - type: precision_at_10
      value: 10.32
    - type: precision_at_100
      value: 1.093
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 32.408
    - type: precision_at_5
      value: 19.973
    - type: recall_at_1
      value: 76.059
    - type: recall_at_10
      value: 93.229
    - type: recall_at_100
      value: 96.387
    - type: recall_at_1000
      value: 97.916
    - type: recall_at_3
      value: 89.025
    - type: recall_at_5
      value: 90.96300000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 20.479
    - type: map_at_10
      value: 33.109
    - type: map_at_100
      value: 34.803
    - type: map_at_1000
      value: 35.003
    - type: map_at_3
      value: 28.967
    - type: map_at_5
      value: 31.385
    - type: mrr_at_1
      value: 40.278000000000006
    - type: mrr_at_10
      value: 48.929
    - type: mrr_at_100
      value: 49.655
    - type: mrr_at_1000
      value: 49.691
    - type: mrr_at_3
      value: 46.605000000000004
    - type: mrr_at_5
      value: 48.056
    - type: ndcg_at_1
      value: 40.278000000000006
    - type: ndcg_at_10
      value: 40.649
    - type: ndcg_at_100
      value: 47.027
    - type: ndcg_at_1000
      value: 50.249
    - type: ndcg_at_3
      value: 37.364000000000004
    - type: ndcg_at_5
      value: 38.494
    - type: precision_at_1
      value: 40.278000000000006
    - type: precision_at_10
      value: 11.327
    - type: precision_at_100
      value: 1.802
    - type: precision_at_1000
      value: 0.23700000000000002
    - type: precision_at_3
      value: 25.102999999999998
    - type: precision_at_5
      value: 18.457
    - type: recall_at_1
      value: 20.479
    - type: recall_at_10
      value: 46.594
    - type: recall_at_100
      value: 71.101
    - type: recall_at_1000
      value: 90.31099999999999
    - type: recall_at_3
      value: 33.378
    - type: recall_at_5
      value: 39.587
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 36.59
    - type: map_at_10
      value: 58.178
    - type: map_at_100
      value: 59.095
    - type: map_at_1000
      value: 59.16400000000001
    - type: map_at_3
      value: 54.907
    - type: map_at_5
      value: 56.89999999999999
    - type: mrr_at_1
      value: 73.18
    - type: mrr_at_10
      value: 79.935
    - type: mrr_at_100
      value: 80.16799999999999
    - type: mrr_at_1000
      value: 80.17800000000001
    - type: mrr_at_3
      value: 78.776
    - type: mrr_at_5
      value: 79.522
    - type: ndcg_at_1
      value: 73.18
    - type: ndcg_at_10
      value: 66.538
    - type: ndcg_at_100
      value: 69.78
    - type: ndcg_at_1000
      value: 71.102
    - type: ndcg_at_3
      value: 61.739
    - type: ndcg_at_5
      value: 64.35600000000001
    - type: precision_at_1
      value: 73.18
    - type: precision_at_10
      value: 14.035
    - type: precision_at_100
      value: 1.657
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 39.684999999999995
    - type: precision_at_5
      value: 25.885
    - type: recall_at_1
      value: 36.59
    - type: recall_at_10
      value: 70.176
    - type: recall_at_100
      value: 82.836
    - type: recall_at_1000
      value: 91.526
    - type: recall_at_3
      value: 59.526999999999994
    - type: recall_at_5
      value: 64.713
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 90.1472
    - type: ap
      value: 85.73994227076815
    - type: f1
      value: 90.1271700788608
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 21.689
    - type: map_at_10
      value: 33.518
    - type: map_at_100
      value: 34.715
    - type: map_at_1000
      value: 34.766000000000005
    - type: map_at_3
      value: 29.781000000000002
    - type: map_at_5
      value: 31.838
    - type: mrr_at_1
      value: 22.249
    - type: mrr_at_10
      value: 34.085
    - type: mrr_at_100
      value: 35.223
    - type: mrr_at_1000
      value: 35.266999999999996
    - type: mrr_at_3
      value: 30.398999999999997
    - type: mrr_at_5
      value: 32.437
    - type: ndcg_at_1
      value: 22.249
    - type: ndcg_at_10
      value: 40.227000000000004
