From 98010585f8279f4c2672cfc593a1a6786dc95b92 Mon Sep 17 00:00:00 2001 From: Seowon Kim <58676931+swkim-sm@users.noreply.github.com> Date: Wed, 23 Jun 2021 01:26:54 +0900 Subject: [PATCH] Add files via upload MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 최종 제출 코드 --- Group1_submission.ipynb | 6105 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 6105 insertions(+) create mode 100644 Group1_submission.ipynb diff --git a/Group1_submission.ipynb b/Group1_submission.ipynb new file mode 100644 index 0000000..1700e7b --- /dev/null +++ b/Group1_submission.ipynb @@ -0,0 +1,6105 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "kernelspec": { + "language": "python", + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.7.10", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + }, + "colab": { + "name": "Group1_submission.ipynb", + "provenance": [], + "collapsed_sections": [] + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "RW7isHq--wkp" + }, + "source": [ + "# Group 1\n", + "\n", + "**공유드라이브 링크**\n", + "https://drive.google.com/drive/folders/1V9MqUQUltjv85btDuDi5nRTPyyI58YM9?usp=sharing\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "j468CYmg-41g" + }, + "source": [ + "## 1. Preparation" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VJxxygYjP6UU" + }, + "source": [ + "### (1) Import packages" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "BI25OF0W-iiJ", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "fa6a45b9-33b4-45b3-f9a0-705d867edc42" + }, + "source": [ + "import os\n", + "from typing import Tuple, List, Sequence, Callable\n", + "\n", + "import cv2\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import torch\n", + "\n", + "from torch import nn, Tensor\n", + "import torch.optim as optim\n", + "from torch.utils.data import Dataset, DataLoader, ConcatDataset\n", + "\n", + "!pip install -U git+https://github.com/albu/albumentations\n", + "import albumentations as A\n", + "from albumentations.pytorch import ToTensorV2\n", + "\n", + "import torch.nn.functional as F\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "import time" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting git+https://github.com/albu/albumentations\n", + " Cloning https://github.com/albu/albumentations to /tmp/pip-req-build-f9efg4fa\n", + " Running command git clone -q https://github.com/albu/albumentations /tmp/pip-req-build-f9efg4fa\n", + "Requirement already satisfied, skipping upgrade: numpy>=1.11.1 in /usr/local/lib/python3.7/dist-packages (from albumentations==1.0.0) (1.19.5)\n", + "Requirement already satisfied, skipping upgrade: scipy in /usr/local/lib/python3.7/dist-packages (from albumentations==1.0.0) (1.4.1)\n", + "Requirement already satisfied, skipping upgrade: scikit-image>=0.16.1 in /usr/local/lib/python3.7/dist-packages (from albumentations==1.0.0) (0.16.2)\n", + "Requirement already satisfied, skipping upgrade: PyYAML in /usr/local/lib/python3.7/dist-packages (from albumentations==1.0.0) (3.13)\n", + "Requirement already satisfied, skipping upgrade: opencv-python>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from albumentations==1.0.0) (4.1.2.30)\n", + "Requirement already satisfied, skipping upgrade: PyWavelets>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations==1.0.0) (1.1.1)\n", + "Requirement already satisfied, skipping upgrade: imageio>=2.3.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations==1.0.0) (2.4.1)\n", + "Requirement already satisfied, skipping upgrade: matplotlib!=3.0.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations==1.0.0) (3.2.2)\n", + "Requirement already satisfied, skipping upgrade: pillow>=4.3.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations==1.0.0) (7.1.2)\n", + "Requirement already satisfied, skipping upgrade: networkx>=2.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations==1.0.0) (2.5.1)\n", + "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations==1.0.0) (0.10.0)\n", + "Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations==1.0.0) (1.3.1)\n", + "Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations==1.0.0) (2.8.1)\n", + "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations==1.0.0) (2.4.7)\n", + "Requirement already satisfied, skipping upgrade: decorator<5,>=4.3 in /usr/local/lib/python3.7/dist-packages (from networkx>=2.0->scikit-image>=0.16.1->albumentations==1.0.0) (4.4.2)\n", + "Requirement already satisfied, skipping upgrade: six in /usr/local/lib/python3.7/dist-packages (from cycler>=0.10->matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations==1.0.0) (1.15.0)\n", + "Building wheels for collected packages: albumentations\n", + " Building wheel for albumentations (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for albumentations: filename=albumentations-1.0.0-cp37-none-any.whl size=98151 sha256=5add450067a68b5d8615faae59f0d900325eec771c50d24053f0d6fe1b0bff9b\n", + " Stored in directory: /tmp/pip-ephem-wheel-cache-tzp6oo_f/wheels/45/8b/e4/2837bbcf517d00732b8e394f8646f22b8723ac00993230188b\n", + "Successfully built albumentations\n", + "Installing collected packages: albumentations\n", + " Found existing installation: albumentations 0.1.12\n", + " Uninstalling albumentations-0.1.12:\n", + " Successfully uninstalled albumentations-0.1.12\n", + "Successfully installed albumentations-1.0.0\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qNr8XqRg_d4J" + }, + "source": [ + "### (2) Google Drive Colab 연결" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "YTdQUrh3_tmY", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "d4c72d5d-9ea1-4704-e829-e306fd76a84c" + }, + "source": [ + "from google.colab import drive\n", + "drive.mount('/content/drive/')" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Mounted at /content/drive/\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "JlqkBopSSZX0" + }, + "source": [ + "# share drive 를 사용할 경우, /content/drive/Shared drive\n", + "os.chdir('/content/drive/My Drive/statml_competition/')" + ], + "execution_count": 4, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nwrZciXP_OVJ" + }, + "source": [ + "### (3) Setting" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "vRFvwqZm-o2r", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "ae522be8-443a-413b-b062-0b9a9a9e1f0d" + }, + "source": [ + "if torch.cuda.is_available():\n", + " device = torch.device('cuda:0')\n", + "else:\n", + " device = torch.device('cpu')\n", + "\n", + "print('using device:', device)" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "stream", + "text": [ + "using device: cuda:0\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "x1mxBZfUxtFz" + }, + "source": [ + "device = \"cuda:0\"\n", + "dtype = torch.float\n", + "ltype = torch.long # entropy" + ], + "execution_count": 7, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sxG5KwkPAxwh" + }, + "source": [ + "## 1. 데이터 로드" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "W4JsNzBA_ZMo", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 196 + }, + "outputId": "6cb24331-c04e-4e85-e188-e4f2ad1bec22" + }, + "source": [ + "train_df = pd.read_csv('./face_image/face_images.csv')\n", + "train_df.head()" + ], + "execution_count": 8, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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pathrealfake
0./face_image/fake/JFH50GFJUL.jpg01
1./face_image/fake/0VPS5TI60G.jpg01
2./face_image/real/61911.jpg10
3./face_image/fake/APADHGXN31.jpg01
4./face_image/fake/SJO2UL69C2.jpg01
\n", + "
" + ], + "text/plain": [ + " path real fake\n", + "0 ./face_image/fake/JFH50GFJUL.jpg 0 1\n", + "1 ./face_image/fake/0VPS5TI60G.jpg 0 1\n", + "2 ./face_image/real/61911.jpg 1 0\n", + "3 ./face_image/fake/APADHGXN31.jpg 0 1\n", + "4 ./face_image/fake/SJO2UL69C2.jpg 0 1" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 8 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9EbVSNQAkn6n" + }, + "source": [ + " 파이토치에서는 **Dataset**과 **DataLoader**를 제공합니다. 파이토치의 Dataset 을 DataLoader 에 전달하여 미니 배치 학습 (batch_size), 데이터 셔플(shuffle=TRUE/FALSE), 병렬 처리(num_workers, colab 에서는 2까지만 가능)를 수행할 수 있습니다. Dataset을 상속받은 CustomDataset 을 정의하고, 이를 DataLoader에 전달하여 사용한다.\n", + "\n", + "```\n", + "class CustomDataset(torch.utils.data.Dataset): \n", + " def __init__(self):\n", + "\n", + " def __len__(self):\n", + "\n", + " def __getitem__(self, idx): \n", + "```\n", + "\n", + " * \\_\\_len\\_\\_ : 데이터셋의 길이 즉 n 리턴\n", + " * \\_\\_getitem\\_\\_ : idx 번째 데이터 리턴\n", + "\n", + "(참고 : https://wikidocs.net/57165 )" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "3pwAoFhcHxqB" + }, + "source": [ + "class FaceDataset(Dataset):\n", + " def __init__(self, image_label, transforms) :\n", + " self.df = image_label\n", + " self.transforms = transforms\n", + " \n", + " def __len__(self) -> int:\n", + " return self.df.shape[0]\n", + "\n", + " def __getitem__(self, index: int) -> Tuple[Tensor]:\n", + " assert index <= len(self), 'index range error' \n", + " \n", + " image_dir = self.df.iloc[index, ]['path']\n", + " image_id = self.df.iloc[index, ]['fake'].astype(np.int64)\n", + " \n", + " image = cv2.imread(image_dir, cv2.COLOR_BGR2RGB)\n", + " target = torch.as_tensor(image_id, dtype=torch.long)\n", + "\n", + " if self.transforms is not None :\n", + " image = self.transforms(image=image)['image']\n", + "\n", + " image = image/255.0\n", + " \n", + " return image, target\n", + "\n", + "class TestDataset(Dataset):\n", + " def __init__(self, image, transforms) :\n", + " self.image = image\n", + " self.transforms = transforms\n", + " \n", + " def __len__(self) -> int:\n", + " return len(self.image)\n", + "\n", + " def __getitem__(self, index: int) -> Tuple[Tensor]:\n", + " assert index <= len(self), 'index range error' \n", + " \n", + " image_name = self.image[index]\n", + " image_dir = './face_image/test_v1.1/' + image_name\n", + "\n", + " image = cv2.imread(image_dir, cv2.COLOR_BGR2RGB)\n", + " \n", + " if self.transforms is not None :\n", + " image = self.transforms(image=image)['image']\n", + " image = image/255.0\n", + "\n", + " return image_name, image" + ], + "execution_count": 9, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bgxoUvzPQ8C2" + }, + "source": [ + "## 이미지 어그멘테이션\n", + "( 참고 : https://github.com/albumentations-team/albumentations )" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "jAWBfl3Sx1zI", + "outputId": "79198bfa-8452-46c8-98a8-58e5a8615383" + }, + "source": [ + "pip install -U albumentations" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Requirement already up-to-date: albumentations in /usr/local/lib/python3.7/dist-packages (1.0.0)\n", + "Requirement already satisfied, skipping upgrade: scipy in /usr/local/lib/python3.7/dist-packages (from albumentations) (1.4.1)\n", + "Requirement already satisfied, skipping upgrade: scikit-image>=0.16.1 in /usr/local/lib/python3.7/dist-packages (from albumentations) (0.16.2)\n", + "Requirement already satisfied, skipping upgrade: opencv-python>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from albumentations) (4.1.2.30)\n", + "Requirement already satisfied, skipping upgrade: numpy>=1.11.1 in /usr/local/lib/python3.7/dist-packages (from albumentations) (1.19.5)\n", + "Requirement already satisfied, skipping upgrade: PyYAML in /usr/local/lib/python3.7/dist-packages (from albumentations) (3.13)\n", + "Requirement already satisfied, skipping upgrade: networkx>=2.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations) (2.5.1)\n", + "Requirement already satisfied, skipping upgrade: matplotlib!=3.0.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations) (3.2.2)\n", + "Requirement already satisfied, skipping upgrade: imageio>=2.3.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations) (2.4.1)\n", + "Requirement already satisfied, skipping upgrade: pillow>=4.3.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations) (7.1.2)\n", + "Requirement already satisfied, skipping upgrade: PyWavelets>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.16.1->albumentations) (1.1.1)\n", + "Requirement already satisfied, skipping upgrade: decorator<5,>=4.3 in /usr/local/lib/python3.7/dist-packages (from networkx>=2.0->scikit-image>=0.16.1->albumentations) (4.4.2)\n", + "Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations) (2.8.1)\n", + "Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations) (1.3.1)\n", + "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations) (2.4.7)\n", + "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations) (0.10.0)\n", + "Requirement already satisfied, skipping upgrade: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.1->matplotlib!=3.0.0,>=2.0.0->scikit-image>=0.16.1->albumentations) (1.15.0)\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "4a6jrMPCmN6S" + }, + "source": [ + "from albumentations import DualTransform, ImageOnlyTransform\n", + "\n", + "def isotropically_resize_image(img, size, interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC):\n", + " h, w = img.shape[:2]\n", + " if max(w, h) == size:\n", + " return img\n", + " if w > h:\n", + " scale = size / w\n", + " h = h * scale\n", + " w = size\n", + " else:\n", + " scale = size / h\n", + " w = w * scale\n", + " h = size\n", + " interpolation = interpolation_up if scale > 1 else interpolation_down\n", + " resized = cv2.resize(img, (int(w), int(h)), interpolation=interpolation)\n", + " return resized\n", + "\n", + "class IsotropicResize(DualTransform):\n", + " def __init__(self, max_side, interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC,\n", + " always_apply=False, p=1):\n", + " super(IsotropicResize, self).__init__(always_apply, p)\n", + " self.max_side = max_side\n", + " self.interpolation_down = interpolation_down\n", + " self.interpolation_up = interpolation_up\n", + "\n", + " def apply(self, img, interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC, **params):\n", + " return isotropically_resize_image(img, size=self.max_side, interpolation_down=interpolation_down,\n", + " interpolation_up=interpolation_up)\n", + "\n", + " def apply_to_mask(self, img, **params):\n", + " return self.apply(img, interpolation_down=cv2.INTER_NEAREST, interpolation_up=cv2.INTER_NEAREST, **params)\n", + "\n", + " def get_transform_init_args_names(self):\n", + " return (\"max_side\", \"interpolation_down\", \"interpolation_up\")\n" + ], + "execution_count": 11, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "NFo9XvK0LNu7", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "1b0e452e-ffcb-4257-8729-b2eccac78bff" + }, + "source": [ + "from albumentations import Compose, RandomBrightnessContrast, \\\n", + " HorizontalFlip, FancyPCA, HueSaturationValue, OneOf, ToGray, \\\n", + " ShiftScaleRotate, ImageCompression, PadIfNeeded, GaussNoise, GaussianBlur, Resize\n", + "\n", + "size = 128\n", + "transforms_tr = Compose([\n", + " ImageCompression(quality_lower=60, quality_upper=100, p=0.5),\n", + " GaussNoise(p=0.1),\n", + " GaussianBlur(blur_limit=3, p=0.05),\n", + " HorizontalFlip(),\n", + " OneOf([\n", + " IsotropicResize(max_side=size, interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC),\n", + " IsotropicResize(max_side=size, interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_LINEAR),\n", + " IsotropicResize(max_side=size, interpolation_down=cv2.INTER_LINEAR, interpolation_up=cv2.INTER_LINEAR),\n", + " ], p=1),\n", + " # Resize(128, 128),\n", + " PadIfNeeded(min_height=size, min_width=size, border_mode=cv2.BORDER_CONSTANT),\n", + " OneOf([RandomBrightnessContrast(), FancyPCA(), HueSaturationValue()], p=0.7),\n", + " ToGray(p=0.2),\n", + " ShiftScaleRotate(shift_limit=0.1, scale_limit=0.2, rotate_limit=10, border_mode=cv2.BORDER_CONSTANT, p=0.5),\n", + " ToTensorV2(), \n", + " ])\n", + "\n", + "transforms_val = Compose([\n", + " IsotropicResize(max_side=size, interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC),\n", + " PadIfNeeded(min_height=size, min_width=size, border_mode=cv2.BORDER_CONSTANT),\n", + " ToTensorV2(), \n", + " ])" + ], + "execution_count": 12, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.7/dist-packages/albumentations/augmentations/transforms.py:1852: UserWarning: blur_limit and sigma_limit minimum value can not be both equal to 0. blur_limit minimum value changed to 3.\n", + " \"blur_limit and sigma_limit minimum value can not be both equal to 0. \"\n" + ], + "name": "stderr" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vmDBxMuARo3N" + }, + "source": [ + "## 학습" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HhpVTPR8pbAZ" + }, + "source": [ + "* learning rate scheduler : 학습 속도를 줄여 학습 정도를 조정할 수 있다. 코드에서 사용한 StepLR 은 지정한 에폭 수(step_size) 마다 gamma 만큼 learning rate 를 감소시킨다. \n", + "* Ealry stopping : 더 이상의 학습을 통한 성능 향상이 없는 경우 학습을 멈추게 한다. 성능 향상은 validation set 에서의 loss 로 확인한다. \n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "faYSIAC6I5Dz", + "outputId": "1b00c982-ec89-4937-ff0c-4ed631bdfa65" + }, + "source": [ + "!pip install timm" + ], + "execution_count": 13, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting timm\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/ee/08/1ccaf8d516935666b7fa5f6aaddf157c66208ea0c93bb847ae09f166354f/timm-0.4.9-py3-none-any.whl (346kB)\n", + "\u001b[K |████████████████████████████████| 348kB 8.8MB/s \n", + "\u001b[?25hRequirement already satisfied: torchvision in /usr/local/lib/python3.7/dist-packages (from timm) (0.9.1+cu101)\n", + "Requirement already satisfied: torch>=1.4 in /usr/local/lib/python3.7/dist-packages (from timm) (1.8.1+cu101)\n", + "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torchvision->timm) (1.19.5)\n", + "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision->timm) (7.1.2)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.4->timm) (3.7.4.3)\n", + "Installing collected packages: timm\n", + "Successfully installed timm-0.4.9\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "o7KiPqdrJWYM", + "outputId": "46c8d838-b9aa-49b4-baea-c86b28add050" + }, + "source": [ + "!pip install torch_optimizer" + ], + "execution_count": 19, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting torch_optimizer\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/af/0f/bc49a0f714a1896b80f31db9ba82eebcb2bad9e0f5757184574f8ecfe2f1/torch_optimizer-0.1.0-py3-none-any.whl (72kB)\n", + "\r\u001b[K |████▌ | 10kB 21.3MB/s eta 0:00:01\r\u001b[K |█████████ | 20kB 25.9MB/s eta 0:00:01\r\u001b[K |█████████████▌ | 30kB 23.1MB/s eta 0:00:01\r\u001b[K |██████████████████ | 40kB 17.8MB/s eta 0:00:01\r\u001b[K |██████████████████████▋ | 51kB 9.1MB/s eta 0:00:01\r\u001b[K |███████████████████████████ | 61kB 10.6MB/s eta 0:00:01\r\u001b[K |███████████████████████████████▋| 71kB 9.6MB/s eta 0:00:01\r\u001b[K |████████████████████████████████| 81kB 6.4MB/s \n", + "\u001b[?25hCollecting pytorch-ranger>=0.1.1\n", + " Downloading https://files.pythonhosted.org/packages/0d/70/12256257d861bbc3e176130d25be1de085ce7a9e60594064888a950f2154/pytorch_ranger-0.1.1-py3-none-any.whl\n", + "Requirement already satisfied: torch>=1.1.0 in /usr/local/lib/python3.7/dist-packages (from torch_optimizer) (1.8.1+cu101)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.1.0->torch_optimizer) (3.7.4.3)\n", + "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torch>=1.1.0->torch_optimizer) (1.19.5)\n", + "Installing collected packages: pytorch-ranger, torch-optimizer\n", + "Successfully installed pytorch-ranger-0.1.1 torch-optimizer-0.1.0\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "t3JX6o1ixg6W" + }, + "source": [ + "### 모델 선언" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "VymbzVOeyTCL" + }, + "source": [ + "import random\n", + "def seed_everything(seed):\n", + " random.seed(seed)\n", + " np.random.seed(seed)\n", + " os.environ[\"PYTHONHASHSEED\"] = str(seed)\n", + " torch.manual_seed(seed)\n", + " torch.cuda.manual_seed(seed) # type: ignore\n", + " torch.backends.cudnn.deterministic = True # type: ignore\n", + " torch.backends.cudnn.benchmark = True # type: ignore" + ], + "execution_count": 20, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "dbHzCKuPw6qJ", + "outputId": "405dd45c-4a5f-441f-db09-4e5728474767" + }, + "source": [ + "from sklearn.model_selection import KFold\n", + "import timm\n", + "import torch_optimizer as optim\n", + "\n", + "num_epochs = 60\n", + "EARLY_STOPPING_EPOCH = 10\n", + "SEED = [42, 111, 555, 777, 888]\n", + "\n", + "best_models = []\n", + "s = 0\n", + "seed_num = len(SEED)\n", + "\n", + "for s in range(seed_num):\n", + " print(\">>>>>>>>>>>> start to train - xception <<<<<<<<<<<<\")\n", + " print(\"seed : \", SEED[s])\n", + " seed_everything(SEED[s])\n", + " \n", + " train, valid = train_test_split(train_df, test_size=0.2, random_state=SEED[s])\n", + "\n", + " model = timm.create_model('xception', pretrained=False)\n", + " num_ftrs = model.fc.in_features\n", + " # print(num_ftrs)\n", + " model.fc = nn.Sequential(\n", + " nn.Dropout(0.5),\n", + " nn.Linear(num_ftrs, 2)\n", + " )\n", + " model.to(device)\n", + "\n", + " # optimizer : RAdam / lr_scheduler : CosineAnnealing\n", + " optimizer = optim.RAdam(model.parameters(), lr=0.0015, betas=(0.9, 0.999), weight_decay=1e-4)\n", + " lr_sched = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=50)\n", + "\n", + " # cuda cache 초기화\n", + " torch.cuda.empty_cache()\n", + "\n", + " tr_dataset = FaceDataset(image_label=train, transforms=transforms_tr)\n", + " val_dataset = FaceDataset(image_label=valid, transforms=transforms_val)\n", + "\n", + " train_loader = DataLoader(tr_dataset, batch_size=64, shuffle=True, num_workers=8)\n", + " valid_loader = DataLoader(val_dataset, batch_size=64, shuffle=True, num_workers=8)\n", + "\n", + " # train 시작\n", + " valid_early_stop = 0\n", + "\n", + " valid_best_loss = float('inf')\n", + " since = time.time()\n", + "\n", + " final_train_loss = []\n", + " final_train_acc = []\n", + " final_valid_loss = []\n", + " final_valid_acc = []\n", + "\n", + " for e in range(num_epochs) :\n", + " print(\"seed : \", SEED[s])\n", + " print(f' ====================== epoch %d ======================' % (e+1) )\n", + " train_loss_list = []\n", + " train_acc_list = []\n", + "\n", + " # train\n", + " model.train()\n", + " for i, (images, targets) in enumerate(train_loader) : \n", + " optimizer.zero_grad()\n", + " \n", + " images = images.to(device, dtype)\n", + " targets = targets.to(device, ltype)\n", + " \n", + " scores = model(images)\n", + " _, preds = scores.max(dim=1)\n", + "\n", + " loss = F.cross_entropy(scores, targets)\n", + " loss.backward()\n", + " optimizer.step()\n", + " \n", + " correct = sum(targets == preds).cpu()\n", + " acc=(correct/64 * 100)\n", + "\n", + " train_loss_list.append(loss)\n", + " train_acc_list.append(acc)\n", + "\n", + " if i % 20 == 0 :\n", + " print(f'Iteration %3.d | Train Loss %.4f | Classifier Accuracy %2.2f' % (i, loss, acc))\n", + "\n", + " train_mean_loss = np.mean(train_loss_list, dtype=\"float64\")\n", + " train_mean_acc = np.mean(train_acc_list, dtype=\"float64\")\n", + "\n", + " final_train_loss.append(train_mean_loss)\n", + " final_train_acc.append(train_mean_acc)\n", + " \n", + " epoch_time = time.time() - since\n", + " since = time.time()\n", + "\n", + " print('')\n", + " print(f'[Summary] Elapsed time : %.0f m %.0f s' % (epoch_time // 60, epoch_time % 60))\n", + " print(f'Train Loss Mean %.4f | Accuracy %2.2f ' % (train_mean_loss, train_mean_acc) )\n", + "\n", + " # validation \n", + " valid_loss_list = []\n", + " valid_acc_list = []\n", + " model.eval()\n", + " for i, (images, targets) in enumerate(valid_loader) : \n", + " optimizer.zero_grad()\n", + " images = images.to(device=device, dtype=dtype)\n", + " targets = targets.to(device=device, dtype=ltype)\n", + "\n", + " with torch.no_grad():\n", + " scores = model(images)\n", + " loss = F.cross_entropy(scores, targets)\n", + " _, preds = scores.max(dim=1)\n", + " \n", + " correct = sum(targets == preds).cpu()\n", + " acc=(correct/64 * 100)\n", + "\n", + " valid_loss_list.append(loss)\n", + " valid_acc_list.append(acc)\n", + " \n", + " val_mean_loss = np.mean(valid_loss_list, dtype=\"float64\")\n", + " val_mean_acc = np.mean(valid_acc_list, dtype=\"float64\")\n", + "\n", + " final_valid_loss.append(val_mean_loss)\n", + " final_valid_acc.append(val_mean_acc)\n", + "\n", + " print(f'Valid Loss Mean %.4f | Accuracy %2.2f ' % (val_mean_loss, val_mean_acc) )\n", + " print('')\n", + "\n", + " if val_mean_loss < valid_best_loss:\n", + " valid_best_loss = val_mean_loss\n", + " valid_early_stop = 0\n", + " # new best model save (valid 기준)\n", + " best_model = model\n", + "\n", + " else:\n", + " # early stopping \n", + " valid_early_stop += 1\n", + " if valid_early_stop >= EARLY_STOPPING_EPOCH:\n", + " print(\"EARLY STOPPING!!\")\n", + " break\n", + "\n", + " lr_sched.step()\n", + " best_models.append(best_model)" + ], + "execution_count": 22, + "outputs": [ + { + "output_type": "stream", + "text": [ + ">>>>>>>>>>>> start to train - xception <<<<<<<<<<<<\n", + "seed : 42\n", + "seed : 42\n", + " ====================== epoch 1 ======================\n" + ], + "name": "stdout" + }, + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:477: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n", + " cpuset_checked))\n" + ], + "name": "stderr" + }, + { + "output_type": "stream", + "text": [ + "\u001b[1;30;43m스트리밍 출력 내용이 길어서 마지막 5000줄이 삭제되었습니다.\u001b[0m\n", + "Iteration 200 | Train Loss 0.1946 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.0680 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0730 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1229 | Accuracy 95.10 \n", + "Valid Loss Mean 0.2653 | Accuracy 90.50 \n", + "\n", + "seed : 42\n", + " ====================== epoch 28 ======================\n", + "Iteration 0 | Train Loss 0.1872 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.1173 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.0967 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0446 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1849 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.1368 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1611 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1300 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1120 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.2042 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.1230 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.0706 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0711 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1239 | Accuracy 95.40 \n", + "Valid Loss Mean 0.1346 | Accuracy 94.59 \n", + "\n", + "seed : 42\n", + " ====================== epoch 29 ======================\n", + "Iteration 0 | Train Loss 0.0761 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0773 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1131 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0968 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.1075 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0855 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.0838 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0660 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1859 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.1205 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1256 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1443 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.2631 | Classifier Accuracy 89.06\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1136 | Accuracy 95.51 \n", + "Valid Loss Mean 0.1524 | Accuracy 94.00 \n", + "\n", + "seed : 42\n", + " ====================== epoch 30 ======================\n", + "Iteration 0 | Train Loss 0.0739 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0591 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.2133 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.0913 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0611 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0622 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0571 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0755 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0646 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0558 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1262 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1254 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.1566 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1014 | Accuracy 96.17 \n", + "Valid Loss Mean 0.1940 | Accuracy 93.08 \n", + "\n", + "seed : 42\n", + " ====================== epoch 31 ======================\n", + "Iteration 0 | Train Loss 0.0782 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0586 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1045 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0372 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.2322 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.0750 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0942 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0617 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1061 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0700 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0842 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1306 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0502 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.0973 | Accuracy 96.23 \n", + "Valid Loss Mean 0.1555 | Accuracy 94.72 \n", + "\n", + "seed : 42\n", + " ====================== epoch 32 ======================\n", + "Iteration 0 | Train Loss 0.0330 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0148 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.2262 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.0320 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0545 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0843 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0710 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0784 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0883 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0725 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1127 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0583 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.1086 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.0949 | Accuracy 96.37 \n", + "Valid Loss Mean 0.1270 | Accuracy 94.79 \n", + "\n", + "seed : 42\n", + " ====================== epoch 33 ======================\n", + "Iteration 0 | Train Loss 0.1292 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.0440 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.2030 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.2147 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.0813 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0468 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0852 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0491 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0866 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1812 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1101 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.1232 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0783 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.0846 | Accuracy 96.77 \n", + "Valid Loss Mean 0.1392 | Accuracy 94.57 \n", + "\n", + "seed : 42\n", + " ====================== epoch 34 ======================\n", + "Iteration 0 | Train Loss 0.1106 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0622 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1183 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1225 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1518 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0335 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.1338 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.1270 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1264 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0404 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0489 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0106 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.2068 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.0737 | Accuracy 97.11 \n", + "Valid Loss Mean 0.1315 | Accuracy 95.34 \n", + "\n", + "seed : 42\n", + " ====================== epoch 35 ======================\n", + "Iteration 0 | Train Loss 0.0610 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0865 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0423 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1100 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.1137 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0748 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0750 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0322 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1697 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0257 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0727 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0283 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0858 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.0815 | Accuracy 96.97 \n", + "Valid Loss Mean 0.1322 | Accuracy 94.92 \n", + "\n", + "seed : 42\n", + " ====================== epoch 36 ======================\n", + "Iteration 0 | Train Loss 0.0403 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0295 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.1980 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.0186 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0396 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0221 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0549 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0974 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0348 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0432 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0141 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0307 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0194 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 42 s\n", + "Train Loss Mean 0.0702 | Accuracy 97.40 \n", + "Valid Loss Mean 0.1285 | Accuracy 95.09 \n", + "\n", + "seed : 42\n", + " ====================== epoch 37 ======================\n", + "Iteration 0 | Train Loss 0.0452 