Linq-AI-Research
/

Linq-Embed-Mistral

@@ -2,2601 +2,6 @@
 tags:
   - transformers
   - mteb
-model-index:
-- name: Linq-Embed-Mistral
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 84.43283582089552
-    - type: ap
-      value: 50.39222584035829
-    - type: f1
-      value: 78.47906270064071
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 95.70445
-    - type: ap
-      value: 94.28273900595173
-    - type: f1
-      value: 95.70048412173735
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 57.644000000000005
-    - type: f1
-      value: 56.993648296704876
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
-    metrics:
-    - type: map_at_1
-      value: 45.804
-    - type: map_at_10
-      value: 61.742
-    - type: map_at_100
-      value: 62.07899999999999
-    - type: map_at_1000
-      value: 62.08
-    - type: map_at_3
-      value: 57.717
-    - type: map_at_5
-      value: 60.27
-    - type: mrr_at_1
-      value: 47.226
-    - type: mrr_at_10
-      value: 62.256
-    - type: mrr_at_100
-      value: 62.601
-    - type: mrr_at_1000
-      value: 62.601
-    - type: mrr_at_3
-      value: 58.203
-    - type: mrr_at_5
-      value: 60.767
-    - type: ndcg_at_1
-      value: 45.804
-    - type: ndcg_at_10
-      value: 69.649
-    - type: ndcg_at_100
-      value: 70.902
-    - type: ndcg_at_1000
-      value: 70.91199999999999
-    - type: ndcg_at_3
-      value: 61.497
-    - type: ndcg_at_5
-      value: 66.097
-    - type: precision_at_1
-      value: 45.804
-    - type: precision_at_10
-      value: 9.452
-    - type: precision_at_100
-      value: 0.996
-    - type: precision_at_1000
-      value: 0.1
-    - type: precision_at_3
-      value: 24.135
-    - type: precision_at_5
-      value: 16.714000000000002
-    - type: recall_at_1
-      value: 45.804
-    - type: recall_at_10
-      value: 94.523
-    - type: recall_at_100
-      value: 99.57300000000001
-    - type: recall_at_1000
-      value: 99.644
-    - type: recall_at_3
-      value: 72.404
-    - type: recall_at_5
-      value: 83.57
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 51.47612678878609
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 47.2977392340418
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 66.82016765243456
-    - type: mrr
-      value: 79.55227982236292
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_pearson
-      value: 89.15068664186332
-    - type: cos_sim_spearman
-      value: 86.4013663041054
-    - type: euclidean_pearson
-      value: 87.36391302921588
-    - type: euclidean_spearman
-      value: 86.4013663041054
-    - type: manhattan_pearson
-      value: 87.46116676558589
-    - type: manhattan_spearman
-      value: 86.78149544753352
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 87.88311688311688
-    - type: f1
-      value: 87.82368154811464
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 42.72860396750569
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 39.58412067938718
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-android
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: f46a197baaae43b4f621051089b82a364682dfeb
-    metrics:
-    - type: map_at_1
-      value: 34.475
-    - type: map_at_10
-      value: 47.221000000000004
-    - type: map_at_100
-      value: 48.879
-    - type: map_at_1000
-      value: 48.986000000000004
-    - type: map_at_3
-      value: 43.326
-    - type: map_at_5
-      value: 45.461
-    - type: mrr_at_1
-      value: 42.346000000000004
-    - type: mrr_at_10
-      value: 53.056000000000004
-    - type: mrr_at_100
-      value: 53.833
-    - type: mrr_at_1000
-      value: 53.86
-    - type: mrr_at_3
-      value: 50.381
-    - type: mrr_at_5
-      value: 51.961999999999996
-    - type: ndcg_at_1
-      value: 42.346000000000004
-    - type: ndcg_at_10
-      value: 54.027
-    - type: ndcg_at_100
-      value: 59.596000000000004
-    - type: ndcg_at_1000
-      value: 60.931000000000004
-    - type: ndcg_at_3
-      value: 48.649
-    - type: ndcg_at_5
-      value: 51.092999999999996
-    - type: precision_at_1
-      value: 42.346000000000004
-    - type: precision_at_10
-      value: 10.358
-    - type: precision_at_100
-      value: 1.629
-    - type: precision_at_1000
-      value: 0.20400000000000001
-    - type: precision_at_3
-      value: 23.319000000000003
-    - type: precision_at_5
-      value: 16.767000000000003
-    - type: recall_at_1
-      value: 34.475
-    - type: recall_at_10
-      value: 67.10300000000001
-    - type: recall_at_100
-      value: 89.899
-    - type: recall_at_1000
-      value: 97.63300000000001
-    - type: recall_at_3
-      value: 51.534
-    - type: recall_at_5
-      value: 58.422
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-english
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
-    metrics:
-    - type: map_at_1
-      value: 37.019999999999996
-    - type: map_at_10
-      value: 48.957
-    - type: map_at_100
-      value: 50.312
-    - type: map_at_1000
-      value: 50.438
-    - type: map_at_3
-      value: 45.544000000000004
-    - type: map_at_5
-      value: 47.477999999999994
-    - type: mrr_at_1
-      value: 45.924
-    - type: mrr_at_10
-      value: 54.994
-    - type: mrr_at_100
-      value: 55.592
-    - type: mrr_at_1000
-      value: 55.625
-    - type: mrr_at_3
-      value: 52.771
-    - type: mrr_at_5
-      value: 54.099
-    - type: ndcg_at_1
-      value: 45.924
-    - type: ndcg_at_10
-      value: 55.031
-    - type: ndcg_at_100
-      value: 59.339
-    - type: ndcg_at_1000
-      value: 61.063
-    - type: ndcg_at_3
-      value: 50.507999999999996
-    - type: ndcg_at_5
-      value: 52.613
-    - type: precision_at_1
-      value: 45.924
-    - type: precision_at_10
-      value: 10.338
-    - type: precision_at_100
-      value: 1.6070000000000002
-    - type: precision_at_1000
-      value: 0.207
-    - type: precision_at_3
-      value: 24.352
-    - type: precision_at_5
-      value: 17.185
-    - type: recall_at_1
-      value: 37.019999999999996
-    - type: recall_at_10
-      value: 65.59700000000001
-    - type: recall_at_100
-      value: 83.465
-    - type: recall_at_1000
-      value: 93.856
-    - type: recall_at_3
-      value: 52.187
-    - type: recall_at_5
-      value: 58.153999999999996
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-gaming
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
-    metrics:
-    - type: map_at_1
-      value: 45.145
-    - type: map_at_10
-      value: 58.628
-    - type: map_at_100
-      value: 59.702999999999996
-    - type: map_at_1000
-      value: 59.74
-    - type: map_at_3
-      value: 55.13
-    - type: map_at_5
-      value: 57.142
-    - type: mrr_at_1
-      value: 51.473
-    - type: mrr_at_10
