revert to previous scores

README.md

@@ -11,7 +11,7 @@ datasets:
 language: en
 license: apache-2.0
 model-index:
-- name: jina-embedding-s-en-v1
+- name: jina-embedding-b-en-v1
   results:
   - task:
       type: Classification
@@ -23,11 +23,11 @@ model-index:
       revision: e8379541af4e31359cca9fbcf4b00f2671dba205
     metrics:
     - type: accuracy
-      value: 64.82089552238806
+      value: 66.58208955223881
     - type: ap
-      value: 27.100981946230778
+      value: 28.455148149555754
     - type: f1
-      value: 58.3354886367184
+      value: 59.973775371110385
   - task:
       type: Classification
     dataset:
@@ -38,11 +38,11 @@ model-index:
       revision: e2d317d38cd51312af73b3d32a06d1a08b442046
     metrics:
     - type: accuracy
-      value: 64.282775
+      value: 65.09505
     - type: ap
-      value: 60.350688924943796
+      value: 61.387245649832614
     - type: f1
-      value: 62.06346948494396
+      value: 62.96831291412068
   - task:
       type: Classification
     dataset:
@@ -53,9 +53,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 30.623999999999995
+      value: 30.633999999999993
     - type: f1
-      value: 29.427789186742153
+      value: 29.638828990078647
   - task:
       type: Retrieval
     dataset:
@@ -963,1053 +963,156 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 22.119
+      value: 25.889
     - type: map_at_10
-      value: 35.609
+      value: 40.604
     - type: map_at_100
-      value: 36.935
+      value: 41.697
     - type: map_at_1000
-      value: 36.957
+      value: 41.705999999999996
     - type: map_at_3
-      value: 31.046000000000003
+      value: 35.217999999999996
     - type: map_at_5
-      value: 33.574
+      value: 38.326
     - type: mrr_at_1
-      value: 22.404
+      value: 26.245
     - type: mrr_at_10
-      value: 35.695
+      value: 40.736
     - type: mrr_at_100
-      value: 37.021
-    - type: mrr_at_1000
-      value: 37.043
-    - type: mrr_at_3
-      value: 31.093
-    - type: mrr_at_5
-      value: 33.635999999999996
-    - type: ndcg_at_1
-      value: 22.119
-    - type: ndcg_at_10
-      value: 43.566
-    - type: ndcg_at_100
-      value: 49.370000000000005
-    - type: ndcg_at_1000
-      value: 49.901
-    - type: ndcg_at_3
-      value: 34.06
-    - type: ndcg_at_5
-      value: 38.653999999999996
-    - type: precision_at_1
-      value: 22.119
-    - type: precision_at_10
-      value: 6.92
-    - type: precision_at_100
-      value: 0.95
-    - type: precision_at_1000
-      value: 0.099
-    - type: precision_at_3
-      value: 14.272000000000002
-    - type: precision_at_5
-      value: 10.811
-    - type: recall_at_1
-      value: 22.119
-    - type: recall_at_10
-      value: 69.203
-    - type: recall_at_100
-      value: 95.021
-    - type: recall_at_1000
-      value: 99.075
-    - type: recall_at_3
-      value: 42.817
-    - type: recall_at_5
-      value: 54.054
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 34.1740289109719
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 23.985251383455463
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 60.24873612289029
-    - type: mrr
-      value: 74.65692740623489
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_pearson
-      value: 86.22415390332444
-    - type: cos_sim_spearman
-      value: 82.9591191954711
-    - type: euclidean_pearson
-      value: 44.096317524324945
-    - type: euclidean_spearman
-      value: 42.95218351391625
-    - type: manhattan_pearson
-      value: 44.07766490545065
-    - type: manhattan_spearman
-      value: 42.78350497166606
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 74.64285714285714
-    - type: f1
-      value: 73.53680835577447
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 28.512813238490164
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 20.942214972649488
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 28.255999999999997
-    - type: map_at_10
-      value: 37.091
-    - type: map_at_100
-      value: 38.428000000000004
-    - type: map_at_1000
-      value: 38.559
-    - type: map_at_3
-      value: 34.073
-    - type: map_at_5
-      value: 35.739
-    - type: mrr_at_1
-      value: 34.907
-    - type: mrr_at_10
-      value: 42.769
-    - type: mrr_at_100
-      value: 43.607
-    - type: mrr_at_1000
-      value: 43.656
-    - type: mrr_at_3
-      value: 39.986
-    - type: mrr_at_5
-      value: 41.581
-    - type: ndcg_at_1
-      value: 34.907
-    - type: ndcg_at_10
-      value: 42.681000000000004
-    - type: ndcg_at_100
-      value: 48.213
-    - type: ndcg_at_1000
-      value: 50.464
-    - type: ndcg_at_3
-      value: 37.813
-    - type: ndcg_at_5
-      value: 39.936
-    - type: precision_at_1
-      value: 34.907
-    - type: precision_at_10
-      value: 7.911
-    - type: precision_at_100
-      value: 1.349
-    - type: precision_at_1000
-      value: 0.184
-    - type: precision_at_3
-      value: 17.93
-    - type: precision_at_5
-      value: 12.732
-    - type: recall_at_1
-      value: 28.255999999999997
-    - type: recall_at_10
-      value: 53.49699999999999
-    - type: recall_at_100
-      value: 77.288
-    - type: recall_at_1000
-      value: 91.776
-    - type: recall_at_3
-      value: 39.18
-    - type: recall_at_5
-      value: 45.365
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 25.563999999999997
-    - type: map_at_10
-      value: 33.913
-    - type: map_at_100
-      value: 34.966
-    - type: map_at_1000
-      value: 35.104
-    - type: map_at_3
-      value: 31.413000000000004
-    - type: map_at_5
-      value: 32.854
-    - type: mrr_at_1
-      value: 31.72
-    - type: mrr_at_10
-      value: 39.391
-    - type: mrr_at_100
-      value: 40.02
-    - type: mrr_at_1000
-      value: 40.076
-    - type: mrr_at_3
-      value: 37.314
-    - type: mrr_at_5
-      value: 38.507999999999996
-    - type: ndcg_at_1
-      value: 31.72
-    - type: ndcg_at_10
-      value: 38.933
-    - type: ndcg_at_100
-      value: 43.024
-    - type: ndcg_at_1000
-      value: 45.556999999999995
-    - type: ndcg_at_3
-      value: 35.225
-    - type: ndcg_at_5
-      value: 36.984
-    - type: precision_at_1
-      value: 31.72
-    - type: precision_at_10
-      value: 7.248
-    - type: precision_at_100
-      value: 1.192
-    - type: precision_at_1000
-      value: 0.16999999999999998
-    - type: precision_at_3
-      value: 16.943
-    - type: precision_at_5
-      value: 11.975
-    - type: recall_at_1
-      value: 25.563999999999997
-    - type: recall_at_10
-      value: 47.808
-    - type: recall_at_100
-      value: 65.182
-    - type: recall_at_1000
-      value: 81.831
-    - type: recall_at_3
-      value: 36.889
-    - type: recall_at_5
-      value: 41.829
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 33.662
-    - type: map_at_10
-      value: 44.096999999999994
-    - type: map_at_100
-      value: 45.153999999999996
-    - type: map_at_1000
-      value: 45.223
-    - type: map_at_3
-      value: 41.377
-    - type: map_at_5
-      value: 42.935
-    - type: mrr_at_1
-      value: 38.997
-    - type: mrr_at_10
-      value: 47.675
-    - type: mrr_at_100
-      value: 48.476
-    - type: mrr_at_1000
-      value: 48.519
-    - type: mrr_at_3
-      value: 45.549
-    - type: mrr_at_5
-      value: 46.884
-    - type: ndcg_at_1
-      value: 38.997
-    - type: ndcg_at_10
-      value: 49.196
-    - type: ndcg_at_100
-      value: 53.788000000000004
-    - type: ndcg_at_1000
-      value: 55.393
-    - type: ndcg_at_3
-      value: 44.67
-    - type: ndcg_at_5
-      value: 46.991
-    - type: precision_at_1
-      value: 38.997
-    - type: precision_at_10
-      value: 7.875
-    - type: precision_at_100
-      value: 1.102
-    - type: precision_at_1000
-      value: 0.13
-    - type: precision_at_3
-      value: 19.854
-    - type: precision_at_5
-      value: 13.605
-    - type: recall_at_1
-      value: 33.662
-    - type: recall_at_10
-      value: 60.75899999999999
-    - type: recall_at_100
-      value: 81.11699999999999
-    - type: recall_at_1000
-      value: 92.805
-    - type: recall_at_3
-      value: 48.577999999999996
-    - type: recall_at_5
-      value: 54.384
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.313
-    - type: map_at_10
-      value: 29.036
-    - type: map_at_100
-      value: 29.975
-    - type: map_at_1000
-      value: 30.063000000000002
-    - type: map_at_3
-      value: 26.878999999999998
-    - type: map_at_5
-      value: 28.005999999999997
-    - type: mrr_at_1
-      value: 23.39
-    - type: mrr_at_10
-      value: 31.072
-    - type: mrr_at_100
-      value: 31.922
-    - type: mrr_at_1000
-      value: 31.995
-    - type: mrr_at_3
-      value: 28.908
-    - type: mrr_at_5
-      value: 30.104999999999997
-    - type: ndcg_at_1
-      value: 23.39
-    - type: ndcg_at_10
-      value: 33.448
-    - type: ndcg_at_100
-      value: 38.255
-    - type: ndcg_at_1000
-      value: 40.542
-    - type: ndcg_at_3
-      value: 29.060000000000002
-    - type: ndcg_at_5
-      value: 31.023
-    - type: precision_at_1
-      value: 23.39
-    - type: precision_at_10
-      value: 5.175
-    - type: precision_at_100
-      value: 0.8049999999999999