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0305 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0614 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0601 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0949 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0211 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0484 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0809 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1222 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0316 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0213 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0929 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0543 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0647 | Accuracy 97.57 \n", + "Valid Loss Mean 0.1487 | Accuracy 94.22 \n", + "\n", + "seed : 42\n", + " ====================== epoch 38 ======================\n", + "Iteration 0 | Train Loss 0.1531 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0450 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0091 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0832 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.0381 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0354 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0632 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0631 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0450 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0286 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0876 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0491 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0703 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0628 | Accuracy 97.66 \n", + "Valid Loss Mean 0.1439 | Accuracy 94.54 \n", + "\n", + "seed : 42\n", + " ====================== epoch 39 ======================\n", + "Iteration 0 | Train Loss 0.0519 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0250 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0316 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0172 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0397 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0283 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0724 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0347 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0679 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0944 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0168 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0316 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0631 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0563 | Accuracy 97.83 \n", + "Valid Loss Mean 0.1307 | Accuracy 95.41 \n", + "\n", + "seed : 42\n", + " ====================== epoch 40 ======================\n", + "Iteration 0 | Train Loss 0.1287 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0608 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0557 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0138 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0547 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0200 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0883 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0133 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0701 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0564 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0595 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0254 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.1214 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0564 | Accuracy 97.87 \n", + "Valid Loss Mean 0.1503 | Accuracy 94.94 \n", + "\n", + "seed : 42\n", + " ====================== epoch 41 ======================\n", + "Iteration 0 | Train Loss 0.0456 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0643 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.1026 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0174 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0347 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0382 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0467 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0217 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0274 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.2071 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0760 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0807 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0273 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0524 | Accuracy 98.00 \n", + "Valid Loss Mean 0.1349 | Accuracy 95.36 \n", + "\n", + "seed : 42\n", + " ====================== epoch 42 ======================\n", + "Iteration 0 | Train Loss 0.0564 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0544 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0311 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0225 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0305 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0575 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0051 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0672 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0188 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0563 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0659 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0840 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0502 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0508 | Accuracy 98.06 \n", + "Valid Loss Mean 0.1173 | Accuracy 96.03 \n", + "\n", + "seed : 42\n", + " ====================== epoch 43 ======================\n", + "Iteration 0 | Train Loss 0.0262 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0430 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0271 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0871 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0366 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0269 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0429 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0043 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0416 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0523 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0298 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0268 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0192 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0477 | Accuracy 98.09 \n", + "Valid Loss Mean 0.1180 | Accuracy 96.06 \n", + "\n", + "seed : 42\n", + " ====================== epoch 44 ======================\n", + "Iteration 0 | Train Loss 0.0236 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0188 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0388 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0531 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0132 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.1377 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.2043 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0508 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0409 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0253 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0300 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0202 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0058 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0459 | Accuracy 98.22 \n", + "Valid Loss Mean 0.1164 | Accuracy 96.18 \n", + "\n", + "seed : 42\n", + " ====================== epoch 45 ======================\n", + "Iteration 0 | Train Loss 0.0096 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0143 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0240 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0420 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1356 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1048 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0367 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0393 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0623 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0770 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0163 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0308 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0157 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0409 | Accuracy 98.44 \n", + "Valid Loss Mean 0.1281 | Accuracy 95.93 \n", + "\n", + "seed : 42\n", + " ====================== epoch 46 ======================\n", + "Iteration 0 | Train Loss 0.0245 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0138 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0827 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0166 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0630 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0317 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0571 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0894 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0195 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0172 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0295 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0147 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0485 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0426 | Accuracy 98.29 \n", + "Valid Loss Mean 0.1327 | Accuracy 95.98 \n", + "\n", + "seed : 42\n", + " ====================== epoch 47 ======================\n", + "Iteration 0 | Train Loss 0.1205 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0320 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0943 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0456 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0139 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0492 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0278 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1175 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0402 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0390 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0198 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0065 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0068 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0381 | Accuracy 98.43 \n", + "Valid Loss Mean 0.1315 | Accuracy 96.01 \n", + "\n", + "seed : 42\n", + " ====================== epoch 48 ======================\n", + "Iteration 0 | Train Loss 0.0338 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0445 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0420 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0100 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0553 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0640 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0737 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0676 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0198 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0276 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0160 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0793 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1183 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0354 | Accuracy 98.59 \n", + "Valid Loss Mean 0.1286 | Accuracy 95.96 \n", + "\n", + "seed : 42\n", + " ====================== epoch 49 ======================\n", + "Iteration 0 | Train Loss 0.0265 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0029 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0834 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0102 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0294 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0071 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0486 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0143 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0154 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0250 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0497 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0265 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0780 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0463 | Accuracy 98.38 \n", + "Valid Loss Mean 0.1263 | Accuracy 96.13 \n", + "\n", + "seed : 42\n", + " ====================== epoch 50 ======================\n", + "Iteration 0 | Train Loss 0.0685 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0359 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0175 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0183 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0480 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0424 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0172 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0121 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0100 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0333 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0746 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0187 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0215 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0398 | Accuracy 98.46 \n", + "Valid Loss Mean 0.1272 | Accuracy 96.11 \n", + "\n", + "seed : 42\n", + " ====================== epoch 51 ======================\n", + "Iteration 0 | Train Loss 0.0471 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0094 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0525 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0674 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0079 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.1450 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0540 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0265 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0228 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0073 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0343 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0292 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0269 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0431 | Accuracy 98.35 \n", + "Valid Loss Mean 0.1289 | Accuracy 96.16 \n", + "\n", + "seed : 42\n", + " ====================== epoch 52 ======================\n", + "Iteration 0 | Train Loss 0.0096 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0069 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0526 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0413 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0510 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0139 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.1840 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0862 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0651 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0605 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0867 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0792 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0035 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0431 | Accuracy 98.42 \n", + "Valid Loss Mean 0.1248 | Accuracy 96.06 \n", + "\n", + "seed : 42\n", + " ====================== epoch 53 ======================\n", + "Iteration 0 | Train Loss 0.0110 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0562 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0331 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0621 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0393 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0433 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0182 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0163 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0588 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0031 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0234 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0127 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0267 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0426 | Accuracy 98.43 \n", + "Valid Loss Mean 0.1263 | Accuracy 96.06 \n", + "\n", + "seed : 42\n", + " ====================== epoch 54 ======================\n", + "Iteration 0 | Train Loss 0.0341 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0441 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0112 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0516 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0060 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0206 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0429 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0170 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0433 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0379 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0119 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0389 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0615 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0386 | Accuracy 98.46 \n", + "Valid Loss Mean 0.1251 | Accuracy 96.08 \n", + "\n", + "EARLY STOPPING!!\n", + ">>>>>>>>>>>> start to train - xception <<<<<<<<<<<<\n", + "seed : 111\n", + "seed : 111\n", + " ====================== epoch 1 ======================\n", + "Iteration 0 | Train Loss 0.7217 | Classifier Accuracy 48.44\n", + "Iteration 20 | Train Loss 0.6421 | Classifier Accuracy 64.06\n", + "Iteration 40 | Train Loss 0.7129 | Classifier Accuracy 57.81\n", + "Iteration 60 | Train Loss 0.7676 | Classifier Accuracy 45.31\n", + "Iteration 80 | Train Loss 0.7026 | Classifier Accuracy 57.81\n", + "Iteration 100 | Train Loss 0.7159 | Classifier Accuracy 60.94\n", + "Iteration 120 | Train Loss 0.6414 | Classifier Accuracy 65.62\n", + "Iteration 140 | Train Loss 0.6709 | Classifier Accuracy 65.62\n", + "Iteration 160 | Train Loss 0.6557 | Classifier Accuracy 56.25\n", + "Iteration 180 | Train Loss 0.5635 | Classifier Accuracy 70.31\n", + "Iteration 200 | Train Loss 0.7052 | Classifier Accuracy 51.56\n", + "Iteration 220 | Train Loss 0.6918 | Classifier Accuracy 59.38\n", + "Iteration 240 | Train Loss 0.6184 | Classifier Accuracy 67.19\n", + "\n", + "[Summary] Elapsed time : 1 m 32 s\n", + "Train Loss Mean 0.6832 | Accuracy 58.19 \n", + "Valid Loss Mean 0.6985 | Accuracy 61.36 \n", + "\n", + "seed : 111\n", + " ====================== epoch 2 ======================\n", + "Iteration 0 | Train Loss 0.6487 | Classifier Accuracy 59.38\n", + "Iteration 20 | Train Loss 0.6385 | Classifier Accuracy 62.50\n", + "Iteration 40 | Train Loss 0.7216 | Classifier Accuracy 50.00\n", + "Iteration 60 | Train Loss 0.6663 | Classifier Accuracy 65.62\n", + "Iteration 80 | Train Loss 0.5146 | Classifier Accuracy 78.12\n", + "Iteration 100 | Train Loss 0.6226 | Classifier Accuracy 60.94\n", + "Iteration 120 | Train Loss 0.5921 | Classifier Accuracy 67.19\n", + "Iteration 140 | Train Loss 0.6306 | Classifier Accuracy 56.25\n", + "Iteration 160 | Train Loss 0.6253 | Classifier Accuracy 65.62\n", + "Iteration 180 | Train Loss 0.5416 | Classifier Accuracy 70.31\n", + "Iteration 200 | Train Loss 0.6949 | Classifier Accuracy 60.94\n", + "Iteration 220 | Train Loss 0.6195 | Classifier Accuracy 71.88\n", + "Iteration 240 | Train Loss 0.5114 | Classifier Accuracy 73.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.6237 | Accuracy 65.09 \n", + "Valid Loss Mean 0.5769 | Accuracy 69.97 \n", + "\n", + "seed : 111\n", + " ====================== epoch 3 ======================\n", + "Iteration 0 | Train Loss 0.5706 | Classifier Accuracy 65.62\n", + "Iteration 20 | Train Loss 0.6391 | Classifier Accuracy 65.62\n", + "Iteration 40 | Train Loss 0.5234 | Classifier Accuracy 73.44\n", + "Iteration 60 | Train Loss 0.6322 | Classifier Accuracy 62.50\n", + "Iteration 80 | Train Loss 0.5394 | Classifier Accuracy 73.44\n", + "Iteration 100 | Train Loss 0.4696 | Classifier Accuracy 82.81\n", + "Iteration 120 | Train Loss 0.5494 | Classifier Accuracy 71.88\n", + "Iteration 140 | Train Loss 0.6229 | Classifier Accuracy 67.19\n", + "Iteration 160 | Train Loss 0.5546 | Classifier Accuracy 67.19\n", + "Iteration 180 | Train Loss 0.5046 | Classifier Accuracy 76.56\n", + "Iteration 200 | Train Loss 0.6947 | Classifier Accuracy 64.06\n", + "Iteration 220 | Train Loss 0.5247 | Classifier Accuracy 70.31\n", + "Iteration 240 | Train Loss 0.6543 | Classifier Accuracy 67.19\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.5730 | Accuracy 70.33 \n", + "Valid Loss Mean 0.4812 | Accuracy 77.11 \n", + "\n", + "seed : 111\n", + " ====================== epoch 4 ======================\n", + "Iteration 0 | Train Loss 0.4318 | Classifier Accuracy 78.12\n", + "Iteration 20 | Train Loss 0.5433 | Classifier Accuracy 78.12\n", + "Iteration 40 | Train Loss 0.5857 | Classifier Accuracy 67.19\n", + "Iteration 60 | Train Loss 0.5138 | Classifier Accuracy 75.00\n", + "Iteration 80 | Train Loss 0.4695 | Classifier Accuracy 81.25\n", + "Iteration 100 | Train Loss 0.5310 | Classifier Accuracy 75.00\n", + "Iteration 120 | Train Loss 0.6570 | Classifier Accuracy 60.94\n", + "Iteration 140 | Train Loss 0.4861 | Classifier Accuracy 81.25\n", + "Iteration 160 | Train Loss 0.4558 | Classifier Accuracy 81.25\n", + "Iteration 180 | Train Loss 0.4994 | Classifier Accuracy 76.56\n", + "Iteration 200 | Train Loss 0.5009 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.4682 | Classifier Accuracy 76.56\n", + "Iteration 240 | Train Loss 0.5611 | Classifier Accuracy 75.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.5361 | Accuracy 73.26 \n", + "Valid Loss Mean 0.4814 | Accuracy 76.26 \n", + "\n", + "seed : 111\n", + " ====================== epoch 5 ======================\n", + "Iteration 0 | Train Loss 0.4743 | Classifier Accuracy 79.69\n", + "Iteration 20 | Train Loss 0.4545 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.4289 | Classifier Accuracy 81.25\n", + "Iteration 60 | Train Loss 0.4490 | Classifier Accuracy 82.81\n", + "Iteration 80 | Train Loss 0.5075 | Classifier Accuracy 68.75\n", + "Iteration 100 | Train Loss 0.4774 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.5829 | Classifier Accuracy 75.00\n", + "Iteration 140 | Train Loss 0.4797 | Classifier Accuracy 75.00\n", + "Iteration 160 | Train Loss 0.4569 | Classifier Accuracy 76.56\n", + "Iteration 180 | Train Loss 0.5087 | Classifier Accuracy 65.62\n", + "Iteration 200 | Train Loss 0.5710 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.4623 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.5271 | Classifier Accuracy 75.00\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.5008 | Accuracy 75.55 \n", + "Valid Loss Mean 0.4716 | Accuracy 78.05 \n", + "\n", + "seed : 111\n", + " ====================== epoch 6 ======================\n", + "Iteration 0 | Train Loss 0.3817 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.4925 | Classifier Accuracy 73.44\n", + "Iteration 40 | Train Loss 0.5283 | Classifier Accuracy 71.88\n", + "Iteration 60 | Train Loss 0.5536 | Classifier Accuracy 73.44\n", + "Iteration 80 | Train Loss 0.4551 | Classifier Accuracy 79.69\n", + "Iteration 100 | Train Loss 0.5108 | Classifier Accuracy 79.69\n", + "Iteration 120 | Train Loss 0.5305 | Classifier Accuracy 73.44\n", + "Iteration 140 | Train Loss 0.5226 | Classifier Accuracy 76.56\n", + "Iteration 160 | Train Loss 0.5018 | Classifier Accuracy 78.12\n", + "Iteration 180 | Train Loss 0.4015 | Classifier Accuracy 79.69\n", + "Iteration 200 | Train Loss 0.3377 | Classifier Accuracy 85.94\n", + "Iteration 220 | Train Loss 0.4963 | Classifier Accuracy 71.88\n", + "Iteration 240 | Train Loss 0.4948 | Classifier Accuracy 81.25\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.4688 | Accuracy 78.05 \n", + "Valid Loss Mean 0.4777 | Accuracy 76.34 \n", + "\n", + "seed : 111\n", + " ====================== epoch 7 ======================\n", + "Iteration 0 | Train Loss 0.5033 | Classifier Accuracy 75.00\n", + "Iteration 20 | Train Loss 0.4128 | Classifier Accuracy 81.25\n", + "Iteration 40 | Train Loss 0.4289 | Classifier Accuracy 85.94\n", + "Iteration 60 | Train Loss 0.4804 | Classifier Accuracy 78.12\n", + "Iteration 80 | Train Loss 0.4460 | Classifier Accuracy 81.25\n", + "Iteration 100 | Train Loss 0.4457 | Classifier Accuracy 79.69\n", + "Iteration 120 | Train Loss 0.4104 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.4263 | Classifier Accuracy 84.38\n", + "Iteration 160 | Train Loss 0.4168 | Classifier Accuracy 78.12\n", + "Iteration 180 | Train Loss 0.6023 | Classifier Accuracy 71.88\n", + "Iteration 200 | Train Loss 0.3963 | Classifier Accuracy 81.25\n", + "Iteration 220 | Train Loss 0.4479 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.4559 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.4353 | Accuracy 79.87 \n", + "Valid Loss Mean 0.3896 | Accuracy 82.34 \n", + "\n", + "seed : 111\n", + " ====================== epoch 8 ======================\n", + "Iteration 0 | Train Loss 0.3879 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.3277 | Classifier Accuracy 85.94\n", + "Iteration 40 | Train Loss 0.5137 | Classifier Accuracy 79.69\n", + "Iteration 60 | Train Loss 0.6223 | Classifier Accuracy 71.88\n", + "Iteration 80 | Train Loss 0.3757 | Classifier Accuracy 85.94\n", + "Iteration 100 | Train Loss 0.3834 | Classifier Accuracy 82.81\n", + "Iteration 120 | Train Loss 0.3853 | Classifier Accuracy 78.12\n", + "Iteration 140 | Train Loss 0.4211 | Classifier Accuracy 78.12\n", + "Iteration 160 | Train Loss 0.4861 | Classifier Accuracy 75.00\n", + "Iteration 180 | Train Loss 0.4483 | Classifier Accuracy 81.25\n", + "Iteration 200 | Train Loss 0.3744 | Classifier Accuracy 82.81\n", + "Iteration 220 | Train Loss 0.3212 | Classifier Accuracy 82.81\n", + "Iteration 240 | Train Loss 0.3397 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.4098 | Accuracy 81.22 \n", + "Valid Loss Mean 0.4159 | Accuracy 80.51 \n", + "\n", + "seed : 111\n", + " ====================== epoch 9 ======================\n", + "Iteration 0 | Train Loss 0.3345 | Classifier Accuracy 85.94\n", + "Iteration 20 | Train Loss 0.4369 | Classifier Accuracy 81.25\n", + "Iteration 40 | Train Loss 0.3539 | Classifier Accuracy 81.25\n", + "Iteration 60 | Train Loss 0.4100 | Classifier Accuracy 82.81\n", + "Iteration 80 | Train Loss 0.4186 | Classifier Accuracy 82.81\n", + "Iteration 100 | Train Loss 0.3588 | Classifier Accuracy 79.69\n", + "Iteration 120 | Train Loss 0.4437 | Classifier Accuracy 82.81\n", + "Iteration 140 | Train Loss 0.4099 | Classifier Accuracy 78.12\n", + "Iteration 160 | Train Loss 0.3443 | Classifier Accuracy 82.81\n", + "Iteration 180 | Train Loss 0.2816 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.3338 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.3940 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.2579 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3802 | Accuracy 83.06 \n", + "Valid Loss Mean 0.3800 | Accuracy 84.23 \n", + "\n", + "seed : 111\n", + " ====================== epoch 10 ======================\n", + "Iteration 0 | Train Loss 0.3549 | Classifier Accuracy 85.94\n", + "Iteration 20 | Train Loss 0.3634 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.3894 | Classifier Accuracy 79.69\n", + "Iteration 60 | Train Loss 0.3647 | Classifier Accuracy 85.94\n", + "Iteration 80 | Train Loss 0.1991 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.4631 | Classifier Accuracy 76.56\n", + "Iteration 120 | Train Loss 0.4687 | Classifier Accuracy 78.12\n", + "Iteration 140 | Train Loss 0.2018 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.4099 | Classifier Accuracy 81.25\n", + "Iteration 180 | Train Loss 0.3218 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.3498 | Classifier Accuracy 81.25\n", + "Iteration 220 | Train Loss 0.2972 | Classifier Accuracy 85.94\n", + "Iteration 240 | Train Loss 0.2411 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3496 | Accuracy 84.50 \n", + "Valid Loss Mean 0.6244 | Accuracy 76.96 \n", + "\n", + "seed : 111\n", + " ====================== epoch 11 ======================\n", + "Iteration 0 | Train Loss 0.2674 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.4654 | Classifier Accuracy 78.12\n", + "Iteration 40 | Train Loss 0.3022 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.3511 | Classifier Accuracy 82.81\n", + "Iteration 80 | Train Loss 0.3012 | Classifier Accuracy 85.94\n", + "Iteration 100 | Train Loss 0.4487 | Classifier Accuracy 81.25\n", + "Iteration 120 | Train Loss 0.2567 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.4062 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.2707 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.2910 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.2462 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.4916 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.3397 | Classifier Accuracy 81.25\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3246 | Accuracy 85.67 \n", + "Valid Loss Mean 0.2802 | Accuracy 87.30 \n", + "\n", + "seed : 111\n", + " ====================== epoch 12 ======================\n", + "Iteration 0 | Train Loss 0.3928 | Classifier Accuracy 82.81\n", + "Iteration 20 | Train Loss 0.3838 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.3368 | Classifier Accuracy 87.50\n", + "Iteration 60 | Train Loss 0.2806 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.6012 | Classifier Accuracy 75.00\n", + "Iteration 100 | Train Loss 0.3375 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.2831 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.3409 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.3055 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.2171 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.2907 | Classifier Accuracy 87.50\n", + "Iteration 220 | Train Loss 0.2983 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.3237 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3046 | Accuracy 87.08 \n", + "Valid Loss Mean 0.2646 | Accuracy 88.67 \n", + "\n", + "seed : 111\n", + " ====================== epoch 13 ======================\n", + "Iteration 0 | Train Loss 0.2827 | Classifier Accuracy 85.94\n", + "Iteration 20 | Train Loss 0.2200 | Classifier Accuracy 87.50\n", + "Iteration 40 | Train Loss 0.2798 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.3742 | Classifier Accuracy 82.81\n", + "Iteration 80 | Train Loss 0.1991 | Classifier Accuracy 87.50\n", + "Iteration 100 | Train Loss 0.3629 | Classifier Accuracy 81.25\n", + "Iteration 120 | Train Loss 0.3006 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.3084 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.2933 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.1766 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.2559 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.2118 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.3059 | Classifier Accuracy 89.06\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.2838 | Accuracy 87.86 \n", + "Valid Loss Mean 0.3182 | Accuracy 85.84 \n", + "\n", + "seed : 111\n", + " ====================== epoch 14 ======================\n", + "Iteration 0 | Train Loss 0.2307 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.2403 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.2564 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.1790 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.2038 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2135 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.4861 | Classifier Accuracy 78.12\n", + "Iteration 140 | Train Loss 0.1777 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.3610 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.1798 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.2363 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.2539 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.2420 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.2670 | Accuracy 88.83 \n", + "Valid Loss Mean 0.3361 | Accuracy 84.97 \n", + "\n", + "seed : 111\n", + " ====================== epoch 15 ======================\n", + "Iteration 0 | Train Loss 0.2730 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.1841 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.2942 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.4647 | Classifier Accuracy 79.69\n", + "Iteration 80 | Train Loss 0.1812 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.2798 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.2305 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.3555 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.1511 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.4105 | Classifier Accuracy 82.81\n", + "Iteration 200 | Train Loss 0.2117 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1232 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.2768 | Classifier Accuracy 89.06\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.2473 | Accuracy 89.64 \n", + "Valid Loss Mean 0.2292 | Accuracy 89.71 \n", + "\n", + "seed : 111\n", + " ====================== epoch 16 ======================\n", + "Iteration 0 | Train Loss 0.1806 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.3441 | Classifier Accuracy 82.81\n", + "Iteration 40 | Train Loss 0.1736 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2069 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.2503 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2717 | Classifier Accuracy 89.06\n", + "Iteration 120 | Train Loss 0.1998 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.1777 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.3206 | Classifier Accuracy 82.81\n", + "Iteration 180 | Train Loss 0.2670 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.2002 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.1349 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1701 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.2291 | Accuracy 90.59 \n", + "Valid Loss Mean 0.2293 | Accuracy 89.88 \n", + "\n", + "seed : 111\n", + " ====================== epoch 17 ======================\n", + "Iteration 0 | Train Loss 0.1871 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.2267 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.2122 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2401 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.2101 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.2188 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1300 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1558 