Update README.md

README.md

@@ -5,14 +5,2609 @@ tags:
 - 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: 67.76119402985074
+    - type: ap
+      value: 29.637849284211114
+    - type: f1
+      value: 61.31181187111905
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 79.7547
+    - type: ap
+      value: 74.21401629809145
+    - type: f1
+      value: 79.65319615433783
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 37.452000000000005
+    - type: f1
+      value: 37.0245198854966
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.152
+    - type: map_at_10
+      value: 46.702
+    - type: map_at_100
+      value: 47.563
+    - type: map_at_1000
+      value: 47.567
+    - type: map_at_3
+      value: 42.058
+    - type: map_at_5
+      value: 44.608
+    - type: mrr_at_1
+      value: 32.006
+    - type: mrr_at_10
+      value: 47.064
+    - type: mrr_at_100
+      value: 47.910000000000004
+    - type: mrr_at_1000
+      value: 47.915
+    - type: mrr_at_3
+      value: 42.283
+    - type: mrr_at_5
+      value: 44.968
+    - type: ndcg_at_1
+      value: 31.152
+    - type: ndcg_at_10
+      value: 55.308
+    - type: ndcg_at_100
+      value: 58.965
+    - type: ndcg_at_1000
+      value: 59.067
+    - type: ndcg_at_3
+      value: 45.698
+    - type: ndcg_at_5
+      value: 50.296
+    - type: precision_at_1
+      value: 31.152
+    - type: precision_at_10
+      value: 8.279
+    - type: precision_at_100
+      value: 0.987
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 18.753
+    - type: precision_at_5
+      value: 13.485
+    - type: recall_at_1
+      value: 31.152
+    - type: recall_at_10
+      value: 82.788
+    - type: recall_at_100
+      value: 98.72
+    - type: recall_at_1000
+      value: 99.502
+    - type: recall_at_3
+      value: 56.259
+    - type: recall_at_5
+      value: 67.425
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 44.52692241938116
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 33.245710292773595
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 58.08493637155168
+    - type: mrr
+      value: 71.94378490084861
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.1602804378326
+    - type: cos_sim_spearman
+      value: 82.92478106365587
+    - type: euclidean_pearson
+      value: 82.27930167277077
+    - type: euclidean_spearman
+      value: 82.18560759458093
+    - type: manhattan_pearson
+      value: 82.34277425888187
+    - type: manhattan_spearman
+      value: 81.72776583704467
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 81.17207792207792
+    - type: f1
+      value: 81.09893836310513
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 36.109308463095516
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 28.06048212317168
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.233999999999998
+    - type: map_at_10
+      value: 38.092999999999996
+    - type: map_at_100
+      value: 39.473
+    - type: map_at_1000
+      value: 39.614
+    - type: map_at_3
+      value: 34.839
+    - type: map_at_5
+      value: 36.523
+    - type: mrr_at_1
+      value: 35.193000000000005
+    - type: mrr_at_10
+      value: 44.089
+    - type: mrr_at_100
+      value: 44.927
+    - type: mrr_at_1000
+      value: 44.988
+    - type: mrr_at_3
+      value: 41.559000000000005
+    - type: mrr_at_5
+      value: 43.162
+    - type: ndcg_at_1
+      value: 35.193000000000005
+    - type: ndcg_at_10
+      value: 44.04
+    - type: ndcg_at_100
+      value: 49.262
+    - type: ndcg_at_1000
+      value: 51.847
+    - type: ndcg_at_3
+      value: 39.248
+    - type: ndcg_at_5
+      value: 41.298
+    - type: precision_at_1
+      value: 35.193000000000005
+    - type: precision_at_10
+      value: 8.555
+    - type: precision_at_100
+      value: 1.3820000000000001
+    - type: precision_at_1000
+      value: 0.189
+    - type: precision_at_3
+      value: 19.123
+    - type: precision_at_5
+      value: 13.648
+    - type: recall_at_1
+      value: 28.233999999999998
+    - type: recall_at_10
+      value: 55.094
+    - type: recall_at_100
+      value: 76.85300000000001
+    - type: recall_at_1000
+      value: 94.163
+    - type: recall_at_3
+      value: 40.782000000000004
+    - type: recall_at_5
+      value: 46.796
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.538
+    - type: map_at_10
+      value: 28.449
+    - type: map_at_100
+      value: 29.471000000000004
+    - type: map_at_1000
+      value: 29.599999999999998
+    - type: map_at_3
+      value: 26.371
+    - type: map_at_5
+      value: 27.58
+    - type: mrr_at_1
+      value: 26.815
+    - type: mrr_at_10
+      value: 33.331
+    - type: mrr_at_100
+      value: 34.114
+    - type: mrr_at_1000
+      value: 34.182
+    - type: mrr_at_3
+      value: 31.561
+    - type: mrr_at_5
+      value: 32.608
+    - type: ndcg_at_1
+      value: 26.815
+    - type: ndcg_at_10
+      value: 32.67
+    - type: ndcg_at_100
+      value: 37.039
+    - type: ndcg_at_1000
+      value: 39.769
+    - type: ndcg_at_3
+      value: 29.523
+    - type: ndcg_at_5
+      value: 31.048
+    - type: precision_at_1
+      value: 26.815
+    - type: precision_at_10
+      value: 5.955
+    - type: precision_at_100
+      value: 1.02
+    - type: precision_at_1000
+      value: 0.152
+    - type: precision_at_3
+      value: 14.033999999999999
+    - type: precision_at_5
+      value: 9.911
+    - type: recall_at_1
+      value: 21.538
+    - type: recall_at_10
+      value: 40.186
+    - type: recall_at_100
+      value: 58.948
+    - type: recall_at_1000
+      value: 77.158
+    - type: recall_at_3
+      value: 30.951
+    - type: recall_at_5
+      value: 35.276
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 35.211999999999996
+    - type: map_at_10
+      value: 46.562
+    - type: map_at_100
+      value: 47.579
+    - type: map_at_1000
+      value: 47.646
+    - type: map_at_3
+      value: 43.485
+    - type: map_at_5
+      value: 45.206
+    - type: mrr_at_1
+      value: 40.627
+    - type: mrr_at_10
+      value: 49.928
+    - type: mrr_at_100
+      value: 50.647
+    - type: mrr_at_1000
+      value: 50.685
+    - type: mrr_at_3
+      value: 47.513
+    - type: mrr_at_5
+      value: 48.958
+    - type: ndcg_at_1
+      value: 40.627
+    - type: ndcg_at_10
+      value: 52.217
+    - type: ndcg_at_100
