Update README.md

README.md

@@ -113,7 +113,7 @@ The model was trained locally on a single-node with multiple Nvidia A100 GPUs us
 
 #### Training Hyperparameters
 
-- **Precision:** We use FP32 precision, the same precision of the base "google/flan-t5-large" model.
+- **Precision:** We trained the model in bfloat16, and subsequently publish it with the same precision of the base "google/flan-t5-large" model in FP32.
 - **Optimizer:** `apex.optimizers.FusedAdam`, a fused kernel version of the AdamW optimizer from Nvidia Apex
 - **Learning Rate:** We use a linear learing rate scheduler with an initial learning rate of 1e-4 to further adjust the CyberSolve LinAlg **1.1** weights
 - **Batch Size:** 64