Update README.md

README.md

@@ -6,7 +6,7 @@ tags:
 license: apache-2.0
 ---
 
-# BERT-based Sentiment Classification Model
+# BERT-based Sentiment Classification Mode
 
 ## Model Details
 - **Model Name:** tabularisai/bert-base-uncased-sentiment-five-classes
@@ -16,11 +16,11 @@ license: apache-2.0
 
 ## Model Description
 
-This model is a fine-tuned version of `bert-base-uncased` for sentiment analysis. It classifies text into five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive.
+This model is a fine-tuned version of `bert-base-uncased` for sentiment analysis. **Trained exclusively on syntethic data produced by SOTA LLMs: Llama3, Gemma2, and more**
 
 ### Training Data
 
-The model was fine-tuned on synthetic data, which allows for targeted training on a diverse range of sentiment expressions without the limitations often found in real-world datasets. This approach enables the model to learn nuanced sentiment patterns across various contexts.
+The model was fine-tuned on synthetic data, which allows for targeted training on a diverse range of sentiment expressions without the limitations often found in real-world datasets. 
 
 ### Training Procedure
 
@@ -117,4 +117,4 @@ Will be included
 
 ## Contact
 
-For questions, feedback, or issues related to this model, please [provide contact information or link to issue tracker].
+For questions, feedback, or issues related to this model, please `info@tabularis.ai`