Add MTEB metadata

README.md

@@ -4,6 +4,7 @@ tags:
 - sentence-transformers
 - feature-extraction
 - sentence-similarity
+- mteb
 language: en
 license: apache-2.0
 datasets:
@@ -28,7 +29,2749 @@ datasets:
 - embedding-data/SPECTER
 - embedding-data/PAQ_pairs
 - embedding-data/WikiAnswers
-
+model-index:
+- name: all-MiniLM-L6-v2
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 64.14925373134331
+    - type: ap
+      value: 27.237875815186907
+    - type: f1
+      value: 58.03105716318715
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 62.582975
+    - type: ap
+      value: 58.26562634146188
+    - type: f1
+      value: 62.304673961004156
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 31.785999999999998
+    - type: f1
+      value: 31.40726949960717
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 25.605
+    - type: map_at_10
+      value: 41.165
+    - type: map_at_100
+      value: 42.230000000000004
+    - type: map_at_1000
+      value: 42.241
+    - type: map_at_3
+      value: 35.965
+    - type: map_at_5
+      value: 38.981
+    - type: ndcg_at_1
+      value: 25.605
+    - type: ndcg_at_10
+      value: 50.166999999999994
+    - type: ndcg_at_100
+      value: 54.534000000000006
+    - type: ndcg_at_1000
+      value: 54.772
+    - type: ndcg_at_3
+      value: 39.434000000000005
+    - type: ndcg_at_5
+      value: 44.876
+    - type: precision_at_1
+      value: 25.605
+    - type: precision_at_10
+      value: 7.908999999999999
+    - type: precision_at_100
+      value: 0.9769999999999999
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 16.500999999999998
+    - type: precision_at_5
+      value: 12.546
+    - type: recall_at_1
+      value: 25.605
+    - type: recall_at_10
+      value: 79.09
+    - type: recall_at_100
+      value: 97.724
+    - type: recall_at_1000
+      value: 99.502
+    - type: recall_at_3
+      value: 49.502
+    - type: recall_at_5
+      value: 62.731
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 46.54595079050156
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 37.85709823840442
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 63.47681681237331
+    - type: mrr
+      value: 77.08657608934617
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.41897516342782
+    - type: cos_sim_spearman
+      value: 81.64041444909368
+    - type: euclidean_pearson
+      value: 82.67500318274435
+    - type: euclidean_spearman
+      value: 81.64041444909368
+    - type: manhattan_pearson
+      value: 82.35165974372227
+    - type: manhattan_spearman
+      value: 81.50968857884978
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 79.75000000000001
+    - type: f1
+      value: 78.92604185699534
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 38.48301914135123
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 33.170209943399804
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 34.660000000000004
+    - type: map_at_10
+      value: 46.938
+    - type: map_at_100
+      value: 48.435
+    - type: map_at_1000
+      value: 48.555
+    - type: map_at_3
+      value: 43.034
+    - type: map_at_5
+      value: 45.055
+    - type: ndcg_at_1
+      value: 42.775
+    - type: ndcg_at_10
+      value: 53.82900000000001
+    - type: ndcg_at_100
+      value: 58.74700000000001
+    - type: ndcg_at_1000
+      value: 60.309000000000005
+    - type: ndcg_at_3
+      value: 48.487
+    - type: ndcg_at_5
+      value: 50.722
+    - type: precision_at_1
+      value: 42.775
+    - type: precision_at_10
+      value: 10.629
+    - type: precision_at_100
+      value: 1.652
+    - type: precision_at_1000
+      value: 0.209
+    - type: precision_at_3
+      value: 23.366999999999997
+    - type: precision_at_5
+      value: 16.967
+    - type: recall_at_1
+      value: 34.660000000000004
+    - type: recall_at_10
+      value: 66.465
+    - type: recall_at_100
+      value: 87.559
+    - type: recall_at_1000
+      value: 97.18299999999999
+    - type: recall_at_3
+      value: 51.01
+    - type: recall_at_5
+      value: 57.412
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 31.180999999999997
+    - type: map_at_10
+      value: 41.802
+    - type: map_at_100
+      value: 43.294
+    - type: map_at_1000
+      value: 43.438
+    - type: map_at_3
+      value: 38.668
+    - type: map_at_5
+      value: 40.559
+    - type: ndcg_at_1
+      value: 39.489999999999995
+    - type: ndcg_at_10
+      value: 47.776
+    - type: ndcg_at_100
+      value: 52.705
+    - type: ndcg_at_1000
+      value: 54.830999999999996
+    - type: ndcg_at_3
+      value: 43.649
+    - type: ndcg_at_5
+      value: 45.885
+    - type: precision_at_1
+      value: 39.489999999999995
+    - type: precision_at_10
+      value: 9.121
+    - type: precision_at_100
+      value: 1.504
+    - type: precision_at_1000
+      value: 0.2
+    - type: precision_at_3
+      value: 21.38
+    - type: precision_at_5
+      value: 15.35
+    - type: recall_at_1
+      value: 31.180999999999997
+    - type: recall_at_10
+      value: 57.714
+    - type: recall_at_100
+      value: 78.342
+    - type: recall_at_1000
+      value: 91.586
+    - type: recall_at_3
+      value: 45.255
+    - type: recall_at_5
+      value: 51.459999999999994
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 38.732
+    - type: map_at_10
+      value: 51.03
+    - type: map_at_100
+      value: 52.078
+    - type: map_at_1000
+      value: 52.132
+    - type: map_at_3
+      value: 47.735
+    - type: map_at_5
+      value: 49.562
+    - type: ndcg_at_1
+      value: 44.074999999999996
+    - type: ndcg_at_10
+      value: 56.923
+    - type: ndcg_at_100
+      value: 61.004999999999995
+    - type: ndcg_at_1000
+      value: 62.12800000000001
+    - type: ndcg_at_3
+      value: 51.381
+    - type: ndcg_at_5
+      value: 54.027
+    - type: precision_at_1
+      value: 44.074999999999996
+    - type: precision_at_10
+      value: 9.21
+    - type: precision_at_100
+      value: 1.221
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 23.009
+    - type: precision_at_5
+      value: 15.748999999999999
+    - type: recall_at_1
+      value: 38.732
+    - type: recall_at_10
+      value: 71.154
+    - type: recall_at_100
+      value: 88.676
+    - type: recall_at_1000
+      value: 96.718
+    - type: recall_at_3
+      value: 56.288000000000004
+    - type: recall_at_5
+      value: 62.792
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 26.837
+    - type: map_at_10
+      value: 35.959
+    - type: map_at_100
+      value: 37.172
+    - type: map_at_1000
+      value: 37.241
+    - type: map_at_3
+      value: 33.027
+    - type: map_at_5
+      value: 34.699000000000005
+    - type: ndcg_at_1
+      value: 29.378999999999998
+    - type: ndcg_at_10
+      value: 41.31
+    - type: ndcg_at_100
+      value: 47.058
+    - type: ndcg_at_1000
+      value: 48.777
+    - type: ndcg_at_3
+      value: 35.564
+    - type: ndcg_at_5
+      value: 38.384
+    - type: precision_at_1
