diff --git "a/README.md" "b/README.md"
--- "a/README.md"
+++ "b/README.md"
@@ -3,7 +3,7 @@ license: cc-by-nc-4.0
 tags:
 - mteb
 model-index:
-- name: text_sonar_basic_encoder
+- name: text_sonar_basic_encoder_normalized
   results:
   - task:
       type: Clustering
@@ -15,7 +15,7 @@ model-index:
       revision: None
     metrics:
     - type: v_measure
-      value: 14.51482032569021
+      value: 18.787544117314575
   - task:
       type: STS
     dataset:
@@ -26,17 +26,17 @@ model-index:
       revision: b44c3b011063adb25877c13823db83bb193913c4
     metrics:
     - type: cos_sim_pearson
-      value: 17.970264353352682
+      value: 17.97026675319667
     - type: cos_sim_spearman
-      value: 17.633997882973155
+      value: 17.63407829948615
     - type: euclidean_pearson
-      value: 14.014776236053123
+      value: 17.704571608660725
     - type: euclidean_spearman
-      value: 15.28941515698961
+      value: 17.634078298828143
     - type: manhattan_pearson
-      value: 13.891563198299256
+      value: 17.606959101509464
     - type: manhattan_spearman
-      value: 15.158415586569143
+      value: 17.549620164990085
   - task:
       type: STS
     dataset:
@@ -47,17 +47,17 @@ model-index:
       revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
     metrics:
     - type: cos_sim_pearson
-      value: 27.670887710562912
+      value: 27.670887504789675
     - type: cos_sim_spearman
-      value: 26.176635036642804
+      value: 26.176629407301782
     - type: euclidean_pearson
-      value: 24.115430353423346
+      value: 28.878485717935586
     - type: euclidean_spearman
-      value: 24.31920807107195
+      value: 26.176635036613355
     - type: manhattan_pearson
-      value: 23.998151286247396
+      value: 28.782373978690103
     - type: manhattan_spearman
-      value: 24.167187716649224
+      value: 26.055266444113794
   - task:
       type: Classification
     dataset:
@@ -68,9 +68,9 @@ model-index:
       revision: None
     metrics:
     - type: accuracy
-      value: 29.85089463220676
+      value: 29.62226640159046
     - type: f1
-      value: 27.632986641843516
+      value: 27.632722290701047
   - task:
       type: Classification
     dataset:
@@ -81,11 +81,11 @@ model-index:
       revision: e8379541af4e31359cca9fbcf4b00f2671dba205
     metrics:
     - type: accuracy
-      value: 78.98507462686568
+      value: 81.49253731343285
     - type: ap
-      value: 44.08138737273602
+      value: 46.61440947240349
     - type: f1
-      value: 73.46285533200773
+      value: 75.68925212232107
   - task:
       type: Classification
     dataset:
@@ -96,11 +96,11 @@ model-index:
       revision: e8379541af4e31359cca9fbcf4b00f2671dba205
     metrics:
     - type: accuracy
-      value: 72.00214132762312
+      value: 72.02355460385438
     - type: ap
-      value: 82.19993680100252
+      value: 83.13664983282676
     - type: f1
-      value: 70.11447824125146
+      value: 70.48997817871013
   - task:
       type: Classification
     dataset:
@@ -111,11 +111,11 @@ model-index:
       revision: e8379541af4e31359cca9fbcf4b00f2671dba205
     metrics:
     - type: accuracy
-      value: 81.28935532233884
+      value: 82.09145427286357
     - type: ap
-      value: 30.144590364670528
+      value: 31.45181004731995
     - type: f1
-      value: 68.42566054607258
+      value: 69.41750580313406
   - task:
       type: Classification
     dataset:
@@ -126,11 +126,11 @@ model-index:
       revision: e8379541af4e31359cca9fbcf4b00f2671dba205
     metrics:
     - type: accuracy
-      value: 67.7730192719486
+      value: 71.78800856531049
     - type: ap
-      value: 18.42471917082788
+      value: 19.65443896353892
     - type: f1
-      value: 55.72761001975526
+      value: 58.436688187826334
   - task:
       type: Classification
     dataset:
@@ -141,11 +141,11 @@ model-index:
       revision: e2d317d38cd51312af73b3d32a06d1a08b442046
     metrics:
     - type: accuracy
-      value: 61.521125
+      value: 62.73074999999999
     - type: ap
-      value: 57.23445163027374
+      value: 58.2839375458089
     - type: f1
-      value: 60.73008406893218
+      value: 62.16204082406629
   - task:
       type: Classification
     dataset:
@@ -156,9 +156,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 30.491999999999997
+      value: 31.552000000000003
     - type: f1
-      value: 29.557204623883994
+      value: 31.125328770568277
   - task:
       type: Classification
     dataset:
@@ -169,9 +169,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 33.386
+      value: 34.611999999999995
     - type: f1
-      value: 31.84048812033152
+      value: 33.93738697105999
   - task:
       type: Classification
     dataset:
@@ -182,9 +182,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 34.866
+      value: 35.172
     - type: f1
-      value: 32.99012859140412
+      value: 34.14112656493798
   - task:
       type: Classification
     dataset:
@@ -195,9 +195,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 34.062000000000005
+      value: 34.910000000000004
     - type: f1
-      value: 33.25848878845983
+      value: 34.276631172288965
   - task:
       type: Classification
     dataset:
@@ -208,9 +208,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 31.023999999999997
+      value: 31.844
     - type: f1
-      value: 30.458831589997278
+      value: 31.478780923476368
   - task:
       type: Classification
     dataset:
@@ -221,9 +221,9 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 30.994
+      value: 31.912000000000003
     - type: f1
-      value: 30.061575356482727
+      value: 31.384992191831312
   - task:
       type: Classification
     dataset:
@@ -234,9 +234,9 @@ model-index:
       revision: 20b0e6081892e78179356fada741b7afa381443d
     metrics:
     - type: accuracy
-      value: 48.223495702005735
+      value: 49.61795606494747
     - type: f1
-      value: 47.162760921004896
+      value: 48.63625944670304
   - task:
       type: Retrieval
     dataset:
@@ -306,6 +306,75 @@ model-index:
       value: 17.354
     - type: recall_at_5
       value: 22.902
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana-pl
+      name: MTEB ArguAna-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 7.752000000000001
+    - type: map_at_10
+      value: 12.248000000000001
+    - type: map_at_100
+      value: 12.882
+    - type: map_at_1000
+      value: 12.963
+    - type: map_at_3
+      value: 10.574
+    - type: map_at_5
+      value: 11.566
+    - type: mrr_at_1
+      value: 7.824000000000001
+    - type: mrr_at_10
+      value: 12.293
+    - type: mrr_at_100
+      value: 12.928
+    - type: mrr_at_1000
+      value: 13.008000000000001
+    - type: mrr_at_3
+      value: 10.586
+    - type: mrr_at_5
+      value: 11.599
+    - type: ndcg_at_1
+      value: 7.752000000000001
+    - type: ndcg_at_10
+      value: 15.035000000000002
+    - type: ndcg_at_100
+      value: 18.497
+    - type: ndcg_at_1000
+      value: 20.896
+    - type: ndcg_at_3
+      value: 11.578
+    - type: ndcg_at_5
+      value: 13.38
+    - type: precision_at_1
+      value: 7.752000000000001
+    - type: precision_at_10
+      value: 2.404
+    - type: precision_at_100
+      value: 0.411
+    - type: precision_at_1000
+      value: 0.061
+    - type: precision_at_3
+      value: 4.836
+    - type: precision_at_5
+      value: 3.784
+    - type: recall_at_1
+      value: 7.752000000000001
+    - type: recall_at_10
+      value: 24.04
+    - type: recall_at_100
+      value: 41.11
+    - type: recall_at_1000
+      value: 60.597
+    - type: recall_at_3
+      value: 14.509
+    - type: recall_at_5
+      value: 18.919
   - task:
       type: Clustering
     dataset:
@@ -316,7 +385,7 @@ model-index:
       revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
     metrics:
     - type: v_measure
-      value: 25.78534535464707
+      value: 26.81177290816682
   - task:
       type: Clustering
     dataset:
@@ -327,7 +396,7 @@ model-index:
       revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
     metrics:
     - type: v_measure
-      value: 22.935310338963955
+      value: 24.346811178757022
   - task:
       type: Reranking
     dataset:
@@ -351,17 +420,17 @@ model-index:
       revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
     metrics:
     - type: cos_sim_pearson
-      value: 77.15058570798328
+      value: 77.15058512395619
     - type: cos_sim_spearman
       value: 79.10541692841936
     - type: euclidean_pearson
-      value: 57.77256072255626
+      value: 75.30525535929353
     - type: euclidean_spearman
-      value: 61.9206880133157
+      value: 79.10541692841936
     - type: manhattan_pearson
-      value: 57.61971995547671
+      value: 75.33508042552984
     - type: manhattan_spearman
-      value: 61.65983869619309
+      value: 78.84577245802708
   - task:
       type: STS
     dataset:
@@ -372,17 +441,17 @@ model-index:
       revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
     metrics:
     - type: cos_sim_pearson
-      value: 37.84739182483413
+      value: 37.84739189558895
     - type: cos_sim_spearman
-      value: 37.6627002178424
+      value: 37.662710610486265
     - type: euclidean_pearson
-      value: 31.20207774134489
+      value: 37.5407537185213
     - type: euclidean_spearman
-      value: 32.258185520047554
+      value: 37.66272446700578
     - type: manhattan_pearson
-      value: 31.45043795745484
+      value: 37.863820146709706
     - type: manhattan_spearman
-      value: 32.432706960003095
+      value: 38.09120266204032
   - task:
       type: BitextMining
     dataset:
@@ -461,9 +530,9 @@ model-index:
       revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
     metrics:
     - type: accuracy
-      value: 70.12012987012987
+      value: 73.49675324675324
     - type: f1
-      value: 69.2899512261214
+      value: 72.88538992490979
   - task:
       type: Clustering
     dataset:
@@ -474,7 +543,7 @@ model-index:
       revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
     metrics:
     - type: v_measure
-      value: 7.691890146277049
+      value: 6.801245618724224
   - task:
       type: Clustering
     dataset:
@@ -485,7 +554,7 @@ model-index:
       revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
     metrics:
     - type: v_measure
-      value: 18.50684170881271
+      value: 20.6156033971932
   - task:
       type: Clustering
     dataset:
@@ -496,7 +565,7 @@ model-index:
       revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
     metrics:
     - type: v_measure
-      value: 16.69474554114157
+      value: 19.077587707743156
   - task:
       type: Clustering
     dataset:
@@ -507,7 +576,7 @@ model-index:
       revision: a2dd5b02a77de3466a3eaa98ae586b5610314496
     metrics:
     - type: v_measure
-      value: 25.00467105836009
+      value: 27.00349462858046
   - task:
       type: Clustering
     dataset:
@@ -518,7 +587,7 @@ model-index:
       revision: 9bfff9a7f8f6dc6ffc9da71c48dd48b68696471d
     metrics:
     - type: v_measure
-      value: 13.043482009500194
+      value: 14.845348131791589
   - task:
       type: BitextMining
     dataset:
@@ -531,9 +600,9 @@ model-index:
     - type: accuracy
       value: 54.0
     - type: f1
-      value: 47.33693528693529
+      value: 47.37026862026861
     - type: precision
-      value: 45.04007936507936
+      value: 45.0734126984127
     - type: recall
       value: 54.0
   - task:
@@ -546,11 +615,11 @@ model-index:
       revision: None
     metrics:
     - type: accuracy
-      value: 66.62
+      value: 63.83000000000001
     - type: ap
-      value: 18.77536577595191
+      value: 18.511972946438764
     - type: f1
-      value: 54.33122331135114
+      value: 53.16787370496645
   - task:
       type: PairClassification
     dataset:
@@ -571,41 +640,41 @@ model-index:
     - type: cos_sim_recall
       value: 79.47368421052632
     - type: dot_accuracy
-      value: 83.7
+      value: 84.39999999999999
     - type: dot_ap
-      value: 51.707245136367455
+      value: 59.968589741258036
     - type: dot_f1
-      value: 52.03619909502262
+      value: 54.90909090909091
     - type: dot_precision
-      value: 45.63492063492063
+      value: 41.94444444444444
     - type: dot_recall
-      value: 60.526315789473685
+      value: 79.47368421052632
     - type: euclidean_accuracy
-      value: 84.3
+      value: 84.39999999999999
     - type: euclidean_ap
-      value: 60.640177471697974
+      value: 59.968589741258036
     - type: euclidean_f1
-      value: 56.55737704918033
+      value: 54.90909090909091
     - type: euclidean_precision
-      value: 46.308724832214764
+      value: 41.94444444444444
     - type: euclidean_recall
-      value: 72.63157894736842
+      value: 79.47368421052632
     - type: manhattan_accuracy
-      value: 84.3
+      value: 84.39999999999999
     - type: manhattan_ap
-      value: 60.642449283992626
+      value: 60.094893481041154
     - type: manhattan_f1
-      value: 56.82242990654205
+      value: 55.452865064695004
     - type: manhattan_precision
-      value: 44.05797101449275
+      value: 42.73504273504273
     - type: manhattan_recall
-      value: 80.0
+      value: 78.94736842105263
     - type: max_accuracy
       value: 84.39999999999999
     - type: max_ap
-      value: 60.642449283992626
+      value: 60.094893481041154
     - type: max_f1
-      value: 56.82242990654205
+      value: 55.452865064695004
   - task:
       type: STS
     dataset:
@@ -616,17 +685,17 @@ model-index:
       revision: None
     metrics:
     - type: cos_sim_pearson
-      value: 83.84274209712814
+      value: 83.8427417206754
     - type: cos_sim_spearman
-      value: 85.76929022706523
+      value: 85.76946319798301
     - type: euclidean_pearson
-      value: 79.29678840568863
+      value: 79.43901249477852
     - type: euclidean_spearman
-      value: 83.83915785622271
+      value: 85.76946319798301
     - type: manhattan_pearson
-      value: 79.51377951133192
+      value: 79.81046681362531
     - type: manhattan_spearman
-      value: 84.01330353535174
+      value: 86.24115514951988
   - task:
       type: Clustering
     dataset:
@@ -637,7 +706,7 @@ model-index:
       revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
     metrics:
     - type: v_measure
-      value: 26.145917838254785
+      value: 27.432031859995952
   - task:
       type: Clustering
     dataset:
@@ -648,7 +717,7 @@ model-index:
       revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
     metrics:
     - type: v_measure
-      value: 28.0310744137802
+      value: 28.32367305628197
   - task:
       type: Reranking
     dataset:
@@ -659,9 +728,9 @@ model-index:
       revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
     metrics:
     - type: map
-      value: 34.30811576227924
+      value: 34.30720667137015
     - type: mrr
-      value: 40.25416666666666
+      value: 40.24416666666666
   - task:
       type: Reranking
     dataset:
@@ -1722,7 +1791,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 58.123872519543
     - type: cos_sim_ap
-      value: 61.860457891021845
+      value: 61.86046509726734
     - type: cos_sim_f1
       value: 68.18181818181817
     - type: cos_sim_precision
@@ -1730,41 +1799,41 @@ model-index:
     - type: cos_sim_recall
       value: 97.49824643441664
     - type: dot_accuracy
-      value: 59.02585688514732
+      value: 58.123872519543
     - type: dot_ap
-      value: 62.10634470973564
+      value: 61.860555259802986
     - type: dot_f1
-      value: 68.3513630463003
+      value: 68.18181818181817
     - type: dot_precision
-      value: 54.259411926353394
+      value: 52.4198617221873
     - type: dot_recall
-      value: 92.33107318213702
+      value: 97.49824643441664
     - type: euclidean_accuracy
-      value: 54.696331930246544
+      value: 58.123872519543
     - type: euclidean_ap
-      value: 59.58239795823632
+      value: 61.87698627731538
     - type: euclidean_f1
-      value: 67.95360660946935
+      value: 68.18181818181817
     - type: euclidean_precision
-      value: 51.46191794007942
+      value: 52.4198617221873
     - type: euclidean_recall
-      value: 100.0
+      value: 97.49824643441664
     - type: manhattan_accuracy
-      value: 54.696331930246544
+      value: 58.123872519543
     - type: manhattan_ap
-      value: 59.593398063507394
+      value: 61.99468883207791
     - type: manhattan_f1
-      value: 67.94311591324383
+      value: 68.33675564681727
     - type: manhattan_precision
-      value: 51.4560770156438
+      value: 52.671562420866046
     - type: manhattan_recall
-      value: 99.9766191255553
+      value: 97.26443768996961
     - type: max_accuracy
-      value: 59.02585688514732
+      value: 58.123872519543
     - type: max_ap
-      value: 62.10634470973564
+      value: 61.99468883207791
     - type: max_f1
-      value: 68.3513630463003
+      value: 68.33675564681727
   - task:
       type: Retrieval
     dataset:
@@ -1781,7 +1850,7 @@ model-index:
     - type: map_at_100
       value: 9.549000000000001
     - type: map_at_1000
-      value: 9.666
+      value: 9.665
     - type: map_at_3
       value: 8.061
     - type: map_at_5
@@ -1803,9 +1872,9 @@ model-index:
     - type: ndcg_at_10
       value: 10.382
     - type: ndcg_at_100
-      value: 14.237
+      value: 14.235999999999999
     - type: ndcg_at_1000
-      value: 18.041
+      value: 18.04
     - type: ndcg_at_3
       value: 8.613999999999999
     - type: ndcg_at_5
@@ -1913,11 +1982,11 @@ model-index:
       revision: 59d12749a3c91a186063c7d729ec392fda94681c
     metrics:
     - type: accuracy
-      value: 70.42553191489363
+      value: 69.96960486322187
     - type: ap
-      value: 90.43423476644443
+      value: 91.23131906690253
     - type: f1
-      value: 55.82951993211343
+      value: 57.11872970138122
   - task:
       type: Classification
     dataset:
@@ -1928,11 +1997,11 @@ model-index:
       revision: 7ebf0b4caa7b2ae39698a889de782c09e6f5ee56
     metrics:
     - type: accuracy
-      value: 50.04504504504504
+      value: 49.75225225225225
     - type: ap
-      value: 50.02574261238442
+      value: 49.88223192425368
     - type: f1
-      value: 49.48578760810561
+      value: 49.55059044107012
   - task:
       type: Classification
     dataset:
@@ -1943,9 +2012,9 @@ model-index:
       revision: edbb03726c04a0efab14fc8c3b8b79e4d420e5a1
     metrics:
     - type: accuracy
-      value: 34.26450180405217
+      value: 37.58534554537886
     - type: f1
-      value: 30.14302584747605
+      value: 33.99440115952713
   - task:
       type: Retrieval
     dataset:
@@ -2094,9 +2163,9 @@ model-index:
       revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
     metrics:
     - type: accuracy
-      value: 36.52
+      value: 38.285000000000004
     - type: f1
-      value: 33.66164203159101
+      value: 35.35979931355028
   - task:
       type: Retrieval
     dataset:
@@ -2166,6 +2235,75 @@ model-index:
       value: 1.4200000000000002
     - type: recall_at_5
       value: 1.81
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa-pl
+      name: MTEB FiQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.959
+    - type: map_at_10
+      value: 1.952
+    - type: map_at_100
+      value: 2.281
+    - type: map_at_1000
+      value: 2.393
+    - type: map_at_3
+      value: 1.703
+    - type: map_at_5
+      value: 1.8319999999999999
+    - type: mrr_at_1
+      value: 2.469
+    - type: mrr_at_10
+      value: 4.547
+    - type: mrr_at_100
+      value: 5.021
+    - type: mrr_at_1000
+      value: 5.1339999999999995
+    - type: mrr_at_3
+      value: 3.884
+    - type: mrr_at_5
+      value: 4.223
+    - type: ndcg_at_1
+      value: 2.469
+    - type: ndcg_at_10
+      value: 3.098
+    - type: ndcg_at_100
+      value: 5.177
+    - type: ndcg_at_1000
+      value: 8.889
+    - type: ndcg_at_3
+      value: 2.7119999999999997
+    - type: ndcg_at_5
+      value: 2.8000000000000003
+    - type: precision_at_1
+      value: 2.469
+    - type: precision_at_10
+      value: 1.065
+    - type: precision_at_100
+      value: 0.321
+    - type: precision_at_1000
+      value: 0.095
+    - type: precision_at_3
+      value: 2.109
+    - type: precision_at_5
+      value: 1.574
+    - type: recall_at_1
+      value: 0.959
+    - type: recall_at_10
+      value: 4.075
+    - type: recall_at_100
+      value: 12.487
+    - type: recall_at_1000
+      value: 36.854
+    - type: recall_at_3
+      value: 2.632
+    - type: recall_at_5
+      value: 3.231
   - task:
       type: Retrieval
     dataset:
@@ -2235,6 +2373,144 @@ model-index:
       value: 2.37
     - type: recall_at_5
       value: 3.077
+  - task:
+      type: Retrieval
+    dataset:
+      type: jinaai/ger_da_lir
+      name: MTEB GerDaLIR
+      config: default
+      split: test
+      revision: 0bb47f1d73827e96964edb84dfe552f62f4fd5eb
+    metrics:
+    - type: map_at_1
+      value: 0.542
+    - type: map_at_10
+      value: 0.8130000000000001
+    - type: map_at_100
+      value: 0.898
+    - type: map_at_1000
+      value: 0.9209999999999999
+    - type: map_at_3
+      value: 0.709
+    - type: map_at_5
+      value: 0.764
+    - type: mrr_at_1
+      value: 0.594
+    - type: mrr_at_10
+      value: 0.8880000000000001
+    - type: mrr_at_100
+      value: 0.9820000000000001
+    - type: mrr_at_1000
+      value: 1.008
+    - type: mrr_at_3
+      value: 0.774
+    - type: mrr_at_5
+      value: 0.832
+    - type: ndcg_at_1
+      value: 0.594
+    - type: ndcg_at_10
+      value: 1.0030000000000001
+    - type: ndcg_at_100
+      value: 1.537
+    - type: ndcg_at_1000
+      value: 2.4330000000000003
+    - type: ndcg_at_3
+      value: 0.782
+    - type: ndcg_at_5
+      value: 0.882
+    - type: precision_at_1
+      value: 0.594
+    - type: precision_at_10
+      value: 0.16999999999999998
+    - type: precision_at_100
+      value: 0.048
+    - type: precision_at_1000
+      value: 0.013
+    - type: precision_at_3
+      value: 0.33899999999999997
+    - type: precision_at_5
+      value: 0.255
+    - type: recall_at_1
+      value: 0.542
+    - type: recall_at_10
+      value: 1.533
+    - type: recall_at_100
+      value: 4.204
+    - type: recall_at_1000
+      value: 11.574
+    - type: recall_at_3
+      value: 0.932
+    - type: recall_at_5
+      value: 1.172
+  - task:
+      type: Retrieval
+    dataset:
+      type: deepset/germandpr
+      name: MTEB GermanDPR
+      config: default
+      split: test
+      revision: 5129d02422a66be600ac89cd3e8531b4f97d347d
+    metrics:
+    - type: map_at_1
+      value: 25.561
+    - type: map_at_10
+      value: 38.873000000000005
+    - type: map_at_100
+      value: 40.004
+    - type: map_at_1000
+      value: 40.03
+    - type: map_at_3
+      value: 34.585
+    - type: map_at_5
+      value: 36.980000000000004
+    - type: mrr_at_1
+      value: 25.463
+    - type: mrr_at_10
+      value: 38.792
+    - type: mrr_at_100
+      value: 39.922000000000004
+    - type: mrr_at_1000
+      value: 39.949
+    - type: mrr_at_3
+      value: 34.504000000000005
+    - type: mrr_at_5
+      value: 36.899
+    - type: ndcg_at_1
+      value: 25.561
+    - type: ndcg_at_10
+      value: 46.477000000000004
+    - type: ndcg_at_100
+      value: 51.751999999999995
+    - type: ndcg_at_1000
+      value: 52.366
+    - type: ndcg_at_3
+      value: 37.645
+    - type: ndcg_at_5
+      value: 41.953
+    - type: precision_at_1
+      value: 25.561
+    - type: precision_at_10
+      value: 7.083
+    - type: precision_at_100
+      value: 0.9490000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 15.512
+    - type: precision_at_5
+      value: 11.395
+    - type: recall_at_1
+      value: 25.561
+    - type: recall_at_10
+      value: 70.829
+    - type: recall_at_100
+      value: 94.92699999999999
+    - type: recall_at_1000
+      value: 99.61
+    - type: recall_at_3
+      value: 46.537
+    - type: recall_at_5
+      value: 56.976000000000006
   - task:
       type: Retrieval
     dataset:
@@ -2304,6 +2580,27 @@ model-index:
       value: 74.002
     - type: recall_at_5
       value: 81.443
+  - task:
+      type: STS
+    dataset:
+      type: jinaai/german-STSbenchmark
+      name: MTEB GermanSTSBenchmark
+      config: default
+      split: test
+      revision: e36907544d44c3a247898ed81540310442329e20
+    metrics:
+    - type: cos_sim_pearson
+      value: 68.82052535790737
+    - type: cos_sim_spearman
+      value: 67.9356892072251
+    - type: euclidean_pearson
+      value: 67.2308663006278
+    - type: euclidean_spearman
+      value: 67.93572522920142
+    - type: manhattan_pearson
+      value: 67.23568952733595
+    - type: manhattan_spearman
+      value: 67.91660489262797
   - task:
       type: Retrieval
     dataset:
@@ -2383,9 +2680,9 @@ model-index:
       revision: 421605374b29664c5fc098418fe20ada9bd55f8a
     metrics:
     - type: accuracy
-      value: 30.157752981916126
+      value: 38.01462100808003
     - type: f1
-      value: 18.801823560719093
+      value: 26.680357453754215
   - task:
       type: Classification
     dataset:
@@ -2396,11 +2693,11 @@ model-index:
       revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
     metrics:
     - type: accuracy
-      value: 55.2292
+      value: 55.7508
     - type: ap
-      value: 53.00916532305935
+      value: 53.28158993124153
     - type: f1
-      value: 54.6906813069184
+      value: 55.34571379744637
   - task:
       type: Classification
     dataset:
@@ -2411,11 +2708,11 @@ model-index:
       revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
     metrics:
     - type: accuracy
-      value: 66.73545966228893
+      value: 69.58724202626641
     - type: ap
-      value: 26.119597600779542
+      value: 30.04577466931377
     - type: f1
-      value: 58.52011222432435
+      value: 62.46921898313143
   - task:
       type: STS
     dataset:
@@ -2426,17 +2723,17 @@ model-index:
       revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
     metrics:
     - type: cos_sim_pearson
-      value: 48.805858778250645
+      value: 48.80585861169271
     - type: cos_sim_spearman
-      value: 50.1102532604773
+      value: 50.11025991147549
     - type: euclidean_pearson
-      value: 48.94915568787808
+      value: 50.055425341198934
     - type: euclidean_spearman
-      value: 49.20965979933496
+      value: 50.11024862622995
     - type: manhattan_pearson
-      value: 48.913528193330855
+      value: 50.029980024931064
     - type: manhattan_spearman
-      value: 49.151438504736994
+      value: 50.074388245963384
   - task:
       type: Classification
     dataset:
@@ -2447,9 +2744,22 @@ model-index:
       revision: de7ba3406ee55ea2cc52a0a41408fa6aede6d3c6
     metrics:
     - type: accuracy
-      value: 53.13333333333333
+      value: 54.266666666666666
     - type: f1
-      value: 51.09906324617105
+      value: 52.181931818742875
+  - task:
+      type: Reranking
+    dataset:
+      type: jinaai/miracl
+      name: MTEB MIRACL
+      config: default
+      split: test
+      revision: d28a029f35c4ff7f616df47b0edf54e6882395e6
+    metrics:
+    - type: map
+      value: 51.40745004398599
+    - type: mrr
+      value: 56.71940267335004
   - task:
       type: Reranking
     dataset:
@@ -2611,9 +2921,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 88.25809393524851
+      value: 89.92476060191518
     - type: f1
-      value: 87.67467702138386
+      value: 89.30222882069823
   - task:
       type: Classification
     dataset:
@@ -2624,9 +2934,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 87.86136939983095
+      value: 89.54353338968724
     - type: f1
-      value: 86.46545913246018
+      value: 88.23043644828002
   - task:
       type: Classification
     dataset:
@@ -2637,9 +2947,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 88.66911274182789
+      value: 90.62374916611076
     - type: f1
-      value: 87.56818480133035
+      value: 89.68544977510335
   - task:
       type: Classification
     dataset:
@@ -2650,9 +2960,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 82.32070153460695
+      value: 86.18540557469466
     - type: f1
-      value: 81.8684135195111
+      value: 85.7362674669331
   - task:
       type: Classification
     dataset:
@@ -2663,9 +2973,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 88.17497310864108
+      value: 89.41556113302258
     - type: f1
-      value: 87.77127061255791
+      value: 89.04934651990581
   - task:
       type: Classification
     dataset:
@@ -2676,9 +2986,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 83.61301989150091
+      value: 85.89511754068715
     - type: f1
-      value: 83.32707952781637
+      value: 85.57630467968119
   - task:
       type: Classification
     dataset:
@@ -2689,9 +2999,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 63.28545371637026
