sentence-transformers gguf feature-extraction mteb sentence-similarity llama-cpp gguf-my-repo en base_model:avsolatorio/GIST-small-Embedding-v0 base_model:quantized:avsolatorio/GIST-small-Embedding-v0 license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: avsolatorio/GIST-small-Embedding-v0
language:
- en
library_name: sentence-transformers
license: mit
pipeline_tag: sentence-similarity
tags:
- feature-extraction
- mteb
- sentence-similarity
- sentence-transformers
- llama-cpp
- gguf-my-repo
model-index:
- name: GIST-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: 75.26865671641791
    - type: ap
      value: 38.25623793370476
    - type: f1
      value: 69.26434651320257
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.232225
    - type: ap
      value: 89.97936072879344
    - type: f1
      value: 93.22122653806187
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 49.715999999999994
    - type: f1
      value: 49.169789920136076
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 34.922
    - type: map_at_10
      value: 50.524
    - type: map_at_100
      value: 51.247
    - type: map_at_1000
      value: 51.249
    - type: map_at_3
      value: 45.887
    - type: map_at_5
      value: 48.592999999999996
    - type: mrr_at_1
      value: 34.922
    - type: mrr_at_10
      value: 50.382000000000005
    - type: mrr_at_100
      value: 51.104000000000006
    - type: mrr_at_1000
      value: 51.105999999999995
    - type: mrr_at_3
      value: 45.733000000000004
    - type: mrr_at_5
      value: 48.428
    - type: ndcg_at_1
      value: 34.922
    - type: ndcg_at_10
      value: 59.12
    - type: ndcg_at_100
      value: 62.083999999999996
    - type: ndcg_at_1000
      value: 62.137
    - type: ndcg_at_3
      value: 49.616
    - type: ndcg_at_5
      value: 54.501
    - type: precision_at_1
      value: 34.922
    - type: precision_at_10
      value: 8.649
    - type: precision_at_100
      value: 0.991
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 20.152
    - type: precision_at_5
      value: 14.466999999999999
    - type: recall_at_1
      value: 34.922
    - type: recall_at_10
      value: 86.48599999999999
    - type: recall_at_100
      value: 99.14699999999999
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 60.455000000000005
    - type: recall_at_5
      value: 72.333
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 47.623282347623714
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 39.86487843524932
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 62.3290291318171
    - type: mrr
      value: 75.2379853141626
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 88.52002953574285
    - type: cos_sim_spearman
      value: 86.98752423842483
    - type: euclidean_pearson
      value: 86.89442688314197
    - type: euclidean_spearman
      value: 86.88631711307471
    - type: manhattan_pearson
      value: 87.03723618507175
    - type: manhattan_spearman
      value: 86.76041062975224
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 86.64935064935065
    - type: f1
      value: 86.61903824934998
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.21904455377494
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 35.43342755570654
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.843
    - type: map_at_10
      value: 43.379
    - type: map_at_100
      value: 44.946999999999996
    - type: map_at_1000
      value: 45.078
    - type: map_at_3
      value: 39.598
    - type: map_at_5
      value: 41.746
    - type: mrr_at_1
      value: 39.199
    - type: mrr_at_10
      value: 49.672
    - type: mrr_at_100
      value: 50.321000000000005
    - type: mrr_at_1000
      value: 50.365
    - type: mrr_at_3
      value: 46.805
    - type: mrr_at_5
      value: 48.579
    - type: ndcg_at_1
      value: 39.199
    - type: ndcg_at_10
      value: 50.163999999999994
    - type: ndcg_at_100
      value: 55.418
    - type: ndcg_at_1000
      value: 57.353
    - type: ndcg_at_3
      value: 44.716
    - type: ndcg_at_5
      value: 47.268
    - type: precision_at_1
      value: 39.199
    - type: precision_at_10
      value: 9.757
    - type: precision_at_100
      value: 1.552
    - type: precision_at_1000
      value: 0.20500000000000002
    - type: precision_at_3
      value: 21.602
    - type: precision_at_5
      value: 15.479000000000001
    - type: recall_at_1
      value: 31.843
    - type: recall_at_10
      value: 62.743
    - type: recall_at_100
      value: 84.78099999999999
    - type: recall_at_1000
      value: 96.86099999999999
    - type: recall_at_3
      value: 46.927
    - type: recall_at_5
      value: 54.355
    - type: map_at_1
      value: 29.321
    - type: map_at_10
      value: 39.062999999999995
    - type: map_at_100
      value: 40.403
    - type: map_at_1000
      value: 40.534
    - type: map_at_3
      value: 36.367
    - type: map_at_5
      value: 37.756
    - type: mrr_at_1
      value: 35.987
    - type: mrr_at_10
      value: 44.708999999999996
    - type: mrr_at_100
      value: 45.394
    - type: mrr_at_1000
      value: 45.436
    - type: mrr_at_3
      value: 42.463
    - type: mrr_at_5
      value: 43.663000000000004
    - type: ndcg_at_1
      value: 35.987
    - type: ndcg_at_10
      value: 44.585
    - type: ndcg_at_100
      value: 49.297999999999995
    - type: ndcg_at_1000
      value: 51.315
    - type: ndcg_at_3
      value: 40.569
    - type: ndcg_at_5
      value: 42.197
    - type: precision_at_1
      value: 35.987
    - type: precision_at_10
      value: 8.369
    - type: precision_at_100
      value: 1.366
    - type: precision_at_1000
      value: 0.184
    - type: precision_at_3
      value: 19.427
    - type: precision_at_5
      value: 13.58
    - type: recall_at_1
      value: 29.321
    - type: recall_at_10
      value: 54.333
    - type: recall_at_100
      value: 74.178
    - type: recall_at_1000
      value: 86.732
    - type: recall_at_3
      value: 42.46
    - type: recall_at_5
      value: 47.089999999999996
    - type: map_at_1
      value: 38.811
    - type: map_at_10
      value: 51.114000000000004
    - type: map_at_100
      value: 52.22
    - type: map_at_1000
