update readme

README.md

@@ -1,5 +1,8 @@
 ---
 tags:
+- feature-extraction
+- sentence-similarity
+- transformers
 - mteb
 model-index:
 - name: embedder-100p
@@ -29,11 +32,11 @@ model-index:
       revision: e2d317d38cd51312af73b3d32a06d1a08b442046
     metrics:
     - type: accuracy
-      value: 70.40859999999999
+      value: 70.40857500000001
     - type: ap
-      value: 64.61614079870762
+      value: 64.61611594622543
     - type: f1
-      value: 70.28138858999333
+      value: 70.28136292034776
   - task:
       type: Classification
     dataset:
@@ -69,17 +72,17 @@ model-index:
     - type: map_at_5
       value: 40.398
     - type: mrr_at_1
-      value: 28.377999999999997
+      value: 28.165000000000003
     - type: mrr_at_10
-      value: 43.138
+      value: 43.05
     - type: mrr_at_100
-      value: 44.088
+      value: 43.994
     - type: mrr_at_1000
-      value: 44.095
+      value: 44.0
     - type: mrr_at_3
-      value: 37.47
+      value: 37.376
     - type: mrr_at_5
-      value: 40.749
+      value: 40.665
     - type: ndcg_at_1
       value: 27.311999999999998
     - type: ndcg_at_10
@@ -126,7 +129,7 @@ model-index:
       revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
     metrics:
     - type: v_measure
-      value: 43.04296157693406
+      value: 42.899186071418946
   - task:
       type: Clustering
     dataset:
@@ -137,7 +140,7 @@ model-index:
       revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
     metrics:
     - type: v_measure
-      value: 32.376069442373264
+      value: 32.44851270109027
   - task:
       type: Reranking
     dataset:
@@ -161,15 +164,15 @@ model-index:
       revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
     metrics:
     - type: cos_sim_pearson
-      value: 80.06754584325645
+      value: 80.06755261269532
     - type: cos_sim_spearman
       value: 75.31798123153732
     - type: euclidean_pearson
-      value: 77.70453914618555
+      value: 77.70454789166935
     - type: euclidean_spearman
       value: 74.07578425253767
     - type: manhattan_pearson
-      value: 77.18020595680719
+      value: 77.18021593857006
     - type: manhattan_spearman
       value: 74.10590542079663
   - task:
@@ -195,7 +198,7 @@ model-index:
       revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
     metrics:
     - type: v_measure
-      value: 37.35544823305565
+      value: 37.236246179832975
   - task:
       type: Clustering
     dataset:
@@ -206,7 +209,7 @@ model-index:
       revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
     metrics:
     - type: v_measure
-      value: 29.97526476348527
+      value: 29.75182197424716
   - task:
       type: Retrieval
     dataset:
@@ -304,7 +307,7 @@ model-index:
     - type: mrr_at_100
       value: 38.942
     - type: mrr_at_1000
-      value: 38.992
+      value: 38.993
     - type: mrr_at_3
       value: 35.435
     - type: mrr_at_5
@@ -316,7 +319,7 @@ model-index:
     - type: ndcg_at_100
       value: 43.562
     - type: ndcg_at_1000
-      value: 46.035
+      value: 46.036
     - type: ndcg_at_3
       value: 33.93
     - type: ndcg_at_5
@@ -690,6 +693,75 @@ model-index:
       value: 34.489
     - type: recall_at_5
       value: 40.182
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.159999999999997
+    - type: map_at_10
+      value: 29.421333333333337
+    - type: map_at_100
+      value: 30.61058333333333
+    - type: map_at_1000
+      value: 30.742416666666667
+    - type: map_at_3
+      value: 26.745833333333337
+    - type: map_at_5
+      value: 28.20291666666667
+    - type: mrr_at_1
+      value: 25.308249999999997
+    - type: mrr_at_10
+      value: 33.21275
+    - type: mrr_at_100
+      value: 34.09341666666666
+    - type: mrr_at_1000
+      value: 34.163000000000004
+    - type: mrr_at_3
+      value: 30.81675
+    - type: mrr_at_5
+      value: 32.16816666666667
+    - type: ndcg_at_1
+      value: 25.308249999999997
+    - type: ndcg_at_10
+      value: 34.46208333333333
+    - type: ndcg_at_100
+      value: 39.77183333333334
+    - type: ndcg_at_1000
+      value: 42.461916666666674
+    - type: ndcg_at_3
