Update README.md

README.md

@@ -6,7 +6,7 @@ datasets:
 
 # TinyAestheticNet
 
-## DATA
+## Data
 
 To measure creativity in paintings, this study utilizes a dataset consisting of 878 open-access modern art paintings. Each artwork was rigorously evaluated by 3 fine arts experts specializing in painting. The experts reached a consensus to score the artworks on a scale of 1 to 10 across 5 distinct criteria:
 * **K1:** Originality
@@ -17,7 +17,7 @@ To measure creativity in paintings, this study utilizes a dataset consisting of
 
 The dataset features a well-balanced distribution, with an almost equal representation of scores across the 1 to 10 scale for each criterion.
 
-## MODEL
+## Model
 
 ```bash
 pip install torch torchvision git+https://github.com/openai/CLIP.git huggingface_hub
@@ -75,10 +75,10 @@ for c, s in zip(criteria, scores):
     print(f"{c}: {s:.2f}/10")
 ```
 
-## PERFORMANCE
+## Performance
 
 ![Performance](TinyAestheticNet_performance.png)
 
-## EXPLAINABILITY
+## Explainability
 
 ![XAI](TinyAestheticNet_xai.png)