+      value: 56.423
+    - type: ndcg_at_1000
+      value: 57.821999999999996
+    - type: ndcg_at_3
+      value: 46.949000000000005
+    - type: ndcg_at_5
+      value: 49.534
+    - type: precision_at_1
+      value: 40.627
+    - type: precision_at_10
+      value: 8.476
+    - type: precision_at_100
+      value: 1.15
+    - type: precision_at_1000
+      value: 0.132
+    - type: precision_at_3
+      value: 21.003
+    - type: precision_at_5
+      value: 14.469999999999999
+    - type: recall_at_1
+      value: 35.211999999999996
+    - type: recall_at_10
+      value: 65.692
+    - type: recall_at_100
+      value: 84.011
+    - type: recall_at_1000
+      value: 94.03099999999999
+    - type: recall_at_3
+      value: 51.404
+    - type: recall_at_5
+      value: 57.882
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.09
+    - type: map_at_10
+      value: 29.516
+    - type: map_at_100
+      value: 30.462
+    - type: map_at_1000
+      value: 30.56
+    - type: map_at_3
+      value: 26.945000000000004
+    - type: map_at_5
+      value: 28.421999999999997
+    - type: mrr_at_1
+      value: 23.616
+    - type: mrr_at_10
+      value: 31.221
+    - type: mrr_at_100
+      value: 32.057
+    - type: mrr_at_1000
+      value: 32.137
+    - type: mrr_at_3
+      value: 28.738000000000003
+    - type: mrr_at_5
+      value: 30.156
+    - type: ndcg_at_1
+      value: 23.616
+    - type: ndcg_at_10
+      value: 33.97
+    - type: ndcg_at_100
+      value: 38.806000000000004
+    - type: ndcg_at_1000
+      value: 41.393
+    - type: ndcg_at_3
+      value: 28.908
+    - type: ndcg_at_5
+      value: 31.433
+    - type: precision_at_1
+      value: 23.616
+    - type: precision_at_10
+      value: 5.299
+    - type: precision_at_100
+      value: 0.812
+    - type: precision_at_1000
+      value: 0.107
+    - type: precision_at_3
+      value: 12.015
+    - type: precision_at_5
+      value: 8.701
+    - type: recall_at_1
+      value: 22.09
+    - type: recall_at_10
+      value: 46.089999999999996
+    - type: recall_at_100
+      value: 68.729
+    - type: recall_at_1000
+      value: 88.435
+    - type: recall_at_3
+      value: 32.584999999999994
+    - type: recall_at_5
+      value: 38.550000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.469
+    - type: map_at_10
+      value: 22.436
+    - type: map_at_100
+      value: 23.465
+    - type: map_at_1000
+      value: 23.608999999999998
+    - type: map_at_3
+      value: 19.716
+    - type: map_at_5
+      value: 21.182000000000002
+    - type: mrr_at_1
+      value: 18.905
+    - type: mrr_at_10
+      value: 26.55
+    - type: mrr_at_100
+      value: 27.46
+    - type: mrr_at_1000
+      value: 27.553
+    - type: mrr_at_3
+      value: 23.921999999999997
+    - type: mrr_at_5
+      value: 25.302999999999997
+    - type: ndcg_at_1
+      value: 18.905
+    - type: ndcg_at_10
+      value: 27.437
+    - type: ndcg_at_100
+      value: 32.555
+    - type: ndcg_at_1000
+      value: 35.885
+    - type: ndcg_at_3
+      value: 22.439
+    - type: ndcg_at_5
+      value: 24.666
+    - type: precision_at_1
+      value: 18.905
+    - type: precision_at_10
+      value: 5.2490000000000006
+    - type: precision_at_100
+      value: 0.889
+    - type: precision_at_1000
+      value: 0.131
+    - type: precision_at_3
+      value: 10.862
+    - type: precision_at_5
+      value: 8.085
+    - type: recall_at_1
+      value: 15.469
+    - type: recall_at_10
+      value: 38.706
+    - type: recall_at_100
+      value: 61.242
+    - type: recall_at_1000
+      value: 84.84
+    - type: recall_at_3
+      value: 24.973
+    - type: recall_at_5
+      value: 30.603
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.918000000000003
+    - type: map_at_10
+      value: 34.296
+    - type: map_at_100
+      value: 35.632000000000005
+    - type: map_at_1000
+      value: 35.748999999999995
+    - type: map_at_3
+      value: 31.304
+    - type: map_at_5
+      value: 33.166000000000004
+    - type: mrr_at_1
+      value: 30.703000000000003
+    - type: mrr_at_10
+      value: 39.655
+    - type: mrr_at_100
+      value: 40.569
+    - type: mrr_at_1000
+      value: 40.621
+    - type: mrr_at_3
+      value: 37.023
+    - type: mrr_at_5
+      value: 38.664
+    - type: ndcg_at_1
+      value: 30.703000000000003
+    - type: ndcg_at_10
+      value: 39.897
+    - type: ndcg_at_100
+      value: 45.777
+    - type: ndcg_at_1000
+      value: 48.082
+    - type: ndcg_at_3
+      value: 35.122
+    - type: ndcg_at_5
+      value: 37.691
+    - type: precision_at_1
+      value: 30.703000000000003
+    - type: precision_at_10
+      value: 7.305000000000001
+    - type: precision_at_100
+      value: 1.208
+    - type: precision_at_1000
+      value: 0.159
+    - type: precision_at_3
+      value: 16.811
+    - type: precision_at_5
+      value: 12.203999999999999
+    - type: recall_at_1
+      value: 24.918000000000003
+    - type: recall_at_10
+      value: 51.31
+    - type: recall_at_100
+      value: 76.534
+    - type: recall_at_1000
+      value: 91.911
+    - type: recall_at_3
+      value: 37.855
+    - type: recall_at_5
+      value: 44.493
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.416
+    - type: map_at_10
+      value: 30.474
+    - type: map_at_100
+      value: 31.759999999999998
+    - type: map_at_1000
+      value: 31.891000000000002
+    - type: map_at_3
+      value: 27.728
+    - type: map_at_5
+      value: 29.247
+    - type: mrr_at_1
+      value: 28.881
+    - type: mrr_at_10
+      value: 36.418
+    - type: mrr_at_100
+      value: 37.347
+    - type: mrr_at_1000
+      value: 37.415
+    - type: mrr_at_3
+      value: 33.942
+    - type: mrr_at_5
+      value: 35.386
+    - type: ndcg_at_1
+      value: 28.881
+    - type: ndcg_at_10
+      value: 35.812
+    - type: ndcg_at_100
+      value: 41.574
+    - type: ndcg_at_1000
+      value: 44.289
+    - type: ndcg_at_3
+      value: 31.239
+    - type: ndcg_at_5
+      value: 33.302
+    - type: precision_at_1
+      value: 28.881
+    - type: precision_at_10
+      value: 6.598
+    - type: precision_at_100
+      value: 1.1079999999999999
+    - type: precision_at_1000
+      value: 0.151
+    - type: precision_at_3
+      value: 14.954
+    - type: precision_at_5
+      value: 10.776
+    - type: recall_at_1
+      value: 22.416