      value: 52.275000000000006
    - type: map_at_3
      value: 47.644999999999996
    - type: map_at_5
      value: 49.675000000000004
    - type: mrr_at_1
      value: 44.389
    - type: mrr_at_10
      value: 54.459
    - type: mrr_at_100
      value: 55.208999999999996
    - type: mrr_at_1000
      value: 55.239000000000004
    - type: mrr_at_3
      value: 51.954
    - type: mrr_at_5
      value: 53.571999999999996
    - type: ndcg_at_1
      value: 44.389
    - type: ndcg_at_10
      value: 56.979
    - type: ndcg_at_100
      value: 61.266
    - type: ndcg_at_1000
      value: 62.315
    - type: ndcg_at_3
      value: 51.342
    - type: ndcg_at_5
      value: 54.33
    - type: precision_at_1
      value: 44.389
    - type: precision_at_10
      value: 9.26
    - type: precision_at_100
      value: 1.226
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 22.926
    - type: precision_at_5
      value: 15.987000000000002
    - type: recall_at_1
      value: 38.811
    - type: recall_at_10
      value: 70.841
    - type: recall_at_100
      value: 89.218
    - type: recall_at_1000
      value: 96.482
    - type: recall_at_3
      value: 56.123999999999995
    - type: recall_at_5
      value: 63.322
    - type: map_at_1
      value: 25.378
    - type: map_at_10
      value: 34.311
    - type: map_at_100
      value: 35.399
    - type: map_at_1000
      value: 35.482
    - type: map_at_3
      value: 31.917
    - type: map_at_5
      value: 33.275
    - type: mrr_at_1
      value: 27.683999999999997
    - type: mrr_at_10
      value: 36.575
    - type: mrr_at_100
      value: 37.492
    - type: mrr_at_1000
      value: 37.556
    - type: mrr_at_3
      value: 34.35
    - type: mrr_at_5
      value: 35.525
    - type: ndcg_at_1
      value: 27.683999999999997
    - type: ndcg_at_10
      value: 39.247
    - type: ndcg_at_100
      value: 44.424
    - type: ndcg_at_1000
      value: 46.478
    - type: ndcg_at_3
      value: 34.684
    - type: ndcg_at_5
      value: 36.886
    - type: precision_at_1
      value: 27.683999999999997
    - type: precision_at_10
      value: 5.989
    - type: precision_at_100
      value: 0.899
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 14.84
    - type: precision_at_5
      value: 10.215
    - type: recall_at_1
      value: 25.378
    - type: recall_at_10
      value: 52.195
    - type: recall_at_100
      value: 75.764
    - type: recall_at_1000
      value: 91.012
    - type: recall_at_3
      value: 39.885999999999996
    - type: recall_at_5
      value: 45.279
    - type: map_at_1
      value: 17.326
    - type: map_at_10
      value: 25.247000000000003
    - type: map_at_100
      value: 26.473000000000003
    - type: map_at_1000
      value: 26.579000000000004
    - type: map_at_3
      value: 22.466
    - type: map_at_5
      value: 24.113
    - type: mrr_at_1
      value: 21.393
    - type: mrr_at_10
      value: 30.187
    - type: mrr_at_100
      value: 31.089
    - type: mrr_at_1000
      value: 31.15
    - type: mrr_at_3
      value: 27.279999999999998
    - type: mrr_at_5
      value: 29.127
    - type: ndcg_at_1
      value: 21.393
    - type: ndcg_at_10
      value: 30.668
    - type: ndcg_at_100
      value: 36.543
    - type: ndcg_at_1000
      value: 39.181
    - type: ndcg_at_3
      value: 25.552000000000003
    - type: ndcg_at_5
      value: 28.176000000000002
    - type: precision_at_1
      value: 21.393
    - type: precision_at_10
      value: 5.784000000000001
    - type: precision_at_100
      value: 1.001
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 12.231
    - type: precision_at_5
      value: 9.179
    - type: recall_at_1
      value: 17.326
    - type: recall_at_10
      value: 42.415000000000006
    - type: recall_at_100
      value: 68.605
    - type: recall_at_1000
      value: 87.694
    - type: recall_at_3
      value: 28.343
    - type: recall_at_5
      value: 35.086
    - type: map_at_1
      value: 29.069
    - type: map_at_10
      value: 40.027
    - type: map_at_100
      value: 41.308
    - type: map_at_1000
      value: 41.412
    - type: map_at_3
      value: 36.864000000000004
    - type: map_at_5
      value: 38.641999999999996
    - type: mrr_at_1
      value: 35.707
    - type: mrr_at_10
      value: 45.527
    - type: mrr_at_100
      value: 46.348
    - type: mrr_at_1000
      value: 46.392
    - type: mrr_at_3
      value: 43.086
    - type: mrr_at_5
      value: 44.645
    - type: ndcg_at_1
      value: 35.707
    - type: ndcg_at_10
      value: 46.117000000000004
    - type: ndcg_at_100
      value: 51.468
    - type: ndcg_at_1000
      value: 53.412000000000006
    - type: ndcg_at_3
      value: 41.224
    - type: ndcg_at_5
      value: 43.637
    - type: precision_at_1
      value: 35.707
    - type: precision_at_10
      value: 8.459999999999999
    - type: precision_at_100
      value: 1.2970000000000002
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 19.731
    - type: precision_at_5
      value: 14.013
    - type: recall_at_1
      value: 29.069
    - type: recall_at_10
      value: 58.343999999999994
    - type: recall_at_100
      value: 81.296
    - type: recall_at_1000
      value: 93.974
    - type: recall_at_3
      value: 44.7
    - type: recall_at_5
      value: 50.88700000000001
    - type: map_at_1
      value: 23.905
    - type: map_at_10
      value: 33.983000000000004
    - type: map_at_100
      value: 35.372
    - type: map_at_1000
      value: 35.487
    - type: map_at_3
      value: 30.902
    - type: map_at_5
      value: 32.505
    - type: mrr_at_1
      value: 29.794999999999998
    - type: mrr_at_10
      value: 39.28
    - type: mrr_at_100
      value: 40.215
    - type: mrr_at_1000
      value: 40.276
    - type: mrr_at_3
      value: 36.701
    - type: mrr_at_5
      value: 38.105
    - type: ndcg_at_1
      value: 29.794999999999998
    - type: ndcg_at_10
      value: 40.041
    - type: ndcg_at_100
      value: 45.884
    - type: ndcg_at_1000
      value: 48.271
    - type: ndcg_at_3
      value: 34.931
    - type: ndcg_at_5
      value: 37.044
    - type: precision_at_1
      value: 29.794999999999998
    - type: precision_at_10