-    - type: precision_at_1000
-      value: 0.10300000000000001
-    - type: precision_at_3
-      value: 12.504999999999999
-    - type: precision_at_5
-      value: 8.61
-    - type: recall_at_1
-      value: 21.313
-    - type: recall_at_10
-      value: 45.345
-    - type: recall_at_100
-      value: 67.752
-    - type: recall_at_1000
-      value: 84.937
-    - type: recall_at_3
-      value: 33.033
-    - type: recall_at_5
-      value: 37.929
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 14.255999999999998
-    - type: map_at_10
-      value: 20.339
-    - type: map_at_100
-      value: 21.491
-    - type: map_at_1000
-      value: 21.616
-    - type: map_at_3
-      value: 18.481
-    - type: map_at_5
-      value: 19.594
-    - type: mrr_at_1
-      value: 17.413
-    - type: mrr_at_10
-      value: 24.146
-    - type: mrr_at_100
-      value: 25.188
-    - type: mrr_at_1000
-      value: 25.273
-    - type: mrr_at_3
-      value: 22.264
-    - type: mrr_at_5
-      value: 23.302
-    - type: ndcg_at_1
-      value: 17.413
-    - type: ndcg_at_10
-      value: 24.272
-    - type: ndcg_at_100
-      value: 29.82
-    - type: ndcg_at_1000
-      value: 33.072
-    - type: ndcg_at_3
-      value: 20.826
-    - type: ndcg_at_5
-      value: 22.535
-    - type: precision_at_1
-      value: 17.413
-    - type: precision_at_10
-      value: 4.366
-    - type: precision_at_100
-      value: 0.818
-    - type: precision_at_1000
-      value: 0.124
-    - type: precision_at_3
-      value: 9.866999999999999
-    - type: precision_at_5
-      value: 7.164
-    - type: recall_at_1
-      value: 14.255999999999998
-    - type: recall_at_10
-      value: 32.497
-    - type: recall_at_100
-      value: 56.592
-    - type: recall_at_1000
-      value: 80.17699999999999
-    - type: recall_at_3
-      value: 23.195
-    - type: recall_at_5
-      value: 27.392
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.709
-    - type: map_at_10
-      value: 31.377
-    - type: map_at_100
-      value: 32.536
-    - type: map_at_1000
-      value: 32.669
-    - type: map_at_3
-      value: 28.572999999999997
-    - type: map_at_5
-      value: 30.205
-    - type: mrr_at_1
-      value: 27.815
-    - type: mrr_at_10
-      value: 36.452
-    - type: mrr_at_100
-      value: 37.302
-    - type: mrr_at_1000
-      value: 37.364000000000004
-    - type: mrr_at_3
-      value: 33.75
-    - type: mrr_at_5
-      value: 35.43
-    - type: ndcg_at_1
-      value: 27.815
-    - type: ndcg_at_10
-      value: 36.84
-    - type: ndcg_at_100
-      value: 42.092
-    - type: ndcg_at_1000
-      value: 44.727
-    - type: ndcg_at_3
-      value: 31.964
-    - type: ndcg_at_5
-      value: 34.428
-    - type: precision_at_1
-      value: 27.815
-    - type: precision_at_10
-      value: 6.67
-    - type: precision_at_100
-      value: 1.093
-    - type: precision_at_1000
-      value: 0.151
-    - type: precision_at_3
-      value: 14.982000000000001
-    - type: precision_at_5
-      value: 10.857
-    - type: recall_at_1
-      value: 22.709
-    - type: recall_at_10
-      value: 48.308
-    - type: recall_at_100
-      value: 70.866
-    - type: recall_at_1000
-      value: 88.236
-    - type: recall_at_3
-      value: 34.709
-    - type: recall_at_5
-      value: 40.996
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.348000000000003
-    - type: map_at_10
-      value: 29.427999999999997
-    - type: map_at_100
-      value: 30.499
-    - type: map_at_1000
-      value: 30.631999999999998
-    - type: map_at_3
-      value: 27.035999999999998
-    - type: map_at_5
-      value: 28.351
-    - type: mrr_at_1
-      value: 27.74
-    - type: mrr_at_10
-      value: 34.424
-    - type: mrr_at_100
-      value: 35.341
-    - type: mrr_at_1000
-      value: 35.419
-    - type: mrr_at_3
-      value: 32.401
-    - type: mrr_at_5
-      value: 33.497
-    - type: ndcg_at_1
-      value: 27.74
-    - type: ndcg_at_10
-      value: 34.136
-    - type: ndcg_at_100
-      value: 39.269
-    - type: ndcg_at_1000
-      value: 42.263
-    - type: ndcg_at_3
-      value: 30.171999999999997
-    - type: ndcg_at_5
-      value: 31.956
-    - type: precision_at_1
-      value: 27.74
-    - type: precision_at_10
-      value: 6.062
-    - type: precision_at_100
-      value: 1.014
-    - type: precision_at_1000
-      value: 0.146
-    - type: precision_at_3
-      value: 14.079
-    - type: precision_at_5
-      value: 9.977
-    - type: recall_at_1
-      value: 22.348000000000003
-    - type: recall_at_10
-      value: 43.477
-    - type: recall_at_100
-      value: 65.945
-    - type: recall_at_1000
-      value: 86.587
-    - type: recall_at_3
-      value: 32.107
-    - type: recall_at_5
-      value: 36.974000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.688499999999998
-    - type: map_at_10
-      value: 29.164666666666665
-    - type: map_at_100
-      value: 30.22575
-    - type: map_at_1000
-      value: 30.350833333333334
-    - type: map_at_3
-      value: 26.82025
-    - type: map_at_5
-      value: 28.14966666666667
-    - type: mrr_at_1
-      value: 25.779249999999998
-    - type: mrr_at_10
-      value: 32.969
-    - type: mrr_at_100
-      value: 33.81725
+      value: 41.829
     - type: mrr_at_1000
-      value: 33.88825
+      value: 41.837999999999994
     - type: mrr_at_3
-      value: 30.831250000000004
+      value: 35.349000000000004
     - type: mrr_at_5
-      value: 32.065000000000005
+      value: 38.425
     - type: ndcg_at_1
-      value: 25.779249999999998
+      value: 25.889
     - type: ndcg_at_10
-      value: 33.73675
+      value: 49.347
     - type: ndcg_at_100
-      value: 38.635666666666665
+      value: 53.956
     - type: ndcg_at_1000
-      value: 41.353500000000004
+      value: 54.2
     - type: ndcg_at_3
-      value: 29.66283333333333
+      value: 38.282
     - type: ndcg_at_5
-      value: 31.607249999999997
+      value: 43.895
     - type: precision_at_1
-      value: 25.779249999999998
+      value: 25.889
     - type: precision_at_10
-      value: 5.861416666666667
+      value: 7.752000000000001
     - type: precision_at_100
-      value: 0.9852500000000002
+      value: 0.976
     - type: precision_at_1000
-      value: 0.14108333333333334
+      value: 0.1
     - type: precision_at_3
-      value: 13.563583333333332
+      value: 15.717999999999998
     - type: precision_at_5
-      value: 9.630333333333335
+      value: 12.162
     - type: recall_at_1
-      value: 21.688499999999998
+      value: 25.889
     - type: recall_at_10
-      value: 43.605
+      value: 77.525
     - type: recall_at_100
-      value: 65.52366666666667
+      value: 97.58200000000001
     - type: recall_at_1000
-      value: 84.69683333333332
+      value: 99.502
     - type: recall_at_3
-      value: 32.195499999999996
+      value: 47.155
     - type: recall_at_5
-      value: 37.25325
+      value: 60.81100000000001
   - task:
-      type: Retrieval
+      type: Clustering
     dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackStatsRetrieval
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
       config: default
       split: test
-      revision: None
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
     metrics:
-    - type: map_at_1
-      value: 17.279
-    - type: map_at_10
-      value: 23.238
-    - type: map_at_100
-      value: 24.026
-    - type: map_at_1000
-      value: 24.13
-    - type: map_at_3
-      value: 20.730999999999998
-    - type: map_at_5
-      value: 22.278000000000002
-    - type: mrr_at_1
-      value: 19.017999999999997
-    - type: mrr_at_10
-      value: 25.188
-    - type: mrr_at_100
-      value: 25.918999999999997
-    - type: mrr_at_1000
-      value: 25.996999999999996
-    - type: mrr_at_3
-      value: 22.776
-    - type: mrr_at_5
-      value: 24.256
-    - type: ndcg_at_1
-      value: 19.017999999999997
-    - type: ndcg_at_10
-      value: 27.171
-    - type: ndcg_at_100
-      value: 31.274
-    - type: ndcg_at_1000
-      value: 34.016000000000005
-    - type: ndcg_at_3
-      value: 22.442
-    - type: ndcg_at_5
-      value: 24.955
-    - type: precision_at_1
-      value: 19.017999999999997
-    - type: precision_at_10
-      value: 4.494
-    - type: precision_at_100
-      value: 0.712
-    - type: precision_at_1000
-      value: 0.10300000000000001
-    - type: precision_at_3
-      value: 9.611
-    - type: precision_at_5
-      value: 7.331
-    - type: recall_at_1
-      value: 17.279
-    - type: recall_at_10
-      value: 37.464999999999996
-    - type: recall_at_100
-      value: 56.458
-    - type: recall_at_1000
-      value: 76.759
-    - type: recall_at_3
-      value: 24.659
-    - type: recall_at_5
-      value: 30.672
+    - type: v_measure
+      value: 39.2179862062943
   - task:
-      type: Retrieval
+      type: Clustering
     dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackTexRetrieval
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
       config: default
       split: test
-      revision: None
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
     metrics:
-    - type: map_at_1
-      value: 14.901
-    - type: map_at_10
-      value: 20.268
-    - type: map_at_100
