6712 lines (6711 with data), 1.6 MB
{
"cells": [
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"id": "VGCYrVKDW2k6"
},
"outputs": [],
"source": [
"# For tips on running notebooks in Google Colab, see\n",
"# https://pytorch.org/tutorials/beginner/colab\n",
"%matplotlib inline\n",
"# from google.colab import drive\n",
"# drive.mount('/content/gdrive/', force_remount=True)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "RiiUBIxUW2k9"
},
"source": [
"\n",
"# Transfer Learning for Computer Vision Tutorial\n",
"**Author**: [Sasank Chilamkurthy](https://chsasank.github.io)\n",
"\n",
"In this tutorial, you will learn how to train a convolutional neural network for\n",
"image classification using transfer learning. You can read more about the transfer\n",
"learning at [cs231n notes](https://cs231n.github.io/transfer-learning/)_\n",
"\n",
"Quoting these notes,\n",
"\n",
" In practice, very few people train an entire Convolutional Network\n",
" from scratch (with random initialization), because it is relatively\n",
" rare to have a dataset of sufficient size. Instead, it is common to\n",
" pretrain a ConvNet on a very large dataset (e.g. ImageNet, which\n",
" contains 1.2 million images with 1000 categories), and then use the\n",
" ConvNet either as an initialization or a fixed feature extractor for\n",
" the task of interest.\n",
"\n",
"These two major transfer learning scenarios look as follows:\n",
"\n",
"- **Finetuning the ConvNet**: Instead of random initialization, we\n",
" initialize the network with a pretrained network, like the one that is\n",
" trained on imagenet 1000 dataset. Rest of the training looks as\n",
" usual.\n",
"- **ConvNet as fixed feature extractor**: Here, we will freeze the weights\n",
" for all of the network except that of the final fully connected\n",
" layer. This last fully connected layer is replaced with a new one\n",
" with random weights and only this layer is trained.\n"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "XyEZTo0NW2k_",
"outputId": "57b83942-f360-489b-bfe2-caf79e66d4ab"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1688180207.494784\n",
"Sat Jul 1 02:56:47 2023\n"
]
}
],
"source": [
"# License: BSD\n",
"# Author: Sasank Chilamkurthy\n",
"\n",
"from __future__ import print_function, division\n",
"\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.optim as optim\n",
"from torch.optim import lr_scheduler\n",
"import torch.backends.cudnn as cudnn\n",
"import numpy as np\n",
"import torchvision\n",
"from torchvision import datasets, models, transforms\n",
"import matplotlib.pyplot as plt\n",
"import time\n",
"import os\n",
"import copy\n",
"\n",
"cudnn.benchmark = True\n",
"plt.ion() # interactive mode\n",
"\n",
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "iehYC9-cW2lA"
},
"source": [
"## Load Data\n",
"\n",
"We will use torchvision and torch.utils.data packages for loading the\n",
"data.\n",
"\n",
"The problem we're going to solve today is to train a model to classify\n",
"**ants** and **bees**. We have about 120 training images each for ants and bees.\n",
"There are 75 validation images for each class. Usually, this is a very\n",
"small dataset to generalize upon, if trained from scratch. Since we\n",
"are using transfer learning, we should be able to generalize reasonably\n",
"well.\n",
"\n",
"This dataset is a very small subset of imagenet.\n",
"\n",
".. Note ::\n",
" Download the data from\n",
" [here](https://download.pytorch.org/tutorial/hymenoptera_data.zip)\n",
" and extract it to the current directory.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"id": "7UvqjeCdW2lA"
},
"outputs": [],
"source": [
"# Data augmentation and normalization for training\n",
"# Just normalization for validation\n",
"data_transforms = {\n",
" 'train': transforms.Compose([\n",
" transforms.RandomResizedCrop(224),\n",
" transforms.RandomHorizontalFlip(),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
" ]),\n",
" 'val': transforms.Compose([\n",
" transforms.Resize(256),\n",
" transforms.CenterCrop(224),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
" ]),\n",
"}\n",
"\n",
"data_dir = '/content/gdrive/MyDrive/Colab Notebooks/data/44 Class 4478 Brain Tumor Images Split 0.627 Shuffle Rename'\n",
"image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
" data_transforms[x])\n",
" for x in ['train', 'val']}\n",
"dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=17,\n",
" shuffle=True, num_workers=2)\n",
" for x in ['train', 'val']}\n",
"dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}\n",
"class_names = image_datasets['train'].classes\n",
"\n",
"device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "MFDw_v0wW2lA"
},
"source": [
"### Visualize a few images\n",
"Let's visualize a few training images so as to understand the data\n",
"augmentations.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 198
},
"id": "tceMTgC6W2lB",
"outputId": "5c4cf0b3-1bed-479c-fe71-71928b0e6717"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"def imshow(inp, title=None):\n",
" \"\"\"Display image for Tensor.\"\"\"\n",
" inp = inp.numpy().transpose((1, 2, 0))\n",
" mean = np.array([0.485, 0.456, 0.406])\n",
" std = np.array([0.229, 0.224, 0.225])\n",
" inp = std * inp + mean\n",
" inp = np.clip(inp, 0, 1)\n",
" plt.imshow(inp)\n",
" if title is not None:\n",
" plt.title(title)\n",
" plt.pause(0.001) # pause a bit so that plots are updated\n",
"\n",
"\n",
"# Get a batch of training data\n",
"inputs, classes = next(iter(dataloaders['train']))\n",
"\n",
"# Make a grid from batch\n",
"out = torchvision.utils.make_grid(inputs)\n",
"\n",
"imshow(out, title=[class_names[x] for x in classes])"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mq3LbRiQW2lB"
},
"source": [
"## Training the model\n",
"\n",
"Now, let's write a general function to train a model. Here, we will\n",
"illustrate:\n",
"\n",
"- Scheduling the learning rate\n",
"- Saving the best model\n",
"\n",
"In the following, parameter ``scheduler`` is an LR scheduler object from\n",
"``torch.optim.lr_scheduler``.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"id": "utSazWwYW2lC"
},
"outputs": [],
"source": [
"import time\n",
"import copy\n",
"from sklearn.metrics import confusion_matrix\n",
"\n",
"def train_model(model, criterion, optimizer, scheduler, num_epochs=30):\n",
" since = time.time()\n",
"\n",
" best_model_wts = copy.deepcopy(model.state_dict())\n",
" best_acc = 0.0\n",
"\n",
" for epoch in range(num_epochs):\n",
" print(f'Epoch {epoch}/{num_epochs - 1}')\n",
" print('-' * 10)\n",
"\n",
" # Each epoch has a training and validation phase\n",
" for phase in ['train', 'val']:\n",
" if phase == 'train':\n",
" model.train() # Set model to training mode\n",
" else:\n",
" model.eval() # Set model to evaluate mode\n",
"\n",
" running_loss = 0.0\n",
" running_corrects = 0\n",
" all_labels = []\n",
" all_preds = []\n",
"\n",
" # Iterate over data.\n",
" for inputs, labels in dataloaders[phase]:\n",
" inputs = inputs.to(device)\n",
" labels = labels.to(device)\n",
"\n",
" # zero the parameter gradients\n",
" optimizer.zero_grad()\n",
"\n",
" # forward\n",
" # track history if only in train\n",
" with torch.set_grad_enabled(phase == 'train'):\n",
" outputs = model(inputs)\n",
" _, preds = torch.max(outputs, 1)\n",
" loss = criterion(outputs, labels)\n",
"\n",
" # backward + optimize only if in training phase\n",
" if phase == 'train':\n",
" loss.backward()\n",
" optimizer.step()\n",
"\n",
" # statistics\n",
" running_loss += loss.item() * inputs.size(0)\n",
" running_corrects += torch.sum(preds == labels.data)\n",
" all_labels.extend(labels.data.cpu().numpy())\n",
" all_preds.extend(preds.cpu().numpy())\n",
"\n",
" if phase == 'train':\n",
" scheduler.step()\n",
"\n",
" epoch_loss = running_loss / dataset_sizes[phase]\n",
" epoch_acc = running_corrects.double() / dataset_sizes[phase]\n",
"\n",
" print(f'{phase} Loss: {epoch_loss:.4f} Acc: {epoch_acc:.4f}')\n",
"\n",
" # Calculate confusion matrix\n",
" np.set_printoptions(threshold=44*44, linewidth=1000)\n",
" cm = confusion_matrix(all_labels, all_preds)\n",
" print(f'Confusion Matrix:\\n{cm}')\n",
"\n",
" # deep copy the model\n",
" if phase == 'val' and epoch_acc > best_acc:\n",
" best_acc = epoch_acc\n",
" best_model_wts = copy.deepcopy(model.state_dict())\n",
"\n",
" print()\n",
"\n",
" time_elapsed = time.time() - since\n",
" print(f'Training complete in {time_elapsed // 60:.0f}m {time_elapsed % 60:.0f}s')\n",
" print(f'Best val Acc: {best_acc:4f}')\n",
"\n",
" # load best model weights\n",
" model.load_state_dict(best_model_wts)\n",
" return model"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "h09FnkFVW2lC"
},
"source": [
"### Visualizing the model predictions\n",
"\n",
"Generic function to display predictions for a few images\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"id": "MVpCbBziW2lC"
},
"outputs": [],
"source": [
"def visualize_model(model, num_images=6):\n",
" was_training = model.training\n",
" model.eval()\n",
" images_so_far = 0\n",
" fig = plt.figure()\n",
"\n",
" with torch.no_grad():\n",
" for i, (inputs, labels) in enumerate(dataloaders['val']):\n",
" inputs = inputs.to(device)\n",
" labels = labels.to(device)\n",
"\n",
" outputs = model(inputs)\n",
" _, preds = torch.max(outputs, 1)\n",
"\n",
" for j in range(inputs.size()[0]):\n",
" images_so_far += 1\n",
" ax = plt.subplot(num_images//2, 2, images_so_far)\n",
" ax.axis('off')\n",
" ax.set_title(f'predicted: {class_names[preds[j]]}')\n",
" imshow(inputs.cpu().data[j])\n",
"\n",
" if images_so_far == num_images:\n",
" model.train(mode=was_training)\n",
" return\n",
" model.train(mode=was_training)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "LxC7G961W2lD"
},
"source": [
"## Finetuning the ConvNet\n",
"\n",
"Load a pretrained model and reset final fully connected layer.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"id": "d0DTgqMvW2lD"
},
"outputs": [],
"source": [
"model_ft = models.resnet18(weights='IMAGENET1K_V1')\n",
"num_ftrs = model_ft.fc.in_features\n",
"# Here the size of each output sample is set to 2.\n",
"# Alternatively, it can be generalized to ``nn.Linear(num_ftrs, len(class_names))``.\n",
"model_ft.fc = nn.Linear(num_ftrs, 44)\n",
"\n",
"model_ft = model_ft.to(device)\n",
"\n",
"criterion = nn.CrossEntropyLoss()\n",
"\n",
"# Observe that all parameters are being optimized\n",
"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.93) #, weight_decay=0.01\n",
"\n",
"# Decay LR by a factor of 0.1 every 7 epochs\n",
"exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)"
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"id": "YRwm8Zp116Se",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "f1918948-1674-403f-b6e9-d2f61b6693ed"
},
"execution_count": 47,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1688180209.156119\n",
"Sat Jul 1 02:56:49 2023\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "asgAWJjkW2lD"
},
"source": [
"### Train and evaluate\n",
"\n",
"It should take around 15-25 min on CPU. On GPU though, it takes less than a\n",
"minute.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"id": "RX6GdXXJW2lE",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "70e895e6-bf69-4b58-cf3c-c8021a4dd5bb"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 0/29\n",
"----------\n",
"train Loss: 2.8423 Acc: 0.2686\n",
"Confusion Matrix:\n",
"[[ 15 6 0 1 4 0 2 0 0 5 0 0 0 0 0 0 1 0 0 0 0 0 0 0 19 11 2 33 1 1 1 0 1 0 0 0 0 0 2 2 3 0 0 0]\n",
" [ 7 37 0 0 2 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 40 1 10 2 5 8 0 0 0 0 0 4 1 0 10 1 0 1 0]\n",
" [ 1 2 18 1 0 0 0 0 0 2 0 0 0 2 0 0 0 1 0 0 0 0 0 0 5 6 24 3 24 0 0 4 0 0 0 0 1 0 3 5 5 0 0 0]\n",
" [ 0 1 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 6 0 14 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 30 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 12 1 2 0 2 3 0 0 0 0 0 1 0 2 0 0 0 0 0]\n",
" [ 0 1 3 0 2 6 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 6 0 18 1 3 0 0 3 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 10 0 4 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 1 0 1 0 2 0 0 0 0 0 1 0 2 6 0 0 0 0]\n",
" [ 0 2 6 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 3 4 2 7 0 0 0 0 0 0 0 0 0 3 1 4 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 1 4 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 1 6 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 14 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 7 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 4 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 10 5 0 7 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 16 0 0 2 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0 0 0 0 0 5 20 0 6 2 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0]\n",
" [ 1 2 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 16 0 9 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 1 0 0 0 0 0 0 0 0 0 7 2 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 1 0 0 0 0 0 0 0 0 0 0 0 4 5 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 0 0 0 0 0 0 0 2 0 0 0 4 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 2 1 0 0 0 0 0 0 0 0 0 0 3 1 0 1 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 10 2 0 5 0 0 0 0 0 0 0 1 0 3 13 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 2 5 0 1 0 0 0 0 0 0 0 2 5 1 0 0 0]\n",
" [ 8 5 2 1 5 0 1 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 74 29 2 22 2 3 4 0 1 0 0 0 1 0 3 2 0 0 1 0]\n",
" [ 3 29 0 2 3 0 0 0 0 5 0 0 0 0 0 0 1 0 0 0 1 0 0 0 36 113 6 4 3 1 9 0 0 0 0 0 2 1 5 6 0 0 1 0]\n",
" [ 0 6 11 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 11 42 8 53 0 2 7 0 0 0 0 0 0 0 2 2 0 0 0]\n",
" [ 6 4 0 2 1 0 1 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 6 1 96 8 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0]\n",
" [ 0 1 8 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 3 5 28 6 106 0 2 0 0 0 0 0 0 0 1 3 3 0 1 0]\n",
" [ 5 2 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 9 1 9 0 11 10 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 3 5 1 0 5 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 37 2 3 2 0 69 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 1 0 14 0 2 0 0 0 0 2 0 0 0 1 0 0 1 0 0 0 0 0 0 0 6 9 14 2 2 0 2 8 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 5 1 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 7 0 16 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 14 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 13 0 2 0 0 2 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 13 2 20 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 1 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 8 8 0 4 2 2 2 0 0 0 0 0 2 0 2 3 1 0 0 0]\n",
" [ 0 6 1 0 3 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 14 0 4 1 0 9 0 0 0 0 0 13 0 2 8 2 0 0 0]\n",
" [ 0 3 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 4 3 3 7 0 1 1 0 0 0 0 1 0 2 3 6 0 0 0]\n",
" [ 1 4 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 17 0 6 3 0 1 0 0 0 0 0 0 0 29 14 5 0 2 0]\n",
" [ 3 5 3 1 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 18 1 8 4 0 6 0 0 0 0 0 4 0 9 48 2 0 1 0]\n",
" [ 0 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 11 2 9 0 2 0 0 0 0 0 0 0 2 9 25 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 0 0 7 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 0 5 1 0 2 0 0 0 0 0 1 0 2 22 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 6 1 5 0 0 0 0 0 0 0 0 0 2 3 1 0 0 0]]\n",
"val Loss: 1.8593 Acc: 0.5063\n",
"Confusion Matrix:\n",
"[[ 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 18 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0]\n",
" [ 0 43 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 6 20 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0]\n",
" [ 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 7 0 0 4 0 0 0 0 0 0 0 3 14 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 5 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 3 11 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 4 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 0 0 0 0 0 0 0 0 0 1 0 0 19 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 10 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 87 0 0 12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 98 1 1 0 0 0 0 0 0 0 0 0 0 1 13 1 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 70 0 2 0 0 2 0 0 0 0 0 0 0 0 9 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 79 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 14 0 74 0 0 0 0 0 0 0 0 0 0 2 10 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 1 0 0 0 6 8 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 4 1 0 0 0 0 70 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 26 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 5 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 3 0 0 1 0 0 0 0 0 1 0 0 6 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 19 0 0 16 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 0 0 1 0 0 0 0 1 0 0 4 9 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 6 0 0 0 0 0 0 0 0 0 0 34 11 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 69 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 3 41 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0]]\n",
"\n",
"Epoch 1/29\n",
"----------\n",
"train Loss: 1.8365 Acc: 0.4898\n",
"Confusion Matrix:\n",
"[[ 48 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 8 0 19 0 5 0 0 3 1 0 2 0 0 4 1 0 0 0 0]\n",
" [ 2 66 1 0 3 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 3 1 9 31 1 3 0 2 5 0 1 0 0 0 0 0 0 12 0 0 1 0]\n",
" [ 1 1 42 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 18 0 0 9 0 0 0 0 0 0 1 1 7 0 0 0]\n",
" [ 2 0 0 31 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 0 0 1 57 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 3 0 0 1 0 0 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 4 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 6 0 3 0 0 0 0 0 1 0 0 5 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 9 0 1 0 0 1 1 0 0 0 1 0 0 1 8 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 6 0 5 0 0 2 0 0 0 0 0 0 1 0 11 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 1 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 1 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 11 1 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 3 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 15 0 0 6 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 3 12 0 0 0 1 5 0 0 1 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 10 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 0 1 0 1 9 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 1 1 0 0 0 0 0 0 0 2 2 1 5 2 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 14 0 0 9 0 0 2 0 0 0 0 0 0 1 2 0 1 9 0 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 5 0 0 0 0 0 0 0 0 1 1 2 6 0 1 0]\n",
" [ 7 0 0 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 109 20 0 13 0 4 1 0 4 1 0 0 0 0 4 2 0 0 0 0]\n",
" [ 0 25 2 0 1 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 17 156 2 2 3 1 5 0 1 1 0 0 5 0 2 4 0 0 1 0]\n",
" [ 0 1 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 76 1 27 0 0 9 0 0 0 0 1 0 0 1 6 0 0 0]\n",
" [ 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 8 1 0 130 1 0 0 0 3 0 0 0 1 0 4 1 0 0 0 0]\n",
" [ 0 1 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 20 0 128 0 0 0 0 0 1 0 1 1 1 2 4 0 0 0]\n",
" [ 5 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 1 0 1 0 41 9 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 11 0 0 0 3 109 0 0 0 0 0 5 0 0 2 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 2 0 0 39 0 0 2 0 0 0 0 0 3 0 0 0]\n",
" [ 8 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 14 0 2 0 0 15 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 3 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 13 0 0 0 0 1 0 1 6 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 1 17 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0]\n",
" [ 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 12 3 0 0 1 2 1 0 0 0 0 2 1 1 6 1 1 0 0 0]\n",
" [ 1 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 11 0 0 0 1 0 0 0 0 0 1 38 2 0 5 2 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 4 0 6 0 1 1 0 0 0 0 1 3 2 1 11 0 0 0]\n",
" [ 7 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 2 0 1 0 0 0 0 0 2 0 1 61 10 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 13 0 0 0 0 1 0 0 0 0 1 1 0 11 84 3 0 1 0]\n",
" [ 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 5 0 8 0 0 1 0 0 0 0 1 0 3 1 43 0 1 0]\n",
" [ 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 6 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0 0]\n",
" [ 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 1 8 0 0 0 0 2 0 0 0 0 0 2 0 0 17 1 0 9 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 7 0 2 0 0 0 0 0 0 0 0 0 0 2 6 0 0 0]]\n",
"val Loss: 1.3377 Acc: 0.6260\n",
"Confusion Matrix:\n",
"[[ 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 17 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 64 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 3 0]\n",
" [ 0 0 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 27 0 6 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 3 0]\n",
" [ 0 0 3 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 2 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 8 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 6 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 5 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 8 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 1 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 86 1 0 8 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 115 4 1 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 78 0 4 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 15 0 81 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0]\n",
" [ 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 30 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 76 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 9 0 0 0 0 27 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 8 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 5 1 0 0 0 0 0 0 0 6 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 20 0 1 14 0 0 2 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 8 0 0 0 0 0 0 0 0 0 0 4 0 1 3 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 50 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 2 66 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 0 0 0 0 0 0 3 0 0 31 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 16 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 2/29\n",
"----------\n",
"train Loss: 1.4704 Acc: 0.5900\n",
"Confusion Matrix:\n",
"[[ 63 3 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 12 2 0 16 0 4 0 0 2 0 0 0 0 0 3 2 0 0 1 0]\n",
" [ 2 92 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 21 1 2 1 1 8 0 1 2 0 1 3 0 0 3 0 0 2 0]\n",
" [ 0 0 64 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 17 0 9 0 0 6 0 0 1 0 0 1 0 1 4 1 0 0]\n",
" [ 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 11 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 6 0 2 0 0 1 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 1 6 0 0 0 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 1 0 0 1 0 0 2 0 1 8 0 0 0 0]\n",
" [ 0 0 13 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 5 0 7 0 0 0 0 0 0 0 0 0 0 3 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 2 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 12 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 8 0 0 0 0 4 0 0 0 0 0 1 0 1 1 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 14 0 0 6 0 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 1 0 0 0 0 0 0 0 0 0 1 0 1 33 0 0 0 0 0 0 0 2 11 1 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 27 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 10 1 1 0 1 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 5 0 0 0 0 0 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0]\n",
" [ 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 13 0 1 3 0 0 0 0 0 0 0 0 0 0 4 0 3 11 0 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 3 0 0 0 0 0 0 0 0 0 1 2 3 0 0 0]\n",
" [ 5 1 0 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 124 10 0 9 0 1 1 0 5 0 0 3 0 0 4 1 1 0 0 0]\n",
" [ 3 18 1 1 1 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 13 170 2 2 0 1 4 1 0 1 0 0 2 0 0 4 0 0 1 0]\n",
" [ 0 0 12 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 91 0 17 0 0 5 0 0 4 0 0 1 1 1 4 0 0 0]\n",
" [ 3 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 138 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 9 1 148 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0]\n",
" [ 3 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 1 0 1 0 54 3 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 5 6 0 0 0 1 117 0 0 0 0 0 1 0 1 3 0 0 0 0]\n",
" [ 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 4 0 0 44 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 12 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 6 0 1 0 0 23 0 0 1 0 0 2 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 1 2 1 0 0 0 0 0 4 18 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 13 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 1 0 2 0 4 1 0 0 0 0 13 2 0 7 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 8 0 0 0 0 0 0 0 0 0 2 40 0 0 9 0 0 1 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 8 1 3 0 1 2 0 0 2 0 0 8 1 0 6 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 7 0 0 3 1 0 0 0 0 0 0 1 0 0 71 6 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 10 1 0 0 0 0 0 0 0 0 0 2 0 5 92 2 0 3 0]\n",
" [ 0 0 8 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 6 0 6 0 0 1 0 0 0 0 0 2 3 1 46 0 0 0]\n",
" [ 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 2 0 0 0 3 0 3 0 0]\n",
" [ 3 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 1 0 2 0 1 1 0 2 0 0 0 0 0 3 0 1 9 0 0 22 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 6 0 4 0 0 0 0 0 0 0 0 1 1 0 2 0 0 0]]\n",
"val Loss: 1.1457 Acc: 0.6721\n",
"Confusion Matrix:\n",
"[[ 56 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 4 71 0 0 0 0 0 3 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 40 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 17 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0]\n",
" [ 0 12 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 7 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 3 0 0 3 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 3 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 1 2 0 0 0 0 3 0 0 1 0 0 0 0 0 14 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 15 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 76 1 0 2 0 1 0 0 3 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 7 2 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 0 1 0 0 0 0 5 114 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 24 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 5 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 42 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 78 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 0 0 28 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 19 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0]\n",
" [ 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 10 0 0 3 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 28 0 0 2 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0 8 0 0 2 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 47 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 1 0 0 0 0 1 0 0 0 0 0 4 0 3 54 0 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 10 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]]\n",
"\n",
"Epoch 3/29\n",
"----------\n",
"train Loss: 1.2677 Acc: 0.6348\n",
"Confusion Matrix:\n",
"[[ 64 5 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 3 0 14 0 3 0 0 2 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 4 85 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 1 1 14 3 2 0 0 3 0 1 10 0 1 5 0 0 3 0 0 6 0]\n",
" [ 0 1 52 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 23 0 10 0 0 6 0 0 0 0 0 3 1 2 2 0 0 0]\n",
" [ 0 0 0 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 0 1 58 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 4 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 8 1 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 5 0 1 0 0 1 0 0 1 0 0 2 1 0 0 0 0]\n",
" [ 1 6 0 0 0 0 0 4 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 5 0 1 7 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 4 1 3 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 1 0 0 0 0 0 0 0 2 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 1 0 0 0 0 0 3 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 8 1 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 4 0 0 0 0 0 0 0 2 4 0 0 0 0 5 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 2 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 6 1 0 3 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 1 0 0 39 0 0 0 0 0 0 0 2 8 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 6 0 0 0 0 0 0 0 0 20 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 4 0 0 3 0 0 2 0 0]\n",
" [ 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 6 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 3 0 0 0 0 0 0 0 1 1 0 0 2 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 24 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 8 1 0 1 0]\n",
