TimeSeries_with_Mish.ipynb

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  "metadata": {
    "colab": {
      "name": "TimeSeries with Mish.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "EPwaEmY2Eeyd",
        "colab_type": "code",
        "outputId": "347cfe42-1309-47a4-cf88-c55f396b99e7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "!git clone https://github.com/timeseriesAI/timeseriesAI.git"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'timeseriesAI'...\n",
            "remote: Enumerating objects: 38, done.\u001b[K\n",
            "remote: Counting objects: 100% (38/38), done.\u001b[K\n",
            "remote: Compressing objects: 100% (29/29), done.\u001b[K\n",
            "remote: Total 38 (delta 4), reused 38 (delta 4), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (38/38), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rXmi1InCEkUv",
        "colab_type": "code",
        "outputId": "e5ea2fcd-8cc4-4a38-8964-6f9f1bee2aec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "%cd timeseriesAI"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/timeseriesAI\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ch404JciE5em",
        "colab_type": "code",
        "outputId": "e49f6a72-7d16-4546-a049-20781b93d520",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 326
        }
      },
      "source": [
        "!pip install tslearn"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tslearn\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/f3/bb/f63c690ee0d6f3b0b3defb4208579af3ef120aa9c2543d327af9c23e93d7/tslearn-0.2.2.tar.gz (520kB)\n",
            "\u001b[K     |████████████████████████████████| 522kB 3.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from tslearn) (1.16.5)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from tslearn) (1.3.1)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.6/dist-packages (from tslearn) (0.21.3)\n",
            "Requirement already satisfied: Cython in /usr/local/lib/python3.6/dist-packages (from tslearn) (0.29.13)\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.6/dist-packages (from tslearn) (0.40.1)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->tslearn) (0.13.2)\n",
            "Requirement already satisfied: llvmlite>=0.25.0dev0 in /usr/local/lib/python3.6/dist-packages (from numba->tslearn) (0.29.0)\n",
            "Building wheels for collected packages: tslearn\n",
            "  Building wheel for tslearn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for tslearn: filename=tslearn-0.2.2-cp36-cp36m-linux_x86_64.whl size=801356 sha256=19774ef18f4560422ce39bf53e60ca8f16c7675a99e7b010c72d029b442ae690\n",
            "  Stored in directory: /root/.cache/pip/wheels/e5/7f/ba/cf984e0e778fae5640d7f4173ec75ce460ad6bbd4eafdae458\n",
            "Successfully built tslearn\n",
            "Installing collected packages: tslearn\n",
            "Successfully installed tslearn-0.2.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mvOz7HaTFAa2",
        "colab_type": "code",
        "outputId": "4a761c89-0e08-4c04-82c4-d5fd3805a53b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        }
      },
      "source": [
        "!pip install pyts"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pyts\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/36/80/5f531de808dbf1625af0434f2fcc55f8c6488980d97ba2cab5cce285c527/pyts-0.9.0-py3-none-any.whl (2.5MB)\n",
            "\u001b[K     |████████████████████████████████| 2.5MB 3.6MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.15.4scipy>=1.3.0scikit-learn>=0.20.1numba>=0.41.0 in /usr/local/lib/python3.6/dist-packages (from pyts) (1.16.5)\n",
            "Installing collected packages: pyts\n",
            "Successfully installed pyts-0.9.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ubJzKIzLEl8e",
        "colab_type": "code",
        "outputId": "a37afac4-f2ba-4d9e-c9ac-551735de479d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        }
      },
      "source": [
        "import fastai, os\n",
        "from fastai_timeseries import *\n",
        "from torchtimeseries.models import *\n",
        "path = Path(os.getcwd())\n",
        "print(path)\n",
        "print('fastai :', fastai.__version__)\n",
        "print('torch  :', torch.__version__)\n",
        "print('device :', device)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>.container { width:100% !important; }</style>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "/content/timeseriesAI\n",
            "fastai : 1.0.57\n",
            "torch  : 1.2.0\n",
            "device : cuda\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "slJiO6dcErUu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dsid = 'ChlorineConcentration'"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N9m05la6FHEm",
        "colab_type": "code",
        "outputId": "401b7be4-c23f-4af0-e386-c24e66985889",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        }
      },
      "source": [
        "X_train, y_train, X_valid, y_valid = get_UCR_data(dsid)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset: ChlorineConcentration\n",
            "Successfully extracted file /tmp/tmpotpc4ygj/ChlorineConcentration.zip to path data/UCR/ChlorineConcentration\n",
            "Successfully extracted dataset\n",
            "X_train: (467, 1, 166)\n",
            "y_train: (467,)\n",
            "X_valid: (3840, 1, 166)\n",
            "y_valid: (3840,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Redj8zoqFISO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "bs = 64                            # ✳️\n",
        "seed = 1234                        # ✳️\n",
        "scale_type = 'standardize'         # ✳️ 'standardize', 'normalize'\n",
        "scale_subtype = 'per_channel'      # ✳️ 'all_samples', 'per_channel', 'per_sample'\n",
        "scale_range = (-1, 1)              # ✳️ for normalization only: usually left to (-1, 1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yA7sQuzAFKcG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "db = (ItemLists('.', TimeSeriesList(X_train), TimeSeriesList(X_valid))\n",
        "      .label_from_lists(y_train, y_valid)\n",
        "      .databunch(bs=min(bs, len(X_train)), val_bs=min(len(X_valid), bs * 2), num_workers=cpus, device=device)\n",
        "      .scale(scale_type=scale_type, scale_subtype=scale_subtype, scale_range=scale_range)\n",
        "     )"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l14dTGJ_FNFO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from torchtimeseries.models import *\n",
        "# Select one arch from these state-of-the-art time series/ 1D models:\n",
        "# ResCNN, FCN, InceptionTime, ResNet\n",
        "arch = MishInceptionTime                     # ✳️   \n",
        "arch_kwargs = dict()                     # ✳️ \n",
        "opt_func=Ranger                          # ✳️ a state-of-the-art optimizer\n",
        "loss_func = LabelSmoothingCrossEntropy() # ✳️"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KtVDFAE8FmQv",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "\n",
        "__all__ = ['InceptionTime']\n",
        "\n",
        "def noop(x):\n",
        "    return x\n",
        "\n",
        "def shortcut(c_in, c_out):\n",
        "    return nn.Sequential(*[nn.Conv1d(c_in, c_out, kernel_size=1), \n",
        "                           nn.BatchNorm1d(c_out)])\n",
        "    \n",
        "class Inception(nn.Module):\n",
        "    def __init__(self, c_in, bottleneck=32, ks=40, nb_filters=32):\n",
        "\n",
        "        super().__init__()\n",
        "        self.bottleneck = nn.Conv1d(c_in, bottleneck, 1) if bottleneck and c_in > 1 else noop\n",
        "        mts_feat = bottleneck or c_in\n",
        "        conv_layers = []\n",
        "        kss = [ks // (2**i) for i in range(3)]\n",
        "        # ensure odd kss until nn.Conv1d with padding='same' is available in pytorch 1.3\n",
        "        kss = [ksi if ksi % 2 != 0 else ksi - 1 for ksi in kss]  \n",
        "        for i in range(len(kss)):\n",
        "            conv_layers.append(\n",
        "                nn.Conv1d(mts_feat, nb_filters, kernel_size=kss[i], padding=kss[i] // 2))\n",
        "        self.conv_layers = nn.ModuleList(conv_layers)\n",
        "        self.maxpool = nn.MaxPool1d(3, stride=1, padding=1)\n",
        "        self.conv = nn.Conv1d(c_in, nb_filters, kernel_size=1)\n",
        "        self.bn = nn.BatchNorm1d(nb_filters * 4)\n",
        "        self.act = Mish()\n",
        "\n",
        "    def forward(self, x):\n",
        "        input_tensor = x\n",
        "        x = self.bottleneck(input_tensor)\n",
        "        for i in range(3):\n",
        "            out_ = self.conv_layers[i](x)\n",
        "            if i == 0: out = out_\n",
        "            else: out = torch.cat((out, out_), 1)\n",
        "        mp = self.conv(self.maxpool(input_tensor))\n",
        "        inc_out = torch.cat((out, mp), 1)\n",
        "        return self.act(self.bn(inc_out))\n",
        "\n",
        "\n",
        "class InceptionBlock(nn.Module):\n",
        "    def __init__(self,c_in,bottleneck=32,ks=40,nb_filters=32,residual=True,depth=6):\n",
        "\n",
        "        super().__init__()\n",
        "\n",
        "        self.residual = residual\n",
        "        self.depth = depth\n",
        "\n",
        "        #inception & residual layers\n",
        "        inc_mods = []\n",
        "        res_layers = []\n",
        "        res = 0\n",
        "        for d in range(depth):\n",
        "            inc_mods.append(\n",
        "                Inception(c_in if d == 0 else nb_filters * 4, bottleneck=bottleneck if d > 0 else 0,ks=ks,\n",
        "                          nb_filters=nb_filters))\n",
        "            if self.residual and d % 3 == 2:\n",
        "                res_layers.append(shortcut(c_in if res == 0 else nb_filters * 4, nb_filters * 4))\n",
        "                res += 1\n",
        "            else: res_layer = res_layers.append(None)\n",
        "        self.inc_mods = nn.ModuleList(inc_mods)\n",
        "        self.res_layers = nn.ModuleList(res_layers)\n",
        "        self.act = Mish()\n",
        "        \n",
        "    def forward(self, x):\n",
        "        res = x\n",
        "        for d, l in enumerate(range(self.depth)):\n",
        "            x = self.inc_mods[d](x)\n",
        "            if self.residual and d % 3 == 2:\n",
        "                res = self.res_layers[d](res)\n",
        "                x += res\n",
        "                res = x\n",
        "                x = self.act(x)\n",
        "        return x\n",
        "    \n",
        "class MishInceptionTime(nn.Module):\n",
        "    def __init__(self,c_in,c_out,bottleneck=32,ks=40,nb_filters=32,residual=True,depth=6):\n",
        "        super().__init__()\n",
        "        self.block = InceptionBlock(c_in,bottleneck=bottleneck,ks=ks,nb_filters=nb_filters,\n",
        "                                    residual=residual,depth=depth)\n",
        "        self.gap = nn.AdaptiveAvgPool1d(1)\n",
        "        self.fc = nn.Linear(nb_filters * 4, c_out)\n",
        "\n",
        "    def forward(self, x):\n",
        "        x = self.block(x)\n",
        "        x = self.gap(x).squeeze(-1)\n",
        "        x = self.fc(x)\n",
        "        return x"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ANGq9mukFz6N",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "import torch.nn.functional as F\n",
        "\n",
        "def mish(input):\n",
        "    '''\n",
        "    Applies the mish function element-wise:\n",
        "    mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x)))\n",
        "    See additional documentation for mish class.\n",
        "    '''\n",
        "    return input * torch.tanh(F.softplus(input))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WckSCbecF2j2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class Mish(nn.Module):\n",
        "    '''\n",
        "    Applies the mish function element-wise:\n",
        "    mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x)))\n",
        "    Shape:\n",
