Feat: update mteb

README.md

@@ -21,9 +21,9 @@ model-index:
       revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
     metrics:
     - type: v_measure
-      value: 62.16774435322237
+      value: 63.19030822769444
     - type: v_measures
-      value: [0.60677169174265, 0.6420496407630484, 0.5831486687495704, 0.6103877439594066, 0.6135248698273804]
+      value: [0.5938891912573394, 0.6171518411959, 0.6042518292029612, 0.6626602879382325, 0.6471224639325329]
   - task:
       type: Clustering
     dataset:
@@ -34,9 +34,9 @@ model-index:
       revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
     metrics:
     - type: v_measure
-      value: 45.11926529002472
+      value: 41.32807908087869
     - type: v_measures
-      value: [0.4690142817423344, 0.48186364883143407, 0.40961058482586177, 0.4555301647788916, 0.49555829107195404]
+      value: [0.3351458197856525, 0.48472823318531566, 0.4631757871803168, 0.43580166532679027, 0.4219041689415661]
   - task:
       type: Reranking
     dataset:
@@ -47,17 +47,17 @@ model-index:
       revision: 65393d0d7a08a10b4e348135e824f385d420b0fd
     metrics:
     - type: map
-      value: 69.49670623246055
+      value: 68.43888603876276
     - type: mrr
-      value: 70.57920059215395
+      value: 69.59097513501659
     - type: nAUC_map_diff1
-      value: 46.93583791194171
+      value: 47.92767021121887
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-      value: 12.952266693104086
+      value: 10.206900586093957
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-      value: 46.49838896134123
+      value: 47.823670000503014
     - type: nAUC_mrr_max
-      value: 12.945500349888256
+      value: 10.266197221615979
   - task:
       type: Retrieval
     dataset:
@@ -68,215 +68,215 @@ model-index:
       revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
     metrics:
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+      value: 34.554
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+      value: 34.621
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+      value: 34.129
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+      value: 30.526999999999997
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+      value: 32.107
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   - task:
       type: Classification
     dataset:
@@ -287,11 +287,11 @@ model-index:
       revision: 1399c76144fd37290681b995c656ef9b2e06e26d
     metrics:
     - type: accuracy
-      value: 36.476000000000006
+      value: 37.102000000000004
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     - type: f1_weighted
-      value: 36.03335046550013
+      value: 36.48213245522153
   - task:
       type: Retrieval
     dataset:
@@ -302,215 +302,215 @@ model-index:
       revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
     metrics:
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-    - type: recall_at_5
       value: 9.91
+    - type: recall_at_5
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   - task:
       type: Clustering
     dataset:
@@ -521,35 +521,35 @@ model-index:
       revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
     metrics:
     - type: v_measure
-      value: 23.558078744326544
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     - type: v_measures
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+      value: [0.28321300949906897, 0.26004472642751963, 0.25956951558284086, 0.24123195304666292, 0.22207486085944725]
   - task:
       type: Clustering
     dataset:
       type: reciTAL/mlsum
       name: MTEB MLSUMClusteringP2P
-      config: fr
+      config: default
       split: test
       revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
     metrics:
     - type: v_measure
-      value: 43.301348316325736
+      value: 44.10635133884183
     - type: v_measures
-      value: [0.4233196411550677, 0.44970595264164037, 0.45186708688635496, 0.42148885803149255, 0.40025908391437176]
+      value: [0.4352021194557699, 0.4616076200837005, 0.4407517544208635, 0.4387026615402928, 0.40575306284000634]
   - task:
       type: Clustering