" [ 0 1 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 1 7 0 0 0]\n",
" [ 9 3 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 123 11 1 6 0 4 0 0 2 0 0 3 0 0 1 2 2 0 0 0]\n",
" [ 1 7 3 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 1 0 12 187 2 0 1 0 2 0 1 4 0 0 0 0 1 5 0 0 0 0]\n",
" [ 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 3 2 93 0 25 0 0 3 0 0 2 0 0 0 0 0 8 0 0 0]\n",
" [ 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 6 0 0 137 0 0 0 0 1 0 0 0 1 0 3 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 16 0 140 0 0 0 0 0 5 0 0 0 1 0 2 0 0 0]\n",
" [ 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 1 0 0 0 65 2 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 3 0 1 1 0 1 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 5 0 0 0 1 120 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 1 0 0 51 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 2 0 0 1 0 31 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 26 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 16 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 4 0 0 1 1 2 0 0 1 0 0 16 2 0 4 3 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 4 0 0 0 0 2 1 0 1 0 2 45 0 1 4 0 0 0 0]\n",
" [ 0 1 5 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 1 7 1 0 0 0 0 0 0 0 0 0 16 0 0 4 0 0 0]\n",
" [ 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 7 0 0 0 0 0 0 0 3 0 0 2 0 0 72 4 1 0 0 0]\n",
" [ 1 3 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 4 0 0 0 0 2 0 0 0 0 0 2 0 5 99 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 4 0 4 0 0 1 0 0 0 0 0 1 2 4 49 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 4 0 0 3 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 0]\n",
" [ 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 0 5 0 0 31 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 0 8 0 1 0 0 0 0 0 1 0 0 1 0 1 3 0 0 0]]\n",
"val Loss: 1.0079 Acc: 0.6978\n",
"Confusion Matrix:\n",
"[[ 38 0 0 0 0 0 6 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 6 0 3 0 0 7 0 0 2 0 0 1 0 0 0 0 0]\n",
" [ 0 48 2 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 12 0 0 4 0 0 1 0 0 0 0]\n",
" [ 0 0 46 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 8 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 6 0]\n",
" [ 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 13 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 7 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 5 0 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 3 0 3 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 68 2 0 16 0 1 0 0 8 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 131 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 1 0 0 52 0 8 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 91 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 93 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 41 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 26 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 6 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 12 0 0 5 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2 30 0 0 5 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 7 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 5 62 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 26 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 0 20 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 4/29\n",
"----------\n",
"train Loss: 1.1029 Acc: 0.6861\n",
"Confusion Matrix:\n",
"[[ 71 2 0 0 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 0 13 0 1 0 0 4 0 0 3 0 0 3 0 0 0 0 0]\n",
" [ 4 99 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 12 0 0 0 0 3 0 2 5 0 1 1 2 0 6 0 0 5 0]\n",
" [ 0 0 59 0 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 12 1 11 0 0 8 0 0 3 0 0 1 0 0 4 0 0 0]\n",
" [ 1 0 0 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 0 0 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 37 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 6 1 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 2 0 0 0 0 0 1 0 0 2 0 0 2 0 0]\n",
" [ 0 3 0 0 1 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 1 0 0 0 0 0 1 0 0 5 1 0 2 0]\n",
" [ 0 0 9 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 3 1 4 0 0 0 0 0 0 0 0 0 1 1 6 0 2 0]\n",
" [ 3 0 0 0 0 0 1 0 0 2 0 0 1 0 0 1 2 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 1 0 0 0 0 0 0 0 4 0 0 0 0 2 0 0 1 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 1 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 6 1 0 3 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 2 0 1 36 0 0 0 0 0 2 0 1 5 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 13 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 4 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 1 4 0 0 1 0 0 0 0 0 0 0 0 0 1 3 1 0 3 0 1 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 4 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 23 0 0 4 0 0 1 0 1 0 0 0 0 0 2 0 2 3 0 0 3 0]\n",
" [ 0 1 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 1]\n",
" [ 4 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 140 6 0 6 0 3 1 0 1 0 0 0 1 0 3 1 0 0 0 0]\n",
" [ 1 10 1 1 0 1 0 2 0 0 0 0 0 2 0 0 7 0 0 0 0 0 0 0 6 182 2 1 1 1 2 0 0 2 0 0 2 0 0 4 1 0 2 0]\n",
" [ 0 0 6 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 104 0 24 0 0 5 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 145 0 0 0 0 3 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 13 0 148 0 0 0 0 0 3 0 0 1 0 0 2 0 0 0]\n",
" [ 3 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 65 4 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 4 6 0 0 1 0 123 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 50 0 0 1 0 1 0 0 0 1 0 0 0]\n",
" [ 5 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 7 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 26 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 8 0 9 0 0 0 0 0 20 0 0 1 0 0 0 0 0 0]\n",
" [ 2 2 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 21 1 0 3 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 4 0 0 0 0 1 0 0 1 0 0 48 1 1 7 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 4 0 1 0 0 0 0 0 1 0 1 23 0 0 0 0 1 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 6 0 0 0 1 0 0 0 0 0 0 2 0 0 79 0 1 0 0 0]\n",
" [ 0 3 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 6 0 0 0 0 1 0 0 0 0 1 0 0 4 99 1 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 4 0 1 0 0 1 0 0 0 0 0 3 1 0 57 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 8 0 0]\n",
" [ 0 5 0 0 1 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 1 0 1 5 0 0 31 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 6 0 1 0 0 1 0 0 0 0 0 1 0 0 4 0 0 1]]\n",
"val Loss: 0.8004 Acc: 0.7582\n",
"Confusion Matrix:\n",
"[[ 44 0 0 0 0 0 4 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 5 0 0 3 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 53 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 8 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 39 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 10 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 5 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 5 0 3 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 26 0 0 0 0 0 0 0 0 7 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 9 0 1 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 1 0 0 0 0 0 0 15 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 2 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 81 6 0 5 0 1 0 0 4 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 133 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 0 6 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 92 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 93 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 0 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 1 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 1 0 0 26 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 3 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 4 0 0 0 0 0 16 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 32 0 0 4 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 11 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 1 0 2 64 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 1 0 0 37 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 20 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 4 0 1 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0]]\n",
"\n",
"Epoch 5/29\n",
"----------\n",
"train Loss: 0.9679 Acc: 0.7218\n",
"Confusion Matrix:\n",
"[[ 78 1 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 13 0 0 2 0 2 0 0 4 0 0 2 0 0 4 0 0 0 0 0]\n",
" [ 1 104 0 0 0 1 0 2 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 1 15 0 3 1 0 0 0 1 3 0 0 2 1 1 2 0 0 3 0]\n",
" [ 0 0 71 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 1 0 0 0 3 0 1 13 0 7 0 0 2 0 0 1 0 0 2 0 0 2 0 0 0]\n",
" [ 0 0 0 32 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 63 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 39 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 9 1 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0 1 0]\n",
" [ 0 3 0 0 1 0 0 16 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1 1 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 3 0 1 1 0 0 0 0 0 2 0 1 3 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 2 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 2 0 2 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 0 0 0 0 0 0 0 5 1 0 1 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 20 1 0 0 0 0 0 0 0 8 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 43 0 0 0 0 0 0 0 1 9 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 15 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 10 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 2 0 0]\n",
" [ 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 1 2 0 0 0 0 0 0 0 0 0 1 1 0 1 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 4 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 2 0 0 0 0 0 24 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 7 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 3 0 2 0 0 0 0 0 0 0 0 2 1 1 1 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 138 15 0 4 0 2 0 0 2 1 0 0 0 0 1 1 0 0 0 0]\n",
" [ 1 4 1 1 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 1 0 0 0 0 7 194 1 2 1 0 7 0 0 1 0 0 2 0 1 2 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 2 102 0 16 0 0 4 0 0 1 0 0 1 0 0 7 0 0 0]\n",
" [ 2 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 144 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 1 150 0 0 0 0 0 3 0 0 0 1 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 8 1 0 0 0 68 3 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 9 0 0 0 0 124 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 8 0 2 0 0 49 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 7 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 38 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 1 32 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 5 0 9 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 1 0 1 2 1 0 0 0 0 0 22 1 0 1 2 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 53 0 0 9 0 0 1 0]\n",
" [ 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 1 0 0 0 0 0 0 0 0 0 0 21 0 1 5 0 1 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 84 1 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 3 1 1 0 0 1 0 0 0 0 1 2 1 2 100 1 0 4 0]\n",
" [ 0 0 6 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 0 0 3 1 1 57 0 0 0]\n",
" [ 1 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 6 1 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 1 1 2 0 0 0 0 1 0 0 0 0 0 1 0 0 6 0 0 32 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 3 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 4]]\n",
"val Loss: 0.7260 Acc: 0.7774\n",
"Confusion Matrix:\n",
"[[ 47 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 14 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 74 0 0 0 0 0 3 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 42 0 0 0 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 3 0 0 6 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 4 0 0 0 0 0 6 1 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 2 0 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 29 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 1 0 0 0 0 1 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 72 1 0 11 0 1 0 0 2 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 2 121 3 0 0 0 3 0 0 0 0 0 1 0 0 2 1 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 4 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 64 0 8 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 91 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 88 0 0 0 0 0 3 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 42 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 82 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 30 0 0 2 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 17 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 0 3 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 29 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0]\n",
" [ 0 5 0 0 0 0 0 1 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 17 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 1 0 0 2]]\n",
"\n",
"Epoch 6/29\n",
"----------\n",
"train Loss: 0.8547 Acc: 0.7449\n",
"Confusion Matrix:\n",
"[[ 82 6 0 0 0 0 3 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 5 0 0 6 0 1 0 0 3 0 0 0 0 0 1 0 0 1 0 0]\n",
" [ 6 106 2 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 8 1 2 0 1 3 0 0 4 0 0 1 0 0 3 0 0 4 0]\n",
" [ 0 0 75 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 13 0 7 0 0 1 0 0 0 0 0 2 0 1 2 0 0 1]\n",
" [ 1 0 0 35 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 60 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 39 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 8 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 1 0 0 2 0 0 2 0 0 1 0 0]\n",
" [ 0 1 0 0 0 0 0 17 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 16 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 2 0 1 0 0 1 0 0 0 0 0 1 0 2 2 0 0 0]\n",
" [ 1 1 0 0 0 0 0 1 0 4 0 0 1 0 0 1 1 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 3 0 0 1 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 21 0 0 0 0 0 0 0 0 6 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 6 0 1 0 0 0 0 0 0 0 0 0 1 0 0 40 0 0 0 0 0 0 0 0 5 0 0 0 1 3 0 0 0 0 0 0 0 1 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 2 13 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 1 1 2 0 3 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 28 0 0 3 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 0 1 0]\n",
" [ 0 0 5 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 2 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 5 1 0 0 0 0 1 0 0 0 0 0 0 0 0 2 2 0 0 1 0 0 0 0 138 9 1 4 0 4 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 4 0 1 2 0 0 1 0 1 1 0 0 1 0 0 2 0 0 0 0 0 0 0 13 185 2 2 1 0 5 0 0 2 0 1 2 0 0 4 0 0 1 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 2 3 105 1 15 0 0 3 0 0 2 0 0 1 1 0 2 0 0 2]\n",
" [ 2 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 143 0 0 1 0 1 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 14 0 143 0 0 0 0 0 7 0 0 0 0 0 2 0 0 1]\n",
" [ 2 1 0 2 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 7 1 0 0 0 67 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 1 132 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 56 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 4 0 1 0 0 41 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 4 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 1 0 0 0 0 0 0 0 24 2 0 4 0 0 0 0 0]\n",
" [ 0 2 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 2 0 1 0 0 0 0 0 1 0 0 55 1 0 0 0 0 0 0]\n",
" [ 0 1 2 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 2 0 0 0 0 0 0 0 0 25 0 2 2 0 1 0]\n",
" [ 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 1 0 0 1 0 0 0 0 0 0 0 79 5 0 0 0 0]\n",
" [ 0 0 1 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 3 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 1 2 1 5 101 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 1 0 0 1 0 0 0 0 0 4 0 0 61 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 38 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 3 0 0 5 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 5]]\n",
"val Loss: 0.6909 Acc: 0.7953\n",
"Confusion Matrix:\n",
"[[ 55 0 0 0 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 80 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 33 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 8 0 0 15 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 0 0 0 34 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 13 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 8 0 1 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 1 0 0 16 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 1 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 87 2 0 3 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 2 127 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 58 0 7 0 0 9 0 0 1 0 0 1 0 0 0 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 37 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 81 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 37 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 5 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 9 0 0 7 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 1 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 12 55 0 1 0 0]\n",
" [ 0 0 1 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 2 0 0 0 0 0 4 0 0 27 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 3 0 0 0 0 0 1 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 19 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 6]]\n",
"\n",
"Epoch 7/29\n",
"----------\n",
"train Loss: 0.7213 Acc: 0.8026\n",
"Confusion Matrix:\n",
"[[ 82 3 0 0 1 0 4 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 5 1 0 5 0 0 0 0 4 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 2 123 0 0 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 4 4 0 0 0 0 1 0 0 0 0 0 1 0 1 2 0 0 0 0]\n",
" [ 0 0 71 0 0 1 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 13 0 6 0 0 6 0 0 3 0 0 0 0 0 3 0 0 0]\n",
" [ 1 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 64 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 4 1 0 0 0 0 15 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 23 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 3 0 0 3 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 2 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0 0 0 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 1 0 10 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 11 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0 0 2 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 2 0 0 0 0 0 0 0 0 1 1 0 2 0 0 1]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 150 6 1 5 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 2 0 9 203 1 0 2 0 0 0 0 1 0 0 2 0 0 5 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 1 0 1 114 0 14 0 0 1 0 0 4 0 0 1 1 0 1 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 148 0 0 0 0 3 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 158 0 0 0 0 0 3 0 0 0 1 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 71 1 0 0 0 0 1 0 1 0 0 0 0 0 0]\n",
" [ 0 4 0 1 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 1 4 0 0 0 0 125 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 57 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 47 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 39 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 5 0 0 1 0 0 26 0 0 0 0 0 0 0 0 1]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 24 0 0 8 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 56 0 2 2 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 1 0 0 0 0 0 0 0 1 29 0 1 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 85 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 9 106 0 0 0 0]\n",
" [ 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 8 0 0 0 0 0 0 0 0 0 0 2 1 0 58 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 2 0 0 0 0 0 5 0 0 33 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 12]]\n",
"val Loss: 0.6075 Acc: 0.8199\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 1 76 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 40 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 3 0 6 0 0 4 0 0 3 0 0 0 0 0 0 0 0 1]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 4 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 5 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 17 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 95 2 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 127 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 3 0 0 5 0 0 0 0 0 0 0 0 65 0 5 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 90 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 97 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 38 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 12 0 0 5 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 31 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 7 63 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 37 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 23 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4]]\n",
"\n",
"Epoch 8/29\n",
"----------\n",
"train Loss: 0.6747 Acc: 0.8155\n",
"Confusion Matrix:\n",
"[[ 95 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 6 0 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0]\n",
" [ 4 118 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 10 0 1 1 0 1 0 0 1 0 0 0 1 1 2 0 0 1 0]\n",
" [ 0 0 77 0 0 2 0 0 2 0 0 0 0 0 1 0 0 2 1 0 0 0 0 0 0 0 8 0 4 0 0 4 0 0 1 1 0 1 0 0 3 0 0 0]\n",
" [ 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 65 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 38 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 3 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 0 3 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 1 0 2 1 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 1 0 0 13 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 17 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 52 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 11 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 1 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 29 0 1 1 0 0 0 0 0 0 0 1 0 0 2 0 0 3 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0]\n",
" [ 5 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 143 5 0 6 0 5 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 11 203 1 0 1 0 4 0 0 1 0 0 2 0 0 1 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 1 0 0 1 0 1 122 0 8 0 0 2 0 0 1 0 0 1 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 152 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 157 0 0 0 0 0 2 0 0 0 2 0 1 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 75 1 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 1 0 0 6 0 0 0 2 122 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 50 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 1 0 1 0 0 0 0 44 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 2 0 2 0 0 1 0 0 33 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 3 0 0 1 1 0 0 0 0 0 0 28 0 0 3 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 1 60 1 1 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 32 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 87 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 3 1 1 0 0 1 0 0 0 0 0 4 0 3 104 0 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 1 0 2 64 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 16 0 0]\n",
" [ 0 3 0 0 0 1 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 37 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 3 0 0 4 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 3]]\n",
"val Loss: 0.5806 Acc: 0.8330\n",
"Confusion Matrix:\n",
"[[ 57 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 1 74 0 0 0 0 0 2 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 44 0 0 0 0 0 2 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 2 0 5 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 5 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 2 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 3 128 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 3 0 0 4 0 0 0 0 0 0 0 0 62 0 7 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 40 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 14 0 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 32 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 65 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 39 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4]]\n",
"\n",
"Epoch 9/29\n",
"----------\n",
"train Loss: 0.6492 Acc: 0.8304\n",
"Confusion Matrix:\n",
"[[ 92 1 0 0 0 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0 1 0 0 4 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 123 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 7 0 0 0 0 3 0 0 1 0 0 1 0 1 2 0 0 0 0]\n",
" [ 0 0 85 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 12 0 2 0 0 1 0 0 3 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 64 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 0 0 0 39 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 6 1 0 0 0 0 15 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 2 0 0 0 0 0 0 0 0 1 0 1 3 0 1 0]\n",
" [ 2 0 0 0 0 0 0 0 0 6 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 28 1 0 0 0 0 0 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 50 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 4 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 15 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 2 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 147 9 0 3 0 2 2 0 1 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 10 207 1 0 0 0 1 1 0 2 0 0 1 0 1 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 122 0 8 0 0 4 0 0 0 0 0 2 0 0 3 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 148 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 159 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 3 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 73 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 2 129 0 0 0 0 0 0 0 0 1 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 46 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 39 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 6 0 0 1 0 0 28 0 0 0 0 0 0 0 0 1]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 33 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 58 0 0 3 1 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 2 27 0 1 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 1 0 0 1 0 0 84 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 3 0 0 0 0 1 0 0 0 0 0 1 1 1 108 0 0 2 0]\n",
" [ 0 0 1 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 2 0 0 0 0 0 1 0 0 2 1 1 63 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 13 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 41 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 2 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 7]]\n",
"val Loss: 0.5614 Acc: 0.8366\n",
"Confusion Matrix:\n",
"[[ 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 81 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 49 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 7 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 17 2 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 1 0 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 128 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 67 0 4 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 93 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 41 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 14 0 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 32 0 0 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 36 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 10/29\n",
"----------\n",
"train Loss: 0.6482 Acc: 0.8229\n",
"Confusion Matrix:\n",
"[[ 92 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 5 0 1 0 0 1 0 0 2 0 0 1 1 0 0 0 0]\n",
" [ 2 124 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 3 0 0 2 0 2 2 0 0 1 0 0 2 0]\n",
" [ 0 0 77 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 12 0 5 0 0 3 0 0 2 0 0 2 0 1 3 0 0 0]\n",
" [ 1 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 63 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 1 0]\n",
" [ 0 0 0 0 0 39 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 1 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0]\n",
" [ 1 4 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 7 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 50 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 10 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 2 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 4 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 33 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 3 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 157 2 0 4 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 7 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 206 2 0 0 0 0 0 0 1 0 0 2 1 1 2 0 0 0 0]\n",
