---
license: mit
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- bge
- mteb
datasets:
- Mihaiii/qa-assistant
model-index:
- name: Squirtle
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 69.59701492537313
    - type: ap
      value: 31.80839087521638
    - type: f1
      value: 63.43204352573031
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 82.09027499999999
    - type: ap
      value: 76.95004336850603
    - type: f1
      value: 82.04505556179174
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 41.943999999999996
    - type: f1
      value: 40.40964457303876
  - task:
      type: Retrieval
    dataset:
      type: mteb/arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 13.869000000000002
    - type: map_at_10
      value: 24.631
    - type: map_at_100
      value: 25.965
    - type: map_at_1000
      value: 26.023000000000003
    - type: map_at_20
      value: 25.442999999999998
    - type: map_at_3
      value: 20.827
    - type: map_at_5
      value: 22.776
    - type: mrr_at_1
      value: 14.580000000000002
    - type: mrr_at_10
      value: 24.91
    - type: mrr_at_100
      value: 26.229999999999997
    - type: mrr_at_1000
      value: 26.288
    - type: mrr_at_20
      value: 25.708
    - type: mrr_at_3
      value: 21.136
    - type: mrr_at_5
      value: 23.02
    - type: ndcg_at_1
      value: 13.869000000000002
    - type: ndcg_at_10
      value: 31.14
    - type: ndcg_at_100
      value: 37.885999999999996
    - type: ndcg_at_1000
      value: 39.497
    - type: ndcg_at_20
      value: 34.068
    - type: ndcg_at_3
      value: 23.163
    - type: ndcg_at_5
      value: 26.677
    - type: precision_at_1
      value: 13.869000000000002
    - type: precision_at_10
      value: 5.220000000000001
    - type: precision_at_100
      value: 0.844
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_20
      value: 3.186
    - type: precision_at_3
      value: 9.981
    - type: precision_at_5
      value: 7.696
    - type: recall_at_1
      value: 13.869000000000002
    - type: recall_at_10
      value: 52.205
    - type: recall_at_100
      value: 84.42399999999999
    - type: recall_at_1000
      value: 97.297
    - type: recall_at_20
      value: 63.727000000000004
    - type: recall_at_3
      value: 29.942999999999998
    - type: recall_at_5
      value: 38.478
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 33.042527574996505
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.68133686033884
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.344372012529384
    - type: mrr
      value: 65.32614430813877
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 69.44065444549933
    - type: cos_sim_spearman
      value: 71.77814153774398
    - type: euclidean_pearson
      value: 70.59416783558756
    - type: euclidean_spearman
      value: 71.77814153774398
    - type: manhattan_pearson
      value: 70.99287197201959
    - type: manhattan_spearman
      value: 72.0769435268729
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.12987012987013
    - type: f1
      value: 65.99991975715585
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.861774505346606
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 21.100665285420916
    - type: v_measures
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  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-android
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 17.835
    - type: map_at_10
      value: 24.718999999999998
    - type: map_at_100
      value: 25.755
    - type: map_at_1000
      value: 25.887
    - type: map_at_20
      value: 25.217
    - type: map_at_3
      value: 23.076
    - type: map_at_5
      value: 23.96
    - type: mrr_at_1
      value: 23.033
    - type: mrr_at_10
      value: 29.868
    - type: mrr_at_100
      value: 30.757
    - type: mrr_at_1000
      value: 30.834
    - type: mrr_at_20
      value: 30.37
    - type: mrr_at_3
      value: 28.112
    - type: mrr_at_5
      value: 29.185
    - type: ndcg_at_1
      value: 23.033
    - type: ndcg_at_10
      value: 28.899
    - type: ndcg_at_100
      value: 33.788000000000004
    - type: ndcg_at_1000
      value: 36.962
    - type: ndcg_at_20
      value: 30.497000000000003
    - type: ndcg_at_3
      value: 26.442
    - type: ndcg_at_5
      value: 27.466
    - type: precision_at_1
      value: 23.033
    - type: precision_at_10
      value: 5.351
    - type: precision_at_100
      value: 0.9610000000000001
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_20
      value: 3.2259999999999995
    - type: precision_at_3
      value: 12.923000000000002
    - type: precision_at_5
      value: 8.956
    - type: recall_at_1
      value: 17.835
    - type: recall_at_10
      value: 36.034
    - type: recall_at_100
      value: 57.615
    - type: recall_at_1000
      value: 79.72
    - type: recall_at_20
      value: 41.894999999999996
    - type: recall_at_3
      value: 28.313
    - type: recall_at_5
      value: 31.639
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-english
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 12.166
    - type: map_at_10
      value: 16.320999999999998
    - type: map_at_100
      value: 16.954
    - type: map_at_1000
      value: 17.054
    - type: map_at_20
      value: 16.651
    - type: map_at_3
      value: 14.890999999999998
    - type: map_at_5
      value: 15.695999999999998
    - type: mrr_at_1
      value: 15.287
    - type: mrr_at_10
      value: 19.487
    - type: mrr_at_100
      value: 20.11
    - type: mrr_at_1000
      value: 20.185
    - type: mrr_at_20
      value: 19.830000000000002
    - type: mrr_at_3
      value: 18.068
    - type: mrr_at_5
      value: 18.855
    - type: ndcg_at_1
      value: 15.287
    - type: ndcg_at_10
      value: 19.198999999999998
    - type: ndcg_at_100
      value: 22.395
    - type: ndcg_at_1000
      value: 25.106
    - type: ndcg_at_20
      value: 20.297
    - type: ndcg_at_3
      value: 16.743
    - type: ndcg_at_5
      value: 17.855999999999998
    - type: precision_at_1
      value: 15.287
    - type: precision_at_10
      value: 3.605
    - type: precision_at_100
      value: 0.638
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_20
      value: 2.166
    - type: precision_at_3
      value: 8.089
    - type: precision_at_5
      value: 5.822
    - type: recall_at_1
      value: 12.166
    - type: recall_at_10
      value: 24.701999999999998
    - type: recall_at_100
      value: 39.199
    - type: recall_at_1000
      value: 58.205
    - type: recall_at_20
      value: 28.791
    - type: recall_at_3
      value: 17.469
    - type: recall_at_5
      value: 20.615
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gaming
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 19.667
    - type: map_at_10
      value: 27.163999999999998
    - type: map_at_100
      value: 28.044000000000004
    - type: map_at_1000
      value: 28.142
    - type: map_at_20
      value: 27.645999999999997
    - type: map_at_3
      value: 24.914
    - type: map_at_5
      value: 26.078000000000003
    - type: mrr_at_1
      value: 23.197000000000003
    - type: mrr_at_10
      value: 30.202
    - type: mrr_at_100
      value: 30.976
    - type: mrr_at_1000
      value: 31.047000000000004
    - type: mrr_at_20
      value: 30.636000000000003
    - type: mrr_at_3
      value: 28.004
    - type: mrr_at_5
      value: 29.164
    - type: ndcg_at_1
      value: 23.197000000000003
    - type: ndcg_at_10
      value: 31.618000000000002
    - type: ndcg_at_100
      value: 35.977