+    - type: recall_at_10
+      value: 46.243
+    - type: recall_at_100
+      value: 71.352
+    - type: recall_at_1000
+      value: 90.034
+    - type: recall_at_3
+      value: 32.873000000000005
+    - type: recall_at_5
+      value: 38.632
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.528166666666667
+    - type: map_at_10
+      value: 30.317833333333333
+    - type: map_at_100
+      value: 31.44108333333333
+    - type: map_at_1000
+      value: 31.566666666666666
+    - type: map_at_3
+      value: 27.84425
+    - type: map_at_5
+      value: 29.233333333333334
+    - type: mrr_at_1
+      value: 26.75733333333333
+    - type: mrr_at_10
+      value: 34.24425
+    - type: mrr_at_100
+      value: 35.11375
+    - type: mrr_at_1000
+      value: 35.184333333333335
+    - type: mrr_at_3
+      value: 32.01225
+    - type: mrr_at_5
+      value: 33.31225
+    - type: ndcg_at_1
+      value: 26.75733333333333
+    - type: ndcg_at_10
+      value: 35.072583333333334
+    - type: ndcg_at_100
+      value: 40.13358333333334
+    - type: ndcg_at_1000
+      value: 42.81825
+    - type: ndcg_at_3
+      value: 30.79275000000001
+    - type: ndcg_at_5
+      value: 32.822
+    - type: precision_at_1
+      value: 26.75733333333333
+    - type: precision_at_10
+      value: 6.128083333333334
+    - type: precision_at_100
+      value: 1.019
+    - type: precision_at_1000
+      value: 0.14391666666666664
+    - type: precision_at_3
+      value: 14.129916666666665
+    - type: precision_at_5
+      value: 10.087416666666668
+    - type: recall_at_1
+      value: 22.528166666666667
+    - type: recall_at_10
+      value: 45.38341666666667
+    - type: recall_at_100
+      value: 67.81791666666668
+    - type: recall_at_1000
+      value: 86.71716666666666
+    - type: recall_at_3
+      value: 33.38741666666667
+    - type: recall_at_5
+      value: 38.62041666666667
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.975
+    - type: map_at_10
+      value: 28.144999999999996
+    - type: map_at_100
+      value: 28.994999999999997
+    - type: map_at_1000
+      value: 29.086000000000002
+    - type: map_at_3
+      value: 25.968999999999998
+    - type: map_at_5
+      value: 27.321
+    - type: mrr_at_1
+      value: 25.0
+    - type: mrr_at_10
+      value: 30.822
+    - type: mrr_at_100
+      value: 31.647
+    - type: mrr_at_1000
+      value: 31.712
+    - type: mrr_at_3
+      value: 28.860000000000003
+    - type: mrr_at_5
+      value: 30.041
+    - type: ndcg_at_1
+      value: 25.0
+    - type: ndcg_at_10
+      value: 31.929999999999996
+    - type: ndcg_at_100
+      value: 36.258
+    - type: ndcg_at_1000
+      value: 38.682
+    - type: ndcg_at_3
+      value: 27.972
+    - type: ndcg_at_5
+      value: 30.089
+    - type: precision_at_1
+      value: 25.0
+    - type: precision_at_10
+      value: 4.923
+    - type: precision_at_100
+      value: 0.767
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 11.860999999999999
+    - type: precision_at_5
+      value: 8.466
+    - type: recall_at_1
+      value: 21.975
+    - type: recall_at_10
+      value: 41.102
+    - type: recall_at_100
+      value: 60.866
+    - type: recall_at_1000
+      value: 78.781
+    - type: recall_at_3
+      value: 30.268
+    - type: recall_at_5
+      value: 35.552
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.845999999999998
+    - type: map_at_10
+      value: 21.861
+    - type: map_at_100
+      value: 22.798
+    - type: map_at_1000
+      value: 22.925
+    - type: map_at_3
+      value: 19.922
+    - type: map_at_5
+      value: 21.054000000000002
+    - type: mrr_at_1
+      value: 19.098000000000003
+    - type: mrr_at_10
+      value: 25.397
+    - type: mrr_at_100
+      value: 26.246000000000002
+    - type: mrr_at_1000
+      value: 26.33
+    - type: mrr_at_3
+      value: 23.469
+    - type: mrr_at_5
+      value: 24.646
+    - type: ndcg_at_1
+      value: 19.098000000000003
+    - type: ndcg_at_10
+      value: 25.807999999999996
+    - type: ndcg_at_100
+      value: 30.445
+    - type: ndcg_at_1000
+      value: 33.666000000000004
+    - type: ndcg_at_3
+      value: 22.292
+    - type: ndcg_at_5
+      value: 24.075
+    - type: precision_at_1
+      value: 19.098000000000003
+    - type: precision_at_10
+      value: 4.58
+    - type: precision_at_100
+      value: 0.8099999999999999
+    - type: precision_at_1000
+      value: 0.126
+    - type: precision_at_3
+      value: 10.346
+    - type: precision_at_5
+      value: 7.542999999999999
+    - type: recall_at_1
+      value: 15.845999999999998
+    - type: recall_at_10
+      value: 34.172999999999995
+    - type: recall_at_100
+      value: 55.24099999999999
+    - type: recall_at_1000
+      value: 78.644
+    - type: recall_at_3
+      value: 24.401
+    - type: recall_at_5
+      value: 28.938000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.974
+    - type: map_at_10
+      value: 30.108
+    - type: map_at_100
+      value: 31.208000000000002
+    - type: map_at_1000
+      value: 31.330999999999996
+    - type: map_at_3
+      value: 27.889999999999997
+    - type: map_at_5
+      value: 29.023
+    - type: mrr_at_1
+      value: 26.493
+    - type: mrr_at_10
+      value: 33.726
+    - type: mrr_at_100
+      value: 34.622
+    - type: mrr_at_1000
+      value: 34.703
+    - type: mrr_at_3
+      value: 31.575999999999997
+    - type: mrr_at_5
+      value: 32.690999999999995
+    - type: ndcg_at_1
+      value: 26.493
+    - type: ndcg_at_10
+      value: 34.664
+    - type: ndcg_at_100
+      value: 39.725
+    - type: ndcg_at_1000
+      value: 42.648
+    - type: ndcg_at_3
+      value: 30.447999999999997
+    - type: ndcg_at_5
+      value: 32.145
+    - type: precision_at_1
+      value: 26.493
+    - type: precision_at_10
+      value: 5.7090000000000005
+    - type: precision_at_100
+      value: 0.9199999999999999
+    - type: precision_at_1000
+      value: 0.129
+    - type: precision_at_3
+      value: 13.464
+    - type: precision_at_5
+      value: 9.384
+    - type: recall_at_1
+      value: 22.974
+    - type: recall_at_10
+      value: 45.097
+    - type: recall_at_100
+      value: 66.908
+    - type: recall_at_1000
+      value: 87.495
+    - type: recall_at_3
+      value: 33.338
+    - type: recall_at_5
+      value: 37.499