" [ 0 0 2 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 1 117 0 10 0 1 3 0 0 1 0 0 1 0 0 2 0 0 2]\n",
" [ 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 149 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 161 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 72 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 6 0 0 0 1 128 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 54 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 5 0 0 0 0 40 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 40 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 5 0 0 0 0 0 27 0 0 0 0 0 0 0 0 1]\n",
" [ 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0 0 0 0 0 0 0 0 0 30 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 58 1 1 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 32 1 0 1 0 0 0]\n",
" [ 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 85 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 2 0 0 0 0 1 0 0 0 0 0 2 3 2 108 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 2 0 0 0 0 0 1 0 0 1 1 2 61 0 0 0]\n",
" [ 0 0 1 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 12 0 0]\n",
" [ 0 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 37 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 5]]\n",
"val Loss: 0.5506 Acc: 0.8342\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 45 0 0 0 0 0 1 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 2 0 5 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 12 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 17 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 86 2 0 3 0 1 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 2 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 129 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 1 0 0 0 0 0 5 0 0 6 0 0 0 0 0 0 0 0 57 0 6 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 91 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 98 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 40 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 15 0 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 3 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 64 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 35 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 11/29\n",
"----------\n",
"train Loss: 0.6328 Acc: 0.8237\n",
"Confusion Matrix:\n",
"[[ 92 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 5 1 0 0 0 2 0 0 1 0 0 1 1 0 0 0 0]\n",
" [ 2 122 0 0 2 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 7 0 0 1 0 1 0 0 2 0 0 0 0 0 2 1 0 1 0]\n",
" [ 0 0 83 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 2 0 0 2 0 0 4 0 0 1 0 2 1 1 0 0]\n",
" [ 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 64 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 40 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 5 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 4 0 0 1 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 23 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 2 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0]\n",
" [ 0 0 0 1 0 0 0 0 0 8 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 1 0 0 0 0 0 0 0 1 0 0 23 1 0 0 0 0 0 0 0 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 47 0 0 0 0 0 0 0 0 5 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 1 0 2 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0 0 0 30 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1]\n",
" [ 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 139 11 0 1 0 4 1 0 2 0 0 0 0 0 4 2 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 10 207 1 1 0 0 0 0 0 1 0 0 2 0 1 2 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 1 121 0 11 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1]\n",
" [ 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 148 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 163 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 74 0 0 1 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 1 128 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 3 0 2 0 0 56 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 46 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 1 35 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 2 0 2 0 0 0 0 0 0 0 29 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 0 0 0 0 0 0 1 57 2 0 2 0 0 1 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 30 0 2 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 0 0 2 0 0 83 2 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 2 1 4 107 1 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 69 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 41 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9]]\n",
"val Loss: 0.5359 Acc: 0.8402\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 1 74 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 44 0 0 0 0 0 2 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 3 0 4 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 17 2 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 98 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 130 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 70 0 3 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 92 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 95 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 40 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 15 0 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 31 0 0 5 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 38 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 12/29\n",
"----------\n",
"train Loss: 0.6064 Acc: 0.8283\n",
"Confusion Matrix:\n",
"[[ 89 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 2 0 3 0 1 0 0 2 0 0 1 0 0 2 0 0 0 0 0]\n",
" [ 2 126 0 0 0 1 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 4 0 0 1 0 3 0 1 0 0 1 1 0 0 1 0 0 1 0]\n",
" [ 0 1 82 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 7 0 3 0 0 3 0 0 4 0 0 0 0 0 0 0 0 1]\n",
" [ 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 40 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 19 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0]\n",
" [ 0 4 0 0 0 1 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 1 3 0 1 0]\n",
" [ 0 0 0 1 0 0 0 0 0 8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 1 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 49 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 2 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 1 0 3 0 0 0 0 0 0 1 0 2 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 14 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1]\n",
" [ 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 151 8 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 1 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 6 209 1 0 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 113 0 8 0 0 2 0 0 3 0 0 4 0 0 5 0 0 1]\n",
" [ 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 148 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 7 1 157 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 72 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 133 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 0 1 0 42 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 37 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 32 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 57 1 0 4 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 35 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 1 0 0 0 0 0 0 0 1 0 0 77 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 1 0 0 0 0 0 0 0 1 1 0 4 107 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 1 0 0 0 0 2 0 0 1 0 1 68 0 0 0]\n",
" [ 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 43 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 5 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 9]]\n",
"val Loss: 0.5290 Acc: 0.8444\n",
"Confusion Matrix:\n",
"[[ 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 80 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 43 0 0 0 0 0 3 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 5 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 1 0 3 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 126 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 1 7 0 0 0 0 0 2 0 0 0 0 0 2 0 0 2 0 0 0 0 0 1 0 0 65 0 4 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 91 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 40 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 34 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 16 0 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 32 0 0 4 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 35 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 23 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4]]\n",
"\n",
"Epoch 13/29\n",
"----------\n",
"train Loss: 0.5979 Acc: 0.8400\n",
"Confusion Matrix:\n",
"[[ 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 4 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 125 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 7 0 0 1 1 1 0 1 2 0 1 1 0 0 0 0 0 1 0]\n",
" [ 0 0 83 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 7 0 0 2 0 0 2 0 0 2 1 0 2 0 0 0]\n",
" [ 1 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 62 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 40 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 5 1 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 28 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 22 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 1 1 0 4 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 0 0 0 1 0 1 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0 3 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 1 0 0 12 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 7 1 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 52 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 22 0 0 0 0 0 0 0 0 5 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 1 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 3 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 33 0 0 3 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1]\n",
" [ 1 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 154 3 0 1 0 2 0 0 4 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 3 2 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 5 210 1 0 0 0 1 0 1 1 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 121 0 13 0 0 3 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 152 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 8 0 155 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 1 0 72 1 0 0 0 0 2 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 134 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 57 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 42 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 39 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 8 0 0 0 0 0 26 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 1 0 0 0 0 0 30 1 0 3 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 63 1 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 3 0 0 81 2 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 4 110 1 1 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 69 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 14 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 2 0 0 2 0 0 38 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 5 0 0 5 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 6]]\n",
"val Loss: 0.5157 Acc: 0.8462\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 47 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 5 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 88 2 0 7 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 64 0 6 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 39 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 38 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 14/29\n",
"----------\n",
"train Loss: 0.5916 Acc: 0.8318\n",
"Confusion Matrix:\n",
"[[102 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 119 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 2 7 1 0 0 0 0 0 0 2 0 0 2 0 0 2 1 0 2 0]\n",
" [ 0 1 76 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 1 2 1 0 7 0 7 0 0 3 0 0 2 0 0 0 0 0 2 0 0 1]\n",
" [ 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 63 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 1 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 2 1 0 0 1 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 1 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 5 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 4 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 24 1 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 51 0 0 0 0 0 1 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 11 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 14 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 0 1 0 0 1 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 30 0 1 2 0 0 0 0 0 0 0 1 0 0 1 1 0 2 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 152 9 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 10 206 0 1 1 0 4 1 0 0 0 0 1 0 1 0 0 0 1 0]\n",
" [ 0 0 5 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 2 118 0 5 0 0 1 0 0 1 0 0 2 0 0 4 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 149 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 159 0 0 0 0 0 3 0 0 0 1 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 74 1 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 1 134 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 56 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 2 0 0 46 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 2 0 1 35 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 34 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 34 1 1 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 1 55 1 0 5 0 0 1 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 29 0 0 3 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 1 0 0 1 0 0 82 3 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 1 116 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 2 0 0 0 0 0 1 0 0 0 1 1 60 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 12 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 43 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 6]]\n",
"val Loss: 0.5125 Acc: 0.8510\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0]\n",
" [ 0 0 43 0 0 0 0 0 1 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 5 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 13 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 7 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 95 1 0 3 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 72 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 97 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 39 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 34 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 39 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4]]\n",
"\n",
"Epoch 15/29\n",
"----------\n",
"train Loss: 0.5629 Acc: 0.8546\n",
"Confusion Matrix:\n",
"[[ 94 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 4 0 1 0 0 2 0 0 1 0 0 1 0 0 0 1 0]\n",
" [ 3 129 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 0 3 0]\n",
" [ 0 0 81 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 9 0 5 0 0 1 0 0 1 0 0 1 0 0 4 0 0 1]\n",
" [ 0 0 0 37 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 2 0 0 38 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 16 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 2 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 3 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 1 0 0 10 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 3 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 33 0 1 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0]\n",
" [ 1 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 150 11 0 3 0 1 1 0 3 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 2 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 7 206 1 0 1 0 2 0 0 0 0 1 2 0 1 2 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 3 123 0 9 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 154 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 158 0 0 0 0 0 3 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 79 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 3 1 0 0 0 0 133 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 53 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 48 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 42 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 34 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 2 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 57 1 1 3 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 29 0 0 3 1 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 2 0 1 0 1 0 0 0 0 0 3 0 0 80 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 3 113 0 0 2 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 70 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 13 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 44 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 10]]\n",
"val Loss: 0.5386 Acc: 0.8402\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 40 0 0 0 0 0 1 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 3 0 5 0 0 7 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 9 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 3 0 1 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 8 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 91 1 0 5 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 2 131 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 71 0 6 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 37 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 15 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 34 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 67 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 0 38 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 16/29\n",
"----------\n",
"train Loss: 0.5949 Acc: 0.8372\n",
"Confusion Matrix:\n",
"[[ 96 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 3 1 1 2 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 117 0 0 0 0 1 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 2 8 0 0 0 0 0 0 1 1 0 0 3 0 1 3 0 0 2 0]\n",
" [ 0 0 81 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 2 0 1 10 0 5 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 63 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 39 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 3 1 0 0 0 0 13 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 2 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 23 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 1 0 1 3 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 2 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 12 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 26 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0 0 0 0 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 9 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 3 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 10 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1]\n",
" [ 2 0 1 2 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 146 8 0 3 0 1 1 0 1 0 0 1 0 0 1 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 6 215 2 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 123 0 5 0 0 3 0 0 2 0 0 5 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 152 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 6 0 153 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 75 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0 2 128 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 55 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 3 0 0 1 0 48 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 38 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 6 0 0 0 0 0 30 0 0 0 0 0 1 0 0 1]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 0 0 0 1 0 0 0 0 0 0 31 0 0 3 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 60 0 0 3 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 2 0 1 1 0 0 0 0 0 0 0 28 0 1 1 0 1 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 87 1 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 1 0 1 0 0 0 0 2 0 3 108 0 1 0 0]\n",
" [ 0 0 3 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 66 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 11 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 1 1 0 1 0 0 43 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 9]]\n",
"val Loss: 0.5064 Acc: 0.8534\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 45 0 0 0 0 0 2 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 2 0 5 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 93 2 0 3 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 2 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 68 0 4 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 91 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 97 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 40 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 38 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4]]\n",
"\n",
"Epoch 17/29\n",
"----------\n",
"train Loss: 0.5704 Acc: 0.8454\n",
"Confusion Matrix:\n",
"[[ 93 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 123 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 5 0 0 1 0 3 0 1 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 75 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 1 0 0 2 0 0 13 0 4 0 0 1 0 0 2 0 0 1 1 0 3 0 0 0]\n",
" [ 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 63 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 1 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 6 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 2 0 0 9 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 1 0 0 14 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 53 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 14 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 1]\n",
" [ 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 152 8 0 1 0 1 0 0 2 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 4 214 2 0 0 1 2 0 2 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 4 120 0 7 0 0 2 0 0 3 0 0 1 1 0 2 0 0 1]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 151 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 161 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 75 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 132 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 2 0 0 57 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 1 0 0 1 0 48 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 37 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 3 0 0 0 0 0 33 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 29 1 1 4 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 1 59 0 1 1 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 32 0 0 3 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 1 0 0 0 0 2 0 0 0 0 0 85 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 4 110 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 1 70 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0]\n",
" [ 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 44 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 4 0 0 0 0 0 0 0 1 0 0 1 0 1 1 0 0 9]]\n",
"val Loss: 0.5191 Acc: 0.8462\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 80 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 48 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 2 0 4 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 17 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 89 2 0 5 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 1 0 0 0 0 0 3 0 0 4 0 0 0 0 0 0 0 0 61 0 4 0 0 3 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 96 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 41 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 3 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 67 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 36 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 18/29\n",
"----------\n",
"train Loss: 0.5864 Acc: 0.8400\n",
"Confusion Matrix:\n",
"[[ 95 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0 4 0 0 1 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 1 127 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 3 0 1 2 1 0 2 0 0 1 0]\n",
" [ 0 0 71 0 0 1 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 1 0 3 0 1 9 0 7 0 0 2 0 0 5 0 0 2 0 0 2 0 0 0]\n",
" [ 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 22 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 2 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 10 1 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 1 18 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 1 0 0 12 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 1 0 0 0 0 0 0 0 4 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 54 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 3 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 10 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 32 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 155 7 0 3 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 8 212 2 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 122 0 12 0 0 1 1 0 0 1 0 1 0 0 3 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 150 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 7 0 155 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 74 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 0 134 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 59 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 3 0 0 0 0 43 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 39 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 6 0 0 0 0 0 29 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 31 0 1 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 59 0 2 2 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 1 30 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0 2 0 0 82 2 0 0 0 0]\n",
" [ 0 1 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 2 0 4 107 0 0 2 0]\n",
" [ 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 1 68 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0]\n",
" [ 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 41 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 12]]\n",
"val Loss: 0.5080 Acc: 0.8534\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 45 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 2 0 5 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 5 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 93 1 0 4 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 66 0 4 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 97 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 41 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 37 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 37 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 19/29\n",
"----------\n",
"train Loss: 0.5838 Acc: 0.8408\n",
"Confusion Matrix:\n",
"[[ 94 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 2 0 0 1 0 0 2 1 0 0 0 0 0 0 0]\n",
" [ 3 128 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 2 1 1 0 0 2 0 0 3 0 0 0 0 0 1 0]\n",
" [ 0 0 84 0 0 1 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 3 0 7 0 0 2 0 0 2 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 2 1 0 0 2 0 0 0 0 0 1 0 1 3 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 1 0 0 10 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 1 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 2 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 14 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 1 2 0 0 0 0 0 1 0 0 2 0 0 1 0 0 27 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 154 6 0 1 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 4 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 8 206 1 0 0 0 6 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 1 2 118 0 11 0 0 2 0 0 2 0 0 1 0 1 2 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 151 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 161 0 0 0 0 0 4 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 76 1 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 135 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 56 0 0 2 0 0 1 1 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 43 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 39 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 6 0 0 0 0 0 29 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 32 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 58 0 1 5 0 0 2 0]\n",
" [ 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 30 0 1 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 87 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 1 2 0 4 111 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 71 0 0 0]\n",
" [ 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 10 0 0]\n",
" [ 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 1 0 0 0 0 0 0 0 0 0 2 0 0 38 0]\n",
" [ 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 8]]\n",