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.2589 | Classifier Accuracy 87.50\n", + "Iteration 180 | Train Loss 0.2982 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.1987 | Classifier Accuracy 87.50\n", + "Iteration 220 | Train Loss 0.1773 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2155 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.2198 | Accuracy 90.83 \n", + "Valid Loss Mean 0.2068 | Accuracy 91.12 \n", + "\n", + "seed : 111\n", + " ====================== epoch 18 ======================\n", + "Iteration 0 | Train Loss 0.0992 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1599 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2986 | Classifier Accuracy 87.50\n", + "Iteration 60 | Train Loss 0.2077 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.2320 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.1296 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1758 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.3660 | Classifier Accuracy 84.38\n", + "Iteration 160 | Train Loss 0.2247 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.1772 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.1517 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.2400 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.3167 | Classifier Accuracy 84.38\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.2083 | Accuracy 91.46 \n", + "Valid Loss Mean 0.2667 | Accuracy 88.07 \n", + "\n", + "seed : 111\n", + " ====================== epoch 19 ======================\n", + "Iteration 0 | Train Loss 0.1812 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1316 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1642 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.2139 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.2628 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.2310 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1652 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.1377 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1171 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1900 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1539 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.2031 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.1867 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.1958 | Accuracy 92.25 \n", + "Valid Loss Mean 0.1847 | Accuracy 91.96 \n", + "\n", + "seed : 111\n", + " ====================== epoch 20 ======================\n", + "Iteration 0 | Train Loss 0.1782 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.1608 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.2415 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.0972 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1414 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2534 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1792 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.2767 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.1918 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1683 | Classifier Accuracy 89.06\n", + "Iteration 200 | Train Loss 0.1689 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.1840 | Classifier Accuracy 87.50\n", + "Iteration 240 | Train Loss 0.2709 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 42 s\n", + "Train Loss Mean 0.1882 | Accuracy 92.29 \n", + "Valid Loss Mean 0.1810 | Accuracy 92.09 \n", + "\n", + "seed : 111\n", + " ====================== epoch 21 ======================\n", + "Iteration 0 | Train Loss 0.1337 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.2366 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2210 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.1292 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1659 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.1206 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1314 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.1880 | Classifier Accuracy 92.19\n", + "Iteration 160 | Train Loss 0.1599 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.1187 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.2070 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.2487 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.0899 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1741 | Accuracy 93.18 \n", + "Valid Loss Mean 0.2447 | Accuracy 90.20 \n", + "\n", + "seed : 111\n", + " ====================== epoch 22 ======================\n", + "Iteration 0 | Train Loss 0.1397 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.1684 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1605 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.1621 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.1634 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1032 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1167 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1828 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1169 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1460 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.1693 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.1399 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1616 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1611 | Accuracy 93.59 \n", + "Valid Loss Mean 0.1653 | Accuracy 93.28 \n", + "\n", + "seed : 111\n", + " ====================== epoch 23 ======================\n", + "Iteration 0 | Train Loss 0.1399 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.1758 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.1382 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.1827 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.0702 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.2101 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1502 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1830 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.1366 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1944 | Classifier Accuracy 89.06\n", + "Iteration 200 | Train Loss 0.1419 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.2352 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.1551 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1477 | Accuracy 93.97 \n", + "Valid Loss Mean 0.2071 | Accuracy 91.99 \n", + "\n", + "seed : 111\n", + " ====================== epoch 24 ======================\n", + "Iteration 0 | Train Loss 0.1832 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1019 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.2101 | Classifier Accuracy 85.94\n", + "Iteration 60 | Train Loss 0.0638 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1649 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.1311 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.3134 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.2159 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.1702 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1536 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.1088 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1949 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.0880 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1478 | Accuracy 94.17 \n", + "Valid Loss Mean 0.2829 | Accuracy 88.67 \n", + "\n", + "seed : 111\n", + " ====================== epoch 25 ======================\n", + "Iteration 0 | Train Loss 0.0924 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0832 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1848 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.1249 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.2601 | Classifier Accuracy 87.50\n", + "Iteration 100 | Train Loss 0.1582 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1030 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0889 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.2496 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.1536 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1748 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.0804 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1299 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1398 | Accuracy 94.56 \n", + "Valid Loss Mean 0.1609 | Accuracy 93.25 \n", + "\n", + "seed : 111\n", + " ====================== epoch 26 ======================\n", + "Iteration 0 | Train Loss 0.0657 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.1048 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0781 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1437 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.1076 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1226 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0884 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.2296 | Classifier Accuracy 92.19\n", + "Iteration 160 | Train Loss 0.1205 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1577 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1072 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0674 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0387 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1246 | Accuracy 95.16 \n", + "Valid Loss Mean 0.1710 | Accuracy 92.46 \n", + "\n", + "seed : 111\n", + " ====================== epoch 27 ======================\n", + "Iteration 0 | Train Loss 0.0599 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1300 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0324 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.1232 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0681 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1293 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0926 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1584 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.0556 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.1157 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.1363 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.1251 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0976 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1173 | Accuracy 95.44 \n", + "Valid Loss Mean 0.1533 | Accuracy 93.70 \n", + "\n", + "seed : 111\n", + " ====================== epoch 28 ======================\n", + "Iteration 0 | Train Loss 0.1013 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1140 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0713 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0798 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0607 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1931 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1067 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0697 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1945 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.1443 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1575 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.1187 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.1599 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1145 | Accuracy 95.46 \n", + "Valid Loss Mean 0.1357 | Accuracy 94.15 \n", + "\n", + "seed : 111\n", + " ====================== epoch 29 ======================\n", + "Iteration 0 | Train Loss 0.0502 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0896 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0949 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0428 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0894 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1308 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1609 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1101 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0539 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.2361 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1381 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.1018 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0489 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1062 | Accuracy 96.02 \n", + "Valid Loss Mean 0.1348 | Accuracy 94.15 \n", + "\n", + "seed : 111\n", + " ====================== epoch 30 ======================\n", + "Iteration 0 | Train Loss 0.0821 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0857 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0697 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.2804 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.0965 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1585 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.1442 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0862 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0234 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0464 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0421 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1155 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1562 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0980 | Accuracy 96.48 \n", + "Valid Loss Mean 0.1308 | Accuracy 94.59 \n", + "\n", + "seed : 111\n", + " ====================== epoch 31 ======================\n", + "Iteration 0 | Train Loss 0.0624 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.1580 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0242 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0547 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1021 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0979 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0376 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0593 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0825 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1253 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.2090 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.1427 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0408 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0928 | Accuracy 96.49 \n", + "Valid Loss Mean 0.1286 | Accuracy 94.47 \n", + "\n", + "seed : 111\n", + " ====================== epoch 32 ======================\n", + "Iteration 0 | Train Loss 0.0930 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0645 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0944 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0639 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0622 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0485 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0406 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0537 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0950 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1117 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0754 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0717 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1081 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0910 | Accuracy 96.47 \n", + "Valid Loss Mean 0.1740 | Accuracy 93.75 \n", + "\n", + "seed : 111\n", + " ====================== epoch 33 ======================\n", + "Iteration 0 | Train Loss 0.0826 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1622 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.0181 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0315 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0678 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1385 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0201 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.1131 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1231 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0245 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.1310 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.2037 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1011 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0816 | Accuracy 96.79 \n", + "Valid Loss Mean 0.1410 | Accuracy 93.65 \n", + "\n", + "seed : 111\n", + " ====================== epoch 34 ======================\n", + "Iteration 0 | Train Loss 0.0627 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0907 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1074 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.0986 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0816 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1177 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0915 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0458 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0388 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0530 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1324 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0319 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0128 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0754 | Accuracy 97.15 \n", + "Valid Loss Mean 0.1236 | Accuracy 95.04 \n", + "\n", + "seed : 111\n", + " ====================== epoch 35 ======================\n", + "Iteration 0 | Train Loss 0.1001 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1220 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0835 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0847 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0568 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0915 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0801 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.1603 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.0736 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0458 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0295 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0866 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1119 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0684 | Accuracy 97.30 \n", + "Valid Loss Mean 0.1240 | Accuracy 95.21 \n", + "\n", + "seed : 111\n", + " ====================== epoch 36 ======================\n", + "Iteration 0 | Train Loss 0.0617 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0475 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0829 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0066 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0583 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0133 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0330 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0331 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0408 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0313 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0375 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0389 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0437 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0685 | Accuracy 97.39 \n", + "Valid Loss Mean 0.1562 | Accuracy 94.17 \n", + "\n", + "seed : 111\n", + " ====================== epoch 37 ======================\n", + "Iteration 0 | Train Loss 0.0729 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0727 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0391 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1460 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.0459 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0963 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0350 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0617 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0116 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.1977 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0525 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0194 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0658 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0613 | Accuracy 97.81 \n", + "Valid Loss Mean 0.1574 | Accuracy 94.15 \n", + "\n", + "seed : 111\n", + " ====================== epoch 38 ======================\n", + "Iteration 0 | Train Loss 0.0193 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0183 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0456 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0588 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0487 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0519 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0567 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0814 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0215 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0030 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0429 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0870 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0244 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0606 | Accuracy 97.70 \n", + "Valid Loss Mean 0.1227 | Accuracy 95.11 \n", + "\n", + "seed : 111\n", + " ====================== epoch 39 ======================\n", + "Iteration 0 | Train Loss 0.0946 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.0240 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1044 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0645 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0729 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0953 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0130 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0172 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0304 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0232 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0214 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0072 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0113 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0552 | Accuracy 97.97 \n", + "Valid Loss Mean 0.1183 | Accuracy 95.41 \n", + "\n", + "seed : 111\n", + " ====================== epoch 40 ======================\n", + "Iteration 0 | Train Loss 0.0522 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0598 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0341 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0169 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0390 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0286 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0202 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1331 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0265 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0079 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0380 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0348 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0840 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0513 | Accuracy 98.02 \n", + "Valid Loss Mean 0.1305 | Accuracy 94.97 \n", + "\n", + "seed : 111\n", + " ====================== epoch 41 ======================\n", + "Iteration 0 | Train Loss 0.0215 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0156 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0473 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0411 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0438 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0343 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0092 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0229 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0562 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0231 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0555 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0265 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0263 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0469 | Accuracy 98.31 \n", + "Valid Loss Mean 0.1279 | Accuracy 95.41 \n", + "\n", + "seed : 111\n", + " ====================== epoch 42 ======================\n", + "Iteration 0 | Train Loss 0.0502 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0768 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0112 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0395 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0333 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0206 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0132 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0491 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0370 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0041 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0505 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0530 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0982 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0504 | Accuracy 98.12 \n", + "Valid Loss Mean 0.1186 | Accuracy 95.71 \n", + "\n", + "seed : 111\n", + " ====================== epoch 43 ======================\n", + "Iteration 0 | Train Loss 0.0119 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0071 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0559 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0321 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0490 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0417 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0355 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0305 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0228 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0541 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0186 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0103 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.1809 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0459 | Accuracy 98.22 \n", + "Valid Loss Mean 0.1236 | Accuracy 95.63 \n", + "\n", + "seed : 111\n", + " ====================== epoch 44 ======================\n", + "Iteration 0 | Train Loss 0.0839 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0371 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0766 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.0323 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0496 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0428 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0057 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0356 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0171 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0347 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0193 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0039 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0925 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0417 | Accuracy 98.33 \n", + "Valid Loss Mean 0.1208 | Accuracy 95.63 \n", + "\n", + "seed : 111\n", + " ====================== epoch 45 ======================\n", + "Iteration 0 | Train Loss 0.0282 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0483 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0563 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0048 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0370 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0235 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0559 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0026 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0474 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0972 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0119 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0477 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0254 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0404 | Accuracy 98.35 \n", + "Valid Loss Mean 0.1139 | Accuracy 95.78 \n", + "\n", + "seed : 111\n", + " ====================== epoch 46 ======================\n", + "Iteration 0 | Train Loss 0.0236 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0111 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0334 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0307 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0799 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0319 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0589 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0182 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0112 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0271 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0181 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0124 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0245 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0398 | Accuracy 98.46 \n", + "Valid Loss Mean 0.1193 | Accuracy 95.81 \n", + "\n", + "seed : 111\n", + " ====================== epoch 47 ======================\n", + "Iteration 0 | Train Loss 0.0696 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0361 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0061 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0361 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0348 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1023 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0071 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0107 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0540 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0092 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0882 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0076 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0245 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0387 | Accuracy 98.51 \n", + "Valid Loss Mean 0.1141 | Accuracy 95.76 \n", + "\n", + "seed : 111\n", + " ====================== epoch 48 ======================\n", + "Iteration 0 | Train Loss 0.0952 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1237 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0064 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0170 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0012 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0899 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0228 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0075 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0220 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.1098 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0384 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0146 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0204 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0404 | Accuracy 98.58 \n", + "Valid Loss Mean 0.1146 | Accuracy 95.83 \n", + "\n", + "seed : 111\n", + " ====================== epoch 49 ======================\n", + "Iteration 0 | Train Loss 0.0191 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0894 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0609 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0829 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0509 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0351 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0097 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0075 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0508 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0836 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0033 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0276 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0195 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0377 | Accuracy 98.58 \n", + "Valid Loss Mean 0.1193 | Accuracy 95.68 \n", + "\n", + "seed : 111\n", + " ====================== epoch 50 ======================\n", + "Iteration 0 | Train Loss 0.0206 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0025 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0402 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0083 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0255 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0991 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0368 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0524 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1219 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0072 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0070 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0124 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0392 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0418 | Accuracy 98.52 \n", + "Valid Loss Mean 0.1139 | Accuracy 95.76 \n", + "\n", + "seed : 111\n", + " ====================== epoch 51 ======================\n", + "Iteration 0 | Train Loss 0.0251 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0281 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0543 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0220 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0227 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0384 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0166 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0446 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0179 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0547 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0579 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0032 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.1066 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0386 | Accuracy 98.51 \n", + "Valid Loss Mean 0.1168 | Accuracy 95.78 \n", + "\n", + "seed : 111\n", + " ====================== epoch 52 ======================\n", + "Iteration 0 | Train Loss 0.0377 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0559 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0061 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0527 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0305 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0095 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0357 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0068 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0126 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0158 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0114 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0269 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0341 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0383 | Accuracy 98.48 \n", + "Valid Loss Mean 0.1143 | Accuracy 95.71 \n", + "\n", + "seed : 111\n", + " ====================== epoch 53 ======================\n", + "Iteration 0 | Train Loss 0.0070 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0292 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0206 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0781 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0082 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0433 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0468 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0065 