    - type: ndcg_at_100
      value: 45.961999999999996
    - type: ndcg_at_1000
      value: 47.248000000000005
    - type: ndcg_at_3
      value: 32.566
    - type: ndcg_at_5
      value: 36.229
    - type: precision_at_1
      value: 22.249
    - type: precision_at_10
      value: 6.358
    - type: precision_at_100
      value: 0.923
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 13.83
    - type: precision_at_5
      value: 10.145999999999999
    - type: recall_at_1
      value: 21.689
    - type: recall_at_10
      value: 60.92999999999999
    - type: recall_at_100
      value: 87.40599999999999
    - type: recall_at_1000
      value: 97.283
    - type: recall_at_3
      value: 40.01
    - type: recall_at_5
      value: 48.776
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 95.28727770177838
    - type: f1
      value: 95.02577308660041
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 79.5736434108527
    - type: f1
      value: 61.2451202054398
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 76.01210490921318
    - type: f1
      value: 73.70188053982473
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 79.33422999327504
    - type: f1
      value: 79.48369022509658
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 34.70891567267726
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 32.15203494451706
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.919517862194173
    - type: mrr
      value: 33.15466289140483
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 5.992
    - type: map_at_10
      value: 13.197000000000001
    - type: map_at_100
      value: 16.907
    - type: map_at_1000
      value: 18.44
    - type: map_at_3
      value: 9.631
    - type: map_at_5
      value: 11.243
    - type: mrr_at_1
      value: 44.272
    - type: mrr_at_10
      value: 53.321
    - type: mrr_at_100
      value: 53.903
    - type: mrr_at_1000
      value: 53.952999999999996
    - type: mrr_at_3
      value: 51.393
    - type: mrr_at_5
      value: 52.708999999999996
    - type: ndcg_at_1
      value: 42.415000000000006
    - type: ndcg_at_10
      value: 34.921
    - type: ndcg_at_100
      value: 32.384
    - type: ndcg_at_1000
      value: 41.260000000000005
    - type: ndcg_at_3
      value: 40.186
    - type: ndcg_at_5
      value: 37.89
    - type: precision_at_1
      value: 44.272
    - type: precision_at_10
      value: 26.006
    - type: precision_at_100
      value: 8.44
    - type: precision_at_1000
      value: 2.136
    - type: precision_at_3
      value: 37.977
    - type: precision_at_5
      value: 32.755
    - type: recall_at_1
      value: 5.992
    - type: recall_at_10
      value: 17.01
    - type: recall_at_100
      value: 33.080999999999996
    - type: recall_at_1000
      value: 65.054
    - type: recall_at_3
      value: 10.528
    - type: recall_at_5
      value: 13.233
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 28.871999999999996
    - type: map_at_10
      value: 43.286
    - type: map_at_100
      value: 44.432
    - type: map_at_1000
      value: 44.464999999999996
    - type: map_at_3
      value: 38.856
    - type: map_at_5
      value: 41.514
    - type: mrr_at_1
      value: 32.619
    - type: mrr_at_10
      value: 45.75
    - type: mrr_at_100
      value: 46.622
    - type: mrr_at_1000
      value: 46.646
    - type: mrr_at_3
      value: 41.985
    - type: mrr_at_5
      value: 44.277
    - type: ndcg_at_1
      value: 32.59
    - type: ndcg_at_10
      value: 50.895999999999994
    - type: ndcg_at_100
      value: 55.711999999999996
    - type: ndcg_at_1000
      value: 56.48800000000001
    - type: ndcg_at_3
      value: 42.504999999999995
    - type: ndcg_at_5
      value: 46.969
    - type: precision_at_1
      value: 32.59
    - type: precision_at_10
      value: 8.543000000000001
    - type: precision_at_100
      value: 1.123
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 19.448
    - type: precision_at_5
      value: 14.218
    - type: recall_at_1
      value: 28.871999999999996
    - type: recall_at_10
      value: 71.748