-      value: 21.143
-    - type: map_at_1000
-      value: 21.264
-    - type: map_at_3
-      value: 18.557000000000002
-    - type: map_at_5
-      value: 19.483
-    - type: mrr_at_1
-      value: 17.997
-    - type: mrr_at_10
-      value: 23.591
-    - type: mrr_at_100
-      value: 24.387
-    - type: mrr_at_1000
-      value: 24.471
-    - type: mrr_at_3
-      value: 21.874
-    - type: mrr_at_5
-      value: 22.797
-    - type: ndcg_at_1
-      value: 17.997
-    - type: ndcg_at_10
-      value: 23.87
-    - type: ndcg_at_100
-      value: 28.459
-    - type: ndcg_at_1000
-      value: 31.66
-    - type: ndcg_at_3
-      value: 20.779
-    - type: ndcg_at_5
-      value: 22.137
-    - type: precision_at_1
-      value: 17.997
-    - type: precision_at_10
-      value: 4.25
-    - type: precision_at_100
-      value: 0.761
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 9.716
-    - type: precision_at_5
-      value: 6.909999999999999
-    - type: recall_at_1
-      value: 14.901
-    - type: recall_at_10
-      value: 31.44
-    - type: recall_at_100
-      value: 52.717000000000006
-    - type: recall_at_1000
-      value: 76.102
-    - type: recall_at_3
-      value: 22.675
-    - type: recall_at_5
-      value: 26.336
+    - type: v_measure
+      value: 29.87826673088078
   - task:
-      type: Retrieval
+      type: Reranking
     dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackUnixRetrieval
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
       config: default
       split: test
-      revision: None
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
     metrics:
-    - type: map_at_1
-      value: 21.52
-    - type: map_at_10
-      value: 28.397
-    - type: map_at_100
-      value: 29.443
-    - type: map_at_1000
-      value: 29.56
-    - type: map_at_3
-      value: 26.501
-    - type: map_at_5
-      value: 27.375
-    - type: mrr_at_1
-      value: 25.28
-    - type: mrr_at_10
-      value: 32.102000000000004
-    - type: mrr_at_100
-      value: 33.005
-    - type: mrr_at_1000
-      value: 33.084
-    - type: mrr_at_3
-      value: 30.208000000000002
-    - type: mrr_at_5
-      value: 31.146
-    - type: ndcg_at_1
-      value: 25.28
-    - type: ndcg_at_10
-      value: 32.635
-    - type: ndcg_at_100
-      value: 37.672
-    - type: ndcg_at_1000
-      value: 40.602
-    - type: ndcg_at_3
-      value: 28.951999999999998
-    - type: ndcg_at_5
-      value: 30.336999999999996
-    - type: precision_at_1
-      value: 25.28
-    - type: precision_at_10
-      value: 5.3260000000000005
-    - type: precision_at_100
-      value: 0.8840000000000001
-    - type: precision_at_1000
-      value: 0.126
-    - type: precision_at_3
-      value: 12.687000000000001
-    - type: precision_at_5
-      value: 8.638
-    - type: recall_at_1
-      value: 21.52
-    - type: recall_at_10
-      value: 41.955
-    - type: recall_at_100
-      value: 64.21
-    - type: recall_at_1000
-      value: 85.28099999999999
-    - type: recall_at_3
-      value: 31.979999999999997
-    - type: recall_at_5
-      value: 35.406
+    - type: map
+      value: 62.72401299412015
+    - type: mrr
+      value: 75.45167743921206
   - task:
-      type: Retrieval
+      type: STS
     dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWebmastersRetrieval
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
       config: default
       split: test
-      revision: None
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
     metrics:
-    - type: map_at_1
-      value: 20.296
-    - type: map_at_10
-      value: 28.449999999999996
-    - type: map_at_100
-      value: 29.847
-    - type: map_at_1000
-      value: 30.073
-    - type: map_at_3
-      value: 25.995
-    - type: map_at_5
-      value: 27.603
-    - type: mrr_at_1
-      value: 25.296000000000003
-    - type: mrr_at_10
-      value: 32.751999999999995
-    - type: mrr_at_100
-      value: 33.705
-    - type: mrr_at_1000
-      value: 33.783
-    - type: mrr_at_3
-      value: 30.731
-    - type: mrr_at_5
-      value: 32.006
-    - type: ndcg_at_1
-      value: 25.296000000000003
-    - type: ndcg_at_10
-      value: 33.555
-    - type: ndcg_at_100
-      value: 38.891999999999996
-    - type: ndcg_at_1000
-      value: 42.088
-    - type: ndcg_at_3
-      value: 29.944
-    - type: ndcg_at_5
-      value: 31.997999999999998
-    - type: precision_at_1
-      value: 25.296000000000003
-    - type: precision_at_10
-      value: 6.542000000000001
-    - type: precision_at_100
-      value: 1.354
-    - type: precision_at_1000
-      value: 0.22599999999999998
-    - type: precision_at_3
-      value: 14.360999999999999
-    - type: precision_at_5
-      value: 10.593
-    - type: recall_at_1
-      value: 20.296
-    - type: recall_at_10
-      value: 42.742000000000004
-    - type: recall_at_100
-      value: 67.351
-    - type: recall_at_1000
-      value: 88.774
-    - type: recall_at_3
-      value: 32.117000000000004
-    - type: recall_at_5
-      value: 37.788
+    - type: cos_sim_pearson
+      value: 85.96510928112639
+    - type: cos_sim_spearman
+      value: 82.64224450538681
+    - type: euclidean_pearson
+      value: 52.03458755006108
+    - type: euclidean_spearman
+      value: 52.83192670285616
+    - type: manhattan_pearson
+      value: 52.14561955040935
+    - type: manhattan_spearman
+      value: 52.9584356095438
   - task:
-      type: Retrieval
+      type: Classification
     dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWordpressRetrieval
+      type: mteb/banking77
+      name: MTEB Banking77Classification
       config: default
       split: test
-      revision: None
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
     metrics:
-    - type: map_at_1
-      value: 18.157999999999998
-    - type: map_at_10
-      value: 24.342
-    - type: map_at_100
-      value: 25.201
-    - type: map_at_1000
-      value: 25.317
-    - type: map_at_3
-      value: 22.227
-    - type: map_at_5
-      value: 23.372999999999998
-    - type: mrr_at_1
-      value: 19.778000000000002
-    - type: mrr_at_10
-      value: 26.066
-    - type: mrr_at_100
-      value: 26.935
-    - type: mrr_at_1000
-      value: 27.022000000000002
-    - type: mrr_at_3
-      value: 24.214
-    - type: mrr_at_5
-      value: 25.268
-    - type: ndcg_at_1
-      value: 19.778000000000002
-    - type: ndcg_at_10
-      value: 28.104000000000003
-    - type: ndcg_at_100
-      value: 32.87
-    - type: ndcg_at_1000
-      value: 35.858000000000004
-    - type: ndcg_at_3
-      value: 24.107
-    - type: ndcg_at_5
-      value: 26.007
-    - type: precision_at_1
-      value: 19.778000000000002
-    - type: precision_at_10
-      value: 4.417999999999999
-    - type: precision_at_100
-      value: 0.739
-    - type: precision_at_1000
-      value: 0.109
-    - type: precision_at_3
-      value: 10.228
-    - type: precision_at_5
-      value: 7.172000000000001
-    - type: recall_at_1
-      value: 18.157999999999998
-    - type: recall_at_10
-      value: 37.967
-    - type: recall_at_100
-      value: 60.806000000000004
-    - type: recall_at_1000
-      value: 83.097
-    - type: recall_at_3
-      value: 27.223999999999997
-    - type: recall_at_5
-      value: 31.968000000000004
+    - type: accuracy
+      value: 84.11363636363636
+    - type: f1
+      value: 84.01098114920124
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 32.991971466919026
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 26.48807922559519
   - task:
       type: Retrieval
     dataset:
@@ -2020,65 +1123,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 7.055
+      value: 8.014000000000001
     - type: map_at_10
-      value: 11.609
+      value: 14.149999999999999
     - type: map_at_100
-      value: 12.83
+      value: 15.539
     - type: map_at_1000
-      value: 12.995000000000001
+      value: 15.711
     - type: map_at_3
-      value: 9.673
+      value: 11.913
     - type: map_at_5
-      value: 10.761999999999999
+      value: 12.982
     - type: mrr_at_1
-      value: 15.309000000000001
+      value: 18.046
     - type: mrr_at_10
-      value: 23.655
+      value: 28.224
     - type: mrr_at_100
-      value: 24.785
+      value: 29.293000000000003
     - type: mrr_at_1000
-      value: 24.856
+      value: 29.348999999999997
     - type: mrr_at_3
-      value: 20.499000000000002
+      value: 25.179000000000002
     - type: mrr_at_5
-      value: 22.425
+      value: 26.827
     - type: ndcg_at_1
-      value: 15.309000000000001
+      value: 18.046
     - type: ndcg_at_10
-      value: 17.252000000000002
+      value: 20.784
     - type: ndcg_at_100
-      value: 22.976
+      value: 26.939999999999998
     - type: ndcg_at_1000
-      value: 26.480999999999998
+      value: 30.453999999999997
     - type: ndcg_at_3
-      value: 13.418
+      value: 16.694
     - type: ndcg_at_5
-      value: 15.084
+      value: 18.049
     - type: precision_at_1
-      value: 15.309000000000001
+      value: 18.046
     - type: precision_at_10
-      value: 5.309
+      value: 6.5280000000000005
     - type: precision_at_100
-      value: 1.1320000000000001
+      value: 1.2959999999999998
     - type: precision_at_1000
