Task3_Federated_Learning.ipynb

{
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    {
      "cell_type": "markdown",
      "id": "3710ba0e",
      "metadata": {
        "id": "3710ba0e"
      },
      "source": [
        "# Import Necessary package"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "84bc6630",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "84bc6630",
        "outputId": "3c8d8faa-28ed-42ca-8f59-c501dbe3596e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Using cuda device\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "import copy\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torchvision\n",
        "import torchvision.transforms as transforms\n",
        "import torch.nn.functional as F\n",
        "import numpy as np\n",
        "from torch.utils.data import Dataset, DataLoader\n",
        "import ssl\n",
        "ssl._create_default_https_context = ssl._create_unverified_context\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
        "print(f\"Using {device} device\")"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "e8ba5f43",
      "metadata": {
        "id": "e8ba5f43"
      },
      "source": [
        "# Define NeuralNetwork"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "3f5844e8",
      "metadata": {
        "id": "3f5844e8"
      },
      "outputs": [],
      "source": [
        "# Task2 Model\n",
        "class NeuralNetwork(nn.Module):\n",
        "    def __init__(self, features):\n",
        "        super(NeuralNetwork, self).__init__()\n",
        "\n",
        "        self.layer1 = nn.Linear(features.shape[1], 256)\n",
        "        self.layer2 = nn.Linear(256, 128)\n",
        "        self.layer3 = nn.Linear(128, 64)\n",
        "        self.output = nn.Linear(64, 4)\n",
        "\n",
        "    def forward(self, x):\n",
        "        y_pred = nn.functional.relu(self.layer1(x))\n",
        "        y_pred = nn.functional.relu(self.layer2(y_pred))\n",
        "        y_pred = nn.functional.relu(self.layer3(y_pred))\n",
        "        y_pred = self.output(y_pred)\n",
        "        return y_pred"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "1cede9a9",
      "metadata": {
        "id": "1cede9a9"
      },
      "source": [
        "# Load Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "id": "20715d35",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 540
        },
        "id": "20715d35",
        "outputId": "ce7d6ccc-49a8-4ec6-9a8b-9bf3539e5396"
      },
      "outputs": [
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              "      <th></th>\n",
              "      <th>number of rooms</th>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const element = document.querySelector('#df-2a78bdb5-fd34-4066-859c-11a92f0b0223');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            "text/plain": [
              "      number of rooms  security level of the community  residence space  \\\n",
              "0                   5                             2.50             2820   \n",
              "1                   2                             1.00             1210   \n",
              "2                   4                             2.50             2200   \n",
              "3                   3                             1.50             1200   \n",
              "4                   3                             1.75             1370   \n",
              "...               ...                              ...              ...   \n",
              "3995                4                             3.50             3840   \n",
              "3996                5                             2.00             2310   \n",
              "3997                4                             2.50             3360   \n",
              "3998                6                             2.50             2640   \n",
              "3999                5                             4.25             6070   \n",
              "\n",
              "      building space  noise level  waterfront  view  air quality level  \\\n",
              "0              67518          2.0           0     0                  3   \n",
              "1               9400          1.0           0     0                  2   \n",
              "2               9397          2.0           0     0                  3   \n",
              "3               9720          1.0           0     0                  4   \n",
              "4               5858          1.0           0     0                  3   \n",
              "...              ...          ...         ...   ...                ...   \n",
              "3995           85728          2.0           0     0                  3   \n",
              "3996           13430          1.5           0     0                  4   \n",
              "3997           22111          2.0           0     0                  3   \n",
              "3998            3680          2.0           0     0                  5   \n",
              "3999          171626          2.0           0     0                  3   \n",
              "\n",
              "      aboveground space   basement space  ...  zip code_WA 98155  \\\n",
              "0                   2820               0  ...                0.0   \n",
              "1                   1210               0  ...                0.0   \n",
              "2                   2200               0  ...                0.0   \n",
              "3                   1200               0  ...                0.0   \n",
              "4                   1370               0  ...                0.0   \n",
              "...                  ...             ...  ...                ...   \n",
              "3995                3840               0  ...                0.0   \n",
              "3996                2310               0  ...                0.0   \n",
              "3997                3360               0  ...                0.0   \n",
              "3998                1760             880  ...                0.0   \n",
              "3999                6070               0  ...                0.0   \n",
              "\n",
              "      zip code_WA 98166  zip code_WA 98168  zip code_WA 98177  \\\n",
              "0                   0.0                0.0                0.0   \n",
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              "4                   0.0                0.0                0.0   \n",
              "...                 ...                ...                ...   \n",
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              "3999                0.0                0.0                0.0   \n",
              "\n",
              "      zip code_WA 98178  zip code_WA 98188  zip code_WA 98198  \\\n",
              "0                   0.0                0.0                0.0   \n",
              "1                   0.0                0.0                0.0   \n",
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              "4                   0.0                0.0                1.0   \n",
              "...                 ...                ...                ...   \n",
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              "3999                0.0                0.0                0.0   \n",
              "\n",
              "      zip code_WA 98199  zip code_WA 98288  zip code_WA 98354  \n",
              "0                   0.0                0.0                0.0  \n",
              "1                   0.0                0.0                0.0  \n",
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              "4                   0.0                0.0                0.0  \n",
              "...                 ...                ...                ...  \n",
              "3995                0.0                0.0                0.0  \n",
              "3996                0.0                0.0                0.0  \n",
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              "3999                0.0                0.0                0.0  \n",
              "\n",
              "[4000 rows x 137 columns]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "df = pd.read_csv(\"/content/sample_data/Train_Data_final.csv\")\n",
        "df['total cost'] = df['total cost'] - 1\n",
        "display(df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "id": "4e8kMMf2PqKF",
      "metadata": {
        "id": "4e8kMMf2PqKF"
      },
      "outputs": [],
      "source": [
        "train_data, test_data = train_test_split(df, test_size=0.2, random_state=42)\n",
        "\n",
        "# Training set\n",
        "train_features = torch.tensor(train_data.drop('total cost', axis=1).values, dtype=torch.float).to(device)\n",
        "train_labels = torch.LongTensor(train_data['total cost'].values).to(device)\n",
        "\n",
        "# Validation set\n",
        "test_features = torch.tensor(test_data.drop('total cost', axis=1).values, dtype=torch.float).to(device)\n",
        "test_labels = torch.LongTensor(test_data['total cost'].values).to(device)\n",
        "\n",
        "train_dataset = torch.utils.data.TensorDataset(train_features,train_labels)\n",
        "test_dataset = torch.utils.data.TensorDataset(test_features,test_labels)\n",
        "# print(train_dataset.target_tensor) "
      ]
    },
    {
      "cell_type": "markdown",
      "id": "5c029182",
      "metadata": {
        "id": "5c029182"
      },
      "source": [
        "# Define the dirichlet distribution function "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "id": "4553d040",
      "metadata": {
        "id": "4553d040"
      },
      "outputs": [],
      "source": [
        "def dirichlet_partition(training_data, testing_data, alpha, user_num):\n",
        "    idxs_train = np.arange(len(training_data))\n",
        "    idxs_valid = np.arange(len(testing_data))\n",
        "\n",
        "    # if hasattr(training_data, 'targets'):\n",
        "    #     labels_train = training_data.targets\n",
        "    #     labels_valid = testing_data.targets\n",
        "    # elif hasattr(training_data, 'img_label'):\n",
        "    #     labels_train = training_data.img_label\n",
        "    #     labels_valid = testing_data.img_label\n",
        "    labels_train = train_labels.detach().cpu().numpy()\n",
        "    labels_valid = test_labels.detach().cpu().numpy()\n",
        "\n",
        "    idxs_labels_train = np.vstack((idxs_train, labels_train))\n",
        "    # print(\"idxs_labels_train 1: \", idxs_labels_train)\n",
        "    idxs_labels_train = idxs_labels_train[:, idxs_labels_train[1,:].argsort()]\n",
        "    # print(\"idxs_labels_train 2: \", idxs_labels_train)\n",
        "    idxs_labels_valid = np.vstack((idxs_valid, labels_valid))\n",
        "    idxs_labels_valid = idxs_labels_valid[:, idxs_labels_valid[1,:].argsort()]\n",
        "\n",
        "    labels = np.unique(labels_train, axis=0)\n",
        "\n",
        "    data_train_dict = data_organize(idxs_labels_train, labels)\n",
        "    # print(\"data_train_dict[0]: \", data_train_dict[0])\n",
        "    # print(\"data_train_dict[9]: \", data_train_dict[9])\n",
        "    data_valid_dict = data_organize(idxs_labels_valid, labels)\n",
        "\n",
        "    data_partition_profile_train = {}\n",
        "    data_partition_profile_valid = {}\n",
        "\n",
        "\n",
        "    for i in range(user_num):\n",
        "        data_partition_profile_train[i] = []\n",
        "        data_partition_profile_valid[i] = []\n",
        "\n",
        "    ## Distribute rest data\n",
        "    for label in data_train_dict:\n",
        "        proportions = np.random.dirichlet(np.repeat(alpha, user_num))\n",
        "        proportions_train = len(data_train_dict[label])*proportions\n",
        "        proportions_valid = len(data_valid_dict[label]) * proportions\n",
        "\n",
        "        for user in data_partition_profile_train:\n",
        "\n",
        "            data_partition_profile_train[user]   \\\n",
        "                = set.union(set(np.random.choice(data_train_dict[label], int(proportions_train[user]) , replace = False)), data_partition_profile_train[user])\n",
        "            data_train_dict[label] = list(set(data_train_dict[label])-data_partition_profile_train[user])\n",
        "\n",
        "\n",
        "            data_partition_profile_valid[user] = set.union(set(\n",
        "                np.random.choice(data_valid_dict[label], int(proportions_valid[user]),\n",
        "                                 replace=False)), data_partition_profile_valid[user])\n",
        "            data_valid_dict[label] = list(set(data_valid_dict[label]) - data_partition_profile_valid[user])\n",
        "\n",
        "\n",
        "        while len(data_train_dict[label]) != 0:\n",
        "            rest_data = data_train_dict[label][0]\n",
        "            user = np.random.randint(0, user_num)\n",
        "            data_partition_profile_train[user].add(rest_data)\n",
        "            data_train_dict[label].remove(rest_data)\n",
        "\n",
        "        while len(data_valid_dict[label]) != 0:\n",
        "            rest_data = data_valid_dict[label][0]\n",
        "            user = np.random.randint(0, user_num)\n",
        "            data_partition_profile_valid[user].add(rest_data)\n",
        "            data_valid_dict[label].remove(rest_data)\n",
        "\n",
        "    for user in data_partition_profile_train:\n",
        "        data_partition_profile_train[user] = list(data_partition_profile_train[user])\n",
        "        data_partition_profile_valid[user] = list(data_partition_profile_valid[user])\n",
        "        np.random.shuffle(data_partition_profile_train[user])\n",
        "        np.random.shuffle(data_partition_profile_valid[user])\n",
        "\n",
        "    return data_partition_profile_train, data_partition_profile_valid\n",
        "\n",
        "\n",
        "def data_organize(idxs_labels, labels):\n",
        "    data_dict = {}\n",
        "\n",
        "    labels = np.unique(labels, axis=0)\n",
        "    for one in labels:\n",
        "        data_dict[one] = []\n",
        "\n",
        "    for i in range(len(idxs_labels[1, :])):\n",
        "        data_dict[idxs_labels[1, i]].append(idxs_labels[0, i])\n",
        "    return data_dict\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "id": "443f00e3",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "443f00e3",
        "outputId": "193388d5-0fcb-4c7e-8581-b8c292941fc6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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503, 1959, 2790, 1584, 398, 325, 3175, 23, 2283, 1241, 1646, 2669, 1406, 1775, 2710, 1855, 2880, 926, 191, 1946, 585, 2120, 2845, 2938, 181, 2798, 2242, 586, 2740, 98, 612, 133, 1087, 2973, 2215, 2913, 377, 2517, 1063, 2952, 2780, 490, 52, 2883, 169, 2100, 703, 1021, 383, 2949, 1377, 2481, 1217, 2878, 3107, 2971, 957, 934, 2056, 939, 871, 2781, 1500, 3127, 574, 1884, 427, 2233, 306, 2951, 635, 1514, 1835, 484, 725, 3126, 2541, 2372, 2230, 3029, 3109, 1408, 1506, 132, 637, 1131, 2588, 219, 2435, 2842, 1995, 2063, 1509, 1316, 1651, 1658, 1444, 556, 1784, 1930, 65, 2130, 2915, 1522, 1577, 1395, 859, 1430, 2675, 2775, 2177, 537, 248, 590, 2859, 2414, 1009, 2154, 1705, 1982, 114, 2891, 2992, 2941, 1554, 3027, 1812, 1785, 1727, 1051, 42, 1197, 2749, 997, 2129, 2535, 1664, 1165, 1352, 2899, 2993, 412, 489, 2126, 2210, 3144, 942, 323, 2785, 85, 1627, 1239, 1814, 2558, 2121, 2592, 1805, 2840, 2759, 1575, 3156, 1213, 2296, 41, 1458, 1870, 2295, 1275, 576, 1439, 2887, 1825, 2922, 1906, 103, 798, 123, 430, 358, 620, 2227, 296, 1397, 2381, 1463, 1023, 2351, 2017, 2084, 160, 1970, 988, 3089, 1956, 259, 3017, 2024, 3051, 1589, 2152, 3025, 505, 2540, 3180, 109, 2375, 1534, 2939, 1770, 1867, 589, 339, 921, 552, 2680, 1819, 1978, 731, 1248, 168, 271, 3074, 3115, 36, 2862, 1742, 2415, 802, 3072, 167, 435, 2345, 1981, 1045, 509, 82, 3044, 1562, 1889, 1583, 176, 2370, 2866, 3167, 563, 3119, 1053, 621, 2668, 1055, 2246, 2307, 2069, 1201, 730, 2748, 684, 1308, 977, 2182, 2040, 1585, 1333, 2181, 538, 301, 2698, 3062, 1160, 758, 381, 1118, 2457, 1413, 1002, 2187, 2399, 2446, 794, 2360, 2000, 2124, 1987, 2895, 2969, 2094, 410, 2489, 2769, 444, 1442, 2646, 2512, 1919, 1334, 2511, 224, 2475, 3042, 1614, 2604, 462, 2582, 2237, 1338, 2016, 675, 1159, 440, 2011, 551, 1844, 1414, 3046, 1856, 2236, 270, 3011, 1271, 276, 171, 2870, 3028, 2929, 1389, 228, 501, 1498, 3110, 22, 83, 768, 331, 286, 2881, 649, 2812, 416, 2002, 1060, 3091, 1872, 1059, 832, 663, 2545, 1994, 492, 33, 1538, 1311, 262, 1176, 332, 1718, 3083, 2894, 615, 606, 2161, 343, 2298, 670, 432, 2164, 1515, 2390, 3057, 1151, 2253, 1886, 1890, 2912, 1830, 918, 2406, 1033, 2135, 1037, 92, 2835, 2128, 284, 1198, 2678, 849, 2445, 2935, 2502, 1778, 982, 665, 1613, 2293, 227, 2994, 1370, 2548, 699, 3032, 2385, 3041, 3185, 2658, 283, 1337, 1068, 1104, 1947, 1290, 2803, 688, 2542, 1949, 463, 2265, 2287, 2722, 90]\n"
          ]
        }
      ],
      "source": [
        "user_num = 4\n",
        "alpha = 9\n",
        "train_index, test_index = dirichlet_partition(train_dataset,test_dataset, alpha=alpha, user_num=user_num)\n",
        "print(\"train_index[0]：\", train_index[0])\n",
        "print(\"train_index[1]：\", train_index[1])\n",
        "print(\"train_index[2]：\", train_index[2])\n",
        "print(\"train_index[3]：\", train_index[3])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "id": "daf6fc1d",
      "metadata": {
        "id": "daf6fc1d"
      },
      "outputs": [],
      "source": [
        "class DatasetSplit(Dataset):\n",
        "    \"\"\"An abstract Dataset class wrapped around Pytorch Dataset class.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self, dataset, idxs):\n",
        "        self.dataset = dataset\n",
        "        self.idxs = [int(i) for i in idxs]\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.idxs)\n",
        "\n",
        "    def __getitem__(self, item):\n",
        "        data, label = self.dataset[self.idxs[item]]\n",
        "        return data,label\n",
        "    \n",
        "train_data_list = []\n",
        "for user_index in range(user_num):\n",
        "    train_data_list.append(DatasetSplit(train_dataset, train_index[user_index]))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "id": "bd802bf8",
      "metadata": {
        "id": "bd802bf8"
      },
      "outputs": [],
      "source": [
        "batch_size = 4000\n",
        "\n",
        "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
        "global_model = NeuralNetwork(train_features).to(device)\n",
        "train_loader = DataLoader(train_dataset,batch_size = batch_size)\n",
        "test_loader = DataLoader(test_dataset,batch_size=batch_size)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "c4c11aaf",
      "metadata": {
        "id": "c4c11aaf"
      },
      "source": [
        "# Local Training function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "id": "080e83e6",
      "metadata": {
        "id": "080e83e6"
      },
      "outputs": [],
      "source": [
        "def local_trainer(dataset, model, global_round, device, local_epoch,batchsize):\n",
        "\n",
        "    dataloader = DataLoader(dataset,batch_size=batchsize)\n",
        "    criterion = nn.CrossEntropyLoss().to(device)\n",
        "    model.train()\n",
        "    epoch_loss = []\n",
        "    optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\n",
        "    for iter in range(local_epoch):\n",
        "        batch_loss = []\n",
        "        for batch_idx, (datas, labels) in enumerate(dataloader):\n",
        "            datas, labels = datas.to(device), labels.to(device)\n",
        "            model.zero_grad()\n",
        "            logits = model(datas)\n",
        "            loss = criterion(logits, labels)\n",
        "            loss.backward()\n",
        "            optimizer.step()\n",
        "\n",
        "            if batch_idx % 10 == 0:\n",
        "                print('| Global Round : {} | Local Epoch : {} | [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
        "                    global_round, iter, batch_idx * len(datas),\n",
        "                    len(dataloader.dataset),\n",
        "                    100. * batch_idx / len(dataloader), loss.item()))\n",
        "            batch_loss.append(loss.item())\n",
        "        epoch_loss.append(sum(batch_loss)/len(batch_loss))\n",
        "    return model.state_dict(), sum(epoch_loss) / len(epoch_loss)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "id": "58f22cbf",
      "metadata": {
        "id": "58f22cbf"
      },
      "outputs": [],
      "source": [
        "def inference(model, testloader):\n",
        "    \"\"\" Returns the inference accuracy and loss.\n",
        "    \"\"\"\n",
        "    model.eval()\n",
        "    criterion = nn.CrossEntropyLoss().to(device)\n",
        "    loss, total, correct = 0.0, 0.0, 0.0\n",
        "    for batch_idx, (datas, labels) in enumerate(testloader):\n",
        "        datas, labels = datas.to(device), labels.to(device)\n",
        "        # Inference\n",
        "        outputs = model(datas)\n",
        "        batch_loss = criterion(outputs, labels)\n",
        "        loss += batch_loss.item()\n",
        "\n",
        "        # Prediction\n",
        "        _, pred_labels = torch.max(outputs, 1)\n",
        "        pred_labels = pred_labels.view(-1)\n",
        "        correct += torch.sum(torch.eq(pred_labels, labels)).item()\n",
        "        total += len(labels)\n",
        "    loss /= (batch_idx+1)\n",
        "    accuracy = correct/total\n",
        "    return accuracy, loss"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "id": "e30ed483",
      "metadata": {
        "id": "e30ed483"
      },
      "outputs": [],
      "source": [
        "def average_weights(w):\n",
        "    \"\"\"\n",
        "    Returns the average of the weights.\n",
        "    \"\"\"\n",
        "    w_avg = copy.deepcopy(w[0])\n",
        "    for key in w_avg.keys():\n",
        "        for i in range(1, len(w)):\n",
        "            w_avg[key] += w[i][key]\n",
        "        w_avg[key] = torch.div(w_avg[key].float(), len(w))\n",
        "    return w_avg"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "id": "17ebcb19",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "17ebcb19",
        "outputId": "12711149-2331-4b6a-a584-17b3708dc785"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[1;30;43m流式输出内容被截断，只能显示最后 5000 行内容。\u001b[0m\n",
            "| Global Round : 37 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.768856\n",
            "| Global Round : 37 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.760565\n",
            "| Global Round : 37 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.756331\n",
            "| Global Round : 37 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.748724\n",
            "| Global Round : 37 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.737556\n",
            "| Global Round : 37 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.723224\n",
            "| Global Round : 37 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.710188\n",
            "| Global Round : 37 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.699184\n",
            "| Global Round : 37 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.691353\n",
            "| Global Round : 37 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.682966\n",
            "| Global Round : 37 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.676744\n",
            "| Global Round : 37 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.670046\n",
            "| Global Round : 37 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.663943\n",
            "| Global Round : 37 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.658541\n",
            "| Global Round : 37 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.654725\n",
            "| Global Round : 37 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.650461\n",
            "| Global Round : 37 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.645103\n",
            "| Global Round : 37 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.638590\n",
            "| Global Round : 37 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.629995\n",
            "| Global Round : 37 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.621044\n",
            "| Global Round : 37 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.615490\n",
            "| Global Round : 37 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.610710\n",
            "| Global Round : 37 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.606110\n",
            "| Global Round : 37 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.601142\n",
            "| Global Round : 37 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.595183\n",
            "| Global Round : 37 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.588957\n",
            "| Global Round : 37 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.583057\n",
            "| Global Round : 37 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.578885\n",
            "| Global Round : 37 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.579841\n",
            "| Global Round : 37 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.569558\n",
            "| Global Round : 37 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.559383\n",
            "| Global Round : 37 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.558079\n",
            "| Global Round : 37 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.551397\n",
            "| Global Round : 37 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.543503\n",
            "| Global Round : 37 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.539968\n",
            "| Global Round : 37 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.536632\n",
            "| Global Round : 37 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.532229\n",
            "| Global Round : 37 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.525936\n",
            "| Global Round : 37 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.523881\n",
            "| Global Round : 37 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.523562\n",
            "| Global Round : 37 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.517067\n",
            "| Global Round : 37 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.512037\n",
            "| Global Round : 37 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.512632\n",
            "| Global Round : 37 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.515083\n",
            "| Global Round : 37 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.503074\n",
            "| Global Round : 37 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.502534\n",
            "| Global Round : 37 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.507534\n",
            "| Global Round : 37 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.494346\n",
            "| Global Round : 37 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.488182\n",
            "| Global Round : 37 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.489488\n",
            "| Global Round : 37 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.487927\n",
            "| Global Round : 37 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.489119\n",
            "| Global Round : 37 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.482121\n",
            "| Global Round : 37 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.488819\n",
            "| Global Round : 37 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.476463\n",
            "| Global Round : 37 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.485021\n",
            "| Global Round : 37 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.480006\n",
            "| Global Round : 37 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.502062\n",
            "| Global Round : 37 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.463129\n",
            "| Global Round : 37 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.455215\n",
            "| Global Round : 37 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.456087\n",
            "| Global Round : 37 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.470029\n",
            "| Global Round : 37 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.513941\n",
            "| Global Round : 37 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.449353\n",
            "| Global Round : 37 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.461949\n",
            "| Global Round : 37 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.545599\n",
            "| Global Round : 37 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.449160\n",
            "| Global Round : 37 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.633730\n",
            "| Global Round : 37 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.737936\n",
            "| Global Round : 37 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.777546\n",
            "| Global Round : 37 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.477569\n",
            "| Global Round : 37 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.936986\n",
            "| Global Round : 37 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.538129\n",
            "| Global Round : 37 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.783279\n",
            "| Global Round : 37 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.809420\n",
            "| Global Round : 37 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.741015\n",
            "| Global Round : 37 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.714996\n",
            "| Global Round : 37 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.288030\n",
            "| Global Round : 37 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 1.174260\n",
            "| Global Round : 37 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 0.998364\n",
            "| Global Round : 37 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.814469\n",
            "| Global Round : 37 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 0.947964\n",
            "| Global Round : 37 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 0.960604\n",
            "| Global Round : 37 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.856994\n",
            "| Global Round : 37 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.845795\n",
            "| Global Round : 37 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.848637\n",
            "| Global Round : 37 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.761820\n",
            "| Global Round : 37 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.773132\n",
            "| Global Round : 37 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.770188\n",
            "| Global Round : 37 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.744124\n",
            "| Global Round : 37 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.748535\n",
            "| Global Round : 37 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.769407\n",
            "| Global Round : 37 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.742290\n",
            "| Global Round : 37 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.730186\n",
            "| Global Round : 37 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.732746\n",
            "| Global Round : 37 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.712942\n",
            "| Global Round : 37 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.693590\n",
            "| Global Round : 37 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.707666\n",
            "| Global Round : 37 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.686707\n",
            "| Global Round : 37 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.679925\n",
            "| Global Round : 37 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.680753\n",
            "| Global Round : 37 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.664005\n",
            "| Global Round : 37 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.664424\n",
            "| Global Round : 37 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.656249\n",
            "| Global Round : 37 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.638625\n",
            "| Global Round : 37 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.638919\n",
            "| Global Round : 37 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.623241\n",
            "| Global Round : 37 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.629622\n",
            "| Global Round : 37 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.610375\n",
            "| Global Round : 37 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.612719\n",
            "| Global Round : 37 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.597216\n",
            "| Global Round : 37 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.602308\n",
            "| Global Round : 37 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.591782\n",
            "| Global Round : 37 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.587634\n",
            "| Global Round : 37 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.580322\n",
            "| Global Round : 37 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.569854\n",
            "| Global Round : 37 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.571009\n",
            "| Global Round : 37 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.560870\n",
            "| Global Round : 37 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.569830\n",
            "| Global Round : 37 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.581356\n",
            "| Global Round : 37 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.605347\n",
            "| Global Round : 37 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.550661\n",
            "| Global Round : 37 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.592436\n",
            "| Global Round : 37 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.625123\n",
            "| Global Round : 37 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.563375\n",
            "| Global Round : 37 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.695385\n",
            "| Global Round : 37 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.694902\n",
            "| Global Round : 37 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.697946\n",
            "| Global Round : 37 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.575522\n",
            "| Global Round : 37 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.620128\n",
            "| Global Round : 37 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.633300\n",
            "| Global Round : 37 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.656330\n",
            "| Global Round : 37 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.542602\n",
            "| Global Round : 37 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.707681\n",
            "| Global Round : 37 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.597791\n",
            "| Global Round : 37 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.695248\n",
            "| Global Round : 37 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.564574\n",
            "| Global Round : 37 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.654828\n",
            "| Global Round : 37 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.546349\n",
            "| Global Round : 37 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.589477\n",
            "| Global Round : 37 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.578575\n",
            "| Global Round : 37 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.545726\n",
            "| Global Round : 37 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.690250\n",
            "| Global Round : 37 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.537562\n",
            "| Global Round : 37 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.567263\n",
            "| Global Round : 37 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.565646\n",
            "| Global Round : 37 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.563671\n",
            "| Global Round : 37 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.567446\n",
            "| Global Round : 37 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.556319\n",
            "| Global Round : 37 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.565895\n",
            "| Global Round : 37 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.554608\n",
            "| Global Round : 37 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.559404\n",
            "| Global Round : 37 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.546809\n",
            "| Global Round : 37 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.549034\n",
            "| Global Round : 37 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.538456\n",
            "| Global Round : 37 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.536315\n",
            "| Global Round : 37 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.533808\n",
            "| Global Round : 37 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.524050\n",
            "| Global Round : 37 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.537485\n",
            "| Global Round : 37 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.517688\n",
            "| Global Round : 37 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.525576\n",
            "| Global Round : 37 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.523384\n",
            "| Global Round : 37 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.515587\n",
            "| Global Round : 37 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.525645\n",
            "| Global Round : 37 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.511530\n",
            "| Global Round : 37 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.513902\n",
            "| Global Round : 37 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.512044\n",
            "| Global Round : 37 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.506256\n",
            "| Global Round : 37 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.511153\n",
            "| Global Round : 37 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.500682\n",
            "| Global Round : 37 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.498428\n",
            "| Global Round : 37 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.499198\n",
            "| Global Round : 37 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.497445\n",
            "| Global Round : 37 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.493095\n",
            "Global Round :37, the training accuracy is 60.6%, and the training loss is 0.877.\n",
            "Global Round :37, the testing accuracy is 56.5%, and the testing loss is 1.36.\n",
            "| Global Round : 38 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.906380\n",
            "| Global Round : 38 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 13.746189\n",
            "| Global Round : 38 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.870306\n",
            "| Global Round : 38 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 1.480964\n",
            "| Global Round : 38 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 2.386618\n",
            "| Global Round : 38 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 2.836622\n",
            "| Global Round : 38 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 2.994749\n",
            "| Global Round : 38 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 2.954831\n",
            "| Global Round : 38 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 2.629056\n",
            "| Global Round : 38 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 2.140036\n",
            "| Global Round : 38 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 1.694590\n",
            "| Global Round : 38 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 1.374133\n",
            "| Global Round : 38 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 1.168054\n",
            "| Global Round : 38 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 1.086677\n",
            "| Global Round : 38 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 1.096244\n",
            "| Global Round : 38 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 1.142555\n",
            "| Global Round : 38 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 1.156327\n",
            "| Global Round : 38 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 1.107646\n",
            "| Global Round : 38 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 1.022308\n",
            "| Global Round : 38 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.940748\n",
            "| Global Round : 38 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.893062\n",
            "| Global Round : 38 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.885497\n",
            "| Global Round : 38 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.905456\n",
            "| Global Round : 38 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.930127\n",
            "| Global Round : 38 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.939973\n",
            "| Global Round : 38 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.926712\n",
            "| Global Round : 38 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.897220\n",
            "| Global Round : 38 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.865867\n",
            "| Global Round : 38 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.839648\n",
            "| Global Round : 38 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.823053\n",
            "| Global Round : 38 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.814044\n",
            "| Global Round : 38 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.810281\n",
            "| Global Round : 38 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.804451\n",
            "| Global Round : 38 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.795986\n",
            "| Global Round : 38 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.798336\n",
            "| Global Round : 38 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.779716\n",
            "| Global Round : 38 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.766664\n",
            "| Global Round : 38 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.759603\n",
            "| Global Round : 38 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.751619\n",
            "| Global Round : 38 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.743271\n",
            "| Global Round : 38 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.738907\n",
            "| Global Round : 38 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.738560\n",
            "| Global Round : 38 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.734830\n",
            "| Global Round : 38 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.727098\n",
            "| Global Round : 38 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.720593\n",
            "| Global Round : 38 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.714286\n",
            "| Global Round : 38 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.706730\n",
            "| Global Round : 38 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.698433\n",
            "| Global Round : 38 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.694196\n",
            "| Global Round : 38 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.692407\n",
            "| Global Round : 38 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.687392\n",
            "| Global Round : 38 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.684718\n",
            "| Global Round : 38 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.679749\n",
            "| Global Round : 38 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.674329\n",
            "| Global Round : 38 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.671550\n",
            "| Global Round : 38 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.666755\n",
            "| Global Round : 38 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.664391\n",
            "| Global Round : 38 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.661411\n",
            "| Global Round : 38 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.659721\n",
            "| Global Round : 38 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.657027\n",
            "| Global Round : 38 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.654643\n",
            "| Global Round : 38 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.650953\n",
            "| Global Round : 38 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.648635\n",
            "| Global Round : 38 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.645403\n",
            "| Global Round : 38 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.644389\n",
            "| Global Round : 38 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.642062\n",
            "| Global Round : 38 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.640143\n",
            "| Global Round : 38 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.636544\n",
            "| Global Round : 38 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.633701\n",
            "| Global Round : 38 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.630177\n",
            "| Global Round : 38 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.627531\n",
            "| Global Round : 38 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.624406\n",
            "| Global Round : 38 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.621409\n",
            "| Global Round : 38 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.618334\n",
            "| Global Round : 38 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.615126\n",
            "| Global Round : 38 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.611238\n",
            "| Global Round : 38 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.607828\n",
            "| Global Round : 38 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.604471\n",
            "| Global Round : 38 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.601652\n",
            "| Global Round : 38 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.597593\n",
            "| Global Round : 38 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.594546\n",
            "| Global Round : 38 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.590686\n",
            "| Global Round : 38 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.586620\n",
            "| Global Round : 38 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.582123\n",
            "| Global Round : 38 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.577883\n",
            "| Global Round : 38 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.574161\n",
            "| Global Round : 38 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.569450\n",
            "| Global Round : 38 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.564720\n",
            "| Global Round : 38 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.560714\n",
            "| Global Round : 38 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.557143\n",
            "| Global Round : 38 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.555869\n",
            "| Global Round : 38 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.550343\n",
            "| Global Round : 38 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.541301\n",
            "| Global Round : 38 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.537125\n",
            "| Global Round : 38 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.535469\n",
            "| Global Round : 38 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.530596\n",
            "| Global Round : 38 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.524512\n",
            "| Global Round : 38 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.524317\n",
            "| Global Round : 38 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.524606\n",
            "| Global Round : 38 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.517153\n",
            "| Global Round : 38 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.868690\n",
            "| Global Round : 38 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 14.800770\n",
            "| Global Round : 38 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 0.986791\n",
            "| Global Round : 38 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.312135\n",
            "| Global Round : 38 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.956102\n",
            "| Global Round : 38 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 2.305909\n",
            "| Global Round : 38 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 2.613220\n",
            "| Global Round : 38 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 2.702154\n",
            "| Global Round : 38 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 2.408889\n",
            "| Global Round : 38 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 1.937372\n",
            "| Global Round : 38 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 1.729980\n",
            "| Global Round : 38 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 1.610784\n",
            "| Global Round : 38 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 1.483297\n",
            "| Global Round : 38 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 1.387095\n",
            "| Global Round : 38 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 1.289337\n",
            "| Global Round : 38 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 1.187956\n",
            "| Global Round : 38 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 1.088324\n",
            "| Global Round : 38 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 1.010611\n",
            "| Global Round : 38 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.981128\n",
            "| Global Round : 38 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 1.010831\n",
            "| Global Round : 38 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 1.052018\n",
            "| Global Round : 38 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 1.031437\n",
            "| Global Round : 38 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.974510\n",
            "| Global Round : 38 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.929887\n",
            "| Global Round : 38 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.913381\n",
            "| Global Round : 38 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.908724\n",
            "| Global Round : 38 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.900149\n",
            "| Global Round : 38 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.887634\n",
            "| Global Round : 38 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.872975\n",
            "| Global Round : 38 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.858557\n",
            "| Global Round : 38 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.846926\n",
            "| Global Round : 38 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.832361\n",
            "| Global Round : 38 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.825060\n",
            "| Global Round : 38 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.818335\n",
            "| Global Round : 38 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.812064\n",
            "| Global Round : 38 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.806985\n",
            "| Global Round : 38 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.802137\n",
            "| Global Round : 38 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.797276\n",
            "| Global Round : 38 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.793769\n",
            "| Global Round : 38 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.789904\n",
            "| Global Round : 38 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.784361\n",
            "| Global Round : 38 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.779644\n",
            "| Global Round : 38 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.776336\n",
            "| Global Round : 38 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.771085\n",
            "| Global Round : 38 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.766784\n",
            "| Global Round : 38 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.761650\n",
            "| Global Round : 38 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.756205\n",
            "| Global Round : 38 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.749967\n",
            "| Global Round : 38 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.746716\n",
            "| Global Round : 38 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.740565\n",
            "| Global Round : 38 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.738195\n",
            "| Global Round : 38 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.735104\n",
            "| Global Round : 38 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.729686\n",
            "| Global Round : 38 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.724867\n",
            "| Global Round : 38 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.722652\n",
            "| Global Round : 38 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.718054\n",
            "| Global Round : 38 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.715221\n",
            "| Global Round : 38 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.712197\n",
            "| Global Round : 38 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.707435\n",
            "| Global Round : 38 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.704922\n",
            "| Global Round : 38 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.703185\n",
            "| Global Round : 38 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.699299\n",
            "| Global Round : 38 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.697772\n",
            "| Global Round : 38 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.696384\n",
            "| Global Round : 38 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.693672\n",
            "| Global Round : 38 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.691321\n",
            "| Global Round : 38 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.689502\n",
            "| Global Round : 38 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.686743\n",
            "| Global Round : 38 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.685139\n",
            "| Global Round : 38 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.683125\n",
            "| Global Round : 38 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.681414\n",
            "| Global Round : 38 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.679669\n",
            "| Global Round : 38 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.677522\n",
            "| Global Round : 38 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.675207\n",
            "| Global Round : 38 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.673937\n",
            "| Global Round : 38 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.672018\n",
            "| Global Round : 38 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.670883\n",
            "| Global Round : 38 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.668732\n",
            "| Global Round : 38 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.667570\n",
            "| Global Round : 38 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.665691\n",
            "| Global Round : 38 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.664523\n",
            "| Global Round : 38 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.663156\n",
            "| Global Round : 38 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.661271\n",
            "| Global Round : 38 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.659910\n",
            "| Global Round : 38 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.658377\n",
            "| Global Round : 38 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.656980\n",
            "| Global Round : 38 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.655358\n",
            "| Global Round : 38 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.654025\n",
            "| Global Round : 38 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.652526\n",
            "| Global Round : 38 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.650978\n",
            "| Global Round : 38 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.649934\n",
            "| Global Round : 38 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.647770\n",
            "| Global Round : 38 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.646610\n",
            "| Global Round : 38 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.644836\n",
            "| Global Round : 38 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.643068\n",
            "| Global Round : 38 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.641452\n",
            "| Global Round : 38 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.639428\n",
            "| Global Round : 38 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.637469\n",
            "| Global Round : 38 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.635612\n",
            "| Global Round : 38 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.633687\n",
            "| Global Round : 38 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.835824\n",
            "| Global Round : 38 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 13.436623\n",
            "| Global Round : 38 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.951790\n",
            "| Global Round : 38 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 1.365253\n",
            "| Global Round : 38 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 2.157595\n",
            "| Global Round : 38 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 2.588597\n",
            "| Global Round : 38 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 2.818862\n",
            "| Global Round : 38 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 2.792762\n",
            "| Global Round : 38 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 2.487854\n",
            "| Global Round : 38 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 2.193657\n",
            "| Global Round : 38 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 2.035276\n",
            "| Global Round : 38 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 1.938931\n",
            "| Global Round : 38 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 1.826384\n",
            "| Global Round : 38 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 1.628947\n",
            "| Global Round : 38 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 1.406327\n",
            "| Global Round : 38 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 1.211571\n",
            "| Global Round : 38 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 1.060710\n",
            "| Global Round : 38 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.974749\n",
            "| Global Round : 38 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.985691\n",
            "| Global Round : 38 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 1.084707\n",
            "| Global Round : 38 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 1.181139\n",
            "| Global Round : 38 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 1.188140\n",
            "| Global Round : 38 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 1.125151\n",
            "| Global Round : 38 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 1.054507\n",
            "| Global Round : 38 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 1.007245\n",
            "| Global Round : 38 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.976490\n",
            "| Global Round : 38 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.949776\n",
            "| Global Round : 38 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.915144\n",
            "| Global Round : 38 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.878823\n",
            "| Global Round : 38 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.884691\n",
            "| Global Round : 38 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.913389\n",
            "| Global Round : 38 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.896038\n",
            "| Global Round : 38 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.866095\n",
            "| Global Round : 38 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.837627\n",
            "| Global Round : 38 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.819770\n",
            "| Global Round : 38 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.810545\n",
            "| Global Round : 38 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.813099\n",
            "| Global Round : 38 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.811717\n",
            "| Global Round : 38 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.798743\n",
            "| Global Round : 38 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.793954\n",
            "| Global Round : 38 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.770372\n",
            "| Global Round : 38 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.757439\n",
            "| Global Round : 38 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.755758\n",
            "| Global Round : 38 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.758935\n",
            "| Global Round : 38 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.759221\n",
            "| Global Round : 38 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.752490\n",
            "| Global Round : 38 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.740619\n",
            "| Global Round : 38 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.730526\n",
            "| Global Round : 38 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.730311\n",
            "| Global Round : 38 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.728557\n",
            "| Global Round : 38 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.725034\n",
            "| Global Round : 38 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.723181\n",
            "| Global Round : 38 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.716727\n",
            "| Global Round : 38 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.708874\n",
            "| Global Round : 38 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.705841\n",
            "| Global Round : 38 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.703484\n",
            "| Global Round : 38 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.699071\n",
            "| Global Round : 38 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.696196\n",
            "| Global Round : 38 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.692058\n",
            "| Global Round : 38 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.686780\n",
            "| Global Round : 38 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.684280\n",
            "| Global Round : 38 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.681828\n",
            "| Global Round : 38 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.675294\n",
            "| Global Round : 38 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.671243\n",
            "| Global Round : 38 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.669802\n",
            "| Global Round : 38 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.666405\n",
            "| Global Round : 38 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.664039\n",
            "| Global Round : 38 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.658513\n",
            "| Global Round : 38 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.656100\n",
            "| Global Round : 38 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.652776\n",
            "| Global Round : 38 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.651333\n",
            "| Global Round : 38 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.646016\n",
            "| Global Round : 38 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.641727\n",
            "| Global Round : 38 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.636023\n",
            "| Global Round : 38 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.642633\n",
            "| Global Round : 38 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.634653\n",
            "| Global Round : 38 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.635694\n",
            "| Global Round : 38 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.635030\n",
            "| Global Round : 38 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.630183\n",
            "| Global Round : 38 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.628086\n",
            "| Global Round : 38 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.618980\n",
            "| Global Round : 38 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.622960\n",
            "| Global Round : 38 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.619829\n",
            "| Global Round : 38 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.608057\n",
            "| Global Round : 38 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.610183\n",
            "| Global Round : 38 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.598424\n",
            "| Global Round : 38 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.608327\n",
