TaylorAI
/

bge-micro

@@ -5,12 +5,2610 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
 ---
-# {MODEL_NAME}
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 <!--- Describe your model here -->

 - feature-extraction
 - sentence-similarity
 - transformers
+- mteb
+model-index:
+- name: bge_micro
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 66.26865671641792
+    - type: ap
+      value: 28.174006539079688
+    - type: f1
+      value: 59.724963358211035
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 75.3691
+    - type: ap
+      value: 69.64182876373573
+    - type: f1
+      value: 75.2906345000088
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 35.806
+    - type: f1
+      value: 35.506516495961904
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.24
+    - type: map_at_10
+      value: 42.832
+    - type: map_at_100
+      value: 43.797000000000004
+    - type: map_at_1000
+      value: 43.804
+    - type: map_at_3
+      value: 38.134
+    - type: map_at_5
+      value: 40.744
+    - type: mrr_at_1
+      value: 27.951999999999998
+    - type: mrr_at_10
+      value: 43.111
+    - type: mrr_at_100
+      value: 44.083
+    - type: mrr_at_1000
+      value: 44.09
+    - type: mrr_at_3
+      value: 38.431
+    - type: mrr_at_5
+      value: 41.019
+    - type: ndcg_at_1
+      value: 27.24
+    - type: ndcg_at_10
+      value: 51.513
+    - type: ndcg_at_100
+      value: 55.762
+    - type: ndcg_at_1000
+      value: 55.938
+    - type: ndcg_at_3
+      value: 41.743
+    - type: ndcg_at_5
+      value: 46.454
+    - type: precision_at_1
+      value: 27.24
+    - type: precision_at_10
+      value: 7.93
+    - type: precision_at_100
+      value: 0.9820000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 17.402
+    - type: precision_at_5
+      value: 12.731
+    - type: recall_at_1
+      value: 27.24
+    - type: recall_at_10
+      value: 79.303
+    - type: recall_at_100
+      value: 98.151
+    - type: recall_at_1000
+      value: 99.502
+    - type: recall_at_3
+      value: 52.205
+    - type: recall_at_5
+      value: 63.656
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 44.59766397469585
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 34.480143023109626
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 58.09326229984527
+    - type: mrr
+      value: 72.18429846546191
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.47582391622187
+    - type: cos_sim_spearman
+      value: 83.41635852964214
+    - type: euclidean_pearson
+      value: 84.21969728559216
+    - type: euclidean_spearman
+      value: 83.46575724558684
+    - type: manhattan_pearson
+      value: 83.83107014910223
+    - type: manhattan_spearman
+      value: 83.13321954800792
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 80.58116883116882
+    - type: f1
+      value: 80.53335622619781
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 37.13458676004344
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 29.720429607514898
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.051000000000002
+    - type: map_at_10
+      value: 36.291000000000004
+    - type: map_at_100
+      value: 37.632
+    - type: map_at_1000
+      value: 37.772
+    - type: map_at_3
+      value: 33.288000000000004
+    - type: map_at_5
+      value: 35.035
+    - type: mrr_at_1
+      value: 33.333
+    - type: mrr_at_10
+      value: 42.642
+    - type: mrr_at_100
+      value: 43.401
+    - type: mrr_at_1000
+      value: 43.463
+    - type: mrr_at_3
+      value: 40.272000000000006
+    - type: mrr_at_5
+      value: 41.753
+    - type: ndcg_at_1
+      value: 33.333
+    - type: ndcg_at_10
+      value: 42.291000000000004
+    - type: ndcg_at_100
+      value: 47.602
+    - type: ndcg_at_1000
+      value: 50.109
+    - type: ndcg_at_3
+      value: 38.033
+    - type: ndcg_at_5
+      value: 40.052
+    - type: precision_at_1
+      value: 33.333
+    - type: precision_at_10
+      value: 8.254999999999999
+    - type: precision_at_100
+      value: 1.353
+    - type: precision_at_1000
+      value: 0.185
+    - type: precision_at_3
+      value: 18.884
+    - type: precision_at_5
+      value: 13.447999999999999
+    - type: recall_at_1
+      value: 26.051000000000002
+    - type: recall_at_10
+      value: 53.107000000000006
+    - type: recall_at_100
+      value: 76.22
+    - type: recall_at_1000
+      value: 92.92399999999999
+    - type: recall_at_3
+      value: 40.073
+    - type: recall_at_5
+      value: 46.327
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.698999999999998
+    - type: map_at_10
+      value: 26.186
+    - type: map_at_100
+      value: 27.133000000000003
+    - type: map_at_1000
+      value: 27.256999999999998
+    - type: map_at_3
+      value: 24.264
+    - type: map_at_5
+      value: 25.307000000000002
+    - type: mrr_at_1
+      value: 24.712999999999997
+    - type: mrr_at_10
+      value: 30.703999999999997
+    - type: mrr_at_100
+      value: 31.445
+    - type: mrr_at_1000
+      value: 31.517
+    - type: mrr_at_3
+      value: 28.992
+    - type: mrr_at_5
+      value: 29.963
+    - type: ndcg_at_1
+      value: 24.712999999999997
+    - type: ndcg_at_10
+      value: 30.198000000000004
+    - type: ndcg_at_100
+      value: 34.412
+    - type: ndcg_at_1000
+      value: 37.174
+    - type: ndcg_at_3
+      value: 27.148
+    - type: ndcg_at_5
+      value: 28.464
+    - type: precision_at_1
+      value: 24.712999999999997
+    - type: precision_at_10
+      value: 5.489999999999999
+    - type: precision_at_100
+      value: 0.955
+    - type: precision_at_1000
+      value: 0.14400000000000002
+    - type: precision_at_3
+      value: 12.803
+    - type: precision_at_5
+      value: 8.981
+    - type: recall_at_1
+      value: 19.698999999999998
+    - type: recall_at_10
+      value: 37.595
+    - type: recall_at_100
+      value: 55.962
+    - type: recall_at_1000
+      value: 74.836
+    - type: recall_at_3
+      value: 28.538999999999998
+    - type: recall_at_5
+      value: 32.279
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 34.224
+    - type: map_at_10
+      value: 44.867000000000004
+    - type: map_at_100
+      value: 45.944
+    - type: map_at_1000
+      value: 46.013999999999996
+    - type: map_at_3
+      value: 42.009
+    - type: map_at_5
+      value: 43.684
+    - type: mrr_at_1
