mikef0x OP t1_iv0d8up wrote on November 4, 2022 at 10:37 AM Reply to comment by BlazeObsidian in [R] Keras image classification high loss by mikef0x model = tf.keras.models.Sequential()model.add(tf.keras.layers.Conv2D(64, (3, 3), input_shape=(124, 124, 3)))model.add(tf.keras.layers.MaxPooling2D((2, 2)))model.add(tf.keras.layers.Conv2D(32, (3, 3)))model.add(tf.keras.layers.MaxPooling2D((2, 2)))model.add(tf.keras.layers.Conv2D(8, (3, 3)))model.add(tf.keras.layers.Flatten())model.add(tf.keras.layers.Dense(4, activation='softmax')) so, i've done like this. loss is low now but accuracy is to high :D i mean on epoch 10 its around 0.99. ​ update: on 20 epoch: accuracy is 1 Permalink Parent 2
mikef0x OP t1_iv036cq wrote on November 4, 2022 at 8:13 AM Reply to comment by BlazeObsidian in [R] Keras image classification high loss by mikef0x Okay thanks Permalink Parent 1
mikef0x OP t1_iv00teb wrote on November 4, 2022 at 7:38 AM Reply to comment by BlazeObsidian in [R] Keras image classification high loss by mikef0x I am beginner at ML. So it would be like this? model = models.Sequential() model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3))) model.add(layers.MaxPooling2D((2, 2))) model.add(layers.Conv2D(64, (3, 3), activation='relu')) model.add(layers.MaxPooling2D((2, 2))) model.add(layers.Conv2D(64, (3, 3), activation='relu')) Permalink Parent 2
[R] Keras image classification high loss Submitted by mikef0x t3_ylrngf on November 4, 2022 at 7:18 AM in MachineLearning 9 comments 1
mikef0x OP t1_iv0d8up wrote
Reply to comment by BlazeObsidian in [R] Keras image classification high loss by mikef0x
model = tf.keras.models.Sequential()model.add(tf.keras.layers.Conv2D(64, (3, 3), input_shape=(124, 124, 3)))model.add(tf.keras.layers.MaxPooling2D((2, 2)))model.add(tf.keras.layers.Conv2D(32, (3, 3)))model.add(tf.keras.layers.MaxPooling2D((2, 2)))model.add(tf.keras.layers.Conv2D(8, (3, 3)))model.add(tf.keras.layers.Flatten())model.add(tf.keras.layers.Dense(4, activation='softmax'))
so, i've done like this. loss is low now but accuracy is to high :D i mean on epoch 10 its around 0.99.
​
update: on 20 epoch: accuracy is 1