Update README.md

README.md

@@ -10,7 +10,7 @@ pinned: false
 license: apache-2.0
 short_description: Gradio
 ---
-GPT-2 Fine-Tuned TinyStories Project
+GPT-2 TinyStories Generator 🏢 - FableWeaver AI
 
 Overview
 
@@ -18,19 +18,19 @@ This project fine-tunes a GPT-2 model on the TinyStories dataset to generate str
 
 Features
 
-Story Generation: Produces coherent, child-friendly short stories.
+✅ Story Generation: Produces structured, child-friendly short stories.
 
-Bias Monitoring: Ensures balanced gender and cultural representation.
+✅ Bias Monitoring: Ensures balanced gender and cultural representation.
 
-Efficient Training: Fine-tuned on 200,000 training samples and 20,000 test samples.
+✅ Efficient Training: Fine-tuned on 200,000 training samples and 20,000 test samples.
 
-Grammar & Readability Improvements: Integrated grammar-checking tools and text refinement.
+✅ Grammar & Readability Enhancements: Integrated grammar-checking tools and text refinement.
 
-Optimized Model Performance: Uses loss tracking, sampling techniques, and bias mitigation strategies.
+✅ Optimized Performance: Uses loss tracking, sampling techniques, and bias mitigation strategies.
 
-System Architecture
+🚀 System Architecture
 
-The model is designed for easy interaction via Hugging Face Spaces and follows this pipeline:
+The model is designed for easy interaction via Hugging Face Spaces and follows this workflow:
 
 Data Preprocessing & Cleaning
 
@@ -60,7 +60,7 @@ Tracked using Weights & Biases (W&B) and TensorBoard.
 
 Analyzed validation loss and coherence checks.
 
-Getting Started
+🔹 Getting Started
 
 Accessing the Model
 
@@ -76,7 +76,7 @@ Click Generate to receive an AI-generated short story.
 
 Modify the prompt and settings (temperature, top-k, top-p) for different results.
 
-Training Details
+📊 Training Details
 
 Model: GPT-2 (124M)
 
@@ -90,7 +90,7 @@ Training Loss: 3.08 → 2.86
 
 Validation Loss: 1.46 → 1.40
 
-Evaluation & Observations
+📝 Evaluation & Observations
 
 Perplexity improved from 8.12 → 2.09, indicating better text fluency.
 
@@ -98,7 +98,7 @@ Validation loss decreased consistently, suggesting effective generalization.
 
 Human evaluation highlighted minor inconsistencies, such as abrupt scene shifts and simplistic narratives.
 
-Ethical Considerations
+⚖️ Ethical Considerations
 
 Bias Monitoring: Pronoun analysis and diversity checks to ensure fairness.
 
@@ -106,7 +106,7 @@ Harmful Content Mitigation: Manually reviewed outputs for stereotypes.
 
 Text Processing Issues: UTF-8 encoding applied to prevent character errors.
 
-Future Improvements
+🔮 Future Improvements
 
 Enhancing Creativity: Fine-tune temperature and randomness settings.
 
@@ -114,17 +114,17 @@ Genre-Specific Training: Introduce theme-based datasets.
 
 Larger Model Training: Experiment with GPT-2 (355M) for richer storytelling.
 
-Contributors
+🤝 Contributors
 
 Charla Pia Vella (Project Developer)
 
 Affiliation: ARI3333 Generative AI
 
-License
+📜 License
 
 This project is released under the Apache-2.0 License.
 
-Acknowledgments
+🎓 Acknowledgments
 
 OpenAI for GPT-2
 
@@ -132,7 +132,9 @@ Hugging Face for the fine-tuning framework
 
 Ronen Eldan for the TinyStories dataset
 
-For more details, visit the Hugging Face Space.
+📌 For more details, visit the Hugging Face Space.
+
+
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference