sentence-transformers safetensors modernbert feature-extraction sentence-similarity mteb en arxiv:2402.01613 base_model:answerdotai/ModernBERT-base base_model:finetune:answerdotai/ModernBERT-base license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model:
- answerdotai/ModernBERT-base
language:
- en
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: binarize_False
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 76.20895522388061
    - type: ap
      value: 39.2507182700391
    - type: f1
      value: 70.1524994873644
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 91.66092499999999
    - type: ap
      value: 88.67291765528996
    - type: f1
      value: 91.65254265062715
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 46.768
    - type: f1
      value: 46.1529444051673
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 24.964
    - type: map_at_10
      value: 39.891
    - type: map_at_100
      value: 41.015
    - type: map_at_1000
      value: 41.027
    - type: map_at_20
      value: 40.788999999999994
    - type: map_at_3
      value: 35.016999999999996
    - type: map_at_5
      value: 37.445
    - type: mrr_at_1
      value: 25.462
    - type: mrr_at_10
      value: 40.081
    - type: mrr_at_100
      value: 41.204
    - type: mrr_at_1000
      value: 41.216
    - type: mrr_at_20
      value: 40.979
    - type: mrr_at_3
      value: 35.171
    - type: mrr_at_5
      value: 37.66
    - type: ndcg_at_1
      value: 24.964
    - type: ndcg_at_10
      value: 48.815999999999995
    - type: ndcg_at_100
      value: 53.415
    - type: ndcg_at_1000
      value: 53.70399999999999
    - type: ndcg_at_20
      value: 51.983000000000004
    - type: ndcg_at_3
      value: 38.417
    - type: ndcg_at_5
      value: 42.833
    - type: precision_at_1
      value: 24.964
    - type: precision_at_10
      value: 7.774
    - type: precision_at_100
      value: 0.9740000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.502
    - type: precision_at_3
      value: 16.098000000000003
    - type: precision_at_5
      value: 11.821
    - type: recall_at_1
      value: 24.964
    - type: recall_at_10
      value: 77.738
    - type: recall_at_100
      value: 97.368
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_20
      value: 90.04299999999999
    - type: recall_at_3
      value: 48.293
    - type: recall_at_5
      value: 59.104
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
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      value: 47.46642893138737
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  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
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  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 59.546570214269444
    - type: mrr
      value: 73.57197819109176
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 88.82818534163955
    - type: cos_sim_spearman
      value: 87.48572836142807
    - type: euclidean_pearson
      value: 87.85699699546558
    - type: euclidean_spearman
      value: 87.43873933894409
    - type: manhattan_pearson
      value: 87.41736797732888
    - type: manhattan_spearman
      value: 87.07909258993207
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 84.57792207792207
    - type: f1
      value: 84.52727174280496
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 38.72890855696805
    - type: v_measures
      value:
      - 0.37363201017038467
      - 0.39757192882016223
      - 0.3941873172297799
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  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 33.88310773970377
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      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
      - 0.3416913241231775
      - 0.343634850219928
      - 0.3538569088433259
      - 0.330378640451087
      - 0.33046099405309765
      - 0.35265391146515984
      - 0.3331545004828837
      - 0.3245349825114234
      - 0.3352908890916282
      - 0.3426537727286653
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 33.62
    - type: map_at_10
      value: 45.384
    - type: map_at_100
      value: 46.739999999999995
    - type: map_at_1000
      value: 46.847
    - type: map_at_20
      value: 46.099000000000004
    - type: map_at_3
      value: 41.766
    - type: map_at_5
      value: 43.891000000000005
    - type: mrr_at_1
      value: 40.916000000000004
    - type: mrr_at_10
      value: 51.15
    - type: mrr_at_100
      value: 51.797000000000004
    - type: mrr_at_1000
      value: 51.833
    - type: mrr_at_20
      value: 51.529
    - type: mrr_at_3
      value: 48.592999999999996
    - type: mrr_at_5
      value: 50.124
    - type: ndcg_at_1
      value: 40.916000000000004
    - type: ndcg_at_10
      value: 51.76500000000001
    - type: ndcg_at_100
      value: 56.706
    - type: ndcg_at_1000
      value: 58.406000000000006
    - type: ndcg_at_20
      value: 53.53
    - type: ndcg_at_3
      value: 46.916999999999994
    - type: ndcg_at_5
      value: 49.282
    - type: precision_at_1
      value: 40.916000000000004
    - type: precision_at_10
      value: 9.9
    - type: precision_at_100
      value: 1.534
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_20
      value: 5.722
    - type: precision_at_3
      value: 22.747
    - type: precision_at_5
      value: 16.338
    - type: recall_at_1
      value: 33.62
    - type: recall_at_10
      value: 63.768
    - type: recall_at_100
      value: 84.629
    - type: recall_at_1000
      value: 95.488
    - type: recall_at_20
      value: 70.127
    - type: recall_at_3
      value: 49.563
    - type: recall_at_5
      value: 56.467999999999996
    - type: map_at_1
      value: 28.017500000000002
    - type: map_at_10
      value: 37.226000000000006
    - type: map_at_100
      value: 38.387249999999995
    - type: map_at_1000
      value: 38.497
    - type: map_at_20
      value: 37.8685
    - type: map_at_3
      value: 34.45716666666666
    - type: map_at_5
      value: 36.02891666666667
    - type: mrr_at_1
      value: 33.0525
    - type: mrr_at_10
      value: 41.375249999999994
    - type: mrr_at_100
      value: 42.214083333333335
    - type: mrr_at_1000
      value: 42.266416666666665
    - type: mrr_at_20
      value: 41.868833333333335
    - type: mrr_at_3
      value: 39.14641666666667
    - type: mrr_at_5
      value: 40.44550000000001
    - type: ndcg_at_1
      value: 33.0525
    - type: ndcg_at_10
      value: 42.40116666666667
    - type: ndcg_at_100
      value: 47.34408333333333
    - type: ndcg_at_1000
      value: 49.45733333333333
    - type: ndcg_at_20
      value: 44.33925
    - type: ndcg_at_3
      value: 37.934916666666666
    - type: ndcg_at_5
      value: 40.07458333333334
    - type: precision_at_1
      value: 33.0525
    - type: precision_at_10
      value: 7.330500000000001
    - type: precision_at_100
      value: 1.1537499999999998
    - type: precision_at_1000
      value: 0.1514166666666667
    - type: precision_at_20
      value: 4.298583333333333
    - type: precision_at_3
      value: 17.37725
    - type: precision_at_5
      value: 12.249500000000001
    - type: recall_at_1
      value: 28.017500000000002
    - type: recall_at_10
      value: 53.424416666666666
    - type: recall_at_100
      value: 75.08983333333332
    - type: recall_at_1000
      value: 89.7495
    - type: recall_at_20