     dataset:
       type: reciTAL/mlsum
       name: MTEB MLSUMClusteringS2S
-      config: fr
+      config: default
       split: test
       revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
     metrics:
     - type: v_measure
-      value: 42.77218507395412
+      value: 43.6574557237274
     - type: v_measures
-      value: [0.43093819041603315, 0.43214445147026653, 0.437274496285348, 0.39675619790062994, 0.3965947118445383]
+      value: [0.431013360873005, 0.45456972088535785, 0.4474907746228345, 0.4318507494303067, 0.3857692351737129]
   - task:
       type: Classification
     dataset:
@@ -560,11 +560,11 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 84.19041653617289
+      value: 86.08518634512997
     - type: f1
-      value: 84.31104471084487
+      value: 86.01437763316983
     - type: f1_weighted
-      value: 84.10618363737768
+      value: 86.03483392539235
   - task:
       type: Classification
     dataset:
@@ -575,11 +575,11 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 58.3463827121829
+      value: 61.23081741309113
     - type: f1
-      value: 43.088632109848426
+      value: 44.76981337966934
     - type: f1_weighted
-      value: 62.107376647577894
+      value: 64.86577219367403
   - task:
       type: Classification
     dataset:
@@ -590,11 +590,11 @@ model-index:
       revision: 18193f187b92da67168c655c9973a165ed9593dd
     metrics:
     - type: accuracy
-      value: 78.43601895734596
+      value: 78.34123222748815
     - type: f1
-      value: 74.45529808417628
+      value: 74.19808376161188
     - type: f1_weighted
-      value: 78.62574024040258
+      value: 78.465165305135
   - task:
       type: Clustering
     dataset:
@@ -605,9 +605,9 @@ model-index:
       revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
     metrics:
     - type: v_measure
-      value: 52.87571544597074
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     - type: v_measures
-      value: [1.0, 0.0363409432192075, 0.14130554872026818, 0.690570263898874, 0.7755690164601873]
+      value: [1.0, 0.052551289167589395, 0.4126124221990744, 0.690570263898874, 0.7755690164601873]
   - task:
       type: Clustering
     dataset:
@@ -618,9 +618,9 @@ model-index:
       revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
     metrics:
     - type: v_measure
-      value: 53.93220782443
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     - type: v_measures
-      value: [1.0, 0.08628485862349315, 0.4767520746594815, 0.41112983961194033, 0.7224436183265853]
+      value: [1.0, 0.06287268264858063, 0.6712730568122484, 0.2169401386066275, 0.7224436183265853]
   - task:
       type: Classification
     dataset:
@@ -631,11 +631,11 @@ model-index:
       revision: 4672e20407010da34463acc759c162ca9734bca6
     metrics:
     - type: accuracy
-      value: 64.57296570275723
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     - type: f1_weighted
-      value: 64.87910807109024
+      value: 65.62227422445625
   - task:
       type: Classification
     dataset:
@@ -646,11 +646,11 @@ model-index:
       revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
     metrics:
     - type: accuracy
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     - type: f1_weighted
-      value: 69.14028442566733
+      value: 69.39025426049528
   - task:
       type: Retrieval
     dataset:
@@ -661,215 +661,215 @@ model-index:
       revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
     metrics:
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       value: 0.094
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     - type: precision_at_5
-      value: 6.223999999999999
+      value: 6.216
     - type: recall_at_1
-      value: 13.514000000000001
+      value: 13.718
     - type: recall_at_10
-      value: 39.23
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     - type: recall_at_100
-      value: 64.292
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     - type: recall_at_1000
-      value: 93.89800000000001
+      value: 94.10300000000001
     - type: recall_at_20
-      value: 47.297
+      value: 46.97