    - type: ndcg_at_1000
      value: 38.458
    - type: ndcg_at_20
      value: 33.242
    - type: ndcg_at_3
      value: 27.285999999999998
    - type: ndcg_at_5
      value: 29.163
    - type: precision_at_1
      value: 23.197000000000003
    - type: precision_at_10
      value: 5.26
    - type: precision_at_100
      value: 0.8200000000000001
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_20
      value: 3.082
    - type: precision_at_3
      value: 12.247
    - type: precision_at_5
      value: 8.577
    - type: recall_at_1
      value: 19.667
    - type: recall_at_10
      value: 42.443
    - type: recall_at_100
      value: 62.254
    - type: recall_at_1000
      value: 80.44
    - type: recall_at_20
      value: 48.447
    - type: recall_at_3
      value: 30.518
    - type: recall_at_5
      value: 35.22
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gis
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.923
    - type: map_at_10
      value: 14.24
    - type: map_at_100
      value: 15.001000000000001
    - type: map_at_1000
      value: 15.092
    - type: map_at_20
      value: 14.623
    - type: map_at_3
      value: 13.168
    - type: map_at_5
      value: 13.678
    - type: mrr_at_1
      value: 11.525
    - type: mrr_at_10
      value: 15.187000000000001
    - type: mrr_at_100
      value: 15.939999999999998
    - type: mrr_at_1000
      value: 16.03
    - type: mrr_at_20
      value: 15.557000000000002
    - type: mrr_at_3
      value: 13.991999999999999
    - type: mrr_at_5
      value: 14.557
    - type: ndcg_at_1
      value: 11.525
    - type: ndcg_at_10
      value: 16.512999999999998
    - type: ndcg_at_100
      value: 20.445
    - type: ndcg_at_1000
      value: 23.398
    - type: ndcg_at_20
      value: 17.832
    - type: ndcg_at_3
      value: 14.224
    - type: ndcg_at_5
      value: 15.136
    - type: precision_at_1
      value: 11.525
    - type: precision_at_10
      value: 2.565
    - type: precision_at_100
      value: 0.484
    - type: precision_at_1000
      value: 0.076
    - type: precision_at_20
      value: 1.582
    - type: precision_at_3
      value: 5.989
    - type: precision_at_5
      value: 4.1579999999999995
    - type: recall_at_1
      value: 10.923
    - type: recall_at_10
      value: 22.695
    - type: recall_at_100
      value: 40.892
    - type: recall_at_1000
      value: 64.456
    - type: recall_at_20
      value: 27.607
    - type: recall_at_3
      value: 16.348
    - type: recall_at_5
      value: 18.504
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-mathematica
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.409
    - type: map_at_10
      value: 8.584999999999999
    - type: map_at_100
      value: 9.392
    - type: map_at_1000
      value: 9.5
    - type: map_at_20
      value: 8.943
    - type: map_at_3
      value: 7.3
    - type: map_at_5
      value: 7.962
    - type: mrr_at_1
      value: 6.965000000000001
    - type: mrr_at_10
      value: 10.593
    - type: mrr_at_100
      value: 11.496
    - type: mrr_at_1000
      value: 11.578
    - type: mrr_at_20
      value: 11.021
    - type: mrr_at_3
      value: 8.976
    - type: mrr_at_5
      value: 9.797
    - type: ndcg_at_1
      value: 6.965000000000001
    - type: ndcg_at_10
      value: 11.056000000000001
    - type: ndcg_at_100
      value: 15.683
    - type: ndcg_at_1000
      value: 18.873
    - type: ndcg_at_20
      value: 12.331
    - type: ndcg_at_3
      value: 8.334
    - type: ndcg_at_5
      value: 9.512
    - type: precision_at_1
      value: 6.965000000000001
    - type: precision_at_10
      value: 2.177
    - type: precision_at_100
      value: 0.54
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_20
      value: 1.468
    - type: precision_at_3
      value: 3.9800000000000004
    - type: precision_at_5
      value: 3.109
    - type: recall_at_1
      value: 5.409
    - type: recall_at_10
      value: 16.895
    - type: recall_at_100
      value: 38.167
    - type: recall_at_1000
      value: 61.783
    - type: recall_at_20
      value: 21.248
    - type: recall_at_3
      value: 9.518
    - type: recall_at_5
      value: 12.426
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-physics
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 13.688
    - type: map_at_10
      value: 19.096
    - type: map_at_100
      value: 20.058
    - type: map_at_1000
      value: 20.194000000000003
    - type: map_at_20
      value: 19.595000000000002
    - type: map_at_3
      value: 17.313000000000002
    - type: map_at_5
      value: 18.41
    - type: mrr_at_1
      value: 17.132
    - type: mrr_at_10
      value: 22.95
    - type: mrr_at_100
      value: 23.799
    - type: mrr_at_1000
      value: 23.884
    - type: mrr_at_20
      value: 23.419999999999998
    - type: mrr_at_3
      value: 20.95
    - type: mrr_at_5
      value: 22.21
    - type: ndcg_at_1
      value: 17.132
    - type: ndcg_at_10
      value: 22.88
    - type: ndcg_at_100
      value: 27.572000000000003
    - type: ndcg_at_1000
      value: 30.824
    - type: ndcg_at_20
      value: 24.516
    - type: ndcg_at_3
      value: 19.64
    - type: ndcg_at_5
      value: 21.4
    - type: precision_at_1
      value: 17.132
    - type: precision_at_10
      value: 4.263999999999999
    - type: precision_at_100
      value: 0.7969999999999999
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_20
      value: 2.6519999999999997
    - type: precision_at_3
      value: 9.336
    - type: precision_at_5
      value: 6.93
    - type: recall_at_1
      value: 13.688
    - type: recall_at_10
      value: 30.537999999999997
    - type: recall_at_100
      value: 51.017999999999994
    - type: recall_at_1000
      value: 73.921
    - type: recall_at_20
      value: 36.174
    - type: recall_at_3
      value: 21.568
    - type: recall_at_5
      value: 26.127
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-programmers
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 8.173
    - type: map_at_10
      value: 11.648
    - type: map_at_100
      value: 12.434000000000001
    - type: map_at_1000
      value: 12.540000000000001
    - type: map_at_20
      value: 12.030000000000001
    - type: map_at_3
      value: 10.568
    - type: map_at_5
      value: 11.064
    - type: mrr_at_1
      value: 10.274
    - type: mrr_at_10
      value: 14.505
    - type: mrr_at_100
      value: 15.332
    - type: mrr_at_1000
      value: 15.409
    - type: mrr_at_20
      value: 14.899999999999999
    - type: mrr_at_3
      value: 13.375
    - type: mrr_at_5
      value: 13.929
    - type: ndcg_at_1
      value: 10.274
    - type: ndcg_at_10
      value: 14.283999999999999
    - type: ndcg_at_100
      value: 18.731
    - type: ndcg_at_1000
      value: 21.744
    - type: ndcg_at_20
      value: 15.647
    - type: ndcg_at_3
      value: 12.278
    - type: ndcg_at_5
      value: 12.974
    - type: precision_at_1
      value: 10.274
    - type: precision_at_10
      value: 2.683
    - type: precision_at_100
      value: 0.582
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_20
      value: 1.7409999999999999
    - type: precision_at_3
      value: 6.088
    - type: precision_at_5
      value: 4.201
    - type: recall_at_1
      value: 8.173
    - type: recall_at_10
      value: 19.642
    - type: recall_at_100
      value: 40.213
    - type: recall_at_1000
      value: 62.083999999999996
    - type: recall_at_20
      value: 24.537
    - type: recall_at_3
      value: 13.700999999999999
    - type: recall_at_5
