Update README.md

README.md

@@ -2799,2811 +2799,9 @@ model-index:
     metrics:
     - type: v_measure
       value: 79.58576208710117
-
----
-tags:
-- mteb
-- arctic
-- arctic-embed
-model-index:
-- name: base
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 76.80597014925374
-    - type: ap
-      value: 39.31198155789558
-    - type: f1
-      value: 70.48198448222148
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 82.831525
-    - type: ap
-      value: 77.4474050181638
-    - type: f1
-      value: 82.77204845110204
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 38.93000000000001
-    - type: f1
-      value: 37.98013371053459
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
-    metrics:
-    - type: map_at_1
-      value: 31.223
-    - type: map_at_10
-      value: 47.43
-    - type: map_at_100
-      value: 48.208
-    - type: map_at_1000
-      value: 48.211
-    - type: map_at_3
-      value: 42.579
-    - type: map_at_5
-      value: 45.263999999999996
-    - type: mrr_at_1
-      value: 31.65
-    - type: mrr_at_10
-      value: 47.573
-    - type: mrr_at_100
-      value: 48.359
-    - type: mrr_at_1000
-      value: 48.362
-    - type: mrr_at_3
-      value: 42.734
-    - type: mrr_at_5
-      value: 45.415
-    - type: ndcg_at_1
-      value: 31.223
-    - type: ndcg_at_10
-      value: 56.436
-    - type: ndcg_at_100
-      value: 59.657000000000004
-    - type: ndcg_at_1000
-      value: 59.731
-    - type: ndcg_at_3
-      value: 46.327
-    - type: ndcg_at_5
-      value: 51.178000000000004
-    - type: precision_at_1
-      value: 31.223
-    - type: precision_at_10
-      value: 8.527999999999999
-    - type: precision_at_100
-      value: 0.991
-    - type: precision_at_1000
-      value: 0.1
-    - type: precision_at_3
-      value: 19.061
-    - type: precision_at_5
-      value: 13.797999999999998
-    - type: recall_at_1
-      value: 31.223
-    - type: recall_at_10
-      value: 85.277
-    - type: recall_at_100
-      value: 99.075
-    - type: recall_at_1000
-      value: 99.644
-    - type: recall_at_3
-      value: 57.18299999999999
-    - type: recall_at_5
-      value: 68.99
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 47.23625429411296
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 37.433880471403654
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 60.53175025582013
-    - type: mrr
-      value: 74.51160796728664
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_pearson
-      value: 88.93746103286769
-    - type: cos_sim_spearman
-      value: 86.62245567912619
-    - type: euclidean_pearson
-      value: 87.154173907501
-    - type: euclidean_spearman
-      value: 86.62245567912619
-    - type: manhattan_pearson
-      value: 87.17682026633462
-    - type: manhattan_spearman
-      value: 86.74775973908348
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 80.33766233766232
-    - type: f1
-      value: 79.64931422442245
-  - task:
-      type: Clustering
-    dataset:
-      type: jinaai/big-patent-clustering
-      name: MTEB BigPatentClustering
-      config: default
-      split: test
-      revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
-    metrics:
-    - type: v_measure
-      value: 19.116028913890613
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 36.966921852810174
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 31.98019698537654
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-android
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: f46a197baaae43b4f621051089b82a364682dfeb
-    metrics:
-    - type: map_at_1
-      value: 34.079
-    - type: map_at_10
-      value: 46.35
-    - type: map_at_100
-      value: 47.785
-    - type: map_at_1000
-      value: 47.903
-    - type: map_at_3
-      value: 42.620999999999995
-    - type: map_at_5
-      value: 44.765
-    - type: mrr_at_1
-      value: 41.345
-    - type: mrr_at_10
-      value: 52.032000000000004
-    - type: mrr_at_100
-      value: 52.690000000000005
-    - type: mrr_at_1000
-      value: 52.727999999999994
-    - type: mrr_at_3
-      value: 49.428
-    - type: mrr_at_5
-      value: 51.093999999999994
-    - type: ndcg_at_1
-      value: 41.345
-    - type: ndcg_at_10
-      value: 53.027
-    - type: ndcg_at_100
-      value: 57.962
-    - type: ndcg_at_1000
-      value: 59.611999999999995
-    - type: ndcg_at_3
-      value: 47.687000000000005
-    - type: ndcg_at_5
-      value: 50.367
-    - type: precision_at_1
-      value: 41.345
-    - type: precision_at_10
-      value: 10.157
-    - type: precision_at_100
-      value: 1.567
-    - type: precision_at_1000
-      value: 0.199
-    - type: precision_at_3
-      value: 23.081
-    - type: precision_at_5
-      value: 16.738
-    - type: recall_at_1
-      value: 34.079
-    - type: recall_at_10
-      value: 65.93900000000001
-    - type: recall_at_100
-      value: 86.42699999999999
-    - type: recall_at_1000
-      value: 96.61
-    - type: recall_at_3
-      value: 50.56699999999999
-    - type: recall_at_5
-      value: 57.82000000000001
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-english
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
-    metrics:
-    - type: map_at_1
-      value: 33.289
-    - type: map_at_10
-      value: 43.681
-    - type: map_at_100
-      value: 45.056000000000004
-    - type: map_at_1000
-      value: 45.171
-    - type: map_at_3
-      value: 40.702
-    - type: map_at_5
-      value: 42.292
-    - type: mrr_at_1
-      value: 41.146
-    - type: mrr_at_10
-      value: 49.604
-    - type: mrr_at_100
-      value: 50.28399999999999
-    - type: mrr_at_1000
-      value: 50.322
-    - type: mrr_at_3
-      value: 47.611
-    - type: mrr_at_5
-      value: 48.717
-    - type: ndcg_at_1
-      value: 41.146
-    - type: ndcg_at_10
-      value: 49.43
-    - type: ndcg_at_100
-      value: 54.01899999999999
-    - type: ndcg_at_1000
-      value: 55.803000000000004
-    - type: ndcg_at_3
-      value: 45.503
-    - type: ndcg_at_5
-      value: 47.198
-    - type: precision_at_1
-      value: 41.146
-    - type: precision_at_10
-      value: 9.268
-    - type: precision_at_100
-      value: 1.4749999999999999
-    - type: precision_at_1000
-      value: 0.19
-    - type: precision_at_3
-      value: 21.932
-    - type: precision_at_5
-      value: 15.389
-    - type: recall_at_1
-      value: 33.289
-    - type: recall_at_10
-      value: 59.209999999999994
-    - type: recall_at_100
-      value: 78.676
-    - type: recall_at_1000
-      value: 89.84100000000001
-    - type: recall_at_3
-      value: 47.351
-    - type: recall_at_5
-      value: 52.178999999999995
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-gaming
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
-    metrics:
-    - type: map_at_1
-      value: 44.483
-    - type: map_at_10
-      value: 56.862
-    - type: map_at_100
-      value: 57.901
-    - type: map_at_1000
-      value: 57.948
-    - type: map_at_3
-      value: 53.737
-    - type: map_at_5
-      value: 55.64
-    - type: mrr_at_1
-      value: 50.658
-    - type: mrr_at_10
-      value: 60.281
-    - type: mrr_at_100
-      value: 60.946
-    - type: mrr_at_1000
-      value: 60.967000000000006
-    - type: mrr_at_3
-      value: 58.192
-    - type: mrr_at_5
-      value: 59.531
-    - type: ndcg_at_1
-      value: 50.658
-    - type: ndcg_at_10
-      value: 62.339
-    - type: ndcg_at_100