+      value: 70.85043319653442
     - type: f1
-      value: 39.28010634448113
+      value: 46.0794069318026
   - task:
       type: Classification
     dataset:
@@ -2702,9 +3012,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 67.51197520428289
+      value: 73.43195266272188
     - type: f1
-      value: 42.75299728819045
+      value: 48.08015719781981
   - task:
       type: Classification
     dataset:
@@ -2715,9 +3025,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 66.75783855903936
+      value: 73.8425617078052
     - type: f1
-      value: 41.9243384646481
+      value: 49.37915156189611
   - task:
       type: Classification
     dataset:
@@ -2728,9 +3038,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 57.61352959599124
+      value: 66.75227059191982
     - type: f1
-      value: 36.60494253557738
+      value: 43.4642946741452
   - task:
       type: Classification
     dataset:
@@ -2741,9 +3051,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 63.209035496593756
+      value: 69.13589100035855
     - type: f1
-      value: 38.34334001455857
+      value: 46.25935961966482
   - task:
       type: Classification
     dataset:
@@ -2754,9 +3064,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 62.01084990958409
+      value: 68.47016274864377
     - type: f1
-      value: 38.90143964367107
+      value: 46.197113305277796
   - task:
       type: Classification
     dataset:
@@ -2767,9 +3077,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 53.48016139878952
+      value: 58.14727639542704
     - type: f1
-      value: 51.413731172932984
+      value: 55.58745169431752
   - task:
       type: Classification
     dataset:
@@ -2780,9 +3090,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 52.74041694687289
+      value: 57.91190316072628
     - type: f1
-      value: 50.85469558689613
+      value: 55.46589962622107
   - task:
       type: Classification
     dataset:
@@ -2793,9 +3103,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 52.42098184263618
+      value: 57.22932078009414
     - type: f1
-      value: 49.036138779692024
+      value: 53.661218041561334
   - task:
       type: Classification
     dataset:
@@ -2806,9 +3116,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 51.72158708809683
+      value: 57.16543375924681
     - type: f1
-      value: 50.92312837840828
+      value: 55.16504653263189
   - task:
       type: Classification
     dataset:
@@ -2819,9 +3129,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 57.71015467383995
+      value: 62.239408204438476
     - type: f1
-      value: 54.43623536118849
+      value: 58.941991707183874
   - task:
       type: Classification
     dataset:
@@ -2832,9 +3142,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 44.86886348352387
+      value: 51.186953597848
     - type: f1
-      value: 45.25621242204162
+      value: 49.59432722397084
   - task:
       type: Classification
     dataset:
@@ -2845,9 +3155,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 55.554808338937455
+      value: 62.030934767989244
     - type: f1
-      value: 52.841205727784924
+      value: 58.836302050830966
   - task:
       type: Classification
     dataset:
@@ -2858,9 +3168,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 55.94149293880296
+      value: 61.314727639542696
     - type: f1
-      value: 52.93531236014481
+      value: 57.80700293522655
   - task:
       type: Classification
     dataset:
@@ -2871,9 +3181,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 58.95090786819098
+      value: 64.20645595158037
     - type: f1
-      value: 55.8924018128682
+      value: 61.36755812840151
   - task:
       type: Classification
     dataset:
@@ -2884,9 +3194,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 57.871553463349024
+      value: 64.36785474108943
     - type: f1
-      value: 55.48077228016125
+      value: 61.15645935863754
   - task:
       type: Classification
     dataset:
@@ -2897,9 +3207,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 59.05514458641561
+      value: 63.97108271687962
     - type: f1
-      value: 56.85428621465761
+      value: 62.07352472659557
   - task:
       type: Classification
     dataset:
@@ -2910,9 +3220,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 62.51849361129792
+      value: 66.67114996637525
     - type: f1
-      value: 59.20555321128111
+      value: 63.420170447126324
   - task:
       type: Classification
     dataset:
@@ -2923,9 +3233,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 58.13718897108272
+      value: 62.864828513786144
     - type: f1
-      value: 55.11327164614034
+      value: 59.655860488861926
   - task:
       type: Classification
     dataset:
@@ -2936,9 +3246,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 51.3046402151984
+      value: 58.55077336919974
     - type: f1
-      value: 49.54359751420772
+      value: 55.28215385204243
   - task:
       type: Classification
     dataset:
@@ -2949,9 +3259,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 59.512441156691324
+      value: 63.453261600538
     - type: f1
-      value: 55.70948727453885
+      value: 59.991998820039186
   - task:
       type: Classification
     dataset:
@@ -2962,9 +3272,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 55.69266980497647
+      value: 61.32145258910558
     - type: f1
-      value: 53.84873884279824
+      value: 58.9676667104426
   - task:
       type: Classification
     dataset:
@@ -2975,9 +3285,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 57.821116341627445
+      value: 62.905178211163424
     - type: f1
-      value: 54.58226169327551
+      value: 59.645126480791674
   - task:
       type: Classification
     dataset:
@@ -2988,9 +3298,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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     metrics:
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@@ -3430,9 +3740,9 @@ model-index:
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     metrics:
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@@ -3443,9 +3753,9 @@ model-index:
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     - type: accuracy
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     metrics:
     - type: accuracy
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@@ -3469,9 +3779,9 @@ model-index:
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     - type: accuracy
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@@ -3482,9 +3792,9 @@ model-index:
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     metrics:
     - type: accuracy
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@@ -3495,9 +3805,9 @@ model-index:
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     metrics:
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@@ -3508,9 +3818,9 @@ model-index:
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@@ -3521,9 +3831,9 @@ model-index:
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     metrics:
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@@ -3534,9 +3844,9 @@ model-index:
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     metrics:
     - type: accuracy
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@@ -3547,9 +3857,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
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@@ -3560,9 +3870,9 @@ model-index:
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     metrics:
     - type: accuracy
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@@ -3573,9 +3883,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
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@@ -3586,9 +3896,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
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@@ -3599,9 +3909,9 @@ model-index:
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     metrics:
     - type: accuracy
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@@ -3612,9 +3922,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
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     dataset:
@@ -3625,9 +3935,9 @@ model-index:
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     metrics:
     - type: accuracy
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   - task:
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@@ -3638,9 +3948,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
     dataset:
@@ -3651,9 +3961,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
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   - task:
       type: Classification
     dataset:
@@ -3664,9 +3974,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
     dataset:
@@ -3677,9 +3987,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
     dataset:
@@ -3690,9 +4000,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
     dataset:
@@ -3703,9 +4013,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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     - type: f1
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   - task:
       type: Classification
     dataset:
@@ -3716,9 +4026,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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   - task:
       type: Classification
     dataset:
@@ -3729,9 +4039,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
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     - type: f1
-      value: 56.12621536279501
+      value: 60.044432258486715
   - task:
       type: Classification
     dataset:
@@ -3742,9 +4052,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 42.66308002689979
+      value: 49.051782111634154
     - type: f1
-      value: 38.86253489600552
+      value: 45.434581931581555
   - task:
       type: Classification
     dataset:
@@ -3755,9 +4065,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 61.20712844653665
+      value: 63.78278412911902
     - type: f1
-      value: 59.38664125148938
+      value: 62.106197625881535
   - task:
       type: Classification
     dataset:
@@ -3768,9 +4078,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 66.16005379959651
+      value: 69.59986550100874
     - type: f1
-      value: 65.37496105527057
+      value: 68.94355682848476
   - task:
       type: Classification
     dataset:
@@ -3781,9 +4091,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 55.46738399462004
+      value: 59.97310020174847
     - type: f1
-      value: 54.74655536412335
+      value: 59.09912773329623
   - task:
       type: Classification
     dataset:
@@ -3794,9 +4104,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 65.8675184936113
+      value: 69.20309347679893
     - type: f1
-      value: 64.4167690022513
+      value: 67.90665916607239
   - task:
       type: Classification
     dataset:
@@ -3807,9 +4117,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 59.34767989240082
+      value: 62.72024209818427
     - type: f1
-      value: 57.584089752919766
+      value: 60.77165334831407
   - task:
       type: Classification
     dataset:
@@ -3820,9 +4130,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 64.92938802958977
+      value: 67.87155346334902
     - type: f1
-      value: 62.689467476962534
+      value: 65.7906032446679
   - task:
       type: Classification
     dataset:
@@ -3833,9 +4143,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 60.860793544048406
+      value: 64.97646267652992
     - type: f1
-      value: 59.642494854830964
+      value: 63.89390215791396
   - task:
       type: Classification
     dataset:
@@ -3846,9 +4156,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 61.99058507061197
+      value: 65.81371889710827
     - type: f1
-      value: 60.80631394200557
+      value: 64.39323436519936
   - task:
       type: Classification
     dataset:
@@ -3859,9 +4169,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 65.773369199731
+      value: 69.79825151311366
     - type: f1
-      value: 64.59673968371376
+      value: 68.53789900442244
   - task:
       type: Classification
     dataset:
@@ -3872,9 +4182,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 66.54673839946201
+      value: 69.98991257565568
     - type: f1
-      value: 65.39512803006458
+      value: 68.93867074879778
   - task:
       type: Classification
     dataset:
@@ -3885,9 +4195,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 63.64492266308002
+      value: 67.50168123739071
     - type: f1
-      value: 62.96480563325382
+      value: 66.7457644903972
   - task:
       type: Classification
     dataset:
@@ -3898,9 +4208,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 64.03833221250841
+      value: 67.52521856086078
     - type: f1
-      value: 63.277354377232754
+      value: 66.83370797374445
   - task:
       type: Classification
     dataset:
@@ -3911,9 +4221,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 63.09683927370544
+      value: 67.96234028244787
     - type: f1
-      value: 63.105668759138
+      value: 67.58983110064196
   - task:
       type: Classification
     dataset:
@@ -3924,9 +4234,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 65.635507733692
+      value: 69.56624075319435
     - type: f1
-      value: 64.1835797433392
+      value: 68.35270162147211
   - task:
       type: Classification
     dataset:
@@ -3937,9 +4247,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 64.96973772696705
+      value: 68.48352387357095
     - type: f1
-      value: 63.000024177311595
+      value: 66.66973143886908
   - task:
       type: Classification
     dataset:
@@ -3950,9 +4260,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 64.7848016139879
+      value: 67.92535305985206
     - type: f1
-      value: 63.36081856889688
+      value: 66.52058462942483
   - task:
       type: Classification
     dataset:
@@ -3963,9 +4273,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 59.97982515131136
+      value: 63.184263618022875
     - type: f1
-      value: 58.457979351949675
+      value: 61.71153164960602
   - task:
       type: Classification
     dataset:
@@ -3976,9 +4286,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 61.19367854741089
+      value: 64.8453261600538
     - type: f1
-      value: 60.244347062989064
+      value: 63.863209439112346
   - task:
       type: Classification
     dataset:
@@ -3989,9 +4299,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 62.67989240080699