+      value: 29.797916666666662
+    - type: ndcg_at_5
+      value: 31.935166666666664
+    - type: precision_at_1
+      value: 25.308249999999997
+    - type: precision_at_10
+      value: 6.260916666666666
+    - type: precision_at_100
+      value: 1.0716666666666665
+    - type: precision_at_1000
+      value: 0.15025000000000002
+    - type: precision_at_3
+      value: 13.926916666666667
+    - type: precision_at_5
+      value: 10.043916666666664
+    - type: recall_at_1
+      value: 21.159999999999997
+    - type: recall_at_10
+      value: 45.61408333333334
+    - type: recall_at_100
+      value: 69.26583333333332
+    - type: recall_at_1000
+      value: 88.22541666666667
+    - type: recall_at_3
+      value: 32.67691666666666
+    - type: recall_at_5
+      value: 38.12716666666667
   - task:
       type: Retrieval
     dataset:
@@ -913,7 +985,7 @@ model-index:
     - type: map_at_100
       value: 28.875
     - type: map_at_1000
-      value: 29.151
+      value: 29.152
     - type: map_at_3
       value: 24.595
     - type: map_at_5
@@ -1186,6 +1258,75 @@ model-index:
       value: 43.470000000000006
     - type: f1
       value: 39.27142511079909
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.468
+    - type: map_at_10
+      value: 49.652
+    - type: map_at_100
+      value: 50.314
+    - type: map_at_1000
+      value: 50.346999999999994
+    - type: map_at_3
+      value: 46.592
+    - type: map_at_5
+      value: 48.553000000000004
+    - type: mrr_at_1
+      value: 40.384
+    - type: mrr_at_10
+      value: 53.03099999999999
+    - type: mrr_at_100
+      value: 53.629000000000005
+    - type: mrr_at_1000
+      value: 53.65299999999999
+    - type: mrr_at_3
+      value: 49.967
+    - type: mrr_at_5
+      value: 51.951
+    - type: ndcg_at_1
+      value: 40.384
+    - type: ndcg_at_10
+      value: 56.318
+    - type: ndcg_at_100
+      value: 59.43000000000001
+    - type: ndcg_at_1000
+      value: 60.266
+    - type: ndcg_at_3
+      value: 50.341
+    - type: ndcg_at_5
+      value: 53.756
+    - type: precision_at_1
+      value: 40.384
+    - type: precision_at_10
+      value: 8.062999999999999
+    - type: precision_at_100
+      value: 0.972
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 20.897
+    - type: precision_at_5
+      value: 14.374
+    - type: recall_at_1
+      value: 37.468
+    - type: recall_at_10
+      value: 73.68900000000001
+    - type: recall_at_100
+      value: 87.844
+    - type: recall_at_1000
+      value: 94.098
+    - type: recall_at_3
+      value: 57.768
+    - type: recall_at_5
+      value: 65.979
   - task:
       type: Retrieval
     dataset:
@@ -1255,6 +1396,75 @@ model-index:
       value: 24.490000000000002
     - type: recall_at_5
       value: 28.621999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.659
+    - type: map_at_10
+      value: 33.622
+    - type: map_at_100
+      value: 34.488
+    - type: map_at_1000
+      value: 34.58
+    - type: map_at_3
+      value: 31.317
+    - type: map_at_5
+      value: 32.689
+    - type: mrr_at_1
+      value: 49.318
+    - type: mrr_at_10
+      value: 57.028999999999996
+    - type: mrr_at_100
+      value: 57.567
+    - type: mrr_at_1000
+      value: 57.603
+    - type: mrr_at_3
+      value: 55.152
+    - type: mrr_at_5
+      value: 56.289
+    - type: ndcg_at_1
+      value: 49.318
+    - type: ndcg_at_10
+      value: 42.091
+    - type: ndcg_at_100
+      value: 45.812999999999995
+    - type: ndcg_at_1000
+      value: 47.902
+    - type: ndcg_at_3
+      value: 38.012
+    - type: ndcg_at_5
+      value: 40.160000000000004
+    - type: precision_at_1
+      value: 49.318
+    - type: precision_at_10
+      value: 8.921
+    - type: precision_at_100
+      value: 1.189
+    - type: precision_at_1000
+      value: 0.147
+    - type: precision_at_3
+      value: 23.655
+    - type: precision_at_5
+      value: 15.897
+    - type: recall_at_1
+      value: 24.659
+    - type: recall_at_10
+      value: 44.605
+    - type: recall_at_100
+      value: 59.453
+    - type: recall_at_1000
+      value: 73.40299999999999