-      value: 62.117999999999995
-    - type: mrr_at_100
-      value: 62.694
-    - type: mrr_at_1000
-      value: 62.709
-    - type: mrr_at_3
-      value: 59.707
-    - type: mrr_at_5
-      value: 61.099000000000004
-    - type: ndcg_at_1
-      value: 51.473
-    - type: ndcg_at_10
-      value: 64.741
-    - type: ndcg_at_100
-      value: 68.47800000000001
-    - type: ndcg_at_1000
-      value: 69.08
-    - type: ndcg_at_3
-      value: 59.069
-    - type: ndcg_at_5
-      value: 61.868
-    - type: precision_at_1
-      value: 51.473
-    - type: precision_at_10
-      value: 10.376000000000001
-    - type: precision_at_100
-      value: 1.307
-    - type: precision_at_1000
-      value: 0.13899999999999998
-    - type: precision_at_3
-      value: 26.165
-    - type: precision_at_5
-      value: 17.855999999999998
-    - type: recall_at_1
-      value: 45.145
-    - type: recall_at_10
-      value: 79.07
-    - type: recall_at_100
-      value: 94.806
-    - type: recall_at_1000
-      value: 98.799
-    - type: recall_at_3
-      value: 64.14999999999999
-    - type: recall_at_5
-      value: 70.989
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-gis
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: 5003b3064772da1887988e05400cf3806fe491f2
-    metrics:
-    - type: map_at_1
-      value: 29.144
-    - type: map_at_10
-      value: 38.742
-    - type: map_at_100
-      value: 39.858
-    - type: map_at_1000
-      value: 39.921
-    - type: map_at_3
-      value: 35.79
-    - type: map_at_5
-      value: 37.269000000000005
-    - type: mrr_at_1
-      value: 31.525
-    - type: mrr_at_10
-      value: 40.925
-    - type: mrr_at_100
-      value: 41.931000000000004
-    - type: mrr_at_1000
-      value: 41.972
-    - type: mrr_at_3
-      value: 38.324000000000005
-    - type: mrr_at_5
-      value: 39.573
-    - type: ndcg_at_1
-      value: 31.525
-    - type: ndcg_at_10
-      value: 44.292
-    - type: ndcg_at_100
-      value: 49.704
-    - type: ndcg_at_1000
-      value: 51.163000000000004
-    - type: ndcg_at_3
-      value: 38.529
-    - type: ndcg_at_5
-      value: 40.904
-    - type: precision_at_1
-      value: 31.525
-    - type: precision_at_10
-      value: 6.825
-    - type: precision_at_100
-      value: 1.005
-    - type: precision_at_1000
-      value: 0.116
-    - type: precision_at_3
-      value: 16.158
-    - type: precision_at_5
-      value: 11.096
-    - type: recall_at_1
-      value: 29.144
-    - type: recall_at_10
-      value: 59.379000000000005
-    - type: recall_at_100
-      value: 83.906
-    - type: recall_at_1000
-      value: 94.649
-    - type: recall_at_3
-      value: 43.602000000000004
-    - type: recall_at_5
-      value: 49.305
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-mathematica
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
-    metrics:
-    - type: map_at_1
-      value: 21.435000000000002
-    - type: map_at_10
-      value: 31.441000000000003
-    - type: map_at_100
-      value: 32.805
-    - type: map_at_1000
-      value: 32.918
-    - type: map_at_3
-      value: 28.164
-    - type: map_at_5
-      value: 29.809
-    - type: mrr_at_1
-      value: 26.99
-    - type: mrr_at_10
-      value: 36.882
-    - type: mrr_at_100
-      value: 37.835
-    - type: mrr_at_1000
-      value: 37.889
-    - type: mrr_at_3
-      value: 34.1
-    - type: mrr_at_5
-      value: 35.587
-    - type: ndcg_at_1
-      value: 26.99
-    - type: ndcg_at_10
-      value: 37.763000000000005
-    - type: ndcg_at_100
-      value: 43.636
-    - type: ndcg_at_1000
-      value: 45.96
-    - type: ndcg_at_3
-      value: 32.04
-    - type: ndcg_at_5
-      value: 34.439
-    - type: precision_at_1
-      value: 26.99
-    - type: precision_at_10
-      value: 7.127
-    - type: precision_at_100
-      value: 1.15
-    - type: precision_at_1000
-      value: 0.147
-    - type: precision_at_3
-      value: 15.629999999999999
-    - type: precision_at_5
-      value: 11.269
-    - type: recall_at_1
-      value: 21.435000000000002
-    - type: recall_at_10
-      value: 51.717999999999996
-    - type: recall_at_100
-      value: 76.51599999999999
-    - type: recall_at_1000
-      value: 92.632
-    - type: recall_at_3
-      value: 35.684
-    - type: recall_at_5
-      value: 41.959
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-physics
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
-    metrics:
-    - type: map_at_1
-      value: 33.129999999999995
-    - type: map_at_10
-      value: 46.006
-    - type: map_at_100
-      value: 47.339999999999996
-    - type: map_at_1000
-      value: 47.435
-    - type: map_at_3
-      value: 42.349
-    - type: map_at_5
-      value: 44.349
-    - type: mrr_at_1
-      value: 40.422999999999995
-    - type: mrr_at_10
-      value: 51.5
-    - type: mrr_at_100
-      value: 52.217999999999996
-    - type: mrr_at_1000
-      value: 52.246
-    - type: mrr_at_3
-      value: 48.973
-    - type: mrr_at_5
-      value: 50.407000000000004
-    - type: ndcg_at_1
-      value: 40.422999999999995
-    - type: ndcg_at_10
-      value: 52.71900000000001
-    - type: ndcg_at_100
-      value: 57.824
-    - type: ndcg_at_1000
-      value: 59.321999999999996
-    - type: ndcg_at_3
-      value: 47.169
-    - type: ndcg_at_5
-      value: 49.774
-    - type: precision_at_1
-      value: 40.422999999999995
-    - type: precision_at_10
-      value: 9.74
-    - type: precision_at_100
-      value: 1.4409999999999998
-    - type: precision_at_1000
-      value: 0.172
-    - type: precision_at_3
-      value: 22.778000000000002
-    - type: precision_at_5
-      value: 16.131
-    - type: recall_at_1
-      value: 33.129999999999995
-    - type: recall_at_10
-      value: 66.864
-    - type: recall_at_100
-      value: 87.812
-    - type: recall_at_1000
-      value: 97.214
-    - type: recall_at_3
-      value: 51.305
-    - type: recall_at_5
-      value: 58.046
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-programmers
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
-    metrics:
-    - type: map_at_1
-      value: 30.062
-    - type: map_at_10
-      value: 42.166
-    - type: map_at_100
-      value: 43.673
-    - type: map_at_1000
-      value: 43.765
-    - type: map_at_3
-      value: 38.035000000000004
-    - type: map_at_5
-      value: 40.39
-    - type: mrr_at_1
-      value: 36.758
-    - type: mrr_at_10
-      value: 47.419
-    - type: mrr_at_100
-      value: 48.352000000000004
-    - type: mrr_at_1000
-      value: 48.387
-    - type: mrr_at_3
-      value: 44.330000000000005
-    - type: mrr_at_5
-      value: 46.197
-    - type: ndcg_at_1
-      value: 36.758
-    - type: ndcg_at_10
-      value: 48.923
-    - type: ndcg_at_100