-      value: 0.17600000000000002
+      value: 0.19499999999999998
     - type: precision_at_3
-      value: 9.62
+      value: 12.465
     - type: precision_at_5
-      value: 7.883
+      value: 9.511
     - type: recall_at_1
-      value: 7.055
+      value: 8.014000000000001
     - type: recall_at_10
-      value: 21.891
+      value: 26.021
     - type: recall_at_100
-      value: 41.979
+      value: 47.692
     - type: recall_at_1000
-      value: 62.239999999999995
+      value: 67.63
     - type: recall_at_3
-      value: 12.722
+      value: 16.122
     - type: recall_at_5
-      value: 16.81
+      value: 19.817
   - task:
       type: Retrieval
     dataset:
@@ -2089,65 +1192,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 6.909
+      value: 7.396
     - type: map_at_10
-      value: 12.844
+      value: 14.543000000000001
     - type: map_at_100
-      value: 16.435
+      value: 19.235
     - type: map_at_1000
-      value: 17.262
+      value: 20.384
     - type: map_at_3
-      value: 10.131
+      value: 10.886
     - type: map_at_5
-      value: 11.269
+      value: 12.61
     - type: mrr_at_1
-      value: 54.50000000000001
+      value: 55.50000000000001
     - type: mrr_at_10
-      value: 62.202
+      value: 63.731
     - type: mrr_at_100
-      value: 62.81
+      value: 64.256
     - type: mrr_at_1000
-      value: 62.824000000000005
+      value: 64.27000000000001
     - type: mrr_at_3
-      value: 60.5
+      value: 61.583
     - type: mrr_at_5
-      value: 61.324999999999996
+      value: 62.92100000000001
     - type: ndcg_at_1
-      value: 42.125
+      value: 43.375
     - type: ndcg_at_10
-      value: 28.284
+      value: 31.352000000000004
     - type: ndcg_at_100
-      value: 30.444
+      value: 34.717999999999996
     - type: ndcg_at_1000
-      value: 36.397
+      value: 41.959
     - type: ndcg_at_3
-      value: 33.439
+      value: 35.319
     - type: ndcg_at_5
-      value: 30.473
+      value: 33.222
     - type: precision_at_1
-      value: 54.50000000000001
+      value: 55.50000000000001
     - type: precision_at_10
-      value: 21.4
+      value: 24.15
     - type: precision_at_100
-      value: 6.192
+      value: 7.42
     - type: precision_at_1000
-      value: 1.398
+      value: 1.66
     - type: precision_at_3
-      value: 36.583
+      value: 37.917
     - type: precision_at_5
-      value: 28.799999999999997
+      value: 31.900000000000002
     - type: recall_at_1
-      value: 6.909
+      value: 7.396
     - type: recall_at_10
-      value: 17.296
+      value: 19.686999999999998
     - type: recall_at_100
-      value: 33.925
+      value: 40.465
     - type: recall_at_1000
-      value: 53.786
+      value: 63.79899999999999
     - type: recall_at_3
-      value: 11.333
+      value: 12.124
     - type: recall_at_5
-      value: 13.529
+      value: 15.28
   - task:
       type: Classification
     dataset:
@@ -2158,9 +1261,9 @@ model-index:
       revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
     metrics:
     - type: accuracy
-      value: 36.08
+      value: 41.33
     - type: f1
-      value: 33.016420191943766
+      value: 37.682972473685496
   - task:
       type: Retrieval
     dataset:
@@ -2171,65 +1274,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 52.605000000000004
+      value: 49.019
     - type: map_at_10
-      value: 63.31400000000001
+      value: 61.219
     - type: map_at_100
-      value: 63.678000000000004
+      value: 61.753
     - type: map_at_1000
-      value: 63.699
+      value: 61.771
     - type: map_at_3
-      value: 61.141
+      value: 58.952000000000005
     - type: map_at_5
-      value: 62.517999999999994
+      value: 60.239
     - type: mrr_at_1
-      value: 56.871
+      value: 53
     - type: mrr_at_10
-      value: 67.915
+      value: 65.678
     - type: mrr_at_100
-      value: 68.24900000000001
+      value: 66.147
     - type: mrr_at_1000
-      value: 68.262
+      value: 66.155
     - type: mrr_at_3
-      value: 65.809
+      value: 63.495999999999995
     - type: mrr_at_5
-      value: 67.171
+      value: 64.75800000000001
     - type: ndcg_at_1
-      value: 56.871
+      value: 53
     - type: ndcg_at_10
-      value: 69.122
+      value: 67.587
     - type: ndcg_at_100
-      value: 70.855
+      value: 69.877
     - type: ndcg_at_1000
-      value: 71.368
+      value: 70.25200000000001
     - type: ndcg_at_3
-      value: 64.974
+      value: 63.174
     - type: ndcg_at_5
-      value: 67.318
+      value: 65.351
     - type: precision_at_1
-      value: 56.871
+      value: 53
     - type: precision_at_10
-      value: 9.029
+      value: 9.067
     - type: precision_at_100
-      value: 0.996
+      value: 1.026
     - type: precision_at_1000
-      value: 0.105
+      value: 0.107
     - type: precision_at_3
-      value: 25.893
+      value: 25.728
     - type: precision_at_5
-      value: 16.838
+      value: 16.637
     - type: recall_at_1
-      value: 52.605000000000004
+      value: 49.019
     - type: recall_at_10
-      value: 82.679
+      value: 82.962
     - type: recall_at_100
-      value: 90.586
+      value: 92.917
     - type: recall_at_1000
-      value: 94.38
+      value: 95.511
     - type: recall_at_3
-      value: 71.447
+      value: 70.838
     - type: recall_at_5
-      value: 77.218
+      value: 76.201
   - task:
       type: Retrieval
     dataset:
@@ -2240,65 +1343,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 10.759
+      value: 16.714000000000002
     - type: map_at_10
-      value: 18.877
+      value: 28.041
     - type: map_at_100
-      value: 20.498
+      value: 29.75
     - type: map_at_1000
-      value: 20.682000000000002
+      value: 29.944
     - type: map_at_3
-      value: 16.159000000000002
+      value: 23.884
     - type: map_at_5
-      value: 17.575
+      value: 26.468000000000004
     - type: mrr_at_1
-      value: 22.531000000000002
+      value: 33.796
     - type: mrr_at_10
-      value: 31.155
+      value: 42.757
     - type: mrr_at_100
-      value: 32.188
+      value: 43.705
     - type: mrr_at_1000
-      value: 32.245000000000005
+      value: 43.751
     - type: mrr_at_3
-      value: 28.781000000000002
+      value: 40.406
     - type: mrr_at_5
-      value: 30.054
+      value: 41.88
     - type: ndcg_at_1
-      value: 22.531000000000002
+      value: 33.796
     - type: ndcg_at_10
-      value: 25.189
+      value: 35.482
     - type: ndcg_at_100
-      value: 31.958
+      value: 42.44
     - type: ndcg_at_1000
-      value: 35.693999999999996
+      value: 45.903
     - type: ndcg_at_3
-      value: 22.235
+      value: 31.922
     - type: ndcg_at_5
-      value: 23.044999999999998
+      value: 33.516
     - type: precision_at_1
-      value: 22.531000000000002
+      value: 33.796
     - type: precision_at_10
-      value: 7.438000000000001
+      value: 10.108
     - type: precision_at_100
-      value: 1.418
+      value: 1.735
     - type: precision_at_1000
-      value: 0.208
+      value: 0.23500000000000001
     - type: precision_at_3
-      value: 15.329
+      value: 21.759
     - type: precision_at_5
-      value: 11.451
+      value: 16.605
     - type: recall_at_1
-      value: 10.759
+      value: 16.714000000000002
     - type: recall_at_10
-      value: 31.416
+      value: 42.38
     - type: recall_at_100
-      value: 56.989000000000004
+      value: 68.84700000000001
     - type: recall_at_1000
-      value: 80.33200000000001
+      value: 90.036
     - type: recall_at_3
-      value: 20.61
+      value: 28.776000000000003
     - type: recall_at_5
-      value: 24.903
+      value: 35.606
   - task:
       type: Retrieval
     dataset:
@@ -2309,65 +1412,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 29.21
+      value: 29.534
     - type: map_at_10
-      value: 38.765
+      value: 40.857
     - type: map_at_100
-      value: 39.498
+      value: 41.715999999999994
     - type: map_at_1000
-      value: 39.568
+      value: 41.795
     - type: map_at_3
-      value: 36.699
+      value: 38.415
     - type: map_at_5
-      value: 37.925
+      value: 39.833
     - type: mrr_at_1
-      value: 58.42
+      value: 59.068
     - type: mrr_at_10
-      value: 65.137
+      value: 66.034
     - type: mrr_at_100
-      value: 65.542
+      value: 66.479
     - type: mrr_at_1000
-      value: 65.568
+      value: 66.50399999999999
     - type: mrr_at_3
-      value: 63.698
+      value: 64.38000000000001
     - type: mrr_at_5
-      value: 64.575
+      value: 65.40599999999999
     - type: ndcg_at_1
-      value: 58.42
+      value: 59.068
     - type: ndcg_at_10
-      value: 47.476
+      value: 49.638
     - type: ndcg_at_100
-      value: 50.466
+      value: 53.093999999999994
     - type: ndcg_at_1000
-      value: 52.064
+      value: 54.813
     - type: ndcg_at_3
-      value: 43.986
+      value: 45.537
     - type: ndcg_at_5
-      value: 45.824
+      value: 47.671
     - type: precision_at_1
-      value: 58.42
+      value: 59.068
     - type: precision_at_10
-      value: 9.649000000000001
+      value: 10.313
     - type: precision_at_100
-      value: 1.201
+      value: 1.304
     - type: precision_at_1000
-      value: 0.14100000000000001
+      value: 0.153
