Update README.md

README.md

@@ -1,11 +1,2515 @@
 ---
-pipeline_tag: sentence-similarity
 tags:
-- sentence-transformers
-- feature-extraction
-- sentence-similarity
-- transformers
-
+- mteb
+model-index:
+- name: ALL_862873
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 50.805970149253746
+    - type: ap
+      value: 21.350961103104364
+    - type: f1
+      value: 46.546166439875044
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 52.567125000000004
+    - type: ap
+      value: 51.37893936391345
+    - type: f1
+      value: 51.8411977908125
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 22.63
+    - type: f1
+      value: 21.964526516204575
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.991
+    - type: map_at_10
+      value: 4.095
+    - type: map_at_100
+      value: 4.763
+    - type: map_at_1000
+      value: 4.8759999999999994
+    - type: map_at_3
+      value: 3.3070000000000004
+    - type: map_at_5
+      value: 3.73
+    - type: mrr_at_1
+      value: 2.0629999999999997
+    - type: mrr_at_10
+      value: 4.119
+    - type: mrr_at_100
+      value: 4.787
+    - type: mrr_at_1000
+      value: 4.9
+    - type: mrr_at_3
+      value: 3.331
+    - type: mrr_at_5
+      value: 3.768
+    - type: ndcg_at_1
+      value: 1.991
+    - type: ndcg_at_10
+      value: 5.346
+    - type: ndcg_at_100
+      value: 9.181000000000001
+    - type: ndcg_at_1000
+      value: 13.004
+    - type: ndcg_at_3
+      value: 3.7199999999999998
+    - type: ndcg_at_5
+      value: 4.482
+    - type: precision_at_1
+      value: 1.991
+    - type: precision_at_10
+      value: 0.9390000000000001
+    - type: precision_at_100
+      value: 0.28700000000000003
+    - type: precision_at_1000
+      value: 0.061
+    - type: precision_at_3
+      value: 1.636
+    - type: precision_at_5
+      value: 1.351
+    - type: recall_at_1
+      value: 1.991
+    - type: recall_at_10
+      value: 9.388
+    - type: recall_at_100
+      value: 28.663
+    - type: recall_at_1000
+      value: 60.597
+    - type: recall_at_3
+      value: 4.9079999999999995
+    - type: recall_at_5
+      value: 6.757000000000001
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 14.790995349964428
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 12.248406292959412
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 44.88116875696166
+    - type: mrr
+      value: 56.07439651760981
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 19.26573437410263
+    - type: cos_sim_spearman
+      value: 21.34145013484056
+    - type: euclidean_pearson
+      value: 22.39226418475093
+    - type: euclidean_spearman
+      value: 23.511981519581447
+    - type: manhattan_pearson
+      value: 22.14346931904813
+    - type: manhattan_spearman
+      value: 23.39390654000631
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 36.42857142857143
+    - type: f1
+      value: 34.81640976406094
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 13.94296328377691
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 9.790764523161606
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.968
+    - type: map_at_10
+      value: 2.106
+    - type: map_at_100
+      value: 2.411
+    - type: map_at_1000
+      value: 2.4899999999999998
+    - type: map_at_3
+      value: 1.797
+    - type: map_at_5
+      value: 1.9959999999999998
+    - type: mrr_at_1
+      value: 1.717
+    - type: mrr_at_10
+      value: 3.0349999999999997
+    - type: mrr_at_100
+      value: 3.4029999999999996
+    - type: mrr_at_1000
+      value: 3.486
+    - type: mrr_at_3
+      value: 2.6470000000000002
+    - type: mrr_at_5
+      value: 2.876
+    - type: ndcg_at_1
+      value: 1.717
+    - type: ndcg_at_10
+      value: 2.9059999999999997
+    - type: ndcg_at_100
+      value: 4.715
+    - type: ndcg_at_1000
+      value: 7.318
+    - type: ndcg_at_3
+      value: 2.415
+    - type: ndcg_at_5
+      value: 2.682
+    - type: precision_at_1
+      value: 1.717
+    - type: precision_at_10
+      value: 0.658
+    - type: precision_at_100
+      value: 0.197
+    - type: precision_at_1000
+      value: 0.054
+    - type: precision_at_3
+      value: 1.431
+    - type: precision_at_5
+      value: 1.059
+    - type: recall_at_1
+      value: 0.968
+    - type: recall_at_10
+      value: 4.531000000000001
+    - type: recall_at_100
+      value: 13.081000000000001
+    - type: recall_at_1000
+      value: 32.443
+    - type: recall_at_3
+      value: 2.8850000000000002
+    - type: recall_at_5
+      value: 3.768
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.9390000000000001
+    - type: map_at_10
+      value: 1.516
+    - type: map_at_100
+      value: 1.6680000000000001
+    - type: map_at_1000
+      value: 1.701
+    - type: map_at_3
+      value: 1.314
+    - type: map_at_5
+      value: 1.388
+    - type: mrr_at_1
+      value: 1.146
+    - type: mrr_at_10
+      value: 1.96
+    - type: mrr_at_100
+      value: 2.166
+    - type: mrr_at_1000
+      value: 2.207
+    - type: mrr_at_3
+      value: 1.72
+    - type: mrr_at_5
+      value: 1.796
+    - type: ndcg_at_1
+      value: 1.146
+    - type: ndcg_at_10
+      value: 1.9769999999999999
+    - type: ndcg_at_100
+      value: 2.8400000000000003
+    - type: ndcg_at_1000
+      value: 4.035
+    - type: ndcg_at_3
+      value: 1.5859999999999999
+    - type: ndcg_at_5
+      value: 1.6709999999999998
+    - type: precision_at_1
+      value: 1.146
+    - type: precision_at_10
+      value: 0.43299999999999994
+    - type: precision_at_100
+      value: 0.11100000000000002
+    - type: precision_at_1000
+      value: 0.027999999999999997
+    - type: precision_at_3
+      value: 0.8699999999999999
+    - type: precision_at_5
+      value: 0.611
+    - type: recall_at_1
+      value: 0.9390000000000001
+    - type: recall_at_10
+      value: 2.949
+    - type: recall_at_100
+      value: 6.737
+    - type: recall_at_1000
+      value: 15.604999999999999
+    - type: recall_at_3
+      value: 1.846
+    - type: recall_at_5
+      value: 2.08
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.28
+    - type: map_at_10
+      value: 2.157