+    - type: recall_at_3
+      value: 35.483
+    - type: recall_at_5
+      value: 39.743
   - task:
       type: Classification
     dataset:
@@ -1270,6 +1480,75 @@ model-index:
       value: 61.82215741645874
     - type: f1
       value: 67.04790333380426
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 13.635
+    - type: map_at_10
+      value: 22.412000000000003
+    - type: map_at_100
+      value: 23.622
+    - type: map_at_1000
+      value: 23.707
+    - type: map_at_3
+      value: 19.368
+    - type: map_at_5
+      value: 21.095
+    - type: mrr_at_1
+      value: 14.04
+    - type: mrr_at_10
+      value: 22.858
+    - type: mrr_at_100
+      value: 24.049
+    - type: mrr_at_1000
+      value: 24.127000000000002
+    - type: mrr_at_3
+      value: 19.852
+    - type: mrr_at_5
+      value: 21.552
+    - type: ndcg_at_1
+      value: 14.04
+    - type: ndcg_at_10
+      value: 27.676000000000002
+    - type: ndcg_at_100
+      value: 33.917
+    - type: ndcg_at_1000
+      value: 36.217
+    - type: ndcg_at_3
+      value: 21.432000000000002
+    - type: ndcg_at_5
+      value: 24.519
+    - type: precision_at_1
+      value: 14.04
+    - type: precision_at_10
+      value: 4.585999999999999
+    - type: precision_at_100
+      value: 0.776
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 9.298
+    - type: precision_at_5
+      value: 7.135
+    - type: recall_at_1
+      value: 13.635
+    - type: recall_at_10
+      value: 44.015
+    - type: recall_at_100
+      value: 73.756
+    - type: recall_at_1000
+      value: 91.743
+    - type: recall_at_3
+      value: 26.941
+    - type: recall_at_5
+      value: 34.378
   - task:
       type: Classification
     dataset:
@@ -1332,7 +1611,7 @@ model-index:
       revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
     metrics:
     - type: v_measure
-      value: 36.5297446116069
+      value: 36.646200212660744
   - task:
       type: Clustering
     dataset:
@@ -1343,7 +1622,20 @@ model-index:
       revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
     metrics:
     - type: v_measure
-      value: 32.93068854285488
+      value: 32.57381797665868
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 30.54815546178676
+    - type: mrr
+      value: 31.40311212966208
   - task:
       type: Retrieval
     dataset:
@@ -1366,17 +1658,17 @@ model-index:
     - type: map_at_5
       value: 6.654
     - type: mrr_at_1
-      value: 34.365
+      value: 33.745999999999995
     - type: mrr_at_10
-      value: 43.854
+      value: 43.513000000000005
     - type: mrr_at_100
-      value: 44.643
+      value: 44.330999999999996
     - type: mrr_at_1000
-      value: 44.701
+      value: 44.388
     - type: mrr_at_3
-      value: 41.589
+      value: 41.28
     - type: mrr_at_5
-      value: 43.075
+      value: 42.766
     - type: ndcg_at_1
       value: 31.889
     - type: ndcg_at_10
@@ -1494,63 +1786,63 @@ model-index:
     - type: map_at_1
       value: 67.534
     - type: map_at_10
-      value: 81.447
+      value: 81.449
     - type: map_at_100
-      value: 82.15299999999999
+      value: 82.15400000000001
     - type: map_at_1000
-      value: 82.172
+      value: 82.173
     - type: map_at_3
-      value: 78.408
+      value: 78.412
     - type: map_at_5
-      value: 80.264
+      value: 80.268
     - type: mrr_at_1
-      value: 77.75999999999999
+      value: 77.77
     - type: mrr_at_10
-      value: 84.602
+      value: 84.60499999999999
     - type: mrr_at_100
-      value: 84.762
+      value: 84.765
     - type: mrr_at_1000
-      value: 84.764
+      value: 84.76700000000001
     - type: mrr_at_3
-      value: 83.488
+      value: 83.493
     - type: mrr_at_5
-      value: 84.21600000000001
+      value: 84.221
     - type: ndcg_at_1
       value: 77.79
     - type: ndcg_at_10
-      value: 85.55199999999999
+      value: 85.555
     - type: ndcg_at_100
-      value: 87.104
+      value: 87.105
     - type: ndcg_at_1000
-      value: 87.259
+      value: 87.261
     - type: ndcg_at_3
-      value: 82.396
+      value: 82.401
     - type: ndcg_at_5
-      value: 84.065