      value: 7.546
    - type: precision_at_100
      value: 1.216
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 16.933
    - type: precision_at_5
      value: 12.1
    - type: recall_at_1
      value: 23.905
    - type: recall_at_10
      value: 52.945
    - type: recall_at_100
      value: 77.551
    - type: recall_at_1000
      value: 93.793
    - type: recall_at_3
      value: 38.364
    - type: recall_at_5
      value: 44.044
    - type: map_at_1
      value: 25.24441666666667
    - type: map_at_10
      value: 34.4595
    - type: map_at_100
      value: 35.699999999999996
    - type: map_at_1000
      value: 35.8155
    - type: map_at_3
      value: 31.608333333333338
    - type: map_at_5
      value: 33.189416666666666
    - type: mrr_at_1
      value: 29.825250000000004
    - type: mrr_at_10
      value: 38.60875
    - type: mrr_at_100
      value: 39.46575
    - type: mrr_at_1000
      value: 39.52458333333333
    - type: mrr_at_3
      value: 36.145166666666675
    - type: mrr_at_5
      value: 37.57625
    - type: ndcg_at_1
      value: 29.825250000000004
    - type: ndcg_at_10
      value: 39.88741666666667
    - type: ndcg_at_100
      value: 45.17966666666667
    - type: ndcg_at_1000
      value: 47.440583333333336
    - type: ndcg_at_3
      value: 35.04591666666666
    - type: ndcg_at_5
      value: 37.32025
    - type: precision_at_1
      value: 29.825250000000004
    - type: precision_at_10
      value: 7.07225
    - type: precision_at_100
      value: 1.1462499999999998
    - type: precision_at_1000
      value: 0.15325
    - type: precision_at_3
      value: 16.18375
    - type: precision_at_5
      value: 11.526833333333334
    - type: recall_at_1
      value: 25.24441666666667
    - type: recall_at_10
      value: 51.744916666666676
    - type: recall_at_100
      value: 75.04574999999998
    - type: recall_at_1000
      value: 90.65558333333334
    - type: recall_at_3
      value: 38.28349999999999
    - type: recall_at_5
      value: 44.16591666666667
    - type: map_at_1
      value: 24.237000000000002
    - type: map_at_10
      value: 30.667
    - type: map_at_100
      value: 31.592
    - type: map_at_1000
      value: 31.688
    - type: map_at_3
      value: 28.810999999999996
    - type: map_at_5
      value: 29.788999999999998
    - type: mrr_at_1
      value: 26.840000000000003
    - type: mrr_at_10
      value: 33.305
    - type: mrr_at_100
      value: 34.089000000000006
    - type: mrr_at_1000
      value: 34.159
    - type: mrr_at_3
      value: 31.518
    - type: mrr_at_5
      value: 32.469
    - type: ndcg_at_1
      value: 26.840000000000003
    - type: ndcg_at_10
      value: 34.541
    - type: ndcg_at_100
      value: 39.206
    - type: ndcg_at_1000
      value: 41.592
    - type: ndcg_at_3
      value: 31.005
    - type: ndcg_at_5
      value: 32.554
    - type: precision_at_1
      value: 26.840000000000003
    - type: precision_at_10
      value: 5.3069999999999995
    - type: precision_at_100
      value: 0.8340000000000001
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 13.292000000000002
    - type: precision_at_5
      value: 9.049
    - type: recall_at_1
      value: 24.237000000000002
    - type: recall_at_10
      value: 43.862
    - type: recall_at_100
      value: 65.352
    - type: recall_at_1000
      value: 82.704
    - type: recall_at_3
      value: 34.009
    - type: recall_at_5
      value: 37.878
    - type: map_at_1
      value: 16.482
    - type: map_at_10
      value: 23.249
    - type: map_at_100
      value: 24.388
    - type: map_at_1000
      value: 24.519
    - type: map_at_3
      value: 20.971
    - type: map_at_5
      value: 22.192
    - type: mrr_at_1
      value: 19.993
    - type: mrr_at_10
      value: 26.985
    - type: mrr_at_100
      value: 27.975
    - type: mrr_at_1000
      value: 28.052
    - type: mrr_at_3
      value: 24.954
    - type: mrr_at_5
      value: 26.070999999999998
    - type: ndcg_at_1
      value: 19.993
    - type: ndcg_at_10
      value: 27.656
    - type: ndcg_at_100
      value: 33.256
    - type: ndcg_at_1000
      value: 36.275
    - type: ndcg_at_3
      value: 23.644000000000002
    - type: ndcg_at_5
      value: 25.466
    - type: precision_at_1
      value: 19.993
    - type: precision_at_10
      value: 5.093
    - type: precision_at_100
      value: 0.932
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 11.149000000000001
    - type: precision_at_5
      value: 8.149000000000001
    - type: recall_at_1
      value: 16.482
    - type: recall_at_10
      value: 37.141999999999996
    - type: recall_at_100
      value: 62.696
    - type: recall_at_1000
      value: 84.333
    - type: recall_at_3
      value: 26.031
    - type: recall_at_5
      value: 30.660999999999998
    - type: map_at_1
      value: 24.887999999999998
    - type: map_at_10
      value: 34.101
    - type: map_at_100
      value: 35.27
    - type: map_at_1000
      value: 35.370000000000005
    - type: map_at_3
      value: 31.283
    - type: map_at_5
      value: 32.72
    - type: mrr_at_1
      value: 29.011
    - type: mrr_at_10
      value: 38.004
    - type: mrr_at_100
      value: 38.879000000000005
    - type: mrr_at_1000
      value: 38.938
    - type: mrr_at_3
      value: 35.571999999999996
    - type: mrr_at_5
      value: 36.789
    - type: ndcg_at_1
      value: 29.011
    - type: ndcg_at_10
      value: 39.586
    - type: ndcg_at_100
      value: 44.939
    - type: ndcg_at_1000
      value: 47.236
    - type: ndcg_at_3
      value: 34.4
    - type: ndcg_at_5
      value: 36.519
    - type: precision_at_1
      value: 29.011
    - type: precision_at_10
      value: 6.763
    - type: precision_at_100
      value: 1.059
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 15.609
    - type: precision_at_5
      value: 10.896
    - type: recall_at_1
      value: 24.887999999999998
    - type: recall_at_10
      value: 52.42
    - type: recall_at_100
      value: 75.803
    - type: recall_at_1000
      value: 91.725
    - type: recall_at_3
      value: 38.080999999999996
    - type: recall_at_5
      value: 43.47
    - type: map_at_1
      value: 23.953
    - type: map_at_10
      value: 32.649