-      value: 54.58
-    - type: ndcg_at_1000
-      value: 56.208000000000006
-    - type: ndcg_at_3
-      value: 42.437999999999995
-    - type: ndcg_at_5
-      value: 45.539
-    - type: precision_at_1
-      value: 36.758
-    - type: precision_at_10
-      value: 9.247
-    - type: precision_at_100
-      value: 1.396
-    - type: precision_at_1000
-      value: 0.17099999999999999
-    - type: precision_at_3
-      value: 20.548
-    - type: precision_at_5
-      value: 15.046000000000001
-    - type: recall_at_1
-      value: 30.062
-    - type: recall_at_10
-      value: 63.54
-    - type: recall_at_100
-      value: 86.54899999999999
-    - type: recall_at_1000
-      value: 97.14699999999999
-    - type: recall_at_3
-      value: 45.62
-    - type: recall_at_5
-      value: 53.687
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
-    metrics:
-    - type: map_at_1
-      value: 30.082666666666665
-    - type: map_at_10
-      value: 41.13875
-    - type: map_at_100
-      value: 42.45525
-    - type: map_at_1000
-      value: 42.561249999999994
-    - type: map_at_3
-      value: 37.822750000000006
-    - type: map_at_5
-      value: 39.62658333333333
-    - type: mrr_at_1
-      value: 35.584
-    - type: mrr_at_10
-      value: 45.4675
-    - type: mrr_at_100
-      value: 46.31016666666667
-    - type: mrr_at_1000
-      value: 46.35191666666666
-    - type: mrr_at_3
-      value: 42.86674999999999
-    - type: mrr_at_5
-      value: 44.31341666666666
-    - type: ndcg_at_1
-      value: 35.584
-    - type: ndcg_at_10
-      value: 47.26516666666667
-    - type: ndcg_at_100
-      value: 52.49108333333332
-    - type: ndcg_at_1000
-      value: 54.24575
-    - type: ndcg_at_3
-      value: 41.83433333333334
-    - type: ndcg_at_5
-      value: 44.29899999999999
-    - type: precision_at_1
-      value: 35.584
-    - type: precision_at_10
-      value: 8.390333333333334
-    - type: precision_at_100
-      value: 1.2941666666666667
-    - type: precision_at_1000
-      value: 0.16308333333333336
-    - type: precision_at_3
-      value: 19.414583333333333
-    - type: precision_at_5
-      value: 13.751
-    - type: recall_at_1
-      value: 30.082666666666665
-    - type: recall_at_10
-      value: 60.88875
-    - type: recall_at_100
-      value: 83.35141666666667
-    - type: recall_at_1000
-      value: 95.0805
-    - type: recall_at_3
-      value: 45.683749999999996
-    - type: recall_at_5
-      value: 52.08208333333333
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-stats
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
-    metrics:
-    - type: map_at_1
-      value: 26.33
-    - type: map_at_10
-      value: 35.762
-    - type: map_at_100
-      value: 36.873
-    - type: map_at_1000
-      value: 36.961
-    - type: map_at_3
-      value: 33.097
-    - type: map_at_5
-      value: 34.526
-    - type: mrr_at_1
-      value: 29.755
-    - type: mrr_at_10
-      value: 38.699
-    - type: mrr_at_100
-      value: 39.556000000000004
-    - type: mrr_at_1000
-      value: 39.611000000000004
-    - type: mrr_at_3
-      value: 36.120000000000005
-    - type: mrr_at_5
-      value: 37.523
-    - type: ndcg_at_1
-      value: 29.755
-    - type: ndcg_at_10
-      value: 41.193999999999996
-    - type: ndcg_at_100
-      value: 46.26
-    - type: ndcg_at_1000
-      value: 48.321
-    - type: ndcg_at_3
-      value: 36.152
-    - type: ndcg_at_5
-      value: 38.478
-    - type: precision_at_1
-      value: 29.755
-    - type: precision_at_10
-      value: 6.7330000000000005
-    - type: precision_at_100
-      value: 1.012
-    - type: precision_at_1000
-      value: 0.126
-    - type: precision_at_3
-      value: 15.951
-    - type: precision_at_5
-      value: 11.258
-    - type: recall_at_1
-      value: 26.33
-    - type: recall_at_10
-      value: 54.856
-    - type: recall_at_100
-      value: 77.45100000000001
-    - type: recall_at_1000
-      value: 92.483
-    - type: recall_at_3
-      value: 40.924
-    - type: recall_at_5
-      value: 46.581
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-tex
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: 46989137a86843e03a6195de44b09deda022eec7
-    metrics:
-    - type: map_at_1
-      value: 20.4
-    - type: map_at_10
-      value: 29.483999999999998
-    - type: map_at_100
-      value: 30.75
-    - type: map_at_1000
-      value: 30.869000000000003
-    - type: map_at_3
-      value: 26.533
-    - type: map_at_5
-      value: 28.192
-    - type: mrr_at_1
-      value: 24.914
-    - type: mrr_at_10
-      value: 33.844
-    - type: mrr_at_100
-      value: 34.787
-    - type: mrr_at_1000
-      value: 34.853
-    - type: mrr_at_3
-      value: 31.223
-    - type: mrr_at_5
-      value: 32.718
-    - type: ndcg_at_1
-      value: 24.914
-    - type: ndcg_at_10
-      value: 35.118
-    - type: ndcg_at_100
-      value: 40.729
-    - type: ndcg_at_1000
-      value: 43.25
-    - type: ndcg_at_3
-      value: 30.011
-    - type: ndcg_at_5
-      value: 32.416
-    - type: precision_at_1
-      value: 24.914
-    - type: precision_at_10
-      value: 6.483
-    - type: precision_at_100
-      value: 1.082
-    - type: precision_at_1000
-      value: 0.148
-    - type: precision_at_3
-      value: 14.280999999999999
-    - type: precision_at_5
-      value: 10.440000000000001
-    - type: recall_at_1
-      value: 20.4
-    - type: recall_at_10
-      value: 47.717
-    - type: recall_at_100
-      value: 72.444
-    - type: recall_at_1000
-      value: 89.97800000000001
-    - type: recall_at_3
-      value: 33.428999999999995
-    - type: recall_at_5
-      value: 39.662
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-unix
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
-    metrics:
-    - type: map_at_1
-      value: 30.896
-    - type: map_at_10
-      value: 41.981
-    - type: map_at_100
-      value: 43.238
-    - type: map_at_1000
-      value: 43.325
-    - type: map_at_3
-      value: 38.66
-    - type: map_at_5
-      value: 40.502
-    - type: mrr_at_1
-      value: 36.66
-    - type: mrr_at_10
-      value: 46.544999999999995
-    - type: mrr_at_100
-      value: 47.412
-    - type: mrr_at_1000
-      value: 47.46
-    - type: mrr_at_3
-      value: 43.812
-    - type: mrr_at_5
-      value: 45.403
-    - type: ndcg_at_1
-      value: 36.66
-    - type: ndcg_at_10
-      value: 48.113
-    - type: ndcg_at_100
-      value: 53.476
-    - type: ndcg_at_1000
-      value: 55.206999999999994
-    - type: ndcg_at_3
-      value: 42.522
-    - type: ndcg_at_5
-      value: 45.132
-    - type: precision_at_1
-      value: 36.66
-    - type: precision_at_10
-      value: 8.274
-    - type: precision_at_100
-      value: 1.2229999999999999
-    - type: precision_at_1000