      value: 60.53375000000001
    - type: recall_at_3
      value: 40.93975000000001
    - type: recall_at_5
      value: 46.51383333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 32.43
    - type: map_at_10
      value: 43.56
    - type: map_at_100
      value: 44.772
    - type: map_at_1000
      value: 44.894
    - type: map_at_20
      value: 44.207
    - type: map_at_3
      value: 40.163
    - type: map_at_5
      value: 42.053000000000004
    - type: mrr_at_1
      value: 40.764
    - type: mrr_at_10
      value: 49.718
    - type: mrr_at_100
      value: 50.265
    - type: mrr_at_1000
      value: 50.304
    - type: mrr_at_20
      value: 50.009
    - type: mrr_at_3
      value: 47.473
    - type: mrr_at_5
      value: 48.801
    - type: ndcg_at_1
      value: 40.764
    - type: ndcg_at_10
      value: 49.571
    - type: ndcg_at_100
      value: 53.474999999999994
    - type: ndcg_at_1000
      value: 55.309
    - type: ndcg_at_20
      value: 51.001
    - type: ndcg_at_3
      value: 45.107
    - type: ndcg_at_5
      value: 47.164
    - type: precision_at_1
      value: 40.764
    - type: precision_at_10
      value: 9.49
    - type: precision_at_100
      value: 1.467
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_20
      value: 5.513
    - type: precision_at_3
      value: 21.996
    - type: precision_at_5
      value: 15.631
    - type: recall_at_1
      value: 32.43
    - type: recall_at_10
      value: 59.935
    - type: recall_at_100
      value: 76.386
    - type: recall_at_1000
      value: 88.011
    - type: recall_at_20
      value: 65.071
    - type: recall_at_3
      value: 46.56
    - type: recall_at_5
      value: 52.513
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 43.195
    - type: map_at_10
      value: 56.013000000000005
    - type: map_at_100
      value: 56.957
    - type: map_at_1000
      value: 57.006
    - type: map_at_20
      value: 56.596000000000004
    - type: map_at_3
      value: 52.807
    - type: map_at_5
      value: 54.555
    - type: mrr_at_1
      value: 49.592000000000006
    - type: mrr_at_10
      value: 59.399
    - type: mrr_at_100
      value: 59.995
    - type: mrr_at_1000
      value: 60.019999999999996
    - type: mrr_at_20
      value: 59.77400000000001
    - type: mrr_at_3
      value: 57.220000000000006
    - type: mrr_at_5
      value: 58.48100000000001
    - type: ndcg_at_1
      value: 49.592000000000006
    - type: ndcg_at_10
      value: 61.682
    - type: ndcg_at_100
      value: 65.33
    - type: ndcg_at_1000
      value: 66.29
    - type: ndcg_at_20
      value: 63.298
    - type: ndcg_at_3
      value: 56.538999999999994
    - type: ndcg_at_5
      value: 58.946
    - type: precision_at_1
      value: 49.592000000000006
    - type: precision_at_10
      value: 9.824
    - type: precision_at_100
      value: 1.25
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_20
      value: 5.423
    - type: precision_at_3
      value: 25.119999999999997
    - type: precision_at_5
      value: 16.977999999999998
    - type: recall_at_1
      value: 43.195
    - type: recall_at_10
      value: 74.979
    - type: recall_at_100
      value: 90.701
    - type: recall_at_1000
      value: 97.474
    - type: recall_at_20
      value: 80.951
    - type: recall_at_3
      value: 61.275999999999996
    - type: recall_at_5
      value: 67.143
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 27.254
    - type: map_at_10
      value: 35.74
    - type: map_at_100
      value: 36.702
    - type: map_at_1000
      value: 36.782
    - type: map_at_20
      value: 36.258
    - type: map_at_3
      value: 33.341
    - type: map_at_5
      value: 34.666999999999994
    - type: mrr_at_1
      value: 28.927000000000003
    - type: mrr_at_10
      value: 37.396
    - type: mrr_at_100
      value: 38.267
    - type: mrr_at_1000
      value: 38.328
    - type: mrr_at_20
      value: 37.865
    - type: mrr_at_3
      value: 35.141
    - type: mrr_at_5
      value: 36.35
    - type: ndcg_at_1
      value: 28.927000000000003
    - type: ndcg_at_10
      value: 40.403
    - type: ndcg_at_100
      value: 45.241
    - type: ndcg_at_1000
      value: 47.278999999999996
    - type: ndcg_at_20
      value: 42.241
    - type: ndcg_at_3
      value: 35.754999999999995
    - type: ndcg_at_5
      value: 37.935
    - type: precision_at_1
      value: 28.927000000000003
    - type: precision_at_10
      value: 6.056
    - type: precision_at_100
      value: 0.893
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_20
      value: 3.458
    - type: precision_at_3
      value: 14.915000000000001
    - type: precision_at_5
      value: 10.282
    - type: recall_at_1
      value: 27.254
    - type: recall_at_10
      value: 52.967
    - type: recall_at_100
      value: 75.224
    - type: recall_at_1000
      value: 90.617
    - type: recall_at_20
      value: 60.053
    - type: recall_at_3
      value: 40.548
    - type: recall_at_5
      value: 45.741
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 17.291999999999998
    - type: map_at_10
      value: 25.56
    - type: map_at_100
      value: 26.694000000000003
    - type: map_at_1000
      value: 26.813
    - type: map_at_20
      value: 26.169999999999998
    - type: map_at_3
      value: 23.151
    - type: map_at_5
      value: 24.535
    - type: mrr_at_1
      value: 21.517
    - type: mrr_at_10
      value: 30.097
    - type: mrr_at_100
      value: 31.087999999999997
    - type: mrr_at_1000
      value: 31.157
    - type: mrr_at_20
      value: 30.689
    - type: mrr_at_3
      value: 27.736
    - type: mrr_at_5
      value: 29.154000000000003
    - type: ndcg_at_1
      value: 21.517
    - type: ndcg_at_10
      value: 30.636000000000003
    - type: ndcg_at_100
      value: 36.015
    - type: ndcg_at_1000
      value: 38.800000000000004
    - type: ndcg_at_20
      value: 32.716
    - type: ndcg_at_3
      value: 26.316
    - type: ndcg_at_5
      value: 28.46
    - type: precision_at_1
      value: 21.517
    - type: precision_at_10
      value: 5.585
    - type: precision_at_100
      value: 0.938
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_20
      value: 3.34
    - type: precision_at_3
      value: 12.769
    - type: precision_at_5
      value: 9.254
    - type: recall_at_1
      value: 17.291999999999998
    - type: recall_at_10
      value: 41.677
    - type: recall_at_100
      value: 64.92999999999999
    - type: recall_at_1000
      value: 84.41300000000001
    - type: recall_at_20
      value: 49.18
    - type: recall_at_3
      value: 29.836000000000002
    - type: recall_at_5
      value: 35.284
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 29.215000000000003
    - type: map_at_10
      value: 39.919
    - type: map_at_100
      value: 41.209
    - type: map_at_1000
      value: 41.31
    - type: map_at_20
      value: 40.62
    - type: map_at_3
      value: 36.565
    - type: map_at_5
      value: 38.439
    - type: mrr_at_1
      value: 35.996
    - type: mrr_at_10
      value: 45.39
    - type: mrr_at_100
      value: 46.205
    - type: mrr_at_1000
      value: 46.247
    - type: mrr_at_20
      value: 45.867000000000004
    - type: mrr_at_3
      value: 42.782
    - type: mrr_at_5
      value: 44.235
    - type: ndcg_at_1
      value: 35.996
    - type: ndcg_at_10
      value: 46.032000000000004
    - type: ndcg_at_100
