- updated notebook and gitignore

.gitignore

@@ -1,2 +1,3 @@
 .ipynb_checkpoints/
 data
+trained_net.pth

nn_image_classification.ipynb

@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "5b898116-e9a8-429d-8491-67db5a65d358",
    "metadata": {},
    "outputs": [
@@ -40,7 +40,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "51.0%"
+      "100.0%\n"
      ]
     }
    ],
@@ -54,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "49712fae-dfe6-4b6f-92ea-2e97a965c15c",
    "metadata": {},
    "outputs": [],
@@ -64,17 +64,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "d783e1a5-3410-4992-88a6-230dd2ec85dd",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([3, 32, 32])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "image.size()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "8ef21399-f2f2-46f4-8268-f60f36bbb533",
    "metadata": {},
    "outputs": [],
@@ -84,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "192ff676-c4b8-4611-9338-ec9b35a502d5",
    "metadata": {},
    "outputs": [],
@@ -111,7 +122,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "f48dd819-9196-4aa5-92c4-ddcc644c6aa9",
    "metadata": {},
    "outputs": [],
@@ -123,10 +134,77 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "3a91ce0c-e71d-4bfb-b945-47edfc8ca8d6",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training epoch 0...\n",
+      "Loss: 2.2366\n",
+      "Training epoch 1...\n",
+      "Loss: 1.7631\n",
+      "Training epoch 2...\n",
+      "Loss: 1.5183\n",
+      "Training epoch 3...\n",
+      "Loss: 1.3860\n",
+      "Training epoch 4...\n",
+      "Loss: 1.2861\n",
+      "Training epoch 5...\n",
+      "Loss: 1.2027\n",
+      "Training epoch 6...\n",
+      "Loss: 1.1302\n",
+      "Training epoch 7...\n",
+      "Loss: 1.0746\n",
+      "Training epoch 8...\n",
+      "Loss: 1.0332\n",
+      "Training epoch 9...\n",
+      "Loss: 0.9863\n",
+      "Training epoch 10...\n",
+      "Loss: 0.9492\n",
+      "Training epoch 11...\n",
+      "Loss: 0.9165\n",
+      "Training epoch 12...\n",
+      "Loss: 0.8859\n",
+      "Training epoch 13...\n",
+      "Loss: 0.8514\n",
+      "Training epoch 14...\n",
+      "Loss: 0.8210\n",
+      "Training epoch 15...\n",
+      "Loss: 0.7903\n",
+      "Training epoch 16...\n",
+      "Loss: 0.7662\n",
+      "Training epoch 17...\n",
+      "Loss: 0.7347\n",
+      "Training epoch 18...\n",
+      "Loss: 0.7096\n",
+      "Training epoch 19...\n",
+      "Loss: 0.6868\n",
+      "Training epoch 20...\n",
+      "Loss: 0.6642\n",
+      "Training epoch 21...\n",
+      "Loss: 0.6387\n",
+      "Training epoch 22...\n",
+      "Loss: 0.6193\n",
+      "Training epoch 23...\n",
+      "Loss: 0.5926\n",
+      "Training epoch 24...\n",
+      "Loss: 0.5701\n",
+      "Training epoch 25...\n",
+      "Loss: 0.5532\n",
+      "Training epoch 26...\n",
+      "Loss: 0.5306\n",
+      "Training epoch 27...\n",
+      "Loss: 0.5090\n",
+      "Training epoch 28...\n",
+      "Loss: 0.4891\n",
+      "Training epoch 29...\n",
+      "Loss: 0.4685\n"
+     ]
+    }
+   ],
    "source": [
     "for epoch in range(30):\n",
     "    print(f'Training epoch {epoch}...')\n",
@@ -148,7 +226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "aa5b2497-90a7-44a9-9985-427b920945eb",
    "metadata": {},
    "outputs": [],
@@ -158,10 +236,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "ff62419f-ead5-4244-9a5e-a21d568bdca8",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<All keys matched successfully>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "net = NeuralNet()\n",
     "net.load_state_dict(torch.load('trained_net.pth'))"
@@ -169,10 +258,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "eb1d4385-d4da-454f-9d8c-d844aa7b24df",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 68.86%\n"
+     ]
+    }
+   ],
    "source": [
     "correct = 0\n",
     "total = 0\n",
@@ -191,10 +288,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "1a4f098f-b1ea-46b7-a7d6-769f80292f5f",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Prediction: cat\n",
+      "Prediction: deer\n",
+      "Prediction: plane\n"
+     ]
+    }
+   ],
    "source": [
     "new_transform = transforms.Compose([\n",
     "    transforms.Resize((32, 32)),  \n",