Update README.md

README.md

@@ -14,9 +14,9 @@ pipeline_tag: text2text-generation
 
 ## 🧠 Abstract
 
-This model presents a fine-tuned version of `umt5-small`, specifically adapted for **abstractive summarization** of Turkish-language texts. Leveraging the multilingual capabilities of the original mT5 architecture, the model has been trained on a high-quality Turkish summarization dataset containing diverse news articles and their human-written summaries. The goal of this model is to generate coherent, concise, and semantically accurate summaries from long-form Turkish content, making it suitable for real-world applications such as news aggregation, document compression, and information retrieval.
+This model presents a fine-tuned version of `umt5-small`, specifically adapted for **abstractive summarization** of Turkish-language texts. Leveraging the multilingual capabilities of the original umT5 architecture, the model has been trained on a high-quality Turkish summarization dataset containing diverse news articles and their human-written summaries. The goal of this model is to generate coherent, concise, and semantically accurate summaries from long-form Turkish content, making it suitable for real-world applications such as news aggregation, document compression, and information retrieval.
 
-Despite its small size (~60M parameters), the model demonstrates strong performance across standard evaluation metrics including **ROUGE** and **METEOR**, achieving results within the commonly accepted thresholds for Turkish-language summarization tasks. It strikes a practical balance between efficiency and quality, making it ideal for use in resource-constrained environments.
+Despite its small size the model demonstrates strong performance across standard evaluation metrics including **ROUGE** and **METEOR**, achieving results within the commonly accepted thresholds for Turkish-language summarization tasks. It strikes a practical balance between efficiency and quality, making it ideal for use in resource-constrained environments.
 
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