    - type: map_at_100
      value: 34.181
    - type: map_at_1000
      value: 34.398
    - type: map_at_3
      value: 29.567
    - type: map_at_5
      value: 31.263
    - type: mrr_at_1
      value: 29.051
    - type: mrr_at_10
      value: 37.419999999999995
    - type: mrr_at_100
      value: 38.396
    - type: mrr_at_1000
      value: 38.458
    - type: mrr_at_3
      value: 34.782999999999994
    - type: mrr_at_5
      value: 36.254999999999995
    - type: ndcg_at_1
      value: 29.051
    - type: ndcg_at_10
      value: 38.595
    - type: ndcg_at_100
      value: 44.6
    - type: ndcg_at_1000
      value: 47.158
    - type: ndcg_at_3
      value: 33.56
    - type: ndcg_at_5
      value: 35.870000000000005
    - type: precision_at_1
      value: 29.051
    - type: precision_at_10
      value: 7.53
    - type: precision_at_100
      value: 1.538
    - type: precision_at_1000
      value: 0.24
    - type: precision_at_3
      value: 15.744
    - type: precision_at_5
      value: 11.542
    - type: recall_at_1
      value: 23.953
    - type: recall_at_10
      value: 50.08200000000001
    - type: recall_at_100
      value: 77.364
    - type: recall_at_1000
      value: 93.57799999999999
    - type: recall_at_3
      value: 35.432
    - type: recall_at_5
      value: 41.875
    - type: map_at_1
      value: 17.72
    - type: map_at_10
      value: 25.724000000000004
    - type: map_at_100
      value: 26.846999999999998
    - type: map_at_1000
      value: 26.964
    - type: map_at_3
      value: 22.909
    - type: map_at_5
      value: 24.596999999999998
    - type: mrr_at_1
      value: 18.854000000000003
    - type: mrr_at_10
      value: 27.182000000000002
    - type: mrr_at_100
      value: 28.182000000000002
    - type: mrr_at_1000
      value: 28.274
    - type: mrr_at_3
      value: 24.276
    - type: mrr_at_5
      value: 26.115
    - type: ndcg_at_1
      value: 18.854000000000003
    - type: ndcg_at_10
      value: 30.470000000000002
    - type: ndcg_at_100
      value: 35.854
    - type: ndcg_at_1000
      value: 38.701
    - type: ndcg_at_3
      value: 24.924
    - type: ndcg_at_5
      value: 27.895999999999997
    - type: precision_at_1
      value: 18.854000000000003
    - type: precision_at_10
      value: 5.009
    - type: precision_at_100
      value: 0.835
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 10.721
    - type: precision_at_5
      value: 8.133
    - type: recall_at_1
      value: 17.72
    - type: recall_at_10
      value: 43.617
    - type: recall_at_100
      value: 67.941
    - type: recall_at_1000
      value: 88.979
    - type: recall_at_3
      value: 29.044999999999998
    - type: recall_at_5
      value: 36.044
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 13.427
    - type: map_at_10
      value: 22.935
    - type: map_at_100
      value: 24.808
    - type: map_at_1000
      value: 24.994
    - type: map_at_3
      value: 19.533
    - type: map_at_5
      value: 21.261
    - type: mrr_at_1
      value: 30.945
    - type: mrr_at_10
      value: 43.242000000000004
    - type: mrr_at_100
      value: 44.013999999999996
    - type: mrr_at_1000
      value: 44.048
    - type: mrr_at_3
      value: 40.109
    - type: mrr_at_5
      value: 42.059999999999995
    - type: ndcg_at_1
      value: 30.945
    - type: ndcg_at_10
      value: 31.828
    - type: ndcg_at_100
      value: 38.801
    - type: ndcg_at_1000
      value: 42.126999999999995
    - type: ndcg_at_3
      value: 26.922
    - type: ndcg_at_5
      value: 28.483999999999998
    - type: precision_at_1
      value: 30.945
    - type: precision_at_10
      value: 9.844
    - type: precision_at_100
      value: 1.7309999999999999
    - type: precision_at_1000
      value: 0.23500000000000001
    - type: precision_at_3
      value: 20.477999999999998
    - type: precision_at_5
      value: 15.27
    - type: recall_at_1
      value: 13.427
    - type: recall_at_10
      value: 37.141000000000005
    - type: recall_at_100
      value: 61.007
    - type: recall_at_1000
      value: 79.742
    - type: recall_at_3
      value: 24.431
    - type: recall_at_5
      value: 29.725
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.122
    - type: map_at_10
      value: 18.799
    - type: map_at_100
      value: 25.724999999999998
    - type: map_at_1000
      value: 27.205000000000002
    - type: map_at_3
      value: 14.194999999999999
    - type: map_at_5
      value: 16.225
    - type: mrr_at_1
      value: 68.0
    - type: mrr_at_10
      value: 76.035
    - type: mrr_at_100
      value: 76.292
    - type: mrr_at_1000
      value: 76.297
    - type: mrr_at_3
      value: 74.458
    - type: mrr_at_5
      value: 75.558
    - type: ndcg_at_1
      value: 56.00000000000001
    - type: ndcg_at_10
      value: 39.761
    - type: ndcg_at_100
      value: 43.736999999999995
    - type: ndcg_at_1000
      value: 51.146
    - type: ndcg_at_3
      value: 45.921
    - type: ndcg_at_5
      value: 42.756
    - type: precision_at_1
      value: 68.0
    - type: precision_at_10
      value: 30.275000000000002
    - type: precision_at_100
      value: 9.343
    - type: precision_at_1000
      value: 1.8270000000000002
    - type: precision_at_3
      value: 49.167
    - type: precision_at_5
      value: 40.699999999999996
    - type: recall_at_1
      value: 9.122
    - type: recall_at_10
      value: 23.669999999999998
    - type: recall_at_100
      value: 48.719
    - type: recall_at_1000
      value: 72.033
    - type: recall_at_3
      value: 15.498999999999999
    - type: recall_at_5
      value: 18.657
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 55.885000000000005
    - type: f1
      value: 50.70726446938571
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 75.709
    - type: map_at_10
      value: 83.345
    - type: map_at_100
      value: 83.557
    - type: map_at_1000
      value: 83.572
    - type: map_at_3
      value: 82.425
    - type: map_at_5
      value: 83.013
    - type: mrr_at_1
      value: 81.593
    - type: mrr_at_10
      value: 88.331
    - type: mrr_at_100
      value: 88.408
    - type: mrr_at_1000
      value: 88.41
    - type: mrr_at_3