+      value: 84.071
     - type: precision_at_1
       value: 77.79
     - type: precision_at_10
-      value: 13.103000000000002
+      value: 13.104
     - type: precision_at_100
       value: 1.5190000000000001
     - type: precision_at_1000
       value: 0.156
     - type: precision_at_3
-      value: 36.153
+      value: 36.157000000000004
     - type: precision_at_5
-      value: 23.854
+      value: 23.86
     - type: recall_at_1
       value: 67.534
     - type: recall_at_10
-      value: 93.57
+      value: 93.573
     - type: recall_at_100
       value: 99.10799999999999
     - type: recall_at_1000
       value: 99.911
     - type: recall_at_3
-      value: 84.565
+      value: 84.575
     - type: recall_at_5
-      value: 89.242
+      value: 89.251
   - task:
       type: Clustering
     dataset:
@@ -1561,7 +1853,7 @@ model-index:
       revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
     metrics:
     - type: v_measure
-      value: 50.692859418431055
+      value: 50.622402916164575
   - task:
       type: Clustering
     dataset:
@@ -1572,7 +1864,7 @@ model-index:
       revision: 282350215ef01743dc01b456c7f5241fa8937f16
     metrics:
     - type: v_measure
-      value: 54.60918566392905
+      value: 54.43689895218044
   - task:
       type: Retrieval
     dataset:
@@ -1652,17 +1944,17 @@ model-index:
       revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
     metrics:
     - type: cos_sim_pearson
-      value: 85.92797781212799
+      value: 85.92797679109452
     - type: cos_sim_spearman
-      value: 80.91206843308156
+      value: 80.91205372065706
     - type: euclidean_pearson
-      value: 83.13392453336924
+      value: 83.1339233055303
     - type: euclidean_spearman
-      value: 80.80408822887594
+      value: 80.80406858672507
     - type: manhattan_pearson
-      value: 83.02335189403584
+      value: 83.023350668501
     - type: manhattan_spearman
-      value: 80.79923937077382
+      value: 80.79924041758802
   - task:
       type: STS
     dataset:
@@ -1673,17 +1965,17 @@ model-index:
       revision: a0d554a64d88156834ff5ae9920b964011b16384
     metrics:
     - type: cos_sim_pearson
-      value: 85.4017983656709
+      value: 85.40179876416202
     - type: cos_sim_spearman
-      value: 76.97735367672956
+      value: 76.97735281189986
     - type: euclidean_pearson
-      value: 81.7824234578701
+      value: 81.78242131839902
     - type: euclidean_spearman
-      value: 75.28260048723786
+      value: 75.2853626575815
     - type: manhattan_pearson
-      value: 81.38214845806081
+      value: 81.38214640501
     - type: manhattan_spearman
-      value: 74.96457943242224
+      value: 74.96725680962342
   - task:
       type: STS
     dataset:
@@ -1694,17 +1986,17 @@ model-index:
       revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
     metrics:
     - type: cos_sim_pearson
-      value: 81.38943576368895
+      value: 81.38943723638555
     - type: cos_sim_spearman
       value: 82.62953855483207
     - type: euclidean_pearson
-      value: 82.44174445208601
+      value: 82.4417464172415
     - type: euclidean_spearman
-      value: 82.82393564259752
+      value: 82.8241086805702
     - type: manhattan_pearson
-      value: 82.0592576486719
+      value: 82.05925934320744
     - type: manhattan_spearman
-      value: 82.44019945976245
+      value: 82.44019953304266
   - task:
       type: STS
     dataset:
@@ -1715,17 +2007,17 @@ model-index:
       revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
     metrics:
     - type: cos_sim_pearson
-      value: 81.56920926205309
+      value: 81.56920959786761
     - type: cos_sim_spearman
-      value: 77.83933445496699
+      value: 77.83933203825715
     - type: euclidean_pearson
-      value: 81.34174612772163
+      value: 81.34174603327101
     - type: euclidean_spearman
-      value: 78.05064601571459
+      value: 78.05064087128034
     - type: manhattan_pearson
-      value: 81.17542466190758
+      value: 81.1754246859513
     - type: manhattan_spearman
-      value: 77.89655461392648
+      value: 77.8965324094323
   - task:
       type: STS