            "| Global Round : 38 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.592433\n",
            "| Global Round : 38 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.597941\n",
            "| Global Round : 38 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.585142\n",
            "| Global Round : 38 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.593617\n",
            "| Global Round : 38 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.579972\n",
            "| Global Round : 38 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.586252\n",
            "| Global Round : 38 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.573142\n",
            "| Global Round : 38 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.582320\n",
            "| Global Round : 38 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.570143\n",
            "| Global Round : 38 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.573068\n",
            "| Global Round : 38 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.561557\n",
            "| Global Round : 38 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.567692\n",
            "| Global Round : 38 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.561696\n",
            "| Global Round : 38 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.897595\n",
            "| Global Round : 38 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 14.569574\n",
            "| Global Round : 38 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.091954\n",
            "| Global Round : 38 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.398180\n",
            "| Global Round : 38 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 2.133656\n",
            "| Global Round : 38 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 2.620381\n",
            "| Global Round : 38 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 2.910604\n",
            "| Global Round : 38 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 2.828270\n",
            "| Global Round : 38 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 2.485547\n",
            "| Global Round : 38 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 2.093811\n",
            "| Global Round : 38 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 1.966015\n",
            "| Global Round : 38 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 1.829984\n",
            "| Global Round : 38 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 1.704794\n",
            "| Global Round : 38 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 1.556799\n",
            "| Global Round : 38 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 1.394732\n",
            "| Global Round : 38 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 1.262735\n",
            "| Global Round : 38 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 1.195873\n",
            "| Global Round : 38 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 1.150556\n",
            "| Global Round : 38 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 1.113262\n",
            "| Global Round : 38 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 1.092467\n",
            "| Global Round : 38 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 1.091483\n",
            "| Global Round : 38 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 1.099443\n",
            "| Global Round : 38 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 1.090609\n",
            "| Global Round : 38 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 1.051625\n",
            "| Global Round : 38 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.994553\n",
            "| Global Round : 38 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.952027\n",
            "| Global Round : 38 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.934197\n",
            "| Global Round : 38 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.938530\n",
            "| Global Round : 38 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.942608\n",
            "| Global Round : 38 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.933429\n",
            "| Global Round : 38 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.922481\n",
            "| Global Round : 38 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.917919\n",
            "| Global Round : 38 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.913508\n",
            "| Global Round : 38 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.902088\n",
            "| Global Round : 38 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.889120\n",
            "| Global Round : 38 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.874832\n",
            "| Global Round : 38 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.861075\n",
            "| Global Round : 38 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.850973\n",
            "| Global Round : 38 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.839033\n",
            "| Global Round : 38 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.826404\n",
            "| Global Round : 38 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.819786\n",
            "| Global Round : 38 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.835017\n",
            "| Global Round : 38 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.829445\n",
            "| Global Round : 38 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.816469\n",
            "| Global Round : 38 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.810936\n",
            "| Global Round : 38 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.808354\n",
            "| Global Round : 38 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.800860\n",
            "| Global Round : 38 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.791022\n",
            "| Global Round : 38 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.783051\n",
            "| Global Round : 38 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.780948\n",
            "| Global Round : 38 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.784278\n",
            "| Global Round : 38 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.782725\n",
            "| Global Round : 38 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.775234\n",
            "| Global Round : 38 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.768581\n",
            "| Global Round : 38 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.765271\n",
            "| Global Round : 38 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.763447\n",
            "| Global Round : 38 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.760620\n",
            "| Global Round : 38 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.756791\n",
            "| Global Round : 38 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.751484\n",
            "| Global Round : 38 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.746290\n",
            "| Global Round : 38 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.744991\n",
            "| Global Round : 38 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.743253\n",
            "| Global Round : 38 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.738931\n",
            "| Global Round : 38 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.734524\n",
            "| Global Round : 38 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.731344\n",
            "| Global Round : 38 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.727944\n",
            "| Global Round : 38 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.725193\n",
            "| Global Round : 38 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.723374\n",
            "| Global Round : 38 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.719549\n",
            "| Global Round : 38 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.717609\n",
            "| Global Round : 38 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.714980\n",
            "| Global Round : 38 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.711563\n",
            "| Global Round : 38 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.709687\n",
            "| Global Round : 38 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.707848\n",
            "| Global Round : 38 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.704750\n",
            "| Global Round : 38 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.702846\n",
            "| Global Round : 38 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.700457\n",
            "| Global Round : 38 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.697558\n",
            "| Global Round : 38 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.695807\n",
            "| Global Round : 38 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.693930\n",
            "| Global Round : 38 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.691245\n",
            "| Global Round : 38 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.688313\n",
            "| Global Round : 38 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.686755\n",
            "| Global Round : 38 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.683709\n",
            "| Global Round : 38 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.681390\n",
            "| Global Round : 38 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.679532\n",
            "| Global Round : 38 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.677024\n",
            "| Global Round : 38 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.674536\n",
            "| Global Round : 38 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.672433\n",
            "| Global Round : 38 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.669808\n",
            "| Global Round : 38 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.668419\n",
            "| Global Round : 38 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.665992\n",
            "| Global Round : 38 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.663068\n",
            "| Global Round : 38 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.661676\n",
            "| Global Round : 38 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.659555\n",
            "| Global Round : 38 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.657566\n",
            "| Global Round : 38 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.654804\n",
            "| Global Round : 38 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.653333\n",
            "| Global Round : 38 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.652103\n",
            "| Global Round : 38 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.652507\n",
            "Global Round :38, the training accuracy is 60.0%, and the training loss is 0.931.\n",
            "Global Round :38, the testing accuracy is 57.1%, and the testing loss is 1.4.\n",
            "| Global Round : 39 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.895124\n",
            "| Global Round : 39 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 1.987041\n",
            "| Global Round : 39 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.850188\n",
            "| Global Round : 39 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 1.235872\n",
            "| Global Round : 39 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 1.373993\n",
            "| Global Round : 39 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 1.253949\n",
            "| Global Round : 39 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 1.088360\n",
            "| Global Round : 39 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 0.989055\n",
            "| Global Round : 39 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 0.960391\n",
            "| Global Round : 39 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.957156\n",
            "| Global Round : 39 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.941966\n",
            "| Global Round : 39 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.907984\n",
            "| Global Round : 39 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.850672\n",
            "| Global Round : 39 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.811348\n",
            "| Global Round : 39 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.812664\n",
            "| Global Round : 39 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.833482\n",
            "| Global Round : 39 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.842665\n",
            "| Global Round : 39 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.824995\n",
            "| Global Round : 39 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.807927\n",
            "| Global Round : 39 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.786386\n",
            "| Global Round : 39 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.770961\n",
            "| Global Round : 39 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.756804\n",
            "| Global Round : 39 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.739234\n",
            "| Global Round : 39 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.723368\n",
            "| Global Round : 39 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.715477\n",
            "| Global Round : 39 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.710890\n",
            "| Global Round : 39 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.706555\n",
            "| Global Round : 39 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.702332\n",
            "| Global Round : 39 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.697096\n",
            "| Global Round : 39 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.687751\n",
            "| Global Round : 39 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.678448\n",
            "| Global Round : 39 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.669308\n",
            "| Global Round : 39 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.657400\n",
            "| Global Round : 39 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.649780\n",
            "| Global Round : 39 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.646692\n",
            "| Global Round : 39 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.636857\n",
            "| Global Round : 39 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.623916\n",
            "| Global Round : 39 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.618011\n",
            "| Global Round : 39 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.602928\n",
            "| Global Round : 39 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.596503\n",
            "| Global Round : 39 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.586257\n",
            "| Global Round : 39 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.576925\n",
            "| Global Round : 39 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.572315\n",
            "| Global Round : 39 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.561341\n",
            "| Global Round : 39 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.561902\n",
            "| Global Round : 39 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.561601\n",
            "| Global Round : 39 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.554523\n",
            "| Global Round : 39 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.530848\n",
            "| Global Round : 39 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.536966\n",
            "| Global Round : 39 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.548135\n",
            "| Global Round : 39 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.546754\n",
            "| Global Round : 39 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.520556\n",
            "| Global Round : 39 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.498787\n",
            "| Global Round : 39 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.514861\n",
            "| Global Round : 39 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.501640\n",
            "| Global Round : 39 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.480768\n",
            "| Global Round : 39 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.481555\n",
            "| Global Round : 39 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.472179\n",
            "| Global Round : 39 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.500381\n",
            "| Global Round : 39 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.542698\n",
            "| Global Round : 39 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.628765\n",
            "| Global Round : 39 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.535791\n",
            "| Global Round : 39 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.469528\n",
            "| Global Round : 39 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.521307\n",
            "| Global Round : 39 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.464266\n",
            "| Global Round : 39 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.501691\n",
            "| Global Round : 39 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.449167\n",
            "| Global Round : 39 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.449756\n",
            "| Global Round : 39 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.487082\n",
            "| Global Round : 39 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.493601\n",
            "| Global Round : 39 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.458193\n",
            "| Global Round : 39 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.407086\n",
            "| Global Round : 39 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.426704\n",
            "| Global Round : 39 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.438183\n",
            "| Global Round : 39 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.401934\n",
            "| Global Round : 39 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.402942\n",
            "| Global Round : 39 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.418728\n",
            "| Global Round : 39 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.406685\n",
            "| Global Round : 39 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.396942\n",
            "| Global Round : 39 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.384869\n",
            "| Global Round : 39 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.384092\n",
            "| Global Round : 39 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.406180\n",
            "| Global Round : 39 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.429716\n",
            "| Global Round : 39 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.496099\n",
            "| Global Round : 39 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.500045\n",
            "| Global Round : 39 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.452323\n",
            "| Global Round : 39 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.396065\n",
            "| Global Round : 39 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.470977\n",
            "| Global Round : 39 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.400419\n",
            "| Global Round : 39 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.411722\n",
            "| Global Round : 39 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.443226\n",
            "| Global Round : 39 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.370457\n",
            "| Global Round : 39 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.400695\n",
            "| Global Round : 39 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.416626\n",
            "| Global Round : 39 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.369426\n",
            "| Global Round : 39 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.374983\n",
            "| Global Round : 39 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.398444\n",
            "| Global Round : 39 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.363723\n",
            "| Global Round : 39 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.370638\n",
            "| Global Round : 39 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.382284\n",
            "| Global Round : 39 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 1.049601\n",
            "| Global Round : 39 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 1.870933\n",
            "| Global Round : 39 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 0.827368\n",
            "| Global Round : 39 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.015090\n",
            "| Global Round : 39 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.066225\n",
            "| Global Round : 39 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 1.057641\n",
            "| Global Round : 39 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.984354\n",
            "| Global Round : 39 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.884262\n",
            "| Global Round : 39 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.859048\n",
            "| Global Round : 39 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.895215\n",
            "| Global Round : 39 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.906174\n",
            "| Global Round : 39 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.873996\n",
            "| Global Round : 39 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.823898\n",
            "| Global Round : 39 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.799381\n",
            "| Global Round : 39 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.811470\n",
            "| Global Round : 39 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.814123\n",
            "| Global Round : 39 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.790078\n",
            "| Global Round : 39 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.771604\n",
            "| Global Round : 39 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.766258\n",
            "| Global Round : 39 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.761626\n",
            "| Global Round : 39 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.749536\n",
            "| Global Round : 39 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.739459\n",
            "| Global Round : 39 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.735186\n",
            "| Global Round : 39 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.718183\n",
            "| Global Round : 39 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.704854\n",
            "| Global Round : 39 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.703538\n",
            "| Global Round : 39 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.701781\n",
            "| Global Round : 39 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.695585\n",
            "| Global Round : 39 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.684614\n",
            "| Global Round : 39 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.672718\n",
            "| Global Round : 39 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.669661\n",
            "| Global Round : 39 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.668070\n",
            "| Global Round : 39 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.662232\n",
            "| Global Round : 39 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.652804\n",
            "| Global Round : 39 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.643694\n",
            "| Global Round : 39 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.641491\n",
            "| Global Round : 39 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.638388\n",
            "| Global Round : 39 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.628312\n",
            "| Global Round : 39 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.620556\n",
            "| Global Round : 39 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.613840\n",
            "| Global Round : 39 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.609514\n",
            "| Global Round : 39 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.619937\n",
            "| Global Round : 39 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.635785\n",
            "| Global Round : 39 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.632280\n",
            "| Global Round : 39 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.586835\n",
            "| Global Round : 39 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.614792\n",
            "| Global Round : 39 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.615801\n",
            "| Global Round : 39 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.573723\n",
            "| Global Round : 39 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.628578\n",
            "| Global Round : 39 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.633237\n",
            "| Global Round : 39 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.566517\n",
            "| Global Round : 39 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.644160\n",
            "| Global Round : 39 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.586594\n",
            "| Global Round : 39 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.590508\n",
            "| Global Round : 39 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.593821\n",
            "| Global Round : 39 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.546521\n",
            "| Global Round : 39 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.591284\n",
            "| Global Round : 39 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.536133\n",
            "| Global Round : 39 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.570111\n",
            "| Global Round : 39 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.554023\n",
            "| Global Round : 39 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.531754\n",
            "| Global Round : 39 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.564164\n",
            "| Global Round : 39 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.521619\n",
            "| Global Round : 39 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.531499\n",
            "| Global Round : 39 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.539353\n",
            "| Global Round : 39 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.506963\n",
            "| Global Round : 39 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.521489\n",
            "| Global Round : 39 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.541702\n",
            "| Global Round : 39 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.528076\n",
            "| Global Round : 39 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.493016\n",
            "| Global Round : 39 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.518970\n",
            "| Global Round : 39 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.528982\n",
            "| Global Round : 39 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.488390\n",
            "| Global Round : 39 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.495957\n",
            "| Global Round : 39 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.539276\n",
            "| Global Round : 39 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.502115\n",
            "| Global Round : 39 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.475281\n",
            "| Global Round : 39 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.484817\n",
            "| Global Round : 39 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.500863\n",
            "| Global Round : 39 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.497208\n",
            "| Global Round : 39 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.468410\n",
            "| Global Round : 39 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.465299\n",
            "| Global Round : 39 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.484510\n",
            "| Global Round : 39 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.491902\n",
            "| Global Round : 39 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.491972\n",
            "| Global Round : 39 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.469370\n",
            "| Global Round : 39 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.453142\n",
            "| Global Round : 39 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.454974\n",
            "| Global Round : 39 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.469464\n",
            "| Global Round : 39 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.481176\n",
            "| Global Round : 39 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.465521\n",
            "| Global Round : 39 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.451863\n",
            "| Global Round : 39 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.439248\n",
            "| Global Round : 39 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.440015\n",
            "| Global Round : 39 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.449754\n",
            "| Global Round : 39 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.461066\n",
            "| Global Round : 39 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.507493\n",
            "| Global Round : 39 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.481831\n",
            "| Global Round : 39 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.446211\n",
            "| Global Round : 39 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.430608\n",
            "| Global Round : 39 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.852694\n",
            "| Global Round : 39 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.573834\n",
            "| Global Round : 39 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.858544\n",
            "| Global Round : 39 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 1.204702\n",
            "| Global Round : 39 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 1.513766\n",
            "| Global Round : 39 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 1.398906\n",
            "| Global Round : 39 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.190539\n",
            "| Global Round : 39 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.072362\n",
            "| Global Round : 39 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.077466\n",
            "| Global Round : 39 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.078130\n",
            "| Global Round : 39 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 1.040320\n",
            "| Global Round : 39 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.976386\n",
            "| Global Round : 39 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.913041\n",
            "| Global Round : 39 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.876829\n",
            "| Global Round : 39 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.870175\n",
            "| Global Round : 39 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.877751\n",
            "| Global Round : 39 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.888259\n",
            "| Global Round : 39 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.890698\n",
            "| Global Round : 39 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.878891\n",
            "| Global Round : 39 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.854595\n",
            "| Global Round : 39 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.832739\n",
            "| Global Round : 39 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.819376\n",
            "| Global Round : 39 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.808369\n",
            "| Global Round : 39 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.783173\n",
            "| Global Round : 39 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.768883\n",
            "| Global Round : 39 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.765105\n",
            "| Global Round : 39 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.753782\n",
            "| Global Round : 39 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.752479\n",
            "| Global Round : 39 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.741852\n",
            "| Global Round : 39 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.738443\n",
            "| Global Round : 39 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.728688\n",
            "| Global Round : 39 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.717166\n",
            "| Global Round : 39 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.711237\n",
            "| Global Round : 39 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.704206\n",
            "| Global Round : 39 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.695353\n",
            "| Global Round : 39 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.687020\n",
            "| Global Round : 39 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.676206\n",
            "| Global Round : 39 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.667583\n",
            "| Global Round : 39 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.662546\n",
            "| Global Round : 39 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.653194\n",
            "| Global Round : 39 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.646749\n",
            "| Global Round : 39 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.640156\n",
            "| Global Round : 39 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.631075\n",
            "| Global Round : 39 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.624011\n",
            "| Global Round : 39 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.615641\n",
            "| Global Round : 39 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.609889\n",
            "| Global Round : 39 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.603950\n",
            "| Global Round : 39 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.597798\n",
            "| Global Round : 39 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.592100\n",
            "| Global Round : 39 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.587720\n",
            "| Global Round : 39 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.581576\n",
            "| Global Round : 39 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.578189\n",
            "| Global Round : 39 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.571389\n",
            "| Global Round : 39 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.567242\n",
            "| Global Round : 39 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.566810\n",
            "| Global Round : 39 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.560879\n",
            "| Global Round : 39 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.558021\n",
            "| Global Round : 39 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.555058\n",
            "| Global Round : 39 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.550100\n",
            "| Global Round : 39 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.545864\n",
            "| Global Round : 39 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.543490\n",
            "| Global Round : 39 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.540721\n",
            "| Global Round : 39 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.536231\n",
            "| Global Round : 39 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.531810\n",
            "| Global Round : 39 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.527472\n",
            "| Global Round : 39 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.528488\n",
            "| Global Round : 39 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.535515\n",
            "| Global Round : 39 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.553613\n",
            "| Global Round : 39 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.533701\n",
            "| Global Round : 39 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.515321\n",
            "| Global Round : 39 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.509151\n",
            "| Global Round : 39 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.526333\n",
            "| Global Round : 39 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.558191\n",
            "| Global Round : 39 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.522725\n",
            "| Global Round : 39 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.494523\n",
            "| Global Round : 39 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.490252\n",
            "| Global Round : 39 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.507621\n",
            "| Global Round : 39 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.520544\n",
            "| Global Round : 39 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.491094\n",
            "| Global Round : 39 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.480147\n",
            "| Global Round : 39 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.486358\n",
            "| Global Round : 39 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.483761\n",
            "| Global Round : 39 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.480333\n",
            "| Global Round : 39 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.476062\n",
            "| Global Round : 39 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.476201\n",
            "| Global Round : 39 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.476525\n",
            "| Global Round : 39 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.498666\n",
            "| Global Round : 39 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.518128\n",
            "| Global Round : 39 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.551664\n",
            "| Global Round : 39 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.501678\n",
            "| Global Round : 39 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.466705\n",
            "| Global Round : 39 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.498991\n",
            "| Global Round : 39 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.487615\n",
            "| Global Round : 39 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.458903\n",
            "| Global Round : 39 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.465188\n",
            "| Global Round : 39 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.483230\n",
            "| Global Round : 39 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.493467\n",
            "| Global Round : 39 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.470114\n",
            "| Global Round : 39 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.447276\n",
            "| Global Round : 39 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.449900\n",
            "| Global Round : 39 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.938625\n",
            "| Global Round : 39 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.680730\n",
            "| Global Round : 39 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.692328\n",
            "| Global Round : 39 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 0.939180\n",
            "| Global Round : 39 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 1.043106\n",
            "| Global Round : 39 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 1.009178\n",
            "| Global Round : 39 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.933171\n",
            "| Global Round : 39 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 0.895946\n",
            "| Global Round : 39 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 0.897910\n",
            "| Global Round : 39 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.928597\n",
            "| Global Round : 39 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.944140\n",
            "| Global Round : 39 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.911507\n",
            "| Global Round : 39 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.864528\n",
            "| Global Round : 39 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.850375\n",
            "| Global Round : 39 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.856122\n",
            "| Global Round : 39 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.845824\n",
            "| Global Round : 39 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.833418\n",
            "| Global Round : 39 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.823567\n",
            "| Global Round : 39 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.815843\n",
            "| Global Round : 39 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.806973\n",
            "| Global Round : 39 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.797298\n",
            "| Global Round : 39 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.789367\n",
            "| Global Round : 39 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.782563\n",
            "| Global Round : 39 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.776182\n",
            "| Global Round : 39 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.772890\n",
            "| Global Round : 39 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.764910\n",
            "| Global Round : 39 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.752578\n",
            "| Global Round : 39 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.744104\n",
            "| Global Round : 39 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.741314\n",
            "| Global Round : 39 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.739473\n",
            "| Global Round : 39 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.735961\n",
            "| Global Round : 39 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.729735\n",
            "| Global Round : 39 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.721986\n",
            "| Global Round : 39 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.717479\n",
            "| Global Round : 39 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.714406\n",
            "| Global Round : 39 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.707967\n",
            "| Global Round : 39 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.701700\n",
            "| Global Round : 39 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.698844\n",
            "| Global Round : 39 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.693079\n",
            "| Global Round : 39 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.682759\n",
            "| Global Round : 39 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.677723\n",
            "| Global Round : 39 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.668974\n",
            "| Global Round : 39 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.657013\n",
            "| Global Round : 39 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.654507\n",
            "| Global Round : 39 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.652812\n",
            "| Global Round : 39 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.651713\n",
            "| Global Round : 39 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.650351\n",
            "| Global Round : 39 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.643077\n",
            "| Global Round : 39 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.638842\n",
            "| Global Round : 39 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.631147\n",
            "| Global Round : 39 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.627511\n",
            "| Global Round : 39 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.619613\n",
            "| Global Round : 39 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.616144\n",
            "| Global Round : 39 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.610602\n",
            "| Global Round : 39 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.607316\n",
            "| Global Round : 39 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.603830\n",
            "| Global Round : 39 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.597453\n",
            "| Global Round : 39 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.594279\n",
            "| Global Round : 39 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.590804\n",
            "| Global Round : 39 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.585489\n",
            "| Global Round : 39 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.582886\n",
            "| Global Round : 39 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.581253\n",
            "| Global Round : 39 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.577406\n",
            "| Global Round : 39 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.574593\n",
            "| Global Round : 39 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.573826\n",
            "| Global Round : 39 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.574380\n",
            "| Global Round : 39 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.569868\n",
            "| Global Round : 39 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.564114\n",
            "| Global Round : 39 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.563572\n",
            "| Global Round : 39 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.565164\n",
            "| Global Round : 39 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.565198\n",
            "| Global Round : 39 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.557397\n",
            "| Global Round : 39 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.553390\n",
            "| Global Round : 39 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.555742\n",
            "| Global Round : 39 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.556577\n",
            "| Global Round : 39 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.552372\n",
            "| Global Round : 39 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.545138\n",
            "| Global Round : 39 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.544358\n",
            "| Global Round : 39 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.546216\n",
            "| Global Round : 39 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.544220\n",
            "| Global Round : 39 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.542076\n",
            "| Global Round : 39 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.535782\n",
            "| Global Round : 39 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.532397\n",
            "| Global Round : 39 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.530313\n",
            "| Global Round : 39 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.529196\n",
            "| Global Round : 39 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.533215\n",
            "| Global Round : 39 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.538984\n",
            "| Global Round : 39 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.554632\n",
            "| Global Round : 39 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.546013\n",
            "| Global Round : 39 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.549257\n",
            "| Global Round : 39 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.521677\n",
            "| Global Round : 39 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.518800\n",
            "| Global Round : 39 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.539888\n",
            "| Global Round : 39 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.526854\n",
            "| Global Round : 39 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.515079\n",
            "| Global Round : 39 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.507087\n",
            "| Global Round : 39 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.512673\n",
            "| Global Round : 39 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.530951\n",
            "| Global Round : 39 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.526512\n",
            "| Global Round : 39 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.531685\n",
            "Global Round :39, the training accuracy is 61.1%, and the training loss is 0.898.\n",
            "Global Round :39, the testing accuracy is 56.2%, and the testing loss is 1.5.\n",
            "| Global Round : 40 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.853183\n",
            "| Global Round : 40 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 2.557298\n",
            "| Global Round : 40 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 1.170483\n",
            "| Global Round : 40 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 0.932179\n",
            "| Global Round : 40 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 1.481029\n",
            "| Global Round : 40 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.815643\n",
            "| Global Round : 40 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 0.789605\n",
            "| Global Round : 40 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 0.962300\n",
            "| Global Round : 40 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.033497\n",
            "| Global Round : 40 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.988624\n",
            "| Global Round : 40 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.876863\n",
            "| Global Round : 40 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.785063\n",
            "| Global Round : 40 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.803411\n",
            "| Global Round : 40 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.873710\n",
            "| Global Round : 40 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.836926\n",
            "| Global Round : 40 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.748134\n",
            "| Global Round : 40 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.719463\n",
            "| Global Round : 40 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.738669\n",
            "| Global Round : 40 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.755715\n",
            "| Global Round : 40 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.762844\n",
            "| Global Round : 40 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.752559\n",
            "| Global Round : 40 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.722140\n",
            "| Global Round : 40 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.687416\n",
            "| Global Round : 40 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.679356\n",
            "| Global Round : 40 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.693184\n",
            "| Global Round : 40 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.692128\n",
            "| Global Round : 40 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.666835\n",
            "| Global Round : 40 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.648729\n",
            "| Global Round : 40 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.649322\n",
            "| Global Round : 40 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.653124\n",
            "| Global Round : 40 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.645427\n",
            "| Global Round : 40 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.629911\n",
            "| Global Round : 40 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.620233\n",
            "| Global Round : 40 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.623933\n",
            "| Global Round : 40 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.626789\n",
            "| Global Round : 40 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.619383\n",
            "| Global Round : 40 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.608196\n",
            "| Global Round : 40 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.601723\n",
            "| Global Round : 40 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.598699\n",
            "| Global Round : 40 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.593312\n",
            "| Global Round : 40 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.584774\n",
            "| Global Round : 40 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.576711\n",
            "| Global Round : 40 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.575517\n",
            "| Global Round : 40 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.572559\n",
            "| Global Round : 40 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.563012\n",
            "| Global Round : 40 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.554281\n",
            "| Global Round : 40 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.550609\n",
            "| Global Round : 40 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.543774\n",
            "| Global Round : 40 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.537561\n",
            "| Global Round : 40 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.531232\n",
            "| Global Round : 40 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.526204\n",
            "| Global Round : 40 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.519324\n",
            "| Global Round : 40 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.514940\n",
            "| Global Round : 40 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.510558\n",
            "| Global Round : 40 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.505666\n",
            "| Global Round : 40 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.503076\n",
            "| Global Round : 40 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.500802\n",
            "| Global Round : 40 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.498351\n",
            "| Global Round : 40 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.494884\n",
            "| Global Round : 40 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.490263\n",
            "| Global Round : 40 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.484356\n",
            "| Global Round : 40 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.482043\n",
            "| Global Round : 40 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.477747\n",
            "| Global Round : 40 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.471270\n",
            "| Global Round : 40 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.468718\n",
            "| Global Round : 40 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.463853\n",
            "| Global Round : 40 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.458804\n",
            "| Global Round : 40 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.453930\n",
            "| Global Round : 40 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.451064\n",
            "| Global Round : 40 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.447600\n",
            "| Global Round : 40 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.442644\n",
            "| Global Round : 40 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.441015\n",
            "| Global Round : 40 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.435328\n",
            "| Global Round : 40 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.432392\n",
            "| Global Round : 40 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.429192\n",
            "| Global Round : 40 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.425440\n",
            "| Global Round : 40 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.423289\n",
            "| Global Round : 40 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.418690\n",
            "| Global Round : 40 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.415315\n",
            "| Global Round : 40 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.413014\n",
            "| Global Round : 40 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.409207\n",
            "| Global Round : 40 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.406323\n",
            "| Global Round : 40 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.404380\n",
            "| Global Round : 40 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.402058\n",
            "| Global Round : 40 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.399809\n",
            "| Global Round : 40 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.397547\n",
            "| Global Round : 40 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.394489\n",
            "| Global Round : 40 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.391894\n",
            "| Global Round : 40 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.390366\n",
            "| Global Round : 40 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.389516\n",
            "| Global Round : 40 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.388737\n",
            "| Global Round : 40 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.385826\n",
            "| Global Round : 40 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.385199\n",
            "| Global Round : 40 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.383493\n",
            "| Global Round : 40 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.385845\n",
            "| Global Round : 40 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.393832\n",
            "| Global Round : 40 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.437359\n",
            "| Global Round : 40 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.620959\n",
            "| Global Round : 40 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.813404\n",
            "| Global Round : 40 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.576434\n",
            "| Global Round : 40 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 1.031430\n",
            "| Global Round : 40 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.275141\n",
            "| Global Round : 40 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.324393\n",
            "| Global Round : 40 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 0.889997\n",
            "| Global Round : 40 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.322953\n",
            "| Global Round : 40 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 1.075647\n",
            "| Global Round : 40 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.805835\n",
            "| Global Round : 40 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.840295\n",
            "| Global Round : 40 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.947562\n",
            "| Global Round : 40 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.993746\n",
            "| Global Round : 40 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.953382\n",
            "| Global Round : 40 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.870627\n",
            "| Global Round : 40 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.853332\n",
            "| Global Round : 40 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.889112\n",
            "| Global Round : 40 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.807787\n",
            "| Global Round : 40 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.756997\n",
            "| Global Round : 40 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.763722\n",
            "| Global Round : 40 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.779260\n",
            "| Global Round : 40 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.784389\n",
            "| Global Round : 40 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.782299\n",
            "| Global Round : 40 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.779491\n",
            "| Global Round : 40 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.768605\n",
            "| Global Round : 40 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.747704\n",
            "| Global Round : 40 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.727303\n",
            "| Global Round : 40 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.706754\n",
            "| Global Round : 40 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.694753\n",
            "| Global Round : 40 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.698560\n",
            "| Global Round : 40 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.703164\n",
            "| Global Round : 40 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.693864\n",
            "| Global Round : 40 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.678371\n",
            "| Global Round : 40 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.666431\n",
            "| Global Round : 40 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.651822\n",
            "| Global Round : 40 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.640235\n",
            "| Global Round : 40 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.639373\n",
            "| Global Round : 40 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.636857\n",
            "| Global Round : 40 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.624350\n",
            "| Global Round : 40 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.617640\n",
            "| Global Round : 40 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.605849\n",
            "| Global Round : 40 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.605272\n",
            "| Global Round : 40 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.597741\n",
            "| Global Round : 40 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.591450\n",
            "| Global Round : 40 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.587146\n",
            "| Global Round : 40 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.583220\n",
            "| Global Round : 40 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.580041\n",
            "| Global Round : 40 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.573583\n",
            "| Global Round : 40 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.566769\n",
            "| Global Round : 40 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.560787\n",
            "| Global Round : 40 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.557186\n",
            "| Global Round : 40 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.555604\n",
            "| Global Round : 40 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.553188\n",
            "| Global Round : 40 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.545957\n",
            "| Global Round : 40 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.537013\n",
            "| Global Round : 40 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.535575\n",
            "| Global Round : 40 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.536716\n",
            "| Global Round : 40 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.537932\n",
            "| Global Round : 40 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.556934\n",
            "| Global Round : 40 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.537330\n",
            "| Global Round : 40 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.532341\n",
            "| Global Round : 40 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.509454\n",
            "| Global Round : 40 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.515612\n",
            "| Global Round : 40 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.563156\n",
            "| Global Round : 40 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.506095\n",
            "| Global Round : 40 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.498512\n",
            "| Global Round : 40 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.528753\n",
            "| Global Round : 40 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.504531\n",
            "| Global Round : 40 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.485711\n",
            "| Global Round : 40 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.480239\n",
            "| Global Round : 40 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.486090\n",
            "| Global Round : 40 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.511011\n",
            "| Global Round : 40 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.505285\n",
            "| Global Round : 40 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.522255\n",
            "| Global Round : 40 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.475863\n",
            "| Global Round : 40 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.463465\n",
            "| Global Round : 40 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.465375\n",
            "| Global Round : 40 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.472478\n",
            "| Global Round : 40 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.506427\n",
            "| Global Round : 40 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.481488\n",
            "| Global Round : 40 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.461577\n",
            "| Global Round : 40 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.452790\n",
            "| Global Round : 40 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.520360\n",