        "        - Input: (N, *) where * means, any number of additional\n",
        "          dimensions\n",
        "        - Output: (N, *), same shape as the input\n",
        "    Examples:\n",
        "        >>> m = Mish()\n",
        "        >>> input = torch.randn(2)\n",
        "        >>> output = m(input)\n",
        "    '''\n",
        "    def __init__(self):\n",
        "        '''\n",
        "        Init method.\n",
        "        '''\n",
        "        super().__init__()\n",
        "\n",
        "    def forward(self, input):\n",
        "        '''\n",
        "        Forward pass of the function.\n",
        "        '''\n",
        "        return mish(input)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WaBMeK2sFOfO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "model = arch(db.features, db.c, **arch_kwargs).to(device)\n",
        "learn = Learner(db, model, opt_func=opt_func, loss_func=loss_func)\n",
        "learn.save('stage_0')\n",
        "print(learn.model)\n",
        "print(learn.summary())"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iAJIqwsYGL7O",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "epochs = 100         # ✳️ \n",
        "max_lr = 1e-2        # ✳️ \n",
        "warmup = False       # ✳️\n",
        "pct_start = .7       # ✳️\n",
        "metrics = [accuracy] # ✳️\n",
        "wd = 1e-2"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8ahFsY92JkGq",
        "colab_type": "code",
        "outputId": "6d3a86e6-2d29-4ef2-82ac-37b304679ac8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "learn.metrics = metrics\n",
        "learn.load('stage_0')\n",
        "learn.fit_one_cycle(epochs, max_lr=4e-3, pct_start=pct_start, moms=(.95, .85) if warmup else (.95, .95),\n",
        "                    div_factor=25.0 if warmup else 1., wd=wd)\n",
        "learn.save('stage_1')\n",
        "learn.recorder.plot_lr()\n",
        "learn.recorder.plot_losses()\n",
        "learn.recorder.plot_metrics()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>1.012777</td>\n",
              "      <td>1.072953</td>\n",
              "      <td>0.532552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>0.953064</td>\n",
              "      <td>1.069419</td>\n",
              "      <td>0.442708</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.924694</td>\n",
              "      <td>1.069815</td>\n",
              "      <td>0.456250</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.903092</td>\n",
              "      <td>1.748473</td>\n",
              "      <td>0.241927</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.873826</td>\n",
              "      <td>1.071273</td>\n",
              "      <td>0.541146</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.828175</td>\n",
              "      <td>1.390200</td>\n",
              "      <td>0.561198</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>0.809174</td>\n",
              "      <td>1.433969</td>\n",
              "      <td>0.606771</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>0.781639</td>\n",
              "      <td>0.858978</td>\n",
              "      <td>0.618490</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>0.753630</td>\n",
              "      <td>1.100971</td>\n",
              "      <td>0.635156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>0.727174</td>\n",
              "      <td>1.581275</td>\n",
              "      <td>0.567969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>0.699877</td>\n",
              "      <td>0.846945</td>\n",
              "      <td>0.659635</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>0.663522</td>\n",
              "      <td>0.729226</td>\n",
              "      <td>0.769792</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>0.631831</td>\n",
              "      <td>0.815644</td>\n",
              "      <td>0.661979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>0.600225</td>\n",
              "      <td>0.807644</td>\n",
              "      <td>0.764583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>0.572676</td>\n",
              "      <td>0.728588</td>\n",
              "      <td>0.772135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.544937</td>\n",
              "      <td>2.087479</td>\n",
              "      <td>0.370573</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.523564</td>\n",
              "      <td>0.997812</td>\n",
              "      <td>0.708073</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.501493</td>\n",
              "      <td>0.843322</td>\n",
              "      <td>0.715104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.482070</td>\n",
              "      <td>1.141018</td>\n",
              "      <td>0.626302</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.463463</td>\n",
              "      <td>0.796837</td>\n",
              "      <td>0.795052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.448785</td>\n",
              "      <td>0.858828</td>\n",
              "      <td>0.731510</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.439685</td>\n",
              "      <td>0.934794</td>\n",
              "      <td>0.745573</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.429768</td>\n",
              "      <td>0.767452</td>\n",
              "      <td>0.787500</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.422663</td>\n",
              "      <td>0.774964</td>\n",
              "      <td>0.782292</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.413418</td>\n",
              "      <td>0.636642</td>\n",
              "      <td>0.836979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.406401</td>\n",
              "      <td>1.116114</td>\n",
              "      <td>0.580469</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>0.398849</td>\n",
              "      <td>0.863338</td>\n",
              "      <td>0.680729</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>0.392019</td>\n",
              "      <td>0.762545</td>\n",
              "      <td>0.758854</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>0.387487</td>\n",
              "      <td>0.782168</td>\n",
              "      <td>0.800781</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>0.383365</td>\n",
              "      <td>0.597646</td>\n",
              "      <td>0.858854</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.377677</td>\n",
              "      <td>1.164683</td>\n",
              "      <td>0.732552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>0.373286</td>\n",
              "      <td>0.660551</td>\n",
              "      <td>0.798698</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>0.366249</td>\n",
              "      <td>0.608770</td>\n",
              "      <td>0.835677</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>0.359654</td>\n",
              "      <td>0.687787</td>\n",
              "      <td>0.830208</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>0.353918</td>\n",
              "      <td>0.563753</td>\n",
              "      <td>0.876562</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>0.348691</td>\n",
              "      <td>0.788348</td>\n",
              "      <td>0.760156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>0.344245</td>\n",
              "      <td>0.772009</td>\n",
              "      <td>0.773438</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>0.342739</td>\n",
              "      <td>0.600686</td>\n",
              "      <td>0.847917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>0.340480</td>\n",
              "      <td>0.577391</td>\n",
              "      <td>0.862500</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>0.338353</td>\n",
              "      <td>0.598812</td>\n",
              "      <td>0.840104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.335321</td>\n",
              "      <td>0.540191</td>\n",
              "      <td>0.881510</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>0.332088</td>\n",
              "      <td>0.558409</td>\n",
              "      <td>0.861458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>0.328655</td>\n",
              "      <td>0.528338</td>\n",
              "      <td>0.883073</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>0.327053</td>\n",
              "      <td>0.677323</td>\n",
              "      <td>0.806771</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>0.324200</td>\n",
              "      <td>0.534867</td>\n",
              "      <td>0.874479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>0.321348</td>\n",
              "      <td>0.580386</td>\n",
              "      <td>0.865104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>0.320071</td>\n",
              "      <td>0.524396</td>\n",
              "      <td>0.886458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>0.317719</td>\n",
              "      <td>0.587627</td>\n",
              "      <td>0.862760</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>0.316825</td>\n",
              "      <td>0.554343</td>\n",
              "      <td>0.870052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>0.317893</td>\n",
              "      <td>0.534202</td>\n",
              "      <td>0.885938</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.317469</td>\n",
              "      <td>0.714208</td>\n",
              "      <td>0.813802</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>0.316341</td>\n",
              "      <td>0.962596</td>\n",
              "      <td>0.681771</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>0.315137</td>\n",
              "      <td>0.600836</td>\n",
              "      <td>0.855990</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>0.315757</td>\n",
              "      <td>0.635627</td>\n",
              "      <td>0.845833</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>0.317272</td>\n",
              "      <td>0.567201</td>\n",
              "      <td>0.876823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>0.316892</td>\n",
              "      <td>0.693297</td>\n",
              "      <td>0.797917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>0.318187</td>\n",
              "      <td>0.740983</td>\n",
              "      <td>0.761458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>0.318742</td>\n",
              "      <td>0.541292</td>\n",
              "      <td>0.863542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>0.318517</td>\n",
              "      <td>0.685558</td>\n",
              "      <td>0.811979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>0.318319</td>\n",
              "      <td>0.573066</td>\n",
              "      <td>0.856250</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.317922</td>\n",
              "      <td>0.645241</td>\n",
              "      <td>0.836979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>0.317544</td>\n",
              "      <td>0.795926</td>\n",
              "      <td>0.768490</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>0.318334</td>\n",
              "      <td>0.609432</td>\n",
              "      <td>0.839323</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>0.317595</td>\n",
              "      <td>0.842797</td>\n",
              "      <td>0.777604</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>0.316292</td>\n",
              "      <td>0.659559</td>\n",
              "      <td>0.844531</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>0.315782</td>\n",
              "      <td>0.533483</td>\n",
              "      <td>0.878906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.315156</td>\n",
              "      <td>0.550381</td>\n",
              "      <td>0.882812</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>0.313982</td>\n",
              "      <td>0.540522</td>\n",
              "      <td>0.873698</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>0.313196</td>\n",
              "      <td>0.523241</td>\n",
              "      <td>0.887500</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>0.312008</td>\n",