-      value: 0.147
-    - type: precision_at_3
-      value: 19.527
-    - type: precision_at_5
-      value: 13.750000000000002
-    - type: recall_at_1
-      value: 30.896
-    - type: recall_at_10
-      value: 62.150000000000006
-    - type: recall_at_100
-      value: 84.921
-    - type: recall_at_1000
-      value: 96.394
-    - type: recall_at_3
-      value: 46.596
-    - type: recall_at_5
-      value: 53.410000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-webmasters
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
-    metrics:
-    - type: map_at_1
-      value: 28.965000000000003
-    - type: map_at_10
-      value: 39.394
-    - type: map_at_100
-      value: 41.077999999999996
-    - type: map_at_1000
-      value: 41.332
-    - type: map_at_3
-      value: 35.876999999999995
-    - type: map_at_5
-      value: 37.649
-    - type: mrr_at_1
-      value: 33.992
-    - type: mrr_at_10
-      value: 43.462
-    - type: mrr_at_100
-      value: 44.388
-    - type: mrr_at_1000
-      value: 44.433
-    - type: mrr_at_3
-      value: 40.711000000000006
-    - type: mrr_at_5
-      value: 41.996
-    - type: ndcg_at_1
-      value: 33.992
-    - type: ndcg_at_10
-      value: 45.997
-    - type: ndcg_at_100
-      value: 51.681
-    - type: ndcg_at_1000
-      value: 53.825
-    - type: ndcg_at_3
-      value: 40.481
-    - type: ndcg_at_5
-      value: 42.611
-    - type: precision_at_1
-      value: 33.992
-    - type: precision_at_10
-      value: 8.972
-    - type: precision_at_100
-      value: 1.717
-    - type: precision_at_1000
-      value: 0.255
-    - type: precision_at_3
-      value: 19.17
-    - type: precision_at_5
-      value: 13.715
-    - type: recall_at_1
-      value: 28.965000000000003
-    - type: recall_at_10
-      value: 59.179
-    - type: recall_at_100
-      value: 84.493
-    - type: recall_at_1000
-      value: 97.36399999999999
-    - type: recall_at_3
-      value: 42.897
-    - type: recall_at_5
-      value: 48.957
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-wordpress
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
-    metrics:
-    - type: map_at_1
-      value: 23.990000000000002
-    - type: map_at_10
-      value: 33.883
-    - type: map_at_100
-      value: 34.954
-    - type: map_at_1000
-      value: 35.045
-    - type: map_at_3
-      value: 31.368000000000002
-    - type: map_at_5
-      value: 32.751999999999995
-    - type: mrr_at_1
-      value: 26.247999999999998
-    - type: mrr_at_10
-      value: 36.166
-    - type: mrr_at_100
-      value: 37.124
-    - type: mrr_at_1000
-      value: 37.178
-    - type: mrr_at_3
-      value: 33.949
-    - type: mrr_at_5
-      value: 35.197
-    - type: ndcg_at_1
-      value: 26.247999999999998
-    - type: ndcg_at_10
-      value: 39.263999999999996
-    - type: ndcg_at_100
-      value: 44.59
-    - type: ndcg_at_1000
-      value: 46.619
-    - type: ndcg_at_3
-      value: 34.444
-    - type: ndcg_at_5
-      value: 36.721
-    - type: precision_at_1
-      value: 26.247999999999998
-    - type: precision_at_10
-      value: 6.211
-    - type: precision_at_100
-      value: 0.9610000000000001
-    - type: precision_at_1000
-      value: 0.125
-    - type: precision_at_3
-      value: 15.096000000000002
-    - type: precision_at_5
-      value: 10.499
-    - type: recall_at_1
-      value: 23.990000000000002
-    - type: recall_at_10
-      value: 53.492
-    - type: recall_at_100
-      value: 77.955
-    - type: recall_at_1000
-      value: 92.81700000000001
-    - type: recall_at_3
-      value: 40.277
-    - type: recall_at_5
-      value: 45.812999999999995
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
-    metrics:
-    - type: map_at_1
-      value: 16.747
-    - type: map_at_10
-      value: 29.168
-    - type: map_at_100
-      value: 31.304
-    - type: map_at_1000
-      value: 31.496000000000002
-    - type: map_at_3
-      value: 24.57
-    - type: map_at_5
-      value: 26.886
-    - type: mrr_at_1
-      value: 37.524
-    - type: mrr_at_10
-      value: 50.588
-    - type: mrr_at_100
-      value: 51.28
-    - type: mrr_at_1000
-      value: 51.29899999999999
-    - type: mrr_at_3
-      value: 47.438
-    - type: mrr_at_5
-      value: 49.434
-    - type: ndcg_at_1
-      value: 37.524
-    - type: ndcg_at_10
-      value: 39.11
-    - type: ndcg_at_100
-      value: 46.373999999999995
-    - type: ndcg_at_1000
-      value: 49.370999999999995
-    - type: ndcg_at_3
-      value: 32.964
-    - type: ndcg_at_5
-      value: 35.028
-    - type: precision_at_1
-      value: 37.524
-    - type: precision_at_10
-      value: 12.137
-    - type: precision_at_100
-      value: 1.9929999999999999
-    - type: precision_at_1000
-      value: 0.256
-    - type: precision_at_3
-      value: 24.886
-    - type: precision_at_5
-      value: 18.762
-    - type: recall_at_1
-      value: 16.747
-    - type: recall_at_10
-      value: 45.486
-    - type: recall_at_100
-      value: 69.705
-    - type: recall_at_1000
-      value: 86.119
-    - type: recall_at_3
-      value: 30.070999999999998
-    - type: recall_at_5
-      value: 36.565
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/dbpedia
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
-    metrics:
-    - type: map_at_1
-      value: 10.495000000000001
-    - type: map_at_10
-      value: 24.005000000000003
-    - type: map_at_100
-      value: 34.37
-    - type: map_at_1000
-      value: 36.268
-    - type: map_at_3
-      value: 16.694
-    - type: map_at_5
-      value: 19.845
-    - type: mrr_at_1
-      value: 75.5
-    - type: mrr_at_10
-      value: 82.458
-    - type: mrr_at_100
-      value: 82.638
-    - type: mrr_at_1000
-      value: 82.64
-    - type: mrr_at_3
-      value: 81.25
-    - type: mrr_at_5
-      value: 82.125
-    - type: ndcg_at_1
-      value: 64.625
-    - type: ndcg_at_10
-      value: 51.322
-    - type: ndcg_at_100
-      value: 55.413999999999994
-    - type: ndcg_at_1000
-      value: 62.169
-    - type: ndcg_at_3
-      value: 56.818999999999996
-    - type: ndcg_at_5
-      value: 54.32900000000001
-    - type: precision_at_1
-      value: 75.5
-    - type: precision_at_10
-      value: 40.849999999999994
-    - type: precision_at_100
-      value: 12.882
-    - type: precision_at_1000
-      value: 2.394
-    - type: precision_at_3
-      value: 59.667
-    - type: precision_at_5
-      value: 52.2
-    - type: recall_at_1
-      value: 10.495000000000001
-    - type: recall_at_10
-      value: 29.226000000000003
-    - type: recall_at_100
-      value: 59.614
-    - type: recall_at_1000
-      value: 81.862
-    - type: recall_at_3
-      value: 17.97
-    - type: recall_at_5
-      value: 22.438
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 51.82