    - type: recall_at_100
      value: 92.55499999999999
    - type: recall_at_1000
      value: 98.327
    - type: recall_at_3
      value: 49.944
    - type: recall_at_5
      value: 60.291
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 70.664
    - type: map_at_10
      value: 84.681
    - type: map_at_100
      value: 85.289
    - type: map_at_1000
      value: 85.306
    - type: map_at_3
      value: 81.719
    - type: map_at_5
      value: 83.601
    - type: mrr_at_1
      value: 81.35
    - type: mrr_at_10
      value: 87.591
    - type: mrr_at_100
      value: 87.691
    - type: mrr_at_1000
      value: 87.693
    - type: mrr_at_3
      value: 86.675
    - type: mrr_at_5
      value: 87.29299999999999
    - type: ndcg_at_1
      value: 81.33
    - type: ndcg_at_10
      value: 88.411
    - type: ndcg_at_100
      value: 89.579
    - type: ndcg_at_1000
      value: 89.687
    - type: ndcg_at_3
      value: 85.613
    - type: ndcg_at_5
      value: 87.17
    - type: precision_at_1
      value: 81.33
    - type: precision_at_10
      value: 13.422
    - type: precision_at_100
      value: 1.5270000000000001
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.463
    - type: precision_at_5
      value: 24.646
    - type: recall_at_1
      value: 70.664
    - type: recall_at_10
      value: 95.54
    - type: recall_at_100
      value: 99.496
    - type: recall_at_1000
      value: 99.978
    - type: recall_at_3
      value: 87.481
    - type: recall_at_5
      value: 91.88499999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 55.40341814991112
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 61.231318481346655
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 4.833
    - type: map_at_10
      value: 13.149
    - type: map_at_100
      value: 15.578
    - type: map_at_1000
      value: 15.963
    - type: map_at_3
      value: 9.269
    - type: map_at_5
      value: 11.182
    - type: mrr_at_1
      value: 23.9
    - type: mrr_at_10
      value: 35.978
    - type: mrr_at_100
      value: 37.076
    - type: mrr_at_1000
      value: 37.126
    - type: mrr_at_3
      value: 32.333
    - type: mrr_at_5
      value: 34.413
    - type: ndcg_at_1
      value: 23.9
    - type: ndcg_at_10
      value: 21.823
    - type: ndcg_at_100
      value: 30.833
    - type: ndcg_at_1000
      value: 36.991
    - type: ndcg_at_3
      value: 20.465
    - type: ndcg_at_5
      value: 17.965999999999998
    - type: precision_at_1
      value: 23.9
    - type: precision_at_10
      value: 11.49
    - type: precision_at_100
      value: 2.444
    - type: precision_at_1000
      value: 0.392
    - type: precision_at_3
      value: 19.3
    - type: precision_at_5
      value: 15.959999999999999
    - type: recall_at_1
      value: 4.833
    - type: recall_at_10
      value: 23.294999999999998
    - type: recall_at_100
      value: 49.63
    - type: recall_at_1000
      value: 79.49199999999999
    - type: recall_at_3
      value: 11.732
    - type: recall_at_5
      value: 16.167
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 85.62938108735759
    - type: cos_sim_spearman
      value: 80.30777094408789
    - type: euclidean_pearson
      value: 82.94516686659536
    - type: euclidean_spearman
      value: 80.34489663248169
    - type: manhattan_pearson
      value: 82.85830094736245
    - type: manhattan_spearman
      value: 80.24902623215449
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 85.23777464247604
    - type: cos_sim_spearman
      value: 75.75714864112797
    - type: euclidean_pearson
      value: 82.33806918604493
    - type: euclidean_spearman
      value: 75.45282124387357
    - type: manhattan_pearson
      value: 82.32555620660538
    - type: manhattan_spearman
      value: 75.49228731684082
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 84.88151620954451
    - type: cos_sim_spearman
      value: 86.08377598473446
    - type: euclidean_pearson
      value: 85.36958329369413
    - type: euclidean_spearman
      value: 86.10274219670679
    - type: manhattan_pearson
      value: 85.25873897594711
