Upload training_notebook.ipynb

training_notebook.ipynb

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+
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# PKR Currency Classifier Training Notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import torch.nn as nn\n",
+    "import torchvision.transforms as transforms\n",
+    "from torchvision import models, datasets\n",
+    "from torch.utils.data import DataLoader\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load dataset\n",
+    "transform = transforms.Compose([\n",
+    "    transforms.Resize((224, 224)),\n",
+    "    transforms.ToTensor(),\n",
+    "    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
+    "])\n",
+    "\n",
+    "train_data = datasets.ImageFolder('currency_dataset', transform=transform)\n",
+    "train_loader = DataLoader(train_data, batch_size=16, shuffle=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model\n",
+    "weights = models.MobileNet_V2_Weights.DEFAULT\n",
+    "model = models.mobilenet_v2(weights=weights)\n",
+    "model.classifier[1] = nn.Linear(model.last_channel, 2)\n",
+    "criterion = nn.CrossEntropyLoss()\n",
+    "optimizer = torch.optim.Adam(model.parameters(), lr=0.001)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Train\n",
+    "model.train()\n",
+    "for epoch in range(5):\n",
+    "    for images, labels in train_loader:\n",
+    "        optimizer.zero_grad()\n",
+    "        outputs = model(images)\n",
+    "        loss = criterion(outputs, labels)\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "    print(f'Epoch {epoch+1}, Loss: {loss.item()}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Save\n",
+    "torch.save(model, 'pkr_currency_classifier.pt')"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "training_notebook.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": ""
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}