Update README.md

README.md

@@ -17,7 +17,7 @@ pipeline_tag: text-classification
 # Model Card for ABSA_Turkish_BERT_Based_Small
 
 <!-- Provide a quick summary of what the model is/does. -->
-This model performs **Aspect-Based Sentiment Analysis (ABSA)** for Turkish text. It predicts sentiment polarity (Positive, Neutral, Negative) towards specific aspects within a given sentence.
+This model performs **Aspect-Based Sentiment Analysis (ABSA) 🚀** for Turkish text. It predicts sentiment polarity (Positive, Neutral, Negative) towards specific aspects within a given sentence.
 
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@@ -26,7 +26,7 @@ This model performs **Aspect-Based Sentiment Analysis (ABSA)** for Turkish text.
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
-This model is fine-tuned from the `dbmdz/bert-base-turkish-cased` pretrained BERT model. It is trained on the **Turkish-ABSA-Wsynthetic.csv** dataset, which contains Turkish restaurant reviews annotated with aspect-based sentiments. The model is capable of identifying the sentiment polarity for specific aspects (e.g., "servis," "fiyatlar") mentioned in Turkish sentences.
+This model is fine-tuned from the `dbmdz/bert-base-turkish-cased` pretrained BERT model. It is trained on the **Turkish-ABSA-Wsynthetic** dataset, which contains Turkish restaurant reviews annotated with aspect-based sentiments. The model is capable of identifying the sentiment polarity for specific aspects (e.g., "servis," "fiyatlar") mentioned in Turkish sentences.
 
 - **Developed by:** Sengil
 - **Language(s):** Turkish 🇹🇷
@@ -120,7 +120,7 @@ The model achieved the following scores on the test set:
 - F1 Score (Weighted): 95.46%
 
 
-## Citation [optional]
+## Citation
 
 ```
 @misc{absa_turkish_bert_based_small,