+    - type: map_at_100
+      value: 2.401
+    - type: map_at_1000
+      value: 2.4570000000000003
+    - type: map_at_3
+      value: 1.865
+    - type: map_at_5
+      value: 1.928
+    - type: mrr_at_1
+      value: 1.505
+    - type: mrr_at_10
+      value: 2.52
+    - type: mrr_at_100
+      value: 2.782
+    - type: mrr_at_1000
+      value: 2.8400000000000003
+    - type: mrr_at_3
+      value: 2.1839999999999997
+    - type: mrr_at_5
+      value: 2.2689999999999997
+    - type: ndcg_at_1
+      value: 1.505
+    - type: ndcg_at_10
+      value: 2.798
+    - type: ndcg_at_100
+      value: 4.2090000000000005
+    - type: ndcg_at_1000
+      value: 6.105
+    - type: ndcg_at_3
+      value: 2.157
+    - type: ndcg_at_5
+      value: 2.258
+    - type: precision_at_1
+      value: 1.505
+    - type: precision_at_10
+      value: 0.5519999999999999
+    - type: precision_at_100
+      value: 0.146
+    - type: precision_at_1000
+      value: 0.034999999999999996
+    - type: precision_at_3
+      value: 1.024
+    - type: precision_at_5
+      value: 0.7020000000000001
+    - type: recall_at_1
+      value: 1.28
+    - type: recall_at_10
+      value: 4.455
+    - type: recall_at_100
+      value: 11.169
+    - type: recall_at_1000
+      value: 26.046000000000003
+    - type: recall_at_3
+      value: 2.6270000000000002
+    - type: recall_at_5
+      value: 2.899
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.264
+    - type: map_at_10
+      value: 0.615
+    - type: map_at_100
+      value: 0.76
+    - type: map_at_1000
+      value: 0.803
+    - type: map_at_3
+      value: 0.40499999999999997
+    - type: map_at_5
+      value: 0.512
+    - type: mrr_at_1
+      value: 0.33899999999999997
+    - type: mrr_at_10
+      value: 0.718
+    - type: mrr_at_100
+      value: 0.8880000000000001
+    - type: mrr_at_1000
+      value: 0.935
+    - type: mrr_at_3
+      value: 0.508
+    - type: mrr_at_5
+      value: 0.616
+    - type: ndcg_at_1
+      value: 0.33899999999999997
+    - type: ndcg_at_10
+      value: 0.9079999999999999
+    - type: ndcg_at_100
+      value: 1.9029999999999998
+    - type: ndcg_at_1000
+      value: 3.4939999999999998
+    - type: ndcg_at_3
+      value: 0.46499999999999997
+    - type: ndcg_at_5
+      value: 0.655
+    - type: precision_at_1
+      value: 0.33899999999999997
+    - type: precision_at_10
+      value: 0.192
+    - type: precision_at_100
+      value: 0.079
+    - type: precision_at_1000
+      value: 0.023
+    - type: precision_at_3
+      value: 0.22599999999999998
+    - type: precision_at_5
+      value: 0.22599999999999998
+    - type: recall_at_1
+      value: 0.264
+    - type: recall_at_10
+      value: 1.789
+    - type: recall_at_100
+      value: 6.927
+    - type: recall_at_1000
+      value: 19.922
+    - type: recall_at_3
+      value: 0.5459999999999999
+    - type: recall_at_5
+      value: 0.9979999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.5599999999999999
+    - type: map_at_10
+      value: 0.9129999999999999
+    - type: map_at_100
+      value: 1.027
+    - type: map_at_1000
+      value: 1.072
+    - type: map_at_3
+      value: 0.715
+    - type: map_at_5
+      value: 0.826
+    - type: mrr_at_1
+      value: 0.8710000000000001
+    - type: mrr_at_10
+      value: 1.331
+    - type: mrr_at_100
+      value: 1.494
+    - type: mrr_at_1000
+      value: 1.547
+    - type: mrr_at_3
+      value: 1.119
+    - type: mrr_at_5
+      value: 1.269
+    - type: ndcg_at_1
+      value: 0.8710000000000001
+    - type: ndcg_at_10
+      value: 1.2590000000000001
+    - type: ndcg_at_100
+      value: 2.023
+    - type: ndcg_at_1000
+      value: 3.737
+    - type: ndcg_at_3
+      value: 0.8750000000000001
+    - type: ndcg_at_5
+      value: 1.079
+    - type: precision_at_1
+      value: 0.8710000000000001
+    - type: precision_at_10
+      value: 0.28600000000000003
+    - type: precision_at_100
+      value: 0.086
+    - type: precision_at_1000
+      value: 0.027999999999999997
+    - type: precision_at_3
+      value: 0.498
+    - type: precision_at_5
+      value: 0.42300000000000004
+    - type: recall_at_1
+      value: 0.5599999999999999
+    - type: recall_at_10
+      value: 1.907
+    - type: recall_at_100
+      value: 5.492
+    - type: recall_at_1000
+      value: 18.974
+    - type: recall_at_3
+      value: 0.943
+    - type: recall_at_5
+      value: 1.41
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.9720000000000002
+    - type: map_at_10
+      value: 2.968
+    - type: map_at_100
+      value: 3.2009999999999996
+    - type: map_at_1000
+      value: 3.2680000000000002
+    - type: map_at_3
+      value: 2.683
+    - type: map_at_5
+      value: 2.8369999999999997
+    - type: mrr_at_1
+      value: 2.406
+    - type: mrr_at_10
+      value: 3.567
+    - type: mrr_at_100
+      value: 3.884
+    - type: mrr_at_1000
+      value: 3.948
+    - type: mrr_at_3
+      value: 3.2239999999999998
+    - type: mrr_at_5
+      value: 3.383
+    - type: ndcg_at_1
+      value: 2.406
+    - type: ndcg_at_10
+      value: 3.63
+    - type: ndcg_at_100
+      value: 5.155
+    - type: ndcg_at_1000
+      value: 7.381
+    - type: ndcg_at_3
+      value: 3.078
+    - type: ndcg_at_5
+      value: 3.3070000000000004
+    - type: precision_at_1
+      value: 2.406
+    - type: precision_at_10
+      value: 0.635
+    - type: precision_at_100
+      value: 0.184
+    - type: precision_at_1000
+      value: 0.048
+    - type: precision_at_3
+      value: 1.4120000000000001
+    - type: precision_at_5
+      value: 1.001
+    - type: recall_at_1
+      value: 1.9720000000000002
+    - type: recall_at_10
+      value: 5.152
+    - type: recall_at_100
+      value: 12.173
+    - type: recall_at_1000
+      value: 28.811999999999998
+    - type: recall_at_3
+      value: 3.556
+    - type: recall_at_5
+      value: 4.181
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.346
+    - type: map_at_10
+      value: 0.619
+    - type: map_at_100
+      value: 0.743
+    - type: map_at_1000
+      value: 0.788
+    - type: map_at_3
+      value: 0.5369999999999999
+    - type: map_at_5
+      value: 0.551