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0920 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0330 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0385 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0105 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0070 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0365 | Accuracy 98.71 \n", + "Valid Loss Mean 0.1152 | Accuracy 95.66 \n", + "\n", + "seed : 111\n", + " ====================== epoch 54 ======================\n", + "Iteration 0 | Train Loss 0.0024 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0430 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0198 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0265 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0149 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0298 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0268 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0263 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0038 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0085 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0436 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1272 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0181 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 43 s\n", + "Train Loss Mean 0.0357 | Accuracy 98.74 \n", + "Valid Loss Mean 0.1129 | Accuracy 95.78 \n", + "\n", + "seed : 111\n", + " ====================== epoch 55 ======================\n", + "Iteration 0 | Train Loss 0.0734 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0309 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0325 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0094 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0402 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0585 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0189 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0067 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0411 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0305 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0275 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0033 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0086 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0375 | Accuracy 98.54 \n", + "Valid Loss Mean 0.1129 | Accuracy 95.81 \n", + "\n", + "seed : 111\n", + " ====================== epoch 56 ======================\n", + "Iteration 0 | Train Loss 0.0234 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0314 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0229 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0080 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0445 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0615 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0407 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0788 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0081 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0379 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0244 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0160 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0142 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0343 | Accuracy 98.81 \n", + "Valid Loss Mean 0.1126 | Accuracy 95.68 \n", + "\n", + "seed : 111\n", + " ====================== epoch 57 ======================\n", + "Iteration 0 | Train Loss 0.0094 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0010 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0148 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0019 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0064 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0391 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0102 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0066 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0118 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.1152 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0066 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0162 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0795 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0338 | Accuracy 98.72 \n", + "Valid Loss Mean 0.1189 | Accuracy 95.54 \n", + "\n", + "seed : 111\n", + " ====================== epoch 58 ======================\n", + "Iteration 0 | Train Loss 0.0107 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0040 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0329 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0152 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0388 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0168 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0276 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0162 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0503 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0295 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0710 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0150 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0345 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.0342 | Accuracy 98.69 \n", + "Valid Loss Mean 0.1135 | Accuracy 95.86 \n", + "\n", + "seed : 111\n", + " ====================== epoch 59 ======================\n", + "Iteration 0 | Train Loss 0.0026 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0220 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0328 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0204 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0571 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0525 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.1165 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0231 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0764 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0383 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0292 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0087 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0421 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0421 | Accuracy 98.52 \n", + "Valid Loss Mean 0.1073 | Accuracy 95.91 \n", + "\n", + "seed : 111\n", + " ====================== epoch 60 ======================\n", + "Iteration 0 | Train Loss 0.0674 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0385 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0553 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0138 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0189 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0181 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0144 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0047 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0673 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0336 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0056 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0734 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1077 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0391 | Accuracy 98.52 \n", + "Valid Loss Mean 0.1046 | Accuracy 96.06 \n", + "\n", + ">>>>>>>>>>>> start to train - xception <<<<<<<<<<<<\n", + "seed : 555\n", + "seed : 555\n", + " ====================== epoch 1 ======================\n", + "Iteration 0 | Train Loss 0.6939 | Classifier Accuracy 56.25\n", + "Iteration 20 | Train Loss 0.6728 | Classifier Accuracy 59.38\n", + "Iteration 40 | Train Loss 0.7082 | Classifier Accuracy 51.56\n", + "Iteration 60 | Train Loss 0.7756 | Classifier Accuracy 53.12\n", + "Iteration 80 | Train Loss 0.6505 | Classifier Accuracy 65.62\n", + "Iteration 100 | Train Loss 0.6739 | Classifier Accuracy 59.38\n", + "Iteration 120 | Train Loss 0.6736 | Classifier Accuracy 65.62\n", + "Iteration 140 | Train Loss 0.6025 | Classifier Accuracy 68.75\n", + "Iteration 160 | Train Loss 0.6538 | Classifier Accuracy 62.50\n", + "Iteration 180 | Train Loss 0.6098 | Classifier Accuracy 68.75\n", + "Iteration 200 | Train Loss 0.6816 | Classifier Accuracy 54.69\n", + "Iteration 220 | Train Loss 0.7388 | Classifier Accuracy 64.06\n", + "Iteration 240 | Train Loss 0.7146 | Classifier Accuracy 56.25\n", + "\n", + "[Summary] Elapsed time : 1 m 32 s\n", + "Train Loss Mean 0.6819 | Accuracy 58.43 \n", + "Valid Loss Mean 1.0479 | Accuracy 52.36 \n", + "\n", + "seed : 555\n", + " ====================== epoch 2 ======================\n", + "Iteration 0 | Train Loss 0.5692 | Classifier Accuracy 73.44\n", + "Iteration 20 | Train Loss 0.6875 | Classifier Accuracy 62.50\n", + "Iteration 40 | Train Loss 0.6311 | Classifier Accuracy 64.06\n", + "Iteration 60 | Train Loss 0.6657 | Classifier Accuracy 59.38\n", + "Iteration 80 | Train Loss 0.5631 | Classifier Accuracy 76.56\n", + "Iteration 100 | Train Loss 0.5380 | Classifier Accuracy 75.00\n", + "Iteration 120 | Train Loss 0.6233 | Classifier Accuracy 64.06\n", + "Iteration 140 | Train Loss 0.5987 | Classifier Accuracy 65.62\n", + "Iteration 160 | Train Loss 0.6670 | Classifier Accuracy 64.06\n", + "Iteration 180 | Train Loss 0.6509 | Classifier Accuracy 62.50\n", + "Iteration 200 | Train Loss 0.5587 | Classifier Accuracy 73.44\n", + "Iteration 220 | Train Loss 0.5808 | Classifier Accuracy 70.31\n", + "Iteration 240 | Train Loss 0.6439 | Classifier Accuracy 62.50\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.6278 | Accuracy 66.30 \n", + "Valid Loss Mean 0.6277 | Accuracy 68.63 \n", + "\n", + "seed : 555\n", + " ====================== epoch 3 ======================\n", + "Iteration 0 | Train Loss 0.5801 | Classifier Accuracy 71.88\n", + "Iteration 20 | Train Loss 0.5731 | Classifier Accuracy 68.75\n", + "Iteration 40 | Train Loss 0.4476 | Classifier Accuracy 76.56\n", + "Iteration 60 | Train Loss 0.5985 | Classifier Accuracy 67.19\n", + "Iteration 80 | Train Loss 0.6016 | Classifier Accuracy 68.75\n", + "Iteration 100 | Train Loss 0.7288 | Classifier Accuracy 70.31\n", + "Iteration 120 | Train Loss 0.6001 | Classifier Accuracy 71.88\n", + "Iteration 140 | Train Loss 0.4631 | Classifier Accuracy 75.00\n", + "Iteration 160 | Train Loss 0.4443 | Classifier Accuracy 78.12\n", + "Iteration 180 | Train Loss 0.5551 | Classifier Accuracy 71.88\n", + "Iteration 200 | Train Loss 0.5840 | Classifier Accuracy 70.31\n", + "Iteration 220 | Train Loss 0.5600 | Classifier Accuracy 73.44\n", + "Iteration 240 | Train Loss 0.5309 | Classifier Accuracy 81.25\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.5673 | Accuracy 71.07 \n", + "Valid Loss Mean 0.5274 | Accuracy 74.16 \n", + "\n", + "seed : 555\n", + " ====================== epoch 4 ======================\n", + "Iteration 0 | Train Loss 0.4826 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.5428 | Classifier Accuracy 70.31\n", + "Iteration 40 | Train Loss 0.5356 | Classifier Accuracy 76.56\n", + "Iteration 60 | Train Loss 0.4874 | Classifier Accuracy 75.00\n", + "Iteration 80 | Train Loss 0.5186 | Classifier Accuracy 76.56\n", + "Iteration 100 | Train Loss 0.4946 | Classifier Accuracy 73.44\n", + "Iteration 120 | Train Loss 0.5054 | Classifier Accuracy 78.12\n", + "Iteration 140 | Train Loss 0.4735 | Classifier Accuracy 75.00\n", + "Iteration 160 | Train Loss 0.6255 | Classifier Accuracy 67.19\n", + "Iteration 180 | Train Loss 0.5483 | Classifier Accuracy 71.88\n", + "Iteration 200 | Train Loss 0.5578 | Classifier Accuracy 67.19\n", + "Iteration 220 | Train Loss 0.5002 | Classifier Accuracy 73.44\n", + "Iteration 240 | Train Loss 0.4236 | Classifier Accuracy 76.56\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.5335 | Accuracy 73.36 \n", + "Valid Loss Mean 0.8697 | Accuracy 54.17 \n", + "\n", + "seed : 555\n", + " ====================== epoch 5 ======================\n", + "Iteration 0 | Train Loss 0.5111 | Classifier Accuracy 73.44\n", + "Iteration 20 | Train Loss 0.5540 | Classifier Accuracy 71.88\n", + "Iteration 40 | Train Loss 0.6050 | Classifier Accuracy 70.31\n", + "Iteration 60 | Train Loss 0.5912 | Classifier Accuracy 73.44\n", + "Iteration 80 | Train Loss 0.4285 | Classifier Accuracy 76.56\n", + "Iteration 100 | Train Loss 0.6333 | Classifier Accuracy 68.75\n", + "Iteration 120 | Train Loss 0.6079 | Classifier Accuracy 68.75\n", + "Iteration 140 | Train Loss 0.3218 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.4881 | Classifier Accuracy 76.56\n", + "Iteration 180 | Train Loss 0.4830 | Classifier Accuracy 78.12\n", + "Iteration 200 | Train Loss 0.5317 | Classifier Accuracy 71.88\n", + "Iteration 220 | Train Loss 0.5875 | Classifier Accuracy 71.88\n", + "Iteration 240 | Train Loss 0.5783 | Classifier Accuracy 73.44\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.5051 | Accuracy 75.41 \n", + "Valid Loss Mean 0.4918 | Accuracy 77.16 \n", + "\n", + "seed : 555\n", + " ====================== epoch 6 ======================\n", + "Iteration 0 | Train Loss 0.4707 | Classifier Accuracy 78.12\n", + "Iteration 20 | Train Loss 0.4808 | Classifier Accuracy 73.44\n", + "Iteration 40 | Train Loss 0.4395 | Classifier Accuracy 76.56\n", + "Iteration 60 | Train Loss 0.5496 | Classifier Accuracy 70.31\n", + "Iteration 80 | Train Loss 0.4467 | Classifier Accuracy 76.56\n", + "Iteration 100 | Train Loss 0.4274 | Classifier Accuracy 85.94\n", + "Iteration 120 | Train Loss 0.4604 | Classifier Accuracy 78.12\n", + "Iteration 140 | Train Loss 0.4488 | Classifier Accuracy 79.69\n", + "Iteration 160 | Train Loss 0.4931 | Classifier Accuracy 78.12\n", + "Iteration 180 | Train Loss 0.5733 | Classifier Accuracy 70.31\n", + "Iteration 200 | Train Loss 0.2758 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.4067 | Classifier Accuracy 78.12\n", + "Iteration 240 | Train Loss 0.4712 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.4772 | Accuracy 77.42 \n", + "Valid Loss Mean 0.4640 | Accuracy 78.37 \n", + "\n", + "seed : 555\n", + " ====================== epoch 7 ======================\n", + "Iteration 0 | Train Loss 0.4428 | Classifier Accuracy 75.00\n", + "Iteration 20 | Train Loss 0.4471 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.4288 | Classifier Accuracy 78.12\n", + "Iteration 60 | Train Loss 0.4206 | Classifier Accuracy 82.81\n", + "Iteration 80 | Train Loss 0.4705 | Classifier Accuracy 78.12\n", + "Iteration 100 | Train Loss 0.3198 | Classifier Accuracy 82.81\n", + "Iteration 120 | Train Loss 0.4292 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.3802 | Classifier Accuracy 85.94\n", + "Iteration 160 | Train Loss 0.4455 | Classifier Accuracy 79.69\n", + "Iteration 180 | Train Loss 0.5249 | Classifier Accuracy 68.75\n", + "Iteration 200 | Train Loss 0.5920 | Classifier Accuracy 75.00\n", + "Iteration 220 | Train Loss 0.4284 | Classifier Accuracy 82.81\n", + "Iteration 240 | Train Loss 0.4421 | Classifier Accuracy 76.56\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.4401 | Accuracy 79.69 \n", + "Valid Loss Mean 0.3905 | Accuracy 82.29 \n", + "\n", + "seed : 555\n", + " ====================== epoch 8 ======================\n", + "Iteration 0 | Train Loss 0.5154 | Classifier Accuracy 79.69\n", + "Iteration 20 | Train Loss 0.5285 | Classifier Accuracy 75.00\n", + "Iteration 40 | Train Loss 0.3644 | Classifier Accuracy 84.38\n", + "Iteration 60 | Train Loss 0.5338 | Classifier Accuracy 78.12\n", + "Iteration 80 | Train Loss 0.2760 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.4799 | Classifier Accuracy 76.56\n", + "Iteration 120 | Train Loss 0.4449 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.4890 | Classifier Accuracy 79.69\n", + "Iteration 160 | Train Loss 0.4372 | Classifier Accuracy 81.25\n", + "Iteration 180 | Train Loss 0.4209 | Classifier Accuracy 78.12\n", + "Iteration 200 | Train Loss 0.3373 | Classifier Accuracy 84.38\n", + "Iteration 220 | Train Loss 0.3731 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.4023 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.4105 | Accuracy 81.36 \n", + "Valid Loss Mean 0.4169 | Accuracy 80.23 \n", + "\n", + "seed : 555\n", + " ====================== epoch 9 ======================\n", + "Iteration 0 | Train Loss 0.5639 | Classifier Accuracy 79.69\n", + "Iteration 20 | Train Loss 0.3880 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.5262 | Classifier Accuracy 76.56\n", + "Iteration 60 | Train Loss 0.3573 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.3305 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.3297 | Classifier Accuracy 89.06\n", + "Iteration 120 | Train Loss 0.3921 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.4427 | Classifier Accuracy 75.00\n", + "Iteration 160 | Train Loss 0.3914 | Classifier Accuracy 84.38\n", + "Iteration 180 | Train Loss 0.5506 | Classifier Accuracy 71.88\n", + "Iteration 200 | Train Loss 0.4543 | Classifier Accuracy 71.88\n", + "Iteration 220 | Train Loss 0.4072 | Classifier Accuracy 76.56\n", + "Iteration 240 | Train Loss 0.3476 | Classifier Accuracy 82.81\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.3796 | Accuracy 82.96 \n", + "Valid Loss Mean 0.3118 | Accuracy 85.59 \n", + "\n", + "seed : 555\n", + " ====================== epoch 10 ======================\n", + "Iteration 0 | Train Loss 0.4235 | Classifier Accuracy 82.81\n", + "Iteration 20 | Train Loss 0.2178 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.3093 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.2713 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.3096 | Classifier Accuracy 85.94\n", + "Iteration 100 | Train Loss 0.3326 | Classifier Accuracy 85.94\n", + "Iteration 120 | Train Loss 0.3664 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.3360 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.3672 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.3222 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.4663 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.2558 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2723 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3591 | Accuracy 84.30 \n", + "Valid Loss Mean 0.3201 | Accuracy 86.09 \n", + "\n", + "seed : 555\n", + " ====================== epoch 11 ======================\n", + "Iteration 0 | Train Loss 0.2931 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.3913 | Classifier Accuracy 85.94\n", + "Iteration 40 | Train Loss 0.2704 | Classifier Accuracy 85.94\n", + "Iteration 60 | Train Loss 0.2561 | Classifier Accuracy 85.94\n", + "Iteration 80 | Train Loss 0.3760 | Classifier Accuracy 85.94\n", + "Iteration 100 | Train Loss 0.1927 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.3032 | Classifier Accuracy 84.38\n", + "Iteration 140 | Train Loss 0.3798 | Classifier Accuracy 78.12\n", + "Iteration 160 | Train Loss 0.2813 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.2105 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.4035 | Classifier Accuracy 82.81\n", + "Iteration 220 | Train Loss 0.3711 | Classifier Accuracy 82.81\n", + "Iteration 240 | Train Loss 0.4624 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3289 | Accuracy 85.60 \n", + "Valid Loss Mean 0.2802 | Accuracy 88.00 \n", + "\n", + "seed : 555\n", + " ====================== epoch 12 ======================\n", + "Iteration 0 | Train Loss 0.2274 | Classifier Accuracy 89.06\n", + "Iteration 20 | Train Loss 0.3015 | Classifier Accuracy 85.94\n", + "Iteration 40 | Train Loss 0.3206 | Classifier Accuracy 82.81\n", + "Iteration 60 | Train Loss 0.3287 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.3036 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.2491 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.3227 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.3148 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.3562 | Classifier Accuracy 82.81\n", + "Iteration 180 | Train Loss 0.2194 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.2417 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.3261 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.1957 | Classifier Accuracy 89.06\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.3053 | Accuracy 86.82 \n", + "Valid Loss Mean 0.5766 | Accuracy 80.83 \n", + "\n", + "seed : 555\n", + " ====================== epoch 13 ======================\n", + "Iteration 0 | Train Loss 0.2728 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.2870 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.5560 | Classifier Accuracy 78.12\n", + "Iteration 60 | Train Loss 0.2094 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.3206 | Classifier Accuracy 85.94\n", + "Iteration 100 | Train Loss 0.2374 | Classifier Accuracy 89.06\n", + "Iteration 120 | Train Loss 0.4881 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.3284 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.3991 | Classifier Accuracy 82.81\n", + "Iteration 180 | Train Loss 0.2123 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.4321 | Classifier Accuracy 76.56\n", + "Iteration 220 | Train Loss 0.2696 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2616 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.2866 | Accuracy 87.69 \n", + "Valid Loss Mean 0.2716 | Accuracy 88.69 \n", + "\n", + "seed : 555\n", + " ====================== epoch 14 ======================\n", + "Iteration 0 | Train Loss 0.3053 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.1994 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.1738 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.1889 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.1934 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2922 | Classifier Accuracy 85.94\n", + "Iteration 120 | Train Loss 0.2978 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.2643 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.4266 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.1624 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.2366 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.2679 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.3327 | Classifier Accuracy 85.94\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.2665 | Accuracy 88.76 \n", + "Valid Loss Mean 0.3017 | Accuracy 87.82 \n", + "\n", + "seed : 555\n", + " ====================== epoch 15 ======================\n", + "Iteration 0 | Train Loss 0.2794 | Classifier Accuracy 89.06\n", + "Iteration 20 | Train Loss 0.2640 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2207 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.3014 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.3866 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.2827 | Classifier Accuracy 87.50\n", + "Iteration 120 | Train Loss 0.1722 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.2297 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.2205 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.2434 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.2439 | Classifier Accuracy 87.50\n", + "Iteration 220 | Train Loss 0.2758 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.2954 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.2555 | Accuracy 89.33 \n", + "Valid Loss Mean 0.2475 | Accuracy 89.86 \n", + "\n", + "seed : 555\n", + " ====================== epoch 16 ======================\n", + "Iteration 0 | Train Loss 0.1987 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.2354 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.1976 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2826 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.2511 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.3180 | Classifier Accuracy 89.06\n", + "Iteration 120 | Train Loss 0.2585 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.2981 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.1810 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.3568 | Classifier Accuracy 84.38\n", + "Iteration 200 | Train Loss 0.1794 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.2667 | Classifier Accuracy 87.50\n", + "Iteration 240 | Train Loss 0.3765 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.2305 | Accuracy 90.32 \n", + "Valid Loss Mean 0.4557 | Accuracy 81.72 \n", + "\n", + "seed : 555\n", + " ====================== epoch 17 ======================\n", + "Iteration 0 | Train Loss 0.3014 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.1543 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1655 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.3682 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.1459 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1086 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.4204 | Classifier Accuracy 84.38\n", + "Iteration 140 | Train Loss 0.2770 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.1938 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.2025 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.2028 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.1457 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.1974 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.2226 | Accuracy 91.00 \n", + "Valid Loss Mean 0.2857 | Accuracy 88.52 \n", + "\n", + "seed : 555\n", + " ====================== epoch 18 ======================\n", + "Iteration 0 | Train Loss 0.1517 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1420 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.2070 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.1573 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.3580 | Classifier Accuracy 87.50\n", + "Iteration 100 | Train Loss 0.1584 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.2366 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1939 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.1963 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.3127 | Classifier Accuracy 84.38\n", + "Iteration 200 | Train Loss 0.2014 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.2950 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2305 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.2071 | Accuracy 91.61 \n", + "Valid Loss Mean 0.2571 | Accuracy 89.71 \n", + "\n", + "seed : 555\n", + " ====================== epoch 19 ======================\n", + "Iteration 0 | Train Loss 0.2515 | Classifier Accuracy 89.06\n", + "Iteration 20 | Train Loss 0.1553 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2894 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.2106 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.2211 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.2663 | Classifier Accuracy 87.50\n", + "Iteration 120 | Train Loss 0.3291 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.2051 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.1439 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.3901 | Classifier Accuracy 84.38\n", + "Iteration 200 | Train Loss 0.1529 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.1682 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.2393 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1993 | Accuracy 91.94 \n", + "Valid Loss Mean 0.2422 | Accuracy 89.41 \n", + "\n", + "seed : 555\n", + " ====================== epoch 20 ======================\n", + "Iteration 0 | Train Loss 0.2444 | Classifier Accuracy 85.94\n", + "Iteration 20 | Train Loss 0.0994 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1721 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2081 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.3012 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.1127 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.3337 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.1063 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1513 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1917 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1199 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.1296 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1168 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1890 | Accuracy 92.42 \n", + "Valid Loss Mean 0.2817 | Accuracy 89.04 \n", + "\n", + "seed : 555\n", + " ====================== epoch 21 ======================\n", + "Iteration 0 | Train Loss 0.2117 | Classifier Accuracy 89.06\n", + "Iteration 20 | Train Loss 0.1851 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.1969 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1806 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.1294 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1414 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1959 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1982 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.2830 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.1837 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.1846 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.1662 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1156 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1762 | Accuracy 92.83 \n", + "Valid Loss Mean 0.1631 | Accuracy 93.28 \n", + "\n", + "seed : 555\n", + " ====================== epoch 22 ======================\n", + "Iteration 0 | Train Loss 0.1350 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.2695 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.2736 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.0867 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0576 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1355 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.0983 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.2186 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.1759 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.3026 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.2222 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1873 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.1968 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1634 | Accuracy 93.58 \n", + "Valid Loss Mean 0.2090 | Accuracy 91.05 \n", + "\n", + "seed : 555\n", + " ====================== epoch 23 ======================\n", + "Iteration 0 | Train Loss 0.1681 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1631 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0984 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.1907 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.2636 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.1122 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1691 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1102 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.2760 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.1943 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.2784 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.1469 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0775 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1495 | Accuracy 94.34 \n", + "Valid Loss Mean 0.2245 | Accuracy 91.15 \n", + "\n", + "seed : 555\n", + " ====================== epoch 24 ======================\n", + "Iteration 0 | Train Loss 0.2375 | Classifier Accuracy 89.06\n", + "Iteration 20 | Train Loss 0.0933 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1578 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1415 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.2415 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0986 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0947 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1460 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0835 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1819 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1144 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0954 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.2587 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1407 | Accuracy 94.54 \n", + "Valid Loss Mean 0.1731 | Accuracy 93.23 \n", + "\n", + "seed : 555\n", + " ====================== epoch 25 ======================\n", + "Iteration 0 | Train Loss 0.0845 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1446 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0856 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0597 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1249 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.1225 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1365 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1106 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1617 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0849 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1101 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1080 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.1581 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1379 | Accuracy 94.70 \n", + "Valid Loss Mean 0.1424 | Accuracy 93.63 \n", + "\n", + "seed : 555\n", + " ====================== epoch 26 ======================\n", + "Iteration 0 | Train Loss 0.1152 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1538 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1839 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2205 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.1312 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.1356 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1185 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1637 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.0739 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.1164 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.1577 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.1747 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.0819 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1254 | Accuracy 95.09 \n", + "Valid Loss Mean 0.2026 | Accuracy 91.99 \n", + "\n", + "seed : 555\n", + " ====================== epoch 27 ======================\n", + "Iteration 0 | Train Loss 0.1302 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.1380 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1036 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.2671 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.2901 | Classifier Accuracy 87.50\n", + "Iteration 100 | Train Loss 0.0950 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1136 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0532 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1530 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.2283 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1116 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0649 