"val Loss: 0.5036 Acc: 0.8546\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 46 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 2 0 5 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 91 2 0 3 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 2 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 0 68 0 4 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 41 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 35 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 4 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 36 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 20/29\n",
"----------\n",
"train Loss: 0.5995 Acc: 0.8333\n",
"Confusion Matrix:\n",
"[[ 95 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 2 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 2 126 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 4 0 1 0 0 1 0 0 2 0 0 1 1 0 4 0 0 0 0]\n",
" [ 0 0 84 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 7 0 6 0 0 0 0 0 1 0 0 2 0 0 3 0 0 0]\n",
" [ 1 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 1 0 0 0 0 21 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 20 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 1 0 0 2 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 9 1 0 0 0 0 0 0 0 0 0 0 4 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 51 0 0 0 0 0 0 0 0 2 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 0 7 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 3 0 0 0 0 0 1 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 2 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 143 6 0 4 0 5 0 0 3 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 8 208 2 0 1 1 1 0 1 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 126 0 9 0 0 2 0 0 2 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 146 1 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 5 0 156 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 3 0 0 0 72 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 133 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 1 0 0 44 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 38 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 4 0 0 0 0 0 28 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 4 0 0 0 0 0 0 0 0 0 0 29 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 1 60 1 0 2 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 4 0 0 0 0 0 0 0 0 0 0 27 0 0 1 0 1 0]\n",
" [ 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 1 0 0 1 0 0 0 1 0 0 0 0 1 80 1 1 0 0 0]\n",
" [ 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 2 1 3 106 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 5 0 2 0 0 0 0 0 0 0 0 0 1 4 63 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 4 0 0 39 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 4 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 7]]\n",
"val Loss: 0.5092 Acc: 0.8450\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 45 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 2 0 5 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 7 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 91 2 0 5 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 69 0 3 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 96 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 39 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 37 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 16 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 3 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 37 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 21/29\n",
"----------\n",
"train Loss: 0.5756 Acc: 0.8532\n",
"Confusion Matrix:\n",
"[[ 98 2 0 0 0 0 2 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 126 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 3 9 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 84 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 8 0 5 0 0 2 0 0 2 0 0 0 0 1 2 0 0 0]\n",
" [ 0 0 0 33 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 65 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 5 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 5 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 19 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 52 0 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 27 0 0 0 0 0 0 0 3 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 4 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 32 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 1]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 158 4 0 1 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 6 212 3 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 132 0 5 0 0 0 0 0 1 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 153 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 7 0 157 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 77 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 2 0 1 0 0 130 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 53 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 47 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 39 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 4 0 4 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 1 0 1 1 0 0 0 0 0 0 31 0 1 1 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 62 2 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 33 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 1 0 0 87 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 2 0 1 0 0 0 0 0 0 0 0 2 0 2 107 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 2 0 0 0 0 0 1 0 0 2 1 1 62 0 0 0]\n",
" [ 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 39 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 3 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 11]]\n",
"val Loss: 0.5247 Acc: 0.8414\n",
"Confusion Matrix:\n",
"[[ 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 47 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 7 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 87 1 0 8 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 60 0 8 0 0 2 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 15 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 3 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 38 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 22/29\n",
"----------\n",
"train Loss: 0.5825 Acc: 0.8418\n",
"Confusion Matrix:\n",
"[[ 89 2 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 1 0 0 5 0 0 1 0 0 2 0 0 1 0 0]\n",
" [ 4 122 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 4 0 1 0 0 1 0 1 2 0 0 1 0 0 2 0 0 1 0]\n",
" [ 0 0 87 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 5 1 4 0 0 1 0 0 2 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 36 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 0 0 1 65 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 5 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 4 0 0 1 0]\n",
" [ 0 1 4 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0 0 0 0 2 1 0 2 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 24 1 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 20 0 0 0 0 0 0 0 0 8 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 12 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 157 8 0 0 0 1 0 0 2 0 0 2 0 0 0 0 0 0 0 0]\n",
" [ 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 11 205 1 0 0 1 2 0 0 1 0 0 1 1 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 126 0 8 0 0 0 0 0 2 0 0 1 0 1 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 150 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 162 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 8 0 0 0 0 69 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 4 132 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 1 1 0 0 57 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 45 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 35 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 4 0 0 0 0 0 27 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 35 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 1 60 0 0 1 0 1 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 1 0 0 0 0 0 0 32 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 2 0 0 2 0 0 86 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 0 2 0 0 0 0 0 0 0 0 2 1 2 109 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 68 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 13 1 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 38 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 9]]\n",
"val Loss: 0.5290 Acc: 0.8420\n",
"Confusion Matrix:\n",
"[[ 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 80 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 46 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 5 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 9 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 8 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 17 1 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 89 1 0 8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 66 0 7 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 41 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 16 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 34 0 0 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 50 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 66 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 3 0 0 31 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 23/29\n",
"----------\n",
"train Loss: 0.6137 Acc: 0.8383\n",
"Confusion Matrix:\n",
"[[ 99 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 3 129 0 0 0 0 0 1 0 0 0 0 1 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0]\n",
" [ 0 0 77 0 0 0 0 0 4 0 0 0 0 0 2 0 0 2 0 0 0 0 0 1 1 1 6 0 6 0 0 2 0 0 1 0 0 2 0 0 1 0 0 1]\n",
" [ 0 1 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 4 1 0 0 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 1 4 0 0 1 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 6 0 2 0 0 1 0 0 0 0 0 1 1 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 20 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 23 0 0 0 0 0 0 0 0 5 0 0 2 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 48 0 0 0 0 0 0 0 0 5 0 0 0 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 22 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 3 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 152 5 1 3 0 1 0 0 2 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 1 10 2 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 4 201 1 0 0 0 4 0 0 1 0 0 0 1 1 2 0 0 0 0]\n",
" [ 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 1 0 120 0 7 0 0 4 0 0 3 0 0 0 0 1 1 0 0 1]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 0 149 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 156 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 76 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 1 133 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 57 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 4 0 0 0 0 44 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 38 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 6 0 0 0 0 0 31 0 0 0 0 0 0 0 0 1]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 1 0 0 0 0 0 0 30 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 59 0 0 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 0 0 0 0 0 2 33 0 0 0 0 0 0]\n",
" [ 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 1 88 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 1 0 0 0 1 1 1 113 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 1 3 0 1 0 0 0 0 0 0 0 0 0 1 1 62 0 0 1]\n",
" [ 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 11 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 44 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11]]\n",
"val Loss: 0.5075 Acc: 0.8528\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 45 0 0 0 0 0 2 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 2 0 5 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 89 2 0 6 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 2 130 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 65 0 5 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 41 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 34 0 0 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 35 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4]]\n",
"\n",
"Epoch 24/29\n",
"----------\n",
"train Loss: 0.5882 Acc: 0.8379\n",
"Confusion Matrix:\n",
"[[ 96 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 2 0 0 0 0 3 0 0 0 0 0 1 0 0 0 1 0]\n",
" [ 1 127 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 3 0 0 0 1 1 0 0 1 0 1 0 1 0 1 0 0 4 0]\n",
" [ 0 0 79 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 8 0 5 0 0 3 0 0 2 0 0 1 0 0 1 0 0 1]\n",
" [ 1 0 0 35 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 64 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 3 0 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 21 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 26 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 45 0 0 0 0 0 0 0 0 6 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 11 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 29 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 1 5 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 151 7 0 2 0 1 0 0 3 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 9 207 0 0 0 1 3 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 129 0 7 0 0 2 0 0 0 0 0 1 0 0 2 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 154 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 4 0 159 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 75 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0 128 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 57 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 44 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 34 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 1 0 0 35 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 2 0 0 30 1 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 1 57 0 0 4 0 0 0 0]\n",
" [ 0 1 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 31 1 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 2 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 2 0 2 112 0 0 0 0]\n",
" [ 0 0 3 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 2 0 66 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 14 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 44 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 7 0 0 0 0 0 0 0 1 0 0 1 0 0 2 0 0 7]]\n",
"val Loss: 0.5118 Acc: 0.8546\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 45 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 2 0 4 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 1 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 128 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 68 0 4 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 41 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 37 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 35 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 25/29\n",
"----------\n",
"train Loss: 0.5913 Acc: 0.8408\n",
"Confusion Matrix:\n",
"[[ 94 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 1 0 3 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 3 122 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2 0 0 1 0 1 1 0 2 3 0 0 0 0 0 0 1 2 0 0 0 1 2 2 0 0 1 0]\n",
" [ 0 0 81 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 8 0 6 0 0 1 0 0 3 0 0 2 1 0 2 0 0 0]\n",
" [ 0 0 0 34 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 3 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 4 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 1 0 0 11 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 16 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 12 0 0 1 0 0 0 0 0 1 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 0 1 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 35 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 3 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 153 8 0 2 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0]\n",
" [ 0 3 0 1 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 11 205 0 1 0 1 1 0 0 0 0 0 1 0 1 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 1 126 0 7 0 0 1 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 150 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 8 0 157 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 2 0 70 3 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 131 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 58 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 49 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 2 35 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 5 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 30 0 0 3 2 0 0 0 0]\n",
" [ 0 4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 57 1 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 34 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 1 0 0 0 0 0 86 1 0 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 3 0 3 110 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 1 3 0 0 0 0 0 0 0 0 4 0 0 61 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 12 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 46 0]\n",
" [ 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 3 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10]]\n",
"val Loss: 0.5280 Acc: 0.8438\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 45 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 5 0 0 7 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 17 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 88 2 0 6 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 128 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 60 0 7 0 0 3 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 41 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 37 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 51 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 67 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 35 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 26/29\n",
"----------\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n",
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"train Loss: 0.6025 Acc: 0.8351\n",
"Confusion Matrix:\n",
"[[ 94 1 0 0 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 1 0 0 2 0 0 3 0 0 0 0 0 0 0 0]\n",
" [ 2 129 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 2 0]\n",
" [ 0 0 75 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 11 0 5 0 0 1 0 0 5 0 0 3 0 0 3 0 1 0]\n",
" [ 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 64 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 1 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 4 0 0 0 0 0 15 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 2 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 2 0 1 0 0 1 0 0 0 0 0 1 0 1 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 3 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 4 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 17 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 49 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 2 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 7 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 1 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 32 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2]\n",
" [ 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 152 5 0 6 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 12 201 2 1 0 1 2 0 1 2 0 0 3 0 1 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 1 2 124 0 6 0 0 1 0 0 3 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 149 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 157 0 0 0 0 0 3 0 0 0 0 1 1 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 73 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 0 134 0 0 1 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 47 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 38 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 4 0 0 0 0 0 32 0 0 0 0 0 0 0 0 1]\n",
" [ 4 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 28 1 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 60 0 0 3 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 1 0 0 29 1 1 1 1 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 1 0 0 85 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 2 1 1 1 109 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 1 0 0 69 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 13 0 0]\n",
" [ 0 3 0 0 0 2 0 1 0 1 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 40 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 5 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 7]]\n",
"val Loss: 0.5215 Acc: 0.8456\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 44 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 8 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 15 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 8 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 93 2 0 4 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 66 0 7 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 93 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 39 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 67 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 2 0 0 35 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 27/29\n",
"----------\n",
"train Loss: 0.5724 Acc: 0.8493\n",
"Confusion Matrix:\n",
"[[ 92 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 5 0 0 7 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0]\n",
" [ 3 128 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 3 0 0 1 0 1 0 0 1 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 0 77 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 7 0 8 0 0 2 0 0 4 0 0 1 0 1 3 0 0 0]\n",
" [ 1 0 0 35 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 39 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 1 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 27 1 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 14 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 2 0 3 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0 1 1 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 158 2 0 2 0 3 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 2 4 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 5 210 1 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 125 0 9 0 0 1 0 0 2 0 0 2 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 153 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 161 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 0 0 74 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 5 0 0 0 2 128 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 1 1 0 56 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 49 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 36 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 5 0 0 1 0 0 29 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 1 0 0 1 0 0 0 0 0 0 27 1 0 1 2 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 56 1 0 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 33 0 0 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 1 0 1 84 1 1 0 0 0]\n",
" [ 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 1 114 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 70 0 0 1]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 38 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9]]\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n",
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"val Loss: 0.5218 Acc: 0.8468\n",
"Confusion Matrix:\n",
"[[ 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 1 77 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 48 0 0 0 0 0 1 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 2 0 4 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 5 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 1 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 89 1 0 5 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 1 0 0 0 0 0 3 0 0 4 0 0 0 0 0 0 0 0 63 0 4 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 97 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 42 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 82 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 35 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 38 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 28/29\n",
"----------\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n",
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"train Loss: 0.5869 Acc: 0.8450\n",
"Confusion Matrix:\n",
"[[ 93 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 1 0 1 0 0 1 0 0 2 0 0 1 3 0 0 0 0]\n",
" [ 4 127 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 1 0 1 1 0 1 1 0 0 1 1 0 1 0 0 1 0]\n",
" [ 0 0 75 0 0 0 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 12 1 6 0 0 1 0 0 0 0 0 1 3 0 3 0 0 0]\n",
" [ 0 0 0 35 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 67 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 39 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 7 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 2 0 0 1 0 0]\n",
" [ 0 2 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0]\n",
" [ 0 0 3 0 0 0 0 0 21 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0 2 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 1 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 1 0 0 12 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 25 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 53 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 9 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 2 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 17 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 2 1 1 1 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 150 5 0 1 0 1 0 0 2 0 0 1 0 0 1 1 0 0 0 0]\n",
" [ 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 211 2 0 0 0 2 0 0 1 0 1 0 0 0 0 0 0 1 0]\n",
" [ 0 0 3 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 127 0 6 0 1 2 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 146 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 5 0 160 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 76 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 132 0 0 1 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 4 0 1 1 0 54 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 45 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 32 0 0 0 0 0 0 0 0 1]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 30 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 1 63 0 0 1 0 0 0 0]\n",
" [ 0 2 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 0 0 0 0 0 0 26 0 0 2 0 1 1]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 1 0 0 0 0 0 0 0 0 0 85 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 2 0 3 110 0 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 68 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 14 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 1 0 2 0 0 43 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 8]]\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n",
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"val Loss: 0.5187 Acc: 0.8492\n",
"Confusion Matrix:\n",
"[[ 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 78 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 50 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 1 0 0 17 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 88 2 0 6 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 1 0 0 0 0 0 3 0 0 5 0 0 0 0 0 1 0 0 59 0 5 0 0 2 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 40 1 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 15 0 0 4 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 33 0 0 4 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 69 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 36 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 23 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Epoch 29/29\n",
"----------\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n",
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"train Loss: 0.6121 Acc: 0.8326\n",
"Confusion Matrix:\n",
"[[ 99 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0]\n",
" [ 0 125 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 5 0 0 0 0 1 0 0 2 0 0 6 0 0 0 0 0 1 0]\n",
" [ 0 0 67 0 0 3 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 9 0 0 2 0 0 1 0 1 3 0 0 4 0 1 0]\n",
" [ 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 1 0 0 64 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 1 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 16 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 1 0 0 0 0 2 0 0 1 0 0]\n",
" [ 0 1 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 1 0 0 0 0 0 2 0 1 3 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 3 0 0 1 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 1 0 0 10 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 1 0 0 4 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 48 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 8 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 13 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 1 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 32 0 3 0 0 0 0 0 1 0 0 0 0 0 1 1 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 1 0 2 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 150 4 1 7 0 2 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 9 213 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 3 1 120 0 10 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 155 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 9 0 154 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 73 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 0 132 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 58 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 49 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 41 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 6 0 4 0 0 0 0 0 29 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 3 0 0 0 1 1 0 0 0 0 0 27 0 1 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 0 0 0 1 58 0 0 4 0 1 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 33 0 0 2 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 1 0 0 2 0 0 81 2 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 2 1 0 0 0 0 0 0 0 0 0 4 0 5 105 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 1 2 0 0 0 0 0 0 0 0 1 2 1 64 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 1 2 1 0 40 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 10]]\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" self._shutdown_workers()\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
"Exception ignored in: File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'<function _MultiProcessingDataLoaderIter.__del__ at 0x7fa4ff05e710>\n",
"\n",
"AssertionErrorTraceback (most recent call last):\n",
": File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1478, in __del__\n",
" can only test a child processself._shutdown_workers()\n",
"\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 1461, in _shutdown_workers\n",
" if w.is_alive():\n",
" File \"/usr/lib/python3.10/multiprocessing/process.py\", line 160, in is_alive\n",
" assert self._parent_pid == os.getpid(), 'can only test a child process'\n",
"AssertionError: can only test a child process\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"val Loss: 0.5068 Acc: 0.8516\n",
"Confusion Matrix:\n",
"[[ 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 79 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 44 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 21 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 15 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 1 0 0 18 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 91 2 0 4 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 2 129 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 65 0 6 0 0 1 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 98 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 41 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 37 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 17 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0 0 3 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 68 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 3 0 0 34 0 0 1]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3]]\n",
"\n",
"Training complete in 18m 12s\n",
"Best val Acc: 0.854578\n"
]
}
],
"source": [
"model_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n",
" num_epochs=30)"
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"id": "Gw__FuGYx0Rc",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "329f9646-00d6-4bc2-8f87-9151dfb5601c"
},
"execution_count": 49,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1688181301.1879928\n",
"Sat Jul 1 03:15:01 2023\n"
]
}
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"id": "BD6f3RK7W2lE",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 923
},
"outputId": "de919ed5-e1d1-4242-819a-491a24c1a729"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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oNgBtseUYig1AW2w5hvJr0RPmUORQSmsAwOl0wjCMRTQsVs273W4Eg0GEQiE4nU64XC4YhgGn0wmv1wvDMNDtdpFIJLBmzRpkMhkprWm32+h0OiiVShgbG8P4+DhqtRp8Ph+cTifq9Tq63S663S7K5TI6nY5pLC6XC4lEAtFoFM1mU36CwSBqtRra7TZqtRoajQbcbjfC4TAikQjcbjecTifa7TYajQZGR0exZs0aBINBdDodOBwOuFwuOc/hcAg7hd/xer2oVqt47bXXUCqV4Pf7UalUkM/nUa1W5TocL98XAHQ6HXm3AJZ8v0tJP4Qn+gaAhyrvxZgnAP1+P1wul2nCEXgA4PV6kU6nkclkpGSm2+1K3V4kEoFhGKjX65iYmACwH1wERKPRgMvlku91Oh0BeDQaFaBzsUilUmg0GshmswI+v98Pt9tt+r7H44HD4UAgEEAgEDDV3BEcBKPL5YLT6UQgEEAoFILD4YDH44HX60Wn04HL5UIkEkGr1UKz2VzEWeW70Atft9sVgPcDuA5FbAAeQDhx9ERxOBymiU0QBQIB+P1+OSccDiMejyMQCAhBWLe2c7lcSKVSiMfjyOVy6Ha7AmgAAhb+7nA4BMB+v9+koQhKwzCk4NTn8yEYDIpW4xg8Hg9cLpcAidfS96EWJAD5N3/4TO12G36/H5FIBPV6Ha1WSzS2fn/83Qbc0mID0CJ64ljB5/P5xPRsNpti9kUiEQQCATQaDQEPJ74VWADgdrvh9Xrh8Xjg9/vR7XZlkjabTQA9Zj8nPgFI7ef3+9FqtUTzEqQejweGYYiWYi8VammCxzAM+Hw+uFwuMR8JPP6uAejz+eR7TqdT7k1tSzNUvzs+r7YqbCCaxQagEq1ZrKaoy+UyabRWqyVmF8HECdjtdtFsNtHpdMTs4yQnQOir6YnebDYFBG63WyYxfyeYut0ufD4fPB4P2u02XC4XWq0WWq0Wut0u2u22AJZmH6/hdrvRarVQrVaRyWTg9/tRr9dF+3Eh0H4hsF+rzs7OolqtyvOUSiUEg0F4PB54PB40m81FALP61DYAzWJHQQ9BODkZLGEwRZupOvBQr9dRLpdRKpXQ6XTE3PP7/fB4PGg0Gpibm0OxWBSAaFOVWoc+oNvtNpmSXCjoUxKIvD81IkHHe/DH4XCgWCyiXC4jEAggHA7L9QkmHZTxeDzodruYnp5GtVoV/7RWq6FUKqHVaol21sGXpYRjsGW/2BpQiQ6oWM1Pmotutxu1Wg3Afs3XbDZF+/B7jUYD+Xwe09PTcLlcSKfTUh9WKBQwOTmJmZkZ0RjUWtRc2nSl1iKIfD6f+J/UrhyDBp3X64XP54PD4ZBr6+BRpVLBvn37EAgEMDAwIBqYms/qw01OTmLXrl0yxlKphFqthmazCZfLBZ/Ph0AggE6nI5aB1fc7GDj7UWwAWuRAIXKu3NR++hwdreT3C4UC2u02yuUyZmdnEQ6HRfMsLCygUqmYtAFNXnY5YxCEmlZrUg14gqnRaAg4rFqGkVWa0DR1s9ksxsbGJL1B35a+Iu+7b98+vP7665ienoZhGCiVSqhWqzJmLhI+n09Mbx63/qujo7Y5agNwkSwV/QR6QRFOUGo6rvhaY3U6HXQ6HeRyOZRKJanG1mYqzTyCdyk/jcEWmqCMtPL6brcbsVgMTqcTtVpNcokEL01Vt9uNTqcjeUZgf36Pfmy73cayZcsQj8dFY3a7XbRaLczOzuJ///d/MTExIQCiz8hgE+8TCARgGIZc15r3s0G3WGwAKqH5RW1GcbvdEjyhT+ZyuVCpVES7EDgAxIRst9toNpsoFoumqCHTBMyvEcDAfnAxt0aAud1uMSFprrZaLQQCAUQiEQn6eL1e8Tup6eh3Avv7sBDU9Xod1WoVPp8PlUoFExMTCIfD4g82Gg2Uy2UsLCygWCyKf1goFGAYBgKBgClow59QKIRGoyH30manDb7FYgPQItRIFIKSEUUAskMQTcF6vY5arYZQKCTmm/bBqLF4bYIrGAwuClx0Oh2JNIbDYfj9fgmE+P1+eL1e2Q+B/mK73YbX65WEfLFYFJYMAzX6OcLhMGq1GnK5nOTvWq0WFhYW4PF44PP5RMO3Wi25f6PRQL1eh9/vFwAyotvtdtFoNBAMBk0Jejv6+d5iA9AiBwrA0IxjoEP7YIZhoFgsynkEIQABGgDJowH7TdlKpYJgMCiRS+1nMqgB9IBGs1JHSmlitlot2SCGzBcd8CA1jWZsq9USE1rfSyf+aV7zeajxQ6GQaHkGfGjetlot0fAE9tHux/nrJDYALWKN0jHcz0mpk9d+v18maa1WQz6fRygUkrwgAIlW6sQ6J2Sr1UKtVjPl21qtFlwuF8LhMHw+n0Q3PR6PRBn1hCYQ6Zclk0kZn05NULNxIWGkkkweUtPo/3GhoNYulUool8uSbuCz6TF0Oh0xeyORiERnbTmw2AA8iDDEDvTyb9SE5EXWajV4vV60220UCgXRSNRuLpdLopeAWcvymE4nRCIRMWcJep/PB7/fj1KpZModkgDAhDfB1Gw2Ua1WxTyktgYgARxGLanlGJDhedS89XodxWJRFhMuCgQiTVtGgdvttnBIG42GCdC2mMUGoBJOPJqV9H20Nmu326KtGFTRDJl6vS7mGOlr7XbbZMbyM33PRqOBZrMp5iADIQQOUxOaUqYjnZqJovN9TJjX63WJpNIsZDDJ6qMyHcFgT6VSET+TviEjs9ok5vWoXcPhMKrVqgDblsViA9AiWjsxtK5pZtQeVqYK/TFyOWmWMhyvKxQIbgZoCDT6aNrEIzhIH6OJqO9JE5M5ykajIZqXZixZKxwztR61db1el0BTs9lEvV6XRUGb3jSXtZbUiwkjrPQtQ6EQ6vW6DcADiA1Ai+hEMRPf+m8r7Yw+G7UWNRU1AScoz+V5BHSj0ZAIajKZlJQDgcJgCK+jgyT0T2mC6tbsBKcmcDebTdHoTKv4fD4TrY5g1cRrUvAo1K60FGhi8nya4y6XC6FQCOVyWaKttpjFBuAvxZokdjqd8Pv94v9Rc+lJRO3k9/sRCoVMZT40Ia38TP03gUbzlPdhbpDHAHPAg2OhltMLAk1Qpg0ACICsDB5qzlAoJFQ0rfW4mHDsTLto0gAA4YISxARgt9tFIBBAMBgUs9z2Bc1iA/CXQlBQaL7pCa6DGQSJLloNhUKiUTj5DjThrPkxXbFO/47mHq9HDUO/jUJzlNfTY6R/6PP5UK/Xxc/kM2vzlvvpMcXCcfBczdyxVjhwwSBljhqWPjKDNzYAzWIDEItTD9r85CTWEw/oTTqmB8LhMNLpNJYvX46FhQWhbmlis9W/1PfV12VEkwwcnUuzgpIaVAddrEwej8eDYDCIXC4nEVtWbZBQTe3IiGYikYDf78f8/LyJHE4/U2tnvhea3dSsHAMBaBOxF4sNQCwGIJPnZLIAvXyYNvWAXi0g/b94PI5isWjyy6hFmX/TiXJdJsSx6D4t1Khas2l/TGsVBlT0vekrsj8MidS8j8738RrDw8NYtmyZEL0ZXdW1h/p7mk7H67KCg+9I509t6YkNwF8KJ5RmmeiJxMlKAHKS69A7OZWFQsEUoKAGJdB0klz3XyHYadrq4xpk/Jtj0dFJTnIdiAH274WYTqfF/OS1GfUslUpoNptIJBIYGhqS1Mrq1asxPj4Op9OJSCQCn8+Hqakp0cAsOqY/zHehUzOMANt1gIvFBiAWm4b0X+jXWPNY2h8zDEMqEKgJCCACQZuPPI+aippDg57HNf1N+2N63DpXyYisHp+OmEajUalL1H4sK/Or1arkCev1OlKpFGKxmKQvAoGAaOT5+XlTlBeAmOStVktykZq0QEDa0hMbgDAThd1uN0KhEMLhsGgIgk/n7ujzMGQP9ExZAk2LNjW1OcnIom4JSFYMo5E0cbXfpXu38Bl0XnAp/1LnF/k5r0kNxYJfJuCZSmi1WqLpotGo1CDStyNJnAsQFxZqSR0osqUn9huxCKsO2H9Fr/LajwMgzYnIGNGgodbS5iMnozZfdXqDIOIxJvV9Pp/Jj9L5QK0ddZpDM2aoza2ApTDlYq3OYPKefi6/63K5EI1GJUeqtS3fh+6PQ7qdDcDFYmtAJYwAUivQP+JkZfs9nbeLRCJCA+P3ufpbNaE1UU2GiW7pRx+P3yX4uBhwMmvzVkdBqaEBiClNjqlu9sTn43FtLuoqfeYS9XN0u12Ew2G0223Mzs6a7qf7hFLjanKDLWaxlyQlnPCc7Fqb0VciCFh5cNxxxwlxmn4Pr6UbObH0h7lCagkm7wGYoqwM5esGutZ2DwQQ/UWtdfUPx8SxM62hUyxa+1KbWa8FQIIvTqcTiUQCoVAIlUoFlUoFAExBJh0oshLCbdkvtgZUwrybBpzO5ZEt4vF4kMlkEI/HBRxkfOjUA6sVWq2W1Avqwl59XR1VJDho+ungjWbAcJzlcnkRSVunLHiM2onPqvmrNEM16LQlwLHRX2XlRTqdxszMjNDs6PdxYbCaxHYi3iw2AH8pDECQW0lNozUIV/FYLIZoNGpq9c7JzonPyUazjtqCtCzN99RhfK05tKmrx8mwPn3Ccrks1DGdf6O5SzMTwKICWU0Z0zWLBD0ByyoImpb0LX0+H2KxmHTlJtB1PpLvzs4BLhYbgL8Ur9crnEhStoCeH8UK8lAohFQqtagoVdfRWSN+DLZEo1GEw2F0u11MTU1henoafr8f8XhctKAOxtD342Rmno/mJgHKVhCkm7GlBAtjOfGpvdhqggW0fH4CkITxcrks46f5qnOO1NSDg4MAsGQ6Ru8/YctisX1A9LQfNZnuC8MIIs20ZDKJcDhs0oqcyLqvpjWJXiwWsXfvXiwsLMDtdiOTySAcDqNQKKBWqwm4tFakhqWfpjWzHhsDItls1uTH0Zd1Op2Ix+OyX4Xu78LSJt6H49DVDdSImqRAbc8E/bJly8QXpolKM1T7m7aYxdaAMLed1xE7mn+6Cxn7Z3KC0t9hQIUTVAd06vW6UMDy+TzGx8fh8/nQaDRQrVZRLpelxbuuuKA/yIANQWjVju12G5OTk8hms1i1apW0F6xUKqLFtD+ok/6a3M17zc3NSasK7oVhfV/0Zan5w+EwOp0OpqenTS03dCTYSuOzxQagmHJ68xEAiwIX3W5XmCSaZqYrFXg9ahLuWlSr1aQxE9sUUkOQBsYNXvReEvV6HUBvWy9dJcGx0RcslUrI5XKoVqtIJBJyfZ3TA3rpC6DnI/Ke9D2DwaDk+DRHVf/wfTFN43A4pCKErQvr9boEd/hObTGLDcBfBlG4oltpZsyheTweJBIJU3sKmoC61wu/z/0UKpWK1MsBMFVYUAMywEEAklRtNd+09ioUCiiXyzj55JMxPDws7BmdJqAm0vQ4HWgBYGrWpInb9Xods7OzYhlo01eb2HxupkJisRiq1aq8N+4loRcOOxjTk74HIE1FUrBYRGudKLFYDJFIxFSgqkuAADOnlBOw0WhIkatua8h2DdztlpqM/hg1ILWg3hmp0WhgYWFBKt2LxSLi8ThOOOEEOU6tp6OrJEsDPWrcUpUKgUAAmUwGkUhEOKIMAmmNSlDrhYI9Q+kzM3XBd6y7AdhiA1CoZ9R2OnSuJ+Tg4CCi0ahMOO2LcZLRJ9LJbfZX4fk6yc28I9tGkN7FHp61Wg3ZbBbFYhEAxKzsdDrIZDJIp9NIJBJYuXIlMpkMxsbGsGPHDtGGzGVaCd38sRbXtlotlMtlzM/PY3BwEGvXroXf78f27dtN+UWanhTts5KmVqvVxJ9lI2I+51LbmPWr9DUAmewmHYx1cmxwxKgmqwI4iXVSmcEQNkyiv6hNWJ1T1ODWnM5ut2vabXdoaAjValXM0UKhIPfWPV2q1SqGhoZw+umnw+v1YufOndIWHugxU5ikp4nL+7EHDPOF7XYbuVxONOnatWtN5Vg6n6dJA9oPJimB74JamIudJrD3u/QNAJeKvmn2hzbPtCaLx+PIZDKmBLeO5rEcyOVyCW9S08V4PlszxGIxuR/9R2qVcrmMdruNUqkkjXaZk+Q1CWAuDvl8HnNzc3C5XEgmk3A6ncjn86aAB/OT9Od0npHJdS4EXq9X/LiFhQXk83mJ9Orn93q9ouWYJ9RsHJrBOh3jdDoRCoVksbKljwC4lNAXA3ogoVnmdDqRSqWQyWQQCARMjA6tXYBekENXTfAcn8+HcDiM5cuXY3R0FMuXL5c28NlsFrt27cLU1BTK5TI6nY4EMNiFWlfbM+Svqyfq9TrGx8eRy+VMIX9qWJ3Li8fj0mSXnbcZDOJz8RkY7c1mszImnWphl27eR7fOcLlcUlFC0PJf3bDXBmEfAXApDciJrU1Fard4PI6hoSFTW0JgsXYDegEXXbPHiZ9IJLBx40acccYZGBkZQSQSEbO12WzK9l9vvfUW9uzZY9qBVm9ZTR+NUVhO/larhenpaWSzWVPynqLpcVZ+Jn+0P0itTGAuLCyIz6vbTtD85vNbS7VIbNDtLMijJThtAPYRAK3CXBZXbubMOLFSqZRoKg027f8RJJVKRdIZeg8/n8+HdevW4cwzz8SGDRuE4qXJzMlkEscffzzWrl2LN954A3v27BHTj5qp2+2iWq2KiQv0TFAAyOfzmJ+fl3SElY/KH83XpP9HEBAkBBuDRryWZvwwMksLwuFwSPSYz64DSfQFGQ0mCOv1et8HY/oWgPSBXC6XTChqAu7dB/SS4ABMwGOEkcTqQCCAeDwuleWBQADHHXccPvKRj2B0dNTUWVprKIfDgWg0ijVr1mDZsmUoFouYnJzEG2+8gcnJSYlKEiyczASO3+9Hs9nEwsICBgcHTTV+QE87aTYLAzO8FoVBFT4r/VNqa16bCXYApsgqfVvePxQKoVQqCah1ICgQCMhn/Sx9A8ClAjA053QQwul0Ci2Mfh0nDoVt55kScLlc0nXM5XIhHo9j7dq1WL9+PUZGRiQgobmhOjHNqgK/3490Oo0VK1Zg5cqVmJubw7vvvoutW7didnZW8oPUVgAkDZLL5QRsuq8nzWsW/+pAjO7CTXBrZo/mxLI0q9PpCHcV6LW0sEZ0O52OVGfw3fO5afrbZmgfA5B5OF1pQGKy3pdPawUCQOfWSOQmaD0eD4aHh7FhwwaMjIwsonQdyORixJD0tIGBAaTTaeRyOZPG08EVmozNZhMzMzPir9HfI2gAyHU1WZvJfV0+ZPWFeV/dirDRaJhKkqxpCFoKDM7w+fR5NMU1Y6cfpW8AqIUTg9oDgJhZ3N4LgCnnZ9U8pJQxXUDziyySwcFB6SCmk9+8v/bRqDk6nQ4WFhbwzjvvwOv1IhKJYM+ePcId1dFVAo0abGJiQnKATqdTfC9qQmozvT+Eprdps5opBZ2w1ykVakGak0BvsaLfqhcnHQDTUWaOQ1sa/SZ9C0D6ZIz4cWKRG8lJwsmpSdo6mc3JQ+0RCoVw/PHHIxKJmO63VKsIwBzUIf1sx44d2Lt3LwYGBjAxMSFbixFQNA+1iZnL5bBr1y5ks1mJymrzkv4nFxFGS2la60oOnbzXZqgeb7PZlDyg1sb0/zTVjewhHbjSW2Hravt+Y8n0LQA52XTEkJOafEVOHIKFnxO8XO0BiGZMp9MYGhoSQFETaLOM1+PxarWKYrGIer2OfD6PfD6P7du3Y/fu3SiXyxLxpDbSRbv6/vPz87IhJ4XPBfT4pKTAcT93Rkjp21KD8fvWxYK/61yeNtXJGdWcWT0e/Tw8F4Ap0NMv0pcA1AEQK0C4anM1plakttTt9nTlBP0rpi+oQfmjgUBhBPbll1/GK6+8gkqlAp/Ph+npaczOzpq0LkUfY8CFJqfubKbzkdYiXofDgUgkgpUrV2L9+vXweDyYmJjAm2++ibGxMdRqNQEXwa5NUIq2AJbKKfIdeL1e2fgFgCn6Su3JMfI994v0JQB1gIGTR1cNkP2v6wM5YbTWsU6aYDCIWCwmPV6skU/rRG40GtizZw+2bNmCrVu3otVqSc2h3jBF5w45BisjhhX5OqhE4OtnBiA5z+XLl+Okk05CLBbD2rVrEY1G4fV6sbCwgIWFBRSLRRNVjtfhYqKvzzHpKKi2GPiOAbMW5Lj5vjSbqB+k7wFIDaabCFGrWBs0cVJY2f8MJDC8rknX/B45noVCQf7N5/N488038eqrr4qGqFar0t+lUqmYKuGtfpxOF7hcLjEhO52OBIkIOr0YMG3x7rvvIhQKYf369chkMjj55JPR7Xaxb98+bNu2TXbN9Xg8UtdIzaavyzYWGnxk7egeNvodUnvrzUD7UfoWgNbgimEYph6dABaZjFZ/sdvtSvkQAx00n3SIHgCmpqbw6quv4s0338T09DRyuRzq9Tr8fj9WrFiBgYEB5HI5MQ9Z7cD92cms0W0rOHF1MIZ+KRcGbRpaTe7JyUkxtTdu3Ai/34/ly5ej2Wxi165d0qpDB3Q035Oi76WDUtTEfOcM7vDd64hrv0pfApATwdpOgkWjVhNoKZNIF6DqsHu5XEa1WkU8HhdwOBwOlMtljI+PY8+ePZidnUWtVkMymcT69euRTqcxOTkp12AxbDQaxczMDHK5nJAFCB5thlIz6ufR5AJqIY7b7XYjkUgglUqh3W5jfHxc8peNRgPFYlH2heD78Pl8Yi7q98h/dbGulenDc/ie2M7iQO+2n6QvAah9MgAmAB6ojZ7WZryG/mFPUZqAnPAM+IyMjODMM89EKBTCG2+8gYWFBQwPDyMcDkvjJE7MZDIpFRihUAgTExPIZrMmnqdOYmtSAQCTmcoiWKAXqeUeEGxZWKlUsGPHDlQqFXS7XezZsweFQkHGrltQaP9Pm6HWthN68aHo8ZL9Qz9QFwb3U2K+LwEImIMpAEwTxto/hRpHgxYwRwRZ2Ds4OIhYLGY6x+v1IhwOI5lMYnBwEMlkUmrmpqen4XA4MDIygqGhIfziF78QYnWn00EqlZIenSRjU/NwsdDRVmsHMv6u/UYSqmdnZ2XstAhcLhcWFhbE/7PyQ/X70mkVDT4m/vmOtZmpFz/dKVxXXJCZ0w/SlwDUkTv+zcmkmR86smelWXEl12bYwMAA1qxZI0waBiWA/cyZaDQqzXkLhQKy2Sza7TYymQwMo1cdMT8/L5xUwzCkKFfX+ul0A8ekgzQEgqZ/cdx8nrm5OVQqFaRSKaTTadRqNeGL8n3oQlttatMP1blU3l83GW42m1KAq0uZSOrW9YV8NpLc+0H6EoAUbdJpvqVOOWgzymoi6Wr6bnf/jkF+v19yh/wOKW7HHXcc8vk80uk0KpWKlC8Fg0EUCgXMzc1J9HV2dhaxWEx6fpbLZSSTSRkfJ781PaG1DxcHnc7w+XyIx+Ni+rJ9hdfrRTKZFIYKxWqqa0tA+5v6npokwIgvNR6vw/0HCVyWKJEsrqPIv87SlwDUSWKd5+OE0lqDovN45JJSUxC4ExMT+PnPf46NGzdiYGDA5Cd1u/t7sGSzWRiGgVQqJb6jz+dDrVZDpVKROr16vS5mZ7fbFeYKJy8XBvp3rD63Nl7iM7I+jznFRqMhZnC328XCwoJUchDgAEwmpvZ5NTDJIbXuX1iv14Wdo7sKELxcGEgcp6Z/L1/81036EoBLsUN0bkszOQhUfZxmmg58uN1uzM7O4rXXXsPQ0BBSqRSAnn/W7Xaxfft2vPXWW1I9T9/Q6dxfP7hs2TJUq1VMTU2hXq9LKwg2+eXmLp1OB+VyWfKVNOPou+qAEUHOZrskGtCkZTt5TUNjQv9AloCVDQNAurAx+NRqtTA7OyvVHPp8qy/N/wN2ZeP+Fv0g/aHnLWINlxNYTKJzgtC01Hktag1qHppP5I1ynzx+n/fh5CLYYrEYhoeHMTg4KKs9t8dOp9NIp9PSLsPhcEg+jtX67LStqy2o3awMHB6nptGV8Et9h6QEXfpkjfpqjQj0tCC5s+wUQCaNNlmtgRkt9AEZGf51l77VgLpLsyY3A70VXvt7/A6LTPUk1IW9fr8f4XB4ERuGOwcNDAygXq8jGo2KT1er1VCtVlEqlYSHGQqFMDg4iFwuZyoxKpfLGBwcRKfTQbFYNJnKDH6wMkFT2KjluIiQEaOJBYaxnxhOTUgtqN+DBiBgrojnfTT49XvkNbSJeyDpl1RE3wIQgGgtHd1byrzSSWZd/8bJx+LUbreLTCaDZDK5qBKcrQZrtZrU9zEAQQ2Xz+dRrVbFrFyxYgWSySTeeecd2cmIwRvmDAkkBi905zRyU9lxTe/vpxPj1NadTkfGaRi9aoel3pMGPTteW9+v1ZqwLgS29CkAKdbuY5rAzMmmGw/poAODGgyf02xLpVIIh8Pwer2o1+vSmn737t2YmJjA5OSkHG82mwgGg4hGo0in04u6a0ciEQwMDCCbzeLdd99dRHcDetpE080AyC6+3LqMPqPWmPyd/hvPYydvABKs0XV6vBcDURrQOglP01yzjrhg9IuGO5j0LQCXokxp6hYAk5YCevk3j8eDlStXmlpOFAoFAVepVEKn08HMzIzU+L377rsYHx+XDteNRgOVSsW0dzy5l8yPMco5PDyMPXv2IJfLSas/qzZm0S5NQJKxi8WiqVJCm8XM8zHnRhOUflun05E2idTAfE/M3RGAvBbQsyx0vxfNDV0qCNOv0tcA1JE9Mvh1rktXIgA9k/S4447D+vXrpXOaw+FALBYTH2xiYgLdbhczMzPodDrYt28fZmZmpGaPEb9CoSDJagZYCCzd/zMajSKRSCCXywHYr7ljsRj8fr+pGzcnOCOsxWJRzEhdPcHNUvT3DGP/NmqaiEASgAYX0NvQlP09dX6P70nX/FHr0XKwAdiTvgWgNcdn9ZEo1JQMIoRCIYyOjspW09SabrcbqVQKhUIB4+PjWFhYkCrzfD4v5h8nI/0ywzAQCoVMNDFquFAoJOkOnQphvo6gjMViQgQ3DEPa33NB0bWF3W5XupppTdXpdJDP5+H3+xeN1WotAJAyJZrxOpDlcOyv6IjFYsjn86ZyrqWu1c/StwCkdtMlOoz8seQHgClaSrBwB1qu5HrPdjb6JWAKhYLsbqQJ1NwbMBgMSthel/9Uq1XxB1k7yIk9ODiIYDCIlStXYnBwECMjI6jVahgbG0On00EymUSj0ZDyJg0MLjQ0I+mjkoNZrVZNfVJpKRBkBKausCCINbDI8+Q9rRFmW/ZLXwJQR+J00IL+nPUz5s60FtKpCqC3bTMAKfehKctJTbON32G0kYDknoG6CLhQKGB+fh6NRkMCKyeeeCICgQAGBgZEm01OTsreE263G2+//TZKpZKASO8NT8YNgytk2zAZT99TV0IAMJUj6QWIAOZ5NO11UGup9IQtfQpAAKaAAVdzUrVognk8HjHf2HKCW0wnk0lT5JG+F8t7uPGJ3+8XBoquGCDnkhqRlDTm6ZLJJKrVKiqVikQgWUI0NDQkO/ZOTU3hP//zP9FoNPBbv/VbOP300zE/P49t27bJZHe5XLIBKDW0DuTQx9PRVEZ/NX1ML0BcJHSnbEY9tV/N6+mSJl7Plj4FoGZ3WKOCVpMN6NGkGDGcnZ3F4OCgkLE13azRaGB+fl5Axw7aNGM5WTudjjBqQqEQUqmUmI3tdlu2ida5OJq7Ho8H1WoVs7OzmJ2dRavVwsaNGzE6OopyuYy9e/cin88vikTyuTSLR4OFZUos2qVFwPb7mifLdhk87vf7RWs6HA7htvI+XOQYhLJlv/QlADVNjP4b+5Mw6LFUFQSwf6JOTk7C7/djdHRUKt+LxSLm5+cxNzeHubk5E5gZEdTRQGo6ak2ad/SltPYjaLko7Ny5U3wsn8+H5cuXw+fzYWpqCrlcTpr5EoB6QSE3VNcP0vfV+xDy+rpOT0eICUqHw4FgMCjvjBHRYrGIUqkkWp0a3AagWfoWgJr/6Xa7UalUUKlUkEgkTMwXTcimT1Or1TA+Pi6Jd5fLhVKphFwuJ8DmbrvUdhRek8Jcm46msoxHB0cozWYTr7/+OpLJJNauXSttLiYnJxEMBoXOZm25oTW+9tUYCSX4+U6YXGfAhSAEesXMXES0b8f3VSgU0Gg0ZEHTRG2bBdOTvgWgrpFjbopsEZpoeqXWJla32xUTMJ/PA4BoqkgkIhONLBIdercSwck+4bl6u2yatPQBObGB/Zt7NhoNvPPOO2g0GojFYuh2u5Le0IEcBlio+biQ6LHwHAJOB1JIc+NeE0xx6P0irKR13XGc1+H+8DYLpid9CUBOFPpWDB5UKhXJhenCUkYQdZCB1Q0EqzbJ2KiJ2lBvmskJrLWFZp6w3TtNvmq1auKUZrNZqeFjSoJak3WCun2F1l70O2kWauK2BpNOFdBnJHAJKL3POxczjpGLBhcrwzAkyKQ3jLGlTwFIk4w+D1f8er2OQqGAZDIp/E+v1ysaQAvBwia3OgxPRoqO/nHVp1moq+8JSGtukrV7+hy9aWen08HQ0BDy+TxmZmaEj0pQaU1GkNEH5P7wmohNsSbW6avqgA435NTpCEqtVpMUC69LypoNPrP0JQABc0kMAwgATCwQnS5gAEVHAq1V4z6fD9FoVBL5BIHeSUnTwwgOah9tDnKBoFbTVQXsvD0xMYH5+Xl5HqZN9PUY5aWfp6+hNR5BzedknpDvRhfaao2pKX30JxcWFiQ/yc+Z4gF6vXhs6WMA0gQEejsD6XyYTkPwd05SbT7SLI1EIuLrMBnOXjBsNc/eLvp6ul+njkh2Oh2hsulIIkP+DocDlUpF+Jg0gdnSQtf8UeNqfqkV2HoB0CTtQCAgiwSPkZjA7+j6yFarhXw+b7qu1+tFMBg0lTHZsl/6dimihtINYhmx1E1tKTpfxupvTm6Xy4VEIiHRUBbQplIpLFu2DOl0GsFgUEL9wOJmtlbydzabRS6XWwR+ak5WxTPwQu3DCOhShHICh89g3cZMvxvt1/G5WThMU5Y/jIR2u13Z5Uk/G3OXvI4Nwp70tQZk/o3/cqLrTSatuUA9eXUFOjt8VSoVjI2NYXp6GplMBm63G5FIBLVaTcChAxYUzZWkCUjCMyc5zeNyuYx0Oo1ms4lsNisV+Jo1owMk2ifU/prOS1qJ0gy+EDiM8hqGIdqMf+tUhKaqad9VB75sAPbEBmCzKfu7sxiVfSw1s4OmIU08XaDKFAbPZ3v3UqkkdX7MiZHhooMznPic5PV6Xba8tjbjpTnYarUQDofRaDTg9/ul2p4AY+6QmlMDAICkXmiOWlMDus2ENm1pUtNiIHFbV1doCprH40E0GoXL5ZIFwk5D9KSvAciJFQwGkU6n4Xa7pYiWNXOcuGwwWy6XTclxax4skUjA7/eLRiQg4vG4bF/NsiEChQTtqakpVCoVac5EbayDHQzObN++XfirPKaZNFZ/FejRzSjat1tKM9Kv5LV1SkKb0AxGcYFiZJksmUQiIakLvceiLX0MQKA3IXWLPmoTlgpxQtHvY/UAQcHVnhM9Ho9jZGREJr3X65VACQBEo1HhSZZKJXi9XiQSCYlsEvwApBhWg4PV7zMzM9LVevny5fIZ73sgAFqjrgSt1RwmQ4ffczqdopUpjI7yPmwaxcWCSXyPx4NSqSSWhS096WsAMqjBmjhOmHw+j2KxKKYTV39+Ryet2cGM2oqakxXnzKMRRAQQKWPMr7GbGk1UAoM5RU5yAMLFJGmAQRQNOmuBrH5m7Ydq7UezURfq8pimp2leKrUgAcj8IGsb2TVA77prS0/6NgoK9Koc6D9p2lWhUBDGvw5Q8HdO8mq1KhFRUsioMfReCJysmuRN8rKuiEin08LEoammS3iozXj9eDwuCwWjjbqnDWDud6P9PpqDOu9prQIhs4faj6Yni23py3Y6HdlRl2NjI+FmsykAtM1Ps/S1BgRg0oCGYUgbiEqlgmw2KxtwWoGkw/4sfGXQwsr/JHDYSyUajcLhcJi0Ltkp1LC6lAfo9aMhqOgnbty4EZlMBmNjY9KWULe30FrQWkhsZbBYxwtAiAik4vH52Y+GAF5YWMD8/LwA0ufzSW60UqlIN247AmqWvgcgzVAmmEOhEMLhMKrVKvL5POLxuCS+gf2Tk+kHBjBKpZKs+NRCGoBArwLA7XZLGL9UKomZSa2pAx2asK0T8Zzk0WgUxx9/PBKJBOr1unRlA8xRTIJfa2WOSZdK8V+CRKci+FzUoPQf6ctOTk6iVqsJULlRTb1elwp8W/stlr4HIADRZLVaDZFIBOFwWIIG+Xwe0WhUEs0ATMWx9OFYFVGpVDAxMSFBCwJYk7M1P5OBCdLdstksFhYWBJBcIOiP8Ycg37Ztm0x2Bli0qae1HoG0VD4QMGs+snQ0zYwalrWTLAhmhJimst/vl5Yc5XIZ5XLZTj8cQGwAohdYYVt2v9+PUCiEWq2GbDaLYDCIVColtCp+hzsW0YQtFAqYmJiQ9n6BQABDQ0MYGRlBJBIB0ItEApDyIGoWMk24p4Imd+t8odvtRjwelw1Q5ufnpUsb84hLmZj03xhY0lxWgkPzXK1UNa2t6dNx4dH+YDgcRjAYNLXbt4MvS4sNQPSCMQyj+3w+0YLlchmTk5MAIAloMj/oC1HzNJtN2XU2EAigXC6jWCyiWq1izZo1Uj3PyU3NyqgmWSacvAQPAQhAfMhgMIi5uTnRoAx+MI1hjWySj8lOaASgNpOtgLUm8TUhPZ/PY3Z2dlFdJckG7ObG5Lttfi4tNgB/KQzGVKtVRCIRBINBSQmUSiXs3bsXkUgEfr8fqVTK5OfpagGWNOmKiH379sHlcuGEE05ANBo1RVV1pLTT6cjuSAQkTVztx9EPjMfjEtrXWk+DiqYjtRJNbZ2QB8xmKL/H90J/V39eKBSEUMBUCRcVq+9na78Diw3AXwrZJIxqplIpRKNR8V9IU6OGSqVSknMjkAjKcrmMYDAIn88n2nVmZgZerxerV6+WjTb5GcP61FQM8gCQTT2paVhBr9sSkgCuW0Rok5LXJ4+UgRqCjuPX7SusZUzal+S4OEa+g0AgIAtMLpeTwmBb+x1YbAAqoSapVCqyoWUoFBIzr9lsyk60nLQUmmDA/oZExWJRdsFlkGd+fh7Dw8NCH6NwgrJvqN4vvVQqAehpHpIC2HqC0Vfm9Ag4nbTnGLjAEGD8lzvb6sguheYnz6eVoNtkeDwehEIhJBIJeL1eITLYzJeDiw1AJWSzaF8wGAyazES9WxI1DSOGOpldLpeF3aKJ0NYiXsC8ZTOpa4lEAs1mEzMzM6YKBSvti0l81gRqjqb23SqVinAxrQsHq9Xpx+oyLV2U63Q60Wg0sHfvXlOntmAwiGQyiXA4jFqtJnsasqrElgOLDUCLUFtVKhXxmyKRiGmHIQY5dBW5rmxg9UOlUkEkEhEGCXmRQI+dAmCRNtTtLvQ9tGmpGS3WJsNkqbAFPQCht1nzk4zCEoTUhAS6Zsfo3B+/6/V6EYvFJMBUKBRkj0Hb9Dy42AC0CM0sJpgzmQwymYw0za3X6yiXy4jH43I+ABM4OGmpTZzO/R2yh4eHEYvF5HsaeARUt9tFPp/H3NycRGF1W3wrk0S3LtT+Hs1OUtr02LTvx/uybWAwGDRpQCsNjtudkR3DagePx4NCoYBCoWCzXg5DbAAuIdRAxWJR9nNPJBICBq7w7PLF7+iWC2zPsLCwAGB/CoO1gboHJyOa9B/L5TLGx8cxPz8vARjts/HaBJkmbZMAHQ6HRUuxFb21wBgwc2F5ffqgBKUubSLAOO5IJCJ72ZfLZQm82OA7dLEBeABhYr5UKskutpFIBKVSCa1WyxRk0ZqOkUoKgyUOx/6O1jQDmXdsNBoSWSVgqWmLxaL0VwF6O/MSRAz86BaETO4zzaCrN6yd3ThWEgd0SoXX0TnFbDaLcrkMAJKOSSQS8p64MNmBl0MXG4AHEKspGo/HMTAwIOZZNpuVgliPxyNmoA7lU6rVqvA0Z2ZmpPs2E+LkWxIMvC+BqIteaepys0+ajDR7ddcyMmN0DxddVqXLlvRz83ydymD7C3YKYBVGt7t/nwianrqLty0HFxuA7yHs9eLz+STHxXQC/zWM3oaYuiXgUr7a3NwcarUali1bZmLF6Jo8Bjny+bxp22nAvHmMbrakSdZ6NycuFpqIrXdD0ltTa42ptSzpaNPT08hms3A49u8GnE6n4XA4kM/nhfFiRz0PX2wAvodoLZjP55FIJBCPx4Udwxyd7pPCya01oa5IL5VKklrg7kPWXjOkb7G2j6biUnV97XZboqvc2YjXIXuGNYc6QMN8IhPl/CHo9b3z+TwmJyelf87g4KCUbNlRz/cnNgAPIp1OR9oMOp1OCchUq1Xha5bLZWk8y8S3Nt+AnmnHfp8ApJCWJGzdMgKAlPboaxIcWstxe+xcLidmIn0+tqLX21wDkIbBuoZQl0wxXcJSo2q1KhuPxmIxIaoXi0VZMGw5fLEBeAhCKhqDFOFwGLFYTKog5ubmJJCi6+00cZvalJUBxWJRqvBpRtI81Il7Blp0T1D6i+xPUyqVhERATQb0+tEAMLXR0G0lmKPU7fM5jkKhgH379iGfz5ueu91uI5fLIZ/Po1Qq2eB7H2ID8BCl2WxK4a3T6UQymZTARLlcxr59+zAwMIBYLCYTWBfX6n0o6L8xUEKQMRXBXYR08ATo+WpaWzFlQooZgcbkuq7U0LlAfT9t1jLgk81mMTU1JdX+iUQCAwMDCAQCKBaLpkoHO+Vw5GID8BCFk79YLEqbBjbHrVar0g+FXauZu6P20k2VgJ5pqn1FBkz09mY6yQ5AOlzrpktL1f5R+y3V/ZpaltQ63YipWq1iYWFBSp1YdTE8PAy/3y/7IJLUbYPv/YkNwMMQmpHFYhF+vx/xeFyqIqghZ2ZmhCVC0HJyUwvqVAA1jq46B3o5PYJHM1IYkCF1DIBoOA18HawxDEM4rNbFgMEXJtoZ0STJemhoCKFQCKVSCYVCQYjWNvjev9gAPExhDq5QKMDr9SISiaDT6WB+fl5aU7BcCYApvG8YhmzRRS2mu5/pbmbaRNRUMt0UiRFN+n26xby1NlBvkKJTGHyWQqEgjBj6rtFoFKlUSvxdTTWz0w1HR2wAHoGwJo8J9FgsJmZitVrFzMwMnE4n4vG4pCUIPvbxZERUlw2RhaK1HEHI5sHsz8laQ+u1GMGkNtV+HvuVckvuyclJ2S5Nt40gzWz58uXSVpAlRpVKxWa6HEXp676gRyraH8zlcuh2u0LaZru+qakpzM/Po9PpSB5O77Crk+OaIK3NR+23MSLK69D31B3HWFrEWkb2F6WW1AGT+fl5zMzMwOPxiBYnsDTTpdPpIJ/PS4mRzXQ5umJrwCMUNuXlBI/H4wiHw0gkEigUCqjVapiZmZH929nMib4cAahNTfprTDWw9IlV74FAwORL6pbyNEvZQJf5xVqtJmNuNpuYmpoSvqnuuMbObAQeC5Hz+bxoPzvocvTFYfTJG9VVAEdTWMITjUYFaNVqFdlsFpVKRUxPmp+hUEgS8DQbyVIBeoEZJtvL5TKmp6fR7XaxatUq6RFDlgqFlfE+n0/MUqYseN1KpYKZmRmUy2WJzHIhYFQ3Ho/D7XabfEN2Nvug/b5+mJp9owH74T/Tlv9/YvuAtthyDMUGoC22HEOxAWiLLcdQbADaYssxFBuAtthyDMUGoC22HEOxAWiLLcdQbADaYssxFBuAtthyDOX/AD+3+uNMwPc2AAAAAElFTkSuQmCC\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"visualize_model(model_ft)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "IMlakxzzW2lE"
},
"source": [
"## ConvNet as fixed feature extractor\n",
"\n",
"Here, we need to freeze all the network except the final layer. We need\n",
"to set ``requires_grad = False`` to freeze the parameters so that the\n",
"gradients are not computed in ``backward()``.\n",
"\n",
"You can read more about this in the documentation\n",
"[here](https://pytorch.org/docs/notes/autograd.html#excluding-subgraphs-from-backward)_.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"id": "PcSyPZ_7W2lE"
},
"outputs": [],
"source": [
"model_conv = torchvision.models.resnet18(weights='IMAGENET1K_V1')\n",
"for param in model_conv.parameters():\n",
" param.requires_grad = False\n",
"\n",
"# Parameters of newly constructed modules have requires_grad=True by default\n",
"num_ftrs = model_conv.fc.in_features\n",
"model_conv.fc = nn.Linear(num_ftrs, 44)\n",
"\n",
"model_conv = model_conv.to(device)\n",
"\n",
"criterion = nn.CrossEntropyLoss()\n",
"\n",
"# Observe that only parameters of final layer are being optimized as\n",
"# opposed to before.\n",
"optimizer_conv = optim.SGD(model_conv.fc.parameters(), lr=0.001, momentum=0.93, weight_decay=0.01)\n",
"\n",
"# Decay LR by a factor of 0.1 every 7 epochs\n",
"exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ufSETcSxW2lE"
},
"source": [
"### Train and evaluate\n",
"\n",
"On CPU this will take about half the time compared to previous scenario.\n",
"This is expected as gradients don't need to be computed for most of the\n",
"network. However, forward does need to be computed.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "v7mm_hpfW2lF",
"outputId": "1bfca85f-2715-48b2-bc51-39a351ecf3fc"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 0/29\n",
"----------\n",
"train Loss: 3.2579 Acc: 0.1649\n",
"Confusion Matrix:\n",
"[[ 6 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 38 22 4 17 8 4 1 0 0 0 1 0 0 0 3 3 1 0 0 0]\n",
" [ 1 11 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 53 5 19 10 1 10 0 0 0 0 0 0 1 1 5 0 0 4 0]\n",
" [ 1 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 19 23 3 32 0 3 0 0 0 0 0 0 2 3 11 2 0 1 0]\n",
" [ 5 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 10 1 10 3 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 27 2 7 2 1 2 0 0 0 0 1 1 2 0 3 0 0 1 0]\n",
" [ 1 0 2 0 1 4 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 10 4 4 8 1 2 1 0 0 0 0 0 2 1 1 2 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 5 3 3 1 2 0 0 0 0 0 0 0 1 2 1 0 0 0 0]\n",
" [ 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 10 1 0 2 0 2 0 0 0 0 0 1 0 2 1 1 0 1 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 2 1 8 0 1 0 0 0 0 0 0 3 3 3 4 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 2 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 2 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 9 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 2 0 1 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 2 1 4 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 7 1 6 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11 5 2 7 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 5 0 0 2 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 27 6 4 1 0 3 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 8 1 17 0 3 0 0 0 0 0 0 1 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 3 1 2 1 0 0 0 0 0 0 0 0 1 0 4 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 6 1 1 2 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 2 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 1 2 0 0 0 0 0 0 0 0 1 2 0 2 0 0 0]\n",
" [ 0 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 8 1 2 6 0 3 0 0 0 0 0 0 0 1 9 2 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 1 10 0 1 1 0 0 0 0 0 1 0 2 5 0 0 0]\n",
" [ 3 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 58 50 6 14 11 4 3 0 0 0 1 0 0 4 0 7 0 0 0 0]\n",
" [ 4 13 4 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 30 106 9 14 11 1 23 0 0 0 1 0 0 0 0 9 3 0 1 0]\n",
" [ 5 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 31 35 7 40 0 8 1 0 0 0 0 0 2 0 3 5 0 4 0]\n",
" [ 6 3 6 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 13 21 9 54 14 1 5 0 0 0 0 0 0 0 6 11 2 0 1 0]\n",
" [ 4 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 15 23 10 90 0 5 2 0 0 0 0 0 1 0 5 3 0 6 0]\n",
" [ 1 6 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 29 14 2 4 2 3 10 0 0 0 0 0 0 1 1 3 1 0 2 0]\n",
" [ 4 7 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 10 54 3 14 7 2 32 0 0 0 0 0 0 2 0 1 0 0 1 0]\n",
" [ 1 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 13 17 2 13 0 10 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 17 2 7 1 2 0 0 0 0 0 0 1 1 0 1 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 22 1 6 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 4 19 0 0 2 0 0 0 0 0 1 0 0 0 0 2 0]\n",
" [ 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 11 1 3 2 0 4 0 0 0 0 0 0 1 4 2 1 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 23 0 5 2 0 10 0 0 0 0 0 6 0 2 4 2 0 4 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 2 6 7 0 1 1 0 0 0 0 1 0 0 4 7 0 1 0]\n",
" [ 2 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 22 5 6 6 2 3 0 0 0 0 0 0 0 12 11 8 0 2 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 39 5 9 14 0 4 0 0 0 0 0 0 1 5 26 3 0 0 0]\n",
" [ 2 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2 13 10 3 15 0 10 0 0 0 0 0 0 0 3 7 8 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 1 1 1 2 0 0 0 0 0 0 0 0 1 3 2 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 16 3 5 3 1 3 0 0 0 0 0 0 0 0 13 3 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 5 0 8 0 1 0 0 0 0 0 0 0 2 0 1 0 0 0]]\n",
"val Loss: 2.6333 Acc: 0.3339\n",
"Confusion Matrix:\n",
"[[ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 44 1 4 10 1 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0]\n",
" [ 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 30 8 3 4 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 35 1 12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 2 0 0 1 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 7 0 0 2 0 0 0 0 0 0 0 1 0 0 4 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 11 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 8 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 3 16 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 3 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 2 2 1 1 0 0 0 0 0 0 0 5 0 1 4 2 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 92 1 5 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 83 7 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 72 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 26 1 1 57 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 1 70 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 47 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 33 0 0 0 0 41 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 3 0 0 1 0 0 0 0 0 1 0 4 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 12 2 5 1 0 0 0 0 0 0 0 10 0 3 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 2 0 0 0 0 0 0 0 0 0 2 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 2 0 2 0 0 0 0 0 0 0 0 0 0 30 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 11 4 1 0 0 0 0 0 0 0 0 4 0 13 30 1 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 13 0 6 0 0 0 0 0 0 0 0 0 4 1 13 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 5 3 2 0 0 0 0 0 0 0 0 1 0 1 7 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]]\n",
"\n",
"Epoch 1/29\n",
"----------\n",
"train Loss: 2.6634 Acc: 0.3082\n",
"Confusion Matrix:\n",
"[[ 8 9 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 42 12 0 23 0 5 1 0 0 0 0 1 0 0 3 2 0 0 1 0]\n",
" [ 3 40 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 46 3 7 1 2 16 0 0 0 0 0 1 0 3 9 1 0 0 0]\n",
