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---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: cai-stellaris-text-embeddings
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 64.86567164179104
    - type: ap
      value: 28.30760041689409
    - type: f1
      value: 59.08589995918376
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.168625
    - type: ap
      value: 60.131922961382166
    - type: f1
      value: 65.02463910192814
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.016
    - type: f1
      value: 30.501226228002924
  - task:
      type: Retrieval
    dataset:
      type: arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 24.609
    - type: map_at_10
      value: 38.793
    - type: map_at_100
      value: 40.074
    - type: map_at_1000
      value: 40.083
    - type: map_at_3
      value: 33.736
    - type: map_at_5
      value: 36.642
    - type: mrr_at_1
      value: 25.533
    - type: mrr_at_10
      value: 39.129999999999995
    - type: mrr_at_100
      value: 40.411
    - type: mrr_at_1000
      value: 40.42
    - type: mrr_at_3
      value: 34.033
    - type: mrr_at_5
      value: 36.956
    - type: ndcg_at_1
      value: 24.609
    - type: ndcg_at_10
      value: 47.288000000000004
    - type: ndcg_at_100
      value: 52.654999999999994
    - type: ndcg_at_1000
      value: 52.88699999999999
    - type: ndcg_at_3
      value: 36.86
    - type: ndcg_at_5
      value: 42.085
    - type: precision_at_1
      value: 24.609
    - type: precision_at_10
      value: 7.468
    - type: precision_at_100
      value: 0.979
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.315000000000001
    - type: precision_at_5
      value: 11.721
    - type: recall_at_1
      value: 24.609
    - type: recall_at_10
      value: 74.68
    - type: recall_at_100
      value: 97.866
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 45.946
    - type: recall_at_5
      value: 58.606
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 42.014046191286525
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 31.406159641263052
  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 60.35266033223575
    - type: mrr
      value: 72.66796376907179
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 74.12337662337661
    - type: f1
      value: 73.12122145084057
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.72513663347855
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 29.280150859689826
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 21.787
    - type: map_at_10
      value: 30.409000000000002
    - type: map_at_100
      value: 31.947
    - type: map_at_1000
      value: 32.09
    - type: map_at_3
      value: 27.214
    - type: map_at_5
      value: 28.810999999999996
    - type: mrr_at_1
      value: 27.039
    - type: mrr_at_10
      value: 35.581
    - type: mrr_at_100
      value: 36.584
    - type: mrr_at_1000
      value: 36.645
    - type: mrr_at_3
      value: 32.713
    - type: mrr_at_5
      value: 34.272999999999996
    - type: ndcg_at_1
      value: 27.039
    - type: ndcg_at_10
      value: 36.157000000000004
    - type: ndcg_at_100
      value: 42.598
    - type: ndcg_at_1000
      value: 45.207
    - type: ndcg_at_3
      value: 30.907
    - type: ndcg_at_5
      value: 33.068
    - type: precision_at_1
      value: 27.039
    - type: precision_at_10
      value: 7.295999999999999
    - type: precision_at_100
      value: 1.303
    - type: precision_at_1000
      value: 0.186
    - type: precision_at_3
      value: 14.926
    - type: precision_at_5
      value: 11.044
    - type: recall_at_1
      value: 21.787
    - type: recall_at_10
      value: 47.693999999999996
    - type: recall_at_100
      value: 75.848
    - type: recall_at_1000
      value: 92.713
    - type: recall_at_3
      value: 32.92
    - type: recall_at_5
      value: 38.794000000000004
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 24.560000000000002
    - type: map_at_10
      value: 34.756
    - type: map_at_100
      value: 36.169000000000004
    - type: map_at_1000
      value: 36.298
    - type: map_at_3
      value: 31.592
    - type: map_at_5
      value: 33.426
    - type: mrr_at_1
      value: 31.274
    - type: mrr_at_10
      value: 40.328
    - type: mrr_at_100
      value: 41.125
    - type: mrr_at_1000
      value: 41.171
    - type: mrr_at_3
      value: 37.866
    - type: mrr_at_5
      value: 39.299
    - type: ndcg_at_1
      value: 31.338
    - type: ndcg_at_10
      value: 40.696
    - type: ndcg_at_100
      value: 45.922000000000004
    - type: ndcg_at_1000
      value: 47.982
    - type: ndcg_at_3
      value: 36.116
    - type: ndcg_at_5
      value: 38.324000000000005
    - type: precision_at_1
      value: 31.338
    - type: precision_at_10
      value: 8.083
    - type: precision_at_100
      value: 1.4040000000000001
    - type: precision_at_1000
      value: 0.189
    - type: precision_at_3
      value: 18.089
    - type: precision_at_5
      value: 13.159
    - type: recall_at_1
      value: 24.560000000000002
    - type: recall_at_10
      value: 51.832
    - type: recall_at_100
      value: 74.26899999999999
    - type: recall_at_1000
      value: 87.331
    - type: recall_at_3
      value: 38.086999999999996
    - type: recall_at_5
      value: 44.294
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 27.256999999999998
    - type: map_at_10
      value: 38.805
    - type: map_at_100
      value: 40.04
    - type: map_at_1000
      value: 40.117000000000004
    - type: map_at_3
      value: 35.425000000000004
    - type: map_at_5
      value: 37.317
    - type: mrr_at_1
      value: 31.912000000000003
    - type: mrr_at_10
      value: 42.045
    - type: mrr_at_100
      value: 42.956
    - type: mrr_at_1000
      value: 43.004
    - type: mrr_at_3
      value: 39.195
    - type: mrr_at_5
      value: 40.866
    - type: ndcg_at_1
      value: 31.912000000000003
    - type: ndcg_at_10
      value: 44.826
    - type: ndcg_at_100
      value: 49.85
    - type: ndcg_at_1000
      value: 51.562
    - type: ndcg_at_3
      value: 38.845
    - type: ndcg_at_5
      value: 41.719
    - type: precision_at_1
      value: 31.912000000000003
    - type: precision_at_10
      value: 7.768
    - type: precision_at_100
      value: 1.115
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 18.015
    - type: precision_at_5
      value: 12.814999999999998
    - type: recall_at_1
      value: 27.256999999999998
    - type: recall_at_10
      value: 59.611999999999995
    - type: recall_at_100
      value: 81.324
    - type: recall_at_1000
      value: 93.801
    - type: recall_at_3
      value: 43.589
    - type: recall_at_5
      value: 50.589
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.588
    - type: map_at_10
      value: 22.936999999999998
    - type: map_at_100
      value: 24.015
    - type: map_at_1000
      value: 24.127000000000002
    - type: map_at_3
      value: 20.47
    - type: map_at_5
      value: 21.799
    - type: mrr_at_1
      value: 16.723
    - type: mrr_at_10
      value: 24.448
    - type: mrr_at_100
      value: 25.482
    - type: mrr_at_1000
      value: 25.568999999999996
    - type: mrr_at_3
      value: 21.94
    - type: mrr_at_5
      value: 23.386000000000003
    - type: ndcg_at_1
      value: 16.723
    - type: ndcg_at_10
      value: 27.451999999999998
    - type: ndcg_at_100
      value: 33.182
    - type: ndcg_at_1000
      value: 36.193999999999996
    - type: ndcg_at_3
      value: 22.545
    - type: ndcg_at_5
      value: 24.837
    - type: precision_at_1
      value: 16.723
    - type: precision_at_10
      value: 4.5760000000000005
    - type: precision_at_100
      value: 0.7929999999999999
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 9.944
    - type: precision_at_5
      value: 7.321999999999999
    - type: recall_at_1
      value: 15.588
    - type: recall_at_10
      value: 40.039
    - type: recall_at_100
      value: 67.17699999999999
    - type: recall_at_1000
      value: 90.181
    - type: recall_at_3
      value: 26.663999999999998
    - type: recall_at_5
      value: 32.144
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 12.142999999999999
    - type: map_at_10
      value: 18.355
    - type: map_at_100
      value: 19.611
    - type: map_at_1000
      value: 19.750999999999998
    - type: map_at_3
      value: 16.073999999999998
    - type: map_at_5
      value: 17.187
    - type: mrr_at_1
      value: 15.547
    - type: mrr_at_10
      value: 22.615
    - type: mrr_at_100
      value: 23.671
    - type: mrr_at_1000
      value: 23.759
    - type: mrr_at_3
      value: 20.149
    - type: mrr_at_5
      value: 21.437
    - type: ndcg_at_1
      value: 15.547
    - type: ndcg_at_10
      value: 22.985
    - type: ndcg_at_100
      value: 29.192
    - type: ndcg_at_1000
      value: 32.448
    - type: ndcg_at_3
      value: 18.503