      value: 51.397999999999996
    - type: ndcg_at_1000
      value: 53.215
    - type: ndcg_at_20
      value: 48.128
    - type: ndcg_at_3
      value: 40.78
    - type: ndcg_at_5
      value: 43.187999999999995
    - type: precision_at_1
      value: 35.996
    - type: precision_at_10
      value: 8.402
    - type: precision_at_100
      value: 1.304
    - type: precision_at_1000
      value: 0.161
    - type: precision_at_20
      value: 4.913
    - type: precision_at_3
      value: 19.442
    - type: precision_at_5
      value: 13.84
    - type: recall_at_1
      value: 29.215000000000003
    - type: recall_at_10
      value: 58.846
    - type: recall_at_100
      value: 81.255
    - type: recall_at_1000
      value: 93.10300000000001
    - type: recall_at_20
      value: 66.193
    - type: recall_at_3
      value: 43.842
    - type: recall_at_5
      value: 50.157
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 28.654000000000003
    - type: map_at_10
      value: 38.635000000000005
    - type: map_at_100
      value: 39.898
    - type: map_at_1000
      value: 40.003
    - type: map_at_20
      value: 39.33
    - type: map_at_3
      value: 35.705999999999996
    - type: map_at_5
      value: 37.294
    - type: mrr_at_1
      value: 34.589
    - type: mrr_at_10
      value: 43.580000000000005
    - type: mrr_at_100
      value: 44.455
    - type: mrr_at_1000
      value: 44.505
    - type: mrr_at_20
      value: 44.088
    - type: mrr_at_3
      value: 41.419
    - type: mrr_at_5
      value: 42.635
    - type: ndcg_at_1
      value: 34.589
    - type: ndcg_at_10
      value: 44.021
    - type: ndcg_at_100
      value: 49.653999999999996
    - type: ndcg_at_1000
      value: 51.695
    - type: ndcg_at_20
      value: 46.190999999999995
    - type: ndcg_at_3
      value: 39.568999999999996
    - type: ndcg_at_5
      value: 41.53
    - type: precision_at_1
      value: 34.589
    - type: precision_at_10
      value: 7.865
    - type: precision_at_100
      value: 1.243
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_20
      value: 4.618
    - type: precision_at_3
      value: 18.531
    - type: precision_at_5
      value: 13.081999999999999
    - type: recall_at_1
      value: 28.654000000000003
    - type: recall_at_10
      value: 54.785
    - type: recall_at_100
      value: 79.532
    - type: recall_at_1000
      value: 92.99199999999999
    - type: recall_at_20
      value: 62.605
    - type: recall_at_3
      value: 42.559000000000005
    - type: recall_at_5
      value: 47.664
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 25.277
    - type: map_at_10
      value: 32.135000000000005
    - type: map_at_100
      value: 33.105000000000004
    - type: map_at_1000
      value: 33.194
    - type: map_at_20
      value: 32.696
    - type: map_at_3
      value: 30.173
    - type: map_at_5
      value: 31.291000000000004
    - type: mrr_at_1
      value: 28.221
    - type: mrr_at_10
      value: 34.915
    - type: mrr_at_100
      value: 35.812
    - type: mrr_at_1000
      value: 35.876000000000005
    - type: mrr_at_20
      value: 35.447
    - type: mrr_at_3
      value: 33.154
    - type: mrr_at_5
      value: 34.19
    - type: ndcg_at_1
      value: 28.221
    - type: ndcg_at_10
      value: 36.086
    - type: ndcg_at_100
      value: 40.778999999999996
    - type: ndcg_at_1000
      value: 43.024
    - type: ndcg_at_20
      value: 38.019
    - type: ndcg_at_3
      value: 32.57
    - type: ndcg_at_5
      value: 34.272000000000006
    - type: precision_at_1
      value: 28.221
    - type: precision_at_10
      value: 5.567
    - type: precision_at_100
      value: 0.84
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_20
      value: 3.2520000000000002
    - type: precision_at_3
      value: 13.905999999999999
    - type: precision_at_5
      value: 9.54
    - type: recall_at_1
      value: 25.277
    - type: recall_at_10
      value: 45.426
    - type: recall_at_100
      value: 66.63900000000001
    - type: recall_at_1000
      value: 83.25
    - type: recall_at_20
      value: 52.723
    - type: recall_at_3
      value: 35.629
    - type: recall_at_5
      value: 39.916000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 18.365000000000002
    - type: map_at_10
      value: 25.387999999999998
    - type: map_at_100
      value: 26.394000000000002
    - type: map_at_1000
      value: 26.509
    - type: map_at_20
      value: 25.927
    - type: map_at_3
      value: 23.182
    - type: map_at_5
      value: 24.383
    - type: mrr_at_1
      value: 22.402
    - type: mrr_at_10
      value: 29.465000000000003
    - type: mrr_at_100
      value: 30.330000000000002
    - type: mrr_at_1000
      value: 30.404999999999998
    - type: mrr_at_20
      value: 29.95
    - type: mrr_at_3
      value: 27.415
    - type: mrr_at_5
      value: 28.548000000000002
    - type: ndcg_at_1
      value: 22.402
    - type: ndcg_at_10
      value: 29.872
    - type: ndcg_at_100
      value: 34.747
    - type: ndcg_at_1000
      value: 37.592999999999996
    - type: ndcg_at_20
      value: 31.653
    - type: ndcg_at_3
      value: 26.040999999999997
    - type: ndcg_at_5
      value: 27.755999999999997
    - type: precision_at_1
      value: 22.402
    - type: precision_at_10
      value: 5.337
    - type: precision_at_100
      value: 0.8959999999999999
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_20
      value: 3.1850000000000005
    - type: precision_at_3
      value: 12.239
    - type: precision_at_5
      value: 8.692
    - type: recall_at_1
      value: 18.365000000000002
    - type: recall_at_10
      value: 39.283
    - type: recall_at_100
      value: 61.412
    - type: recall_at_1000
      value: 81.922
    - type: recall_at_20
      value: 45.917
    - type: recall_at_3
      value: 28.462
    - type: recall_at_5
      value: 33.040000000000006
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 29.687
    - type: map_at_10
      value: 37.667
    - type: map_at_100
      value: 38.76
    - type: map_at_1000
      value: 38.863
    - type: map_at_20
      value: 38.287
    - type: map_at_3
      value: 35.157
    - type: map_at_5
      value: 36.732
    - type: mrr_at_1
      value: 35.168
    - type: mrr_at_10
      value: 42.309999999999995
    - type: mrr_at_100
      value: 43.169999999999995
    - type: mrr_at_1000
      value: 43.227
    - type: mrr_at_20
      value: 42.826
    - type: mrr_at_3
      value: 40.065
    - type: mrr_at_5
      value: 41.549
    - type: ndcg_at_1
      value: 35.168
    - type: ndcg_at_10
      value: 42.463
    - type: ndcg_at_100
      value: 47.475
    - type: ndcg_at_1000
      value: 49.735
    - type: ndcg_at_20
      value: 44.440000000000005
    - type: ndcg_at_3
      value: 38.108
    - type: ndcg_at_5
      value: 40.507
    - type: precision_at_1
      value: 35.168
    - type: precision_at_10
      value: 6.847
    - type: precision_at_100
      value: 1.048
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_20
      value: 3.9510000000000005
    - type: precision_at_3
      value: 16.884
    - type: precision_at_5
      value: 11.884
    - type: recall_at_1
      value: 29.687
    - type: recall_at_10
      value: 52.413
    - type: recall_at_100
      value: 74.21799999999999
    - type: recall_at_1000
      value: 90.022
    - type: recall_at_20
      value: 59.559
