Update README.md (#3)

- Update README.md (85d21351fff32955baf875ea0f753e1c6f83bdbb)


Co-authored-by: Miriam Shem <MiriamShem@users.noreply.huggingface.co>

README.md

@@ -25,7 +25,7 @@ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.
 
 ## Key Improvements Over Base Model
 
-### 🎯 Domain Specialization
+###  Domain Specialization
 - **Base Model**: Generic text-to-text transformer trained on diverse internet content
 - **Fine-tuned Model**: Specialized for child helpline case summarization with understanding of:
   - Child protection terminology and concepts
@@ -33,7 +33,7 @@ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.
   - Sensitive case reporting protocols
   - Legal and procedural references specific to child welfare
 
-### 📊 Enhanced Performance
+###  Enhanced Performance
 - **Contextual Understanding**: Better comprehension of child welfare scenarios including child labor, forced marriage, abuse cases
 - **Structured Summaries**: Generates concise, actionable summaries that capture key information:
   - Caller identity and location
@@ -41,7 +41,7 @@ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.
   - Action items and referrals provided
 - **Sensitive Content Handling**: Trained to appropriately summarize sensitive child protection cases while maintaining essential details
 
-### 🔧 Technical Specifications
+###  Technical Specifications
 
 | Configuration | Value |
 |---------------|--------|
@@ -182,11 +182,11 @@ This model is specifically designed for:
 Compared to the base FLAN-T5 model, this fine-tuned version shows significant improvements across all evaluation metrics:
 
 ### Key Improvements:
-- **📈 ROUGE Scores**: 50-84% improvement across ROUGE-1, ROUGE-2, and ROUGE-L metrics
-- **🎯 Domain Accuracy**: 94% accuracy in using child protection terminology (vs 52% for base model)
-- **🔍 Information Extraction**: 91% success rate in identifying key case details (vs 68% for base model)
-- **⚡ Action Item Detection**: 87% accuracy in identifying referrals and follow-up actions (vs 45% for base model)
-- **✅ Professional Assessment**: 4.4/5 overall quality rating from child protection professionals (vs 2.8/5 for base model)
+- ** ROUGE Scores**: 50-84% improvement across ROUGE-1, ROUGE-2, and ROUGE-L metrics
+- ** Domain Accuracy**: 94% accuracy in using child protection terminology (vs 52% for base model)
+- ** Information Extraction**: 91% success rate in identifying key case details (vs 68% for base model)
+- ** Action Item Detection**: 87% accuracy in identifying referrals and follow-up actions (vs 45% for base model)
+- ** Professional Assessment**: 4.4/5 overall quality rating from child protection professionals (vs 2.8/5 for base model)
 
 ### Performance Highlights:
 - **Relevance**: Better identification of key information in child protection contexts
@@ -202,10 +202,10 @@ If you use this model in your research or applications, please cite:
 ```bibtex
 @misc{flan-t5-child-helpline-summarizer,
   title={Fine-tuned FLAN-T5 for Child Helpline Case Summarization},
-  author={Bitz},
+  author={openchs},
   year={2024},
   publisher={Hugging Face},
-  howpublished={\url{https://huggingface.co/bitz/flan-t5-child-helpline-summarizer}}
+  howpublished={\url{https://huggingface.co/openchs/sum-flan-t5-base-synthetic-v1}}
 }
 ```