+      value: 65.39340954942838
     - type: f1
-      value: 61.03003364010584
+      value: 63.85484524633183
   - task:
       type: Classification
     dataset:
@@ -4002,9 +4312,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 64.70410221923335
+      value: 67.9892400806994
     - type: f1
-      value: 63.194634988237894
+      value: 66.57022479007357
   - task:
       type: Classification
     dataset:
@@ -4015,9 +4325,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 60.45057162071284
+      value: 63.399462004034966
     - type: f1
-      value: 58.75729037108071
+      value: 61.62381473991175
   - task:
       type: Classification
     dataset:
@@ -4028,9 +4338,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 58.315400134498994
+      value: 65.773369199731
     - type: f1
-      value: 59.46974195941193
+      value: 65.58317907780943
   - task:
       type: Classification
     dataset:
@@ -4041,9 +4351,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 62.562205783456626
+      value: 65.8069939475454
     - type: f1
-      value: 61.18682850669083
+      value: 64.47027323557235
   - task:
       type: Classification
     dataset:
@@ -4054,9 +4364,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 62.868190988567584
+      value: 66.51647612642904
     - type: f1
-      value: 62.04867947782604
+      value: 65.66061210324213
   - task:
       type: Classification
     dataset:
@@ -4067,9 +4377,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 65.35642232683256
+      value: 68.88365837256221
     - type: f1
-      value: 63.940631681609915
+      value: 67.56956454874091
   - task:
       type: Classification
     dataset:
@@ -4080,9 +4390,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 58.81640887693342
+      value: 63.29858776059179
     - type: f1
-      value: 58.4125957354379
+      value: 62.76318771484755
   - task:
       type: Retrieval
     dataset:
@@ -4162,7 +4472,7 @@ model-index:
       revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
     metrics:
     - type: v_measure
-      value: 19.340284691485483
+      value: 19.061819627060558
   - task:
       type: Clustering
     dataset:
@@ -4173,7 +4483,7 @@ model-index:
       revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
     metrics:
     - type: v_measure
-      value: 17.003121027783283
+      value: 19.79520446745267
   - task:
       type: Reranking
     dataset:
@@ -4184,9 +4494,9 @@ model-index:
       revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
     metrics:
     - type: map
-      value: 26.881341526634174
+      value: 26.881162218991285
     - type: mrr
-      value: 27.23083862187728
+      value: 27.23201335662217
   - task:
       type: Classification
     dataset:
@@ -4197,9 +4507,9 @@ model-index:
       revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
     metrics:
     - type: accuracy
-      value: 54.08666666666667
+      value: 57.69
     - type: f1
-      value: 53.05912174796259
+      value: 57.370451927892695
   - task:
       type: Retrieval
     dataset:
@@ -4269,6 +4579,75 @@ model-index:
       value: 0.931
     - type: recall_at_5
       value: 1.698
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus-pl
+      name: MTEB NFCorpus-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.307
+    - type: map_at_10
+      value: 0.835
+    - type: map_at_100
+      value: 1.503
+    - type: map_at_1000
+      value: 2.263
+    - type: map_at_3
+      value: 0.503
+    - type: map_at_5
+      value: 0.567
+    - type: mrr_at_1
+      value: 4.025
+    - type: mrr_at_10
+      value: 9.731
+    - type: mrr_at_100
+      value: 11.229
+    - type: mrr_at_1000
+      value: 11.34
+    - type: mrr_at_3
+      value: 6.811
+    - type: mrr_at_5
+      value: 8.126999999999999
+    - type: ndcg_at_1
+      value: 3.56
+    - type: ndcg_at_10
+      value: 4.596
+    - type: ndcg_at_100
+      value: 7.567
+    - type: ndcg_at_1000
+      value: 17.76
+    - type: ndcg_at_3
+      value: 3.52
+    - type: ndcg_at_5
+      value: 3.823
+    - type: precision_at_1
+      value: 4.025
+    - type: precision_at_10
+      value: 4.334
+    - type: precision_at_100
+      value: 2.842
+    - type: precision_at_1000
+      value: 1.506
+    - type: precision_at_3
+      value: 3.818
+    - type: precision_at_5
+      value: 4.149
+    - type: recall_at_1
+      value: 0.307
+    - type: recall_at_10
+      value: 2.543
+    - type: recall_at_100
+      value: 12.152000000000001
+    - type: recall_at_1000
+      value: 46.878
+    - type: recall_at_3
+      value: 0.755
+    - type: recall_at_5
+      value: 0.975
   - task:
       type: Retrieval
     dataset:
@@ -4417,9 +4796,9 @@ model-index:
       revision: 07b99ab3363c2e7f8f87015b01c21f4d9b917ce3
     metrics:
     - type: accuracy
-      value: 48.720703125
+      value: 48.251953125
     - type: f1
-      value: 44.40194414610097
+      value: 45.42526611578402
   - task:
       type: Classification
     dataset:
@@ -4430,9 +4809,9 @@ model-index:
       revision: e254179d18ab0165fdb6dbef91178266222bee2a
     metrics:
     - type: accuracy
-      value: 46.626666666666665
+      value: 48.403333333333336
     - type: f1
-      value: 44.771861545457476
+      value: 47.9287124185198
   - task:
       type: BitextMining
     dataset:
@@ -4443,13 +4822,13 @@ model-index:
       revision: None
     metrics:
     - type: accuracy
-      value: 94.73684210526315
-    - type: f1
       value: 93.85964912280701
+    - type: f1
+      value: 92.98245614035088
     - type: precision
-      value: 93.42105263157895
+      value: 92.54385964912281
     - type: recall
-      value: 94.73684210526315
+      value: 93.85964912280701
   - task:
       type: Classification
     dataset:
@@ -4460,11 +4839,11 @@ model-index:
       revision: f7393532774c66312378d30b197610b43d751972
     metrics:
     - type: accuracy
-      value: 55.408333333333324
+      value: 55.991666666666674
     - type: ap
-      value: 53.03584049725229
+      value: 53.417849849746226
     - type: f1
-      value: 55.0030558323002
+      value: 55.757916182475384
   - task:
       type: PairClassification
     dataset:
@@ -4477,7 +4856,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 54.68327016783974
     - type: cos_sim_ap
-      value: 55.175113037501625
+      value: 55.175059616546406
     - type: cos_sim_f1
       value: 67.81733189500179
     - type: cos_sim_precision
@@ -4485,41 +4864,41 @@ model-index:
     - type: cos_sim_recall
       value: 99.57761351636748
     - type: dot_accuracy
-      value: 53.3838657282079
+      value: 54.68327016783974
     - type: dot_ap
-      value: 54.09970939118489
+      value: 55.175059616546406
     - type: dot_f1
-      value: 67.81485468245427
+      value: 67.81733189500179
     - type: dot_precision
-      value: 51.358695652173914
+      value: 51.41766630316249
     - type: dot_recall
-      value: 99.78880675818374
+      value: 99.57761351636748
     - type: euclidean_accuracy
-      value: 52.680021656740664
+      value: 54.68327016783974
     - type: euclidean_ap
-      value: 54.61964760120384
+      value: 55.17510180566365
     - type: euclidean_f1
-      value: 67.86743515850145
+      value: 67.81733189500179
     - type: euclidean_precision
-      value: 51.50355385456533
+      value: 51.41766630316249
     - type: euclidean_recall
-      value: 99.47201689545935
+      value: 99.57761351636748
     - type: manhattan_accuracy
-      value: 52.84244721169464
+      value: 55.44125609095831
     - type: manhattan_ap
-      value: 54.95963401318357
+      value: 55.76283671826867
     - type: manhattan_f1
-      value: 67.96818510484454
+      value: 68.05905653583004
     - type: manhattan_precision
-      value: 51.67674546454095
+      value: 51.63934426229508
     - type: manhattan_recall
-      value: 99.26082365364309
+      value: 99.78880675818374
     - type: max_accuracy
-      value: 54.68327016783974
+      value: 55.44125609095831
     - type: max_ap
-      value: 55.175113037501625
+      value: 55.76283671826867
     - type: max_f1
-      value: 67.96818510484454
+      value: 68.05905653583004
   - task:
       type: Classification
     dataset:
@@ -4530,11 +4909,11 @@ model-index:
       revision: e610f2ebd179a8fda30ae534c3878750a96db120
     metrics:
     - type: accuracy
-      value: 71.38
+      value: 75.64
     - type: ap
-      value: 67.98361406325826
+      value: 71.45085103287833
     - type: f1
-      value: 71.32677133367216
+      value: 75.52254495697326
   - task:
       type: Classification
     dataset:
@@ -4545,11 +4924,11 @@ model-index:
       revision: None
     metrics:
     - type: accuracy
-      value: 73.79090645815232
+      value: 73.86620330147699
     - type: ap
-      value: 79.78709287447715
+      value: 80.58015815306322
     - type: f1
-      value: 71.11540289567428
+      value: 71.49082510883872
   - task:
       type: STS
     dataset:
@@ -4560,17 +4939,17 @@ model-index:
       revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
     metrics:
     - type: cos_sim_pearson
-      value: 29.52361484634536
+      value: 29.52361689421863
     - type: cos_sim_spearman
-      value: 32.749971481829185
+      value: 32.750058577257875
     - type: euclidean_pearson
-      value: 32.54178605588255
+      value: 34.583472972871796
     - type: euclidean_spearman
-      value: 31.470626091963805
+      value: 32.75328764421994
     - type: manhattan_pearson
-      value: 32.59570732501661
+      value: 34.727366510326995
     - type: manhattan_spearman
-      value: 31.45843300214921
+      value: 32.787167142114214
   - task:
       type: PairClassification
     dataset:
@@ -4591,19 +4970,19 @@ model-index:
     - type: cos_sim_recall
       value: 99.83443708609272
     - type: dot_accuracy
-      value: 64.1
+      value: 71.1
     - type: dot_ap
-      value: 68.24516982673607
+      value: 85.36544548691204
     - type: dot_f1
-      value: 75.9412890874282
+      value: 75.23393636930756
     - type: dot_precision
-      value: 61.78608515057113
+      value: 60.36036036036037
     - type: dot_recall
-      value: 98.50993377483444
+      value: 99.83443708609272
     - type: euclidean_accuracy
-      value: 73.0
+      value: 71.1
     - type: euclidean_ap
-      value: 85.77605840690839
+      value: 85.36544548691205
     - type: euclidean_f1
       value: 75.23393636930756
     - type: euclidean_precision
@@ -4611,9 +4990,9 @@ model-index:
     - type: euclidean_recall
       value: 99.83443708609272
     - type: manhattan_accuracy
-      value: 73.0
+      value: 71.1
     - type: manhattan_ap
-      value: 85.77723100027544
+      value: 85.33853868545614
     - type: manhattan_f1
       value: 75.23393636930756
     - type: manhattan_precision
@@ -4621,11 +5000,11 @@ model-index:
     - type: manhattan_recall
       value: 99.83443708609272
     - type: max_accuracy
-      value: 73.0
+      value: 71.1
     - type: max_ap
-      value: 85.77723100027544
+      value: 85.36544548691205
     - type: max_f1
-      value: 75.9412890874282
+      value: 75.23393636930756
   - task:
       type: PairClassification
     dataset:
@@ -4646,41 +5025,426 @@ model-index:
     - type: cos_sim_recall
       value: 91.15853658536585
     - type: dot_accuracy
-      value: 85.9925788497217
+      value: 90.81632653061224
     - type: dot_ap
-      value: 83.51557404204843
+      value: 91.97693749083473
     - type: dot_f1
-      value: 78.0141843971631
+      value: 85.55078683834049
     - type: dot_precision
-      value: 72.94429708222812
+      value: 80.59299191374663
     - type: dot_recall
-      value: 83.84146341463415
+      value: 91.15853658536585
     - type: euclidean_accuracy
-      value: 88.12615955473099
+      value: 90.81632653061224
     - type: euclidean_ap
-      value: 88.83596272873487
+      value: 91.97693749083473
     - type: euclidean_f1
-      value: 80.46647230320698
+      value: 85.55078683834049
     - type: euclidean_precision
-      value: 77.09497206703911
+      value: 80.59299191374663
     - type: euclidean_recall
-      value: 84.14634146341463
+      value: 91.15853658536585
     - type: manhattan_accuracy
-      value: 88.31168831168831
+      value: 90.9090909090909
     - type: manhattan_ap
-      value: 89.15769755969164
+      value: 92.043441286281
     - type: manhattan_f1
-      value: 80.62678062678062
+      value: 85.34482758620689
     - type: manhattan_precision
-      value: 75.66844919786097
+      value: 80.70652173913044
     - type: manhattan_recall
-      value: 86.28048780487805
+      value: 90.54878048780488
     - type: max_accuracy
-      value: 90.81632653061224
+      value: 90.9090909090909
     - type: max_ap
-      value: 91.97693749083473
+      value: 92.043441286281
     - type: max_f1
       value: 85.55078683834049
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (de)
+      config: de
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 70.35
+    - type: cos_sim_ap
+      value: 72.01641717127626
+    - type: cos_sim_f1
+      value: 64.49511400651467
+    - type: cos_sim_precision
+      value: 55.26315789473685
+    - type: cos_sim_recall
+      value: 77.43016759776536
+    - type: dot_accuracy
+      value: 70.35
+    - type: dot_ap
+      value: 72.06599137974572
+    - type: dot_f1
+      value: 64.49511400651467
+    - type: dot_precision
+      value: 55.26315789473685
+    - type: dot_recall
+      value: 77.43016759776536
+    - type: euclidean_accuracy
+      value: 70.35
+    - type: euclidean_ap
+      value: 71.92019289154159
+    - type: euclidean_f1
+      value: 64.49511400651467
+    - type: euclidean_precision
+      value: 55.26315789473685
+    - type: euclidean_recall
+      value: 77.43016759776536
+    - type: manhattan_accuracy
+      value: 70.35
+    - type: manhattan_ap
+      value: 71.92979188519502
+    - type: manhattan_f1
+      value: 64.60409019402202
+    - type: manhattan_precision
+      value: 60.86956521739131
+    - type: manhattan_recall
+      value: 68.8268156424581
+    - type: max_accuracy
+      value: 70.35
+    - type: max_ap
+      value: 72.06599137974572
+    - type: max_f1
+      value: 64.60409019402202
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (en)
+      config: en
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 71.0
+    - type: cos_sim_ap
+      value: 74.73017292645147
+    - type: cos_sim_f1
