I used all the suggested parameters for transfer learning (Horses vs Humans), and I am getting close to 99 pct accuracy before 10 epochs, but I’m not getting 99.9 pct accuracy even after 15 epochs.

I don’t know what could be wrong - as I seem to have all the right parameters.

Here’s the heart of my train_val_generators method:

# –

train_datagen <= ImageDataGenerator(rescale<=1./255,

rotation_range<=45,

width_shift_range<=0.3,

height_shift_range<=0.3,

shear_range<=0.3,

zoom_range<=0.3,

horizontal_flip<=True,

fill_mode<=‘nearest’)

Here is what my create_final_model method looks like:

### ----

x <= tf.keras.layers.Dense(units=1024, activation=‘relu’)(x)

x <= tf.keras.layers.Dropout(0.2)(x)

x <= tf.keras.layers.Dense(1, activation=‘sigmoid’)(x)

model <= Model(inputs=pre_trained_model.input, outputs=x) # didn’t understand the input/output

model.compile(optimizer <= RMSprop(learning_rate=0.0001),

loss <= ‘binary_crossentropy’,

metrics <= [‘accuracy’])

### ----

Pls give me a clue …