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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "x2SSsQMSknm2"
},
"source": [
"#### ResNet18 모델 아키텍처 정의"
]
},
{
"cell_type": "code",
"metadata": {
"id": "zpUcgk5xkgGZ"
},
"source": [
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"import torch.optim as optim\n",
"import os\n",
"\n",
"\n",
"# ResNet18을 위해 최대한 간단히 수정한 BasicBlock 클래스\n",
"class BasicBlock(nn.Module):\n",
" def __init__(self, in_planes, planes, stride=1):\n",
" super(BasicBlock, self).__init__()\n",
"\n",
" # 3x3 필터를 사용 (너비와 높이를 줄일 때는 stride 값 조절)\n",
" self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)\n",
" self.bn1 = nn.BatchNorm2d(planes) # 배치 정규화(batch normalization)\n",
"\n",
" # 3x3 필터를 사용 (패딩을 1만큼 주기 때문에 너비와 높이가 동일)\n",
" self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=1, padding=1, bias=False)\n",
" self.bn2 = nn.BatchNorm2d(planes) # 배치 정규화(batch normalization)\n",
"\n",
" self.shortcut = nn.Sequential() # identity인 경우\n",
" if stride != 1: # stride가 1이 아니라면, identity mapping이 아닌 경우\n",
" self.shortcut = nn.Sequential(\n",
" nn.Conv2d(in_planes, planes, kernel_size=1, stride=stride, bias=False),\n",
" nn.BatchNorm2d(planes)\n",
" )\n",
"\n",
" def forward(self, x):\n",
" out = F.relu(self.bn1(self.conv1(x)))\n",
" out = self.bn2(self.conv2(out))\n",
" out += self.shortcut(x) # (핵심) skip connection\n",
" out = F.relu(out)\n",
" return out\n",
"\n",
"\n",
"# ResNet 클래스 정의\n",
"class ResNet(nn.Module):\n",
" def __init__(self, block, num_blocks, num_classes=10):\n",
" super(ResNet, self).__init__()\n",
" self.in_planes = 64\n",
"\n",
" # 64개의 3x3 필터(filter)를 사용\n",
" self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\n",
" self.bn1 = nn.BatchNorm2d(64)\n",
" self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)\n",
" self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)\n",
" self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)\n",
" self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)\n",
" self.linear = nn.Linear(512, num_classes)\n",
"\n",
" def _make_layer(self, block, planes, num_blocks, stride):\n",
" strides = [stride] + [1] * (num_blocks - 1)\n",
" layers = []\n",
" for stride in strides:\n",
" layers.append(block(self.in_planes, planes, stride))\n",
" self.in_planes = planes # 다음 레이어를 위해 채널 수 변경\n",
" return nn.Sequential(*layers)\n",
"\n",
" def forward(self, x):\n",
" out = F.relu(self.bn1(self.conv1(x)))\n",
" out = self.layer1(out)\n",
" out = self.layer2(out)\n",
" out = self.layer3(out)\n",
" out = self.layer4(out) # 출력: [batch_size, 512, 4, 4]\n",
" out = F.avg_pool2d(out, 4) # 출력: [batch_size, 512, 1, 1]\n",
" out = out.view(out.size(0), -1) # 출력: [batch_size, 512]\n",
" out = self.linear(out)\n",
" return out\n",
"\n",
"\n",
"# ResNet18 함수 정의\n",
"def ResNet18():\n",
" return ResNet(BasicBlock, [2, 2, 2, 2])"
],
"execution_count": 1,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "nCNacrgtktlr"
},
"source": [
"#### 데이터셋(Dataset) 다운로드 및 불러오기"
]
},
{
"cell_type": "code",
"metadata": {
"id": "EmmQZ8p5kq_C",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 118,
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"outputId": "96dda201-7fc9-4560-ebf6-1b0bf71e9006"
},
"source": [
"import torchvision\n",
"import torchvision.transforms as transforms\n",
"\n",
"transform_train = transforms.Compose([\n",
" transforms.RandomCrop(32, padding=4),\n",
" transforms.RandomHorizontalFlip(),\n",
" transforms.ToTensor(),\n",
"])\n",
"\n",
"transform_test = transforms.Compose([\n",
" transforms.ToTensor(),\n",
"])\n",
"\n",
"train_dataset = torchvision.datasets.CIFAR10(root='./data', train=True, download=True, transform=transform_train)\n",
"test_dataset = torchvision.datasets.CIFAR10(root='./data', train=False, download=True, transform=transform_test)\n",
"\n",
"train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=128, shuffle=True, num_workers=2)\n",
"test_loader = torch.utils.data.DataLoader(test_dataset, batch_size=100, shuffle=False, num_workers=2)"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"text": [
"Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to ./data/cifar-10-python.tar.gz\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
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"tags": []
}
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{
"output_type": "stream",
"text": [
"\n",
"Extracting ./data/cifar-10-python.tar.gz to ./data\n",
"Files already downloaded and verified\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Dl1-47E7pHD_"
},
"source": [
"#### 환경 설정 및 학습(Training) 함수 정의"
]
},
{
"cell_type": "code",
"metadata": {
"id": "bhm_eVykk-Z8"
},
"source": [
"device = 'cuda'\n",
"\n",
"net = ResNet18()\n",
"net = net.to(device)\n",
"\n",
"learning_rate = 0.1\n",
"file_name = 'resnet18_cifar10.pth'\n",
"\n",
"criterion = nn.CrossEntropyLoss()\n",
"optimizer = optim.SGD(net.parameters(), lr=learning_rate, momentum=0.9, weight_decay=0.0002)\n",
"\n",
"\n",
"def train(epoch):\n",
" print('\\n[ Train epoch: %d ]' % epoch)\n",
" net.train()\n",
" train_loss = 0\n",
" correct = 0\n",
" total = 0\n",
"\n",
" for batch_idx, (inputs, targets) in enumerate(train_loader):\n",
" inputs, targets = inputs.to(device), targets.to(device)\n",
" optimizer.zero_grad()\n",
"\n",
" outputs = net(inputs)\n",
" loss = criterion(outputs, targets)\n",
" loss.backward()\n",
"\n",
" optimizer.step()\n",
" train_loss += loss.item()\n",
" _, predicted = outputs.max(1)\n",
"\n",
" total += targets.size(0)\n",
" current_correct = predicted.eq(targets).sum().item()\n",
" correct += current_correct\n",
" \n",
" if batch_idx % 100 == 0:\n",
" print('\\nCurrent batch:', str(batch_idx))\n",
" print('Current batch average train accuracy:', current_correct / targets.size(0))\n",
" print('Current batch average train loss:', loss.item() / targets.size(0))\n",
"\n",
" print('\\nTotal average train accuarcy:', correct / total)\n",
" print('Total average train loss:', train_loss / total)\n",
"\n",
"\n",
"def test(epoch):\n",
" print('\\n[ Test epoch: %d ]' % epoch)\n",
" net.eval()\n",
" loss = 0\n",
" correct = 0\n",
" total = 0\n",
"\n",
" for batch_idx, (inputs, targets) in enumerate(test_loader):\n",
" inputs, targets = inputs.to(device), targets.to(device)\n",
" total += targets.size(0)\n",
"\n",
" outputs = net(inputs)\n",
" loss += criterion(outputs, targets).item()\n",
"\n",
" _, predicted = outputs.max(1)\n",
" correct += predicted.eq(targets).sum().item()\n",
"\n",
" print('\\nTotal average test accuarcy:', correct / total)\n",
" print('Total average test loss:', loss / total)\n",
"\n",
" state = {\n",
" 'net': net.state_dict()\n",
" }\n",
" if not os.path.isdir('checkpoint'):\n",
" os.mkdir('checkpoint')\n",
" torch.save(state, './checkpoint/' + file_name)\n",
" print('Model Saved!')"
],
"execution_count": 3,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "0mv5z7CEMRrn"
},
"source": [
"#### 학습(Training) 진행"
]
},
{
"cell_type": "code",
"metadata": {
"id": "4voLj7TKlaB1",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "b23e1aa6-e9ec-415e-dafb-0083ebff0dbc"
},
"source": [
"import time\n",
"\n",
"\n",
"def adjust_learning_rate(optimizer, epoch):\n",
" lr = learning_rate\n",
" if epoch >= 50:\n",
" lr /= 10\n",
" if epoch >= 100:\n",
" lr /= 10\n",
" for param_group in optimizer.param_groups:\n",
" param_group['lr'] = lr\n",
"\n",
"start_time = time.time()\n",
"\n",
"for epoch in range(0, 150):\n",
" adjust_learning_rate(optimizer, epoch)\n",
" train(epoch)\n",
" test(epoch)\n",
" print('\\nTime elapsed:', time.time() - start_time)"
],
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": [
"\n",
"[ Train epoch: 0 ]\n",
"\n",
"Current batch: 0\n",
"Current batch average train accuracy: 0.09375\n",
"Current batch average train loss: 0.018886184319853783\n",
"\n",
"Current batch: 100\n",
"Current batch average train accuracy: 0.2734375\n",
"Current batch average train loss: 0.014718282967805862\n",
"\n",
"Current batch: 200\n",
"Current batch average train accuracy: 0.3671875\n",
"Current batch average train loss: 0.014242153614759445\n",
"\n",
"Current batch: 300\n",
"Current batch average train accuracy: 0.359375\n",
"Current batch average train loss: 0.013957763090729713\n",
"\n",
"Total average train accuarcy: 0.33596\n",
"Total average train loss: 0.014389348886013032\n",
"\n",
"[ Test epoch: 0 ]\n",
"\n",
"Total average test accuarcy: 0.3378\n",
"Total average test loss: 0.020276899695396422\n",
"Model Saved!\n",
"\n",
"Time elapsed: 64.44241976737976\n",
"\n",
"[ Train epoch: 1 ]\n",
"\n",
"Current batch: 0\n",
"Current batch average train accuracy: 0.390625\n",
"Current batch average train loss: 0.011884287931025028\n",
"\n",
"Current batch: 100\n",
"Current batch average train accuracy: 0.4609375\n",
"Current batch average train loss: 0.011372450739145279\n",
"\n",
"Current batch: 200\n",
"Current batch average train accuracy: 0.515625\n",
"Current batch average train loss: 0.01057681068778038\n",
"\n",
"Current batch: 300\n",
"Current batch average train accuracy: 0.546875\n",
"Current batch average train loss: 0.0099992910400033\n",
"\n",
"Total average train accuarcy: 0.49874\n",
"Total average train loss: 0.010656513631343841\n",
"\n",
"[ Test epoch: 1 ]\n",
"\n",
"Total average test accuarcy: 0.5508\n",
"Total average test loss: 0.012453191781044006\n",
"Model Saved!\n",
"\n",
"Time elapsed: 129.17036938667297\n",
"\n",
"[ Train epoch: 2 ]\n",
"\n",
"Current batch: 0\n",
"Current batch average train accuracy: 0.546875\n",
"Current batch average train loss: 0.009568811394274235\n",
"\n",
"Current batch: 100\n",
"Current batch average train accuracy: 0.546875\n",
"Current batch average train loss: 0.009234337136149406\n",
"\n",
"Current batch: 200\n",
"Current batch average train accuracy: 0.609375\n",
"Current batch average train loss: 0.008707437664270401\n",
"\n",
"Current batch: 300\n",
"Current batch average train accuracy: 0.625\n",
"Current batch average train loss: 0.008674639277160168\n",
"\n",
"Total average train accuarcy: 0.61538\n",
"Total average train loss: 0.008443874225616455\n",
"\n",
"[ Test epoch: 2 ]\n",
"\n",
"Total average test accuarcy: 0.5994\n",
"Total average test loss: 0.011250553631782532\n",
"Model Saved!\n",
"\n",
"Time elapsed: 194.5965633392334\n",
"\n",
"[ Train epoch: 3 ]\n",
"\n",
"Current batch: 0\n",
"Current batch average train accuracy: 0.7265625\n",
"Current batch average train loss: 0.006437853444367647\n",
"\n",
"Current batch: 100\n",
"Current batch average train accuracy: 0.65625\n",
"Current batch average train loss: 0.0069402712397277355\n",
"\n",
"Current batch: 200\n",
"Current batch average train accuracy: 0.65625\n",
"Current batch average train loss: 0.007859010249376297\n",
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"Current batch average train accuracy: 0.75\n",
"Current batch average train loss: 0.00678347097709775\n",
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"Total average train accuarcy: 0.67656\n",
"Total average train loss: 0.007134215934276581\n",
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"[ Test epoch: 3 ]\n",
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"Total average test accuarcy: 0.4649\n",
"Total average test loss: 0.0168255980014801\n",
"Model Saved!\n",
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"Time elapsed: 260.0428605079651\n",
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"[ Train epoch: 4 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.6875\n",
"Current batch average train loss: 0.006170612759888172\n",
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"Current batch average train loss: 0.0061060236766934395\n",
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"Current batch average train accuracy: 0.765625\n",
"Current batch average train loss: 0.0059174709022045135\n",
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"Current batch average train accuracy: 0.75\n",
"Current batch average train loss: 0.005906655453145504\n",
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"Total average train accuarcy: 0.72524\n",
"Total average train loss: 0.006093273480534554\n",
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"[ Test epoch: 4 ]\n",
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"Total average test accuarcy: 0.6889\n",
"Total average test loss: 0.009331835901737213\n",
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"Time elapsed: 325.60246682167053\n",
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"[ Train epoch: 5 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.734375\n",
"Current batch average train loss: 0.005777167156338692\n",
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"Current batch average train accuracy: 0.6875\n",
"Current batch average train loss: 0.006888024974614382\n",
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"Current batch average train accuracy: 0.765625\n",
"Current batch average train loss: 0.005506306421011686\n",
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"Current batch average train accuracy: 0.71875\n",
"Current batch average train loss: 0.005440236534923315\n",
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"Total average train accuarcy: 0.76258\n",
"Total average train loss: 0.005287064665555954\n",
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"[ Test epoch: 5 ]\n",
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"Total average test accuarcy: 0.7067\n",
"Total average test loss: 0.008627147650718689\n",
"Model Saved!\n",
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"Time elapsed: 391.20608496665955\n",
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"[ Train epoch: 6 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.75\n",
"Current batch average train loss: 0.005495917052030563\n",
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"Current batch average train loss: 0.003429488046094775\n",
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"Current batch average train accuracy: 0.8046875\n",
"Current batch average train loss: 0.004394953604787588\n",
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"Current batch average train accuracy: 0.84375\n",
"Current batch average train loss: 0.0039040944539010525\n",
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"Total average train accuarcy: 0.79366\n",
"Total average train loss: 0.00465249278485775\n",
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"[ Test epoch: 6 ]\n",
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"Total average test accuarcy: 0.714\n",
"Total average test loss: 0.00807059274315834\n",
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"Time elapsed: 457.04896879196167\n",
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"[ Train epoch: 7 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.8828125\n",
"Current batch average train loss: 0.0034638831857591867\n",
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"Current batch average train loss: 0.004656535107642412\n",
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"Current batch average train loss: 0.0030394589994102716\n",
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"Current batch average train accuracy: 0.8828125\n",
"Current batch average train loss: 0.0027536724228411913\n",
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"Total average train accuarcy: 0.81106\n",
"Total average train loss: 0.004228765366673469\n",
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"[ Test epoch: 7 ]\n",
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"Total average test accuarcy: 0.782\n",
"Total average test loss: 0.006416438111662865\n",
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"Time elapsed: 522.8865828514099\n",
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"[ Train epoch: 8 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.84375\n",
"Current batch average train loss: 0.0037816339172422886\n",
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"Current batch average train loss: 0.0043265060521662235\n",
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"Current batch average train accuracy: 0.8203125\n",
"Current batch average train loss: 0.004202579148113728\n",
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"Current batch average train accuracy: 0.8359375\n",
"Current batch average train loss: 0.0036502364091575146\n",
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"Total average train accuarcy: 0.83008\n",
"Total average train loss: 0.003872908027172089\n",
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"[ Test epoch: 8 ]\n",
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"Total average test accuarcy: 0.8066\n",
"Total average test loss: 0.0055959536910057065\n",
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"Time elapsed: 588.6080222129822\n",
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"[ Train epoch: 9 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.8828125\n",
"Current batch average train loss: 0.0027854160871356726\n",
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"Current batch average train accuracy: 0.8125\n",
"Current batch average train loss: 0.004375057760626078\n",
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"Current batch average train accuracy: 0.875\n",
"Current batch average train loss: 0.00284283934161067\n",
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"Current batch average train accuracy: 0.828125\n",
"Current batch average train loss: 0.004386452957987785\n",
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"Total average train accuarcy: 0.84166\n",
"Total average train loss: 0.0035957751268148423\n",
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"[ Test epoch: 9 ]\n",
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"Total average test accuarcy: 0.8228\n",
"Total average test loss: 0.005224220591783523\n",
"Model Saved!\n",
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"Time elapsed: 654.1568324565887\n",
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"[ Train epoch: 10 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.8359375\n",
"Current batch average train loss: 0.0039001505356281996\n",
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"Current batch average train loss: 0.0030613895505666733\n",
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"Current batch average train accuracy: 0.8203125\n",
"Current batch average train loss: 0.0034247678704559803\n",
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"Current batch average train accuracy: 0.8828125\n",
"Current batch average train loss: 0.0028981794603168964\n",
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"Total average train accuarcy: 0.84958\n",
"Total average train loss: 0.0033763435888290406\n",
"\n",
"[ Test epoch: 10 ]\n",
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"Total average test accuarcy: 0.8211\n",
"Total average test loss: 0.005217667061090469\n",
"Model Saved!\n",
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"Time elapsed: 719.7141706943512\n",
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"[ Train epoch: 11 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.890625\n",
"Current batch average train loss: 0.0032007344998419285\n",
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"Current batch average train loss: 0.003097456879913807\n",
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"Current batch average train accuracy: 0.8671875\n",
"Current batch average train loss: 0.0030325788538903\n",
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"Current batch average train accuracy: 0.8359375\n",
"Current batch average train loss: 0.004001395311206579\n",
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"Total average train accuarcy: 0.86186\n",
"Total average train loss: 0.003141398875117302\n",
"\n",
"[ Test epoch: 11 ]\n",
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"Total average test accuarcy: 0.7683\n",
"Total average test loss: 0.007266859716176986\n",
"Model Saved!\n",
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"Time elapsed: 785.2830169200897\n",
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"[ Train epoch: 12 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.8671875\n",
"Current batch average train loss: 0.0036921673454344273\n",
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"Current batch average train loss: 0.0037094030994921923\n",
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"Current batch average train accuracy: 0.8671875\n",
"Current batch average train loss: 0.003164077177643776\n",
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"Current batch average train accuracy: 0.796875\n",
"Current batch average train loss: 0.00428383145481348\n",
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"Total average train accuarcy: 0.86696\n",
"Total average train loss: 0.0029882738092541694\n",
"\n",
"[ Test epoch: 12 ]\n",
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"Total average test accuarcy: 0.8224\n",
"Total average test loss: 0.005246723374724388\n",
"Model Saved!\n",
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"Time elapsed: 850.6815376281738\n",
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"[ Train epoch: 13 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.8203125\n",
"Current batch average train loss: 0.003898496273905039\n",
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"Current batch average train loss: 0.0032388463150709867\n",
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"Current batch average train accuracy: 0.84375\n",
"Current batch average train loss: 0.003105225507169962\n",
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"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.002020275918766856\n",
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"Total average train accuarcy: 0.87484\n",
"Total average train loss: 0.002844099721312523\n",
"\n",
"[ Test epoch: 13 ]\n",
"\n",
"Total average test accuarcy: 0.8367\n",
"Total average test loss: 0.00512024128139019\n",
"Model Saved!\n",
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"Time elapsed: 915.9439511299133\n",
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"[ Train epoch: 14 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.90625\n",
"Current batch average train loss: 0.002521915128454566\n",
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"Current batch average train accuracy: 0.8515625\n",
"Current batch average train loss: 0.003154273144900799\n",
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"Current batch average train accuracy: 0.8828125\n",
"Current batch average train loss: 0.0024940362200140953\n",
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"Current batch average train accuracy: 0.90625\n",
"Current batch average train loss: 0.0024035638198256493\n",
"\n",
"Total average train accuarcy: 0.87962\n",
"Total average train loss: 0.002715751133561134\n",
"\n",
"[ Test epoch: 14 ]\n",
"\n",
"Total average test accuarcy: 0.8002\n",
"Total average test loss: 0.005981730431318283\n",
"Model Saved!\n",
"\n",
"Time elapsed: 981.3776617050171\n",
"\n",
"[ Train epoch: 15 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.859375\n",
"Current batch average train loss: 0.0037457605358213186\n",
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"Current batch average train loss: 0.002773375017568469\n",
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"Current batch average train accuracy: 0.8671875\n",
"Current batch average train loss: 0.0027577450964599848\n",
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"Current batch: 300\n",
"Current batch average train accuracy: 0.8515625\n",
"Current batch average train loss: 0.0030494278762489557\n",
"\n",
"Total average train accuarcy: 0.88214\n",
"Total average train loss: 0.0026384240517020228\n",
"\n",
"[ Test epoch: 15 ]\n",
"\n",
"Total average test accuarcy: 0.828\n",
"Total average test loss: 0.005358910104632378\n",
"Model Saved!\n",
"\n",
"Time elapsed: 1046.6485683918\n",
"\n",
"[ Train epoch: 16 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.8515625\n",
"Current batch average train loss: 0.0029790359549224377\n",
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"Current batch average train loss: 0.001990638906136155\n",
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"Current batch average train accuracy: 0.875\n",
"Current batch average train loss: 0.0023590491618961096\n",
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"Current batch: 300\n",
"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0021737031638622284\n",
"\n",
"Total average train accuarcy: 0.88986\n",
"Total average train loss: 0.0024933928084373475\n",
"\n",
"[ Test epoch: 16 ]\n",
"\n",
"Total average test accuarcy: 0.829\n",
"Total average test loss: 0.005160576257109642\n",
"Model Saved!\n",
"\n",
"Time elapsed: 1111.816444158554\n",
"\n",
"[ Train epoch: 17 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.890625\n",
"Current batch average train loss: 0.002262494759634137\n",
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"Current batch average train loss: 0.0017740479670464993\n",
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"Current batch average train accuracy: 0.90625\n",
"Current batch average train loss: 0.0019647746812552214\n",
"\n",
"Current batch: 300\n",
"Current batch average train accuracy: 0.828125\n",
"Current batch average train loss: 0.0032664199825376272\n",
"\n",
"Total average train accuarcy: 0.89062\n",
"Total average train loss: 0.0024637141755223272\n",
"\n",
"[ Test epoch: 17 ]\n",
"\n",
"Total average test accuarcy: 0.8025\n",
"Total average test loss: 0.005894530060887337\n",
"Model Saved!\n",
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"Time elapsed: 1176.9801044464111\n",
"\n",
"[ Train epoch: 18 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0017018250655382872\n",
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"Current batch average train loss: 0.002324869390577078\n",
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"Current batch average train accuracy: 0.8671875\n",
"Current batch average train loss: 0.0028680097311735153\n",
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"Current batch average train accuracy: 0.8984375\n",
"Current batch average train loss: 0.002435174537822604\n",
"\n",
"Total average train accuarcy: 0.89526\n",
"Total average train loss: 0.0023731366169452667\n",
"\n",
"[ Test epoch: 18 ]\n",
"\n",
"Total average test accuarcy: 0.7885\n",
"Total average test loss: 0.007160867366194725\n",
"Model Saved!\n",
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"Time elapsed: 1242.2385549545288\n",
"\n",
"[ Train epoch: 19 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.890625\n",
"Current batch average train loss: 0.0023944915737956762\n",
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"Current batch average train loss: 0.002863684669137001\n",
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"Current batch average train loss: 0.002352365292608738\n",
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"Current batch average train accuracy: 0.890625\n",
"Current batch average train loss: 0.002593992743641138\n",
"\n",
"Total average train accuarcy: 0.8965\n",
"Total average train loss: 0.0023254797396063806\n",
"\n",
"[ Test epoch: 19 ]\n",
"\n",
"Total average test accuarcy: 0.8558\n",
"Total average test loss: 0.004390507641434669\n",
"Model Saved!\n",
"\n",
"Time elapsed: 1307.2592754364014\n",
"\n",
"[ Train epoch: 20 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9140625\n",
"Current batch average train loss: 0.0022075774613767862\n",
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"Current batch average train loss: 0.0030193168204277754\n",
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"Current batch average train loss: 0.003226758213713765\n",
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"Current batch average train accuracy: 0.90625\n",
"Current batch average train loss: 0.002304562134668231\n",
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"Total average train accuarcy: 0.90244\n",
"Total average train loss: 0.002222392808943987\n",
"\n",
"[ Test epoch: 20 ]\n",
"\n",
"Total average test accuarcy: 0.8286\n",
"Total average test loss: 0.005180907422304154\n",
"Model Saved!\n",
"\n",
"Time elapsed: 1372.4084281921387\n",
"\n",
"[ Train epoch: 21 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0017990306951105595\n",
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"Current batch average train loss: 0.0016074628802016377\n",
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"Current batch average train loss: 0.0024036234244704247\n",
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"Current batch: 300\n",
"Current batch average train accuracy: 0.875\n",
"Current batch average train loss: 0.00265950127504766\n",
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"Total average train accuarcy: 0.90414\n",
"Total average train loss: 0.002183544486761093\n",
"\n",
"[ Test epoch: 21 ]\n",
"\n",
"Total average test accuarcy: 0.8153\n",
"Total average test loss: 0.005904838621616363\n",
"Model Saved!\n",
"\n",
"Time elapsed: 1437.614485502243\n",
"\n",
"[ Train epoch: 22 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0021719729993492365\n",
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"Current batch average train loss: 0.001340333721600473\n",
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"Current batch average train loss: 0.0019369913497939706\n",
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"Current batch average train accuracy: 0.953125\n",
"Current batch average train loss: 0.0019616622012108564\n",
"\n",
"Total average train accuarcy: 0.90342\n",
"Total average train loss: 0.0021502127875387667\n",
"\n",
"[ Test epoch: 22 ]\n",
"\n",
"Total average test accuarcy: 0.8536\n",
"Total average test loss: 0.004661404183506966\n",
"Model Saved!\n",
"\n",
"Time elapsed: 1502.7567431926727\n",
"\n",
"[ Train epoch: 23 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.890625\n",
"Current batch average train loss: 0.0020781485363841057\n",
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"Current batch average train accuracy: 0.8984375\n",
"Current batch average train loss: 0.0024992136750370264\n",
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"Current batch average train accuracy: 0.953125\n",
"Current batch average train loss: 0.0013185242423787713\n",
"\n",
"Total average train accuarcy: 0.90416\n",
"Total average train loss: 0.002141147620677948\n",
"\n",
"[ Test epoch: 23 ]\n",
"\n",
"Total average test accuarcy: 0.8555\n",
"Total average test loss: 0.0044771710097789765\n",
"Model Saved!\n",
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"[ Train epoch: 24 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0017307460075244308\n",
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"Current batch average train loss: 0.00150921824388206\n",
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"Current batch average train accuracy: 0.875\n",
"Current batch average train loss: 0.002602082211524248\n",
"\n",
"Total average train accuarcy: 0.91092\n",
"Total average train loss: 0.0020226946015655996\n",
"\n",
"[ Test epoch: 24 ]\n",
"\n",
"Total average test accuarcy: 0.8452\n",
"Total average test loss: 0.004882140263915062\n",
"Model Saved!\n",
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"\n",
"[ Train epoch: 25 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9375\n",
"Current batch average train loss: 0.001501653459854424\n",
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"Current batch average train loss: 0.0020916899666190147\n",
"\n",
"Total average train accuarcy: 0.91248\n",
"Total average train loss: 0.0019839637617766856\n",
"\n",
"[ Test epoch: 25 ]\n",
"\n",
"Total average test accuarcy: 0.8455\n",
"Total average test loss: 0.004983460000157356\n",
"Model Saved!\n",
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"[ Train epoch: 26 ]\n",
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"Current batch average train accuracy: 0.8984375\n",
"Current batch average train loss: 0.002103193197399378\n",
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"Current batch average train loss: 0.0014048026641830802\n",
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"Total average train accuarcy: 0.91152\n",
"Total average train loss: 0.00199653298124671\n",
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"[ Test epoch: 26 ]\n",
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"Total average test accuarcy: 0.8578\n",
"Total average test loss: 0.00452647288441658\n",
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"[ Train epoch: 27 ]\n",
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"Current batch average train loss: 0.002093350514769554\n",
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"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0017482917755842209\n",
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"Total average train accuarcy: 0.91484\n",
"Total average train loss: 0.0019143124796450139\n",
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"Total average test accuarcy: 0.8377\n",
"Total average test loss: 0.0052340492933988575\n",
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"[ Train epoch: 28 ]\n",
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"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0018023427110165358\n",
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"Current batch average train loss: 0.0015654407907277346\n",
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"Total average train accuarcy: 0.91474\n",
"Total average train loss: 0.0019159259843826294\n",
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"Total average test accuarcy: 0.7742\n",
"Total average test loss: 0.00764937507212162\n",
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"[ Train epoch: 29 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9375\n",
"Current batch average train loss: 0.001464035245589912\n",