+      value: 66.73427991886409
+    - type: cos_sim_precision
+      value: 61.78403755868545
+    - type: cos_sim_recall
+      value: 72.54685777287762
+    - type: dot_accuracy
+      value: 71.0
+    - type: dot_ap
+      value: 74.73017292645147
+    - type: dot_f1
+      value: 66.73427991886409
+    - type: dot_precision
+      value: 61.78403755868545
+    - type: dot_recall
+      value: 72.54685777287762
+    - type: euclidean_accuracy
+      value: 71.0
+    - type: euclidean_ap
+      value: 74.73013082197343
+    - type: euclidean_f1
+      value: 66.73427991886409
+    - type: euclidean_precision
+      value: 61.78403755868545
+    - type: euclidean_recall
+      value: 72.54685777287762
+    - type: manhattan_accuracy
+      value: 70.95
+    - type: manhattan_ap
+      value: 74.71203917486744
+    - type: manhattan_f1
+      value: 66.86868686868686
+    - type: manhattan_precision
+      value: 61.696178937558244
+    - type: manhattan_recall
+      value: 72.98787210584344
+    - type: max_accuracy
+      value: 71.0
+    - type: max_ap
+      value: 74.73017292645147
+    - type: max_f1
+      value: 66.86868686868686
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (es)
+      config: es
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 67.7
+    - type: cos_sim_ap
+      value: 69.70320170421651
+    - type: cos_sim_f1
+      value: 62.55625562556255
+    - type: cos_sim_precision
+      value: 52.851711026615966
+    - type: cos_sim_recall
+      value: 76.62624035281146
+    - type: dot_accuracy
+      value: 67.7
+    - type: dot_ap
+      value: 69.70320170421651
+    - type: dot_f1
+      value: 62.55625562556255
+    - type: dot_precision
+      value: 52.851711026615966
+    - type: dot_recall
+      value: 76.62624035281146
+    - type: euclidean_accuracy
+      value: 67.7
+    - type: euclidean_ap
+      value: 69.70320170421651
+    - type: euclidean_f1
+      value: 62.55625562556255
+    - type: euclidean_precision
+      value: 52.851711026615966
+    - type: euclidean_recall
+      value: 76.62624035281146
+    - type: manhattan_accuracy
+      value: 67.75
+    - type: manhattan_ap
+      value: 69.67833816050764
+    - type: manhattan_f1
+      value: 62.734082397003746
+    - type: manhattan_precision
+      value: 54.515866558177386
+    - type: manhattan_recall
+      value: 73.8699007717751
+    - type: max_accuracy
+      value: 67.75
+    - type: max_ap
+      value: 69.70320170421651
+    - type: max_f1
+      value: 62.734082397003746
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (fr)
+      config: fr
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 69.0
+    - type: cos_sim_ap
+      value: 71.36406639969131
+    - type: cos_sim_f1
+      value: 64.45993031358886
+    - type: cos_sim_precision
+      value: 53.12275664034458
+    - type: cos_sim_recall
+      value: 81.94905869324474
+    - type: dot_accuracy
+      value: 69.0
+    - type: dot_ap
+      value: 71.2599779415656
+    - type: dot_f1
+      value: 64.45993031358886
+    - type: dot_precision
+      value: 53.12275664034458
+    - type: dot_recall
+      value: 81.94905869324474
+    - type: euclidean_accuracy
+      value: 69.0
+    - type: euclidean_ap
+      value: 71.3126257271965
+    - type: euclidean_f1
+      value: 64.45993031358886
+    - type: euclidean_precision
+      value: 53.12275664034458
+    - type: euclidean_recall
+      value: 81.94905869324474
+    - type: manhattan_accuracy
+      value: 69.0
+    - type: manhattan_ap
+      value: 71.29361764028188
+    - type: manhattan_f1
+      value: 64.54789615040288
+    - type: manhattan_precision
+      value: 54.16979714500376
+    - type: manhattan_recall
+      value: 79.84496124031007
+    - type: max_accuracy
+      value: 69.0
+    - type: max_ap
+      value: 71.36406639969131
+    - type: max_f1
+      value: 64.54789615040288
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (ja)
+      config: ja
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 63.849999999999994
+    - type: cos_sim_ap
+      value: 60.914955950361026
+    - type: cos_sim_f1
+      value: 62.4556422995032
+    - type: cos_sim_precision
+      value: 45.47803617571059
+    - type: cos_sim_recall
+      value: 99.66024915062289
+    - type: dot_accuracy
+      value: 63.849999999999994
+    - type: dot_ap
+      value: 60.808056565465506
+    - type: dot_f1
+      value: 62.4556422995032
+    - type: dot_precision
+      value: 45.47803617571059
+    - type: dot_recall
+      value: 99.66024915062289
+    - type: euclidean_accuracy
+      value: 63.849999999999994
+    - type: euclidean_ap
+      value: 60.8231492677072
+    - type: euclidean_f1
+      value: 62.4556422995032
+    - type: euclidean_precision
+      value: 45.47803617571059
+    - type: euclidean_recall
+      value: 99.66024915062289
+    - type: manhattan_accuracy
+      value: 63.800000000000004
+    - type: manhattan_ap
+      value: 60.86392751846975
+    - type: manhattan_f1
+      value: 62.43348705214614
+    - type: manhattan_precision
+      value: 45.45454545454545
+    - type: manhattan_recall
+      value: 99.66024915062289
+    - type: max_accuracy
+      value: 63.849999999999994
+    - type: max_ap
+      value: 60.914955950361026
+    - type: max_f1
+      value: 62.4556422995032
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (ko)
+      config: ko
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 61.1
+    - type: cos_sim_ap
+      value: 58.40339411735916
+    - type: cos_sim_f1
+      value: 62.7906976744186
+    - type: cos_sim_precision
+      value: 46.55172413793103
+    - type: cos_sim_recall
+      value: 96.42857142857143
+    - type: dot_accuracy
+      value: 61.1
+    - type: dot_ap
+      value: 58.439189685586456
+    - type: dot_f1
+      value: 62.7906976744186
+    - type: dot_precision
+      value: 46.55172413793103
+    - type: dot_recall
+      value: 96.42857142857143
+    - type: euclidean_accuracy
+      value: 61.1
+    - type: euclidean_ap
+      value: 58.34968788203145
+    - type: euclidean_f1
+      value: 62.7906976744186
+    - type: euclidean_precision
+      value: 46.55172413793103
+    - type: euclidean_recall
+      value: 96.42857142857143
+    - type: manhattan_accuracy
+      value: 61.1
+    - type: manhattan_ap
+      value: 58.31504446861402
+    - type: manhattan_f1
+      value: 62.636562272396226
+    - type: manhattan_precision
+      value: 46.48648648648649
+    - type: manhattan_recall
+      value: 95.98214285714286
+    - type: max_accuracy
+      value: 61.1
+    - type: max_ap
+      value: 58.439189685586456
+    - type: max_f1
+      value: 62.7906976744186
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (zh)
+      config: zh
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 64.2
+    - type: cos_sim_ap
+      value: 63.73722153283802
+    - type: cos_sim_f1
+      value: 62.52707581227437
+    - type: cos_sim_precision
+      value: 46.16204690831556
+    - type: cos_sim_recall
+      value: 96.86800894854586
+    - type: dot_accuracy
+      value: 64.2
+    - type: dot_ap
+      value: 63.67335241021108
+    - type: dot_f1
+      value: 62.52707581227437
+    - type: dot_precision
+      value: 46.16204690831556
+    - type: dot_recall
+      value: 96.86800894854586
+    - type: euclidean_accuracy
+      value: 64.2
+    - type: euclidean_ap
+      value: 63.77399571117368
+    - type: euclidean_f1
+      value: 62.52707581227437
+    - type: euclidean_precision
+      value: 46.16204690831556
+    - type: euclidean_recall
+      value: 96.86800894854586
+    - type: manhattan_accuracy
+      value: 64.5
+    - type: manhattan_ap
+      value: 63.747406783360816
+    - type: manhattan_f1
+      value: 62.58601955813112
+    - type: manhattan_precision
+      value: 46.27745045527584
+    - type: manhattan_recall
+      value: 96.64429530201343
+    - type: max_accuracy
+      value: 64.5
+    - type: max_ap
+      value: 63.77399571117368
+    - type: max_f1
+      value: 62.58601955813112
   - task:
       type: Classification
     dataset:
@@ -4691,9 +5455,9 @@ model-index:
       revision: None
     metrics:
     - type: accuracy
-      value: 50.72022160664821
+      value: 52.797783933518005
     - type: f1
-      value: 51.12376375708585
+      value: 53.84971294048786
   - task:
       type: Classification
     dataset:
@@ -4704,9 +5468,9 @@ model-index:
       revision: None
     metrics:
     - type: accuracy
-      value: 33.36032388663968
+      value: 38.40080971659919
     - type: f1
-      value: 27.16896572816315
+      value: 30.38990873840624
   - task:
       type: STS
     dataset:
@@ -4717,17 +5481,86 @@ model-index:
       revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
     metrics:
     - type: cos_sim_pearson
-      value: 23.34232603207876
+      value: 23.34232568997104
     - type: cos_sim_spearman
-      value: 24.4795842135422
+      value: 24.47961936211083
     - type: euclidean_pearson
-      value: 19.94484261154701
+      value: 22.03140944610336
     - type: euclidean_spearman
-      value: 20.678133816020438
+      value: 24.47949166265398
     - type: manhattan_pearson
-      value: 22.39245233528255
+      value: 25.542406448726908
     - type: manhattan_spearman
-      value: 22.93218231516663
+      value: 28.655724283839533
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora-pl
+      name: MTEB Quora-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 59.938
+    - type: map_at_10
+      value: 72.734
+    - type: map_at_100
+      value: 73.564
+    - type: map_at_1000
+      value: 73.602
+    - type: map_at_3
+      value: 69.707
+    - type: map_at_5
+      value: 71.515
+    - type: mrr_at_1
+      value: 69.28
+    - type: mrr_at_10
+      value: 76.97500000000001
+    - type: mrr_at_100
+      value: 77.27199999999999
+    - type: mrr_at_1000
+      value: 77.28
+    - type: mrr_at_3
+      value: 75.355
+    - type: mrr_at_5
+      value: 76.389
+    - type: ndcg_at_1
+      value: 69.33
+    - type: ndcg_at_10
+      value: 77.61099999999999
+    - type: ndcg_at_100
+      value: 80.02
+    - type: ndcg_at_1000
+      value: 80.487
+    - type: ndcg_at_3
+      value: 73.764
+    - type: ndcg_at_5
+      value: 75.723
+    - type: precision_at_1
+      value: 69.33
+    - type: precision_at_10
+      value: 11.917
+    - type: precision_at_100
+      value: 1.447
+    - type: precision_at_1000
+      value: 0.154
+    - type: precision_at_3
+      value: 32.29
+    - type: precision_at_5
+      value: 21.432000000000002
+    - type: recall_at_1
+      value: 59.938
+    - type: recall_at_10
+      value: 87.252
+    - type: recall_at_100
+      value: 96.612
+    - type: recall_at_1000
+      value: 99.388
+    - type: recall_at_3
+      value: 76.264
+    - type: recall_at_5
+      value: 81.71000000000001
   - task:
       type: Retrieval
     dataset:
@@ -4738,41 +5571,41 @@ model-index:
       revision: None
     metrics:
     - type: map_at_1
-      value: 61.451
+      value: 61.458999999999996
     - type: map_at_10
-      value: 73.898
+      value: 73.90299999999999
     - type: map_at_100
-      value: 74.72800000000001
+      value: 74.733
     - type: map_at_1000
-      value: 74.766
+      value: 74.771
     - type: map_at_3
-      value: 70.994
+      value: 70.999
     - type: map_at_5
-      value: 72.74000000000001
+      value: 72.745
     - type: mrr_at_1
-      value: 70.94
+      value: 70.93
     - type: mrr_at_10
-      value: 78.35600000000001
+      value: 78.353
     - type: mrr_at_100
-      value: 78.64
+      value: 78.636
     - type: mrr_at_1000
-      value: 78.647
+      value: 78.644
     - type: mrr_at_3
-      value: 76.912
+      value: 76.908
     - type: mrr_at_5
-      value: 77.81
+      value: 77.807
     - type: ndcg_at_1
       value: 70.93
     - type: ndcg_at_10
-      value: 78.622
+      value: 78.625
     - type: ndcg_at_100
-      value: 81.00699999999999
+      value: 81.01
     - type: ndcg_at_1000
-      value: 81.453
+      value: 81.45700000000001
     - type: ndcg_at_3
-      value: 75.03999999999999
+      value: 75.045
     - type: ndcg_at_5
-      value: 76.839
+      value: 76.84299999999999
     - type: precision_at_1
       value: 70.93
     - type: precision_at_10
@@ -4786,7 +5619,7 @@ model-index:
     - type: precision_at_5
       value: 21.598
     - type: recall_at_1
-      value: 61.451
+      value: 61.458999999999996
     - type: recall_at_10
       value: 87.608
     - type: recall_at_100
@@ -4794,7 +5627,7 @@ model-index:
     - type: recall_at_1000
       value: 99.445
     - type: recall_at_3
-      value: 77.348
+      value: 77.354
     - type: recall_at_5
       value: 82.334
   - task:
@@ -4807,7 +5640,7 @@ model-index:
       revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
     metrics:
     - type: v_measure
-      value: 18.928966218247353
+      value: 28.519889100999958
   - task:
       type: Clustering
     dataset:
@@ -4818,7 +5651,7 @@ model-index:
       revision: 282350215ef01743dc01b456c7f5241fa8937f16
     metrics:
     - type: v_measure
-      value: 35.948929675640414
+      value: 38.62765374782771
   - task:
       type: Retrieval
     dataset:
@@ -4888,6 +5721,75 @@ model-index:
       value: 1.0699999999999998
     - type: recall_at_5
       value: 1.27
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs-pl
+      name: MTEB SCIDOCS-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.32
+    - type: map_at_10
+      value: 0.676
+    - type: map_at_100
+      value: 0.847
+    - type: map_at_1000
+      value: 1.032
+    - type: map_at_3
+      value: 0.5369999999999999
+    - type: map_at_5
+      value: 0.592
+    - type: mrr_at_1
+      value: 1.6
+    - type: mrr_at_10
+      value: 2.863
+    - type: mrr_at_100
+      value: 3.334
+    - type: mrr_at_1000
+      value: 3.5479999999999996
+    - type: mrr_at_3
+      value: 2.317
+    - type: mrr_at_5
+      value: 2.587
+    - type: ndcg_at_1
+      value: 1.6
+    - type: ndcg_at_10
+      value: 1.397
+    - type: ndcg_at_100
+      value: 2.819
+    - type: ndcg_at_1000
+      value: 9.349
+    - type: ndcg_at_3
+      value: 1.3
+    - type: ndcg_at_5
+      value: 1.1079999999999999
+    - type: precision_at_1
+      value: 1.6
+    - type: precision_at_10
+      value: 0.74
+    - type: precision_at_100
+      value: 0.295
+    - type: precision_at_1000
+      value: 0.194
