Update README.md

README.md

@@ -24,7 +24,8 @@ It achieves the following results on the evaluation set:
 
 ## Spectrum Fine-tuning:
 I have used the **Spectrum Fine-tuning** method as described in [Eric Hartford et. al 2024](https://arxiv.org/abs/2406.06623), which selectively targets some ***t%*** of the model layers with the highest **Signal-to-Noise Ratio (SNR)**. By focusing on the most information-dense layers, this approach maximizes fine-tuning efficiency while minimizing compute resources.
-The key goal of Spectrum Fine-tuning is: *minimize the memory footprint and accelerate LLM training without sacrificing performance.*
+
+**The key goal of Spectrum Fine-tuning is:** *minimize the memory footprint and accelerate LLM training without sacrificing performance.*
 
 The 25% layer selection ensures minimal computational overhead for fine-tuning.