+      value: 39.436
+    - type: mrr_at_10
+      value: 48.301
+    - type: mrr_at_100
+      value: 49.055
+    - type: mrr_at_1000
+      value: 49.099
+    - type: mrr_at_3
+      value: 45.956
+    - type: mrr_at_5
+      value: 47.445
+    - type: ndcg_at_1
+      value: 39.436
+    - type: ndcg_at_10
+      value: 50.214000000000006
+    - type: ndcg_at_100
+      value: 54.63
+    - type: ndcg_at_1000
+      value: 56.165
+    - type: ndcg_at_3
+      value: 45.272
+    - type: ndcg_at_5
+      value: 47.826
+    - type: precision_at_1
+      value: 39.436
+    - type: precision_at_10
+      value: 8.037999999999998
+    - type: precision_at_100
+      value: 1.118
+    - type: precision_at_1000
+      value: 0.13
+    - type: precision_at_3
+      value: 20.125
+    - type: precision_at_5
+      value: 13.918
+    - type: recall_at_1
+      value: 34.224
+    - type: recall_at_10
+      value: 62.690999999999995
+    - type: recall_at_100
+      value: 81.951
+    - type: recall_at_1000
+      value: 92.93299999999999
+    - type: recall_at_3
+      value: 49.299
+    - type: recall_at_5
+      value: 55.533
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.375
+    - type: map_at_10
+      value: 28.366000000000003
+    - type: map_at_100
+      value: 29.363
+    - type: map_at_1000
+      value: 29.458000000000002
+    - type: map_at_3
+      value: 26.247
+    - type: map_at_5
+      value: 27.439000000000004
+    - type: mrr_at_1
+      value: 22.938
+    - type: mrr_at_10
+      value: 30.072
+    - type: mrr_at_100
+      value: 30.993
+    - type: mrr_at_1000
+      value: 31.070999999999998
+    - type: mrr_at_3
+      value: 28.004
+    - type: mrr_at_5
+      value: 29.179
+    - type: ndcg_at_1
+      value: 22.938
+    - type: ndcg_at_10
+      value: 32.516
+    - type: ndcg_at_100
+      value: 37.641999999999996
+    - type: ndcg_at_1000
+      value: 40.150999999999996
+    - type: ndcg_at_3
+      value: 28.341
+    - type: ndcg_at_5
+      value: 30.394
+    - type: precision_at_1
+      value: 22.938
+    - type: precision_at_10
+      value: 5.028
+    - type: precision_at_100
+      value: 0.8
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 12.052999999999999
+    - type: precision_at_5
+      value: 8.497
+    - type: recall_at_1
+      value: 21.375
+    - type: recall_at_10
+      value: 43.682
+    - type: recall_at_100
+      value: 67.619
+    - type: recall_at_1000
+      value: 86.64699999999999
+    - type: recall_at_3
+      value: 32.478
+    - type: recall_at_5
+      value: 37.347
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.95
+    - type: map_at_10
+      value: 21.417
+    - type: map_at_100
+      value: 22.525000000000002
+    - type: map_at_1000
+      value: 22.665
+    - type: map_at_3
+      value: 18.684
+    - type: map_at_5
+      value: 20.275000000000002
+    - type: mrr_at_1
+      value: 18.159
+    - type: mrr_at_10
+      value: 25.373
+    - type: mrr_at_100
+      value: 26.348
+    - type: mrr_at_1000
+      value: 26.432
+    - type: mrr_at_3
+      value: 22.698999999999998
+    - type: mrr_at_5
+      value: 24.254
+    - type: ndcg_at_1
+      value: 18.159
+    - type: ndcg_at_10
+      value: 26.043
+    - type: ndcg_at_100
+      value: 31.491999999999997
+    - type: ndcg_at_1000
+      value: 34.818
+    - type: ndcg_at_3
+      value: 21.05
+    - type: ndcg_at_5
+      value: 23.580000000000002
+    - type: precision_at_1
+      value: 18.159
+    - type: precision_at_10
+      value: 4.938
+    - type: precision_at_100
+      value: 0.872
+    - type: precision_at_1000
+      value: 0.129
+    - type: precision_at_3
+      value: 9.908999999999999
+    - type: precision_at_5
+      value: 7.611999999999999
+    - type: recall_at_1
+      value: 14.95
+    - type: recall_at_10
+      value: 36.285000000000004
+    - type: recall_at_100
+      value: 60.431999999999995
+    - type: recall_at_1000
+      value: 84.208
+    - type: recall_at_3
+      value: 23.006
+    - type: recall_at_5
+      value: 29.304999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.580000000000002
+    - type: map_at_10
+      value: 32.906
+    - type: map_at_100
+      value: 34.222
+    - type: map_at_1000
+      value: 34.346
+    - type: map_at_3
+      value: 29.891000000000002
+    - type: map_at_5
+      value: 31.679000000000002
+    - type: mrr_at_1
+      value: 28.778
+    - type: mrr_at_10
+      value: 37.783
+    - type: mrr_at_100
+      value: 38.746
+    - type: mrr_at_1000
+      value: 38.804
+    - type: mrr_at_3
+      value: 35.098
+    - type: mrr_at_5
+      value: 36.739
+    - type: ndcg_at_1
+      value: 28.778
+    - type: ndcg_at_10
+      value: 38.484
+    - type: ndcg_at_100
+      value: 44.322
+    - type: ndcg_at_1000
+      value: 46.772000000000006
+    - type: ndcg_at_3
+      value: 33.586
+    - type: ndcg_at_5
+      value: 36.098
+    - type: precision_at_1
+      value: 28.778
+    - type: precision_at_10
+      value: 7.151000000000001
+    - type: precision_at_100
+      value: 1.185
+    - type: precision_at_1000
+      value: 0.158
+    - type: precision_at_3
+      value: 16.105
+    - type: precision_at_5
+      value: 11.704
+    - type: recall_at_1
+      value: 23.580000000000002
+    - type: recall_at_10
+      value: 50.151999999999994
+    - type: recall_at_100
+      value: 75.114
+    - type: recall_at_1000
+      value: 91.467
+    - type: recall_at_3
+      value: 36.552
+    - type: recall_at_5
+      value: 43.014
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.669999999999998
+    - type: map_at_10
+      value: 28.687
+    - type: map_at_100
+      value: 30.061
+    - type: map_at_1000
+      value: 30.197000000000003
+    - type: map_at_3
+      value: 26.134
+    - type: map_at_5
+      value: 27.508
+    - type: mrr_at_1
+      value: 26.256
+    - type: mrr_at_10
+      value: 34.105999999999995
+    - type: mrr_at_100
+      value: 35.137
+    - type: mrr_at_1000
+      value: 35.214
+    - type: mrr_at_3
+      value: 31.791999999999998
+    - type: mrr_at_5
+      value: 33.145
+    - type: ndcg_at_1
+      value: 26.256
+    - type: ndcg_at_10
+      value: 33.68
+    - type: ndcg_at_100
+      value: 39.7
+    - type: ndcg_at_1000
+      value: 42.625
+    - type: ndcg_at_3
+      value: 29.457
+    - type: ndcg_at_5
+      value: 31.355
+    - type: precision_at_1
