Update README.md

README.md

@@ -12,7 +12,7 @@ datasets:
 ---
 # ConvoBrief: LoRA-enhanced BART Model for Dialogue Summarization
 
-This model is a variant of the 'facebook/bart-large-cnn' model, optimized with LoRA (Local Relational Aggregation) for dialogue summarization tasks. LoRA enhances feature aggregation across different positions in the sequence, making it particularly effective for capturing the nuances of dialogues.
+This model is a variant of the `facebook/bart-large-cnn` model, enhanced with Low-Rank Adaptation (LoRA) for dialogue summarization tasks. LoRA employs Low-Rank Attention to facilitate feature aggregation across different positions in the sequence, making it particularly effective for capturing the nuances of dialogues.
 
 ## LoRA Configuration:
 
@@ -26,7 +26,7 @@ This model is a variant of the 'facebook/bart-large-cnn' model, optimized with L
 This model has been fine-tuned using the PEFT (Parameter-Efficient Fine-Tuning) approach, striking a balance between dialogue summarization objectives for optimal performance.
 ## Usage:
 
-Deploy this LoRA-enhanced BART model for dialogue summarization tasks, where it excels in distilling meaningful summaries from conversational text. Capture the richness of dialogues and generate concise yet informative summaries using the enhanced contextual understanding provided by LoRA.
+Deploy this LoRA-enhanced BART model for dialogue summarization tasks, leveraging the power of Low-Rank Adaptation to capture contextual dependencies in conversations. Generate concise and informative summaries from conversational text, enhancing your applications with enriched context-awareness.
 ```python
 from peft import PeftModel, PeftConfig
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
@@ -72,8 +72,6 @@ print("Original Dialogue:\n", full_dialogue)
 print("Generated Summary:\n", summary[0]['summary_text'])
 ```
 
-Feel free to customize and expand upon this description and usage example to provide additional context and details about your LoRA-enhanced BART model and how users can effectively use it for dialogue summarization tasks.
-
 ### Framework versions
 
 - PEFT 0.4.0