            "| Global Round : 40 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.647828\n",
            "| Global Round : 40 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.459714\n",
            "| Global Round : 40 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.850914\n",
            "| Global Round : 40 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.973937\n",
            "| Global Round : 40 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 1.271340\n",
            "| Global Round : 40 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.957655\n",
            "| Global Round : 40 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 1.071814\n",
            "| Global Round : 40 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.739022\n",
            "| Global Round : 40 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.732918\n",
            "| Global Round : 40 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.706512\n",
            "| Global Round : 40 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.683348\n",
            "| Global Round : 40 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.667575\n",
            "| Global Round : 40 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.738199\n",
            "| Global Round : 40 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.678815\n",
            "| Global Round : 40 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.709539\n",
            "| Global Round : 40 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.625677\n",
            "| Global Round : 40 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.635522\n",
            "| Global Round : 40 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.620085\n",
            "| Global Round : 40 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.624184\n",
            "| Global Round : 40 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.622101\n",
            "| Global Round : 40 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.803921\n",
            "| Global Round : 40 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.498474\n",
            "| Global Round : 40 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 1.213006\n",
            "| Global Round : 40 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 1.000349\n",
            "| Global Round : 40 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 1.501352\n",
            "| Global Round : 40 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.805160\n",
            "| Global Round : 40 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 0.832204\n",
            "| Global Round : 40 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 0.986823\n",
            "| Global Round : 40 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.057349\n",
            "| Global Round : 40 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.012169\n",
            "| Global Round : 40 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.898198\n",
            "| Global Round : 40 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.796095\n",
            "| Global Round : 40 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.797704\n",
            "| Global Round : 40 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.883803\n",
            "| Global Round : 40 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.874998\n",
            "| Global Round : 40 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.791786\n",
            "| Global Round : 40 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.736659\n",
            "| Global Round : 40 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.739921\n",
            "| Global Round : 40 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.760636\n",
            "| Global Round : 40 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.756059\n",
            "| Global Round : 40 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.735402\n",
            "| Global Round : 40 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.713967\n",
            "| Global Round : 40 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.708463\n",
            "| Global Round : 40 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.718244\n",
            "| Global Round : 40 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.720059\n",
            "| Global Round : 40 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.690857\n",
            "| Global Round : 40 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.671253\n",
            "| Global Round : 40 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.677076\n",
            "| Global Round : 40 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.676763\n",
            "| Global Round : 40 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.660008\n",
            "| Global Round : 40 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.645107\n",
            "| Global Round : 40 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.654167\n",
            "| Global Round : 40 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.636517\n",
            "| Global Round : 40 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.623740\n",
            "| Global Round : 40 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.627489\n",
            "| Global Round : 40 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.614715\n",
            "| Global Round : 40 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.599358\n",
            "| Global Round : 40 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.606311\n",
            "| Global Round : 40 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.587251\n",
            "| Global Round : 40 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.583378\n",
            "| Global Round : 40 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.577475\n",
            "| Global Round : 40 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.563793\n",
            "| Global Round : 40 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.564192\n",
            "| Global Round : 40 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.551231\n",
            "| Global Round : 40 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.550500\n",
            "| Global Round : 40 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.537743\n",
            "| Global Round : 40 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.540506\n",
            "| Global Round : 40 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.530695\n",
            "| Global Round : 40 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.528622\n",
            "| Global Round : 40 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.521603\n",
            "| Global Round : 40 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.515109\n",
            "| Global Round : 40 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.518456\n",
            "| Global Round : 40 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.508088\n",
            "| Global Round : 40 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.506093\n",
            "| Global Round : 40 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.510274\n",
            "| Global Round : 40 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.500060\n",
            "| Global Round : 40 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.497599\n",
            "| Global Round : 40 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.502001\n",
            "| Global Round : 40 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.494440\n",
            "| Global Round : 40 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.488569\n",
            "| Global Round : 40 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.486779\n",
            "| Global Round : 40 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.486986\n",
            "| Global Round : 40 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.486090\n",
            "| Global Round : 40 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.481197\n",
            "| Global Round : 40 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.476840\n",
            "| Global Round : 40 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.473781\n",
            "| Global Round : 40 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.471524\n",
            "| Global Round : 40 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.469598\n",
            "| Global Round : 40 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.467895\n",
            "| Global Round : 40 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.466643\n",
            "| Global Round : 40 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.469619\n",
            "| Global Round : 40 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.492851\n",
            "| Global Round : 40 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.497709\n",
            "| Global Round : 40 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.508561\n",
            "| Global Round : 40 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.463992\n",
            "| Global Round : 40 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.509042\n",
            "| Global Round : 40 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.553403\n",
            "| Global Round : 40 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.462280\n",
            "| Global Round : 40 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.630505\n",
            "| Global Round : 40 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.667102\n",
            "| Global Round : 40 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.633265\n",
            "| Global Round : 40 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.542552\n",
            "| Global Round : 40 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.568684\n",
            "| Global Round : 40 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.554930\n",
            "| Global Round : 40 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.600354\n",
            "| Global Round : 40 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.483902\n",
            "| Global Round : 40 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.635186\n",
            "| Global Round : 40 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.534858\n",
            "| Global Round : 40 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.639006\n",
            "| Global Round : 40 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.502513\n",
            "| Global Round : 40 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.655726\n",
            "| Global Round : 40 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.483723\n",
            "| Global Round : 40 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.546194\n",
            "| Global Round : 40 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.509720\n",
            "| Global Round : 40 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.515779\n",
            "| Global Round : 40 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.531440\n",
            "| Global Round : 40 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.487838\n",
            "| Global Round : 40 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.510970\n",
            "| Global Round : 40 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.463688\n",
            "| Global Round : 40 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.516161\n",
            "| Global Round : 40 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.914268\n",
            "| Global Round : 40 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.544294\n",
            "| Global Round : 40 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.350366\n",
            "| Global Round : 40 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 0.955586\n",
            "| Global Round : 40 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 1.663024\n",
            "| Global Round : 40 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 0.917666\n",
            "| Global Round : 40 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.871626\n",
            "| Global Round : 40 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.024269\n",
            "| Global Round : 40 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 1.137779\n",
            "| Global Round : 40 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 1.117442\n",
            "| Global Round : 40 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 1.008965\n",
            "| Global Round : 40 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.890984\n",
            "| Global Round : 40 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.827991\n",
            "| Global Round : 40 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.859588\n",
            "| Global Round : 40 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.941947\n",
            "| Global Round : 40 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.938352\n",
            "| Global Round : 40 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.863065\n",
            "| Global Round : 40 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.810155\n",
            "| Global Round : 40 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.806079\n",
            "| Global Round : 40 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.820964\n",
            "| Global Round : 40 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.837004\n",
            "| Global Round : 40 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.837510\n",
            "| Global Round : 40 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.820038\n",
            "| Global Round : 40 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.794121\n",
            "| Global Round : 40 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.772606\n",
            "| Global Round : 40 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.766200\n",
            "| Global Round : 40 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.773593\n",
            "| Global Round : 40 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.777562\n",
            "| Global Round : 40 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.765528\n",
            "| Global Round : 40 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.745278\n",
            "| Global Round : 40 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.732173\n",
            "| Global Round : 40 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.731953\n",
            "| Global Round : 40 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.737036\n",
            "| Global Round : 40 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.735967\n",
            "| Global Round : 40 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.725566\n",
            "| Global Round : 40 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.712588\n",
            "| Global Round : 40 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.705992\n",
            "| Global Round : 40 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.705151\n",
            "| Global Round : 40 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.700493\n",
            "| Global Round : 40 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.690346\n",
            "| Global Round : 40 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.681120\n",
            "| Global Round : 40 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.677657\n",
            "| Global Round : 40 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.672632\n",
            "| Global Round : 40 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.660612\n",
            "| Global Round : 40 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.647916\n",
            "| Global Round : 40 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.651446\n",
            "| Global Round : 40 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.635169\n",
            "| Global Round : 40 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.629436\n",
            "| Global Round : 40 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.626728\n",
            "| Global Round : 40 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.614093\n",
            "| Global Round : 40 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.618137\n",
            "| Global Round : 40 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.601815\n",
            "| Global Round : 40 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.602079\n",
            "| Global Round : 40 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.587532\n",
            "| Global Round : 40 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.593498\n",
            "| Global Round : 40 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.582748\n",
            "| Global Round : 40 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.581658\n",
            "| Global Round : 40 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.569434\n",
            "| Global Round : 40 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.570648\n",
            "| Global Round : 40 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.571980\n",
            "| Global Round : 40 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.561107\n",
            "| Global Round : 40 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.574319\n",
            "| Global Round : 40 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.556461\n",
            "| Global Round : 40 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.554705\n",
            "| Global Round : 40 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.558693\n",
            "| Global Round : 40 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.543900\n",
            "| Global Round : 40 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.545171\n",
            "| Global Round : 40 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.540851\n",
            "| Global Round : 40 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.532639\n",
            "| Global Round : 40 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.531420\n",
            "| Global Round : 40 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.528090\n",
            "| Global Round : 40 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.528303\n",
            "| Global Round : 40 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.524876\n",
            "| Global Round : 40 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.522205\n",
            "| Global Round : 40 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.517622\n",
            "| Global Round : 40 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.516185\n",
            "| Global Round : 40 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.521262\n",
            "| Global Round : 40 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.525039\n",
            "| Global Round : 40 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.513434\n",
            "| Global Round : 40 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.509647\n",
            "| Global Round : 40 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.507660\n",
            "| Global Round : 40 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.520442\n",
            "| Global Round : 40 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.532045\n",
            "| Global Round : 40 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.549725\n",
            "| Global Round : 40 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.508161\n",
            "| Global Round : 40 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.496189\n",
            "| Global Round : 40 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.514149\n",
            "| Global Round : 40 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.535254\n",
            "| Global Round : 40 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.554434\n",
            "| Global Round : 40 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.497091\n",
            "| Global Round : 40 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.506490\n",
            "| Global Round : 40 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.551531\n",
            "| Global Round : 40 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.490314\n",
            "| Global Round : 40 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.521480\n",
            "| Global Round : 40 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.599776\n",
            "| Global Round : 40 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.487922\n",
            "| Global Round : 40 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.697747\n",
            "| Global Round : 40 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.818281\n",
            "| Global Round : 40 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.898767\n",
            "| Global Round : 40 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.595172\n",
            "Global Round :40, the training accuracy is 68.3%, and the training loss is 0.78.\n",
            "Global Round :40, the testing accuracy is 66.4%, and the testing loss is 1.29.\n",
            "| Global Round : 41 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.744719\n",
            "| Global Round : 41 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 2.075553\n",
            "| Global Round : 41 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.799420\n",
            "| Global Round : 41 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 4.058618\n",
            "| Global Round : 41 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.771787\n",
            "| Global Round : 41 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.957543\n",
            "| Global Round : 41 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 1.359310\n",
            "| Global Round : 41 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 1.530855\n",
            "| Global Round : 41 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.550360\n",
            "| Global Round : 41 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 1.468815\n",
            "| Global Round : 41 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 1.263743\n",
            "| Global Round : 41 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 1.030491\n",
            "| Global Round : 41 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.892128\n",
            "| Global Round : 41 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.865279\n",
            "| Global Round : 41 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.901165\n",
            "| Global Round : 41 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.928066\n",
            "| Global Round : 41 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.905185\n",
            "| Global Round : 41 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.856166\n",
            "| Global Round : 41 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.817715\n",
            "| Global Round : 41 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.801229\n",
            "| Global Round : 41 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.800782\n",
            "| Global Round : 41 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.800598\n",
            "| Global Round : 41 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.796010\n",
            "| Global Round : 41 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.781851\n",
            "| Global Round : 41 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.751582\n",
            "| Global Round : 41 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.718950\n",
            "| Global Round : 41 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.704505\n",
            "| Global Round : 41 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.704362\n",
            "| Global Round : 41 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.695677\n",
            "| Global Round : 41 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.683887\n",
            "| Global Round : 41 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.680033\n",
            "| Global Round : 41 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.679140\n",
            "| Global Round : 41 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.672904\n",
            "| Global Round : 41 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.660807\n",
            "| Global Round : 41 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.645215\n",
            "| Global Round : 41 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.630230\n",
            "| Global Round : 41 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.617770\n",
            "| Global Round : 41 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.606323\n",
            "| Global Round : 41 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.654632\n",
            "| Global Round : 41 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.596036\n",
            "| Global Round : 41 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.599484\n",
            "| Global Round : 41 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.597446\n",
            "| Global Round : 41 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.590928\n",
            "| Global Round : 41 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.585214\n",
            "| Global Round : 41 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.583045\n",
            "| Global Round : 41 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.578012\n",
            "| Global Round : 41 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.566185\n",
            "| Global Round : 41 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.554559\n",
            "| Global Round : 41 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.547102\n",
            "| Global Round : 41 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.542107\n",
            "| Global Round : 41 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.537924\n",
            "| Global Round : 41 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.532679\n",
            "| Global Round : 41 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.524221\n",
            "| Global Round : 41 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.515996\n",
            "| Global Round : 41 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.510356\n",
            "| Global Round : 41 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.503797\n",
            "| Global Round : 41 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.497564\n",
            "| Global Round : 41 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.492922\n",
            "| Global Round : 41 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.486322\n",
            "| Global Round : 41 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.479153\n",
            "| Global Round : 41 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.470506\n",
            "| Global Round : 41 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.463673\n",
            "| Global Round : 41 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.458642\n",
            "| Global Round : 41 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.451143\n",
            "| Global Round : 41 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.444985\n",
            "| Global Round : 41 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.440770\n",
            "| Global Round : 41 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.434133\n",
            "| Global Round : 41 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.426802\n",
            "| Global Round : 41 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.423331\n",
            "| Global Round : 41 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.418911\n",
            "| Global Round : 41 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.416402\n",
            "| Global Round : 41 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.411863\n",
            "| Global Round : 41 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.406333\n",
            "| Global Round : 41 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.403078\n",
            "| Global Round : 41 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.399278\n",
            "| Global Round : 41 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.396000\n",
            "| Global Round : 41 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.392889\n",
            "| Global Round : 41 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.388162\n",
            "| Global Round : 41 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.385004\n",
            "| Global Round : 41 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.378574\n",
            "| Global Round : 41 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.372871\n",
            "| Global Round : 41 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.377411\n",
            "| Global Round : 41 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.381694\n",
            "| Global Round : 41 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.423161\n",
            "| Global Round : 41 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.402811\n",
            "| Global Round : 41 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.371287\n",
            "| Global Round : 41 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.364907\n",
            "| Global Round : 41 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.386361\n",
            "| Global Round : 41 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.380183\n",
            "| Global Round : 41 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.354614\n",
            "| Global Round : 41 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.370243\n",
            "| Global Round : 41 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.371152\n",
            "| Global Round : 41 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.349422\n",
            "| Global Round : 41 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.358129\n",
            "| Global Round : 41 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.363401\n",
            "| Global Round : 41 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.347728\n",
            "| Global Round : 41 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.342492\n",
            "| Global Round : 41 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.350005\n",
            "| Global Round : 41 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.352181\n",
            "| Global Round : 41 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.340494\n",
            "| Global Round : 41 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.903275\n",
            "| Global Round : 41 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.026931\n",
            "| Global Round : 41 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.163010\n",
            "| Global Round : 41 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 2.289485\n",
            "| Global Round : 41 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.043189\n",
            "| Global Round : 41 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.930329\n",
            "| Global Round : 41 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 1.014327\n",
            "| Global Round : 41 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 1.049551\n",
            "| Global Round : 41 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 1.031790\n",
            "| Global Round : 41 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.967296\n",
            "| Global Round : 41 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.881158\n",
            "| Global Round : 41 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.855446\n",
            "| Global Round : 41 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.810904\n",
            "| Global Round : 41 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.799269\n",
            "| Global Round : 41 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.816317\n",
            "| Global Round : 41 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.813146\n",
            "| Global Round : 41 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.799922\n",
            "| Global Round : 41 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.802919\n",
            "| Global Round : 41 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.791061\n",
            "| Global Round : 41 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.785305\n",
            "| Global Round : 41 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.767869\n",
            "| Global Round : 41 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.759105\n",
            "| Global Round : 41 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.753603\n",
            "| Global Round : 41 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.738922\n",
            "| Global Round : 41 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.722203\n",
            "| Global Round : 41 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.718330\n",
            "| Global Round : 41 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.711939\n",
            "| Global Round : 41 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.703642\n",
            "| Global Round : 41 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.695765\n",
            "| Global Round : 41 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.677646\n",
            "| Global Round : 41 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.667967\n",
            "| Global Round : 41 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.662403\n",
            "| Global Round : 41 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.654854\n",
            "| Global Round : 41 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.647330\n",
            "| Global Round : 41 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.638929\n",
            "| Global Round : 41 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.632094\n",
            "| Global Round : 41 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.628241\n",
            "| Global Round : 41 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.617928\n",
            "| Global Round : 41 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.606177\n",
            "| Global Round : 41 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.596987\n",
            "| Global Round : 41 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.597523\n",
            "| Global Round : 41 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.588306\n",
            "| Global Round : 41 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.582201\n",
            "| Global Round : 41 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.579446\n",
            "| Global Round : 41 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.574057\n",
            "| Global Round : 41 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.571330\n",
            "| Global Round : 41 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.562896\n",
            "| Global Round : 41 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.561915\n",
            "| Global Round : 41 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.555569\n",
            "| Global Round : 41 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.548641\n",
            "| Global Round : 41 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.548415\n",
            "| Global Round : 41 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.542839\n",
            "| Global Round : 41 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.535460\n",
            "| Global Round : 41 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.533787\n",
            "| Global Round : 41 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.532637\n",
            "| Global Round : 41 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.524175\n",
            "| Global Round : 41 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.517157\n",
            "| Global Round : 41 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.514926\n",
            "| Global Round : 41 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.516791\n",
            "| Global Round : 41 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.514500\n",
            "| Global Round : 41 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.503231\n",
            "| Global Round : 41 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.496058\n",
            "| Global Round : 41 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.498693\n",
            "| Global Round : 41 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.504139\n",
            "| Global Round : 41 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.500052\n",
            "| Global Round : 41 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.483399\n",
            "| Global Round : 41 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.472225\n",
            "| Global Round : 41 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.474304\n",
            "| Global Round : 41 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.485089\n",
            "| Global Round : 41 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.495680\n",
            "| Global Round : 41 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.493175\n",
            "| Global Round : 41 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.478078\n",
            "| Global Round : 41 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.460047\n",
            "| Global Round : 41 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.468797\n",
            "| Global Round : 41 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.459864\n",
            "| Global Round : 41 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.448186\n",
            "| Global Round : 41 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.445886\n",
            "| Global Round : 41 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.451553\n",
            "| Global Round : 41 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.446671\n",
            "| Global Round : 41 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.442411\n",
            "| Global Round : 41 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.438944\n",
            "| Global Round : 41 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.435133\n",
            "| Global Round : 41 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.429407\n",
            "| Global Round : 41 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.427531\n",
            "| Global Round : 41 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.431962\n",
            "| Global Round : 41 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.443175\n",
            "| Global Round : 41 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.477160\n",
            "| Global Round : 41 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.520552\n",
            "| Global Round : 41 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.457570\n",
            "| Global Round : 41 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.433374\n",
            "| Global Round : 41 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.468000\n",
            "| Global Round : 41 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.421133\n",
            "| Global Round : 41 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.445701\n",
            "| Global Round : 41 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.489684\n",
            "| Global Round : 41 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.427315\n",
            "| Global Round : 41 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.417472\n",
            "| Global Round : 41 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.466411\n",
            "| Global Round : 41 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.417067\n",
            "| Global Round : 41 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.424203\n",
            "| Global Round : 41 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.444124\n",
            "| Global Round : 41 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.707189\n",
            "| Global Round : 41 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.020094\n",
            "| Global Round : 41 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 1.248378\n",
            "| Global Round : 41 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 0.723668\n",
            "| Global Round : 41 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 0.781090\n",
            "| Global Round : 41 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.852295\n",
            "| Global Round : 41 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 0.794393\n",
            "| Global Round : 41 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 0.770356\n",
            "| Global Round : 41 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 0.728648\n",
            "| Global Round : 41 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 0.737728\n",
            "| Global Round : 41 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.732394\n",
            "| Global Round : 41 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.731404\n",
            "| Global Round : 41 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.732325\n",
            "| Global Round : 41 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.713071\n",
            "| Global Round : 41 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.687521\n",
            "| Global Round : 41 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.669245\n",
            "| Global Round : 41 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.641096\n",
            "| Global Round : 41 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.626547\n",
            "| Global Round : 41 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.607548\n",
            "| Global Round : 41 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.596431\n",
            "| Global Round : 41 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.591175\n",
            "| Global Round : 41 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.581888\n",
            "| Global Round : 41 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.573469\n",
            "| Global Round : 41 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.561436\n",
            "| Global Round : 41 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.555047\n",
            "| Global Round : 41 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.557060\n",
            "| Global Round : 41 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.539068\n",
            "| Global Round : 41 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.530688\n",
            "| Global Round : 41 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.534244\n",
            "| Global Round : 41 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.524459\n",
            "| Global Round : 41 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.515387\n",
            "| Global Round : 41 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.512181\n",
            "| Global Round : 41 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.513958\n",
            "| Global Round : 41 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.507974\n",
            "| Global Round : 41 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.496654\n",
            "| Global Round : 41 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.491285\n",
            "| Global Round : 41 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.491312\n",
            "| Global Round : 41 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.489517\n",
            "| Global Round : 41 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.495987\n",
            "| Global Round : 41 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.496882\n",
            "| Global Round : 41 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.525318\n",
            "| Global Round : 41 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.495816\n",
            "| Global Round : 41 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.480632\n",
            "| Global Round : 41 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.470255\n",
            "| Global Round : 41 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.485110\n",
            "| Global Round : 41 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.527113\n",
            "| Global Round : 41 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.470350\n",
            "| Global Round : 41 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.461434\n",
            "| Global Round : 41 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.481599\n",
            "| Global Round : 41 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.468474\n",
            "| Global Round : 41 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.457386\n",
            "| Global Round : 41 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.451044\n",
            "| Global Round : 41 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.454819\n",
            "| Global Round : 41 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.461765\n",
            "| Global Round : 41 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.465436\n",
            "| Global Round : 41 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.475145\n",
            "| Global Round : 41 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.455397\n",
            "| Global Round : 41 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.447724\n",
            "| Global Round : 41 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.439514\n",
            "| Global Round : 41 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.436551\n",
            "| Global Round : 41 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.437475\n",
            "| Global Round : 41 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.441457\n",
            "| Global Round : 41 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.462233\n",
            "| Global Round : 41 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.466298\n",
            "| Global Round : 41 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.508344\n",
            "| Global Round : 41 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.429196\n",
            "| Global Round : 41 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.474702\n",
            "| Global Round : 41 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.617271\n",
            "| Global Round : 41 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.445539\n",
            "| Global Round : 41 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.803679\n",
            "| Global Round : 41 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.773813\n",
            "| Global Round : 41 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.982510\n",
            "| Global Round : 41 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.649906\n",
            "| Global Round : 41 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.610539\n",
            "| Global Round : 41 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.740614\n",
            "| Global Round : 41 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.533527\n",
            "| Global Round : 41 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.716683\n",
            "| Global Round : 41 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.725813\n",
            "| Global Round : 41 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.582231\n",
            "| Global Round : 41 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.563818\n",
            "| Global Round : 41 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.676970\n",
            "| Global Round : 41 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.557660\n",
            "| Global Round : 41 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.542629\n",
            "| Global Round : 41 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.595942\n",
            "| Global Round : 41 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.576560\n",
            "| Global Round : 41 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.523850\n",
            "| Global Round : 41 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.551667\n",
            "| Global Round : 41 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.550471\n",
            "| Global Round : 41 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.497193\n",
            "| Global Round : 41 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.530910\n",
            "| Global Round : 41 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.511684\n",
            "| Global Round : 41 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.482907\n",
            "| Global Round : 41 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.517657\n",
            "| Global Round : 41 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.472045\n",
            "| Global Round : 41 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.473085\n",
            "| Global Round : 41 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.468914\n",
            "| Global Round : 41 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.449613\n",
            "| Global Round : 41 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.470744\n",
            "| Global Round : 41 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.435838\n",
            "| Global Round : 41 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.447558\n",
            "| Global Round : 41 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.779270\n",
            "| Global Round : 41 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 1.558838\n",
            "| Global Round : 41 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 2.968287\n",
            "| Global Round : 41 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.070906\n",
            "| Global Round : 41 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 1.039115\n",
            "| Global Round : 41 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 1.127602\n",
            "| Global Round : 41 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 1.154130\n",
            "| Global Round : 41 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.180092\n",
            "| Global Round : 41 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 1.156983\n",
            "| Global Round : 41 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.964898\n",
            "| Global Round : 41 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.894519\n",
            "| Global Round : 41 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.885521\n",
            "| Global Round : 41 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.886545\n",
            "| Global Round : 41 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.889673\n",
            "| Global Round : 41 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.910414\n",
            "| Global Round : 41 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.894199\n",
            "| Global Round : 41 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.861209\n",
            "| Global Round : 41 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.837377\n",
            "| Global Round : 41 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.808771\n",
            "| Global Round : 41 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.792784\n",
            "| Global Round : 41 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.770962\n",
            "| Global Round : 41 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.750866\n",
            "| Global Round : 41 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.740277\n",
            "| Global Round : 41 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.729778\n",
            "| Global Round : 41 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.724399\n",
            "| Global Round : 41 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.714497\n",
            "| Global Round : 41 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.710039\n",
            "| Global Round : 41 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.699387\n",
            "| Global Round : 41 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.687319\n",
            "| Global Round : 41 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.668806\n",
            "| Global Round : 41 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.649025\n",
            "| Global Round : 41 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.631499\n",
            "| Global Round : 41 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.617820\n",
            "| Global Round : 41 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.605426\n",
            "| Global Round : 41 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.592722\n",
            "| Global Round : 41 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.581752\n",
            "| Global Round : 41 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.571488\n",
            "| Global Round : 41 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.567439\n",
            "| Global Round : 41 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.565942\n",
            "| Global Round : 41 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.566424\n",
            "| Global Round : 41 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.563912\n",
            "| Global Round : 41 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.552166\n",
            "| Global Round : 41 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.540852\n",
            "| Global Round : 41 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.537909\n",
            "| Global Round : 41 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.557133\n",
            "| Global Round : 41 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.600115\n",
            "| Global Round : 41 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.677638\n",
            "| Global Round : 41 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.518320\n",
            "| Global Round : 41 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.668459\n",
            "| Global Round : 41 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.592202\n",
            "| Global Round : 41 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.607978\n",
            "| Global Round : 41 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.551607\n",
            "| Global Round : 41 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.578236\n",
            "| Global Round : 41 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.550711\n",
            "| Global Round : 41 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.584734\n",
            "| Global Round : 41 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.511703\n",
            "| Global Round : 41 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.582014\n",
            "| Global Round : 41 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.511049\n",
            "| Global Round : 41 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.568516\n",
            "| Global Round : 41 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.494605\n",
            "| Global Round : 41 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.549523\n",
            "| Global Round : 41 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.491408\n",
            "| Global Round : 41 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.531937\n",
            "| Global Round : 41 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.485091\n",
            "| Global Round : 41 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.522941\n",
            "| Global Round : 41 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.484553\n",
            "| Global Round : 41 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.507284\n",
            "| Global Round : 41 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.479718\n",
            "| Global Round : 41 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.490079\n",
            "| Global Round : 41 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.478294\n",
            "| Global Round : 41 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.478707\n",
            "| Global Round : 41 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.480987\n",
            "| Global Round : 41 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.470548\n",
            "| Global Round : 41 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.479100\n",
            "| Global Round : 41 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.463452\n",
            "| Global Round : 41 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.472783\n",
            "| Global Round : 41 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.464259\n",
            "| Global Round : 41 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.464611\n",
            "| Global Round : 41 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.466443\n",
            "| Global Round : 41 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.454911\n",
            "| Global Round : 41 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.464482\n",
            "| Global Round : 41 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.459339\n",
            "| Global Round : 41 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.451232\n",
            "| Global Round : 41 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.459141\n",
            "| Global Round : 41 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.454621\n",
            "| Global Round : 41 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.446816\n",
            "| Global Round : 41 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.451713\n",
            "| Global Round : 41 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.448530\n",
            "| Global Round : 41 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.442436\n",
            "| Global Round : 41 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.445473\n",
            "| Global Round : 41 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.444438\n",
            "| Global Round : 41 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.438083\n",
            "| Global Round : 41 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.439421\n",
            "| Global Round : 41 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.440838\n",
            "| Global Round : 41 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.439400\n",
            "| Global Round : 41 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.433451\n",
            "| Global Round : 41 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.433323\n",
            "| Global Round : 41 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.435991\n",
            "| Global Round : 41 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.433978\n",
            "| Global Round : 41 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.433120\n",
            "Global Round :41, the training accuracy is 66.6%, and the training loss is 0.816.\n",
            "Global Round :41, the testing accuracy is 63.2%, and the testing loss is 1.37.\n",
            "| Global Round : 42 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.752517\n",
            "| Global Round : 42 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 2.608442\n",
            "| Global Round : 42 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.761972\n",
            "| Global Round : 42 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 2.037581\n",
            "| Global Round : 42 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.898156\n",
            "| Global Round : 42 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.705423\n",
            "| Global Round : 42 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 0.895789\n",
            "| Global Round : 42 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 1.042024\n",
            "| Global Round : 42 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.053748\n",
            "| Global Round : 42 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.963093\n",
            "| Global Round : 42 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.823419\n",
            "| Global Round : 42 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.741042\n",
            "| Global Round : 42 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.821324\n",
            "| Global Round : 42 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.813904\n",
            "| Global Round : 42 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.785526\n",
            "| Global Round : 42 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.753787\n",
            "| Global Round : 42 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.740439\n",
            "| Global Round : 42 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.739320\n",
            "| Global Round : 42 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.750705\n",
            "| Global Round : 42 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.757436\n",
            "| Global Round : 42 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.749029\n",
            "| Global Round : 42 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.731181\n",
            "| Global Round : 42 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.706796\n",
            "| Global Round : 42 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.681682\n",
            "| Global Round : 42 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.664732\n",
            "| Global Round : 42 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.660111\n",
            "| Global Round : 42 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.664129\n",
            "| Global Round : 42 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.664215\n",
            "| Global Round : 42 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.653141\n",
            "| Global Round : 42 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.639733\n",
            "| Global Round : 42 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.632758\n",
            "| Global Round : 42 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.628480\n",
            "| Global Round : 42 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.622643\n",
            "| Global Round : 42 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.613368\n",
            "| Global Round : 42 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.604907\n",
            "| Global Round : 42 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.598996\n",
            "| Global Round : 42 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.596085\n",
            "| Global Round : 42 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.592501\n",
            "| Global Round : 42 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.584522\n",
            "| Global Round : 42 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.576962\n",
            "| Global Round : 42 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.572487\n",
            "| Global Round : 42 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.568063\n",
            "| Global Round : 42 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.562491\n",
            "| Global Round : 42 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.554973\n",
            "| Global Round : 42 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.549745\n",
            "| Global Round : 42 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.545707\n",
            "| Global Round : 42 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.540490\n",
            "| Global Round : 42 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.535266\n",
            "| Global Round : 42 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.530880\n",
            "| Global Round : 42 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.526098\n",
            "| Global Round : 42 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.520924\n",
            "| Global Round : 42 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.515566\n",
            "| Global Round : 42 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.510589\n",
            "| Global Round : 42 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.505610\n",
            "| Global Round : 42 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.500270\n",
            "| Global Round : 42 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.496042\n",
            "| Global Round : 42 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.490905\n",
            "| Global Round : 42 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.486058\n",
            "| Global Round : 42 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.481691\n",
            "| Global Round : 42 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.476542\n",
            "| Global Round : 42 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.471638\n",
            "| Global Round : 42 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.466636\n",
            "| Global Round : 42 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.460871\n",
            "| Global Round : 42 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.455918\n",
            "| Global Round : 42 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.451048\n",
            "| Global Round : 42 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.446329\n",
            "| Global Round : 42 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.440731\n",
            "| Global Round : 42 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.436204\n",
            "| Global Round : 42 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.430749\n",
            "| Global Round : 42 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.424090\n",
            "| Global Round : 42 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.417929\n",
            "| Global Round : 42 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.412039\n",
            "| Global Round : 42 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.406817\n",
