Update README.md

README.md

@@ -61,14 +61,9 @@ Optimal Answer: I developed a predictive model using Python and scikit-learn to
 After creating this dataset, I uploaded it to my project notebook. Then, I modified the dataset to reformat it and make it easier to train. I created an 'Instruct' column with each row's job title,
 description, applicant profile, and the prompt 'Generate a relevant interview question and 
 provide an optimal answer using the information from this applicant's profile. Interview Question and Optimal Answer:'.  Then I combined the interview question/ optimal answer 
-into one column labeled 'Answer'. 
-
-I established a training, validation, and testing split using scikit-learn's train_test_split function and pandas .sample() method for shuffling. The proportions are as follows:
-
-Training: 3,200 examples (64% of total)
-Validation: 800 examples (16% of total)
-Testing: 1,000 examples (20% of total)
-Random seed: 42
+into one column labeled 'Answer'. Finally, I established a training, validation, and testing split using scikit-learn's train_test_split function and pandas .sample() 
+method for shuffling. The proportions are as follows: Training: 3,200 examples (64% of total), Validation: 800 examples (16% of total), Testing: 1,000 examples (20% of total), 
+with Random seed: 42.
 
 
 ## Methodology