-    - type: f1
-      value: 47.794956731921054
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
-    metrics:
-    - type: map_at_1
-      value: 82.52199999999999
-    - type: map_at_10
-      value: 89.794
-    - type: map_at_100
-      value: 89.962
-    - type: map_at_1000
-      value: 89.972
-    - type: map_at_3
-      value: 88.95100000000001
-    - type: map_at_5
-      value: 89.524
-    - type: mrr_at_1
-      value: 88.809
-    - type: mrr_at_10
-      value: 93.554
-    - type: mrr_at_100
-      value: 93.577
-    - type: mrr_at_1000
-      value: 93.577
-    - type: mrr_at_3
-      value: 93.324
-    - type: mrr_at_5
-      value: 93.516
-    - type: ndcg_at_1
-      value: 88.809
-    - type: ndcg_at_10
-      value: 92.419
-    - type: ndcg_at_100
-      value: 92.95
-    - type: ndcg_at_1000
-      value: 93.10000000000001
-    - type: ndcg_at_3
-      value: 91.45299999999999
-    - type: ndcg_at_5
-      value: 92.05
-    - type: precision_at_1
-      value: 88.809
-    - type: precision_at_10
-      value: 10.911999999999999
-    - type: precision_at_100
-      value: 1.143
-    - type: precision_at_1000
-      value: 0.117
-    - type: precision_at_3
-      value: 34.623
-    - type: precision_at_5
-      value: 21.343999999999998
-    - type: recall_at_1
-      value: 82.52199999999999
-    - type: recall_at_10
-      value: 96.59400000000001
-    - type: recall_at_100
-      value: 98.55699999999999
-    - type: recall_at_1000
-      value: 99.413
-    - type: recall_at_3
-      value: 94.02199999999999
-    - type: recall_at_5
-      value: 95.582
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
-    metrics:
-    - type: map_at_1
-      value: 32.842
-    - type: map_at_10
-      value: 53.147
-    - type: map_at_100
-      value: 55.265
-    - type: map_at_1000
-      value: 55.37
-    - type: map_at_3
-      value: 46.495
-    - type: map_at_5
-      value: 50.214999999999996
-    - type: mrr_at_1
-      value: 61.574
-    - type: mrr_at_10
-      value: 68.426
-    - type: mrr_at_100
-      value: 68.935
-    - type: mrr_at_1000
-      value: 68.95400000000001
-    - type: mrr_at_3
-      value: 66.307
-    - type: mrr_at_5
-      value: 67.611
-    - type: ndcg_at_1
-      value: 61.574
-    - type: ndcg_at_10
-      value: 61.205
-    - type: ndcg_at_100
-      value: 67.25999999999999
-    - type: ndcg_at_1000
-      value: 68.657
-    - type: ndcg_at_3
-      value: 56.717
-    - type: ndcg_at_5
-      value: 58.196999999999996
-    - type: precision_at_1
-      value: 61.574
-    - type: precision_at_10
-      value: 16.852
-    - type: precision_at_100
-      value: 2.33
-    - type: precision_at_1000
-      value: 0.256
-    - type: precision_at_3
-      value: 37.5
-    - type: precision_at_5
-      value: 27.468999999999998
-    - type: recall_at_1
-      value: 32.842
-    - type: recall_at_10
-      value: 68.157
-    - type: recall_at_100
-      value: 89.5
-    - type: recall_at_1000
-      value: 97.68599999999999
-    - type: recall_at_3
-      value: 50.783
-    - type: recall_at_5
-      value: 58.672000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: ab518f4d6fcca38d87c25209f94beba119d02014
-    metrics:
-    - type: map_at_1
-      value: 39.068000000000005
-    - type: map_at_10
-      value: 69.253
-    - type: map_at_100
-      value: 70.036
-    - type: map_at_1000
-      value: 70.081
-    - type: map_at_3
-      value: 65.621
-    - type: map_at_5
-      value: 67.976
-    - type: mrr_at_1
-      value: 78.13600000000001
-    - type: mrr_at_10
-      value: 84.328
-    - type: mrr_at_100
-      value: 84.515
-    - type: mrr_at_1000
-      value: 84.52300000000001
-    - type: mrr_at_3
-      value: 83.52199999999999
-    - type: mrr_at_5
-      value: 84.019
-    - type: ndcg_at_1
-      value: 78.13600000000001
-    - type: ndcg_at_10
-      value: 76.236
-    - type: ndcg_at_100
-      value: 78.891
-    - type: ndcg_at_1000
-      value: 79.73400000000001
-    - type: ndcg_at_3
-      value: 71.258
-    - type: ndcg_at_5
-      value: 74.129
-    - type: precision_at_1
-      value: 78.13600000000001
-    - type: precision_at_10
-      value: 16.347
-    - type: precision_at_100
-      value: 1.839
-    - type: precision_at_1000
-      value: 0.19499999999999998
-    - type: precision_at_3
-      value: 47.189
-    - type: precision_at_5
-      value: 30.581999999999997
-    - type: recall_at_1
-      value: 39.068000000000005
-    - type: recall_at_10
-      value: 81.735
-    - type: recall_at_100
-      value: 91.945
-    - type: recall_at_1000
-      value: 97.44800000000001
-    - type: recall_at_3
-      value: 70.783
-    - type: recall_at_5
-      value: 76.455
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 94.7764
-    - type: ap
-      value: 92.67841294818406
-    - type: f1
-      value: 94.77375157383646
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: c5a29a104738b98a9e76336939199e264163d4a0
-    metrics:
-    - type: map_at_1
-      value: 24.624
-    - type: map_at_10
-      value: 37.861
-    - type: map_at_100
-      value: 39.011
-    - type: map_at_1000
-      value: 39.052
-    - type: map_at_3
-      value: 33.76
-    - type: map_at_5
-      value: 36.153
-    - type: mrr_at_1
-      value: 25.358000000000004
-    - type: mrr_at_10
-      value: 38.5
-    - type: mrr_at_100
-      value: 39.572
-    - type: mrr_at_1000
-      value: 39.607
-    - type: mrr_at_3
-      value: 34.491
-    - type: mrr_at_5
-      value: 36.83
-    - type: ndcg_at_1
-      value: 25.358000000000004
-    - type: ndcg_at_10
-      value: 45.214999999999996
-    - type: ndcg_at_100
-      value: 50.56
-    - type: ndcg_at_1000
-      value: 51.507999999999996
-    - type: ndcg_at_3
-      value: 36.925999999999995
-    - type: ndcg_at_5
-      value: 41.182
-    - type: precision_at_1
-      value: 25.358000000000004
-    - type: precision_at_10
-      value: 7.090000000000001
-    - type: precision_at_100
-      value: 0.9740000000000001
-    - type: precision_at_1000
-      value: 0.106
-    - type: precision_at_3
-      value: 15.697
-    - type: precision_at_5
-      value: 11.599
-    - type: recall_at_1
-      value: 24.624
-    - type: recall_at_10
-      value: 67.78699999999999
-    - type: recall_at_100
-      value: 92.11200000000001
-    - type: recall_at_1000
-      value: 99.208
-    - type: recall_at_3
-      value: 45.362
-    - type: recall_at_5
-      value: 55.58
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 96.83310533515733
-    - type: f1
-      value: 96.57069781347995
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 89.5690834473324
-    - type: f1
-      value: 73.7275204564728
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 82.67316745124411