+      value: 29.378999999999998
+    - type: precision_at_10
+      value: 6.361999999999999
+    - type: precision_at_100
+      value: 0.98
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 15.028
+    - type: precision_at_5
+      value: 10.667
+    - type: recall_at_1
+      value: 26.837
+    - type: recall_at_10
+      value: 55.667
+    - type: recall_at_100
+      value: 81.843
+    - type: recall_at_1000
+      value: 94.707
+    - type: recall_at_3
+      value: 40.049
+    - type: recall_at_5
+      value: 46.92
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 15.142
+    - type: map_at_10
+      value: 23.727999999999998
+    - type: map_at_100
+      value: 25.137999999999998
+    - type: map_at_1000
+      value: 25.256
+    - type: map_at_3
+      value: 20.673
+    - type: map_at_5
+      value: 22.325999999999997
+    - type: ndcg_at_1
+      value: 18.407999999999998
+    - type: ndcg_at_10
+      value: 29.286
+    - type: ndcg_at_100
+      value: 35.753
+    - type: ndcg_at_1000
+      value: 38.541
+    - type: ndcg_at_3
+      value: 23.599
+    - type: ndcg_at_5
+      value: 26.262
+    - type: precision_at_1
+      value: 18.407999999999998
+    - type: precision_at_10
+      value: 5.697
+    - type: precision_at_100
+      value: 1.034
+    - type: precision_at_1000
+      value: 0.14100000000000001
+    - type: precision_at_3
+      value: 11.567
+    - type: precision_at_5
+      value: 8.781
+    - type: recall_at_1
+      value: 15.142
+    - type: recall_at_10
+      value: 42.476
+    - type: recall_at_100
+      value: 70.22699999999999
+    - type: recall_at_1000
+      value: 90.02799999999999
+    - type: recall_at_3
+      value: 27.056
+    - type: recall_at_5
+      value: 33.663
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 29.142000000000003
+    - type: map_at_10
+      value: 40.735
+    - type: map_at_100
+      value: 42.155
+    - type: map_at_1000
+      value: 42.27
+    - type: map_at_3
+      value: 37.491
+    - type: map_at_5
+      value: 39.475
+    - type: ndcg_at_1
+      value: 35.515
+    - type: ndcg_at_10
+      value: 46.982
+    - type: ndcg_at_100
+      value: 52.913
+    - type: ndcg_at_1000
+      value: 54.759
+    - type: ndcg_at_3
+      value: 42.164
+    - type: ndcg_at_5
+      value: 44.674
+    - type: precision_at_1
+      value: 35.515
+    - type: precision_at_10
+      value: 8.624
+    - type: precision_at_100
+      value: 1.377
+    - type: precision_at_1000
+      value: 0.173
+    - type: precision_at_3
+      value: 20.468
+    - type: precision_at_5
+      value: 14.649000000000001
+    - type: recall_at_1
+      value: 29.142000000000003
+    - type: recall_at_10
+      value: 59.693
+    - type: recall_at_100
+      value: 84.84899999999999
+    - type: recall_at_1000
+      value: 96.451
+    - type: recall_at_3
+      value: 46.086
+    - type: recall_at_5
+      value: 52.556000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 22.081999999999997
+    - type: map_at_10
+      value: 32.74
+    - type: map_at_100
+      value: 34.108
+    - type: map_at_1000
+      value: 34.233000000000004
+    - type: map_at_3
+      value: 29.282999999999998
+    - type: map_at_5
+      value: 31.127
+    - type: ndcg_at_1
+      value: 26.712000000000003
+    - type: ndcg_at_10
+      value: 38.968
+    - type: ndcg_at_100
+      value: 44.64
+    - type: ndcg_at_1000
+      value: 47.193000000000005
+    - type: ndcg_at_3
+      value: 33.311
+    - type: ndcg_at_5
+      value: 35.76
+    - type: precision_at_1
+      value: 26.712000000000003
+    - type: precision_at_10
+      value: 7.534000000000001
+    - type: precision_at_100
+      value: 1.2149999999999999
+    - type: precision_at_1000
+      value: 0.163
+    - type: precision_at_3
+      value: 16.476
+    - type: precision_at_5
+      value: 12.009
+    - type: recall_at_1
+      value: 22.081999999999997
+    - type: recall_at_10
+      value: 52.859
+    - type: recall_at_100
+      value: 76.812
+    - type: recall_at_1000
+      value: 94.248
+    - type: recall_at_3
+      value: 36.964999999999996
+    - type: recall_at_5
+      value: 43.338
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 25.825750000000003
+    - type: map_at_10
+      value: 35.614666666666665
+    - type: map_at_100
+      value: 36.952416666666664
+    - type: map_at_1000
+      value: 37.07433333333334
+    - type: map_at_3
+      value: 32.519916666666674
+    - type: map_at_5
+      value: 34.22966666666667
+    - type: ndcg_at_1
+      value: 30.616416666666662
+    - type: ndcg_at_10
+      value: 41.32475
+    - type: ndcg_at_100
+      value: 46.907
+    - type: ndcg_at_1000
+      value: 49.12475
+    - type: ndcg_at_3
+      value: 36.1415
+    - type: ndcg_at_5
+      value: 38.54916666666666
+    - type: precision_at_1
+      value: 30.616416666666662
+    - type: precision_at_10
+      value: 7.427166666666666
+    - type: precision_at_100
+      value: 1.2174166666666666
+    - type: precision_at_1000
+      value: 0.16066666666666665
+    - type: precision_at_3
+      value: 16.849083333333333
+    - type: precision_at_5
+      value: 12.1105
+    - type: recall_at_1
+      value: 25.825750000000003
+    - type: recall_at_10
+      value: 53.95283333333333
+    - type: recall_at_100
+      value: 78.408
+    - type: recall_at_1000
+      value: 93.60841666666666
+    - type: recall_at_3
+      value: 39.51116666666667
+    - type: recall_at_5
+      value: 45.67041666666667
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 23.147000000000002
+    - type: map_at_10
+      value: 30.867
+    - type: map_at_100
+      value: 31.961000000000002
+    - type: map_at_1000
+      value: 32.074999999999996
+    - type: map_at_3
+      value: 28.598000000000003
+    - type: map_at_5
+      value: 29.715000000000003
+    - type: ndcg_at_1
+      value: 26.074
+    - type: ndcg_at_10
+      value: 35.379
+    - type: ndcg_at_100
+      value: 40.668
+    - type: ndcg_at_1000
+      value: 43.271
+    - type: ndcg_at_3
+      value: 31.291000000000004
+    - type: ndcg_at_5
+      value: 32.828
+    - type: precision_at_1
+      value: 26.074
+    - type: precision_at_10
+      value: 5.782
+    - type: precision_at_100
+      value: 0.9159999999999999
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_3
+      value: 13.905999999999999
+    - type: precision_at_5
+      value: 9.508999999999999
+    - type: recall_at_1
+      value: 23.147000000000002
+    - type: recall_at_10
+      value: 46.308
+    - type: recall_at_100
+      value: 70.529
+    - type: recall_at_1000
+      value: 89.53
+    - type: recall_at_3
+      value: 34.504000000000005
+    - type: recall_at_5
+      value: 38.472
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 17.573
+    - type: map_at_10
+      value: 25.480999999999998
+    - type: map_at_100
+      value: 26.740000000000002
+    - type: map_at_1000
+      value: 26.881
+    - type: map_at_3
+      value: 22.962
