fix pair cls bug

README.md

@@ -1,8 +1,8 @@
 ---
 tags:
-- mteb
+- my_mteb
 model-index:
-- name: xlm3b5
+- name: xlm3b5_step3len260_b128g8_lr1e-5
   results:
   - task:
       type: Classification
@@ -182,9 +182,9 @@ model-index:
       revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
     metrics:
     - type: accuracy
-      value: 1.4123376623376624
+      value: 1.422077922077922
     - type: f1
-      value: 0.06543826204021423
+      value: 0.06502366027548179
   - task:
       type: Clustering
     dataset:
@@ -1556,9 +1556,9 @@ model-index:
       revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
     metrics:
     - type: accuracy
-      value: 20.503875968992244
+      value: 36.3657090743274
     - type: f1
-      value: 13.560556256747041
+      value: 27.22838800222161
   - task:
       type: Classification
     dataset:
@@ -1569,9 +1569,9 @@ model-index:
       revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
     metrics:
     - type: accuracy
-      value: 1.5868673050615598
+      value: 1.0168718650250799
     - type: f1
-      value: 0.07893368834661864
+      value: 0.0674636098084213
   - task:
       type: Classification
     dataset:
@@ -1582,9 +1582,9 @@ model-index:
       revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
     metrics:
     - type: accuracy
-      value: 1.815736381977135
+      value: 1.8829858776059176
     - type: f1
-      value: 0.07389251629624266
+      value: 0.08021151737444676
   - task:
       type: Classification
     dataset:
@@ -1595,9 +1595,9 @@ model-index:
       revision: 7d571f92784cd94a019292a1f45445077d0ef634
     metrics:
     - type: accuracy
-      value: 7.89172831203766
+      value: 8.681909885675857
     - type: f1
-      value: 0.8047482245600247
+      value: 2.752826896423761
   - task:
       type: Clustering
     dataset:
@@ -2212,51 +2212,51 @@ model-index:
       revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
     metrics:
     - type: cos_sim_accuracy
-      value: 99.01089108910891
+      value: 99.56336633663366
     - type: cos_sim_ap
-      value: 1.3258822225796068
+      value: 86.13024319858586
     - type: cos_sim_f1
-      value: 2.981148619026743
+      value: 76.80157946692991
     - type: cos_sim_precision
-      value: 2.6541764246682282
+      value: 75.82846003898635
     - type: cos_sim_recall
-      value: 3.4000000000000004
+      value: 77.8
     - type: dot_accuracy
-      value: 99.0089108910891
+      value: 99.56336633663366
     - type: dot_ap
-      value: 1.3780579724370194
+      value: 86.13028343072267
     - type: dot_f1
-      value: 2.9675425038639873
+      value: 76.80157946692991
     - type: dot_precision
-      value: 2.1476510067114094
+      value: 75.82846003898635
     - type: dot_recall
-      value: 4.8
+      value: 77.8
     - type: euclidean_accuracy
-      value: 99.01089108910891
+      value: 99.56336633663366
     - type: euclidean_ap
-      value: 1.3226816682194076
+      value: 86.13029040641543
     - type: euclidean_f1
-      value: 2.9817780231916067
+      value: 76.80157946692991
     - type: euclidean_precision
-      value: 2.059496567505721
+      value: 75.82846003898635
     - type: euclidean_recall
-      value: 5.4
+      value: 77.8
     - type: manhattan_accuracy
-      value: 99.01089108910891
+      value: 99.56534653465347
     - type: manhattan_ap
-      value: 1.3257832418895792
+      value: 86.24817068330776
     - type: manhattan_f1
-      value: 3.0476190476190474
+      value: 77.13580246913581
     - type: manhattan_precision
-      value: 2.909090909090909
+      value: 76.19512195121952
     - type: manhattan_recall
-      value: 3.2
+      value: 78.10000000000001
     - type: max_accuracy
-      value: 99.01089108910891
+      value: 99.56534653465347
     - type: max_ap
-      value: 1.3780579724370194
+      value: 86.24817068330776
     - type: max_f1
-      value: 3.0476190476190474
+      value: 77.13580246913581
   - task:
       type: Clustering
     dataset:
@@ -2496,51 +2496,51 @@ model-index:
       revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
     metrics:
     - type: cos_sim_accuracy
-      value: 77.63008881206413
+      value: 84.13899982118377