    - type: recall_at_3
      value: 40.717999999999996
    - type: recall_at_5
      value: 46.833999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 28.233000000000004
    - type: map_at_10
      value: 36.492000000000004
    - type: map_at_100
      value: 38.157999999999994
    - type: map_at_1000
      value: 38.391999999999996
    - type: map_at_20
      value: 37.336999999999996
    - type: map_at_3
      value: 33.833999999999996
    - type: map_at_5
      value: 35.225
    - type: mrr_at_1
      value: 33.399
    - type: mrr_at_10
      value: 40.983000000000004
    - type: mrr_at_100
      value: 42.065999999999995
    - type: mrr_at_1000
      value: 42.117
    - type: mrr_at_20
      value: 41.635
    - type: mrr_at_3
      value: 38.999
    - type: mrr_at_5
      value: 40.105000000000004
    - type: ndcg_at_1
      value: 33.399
    - type: ndcg_at_10
      value: 41.764
    - type: ndcg_at_100
      value: 47.894
    - type: ndcg_at_1000
      value: 50.304
    - type: ndcg_at_20
      value: 43.986999999999995
    - type: ndcg_at_3
      value: 37.861
    - type: ndcg_at_5
      value: 39.532000000000004
    - type: precision_at_1
      value: 33.399
    - type: precision_at_10
      value: 7.806
    - type: precision_at_100
      value: 1.609
    - type: precision_at_1000
      value: 0.244
    - type: precision_at_20
      value: 5.01
    - type: precision_at_3
      value: 17.655
    - type: precision_at_5
      value: 12.49
    - type: recall_at_1
      value: 28.233000000000004
    - type: recall_at_10
      value: 51.031000000000006
    - type: recall_at_100
      value: 78.597
    - type: recall_at_1000
      value: 93.907
    - type: recall_at_20
      value: 59.231
    - type: recall_at_3
      value: 39.018
    - type: recall_at_5
      value: 43.905
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 22.988
    - type: map_at_10
      value: 30.219
    - type: map_at_100
      value: 31.258000000000003
    - type: map_at_1000
      value: 31.351000000000003
    - type: map_at_20
      value: 30.895
    - type: map_at_3
      value: 27.641
    - type: map_at_5
      value: 29.282000000000004
    - type: mrr_at_1
      value: 25.139
    - type: mrr_at_10
      value: 32.1
    - type: mrr_at_100
      value: 33.119
    - type: mrr_at_1000
      value: 33.178000000000004
    - type: mrr_at_20
      value: 32.747
    - type: mrr_at_3
      value: 29.759999999999998
    - type: mrr_at_5
      value: 31.174000000000003
    - type: ndcg_at_1
      value: 25.139
    - type: ndcg_at_10
      value: 34.519
    - type: ndcg_at_100
      value: 39.415
    - type: ndcg_at_1000
      value: 41.837999999999994
    - type: ndcg_at_20
      value: 36.867
    - type: ndcg_at_3
      value: 29.656
    - type: ndcg_at_5
      value: 32.323
    - type: precision_at_1
      value: 25.139
    - type: precision_at_10
      value: 5.287
    - type: precision_at_100
      value: 0.823
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_20
      value: 3.198
    - type: precision_at_3
      value: 12.323
    - type: precision_at_5
      value: 8.982999999999999
    - type: recall_at_1
      value: 22.988
    - type: recall_at_10
      value: 45.983000000000004
    - type: recall_at_100
      value: 67.55499999999999
    - type: recall_at_1000
      value: 85.795
    - type: recall_at_20
      value: 54.795
    - type: recall_at_3
      value: 33.266
    - type: recall_at_5
      value: 39.501
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 9.466
    - type: map_at_10
      value: 15.967
    - type: map_at_100
      value: 17.804000000000002
    - type: map_at_1000
      value: 18.003
    - type: map_at_20
      value: 16.929
    - type: map_at_3
      value: 13.248
    - type: map_at_5
      value: 14.6
    - type: mrr_at_1
      value: 21.303
    - type: mrr_at_10
      value: 30.908
    - type: mrr_at_100
      value: 32.16
    - type: mrr_at_1000
      value: 32.211
    - type: mrr_at_20
      value: 31.721
    - type: mrr_at_3
      value: 27.6
    - type: mrr_at_5
      value: 29.402
    - type: ndcg_at_1
      value: 21.303
    - type: ndcg_at_10
      value: 22.972
    - type: ndcg_at_100
      value: 30.782999999999998
    - type: ndcg_at_1000
      value: 34.382000000000005
    - type: ndcg_at_20
      value: 25.983
    - type: ndcg_at_3
      value: 18.278
    - type: ndcg_at_5
      value: 19.894000000000002
    - type: precision_at_1
      value: 21.303
    - type: precision_at_10
      value: 7.225
    - type: precision_at_100
      value: 1.549
    - type: precision_at_1000
      value: 0.22100000000000003
    - type: precision_at_20
      value: 4.883
    - type: precision_at_3
      value: 13.442000000000002
    - type: precision_at_5
      value: 10.463000000000001
    - type: recall_at_1
      value: 9.466
    - type: recall_at_10
      value: 28.261999999999997
    - type: recall_at_100
      value: 55.541
    - type: recall_at_1000
      value: 75.723
    - type: recall_at_20
      value: 36.934
    - type: recall_at_3
      value: 16.862
    - type: recall_at_5
      value: 21.365000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 8.425
    - type: map_at_10
      value: 18.485
    - type: map_at_100
      value: 25.790000000000003
    - type: map_at_1000
      value: 27.205000000000002
    - type: map_at_20
      value: 21.201
    - type: map_at_3
      value: 13.26
    - type: map_at_5
      value: 15.328
    - type: mrr_at_1
      value: 62.0
    - type: mrr_at_10
      value: 70.954
    - type: mrr_at_100
      value: 71.311
    - type: mrr_at_1000
      value: 71.318
    - type: mrr_at_20
      value: 71.18100000000001
    - type: mrr_at_3
      value: 68.708
    - type: mrr_at_5
      value: 70.296
    - type: ndcg_at_1
      value: 50.0
    - type: ndcg_at_10
      value: 37.972
    - type: ndcg_at_100
      value: 42.725
    - type: ndcg_at_1000
      value: 49.617
    - type: ndcg_at_20
      value: 37.478
    - type: ndcg_at_3
      value: 42.378
    - type: ndcg_at_5
      value: 39.678000000000004
    - type: precision_at_1
      value: 62.0
    - type: precision_at_10
      value: 30.175
    - type: precision_at_100
      value: 9.56
    - type: precision_at_1000
      value: 1.8350000000000002
    - type: precision_at_20
      value: 22.400000000000002
    - type: precision_at_3
      value: 46.083
    - type: precision_at_5
      value: 38.65
    - type: recall_at_1
      value: 8.425
    - type: recall_at_10
      value: 24.52
    - type: recall_at_100
      value: 49.79
    - type: recall_at_1000
      value: 71.27799999999999
    - type: recall_at_20
      value: 30.938
    - type: recall_at_3
      value: 14.466999999999999
    - type: recall_at_5
      value: 18.13
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.615
    - type: f1
      value: 40.05868641887659
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 46.028000000000006
    - type: map_at_10
      value: 60.24699999999999
    - type: map_at_100
      value: 60.745000000000005
    - type: map_at_1000
      value: 60.763
    - type: map_at_20
      value: 60.590999999999994
    - type: map_at_3
      value: 57.32000000000001
    - type: map_at_5
      value: 59.245999999999995
    - type: mrr_at_1
      value: 49.565
    - type: mrr_at_10
      value: 63.980000000000004
    - type: mrr_at_100
      value: 64.393
    - type: mrr_at_1000