+    - type: map_at_5
+      value: 24.366
+    - type: ndcg_at_1
+      value: 21.783
+    - type: ndcg_at_10
+      value: 30.519000000000002
+    - type: ndcg_at_100
+      value: 36.449
+    - type: ndcg_at_1000
+      value: 39.476
+    - type: ndcg_at_3
+      value: 26.104
+    - type: ndcg_at_5
+      value: 28.142
+    - type: precision_at_1
+      value: 21.783
+    - type: precision_at_10
+      value: 5.716
+    - type: precision_at_100
+      value: 1.036
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 12.629000000000001
+    - type: precision_at_5
+      value: 9.188
+    - type: recall_at_1
+      value: 17.573
+    - type: recall_at_10
+      value: 41.565999999999995
+    - type: recall_at_100
+      value: 68.31099999999999
+    - type: recall_at_1000
+      value: 89.66
+    - type: recall_at_3
+      value: 28.998
+    - type: recall_at_5
+      value: 34.409
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 25.393
+    - type: map_at_10
+      value: 35.408
+    - type: map_at_100
+      value: 36.765
+    - type: map_at_1000
+      value: 36.870000000000005
+    - type: map_at_3
+      value: 31.858999999999998
+    - type: map_at_5
+      value: 34.088
+    - type: ndcg_at_1
+      value: 30.409999999999997
+    - type: ndcg_at_10
+      value: 41.31
+    - type: ndcg_at_100
+      value: 47.317
+    - type: ndcg_at_1000
+      value: 49.451
+    - type: ndcg_at_3
+      value: 35.156
+    - type: ndcg_at_5
+      value: 38.550000000000004
+    - type: precision_at_1
+      value: 30.409999999999997
+    - type: precision_at_10
+      value: 7.285
+    - type: precision_at_100
+      value: 1.16
+    - type: precision_at_1000
+      value: 0.145
+    - type: precision_at_3
+      value: 16.2
+    - type: precision_at_5
+      value: 12.015
+    - type: recall_at_1
+      value: 25.393
+    - type: recall_at_10
+      value: 54.955
+    - type: recall_at_100
+      value: 81.074
+    - type: recall_at_1000
+      value: 95.517
+    - type: recall_at_3
+      value: 38.646
+    - type: recall_at_5
+      value: 47.155
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 25.219
+    - type: map_at_10
+      value: 34.317
+    - type: map_at_100
+      value: 36.099
+    - type: map_at_1000
+      value: 36.339
+    - type: map_at_3
+      value: 31.118000000000002
+    - type: map_at_5
+      value: 32.759
+    - type: ndcg_at_1
+      value: 30.04
+    - type: ndcg_at_10
+      value: 40.467
+    - type: ndcg_at_100
+      value: 46.918
+    - type: ndcg_at_1000
+      value: 49.263
+    - type: ndcg_at_3
+      value: 34.976
+    - type: ndcg_at_5
+      value: 37.345
+    - type: precision_at_1
+      value: 30.04
+    - type: precision_at_10
+      value: 7.786999999999999
+    - type: precision_at_100
+      value: 1.638
+    - type: precision_at_1000
+      value: 0.249
+    - type: precision_at_3
+      value: 16.206
+    - type: precision_at_5
+      value: 11.976
+    - type: recall_at_1
+      value: 25.219
+    - type: recall_at_10
+      value: 52.443
+    - type: recall_at_100
+      value: 80.523
+    - type: recall_at_1000
+      value: 95.025
+    - type: recall_at_3
+      value: 37.216
+    - type: recall_at_5
+      value: 43.086999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 20.801
+    - type: map_at_10
+      value: 28.371000000000002
+    - type: map_at_100
+      value: 29.483999999999998
+    - type: map_at_1000
+      value: 29.602
+    - type: map_at_3
+      value: 25.790999999999997
+    - type: map_at_5
+      value: 27.025
+    - type: ndcg_at_1
+      value: 22.736
+    - type: ndcg_at_10
+      value: 33.147999999999996
+    - type: ndcg_at_100
+      value: 38.711
+    - type: ndcg_at_1000
+      value: 41.498000000000005
+    - type: ndcg_at_3
+      value: 28.016000000000002
+    - type: ndcg_at_5
+      value: 30.011
+    - type: precision_at_1
+      value: 22.736
+    - type: precision_at_10
+      value: 5.379
+    - type: precision_at_100
+      value: 0.876
+    - type: precision_at_1000
+      value: 0.125
+    - type: precision_at_3
+      value: 11.953
+    - type: precision_at_5
+      value: 8.466
+    - type: recall_at_1
+      value: 20.801
+    - type: recall_at_10
+      value: 46.134
+    - type: recall_at_100
+      value: 72.151
+    - type: recall_at_1000
+      value: 92.648
+    - type: recall_at_3
+      value: 32.061
+    - type: recall_at_5
+      value: 36.781000000000006
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 7.9159999999999995
+    - type: map_at_10
+      value: 13.769
+    - type: map_at_100
+      value: 15.447
+    - type: map_at_1000
+      value: 15.634
+    - type: map_at_3
+      value: 11.234
+    - type: map_at_5
+      value: 12.581999999999999
+    - type: ndcg_at_1
+      value: 17.72
+    - type: ndcg_at_10
+      value: 20.272000000000002
+    - type: ndcg_at_100
+      value: 27.748
+    - type: ndcg_at_1000
+      value: 31.457
+    - type: ndcg_at_3
+      value: 15.742
+    - type: ndcg_at_5
+      value: 17.494
+    - type: precision_at_1
+      value: 17.72
+    - type: precision_at_10
+      value: 6.554
+    - type: precision_at_100
+      value: 1.438
+    - type: precision_at_1000
+      value: 0.212
+    - type: precision_at_3
+      value: 11.705
+    - type: precision_at_5
+      value: 9.511
+    - type: recall_at_1
+      value: 7.9159999999999995
+    - type: recall_at_10
+      value: 25.389
+    - type: recall_at_100
+      value: 52.042
+    - type: recall_at_1000
+      value: 73.166
+    - type: recall_at_3
+      value: 14.585999999999999
+    - type: recall_at_5
+      value: 19.145
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 7.172000000000001
+    - type: map_at_10
+      value: 14.507
+    - type: map_at_100
+      value: 20.094
+    - type: map_at_1000
+      value: 21.357
+    - type: map_at_3
+      value: 10.45
+    - type: map_at_5
+      value: 12.135
+    - type: ndcg_at_1
+      value: 42.375
+    - type: ndcg_at_10
+      value: 32.33
+    - type: ndcg_at_100
+      value: 36.370000000000005
+    - type: ndcg_at_1000
+      value: 43.596000000000004
+    - type: ndcg_at_3
+      value: 35.006
+    - type: ndcg_at_5
+      value: 33.35
+    - type: precision_at_1
+      value: 54.50000000000001
+    - type: precision_at_10
+      value: 26.424999999999997
+    - type: precision_at_100
+      value: 8.24
+    - type: precision_at_1000
+      value: 1.765
+    - type: precision_at_3
+      value: 38.667
+    - type: precision_at_5
+      value: 33.0
+    - type: recall_at_1
+      value: 7.172000000000001
+    - type: recall_at_10
+      value: 19.922
+    - type: recall_at_100
+      value: 43.273
+    - type: recall_at_1000
+      value: 67.157
+    - type: recall_at_3
+      value: 11.521
+    - type: recall_at_5
+      value: 14.667
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 38.43
+    - type: f1
+      value: 35.26220518237799
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 34.076
+    - type: map_at_10