      value: 87.714
    - type: mrr_at_5
      value: 88.122
    - type: ndcg_at_1
      value: 81.593
    - type: ndcg_at_10
      value: 86.925
    - type: ndcg_at_100
      value: 87.67
    - type: ndcg_at_1000
      value: 87.924
    - type: ndcg_at_3
      value: 85.5
    - type: ndcg_at_5
      value: 86.283
    - type: precision_at_1
      value: 81.593
    - type: precision_at_10
      value: 10.264
    - type: precision_at_100
      value: 1.084
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 32.388
    - type: precision_at_5
      value: 19.991
    - type: recall_at_1
      value: 75.709
    - type: recall_at_10
      value: 93.107
    - type: recall_at_100
      value: 96.024
    - type: recall_at_1000
      value: 97.603
    - type: recall_at_3
      value: 89.08500000000001
    - type: recall_at_5
      value: 91.15299999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 19.121
    - type: map_at_10
      value: 31.78
    - type: map_at_100
      value: 33.497
    - type: map_at_1000
      value: 33.696
    - type: map_at_3
      value: 27.893
    - type: map_at_5
      value: 30.087000000000003
    - type: mrr_at_1
      value: 38.272
    - type: mrr_at_10
      value: 47.176
    - type: mrr_at_100
      value: 48.002
    - type: mrr_at_1000
      value: 48.044
    - type: mrr_at_3
      value: 45.086999999999996
    - type: mrr_at_5
      value: 46.337
    - type: ndcg_at_1
      value: 38.272
    - type: ndcg_at_10
      value: 39.145
    - type: ndcg_at_100
      value: 45.696999999999996
    - type: ndcg_at_1000
      value: 49.0
    - type: ndcg_at_3
      value: 36.148
    - type: ndcg_at_5
      value: 37.023
    - type: precision_at_1
      value: 38.272
    - type: precision_at_10
      value: 11.065
    - type: precision_at_100
      value: 1.7840000000000003
    - type: precision_at_1000
      value: 0.23600000000000002
    - type: precision_at_3
      value: 24.587999999999997
    - type: precision_at_5
      value: 18.056
    - type: recall_at_1
      value: 19.121
    - type: recall_at_10
      value: 44.857
    - type: recall_at_100
      value: 69.774
    - type: recall_at_1000
      value: 89.645
    - type: recall_at_3
      value: 32.588
    - type: recall_at_5
      value: 37.939
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 36.428
    - type: map_at_10
      value: 56.891999999999996
    - type: map_at_100
      value: 57.82899999999999
    - type: map_at_1000
      value: 57.896
    - type: map_at_3
      value: 53.762
    - type: map_at_5
      value: 55.718
    - type: mrr_at_1
      value: 72.856
    - type: mrr_at_10
      value: 79.245
    - type: mrr_at_100
      value: 79.515
    - type: mrr_at_1000
      value: 79.525
    - type: mrr_at_3
      value: 78.143
    - type: mrr_at_5
      value: 78.822
    - type: ndcg_at_1
      value: 72.856
    - type: ndcg_at_10
      value: 65.204
    - type: ndcg_at_100
      value: 68.552
    - type: ndcg_at_1000
      value: 69.902
    - type: ndcg_at_3
      value: 60.632
    - type: ndcg_at_5
      value: 63.161
    - type: precision_at_1
      value: 72.856
    - type: precision_at_10
      value: 13.65
    - type: precision_at_100
      value: 1.6260000000000001
    - type: precision_at_1000
      value: 0.181
    - type: precision_at_3
      value: 38.753
    - type: precision_at_5
      value: 25.251
    - type: recall_at_1
      value: 36.428
    - type: recall_at_10
      value: 68.25099999999999
    - type: recall_at_100
      value: 81.317
    - type: recall_at_1000
      value: 90.27
    - type: recall_at_3
      value: 58.13
    - type: recall_at_5
      value: 63.126000000000005
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 89.4868
    - type: ap
      value: 84.88319192880247
    - type: f1
      value: 89.46144458052846
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 21.282999999999998
    - type: map_at_10
      value: 33.045
    - type: map_at_100
      value: 34.238
    - type: map_at_1000
      value: 34.29
    - type: map_at_3
      value: 29.305999999999997
    - type: map_at_5
      value: 31.391000000000002
    - type: mrr_at_1
      value: 21.92
    - type: mrr_at_10
      value: 33.649
    - type: mrr_at_100
      value: 34.791
    - type: mrr_at_1000
      value: 34.837
    - type: mrr_at_3
      value: 30.0
    - type: mrr_at_5
      value: 32.039
    - type: ndcg_at_1
      value: 21.92
    - type: ndcg_at_10
      value: 39.729
    - type: ndcg_at_100
      value: 45.484
    - type: ndcg_at_1000
      value: 46.817
    - type: ndcg_at_3
      value: 32.084
    - type: ndcg_at_5
      value: 35.789
    - type: precision_at_1
      value: 21.92
    - type: precision_at_10
      value: 6.297
    - type: precision_at_100
      value: 0.918
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 13.639000000000001
    - type: precision_at_5
      value: 10.054
    - type: recall_at_1
      value: 21.282999999999998
    - type: recall_at_10
      value: 60.343999999999994
    - type: recall_at_100
      value: 86.981
    - type: recall_at_1000
      value: 97.205
    - type: recall_at_3
      value: 39.452999999999996
    - type: recall_at_5
      value: 48.333
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 95.47879616963064
    - type: f1
      value: 95.21800589958251
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 79.09256725946192
    - type: f1
      value: 60.554043889452515
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 75.53463349024882
    - type: f1
      value: 73.14418495756476
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 79.22663080026899
    - type: f1
      value: 79.331456217501
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 34.50316010430136
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 32.15612040042282
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.36227552557184
    - type: mrr
      value: 33.57901344209811
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.6610000000000005
    - type: map_at_10
      value: 12.992
    - type: map_at_100
      value: 16.756999999999998
    - type: map_at_1000
      value: 18.25
    - type: map_at_3
      value: 9.471
    - type: map_at_5
      value: 11.116
