sentence-transformers pytorch onnx nomic_bert feature-extraction sentence-similarity mteb custom_code arxiv:2402.01613 model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: epoch_0_model
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 78.67164179104476
    - type: ap
      value: 42.7379383648841
    - type: f1
      value: 72.79997373883408
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 90.413775
    - type: ap
      value: 87.08812293673202
    - type: f1
      value: 90.39246586225426
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 47.80799999999999
    - type: f1
      value: 47.25679462673503
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 30.37
    - type: map_at_10
      value: 45.748
    - type: map_at_100
      value: 46.617
    - type: map_at_1000
      value: 46.622
    - type: map_at_3
      value: 40.564
    - type: map_at_5
      value: 43.69
    - type: mrr_at_1
      value: 30.868000000000002
    - type: mrr_at_10
      value: 45.905
    - type: mrr_at_100
      value: 46.787
    - type: mrr_at_1000
      value: 46.792
    - type: mrr_at_3
      value: 40.717999999999996
    - type: mrr_at_5
      value: 43.851
    - type: ndcg_at_1
      value: 30.37
    - type: ndcg_at_10
      value: 54.662
    - type: ndcg_at_100
      value: 58.23700000000001
    - type: ndcg_at_1000
      value: 58.373
    - type: ndcg_at_3
      value: 44.069
    - type: ndcg_at_5
      value: 49.728
    - type: precision_at_1
      value: 30.37
    - type: precision_at_10
      value: 8.321000000000002
    - type: precision_at_100
      value: 0.985
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 18.089
    - type: precision_at_5
      value: 13.613
    - type: recall_at_1
      value: 30.37
    - type: recall_at_10
      value: 83.21499999999999
    - type: recall_at_100
      value: 98.506
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 54.266999999999996
    - type: recall_at_5
      value: 68.065
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 45.85329429748079
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 36.12666783330692
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 57.58783867794241
    - type: mrr
      value: 71.84078617596622
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 87.92453139507079
    - type: cos_sim_spearman
      value: 85.37122234964886
    - type: euclidean_pearson
      value: 86.19345621799168
    - type: euclidean_spearman
      value: 85.37122234964886
    - type: manhattan_pearson
      value: 86.4685290616604
    - type: manhattan_spearman
      value: 85.91400580167537
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 83.81818181818181
    - type: f1
      value: 83.76155217378863
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 38.46362764203256
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 33.13807021168658
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 29.725
    - type: map_at_10
      value: 39.654
    - type: map_at_100
      value: 41.022
    - type: map_at_1000
      value: 41.144999999999996
    - type: map_at_3
      value: 36.819
    - type: map_at_5
      value: 38.376
    - type: mrr_at_1
      value: 36.195
    - type: mrr_at_10
      value: 45.171
    - type: mrr_at_100
      value: 45.987
    - type: mrr_at_1000
      value: 46.033
    - type: mrr_at_3
      value: 43.038
    - type: mrr_at_5
      value: 44.196000000000005
    - type: ndcg_at_1
      value: 36.195
    - type: ndcg_at_10
      value: 45.194
    - type: ndcg_at_100
      value: 50.516000000000005
    - type: ndcg_at_1000
      value: 52.739000000000004
    - type: ndcg_at_3
      value: 41.142
    - type: ndcg_at_5
      value: 42.973
    - type: precision_at_1
      value: 36.195
    - type: precision_at_10
      value: 8.312
    - type: precision_at_100
      value: 1.346
    - type: precision_at_1000
      value: 0.182
    - type: precision_at_3
      value: 19.599
    - type: precision_at_5
      value: 13.847999999999999
    - type: recall_at_1
      value: 29.725
    - type: recall_at_10
      value: 55.51199999999999
    - type: recall_at_100
      value: 78.182
    - type: recall_at_1000
      value: 92.727
    - type: recall_at_3
      value: 43.287
    - type: recall_at_5
      value: 48.732
    - type: map_at_1
      value: 30.23
    - type: map_at_10
      value: 40.091
    - type: map_at_100
      value: 41.251
    - type: map_at_1000
      value: 41.384
    - type: map_at_3
      value: 37.247
    - type: map_at_5
      value: 38.865
    - type: mrr_at_1
      value: 38.279999999999994
    - type: mrr_at_10
      value: 46.288000000000004
    - type: mrr_at_100
      value: 47.022999999999996
    - type: mrr_at_1000
      value: 47.068
    - type: mrr_at_3
      value: 44.395
    - type: mrr_at_5
      value: 45.446
    - type: ndcg_at_1
      value: 38.279999999999994
    - type: ndcg_at_10
      value: 45.647
    - type: ndcg_at_100
      value: 49.851
    - type: ndcg_at_1000
      value: 51.991
    - type: ndcg_at_3
      value: 41.795
    - type: ndcg_at_5
      value: 43.578
    - type: precision_at_1
      value: 38.279999999999994
    - type: precision_at_10
      value: 8.522
    - type: precision_at_100
      value: 1.361
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 20.297
    - type: precision_at_5
      value: 14.255
    - type: recall_at_1
      value: 30.23
    - type: recall_at_10
      value: 55.094
    - type: recall_at_100
      value: 72.887
    - type: recall_at_1000
      value: 86.295
    - type: recall_at_3
      value: 43.244
    - type: recall_at_5
      value: 48.507
    - type: map_at_1
      value: 40.854
    - type: map_at_10
      value: 52.232
    - type: map_at_100
      value: 53.129000000000005
    - type: map_at_1000
      value: 53.185
    - type: map_at_3
      value: 49.094
    - type: map_at_5
      value: 50.834999999999994
    - type: mrr_at_1
      value: 46.708
    - type: mrr_at_10
      value: 56.021
    - type: mrr_at_100
      value: 56.584
    - type: mrr_at_1000
      value: 56.611999999999995
    - type: mrr_at_3
      value: 53.657
    - type: mrr_at_5
      value: 55.027