+      value: 45.482
+    - type: map_at_100
+      value: 46.269
+    - type: map_at_1000
+      value: 46.309
+    - type: map_at_3
+      value: 42.614000000000004
+    - type: map_at_5
+      value: 44.314
+    - type: ndcg_at_1
+      value: 36.529
+    - type: ndcg_at_10
+      value: 51.934000000000005
+    - type: ndcg_at_100
+      value: 55.525000000000006
+    - type: ndcg_at_1000
+      value: 56.568
+    - type: ndcg_at_3
+      value: 46.169
+    - type: ndcg_at_5
+      value: 49.163000000000004
+    - type: precision_at_1
+      value: 36.529
+    - type: precision_at_10
+      value: 7.5649999999999995
+    - type: precision_at_100
+      value: 0.947
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 19.326999999999998
+    - type: precision_at_5
+      value: 13.239999999999998
+    - type: recall_at_1
+      value: 34.076
+    - type: recall_at_10
+      value: 69.009
+    - type: recall_at_100
+      value: 85.047
+    - type: recall_at_1000
+      value: 92.962
+    - type: recall_at_3
+      value: 53.446000000000005
+    - type: recall_at_5
+      value: 60.622
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 17.14
+    - type: map_at_10
+      value: 29.141000000000002
+    - type: map_at_100
+      value: 30.956
+    - type: map_at_1000
+      value: 31.159
+    - type: map_at_3
+      value: 25.188
+    - type: map_at_5
+      value: 27.506999999999998
+    - type: ndcg_at_1
+      value: 34.721999999999994
+    - type: ndcg_at_10
+      value: 36.867
+    - type: ndcg_at_100
+      value: 43.931
+    - type: ndcg_at_1000
+      value: 47.276
+    - type: ndcg_at_3
+      value: 33.18
+    - type: ndcg_at_5
+      value: 34.504000000000005
+    - type: precision_at_1
+      value: 34.721999999999994
+    - type: precision_at_10
+      value: 10.448
+    - type: precision_at_100
+      value: 1.778
+    - type: precision_at_1000
+      value: 0.23600000000000002
+    - type: precision_at_3
+      value: 22.377
+    - type: precision_at_5
+      value: 16.759
+    - type: recall_at_1
+      value: 17.14
+    - type: recall_at_10
+      value: 44.131
+    - type: recall_at_100
+      value: 70.60600000000001
+    - type: recall_at_1000
+      value: 90.672
+    - type: recall_at_3
+      value: 30.536
+    - type: recall_at_5
+      value: 36.706
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 27.717999999999996
+    - type: map_at_10
+      value: 37.63
+    - type: map_at_100
+      value: 38.534
+    - type: map_at_1000
+      value: 38.619
+    - type: map_at_3
+      value: 35.197
+    - type: map_at_5
+      value: 36.592999999999996
+    - type: ndcg_at_1
+      value: 55.43599999999999
+    - type: ndcg_at_10
+      value: 46.513
+    - type: ndcg_at_100
+      value: 50.21
+    - type: ndcg_at_1000
+      value: 52.049
+    - type: ndcg_at_3
+      value: 42.333999999999996
+    - type: ndcg_at_5
+      value: 44.45
+    - type: precision_at_1
+      value: 55.43599999999999
+    - type: precision_at_10
+      value: 9.741
+    - type: precision_at_100
+      value: 1.2670000000000001
+    - type: precision_at_1000
+      value: 0.151
+    - type: precision_at_3
+      value: 26.194
+    - type: precision_at_5
+      value: 17.396
+    - type: recall_at_1
+      value: 27.717999999999996
+    - type: recall_at_10
+      value: 48.704
+    - type: recall_at_100
+      value: 63.363
+    - type: recall_at_1000
+      value: 75.564
+    - type: recall_at_3
+      value: 39.291
+    - type: recall_at_5
+      value: 43.491
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 60.6612
+    - type: ap
+      value: 56.73559487964456
+    - type: f1
+      value: 60.39970244353384
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+    metrics:
+    - type: map_at_1
+      value: 18.715
+    - type: map_at_10
+      value: 30.014999999999997
+    - type: map_at_100
+      value: 31.208999999999996
+    - type: map_at_1000
+      value: 31.269999999999996
+    - type: map_at_3
+      value: 26.299
+    - type: map_at_5
+      value: 28.408
+    - type: ndcg_at_1
+      value: 19.255
+    - type: ndcg_at_10
+      value: 36.542
+    - type: ndcg_at_100
+      value: 42.471
+    - type: ndcg_at_1000
+      value: 44.022
+    - type: ndcg_at_3
+      value: 28.921000000000003
+    - type: ndcg_at_5
+      value: 32.676
+    - type: precision_at_1
+      value: 19.255
+    - type: precision_at_10
+      value: 5.91
+    - type: precision_at_100
+      value: 0.8920000000000001
+    - type: precision_at_1000
+      value: 0.10200000000000001
+    - type: precision_at_3
+      value: 12.388
+    - type: precision_at_5
+      value: 9.33
+    - type: recall_at_1
+      value: 18.715
+    - type: recall_at_10
+      value: 56.76
+    - type: recall_at_100
+      value: 84.481
+    - type: recall_at_1000
+      value: 96.44
+    - type: recall_at_3
+      value: 35.942
+    - type: recall_at_5
+      value: 44.926
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 91.56178750569997
+    - type: f1
+      value: 91.02309252160694
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 62.18194254445966
+    - type: f1
+      value: 43.090624769020444
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 67.404169468729
+    - type: f1
+      value: 64.82901615433794
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 75.75655682582381
+    - type: f1
+      value: 74.93126114560368
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 34.40873490143895
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 32.292207500530914
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 30.798042020200267
+    - type: mrr
+      value: 31.803264263405513
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 4.3229999999999995
+    - type: map_at_10
+      value: 11.048
+    - type: map_at_100
+      value: 14.244000000000002
+    - type: map_at_1000
+      value: 15.684000000000001
+    - type: map_at_3
+      value: 7.7219999999999995
+    - type: map_at_5
+      value: 9.231
+    - type: ndcg_at_1
+      value: 39.474
+    - type: ndcg_at_10
+      value: 31.594
+    - type: ndcg_at_100
+      value: 29.455
+    - type: ndcg_at_1000
+      value: 38.283
+    - type: ndcg_at_3
+      value: 36.355
+    - type: ndcg_at_5
+      value: 34.164
+    - type: precision_at_1
+      value: 41.486000000000004
+    - type: precision_at_10
+      value: 24.334
+    - type: precision_at_100
+      value: 7.981000000000001
+    - type: precision_at_1000
+      value: 2.096
+    - type: precision_at_3
+      value: 34.881
+    - type: precision_at_5
+      value: 30.279
+    - type: recall_at_1
+      value: 4.3229999999999995
+    - type: recall_at_10
+      value: 15.498999999999999
+    - type: recall_at_100
+      value: 31.151
+    - type: recall_at_1000
+      value: 63.211
+    - type: recall_at_3
+      value: 9.053
+    - type: recall_at_5
+      value: 11.959
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 22.644000000000002
+    - type: map_at_10
+      value: 36.335
+    - type: map_at_100