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"Current batch average train loss: 0.002150006825104356\n",
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"Total average train loss: 0.0018665560477972032\n",
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"Total average test accuarcy: 0.8484\n",
"Total average test loss: 0.004895528608560562\n",
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"[ Train epoch: 30 ]\n",
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"Current batch average train accuracy: 0.8984375\n",
"Current batch average train loss: 0.0021092428360134363\n",
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"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.001448625116609037\n",
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"Total average train accuarcy: 0.91888\n",
"Total average train loss: 0.0018302061210572719\n",
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"[ Test epoch: 30 ]\n",
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"Total average test accuarcy: 0.8612\n",
"Total average test loss: 0.004394087992608547\n",
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"[ Train epoch: 31 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.890625\n",
"Current batch average train loss: 0.002364915329962969\n",
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"Current batch average train accuracy: 0.9375\n",
"Current batch average train loss: 0.0012464987812563777\n",
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"Total average train accuarcy: 0.92024\n",
"Total average train loss: 0.0018038738970458507\n",
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"[ Test epoch: 31 ]\n",
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"Total average test accuarcy: 0.8828\n",
"Total average test loss: 0.0036856054723262786\n",
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"[ Train epoch: 32 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9375\n",
"Current batch average train loss: 0.0013860393082723022\n",
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"Current batch average train loss: 0.0024778132792562246\n",
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"Current batch average train loss: 0.0013855871511623263\n",
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"Current batch average train accuracy: 0.859375\n",
"Current batch average train loss: 0.002746005542576313\n",
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"Total average train accuarcy: 0.91686\n",
"Total average train loss: 0.0018555175212025643\n",
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"[ Test epoch: 32 ]\n",
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"Total average test accuarcy: 0.8626\n",
"Total average test loss: 0.0043950420618057255\n",
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"[ Train epoch: 33 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0019339118152856827\n",
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"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0017624860629439354\n",
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"Total average train accuarcy: 0.92356\n",
"Total average train loss: 0.001740677943378687\n",
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"[ Test epoch: 33 ]\n",
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"Total average test accuarcy: 0.8524\n",
"Total average test loss: 0.004724253417551517\n",
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"[ Train epoch: 34 ]\n",
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"Current batch average train accuracy: 0.9375\n",
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"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.002248841803520918\n",
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"Current batch average train accuracy: 0.90625\n",
"Current batch average train loss: 0.00206956104375422\n",
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"Total average train accuarcy: 0.92244\n",
"Total average train loss: 0.0017587337781488895\n",
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"[ Test epoch: 34 ]\n",
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"Total average test accuarcy: 0.8292\n",
"Total average test loss: 0.005497554501891136\n",
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"[ Train epoch: 35 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.953125\n",
"Current batch average train loss: 0.0014024014817550778\n",
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"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0018985881470143795\n",
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"Current batch average train accuracy: 0.9140625\n",
"Current batch average train loss: 0.0016227979212999344\n",
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"Total average train accuarcy: 0.92604\n",
"Total average train loss: 0.0016871381083130837\n",
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"[ Test epoch: 35 ]\n",
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"Total average test accuarcy: 0.8724\n",
"Total average test loss: 0.004010023872554302\n",
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"[ Train epoch: 36 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9609375\n",
"Current batch average train loss: 0.0009980658069252968\n",
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"Current batch average train accuracy: 0.9296875\n",
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"Current batch average train accuracy: 0.953125\n",
"Current batch average train loss: 0.0011646565981209278\n",
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"Total average train accuarcy: 0.92296\n",
"Total average train loss: 0.0017400217370688916\n",
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"[ Test epoch: 36 ]\n",
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"Total average test accuarcy: 0.8502\n",
"Total average test loss: 0.0050378815367817876\n",
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"[ Train epoch: 37 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0011731109116226435\n",
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"Current batch average train loss: 0.0013201790861785412\n",
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"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0018244449747726321\n",
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"Total average train accuarcy: 0.92594\n",
"Total average train loss: 0.001677812993824482\n",
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"[ Test epoch: 37 ]\n",
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"Total average test accuarcy: 0.8345\n",
"Total average test loss: 0.00535914953649044\n",
"Model Saved!\n",
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"[ Train epoch: 38 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.921875\n",
"Current batch average train loss: 0.0013010281836614013\n",
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"Current batch average train loss: 0.0016679002437740564\n",
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"Current batch average train accuracy: 0.9375\n",
"Current batch average train loss: 0.0019929504487663507\n",
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"Total average train accuarcy: 0.92656\n",
"Total average train loss: 0.0016688357290625573\n",
"\n",
"[ Test epoch: 38 ]\n",
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"Total average test accuarcy: 0.8556\n",
"Total average test loss: 0.004704334177076817\n",
"Model Saved!\n",
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"[ Train epoch: 39 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9140625\n",
"Current batch average train loss: 0.0019515615422278643\n",
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"Current batch average train accuracy: 0.875\n",
"Current batch average train loss: 0.002013532677665353\n",
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"Current batch average train accuracy: 0.96875\n",
"Current batch average train loss: 0.000849031493999064\n",
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"Current batch average train accuracy: 0.96875\n",
"Current batch average train loss: 0.0009219026542268693\n",
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"Total average train accuarcy: 0.92526\n",
"Total average train loss: 0.001665615183264017\n",
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"[ Test epoch: 39 ]\n",
"\n",
"Total average test accuarcy: 0.821\n",
"Total average test loss: 0.006029051429033279\n",
"Model Saved!\n",
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"[ Train epoch: 40 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.001412225654348731\n",
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"Current batch average train accuracy: 0.9296875\n",
"Current batch average train loss: 0.0018242066726088524\n",
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"Total average train accuarcy: 0.9283\n",
"Total average train loss: 0.0016114952689409256\n",
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"[ Test epoch: 40 ]\n",
