Identify Labels wrt categories after label encoding

Question

I have label encoded a part of my data. Now I want to identify what label was given to which category.

below mentioned is the Label encoder code and its fit and transform on dataframe df creating df1.

from sklearn.preprocessing import LabelEncoder
from sklearn.pipeline import Pipeline

class MultiColumnLabelEncoder:
    def __init__(self,columns = None):
        self.columns = columns # array of column names to encode

    def fit(self,X,y=None):
        return self # not relevant here

    def transform(self,X):
        '''
        Transforms columns of X specified in self.columns using
        LabelEncoder(). If no columns specified, transforms all
        columns in X.
        '''
        output = X.copy()
        if self.columns is not None:
            for col in self.columns:
                output[col] = LabelEncoder().fit_transform(output[col])
        else:
            for colname,col in output.iteritems():
                output[colname] = LabelEncoder().fit_transform(col)
        return output

    def fit_transform(self,X,y=None):
        return self.fit(X,y).transform(X)

df1 = MultiColumnLabelEncoder(columns = ['EntryTerm','DEPENDENCYCODE']).fit_transform(df)

Here EntryTerm has two categories and DEPENDENCYCODE has multiple categories.

I want to identify if EntryTerm = 082021 was assigned 0 or 1 as label. And if DEPENCENCYCODE = 'B' was assigned 0, 1, 2 ,3 or 4 label.

Thanks.