     - type: recall_at_3
-      value: 26.003
+      value: 25.921
     - type: recall_at_5
-      value: 31.122
+      value: 31.080999999999996
   - task:
       type: PairClassification
     dataset:
@@ -879,52 +879,52 @@ model-index:
       split: test
       revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
     metrics:
-    - type: cos_sim_accuracy
-      value: 80.72207084468664
-    - type: cos_sim_ap
-      value: 92.59899042186348
-    - type: cos_sim_f1
-      value: 87.02702702702703
-    - type: cos_sim_precision
-      value: 79.63726298433635
-    - type: cos_sim_recall
-      value: 95.92850049652433
-    - type: dot_accuracy
-      value: 80.79019073569482
-    - type: dot_ap
-      value: 92.27564754544716
-    - type: dot_f1
-      value: 87.13503649635037
-    - type: dot_precision
-      value: 80.59071729957806
-    - type: dot_recall
-      value: 94.83614697120158
-    - type: euclidean_accuracy
-      value: 80.51771117166212
-    - type: euclidean_ap
-      value: 92.1992933566427
-    - type: euclidean_f1
-      value: 86.73050615595076
-    - type: euclidean_precision
-      value: 80.18549747048904
-    - type: euclidean_recall
-      value: 94.43892750744787
-    - type: manhattan_accuracy
-      value: 80.3133514986376
-    - type: manhattan_ap
-      value: 92.1464473897072
-    - type: manhattan_f1
-      value: 86.8217054263566
-    - type: manhattan_precision
-      value: 80.26981450252951
-    - type: manhattan_recall
-      value: 94.5382323733863
-    - type: max_accuracy
-      value: 80.79019073569482
-    - type: max_ap
-      value: 92.59899042186348
-    - type: max_f1
-      value: 87.13503649635037
+      - type: cos_sim_accuracy
+        value: 81.81198910081744
+      - type: cos_sim_ap
+        value: 92.92034333454589
+      - type: cos_sim_f1
+        value: 87.20651653090561
+      - type: cos_sim_precision
+        value: 84.25925925925926
+      - type: cos_sim_recall
+        value: 90.36742800397219
+      - type: dot_accuracy
+        value: 81.06267029992752
+      - type: dot_ap
+        value: 92.19923182286357
+      - type: dot_f1
+        value: 87.23307587460246
+      - type: dot_precision
+        value: 80.40200995025126
+      - type: dot_recall
+        value: 95.33267130089378
+      - type: euclidean_accuracy
+        value: 81.06267029992752
+      - type: euclidean_ap
+        value: 92.58456772515232
+      - type: euclidean_f1
+        value: 86.94835680751173
+      - type: euclidean_precision
+        value: 82.45770258236865
+      - type: euclidean_recall
+        value: 91.95630585898709
+      - type: manhattan_accuracy
+        value: 80.92643051771117
+      - type: manhattan_ap
+        value: 92.47972548332238
+      - type: manhattan_f1
+        value: 86.88372093023257
+      - type: manhattan_precision
+        value: 81.71478565179353
+      - type: manhattan_recall
+        value: 92.75074478649454
+      - type: max_accuracy
+        value: 81.81198910081744
+      - type: max_ap
+        value: 92.92034333454589
+      - type: max_f1
+        value: 87.23307587460246
   - task:
       type: PairClassification
     dataset:
@@ -935,9 +935,9 @@ model-index:
       revision: 8a04d940a42cd40658986fdd8e3da561533a3646
     metrics:
     - type: cos_sim_accuracy
-      value: 60.75000000000001
+      value: 60.550000000000004
     - type: cos_sim_ap
-      value: 58.62577310571759
+      value: 58.1865824487652
     - type: cos_sim_f1
       value: 62.491349480968864
     - type: cos_sim_precision
@@ -945,19 +945,19 @@ model-index:
     - type: cos_sim_recall
       value: 100.0
     - type: dot_accuracy
-      value: 56.10000000000001
+      value: 56.49999999999999
     - type: dot_ap
-      value: 50.150973841607005
+      value: 49.511525626044474
     - type: dot_f1
-      value: 62.491349480968864
+      value: 62.76595744680852
     - type: dot_precision
-      value: 45.44539506794162
+      value: 46.165884194053206
     - type: dot_recall
-      value: 100.0
+      value: 98.00664451827242
     - type: euclidean_accuracy
-      value: 60.550000000000004