+    - type: mrr_at_1
+      value: 0.571
+    - type: mrr_at_10
+      value: 1.0619999999999998
+    - type: mrr_at_100
+      value: 1.2109999999999999
+    - type: mrr_at_1000
+      value: 1.265
+    - type: mrr_at_3
+      value: 0.818
+    - type: mrr_at_5
+      value: 0.927
+    - type: ndcg_at_1
+      value: 0.571
+    - type: ndcg_at_10
+      value: 0.919
+    - type: ndcg_at_100
+      value: 1.688
+    - type: ndcg_at_1000
+      value: 3.3649999999999998
+    - type: ndcg_at_3
+      value: 0.6779999999999999
+    - type: ndcg_at_5
+      value: 0.7230000000000001
+    - type: precision_at_1
+      value: 0.571
+    - type: precision_at_10
+      value: 0.27399999999999997
+    - type: precision_at_100
+      value: 0.084
+    - type: precision_at_1000
+      value: 0.029
+    - type: precision_at_3
+      value: 0.381
+    - type: precision_at_5
+      value: 0.32
+    - type: recall_at_1
+      value: 0.346
+    - type: recall_at_10
+      value: 1.397
+    - type: recall_at_100
+      value: 5.079000000000001
+    - type: recall_at_1000
+      value: 18.060000000000002
+    - type: recall_at_3
+      value: 0.774
+    - type: recall_at_5
+      value: 0.8340000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.69
+    - type: map_at_10
+      value: 0.897
+    - type: map_at_100
+      value: 1.0030000000000001
+    - type: map_at_1000
+      value: 1.034
+    - type: map_at_3
+      value: 0.818
+    - type: map_at_5
+      value: 0.864
+    - type: mrr_at_1
+      value: 0.767
+    - type: mrr_at_10
+      value: 1.008
+    - type: mrr_at_100
+      value: 1.145
+    - type: mrr_at_1000
+      value: 1.183
+    - type: mrr_at_3
+      value: 0.895
+    - type: mrr_at_5
+      value: 0.9560000000000001
+    - type: ndcg_at_1
+      value: 0.767
+    - type: ndcg_at_10
+      value: 1.0739999999999998
+    - type: ndcg_at_100
+      value: 1.757
+    - type: ndcg_at_1000
+      value: 2.9090000000000003
+    - type: ndcg_at_3
+      value: 0.881
+    - type: ndcg_at_5
+      value: 0.9769999999999999
+    - type: precision_at_1
+      value: 0.767
+    - type: precision_at_10
+      value: 0.184
+    - type: precision_at_100
+      value: 0.06
+    - type: precision_at_1000
+      value: 0.018000000000000002
+    - type: precision_at_3
+      value: 0.358
+    - type: precision_at_5
+      value: 0.27599999999999997
+    - type: recall_at_1
+      value: 0.69
+    - type: recall_at_10
+      value: 1.508
+    - type: recall_at_100
+      value: 4.858
+    - type: recall_at_1000
+      value: 14.007
+    - type: recall_at_3
+      value: 0.997
+    - type: recall_at_5
+      value: 1.2269999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.338
+    - type: map_at_10
+      value: 0.661
+    - type: map_at_100
+      value: 0.7969999999999999
+    - type: map_at_1000
+      value: 0.8290000000000001
+    - type: map_at_3
+      value: 0.5559999999999999
+    - type: map_at_5
+      value: 0.5910000000000001
+    - type: mrr_at_1
+      value: 0.482
+    - type: mrr_at_10
+      value: 0.88
+    - type: mrr_at_100
+      value: 1.036
+    - type: mrr_at_1000
+      value: 1.075
+    - type: mrr_at_3
+      value: 0.74
+    - type: mrr_at_5
+      value: 0.779
+    - type: ndcg_at_1
+      value: 0.482
+    - type: ndcg_at_10
+      value: 0.924
+    - type: ndcg_at_100
+      value: 1.736
+    - type: ndcg_at_1000
+      value: 2.926
+    - type: ndcg_at_3
+      value: 0.677
+    - type: ndcg_at_5
+      value: 0.732
+    - type: precision_at_1
+      value: 0.482
+    - type: precision_at_10
+      value: 0.20600000000000002
+    - type: precision_at_100
+      value: 0.078
+    - type: precision_at_1000
+      value: 0.023
+    - type: precision_at_3
+      value: 0.367
+    - type: precision_at_5
+      value: 0.255
+    - type: recall_at_1
+      value: 0.338
+    - type: recall_at_10
+      value: 1.545
+    - type: recall_at_100
+      value: 5.38
+    - type: recall_at_1000
+      value: 14.609
+    - type: recall_at_3
+      value: 0.826
+    - type: recall_at_5
+      value: 0.975
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.8240000000000001
+    - type: map_at_10
+      value: 1.254
+    - type: map_at_100
+      value: 1.389
+    - type: map_at_1000
+      value: 1.419
+    - type: map_at_3
+      value: 1.158
+    - type: map_at_5
+      value: 1.189
+    - type: mrr_at_1
+      value: 0.9329999999999999
+    - type: mrr_at_10
+      value: 1.4200000000000002
+    - type: mrr_at_100
+      value: 1.59
+    - type: mrr_at_1000
+      value: 1.629
+    - type: mrr_at_3
+      value: 1.29
+    - type: mrr_at_5
+      value: 1.332
+    - type: ndcg_at_1
+      value: 0.9329999999999999
+    - type: ndcg_at_10
+      value: 1.53
+    - type: ndcg_at_100
+      value: 2.418
+    - type: ndcg_at_1000
+      value: 3.7310000000000003
+    - type: ndcg_at_3
+      value: 1.302
+    - type: ndcg_at_5
+      value: 1.363
+    - type: precision_at_1
+      value: 0.9329999999999999
+    - type: precision_at_10
+      value: 0.271
+    - type: precision_at_100
+      value: 0.083
+    - type: precision_at_1000
+      value: 0.024
+    - type: precision_at_3
+      value: 0.622
+    - type: precision_at_5
+      value: 0.41000000000000003
+    - type: recall_at_1
+      value: 0.8240000000000001
+    - type: recall_at_10
+      value: 2.1999999999999997
+    - type: recall_at_100
+      value: 6.584
+    - type: recall_at_1000
+      value: 17.068
+    - type: recall_at_3
+      value: 1.5859999999999999
+    - type: recall_at_5
+      value: 1.7260000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.404
+    - type: map_at_10
+      value: 0.788
+    - type: map_at_100
+      value: 0.9860000000000001
+    - type: map_at_1000
+      value: 1.04
+    - type: map_at_3
+      value: 0.676
+    - type: map_at_5
+      value: 0.733
+    - type: mrr_at_1
+      value: 0.5930000000000001
+    - type: mrr_at_10
+      value: 1.278
+    - type: mrr_at_100
+      value: 1.545
+    - type: mrr_at_1000
+      value: 1.599
+    - type: mrr_at_3
+      value: 1.054
+    - type: mrr_at_5
+      value: 1.192
+    - type: ndcg_at_1
+      value: 0.5930000000000001