            "| Global Round : 42 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.400680\n",
            "| Global Round : 42 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.393580\n",
            "| Global Round : 42 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.388385\n",
            "| Global Round : 42 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.385590\n",
            "| Global Round : 42 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.385936\n",
            "| Global Round : 42 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.390047\n",
            "| Global Round : 42 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.405885\n",
            "| Global Round : 42 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.432788\n",
            "| Global Round : 42 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.400410\n",
            "| Global Round : 42 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.370838\n",
            "| Global Round : 42 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.396510\n",
            "| Global Round : 42 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.403146\n",
            "| Global Round : 42 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.377989\n",
            "| Global Round : 42 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.362737\n",
            "| Global Round : 42 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.386328\n",
            "| Global Round : 42 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.439075\n",
            "| Global Round : 42 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.391515\n",
            "| Global Round : 42 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.357363\n",
            "| Global Round : 42 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.364083\n",
            "| Global Round : 42 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.367597\n",
            "| Global Round : 42 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.355770\n",
            "| Global Round : 42 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.344752\n",
            "| Global Round : 42 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.351766\n",
            "| Global Round : 42 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.376750\n",
            "| Global Round : 42 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.379890\n",
            "| Global Round : 42 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.398463\n",
            "| Global Round : 42 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.349508\n",
            "| Global Round : 42 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.977182\n",
            "| Global Round : 42 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.415017\n",
            "| Global Round : 42 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.010660\n",
            "| Global Round : 42 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.065142\n",
            "| Global Round : 42 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.243793\n",
            "| Global Round : 42 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.825131\n",
            "| Global Round : 42 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.843315\n",
            "| Global Round : 42 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.950792\n",
            "| Global Round : 42 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.996077\n",
            "| Global Round : 42 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.966742\n",
            "| Global Round : 42 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.890298\n",
            "| Global Round : 42 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.814605\n",
            "| Global Round : 42 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.804897\n",
            "| Global Round : 42 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.855717\n",
            "| Global Round : 42 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.852066\n",
            "| Global Round : 42 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.779164\n",
            "| Global Round : 42 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.734490\n",
            "| Global Round : 42 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.741631\n",
            "| Global Round : 42 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.763744\n",
            "| Global Round : 42 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.771920\n",
            "| Global Round : 42 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.754745\n",
            "| Global Round : 42 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.722260\n",
            "| Global Round : 42 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.695822\n",
            "| Global Round : 42 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.716128\n",
            "| Global Round : 42 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.711291\n",
            "| Global Round : 42 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.660244\n",
            "| Global Round : 42 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.655661\n",
            "| Global Round : 42 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.672534\n",
            "| Global Round : 42 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.654721\n",
            "| Global Round : 42 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.620849\n",
            "| Global Round : 42 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.625992\n",
            "| Global Round : 42 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.630314\n",
            "| Global Round : 42 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.591247\n",
            "| Global Round : 42 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.601135\n",
            "| Global Round : 42 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.599280\n",
            "| Global Round : 42 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.565771\n",
            "| Global Round : 42 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.599439\n",
            "| Global Round : 42 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.552002\n",
            "| Global Round : 42 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.572511\n",
            "| Global Round : 42 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.547477\n",
            "| Global Round : 42 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.564001\n",
            "| Global Round : 42 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.530777\n",
            "| Global Round : 42 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.540549\n",
            "| Global Round : 42 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.523190\n",
            "| Global Round : 42 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.534904\n",
            "| Global Round : 42 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.518582\n",
            "| Global Round : 42 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.519573\n",
            "| Global Round : 42 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.509372\n",
            "| Global Round : 42 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.493773\n",
            "| Global Round : 42 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.495825\n",
            "| Global Round : 42 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.487778\n",
            "| Global Round : 42 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.479398\n",
            "| Global Round : 42 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.475602\n",
            "| Global Round : 42 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.473860\n",
            "| Global Round : 42 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.468891\n",
            "| Global Round : 42 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.463896\n",
            "| Global Round : 42 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.461341\n",
            "| Global Round : 42 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.460333\n",
            "| Global Round : 42 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.457968\n",
            "| Global Round : 42 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.463288\n",
            "| Global Round : 42 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.473788\n",
            "| Global Round : 42 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.509253\n",
            "| Global Round : 42 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.476605\n",
            "| Global Round : 42 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.462639\n",
            "| Global Round : 42 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.441251\n",
            "| Global Round : 42 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.444209\n",
            "| Global Round : 42 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.476110\n",
            "| Global Round : 42 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.457533\n",
            "| Global Round : 42 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.438671\n",
            "| Global Round : 42 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.431507\n",
            "| Global Round : 42 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.439396\n",
            "| Global Round : 42 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.444670\n",
            "| Global Round : 42 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.432909\n",
            "| Global Round : 42 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.424758\n",
            "| Global Round : 42 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.427630\n",
            "| Global Round : 42 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.431996\n",
            "| Global Round : 42 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.432295\n",
            "| Global Round : 42 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.426918\n",
            "| Global Round : 42 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.423941\n",
            "| Global Round : 42 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.414471\n",
            "| Global Round : 42 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.410968\n",
            "| Global Round : 42 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.413904\n",
            "| Global Round : 42 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.428626\n",
            "| Global Round : 42 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.479270\n",
            "| Global Round : 42 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.476082\n",
            "| Global Round : 42 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.515825\n",
            "| Global Round : 42 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.408052\n",
            "| Global Round : 42 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.439815\n",
            "| Global Round : 42 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.572735\n",
            "| Global Round : 42 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.408487\n",
            "| Global Round : 42 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.555449\n",
            "| Global Round : 42 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.760327\n",
            "| Global Round : 42 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.596954\n",
            "| Global Round : 42 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.820126\n",
            "| Global Round : 42 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.533903\n",
            "| Global Round : 42 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.750648\n",
            "| Global Round : 42 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.479694\n",
            "| Global Round : 42 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.675099\n",
            "| Global Round : 42 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.430420\n",
            "| Global Round : 42 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.544418\n",
            "| Global Round : 42 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.755158\n",
            "| Global Round : 42 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.553283\n",
            "| Global Round : 42 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.783877\n",
            "| Global Round : 42 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 2.460472\n",
            "| Global Round : 42 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 0.906837\n",
            "| Global Round : 42 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.793270\n",
            "| Global Round : 42 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.025155\n",
            "| Global Round : 42 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.186393\n",
            "| Global Round : 42 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.242472\n",
            "| Global Round : 42 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.190618\n",
            "| Global Round : 42 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 1.062817\n",
            "| Global Round : 42 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.907781\n",
            "| Global Round : 42 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.796497\n",
            "| Global Round : 42 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.819087\n",
            "| Global Round : 42 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.884482\n",
            "| Global Round : 42 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.868594\n",
            "| Global Round : 42 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.830937\n",
            "| Global Round : 42 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.812661\n",
            "| Global Round : 42 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.804399\n",
            "| Global Round : 42 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.797748\n",
            "| Global Round : 42 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.794319\n",
            "| Global Round : 42 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.784361\n",
            "| Global Round : 42 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.773779\n",
            "| Global Round : 42 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.769601\n",
            "| Global Round : 42 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.763400\n",
            "| Global Round : 42 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.754632\n",
            "| Global Round : 42 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.741378\n",
            "| Global Round : 42 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.724569\n",
            "| Global Round : 42 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.709517\n",
            "| Global Round : 42 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.700285\n",
            "| Global Round : 42 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.699412\n",
            "| Global Round : 42 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.704837\n",
            "| Global Round : 42 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.702438\n",
            "| Global Round : 42 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.688252\n",
            "| Global Round : 42 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.678793\n",
            "| Global Round : 42 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.674329\n",
            "| Global Round : 42 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.671299\n",
            "| Global Round : 42 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.669372\n",
            "| Global Round : 42 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.667245\n",
            "| Global Round : 42 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.661840\n",
            "| Global Round : 42 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.657317\n",
            "| Global Round : 42 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.654988\n",
            "| Global Round : 42 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.650693\n",
            "| Global Round : 42 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.643525\n",
            "| Global Round : 42 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.638087\n",
            "| Global Round : 42 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.638507\n",
            "| Global Round : 42 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.636243\n",
            "| Global Round : 42 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.632453\n",
            "| Global Round : 42 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.628490\n",
            "| Global Round : 42 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.623554\n",
            "| Global Round : 42 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.620031\n",
            "| Global Round : 42 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.616613\n",
            "| Global Round : 42 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.612011\n",
            "| Global Round : 42 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.608906\n",
            "| Global Round : 42 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.605016\n",
            "| Global Round : 42 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.602593\n",
            "| Global Round : 42 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.598951\n",
            "| Global Round : 42 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.594553\n",
            "| Global Round : 42 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.590284\n",
            "| Global Round : 42 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.585396\n",
            "| Global Round : 42 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.582170\n",
            "| Global Round : 42 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.577413\n",
            "| Global Round : 42 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.573624\n",
            "| Global Round : 42 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.569595\n",
            "| Global Round : 42 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.565879\n",
            "| Global Round : 42 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.562109\n",
            "| Global Round : 42 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.558537\n",
            "| Global Round : 42 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.554790\n",
            "| Global Round : 42 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.549886\n",
            "| Global Round : 42 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.546087\n",
            "| Global Round : 42 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.541246\n",
            "| Global Round : 42 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.536442\n",
            "| Global Round : 42 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.531182\n",
            "| Global Round : 42 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.525264\n",
            "| Global Round : 42 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.519820\n",
            "| Global Round : 42 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.515934\n",
            "| Global Round : 42 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.511013\n",
            "| Global Round : 42 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.507157\n",
            "| Global Round : 42 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.502903\n",
            "| Global Round : 42 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.499099\n",
            "| Global Round : 42 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.494502\n",
            "| Global Round : 42 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.490827\n",
            "| Global Round : 42 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.487172\n",
            "| Global Round : 42 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.484062\n",
            "| Global Round : 42 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.479969\n",
            "| Global Round : 42 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.477092\n",
            "| Global Round : 42 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.472446\n",
            "| Global Round : 42 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.467610\n",
            "| Global Round : 42 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.462824\n",
            "| Global Round : 42 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.458600\n",
            "| Global Round : 42 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.453610\n",
            "| Global Round : 42 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.450401\n",
            "| Global Round : 42 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.445464\n",
            "| Global Round : 42 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.445888\n",
            "| Global Round : 42 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.445573\n",
            "| Global Round : 42 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.458312\n",
            "| Global Round : 42 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.443049\n",
            "| Global Round : 42 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.445673\n",
            "| Global Round : 42 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.442958\n",
            "| Global Round : 42 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.444850\n",
            "| Global Round : 42 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.797951\n",
            "| Global Round : 42 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.463576\n",
            "| Global Round : 42 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 0.963958\n",
            "| Global Round : 42 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.669395\n",
            "| Global Round : 42 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 0.928795\n",
            "| Global Round : 42 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 0.827515\n",
            "| Global Round : 42 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.931060\n",
            "| Global Round : 42 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.017832\n",
            "| Global Round : 42 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 1.034578\n",
            "| Global Round : 42 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.987285\n",
            "| Global Round : 42 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.908188\n",
            "| Global Round : 42 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.837880\n",
            "| Global Round : 42 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.834209\n",
            "| Global Round : 42 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.860318\n",
            "| Global Round : 42 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.867811\n",
            "| Global Round : 42 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.802584\n",
            "| Global Round : 42 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.776804\n",
            "| Global Round : 42 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.769149\n",
            "| Global Round : 42 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.764164\n",
            "| Global Round : 42 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.750219\n",
            "| Global Round : 42 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.729620\n",
            "| Global Round : 42 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.725813\n",
            "| Global Round : 42 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.748863\n",
            "| Global Round : 42 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.731373\n",
            "| Global Round : 42 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.708062\n",
            "| Global Round : 42 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.710654\n",
            "| Global Round : 42 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.711516\n",
            "| Global Round : 42 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.691705\n",
            "| Global Round : 42 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.670347\n",
            "| Global Round : 42 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.671441\n",
            "| Global Round : 42 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.658454\n",
            "| Global Round : 42 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.634224\n",
            "| Global Round : 42 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.639091\n",
            "| Global Round : 42 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.621187\n",
            "| Global Round : 42 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.603421\n",
            "| Global Round : 42 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.603166\n",
            "| Global Round : 42 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.589258\n",
            "| Global Round : 42 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.578207\n",
            "| Global Round : 42 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.570273\n",
            "| Global Round : 42 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.571181\n",
            "| Global Round : 42 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.564126\n",
            "| Global Round : 42 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.552903\n",
            "| Global Round : 42 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.552157\n",
            "| Global Round : 42 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.553148\n",
            "| Global Round : 42 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.546845\n",
            "| Global Round : 42 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.540728\n",
            "| Global Round : 42 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.537380\n",
            "| Global Round : 42 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.534390\n",
            "| Global Round : 42 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.529056\n",
            "| Global Round : 42 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.522914\n",
            "| Global Round : 42 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.518942\n",
            "| Global Round : 42 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.517396\n",
            "| Global Round : 42 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.515532\n",
            "| Global Round : 42 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.512066\n",
            "| Global Round : 42 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.509080\n",
            "| Global Round : 42 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.508685\n",
            "| Global Round : 42 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.506213\n",
            "| Global Round : 42 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.501589\n",
            "| Global Round : 42 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.497303\n",
            "| Global Round : 42 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.497251\n",
            "| Global Round : 42 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.495142\n",
            "| Global Round : 42 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.492005\n",
            "| Global Round : 42 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.489531\n",
            "| Global Round : 42 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.487856\n",
            "| Global Round : 42 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.486892\n",
            "| Global Round : 42 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.481941\n",
            "| Global Round : 42 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.480556\n",
            "| Global Round : 42 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.480817\n",
            "| Global Round : 42 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.480485\n",
            "| Global Round : 42 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.481339\n",
            "| Global Round : 42 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.485574\n",
            "| Global Round : 42 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.504995\n",
            "| Global Round : 42 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.494837\n",
            "| Global Round : 42 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.486001\n",
            "| Global Round : 42 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.466805\n",
            "| Global Round : 42 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.473104\n",
            "| Global Round : 42 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.497816\n",
            "| Global Round : 42 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.487939\n",
            "| Global Round : 42 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.484732\n",
            "| Global Round : 42 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.461388\n",
            "| Global Round : 42 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.465479\n",
            "| Global Round : 42 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.488232\n",
            "| Global Round : 42 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.469695\n",
            "| Global Round : 42 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.456861\n",
            "| Global Round : 42 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.450563\n",
            "| Global Round : 42 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.453732\n",
            "| Global Round : 42 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.457676\n",
            "| Global Round : 42 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.454857\n",
            "| Global Round : 42 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.453770\n",
            "| Global Round : 42 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.449455\n",
            "| Global Round : 42 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.448606\n",
            "| Global Round : 42 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.448951\n",
            "| Global Round : 42 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.455124\n",
            "| Global Round : 42 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.455867\n",
            "| Global Round : 42 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.473699\n",
            "| Global Round : 42 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.459101\n",
            "| Global Round : 42 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.453745\n",
            "| Global Round : 42 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.438775\n",
            "| Global Round : 42 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.437410\n",
            "| Global Round : 42 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.446899\n",
            "Global Round :42, the training accuracy is 69.7%, and the training loss is 0.771.\n",
            "Global Round :42, the testing accuracy is 66.5%, and the testing loss is 1.33.\n",
            "| Global Round : 43 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.683128\n",
            "| Global Round : 43 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 2.094019\n",
            "| Global Round : 43 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.709755\n",
            "| Global Round : 43 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 2.322524\n",
            "| Global Round : 43 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.644981\n",
            "| Global Round : 43 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 1.139941\n",
            "| Global Round : 43 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 1.403544\n",
            "| Global Round : 43 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 1.421747\n",
            "| Global Round : 43 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.257793\n",
            "| Global Round : 43 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 1.007505\n",
            "| Global Round : 43 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.800806\n",
            "| Global Round : 43 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.804474\n",
            "| Global Round : 43 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.922192\n",
            "| Global Round : 43 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.987562\n",
            "| Global Round : 43 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.902198\n",
            "| Global Round : 43 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.792609\n",
            "| Global Round : 43 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.734809\n",
            "| Global Round : 43 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.753862\n",
            "| Global Round : 43 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.810697\n",
            "| Global Round : 43 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.830458\n",
            "| Global Round : 43 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.786451\n",
            "| Global Round : 43 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.726556\n",
            "| Global Round : 43 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.682053\n",
            "| Global Round : 43 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.658467\n",
            "| Global Round : 43 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.658133\n",
            "| Global Round : 43 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.667233\n",
            "| Global Round : 43 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.668952\n",
            "| Global Round : 43 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.642488\n",
            "| Global Round : 43 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.618863\n",
            "| Global Round : 43 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.611066\n",
            "| Global Round : 43 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.613616\n",
            "| Global Round : 43 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.608632\n",
            "| Global Round : 43 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.588920\n",
            "| Global Round : 43 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.569725\n",
            "| Global Round : 43 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.563107\n",
            "| Global Round : 43 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.561495\n",
            "| Global Round : 43 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.558243\n",
            "| Global Round : 43 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.546902\n",
            "| Global Round : 43 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.532694\n",
            "| Global Round : 43 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.520466\n",
            "| Global Round : 43 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.512638\n",
            "| Global Round : 43 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.504948\n",
            "| Global Round : 43 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.499091\n",
            "| Global Round : 43 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.494345\n",
            "| Global Round : 43 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.489238\n",
            "| Global Round : 43 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.484940\n",
            "| Global Round : 43 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.480136\n",
            "| Global Round : 43 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.474382\n",
            "| Global Round : 43 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.469227\n",
            "| Global Round : 43 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.466102\n",
            "| Global Round : 43 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.462850\n",
            "| Global Round : 43 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.462158\n",
            "| Global Round : 43 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.455420\n",
            "| Global Round : 43 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.452445\n",
            "| Global Round : 43 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.447644\n",
            "| Global Round : 43 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.444148\n",
            "| Global Round : 43 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.441993\n",
            "| Global Round : 43 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.439245\n",
            "| Global Round : 43 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.436044\n",
            "| Global Round : 43 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.433355\n",
            "| Global Round : 43 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.430723\n",
            "| Global Round : 43 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.428689\n",
            "| Global Round : 43 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.425098\n",
            "| Global Round : 43 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.421093\n",
            "| Global Round : 43 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.416861\n",
            "| Global Round : 43 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.411775\n",
            "| Global Round : 43 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.408358\n",
            "| Global Round : 43 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.406979\n",
            "| Global Round : 43 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.403847\n",
            "| Global Round : 43 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.400922\n",
            "| Global Round : 43 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.396658\n",
            "| Global Round : 43 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.392723\n",
            "| Global Round : 43 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.389113\n",
            "| Global Round : 43 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.385632\n",
            "| Global Round : 43 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.384010\n",
            "| Global Round : 43 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.386333\n",
            "| Global Round : 43 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.404564\n",
            "| Global Round : 43 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.392512\n",
            "| Global Round : 43 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.376453\n",
            "| Global Round : 43 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.372405\n",
            "| Global Round : 43 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.378641\n",
            "| Global Round : 43 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.378245\n",
            "| Global Round : 43 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.365127\n",
            "| Global Round : 43 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.359484\n",
            "| Global Round : 43 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.359196\n",
            "| Global Round : 43 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.360331\n",
            "| Global Round : 43 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.367387\n",
            "| Global Round : 43 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.376615\n",
            "| Global Round : 43 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.380370\n",
            "| Global Round : 43 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.357288\n",
            "| Global Round : 43 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.345839\n",
            "| Global Round : 43 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.346037\n",
            "| Global Round : 43 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.350996\n",
            "| Global Round : 43 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.355823\n",
            "| Global Round : 43 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.355892\n",
            "| Global Round : 43 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.353461\n",
            "| Global Round : 43 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.347292\n",
            "| Global Round : 43 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.334762\n",
            "| Global Round : 43 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.328993\n",
            "| Global Round : 43 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.329858\n",
            "| Global Round : 43 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.960206\n",
            "| Global Round : 43 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.066033\n",
            "| Global Round : 43 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.133542\n",
            "| Global Round : 43 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.122383\n",
            "| Global Round : 43 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.232405\n",
            "| Global Round : 43 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.959331\n",
            "| Global Round : 43 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.827010\n",
            "| Global Round : 43 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.864399\n",
            "| Global Round : 43 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.891460\n",
            "| Global Round : 43 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.839068\n",
            "| Global Round : 43 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.821140\n",
            "| Global Round : 43 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.923761\n",
            "| Global Round : 43 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.796166\n",
            "| Global Round : 43 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.841200\n",
            "| Global Round : 43 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.836499\n",
            "| Global Round : 43 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.751565\n",
            "| Global Round : 43 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.727110\n",
            "| Global Round : 43 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.731361\n",
            "| Global Round : 43 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.670793\n",
            "| Global Round : 43 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.692725\n",
            "| Global Round : 43 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.667256\n",
            "| Global Round : 43 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.651729\n",
            "| Global Round : 43 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.672111\n",
            "| Global Round : 43 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.632022\n",
            "| Global Round : 43 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.641158\n",
            "| Global Round : 43 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.623912\n",
            "| Global Round : 43 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.598699\n",
            "| Global Round : 43 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.604888\n",
            "| Global Round : 43 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.570866\n",
            "| Global Round : 43 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.579625\n",
            "| Global Round : 43 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.548382\n",
            "| Global Round : 43 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.590341\n",
            "| Global Round : 43 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.586684\n",
            "| Global Round : 43 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.573013\n",
            "| Global Round : 43 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.566550\n",
            "| Global Round : 43 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.527006\n",
            "| Global Round : 43 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.531101\n",
            "| Global Round : 43 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.510222\n",
            "| Global Round : 43 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.513231\n",
            "| Global Round : 43 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.509700\n",
            "| Global Round : 43 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.490576\n",
            "| Global Round : 43 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.486555\n",
            "| Global Round : 43 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.487681\n",
            "| Global Round : 43 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.486125\n",
            "| Global Round : 43 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.479485\n",
            "| Global Round : 43 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.471862\n",
            "| Global Round : 43 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.476452\n",
            "| Global Round : 43 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.523186\n",
            "| Global Round : 43 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.487874\n",
            "| Global Round : 43 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.483944\n",
            "| Global Round : 43 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.454127\n",
            "| Global Round : 43 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.456954\n",
            "| Global Round : 43 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.485953\n",
            "| Global Round : 43 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.469396\n",
            "| Global Round : 43 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.466977\n",
            "| Global Round : 43 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.442373\n",
            "| Global Round : 43 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.444080\n",
            "| Global Round : 43 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.469708\n",
            "| Global Round : 43 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.459311\n",
            "| Global Round : 43 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.459434\n",
            "| Global Round : 43 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.435772\n",
            "| Global Round : 43 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.429978\n",
            "| Global Round : 43 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.437975\n",
            "| Global Round : 43 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.443912\n",
            "| Global Round : 43 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.463091\n",
            "| Global Round : 43 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.439125\n",
            "| Global Round : 43 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.427698\n",
            "| Global Round : 43 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.417607\n",
            "| Global Round : 43 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.424336\n",
            "| Global Round : 43 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.468559\n",
            "| Global Round : 43 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.467657\n",
            "| Global Round : 43 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.520096\n",
            "| Global Round : 43 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.421183\n",
            "| Global Round : 43 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.431917\n",
            "| Global Round : 43 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.540170\n",
            "| Global Round : 43 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.421517\n",
            "| Global Round : 43 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.425598\n",
            "| Global Round : 43 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.518896\n",
            "| Global Round : 43 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.415773\n",
            "| Global Round : 43 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.442616\n",
            "| Global Round : 43 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.578529\n",
            "| Global Round : 43 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.413534\n",
            "| Global Round : 43 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.807631\n",
            "| Global Round : 43 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.927659\n",
            "| Global Round : 43 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 1.177973\n",
            "| Global Round : 43 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.921226\n",
            "| Global Round : 43 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.714042\n",
            "| Global Round : 43 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.941536\n",
            "| Global Round : 43 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.524719\n",
            "| Global Round : 43 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.657220\n",
            "| Global Round : 43 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.696057\n",
            "| Global Round : 43 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.669263\n",
            "| Global Round : 43 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.698359\n",
            "| Global Round : 43 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.567376\n",
            "| Global Round : 43 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.566251\n",
            "| Global Round : 43 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.606882\n",
            "| Global Round : 43 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.617808\n",
            "| Global Round : 43 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.621086\n",
            "| Global Round : 43 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.611337\n",
            "| Global Round : 43 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.571132\n",
            "| Global Round : 43 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.693273\n",
            "| Global Round : 43 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.319863\n",
            "| Global Round : 43 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.949970\n",
            "| Global Round : 43 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 2.451452\n",
            "| Global Round : 43 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 0.834315\n",
            "| Global Round : 43 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.901305\n",
            "| Global Round : 43 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.058359\n",
            "| Global Round : 43 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.149074\n",
            "| Global Round : 43 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.122046\n",
            "| Global Round : 43 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.001107\n",
            "| Global Round : 43 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.831218\n",
            "| Global Round : 43 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.769388\n",
            "| Global Round : 43 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.881119\n",
            "| Global Round : 43 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.855271\n",
            "| Global Round : 43 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.828278\n",
            "| Global Round : 43 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.792860\n",
            "| Global Round : 43 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.777521\n",
            "| Global Round : 43 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.789348\n",
            "| Global Round : 43 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.803891\n",
            "| Global Round : 43 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.812273\n",
            "| Global Round : 43 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.806288\n",
            "| Global Round : 43 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.787481\n",
            "| Global Round : 43 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.762109\n",
            "| Global Round : 43 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.735743\n",
            "| Global Round : 43 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.718992\n",
            "| Global Round : 43 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.712545\n",
            "| Global Round : 43 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.715296\n",
            "| Global Round : 43 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.715026\n",
            "| Global Round : 43 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.705718\n",
            "| Global Round : 43 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.692813\n",
            "| Global Round : 43 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.685514\n",
            "| Global Round : 43 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.681178\n",
            "| Global Round : 43 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.673896\n",
            "| Global Round : 43 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.663844\n",
            "| Global Round : 43 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.654528\n",
            "| Global Round : 43 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.647114\n",
            "| Global Round : 43 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.642196\n",
            "| Global Round : 43 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.637090\n",
            "| Global Round : 43 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.630972\n",
            "| Global Round : 43 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.624975\n",
            "| Global Round : 43 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.619038\n",
            "| Global Round : 43 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.613656\n",
            "| Global Round : 43 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.609008\n",
            "| Global Round : 43 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.605094\n",
            "| Global Round : 43 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.601628\n",
            "| Global Round : 43 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.597065\n",
            "| Global Round : 43 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.592680\n",
            "| Global Round : 43 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.588250\n",
            "| Global Round : 43 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.583476\n",
            "| Global Round : 43 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.577709\n",
            "| Global Round : 43 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.572299\n",
            "| Global Round : 43 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.567301\n",
            "| Global Round : 43 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.564008\n",
            "| Global Round : 43 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.560538\n",
            "| Global Round : 43 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.555262\n",
            "| Global Round : 43 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.550375\n",
            "| Global Round : 43 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.547074\n",
            "| Global Round : 43 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.540469\n",
            "| Global Round : 43 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.538854\n",
            "| Global Round : 43 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.528065\n",
            "| Global Round : 43 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.525095\n",
            "| Global Round : 43 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.523360\n",
            "| Global Round : 43 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.519511\n",
            "| Global Round : 43 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.511785\n",
            "| Global Round : 43 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.514281\n",
            "| Global Round : 43 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.507565\n",
            "| Global Round : 43 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.500738\n",
            "| Global Round : 43 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.518440\n",
            "| Global Round : 43 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.515359\n",
            "| Global Round : 43 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.504106\n",
            "| Global Round : 43 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.518619\n",
            "| Global Round : 43 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.490251\n",
            "| Global Round : 43 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.491916\n",
            "| Global Round : 43 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.493215\n",
            "| Global Round : 43 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.483984\n",
            "| Global Round : 43 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.475694\n",
            "| Global Round : 43 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.475468\n",
            "| Global Round : 43 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.474376\n",
            "| Global Round : 43 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.468636\n",
            "| Global Round : 43 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.463235\n",
            "| Global Round : 43 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.466246\n",
            "| Global Round : 43 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.461326\n",
            "| Global Round : 43 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.463073\n",
            "| Global Round : 43 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.462925\n",
            "| Global Round : 43 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.454444\n",
            "| Global Round : 43 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.449750\n",
            "| Global Round : 43 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.457705\n",
            "| Global Round : 43 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.477788\n",
            "| Global Round : 43 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.495510\n",
            "| Global Round : 43 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.448895\n",
            "| Global Round : 43 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.462867\n",
            "| Global Round : 43 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.471333\n",
            "| Global Round : 43 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.439784\n",
            "| Global Round : 43 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.466380\n",
            "| Global Round : 43 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.477767\n",
            "| Global Round : 43 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.432890\n",
            "| Global Round : 43 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.459555\n",
            "| Global Round : 43 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.477360\n",
            "| Global Round : 43 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.429139\n",
            "| Global Round : 43 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.463401\n",
            "| Global Round : 43 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.765723\n",
            "| Global Round : 43 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.241275\n",
            "| Global Round : 43 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.149892\n",
            "| Global Round : 43 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.971969\n",
            "| Global Round : 43 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 0.934337\n",
            "| Global Round : 43 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 0.929294\n",
            "| Global Round : 43 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 1.013188\n",
            "| Global Round : 43 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.049896\n",
            "| Global Round : 43 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 0.991835\n",
            "| Global Round : 43 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.874949\n",
            "| Global Round : 43 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.775455\n",
            "| Global Round : 43 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.843029\n",
            "| Global Round : 43 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.888923\n",
            "| Global Round : 43 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.836584\n",
            "| Global Round : 43 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.797258\n",
            "| Global Round : 43 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.817120\n",
            "| Global Round : 43 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.832422\n",
            "| Global Round : 43 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.835614\n",
            "| Global Round : 43 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.818266\n",
            "| Global Round : 43 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.787942\n",
            "| Global Round : 43 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.773628\n",
            "| Global Round : 43 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.780896\n",
            "| Global Round : 43 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.766813\n",
            "| Global Round : 43 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.749873\n",
            "| Global Round : 43 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.746200\n",
            "| Global Round : 43 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.757970\n",
            "| Global Round : 43 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.759623\n",
            "| Global Round : 43 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.743908\n",
            "| Global Round : 43 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.731583\n",
            "| Global Round : 43 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.730623\n",
            "| Global Round : 43 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.730111\n",
            "| Global Round : 43 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.721440\n",
            "| Global Round : 43 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.707245\n",
            "| Global Round : 43 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.699738\n",
            "| Global Round : 43 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.701203\n",
            "| Global Round : 43 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.692360\n",
            "| Global Round : 43 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.681633\n",
            "| Global Round : 43 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.678602\n",
            "| Global Round : 43 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.675101\n",
            "| Global Round : 43 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.671186\n",
            "| Global Round : 43 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.663788\n",
            "| Global Round : 43 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.656955\n",
            "| Global Round : 43 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.652968\n",
            "| Global Round : 43 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.648352\n",
            "| Global Round : 43 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.642601\n",
            "| Global Round : 43 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.634729\n",
            "| Global Round : 43 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.625763\n",
            "| Global Round : 43 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.620690\n",
            "| Global Round : 43 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.609044\n",
            "| Global Round : 43 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.598718\n",
            "| Global Round : 43 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.615467\n",
            "| Global Round : 43 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.597348\n",
            "| Global Round : 43 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.596680\n",
            "| Global Round : 43 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.590380\n",
            "| Global Round : 43 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.576954\n",
            "| Global Round : 43 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.577342\n",
            "| Global Round : 43 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.558024\n",
            "| Global Round : 43 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.559593\n",
            "| Global Round : 43 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.544443\n",
            "| Global Round : 43 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.543822\n",
            "| Global Round : 43 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.532015\n",
            "| Global Round : 43 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.519914\n",
            "| Global Round : 43 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.522000\n",
            "| Global Round : 43 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.532696\n",
            "| Global Round : 43 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.562860\n",
            "| Global Round : 43 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.553716\n",
            "| Global Round : 43 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.505899\n",
            "| Global Round : 43 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.525258\n",