    - type: ndcg_at_1
      value: 46.708
    - type: ndcg_at_10
      value: 57.89
    - type: ndcg_at_100
      value: 61.541999999999994
    - type: ndcg_at_1000
      value: 62.754
    - type: ndcg_at_3
      value: 52.632
    - type: ndcg_at_5
      value: 55.104
    - type: precision_at_1
      value: 46.708
    - type: precision_at_10
      value: 9.122
    - type: precision_at_100
      value: 1.187
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 23.072
    - type: precision_at_5
      value: 15.661
    - type: recall_at_1
      value: 40.854
    - type: recall_at_10
      value: 70.98
    - type: recall_at_100
      value: 86.947
    - type: recall_at_1000
      value: 95.62
    - type: recall_at_3
      value: 56.782999999999994
    - type: recall_at_5
      value: 62.980000000000004
    - type: map_at_1
      value: 26.366
    - type: map_at_10
      value: 33.674
    - type: map_at_100
      value: 34.58
    - type: map_at_1000
      value: 34.662
    - type: map_at_3
      value: 31.596999999999998
    - type: map_at_5
      value: 32.596000000000004
    - type: mrr_at_1
      value: 28.588
    - type: mrr_at_10
      value: 35.912
    - type: mrr_at_100
      value: 36.696
    - type: mrr_at_1000
      value: 36.760999999999996
    - type: mrr_at_3
      value: 33.823
    - type: mrr_at_5
      value: 34.829
    - type: ndcg_at_1
      value: 28.588
    - type: ndcg_at_10
      value: 38.031
    - type: ndcg_at_100
      value: 42.678
    - type: ndcg_at_1000
      value: 44.871
    - type: ndcg_at_3
      value: 33.815
    - type: ndcg_at_5
      value: 35.531
    - type: precision_at_1
      value: 28.588
    - type: precision_at_10
      value: 5.638
    - type: precision_at_100
      value: 0.8380000000000001
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 13.974
    - type: precision_at_5
      value: 9.401
    - type: recall_at_1
      value: 26.366
    - type: recall_at_10
      value: 49.353
    - type: recall_at_100
      value: 71.194
    - type: recall_at_1000
      value: 87.842
    - type: recall_at_3
      value: 37.829
    - type: recall_at_5
      value: 41.976
    - type: map_at_1
      value: 16.634
    - type: map_at_10
      value: 23.271
    - type: map_at_100
      value: 24.366
    - type: map_at_1000
      value: 24.484
    - type: map_at_3
      value: 21.075
    - type: map_at_5
      value: 22.364
    - type: mrr_at_1
      value: 20.522000000000002
    - type: mrr_at_10
      value: 27.735
    - type: mrr_at_100
      value: 28.691
    - type: mrr_at_1000
      value: 28.762999999999998
    - type: mrr_at_3
      value: 25.518
    - type: mrr_at_5
      value: 26.762000000000004
    - type: ndcg_at_1
      value: 20.522000000000002
    - type: ndcg_at_10
      value: 27.791
    - type: ndcg_at_100
      value: 33.101
    - type: ndcg_at_1000
      value: 36.075
    - type: ndcg_at_3
      value: 23.74
    - type: ndcg_at_5
      value: 25.691000000000003
    - type: precision_at_1
      value: 20.522000000000002
    - type: precision_at_10
      value: 4.963
    - type: precision_at_100
      value: 0.873
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 11.111
    - type: precision_at_5
      value: 8.01
    - type: recall_at_1
      value: 16.634
    - type: recall_at_10
      value: 37.498
    - type: recall_at_100
      value: 60.598
    - type: recall_at_1000
      value: 81.828
    - type: recall_at_3
      value: 26.136
    - type: recall_at_5
      value: 31.211
    - type: map_at_1
      value: 28.200999999999997
    - type: map_at_10
      value: 37.619
    - type: map_at_100
      value: 38.834999999999994
    - type: map_at_1000
      value: 38.951
    - type: map_at_3
      value: 35.119
    - type: map_at_5
      value: 36.559999999999995
    - type: mrr_at_1
      value: 33.782000000000004
    - type: mrr_at_10
      value: 43.033
    - type: mrr_at_100
      value: 43.761
    - type: mrr_at_1000
      value: 43.818
    - type: mrr_at_3
      value: 40.727999999999994
    - type: mrr_at_5
      value: 42.129
    - type: ndcg_at_1
      value: 33.782000000000004
    - type: ndcg_at_10
      value: 43.178
    - type: ndcg_at_100
      value: 48.27
    - type: ndcg_at_1000
      value: 50.559
    - type: ndcg_at_3
      value: 38.974
    - type: ndcg_at_5
      value: 41.019
    - type: precision_at_1
      value: 33.782000000000004
    - type: precision_at_10
      value: 7.575
    - type: precision_at_100
      value: 1.1820000000000002
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 18.223
    - type: precision_at_5
      value: 12.742999999999999
    - type: recall_at_1
      value: 28.200999999999997
    - type: recall_at_10
      value: 54.089
    - type: recall_at_100
      value: 75.57000000000001
    - type: recall_at_1000
      value: 90.827
    - type: recall_at_3
      value: 42.435
    - type: recall_at_5
      value: 47.652
    - type: map_at_1
      value: 25.313000000000002
    - type: map_at_10
      value: 34.329
    - type: map_at_100
      value: 35.445
    - type: map_at_1000
      value: 35.556
    - type: map_at_3
      value: 31.659
    - type: map_at_5
      value: 32.981
    - type: mrr_at_1
      value: 30.822
    - type: mrr_at_10
      value: 39.084
    - type: mrr_at_100
      value: 39.97
    - type: mrr_at_1000
      value: 40.025
    - type: mrr_at_3
      value: 36.815
    - type: mrr_at_5
      value: 38.002
    - type: ndcg_at_1
      value: 30.822
    - type: ndcg_at_10
      value: 39.512
    - type: ndcg_at_100
      value: 44.925
    - type: ndcg_at_1000
      value: 47.274
    - type: ndcg_at_3
      value: 35.055
    - type: ndcg_at_5
      value: 36.788
    - type: precision_at_1
      value: 30.822
    - type: precision_at_10
      value: 7.1
    - type: precision_at_100
      value: 1.15
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_3
      value: 16.476
    - type: precision_at_5
      value: 11.461
    - type: recall_at_1
      value: 25.313000000000002
    - type: recall_at_10
      value: 50.178
    - type: recall_at_100
      value: 74.312
    - type: recall_at_1000
      value: 90.50200000000001