      value: 15.751000000000001
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.252416666666667
    - type: map_at_10
      value: 15.589583333333334
    - type: map_at_100
      value: 16.381166666666665
    - type: map_at_1000
      value: 16.490333333333332
    - type: map_at_20
      value: 15.99116666666667
    - type: map_at_3
      value: 14.140916666666667
    - type: map_at_5
      value: 14.9045
    - type: mrr_at_1
      value: 13.710416666666664
    - type: mrr_at_10
      value: 18.34416666666667
    - type: mrr_at_100
      value: 19.110083333333336
    - type: mrr_at_1000
      value: 19.192583333333335
    - type: mrr_at_20
      value: 18.74783333333333
    - type: mrr_at_3
      value: 16.799416666666666
    - type: mrr_at_5
      value: 17.62725
    - type: ndcg_at_1
      value: 13.710416666666664
    - type: ndcg_at_10
      value: 18.628583333333335
    - type: ndcg_at_100
      value: 22.733666666666668
    - type: ndcg_at_1000
      value: 25.728499999999997
    - type: ndcg_at_20
      value: 19.994500000000002
    - type: ndcg_at_3
      value: 15.918083333333332
    - type: ndcg_at_5
      value: 17.086999999999996
    - type: precision_at_1
      value: 13.710416666666664
    - type: precision_at_10
      value: 3.3575
    - type: precision_at_100
      value: 0.6368333333333333
    - type: precision_at_1000
      value: 0.10508333333333333
    - type: precision_at_20
      value: 2.074833333333333
    - type: precision_at_3
      value: 7.440333333333333
    - type: precision_at_5
      value: 5.341916666666667
    - type: recall_at_1
      value: 11.252416666666667
    - type: recall_at_10
      value: 25.200833333333332
    - type: recall_at_100
      value: 44.075333333333326
    - type: recall_at_1000
      value: 66.12541666666665
    - type: recall_at_20
      value: 30.24916666666667
    - type: recall_at_3
      value: 17.46591666666667
    - type: recall_at_5
      value: 20.53691666666667
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-stats
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 8.696
    - type: map_at_10
      value: 12.339
    - type: map_at_100
      value: 12.946
    - type: map_at_1000
      value: 13.04
    - type: map_at_20
      value: 12.6
    - type: map_at_3
      value: 11.06
    - type: map_at_5
      value: 11.530999999999999
    - type: mrr_at_1
      value: 10.276
    - type: mrr_at_10
      value: 14.463999999999999
    - type: mrr_at_100
      value: 15.07
    - type: mrr_at_1000
      value: 15.152
    - type: mrr_at_20
      value: 14.737
    - type: mrr_at_3
      value: 13.037
    - type: mrr_at_5
      value: 13.627
    - type: ndcg_at_1
      value: 10.276
    - type: ndcg_at_10
      value: 15.085
    - type: ndcg_at_100
      value: 18.538
    - type: ndcg_at_1000
      value: 21.461
    - type: ndcg_at_20
      value: 15.976
    - type: ndcg_at_3
      value: 12.454
    - type: ndcg_at_5
      value: 13.195
    - type: precision_at_1
      value: 10.276
    - type: precision_at_10
      value: 2.669
    - type: precision_at_100
      value: 0.48900000000000005
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_20
      value: 1.572
    - type: precision_at_3
      value: 5.726
    - type: precision_at_5
      value: 3.9570000000000003
    - type: recall_at_1
      value: 8.696
    - type: recall_at_10
      value: 21.766
    - type: recall_at_100
      value: 38.269
    - type: recall_at_1000
      value: 61.106
    - type: recall_at_20
      value: 24.992
    - type: recall_at_3
      value: 14.032
    - type: recall_at_5
      value: 15.967999999999998
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-tex
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.13
    - type: map_at_10
      value: 9.067
    - type: map_at_100
      value: 9.687999999999999
    - type: map_at_1000
      value: 9.792
    - type: map_at_20
      value: 9.384
    - type: map_at_3
      value: 8.006
    - type: map_at_5
      value: 8.581999999999999
    - type: mrr_at_1
      value: 7.605
    - type: mrr_at_10
      value: 11.111
    - type: mrr_at_100
      value: 11.745999999999999
    - type: mrr_at_1000
      value: 11.837
    - type: mrr_at_20
      value: 11.452
    - type: mrr_at_3
      value: 9.922
    - type: mrr_at_5
      value: 10.522
    - type: ndcg_at_1
      value: 7.605
    - type: ndcg_at_10
      value: 11.302
    - type: ndcg_at_100
      value: 14.629
    - type: ndcg_at_1000
      value: 17.739
    - type: ndcg_at_20
      value: 12.411
    - type: ndcg_at_3
      value: 9.28
    - type: ndcg_at_5
      value: 10.161000000000001
    - type: precision_at_1
      value: 7.605
    - type: precision_at_10
      value: 2.22
    - type: precision_at_100
      value: 0.46499999999999997
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_20
      value: 1.428
    - type: precision_at_3
      value: 4.565
    - type: precision_at_5
      value: 3.3649999999999998
    - type: recall_at_1
      value: 6.13
    - type: recall_at_10
      value: 16.009999999999998
    - type: recall_at_100
      value: 31.467
    - type: recall_at_1000
      value: 54.722
    - type: recall_at_20
      value: 20.137
    - type: recall_at_3
      value: 10.347000000000001
    - type: recall_at_5
      value: 12.692
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-unix
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.645
    - type: map_at_10
      value: 15.466
    - type: map_at_100
      value: 16.147
    - type: map_at_1000
      value: 16.247
    - type: map_at_20
      value: 15.806999999999999
    - type: map_at_3
      value: 14.011000000000001
    - type: map_at_5
      value: 14.967
    - type: mrr_at_1
      value: 14.179
    - type: mrr_at_10
      value: 18.512
    - type: mrr_at_100
      value: 19.184
    - type: mrr_at_1000
      value: 19.267
    - type: mrr_at_20
      value: 18.855
    - type: mrr_at_3
      value: 16.993
    - type: mrr_at_5
      value: 17.954
    - type: ndcg_at_1
      value: 14.179
    - type: ndcg_at_10
      value: 18.311
    - type: ndcg_at_100
      value: 21.996
    - type: ndcg_at_1000
      value: 24.942
    - type: ndcg_at_20
      value: 19.522000000000002
    - type: ndcg_at_3
      value: 15.593000000000002
    - type: ndcg_at_5
      value: 17.116
    - type: precision_at_1
      value: 14.179
    - type: precision_at_10
      value: 3.116
    - type: precision_at_100
      value: 0.5519999999999999
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_20
      value: 1.87
    - type: precision_at_3
      value: 7.090000000000001
    - type: precision_at_5
      value: 5.224
    - type: recall_at_1
      value: 11.645
    - type: recall_at_10
      value: 24.206
    - type: recall_at_100
      value: 41.29
    - type: recall_at_1000
      value: 63.205999999999996
    - type: recall_at_20
      value: 28.659000000000002
    - type: recall_at_3
      value: 16.771
    - type: recall_at_5
      value: 20.602
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-webmasters
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.435
    - type: map_at_10
      value: 17.263
    - type: map_at_100
      value: 18.137
    - type: map_at_1000
      value: 18.282999999999998
    - type: map_at_20
      value: 17.724
    - type: map_at_3
      value: 15.648000000000001
    - type: map_at_5
      value: 16.542
    - type: mrr_at_1
      value: 15.809999999999999
    - type: mrr_at_10
      value: 20.687
    - type: mrr_at_100
      value: 21.484
    - type: mrr_at_1000
      value: 21.567
    - type: mrr_at_20