-    - type: f1
-      value: 79.70626515721662
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 85.01344989912575
-    - type: f1
-      value: 84.45181022816965
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 37.843426126777295
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 36.651728547241476
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 32.05750522793288
-    - type: mrr
-      value: 33.28067556869468
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
-    metrics:
-    - type: map_at_1
-      value: 6.744
-    - type: map_at_10
-      value: 16.235
-    - type: map_at_100
-      value: 20.767
-    - type: map_at_1000
-      value: 22.469
-    - type: map_at_3
-      value: 11.708
-    - type: map_at_5
-      value: 13.924
-    - type: mrr_at_1
-      value: 55.728
-    - type: mrr_at_10
-      value: 63.869
-    - type: mrr_at_100
-      value: 64.322
-    - type: mrr_at_1000
-      value: 64.342
-    - type: mrr_at_3
-      value: 62.022999999999996
-    - type: mrr_at_5
-      value: 63.105999999999995
-    - type: ndcg_at_1
-      value: 53.096
-    - type: ndcg_at_10
-      value: 41.618
-    - type: ndcg_at_100
-      value: 38.562999999999995
-    - type: ndcg_at_1000
-      value: 47.006
-    - type: ndcg_at_3
-      value: 47.657
-    - type: ndcg_at_5
-      value: 45.562999999999995
-    - type: precision_at_1
-      value: 55.108000000000004
-    - type: precision_at_10
-      value: 30.464000000000002
-    - type: precision_at_100
-      value: 9.737
-    - type: precision_at_1000
-      value: 2.2720000000000002
-    - type: precision_at_3
-      value: 44.376
-    - type: precision_at_5
-      value: 39.505
-    - type: recall_at_1
-      value: 6.744
-    - type: recall_at_10
-      value: 21.11
-    - type: recall_at_100
-      value: 39.69
-    - type: recall_at_1000
-      value: 70.44
-    - type: recall_at_3
-      value: 13.120000000000001
-    - type: recall_at_5
-      value: 16.669
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
-    metrics:
-    - type: map_at_1
-      value: 46.263
-    - type: map_at_10
-      value: 63.525
-    - type: map_at_100
-      value: 64.142
-    - type: map_at_1000
-      value: 64.14800000000001
-    - type: map_at_3
-      value: 59.653
-    - type: map_at_5
-      value: 62.244
-    - type: mrr_at_1
-      value: 51.796
-    - type: mrr_at_10
-      value: 65.764
-    - type: mrr_at_100
-      value: 66.155
-    - type: mrr_at_1000
-      value: 66.158
-    - type: mrr_at_3
-      value: 63.05500000000001
-    - type: mrr_at_5
-      value: 64.924
-    - type: ndcg_at_1
-      value: 51.766999999999996
-    - type: ndcg_at_10
-      value: 70.626
-    - type: ndcg_at_100
-      value: 72.905
-    - type: ndcg_at_1000
-      value: 73.021
-    - type: ndcg_at_3
-      value: 63.937999999999995
-    - type: ndcg_at_5
-      value: 68.00699999999999
-    - type: precision_at_1
-      value: 51.766999999999996
-    - type: precision_at_10
-      value: 10.768
-    - type: precision_at_100
-      value: 1.203
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 28.409000000000002
-    - type: precision_at_5
-      value: 19.502
-    - type: recall_at_1
-      value: 46.263
-    - type: recall_at_10
-      value: 89.554
-    - type: recall_at_100
-      value: 98.914
-    - type: recall_at_1000
-      value: 99.754
-    - type: recall_at_3
-      value: 72.89999999999999
-    - type: recall_at_5
-      value: 82.1
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
-    metrics:
-    - type: map_at_1
-      value: 72.748
-    - type: map_at_10
-      value: 86.87700000000001
-    - type: map_at_100
-      value: 87.46199999999999
-    - type: map_at_1000
-      value: 87.47399999999999
-    - type: map_at_3
-      value: 83.95700000000001
-    - type: map_at_5
-      value: 85.82300000000001
-    - type: mrr_at_1
-      value: 83.62
-    - type: mrr_at_10
-      value: 89.415
-    - type: mrr_at_100
-      value: 89.484
-    - type: mrr_at_1000
-      value: 89.484
-    - type: mrr_at_3
-      value: 88.633
-    - type: mrr_at_5
-      value: 89.176
-    - type: ndcg_at_1
-      value: 83.62
-    - type: ndcg_at_10
-      value: 90.27
-    - type: ndcg_at_100
-      value: 91.23599999999999
-    - type: ndcg_at_1000
-      value: 91.293
-    - type: ndcg_at_3
-      value: 87.69500000000001
-    - type: ndcg_at_5
-      value: 89.171
-    - type: precision_at_1
-      value: 83.62
-    - type: precision_at_10
-      value: 13.683
-    - type: precision_at_100
-      value: 1.542
-    - type: precision_at_1000
-      value: 0.157
-    - type: precision_at_3
-      value: 38.363
-    - type: precision_at_5
-      value: 25.196
-    - type: recall_at_1
-      value: 72.748
-    - type: recall_at_10
-      value: 96.61699999999999
-    - type: recall_at_100
-      value: 99.789
-    - type: recall_at_1000
-      value: 99.997
-    - type: recall_at_3
-      value: 89.21
-    - type: recall_at_5
-      value: 93.418
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 61.51909029379199
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
-    metrics:
-    - type: v_measure
-      value: 68.24483162045645
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
-    metrics:
-    - type: map_at_1
-      value: 4.793
-    - type: map_at_10
-      value: 13.092
-    - type: map_at_100
-      value: 15.434000000000001
-    - type: map_at_1000
-      value: 15.748999999999999
-    - type: map_at_3
-      value: 9.139
-    - type: map_at_5
-      value: 11.033
-    - type: mrr_at_1
-      value: 23.599999999999998
-    - type: mrr_at_10
-      value: 35.892
-    - type: mrr_at_100
-      value: 36.962
-    - type: mrr_at_1000
-      value: 37.009
-    - type: mrr_at_3
-      value: 32.550000000000004
-    - type: mrr_at_5
-      value: 34.415
-    - type: ndcg_at_1
-      value: 23.599999999999998
-    - type: ndcg_at_10
-      value: 21.932
-    - type: ndcg_at_100
-      value: 30.433
-    - type: ndcg_at_1000
-      value: 35.668
-    - type: ndcg_at_3
-      value: 20.483999999999998
-    - type: ndcg_at_5
-      value: 17.964
-    - type: precision_at_1
-      value: 23.599999999999998
-    - type: precision_at_10
-      value: 11.63
-    - type: precision_at_100
-      value: 2.383
-    - type: precision_at_1000
-      value: 0.363
-    - type: precision_at_3
-      value: 19.567
-    - type: precision_at_5
-      value: 16.06
-    - type: recall_at_1
-      value: 4.793
-    - type: recall_at_10
-      value: 23.558
-    - type: recall_at_100
-      value: 48.376999999999995
-    - type: recall_at_1000
-      value: 73.75699999999999
-    - type: recall_at_3
-      value: 11.903
-    - type: recall_at_5
-      value: 16.278000000000002