     - type: precision_at_3
-      value: 26.977
+      value: 28.278
     - type: precision_at_5
-      value: 17.642
+      value: 18.658
     - type: recall_at_1
-      value: 29.21
+      value: 29.534
     - type: recall_at_10
-      value: 48.244
+      value: 51.56699999999999
     - type: recall_at_100
-      value: 60.041
+      value: 65.199
     - type: recall_at_1000
-      value: 70.743
+      value: 76.678
     - type: recall_at_3
-      value: 40.466
+      value: 42.417
     - type: recall_at_5
-      value: 44.105
+      value: 46.644000000000005
   - task:
       type: Classification
     dataset:
@@ -2378,11 +1481,11 @@ model-index:
       revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
     metrics:
     - type: accuracy
-      value: 58.7064
+      value: 65.74719999999999
     - type: ap
-      value: 55.36326227125519
+      value: 60.57322504947344
     - type: f1
-      value: 57.46763115215848
+      value: 65.37875006542282
   - task:
       type: Retrieval
     dataset:
@@ -2393,65 +1496,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 15.889000000000001
+      value: 15.695999999999998
     - type: map_at_10
-      value: 25.979000000000003
+      value: 26.661
     - type: map_at_100
-      value: 27.21
+      value: 27.982000000000003
     - type: map_at_1000
-      value: 27.284000000000002
+      value: 28.049000000000003
     - type: map_at_3
-      value: 22.665
+      value: 23.057
     - type: map_at_5
-      value: 24.578
+      value: 25.079
     - type: mrr_at_1
-      value: 16.39
+      value: 16.16
     - type: mrr_at_10
-      value: 26.504
+      value: 27.150999999999996
     - type: mrr_at_100
-      value: 27.689999999999998
+      value: 28.423
     - type: mrr_at_1000
-      value: 27.758
+      value: 28.483999999999998
     - type: mrr_at_3
-      value: 23.24
+      value: 23.577
     - type: mrr_at_5
-      value: 25.108000000000004
+      value: 25.585
     - type: ndcg_at_1
-      value: 16.39
+      value: 16.16
     - type: ndcg_at_10
-      value: 31.799
+      value: 33.017
     - type: ndcg_at_100
-      value: 38.034
+      value: 39.582
     - type: ndcg_at_1000
-      value: 39.979
+      value: 41.28
     - type: ndcg_at_3
-      value: 25.054
+      value: 25.607000000000003
     - type: ndcg_at_5
-      value: 28.463
+      value: 29.214000000000002
     - type: precision_at_1
-      value: 16.39
+      value: 16.16
     - type: precision_at_10
-      value: 5.189
+      value: 5.506
     - type: precision_at_100
-      value: 0.835
+      value: 0.882
     - type: precision_at_1000
-      value: 0.1
+      value: 0.10300000000000001
     - type: precision_at_3
-      value: 10.84
+      value: 11.199
     - type: precision_at_5
-      value: 8.238
+      value: 8.55
     - type: recall_at_1
-      value: 15.889000000000001
+      value: 15.695999999999998
     - type: recall_at_10
-      value: 49.739
+      value: 52.736000000000004
     - type: recall_at_100
-      value: 79.251
+      value: 83.523
     - type: recall_at_1000
-      value: 94.298
+      value: 96.588
     - type: recall_at_3
-      value: 31.427
+      value: 32.484
     - type: recall_at_5
-      value: 39.623000000000005
+      value: 41.117
   - task:
       type: Classification
     dataset:
@@ -2462,9 +1565,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 88.81668946648426
+      value: 91.71682626538988
     - type: f1
-      value: 88.55200075528438
+      value: 91.60647677401211
   - task:
       type: Classification
     dataset:
@@ -2475,9 +1578,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 58.611491108071135
+      value: 74.94756041951665
     - type: f1
-      value: 42.12391403999353
+      value: 57.26936028487369
   - task:
       type: Classification
     dataset:
@@ -2488,9 +1591,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 64.67047747141896
+      value: 71.43241425689307
     - type: f1
-      value: 62.88410885922258
+      value: 68.80370629448252
   - task:
       type: Classification
     dataset:
@@ -2501,9 +1604,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 71.78547410894419
+      value: 77.04774714189642
     - type: f1
-      value: 71.69467869218154
+      value: 76.93545888412446
   - task:
       type: Clustering
     dataset:
@@ -2514,7 +1617,7 @@ model-index:
       revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
     metrics:
     - type: v_measure
-      value: 27.23799937752035
+      value: 30.009784989313765
   - task:
       type: Clustering
     dataset:
@@ -2525,7 +1628,7 @@ model-index:
       revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
     metrics:
     - type: v_measure
-      value: 23.26502601343789
+      value: 25.568442512328872
   - task:
       type: Reranking
     dataset:
@@ -2536,9 +1639,9 @@ model-index:
       revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
     metrics:
     - type: map
-      value: 30.680711484149832
+      value: 31.013959341949697
     - type: mrr
-      value: 31.705059795117307
+      value: 31.998487836684575
   - task:
       type: Retrieval
     dataset:
@@ -2549,65 +1652,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 4.077
+      value: 4.316
     - type: map_at_10
-      value: 8.657
+      value: 10.287
     - type: map_at_100
-      value: 10.753
+      value: 12.817
     - type: map_at_1000
-      value: 11.885
+      value: 14.141
     - type: map_at_3
-      value: 6.5089999999999995
+      value: 7.728
     - type: map_at_5
-      value: 7.405
+      value: 8.876000000000001
     - type: mrr_at_1
-      value: 38.7
+      value: 39.628
     - type: mrr_at_10
-      value: 46.065
+      value: 48.423
     - type: mrr_at_100
-      value: 46.772000000000006
+      value: 49.153999999999996
     - type: mrr_at_1000
-      value: 46.83
+      value: 49.198
     - type: mrr_at_3
-      value: 44.118
+      value: 45.666000000000004
     - type: mrr_at_5
-      value: 45.015
+      value: 47.477000000000004
     - type: ndcg_at_1
-      value: 36.997
+      value: 36.533
     - type: ndcg_at_10
-      value: 25.96
+      value: 29.304000000000002
     - type: ndcg_at_100
-      value: 23.607
+      value: 27.078000000000003
     - type: ndcg_at_1000
-      value: 32.317
+      value: 36.221
     - type: ndcg_at_3
-      value: 31.06
+      value: 33.256
     - type: ndcg_at_5
-      value: 28.921000000000003
+      value: 31.465
     - type: precision_at_1
-      value: 38.7
+      value: 39.009
     - type: precision_at_10
-      value: 19.195
+      value: 22.043
     - type: precision_at_100
-      value: 6.164
+      value: 7.115
     - type: precision_at_1000
-      value: 1.839
+      value: 1.991
     - type: precision_at_3
-      value: 28.999000000000002
+      value: 31.476
     - type: precision_at_5
-      value: 25.014999999999997
+      value: 27.616000000000003
     - type: recall_at_1
-      value: 4.077
+      value: 4.316
     - type: recall_at_10
-      value: 11.802
+      value: 14.507
     - type: recall_at_100
-      value: 24.365000000000002
+      value: 28.847
     - type: recall_at_1000
-      value: 55.277
+      value: 61.758
     - type: recall_at_3
-      value: 7.435
+      value: 8.753
     - type: recall_at_5
-      value: 8.713999999999999
+      value: 11.153
   - task:
       type: Retrieval
     dataset:
@@ -2618,65 +1721,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 19.588
+      value: 22.374
     - type: map_at_10
-      value: 32.08
+      value: 36.095
     - type: map_at_100
-      value: 33.32
+      value: 37.413999999999994
     - type: map_at_1000
-      value: 33.377
+      value: 37.46
     - type: map_at_3
-      value: 28.166000000000004
+      value: 31.711
     - type: map_at_5
-      value: 30.383
+      value: 34.294999999999995
     - type: mrr_at_1
-      value: 22.161
+      value: 25.406000000000002
     - type: mrr_at_10
-      value: 34.121
+      value: 38.424
     - type: mrr_at_100
-      value: 35.171
+      value: 39.456
     - type: mrr_at_1000
-      value: 35.214
+      value: 39.488
     - type: mrr_at_3
-      value: 30.692000000000004
+      value: 34.613
     - type: mrr_at_5
-      value: 32.706
+      value: 36.864999999999995
     - type: ndcg_at_1
-      value: 22.131999999999998
+      value: 25.406000000000002
     - type: ndcg_at_10
-      value: 38.887
+      value: 43.614000000000004
     - type: ndcg_at_100
-      value: 44.433
+      value: 49.166
     - type: ndcg_at_1000
-      value: 45.823
+      value: 50.212
     - type: ndcg_at_3
-      value: 31.35
+      value: 35.221999999999994
     - type: ndcg_at_5
-      value: 35.144
+      value: 39.571
     - type: precision_at_1
-      value: 22.131999999999998
+      value: 25.406000000000002
     - type: precision_at_10
-      value: 6.8629999999999995
+      value: 7.654
     - type: precision_at_100
-      value: 0.993
+      value: 1.0699999999999998
     - type: precision_at_1000
-      value: 0.11199999999999999
+      value: 0.117
     - type: precision_at_3
-      value: 14.706
+      value: 16.425
     - type: precision_at_5
-      value: 10.972999999999999
+      value: 12.352
     - type: recall_at_1
-      value: 19.588
+      value: 22.374