      value: 21.124000000000002
    - type: mrr_at_3
      value: 19.104
    - type: mrr_at_5
      value: 19.974
    - type: ndcg_at_1
      value: 15.809999999999999
    - type: ndcg_at_10
      value: 20.801
    - type: ndcg_at_100
      value: 25.001
    - type: ndcg_at_1000
      value: 28.347
    - type: ndcg_at_20
      value: 22.223000000000003
    - type: ndcg_at_3
      value: 18.046
    - type: ndcg_at_5
      value: 19.308
    - type: precision_at_1
      value: 15.809999999999999
    - type: precision_at_10
      value: 4.032
    - type: precision_at_100
      value: 0.832
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_20
      value: 2.54
    - type: precision_at_3
      value: 8.63
    - type: precision_at_5
      value: 6.4030000000000005
    - type: recall_at_1
      value: 12.435
    - type: recall_at_10
      value: 27.495000000000005
    - type: recall_at_100
      value: 47.522999999999996
    - type: recall_at_1000
      value: 70.804
    - type: recall_at_20
      value: 33.334
    - type: recall_at_3
      value: 19.192
    - type: recall_at_5
      value: 22.435
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-wordpress
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.262
    - type: map_at_10
      value: 11.167
    - type: map_at_100
      value: 12.017999999999999
    - type: map_at_1000
      value: 12.113
    - type: map_at_20
      value: 11.674
    - type: map_at_3
      value: 9.736
    - type: map_at_5
      value: 10.384
    - type: mrr_at_1
      value: 9.242
    - type: mrr_at_10
      value: 12.564
    - type: mrr_at_100
      value: 13.427
    - type: mrr_at_1000
      value: 13.520999999999999
    - type: mrr_at_20
      value: 13.072000000000001
    - type: mrr_at_3
      value: 11.06
    - type: mrr_at_5
      value: 11.753
    - type: ndcg_at_1
      value: 9.242
    - type: ndcg_at_10
      value: 13.594999999999999
    - type: ndcg_at_100
      value: 18.049
    - type: ndcg_at_1000
      value: 20.888
    - type: ndcg_at_20
      value: 15.440000000000001
    - type: ndcg_at_3
      value: 10.697
    - type: ndcg_at_5
      value: 11.757
    - type: precision_at_1
      value: 9.242
    - type: precision_at_10
      value: 2.348
    - type: precision_at_100
      value: 0.482
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_20
      value: 1.5709999999999997
    - type: precision_at_3
      value: 4.621
    - type: precision_at_5
      value: 3.401
    - type: recall_at_1
      value: 8.262
    - type: recall_at_10
      value: 19.983999999999998
    - type: recall_at_100
      value: 40.997
    - type: recall_at_1000
      value: 63.058
    - type: recall_at_20
      value: 27.168999999999997
    - type: recall_at_3
      value: 11.814
    - type: recall_at_5
      value: 14.463999999999999
  - task:
      type: Retrieval
    dataset:
      type: mteb/climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 4.058
    - type: map_at_10
      value: 6.734
    - type: map_at_100
      value: 7.593999999999999
    - type: map_at_1000
      value: 7.736999999999999
    - type: map_at_20
      value: 7.102
    - type: map_at_3
      value: 5.559
    - type: map_at_5
      value: 6.178999999999999
    - type: mrr_at_1
      value: 8.404
    - type: mrr_at_10
      value: 13.514999999999999
    - type: mrr_at_100
      value: 14.518
    - type: mrr_at_1000
      value: 14.599
    - type: mrr_at_20
      value: 14.025000000000002
    - type: mrr_at_3
      value: 11.584999999999999
    - type: mrr_at_5
      value: 12.588
    - type: ndcg_at_1
      value: 8.404
    - type: ndcg_at_10
      value: 10.02
    - type: ndcg_at_100
      value: 14.771999999999998
    - type: ndcg_at_1000
      value: 18.251
    - type: ndcg_at_20
      value: 11.378
    - type: ndcg_at_3
      value: 7.675
    - type: ndcg_at_5
      value: 8.558
    - type: precision_at_1
      value: 8.404
    - type: precision_at_10
      value: 3.212
    - type: precision_at_100
      value: 0.83
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_20
      value: 2.186
    - type: precision_at_3
      value: 5.624
    - type: precision_at_5
      value: 4.5600000000000005
    - type: recall_at_1
      value: 4.058
    - type: recall_at_10
      value: 12.751999999999999
    - type: recall_at_100
      value: 30.219
    - type: recall_at_1000
      value: 50.749
    - type: recall_at_20
      value: 16.634
    - type: recall_at_3
      value: 7.234999999999999
    - type: recall_at_5
      value: 9.418
  - task:
      type: Retrieval
    dataset:
      type: mteb/dbpedia
      name: MTEB DBPedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 5.516
    - type: map_at_10
      value: 11.001
    - type: map_at_100
      value: 14.527999999999999
    - type: map_at_1000
      value: 15.417
    - type: map_at_20
      value: 12.446
    - type: map_at_3
      value: 8.269
    - type: map_at_5
      value: 9.345
    - type: mrr_at_1
      value: 43.5
    - type: mrr_at_10
      value: 54.078
    - type: mrr_at_100
      value: 54.655
    - type: mrr_at_1000
      value: 54.679
    - type: mrr_at_20
      value: 54.461999999999996
    - type: mrr_at_3
      value: 51.37500000000001
    - type: mrr_at_5
      value: 53.25
    - type: ndcg_at_1
      value: 33.125
    - type: ndcg_at_10
      value: 25.665
    - type: ndcg_at_100
      value: 28.116000000000003
    - type: ndcg_at_1000
      value: 34.477000000000004
    - type: ndcg_at_20
      value: 25.027
    - type: ndcg_at_3
      value: 28.4
    - type: ndcg_at_5
      value: 27.094
    - type: precision_at_1
      value: 43.5
    - type: precision_at_10
      value: 21.65
    - type: precision_at_100
      value: 6.351999999999999
    - type: precision_at_1000
      value: 1.306
    - type: precision_at_20
      value: 15.662
    - type: precision_at_3
      value: 32.333
    - type: precision_at_5
      value: 28.199999999999996
    - type: recall_at_1
      value: 5.516
    - type: recall_at_10
      value: 15.457
    - type: recall_at_100
      value: 32.903
    - type: recall_at_1000
      value: 53.81700000000001
    - type: recall_at_20
      value: 20.365
    - type: recall_at_3
      value: 9.528
    - type: recall_at_5
      value: 11.619
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 45.79
    - type: f1
      value: 38.89634882093881
  - task:
      type: Retrieval
    dataset:
      type: mteb/fever
      name: MTEB FEVER
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 18.063000000000002
    - type: map_at_10
      value: 24.911
    - type: map_at_100
      value: 25.688
    - type: map_at_1000
      value: 25.758
    - type: map_at_20
      value: 25.358999999999998
    - type: map_at_3
      value: 22.743
    - type: map_at_5
      value: 23.924
    - type: mrr_at_1
      value: 19.472
    - type: mrr_at_10
      value: 26.587
    - type: mrr_at_100
      value: 27.362
    - type: mrr_at_1000
      value: 27.428
    - type: mrr_at_20
      value: 27.040999999999997
    - type: mrr_at_3
      value: 24.362000000000002
    - type: mrr_at_5
      value: 25.593
    - type: ndcg_at_1
      value: 19.472
    - type: ndcg_at_10
      value: 29.183999999999997
    - type: ndcg_at_100
      value: 33.207
    - type: ndcg_at_1000
      value: 35.21
    - type: ndcg_at_20
      value: 30.791
    - type: ndcg_at_3
      value: 24.701999999999998
    - type: ndcg_at_5
      value: 26.823000000000004
    - type: precision_at_1
      value: 19.472
    - type: precision_at_10
      value: 4.469
    - type: precision_at_100
      value: 0.6629999999999999