    - type: ndcg_at_5
      value: 20.322000000000003
    - type: precision_at_1
      value: 15.547
    - type: precision_at_10
      value: 4.49
    - type: precision_at_100
      value: 0.8840000000000001
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 8.872
    - type: precision_at_5
      value: 6.741
    - type: recall_at_1
      value: 12.142999999999999
    - type: recall_at_10
      value: 33.271
    - type: recall_at_100
      value: 60.95399999999999
    - type: recall_at_1000
      value: 83.963
    - type: recall_at_3
      value: 20.645
    - type: recall_at_5
      value: 25.34
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.09
    - type: map_at_10
      value: 30.220000000000002
    - type: map_at_100
      value: 31.741999999999997
    - type: map_at_1000
      value: 31.878
    - type: map_at_3
      value: 27.455000000000002
    - type: map_at_5
      value: 28.808
    - type: mrr_at_1
      value: 27.718999999999998
    - type: mrr_at_10
      value: 35.476
    - type: mrr_at_100
      value: 36.53
    - type: mrr_at_1000
      value: 36.602000000000004
    - type: mrr_at_3
      value: 33.157
    - type: mrr_at_5
      value: 34.36
    - type: ndcg_at_1
      value: 27.718999999999998
    - type: ndcg_at_10
      value: 35.547000000000004
    - type: ndcg_at_100
      value: 42.079
    - type: ndcg_at_1000
      value: 44.861000000000004
    - type: ndcg_at_3
      value: 30.932
    - type: ndcg_at_5
      value: 32.748
    - type: precision_at_1
      value: 27.718999999999998
    - type: precision_at_10
      value: 6.795
    - type: precision_at_100
      value: 1.194
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 14.758
    - type: precision_at_5
      value: 10.549
    - type: recall_at_1
      value: 22.09
    - type: recall_at_10
      value: 46.357
    - type: recall_at_100
      value: 74.002
    - type: recall_at_1000
      value: 92.99199999999999
    - type: recall_at_3
      value: 33.138
    - type: recall_at_5
      value: 38.034
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 16.904
    - type: map_at_10
      value: 25.075999999999997
    - type: map_at_100
      value: 26.400000000000002
    - type: map_at_1000
      value: 26.525
    - type: map_at_3
      value: 22.191
    - type: map_at_5
      value: 23.947
    - type: mrr_at_1
      value: 21.461
    - type: mrr_at_10
      value: 29.614
    - type: mrr_at_100
      value: 30.602
    - type: mrr_at_1000
      value: 30.677
    - type: mrr_at_3
      value: 27.017000000000003
    - type: mrr_at_5
      value: 28.626
    - type: ndcg_at_1
      value: 21.461
    - type: ndcg_at_10
      value: 30.304
    - type: ndcg_at_100
      value: 36.521
    - type: ndcg_at_1000
      value: 39.366
    - type: ndcg_at_3
      value: 25.267
    - type: ndcg_at_5
      value: 27.918
    - type: precision_at_1
      value: 21.461
    - type: precision_at_10
      value: 5.868
    - type: precision_at_100
      value: 1.072
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_3
      value: 12.291
    - type: precision_at_5
      value: 9.429
    - type: recall_at_1
      value: 16.904
    - type: recall_at_10
      value: 41.521
    - type: recall_at_100
      value: 68.919
    - type: recall_at_1000
      value: 88.852
    - type: recall_at_3
      value: 27.733999999999998
    - type: recall_at_5
      value: 34.439
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 18.327916666666667
    - type: map_at_10
      value: 26.068
    - type: map_at_100
      value: 27.358833333333333
    - type: map_at_1000
      value: 27.491583333333335
    - type: map_at_3
      value: 23.45508333333333
    - type: map_at_5
      value: 24.857916666666664
    - type: mrr_at_1
      value: 22.05066666666667
    - type: mrr_at_10
      value: 29.805083333333332
    - type: mrr_at_100
      value: 30.80283333333333
    - type: mrr_at_1000
      value: 30.876166666666666
    - type: mrr_at_3
      value: 27.381083333333333
    - type: mrr_at_5
      value: 28.72441666666667
    - type: ndcg_at_1
      value: 22.056000000000004
    - type: ndcg_at_10
      value: 31.029416666666666
    - type: ndcg_at_100
      value: 36.90174999999999
    - type: ndcg_at_1000
      value: 39.716249999999995
    - type: ndcg_at_3
      value: 26.35533333333333
    - type: ndcg_at_5
      value: 28.471500000000006
    - type: precision_at_1
      value: 22.056000000000004
    - type: precision_at_10
      value: 5.7645833333333325