    - type: mrr_at_1
      value: 43.653
    - type: mrr_at_10
      value: 53.388999999999996
    - type: mrr_at_100
      value: 53.982
    - type: mrr_at_1000
      value: 54.033
    - type: mrr_at_3
      value: 51.858000000000004
    - type: mrr_at_5
      value: 53.019000000000005
    - type: ndcg_at_1
      value: 41.641
    - type: ndcg_at_10
      value: 34.691
    - type: ndcg_at_100
      value: 32.305
    - type: ndcg_at_1000
      value: 41.132999999999996
    - type: ndcg_at_3
      value: 40.614
    - type: ndcg_at_5
      value: 38.456
    - type: precision_at_1
      value: 43.344
    - type: precision_at_10
      value: 25.881999999999998
    - type: precision_at_100
      value: 8.483
    - type: precision_at_1000
      value: 2.131
    - type: precision_at_3
      value: 38.803
    - type: precision_at_5
      value: 33.87
    - type: recall_at_1
      value: 5.6610000000000005
    - type: recall_at_10
      value: 16.826
    - type: recall_at_100
      value: 32.939
    - type: recall_at_1000
      value: 65.161
    - type: recall_at_3
      value: 10.756
    - type: recall_at_5
      value: 13.331000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 26.692
    - type: map_at_10
      value: 41.065000000000005
    - type: map_at_100
      value: 42.235
    - type: map_at_1000
      value: 42.27
    - type: map_at_3
      value: 36.635
    - type: map_at_5
      value: 39.219
    - type: mrr_at_1
      value: 30.214000000000002
    - type: mrr_at_10
      value: 43.443
    - type: mrr_at_100
      value: 44.326
    - type: mrr_at_1000
      value: 44.352000000000004
    - type: mrr_at_3
      value: 39.623999999999995
    - type: mrr_at_5
      value: 41.898
    - type: ndcg_at_1
      value: 30.214000000000002
    - type: ndcg_at_10
      value: 48.692
    - type: ndcg_at_100
      value: 53.671
    - type: ndcg_at_1000
      value: 54.522000000000006
    - type: ndcg_at_3
      value: 40.245
    - type: ndcg_at_5
      value: 44.580999999999996
    - type: precision_at_1
      value: 30.214000000000002
    - type: precision_at_10
      value: 8.3
    - type: precision_at_100
      value: 1.1079999999999999
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 18.521
    - type: precision_at_5
      value: 13.627
    - type: recall_at_1
      value: 26.692
    - type: recall_at_10
      value: 69.699
    - type: recall_at_100
      value: 91.425
    - type: recall_at_1000
      value: 97.78099999999999
    - type: recall_at_3
      value: 47.711
    - type: recall_at_5
      value: 57.643
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.962
    - type: map_at_10
      value: 84.772
    - type: map_at_100
      value: 85.402
    - type: map_at_1000
      value: 85.418
    - type: map_at_3
      value: 81.89
    - type: map_at_5
      value: 83.685
    - type: mrr_at_1
      value: 81.67
    - type: mrr_at_10
      value: 87.681
    - type: mrr_at_100
      value: 87.792
    - type: mrr_at_1000
      value: 87.79299999999999
    - type: mrr_at_3
      value: 86.803
    - type: mrr_at_5
      value: 87.392
    - type: ndcg_at_1
      value: 81.69
    - type: ndcg_at_10
      value: 88.429
    - type: ndcg_at_100
      value: 89.66
    - type: ndcg_at_1000
      value: 89.762
    - type: ndcg_at_3
      value: 85.75
    - type: ndcg_at_5
      value: 87.20700000000001
    - type: precision_at_1
      value: 81.69
    - type: precision_at_10
      value: 13.395000000000001
    - type: precision_at_100
      value: 1.528
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.507000000000005
    - type: precision_at_5
      value: 24.614
    - type: recall_at_1
      value: 70.962
    - type: recall_at_10
      value: 95.339
    - type: recall_at_100
      value: 99.543
    - type: recall_at_1000
      value: 99.984
    - type: recall_at_3
      value: 87.54899999999999
    - type: recall_at_5
      value: 91.726
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 55.506631779239555
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 60.63731341848479
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.852
    - type: map_at_10
      value: 13.175
    - type: map_at_100
      value: 15.623999999999999
    - type: map_at_1000
      value: 16.002
    - type: map_at_3
      value: 9.103
    - type: map_at_5
      value: 11.068999999999999
    - type: mrr_at_1
      value: 23.9
    - type: mrr_at_10
      value: 35.847
    - type: mrr_at_100
      value: 36.968
    - type: mrr_at_1000
      value: 37.018
    - type: mrr_at_3
      value: 32.300000000000004
    - type: mrr_at_5
      value: 34.14
    - type: ndcg_at_1
      value: 23.9
    - type: ndcg_at_10
      value: 21.889
    - type: ndcg_at_100
      value: 30.903000000000002
    - type: ndcg_at_1000
      value: 36.992000000000004
    - type: ndcg_at_3
      value: 20.274
    - type: ndcg_at_5
      value: 17.773
    - type: precision_at_1
      value: 23.9
    - type: precision_at_10
      value: 11.61
    - type: precision_at_100
      value: 2.4539999999999997
    - type: precision_at_1000
      value: 0.391
    - type: precision_at_3
      value: 19.133
    - type: precision_at_5
      value: 15.740000000000002
    - type: recall_at_1
      value: 4.852
    - type: recall_at_10
      value: 23.507
    - type: recall_at_100
      value: 49.775000000000006
    - type: recall_at_1000
      value: 79.308
    - type: recall_at_3
      value: 11.637
    - type: recall_at_5
      value: 15.947
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 86.03345827446948
    - type: cos_sim_spearman
      value: 80.53174518259549
    - type: euclidean_pearson
      value: 83.44538971660883
    - type: euclidean_spearman
      value: 80.57344324098692
    - type: manhattan_pearson
      value: 83.36528808195459
    - type: manhattan_spearman
      value: 80.48931287157902
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 85.21363088257881
    - type: cos_sim_spearman
      value: 75.56589127055523
    - type: euclidean_pearson
      value: 82.32868324521908
    - type: euclidean_spearman
      value: 75.31928550664554
    - type: manhattan_pearson
      value: 82.31332875713211
    - type: manhattan_spearman