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.408
+    - type: map_at_10
+      value: 29.580000000000002
+    - type: map_at_100
+      value: 31.145
+    - type: map_at_1000
+      value: 31.369000000000003
+    - type: map_at_3
+      value: 27.634999999999998
+    - type: map_at_5
+      value: 28.766000000000002
+    - type: mrr_at_1
+      value: 27.272999999999996
+    - type: mrr_at_10
+      value: 33.93
+    - type: mrr_at_100
+      value: 34.963
+    - type: mrr_at_1000
+      value: 35.031
+    - type: mrr_at_3
+      value: 32.016
+    - type: mrr_at_5
+      value: 33.221000000000004
+    - type: ndcg_at_1
+      value: 27.272999999999996
+    - type: ndcg_at_10
+      value: 33.993
+    - type: ndcg_at_100
+      value: 40.333999999999996
+    - type: ndcg_at_1000
+      value: 43.361
+    - type: ndcg_at_3
+      value: 30.918
+    - type: ndcg_at_5
+      value: 32.552
+    - type: precision_at_1
+      value: 27.272999999999996
+    - type: precision_at_10
+      value: 6.285
+    - type: precision_at_100
+      value: 1.389
+    - type: precision_at_1000
+      value: 0.232
+    - type: precision_at_3
+      value: 14.427000000000001
+    - type: precision_at_5
+      value: 10.356
+    - type: recall_at_1
+      value: 22.408
+    - type: recall_at_10
+      value: 41.318
+    - type: recall_at_100
+      value: 70.539
+    - type: recall_at_1000
+      value: 90.197
+    - type: recall_at_3
+      value: 32.513
+    - type: recall_at_5
+      value: 37.0
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.258000000000003
+    - type: map_at_10
+      value: 24.294
+    - type: map_at_100
+      value: 25.305
+    - type: map_at_1000
+      value: 25.419999999999998
+    - type: map_at_3
+      value: 22.326999999999998
+    - type: map_at_5
+      value: 23.31
+    - type: mrr_at_1
+      value: 18.484
+    - type: mrr_at_10
+      value: 25.863999999999997
+    - type: mrr_at_100
+      value: 26.766000000000002
+    - type: mrr_at_1000
+      value: 26.855
+    - type: mrr_at_3
+      value: 23.968
+    - type: mrr_at_5
+      value: 24.911
+    - type: ndcg_at_1
+      value: 18.484
+    - type: ndcg_at_10
+      value: 28.433000000000003
+    - type: ndcg_at_100
+      value: 33.405
+    - type: ndcg_at_1000
+      value: 36.375
+    - type: ndcg_at_3
+      value: 24.455
+    - type: ndcg_at_5
+      value: 26.031
+    - type: precision_at_1
+      value: 18.484
+    - type: precision_at_10
+      value: 4.603
+    - type: precision_at_100
+      value: 0.773
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 10.659
+    - type: precision_at_5
+      value: 7.505000000000001
+    - type: recall_at_1
+      value: 17.258000000000003
+    - type: recall_at_10
+      value: 39.589999999999996
+    - type: recall_at_100
+      value: 62.592000000000006
+    - type: recall_at_1000
+      value: 84.917
+    - type: recall_at_3
+      value: 28.706
+    - type: recall_at_5
+      value: 32.224000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 10.578999999999999
+    - type: map_at_10
+      value: 17.642
+    - type: map_at_100
+      value: 19.451
+    - type: map_at_1000
+      value: 19.647000000000002
+    - type: map_at_3
+      value: 14.618
+    - type: map_at_5
+      value: 16.145
+    - type: mrr_at_1
+      value: 23.322000000000003
+    - type: mrr_at_10
+      value: 34.204
+    - type: mrr_at_100
+      value: 35.185
+    - type: mrr_at_1000
+      value: 35.235
+    - type: mrr_at_3
+      value: 30.847
+    - type: mrr_at_5
+      value: 32.824
+    - type: ndcg_at_1
+      value: 23.322000000000003
+    - type: ndcg_at_10
+      value: 25.352999999999998
+    - type: ndcg_at_100
+      value: 32.574
+    - type: ndcg_at_1000
+      value: 36.073
+    - type: ndcg_at_3
+      value: 20.318
+    - type: ndcg_at_5
+      value: 22.111
+    - type: precision_at_1
+      value: 23.322000000000003
+    - type: precision_at_10
+      value: 8.02
+    - type: precision_at_100
+      value: 1.5730000000000002
+    - type: precision_at_1000
+      value: 0.22200000000000003
+    - type: precision_at_3
+      value: 15.049000000000001
+    - type: precision_at_5
+      value: 11.87
+    - type: recall_at_1
+      value: 10.578999999999999
+    - type: recall_at_10
+      value: 30.964999999999996
+    - type: recall_at_100
+      value: 55.986000000000004
+    - type: recall_at_1000
+      value: 75.565
+    - type: recall_at_3
+      value: 18.686
+    - type: recall_at_5
+      value: 23.629
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 7.327
+    - type: map_at_10
+      value: 14.904
+    - type: map_at_100
+      value: 20.29
+    - type: map_at_1000
+      value: 21.42
+    - type: map_at_3
+      value: 10.911
+    - type: map_at_5
+      value: 12.791
+    - type: mrr_at_1
+      value: 57.25
+    - type: mrr_at_10
+      value: 66.62700000000001
+    - type: mrr_at_100
+      value: 67.035
+    - type: mrr_at_1000
+      value: 67.052
+    - type: mrr_at_3
+      value: 64.833
+    - type: mrr_at_5
+      value: 65.908
+    - type: ndcg_at_1
+      value: 43.75
+    - type: ndcg_at_10
+      value: 32.246
+    - type: ndcg_at_100
+      value: 35.774
+    - type: ndcg_at_1000
+      value: 42.872
+    - type: ndcg_at_3
+      value: 36.64
+    - type: ndcg_at_5
+      value: 34.487
+    - type: precision_at_1
+      value: 57.25
+    - type: precision_at_10
+      value: 25.924999999999997
+    - type: precision_at_100
+      value: 7.670000000000001
+    - type: precision_at_1000
+      value: 1.599
+    - type: precision_at_3
+      value: 41.167
+    - type: precision_at_5
+      value: 34.65
+    - type: recall_at_1
+      value: 7.327
+    - type: recall_at_10
+      value: 19.625
+    - type: recall_at_100
+      value: 41.601
+    - type: recall_at_1000
+      value: 65.117
+    - type: recall_at_3
+      value: 12.308
+    - type: recall_at_5
+      value: 15.437999999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 44.53
+    - type: f1
+      value: 39.39884255816736
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 58.913000000000004
+    - type: map_at_10
+      value: 69.592
+    - type: map_at_100
+      value: 69.95599999999999
+    - type: map_at_1000
+      value: 69.973
+    - type: map_at_3
+      value: 67.716
+    - type: map_at_5
+      value: 68.899
+    - type: mrr_at_1
+      value: 63.561