+      value: 26.256
+    - type: precision_at_10
+      value: 6.2330000000000005
+    - type: precision_at_100
+      value: 1.08
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 14.193
+    - type: precision_at_5
+      value: 10.113999999999999
+    - type: recall_at_1
+      value: 20.669999999999998
+    - type: recall_at_10
+      value: 43.254999999999995
+    - type: recall_at_100
+      value: 69.118
+    - type: recall_at_1000
+      value: 89.408
+    - type: recall_at_3
+      value: 31.135
+    - type: recall_at_5
+      value: 36.574
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.488833333333336
+    - type: map_at_10
+      value: 29.025416666666665
+    - type: map_at_100
+      value: 30.141249999999992
+    - type: map_at_1000
+      value: 30.264083333333335
+    - type: map_at_3
+      value: 26.599333333333337
+    - type: map_at_5
+      value: 28.004666666666665
+    - type: mrr_at_1
+      value: 25.515
+    - type: mrr_at_10
+      value: 32.8235
+    - type: mrr_at_100
+      value: 33.69958333333333
+    - type: mrr_at_1000
+      value: 33.77191666666668
+    - type: mrr_at_3
+      value: 30.581000000000003
+    - type: mrr_at_5
+      value: 31.919666666666668
+    - type: ndcg_at_1
+      value: 25.515
+    - type: ndcg_at_10
+      value: 33.64241666666666
+    - type: ndcg_at_100
+      value: 38.75816666666667
+    - type: ndcg_at_1000
+      value: 41.472166666666666
+    - type: ndcg_at_3
+      value: 29.435083333333335
+    - type: ndcg_at_5
+      value: 31.519083333333338
+    - type: precision_at_1
+      value: 25.515
+    - type: precision_at_10
+      value: 5.89725
+    - type: precision_at_100
+      value: 0.9918333333333335
+    - type: precision_at_1000
+      value: 0.14075
+    - type: precision_at_3
+      value: 13.504000000000001
+    - type: precision_at_5
+      value: 9.6885
+    - type: recall_at_1
+      value: 21.488833333333336
+    - type: recall_at_10
+      value: 43.60808333333333
+    - type: recall_at_100
+      value: 66.5045
+    - type: recall_at_1000
+      value: 85.70024999999998
+    - type: recall_at_3
+      value: 31.922166666666662
+    - type: recall_at_5
+      value: 37.29758333333334
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.781
+    - type: map_at_10
+      value: 27.173000000000002
+    - type: map_at_100
+      value: 27.967
+    - type: map_at_1000
+      value: 28.061999999999998
+    - type: map_at_3
+      value: 24.973
+    - type: map_at_5
+      value: 26.279999999999998
+    - type: mrr_at_1
+      value: 23.773
+    - type: mrr_at_10
+      value: 29.849999999999998
+    - type: mrr_at_100
+      value: 30.595
+    - type: mrr_at_1000
+      value: 30.669
+    - type: mrr_at_3
+      value: 27.761000000000003
+    - type: mrr_at_5
+      value: 29.003
+    - type: ndcg_at_1
+      value: 23.773
+    - type: ndcg_at_10
+      value: 31.033
+    - type: ndcg_at_100
+      value: 35.174
+    - type: ndcg_at_1000
+      value: 37.72
+    - type: ndcg_at_3
+      value: 26.927
+    - type: ndcg_at_5
+      value: 29.047
+    - type: precision_at_1
+      value: 23.773
+    - type: precision_at_10
+      value: 4.8469999999999995
+    - type: precision_at_100
+      value: 0.75
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 11.452
+    - type: precision_at_5
+      value: 8.129
+    - type: recall_at_1
+      value: 20.781
+    - type: recall_at_10
+      value: 40.463
+    - type: recall_at_100
+      value: 59.483
+    - type: recall_at_1000
+      value: 78.396
+    - type: recall_at_3
+      value: 29.241
+    - type: recall_at_5
+      value: 34.544000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.074000000000002
+    - type: map_at_10
+      value: 20.757
+    - type: map_at_100
+      value: 21.72
+    - type: map_at_1000
+      value: 21.844
+    - type: map_at_3
+      value: 18.929000000000002
+    - type: map_at_5
+      value: 19.894000000000002
+    - type: mrr_at_1
+      value: 18.307000000000002
+    - type: mrr_at_10
+      value: 24.215
+    - type: mrr_at_100
+      value: 25.083
+    - type: mrr_at_1000
+      value: 25.168000000000003
+    - type: mrr_at_3
+      value: 22.316
+    - type: mrr_at_5
+      value: 23.36
+    - type: ndcg_at_1
+      value: 18.307000000000002
+    - type: ndcg_at_10
+      value: 24.651999999999997
+    - type: ndcg_at_100
+      value: 29.296
+    - type: ndcg_at_1000
+      value: 32.538
+    - type: ndcg_at_3
+      value: 21.243000000000002
+    - type: ndcg_at_5
+      value: 22.727
+    - type: precision_at_1
+      value: 18.307000000000002
+    - type: precision_at_10
+      value: 4.446
+    - type: precision_at_100
+      value: 0.792
+    - type: precision_at_1000
+      value: 0.124
+    - type: precision_at_3
+      value: 9.945
+    - type: precision_at_5
+      value: 7.123
+    - type: recall_at_1
+      value: 15.074000000000002
+    - type: recall_at_10
+      value: 33.031
+    - type: recall_at_100
+      value: 53.954
+    - type: recall_at_1000
+      value: 77.631
+    - type: recall_at_3
+      value: 23.253
+    - type: recall_at_5
+      value: 27.218999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.04
+    - type: map_at_10
+      value: 28.226000000000003
+    - type: map_at_100
+      value: 29.337999999999997
+    - type: map_at_1000
+      value: 29.448999999999998
+    - type: map_at_3
+      value: 25.759
+    - type: map_at_5
+      value: 27.226
+    - type: mrr_at_1
+      value: 24.067
+    - type: mrr_at_10
+      value: 31.646
+    - type: mrr_at_100
+      value: 32.592999999999996
+    - type: mrr_at_1000
+      value: 32.668
+    - type: mrr_at_3
+      value: 29.26
+    - type: mrr_at_5
+      value: 30.725
+    - type: ndcg_at_1
+      value: 24.067
+    - type: ndcg_at_10
+      value: 32.789
+    - type: ndcg_at_100
+      value: 38.253
+    - type: ndcg_at_1000
+      value: 40.961
+    - type: ndcg_at_3
+      value: 28.189999999999998
+    - type: ndcg_at_5
+      value: 30.557000000000002
+    - type: precision_at_1
+      value: 24.067
+    - type: precision_at_10
+      value: 5.532
+    - type: precision_at_100
+      value: 0.928
+    - type: precision_at_1000
+      value: 0.128
+    - type: precision_at_3
+      value: 12.5
+    - type: precision_at_5
+      value: 9.16
+    - type: recall_at_1
+      value: 21.04
+    - type: recall_at_10
+      value: 43.167