+    - type: precision_at_3
+      value: 1.2
+    - type: precision_at_5
+      value: 0.96
+    - type: recall_at_1
+      value: 0.32
+    - type: recall_at_10
+      value: 1.505
+    - type: recall_at_100
+      value: 5.988
+    - type: recall_at_1000
+      value: 39.308
+    - type: recall_at_3
+      value: 0.72
+    - type: recall_at_5
+      value: 0.9650000000000001
   - task:
       type: PairClassification
     dataset:
@@ -4900,7 +5802,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 73.84834896045659
     - type: cos_sim_ap
-      value: 55.48406649230719
+      value: 55.484124732566606
     - type: cos_sim_f1
       value: 57.34228187919464
     - type: cos_sim_precision
@@ -4908,41 +5810,41 @@ model-index:
     - type: cos_sim_recall
       value: 76.06837606837607
     - type: dot_accuracy
-      value: 72.6049735018345
+      value: 73.84834896045659
     - type: dot_ap
-      value: 47.4643427557602
+      value: 55.48400003295399
     - type: dot_f1
-      value: 55.22423104015027
+      value: 57.34228187919464
     - type: dot_precision
-      value: 41.190893169877405
+      value: 46.01464885825076
     - type: dot_recall
-      value: 83.76068376068376
+      value: 76.06837606837607
     - type: euclidean_accuracy
-      value: 74.01141459437423
+      value: 73.84834896045659
     - type: euclidean_ap
-      value: 55.32291633102242
+      value: 55.48407331902175
     - type: euclidean_f1
-      value: 56.970649895178184
+      value: 57.34228187919464
     - type: euclidean_precision
-      value: 45.066334991708125
+      value: 46.01464885825076
     - type: euclidean_recall
-      value: 77.42165242165242
+      value: 76.06837606837607
     - type: manhattan_accuracy
-      value: 73.99103139013454
+      value: 73.80758255197716
     - type: manhattan_ap
-      value: 55.25996778114356
+      value: 55.42477275597209
     - type: manhattan_f1
-      value: 57.0203644158628
+      value: 57.55860953920776
     - type: manhattan_precision
-      value: 45.70446735395189
+      value: 46.29388816644994
     - type: manhattan_recall
-      value: 75.78347578347578
+      value: 76.06837606837607
     - type: max_accuracy
-      value: 74.01141459437423
+      value: 73.84834896045659
     - type: max_ap
-      value: 55.48406649230719
+      value: 55.484124732566606
     - type: max_f1
-      value: 57.34228187919464
+      value: 57.55860953920776
   - task:
       type: STS
     dataset:
@@ -4953,17 +5855,17 @@ model-index:
       revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
     metrics:
     - type: cos_sim_pearson
-      value: 67.0394316443087
+      value: 67.03943120783973
     - type: cos_sim_spearman
-      value: 62.93973839554845
+      value: 62.93971145260584
     - type: euclidean_pearson
-      value: 57.60094512966203
+      value: 64.13947263916926
     - type: euclidean_spearman
-      value: 57.05926985559664
+      value: 62.93972324235839
     - type: manhattan_pearson
-      value: 57.53054316732484
+      value: 64.11295322654566
     - type: manhattan_spearman
-      value: 56.98810707222501
+      value: 62.92816122293202
   - task:
       type: STS
     dataset:
@@ -4974,17 +5876,17 @@ model-index:
       revision: None
     metrics:
     - type: cos_sim_pearson
-      value: 67.75034195626081
+      value: 67.75034167381077
     - type: cos_sim_spearman
-      value: 62.98156510096241
+      value: 62.98158872758643
     - type: euclidean_pearson
-      value: 60.102373885669
+      value: 64.25794794439082
     - type: euclidean_spearman
-      value: 58.78567620580185
+      value: 62.981566596223125
     - type: manhattan_pearson
-      value: 60.06786982256782
+      value: 64.25439446502435
     - type: manhattan_spearman
-      value: 58.782787914089305
+      value: 63.01301439900365
   - task:
       type: STS
     dataset:
@@ -4995,17 +5897,17 @@ model-index:
       revision: a0d554a64d88156834ff5ae9920b964011b16384
     metrics:
     - type: cos_sim_pearson
-      value: 61.62220407968201
+      value: 61.622204530882755
     - type: cos_sim_spearman
-      value: 65.46331444956428
+      value: 65.4632047656541
     - type: euclidean_pearson
-      value: 53.17721859223576
+      value: 59.21529585527598
     - type: euclidean_spearman
-      value: 62.26490113361859
+      value: 65.4638163967956
     - type: manhattan_pearson
-      value: 53.24730859766875
+      value: 59.39341472707122
     - type: manhattan_spearman
-      value: 62.27695125302589
+      value: 65.57635757250173
   - task:
       type: STS
     dataset:
@@ -5016,17 +5918,17 @@ model-index:
       revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
     metrics:
     - type: cos_sim_pearson
-      value: 60.32974355127381
+      value: 60.329743331971486
     - type: cos_sim_spearman
-      value: 62.786126823027246
+      value: 62.78607195958339
     - type: euclidean_pearson
-      value: 48.85507668127239
+      value: 62.07415212138581
     - type: euclidean_spearman
-      value: 50.87786603451179
+      value: 62.78618151904129
     - type: manhattan_pearson
-      value: 49.12859466063693
+      value: 62.41250554765521
     - type: manhattan_spearman
-      value: 50.84858327663952
+      value: 62.87580558029627
   - task:
       type: STS
     dataset:
@@ -5037,17 +5939,17 @@ model-index:
       revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
     metrics:
     - type: cos_sim_pearson
-      value: 59.1627744693388
+      value: 59.16277512775291
     - type: cos_sim_spearman
-      value: 57.53692924942505
+      value: 57.53693422381856
     - type: euclidean_pearson
-      value: 43.86657039278782
+      value: 57.85017283427473
     - type: euclidean_spearman
-      value: 45.082440020418424
+      value: 57.53697385589326
     - type: manhattan_pearson
-      value: 43.955740479348044
+      value: 58.049796184955596
     - type: manhattan_spearman
-      value: 45.15905727160372
+      value: 57.76174789162225
   - task:
       type: STS
     dataset:
@@ -5058,17 +5960,17 @@ model-index:
       revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
     metrics:
     - type: cos_sim_pearson
-      value: 74.42588616006334
+      value: 74.42588553600197
     - type: cos_sim_spearman
-      value: 74.25087851075787
+      value: 74.25087788257943
     - type: euclidean_pearson
-      value: 63.646746727259774
+      value: 73.35436018935222
     - type: euclidean_spearman
-      value: 63.150219043712106
+      value: 74.25087694991477
     - type: manhattan_pearson
-      value: 63.5341614083317
+      value: 73.33747415771185
     - type: manhattan_spearman
-      value: 63.00883784164611
+      value: 74.21504509447377
   - task:
       type: STS
     dataset:
@@ -5079,17 +5981,17 @@ model-index:
       revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
     metrics:
     - type: cos_sim_pearson
-      value: 75.77242395196524
+      value: 75.77242432372144
     - type: cos_sim_spearman
       value: 75.72930700521489
     - type: euclidean_pearson
-      value: 68.76523039736611
+      value: 75.6995220623788
     - type: euclidean_spearman
-      value: 67.96962494828459
+      value: 75.72930646047212
     - type: manhattan_pearson
-      value: 68.66742487680166
+      value: 75.65841087952896
     - type: manhattan_spearman
-      value: 67.89168383123581
+      value: 75.69567692328437
   - task:
       type: STS
     dataset:
@@ -5100,17 +6002,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 66.24952916970275
+      value: 66.2495297342053
     - type: cos_sim_spearman
-      value: 66.14121993606645
+      value: 66.14124319602982
     - type: euclidean_pearson
-      value: 48.49193377121151
+      value: 66.49498096178358
     - type: euclidean_spearman
-      value: 48.30443629726529
+      value: 66.14121792287747
     - type: manhattan_pearson
-      value: 48.580679507100214
+      value: 66.51560623835172
     - type: manhattan_spearman
-      value: 48.163570736145374
+      value: 66.05794413582558
   - task:
       type: STS
     dataset:
@@ -5121,17 +6023,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 75.00451698478369
+      value: 75.0045186560239
     - type: cos_sim_spearman
       value: 74.96504390762252
     - type: euclidean_pearson
-      value: 71.41544320562012
+      value: 74.20988464347049
     - type: euclidean_spearman
-      value: 69.8671968302191
+      value: 74.98114602301776
     - type: manhattan_pearson
-      value: 71.51396887529955
+      value: 74.37929169860529
     - type: manhattan_spearman
-      value: 70.13646740313014
+      value: 75.37049827509504
   - task:
       type: STS
     dataset:
@@ -5142,17 +6044,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 73.88477970895238
+      value: 73.88478151514396
     - type: cos_sim_spearman
       value: 74.05322141272103
     - type: euclidean_pearson
-      value: 60.60761818278518
+      value: 73.52175483343693
     - type: euclidean_spearman
-      value: 59.33251110095505
+      value: 74.05322141272103
     - type: manhattan_pearson
-      value: 60.419868469543594
+      value: 73.35875118828287
     - type: manhattan_spearman
-      value: 59.298607116416505
+      value: 73.83972625384673
   - task:
       type: STS
     dataset:
@@ -5163,17 +6065,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 75.57014739802696
+      value: 75.57014781622605
     - type: cos_sim_spearman
       value: 74.95329129562734
     - type: euclidean_pearson
-      value: 66.04424909946401
+      value: 75.5667786729257
     - type: euclidean_spearman
-      value: 65.36290486357399
+      value: 74.95329129562734
     - type: manhattan_pearson
-      value: 65.85564903072199
+      value: 75.39548673816147
     - type: manhattan_spearman
-      value: 65.1132393036515
+      value: 74.89428642503749
   - task:
       type: STS
     dataset:
@@ -5184,17 +6086,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 80.04007186284058
+      value: 80.04007129652777
     - type: cos_sim_spearman
       value: 79.94429611477106
     - type: euclidean_pearson
-      value: 73.04121359782312
+      value: 79.91583070858822
     - type: euclidean_spearman
-      value: 72.46378547225223
+      value: 79.94429611477106
     - type: manhattan_pearson
-      value: 73.20754563807353
+      value: 80.14382273152769
     - type: manhattan_spearman
-      value: 72.61008679959097
+      value: 80.23862855392836
   - task:
       type: STS
     dataset:
@@ -5205,17 +6107,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 77.28740927858394
+      value: 77.28740870194635
     - type: cos_sim_spearman
       value: 77.18286391819586
     - type: euclidean_pearson
-      value: 67.75873608167655
+      value: 77.05644328687119
     - type: euclidean_spearman
-      value: 66.81787653005944
+      value: 77.18286391819586
     - type: manhattan_pearson
-      value: 67.77279216343489
+      value: 77.15625898067294
     - type: manhattan_spearman
-      value: 66.9579776982823
+      value: 77.03165154316278
   - task:
       type: STS
     dataset:
@@ -5226,17 +6128,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 72.99292955338515
+      value: 72.99293002371301
     - type: cos_sim_spearman
       value: 72.24657859872468
     - type: euclidean_pearson
-      value: 63.52202589317903
+      value: 73.38839879755461
     - type: euclidean_spearman
-      value: 62.33443239002958
+      value: 72.24657859872468
     - type: manhattan_pearson
-      value: 63.769212052975476
+      value: 73.6627728800822
     - type: manhattan_spearman
-      value: 62.81347262019862
+      value: 72.70893449698669
   - task:
       type: STS
     dataset:
@@ -5247,17 +6149,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 81.37213847952495
+      value: 81.37213723705916
     - type: cos_sim_spearman
       value: 80.64548512701263
     - type: euclidean_pearson
-      value: 78.20509452005497
+      value: 80.94992193351284
     - type: euclidean_spearman
-      value: 76.92821412749807
+      value: 80.64484963200427
     - type: manhattan_pearson
-      value: 78.18187623856416
+      value: 80.92246813841794
     - type: manhattan_spearman
-      value: 76.80662828217807
+      value: 80.68860823161657
   - task:
       type: STS
     dataset:
@@ -5268,17 +6170,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 77.54059838849403
+      value: 77.54059604962391
     - type: cos_sim_spearman
       value: 77.19559169700682
     - type: euclidean_pearson
-      value: 65.48086288727644
+      value: 77.32739821317861
     - type: euclidean_spearman
-      value: 65.00387848487095
+      value: 77.19559169700682
     - type: manhattan_pearson
-      value: 65.39875192421043
+      value: 77.29224328831437
     - type: manhattan_spearman
-      value: 64.99073212282424
+      value: 77.24394878313191
   - task:
       type: STS
     dataset:
@@ -5289,17 +6191,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 79.06396980015494
+      value: 79.06397062195414
     - type: cos_sim_spearman
       value: 78.66694637555244
     - type: euclidean_pearson
-      value: 69.77559635500967
+      value: 79.34923290885872
     - type: euclidean_spearman
-      value: 69.6548076752796
+      value: 78.66694637555244
     - type: manhattan_pearson
-      value: 69.80486003899448
+      value: 79.50802161625809
     - type: manhattan_spearman
-      value: 69.64277606323098
+      value: 78.79195213396169
   - task:
       type: STS
     dataset:
@@ -5310,17 +6212,17 @@ model-index:
       revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
     metrics:
     - type: cos_sim_pearson
-      value: 78.66045887460483
+      value: 78.66045829245238
     - type: cos_sim_spearman
       value: 78.14055373851183
     - type: euclidean_pearson
-      value: 69.24649434854432
+      value: 78.94489279300518
     - type: euclidean_spearman
-      value: 68.92768315926817
+      value: 78.14055373851183
     - type: manhattan_pearson
-      value: 69.53186552758453
+      value: 79.33473165536323
     - type: manhattan_spearman
-      value: 69.1888421760678
+      value: 78.5783429705299
   - task:
       type: STS
     dataset:
@@ -5331,17 +6233,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 36.63454695072987
+      value: 36.63454535818336
     - type: cos_sim_spearman
       value: 47.12016162570126
     - type: euclidean_pearson
-      value: 40.706330494343604