+      value: 37.687
+    - type: map_at_1000
+      value: 37.733
+    - type: map_at_3
+      value: 31.928
+    - type: map_at_5
+      value: 34.586
+    - type: ndcg_at_1
+      value: 25.607999999999997
+    - type: ndcg_at_10
+      value: 43.869
+    - type: ndcg_at_100
+      value: 49.730000000000004
+    - type: ndcg_at_1000
+      value: 50.749
+    - type: ndcg_at_3
+      value: 35.418
+    - type: ndcg_at_5
+      value: 39.961999999999996
+    - type: precision_at_1
+      value: 25.607999999999997
+    - type: precision_at_10
+      value: 7.697
+    - type: precision_at_100
+      value: 1.093
+    - type: precision_at_1000
+      value: 0.11900000000000001
+    - type: precision_at_3
+      value: 16.522000000000002
+    - type: precision_at_5
+      value: 12.486
+    - type: recall_at_1
+      value: 22.644000000000002
+    - type: recall_at_10
+      value: 64.711
+    - type: recall_at_100
+      value: 90.32900000000001
+    - type: recall_at_1000
+      value: 97.82
+    - type: recall_at_3
+      value: 42.754999999999995
+    - type: recall_at_5
+      value: 53.37
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 69.76
+    - type: map_at_10
+      value: 83.64200000000001
+    - type: map_at_100
+      value: 84.312
+    - type: map_at_1000
+      value: 84.329
+    - type: map_at_3
+      value: 80.537
+    - type: map_at_5
+      value: 82.494
+    - type: ndcg_at_1
+      value: 80.41
+    - type: ndcg_at_10
+      value: 87.556
+    - type: ndcg_at_100
+      value: 88.847
+    - type: ndcg_at_1000
+      value: 88.959
+    - type: ndcg_at_3
+      value: 84.466
+    - type: ndcg_at_5
+      value: 86.193
+    - type: precision_at_1
+      value: 80.41
+    - type: precision_at_10
+      value: 13.374
+    - type: precision_at_100
+      value: 1.529
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 36.953
+    - type: precision_at_5
+      value: 24.401999999999997
+    - type: recall_at_1
+      value: 69.76
+    - type: recall_at_10
+      value: 95.029
+    - type: recall_at_100
+      value: 99.44
+    - type: recall_at_1000
+      value: 99.979
+    - type: recall_at_3
+      value: 86.215
+    - type: recall_at_5
+      value: 91.03999999999999
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 50.66969274980475
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 54.15176409632201
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 4.853
+    - type: map_at_10
+      value: 12.937999999999999
+    - type: map_at_100
+      value: 15.588
+    - type: map_at_1000
+      value: 15.939
+    - type: map_at_3
+      value: 9.135
+    - type: map_at_5
+      value: 11.004
+    - type: ndcg_at_1
+      value: 24.0
+    - type: ndcg_at_10
+      value: 21.641
+    - type: ndcg_at_100
+      value: 31.212
+    - type: ndcg_at_1000
+      value: 36.854
+    - type: ndcg_at_3
+      value: 20.284
+    - type: ndcg_at_5
+      value: 17.737
+    - type: precision_at_1
+      value: 24.0
+    - type: precision_at_10
+      value: 11.4
+    - type: precision_at_100
+      value: 2.516
+    - type: precision_at_1000
+      value: 0.387
+    - type: precision_at_3
+      value: 19.167
+    - type: precision_at_5
+      value: 15.72
+    - type: recall_at_1
+      value: 4.853
+    - type: recall_at_10
+      value: 23.087
+    - type: recall_at_100
+      value: 51.012
+    - type: recall_at_1000
+      value: 78.49000000000001
+    - type: recall_at_3
+      value: 11.658
+    - type: recall_at_5
+      value: 15.923000000000002
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.91595834747078
+    - type: cos_sim_spearman
+      value: 77.58245130495686
+    - type: euclidean_pearson
+      value: 80.77605511224702
+    - type: euclidean_spearman
+      value: 77.58244681255565
+    - type: manhattan_pearson
+      value: 80.70675261518134
+    - type: manhattan_spearman
+      value: 77.48238642250558
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.35998585185463
+    - type: cos_sim_spearman
+      value: 72.36900735029991
+    - type: euclidean_pearson
+      value: 77.44425972881783
+    - type: euclidean_spearman
+      value: 72.36900735029991
+    - type: manhattan_pearson
+      value: 77.48268272405316
+    - type: manhattan_spearman
+      value: 72.36650357806357
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.15192226911441
+    - type: cos_sim_spearman
+      value: 80.60316722220763
+    - type: euclidean_pearson
+      value: 79.9515074804673
+    - type: euclidean_spearman
+      value: 80.60316715056034
+    - type: manhattan_pearson
+      value: 80.01037050043855
+    - type: manhattan_spearman
+      value: 80.70244228209006
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.80137749134273
+    - type: cos_sim_spearman
+      value: 75.58912800301661
+    - type: euclidean_pearson
+      value: 78.89739732785547
+    - type: euclidean_spearman
+      value: 75.58912800301661
+    - type: manhattan_pearson
+      value: 78.88130916509184
+    - type: manhattan_spearman
+      value: 75.56512617108156
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.73605558012511
+    - type: cos_sim_spearman
+      value: 85.38966051883823
+    - type: euclidean_pearson
+      value: 84.65792305262497
+    - type: euclidean_spearman
+      value: 85.38965068015148
+    - type: manhattan_pearson
+      value: 84.6284531553976
+    - type: manhattan_spearman
+      value: 85.36525580485275
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 77.93667023468089
+    - type: cos_sim_spearman
+      value: 78.98945343973261
+    - type: euclidean_pearson
+      value: 78.55627105899589
+    - type: euclidean_spearman
+      value: 78.98945343973261
+    - type: manhattan_pearson
+      value: 78.47171138630095
+    - type: manhattan_spearman
+      value: 78.90029153062082
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (ko-ko)
+      config: ko-ko
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 38.02556869388448
+    - type: cos_sim_spearman
+      value: 43.39452386216687
+    - type: euclidean_pearson
+      value: 42.85346056221848
+    - type: euclidean_spearman
+      value: 43.39454482701475
+    - type: manhattan_pearson
+      value: 42.80255086270408
+    - type: manhattan_spearman
+      value: 43.35745739810561
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (ar-ar)
+      config: ar-ar
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 50.19733275252325
+    - type: cos_sim_spearman
+      value: 50.892912699226166
+    - type: euclidean_pearson
+      value: 53.38352259940662
+    - type: euclidean_spearman
+      value: 50.892912699226166
+    - type: manhattan_pearson
+      value: 53.48429031763742
+    - type: manhattan_spearman
+      value: 50.961509277559394
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-ar)
+      config: en-ar
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: -5.346248828225636
+    - type: cos_sim_spearman
+      value: -4.276245759627542
+    - type: euclidean_pearson