            "| Global Round : 43 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.527566\n",
            "| Global Round : 43 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.491429\n",
            "| Global Round : 43 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.504837\n",
            "| Global Round : 43 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.514355\n",
            "| Global Round : 43 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.481447\n",
            "| Global Round : 43 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.497452\n",
            "| Global Round : 43 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.517158\n",
            "| Global Round : 43 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.484102\n",
            "| Global Round : 43 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.470560\n",
            "| Global Round : 43 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.479726\n",
            "| Global Round : 43 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.476319\n",
            "| Global Round : 43 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.465563\n",
            "| Global Round : 43 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.460263\n",
            "| Global Round : 43 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.466883\n",
            "| Global Round : 43 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.469330\n",
            "| Global Round : 43 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.461705\n",
            "| Global Round : 43 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.457051\n",
            "| Global Round : 43 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.450446\n",
            "| Global Round : 43 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.445921\n",
            "| Global Round : 43 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.444634\n",
            "| Global Round : 43 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.443347\n",
            "| Global Round : 43 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.446295\n",
            "| Global Round : 43 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.450511\n",
            "| Global Round : 43 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.459441\n",
            "| Global Round : 43 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.485145\n",
            "| Global Round : 43 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.473463\n",
            "| Global Round : 43 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.465656\n",
            "| Global Round : 43 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.439574\n",
            "| Global Round : 43 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.427930\n",
            "| Global Round : 43 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.443548\n",
            "| Global Round : 43 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.467825\n",
            "| Global Round : 43 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.506705\n",
            "Global Round :43, the training accuracy is 63.3%, and the training loss is 0.896.\n",
            "Global Round :43, the testing accuracy is 59.1%, and the testing loss is 1.5.\n",
            "| Global Round : 44 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.851361\n",
            "| Global Round : 44 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 1.805967\n",
            "| Global Round : 44 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.746618\n",
            "| Global Round : 44 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 1.727419\n",
            "| Global Round : 44 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.801253\n",
            "| Global Round : 44 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.752487\n",
            "| Global Round : 44 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 0.967794\n",
            "| Global Round : 44 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 1.065422\n",
            "| Global Round : 44 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.019774\n",
            "| Global Round : 44 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.877949\n",
            "| Global Round : 44 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.741004\n",
            "| Global Round : 44 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.706559\n",
            "| Global Round : 44 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.799763\n",
            "| Global Round : 44 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.829572\n",
            "| Global Round : 44 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.740073\n",
            "| Global Round : 44 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.677750\n",
            "| Global Round : 44 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.686808\n",
            "| Global Round : 44 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.702596\n",
            "| Global Round : 44 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.681322\n",
            "| Global Round : 44 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.667243\n",
            "| Global Round : 44 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.663041\n",
            "| Global Round : 44 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.657461\n",
            "| Global Round : 44 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.649369\n",
            "| Global Round : 44 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.639334\n",
            "| Global Round : 44 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.623639\n",
            "| Global Round : 44 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.604735\n",
            "| Global Round : 44 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.578053\n",
            "| Global Round : 44 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.607913\n",
            "| Global Round : 44 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.552531\n",
            "| Global Round : 44 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.569448\n",
            "| Global Round : 44 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.561200\n",
            "| Global Round : 44 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.520545\n",
            "| Global Round : 44 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.523777\n",
            "| Global Round : 44 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.508904\n",
            "| Global Round : 44 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.496695\n",
            "| Global Round : 44 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.502054\n",
            "| Global Round : 44 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.469124\n",
            "| Global Round : 44 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.495922\n",
            "| Global Round : 44 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.463997\n",
            "| Global Round : 44 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.464094\n",
            "| Global Round : 44 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.442419\n",
            "| Global Round : 44 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.436236\n",
            "| Global Round : 44 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.440688\n",
            "| Global Round : 44 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.428584\n",
            "| Global Round : 44 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.436738\n",
            "| Global Round : 44 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.414294\n",
            "| Global Round : 44 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.420400\n",
            "| Global Round : 44 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.402740\n",
            "| Global Round : 44 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.411473\n",
            "| Global Round : 44 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.398520\n",
            "| Global Round : 44 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.395165\n",
            "| Global Round : 44 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.394495\n",
            "| Global Round : 44 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.381013\n",
            "| Global Round : 44 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.388741\n",
            "| Global Round : 44 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.380851\n",
            "| Global Round : 44 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.372747\n",
            "| Global Round : 44 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.374324\n",
            "| Global Round : 44 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.367502\n",
            "| Global Round : 44 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.363382\n",
            "| Global Round : 44 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.364161\n",
            "| Global Round : 44 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.359110\n",
            "| Global Round : 44 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.352679\n",
            "| Global Round : 44 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.351398\n",
            "| Global Round : 44 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.350500\n",
            "| Global Round : 44 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.347649\n",
            "| Global Round : 44 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.343689\n",
            "| Global Round : 44 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.340096\n",
            "| Global Round : 44 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.336978\n",
            "| Global Round : 44 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.334939\n",
            "| Global Round : 44 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.333618\n",
            "| Global Round : 44 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.333959\n",
            "| Global Round : 44 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.342461\n",
            "| Global Round : 44 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.365009\n",
            "| Global Round : 44 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.382749\n",
            "| Global Round : 44 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.389604\n",
            "| Global Round : 44 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.344168\n",
            "| Global Round : 44 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.323449\n",
            "| Global Round : 44 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.352964\n",
            "| Global Round : 44 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.356549\n",
            "| Global Round : 44 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.328408\n",
            "| Global Round : 44 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.316995\n",
            "| Global Round : 44 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.331951\n",
            "| Global Round : 44 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.340277\n",
            "| Global Round : 44 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.327230\n",
            "| Global Round : 44 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.311877\n",
            "| Global Round : 44 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.309953\n",
            "| Global Round : 44 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.326712\n",
            "| Global Round : 44 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.354772\n",
            "| Global Round : 44 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.344942\n",
            "| Global Round : 44 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.326498\n",
            "| Global Round : 44 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.307551\n",
            "| Global Round : 44 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.303400\n",
            "| Global Round : 44 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.316142\n",
            "| Global Round : 44 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.330778\n",
            "| Global Round : 44 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.337382\n",
            "| Global Round : 44 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.317361\n",
            "| Global Round : 44 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.294962\n",
            "| Global Round : 44 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.295505\n",
            "| Global Round : 44 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.306160\n",
            "| Global Round : 44 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.310076\n",
            "| Global Round : 44 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 1.036338\n",
            "| Global Round : 44 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.025439\n",
            "| Global Round : 44 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 0.855073\n",
            "| Global Round : 44 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.387548\n",
            "| Global Round : 44 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.030236\n",
            "| Global Round : 44 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.761580\n",
            "| Global Round : 44 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.853050\n",
            "| Global Round : 44 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.964884\n",
            "| Global Round : 44 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.971269\n",
            "| Global Round : 44 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.899493\n",
            "| Global Round : 44 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.819588\n",
            "| Global Round : 44 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.816176\n",
            "| Global Round : 44 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.863587\n",
            "| Global Round : 44 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.836984\n",
            "| Global Round : 44 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.738878\n",
            "| Global Round : 44 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.711037\n",
            "| Global Round : 44 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.742698\n",
            "| Global Round : 44 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.727030\n",
            "| Global Round : 44 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.684845\n",
            "| Global Round : 44 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.687036\n",
            "| Global Round : 44 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.658320\n",
            "| Global Round : 44 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.611274\n",
            "| Global Round : 44 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.626480\n",
            "| Global Round : 44 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.620781\n",
            "| Global Round : 44 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.647839\n",
            "| Global Round : 44 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.601639\n",
            "| Global Round : 44 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.607103\n",
            "| Global Round : 44 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.565472\n",
            "| Global Round : 44 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.595874\n",
            "| Global Round : 44 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.559212\n",
            "| Global Round : 44 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.566663\n",
            "| Global Round : 44 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.541521\n",
            "| Global Round : 44 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.542981\n",
            "| Global Round : 44 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.518462\n",
            "| Global Round : 44 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.533492\n",
            "| Global Round : 44 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.509917\n",
            "| Global Round : 44 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.510213\n",
            "| Global Round : 44 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.511249\n",
            "| Global Round : 44 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.501909\n",
            "| Global Round : 44 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.519566\n",
            "| Global Round : 44 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.493748\n",
            "| Global Round : 44 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.480154\n",
            "| Global Round : 44 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.534306\n",
            "| Global Round : 44 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.567952\n",
            "| Global Round : 44 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.482635\n",
            "| Global Round : 44 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.637062\n",
            "| Global Round : 44 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.594862\n",
            "| Global Round : 44 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.674514\n",
            "| Global Round : 44 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.515735\n",
            "| Global Round : 44 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.766284\n",
            "| Global Round : 44 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.487409\n",
            "| Global Round : 44 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.633474\n",
            "| Global Round : 44 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.573183\n",
            "| Global Round : 44 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.507384\n",
            "| Global Round : 44 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.602620\n",
            "| Global Round : 44 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.474998\n",
            "| Global Round : 44 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.550405\n",
            "| Global Round : 44 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.530786\n",
            "| Global Round : 44 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.487030\n",
            "| Global Round : 44 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.547758\n",
            "| Global Round : 44 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.458446\n",
            "| Global Round : 44 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.495207\n",
            "| Global Round : 44 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.486135\n",
            "| Global Round : 44 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.485873\n",
            "| Global Round : 44 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.480343\n",
            "| Global Round : 44 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.454506\n",
            "| Global Round : 44 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.470493\n",
            "| Global Round : 44 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.448786\n",
            "| Global Round : 44 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.475867\n",
            "| Global Round : 44 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.433737\n",
            "| Global Round : 44 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.447511\n",
            "| Global Round : 44 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.434685\n",
            "| Global Round : 44 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.449051\n",
            "| Global Round : 44 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.428758\n",
            "| Global Round : 44 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.429674\n",
            "| Global Round : 44 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.427886\n",
            "| Global Round : 44 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.424053\n",
            "| Global Round : 44 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.423029\n",
            "| Global Round : 44 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.410588\n",
            "| Global Round : 44 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.432164\n",
            "| Global Round : 44 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.415423\n",
            "| Global Round : 44 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.407252\n",
            "| Global Round : 44 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.420803\n",
            "| Global Round : 44 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.406292\n",
            "| Global Round : 44 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.405006\n",
            "| Global Round : 44 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.412894\n",
            "| Global Round : 44 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.398354\n",
            "| Global Round : 44 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.397787\n",
            "| Global Round : 44 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.404972\n",
            "| Global Round : 44 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.392427\n",
            "| Global Round : 44 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.393403\n",
            "| Global Round : 44 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.398423\n",
            "| Global Round : 44 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.390616\n",
            "| Global Round : 44 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.385113\n",
            "| Global Round : 44 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.390058\n",
            "| Global Round : 44 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.385755\n",
            "| Global Round : 44 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.380713\n",
            "| Global Round : 44 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.382636\n",
            "| Global Round : 44 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.385444\n",
            "| Global Round : 44 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.379736\n",
            "| Global Round : 44 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.808887\n",
            "| Global Round : 44 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 1.944927\n",
            "| Global Round : 44 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.716589\n",
            "| Global Round : 44 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 2.144941\n",
            "| Global Round : 44 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 0.762649\n",
            "| Global Round : 44 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.804559\n",
            "| Global Round : 44 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.100778\n",
            "| Global Round : 44 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.247955\n",
            "| Global Round : 44 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.227374\n",
            "| Global Round : 44 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.108998\n",
            "| Global Round : 44 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.977503\n",
            "| Global Round : 44 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.880051\n",
            "| Global Round : 44 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.827052\n",
            "| Global Round : 44 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.813920\n",
            "| Global Round : 44 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.836743\n",
            "| Global Round : 44 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.857032\n",
            "| Global Round : 44 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.835650\n",
            "| Global Round : 44 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.786965\n",
            "| Global Round : 44 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.746089\n",
            "| Global Round : 44 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.731531\n",
            "| Global Round : 44 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.742086\n",
            "| Global Round : 44 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.769254\n",
            "| Global Round : 44 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.744325\n",
            "| Global Round : 44 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.709775\n",
            "| Global Round : 44 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.683273\n",
            "| Global Round : 44 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.672362\n",
            "| Global Round : 44 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.674199\n",
            "| Global Round : 44 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.654857\n",
            "| Global Round : 44 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.643341\n",
            "| Global Round : 44 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.633946\n",
            "| Global Round : 44 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.625179\n",
            "| Global Round : 44 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.623499\n",
            "| Global Round : 44 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.614254\n",
            "| Global Round : 44 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.627352\n",
            "| Global Round : 44 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.608770\n",
            "| Global Round : 44 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.610110\n",
            "| Global Round : 44 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.598659\n",
            "| Global Round : 44 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.583298\n",
            "| Global Round : 44 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.585532\n",
            "| Global Round : 44 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.572405\n",
            "| Global Round : 44 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.571712\n",
            "| Global Round : 44 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.558258\n",
            "| Global Round : 44 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.562994\n",
            "| Global Round : 44 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.549105\n",
            "| Global Round : 44 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.547625\n",
            "| Global Round : 44 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.537712\n",
            "| Global Round : 44 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.534855\n",
            "| Global Round : 44 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.529023\n",
            "| Global Round : 44 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.523290\n",
            "| Global Round : 44 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.518864\n",
            "| Global Round : 44 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.513635\n",
            "| Global Round : 44 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.512904\n",
            "| Global Round : 44 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.504335\n",
            "| Global Round : 44 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.504472\n",
            "| Global Round : 44 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.497040\n",
            "| Global Round : 44 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.497173\n",
            "| Global Round : 44 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.493748\n",
            "| Global Round : 44 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.489391\n",
            "| Global Round : 44 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.491429\n",
            "| Global Round : 44 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.483718\n",
            "| Global Round : 44 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.488279\n",
            "| Global Round : 44 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.488172\n",
            "| Global Round : 44 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.477137\n",
            "| Global Round : 44 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.482529\n",
            "| Global Round : 44 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.472641\n",
            "| Global Round : 44 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.476527\n",
            "| Global Round : 44 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.470805\n",
            "| Global Round : 44 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.467516\n",
            "| Global Round : 44 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.473106\n",
            "| Global Round : 44 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.460954\n",
            "| Global Round : 44 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.470331\n",
            "| Global Round : 44 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.481602\n",
            "| Global Round : 44 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.456949\n",
            "| Global Round : 44 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.472014\n",
            "| Global Round : 44 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.481629\n",
            "| Global Round : 44 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.452152\n",
            "| Global Round : 44 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.484245\n",
            "| Global Round : 44 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.478194\n",
            "| Global Round : 44 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.451391\n",
            "| Global Round : 44 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.483468\n",
            "| Global Round : 44 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.450642\n",
            "| Global Round : 44 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.458014\n",
            "| Global Round : 44 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.458227\n",
            "| Global Round : 44 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.441317\n",
            "| Global Round : 44 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.453960\n",
            "| Global Round : 44 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.441103\n",
            "| Global Round : 44 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.437516\n",
            "| Global Round : 44 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.442411\n",
            "| Global Round : 44 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.435518\n",
            "| Global Round : 44 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.431354\n",
            "| Global Round : 44 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.431257\n",
            "| Global Round : 44 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.432242\n",
            "| Global Round : 44 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.434258\n",
            "| Global Round : 44 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.432235\n",
            "| Global Round : 44 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.429942\n",
            "| Global Round : 44 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.423831\n",
            "| Global Round : 44 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.424348\n",
            "| Global Round : 44 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.432870\n",
            "| Global Round : 44 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.435782\n",
            "| Global Round : 44 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.434556\n",
            "| Global Round : 44 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.902129\n",
            "| Global Round : 44 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 1.681961\n",
            "| Global Round : 44 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.122781\n",
            "| Global Round : 44 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 0.878849\n",
            "| Global Round : 44 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 0.791099\n",
            "| Global Round : 44 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 0.779652\n",
            "| Global Round : 44 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.795460\n",
            "| Global Round : 44 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 0.747786\n",
            "| Global Round : 44 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 0.746062\n",
            "| Global Round : 44 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.709372\n",
            "| Global Round : 44 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.688779\n",
            "| Global Round : 44 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.673513\n",
            "| Global Round : 44 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.648313\n",
            "| Global Round : 44 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.614798\n",
            "| Global Round : 44 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.627028\n",
            "| Global Round : 44 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.604876\n",
            "| Global Round : 44 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.609947\n",
            "| Global Round : 44 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.598419\n",
            "| Global Round : 44 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.576485\n",
            "| Global Round : 44 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.604954\n",
            "| Global Round : 44 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.604218\n",
            "| Global Round : 44 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.576552\n",
            "| Global Round : 44 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.610804\n",
            "| Global Round : 44 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.558576\n",
            "| Global Round : 44 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.570902\n",
            "| Global Round : 44 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.549355\n",
            "| Global Round : 44 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.545854\n",
            "| Global Round : 44 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.556291\n",
            "| Global Round : 44 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.524400\n",
            "| Global Round : 44 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.565216\n",
            "| Global Round : 44 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.555799\n",
            "| Global Round : 44 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.530991\n",
            "| Global Round : 44 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.580781\n",
            "| Global Round : 44 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.532804\n",
            "| Global Round : 44 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.533166\n",
            "| Global Round : 44 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.543121\n",
            "| Global Round : 44 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.503861\n",
            "| Global Round : 44 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.534954\n",
            "| Global Round : 44 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.502097\n",
            "| Global Round : 44 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.524165\n",
            "| Global Round : 44 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.527007\n",
            "| Global Round : 44 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.501970\n",
            "| Global Round : 44 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.543568\n",
            "| Global Round : 44 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.499946\n",
            "| Global Round : 44 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.504538\n",
            "| Global Round : 44 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.512252\n",
            "| Global Round : 44 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.481959\n",
            "| Global Round : 44 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.500901\n",
            "| Global Round : 44 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.487443\n",
            "| Global Round : 44 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.475597\n",
            "| Global Round : 44 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.485130\n",
            "| Global Round : 44 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.474109\n",
            "| Global Round : 44 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.469599\n",
            "| Global Round : 44 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.476440\n",
            "| Global Round : 44 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.469722\n",
            "| Global Round : 44 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.464334\n",
            "| Global Round : 44 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.462930\n",
            "| Global Round : 44 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.463720\n",
            "| Global Round : 44 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.464433\n",
            "| Global Round : 44 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.464312\n",
            "| Global Round : 44 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.462081\n",
            "| Global Round : 44 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.459211\n",
            "| Global Round : 44 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.455022\n",
            "| Global Round : 44 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.451790\n",
            "| Global Round : 44 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.449872\n",
            "| Global Round : 44 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.452515\n",
            "| Global Round : 44 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.465152\n",
            "| Global Round : 44 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.499793\n",
            "| Global Round : 44 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.482254\n",
            "| Global Round : 44 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.482133\n",
            "| Global Round : 44 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.449143\n",
            "| Global Round : 44 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.450652\n",
            "| Global Round : 44 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.481458\n",
            "| Global Round : 44 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.479358\n",
            "| Global Round : 44 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.481247\n",
            "| Global Round : 44 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.447742\n",
            "| Global Round : 44 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.462997\n",
            "| Global Round : 44 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.492593\n",
            "| Global Round : 44 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.447632\n",
            "| Global Round : 44 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.444196\n",
            "| Global Round : 44 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.474884\n",
            "| Global Round : 44 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.458542\n",
            "| Global Round : 44 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.434632\n",
            "| Global Round : 44 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.442288\n",
            "| Global Round : 44 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.466817\n",
            "| Global Round : 44 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.512695\n",
            "| Global Round : 44 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.451606\n",
            "| Global Round : 44 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.434455\n",
            "| Global Round : 44 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.451460\n",
            "| Global Round : 44 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.452025\n",
            "| Global Round : 44 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.447309\n",
            "| Global Round : 44 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.426635\n",
            "| Global Round : 44 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.429607\n",
            "| Global Round : 44 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.446290\n",
            "| Global Round : 44 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.434897\n",
            "| Global Round : 44 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.424610\n",
            "| Global Round : 44 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.419174\n",
            "| Global Round : 44 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.425702\n",
            "| Global Round : 44 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.431456\n",
            "| Global Round : 44 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.421663\n",
            "Global Round :44, the training accuracy is 66.3%, and the training loss is 0.796.\n",
            "Global Round :44, the testing accuracy is 66.5%, and the testing loss is 1.39.\n",
            "| Global Round : 45 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.753012\n",
            "| Global Round : 45 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 3.489697\n",
            "| Global Round : 45 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 1.632161\n",
            "| Global Round : 45 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 2.047030\n",
            "| Global Round : 45 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 1.772675\n",
            "| Global Round : 45 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 1.381399\n",
            "| Global Round : 45 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 1.135920\n",
            "| Global Round : 45 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 1.097183\n",
            "| Global Round : 45 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.121537\n",
            "| Global Round : 45 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 1.086067\n",
            "| Global Round : 45 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.995358\n",
            "| Global Round : 45 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.905238\n",
            "| Global Round : 45 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.846944\n",
            "| Global Round : 45 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.850619\n",
            "| Global Round : 45 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.882298\n",
            "| Global Round : 45 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.895817\n",
            "| Global Round : 45 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.881127\n",
            "| Global Round : 45 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.850503\n",
            "| Global Round : 45 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.811070\n",
            "| Global Round : 45 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.782970\n",
            "| Global Round : 45 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.766900\n",
            "| Global Round : 45 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.758239\n",
            "| Global Round : 45 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.749112\n",
            "| Global Round : 45 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.739594\n",
            "| Global Round : 45 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.725108\n",
            "| Global Round : 45 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.711359\n",
            "| Global Round : 45 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.702832\n",
            "| Global Round : 45 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.697454\n",
            "| Global Round : 45 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.688706\n",
            "| Global Round : 45 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.674901\n",
            "| Global Round : 45 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.665032\n",
            "| Global Round : 45 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.653797\n",
            "| Global Round : 45 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.644518\n",
            "| Global Round : 45 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.640899\n",
            "| Global Round : 45 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.639000\n",
            "| Global Round : 45 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.633583\n",
            "| Global Round : 45 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.628001\n",
            "| Global Round : 45 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.623271\n",
            "| Global Round : 45 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.618974\n",
            "| Global Round : 45 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.612765\n",
            "| Global Round : 45 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.605806\n",
            "| Global Round : 45 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.600100\n",
            "| Global Round : 45 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.595379\n",
            "| Global Round : 45 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.590571\n",
            "| Global Round : 45 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.586258\n",
            "| Global Round : 45 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.581296\n",
            "| Global Round : 45 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.577202\n",
            "| Global Round : 45 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.571770\n",
            "| Global Round : 45 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.565911\n",
            "| Global Round : 45 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.561388\n",
            "| Global Round : 45 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.558049\n",
            "| Global Round : 45 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.554116\n",
            "| Global Round : 45 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.550070\n",
            "| Global Round : 45 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.545466\n",
            "| Global Round : 45 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.541190\n",
            "| Global Round : 45 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.536263\n",
            "| Global Round : 45 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.532120\n",
            "| Global Round : 45 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.528175\n",
            "| Global Round : 45 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.523202\n",
            "| Global Round : 45 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.517409\n",
            "| Global Round : 45 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.512430\n",
            "| Global Round : 45 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.506909\n",
            "| Global Round : 45 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.502201\n",
            "| Global Round : 45 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.497479\n",
            "| Global Round : 45 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.492107\n",
            "| Global Round : 45 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.486709\n",
            "| Global Round : 45 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.481871\n",
            "| Global Round : 45 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.477762\n",
            "| Global Round : 45 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.474252\n",
            "| Global Round : 45 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.470964\n",
            "| Global Round : 45 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.467293\n",
            "| Global Round : 45 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.463393\n",
            "| Global Round : 45 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.459698\n",
            "| Global Round : 45 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.455590\n",
            "| Global Round : 45 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.451075\n",
            "| Global Round : 45 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.443349\n",
            "| Global Round : 45 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.437473\n",
            "| Global Round : 45 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.432184\n",
            "| Global Round : 45 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.426289\n",
            "| Global Round : 45 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.423511\n",
            "| Global Round : 45 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.420638\n",
            "| Global Round : 45 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.418092\n",
            "| Global Round : 45 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.414044\n",
            "| Global Round : 45 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.409581\n",
            "| Global Round : 45 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.406540\n",
            "| Global Round : 45 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.403160\n",
            "| Global Round : 45 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.399888\n",
            "| Global Round : 45 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.396903\n",
            "| Global Round : 45 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.392380\n",
            "| Global Round : 45 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.389992\n",
            "| Global Round : 45 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.387134\n",
            "| Global Round : 45 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.386051\n",
            "| Global Round : 45 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.384693\n",
            "| Global Round : 45 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.381722\n",
            "| Global Round : 45 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.380729\n",
            "| Global Round : 45 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.376693\n",
            "| Global Round : 45 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.375261\n",
            "| Global Round : 45 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.371824\n",
            "| Global Round : 45 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.369817\n",
            "| Global Round : 45 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.368352\n",
            "| Global Round : 45 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.925205\n",
            "| Global Round : 45 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.059090\n",
            "| Global Round : 45 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.387553\n",
            "| Global Round : 45 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.111411\n",
            "| Global Round : 45 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.194464\n",
            "| Global Round : 45 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 1.287330\n",
            "| Global Round : 45 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 1.027016\n",
            "| Global Round : 45 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.922755\n",
            "| Global Round : 45 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.923933\n",
            "| Global Round : 45 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.881986\n",
            "| Global Round : 45 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.808633\n",
            "| Global Round : 45 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.816667\n",
            "| Global Round : 45 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.911954\n",
            "| Global Round : 45 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.867728\n",
            "| Global Round : 45 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.777866\n",
            "| Global Round : 45 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.753446\n",
            "| Global Round : 45 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.749939\n",
            "| Global Round : 45 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.738967\n",
            "| Global Round : 45 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.718725\n",
            "| Global Round : 45 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.683931\n",
            "| Global Round : 45 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.654618\n",
            "| Global Round : 45 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.664246\n",
            "| Global Round : 45 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.692284\n",
            "| Global Round : 45 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.691408\n",
            "| Global Round : 45 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.658666\n",
            "| Global Round : 45 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.633443\n",
            "| Global Round : 45 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.628789\n",
            "| Global Round : 45 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.629463\n",
            "| Global Round : 45 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.621707\n",
            "| Global Round : 45 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.604772\n",
            "| Global Round : 45 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.589601\n",
            "| Global Round : 45 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.584172\n",
            "| Global Round : 45 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.580129\n",
            "| Global Round : 45 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.575948\n",
            "| Global Round : 45 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.563615\n",
            "| Global Round : 45 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.548839\n",
            "| Global Round : 45 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.543200\n",
            "| Global Round : 45 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.544163\n",
            "| Global Round : 45 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.536917\n",
            "| Global Round : 45 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.522679\n",
            "| Global Round : 45 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.514628\n",
            "| Global Round : 45 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.509095\n",
            "| Global Round : 45 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.503027\n",
            "| Global Round : 45 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.497741\n",
            "| Global Round : 45 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.494190\n",
            "| Global Round : 45 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.484318\n",
            "| Global Round : 45 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.475643\n",
            "| Global Round : 45 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.475583\n",
            "| Global Round : 45 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.475185\n",
            "| Global Round : 45 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.465584\n",
            "| Global Round : 45 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.456365\n",
            "| Global Round : 45 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.451114\n",
            "| Global Round : 45 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.451739\n",
            "| Global Round : 45 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.456468\n",
            "| Global Round : 45 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.477904\n",
            "| Global Round : 45 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.541535\n",
            "| Global Round : 45 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.477979\n",
            "| Global Round : 45 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.439309\n",
            "| Global Round : 45 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.470187\n",
            "| Global Round : 45 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.481494\n",
            "| Global Round : 45 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.445709\n",
            "| Global Round : 45 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.422059\n",
            "| Global Round : 45 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.440841\n",
            "| Global Round : 45 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.436977\n",
            "| Global Round : 45 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.416832\n",
            "| Global Round : 45 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.428114\n",
            "| Global Round : 45 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.432966\n",
            "| Global Round : 45 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.413749\n",
            "| Global Round : 45 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.405839\n",
            "| Global Round : 45 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.412679\n",
            "| Global Round : 45 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.409475\n",
            "| Global Round : 45 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.400808\n",
            "| Global Round : 45 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.399183\n",
            "| Global Round : 45 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.403304\n",
            "| Global Round : 45 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.403760\n",
            "| Global Round : 45 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.395090\n",
            "| Global Round : 45 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.389125\n",
            "| Global Round : 45 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.387469\n",
            "| Global Round : 45 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.391923\n",
            "| Global Round : 45 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.416462\n",
            "| Global Round : 45 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.444940\n",
            "| Global Round : 45 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.617153\n",
            "| Global Round : 45 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.432435\n",
            "| Global Round : 45 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.389087\n",
            "| Global Round : 45 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.431334\n",
            "| Global Round : 45 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.390949\n",
            "| Global Round : 45 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.401653\n",
            "| Global Round : 45 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.438339\n",
            "| Global Round : 45 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.380188\n",
            "| Global Round : 45 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.424023\n",
            "| Global Round : 45 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.508305\n",
            "| Global Round : 45 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.374920\n",
            "| Global Round : 45 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.529542\n",
            "| Global Round : 45 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.685016\n",
            "| Global Round : 45 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.453421\n",
            "| Global Round : 45 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.736475\n",
            "| Global Round : 45 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.427262\n",
            "| Global Round : 45 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.644925\n",
            "| Global Round : 45 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.455520\n",
            "| Global Round : 45 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.522325\n",
            "| Global Round : 45 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.729611\n",
            "| Global Round : 45 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 5.882440\n",
            "| Global Round : 45 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.980528\n",
            "| Global Round : 45 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 2.210348\n",
            "| Global Round : 45 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 2.571199\n",
            "| Global Round : 45 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 2.285254\n",
            "| Global Round : 45 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.860595\n",
            "| Global Round : 45 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.514692\n",
            "| Global Round : 45 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.325598\n",
            "| Global Round : 45 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.275660\n",
            "| Global Round : 45 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 1.255830\n",
            "| Global Round : 45 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 1.210649\n",
            "| Global Round : 45 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 1.133040\n",
            "| Global Round : 45 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 1.040916\n",
            "| Global Round : 45 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.980434\n",
            "| Global Round : 45 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.967440\n",
            "| Global Round : 45 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.965290\n",
            "| Global Round : 45 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.954014\n",
            "| Global Round : 45 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.936156\n",
            "| Global Round : 45 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.923867\n",
            "| Global Round : 45 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.916486\n",
            "| Global Round : 45 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.905451\n",
            "| Global Round : 45 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.888354\n",
            "| Global Round : 45 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.862171\n",
            "| Global Round : 45 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.829142\n",
            "| Global Round : 45 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.791158\n",
            "| Global Round : 45 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.772421\n",
            "| Global Round : 45 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.773656\n",
            "| Global Round : 45 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.778963\n",
            "| Global Round : 45 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.781083\n",
            "| Global Round : 45 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.783009\n",
            "| Global Round : 45 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.739532\n",
            "| Global Round : 45 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.715337\n",
            "| Global Round : 45 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.702085\n",
            "| Global Round : 45 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.702539\n",
            "| Global Round : 45 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.700433\n",
            "| Global Round : 45 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.701030\n",
            "| Global Round : 45 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.699212\n",
            "| Global Round : 45 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.693895\n",
            "| Global Round : 45 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.684329\n",
            "| Global Round : 45 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.670652\n",
            "| Global Round : 45 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.664565\n",
            "| Global Round : 45 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.660617\n",
            "| Global Round : 45 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.654136\n",
            "| Global Round : 45 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.648255\n",
            "| Global Round : 45 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.649749\n",
            "| Global Round : 45 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.649435\n",
            "| Global Round : 45 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.632838\n",
            "| Global Round : 45 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.623301\n",
            "| Global Round : 45 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.611798\n",
            "| Global Round : 45 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.603792\n",
            "| Global Round : 45 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.596181\n",
            "| Global Round : 45 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.593726\n",
            "| Global Round : 45 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.585447\n",
            "| Global Round : 45 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.579678\n",
            "| Global Round : 45 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.571121\n",
            "| Global Round : 45 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.558432\n",
            "| Global Round : 45 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.562682\n",
            "| Global Round : 45 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.553519\n",
            "| Global Round : 45 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.551806\n",
            "| Global Round : 45 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.554324\n",
            "| Global Round : 45 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.545632\n",
