Update README.md

README.md

@@ -7,7 +7,7 @@ base_model:
 - Qwen/Qwen2.5-7B-Instruct
 ---
 
-## Introduction
+# Introduction
 
 According to the August 2025 jobs report, overall unemployment has risen, with the unemployment rate for workers aged 16-24 rising to 10.5% (Bureau of Labor Statistics, 2025). The primary demographic 
 of this age range is recent college graduates, many of whom carry student loan debt and are unable to find stable, long-term employment. While this could be 
@@ -24,7 +24,7 @@ After finetuning, the LLM performed with a 21.578 in the SQuADv2 benchmark, a
 0.597 in the humaneval benchmark, a 5.040 bleu score in the E2E NLG Challenge benchmark, and a bert score mean precision of 0.813, mean recall of 0.848, and mean f1 of 0.830
 on a train/test split. The bert scores specifically indicate that my model has a strong alignment between generated and expected responses.
 
-## Data
+# Data
 
 I was able to find a training dataset of job postings on Kaggle (Arshkon, 2023), under a project labeled ‘LinkedIn Job Postings 2023 Data Analysis’. 
 The dataset used has ~15,000 jobs from LinkedIn. It includes the company, job title, and a description that includes necessary skills.