+      value: 60.199999999999996
     - type: euclidean_ap
-      value: 58.42883888530385
+      value: 58.003058708335246
     - type: euclidean_f1
       value: 62.491349480968864
     - type: euclidean_precision
@@ -965,9 +965,9 @@ model-index:
     - type: euclidean_recall
       value: 100.0
     - type: manhattan_accuracy
-      value: 60.5
+      value: 60.199999999999996
     - type: manhattan_ap
-      value: 58.474590272503214
+      value: 58.02420001567834
     - type: manhattan_f1
       value: 62.491349480968864
     - type: manhattan_precision
@@ -975,11 +975,11 @@ model-index:
     - type: manhattan_recall
       value: 100.0
     - type: max_accuracy
-      value: 60.75000000000001
+      value: 60.550000000000004
     - type: max_ap
-      value: 58.62577310571759
+      value: 58.1865824487652
     - type: max_f1
-      value: 62.491349480968864
+      value: 62.76595744680852
   - task:
       type: STS
     dataset:
@@ -990,17 +990,17 @@ model-index:
       revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
     metrics:
     - type: cos_sim_pearson
-      value: 80.76682266570421
+      value: 81.35988610550564
     - type: cos_sim_spearman
-      value: 72.87656590123949
+      value: 74.30702501405389
     - type: euclidean_pearson
-      value: 77.19658924853128
+      value: 77.98265846914386
     - type: euclidean_spearman
-      value: 72.63728770955521
+      value: 74.28309779423242
     - type: manhattan_pearson
-      value: 77.11028731757044
+      value: 77.91611618952486
     - type: manhattan_spearman
-      value: 72.4475625515528
+      value: 74.09543847416339
   - task:
       type: STS
     dataset:
@@ -1011,17 +1011,17 @@ model-index:
       revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
     metrics:
     - type: cos_sim_pearson
-      value: 81.47132547305752
+      value: 82.87930229178569
     - type: cos_sim_spearman
-      value: 82.57064642049959
+      value: 82.91122500126046
     - type: euclidean_pearson
-      value: 81.24198270906861
+      value: 82.30161381658885
     - type: euclidean_spearman
-      value: 82.43330741557487
+      value: 82.80157531184477
     - type: manhattan_pearson
-      value: 81.21813802112128
+      value: 82.59746592491155
     - type: manhattan_spearman
-      value: 82.54904875440255
+      value: 82.91620907805208
   - task:
       type: STS
     dataset:
@@ -1032,17 +1032,17 @@ model-index:
       revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
     metrics:
     - type: cos_sim_pearson
-      value: 83.17606773302035
+      value: 83.44206580073515
     - type: cos_sim_spearman
-      value: 82.51272412228484
+      value: 83.29855460437528
     - type: euclidean_pearson
-      value: 81.70010207800043
+      value: 82.28885833656986
     - type: euclidean_spearman
-      value: 81.89351174275659
+      value: 83.17545506016941
     - type: manhattan_pearson
-      value: 81.59549402980223
+      value: 82.16568250036501
     - type: manhattan_spearman
-      value: 81.8299015346327
+      value: 83.0743139221437
   - task:
       type: Summarization
     dataset:
@@ -1053,13 +1053,13 @@ model-index:
       revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
     metrics:
     - type: cos_sim_pearson
-      value: 30.739120683102207
+      value: 31.280485627024635
     - type: cos_sim_spearman
-      value: 31.550133032106963
+      value: 32.33005962500831
     - type: dot_pearson
-      value: 29.33458197921011
+      value: 30.158348138782753
     - type: dot_spearman
-      value: 30.784401437054438
+      value: 30.392045689426418
   - task:
       type: Reranking
     dataset:
@@ -1070,17 +1070,17 @@ model-index:
       revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
     metrics:
     - type: map
-      value: 82.50119047619047
+      value: 81.67777777777776
     - type: mrr
-      value: 82.50119047619047
+      value: 81.67777777777776
     - type: nAUC_map_diff1
-      value: 60.74442499288283
+      value: 59.89472485574524
     - type: nAUC_map_max
-      value: 10.220044072999142
+      value: 8.215249384307162
     - type: nAUC_mrr_diff1
-      value: 60.74442499288283
+      value: 59.89472485574524
     - type: nAUC_mrr_max
-      value: 10.220044072999142
+      value: 8.215249384307162
   - task:
       type: Retrieval
     dataset:
@@ -1093,115 +1093,115 @@ model-index:
     - type: map_at_1
       value: 62.0
     - type: map_at_10
-      value: 72.64
+      value: 72.887
     - type: map_at_100
-      value: 73.06
+      value: 73.181
     - type: map_at_1000
-      value: 73.06
+      value: 73.181
     - type: map_at_20
-      value: 72.952
+      value: 73.16
     - type: map_at_3
-      value: 70.333
+      value: 70.667
     - type: map_at_5
-      value: 71.68299999999999
+      value: 71.56700000000001
     - type: mrr_at_1
       value: 62.0
     - type: mrr_at_10
-      value: 72.63968253968254
+      value: 72.88690476190479
     - type: mrr_at_100
-      value: 73.06048581048583
+      value: 73.18055555555557
     - type: mrr_at_1000
-      value: 73.06048581048583
+      value: 73.18055555555557
     - type: mrr_at_20
-      value: 72.95202020202022
+      value: 73.15972222222224
     - type: mrr_at_3
-      value: 70.33333333333333
+      value: 70.66666666666667
     - type: mrr_at_5
-      value: 71.68333333333334
+      value: 71.56666666666666
     - type: nauc_map_at_1000_diff1
-      value: 50.08527740824938
+      value: 47.52352042312832
     - type: nauc_map_at_1000_max
-      value: 21.248476927494586
+      value: 12.229977029802052
     - type: nauc_map_at_100_diff1
-      value: 50.08527740824938
+      value: 47.52352042312832
     - type: nauc_map_at_100_max
-      value: 21.248476927494586
+      value: 12.229977029802052
     - type: nauc_map_at_10_diff1
-      value: 50.09694367886595
+      value: 47.83118981173179
     - type: nauc_map_at_10_max
-      value: 22.296393895985513
+      value: 12.67122414331949
     - type: nauc_map_at_1_diff1
-      value: 47.37101190659324
+      value: 48.29708026951358
     - type: nauc_map_at_1_max
-      value: 12.483463064947799
+      value: 5.016460019075176
     - type: nauc_map_at_20_diff1
-      value: 50.128296940080105
+      value: 47.5126416742559
     - type: nauc_map_at_20_max
-      value: 21.45784940740765
+      value: 12.23002184861472
     - type: nauc_map_at_3_diff1
-      value: 50.744726539402386
+      value: 48.18168651330906
     - type: nauc_map_at_3_max
-      value: 22.579560944336937
+      value: 14.063513453945578
     - type: nauc_map_at_5_diff1
-      value: 50.74065172911254
+      value: 46.8656518414084
     - type: nauc_map_at_5_max
-      value: 22.270361065268915
+      value: 13.22896127813873
     - type: nauc_mrr_at_1000_diff1
-      value: 50.08527740824938
+      value: 47.52352042312832
     - type: nauc_mrr_at_1000_max
-      value: 21.248476927494586
+      value: 12.229977029802052
     - type: nauc_mrr_at_100_diff1
-      value: 50.08527740824938
+      value: 47.52352042312832
     - type: nauc_mrr_at_100_max
-      value: 21.248476927494586
+      value: 12.229977029802052
     - type: nauc_mrr_at_10_diff1
-      value: 50.09694367886595
+      value: 47.83118981173179
     - type: nauc_mrr_at_10_max
-      value: 22.296393895985513
+      value: 12.67122414331949
     - type: nauc_mrr_at_1_diff1
-      value: 47.37101190659324
+      value: 48.29708026951358
     - type: nauc_mrr_at_1_max
-      value: 12.483463064947799
+      value: 5.016460019075176
     - type: nauc_mrr_at_20_diff1
-      value: 50.128296940080105
+      value: 47.5126416742559
     - type: nauc_mrr_at_20_max
-      value: 21.45784940740765
+      value: 12.23002184861472
     - type: nauc_mrr_at_3_diff1
-      value: 50.744726539402386
+      value: 48.18168651330906
     - type: nauc_mrr_at_3_max
-      value: 22.579560944336937
+      value: 14.063513453945578
     - type: nauc_mrr_at_5_diff1
-      value: 50.74065172911254
+      value: 46.8656518414084
     - type: nauc_mrr_at_5_max
-      value: 22.270361065268915
+      value: 13.22896127813873
     - type: nauc_ndcg_at_1000_diff1
-      value: 50.189203918396
+      value: 47.56455972451391
     - type: nauc_ndcg_at_1000_max