    - type: recall_at_3
      value: 37.626
    - type: recall_at_5
      value: 42.34
    - type: map_at_1
      value: 25.502250000000004
    - type: map_at_10
      value: 33.655166666666666
    - type: map_at_100
      value: 34.72833333333333
    - type: map_at_1000
      value: 34.84375
    - type: map_at_3
      value: 31.253999999999998
    - type: map_at_5
      value: 32.55075
    - type: mrr_at_1
      value: 29.91975
    - type: mrr_at_10
      value: 37.65441666666667
    - type: mrr_at_100
      value: 38.464416666666665
    - type: mrr_at_1000
      value: 38.52591666666667
    - type: mrr_at_3
      value: 35.57858333333333
    - type: mrr_at_5
      value: 36.71083333333333
    - type: ndcg_at_1
      value: 29.91975
    - type: ndcg_at_10
      value: 38.47316666666667
    - type: ndcg_at_100
      value: 43.256416666666674
    - type: ndcg_at_1000
      value: 45.70658333333333
    - type: ndcg_at_3
      value: 34.350833333333334
    - type: ndcg_at_5
      value: 36.184583333333336
    - type: precision_at_1
      value: 29.91975
    - type: precision_at_10
      value: 6.5489999999999995
    - type: precision_at_100
      value: 1.0553333333333332
    - type: precision_at_1000
      value: 0.14516666666666667
    - type: precision_at_3
      value: 15.579083333333333
    - type: precision_at_5
      value: 10.851083333333332
    - type: recall_at_1
      value: 25.502250000000004
    - type: recall_at_10
      value: 48.7965
    - type: recall_at_100
      value: 69.93500000000002
    - type: recall_at_1000
      value: 87.17049999999999
    - type: recall_at_3
      value: 37.20433333333333
    - type: recall_at_5
      value: 42.00783333333333
    - type: map_at_1
      value: 23.777
    - type: map_at_10
      value: 29.932
    - type: map_at_100
      value: 30.778
    - type: map_at_1000
      value: 30.879
    - type: map_at_3
      value: 27.898
    - type: map_at_5
      value: 29.086000000000002
    - type: mrr_at_1
      value: 26.227
    - type: mrr_at_10
      value: 32.443
    - type: mrr_at_100
      value: 33.212
    - type: mrr_at_1000
      value: 33.29
    - type: mrr_at_3
      value: 30.419
    - type: mrr_at_5
      value: 31.616
    - type: ndcg_at_1
      value: 26.227
    - type: ndcg_at_10
      value: 33.774
    - type: ndcg_at_100
      value: 37.917
    - type: ndcg_at_1000
      value: 40.557
    - type: ndcg_at_3
      value: 29.875
    - type: ndcg_at_5
      value: 31.845000000000002
    - type: precision_at_1
      value: 26.227
    - type: precision_at_10
      value: 5.153
    - type: precision_at_100
      value: 0.784
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 12.423
    - type: precision_at_5
      value: 8.773
    - type: recall_at_1
      value: 23.777
    - type: recall_at_10
      value: 43.142
    - type: recall_at_100
      value: 61.68900000000001
    - type: recall_at_1000
      value: 81.37100000000001
    - type: recall_at_3
      value: 32.582
    - type: recall_at_5
      value: 37.403
    - type: map_at_1
      value: 16.659
    - type: map_at_10
      value: 22.926
    - type: map_at_100
      value: 23.837
    - type: map_at_1000
      value: 23.953
    - type: map_at_3
      value: 21.029999999999998
    - type: map_at_5
      value: 22.019
    - type: mrr_at_1
      value: 19.649
    - type: mrr_at_10
      value: 26.32
    - type: mrr_at_100
      value: 27.143
    - type: mrr_at_1000
      value: 27.222
    - type: mrr_at_3
      value: 24.484
    - type: mrr_at_5
      value: 25.468000000000004
    - type: ndcg_at_1
      value: 19.649
    - type: ndcg_at_10
      value: 26.941
    - type: ndcg_at_100
      value: 31.522
    - type: ndcg_at_1000
      value: 34.538999999999994
    - type: ndcg_at_3
      value: 23.419999999999998
    - type: ndcg_at_5
      value: 24.927
    - type: precision_at_1
      value: 19.649
    - type: precision_at_10
      value: 4.7010000000000005
    - type: precision_at_100
      value: 0.8130000000000001
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 10.735999999999999
    - type: precision_at_5
      value: 7.591
    - type: recall_at_1
      value: 16.659
    - type: recall_at_10
      value: 35.721000000000004
    - type: recall_at_100
      value: 56.43
    - type: recall_at_1000
      value: 78.464
    - type: recall_at_3
      value: 25.878
    - type: recall_at_5
      value: 29.731999999999996
    - type: map_at_1
      value: 24.309
    - type: map_at_10
      value: 31.990000000000002
    - type: map_at_100
      value: 32.895
    - type: map_at_1000
      value: 33.0
    - type: map_at_3
      value: 29.848999999999997
    - type: map_at_5
      value: 30.942999999999998
    - type: mrr_at_1
      value: 28.638
    - type: mrr_at_10
      value: 36.036
    - type: mrr_at_100
      value: 36.787
    - type: mrr_at_1000
      value: 36.855
    - type: mrr_at_3
      value: 34.08
    - type: mrr_at_5
      value: 35.073
    - type: ndcg_at_1
      value: 28.638
    - type: ndcg_at_10
      value: 36.588
    - type: ndcg_at_100
      value: 41.152
    - type: ndcg_at_1000
      value: 43.769999999999996
    - type: ndcg_at_3
      value: 32.632
    - type: ndcg_at_5
      value: 34.249
    - type: precision_at_1
      value: 28.638
    - type: precision_at_10
      value: 5.942
    - type: precision_at_100
      value: 0.9249999999999999
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 14.582999999999998
    - type: precision_at_5
      value: 9.944
    - type: recall_at_1
      value: 24.309
    - type: recall_at_10
      value: 46.725
    - type: recall_at_100
      value: 67.11
    - type: recall_at_1000
      value: 85.91499999999999
    - type: recall_at_3
      value: 35.72
    - type: recall_at_5
      value: 39.854
    - type: map_at_1
      value: 22.997999999999998
    - type: map_at_10
      value: 30.564000000000004
    - type: map_at_100
      value: 32.06
    - type: map_at_1000
      value: 32.282
    - type: map_at_3
      value: 28.12
    - type: map_at_5
      value: 29.395
    - type: mrr_at_1
      value: 27.075
    - type: mrr_at_10
      value: 34.510999999999996