" [ 1 1 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 8 24 4 29 0 0 5 0 0 0 0 0 0 1 9 8 0 0 0]\n",
" [ 3 1 0 10 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 8 0 10 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 22 0 1 1 2 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 2 0 4 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 10 2 3 0 0 3 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 3 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 7 0 4 0 0 0 0 0 0 0 0 0 0 4 1 0 0 1 0]\n",
" [ 1 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 1 1 1 0 2 0 0 0 0 0 1 0 3 4 0 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 10 0 0 1 0 0 0 0 0 0 1 8 3 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 9 1 0 2 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 6 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 4 1 9 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 10 0 1 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 29 0 3 0 0 4 0 0 0 0 0 1 0 0 5 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 20 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 3 4 0 0 0 0 0 0 0 0 0 0 3 2 1 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 0 0 1 0 0 0 0 0 2 1 1 6 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 3 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 4 1 1 0 0 0]\n",
" [ 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 5 0 4 6 0 1 0 0 0 0 0 0 0 2 15 1 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 4 0 6 0 0 0 0 0 0 0 0 0 0 3 4 0 0 0]\n",
" [ 6 6 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 89 33 2 18 3 2 5 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 5 24 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36 112 3 4 4 1 13 0 0 0 0 0 7 0 3 14 1 0 0 0]\n",
" [ 1 0 7 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 57 2 56 0 1 5 0 0 0 0 0 0 1 1 3 0 0 0]\n",
" [ 6 1 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 19 7 2 109 1 0 1 0 0 0 0 0 1 0 3 2 1 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 25 2 129 0 0 0 0 0 0 0 0 0 2 1 5 0 0 0]\n",
" [ 6 6 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 13 0 4 0 12 13 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 31 3 0 0 3 86 0 0 0 0 0 0 1 0 3 1 0 0 0]\n",
" [ 0 2 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 17 1 10 0 3 14 0 0 0 0 0 0 0 2 1 0 0 0]\n",
" [ 6 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 10 1 14 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 23 0 0 0 2 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 1 19 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 11 5 0 6 3 4 0 0 0 0 0 0 0 0 5 2 0 0 0 0]\n",
" [ 0 5 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 5 1 0 11 0 0 0 0 0 15 0 4 6 1 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 8 2 8 0 0 0 0 0 0 0 0 0 4 4 4 0 0 0]\n",
" [ 1 1 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 6 1 4 4 0 2 0 0 0 0 0 0 0 39 19 0 0 0 0]\n",
" [ 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 28 2 1 1 0 6 0 0 0 0 0 2 0 11 57 1 0 1 0]\n",
" [ 0 2 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 7 9 0 8 0 1 1 0 0 0 0 0 0 5 6 28 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 5 1 2 0 0 0 0 0 0 0 0 0 0 1 2 1 0 1 0]\n",
" [ 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 12 3 5 0 0 3 0 0 0 0 0 0 0 1 17 2 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 6 0 0 0 0 0 0 0 0 0 2 1 1 0 0 0]]\n",
"val Loss: 2.2436 Acc: 0.4159\n",
"Confusion Matrix:\n",
"[[ 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 4 0 23 1 9 0 0 0 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 0 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 37 0 6 3 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 1 9 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 8 3 23 0 1 2 0 0 2 0 0 0 1 0 8 0 0 0]\n",
" [ 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 1 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 4 1 2 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 2 1 0 0 0 0 0 0 1 0 0 2 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 1 4 0 0 2 0 0 0 0 1 0 0 0 6 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 1 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 2 14 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 10 0 5 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 3 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 3 0 0 0 0 0 1 1 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 2 1 0 0 0 0 0 0 0 5 0 0 8 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 3 1 3 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52 21 0 24 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 112 1 11 2 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 37 4 23 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 91 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 91 0 0 0 0 0 0 0 1 0 1 1 1 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 5 0 1 0 16 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 31 0 0 0 0 51 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 0 11 0 1 13 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 8 0 12 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 9 0 0 1 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 6 0 4 3 0 0 0 0 0 3 0 3 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 10 0 0 1 0 0 0 0 0 14 0 3 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 5 0 0 0 0 0 1 0 2 0 2 0 4 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 8 0 10 0 0 0 0 0 0 0 0 0 0 29 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 6 0 0 0 0 0 0 0 0 13 0 10 31 1 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 7 0 0 0 0 0 0 0 1 0 1 5 23 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 3 0 0 0 0 0 0 0 0 0 0 2 6 1 0 3 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 6 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0]]\n",
"\n",
"Epoch 2/29\n",
"----------\n",
"train Loss: 2.4058 Acc: 0.3801\n",
"Confusion Matrix:\n",
"[[ 14 8 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 40 6 2 15 1 5 3 0 1 0 0 0 0 1 4 7 0 0 0 0]\n",
" [ 1 55 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 13 35 1 11 0 2 4 0 0 0 0 0 4 0 2 12 1 0 0 0]\n",
" [ 0 1 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 5 16 1 33 0 0 8 0 0 1 0 0 3 2 3 8 0 0 0]\n",
" [ 0 1 0 24 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 4 0 1 52 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 8 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 7 0 2 0 0 2 0 0 0 0 1 0 0 2 1 0 0 0]\n",
" [ 3 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 3 0 4 0 1 0 0 0 0 0 0 0 0 1 4 0 0 2 0]\n",
" [ 1 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 1 0 4 0 0 0 0 0 3 0 2 6 0 0 0 0]\n",
" [ 1 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 1 2 0 1 2 0 0 0 0 1 0 3 6 6 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 2 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 4 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 2 0 7 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 0 0 0 1 4 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 0 3 0 0 2 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 15 2 1 10 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 7 23 1 1 0 0 3 0 1 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 8 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 1 0 0 0 0 0 0 0 0 0 2 8 3 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 0 0 1 0 0 0 0 0 0 1 3 5 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 2 0 0 0 0 0 0 0 0 0 1 2 1 0 0 0]\n",
" [ 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 1 0 0 0 0 0 0 0 0 2 4 1 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 4 0 4 8 0 0 0 0 0 0 0 5 0 4 10 1 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 13 0 0 0 0 0 0 0 1 0 0 2 4 0 0 0]\n",
" [ 9 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 103 24 1 18 2 1 1 0 1 0 0 0 0 0 1 3 2 0 0 0]\n",
" [ 3 18 2 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 26 121 3 11 5 2 10 1 0 0 0 0 9 0 1 14 0 0 0 0]\n",
" [ 0 4 8 0 2 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 72 5 29 1 0 4 0 0 1 0 0 1 2 3 4 0 0 0]\n",
" [ 7 3 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 8 4 1 112 1 0 0 0 0 0 0 0 4 1 6 3 1 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 8 5 140 0 0 0 0 0 0 0 0 0 1 3 7 0 0 0]\n",
" [ 5 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 7 0 0 0 32 9 0 2 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 8 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 23 2 1 3 0 93 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 2 9 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 15 1 5 0 2 19 0 0 1 0 1 0 0 1 2 0 0 0]\n",
" [ 7 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 8 1 11 0 1 0 0 2 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 16 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 6 16 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 0 19 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 1 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 6 0 7 0 3 0 0 0 0 0 0 0 1 4 1 1 0 0 0]\n",
" [ 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 14 0 3 3 0 10 0 0 0 0 0 25 0 3 4 0 0 1 0]\n",
" [ 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 8 4 3 0 0 1 0 0 0 0 2 0 4 7 3 0 0 0]\n",
" [ 0 3 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 8 2 6 1 2 0 0 0 0 0 0 1 0 43 13 0 0 1 0]\n",
" [ 1 4 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 17 1 5 1 1 6 0 0 0 0 0 2 1 9 68 1 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 7 6 1 11 0 0 1 0 0 0 0 2 2 4 7 27 0 1 0]\n",
" [ 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0 2 0 0 0 0 0 0 0 0 0 0 2 2 1 0 0 0]\n",
" [ 2 9 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 1 1 3 0 0 0 0 0 0 0 1 0 3 19 0 0 4 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 8 0 0 0 0 0 0 0 0 1 0 2 1 0 0 0]]\n",
"val Loss: 2.1408 Acc: 0.4536\n",
"Confusion Matrix:\n",
"[[ 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 18 3 0 11 4 13 0 0 3 0 0 0 0 0 9 0 0 0 0 0]\n",
" [ 0 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 2 0 2 17 0 1 11 1 1 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 39 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0]\n",
" [ 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 7 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 0 0 1 1 2 0 0 2 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 3 0 0 3 1 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 1 3 0 0 1 0 4 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 8 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 6 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 1 0 0 2 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 74 7 0 13 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 8 102 0 5 8 2 1 0 0 0 0 0 0 0 5 1 0 0 0 0]\n",
" [ 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 0 55 0 0 2 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 78 3 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 3 0 0 2 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 1 0 74 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 18 2 0 5 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 0 0 3 0 7 2 0 0 0 0 0 0 0 6 0 0 0 1 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 5 4 1 4 0 0 0 0 0 7 0 7 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 11 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 6 0 0 0 1 0 0 0 0 0 0 0 0 0 46 0 0 0 0 0]\n",
" [ 0 1 3 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 5 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 21 36 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 1 0 21 0 0 0 0 0 0 0 0 0 3 0 12 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 5 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0 3 0 0 0 9 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]]\n",
"\n",
"Epoch 3/29\n",
"----------\n",
"train Loss: 2.2485 Acc: 0.4093\n",
"Confusion Matrix:\n",
"[[ 21 10 3 0 3 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 24 6 1 17 0 8 0 0 2 0 0 0 0 0 7 4 0 0 1 0]\n",
" [ 6 58 3 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 1 0 4 33 1 7 5 1 5 0 1 0 0 0 3 2 4 6 0 0 0 0]\n",
" [ 0 1 28 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 4 29 4 20 0 0 2 0 0 2 0 0 1 3 4 5 0 1 0]\n",
" [ 0 0 0 28 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 5 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 1 0 49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 9 0 3 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 2 0 3 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 1 1 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 3 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 3 0 6 0 2 0 0 0 0 0 0 0 0 4 2 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 6 0 0 6 1 3 0 0 0 0 0 1 0 3 5 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 2 3 0 0 3 0 0 0 0 0 1 1 7 4 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 0 1 2 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 5 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 9 1 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 12 1 1 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 9 0 7 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 14 4 1 8 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 9 1 0 1 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 6 18 1 0 0 1 2 0 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 15 0 9 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 4 1 0 0 0 0 0 0 2 1 1 3 1 0 0 2 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 3 1 4 5 1 0 0 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 5 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 3 5 1 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 9 0 2 3 0 2 2 0 1 0 0 0 0 0 4 0 1 13 1 0 1 0]\n",
" [ 0 0 5 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 3 0 3 0 0 0 0 0 0 0 0 1 2 1 6 0 0 0]\n",
" [ 4 4 1 3 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 92 29 1 12 2 8 2 0 2 0 0 0 0 0 2 3 0 0 1 0]\n",
" [ 2 13 1 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 26 138 2 6 4 0 13 0 0 0 0 0 2 2 3 13 0 0 0 0]\n",
" [ 0 1 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 74 0 36 0 0 5 0 0 1 0 0 0 3 1 8 0 0 0]\n",
" [ 2 4 4 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 5 1 115 0 1 1 0 0 0 0 0 2 0 7 1 0 0 0 0]\n",
" [ 0 1 6 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 17 1 127 0 1 0 0 0 3 0 0 1 1 1 5 0 0 0]\n",
" [ 3 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 6 0 3 1 35 12 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 17 2 0 0 1 106 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 1 8 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 16 0 8 0 1 22 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 6 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 7 0 14 1 2 0 0 4 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 26 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 21 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 7 0 5 1 3 0 0 0 0 0 3 3 1 6 1 0 0 0 0]\n",
" [ 0 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 11 0 3 1 0 10 0 0 0 0 0 26 1 2 6 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 6 3 3 0 3 1 0 0 0 0 0 2 2 3 7 0 1 0]\n",
" [ 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 6 0 5 3 0 2 0 0 0 0 1 1 1 48 11 2 0 0 0]\n",
" [ 1 2 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 17 0 3 1 1 4 0 0 0 0 0 2 1 14 68 1 0 2 0]\n",
" [ 0 1 11 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 1 7 0 0 0 0 0 1 0 0 2 4 5 32 0 0 0]\n",
" [ 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 1 0 0 0 0 0 0 0 0 0 0 5 3 0 0 1 0]\n",
" [ 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 11 1 1 0 0 1 0 0 0 0 0 1 1 5 17 0 0 6 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 1 4 0 0 0 0 0 1 0 0 1 0 2 3 0 0 0]]\n",
"val Loss: 1.8998 Acc: 0.4931\n",
"Confusion Matrix:\n",
"[[ 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 8 1 14 3 11 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 4 2 4 0 1 0 0 0 0 0 0 0 0 8 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 21 0 24 0 0 4 0 0 1 0 0 0 0 7 4 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 1 1 2 0 0 0 0 0 0 0 0 0 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 1 0 0 0 0 0 0 0 0 0 8 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 6 0 5 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 9 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 0 0 0 0 0 0 0 4 2 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 9 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 2 0 1 0 0 0 0 0 0 0 0 1 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 5 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0]\n",
" [ 7 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 45 21 1 18 0 4 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 119 1 5 4 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 56 0 24 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 96 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 6 0 0 2 29 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 10 1 0 0 0 70 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 7 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 0 7 0 4 0 0 5 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 9 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 2 3 0 0 1 0 5 1 0 3 3 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 6 3 0 0 0 0 0 0 0 10 0 0 8 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 11 0 0 2 0 0 0 0 0 1 0 1 0 0 1 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 7 1 0 0 0 0 0 0 1 0 0 19 18 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 0 0 0 1 0 1 60 0 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 3 0 14 0 0 0 0 0 0 0 0 0 0 9 16 0 0 1]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 7 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 6 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]]\n",
"\n",
"Epoch 4/29\n",
"----------\n",
"train Loss: 2.1364 Acc: 0.4332\n",
"Confusion Matrix:\n",
"[[ 28 6 0 0 1 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 23 6 1 20 2 6 0 0 4 0 0 0 1 0 3 2 0 0 3 1]\n",
" [ 5 54 2 0 2 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 3 37 2 12 2 0 8 0 2 1 0 0 3 0 3 5 0 0 0 0]\n",
" [ 0 0 33 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 10 19 0 15 0 2 11 0 0 1 0 0 0 0 2 10 0 0 0]\n",
" [ 1 0 0 25 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 7 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 52 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 10 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 3 0 9 0 0 0 0 1 0 0 0 0 0 2 1 1 0 0 0]\n",
" [ 2 3 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 1 2 0 2 0 0 0 0 0 0 0 5 6 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 2 3 1 0 3 0 0 0 0 0 1 1 3 8 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 4 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 4 0 0 1 1 8 0 0 0 0 0 1 0 0 3 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 7 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 5 2 0 0 0 0 0 0 0 14 1 0 7 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 0 2 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 7 17 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 3 20 0 5 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 1 3 0 0 0 0 0 0 0 1 0 0 3 6 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 7 0 1 0 0 0 0 0 0 0 0 1 0 2 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 5 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 2 2 0 1 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 1 3 0 3 4 0 1 0 0 0 0 0 4 1 3 9 1 0 0 0]\n",
" [ 1 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 8 0 0 0 0 0 0 0 0 0 1 3 4 0 0 0]\n",
" [ 8 6 0 3 3 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 91 24 0 18 1 9 0 0 1 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 3 10 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 19 150 2 13 5 1 10 0 1 0 0 0 5 0 1 7 0 0 0 0]\n",
" [ 0 1 5 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 13 75 2 29 0 1 4 0 0 2 0 1 0 2 1 5 0 0 0]\n",
" [ 7 2 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 12 6 0 112 1 1 2 0 3 0 0 1 0 0 2 0 1 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 26 2 127 0 0 0 0 0 1 0 0 0 1 1 4 0 0 0]\n",
" [ 8 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 3 0 2 0 44 9 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 13 0 2 1 2 104 0 0 0 0 0 3 0 0 2 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 5 17 0 5 0 1 25 1 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 7 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 9 0 11 0 2 0 0 9 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 13 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 22 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 20 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 9 0 1 1 3 1 0 0 1 0 0 0 1 6 3 0 0 0 0]\n",
" [ 2 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 15 0 4 0 0 9 0 0 0 0 0 24 1 1 5 1 0 1 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 7 2 9 0 0 2 0 0 0 0 0 1 1 1 6 0 1 0]\n",
" [ 2 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 5 0 5 1 0 0 0 1 0 0 0 0 0 53 7 3 0 0 0]\n",
" [ 1 3 2 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 16 0 2 0 0 1 0 0 0 0 0 2 0 10 77 2 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 7 1 9 0 1 1 0 0 1 0 0 1 3 4 37 0 0 0]\n",
" [ 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 1 1 0 0 0 0 1 0 0 0 0 0 0 3 1 0 5 0]\n",
" [ 1 9 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 1 7 1 5 1 0 1 0 0 0 0 0 0 0 2 11 0 0 10 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 5 0 0 0 0 0 1 0 0 0 1 0 3 0 0 0]]\n",
"val Loss: 1.8195 Acc: 0.5099\n",
"Confusion Matrix:\n",
"[[32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 1 15 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 1 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 3 15 2 2 4 0 5 0 0 0 0 0 5 0 1 6 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 22 0 22 0 0 5 0 0 0 0 0 0 0 4 4 0 0 0]\n",
" [ 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 0 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 1 0 1 0 0 0 0 0 0 0 0 8 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 4 0 0 3 0 0 0 0 0 0 0 1 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 3 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 1 1 0 0 0 0 5 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 6 0 0 0 0 0 0 0 6 1 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 5 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 13 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 1 0 0 0 0 0 0 1 0 1 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 3 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 1 5 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 1 0 0 0 0 1 0 0 0 0 0 2 0 0 12 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 3 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0]\n",
" [ 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 68 7 0 14 0 0 1 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 96 2 8 3 0 6 0 0 0 0 0 4 0 1 9 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 69 0 15 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 1 93 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 1 0 0 1 18 5 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 1 0 0 0 76 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 6 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 15 2 0 6 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 11 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 3 0 0 3 0 0 1 0 3 2 0 5 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 2 0 1 0 0 0 0 0 23 0 3 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 5 0 0 2 0 0 0 0 0 1 2 0 3 0 1 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 5 0 0 0 0 0 0 0 0 0 0 39 5 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 8 0 6 54 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 5 0 11 0 0 0 0 0 0 0 0 0 2 8 16 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 0 1 0 0 0 0 5 0 0 0 0 0 0 0 2 6 0 0 10 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 6 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]]\n",
"\n",
"Epoch 5/29\n",
"----------\n",
"train Loss: 2.0517 Acc: 0.4503\n",
"Confusion Matrix:\n",
"[[ 35 5 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 23 6 0 13 0 6 0 0 8 0 0 0 2 0 2 3 1 0 0 0]\n",
" [ 3 56 2 0 3 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 8 38 1 13 1 1 3 0 2 0 0 0 1 0 2 3 1 0 3 0]\n",
" [ 1 1 32 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 3 27 1 20 0 0 3 1 0 1 0 0 2 3 0 8 0 1 0]\n",
" [ 1 0 0 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 3 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 2 0 0 51 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 5 0 3 1 0 2 0 0 0 0 0 1 3 0 0 1 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 5 1 1 1 1 2 0 0 0 0 0 2 0 4 1 0 0 2 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 1 6 0 0 3 0 0 0 0 0 0 0 4 8 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 3 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 0 2 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 8 0 0 3 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 0 0 1 1 4 0 0 0 0 0 1 0 1 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 1 0 0 2 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 0 0 0 0 0 0 13 4 0 4 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1]\n",
" [ 0 8 0 0 2 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 21 0 1 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0]\n",
" [ 0 2 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 15 0 9 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 6 2 2 0 1 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 1 0 0 0 7 3 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 1 0 0 0 0 0 2 0 3 0 1 0]\n",
" [ 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 10 0 1 2 0 1 2 0 2 0 0 0 0 0 5 0 2 11 1 0 1 0]\n",
" [ 0 1 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 3 0 5 0 0 0 0 0 0 0 0 0 1 3 8 0 0 0]\n",
" [ 13 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 102 24 3 10 0 3 4 0 3 0 0 0 0 0 3 1 1 0 0 0]\n",
" [ 2 17 1 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 22 136 7 8 5 1 10 0 1 0 0 0 4 0 2 8 1 0 1 0]\n",
" [ 0 1 11 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 77 0 26 0 0 8 0 0 3 0 3 0 1 5 2 0 0 0]\n",
" [ 5 3 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 123 0 0 1 0 2 0 0 0 3 0 4 1 0 0 2 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 19 2 135 0 0 0 0 0 2 0 0 1 0 0 3 0 0 0]\n",
" [ 9 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 3 1 2 0 42 8 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 5 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 15 1 1 0 0 106 1 0 0 0 0 2 0 0 2 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 16 2 8 0 0 28 0 0 1 0 0 0 0 2 1 0 0 0]\n",
" [ 7 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 3 0 10 0 2 1 0 11 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 18 0 0 0 1 2 0 2 4 0 0 0 0 0 1 0 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 1 17 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 4 0 5 2 6 3 0 0 0 0 1 0 1 4 3 0 0 0 0]\n",
" [ 0 4 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 11 0 4 1 0 3 0 0 0 0 0 32 0 2 4 0 0 2 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 5 3 6 0 0 0 0 0 0 0 3 0 2 5 2 0 0 0]\n",
" [ 6 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 5 1 7 2 0 1 0 0 0 0 0 0 0 55 11 0 0 0 0]\n",
" [ 2 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 14 1 2 2 0 2 0 0 0 0 0 0 1 7 80 1 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 9 0 7 0 0 3 0 0 0 0 0 1 3 7 35 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 0 0 0 0 1 0 0 0 0 0 3 2 0 0 3 0]\n",
" [ 3 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 9 1 1 1 0 0 0 0 0 0 0 0 0 2 13 0 0 12 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 6 0 0 1 0 0 2 0 0 1 1 2 2 0 0 1]]\n",
"val Loss: 1.7644 Acc: 0.5135\n",
"Confusion Matrix:\n",
"[[17 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 27 0 0 9 3 0 0 0 3 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 60 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 8 0 2 2 3 0 3 0 0 0 0 0 4 0 0 3 0 0 0 0]\n",
" [ 0 2 20 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 7 0 22 0 0 6 0 0 0 0 0 0 0 2 1 0 0 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 1 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 1 1 0 0 0 0 0 0 0 0 4 2 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 2 0 0 1 0 0 0 0 0 0 1 1 0 0 3 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 3 0 0 0 0 0 5 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 5 4 0 0 0 0 0 0 0 9 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 10 0 8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 4 0 3 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 1 0 0 0 1 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 10 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 92 0 0 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 40 53 1 3 3 0 8 0 0 0 0 0 7 0 1 4 0 0 0 0]\n",