-      value: 22.390609940816248
+      value: 12.900901768894494
     - type: nauc_ndcg_at_100_diff1
-      value: 50.189203918396
+      value: 47.56455972451391
     - type: nauc_ndcg_at_100_max
-      value: 22.390609940816248
+      value: 12.900901768894494
     - type: nauc_ndcg_at_10_diff1
-      value: 50.18969760392006
+      value: 48.92225620164975
     - type: nauc_ndcg_at_10_max
-      value: 26.941106150664424
+      value: 14.848602834576374
     - type: nauc_ndcg_at_1_diff1
-      value: 47.37101190659324
+      value: 48.29708026951358
     - type: nauc_ndcg_at_1_max
-      value: 12.483463064947799
+      value: 5.016460019075176
     - type: nauc_ndcg_at_20_diff1
-      value: 50.21215501702988
+      value: 47.44500349427683
     - type: nauc_ndcg_at_20_max
-      value: 23.708162881601485
+      value: 12.894569953616672
     - type: nauc_ndcg_at_3_diff1
-      value: 51.624830876343665
+      value: 48.79515966817958
     - type: nauc_ndcg_at_3_max
-      value: 26.399573078561655
+      value: 17.067858878871014
     - type: nauc_ndcg_at_5_diff1
-      value: 51.69995630080373
+      value: 46.2582129725611
     - type: nauc_ndcg_at_5_max
-      value: 26.096565329394988
+      value: 15.802131944100553
     - type: nauc_precision_at_1000_diff1
       value: nan
     - type: nauc_precision_at_1000_max
@@ -1211,25 +1211,25 @@ model-index:
     - type: nauc_precision_at_100_max
       value: nan
     - type: nauc_precision_at_10_diff1
-      value: 49.35974389755923
+      value: 67.1335200746968
     - type: nauc_precision_at_10_max
-      value: 72.25556889422438
+      value: 41.521942110178045
     - type: nauc_precision_at_1_diff1
-      value: 47.37101190659324
+      value: 48.29708026951358
     - type: nauc_precision_at_1_max
-      value: 12.483463064947799
+      value: 5.016460019075176
     - type: nauc_precision_at_20_diff1
-      value: 47.3389355742298
+      value: 35.80765639589114
     - type: nauc_precision_at_20_max
-      value: 59.38375350140046
+      value: 12.278244631185926
     - type: nauc_precision_at_3_diff1
-      value: 54.820179820179774
+      value: 51.516580229451506
     - type: nauc_precision_at_3_max
-      value: 41.00399600399594
+      value: 28.765257478128753
     - type: nauc_precision_at_5_diff1
-      value: 56.32880698351117
+      value: 43.146762121705116
     - type: nauc_precision_at_5_max
-      value: 45.28543716225577
+      value: 27.715587373901627
     - type: nauc_recall_at_1000_diff1
       value: nan
     - type: nauc_recall_at_1000_max
@@ -1239,67 +1239,67 @@ model-index:
     - type: nauc_recall_at_100_max
       value: nan
     - type: nauc_recall_at_10_diff1
-      value: 49.35974389755904
+      value: 67.13352007469638
     - type: nauc_recall_at_10_max
-      value: 72.25556889422437
+      value: 41.52194211017754
     - type: nauc_recall_at_1_diff1
-      value: 47.37101190659324
+      value: 48.29708026951358
     - type: nauc_recall_at_1_max
-      value: 12.483463064947799
+      value: 5.016460019075176
     - type: nauc_recall_at_20_diff1
-      value: 47.33893557422995
+      value: 35.80765639589109
     - type: nauc_recall_at_20_max
-      value: 59.38375350140056
+      value: 12.278244631185359
     - type: nauc_recall_at_3_diff1
-      value: 54.820179820179774
+      value: 51.516580229451556
     - type: nauc_recall_at_3_max
-      value: 41.003996003995894
+      value: 28.765257478128735
     - type: nauc_recall_at_5_diff1
-      value: 56.32880698351108
+      value: 43.14676212170519
     - type: nauc_recall_at_5_max
-      value: 45.28543716225559
+      value: 27.7155873739018
     - type: ndcg_at_1
       value: 62.0
     - type: ndcg_at_10
-      value: 77.574
+      value: 78.188
     - type: ndcg_at_100
-      value: 79.245
+      value: 79.372
     - type: ndcg_at_1000
-      value: 79.245
+      value: 79.372
     - type: ndcg_at_20
-      value: 78.629
+      value: 79.194
     - type: ndcg_at_3
-      value: 72.833
+      value: 73.333
     - type: ndcg_at_5
-      value: 75.286
+      value: 74.968
     - type: precision_at_1
       value: 62.0