+    - type: ndcg_at_10
+      value: 1.1280000000000001
+    - type: ndcg_at_100
+      value: 2.2689999999999997
+    - type: ndcg_at_1000
+      value: 4.274
+    - type: ndcg_at_3
+      value: 0.919
+    - type: ndcg_at_5
+      value: 1.038
+    - type: precision_at_1
+      value: 0.5930000000000001
+    - type: precision_at_10
+      value: 0.296
+    - type: precision_at_100
+      value: 0.152
+    - type: precision_at_1000
+      value: 0.05
+    - type: precision_at_3
+      value: 0.527
+    - type: precision_at_5
+      value: 0.47400000000000003
+    - type: recall_at_1
+      value: 0.404
+    - type: recall_at_10
+      value: 1.601
+    - type: recall_at_100
+      value: 6.885
+    - type: recall_at_1000
+      value: 22.356
+    - type: recall_at_3
+      value: 0.9490000000000001
+    - type: recall_at_5
+      value: 1.206
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.185
+    - type: map_at_10
+      value: 0.192
+    - type: map_at_100
+      value: 0.271
+    - type: map_at_1000
+      value: 0.307
+    - type: map_at_3
+      value: 0.185
+    - type: map_at_5
+      value: 0.185
+    - type: mrr_at_1
+      value: 0.185
+    - type: mrr_at_10
+      value: 0.20500000000000002
+    - type: mrr_at_100
+      value: 0.292
+    - type: mrr_at_1000
+      value: 0.331
+    - type: mrr_at_3
+      value: 0.185
+    - type: mrr_at_5
+      value: 0.185
+    - type: ndcg_at_1
+      value: 0.185
+    - type: ndcg_at_10
+      value: 0.211
+    - type: ndcg_at_100
+      value: 0.757
+    - type: ndcg_at_1000
+      value: 1.928
+    - type: ndcg_at_3
+      value: 0.185
+    - type: ndcg_at_5
+      value: 0.185
+    - type: precision_at_1
+      value: 0.185
+    - type: precision_at_10
+      value: 0.037
+    - type: precision_at_100
+      value: 0.039
+    - type: precision_at_1000
+      value: 0.015
+    - type: precision_at_3
+      value: 0.062
+    - type: precision_at_5
+      value: 0.037
+    - type: recall_at_1
+      value: 0.185
+    - type: recall_at_10
+      value: 0.246
+    - type: recall_at_100
+      value: 3.05
+    - type: recall_at_1000
+      value: 12.5
+    - type: recall_at_3
+      value: 0.185
+    - type: recall_at_5
+      value: 0.185
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.241
+    - type: map_at_10
+      value: 0.372
+    - type: map_at_100
+      value: 0.45999999999999996
+    - type: map_at_1000
+      value: 0.47600000000000003
+    - type: map_at_3
+      value: 0.33999999999999997
+    - type: map_at_5
+      value: 0.359
+    - type: mrr_at_1
+      value: 0.651
+    - type: mrr_at_10
+      value: 1.03
+    - type: mrr_at_100
+      value: 1.2489999999999999
+    - type: mrr_at_1000
+      value: 1.282
+    - type: mrr_at_3
+      value: 0.9450000000000001
+    - type: mrr_at_5
+      value: 1.0030000000000001
+    - type: ndcg_at_1
+      value: 0.651
+    - type: ndcg_at_10
+      value: 0.588
+    - type: ndcg_at_100
+      value: 1.2550000000000001
+    - type: ndcg_at_1000
+      value: 1.9040000000000001
+    - type: ndcg_at_3
+      value: 0.547
+    - type: ndcg_at_5
+      value: 0.549
+    - type: precision_at_1
+      value: 0.651
+    - type: precision_at_10
+      value: 0.182
+    - type: precision_at_100
+      value: 0.086
+    - type: precision_at_1000
+      value: 0.02
+    - type: precision_at_3
+      value: 0.434
+    - type: precision_at_5
+      value: 0.313
+    - type: recall_at_1
+      value: 0.241
+    - type: recall_at_10
+      value: 0.63
+    - type: recall_at_100
+      value: 3.1759999999999997
+    - type: recall_at_1000
+      value: 7.175
+    - type: recall_at_3
+      value: 0.46299999999999997
+    - type: recall_at_5
+      value: 0.543
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.04
+    - type: map_at_10
+      value: 0.089
+    - type: map_at_100
+      value: 0.133
+    - type: map_at_1000
+      value: 0.165
+    - type: map_at_3
+      value: 0.054
+    - type: map_at_5
+      value: 0.056999999999999995
+    - type: mrr_at_1
+      value: 0.75
+    - type: mrr_at_10
+      value: 1.4749999999999999
+    - type: mrr_at_100
+      value: 1.8010000000000002
+    - type: mrr_at_1000
+      value: 1.847
+    - type: mrr_at_3
+      value: 1.208
+    - type: mrr_at_5
+      value: 1.333
+    - type: ndcg_at_1
+      value: 0.625
+    - type: ndcg_at_10
+      value: 0.428
+    - type: ndcg_at_100
+      value: 0.705
+    - type: ndcg_at_1000
+      value: 1.564
+    - type: ndcg_at_3
+      value: 0.5369999999999999
+    - type: ndcg_at_5
+      value: 0.468
+    - type: precision_at_1
+      value: 0.75
+    - type: precision_at_10
+      value: 0.375
+    - type: precision_at_100
+      value: 0.27499999999999997
+    - type: precision_at_1000
+      value: 0.10300000000000001
+    - type: precision_at_3
+      value: 0.583
+    - type: precision_at_5
+      value: 0.5
+    - type: recall_at_1
+      value: 0.04
+    - type: recall_at_10
+      value: 0.385
+    - type: recall_at_100
+      value: 1.2670000000000001
+    - type: recall_at_1000
+      value: 4.522
+    - type: recall_at_3
+      value: 0.07100000000000001
+    - type: recall_at_5
+      value: 0.08099999999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 22.749999999999996
+    - type: f1
+      value: 19.335020165482693
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.257
+    - type: map_at_10
+      value: 0.416
+    - type: map_at_100
+      value: 0.451
+    - type: map_at_1000
+      value: 0.46499999999999997
+    - type: map_at_3
+      value: 0.37
+    - type: map_at_5
+      value: 0.386
+    - type: mrr_at_1
+      value: 0.27
+    - type: mrr_at_10
+      value: 0.44200000000000006
+    - type: mrr_at_100
+      value: 0.48
+    - type: mrr_at_1000
+      value: 0.49500000000000005
+    - type: mrr_at_3
+      value: 0.38999999999999996
+    - type: mrr_at_5
+      value: 0.411
+    - type: ndcg_at_1
+      value: 0.27
+    - type: ndcg_at_10
+      value: 0.51
+    - type: ndcg_at_100
+      value: 0.738
+    - type: ndcg_at_1000
+      value: 1.2630000000000001
+    - type: ndcg_at_3
+      value: 0.41000000000000003
+    - type: ndcg_at_5
+      value: 0.439
+    - type: precision_at_1
+      value: 0.27
+    - type: precision_at_10
+      value: 0.084
+    - type: precision_at_100
+      value: 0.021
+    - type: precision_at_1000
+      value: 0.006999999999999999
+    - type: precision_at_3
+      value: 0.17500000000000002
+    - type: precision_at_5
+      value: 0.123
+    - type: recall_at_1
+      value: 0.257
+    - type: recall_at_10
+      value: 0.786
+    - type: recall_at_100
+      value: 1.959
+    - type: recall_at_1000
+      value: 6.334
+    - type: recall_at_3
+      value: 0.49699999999999994
+    - type: recall_at_5
+      value: 0.5680000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.28900000000000003
+    - type: map_at_10
+      value: 0.475
+    - type: map_at_100
+      value: 0.559
+    - type: map_at_1000
+      value: 0.5930000000000001
+    - type: map_at_3
+      value: 0.38999999999999996
+    - type: map_at_5
+      value: 0.41700000000000004
+    - type: mrr_at_1
+      value: 0.772
+    - type: mrr_at_10
+      value: 1.107
+    - type: mrr_at_100
+      value: 1.269
+    - type: mrr_at_1000
+      value: 1.323
+    - type: mrr_at_3
+      value: 0.9520000000000001
+    - type: mrr_at_5
+      value: 1.0290000000000001
+    - type: ndcg_at_1
+      value: 0.772
+    - type: ndcg_at_10
+      value: 0.755
+    - type: ndcg_at_100
+      value: 1.256
+    - type: ndcg_at_1000
+      value: 2.55
+    - type: ndcg_at_3
+      value: 0.633
+    - type: ndcg_at_5
+      value: 0.639
+    - type: precision_at_1
+      value: 0.772
+    - type: precision_at_10
+      value: 0.262
+    - type: precision_at_100
+      value: 0.082
+    - type: precision_at_1000
+      value: 0.03
+    - type: precision_at_3
+      value: 0.46299999999999997
+    - type: precision_at_5
+      value: 0.33999999999999997
+    - type: recall_at_1
+      value: 0.28900000000000003
+    - type: recall_at_10
+      value: 0.976
+    - type: recall_at_100
+      value: 2.802
+    - type: recall_at_1000
+      value: 11.466
+    - type: recall_at_3
+      value: 0.54
+    - type: recall_at_5
+      value: 0.6479999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.257
+    - type: map_at_10
+      value: 0.395
+    - type: map_at_100
+      value: 0.436
+    - type: map_at_1000
+      value: 0.447
+    - type: map_at_3
+      value: 0.347
+    - type: map_at_5
+      value: 0.369
+    - type: mrr_at_1
+      value: 0.513
+    - type: mrr_at_10
+      value: 0.787
+    - type: mrr_at_100
+      value: 0.865
+    - type: mrr_at_1000
+      value: 0.8840000000000001
+    - type: mrr_at_3
+      value: 0.6930000000000001
+    - type: mrr_at_5
+      value: 0.738
+    - type: ndcg_at_1
+      value: 0.513
+    - type: ndcg_at_10
+      value: 0.587
+    - type: ndcg_at_100
+      value: 0.881
+    - type: ndcg_at_1000
+      value: 1.336
+    - type: ndcg_at_3
+      value: 0.46299999999999997
+    - type: ndcg_at_5
+      value: 0.511
+    - type: precision_at_1
+      value: 0.513
+    - type: precision_at_10
+      value: 0.151
+    - type: precision_at_100
+      value: 0.04
+    - type: precision_at_1000
+      value: 0.01
+    - type: precision_at_3
+      value: 0.311
+    - type: precision_at_5
+      value: 0.22399999999999998
+    - type: recall_at_1
+      value: 0.257
+    - type: recall_at_10
+      value: 0.756
+    - type: recall_at_100
+      value: 1.9849999999999999
+    - type: recall_at_1000
+      value: 5.111000000000001
+    - type: recall_at_3
+      value: 0.466
+    - type: recall_at_5
+      value: 0.5599999999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 50.76400000000001
+    - type: ap
+      value: 50.41569411130455
+    - type: f1
+      value: 50.14266303576945
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.14300000000000002
+    - type: map_at_10
+      value: 0.23700000000000002
+    - type: map_at_100
+      value: 0.27799999999999997
+    - type: map_at_1000
+      value: 0.291
+    - type: map_at_3
+      value: 0.197
+    - type: map_at_5
+      value: 0.215
+    - type: mrr_at_1
+      value: 0.14300000000000002
+    - type: mrr_at_10
+      value: 0.247
+    - type: mrr_at_100
+      value: 0.29
+    - type: mrr_at_1000
+      value: 0.303
+    - type: mrr_at_3
+      value: 0.201
+    - type: mrr_at_5
+      value: 0.219
+    - type: ndcg_at_1
+      value: 0.14300000000000002
+    - type: ndcg_at_10
+      value: 0.307
+    - type: ndcg_at_100
+      value: 0.5720000000000001
+    - type: ndcg_at_1000
+      value: 1.053
+    - type: ndcg_at_3
+      value: 0.215
+    - type: ndcg_at_5
+      value: 0.248
+    - type: precision_at_1
+      value: 0.14300000000000002
+    - type: precision_at_10
+      value: 0.056999999999999995
+    - type: precision_at_100
+      value: 0.02
+    - type: precision_at_1000
+      value: 0.006
+    - type: precision_at_3
+      value: 0.091
+    - type: precision_at_5
+      value: 0.07200000000000001
+    - type: recall_at_1
+      value: 0.14300000000000002
+    - type: recall_at_10
+      value: 0.522
+    - type: recall_at_100
+      value: 1.9009999999999998
+    - type: recall_at_1000
+      value: 5.893000000000001
+    - type: recall_at_3
+      value: 0.263
+    - type: recall_at_5
+      value: 0.34099999999999997
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 61.03283173734611
+    - type: f1
+      value: 61.24012492746259
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 29.68308253533972
+    - type: f1
+      value: 16.243459114946905
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 34.330867518493605
+    - type: f1
+      value: 33.176158044175935
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 44.13248150638871
+    - type: f1
+      value: 44.24904249078732
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 15.698400177259078
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 14.888797785310235
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 25.652445385382126
+    - type: mrr
+      value: 25.891573325600227
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.322
+    - type: map_at_10
+      value: 0.7230000000000001
+    - type: map_at_100
+      value: 1.248