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"Total average test accuarcy: 0.8539\n",
"Total average test loss: 0.004685957215726375\n",
"Model Saved!\n",
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"[ Train epoch: 41 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.953125\n",
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"Current batch average train loss: 0.0012640099739655852\n",
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"Current batch average train loss: 0.0015374139184132218\n",
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"Total average train accuarcy: 0.92882\n",
"Total average train loss: 0.001608050260692835\n",
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"[ Test epoch: 41 ]\n",
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"Total average test accuarcy: 0.8605\n",
"Total average test loss: 0.004522820676863193\n",
"Model Saved!\n",
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"[ Train epoch: 42 ]\n",
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"Current batch: 0\n",
"Current batch average train accuracy: 0.921875\n",
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"Current batch average train loss: 0.00204099016264081\n",
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"Total average train accuarcy: 0.92916\n",
"Total average train loss: 0.0016000386282801627\n",
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"[ Test epoch: 42 ]\n",
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"Total average test accuarcy: 0.8326\n",
"Total average test loss: 0.005393351772427559\n",
"Model Saved!\n",
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"[ Train epoch: 43 ]\n",
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"Current batch: 0\n",
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"Total average train accuarcy: 0.92862\n",
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"[ Test epoch: 43 ]\n",
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"Total average test accuarcy: 0.8793\n",
"Total average test loss: 0.00371943289488554\n",
"Model Saved!\n",
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"[ Train epoch: 44 ]\n",
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"Current batch: 0\n",
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"Total average train accuarcy: 0.92844\n",
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"[ Test epoch: 44 ]\n",
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"Total average test accuarcy: 0.8362\n",
"Total average test loss: 0.005563184508681297\n",
"Model Saved!\n",
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"[ Train epoch: 45 ]\n",
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"Current batch: 0\n",
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"Total average train accuarcy: 0.93134\n",
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"[ Test epoch: 45 ]\n",
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"Total average test accuarcy: 0.8846\n",
"Total average test loss: 0.0035636545330286025\n",
"Model Saved!\n",
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"[ Train epoch: 46 ]\n",
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"Current batch: 0\n",
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"Total average train accuarcy: 0.93152\n",
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"[ Test epoch: 46 ]\n",
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"Total average test accuarcy: 0.8814\n",
"Total average test loss: 0.003762340094149113\n",
"Model Saved!\n",
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"[ Train epoch: 47 ]\n",
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"[ Test epoch: 47 ]\n",
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"Total average test accuarcy: 0.827\n",
"Total average test loss: 0.006331878098845482\n",
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"[ Train epoch: 48 ]\n",
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"Current batch average train accuracy: 0.9765625\n",
"Current batch average train loss: 0.0007683882722631097\n",
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"Total average train loss: 0.0015598761312663556\n",
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"[ Test epoch: 48 ]\n",
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"Total average test accuarcy: 0.8674\n",
"Total average test loss: 0.004099275637418032\n",
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"[ Train epoch: 49 ]\n",
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"Current batch average train accuracy: 0.9375\n",
"Current batch average train loss: 0.0011007587891072035\n",
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"Current batch average train loss: 0.001224679290316999\n",
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"Current batch average train loss: 0.001971028745174408\n",
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"Current batch average train loss: 0.001353067927993834\n",
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"Total average test accuarcy: 0.864\n",
"Total average test loss: 0.004339705915749073\n",
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"Current batch average train loss: 0.00047150993486866355\n",
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"Total average test loss: 0.002042439039051533\n",
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"Total average test loss: 0.0020363290250301363\n",
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"Total average test loss: 0.0021123871836811305\n",
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"Total average test accuarcy: 0.9359\n",
"Total average test loss: 0.0020702130291610954\n",
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"Total average test accuarcy: 0.9391\n",
"Total average test loss: 0.002100367146730423\n",
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"Current batch average train loss: 0.00011751160491257906\n",
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"Total average test accuarcy: 0.9392\n",
"Total average test loss: 0.0021456848196685315\n",
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"Current batch average train loss: 8.95843913895078e-05\n",
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"Current batch average train loss: 0.00043348741019144654\n",
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"Total average train accuarcy: 0.99144\n",
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"[ Test epoch: 56 ]\n",
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"Total average test accuarcy: 0.9376\n",
"Total average test loss: 0.0021299052372574807\n",
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"Total average train accuarcy: 0.99272\n",
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"Total average test accuarcy: 0.9386\n",
"Total average test loss: 0.0022005413338541985\n",
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"Total average train accuarcy: 0.99376\n",
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"[ Test epoch: 58 ]\n",
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"Total average test accuarcy: 0.9403\n",
"Total average test loss: 0.002180739787966013\n",
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"[ Train epoch: 59 ]\n",
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"Current batch average train loss: 0.00011011668539140373\n",
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"Total average train accuarcy: 0.9947\n",
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"[ Test epoch: 59 ]\n",
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"Total average test accuarcy: 0.9384\n",
"Total average test loss: 0.0021947781559079884\n",
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"[ Train epoch: 60 ]\n",
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"Current batch average train loss: 0.00011075451038777828\n",
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"Current batch average train loss: 0.00011462959082564339\n",
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"Total average train accuarcy: 0.99514\n",
"Total average train loss: 0.00013222238335292786\n",
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"[ Test epoch: 60 ]\n",
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"Total average test accuarcy: 0.9406\n",
"Total average test loss: 0.0022565451882779596\n",
"Model Saved!\n",
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"[ Train epoch: 61 ]\n",
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"Current batch: 0\n",
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"Current batch average train loss: 0.00011446045391494408\n",
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"Total average train accuarcy: 0.99492\n",
"Total average train loss: 0.00013716669623041526\n",
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"[ Test epoch: 61 ]\n",
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"Total average test accuarcy: 0.9414\n",
"Total average test loss: 0.0022395547054708\n",
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"[ Train epoch: 62 ]\n",