    - type: precision_at_100
      value: 1.0406666666666666
    - type: precision_at_1000
      value: 0.14850000000000002
    - type: precision_at_3
      value: 12.391416666666666
    - type: precision_at_5
      value: 9.112499999999999
    - type: recall_at_1
      value: 18.327916666666667
    - type: recall_at_10
      value: 42.15083333333333
    - type: recall_at_100
      value: 68.38666666666666
    - type: recall_at_1000
      value: 88.24183333333333
    - type: recall_at_3
      value: 29.094416666666667
    - type: recall_at_5
      value: 34.48716666666666
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.009
    - type: map_at_10
      value: 21.251
    - type: map_at_100
      value: 22.337
    - type: map_at_1000
      value: 22.455
    - type: map_at_3
      value: 19.241
    - type: map_at_5
      value: 20.381
    - type: mrr_at_1
      value: 17.638
    - type: mrr_at_10
      value: 24.184
    - type: mrr_at_100
      value: 25.156
    - type: mrr_at_1000
      value: 25.239
    - type: mrr_at_3
      value: 22.29
    - type: mrr_at_5
      value: 23.363999999999997
    - type: ndcg_at_1
      value: 17.638
    - type: ndcg_at_10
      value: 25.269000000000002
    - type: ndcg_at_100
      value: 30.781999999999996
    - type: ndcg_at_1000
      value: 33.757
    - type: ndcg_at_3
      value: 21.457
    - type: ndcg_at_5
      value: 23.293
    - type: precision_at_1
      value: 17.638
    - type: precision_at_10
      value: 4.294
    - type: precision_at_100
      value: 0.771
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 9.815999999999999
    - type: precision_at_5
      value: 7.086
    - type: recall_at_1
      value: 15.009
    - type: recall_at_10
      value: 35.014
    - type: recall_at_100
      value: 60.45399999999999
    - type: recall_at_1000
      value: 82.416
    - type: recall_at_3
      value: 24.131
    - type: recall_at_5
      value: 28.846
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 12.518
    - type: map_at_10
      value: 18.226
    - type: map_at_100
      value: 19.355
    - type: map_at_1000
      value: 19.496
    - type: map_at_3
      value: 16.243
    - type: map_at_5
      value: 17.288999999999998
    - type: mrr_at_1
      value: 15.382000000000001
    - type: mrr_at_10
      value: 21.559
    - type: mrr_at_100
      value: 22.587
    - type: mrr_at_1000
      value: 22.677
    - type: mrr_at_3
      value: 19.597
    - type: mrr_at_5
      value: 20.585
    - type: ndcg_at_1
      value: 15.382000000000001
    - type: ndcg_at_10
      value: 22.198
    - type: ndcg_at_100
      value: 27.860000000000003
    - type: ndcg_at_1000
      value: 31.302999999999997
    - type: ndcg_at_3
      value: 18.541
    - type: ndcg_at_5
      value: 20.089000000000002
    - type: precision_at_1
      value: 15.382000000000001
    - type: precision_at_10
      value: 4.178
    - type: precision_at_100
      value: 0.8380000000000001
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 8.866999999999999
    - type: precision_at_5
      value: 6.476
    - type: recall_at_1
      value: 12.518
    - type: recall_at_10
      value: 31.036
    - type: recall_at_100
      value: 56.727000000000004
    - type: recall_at_1000
      value: 81.66799999999999
    - type: recall_at_3
      value: 20.610999999999997
    - type: recall_at_5
      value: 24.744
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 18.357
    - type: map_at_10
      value: 25.384
    - type: map_at_100
      value: 26.640000000000004
    - type: map_at_1000
      value: 26.762999999999998
    - type: map_at_3
      value: 22.863
    - type: map_at_5
      value: 24.197
    - type: mrr_at_1
      value: 21.735
    - type: mrr_at_10
      value: 29.069
    - type: mrr_at_100
      value: 30.119
    - type: mrr_at_1000
      value: 30.194
    - type: mrr_at_3
      value: 26.663999999999998
    - type: mrr_at_5
      value: 27.904
    - type: ndcg_at_1
      value: 21.735
    - type: ndcg_at_10
      value: 30.153999999999996
    - type: ndcg_at_100
      value: 36.262
    - type: ndcg_at_1000
      value: 39.206
    - type: ndcg_at_3
      value: 25.365
    - type: ndcg_at_5
      value: 27.403
    - type: precision_at_1
      value: 21.735
    - type: precision_at_10
      value: 5.354
    - type: precision_at_100
      value: 0.958
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 11.567
    - type: precision_at_5
      value: 8.469999999999999