+    - type: mrr_at_10
+      value: 74.2
+    - type: mrr_at_100
+      value: 74.468
+    - type: mrr_at_1000
+      value: 74.47500000000001
+    - type: mrr_at_3
+      value: 72.442
+    - type: mrr_at_5
+      value: 73.58
+    - type: ndcg_at_1
+      value: 63.561
+    - type: ndcg_at_10
+      value: 74.988
+    - type: ndcg_at_100
+      value: 76.52799999999999
+    - type: ndcg_at_1000
+      value: 76.88000000000001
+    - type: ndcg_at_3
+      value: 71.455
+    - type: ndcg_at_5
+      value: 73.42699999999999
+    - type: precision_at_1
+      value: 63.561
+    - type: precision_at_10
+      value: 9.547
+    - type: precision_at_100
+      value: 1.044
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 28.143
+    - type: precision_at_5
+      value: 18.008
+    - type: recall_at_1
+      value: 58.913000000000004
+    - type: recall_at_10
+      value: 87.18
+    - type: recall_at_100
+      value: 93.852
+    - type: recall_at_1000
+      value: 96.256
+    - type: recall_at_3
+      value: 77.55199999999999
+    - type: recall_at_5
+      value: 82.42399999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 11.761000000000001
+    - type: map_at_10
+      value: 19.564999999999998
+    - type: map_at_100
+      value: 21.099
+    - type: map_at_1000
+      value: 21.288999999999998
+    - type: map_at_3
+      value: 16.683999999999997
+    - type: map_at_5
+      value: 18.307000000000002
+    - type: mrr_at_1
+      value: 23.302
+    - type: mrr_at_10
+      value: 30.979
+    - type: mrr_at_100
+      value: 32.121
+    - type: mrr_at_1000
+      value: 32.186
+    - type: mrr_at_3
+      value: 28.549000000000003
+    - type: mrr_at_5
+      value: 30.038999999999998
+    - type: ndcg_at_1
+      value: 23.302
+    - type: ndcg_at_10
+      value: 25.592
+    - type: ndcg_at_100
+      value: 32.416
+    - type: ndcg_at_1000
+      value: 36.277
+    - type: ndcg_at_3
+      value: 22.151
+    - type: ndcg_at_5
+      value: 23.483999999999998
+    - type: precision_at_1
+      value: 23.302
+    - type: precision_at_10
+      value: 7.377000000000001
+    - type: precision_at_100
+      value: 1.415
+    - type: precision_at_1000
+      value: 0.212
+    - type: precision_at_3
+      value: 14.712
+    - type: precision_at_5
+      value: 11.358
+    - type: recall_at_1
+      value: 11.761000000000001
+    - type: recall_at_10
+      value: 31.696
+    - type: recall_at_100
+      value: 58.01500000000001
+    - type: recall_at_1000
+      value: 81.572
+    - type: recall_at_3
+      value: 20.742
+    - type: recall_at_5
+      value: 25.707
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.275
+    - type: map_at_10
+      value: 44.712
+    - type: map_at_100
+      value: 45.621
+    - type: map_at_1000
+      value: 45.698
+    - type: map_at_3
+      value: 42.016999999999996
+    - type: map_at_5
+      value: 43.659
+    - type: mrr_at_1
+      value: 64.551
+    - type: mrr_at_10
+      value: 71.58099999999999
+    - type: mrr_at_100
+      value: 71.952
+    - type: mrr_at_1000
+      value: 71.96900000000001
+    - type: mrr_at_3
+      value: 70.236
+    - type: mrr_at_5
+      value: 71.051
+    - type: ndcg_at_1
+      value: 64.551
+    - type: ndcg_at_10
+      value: 53.913999999999994
+    - type: ndcg_at_100
+      value: 57.421
+    - type: ndcg_at_1000
+      value: 59.06
+    - type: ndcg_at_3
+      value: 49.716
+    - type: ndcg_at_5
+      value: 51.971999999999994
+    - type: precision_at_1
+      value: 64.551
+    - type: precision_at_10
+      value: 11.110000000000001
+    - type: precision_at_100
+      value: 1.388
+    - type: precision_at_1000
+      value: 0.161
+    - type: precision_at_3
+      value: 30.822
+    - type: precision_at_5
+      value: 20.273
+    - type: recall_at_1
+      value: 32.275
+    - type: recall_at_10
+      value: 55.55
+    - type: recall_at_100
+      value: 69.38600000000001
+    - type: recall_at_1000
+      value: 80.35799999999999
+    - type: recall_at_3
+      value: 46.232
+    - type: recall_at_5
+      value: 50.682
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 76.4604
+    - type: ap
+      value: 70.40498168422701
+    - type: f1
+      value: 76.38572688476046
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.065999999999999
+    - type: map_at_10
+      value: 25.058000000000003
+    - type: map_at_100
+      value: 26.268
+    - type: map_at_1000
+      value: 26.344
+    - type: map_at_3
+      value: 21.626
+    - type: map_at_5
+      value: 23.513
+    - type: mrr_at_1
+      value: 15.501000000000001
+    - type: mrr_at_10
+      value: 25.548
+    - type: mrr_at_100
+      value: 26.723000000000003
+    - type: mrr_at_1000
+      value: 26.793
+    - type: mrr_at_3
+      value: 22.142
+    - type: mrr_at_5
+      value: 24.024
+    - type: ndcg_at_1
+      value: 15.501000000000001
+    - type: ndcg_at_10
+      value: 31.008000000000003
+    - type: ndcg_at_100
+      value: 37.08
+    - type: ndcg_at_1000
+      value: 39.102
+    - type: ndcg_at_3
+      value: 23.921999999999997
+    - type: ndcg_at_5
+      value: 27.307
+    - type: precision_at_1
+      value: 15.501000000000001
+    - type: precision_at_10
+      value: 5.155
+    - type: precision_at_100
+      value: 0.822
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 10.363
+    - type: precision_at_5
+      value: 7.917000000000001
+    - type: recall_at_1
+      value: 15.065999999999999
+    - type: recall_at_10
+      value: 49.507
+    - type: recall_at_100
+      value: 78.118
+    - type: recall_at_1000
+      value: 93.881
+    - type: recall_at_3
+      value: 30.075000000000003
+    - type: recall_at_5
+      value: 38.222
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 90.6703146374829
+    - type: f1
+      value: 90.1258004293966
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 68.29229366165072
+    - type: f1
+      value: 50.016194478997875
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 68.57767316745124
+    - type: f1
+      value: 67.16194062146954
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 73.92064559515804
+    - type: f1
+      value: 73.6680729569968
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 31.56335607367883
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 28.131807833734268