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"Current batch average train accuracy: 0.984375\n",
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"Total average train accuarcy: 0.99566\n",
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"[ Test epoch: 62 ]\n",
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"Total average test accuarcy: 0.9392\n",
"Total average test loss: 0.0022781492352485656\n",
"Model Saved!\n",
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"[ Train epoch: 63 ]\n",
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"Current batch: 0\n",
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"Total average train accuarcy: 0.99638\n",
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"[ Test epoch: 63 ]\n",
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"Total average test accuarcy: 0.9407\n",
"Total average test loss: 0.0022443190429359675\n",
"Model Saved!\n",
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"[ Train epoch: 64 ]\n",
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"[ Test epoch: 64 ]\n",
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"Total average test accuarcy: 0.9404\n",
"Total average test loss: 0.0023166307650506496\n",
"Model Saved!\n",
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"[ Train epoch: 65 ]\n",
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"Total average train accuarcy: 0.99676\n",
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"[ Test epoch: 65 ]\n",
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"Total average test accuarcy: 0.9399\n",
"Total average test loss: 0.0023136275727301835\n",
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"[ Train epoch: 66 ]\n",
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"[ Test epoch: 66 ]\n",
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"Total average test accuarcy: 0.9403\n",
"Total average test loss: 0.0023215581107884644\n",
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"[ Train epoch: 67 ]\n",
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"[ Test epoch: 67 ]\n",
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"Total average test accuarcy: 0.9408\n",
"Total average test loss: 0.0023388460461050272\n",
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"[ Train epoch: 68 ]\n",
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"[ Test epoch: 68 ]\n",
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"Total average test accuarcy: 0.9407\n",
"Total average test loss: 0.0023476215187460186\n",
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"[ Train epoch: 69 ]\n",
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"Total average train accuarcy: 0.9977\n",
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"[ Test epoch: 69 ]\n",
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"Total average test accuarcy: 0.9416\n",
"Total average test loss: 0.0023727605421096087\n",
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"[ Train epoch: 70 ]\n",
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"[ Test epoch: 70 ]\n",
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"Total average test accuarcy: 0.9424\n",
"Total average test loss: 0.002354882015287876\n",
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"[ Train epoch: 71 ]\n",
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"[ Test epoch: 71 ]\n",
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"Total average test accuarcy: 0.943\n",
"Total average test loss: 0.00238575884886086\n",
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"[ Train epoch: 72 ]\n",
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"[ Test epoch: 72 ]\n",
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"Total average test loss: 0.0023606389962136745\n",
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"Total average test accuarcy: 0.9412\n",
"Total average test loss: 0.002456456292793155\n",
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"Total average test loss: 0.002439411482587457\n",
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"[ Train epoch: 75 ]\n",
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"Total average test accuarcy: 0.9426\n",
"Total average test loss: 0.002410224162787199\n",
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"[ Train epoch: 76 ]\n",
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"Total average test accuarcy: 0.942\n",
"Total average test loss: 0.0024041186265647413\n",
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"Total average test accuarcy: 0.9429\n",
"Total average test loss: 0.0023839260559529066\n",
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"Total average test accuarcy: 0.9423\n",
"Total average test loss: 0.002381409988552332\n",
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"Current batch average train loss: 0.00011024356354027987\n",
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"Total average train accuarcy: 0.9986\n",
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"[ Test epoch: 79 ]\n",
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"Total average test accuarcy: 0.942\n",
"Total average test loss: 0.0024244185242801907\n",
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"Total average train accuarcy: 0.99872\n",
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"[ Test epoch: 80 ]\n",
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"Total average test accuarcy: 0.9409\n",
"Total average test loss: 0.0024252258501946925\n",
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"[ Train epoch: 81 ]\n",
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"Total average train accuarcy: 0.99838\n",
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"[ Test epoch: 81 ]\n",
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"Total average test accuarcy: 0.9403\n",
"Total average test loss: 0.0026358227923512457\n",
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"[ Train epoch: 82 ]\n",
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"Total average train accuarcy: 0.99852\n",
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"[ Test epoch: 82 ]\n",
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"Total average test accuarcy: 0.9415\n",
"Total average test loss: 0.0024614011351019142\n",
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"[ Train epoch: 83 ]\n",
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"Total average train accuarcy: 0.99888\n",
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"[ Test epoch: 83 ]\n",
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"Total average test accuarcy: 0.9424\n",
"Total average test loss: 0.002410751759260893\n",
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"[ Train epoch: 84 ]\n",
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"Total average train accuarcy: 0.99886\n",
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"[ Test epoch: 84 ]\n",
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"Total average test accuarcy: 0.9428\n",
"Total average test loss: 0.002411500571668148\n",
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"[ Train epoch: 85 ]\n",
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"Total average train accuarcy: 0.99876\n",
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"[ Test epoch: 85 ]\n",
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"Total average test accuarcy: 0.9431\n",
"Total average test loss: 0.002464181225001812\n",
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"[ Train epoch: 86 ]\n",
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"Total average train accuarcy: 0.9991\n",
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"[ Test epoch: 86 ]\n",
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"Total average test accuarcy: 0.942\n",
"Total average test loss: 0.0024256845619529486\n",
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"[ Train epoch: 87 ]\n",
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"Total average train accuarcy: 0.999\n",
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"[ Test epoch: 87 ]\n",
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"Total average test accuarcy: 0.9435\n",
"Total average test loss: 0.0024585736326873304\n",
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"[ Train epoch: 88 ]\n",
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"[ Test epoch: 88 ]\n",
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"Total average test accuarcy: 0.9418\n",
"Total average test loss: 0.0024409345868974925\n",
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"[ Train epoch: 89 ]\n",
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"[ Test epoch: 89 ]\n",
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"Total average test accuarcy: 0.9418\n",
"Total average test loss: 0.002495967160910368\n",
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"[ Train epoch: 90 ]\n",
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"[ Test epoch: 90 ]\n",
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"Total average test accuarcy: 0.9414\n",