     dataset:
@@ -1736,17 +2028,17 @@ model-index:
       revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
     metrics:
     - type: cos_sim_pearson
-      value: 84.70673349392224
+      value: 84.70673290528633
     - type: cos_sim_spearman
-      value: 85.91810021018937
+      value: 85.918072169933
     - type: euclidean_pearson
-      value: 85.49668352710347
+      value: 85.49668339564212
     - type: euclidean_spearman
-      value: 86.07561846419777
+      value: 86.07562791847965
     - type: manhattan_pearson
-      value: 85.46112249008104
+      value: 85.46112200749786
     - type: manhattan_spearman
-      value: 86.06360341157644
+      value: 86.06360174588102
   - task:
       type: STS
     dataset:
@@ -1757,17 +2049,17 @@ model-index:
       revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
     metrics:
     - type: cos_sim_pearson
-      value: 78.57362568259491
+      value: 78.57362584144626
     - type: cos_sim_spearman
       value: 80.68461073524229
     - type: euclidean_pearson
-      value: 81.86974763548425
+      value: 81.86974700030184
     - type: euclidean_spearman
-      value: 81.95566663477153
+      value: 81.9556672243023
     - type: manhattan_pearson
-      value: 81.58501328641869
+      value: 81.58501319903948
     - type: manhattan_spearman
-      value: 81.65934245751299
+      value: 81.65934304491222
   - task:
       type: STS
     dataset:
@@ -1778,15 +2070,15 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 89.05177322670748
+      value: 89.0517739143147
     - type: cos_sim_spearman
       value: 88.99264497015508
     - type: euclidean_pearson
-      value: 88.6014395983479
+      value: 88.60143851830212
     - type: euclidean_spearman
       value: 88.417049574577
     - type: manhattan_pearson
-      value: 88.71275753473458
+      value: 88.71275731832226
     - type: manhattan_spearman
       value: 88.62174073802386
   - task:
@@ -1799,15 +2091,15 @@ model-index:
       revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
     metrics:
     - type: cos_sim_pearson
-      value: 65.92377340266665
+      value: 65.92377536840165
     - type: cos_sim_spearman
       value: 68.25861908141049
     - type: euclidean_pearson
-      value: 67.74046333852377
+      value: 67.74046365058068
     - type: euclidean_spearman
       value: 67.74440638624723
     - type: manhattan_pearson
-      value: 67.72314507899021
+      value: 67.72314553247108
     - type: manhattan_spearman
       value: 67.58993746063668
   - task:
@@ -1820,15 +2112,15 @@ model-index:
       revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
     metrics:
     - type: cos_sim_pearson
-      value: 84.01280176574436
+      value: 84.01280212650944
     - type: cos_sim_spearman
       value: 84.2021805427655
     - type: euclidean_pearson
-      value: 85.25937079924432
+      value: 85.2593711183253
     - type: euclidean_spearman
       value: 84.7692260813728
     - type: manhattan_pearson
-      value: 85.20370061224156
+      value: 85.20370142077513
     - type: manhattan_spearman
       value: 84.68261435873887
   - task:
@@ -1935,7 +2227,7 @@ model-index:
     - type: dot_accuracy
       value: 99.6009900990099
     - type: dot_ap
-      value: 85.37859661864812
+      value: 85.37859415933599
     - type: dot_f1
       value: 79.68285431119922
     - type: dot_precision
@@ -1945,7 +2237,7 @@ model-index:
     - type: euclidean_accuracy
       value: 99.66435643564357
     - type: euclidean_ap
-      value: 90.28983244955693
+      value: 90.28983244955695
     - type: euclidean_f1
       value: 82.47925817471938
     - type: euclidean_precision
@@ -1955,7 +2247,7 @@ model-index:
     - type: manhattan_accuracy
       value: 99.65247524752475
     - type: manhattan_ap
-      value: 89.75455639322132
+      value: 89.75455076116366
     - type: manhattan_f1
       value: 81.63682864450128
     - type: manhattan_precision
@@ -1978,7 +2270,7 @@ model-index:
       revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
     metrics:
     - type: v_measure
-      value: 53.295453205851
+      value: 54.25773656414605