    - type: mrr_at_100
      value: 35.549
    - type: mrr_at_1000
      value: 35.616
    - type: mrr_at_3
      value: 32.444
    - type: mrr_at_5
      value: 33.589999999999996
    - type: ndcg_at_1
      value: 27.075
    - type: ndcg_at_10
      value: 35.582
    - type: ndcg_at_100
      value: 41.308
    - type: ndcg_at_1000
      value: 44.385999999999996
    - type: ndcg_at_3
      value: 31.467
    - type: ndcg_at_5
      value: 33.189
    - type: precision_at_1
      value: 27.075
    - type: precision_at_10
      value: 6.68
    - type: precision_at_100
      value: 1.427
    - type: precision_at_1000
      value: 0.231
    - type: precision_at_3
      value: 14.625
    - type: precision_at_5
      value: 10.356
    - type: recall_at_1
      value: 22.997999999999998
    - type: recall_at_10
      value: 45.196
    - type: recall_at_100
      value: 70.319
    - type: recall_at_1000
      value: 90.766
    - type: recall_at_3
      value: 33.487
    - type: recall_at_5
      value: 38.297
    - type: map_at_1
      value: 20.961
    - type: map_at_10
      value: 27.58
    - type: map_at_100
      value: 28.542
    - type: map_at_1000
      value: 28.644
    - type: map_at_3
      value: 25.541000000000004
    - type: map_at_5
      value: 26.589000000000002
    - type: mrr_at_1
      value: 22.551
    - type: mrr_at_10
      value: 29.298999999999996
    - type: mrr_at_100
      value: 30.17
    - type: mrr_at_1000
      value: 30.248
    - type: mrr_at_3
      value: 27.542
    - type: mrr_at_5
      value: 28.392
    - type: ndcg_at_1
      value: 22.551
    - type: ndcg_at_10
      value: 31.55
    - type: ndcg_at_100
      value: 36.295
    - type: ndcg_at_1000
      value: 38.964
    - type: ndcg_at_3
      value: 27.663
    - type: ndcg_at_5
      value: 29.321
    - type: precision_at_1
      value: 22.551
    - type: precision_at_10
      value: 4.88
    - type: precision_at_100
      value: 0.7779999999999999
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 11.83
    - type: precision_at_5
      value: 8.17
    - type: recall_at_1
      value: 20.961
    - type: recall_at_10
      value: 42.07
    - type: recall_at_100
      value: 63.982000000000006
    - type: recall_at_1000
      value: 83.889
    - type: recall_at_3
      value: 31.445
    - type: recall_at_5
      value: 35.410000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 11.314
    - type: map_at_10
      value: 18.983
    - type: map_at_100
      value: 20.851
    - type: map_at_1000
      value: 21.066
    - type: map_at_3
      value: 16.014
    - type: map_at_5
      value: 17.569000000000003
    - type: mrr_at_1
      value: 25.277
    - type: mrr_at_10
      value: 36.657000000000004
    - type: mrr_at_100
      value: 37.646
    - type: mrr_at_1000
      value: 37.686
    - type: mrr_at_3
      value: 33.17
    - type: mrr_at_5
      value: 35.232
    - type: ndcg_at_1
      value: 25.277
    - type: ndcg_at_10
      value: 27.011000000000003
    - type: ndcg_at_100
      value: 34.418
    - type: ndcg_at_1000
      value: 38.089
    - type: ndcg_at_3
      value: 22.026
    - type: ndcg_at_5
      value: 23.866
    - type: precision_at_1
      value: 25.277
    - type: precision_at_10
      value: 8.397
    - type: precision_at_100
      value: 1.6320000000000001
    - type: precision_at_1000
      value: 0.22999999999999998
    - type: precision_at_3
      value: 16.156000000000002
    - type: precision_at_5
      value: 12.612000000000002
    - type: recall_at_1
      value: 11.314
    - type: recall_at_10
      value: 32.474
    - type: recall_at_100
      value: 57.926
    - type: recall_at_1000
      value: 78.387
    - type: recall_at_3
      value: 20.415
    - type: recall_at_5
      value: 25.407999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.835999999999999
    - type: map_at_10
      value: 19.73
    - type: map_at_100
      value: 28.011000000000003
    - type: map_at_1000
      value: 29.519000000000002
    - type: map_at_3
      value: 14.249
    - type: map_at_5
      value: 16.472
    - type: mrr_at_1
      value: 67.0
    - type: mrr_at_10
      value: 74.632
    - type: mrr_at_100
      value: 74.97200000000001
    - type: mrr_at_1000
      value: 74.97500000000001
    - type: mrr_at_3
      value: 72.958
    - type: mrr_at_5
      value: 73.908
    - type: ndcg_at_1
      value: 55.875
    - type: ndcg_at_10
      value: 42.071999999999996
    - type: ndcg_at_100
      value: 46.091
    - type: ndcg_at_1000
      value: 52.737
    - type: ndcg_at_3
      value: 47.079
    - type: ndcg_at_5
      value: 43.788
    - type: precision_at_1
      value: 67.0
    - type: precision_at_10
      value: 33.45
    - type: precision_at_100
      value: 10.633
    - type: precision_at_1000
      value: 2.067
    - type: precision_at_3
      value: 49.583
    - type: precision_at_5
      value: 41.25
    - type: recall_at_1
      value: 8.835999999999999
    - type: recall_at_10
      value: 24.872
    - type: recall_at_100
      value: 51.427
    - type: recall_at_1000
      value: 72.17099999999999
    - type: recall_at_3
      value: 15.631999999999998
    - type: recall_at_5
      value: 18.956
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 48.80500000000001
    - type: f1
      value: 43.91955883597831
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 61.480999999999995
    - type: map_at_10
      value: 72.162
    - type: map_at_100
      value: 72.487
    - type: map_at_1000
      value: 72.504
    - type: map_at_3
      value: 70.354
    - type: map_at_5
      value: 71.509
    - type: mrr_at_1
      value: 66.262
    - type: mrr_at_10
      value: 76.605
    - type: mrr_at_100
      value: 76.833
    - type: mrr_at_1000
      value: 76.839
    - type: mrr_at_3
      value: 74.977
    - type: mrr_at_5
      value: 76.06
    - type: ndcg_at_1
      value: 66.262
    - type: ndcg_at_10
      value: 77.323
    - type: ndcg_at_100
      value: 78.685
    - type: ndcg_at_1000
      value: 79.032
    - type: ndcg_at_3
      value: 74.015
    - type: ndcg_at_5
      value: 75.916
    - type: precision_at_1
      value: 66.262