-      value: 66.28399999999999
-    - type: ndcg_at_1000
-      value: 67.166
-    - type: ndcg_at_3
-      value: 57.458
-    - type: ndcg_at_5
-      value: 60.112
-    - type: precision_at_1
-      value: 50.658
-    - type: precision_at_10
-      value: 9.762
-    - type: precision_at_100
-      value: 1.26
-    - type: precision_at_1000
-      value: 0.13799999999999998
-    - type: precision_at_3
-      value: 25.329
-    - type: precision_at_5
-      value: 17.254
-    - type: recall_at_1
-      value: 44.483
-    - type: recall_at_10
-      value: 74.819
-    - type: recall_at_100
-      value: 91.702
-    - type: recall_at_1000
-      value: 97.84
-    - type: recall_at_3
-      value: 62.13999999999999
-    - type: recall_at_5
-      value: 68.569
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-gis
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: 5003b3064772da1887988e05400cf3806fe491f2
-    metrics:
-    - type: map_at_1
-      value: 26.489
-    - type: map_at_10
-      value: 37.004999999999995
-    - type: map_at_100
-      value: 38.001000000000005
-    - type: map_at_1000
-      value: 38.085
-    - type: map_at_3
-      value: 34.239999999999995
-    - type: map_at_5
-      value: 35.934
-    - type: mrr_at_1
-      value: 28.362
-    - type: mrr_at_10
-      value: 38.807
-    - type: mrr_at_100
-      value: 39.671
-    - type: mrr_at_1000
-      value: 39.736
-    - type: mrr_at_3
-      value: 36.29
-    - type: mrr_at_5
-      value: 37.906
-    - type: ndcg_at_1
-      value: 28.362
-    - type: ndcg_at_10
-      value: 42.510999999999996
-    - type: ndcg_at_100
-      value: 47.226
-    - type: ndcg_at_1000
-      value: 49.226
-    - type: ndcg_at_3
-      value: 37.295
-    - type: ndcg_at_5
-      value: 40.165
-    - type: precision_at_1
-      value: 28.362
-    - type: precision_at_10
-      value: 6.633
-    - type: precision_at_100
-      value: 0.9490000000000001
-    - type: precision_at_1000
-      value: 0.11499999999999999
-    - type: precision_at_3
-      value: 16.234
-    - type: precision_at_5
-      value: 11.434999999999999
-    - type: recall_at_1
-      value: 26.489
-    - type: recall_at_10
-      value: 57.457
-    - type: recall_at_100
-      value: 78.712
-    - type: recall_at_1000
-      value: 93.565
-    - type: recall_at_3
-      value: 43.748
-    - type: recall_at_5
-      value: 50.589
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-mathematica
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
-    metrics:
-    - type: map_at_1
-      value: 12.418999999999999
-    - type: map_at_10
-      value: 22.866
-    - type: map_at_100
-      value: 24.365000000000002
-    - type: map_at_1000
-      value: 24.479
-    - type: map_at_3
-      value: 19.965
-    - type: map_at_5
-      value: 21.684
-    - type: mrr_at_1
-      value: 14.677000000000001
-    - type: mrr_at_10
-      value: 26.316
-    - type: mrr_at_100
-      value: 27.514
-    - type: mrr_at_1000
-      value: 27.57
-    - type: mrr_at_3
-      value: 23.3
-    - type: mrr_at_5
-      value: 25.191000000000003
-    - type: ndcg_at_1
-      value: 14.677000000000001
-    - type: ndcg_at_10
-      value: 28.875
-    - type: ndcg_at_100
-      value: 35.607
-    - type: ndcg_at_1000
-      value: 38.237
-    - type: ndcg_at_3
-      value: 23.284
-    - type: ndcg_at_5
-      value: 26.226
-    - type: precision_at_1
-      value: 14.677000000000001
-    - type: precision_at_10
-      value: 5.771
-    - type: precision_at_100
-      value: 1.058
-    - type: precision_at_1000
-      value: 0.14200000000000002
-    - type: precision_at_3
-      value: 11.940000000000001
-    - type: precision_at_5
-      value: 9.229
-    - type: recall_at_1
-      value: 12.418999999999999
-    - type: recall_at_10
-      value: 43.333
-    - type: recall_at_100
-      value: 71.942
-    - type: recall_at_1000
-      value: 90.67399999999999
-    - type: recall_at_3
-      value: 28.787000000000003
-    - type: recall_at_5
-      value: 35.638
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-physics
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
-    metrics:
-    - type: map_at_1
-      value: 31.686999999999998
-    - type: map_at_10
-      value: 42.331
-    - type: map_at_100
-      value: 43.655
-    - type: map_at_1000
-      value: 43.771
-    - type: map_at_3
-      value: 38.944
-    - type: map_at_5
-      value: 40.991
-    - type: mrr_at_1
-      value: 37.921
-    - type: mrr_at_10
-      value: 47.534
-    - type: mrr_at_100
-      value: 48.362
-    - type: mrr_at_1000
-      value: 48.405
-    - type: mrr_at_3
-      value: 44.995000000000005
-    - type: mrr_at_5
-      value: 46.617
-    - type: ndcg_at_1
-      value: 37.921
-    - type: ndcg_at_10
-      value: 48.236000000000004
-    - type: ndcg_at_100
-      value: 53.705000000000005
-    - type: ndcg_at_1000
-      value: 55.596000000000004
-    - type: ndcg_at_3
-      value: 43.11
-    - type: ndcg_at_5
-      value: 45.862
-    - type: precision_at_1
-      value: 37.921
-    - type: precision_at_10
-      value: 8.643
-    - type: precision_at_100
-      value: 1.336
-    - type: precision_at_1000
-      value: 0.166
-    - type: precision_at_3
-      value: 20.308
-    - type: precision_at_5
-      value: 14.514
-    - type: recall_at_1
-      value: 31.686999999999998
-    - type: recall_at_10
-      value: 60.126999999999995
-    - type: recall_at_100
-      value: 83.10600000000001
-    - type: recall_at_1000
-      value: 95.15
-    - type: recall_at_3
-      value: 46.098
-    - type: recall_at_5
-      value: 53.179
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-programmers
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
-    metrics:
-    - type: map_at_1
-      value: 28.686
-    - type: map_at_10
-      value: 39.146
-    - type: map_at_100
-      value: 40.543
-    - type: map_at_1000
-      value: 40.644999999999996
-    - type: map_at_3
-      value: 36.195
-    - type: map_at_5
-      value: 37.919000000000004
-    - type: mrr_at_1
-      value: 35.160000000000004
-    - type: mrr_at_10
-      value: 44.711
-    - type: mrr_at_100
-      value: 45.609
-    - type: mrr_at_1000
-      value: 45.655
-    - type: mrr_at_3
-      value: 42.409
-    - type: mrr_at_5
-      value: 43.779
-    - type: ndcg_at_1
-      value: 35.160000000000004
-    - type: ndcg_at_10
-      value: 44.977000000000004
-    - type: ndcg_at_100
-      value: 50.663000000000004
-    - type: ndcg_at_1000
-      value: 52.794
-    - type: ndcg_at_3
-      value: 40.532000000000004
-    - type: ndcg_at_5
-      value: 42.641
-    - type: precision_at_1
-      value: 35.160000000000004
-    - type: precision_at_10
-      value: 8.014000000000001
-    - type: precision_at_100
-      value: 1.269
-    - type: precision_at_1000
-      value: 0.163
-    - type: precision_at_3
-      value: 19.444
-    - type: precision_at_5
-      value: 13.653
-    - type: recall_at_1
-      value: 28.686
-    - type: recall_at_10
-      value: 56.801
-    - type: recall_at_100
-      value: 80.559
-    - type: recall_at_1000
-      value: 95.052
-    - type: recall_at_3
-      value: 43.675999999999995
-    - type: recall_at_5
-      value: 49.703
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
-    metrics:
-    - type: map_at_1
-      value: 28.173833333333338
-    - type: map_at_10
-      value: 38.202083333333334
-    - type: map_at_100