              "      <td>0.518488</td>\n",
              "      <td>0.896615</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.310994</td>\n",
              "      <td>0.607449</td>\n",
              "      <td>0.840885</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>0.309322</td>\n",
              "      <td>0.510228</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>0.307950</td>\n",
              "      <td>0.503333</td>\n",
              "      <td>0.894010</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>0.306672</td>\n",
              "      <td>0.501509</td>\n",
              "      <td>0.894792</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>0.305640</td>\n",
              "      <td>0.497061</td>\n",
              "      <td>0.892708</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>0.304498</td>\n",
              "      <td>0.507930</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.303506</td>\n",
              "      <td>0.503825</td>\n",
              "      <td>0.891406</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>0.302653</td>\n",
              "      <td>0.496641</td>\n",
              "      <td>0.893229</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>0.301787</td>\n",
              "      <td>0.501654</td>\n",
              "      <td>0.890104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>0.300851</td>\n",
              "      <td>0.501633</td>\n",
              "      <td>0.898438</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.300633</td>\n",
              "      <td>0.509236</td>\n",
              "      <td>0.896875</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>0.300063</td>\n",
              "      <td>0.512273</td>\n",
              "      <td>0.893750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>0.299460</td>\n",
              "      <td>0.494410</td>\n",
              "      <td>0.896094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>0.298913</td>\n",
              "      <td>0.504752</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>0.298594</td>\n",
              "      <td>0.498473</td>\n",
              "      <td>0.897135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>0.298456</td>\n",
              "      <td>0.492723</td>\n",
              "      <td>0.895052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>0.298215</td>\n",
              "      <td>0.494489</td>\n",
              "      <td>0.896875</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>0.297897</td>\n",
              "      <td>0.492124</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>0.297677</td>\n",
              "      <td>0.492225</td>\n",
              "      <td>0.898177</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>0.297577</td>\n",
              "      <td>0.495610</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.297185</td>\n",
              "      <td>0.497093</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>0.296789</td>\n",
              "      <td>0.497737</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>0.296479</td>\n",
              "      <td>0.496586</td>\n",
              "      <td>0.900521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>0.296195</td>\n",
              "      <td>0.494868</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>0.295765</td>\n",
              "      <td>0.495916</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>0.295699</td>\n",
              "      <td>0.496948</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.295725</td>\n",
              "      <td>0.497435</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>0.295355</td>\n",
              "      <td>0.496948</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>0.295364</td>\n",
              "      <td>0.495899</td>\n",
              "      <td>0.900521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>0.295196</td>\n",
              "      <td>0.496116</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
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2AP0LbNtUTUQc/F/rTaDmyMI2Myu+j506mOUbd/Lq1o57m6xDDvJHbrrSZqcs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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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GVmFYBBNxSzUds+KWXaSCoSj9hL4WjF2A10dT4WyLtT3lHF9RRIZP+NqDq9lx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\nRK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WtXePcM2XfsMjezt5xVrr7ns8i5kGDsOhCJVeD+uaqyb1z3dIZAytnnqH7+D3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\nnTaTVV2+pIcAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cz1BGpCHJ0_Q",
        "colab_type": "code",
        "outputId": "6ed3364b-44f1-4a96-e4c2-ef603c152ac5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "learn.metrics = metrics\n",
        "learn.load('stage_0')\n",
        "learn.fit_one_cycle(epochs, max_lr=4e-3, pct_start=pct_start, moms=(.95, .85) if warmup else (.95, .95),\n",
        "                    div_factor=25.0 if warmup else 1., wd=wd)\n",
        "learn.save('stage_1')\n",
        "learn.recorder.plot_lr()\n",
        "learn.recorder.plot_losses()\n",
        "learn.recorder.plot_metrics()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.891233</td>\n",
              "      <td>1.037587</td>\n",
              "      <td>0.532552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>0.804997</td>\n",
              "      <td>1.021346</td>\n",
              "      <td>0.548958</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.748274</td>\n",
              "      <td>1.056554</td>\n",
              "      <td>0.535677</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.702822</td>\n",
              "      <td>0.945077</td>\n",
              "      <td>0.554688</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.684712</td>\n",
              "      <td>0.842232</td>\n",
              "      <td>0.715625</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.650794</td>\n",
              "      <td>1.222847</td>\n",
              "      <td>0.600260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>0.628617</td>\n",
              "      <td>2.698659</td>\n",
              "      <td>0.549219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>0.603821</td>\n",
              "      <td>1.139335</td>\n",
              "      <td>0.678646</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>0.576940</td>\n",
              "      <td>1.746294</td>\n",
              "      <td>0.609635</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>0.551879</td>\n",
              "      <td>0.882357</td>\n",
              "      <td>0.729427</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>0.525541</td>\n",
              "      <td>1.088757</td>\n",
              "      <td>0.635938</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>0.511055</td>\n",
              "      <td>1.846769</td>\n",
              "      <td>0.468490</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>0.490491</td>\n",
              "      <td>0.686554</td>\n",
              "      <td>0.783594</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>0.470063</td>\n",
              "      <td>0.956487</td>\n",
              "      <td>0.711458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>0.452537</td>\n",
              "      <td>0.580982</td>\n",
              "      <td>0.853646</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.437715</td>\n",
              "      <td>0.766264</td>\n",
              "      <td>0.777865</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.425130</td>\n",
              "      <td>1.224814</td>\n",
              "      <td>0.543750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.412877</td>\n",
              "      <td>0.774330</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.402698</td>\n",
              "      <td>1.221333</td>\n",
              "      <td>0.638281</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.393267</td>\n",
              "      <td>0.573518</td>\n",
              "      <td>0.870313</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.383209</td>\n",
              "      <td>0.829801</td>\n",
              "      <td>0.740625</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.374638</td>\n",
              "      <td>0.733077</td>\n",
              "      <td>0.785937</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.366114</td>\n",
              "      <td>0.546158</td>\n",
              "      <td>0.875521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.358143</td>\n",
              "      <td>0.521163</td>\n",
              "      <td>0.888802</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.352296</td>\n",
              "      <td>0.516444</td>\n",
              "      <td>0.889323</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.346772</td>\n",
              "      <td>0.552129</td>\n",
              "      <td>0.864583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>0.344788</td>\n",
              "      <td>0.684507</td>\n",
              "      <td>0.806771</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>0.340982</td>\n",
              "      <td>0.538589</td>\n",
              "      <td>0.889063</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>0.337190</td>\n",
              "      <td>0.583673</td>\n",
              "      <td>0.860156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>0.334819</td>\n",
              "      <td>0.531805</td>\n",
              "      <td>0.878906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.331453</td>\n",
              "      <td>0.593177</td>\n",
              "      <td>0.861458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>0.329220</td>\n",
              "      <td>0.602869</td>\n",
              "      <td>0.862760</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>0.326365</td>\n",
              "      <td>0.539233</td>\n",
              "      <td>0.882552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>0.323428</td>\n",
              "      <td>0.590564</td>\n",
              "      <td>0.860937</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>0.320308</td>\n",
              "      <td>0.521164</td>\n",
              "      <td>0.890365</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>0.317795</td>\n",
              "      <td>0.514045</td>\n",
              "      <td>0.883073</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>0.315515</td>\n",
              "      <td>0.521145</td>\n",
              "      <td>0.883854</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>0.313607</td>\n",
              "      <td>0.517564</td>\n",
              "      <td>0.889844</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>0.312048</td>\n",
              "      <td>0.591992</td>\n",
              "      <td>0.860156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>0.310616</td>\n",
              "      <td>0.537740</td>\n",
              "      <td>0.886198</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.309277</td>\n",
              "      <td>0.513691</td>\n",
              "      <td>0.893229</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>0.308686</td>\n",
              "      <td>0.516131</td>\n",
              "      <td>0.886198</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>0.307518</td>\n",
              "      <td>0.519246</td>\n",
              "      <td>0.889583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>0.306658</td>\n",
              "      <td>0.525523</td>\n",
              "      <td>0.889583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>0.305614</td>\n",
              "      <td>0.510538</td>\n",
              "      <td>0.896094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>0.305059</td>\n",
              "      <td>0.512496</td>\n",
              "      <td>0.891406</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>0.304134</td>\n",
              "      <td>0.536463</td>\n",
              "      <td>0.870833</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>0.303309</td>\n",
              "      <td>0.500545</td>\n",
