Make sure eval subset is sampled without replacing (#3651)

Explicitly specify `replace=False` for
[numpy.random.choice](https://numpy.org/doc/stable/reference/random/generated/numpy.random.choice.html)
(it was missing and default is `replace=True` which could lead to
duplicate examples in the evaluation set).

model/model_training/custom_datasets/__init__.py

@@ -196,7 +196,7 @@ def get_one_dataset(
         train, eval = train_val_dataset(dataset, val_split=val_split)
 
     if eval and max_val_set and len(eval) > max_val_set:
-        subset_indices = np.random.choice(len(eval), max_val_set)
+        subset_indices = np.random.choice(len(eval), size=max_val_set, replace=False)
         eval = Subset(eval, subset_indices)
 
     return train, eval