-      value: 39.47475
-    - type: map_at_1000
-      value: 39.586499999999994
-    - type: map_at_3
-      value: 35.17308333333334
-    - type: map_at_5
-      value: 36.914
-    - type: mrr_at_1
-      value: 32.92958333333333
-    - type: mrr_at_10
-      value: 42.16758333333333
-    - type: mrr_at_100
-      value: 43.04108333333333
-    - type: mrr_at_1000
-      value: 43.092499999999994
-    - type: mrr_at_3
-      value: 39.69166666666666
-    - type: mrr_at_5
-      value: 41.19458333333333
-    - type: ndcg_at_1
-      value: 32.92958333333333
-    - type: ndcg_at_10
-      value: 43.80583333333333
-    - type: ndcg_at_100
-      value: 49.060916666666664
-    - type: ndcg_at_1000
-      value: 51.127250000000004
-    - type: ndcg_at_3
-      value: 38.80383333333333
-    - type: ndcg_at_5
-      value: 41.29658333333333
-    - type: precision_at_1
-      value: 32.92958333333333
-    - type: precision_at_10
-      value: 7.655666666666666
-    - type: precision_at_100
-      value: 1.2094166666666668
-    - type: precision_at_1000
-      value: 0.15750000000000003
-    - type: precision_at_3
-      value: 17.87975
-    - type: precision_at_5
-      value: 12.741833333333332
-    - type: recall_at_1
-      value: 28.173833333333338
-    - type: recall_at_10
-      value: 56.219249999999995
-    - type: recall_at_100
-      value: 79.01416666666665
-    - type: recall_at_1000
-      value: 93.13425000000001
-    - type: recall_at_3
-      value: 42.39241666666667
-    - type: recall_at_5
-      value: 48.764833333333335
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-stats
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
-    metrics:
-    - type: map_at_1
-      value: 25.625999999999998
-    - type: map_at_10
-      value: 32.808
-    - type: map_at_100
-      value: 33.951
-    - type: map_at_1000
-      value: 34.052
-    - type: map_at_3
-      value: 30.536
-    - type: map_at_5
-      value: 31.77
-    - type: mrr_at_1
-      value: 28.374
-    - type: mrr_at_10
-      value: 35.527
-    - type: mrr_at_100
-      value: 36.451
-    - type: mrr_at_1000
-      value: 36.522
-    - type: mrr_at_3
-      value: 33.410000000000004
-    - type: mrr_at_5
-      value: 34.537
-    - type: ndcg_at_1
-      value: 28.374
-    - type: ndcg_at_10
-      value: 37.172
-    - type: ndcg_at_100
-      value: 42.474000000000004
-    - type: ndcg_at_1000
-      value: 44.853
-    - type: ndcg_at_3
-      value: 32.931
-    - type: ndcg_at_5
-      value: 34.882999999999996
-    - type: precision_at_1
-      value: 28.374
-    - type: precision_at_10
-      value: 5.813
-    - type: precision_at_100
-      value: 0.928
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 14.008000000000001
-    - type: precision_at_5
-      value: 9.754999999999999
-    - type: recall_at_1
-      value: 25.625999999999998
-    - type: recall_at_10
-      value: 47.812
-    - type: recall_at_100
-      value: 71.61800000000001
-    - type: recall_at_1000
-      value: 88.881
-    - type: recall_at_3
-      value: 35.876999999999995
-    - type: recall_at_5
-      value: 40.839
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-tex
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: 46989137a86843e03a6195de44b09deda022eec7
-    metrics:
-    - type: map_at_1
-      value: 18.233
-    - type: map_at_10
-      value: 26.375999999999998
-    - type: map_at_100
-      value: 27.575
-    - type: map_at_1000
-      value: 27.706999999999997
-    - type: map_at_3
-      value: 23.619
-    - type: map_at_5
-      value: 25.217
-    - type: mrr_at_1
-      value: 22.023
-    - type: mrr_at_10
-      value: 30.122
-    - type: mrr_at_100
-      value: 31.083
-    - type: mrr_at_1000
-      value: 31.163999999999998
-    - type: mrr_at_3
-      value: 27.541
-    - type: mrr_at_5
-      value: 29.061999999999998
-    - type: ndcg_at_1
-      value: 22.023
-    - type: ndcg_at_10
-      value: 31.476
-    - type: ndcg_at_100
-      value: 37.114000000000004
-    - type: ndcg_at_1000
-      value: 39.981
-    - type: ndcg_at_3
-      value: 26.538
-    - type: ndcg_at_5
-      value: 29.016
-    - type: precision_at_1
-      value: 22.023
-    - type: precision_at_10
-      value: 5.819
-    - type: precision_at_100
-      value: 1.018
-    - type: precision_at_1000
-      value: 0.14300000000000002
-    - type: precision_at_3
-      value: 12.583
-    - type: precision_at_5
-      value: 9.36
-    - type: recall_at_1
-      value: 18.233
-    - type: recall_at_10
-      value: 43.029
-    - type: recall_at_100
-      value: 68.253
-    - type: recall_at_1000
-      value: 88.319
-    - type: recall_at_3
-      value: 29.541
-    - type: recall_at_5
-      value: 35.783
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-unix
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
-    metrics:
-    - type: map_at_1
-      value: 28.923
-    - type: map_at_10
-      value: 39.231
-    - type: map_at_100
-      value: 40.483000000000004
-    - type: map_at_1000
-      value: 40.575
-    - type: map_at_3
-      value: 35.94
-    - type: map_at_5
-      value: 37.683
-    - type: mrr_at_1
-      value: 33.955
-    - type: mrr_at_10
-      value: 43.163000000000004
-    - type: mrr_at_100
-      value: 44.054
-    - type: mrr_at_1000
-      value: 44.099
-    - type: mrr_at_3
-      value: 40.361000000000004
-    - type: mrr_at_5
-      value: 41.905
-    - type: ndcg_at_1
-      value: 33.955
-    - type: ndcg_at_10
-      value: 45.068000000000005
-    - type: ndcg_at_100
-      value: 50.470000000000006
-    - type: ndcg_at_1000
-      value: 52.349000000000004
-    - type: ndcg_at_3
-      value: 39.298
-    - type: ndcg_at_5
-      value: 41.821999999999996
-    - type: precision_at_1
-      value: 33.955
-    - type: precision_at_10
-      value: 7.649
-    - type: precision_at_100
-      value: 1.173
-    - type: precision_at_1000
-      value: 0.14200000000000002
-    - type: precision_at_3
-      value: 17.817
-    - type: precision_at_5
-      value: 12.537
-    - type: recall_at_1
-      value: 28.923
-    - type: recall_at_10
-      value: 58.934
-    - type: recall_at_100
-      value: 81.809
-    - type: recall_at_1000
-      value: 94.71300000000001
-    - type: recall_at_3
-      value: 42.975
-    - type: recall_at_5
-      value: 49.501
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-webmasters
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
-    metrics:
-    - type: map_at_1
-      value: 28.596
-    - type: map_at_10
-      value: 38.735
-    - type: map_at_100
-      value: 40.264
-    - type: map_at_1000
-      value: 40.48
-    - type: map_at_3
-      value: 35.394999999999996
-    - type: map_at_5
-      value: 37.099
-    - type: mrr_at_1
-      value: 33.992
-    - type: mrr_at_10
-      value: 43.076
-    - type: mrr_at_100
-      value: 44.005
-    - type: mrr_at_1000
-      value: 44.043
-    - type: mrr_at_3
-      value: 40.415
-    - type: mrr_at_5
-      value: 41.957
-    - type: ndcg_at_1
-      value: 33.992
-    - type: ndcg_at_10
-      value: 44.896
-    - type: ndcg_at_100
-      value: 50.44499999999999
-    - type: ndcg_at_1000
-      value: 52.675000000000004
-    - type: ndcg_at_3
-      value: 39.783
-    - type: ndcg_at_5
-      value: 41.997
-    - type: precision_at_1
-      value: 33.992
-    - type: precision_at_10
-      value: 8.498
-    - type: precision_at_100
-      value: 1.585