+      value: 39.07268779927362
     - type: euclidean_spearman
-      value: 48.865006150948616
+      value: 47.12016162570126
     - type: manhattan_pearson
-      value: 45.099280138151926
+      value: 41.723119770725944
     - type: manhattan_spearman
-      value: 51.15098931364965
+      value: 47.90334362422989
   - task:
       type: STS
     dataset:
@@ -5352,17 +6254,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 13.32554927123781
+      value: 13.325547358617957
     - type: cos_sim_spearman
       value: 24.094051740693416
     - type: euclidean_pearson
-      value: 5.733247674182589
+      value: 10.39110006005262
     - type: euclidean_spearman
-      value: 17.32765054587116
+      value: 24.094051740693416
     - type: manhattan_pearson
-      value: 7.85068670554767
+      value: 12.4380555005162
     - type: manhattan_spearman
-      value: 19.003823576388488
+      value: 25.176800279885715
   - task:
       type: STS
     dataset:
@@ -5373,17 +6275,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 41.212816807176836
+      value: 41.21281570342249
     - type: cos_sim_spearman
       value: 55.397885077207974
     - type: euclidean_pearson
-      value: 44.32687000784094
+      value: 43.96150945976646
     - type: euclidean_spearman
-      value: 54.40126826356849
+      value: 55.397885077207974
     - type: manhattan_pearson
-      value: 49.72970710546519
+      value: 49.58812224529121
     - type: manhattan_spearman
-      value: 56.49113106101981
+      value: 55.35874879475974
   - task:
       type: STS
     dataset:
@@ -5394,17 +6296,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 5.985016492310366
+      value: 5.985012243744998
     - type: cos_sim_spearman
       value: 25.307464943919012
     - type: euclidean_pearson
-      value: -6.568128940119214
+      value: -4.080537702499046
     - type: euclidean_spearman
-      value: 23.37422025614559
+      value: 25.307464943919012
     - type: manhattan_pearson
-      value: -4.99967062376341
+      value: -2.5058642304196543
     - type: manhattan_spearman
-      value: 25.00987603568494
+      value: 26.751588484373233
   - task:
       type: STS
     dataset:
@@ -5415,17 +6317,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 34.44666733247214
+      value: 34.44666578772084
     - type: cos_sim_spearman
       value: 46.45977141800899
     - type: euclidean_pearson
-      value: 38.168335484005496
+      value: 38.78305544036559
     - type: euclidean_spearman
-      value: 45.87203585565584
+      value: 46.45977141800899
     - type: manhattan_pearson
-      value: 45.96851222581045
+      value: 46.45101297876112
     - type: manhattan_spearman
-      value: 50.72243559635815
+      value: 50.642972694093814
   - task:
       type: STS
     dataset:
@@ -5436,17 +6338,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 28.095330260570044
+      value: 28.095327083873055
     - type: cos_sim_spearman
       value: 40.24741745875892
     - type: euclidean_pearson
-      value: 34.298302094447
+      value: 29.141496784653892
     - type: euclidean_spearman
-      value: 41.75099510117058
+      value: 40.24741745875892
     - type: manhattan_pearson
-      value: 36.822574344860016
+      value: 32.013290716034064
     - type: manhattan_spearman
-      value: 43.24173881526762
+      value: 40.85454084311211
   - task:
       type: STS
     dataset:
@@ -5457,17 +6359,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 27.467875570822507
+      value: 27.46788309503312
     - type: cos_sim_spearman
       value: 43.57385391855994
     - type: euclidean_pearson
-      value: 22.17414485325322
+      value: 24.558349674326177
     - type: euclidean_spearman
-      value: 39.95656416250951
+      value: 43.57385391855994
     - type: manhattan_pearson
-      value: 26.066273487373664
+      value: 28.974505207055866
     - type: manhattan_spearman
-      value: 40.14230396654245
+      value: 44.111553205713
   - task:
       type: STS
     dataset:
@@ -5478,17 +6380,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 34.87842153404196
+      value: 34.87841073990563
     - type: cos_sim_spearman
       value: 52.8221686505807
     - type: euclidean_pearson
-      value: 35.93221146007856
+      value: 38.36114580544504
     - type: euclidean_spearman
-      value: 51.489361135954105
+      value: 52.8221686505807
     - type: manhattan_pearson
-      value: 44.030913421863026
+      value: 46.69329448756753
     - type: manhattan_spearman
-      value: 52.999521693608465
+      value: 53.9140781097337
   - task:
       type: STS
     dataset:
@@ -5499,17 +6401,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 49.999270334861315
+      value: 49.999267528357
     - type: cos_sim_spearman
       value: 61.71837669697145
     - type: euclidean_pearson
-      value: 49.955296540972824
+      value: 53.578476744372274
     - type: euclidean_spearman
-      value: 56.505586159244515
+      value: 61.71837669697145
     - type: manhattan_pearson
-      value: 52.49957702118715
+      value: 56.410294227490795
     - type: manhattan_spearman
-      value: 57.12582682664643
+      value: 60.684457655864875
   - task:
       type: STS
     dataset:
@@ -5520,17 +6422,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 22.43564766265908
+      value: 22.43564137760586
     - type: cos_sim_spearman
       value: 34.28346144104183
     - type: euclidean_pearson
-      value: 33.017091607053786
+      value: 27.41326011184764
     - type: euclidean_spearman
-      value: 37.60239300835095
+      value: 34.28346144104183
     - type: manhattan_pearson
-      value: 43.842762856035904
+      value: 35.62923154232163
     - type: manhattan_spearman
-      value: 44.71536370367842
+      value: 37.937151135297185
   - task:
       type: STS
     dataset:
@@ -5541,17 +6443,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 44.34071373662986
+      value: 44.34071611983998
     - type: cos_sim_spearman
       value: 57.823185616169646
     - type: euclidean_pearson
-      value: 53.672221309748835
+      value: 49.29310650157244
     - type: euclidean_spearman
-      value: 62.001696407713126
+      value: 57.823185616169646
     - type: manhattan_pearson
-      value: 61.30617811516088
+      value: 55.93298736518848
     - type: manhattan_spearman
-      value: 63.97035045686644
+      value: 58.57556581684834
   - task:
       type: STS
     dataset:
@@ -5562,17 +6464,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 56.07027264854201
+      value: 56.07027840344927
     - type: cos_sim_spearman
       value: 62.20158260763411
     - type: euclidean_pearson
-      value: 55.89068916951512
+      value: 55.887969718543616
     - type: euclidean_spearman
-      value: 61.46687669950822
+      value: 62.20158260763411
     - type: manhattan_pearson
-      value: 55.82045134105482
+      value: 56.081533365738444
     - type: manhattan_spearman
-      value: 61.097021240849394
+      value: 62.018651361750685
   - task:
       type: STS
     dataset:
@@ -5583,17 +6485,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 41.418158049627344
+      value: 41.41816324477061
     - type: cos_sim_spearman
       value: 44.71684955996943
     - type: euclidean_pearson
-      value: 44.09873868592676
+      value: 42.74585025834968
     - type: euclidean_spearman
-      value: 48.582169034980765
+      value: 44.71684955996943
     - type: manhattan_pearson
-      value: 51.11307812290116
+      value: 47.992481632815256
     - type: manhattan_spearman
-      value: 51.613996439908796
+      value: 46.18587933349126
   - task:
       type: STS
     dataset:
@@ -5604,17 +6506,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 38.89141661170763
+      value: 38.89140730917917
     - type: cos_sim_spearman
       value: 49.18633779347391
     - type: euclidean_pearson
-      value: 48.37473555026282
+      value: 43.27605428753535
     - type: euclidean_spearman
-      value: 54.17536451762477
+      value: 49.18633779347391
     - type: manhattan_pearson
-      value: 55.06464763414177
+      value: 48.22046568809415
     - type: manhattan_spearman
-      value: 55.27394644455171
+      value: 49.248416391249464
   - task:
       type: STS
     dataset:
@@ -5625,17 +6527,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 40.31621370101309
+      value: 40.31620568726327
     - type: cos_sim_spearman
       value: 49.13034440774138
     - type: euclidean_pearson
-      value: 46.55326804225437
+      value: 43.95169508285692
     - type: euclidean_spearman
-      value: 50.04387120070582
+      value: 49.13034440774138
     - type: manhattan_pearson
-      value: 51.108871970953615
+      value: 48.84250981398146
     - type: manhattan_spearman
-      value: 50.77822527742335
+      value: 49.54216339903405
   - task:
       type: STS
     dataset:
@@ -5646,17 +6548,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 27.07459941263371
+      value: 27.074582378144058
     - type: cos_sim_spearman
       value: 41.29498619968451
     - type: euclidean_pearson
-      value: 28.81148557875536
+      value: 28.993986097276505
     - type: euclidean_spearman
-      value: 44.23270186092313
+      value: 41.29498619968451
     - type: manhattan_pearson
-      value: 33.37331199208485
+      value: 32.079813951133254
     - type: manhattan_spearman
-      value: 44.702014347511174
+      value: 43.664111732941464
   - task:
       type: STS
     dataset:
@@ -5667,17 +6569,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 6.864350141604963
+      value: 6.864334110072116
     - type: cos_sim_spearman
       value: 25.805458732687914
     - type: euclidean_pearson
-      value: 22.41182782328486
+      value: 11.435920047618103
     - type: euclidean_spearman
-      value: 41.47965741399835
+      value: 25.805458732687914
     - type: manhattan_pearson
-      value: 27.52235896097151
+      value: 15.036308569899552
     - type: manhattan_spearman
-      value: 45.11336162695441
+      value: 25.405135387192757
   - task:
       type: STS
     dataset:
@@ -5688,17 +6590,17 @@ model-index:
       revision: eea2b4fe26a775864c896887d910b76a8098ad3f
     metrics:
     - type: cos_sim_pearson
-      value: 65.4403182219975
+      value: 65.44029549925597
     - type: cos_sim_spearman
       value: 61.97797868009122
     - type: euclidean_pearson
-      value: 57.9607330049556
+      value: 65.92740669959876
     - type: euclidean_spearman
-      value: 50.709255283710995
+      value: 61.97797868009122
     - type: manhattan_pearson
-      value: 61.3956353319538
+      value: 70.29575044091207
     - type: manhattan_spearman
-      value: 61.97797868009122
+      value: 73.24670207647144
   - task:
       type: STS
     dataset:
@@ -5709,17 +6611,17 @@ model-index:
       revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
     metrics:
     - type: cos_sim_pearson
-      value: 51.354132781205294
+      value: 51.35413149349556
     - type: cos_sim_spearman
-      value: 50.17494133468151
+      value: 50.175051356729924
     - type: euclidean_pearson
-      value: 38.11014000059295
+      value: 53.12039152785364
     - type: euclidean_spearman
-      value: 37.5997050693584
+      value: 50.174289111089685
     - type: manhattan_pearson
-      value: 37.99036693507327
+      value: 53.0731746793555
     - type: manhattan_spearman
-      value: 37.584133861146974
+      value: 50.15176393928403
   - task:
       type: STS
     dataset:
@@ -5730,17 +6632,17 @@ model-index:
       revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
     metrics:
     - type: cos_sim_pearson
-      value: 67.84222997484147
+      value: 67.84222983023291
     - type: cos_sim_spearman
       value: 67.39086924655895
     - type: euclidean_pearson
-      value: 51.87216665821589
+      value: 67.3393327127967
     - type: euclidean_spearman
-      value: 51.309915218441695
+      value: 67.39088047106472
     - type: manhattan_pearson
-      value: 51.871943884893454
+      value: 67.40316731822271
     - type: manhattan_spearman
-      value: 51.271356979504375
+      value: 67.49067800994015
   - task:
       type: Classification
     dataset:
@@ -5751,11 +6653,11 @@ model-index:
       revision: 1de08520a7b361e92ffa2a2201ebd41942c54675
     metrics:
     - type: accuracy
-      value: 50.68359375
+      value: 50.62988281250001
     - type: ap
-      value: 50.348173771768124
+      value: 50.32274824114816
     - type: f1
-      value: 50.38855675524828
+      value: 50.37741703766756
   - task:
       type: Classification
     dataset:
@@ -5766,11 +6668,11 @@ model-index:
       revision: 237111a078ad5a834a55c57803d40bbe410ed03b
     metrics:
     - type: accuracy
-      value: 50.9033203125
+      value: 51.181640625
     - type: ap
-      value: 50.464534818390305
+      value: 50.60884394099696
     - type: f1
-      value: 50.12338348445107
+      value: 50.866988720930415
   - task:
       type: Classification
     dataset:
@@ -5781,11 +6683,11 @@ model-index:
       revision: 9d9a2a4092ed3cacf0744592f6d2f32ab8ef4c0b
     metrics:
     - type: accuracy
-      value: 50.7568359375
+      value: 50.9375
     - type: ap
-      value: 50.38550393534486
+      value: 50.47969135089731
     - type: f1
-      value: 50.19852110629762
+      value: 50.62913552324756
   - task:
       type: Classification
     dataset:
@@ -5796,11 +6698,11 @@ model-index:
       revision: 1b48e3dcb02872335ff985ff938a054a4ed99008
     metrics:
     - type: accuracy
-      value: 50.9619140625
+      value: 51.1474609375
     - type: ap
-      value: 50.494690837095156
+      value: 50.5894187272385
     - type: f1
-      value: 50.26727387729569
+      value: 50.901812392367916
   - task:
       type: Reranking
     dataset:
@@ -5883,6 +6785,75 @@ model-index:
       value: 35.693999999999996
     - type: recall_at_5
       value: 40.944
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact-pl
+      name: MTEB SciFact-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.706
+    - type: map_at_10
+      value: 28.333000000000002
+    - type: map_at_100
+      value: 29.364
+    - type: map_at_1000
+      value: 29.451
+    - type: map_at_3
+      value: 26.112999999999996
+    - type: map_at_5
+      value: 27.502
+    - type: mrr_at_1
+      value: 23.0
+    - type: mrr_at_10
+      value: 29.555999999999997
+    - type: mrr_at_100
+      value: 30.536
+    - type: mrr_at_1000
+      value: 30.606
