Label Encoder encoding the same class as two integers
The correct way of using sklearn's LabelEncoder is the following:

from sklearn.preprocessing import LabelEncoder
import random

keys = [
    '8861892541fffff', '886189254dfffff', '8861892543fffff', '8861892547fffff', 
    '8861892545fffff', '8861892569fffff', '8861892727fffff', '886189255dfffff', 
    '8861893597fffff', '8861892555fffff', '886189209bfffff', '8861892549fffff'
]

data = [random.choice(keys) for _ in range(100)]

le = LabelEncoder().fit(data)

print(le.classes_)
# ['886189209bfffff' '8861892541fffff' '8861892543fffff' '8861892545fffff'
#  '8861892547fffff' '8861892549fffff' '886189254dfffff' '8861892555fffff'
#  '886189255dfffff' '8861892569fffff' '8861892727fffff' '8861893597fffff']

print(le.transform(['8861892727fffff']))
# [10]

print(le.inverse_transform([10]))
# ['8861892727fffff']