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_20
      value: 2.59
    - type: precision_at_3
      value: 10.401
    - type: precision_at_5
      value: 7.363
    - type: recall_at_1
      value: 18.063000000000002
    - type: recall_at_10
      value: 41.071999999999996
    - type: recall_at_100
      value: 60.049
    - type: recall_at_1000
      value: 75.64699999999999
    - type: recall_at_20
      value: 47.211999999999996
    - type: recall_at_3
      value: 28.796
    - type: recall_at_5
      value: 33.894999999999996
  - task:
      type: Retrieval
    dataset:
      type: mteb/fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 2.45
    - type: map_at_10
      value: 4.255
    - type: map_at_100
      value: 4.809
    - type: map_at_1000
      value: 4.954
    - type: map_at_20
      value: 4.513
    - type: map_at_3
      value: 3.4029999999999996
    - type: map_at_5
      value: 3.782
    - type: mrr_at_1
      value: 4.938
    - type: mrr_at_10
      value: 8.231
    - type: mrr_at_100
      value: 8.902000000000001
    - type: mrr_at_1000
      value: 9.019
    - type: mrr_at_20
      value: 8.530999999999999
    - type: mrr_at_3
      value: 6.944
    - type: mrr_at_5
      value: 7.623
    - type: ndcg_at_1
      value: 4.938
    - type: ndcg_at_10
      value: 6.425
    - type: ndcg_at_100
      value: 9.661999999999999
    - type: ndcg_at_1000
      value: 13.911999999999999
    - type: ndcg_at_20
      value: 7.3
    - type: ndcg_at_3
      value: 4.907
    - type: ndcg_at_5
      value: 5.406
    - type: precision_at_1
      value: 4.938
    - type: precision_at_10
      value: 2.037
    - type: precision_at_100
      value: 0.528
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_20
      value: 1.366
    - type: precision_at_3
      value: 3.344
    - type: precision_at_5
      value: 2.7470000000000003
    - type: recall_at_1
      value: 2.45
    - type: recall_at_10
      value: 8.987
    - type: recall_at_100
      value: 22.302
    - type: recall_at_1000
      value: 49.903999999999996
    - type: recall_at_20
      value: 11.712
    - type: recall_at_3
      value: 4.675
    - type: recall_at_5
      value: 6.161
  - task:
      type: Retrieval
    dataset:
      type: mteb/hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 23.585
    - type: map_at_10
      value: 31.893
    - type: map_at_100
      value: 32.851
    - type: map_at_1000
      value: 32.951
    - type: map_at_20
      value: 32.415
    - type: map_at_3
      value: 29.787000000000003
    - type: map_at_5
      value: 31.012
    - type: mrr_at_1
      value: 47.171
    - type: mrr_at_10
      value: 54.333
    - type: mrr_at_100
      value: 54.949000000000005
    - type: mrr_at_1000
      value: 54.98800000000001
    - type: mrr_at_20
      value: 54.702
    - type: mrr_at_3
      value: 52.632999999999996
    - type: mrr_at_5
      value: 53.652
    - type: ndcg_at_1
      value: 47.171
    - type: ndcg_at_10
      value: 39.884
    - type: ndcg_at_100
      value: 44.019000000000005
    - type: ndcg_at_1000
      value: 46.303
    - type: ndcg_at_20
      value: 41.461999999999996
    - type: ndcg_at_3
      value: 36.153999999999996
    - type: ndcg_at_5
      value: 38.072
    - type: precision_at_1
      value: 47.171
    - type: precision_at_10
      value: 8.396
    - type: precision_at_100
      value: 1.169
    - type: precision_at_1000
      value: 0.147
    - type: precision_at_20
      value: 4.707
    - type: precision_at_3
      value: 22.408
    - type: precision_at_5
      value: 14.966
    - type: recall_at_1
      value: 23.585
    - type: recall_at_10
      value: 41.978
    - type: recall_at_100
      value: 58.447
    - type: recall_at_1000
      value: 73.7
    - type: recall_at_20
      value: 47.07
    - type: recall_at_3
      value: 33.611999999999995
    - type: recall_at_5
      value: 37.413999999999994
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 74.9528
    - type: ap
      value: 69.50790744137139
    - type: f1
      value: 74.77689594327182
  - task:
      type: Retrieval
    dataset:
      type: mteb/msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 8.186
    - type: map_at_10
      value: 13.352
    - type: map_at_100
      value: 14.147000000000002
    - type: map_at_1000
      value: 14.231
    - type: map_at_20
      value: 13.753000000000002
    - type: map_at_3
      value: 11.529
    - type: map_at_5
      value: 12.497
    - type: mrr_at_1
      value: 8.424
    - type: mrr_at_10
      value: 13.675999999999998
    - type: mrr_at_100
      value: 14.475999999999999
    - type: mrr_at_1000
      value: 14.557
    - type: mrr_at_20
      value: 14.084
    - type: mrr_at_3
      value: 11.843
    - type: mrr_at_5
      value: 12.82
    - type: ndcg_at_1
      value: 8.424
    - type: ndcg_at_10
      value: 16.534
    - type: ndcg_at_100
      value: 20.982
    - type: ndcg_at_1000
      value: 23.538999999999998
    - type: ndcg_at_20
      value: 18.012
    - type: ndcg_at_3
      value: 12.729
    - type: ndcg_at_5
      value: 14.466999999999999
    - type: precision_at_1
      value: 8.424
    - type: precision_at_10
      value: 2.7449999999999997
    - type: precision_at_100
      value: 0.507
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_20
      value: 1.683
    - type: precision_at_3
      value: 5.478000000000001
    - type: precision_at_5
      value: 4.16
    - type: recall_at_1
      value: 8.186
    - type: recall_at_10
      value: 26.415
    - type: recall_at_100
      value: 48.282000000000004
    - type: recall_at_1000
      value: 68.869
    - type: recall_at_20
      value: 32.207
    - type: recall_at_3
      value: 15.909
    - type: recall_at_5
      value: 20.09
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.26858185134519
    - type: f1
      value: 86.73793752046078
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 54.65800273597811
    - type: f1
      value: 36.16413360524473
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.519838601210495
    - type: f1
      value: 58.35755839392156
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 67.04102219233357
    - type: f1
      value: 65.55523696441647
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.16765056253893
    - type: v_measures
      value: [0.2535665532592405, 0.25745435154373697, 0.2588139996653209, 0.2563977645588755, 0.2572790917147801, 0.28011260965698515, 0.28489569719921415, 0.2978121202496781, 0.2927319740642704, 0.27770089434179124, 0.2535665532592405, 0.25745435154373697, 0.2588139996653209, 0.2563977645588755, 0.2572790917147801, 0.28011260965698515, 0.28489569719921415, 0.2978121202496781, 0.2927319740642704, 0.27770089434179124, 0.2535665532592405, 0.25745435154373697, 0.2588139996653209, 0.2563977645588755, 0.2572790917147801, 0.28011260965698515, 0.28489569719921415, 0.2978121202496781, 0.2927319740642704, 0.27770089434179124, 0.2535665532592405, 0.25745435154373697, 0.2588139996653209, 0.2563977645588755, 0.2572790917147801, 0.28011260965698515, 0.28489569719921415, 0.2978121202496781, 0.2927319740642704, 0.27770089434179124, 0.2535665532592405, 0.25745435154373697, 0.2588139996653209, 0.2563977645588755, 0.2572790917147801, 0.28011260965698515, 0.28489569719921415, 0.2978121202496781, 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  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.778196508186724
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      type: mteb/mind_small
      name: MTEB MindSmallReranking
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.088514713666076
    - type: mrr
      value: 31.010218178449588
  - task:
      type: Retrieval
    dataset:
      type: mteb/nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.228
    - type: map_at_10
      value: 4.338
    - type: map_at_100
      value: 5.427
    - type: map_at_1000
      value: 6.325
    - type: map_at_20
      value: 4.729
    - type: map_at_3
      value: 3.495
    - type: map_at_5
      value: 3.8150000000000004
    - type: mrr_at_1
      value: 22.291
    - type: mrr_at_10
      value: 29.622
    - type: mrr_at_100
      value: 30.547
    - type: mrr_at_1000
      value: 30.618000000000002
    - type: mrr_at_20
      value: 30.070000000000004
    - type: mrr_at_3
      value: 27.141
    - type: mrr_at_5
      value: 28.488000000000003
    - type: ndcg_at_1
      value: 21.362000000000002
    - type: ndcg_at_10
      value: 15.64
    - type: ndcg_at_100
      value: 14.832
    - type: ndcg_at_1000
      value: 23.980999999999998
    - type: ndcg_at_20
      value: 14.408000000000001
    - type: ndcg_at_3
      value: 18.719
    - type: ndcg_at_5
      value: 17.137
    - type: precision_at_1
      value: 21.981
    - type: precision_at_10
      value: 11.548
    - type: precision_at_100
      value: 4.223
    - type: precision_at_1000
      value: 1.6500000000000001
    - type: precision_at_20
      value: 8.39
    - type: precision_at_3
      value: 17.337
    - type: precision_at_5
      value: 14.613000000000001
    - type: recall_at_1
      value: 2.228
    - type: recall_at_10
      value: 6.9190000000000005
    - type: recall_at_100
      value: 16.854
    - type: recall_at_1000
      value: 49.179
    - type: recall_at_20
      value: 9.166
    - type: recall_at_3
      value: 4.263
    - type: recall_at_5
      value: 4.956
  - task:
      type: Retrieval
    dataset:
      type: mteb/nq
      name: MTEB NQ
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.176
    - type: map_at_10
      value: 15.720999999999998
    - type: map_at_100
      value: 16.847
    - type: map_at_1000
      value: 16.939999999999998
    - type: map_at_20
      value: 16.355
    - type: map_at_3
      value: 13.402
    - type: map_at_5
      value: 14.663
    - type: mrr_at_1
      value: 10.458
    - type: mrr_at_10
      value: 17.413
    - type: mrr_at_100
      value: 18.442
    - type: mrr_at_1000
      value: 18.52
    - type: mrr_at_20
      value: 18.006
    - type: mrr_at_3
      value: 15.043999999999999
    - type: mrr_at_5
      value: 16.367
    - type: ndcg_at_1
      value: 10.458
    - type: ndcg_at_10
      value: 19.994999999999997
    - type: ndcg_at_100
      value: 25.665
    - type: ndcg_at_1000
      value: 28.277
    - type: ndcg_at_20
      value: 22.233
    - type: ndcg_at_3
      value: 15.168999999999999
    - type: ndcg_at_5
      value: 17.453
    - type: precision_at_1
      value: 10.458
    - type: precision_at_10
      value: 3.711
    - type: precision_at_100
      value: 0.697
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_20
      value: 2.3810000000000002
    - type: precision_at_3
      value: 7.204000000000001
    - type: precision_at_5
      value: 5.568
    - type: recall_at_1
      value: 9.176
    - type: recall_at_10
      value: 31.646
    - type: recall_at_100
      value: 57.865
    - type: recall_at_1000
      value: 78.11399999999999
    - type: recall_at_20
      value: 40.117000000000004
    - type: recall_at_3
      value: 18.67
    - type: recall_at_5
      value: 24.063000000000002
  - task:
      type: Retrieval
    dataset:
      type: mteb/quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 62.597
    - type: map_at_10
      value: 75.3
    - type: map_at_100
      value: 76.057
    - type: map_at_1000
      value: 76.089
    - type: map_at_20
      value: 75.762
    - type: map_at_3
      value: 72.41499999999999
    - type: map_at_5
      value: 74.139
    - type: mrr_at_1
      value: 72.11999999999999
    - type: mrr_at_10
      value: 79.44600000000001
    - type: mrr_at_100
      value: 79.691
    - type: mrr_at_1000
      value: 79.696
    - type: mrr_at_20
      value: 79.604
    - type: mrr_at_3
      value: 78.015
    - type: mrr_at_5
      value: 78.90700000000001
    - type: ndcg_at_1
      value: 72.15
    - type: ndcg_at_10
      value: 79.937
    - type: ndcg_at_100
      value: 82.074
    - type: ndcg_at_1000
      value: 82.443
    - type: ndcg_at_20
      value: 80.916
    - type: ndcg_at_3
      value: 76.452
    - type: ndcg_at_5
      value: 78.192
    - type: precision_at_1
      value: 72.15
    - type: precision_at_10
      value: 12.117
    - type: precision_at_100
      value: 1.4500000000000002
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_20
      value: 6.503
    - type: precision_at_3
      value: 33.267
    - type: precision_at_5
      value: 21.944
    - type: recall_at_1
      value: 62.597
    - type: recall_at_10
      value: 88.911
    - type: recall_at_100
      value: 97.112
    - type: recall_at_1000
      value: 99.229
    - type: recall_at_20
      value: 92.231
    - type: recall_at_3
      value: 78.83099999999999
    - type: recall_at_5
      value: 83.757
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 31.453135224292588
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 43.69122416835423
    - type: v_measures
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  - task:
      type: Retrieval
    dataset:
      type: mteb/scidocs
      name: MTEB SCIDOCS
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 2.558
    - type: map_at_10
      value: 5.4670000000000005
    - type: map_at_100
      value: 6.601999999999999
    - type: map_at_1000
      value: 6.816
    - type: map_at_20
      value: 6.013
    - type: map_at_3
      value: 4.132000000000001
    - type: map_at_5
      value: 4.672
    - type: mrr_at_1
      value: 12.5
    - type: mrr_at_10
      value: 18.454
    - type: mrr_at_100
      value: 19.585
    - type: mrr_at_1000
      value: 19.698999999999998
    - type: mrr_at_20
      value: 19.093
    - type: mrr_at_3
      value: 16.25
    - type: mrr_at_5
      value: 17.349999999999998
    - type: ndcg_at_1
      value: 12.5
    - type: ndcg_at_10
      value: 9.931
    - type: ndcg_at_100
      value: 15.332
    - type: ndcg_at_1000
      value: 20.285
    - type: ndcg_at_20
      value: 11.73
    - type: ndcg_at_3
      value: 9.425
    - type: ndcg_at_5
      value: 7.994
    - type: precision_at_1
      value: 12.5
    - type: precision_at_10
      value: 5.11
    - type: precision_at_100
      value: 1.299
    - type: precision_at_1000
      value: 0.251
    - type: precision_at_20
      value: 3.5999999999999996
    - type: precision_at_3
      value: 8.533
    - type: precision_at_5
      value: 6.7
    - type: recall_at_1
      value: 2.558
    - type: recall_at_10
      value: 10.4
    - type: recall_at_100
      value: 26.35
    - type: recall_at_1000
      value: 50.888
    - type: recall_at_20
      value: 14.610000000000001
    - type: recall_at_3
      value: 5.208
    - type: recall_at_5
      value: 6.808
  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 80.46080544471825
    - type: cos_sim_spearman
      value: 77.33681018334157
    - type: euclidean_pearson
      value: 78.32030772877526
    - type: euclidean_spearman
      value: 77.3367915580176
    - type: manhattan_pearson
      value: 78.23694581981565
    - type: manhattan_spearman
      value: 77.24572801084182
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.33143319366522