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 31.07390328719844
+    - type: mrr
+      value: 32.117370992867905
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.274
+    - type: map_at_10
+      value: 11.489
+    - type: map_at_100
+      value: 14.518
+    - type: map_at_1000
+      value: 15.914
+    - type: map_at_3
+      value: 8.399
+    - type: map_at_5
+      value: 9.889000000000001
+    - type: mrr_at_1
+      value: 42.724000000000004
+    - type: mrr_at_10
+      value: 51.486
+    - type: mrr_at_100
+      value: 51.941
+    - type: mrr_at_1000
+      value: 51.99
+    - type: mrr_at_3
+      value: 49.278
+    - type: mrr_at_5
+      value: 50.485
+    - type: ndcg_at_1
+      value: 39.938
+    - type: ndcg_at_10
+      value: 31.862000000000002
+    - type: ndcg_at_100
+      value: 29.235
+    - type: ndcg_at_1000
+      value: 37.802
+    - type: ndcg_at_3
+      value: 35.754999999999995
+    - type: ndcg_at_5
+      value: 34.447
+    - type: precision_at_1
+      value: 42.105
+    - type: precision_at_10
+      value: 23.901
+    - type: precision_at_100
+      value: 7.715
+    - type: precision_at_1000
+      value: 2.045
+    - type: precision_at_3
+      value: 33.437
+    - type: precision_at_5
+      value: 29.782999999999998
+    - type: recall_at_1
+      value: 5.274
+    - type: recall_at_10
+      value: 15.351
+    - type: recall_at_100
+      value: 29.791
+    - type: recall_at_1000
+      value: 60.722
+    - type: recall_at_3
+      value: 9.411
+    - type: recall_at_5
+      value: 12.171999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.099
+    - type: map_at_10
+      value: 27.913
+    - type: map_at_100
+      value: 29.281000000000002
+    - type: map_at_1000
+      value: 29.343999999999998
+    - type: map_at_3
+      value: 23.791
+    - type: map_at_5
+      value: 26.049
+    - type: mrr_at_1
+      value: 18.337
+    - type: mrr_at_10
+      value: 29.953999999999997
+    - type: mrr_at_100
+      value: 31.080999999999996
+    - type: mrr_at_1000
+      value: 31.130000000000003
+    - type: mrr_at_3
+      value: 26.168000000000003
+    - type: mrr_at_5
+      value: 28.277
+    - type: ndcg_at_1
+      value: 18.308
+    - type: ndcg_at_10
+      value: 34.938
+    - type: ndcg_at_100
+      value: 41.125
+    - type: ndcg_at_1000
+      value: 42.708
+    - type: ndcg_at_3
+      value: 26.805
+    - type: ndcg_at_5
+      value: 30.686999999999998
+    - type: precision_at_1
+      value: 18.308
+    - type: precision_at_10
+      value: 6.476999999999999
+    - type: precision_at_100
+      value: 0.9939999999999999
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 12.784999999999998
+    - type: precision_at_5
+      value: 9.878
+    - type: recall_at_1
+      value: 16.099
+    - type: recall_at_10
+      value: 54.63
+    - type: recall_at_100
+      value: 82.24900000000001
+    - type: recall_at_1000
+      value: 94.242
+    - type: recall_at_3
+      value: 33.174
+    - type: recall_at_5
+      value: 42.164
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 67.947
+    - type: map_at_10
+      value: 81.499
+    - type: map_at_100
+      value: 82.17
+    - type: map_at_1000
+      value: 82.194
+    - type: map_at_3
+      value: 78.567
+    - type: map_at_5
+      value: 80.34400000000001
+    - type: mrr_at_1
+      value: 78.18
+    - type: mrr_at_10
+      value: 85.05
+    - type: mrr_at_100
+      value: 85.179
+    - type: mrr_at_1000
+      value: 85.181
+    - type: mrr_at_3
+      value: 83.91
+    - type: mrr_at_5
+      value: 84.638
+    - type: ndcg_at_1
+      value: 78.2
+    - type: ndcg_at_10
+      value: 85.715
+    - type: ndcg_at_100
+      value: 87.2
+    - type: ndcg_at_1000
+      value: 87.39
+    - type: ndcg_at_3
+      value: 82.572
+    - type: ndcg_at_5
+      value: 84.176
+    - type: precision_at_1
+      value: 78.2
+    - type: precision_at_10
+      value: 12.973
+    - type: precision_at_100
+      value: 1.5010000000000001
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 35.949999999999996
+    - type: precision_at_5
+      value: 23.62
+    - type: recall_at_1
+      value: 67.947
+    - type: recall_at_10
+      value: 93.804
+    - type: recall_at_100
+      value: 98.971
+    - type: recall_at_1000
+      value: 99.91600000000001
+    - type: recall_at_3
+      value: 84.75399999999999
+    - type: recall_at_5
+      value: 89.32
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 45.457201684255104
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 55.162226937477875
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.173
+    - type: map_at_10
+      value: 10.463000000000001
+    - type: map_at_100
+      value: 12.278
+    - type: map_at_1000
+      value: 12.572
+    - type: map_at_3
+      value: 7.528
+    - type: map_at_5
+      value: 8.863
+    - type: mrr_at_1
+      value: 20.599999999999998
+    - type: mrr_at_10
+      value: 30.422
+    - type: mrr_at_100
+      value: 31.6
+    - type: mrr_at_1000
+      value: 31.663000000000004
+    - type: mrr_at_3
+      value: 27.400000000000002
+    - type: mrr_at_5
+      value: 29.065
+    - type: ndcg_at_1
+      value: 20.599999999999998
+    - type: ndcg_at_10
+      value: 17.687
+    - type: ndcg_at_100
+      value: 25.172
+    - type: ndcg_at_1000
+      value: 30.617
+    - type: ndcg_at_3
+      value: 16.81
+    - type: ndcg_at_5
+      value: 14.499
+    - type: precision_at_1
+      value: 20.599999999999998
+    - type: precision_at_10
+      value: 9.17
+    - type: precision_at_100
+      value: 2.004
+    - type: precision_at_1000
+      value: 0.332
+    - type: precision_at_3
+      value: 15.6
+    - type: precision_at_5
+      value: 12.58
+    - type: recall_at_1
+      value: 4.173
+    - type: recall_at_10
+      value: 18.575
+    - type: recall_at_100
+      value: 40.692
+    - type: recall_at_1000
+      value: 67.467
+    - type: recall_at_3
+      value: 9.488000000000001
+    - type: recall_at_5
+      value: 12.738
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.12603499315416
+    - type: cos_sim_spearman
+      value: 73.62060290948378
+    - type: euclidean_pearson
+      value: 78.14083565781135
+    - type: euclidean_spearman
+      value: 73.16840437541543
+    - type: manhattan_pearson
+      value: 77.92017261109734
+    - type: manhattan_spearman