     - type: recall_at_10
-      value: 57.703
+      value: 64.337
     - type: recall_at_100
-      value: 82.194
+      value: 88.374
     - type: recall_at_1000
-      value: 92.623
+      value: 96.101
     - type: recall_at_3
-      value: 38.012
+      value: 42.5
     - type: recall_at_5
-      value: 46.847
+      value: 52.556000000000004
   - task:
       type: Retrieval
     dataset:
@@ -2687,65 +1790,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 68.038
+      value: 69.301
     - type: map_at_10
-      value: 81.572
+      value: 83.128
     - type: map_at_100
-      value: 82.25200000000001
+      value: 83.779
     - type: map_at_1000
-      value: 82.27600000000001
+      value: 83.798
     - type: map_at_3
-      value: 78.618
+      value: 80.11399999999999
     - type: map_at_5
-      value: 80.449
+      value: 82.00699999999999
     - type: mrr_at_1
-      value: 78.31
+      value: 79.81
     - type: mrr_at_10
-      value: 84.98
+      value: 86.28
     - type: mrr_at_100
-      value: 85.122
+      value: 86.399
     - type: mrr_at_1000
-      value: 85.124
+      value: 86.401
     - type: mrr_at_3
-      value: 83.852
+      value: 85.26
     - type: mrr_at_5
-      value: 84.6
+      value: 85.93499999999999
     - type: ndcg_at_1
-      value: 78.31
+      value: 79.80000000000001
     - type: ndcg_at_10
-      value: 85.693
+      value: 87.06700000000001
     - type: ndcg_at_100
-      value: 87.191
+      value: 88.41799999999999
     - type: ndcg_at_1000
-      value: 87.386
+      value: 88.554
     - type: ndcg_at_3
-      value: 82.585
+      value: 84.052
     - type: ndcg_at_5
-      value: 84.255
+      value: 85.711
     - type: precision_at_1
-      value: 78.31
+      value: 79.80000000000001
     - type: precision_at_10
-      value: 12.986
+      value: 13.224
     - type: precision_at_100
-      value: 1.505
+      value: 1.5230000000000001
     - type: precision_at_1000
-      value: 0.156
+      value: 0.157
     - type: precision_at_3
-      value: 36.007
+      value: 36.723
     - type: precision_at_5
-      value: 23.735999999999997
+      value: 24.192
     - type: recall_at_1
-      value: 68.038
+      value: 69.301
     - type: recall_at_10
-      value: 93.598
+      value: 94.589
     - type: recall_at_100
-      value: 98.869
+      value: 99.29299999999999
     - type: recall_at_1000
-      value: 99.86500000000001
+      value: 99.965
     - type: recall_at_3
-      value: 84.628
+      value: 86.045
     - type: recall_at_5
-      value: 89.316
+      value: 90.656
   - task:
       type: Clustering
     dataset:
@@ -2756,7 +1859,7 @@ model-index:
       revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
     metrics:
     - type: v_measure
-      value: 37.948231664922865
+      value: 43.09903181165838
   - task:
       type: Clustering
     dataset:
@@ -2767,7 +1870,7 @@ model-index:
       revision: 282350215ef01743dc01b456c7f5241fa8937f16
     metrics:
     - type: v_measure
-      value: 49.90597913763894
+      value: 51.710378422887594
   - task:
       type: Retrieval
     dataset:
@@ -2778,65 +1881,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 3.753
+      value: 4.138
     - type: map_at_10
-      value: 8.915
+      value: 10.419
     - type: map_at_100
-      value: 10.374
+      value: 12.321
     - type: map_at_1000
-      value: 10.612
+      value: 12.605
     - type: map_at_3
-      value: 6.577
+      value: 7.445
     - type: map_at_5
-      value: 7.8
+      value: 8.859
     - type: mrr_at_1
-      value: 18.4
+      value: 20.4
     - type: mrr_at_10
-      value: 27.325
+      value: 30.148999999999997
     - type: mrr_at_100
-      value: 28.419
+      value: 31.357000000000003
     - type: mrr_at_1000
-      value: 28.494000000000003
+      value: 31.424999999999997
     - type: mrr_at_3
-      value: 24.349999999999998
+      value: 26.983
     - type: mrr_at_5
-      value: 26.205000000000002
+      value: 28.883
     - type: ndcg_at_1
-      value: 18.4
+      value: 20.4
     - type: ndcg_at_10
-      value: 15.293000000000001
+      value: 17.713
     - type: ndcg_at_100
-      value: 21.592
+      value: 25.221
     - type: ndcg_at_1000
-      value: 26.473000000000003
+      value: 30.381999999999998
     - type: ndcg_at_3
-      value: 14.748
+      value: 16.607
     - type: ndcg_at_5
-      value: 12.98
+      value: 14.559
     - type: precision_at_1
-      value: 18.4
+      value: 20.4
     - type: precision_at_10
-      value: 7.779999999999999
+      value: 9.3
     - type: precision_at_100
-      value: 1.693
+      value: 2.0060000000000002
     - type: precision_at_1000
-      value: 0.28800000000000003
+      value: 0.32399999999999995
     - type: precision_at_3
-      value: 13.700000000000001
+      value: 15.5
     - type: precision_at_5
-      value: 11.379999999999999
+      value: 12.839999999999998
     - type: recall_at_1
-      value: 3.753
+      value: 4.138
     - type: recall_at_10
-      value: 15.806999999999999
+      value: 18.813
     - type: recall_at_100
-      value: 34.37
+      value: 40.692
     - type: recall_at_1000
-      value: 58.463
+      value: 65.835
     - type: recall_at_3
-      value: 8.338
+      value: 9.418
     - type: recall_at_5
-      value: 11.538
+      value: 12.983
   - task:
       type: STS
     dataset:
@@ -2847,17 +1950,17 @@ model-index:
       revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
     metrics:
     - type: cos_sim_pearson
-      value: 82.58843987639705
+      value: 83.25944192442188
     - type: cos_sim_spearman
-      value: 76.33071660715956
+      value: 75.04296759426568
     - type: euclidean_pearson
-      value: 72.8029921002978
+      value: 74.8130340249869
     - type: euclidean_spearman
-      value: 69.34534284782808
+      value: 68.40180320816793
     - type: manhattan_pearson
-      value: 72.49781034973653
+      value: 74.9149619199144
     - type: manhattan_spearman
-      value: 69.24754112621694
+      value: 68.52380798258379
   - task:
       type: STS
     dataset:
@@ -2868,17 +1971,17 @@ model-index:
       revision: a0d554a64d88156834ff5ae9920b964011b16384
     metrics:
     - type: cos_sim_pearson
-      value: 83.31673079903189
+      value: 81.91983072545858
     - type: cos_sim_spearman
-      value: 74.27699263517789
+      value: 73.5129498787296
     - type: euclidean_pearson
-      value: 69.4008910999579
+      value: 66.76535523270856
     - type: euclidean_spearman
-      value: 59.0716984643048
+      value: 56.64797879544097
     - type: manhattan_pearson
-      value: 68.87342686919199
+      value: 66.12191731384162
     - type: manhattan_spearman
-      value: 58.904612865335025
+      value: 56.37753861965956
   - task:
       type: STS
     dataset:
@@ -2889,17 +1992,17 @@ model-index:
       revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
     metrics:
     - type: cos_sim_pearson
-      value: 77.59122302327788
+      value: 77.71164758747632
     - type: cos_sim_spearman
-      value: 78.55383586979005
+      value: 79.1530762030973
     - type: euclidean_pearson
-      value: 68.18338642204289
+      value: 69.50621786400177
     - type: euclidean_spearman
-      value: 68.95092864180276
+      value: 70.44898083428744
     - type: manhattan_pearson
-      value: 68.08807059822706
+      value: 69.04018458995307
     - type: manhattan_spearman
-      value: 68.86135938270193
+      value: 70.00888532086853
   - task:
       type: STS
     dataset:
@@ -2910,17 +2013,17 @@ model-index:
       revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
     metrics:
     - type: cos_sim_pearson
-      value: 78.51766841424501
+      value: 78.90774995778577
     - type: cos_sim_spearman
-      value: 73.84318001499558
+      value: 75.24229403562713
     - type: euclidean_pearson
-      value: 67.2007138855177
+      value: 68.5838924571539
     - type: euclidean_spearman
-      value: 63.98672842723766
+      value: 65.06652398167358
     - type: manhattan_pearson
-      value: 67.17773810895949
+      value: 68.23143277902628
     - type: manhattan_spearman
-      value: 64.07359154832962
+      value: 64.79624516012709
   - task:
       type: STS
     dataset:
@@ -2931,17 +2034,17 @@ model-index:
       revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
     metrics:
     - type: cos_sim_pearson
-      value: 82.73438541570299
+      value: 83.78074322110155
     - type: cos_sim_spearman
-      value: 83.71357922283677
+      value: 85.12071478276958
     - type: euclidean_pearson
-      value: 57.50131347498546
+      value: 65.00147804089737
     - type: euclidean_spearman
-      value: 57.73623619252132
+      value: 66.02559342831921
     - type: manhattan_pearson
-      value: 58.082992079000725
+      value: 65.01270190203297
     - type: manhattan_spearman
-      value: 58.42728201167522
+      value: 66.13038450207748
   - task:
       type: STS
     dataset:
@@ -2952,17 +2055,17 @@ model-index:
       revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
     metrics:
     - type: cos_sim_pearson
-      value: 78.14794654172421
+      value: 77.29395327338185
     - type: cos_sim_spearman
-      value: 80.025736165043