    - type: precision_at_10
      value: 9.757
    - type: precision_at_100
      value: 1.059
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 29.032999999999998
    - type: precision_at_5
      value: 18.5
    - type: recall_at_1
      value: 61.480999999999995
    - type: recall_at_10
      value: 88.878
    - type: recall_at_100
      value: 94.719
    - type: recall_at_1000
      value: 97.066
    - type: recall_at_3
      value: 79.95100000000001
    - type: recall_at_5
      value: 84.691
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 19.925
    - type: map_at_10
      value: 31.621
    - type: map_at_100
      value: 33.282000000000004
    - type: map_at_1000
      value: 33.455
    - type: map_at_3
      value: 27.504
    - type: map_at_5
      value: 29.921999999999997
    - type: mrr_at_1
      value: 39.660000000000004
    - type: mrr_at_10
      value: 47.366
    - type: mrr_at_100
      value: 48.179
    - type: mrr_at_1000
      value: 48.219
    - type: mrr_at_3
      value: 45.062000000000005
    - type: mrr_at_5
      value: 46.404
    - type: ndcg_at_1
      value: 39.660000000000004
    - type: ndcg_at_10
      value: 39.019
    - type: ndcg_at_100
      value: 45.286
    - type: ndcg_at_1000
      value: 48.370000000000005
    - type: ndcg_at_3
      value: 35.421
    - type: ndcg_at_5
      value: 36.767
    - type: precision_at_1
      value: 39.660000000000004
    - type: precision_at_10
      value: 10.494
    - type: precision_at_100
      value: 1.7069999999999999
    - type: precision_at_1000
      value: 0.22599999999999998
    - type: precision_at_3
      value: 23.200000000000003
    - type: precision_at_5
      value: 17.253
    - type: recall_at_1
      value: 19.925
    - type: recall_at_10
      value: 45.48
    - type: recall_at_100
      value: 68.585
    - type: recall_at_1000
      value: 87.128
    - type: recall_at_3
      value: 31.913000000000004
    - type: recall_at_5
      value: 38.107
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 37.961
    - type: map_at_10
      value: 55.010000000000005
    - type: map_at_100
      value: 55.896
    - type: map_at_1000
      value: 55.962
    - type: map_at_3
      value: 52.03
    - type: map_at_5
      value: 53.866
    - type: mrr_at_1
      value: 75.922
    - type: mrr_at_10
      value: 81.655
    - type: mrr_at_100
      value: 81.879
    - type: mrr_at_1000
      value: 81.889
    - type: mrr_at_3
      value: 80.657
    - type: mrr_at_5
      value: 81.291
    - type: ndcg_at_1
      value: 75.922
    - type: ndcg_at_10
      value: 64.119
    - type: ndcg_at_100
      value: 67.25
    - type: ndcg_at_1000
      value: 68.55499999999999
    - type: ndcg_at_3
      value: 59.792
    - type: ndcg_at_5
      value: 62.165000000000006
    - type: precision_at_1
      value: 75.922
    - type: precision_at_10
      value: 13.155
    - type: precision_at_100
      value: 1.5599999999999998
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_3
      value: 37.461
    - type: precision_at_5
      value: 24.351
    - type: recall_at_1
      value: 37.961
    - type: recall_at_10
      value: 65.77300000000001
    - type: recall_at_100
      value: 78.015
    - type: recall_at_1000
      value: 86.685
    - type: recall_at_3
      value: 56.192
    - type: recall_at_5
      value: 60.878
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 83.7804
    - type: ap
      value: 78.89508987851809
    - type: f1
      value: 83.72392373438922
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 23.807000000000002
    - type: map_at_10
      value: 36.411
    - type: map_at_100
      value: 37.574000000000005
    - type: map_at_1000
      value: 37.618
    - type: map_at_3
      value: 32.653
    - type: map_at_5
      value: 34.902
    - type: mrr_at_1
      value: 24.499000000000002
    - type: mrr_at_10
      value: 37.045
    - type: mrr_at_100
      value: 38.135999999999996
    - type: mrr_at_1000
      value: 38.175
    - type: mrr_at_3
      value: 33.326
    - type: mrr_at_5
      value: 35.561
    - type: ndcg_at_1
      value: 24.512999999999998
    - type: ndcg_at_10
      value: 43.328
    - type: ndcg_at_100
      value: 48.779
    - type: ndcg_at_1000
      value: 49.897999999999996
    - type: ndcg_at_3
      value: 35.713
    - type: ndcg_at_5
      value: 39.729
    - type: precision_at_1
      value: 24.512999999999998
    - type: precision_at_10
      value: 6.7379999999999995
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 15.196000000000002
    - type: precision_at_5
      value: 11.158
    - type: recall_at_1
      value: 23.807000000000002
    - type: recall_at_10
      value: 64.488
    - type: recall_at_100
      value: 89.386
    - type: recall_at_1000
      value: 97.968
    - type: recall_at_3
      value: 43.891000000000005
    - type: recall_at_5
      value: 53.535
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 93.47013223894209
    - type: f1
      value: 93.15020887152107
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 75.27131782945737
    - type: f1
      value: 58.45703758149779
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 72.76395427034298
    - type: f1
      value: 70.6084399610629
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 76.69804976462676
    - type: f1
      value: 76.61599181962723
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.7253797676744
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 30.547731924629424
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.286918745183772
    - type: mrr
      value: 32.47449315230336
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.894
    - type: map_at_10
      value: 13.405000000000001
    - type: map_at_100
      value: 16.586000000000002
    - type: map_at_1000
      value: 17.919
    - type: map_at_3
      value: 10.066
    - type: map_at_5
      value: 11.679
    - type: mrr_at_1
      value: 45.201
    - type: mrr_at_10
      value: 54.018
    - type: mrr_at_100
      value: 54.581999999999994
    - type: mrr_at_1000
      value: 54.623
    - type: mrr_at_3
      value: 51.6