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0417 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1165 | Accuracy 95.42 \n", + "Valid Loss Mean 0.1690 | Accuracy 93.28 \n", + "\n", + "seed : 555\n", + " ====================== epoch 28 ======================\n", + "Iteration 0 | Train Loss 0.0637 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.2464 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.0998 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0682 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1313 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0641 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.1052 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0892 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1110 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0340 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0218 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.2697 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.0522 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1132 | Accuracy 95.66 \n", + "Valid Loss Mean 0.1320 | Accuracy 94.17 \n", + "\n", + "seed : 555\n", + " ====================== epoch 29 ======================\n", + "Iteration 0 | Train Loss 0.1002 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0624 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.1552 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1098 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0736 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1083 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1827 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1047 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0876 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1484 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1736 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.0587 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.1026 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.1025 | Accuracy 96.15 \n", + "Valid Loss Mean 0.1647 | Accuracy 93.15 \n", + "\n", + "seed : 555\n", + " ====================== epoch 30 ======================\n", + "Iteration 0 | Train Loss 0.0731 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0877 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.2259 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.0562 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1174 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.1416 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1432 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0307 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0968 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0934 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0710 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1058 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.0642 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0999 | Accuracy 96.04 \n", + "Valid Loss Mean 0.1449 | Accuracy 94.82 \n", + "\n", + "seed : 555\n", + " ====================== epoch 31 ======================\n", + "Iteration 0 | Train Loss 0.1832 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.1634 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1040 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0215 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0888 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0560 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0530 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0542 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0371 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0958 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0736 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.1191 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0489 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0915 | Accuracy 96.49 \n", + "Valid Loss Mean 0.1394 | Accuracy 94.47 \n", + "\n", + "seed : 555\n", + " ====================== epoch 32 ======================\n", + "Iteration 0 | Train Loss 0.0442 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0448 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0361 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0252 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0417 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1783 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.0533 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0509 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0545 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1332 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0422 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1220 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.2045 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0892 | Accuracy 96.55 \n", + "Valid Loss Mean 0.1453 | Accuracy 94.42 \n", + "\n", + "seed : 555\n", + " ====================== epoch 33 ======================\n", + "Iteration 0 | Train Loss 0.1296 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0810 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0213 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0286 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0673 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0752 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0949 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0841 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0602 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0361 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.2555 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0235 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0182 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0788 | Accuracy 96.95 \n", + "Valid Loss Mean 0.1482 | Accuracy 94.94 \n", + "\n", + "seed : 555\n", + " ====================== epoch 34 ======================\n", + "Iteration 0 | Train Loss 0.0539 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1326 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.1027 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1544 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.1751 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0714 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0154 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.1223 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0833 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0209 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.1140 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0291 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0165 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0753 | Accuracy 97.12 \n", + "Valid Loss Mean 0.1528 | Accuracy 95.06 \n", + "\n", + "seed : 555\n", + " ====================== epoch 35 ======================\n", + "Iteration 0 | Train Loss 0.0466 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0262 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0398 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0656 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0653 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0402 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0640 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1068 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1141 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1500 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0628 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1184 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0808 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0703 | Accuracy 97.36 \n", + "Valid Loss Mean 0.1240 | Accuracy 95.24 \n", + "\n", + "seed : 555\n", + " ====================== epoch 36 ======================\n", + "Iteration 0 | Train Loss 0.0806 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0627 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0880 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0803 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.0364 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0316 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0912 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0790 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0795 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0363 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0734 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1383 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1672 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0699 | Accuracy 97.41 \n", + "Valid Loss Mean 0.1289 | Accuracy 94.94 \n", + "\n", + "seed : 555\n", + " ====================== epoch 37 ======================\n", + "Iteration 0 | Train Loss 0.0855 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0766 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.1837 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.0763 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0464 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0075 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.1258 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.0751 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1517 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.0606 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0866 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0671 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0934 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0626 | Accuracy 97.56 \n", + "Valid Loss Mean 0.1845 | Accuracy 93.23 \n", + "\n", + "seed : 555\n", + " ====================== epoch 38 ======================\n", + "Iteration 0 | Train Loss 0.0160 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0662 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0405 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0604 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.2168 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0909 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0308 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0670 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0560 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0687 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0370 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0581 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0787 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0604 | Accuracy 97.70 \n", + "Valid Loss Mean 0.1241 | Accuracy 95.36 \n", + "\n", + "seed : 555\n", + " ====================== epoch 39 ======================\n", + "Iteration 0 | Train Loss 0.0111 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.1040 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0551 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1778 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0256 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0117 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.1201 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0039 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0574 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0968 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0114 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0188 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.2607 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0532 | Accuracy 97.93 \n", + "Valid Loss Mean 0.1307 | Accuracy 95.36 \n", + "\n", + "seed : 555\n", + " ====================== epoch 40 ======================\n", + "Iteration 0 | Train Loss 0.0100 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0209 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0793 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1271 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.0365 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0126 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0421 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0199 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0776 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0206 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0300 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0292 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0159 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0535 | Accuracy 98.04 \n", + "Valid Loss Mean 0.1218 | Accuracy 95.49 \n", + "\n", + "seed : 555\n", + " ====================== epoch 41 ======================\n", + "Iteration 0 | Train Loss 0.0272 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0329 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0903 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1020 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0397 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0709 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0157 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0091 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0191 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0918 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0145 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.1458 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.0469 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0488 | Accuracy 98.29 \n", + "Valid Loss Mean 0.1166 | Accuracy 95.76 \n", + "\n", + "seed : 555\n", + " ====================== epoch 42 ======================\n", + "Iteration 0 | Train Loss 0.0467 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0118 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0322 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0209 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0296 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0403 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0884 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0402 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0904 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0718 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0372 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0579 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0444 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0483 | Accuracy 98.21 \n", + "Valid Loss Mean 0.1129 | Accuracy 95.93 \n", + "\n", + "seed : 555\n", + " ====================== epoch 43 ======================\n", + "Iteration 0 | Train Loss 0.0668 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0361 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0629 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0169 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0847 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0432 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0981 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1995 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.0579 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0490 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0253 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0071 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0477 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0459 | Accuracy 98.44 \n", + "Valid Loss Mean 0.1129 | Accuracy 95.41 \n", + "\n", + "seed : 555\n", + " ====================== epoch 44 ======================\n", + "Iteration 0 | Train Loss 0.0218 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.1281 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0093 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0160 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0234 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0216 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0430 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0085 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0127 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0820 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0449 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0088 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0799 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0411 | Accuracy 98.53 \n", + "Valid Loss Mean 0.1146 | Accuracy 95.76 \n", + "\n", + "seed : 555\n", + " ====================== epoch 45 ======================\n", + "Iteration 0 | Train Loss 0.0655 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0351 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0570 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0334 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0123 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0611 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0909 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0377 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0590 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0042 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.1217 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.1019 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0498 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0417 | Accuracy 98.52 \n", + "Valid Loss Mean 0.1126 | Accuracy 95.88 \n", + "\n", + "seed : 555\n", + " ====================== epoch 46 ======================\n", + "Iteration 0 | Train Loss 0.0456 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0159 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0088 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0526 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0805 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0133 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0433 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0568 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0155 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0043 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0332 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0126 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.1033 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0398 | Accuracy 98.51 \n", + "Valid Loss Mean 0.1136 | Accuracy 96.01 \n", + "\n", + "seed : 555\n", + " ====================== epoch 47 ======================\n", + "Iteration 0 | Train Loss 0.0687 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0623 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0525 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0095 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0262 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0838 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0065 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.1517 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1170 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0249 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0283 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0212 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0138 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0406 | Accuracy 98.55 \n", + "Valid Loss Mean 0.1194 | Accuracy 95.96 \n", + "\n", + "seed : 555\n", + " ====================== epoch 48 ======================\n", + "Iteration 0 | Train Loss 0.0239 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0533 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0174 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0309 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0385 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0548 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0254 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0675 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0140 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0261 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0359 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0452 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0362 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0411 | Accuracy 98.38 \n", + "Valid Loss Mean 0.1171 | Accuracy 96.06 \n", + "\n", + "seed : 555\n", + " ====================== epoch 49 ======================\n", + "Iteration 0 | Train Loss 0.0235 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.1080 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0151 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0664 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1213 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0361 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0191 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0278 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0080 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0351 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0692 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0894 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0209 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0380 | Accuracy 98.59 \n", + "Valid Loss Mean 0.1167 | Accuracy 96.01 \n", + "\n", + "seed : 555\n", + " ====================== epoch 50 ======================\n", + "Iteration 0 | Train Loss 0.0251 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0163 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0216 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0384 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0227 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0283 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0683 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0102 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0410 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0313 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0351 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0279 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0682 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0365 | Accuracy 98.59 \n", + "Valid Loss Mean 0.1173 | Accuracy 95.93 \n", + "\n", + "seed : 555\n", + " ====================== epoch 51 ======================\n", + "Iteration 0 | Train Loss 0.0459 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0327 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0238 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0453 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0335 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0238 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0631 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0646 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0205 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0433 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0167 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1578 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.0141 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0366 | Accuracy 98.60 \n", + "Valid Loss Mean 0.1139 | Accuracy 96.03 \n", + "\n", + "seed : 555\n", + " ====================== epoch 52 ======================\n", + "Iteration 0 | Train Loss 0.0151 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0554 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0284 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0021 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0024 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0036 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.1268 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0066 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0158 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0328 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0348 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0305 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0278 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0385 | Accuracy 98.58 \n", + "Valid Loss Mean 0.1153 | Accuracy 95.98 \n", + "\n", + "seed : 555\n", + " ====================== epoch 53 ======================\n", + "Iteration 0 | Train Loss 0.0071 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0357 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0334 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0086 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0232 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0405 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0108 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0481 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0119 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0159 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0446 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0659 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0481 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0377 | Accuracy 98.58 \n", + "Valid Loss Mean 0.1165 | Accuracy 96.08 \n", + "\n", + "seed : 555\n", + " ====================== epoch 54 ======================\n", + "Iteration 0 | Train Loss 0.0060 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0675 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0209 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0246 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0628 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0191 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0321 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0091 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0577 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0593 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0278 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0150 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0386 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0390 | Accuracy 98.50 \n", + "Valid Loss Mean 0.1170 | Accuracy 96.08 \n", + "\n", + "seed : 555\n", + " ====================== epoch 55 ======================\n", + "Iteration 0 | Train Loss 0.0226 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0068 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0234 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0158 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0771 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0348 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0310 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0466 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0676 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0225 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0042 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0231 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0602 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0390 | Accuracy 98.50 \n", + "Valid Loss Mean 0.1184 | Accuracy 96.01 \n", + "\n", + "EARLY STOPPING!!\n", + ">>>>>>>>>>>> start to train - xception <<<<<<<<<<<<\n", + "seed : 777\n", + "seed : 777\n", + " ====================== epoch 1 ======================\n", + "Iteration 0 | Train Loss 0.7242 | Classifier Accuracy 42.19\n", + "Iteration 20 | Train Loss 0.7294 | Classifier Accuracy 48.44\n", + "Iteration 40 | Train Loss 0.6548 | Classifier Accuracy 62.50\n", + "Iteration 60 | Train Loss 0.6909 | Classifier Accuracy 59.38\n", + "Iteration 80 | Train Loss 0.7136 | Classifier Accuracy 59.38\n", + "Iteration 100 | Train Loss 0.6596 | Classifier Accuracy 56.25\n", + "Iteration 120 | Train Loss 0.6546 | Classifier Accuracy 59.38\n", + "Iteration 140 | Train Loss 0.6856 | Classifier Accuracy 54.69\n", + "Iteration 160 | Train Loss 0.6326 | Classifier Accuracy 65.62\n", + "Iteration 180 | Train Loss 0.6428 | Classifier Accuracy 67.19\n", + "Iteration 200 | Train Loss 0.6731 | Classifier Accuracy 62.50\n", + "Iteration 220 | Train Loss 0.7458 | Classifier Accuracy 53.12\n", + "Iteration 240 | Train Loss 0.6515 | Classifier Accuracy 59.38\n", + "\n", + "[Summary] Elapsed time : 1 m 33 s\n", + "Train Loss Mean 0.6908 | Accuracy 56.75 \n", + "Valid Loss Mean 0.6200 | Accuracy 64.76 \n", + "\n", + "seed : 777\n", + " ====================== epoch 2 ======================\n", + "Iteration 0 | Train Loss 0.6677 | Classifier Accuracy 59.38\n", + "Iteration 20 | Train Loss 0.6662 | Classifier Accuracy 59.38\n", + "Iteration 40 | Train Loss 0.6778 | Classifier Accuracy 62.50\n", + "Iteration 60 | Train Loss 0.6778 | Classifier Accuracy 60.94\n", + "Iteration 80 | Train Loss 0.6702 | Classifier Accuracy 59.38\n", + "Iteration 100 | Train Loss 0.6142 | Classifier Accuracy 67.19\n", + "Iteration 120 | Train Loss 0.6198 | Classifier Accuracy 64.06\n", + "Iteration 140 | Train Loss 0.6398 | Classifier Accuracy 65.62\n", + "Iteration 160 | Train Loss 0.7212 | Classifier Accuracy 54.69\n", + "Iteration 180 | Train Loss 0.6766 | Classifier Accuracy 62.50\n", + "Iteration 200 | Train Loss 0.6046 | Classifier Accuracy 68.75\n", + "Iteration 220 | Train Loss 0.5687 | Classifier Accuracy 70.31\n", + "Iteration 240 | Train Loss 0.6717 | Classifier Accuracy 59.38\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.6350 | Accuracy 64.43 \n", + "Valid Loss Mean 0.7053 | Accuracy 63.79 \n", + "\n", + "seed : 777\n", + " ====================== epoch 3 ======================\n", + "Iteration 0 | Train Loss 0.5549 | Classifier Accuracy 71.88\n", + "Iteration 20 | Train Loss 0.6471 | Classifier Accuracy 68.75\n", + "Iteration 40 | Train Loss 0.5370 | Classifier Accuracy 79.69\n", + "Iteration 60 | Train Loss 0.7402 | Classifier Accuracy 60.94\n", + "Iteration 80 | Train Loss 0.5353 | Classifier Accuracy 68.75\n", + "Iteration 100 | Train Loss 0.5774 | Classifier Accuracy 68.75\n", + "Iteration 120 | Train Loss 0.5555 | Classifier Accuracy 71.88\n", + "Iteration 140 | Train Loss 0.5652 | Classifier Accuracy 67.19\n", + "Iteration 160 | Train Loss 0.5259 | Classifier Accuracy 65.62\n", + "Iteration 180 | Train Loss 0.5658 | Classifier Accuracy 67.19\n", + "Iteration 200 | Train Loss 0.5122 | Classifier Accuracy 75.00\n", + "Iteration 220 | Train Loss 0.4325 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.5679 | Classifier Accuracy 75.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.5810 | Accuracy 70.03 \n", + "Valid Loss Mean 0.5674 | Accuracy 69.22 \n", + "\n", + "seed : 777\n", + " ====================== epoch 4 ======================\n", + "Iteration 0 | Train Loss 0.5798 | Classifier Accuracy 70.31\n", + "Iteration 20 | Train Loss 0.4810 | Classifier Accuracy 76.56\n", + "Iteration 40 | Train Loss 0.4745 | Classifier Accuracy 75.00\n", + "Iteration 60 | Train Loss 0.5319 | Classifier Accuracy 75.00\n", + "Iteration 80 | Train Loss 0.5308 | Classifier Accuracy 73.44\n", + "Iteration 100 | Train Loss 0.6316 | Classifier Accuracy 64.06\n", + "Iteration 120 | Train Loss 0.5480 | Classifier Accuracy 70.31\n", + "Iteration 140 | Train Loss 0.4691 | Classifier Accuracy 81.25\n", + "Iteration 160 | Train Loss 0.5310 | Classifier Accuracy 70.31\n", + "Iteration 180 | Train Loss 0.5376 | Classifier Accuracy 79.69\n", + "Iteration 200 | Train Loss 0.5395 | Classifier Accuracy 70.31\n", + "Iteration 220 | Train Loss 0.4966 | Classifier Accuracy 76.56\n", + "Iteration 240 | Train Loss 0.5619 | Classifier Accuracy 73.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.5395 | Accuracy 72.82 \n", + "Valid Loss Mean 0.5352 | Accuracy 75.32 \n", + "\n", + "seed : 777\n", + " ====================== epoch 5 ======================\n", + "Iteration 0 | Train Loss 0.5644 | Classifier Accuracy 76.56\n", + "Iteration 20 | Train Loss 0.5854 | Classifier Accuracy 68.75\n", + "Iteration 40 | Train Loss 0.5395 | Classifier Accuracy 78.12\n", + "Iteration 60 | Train Loss 0.4499 | Classifier Accuracy 78.12\n", + "Iteration 80 | Train Loss 0.4569 | Classifier Accuracy 81.25\n", + "Iteration 100 | Train Loss 0.5799 | Classifier Accuracy 68.75\n", + "Iteration 120 | Train Loss 0.6526 | Classifier Accuracy 64.06\n", + "Iteration 140 | Train Loss 0.4709 | Classifier Accuracy 75.00\n", + "Iteration 160 | Train Loss 0.5974 | Classifier Accuracy 68.75\n", + "Iteration 180 | Train Loss 0.3996 | Classifier Accuracy 82.81\n", + "Iteration 200 | Train Loss 0.4432 | Classifier Accuracy 76.56\n", + "Iteration 220 | Train Loss 0.4677 | Classifier Accuracy 76.56\n", + "Iteration 240 | Train Loss 0.5081 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.5200 | Accuracy 74.58 \n", + "Valid Loss Mean 0.4351 | Accuracy 79.04 \n", + "\n", + "seed : 777\n", + " ====================== epoch 6 ======================\n", + "Iteration 0 | Train Loss 0.5509 | Classifier Accuracy 71.88\n", + "Iteration 20 | Train Loss 0.5974 | Classifier Accuracy 70.31\n", + "Iteration 40 | Train Loss 0.5509 | Classifier Accuracy 70.31\n", + "Iteration 60 | Train Loss 0.4574 | Classifier Accuracy 79.69\n", + "Iteration 80 | Train Loss 0.4751 | Classifier Accuracy 70.31\n", + "Iteration 100 | Train Loss 0.6050 | Classifier Accuracy 71.88\n", + "Iteration 120 | Train Loss 0.5566 | Classifier Accuracy 75.00\n", + "Iteration 140 | Train Loss 0.4031 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.4229 | Classifier Accuracy 79.69\n", + "Iteration 180 | Train Loss 0.4913 | Classifier Accuracy 75.00\n", + "Iteration 200 | Train Loss 0.4792 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.5888 | Classifier Accuracy 75.00\n", + "Iteration 240 | Train Loss 0.4848 | Classifier Accuracy 76.56\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.4844 | Accuracy 76.53 \n", + "Valid Loss Mean 0.4807 | Accuracy 75.37 \n", + "\n", + "seed : 777\n", + " ====================== epoch 7 ======================\n", + "Iteration 0 | Train Loss 0.4733 | Classifier Accuracy 81.25\n", + "Iteration 20 | Train Loss 0.4404 | Classifier Accuracy 82.81\n", + "Iteration 40 | Train Loss 0.3604 | Classifier Accuracy 84.38\n", + "Iteration 60 | Train Loss 0.4148 | Classifier Accuracy 81.25\n", + "Iteration 80 | Train Loss 0.4346 | Classifier Accuracy 76.56\n", + "Iteration 100 | Train Loss 0.5071 | Classifier Accuracy 73.44\n", + "Iteration 120 | Train Loss 0.4827 | Classifier Accuracy 76.56\n", + "Iteration 140 | Train Loss 0.4410 | Classifier Accuracy 76.56\n", + "Iteration 160 | Train Loss 0.4845 | Classifier Accuracy 75.00\n", + "Iteration 180 | Train Loss 0.5418 | Classifier Accuracy 73.44\n", + "Iteration 200 | Train Loss 0.2986 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.4408 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.4759 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.4533 | Accuracy 78.83 \n", + "Valid Loss Mean 0.3974 | Accuracy 80.61 \n", + "\n", + "seed : 777\n", + " ====================== epoch 8 ======================\n", + "Iteration 0 | Train Loss 0.3743 | Classifier Accuracy 82.81\n", + "Iteration 20 | Train Loss 0.3913 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.3235 | Classifier Accuracy 87.50\n", + "Iteration 60 | Train Loss 0.5747 | Classifier Accuracy 64.06\n", + "Iteration 80 | Train Loss 0.3650 | Classifier Accuracy 82.81\n", + "Iteration 100 | Train Loss 0.3692 | Classifier Accuracy 89.06\n", + "Iteration 120 | Train Loss 0.4178 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.3010 | Classifier Accuracy 92.19\n", + "Iteration 160 | Train Loss 0.3804 | Classifier Accuracy 84.38\n", + "Iteration 180 | Train Loss 0.4374 | Classifier Accuracy 76.56\n", + "Iteration 200 | Train Loss 0.5852 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.3350 | Classifier Accuracy 85.94\n", + "Iteration 240 | Train Loss 0.3894 | Classifier Accuracy 82.81\n", + "\n", + "[Summary] Elapsed time : 1 m 44 s\n", + "Train Loss Mean 0.4243 | Accuracy 80.79 \n", + "Valid Loss Mean 0.3998 | Accuracy 82.14 \n", + "\n", + "seed : 777\n", + " ====================== epoch 9 ======================\n", + "Iteration 0 | Train Loss 0.3517 | Classifier Accuracy 82.81\n", + "Iteration 20 | Train Loss 0.4184 | Classifier Accuracy 78.12\n", + "Iteration 40 | Train Loss 0.3003 | Classifier Accuracy 85.94\n", + "Iteration 60 | Train Loss 0.4209 | Classifier Accuracy 82.81\n", + "Iteration 80 | Train Loss 0.3821 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.3561 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.3155 | Classifier Accuracy 82.81\n", + "Iteration 140 | Train Loss 0.4118 | Classifier Accuracy 84.38\n", + "Iteration 160 | Train Loss 0.2868 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.3328 | Classifier Accuracy 84.38\n", + "Iteration 200 | Train Loss 0.3633 | Classifier Accuracy 87.50\n", + "Iteration 220 | Train Loss 0.4364 | Classifier Accuracy 79.69\n", + "Iteration 240 | Train Loss 0.4893 | Classifier Accuracy 73.