      value: 75.35376322099196
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 85.09085593258487
    - type: cos_sim_spearman
      value: 86.26355088415221
    - type: euclidean_pearson
      value: 85.49646115361156
    - type: euclidean_spearman
      value: 86.20652472228703
    - type: manhattan_pearson
      value: 85.44084081123815
    - type: manhattan_spearman
      value: 86.1162623448951
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 84.68250248349368
    - type: cos_sim_spearman
      value: 82.29883673695083
    - type: euclidean_pearson
      value: 84.17633035446019
    - type: euclidean_spearman
      value: 82.19990511264791
    - type: manhattan_pearson
      value: 84.17408410692279
    - type: manhattan_spearman
      value: 82.249873895981
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 87.31878760045024
    - type: cos_sim_spearman
      value: 88.7364409031183
    - type: euclidean_pearson
      value: 88.230537618603
    - type: euclidean_spearman
      value: 88.76484309646318
    - type: manhattan_pearson
      value: 88.17689071136469
    - type: manhattan_spearman
      value: 88.72809249037928
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 83.41078559110638
    - type: cos_sim_spearman
      value: 85.27439135411049
    - type: euclidean_pearson
      value: 84.5333571592088
    - type: euclidean_spearman
      value: 85.25645460575957
    - type: manhattan_pearson
      value: 84.38428921610226
    - type: manhattan_spearman
      value: 85.07796040798796
  - 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: 88.82374132382576
    - type: cos_sim_spearman
      value: 89.02101343562433
    - type: euclidean_pearson
      value: 89.50729765458932
    - type: euclidean_spearman
      value: 89.04184772869253
    - type: manhattan_pearson
      value: 89.51737904059856
    - type: manhattan_spearman
      value: 89.12925950440676
  - 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: 67.56051823873482
    - type: cos_sim_spearman
      value: 68.50988748185463
    - type: euclidean_pearson
      value: 69.16524346147456
    - type: euclidean_spearman
      value: 68.61859952449579
    - type: manhattan_pearson
      value: 69.10618915706995
    - type: manhattan_spearman
      value: 68.36401769459522
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 85.4159693872625
    - type: cos_sim_spearman
      value: 87.07819121764247
    - type: euclidean_pearson
      value: 87.03013260863153
    - type: euclidean_spearman
      value: 87.06547293631309
    - type: manhattan_pearson
      value: 86.8129744446062
    - type: manhattan_spearman
      value: 86.88494096335627
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 86.47758088996575
    - type: mrr
      value: 96.17891458577733
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 57.538999999999994
    - type: map_at_10
      value: 66.562
    - type: map_at_100
      value: 67.254
    - type: map_at_1000
      value: 67.284
    - type: map_at_3
      value: 63.722
    - type: map_at_5
      value: 65.422
    - type: mrr_at_1
      value: 60.0
    - type: mrr_at_10
      value: 67.354
    - type: mrr_at_100
      value: 67.908
    - type: mrr_at_1000
      value: 67.93299999999999
    - type: mrr_at_3
      value: 65.056
    - type: mrr_at_5
      value: 66.43900000000001
    - type: ndcg_at_1
      value: 60.0
    - type: ndcg_at_10
      value: 70.858
    - type: ndcg_at_100
      value: 73.67099999999999
    - type: ndcg_at_1000
      value: 74.26700000000001
    - type: ndcg_at_3
      value: 65.911
    - type: ndcg_at_5
      value: 68.42200000000001
    - type: precision_at_1
      value: 60.0
    - type: precision_at_10
      value: 9.4
    - type: precision_at_100
      value: 1.083
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 25.444
    - type: precision_at_5
      value: 17.0
    - type: recall_at_1
      value: 57.538999999999994
    - type: recall_at_10
      value: 83.233
    - type: recall_at_100
      value: 95.667
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 69.883
    - type: recall_at_5
      value: 76.19399999999999
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.82574257425742
    - type: cos_sim_ap
      value: 95.78722833053911
    - type: cos_sim_f1
      value: 90.94650205761316
    - type: cos_sim_precision
      value: 93.64406779661016
    - type: cos_sim_recall
      value: 88.4
    - type: dot_accuracy
      value: 99.83366336633664
    - type: dot_ap
      value: 95.89733601612964
    - type: dot_f1
      value: 91.41981613891727
    - type: dot_precision
      value: 93.42379958246346
    - type: dot_recall
      value: 89.5
    - type: euclidean_accuracy
      value: 99.82574257425742
    - type: euclidean_ap
      value: 95.75227035138846
    - type: euclidean_f1
      value: 90.96509240246407
    - type: euclidean_precision
      value: 93.45991561181435
    - type: euclidean_recall
      value: 88.6
    - type: manhattan_accuracy
      value: 99.82574257425742
    - type: manhattan_ap
      value: 95.76278266220176
    - type: manhattan_f1
      value: 91.08409321175279
    - type: manhattan_precision
      value: 92.29979466119097
    - type: manhattan_recall
      value: 89.9
    - type: max_accuracy
      value: 99.83366336633664
    - type: max_ap
      value: 95.89733601612964
    - type: max_f1
      value: 91.41981613891727
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 61.905425988638605
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 36.159589881679736
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 53.0605499476397
    - type: mrr
      value: 53.91594516594517
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.202718009067
    - type: cos_sim_spearman
      value: 31.136199912366987
    - type: dot_pearson
      value: 30.66329011927951
    - type: dot_spearman
      value: 30.107664909625107
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.209
    - type: map_at_10
      value: 1.712
    - type: map_at_100
      value: 9.464
    - type: map_at_1000
      value: 23.437
    - type: map_at_3
      value: 0.609
    - type: map_at_5
      value: 0.9440000000000001
    - type: mrr_at_1