+      value: 80.07128686563352
     - type: euclidean_pearson
-      value: 65.87773913985473
+      value: 65.97939065455975
     - type: euclidean_spearman
-      value: 66.69337751784794
+      value: 66.80283051081129
     - type: manhattan_pearson
-      value: 66.01039761004415
+      value: 65.6750450606584
     - type: manhattan_spearman
-      value: 66.89215027952318
+      value: 66.55805829330733
   - task:
       type: STS
     dataset:
@@ -2973,17 +2076,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 87.10554507136152
+      value: 87.64956503192369
     - type: cos_sim_spearman
-      value: 87.4898082140765
+      value: 87.95719598052727
     - type: euclidean_pearson
-      value: 72.19391114541367
+      value: 73.35178669405819
     - type: euclidean_spearman
-      value: 70.36647944993783
+      value: 71.58959083579994
     - type: manhattan_pearson
-      value: 72.18680758133698
+      value: 73.24156949179472
     - type: manhattan_spearman
-      value: 70.3871215447305
+      value: 71.35933730170666
   - task:
       type: STS
     dataset:
@@ -2994,17 +2097,17 @@ model-index:
       revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
     metrics:
     - type: cos_sim_pearson
-      value: 64.54868111501618
+      value: 66.61640922485357
     - type: cos_sim_spearman
-      value: 64.25173617448473
+      value: 66.08406266387749
     - type: euclidean_pearson
-      value: 39.116088900637116
+      value: 43.684972836995776
     - type: euclidean_spearman
-      value: 53.300772929884
+      value: 60.26686390609082
     - type: manhattan_pearson
-      value: 38.3844195287959
+      value: 43.694268683941154
     - type: manhattan_spearman
-      value: 52.846675312001246
+      value: 59.61419719435629
   - task:
       type: STS
     dataset:
@@ -3015,17 +2118,17 @@ model-index:
       revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
     metrics:
     - type: cos_sim_pearson
-      value: 80.04396610550214
+      value: 81.73624666044613
     - type: cos_sim_spearman
-      value: 79.19504854997832
+      value: 81.68869881979401
     - type: euclidean_pearson
-      value: 66.3284657637072
+      value: 72.47205990508046
     - type: euclidean_spearman
-      value: 63.69531796729492
+      value: 71.02381428101695
     - type: manhattan_pearson
-      value: 66.82324081038026
+      value: 72.4947870027535
     - type: manhattan_spearman
-      value: 64.18254512904923
+      value: 71.0789806652577
   - task:
       type: Reranking
     dataset:
@@ -3036,9 +2139,9 @@ model-index:
       revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
     metrics:
     - type: map
-      value: 74.16264051781705
+      value: 79.53671929012175
     - type: mrr
-      value: 91.80864796060874
+      value: 93.96566033820936
   - task:
       type: Retrieval
     dataset:
@@ -3049,65 +2152,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 38.983000000000004
+      value: 43.761
     - type: map_at_10
-      value: 47.858000000000004
+      value: 53.846000000000004
     - type: map_at_100
-      value: 48.695
+      value: 54.55799999999999
     - type: map_at_1000
-      value: 48.752
+      value: 54.620999999999995
     - type: map_at_3
-      value: 45.444
+      value: 51.513
     - type: map_at_5
-      value: 46.906
+      value: 52.591
     - type: mrr_at_1
-      value: 41.333
+      value: 46.666999999999994
     - type: mrr_at_10
-      value: 49.935
+      value: 55.461000000000006
     - type: mrr_at_100
-      value: 50.51
+      value: 56.008
     - type: mrr_at_1000
-      value: 50.55500000000001
+      value: 56.069
     - type: mrr_at_3
-      value: 47.833
+      value: 53.5
     - type: mrr_at_5
-      value: 49.117
+      value: 54.417
     - type: ndcg_at_1
-      value: 41.333
+      value: 46.666999999999994
     - type: ndcg_at_10
-      value: 52.398999999999994
+      value: 58.599000000000004
     - type: ndcg_at_100
-      value: 56.196
+      value: 61.538000000000004
     - type: ndcg_at_1000
-      value: 57.838
+      value: 63.22
     - type: ndcg_at_3
-      value: 47.987
+      value: 54.254999999999995
     - type: ndcg_at_5
-      value: 50.356
+      value: 55.861000000000004
     - type: precision_at_1
-      value: 41.333
+      value: 46.666999999999994
     - type: precision_at_10
-      value: 7.167
+      value: 8.033
     - type: precision_at_100
-      value: 0.9299999999999999
+      value: 0.963
     - type: precision_at_1000
-      value: 0.108
+      value: 0.11
     - type: precision_at_3
-      value: 19.0
+      value: 21.667
     - type: precision_at_5
-      value: 12.8
+      value: 14.066999999999998
     - type: recall_at_1
-      value: 38.983000000000004
+      value: 43.761
     - type: recall_at_10
-      value: 64.183
+      value: 71.65599999999999
     - type: recall_at_100
-      value: 82.02199999999999
+      value: 84.433
     - type: recall_at_1000
-      value: 95.167
+      value: 97.5
     - type: recall_at_3
-      value: 52.383
+      value: 59.522
     - type: recall_at_5
-      value: 58.411
+      value: 63.632999999999996
   - task:
       type: PairClassification
     dataset:
@@ -3118,51 +2221,51 @@ model-index:
       revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
     metrics:
     - type: cos_sim_accuracy
-      value: 99.8019801980198
+      value: 99.68811881188118
     - type: cos_sim_ap
-      value: 94.9287554635848
+      value: 91.08077352794682
     - type: cos_sim_f1
-      value: 89.83739837398375
+      value: 84.38570729319628
     - type: cos_sim_precision
-      value: 91.32231404958677
+      value: 82.64621284755513
     - type: cos_sim_recall
-      value: 88.4
+      value: 86.2
     - type: dot_accuracy
-      value: 99.23762376237623
+      value: 99.14653465346535
     - type: dot_ap
-      value: 55.22534191245801
+      value: 45.24942149367904
     - type: dot_f1
-      value: 54.054054054054056
+      value: 46.470062555853445
     - type: dot_precision
-      value: 55.15088449531738
+      value: 42.003231017770595
     - type: dot_recall
-      value: 53.0
+      value: 52
     - type: euclidean_accuracy
-      value: 99.6108910891089
+      value: 99.56930693069307
     - type: euclidean_ap
-      value: 82.5195111329438
+      value: 80.28575652582506
     - type: euclidean_f1
-      value: 78.2847718526663
+      value: 75.52054023635341
     - type: euclidean_precision
-      value: 86.93528693528694
+      value: 86.35778635778635
     - type: euclidean_recall
-      value: 71.2
+      value: 67.10000000000001
     - type: manhattan_accuracy
-      value: 99.5970297029703
+      value: 99.56039603960396
     - type: manhattan_ap
-      value: 81.96876777875492
+      value: 79.74630510301085
     - type: manhattan_f1
-      value: 77.33773377337734
+      value: 74.67569091934575
     - type: manhattan_precision
-      value: 85.94132029339853
+      value: 85.64036222509702
     - type: manhattan_recall
-      value: 70.3
+      value: 66.2
     - type: max_accuracy
-      value: 99.8019801980198
+      value: 99.68811881188118
     - type: max_ap
-      value: 94.9287554635848
+      value: 91.08077352794682
     - type: max_f1
-      value: 89.83739837398375
+      value: 84.38570729319628
   - task:
       type: Clustering
     dataset:
@@ -3173,7 +2276,7 @@ model-index:
       revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
     metrics:
     - type: v_measure
-      value: 46.34997003954114
+      value: 52.0788049295693
   - task:
       type: Clustering
     dataset:
@@ -3184,7 +2287,7 @@ model-index:
       revision: 815ca46b2622cec33ccafc3735d572c266efdb44
     metrics:
     - type: v_measure
-      value: 31.462336020554893
+      value: 31.606006030205545
   - task:
       type: Reranking
     dataset:
@@ -3195,9 +2298,9 @@ model-index:
       revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
     metrics:
     - type: map
-      value: 47.1757817459526
+      value: 50.87384988372756
     - type: mrr
-      value: 47.941057104660054
+      value: 51.62476922587217
   - task:
       type: Summarization
     dataset:
@@ -3208,13 +2311,13 @@ model-index:
       revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
     metrics:
     - type: cos_sim_pearson
-      value: 30.56106249068471
+      value: 30.355859978837156
     - type: cos_sim_spearman
-      value: 31.24613190558528
+      value: 30.0847548337847
     - type: dot_pearson
-      value: 20.486610035794257
+      value: 19.391736817587557
     - type: dot_spearman
-      value: 23.115667545894546
+      value: 20.732256259543014
   - task:
       type: Retrieval
     dataset:
@@ -3225,65 +2328,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 0.182
+      value: 0.19
     - type: map_at_10
-      value: 1.155
+      value: 1.2850000000000001
     - type: map_at_100
-      value: 5.118
+      value: 6.376999999999999
     - type: map_at_1000
-      value: 11.827
+      value: 15.21
     - type: map_at_3
-      value: 0.482
+      value: 0.492
     - type: map_at_5
-      value: 0.712
+      value: 0.776
     - type: mrr_at_1
-      value: 70.0
+      value: 68
     - type: mrr_at_10
-      value: 79.483
+      value: 79.783
     - type: mrr_at_100