   - task:
       type: Clustering
     dataset:
@@ -1989,7 +2281,7 @@ model-index:
       revision: 815ca46b2622cec33ccafc3735d572c266efdb44
     metrics:
     - type: v_measure
-      value: 32.64179363201445
+      value: 32.52034918177213
   - task:
       type: Reranking
     dataset:
@@ -2000,26 +2292,9 @@ model-index:
       revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
     metrics:
     - type: map
-      value: 47.103383708653894
+      value: 47.10460797458404
     - type: mrr
-      value: 47.64253618113912
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 30.794109958863856
-    - type: cos_sim_spearman
-      value: 32.38893238877061
-    - type: dot_pearson
-      value: 25.573206015466006
-    - type: dot_spearman
-      value: 26.69770548172811
+      value: 47.67126358119005
   - task:
       type: Retrieval
     dataset:
@@ -2168,11 +2443,11 @@ model-index:
       revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
     metrics:
     - type: accuracy
-      value: 67.4808
+      value: 67.481
     - type: ap
-      value: 12.474767995994732
+      value: 12.474830532963725
     - type: f1
-      value: 51.7199877262739
+      value: 51.720124230716834
   - task:
       type: Classification
     dataset:
@@ -2196,7 +2471,7 @@ model-index:
       revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
     metrics:
     - type: v_measure
-      value: 45.75265994155206
+      value: 45.695133575997474
   - task:
       type: PairClassification
     dataset:
@@ -2209,7 +2484,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 84.16284198605233
     - type: cos_sim_ap
-      value: 67.7713341907894
+      value: 67.77133994574282
     - type: cos_sim_f1
       value: 63.007767732076914
     - type: cos_sim_precision
@@ -2219,7 +2494,7 @@ model-index:
     - type: dot_accuracy
       value: 80.60439887941826
     - type: dot_ap
-      value: 55.17279708911177
+      value: 55.17278808505333
     - type: dot_f1
       value: 55.023250784038055
     - type: dot_precision
@@ -2229,7 +2504,7 @@ model-index:
     - type: euclidean_accuracy
       value: 84.75889610776659
     - type: euclidean_ap
-      value: 69.339283557053
+      value: 69.33925609880741
     - type: euclidean_f1
       value: 64.72887151929653
     - type: euclidean_precision
@@ -2239,7 +2514,7 @@ model-index:
     - type: manhattan_accuracy
       value: 84.84234368480658
     - type: manhattan_ap
-      value: 69.50781739580388
+      value: 69.50780726475959
     - type: manhattan_f1
       value: 64.78766430738119
     - type: manhattan_precision
@@ -2249,7 +2524,7 @@ model-index:
     - type: max_accuracy
       value: 84.84234368480658
     - type: max_ap
-      value: 69.50781739580388
+      value: 69.50780726475959
     - type: max_f1
       value: 64.78766430738119
   - task:
@@ -2264,7 +2539,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 88.46198626149726
     - type: cos_sim_ap
-      value: 84.64910523561979
+      value: 84.64911720373662
     - type: cos_sim_f1
       value: 77.18601251827143
     - type: cos_sim_precision
@@ -2274,7 +2549,7 @@ model-index:
     - type: dot_accuracy
       value: 86.79512554818179
     - type: dot_ap
-      value: 80.43209362097343
+      value: 80.43213280609042
     - type: dot_f1
       value: 74.18943791589976
     - type: dot_precision
@@ -2284,7 +2559,7 @@ model-index:
     - type: euclidean_accuracy
       value: 88.2368921488726
     - type: euclidean_ap
-      value: 84.27906162916011
+      value: 84.2791000321804
     - type: euclidean_f1
       value: 76.62216238453198
     - type: euclidean_precision
@@ -2294,7 +2569,7 @@ model-index:
     - type: manhattan_accuracy
       value: 88.29122521054062
     - type: manhattan_ap
-      value: 84.2549146077175
+      value: 84.25495067571485
     - type: manhattan_f1
       value: 76.60077590984667
     - type: manhattan_precision
@@ -2304,7 +2579,7 @@ model-index:
     - type: max_accuracy
       value: 88.46198626149726
     - type: max_ap
-      value: 84.64910523561979
+      value: 84.64911720373662
     - type: max_f1
       value: 77.18601251827143
 ---