finishes classification scripts

ClassificationTopic.py

@@ -1,12 +1,9 @@
-import re
-import string
 import numpy as np
 import pandas as pd
 from datetime import datetime
 from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 from datasets import load_dataset
 from transformers.pipelines.pt_utils import KeyDataset
-from funs.CleanTweets import remove_URL, remove_emoji, remove_html, remove_punct
 
 
 #%%
@@ -99,8 +96,8 @@ for out in pipe(KeyDataset(dataset['train'], "cleanContent"), batch_size=8, trun
     # Exactly the same output as before, but the content are passed
     # as batches to the model
 # %%
-dfClassify['output_label'] = output_labels
-dfClassify['output_score'] = output_score
+dfClassify['output_label_topicCov'] = output_labels
+dfClassify['output_score_topicCov'] = output_score
 
 timeEnd = datetime.now()
 timeTotal = timeEnd - timeStart