Update README.md

adding inference speed and model size

README.md

@@ -159,9 +159,16 @@ The interpolation transformed the CERRA dataset to match the regular grid struct
 
 ### Speeds, Sizes, Times
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+- Training time: 
 
-More information needed
+- Model size: The ConvSwin2SR model is a robust machine learning model boasting a total of 12,383,377 parameters.
+  This size reflects a substantial capacity for learning and generalizing complex relationships within the data, enabling the model to
+  effectively upscale lower-resolution reanalysis grids to higher-resolution versions.
+
+- Inference speed: The ConvSwin2SR model demonstrates a commendable inference speed, particularly when handling a substantial batch of samples.
+  Specifically, when tasked with downscaling 248 samples, which is synonymous with processing data for an entire month at 3-hour intervals,
+  the model completes the operation in a mere 21 seconds. This level of efficiency is observed in a local computing environment outfitted with 16GB o
+  f RAM and 4GB of GPU memory. 
  
 # Evaluation