+    - type: map_at_1000
+      value: 1.873
+    - type: map_at_3
+      value: 0.479
+    - type: map_at_5
+      value: 0.5700000000000001
+    - type: mrr_at_1
+      value: 6.502
+    - type: mrr_at_10
+      value: 10.735
+    - type: mrr_at_100
+      value: 11.848
+    - type: mrr_at_1000
+      value: 11.995000000000001
+    - type: mrr_at_3
+      value: 9.391
+    - type: mrr_at_5
+      value: 9.732000000000001
+    - type: ndcg_at_1
+      value: 6.037
+    - type: ndcg_at_10
+      value: 4.873
+    - type: ndcg_at_100
+      value: 5.959
+    - type: ndcg_at_1000
+      value: 14.424000000000001
+    - type: ndcg_at_3
+      value: 5.4559999999999995
+    - type: ndcg_at_5
+      value: 5.074
+    - type: precision_at_1
+      value: 6.192
+    - type: precision_at_10
+      value: 4.458
+    - type: precision_at_100
+      value: 2.5700000000000003
+    - type: precision_at_1000
+      value: 1.3679999999999999
+    - type: precision_at_3
+      value: 5.676
+    - type: precision_at_5
+      value: 4.954
+    - type: recall_at_1
+      value: 0.322
+    - type: recall_at_10
+      value: 1.545
+    - type: recall_at_100
+      value: 8.301
+    - type: recall_at_1000
+      value: 37.294
+    - type: recall_at_3
+      value: 0.623
+    - type: recall_at_5
+      value: 0.865
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.188
+    - type: map_at_10
+      value: 0.27
+    - type: map_at_100
+      value: 0.322
+    - type: map_at_1000
+      value: 0.335
+    - type: map_at_3
+      value: 0.246
+    - type: map_at_5
+      value: 0.246
+    - type: mrr_at_1
+      value: 0.203
+    - type: mrr_at_10
+      value: 0.28300000000000003
+    - type: mrr_at_100
+      value: 0.344
+    - type: mrr_at_1000
+      value: 0.357
+    - type: mrr_at_3
+      value: 0.261
+    - type: mrr_at_5
+      value: 0.261
+    - type: ndcg_at_1
+      value: 0.203
+    - type: ndcg_at_10
+      value: 0.329
+    - type: ndcg_at_100
+      value: 0.628
+    - type: ndcg_at_1000
+      value: 1.0959999999999999
+    - type: ndcg_at_3
+      value: 0.272
+    - type: ndcg_at_5
+      value: 0.272
+    - type: precision_at_1
+      value: 0.203
+    - type: precision_at_10
+      value: 0.055
+    - type: precision_at_100
+      value: 0.024
+    - type: precision_at_1000
+      value: 0.006999999999999999
+    - type: precision_at_3
+      value: 0.116
+    - type: precision_at_5
+      value: 0.06999999999999999
+    - type: recall_at_1
+      value: 0.188
+    - type: recall_at_10
+      value: 0.507
+    - type: recall_at_100
+      value: 1.883
+    - type: recall_at_1000
+      value: 5.609999999999999
+    - type: recall_at_3
+      value: 0.333
+    - type: recall_at_5
+      value: 0.333
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.016000000000002
+    - type: map_at_10
+      value: 28.977999999999998
+    - type: map_at_100
+      value: 29.579
+    - type: map_at_1000
+      value: 29.648999999999997
+    - type: map_at_3
+      value: 27.673
+    - type: map_at_5
+      value: 28.427000000000003
+    - type: mrr_at_1
+      value: 27.93
+    - type: mrr_at_10
+      value: 32.462999999999994
+    - type: mrr_at_100
+      value: 32.993
+    - type: mrr_at_1000
+      value: 33.044000000000004
+    - type: mrr_at_3
+      value: 31.252000000000002
+    - type: mrr_at_5
+      value: 31.968999999999998
+    - type: ndcg_at_1
+      value: 27.96
+    - type: ndcg_at_10
+      value: 31.954
+    - type: ndcg_at_100
+      value: 34.882000000000005
+    - type: ndcg_at_1000
+      value: 36.751
+    - type: ndcg_at_3
+      value: 29.767
+    - type: ndcg_at_5
+      value: 30.816
+    - type: precision_at_1
+      value: 27.96
+    - type: precision_at_10
+      value: 4.826
+    - type: precision_at_100
+      value: 0.697
+    - type: precision_at_1000
+      value: 0.093
+    - type: precision_at_3
+      value: 12.837000000000002
+    - type: precision_at_5
+      value: 8.559999999999999
+    - type: recall_at_1
+      value: 24.016000000000002
+    - type: recall_at_10
+      value: 37.574999999999996
+    - type: recall_at_100
+      value: 50.843
+    - type: recall_at_1000
+      value: 64.654
+    - type: recall_at_3
+      value: 31.182
+    - type: recall_at_5
+      value: 34.055
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 18.38048892083281
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 27.103011764141478
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.18
+    - type: map_at_10
+      value: 0.457
+    - type: map_at_100
+      value: 0.634
+    - type: map_at_1000
+      value: 0.7000000000000001
+    - type: map_at_3
+      value: 0.333
+    - type: map_at_5
+      value: 0.387
+    - type: mrr_at_1
+      value: 0.8999999999999999
+    - type: mrr_at_10
+      value: 1.967
+    - type: mrr_at_100
+      value: 2.396
+    - type: mrr_at_1000
+      value: 2.495
+    - type: mrr_at_3
+      value: 1.567
+    - type: mrr_at_5
+      value: 1.7670000000000001
+    - type: ndcg_at_1
+      value: 0.8999999999999999
+    - type: ndcg_at_10
+      value: 1.022
+    - type: ndcg_at_100
+      value: 2.366
+    - type: ndcg_at_1000
+      value: 4.689
+    - type: ndcg_at_3
+      value: 0.882
+    - type: ndcg_at_5
+      value: 0.7929999999999999
+    - type: precision_at_1
+      value: 0.8999999999999999
+    - type: precision_at_10
+      value: 0.58
+    - type: precision_at_100
+      value: 0.263
+    - type: precision_at_1000
+      value: 0.084
+    - type: precision_at_3
+      value: 0.8999999999999999
+    - type: precision_at_5
+      value: 0.74
+    - type: recall_at_1
+      value: 0.18
+    - type: recall_at_10
+      value: 1.208
+    - type: recall_at_100
+      value: 5.373
+    - type: recall_at_1000
+      value: 17.112
+    - type: recall_at_3
+      value: 0.5579999999999999
+    - type: recall_at_5
+      value: 0.7779999999999999
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 55.229896309578905
+    - type: cos_sim_spearman
+      value: 48.54616726085393
+    - type: euclidean_pearson
+      value: 53.828130644322
+    - type: euclidean_spearman
+      value: 48.2907441223958
+    - type: manhattan_pearson
+      value: 53.72684612327582
+    - type: manhattan_spearman
+      value: 48.228319721712744
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 57.73555535277214
+    - type: cos_sim_spearman
+      value: 55.58790083939622
+    - type: euclidean_pearson
+      value: 61.009463373795384
+    - type: euclidean_spearman
+      value: 56.696846101196044
+    - type: manhattan_pearson
+      value: 60.875111392597894
+    - type: manhattan_spearman
+      value: 56.63100766160946
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 19.47269635955134
+    - type: cos_sim_spearman
+      value: 18.35951746300603
+    - type: euclidean_pearson
+      value: 23.130707248318714
+    - type: euclidean_spearman
+      value: 22.92241668287248
+    - type: manhattan_pearson
+      value: 22.99371642148021
+    - type: manhattan_spearman
+      value: 22.770233678121897
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.78346805351368
+    - type: cos_sim_spearman
+      value: 28.84281669682782
+    - type: euclidean_pearson
+      value: 34.508176962091156
+    - type: euclidean_spearman
+      value: 32.269242265609975
+    - type: manhattan_pearson
+      value: 34.41366600914297
+    - type: manhattan_spearman
+      value: 32.15352239729175
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 29.550332218260465
+    - type: cos_sim_spearman
+      value: 29.188654452524528
+    - type: euclidean_pearson
+      value: 33.80339596511417
+    - type: euclidean_spearman
+      value: 33.49607278843874
+    - type: manhattan_pearson
+      value: 33.589427741967334
+    - type: manhattan_spearman
+      value: 33.288312003652884
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 27.163752699585885
+    - type: cos_sim_spearman
+      value: 39.0544187582685
+    - type: euclidean_pearson
+      value: 38.93841642732113
+    - type: euclidean_spearman
+      value: 42.861814968921294
+    - type: manhattan_pearson
+      value: 38.78821319739337
+    - type: manhattan_spearman
+      value: 42.757121435678954
+  - 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: 57.15429605615292
+    - type: cos_sim_spearman
+      value: 61.21576579300284
+    - type: euclidean_pearson
+      value: 59.2835939062064
+    - type: euclidean_spearman
+      value: 60.902713241808236
+    - type: manhattan_pearson
+      value: 59.510770285546364
+    - type: manhattan_spearman
+      value: 61.02979474159327
+  - 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: 41.81726547830133
+    - type: cos_sim_spearman
+      value: 44.45123398124273
+    - type: euclidean_pearson
+      value: 46.44144033159064
+    - type: euclidean_spearman
+      value: 46.61348337508052
+    - type: manhattan_pearson
+      value: 46.48092744041165
+    - type: manhattan_spearman
+      value: 46.78049599791891
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 46.085942179295465
+    - type: cos_sim_spearman
+      value: 44.394736992467365
+    - type: euclidean_pearson
+      value: 47.06981069147408
+    - type: euclidean_spearman
+      value: 45.40499474054004
+    - type: manhattan_pearson
+      value: 46.96497631950794
+    - type: manhattan_spearman
+      value: 45.31936619298336
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 43.89526517578129
+    - type: mrr
+      value: 64.30753070458954
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.417
+    - type: map_at_10
+      value: 2.189
+    - type: map_at_100
+      value: 2.5669999999999997
+    - type: map_at_1000
+      value: 2.662
+    - type: map_at_3
+      value: 1.694
+    - type: map_at_5
+      value: 1.928
+    - type: mrr_at_1
+      value: 1.667
+    - type: mrr_at_10
+      value: 2.4899999999999998
+    - type: mrr_at_100
+      value: 2.8400000000000003
+    - type: mrr_at_1000
+      value: 2.928
+    - type: mrr_at_3
+      value: 1.944
+    - type: mrr_at_5
+      value: 2.178
+    - type: ndcg_at_1
+      value: 1.667
+    - type: ndcg_at_10
+      value: 2.913
+    - type: ndcg_at_100
+      value: 5.482
+    - type: ndcg_at_1000
+      value: 8.731
+    - type: ndcg_at_3
+      value: 1.867
+    - type: ndcg_at_5
+      value: 2.257
+    - type: precision_at_1
+      value: 1.667
+    - type: precision_at_10
+      value: 0.567
+    - type: precision_at_100
+      value: 0.213
+    - type: precision_at_1000
+      value: 0.053
+    - type: precision_at_3
+      value: 0.7779999999999999
+    - type: precision_at_5
+      value: 0.6669999999999999
+    - type: recall_at_1
+      value: 1.417
+    - type: recall_at_10
+      value: 5.028
+    - type: recall_at_100
+      value: 18.5
+    - type: recall_at_1000
+      value: 45.072
+    - type: recall_at_3
+      value: 2.083
+    - type: recall_at_5
+      value: 3.083
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.02871287128713
+    - type: cos_sim_ap
+      value: 17.404404071912694
+    - type: cos_sim_f1
+      value: 25.89285714285714
+    - type: cos_sim_precision
+      value: 29.292929292929294
+    - type: cos_sim_recall
+      value: 23.200000000000003
+    - type: dot_accuracy
+      value: 99.0118811881188
+    - type: dot_ap
+      value: 5.4739000785007335
+    - type: dot_f1
+      value: 12.178702570379436
+    - type: dot_precision
+      value: 8.774250440917108
+    - type: dot_recall
+      value: 19.900000000000002
+    - type: euclidean_accuracy
+      value: 99.03663366336633
+    - type: euclidean_ap
+      value: 19.20851069839796
+    - type: euclidean_f1
+      value: 27.16555612506407
+    - type: euclidean_precision
+      value: 27.865404837013667
+    - type: euclidean_recall
+      value: 26.5
+    - type: manhattan_accuracy
+      value: 99.03663366336633
+    - type: manhattan_ap
+      value: 19.12862913626528
+    - type: manhattan_f1
+      value: 26.96629213483146
+    - type: manhattan_precision
+      value: 28.99884925201381
+    - type: manhattan_recall
+      value: 25.2
+    - type: max_accuracy
+      value: 99.03663366336633
+    - type: max_ap
+      value: 19.20851069839796
+    - type: max_f1
+      value: 27.16555612506407
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 23.657118721775905