              "      <td>0.898438</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>0.302620</td>\n",
              "      <td>0.520819</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>0.301786</td>\n",
              "      <td>0.506906</td>\n",
              "      <td>0.894010</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.301766</td>\n",
              "      <td>0.523104</td>\n",
              "      <td>0.890104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>0.301639</td>\n",
              "      <td>0.518995</td>\n",
              "      <td>0.887760</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>0.301685</td>\n",
              "      <td>0.509778</td>\n",
              "      <td>0.896354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>0.301407</td>\n",
              "      <td>0.531947</td>\n",
              "      <td>0.885677</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>0.300700</td>\n",
              "      <td>0.508494</td>\n",
              "      <td>0.898698</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>0.300041</td>\n",
              "      <td>0.516271</td>\n",
              "      <td>0.891146</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>0.299922</td>\n",
              "      <td>0.524746</td>\n",
              "      <td>0.894531</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>0.299429</td>\n",
              "      <td>0.528077</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>0.299169</td>\n",
              "      <td>0.515413</td>\n",
              "      <td>0.884635</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>0.299569</td>\n",
              "      <td>0.510083</td>\n",
              "      <td>0.888021</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.299197</td>\n",
              "      <td>0.512563</td>\n",
              "      <td>0.884896</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>0.299353</td>\n",
              "      <td>0.511723</td>\n",
              "      <td>0.891667</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>0.298996</td>\n",
              "      <td>0.526859</td>\n",
              "      <td>0.876562</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>0.299486</td>\n",
              "      <td>0.559609</td>\n",
              "      <td>0.883333</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>0.299761</td>\n",
              "      <td>0.562444</td>\n",
              "      <td>0.879948</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>0.299664</td>\n",
              "      <td>0.506171</td>\n",
              "      <td>0.883594</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.299719</td>\n",
              "      <td>0.539666</td>\n",
              "      <td>0.875000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>0.299719</td>\n",
              "      <td>0.496684</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>0.299219</td>\n",
              "      <td>0.501451</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>0.298750</td>\n",
              "      <td>0.500830</td>\n",
              "      <td>0.900781</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.298561</td>\n",
              "      <td>0.508136</td>\n",
              "      <td>0.889583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>0.298302</td>\n",
              "      <td>0.521251</td>\n",
              "      <td>0.885938</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>0.298143</td>\n",
              "      <td>0.511165</td>\n",
              "      <td>0.898177</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>0.297749</td>\n",
              "      <td>0.493944</td>\n",
              "      <td>0.901302</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>0.297740</td>\n",
              "      <td>0.522518</td>\n",
              "      <td>0.893750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>0.297906</td>\n",
              "      <td>0.496480</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.297808</td>\n",
              "      <td>0.499782</td>\n",
              "      <td>0.894792</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>0.297471</td>\n",
              "      <td>0.492262</td>\n",
              "      <td>0.905469</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>0.297453</td>\n",
              "      <td>0.503731</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>0.297123</td>\n",
              "      <td>0.506529</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.296628</td>\n",
              "      <td>0.507527</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>0.296265</td>\n",
              "      <td>0.497598</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>0.296473</td>\n",
              "      <td>0.493957</td>\n",
              "      <td>0.902604</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>0.296478</td>\n",
              "      <td>0.497956</td>\n",
              "      <td>0.900781</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>0.296394</td>\n",
              "      <td>0.503042</td>\n",
              "      <td>0.902344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>0.296165</td>\n",
              "      <td>0.509034</td>\n",
              "      <td>0.896875</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>0.295771</td>\n",
              "      <td>0.496622</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>0.295587</td>\n",
              "      <td>0.491062</td>\n",
              "      <td>0.903906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>0.295830</td>\n",
              "      <td>0.500669</td>\n",
              "      <td>0.902865</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>0.295812</td>\n",
              "      <td>0.495612</td>\n",
              "      <td>0.904167</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.296217</td>\n",
              "      <td>0.502371</td>\n",
              "      <td>0.901563</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>0.295847</td>\n",
              "      <td>0.494026</td>\n",
              "      <td>0.902083</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>0.295568</td>\n",
              "      <td>0.492143</td>\n",
              "      <td>0.903906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>0.295346</td>\n",
              "      <td>0.491907</td>\n",
              "      <td>0.904688</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>0.295197</td>\n",
              "      <td>0.492430</td>\n",
              "      <td>0.903646</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>0.295353</td>\n",
              "      <td>0.492279</td>\n",
              "      <td>0.903385</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.295442</td>\n",
              "      <td>0.492315</td>\n",
              "      <td>0.903385</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>0.295490</td>\n",
              "      <td>0.493760</td>\n",
              "      <td>0.904688</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>0.295166</td>\n",
              "      <td>0.494271</td>\n",
              "      <td>0.904427</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>0.294970</td>\n",
              "      <td>0.495049</td>\n",
              "      <td>0.903906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
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2AP0LbNtUTUQc/F/rTaDmyMI2Myu+j506mOUbd/Lq1o57m6xDDvJHbrrSZqcs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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1T0PNM91nt6IofY5+KwqXnTiGU46s4u63NvNfT8RdMbTncHMKtTV2Gwofxcxq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\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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S2buPenKMPgKs5bPjvZnCtDHl+H06cU0plZsGhRHkZApOUHDmFJR7lqEIB61/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\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6ws2JkIqGQNf",
        "colab_type": "code",
        "outputId": "34bd1afa-8f79-404f-da40-39da11cb8ced",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "learn.metrics = metrics\n",
        "learn.load('stage_0')\n",
        "learn.fit_one_cycle(epochs, max_lr=4e-3, pct_start=pct_start, moms=(.95, .85) if warmup else (.95, .95),\n",
        "                    div_factor=25.0 if warmup else 1., wd=wd)\n",
        "learn.save('stage_1')\n",
        "learn.recorder.plot_lr()\n",
        "learn.recorder.plot_losses()\n",
        "learn.recorder.plot_metrics()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.874231</td>\n",
              "      <td>1.039352</td>\n",
              "      <td>0.532552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>0.775063</td>\n",
              "      <td>1.024203</td>\n",
              "      <td>0.546615</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.741288</td>\n",
              "      <td>1.016412</td>\n",
              "      <td>0.554167</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.683083</td>\n",
              "      <td>1.095043</td>\n",
              "      <td>0.543750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.659810</td>\n",
              "      <td>0.795064</td>\n",
              "      <td>0.745833</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.624149</td>\n",
              "      <td>1.495347</td>\n",
              "      <td>0.595052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>0.587847</td>\n",
              "      <td>0.821074</td>\n",
              "      <td>0.732031</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>0.563775</td>\n",
              "      <td>1.233944</td>\n",
              "      <td>0.498437</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>0.542913</td>\n",
              "      <td>1.445157</td>\n",
              "      <td>0.601562</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>0.526146</td>\n",
              "      <td>1.015020</td>\n",
              "      <td>0.635156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>0.510013</td>\n",
              "      <td>1.921529</td>\n",
              "      <td>0.429948</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>0.502381</td>\n",
              "      <td>4.523854</td>\n",
              "      <td>0.546094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>0.488497</td>\n",
              "      <td>0.909495</td>\n",
              "      <td>0.778906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>0.473940</td>\n",
              "      <td>0.893025</td>\n",
              "      <td>0.726562</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>0.459204</td>\n",
              "      <td>0.626350</td>\n",
              "      <td>0.835938</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.443991</td>\n",
              "      <td>0.851718</td>\n",
              "      <td>0.701563</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.430032</td>\n",
              "      <td>0.700665</td>\n",
              "      <td>0.770573</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.416532</td>\n",
              "      <td>0.653275</td>\n",
              "      <td>0.820312</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.404334</td>\n",
              "      <td>0.729627</td>\n",
              "      <td>0.752604</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.393844</td>\n",
              "      <td>0.555171</td>\n",
              "      <td>0.861979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.384031</td>\n",
              "      <td>0.630179</td>\n",
              "      <td>0.840885</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.376234</td>\n",
              "      <td>0.713505</td>\n",
              "      <td>0.817969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.368765</td>\n",
              "      <td>0.554720</td>\n",
              "      <td>0.871354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.361950</td>\n",
              "      <td>0.567380</td>\n",
              "      <td>0.867708</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.354902</td>\n",
              "      <td>0.576046</td>\n",
              "      <td>0.868750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.348402</td>\n",
              "      <td>0.555593</td>\n",
              "      <td>0.874219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>0.344160</td>\n",
              "      <td>0.631245</td>\n",
              "      <td>0.847135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>0.339413</td>\n",
              "      <td>0.562635</td>\n",
              "      <td>0.872396</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>0.334409</td>\n",
              "      <td>0.536361</td>\n",
              "      <td>0.869531</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>0.330102</td>\n",
              "      <td>0.515179</td>\n",
              "      <td>0.886979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.326269</td>\n",
              "      <td>0.724043</td>\n",
              "      <td>0.788542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>0.323945</td>\n",
              "      <td>0.711639</td>\n",
              "      <td>0.800521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>0.321255</td>\n",
              "      <td>0.557792</td>\n",
              "      <td>0.861979</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>0.319055</td>\n",
              "      <td>0.569374</td>\n",
              "      <td>0.859115</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>0.317020</td>\n",
              "      <td>0.528967</td>\n",
              "      <td>0.886458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>0.315545</td>\n",
              "      <td>0.552009</td>\n",
              "      <td>0.871094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>0.313885</td>\n",
              "      <td>0.618737</td>\n",
              "      <td>0.859635</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>0.312354</td>\n",
              "      <td>0.509359</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>0.310958</td>\n",
              "      <td>0.547445</td>\n",
              "      <td>0.882552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>0.309529</td>\n",
              "      <td>0.536852</td>\n",
              "      <td>0.883854</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.308226</td>\n",
              "      <td>0.550142</td>\n",
              "      <td>0.870313</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>0.307356</td>\n",
              "      <td>0.515248</td>\n",
              "      <td>0.882552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>0.306332</td>\n",
              "      <td>0.509821</td>\n",
              "      <td>0.887760</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>0.305243</td>\n",
              "      <td>0.537185</td>\n",
              "      <td>0.880990</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>0.304368</td>\n",
              "      <td>0.511990</td>\n",
              "      <td>0.893750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>0.303725</td>\n",
              "      <td>0.542573</td>\n",
              "      <td>0.884896</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>0.303056</td>\n",
              "      <td>0.538173</td>\n",
              "      <td>0.890625</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>0.302518</td>\n",
              "      <td>0.505565</td>\n",
              "      <td>0.891146</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>0.301688</td>\n",
              "      <td>0.542131</td>\n",
              "      <td>0.885156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>0.301065</td>\n",
              "      <td>0.502420</td>\n",
              "      <td>0.890885</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.300372</td>\n",
              "      <td>0.535986</td>\n",
              "      <td>0.877344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>0.300045</td>\n",
              "      <td>0.557442</td>\n",
              "      <td>0.869531</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>0.299731</td>\n",
              "      <td>0.505306</td>\n",
              "      <td>0.897396</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>0.299332</td>\n",
              "      <td>0.519055</td>\n",
              "      <td>0.883073</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>0.299350</td>\n",
              "      <td>0.497253</td>\n",
              "      <td>0.896354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>0.298708</td>\n",
              "      <td>0.510140</td>\n",
              "      <td>0.897656</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>0.298323</td>\n",
              "      <td>0.503895</td>\n",
              "      <td>0.892708</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>0.298431</td>\n",
              "      <td>0.492300</td>\n",
              "      <td>0.896354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>0.298279</td>\n",
              "      <td>0.523505</td>\n",
              "      <td>0.890625</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>0.297909</td>\n",
              "      <td>0.503429</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.297660</td>\n",
              "      <td>0.533049</td>\n",
              "      <td>0.885938</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>0.298032</td>\n",
              "      <td>0.527653</td>\n",
              "      <td>0.880469</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>0.298936</td>\n",
              "      <td>0.546540</td>\n",
              "      <td>0.867969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>0.300573</td>\n",
              "      <td>0.586235</td>\n",
              "      <td>0.864323</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>0.304952</td>\n",
              "      <td>0.539784</td>\n",
              "      <td>0.888281</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>0.308673</td>\n",
              "      <td>1.913375</td>\n",
              "      <td>0.349479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.309996</td>\n",
              "      <td>0.933137</td>\n",
              "      <td>0.795833</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>0.310011</td>\n",
              "      <td>0.948775</td>\n",
              "      <td>0.738281</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>0.309684</td>\n",
              "      <td>0.651021</td>\n",
              "      <td>0.847917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>0.308358</td>\n",
              "      <td>0.559605</td>\n",
              "      <td>0.878125</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.307227</td>\n",
              "      <td>0.527371</td>\n",
              "      <td>0.885417</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>0.305764</td>\n",
              "      <td>0.575436</td>\n",
              "      <td>0.855208</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>0.304820</td>\n",
              "      <td>0.529240</td>\n",
              "      <td>0.880469</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>0.304680</td>\n",
              "      <td>0.517044</td>\n",
              "      <td>0.877344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>0.303973</td>\n",
              "      <td>0.516368</td>\n",
              "      <td>0.885417</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>0.303305</td>\n",
              "      <td>0.541206</td>\n",
              "      <td>0.881250</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.302602</td>\n",
              "      <td>0.531820</td>\n",
              "      <td>0.881510</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>0.301951</td>\n",
              "      <td>0.501032</td>\n",
              "      <td>0.896875</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>0.301582</td>\n",
              "      <td>0.522275</td>\n",
              "      <td>0.884375</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>0.301379</td>\n",
              "      <td>0.503882</td>\n",
              "      <td>0.886719</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.300866</td>\n",
              "      <td>0.505720</td>\n",
              "      <td>0.892969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>0.300174</td>\n",
              "      <td>0.522158</td>\n",
              "      <td>0.893490</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>0.299760</td>\n",
              "      <td>0.502691</td>\n",
              "      <td>0.897917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>0.299475</td>\n",
              "      <td>0.501171</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>0.298848</td>\n",
              "      <td>0.497669</td>\n",
              "      <td>0.897917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>0.298338</td>\n",
              "      <td>0.508630</td>\n",
              "      <td>0.896615</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>0.299016</td>\n",
              "      <td>0.510847</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>0.299014</td>\n",
              "      <td>0.518068</td>\n",
              "      <td>0.896094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>0.298850</td>\n",
              "      <td>0.501341</td>\n",
              "      <td>0.898958</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>0.298747</td>\n",
              "      <td>0.500241</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.298257</td>\n",
              "      <td>0.501293</td>\n",
              "      <td>0.900781</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>0.298009</td>\n",
              "      <td>0.503621</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>0.298331</td>\n",
              "      <td>0.496872</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>0.298013</td>\n",
              "      <td>0.496745</td>\n",
              "      <td>0.896354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>0.297539</td>\n",
              "      <td>0.498533</td>\n",
              "      <td>0.897396</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>0.297427</td>\n",
              "      <td>0.499705</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.297004</td>\n",
              "      <td>0.501491</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>0.296930</td>\n",
              "      <td>0.500032</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>0.296607</td>\n",
              "      <td>0.501400</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>0.296293</td>\n",
              "      <td>0.501102</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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2AP0LbNtUTUQc/F/rTaDmyMI2Myu+j506mOUbd/Lq1o57m6xDDvJHbrrSZqcs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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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44NfQbyBceBuM+ggMGA2VJ8Nb97b35HEOnvi6XnnrotthysXa2+f13x56b5/3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\nhdkBzbMTbQQAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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tL3HEZo0UlMEgIng9kqKjOU7A52FabRlbGnsjBaUwUKeQQ4J2+mhHczehSIyW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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DIy_6oZ4G28G",
        "colab_type": "code",
        "outputId": "106731cd-c30b-459f-aa0d-dd58dde48cbe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "learn.metrics = metrics\n",
        "learn.load('stage_0')\n",
        "learn.fit_one_cycle(epochs, max_lr=4e-3, pct_start=pct_start, moms=(.95, .85) if warmup else (.95, .95),\n",
        "                    div_factor=25.0 if warmup else 1., wd=wd)\n",
        "learn.save('stage_1')\n",
        "learn.recorder.plot_lr()\n",
        "learn.recorder.plot_losses()\n",
        "learn.recorder.plot_metrics()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.873835</td>\n",
              "      <td>1.056990</td>\n",
              "      <td>0.532552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>0.692181</td>\n",
              "      <td>1.045930</td>\n",
              "      <td>0.554167</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.644222</td>\n",
