Update README.md

README.md

@@ -25,7 +25,7 @@ We are thrilled to introduce a specialized collection of **68 large language mod
 💡 **Key Features:**
 - **Domain-Specific Training:** FinText utilises diverse financial datasets such as news articles, regulatory filings, IP records, corporate speeches (ECB, FED), and more.
 - **Time-Period Specific Models:** Separate models are pre-trained for each year from **2007 to 2023**, ensuring the utmost precision and historical relevance.
-- **RoBERTa Architecture:** The suite includes both a **base model** with **125 million parameters** and a **smaller variant** with **51 million parameters**—totalling 34 pre-trained models. 🎯
+- **RoBERTa Architecture:** The suite includes both a **base model** with **125 million parameters** and a **smaller variant** with **51 million parameters**.
 - **Two distinct pre-training durations:** We also introduce a series of models to explore the impact of futher pre-training. These models are pre-trained for an additional 5 epochs, extending the total pre-training epochs to 10.
 
 Stay tuned for upcoming updates and new features for FinText. We expect to launch stages 2 and 3 within the next 9 months. 🎉