    - type: mrr_at_5
      value: 53.473000000000006
    - type: ndcg_at_1
      value: 43.189
    - type: ndcg_at_10
      value: 35.306
    - type: ndcg_at_100
      value: 31.505
    - type: ndcg_at_1000
      value: 39.991
    - type: ndcg_at_3
      value: 41.108
    - type: ndcg_at_5
      value: 39.039
    - type: precision_at_1
      value: 44.582
    - type: precision_at_10
      value: 26.161
    - type: precision_at_100
      value: 7.867
    - type: precision_at_1000
      value: 2.043
    - type: precision_at_3
      value: 39.112
    - type: precision_at_5
      value: 34.18
    - type: recall_at_1
      value: 5.894
    - type: recall_at_10
      value: 16.88
    - type: recall_at_100
      value: 30.671
    - type: recall_at_1000
      value: 61.42999999999999
    - type: recall_at_3
      value: 11.022
    - type: recall_at_5
      value: 13.697999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 38.440999999999995
    - type: map_at_10
      value: 54.187
    - type: map_at_100
      value: 55.022000000000006
    - type: map_at_1000
      value: 55.044000000000004
    - type: map_at_3
      value: 50.174
    - type: map_at_5
      value: 52.61
    - type: mrr_at_1
      value: 42.903000000000006
    - type: mrr_at_10
      value: 56.699
    - type: mrr_at_100
      value: 57.31
    - type: mrr_at_1000
      value: 57.325
    - type: mrr_at_3
      value: 53.63099999999999
    - type: mrr_at_5
      value: 55.596000000000004
    - type: ndcg_at_1
      value: 42.903000000000006
    - type: ndcg_at_10
      value: 61.434
    - type: ndcg_at_100
      value: 64.852
    - type: ndcg_at_1000
      value: 65.36
    - type: ndcg_at_3
      value: 54.193000000000005
    - type: ndcg_at_5
      value: 58.15
    - type: precision_at_1
      value: 42.903000000000006
    - type: precision_at_10
      value: 9.623
    - type: precision_at_100
      value: 1.1560000000000001
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 24.034
    - type: precision_at_5
      value: 16.779
    - type: recall_at_1
      value: 38.440999999999995
    - type: recall_at_10
      value: 80.72399999999999
    - type: recall_at_100
      value: 95.329
    - type: recall_at_1000
      value: 99.059
    - type: recall_at_3
      value: 62.343
    - type: recall_at_5
      value: 71.304
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.85000000000001
    - type: map_at_10
      value: 84.54
    - type: map_at_100
      value: 85.148
    - type: map_at_1000
      value: 85.168
    - type: map_at_3
      value: 81.631
    - type: map_at_5
      value: 83.45700000000001
    - type: mrr_at_1
      value: 81.58
    - type: mrr_at_10
      value: 87.732
    - type: mrr_at_100
      value: 87.825
    - type: mrr_at_1000
      value: 87.82600000000001
    - type: mrr_at_3
      value: 86.783
    - type: mrr_at_5
      value: 87.437
    - type: ndcg_at_1
      value: 81.56
    - type: ndcg_at_10
      value: 88.32900000000001
    - type: ndcg_at_100
      value: 89.513
    - type: ndcg_at_1000
      value: 89.63799999999999
    - type: ndcg_at_3
      value: 85.51100000000001
    - type: ndcg_at_5
      value: 87.062
    - type: precision_at_1
      value: 81.56
    - type: precision_at_10
      value: 13.349
    - type: precision_at_100
      value: 1.518
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 37.293
    - type: precision_at_5
      value: 24.502
    - type: recall_at_1
      value: 70.85000000000001
    - type: recall_at_10
      value: 95.351
    - type: recall_at_100
      value: 99.405
    - type: recall_at_1000
      value: 99.958
    - type: recall_at_3
      value: 87.184
    - type: recall_at_5
      value: 91.625
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 56.81818576893834
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 61.57033658868022
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.468
    - type: map_at_10
      value: 11.109
    - type: map_at_100
      value: 12.921
    - type: map_at_1000
      value: 13.187999999999999
    - type: map_at_3
      value: 8.094999999999999
    - type: map_at_5
      value: 9.664
    - type: mrr_at_1
      value: 22.1
    - type: mrr_at_10
      value: 32.482
    - type: mrr_at_100
      value: 33.558
    - type: mrr_at_1000
      value: 33.623999999999995
    - type: mrr_at_3
      value: 29.25
    - type: mrr_at_5
      value: 31.080000000000002
    - type: ndcg_at_1
      value: 22.1
    - type: ndcg_at_10
      value: 18.695999999999998
    - type: ndcg_at_100
      value: 25.749
    - type: ndcg_at_1000
      value: 30.711
    - type: ndcg_at_3
      value: 17.974
    - type: ndcg_at_5
      value: 15.684000000000001
    - type: precision_at_1
      value: 22.1
    - type: precision_at_10
      value: 9.56
    - type: precision_at_100
      value: 1.966
    - type: precision_at_1000
      value: 0.316
    - type: precision_at_3
      value: 16.667
    - type: precision_at_5
      value: 13.68
    - type: recall_at_1
      value: 4.468
    - type: recall_at_10
      value: 19.373
    - type: recall_at_100
      value: 39.853
    - type: recall_at_1000
      value: 64.118
    - type: recall_at_3
      value: 10.133000000000001
    - type: recall_at_5
      value: 13.877999999999998
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 80.11452150923512
    - type: cos_sim_spearman
      value: 77.3007421887329
    - type: euclidean_pearson
      value: 78.2493681078981
    - type: euclidean_spearman
      value: 77.3007432741821
    - type: manhattan_pearson
      value: 78.19716818242554
    - type: manhattan_spearman
      value: 77.26439033199102
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 82.70293570563516
    - type: cos_sim_spearman
      value: 77.97040896962338
    - type: euclidean_pearson
      value: 77.98827330337348
    - type: euclidean_spearman
      value: 77.9704358930525
    - type: manhattan_pearson
      value: 78.06991702207395
    - type: manhattan_spearman
      value: 78.03857843100195
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.81236960157503
    - type: cos_sim_spearman
      value: 79.38801416063187
    - type: euclidean_pearson