     - type: cos_sim_ap
-      value: 23.98771112381251
+      value: 68.03329474978145
     - type: cos_sim_f1
-      value: 36.874665107896156
+      value: 63.31192005710206
     - type: cos_sim_precision
-      value: 22.61186450803513
+      value: 57.6473136915078
     - type: cos_sim_recall
-      value: 99.86807387862797
+      value: 70.21108179419525
     - type: dot_accuracy
-      value: 77.624128270847
+      value: 84.13899982118377
     - type: dot_ap
-      value: 23.81883137521807
+      value: 68.03324775052695
     - type: dot_f1
-      value: 36.86411827643225
+      value: 63.31192005710206
     - type: dot_precision
-      value: 22.59718578583353
+      value: 57.6473136915078
     - type: dot_recall
-      value: 100.0
+      value: 70.21108179419525
     - type: euclidean_accuracy
-      value: 77.63008881206413
+      value: 84.13899982118377
     - type: euclidean_ap
-      value: 24.056639112615873
+      value: 68.03331114508686
     - type: euclidean_f1
-      value: 36.8782579042237
+      value: 63.31192005710206
     - type: euclidean_precision
-      value: 22.61456652924658
+      value: 57.6473136915078
     - type: euclidean_recall
-      value: 99.86807387862797
+      value: 70.21108179419525
     - type: manhattan_accuracy
-      value: 77.63604935328128
+      value: 84.12111819753234
     - type: manhattan_ap
-      value: 24.040167793537755
+      value: 67.97378509663328
     - type: manhattan_f1
-      value: 36.86514886164623
+      value: 63.38468945594607
     - type: manhattan_precision
-      value: 22.59930812358344
+      value: 58.2779991146525
     - type: manhattan_recall
-      value: 99.9736147757256
+      value: 69.47229551451187
     - type: max_accuracy
-      value: 77.63604935328128
+      value: 84.13899982118377
     - type: max_ap
-      value: 24.056639112615873
+      value: 68.03331114508686
     - type: max_f1
-      value: 36.8782579042237
+      value: 63.38468945594607
   - task:
       type: PairClassification
     dataset:
@@ -2551,49 +2551,49 @@ model-index:
       revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
     metrics:
     - type: cos_sim_accuracy
-      value: 75.04366049598323
+      value: 87.68774013272791
     - type: cos_sim_ap
-      value: 26.157700936768393
+      value: 83.51733662214374
     - type: cos_sim_f1
-      value: 40.26479388555571
+      value: 75.82190771045259
     - type: cos_sim_precision
-      value: 25.20819178879938
+      value: 72.72341628959276
     - type: cos_sim_recall
-      value: 99.98460117031107
+      value: 79.19618109023713
     - type: dot_accuracy
-      value: 75.01843443163737
+      value: 87.68774013272791
     - type: dot_ap
-      value: 26.007081173722646
+      value: 83.5173527754126
     - type: dot_f1
-      value: 40.267311687908965
+      value: 75.82190771045259
     - type: dot_precision
-      value: 25.210655069312317
+      value: 72.72341628959276
     - type: dot_recall
-      value: 99.97690175546659
+      value: 79.19618109023713
     - type: euclidean_accuracy
-      value: 75.04366049598323
+      value: 87.68774013272791
     - type: euclidean_ap
-      value: 26.208660893446407
+      value: 83.51734651146224
     - type: euclidean_f1
-      value: 40.264773361443545
+      value: 75.82190771045259
     - type: euclidean_precision
-      value: 25.20768633540373
+      value: 72.72341628959276
     - type: euclidean_recall
-      value: 99.99230058515552
+      value: 79.19618109023713
     - type: manhattan_accuracy
-      value: 75.04754142895952
+      value: 87.67221640082276
     - type: manhattan_ap
-      value: 26.202762141501218
+      value: 83.51179463759505
     - type: manhattan_f1
-      value: 40.262358121937595
+      value: 75.76243980738361
     - type: manhattan_precision
-      value: 25.20775085430258
+      value: 71.99112590127565
     - type: manhattan_recall
-      value: 99.96150292577765
+      value: 79.95072374499537
     - type: max_accuracy
-      value: 75.04754142895952
+      value: 87.68774013272791
     - type: max_ap
-      value: 26.208660893446407
+      value: 83.5173527754126
     - type: max_f1
-      value: 40.267311687908965
----
+      value: 75.82190771045259
+---