    - type: recall_at_1
      value: 18.357
    - type: recall_at_10
      value: 41.205000000000005
    - type: recall_at_100
      value: 68.30000000000001
    - type: recall_at_1000
      value: 89.294
    - type: recall_at_3
      value: 27.969
    - type: recall_at_5
      value: 32.989000000000004
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 18.226
    - type: map_at_10
      value: 25.766
    - type: map_at_100
      value: 27.345000000000002
    - type: map_at_1000
      value: 27.575
    - type: map_at_3
      value: 22.945999999999998
    - type: map_at_5
      value: 24.383
    - type: mrr_at_1
      value: 21.542
    - type: mrr_at_10
      value: 29.448
    - type: mrr_at_100
      value: 30.509999999999998
    - type: mrr_at_1000
      value: 30.575000000000003
    - type: mrr_at_3
      value: 26.482
    - type: mrr_at_5
      value: 28.072999999999997
    - type: ndcg_at_1
      value: 21.542
    - type: ndcg_at_10
      value: 31.392999999999997
    - type: ndcg_at_100
      value: 37.589
    - type: ndcg_at_1000
      value: 40.717
    - type: ndcg_at_3
      value: 26.179000000000002
    - type: ndcg_at_5
      value: 28.557
    - type: precision_at_1
      value: 21.542
    - type: precision_at_10
      value: 6.462
    - type: precision_at_100
      value: 1.415
    - type: precision_at_1000
      value: 0.234
    - type: precision_at_3
      value: 12.187000000000001
    - type: precision_at_5
      value: 9.605
    - type: recall_at_1
      value: 18.226
    - type: recall_at_10
      value: 42.853
    - type: recall_at_100
      value: 70.97200000000001
    - type: recall_at_1000
      value: 91.662
    - type: recall_at_3
      value: 28.555999999999997
    - type: recall_at_5
      value: 34.203
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.495999999999999
    - type: map_at_10
      value: 21.631
    - type: map_at_100
      value: 22.705000000000002
    - type: map_at_1000
      value: 22.823999999999998
    - type: map_at_3
      value: 19.747
    - type: map_at_5
      value: 20.75
    - type: mrr_at_1
      value: 16.636
    - type: mrr_at_10
      value: 23.294
    - type: mrr_at_100
      value: 24.312
    - type: mrr_at_1000
      value: 24.401999999999997
    - type: mrr_at_3
      value: 21.503
    - type: mrr_at_5
      value: 22.52
    - type: ndcg_at_1
      value: 16.636
    - type: ndcg_at_10
      value: 25.372
    - type: ndcg_at_100
      value: 30.984
    - type: ndcg_at_1000
      value: 33.992
    - type: ndcg_at_3
      value: 21.607000000000003
    - type: ndcg_at_5
      value: 23.380000000000003
    - type: precision_at_1
      value: 16.636
    - type: precision_at_10
      value: 4.011
    - type: precision_at_100
      value: 0.741
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 9.365
    - type: precision_at_5
      value: 6.654
    - type: recall_at_1
      value: 15.495999999999999
    - type: recall_at_10
      value: 35.376000000000005
    - type: recall_at_100
      value: 61.694
    - type: recall_at_1000
      value: 84.029
    - type: recall_at_3
      value: 25.089
    - type: recall_at_5
      value: 29.43
  - task:
      type: Retrieval
    dataset:
      type: climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.662
    - type: map_at_10
      value: 8.638
    - type: map_at_100
      value: 9.86
    - type: map_at_1000
      value: 10.032
    - type: map_at_3
      value: 6.793
    - type: map_at_5
      value: 7.761
    - type: mrr_at_1
      value: 10.684000000000001
    - type: mrr_at_10
      value: 17.982
    - type: mrr_at_100
      value: 19.152
    - type: mrr_at_1000
      value: 19.231
    - type: mrr_at_3
      value: 15.113999999999999
    - type: mrr_at_5
      value: 16.658
    - type: ndcg_at_1
      value: 10.684000000000001
    - type: ndcg_at_10
      value: 13.483
    - type: ndcg_at_100
      value: 19.48
    - type: ndcg_at_1000
      value: 23.232
    - type: ndcg_at_3
      value: 9.75
    - type: ndcg_at_5
      value: 11.208
    - type: precision_at_1
      value: 10.684000000000001
    - type: precision_at_10
      value: 4.573
    - type: precision_at_100
      value: 1.085
    - type: precision_at_1000
      value: 0.17600000000000002
    - type: precision_at_3
      value: 7.514
    - type: precision_at_5
      value: 6.241
    - type: recall_at_1
      value: 4.662
    - type: recall_at_10
      value: 18.125
    - type: recall_at_100
      value: 39.675