              "      <td>1.045480</td>\n",
              "      <td>0.558073</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.660124</td>\n",
              "      <td>1.181455</td>\n",
              "      <td>0.579167</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.646364</td>\n",
              "      <td>0.736438</td>\n",
              "      <td>0.740885</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.609011</td>\n",
              "      <td>0.831515</td>\n",
              "      <td>0.685938</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>0.576369</td>\n",
              "      <td>0.934401</td>\n",
              "      <td>0.618490</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>0.551749</td>\n",
              "      <td>4.531230</td>\n",
              "      <td>0.546354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>0.532110</td>\n",
              "      <td>2.181627</td>\n",
              "      <td>0.634115</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>0.510009</td>\n",
              "      <td>1.019105</td>\n",
              "      <td>0.741146</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>0.494718</td>\n",
              "      <td>1.370600</td>\n",
              "      <td>0.720052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>0.476898</td>\n",
              "      <td>1.439400</td>\n",
              "      <td>0.469010</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>0.459524</td>\n",
              "      <td>0.637677</td>\n",
              "      <td>0.842969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>0.440191</td>\n",
              "      <td>0.665406</td>\n",
              "      <td>0.811458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>0.424669</td>\n",
              "      <td>0.754371</td>\n",
              "      <td>0.781250</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.410196</td>\n",
              "      <td>0.751117</td>\n",
              "      <td>0.800521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.397550</td>\n",
              "      <td>0.908229</td>\n",
              "      <td>0.703125</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.387447</td>\n",
              "      <td>0.561151</td>\n",
              "      <td>0.865104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.377120</td>\n",
              "      <td>0.614459</td>\n",
              "      <td>0.861198</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.369060</td>\n",
              "      <td>0.578579</td>\n",
              "      <td>0.857031</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.361457</td>\n",
              "      <td>0.620709</td>\n",
              "      <td>0.830729</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.354482</td>\n",
              "      <td>0.566500</td>\n",
              "      <td>0.871615</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.347955</td>\n",
              "      <td>0.550401</td>\n",
              "      <td>0.882812</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.341621</td>\n",
              "      <td>0.691815</td>\n",
              "      <td>0.822656</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.336331</td>\n",
              "      <td>0.537200</td>\n",
              "      <td>0.888281</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.331654</td>\n",
              "      <td>0.531438</td>\n",
              "      <td>0.884115</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>0.328133</td>\n",
              "      <td>0.534487</td>\n",
              "      <td>0.878906</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>0.326300</td>\n",
              "      <td>0.643905</td>\n",
              "      <td>0.827083</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>0.331411</td>\n",
              "      <td>0.762068</td>\n",
              "      <td>0.778385</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>0.332777</td>\n",
              "      <td>0.643141</td>\n",
              "      <td>0.861719</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.332272</td>\n",
              "      <td>0.712395</td>\n",
              "      <td>0.807292</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>0.332370</td>\n",
              "      <td>0.898704</td>\n",
              "      <td>0.664062</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>0.330683</td>\n",
              "      <td>0.749340</td>\n",
              "      <td>0.804688</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>0.328282</td>\n",
              "      <td>0.638020</td>\n",
              "      <td>0.817969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>0.326932</td>\n",
              "      <td>0.544888</td>\n",
              "      <td>0.869792</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>0.325561</td>\n",
              "      <td>1.067524</td>\n",
              "      <td>0.618229</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>0.323708</td>\n",
              "      <td>1.380604</td>\n",
              "      <td>0.639583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>0.321848</td>\n",
              "      <td>0.619158</td>\n",
              "      <td>0.832812</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>0.318995</td>\n",
              "      <td>0.560784</td>\n",
              "      <td>0.859896</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>0.316869</td>\n",
              "      <td>0.523966</td>\n",
              "      <td>0.884896</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.314658</td>\n",
              "      <td>0.515820</td>\n",
              "      <td>0.889583</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>0.312470</td>\n",
              "      <td>0.583705</td>\n",
              "      <td>0.871875</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>0.310451</td>\n",
              "      <td>0.547985</td>\n",
              "      <td>0.885677</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>0.308657</td>\n",
              "      <td>0.531006</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>0.307226</td>\n",
              "      <td>0.517945</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>0.306118</td>\n",
              "      <td>0.515399</td>\n",
              "      <td>0.886198</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>0.305105</td>\n",
              "      <td>0.512327</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>0.304214</td>\n",
              "      <td>0.505300</td>\n",
              "      <td>0.896875</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>0.303300</td>\n",
              "      <td>0.522472</td>\n",
              "      <td>0.895052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>0.302452</td>\n",
              "      <td>0.530054</td>\n",
              "      <td>0.894010</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.302076</td>\n",
              "      <td>0.501454</td>\n",
              "      <td>0.896094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>0.301527</td>\n",
              "      <td>0.506612</td>\n",
              "      <td>0.887760</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>0.301141</td>\n",
              "      <td>0.507737</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>0.300642</td>\n",
              "      <td>0.511656</td>\n",
              "      <td>0.898438</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>0.299867</td>\n",
              "      <td>0.514703</td>\n",
              "      <td>0.896615</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>0.299800</td>\n",
              "      <td>0.507033</td>\n",
              "      <td>0.888542</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>0.299190</td>\n",
              "      <td>0.508440</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>0.299209</td>\n",
              "      <td>0.501310</td>\n",
              "      <td>0.898698</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>0.299383</td>\n",
              "      <td>0.557772</td>\n",
              "      <td>0.882292</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>0.299254</td>\n",
              "      <td>0.498936</td>\n",
              "      <td>0.890625</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.298892</td>\n",
              "      <td>0.613309</td>\n",
              "      <td>0.857813</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>0.298720</td>\n",
              "      <td>0.551241</td>\n",
              "      <td>0.874219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>0.298721</td>\n",
              "      <td>0.495661</td>\n",
              "      <td>0.892969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>0.298657</td>\n",
              "      <td>0.527145</td>\n",
              "      <td>0.895052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>0.298691</td>\n",
              "      <td>0.502159</td>\n",
              "      <td>0.900781</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>0.298255</td>\n",
              "      <td>0.491913</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.297933</td>\n",
              "      <td>0.498505</td>\n",
              "      <td>0.893750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>0.297918</td>\n",
              "      <td>0.505898</td>\n",
              "      <td>0.896615</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>0.297422</td>\n",
              "      <td>0.512517</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>0.297041</td>\n",
              "      <td>0.506892</td>\n",
              "      <td>0.896094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.296904</td>\n",
              "      <td>0.491857</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>0.296697</td>\n",
              "      <td>0.495649</td>\n",
              "      <td>0.902604</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>0.296682</td>\n",
              "      <td>0.497246</td>\n",
              "      <td>0.895573</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>0.296738</td>\n",
              "      <td>0.494023</td>\n",
              "      <td>0.898177</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>0.296530</td>\n",
              "      <td>0.502794</td>\n",
              "      <td>0.897656</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>0.296497</td>\n",
              "      <td>0.497665</td>\n",
              "      <td>0.901302</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.296520</td>\n",
              "      <td>0.492288</td>\n",
              "      <td>0.898438</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>0.296242</td>\n",
              "      <td>0.494176</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>0.296320</td>\n",
              "      <td>0.515816</td>\n",
              "      <td>0.893490</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>0.296221</td>\n",
              "      <td>0.498954</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.296016</td>\n",
              "      <td>0.517740</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>0.295712</td>\n",
              "      <td>0.496718</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>0.295764</td>\n",
              "      <td>0.489261</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>0.295436</td>\n",
              "      <td>0.493807</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>0.295331</td>\n",
              "      <td>0.494276</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>0.295364</td>\n",
              "      <td>0.498418</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>0.295457</td>\n",
              "      <td>0.493238</td>\n",
              "      <td>0.897917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>0.295142</td>\n",
              "      <td>0.497525</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>0.294961</td>\n",
              "      <td>0.499958</td>\n",
              "      <td>0.898177</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>0.294845</td>\n",
