Reduced permutations from 2 copies to 1 copy of training data to reduce training time

src/training/prep_finetuning.py

@@ -59,7 +59,7 @@ class CategoryDataGenerator(TrainingDataGenerator):
         for c in Category.all.values():
             prod_names = [p.name for p in c.products]
             total_prod_count = len(prod_names)
-            for _ in range(2):
+            for _ in range(1):
                 working_prod_names = copy(prod_names)
                 shuffle(working_prod_names)
                 while len(working_prod_names) > 0:
@@ -125,7 +125,7 @@ class FeatureDataGenerator(TrainingDataGenerator):
         # 1. First generate Q&A for what features are available by category
         for c in Category.all.values():
             cat_features = [f.name for f in c.features]
-            for _ in range(2):
+            for _ in range(1):
                 working_cat_features = copy(cat_features)
                 shuffle(working_cat_features)
                 while len(working_cat_features) > 0:
@@ -153,7 +153,7 @@ class FeatureDataGenerator(TrainingDataGenerator):
             cat_name = f.category.name
             prod_names = [p.name for p in f.products]
 
-            for _ in range(2):
+            for _ in range(1):
                 working_prod_names = copy(prod_names)
                 while len(working_prod_names) > 0:
                     some_prods = pop_n(working_prod_names, 3)