Update README.md

README.md

@@ -182,7 +182,7 @@ More information needed
 
 ## Model Architecture and Objective
 
-The model architecture is based on the original Swin2 arcthitecture for Super Resolution (SR) tasks. The library [transformers](https://github.com/huggingface/transformers) is used to simplify the model design.
+The model architecture is based on the original Swin2 architecture for Super Resolution (SR) tasks. The library [transformers](https://github.com/huggingface/transformers) is used to simplify the model design.
 
 ![architecture](architecture.png)
 
@@ -191,7 +191,7 @@ As the real upscale ratio is ~5 and the output shape of the region considered is
 
 This network is trained to learn the residuals of the bicubic interpolation.
 
-The specific parameters of this networks are available in [config.json](https://huggingface.co/predictia/convswin2sr_mediterranean/blob/main/config.json).
+The specific parameters of this network are available in [config.json](https://huggingface.co/predictia/convswin2sr_mediterranean/blob/main/config.json).
 
 
 ## Compute Infrastructure