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 27.343558395037043
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 23.346327148080043
+    - type: mrr
+      value: 21.99097063067651
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.032
+    - type: map_at_10
+      value: 0.157
+    - type: map_at_100
+      value: 0.583
+    - type: map_at_1000
+      value: 1.48
+    - type: map_at_3
+      value: 0.066
+    - type: map_at_5
+      value: 0.105
+    - type: mrr_at_1
+      value: 10.0
+    - type: mrr_at_10
+      value: 16.99
+    - type: mrr_at_100
+      value: 18.284
+    - type: mrr_at_1000
+      value: 18.394
+    - type: mrr_at_3
+      value: 14.000000000000002
+    - type: mrr_at_5
+      value: 15.8
+    - type: ndcg_at_1
+      value: 8.0
+    - type: ndcg_at_10
+      value: 7.504
+    - type: ndcg_at_100
+      value: 5.339
+    - type: ndcg_at_1000
+      value: 6.046
+    - type: ndcg_at_3
+      value: 8.358
+    - type: ndcg_at_5
+      value: 8.142000000000001
+    - type: precision_at_1
+      value: 10.0
+    - type: precision_at_10
+      value: 8.6
+    - type: precision_at_100
+      value: 5.9799999999999995
+    - type: precision_at_1000
+      value: 2.976
+    - type: precision_at_3
+      value: 9.333
+    - type: precision_at_5
+      value: 9.2
+    - type: recall_at_1
+      value: 0.032
+    - type: recall_at_10
+      value: 0.252
+    - type: recall_at_100
+      value: 1.529
+    - type: recall_at_1000
+      value: 6.364
+    - type: recall_at_3
+      value: 0.08499999999999999
+    - type: recall_at_5
+      value: 0.154
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.44200000000000006
+    - type: map_at_10
+      value: 0.996
+    - type: map_at_100
+      value: 1.317
+    - type: map_at_1000
+      value: 1.624
+    - type: map_at_3
+      value: 0.736
+    - type: map_at_5
+      value: 0.951
+    - type: mrr_at_1
+      value: 4.082
+    - type: mrr_at_10
+      value: 10.102
+    - type: mrr_at_100
+      value: 10.978
+    - type: mrr_at_1000
+      value: 11.1
+    - type: mrr_at_3
+      value: 7.8229999999999995
+    - type: mrr_at_5
+      value: 9.252
+    - type: ndcg_at_1
+      value: 4.082
+    - type: ndcg_at_10
+      value: 3.821
+    - type: ndcg_at_100
+      value: 5.682
+    - type: ndcg_at_1000
+      value: 10.96
+    - type: ndcg_at_3
+      value: 4.813
+    - type: ndcg_at_5
+      value: 4.757
+    - type: precision_at_1
+      value: 4.082
+    - type: precision_at_10
+      value: 3.061
+    - type: precision_at_100
+      value: 1.367
+    - type: precision_at_1000
+      value: 0.46299999999999997
+    - type: precision_at_3
+      value: 4.7620000000000005
+    - type: precision_at_5
+      value: 4.898000000000001
+    - type: recall_at_1
+      value: 0.44200000000000006
+    - type: recall_at_10
+      value: 2.059
+    - type: recall_at_100
+      value: 7.439
+    - type: recall_at_1000
+      value: 25.191000000000003
+    - type: recall_at_3
+      value: 1.095
+    - type: recall_at_5
+      value: 1.725
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 54.925999999999995
+    - type: ap
+      value: 9.658236434063275
+    - type: f1
+      value: 43.469829154993064
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 40.7498585172609
+    - type: f1
+      value: 40.720120106546574
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 20.165152514024733
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 77.59432556476128
+    - type: cos_sim_ap
+      value: 30.37846072188074
+    - type: cos_sim_f1
+      value: 37.9231242656521
+    - type: cos_sim_precision
+      value: 24.064474898814172
+    - type: cos_sim_recall
+      value: 89.41952506596306
+    - type: dot_accuracy
+      value: 77.42146986946415
+    - type: dot_ap
+      value: 24.073476661930034
+    - type: dot_f1
+      value: 37.710580857735025
+    - type: dot_precision
+      value: 23.61083383243495
+    - type: dot_recall
+      value: 93.61477572559367
+    - type: euclidean_accuracy
+      value: 77.64797043571556
+    - type: euclidean_ap
+      value: 31.892152386237594
+    - type: euclidean_f1
+      value: 38.21154759481647
+    - type: euclidean_precision
+      value: 25.719243766554023
+    - type: euclidean_recall
+      value: 74.30079155672823
+    - type: manhattan_accuracy
+      value: 77.6539309769327
+    - type: manhattan_ap
+      value: 31.89545356309865
+    - type: manhattan_f1
+      value: 38.16428166172855
+    - type: manhattan_precision
+      value: 25.07247577238466
+    - type: manhattan_recall
+      value: 79.86807387862797
+    - type: max_accuracy
+      value: 77.6539309769327
+    - type: max_ap
+      value: 31.89545356309865
+    - type: max_f1
+      value: 38.21154759481647
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 76.56886715566422
+    - type: cos_sim_ap
+      value: 44.04480929059786
+    - type: cos_sim_f1
+      value: 43.73100054674686
+    - type: cos_sim_precision
+      value: 30.540367168647098
+    - type: cos_sim_recall
+      value: 76.97874961502926
+    - type: dot_accuracy
+      value: 74.80110218496526
+    - type: dot_ap
+      value: 26.487746384962758
+    - type: dot_f1
+      value: 40.91940608182585
+    - type: dot_precision
+      value: 25.9157358738502
+    - type: dot_recall
+      value: 97.18201416692331
+    - type: euclidean_accuracy
+      value: 76.97054371870998
+    - type: euclidean_ap
+      value: 47.079120397438416
+    - type: euclidean_f1
+      value: 45.866182572614115
+    - type: euclidean_precision
+      value: 34.580791490692945
+    - type: euclidean_recall
+      value: 68.0859254696643
+    - type: manhattan_accuracy
+      value: 76.96084138626927
+    - type: manhattan_ap
+      value: 47.168701873575976
+    - type: manhattan_f1
+      value: 45.985439966237614
+    - type: manhattan_precision
+      value: 34.974321938693635
+    - type: manhattan_recall
+      value: 67.11579919926086
+    - type: max_accuracy
+      value: 76.97054371870998
+    - type: max_ap
+      value: 47.168701873575976
+    - type: max_f1
+      value: 45.985439966237614
 ---
 
 # {MODEL_NAME}