    - type: recall_at_1000
      value: 61.332
    - type: recall_at_3
      value: 9.239
    - type: recall_at_5
      value: 12.863
  - task:
      type: Retrieval
    dataset:
      type: dbpedia-entity
      name: MTEB DBPedia
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.869
    - type: map_at_10
      value: 8.701
    - type: map_at_100
      value: 11.806999999999999
    - type: map_at_1000
      value: 12.676000000000002
    - type: map_at_3
      value: 6.3100000000000005
    - type: map_at_5
      value: 7.471
    - type: mrr_at_1
      value: 38.5
    - type: mrr_at_10
      value: 48.754
    - type: mrr_at_100
      value: 49.544
    - type: mrr_at_1000
      value: 49.568
    - type: mrr_at_3
      value: 46.167
    - type: mrr_at_5
      value: 47.679
    - type: ndcg_at_1
      value: 30.5
    - type: ndcg_at_10
      value: 22.454
    - type: ndcg_at_100
      value: 25.380999999999997
    - type: ndcg_at_1000
      value: 31.582
    - type: ndcg_at_3
      value: 25.617
    - type: ndcg_at_5
      value: 24.254
    - type: precision_at_1
      value: 38.5
    - type: precision_at_10
      value: 18.4
    - type: precision_at_100
      value: 6.02
    - type: precision_at_1000
      value: 1.34
    - type: precision_at_3
      value: 29.083
    - type: precision_at_5
      value: 24.85
    - type: recall_at_1
      value: 3.869
    - type: recall_at_10
      value: 12.902
    - type: recall_at_100
      value: 30.496000000000002
    - type: recall_at_1000
      value: 51.066
    - type: recall_at_3
      value: 7.396
    - type: recall_at_5
      value: 9.852
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 36.705000000000005
    - type: f1
      value: 32.72625967901387
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 66.89840000000001
    - type: ap
      value: 61.43175045563333
    - type: f1
      value: 66.67945656405962
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.12676698586411
    - type: f1
      value: 88.48426641357668
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 62.61513907888736
    - type: f1
      value: 40.96251281624023
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.95359784801614
    - type: f1
      value: 58.85654625260125
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.1983860121049
    - type: f1
      value: 68.73455379435487
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.772017072895846
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 30.944581802089044
  - task:
      type: Reranking
    dataset:
      type: mteb/mind_small
      name: MTEB MindSmallReranking
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.977328237697133
    - type: mrr
      value: 32.02612207306447
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 43.08588418858767
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 56.53785276450797
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 81.44882719207659
    - type: mrr
      value: 94.71082022552609
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.77821782178218
    - type: cos_sim_ap
      value: 93.22909989796688
    - type: cos_sim_f1
      value: 88.41778697001035
    - type: cos_sim_precision
      value: 91.54175588865097
    - type: cos_sim_recall
      value: 85.5
    - type: dot_accuracy
      value: 99.77821782178218
    - type: dot_ap
      value: 93.2290998979669
    - type: dot_f1
      value: 88.41778697001035
    - type: dot_precision
      value: 91.54175588865097
    - type: dot_recall
      value: 85.5
    - type: euclidean_accuracy
      value: 99.77821782178218
    - type: euclidean_ap
      value: 93.2290998979669
    - type: euclidean_f1
      value: 88.41778697001035
    - type: euclidean_precision
      value: 91.54175588865097
    - type: euclidean_recall
      value: 85.5
    - type: manhattan_accuracy
      value: 99.77524752475247
    - type: manhattan_ap
      value: 93.18492132451668
    - type: manhattan_f1
      value: 88.19552782111285
    - type: manhattan_precision
      value: 91.87432286023835
    - type: manhattan_recall
      value: 84.8
    - type: max_accuracy
      value: 99.77821782178218
    - type: max_ap
      value: 93.2290998979669
    - type: max_f1
      value: 88.41778697001035
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 48.225188905490285
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 34.76195959924048
  - task:
      type: Reranking
    dataset:
      type: mteb/stackoverflowdupquestions-reranking