" [ 0 0 11 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 51 0 16 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 75 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 1 93 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 16 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 26 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 1 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 0 1 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 2 0 0 2 0 0 0 0 3 4 0 5 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 1 0 0 0 0 0 0 0 24 0 4 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 0 0 0 1 0 2 6 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 2 0 0 0 0 0 0 0 0 0 0 37 5 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 0 0 0 1 0 0 0 0 0 8 0 5 50 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 2 0 9 0 0 0 0 0 0 0 0 1 0 6 12 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 2 1 0]\n",
" [ 0 12 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 3 0 0 0 0 0 1 0 1 4 0 0 7 0]\n",
" [ 0 0 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]]\n",
"\n",
"Epoch 6/29\n",
"----------\n",
"train Loss: 1.9498 Acc: 0.4767\n",
"Confusion Matrix:\n",
"[[ 32 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 27 6 0 22 0 4 1 0 2 0 0 0 0 0 5 3 1 0 0 0]\n",
" [ 0 70 2 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 7 27 2 7 3 5 3 0 0 1 0 1 2 1 1 4 0 0 4 0]\n",
" [ 0 1 44 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 7 17 2 18 0 0 3 0 0 1 0 0 1 3 1 5 0 2 0]\n",
" [ 0 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 2 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 0 1 53 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 5 0 0 0 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 1 0 0 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 3 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 3 0 8 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 4 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 8 0 0 2 0 1 0 0 0 0 0 1 1 1 4 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 5 0 0 1 0 0 0 0 0 0 2 1 11 0 0 0]\n",
" [ 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 1 0 2 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 2 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 4 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 1 0 0 0 0 0 0 0 6 1 1 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 10 0 0 1 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 9 0 4 0 0 2 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 13 2 0 6 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 3 15 0 0 0 1 4 0 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 3 14 0 9 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 3 0 3 1 0 0 0 0 0 0 0 1 0 3 1 0 0 3 0]\n",
" [ 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 3 0 0 0 0 0 0 0 0 2 0 1 2 2 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 1 2 4 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 13 0 1 1 0 2 2 1 0 0 0 0 0 0 2 1 1 8 2 0 4 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 6 0 0 0 0 0 0 0 0 0 2 2 6 0 1 0]\n",
" [ 4 2 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 112 23 2 11 2 5 2 0 2 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 3 18 3 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 26 134 5 7 2 1 6 1 1 0 0 0 7 0 2 10 1 0 1 0]\n",
" [ 0 1 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 12 72 4 24 0 1 3 0 0 4 0 1 0 1 3 4 0 0 0]\n",
" [ 2 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 9 3 0 126 0 1 1 0 4 0 0 0 1 1 3 1 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 14 1 132 0 0 2 0 0 2 0 0 0 2 2 3 0 0 0]\n",
" [ 3 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 2 0 1 0 46 5 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 10 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 4 110 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 13 1 6 0 1 29 0 0 1 0 1 0 0 0 0 0 0 0]\n",
" [ 9 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 17 2 0 8 0 0 0 0 13 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 15 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 14 0 0 0 0 1 0 0 8 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 11 0 12 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 5 0 3 2 3 1 0 1 1 0 5 1 2 6 2 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 14 0 3 1 0 3 0 0 0 0 1 29 0 4 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 4 6 0 2 0 0 2 0 0 0 0 0 4 2 6 4 0 1 0]\n",
" [ 1 1 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 9 7 0 2 1 0 1 0 1 0 0 0 1 1 56 6 0 0 0 0]\n",
" [ 0 4 2 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 2 13 0 2 0 0 1 0 0 0 0 0 3 1 10 77 3 0 0 0]\n",
" [ 0 2 9 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 8 0 8 0 0 1 0 0 0 0 0 0 0 5 36 0 0 0]\n",
" [ 3 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 1 4 0 0 3 0]\n",
" [ 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 3 1 6 0 0 3 0 0 0 0 0 2 0 2 10 0 0 13 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 1 6 0 0 0 0 0 1 0 0 1 0 1 3 0 0 0]]\n",
"val Loss: 1.6813 Acc: 0.5440\n",
"Confusion Matrix:\n",
"[[18 10 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 2 8 1 4 0 0 2 0 0 0 0 0 6 0 1 0 0 0]\n",
" [ 0 56 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 3 5 2 1 3 0 4 0 0 0 0 0 0 0 0 9 0 0 0 0]\n",
" [ 0 1 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 13 0 0 4 0 0 0 0 0 0 0 3 2 0 1 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 2 0 0 0 0 0 0 0 0 2 5 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 7 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 3 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 1 1 0 0 0 0 6 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 9 2 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 1 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 16 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 2 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 3 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 6 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 11 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 4 1 0 0 0]\n",
" [ 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 77 1 3 8 0 0 1 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 91 5 0 1 0 14 0 0 0 0 0 0 0 1 6 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 70 0 8 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 83 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 9 1 85 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 2 0 0 1 22 3 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 76 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 15 0 0 1 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 5 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 1 0 0 4 0 0 1 0 4 2 0 5 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 3 0 0 0 0 0 0 0 0 21 0 4 6 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 7 0 1 0 0 0 0 0 0 0 0 1 1 4 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 43 6 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 4 0 6 57 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 6 0 7 0 0 0 0 0 0 0 0 0 0 12 14 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0]\n",
" [ 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 8 0 0 8 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]]\n",
"\n",
"Epoch 7/29\n",
"----------\n",
"train Loss: 1.8850 Acc: 0.4995\n",
"Confusion Matrix:\n",
"[[ 34 7 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 9 0 15 2 6 1 0 5 0 0 0 0 0 4 2 0 0 0 0]\n",
" [ 3 74 0 1 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 5 26 1 5 2 2 7 0 0 0 0 0 3 0 5 5 0 0 1 0]\n",
" [ 1 2 43 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 23 1 19 0 0 4 0 0 0 0 1 2 0 5 1 0 0 0]\n",
" [ 3 0 0 29 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 2 57 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 1 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 2 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 2 0 7 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 4 1 4 0 0 0 0 0 0 1 2 6 0 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 6 1 4 0 0 3 0 0 0 0 0 1 2 3 4 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 2 0 2 1 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 3 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 5 2 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 2 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 3 0 0 0 1 10 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 5 0 0 4 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 2 0 1 0 1 0 0 0 0 0 0 0 0 0 0 14 3 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 1 14 0 0 0 2 2 0 1 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 19 0 9 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 2 0 3 1 0 0 0 0 0 0 0 1 0 4 2 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 1 0 0 0 0 0 0 0 1 0 1 9 1 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 1 0 1 0 0 0 0 1 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 2 4 0 2 1 0 2 0 0 0 0 0 4 0 1 9 2 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 2 0 3 0 1 0 0 0 0 0 0 0 2 3 4 0 1 0]\n",
" [ 4 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 118 15 1 14 1 2 0 0 0 0 0 1 0 0 4 2 1 0 0 0]\n",
" [ 2 9 0 0 4 1 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 2 0 24 139 5 6 3 2 9 1 1 0 0 0 6 1 2 10 0 0 0 0]\n",
" [ 0 3 13 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 77 2 23 0 0 5 0 0 5 0 1 1 1 0 5 0 0 0]\n",
" [ 3 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 2 0 130 1 0 0 0 0 0 0 0 1 0 5 2 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 19 2 136 0 1 0 0 0 1 0 0 0 2 1 2 0 0 0]\n",
" [ 2 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 3 0 0 0 52 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 14 0 0 0 1 111 0 0 1 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 18 0 3 0 2 29 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 10 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 3 1 12 0 1 0 0 11 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 15 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 17 0 1 0 0 1 0 0 4 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 13 0 9 0 1 0 0 0 9 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 7 0 2 4 0 0 0 0 0 0 7 1 0 6 3 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 1 3 1 0 3 0 0 0 0 1 38 0 5 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 5 2 3 0 1 2 0 1 0 0 1 6 3 2 6 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 9 5 0 4 4 0 0 0 0 0 0 0 0 0 59 9 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 8 1 0 0 0 2 0 0 0 0 1 4 0 8 91 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 8 0 9 0 1 0 0 0 0 0 0 1 1 4 40 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 2 0 0 0 0 2 0 0 1 0 0 4 3 1 0 0 0]\n",
" [ 2 11 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 8 0 1 0 0 1 0 0 0 0 0 1 0 5 9 0 0 10 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 4 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1]]\n",
"val Loss: 1.6210 Acc: 0.5787\n",
"Confusion Matrix:\n",
"[[ 28 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 1 10 1 2 0 0 5 0 0 0 0 0 6 0 1 0 0 0]\n",
" [ 1 50 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 4 14 2 2 3 0 3 0 0 0 0 0 0 0 1 4 0 0 0 0]\n",
" [ 0 1 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 12 0 0 3 0 0 0 0 0 0 0 2 4 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 2 0 0 0 0 0 4 3 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 2 0]\n",
" [ 0 0 4 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 14 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 2 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 11 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 71 7 0 12 0 0 1 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 110 2 4 1 0 4 0 0 0 0 0 1 0 0 6 0 0 0 0]\n",
" [ 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 62 0 8 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 5 1 89 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 3 0 0 1 27 1 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 3 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 6 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 2 0 0 4 0 1 1 0 4 1 0 6 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 4 1 0 0 0 0 0 0 0 20 0 4 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 2 2 0 4 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 43 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 9 54 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 3 0 6 0 0 0 0 0 0 0 0 0 1 4 25 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0]\n",
" [ 1 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 4 0 0 11 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1]]\n",
"\n",
"Epoch 8/29\n",
"----------\n",
"train Loss: 1.8691 Acc: 0.5045\n",
"Confusion Matrix:\n",
"[[ 42 4 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 5 0 20 1 7 1 0 1 0 0 0 1 0 2 2 1 0 0 0]\n",
" [ 3 70 1 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 6 28 1 9 1 5 4 0 1 0 0 0 1 0 2 6 0 0 3 0]\n",
" [ 0 0 40 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 24 1 19 0 0 5 0 0 0 0 0 0 3 3 7 0 1 0]\n",
" [ 1 1 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 2 54 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 4 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 2 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 5 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 2 0 5 0 2 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 0 6 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 1 4 0 2 0 0 0 0 0 1 0 2 4 0 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 1 3 0 0 0 0 0 0 1 1 8 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 2 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 4 0 0 0 1 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 5 1 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 9 1 0 0 1 8 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 0 3 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 13 1 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 1 0 1 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 1 14 2 0 0 1 2 0 0 0 0 0 2 0 0 2 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 1 13 1 9 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 0 0 0 0 0 1 2 0 5 3 0 0 1 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 3 2 0 7 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 1 4 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 2 1 0 0 0 0 0 0 0 0 2 2 2 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 1 5 0 3 1 0 3 0 0 0 0 0 1 0 2 10 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 5 0 0 0 0 0 0 0 0 0 1 1 9 0 0 0]\n",
" [ 13 2 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 107 13 0 14 3 5 2 0 0 0 0 0 0 0 4 2 1 0 0 0]\n",
" [ 4 10 0 1 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 22 145 8 5 4 3 8 0 0 1 0 0 4 0 1 10 0 0 0 0]\n",
" [ 0 1 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 88 4 22 0 0 6 0 0 2 0 0 0 1 3 4 0 0 0]\n",
" [ 5 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 1 1 130 1 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 15 1 140 0 0 1 0 0 2 0 0 1 1 1 5 0 0 0]\n",
" [ 7 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 10 5 0 1 0 44 11 0 1 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 3 5 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 11 0 1 1 0 107 0 0 1 0 0 1 0 0 5 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 15 0 7 0 2 35 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 3 0 12 0 0 1 0 17 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 14 0 1 0 0 1 0 0 11 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 12 0 1 1 0 0 13 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 6 0 4 2 5 1 0 1 0 0 4 1 2 4 2 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 14 0 4 0 0 6 0 0 0 0 0 31 2 2 3 0 0 0 0]\n",
" [ 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 3 8 0 0 3 0 0 0 1 1 3 0 3 4 0 0 0]\n",
" [ 5 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 5 4 0 1 3 0 0 0 0 0 0 0 1 0 64 5 2 0 0 0]\n",
" [ 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 11 0 1 3 0 1 0 0 0 0 0 1 0 10 85 3 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 9 0 4 0 1 1 0 0 0 0 0 2 3 6 42 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 1 0 2 0 0 0 0 1 0 0 0 1 0 1 4 1 1 1 0]\n",
" [ 0 12 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 10 0 4 0 0 0 0 0 0 0 0 1 0 0 7 0 0 14 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 0 2 0 0 1 0 0 0 0 0 1 0 2 4 0 0 0]]\n",
"val Loss: 1.5895 Acc: 0.5859\n",
"Confusion Matrix:\n",
"[[ 25 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 1 12 1 4 0 0 5 0 0 0 0 0 4 0 2 0 0 0]\n",
" [ 1 53 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 4 11 2 2 3 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0]\n",
" [ 0 2 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 15 0 0 6 0 0 0 0 0 0 0 0 7 0 1 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 2 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 7 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 11 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 1 0 0 0 0 1 1 2 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 8 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 74 4 0 12 0 1 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 109 1 6 2 1 3 0 0 0 0 0 0 0 0 4 1 0 0 0]\n",
" [ 0 0 13 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 52 0 15 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 1 93 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 2 0 0 1 29 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 3 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 1 8 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 1 3 0 0 1 0 4 2 0 5 0 0 0 1 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 5 1 0 0 0 0 0 0 0 21 0 5 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 5 0 1 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 38 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 1 0 0 0 0 0 6 0 8 51 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 2 30 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 1 0 0 15 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 9/29\n",
"----------\n",
"train Loss: 1.8384 Acc: 0.5173\n",
"Confusion Matrix:\n",
"[[ 48 7 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 20 3 1 12 1 4 1 0 3 0 0 0 0 0 3 2 1 0 2 0]\n",
" [ 4 60 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 42 2 8 1 3 5 0 0 0 0 0 2 0 1 5 0 0 2 0]\n",
" [ 0 1 45 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 22 0 19 0 0 4 0 0 2 0 0 1 2 3 3 0 0 0]\n",
" [ 0 0 0 32 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 1 53 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 8 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 1 0 1 0 2 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 1 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 2 0 6 1 2 0 0 0 0 0 1 0 0 2 1 0 0 1 0]\n",
" [ 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 0 0 2 1 2 0 0 0 0 0 1 0 4 2 1 0 1 0]\n",
" [ 1 2 6 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 7 0 0 2 0 0 0 0 0 0 0 2 4 0 1 0]\n",
" [ 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 2 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 9 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 9 0 0 0 1 9 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 8 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 11 3 0 0 0 0 0 0 0 13 1 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 3 16 0 1 0 1 3 0 0 1 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 13 1 11 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 1 0 1 0 0 2 2 0 0 0 0 0 0 0 1 0 2 2 2 0 3 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 1 10 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 2 0 0 2 0 0 0 0 0 0 0 0 0 2 2 3 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 15 0 0 1 0 2 2 0 2 0 0 0 0 0 4 0 2 10 0 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 8 0 0 0 0 0 0 0 1 0 0 0 5 0 0 0]\n",
" [ 4 2 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 119 16 2 12 1 4 1 0 2 0 0 0 1 0 4 0 0 0 0 0]\n",
" [ 1 15 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 149 4 8 3 3 7 0 2 0 0 0 3 0 1 11 0 0 2 0]\n",
" [ 0 2 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 83 0 27 0 0 3 0 0 3 0 0 0 0 2 4 0 0 0]\n",
" [ 3 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 5 0 134 0 0 0 0 2 0 0 0 1 0 3 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 10 2 144 0 0 0 0 0 1 0 0 1 1 0 6 0 1 0]\n",
" [ 1 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 5 0 2 0 56 3 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 15 0 1 0 0 109 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 9 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 7 1 5 0 1 31 0 0 1 0 0 0 0 1 1 0 0 0]\n",
" [ 6 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 4 0 10 0 1 0 0 16 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 14 0 0 0 2 1 0 0 9 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 12 0 12 0 0 0 0 0 11 0 0 0 0 1 0 0 0 0]\n",
" [ 2 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 0 5 2 1 0 0 0 0 0 6 1 0 7 0 1 0 0 0]\n",
" [ 0 5 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 10 0 4 0 0 5 0 0 0 0 1 35 0 3 1 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 5 3 8 0 0 2 0 0 0 0 1 6 0 2 3 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 4 3 0 0 0 0 0 0 0 0 0 64 11 1 0 0 0]\n",
" [ 0 5 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 11 1 1 2 1 2 0 0 0 0 0 0 0 6 82 1 0 1 0]\n",
" [ 1 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 1 7 0 1 1 0 0 0 0 0 1 0 5 41 0 1 0]\n",
" [ 1 1 2 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 2 0 0 0 0 0 0 0 1 0 0 0 2 1 0 3 0]\n",
" [ 1 10 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 5 0 3 0 0 1 0 0 0 0 0 1 0 0 8 0 0 18 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 5 0 3 1 0 0 0 0 0 0 0 1 0 0 5 0 0 0]]\n",
"val Loss: 1.5951 Acc: 0.5847\n",
"Confusion Matrix:\n",
"[[ 29 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 10 1 1 0 0 5 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 1 50 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 16 2 2 3 0 1 0 0 0 0 0 0 0 0 6 0 0 0 0]\n",
" [ 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 13 0 0 3 0 0 0 0 0 0 0 0 6 0 1 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 1 1 2 0 0 1 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 13 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 1 0 0 0 0 1 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 4 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 70 6 0 13 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 111 3 4 2 0 3 0 0 0 0 0 0 0 0 7 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 64 0 9 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 4 1 91 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 2 0 0 1 24 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 74 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 3 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 6 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 0 3 0 2 0 0 4 1 0 5 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 5 1 0 0 0 0 0 0 0 19 0 3 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 5 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 42 6 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 4 60 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 3 0 7 0 0 0 0 0 0 0 0 0 0 4 25 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 0 0 0 0 0 0 0 4 0 0 13 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 10/29\n",
"----------\n",
"train Loss: 1.8459 Acc: 0.5084\n",
"Confusion Matrix:\n",
"[[ 33 7 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 7 2 20 0 3 0 0 3 0 0 1 0 0 4 3 1 0 0 0]\n",
" [ 7 61 0 0 3 0 0 0 1 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 7 37 1 10 1 0 0 0 1 1 0 0 0 0 4 6 1 0 0 0]\n",
" [ 1 1 42 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 25 1 16 1 0 6 0 0 2 0 0 0 0 5 5 0 0 0]\n",
" [ 0 1 1 31 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 55 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 5 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 4 0 3 0 0 1 0 0 0 0 1 2 3 0 0 1 0]\n",
" [ 2 4 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 5 1 0 2 0 1 0 0 0 0 0 2 1 2 3 0 0 0 0]\n",
" [ 0 1 6 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 1 7 0 0 1 0 0 0 0 0 0 1 2 6 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 1 1 2 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 1 0 2 0 4 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 2 5 0 0 0 0 9 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 3 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 8 2 0 0 0 0 0 0 0 15 0 0 5 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 1 1 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 1 0 0 15 0 1 0 1 3 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 1 0 20 0 5 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 2 1 2 1 1 0 0 0 0 0 0 1 0 4 3 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 4 0 4 0 0 0 0 0 0 0 1 1 1 1 4 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 6 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 2 0 0 0 0 0 0 0 0 0 1 0 2 0 2 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 14 0 0 3 1 2 1 0 0 0 0 0 0 0 4 0 0 12 1 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 6 0 0 0 0 0 0 0 1 0 2 2 2 0 0 0]\n",
" [ 5 4 0 1 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 123 11 2 8 0 4 2 0 1 0 0 0 0 0 6 1 0 0 0 0]\n",
" [ 2 14 1 0 3 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 18 151 6 8 2 2 8 0 0 0 0 1 1 0 2 7 0 0 1 0]\n",
" [ 0 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 97 0 21 0 0 2 0 0 3 0 1 0 2 3 2 0 0 0]\n",
" [ 4 5 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 2 0 126 0 0 0 0 2 0 0 0 1 0 6 1 0 0 0 0]\n",
" [ 0 2 2 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 13 2 137 0 0 1 0 0 0 0 0 0 3 1 5 0 0 0]\n",
" [ 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 5 0 1 0 49 7 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 7 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 110 0 0 0 0 0 2 0 0 2 0 0 0 0]\n",
" [ 1 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 12 0 5 0 0 29 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 6 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 6 0 8 0 0 0 0 16 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 13 0 0 0 1 0 0 1 14 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 16 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 5 0 5 2 5 0 0 1 0 0 3 1 0 7 1 1 0 0 0]\n",
" [ 1 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 12 0 1 0 0 1 0 0 0 0 1 35 0 4 8 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 3 5 0 2 2 0 0 0 1 2 5 2 4 2 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 6 0 4 0 1 1 0 0 0 0 1 0 0 60 8 0 0 1 0]\n",
" [ 1 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 10 1 0 0 0 1 0 0 0 0 0 2 0 10 87 1 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 6 0 6 0 0 0 0 0 0 0 0 1 1 8 43 0 0 0]\n",
" [ 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 2 0 0 0 0 2 0 0 0 0 0 2 2 0 1 2 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 1 4 0 0 4 0 0 0 0 0 3 0 0 10 0 0 14 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 8 0 4 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0]]\n",
"val Loss: 1.5938 Acc: 0.5877\n",
"Confusion Matrix:\n",
"[[ 24 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 9 1 5 0 0 5 0 0 1 0 0 5 0 1 0 1 0]\n",
" [ 0 54 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 9 2 2 2 0 3 0 0 0 0 0 1 0 0 5 1 0 2 0]\n",
" [ 0 0 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 12 0 0 5 0 0 0 0 0 0 0 0 9 0 1 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 1 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 1 0 0 0 0 0 0 0 0 0 6 0 0 3 0]\n",
" [ 0 0 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 9 2 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 14 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 3 1 0 0 0 0 1 2 1 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 10 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 4 0 8 0 2 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 107 2 4 2 1 5 0 0 0 0 0 1 0 0 5 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 63 0 7 0 0 3 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 88 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 6 1 86 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 2 0 0 1 30 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 6 0 0 1 0 0 7 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 2 3 0 1 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 4 1 0 0 0 0 0 0 0 21 0 3 5 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 1 0 0 1 0 0 3 0 0 5 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 41 6 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 5 56 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 6 0 0 0 0 0 0 0 0 0 0 3 30 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 1 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 1]]\n",
"\n",
"Epoch 11/29\n",
"----------\n",
"train Loss: 1.8452 Acc: 0.5141\n",
"Confusion Matrix:\n",
"[[ 37 7 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 20 6 0 23 0 8 0 0 4 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 3 85 0 1 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 3 23 1 6 0 1 3 0 2 1 0 0 1 0 1 9 0 0 0 0]\n",