+      value: 72.8805059949965
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.75955377133172
+    - type: cos_sim_spearman
+      value: 71.8872633964069
+    - type: euclidean_pearson
+      value: 76.31922068538256
+    - type: euclidean_spearman
+      value: 70.86449661855376
+    - type: manhattan_pearson
+      value: 76.47852229730407
+    - type: manhattan_spearman
+      value: 70.99367421984789
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.80762722908158
+    - type: cos_sim_spearman
+      value: 79.84588978756372
+    - type: euclidean_pearson
+      value: 79.8216849781164
+    - type: euclidean_spearman
+      value: 80.22647061695481
+    - type: manhattan_pearson
+      value: 79.56604194112572
+    - type: manhattan_spearman
+      value: 79.96495189862462
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.1012718092742
+    - type: cos_sim_spearman
+      value: 76.86011381793661
+    - type: euclidean_pearson
+      value: 79.94426039862019
+    - type: euclidean_spearman
+      value: 77.36751135465131
+    - type: manhattan_pearson
+      value: 79.87959373304288
+    - type: manhattan_spearman
+      value: 77.37717129004746
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.90618420346104
+    - type: cos_sim_spearman
+      value: 84.77290791243722
+    - type: euclidean_pearson
+      value: 84.64732258073293
+    - type: euclidean_spearman
+      value: 85.21053649543357
+    - type: manhattan_pearson
+      value: 84.61616883522647
+    - type: manhattan_spearman
+      value: 85.19803126766931
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.52192114059063
+    - type: cos_sim_spearman
+      value: 81.9103244827937
+    - type: euclidean_pearson
+      value: 80.99375176138985
+    - type: euclidean_spearman
+      value: 81.540250641079
+    - type: manhattan_pearson
+      value: 80.84979573396426
+    - type: manhattan_spearman
+      value: 81.3742591621492
+  - 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: 85.82166001234197
+    - type: cos_sim_spearman
+      value: 86.81857495659123
+    - type: euclidean_pearson
+      value: 85.72798403202849
+    - type: euclidean_spearman
+      value: 85.70482438950965
+    - type: manhattan_pearson
+      value: 85.51579093130357
+    - type: manhattan_spearman
+      value: 85.41233705379751
+  - 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: 64.48071151079803
+    - type: cos_sim_spearman
+      value: 65.37838108084044
+    - type: euclidean_pearson
+      value: 64.67378947096257
+    - type: euclidean_spearman
+      value: 65.39187147219869
+    - type: manhattan_pearson
+      value: 65.35487466133208
+    - type: manhattan_spearman
+      value: 65.51328499442272
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.64702367823314
+    - type: cos_sim_spearman
+      value: 82.49732953181818
+    - type: euclidean_pearson
+      value: 83.05996062475664
+    - type: euclidean_spearman
+      value: 82.28159546751176
+    - type: manhattan_pearson
+      value: 82.98305503664952
+    - type: manhattan_spearman
+      value: 82.18405771943928
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 78.5744649318696
+    - type: mrr
+      value: 93.35386291268645
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 52.093999999999994
+    - type: map_at_10
+      value: 61.646
+    - type: map_at_100
+      value: 62.197
+    - type: map_at_1000
+      value: 62.22800000000001
+    - type: map_at_3
+      value: 58.411
+    - type: map_at_5
+      value: 60.585
+    - type: mrr_at_1
+      value: 55.00000000000001
+    - type: mrr_at_10
+      value: 62.690999999999995
+    - type: mrr_at_100
+      value: 63.139
+    - type: mrr_at_1000
+      value: 63.166999999999994
+    - type: mrr_at_3
+      value: 60.111000000000004
+    - type: mrr_at_5
+      value: 61.778
+    - type: ndcg_at_1
+      value: 55.00000000000001
+    - type: ndcg_at_10
+      value: 66.271
+    - type: ndcg_at_100
+      value: 68.879
+    - type: ndcg_at_1000
+      value: 69.722
+    - type: ndcg_at_3
+      value: 60.672000000000004
+    - type: ndcg_at_5
+      value: 63.929
+    - type: precision_at_1
+      value: 55.00000000000001
+    - type: precision_at_10
+      value: 9.0
+    - type: precision_at_100
+      value: 1.043
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 23.555999999999997
+    - type: precision_at_5
+      value: 16.2
+    - type: recall_at_1
+      value: 52.093999999999994
+    - type: recall_at_10
+      value: 79.567
+    - type: recall_at_100
+      value: 91.60000000000001
+    - type: recall_at_1000
+      value: 98.333
+    - type: recall_at_3
+      value: 64.633
+    - type: recall_at_5
+      value: 72.68299999999999
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.83267326732673
+    - type: cos_sim_ap
+      value: 95.77995366495178
+    - type: cos_sim_f1
+      value: 91.51180311401306
+    - type: cos_sim_precision
+      value: 91.92734611503532
+    - type: cos_sim_recall
+      value: 91.10000000000001
+    - type: dot_accuracy
+      value: 99.63366336633663
+    - type: dot_ap
+      value: 88.53996286967461
+    - type: dot_f1
+      value: 81.06537530266343
+    - type: dot_precision
+      value: 78.59154929577464
+    - type: dot_recall
+      value: 83.7
+    - type: euclidean_accuracy
+      value: 99.82376237623762
+    - type: euclidean_ap
+      value: 95.53192209281187
+    - type: euclidean_f1
+      value: 91.19683481701286
+    - type: euclidean_precision
+      value: 90.21526418786692
+    - type: euclidean_recall
+      value: 92.2
+    - type: manhattan_accuracy
+      value: 99.82376237623762
+    - type: manhattan_ap
+      value: 95.55642082191741
+    - type: manhattan_f1
+      value: 91.16186693147964
+    - type: manhattan_precision
+      value: 90.53254437869822
+    - type: manhattan_recall
+      value: 91.8
+    - type: max_accuracy
+      value: 99.83267326732673
+    - type: max_ap
+      value: 95.77995366495178
+    - type: max_f1
+      value: 91.51180311401306
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 54.508462134213474
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 34.06549765184959
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 49.43129549466616
+    - type: mrr
+      value: 50.20613169510227
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.069516173193044