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
-    metrics:
-    - type: cos_sim_pearson
-      value: 87.31937967632581
-    - type: cos_sim_spearman
-      value: 84.30523596401186
-    - type: euclidean_pearson
-      value: 84.19537987069458
-    - type: euclidean_spearman
-      value: 84.30522052876
-    - type: manhattan_pearson
-      value: 84.16420807244911
-    - type: manhattan_spearman
-      value: 84.28515410219309
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_pearson
-      value: 86.17180810119646
-    - type: cos_sim_spearman
-      value: 78.44413657529002
-    - type: euclidean_pearson
-      value: 81.69054139101816
-    - type: euclidean_spearman
-      value: 78.44412412142488
-    - type: manhattan_pearson
-      value: 82.04975789626462
-    - type: manhattan_spearman
-      value: 78.78390856857253
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_pearson
-      value: 88.35737871089687
-    - type: cos_sim_spearman
-      value: 88.26850223126127
-    - type: euclidean_pearson
-      value: 87.44100858335746
-    - type: euclidean_spearman
-      value: 88.26850223126127
-    - type: manhattan_pearson
-      value: 87.61572015772133
-    - type: manhattan_spearman
-      value: 88.56229552813319
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_pearson
-      value: 86.8395966764906
-    - type: cos_sim_spearman
-      value: 84.49441798385489
-    - type: euclidean_pearson
-      value: 85.3259176121388
-    - type: euclidean_spearman
-      value: 84.49442124804686
-    - type: manhattan_pearson
-      value: 85.35153862806513
-    - type: manhattan_spearman
-      value: 84.60094577432503
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_pearson
-      value: 90.14048269057345
-    - type: cos_sim_spearman
-      value: 90.27866978947013
-    - type: euclidean_pearson
-      value: 89.35308361940393
-    - type: euclidean_spearman
-      value: 90.27866978947013
-    - type: manhattan_pearson
-      value: 89.37601244066997
-    - type: manhattan_spearman
-      value: 90.42707449698062
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_pearson
-      value: 86.8522678865688
-    - type: cos_sim_spearman
-      value: 87.37396401580446
-    - type: euclidean_pearson
-      value: 86.37219665505377
-    - type: euclidean_spearman
-      value: 87.37396385867791
-    - type: manhattan_pearson
-      value: 86.44628823799896
-    - type: manhattan_spearman
-      value: 87.49116026788859
-  - 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: 92.94248481968916
-    - type: cos_sim_spearman
-      value: 92.68185242943188
-    - type: euclidean_pearson
-      value: 92.33802342092979
-    - type: euclidean_spearman
-      value: 92.68185242943188
-    - type: manhattan_pearson
-      value: 92.2011323340474
-    - type: manhattan_spearman
-      value: 92.43364757640346
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts22-crosslingual-sts
-      name: MTEB STS22 (en)
-      config: en
-      split: test
-      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
-    metrics:
-    - type: cos_sim_pearson
-      value: 70.2918782293091
-    - type: cos_sim_spearman
-      value: 68.61986257003369
-    - type: euclidean_pearson
-      value: 70.51920905899138
-    - type: euclidean_spearman
-      value: 68.61986257003369
-    - type: manhattan_pearson
-      value: 70.64673843811433
-    - type: manhattan_spearman
-      value: 68.86711466517345
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_pearson
-      value: 88.62956838105524
-    - type: cos_sim_spearman
-      value: 88.80650007123052
-    - type: euclidean_pearson
-      value: 88.37976252122822
-    - type: euclidean_spearman
-      value: 88.80650007123052
-    - type: manhattan_pearson
-      value: 88.49866938476616
-    - type: manhattan_spearman
-      value: 89.02489665452616
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 86.40175229911527
-    - type: mrr
-      value: 96.61958230585682
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: 0228b52cf27578f30900b9e5271d331663a030d7
-    metrics:
-    - type: map_at_1
-      value: 63.05
-    - type: map_at_10
-      value: 73.844
-    - type: map_at_100
-      value: 74.313
-    - type: map_at_1000
-      value: 74.321
-    - type: map_at_3
-      value: 71.17999999999999
-    - type: map_at_5
-      value: 72.842
-    - type: mrr_at_1
-      value: 65.667
-    - type: mrr_at_10
-      value: 74.772
-    - type: mrr_at_100
-      value: 75.087
-    - type: mrr_at_1000
-      value: 75.095
-    - type: mrr_at_3
-      value: 72.944
-    - type: mrr_at_5
-      value: 74.078
-    - type: ndcg_at_1
-      value: 65.667
-    - type: ndcg_at_10
-      value: 78.31700000000001
-    - type: ndcg_at_100
-      value: 79.969
-    - type: ndcg_at_1000
-      value: 80.25
-    - type: ndcg_at_3
-      value: 74.099
-    - type: ndcg_at_5
-      value: 76.338
-    - type: precision_at_1
-      value: 65.667
-    - type: precision_at_10
-      value: 10.233
-    - type: precision_at_100
-      value: 1.107
-    - type: precision_at_1000
-      value: 0.11299999999999999
-    - type: precision_at_3
-      value: 28.889
-    - type: precision_at_5
-      value: 19.0
-    - type: recall_at_1
-      value: 63.05
-    - type: recall_at_10
-      value: 90.822
-    - type: recall_at_100
-      value: 97.667
-    - type: recall_at_1000
-      value: 100.0
-    - type: recall_at_3
-      value: 79.489
-    - type: recall_at_5
-      value: 85.161
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.83564356435643
-    - type: cos_sim_ap
-      value: 96.10619363017767
-    - type: cos_sim_f1
-      value: 91.61225514816677
-    - type: cos_sim_precision
-      value: 92.02825428859738
-    - type: cos_sim_recall
-      value: 91.2
-    - type: dot_accuracy
-      value: 99.83564356435643
-    - type: dot_ap
-      value: 96.10619363017767
-    - type: dot_f1
-      value: 91.61225514816677
-    - type: dot_precision
-      value: 92.02825428859738
-    - type: dot_recall
-      value: 91.2
-    - type: euclidean_accuracy
-      value: 99.83564356435643
-    - type: euclidean_ap
-      value: 96.10619363017769
-    - type: euclidean_f1
-      value: 91.61225514816677
-    - type: euclidean_precision
-      value: 92.02825428859738
-    - type: euclidean_recall
-      value: 91.2
-    - type: manhattan_accuracy
-      value: 99.84158415841584
-    - type: manhattan_ap
-      value: 96.27527798658713
-    - type: manhattan_f1
-      value: 92.0
-    - type: manhattan_precision
-      value: 92.0
-    - type: manhattan_recall
-      value: 92.0
-    - type: max_accuracy
-      value: 99.84158415841584
-    - type: max_ap
-      value: 96.27527798658713
-    - type: max_f1
-      value: 92.0