+    - type: mrr_at_3
+      value: 27.333000000000002
+    - type: mrr_at_5
+      value: 28.717
+    - type: ndcg_at_1
+      value: 23.0
+    - type: ndcg_at_10
+      value: 32.238
+    - type: ndcg_at_100
+      value: 37.785999999999994
+    - type: ndcg_at_1000
+      value: 40.266999999999996
+    - type: ndcg_at_3
+      value: 27.961000000000002
+    - type: ndcg_at_5
+      value: 30.322
+    - type: precision_at_1
+      value: 23.0
+    - type: precision_at_10
+      value: 4.7669999999999995
+    - type: precision_at_100
+      value: 0.787
+    - type: precision_at_1000
+      value: 0.10200000000000001
+    - type: precision_at_3
+      value: 11.444
+    - type: precision_at_5
+      value: 8.200000000000001
+    - type: recall_at_1
+      value: 21.706
+    - type: recall_at_10
+      value: 43.206
+    - type: recall_at_100
+      value: 69.678
+    - type: recall_at_1000
+      value: 89.333
+    - type: recall_at_3
+      value: 31.900000000000002
+    - type: recall_at_5
+      value: 37.594
   - task:
       type: PairClassification
     dataset:
@@ -5903,41 +6874,41 @@ model-index:
     - type: cos_sim_recall
       value: 68.4
     - type: dot_accuracy
-      value: 99.19108910891089
+      value: 99.5
     - type: dot_ap
-      value: 49.25491405967686
+      value: 77.07584309978081
     - type: dot_f1
-      value: 49.716932578486876
+      value: 71.8864950078823
     - type: dot_precision
-      value: 51.21951219512195
+      value: 75.74750830564784
     - type: dot_recall
-      value: 48.3
+      value: 68.4
     - type: euclidean_accuracy
-      value: 99.19009900990099
+      value: 99.5
     - type: euclidean_ap
-      value: 42.03570656308142
+      value: 77.07584309978081
     - type: euclidean_f1
-      value: 44.82153306026916
+      value: 71.8864950078823
     - type: euclidean_precision
-      value: 54.01974612129761
+      value: 75.74750830564784
     - type: euclidean_recall
-      value: 38.3
+      value: 68.4
     - type: manhattan_accuracy
-      value: 99.19207920792078
+      value: 99.50594059405941
     - type: manhattan_ap
-      value: 42.109436522707014
+      value: 77.41658577240027
     - type: manhattan_f1
-      value: 44.79905437352246
+      value: 71.91374663072777
     - type: manhattan_precision
-      value: 54.76878612716764
+      value: 78.01169590643275
     - type: manhattan_recall
-      value: 37.9
+      value: 66.7
     - type: max_accuracy
-      value: 99.5
+      value: 99.50594059405941
     - type: max_ap
-      value: 77.07584309978081
+      value: 77.41658577240027
     - type: max_f1
-      value: 71.8864950078823
+      value: 71.91374663072777
   - task:
       type: Clustering
     dataset:
@@ -5948,7 +6919,7 @@ model-index:
       revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
     metrics:
     - type: v_measure
-      value: 37.40985053432638
+      value: 46.32521494308228
   - task:
       type: Clustering
     dataset:
@@ -5959,7 +6930,7 @@ model-index:
       revision: 815ca46b2622cec33ccafc3735d572c266efdb44
     metrics:
     - type: v_measure
-      value: 19.657671371166966
+      value: 20.573273825125266
   - task:
       type: Reranking
     dataset:
@@ -5983,13 +6954,13 @@ model-index:
       revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
     metrics:
     - type: cos_sim_pearson
-      value: 29.305333790118766
+      value: 29.305330424238836
     - type: cos_sim_spearman
       value: 30.556621737388685
     - type: dot_pearson
-      value: 30.309505984206115
+      value: 29.30533056265583
     - type: dot_spearman
-      value: 31.302092660260872
+      value: 30.556621737388685
   - task:
       type: Classification
     dataset:
@@ -6000,9 +6971,9 @@ model-index:
       revision: 3c62f26bafdc4c4e1c16401ad4b32f0a94b46612
     metrics:
     - type: accuracy
-      value: 66.8701171875
+      value: 68.4716796875
     - type: f1
-      value: 54.75017096649799
+      value: 59.865730786092364
   - task:
       type: Reranking
     dataset:
@@ -6095,9 +7066,9 @@ model-index:
       revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
     metrics:
     - type: accuracy
-      value: 37.254
+      value: 40.946
     - type: f1
-      value: 36.23675255530671
+      value: 39.56517169731474
   - task:
       type: Retrieval
     dataset:
@@ -6167,6 +7138,75 @@ model-index:
       value: 0.28200000000000003
     - type: recall_at_5
       value: 0.379
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid-pl
+      name: MTEB TRECCOVID-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.124
+    - type: map_at_10
+      value: 0.45199999999999996
+    - type: map_at_100
+      value: 0.874
+    - type: map_at_1000
+      value: 1.1039999999999999
+    - type: map_at_3
+      value: 0.253
+    - type: map_at_5
+      value: 0.32299999999999995
+    - type: mrr_at_1
+      value: 36.0
+    - type: mrr_at_10
+      value: 47.56
+    - type: mrr_at_100
+      value: 48.532
+    - type: mrr_at_1000
+      value: 48.579
+    - type: mrr_at_3
+      value: 45.0
+    - type: mrr_at_5
+      value: 45.5
+    - type: ndcg_at_1
+      value: 34.0
+    - type: ndcg_at_10
+      value: 24.529
+    - type: ndcg_at_100
+      value: 10.427
+    - type: ndcg_at_1000
+      value: 6.457
+    - type: ndcg_at_3
+      value: 31.173000000000002
+    - type: ndcg_at_5
+      value: 27.738000000000003
+    - type: precision_at_1
+      value: 38.0
+    - type: precision_at_10
+      value: 25.4
+    - type: precision_at_100
+      value: 8.88
+    - type: precision_at_1000
+      value: 2.2159999999999997
+    - type: precision_at_3
+      value: 34.666999999999994
+    - type: precision_at_5
+      value: 29.2
+    - type: recall_at_1
+      value: 0.124
+    - type: recall_at_10
+      value: 0.618
+    - type: recall_at_100
+      value: 1.9349999999999998
+    - type: recall_at_1000
+      value: 4.808
+    - type: recall_at_3
+      value: 0.28300000000000003
+    - type: recall_at_5
+      value: 0.382
   - task:
       type: BitextMining
     dataset:
@@ -6519,7 +7559,7 @@ model-index:
     - type: accuracy
       value: 70.47619047619048
     - type: f1
-      value: 66.63032734461308
+      value: 66.63032734461306
     - type: precision
       value: 65.46459191863879
     - type: recall
@@ -8081,7 +9121,7 @@ model-index:
       revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558
     metrics:
     - type: v_measure
-      value: 19.988360713728564
+      value: 21.827519839402644
   - task:
       type: Clustering
     dataset:
@@ -8092,7 +9132,7 @@ model-index:
       revision: 6cddbe003f12b9b140aec477b583ac4191f01786
     metrics:
     - type: v_measure
-      value: 25.49952010397176
+      value: 27.160188241713684
   - task:
       type: Clustering
     dataset:
@@ -8103,7 +9143,7 @@ model-index:
       revision: 5798586b105c0434e4f0fe5e767abe619442cf93
     metrics:
     - type: v_measure
-      value: 32.012653950111556
+      value: 38.54459276932986
   - task:
       type: Clustering
     dataset:
@@ -8114,7 +9154,7 @@ model-index:
       revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
     metrics:
     - type: v_measure
-      value: 42.08914091890925
+      value: 43.4460576234314
   - task:
       type: Retrieval
     dataset:
@@ -8194,11 +9234,11 @@ model-index:
       revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
     metrics:
     - type: accuracy
-      value: 63.5394
+      value: 67.28359999999999
     - type: ap
-      value: 11.440330234311777
+      value: 12.424592214862038
     - type: f1
-      value: 48.937405112008854
+      value: 51.53630450055703
   - task:
       type: Classification
     dataset:
@@ -8209,9 +9249,9 @@ model-index:
       revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
     metrics:
     - type: accuracy
-      value: 55.16694963214488
+      value: 56.23372948500284
     - type: f1
-      value: 55.275387066931124
+      value: 56.440924587214234
   - task:
       type: Clustering
     dataset:
@@ -8222,7 +9262,7 @@ model-index:
       revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
     metrics:
     - type: v_measure
-      value: 19.628551067284956
+      value: 24.410059815620116
   - task:
       type: PairClassification
     dataset:
@@ -8235,7 +9275,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 80.3302139834297
     - type: cos_sim_ap
-      value: 53.577244820707605
+      value: 53.57723069745093
     - type: cos_sim_f1
       value: 51.58639580004565
     - type: cos_sim_precision
@@ -8243,39 +9283,39 @@ model-index:
     - type: cos_sim_recall
       value: 59.63060686015831
     - type: dot_accuracy
-      value: 80.14543720569827
+      value: 80.3302139834297
     - type: dot_ap
-      value: 52.0875752603294
+      value: 53.57723006705641
     - type: dot_f1
-      value: 51.38086062941555
+      value: 51.58639580004565
     - type: dot_precision
-      value: 43.22766570605187
+      value: 45.45454545454545
     - type: dot_recall
-      value: 63.3245382585752
+      value: 59.63060686015831
     - type: euclidean_accuracy
-      value: 78.82815759670979
+      value: 80.3302139834297
     - type: euclidean_ap
-      value: 42.100001806860824
+      value: 53.57723050286929
     - type: euclidean_f1
-      value: 42.769230769230774
+      value: 51.58639580004565
     - type: euclidean_precision
-      value: 34.98322147651007
+      value: 45.45454545454545
     - type: euclidean_recall
-      value: 55.01319261213721
+      value: 59.63060686015831
     - type: manhattan_accuracy
-      value: 78.82815759670979
+      value: 80.31233235977827
     - type: manhattan_ap
-      value: 41.936649509973165
+      value: 53.44943961562638
     - type: manhattan_f1
-      value: 42.57720324202319
+      value: 51.24183006535947
     - type: manhattan_precision
-      value: 34.832969615578314
+      value: 43.63636363636363
     - type: manhattan_recall
-      value: 54.74934036939314
+      value: 62.05804749340369
     - type: max_accuracy
       value: 80.3302139834297
     - type: max_ap
-      value: 53.577244820707605
+      value: 53.57723069745093
     - type: max_f1
       value: 51.58639580004565
   - task:
@@ -8290,7 +9330,7 @@ model-index:
     - type: cos_sim_accuracy
       value: 87.45876508712695
     - type: cos_sim_ap
-      value: 83.53208334948403
+      value: 83.5320716566614
     - type: cos_sim_f1
       value: 75.54560716284276
     - type: cos_sim_precision
@@ -8298,39 +9338,39 @@ model-index:
     - type: cos_sim_recall
       value: 77.95657530027718
     - type: dot_accuracy
-      value: 85.64054798773626
+      value: 87.45876508712695
     - type: dot_ap
-      value: 77.96456929342345
+      value: 83.53209944887666
     - type: dot_f1
-      value: 72.09775967413442
+      value: 75.54560716284276
     - type: dot_precision
-      value: 67.26448429895326
+      value: 73.27929362379678
     - type: dot_recall
-      value: 77.6793963658762
+      value: 77.95657530027718
     - type: euclidean_accuracy
-      value: 84.78480226646485
+      value: 87.45876508712695
     - type: euclidean_ap
-      value: 75.64618087898923
+      value: 83.53205938307582
     - type: euclidean_f1
-      value: 67.1075581395349
+      value: 75.54560716284276
     - type: euclidean_precision
-      value: 63.54252683732452
+      value: 73.27929362379678
     - type: euclidean_recall
-      value: 71.0963966738528
+      value: 77.95657530027718
     - type: manhattan_accuracy
-      value: 84.72658827182055
+      value: 87.52280048123569
     - type: manhattan_ap
-      value: 75.51009726264691
+      value: 83.4884324728773
     - type: manhattan_f1
-      value: 67.00128311570685
+      value: 75.43366677906411
     - type: manhattan_precision
-      value: 65.70688378978534
+      value: 73.46566445303948
     - type: manhattan_recall
-      value: 68.34770557437635
+      value: 77.51000923929782
     - type: max_accuracy
-      value: 87.45876508712695
+      value: 87.52280048123569
     - type: max_ap
-      value: 83.53208334948403
+      value: 83.53209944887666
     - type: max_f1
       value: 75.54560716284276
   - task:
@@ -8412,11 +9452,11 @@ model-index:
       revision: 339287def212450dcaa9df8c22bf93e9980c7023
     metrics:
     - type: accuracy
-      value: 70.44
+      value: 76.12
     - type: ap
-      value: 49.70788956752899
+      value: 54.1619589378045
     - type: f1
-      value: 69.57867775339233
+      value: 74.32372858884229
   - task:
       type: Clustering
     dataset:
@@ -8427,7 +9467,76 @@ model-index:
       revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
     metrics:
     - type: v_measure
-      value: 48.038657353672534
+      value: 50.71744674029636
+  - task:
+      type: Retrieval
+    dataset:
+      type: jinaai/xmarket_de
+      name: MTEB XMarketDE
+      config: default
+      split: test
+      revision: 2336818db4c06570fcdf263e1bcb9993b786f67a
+    metrics:
+    - type: map_at_1
+      value: 0.182
+    - type: map_at_10
+      value: 0.266
+    - type: map_at_100
+      value: 0.295
+    - type: map_at_1000
+      value: 0.313
+    - type: map_at_3
+      value: 0.232
+    - type: map_at_5
+      value: 0.23800000000000002
+    - type: mrr_at_1
+      value: 1.3379999999999999
+    - type: mrr_at_10
+      value: 1.918
+    - type: mrr_at_100
+      value: 2.051
+    - type: mrr_at_1000
+      value: 2.084
+    - type: mrr_at_3
+      value: 1.7049999999999998
+    - type: mrr_at_5
+      value: 1.791
+    - type: ndcg_at_1
+      value: 1.3379999999999999
+    - type: ndcg_at_10
+      value: 0.859
+    - type: ndcg_at_100
+      value: 0.8500000000000001
+    - type: ndcg_at_1000
+      value: 1.345
+    - type: ndcg_at_3
+      value: 1.032
+    - type: ndcg_at_5
+      value: 0.918
+    - type: precision_at_1
+      value: 1.3379999999999999
+    - type: precision_at_10
+      value: 0.528
+    - type: precision_at_100
+      value: 0.22699999999999998
+    - type: precision_at_1000
+      value: 0.132
+    - type: precision_at_3
+      value: 0.8829999999999999
+    - type: precision_at_5
+      value: 0.6890000000000001
+    - type: recall_at_1
+      value: 0.182
+    - type: recall_at_10
+      value: 0.51
+    - type: recall_at_100
+      value: 1.2229999999999999
+    - type: recall_at_1000
+      value: 4.183
+    - type: recall_at_3
+      value: 0.292
+    - type: recall_at_5
+      value: 0.315
 ---
 
 # SONAR