      value: 79.35003045476847
    - type: euclidean_spearman
      value: 79.38797289536578
    - type: manhattan_pearson
      value: 79.33155563344724
    - type: manhattan_spearman
      value: 79.3858955436803
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.35604880089507
    - type: cos_sim_spearman
      value: 78.17327332594571
    - type: euclidean_pearson
      value: 77.30302038209295
    - type: euclidean_spearman
      value: 78.17327332594571
    - type: manhattan_pearson
      value: 77.31323781935417
    - type: manhattan_spearman
      value: 78.20141256686921
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 84.29348597583
    - type: cos_sim_spearman
      value: 85.50877410088334
    - type: euclidean_pearson
      value: 85.22367284169081
    - type: euclidean_spearman
      value: 85.50877410088334
    - type: manhattan_pearson
      value: 85.17979979737612
    - type: manhattan_spearman
      value: 85.46459282596254
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 83.16190794761513
    - type: cos_sim_spearman
      value: 84.94610605287254
    - type: euclidean_pearson
      value: 83.95587174131369
    - type: euclidean_spearman
      value: 84.94610605287254
    - type: manhattan_pearson
      value: 83.99025745366798
    - type: manhattan_spearman
      value: 84.98123107148953
  - 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: 85.3047190687711
    - type: cos_sim_spearman
      value: 85.86642469958113
    - type: euclidean_pearson
      value: 86.74377658528041
    - type: euclidean_spearman
      value: 85.86642469958113
    - type: manhattan_pearson
      value: 86.56967885987439
    - type: manhattan_spearman
      value: 85.63613272583275
  - 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: 64.8298932792099
    - type: cos_sim_spearman
      value: 64.27626667878636
    - type: euclidean_pearson
      value: 66.01603861201576
    - type: euclidean_spearman
      value: 64.27626667878636
    - type: manhattan_pearson
      value: 66.31232809448106
    - type: manhattan_spearman
      value: 64.46190921631559
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 82.73696291316243
    - type: cos_sim_spearman
      value: 83.41508337893958
    - type: euclidean_pearson
      value: 82.8827053024064
    - type: euclidean_spearman
      value: 83.41508337893958
    - type: manhattan_pearson
      value: 82.85613329045803
    - type: manhattan_spearman
      value: 83.40522047443645
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 75.51490079179645
    - type: mrr
      value: 92.6809655486126
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 58.594
    - type: map_at_10
      value: 67.208
    - type: map_at_100
      value: 67.702
    - type: map_at_1000
      value: 67.73
    - type: map_at_3
      value: 64.815
    - type: map_at_5
      value: 65.946
    - type: mrr_at_1
      value: 61.667
    - type: mrr_at_10
      value: 68.52000000000001
    - type: mrr_at_100
      value: 68.888
    - type: mrr_at_1000
      value: 68.911
    - type: mrr_at_3
      value: 66.833
    - type: mrr_at_5
      value: 67.617
    - type: ndcg_at_1
      value: 61.667
    - type: ndcg_at_10
      value: 71.511
    - type: ndcg_at_100
      value: 73.765
    - type: ndcg_at_1000
      value: 74.40299999999999
    - type: ndcg_at_3
      value: 67.411
    - type: ndcg_at_5
      value: 68.88
    - type: precision_at_1
      value: 61.667
    - type: precision_at_10
      value: 9.433
    - type: precision_at_100
      value: 1.0670000000000002
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 26.222
    - type: precision_at_5
      value: 16.866999999999997
    - type: recall_at_1
      value: 58.594
    - type: recall_at_10
      value: 83.439
    - type: recall_at_100
      value: 94.1
    - type: recall_at_1000
      value: 99.0
    - type: recall_at_3
      value: 71.922
    - type: recall_at_5
      value: 75.678
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.7990099009901
    - type: cos_sim_ap
      value: 94.8316184070519
    - type: cos_sim_f1
      value: 89.75265017667844
    - type: cos_sim_precision
      value: 90.62181447502549
    - type: cos_sim_recall
      value: 88.9
    - type: dot_accuracy
      value: 99.7990099009901
    - type: dot_ap
      value: 94.831611518794
    - type: dot_f1
      value: 89.75265017667844
    - type: dot_precision
      value: 90.62181447502549
    - type: dot_recall
      value: 88.9
    - type: euclidean_accuracy
      value: 99.7990099009901
    - type: euclidean_ap
      value: 94.83161335144017
    - type: euclidean_f1
      value: 89.75265017667844
    - type: euclidean_precision
      value: 90.62181447502549
    - type: euclidean_recall
      value: 88.9
    - type: manhattan_accuracy
      value: 99.8
    - type: manhattan_ap
      value: 94.84210829841739
    - type: manhattan_f1
      value: 89.60905349794238
    - type: manhattan_precision
      value: 92.26694915254238
    - type: manhattan_recall
      value: 87.1
    - type: max_accuracy
      value: 99.8
    - type: max_ap
      value: 94.84210829841739
    - type: max_f1
      value: 89.75265017667844
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 63.18343792633894
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 33.50944549814364
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 48.89100016028111
    - type: mrr
      value: 49.607630931160344
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.628145384101522
    - type: cos_sim_spearman
      value: 31.275306930726675
    - type: dot_pearson
      value: 30.62814883550051
    - type: dot_spearman
      value: 31.275306930726675
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.26
    - type: map_at_10
      value: 2.163
    - type: map_at_100
      value: 12.29
    - type: map_at_1000
      value: 29.221999999999998
    - type: map_at_3
      value: 0.729
    - type: map_at_5
      value: 1.161
    - type: mrr_at_1
      value: 96.0
    - type: mrr_at_10
      value: 98.0
    - type: mrr_at_100
      value: 98.0
    - type: mrr_at_1000
      value: 98.0
    - type: mrr_at_3
