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