Update README.md

README.md

@@ -2,16 +2,18 @@
 language: en
 license: apache-2.0
 datasets:
-  - custom
+- custom
 tags:
-  - summarization
-  - flan-t5
-  - youtube
-  - fine-tuned
+- summarization
+- flan-t5
+- youtube
+- fine-tuned
 base_model: google/flan-t5-base
 model-index:
-  - name: Flan T5 YouTube Summarizer
-    results: []
+- name: Flan T5 YouTube Summarizer
+  results: []
+metrics:
+- rouge
 ---
 
 # 📺 T5 YouTube Summarizer
@@ -27,7 +29,7 @@ This is a fine-tuned [flan-t5-base](https://huggingface.co/google/flan-t5-base)
 - **Training Data**: YouTube video transcripts and human-written summaries
 - **Max Input Length**: 512 tokens
 - **Max Output Length**: 256 tokens
-- **Fine-tuning Epochs**: 10
+- **Fine-tuning Epochs**: 5
 - **Tokenizer**: T5Tokenizer (pretrained)
 
 ---
@@ -44,7 +46,7 @@ This model is designed to generate short, informative summaries from long transc
 
 ## 🚀 How to Use
 
-python
+```python
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 
 # Load the model
@@ -69,7 +71,7 @@ summary_ids = model.generate(
 
 summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
 print(summary)
-
+```
 
 ## 📊 Evaluation
 
@@ -83,9 +85,11 @@ print(summary)
 
 ## 📌 Citation
 If you use this model in your work, consider citing:
+```
 @misc{t5ytsummarizer2025,
   title={Flan T5 YouTube Transcript Summarizer},
   author={Muhammad Bilal Yousaf},
   year={2025},
   howpublished={\url{https://huggingface.co/bilal521/flan-t5-youtube-summarizer}},
-}
+}
+```