+      value: -5.34997238478067
+    - type: euclidean_spearman
+      value: -4.276245759627542
+    - type: manhattan_pearson
+      value: -1.599674226848396
+    - type: manhattan_spearman
+      value: -0.6972996366546237
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-de)
+      config: en-de
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 37.0025013483991
+    - type: cos_sim_spearman
+      value: 35.81883942216964
+    - type: euclidean_pearson
+      value: 36.69612954510884
+    - type: euclidean_spearman
+      value: 35.81883942216964
+    - type: manhattan_pearson
+      value: 35.141229073611555
+    - type: manhattan_spearman
+      value: 32.04594883372404
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.02366672243191
+    - type: cos_sim_spearman
+      value: 87.58779089494524
+    - type: euclidean_pearson
+      value: 87.99011173645361
+    - type: euclidean_spearman
+      value: 87.58779089494524
+    - type: manhattan_pearson
+      value: 87.71266341564564
+    - type: manhattan_spearman
+      value: 87.24437101621581
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-tr)
+      config: en-tr
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 6.928208810824121
+    - type: cos_sim_spearman
+      value: 4.496540073637865
+    - type: euclidean_pearson
+      value: 7.258004484570359
+    - type: euclidean_spearman
+      value: 4.496540073637865
+    - type: manhattan_pearson
+      value: 4.294687250993676
+    - type: manhattan_spearman
+      value: 2.517822531443102
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (es-en)
+      config: es-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 17.49363358339176
+    - type: cos_sim_spearman
+      value: 16.31316318682868
+    - type: euclidean_pearson
+      value: 17.834234153786475
+    - type: euclidean_spearman
+      value: 16.31316318682868
+    - type: manhattan_pearson
+      value: 16.928139101229352
+    - type: manhattan_spearman
+      value: 15.00071366769135
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (es-es)
+      config: es-es
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 77.04145671005833
+    - type: cos_sim_spearman
+      value: 76.11599994398748
+    - type: euclidean_pearson
+      value: 78.21801117699432
+    - type: euclidean_spearman
+      value: 76.11599994398748
+    - type: manhattan_pearson
+      value: 77.87062358292948
+    - type: manhattan_spearman
+      value: 75.64561332109221
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (fr-en)
+      config: fr-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 37.9961687967439
+    - type: cos_sim_spearman
+      value: 37.09338306656542
+    - type: euclidean_pearson
+      value: 37.81002317191932
+    - type: euclidean_spearman
+      value: 37.09338306656542
+    - type: manhattan_pearson
+      value: 37.58237523973875
+    - type: manhattan_spearman
+      value: 36.52020936925911
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (it-en)
+      config: it-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 26.739991134614716
+    - type: cos_sim_spearman
+      value: 24.4457755448559
+    - type: euclidean_pearson
+      value: 26.804935356831862
+    - type: euclidean_spearman
+      value: 24.442532087041023
+    - type: manhattan_pearson
+      value: 27.571123840765026
+    - type: manhattan_spearman
+      value: 25.554721155049045
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (nl-en)
+      config: nl-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 32.71761762628939
+    - type: cos_sim_spearman
+      value: 28.99879893370601
+    - type: euclidean_pearson
+      value: 32.92831060810701
+    - type: euclidean_spearman
+      value: 28.99879893370601
+    - type: manhattan_pearson
+      value: 33.30410551798337
+    - type: manhattan_spearman
+      value: 29.442853829506593
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 67.09882753030891
+    - type: cos_sim_spearman
+      value: 67.21465212910987
+    - type: euclidean_pearson
+      value: 68.21374069918403
+    - type: euclidean_spearman
+      value: 67.21465212910987
+    - type: manhattan_pearson
+      value: 68.41388868877884
+    - type: manhattan_spearman
+      value: 67.83615682571867
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de)
+      config: de
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 26.596033966146116
+    - type: cos_sim_spearman
+      value: 31.044353994772354
+    - type: euclidean_pearson
+      value: 21.51728902500591
+    - type: euclidean_spearman
+      value: 31.044353994772354
+    - type: manhattan_pearson
+      value: 21.718468273577894
+    - type: manhattan_spearman
+      value: 31.197915595597696
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (es)
+      config: es
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 44.33815143022264
+    - type: cos_sim_spearman
+      value: 54.77772552456677
+    - type: euclidean_pearson
+      value: 48.483578263920634
+    - type: euclidean_spearman
+      value: 54.77772552456677
+    - type: manhattan_pearson
+      value: 49.29424073081744
+    - type: manhattan_spearman
+      value: 55.259696552690954
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (pl)
+      config: pl
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 8.000336595206134
+    - type: cos_sim_spearman
+      value: 26.768906191975933
+    - type: euclidean_pearson
+      value: 1.4181188576056134
+    - type: euclidean_spearman
+      value: 26.768906191975933
+    - type: manhattan_pearson
+      value: 1.588769366202155
+    - type: manhattan_spearman
+      value: 26.76300987426348
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (tr)
+      config: tr
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 20.597902459466386
+    - type: cos_sim_spearman
+      value: 33.694510807738595
+    - type: euclidean_pearson
+      value: 26.964862787540962
+    - type: euclidean_spearman
+      value: 33.694510807738595
+    - type: manhattan_pearson
+      value: 27.530294926210807
+    - type: manhattan_spearman
+      value: 33.74254435313719
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (ar)
+      config: ar
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 5.006610360999117
+    - type: cos_sim_spearman
+      value: 22.63866797712348
+    - type: euclidean_pearson
+      value: 13.082283087945362
+    - type: euclidean_spearman
+      value: 22.63866797712348
+    - type: manhattan_pearson
+      value: 13.260328120447722
+    - type: manhattan_spearman
+      value: 22.340169287120716
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (ru)
+      config: ru
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.03100716792233671
+    - type: cos_sim_spearman
+      value: 14.721380413194854
+    - type: euclidean_pearson
+      value: 4.871526064730011
+    - type: euclidean_spearman
+      value: 14.721380413194854
+    - type: manhattan_pearson
+      value: 5.7576102223040735
+    - type: manhattan_spearman
+      value: 15.08182690716095
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (zh)
+      config: zh
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 23.127885111414432
+    - type: cos_sim_spearman
+      value: 44.92964024177277
+    - type: euclidean_pearson
+      value: 31.061639313469925
+    - type: euclidean_spearman
+      value: 44.92964024177277
+    - type: manhattan_pearson
+      value: 31.77656358573927
+    - type: manhattan_spearman
+      value: 44.964763982886375
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (fr)
+      config: fr
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 70.64344773137496
+    - type: cos_sim_spearman
+      value: 77.00398643056744
+    - type: euclidean_pearson
+      value: 71.58320199923101
+    - type: euclidean_spearman
+      value: 77.00398643056744
+    - type: manhattan_pearson
+      value: 71.64373853764818
+    - type: manhattan_spearman
+      value: 76.71158725879226
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de-en)
+      config: de-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 47.54531236654512
+    - type: cos_sim_spearman
+      value: 44.038685024247606
+    - type: euclidean_pearson
+      value: 48.46975590869453
+    - type: euclidean_spearman
+      value: 44.038685024247606
+    - type: manhattan_pearson
+      value: 48.10217367438755
+    - type: manhattan_spearman
+      value: 44.4428504653391
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (es-en)
+      config: es-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 49.93601240112664
+    - type: cos_sim_spearman
+      value: 53.41895837272506
+    - type: euclidean_pearson
+      value: 50.16469746986203
+    - type: euclidean_spearman
+      value: 53.41895837272506
+    - type: manhattan_pearson
+      value: 49.86265183075983
+    - type: manhattan_spearman
+      value: 53.10065931046005
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (it)
+      config: it
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 57.4312835830767
+    - type: cos_sim_spearman
+      value: 60.39610834515271
+    - type: euclidean_pearson
+      value: 57.81507077373551
+    - type: euclidean_spearman
+      value: 60.39610834515271
+    - type: manhattan_pearson
+      value: 57.83823485037898
+    - type: manhattan_spearman
+      value: 60.374938260317535
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (pl-en)
+      config: pl-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 35.08730015173829
+    - type: cos_sim_spearman
+      value: 32.79791295777814
+    - type: euclidean_pearson
+      value: 34.54132550386404
+    - type: euclidean_spearman
+      value: 32.79791295777814
+    - type: manhattan_pearson
+      value: 36.273935331272256
+    - type: manhattan_spearman
+      value: 35.88704294252439
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (zh-en)
+      config: zh-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 37.41111741585122
+    - type: cos_sim_spearman
+      value: 41.64399741744448
+    - type: euclidean_pearson
+      value: 36.83160927711053
+    - type: euclidean_spearman
+      value: 41.64399741744448
+    - type: manhattan_pearson
+      value: 35.71015224548175
+    - type: manhattan_spearman
+      value: 41.460551673456045
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (es-it)
+      config: es-it
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 42.568537775842245
+    - type: cos_sim_spearman
+      value: 44.2699366594503
+    - type: euclidean_pearson
+      value: 43.569828137034264
+    - type: euclidean_spearman
+      value: 44.2699366594503
+    - type: manhattan_pearson
+      value: 43.954212787242284
+    - type: manhattan_spearman
+      value: 44.32159550471527
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de-fr)
+      config: de-fr
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 26.472844763068938
+    - type: cos_sim_spearman
+      value: 30.067587482078228
+    - type: euclidean_pearson
+      value: 26.87230792075073
+    - type: euclidean_spearman
+      value: 30.067587482078228
+    - type: manhattan_pearson
+      value: 25.808959063835424
+    - type: manhattan_spearman
+      value: 27.996294873002153
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de-pl)
+      config: de-pl
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 7.026566971631159
+    - type: cos_sim_spearman
+      value: 4.9270565599404135
+    - type: euclidean_pearson
+      value: 6.729027056926625
+    - type: euclidean_spearman
+      value: 4.9270565599404135
+    - type: manhattan_pearson
+      value: 9.01762174854638
+    - type: manhattan_spearman
+      value: 7.359790736410993
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (fr-pl)
+      config: fr-pl
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 54.305559003968206
+    - type: cos_sim_spearman
+      value: 50.709255283710995
+    - type: euclidean_pearson
+      value: 53.00660084455784
+    - type: euclidean_spearman
+      value: 50.709255283710995
+    - type: manhattan_pearson
+      value: 52.33784187543789
+    - type: manhattan_spearman
+      value: 50.709255283710995
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.7406424090513
+    - type: cos_sim_spearman
+      value: 82.03246731235654
+    - type: euclidean_pearson
+      value: 82.55616747173353
+    - type: euclidean_spearman
+      value: 82.03246731235654
+    - type: manhattan_pearson
+      value: 82.49144455072748
+    - type: manhattan_spearman
+      value: 81.94552526855261
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 87.11941318470207
+    - type: mrr
+      value: 96.39370705547176
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 48.233
+    - type: map_at_10
+      value: 59.592999999999996
+    - type: map_at_100
+      value: 60.307
+    - type: map_at_1000
+      value: 60.343
+    - type: map_at_3
+      value: 56.564
+    - type: map_at_5
+      value: 58.826
+    - type: ndcg_at_1
+      value: 50.333000000000006
+    - type: ndcg_at_10
+      value: 64.508
+    - type: ndcg_at_100
+      value: 67.66499999999999
+    - type: ndcg_at_1000
+      value: 68.552
+    - type: ndcg_at_3
+      value: 59.673
+    - type: ndcg_at_5
+      value: 62.928
+    - type: precision_at_1
+      value: 50.333000000000006
+    - type: precision_at_10
+      value: 8.833
+    - type: precision_at_100
+      value: 1.053
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 23.778
+    - type: precision_at_5
+      value: 16.400000000000002
+    - type: recall_at_1
+      value: 48.233
+    - type: recall_at_10
+      value: 78.333
+    - type: recall_at_100
+      value: 92.5
+    - type: recall_at_1000
+      value: 99.333
+    - type: recall_at_3
+      value: 66.033
+    - type: recall_at_5
+      value: 73.79400000000001
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.78514851485149
+    - type: cos_sim_ap
+      value: 94.55063045792446
+    - type: cos_sim_f1
+      value: 89.01265822784809