      value: 64.398
    - type: mrr_at_20
      value: 64.285
    - type: mrr_at_3
      value: 61.109
    - type: mrr_at_5
      value: 63.032999999999994
    - type: ndcg_at_1
      value: 49.565
    - type: ndcg_at_10
      value: 67.391
    - type: ndcg_at_100
      value: 69.488
    - type: ndcg_at_1000
      value: 69.82000000000001
    - type: ndcg_at_20
      value: 68.55499999999999
    - type: ndcg_at_3
      value: 61.768
    - type: ndcg_at_5
      value: 65.09899999999999
    - type: precision_at_1
      value: 49.565
    - type: precision_at_10
      value: 9.388
    - type: precision_at_100
      value: 1.055
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_20
      value: 4.958
    - type: precision_at_3
      value: 25.602999999999998
    - type: precision_at_5
      value: 17.177
    - type: recall_at_1
      value: 46.028000000000006
    - type: recall_at_10
      value: 85.685
    - type: recall_at_100
      value: 94.64099999999999
    - type: recall_at_1000
      value: 96.878
    - type: recall_at_20
      value: 90.065
    - type: recall_at_3
      value: 70.783
    - type: recall_at_5
      value: 78.818
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 20.371
    - type: map_at_10
      value: 34.364
    - type: map_at_100
      value: 36.315
    - type: map_at_1000
      value: 36.477
    - type: map_at_20
      value: 35.443999999999996
    - type: map_at_3
      value: 29.845
    - type: map_at_5
      value: 32.559
    - type: mrr_at_1
      value: 41.049
    - type: mrr_at_10
      value: 50.552
    - type: mrr_at_100
      value: 51.33
    - type: mrr_at_1000
      value: 51.361000000000004
    - type: mrr_at_20
      value: 51.032
    - type: mrr_at_3
      value: 48.251
    - type: mrr_at_5
      value: 49.509
    - type: ndcg_at_1
      value: 41.049
    - type: ndcg_at_10
      value: 42.527
    - type: ndcg_at_100
      value: 49.293
    - type: ndcg_at_1000
      value: 52.014
    - type: ndcg_at_20
      value: 45.245999999999995
    - type: ndcg_at_3
      value: 38.802
    - type: ndcg_at_5
      value: 40.19
    - type: precision_at_1
      value: 41.049
    - type: precision_at_10
      value: 11.914
    - type: precision_at_100
      value: 1.889
    - type: precision_at_1000
      value: 0.23900000000000002
    - type: precision_at_20
      value: 7.106
    - type: precision_at_3
      value: 26.44
    - type: precision_at_5
      value: 19.599
    - type: recall_at_1
      value: 20.371
    - type: recall_at_10
      value: 50.20099999999999
    - type: recall_at_100
      value: 74.85300000000001
    - type: recall_at_1000
      value: 91.166
    - type: recall_at_20
      value: 58.559000000000005
    - type: recall_at_3
      value: 35.32
    - type: recall_at_5
      value: 42.106
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 35.205999999999996
    - type: map_at_10
      value: 50.463
    - type: map_at_100
      value: 51.321000000000005
    - type: map_at_1000
      value: 51.391
    - type: map_at_20
      value: 50.965
    - type: map_at_3
      value: 47.331
    - type: map_at_5
      value: 49.247
    - type: mrr_at_1
      value: 70.41199999999999
    - type: mrr_at_10
      value: 77.577
    - type: mrr_at_100
      value: 77.835
    - type: mrr_at_1000
      value: 77.847
    - type: mrr_at_20
      value: 77.755
    - type: mrr_at_3
      value: 76.291
    - type: mrr_at_5
      value: 77.128
    - type: ndcg_at_1
      value: 70.41199999999999
    - type: ndcg_at_10
      value: 60.002
    - type: ndcg_at_100
      value: 63.1
    - type: ndcg_at_1000
      value: 64.491
    - type: ndcg_at_20
      value: 61.321000000000005
    - type: ndcg_at_3
      value: 55.318999999999996
    - type: ndcg_at_5
      value: 57.886
    - type: precision_at_1
      value: 70.41199999999999
    - type: precision_at_10
      value: 12.46
    - type: precision_at_100
      value: 1.488
    - type: precision_at_1000
      value: 0.167
    - type: precision_at_20
      value: 6.656
    - type: precision_at_3
      value: 34.634
    - type: precision_at_5
      value: 22.804
    - type: recall_at_1
      value: 35.205999999999996
    - type: recall_at_10
      value: 62.302
    - type: recall_at_100
      value: 74.409
    - type: recall_at_1000
      value: 83.633
    - type: recall_at_20
      value: 66.556
    - type: recall_at_3
      value: 51.951
    - type: recall_at_5
      value: 57.009
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 88.73559999999999
    - type: ap
      value: 84.40550091347858
    - type: f1
      value: 88.6897413895929
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 15.634
    - type: map_at_10
      value: 27.287
    - type: map_at_100
      value: 28.62
    - type: map_at_1000
      value: 28.677999999999997
    - type: map_at_20
      value: 28.113
    - type: map_at_3
      value: 23.227999999999998
    - type: map_at_5
      value: 25.509999999999998
    - type: mrr_at_1
      value: 16.103
    - type: mrr_at_10
      value: 27.772999999999996
    - type: mrr_at_100
      value: 29.055999999999997
    - type: mrr_at_1000
      value: 29.108
    - type: mrr_at_20
      value: 28.573999999999998
    - type: mrr_at_3
      value: 23.766000000000002
    - type: mrr_at_5
      value: 26.005
    - type: ndcg_at_1
      value: 16.103
    - type: ndcg_at_10
      value: 34.233999999999995
    - type: ndcg_at_100
      value: 40.748
    - type: ndcg_at_1000
      value: 42.189
    - type: ndcg_at_20
      value: 37.199
    - type: ndcg_at_3
      value: 25.913999999999998
    - type: ndcg_at_5
      value: 29.992
    - type: precision_at_1
      value: 16.103
    - type: precision_at_10
      value: 5.838
    - type: precision_at_100
      value: 0.909
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_20
      value: 3.535
    - type: precision_at_3
      value: 11.471
    - type: precision_at_5
      value: 8.953999999999999
    - type: recall_at_1
      value: 15.634
    - type: recall_at_10
      value: 55.887
    - type: recall_at_100
      value: 86.188
    - type: recall_at_1000
      value: 97.17
    - type: recall_at_20
      value: 67.461
    - type: recall_at_3
      value: 33.17
    - type: recall_at_5
      value: 42.988
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 92.2936616507068
    - type: f1
      value: 92.02636761092074
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 73.5248518011856
    - type: f1
      value: 53.05521175765365
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 70.21856086079356
    - type: f1
      value: 67.85484208485116
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 75.27236045729657
    - type: f1
      value: 74.916229419199
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.750593892555116
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  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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      value: 30.746118307596042
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  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.633568196946598
    - type: mrr
      value: 31.699313664022284
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 6.164
    - type: map_at_10
      value: 13.353000000000002
    - type: map_at_100
      value: 16.468
    - type: map_at_1000
      value: 17.916
    - type: map_at_20
      value: 14.677000000000001