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.3984 | Accuracy 82.05 \n", + "Valid Loss Mean 0.3483 | Accuracy 84.33 \n", + "\n", + "seed : 777\n", + " ====================== epoch 10 ======================\n", + "Iteration 0 | Train Loss 0.2931 | Classifier Accuracy 85.94\n", + "Iteration 20 | Train Loss 0.3399 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.3963 | Classifier Accuracy 78.12\n", + "Iteration 60 | Train Loss 0.3081 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.3229 | Classifier Accuracy 82.81\n", + "Iteration 100 | Train Loss 0.3104 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.4174 | Classifier Accuracy 82.81\n", + "Iteration 140 | Train Loss 0.3440 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.3657 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.2930 | Classifier Accuracy 85.94\n", + "Iteration 200 | Train Loss 0.4072 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.3845 | Classifier Accuracy 82.81\n", + "Iteration 240 | Train Loss 0.2670 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.3600 | Accuracy 84.22 \n", + "Valid Loss Mean 0.4698 | Accuracy 79.99 \n", + "\n", + "seed : 777\n", + " ====================== epoch 11 ======================\n", + "Iteration 0 | Train Loss 0.3600 | Classifier Accuracy 85.94\n", + "Iteration 20 | Train Loss 0.3028 | Classifier Accuracy 85.94\n", + "Iteration 40 | Train Loss 0.3131 | Classifier Accuracy 84.38\n", + "Iteration 60 | Train Loss 0.3307 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.4119 | Classifier Accuracy 82.81\n", + "Iteration 100 | Train Loss 0.4901 | Classifier Accuracy 79.69\n", + "Iteration 120 | Train Loss 0.3859 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.3354 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.2787 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.2513 | Classifier Accuracy 85.94\n", + "Iteration 200 | Train Loss 0.3644 | Classifier Accuracy 79.69\n", + "Iteration 220 | Train Loss 0.4393 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.3307 | Classifier Accuracy 82.81\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.3384 | Accuracy 85.38 \n", + "Valid Loss Mean 0.3358 | Accuracy 84.40 \n", + "\n", + "seed : 777\n", + " ====================== epoch 12 ======================\n", + "Iteration 0 | Train Loss 0.2875 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.2826 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2561 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.3109 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.2379 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.3622 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.3058 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.2799 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.2978 | Classifier Accuracy 84.38\n", + "Iteration 180 | Train Loss 0.3589 | Classifier Accuracy 81.25\n", + "Iteration 200 | Train Loss 0.4185 | Classifier Accuracy 78.12\n", + "Iteration 220 | Train Loss 0.2893 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.4061 | Classifier Accuracy 76.56\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.3155 | Accuracy 86.46 \n", + "Valid Loss Mean 0.2908 | Accuracy 87.65 \n", + "\n", + "seed : 777\n", + " ====================== epoch 13 ======================\n", + "Iteration 0 | Train Loss 0.1932 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.2046 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.3281 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.3501 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.2141 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2427 | Classifier Accuracy 82.81\n", + "Iteration 120 | Train Loss 0.2382 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.3667 | Classifier Accuracy 85.94\n", + "Iteration 160 | Train Loss 0.2408 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.3824 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.4340 | Classifier Accuracy 81.25\n", + "Iteration 220 | Train Loss 0.2969 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.2155 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.2876 | Accuracy 87.84 \n", + "Valid Loss Mean 0.2640 | Accuracy 87.45 \n", + "\n", + "seed : 777\n", + " ====================== epoch 14 ======================\n", + "Iteration 0 | Train Loss 0.1914 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.2772 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.3401 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.1963 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.3918 | Classifier Accuracy 79.69\n", + "Iteration 100 | Train Loss 0.2764 | Classifier Accuracy 87.50\n", + "Iteration 120 | Train Loss 0.4247 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.5485 | Classifier Accuracy 76.56\n", + "Iteration 160 | Train Loss 0.3577 | Classifier Accuracy 87.50\n", + "Iteration 180 | Train Loss 0.1772 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.3375 | Classifier Accuracy 84.38\n", + "Iteration 220 | Train Loss 0.1685 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.2974 | Classifier Accuracy 85.94\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.2745 | Accuracy 88.49 \n", + "Valid Loss Mean 0.3948 | Accuracy 85.66 \n", + "\n", + "seed : 777\n", + " ====================== epoch 15 ======================\n", + "Iteration 0 | Train Loss 0.2394 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.3089 | Classifier Accuracy 85.94\n", + "Iteration 40 | Train Loss 0.3001 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2624 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.1696 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.2607 | Classifier Accuracy 87.50\n", + "Iteration 120 | Train Loss 0.3114 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.2200 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.3523 | Classifier Accuracy 87.50\n", + "Iteration 180 | Train Loss 0.2985 | Classifier Accuracy 82.81\n", + "Iteration 200 | Train Loss 0.3042 | Classifier Accuracy 81.25\n", + "Iteration 220 | Train Loss 0.2727 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.2379 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.2550 | Accuracy 89.31 \n", + "Valid Loss Mean 0.1971 | Accuracy 91.00 \n", + "\n", + "seed : 777\n", + " ====================== epoch 16 ======================\n", + "Iteration 0 | Train Loss 0.2227 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.3756 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.2081 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.2717 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.3143 | Classifier Accuracy 84.38\n", + "Iteration 100 | Train Loss 0.2145 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.2562 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.3580 | Classifier Accuracy 84.38\n", + "Iteration 160 | Train Loss 0.2869 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.2316 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.2070 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.2944 | Classifier Accuracy 87.50\n", + "Iteration 240 | Train Loss 0.1881 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2438 | Accuracy 89.96 \n", + "Valid Loss Mean 0.2094 | Accuracy 90.82 \n", + "\n", + "seed : 777\n", + " ====================== epoch 17 ======================\n", + "Iteration 0 | Train Loss 0.1676 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.1331 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1662 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1854 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.1294 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2035 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1980 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.2180 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.0970 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.2099 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.2802 | Classifier Accuracy 82.81\n", + "Iteration 220 | Train Loss 0.1704 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.1371 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.2243 | Accuracy 90.83 \n", + "Valid Loss Mean 0.2579 | Accuracy 89.29 \n", + "\n", + "seed : 777\n", + " ====================== epoch 18 ======================\n", + "Iteration 0 | Train Loss 0.2684 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.1342 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.3498 | Classifier Accuracy 82.81\n", + "Iteration 60 | Train Loss 0.2043 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.1111 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1227 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.3138 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1338 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1220 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1150 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.2804 | Classifier Accuracy 84.38\n", + "Iteration 220 | Train Loss 0.1681 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.1589 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2052 | Accuracy 91.58 \n", + "Valid Loss Mean 0.2416 | Accuracy 90.13 \n", + "\n", + "seed : 777\n", + " ====================== epoch 19 ======================\n", + "Iteration 0 | Train Loss 0.1632 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.2083 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1353 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1036 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1470 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2220 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1351 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.1935 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.2913 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.1315 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.2268 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.3794 | Classifier Accuracy 85.94\n", + "Iteration 240 | Train Loss 0.1810 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1976 | Accuracy 91.98 \n", + "Valid Loss Mean 0.1644 | Accuracy 92.36 \n", + "\n", + "seed : 777\n", + " ====================== epoch 20 ======================\n", + "Iteration 0 | Train Loss 0.2268 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.1436 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.1978 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.1530 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.2101 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.2434 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.1174 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.2012 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.1542 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1593 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.1680 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.1389 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1748 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 48 s\n", + "Train Loss Mean 0.1837 | Accuracy 92.49 \n", + "Valid Loss Mean 0.1779 | Accuracy 93.01 \n", + "\n", + "seed : 777\n", + " ====================== epoch 21 ======================\n", + "Iteration 0 | Train Loss 0.1316 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1783 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2501 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.1425 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.1590 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1671 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1370 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.2138 | Classifier Accuracy 92.19\n", + "Iteration 160 | Train Loss 0.3829 | Classifier Accuracy 81.25\n", + "Iteration 180 | Train Loss 0.1948 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.1421 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.2151 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.2686 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 48 s\n", + "Train Loss Mean 0.1755 | Accuracy 92.83 \n", + "Valid Loss Mean 0.2139 | Accuracy 90.38 \n", + "\n", + "seed : 777\n", + " ====================== epoch 22 ======================\n", + "Iteration 0 | Train Loss 0.1391 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.2465 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2826 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.1348 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.3050 | Classifier Accuracy 87.50\n", + "Iteration 100 | Train Loss 0.1648 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1682 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1529 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1217 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0936 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.2932 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.1904 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.2380 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1697 | Accuracy 93.20 \n", + "Valid Loss Mean 0.1784 | Accuracy 92.61 \n", + "\n", + "seed : 777\n", + " ====================== epoch 23 ======================\n", + "Iteration 0 | Train Loss 0.1430 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.1607 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1221 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.1165 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.1145 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1344 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1551 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.1207 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.3364 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.1082 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1214 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.2287 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.1621 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1525 | Accuracy 93.92 \n", + "Valid Loss Mean 0.2088 | Accuracy 92.34 \n", + "\n", + "seed : 777\n", + " ====================== epoch 24 ======================\n", + "Iteration 0 | Train Loss 0.1147 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1576 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.2047 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1778 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.1706 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.0828 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0710 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1428 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.2510 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0736 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.1076 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.3248 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.1706 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1493 | Accuracy 94.08 \n", + "Valid Loss Mean 0.1741 | Accuracy 92.78 \n", + "\n", + "seed : 777\n", + " ====================== epoch 25 ======================\n", + "Iteration 0 | Train Loss 0.1210 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0694 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.2121 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.1800 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.2236 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.1757 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.1170 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1577 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1952 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1579 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.1428 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1681 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.2764 | Classifier Accuracy 89.06\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1380 | Accuracy 94.53 \n", + "Valid Loss Mean 0.4045 | Accuracy 84.85 \n", + "\n", + "seed : 777\n", + " ====================== epoch 26 ======================\n", + "Iteration 0 | Train Loss 0.0515 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.1666 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1044 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1201 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.1938 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.1882 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1151 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1682 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1425 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.0927 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0392 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0785 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.1368 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1262 | Accuracy 95.15 \n", + "Valid Loss Mean 0.1588 | Accuracy 93.40 \n", + "\n", + "seed : 777\n", + " ====================== epoch 27 ======================\n", + "Iteration 0 | Train Loss 0.1314 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1273 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.2332 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1006 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.1150 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.2407 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.0798 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1451 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.0569 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.1748 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.1434 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1456 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.0791 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1197 | Accuracy 95.32 \n", + "Valid Loss Mean 0.1467 | Accuracy 93.80 \n", + "\n", + "seed : 777\n", + " ====================== epoch 28 ======================\n", + "Iteration 0 | Train Loss 0.1351 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0992 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0610 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0461 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1474 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0421 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.1952 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.1668 | Classifier Accuracy 92.19\n", + "Iteration 160 | Train Loss 0.0993 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0859 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0866 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.1032 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1017 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1153 | Accuracy 95.60 \n", + "Valid Loss Mean 0.1330 | Accuracy 94.12 \n", + "\n", + "seed : 777\n", + " ====================== epoch 29 ======================\n", + "Iteration 0 | Train Loss 0.0945 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1056 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0643 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0871 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.0973 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.2163 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1161 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0860 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0629 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.1118 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.1394 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1051 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1731 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1097 | Accuracy 95.89 \n", + "Valid Loss Mean 0.1569 | Accuracy 94.35 \n", + "\n", + "seed : 777\n", + " ====================== epoch 30 ======================\n", + "Iteration 0 | Train Loss 0.1358 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0995 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.2220 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.0762 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1217 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1135 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.1294 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.2265 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1397 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0628 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1011 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0868 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0804 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0948 | Accuracy 96.27 \n", + "Valid Loss Mean 0.1383 | Accuracy 94.94 \n", + "\n", + "seed : 777\n", + " ====================== epoch 31 ======================\n", + "Iteration 0 | Train Loss 0.0649 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0666 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0563 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0357 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0765 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1121 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1580 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0500 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0644 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0564 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1321 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0659 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0999 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0934 | Accuracy 96.47 \n", + "Valid Loss Mean 0.1458 | Accuracy 94.20 \n", + "\n", + "seed : 777\n", + " ====================== epoch 32 ======================\n", + "Iteration 0 | Train Loss 0.0494 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1146 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.0579 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0922 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1953 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.1156 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0332 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0915 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1163 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0336 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0525 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0956 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1566 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0892 | Accuracy 96.54 \n", + "Valid Loss Mean 0.1526 | Accuracy 93.90 \n", + "\n", + "seed : 777\n", + " ====================== epoch 33 ======================\n", + "Iteration 0 | Train Loss 0.1169 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.1180 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1398 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.0515 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0708 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.1365 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0886 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0606 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0589 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0760 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0334 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0824 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1456 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0780 | Accuracy 96.99 \n", + "Valid Loss Mean 0.1404 | Accuracy 94.97 \n", + "\n", + "seed : 777\n", + " ====================== epoch 34 ======================\n", + "Iteration 0 | Train Loss 0.1356 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0385 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0718 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0204 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0388 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0862 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0248 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0744 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0332 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0855 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0425 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0267 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0947 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0803 | Accuracy 97.07 \n", + "Valid Loss Mean 0.1481 | Accuracy 94.25 \n", + "\n", + "seed : 777\n", + " ====================== epoch 35 ======================\n", + "Iteration 0 | Train Loss 0.0283 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0881 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1387 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1092 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0619 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0695 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1431 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.1251 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0300 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0283 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0871 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0569 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0401 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 48 s\n", + "Train Loss Mean 0.0741 | Accuracy 97.26 \n", + "Valid Loss Mean 0.1215 | Accuracy 95.19 \n", + "\n", + "seed : 777\n", + " ====================== epoch 36 ======================\n", + "Iteration 0 | Train Loss 0.0683 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0735 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0950 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0406 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.2891 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0041 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0166 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.1804 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1396 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0963 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0406 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0237 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0882 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0633 | Accuracy 97.78 \n", + "Valid Loss Mean 0.1244 | Accuracy 95.11 \n", + "\n", + "seed : 777\n", + " ====================== epoch 37 ======================\n", + "Iteration 0 | Train Loss 0.0769 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0381 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0160 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1344 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0822 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0958 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0691 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0509 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0161 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0141 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.1381 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.0890 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0897 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0628 | Accuracy 97.61 \n", + "Valid Loss Mean 0.1511 | Accuracy 94.42 \n", + "\n", + "seed : 777\n", + " ====================== epoch 38 ======================\n", + "Iteration 0 | Train Loss 0.1086 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0176 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1164 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.1406 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.0581 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0919 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.1060 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0217 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0934 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0958 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0777 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0770 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0695 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0647 | Accuracy 97.51 \n", + "Valid Loss Mean 0.1223 | Accuracy 95.59 \n", + "\n", + "seed : 777\n", + " ====================== epoch 39 ======================\n", + "Iteration 0 | Train Loss 0.0321 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0922 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0632 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0292 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0313 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0583 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0224 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.1750 | Classifier Accuracy 92.19\n", + "Iteration 160 | Train Loss 0.0724 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0906 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0216 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0828 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0306 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0540 | Accuracy 98.07 \n", + "Valid Loss Mean 0.1239 | Accuracy 95.71 \n", + "\n", + "seed : 777\n", + " ====================== epoch 40 ======================\n", + "Iteration 0 | Train Loss 0.0462 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0630 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0140 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.1416 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.0066 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0871 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0054 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0316 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0778 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0852 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0444 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0092 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0242 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0528 | Accuracy 98.09 \n", + "Valid Loss Mean 0.1217 | Accuracy 95.54 \n", + "\n", + "seed : 777\n", + " ====================== epoch 41 ======================\n", + "Iteration 0 | Train Loss 0.0183 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0229 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0240 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0637 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0810 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0210 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0112 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0259 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1416 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0484 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0324 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0121 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0387 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0509 | Accuracy 98.14 \n", + "Valid Loss Mean 0.1191 | Accuracy 95.86 \n", + "\n", + "seed : 777\n", + " ====================== epoch 42 ======================\n", + "Iteration 0 | Train Loss 0.0258 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0756 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0535 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0131 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0571 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0827 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0366 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0059 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0594 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0035 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0117 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0877 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0596 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0482 | Accuracy 98.22 \n", + "Valid Loss Mean 0.1282 | Accuracy 95.39 \n", + "\n", + "seed : 777\n", + " ====================== epoch 43 ======================\n", + "Iteration 0 | Train Loss 0.0807 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0248 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0129 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0068 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0364 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0516 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1604 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.0302 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0182 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0434 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0218 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0883 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0304 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0408 | Accuracy 98.39 \n", + "Valid Loss Mean 0.1336 | Accuracy 95.66 \n", + "\n", + "seed : 777\n", + " ====================== epoch 44 ======================\n", + "Iteration 0 | Train Loss 0.0886 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0308 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0499 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0352 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0428 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0434 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1366 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0876 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0186 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0618 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0215 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0212 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0302 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0432 | Accuracy 98.30 \n", + "Valid Loss Mean 0.1270 | Accuracy 95.59 \n", + "\n", + "seed : 777\n", + " ====================== epoch 45 ======================\n", + "Iteration 0 | Train Loss 0.0365 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0311 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0384 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0083 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0222 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0588 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0792 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0363 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0289 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0431 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0135 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0455 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0079 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0439 | Accuracy 98.41 \n", + "Valid Loss Mean 0.1223 | Accuracy 95.71 \n", + "\n", + "seed : 777\n", + " ====================== epoch 46 ======================\n", + "Iteration 0 | Train Loss 0.0066 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0149 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1020 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0788 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0952 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0300 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0245 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0361 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0279 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0224 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0194 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0158 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0064 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0387 | Accuracy 98.47 \n", + "Valid Loss Mean 0.1223 | Accuracy 95.88 \n", + "\n", + "seed : 777\n", + " ====================== epoch 47 ======================\n", + "Iteration 0 | Train Loss 0.0827 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.1009 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0504 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0259 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0179 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0776 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0440 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0810 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0170 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0816 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0205 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0046 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0467 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0397 | Accuracy 98.53 \n", + "Valid Loss Mean 0.1213 | Accuracy 95.76 \n", + "\n", + "seed : 777\n", + " ====================== epoch 48 ======================\n", + "Iteration 0 | Train Loss 0.0482 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.1046 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0023 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0249 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0344 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0020 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0099 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0349 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0912 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0149 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0413 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0693 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0029 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0414 | Accuracy 98.45 \n", + "Valid Loss Mean 0.1239 | Accuracy 95.63 \n", + "\n", + "seed : 777\n", + " ====================== epoch 49 ======================\n", + "Iteration 0 | Train Loss 0.0877 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0457 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0732 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0017 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0143 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0300 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0204 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0142 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.1003 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1351 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0247 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0110 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0320 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0375 | Accuracy 98.64 \n", + "Valid Loss Mean 0.1229 | Accuracy 95.78 \n", + "\n", + "seed : 777\n", + " ====================== epoch 50 ======================\n", + "Iteration 0 | Train Loss 0.0140 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0082 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0029 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0378 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0172 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0132 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0179 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0469 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0025 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0045 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0223 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0472 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0112 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0362 | Accuracy 98.72 \n", + "Valid Loss Mean 0.1258 | Accuracy 95.78 \n", + "\n", + "seed : 777\n", + " ====================== epoch 51 ======================\n", + "Iteration 0 | Train Loss 0.0521 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.1206 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0658 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0875 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0269 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0556 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0349 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0327 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0629 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0855 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0385 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0145 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0190 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.0401 | Accuracy 98.45 \n", + "Valid Loss Mean 0.1196 | Accuracy 95.86 \n", + "\n", + "EARLY STOPPING!!\n", + ">>>>>>>>>>>> start to train - xception <<<<<<<<<<<<\n", + "seed : 888\n", + "seed : 888\n", + " ====================== epoch 1 ======================\n", + "Iteration 0 | Train Loss 0.7391 | Classifier Accuracy 50.00\n", + "Iteration 20 | Train Loss 0.6480 | Classifier Accuracy 64.06\n", + "Iteration 40 | Train Loss 0.7971 | Classifier Accuracy 53.12\n", + "Iteration 60 | Train Loss 0.5812 | Classifier Accuracy 70.31\n", + "Iteration 80 | Train Loss 0.6906 | Classifier Accuracy 53.12\n", + "Iteration 100 | Train Loss 0.7541 | Classifier Accuracy 53.12\n", + "Iteration 120 | Train Loss 0.7123 | Classifier Accuracy 56.25\n", + "Iteration 140 | Train Loss 0.6212 | Classifier Accuracy 68.75\n", + "Iteration 160 | Train Loss 0.6838 | Classifier Accuracy 59.38\n", + "Iteration 180 | Train Loss 0.7311 | Classifier Accuracy 57.81\n", + "Iteration 200 | Train Loss 0.6774 | Classifier Accuracy 60.94\n", + "Iteration 220 | Train Loss 0.6151 | Classifier Accuracy 67.19\n", + "Iteration 240 | Train Loss 0.5741 | Classifier Accuracy 73.44\n", + "\n", + "[Summary] Elapsed time : 1 m 33 s\n", + "Train Loss Mean 0.6884 | Accuracy 57.14 \n", + "Valid Loss Mean 0.6288 | Accuracy 64.04 \n", + "\n", + "seed : 888\n", + " ====================== epoch 2 ======================\n", + "Iteration 0 | Train Loss 0.6628 | Classifier Accuracy 62.50\n", + "Iteration 20 | Train Loss 0.6545 | Classifier Accuracy 57.81\n", + "Iteration 40 | Train Loss 0.6867 | Classifier Accuracy 57.81\n", + "Iteration 60 | Train Loss 0.6671 | Classifier Accuracy 59.38\n", + "Iteration 80 | Train Loss 0.6400 | Classifier Accuracy 65.62\n", + "Iteration 100 | Train Loss 0.7134 | Classifier Accuracy 59.38\n", + "Iteration 120 | Train Loss 0.6518 | Classifier Accuracy 59.38\n", + "Iteration 140 | Train Loss 0.6811 | Classifier Accuracy 62.50\n", + "Iteration 160 | Train Loss 0.6764 | Classifier Accuracy 57.81\n", + "Iteration 180 | Train Loss 0.6176 | Classifier Accuracy 64.06\n", + "Iteration 200 | Train Loss 0.5337 | Classifier Accuracy 67.19\n", + "Iteration 220 | Train Loss 0.6079 | Classifier Accuracy 68.75\n", + "Iteration 240 | Train Loss 0.6317 | Classifier Accuracy 65.62\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.6331 | Accuracy 64.77 \n", + "Valid Loss Mean 0.6795 | Accuracy 65.65 \n", + "\n", + "seed : 888\n", + " ====================== epoch 3 ======================\n", + "Iteration 0 | Train Loss 0.6570 | Classifier Accuracy 70.31\n", + "Iteration 20 | Train Loss 0.5675 | Classifier Accuracy 67.19\n", + "Iteration 40 | Train Loss 0.5888 | Classifier Accuracy 68.75\n", + "Iteration 60 | Train Loss 0.5895 | Classifier Accuracy 67.19\n", + "Iteration 80 | Train Loss 0.6419 | Classifier Accuracy 70.31\n", + "Iteration 100 | Train Loss 0.5619 | Classifier Accuracy 68.75\n", + "Iteration 120 | Train Loss 0.6018 | Classifier Accuracy 70.31\n", + "Iteration 140 | Train Loss 0.5682 | Classifier Accuracy 68.75\n", + "Iteration 160 | Train Loss 0.5361 | Classifier Accuracy 73.44\n", + "Iteration 180 | Train Loss 0.6469 | Classifier Accuracy 59.38\n", + "Iteration 200 | Train Loss 0.5683 | Classifier Accuracy 67.19\n", + "Iteration 220 | Train Loss 0.6652 | Classifier Accuracy 60.94\n", + "Iteration 240 | Train Loss 0.4827 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.5814 | Accuracy 69.97 \n", + "Valid Loss Mean 0.5752 | Accuracy 68.82 \n", + "\n", + "seed : 888\n", + " ====================== epoch 4 ======================\n", + "Iteration 0 | Train Loss 0.4822 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.5935 | Classifier Accuracy 75.00\n", + "Iteration 40 | Train Loss 0.6301 | Classifier Accuracy 59.38\n", + "Iteration 60 | Train Loss 0.5814 | Classifier Accuracy 76.56\n", + "Iteration 80 | Train Loss 0.5410 | Classifier Accuracy 76.56\n", + "Iteration 100 | Train Loss 0.5010 | Classifier Accuracy 76.56\n", + "Iteration 120 | Train Loss 0.4827 | Classifier Accuracy 79.69\n", + "Iteration 140 | Train Loss 0.5278 | Classifier Accuracy 71.88\n", + "Iteration 160 | Train Loss 0.5985 | Classifier Accuracy 65.62\n", + "Iteration 180 | Train Loss 0.4850 | Classifier Accuracy 73.44\n", + "Iteration 200 | Train Loss 0.4286 | Classifier Accuracy 81.25\n", + "Iteration 220 | Train Loss 0.4828 | Classifier Accuracy 75.00\n", + "Iteration 240 | Train Loss 0.6294 | Classifier Accuracy 67.19\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.5462 | Accuracy 72.24 \n", + "Valid Loss Mean 0.5230 | Accuracy 76.44 \n", + "\n", + "seed : 888\n", + " ====================== epoch 5 ======================\n", + "Iteration 0 | Train Loss 0.5738 | Classifier Accuracy 73.44\n", + "Iteration 20 | Train Loss 0.5885 | Classifier Accuracy 75.00\n", + "Iteration 40 | Train Loss 0.4842 | Classifier Accuracy 73.44\n", + "Iteration 60 | Train Loss 0.5334 | Classifier Accuracy 64.06\n", + "Iteration 80 | Train Loss 0.4936 | Classifier Accuracy 75.00\n", + "Iteration 100 | Train Loss 0.6361 | Classifier Accuracy 71.88\n", + "Iteration 120 | Train Loss 0.4709 | Classifier Accuracy 79.69\n", + "Iteration 140 | Train Loss 0.5606 | Classifier Accuracy 73.44\n", + "Iteration 160 | Train Loss 0.5558 | Classifier Accuracy 71.88\n", + "Iteration 180 | Train Loss 0.5089 | Classifier Accuracy 78.12\n", + "Iteration 200 | Train Loss 0.5225 | Classifier Accuracy 71.88\n", + "Iteration 220 | Train Loss 0.5495 | Classifier Accuracy 78.12\n", + "Iteration 240 | Train Loss 0.5433 | Classifier Accuracy 71.88\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.5148 | Accuracy 75.15 \n", + "Valid Loss Mean 0.4395 | Accuracy 79.61 \n", + "\n", + "seed : 888\n", + " ====================== epoch 6 ======================\n", + "Iteration 0 | Train Loss 0.5169 | Classifier Accuracy 79.69\n", + "Iteration 20 | Train Loss 0.3408 | Classifier Accuracy 82.81\n", + "Iteration 40 | Train Loss 0.6058 | Classifier Accuracy 75.00\n", + "Iteration 60 | Train Loss 0.5417 | Classifier Accuracy 71.88\n", + "Iteration 80 | Train Loss 0.4156 | Classifier Accuracy 79.69\n", + "Iteration 100 | Train Loss 0.5562 | Classifier Accuracy 70.31\n", + "Iteration 120 | Train Loss 0.4168 | Classifier Accuracy 82.81\n", + "Iteration 140 | Train Loss 0.4553 | Classifier Accuracy 71.88\n", + "Iteration 160 | Train Loss 0.5198 | Classifier Accuracy 73.44\n", + "Iteration 180 | Train Loss 0.4692 | Classifier Accuracy 78.12\n", + "Iteration 200 | Train Loss 0.4716 | Classifier Accuracy 81.25\n", + "Iteration 220 | Train Loss 0.4410 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.5597 | Classifier Accuracy 78.12\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.4874 | Accuracy 76.76 \n", + "Valid Loss Mean 0.4504 | Accuracy 78.62 \n", + "\n", + "seed : 888\n", + " ====================== epoch 7 ======================\n", + "Iteration 0 | Train Loss 0.4285 | Classifier Accuracy 76.56\n", + "Iteration 20 | Train Loss 0.4120 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.4758 | Classifier Accuracy 76.56\n", + "Iteration 60 | Train Loss 0.4715 | Classifier Accuracy 76.56\n", + "Iteration 80 | Train Loss 0.4001 | Classifier Accuracy 82.81\n", + "Iteration 100 | Train Loss 0.4615 | Classifier Accuracy 73.44\n", + "Iteration 120 | Train Loss 0.4934 | Classifier Accuracy 76.56\n", + "Iteration 140 | Train Loss 0.3871 | Classifier Accuracy 81.25\n", + "Iteration 160 | Train Loss 0.3599 | Classifier Accuracy 81.25\n", + "Iteration 180 | Train Loss 0.4625 | Classifier Accuracy 78.12\n", + "Iteration 200 | Train Loss 0.5504 | Classifier Accuracy 71.88\n", + "Iteration 220 | Train Loss 0.4553 | Classifier Accuracy 75.00\n", + "Iteration 240 | Train Loss 0.4325 | Classifier Accuracy 82.81\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.4547 | Accuracy 78.79 \n", + "Valid Loss Mean 0.3948 | Accuracy 81.72 \n", + "\n", + "seed : 888\n", + " ====================== epoch 8 ======================\n", + "Iteration 0 | Train Loss 0.5201 | Classifier Accuracy 71.88\n", + "Iteration 20 | Train Loss 0.4511 | Classifier Accuracy 81.25\n", + "Iteration 40 | Train Loss 0.4553 | Classifier Accuracy 81.25\n", + "Iteration 60 | Train Loss 0.3189 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.2893 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.3412 | Classifier Accuracy 82.81\n", + "Iteration 120 | Train Loss 0.6035 | Classifier Accuracy 73.44\n", + "Iteration 140 | Train Loss 0.4380 | Classifier Accuracy 81.25\n", + "Iteration 160 | Train Loss 0.6469 | Classifier Accuracy 67.19\n", + "Iteration 180 | Train Loss 0.5263 | Classifier Accuracy 78.12\n", + "Iteration 200 | Train Loss 0.5544 | Classifier Accuracy 76.56\n", + "Iteration 220 | Train Loss 0.3603 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.4717 | Classifier Accuracy 73.44\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.4301 | Accuracy 80.14 \n", + "Valid Loss Mean 0.3953 | Accuracy 81.80 \n", + "\n", + "seed : 888\n", + " ====================== epoch 9 ======================\n", + "Iteration 0 | Train Loss 0.3225 | Classifier Accuracy 81.25\n", + "Iteration 20 | Train Loss 0.4315 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.3791 | Classifier Accuracy 87.50\n", + "Iteration 60 | Train Loss 0.4570 | Classifier Accuracy 76.56\n", + "Iteration 80 | Train Loss 0.2671 | Classifier Accuracy 84.38\n", + "Iteration 100 | Train Loss 0.4367 | Classifier Accuracy 75.00\n", + "Iteration 120 | Train Loss 0.3734 | Classifier Accuracy 85.94\n", + "Iteration 140 | Train Loss 0.3643 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.3616 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.3306 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.4228 | Classifier Accuracy 84.38\n", + "Iteration 220 | Train Loss 0.3725 | Classifier Accuracy 82.81\n", + "Iteration 240 | Train Loss 0.4011 | Classifier Accuracy 85.94\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.4026 | Accuracy 81.79 \n", + "Valid Loss Mean 0.3996 | Accuracy 81.45 \n", + "\n", + "seed : 888\n", + " ====================== epoch 10 ======================\n", + "Iteration 0 | Train Loss 0.4062 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.3683 | Classifier Accuracy 81.25\n", + "Iteration 40 | Train Loss 0.3135 | Classifier Accuracy 87.50\n", + "Iteration 60 | Train Loss 0.3775 | Classifier Accuracy 84.38\n", + "Iteration 80 | Train Loss 0.4636 | Classifier Accuracy 71.88\n", + "Iteration 100 | Train Loss 0.3952 | Classifier Accuracy 79.69\n", + "Iteration 120 | Train Loss 0.3917 | Classifier Accuracy 76.56\n", + "Iteration 140 | Train Loss 0.3472 | Classifier Accuracy 84.38\n", + "Iteration 160 | Train Loss 0.3743 | Classifier Accuracy 81.25\n", + "Iteration 180 | Train Loss 0.5169 | Classifier Accuracy 79.69\n", + "Iteration 200 | Train Loss 0.3161 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.3258 | Classifier Accuracy 82.81\n", + "Iteration 240 | Train Loss 0.5641 | Classifier Accuracy 70.31\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.3742 | Accuracy 83.16 \n", + "Valid Loss Mean 0.3227 | Accuracy 85.91 \n", + "\n", + "seed : 888\n", + " ====================== epoch 11 ======================\n", + "Iteration 0 | Train Loss 0.3660 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.4165 | Classifier Accuracy 79.69\n", + "Iteration 40 | Train Loss 0.3151 | Classifier Accuracy 87.50\n", + "Iteration 60 | Train Loss 0.3081 | Classifier Accuracy 87.50\n", + "Iteration 80 | Train Loss 0.3006 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.3002 | Classifier Accuracy 82.81\n", + "Iteration 120 | Train Loss 0.3682 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.3238 | Classifier Accuracy 82.81\n", + "Iteration 160 | Train Loss 0.3374 | Classifier Accuracy 82.81\n", + "Iteration 180 | Train Loss 0.4155 | Classifier Accuracy 81.25\n", + "Iteration 200 | Train Loss 0.2717 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.3585 | Classifier Accuracy 81.25\n", + "Iteration 240 | Train Loss 0.3278 | Classifier Accuracy 89.06\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.3514 | Accuracy 84.44 \n", + "Valid Loss Mean 0.5021 | Accuracy 77.98 \n", + "\n", + "seed : 888\n", + " ====================== epoch 12 ======================\n", + "Iteration 0 | Train Loss 0.3679 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.4133 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.3319 | Classifier Accuracy 82.81\n", + "Iteration 60 | Train Loss 0.1829 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.2234 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2780 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.4194 | Classifier Accuracy 81.25\n", + "Iteration 140 | Train Loss 0.3860 | Classifier Accuracy 81.25\n", + "Iteration 160 | Train Loss 0.3093 | Classifier Accuracy 85.94\n", + "Iteration 180 | Train Loss 0.4644 | Classifier Accuracy 76.56\n", + "Iteration 200 | Train Loss 0.2529 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.3132 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.3268 | Classifier Accuracy 84.38\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.3200 | Accuracy 86.11 \n", + "Valid Loss Mean 0.2704 | Accuracy 88.14 \n", + "\n", + "seed : 888\n", + " ====================== epoch 13 ======================\n", + "Iteration 0 | Train Loss 0.2419 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.2437 | Classifier Accuracy 87.50\n", + "Iteration 40 | Train Loss 0.3290 | Classifier Accuracy 84.38\n", + "Iteration 60 | Train Loss 0.2416 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.2098 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.3280 | Classifier Accuracy 85.94\n", + "Iteration 120 | Train Loss 0.3985 | Classifier Accuracy 82.81\n", + "Iteration 140 | Train Loss 0.3053 | Classifier Accuracy 89.06\n", + "Iteration 160 | Train Loss 0.1987 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.2936 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.4144 | Classifier Accuracy 85.94\n", + "Iteration 220 | Train Loss 0.3732 | Classifier Accuracy 84.38\n", + "Iteration 240 | Train Loss 0.1701 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.3017 | Accuracy 87.25 \n", + "Valid Loss Mean 0.3107 | Accuracy 86.09 \n", + "\n", + "seed : 888\n", + " ====================== epoch 14 ======================\n", + "Iteration 0 | Train Loss 0.3281 | Classifier Accuracy 84.38\n", + "Iteration 20 | Train Loss 0.2084 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2083 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.2195 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.2476 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2792 | Classifier Accuracy 85.94\n", + "Iteration 120 | Train Loss 0.3063 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.2625 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.2640 | Classifier Accuracy 87.50\n", + "Iteration 180 | Train Loss 0.2336 | Classifier Accuracy 89.06\n", + "Iteration 200 | Train Loss 0.1577 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.2150 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2410 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2833 | Accuracy 87.88 \n", + "Valid Loss Mean 0.2177 | Accuracy 90.43 \n", + "\n", + "seed : 888\n", + " ====================== epoch 15 ======================\n", + "Iteration 0 | Train Loss 0.3024 | Classifier Accuracy 89.06\n", + "Iteration 20 | Train Loss 0.2009 | Classifier Accuracy 90.62\n", + "Iteration 40 | Train Loss 0.2157 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.1735 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.3207 | Classifier Accuracy 89.06\n", + "Iteration 100 | Train Loss 0.2624 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.2733 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.2455 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.1793 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.2326 | Classifier Accuracy 92.19\n", + "Iteration 200 | Train Loss 0.3067 | Classifier Accuracy 87.50\n", + "Iteration 220 | Train Loss 0.3019 | Classifier Accuracy 85.94\n", + "Iteration 240 | Train Loss 0.2871 | Classifier Accuracy 84.38\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2609 | Accuracy 88.84 \n", + "Valid Loss Mean 0.3292 | Accuracy 86.06 \n", + "\n", + "seed : 888\n", + " ====================== epoch 16 ======================\n", + "Iteration 0 | Train Loss 0.3746 | Classifier Accuracy 78.12\n", + "Iteration 20 | Train Loss 0.2828 | Classifier Accuracy 87.50\n", + "Iteration 40 | Train Loss 0.3581 | Classifier Accuracy 85.94\n", + "Iteration 60 | Train Loss 0.2468 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.2494 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2247 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.3364 | Classifier Accuracy 87.50\n", + "Iteration 140 | Train Loss 0.2431 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.2293 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.1787 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.2969 | Classifier Accuracy 84.38\n", + "Iteration 220 | Train Loss 0.1649 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.1376 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2503 | Accuracy 89.69 \n", + "Valid Loss Mean 0.2233 | Accuracy 90.62 \n", + "\n", + "seed : 888\n", + " ====================== epoch 17 ======================\n", + "Iteration 0 | Train Loss 0.2665 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.1699 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.2095 | Classifier Accuracy 89.06\n", + "Iteration 60 | Train Loss 0.1712 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.2703 | Classifier Accuracy 85.94\n", + "Iteration 100 | Train Loss 0.2032 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.2580 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.2031 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.1909 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.2065 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.2700 | Classifier Accuracy 89.06\n", + "Iteration 220 | Train Loss 0.2958 | Classifier Accuracy 85.94\n", + "Iteration 240 | Train Loss 0.2388 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2275 | Accuracy 90.66 \n", + "Valid Loss Mean 0.2348 | Accuracy 90.00 \n", + "\n", + "seed : 888\n", + " ====================== epoch 18 ======================\n", + "Iteration 0 | Train Loss 0.1275 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.2610 | Classifier Accuracy 84.38\n", + "Iteration 40 | Train Loss 0.2115 | Classifier Accuracy 90.62\n", + "Iteration 60 | Train Loss 0.2350 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.1776 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2337 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.2855 | Classifier Accuracy 89.06\n", + "Iteration 140 | Train Loss 0.2460 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.1760 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.2827 | Classifier Accuracy 87.50\n", + "Iteration 200 | Train Loss 0.3619 | Classifier Accuracy 84.38\n", + "Iteration 220 | Train Loss 0.2333 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2634 | Classifier Accuracy 87.50\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2207 | Accuracy 90.81 \n", + "Valid Loss Mean 0.2339 | Accuracy 90.00 \n", + "\n", + "seed : 888\n", + " ====================== epoch 19 ======================\n", + "Iteration 0 | Train Loss 0.1867 | Classifier Accuracy 90.62\n", + "Iteration 20 | Train Loss 0.1649 | Classifier Accuracy 92.19\n", + "Iteration 40 | Train Loss 0.1078 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.1866 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.1881 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.2458 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1637 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.2708 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.1909 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1294 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.2035 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.0949 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1861 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.2072 | Accuracy 91.51 \n", + "Valid Loss Mean 0.1772 | Accuracy 92.19 \n", + "\n", + "seed : 888\n", + " ====================== epoch 20 ======================\n", + "Iteration 0 | Train Loss 0.1745 | Classifier Accuracy 87.50\n", + "Iteration 20 | Train Loss 0.1396 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1477 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.1611 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.1317 | Classifier Accuracy 92.19\n", + "Iteration 100 | Train Loss 0.2254 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.1046 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.2815 | Classifier Accuracy 87.50\n", + "Iteration 160 | Train Loss 0.1406 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.1571 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.2062 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1611 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.1401 | Classifier Accuracy 92.19\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1814 | Accuracy 92.65 \n", + "Valid Loss Mean 0.1763 | Accuracy 92.61 \n", + "\n", + "seed : 888\n", + " ====================== epoch 21 ======================\n", + "Iteration 0 | Train Loss 0.1187 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.2566 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.1225 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1950 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.1207 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.3046 | Classifier Accuracy 84.38\n", + "Iteration 120 | Train Loss 0.2085 | Classifier Accuracy 90.62\n", + "Iteration 140 | Train Loss 0.0560 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.2064 | Classifier Accuracy 90.62\n", + "Iteration 180 | Train Loss 0.1801 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.2264 | Classifier Accuracy 90.62\n", + "Iteration 220 | Train Loss 0.1537 | Classifier Accuracy 90.62\n", + "Iteration 240 | Train Loss 0.2327 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1781 | Accuracy 92.84 \n", + "Valid Loss Mean 0.1727 | Accuracy 92.68 \n", + "\n", + "seed : 888\n", + " ====================== epoch 22 ======================\n", + "Iteration 0 | Train Loss 0.1451 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1365 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.1129 | Classifier Accuracy 93.75\n", + "Iteration 60 | Train Loss 0.2008 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.2330 | Classifier Accuracy 90.62\n", + "Iteration 100 | Train Loss 0.2618 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.2069 | Classifier Accuracy 95.31\n", + "Iteration 140 | Train Loss 0.1757 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1507 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.1139 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.1402 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.2027 | Classifier Accuracy 89.06\n", + "Iteration 240 | Train Loss 0.1366 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1689 | Accuracy 93.24 \n", + "Valid Loss Mean 0.1925 | Accuracy 91.47 \n", + "\n", + "seed : 888\n", + " ====================== epoch 23 ======================\n", + "Iteration 0 | Train Loss 0.1723 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.1172 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.1168 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.1260 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.1779 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2871 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1616 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0604 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.1261 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0449 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.1144 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.1416 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0570 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1571 | Accuracy 93.69 \n", + "Valid Loss Mean 0.1985 | Accuracy 91.99 \n", + "\n", + "seed : 888\n", + " ====================== epoch 24 ======================\n", + "Iteration 0 | Train Loss 0.0943 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.1299 | Classifier Accuracy 93.75\n", + "Iteration 40 | Train Loss 0.0492 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.1671 | Classifier Accuracy 89.06\n", + "Iteration 80 | Train Loss 0.1437 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.2325 | Classifier Accuracy 90.62\n", + "Iteration 120 | Train Loss 0.1267 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.1464 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.2307 | Classifier Accuracy 89.06\n", + "Iteration 180 | Train Loss 0.0946 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.1474 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1649 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1674 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.1499 | Accuracy 94.08 \n", + "Valid Loss Mean 0.1664 | Accuracy 93.40 \n", + "\n", + "seed : 888\n", + " ====================== epoch 25 ======================\n", + "Iteration 0 | Train Loss 0.2044 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.2424 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.1483 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1619 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.1376 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0875 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1148 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1057 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0886 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1364 | Classifier Accuracy 90.62\n", + "Iteration 200 | Train Loss 0.1739 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.0869 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.1073 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1425 | Accuracy 94.39 \n", + "Valid Loss Mean 0.1477 | Accuracy 93.65 \n", + "\n", + "seed : 888\n", + " ====================== epoch 26 ======================\n", + "Iteration 0 | Train Loss 0.0937 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.2095 | Classifier Accuracy 89.06\n", + "Iteration 40 | Train Loss 0.0463 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0358 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0933 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1686 | Classifier Accuracy 93.75\n", + "Iteration 120 | Train Loss 0.0863 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1067 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.1423 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.2191 | Classifier Accuracy 89.06\n", + "Iteration 200 | Train Loss 0.1797 | Classifier Accuracy 92.19\n", + "Iteration 220 | Train Loss 0.0758 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.1306 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 48 s\n", + "Train Loss Mean 0.1327 | Accuracy 94.78 \n", + "Valid Loss Mean 0.1648 | Accuracy 93.08 \n", + "\n", + "seed : 888\n", + " ====================== epoch 27 ======================\n", + "Iteration 0 | Train Loss 0.1253 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0291 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1195 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.0900 | Classifier Accuracy 93.75\n", + "Iteration 80 | Train Loss 0.1487 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.1049 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0766 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.2470 | Classifier Accuracy 90.62\n", + "Iteration 160 | Train Loss 0.0727 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1719 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0993 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0707 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1867 | Classifier Accuracy 90.62\n", + "\n", + "[Summary] Elapsed time : 1 m 48 s\n", + "Train Loss Mean 0.1221 | Accuracy 95.38 \n", + "Valid Loss Mean 0.1444 | Accuracy 93.95 \n", + "\n", + "seed : 888\n", + " ====================== epoch 28 ======================\n", + "Iteration 0 | Train Loss 0.0793 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0572 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0737 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.1335 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0667 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1412 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0356 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0964 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0673 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0918 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.1458 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0879 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.1188 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 48 s\n", + "Train Loss Mean 0.1104 | Accuracy 95.56 \n", + "Valid Loss Mean 0.1669 | Accuracy 93.73 \n", + "\n", + "seed : 888\n", + " ====================== epoch 29 ======================\n", + "Iteration 0 | Train Loss 0.1182 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0430 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1421 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.2311 | Classifier Accuracy 90.62\n", + "Iteration 80 | Train Loss 0.0409 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.1814 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.0643 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0624 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0784 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1175 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.1549 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.1109 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0962 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 47 s\n", + "Train Loss Mean 0.1128 | Accuracy 95.60 \n", + "Valid Loss Mean 0.1528 | Accuracy 94.00 \n", + "\n", + "seed : 888\n", + " ====================== epoch 30 ======================\n", + "Iteration 0 | Train Loss 0.0987 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0741 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0892 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.1368 | Classifier Accuracy 92.19\n", + "Iteration 80 | Train Loss 0.2008 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.1185 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0680 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0904 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0894 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0776 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0196 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0227 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0751 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0950 | Accuracy 96.14 \n", + "Valid Loss Mean 0.2143 | Accuracy 92.61 \n", + "\n", + "seed : 888\n", + " ====================== epoch 31 ======================\n", + "Iteration 0 | Train Loss 0.2091 | Classifier Accuracy 92.19\n", + "Iteration 20 | Train Loss 0.0590 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.1149 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0752 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1238 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0599 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.2254 | Classifier Accuracy 92.19\n", + "Iteration 140 | Train Loss 0.0280 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0889 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.1294 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0538 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.1545 | Classifier Accuracy 92.19\n", + "Iteration 240 | Train Loss 0.1648 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.1002 | Accuracy 96.11 \n", + "Valid Loss Mean 0.1336 | Accuracy 94.32 \n", + "\n", + "seed : 888\n", + " ====================== epoch 32 ======================\n", + "Iteration 0 | Train Loss 0.0503 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0756 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0878 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0136 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.1590 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0977 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0655 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0918 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0782 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0588 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0725 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0106 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.1319 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0878 | Accuracy 96.54 \n", + "Valid Loss Mean 0.1532 | Accuracy 94.35 \n", + "\n", + "seed : 888\n", + " ====================== epoch 33 ======================\n", + "Iteration 0 | Train Loss 0.0583 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0307 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1428 | Classifier Accuracy 92.19\n", + "Iteration 60 | Train Loss 0.0729 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0824 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0558 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0680 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0519 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1113 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.1061 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0272 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0585 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0640 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0840 | Accuracy 96.72 \n", + "Valid Loss Mean 0.1359 | Accuracy 94.62 \n", + "\n", + "seed : 888\n", + " ====================== epoch 34 ======================\n", + "Iteration 0 | Train Loss 0.0392 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0837 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.1074 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0980 | Classifier Accuracy 95.31\n", + "Iteration 80 | Train Loss 0.1322 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.1781 | Classifier Accuracy 92.19\n", + "Iteration 120 | Train Loss 0.0727 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0908 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.1286 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0924 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.1034 | Classifier Accuracy 93.75\n", + "Iteration 220 | Train Loss 0.0334 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.1627 | Classifier Accuracy 93.75\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0778 | Accuracy 97.03 \n", + "Valid Loss Mean 0.1389 | Accuracy 94.89 \n", + "\n", + "seed : 888\n", + " ====================== epoch 35 ======================\n", + "Iteration 0 | Train Loss 0.1425 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0800 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0614 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.1001 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0725 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0986 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0873 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.1070 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0725 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0569 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0327 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0437 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0838 | Classifier Accuracy 95.31\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0709 | Accuracy 97.21 \n", + "Valid Loss Mean 0.1366 | Accuracy 95.04 \n", + "\n", + "seed : 888\n", + " ====================== epoch 36 ======================\n", + "Iteration 0 | Train Loss 0.0494 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0721 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0488 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0162 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0580 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0380 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0212 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0429 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1523 | Classifier Accuracy 92.19\n", + "Iteration 180 | Train Loss 0.0110 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0467 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0629 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0762 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0661 | Accuracy 97.55 \n", + "Valid Loss Mean 0.1308 | Accuracy 95.16 \n", + "\n", + "seed : 888\n", + " ====================== epoch 37 ======================\n", + "Iteration 0 | Train Loss 0.0733 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0232 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0338 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0669 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0917 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0231 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0619 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0686 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0472 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0349 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0246 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.1313 | Classifier Accuracy 93.75\n", + "Iteration 240 | Train Loss 0.0481 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0652 | Accuracy 97.55 \n", + "Valid Loss Mean 0.1318 | Accuracy 95.21 \n", + "\n", + "seed : 888\n", + " ====================== epoch 38 ======================\n", + "Iteration 0 | Train Loss 0.0301 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0431 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0448 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0145 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.1532 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0950 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0276 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0130 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0261 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0862 | Classifier Accuracy 93.75\n", + "Iteration 200 | Train Loss 0.0590 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.1227 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0145 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0633 | Accuracy 97.43 \n", + "Valid Loss Mean 0.1308 | Accuracy 95.31 \n", + "\n", + "seed : 888\n", + " ====================== epoch 39 ======================\n", + "Iteration 0 | Train Loss 0.0108 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.1089 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0592 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0461 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0406 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0525 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.1000 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1466 | Classifier Accuracy 93.75\n", + "Iteration 160 | Train Loss 0.0451 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0715 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0315 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0884 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0423 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0619 | Accuracy 97.64 \n", + "Valid Loss Mean 0.1236 | Accuracy 95.71 \n", + "\n", + "seed : 888\n", + " ====================== epoch 40 ======================\n", + "Iteration 0 | Train Loss 0.0324 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0105 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0117 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0195 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0270 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0171 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0205 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0305 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0657 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0516 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0411 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0947 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0305 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0527 | Accuracy 97.95 \n", + "Valid Loss Mean 0.1387 | Accuracy 95.34 \n", + "\n", + "seed : 888\n", + " ====================== epoch 41 ======================\n", + "Iteration 0 | Train Loss 0.0074 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0376 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0268 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0061 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0565 | Classifier Accuracy 96.88\n", + "Iteration 100 | Train Loss 0.0152 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0276 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0191 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1486 | Classifier Accuracy 93.75\n", + "Iteration 180 | Train Loss 0.0930 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0231 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0202 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0403 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0485 | Accuracy 98.17 \n", + "Valid Loss Mean 0.1254 | Accuracy 95.59 \n", + "\n", + "seed : 888\n", + " ====================== epoch 42 ======================\n", + "Iteration 0 | Train Loss 0.0242 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.2116 | Classifier Accuracy 95.31\n", + "Iteration 40 | Train Loss 0.0992 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0396 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0526 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0118 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.1109 | Classifier Accuracy 93.75\n", + "Iteration 140 | Train Loss 0.0499 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0562 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0642 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0277 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0192 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0170 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0467 | Accuracy 98.26 \n", + "Valid Loss Mean 0.1416 | Accuracy 95.26 \n", + "\n", + "seed : 888\n", + " ====================== epoch 43 ======================\n", + "Iteration 0 | Train Loss 0.0680 | Classifier Accuracy 95.31\n", + "Iteration 20 | Train Loss 0.0105 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0858 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0311 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0211 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0067 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0395 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.1100 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0132 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0540 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0297 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0111 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0155 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0418 | Accuracy 98.46 \n", + "Valid Loss Mean 0.1328 | Accuracy 95.54 \n", + "\n", + "seed : 888\n", + " ====================== epoch 44 ======================\n", + "Iteration 0 | Train Loss 0.0302 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0519 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0829 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0792 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.0027 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0096 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0567 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0261 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.1144 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0503 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0129 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0067 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0341 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0472 | Accuracy 98.25 \n", + "Valid Loss Mean 0.1389 | Accuracy 95.51 \n", + "\n", + "seed : 888\n", + " ====================== epoch 45 ======================\n", + "Iteration 0 | Train Loss 0.0170 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0959 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0173 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0054 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.1318 | Classifier Accuracy 93.75\n", + "Iteration 100 | Train Loss 0.0781 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0632 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0107 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0725 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0277 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0263 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0423 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0192 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0401 | Accuracy 98.41 \n", + "Valid Loss Mean 0.1270 | Accuracy 95.46 \n", + "\n", + "seed : 888\n", + " ====================== epoch 46 ======================\n", + "Iteration 0 | Train Loss 0.0292 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0437 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0236 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0079 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0471 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0824 | Classifier Accuracy 95.31\n", + "Iteration 120 | Train Loss 0.0835 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0998 | Classifier Accuracy 95.31\n", + "Iteration 160 | Train Loss 0.0523 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0246 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0603 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0239 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0230 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0412 | Accuracy 98.42 \n", + "Valid Loss Mean 0.1216 | Accuracy 95.71 \n", + "\n", + "seed : 888\n", + " ====================== epoch 47 ======================\n", + "Iteration 0 | Train Loss 0.0347 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0104 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0148 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0233 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.1281 | Classifier Accuracy 95.31\n", + "Iteration 100 | Train Loss 0.0449 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0166 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0289 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0408 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0143 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0309 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0578 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0509 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0389 | Accuracy 98.56 \n", + "Valid Loss Mean 0.1276 | Accuracy 95.61 \n", + "\n", + "seed : 888\n", + " ====================== epoch 48 ======================\n", + "Iteration 0 | Train Loss 0.0550 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0381 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0722 | Classifier Accuracy 95.31\n", + "Iteration 60 | Train Loss 0.0144 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0442 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0513 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0036 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0445 | Classifier Accuracy 96.88\n", + "Iteration 160 | Train Loss 0.0949 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0836 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0997 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0331 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0065 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0394 | Accuracy 98.46 \n", + "Valid Loss Mean 0.1261 | Accuracy 95.59 \n", + "\n", + "seed : 888\n", + " ====================== epoch 49 ======================\n", + "Iteration 0 | Train Loss 0.0106 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0032 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.1245 | Classifier Accuracy 96.88\n", + "Iteration 60 | Train Loss 0.0050 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0192 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0079 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0186 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0141 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0052 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0268 | Classifier Accuracy 98.44\n", + "Iteration 200 | Train Loss 0.0491 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0105 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0377 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0372 | Accuracy 98.64 \n", + "Valid Loss Mean 0.1291 | Accuracy 95.61 \n", + "\n", + "seed : 888\n", + " ====================== epoch 50 ======================\n", + "Iteration 0 | Train Loss 0.0039 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0090 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0423 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0165 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0061 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0269 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0909 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0298 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0728 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0557 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0020 | Classifier Accuracy 100.00\n", + "Iteration 220 | Train Loss 0.0098 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0438 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0375 | Accuracy 98.58 \n", + "Valid Loss Mean 0.1278 | Accuracy 95.73 \n", + "\n", + "seed : 888\n", + " ====================== epoch 51 ======================\n", + "Iteration 0 | Train Loss 0.0769 | Classifier Accuracy 93.75\n", + "Iteration 20 | Train Loss 0.0643 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0176 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0963 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0061 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0512 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0699 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0127 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0451 | Classifier Accuracy 96.88\n", + "Iteration 180 | Train Loss 0.0157 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0320 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0466 | Classifier Accuracy 96.88\n", + "Iteration 240 | Train Loss 0.0243 | Classifier Accuracy 98.44\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0395 | Accuracy 98.48 \n", + "Valid Loss Mean 0.1270 | Accuracy 95.63 \n", + "\n", + "seed : 888\n", + " ====================== epoch 52 ======================\n", + "Iteration 0 | Train Loss 0.0046 | Classifier Accuracy 100.00\n", + "Iteration 20 | Train Loss 0.0154 | Classifier Accuracy 100.00\n", + "Iteration 40 | Train Loss 0.0071 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0615 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0262 | Classifier Accuracy 100.00\n", + "Iteration 100 | Train Loss 0.0175 | Classifier Accuracy 100.00\n", + "Iteration 120 | Train Loss 0.0326 | Classifier Accuracy 98.44\n", + "Iteration 140 | Train Loss 0.0393 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.1215 | Classifier Accuracy 95.31\n", + "Iteration 180 | Train Loss 0.0940 | Classifier Accuracy 95.31\n", + "Iteration 200 | Train Loss 0.0709 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0448 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0170 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0393 | Accuracy 98.53 \n", + "Valid Loss Mean 0.1283 | Accuracy 95.63 \n", + "\n", + "seed : 888\n", + " ====================== epoch 53 ======================\n", + "Iteration 0 | Train Loss 0.1065 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0221 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0313 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0104 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0605 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0495 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0427 | Classifier Accuracy 96.88\n", + "Iteration 140 | Train Loss 0.0260 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0170 | Classifier Accuracy 98.44\n", + "Iteration 180 | Train Loss 0.0116 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0273 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0231 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0504 | Classifier Accuracy 96.88\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0407 | Accuracy 98.56 \n", + "Valid Loss Mean 0.1299 | Accuracy 95.71 \n", + "\n", + "seed : 888\n", + " ====================== epoch 54 ======================\n", + "Iteration 0 | Train Loss 0.0401 | Classifier Accuracy 98.44\n", + "Iteration 20 | Train Loss 0.0162 | Classifier Accuracy 98.44\n", + "Iteration 40 | Train Loss 0.0140 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0251 | Classifier Accuracy 100.00\n", + "Iteration 80 | Train Loss 0.0244 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0270 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0121 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0236 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0166 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.1258 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0230 | Classifier Accuracy 98.44\n", + "Iteration 220 | Train Loss 0.0782 | Classifier Accuracy 95.31\n", + "Iteration 240 | Train Loss 0.0153 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0424 | Accuracy 98.49 \n", + "Valid Loss Mean 0.1285 | Accuracy 95.63 \n", + "\n", + "seed : 888\n", + " ====================== epoch 55 ======================\n", + "Iteration 0 | Train Loss 0.0379 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0736 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0204 | Classifier Accuracy 100.00\n", + "Iteration 60 | Train Loss 0.0458 | Classifier Accuracy 98.44\n", + "Iteration 80 | Train Loss 0.1103 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0506 | Classifier Accuracy 96.88\n", + "Iteration 120 | Train Loss 0.0098 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0093 | Classifier Accuracy 100.00\n", + "Iteration 160 | Train Loss 0.0079 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0049 | Classifier Accuracy 100.00\n", + "Iteration 200 | Train Loss 0.0817 | Classifier Accuracy 95.31\n", + "Iteration 220 | Train Loss 0.0060 | Classifier Accuracy 100.00\n", + "Iteration 240 | Train Loss 0.0154 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 46 s\n", + "Train Loss Mean 0.0371 | Accuracy 98.59 \n", + "Valid Loss Mean 0.1281 | Accuracy 95.63 \n", + "\n", + "seed : 888\n", + " ====================== epoch 56 ======================\n", + "Iteration 0 | Train Loss 0.0744 | Classifier Accuracy 96.88\n", + "Iteration 20 | Train Loss 0.0678 | Classifier Accuracy 96.88\n", + "Iteration 40 | Train Loss 0.0489 | Classifier Accuracy 98.44\n", + "Iteration 60 | Train Loss 0.0475 | Classifier Accuracy 96.88\n", + "Iteration 80 | Train Loss 0.0293 | Classifier Accuracy 98.44\n", + "Iteration 100 | Train Loss 0.0423 | Classifier Accuracy 98.44\n", + "Iteration 120 | Train Loss 0.0082 | Classifier Accuracy 100.00\n", + "Iteration 140 | Train Loss 0.0342 | Classifier Accuracy 98.44\n", + "Iteration 160 | Train Loss 0.0161 | Classifier Accuracy 100.00\n", + "Iteration 180 | Train Loss 0.0509 | Classifier Accuracy 96.88\n", + "Iteration 200 | Train Loss 0.0611 | Classifier Accuracy 96.88\n", + "Iteration 220 | Train Loss 0.0343 | Classifier Accuracy 98.44\n", + "Iteration 240 | Train Loss 0.0100 | Classifier Accuracy 100.00\n", + "\n", + "[Summary] Elapsed time : 1 m 45 s\n", + "Train Loss Mean 0.0387 | Accuracy 98.58 \n", + "Valid Loss Mean 0.1319 | Accuracy 95.63 \n", + "\n", + "EARLY STOPPING!!\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "KubZ_LvlbwG0", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 298 + }, + "outputId": "7aa0ab8c-4948-4020-abc8-2443e84d407c" + }, + "source": [ + "fig, (ax1, ax2) = plt.subplots(2, sharex=True)\n", + "ax1.plot(final_train_loss)\n", + "ax1.plot(final_valid_loss)\n", + "ax1.legend(['train', 'valid'])\n", + "ax1.set_title('Loss')\n", + "\n", + "ax2.plot(final_train_acc)\n", + "ax2.plot(final_valid_acc)\n", + "ax2.legend(['train', 'valid'])\n", + "ax2.set_title('Accuracy')" + ], + "execution_count": 24, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Accuracy')" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 24 + }, + { + "output_type": "display_data", + "data": { + "image/png": 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\n", 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" + ], + "text/plain": [ + " image label\n", + "0 test14200.jpg NaN\n", + "1 test12178.jpg NaN\n", + "2 test12713.jpg NaN\n", + "3 test13712.jpg NaN\n", + "4 test11739.jpg NaN" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 25 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "lxVAE_sjHRbM" + }, + "source": [ + "test_dataset = TestDataset(submission['image'], transforms_val)\n", + "test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False, num_workers=8)" + ], + "execution_count": 26, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nrJb1PCBNBWC" + }, + "source": [ + "## 앙상블 - soft voting" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Fyqjg7sJNAgn" + }, + "source": [ + "import numpy as np\n", + "# softmax_0: 0으로 분류할 확률\n", + "def softmax_0(score0, score1) :\n", + " exp_a0 = np.exp(score0)\n", + " exp_a1 = np.exp(score1)\n", + " sum_exp = exp_a0+exp_a1\n", + " y = exp_a0 / sum_exp\n", + " return y\n", + "\n", + "# ensemble 시 threshold 설정을 위해 모든 score를 probability로 변환" + ], + "execution_count": 27, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "r8YFXYIxyuiW" + }, + "source": [ + "prob_zero = [0 for _ in range(5000)]\n", + "prob_zero_35 = [0 for _ in range(5000)]\n", + "\n", + "n = len(best_models)\n", + "\n", + "for model in best_models:\n", + " model.to(device)\n", + " model.eval() # model load 후, inference를 위한 eval 모드로 다시 설정\n", + "\n", + " predictions = []\n", + " files = []\n", + " score_list = []\n", + "\n", + " with torch.no_grad():\n", + " for img_names, images in test_loader:\n", + " images = images.to(device=device, dtype=dtype)\n", + " scores = model(images)\n", + " _, preds = scores.max(dim=1)\n", + " \n", + " files.extend(img_names)\n", + " predictions.extend(preds.squeeze(0).detach().cpu().numpy())\n", + " score_list.extend(scores.squeeze(0).detach().cpu().numpy()) ## score 형태 그대로 리스트에 저장/ 형태 [[3.XXXXXX, -3.XXXXXX], [..], ...]\n", + "\n", + " for i, score in enumerate(score_list):\n", + " prob_zero[i] += softmax_0(score[0], score[1])\n", + "\n", + "for i in range(5000):\n", + " prob_zero[i] /= n\n", + " prob_zero_35[i] = (prob_zero[i]<0.35)*1" + ], + "execution_count": 39, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "A0-s9pS0Hew8" + }, + "source": [ + "ensemble_sub = pd.DataFrame(columns=submission.columns)\n", + "ensemble_sub['image'] = files\n", + "ensemble_sub['label'] = prob_zero_35" + ], + "execution_count": 35, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "TBvSh_voHf7t" + }, + "source": [ + "ensemble_sub.to_csv(\"./submission_group1.csv\", index=False)" + ], + "execution_count": 36, + "outputs": [] + } + ] +} \ No newline at end of file