              "      <td>0.493699</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.294629</td>\n",
              "      <td>0.490399</td>\n",
              "      <td>0.903646</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>0.294598</td>\n",
              "      <td>0.492483</td>\n",
              "      <td>0.903385</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>0.294449</td>\n",
              "      <td>0.495220</td>\n",
              "      <td>0.902083</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>0.294311</td>\n",
              "      <td>0.493128</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>0.294179</td>\n",
              "      <td>0.493102</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>0.294338</td>\n",
              "      <td>0.493508</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.294340</td>\n",
              "      <td>0.491752</td>\n",
              "      <td>0.902083</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>0.294445</td>\n",
              "      <td>0.491364</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>0.294667</td>\n",
              "      <td>0.492182</td>\n",
              "      <td>0.901563</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>0.294536</td>\n",
              "      <td>0.492485</td>\n",
              "      <td>0.901563</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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2AP0LbNtUTUQc/F/rTaDmyMI2Myu+j506mOUbd/Lq1o57m6xDDvJHbrrSZqcs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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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IrHvH7ZY34ImvwnvOglkf8VM3J+Lw3M3wx2/B1AvgvJu6LuGY9MLP/dnD7/2m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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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dQ0PQx6XL2mkK+RkMp4ePKtm45hAK+NwmtcycgvP4pJyCUzmVJacAVi4ilyiM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\nFEVRFBcVBUVRFMXl/wNUbiOoumQeGAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P_f921wka4O3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "68ce3055-f9ee-4313-bf66-8b6848421130"
      },
      "source": [
        "learn.metrics = metrics\n",
        "learn.load('stage_0')\n",
        "learn.fit_one_cycle(epochs, max_lr=4e-3, pct_start=pct_start, moms=(.95, .85) if warmup else (.95, .95),\n",
        "                    div_factor=25.0 if warmup else 1., wd=wd)\n",
        "learn.save('stage_1')\n",
        "learn.recorder.plot_lr()\n",
        "learn.recorder.plot_losses()\n",
        "learn.recorder.plot_metrics()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.848346</td>\n",
              "      <td>1.161249</td>\n",
              "      <td>0.532552</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>0.691616</td>\n",
              "      <td>1.098905</td>\n",
              "      <td>0.553125</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.648643</td>\n",
              "      <td>1.049506</td>\n",
              "      <td>0.551823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.606168</td>\n",
              "      <td>1.465748</td>\n",
              "      <td>0.333073</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.573156</td>\n",
              "      <td>0.744473</td>\n",
              "      <td>0.766146</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.553656</td>\n",
              "      <td>3.028317</td>\n",
              "      <td>0.333854</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>0.535069</td>\n",
              "      <td>4.280865</td>\n",
              "      <td>0.320312</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>0.518013</td>\n",
              "      <td>2.079392</td>\n",
              "      <td>0.618750</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>0.496766</td>\n",
              "      <td>1.542135</td>\n",
              "      <td>0.504167</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>0.482141</td>\n",
              "      <td>0.694181</td>\n",
              "      <td>0.802604</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>0.464025</td>\n",
              "      <td>1.587311</td>\n",
              "      <td>0.481510</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>0.449718</td>\n",
              "      <td>1.340443</td>\n",
              "      <td>0.611719</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>0.436093</td>\n",
              "      <td>1.069532</td>\n",
              "      <td>0.645573</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>0.423485</td>\n",
              "      <td>3.163556</td>\n",
              "      <td>0.550521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>0.410125</td>\n",
              "      <td>0.706474</td>\n",
              "      <td>0.830990</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.397335</td>\n",
              "      <td>0.689290</td>\n",
              "      <td>0.809115</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.388021</td>\n",
              "      <td>8.500474</td>\n",
              "      <td>0.250521</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.379958</td>\n",
              "      <td>0.672757</td>\n",
              "      <td>0.806510</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.371800</td>\n",
              "      <td>0.805087</td>\n",
              "      <td>0.749479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.364541</td>\n",
              "      <td>0.551345</td>\n",
              "      <td>0.876562</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.357270</td>\n",
              "      <td>0.549452</td>\n",
              "      <td>0.878125</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.350500</td>\n",
              "      <td>0.575999</td>\n",
              "      <td>0.873958</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.343867</td>\n",
              "      <td>0.528869</td>\n",
              "      <td>0.885156</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.338031</td>\n",
              "      <td>0.553662</td>\n",
              "      <td>0.876823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.333323</td>\n",
              "      <td>0.518551</td>\n",
              "      <td>0.888802</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.328977</td>\n",
              "      <td>0.558965</td>\n",
              "      <td>0.862240</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>0.325442</td>\n",
              "      <td>0.536481</td>\n",
              "      <td>0.884115</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>0.322837</td>\n",
              "      <td>0.562605</td>\n",
              "      <td>0.880990</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>0.319589</td>\n",
              "      <td>0.571391</td>\n",
              "      <td>0.882812</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>0.316586</td>\n",
              "      <td>0.518097</td>\n",
              "      <td>0.891667</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.314008</td>\n",
              "      <td>0.524354</td>\n",
              "      <td>0.886458</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>0.312170</td>\n",
              "      <td>0.505875</td>\n",
              "      <td>0.892969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>0.310070</td>\n",
              "      <td>0.504709</td>\n",
              "      <td>0.893229</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>0.308754</td>\n",
              "      <td>0.517910</td>\n",
              "      <td>0.890104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>0.307181</td>\n",
              "      <td>0.508728</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>0.305937</td>\n",
              "      <td>0.538237</td>\n",
              "      <td>0.873177</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>0.304804</td>\n",
              "      <td>0.505808</td>\n",
              "      <td>0.892969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>0.304315</td>\n",
              "      <td>0.505783</td>\n",
              "      <td>0.888802</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>0.303456</td>\n",
              "      <td>0.561529</td>\n",
              "      <td>0.882812</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>0.302471</td>\n",
              "      <td>0.507597</td>\n",
              "      <td>0.894792</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.301726</td>\n",
              "      <td>0.515306</td>\n",
              "      <td>0.890625</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>0.301175</td>\n",
              "      <td>0.496596</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>0.300422</td>\n",
              "      <td>0.503201</td>\n",
              "      <td>0.893229</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>0.299563</td>\n",
              "      <td>0.501729</td>\n",
              "      <td>0.894271</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>0.298858</td>\n",
              "      <td>0.506537</td>\n",
              "      <td>0.898698</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>0.299019</td>\n",
              "      <td>0.500441</td>\n",
              "      <td>0.892708</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>0.298540</td>\n",
              "      <td>0.515671</td>\n",
              "      <td>0.895052</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>0.298028</td>\n",
              "      <td>0.504168</td>\n",
              "      <td>0.897396</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>0.298379</td>\n",
              "      <td>0.555486</td>\n",
              "      <td>0.886719</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>0.298338</td>\n",
              "      <td>0.503792</td>\n",
              "      <td>0.899479</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.298159</td>\n",
              "      <td>0.557436</td>\n",
              "      <td>0.863021</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>0.298016</td>\n",
              "      <td>0.526290</td>\n",
              "      <td>0.895573</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>0.297909</td>\n",
              "      <td>0.507281</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>0.297732</td>\n",
              "      <td>0.498778</td>\n",
              "      <td>0.894792</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>0.297253</td>\n",
              "      <td>0.504327</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>0.297008</td>\n",
              "      <td>0.503590</td>\n",
              "      <td>0.898958</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>0.297016</td>\n",
              "      <td>0.515169</td>\n",
              "      <td>0.897135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>0.297007</td>\n",
              "      <td>0.501387</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>0.296843</td>\n",
              "      <td>0.498163</td>\n",
              "      <td>0.897135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>0.296849</td>\n",
              "      <td>0.496836</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.296543</td>\n",
              "      <td>0.499929</td>\n",
              "      <td>0.902344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>0.296265</td>\n",
              "      <td>0.504982</td>\n",
              "      <td>0.897917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>0.296342</td>\n",
              "      <td>0.497345</td>\n",
              "      <td>0.898698</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>0.296513</td>\n",
              "      <td>0.512017</td>\n",
              "      <td>0.897917</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>0.296297</td>\n",
              "      <td>0.507291</td>\n",
              "      <td>0.898958</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>0.297065</td>\n",
              "      <td>0.617584</td>\n",
              "      <td>0.846094</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.296845</td>\n",
              "      <td>0.603752</td>\n",