    - type: map_at_3
      value: 9.976
    - type: map_at_5
      value: 11.369
    - type: mrr_at_1
      value: 48.297000000000004
    - type: mrr_at_10
      value: 55.779
    - type: mrr_at_100
      value: 56.367
    - type: mrr_at_1000
      value: 56.413000000000004
    - type: mrr_at_20
      value: 56.123999999999995
    - type: mrr_at_3
      value: 54.334
    - type: mrr_at_5
      value: 55.00000000000001
    - type: ndcg_at_1
      value: 46.285
    - type: ndcg_at_10
      value: 35.333999999999996
    - type: ndcg_at_100
      value: 31.696999999999996
    - type: ndcg_at_1000
      value: 40.544999999999995
    - type: ndcg_at_20
      value: 32.694
    - type: ndcg_at_3
      value: 41.373
    - type: ndcg_at_5
      value: 38.324999999999996
    - type: precision_at_1
      value: 48.297000000000004
    - type: precision_at_10
      value: 26.006
    - type: precision_at_100
      value: 7.901
    - type: precision_at_1000
      value: 2.073
    - type: precision_at_20
      value: 18.884999999999998
    - type: precision_at_3
      value: 38.7
    - type: precision_at_5
      value: 32.632
    - type: recall_at_1
      value: 6.164
    - type: recall_at_10
      value: 16.913
    - type: recall_at_100
      value: 30.956
    - type: recall_at_1000
      value: 63.147
    - type: recall_at_20
      value: 20.319000000000003
    - type: recall_at_3
      value: 10.894
    - type: recall_at_5
      value: 13.039000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 22.707
    - type: map_at_10
      value: 37.815
    - type: map_at_100
      value: 39.129000000000005
    - type: map_at_1000
      value: 39.157
    - type: map_at_20
      value: 38.685
    - type: map_at_3
      value: 32.784
    - type: map_at_5
      value: 35.66
    - type: mrr_at_1
      value: 25.695
    - type: mrr_at_10
      value: 40.245999999999995
    - type: mrr_at_100
      value: 41.239
    - type: mrr_at_1000
      value: 41.259
    - type: mrr_at_20
      value: 40.907
    - type: mrr_at_3
      value: 35.936
    - type: mrr_at_5
      value: 38.457
    - type: ndcg_at_1
      value: 25.666
    - type: ndcg_at_10
      value: 46.317
    - type: ndcg_at_100
      value: 51.82
    - type: ndcg_at_1000
      value: 52.471999999999994
    - type: ndcg_at_20
      value: 49.175000000000004
    - type: ndcg_at_3
      value: 36.69
    - type: ndcg_at_5
      value: 41.537
    - type: precision_at_1
      value: 25.666
    - type: precision_at_10
      value: 8.34
    - type: precision_at_100
      value: 1.1360000000000001
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_20
      value: 4.848
    - type: precision_at_3
      value: 17.304
    - type: precision_at_5
      value: 13.163
    - type: recall_at_1
      value: 22.707
    - type: recall_at_10
      value: 69.988
    - type: recall_at_100
      value: 93.733
    - type: recall_at_1000
      value: 98.571
    - type: recall_at_20
      value: 80.71199999999999
    - type: recall_at_3
      value: 44.858
    - type: recall_at_5
      value: 56.035000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 70.88600000000001
    - type: map_at_10
      value: 84.848
    - type: map_at_100
      value: 85.45700000000001
    - type: map_at_1000
      value: 85.473
    - type: map_at_20
      value: 85.239
    - type: map_at_3
      value: 81.89800000000001
    - type: map_at_5
      value: 83.786
    - type: mrr_at_1
      value: 81.64
    - type: mrr_at_10
      value: 87.90400000000001
    - type: mrr_at_100
      value: 87.98899999999999
    - type: mrr_at_1000
      value: 87.99
    - type: mrr_at_20
      value: 87.968
    - type: mrr_at_3
      value: 86.978
    - type: mrr_at_5
      value: 87.631
    - type: ndcg_at_1
      value: 81.66
    - type: ndcg_at_10
      value: 88.627
    - type: ndcg_at_100
      value: 89.769
    - type: ndcg_at_1000
      value: 89.86800000000001
    - type: ndcg_at_20
      value: 89.232
    - type: ndcg_at_3
      value: 85.804
    - type: ndcg_at_5
      value: 87.41
    - type: precision_at_1
      value: 81.66
    - type: precision_at_10
      value: 13.427
    - type: precision_at_100
      value: 1.528
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_20
      value: 7.106
    - type: precision_at_3
      value: 37.492999999999995
    - type: precision_at_5
      value: 24.666
    - type: recall_at_1
      value: 70.88600000000001
    - type: recall_at_10
      value: 95.734
    - type: recall_at_100
      value: 99.565
    - type: recall_at_1000
      value: 99.982
    - type: recall_at_20
      value: 97.661
    - type: recall_at_3
      value: 87.605
    - type: recall_at_5
      value: 92.169
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 56.21080787817221
    - type: v_measures
      value:
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  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 62.695441918144745
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      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
      - 0.6567314795009059
      - 0.6913306724738202
      - 0.6676599210494237
      - 0.40983324085642114
      - 0.7120033776430696
      - 0.6222687713138416
      - 0.36420652956305893
      - 0.7314242972357771
      - 0.6973642134040027
      - 0.7167216887741535
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: None
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 4.803
    - type: map_at_10
      value: 11.965
    - type: map_at_100
      value: 13.969000000000001
    - type: map_at_1000
      value: 14.251
    - type: map_at_20
      value: 13.074
    - type: map_at_3
      value: 8.704
    - type: map_at_5
      value: 10.39
    - type: mrr_at_1
      value: 23.7
    - type: mrr_at_10
      value: 34.300000000000004
    - type: mrr_at_100
      value: 35.413
    - type: mrr_at_1000
      value: 35.47
    - type: mrr_at_20
      value: 34.971999999999994
    - type: mrr_at_3
      value: 31.35
    - type: mrr_at_5
      value: 33.11
    - type: ndcg_at_1
      value: 23.7
    - type: ndcg_at_10
      value: 19.833000000000002
    - type: ndcg_at_100
      value: 27.543
    - type: ndcg_at_1000
      value: 32.657000000000004
    - type: ndcg_at_20
      value: 22.753999999999998
    - type: ndcg_at_3
      value: 19.371
    - type: ndcg_at_5
      value: 16.81
    - type: precision_at_1
      value: 23.7
    - type: precision_at_10
      value: 10.08
    - type: precision_at_100
      value: 2.114
    - type: precision_at_1000
      value: 0.335
    - type: precision_at_20
      value: 6.7299999999999995
    - type: precision_at_3
      value: 18.099999999999998
    - type: precision_at_5
      value: 14.680000000000001
    - type: recall_at_1
      value: 4.803
    - type: recall_at_10
      value: 20.408
    - type: recall_at_100
      value: 42.937999999999995
    - type: recall_at_1000
      value: 67.957
    - type: recall_at_20
      value: 27.253
    - type: recall_at_3
      value: 11.008
    - type: recall_at_5
      value: 14.878
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 80.56573112423378
    - type: cos_sim_spearman
      value: 74.17802402341557
    - type: euclidean_pearson
      value: 77.64719557838848
    - type: euclidean_spearman
      value: 74.18218845491099
    - type: manhattan_pearson
      value: 77.65349040610312
    - type: manhattan_spearman
      value: 74.24528452265194