+    - type: recall_at_100
+      value: 67.569
+    - type: recall_at_1000
+      value: 86.817
+    - type: recall_at_3
+      value: 31.178
+    - type: recall_at_5
+      value: 36.730000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.439
+    - type: map_at_10
+      value: 28.531000000000002
+    - type: map_at_100
+      value: 29.953999999999997
+    - type: map_at_1000
+      value: 30.171
+    - type: map_at_3
+      value: 26.546999999999997
+    - type: map_at_5
+      value: 27.71
+    - type: mrr_at_1
+      value: 26.087
+    - type: mrr_at_10
+      value: 32.635
+    - type: mrr_at_100
+      value: 33.629999999999995
+    - type: mrr_at_1000
+      value: 33.71
+    - type: mrr_at_3
+      value: 30.731
+    - type: mrr_at_5
+      value: 31.807999999999996
+    - type: ndcg_at_1
+      value: 26.087
+    - type: ndcg_at_10
+      value: 32.975
+    - type: ndcg_at_100
+      value: 38.853
+    - type: ndcg_at_1000
+      value: 42.158
+    - type: ndcg_at_3
+      value: 29.894
+    - type: ndcg_at_5
+      value: 31.397000000000002
+    - type: precision_at_1
+      value: 26.087
+    - type: precision_at_10
+      value: 6.2059999999999995
+    - type: precision_at_100
+      value: 1.298
+    - type: precision_at_1000
+      value: 0.22200000000000003
+    - type: precision_at_3
+      value: 14.097000000000001
+    - type: precision_at_5
+      value: 9.959999999999999
+    - type: recall_at_1
+      value: 21.439
+    - type: recall_at_10
+      value: 40.519
+    - type: recall_at_100
+      value: 68.073
+    - type: recall_at_1000
+      value: 89.513
+    - type: recall_at_3
+      value: 31.513
+    - type: recall_at_5
+      value: 35.702
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 18.983
+    - type: map_at_10
+      value: 24.898
+    - type: map_at_100
+      value: 25.836
+    - type: map_at_1000
+      value: 25.934
+    - type: map_at_3
+      value: 22.467000000000002
+    - type: map_at_5
+      value: 24.019
+    - type: mrr_at_1
+      value: 20.333000000000002
+    - type: mrr_at_10
+      value: 26.555
+    - type: mrr_at_100
+      value: 27.369
+    - type: mrr_at_1000
+      value: 27.448
+    - type: mrr_at_3
+      value: 24.091
+    - type: mrr_at_5
+      value: 25.662000000000003
+    - type: ndcg_at_1
+      value: 20.333000000000002
+    - type: ndcg_at_10
+      value: 28.834
+    - type: ndcg_at_100
+      value: 33.722
+    - type: ndcg_at_1000
+      value: 36.475
+    - type: ndcg_at_3
+      value: 24.08
+    - type: ndcg_at_5
+      value: 26.732
+    - type: precision_at_1
+      value: 20.333000000000002
+    - type: precision_at_10
+      value: 4.603
+    - type: precision_at_100
+      value: 0.771
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 9.982000000000001
+    - type: precision_at_5
+      value: 7.6160000000000005
+    - type: recall_at_1
+      value: 18.983
+    - type: recall_at_10
+      value: 39.35
+    - type: recall_at_100
+      value: 62.559
+    - type: recall_at_1000
+      value: 83.623
+    - type: recall_at_3
+      value: 26.799
+    - type: recall_at_5
+      value: 32.997
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 10.621
+    - type: map_at_10
+      value: 17.298
+    - type: map_at_100
+      value: 18.983
+    - type: map_at_1000
+      value: 19.182
+    - type: map_at_3
+      value: 14.552999999999999
+    - type: map_at_5
+      value: 15.912
+    - type: mrr_at_1
+      value: 23.453
+    - type: mrr_at_10
+      value: 33.932
+    - type: mrr_at_100
+      value: 34.891
+    - type: mrr_at_1000
+      value: 34.943000000000005
+    - type: mrr_at_3
+      value: 30.770999999999997
+    - type: mrr_at_5
+      value: 32.556000000000004
+    - type: ndcg_at_1
+      value: 23.453
+    - type: ndcg_at_10
+      value: 24.771
+    - type: ndcg_at_100
+      value: 31.738
+    - type: ndcg_at_1000
+      value: 35.419
+    - type: ndcg_at_3
+      value: 20.22
+    - type: ndcg_at_5
+      value: 21.698999999999998
+    - type: precision_at_1
+      value: 23.453
+    - type: precision_at_10
+      value: 7.785
+    - type: precision_at_100
+      value: 1.5270000000000001
+    - type: precision_at_1000
+      value: 0.22
+    - type: precision_at_3
+      value: 14.962
+    - type: precision_at_5
+      value: 11.401
+    - type: recall_at_1
+      value: 10.621
+    - type: recall_at_10
+      value: 29.726000000000003
+    - type: recall_at_100
+      value: 53.996
+    - type: recall_at_1000
+      value: 74.878
+    - type: recall_at_3
+      value: 18.572
+    - type: recall_at_5
+      value: 22.994999999999997
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.819
+    - type: map_at_10
+      value: 14.188
+    - type: map_at_100
+      value: 19.627
+    - type: map_at_1000
+      value: 20.757
+    - type: map_at_3
+      value: 10.352
+    - type: map_at_5
+      value: 12.096
+    - type: mrr_at_1
+      value: 54.25
+    - type: mrr_at_10
+      value: 63.798
+    - type: mrr_at_100
+      value: 64.25
+    - type: mrr_at_1000
+      value: 64.268
+    - type: mrr_at_3
+      value: 61.667
+    - type: mrr_at_5
+      value: 63.153999999999996
+    - type: ndcg_at_1
+      value: 39.5
+    - type: ndcg_at_10
+      value: 31.064999999999998
+    - type: ndcg_at_100
+      value: 34.701
+    - type: ndcg_at_1000
+      value: 41.687000000000005
+    - type: ndcg_at_3
+      value: 34.455999999999996
+    - type: ndcg_at_5
+      value: 32.919
+    - type: precision_at_1
+      value: 54.25
+    - type: precision_at_10
+      value: 25.4
+    - type: precision_at_100
+      value: 7.79
+    - type: precision_at_1000
+      value: 1.577
+    - type: precision_at_3
+      value: 39.333
+    - type: precision_at_5
+      value: 33.6
+    - type: recall_at_1
+      value: 6.819
+    - type: recall_at_10
+      value: 19.134
+    - type: recall_at_100
+      value: 41.191
+    - type: recall_at_1000
+      value: 64.699
+    - type: recall_at_3
+      value: 11.637
+    - type: recall_at_5
+      value: 14.807
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 42.474999999999994
+    - type: f1
+      value: 37.79154895614037
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 53.187
+    - type: map_at_10
+      value: 64.031
+    - type: map_at_100
+      value: 64.507
+    - type: map_at_1000
+      value: 64.526
+    - type: map_at_3
+      value: 61.926
+    - type: map_at_5
+      value: 63.278999999999996
+    - type: mrr_at_1
+      value: 57.396
+    - type: mrr_at_10
+      value: 68.296
+    - type: mrr_at_100
+      value: 68.679
+    - type: mrr_at_1000
+      value: 68.688
+    - type: mrr_at_3
+      value: 66.289
+    - type: mrr_at_5
+      value: 67.593
+    - type: ndcg_at_1
+      value: 57.396
+    - type: ndcg_at_10
+      value: 69.64
+    - type: ndcg_at_100
+      value: 71.75399999999999
+    - type: ndcg_at_1000
+      value: 72.179
+    - type: ndcg_at_3
+      value: 65.66199999999999
+    - type: ndcg_at_5
+      value: 67.932
+    - type: precision_at_1
+      value: 57.396
+    - type: precision_at_10
+      value: 9.073
+    - type: precision_at_100
+      value: 1.024
+    - type: precision_at_1000
+      value: 0.107
+    - type: precision_at_3
+      value: 26.133
+    - type: precision_at_5
+      value: 16.943
+    - type: recall_at_1
+      value: 53.187
+    - type: recall_at_10
+      value: 82.839
+    - type: recall_at_100
+      value: 92.231
+    - type: recall_at_1000
+      value: 95.249
+    - type: recall_at_3
+      value: 72.077
+    - type: recall_at_5
+      value: 77.667
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 10.957
+    - type: map_at_10
+      value: 18.427
+    - type: map_at_100
+      value: 19.885
+    - type: map_at_1000
+      value: 20.088
+    - type: map_at_3
+      value: 15.709000000000001
+    - type: map_at_5
+      value: 17.153
+    - type: mrr_at_1
+      value: 22.377
+    - type: mrr_at_10
+      value: 30.076999999999998
+    - type: mrr_at_100
+      value: 31.233
+    - type: mrr_at_1000
+      value: 31.311
+    - type: mrr_at_3
+      value: 27.521
+    - type: mrr_at_5
+      value: 29.025000000000002
+    - type: ndcg_at_1
+      value: 22.377
+    - type: ndcg_at_10
+      value: 24.367
+    - type: ndcg_at_100
+      value: 31.04
+    - type: ndcg_at_1000
+      value: 35.106
+    - type: ndcg_at_3
+      value: 21.051000000000002
+    - type: ndcg_at_5
+      value: 22.231
+    - type: precision_at_1
+      value: 22.377
+    - type: precision_at_10
+      value: 7.005999999999999
+    - type: precision_at_100
+      value: 1.3599999999999999
+    - type: precision_at_1000
+      value: 0.208
+    - type: precision_at_3
+      value: 13.991999999999999
+    - type: precision_at_5
+      value: 10.833
+    - type: recall_at_1
+      value: 10.957
+    - type: recall_at_10
+      value: 30.274
+    - type: recall_at_100
+      value: 55.982
+    - type: recall_at_1000
+      value: 80.757
+    - type: recall_at_3
+      value: 19.55
+    - type: recall_at_5
+      value: 24.105999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.526999999999997
+    - type: map_at_10
+      value: 40.714
+    - type: map_at_100
+      value: 41.655
+    - type: map_at_1000
+      value: 41.744
+    - type: map_at_3
+      value: 38.171
+    - type: map_at_5
+      value: 39.646
+    - type: mrr_at_1
+      value: 59.055
+    - type: mrr_at_10
+      value: 66.411
+    - type: mrr_at_100
+      value: 66.85900000000001
+    - type: mrr_at_1000
+      value: 66.88300000000001
+    - type: mrr_at_3
+      value: 64.846
+    - type: mrr_at_5
+      value: 65.824
+    - type: ndcg_at_1
+      value: 59.055
+    - type: ndcg_at_10
+      value: 49.732
+    - type: ndcg_at_100
+      value: 53.441
+    - type: ndcg_at_1000
+      value: 55.354000000000006
+    - type: ndcg_at_3
+      value: 45.551
+    - type: ndcg_at_5
+      value: 47.719
+    - type: precision_at_1
+      value: 59.055
+    - type: precision_at_10
+      value: 10.366
+    - type: precision_at_100
+      value: 1.328
+    - type: precision_at_1000
+      value: 0.158
+    - type: precision_at_3
+      value: 28.322999999999997
+    - type: precision_at_5
+      value: 18.709
+    - type: recall_at_1
+      value: 29.526999999999997
+    - type: recall_at_10
+      value: 51.83
+    - type: recall_at_100
+      value: 66.42099999999999
+    - type: recall_at_1000
+      value: 79.176
+    - type: recall_at_3
+      value: 42.485
+    - type: recall_at_5
+      value: 46.772000000000006
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 70.69959999999999
+    - type: ap
+      value: 64.95539314492567
+    - type: f1
+      value: 70.5554935943308
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 13.153
+    - type: map_at_10
+      value: 22.277
+    - type: map_at_100
+      value: 23.462
+    - type: map_at_1000
+      value: 23.546
+    - type: map_at_3
+      value: 19.026
+    - type: map_at_5
+      value: 20.825
+    - type: mrr_at_1
+      value: 13.539000000000001
+    - type: mrr_at_10
+      value: 22.753
+    - type: mrr_at_100
+      value: 23.906
+    - type: mrr_at_1000
+      value: 23.982999999999997
+    - type: mrr_at_3
+      value: 19.484
+    - type: mrr_at_5
+      value: 21.306
+    - type: ndcg_at_1
+      value: 13.553
+    - type: ndcg_at_10
+      value: 27.848
+    - type: ndcg_at_100
+      value: 33.900999999999996
+    - type: ndcg_at_1000
+      value: 36.155
+    - type: ndcg_at_3
+      value: 21.116
+    - type: ndcg_at_5
+      value: 24.349999999999998
+    - type: precision_at_1
+      value: 13.553
+    - type: precision_at_10
+      value: 4.695
+    - type: precision_at_100
+      value: 0.7779999999999999
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 9.207
+    - type: precision_at_5
+      value: 7.155
+    - type: recall_at_1
+      value: 13.153
+    - type: recall_at_10
+      value: 45.205
+    - type: recall_at_100
+      value: 73.978
+    - type: recall_at_1000
+      value: 91.541
+    - type: recall_at_3
+      value: 26.735
+    - type: recall_at_5
+      value: 34.493
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 90.2530779753762
+    - type: f1
+      value: 89.59402328284126
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 67.95029639762883
+    - type: f1
+      value: 48.99988836758662
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 67.77740416946874
+    - type: f1
+      value: 66.21341120969817
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 73.03631472763955
+    - type: f1
+      value: 72.5779336237941
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 31.98182669158824
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 29.259462874407582
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 31.29342377286548
+    - type: mrr