-      value: 79.637
+      value: 79.783
     - type: mrr_at_1000
-      value: 79.637
+      value: 79.783
     - type: mrr_at_3
-      value: 77.667
+      value: 77.333
     - type: mrr_at_5
-      value: 78.567
+      value: 79.533
     - type: ndcg_at_1
-      value: 63.0
+      value: 62
     - type: ndcg_at_10
-      value: 52.303
+      value: 54.635
     - type: ndcg_at_100
-      value: 37.361
+      value: 40.939
     - type: ndcg_at_1000
-      value: 32.84
+      value: 37.716
     - type: ndcg_at_3
-      value: 58.274
+      value: 58.531
     - type: ndcg_at_5
-      value: 55.601
+      value: 58.762
     - type: precision_at_1
-      value: 70.0
+      value: 68
     - type: precision_at_10
-      value: 55.60000000000001
+      value: 58.8
     - type: precision_at_100
-      value: 37.96
+      value: 41.74
     - type: precision_at_1000
-      value: 14.738000000000001
+      value: 16.938
     - type: precision_at_3
-      value: 62.666999999999994
+      value: 64
     - type: precision_at_5
-      value: 60.0
+      value: 64.8
     - type: recall_at_1
-      value: 0.182
+      value: 0.19
     - type: recall_at_10
-      value: 1.4120000000000001
+      value: 1.547
     - type: recall_at_100
-      value: 8.533
+      value: 9.739
     - type: recall_at_1000
-      value: 30.572
+      value: 35.815000000000005
     - type: recall_at_3
-      value: 0.5309999999999999
+      value: 0.528
     - type: recall_at_5
-      value: 0.814
+      value: 0.894
   - task:
       type: Retrieval
     dataset:
@@ -3294,65 +2397,65 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 1.385
+      value: 1.514
     - type: map_at_10
-      value: 7.185999999999999
+      value: 7.163
     - type: map_at_100
-      value: 11.642
+      value: 11.623999999999999
     - type: map_at_1000
-      value: 12.953000000000001
+      value: 13.062999999999999
     - type: map_at_3
-      value: 3.496
+      value: 3.51
     - type: map_at_5
-      value: 4.82
+      value: 4.661
     - type: mrr_at_1
-      value: 16.326999999999998
+      value: 20.408
     - type: mrr_at_10
-      value: 29.461
+      value: 33.993
     - type: mrr_at_100
-      value: 31.436999999999998
+      value: 35.257
     - type: mrr_at_1000
-      value: 31.436999999999998
+      value: 35.313
     - type: mrr_at_3
-      value: 24.490000000000002
+      value: 30.272
     - type: mrr_at_5
-      value: 27.857
+      value: 31.701
     - type: ndcg_at_1
-      value: 14.285999999999998
+      value: 18.367
     - type: ndcg_at_10
-      value: 16.672
+      value: 18.062
     - type: ndcg_at_100
-      value: 28.691
+      value: 28.441
     - type: ndcg_at_1000
-      value: 39.817
+      value: 40.748
     - type: ndcg_at_3
-      value: 15.277
+      value: 18.651999999999997
     - type: ndcg_at_5
-      value: 15.823
+      value: 17.055
     - type: precision_at_1
-      value: 16.326999999999998
+      value: 20.408
     - type: precision_at_10
-      value: 15.509999999999998
+      value: 17.551
     - type: precision_at_100
-      value: 6.49
+      value: 6.223999999999999
     - type: precision_at_1000
-      value: 1.4080000000000001
+      value: 1.427
     - type: precision_at_3
-      value: 16.326999999999998
+      value: 20.408
     - type: precision_at_5
-      value: 16.735
+      value: 17.959
     - type: recall_at_1
-      value: 1.385
+      value: 1.514
     - type: recall_at_10
-      value: 12.586
+      value: 13.447000000000001
     - type: recall_at_100
-      value: 40.765
+      value: 39.77
     - type: recall_at_1000
-      value: 75.198
+      value: 76.95
     - type: recall_at_3
-      value: 4.326
+      value: 4.806
     - type: recall_at_5
-      value: 7.074999999999999
+      value: 6.873
   - task:
       type: Classification
     dataset:
@@ -3363,11 +2466,11 @@ model-index:
       revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
     metrics:
     - type: accuracy
-      value: 59.4402
+      value: 65.53179999999999
     - type: ap
-      value: 10.16922814263879
+      value: 11.504743595308318
     - type: f1
-      value: 45.374485104940476
+      value: 49.74264614001562
   - task:
       type: Classification
     dataset:
@@ -3378,9 +2481,9 @@ model-index:
       revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
     metrics:
     - type: accuracy
-      value: 54.25863044708545
+      value: 56.47425014148275
     - type: f1
-      value: 54.20154252609619
+      value: 56.555750746223346
   - task:
       type: Clustering
     dataset:
@@ -3391,7 +2494,7 @@ model-index:
       revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
     metrics:
     - type: v_measure
-      value: 34.3883169293051
+      value: 39.27004599453324
   - task:
       type: PairClassification
     dataset:
@@ -3402,51 +2505,51 @@ model-index:
       revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
     metrics:
     - type: cos_sim_accuracy
-      value: 81.76670441676104
+      value: 84.47875067056088
     - type: cos_sim_ap
-      value: 59.29878710961347
+      value: 68.630858164926
     - type: cos_sim_f1
-      value: 57.33284971587474
+      value: 64.5112402121748
     - type: cos_sim_precision
-      value: 52.9122963624191
+      value: 61.87015503875969
     - type: cos_sim_recall
-      value: 62.559366754617415
+      value: 67.38786279683377
     - type: dot_accuracy
-      value: 77.52279907015557
+      value: 77.68969422423557
     - type: dot_ap
-      value: 34.17588904643467
+      value: 37.28838556128439
     - type: dot_f1
-      value: 41.063567529494634
+      value: 43.27918525376652
     - type: dot_precision
-      value: 30.813953488372093
+      value: 31.776047460140898
     - type: dot_recall
-      value: 61.53034300791557
+      value: 67.83641160949868
     - type: euclidean_accuracy
-      value: 80.61631996185254
+      value: 82.67866722298385
     - type: euclidean_ap
-      value: 54.00362361479352
+      value: 62.72011158877603
     - type: euclidean_f1
-      value: 53.99111751290361
+      value: 60.39579770339605
     - type: euclidean_precision
-      value: 49.52653600528518
+      value: 56.23293903548681
     - type: euclidean_recall
-      value: 59.340369393139845
+      value: 65.22427440633246
     - type: manhattan_accuracy
-      value: 80.65208320915539
+      value: 82.67866722298385
     - type: manhattan_ap
-      value: 54.18329507159467
+      value: 62.80364769571995
     - type: manhattan_f1
-      value: 53.85550960836779
+      value: 60.413827282864574
     - type: manhattan_precision
-      value: 49.954873646209386
+      value: 56.94931090866619
     - type: manhattan_recall
-      value: 58.41688654353562
+      value: 64.32717678100263
     - type: max_accuracy
-      value: 81.76670441676104
+      value: 84.47875067056088
     - type: max_ap
-      value: 59.29878710961347
+      value: 68.630858164926
     - type: max_f1
-      value: 57.33284971587474
+      value: 64.5112402121748
   - task:
       type: PairClassification
     dataset:
@@ -3457,51 +2560,51 @@ model-index:
       revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
     metrics:
     - type: cos_sim_accuracy
-      value: 87.99433383785463
+      value: 88.4192959987581
     - type: cos_sim_ap
-      value: 83.43513915159009
+      value: 84.81803796578367
     - type: cos_sim_f1
-      value: 76.3906784964842
+      value: 77.1643709825528
     - type: cos_sim_precision
-      value: 73.19223985890653
+      value: 73.77958839643183
     - type: cos_sim_recall
-      value: 79.88142901139513
+      value: 80.874653526332
     - type: dot_accuracy
-      value: 81.96142352621571
+      value: 81.99441145651414
     - type: dot_ap
-      value: 67.78764755689359
+      value: 67.908510950511
     - type: dot_f1
-      value: 64.42823356983445
+      value: 64.4734255193656
     - type: dot_precision
-      value: 56.77801913931779
+      value: 56.120935539075866
     - type: dot_recall
-      value: 74.46104096088698
+      value: 75.74684323991376
     - type: euclidean_accuracy
-      value: 81.9478402607987
+      value: 82.67163426087632
     - type: euclidean_ap
-      value: 67.13958457373279
+      value: 70.1466353903414
     - type: euclidean_f1
-      value: 60.45118343195266
+      value: 62.686024087617795
     - type: euclidean_precision
-      value: 58.1625391403359
+      value: 59.42738875474301
     - type: euclidean_recall
-      value: 62.92731752386819
+      value: 66.32275947028026
     - type: manhattan_accuracy
-      value: 82.01769705437188
+      value: 82.6483486630186
     - type: manhattan_ap
-      value: 67.24709477497046
+      value: 70.12958345267741
     - type: manhattan_f1
-      value: 60.4103846436714
+      value: 62.5966218150587
     - type: manhattan_precision
-      value: 57.82063916654935
+      value: 58.47820272800214
     - type: manhattan_recall
-      value: 63.24299353249153
+      value: 67.33908222975053
     - type: max_accuracy
-      value: 87.99433383785463
+      value: 88.4192959987581
     - type: max_ap
-      value: 83.43513915159009
+      value: 84.81803796578367
     - type: max_f1
-      value: 76.3906784964842
+      value: 77.1643709825528
 ---
 ---