Extend list of accepted values for positive matches.
Change data_processing.py (see in particular lines 37-43, but you may have to do other changes in subsequent lines) so it also accepts, positive, negative, correct, and wrong:
for i in range(len(df_list)):
tmp_split_row = df_list[i].split(csv_sep)
if str(tmp_split_row[2]).strip().lower() not in ["true", "false", "1", "0"]:
print(f"SKIP: {df_list[i]}")
# change the label to remove_me,
# we drop the rows with no true|false in the label column
tmp_split_row = f"X{csv_sep}X{csv_sep}remove_me".split(csv_sep)
Extend list of accepted values for positive matches.
Change
data_processing.py(see in particular lines 37-43, but you may have to do other changes in subsequent lines) so it also accepts,positive,negative,correct, andwrong: