Update README.md

README.md

@@ -51,7 +51,7 @@ $$
 $$
 
 Where:
-- $$ \theta_s $$ and $ \theta_t $ represent student (trainable) and teacher (frozen) model parameters
+- $\theta_s$ and $\theta_t$ represent student (trainable) and teacher (frozen) model parameters
 - $$P_{\theta}^{(i)}$$ denotes the probability distribution at reasoning step $$i$$
 - $$ \lambda(t) = \lambda_0 \cdot (1 + \gamma \cdot \text{complexity}(x_t)) $$ is the dynamic weight function
 - $\alpha_i = \exp(-\delta \cdot i/T)$ implements exponential decay for later reasoning steps