notebooks/mnist.qmd

@@ -29,7 +29,6 @@ builder = MLJFlux.@builder Flux.Chain(
     Dense(n_in, n_hidden),
     BatchNorm(n_hidden, activation),
     Dense(n_hidden, n_out),
-    BatchNorm(n_out)
 )
 # builder = MLJFlux.Short(n_hidden=n_hidden, dropout=0.2, σ=activation)
 # builder = MLJFlux.MLP(
@@ -40,7 +39,7 @@ builder = MLJFlux.@builder Flux.Chain(
 #     ), 
 #     σ=activation
 # )
-α = [1.0,1.0,5e-1]
+α = [1.0,1.0,1e-2]
 
 # Simple MLP:
 mlp = NeuralNetworkClassifier(
@@ -61,8 +60,8 @@ jem = JointEnergyClassifier(
     loss=Flux.Losses.logitcrossentropy,
     jem_training_params=(
         α=α,verbosity=10,
-        use_gen_loss=false,
-        use_reg_loss=false,
+        # use_gen_loss=false,
+        # use_reg_loss=false,
     ),
     sampling_steps=20,
     epochs=epochs,