    - type: manhattan_spearman
      value: 85.98096461661584
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 84.29360558735978
    - type: cos_sim_spearman
      value: 82.28284203795577
    - type: euclidean_pearson
      value: 83.81636655536633
    - type: euclidean_spearman
      value: 82.24340438530236
    - type: manhattan_pearson
      value: 83.83914453428608
    - type: manhattan_spearman
      value: 82.28391354080694
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 87.47344180426744
    - type: cos_sim_spearman
      value: 88.90045649789438
    - type: euclidean_pearson
      value: 88.43020815961273
    - type: euclidean_spearman
      value: 89.0087449011776
    - type: manhattan_pearson
      value: 88.37601826505525
    - type: manhattan_spearman
      value: 88.96756360690617
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 83.35997025304613
    - type: cos_sim_spearman
      value: 85.18237675717147
    - type: euclidean_pearson
      value: 84.46478196990202
    - type: euclidean_spearman
      value: 85.27748677712205
    - type: manhattan_pearson
      value: 84.29342543953123
    - type: manhattan_spearman
      value: 85.10579612516567
  - 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: 88.56668329596836
    - type: cos_sim_spearman
      value: 88.72837234129177
    - type: euclidean_pearson
      value: 89.39395650897828
    - type: euclidean_spearman
      value: 88.82001247906778
    - type: manhattan_pearson
      value: 89.41735354368878
    - type: manhattan_spearman
      value: 88.95159141850039
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 67.466167902991
    - type: cos_sim_spearman
      value: 68.54466147197274
    - type: euclidean_pearson
      value: 69.35551179564695
    - type: euclidean_spearman
      value: 68.75455717749132
    - type: manhattan_pearson
      value: 69.42432368208264
    - type: manhattan_spearman
      value: 68.83203709670562
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 85.33241300373689
    - type: cos_sim_spearman
      value: 86.97909372129874
    - type: euclidean_pearson
      value: 86.99526113559924
    - type: euclidean_spearman
      value: 87.02644372623219
    - type: manhattan_pearson
      value: 86.78744182759846
    - type: manhattan_spearman
      value: 86.8886180198196
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 86.18374413668717
    - type: mrr
      value: 95.93213068703264
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 58.31699999999999
    - type: map_at_10
      value: 67.691
    - type: map_at_100
      value: 68.201
    - type: map_at_1000
      value: 68.232
    - type: map_at_3
      value: 64.47800000000001
    - type: map_at_5
      value: 66.51
    - type: mrr_at_1
      value: 61.0
    - type: mrr_at_10
      value: 68.621
    - type: mrr_at_100
      value: 68.973
    - type: mrr_at_1000
      value: 69.002
    - type: mrr_at_3
      value: 66.111
    - type: mrr_at_5
      value: 67.578
    - type: ndcg_at_1
      value: 61.0
    - type: ndcg_at_10
      value: 72.219
    - type: ndcg_at_100
      value: 74.397
    - type: ndcg_at_1000
      value: 75.021
    - type: ndcg_at_3
      value: 66.747
    - type: ndcg_at_5
      value: 69.609
    - type: precision_at_1
      value: 61.0
    - type: precision_at_10
      value: 9.6
    - type: precision_at_100
      value: 1.08
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 25.667
    - type: precision_at_5
      value: 17.267
    - type: recall_at_1
      value: 58.31699999999999
    - type: recall_at_10
      value: 85.233
    - type: recall_at_100
      value: 95.167
    - type: recall_at_1000
      value: 99.667
    - type: recall_at_3
      value: 70.589
    - type: recall_at_5
      value: 77.628
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.83267326732673
    - type: cos_sim_ap
      value: 96.13707107038228
    - type: cos_sim_f1
      value: 91.48830263812842
    - type: cos_sim_precision
      value: 91.0802775024777
    - type: cos_sim_recall
      value: 91.9
    - type: dot_accuracy
