data update

README.md

@@ -283,9 +283,9 @@ print(output)
 
 <!-- TO DO: To be completed once the paper is ready -->
 ## Training Data
-This model is trained on a mix of open-source and proprietary datasets. 
-* Phase 1: The data for phase 1 is sourced from diverse domains, such as: web, code, academic sources, books, and math data.
-* Phase 2: The data for phase 2 comprises a curated mix of high-quality data from the same domains, plus multilingual and instruction data. The goal of this second training phase is to enhance the model’s performance on specific tasks.
+This model is trained on a mix of open-source and proprietary data following a two-phase training strategy.
+* Phase 1 data: The data for phase 1 is sourced from diverse domains, such as: web, code, academic sources, books, and math data.
+* Phase 2 data: The data for phase 2 comprises a curated mix of high-quality data from the same domains, plus multilingual and instruction data. The goal of this second training phase is to enhance the model’s performance on specific tasks.
   
 ## Infrastructure 
 We train the Granite Language models using IBM's super computing cluster, Blue Vela, which is outfitted with NVIDIA H100 GPUs. This cluster provides a scalable and efficient infrastructure for training our models over thousands of GPUs.