Update README.md

README.md

@@ -10,4 +10,4 @@ This repository contains a fine-tuned version of the `distilbert-base-uncased` m
 The fine-tuned model utilizes the `distilbert-base-uncased` architecture, trained on a dataset of GPT-3.5-generated tweets. It is designed to input a sentence and output a binary sentiment label, `0` for positive and `1` for negative.
 
 ## Training Data
-The model was trained on a dataset consisting of tweets generated and labeled with sentiments by GPT-3.5. Each tweet in the training set was manually labeled as either positive or negative to provide ground truth for training.
+The model was trained on a dataset consisting of tweets generated and labeled with sentiments by GPT-3.5. Each tweet in the training set was labeled as either positive or negative to provide ground truth for training.