+      value: 32.32805799117226
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.692
+    - type: map_at_10
+      value: 10.559000000000001
+    - type: map_at_100
+      value: 13.665
+    - type: map_at_1000
+      value: 15.082
+    - type: map_at_3
+      value: 7.68
+    - type: map_at_5
+      value: 8.844000000000001
+    - type: mrr_at_1
+      value: 38.7
+    - type: mrr_at_10
+      value: 47.864000000000004
+    - type: mrr_at_100
+      value: 48.583999999999996
+    - type: mrr_at_1000
+      value: 48.636
+    - type: mrr_at_3
+      value: 45.975
+    - type: mrr_at_5
+      value: 47.074
+    - type: ndcg_at_1
+      value: 36.378
+    - type: ndcg_at_10
+      value: 30.038999999999998
+    - type: ndcg_at_100
+      value: 28.226000000000003
+    - type: ndcg_at_1000
+      value: 36.958
+    - type: ndcg_at_3
+      value: 33.469
+    - type: ndcg_at_5
+      value: 32.096999999999994
+    - type: precision_at_1
+      value: 38.080000000000005
+    - type: precision_at_10
+      value: 22.941
+    - type: precision_at_100
+      value: 7.632
+    - type: precision_at_1000
+      value: 2.0420000000000003
+    - type: precision_at_3
+      value: 31.579
+    - type: precision_at_5
+      value: 28.235
+    - type: recall_at_1
+      value: 4.692
+    - type: recall_at_10
+      value: 14.496
+    - type: recall_at_100
+      value: 29.69
+    - type: recall_at_1000
+      value: 61.229
+    - type: recall_at_3
+      value: 8.871
+    - type: recall_at_5
+      value: 10.825999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 13.120000000000001
+    - type: map_at_10
+      value: 24.092
+    - type: map_at_100
+      value: 25.485999999999997
+    - type: map_at_1000
+      value: 25.557999999999996
+    - type: map_at_3
+      value: 20.076
+    - type: map_at_5
+      value: 22.368
+    - type: mrr_at_1
+      value: 15.093
+    - type: mrr_at_10
+      value: 26.142
+    - type: mrr_at_100
+      value: 27.301
+    - type: mrr_at_1000
+      value: 27.357
+    - type: mrr_at_3
+      value: 22.364
+    - type: mrr_at_5
+      value: 24.564
+    - type: ndcg_at_1
+      value: 15.093
+    - type: ndcg_at_10
+      value: 30.734
+    - type: ndcg_at_100
+      value: 37.147999999999996
+    - type: ndcg_at_1000
+      value: 38.997
+    - type: ndcg_at_3
+      value: 22.82
+    - type: ndcg_at_5
+      value: 26.806
+    - type: precision_at_1
+      value: 15.093
+    - type: precision_at_10
+      value: 5.863
+    - type: precision_at_100
+      value: 0.942
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 11.047
+    - type: precision_at_5
+      value: 8.863999999999999
+    - type: recall_at_1
+      value: 13.120000000000001
+    - type: recall_at_10
+      value: 49.189
+    - type: recall_at_100
+      value: 78.032
+    - type: recall_at_1000
+      value: 92.034
+    - type: recall_at_3
+      value: 28.483000000000004
+    - type: recall_at_5
+      value: 37.756
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 67.765
+    - type: map_at_10
+      value: 81.069
+    - type: map_at_100
+      value: 81.757
+    - type: map_at_1000
+      value: 81.782
+    - type: map_at_3
+      value: 78.148
+    - type: map_at_5
+      value: 79.95400000000001
+    - type: mrr_at_1
+      value: 77.8
+    - type: mrr_at_10
+      value: 84.639
+    - type: mrr_at_100
+      value: 84.789
+    - type: mrr_at_1000
+      value: 84.79100000000001
+    - type: mrr_at_3
+      value: 83.467
+    - type: mrr_at_5
+      value: 84.251
+    - type: ndcg_at_1
+      value: 77.82
+    - type: ndcg_at_10
+      value: 85.286
+    - type: ndcg_at_100
+      value: 86.86500000000001
+    - type: ndcg_at_1000
+      value: 87.062
+    - type: ndcg_at_3
+      value: 82.116
+    - type: ndcg_at_5
+      value: 83.811
+    - type: precision_at_1
+      value: 77.82
+    - type: precision_at_10
+      value: 12.867999999999999
+    - type: precision_at_100
+      value: 1.498
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 35.723
+    - type: precision_at_5
+      value: 23.52
+    - type: recall_at_1
+      value: 67.765
+    - type: recall_at_10
+      value: 93.381
+    - type: recall_at_100
+      value: 98.901
+    - type: recall_at_1000
+      value: 99.864
+    - type: recall_at_3
+      value: 84.301
+    - type: recall_at_5
+      value: 89.049
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 45.27190981742137
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 54.47444004585028
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.213
+    - type: map_at_10
+      value: 10.166
+    - type: map_at_100
+      value: 11.987
+    - type: map_at_1000
+      value: 12.285
+    - type: map_at_3
+      value: 7.538
+    - type: map_at_5
+      value: 8.606
+    - type: mrr_at_1
+      value: 20.8
+    - type: mrr_at_10
+      value: 30.066
+    - type: mrr_at_100
+      value: 31.290000000000003
+    - type: mrr_at_1000
+      value: 31.357000000000003
+    - type: mrr_at_3
+      value: 27.083000000000002
+    - type: mrr_at_5
+      value: 28.748
+    - type: ndcg_at_1
+      value: 20.8
+    - type: ndcg_at_10
+      value: 17.258000000000003
+    - type: ndcg_at_100
+      value: 24.801000000000002
+    - type: ndcg_at_1000
+      value: 30.348999999999997
+    - type: ndcg_at_3
+      value: 16.719
+    - type: ndcg_at_5
+      value: 14.145
+    - type: precision_at_1
+      value: 20.8
+    - type: precision_at_10
+      value: 8.88
+    - type: precision_at_100
+      value: 1.9789999999999999
+    - type: precision_at_1000
+      value: 0.332
+    - type: precision_at_3
+      value: 15.5
+    - type: precision_at_5
+      value: 12.1
+    - type: recall_at_1
+      value: 4.213
+    - type: recall_at_10
+      value: 17.983
+    - type: recall_at_100
+      value: 40.167
+    - type: recall_at_1000
+      value: 67.43
+    - type: recall_at_3
+      value: 9.433
+    - type: recall_at_5
+      value: 12.267999999999999
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.36742239848913
+    - type: cos_sim_spearman
+      value: 72.39470010828755
+    - type: euclidean_pearson
+      value: 77.26919895870947
+    - type: euclidean_spearman
+      value: 72.26534999077315
+    - type: manhattan_pearson
+      value: 77.04066349814258
+    - type: manhattan_spearman
+      value: 72.0072248699278
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.26991474037257