-    - type: precision_at_1000
-      value: 0.248
-    - type: precision_at_3
-      value: 18.511
-    - type: precision_at_5
-      value: 13.241
-    - type: recall_at_1
-      value: 28.596
-    - type: recall_at_10
-      value: 56.885
-    - type: recall_at_100
-      value: 82.306
-    - type: recall_at_1000
-      value: 95.813
-    - type: recall_at_3
-      value: 42.168
-    - type: recall_at_5
-      value: 48.32
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack-wordpress
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
-    metrics:
-    - type: map_at_1
-      value: 25.576
-    - type: map_at_10
-      value: 33.034
-    - type: map_at_100
-      value: 34.117999999999995
-    - type: map_at_1000
-      value: 34.222
-    - type: map_at_3
-      value: 30.183
-    - type: map_at_5
-      value: 31.974000000000004
-    - type: mrr_at_1
-      value: 27.542
-    - type: mrr_at_10
-      value: 34.838
-    - type: mrr_at_100
-      value: 35.824
-    - type: mrr_at_1000
-      value: 35.899
-    - type: mrr_at_3
-      value: 32.348
-    - type: mrr_at_5
-      value: 34.039
-    - type: ndcg_at_1
-      value: 27.542
-    - type: ndcg_at_10
-      value: 37.663000000000004
-    - type: ndcg_at_100
-      value: 42.762
-    - type: ndcg_at_1000
-      value: 45.235
-    - type: ndcg_at_3
-      value: 32.227
-    - type: ndcg_at_5
-      value: 35.27
-    - type: precision_at_1
-      value: 27.542
-    - type: precision_at_10
-      value: 5.840999999999999
-    - type: precision_at_100
-      value: 0.895
-    - type: precision_at_1000
-      value: 0.123
-    - type: precision_at_3
-      value: 13.370000000000001
-    - type: precision_at_5
-      value: 9.797
-    - type: recall_at_1
-      value: 25.576
-    - type: recall_at_10
-      value: 50.285000000000004
-    - type: recall_at_100
-      value: 73.06
-    - type: recall_at_1000
-      value: 91.15299999999999
-    - type: recall_at_3
-      value: 35.781
-    - type: recall_at_5
-      value: 43.058
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
-    metrics:
-    - type: map_at_1
-      value: 17.061
-    - type: map_at_10
-      value: 29.464000000000002
-    - type: map_at_100
-      value: 31.552999999999997
-    - type: map_at_1000
-      value: 31.707
-    - type: map_at_3
-      value: 24.834999999999997
-    - type: map_at_5
-      value: 27.355
-    - type: mrr_at_1
-      value: 38.958
-    - type: mrr_at_10
-      value: 51.578
-    - type: mrr_at_100
-      value: 52.262
-    - type: mrr_at_1000
-      value: 52.283
-    - type: mrr_at_3
-      value: 48.599
-    - type: mrr_at_5
-      value: 50.404
-    - type: ndcg_at_1
-      value: 38.958
-    - type: ndcg_at_10
-      value: 39.367999999999995
-    - type: ndcg_at_100
-      value: 46.521
-    - type: ndcg_at_1000
-      value: 49.086999999999996
-    - type: ndcg_at_3
-      value: 33.442
-    - type: ndcg_at_5
-      value: 35.515
-    - type: precision_at_1
-      value: 38.958
-    - type: precision_at_10
-      value: 12.110999999999999
-    - type: precision_at_100
-      value: 1.982
-    - type: precision_at_1000
-      value: 0.247
-    - type: precision_at_3
-      value: 25.102999999999998
-    - type: precision_at_5
-      value: 18.971
-    - type: recall_at_1
-      value: 17.061
-    - type: recall_at_10
-      value: 45.198
-    - type: recall_at_100
-      value: 69.18900000000001
-    - type: recall_at_1000
-      value: 83.38499999999999
-    - type: recall_at_3
-      value: 30.241
-    - type: recall_at_5
-      value: 36.851
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/dbpedia
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
-    metrics:
-    - type: map_at_1
-      value: 9.398
-    - type: map_at_10
-      value: 21.421
-    - type: map_at_100
-      value: 31.649
-    - type: map_at_1000
-      value: 33.469
-    - type: map_at_3
-      value: 15.310000000000002
-    - type: map_at_5
-      value: 17.946
-    - type: mrr_at_1
-      value: 71
-    - type: mrr_at_10
-      value: 78.92099999999999
-    - type: mrr_at_100
-      value: 79.225
-    - type: mrr_at_1000
-      value: 79.23
-    - type: mrr_at_3
-      value: 77.792
-    - type: mrr_at_5
-      value: 78.467
-    - type: ndcg_at_1
-      value: 57.99999999999999
-    - type: ndcg_at_10
-      value: 44.733000000000004
-    - type: ndcg_at_100
-      value: 50.646
-    - type: ndcg_at_1000
-      value: 57.903999999999996
-    - type: ndcg_at_3
-      value: 49.175999999999995
-    - type: ndcg_at_5
-      value: 46.800999999999995
-    - type: precision_at_1
-      value: 71
-    - type: precision_at_10
-      value: 36.25
-    - type: precision_at_100
-      value: 12.135
-    - type: precision_at_1000
-      value: 2.26
-    - type: precision_at_3
-      value: 52.75
-    - type: precision_at_5
-      value: 45.65
-    - type: recall_at_1
-      value: 9.398
-    - type: recall_at_10
-      value: 26.596999999999998
-    - type: recall_at_100
-      value: 57.943
-    - type: recall_at_1000
-      value: 81.147
-    - type: recall_at_3
-      value: 16.634
-    - type: recall_at_5
-      value: 20.7
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 46.535000000000004
-    - type: f1
-      value: 42.53702746452163
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
-    metrics:
-    - type: map_at_1
-      value: 77.235
-    - type: map_at_10
-      value: 85.504
-    - type: map_at_100
-      value: 85.707
-    - type: map_at_1000
-      value: 85.718
-    - type: map_at_3
-      value: 84.425
-    - type: map_at_5
-      value: 85.13
-    - type: mrr_at_1
-      value: 83.363
-    - type: mrr_at_10
-      value: 89.916
-    - type: mrr_at_100
-      value: 89.955
-    - type: mrr_at_1000
-      value: 89.956
-    - type: mrr_at_3
-      value: 89.32600000000001
-    - type: mrr_at_5
-      value: 89.79
-    - type: ndcg_at_1
-      value: 83.363
-    - type: ndcg_at_10
-      value: 89.015
-    - type: ndcg_at_100
-      value: 89.649
-    - type: ndcg_at_1000
-      value: 89.825
-    - type: ndcg_at_3
-      value: 87.45100000000001
-    - type: ndcg_at_5
-      value: 88.39399999999999
-    - type: precision_at_1
-      value: 83.363
-    - type: precision_at_10
-      value: 10.659
-    - type: precision_at_100
-      value: 1.122
-    - type: precision_at_1000
-      value: 0.11499999999999999
-    - type: precision_at_3
-      value: 33.338
-    - type: precision_at_5
-      value: 20.671999999999997
-    - type: recall_at_1
-      value: 77.235
-    - type: recall_at_10
-      value: 95.389
-    - type: recall_at_100
-      value: 97.722
-    - type: recall_at_1000
-      value: 98.744
-    - type: recall_at_3
-      value: 91.19800000000001
-    - type: recall_at_5
-      value: 93.635
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
-    metrics:
-    - type: map_at_1
-      value: 20.835
-    - type: map_at_10
-      value: 34.459
-    - type: map_at_100
-      value: 36.335
-    - type: map_at_1000
-      value: 36.518
-    - type: map_at_3
-      value: 30.581000000000003
-    - type: map_at_5
-      value: 32.859
-    - type: mrr_at_1
-      value: 40.894999999999996
-    - type: mrr_at_10
-      value: 50.491
-    - type: mrr_at_100
-      value: 51.243
-    - type: mrr_at_1000
-      value: 51.286
-    - type: mrr_at_3
-      value: 47.994
-    - type: mrr_at_5
-      value: 49.429
-    - type: ndcg_at_1
-      value: 40.894999999999996