            "| Global Round : 45 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.540174\n",
            "| Global Round : 45 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.534095\n",
            "| Global Round : 45 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.532166\n",
            "| Global Round : 45 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.533422\n",
            "| Global Round : 45 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.525418\n",
            "| Global Round : 45 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.521885\n",
            "| Global Round : 45 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.516901\n",
            "| Global Round : 45 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.515459\n",
            "| Global Round : 45 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.512013\n",
            "| Global Round : 45 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.508469\n",
            "| Global Round : 45 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.506329\n",
            "| Global Round : 45 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.502887\n",
            "| Global Round : 45 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.498867\n",
            "| Global Round : 45 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.496401\n",
            "| Global Round : 45 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.495016\n",
            "| Global Round : 45 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.490169\n",
            "| Global Round : 45 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.493376\n",
            "| Global Round : 45 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.491509\n",
            "| Global Round : 45 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.485202\n",
            "| Global Round : 45 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.483322\n",
            "| Global Round : 45 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.478887\n",
            "| Global Round : 45 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.473594\n",
            "| Global Round : 45 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.474175\n",
            "| Global Round : 45 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.470534\n",
            "| Global Round : 45 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.465975\n",
            "| Global Round : 45 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.467035\n",
            "| Global Round : 45 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.462797\n",
            "| Global Round : 45 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.460696\n",
            "| Global Round : 45 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.456252\n",
            "| Global Round : 45 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.458284\n",
            "| Global Round : 45 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.455582\n",
            "| Global Round : 45 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.450538\n",
            "| Global Round : 45 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.449000\n",
            "| Global Round : 45 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.447246\n",
            "| Global Round : 45 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.450034\n",
            "| Global Round : 45 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.445372\n",
            "| Global Round : 45 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.443308\n",
            "| Global Round : 45 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.439911\n",
            "| Global Round : 45 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.789296\n",
            "| Global Round : 45 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 4.079172\n",
            "| Global Round : 45 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.572890\n",
            "| Global Round : 45 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.731172\n",
            "| Global Round : 45 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 1.521642\n",
            "| Global Round : 45 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 1.346334\n",
            "| Global Round : 45 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 1.368468\n",
            "| Global Round : 45 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.405826\n",
            "| Global Round : 45 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 1.311817\n",
            "| Global Round : 45 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 1.155176\n",
            "| Global Round : 45 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 1.040007\n",
            "| Global Round : 45 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.979367\n",
            "| Global Round : 45 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.911056\n",
            "| Global Round : 45 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.867698\n",
            "| Global Round : 45 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.854837\n",
            "| Global Round : 45 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.857779\n",
            "| Global Round : 45 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.885027\n",
            "| Global Round : 45 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.897982\n",
            "| Global Round : 45 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.876443\n",
            "| Global Round : 45 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.851825\n",
            "| Global Round : 45 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.848633\n",
            "| Global Round : 45 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.846247\n",
            "| Global Round : 45 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.832434\n",
            "| Global Round : 45 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.828849\n",
            "| Global Round : 45 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.828015\n",
            "| Global Round : 45 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.817096\n",
            "| Global Round : 45 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.797330\n",
            "| Global Round : 45 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.771404\n",
            "| Global Round : 45 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.748067\n",
            "| Global Round : 45 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.758535\n",
            "| Global Round : 45 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.747283\n",
            "| Global Round : 45 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.760817\n",
            "| Global Round : 45 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.750154\n",
            "| Global Round : 45 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.729148\n",
            "| Global Round : 45 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.728492\n",
            "| Global Round : 45 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.736423\n",
            "| Global Round : 45 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.730562\n",
            "| Global Round : 45 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.717889\n",
            "| Global Round : 45 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.719064\n",
            "| Global Round : 45 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.721484\n",
            "| Global Round : 45 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.710081\n",
            "| Global Round : 45 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.701330\n",
            "| Global Round : 45 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.705599\n",
            "| Global Round : 45 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.703463\n",
            "| Global Round : 45 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.694055\n",
            "| Global Round : 45 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.694300\n",
            "| Global Round : 45 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.695076\n",
            "| Global Round : 45 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.687547\n",
            "| Global Round : 45 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.683246\n",
            "| Global Round : 45 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.684188\n",
            "| Global Round : 45 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.681262\n",
            "| Global Round : 45 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.676448\n",
            "| Global Round : 45 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.676523\n",
            "| Global Round : 45 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.674429\n",
            "| Global Round : 45 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.669257\n",
            "| Global Round : 45 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.667220\n",
            "| Global Round : 45 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.666089\n",
            "| Global Round : 45 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.662585\n",
            "| Global Round : 45 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.659785\n",
            "| Global Round : 45 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.658741\n",
            "| Global Round : 45 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.656305\n",
            "| Global Round : 45 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.654158\n",
            "| Global Round : 45 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.652026\n",
            "| Global Round : 45 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.649924\n",
            "| Global Round : 45 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.648617\n",
            "| Global Round : 45 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.646043\n",
            "| Global Round : 45 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.643752\n",
            "| Global Round : 45 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.642552\n",
            "| Global Round : 45 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.639418\n",
            "| Global Round : 45 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.637571\n",
            "| Global Round : 45 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.635658\n",
            "| Global Round : 45 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.633315\n",
            "| Global Round : 45 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.631562\n",
            "| Global Round : 45 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.628995\n",
            "| Global Round : 45 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.627563\n",
            "| Global Round : 45 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.625251\n",
            "| Global Round : 45 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.623260\n",
            "| Global Round : 45 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.621541\n",
            "| Global Round : 45 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.619386\n",
            "| Global Round : 45 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.618020\n",
            "| Global Round : 45 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.615641\n",
            "| Global Round : 45 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.613800\n",
            "| Global Round : 45 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.611772\n",
            "| Global Round : 45 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.609826\n",
            "| Global Round : 45 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.608071\n",
            "| Global Round : 45 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.605908\n",
            "| Global Round : 45 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.604111\n",
            "| Global Round : 45 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.602164\n",
            "| Global Round : 45 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.600098\n",
            "| Global Round : 45 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.598235\n",
            "| Global Round : 45 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.595832\n",
            "| Global Round : 45 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.593996\n",
            "| Global Round : 45 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.591767\n",
            "| Global Round : 45 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.589532\n",
            "| Global Round : 45 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.587395\n",
            "| Global Round : 45 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.585217\n",
            "| Global Round : 45 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.583381\n",
            "| Global Round : 45 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.580853\n",
            "| Global Round : 45 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.579158\n",
            "| Global Round : 45 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.577186\n",
            "Global Round :45, the training accuracy is 60.8%, and the training loss is 0.856.\n",
            "Global Round :45, the testing accuracy is 58.1%, and the testing loss is 1.48.\n",
            "| Global Round : 46 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.837108\n",
            "| Global Round : 46 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 1.918245\n",
            "| Global Round : 46 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.827243\n",
            "| Global Round : 46 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 1.262862\n",
            "| Global Round : 46 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.948628\n",
            "| Global Round : 46 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.705521\n",
            "| Global Round : 46 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 0.809734\n",
            "| Global Round : 46 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 0.929766\n",
            "| Global Round : 46 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 0.929817\n",
            "| Global Round : 46 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.832507\n",
            "| Global Round : 46 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.744616\n",
            "| Global Round : 46 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.729603\n",
            "| Global Round : 46 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.738749\n",
            "| Global Round : 46 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.702252\n",
            "| Global Round : 46 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.645031\n",
            "| Global Round : 46 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.637958\n",
            "| Global Round : 46 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.664454\n",
            "| Global Round : 46 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.635409\n",
            "| Global Round : 46 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.635958\n",
            "| Global Round : 46 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.622085\n",
            "| Global Round : 46 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.594371\n",
            "| Global Round : 46 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.555233\n",
            "| Global Round : 46 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.556970\n",
            "| Global Round : 46 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.550152\n",
            "| Global Round : 46 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.538384\n",
            "| Global Round : 46 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.532960\n",
            "| Global Round : 46 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.505869\n",
            "| Global Round : 46 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.501698\n",
            "| Global Round : 46 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.488321\n",
            "| Global Round : 46 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.485881\n",
            "| Global Round : 46 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.490056\n",
            "| Global Round : 46 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.470741\n",
            "| Global Round : 46 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.467826\n",
            "| Global Round : 46 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.453194\n",
            "| Global Round : 46 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.455099\n",
            "| Global Round : 46 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.443876\n",
            "| Global Round : 46 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.438592\n",
            "| Global Round : 46 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.432212\n",
            "| Global Round : 46 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.432222\n",
            "| Global Round : 46 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.426036\n",
            "| Global Round : 46 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.424284\n",
            "| Global Round : 46 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.417852\n",
            "| Global Round : 46 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.416434\n",
            "| Global Round : 46 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.410670\n",
            "| Global Round : 46 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.404276\n",
            "| Global Round : 46 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.405365\n",
            "| Global Round : 46 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.401298\n",
            "| Global Round : 46 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.399048\n",
            "| Global Round : 46 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.394668\n",
            "| Global Round : 46 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.392171\n",
            "| Global Round : 46 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.389530\n",
            "| Global Round : 46 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.387894\n",
            "| Global Round : 46 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.389497\n",
            "| Global Round : 46 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.384374\n",
            "| Global Round : 46 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.380967\n",
            "| Global Round : 46 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.376590\n",
            "| Global Round : 46 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.380585\n",
            "| Global Round : 46 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.391225\n",
            "| Global Round : 46 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.381035\n",
            "| Global Round : 46 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.371029\n",
            "| Global Round : 46 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.365660\n",
            "| Global Round : 46 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.363550\n",
            "| Global Round : 46 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.362783\n",
            "| Global Round : 46 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.362085\n",
            "| Global Round : 46 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.371759\n",
            "| Global Round : 46 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.398831\n",
            "| Global Round : 46 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.434524\n",
            "| Global Round : 46 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.452242\n",
            "| Global Round : 46 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.387999\n",
            "| Global Round : 46 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.375199\n",
            "| Global Round : 46 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.406742\n",
            "| Global Round : 46 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.362418\n",
            "| Global Round : 46 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.384287\n",
            "| Global Round : 46 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.379660\n",
            "| Global Round : 46 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.361063\n",
            "| Global Round : 46 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.384834\n",
            "| Global Round : 46 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.351796\n",
            "| Global Round : 46 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.376248\n",
            "| Global Round : 46 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.369208\n",
            "| Global Round : 46 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.345586\n",
            "| Global Round : 46 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.372978\n",
            "| Global Round : 46 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.369978\n",
            "| Global Round : 46 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.343828\n",
            "| Global Round : 46 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.381708\n",
            "| Global Round : 46 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.380286\n",
            "| Global Round : 46 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.337796\n",
            "| Global Round : 46 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.370028\n",
            "| Global Round : 46 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.392922\n",
            "| Global Round : 46 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.336853\n",
            "| Global Round : 46 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.364707\n",
            "| Global Round : 46 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.384446\n",
            "| Global Round : 46 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.331651\n",
            "| Global Round : 46 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.361389\n",
            "| Global Round : 46 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.388011\n",
            "| Global Round : 46 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.329882\n",
            "| Global Round : 46 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.359218\n",
            "| Global Round : 46 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.369141\n",
            "| Global Round : 46 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.324897\n",
            "| Global Round : 46 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.371665\n",
            "| Global Round : 46 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.383880\n",
            "| Global Round : 46 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.944011\n",
            "| Global Round : 46 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.233597\n",
            "| Global Round : 46 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.065508\n",
            "| Global Round : 46 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 0.945415\n",
            "| Global Round : 46 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.298081\n",
            "| Global Round : 46 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.946611\n",
            "| Global Round : 46 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.819028\n",
            "| Global Round : 46 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.899961\n",
            "| Global Round : 46 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.976550\n",
            "| Global Round : 46 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.969400\n",
            "| Global Round : 46 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.881498\n",
            "| Global Round : 46 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.783943\n",
            "| Global Round : 46 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.758449\n",
            "| Global Round : 46 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.807599\n",
            "| Global Round : 46 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.807205\n",
            "| Global Round : 46 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.738808\n",
            "| Global Round : 46 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.714000\n",
            "| Global Round : 46 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.738387\n",
            "| Global Round : 46 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.756250\n",
            "| Global Round : 46 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.741481\n",
            "| Global Round : 46 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.697849\n",
            "| Global Round : 46 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.668764\n",
            "| Global Round : 46 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.697233\n",
            "| Global Round : 46 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.698730\n",
            "| Global Round : 46 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.655172\n",
            "| Global Round : 46 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.650569\n",
            "| Global Round : 46 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.665707\n",
            "| Global Round : 46 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.653022\n",
            "| Global Round : 46 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.623313\n",
            "| Global Round : 46 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.627447\n",
            "| Global Round : 46 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.636780\n",
            "| Global Round : 46 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.602862\n",
            "| Global Round : 46 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.609791\n",
            "| Global Round : 46 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.615155\n",
            "| Global Round : 46 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.589066\n",
            "| Global Round : 46 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.576924\n",
            "| Global Round : 46 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.579828\n",
            "| Global Round : 46 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.550620\n",
            "| Global Round : 46 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.551400\n",
            "| Global Round : 46 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.539579\n",
            "| Global Round : 46 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.530607\n",
            "| Global Round : 46 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.520832\n",
            "| Global Round : 46 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.515410\n",
            "| Global Round : 46 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.508526\n",
            "| Global Round : 46 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.509141\n",
            "| Global Round : 46 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.488044\n",
            "| Global Round : 46 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.483164\n",
            "| Global Round : 46 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.486073\n",
            "| Global Round : 46 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.484157\n",
            "| Global Round : 46 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.461142\n",
            "| Global Round : 46 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.461953\n",
            "| Global Round : 46 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.474093\n",
            "| Global Round : 46 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.450772\n",
            "| Global Round : 46 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.440931\n",
            "| Global Round : 46 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.437042\n",
            "| Global Round : 46 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.440813\n",
            "| Global Round : 46 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.450169\n",
            "| Global Round : 46 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.436816\n",
            "| Global Round : 46 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.432187\n",
            "| Global Round : 46 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.426646\n",
            "| Global Round : 46 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.420536\n",
            "| Global Round : 46 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.414926\n",
            "| Global Round : 46 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.412957\n",
            "| Global Round : 46 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.414983\n",
            "| Global Round : 46 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.420693\n",
            "| Global Round : 46 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.457752\n",
            "| Global Round : 46 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.472073\n",
            "| Global Round : 46 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.537776\n",
            "| Global Round : 46 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.403690\n",
            "| Global Round : 46 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.508650\n",
            "| Global Round : 46 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.598167\n",
            "| Global Round : 46 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.450171\n",
            "| Global Round : 46 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.754471\n",
            "| Global Round : 46 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.569073\n",
            "| Global Round : 46 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.724902\n",
            "| Global Round : 46 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.430726\n",
            "| Global Round : 46 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.779581\n",
            "| Global Round : 46 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.464361\n",
            "| Global Round : 46 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.699070\n",
            "| Global Round : 46 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.482887\n",
            "| Global Round : 46 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.550939\n",
            "| Global Round : 46 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.492088\n",
            "| Global Round : 46 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.479913\n",
            "| Global Round : 46 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.580055\n",
            "| Global Round : 46 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.424690\n",
            "| Global Round : 46 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.556763\n",
            "| Global Round : 46 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.420990\n",
            "| Global Round : 46 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.474540\n",
            "| Global Round : 46 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.486210\n",
            "| Global Round : 46 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.405555\n",
            "| Global Round : 46 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.505414\n",
            "| Global Round : 46 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.402337\n",
            "| Global Round : 46 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.460483\n",
            "| Global Round : 46 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.420631\n",
            "| Global Round : 46 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.421461\n",
            "| Global Round : 46 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.421935\n",
            "| Global Round : 46 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.407815\n",
            "| Global Round : 46 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.431000\n",
            "| Global Round : 46 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.391225\n",
            "| Global Round : 46 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.432751\n",
            "| Global Round : 46 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.817007\n",
            "| Global Round : 46 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.385898\n",
            "| Global Round : 46 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 0.958855\n",
            "| Global Round : 46 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 1.148039\n",
            "| Global Round : 46 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 1.208772\n",
            "| Global Round : 46 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.790771\n",
            "| Global Round : 46 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 0.793491\n",
            "| Global Round : 46 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 0.926007\n",
            "| Global Round : 46 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 0.983858\n",
            "| Global Round : 46 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 0.937210\n",
            "| Global Round : 46 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.820213\n",
            "| Global Round : 46 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.748679\n",
            "| Global Round : 46 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.785686\n",
            "| Global Round : 46 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.812782\n",
            "| Global Round : 46 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.748449\n",
            "| Global Round : 46 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.699547\n",
            "| Global Round : 46 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.709639\n",
            "| Global Round : 46 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.745790\n",
            "| Global Round : 46 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.759167\n",
            "| Global Round : 46 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.740674\n",
            "| Global Round : 46 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.710495\n",
            "| Global Round : 46 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.691832\n",
            "| Global Round : 46 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.691070\n",
            "| Global Round : 46 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.689573\n",
            "| Global Round : 46 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.672437\n",
            "| Global Round : 46 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.656969\n",
            "| Global Round : 46 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.660821\n",
            "| Global Round : 46 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.668991\n",
            "| Global Round : 46 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.664966\n",
            "| Global Round : 46 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.650504\n",
            "| Global Round : 46 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.639593\n",
            "| Global Round : 46 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.635349\n",
            "| Global Round : 46 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.629993\n",
            "| Global Round : 46 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.621580\n",
            "| Global Round : 46 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.616049\n",
            "| Global Round : 46 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.614258\n",
            "| Global Round : 46 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.609887\n",
            "| Global Round : 46 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.601461\n",
            "| Global Round : 46 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.596187\n",
            "| Global Round : 46 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.593329\n",
            "| Global Round : 46 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.590464\n",
            "| Global Round : 46 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.583853\n",
            "| Global Round : 46 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.577426\n",
            "| Global Round : 46 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.574114\n",
            "| Global Round : 46 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.569796\n",
            "| Global Round : 46 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.563243\n",
            "| Global Round : 46 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.557135\n",
            "| Global Round : 46 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.553720\n",
            "| Global Round : 46 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.549407\n",
            "| Global Round : 46 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.543286\n",
            "| Global Round : 46 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.538289\n",
            "| Global Round : 46 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.531668\n",
            "| Global Round : 46 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.525455\n",
            "| Global Round : 46 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.522186\n",
            "| Global Round : 46 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.516557\n",
            "| Global Round : 46 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.510495\n",
            "| Global Round : 46 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.507329\n",
            "| Global Round : 46 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.502731\n",
            "| Global Round : 46 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.494143\n",
            "| Global Round : 46 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.491639\n",
            "| Global Round : 46 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.482711\n",
            "| Global Round : 46 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.482967\n",
            "| Global Round : 46 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.478409\n",
            "| Global Round : 46 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.471527\n",
            "| Global Round : 46 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.476830\n",
            "| Global Round : 46 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.473659\n",
            "| Global Round : 46 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.493710\n",
            "| Global Round : 46 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.506949\n",
            "| Global Round : 46 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.513769\n",
            "| Global Round : 46 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.471681\n",
            "| Global Round : 46 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.505760\n",
            "| Global Round : 46 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.471984\n",
            "| Global Round : 46 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.485446\n",
            "| Global Round : 46 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.465635\n",
            "| Global Round : 46 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.459287\n",
            "| Global Round : 46 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.474373\n",
            "| Global Round : 46 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.451477\n",
            "| Global Round : 46 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.447864\n",
            "| Global Round : 46 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.460625\n",
            "| Global Round : 46 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.454223\n",
            "| Global Round : 46 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.436723\n",
            "| Global Round : 46 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.443678\n",
            "| Global Round : 46 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.455875\n",
            "| Global Round : 46 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.486214\n",
            "| Global Round : 46 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.464344\n",
            "| Global Round : 46 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.441816\n",
            "| Global Round : 46 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.444187\n",
            "| Global Round : 46 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.446891\n",
            "| Global Round : 46 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.433858\n",
            "| Global Round : 46 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.425139\n",
            "| Global Round : 46 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.453397\n",
            "| Global Round : 46 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.498984\n",
            "| Global Round : 46 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.432065\n",
            "| Global Round : 46 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.439699\n",
            "| Global Round : 46 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.462784\n",
            "| Global Round : 46 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.419093\n",
            "| Global Round : 46 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.471810\n",
            "| Global Round : 46 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.514174\n",
            "| Global Round : 46 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.421179\n",
            "| Global Round : 46 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.520320\n",
            "| Global Round : 46 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.839217\n",
            "| Global Round : 46 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.624060\n",
            "| Global Round : 46 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.119203\n",
            "| Global Round : 46 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 0.971892\n",
            "| Global Round : 46 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 1.550674\n",
            "| Global Round : 46 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 1.093940\n",
            "| Global Round : 46 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.835160\n",
            "| Global Round : 46 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 0.901699\n",
            "| Global Round : 46 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 1.047040\n",
            "| Global Round : 46 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 1.097816\n",
            "| Global Round : 46 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 1.040103\n",
            "| Global Round : 46 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.922390\n",
            "| Global Round : 46 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.803843\n",
            "| Global Round : 46 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.768054\n",
            "| Global Round : 46 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.835721\n",
            "| Global Round : 46 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.867324\n",
            "| Global Round : 46 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.798702\n",
            "| Global Round : 46 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.737321\n",
            "| Global Round : 46 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.752408\n",
            "| Global Round : 46 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.777711\n",
            "| Global Round : 46 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.775191\n",
            "| Global Round : 46 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.752036\n",
            "| Global Round : 46 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.719822\n",
            "| Global Round : 46 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.712978\n",
            "| Global Round : 46 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.731591\n",
            "| Global Round : 46 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.731092\n",
            "| Global Round : 46 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.700521\n",
            "| Global Round : 46 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.684150\n",
            "| Global Round : 46 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.689928\n",
            "| Global Round : 46 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.693263\n",
            "| Global Round : 46 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.681410\n",
            "| Global Round : 46 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.667120\n",
            "| Global Round : 46 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.664214\n",
            "| Global Round : 46 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.666664\n",
            "| Global Round : 46 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.659828\n",
            "| Global Round : 46 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.645266\n",
            "| Global Round : 46 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.640052\n",
            "| Global Round : 46 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.639961\n",
            "| Global Round : 46 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.632234\n",
            "| Global Round : 46 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.625746\n",
            "| Global Round : 46 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.622909\n",
            "| Global Round : 46 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.616711\n",
            "| Global Round : 46 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.609260\n",
            "| Global Round : 46 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.608795\n",
            "| Global Round : 46 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.602013\n",
            "| Global Round : 46 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.595959\n",
            "| Global Round : 46 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.592772\n",
            "| Global Round : 46 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.585316\n",
            "| Global Round : 46 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.582407\n",
            "| Global Round : 46 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.574744\n",
            "| Global Round : 46 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.574537\n",
            "| Global Round : 46 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.568590\n",
            "| Global Round : 46 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.567805\n",
            "| Global Round : 46 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.562204\n",
            "| Global Round : 46 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.558682\n",
            "| Global Round : 46 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.556164\n",
            "| Global Round : 46 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.553104\n",
            "| Global Round : 46 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.550997\n",
            "| Global Round : 46 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.546642\n",
            "| Global Round : 46 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.546462\n",
            "| Global Round : 46 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.541226\n",
            "| Global Round : 46 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.537912\n",
            "| Global Round : 46 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.534175\n",
            "| Global Round : 46 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.532218\n",
            "| Global Round : 46 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.530620\n",
            "| Global Round : 46 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.526360\n",
            "| Global Round : 46 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.524426\n",
            "| Global Round : 46 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.519736\n",
            "| Global Round : 46 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.516025\n",
            "| Global Round : 46 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.514511\n",
            "| Global Round : 46 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.512133\n",
            "| Global Round : 46 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.507384\n",
            "| Global Round : 46 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.505287\n",
            "| Global Round : 46 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.502627\n",
            "| Global Round : 46 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.496314\n",
            "| Global Round : 46 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.497787\n",
            "| Global Round : 46 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.515079\n",
            "| Global Round : 46 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.528457\n",
            "| Global Round : 46 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.494078\n",
            "| Global Round : 46 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.527876\n",
            "| Global Round : 46 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.520387\n",
            "| Global Round : 46 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.492233\n",
            "| Global Round : 46 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.533962\n",
            "| Global Round : 46 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.509748\n",
            "| Global Round : 46 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.491276\n",
            "| Global Round : 46 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.541026\n",
            "| Global Round : 46 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.492339\n",
            "| Global Round : 46 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.490119\n",
            "| Global Round : 46 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.514937\n",
            "| Global Round : 46 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.475875\n",
            "| Global Round : 46 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.488030\n",
            "| Global Round : 46 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.495481\n",
            "| Global Round : 46 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.465892\n",
            "| Global Round : 46 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.480740\n",
            "| Global Round : 46 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.468494\n",
            "| Global Round : 46 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.462853\n",
            "| Global Round : 46 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.474266\n",
            "| Global Round : 46 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.457867\n",
            "| Global Round : 46 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.455434\n",
            "| Global Round : 46 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.465230\n",
            "Global Round :46, the training accuracy is 69.3%, and the training loss is 0.772.\n",
            "Global Round :46, the testing accuracy is 68.5%, and the testing loss is 1.39.\n",
            "| Global Round : 47 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.777789\n",
            "| Global Round : 47 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 0.957314\n",
            "| Global Round : 47 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.941427\n",
            "| Global Round : 47 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 1.041035\n",
            "| Global Round : 47 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.788424\n",
            "| Global Round : 47 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.808352\n",
            "| Global Round : 47 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 0.654381\n",
            "| Global Round : 47 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 0.690325\n",
            "| Global Round : 47 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 0.719430\n",
            "| Global Round : 47 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.640541\n",
            "| Global Round : 47 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.667760\n",
            "| Global Round : 47 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.626617\n",
            "| Global Round : 47 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.549081\n",
            "| Global Round : 47 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.543266\n",
            "| Global Round : 47 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.523052\n",
            "| Global Round : 47 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.554815\n",
            "| Global Round : 47 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.500231\n",
            "| Global Round : 47 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.502413\n",
            "| Global Round : 47 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.510107\n",
            "| Global Round : 47 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.511157\n",
            "| Global Round : 47 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.492876\n",
            "| Global Round : 47 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.470149\n",
            "| Global Round : 47 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.456948\n",
            "| Global Round : 47 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.455251\n",
            "| Global Round : 47 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.457702\n",
            "| Global Round : 47 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.451401\n",
            "| Global Round : 47 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.425834\n",
            "| Global Round : 47 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.431052\n",
            "| Global Round : 47 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.412881\n",
            "| Global Round : 47 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.423432\n",
            "| Global Round : 47 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.412746\n",
            "| Global Round : 47 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.403925\n",
            "| Global Round : 47 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.407972\n",
            "| Global Round : 47 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.385695\n",
            "| Global Round : 47 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.378687\n",
            "| Global Round : 47 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.398331\n",
            "| Global Round : 47 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.392520\n",
            "| Global Round : 47 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.373232\n",
            "| Global Round : 47 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.362543\n",
            "| Global Round : 47 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.359130\n",
            "| Global Round : 47 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.362552\n",
            "| Global Round : 47 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.354330\n",
            "| Global Round : 47 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.348462\n",
            "| Global Round : 47 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.345404\n",
            "| Global Round : 47 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.343561\n",
            "| Global Round : 47 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.345628\n",
            "| Global Round : 47 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.337227\n",
            "| Global Round : 47 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.336080\n",
            "| Global Round : 47 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.331939\n",
            "| Global Round : 47 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.334332\n",
            "| Global Round : 47 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.344667\n",
            "| Global Round : 47 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.375414\n",
            "| Global Round : 47 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.408242\n",
            "| Global Round : 47 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.373868\n",
            "| Global Round : 47 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.330988\n",
            "| Global Round : 47 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.382385\n",
            "| Global Round : 47 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.437759\n",
            "| Global Round : 47 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.360100\n",
            "| Global Round : 47 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.362977\n",
            "| Global Round : 47 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.386031\n",
            "| Global Round : 47 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.343730\n",
            "| Global Round : 47 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.344561\n",
            "| Global Round : 47 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.365338\n",
            "| Global Round : 47 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.332321\n",
            "| Global Round : 47 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.334937\n",
            "| Global Round : 47 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.359138\n",
            "| Global Round : 47 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.323501\n",
            "| Global Round : 47 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.329460\n",
            "| Global Round : 47 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.350585\n",
            "| Global Round : 47 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.325337\n",
            "| Global Round : 47 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.319620\n",
            "| Global Round : 47 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.341235\n",
            "| Global Round : 47 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.326533\n",
            "| Global Round : 47 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.308203\n",
            "| Global Round : 47 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.319673\n",
            "| Global Round : 47 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.324657\n",
            "| Global Round : 47 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.307254\n",
            "| Global Round : 47 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.305527\n",
            "| Global Round : 47 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.306496\n",
            "| Global Round : 47 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.303781\n",
            "| Global Round : 47 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.300011\n",
            "| Global Round : 47 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.297439\n",
            "| Global Round : 47 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.296597\n",
            "| Global Round : 47 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.295017\n",
            "| Global Round : 47 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.295720\n",
            "| Global Round : 47 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.294848\n",
            "| Global Round : 47 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.291709\n",
            "| Global Round : 47 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.291059\n",
            "| Global Round : 47 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.288927\n",
            "| Global Round : 47 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.288140\n",
            "| Global Round : 47 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.285932\n",
            "| Global Round : 47 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.285629\n",
            "| Global Round : 47 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.284796\n",
            "| Global Round : 47 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.284728\n",
            "| Global Round : 47 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.291737\n",
            "| Global Round : 47 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.318163\n",
            "| Global Round : 47 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.437328\n",
            "| Global Round : 47 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.520666\n",
            "| Global Round : 47 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.528699\n",
            "| Global Round : 47 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.386884\n",
            "| Global Round : 47 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.876726\n",
            "| Global Round : 47 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 1.982345\n",
            "| Global Round : 47 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.102181\n",
            "| Global Round : 47 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 0.820002\n",
            "| Global Round : 47 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 0.787163\n",
            "| Global Round : 47 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.840595\n",
            "| Global Round : 47 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.814564\n",
            "| Global Round : 47 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.728462\n",
            "| Global Round : 47 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.694997\n",
            "| Global Round : 47 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.711516\n",
            "| Global Round : 47 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.682678\n",
            "| Global Round : 47 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.684185\n",
            "| Global Round : 47 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.711619\n",
            "| Global Round : 47 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.695546\n",
            "| Global Round : 47 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.654577\n",
            "| Global Round : 47 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.635111\n",
            "| Global Round : 47 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.628335\n",
            "| Global Round : 47 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.614681\n",
            "| Global Round : 47 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.611940\n",
            "| Global Round : 47 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.605373\n",
            "| Global Round : 47 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.591612\n",
            "| Global Round : 47 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.576400\n",
            "| Global Round : 47 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.559889\n",
            "| Global Round : 47 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.545481\n",
            "| Global Round : 47 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.532725\n",
            "| Global Round : 47 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.523204\n",
            "| Global Round : 47 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.505898\n",
            "| Global Round : 47 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.502534\n",
            "| Global Round : 47 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.500168\n",
            "| Global Round : 47 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.484586\n",
            "| Global Round : 47 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.498890\n",
            "| Global Round : 47 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.489933\n",
            "| Global Round : 47 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.468179\n",
            "| Global Round : 47 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.489104\n",
            "| Global Round : 47 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.485104\n",
            "| Global Round : 47 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.453207\n",
            "| Global Round : 47 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.486814\n",
            "| Global Round : 47 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.501069\n",
            "| Global Round : 47 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.467762\n",
            "| Global Round : 47 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.564212\n",
            "| Global Round : 47 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.494117\n",
            "| Global Round : 47 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.512450\n",
            "| Global Round : 47 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.522080\n",
            "| Global Round : 47 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.425103\n",
            "| Global Round : 47 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.475259\n",
            "| Global Round : 47 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.472329\n",
            "| Global Round : 47 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.502924\n",
            "| Global Round : 47 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.431523\n",
            "| Global Round : 47 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.460895\n",
            "| Global Round : 47 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.446977\n",
            "| Global Round : 47 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.424903\n",
            "| Global Round : 47 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.420937\n",
            "| Global Round : 47 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.431680\n",
            "| Global Round : 47 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.448001\n",
            "| Global Round : 47 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.423935\n",