+    - type: cos_sim_spearman
+      value: 71.90287122017716
+    - type: euclidean_pearson
+      value: 76.68006075912453
+    - type: euclidean_spearman
+      value: 71.69301858764365
+    - type: manhattan_pearson
+      value: 76.72277285842371
+    - type: manhattan_spearman
+      value: 71.73265239703795
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.74371413317881
+    - type: cos_sim_spearman
+      value: 80.9279612820358
+    - type: euclidean_pearson
+      value: 80.6417435294782
+    - type: euclidean_spearman
+      value: 81.17460969254459
+    - type: manhattan_pearson
+      value: 80.51820155178402
+    - type: manhattan_spearman
+      value: 81.08028700017084
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.37085777051112
+    - type: cos_sim_spearman
+      value: 76.60308382518285
+    - type: euclidean_pearson
+      value: 79.59684787227351
+    - type: euclidean_spearman
+      value: 76.8769048249242
+    - type: manhattan_pearson
+      value: 79.55617632538295
+    - type: manhattan_spearman
+      value: 76.90186497973124
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.99513105301321
+    - type: cos_sim_spearman
+      value: 84.92034548133665
+    - type: euclidean_pearson
+      value: 84.70872540095195
+    - type: euclidean_spearman
+      value: 85.14591726040749
+    - type: manhattan_pearson
+      value: 84.65707417430595
+    - type: manhattan_spearman
+      value: 85.10407163865375
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.40758449150897
+    - type: cos_sim_spearman
+      value: 80.71692246880549
+    - type: euclidean_pearson
+      value: 80.51658552062683
+    - type: euclidean_spearman
+      value: 80.87118389043233
+    - type: manhattan_pearson
+      value: 80.41534690825016
+    - type: manhattan_spearman
+      value: 80.73925282537256
+  - 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: 84.93617076910748
+    - type: cos_sim_spearman
+      value: 85.61118538966805
+    - type: euclidean_pearson
+      value: 85.56187558635287
+    - type: euclidean_spearman
+      value: 85.21910090757267
+    - type: manhattan_pearson
+      value: 85.29916699037645
+    - type: manhattan_spearman
+      value: 84.96820527868671
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 64.22294088543077
+    - type: cos_sim_spearman
+      value: 65.89748502901078
+    - type: euclidean_pearson
+      value: 66.15637850660805
+    - type: euclidean_spearman
+      value: 65.86095841381278
+    - type: manhattan_pearson
+      value: 66.80966197857856
+    - type: manhattan_spearman
+      value: 66.48325202219692
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.75298158703048
+    - type: cos_sim_spearman
+      value: 81.32168373072322
+    - type: euclidean_pearson
+      value: 82.3251793712207
+    - type: euclidean_spearman
+      value: 81.31655163330606
+    - type: manhattan_pearson
+      value: 82.14136865023298
+    - type: manhattan_spearman
+      value: 81.13410964028606
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 78.77937068780793
+    - type: mrr
+      value: 93.334709952357
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 50.705999999999996
+    - type: map_at_10
+      value: 60.699999999999996
+    - type: map_at_100
+      value: 61.256
+    - type: map_at_1000
+      value: 61.285000000000004
+    - type: map_at_3
+      value: 57.633
+    - type: map_at_5
+      value: 59.648
+    - type: mrr_at_1
+      value: 53.0
+    - type: mrr_at_10
+      value: 61.717999999999996
+    - type: mrr_at_100
+      value: 62.165000000000006
+    - type: mrr_at_1000
+      value: 62.190999999999995
+    - type: mrr_at_3
+      value: 59.389
+    - type: mrr_at_5
+      value: 60.922
+    - type: ndcg_at_1
+      value: 53.0
+    - type: ndcg_at_10
+      value: 65.413
+    - type: ndcg_at_100
+      value: 68.089
+    - type: ndcg_at_1000
+      value: 69.01899999999999
+    - type: ndcg_at_3
+      value: 60.327
+    - type: ndcg_at_5
+      value: 63.263999999999996
+    - type: precision_at_1
+      value: 53.0
+    - type: precision_at_10
+      value: 8.933
+    - type: precision_at_100
+      value: 1.04
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 23.778
+    - type: precision_at_5
+      value: 16.2
+    - type: recall_at_1
+      value: 50.705999999999996
+    - type: recall_at_10
+      value: 78.633
+    - type: recall_at_100
+      value: 91.333
+    - type: recall_at_1000
+      value: 99.0
+    - type: recall_at_3
+      value: 65.328
+    - type: recall_at_5
+      value: 72.583
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.82178217821782
+    - type: cos_sim_ap
+      value: 95.30078788098801
+    - type: cos_sim_f1
+      value: 91.11549851924975
+    - type: cos_sim_precision
+      value: 89.96101364522417
+    - type: cos_sim_recall
+      value: 92.30000000000001
+    - type: dot_accuracy
+      value: 99.74851485148515
+    - type: dot_ap
+      value: 93.12383012680787
+    - type: dot_f1
+      value: 87.17171717171716
+    - type: dot_precision
+      value: 88.06122448979592
+    - type: dot_recall
+      value: 86.3
+    - type: euclidean_accuracy
+      value: 99.82673267326733
+    - type: euclidean_ap
+      value: 95.29507269622621
+    - type: euclidean_f1
+      value: 91.3151364764268
+    - type: euclidean_precision
+      value: 90.64039408866995
+    - type: euclidean_recall
+      value: 92.0
+    - type: manhattan_accuracy
+      value: 99.82178217821782
+    - type: manhattan_ap
+      value: 95.34300712110257
+    - type: manhattan_f1
+      value: 91.05367793240556
+    - type: manhattan_precision
+      value: 90.51383399209486
+    - type: manhattan_recall
+      value: 91.60000000000001
+    - type: max_accuracy
+      value: 99.82673267326733
+    - type: max_ap
+      value: 95.34300712110257
+    - type: max_f1
+      value: 91.3151364764268
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 53.10993894014712
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 34.67216071080345
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 48.96344255085851
+    - type: mrr
+      value: 49.816123419064596
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.580410074992177
+    - type: cos_sim_spearman
+      value: 31.155995112739966
+    - type: dot_pearson
+      value: 31.112094423048998
+    - type: dot_spearman