      value: 99.83069306930693
    - type: dot_ap
      value: 96.21199069147254
    - type: dot_f1
      value: 91.36295556665004
    - type: dot_precision
      value: 91.22632103688933
    - type: dot_recall
      value: 91.5
    - type: euclidean_accuracy
      value: 99.83267326732673
    - type: euclidean_ap
      value: 96.08957801367436
    - type: euclidean_f1
      value: 91.33004926108374
    - type: euclidean_precision
      value: 90.0
    - type: euclidean_recall
      value: 92.7
    - type: manhattan_accuracy
      value: 99.83564356435643
    - type: manhattan_ap
      value: 96.10534946461945
    - type: manhattan_f1
      value: 91.74950298210736
    - type: manhattan_precision
      value: 91.20553359683794
    - type: manhattan_recall
      value: 92.30000000000001
    - type: max_accuracy
      value: 99.83564356435643
    - type: max_ap
      value: 96.21199069147254
    - type: max_f1
      value: 91.74950298210736
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 62.045718843534736
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 36.6501777041092
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 52.963913408053955
    - type: mrr
      value: 53.87972423818012
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.44195730764998
    - type: cos_sim_spearman
      value: 30.59626288679397
    - type: dot_pearson
      value: 30.22974492404086
    - type: dot_spearman
      value: 29.345245972906497
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.24
    - type: map_at_10
      value: 2.01
    - type: map_at_100
      value: 11.928999999999998
    - type: map_at_1000
      value: 29.034
    - type: map_at_3
      value: 0.679
    - type: map_at_5
      value: 1.064
    - type: mrr_at_1
      value: 92.0
    - type: mrr_at_10
      value: 96.0
    - type: mrr_at_100
      value: 96.0
    - type: mrr_at_1000
      value: 96.0
    - type: mrr_at_3
      value: 96.0
    - type: mrr_at_5
      value: 96.0
    - type: ndcg_at_1
      value: 87.0
    - type: ndcg_at_10
      value: 80.118
    - type: ndcg_at_100
      value: 60.753
    - type: ndcg_at_1000
      value: 54.632999999999996
    - type: ndcg_at_3
      value: 83.073
    - type: ndcg_at_5
      value: 80.733
    - type: precision_at_1
      value: 92.0
    - type: precision_at_10
      value: 84.8
    - type: precision_at_100
      value: 62.019999999999996
    - type: precision_at_1000
      value: 24.028
    - type: precision_at_3
      value: 87.333
    - type: precision_at_5
      value: 85.2
    - type: recall_at_1
      value: 0.24
    - type: recall_at_10
      value: 2.205
    - type: recall_at_100
      value: 15.068000000000001
    - type: recall_at_1000
      value: 51.796
    - type: recall_at_3
      value: 0.698
    - type: recall_at_5
      value: 1.1199999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 3.066
    - type: map_at_10
      value: 9.219
    - type: map_at_100
      value: 15.387
    - type: map_at_1000
      value: 16.957
    - type: map_at_3
      value: 5.146
    - type: map_at_5
      value: 6.6739999999999995
    - type: mrr_at_1
      value: 40.816
    - type: mrr_at_10
      value: 50.844
    - type: mrr_at_100
      value: 51.664
    - type: mrr_at_1000
      value: 51.664
    - type: mrr_at_3
      value: 46.259
    - type: mrr_at_5
      value: 49.116
    - type: ndcg_at_1
      value: 37.755
    - type: ndcg_at_10
      value: 23.477
    - type: ndcg_at_100
      value: 36.268
    - type: ndcg_at_1000
      value: 47.946
    - type: ndcg_at_3
      value: 25.832
    - type: ndcg_at_5
      value: 24.235
    - type: precision_at_1
      value: 40.816
    - type: precision_at_10
      value: 20.204
    - type: precision_at_100
      value: 7.611999999999999
    - type: precision_at_1000
      value: 1.543
    - type: precision_at_3
      value: 25.169999999999998
    - type: precision_at_5
      value: 23.265
    - type: recall_at_1
      value: 3.066
    - type: recall_at_10
      value: 14.985999999999999
    - type: recall_at_100
      value: 47.902
    - type: recall_at_1000
      value: 83.56400000000001