-    - type: ndcg_at_10
-      value: 42.403
-    - type: ndcg_at_100
-      value: 48.954
-    - type: ndcg_at_1000
-      value: 51.961
-    - type: ndcg_at_3
-      value: 39.11
-    - type: ndcg_at_5
-      value: 40.152
-    - type: precision_at_1
-      value: 40.894999999999996
-    - type: precision_at_10
-      value: 11.466
-    - type: precision_at_100
-      value: 1.833
-    - type: precision_at_1000
-      value: 0.23700000000000002
-    - type: precision_at_3
-      value: 25.874000000000002
-    - type: precision_at_5
-      value: 19.012
-    - type: recall_at_1
-      value: 20.835
-    - type: recall_at_10
-      value: 49.535000000000004
-    - type: recall_at_100
-      value: 73.39099999999999
-    - type: recall_at_1000
-      value: 91.01599999999999
-    - type: recall_at_3
-      value: 36.379
-    - type: recall_at_5
-      value: 42.059999999999995
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: ab518f4d6fcca38d87c25209f94beba119d02014
-    metrics:
-    - type: map_at_1
-      value: 40.945
-    - type: map_at_10
-      value: 65.376
-    - type: map_at_100
-      value: 66.278
-    - type: map_at_1000
-      value: 66.33
-    - type: map_at_3
-      value: 61.753
-    - type: map_at_5
-      value: 64.077
-    - type: mrr_at_1
-      value: 81.891
-    - type: mrr_at_10
-      value: 87.256
-    - type: mrr_at_100
-      value: 87.392
-    - type: mrr_at_1000
-      value: 87.395
-    - type: mrr_at_3
-      value: 86.442
-    - type: mrr_at_5
-      value: 86.991
-    - type: ndcg_at_1
-      value: 81.891
-    - type: ndcg_at_10
-      value: 73.654
-    - type: ndcg_at_100
-      value: 76.62299999999999
-    - type: ndcg_at_1000
-      value: 77.60000000000001
-    - type: ndcg_at_3
-      value: 68.71199999999999
-    - type: ndcg_at_5
-      value: 71.563
-    - type: precision_at_1
-      value: 81.891
-    - type: precision_at_10
-      value: 15.409
-    - type: precision_at_100
-      value: 1.77
-    - type: precision_at_1000
-      value: 0.19
-    - type: precision_at_3
-      value: 44.15
-    - type: precision_at_5
-      value: 28.732000000000003
-    - type: recall_at_1
-      value: 40.945
-    - type: recall_at_10
-      value: 77.04299999999999
-    - type: recall_at_100
-      value: 88.508
-    - type: recall_at_1000
-      value: 94.943
-    - type: recall_at_3
-      value: 66.226
-    - type: recall_at_5
-      value: 71.83
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 74.08200000000001
-    - type: ap
-      value: 68.10929101713998
-    - type: f1
-      value: 73.98447117652009
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: c5a29a104738b98a9e76336939199e264163d4a0
-    metrics:
-    - type: map_at_1
-      value: 21.729000000000003
-    - type: map_at_10
-      value: 34.602
-    - type: map_at_100
-      value: 35.756
-    - type: map_at_1000
-      value: 35.803000000000004
-    - type: map_at_3
-      value: 30.619000000000003
-    - type: map_at_5
-      value: 32.914
-    - type: mrr_at_1
-      value: 22.364
-    - type: mrr_at_10
-      value: 35.183
-    - type: mrr_at_100
-      value: 36.287000000000006
-    - type: mrr_at_1000
-      value: 36.327999999999996
-    - type: mrr_at_3
-      value: 31.258000000000003
-    - type: mrr_at_5
-      value: 33.542
-    - type: ndcg_at_1
-      value: 22.364
-    - type: ndcg_at_10
-      value: 41.765
-    - type: ndcg_at_100
-      value: 47.293
-    - type: ndcg_at_1000
-      value: 48.457
-    - type: ndcg_at_3
-      value: 33.676
-    - type: ndcg_at_5
-      value: 37.783
-    - type: precision_at_1
-      value: 22.364
-    - type: precision_at_10
-      value: 6.662
-    - type: precision_at_100
-      value: 0.943
-    - type: precision_at_1000
-      value: 0.104
-    - type: precision_at_3
-      value: 14.435999999999998
-    - type: precision_at_5
-      value: 10.764999999999999
-    - type: recall_at_1
-      value: 21.729000000000003
-    - type: recall_at_10
-      value: 63.815999999999995
-    - type: recall_at_100
-      value: 89.265
-    - type: recall_at_1000
-      value: 98.149
-    - type: recall_at_3
-      value: 41.898
-    - type: recall_at_5
-      value: 51.76500000000001
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 92.73141814865483
-    - type: f1
-      value: 92.17518476408004
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 65.18011855905152
-    - type: f1
-      value: 46.70999638311856
-  - task:
-      type: Classification
-    dataset:
-      type: masakhane/masakhanews
-      name: MTEB MasakhaNEWSClassification (eng)
-      config: eng
-      split: test
-      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
-    metrics:
-    - type: accuracy
-      value: 75.24261603375525
-    - type: f1
-      value: 74.07895183913367
-  - task:
-      type: Clustering
-    dataset:
-      type: masakhane/masakhanews
-      name: MTEB MasakhaNEWSClusteringP2P (eng)
-      config: eng
-      split: test
-      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
-    metrics:
-    - type: v_measure
-      value: 28.43855875387446
-  - task:
-      type: Clustering
-    dataset:
-      type: masakhane/masakhanews
-      name: MTEB MasakhaNEWSClusteringS2S (eng)
-      config: eng
-      split: test
-      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
-    metrics:
-    - type: v_measure
-      value: 29.05331990256969
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 66.92333557498318
-    - type: f1
-      value: 64.29789389602692
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 72.74714189643578
-    - type: f1
-      value: 71.672585608315
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 31.503564225501613
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 28.410225127136457
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 29.170019896091908
-    - type: mrr
-      value: 29.881276831500976
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
-    metrics:
-    - type: map_at_1
-      value: 6.544
-    - type: map_at_10
-      value: 14.116999999999999
-    - type: map_at_100
-      value: 17.522
-    - type: map_at_1000
-      value: 19
-    - type: map_at_3
-      value: 10.369
-    - type: map_at_5
-      value: 12.189
-    - type: mrr_at_1
-      value: 47.988
-    - type: mrr_at_10
-      value: 56.84
-    - type: mrr_at_100
-      value: 57.367000000000004
-    - type: mrr_at_1000
-      value: 57.403000000000006
-    - type: mrr_at_3
-      value: 54.592
-    - type: mrr_at_5
-      value: 56.233
-    - type: ndcg_at_1
-      value: 45.82
-    - type: ndcg_at_10
-      value: 36.767
-    - type: ndcg_at_100
-      value: 33.356
-    - type: ndcg_at_1000
-      value: 42.062
-    - type: ndcg_at_3
-      value: 42.15
-    - type: ndcg_at_5
-      value: 40.355000000000004
-    - type: precision_at_1
-      value: 47.988
-    - type: precision_at_10
-      value: 27.121000000000002
-    - type: precision_at_100
-      value: 8.455
-    - type: precision_at_1000
-      value: 2.103
-    - type: precision_at_3
-      value: 39.628
-    - type: precision_at_5
-      value: 35.356
-    - type: recall_at_1
-      value: 6.544
-    - type: recall_at_10
-      value: 17.928
-    - type: recall_at_100
-      value: 32.843
-    - type: recall_at_1000
-      value: 65.752
-    - type: recall_at_3
-      value: 11.297
-    - type: recall_at_5
-      value: 14.357000000000001
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
