Fine-tuning InceptionV3: Correct number of layers for two last inception blocks.
@@ -130,10 +130,10 @@ for i, layer in enumerate(base_model.layers):
print(i, layer.name)
# we chose to train the top 2 inception blocks, i.e. we will freeze
-# the first 172 layers and unfreeze the rest:
-for layer in model.layers[:172]:
+# the first 249 layers and unfreeze the rest:
+for layer in model.layers[:249]:
layer.trainable = False
-for layer in model.layers[172:]:
+for layer in model.layers[249:]:
layer.trainable = True
# we need to recompile the model for these modifications to take effect