"Total average test loss: 0.0024909209303557874\n",
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"[ Train epoch: 91 ]\n",
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"[ Test epoch: 91 ]\n",
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"Total average test accuarcy: 0.9433\n",
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"[ Train epoch: 92 ]\n",
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"[ Test epoch: 92 ]\n",
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"[ Test epoch: 93 ]\n",
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"Total average test accuarcy: 0.9419\n",
"Total average test loss: 0.0025234534569084643\n",
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"[ Train epoch: 94 ]\n",
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"Total average test loss: 0.002536164590343833\n",
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"Total average test accuarcy: 0.943\n",
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"Total average test accuarcy: 0.9427\n",
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"Total average test accuarcy: 0.9439\n",
"Total average test loss: 0.002466669843904674\n",
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"Total average test accuarcy: 0.9441\n",
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"[ Test epoch: 100 ]\n",
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"Total average test accuarcy: 0.944\n",
"Total average test loss: 0.002318990034982562\n",
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"Total average test accuarcy: 0.9456\n",
"Total average test loss: 0.0023157222032546996\n",
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"[ Train epoch: 102 ]\n",
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"[ Test epoch: 102 ]\n",
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"Total average test accuarcy: 0.9462\n",
"Total average test loss: 0.0023161722268909214\n",
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"[ Test epoch: 103 ]\n",
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"Total average test accuarcy: 0.9462\n",
"Total average test loss: 0.0023164190530776977\n",
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"[ Test epoch: 104 ]\n",
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"Total average test accuarcy: 0.9447\n",
"Total average test loss: 0.0023148644093424083\n",
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"[ Train epoch: 105 ]\n",
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"[ Test epoch: 105 ]\n",
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"Total average test accuarcy: 0.9471\n",
"Total average test loss: 0.0023176269069314004\n",
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"[ Train epoch: 106 ]\n",
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"[ Test epoch: 106 ]\n",
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"Total average test accuarcy: 0.9463\n",
"Total average test loss: 0.002307626076415181\n",
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"[ Train epoch: 107 ]\n",
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"[ Test epoch: 107 ]\n",
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"Total average test accuarcy: 0.9457\n",
"Total average test loss: 0.002321923907101154\n",
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"[ Train epoch: 108 ]\n",
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"[ Test epoch: 108 ]\n",
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"Total average test accuarcy: 0.9454\n",
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"[ Train epoch: 109 ]\n",
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"[ Test epoch: 109 ]\n",
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"Total average test accuarcy: 0.9461\n",
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"[ Train epoch: 110 ]\n",
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"[ Test epoch: 110 ]\n",
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"[ Test epoch: 111 ]\n",
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"Total average test accuarcy: 0.9459\n",
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"[ Train epoch: 112 ]\n",
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"[ Test epoch: 112 ]\n",
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"Total average test accuarcy: 0.946\n",
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"[ Train epoch: 113 ]\n",
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"[ Train epoch: 114 ]\n",
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"[ Test epoch: 115 ]\n",
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"Current batch average train loss: 5.368553047446767e-06\n",
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"Total average train accuarcy: 0.99992\n",
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"\n",
"[ Test epoch: 138 ]\n",
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"Total average test accuarcy: 0.9462\n",
"Total average test loss: 0.0022931552059948443\n",
"Model Saved!\n",
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"[ Train epoch: 139 ]\n",
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"[ Test epoch: 139 ]\n",
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"Total average test accuarcy: 0.9458\n",
"Total average test loss: 0.002283366718143225\n",
"Model Saved!\n",
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"[ Train epoch: 140 ]\n",
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"Total average train accuarcy: 0.99982\n",
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"[ Test epoch: 140 ]\n",
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"Total average test accuarcy: 0.9463\n",
"Total average test loss: 0.0022746375638991595\n",
"Model Saved!\n",
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"[ Train epoch: 141 ]\n",
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"[ Test epoch: 141 ]\n",
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"Total average test accuarcy: 0.9459\n",
"Total average test loss: 0.002298483145236969\n",
"Model Saved!\n",
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"[ Train epoch: 142 ]\n",
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"Total average train accuarcy: 0.99986\n",
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"[ Test epoch: 142 ]\n",
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"Total average test accuarcy: 0.9458\n",
"Total average test loss: 0.002277921028807759\n",
"Model Saved!\n",
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"[ Train epoch: 143 ]\n",
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"Total average train accuarcy: 0.9998\n",
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"[ Test epoch: 143 ]\n",
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"Total average test accuarcy: 0.947\n",
"Total average test loss: 0.0022749586187303067\n",
"Model Saved!\n",
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"[ Train epoch: 144 ]\n",
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"Total average train accuarcy: 0.99992\n",
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"[ Test epoch: 144 ]\n",
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"Total average test accuarcy: 0.9463\n",
"Total average test loss: 0.002293874920532107\n",
"Model Saved!\n",
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"[ Train epoch: 145 ]\n",
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"[ Test epoch: 145 ]\n",
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"Total average test accuarcy: 0.9461\n",
"Total average test loss: 0.0022912001062184574\n",
"Model Saved!\n",
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"[ Train epoch: 146 ]\n",
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"Total average train accuarcy: 0.99988\n",
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"[ Test epoch: 146 ]\n",
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"Total average test accuarcy: 0.9464\n",
"Total average test loss: 0.002263487147912383\n",
"Model Saved!\n",
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"[ Train epoch: 147 ]\n",
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"[ Test epoch: 147 ]\n",
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"Total average test accuarcy: 0.9465\n",
"Total average test loss: 0.0022913724932819603\n",
"Model Saved!\n",
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"[ Train epoch: 148 ]\n",
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"[ Test epoch: 148 ]\n",
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"Total average test accuarcy: 0.946\n",
"Total average test loss: 0.0022807286474853753\n",
"Model Saved!\n",
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"[ Train epoch: 149 ]\n",
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"[ Test epoch: 149 ]\n",
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"Total average test accuarcy: 0.9467\n",
"Total average test loss: 0.002270778361707926\n",
"Model Saved!\n",
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],
"name": "stdout"
}
]
}
]
}