     - type: precision_at_10
-      value: 9.3
+      value: 9.5
     - type: precision_at_100
       value: 1.0
     - type: precision_at_1000
       value: 0.1
     - type: precision_at_20
-      value: 4.8500000000000005
+      value: 4.95
     - type: precision_at_3
-      value: 26.667
+      value: 27.0
     - type: precision_at_5
-      value: 17.2
+      value: 17.0
     - type: recall_at_1
       value: 62.0
     - type: recall_at_10
-      value: 93.0
+      value: 95.0
     - type: recall_at_100
       value: 100.0
     - type: recall_at_1000
       value: 100.0
     - type: recall_at_20
-      value: 97.0
+      value: 99.0
     - type: recall_at_3
-      value: 80.0
+      value: 81.0
     - type: recall_at_5
-      value: 86.0
+      value: 85.0
   - task:
       type: Retrieval
     dataset:
@@ -1310,215 +1310,215 @@ model-index:
       revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
     metrics:
     - type: map_at_1
-      value: 36.974000000000004
+      value: 36.611
     - type: map_at_10
-      value: 56.879000000000005
+      value: 57.187
     - type: map_at_100
-      value: 58.288
+      value: 58.631
     - type: map_at_1000
-      value: 58.375
+      value: 58.709999999999994
     - type: map_at_20
-      value: 57.737
+      value: 58.08
     - type: map_at_3
-      value: 51.162
+      value: 50.998
     - type: map_at_5
-      value: 54.752
+      value: 55.191
     - type: mrr_at_1
-      value: 57.943925233644855
+      value: 57.810413885180246
     - type: mrr_at_10
-      value: 65.70882870282065
+      value: 65.8401148621442
     - type: mrr_at_100
-      value: 66.28374236332951
+      value: 66.40333125160906
     - type: mrr_at_1000
-      value: 66.30262698230914
+      value: 66.42402394693958
     - type: mrr_at_20
-      value: 66.0551354222895
+      value: 66.18532893351842
     - type: mrr_at_3
-      value: 63.773920783266526
+      value: 63.81842456608808
     - type: mrr_at_5
-      value: 64.85536270582992
+      value: 65.18691588785039
     - type: nauc_map_at_1000_diff1
-      value: 47.687404840174466
+      value: 50.788831583223235
     - type: nauc_map_at_1000_max
-      value: 51.07479500215987
+      value: 51.55624948390649
     - type: nauc_map_at_100_diff1
-      value: 47.654118256249376
+      value: 50.7629709789859
     - type: nauc_map_at_100_max
-      value: 51.07088520770559
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   - task:
       type: Classification
     dataset:
@@ -8108,7 +8108,7 @@ language:
 
 # [bilingual-embedding-small](https://huggingface.co/Lajavaness/bilingual-embedding-small)
 
-Bilingual-embedding is the Embedding Model for bilingual language: french and english. This model is a specialized sentence-embedding trained specifically for the bilingual language, leveraging the robust capabilities of [XLM-RoBERTa](https://huggingface.co/intfloat/multilingual-e5-small), a pre-trained language model based on the [XLM-RoBERTa](https://huggingface.co/intfloat/multilingual-e5-small) architecture. The model utilizes xlm-roberta to encode english-french sentences into a 1024-dimensional vector space, facilitating a wide range of applications from semantic search to text clustering. The embeddings capture the nuanced meanings of english-french sentences, reflecting both the lexical and contextual layers of the language.
+Bilingual-embedding is the Embedding Model for bilingual language: french and english. This model is a specialized sentence-embedding trained specifically for the bilingual language, leveraging the robust capabilities of [Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384), a pre-trained language model  is built upon [multilingual-e5](https://huggingface.co/intfloat/multilingual-e5-small) architecture. The model utilizes MiniLM to encode english-french sentences into a 1024-dimensional vector space, facilitating a wide range of applications from semantic search to text clustering. The embeddings capture the nuanced meanings of english-french sentences, reflecting both the lexical and contextual layers of the language.
 
 
 ## Full Model Architecture