+    - type: cos_sim_precision
+      value: 90.15384615384615
+    - type: cos_sim_recall
+      value: 87.9
+    - type: dot_accuracy
+      value: 99.78514851485149
+    - type: dot_ap
+      value: 94.55063045792447
+    - type: dot_f1
+      value: 89.01265822784809
+    - type: dot_precision
+      value: 90.15384615384615
+    - type: dot_recall
+      value: 87.9
+    - type: euclidean_accuracy
+      value: 99.78514851485149
+    - type: euclidean_ap
+      value: 94.55063045792447
+    - type: euclidean_f1
+      value: 89.01265822784809
+    - type: euclidean_precision
+      value: 90.15384615384615
+    - type: euclidean_recall
+      value: 87.9
+    - type: manhattan_accuracy
+      value: 99.78415841584159
+    - type: manhattan_ap
+      value: 94.54002074215008
+    - type: manhattan_f1
+      value: 88.98989898989899
+    - type: manhattan_precision
+      value: 89.89795918367346
+    - type: manhattan_recall
+      value: 88.1
+    - type: max_accuracy
+      value: 99.78514851485149
+    - type: max_ap
+      value: 94.55063045792447
+    - type: max_f1
+      value: 89.01265822784809
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 53.361421662036015
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 38.001825627800976
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 50.762134384316084
+    - type: mrr
+      value: 51.39383594346829
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.508420334813536
+    - type: cos_sim_spearman
+      value: 30.808757671244493
+    - type: dot_pearson
+      value: 30.508418240633862
+    - type: dot_spearman
+      value: 30.808757671244493
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 0.169
+    - type: map_at_10
+      value: 1.054
+    - type: map_at_100
+      value: 5.308
+    - type: map_at_1000
+      value: 13.313
+    - type: map_at_3
+      value: 0.40800000000000003
+    - type: map_at_5
+      value: 0.627
+    - type: ndcg_at_1
+      value: 56.00000000000001
+    - type: ndcg_at_10
+      value: 47.246
+    - type: ndcg_at_100
+      value: 35.172
+    - type: ndcg_at_1000
+      value: 34.031
+    - type: ndcg_at_3
+      value: 51.939
+    - type: ndcg_at_5
+      value: 50.568999999999996
+    - type: precision_at_1
+      value: 62.0
+    - type: precision_at_10
+      value: 50.4
+    - type: precision_at_100
+      value: 36.14
+    - type: precision_at_1000
+      value: 15.45
+    - type: precision_at_3
+      value: 56.00000000000001
+    - type: precision_at_5
+      value: 55.2
+    - type: recall_at_1
+      value: 0.169
+    - type: recall_at_10
+      value: 1.284
+    - type: recall_at_100
+      value: 8.552
+    - type: recall_at_1000
+      value: 32.81
+    - type: recall_at_3
+      value: 0.44
+    - type: recall_at_5
+      value: 0.709
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 1.49
+    - type: map_at_10
+      value: 6.39
+    - type: map_at_100
+      value: 11.424
+    - type: map_at_1000
+      value: 12.847
+    - type: map_at_3
+      value: 3.055
+    - type: map_at_5
+      value: 3.966
+    - type: ndcg_at_1
+      value: 17.347
+    - type: ndcg_at_10
+      value: 16.904
+    - type: ndcg_at_100
+      value: 29.187
+    - type: ndcg_at_1000
+      value: 40.994
+    - type: ndcg_at_3
+      value: 15.669
+    - type: ndcg_at_5
+      value: 16.034000000000002
+    - type: precision_at_1
+      value: 18.367
+    - type: precision_at_10
+      value: 16.326999999999998
+    - type: precision_at_100
+      value: 6.673
+    - type: precision_at_1000
+      value: 1.439
+    - type: precision_at_3
+      value: 17.687
+    - type: precision_at_5
+      value: 17.143
+    - type: recall_at_1
+      value: 1.49
+    - type: recall_at_10
+      value: 12.499
+    - type: recall_at_100
+      value: 41.711
+    - type: recall_at_1000
+      value: 78.286
+    - type: recall_at_3
+      value: 4.055000000000001
+    - type: recall_at_5
+      value: 6.5040000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 66.9918
+    - type: ap
+      value: 12.24755801720171
+    - type: f1
+      value: 51.31653313211933
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 55.410299943406905
+    - type: f1
+      value: 55.71547395803944
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 46.860271427647774
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_accuracy
+      value: 84.1151576563152
+    - type: cos_sim_ap
+      value: 67.85802440228593
+    - type: cos_sim_f1
+      value: 64.08006919560113
+    - type: cos_sim_precision
+      value: 60.260283523123405
+    - type: cos_sim_recall
+      value: 68.41688654353561
+    - type: dot_accuracy
+      value: 84.1151576563152
+    - type: dot_ap
+      value: 67.85802503410727
+    - type: dot_f1
+      value: 64.08006919560113
+    - type: dot_precision
+      value: 60.260283523123405
+    - type: dot_recall
+      value: 68.41688654353561
+    - type: euclidean_accuracy
+      value: 84.1151576563152
+    - type: euclidean_ap
+      value: 67.85802845168082
+    - type: euclidean_f1
+      value: 64.08006919560113
+    - type: euclidean_precision
+      value: 60.260283523123405
+    - type: euclidean_recall
+      value: 68.41688654353561
+    - type: manhattan_accuracy
+      value: 83.96614412588663
+    - type: manhattan_ap
+      value: 67.66935451307549
+    - type: manhattan_f1
+      value: 63.82363570654138
+    - type: manhattan_precision
+      value: 58.72312125914432
+    - type: manhattan_recall
+      value: 69.89445910290237
+    - type: max_accuracy
+      value: 84.1151576563152
+    - type: max_ap
+      value: 67.85802845168082
+    - type: max_f1
+      value: 64.08006919560113
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.2504754142896
+    - type: cos_sim_ap
+      value: 84.70165951451109
+    - type: cos_sim_f1
+      value: 76.57057281916886
+    - type: cos_sim_precision
+      value: 74.5226643346451
+    - type: cos_sim_recall
+      value: 78.73421619956883
+    - type: dot_accuracy
+      value: 88.2504754142896
+    - type: dot_ap
+      value: 84.7016596919848
+    - type: dot_f1
+      value: 76.57057281916886
+    - type: dot_precision
+      value: 74.5226643346451
+    - type: dot_recall
+      value: 78.73421619956883
+    - type: euclidean_accuracy
+      value: 88.2504754142896
+    - type: euclidean_ap
+      value: 84.70166029488888
+    - type: euclidean_f1
+      value: 76.57057281916886
+    - type: euclidean_precision
+      value: 74.5226643346451
+    - type: euclidean_recall
+      value: 78.73421619956883
+    - type: manhattan_accuracy
+      value: 88.27376101214732
+    - type: manhattan_ap
+      value: 84.63518812822186
+    - type: manhattan_f1
+      value: 76.55138674594514
+    - type: manhattan_precision
+      value: 74.86934118513065
+    - type: manhattan_recall
+      value: 78.31074838312288
+    - type: max_accuracy
+      value: 88.27376101214732
+    - type: max_ap
+      value: 84.70166029488888
+    - type: max_f1
+      value: 76.57057281916886
 ---