      name: MTEB StackOverflowDupQuestions
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 48.16986372261003
    - type: mrr
      value: 48.7718837535014
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 63.567200000000014
    - type: ap
      value: 11.412292644030266
    - type: f1
      value: 49.102043399207716
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 51.04414261460101
    - type: f1
      value: 51.22880449155832
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 34.35595440606073
  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.6754485307266
    - type: cos_sim_ap
      value: 69.6007143804539
    - type: cos_sim_f1
      value: 65.99822312476202
    - type: cos_sim_precision
      value: 63.58522866226461
    - type: cos_sim_recall
      value: 68.60158311345647
    - type: dot_accuracy
      value: 84.6754485307266
    - type: dot_ap
      value: 69.60070881520775
    - type: dot_f1
      value: 65.99822312476202
    - type: dot_precision
      value: 63.58522866226461
    - type: dot_recall
      value: 68.60158311345647
    - type: euclidean_accuracy
      value: 84.6754485307266
    - type: euclidean_ap
      value: 69.60071394457518
    - type: euclidean_f1
      value: 65.99822312476202
    - type: euclidean_precision
      value: 63.58522866226461
    - type: euclidean_recall
      value: 68.60158311345647
    - type: manhattan_accuracy
      value: 84.6754485307266
    - type: manhattan_ap
      value: 69.57324451019119
    - type: manhattan_f1
      value: 65.7235045917101
    - type: manhattan_precision
      value: 62.04311152764761
    - type: manhattan_recall
      value: 69.86807387862797
    - type: max_accuracy
      value: 84.6754485307266
    - type: max_ap
      value: 69.6007143804539
    - type: max_f1
      value: 65.99822312476202
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.63922847052432
    - type: cos_sim_ap
      value: 83.48934190421085
    - type: cos_sim_f1
      value: 75.42265503384861
    - type: cos_sim_precision
      value: 71.17868124359413
    - type: cos_sim_recall
      value: 80.20480443486295
    - type: dot_accuracy
      value: 87.63922847052432
    - type: dot_ap
      value: 83.4893468701264
    - type: dot_f1
      value: 75.42265503384861
    - type: dot_precision
      value: 71.17868124359413
    - type: dot_recall
      value: 80.20480443486295
    - type: euclidean_accuracy
      value: 87.63922847052432
    - type: euclidean_ap
      value: 83.48934073168017
    - type: euclidean_f1
      value: 75.42265503384861
    - type: euclidean_precision
      value: 71.17868124359413
    - type: euclidean_recall
      value: 80.20480443486295
    - type: manhattan_accuracy
      value: 87.66251406838204
    - type: manhattan_ap
      value: 83.46319621504654
    - type: manhattan_f1
      value: 75.41883304448297
    - type: manhattan_precision
      value: 71.0089747076421
    - type: manhattan_recall
      value: 80.41268863566368
    - type: max_accuracy
      value: 87.66251406838204
    - type: max_ap
      value: 83.4893468701264
    - type: max_f1
      value: 75.42265503384861
---


# {MODEL_NAME}

This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.

<!--- Describe your model here -->

## Usage (Sentence-Transformers)

Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('{MODEL_NAME}')
embeddings = model.encode(sentences)
print(embeddings)
```



## Evaluation Results

<!--- Describe how your model was evaluated -->

For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME})


## Training
The model was trained with the parameters:

**DataLoader**:

`torch.utils.data.dataloader.DataLoader` of length 15607 with parameters:
```
{'batch_size': 48, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
```

**Loss**:

`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters:
  ```
  {'scale': 20.0, 'similarity_fct': 'cos_sim'}
  ```

Parameters of the fit()-Method:
```
{
    "epochs": 10,
    "evaluation_steps": 0,
    "evaluator": "NoneType",
    "max_grad_norm": 1,
    "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
    "optimizer_params": {
        "lr": 2e-05
    },
    "scheduler": "WarmupLinear",
    "steps_per_epoch": null,
    "warmup_steps": 1000,
    "weight_decay": 0.01
}
```


## Full Model Architecture
```
SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
  (2): Normalize()
)
```

## Citing & Authors

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