-    metrics:
-    - type: map_at_1
-      value: 39.262
-    - type: map_at_10
-      value: 55.095000000000006
-    - type: map_at_100
-      value: 55.93900000000001
-    - type: map_at_1000
-      value: 55.955999999999996
-    - type: map_at_3
-      value: 50.93
-    - type: map_at_5
-      value: 53.491
-    - type: mrr_at_1
-      value: 43.598
-    - type: mrr_at_10
-      value: 57.379999999999995
-    - type: mrr_at_100
-      value: 57.940999999999995
-    - type: mrr_at_1000
-      value: 57.952000000000005
-    - type: mrr_at_3
-      value: 53.998000000000005
-    - type: mrr_at_5
-      value: 56.128
-    - type: ndcg_at_1
-      value: 43.598
-    - type: ndcg_at_10
-      value: 62.427
-    - type: ndcg_at_100
-      value: 65.759
-    - type: ndcg_at_1000
-      value: 66.133
-    - type: ndcg_at_3
-      value: 54.745999999999995
-    - type: ndcg_at_5
-      value: 58.975
-    - type: precision_at_1
-      value: 43.598
-    - type: precision_at_10
-      value: 9.789
-    - type: precision_at_100
-      value: 1.171
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 24.295
-    - type: precision_at_5
-      value: 17.028
-    - type: recall_at_1
-      value: 39.262
-    - type: recall_at_10
-      value: 82.317
-    - type: recall_at_100
-      value: 96.391
-    - type: recall_at_1000
-      value: 99.116
-    - type: recall_at_3
-      value: 62.621
-    - type: recall_at_5
-      value: 72.357
-  - task:
-      type: Classification
-    dataset:
-      type: ag_news
-      name: MTEB NewsClassification
-      config: default
-      split: test
-      revision: eb185aade064a813bc0b7f42de02595523103ca4
-    metrics:
-    - type: accuracy
-      value: 78.17500000000001
-    - type: f1
-      value: 78.01940892857273
-  - task:
-      type: PairClassification
-    dataset:
-      type: GEM/opusparcus
-      name: MTEB OpusparcusPC (en)
-      config: en
-      split: test
-      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.89816700610999
-    - type: cos_sim_ap
-      value: 100
-    - type: cos_sim_f1
-      value: 99.9490575649516
-    - type: cos_sim_precision
-      value: 100
-    - type: cos_sim_recall
-      value: 99.89816700610999
-    - type: dot_accuracy
-      value: 99.89816700610999
-    - type: dot_ap
-      value: 100
-    - type: dot_f1
-      value: 99.9490575649516
-    - type: dot_precision
-      value: 100
-    - type: dot_recall
-      value: 99.89816700610999
-    - type: euclidean_accuracy
-      value: 99.89816700610999
-    - type: euclidean_ap
-      value: 100
-    - type: euclidean_f1
-      value: 99.9490575649516
-    - type: euclidean_precision
-      value: 100
-    - type: euclidean_recall
-      value: 99.89816700610999
-    - type: manhattan_accuracy
-      value: 99.89816700610999
-    - type: manhattan_ap
-      value: 100
-    - type: manhattan_f1
-      value: 99.9490575649516
-    - type: manhattan_precision
-      value: 100
-    - type: manhattan_recall
-      value: 99.89816700610999
-    - type: max_accuracy
-      value: 99.89816700610999
-    - type: max_ap
-      value: 100
-    - type: max_f1
-      value: 99.9490575649516
-  - task:
-      type: PairClassification
-    dataset:
-      type: paws-x
-      name: MTEB PawsX (en)
-      config: en
-      split: test
-      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
-    metrics:
-    - type: cos_sim_accuracy
-      value: 61
-    - type: cos_sim_ap
-      value: 59.630757252602464
-    - type: cos_sim_f1
-      value: 62.37521514629949
-    - type: cos_sim_precision
-      value: 45.34534534534534
-    - type: cos_sim_recall
-      value: 99.88974641675854
-    - type: dot_accuracy
-      value: 61
-    - type: dot_ap
-      value: 59.631527308059006
-    - type: dot_f1
-      value: 62.37521514629949
-    - type: dot_precision
-      value: 45.34534534534534
-    - type: dot_recall
-      value: 99.88974641675854
-    - type: euclidean_accuracy
-      value: 61
-    - type: euclidean_ap
-      value: 59.630757252602464
-    - type: euclidean_f1
-      value: 62.37521514629949
-    - type: euclidean_precision
-      value: 45.34534534534534
-    - type: euclidean_recall
-      value: 99.88974641675854
-    - type: manhattan_accuracy
-      value: 60.9
-    - type: manhattan_ap
-      value: 59.613947780462254
-    - type: manhattan_f1
-      value: 62.37521514629949
-    - type: manhattan_precision
-      value: 45.34534534534534
-    - type: manhattan_recall
-      value: 99.88974641675854
-    - type: max_accuracy
-      value: 61
-    - type: max_ap
-      value: 59.631527308059006
-    - type: max_f1
-      value: 62.37521514629949
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
-    metrics:
-    - type: map_at_1
-      value: 69.963
-    - type: map_at_10
-      value: 83.59400000000001
-    - type: map_at_100
-      value: 84.236
-    - type: map_at_1000
-      value: 84.255
-    - type: map_at_3
-      value: 80.69800000000001
-    - type: map_at_5
-      value: 82.568
-    - type: mrr_at_1
-      value: 80.58999999999999
-    - type: mrr_at_10
-      value: 86.78200000000001
-    - type: mrr_at_100
-      value: 86.89099999999999
-    - type: mrr_at_1000
-      value: 86.893
-    - type: mrr_at_3
-      value: 85.757
-    - type: mrr_at_5
-      value: 86.507
-    - type: ndcg_at_1
-      value: 80.60000000000001
-    - type: ndcg_at_10
-      value: 87.41799999999999
-    - type: ndcg_at_100
-      value: 88.723
-    - type: ndcg_at_1000
-      value: 88.875
-    - type: ndcg_at_3
-      value: 84.565
-    - type: ndcg_at_5
-      value: 86.236
-    - type: precision_at_1
-      value: 80.60000000000001
-    - type: precision_at_10
-      value: 13.239
-    - type: precision_at_100
-      value: 1.5150000000000001
-    - type: precision_at_1000
-      value: 0.156
-    - type: precision_at_3
-      value: 36.947
-    - type: precision_at_5
-      value: 24.354
-    - type: recall_at_1
-      value: 69.963
-    - type: recall_at_10
-      value: 94.553
-    - type: recall_at_100
-      value: 99.104
-    - type: recall_at_1000
-      value: 99.872
-    - type: recall_at_3
-      value: 86.317
-    - type: recall_at_5
-      value: 91.023
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 47.52890410998761
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
-    metrics:
-    - type: v_measure
-      value: 62.760692287940486
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
-    metrics:
-    - type: map_at_1
-      value: 5.093
-    - type: map_at_10
-      value: 12.695
-    - type: map_at_100
-      value: 14.824000000000002
-    - type: map_at_1000
-      value: 15.123000000000001
-    - type: map_at_3
-      value: 8.968
-    - type: map_at_5
-      value: 10.828
-    - type: mrr_at_1
-      value: 25.1
-    - type: mrr_at_10
-      value: 35.894999999999996
-    - type: mrr_at_100
-      value: 36.966
-    - type: mrr_at_1000
-      value: 37.019999999999996
-    - type: mrr_at_3
-      value: 32.467
-    - type: mrr_at_5
-      value: 34.416999999999994
-    - type: ndcg_at_1
-      value: 25.1
-    - type: ndcg_at_10
-      value: 21.096999999999998
-    - type: ndcg_at_100
-      value: 29.202
-    - type: ndcg_at_1000
-      value: 34.541
-    - type: ndcg_at_3
-      value: 19.875
-    - type: ndcg_at_5
-      value: 17.497
-    - type: precision_at_1
-      value: 25.1
-    - type: precision_at_10
-      value: 10.9
-    - type: precision_at_100
-      value: 2.255