            "| Global Round : 47 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.417891\n",
            "| Global Round : 47 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.445563\n",
            "| Global Round : 47 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.415618\n",
            "| Global Round : 47 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.408280\n",
            "| Global Round : 47 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.446651\n",
            "| Global Round : 47 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.415416\n",
            "| Global Round : 47 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.395840\n",
            "| Global Round : 47 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.421039\n",
            "| Global Round : 47 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.408264\n",
            "| Global Round : 47 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.402882\n",
            "| Global Round : 47 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.404809\n",
            "| Global Round : 47 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.387887\n",
            "| Global Round : 47 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.398124\n",
            "| Global Round : 47 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.396987\n",
            "| Global Round : 47 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.383114\n",
            "| Global Round : 47 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.388966\n",
            "| Global Round : 47 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.388113\n",
            "| Global Round : 47 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.378850\n",
            "| Global Round : 47 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.386826\n",
            "| Global Round : 47 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.389811\n",
            "| Global Round : 47 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.377034\n",
            "| Global Round : 47 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.373012\n",
            "| Global Round : 47 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.380874\n",
            "| Global Round : 47 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.380088\n",
            "| Global Round : 47 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.369697\n",
            "| Global Round : 47 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.373196\n",
            "| Global Round : 47 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.387190\n",
            "| Global Round : 47 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.382045\n",
            "| Global Round : 47 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.368088\n",
            "| Global Round : 47 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.364052\n",
            "| Global Round : 47 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.367288\n",
            "| Global Round : 47 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.376337\n",
            "| Global Round : 47 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.377649\n",
            "| Global Round : 47 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.367635\n",
            "| Global Round : 47 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.358801\n",
            "| Global Round : 47 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.360957\n",
            "| Global Round : 47 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.365592\n",
            "| Global Round : 47 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.368350\n",
            "| Global Round : 47 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.364051\n",
            "| Global Round : 47 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.356925\n",
            "| Global Round : 47 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.354142\n",
            "| Global Round : 47 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.356897\n",
            "| Global Round : 47 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.361548\n",
            "| Global Round : 47 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.358606\n",
            "| Global Round : 47 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.355042\n",
            "| Global Round : 47 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.718335\n",
            "| Global Round : 47 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.927580\n",
            "| Global Round : 47 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 1.508728\n",
            "| Global Round : 47 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 1.978321\n",
            "| Global Round : 47 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 1.748274\n",
            "| Global Round : 47 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 1.432788\n",
            "| Global Round : 47 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.274541\n",
            "| Global Round : 47 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.260551\n",
            "| Global Round : 47 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.194201\n",
            "| Global Round : 47 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 0.991081\n",
            "| Global Round : 47 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.849212\n",
            "| Global Round : 47 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.796154\n",
            "| Global Round : 47 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.798811\n",
            "| Global Round : 47 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.829389\n",
            "| Global Round : 47 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.853850\n",
            "| Global Round : 47 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.854829\n",
            "| Global Round : 47 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.838169\n",
            "| Global Round : 47 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.801211\n",
            "| Global Round : 47 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.766299\n",
            "| Global Round : 47 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.744131\n",
            "| Global Round : 47 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.729414\n",
            "| Global Round : 47 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.714676\n",
            "| Global Round : 47 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.700051\n",
            "| Global Round : 47 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.692290\n",
            "| Global Round : 47 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.688513\n",
            "| Global Round : 47 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.683507\n",
            "| Global Round : 47 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.685030\n",
            "| Global Round : 47 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.674892\n",
            "| Global Round : 47 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.671137\n",
            "| Global Round : 47 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.665114\n",
            "| Global Round : 47 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.657099\n",
            "| Global Round : 47 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.649297\n",
            "| Global Round : 47 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.643548\n",
            "| Global Round : 47 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.638196\n",
            "| Global Round : 47 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.630828\n",
            "| Global Round : 47 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.622625\n",
            "| Global Round : 47 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.613590\n",
            "| Global Round : 47 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.605697\n",
            "| Global Round : 47 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.599377\n",
            "| Global Round : 47 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.593455\n",
            "| Global Round : 47 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.587125\n",
            "| Global Round : 47 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.580772\n",
            "| Global Round : 47 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.573280\n",
            "| Global Round : 47 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.566161\n",
            "| Global Round : 47 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.562415\n",
            "| Global Round : 47 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.557550\n",
            "| Global Round : 47 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.549606\n",
            "| Global Round : 47 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.540429\n",
            "| Global Round : 47 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.531265\n",
            "| Global Round : 47 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.521122\n",
            "| Global Round : 47 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.513773\n",
            "| Global Round : 47 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.506727\n",
            "| Global Round : 47 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.499991\n",
            "| Global Round : 47 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.494615\n",
            "| Global Round : 47 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.489302\n",
            "| Global Round : 47 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.486193\n",
            "| Global Round : 47 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.482657\n",
            "| Global Round : 47 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.480752\n",
            "| Global Round : 47 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.477836\n",
            "| Global Round : 47 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.473171\n",
            "| Global Round : 47 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.466751\n",
            "| Global Round : 47 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.461898\n",
            "| Global Round : 47 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.459879\n",
            "| Global Round : 47 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.462017\n",
            "| Global Round : 47 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.457922\n",
            "| Global Round : 47 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.453383\n",
            "| Global Round : 47 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.452221\n",
            "| Global Round : 47 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.452248\n",
            "| Global Round : 47 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.451398\n",
            "| Global Round : 47 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.444780\n",
            "| Global Round : 47 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.441485\n",
            "| Global Round : 47 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.440856\n",
            "| Global Round : 47 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.438230\n",
            "| Global Round : 47 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.436818\n",
            "| Global Round : 47 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.434651\n",
            "| Global Round : 47 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.433971\n",
            "| Global Round : 47 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.431746\n",
            "| Global Round : 47 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.429180\n",
            "| Global Round : 47 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.425871\n",
            "| Global Round : 47 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.423714\n",
            "| Global Round : 47 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.422107\n",
            "| Global Round : 47 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.419748\n",
            "| Global Round : 47 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.417975\n",
            "| Global Round : 47 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.417388\n",
            "| Global Round : 47 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.417954\n",
            "| Global Round : 47 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.420170\n",
            "| Global Round : 47 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.428611\n",
            "| Global Round : 47 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.431617\n",
            "| Global Round : 47 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.439688\n",
            "| Global Round : 47 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.416779\n",
            "| Global Round : 47 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.413443\n",
            "| Global Round : 47 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.425813\n",
            "| Global Round : 47 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.416976\n",
            "| Global Round : 47 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.407938\n",
            "| Global Round : 47 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.403966\n",
            "| Global Round : 47 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.408780\n",
            "| Global Round : 47 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.411891\n",
            "| Global Round : 47 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.403494\n",
            "| Global Round : 47 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.398355\n",
            "| Global Round : 47 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.396901\n",
            "| Global Round : 47 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.735840\n",
            "| Global Round : 47 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 1.522384\n",
            "| Global Round : 47 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.929273\n",
            "| Global Round : 47 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 0.689396\n",
            "| Global Round : 47 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 0.913308\n",
            "| Global Round : 47 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 1.045986\n",
            "| Global Round : 47 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 1.090955\n",
            "| Global Round : 47 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.028061\n",
            "| Global Round : 47 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 0.928476\n",
            "| Global Round : 47 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.841005\n",
            "| Global Round : 47 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.781561\n",
            "| Global Round : 47 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.773669\n",
            "| Global Round : 47 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.764300\n",
            "| Global Round : 47 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.772755\n",
            "| Global Round : 47 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.773701\n",
            "| Global Round : 47 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.746119\n",
            "| Global Round : 47 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.706863\n",
            "| Global Round : 47 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.677766\n",
            "| Global Round : 47 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.647251\n",
            "| Global Round : 47 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.625377\n",
            "| Global Round : 47 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.611656\n",
            "| Global Round : 47 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.603873\n",
            "| Global Round : 47 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.597071\n",
            "| Global Round : 47 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.590066\n",
            "| Global Round : 47 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.586985\n",
            "| Global Round : 47 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.582641\n",
            "| Global Round : 47 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.590868\n",
            "| Global Round : 47 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.572990\n",
            "| Global Round : 47 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.566038\n",
            "| Global Round : 47 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.561803\n",
            "| Global Round : 47 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.551361\n",
            "| Global Round : 47 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.546400\n",
            "| Global Round : 47 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.532815\n",
            "| Global Round : 47 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.535880\n",
            "| Global Round : 47 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.523616\n",
            "| Global Round : 47 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.525997\n",
            "| Global Round : 47 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.518614\n",
            "| Global Round : 47 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.514526\n",
            "| Global Round : 47 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.510601\n",
            "| Global Round : 47 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.505001\n",
            "| Global Round : 47 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.506978\n",
            "| Global Round : 47 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.498687\n",
            "| Global Round : 47 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.499953\n",
            "| Global Round : 47 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.491417\n",
            "| Global Round : 47 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.487760\n",
            "| Global Round : 47 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.485754\n",
            "| Global Round : 47 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.480182\n",
            "| Global Round : 47 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.478102\n",
            "| Global Round : 47 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.474403\n",
            "| Global Round : 47 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.470492\n",
            "| Global Round : 47 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.468948\n",
            "| Global Round : 47 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.466589\n",
            "| Global Round : 47 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.463662\n",
            "| Global Round : 47 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.461185\n",
            "| Global Round : 47 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.458629\n",
            "| Global Round : 47 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.455279\n",
            "| Global Round : 47 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.453303\n",
            "| Global Round : 47 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.452645\n",
            "| Global Round : 47 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.451482\n",
            "| Global Round : 47 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.452792\n",
            "| Global Round : 47 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.451576\n",
            "| Global Round : 47 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.453714\n",
            "| Global Round : 47 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.448569\n",
            "| Global Round : 47 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.441429\n",
            "| Global Round : 47 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.438258\n",
            "| Global Round : 47 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.437571\n",
            "| Global Round : 47 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.448396\n",
            "| Global Round : 47 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.468986\n",
            "| Global Round : 47 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.499151\n",
            "| Global Round : 47 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.443703\n",
            "| Global Round : 47 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.438486\n",
            "| Global Round : 47 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.475819\n",
            "| Global Round : 47 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.462088\n",
            "| Global Round : 47 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.468122\n",
            "| Global Round : 47 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.437681\n",
            "| Global Round : 47 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.445852\n",
            "| Global Round : 47 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.465173\n",
            "| Global Round : 47 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.438816\n",
            "| Global Round : 47 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.425404\n",
            "| Global Round : 47 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.439620\n",
            "| Global Round : 47 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.435988\n",
            "| Global Round : 47 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.425167\n",
            "| Global Round : 47 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.419510\n",
            "| Global Round : 47 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.424288\n",
            "| Global Round : 47 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.424053\n",
            "| Global Round : 47 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.430220\n",
            "| Global Round : 47 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.445787\n",
            "| Global Round : 47 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.432810\n",
            "| Global Round : 47 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.417899\n",
            "| Global Round : 47 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.416137\n",
            "| Global Round : 47 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.420368\n",
            "| Global Round : 47 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.425643\n",
            "| Global Round : 47 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.411970\n",
            "| Global Round : 47 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.405012\n",
            "| Global Round : 47 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.410250\n",
            "| Global Round : 47 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.415352\n",
            "| Global Round : 47 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.410109\n",
            "| Global Round : 47 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.406126\n",
            "| Global Round : 47 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.402683\n",
            "| Global Round : 47 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.401233\n",
            "Global Round :47, the training accuracy is 71.7%, and the training loss is 0.754.\n",
            "Global Round :47, the testing accuracy is 68.5%, and the testing loss is 1.41.\n",
            "| Global Round : 48 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.704550\n",
            "| Global Round : 48 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 2.393291\n",
            "| Global Round : 48 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.854609\n",
            "| Global Round : 48 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 5.015558\n",
            "| Global Round : 48 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 0.665878\n",
            "| Global Round : 48 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 0.963497\n",
            "| Global Round : 48 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 1.434373\n",
            "| Global Round : 48 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 1.736639\n",
            "| Global Round : 48 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 1.846999\n",
            "| Global Round : 48 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 1.812159\n",
            "| Global Round : 48 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 1.677203\n",
            "| Global Round : 48 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 1.499046\n",
            "| Global Round : 48 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 1.325163\n",
            "| Global Round : 48 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 1.171086\n",
            "| Global Round : 48 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 1.043433\n",
            "| Global Round : 48 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.932218\n",
            "| Global Round : 48 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.844211\n",
            "| Global Round : 48 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.787402\n",
            "| Global Round : 48 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.754798\n",
            "| Global Round : 48 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.744334\n",
            "| Global Round : 48 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.737367\n",
            "| Global Round : 48 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.712479\n",
            "| Global Round : 48 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.704225\n",
            "| Global Round : 48 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.700687\n",
            "| Global Round : 48 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.674919\n",
            "| Global Round : 48 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.672579\n",
            "| Global Round : 48 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.665325\n",
            "| Global Round : 48 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.634153\n",
            "| Global Round : 48 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.609982\n",
            "| Global Round : 48 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.585777\n",
            "| Global Round : 48 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.553053\n",
            "| Global Round : 48 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.541616\n",
            "| Global Round : 48 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.523512\n",
            "| Global Round : 48 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.515489\n",
            "| Global Round : 48 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.510586\n",
            "| Global Round : 48 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.503931\n",
            "| Global Round : 48 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.500068\n",
            "| Global Round : 48 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.496599\n",
            "| Global Round : 48 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.490453\n",
            "| Global Round : 48 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.485535\n",
            "| Global Round : 48 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.475286\n",
            "| Global Round : 48 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.468850\n",
            "| Global Round : 48 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.465365\n",
            "| Global Round : 48 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.460603\n",
            "| Global Round : 48 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.457513\n",
            "| Global Round : 48 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.450792\n",
            "| Global Round : 48 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.446479\n",
            "| Global Round : 48 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.441502\n",
            "| Global Round : 48 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.435970\n",
            "| Global Round : 48 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.430830\n",
            "| Global Round : 48 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.424181\n",
            "| Global Round : 48 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.417909\n",
            "| Global Round : 48 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.413241\n",
            "| Global Round : 48 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.406999\n",
            "| Global Round : 48 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.402983\n",
            "| Global Round : 48 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.398469\n",
            "| Global Round : 48 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.395631\n",
            "| Global Round : 48 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.391069\n",
            "| Global Round : 48 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.387111\n",
            "| Global Round : 48 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.382240\n",
            "| Global Round : 48 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.378820\n",
            "| Global Round : 48 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.378530\n",
            "| Global Round : 48 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.373939\n",
            "| Global Round : 48 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.372542\n",
            "| Global Round : 48 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.378150\n",
            "| Global Round : 48 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.383201\n",
            "| Global Round : 48 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.380852\n",
            "| Global Round : 48 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.386672\n",
            "| Global Round : 48 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.364164\n",
            "| Global Round : 48 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.359491\n",
            "| Global Round : 48 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.372229\n",
            "| Global Round : 48 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.355519\n",
            "| Global Round : 48 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.348863\n",
            "| Global Round : 48 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.354098\n",
            "| Global Round : 48 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.348845\n",
            "| Global Round : 48 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.347408\n",
            "| Global Round : 48 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.342510\n",
            "| Global Round : 48 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.343080\n",
            "| Global Round : 48 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.343956\n",
            "| Global Round : 48 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.335521\n",
            "| Global Round : 48 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.334673\n",
            "| Global Round : 48 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.331900\n",
            "| Global Round : 48 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.331965\n",
            "| Global Round : 48 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.338668\n",
            "| Global Round : 48 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.339981\n",
            "| Global Round : 48 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.363697\n",
            "| Global Round : 48 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.355774\n",
            "| Global Round : 48 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.346085\n",
            "| Global Round : 48 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.321518\n",
            "| Global Round : 48 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.325540\n",
            "| Global Round : 48 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.353342\n",
            "| Global Round : 48 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.328685\n",
            "| Global Round : 48 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.313223\n",
            "| Global Round : 48 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.320193\n",
            "| Global Round : 48 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.327223\n",
            "| Global Round : 48 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.320643\n",
            "| Global Round : 48 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.308572\n",
            "| Global Round : 48 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.325947\n",
            "| Global Round : 48 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.346471\n",
            "| Global Round : 48 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.320938\n",
            "| Global Round : 48 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.900801\n",
            "| Global Round : 48 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 2.291017\n",
            "| Global Round : 48 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 1.264697\n",
            "| Global Round : 48 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 1.079563\n",
            "| Global Round : 48 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 1.081263\n",
            "| Global Round : 48 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.771287\n",
            "| Global Round : 48 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 0.828138\n",
            "| Global Round : 48 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 0.876223\n",
            "| Global Round : 48 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 0.828180\n",
            "| Global Round : 48 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 0.740797\n",
            "| Global Round : 48 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.751677\n",
            "| Global Round : 48 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.809701\n",
            "| Global Round : 48 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.739561\n",
            "| Global Round : 48 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.703560\n",
            "| Global Round : 48 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.714158\n",
            "| Global Round : 48 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.710140\n",
            "| Global Round : 48 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.672018\n",
            "| Global Round : 48 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.626311\n",
            "| Global Round : 48 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.656925\n",
            "| Global Round : 48 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.612796\n",
            "| Global Round : 48 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.598642\n",
            "| Global Round : 48 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.603658\n",
            "| Global Round : 48 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.563995\n",
            "| Global Round : 48 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.599638\n",
            "| Global Round : 48 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.543456\n",
            "| Global Round : 48 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.570178\n",
            "| Global Round : 48 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.521008\n",
            "| Global Round : 48 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.572308\n",
            "| Global Round : 48 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.521637\n",
            "| Global Round : 48 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.554069\n",
            "| Global Round : 48 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.504296\n",
            "| Global Round : 48 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.555047\n",
            "| Global Round : 48 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.518934\n",
            "| Global Round : 48 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.541687\n",
            "| Global Round : 48 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.486437\n",
            "| Global Round : 48 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.551279\n",
            "| Global Round : 48 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.509137\n",
            "| Global Round : 48 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.561462\n",
            "| Global Round : 48 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.479837\n",
            "| Global Round : 48 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.554725\n",
            "| Global Round : 48 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.471115\n",
            "| Global Round : 48 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.522328\n",
            "| Global Round : 48 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.470198\n",
            "| Global Round : 48 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.505311\n",
            "| Global Round : 48 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.454111\n",
            "| Global Round : 48 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.473067\n",
            "| Global Round : 48 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.460458\n",
            "| Global Round : 48 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.450037\n",
            "| Global Round : 48 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.450606\n",
            "| Global Round : 48 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.450906\n",
            "| Global Round : 48 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.451267\n",
            "| Global Round : 48 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.438071\n",
            "| Global Round : 48 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.439570\n",
            "| Global Round : 48 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.450111\n",
            "| Global Round : 48 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.436555\n",
            "| Global Round : 48 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.476943\n",
            "| Global Round : 48 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.472132\n",
            "| Global Round : 48 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.464114\n",
            "| Global Round : 48 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.460127\n",
            "| Global Round : 48 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.415853\n",
            "| Global Round : 48 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.429894\n",
            "| Global Round : 48 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.416970\n",
            "| Global Round : 48 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.429830\n",
            "| Global Round : 48 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.433167\n",
            "| Global Round : 48 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.410352\n",
            "| Global Round : 48 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.440020\n",
            "| Global Round : 48 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.414894\n",
            "| Global Round : 48 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.404198\n",
            "| Global Round : 48 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.448162\n",
            "| Global Round : 48 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.460159\n",
            "| Global Round : 48 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.401490\n",
            "| Global Round : 48 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.527945\n",
            "| Global Round : 48 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.528965\n",
            "| Global Round : 48 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.493669\n",
            "| Global Round : 48 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.517242\n",
            "| Global Round : 48 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.399802\n",
            "| Global Round : 48 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.484854\n",
            "| Global Round : 48 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.404663\n",
            "| Global Round : 48 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.495153\n",
            "| Global Round : 48 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.421443\n",
            "| Global Round : 48 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.457112\n",
            "| Global Round : 48 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.402540\n",
            "| Global Round : 48 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.432136\n",
            "| Global Round : 48 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.423934\n",
            "| Global Round : 48 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.429196\n",
            "| Global Round : 48 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.404998\n",
            "| Global Round : 48 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.408728\n",
            "| Global Round : 48 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.412019\n",
            "| Global Round : 48 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.403450\n",
            "| Global Round : 48 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.406572\n",
            "| Global Round : 48 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.380659\n",
            "| Global Round : 48 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.397426\n",
            "| Global Round : 48 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.379175\n",
            "| Global Round : 48 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.393608\n",
            "| Global Round : 48 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.376691\n",
            "| Global Round : 48 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.379325\n",
            "| Global Round : 48 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.375515\n",
            "| Global Round : 48 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.369067\n",
            "| Global Round : 48 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.371940\n",
            "| Global Round : 48 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.366587\n",
            "| Global Round : 48 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.695550\n",
            "| Global Round : 48 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 2.299720\n",
            "| Global Round : 48 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 1.073949\n",
            "| Global Round : 48 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 2.807494\n",
            "| Global Round : 48 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 0.895559\n",
            "| Global Round : 48 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.999112\n",
            "| Global Round : 48 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 1.264367\n",
            "| Global Round : 48 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 1.386162\n",
            "| Global Round : 48 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 1.377242\n",
            "| Global Round : 48 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 1.264914\n",
            "| Global Round : 48 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 1.091645\n",
            "| Global Round : 48 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.918537\n",
            "| Global Round : 48 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.800003\n",
            "| Global Round : 48 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.801454\n",
            "| Global Round : 48 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.889045\n",
            "| Global Round : 48 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.884187\n",
            "| Global Round : 48 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.786391\n",
            "| Global Round : 48 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.804843\n",
            "| Global Round : 48 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.731199\n",
            "| Global Round : 48 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.717733\n",
            "| Global Round : 48 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.721367\n",
            "| Global Round : 48 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.717917\n",
            "| Global Round : 48 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.698578\n",
            "| Global Round : 48 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.676509\n",
            "| Global Round : 48 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.664540\n",
            "| Global Round : 48 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.666259\n",
            "| Global Round : 48 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.666359\n",
            "| Global Round : 48 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.661280\n",
            "| Global Round : 48 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.647440\n",
            "| Global Round : 48 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.637563\n",
            "| Global Round : 48 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.641307\n",
            "| Global Round : 48 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.639612\n",
            "| Global Round : 48 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.626438\n",
            "| Global Round : 48 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.619999\n",
            "| Global Round : 48 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.617982\n",
            "| Global Round : 48 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.609540\n",
            "| Global Round : 48 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.600253\n",
            "| Global Round : 48 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.602498\n",
            "| Global Round : 48 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.598193\n",
            "| Global Round : 48 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.592242\n",
            "| Global Round : 48 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.580912\n",
            "| Global Round : 48 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.573591\n",
            "| Global Round : 48 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.570100\n",
            "| Global Round : 48 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.567208\n",
            "| Global Round : 48 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.561005\n",
            "| Global Round : 48 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.557238\n",
            "| Global Round : 48 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.555657\n",
            "| Global Round : 48 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.544401\n",
            "| Global Round : 48 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.538502\n",
            "| Global Round : 48 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.537487\n",
            "| Global Round : 48 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.526421\n",
            "| Global Round : 48 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.526450\n",
            "| Global Round : 48 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.520867\n",
            "| Global Round : 48 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.510764\n",
            "| Global Round : 48 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.512572\n",
            "| Global Round : 48 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.503231\n",
            "| Global Round : 48 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.503182\n",
            "| Global Round : 48 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.501314\n",
            "| Global Round : 48 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.496519\n",
            "| Global Round : 48 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.493172\n",
            "| Global Round : 48 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.492186\n",
            "| Global Round : 48 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.485778\n",
            "| Global Round : 48 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.485476\n",
            "| Global Round : 48 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.483737\n",
            "| Global Round : 48 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.478122\n",
            "| Global Round : 48 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.478684\n",
            "| Global Round : 48 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.474123\n",
            "| Global Round : 48 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.471355\n",
            "| Global Round : 48 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.469475\n",
            "| Global Round : 48 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.466524\n",
            "| Global Round : 48 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.464187\n",
            "| Global Round : 48 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.469835\n",
            "| Global Round : 48 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.459480\n",
            "| Global Round : 48 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.460746\n",
            "| Global Round : 48 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.459128\n",
            "| Global Round : 48 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.454312\n",
            "| Global Round : 48 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.459933\n",
            "| Global Round : 48 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.449530\n",
            "| Global Round : 48 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.464709\n",
            "| Global Round : 48 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.448606\n",
            "| Global Round : 48 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.455562\n",
            "| Global Round : 48 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.447582\n",
            "| Global Round : 48 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.443882\n",
            "| Global Round : 48 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.446723\n",
            "| Global Round : 48 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.436013\n",
            "| Global Round : 48 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.441228\n",
            "| Global Round : 48 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.431812\n",
            "| Global Round : 48 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.431748\n",
            "| Global Round : 48 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.430134\n",
            "| Global Round : 48 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.426566\n",
            "| Global Round : 48 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.426718\n",
            "| Global Round : 48 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.425106\n",
            "| Global Round : 48 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.421343\n",
            "| Global Round : 48 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.420848\n",
            "| Global Round : 48 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.420006\n",
            "| Global Round : 48 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.416130\n",
            "| Global Round : 48 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.416660\n",
            "| Global Round : 48 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.415171\n",
            "| Global Round : 48 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.411224\n",
            "| Global Round : 48 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.411617\n",
            "| Global Round : 48 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.733087\n",
            "| Global Round : 48 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 2.234710\n",
            "| Global Round : 48 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 1.222774\n",
            "| Global Round : 48 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 1.106423\n",
            "| Global Round : 48 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 0.782759\n",
            "| Global Round : 48 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 0.804685\n",
            "| Global Round : 48 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 0.839409\n",
            "| Global Round : 48 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 0.803027\n",
            "| Global Round : 48 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 0.807511\n",
            "| Global Round : 48 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 0.753911\n",
            "| Global Round : 48 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 0.727506\n",
            "| Global Round : 48 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 0.710796\n",
            "| Global Round : 48 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 0.710526\n",
            "| Global Round : 48 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 0.689361\n",
            "| Global Round : 48 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.678061\n",
            "| Global Round : 48 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.663546\n",
            "| Global Round : 48 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.659929\n",
            "| Global Round : 48 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.645056\n",
            "| Global Round : 48 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.644265\n",
            "| Global Round : 48 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.636773\n",
            "| Global Round : 48 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.618804\n",
            "| Global Round : 48 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.606023\n",
            "| Global Round : 48 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.585761\n",
            "| Global Round : 48 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.577051\n",
            "| Global Round : 48 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.577601\n",
            "| Global Round : 48 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.568106\n",
            "| Global Round : 48 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.557117\n",
            "| Global Round : 48 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.551490\n",
            "| Global Round : 48 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.548425\n",
            "| Global Round : 48 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.540546\n",
            "| Global Round : 48 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.531341\n",
            "| Global Round : 48 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.530828\n",
            "| Global Round : 48 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.529285\n",
            "| Global Round : 48 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.542644\n",
            "| Global Round : 48 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.563544\n",
            "| Global Round : 48 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.513889\n",
            "| Global Round : 48 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.604744\n",
            "| Global Round : 48 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.640605\n",
            "| Global Round : 48 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.650311\n",
            "| Global Round : 48 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.505846\n",
            "| Global Round : 48 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.721203\n",
            "| Global Round : 48 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.647473\n",
            "| Global Round : 48 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.823477\n",
            "| Global Round : 48 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.729648\n",
            "| Global Round : 48 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.570368\n",
            "| Global Round : 48 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.772890\n",
            "| Global Round : 48 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.571777\n",
            "| Global Round : 48 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.584464\n",
            "| Global Round : 48 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.658702\n",
            "| Global Round : 48 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.564913\n",
            "| Global Round : 48 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.581234\n",
            "| Global Round : 48 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.554038\n",
            "| Global Round : 48 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.528757\n",
            "| Global Round : 48 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.560230\n",
            "| Global Round : 48 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.517081\n",
            "| Global Round : 48 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.514320\n",
            "| Global Round : 48 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.525211\n",
            "| Global Round : 48 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.504420\n",
            "| Global Round : 48 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.519278\n",
            "| Global Round : 48 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.483233\n",
            "| Global Round : 48 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.514170\n",
            "| Global Round : 48 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.482623\n",
            "| Global Round : 48 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.503006\n",
            "| Global Round : 48 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.482129\n",
            "| Global Round : 48 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.491104\n",
            "| Global Round : 48 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.471096\n",
            "| Global Round : 48 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.480392\n",
            "| Global Round : 48 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.466844\n",
            "| Global Round : 48 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.475265\n",
            "| Global Round : 48 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.458964\n",
            "| Global Round : 48 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.465240\n",
            "| Global Round : 48 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.457724\n",
            "| Global Round : 48 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.459782\n",
            "| Global Round : 48 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.457040\n",
            "| Global Round : 48 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.453372\n",
            "| Global Round : 48 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.456277\n",
            "| Global Round : 48 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.447367\n",
            "| Global Round : 48 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.451569\n",
            "| Global Round : 48 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.446822\n",
            "| Global Round : 48 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.444074\n",
            "| Global Round : 48 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.448145\n",
            "| Global Round : 48 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.440275\n",
            "| Global Round : 48 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.440554\n",
            "| Global Round : 48 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.440625\n",
            "| Global Round : 48 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.435491\n",
            "| Global Round : 48 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.437544\n",
            "| Global Round : 48 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.436504\n",
            "| Global Round : 48 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.431295\n",
            "| Global Round : 48 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.434296\n",
            "| Global Round : 48 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.436558\n",
            "| Global Round : 48 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.428793\n",
            "| Global Round : 48 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.426743\n",
            "| Global Round : 48 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.430988\n",
            "| Global Round : 48 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.426177\n",
            "| Global Round : 48 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.422531\n",
            "| Global Round : 48 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.420713\n",
            "| Global Round : 48 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.420526\n",
            "| Global Round : 48 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.422272\n",
            "| Global Round : 48 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.423120\n",
            "| Global Round : 48 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.428239\n",
            "Global Round :48, the training accuracy is 59.2%, and the training loss is 0.901.\n",
            "Global Round :48, the testing accuracy is 55.0%, and the testing loss is 1.57.\n",
            "| Global Round : 49 | Local Epoch : 0 | [0/734 (0%)]\tLoss: 0.994295\n",
            "| Global Round : 49 | Local Epoch : 1 | [0/734 (0%)]\tLoss: 0.741836\n",
            "| Global Round : 49 | Local Epoch : 2 | [0/734 (0%)]\tLoss: 0.681667\n",
            "| Global Round : 49 | Local Epoch : 3 | [0/734 (0%)]\tLoss: 0.987163\n",
            "| Global Round : 49 | Local Epoch : 4 | [0/734 (0%)]\tLoss: 1.043491\n",
            "| Global Round : 49 | Local Epoch : 5 | [0/734 (0%)]\tLoss: 1.155138\n",
            "| Global Round : 49 | Local Epoch : 6 | [0/734 (0%)]\tLoss: 0.816112\n",
            "| Global Round : 49 | Local Epoch : 7 | [0/734 (0%)]\tLoss: 0.584905\n",
            "| Global Round : 49 | Local Epoch : 8 | [0/734 (0%)]\tLoss: 0.922446\n",
            "| Global Round : 49 | Local Epoch : 9 | [0/734 (0%)]\tLoss: 0.741592\n",
            "| Global Round : 49 | Local Epoch : 10 | [0/734 (0%)]\tLoss: 0.599517\n",
            "| Global Round : 49 | Local Epoch : 11 | [0/734 (0%)]\tLoss: 0.680387\n",
            "| Global Round : 49 | Local Epoch : 12 | [0/734 (0%)]\tLoss: 0.753498\n",
            "| Global Round : 49 | Local Epoch : 13 | [0/734 (0%)]\tLoss: 0.734152\n",
            "| Global Round : 49 | Local Epoch : 14 | [0/734 (0%)]\tLoss: 0.651559\n",
            "| Global Round : 49 | Local Epoch : 15 | [0/734 (0%)]\tLoss: 0.590600\n",
            "| Global Round : 49 | Local Epoch : 16 | [0/734 (0%)]\tLoss: 0.619927\n",
            "| Global Round : 49 | Local Epoch : 17 | [0/734 (0%)]\tLoss: 0.649934\n",
            "| Global Round : 49 | Local Epoch : 18 | [0/734 (0%)]\tLoss: 0.584596\n",
            "| Global Round : 49 | Local Epoch : 19 | [0/734 (0%)]\tLoss: 0.549454\n",
            "| Global Round : 49 | Local Epoch : 20 | [0/734 (0%)]\tLoss: 0.575252\n",
            "| Global Round : 49 | Local Epoch : 21 | [0/734 (0%)]\tLoss: 0.596637\n",
            "| Global Round : 49 | Local Epoch : 22 | [0/734 (0%)]\tLoss: 0.572284\n",
            "| Global Round : 49 | Local Epoch : 23 | [0/734 (0%)]\tLoss: 0.536738\n",
            "| Global Round : 49 | Local Epoch : 24 | [0/734 (0%)]\tLoss: 0.545051\n",
            "| Global Round : 49 | Local Epoch : 25 | [0/734 (0%)]\tLoss: 0.557881\n",
            "| Global Round : 49 | Local Epoch : 26 | [0/734 (0%)]\tLoss: 0.520595\n",
            "| Global Round : 49 | Local Epoch : 27 | [0/734 (0%)]\tLoss: 0.505523\n",
            "| Global Round : 49 | Local Epoch : 28 | [0/734 (0%)]\tLoss: 0.512878\n",
            "| Global Round : 49 | Local Epoch : 29 | [0/734 (0%)]\tLoss: 0.498939\n",
            "| Global Round : 49 | Local Epoch : 30 | [0/734 (0%)]\tLoss: 0.471729\n",
            "| Global Round : 49 | Local Epoch : 31 | [0/734 (0%)]\tLoss: 0.478103\n",
            "| Global Round : 49 | Local Epoch : 32 | [0/734 (0%)]\tLoss: 0.473678\n",
            "| Global Round : 49 | Local Epoch : 33 | [0/734 (0%)]\tLoss: 0.453213\n",
            "| Global Round : 49 | Local Epoch : 34 | [0/734 (0%)]\tLoss: 0.456528\n",
            "| Global Round : 49 | Local Epoch : 35 | [0/734 (0%)]\tLoss: 0.442959\n",
            "| Global Round : 49 | Local Epoch : 36 | [0/734 (0%)]\tLoss: 0.427867\n",
            "| Global Round : 49 | Local Epoch : 37 | [0/734 (0%)]\tLoss: 0.433977\n",
            "| Global Round : 49 | Local Epoch : 38 | [0/734 (0%)]\tLoss: 0.418073\n",
            "| Global Round : 49 | Local Epoch : 39 | [0/734 (0%)]\tLoss: 0.418322\n",
            "| Global Round : 49 | Local Epoch : 40 | [0/734 (0%)]\tLoss: 0.412703\n",
            "| Global Round : 49 | Local Epoch : 41 | [0/734 (0%)]\tLoss: 0.408044\n",
            "| Global Round : 49 | Local Epoch : 42 | [0/734 (0%)]\tLoss: 0.394691\n",
            "| Global Round : 49 | Local Epoch : 43 | [0/734 (0%)]\tLoss: 0.394462\n",
            "| Global Round : 49 | Local Epoch : 44 | [0/734 (0%)]\tLoss: 0.385769\n",
            "| Global Round : 49 | Local Epoch : 45 | [0/734 (0%)]\tLoss: 0.386566\n",
            "| Global Round : 49 | Local Epoch : 46 | [0/734 (0%)]\tLoss: 0.389721\n",
            "| Global Round : 49 | Local Epoch : 47 | [0/734 (0%)]\tLoss: 0.375921\n",
            "| Global Round : 49 | Local Epoch : 48 | [0/734 (0%)]\tLoss: 0.370830\n",
            "| Global Round : 49 | Local Epoch : 49 | [0/734 (0%)]\tLoss: 0.373519\n",
            "| Global Round : 49 | Local Epoch : 50 | [0/734 (0%)]\tLoss: 0.364119\n",
            "| Global Round : 49 | Local Epoch : 51 | [0/734 (0%)]\tLoss: 0.360983\n",
            "| Global Round : 49 | Local Epoch : 52 | [0/734 (0%)]\tLoss: 0.362589\n",
            "| Global Round : 49 | Local Epoch : 53 | [0/734 (0%)]\tLoss: 0.354232\n",