    - type: cos_sim_spearman
      value: 70.15243619467687
    - type: euclidean_pearson
      value: 74.35384725257417
    - type: euclidean_spearman
      value: 70.15020588975051
    - type: manhattan_pearson
      value: 74.49763893926959
    - type: manhattan_spearman
      value: 70.35289409088577
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.43426290814391
    - type: cos_sim_spearman
      value: 78.41580967540904
    - type: euclidean_pearson
      value: 77.87697798842441
    - type: euclidean_spearman
      value: 78.41580967540904
    - type: manhattan_pearson
      value: 77.7742301162175
    - type: manhattan_spearman
      value: 78.23561925777014
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 75.72059066580607
    - type: cos_sim_spearman
      value: 74.76063270848232
    - type: euclidean_pearson
      value: 75.96422568212527
    - type: euclidean_spearman
      value: 74.76063912580608
    - type: manhattan_pearson
      value: 75.93446446206052
    - type: manhattan_spearman
      value: 74.80351881324513
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.50308070637769
    - type: cos_sim_spearman
      value: 82.00177922226122
    - type: euclidean_pearson
      value: 81.88334998600465
    - type: euclidean_spearman
      value: 82.00175996908672
    - type: manhattan_pearson
      value: 82.04162815561806
    - type: manhattan_spearman
      value: 82.16179492395742
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 72.660749090443
    - type: cos_sim_spearman
      value: 78.27062791462116
    - type: euclidean_pearson
      value: 77.22132046879575
    - type: euclidean_spearman
      value: 78.27062749235377
    - type: manhattan_pearson
      value: 77.30349168561915
    - type: manhattan_spearman
      value: 78.38610133247218
  - task:
      type: STS
    dataset:
      type: mteb/sts17-crosslingual-sts
      name: MTEB STS17 (en-en)
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.40073205259823
    - type: cos_sim_spearman
      value: 85.85093351857286
    - type: euclidean_pearson
      value: 86.39555107737667
    - type: euclidean_spearman
      value: 85.85093351857286
    - type: manhattan_pearson
      value: 86.15780582794078
    - type: manhattan_spearman
      value: 85.67768599300385
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (en)
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 54.06121880120164
    - type: cos_sim_spearman
      value: 61.20018366762684
    - type: euclidean_pearson
      value: 59.08089664894604
    - type: euclidean_spearman
      value: 61.20018366762684
    - type: manhattan_pearson
      value: 58.88169190353213
    - type: manhattan_spearman
      value: 60.82629422553597
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.9607252955321
    - type: cos_sim_spearman
      value: 79.20891358738938
    - type: euclidean_pearson
      value: 79.53044888138301
    - type: euclidean_spearman
      value: 79.20891358738938
    - type: manhattan_pearson
      value: 79.37313113618887
    - type: manhattan_spearman
      value: 79.0667751270519
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.0421477784269
    - type: mrr
      value: 89.94940426312975
  - task:
      type: Retrieval
    dataset:
      type: mteb/scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 31.900000000000002
    - type: map_at_10
      value: 38.494
    - type: map_at_100
      value: 39.353
    - type: map_at_1000
      value: 39.427
    - type: map_at_20
      value: 38.952
    - type: map_at_3
      value: 36.238
    - type: map_at_5
      value: 37.36
    - type: mrr_at_1
      value: 34.0
    - type: mrr_at_10
      value: 40.327
    - type: mrr_at_100
      value: 41.052
    - type: mrr_at_1000
      value: 41.120000000000005
    - type: mrr_at_20
      value: 40.737
    - type: mrr_at_3
      value: 38.333
    - type: mrr_at_5
      value: 39.367000000000004
    - type: ndcg_at_1
      value: 34.0
    - type: ndcg_at_10
      value: 42.419000000000004
    - type: ndcg_at_100
      value: 46.589000000000006
    - type: ndcg_at_1000
      value: 48.966
    - type: ndcg_at_20
      value: 43.980000000000004
    - type: ndcg_at_3
      value: 38.124
    - type: ndcg_at_5
      value: 39.952
    - type: precision_at_1
      value: 34.0
    - type: precision_at_10
      value: 5.933
    - type: precision_at_100
      value: 0.8330000000000001
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 3.3329999999999997
    - type: precision_at_3
      value: 15.0
    - type: precision_at_5
      value: 10.067
    - type: recall_at_1
      value: 31.900000000000002
    - type: recall_at_10
      value: 52.800000000000004
    - type: recall_at_100
      value: 72.10600000000001
    - type: recall_at_1000
      value: 91.60000000000001
    - type: recall_at_20
      value: 58.699999999999996
    - type: recall_at_3
      value: 41.317
    - type: recall_at_5
      value: 45.761
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.62871287128714
    - type: cos_sim_ap
      value: 85.22434241429664
    - type: cos_sim_f1
      value: 79.31605074462217
    - type: cos_sim_precision
      value: 88.43788437884379
    - type: cos_sim_recall
      value: 71.89999999999999
    - type: dot_accuracy
      value: 99.62871287128714
    - type: dot_ap
      value: 85.22434241429666
    - type: dot_f1
      value: 79.31605074462217
    - type: dot_precision
      value: 88.43788437884379
    - type: dot_recall
      value: 71.89999999999999
    - type: euclidean_accuracy
      value: 99.62871287128714
    - type: euclidean_ap
      value: 85.22434237736961
    - type: euclidean_f1
      value: 79.31605074462217
    - type: euclidean_precision
      value: 88.43788437884379
    - type: euclidean_recall
      value: 71.89999999999999
    - type: manhattan_accuracy
      value: 99.62475247524752
    - type: manhattan_ap
      value: 85.53918872229502
    - type: manhattan_f1
      value: 79.38618925831203
    - type: manhattan_precision
      value: 81.2565445026178
    - type: manhattan_recall
      value: 77.60000000000001
    - type: max_accuracy
      value: 99.62871287128714
    - type: max_ap
      value: 85.53918872229502
    - type: max_f1
      value: 79.38618925831203
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 39.16142357597941
    - type: v_measures
      value: [0.3824405761636396, 0.44216202123263126, 0.3390286805950001, 0.40370202650437953, 0.3687764786128344, 0.3002689364743748, 0.3406756129607103, 0.4239251906201308, 0.41513537797197647, 0.39562333880392536, 0.44243846336620263, 0.4564014124962121, 0.46843968839295613, 0.3486700249457605, 0.3931094737880025, 0.38614031871714743, 0.39009948062151834, 0.3952861715088528, 0.3768164106667065, 0.39372559829701875, 0.41022022885425324, 0.3442845107165114, 0.36768421400456974, 0.40522290066464794, 0.40007875701488965, 0.3824405761636396, 0.44216202123263126, 0.3390286805950001, 0.40370202650437953, 0.3687764786128344, 0.3002689364743748, 0.3406756129607103, 0.4239251906201308, 0.41513537797197647, 0.39562333880392536, 0.44243846336620263, 0.4564014124962121, 0.46843968839295613, 0.3486700249457605, 0.3931094737880025, 0.38614031871714743, 0.39009948062151834, 0.3952861715088528, 0.3768164106667065, 0.39372559829701875, 0.41022022885425324, 0.3442845107165114, 0.36768421400456974, 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  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.175984546605825
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      type: mteb/stackoverflowdupquestions-reranking