-    - type: precision_at_1000
-      value: 0.35400000000000004
-    - type: precision_at_3
-      value: 18.367
-    - type: precision_at_5
-      value: 15.299999999999999
-    - type: recall_at_1
-      value: 5.093
-    - type: recall_at_10
-      value: 22.092
-    - type: recall_at_100
-      value: 45.778
-    - type: recall_at_1000
-      value: 71.985
-    - type: recall_at_3
-      value: 11.167
-    - type: recall_at_5
-      value: 15.501999999999999
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
-    metrics:
-    - type: cos_sim_pearson
-      value: 74.04386981759481
-    - type: cos_sim_spearman
-      value: 69.12484963763646
-    - type: euclidean_pearson
-      value: 71.49384353291062
-    - type: euclidean_spearman
-      value: 69.12484548317074
-    - type: manhattan_pearson
-      value: 71.49828173987272
-    - type: manhattan_spearman
-      value: 69.08350274367014
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_pearson
-      value: 66.95372527615659
-    - type: cos_sim_spearman
-      value: 66.96821894433991
-    - type: euclidean_pearson
-      value: 64.675348002074
-    - type: euclidean_spearman
-      value: 66.96821894433991
-    - type: manhattan_pearson
-      value: 64.5965887073831
-    - type: manhattan_spearman
-      value: 66.88569076794741
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_pearson
-      value: 77.34698437961983
-    - type: cos_sim_spearman
-      value: 79.1153001117325
-    - type: euclidean_pearson
-      value: 78.53562874696966
-    - type: euclidean_spearman
-      value: 79.11530018205724
-    - type: manhattan_pearson
-      value: 78.46484988944093
-    - type: manhattan_spearman
-      value: 79.01416027493104
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_pearson
-      value: 68.81220371935373
-    - type: cos_sim_spearman
-      value: 68.50538405089604
-    - type: euclidean_pearson
-      value: 68.69204272683749
-    - type: euclidean_spearman
-      value: 68.50534223912419
-    - type: manhattan_pearson
-      value: 68.67300120149523
-    - type: manhattan_spearman
-      value: 68.45404301623115
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_pearson
-      value: 78.2464678879813
-    - type: cos_sim_spearman
-      value: 79.92003940566667
-    - type: euclidean_pearson
-      value: 79.8080778793964
-    - type: euclidean_spearman
-      value: 79.92003940566667
-    - type: manhattan_pearson
-      value: 79.80153621444681
-    - type: manhattan_spearman
-      value: 79.91293261418134
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_pearson
-      value: 76.31179207708662
-    - type: cos_sim_spearman
-      value: 78.65597349856115
-    - type: euclidean_pearson
-      value: 78.76937027472678
-    - type: euclidean_spearman
-      value: 78.65597349856115
-    - type: manhattan_pearson
-      value: 78.77129513300605
-    - type: manhattan_spearman
-      value: 78.62640467680775
-  - 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: 79.43158429552561
-    - type: cos_sim_spearman
-      value: 81.46108646565362
-    - type: euclidean_pearson
-      value: 81.47071791452292
-    - type: euclidean_spearman
-      value: 81.46108646565362
-    - type: manhattan_pearson
-      value: 81.56920643846031
-    - type: manhattan_spearman
-      value: 81.42226241399516
-  - 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: 66.89546474141514
-    - type: cos_sim_spearman
-      value: 65.8393752170531
-    - type: euclidean_pearson
-      value: 67.2580522762307
-    - type: euclidean_spearman
-      value: 65.8393752170531
-    - type: manhattan_pearson
-      value: 67.45157729300522
-    - type: manhattan_spearman
-      value: 66.19470854403802
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_pearson
-      value: 71.39566306334434
-    - type: cos_sim_spearman
-      value: 74.0981396086974
-    - type: euclidean_pearson
-      value: 73.7834496259745
-    - type: euclidean_spearman
-      value: 74.09803741302046
-    - type: manhattan_pearson
-      value: 73.79958138780945
-    - type: manhattan_spearman
-      value: 74.09894837555905
-  - task:
-      type: STS
-    dataset:
-      type: PhilipMay/stsb_multi_mt
-      name: MTEB STSBenchmarkMultilingualSTS (en)
-      config: en
-      split: test
-      revision: 93d57ef91790589e3ce9c365164337a8a78b7632
-    metrics:
-    - type: cos_sim_pearson
-      value: 71.39566311006806
-    - type: cos_sim_spearman
-      value: 74.0981396086974
-    - type: euclidean_pearson
-      value: 73.78344970897099
-    - type: euclidean_spearman
-      value: 74.09803741302046
-    - type: manhattan_pearson
-      value: 73.79958147136705
-    - type: manhattan_spearman
-      value: 74.09894837555905
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 80.81059564334683
-    - type: mrr
-      value: 94.62696617108381
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: 0228b52cf27578f30900b9e5271d331663a030d7
-    metrics:
-    - type: map_at_1
-      value: 57.760999999999996
-    - type: map_at_10
-      value: 68.614
-    - type: map_at_100
-      value: 69.109
-    - type: map_at_1000
-      value: 69.134
-    - type: map_at_3
-      value: 65.735
-    - type: map_at_5
-      value: 67.42099999999999
-    - type: mrr_at_1
-      value: 60.667
-    - type: mrr_at_10
-      value: 69.94200000000001
-    - type: mrr_at_100
-      value: 70.254
-    - type: mrr_at_1000
-      value: 70.28
-    - type: mrr_at_3
-      value: 67.72200000000001
-    - type: mrr_at_5
-      value: 69.18900000000001
-    - type: ndcg_at_1
-      value: 60.667
-    - type: ndcg_at_10
-      value: 73.548
-    - type: ndcg_at_100
-      value: 75.381
-    - type: ndcg_at_1000
-      value: 75.991
-    - type: ndcg_at_3
-      value: 68.685
-    - type: ndcg_at_5
-      value: 71.26
-    - type: precision_at_1
-      value: 60.667
-    - type: precision_at_10
-      value: 9.833
-    - type: precision_at_100
-      value: 1.08
-    - type: precision_at_1000
-      value: 0.11299999999999999
-    - type: precision_at_3
-      value: 26.889000000000003
-    - type: precision_at_5
-      value: 17.8
-    - type: recall_at_1
-      value: 57.760999999999996
-    - type: recall_at_10
-      value: 87.13300000000001
-    - type: recall_at_100
-      value: 95
-    - type: recall_at_1000
-      value: 99.667
-    - type: recall_at_3
-      value: 74.211
-    - type: recall_at_5
-      value: 80.63900000000001
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.81881188118813
-    - type: cos_sim_ap
-      value: 95.21196473745837
-    - type: cos_sim_f1
-      value: 90.69767441860465
-    - type: cos_sim_precision
-      value: 91.71779141104295
-    - type: cos_sim_recall
-      value: 89.7
-    - type: dot_accuracy
-      value: 99.81881188118813
-    - type: dot_ap
-      value: 95.21196473745837
-    - type: dot_f1
-      value: 90.69767441860465
-    - type: dot_precision
-      value: 91.71779141104295
-    - type: dot_recall
-      value: 89.7
-    - type: euclidean_accuracy
-      value: 99.81881188118813
-    - type: euclidean_ap
-      value: 95.21196473745839
-    - type: euclidean_f1
-      value: 90.69767441860465
-    - type: euclidean_precision
-      value: 91.71779141104295
-    - type: euclidean_recall
-      value: 89.7
-    - type: manhattan_accuracy
-      value: 99.81287128712871
-    - type: manhattan_ap
-      value: 95.16667174835017
-    - type: manhattan_f1