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.8662929981252
    - type: cos_sim_spearman
      value: 73.18685763781161
    - type: euclidean_pearson
      value: 74.05220881070804
    - type: euclidean_spearman
      value: 73.1802498913973
    - type: manhattan_pearson
      value: 73.95702570399803
    - type: manhattan_spearman
      value: 73.148251314861
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 83.3566965914774
    - type: cos_sim_spearman
      value: 83.57082995137267
    - type: euclidean_pearson
      value: 83.0673597536666
    - type: euclidean_spearman
      value: 83.56179042864954
    - type: manhattan_pearson
      value: 82.99371986719699
    - type: manhattan_spearman
      value: 83.4564971341052
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 82.29928049097985
    - type: cos_sim_spearman
      value: 79.24507751018872
    - type: euclidean_pearson
      value: 81.05714342924686
    - type: euclidean_spearman
      value: 79.24448099194757
    - type: manhattan_pearson
      value: 81.1323440664372
    - type: manhattan_spearman
      value: 79.33271509619381
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.52550571006007
    - type: cos_sim_spearman
      value: 87.09852049607704
    - type: euclidean_pearson
      value: 86.6667274835381
    - type: euclidean_spearman
      value: 87.10282548900487
    - type: manhattan_pearson
      value: 86.65166599447521
    - type: manhattan_spearman
      value: 87.08134750847402
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 82.03173421048572
    - type: cos_sim_spearman
      value: 82.68144478503824
    - type: euclidean_pearson
      value: 82.16342331747909
    - type: euclidean_spearman
      value: 82.68199277546111
    - type: manhattan_pearson
      value: 82.17641395526667
    - type: manhattan_spearman
      value: 82.70409481262362
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 87.83421066375598
    - type: cos_sim_spearman
      value: 88.1065724802746
    - type: euclidean_pearson
      value: 87.9179286282574
    - type: euclidean_spearman
      value: 88.13943838539143
    - type: manhattan_pearson
      value: 87.78121970619249
    - type: manhattan_spearman
      value: 87.97091893740061
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.18977730855335
    - type: cos_sim_spearman
      value: 64.32281973949075
    - type: euclidean_pearson
      value: 65.88520469364576
    - type: euclidean_spearman
      value: 64.33592296112258
    - type: manhattan_pearson
      value: 65.77016266953936
    - type: manhattan_spearman
      value: 64.37327935074376
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 83.82183713235801
    - type: cos_sim_spearman
      value: 83.40253231983908
    - type: euclidean_pearson
      value: 83.3368925429508
    - type: euclidean_spearman
      value: 83.40496299801828
    - type: manhattan_pearson
      value: 83.37982295504875
    - type: manhattan_spearman
      value: 83.44331438539328
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 81.57437869315952
    - type: mrr
      value: 95.02558715794011
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 56.89999999999999
    - type: map_at_10
      value: 67.637
    - type: map_at_100
      value: 68.107
    - type: map_at_1000
      value: 68.128
    - type: map_at_20
      value: 67.92099999999999
    - type: map_at_3
      value: 64.86
    - type: map_at_5
      value: 66.44200000000001
    - type: mrr_at_1
      value: 59.333000000000006
    - type: mrr_at_10
      value: 68.352
    - type: mrr_at_100
      value: 68.74
    - type: mrr_at_1000
      value: 68.76100000000001
    - type: mrr_at_20
      value: 68.597
    - type: mrr_at_3
      value: 66.333
    - type: mrr_at_5
      value: 67.583
    - type: ndcg_at_1
      value: 59.333000000000006
    - type: ndcg_at_10
      value: 72.30199999999999
    - type: ndcg_at_100
      value: 74.374
    - type: ndcg_at_1000
      value: 74.995
    - type: ndcg_at_20
      value: 73.22800000000001
    - type: ndcg_at_3
      value: 67.584
    - type: ndcg_at_5
      value: 69.95700000000001
    - type: precision_at_1
      value: 59.333000000000006
    - type: precision_at_10
      value: 9.700000000000001
    - type: precision_at_100
      value: 1.08
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 5.050000000000001
    - type: precision_at_3
      value: 26.667
    - type: precision_at_5
      value: 17.533
    - type: recall_at_1
      value: 56.89999999999999
    - type: recall_at_10
      value: 85.68900000000001
    - type: recall_at_100
      value: 95.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 89.2
    - type: recall_at_3
      value: 72.906
    - type: recall_at_5
      value: 79.039
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.81485148514851
    - type: cos_sim_ap
      value: 95.58169993718987
    - type: cos_sim_f1
      value: 90.5027932960894
    - type: cos_sim_precision
      value: 91.95046439628483
    - type: cos_sim_recall
      value: 89.1
    - type: dot_accuracy
      value: 99.81485148514851
    - type: dot_ap
      value: 95.5719777669169
    - type: dot_f1
      value: 90.51243023845764
    - type: dot_precision
      value: 91.86405767250257
    - type: dot_recall
      value: 89.2
    - type: euclidean_accuracy
      value: 99.81584158415842
    - type: euclidean_ap
      value: 95.58771856329962
    - type: euclidean_f1
      value: 90.54878048780488
    - type: euclidean_precision
      value: 92.04545454545455
    - type: euclidean_recall
      value: 89.1
    - type: manhattan_accuracy
      value: 99.81287128712871
    - type: manhattan_ap
      value: 95.58869634659905
    - type: manhattan_f1
      value: 90.30271934325295
    - type: manhattan_precision
      value: 92.72918861959958
    - type: manhattan_recall
      value: 88.0
    - type: max_accuracy
      value: 99.81584158415842
    - type: max_ap
      value: 95.58869634659905
    - type: max_f1
      value: 90.54878048780488
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 66.81466934930805
    - type: v_measures
      value:
      - 0.6549319157284832
      - 0.729102722021156
      - 0.5645023963515139
      - 0.6675700545366731
      - 0.7106324328008338
      - 0.6319760643208963
      - 0.6114787245939142
      - 0.7374837646425462
      - 0.6662072905119479
      - 0.6677848929819692
      - 0.751779276675506
      - 0.759089429391716
      - 0.7602209390862023
      - 0.6492366899599431
      - 0.6195040191500187
      - 0.6499553625304811
      - 0.6426200803991593
      - 0.6501320764151193
      - 0.64076653277881
      - 0.6308932508075157
      - 0.6858425302866819
      - 0.6480916795406368
      - 0.621952158159244
      - 0.6919485686557781
      - 0.6599644850002667
      - 0.6549319157284832
      - 0.729102722021156
      - 0.5645023963515139
      - 0.6675700545366731
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  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
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  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 48.253810565773705
    - type: mrr
      value: 49.14455744418979
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.976959578668456
    - type: cos_sim_spearman
      value: 31.195930170179643
    - type: dot_pearson
      value: 31.023896821497786
    - type: dot_spearman