      name: MTEB StackOverflowDupQuestions
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 40.56760857818254
    - type: mrr
      value: 40.94357439945675
  - task:
      type: Summarization
    dataset:
      type: mteb/summeval
      name: MTEB SummEval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.764610926778037
    - type: cos_sim_spearman
      value: 30.298920879214158
    - type: dot_pearson
      value: 30.764611831321552
    - type: dot_spearman
      value: 30.298299440561465
  - task:
      type: Retrieval
    dataset:
      type: mteb/trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.109
    - type: map_at_10
      value: 0.781
    - type: map_at_100
      value: 2.995
    - type: map_at_1000
      value: 6.854
    - type: map_at_20
      value: 1.2
    - type: map_at_3
      value: 0.28700000000000003
    - type: map_at_5
      value: 0.434
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 54.955
    - type: mrr_at_100
      value: 55.655
    - type: mrr_at_1000
      value: 55.689
    - type: mrr_at_20
      value: 55.42399999999999
    - type: mrr_at_3
      value: 51.0
    - type: mrr_at_5
      value: 53.800000000000004
    - type: ndcg_at_1
      value: 39.0
    - type: ndcg_at_10
      value: 39.479
    - type: ndcg_at_100
      value: 25.752000000000002
    - type: ndcg_at_1000
      value: 22.868
    - type: ndcg_at_20
      value: 35.707
    - type: ndcg_at_3
      value: 39.419
    - type: ndcg_at_5
      value: 39.64
    - type: precision_at_1
      value: 42.0
    - type: precision_at_10
      value: 43.6
    - type: precision_at_100
      value: 25.88
    - type: precision_at_1000
      value: 10.784
    - type: precision_at_20
      value: 37.8
    - type: precision_at_3
      value: 43.333
    - type: precision_at_5
      value: 43.6
    - type: recall_at_1
      value: 0.109
    - type: recall_at_10
      value: 1.038
    - type: recall_at_100
      value: 5.495
    - type: recall_at_1000
      value: 21.665
    - type: recall_at_20
      value: 1.722
    - type: recall_at_3
      value: 0.318
    - type: recall_at_5
      value: 0.522
  - task:
      type: Retrieval
    dataset:
      type: mteb/touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.302
    - type: map_at_10
      value: 2.514
    - type: map_at_100
      value: 3.341
    - type: map_at_1000
      value: 3.757
    - type: map_at_20
      value: 2.85
    - type: map_at_3
      value: 1.8450000000000002
    - type: map_at_5
      value: 1.873
    - type: mrr_at_1
      value: 18.367
    - type: mrr_at_10
      value: 24.789
    - type: mrr_at_100
      value: 26.517000000000003
    - type: mrr_at_1000
      value: 26.593
    - type: mrr_at_20
      value: 25.946
    - type: mrr_at_3
      value: 22.448999999999998
    - type: mrr_at_5
      value: 22.959
    - type: ndcg_at_1
      value: 16.326999999999998
    - type: ndcg_at_10
      value: 7.7509999999999994
    - type: ndcg_at_100
      value: 10.67
    - type: ndcg_at_1000
      value: 17.76
    - type: ndcg_at_20
      value: 7.674
    - type: ndcg_at_3
      value: 10.369
    - type: ndcg_at_5
      value: 7.840999999999999
    - type: precision_at_1
      value: 18.367
    - type: precision_at_10
      value: 7.142999999999999
    - type: precision_at_100
      value: 2.327
    - type: precision_at_1000
      value: 0.6779999999999999
    - type: precision_at_20
      value: 5.408
    - type: precision_at_3
      value: 11.565
    - type: precision_at_5
      value: 7.3469999999999995
    - type: recall_at_1
      value: 1.302
    - type: recall_at_10
      value: 4.919
    - type: recall_at_100
      value: 14.430000000000001
    - type: recall_at_1000
      value: 36.949
    - type: recall_at_20
      value: 7.0040000000000004
    - type: recall_at_3
      value: 2.2319999999999998
    - type: recall_at_5
      value: 2.3449999999999998
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 64.47265625
    - type: ap
      value: 11.979631561643862
    - type: f1
      value: 49.90647543589666
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 61.79966044142614
    - type: f1
      value: 61.89030508018869
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 28.234217666259703
    - type: v_measures
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  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.0317100792752
    - type: cos_sim_ap
      value: 67.56361271781817
    - type: cos_sim_f1
      value: 63.082081211970696
    - type: cos_sim_precision
      value: 59.58245367112362
    - type: cos_sim_recall
      value: 67.01846965699208
    - type: dot_accuracy
      value: 84.0317100792752
    - type: dot_ap
      value: 67.56359342938897
    - type: dot_f1
      value: 63.082081211970696
    - type: dot_precision
      value: 59.58245367112362
    - type: dot_recall
      value: 67.01846965699208
    - type: euclidean_accuracy
      value: 84.0317100792752
    - type: euclidean_ap
      value: 67.5636169518733
    - type: euclidean_f1
      value: 63.082081211970696
    - type: euclidean_precision
      value: 59.58245367112362
    - type: euclidean_recall
      value: 67.01846965699208
    - type: manhattan_accuracy
      value: 84.0734338677952
    - type: manhattan_ap
      value: 67.44969672020721
    - type: manhattan_f1
      value: 63.09479205695017
    - type: manhattan_precision
      value: 59.90040313018734
    - type: manhattan_recall
      value: 66.64907651715039
    - type: max_accuracy
      value: 84.0734338677952
    - type: max_ap
      value: 67.5636169518733
    - type: max_f1
      value: 63.09479205695017
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.60624054022587
    - type: cos_sim_ap
      value: 82.94451598409692
    - type: cos_sim_f1
      value: 74.76484194294527
    - type: cos_sim_precision
      value: 74.86874613959235
    - type: cos_sim_recall
      value: 74.66122574684324
    - type: dot_accuracy
      value: 87.60624054022587
    - type: dot_ap
      value: 82.94451133280317
    - type: dot_f1
      value: 74.76484194294527
    - type: dot_precision
      value: 74.86874613959235
    - type: dot_recall
      value: 74.66122574684324
    - type: euclidean_accuracy
      value: 87.60624054022587
    - type: euclidean_ap
      value: 82.94449586426977
    - type: euclidean_f1
      value: 74.76484194294527
    - type: euclidean_precision
      value: 74.86874613959235
    - type: euclidean_recall
      value: 74.66122574684324
    - type: manhattan_accuracy
      value: 87.63922847052432
    - type: manhattan_ap
      value: 82.9449637573502
    - type: manhattan_f1
      value: 74.9452996046217
    - type: manhattan_precision
      value: 74.73015386970833
    - type: manhattan_recall
      value: 75.1616877117339
    - type: max_accuracy
      value: 87.63922847052432
    - type: max_ap
      value: 82.9449637573502
    - type: max_f1
      value: 74.9452996046217
---
# Squirtle

Squirtle is a distill of [bge-base-en-v1.5](BAAI/bge-base-en-v1.5).

## Intended purpose

<span style="color:blue">This model is designed for use in semantic-autocomplete ([click here for demo](https://mihaiii.github.io/semantic-autocomplete/)).</span>
Make sure you also pass `pipelineParams={{ pooling: "cls", normalize: true }}` since the default pooling in the component is mean.

## Usage

Other than within [semantic-autocomplete](https://github.com/Mihaiii/semantic-autocomplete), you can use this model same as [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5#usage).