+      value: 31.29974829801922
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.17700000000000002
+    - type: map_at_10
+      value: 1.22
+    - type: map_at_100
+      value: 6.2170000000000005
+    - type: map_at_1000
+      value: 15.406
+    - type: map_at_3
+      value: 0.483
+    - type: map_at_5
+      value: 0.729
+    - type: mrr_at_1
+      value: 64.0
+    - type: mrr_at_10
+      value: 76.333
+    - type: mrr_at_100
+      value: 76.47
+    - type: mrr_at_1000
+      value: 76.47
+    - type: mrr_at_3
+      value: 75.0
+    - type: mrr_at_5
+      value: 76.0
+    - type: ndcg_at_1
+      value: 59.0
+    - type: ndcg_at_10
+      value: 52.62
+    - type: ndcg_at_100
+      value: 39.932
+    - type: ndcg_at_1000
+      value: 37.317
+    - type: ndcg_at_3
+      value: 57.123000000000005
+    - type: ndcg_at_5
+      value: 56.376000000000005
+    - type: precision_at_1
+      value: 64.0
+    - type: precision_at_10
+      value: 55.800000000000004
+    - type: precision_at_100
+      value: 41.04
+    - type: precision_at_1000
+      value: 17.124
+    - type: precision_at_3
+      value: 63.333
+    - type: precision_at_5
+      value: 62.0
+    - type: recall_at_1
+      value: 0.17700000000000002
+    - type: recall_at_10
+      value: 1.46
+    - type: recall_at_100
+      value: 9.472999999999999
+    - type: recall_at_1000
+      value: 35.661
+    - type: recall_at_3
+      value: 0.527
+    - type: recall_at_5
+      value: 0.8250000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.539
+    - type: map_at_10
+      value: 7.178
+    - type: map_at_100
+      value: 12.543000000000001
+    - type: map_at_1000
+      value: 14.126
+    - type: map_at_3
+      value: 3.09
+    - type: map_at_5
+      value: 5.008
+    - type: mrr_at_1
+      value: 18.367
+    - type: mrr_at_10
+      value: 32.933
+    - type: mrr_at_100
+      value: 34.176
+    - type: mrr_at_1000
+      value: 34.176
+    - type: mrr_at_3
+      value: 27.551
+    - type: mrr_at_5
+      value: 30.714000000000002
+    - type: ndcg_at_1
+      value: 15.306000000000001
+    - type: ndcg_at_10
+      value: 18.343
+    - type: ndcg_at_100
+      value: 30.076000000000004
+    - type: ndcg_at_1000
+      value: 42.266999999999996
+    - type: ndcg_at_3
+      value: 17.233999999999998
+    - type: ndcg_at_5
+      value: 18.677
+    - type: precision_at_1
+      value: 18.367
+    - type: precision_at_10
+      value: 18.367
+    - type: precision_at_100
+      value: 6.837
+    - type: precision_at_1000
+      value: 1.467
+    - type: precision_at_3
+      value: 19.048000000000002
+    - type: precision_at_5
+      value: 21.224
+    - type: recall_at_1
+      value: 1.539
+    - type: recall_at_10
+      value: 13.289000000000001
+    - type: recall_at_100
+      value: 42.480000000000004
+    - type: recall_at_1000
+      value: 79.463
+    - type: recall_at_3
+      value: 4.202999999999999
+    - type: recall_at_5
+      value: 7.9030000000000005
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 69.2056
+    - type: ap
+      value: 13.564165903349778
+    - type: f1
+      value: 53.303385089202656
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 56.71477079796264
+    - type: f1
+      value: 57.01563439439609
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 39.373040570976514
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.44757703999524
+    - type: cos_sim_ap
+      value: 65.78689843625949
+    - type: cos_sim_f1
+      value: 62.25549384206713
+    - type: cos_sim_precision
+      value: 57.39091718610864
+    - type: cos_sim_recall
+      value: 68.02110817941951
+    - type: dot_accuracy
+      value: 81.3971508612982
+    - type: dot_ap
+      value: 58.42933051967154
+    - type: dot_f1
+      value: 57.85580214198962
+    - type: dot_precision
+      value: 49.74368710841086
+    - type: dot_recall
+      value: 69.12928759894459
+    - type: euclidean_accuracy
+      value: 83.54294569946951
+    - type: euclidean_ap
+      value: 66.10612585693795
+    - type: euclidean_f1
+      value: 62.66666666666667
+    - type: euclidean_precision
+      value: 58.88631090487239
+    - type: euclidean_recall
+      value: 66.96569920844327
+    - type: manhattan_accuracy
+      value: 83.43565595756095
+    - type: manhattan_ap
+      value: 65.88532290329134
+    - type: manhattan_f1
+      value: 62.58408721874276
+    - type: manhattan_precision
+      value: 55.836092715231786
+    - type: manhattan_recall
+      value: 71.18733509234828
+    - type: max_accuracy
+      value: 83.54294569946951
+    - type: max_ap
+      value: 66.10612585693795
+    - type: max_f1
+      value: 62.66666666666667
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.02344083517679
+    - type: cos_sim_ap
+      value: 84.21589190889944
+    - type: cos_sim_f1
+      value: 76.36723039754007
+    - type: cos_sim_precision
+      value: 72.79134682484299
+    - type: cos_sim_recall
+      value: 80.31259624268556
+    - type: dot_accuracy
+      value: 87.43353902278108
+    - type: dot_ap
+      value: 82.08962394120071
+    - type: dot_f1
+      value: 74.97709923664122
+    - type: dot_precision
+      value: 74.34150772025431
+    - type: dot_recall
+      value: 75.62365260240222
+    - type: euclidean_accuracy
+      value: 87.97686963946133
+    - type: euclidean_ap
+      value: 84.20578083922416
+    - type: euclidean_f1
+      value: 76.4299182903834
+    - type: euclidean_precision
+      value: 73.51874244256348
+    - type: euclidean_recall
+      value: 79.58115183246073
+    - type: manhattan_accuracy
+      value: 88.00209570380719
+    - type: manhattan_ap
+      value: 84.14700304263556
+    - type: manhattan_f1
+      value: 76.36429345861944
+    - type: manhattan_precision
+      value: 71.95886119057349
+    - type: manhattan_recall
+      value: 81.34431783184478
+    - type: max_accuracy
+      value: 88.02344083517679
+    - type: max_ap
+      value: 84.21589190889944
+    - type: max_f1
+      value: 76.4299182903834
 ---
+# bge-micro
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
+It is distilled from [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5/blob/main/config.json), with 1/4 the non-embedding parameters.
+It has 1/2 the parameters of the smallest commonly-used embedding model, all-MiniLM-L6-v2, with similar performance.
 <!--- Describe your model here -->