      value: 78.0
    - type: mrr_at_10
      value: 86.833
    - type: mrr_at_100
      value: 86.833
    - type: mrr_at_1000
      value: 86.833
    - type: mrr_at_3
      value: 85.333
    - type: mrr_at_5
      value: 86.833
    - type: ndcg_at_1
      value: 74.0
    - type: ndcg_at_10
      value: 69.14
    - type: ndcg_at_100
      value: 53.047999999999995
    - type: ndcg_at_1000
      value: 48.577
    - type: ndcg_at_3
      value: 75.592
    - type: ndcg_at_5
      value: 72.509
    - type: precision_at_1
      value: 78.0
    - type: precision_at_10
      value: 73.0
    - type: precision_at_100
      value: 54.44
    - type: precision_at_1000
      value: 21.326
    - type: precision_at_3
      value: 80.667
    - type: precision_at_5
      value: 77.2
    - type: recall_at_1
      value: 0.209
    - type: recall_at_10
      value: 1.932
    - type: recall_at_100
      value: 13.211999999999998
    - type: recall_at_1000
      value: 45.774
    - type: recall_at_3
      value: 0.644
    - type: recall_at_5
      value: 1.0290000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.609
    - type: map_at_10
      value: 8.334999999999999
    - type: map_at_100
      value: 14.604000000000001
    - type: map_at_1000
      value: 16.177
    - type: map_at_3
      value: 4.87
    - type: map_at_5
      value: 6.3149999999999995
    - type: mrr_at_1
      value: 32.653
    - type: mrr_at_10
      value: 45.047
    - type: mrr_at_100
      value: 45.808
    - type: mrr_at_1000
      value: 45.808
    - type: mrr_at_3
      value: 41.497
    - type: mrr_at_5
      value: 43.231
    - type: ndcg_at_1
      value: 30.612000000000002
    - type: ndcg_at_10
      value: 21.193
    - type: ndcg_at_100
      value: 34.97
    - type: ndcg_at_1000
      value: 46.69
    - type: ndcg_at_3
      value: 24.823
    - type: ndcg_at_5
      value: 22.872999999999998
    - type: precision_at_1
      value: 32.653
    - type: precision_at_10
      value: 17.959
    - type: precision_at_100
      value: 7.4079999999999995
    - type: precision_at_1000
      value: 1.537
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 22.448999999999998
    - type: recall_at_1
      value: 2.609
    - type: recall_at_10
      value: 13.63
    - type: recall_at_100
      value: 47.014
    - type: recall_at_1000
      value: 83.176
    - type: recall_at_3
      value: 5.925
    - type: recall_at_5
      value: 8.574
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 72.80239999999999
    - type: ap
      value: 15.497911013214791
    - type: f1
      value: 56.258411577947285
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 61.00452744765139
    - type: f1
      value: 61.42228624410908
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 50.00516915962345
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 85.62317458425225
    - type: cos_sim_ap
      value: 72.95115658063823
    - type: cos_sim_f1
      value: 66.78976523344764
    - type: cos_sim_precision
      value: 66.77215189873418
    - type: cos_sim_recall
      value: 66.80738786279683
    - type: dot_accuracy
      value: 85.62317458425225
    - type: dot_ap
      value: 73.10385271517778
    - type: dot_f1
      value: 66.94853829427399
    - type: dot_precision
      value: 61.74242424242424
    - type: dot_recall
      value: 73.11345646437995
    - type: euclidean_accuracy
      value: 85.65893783155511
    - type: euclidean_ap
      value: 72.87428208473992
    - type: euclidean_f1
      value: 66.70919994896005
    - type: euclidean_precision
      value: 64.5910551025451
    - type: euclidean_recall
      value: 68.97097625329816
    - type: manhattan_accuracy
      value: 85.59933241938367
    - type: manhattan_ap
      value: 72.67282695064966
    - type: manhattan_f1
      value: 66.67537215983286
    - type: manhattan_precision
      value: 66.00310237849017
    - type: manhattan_recall
      value: 67.36147757255937
    - type: max_accuracy
      value: 85.65893783155511
    - type: max_ap
      value: 73.10385271517778
    - type: max_f1
      value: 66.94853829427399
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.69096130709822
    - type: cos_sim_ap
      value: 85.30326978668063
    - type: cos_sim_f1
      value: 77.747088683189
    - type: cos_sim_precision
      value: 75.4491451753115
    - type: cos_sim_recall
      value: 80.189405605174
    - type: dot_accuracy
      value: 88.43870066363954
    - type: dot_ap
      value: 84.62999949222983
    - type: dot_f1
      value: 77.3074661963551
    - type: dot_precision
      value: 73.93871239808828
    - type: dot_recall
      value: 80.99784416384355
    - type: euclidean_accuracy
      value: 88.70066363953894
    - type: euclidean_ap
      value: 85.34184508966621
    - type: euclidean_f1
      value: 77.76871756856931
    - type: euclidean_precision
      value: 74.97855917667239
    - type: euclidean_recall
      value: 80.77456113335386
    - type: manhattan_accuracy
      value: 88.68319944114566
    - type: manhattan_ap
      value: 85.3026464242333
    - type: manhattan_f1
      value: 77.66561049296294
    - type: manhattan_precision
      value: 74.4665818849795
    - type: manhattan_recall
      value: 81.15183246073299
    - type: max_accuracy
      value: 88.70066363953894
    - type: max_ap
      value: 85.34184508966621
    - type: max_f1
      value: 77.76871756856931
---

# soumitsr/GIST-small-Embedding-v0-Q8_0-GGUF
This model was converted to GGUF format from [`avsolatorio/GIST-small-Embedding-v0`](https://huggingface.co/avsolatorio/GIST-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/GIST-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 soumitsr/GIST-small-Embedding-v0-Q8_0-GGUF --hf-file gist-small-embedding-v0-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo soumitsr/GIST-small-Embedding-v0-Q8_0-GGUF --hf-file gist-small-embedding-v0-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 soumitsr/GIST-small-Embedding-v0-Q8_0-GGUF --hf-file gist-small-embedding-v0-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo soumitsr/GIST-small-Embedding-v0-Q8_0-GGUF --hf-file gist-small-embedding-v0-q8_0.gguf -c 2048
```