+    - type: cos_sim_spearman
+      value: 29.872498354017353
+    - type: dot_pearson
+      value: 28.80761257516063
+    - type: dot_spearman
+      value: 28.397422678527708
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.169
+    - type: map_at_10
+      value: 1.208
+    - type: map_at_100
+      value: 5.925
+    - type: map_at_1000
+      value: 14.427000000000001
+    - type: map_at_3
+      value: 0.457
+    - type: map_at_5
+      value: 0.716
+    - type: mrr_at_1
+      value: 64.0
+    - type: mrr_at_10
+      value: 74.075
+    - type: mrr_at_100
+      value: 74.303
+    - type: mrr_at_1000
+      value: 74.303
+    - type: mrr_at_3
+      value: 71.0
+    - type: mrr_at_5
+      value: 72.89999999999999
+    - type: ndcg_at_1
+      value: 57.99999999999999
+    - type: ndcg_at_10
+      value: 50.376
+    - type: ndcg_at_100
+      value: 38.582
+    - type: ndcg_at_1000
+      value: 35.663
+    - type: ndcg_at_3
+      value: 55.592
+    - type: ndcg_at_5
+      value: 53.647999999999996
+    - type: precision_at_1
+      value: 64.0
+    - type: precision_at_10
+      value: 53.2
+    - type: precision_at_100
+      value: 39.6
+    - type: precision_at_1000
+      value: 16.218
+    - type: precision_at_3
+      value: 59.333000000000006
+    - type: precision_at_5
+      value: 57.599999999999994
+    - type: recall_at_1
+      value: 0.169
+    - type: recall_at_10
+      value: 1.423
+    - type: recall_at_100
+      value: 9.049999999999999
+    - type: recall_at_1000
+      value: 34.056999999999995
+    - type: recall_at_3
+      value: 0.48700000000000004
+    - type: recall_at_5
+      value: 0.792
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.319
+    - type: map_at_10
+      value: 7.112
+    - type: map_at_100
+      value: 12.588
+    - type: map_at_1000
+      value: 14.056
+    - type: map_at_3
+      value: 2.8049999999999997
+    - type: map_at_5
+      value: 4.68
+    - type: mrr_at_1
+      value: 18.367
+    - type: mrr_at_10
+      value: 33.94
+    - type: mrr_at_100
+      value: 35.193000000000005
+    - type: mrr_at_1000
+      value: 35.193000000000005
+    - type: mrr_at_3
+      value: 29.932
+    - type: mrr_at_5
+      value: 32.279
+    - type: ndcg_at_1
+      value: 15.306000000000001
+    - type: ndcg_at_10
+      value: 18.096
+    - type: ndcg_at_100
+      value: 30.512
+    - type: ndcg_at_1000
+      value: 42.148
+    - type: ndcg_at_3
+      value: 17.034
+    - type: ndcg_at_5
+      value: 18.509
+    - type: precision_at_1
+      value: 18.367
+    - type: precision_at_10
+      value: 18.776
+    - type: precision_at_100
+      value: 7.02
+    - type: precision_at_1000
+      value: 1.467
+    - type: precision_at_3
+      value: 19.048000000000002
+    - type: precision_at_5
+      value: 22.041
+    - type: recall_at_1
+      value: 1.319
+    - type: recall_at_10
+      value: 13.748
+    - type: recall_at_100
+      value: 43.972
+    - type: recall_at_1000
+      value: 79.557
+    - type: recall_at_3
+      value: 4.042
+    - type: recall_at_5
+      value: 7.742
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.2282
+    - type: ap
+      value: 13.995763859570426
+    - type: f1
+      value: 54.08126256731344
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 57.64006791171477
+    - type: f1
+      value: 57.95841320748957
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 40.19267841788564
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.96614412588663
+    - type: cos_sim_ap
+      value: 67.75985678572738
+    - type: cos_sim_f1
+      value: 64.04661542276222
+    - type: cos_sim_precision
+      value: 60.406922357343305
+    - type: cos_sim_recall
+      value: 68.15303430079156
+    - type: dot_accuracy
+      value: 79.5732252488526
+    - type: dot_ap
+      value: 51.30562107572645
+    - type: dot_f1
+      value: 53.120759837177744
+    - type: dot_precision
+      value: 46.478037198258804
+    - type: dot_recall
+      value: 61.97889182058047
+    - type: euclidean_accuracy
+      value: 84.00786791440663
+    - type: euclidean_ap
+      value: 67.58930214486998
+    - type: euclidean_f1
+      value: 64.424821579775
+    - type: euclidean_precision
+      value: 59.4817958454322
+    - type: euclidean_recall
+      value: 70.26385224274406
+    - type: manhattan_accuracy
+      value: 83.87673600762949
+    - type: manhattan_ap
+      value: 67.4250981523309
+    - type: manhattan_f1
+      value: 64.10286658015808
+    - type: manhattan_precision
+      value: 57.96885001066781
+    - type: manhattan_recall
+      value: 71.68865435356201
+    - type: max_accuracy
+      value: 84.00786791440663
+    - type: max_ap
+      value: 67.75985678572738
+    - type: max_f1
+      value: 64.424821579775
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.41347459929368
+    - type: cos_sim_ap
+      value: 84.89261930113058
+    - type: cos_sim_f1
+      value: 77.13677607258877
+    - type: cos_sim_precision
+      value: 74.88581164358733
+    - type: cos_sim_recall
+      value: 79.52725592854944
+    - type: dot_accuracy
+      value: 86.32359219156285
+    - type: dot_ap
+      value: 79.29794992131094
+    - type: dot_f1
+      value: 72.84356337679777
+    - type: dot_precision
+      value: 67.31761478675462
+    - type: dot_recall
+      value: 79.35786880197105
+    - type: euclidean_accuracy
+      value: 88.33585593976791
+    - type: euclidean_ap
+      value: 84.73257641312746
+    - type: euclidean_f1
+      value: 76.83529582788195
+    - type: euclidean_precision
+      value: 72.76294052863436
+    - type: euclidean_recall
+      value: 81.3905143209116
+    - type: manhattan_accuracy
+      value: 88.3086894089339
+    - type: manhattan_ap
+      value: 84.66304891729399
+    - type: manhattan_f1
+      value: 76.8181650632165
+    - type: manhattan_precision
+      value: 73.6864436744219
+    - type: manhattan_recall
+      value: 80.22790267939637
+    - type: max_accuracy
+      value: 88.41347459929368
+    - type: max_ap
+      value: 84.89261930113058
+    - type: max_f1
+      value: 77.13677607258877
 ---
 
-# {MODEL_NAME}
+# bge-micro-v2
 
 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 -->
+Distilled in a 2-step training process (bge-micro was step 1) from `BAAI/bge-small-en-v1.5`.
 
 ## Usage (Sentence-Transformers)