            "| Global Round : 49 | Local Epoch : 54 | [0/734 (0%)]\tLoss: 0.350222\n",
            "| Global Round : 49 | Local Epoch : 55 | [0/734 (0%)]\tLoss: 0.344367\n",
            "| Global Round : 49 | Local Epoch : 56 | [0/734 (0%)]\tLoss: 0.339609\n",
            "| Global Round : 49 | Local Epoch : 57 | [0/734 (0%)]\tLoss: 0.337418\n",
            "| Global Round : 49 | Local Epoch : 58 | [0/734 (0%)]\tLoss: 0.336468\n",
            "| Global Round : 49 | Local Epoch : 59 | [0/734 (0%)]\tLoss: 0.335456\n",
            "| Global Round : 49 | Local Epoch : 60 | [0/734 (0%)]\tLoss: 0.333772\n",
            "| Global Round : 49 | Local Epoch : 61 | [0/734 (0%)]\tLoss: 0.332742\n",
            "| Global Round : 49 | Local Epoch : 62 | [0/734 (0%)]\tLoss: 0.340052\n",
            "| Global Round : 49 | Local Epoch : 63 | [0/734 (0%)]\tLoss: 0.374141\n",
            "| Global Round : 49 | Local Epoch : 64 | [0/734 (0%)]\tLoss: 0.361726\n",
            "| Global Round : 49 | Local Epoch : 65 | [0/734 (0%)]\tLoss: 0.363297\n",
            "| Global Round : 49 | Local Epoch : 66 | [0/734 (0%)]\tLoss: 0.328036\n",
            "| Global Round : 49 | Local Epoch : 67 | [0/734 (0%)]\tLoss: 0.333442\n",
            "| Global Round : 49 | Local Epoch : 68 | [0/734 (0%)]\tLoss: 0.372747\n",
            "| Global Round : 49 | Local Epoch : 69 | [0/734 (0%)]\tLoss: 0.347152\n",
            "| Global Round : 49 | Local Epoch : 70 | [0/734 (0%)]\tLoss: 0.333074\n",
            "| Global Round : 49 | Local Epoch : 71 | [0/734 (0%)]\tLoss: 0.319698\n",
            "| Global Round : 49 | Local Epoch : 72 | [0/734 (0%)]\tLoss: 0.315536\n",
            "| Global Round : 49 | Local Epoch : 73 | [0/734 (0%)]\tLoss: 0.319353\n",
            "| Global Round : 49 | Local Epoch : 74 | [0/734 (0%)]\tLoss: 0.328628\n",
            "| Global Round : 49 | Local Epoch : 75 | [0/734 (0%)]\tLoss: 0.356703\n",
            "| Global Round : 49 | Local Epoch : 76 | [0/734 (0%)]\tLoss: 0.354746\n",
            "| Global Round : 49 | Local Epoch : 77 | [0/734 (0%)]\tLoss: 0.372451\n",
            "| Global Round : 49 | Local Epoch : 78 | [0/734 (0%)]\tLoss: 0.313779\n",
            "| Global Round : 49 | Local Epoch : 79 | [0/734 (0%)]\tLoss: 0.351251\n",
            "| Global Round : 49 | Local Epoch : 80 | [0/734 (0%)]\tLoss: 0.443618\n",
            "| Global Round : 49 | Local Epoch : 81 | [0/734 (0%)]\tLoss: 0.309229\n",
            "| Global Round : 49 | Local Epoch : 82 | [0/734 (0%)]\tLoss: 0.428584\n",
            "| Global Round : 49 | Local Epoch : 83 | [0/734 (0%)]\tLoss: 0.535651\n",
            "| Global Round : 49 | Local Epoch : 84 | [0/734 (0%)]\tLoss: 0.421588\n",
            "| Global Round : 49 | Local Epoch : 85 | [0/734 (0%)]\tLoss: 0.530506\n",
            "| Global Round : 49 | Local Epoch : 86 | [0/734 (0%)]\tLoss: 0.340298\n",
            "| Global Round : 49 | Local Epoch : 87 | [0/734 (0%)]\tLoss: 0.445531\n",
            "| Global Round : 49 | Local Epoch : 88 | [0/734 (0%)]\tLoss: 0.320950\n",
            "| Global Round : 49 | Local Epoch : 89 | [0/734 (0%)]\tLoss: 0.467867\n",
            "| Global Round : 49 | Local Epoch : 90 | [0/734 (0%)]\tLoss: 0.400605\n",
            "| Global Round : 49 | Local Epoch : 91 | [0/734 (0%)]\tLoss: 0.463161\n",
            "| Global Round : 49 | Local Epoch : 92 | [0/734 (0%)]\tLoss: 0.346116\n",
            "| Global Round : 49 | Local Epoch : 93 | [0/734 (0%)]\tLoss: 0.495530\n",
            "| Global Round : 49 | Local Epoch : 94 | [0/734 (0%)]\tLoss: 0.338510\n",
            "| Global Round : 49 | Local Epoch : 95 | [0/734 (0%)]\tLoss: 0.447711\n",
            "| Global Round : 49 | Local Epoch : 96 | [0/734 (0%)]\tLoss: 0.323886\n",
            "| Global Round : 49 | Local Epoch : 97 | [0/734 (0%)]\tLoss: 0.469656\n",
            "| Global Round : 49 | Local Epoch : 98 | [0/734 (0%)]\tLoss: 0.343895\n",
            "| Global Round : 49 | Local Epoch : 99 | [0/734 (0%)]\tLoss: 0.431641\n",
            "| Global Round : 49 | Local Epoch : 0 | [0/705 (0%)]\tLoss: 0.956176\n",
            "| Global Round : 49 | Local Epoch : 1 | [0/705 (0%)]\tLoss: 1.721928\n",
            "| Global Round : 49 | Local Epoch : 2 | [0/705 (0%)]\tLoss: 0.790991\n",
            "| Global Round : 49 | Local Epoch : 3 | [0/705 (0%)]\tLoss: 2.152587\n",
            "| Global Round : 49 | Local Epoch : 4 | [0/705 (0%)]\tLoss: 0.735286\n",
            "| Global Round : 49 | Local Epoch : 5 | [0/705 (0%)]\tLoss: 0.824363\n",
            "| Global Round : 49 | Local Epoch : 6 | [0/705 (0%)]\tLoss: 1.082675\n",
            "| Global Round : 49 | Local Epoch : 7 | [0/705 (0%)]\tLoss: 1.208264\n",
            "| Global Round : 49 | Local Epoch : 8 | [0/705 (0%)]\tLoss: 1.162575\n",
            "| Global Round : 49 | Local Epoch : 9 | [0/705 (0%)]\tLoss: 1.057176\n",
            "| Global Round : 49 | Local Epoch : 10 | [0/705 (0%)]\tLoss: 0.966938\n",
            "| Global Round : 49 | Local Epoch : 11 | [0/705 (0%)]\tLoss: 0.907799\n",
            "| Global Round : 49 | Local Epoch : 12 | [0/705 (0%)]\tLoss: 0.865468\n",
            "| Global Round : 49 | Local Epoch : 13 | [0/705 (0%)]\tLoss: 0.832637\n",
            "| Global Round : 49 | Local Epoch : 14 | [0/705 (0%)]\tLoss: 0.781747\n",
            "| Global Round : 49 | Local Epoch : 15 | [0/705 (0%)]\tLoss: 0.744228\n",
            "| Global Round : 49 | Local Epoch : 16 | [0/705 (0%)]\tLoss: 0.742881\n",
            "| Global Round : 49 | Local Epoch : 17 | [0/705 (0%)]\tLoss: 0.763600\n",
            "| Global Round : 49 | Local Epoch : 18 | [0/705 (0%)]\tLoss: 0.780068\n",
            "| Global Round : 49 | Local Epoch : 19 | [0/705 (0%)]\tLoss: 0.779955\n",
            "| Global Round : 49 | Local Epoch : 20 | [0/705 (0%)]\tLoss: 0.765239\n",
            "| Global Round : 49 | Local Epoch : 21 | [0/705 (0%)]\tLoss: 0.747092\n",
            "| Global Round : 49 | Local Epoch : 22 | [0/705 (0%)]\tLoss: 0.732427\n",
            "| Global Round : 49 | Local Epoch : 23 | [0/705 (0%)]\tLoss: 0.717150\n",
            "| Global Round : 49 | Local Epoch : 24 | [0/705 (0%)]\tLoss: 0.694455\n",
            "| Global Round : 49 | Local Epoch : 25 | [0/705 (0%)]\tLoss: 0.672926\n",
            "| Global Round : 49 | Local Epoch : 26 | [0/705 (0%)]\tLoss: 0.662145\n",
            "| Global Round : 49 | Local Epoch : 27 | [0/705 (0%)]\tLoss: 0.656875\n",
            "| Global Round : 49 | Local Epoch : 28 | [0/705 (0%)]\tLoss: 0.654764\n",
            "| Global Round : 49 | Local Epoch : 29 | [0/705 (0%)]\tLoss: 0.654668\n",
            "| Global Round : 49 | Local Epoch : 30 | [0/705 (0%)]\tLoss: 0.652308\n",
            "| Global Round : 49 | Local Epoch : 31 | [0/705 (0%)]\tLoss: 0.646638\n",
            "| Global Round : 49 | Local Epoch : 32 | [0/705 (0%)]\tLoss: 0.640033\n",
            "| Global Round : 49 | Local Epoch : 33 | [0/705 (0%)]\tLoss: 0.633943\n",
            "| Global Round : 49 | Local Epoch : 34 | [0/705 (0%)]\tLoss: 0.629678\n",
            "| Global Round : 49 | Local Epoch : 35 | [0/705 (0%)]\tLoss: 0.622667\n",
            "| Global Round : 49 | Local Epoch : 36 | [0/705 (0%)]\tLoss: 0.613163\n",
            "| Global Round : 49 | Local Epoch : 37 | [0/705 (0%)]\tLoss: 0.604931\n",
            "| Global Round : 49 | Local Epoch : 38 | [0/705 (0%)]\tLoss: 0.600550\n",
            "| Global Round : 49 | Local Epoch : 39 | [0/705 (0%)]\tLoss: 0.596917\n",
            "| Global Round : 49 | Local Epoch : 40 | [0/705 (0%)]\tLoss: 0.591811\n",
            "| Global Round : 49 | Local Epoch : 41 | [0/705 (0%)]\tLoss: 0.586653\n",
            "| Global Round : 49 | Local Epoch : 42 | [0/705 (0%)]\tLoss: 0.580300\n",
            "| Global Round : 49 | Local Epoch : 43 | [0/705 (0%)]\tLoss: 0.573187\n",
            "| Global Round : 49 | Local Epoch : 44 | [0/705 (0%)]\tLoss: 0.564994\n",
            "| Global Round : 49 | Local Epoch : 45 | [0/705 (0%)]\tLoss: 0.556933\n",
            "| Global Round : 49 | Local Epoch : 46 | [0/705 (0%)]\tLoss: 0.548831\n",
            "| Global Round : 49 | Local Epoch : 47 | [0/705 (0%)]\tLoss: 0.540942\n",
            "| Global Round : 49 | Local Epoch : 48 | [0/705 (0%)]\tLoss: 0.534987\n",
            "| Global Round : 49 | Local Epoch : 49 | [0/705 (0%)]\tLoss: 0.529238\n",
            "| Global Round : 49 | Local Epoch : 50 | [0/705 (0%)]\tLoss: 0.522980\n",
            "| Global Round : 49 | Local Epoch : 51 | [0/705 (0%)]\tLoss: 0.517767\n",
            "| Global Round : 49 | Local Epoch : 52 | [0/705 (0%)]\tLoss: 0.514371\n",
            "| Global Round : 49 | Local Epoch : 53 | [0/705 (0%)]\tLoss: 0.511555\n",
            "| Global Round : 49 | Local Epoch : 54 | [0/705 (0%)]\tLoss: 0.503093\n",
            "| Global Round : 49 | Local Epoch : 55 | [0/705 (0%)]\tLoss: 0.503347\n",
            "| Global Round : 49 | Local Epoch : 56 | [0/705 (0%)]\tLoss: 0.515155\n",
            "| Global Round : 49 | Local Epoch : 57 | [0/705 (0%)]\tLoss: 0.496632\n",
            "| Global Round : 49 | Local Epoch : 58 | [0/705 (0%)]\tLoss: 0.502728\n",
            "| Global Round : 49 | Local Epoch : 59 | [0/705 (0%)]\tLoss: 0.482981\n",
            "| Global Round : 49 | Local Epoch : 60 | [0/705 (0%)]\tLoss: 0.484443\n",
            "| Global Round : 49 | Local Epoch : 61 | [0/705 (0%)]\tLoss: 0.476003\n",
            "| Global Round : 49 | Local Epoch : 62 | [0/705 (0%)]\tLoss: 0.477258\n",
            "| Global Round : 49 | Local Epoch : 63 | [0/705 (0%)]\tLoss: 0.465739\n",
            "| Global Round : 49 | Local Epoch : 64 | [0/705 (0%)]\tLoss: 0.468409\n",
            "| Global Round : 49 | Local Epoch : 65 | [0/705 (0%)]\tLoss: 0.459972\n",
            "| Global Round : 49 | Local Epoch : 66 | [0/705 (0%)]\tLoss: 0.454108\n",
            "| Global Round : 49 | Local Epoch : 67 | [0/705 (0%)]\tLoss: 0.449927\n",
            "| Global Round : 49 | Local Epoch : 68 | [0/705 (0%)]\tLoss: 0.441785\n",
            "| Global Round : 49 | Local Epoch : 69 | [0/705 (0%)]\tLoss: 0.441367\n",
            "| Global Round : 49 | Local Epoch : 70 | [0/705 (0%)]\tLoss: 0.463691\n",
            "| Global Round : 49 | Local Epoch : 71 | [0/705 (0%)]\tLoss: 0.510265\n",
            "| Global Round : 49 | Local Epoch : 72 | [0/705 (0%)]\tLoss: 0.496049\n",
            "| Global Round : 49 | Local Epoch : 73 | [0/705 (0%)]\tLoss: 0.434467\n",
            "| Global Round : 49 | Local Epoch : 74 | [0/705 (0%)]\tLoss: 0.458347\n",
            "| Global Round : 49 | Local Epoch : 75 | [0/705 (0%)]\tLoss: 0.458229\n",
            "| Global Round : 49 | Local Epoch : 76 | [0/705 (0%)]\tLoss: 0.433653\n",
            "| Global Round : 49 | Local Epoch : 77 | [0/705 (0%)]\tLoss: 0.468960\n",
            "| Global Round : 49 | Local Epoch : 78 | [0/705 (0%)]\tLoss: 0.421124\n",
            "| Global Round : 49 | Local Epoch : 79 | [0/705 (0%)]\tLoss: 0.454557\n",
            "| Global Round : 49 | Local Epoch : 80 | [0/705 (0%)]\tLoss: 0.441190\n",
            "| Global Round : 49 | Local Epoch : 81 | [0/705 (0%)]\tLoss: 0.421961\n",
            "| Global Round : 49 | Local Epoch : 82 | [0/705 (0%)]\tLoss: 0.463744\n",
            "| Global Round : 49 | Local Epoch : 83 | [0/705 (0%)]\tLoss: 0.417917\n",
            "| Global Round : 49 | Local Epoch : 84 | [0/705 (0%)]\tLoss: 0.431649\n",
            "| Global Round : 49 | Local Epoch : 85 | [0/705 (0%)]\tLoss: 0.438602\n",
            "| Global Round : 49 | Local Epoch : 86 | [0/705 (0%)]\tLoss: 0.406104\n",
            "| Global Round : 49 | Local Epoch : 87 | [0/705 (0%)]\tLoss: 0.434658\n",
            "| Global Round : 49 | Local Epoch : 88 | [0/705 (0%)]\tLoss: 0.410687\n",
            "| Global Round : 49 | Local Epoch : 89 | [0/705 (0%)]\tLoss: 0.408984\n",
            "| Global Round : 49 | Local Epoch : 90 | [0/705 (0%)]\tLoss: 0.426305\n",
            "| Global Round : 49 | Local Epoch : 91 | [0/705 (0%)]\tLoss: 0.397646\n",
            "| Global Round : 49 | Local Epoch : 92 | [0/705 (0%)]\tLoss: 0.398707\n",
            "| Global Round : 49 | Local Epoch : 93 | [0/705 (0%)]\tLoss: 0.430637\n",
            "| Global Round : 49 | Local Epoch : 94 | [0/705 (0%)]\tLoss: 0.416088\n",
            "| Global Round : 49 | Local Epoch : 95 | [0/705 (0%)]\tLoss: 0.394730\n",
            "| Global Round : 49 | Local Epoch : 96 | [0/705 (0%)]\tLoss: 0.383676\n",
            "| Global Round : 49 | Local Epoch : 97 | [0/705 (0%)]\tLoss: 0.400066\n",
            "| Global Round : 49 | Local Epoch : 98 | [0/705 (0%)]\tLoss: 0.413080\n",
            "| Global Round : 49 | Local Epoch : 99 | [0/705 (0%)]\tLoss: 0.384997\n",
            "| Global Round : 49 | Local Epoch : 0 | [0/816 (0%)]\tLoss: 0.857729\n",
            "| Global Round : 49 | Local Epoch : 1 | [0/816 (0%)]\tLoss: 0.809483\n",
            "| Global Round : 49 | Local Epoch : 2 | [0/816 (0%)]\tLoss: 1.486917\n",
            "| Global Round : 49 | Local Epoch : 3 | [0/816 (0%)]\tLoss: 0.873925\n",
            "| Global Round : 49 | Local Epoch : 4 | [0/816 (0%)]\tLoss: 0.789504\n",
            "| Global Round : 49 | Local Epoch : 5 | [0/816 (0%)]\tLoss: 0.894289\n",
            "| Global Round : 49 | Local Epoch : 6 | [0/816 (0%)]\tLoss: 0.659625\n",
            "| Global Round : 49 | Local Epoch : 7 | [0/816 (0%)]\tLoss: 0.772110\n",
            "| Global Round : 49 | Local Epoch : 8 | [0/816 (0%)]\tLoss: 0.840336\n",
            "| Global Round : 49 | Local Epoch : 9 | [0/816 (0%)]\tLoss: 0.759124\n",
            "| Global Round : 49 | Local Epoch : 10 | [0/816 (0%)]\tLoss: 0.640597\n",
            "| Global Round : 49 | Local Epoch : 11 | [0/816 (0%)]\tLoss: 0.649596\n",
            "| Global Round : 49 | Local Epoch : 12 | [0/816 (0%)]\tLoss: 0.695582\n",
            "| Global Round : 49 | Local Epoch : 13 | [0/816 (0%)]\tLoss: 0.616617\n",
            "| Global Round : 49 | Local Epoch : 14 | [0/816 (0%)]\tLoss: 0.636244\n",
            "| Global Round : 49 | Local Epoch : 15 | [0/816 (0%)]\tLoss: 0.612902\n",
            "| Global Round : 49 | Local Epoch : 16 | [0/816 (0%)]\tLoss: 0.561753\n",
            "| Global Round : 49 | Local Epoch : 17 | [0/816 (0%)]\tLoss: 0.588893\n",
            "| Global Round : 49 | Local Epoch : 18 | [0/816 (0%)]\tLoss: 0.556484\n",
            "| Global Round : 49 | Local Epoch : 19 | [0/816 (0%)]\tLoss: 0.601189\n",
            "| Global Round : 49 | Local Epoch : 20 | [0/816 (0%)]\tLoss: 0.521137\n",
            "| Global Round : 49 | Local Epoch : 21 | [0/816 (0%)]\tLoss: 0.546402\n",
            "| Global Round : 49 | Local Epoch : 22 | [0/816 (0%)]\tLoss: 0.537216\n",
            "| Global Round : 49 | Local Epoch : 23 | [0/816 (0%)]\tLoss: 0.526758\n",
            "| Global Round : 49 | Local Epoch : 24 | [0/816 (0%)]\tLoss: 0.523284\n",
            "| Global Round : 49 | Local Epoch : 25 | [0/816 (0%)]\tLoss: 0.506730\n",
            "| Global Round : 49 | Local Epoch : 26 | [0/816 (0%)]\tLoss: 0.504117\n",
            "| Global Round : 49 | Local Epoch : 27 | [0/816 (0%)]\tLoss: 0.484277\n",
            "| Global Round : 49 | Local Epoch : 28 | [0/816 (0%)]\tLoss: 0.484220\n",
            "| Global Round : 49 | Local Epoch : 29 | [0/816 (0%)]\tLoss: 0.479470\n",
            "| Global Round : 49 | Local Epoch : 30 | [0/816 (0%)]\tLoss: 0.463405\n",
            "| Global Round : 49 | Local Epoch : 31 | [0/816 (0%)]\tLoss: 0.466610\n",
            "| Global Round : 49 | Local Epoch : 32 | [0/816 (0%)]\tLoss: 0.453890\n",
            "| Global Round : 49 | Local Epoch : 33 | [0/816 (0%)]\tLoss: 0.441365\n",
            "| Global Round : 49 | Local Epoch : 34 | [0/816 (0%)]\tLoss: 0.435869\n",
            "| Global Round : 49 | Local Epoch : 35 | [0/816 (0%)]\tLoss: 0.430575\n",
            "| Global Round : 49 | Local Epoch : 36 | [0/816 (0%)]\tLoss: 0.427525\n",
            "| Global Round : 49 | Local Epoch : 37 | [0/816 (0%)]\tLoss: 0.425823\n",
            "| Global Round : 49 | Local Epoch : 38 | [0/816 (0%)]\tLoss: 0.422797\n",
            "| Global Round : 49 | Local Epoch : 39 | [0/816 (0%)]\tLoss: 0.417298\n",
            "| Global Round : 49 | Local Epoch : 40 | [0/816 (0%)]\tLoss: 0.412258\n",
            "| Global Round : 49 | Local Epoch : 41 | [0/816 (0%)]\tLoss: 0.411373\n",
            "| Global Round : 49 | Local Epoch : 42 | [0/816 (0%)]\tLoss: 0.408298\n",
            "| Global Round : 49 | Local Epoch : 43 | [0/816 (0%)]\tLoss: 0.409264\n",
            "| Global Round : 49 | Local Epoch : 44 | [0/816 (0%)]\tLoss: 0.411846\n",
            "| Global Round : 49 | Local Epoch : 45 | [0/816 (0%)]\tLoss: 0.426937\n",
            "| Global Round : 49 | Local Epoch : 46 | [0/816 (0%)]\tLoss: 0.417154\n",
            "| Global Round : 49 | Local Epoch : 47 | [0/816 (0%)]\tLoss: 0.411333\n",
            "| Global Round : 49 | Local Epoch : 48 | [0/816 (0%)]\tLoss: 0.394255\n",
            "| Global Round : 49 | Local Epoch : 49 | [0/816 (0%)]\tLoss: 0.391961\n",
            "| Global Round : 49 | Local Epoch : 50 | [0/816 (0%)]\tLoss: 0.407189\n",
            "| Global Round : 49 | Local Epoch : 51 | [0/816 (0%)]\tLoss: 0.424115\n",
            "| Global Round : 49 | Local Epoch : 52 | [0/816 (0%)]\tLoss: 0.470188\n",
            "| Global Round : 49 | Local Epoch : 53 | [0/816 (0%)]\tLoss: 0.396500\n",
            "| Global Round : 49 | Local Epoch : 54 | [0/816 (0%)]\tLoss: 0.423588\n",
            "| Global Round : 49 | Local Epoch : 55 | [0/816 (0%)]\tLoss: 0.481490\n",
            "| Global Round : 49 | Local Epoch : 56 | [0/816 (0%)]\tLoss: 0.387111\n",
            "| Global Round : 49 | Local Epoch : 57 | [0/816 (0%)]\tLoss: 0.533600\n",
            "| Global Round : 49 | Local Epoch : 58 | [0/816 (0%)]\tLoss: 0.553625\n",
            "| Global Round : 49 | Local Epoch : 59 | [0/816 (0%)]\tLoss: 0.576458\n",
            "| Global Round : 49 | Local Epoch : 60 | [0/816 (0%)]\tLoss: 0.429126\n",
            "| Global Round : 49 | Local Epoch : 61 | [0/816 (0%)]\tLoss: 0.613366\n",
            "| Global Round : 49 | Local Epoch : 62 | [0/816 (0%)]\tLoss: 0.424565\n",
            "| Global Round : 49 | Local Epoch : 63 | [0/816 (0%)]\tLoss: 0.542055\n",
            "| Global Round : 49 | Local Epoch : 64 | [0/816 (0%)]\tLoss: 0.443557\n",
            "| Global Round : 49 | Local Epoch : 65 | [0/816 (0%)]\tLoss: 0.501557\n",
            "| Global Round : 49 | Local Epoch : 66 | [0/816 (0%)]\tLoss: 0.462004\n",
            "| Global Round : 49 | Local Epoch : 67 | [0/816 (0%)]\tLoss: 0.446362\n",
            "| Global Round : 49 | Local Epoch : 68 | [0/816 (0%)]\tLoss: 0.458384\n",
            "| Global Round : 49 | Local Epoch : 69 | [0/816 (0%)]\tLoss: 0.418625\n",
            "| Global Round : 49 | Local Epoch : 70 | [0/816 (0%)]\tLoss: 0.442446\n",
            "| Global Round : 49 | Local Epoch : 71 | [0/816 (0%)]\tLoss: 0.437003\n",
            "| Global Round : 49 | Local Epoch : 72 | [0/816 (0%)]\tLoss: 0.397237\n",
            "| Global Round : 49 | Local Epoch : 73 | [0/816 (0%)]\tLoss: 0.397045\n",
            "| Global Round : 49 | Local Epoch : 74 | [0/816 (0%)]\tLoss: 0.416913\n",
            "| Global Round : 49 | Local Epoch : 75 | [0/816 (0%)]\tLoss: 0.416213\n",
            "| Global Round : 49 | Local Epoch : 76 | [0/816 (0%)]\tLoss: 0.398380\n",
            "| Global Round : 49 | Local Epoch : 77 | [0/816 (0%)]\tLoss: 0.383972\n",
            "| Global Round : 49 | Local Epoch : 78 | [0/816 (0%)]\tLoss: 0.388378\n",
            "| Global Round : 49 | Local Epoch : 79 | [0/816 (0%)]\tLoss: 0.398615\n",
            "| Global Round : 49 | Local Epoch : 80 | [0/816 (0%)]\tLoss: 0.386807\n",
            "| Global Round : 49 | Local Epoch : 81 | [0/816 (0%)]\tLoss: 0.384145\n",
            "| Global Round : 49 | Local Epoch : 82 | [0/816 (0%)]\tLoss: 0.380867\n",
            "| Global Round : 49 | Local Epoch : 83 | [0/816 (0%)]\tLoss: 0.382430\n",
            "| Global Round : 49 | Local Epoch : 84 | [0/816 (0%)]\tLoss: 0.381113\n",
            "| Global Round : 49 | Local Epoch : 85 | [0/816 (0%)]\tLoss: 0.374828\n",
            "| Global Round : 49 | Local Epoch : 86 | [0/816 (0%)]\tLoss: 0.369537\n",
            "| Global Round : 49 | Local Epoch : 87 | [0/816 (0%)]\tLoss: 0.367240\n",
            "| Global Round : 49 | Local Epoch : 88 | [0/816 (0%)]\tLoss: 0.370801\n",
            "| Global Round : 49 | Local Epoch : 89 | [0/816 (0%)]\tLoss: 0.372930\n",
            "| Global Round : 49 | Local Epoch : 90 | [0/816 (0%)]\tLoss: 0.364479\n",
            "| Global Round : 49 | Local Epoch : 91 | [0/816 (0%)]\tLoss: 0.363242\n",
            "| Global Round : 49 | Local Epoch : 92 | [0/816 (0%)]\tLoss: 0.361127\n",
            "| Global Round : 49 | Local Epoch : 93 | [0/816 (0%)]\tLoss: 0.360935\n",
            "| Global Round : 49 | Local Epoch : 94 | [0/816 (0%)]\tLoss: 0.360803\n",
            "| Global Round : 49 | Local Epoch : 95 | [0/816 (0%)]\tLoss: 0.355926\n",
            "| Global Round : 49 | Local Epoch : 96 | [0/816 (0%)]\tLoss: 0.362406\n",
            "| Global Round : 49 | Local Epoch : 97 | [0/816 (0%)]\tLoss: 0.364836\n",
            "| Global Round : 49 | Local Epoch : 98 | [0/816 (0%)]\tLoss: 0.366334\n",
            "| Global Round : 49 | Local Epoch : 99 | [0/816 (0%)]\tLoss: 0.367911\n",
            "| Global Round : 49 | Local Epoch : 0 | [0/945 (0%)]\tLoss: 0.824338\n",
            "| Global Round : 49 | Local Epoch : 1 | [0/945 (0%)]\tLoss: 1.512568\n",
            "| Global Round : 49 | Local Epoch : 2 | [0/945 (0%)]\tLoss: 0.755833\n",
            "| Global Round : 49 | Local Epoch : 3 | [0/945 (0%)]\tLoss: 2.153949\n",
            "| Global Round : 49 | Local Epoch : 4 | [0/945 (0%)]\tLoss: 0.689879\n",
            "| Global Round : 49 | Local Epoch : 5 | [0/945 (0%)]\tLoss: 1.037725\n",
            "| Global Round : 49 | Local Epoch : 6 | [0/945 (0%)]\tLoss: 1.339981\n",
            "| Global Round : 49 | Local Epoch : 7 | [0/945 (0%)]\tLoss: 1.444231\n",
            "| Global Round : 49 | Local Epoch : 8 | [0/945 (0%)]\tLoss: 1.331183\n",
            "| Global Round : 49 | Local Epoch : 9 | [0/945 (0%)]\tLoss: 1.177682\n",
            "| Global Round : 49 | Local Epoch : 10 | [0/945 (0%)]\tLoss: 1.071284\n",
            "| Global Round : 49 | Local Epoch : 11 | [0/945 (0%)]\tLoss: 1.061147\n",
            "| Global Round : 49 | Local Epoch : 12 | [0/945 (0%)]\tLoss: 1.062887\n",
            "| Global Round : 49 | Local Epoch : 13 | [0/945 (0%)]\tLoss: 1.016882\n",
            "| Global Round : 49 | Local Epoch : 14 | [0/945 (0%)]\tLoss: 0.934932\n",
            "| Global Round : 49 | Local Epoch : 15 | [0/945 (0%)]\tLoss: 0.854458\n",
            "| Global Round : 49 | Local Epoch : 16 | [0/945 (0%)]\tLoss: 0.801416\n",
            "| Global Round : 49 | Local Epoch : 17 | [0/945 (0%)]\tLoss: 0.778116\n",
            "| Global Round : 49 | Local Epoch : 18 | [0/945 (0%)]\tLoss: 0.778035\n",
            "| Global Round : 49 | Local Epoch : 19 | [0/945 (0%)]\tLoss: 0.779975\n",
            "| Global Round : 49 | Local Epoch : 20 | [0/945 (0%)]\tLoss: 0.770543\n",
            "| Global Round : 49 | Local Epoch : 21 | [0/945 (0%)]\tLoss: 0.794712\n",
            "| Global Round : 49 | Local Epoch : 22 | [0/945 (0%)]\tLoss: 0.757324\n",
            "| Global Round : 49 | Local Epoch : 23 | [0/945 (0%)]\tLoss: 0.738146\n",
            "| Global Round : 49 | Local Epoch : 24 | [0/945 (0%)]\tLoss: 0.719474\n",
            "| Global Round : 49 | Local Epoch : 25 | [0/945 (0%)]\tLoss: 0.680880\n",
            "| Global Round : 49 | Local Epoch : 26 | [0/945 (0%)]\tLoss: 0.684924\n",
            "| Global Round : 49 | Local Epoch : 27 | [0/945 (0%)]\tLoss: 0.667719\n",
            "| Global Round : 49 | Local Epoch : 28 | [0/945 (0%)]\tLoss: 0.652234\n",
            "| Global Round : 49 | Local Epoch : 29 | [0/945 (0%)]\tLoss: 0.652458\n",
            "| Global Round : 49 | Local Epoch : 30 | [0/945 (0%)]\tLoss: 0.639716\n",
            "| Global Round : 49 | Local Epoch : 31 | [0/945 (0%)]\tLoss: 0.623773\n",
            "| Global Round : 49 | Local Epoch : 32 | [0/945 (0%)]\tLoss: 0.623491\n",
            "| Global Round : 49 | Local Epoch : 33 | [0/945 (0%)]\tLoss: 0.606850\n",
            "| Global Round : 49 | Local Epoch : 34 | [0/945 (0%)]\tLoss: 0.603215\n",
            "| Global Round : 49 | Local Epoch : 35 | [0/945 (0%)]\tLoss: 0.600285\n",
            "| Global Round : 49 | Local Epoch : 36 | [0/945 (0%)]\tLoss: 0.585965\n",
            "| Global Round : 49 | Local Epoch : 37 | [0/945 (0%)]\tLoss: 0.593993\n",
            "| Global Round : 49 | Local Epoch : 38 | [0/945 (0%)]\tLoss: 0.580875\n",
            "| Global Round : 49 | Local Epoch : 39 | [0/945 (0%)]\tLoss: 0.579747\n",
            "| Global Round : 49 | Local Epoch : 40 | [0/945 (0%)]\tLoss: 0.563981\n",
            "| Global Round : 49 | Local Epoch : 41 | [0/945 (0%)]\tLoss: 0.569687\n",
            "| Global Round : 49 | Local Epoch : 42 | [0/945 (0%)]\tLoss: 0.565213\n",
            "| Global Round : 49 | Local Epoch : 43 | [0/945 (0%)]\tLoss: 0.561467\n",
            "| Global Round : 49 | Local Epoch : 44 | [0/945 (0%)]\tLoss: 0.552417\n",
            "| Global Round : 49 | Local Epoch : 45 | [0/945 (0%)]\tLoss: 0.549344\n",
            "| Global Round : 49 | Local Epoch : 46 | [0/945 (0%)]\tLoss: 0.553863\n",
            "| Global Round : 49 | Local Epoch : 47 | [0/945 (0%)]\tLoss: 0.542446\n",
            "| Global Round : 49 | Local Epoch : 48 | [0/945 (0%)]\tLoss: 0.548596\n",
            "| Global Round : 49 | Local Epoch : 49 | [0/945 (0%)]\tLoss: 0.533067\n",
            "| Global Round : 49 | Local Epoch : 50 | [0/945 (0%)]\tLoss: 0.533935\n",
            "| Global Round : 49 | Local Epoch : 51 | [0/945 (0%)]\tLoss: 0.525443\n",
            "| Global Round : 49 | Local Epoch : 52 | [0/945 (0%)]\tLoss: 0.525826\n",
            "| Global Round : 49 | Local Epoch : 53 | [0/945 (0%)]\tLoss: 0.522963\n",
            "| Global Round : 49 | Local Epoch : 54 | [0/945 (0%)]\tLoss: 0.520232\n",
            "| Global Round : 49 | Local Epoch : 55 | [0/945 (0%)]\tLoss: 0.517676\n",
            "| Global Round : 49 | Local Epoch : 56 | [0/945 (0%)]\tLoss: 0.513739\n",
            "| Global Round : 49 | Local Epoch : 57 | [0/945 (0%)]\tLoss: 0.520553\n",
            "| Global Round : 49 | Local Epoch : 58 | [0/945 (0%)]\tLoss: 0.504985\n",
            "| Global Round : 49 | Local Epoch : 59 | [0/945 (0%)]\tLoss: 0.533411\n",
            "| Global Round : 49 | Local Epoch : 60 | [0/945 (0%)]\tLoss: 0.531291\n",
            "| Global Round : 49 | Local Epoch : 61 | [0/945 (0%)]\tLoss: 0.525557\n",
            "| Global Round : 49 | Local Epoch : 62 | [0/945 (0%)]\tLoss: 0.506622\n",
            "| Global Round : 49 | Local Epoch : 63 | [0/945 (0%)]\tLoss: 0.517705\n",
            "| Global Round : 49 | Local Epoch : 64 | [0/945 (0%)]\tLoss: 0.512701\n",
            "| Global Round : 49 | Local Epoch : 65 | [0/945 (0%)]\tLoss: 0.506592\n",
            "| Global Round : 49 | Local Epoch : 66 | [0/945 (0%)]\tLoss: 0.497104\n",
            "| Global Round : 49 | Local Epoch : 67 | [0/945 (0%)]\tLoss: 0.495324\n",
            "| Global Round : 49 | Local Epoch : 68 | [0/945 (0%)]\tLoss: 0.494666\n",
            "| Global Round : 49 | Local Epoch : 69 | [0/945 (0%)]\tLoss: 0.479188\n",
            "| Global Round : 49 | Local Epoch : 70 | [0/945 (0%)]\tLoss: 0.502586\n",
            "| Global Round : 49 | Local Epoch : 71 | [0/945 (0%)]\tLoss: 0.485421\n",
            "| Global Round : 49 | Local Epoch : 72 | [0/945 (0%)]\tLoss: 0.483388\n",
            "| Global Round : 49 | Local Epoch : 73 | [0/945 (0%)]\tLoss: 0.485966\n",
            "| Global Round : 49 | Local Epoch : 74 | [0/945 (0%)]\tLoss: 0.466205\n",
            "| Global Round : 49 | Local Epoch : 75 | [0/945 (0%)]\tLoss: 0.478810\n",
            "| Global Round : 49 | Local Epoch : 76 | [0/945 (0%)]\tLoss: 0.459310\n",
            "| Global Round : 49 | Local Epoch : 77 | [0/945 (0%)]\tLoss: 0.463623\n",
            "| Global Round : 49 | Local Epoch : 78 | [0/945 (0%)]\tLoss: 0.464540\n",
            "| Global Round : 49 | Local Epoch : 79 | [0/945 (0%)]\tLoss: 0.455567\n",
            "| Global Round : 49 | Local Epoch : 80 | [0/945 (0%)]\tLoss: 0.463704\n",
            "| Global Round : 49 | Local Epoch : 81 | [0/945 (0%)]\tLoss: 0.454650\n",
            "| Global Round : 49 | Local Epoch : 82 | [0/945 (0%)]\tLoss: 0.447044\n",
            "| Global Round : 49 | Local Epoch : 83 | [0/945 (0%)]\tLoss: 0.453526\n",
            "| Global Round : 49 | Local Epoch : 84 | [0/945 (0%)]\tLoss: 0.449987\n",
            "| Global Round : 49 | Local Epoch : 85 | [0/945 (0%)]\tLoss: 0.441608\n",
            "| Global Round : 49 | Local Epoch : 86 | [0/945 (0%)]\tLoss: 0.446925\n",
            "| Global Round : 49 | Local Epoch : 87 | [0/945 (0%)]\tLoss: 0.458109\n",
            "| Global Round : 49 | Local Epoch : 88 | [0/945 (0%)]\tLoss: 0.437082\n",
            "| Global Round : 49 | Local Epoch : 89 | [0/945 (0%)]\tLoss: 0.442730\n",
            "| Global Round : 49 | Local Epoch : 90 | [0/945 (0%)]\tLoss: 0.454590\n",
            "| Global Round : 49 | Local Epoch : 91 | [0/945 (0%)]\tLoss: 0.431057\n",
            "| Global Round : 49 | Local Epoch : 92 | [0/945 (0%)]\tLoss: 0.440123\n",
            "| Global Round : 49 | Local Epoch : 93 | [0/945 (0%)]\tLoss: 0.460631\n",
            "| Global Round : 49 | Local Epoch : 94 | [0/945 (0%)]\tLoss: 0.430887\n",
            "| Global Round : 49 | Local Epoch : 95 | [0/945 (0%)]\tLoss: 0.436090\n",
            "| Global Round : 49 | Local Epoch : 96 | [0/945 (0%)]\tLoss: 0.462047\n",
            "| Global Round : 49 | Local Epoch : 97 | [0/945 (0%)]\tLoss: 0.430455\n",
            "| Global Round : 49 | Local Epoch : 98 | [0/945 (0%)]\tLoss: 0.426151\n",
            "| Global Round : 49 | Local Epoch : 99 | [0/945 (0%)]\tLoss: 0.446864\n",
            "Global Round :49, the training accuracy is 70.8%, and the training loss is 0.758.\n",
            "Global Round :49, the testing accuracy is 67.8%, and the testing loss is 1.38.\n"
          ]
        }
      ],
      "source": [
        "global_rounds = 50\n",
        "local_epochs = 100\n",
        "rounds = []\n",
        "losses_train = []\n",
        "losses_test = []\n",
        "acces_train = []\n",
        "acces_test = []\n",
        "count = 0\n",
        "for round_idx in range(global_rounds):\n",
        "    local_weights = []\n",
        "    local_losses = []\n",
        "    global_acc = []\n",
        "    rounds.append(round_idx+1)\n",
        "    for user_index in range(user_num):\n",
        "        model_weights, loss = local_trainer(train_data_list[user_index], copy.deepcopy(global_model), round_idx, device, local_epochs,batch_size)\n",
        "        local_weights.append(copy.deepcopy(model_weights))\n",
        "        local_losses.append(loss)\n",
        "\n",
        "\n",
        "    global_weight = average_weights(local_weights)\n",
        "    global_model.load_state_dict(global_weight)\n",
        "    train_acc,train_loss = inference(global_model,train_loader)\n",
        "    losses_train.append(train_loss)\n",
        "    acces_train.append(train_acc)\n",
        "    print('Global Round :{}, the training accuracy is {:.3}%, and the training loss is {:.3}.'.format(round_idx, 100 * train_acc, train_loss))\n",
        "    test_acc, test_loss = inference(global_model, test_loader)\n",
        "    losses_test.append(test_loss)\n",
        "    acces_test.append(test_acc)\n",
        "    print('Global Round :{}, the testing accuracy is {:.3}%, and the testing loss is {:.3}.'.format(round_idx, 100 * test_acc, test_loss))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "id": "AoXqPJs62emG",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "AoXqPJs62emG",
        "outputId": "2022325e-15f4-4069-a596-c67aabda6ab7"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.plot(rounds, losses_train, label=\"Training Loss\")\n",
        "plt.plot(rounds, losses_test, label=\"Testing Loss\")\n",
        "plt.xlabel(\"Global Rounds\")\n",
        "plt.ylabel(\"Loss\")\n",
        "plt.title(\"Training and Testing Losses\")\n",
        "plt.legend()\n",
        "plt.savefig('/content/sample_data/loss.png')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "id": "NSt63eu8-U8c",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "NSt63eu8-U8c",
        "outputId": "52cb2044-80e2-4604-bb19-9b364ed67601"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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jrrvuYvHixQCkp6fz8MMPc/HFFzNnzhyuuOIK7z7nn38+TU1NxrxkGFH8c+VeYiPsXHvcOADS4iKpb+mgw9V/qLlSikpHGxnxkf3OHRRKqZC8gOOAt3w+3w3c3cf8T4AzrPdXAQ/5bHsIuKqv882fP1/1ZNu2bb3GRiONjY1KKaXcbre67bbb1B//+MdhXtHgWLNmjTrxxBP7nGN+54ajicLqJjX+rtfVL97o+rt9YnWhyv/B66qsvrXf/R2t7Sr/B6+rh97fM+g1AGtVgPtqKE1MOUCRz+dia6wXIpIPjAfeHci+IvI1EVkrImtNyGNg/vWvfzF37lxmzJhBQ0MDt9xyy3AvacD8+te/5pJLLuFXv/rVcC/FYBgyHv5gH2E2G189sSt4Iy1OawPBhLpWWnPSQ6RBHClRTFcCLyilXAPZSSn1sFJqgVJqgQl5DMy3v/1tNm7cyLZt23jyySeJiYkZ7iUNmLvuuosDBw5w4oknDvdSDCMcpRRvb6sIysRzKFQ2Onl+XTGXzM8lM6HLh+AREMH4ISodes5R54MASoA8n8+51pg/rgSe9vk8kH0NBoNhyHh7WwU3P76W/23tHUo+lPz7o/10utzc8oUJ3cbTPRpEMAKiUUf+hcoHEUoBsQYoEJHxIhKBFgLLek4SkalAMrDKZ/gt4EwRSbac02daYwaDwRBSXlqvn0W3lTWE7BwNrR08ufog587KZlxa90COtPgIIDgNwmOGCpUGEbI8CKVUp4h8A31jtwNLlVJbReQ+tFPEIyyuBJ6xnCWefWtF5H60kAG4TynVf6quwWAYUpwdLqLCR09IcX1LO+/s0JrDTqvsRShYsa2CprZObj5pQq9tMRFhxEbYqW7su6AnaAEREWYjITo0t/KQJsoppZYDy3uM/bTH53sD7LsUWBqyxRkMhj5Zd6COqx5ezXvfX0JOUvRwL+ew8NqmMjpcioKMOG9dpFBwoKYZm8C07AS/29Pig8uF0DkQkSHrhXKkOKlHJIdS7ht0trFvtdYHH3zQW25iKKiuriY8PJwHH3xwyI5pGDnsKHfQ7nKzryr4rN6B4nB2sGpvTciOP1BeXl/MlMx4Lpg7huK61pD1ZSiqayU7MZqIMP+34GCT5SobnaHLgcAIiJDiKfe9ceNGbr31Vm800caNG4mIiOh3/54C4tZbb+Xaa68dsvU9//zzLF68uFvl1lAQigRAQ+jxmDhCWTjup69s4epHVuM4Ahrk7K9uZv3Bei4+JoepWfrJfldFaLSIg7UtjE2OBLfb7ystLiLoKKZQ+R/ACIjDzrp16zj55JOZP38+Z511FmVlZYAuXDd9+nRmz57NlVdeSWFhIQ8++CB/+tOfmDt3Lh9++CH33nsvv//97wFYsmQJP/jBD1i4cCGTJ0/mww8/BHRW9OWXX8706dO56KKLWLRoEWvXrvW7lqeffpo//OEPlJSUUFxc7B33V8bbX8nvwsJCZs6c6d3v97//Pffee693fXfccQcLFizgL3/5C6+99hqLFi1i3rx5nH766d5ig57M6FmzZjF79mxefPFFli5dyh133OE97r/+9S++/e1vD80vwBA0nhtUMLbwwbC7opFXPy/FreBgTUtIzjEQXl5fjE3gwnk5TMmKBwiZmSm1ei3/r/x8uC+59+vnGcxnR9B5EKHKgYBRVKyP/94F5ZuH9phZs+CcXwc9XSnFN7/5TV599VXS09N59tln+dGPfsTSpUv59a9/zf79+4mMjKS+vp6kpCRuvfXWbk2G3nnnnW7H6+zs5LPPPmP58uX87Gc/Y8WKFfzjH/8gOTmZbdu2sWXLFubOnet3LUVFRZSVlbFw4UIuv/xynn32Wb773e8GLOPtr+R3XV1dn9fb3t7uFU51dXWsXr0aEeGRRx7ht7/9LX/4wx+4//77SUxMZPPmzd554eHh/OIXv+B3v/sd4eHh/Oc//+Ghhx4K+ns2DA01zZaACJEG8ecVu73vD9S0MDMnsY/Zg+fhD/by7o5KHr9xUUCTjtuteGlDCSdMSiMzIQqlFHGRYSFxVLe2u8hz7iQsvBNO+h7YfawJna3w0Z+YpAqpa0mmw+Um3O5/zc4OFw2tHSE1MY0eAXEE0NbWxpYtWzjjjDMAXfguOzsbgNmzZ3P11Vdz4YUXcuGFFwZ1vIsvvhiA+fPne4vxffTRR3zrW98CYObMmcyePdvvvs8++yyXX345AFdeeSU33ngj3/3udwOW8X733Xe9/g9Pye/+BIRvHaXi4mKuuOIKysrKaG9v95bzXrFiBc8884x3XnKyLrl16qmn8vrrrzNt2jQ6Ojq8VWYNhw+P5hBMPP5A2Vbq4I3NZdx4wniWfryfA7XNQ34OD+/uqGT1vlr+uXIv3zq9wO+ctQfqKK5r5btnTgZARJicGRpHdXFdC1lSS6c9irBTfwy+Dma3Cz76M2mie9fUNrd3S6LzxRvimmAExKEzgCf9UKGUYsaMGaxatarXtjfeeIMPPviA1157jV/84hfeJ+q+8JT3Hmhpb9DmpfLycm/Z7NLSUnbv3t3PXt3xLe0N9CrX7Vuo75vf/Cbf+c53OP/881m5cqXXFBWIm266iV/+8pdMnTrVFOcbJrwmpqahNzH9acUu4qPC+NZpBSz7vCSkJqa9Vc2IwN/f283ZM7O85iNfXlpfTEyEnbNmZHnHpmYn8PrnpSilhjRKqMgjIGKzCet5XJsdYlJIUjoHo6qxLaCAqAxxDgQYH8RhJTIykqqqKq+A6OjoYOvWrbjdboqKijjllFP4zW9+Q0NDA01NTcTHx9PYOLAnmBNOOIHnnnsOgG3btvkVNLt27aKpqYmSkhJvee+7776bp59+OmAZb38lvzMzM6msrKSmpoa2tjZef/31gOvyLWv+2GOPecfPOOMMHnjgAe9nj1ayaNEiioqKeOqpp/rsgmcIHVVeH8TQahCbiut1tvJJE0iMDmNqkuJAiASEw9lBVWMbN504nviocO58cRMut+o2x9nh4o1NZZw9M4uYiK5n5qlZ8TicnZQ7AvcpGQwHa7SAsCX6LU0HMWnEu+qBvs17Hg1i7vofw3NDF7ziixEQhxGbzcYLL7zAD37wA+bMmcPcuXP55JNPcLlcXHPNNcyaNYt58+Zx++23k5SUxJe+9CVefvllr5M6GP7v//6Pqqoqpk+fzo9//GNmzJjRq7z3008/zUUXXdRt7JJLLuHpp58OWMbbX8nv8PBwfvrTn7Jw4ULOOOMMpk6dGnBd9957L5dddhnz58/3mq8AfvzjH1NXV8fMmTOZM2cO7733nnfb5ZdfzgknnOA1OxkOH84OF41OrZUOtQ/ij2/vIikmnBtOGAerHuDh2hsora4f0nN42FelTVfHjkvhni9N5/OiepZ+tL/bnBXbK2hs6+SSY3K7jU/JDI2j+mBtK2OkjvDkMf4nxKYR3VEP9K29VVllNuIa94AzNFnfo8fENMz4mlQ++OCDXts/+uijXmOTJ09m06ZN3s8nnXSS9/3KlSu979PS0rw+iKioKJ544gmioqLYu3cvp59+Ovn5+d2Oe8899/Q61+zZs9m+fTsA1113Hddd171HU2ZmJq+++mqv/W6//XZuv/32XuO+6wO44IILuOCCC3rNi4uL66ZR+PLRRx+Z6KUh5H9bywmzC6dOzex3bk2zvjGlxkZQ09yO262wDUHXsnUH6li5s4ofnD2V+MgwWP8YMe4mXI3ltHW6iAwb2qztvVZntgnpcUxMj+W1z0v5w9s7OWN6prfExUvrS8hOjGLxhNRu+3pCXXeWN3LKlIwhW1NxbRMZUockBNAgYtOIqNgG9C2cKxvbsAmEOWsgbeKQrc8Xo0GMMFpaWjjxxBOZM2cOF110Ef/4xz+Cyrk4kqivr2fy5MlER0dz2mmnDfdyRgQbi+r5+lPr+ePbu4KaX93YxizZx8fua0h3V1PfOjR5Cn98eydpcRFcd3w+lG2Ear2eDOooqm0dknP4sq+6iTCbkJ8ag4jw8wtnEW6zcddLm3C7FVWNbby/q4oL5ub0atuZGBNOdmLUkEcyOWrKCKcT4gNoEDFp2FpqiA6392neq3S0kRYXiTRVQWxoqlkbDWKEER8fHzDv4WghKSmJXbuCu5EZ+qehtYNvPLWeDpeivCE4c1F1UxszbIVEKScFthKqm9pIiT20B41Ve2v4eE8NPzlvurb1b3rOuy1T6jhY28ykjLhDOkdP9lY2MzY1xhsqmpUYxY++OI27XtrM02sO0tbhxuVWXHyM/6f5KVnxbC9zDNl6lFJ01pfoR/OEwCYmWuvIiLP3o0E4yY1TUNcMcaERECNeg/CpAWgY4ZjfdW+UUtz5wueUNzg5ZUo6Nc1tQfU5qG5qI516ADKoP2RHtVKKP769k8yESK5eNBZcnbD5BRh7vD6H1IfEUb23qomJ6d2FzhXH5nHCpFR+tXwHT6w+wKycRCZn9o5sAi0g9lY1DVlviNrmdpI6q/WHQAIiJg1QjI9t7zPEuLKxjYnR1ncWIg1iRAuIqKgoampqzI1jFKCUoqamhqio0IX8HY089kkhb22t4K5zpnLG9CyUCq5TWXVTO+miHZ8ZUn/IuRAf7q5mTWEd3zhlkq4Ou/99aK6ExbeibOHkhg29gOh0uSmsaWZCevdy2iLCry+ejcut2FfdzEXzAvgC0JFMHS7F/uqhydM4WKsjmIC+NQggP6q1zyz2ysY28qM8AmLofCS+jGgTU25uLsXFxZh2pKODqKgocnNz+584SthUXM8vlm/n9GkZfPXE8by3sxKAcoeTMf1UZ61qbGOy3SMg6g4pF8LlVvzmzR3kJEVz+bFWH7BNz0FUIkw+G4nPYnxrI5/UDG2yXHFdKx0uxeRkGzRXe2+8AHkpMfzoi9P43Vs7OX9ujxt1Qwk8fQVcspQpmTovYkd5Y0AtA4D//QQiYmHJXX2uqaiulSypRdnCkEBP/dY6cyOaA5qYXG5FTVMbuRFN3fYZaka0gAgPD/dm7BoMowmHs4NvPLWB9LhIfn/ZHETEm3BVGURcf3VTG1l2B7ghy1bPpkPQIJ5dU8TWUgd/u2qejlJqb4btr8GsSyEsEuIyyWlv4EDt0GoQe60qtCcV/h0+eRe+9TnYu2551yzO58sLx/aOztr0jC7LU/gBE+fdQJhN2FHm4Pw5AZ74gZb1z9ARkURifwKitoVsqUXFZSG2ABFbMfpmnx3eRG1LO50uN2E9ym3UNLXhVpBptxzocaHRIEa0iclgGI0opbjrxU2U1Lfyty/PIylGO5c9AqK8ITgBkS71AIyxNwzaB1Hf0s7v3trBovEpnDdbl5Vhx3LoaIbZVimW+CzSqKO4trVXEtuh4BEQyS37wVEM+1f2muM3dHfzi/pn9R4iw+xMSI/tM5KpqbGeGGclEY6D0I85u6i2hbywemyBzEvg1QbSbY0oBbUtvbU3TxZ1Klb+Q0xoNAgjIAyGEcYTqw+wfHM5d541hfn5Kd7xlJgIwu1CRZA+iGR3PaB9EINNlvvT27toaO3g3vNndJWr2PQsJObB2OP05/hsEjqraXe5hzRreW9lM6mxEYQ3l1nnfb7/nSq3Q+VW/b5Gl56ZkpXQZ7LcJ599BkA0Tprryvs8/MHaFsbY6gL7HwCiUwAhBR095c8P4fEjJal6iEyE8ND43oyAMBhGENrev5OTCtJ6tbO02YSM+CgqgtAgmhvriVROsIWRouoGpUFsL3Pw/1Yf4JrF+V2d05qqYO+7MOsysFm3n/gsIjscRNLOgSH0Q+yrbmJiWiw4Sq0FvabNW32x5SUQG4w7Caq1gJiaFU9JfeDmQds2rfO+P7B7a5+HP1jTTLq7GgIlyYE2g0Unk+jW2oE/4VzpyaLurAuZ/wGMgDAYRhQHapppauvk/Dlj/JpPMhMi+31K73C5iXBaoZjp04hUbbQ29V25tydKKe5dtpXE6HC+c8bkrg1bXwLlgtmXd43Fa9NThtQNaSTT3qpmZqa6oaMFpnxRm7V2LA+8g1Kw5QUY/wXIPx7qD0KH01tyw1/zoMLqZlR1V5HLyoM7Ah6+w+WmyVGrBW9Cdt+Lj00jtrMeCCAgHHosqq02ZP4HCLGAEJGzRWSniOwREb/eGxG5XES2ichWEXnKZ9wlIhut17JQrtNgGCl4bOWeMhE9yUqMoqIfAVHT1O7NgSBbl4sPb64cULj465vK+HR/Ld87a4rXBwJo81LWLMiY1jUWr0t/5NiHLtS1rrmd2uZ2ZsZZUT6zLoWEXNj8XOCdyjZC7T6YeQmkFgAKavcxNVsLiO1lvQXEi+uLmWgrwxWjb9ItFXsDH77eSbrqJ8TVQ0wake16rr+w5MrGNhKjw7G1VB2dGoSI2IEHgHOA6cBVIjK9x5wC4G7gBKXUDOAOn82tSqm51uv8UK3TYBhJbC9vxCZQkOknI3n597m+7u9UOPo2F2kHteX8zNICIknV4mgNrqR8S3snv1y+nRljErjy2LE+B94DJeu6nNMeLA1iWlwrB4eoL8S+ai0YJkZZWdCJeTD7MtjzjjZz+WPLi2ALh6nnQdokPVazm5ykaOL9NA9yuRUvritmdlQV9uxZ1NlTsdUXBlzTwdoWssXqv92XiQkgNg27s5bIMFtAE1NGfCQ0V4UsBwJCq0EsBPYopfYppdqBZ4Ce1dpuBh5QStUBKKUqQ7geg2HEs6PMwbi0WJ2M5ovbDZufZ3LzOpraOmlqC3yzr/KJYPJoEBnUBZ0s94/39lLW4ORn58/oXt9o83OAwMxLu+9gCYhJ0Y1DpkHsrdSCJtfu88Q+63Jt3tr6Uu8d3G7tf5h0GsSkQKolIKp36+ZBWfG9BMSqvTWUNrSSq0ogrYDW2DyS20sD+io8fSAA7zUHJDYNaa4iLS7Sbw5KZWMbWfFh0FIbsixqCK2AyAGKfD4XW2O+TAYmi8jHIrJaRM722RYlImut8Qv9nUBEvmbNWWuS4QwG2FnRyDR/5qWa3dBaR1x7BaD6NDPVWFnUSuxeU1CwkUwHapp5+IN9XDh3DAvGdUVQoZQ2L004ubf9PToZ7BHkhzs4WNMyJJUP9lY1EWG3kdxZBWKH+CzInA6Zs/Q6elL0KThKuoRXZLy+idfsAXTJjR3ljm5re35dEZOiGgnrbIHUSdhSxzNWKtlS4r9208HaFsaI5cvpT0DEpEFLLZlxYQF9EONjnIAKWR0mGH4ndRhQACwBrgL+JSJJ1rZ8pdQC4MvAn0WkVz1bpdTDSqkFSqkF6emh+5IMhqOB5rZODtS0MNVPxzQOrgYgzOUkiaY+I5k8dZhUbBpEJeEOiw5aQPxq+Q7C7MLd507rvqF4LdQV6qf4nohAXBZZtnoa2zqpazn0yrF7q5oYnxaLrbFMCwdPUtrsy7WZq6aHr2DLixAWDVPO6RpLneQVENOs5kFl1vfmcHbw5pZyvjzRerpPKyAhu4BsqWXbwQq/ayqqbWFiVIM2CYX1U/gwVtdjGhvT3ssHoZSiqqmN/EjLHHeUahAlQJ7P51xrzJdiYJlSqkMptR/YhRYYKKVKrJ/7gJXAvBCu1WA4YnF2uIKat9OKsvHXUpOiT71vx0gNFY19CIjGNrLsDUhcJoig4jLJlP5DXZVSrNxVyaXzc3u3yVz3KIRFwbQv+d85PosUt7bPFw5BqOu+qmYmZsRCQ3F3h/CsSwHpVkkWVydsewUmnwWRPr6btAId6qoUU3x6QwC8/nkZbZ1uzsy0tIXUAmIytVmq9ID/SsRFtS2MDavvP4IJfOoxNfcyMTlaO2nvdDMmzFNm4+j0QawBCkRkvIhEAFcCPaORXkFrD4hIGtrktE9EkkUk0mf8BGBbCNdqMBxxuN2KH7+ymfn3vx1U9rPn5uXNOfDl4GqI03WFsqS2z7Lf1U1tZNkcWkAAtvhsS4Poux5TZWMbzg43BT1Ldu94AzY+AQu+ClH+o6uIzyKuQwuIQ+1P3d7p5kBtCxPS4nQOhK9DOGGMDmPd9GxX1nPhB9rZO/OS7gdKnQTOemip6dVd7vl1RUzOjCPHVQLhsfq4yeMAaC7z39v9YG0LGdT276AGb2b0mPBmapvbumWYe3IgMu2WcDoaNQilVCfwDeAtYDvwnFJqq4jcJyKeqKS3gBoR2Qa8B3xfKVUDTAPWisjn1vivlVJGQBhGDZ0uN999/nOeWH2Q5nYXq/fV9LvPjjIHcZFh5PQsxNdUBbV7YYZuMzs+vL5PH0R1UztpUg+WgJD4TLJtDf2amDwO5vxUn+qp9Qfhldsgey6c3ruToZf4bMJbKhDhkB3VB2ubcbkVE9NjegsI0Gamuv3a7AXavBQRDwVndJ+XWqB/Vu/2aR7kYE9lExsO1nPp/FykZg+kTtRmshRd9y2yqYiGHmayRmcHdS0dJHdW9x/iCl4NItPehFtBnU+5DU+ZjRRPpNnR6oNQSi1XSk1WSk1USv3CGvupUmqZ9V4ppb6jlJqulJqllHrGGv/E+jzH+vnvUK7TYDiSaOt08fWn1vPyhhK+e8Zk4iLDWHugtt/9tpc3MjkzrneCXLEuBcG0L4EtjImRfQuImsZWktz1XQlY8dmkUdevgPCYhvJTY/RAZzs8f4N+Ur/sP7owXyDis5A2B+Pi4cAhhrrusSKYJie6dXJczxvytC9pc9fm56CzTWdYTzsPwnsIVp9QV/A4qht5YV0xdptw4bwcvc0T8RSbjsserR3Vpd17RBfVthJJO1GdDf07qMGrQaSJ1lh8/RAeDSLRVQ/2CIgMoJUNAcPtpDYYDD60tru46bG1vLW1gnu/NJ1vnlbAvLFJrC3sO5NZKcXO8kamBjIv2SMgZz7EZ5MXVtdnNnV7Uy1huLwaBPGZxNJKY2NDwH1ARzCF2aRLg3nnZ1CyFs7/K6RM6HNf4rX5a1ai85BNTJ4ciPER1noTe2gQUYnaGb3lRdj1JjgbepuXAJLy9ffmLbmRwN6qJl5aX8wpU9LJiBatIaVZmoYIJI9jrFSyqbiHgPANcQ3KxKT7YyfRu9yGJ4tal9nI0OcNEUZAGAxHCA5nB9cu/ZSP91Tz20tnc/0J2mRx7LgUdlY00tBHX+hyh5OG1g6mBXJQZ8/VBd0ScsimxnuT6YnLrQhrtULGPRqE5bvA0XchugM1LeQkR+vS1DvfhFV/h2Nv8pq2+sQSEFPjmg+57PfeymYyEyKJcVrRRP5uyLOvgJYaePOHOsx2wpLec2x2LdisSCZP86DKxjYunZ+rs66Vu8sUBdhTxzMxrIrNJfXdDuUp863XE4SJyarHFO/Sx+kmIBrbiA63E9ZaHdIsajACwmA4Iqhrbufqf33KhoP1/O2qY7h8QVcA4IJxySgF6w8G1iJ2lHkimHpoEB1OKN0AYxfpz4k5pLqqqXA4cfsprV3b3E6qp8yGjwYBENbSd7mNAzUt2v/QUAyv3KpLapz5i36u3MIyu0yMaqKqsY3mPhL5+sPbZrShWA/4uyFPPE0LBkcxTL8A7OH+D5Y6yatBeKLDUmIjOHVqpnfca4oCSB5PLhVsKqrvdpiDtS2Mj6gPvB5/xKQR46nH1NjdB5GREIk0V4W0DhMYAWEwHBH8ecUudpY38q9rF/DF2d1t1HPzkrDbhLWFgf0QnuiaXiGuZRvB1Q55i/XnhDEkdFTS6Xb77TPg24u6S0Do9SS7awNmYCulKKxpZnxyBLxwow4dveyx4MtQWxpEbpg+98FBahFKKfZ5BISjVFdm9WhAvoRFwIyL9Xt/5iUPaQXaoe3qZGJ6HHGRYVxyTA4RYTavb8LrgwBIHkeEaqOtvpy65q7vt6i2hYJoKyw1GB8EQGwaYc4aInqU26h0+JbZCG3+lxEQBsMRwMbiBubnJ3PK1N5PhDERYcwck9CnH2JHuYOcpGgSo3s8CVsJcuRZGkRCLnZ3Oyk0+g2d7VaHyRMdYwmKvkJd61s6aHR2clH9Y9qkdf5fdHRPsEQlQVgUGZZwGmwkU3VTOw5nJxPTrTLfcVndush146TvwOn3Qv6JgQ+YWgDuTqg/QESYjbe+/QW+d9YU62R79M0+0kcoW6GueVLJ5pIuP8TB2hbGh9fr3g2Rfupk+SM2DWmuIT0usluZk6qmNjLijIAwGEYFLrdiZ7mD6WMCR6PMz09hY1E97Z1uv9t3lDUGSJD7TNvRPTd7y2GbLTV+I5k8neTc9qiu6JjoZNy2CKs3tX/fhfYbKGaWPqd9Dn09lftDBOIySXTpMuODLdrn6SI3IT1Ol87oy5yTmAsnfrurL4U/0rpCXQFykqJ121ToHsHkwRIQY30EhNutKKprZYy9n0ZBPYlJg+Yq0uIiugnmKkcbeTEdWjM0AsJgGNnsr27G2eH2n+Bmcey4ZNo63b3CJ0Enhu2taupdYkMp/TTvMS+B9waVLbV+q7pWN+o6TMT5RMeI0BmToTWIANnUB2qayaCesI4myD+hnysOQHw2ES2VJMWED1qD8AiIiRlBCIhgSO0e6upFKS000gq6jyeNBYQ5cXVsKq4H9BN/e6ebVFeQORAeYtOgtZb02HDv997a7qKxrZO8KEuAGh+EwTCy2V6mM2Kn9yEg5o9LBmCdHzPT3qomOt2qd4hrzV5oqe5yUIPuiYAut+Ev1LW6qY1MaUAsx7QHic8ko49ciMLqFibZrM5taZP9zumX+CxoLCc/JWbQPoh9Vc1Eh9vJjo+EhhKtJRwKMSm6BWh1DwHRUqOzrHtqEOFRkDCG6VG1bLZCXT3XEt9RFVyZDe+500C5yYtu85qYPDkQY+xWZVkTxWQwjGy2lTkItwuTepaoAJ1sVvgxGfFR5KfGsMaPo3pHuRYwvTSIIo//wUeDiE0HWzgTI+up9CMgqpp86jD5YE8cQ4bUUxXAB3GgtpljYqxq/YMWENnQWM7Y1NhB12PaW9XEhPRYbB2N/pPkBkNagTfU1Yvnc2pB7/nJ48iXSkobnFQ3tVFU20IYnUS0VgWXA+HBuvnnRjZT29yO2628WdQZXgFhNAiDYUSzrdTBpIx4HRnTk4//Ao+eC1U7WZCfwroDdb1CTXeUNxJhtzE+Lbb7vgdXa+ev7w3bZoOEMYwNqw+gQbSTRn0v04UtXldbDeiDqGlhZmSFLlkR7ydqKBjiM6G9kUmJitJ6Jx0u//6WvtACIk5rDzA0AiK1oLcG4S/E1UPyOFLatTa1uaRB12CSBgQ1cBMTkB3WhMutqGtp9+aveEORjQ/CYBjZbC9zMC3bj4PZ1QFrrSozRZ+xYFwyNc3t7K/u/nS9o6yRSRlxhNt7/DsXfaqjl3o6YRNyGGOr9RvFVOdoJlE5ukJcPcRnkkAzDQ3+ex0cqGlhIqX6aXuwmb1W+OfkGF1LqaSudUC7OztcFNe1dkUwgdekdkikTYLmSp1x7aFmt86yTsrvPT95PBGtFURJO5uLtYCY4Wl9Gj9AJzWQaVVtrW5q95qYElz1gHgzrkOFERAGwzBS3dRGZWObf//D9mXQWKbfl6zlWMsP0TPcdUe5o7d5qaUWqnd19z94SMwh3V3lNVf44m6yzEQ9nZ9WLoGrsXc2dVNbJ9VNbWR3FkH6FD9XGSSW5jEuUptPBppRXVjTjFJYORBDrEFAdzNT9R4dHebpM+GLFcl0fHIjm4obKK5tZWps08DXY2kQKWih7PlbCbMJ0e212j8SKIR3iDACwmAYRvp0UH/6ECSPh/EnQ8k6JqbHkRwT3q1wX11zOxWONqb21ECKrAJ9eX4EREIOiR3V1DU7aevs6jXhditdvgH8aBD65m3zCBAfDtQ0E0srcW0VvaN6BoKlQYyx1wNwcIB+CE+b0S4BIYM3d/niDXX1ERD+Qlw9WALiuJQmNpfUc7C2hYmRlvYxoDBXrR0kuLsERFVjG+nxkUhL6HMgwAgIg2FY2Vaq//l7hbiWbtQmooU3Q95CqNiGdLQyPz+5mwbhyaCe2rPERtFqsIXBmGN6nzQhB7vqIJXGbjWZGlo7SFbWsQMIiPDW3gLiYE0LE8TSdAbroPY5R0JHNVHhtgGHunpCXMenxWoBEZ8VuITGQEger9uWekJdXZ1Quz+wMLQExKyYOiocbZQ7nOSF1esKstHJwZ/XHg5RSbooH7qia2Vjm86ibjICwmAY8WwvczAmMYrk2B4tKD97GMJjYO7VugqrckHZ5ywYl8K+6mZqLGdxwAimg59C9hyIiOl90gDJct2yqHvefCwTU5Krhpb27uU2CmtamCiHGOIKOjEvLBppqmBsSgyFAxQQ+6qayEmKJjrCbvWBGALzEuiyHMn5XY7p+gPg7vAfwQTaNBQRx3h7lzDNoEavZ6D+mdg0ItpribDbtA/C4SQ9PuqwZFGDERAGwyExmEgbX7aVOXprD83VsPkFmHMVRCdpAQFQspYF+ZYf4oB+qtxZ3khKbATp8T69FjrboXR99/BWX6xQy565EFXd6jD18EHEpOKWMJ1N3dg91PVgbbOOYLKF9V/Wuy9EvLkQY1NiB5RN3dDSwdoDdTpBDnQU01AJCOjWn7orgimAgLDKfqd1lOFpzZHUMcAQVw8xaUhzNalxEd1MTByGQn1gBITBMGiWby5jxk/f6rPKal84O1zsrWruXWJj3aPgaoOFX9Of4zIgcSwUr2VWbiIRYTZv4b7t5Y1MzYpHfJ9Myz6HTqd/BzV4b1RZPbKpq5t0FrUrIqF38xybjfaoVDKo71YXCHSS3IyIMm2KOVSTjpULMS5VJ8v1VT3WQ11zO19+ZDWVjjZuOlGXSNcaxBBEMHlILdCJh263/yJ9PUkeh73hgDe3JcZZEXyRPl9i06ClhrS4SMoaWqlpbic7FmhzhDxJDoyAMBgGxdrCWu54diPtLjfv7ehtlw+G3RU6vr2bBuHqhLVLtWM6Y2rXeO58KFlPZJid2TmJrD1Qh9ut2FXupwZT0af6ZyANIjYNZY8kz17b3cTUqOswBXoydcdlWQX7uguIg7UtjFelh2Ze8hCfBY1l5KfG4Oxw+4208qW6qY2r/rWa3ZVNPHztfL4wOR2cDmhvHFoNIm0SdLbq8uDVu3V2dUxK4PnJ46CukNk5icSEC7bmisGtJzYNmqtJi4vw9hzPi7Q0qxAnyYEREAbDgNlX1cRNj68lJymagow4Pt3ffztQf/iNYNrxunawLrql++ScBdBwEJoqWTAuhS0lDeyqbKS1w8U0fw7q5HHePg69EEESxjCuR2/q6qY2MqQBW4D9bPFZvQr2OTtcVDQ0kd5RDOlDJSDKKbCevL/59IaAGlplo5OrHl5NYU0zS687liVTrBvmUIa4evDpT03Nnv6jtZLHQaeT75+QyGNXTERc7YM2MdFSQ0ZcuLdg3xgrL+Ko90GIyNkislNE9ojIXQHmXC4i20Rkq4g85TN+nYjstl7XhXKdBkOwVDe1cf1/1mAX4dEbjmXJlHQ2FtXj7HD1v3MPtpU5iI2wMzbFx5H86UO64Nvks7tP9voh1nHsuGQ6XIpn1xQBdA9xdbt1BrW/8FZfEnLI6ZEsV93URpatd5kND+FJ2VbBvi4fRHFdC7lUYledQ6dBdDSzKCec+y+Ywb6qJi7+xyd87fG17Kpo9E4rb3By5UOrKalv5dEbFnJigY+5xSsgBnFDDkSaTy5EzZ7ADmoPydrUldlZzrEpVsLfQOoweYhNA+UiJ6rrO+8qx34UaxAiYgceAM4BpgNXicj0HnMKgLuBE5RSM4A7rPEU4B5gEbAQuEdEBhAfZjAMPa3tLr762FoqG508ct0C8lNjWTQ+lfZONxt7dBALhm2lDqZmJ2DzeDLLN8PBT+DYm3snYGXP0aGWxWuZbzmqX1hXjAgUZPgIiOLPtANz0hl9nzwxhwxV3UOD8JTZ8C8g7AnZpEojdY4m79iBmhYmDUUEkwfLTi9NlXzluHG8//1T+O4Zk1m1t4az/vwB333uc9YU1nLFw6uobGzj8RsXsnhCj2xiTxZ1z17Uh0Jcpi4jUroBmir8l9jwxQp1pa6wK9lxUCYmrSXkRHQ57FO8kWZHtw9iIbBHKbVPKdUOPANc0GPOzcADSunga6WUx5h7FvC2UqrW2vY20OORymA4fLjcim89s4FNxfX85cp5zBurb9LHjktBBD7dNzAzk1KK7WWO7ualTx+CsGiYd03vHSJiIHM6lKwlKSaCgow4Gp2djE+N1WGdHra+AvZImNLPv0tCDkmuaqocrV5HcGNjAzG0Bn4ytQRHe0NXNnX3ENdDSJLz4Elss26qsZFhfPO0Aj648xRuPmkCr20q5bIHV1Hb3M7jX13IgnF+/AANVpKcv05yg0VEC4Vdb+nP/WkQSXl6DXWFh6bRWMlynnIbIhBv5UUc7SamHKDI53OxNebLZGCyiHwsIqtF5OwB7IuIfE1E1orI2qqqqiFcusHQhVKK+1/fxv+2VXDPedM5a0bXjScxJpypWQl8ur9mQMcsrmulsa2zy0HdUgubn4c5VwR2fuYsgJIN4HazwCq70cu8tO1VmHR69y5n/kgYg125iOmoxeHUeQ2qsUJvC6BBeJ7ulU+5jYM1zUwNK0PFZUFUYt/nDAZPpE+Pkh7JsRH88NxpvP/9JXz9lIk8ffNijhkbwKjgKNFCLizC//bBkloArdaDQH/CMCxSlxqv22+1PrUP7oZuaQlpov1VKTER2FtqIDwWImL72nNIGG4ndRhQACwBrgL+JSJJwe6slHpYKbVAKbUgPT300tQwOnny04M8+kkhN504nutPGN9r+6LxKaw/WBew25s/tnkc1J4Q1w3/T4emekJb/ZG7ANoaoGYPC/K1EJmS6aOBFK+BxlKYcWH/C0js6gtR6XCilMLeYj1kBRQQetzeUuEdKqxpYWp4OTIU2oPvuT1mmR5kJ0bz/bOmMjOnD2HkKB1a/4MHzzWK3etj6BMrkglHmRZ8/uo29UdM93pMOgeisqtDYIgJpYAoAfJ8PudaY74UA8uUUh1Kqf3ALrTACGZfgyHkbC9zcN/r21gyJZ0fnjvN75zFE1Jwdri9HcSCYVupA5vAlEzrSX/Li1pDyJwReCcfR/UJk9JIiY3ghEk+9vdtr2jzUk8Htz8SPNnUtZQ7nDicnSS5rfUHuvlYJpvI1i5t/WBNM/nu4qHxP4DWfMJje2kQA2IoOsn5w5P3kJwfnHaSnN9lYhrseiwTU7xL+x28SXKHwbwEoRUQa4ACERkvIhHAlcCyHnNeQWsPiEga2uS0D3gLOFNEki3n9JnWmMFw2Ghp7+QbT60nMTqc3182p8uZ7ItSLByv/4kHEu66vczB+DTLf1B3QCe3TT+/753SJmtHaclashKjWP+TM7ps8F7z0mkQFbgznRdLg8iWGsqtxjbpUq+3BdIgYtNRCAmuGpwdLjpdblrqyohxNw2dgPDJph40odIgPAKirwQ5X5LHaYd2zd7BRTCBFkRRiUR11BJmEzLio6w6TKGPYIIQCgilVCfwDfSNfTvwnFJqq4jcJyKe/4S3gBoR2Qa8B3xfKVWjlKoF7kcLmTXAfdaYwXDI/OSVLfz89W109lMm42fLtrGvupk/XzGXtLjI3hMqt8Ov80kpWcnkzIHlQ3QrsbHjdf1z6nl972SzQ848KF7be1vJWv2kOv3C4BYQnYwKiyJbaqlsbLOS5BpQiNes0Qt7GM5InU1d3dRGab2TccpyUA9FDoQHK5t6UDgdOst4KCOYPKROArEFLww9ZihH8aEJLKvcxi0nT+CCuWMsDSL0EUygfQAhQym1HFjeY+ynPu8V8B3r1XPfpcDSUK7PMDp5fVMpdS0d7K1q4u9fPobYyN7/Bss+L+XZtUV8/ZSJnDApwD/juse0T+DVr3PK+KU8samWTpebsJ6Ne3rQ0NpBcV0rX140Vg9sfw0yZ0LqxP4XnzMfPvkbdDh1/2MPW1/RDWz6i17yIIIk5JDfWctHDU5dZoN6XNGphPXRY6AjOoPMljqqm9ppdHYw8VD7UPsjPhNK1g9uX2+joBAIiIgYuPp5yJwV3HxfP8Vgymx4iE2Dlmq+f9lUcLt0n/HDkAMBw++kNhgOK84OF3UtHczJS+KD3dVc9uCqXp3VDta08MOXNnPM2CTuOD3Aja+zHTY/p2/Yznqur/0Lze2dbCn133HNlx1lPiW+Gyt0Ytu0LwV3ATkLwN0J5Zu6xjzmpYmnDSySKDGHXLvOpvZWcu3vxhOXaSXLtVFY08IkKcEdHjOwTmn94dEggqjD1ItQZFH7Mun0wBnqPfHkQsChrSc2HZqtKLnWOlDuEeGDMBgGjMPZ4W2r2I39H+gidoeIp//B1YvG8u/rFnCgppmL/vGxt+xFh8vNN5/ZgAj85cp5vdt4etjzNrTUwMl3wSk/Irv0bS6yfcSn+/oPd/VEMM3IToCdbwBqAAKiy1HtpWSdNmMEE73kS0IOWVT7CIh6bP002LEnZnvrMR2saabAVqYjmHq2NT0U4rN03aO2/oVtL0KpQQyUmBTtM4JDNDGlaq0BwNOwyQgIw2ijw+XmqodXs/iX7/C1x9fy0e5qVOUOeOoKeOxL8Nq3unX1au908+HuKh75cF+//gQPFZbwyUyIYsmUDJ6/9XiUgsseXMX7u6r4/f928nlRPb+5ZDZ5viUwerLxKe3MnXgqHP9NGHsc90c8xq7dO/pdw/YyB2lxVonu7a/pEtkZ0/vdD9DOzoSc7n6Iba9Y5qVzgjuG91g5JLlqqWxoprqpnUxb4DpMHiKTskmlgZrGFgprWiiwlyFph9Bm1B8BciGCwqNBHIpJZ6gQgZRx+v1gndTgLdiH261DXOGwCYjQNjQ1GAbAQ+/vZWupgwvnjmHzrr3s3/Urjgt7F1dYDGrxt4hc/Rdatyzjf0lX8Pa2Ct7fWUVjm07ymj4mgeMn9u+485iTshKivPu98vUTuPHRNdz46BpcbsWXF43l3Fl9/EM3V8OuN2HxbV09gS/8J+F/P47Lin6Jy3U2dnvgmHePg1qcDVozOu7rA2skkzNfO6VBm2G2vaoF1UAT1RJzsOOCpkoqG5JJpb5fE1NY0hgQRWt9BRXVbWSpyqH1P0D3bOqB9rh2lOgIn6FOkhssyeN0CZVDEVgxuh4Tznr9twfGB2EYXeyuaOSv7+zhghmp/DnnPVaEfYurw9/jzahzWdz0e+Z9cjz7wiaw9d1n+NYzG1m9r4ZzZ2Vz/4UzASit92OW8oOn9pBHQABkJUbx3K3HcdrUDOaNTeKn5/XzNL/5Be0HmPPlrrGU8WybdReLZQsVK/4acNcOl5tdFU26xMaut/RxpvUT3tqTnPk6vr65RpuXGoqCj17yxdMXghpKysuJoDNwiKsHKxeis74UW91ePTZUSXI9zjE4DaI0NBFMg2X8yZB/os6sHiwebaGl5rCbmIwGYRh2XG7FnS9uIibSzm/CH4J3XkKmnIuccR9fTCtgbHEDj68qZPW+xVzV+TSvXj+ZmZMnYbcJzg4XP3llC2X1rUGdq8LhJDLMRkJ09z/9uMgwHr52AUqp7s13/PH5U5A9V9dG8iHrlK/xzvpXOPnTX8Ex5/p9+t1X1Ux7p1s7qLcv085df32j+yJ3gf5Zsg72vw+28IGbl8AnWa6GnY4YiKR/AWE93TdUFTPWVQ92QqBB9J1N3ScNJcFFgx0uFt6sX4dCrJUM2VytQ1xtYRCVdMhLCwajQRiGnUc/KWTDwXruO2c8UXv+CwtuhKue9j6ZzspN5HeXzeHL196KoJjTshq7lbQWFW4nNTaC0obgNIhyRxtZiVEBhUC/wqF8i05qm3t1r03ZSTH8Le52nETCy7eAq6PXHI8zfEZ6GOx5B6adN3AHb/ZcHY9fvAa2LdPmpeikgR0DuvWmzvAkyfX3ZGoJENVYzkRbKUpsQ39DjozXzt3Giv7n9mQoe1EfKXjyUpqrtA8iJm1ogwL6wAgIw7BysKaF37+1k1OmpPOluJ06emV6z6K/FlmzITEPdnZLrSE7KYqyhiA1iAYnmT7mpQHz+dP6iX3WpX43F0yYyD3qZl0W+t37e23fVuYgIszGhPrV+lqDjV7yJTIO0qfBhid0E6FA31d/RCWhwqLJllrS8PQY6M/EpLdnUM9EKaUzIf/QzCeBsDrLDYi2Rp2XciREMA0lXhNTtdYiDlMdJghCQIjIl0TECBLDkKOU4q6XNmG3Cb+4aBay87/a0Zp/gv8dRGDKubD3XWjvqo+fnRjdK5chEBWNhyAgXB2w6TmdjBag4uqiCam82DqfuunXwMd/0f4Ki5b2Tj7eU82UzHjsO1/XbSvHHj+4teTO14X5bOEw9dzBHUMEEnMZY6sNvglNWAStYUlkSB0TpRR7xhCblzwMptzGkRTiOpTEeExMlg/iMPkfIDgN4gpgt4j8VkSm9jvbYAiSZ9YU8cneGu4+dypjEiJg13+h4My+G99PPVdXPd37nndoTGIUpUH4IJRSlDc4yUoY5BPvnne0iu/rnO7BovFacLw+5g5983/161C6gaLaFi755yq2lzm4btEYHQU19dyuKKiB4smHmLAEogffS0sScxhrryVd6nHbwoM6ljM6nSypZaKtDNtAo4yCxZ8G4XbB+sfhr8fAint1/25fQp0kN1yERUBkYpcGcZjqMEEQAkIpdQ0wD9gLPCoiq6w+DP0UnDcYAlPW0Mov39jO4gkpXHXsWCj6VEdpTOnnaTj/BK1l+JiZshKjcTg7aW7r7GNHXeKirdM9eA1i45Pa/lsQuFtbbnI0YxKjWHXAAZc/DrHptD1xJdf/7XVK6lr4zw0LuTR5n04CG2j0ki9jjwcEZl8++GMAJOSSJVqD6IxODyrc1hWTyTzbHiLoGHoHtQePBuHJpt7zDjx4Eiz7pg75/OhP8MRFunCdB68GMcIEBGhHtccHcZjqMEGQPgillAN4Ad0VLhu4CFgvIt8M4doMIwSlFJUOJ5/tr+W5tUX8/q2d3PTYWjrcbn5zyWxdJXXHG9pcMun0vg9mD9daxq439RMlMCZJ3/D780NUWFnUOdEd0Nk2sItoqdXnnH1FnxqOiLBoQiqf7a9Fxabx6tTf4W6u5S+2P/Lqbcdy8uR0Hb0UEa9DIAdL+mS4fT3MumzwxwBIGEOKu44saoKOrZf4TFLF6g8dMgGRDa42OLgKnrgEnrgY2pvgskfh9o1wwT+g6DN4+OSupMGGEapBgDYr1RVq7fkw5UBAEGGuVuXVG4BJwOPAQqVUpYjEANuAv4V2iYajlaa2Tq5f+hlbSx20dri843abkJscza8unkV+aqx+Sty5HMZ/IbhS1VPO1d3Xij6F/OPJTowGoKzByaSMwIptuZUD8YVVN8KnnXDNi96y1/2y5UVwtcPcq/qdumh8Ci9vKOHGR9fw3k43d4+9k1sqfw6f3gPn/VkLw8lndi+2NxhSJhza/gCJOdhwM8N2gLCEE4PaJTzJ5wY81DkQHjzJcv85R2uMZ/5cN1PyOMTnXQ1ZM+HZa2Dp2XDOb3S5kdj00DjNh5uYNB3SDIfVBxGMAfQS4E9KqQ98B5VSLSLy1dAsyzASWL65jLUH6rhqYR7TshPIT41lXGoMY5Kiu9c4qtoJtft0RnEwTDpdaxs73rAEhKVB9JMsV2E5sqMd+6GjGR45A655oe8mPR42PgVZs/SrHxZN0E7F93ZW8a3TCrj5tHPhvVb48A9ac2mpHlz0UihI0AIyWZqCLkKXkK57eblj0rEFao96qGTP1bb2mZfAyXf6DwrIngNfex9euhne+A6ERQ088/poITZVa1BwWH0QwQiIewGvt0hEooFMpVShUuqdUC3McPTzyoYS8lNj+OVFs/rOL9j5hv7Zn//BQ1SC1jZ2Loczf05mQhQiUNqviclJLK3YOpph9pX6iWzpOXDlkzD+pMA7lqyD0vVw1q+CWt641Bi+eeokZucmccZ066Z7yo+hYhtselZ3fZsU2I9xWPE1x/QX4tpjnm0oe0D0JHUifH93//NiUuDLz8P7v9Ev3wqqIwnfHh1HmA/iecC3EprLGjMYAlLe4GTVvhounJvTf/LZjuU6m3ggtuOp52qto2onEWE20uIi+9Ugyh1OJkVbT2ETT4Gvvq1NGU9cDFtf7r1D0Rp47lp45HQdRRKkvV9E+O6ZU7qEA+jEposf1rkcsy7VuQxHAr5lKYK1bXvMP6EyLw0Umw1OuRu+thLO+uVwryY0+JqVDqMPIhgBEaaUavd8sN4fIZWwDEcqyz4vQSm4cF4/MemN5brw3EBj+T3ahqV9jEmMCkqDmBxr5U/EZUJSHtz4phZOz98Aqx/UoZNbX9Hmp3+fDvtWwvG3w/+tOvQEpagEuOUDOP8IcttFJXaVpA72xuMR5ENdxfVQGTM3eJ/S0Yav1hCo418ICEZAVPm0CEVELgCqQ7ckw0jg5Q2lzMlLYnxabN8Td/5X/5zyxYGdIMGqYbRDC4hgkuUqHG1MiLI0CM9TcEwKXPsKTP0ivPkD+ONUeP46HU54zm/h29vgjJ8NXQE4Ed069EjCc8MP1sSUNBYu/Q8c85XQrcnQHU+yXFTSYa1UG4yAuBX4oYgcFJEi4AfALcEcXETOFpGdIrJHRO7ys/16EakSkY3W6yafbS6f8WXBXpBh+NlR7mB7mYOL5gZhMtq5XNuNM6YN/ERTz7Wa5ZSRlRhFWT8CotzhJDfMakLj2xgnPFrnLBz3Db2OK56Ab66HRbccOaagUOIRfgMxXcy8WNdMMhwePBrEYYxggiCc1EqpvcBiEYmzPjcFc2ARsQMPAGcAxcAaEVmmlNrWY+qzSqlv+DlEq1JqbjDnMhxZvLKhFLtNOG9OPwKirVGbcI69eWD9EDxM+SK8+3PY9V/GJJ1MU1snDmcHCVG98xQ6XG6qm9rIymjQTuKe1TBtdjjrFwNfw0jAU5riMEbHGAaIRzAcRv8DBFnuW0S+CMwAojwOR6XUff3sthDYo5TaZx3jGeACdO6EYYTidiuWbSzhCwVppMX1E4++5x2dWzDYWkIZ07T2sWM52bPOBnSoa0JWbwFR3dSGUpCmanU452AE0khl4im6TMVo0JaOVjwmpsMYwQTBFet7EF2P6ZuAAJcB+UEcOwco8vlcbI315BIR2SQiL4hIns94lIisFZHVInJhEOczHAF8VlhLaYOzf+c0aPNSdDLkLR7cyUS0FrH/fXJjdZmNQI5qj38isbOmqyGNQTPzEviKnyguw5FDWKTW8JLGHtbTBuODOF4pdS1Qp5T6GXAcMFQB0K8B45RSs4G3gcd8tuUrpRYAXwb+LCK9is5bNaHWisjaqqqqnpsNw8ArG0qIibB3D/H0h6tDd1SbfPbgC9YBTDoVXO3kte4ECOio9nSSi2mvDjohzGA4orhhOZz0vcN6ymAEhOc/rkVExgAd6HpM/VEC+GoEudaYF6VUjVLKUxTnEWC+z7YS6+c+YCW6YCA99n9YKbVAKbUgPf3wOm8MvXF2uHhjcxlnz8giJqKfm/7BVbrHbrDJcYFIHq9/dFRiEwJ2lvPUYYporToyGtobDAMlrWBwjaEOgWAExGsikgT8DlgPFAJPBbHfGqBARMaLSARwJdAtGklEfP9Tzwe2W+PJIhJpvU8DTsD4Lo54Vu6spNHZGZx5acdy7SyeeOqhndRysNobS8mIjwrYWa7c4STO3oGtrSH4cE6DYZTT52Oe1SjoHaVUPfCiiLwORCmlGvo7sFKqU0S+AbyF7ly7VCm1VUTuA9YqpZYBt1s5Fp1ALXC9tfs04CERcaOF2K/9RD8ZjjBe3lBCWlwkx09M7b2xtU5X3Sz6DIo/g4OrdS+DQ3WMhkdp22xDEdlJxwes6FrR4GRabAu00z3E1WAwBKRPAaGUcovIA1jmHcscFHSdZKXUcmB5j7Gf+ry/G7jbz36fAP1XRTMcMdS3tPPejiquWZxPmKcQX1uTbuyy/32o3qXHxKaL4829Gk741tCcPDEXGooZkxjt7fnck4pGJwUxTVpAGCe1wRAUwXgH3xGRS4CXlPJ07zAYurN8czntLjcXecxLbU3w5KVaY5h0uu6jkLdQZz8PdThlYg5U7SJrXBTv7qhEKdWr/lN5g5OTY3tkURsMhj4JRkDcAnwH6BQRJzrUVSmlgijcbxgtvLKhhInpsczMSbCEw2VaOFzyLx1GGUoS82DPu2QnRNLa4aKhtYOkmO7lCCocbeQm+smiNhgMAQmm5Wi8UsqmlIpQSiVYn41wMHjZU9nEZ4W1XDQvB2lvhqcuh6LVh0c4gDYxdTQzNrYDgNIeVV2b2jppausky1YPtjCIDlEPA4NhhBFMR7kv+Bvv2UDIcHShlOJHr2xhWnYCX1kcTN5jb9xuxROfHuA3/91BbISdi2cla+FwcBVcfJiEA3greI611QC69ej0MV3PMJ4ciFRVqyOYbEF12jUYRj3BmJi+7/M+Cl1CYx1wiPGJhuFkf3UzT316EIC9lU385Lzp2G2W3d5ttf/o40a6u6KRu17azLoDdZxUkMavzpvImDeu7xIOsy4N8RX4YAmITFUNhPUKdfV0kkvorDUhrgbDAAimWF+33ohWOYw/h2pBo43KRifJMRHdW3AeBj7crSu2XzQvh0c/KaS4roW/XjWPmDCBxy/QfaK/8nKv0sJtnS7+uXIvD7y3h9jIMP54+RwumpmMPHUFHPgYLnr48AoH8LbNTOyoIMyWS3mPUNdy3yzqtCHo42wwjBIGc1cqRucpGA6RhpYOlvxuJY99UnjYz/3h7mrGpsTwpyvmct8FM3h3RyVXPLSaxg/+AYUfwoGP4J2feee3trt4Y1MZ5/31I/68YjfnzMxmxXdO5uJ5Ocgr/weFH8FFD8Hs4LquDSmx6WCPwOYoJjMhqldnOW8WdUulKbNhMAyAYHwQfwM84a02YC46o9pwiKzcVUlLu4u1hXXc1EdL5KGmw+Vm1d5qLrBCUq89bhw5SdH86un/YV/5c5rylhCXVQCr/s46prO0Zhrvbq+ktcNFTlI0S69fwKlTrRvtB7+Dba/A6T+D2ZcfvovwxWbTGdUNxWT76SxX4XCSHAnSagr1GQwDIRgfxFqf953A00qpj0O0nlHFiu2VAGwp7TcxfUjZcLCe5nYXXyjoKh182tQMFua/CEVw8cHLmBI+kdvU20z85PsU2n/PxcfM4ouzslk4PqUrEW7Hct2PYdZlQ5f0NlgSc6GhhOykaDYV13fbVN7gZFp8KzRhNAiDYQAEIyBeAJxKKRfoRkAiEqOUagnt0kY2HS43K3dWEmG3UVzXSkNLB4kxvfsYhIKPdldhEzhuok9t+S0vEl/0Hg0n30/01nF8cqCJ/Gm/5o69N/F65lLk/P+C3Wd9lTvgpa9B9lzdY3m4+ysk5sH+D8jOjuKtrc5uyXIVjU5mRzdpAWE0CIMhaILxQbwDRPt8jgZWhGY5o4c1hbU0Oju54lhd8HbrYdQiPthdzZy8JBKjrRt+cw38907IWUDiyV/n1W+cyNofn873rjyHsAv+ihSvgXfv7zpASy08faVu1XnlU/rncJOYA42ljIkPo73TTW1zu3dTRYOT/MhG/cEkyRkMQROMgIjybTNqvY8J3ZJGB+9s19rDLSfrqJrDZWZqaOlgU3E9J03y0R7+9yNwNmhNwGYH6CpVMfMSWHAjfPwX2PU/cHXCCzdCQ7Hu3ZwYROXWw0FiLig34yxB4OlP7XYrKhvb/PeiNhgMfRKMgGgWkWM8H0RkPuC/ZKYhKJRSrNhewfGTUslNjiEnKZotJf6LzA01n+ytxq3gpMlW/4w978DnT8OJ34HM6f53OutXkDkLXr4FXrsd9r0H5/0Rxi46LGsOCisXItdKliu1+kLUNLfT6VZk2ep0ocDD3PTdYDiaCUZA3AE8LyIfishHwLPAN0K6qhHO3qomDtS0cNo07TCdMSbhsGkQH+6pJi4yjLl5SdDeDK/fAWmT4Qt9dKoKj4LLHtX9ozc+CQtvgWOuPSzrDZpEbapLd+vOgh4NwpNFneyu08LB0pAMBkP/BJMot0ZEpgJTrKGdSqmO0C5rZOOJXjptagYAM3MSeXt7BU1tncRFHkL7zSD4cHcViyek6sS8Fb+E+oNww5u6521fpE3SQmLPO3Dm/X3PHQ6sxkHxbRWE25O8AqLcm0VdY8xLBsMA6VeDEJGvA7FKqS1KqS1AnIj8X+iXNnJ5Z3sF07MTGJMYBe/+nEWxpShFwF4GQ8WBmmaKals5qSAN2lvg04dg3jWQf1xwByg4A875dfdopiOFyDiISsLmKCYrMcrbOKii0SeL2kQwGQwDIhgT081WRzkAlFJ1wM0hW9EIp665nXUH6jh9WgbUH4APfsfskucB2FISWjPTB1Z5jZMK0qB0A7g7YOqX+tnrKCIxz0qWi/ZmU1c0OLEJhDVXmBwIg2GABCMg7OLTfUVE7EBEH/MNffDezkrcCu1/KN0AQHTZp6TFRYbcUf3R7ipykqIZnxar234C5B4b0nMeVqzOcr7Z1OUOJ5mxYUhzldEgDIYBEoyAeBN4VkROE5HTgKeB/4Z2WSOXd7ZXkhEfyaycRK+AoHoXx2W5QpoL0ely88meGk4qSNMhrEWfQeokiPXTP/poxSsgoqlwOHG7FRWONqbEOwFlNAiDYYAEIyB+ALwL3Gq9NtM9cS4gInK2iOwUkT0icpef7deLSJWIbLReN/lsu05Edluv64K7nCOb9k437++q4rRpGdhsAiXrIUK33zw9Zh+7K5twdrhCcu7PixtobOvkpIJ0Xam16DPIXRiScw0bibngrGdsnIsOl6K6uY0Kh5OJ0c16e3z28K7PYDjKCKajnBv4FChE94I4Fdje336WKeoB4BxgOnCViPgLtH9WKTXXej1i7ZsC3AMsss55j4gkB3VFRzCf7q+hqa2T06Zm6p4LZZ/DzIshPIY57q243Iqd5Y0hOfeHu6sQgeMnpkLdfmiphrwRZF4Cby7EuLB6AMrqnZQ7nIyLtEx3xsRkMAyIgAJCRCaLyD0isgP4G3AQQCl1ilLq70EceyGwRym1TynVDjwDXBDkus4C3lZK1VpO8beBs4Pc94jlne2VRIbZOGFSGtTugzaHforPW8iYem1uClU+xEe7q5mdk0hybITWHgDyjqBEt6HAEhBjRDvjC2uaqW/pIDfM+k6NiclgGBB9aRA70NrCeUqpE5VSfwMGYv/IAYp8PhdbYz25REQ2icgLVjOioPcVka+JyFoRWVtVVTWApR1+PNnTJ05KIzrC3uV/GDMP8k8gvHoruVHtIXFUO5wdbCiq50RP9daizyAiHtKnDvm5hhVLQKS5dJ7JxqJ6ANJF/yQ2YxgWZTAcvfQlIC4GyoD3RORfloN6qEt2vgaMU0rNRmsJjw1kZ6XUw0qpBUqpBenpR3YJhV0VTRTXtXqzpyndAGHR+iadfzyC4oLUgyFxVK/eW4PLrbT/ASz/w/yRl1UclwViJ9ZZTmSYjQ0H6wFIcddBTGqv7ngGg6FvAgoIpdQrSqkrganAe+iSGxki8k8ROTOIY5cAeT6fc60x33PUKKXarI+PAPOD3fdoY8X2CgBOm2Y9xZZugOzZYA+DnPlgj+DEiF3sKGukw+Ue0nN/uLuamAg7x4xNhrZGqNw68sxLoL/LhDGIo4TsxCi2lWptTGdRGwe1wTBQgnFSNyulnrJ6U+cCG9CRTf2xBigQkfEiEgFcCSzznSAivv+159Pl/H4LOFNEki3n9JnW2NDT4YTdK6DuQEgO7+Gd7RXMzk0kMyEK3C7toB4zT28Mj4ac+Uxxbqbd5WZ3RVPfBxsgnvIaEWE2HTml3CMvgsmDt7NcNO2WoI1yVkGc8T8YDANlQD2plVJ1llnntCDmdqKL+r2FvvE/p5TaKiL3icj51rTbRWSriHwO3A5cb+1bC9yPFjJrgPussSGnoaEWnryE/ateCsXhAahqbGNDUb2OXgKo3gUdzV0CAiD/eJIbthKNc8jMTKX1rfzijW0U1rRw4iQf/wNoE9NIJDEXGorITowCICrchr25wtRhMhgGQUgrwymllgPLe4z91Of93cDdAfZdCiwN5foAJCYFlxJqK0sYH6JzLP14P0rBubOsm5Svg9pD/vHIh3/g+Ii9bC2dymWHcL5NxfU88uF+3thchlKK82Znc9kC7cCl+DPt94g+6qOG/ZOYC9teJXuK9jdkx0cgzZVGgzAYBkFoS4ceBcRHR1JLPNJSHZLjVzic/Ofj/VwwdwwFmfF6sHSDTpBLndQ1MW8RiI1z4vfxzCBqMrndOkrqkY/289n+WuIiw7jh+HFcd/w48lJiPJOgeA1MPW8IruwIJTEX3B1MiNIdcSfGtUNLp/FBGAyDYNQLCBGhwZaIvbUmJMf/84rduNyK754xpWuwdANkz+keRRQZD9lzWODYwU/LHLjcCrut/6CxlvZOXlxXzL8/2k9hTQs5SdH8+IvTuPzYPBKielRdrdkDrXWQN0L9D+DtCzE2XFskJ0Vb/hyTA2EwDJhRLyAAmsKSiWobehfHvqomnltbxDWLxjI21XqKd3VA+WY49qbeO+SfQN6nD9PZ7mR/dTOTMuICHrvC4eSxTwp58tODNLR2MCcvib+dOYVzZmYRZg/gWioeoQlyvlgtULNUDZBgsqgNhkPACAigLSKF5NbdQ37cP/xvF5FhNr5xakHXYOV26HR29z94yD8e+6q/M1v2srX0WL8C4kB1E39ZsZvXNpfR6VacNT2Lm78wnmPGJnf1kQ5E0acQlQipBX3PO5qxkuXS3ZVEhScxIcpoEAbDYDECAuiISiGheWgT1DYV1/PG5jJuP62A9Hifbm3+HNQexurGPceH7WRLSQMXzO2ePL6j3MG2h27gHvcqLsq9hPHn3kFu/sTgF1W0Rpf3tg0oeO3oIioJIuKIai5j5fduIX3DZj1uNAiDYcCM4DtF8KiYNBJpwtXRPmTH/M2bO0iJjeDmk3rERpVugMhESJnQe6eYFMiYzpKo3b1KbmwtbeBfD/2Fi9UKotLGclLF/yP3sUXw8q3aZNUfrfVQtWNkm5cARLyhrlmJUdibK7XQCI8a7pUZDEcdRkAA9nhdgqK+unxIjvfh7io+3lPDN06ZRHxPR3HpBhgzV9/I/JF/PDNc29lRWotSCtDayDcffpOfqIdoS59F5P99CLevh2O/CtuWwYMnwmPn637RgShZC6iR1SAoEIm54LAS75vKTQ6EwTBIjIAAwhO0fbq+ujSo+UW1LazcWem3JIbbrfjNmzvITY7m6sVju2/sbIOKrf7NSx7yjyfS3Upu216K61pZd6COq/+1mvttD5Nobyfyskd0T+iUCXDOb+A7W+H0n0H1bnjiYtj0XIBFrwFEl/UY6VjZ1AA0lpscCINhkBgfBBCdpG8gzbVlQc3/1X+3s3xzOWlxkVw6P5crjs3TbTyBNzaXsaXEwR8vn0NkWI9ieBVbdR/ovgTE2OMBWGjbzqOfFPLMZwe5NuoDTmhfC2f9CjJ6VGCNToYT74DFt8H/uwiWfVPnV+Qc031e8WeQOQOiEoK6xqOaxDxoroKOVmisgPzjhntFBsNRidEggIRUnUTlbKgIan5xXSsFGXHMG5vEvz7cxym/X8kVD63ipfXF/OF/O5maFd/LwQxA6Xr9sy8BkZCNO3kCi+07+fdH+5kbX8/31aMw7iRYdGvg/cIi4fLHdUnrZ67WN0YPbjcUrx0d5iXwRjLRUKJNTEaDMBgGhREQQGL6GAA6HZVBzS9vcDI3L4l/XbuAVXedyp1nT6Hc4eQ7z31OYU0Ld549xX+SW+kGXXY6aWzvbT7Yxh3PYvtOpmZE85+kpdhsdrjwn/1HH8WmwZVPgrMenvuKNmmBdk63OUZ2gpwvHgFRsRlc7SaL2mAYJEZAAHEJqXQoO6q5/6ZDnS431U1tZFnF4DISovi/JZN477tLePrmxfz2ktmcMiVAY5rSjVp76C9fIf8E4lUj/x3/HBEln2pfQ1Je3/t4yJ4NF/5D5zy88V2r//SnettIj2Dy4BEQxWv1T5MDYTAMCuODAMRmo0ESsLX0X26juqkdt0KX7fbBZhOOm5jKcRNT/e/Y3qKT5Kac0/+C8rUfQj5/WtdNmnNV//v4MuMi7e/44HeQNUuXFo9J9R9aOxJJ0BohJev0T5MDYTAMCiMgLBrtyUQEUW6j3OEEICthgHH1FVtAufr2P3hIyoeEXHC1wZf+0r/G4Y8lP4SKbfDm3doxnbdocMc5GgmL1H6H0o36swlzNRgGhTExWbRGJBHTEYSAaLAEROIABURfGdQ9EYHL/gNfeUX7FQaDzQYXPwRpk0d+gT5/JOZCZ6t+b5zUBsOgMALCoj0ylThX/+U2KiwNoqeJqV9K1usbVbAO07yFkDVzYOfoSWQ8XPWUjoCa+qVDO9bRhscPEREPkYGLHhoMhsAYE5OFKzqVpLoGOl3uwNVQ0SamcLuQGhsxsBOUbgjOQT3UpEyA618/vOc8ErDKfhsHtcEweIwGYWGLSydeWql1OPqcV9HgJCM+ClsQvRq8tDXqNqPBmJcMQ0OClYdiHNQGw6AxAsIiLF6HptZV9Z1NXe5wkpkQ2eecbjRV6YJ6o6UO0pGCx8RkNAiDYdCEVECIyNkislNE9ojIXX3Mu0RElIgssD6PE5FWEdlovR4M5ToBopK0gGiq7btgX7nDGbyDeuvL8I9FsPt/cPq9MPHUQ1ylIWi8AsIkyRkMgyVkPggRsQMPAGcAxcAaEVmmlNrWY1488C3g0x6H2KuUmhuq9fUkLlnfSFrr+hYQFQ1OTp6c3vfBmqt1ktq2V7RZ6cJ/Qsa0IVqpISiS8kFsXb4Ig8EwYELppF4I7FFK7QMQkWeAC4BtPebdD/wG+H4I19IvCVa5jfY+ym00Ojtobnf1nQOx7VV4/TvgbIBTfwIn3AF2Ewtw2IlNhRv+qxMFDQbDoAjlnSsHKPL5XAx0q/UgIscAeUqpN0Skp4AYLyIbAAfwY6XUhz1PICJfA74GMHZs3/WN+iPGMjG5GwMLCE+Iay8TU81ebU7a+oqu/5M9F657DTKnH9KaDIfI2MXDvQKD4ahm2B5tRcQG/BG43s/mMmCsUqpGROYDr4jIDKVUtxAjpdTDwMMACxYsUIe0nsgE2ghH+ii3Ud6gi99lJkRpobDtFS0YPB3dchfCub+H+dfrng0Gg8FwFBNKAVEC+BqAc60xD/HATGCl6NyALGCZiJyvlFoLtAEopdaJyF5gMrA2ZKsVwWFLIsxZHXCKp8zG1O1/hzV/1IO5C+GsX8L0C7ocowaDwTACCKWAWAMUiMh4tGC4EviyZ6NSqgHw1pEQkZXA95RSa0UkHahVSrlEZAJQAOwL4VoBaAlLIqq9LuB2j4kpofwTyJgBX342+CqrBoPBcJQRsjBXpVQn8A3gLWA78JxSaquI3Cci5/ez+xeATSKyEXgBuFUp1X+hpEPEGZlCbGd9wO3lDU4So8Ox1R/QfaWNcDAYDCOYkPoglFLLgeU9xn4aYO4Sn/cvAi+Gcm3+6IxKI8mxN2C5jXKHk7x4GzjKIHnc4V6ewWAwHFZMJrUvsamk4qC2ud3v5gqHkxmx9fpDUv7hW5fBYDAMA0ZA+BAWn0G0tFNV698PUd7gZEqE5cQ2GoTBYBjhGAHhQ0SCrtvTWFPaa5un1Wi+zQgIg8EwOjACwofYZC0gWuoqem2ramrDrWCMqoCwaIgL0HfaYDAYRghGQPgQn6rrMTnrewsITye51I5SSM4fPe07DQbDqMUICB+ik7QG0dnUu9yGJwcivrXEmJcMBsOowAgIX6z+z9Jc1WuT1iAUkU1FRkAYDIZRgREQvkTE0ipR2Fp712Mqd7SRYW/C1t5kBITBYBgVGAHRg2Z7EpFtvZO2KxxOZpscCIPBMIowAqIHrRHJxHb0zoMob3AyPdoSHEaDMBgMowAjIHrQEZlKvLuBDpe723iFw8nEMMv0lGw0CIPBMPIxAqIH7pg0UqV7uQ2llK7DJJUQmwERscO4QoPBYDg8GAHRA1tcOik4qLLCWgEa2zppaXeR6Soz2oPBYBg1GAHRg/CEDCKlk9q6rkimCitJLqmt1PgfDAbDqMEIiB54kuWaa8q8Y+UOJ2F0EtNabgSEwWAYNRgB0YM4q9xGa0NXNnV5g5NsqUGUy4S4GgyGUYMRED2IStQaRIejqx5ThcPJWLEEhtEgDAbDKMEIiJ7E6HIbqqmr3Ea5w8nUSE+I67hhWJTBYDAcfoyA6ImnHlNLtXeovKGNyRG1YAuHhDHDtTKDwWA4rIRUQIjI2SKyU0T2iMhdfcy7RESUiCzwGbvb2m+niJwVynV2IyySVlssET7lNiocTsbZqyApD2z2w7YUg8FgGE7CQnVgEbEDDwBnAMXAGhFZppTa1mNePPAt4FOfsenAlcAMYAywQkQmK6VcoVqvL81hyUS3dwmIcoeTMWEVxrxkMBhGFaHUIBYCe5RS+5RS7cAzwAV+5t0P/AZw+oxdADyjlGpTSu0H9ljHOyy0R6YQ56qnw+Wmw2o1mtZRZgSEwWAYVYRSQOQART6fi60xLyJyDJCnlHpjoPta+39NRNaKyNqqqt49HAaLKzqVVHFQ09ROVWMbcaqF6M4GIyAMBsOoYtic1CJiA/4IfHewx1BKPayUWqCUWpCenj50i4tNJ00cVDe1ddVgApMDYTAYRhUh80EAJUCez+dca8xDPDATWCm6v3MWsExEzg9i35ASFp9BMo1scbTi7FRdAsJoEAaDYRQRSg1iDVAgIuNFJALtdF7m2aiUalBKpSmlximlxgGrgfOVUmuteVeKSKSIjAcKgM9CuNZuRCVlECZuGuqqKDdJcgaDYZQSMg1CKdUpIt8A3gLswFKl1FYRuQ9Yq5Ra1se+W0XkOWAb0Al8/XBFMAHEJlvlNurKKbflMs5WjYpKQqKTDtcSDAaDYdgJpYkJpdRyYHmPsZ8GmLukx+dfAL8I2eL6ICIxAwBnQwUVtjROCa9CTJlvg8EwyjCZ1P6wym24m6q6nNTGvGQwGEYZIdUgjlpidUSUNFdT2dlKhtsICIPBMPowAsIfMakA2J01uFvKCLd3mBBXg8Ew6jAmJn/Yw2ixJxDWWkNGp9U4yGgQBoNhlGEERACcESkkqXrG2kyIq8FgGJ0YARGAzqgUUqWRPKlEiQ0S8/rfyWAwGEYQRkAEQMWkk4qDPKnCFZcNYRHDvSSDwWA4rBgndQBs8emkiIOxVCIp44d7OQaDwXDYMQIiABEJGcTThNjKsacctkrjBoPBcMRgTEwBiEnOwiaKFBzGQW0wGEYlRkAEIDwho+tD0rhhW4fBYDAMF0ZABMIqtwEYDcJgMIxKjIAIRKxPAyIjIAwGwyjECIhAeAREeCzEpvU912AwGEYgRkAEIjoZxAbJ+aA73hkMBsOowgiIQNhsumifMS8ZDIZRismD6IvTfgrJJknOYDCMToyA6Itjrh3uFRgMBsOwEVITk4icLSI7RWSPiNzlZ/utIrJZRDaKyEciMt0aHycirdb4RhF5MJTrNBgMBkNvQqZBiIgdeAA4AygG1ojIMqXUNp9pTymlHrTmnw/8ETjb2rZXKTU3VOszGAwGQ9+EUoNYCOxRSu1TSrUDzwAX+E5QSjl8PsYCKoTrMRgMBsMACKWAyAGKfD4XW2PdEJGvi8he4LfA7T6bxovIBhF5X0RO8ncCEfmaiKwVkbVVVVVDuXaDwWAY9Qx7mKtS6gGl1ETgB8CPreEyYKxSah7wHeApEUnws+/DSqkFSqkF6enpPTcbDAaD4RAIpYAoAXzbsOVaY4F4BrgQQCnVppSqsd6vA/YCk0OzTIPBYDD4I5QCYg1QICLjRSQCuBJY5jtBRAp8Pn4R2G2Np1tObkRkAlAA7AvhWg0Gg8HQg5BFMSmlOkXkG8BbgB1YqpTaKiL3AWuVUsuAb4jI6UAHUAdcZ+3+BeA+EekA3MCtSqnaUK3VYDAYDL0RpUZG4JCIVAEH+pmWBlQfhuUciYzWazfXPbow1z1w8pVSfp24I0ZABIOIrFVKLRjudQwHo/XazXWPLsx1Dy3DHsVkMBgMhiMTIyAMBoPB4JfRJiAeHu4FDCOj9drNdY8uzHUPIaPKB2EwGAyG4BltGoTBYDAYgsQICIPBYDD4ZdQIiP56U4wURGSpiFSKyBafsRQReVtEdls/k4dzjaFARPJE5D0R2SYiW0XkW9b4iL52EYkSkc9E5HPrun9mjY8XkU+tv/dnrWoGIw4RsVtFPV+3Po+W6y706aWz1hob8r/1USEgfHpTnANMB67yNCcagTxKV08ND3cB7yilCoB3rM8jjU7gu0qp6cBi4OvW73ikX3sbcKpSag4wFzhbRBYDvwH+pJSahK5S8NXhW2JI+Raw3efzaLlugFOUUnN98h+G/G99VAgIguhNMVJQSn0A9CxLcgHwmPX+MayiiCMJpVSZUmq99b4RfdPIYYRfu9I0WR/DrZcCTgVesMZH3HUDiEguuobbI9ZnYRRcdx8M+d/6aBEQQfWmGMFkKqXKrPflQOZwLibUiMg4YB7wKaPg2i0zy0agEngbXf24XinVaU0ZqX/vfwbuRNdrA0hldFw36IeA/4nIOhH5mjU25H/rISvWZzgyUUopERmxsc0iEge8CNyhlHLoh0rNSL12pZQLmCsiScDLwNThXVHoEZHzgEql1DoRWTLMyxkOTlRKlYhIBvC2iOzw3ThUf+ujRYMYaG+KkUaFiGQDWD8rh3k9IUFEwtHC4Uml1EvW8Ki4dgClVD3wHnAckCQingfAkfj3fgJwvogUok3GpwJ/YeRfNwBKqRLrZyX6oWAhIfhbHy0Cot/eFCOcZXSVUr8OeHUY1xISLPvzv4HtSqk/+mwa0ddu9U5Jst5HA2eg/S/vAZda00bcdSul7lZK5SqlxqH/n99VSl3NCL9uABGJFZF4z3vgTGALIfhbHzWZ1CJyLtpm6elN8YvhXVFoEJGngSXo8r8VwD3AK8BzwFh0SfTLR1p/DRE5EfgQ2EyXTfqHaD/EiL12EZmNdkja0Q98zyml7rMabT0DpAAbgGuUUm3Dt9LQYZmYvqeUOm80XLd1jS9bH8OAp5RSvxCRVIb4b33UCAiDwWAwDIzRYmIyGAwGwwAxAsJgMBgMfjECwmAwGAx+MQLCYDAYDH4xAsJgMBgMfjECwjBiEZFMEXlKRPZZJQlWichF1rYlngqgfex/r4h8b4DnbAow7rIqb24Rkdc8uQuhQkSuF5G/h/IchpGPERCGEYmVOPcK8IFSaoJSaj46oSp3mJbUalXenIkupvj1YVqHwRA0RkAYRiqnAu1KqQc9A0qpA0qpv/WcaNXRf0VENonIaiv5zMMcS/PYLSI3W/PjROQdEVlv1eQfaGXgVVhF5ERkrnXOTSLysqeGv4isFJEF1vs0q6SERzN4SUTetNb0W5/ruEFEdonIZ+hSFJ7xyyzN5XMR+WCAazWMYkyxPsNIZQawPsi5PwM2KKUuFJFTgcfRvRUAZqP7S8QCG0TkDXSNm4usYoBpwGoRWaaCyDq1epOchi4LgnWubyql3heR+9CZ73f0c5i56Gq1bcBOEfkbuh/Gz4D5QAO65MQGa/5PgbOs4m5J/a3RYPBgNAjDqEBEHrCeoNf42Xwi8P8AlFLvAqkikmBte1Up1aqUqkbfdBcCAvxSRDYBK9DaQH+llaOtktyeMsxvi0gikKSUet+a8xjwhSAu5x2lVINSyglsA/KBRcBKpVSV1fPkWZ/5HwOPWhqQPYjjGwyAERCGkctW4BjPB6XU19FP7ukDPE5PrUABV1vHma+UmouueRXVz3Farbn5aAHTnw+ik67/z57H9q0t5KIfS4BS6lbgx+iKxuusmj0GQ78YAWEYqbwLRInIbT5jMQHmfoi+6XsKv1UrpRzWtgtE931ORRdBXAMkonsRdIjIKeibflAopVqA24HvAs1AnYicZG3+CuDRJgrR5iLoqk7aF58CJ4tIqlX2/DLPBhGZqJT6VCn1U6CK7qXvDYaAGB+EYURiNUy5EPiTiNyJvjE2Az/wM/1eYKllMmqhq2QywCa0aSkNuF8pVSoiTwKvichmYC2wgwGglNpgnesq61wPikgMsA+4wZr2e+A50d3C3gjimGUici/aAV4PbPTZ/DsRKUBrLu8Anw9kvYbRi6nmajAYDAa/GBOTwWAwGPxiBITBYDAY/GIEhMFgMBj8YgSEwWAwGPxiBITBYDAY/GIEhMFgMBj8YgSEwWAwGPzy/wGnQODLRwxxKgAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.plot(rounds, acces_train, label=\"Training Accuracy\")\n",
        "plt.plot(rounds, acces_test, label=\"Testing Accuracy\")\n",
        "plt.xlabel(\"Global Rounds\")\n",
        "plt.ylabel(\"Accuracy\")\n",
        "plt.title(\"Training and Validation Accuracies\")\n",
        "plt.legend()\n",
        "plt.savefig('/content/sample_data/Accuracy.png')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "Mzq3XIVFt6Ep",
      "metadata": {
        "id": "Mzq3XIVFt6Ep"
      },
      "outputs": [],
      "source": [
        "test_data = pd.read_csv(\"/content/sample_data/Test_Data_adjust.csv\")\n",
        "\n",
        "test_features = torch.tensor(test_data.values, dtype=torch.float).to(device)\n",
        "\n",
        "global_model.eval()\n",
        "\n",
        "# Cancel gradient to use model\n",
        "with torch.no_grad():\n",
        "    y_pred_test = global_model(test_features)\n",
        "\n",
        "_, predicted_labels = torch.max(y_pred_test, 1)\n",
        "\n",
        "predicted_labels_np = predicted_labels.cpu().numpy()\n",
        "\n",
        "raw_Test_Data = pd.read_csv(\"/content/sample_data/Test_Data.csv\")\n",
        "\n",
        "raw_Test_Data['total cost'] = predicted_labels_np + 1\n",
        "\n",
        "raw_Test_Data.to_csv(\"/content/sample_data/prediction.csv\", index=False)"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.9"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}