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 76.93753872885304
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 46.044085080870126
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 55.885129730227256
-    - type: mrr
-      value: 56.95062494694848
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 31.202047940935508
-    - type: cos_sim_spearman
-      value: 30.984832035722228
-    - type: dot_pearson
-      value: 31.20204247226978
-    - type: dot_spearman
-      value: 30.984832035722228
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
-    metrics:
-    - type: map_at_1
-      value: 0.245
-    - type: map_at_10
-      value: 2.249
-    - type: map_at_100
-      value: 14.85
-    - type: map_at_1000
-      value: 36.596000000000004
-    - type: map_at_3
-      value: 0.717
-    - type: map_at_5
-      value: 1.18
-    - type: mrr_at_1
-      value: 94.0
-    - type: mrr_at_10
-      value: 96.167
-    - type: mrr_at_100
-      value: 96.167
-    - type: mrr_at_1000
-      value: 96.167
-    - type: mrr_at_3
-      value: 95.667
-    - type: mrr_at_5
-      value: 96.167
-    - type: ndcg_at_1
-      value: 91.0
-    - type: ndcg_at_10
-      value: 87.09700000000001
-    - type: ndcg_at_100
-      value: 69.637
-    - type: ndcg_at_1000
-      value: 62.257
-    - type: ndcg_at_3
-      value: 90.235
-    - type: ndcg_at_5
-      value: 89.51400000000001
-    - type: precision_at_1
-      value: 94.0
-    - type: precision_at_10
-      value: 90.60000000000001
-    - type: precision_at_100
-      value: 71.38
-    - type: precision_at_1000
-      value: 27.400000000000002
-    - type: precision_at_3
-      value: 94.0
-    - type: precision_at_5
-      value: 93.2
-    - type: recall_at_1
-      value: 0.245
-    - type: recall_at_10
-      value: 2.366
-    - type: recall_at_100
-      value: 17.491
-    - type: recall_at_1000
-      value: 58.772999999999996
-    - type: recall_at_3
-      value: 0.7270000000000001
-    - type: recall_at_5
-      value: 1.221
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
-    metrics:
-    - type: map_at_1
-      value: 3.435
-    - type: map_at_10
-      value: 12.147
-    - type: map_at_100
-      value: 18.724
-    - type: map_at_1000
-      value: 20.426
-    - type: map_at_3
-      value: 6.526999999999999
-    - type: map_at_5
-      value: 9.198
-    - type: mrr_at_1
-      value: 48.980000000000004
-    - type: mrr_at_10
-      value: 62.970000000000006
-    - type: mrr_at_100
-      value: 63.288999999999994
-    - type: mrr_at_1000
-      value: 63.288999999999994
-    - type: mrr_at_3
-      value: 59.184000000000005
-    - type: mrr_at_5
-      value: 61.224000000000004
-    - type: ndcg_at_1
-      value: 46.939
-    - type: ndcg_at_10
-      value: 30.61
-    - type: ndcg_at_100
-      value: 41.683
-    - type: ndcg_at_1000
-      value: 53.144000000000005
-    - type: ndcg_at_3
-      value: 36.284
-    - type: ndcg_at_5
-      value: 34.345
-    - type: precision_at_1
-      value: 48.980000000000004
-    - type: precision_at_10
-      value: 26.122
-    - type: precision_at_100
-      value: 8.204
-    - type: precision_at_1000
-      value: 1.6019999999999999
-    - type: precision_at_3
-      value: 35.374
-    - type: precision_at_5
-      value: 32.653
-    - type: recall_at_1
-      value: 3.435
-    - type: recall_at_10
-      value: 18.953
-    - type: recall_at_100
-      value: 50.775000000000006
-    - type: recall_at_1000
-      value: 85.858
-    - type: recall_at_3
-      value: 7.813000000000001
-    - type: recall_at_5
-      value: 11.952
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
-    metrics:
-    - type: accuracy
-      value: 71.2938
-    - type: ap
-      value: 15.090139095602268
-    - type: f1
-      value: 55.23862650598296
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 64.7623089983022
-    - type: f1
-      value: 65.07617131099336
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 57.2988222684939
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 88.6034451928235
-    - type: cos_sim_ap
-      value: 81.51815279166863
-    - type: cos_sim_f1
-      value: 74.43794671864849
-    - type: cos_sim_precision
-      value: 73.34186939820742
-    - type: cos_sim_recall
-      value: 75.56728232189973
-    - type: dot_accuracy
-      value: 88.6034451928235
-    - type: dot_ap
-      value: 81.51816956866841
-    - type: dot_f1
-      value: 74.43794671864849
-    - type: dot_precision
-      value: 73.34186939820742
-    - type: dot_recall
-      value: 75.56728232189973
-    - type: euclidean_accuracy
-      value: 88.6034451928235
-    - type: euclidean_ap
-      value: 81.51817015121485
-    - type: euclidean_f1
-      value: 74.43794671864849
-    - type: euclidean_precision
-      value: 73.34186939820742
-    - type: euclidean_recall
-      value: 75.56728232189973
-    - type: manhattan_accuracy
-      value: 88.5736424867378
-    - type: manhattan_ap
-      value: 81.37610101292196
-    - type: manhattan_f1
-      value: 74.2504182215931
-    - type: manhattan_precision
-      value: 72.46922883697563
-    - type: manhattan_recall
-      value: 76.12137203166228
-    - type: max_accuracy
-      value: 88.6034451928235
-    - type: max_ap
-      value: 81.51817015121485
-    - type: max_f1
-      value: 74.43794671864849
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 89.53118329646446
-    - type: cos_sim_ap
-      value: 87.41972033060013
-    - type: cos_sim_f1
-      value: 79.4392523364486
-    - type: cos_sim_precision
-      value: 75.53457372951958
-    - type: cos_sim_recall
-      value: 83.7696335078534
-    - type: dot_accuracy
-      value: 89.53118329646446
-    - type: dot_ap
-      value: 87.41971646088945
-    - type: dot_f1
-      value: 79.4392523364486
-    - type: dot_precision
-      value: 75.53457372951958
-    - type: dot_recall
-      value: 83.7696335078534
-    - type: euclidean_accuracy
-      value: 89.53118329646446
-    - type: euclidean_ap
-      value: 87.41972415605997
-    - type: euclidean_f1
-      value: 79.4392523364486
-    - type: euclidean_precision
-      value: 75.53457372951958
-    - type: euclidean_recall
-      value: 83.7696335078534
-    - type: manhattan_accuracy
-      value: 89.5855163581325
-    - type: manhattan_ap
-      value: 87.51158697451964
-    - type: manhattan_f1
-      value: 79.54455087655883
-    - type: manhattan_precision
-      value: 74.96763643796416
-    - type: manhattan_recall
-      value: 84.71666153372344
-    - type: max_accuracy
-      value: 89.5855163581325
-    - type: max_ap
-      value: 87.51158697451964
-    - type: max_f1
-      value: 79.54455087655883
 language:
   - en
 license: cc-by-nc-4.0

 tags:
   - transformers
   - mteb
 language:
   - en
 license: cc-by-nc-4.0