    - type: recall_at_3
      value: 5.755
    - type: recall_at_5
      value: 8.741999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 69.437
    - type: ap
      value: 12.844066827082706
    - type: f1
      value: 52.74974809872495
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 61.26768534238823
    - type: f1
      value: 61.65100187399282
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 49.860968711078804
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 85.7423854085951
    - type: cos_sim_ap
      value: 73.47560303339571
    - type: cos_sim_f1
      value: 67.372778183589
    - type: cos_sim_precision
      value: 62.54520795660036
    - type: cos_sim_recall
      value: 73.00791556728232
    - type: dot_accuracy
      value: 85.36091077069798
    - type: dot_ap
      value: 72.42521572307255
    - type: dot_f1
      value: 66.90576304724215
    - type: dot_precision
      value: 62.96554934823091
    - type: dot_recall
      value: 71.37203166226914
    - type: euclidean_accuracy
      value: 85.76026703224653
    - type: euclidean_ap
      value: 73.44852563860128
    - type: euclidean_f1
      value: 67.3
    - type: euclidean_precision
      value: 63.94299287410926
    - type: euclidean_recall
      value: 71.02902374670185
    - type: manhattan_accuracy
      value: 85.7423854085951
    - type: manhattan_ap
      value: 73.2635034755551
    - type: manhattan_f1
      value: 67.3180263800684
    - type: manhattan_precision
      value: 62.66484765802638
    - type: manhattan_recall
      value: 72.71767810026385
    - type: max_accuracy
      value: 85.76026703224653
    - type: max_ap
      value: 73.47560303339571
    - type: max_f1
      value: 67.372778183589
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.67543757519307
    - type: cos_sim_ap
      value: 85.35516518531304
    - type: cos_sim_f1
      value: 77.58197635511934
    - type: cos_sim_precision
      value: 75.01078360891445
    - type: cos_sim_recall
      value: 80.33569448721897
    - type: dot_accuracy
      value: 87.61400240617844
    - type: dot_ap
      value: 83.0774968268665
    - type: dot_f1
      value: 75.68229012162561
    - type: dot_precision
      value: 72.99713876967095
    - type: dot_recall
      value: 78.57252848783493
    - type: euclidean_accuracy
      value: 88.73753250281368
    - type: euclidean_ap
      value: 85.48043564821317
    - type: euclidean_f1
      value: 77.75975862719216
    - type: euclidean_precision
      value: 76.21054187920456
    - type: euclidean_recall
      value: 79.37326763166
    - type: manhattan_accuracy
      value: 88.75111576823068
    - type: manhattan_ap
      value: 85.44993439423668
    - type: manhattan_f1
      value: 77.6861329994845
    - type: manhattan_precision
      value: 74.44601270289344
    - type: manhattan_recall
      value: 81.22112719433323
    - type: max_accuracy
      value: 88.75111576823068
    - type: max_ap
      value: 85.48043564821317
    - type: max_f1
      value: 77.75975862719216
---

# twine-network/NoInstruct-small-Embedding-v0-Q5_K_M-GGUF
This model was converted to GGUF format from [`avsolatorio/NoInstruct-small-Embedding-v0`](https://huggingface.co/avsolatorio/NoInstruct-small-Embedding-v0) 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/avsolatorio/NoInstruct-small-Embedding-v0) 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 twine-network/NoInstruct-small-Embedding-v0-Q5_K_M-GGUF --hf-file noinstruct-small-embedding-v0-q5_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q5_K_M-GGUF --hf-file noinstruct-small-embedding-v0-q5_k_m.gguf -c 2048
```

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

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

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

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q5_K_M-GGUF --hf-file noinstruct-small-embedding-v0-q5_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo twine-network/NoInstruct-small-Embedding-v0-Q5_K_M-GGUF --hf-file noinstruct-small-embedding-v0-q5_k_m.gguf -c 2048
```
