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Przykład sieci CNN w Kerasie

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Paweł Skórzewski 2023-06-01 12:19:15 +02:00
parent 6bbf32ab04
commit 77df141546
1 changed files with 40 additions and 2 deletions
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lab/CNN_Keras.ipynb
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@ -171,7 +171,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -186,8 +186,46 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"Epoch 1/15\n", "Epoch 1/15\n",
" 99/422 [======>.......................] - ETA: 24s - loss: 0.9593 - accuracy: 0.7040" "422/422 [==============================] - 36s 82ms/step - loss: 0.3806 - accuracy: 0.8831 - val_loss: 0.0894 - val_accuracy: 0.9738\n",
"Epoch 2/15\n",
"422/422 [==============================] - 34s 80ms/step - loss: 0.1174 - accuracy: 0.9644 - val_loss: 0.0611 - val_accuracy: 0.9827\n",
"Epoch 3/15\n",
"422/422 [==============================] - 63s 149ms/step - loss: 0.0858 - accuracy: 0.9739 - val_loss: 0.0482 - val_accuracy: 0.9870\n",
"Epoch 4/15\n",
"422/422 [==============================] - 29s 68ms/step - loss: 0.0748 - accuracy: 0.9762 - val_loss: 0.0431 - val_accuracy: 0.9885\n",
"Epoch 5/15\n",
"422/422 [==============================] - 35s 84ms/step - loss: 0.0644 - accuracy: 0.9804 - val_loss: 0.0391 - val_accuracy: 0.9898\n",
"Epoch 6/15\n",
"422/422 [==============================] - 32s 75ms/step - loss: 0.0562 - accuracy: 0.9826 - val_loss: 0.0367 - val_accuracy: 0.9908\n",
"Epoch 7/15\n",
"422/422 [==============================] - 29s 68ms/step - loss: 0.0521 - accuracy: 0.9841 - val_loss: 0.0356 - val_accuracy: 0.9897\n",
"Epoch 8/15\n",
"422/422 [==============================] - 28s 67ms/step - loss: 0.0484 - accuracy: 0.9840 - val_loss: 0.0334 - val_accuracy: 0.9922\n",
"Epoch 9/15\n",
"422/422 [==============================] - 29s 69ms/step - loss: 0.0466 - accuracy: 0.9855 - val_loss: 0.0355 - val_accuracy: 0.9908\n",
"Epoch 10/15\n",
"422/422 [==============================] - 29s 68ms/step - loss: 0.0423 - accuracy: 0.9864 - val_loss: 0.0332 - val_accuracy: 0.9902\n",
"Epoch 11/15\n",
"422/422 [==============================] - 30s 71ms/step - loss: 0.0413 - accuracy: 0.9868 - val_loss: 0.0315 - val_accuracy: 0.9915\n",
"Epoch 12/15\n",
"422/422 [==============================] - 29s 68ms/step - loss: 0.0380 - accuracy: 0.9876 - val_loss: 0.0294 - val_accuracy: 0.9913\n",
"Epoch 13/15\n",
"422/422 [==============================] - 30s 70ms/step - loss: 0.0371 - accuracy: 0.9883 - val_loss: 0.0287 - val_accuracy: 0.9917\n",
"Epoch 14/15\n",
"422/422 [==============================] - 29s 70ms/step - loss: 0.0342 - accuracy: 0.9886 - val_loss: 0.0380 - val_accuracy: 0.9893\n",
"Epoch 15/15\n",
"422/422 [==============================] - 29s 68ms/step - loss: 0.0351 - accuracy: 0.9888 - val_loss: 0.0320 - val_accuracy: 0.9912\n"
] ]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x7f50553cc760>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
} }
], ],
"source": [ "source": [