Update README.md

README.md

@@ -30,7 +30,7 @@ The primary objective of this model is to **serve the unique needs of Indian sto
 
 **IndicFinGPT 125M** utilizes the **Pile dataset** created by EleutherAI and includes the **top 100 tickers** (by volume and liquidity) from Indian stock markets, covering data from **January 1, 2018, to October 30, 2024**. This dataset encompasses diverse market periods, including **pre-COVID-19 (stable), COVID-19 (volatile), and post-COVID-19 (recovery phase)**. Such comprehensive data exposure allows the model to recognize **problem-solution patterns across various bull and bear runs**.
 The training data also incorporates **local influences** such as cultural factors and **market-specific volatility**, enhancing its ability to perform **automated technical analysis** for chartless trading. Key capabilities include identifying **classical chart patterns** using technical analysis, conducting **earnings analysis**, interpreting **market sentiment** from multiple sources, and **assessing risks**, all aimed at **improving decision-making for Indian investors**.
-This model was trained on **310 billion tokens over 692,380 steps. It utilized Quantized Low-Rank Adoption method on top of  the masked autoregressive language model architecture of Neo, utilizing cross-entropy loss, F1, Accuracy, Precision, recall,Pattern Detection Rate, and Cross-Entropy Loss as performance metrics.
+This model was trained on **310 billion tokens over 692,380 steps**. It utilized 4-bit Quantized Low-Rank Adoption (PEFT) method on top of  the masked autoregressive language model architecture of Neo, utilizing cross-entropy loss, F1, Accuracy, Precision, recall,Pattern Detection Rate, and Cross-Entropy Loss as performance metrics.
 
 
 ## First Indic-Stock Small Language Model Focused Top 100 Companies Listed in NSE and BSE Stock Exchanges