      value: 30.873340062924225
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: None
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.231
    - type: map_at_10
      value: 1.6709999999999998
    - type: map_at_100
      value: 10.578999999999999
    - type: map_at_1000
      value: 26.997
    - type: map_at_20
      value: 3.032
    - type: map_at_3
      value: 0.584
    - type: map_at_5
      value: 0.9249999999999999
    - type: mrr_at_1
      value: 82.0
    - type: mrr_at_10
      value: 89.833
    - type: mrr_at_100
      value: 89.833
    - type: mrr_at_1000
      value: 89.833
    - type: mrr_at_20
      value: 89.833
    - type: mrr_at_3
      value: 89.333
    - type: mrr_at_5
      value: 89.833
    - type: ndcg_at_1
      value: 72.0
    - type: ndcg_at_10
      value: 68.44200000000001
    - type: ndcg_at_100
      value: 56.06100000000001
    - type: ndcg_at_1000
      value: 53.315
    - type: ndcg_at_20
      value: 65.781
    - type: ndcg_at_3
      value: 69.69300000000001
    - type: ndcg_at_5
      value: 70.538
    - type: precision_at_1
      value: 82.0
    - type: precision_at_10
      value: 73.2
    - type: precision_at_100
      value: 58.34
    - type: precision_at_1000
      value: 23.854
    - type: precision_at_20
      value: 70.1
    - type: precision_at_3
      value: 76.667
    - type: precision_at_5
      value: 76.4
    - type: recall_at_1
      value: 0.231
    - type: recall_at_10
      value: 1.94
    - type: recall_at_100
      value: 14.26
    - type: recall_at_1000
      value: 51.013
    - type: recall_at_20
      value: 3.6519999999999997
    - type: recall_at_3
      value: 0.623
    - type: recall_at_5
      value: 1.022
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.3419999999999999
    - type: map_at_10
      value: 6.959999999999999
    - type: map_at_100
      value: 12.649
    - type: map_at_1000
      value: 14.332
    - type: map_at_20
      value: 9.48
    - type: map_at_3
      value: 3.447
    - type: map_at_5
      value: 4.811
    - type: mrr_at_1
      value: 18.367
    - type: mrr_at_10
      value: 33.273
    - type: mrr_at_100
      value: 34.611
    - type: mrr_at_1000
      value: 34.628
    - type: mrr_at_20
      value: 34.165
    - type: mrr_at_3
      value: 29.252
    - type: mrr_at_5
      value: 30.578
    - type: ndcg_at_1
      value: 16.326999999999998
    - type: ndcg_at_10
      value: 18.581
    - type: ndcg_at_100
      value: 31.512
    - type: ndcg_at_1000
      value: 43.93
    - type: ndcg_at_20
      value: 20.578
    - type: ndcg_at_3
      value: 18.179000000000002
    - type: ndcg_at_5
      value: 17.772
    - type: precision_at_1
      value: 18.367
    - type: precision_at_10
      value: 17.551
    - type: precision_at_100
      value: 7.102
    - type: precision_at_1000
      value: 1.533
    - type: precision_at_20
      value: 14.388000000000002
    - type: precision_at_3
      value: 20.408
    - type: precision_at_5
      value: 19.184
    - type: recall_at_1
      value: 1.3419999999999999
    - type: recall_at_10
      value: 13.081999999999999
    - type: recall_at_100
      value: 45.397
    - type: recall_at_1000
      value: 82.866
    - type: recall_at_20
      value: 21.034
    - type: recall_at_3
      value: 4.644
    - type: recall_at_5
      value: 7.449
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 67.5634765625
    - type: ap
      value: 12.539329872788752
    - type: f1
      value: 51.61250153500541
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.850028296547805
    - type: f1
      value: 55.18064459526432
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 47.6299204409476
    - type: v_measures
      value:
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  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.78732788937235
    - type: cos_sim_ap
      value: 66.7369597819357
    - type: cos_sim_f1
      value: 61.900121802679664
    - type: cos_sim_precision
      value: 57.48868778280543
    - type: cos_sim_recall
      value: 67.04485488126649
    - type: dot_accuracy
      value: 83.77540680693807
    - type: dot_ap
      value: 66.7494206279536
    - type: dot_f1
      value: 61.906496660595025
    - type: dot_precision
      value: 57.34533183352081
    - type: dot_recall
      value: 67.25593667546174
    - type: euclidean_accuracy
      value: 83.78136734815521
    - type: euclidean_ap
      value: 66.72851072777382
    - type: euclidean_f1
      value: 61.89545676599902
    - type: euclidean_precision
      value: 57.617098681218735
    - type: euclidean_recall
      value: 66.86015831134564
    - type: manhattan_accuracy
      value: 83.69195922989807
    - type: manhattan_ap
      value: 66.67869948457852
    - type: manhattan_f1
      value: 61.948212083847096
    - type: manhattan_precision
      value: 58.14814814814815
    - type: manhattan_recall
      value: 66.2796833773087
    - type: max_accuracy
      value: 83.78732788937235
    - type: max_ap
      value: 66.7494206279536
    - type: max_f1
      value: 61.948212083847096
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.06935227228627
    - type: cos_sim_ap
      value: 86.01490350477971
    - type: cos_sim_f1
      value: 78.5821414200534
    - type: cos_sim_precision
      value: 74.85539061955538
    - type: cos_sim_recall
      value: 82.69941484447182
    - type: dot_accuracy
      value: 89.06741180579812
    - type: dot_ap
      value: 86.00939130135514
    - type: dot_f1
      value: 78.5863394982604
    - type: dot_precision
      value: 74.93888384438081
    - type: dot_recall
      value: 82.60702186633816
    - type: euclidean_accuracy
      value: 89.06547133930997
    - type: euclidean_ap
      value: 86.01611265260871
    - type: euclidean_f1
      value: 78.5754075834664
    - type: euclidean_precision
      value: 75.89497094483106
    - type: euclidean_recall
      value: 81.45210963966738
    - type: manhattan_accuracy
      value: 89.03636434198782
    - type: manhattan_ap
      value: 85.98483745706906
    - type: manhattan_f1
      value: 78.52461404019809
    - type: manhattan_precision
      value: 74.48880906327715
    - type: manhattan_recall
      value: 83.02279026793964
    - type: max_accuracy
      value: 89.06935227228627
    - type: max_ap
      value: 86.01611265260871
    - type: max_f1
      value: 78.5863394982604
---

# ModernBERT-Embed-Unsupervised

`modernbert-embed-unsupervised` is the unsupervised checkpoint trained with the [contrastors](https://github.com/nomic-ai/contrastors) library 
for 1 epoch over the 235M weakly-supervised contrastive pairs curated in [Nomic Embed](https://arxiv.org/abs/2402.01613).

We suggest using [moderbert-embed](https://huggingface.co/nomic-ai/modernbert-embed) for embedding tasks.

## Performance

The modernbert-unsupervised model performs similarly to the `nomic-embed-text-v1_unsup` model

| Model | Average (56) | Classification (12) | Clustering (11) | Pair Classification (3) | Reranking (4) | Retrieval (15) | STS (10) | Overall |
|-------|--------------|--------------------:|-----------------|------------------------|---------------|----------------|-----------|----------|
| nomic-embed-text-v1_unsup | 59.9 | 71.2 | 42.5 | 83.7 | 55.0 | 48.0 | 80.8 | 30.7 |
| modernbert-embed-unsupervised | 60.03 | 72.11 | 44.34 | 82.78 | 55.0 | 47.05 | 80.33 | 31.2 |

