Update README.md

README.md

@@ -26,8 +26,6 @@ The dataset used is provided by the Museum of London. The sherds dataset include
 
 ## Setup
 
-##### a. Load dataset folder 
-
 Step 1: Install the necessary libraries and items
 
 ```
@@ -67,31 +65,6 @@ Step 6: Inference.
 #Write inference code
 ```
 
-##### b. Configure hyperparameters 
-
-In the 'hyperparameters' section, there are several hypermaraters that can be configured. 
-
-* epoch_num -> number of epochs
-* patience -> patience for early stopping (# of consecutive epochs where validation loss doesn't improve before training is broken)
-* val_interval -> frequency that the model is evaluated
-* alpha -> weighting for dice loss
-* beta -> weighting for cross-entropy (classification) loss
-* batch_size in train_dataloder -> training batch size
-* batch_size in val_dataloader -> validation batch size
-* lr in optimizer -> learning rate
-
-Hyperparameters for the model architecture: 
-
-* encoder_name -> what encoder model we are using(usually set to resnet34).
-* encoder_weights -> weight initialization(can be set to either 'ImageNet' or 'Xavier').
-
-For dataset size:
-
-* The '[:some_number]' in the creating mask section -> cap on the number of samples per class
-
-##### c. Run the code
-
-Click 'Runtime' -> 'Run all'. 
 
 ## Model Architecture