-      value: 90.41095890410959
-    - type: manhattan_precision
-      value: 91.7610710607621
-    - type: manhattan_recall
-      value: 89.1
-    - type: max_accuracy
-      value: 99.81881188118813
-    - type: max_ap
-      value: 95.21196473745839
-    - type: max_f1
-      value: 90.69767441860465
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 59.54942204515638
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 39.42892282672948
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 51.189033075914324
-    - type: mrr
-      value: 51.97014790764791
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 30.09466569775977
-    - type: cos_sim_spearman
-      value: 30.31058660775912
-    - type: dot_pearson
-      value: 30.09466438861689
-    - type: dot_spearman
-      value: 30.31058660775912
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
-    metrics:
-    - type: map_at_1
-      value: 0.253
-    - type: map_at_10
-      value: 2.07
-    - type: map_at_100
-      value: 12.679000000000002
-    - type: map_at_1000
-      value: 30.412
-    - type: map_at_3
-      value: 0.688
-    - type: map_at_5
-      value: 1.079
-    - type: mrr_at_1
-      value: 96
-    - type: mrr_at_10
-      value: 98
-    - type: mrr_at_100
-      value: 98
-    - type: mrr_at_1000
-      value: 98
-    - type: mrr_at_3
-      value: 98
-    - type: mrr_at_5
-      value: 98
-    - type: ndcg_at_1
-      value: 89
-    - type: ndcg_at_10
-      value: 79.646
-    - type: ndcg_at_100
-      value: 62.217999999999996
-    - type: ndcg_at_1000
-      value: 55.13400000000001
-    - type: ndcg_at_3
-      value: 83.458
-    - type: ndcg_at_5
-      value: 80.982
-    - type: precision_at_1
-      value: 96
-    - type: precision_at_10
-      value: 84.6
-    - type: precision_at_100
-      value: 64.34
-    - type: precision_at_1000
-      value: 24.534
-    - type: precision_at_3
-      value: 88.667
-    - type: precision_at_5
-      value: 85.6
-    - type: recall_at_1
-      value: 0.253
-    - type: recall_at_10
-      value: 2.253
-    - type: recall_at_100
-      value: 15.606
-    - type: recall_at_1000
-      value: 51.595
-    - type: recall_at_3
-      value: 0.7100000000000001
-    - type: recall_at_5
-      value: 1.139
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
-    metrics:
-    - type: map_at_1
-      value: 3.0540000000000003
-    - type: map_at_10
-      value: 13.078999999999999
-    - type: map_at_100
-      value: 19.468
-    - type: map_at_1000
-      value: 21.006
-    - type: map_at_3
-      value: 6.8629999999999995
-    - type: map_at_5
-      value: 9.187
-    - type: mrr_at_1
-      value: 42.857
-    - type: mrr_at_10
-      value: 56.735
-    - type: mrr_at_100
-      value: 57.352000000000004
-    - type: mrr_at_1000
-      value: 57.352000000000004
-    - type: mrr_at_3
-      value: 52.721
-    - type: mrr_at_5
-      value: 54.66
-    - type: ndcg_at_1
-      value: 38.775999999999996
-    - type: ndcg_at_10
-      value: 31.469
-    - type: ndcg_at_100
-      value: 42.016999999999996
-    - type: ndcg_at_1000
-      value: 52.60399999999999
-    - type: ndcg_at_3
-      value: 35.894
-    - type: ndcg_at_5
-      value: 33.873
-    - type: precision_at_1
-      value: 42.857
-    - type: precision_at_10
-      value: 27.346999999999998
-    - type: precision_at_100
-      value: 8.327
-    - type: precision_at_1000
-      value: 1.551
-    - type: precision_at_3
-      value: 36.735
-    - type: precision_at_5
-      value: 33.469
-    - type: recall_at_1
-      value: 3.0540000000000003
-    - type: recall_at_10
-      value: 19.185
-    - type: recall_at_100
-      value: 51.056000000000004
-    - type: recall_at_1000
-      value: 82.814
-    - type: recall_at_3
-      value: 7.961
-    - type: recall_at_5
-      value: 11.829
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
-    metrics:
-    - type: accuracy
-      value: 64.9346
-    - type: ap
-      value: 12.121605736777527
-    - type: f1
-      value: 50.169902005887955
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 56.72608941709111
-    - type: f1
-      value: 57.0702928875253
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 37.72671554400943
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 82.84556237706384
-    - type: cos_sim_ap
-      value: 63.28364215788651
-    - type: cos_sim_f1
-      value: 60.00000000000001
-    - type: cos_sim_precision
-      value: 54.45161290322581
-    - type: cos_sim_recall
-      value: 66.80738786279683
-    - type: dot_accuracy
-      value: 82.84556237706384
-    - type: dot_ap
-      value: 63.28364302860433
-    - type: dot_f1
-      value: 60.00000000000001
-    - type: dot_precision
-      value: 54.45161290322581
-    - type: dot_recall
-      value: 66.80738786279683
-    - type: euclidean_accuracy
-      value: 82.84556237706384
-    - type: euclidean_ap
-      value: 63.28363625097978
-    - type: euclidean_f1
-      value: 60.00000000000001
-    - type: euclidean_precision
-      value: 54.45161290322581
-    - type: euclidean_recall
-      value: 66.80738786279683
-    - type: manhattan_accuracy
-      value: 82.86940454193241
-    - type: manhattan_ap
-      value: 63.244773709836764
-    - type: manhattan_f1
-      value: 60.12680942696495
-    - type: manhattan_precision
-      value: 55.00109433136353
-    - type: manhattan_recall
-      value: 66.3060686015831
-    - type: max_accuracy
-      value: 82.86940454193241
-    - type: max_ap
-      value: 63.28364302860433
-    - type: max_f1
-      value: 60.12680942696495
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 88.32033220786278
-    - type: cos_sim_ap
-      value: 84.71928176006863
-    - type: cos_sim_f1
-      value: 76.51483333969684
-    - type: cos_sim_precision
-      value: 75.89184276300841
-    - type: cos_sim_recall
-      value: 77.14813674160764
-    - type: dot_accuracy
-      value: 88.32033220786278
-    - type: dot_ap
-      value: 84.71928330149228
-    - type: dot_f1
-      value: 76.51483333969684
-    - type: dot_precision
-      value: 75.89184276300841
-    - type: dot_recall
-      value: 77.14813674160764
-    - type: euclidean_accuracy
-      value: 88.32033220786278
-    - type: euclidean_ap
-      value: 84.71928045384345
-    - type: euclidean_f1
-      value: 76.51483333969684
-    - type: euclidean_precision
-      value: 75.89184276300841
-    - type: euclidean_recall
-      value: 77.14813674160764
-    - type: manhattan_accuracy
-      value: 88.27570147863545
-    - type: manhattan_ap
-      value: 84.68523541579755
-    - type: manhattan_f1
-      value: 76.51512269355146
-    - type: manhattan_precision
-      value: 75.62608107091825
-    - type: manhattan_recall
-      value: 77.42531567600862
-    - type: max_accuracy
-      value: 88.32033220786278
-    - type: max_ap
-      value: 84.71928330149228
-    - type: max_f1
-      value: 76.51512269355146
-  - task:
-      type: Clustering
-    dataset:
-      type: jinaai/cities_wiki_clustering
-      name: MTEB WikiCitiesClustering
-      config: default
-      split: test
-      revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
-    metrics:
-    - type: v_measure
-      value: 85.30624598674467
 license: apache-2.0
 ---
-<h1 align="center">Snowflake's Artic-embed-</h1>
+<h1 align="center">Snowflake's Artic-embed-s</h1>
 <h4 align="center">
    <p>
        <a href=#news>News</a> |