Update README.md

README.md

@@ -1845,47 +1845,47 @@ model-index:
     - type: cos_sim_accuracy
       value: 99.89816700610999
     - type: cos_sim_ap
-      value: 100
+      value: 100.0
     - type: cos_sim_f1
       value: 99.9490575649516
     - type: cos_sim_precision
-      value: 100
+      value: 100.0
     - type: cos_sim_recall
       value: 99.89816700610999
     - type: dot_accuracy
       value: 99.89816700610999
     - type: dot_ap
-      value: 100
+      value: 100.0
     - type: dot_f1
       value: 99.9490575649516
     - type: dot_precision
-      value: 100
+      value: 100.0
     - type: dot_recall
       value: 99.89816700610999
     - type: euclidean_accuracy
       value: 99.89816700610999
     - type: euclidean_ap
-      value: 100
+      value: 100.0
     - type: euclidean_f1
       value: 99.9490575649516
     - type: euclidean_precision
-      value: 100
+      value: 100.0
     - type: euclidean_recall
       value: 99.89816700610999
     - type: manhattan_accuracy
       value: 99.89816700610999
     - type: manhattan_ap
-      value: 100
+      value: 100.0
     - type: manhattan_f1
       value: 99.9490575649516
     - type: manhattan_precision
-      value: 100
+      value: 100.0
     - type: manhattan_recall
       value: 99.89816700610999
     - type: max_accuracy
       value: 99.89816700610999
     - type: max_ap
-      value: 100
+      value: 100.0
     - type: max_f1
       value: 99.9490575649516
   - task:
@@ -1906,7 +1906,7 @@ model-index:
     - type: cos_sim_precision
       value: 45.46365914786967
     - type: cos_sim_recall
-      value: 100
+      value: 100.0
     - type: dot_accuracy
       value: 61.75000000000001
     - type: dot_ap
@@ -1916,7 +1916,7 @@ model-index:
     - type: dot_precision
       value: 45.46365914786967
     - type: dot_recall
-      value: 100
+      value: 100.0
     - type: euclidean_accuracy
       value: 61.75000000000001
     - type: euclidean_ap
@@ -1926,7 +1926,7 @@ model-index:
     - type: euclidean_precision
       value: 45.46365914786967
     - type: euclidean_recall
-      value: 100
+      value: 100.0
     - type: manhattan_accuracy
       value: 61.75000000000001
     - type: manhattan_ap
@@ -1936,7 +1936,7 @@ model-index:
     - type: manhattan_precision
       value: 45.46365914786967
     - type: manhattan_recall
-      value: 100
+      value: 100.0
     - type: max_accuracy
       value: 61.75000000000001
     - type: max_ap
@@ -2348,7 +2348,7 @@ model-index:
     - type: map_at_5
       value: 64.354
     - type: mrr_at_1
-      value: 59
+      value: 59.0
     - type: mrr_at_10
       value: 66.74900000000001
     - type: mrr_at_100
@@ -2360,7 +2360,7 @@ model-index:
     - type: mrr_at_5
       value: 65.956
     - type: ndcg_at_1
-      value: 59
+      value: 59.0
     - type: ndcg_at_10
       value: 69.95599999999999
     - type: ndcg_at_100
@@ -2372,7 +2372,7 @@ model-index:
     - type: ndcg_at_5
       value: 67.633
     - type: precision_at_1
-      value: 59
+      value: 59.0
     - type: precision_at_10
       value: 9.333
     - type: precision_at_100
@@ -2380,7 +2380,7 @@ model-index:
     - type: precision_at_1000
       value: 0.11199999999999999
     - type: precision_at_3
-      value: 26
+      value: 26.0
     - type: precision_at_5
       value: 16.866999999999997
     - type: recall_at_1
@@ -2390,7 +2390,7 @@ model-index:
     - type: recall_at_100
       value: 92.767
     - type: recall_at_1000
-      value: 99
+      value: 99.0
     - type: recall_at_3
       value: 70.95
     - type: recall_at_5
@@ -2524,7 +2524,7 @@ model-index:
     - type: map_at_5
       value: 1.11
     - type: mrr_at_1
-      value: 96
+      value: 96.0
     - type: mrr_at_10
       value: 97.167
     - type: mrr_at_100
@@ -2536,7 +2536,7 @@ model-index:
     - type: mrr_at_5
       value: 97.167
     - type: ndcg_at_1
-      value: 91
+      value: 91.0
     - type: ndcg_at_10
       value: 81.69800000000001
     - type: ndcg_at_100
@@ -2548,9 +2548,9 @@ model-index:
     - type: ndcg_at_5
       value: 84.286
     - type: precision_at_1
-      value: 96
+      value: 96.0
     - type: precision_at_10
-      value: 87
+      value: 87.0
     - type: precision_at_100
       value: 64.86
     - type: precision_at_1000