              "      <td>0.840104</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>0.296956</td>\n",
              "      <td>0.542668</td>\n",
              "      <td>0.889063</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>0.296570</td>\n",
              "      <td>0.735754</td>\n",
              "      <td>0.808594</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>0.296402</td>\n",
              "      <td>0.515533</td>\n",
              "      <td>0.897656</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.296171</td>\n",
              "      <td>0.501619</td>\n",
              "      <td>0.899219</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>0.296093</td>\n",
              "      <td>0.491486</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>0.296056</td>\n",
              "      <td>0.501349</td>\n",
              "      <td>0.896354</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>0.295936</td>\n",
              "      <td>0.517857</td>\n",
              "      <td>0.881510</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>0.295783</td>\n",
              "      <td>0.495170</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>0.295625</td>\n",
              "      <td>0.515946</td>\n",
              "      <td>0.897135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.295867</td>\n",
              "      <td>0.516514</td>\n",
              "      <td>0.882031</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>0.295791</td>\n",
              "      <td>0.489528</td>\n",
              "      <td>0.897396</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>0.295693</td>\n",
              "      <td>0.552577</td>\n",
              "      <td>0.885417</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>0.295760</td>\n",
              "      <td>0.496758</td>\n",
              "      <td>0.894531</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.295510</td>\n",
              "      <td>0.524753</td>\n",
              "      <td>0.892969</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>0.295560</td>\n",
              "      <td>0.492587</td>\n",
              "      <td>0.897135</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>0.295551</td>\n",
              "      <td>0.490345</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>0.295557</td>\n",
              "      <td>0.490355</td>\n",
              "      <td>0.901302</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>0.295872</td>\n",
              "      <td>0.486512</td>\n",
              "      <td>0.899740</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>0.295809</td>\n",
              "      <td>0.491470</td>\n",
              "      <td>0.900260</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>0.295617</td>\n",
              "      <td>0.493912</td>\n",
              "      <td>0.901563</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>0.295480</td>\n",
              "      <td>0.496162</td>\n",
              "      <td>0.903385</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>0.295433</td>\n",
              "      <td>0.500505</td>\n",
              "      <td>0.904167</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>0.295260</td>\n",
              "      <td>0.497074</td>\n",
              "      <td>0.901563</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.295519</td>\n",
              "      <td>0.493255</td>\n",
              "      <td>0.902083</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>0.295222</td>\n",
              "      <td>0.497656</td>\n",
              "      <td>0.902344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>0.294990</td>\n",
              "      <td>0.498030</td>\n",
              "      <td>0.902344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>0.295041</td>\n",
              "      <td>0.493419</td>\n",
              "      <td>0.902604</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>0.294808</td>\n",
              "      <td>0.494513</td>\n",
              "      <td>0.902344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>0.294681</td>\n",
              "      <td>0.494958</td>\n",
              "      <td>0.901042</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.294640</td>\n",
              "      <td>0.495791</td>\n",
              "      <td>0.902344</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>0.294559</td>\n",
              "      <td>0.495474</td>\n",
              "      <td>0.902083</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>0.294884</td>\n",
              "      <td>0.494563</td>\n",
              "      <td>0.901823</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>0.294939</td>\n",
              "      <td>0.494211</td>\n",
              "      <td>0.901302</td>\n",
              "      <td>00:01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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2AP0LbNtUTUQc/F/rTaDmyMI2Myu+j506mOUbd/Lq1o57m6xDDvJHbrrSZqcs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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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zp1Rw1ORyjp1WxeTK0ljbNmBhLz9kBX4CN/BloESn/27B/Hf6/+Q718OeP8OE\nWpi3zE8Rva8RNv3SHyTAX8Bl2kI/VLTxudQ3kNNNmARLPwBv+gv/qaRzH1ihP3ldezSUVPRev/OA\n7y12tMGEGv/6ZAK2PQmvPu6vKzyzISiNHZc6GB18w5/XeOJGaN0OVTPgpA/DiVcG1xFo9fuumj68\nA1Ciy5+kLCz25bTCYtixHtbcDM/c5Q+mSy+Hhiv9AeDJm+Dpn0DXfqhbAHNO9/MzTX4TTDmm9zUP\nDiWZ9DO1du6HqiP8fqIQXr2toAiKyvy/+Y8v9tdtuHglHPMX/v6eP8PqG/y/P/he/8cfS7X/ro/A\n8/fBVb+HKcf27SRk6mr3nYOCQpg0t/f6+5v93xrOt6+sGibO9p0L5/yJ4j/8q7/c6JIV/uJEtUf7\nTsfODf7ff9ZJ/lOJZKXAH4T2rgRbGvfx0p597GxpZ+OOVl5s2seOvQfZ35mgM+1gcER1GW8+ooop\nlSXMq6tkRk0Z06rKmFEzgek1ZZQWFR5iTxFyDtbdCm27/PTLyYQP3Rn1fq7+HU/54ZvP3u3/489Y\n4mftbHnN/wfbH8w3NKMeFrzLT93c+Jz/KSyGGUthZr0PsvJa//yOdT6AN92XmvI5U1mN/09vhf5b\nyO0t/f8OBUX+3Efrdv+4uCIVfJ1BL3rOmf5Txab74KVVWTZi/pPJpDn+PelsS3172Qp8WxKd/uDU\ndcAfDEsq/YHp4Bv+YOTSTlCWToSOFn+wXPR+f//5+1O/b2Gpv15x7Vx45VHfG+7a3/v1E2r8T2Gp\n32fn/uDgaT7kEp3BtY7T3sPyKf69KCr1bSwsTr2P4WsSXT4Ew98l0el/j9Jqf7uvEVq2924P5ocP\n/9VP/L9ppsaNsOaH/nc68tTU8pZt8N0G6D7oPxVWT/fzTlVMgfLJ/j070Ox/Wnf49zFUXO4/YRaV\nQdNmOLCn734r6mDmif71257014ie1QDP/8p/2py60H9iTe901M6D2Sf77RcU+Z/0T+JFpX6fBUXB\n+3TAv1eJTr/NZHfwnZcuSHT7jk13e/DJt9D/exWV+G0UlfrHybT33CVSV7grLPbrFU/w/0Yumfa8\nS7tNpl7T809i/m/TClJ/E5g/2L7rur7v1QAo8COSSDp2thxk654DbNrZynM7WnixaT9NbR3sam3v\nta4ZTK0qZWbNBGZOKg9uJzCzpoypVWVMrS5lckUphQU5LBc513fKh2QSmjb5P7CJswa/zdYdvodY\nUul/Eh1+TqHXX4R9u/3BJ7wge9URvhdeWu3D/+Dr/vmZJ/qfknIfLi8/4j+FhN9HKJ7gQ2j64tR+\nmzb77yJYgW97cbk/WDS/AG9w1zl6AAANIElEQVRs9f/RwzC3gtSBsKjUb6+ozP+H79znQ7isBmpm\n+96tS8C+Jti/G6a8GRb/pQ9t8CWvp2/zwbfkMqiYnGpTogtef9mH054t/r1p3+sPJolOfxArKffh\nEQZBYZEPvMppvk37Gv3vsa/Jv5dhuIfvo0umDgLh71Jc7h93HvDva+d+f/5n4mz/njvnw8wl/SeU\nmiMH/+/cuNEf1Fq3+wPJ/iYf3vub/XtdPsmHf9V0qDkKJh3l29640U8HnuiEumP9gIOq6UHImf8b\n2b7Of7JMdsFpn/BtLCr17/WTN/mBDNMX+3JT9Ux47XH/N7Jrgw/gZFfv+aVcMhXsoaIJUFzm37uC\n4lR5rqDY/xsUlaXCPZnwr+/u8P8G3R3+/SsIg72s93dkEl3++a6Dft9hgFvwySYMdSz1e4c565Kk\nDgbJ1MGhfDJ89DeD/3dCgZ8T+zq62d3azq7Wdra/cZDtew+mbvceZMfeg3Qler+3hQXGlMoS6qpK\n/UGgqjS472/rqsqYUllCVVkxVWVFFBeOuUFUIvFJdPuDQWHp4ctQY8hgAn9MzIc/EipLi6isq+x3\npE8y6Wja18HOlnYaW9vZ3dpOY2sHja3tNO3rYFdLO89sb6F5Xwf9fVWgrLigJ/yryoqpLivy90tT\ny6rCZT3P915WUjR+/vBlnCss8j/SL707MSkoMKZVlzGtuuyQ63Unkrx+oJPdrR007eugeV8nbe1d\ntLV3p9120xrc37H3YM+ycLjpoRQVGKVFBZQWF1JaVEBZcOt/CiktLuj1fGlRcFtcQFlRISVFBRQV\nGEWF4a3524KC4H4BhQVGcaEFt+mP01/jlxvBJ16sp9pkBmap5wqC+6St55/r/XoMCqzv8l7bTXt9\ngVnPvkTGIwX+CCsqLAjKO4c+MGTTlUiyL+OAkHmwONiVoKM7SUd3go6uZM/99i5/u6+jm+Z9wfPd\nyZ7lHd3JXiesx6L+DiRmfQ8W1usgFDxOPzj1s/0sSwe0XraXZl9vONsb2IEv6/YG8NL+35mBGc5x\neTh7Hk6HYKiv/MiZc7nslKOGvN+BUuCPYsWFBUyqKGFSRUks208mHZ2JJImkozvh6E4m6U46/5MI\n7ofLE6nliaSjK+lIpC8PHrvg3KUDnHM48OewcGnLIdnznOtZ5tLvB6+HYN2014bbItxH8Fz6er22\nS/bXu8NtN9hmNtkWZ1sz+8v7Lsy6vaz7GOBrB9iWbNvL+uLBr3Lo1w/j3OJw9j2cU5rD2e+UHA35\nVuBLvwoKjLLMCd1EZNTSGT0RkXEi1sA3s3eY2WYze8HMrolzXyIicmixBb6ZFQLfA84HFgIrzGxh\nXPsTEZFDi7OHfzLwgnPuJedcJ3AHcGGM+xMRkUOIM/BnAq+lPd4WLBMRkREw4idtzewqM1tjZmua\nmppGujkiImNWnIG/HZid9nhWsKwX59yNzrkG51xDXV1d5tMiIhKROAP/SeBNZjbXzEqAS4FfxLg/\nERE5hFhnyzSzC4DrgULgZufcNw6zfhPwyhB3NwXIMvl2XhpNbYXR1d7R1FYYXe0dTW2F0dXe4bT1\nKOfcgMojeTU98nCY2ZqBThE60kZTW2F0tXc0tRVGV3tHU1thdLU3V20d8ZO2IiKSGwp8EZFxYiwF\n/o0j3YBBGE1thdHV3tHUVhhd7R1NbYXR1d6ctHXM1PBFROTQxlIPX0REDmHUB34+zshpZjeb2W4z\nezZtWa2ZPWRmW4LbScFyM7PvBO3fYGb1OW7rbDNbZWYbzew5M/tUnre3zMyeMLOng/Z+LVg+18xW\nB+36SfDdD8ysNHj8QvD8nFy2N2hDoZk9ZWb3jYK2bjWzZ8xsvZmtCZbl699CjZndZWbPm9kmMzst\nj9t6bPCehj+tZvbpnLfXX9VndP7gx/e/CBwNlABPAwvzoF1nAfXAs2nLvglcE9y/BvjX4P4FwAP4\nq6OdCqzOcVunA/XB/Srgz/jZTfO1vQZUBveLgdVBO34KXBos/z5wdXD/48D3g/uXAj8Zgb+HzwK3\nAfcFj/O5rVuBKRnL8vVv4UfAR4P7JUBNvrY1o92FwC7gqFy3d0R+4QjfuNOAB9MefwH4wki3K2jL\nnIzA3wxMD+5PBzYH9/8LWJFtvRFq973AX4yG9gLlwDrgFPyXVooy/y6AB4HTgvtFwXqWwzbOAn4L\nnAPcF/wHzsu2BvvNFvh597cATAReznx/8rGtWdr+NuDRkWjvaC/pjKYZOac553YG93cB04L7efM7\nBCWEpfhec962NyiRrAd2Aw/hP+Xtdc51Z2lTT3uD51uAyTls7vXAPwDhFeEnk79tBX9p1l+b2Voz\nuypYlo9/C3OBJmBlUC77gZlV5GlbM10K3B7cz2l7R3vgj0rOH7LzaniUmVUCdwOfds61pj+Xb+11\nziWcc0vwveeTgfkj3KSszOxdwG7n3NqRbssgnOGcq8dfuOhvzeys9Cfz6G+hCF82vcE5txTYjy+J\n9MijtvYIzte8B7gz87lctHe0B/6AZuTME41mNh0guN0dLB/x38HMivFh/2Pn3M+CxXnb3pBzbi+w\nCl8WqTGzoixt6mlv8PxEoDlHTTwdeI+ZbcVfAOgc4Nt52lYAnHPbg9vdwD34A2o+/i1sA7Y551YH\nj+/CHwDysa3pzgfWOecag8c5be9oD/zRNCPnL4APBfc/hK+Vh8s/GJyVPxVoSfuIFzszM+CHwCbn\n3HWjoL11ZlYT3J+AP9+wCR/8y/tpb/h7LAd+F/SkYuec+4JzbpZzbg7+b/N3zrnL8rGtAGZWYWZV\n4X18rflZ8vBvwTm3C3jNzI4NFp0LbMzHtmZYQaqcE7Yrd+0diZMWEZ8AuQA/suRF4J9Guj1Bm24H\ndgJd+J7IR/C12N8CW4DfALXBuoa/9u+LwDNAQ47begb+Y+QGYH3wc0Eet3cx8FTQ3meBLwfLjwae\nAF7Af1wuDZaXBY9fCJ4/eoT+Js4mNUonL9satOvp4Oe58P9THv8tLAHWBH8LPwcm5WtbgzZU4D+x\nTUxbltP26pu2IiLjxGgv6YiIyAAp8EVExgkFvojIOKHAFxEZJxT4IiLjhAJfcsrMEsFsgU+b2Toz\ne8th1q8xs48PYLu/N7NRcf3SXDGzW8xs+eHXlPFCgS+5dtA5t8Q5dwJ+srv/e5j1a/CzSOaltG/M\niuQ9Bb6MpGrgDfBz+ZjZb4Ne/zNmdmGwzrXAvOBTwb8F6/5jsM7TZnZt2vYuNj9X/p/N7Mxg3UIz\n+zczezKYV/yvg+XTzezhYLvPhuunMz83/DeDfT1hZscEy28xs++b2Wrgm8Gc5j8Ptv+4mS1O+51W\nBq/fYGbvD5a/zcweC37XO4N5jDCza81fl2CDmX0rWHZx0L6nzezhw/xOZmb/Yf76EL8Bpkb5jyWj\nn3onkmsTzM90WYafDvacYHk7cJFzrtXMpgCPm9kv8BNiLXJ+sjTM7HzgQuAU59wBM6tN23aRc+5k\nM7sA+ApwHv5bzi3OuZPMrBR41Mx+DbwPPy3xN8ysED/VcjYtzrnjzeyD+Jkv3xUsnwW8xTmXMLPv\nAk85595rZucAt+K/Bfp/wtcHbZ8U/G5fAs5zzu03s38EPmtm3wMuAuY751w4fQTwZeDtzrntacv6\n+52WAsfir2cwDT/VwM0D+leRcUGBL7l2MC28TwNuNbNF+K+S/4v52RmT+Klgp2V5/XnASufcAQDn\n3Otpz4UTv63FX48A/Hwwi9Nq2ROBN+HnYbrZ/MRxP3fOre+nvben3f6/tOV3OucSwf0zgPcH7fmd\nmU02s+qgrZeGL3DOvWF+Bs2F+JAGf+GOx/BTIbcDPzR/Zaz7gpc9CtxiZj9N+/36+53OAm4P2rXD\nzH7Xz+8k45QCX0aMc+6xoMdbh5+/pw440TnXZX6GybJBbrIjuE2Q+ts24O+ccw9mrhwcXN6JD9Tr\nnHO3ZmtmP/f3D7JtPbsFHnLOrcjSnpPxk4AtBz4BnOOc+xszOyVo51ozO7G/3yn4ZCPSL9XwZcSY\n2Xz85d6a8b3U3UHYL8Nf/g2gDX/pxdBDwJVmVh5sI72kk82DwNVBTx4ze7P5WSGPAhqdczcBP8BP\nrZvNX6bdPtbPOo8AlwXbPxvY4/w1BR4C/jbt950EPA6cnnY+oCJoUyV+Uq37gc8AJwTPz3POrXbO\nfRl/wY/Z/f1OwMPAXwY1/unAssO8NzLOqIcvuRbW8MH3VD8U1MF/DPzSzJ7Bz4D4PIBzrtnMHjV/\nQfgHnHOfN7MlwBoz6wTuB754iP39AF/eWWe+htIEvBc/e+XnzawL2Ad8sJ/XTzKzDfhPD3165YGv\n4stDG4ADpKa7/Wfge0HbE8DXnHM/M7MrgNuD+jv4mn4bcK+ZlQXvy2eD5/7NzN4ULPstfibLDf38\nTvfgz4lsBF6l/wOUjFOaLVOkH0FZqcE5t2ek2yISBZV0RETGCfXwRUTGCfXwRUTGCQW+iMg4ocAX\nERknFPgiIuOEAl9EZJxQ4IuIjBP/H7/SzEhRqUsDAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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PJFPw9lMAKh6BVK6mEC1Y5sKLD2ErNBtjhphdVcpIpbPUxN3unwGMIHKWufAy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\nMTkWFIwxxuRYUDDGGJPz/wEyvVo0vX+AEAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M-WWpA3NMer_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "res = np.array([0.900260, 0.903906, 0.899479, 0.901563, 0.901302])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EU1oNpioOS0N",
        "colab_type": "code",
        "outputId": "524da247-5b07-4231-97a1-46903468eea0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "res.mean()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9013019999999999"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mDQhqwhFOTcs",
        "colab_type": "code",
        "outputId": "4ad84995-a02d-4a97-f5ef-13c65015d728",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "res.std()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0015005352378401474"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    }
  ]
}