      value: 98.0
    - type: mrr_at_5
      value: 98.0
    - type: ndcg_at_1
      value: 89.0
    - type: ndcg_at_10
      value: 82.312
    - type: ndcg_at_100
      value: 61.971
    - type: ndcg_at_1000
      value: 54.065
    - type: ndcg_at_3
      value: 87.87700000000001
    - type: ndcg_at_5
      value: 85.475
    - type: precision_at_1
      value: 96.0
    - type: precision_at_10
      value: 87.4
    - type: precision_at_100
      value: 64.02
    - type: precision_at_1000
      value: 24.093999999999998
    - type: precision_at_3
      value: 94.0
    - type: precision_at_5
      value: 90.8
    - type: recall_at_1
      value: 0.26
    - type: recall_at_10
      value: 2.302
    - type: recall_at_100
      value: 15.148
    - type: recall_at_1000
      value: 50.55
    - type: recall_at_3
      value: 0.744
    - type: recall_at_5
      value: 1.198
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.217
    - type: map_at_10
      value: 11.378
    - type: map_at_100
      value: 18.022
    - type: map_at_1000
      value: 19.544
    - type: map_at_3
      value: 6.079
    - type: map_at_5
      value: 8.559
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 48.423
    - type: mrr_at_100
      value: 49.028
    - type: mrr_at_1000
      value: 49.028
    - type: mrr_at_3
      value: 44.897999999999996
    - type: mrr_at_5
      value: 46.531
    - type: ndcg_at_1
      value: 25.509999999999998
    - type: ndcg_at_10
      value: 27.860000000000003
    - type: ndcg_at_100
      value: 39.34
    - type: ndcg_at_1000
      value: 50.21
    - type: ndcg_at_3
      value: 30.968
    - type: ndcg_at_5
      value: 29.541
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 25.918000000000003
    - type: precision_at_100
      value: 8.184
    - type: precision_at_1000
      value: 1.545
    - type: precision_at_3
      value: 35.374
    - type: precision_at_5
      value: 31.837
    - type: recall_at_1
      value: 2.217
    - type: recall_at_10
      value: 18.511
    - type: recall_at_100
      value: 50.178
    - type: recall_at_1000
      value: 83.07600000000001
    - type: recall_at_3
      value: 7.811999999999999
    - type: recall_at_5
      value: 11.684
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.386
    - type: ap
      value: 14.58573366644018
    - type: f1
      value: 55.0170316975105
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 60.868704018109796
    - type: f1
      value: 61.175908652496624
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 48.72082824812323
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 85.43839780652083
    - type: cos_sim_ap
      value: 72.55258980537292
    - type: cos_sim_f1
      value: 66.4145419055752
    - type: cos_sim_precision
      value: 61.765373269798054
    - type: cos_sim_recall
      value: 71.82058047493403
    - type: dot_accuracy
      value: 85.43839780652083
    - type: dot_ap
      value: 72.55256370197756
    - type: dot_f1
      value: 66.4145419055752
    - type: dot_precision
      value: 61.765373269798054
    - type: dot_recall
      value: 71.82058047493403
    - type: euclidean_accuracy
      value: 85.43839780652083
    - type: euclidean_ap
      value: 72.55259011957311
    - type: euclidean_f1
      value: 66.4145419055752
    - type: euclidean_precision
      value: 61.765373269798054
    - type: euclidean_recall
      value: 71.82058047493403
    - type: manhattan_accuracy
      value: 85.40263455921799
    - type: manhattan_ap
      value: 72.47856062032
    - type: manhattan_f1
      value: 66.39413249969942
    - type: manhattan_precision
      value: 60.989617848464775
    - type: manhattan_recall
      value: 72.84960422163589
    - type: max_accuracy
      value: 85.43839780652083
    - type: max_ap
      value: 72.55259011957311
    - type: max_f1
      value: 66.4145419055752
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.24981565568363
    - type: cos_sim_ap
      value: 86.38437585690401
    - type: cos_sim_f1
      value: 78.79039565086076
    - type: cos_sim_precision
      value: 77.29629629629629
    - type: cos_sim_recall
      value: 80.34339390206344
    - type: dot_accuracy
      value: 89.24981565568363
    - type: dot_ap
      value: 86.38437587564587
    - type: dot_f1
      value: 78.79039565086076
    - type: dot_precision
      value: 77.29629629629629
    - type: dot_recall
      value: 80.34339390206344
    - type: euclidean_accuracy
      value: 89.24981565568363
    - type: euclidean_ap
      value: 86.38437691024106
    - type: euclidean_f1
      value: 78.79039565086076
    - type: euclidean_precision
      value: 77.29629629629629
    - type: euclidean_recall
      value: 80.34339390206344
    - type: manhattan_accuracy
      value: 89.25563705514806
    - type: manhattan_ap
      value: 86.35729146774388
    - type: manhattan_f1
      value: 78.7238059278837
    - type: manhattan_precision
      value: 77.23938653034007
    - type: manhattan_recall
      value: 80.26639975361873
    - type: max_accuracy
      value: 89.25563705514806
    - type: max_ap
      value: 86.38437691024106
    - type: max_f1
      value: 78.79039565086076
---

# nomic-embed-text-v1-ablated: A Reproducible Long Context (8192) Text Embedder 

`nomic-embed-text-v1-ablated` is 8192 context length text encoder. This is a checkpoint trained after modifying the training dataset to be different from the dataset used to train our [final model](https://huggingface.co/nomic-ai/nomic-embed-text-v1). The purpose of releasing this checkpoint is to understand the impact that subsets of our training data had on model outcomes. This release is part of our commitment to open-source training artifacts from our Nomic Embed Text tech report [here](https://arxiv.org/pdf/2402.01613)

If you want to use a model to extract embeddings, we suggest using [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1).


# Join the Nomic Community

- Nomic: [https://nomic.ai](https://nomic.ai)
- Discord: [https://discord.gg/myY5YDR8z8](https://discord.gg/myY5YDR8z8)
- Twitter: [https://twitter.com/nomic_ai](https://twitter.com/nomic_ai)