" [ 0 1 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 24 3 20 0 0 7 0 0 1 0 0 0 1 1 4 0 0 0]\n",
" [ 0 0 0 32 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 0 0 1 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 1 1 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 1 0 8 0 0 0 0 0 0 0 0 1 0 4 1 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 1 3 1 3 0 0 0 0 0 2 0 5 3 0 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 5 0 6 0 0 3 0 0 0 0 0 1 0 4 5 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 2 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 1 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 0 1 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 7 1 2 0 1 7 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 9 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 13 0 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 4 17 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 3 14 0 7 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 1 0 2 1 0 0 0 0 0 0 0 0 1 1 4 1 0 2 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 1 0 0 0 0 0 0 0 0 0 0 2 7 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 1 0 0 0 0 0 1 0 1 0 1 3 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 10 0 1 8 0 4 4 0 0 0 0 0 0 0 4 0 0 4 1 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 2 1 0 5 0 0 0 0 0 0 0 0 0 0 5 4 0 0 0]\n",
" [ 6 5 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 107 16 0 14 2 7 1 1 2 0 0 0 1 0 4 1 0 0 0 0]\n",
" [ 2 16 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 20 144 2 9 6 3 8 0 1 0 0 0 6 0 3 7 0 0 0 0]\n",
" [ 1 2 18 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 79 2 21 0 1 3 0 0 2 0 0 1 2 1 4 0 0 0]\n",
" [ 2 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 2 0 134 0 1 0 0 0 0 0 0 1 0 1 2 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 15 1 137 0 0 0 0 0 2 0 0 4 1 0 3 0 1 0]\n",
" [ 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 3 0 1 0 49 4 1 1 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 11 1 0 1 0 111 0 0 1 0 0 0 0 0 3 1 0 0 0]\n",
" [ 0 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 10 0 3 0 0 40 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 6 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 5 0 9 0 0 0 0 19 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 2 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 14 0 1 0 0 0 0 1 10 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 14 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 2 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 2 1 3 4 2 1 0 1 0 0 5 3 0 7 1 0 0 0 0]\n",
" [ 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 6 0 0 1 0 0 0 0 0 36 1 1 6 0 0 1 0]\n",
" [ 0 2 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 5 1 3 0 0 0 0 0 0 0 0 4 3 5 4 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 6 6 0 2 0 0 0 0 0 0 0 1 1 1 60 11 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 4 0 0 0 0 0 0 0 1 3 0 8 85 2 0 2 0]\n",
" [ 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 6 1 2 0 1 2 0 0 1 0 0 0 3 3 45 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 1 0 0 1 0 0 1 0 0 1 4 0 0 1 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 0 6 0 1 1 0 2 1 0 0 0 0 0 0 3 7 2 0 16 0]\n",
" [ 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 4 1 0 0 0 0 1 0 0 0 0 1 4 0 0 0]]\n",
"val Loss: 1.6006 Acc: 0.5859\n",
"Confusion Matrix:\n",
"[[ 34 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 1 9 1 2 0 0 3 0 0 0 0 0 6 0 2 0 0 0]\n",
" [ 2 57 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 3 8 2 2 3 0 0 0 0 0 0 0 0 0 3 4 0 0 0 0]\n",
" [ 0 1 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 15 0 0 3 0 0 0 0 0 0 0 0 9 0 1 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 5 2 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 1 5 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 8 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 15 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 5 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 3 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 5 0 0 0]\n",
" [ 7 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 69 4 0 12 0 0 0 0 2 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 107 2 5 2 0 3 0 0 0 0 0 1 0 2 4 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 67 0 8 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 5 1 89 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 1 0 0 1 26 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 1 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 6 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 2 0 1 1 0 5 0 0 7 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 6 1 0 0 0 0 0 0 0 19 0 6 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 2 2 0 6 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 46 3 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 15 51 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 7 0 0 0 0 0 0 0 0 0 1 3 29 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 1 0 0 15 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]]\n",
"\n",
"Epoch 12/29\n",
"----------\n",
"train Loss: 1.8509 Acc: 0.5109\n",
"Confusion Matrix:\n",
"[[ 45 8 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 5 1 12 0 6 0 0 2 0 0 0 2 0 2 3 2 0 0 0]\n",
" [ 1 71 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 5 23 3 3 2 2 4 0 1 1 0 1 4 1 8 8 0 0 2 0]\n",
" [ 0 1 37 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 3 22 0 21 0 0 8 0 0 0 0 0 1 2 2 5 0 0 0]\n",
" [ 0 0 0 30 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 54 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 2 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 8 0 3 0 0 2 0 0 0 1 0 4 1 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 1 2 0 3 0 0 0 0 0 0 0 2 5 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 5 0 7 0 0 3 0 0 0 0 0 0 2 0 8 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 1 0 1 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 3 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 8 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 10 0 1 0 1 8 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 8 0 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 11 3 0 0 0 0 0 0 0 12 2 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 2 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 0 0 1 0 3 16 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 19 0 3 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 2 5 1 0 0 0]\n",
" [ 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 1 1 2 4 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 3 0 0 4 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 0 3 0 0 0 1 0 0 0 0 0 2 1 2 0 1 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 1 6 0 3 1 0 0 0 0 0 0 0 3 1 0 12 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 4 0 0 0 0 0 0 0 0 1 2 0 9 0 0 0]\n",
" [ 3 4 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 109 23 0 16 0 6 0 0 0 0 0 0 0 0 6 1 0 0 0 0]\n",
" [ 3 14 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 15 154 4 9 6 3 8 0 0 1 0 0 2 0 1 7 0 0 0 0]\n",
" [ 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 88 0 24 0 1 7 0 0 1 0 1 1 2 2 3 0 0 0]\n",
" [ 6 6 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 1 127 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 23 2 135 0 0 0 0 0 1 0 0 0 2 0 2 0 0 0]\n",
" [ 3 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 1 0 1 0 54 5 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 12 0 1 0 3 109 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 10 0 4 0 0 29 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 8 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 5 0 8 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 15 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 15 0 1 0 0 1 0 3 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 14 0 0 0 0 0 14 0 1 0 0 0 1 0 0 0]\n",
" [ 0 2 1 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 9 5 0 3 0 1 1 0 1 0 0 7 0 0 5 1 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 6 2 0 1 0 0 0 0 0 37 1 3 3 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 3 0 4 0 1 1 0 0 0 0 1 10 3 0 6 0 0 0]\n",
" [ 3 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 3 1 4 3 1 1 0 1 0 0 1 2 0 53 9 0 0 0 0]\n",
" [ 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 17 1 0 1 0 1 0 0 0 0 0 1 1 6 82 2 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 8 1 8 0 1 1 0 0 0 0 0 1 2 4 39 0 0 0]\n",
" [ 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 4 1 1 0 0 0 0 0 0 0 0 1 2 0 0 2 0]\n",
" [ 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 1 2 0 0 2 0 0 0 0 0 1 1 1 3 0 0 18 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 1 3 0 0 1 0 0 0 0 0 2 1 0 3 0 0 1]]\n",
"val Loss: 1.6204 Acc: 0.5817\n",
"Confusion Matrix:\n",
"[[ 37 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 1 9 1 0 0 0 2 0 0 0 0 0 1 0 1 0 2 0]\n",
" [ 1 57 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 2 8 2 2 3 0 1 0 0 0 0 0 1 0 0 5 0 0 2 0]\n",
" [ 0 1 19 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 17 0 13 0 0 3 0 0 0 0 0 0 0 2 3 0 3 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 0 1 2 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 3 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 3 0 0 0 0 6 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 9 2 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 15 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 2 1 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 10 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 9 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 73 4 0 8 0 1 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 109 2 2 2 0 5 0 0 0 0 0 1 0 0 5 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 68 0 7 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 0 82 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 9 1 85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 3 0 0 0 26 1 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 1 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 1 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 2 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 5 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 4 0 1 1 0 4 3 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 4 1 0 0 0 0 0 0 0 22 0 3 3 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 6 0 1 0 0 0 0 0 1 0 0 2 0 1 4 0 2 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 37 7 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 3 57 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 1 2 0 6 0 0 0 0 0 0 0 0 0 0 6 22 0 1 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 2 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0]]\n",
"\n",
"Epoch 13/29\n",
"----------\n",
"train Loss: 1.8332 Acc: 0.5130\n",
"Confusion Matrix:\n",
"[[ 42 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 17 5 0 20 0 6 0 0 5 0 0 0 0 0 6 4 0 0 1 0]\n",
" [ 6 63 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 6 35 5 9 0 2 5 0 0 0 0 0 1 0 2 6 0 0 1 0]\n",
" [ 1 2 38 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 5 15 0 27 0 0 4 0 0 1 0 0 2 0 3 2 0 2 0]\n",
" [ 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 1 56 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 8 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 3 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 1 6 0 1 0 0 0 0 0 0 1 0 1 3 0 0 0 0]\n",
" [ 1 6 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 7 0 0 4 0 2 0 0 0 0 0 2 0 1 2 0 0 2 0]\n",
" [ 0 0 7 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 1 4 0 0 2 0 0 0 0 1 1 1 4 5 0 0 0]\n",
" [ 1 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 1 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 1 0 3 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 0 1 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 11 1 0 0 0 0 0 0 0 11 1 0 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1]\n",
" [ 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 1 0 5 16 0 1 0 1 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 18 0 8 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 2 1 0 0 0 0 0 0 0 1 1 3 4 1 0 3 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 1 1 1 8 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 1 0 0 1 2 0 0 0 0 0 0 0 0 2 0 2 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 2 0 0 3 0 1 0 0 0 0 0 3 1 0 14 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 2 0 4 1 0 0 0 0 0 0 2 0 1 0 3 0 0 0]\n",
" [ 7 5 0 1 3 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 113 23 1 8 1 1 0 0 0 0 0 0 0 0 2 4 0 0 0 0]\n",
" [ 2 16 0 1 1 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 19 152 4 8 2 0 7 0 0 1 0 1 4 1 2 6 0 0 0 0]\n",
" [ 0 2 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 88 1 24 0 0 4 0 0 2 0 0 0 0 3 7 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 139 0 0 0 0 1 0 0 0 1 0 2 0 0 0 0 0]\n",
" [ 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 20 2 134 0 0 0 0 0 2 0 0 0 0 0 6 0 0 0]\n",
" [ 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 1 0 48 6 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 0 0 0 1 121 0 0 0 0 1 0 0 0 1 1 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 17 0 4 0 0 34 0 0 1 0 0 0 1 0 0 0 0 0]\n",
" [ 11 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 2 0 10 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 17 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 0 0 1 2 0 0 9 0 0 1 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 16 0 0 1 0 0 13 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 3 0 5 2 4 0 0 0 0 0 5 1 0 8 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 5 0 0 5 0 0 0 0 0 39 0 2 4 1 0 1 0]\n",
" [ 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 8 2 4 0 0 2 0 0 0 0 0 2 3 4 9 0 0 0]\n",
" [ 3 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 3 1 1 0 0 2 0 0 0 0 1 1 0 59 12 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 14 0 2 1 1 2 0 0 0 0 1 0 0 7 84 2 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 1 11 0 1 1 0 0 0 0 1 0 2 6 38 0 0 0]\n",
" [ 1 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 1 5 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 6 0 2 2 0 3 0 0 0 0 0 0 0 0 10 0 0 18 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 4 0 0 0 0 0 0 0 0 0 1 0 4 0 0 0]]\n",
"val Loss: 1.5807 Acc: 0.5925\n",
"Confusion Matrix:\n",
"[[ 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 1 11 1 1 0 0 3 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 0 55 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 13 2 2 3 0 0 0 0 0 0 0 0 0 1 3 0 0 2 0]\n",
" [ 0 1 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 10 0 18 0 0 5 0 0 1 0 0 0 0 0 7 0 2 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 12 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 4 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 1 0 0 0 0 1 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 4 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 73 4 0 13 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 114 2 3 2 0 2 0 0 0 0 0 0 0 0 5 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 62 0 11 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 3 1 92 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 2 0 0 1 26 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 0 0 0 0 74 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 27 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 0 2 0 1 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 6 1 0 0 0 0 0 0 0 19 0 3 2 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 4 0 0 0 0 0 0 0 0 0 0 40 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 1 0 0 0 0 0 0 0 0 4 0 5 55 0 0 2 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 3 27 0 0 1]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 14/29\n",
"----------\n",
"train Loss: 1.8217 Acc: 0.5155\n",
"Confusion Matrix:\n",
"[[ 54 3 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 12 7 0 17 2 4 1 0 2 0 0 1 0 0 2 1 0 0 1 0]\n",
" [ 6 68 1 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 28 2 9 2 5 1 1 0 1 0 0 3 0 3 7 0 0 1 0]\n",
" [ 0 4 28 1 0 1 0 0 4 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 5 15 1 23 0 0 13 0 0 0 0 0 1 1 1 5 0 0 0]\n",
" [ 1 1 0 29 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 58 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 0 2 1 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 2 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 1 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 5 0 2 0 0 1 0 0 0 0 0 3 2 0 1 0 0]\n",
" [ 1 4 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 8 1 0 1 0 1 0 0 0 0 0 0 0 3 3 0 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 4 2 1 0 0 3 0 0 0 0 0 2 1 2 4 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 2 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 2 0 0 4 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 4 0 0 0 1 0 0 0 0 0 0 0 1 0 0 2 1 0 0 0 0 0 0 0 4 1 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 2 11 0 0 1 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 5 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 14 0 0 6 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 8 0 0 2 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 2 20 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 20 0 4 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 2 1 0 0 0 0 0 0 0 0 0 8 3 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 1 0 3 0 1 0 0 0 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 2 0 0 3 0 0 0]\n",
" [ 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 4 0 2 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 16 0 2 4 0 0 1 0 0 0 0 0 0 0 3 0 1 10 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 6 0 0 0 0 0 0 0 0 0 1 0 11 0 0 0]\n",
" [ 4 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 113 15 1 16 2 10 1 0 1 0 0 0 0 0 3 0 1 0 1 0]\n",
" [ 0 16 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 19 157 2 3 3 6 3 0 0 1 0 0 4 1 3 7 0 0 0 0]\n",
" [ 0 2 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 4 3 89 1 26 0 0 5 0 0 2 0 0 1 2 0 5 0 0 0]\n",
" [ 6 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 132 1 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 15 0 132 0 1 0 0 0 6 0 0 1 1 1 9 0 0 0]\n",
" [ 2 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 6 0 1 0 47 6 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 5 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 15 1 0 1 2 107 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 9 0 2 0 1 39 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 8 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 12 5 0 10 0 1 0 0 15 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 17 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 17 0 0 0 1 0 0 0 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 14 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 3 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 6 1 4 1 1 0 0 0 1 0 5 1 0 4 3 0 0 0 0]\n",
" [ 1 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 5 0 0 3 0 0 0 0 1 36 0 2 2 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 1 5 0 0 1 0 0 0 1 1 8 2 3 3 0 1 0]\n",
" [ 1 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 11 3 0 2 2 0 1 0 0 0 0 0 1 0 61 7 0 0 0 0]\n",
" [ 1 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 12 0 2 2 0 1 0 0 0 0 0 4 1 9 80 3 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 7 2 3 0 0 1 0 0 0 0 0 1 6 2 47 0 0 0]\n",
" [ 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 1 0 1 0 0 0 0 1 0 0 0 0 0 1 2 0 2 3 0]\n",
" [ 2 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 6 0 4 0 0 0 0 0 1 1 0 2 0 0 6 1 0 18 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 7 0 3 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0]]\n",
"val Loss: 1.5955 Acc: 0.5895\n",
"Confusion Matrix:\n",
"[[ 28 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 9 1 1 0 0 4 0 0 1 0 0 4 0 2 0 1 0]\n",
" [ 0 51 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 2 14 2 2 3 0 3 0 0 0 0 0 0 0 0 4 0 0 2 0]\n",
" [ 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 14 0 16 0 0 5 0 0 0 0 0 0 0 0 7 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 1 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 14 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 3 1 0 0 0 0 1 3 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 71 8 0 11 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 112 2 3 2 0 3 0 0 0 0 0 1 0 0 5 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 63 0 12 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 87 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 4 1 91 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 3 0 0 1 26 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 1 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 7 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 3 0 1 3 0 1 1 0 5 1 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 4 1 0 0 0 0 0 0 0 21 0 2 5 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 1 0 0 0 0 0 0 0 0 0 0 41 6 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 3 58 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 3 27 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 2 0 0 16 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 15/29\n",
"----------\n",
"train Loss: 1.8107 Acc: 0.5337\n",
"Confusion Matrix:\n",
"[[ 44 4 1 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 11 7 0 16 1 8 0 0 3 1 0 0 3 0 5 1 0 0 2 0]\n",
" [ 1 74 0 0 3 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 1 0 7 26 1 8 3 1 4 0 0 0 0 1 1 0 3 6 0 0 1 0]\n",
" [ 0 0 42 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 17 1 21 0 0 10 0 0 0 0 1 1 2 4 1 0 2 1]\n",
" [ 0 2 0 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 1 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 1 0 0 1 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 4 0 0 0 0 0 0 0 1 1 0 2 3 0 0 0 0]\n",
" [ 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 1 2 0 3 0 0 0 0 0 0 0 3 4 0 0 2 0]\n",
" [ 0 0 5 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 4 3 4 0 0 4 0 0 0 0 0 0 1 0 8 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 1 2 2 0 0 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 4 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 5 1 0 2 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 10 0 0 0 1 7 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 1 4 0 1 3 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 12 1 0 0 0 0 0 0 0 12 1 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 1 14 0 2 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 1 18 0 6 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 2 1 0 0 0 0 0 0 0 1 1 4 3 0 0 2 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 1 0 0 2 0 0 1 0 0 0 0 0 0 0 1 1 0 7 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 4 0 0 0 0 0 0 0 1 0 0 1 2 0 0 0]\n",
" [ 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 1 6 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 16 0 1 1 0 3 2 0 1 0 0 0 0 1 1 2 3 8 0 0 2 0]\n",
" [ 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 1 0 4 0 0 0 0 0 0 0 0 0 1 2 5 0 1 0]\n",
" [ 6 4 1 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 109 18 1 12 1 6 2 0 1 0 0 0 0 0 4 3 0 0 0 0]\n",
" [ 1 6 1 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 13 170 1 9 4 1 4 0 3 0 0 0 6 0 3 5 0 0 0 0]\n",
" [ 0 1 7 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 83 1 20 0 0 9 0 0 1 1 0 0 1 1 8 0 0 1]\n",
" [ 2 7 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 1 0 130 0 2 1 0 2 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 3 142 0 0 0 0 0 3 0 0 0 3 1 5 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 7 0 1 0 51 6 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 16 1 1 0 1 108 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 9 1 6 0 0 42 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 11 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 1 11 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 0 3 0 0 14 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 13 0 0 1 0 0 14 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 2 0 3 1 7 1 0 0 0 0 8 1 0 8 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 12 0 3 0 0 4 0 0 0 0 0 34 0 4 5 0 0 1 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 4 3 3 3 0 2 1 0 0 0 0 3 6 0 4 4 0 1 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 3 7 0 3 3 0 2 0 0 0 0 0 0 0 61 11 0 0 0 0]\n",
" [ 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 12 0 1 2 0 3 0 0 0 0 0 1 3 8 84 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 8 2 5 0 1 1 0 0 0 0 0 0 2 4 44 0 0 0]\n",
" [ 2 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 0 0 0 0 1 0 0 0 0 0 0 4 0 2 2 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 6 1 3 1 0 1 1 0 0 0 0 1 0 0 10 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 5 0 3 0 0 0 0 0 1 0 0 0 0 1 5 0 0 1]]\n",
"val Loss: 1.5949 Acc: 0.5829\n",
"Confusion Matrix:\n",
"[[ 31 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 1 11 1 2 0 0 1 0 0 0 0 0 6 0 1 0 0 0]\n",
" [ 0 49 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 3 15 2 2 3 0 3 0 0 0 0 0 0 0 1 3 0 0 2 0]\n",
" [ 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 10 0 16 0 0 5 0 0 0 0 0 0 0 0 7 0 2 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 0 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 12 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 3 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 2 0 0 0 0 0 1 4 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 2 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 73 7 0 11 0 0 1 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 107 2 4 2 1 4 0 0 0 0 0 2 0 1 6 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 56 0 13 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 1 92 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 3 0 0 1 27 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 7 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 3 0 1 3 0 1 1 0 5 1 0 5 0 0 0 1 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 5 1 0 0 0 0 0 0 0 21 0 4 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 0 0 0 1 0 0 3 0 0 5 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 42 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 1 0 0 0 0 0 4 0 7 55 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 3 27 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 1 0 14 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 16/29\n",
"----------\n",
"train Loss: 1.8267 Acc: 0.5226\n",
"Confusion Matrix:\n",
"[[ 41 6 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 5 0 15 4 6 0 0 7 0 0 0 2 0 1 2 1 0 0 0]\n",
" [ 5 67 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 7 33 2 8 1 1 2 0 0 1 0 0 2 0 5 4 0 0 4 0]\n",
" [ 1 0 44 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 16 0 19 0 0 11 0 0 1 0 0 0 0 5 7 0 1 0]\n",
" [ 1 0 0 32 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 1 54 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 8 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 3 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 3 0 4 0 3 0 0 0 0 0 0 1 0 3 0 0 0 0 0]\n",
" [ 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9 1 2 3 1 3 0 0 0 0 0 0 0 3 4 0 0 0 0]\n",
" [ 0 0 6 0 0 1 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 4 0 0 4 0 0 0 0 0 0 1 3 8 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 2 3 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 3 0 0 3 0 0 1 0 0 1 0 0 1 0 0 0]\n",
" [ 2 1 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 5 1 0 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 8 0 0 2 1 8 0 0 0 0 1 1 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 7 0 3 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 2 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 12 0 0 5 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 3 17 0 1 0 2 0 1 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 21 0 5 0 0 1 0 0 3 0 0 0 1 0 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 4 3 0 0 2 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 1 4 0 1 0 0 0 0 0 0 0 0 0 0 3 4 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 3 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 3 0 0 0]\n",
" [ 0 1 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 2 0 0 2 0 1 0 0 0 0 0 2 0 3 8 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 1 5 0 0 1 0 0 1 0 0 0 0 2 4 0 0 0]\n",
" [ 7 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 116 19 0 10 1 3 1 1 2 0 0 0 3 1 3 0 0 0 0 0]\n",
" [ 3 9 1 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 16 157 1 9 4 3 9 1 1 0 0 0 1 0 2 9 1 0 0 0]\n",
" [ 0 2 3 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 5 94 2 19 0 0 6 0 0 2 0 1 0 0 3 5 0 0 0]\n",
" [ 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 6 3 131 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 10 2 143 0 0 0 0 0 1 0 0 0 3 1 6 0 0 0]\n",
" [ 5 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 4 0 3 0 46 6 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 8 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 8 0 1 0 1 109 0 0 0 0 0 2 0 0 2 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 8 0 4 0 0 42 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 11 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 5 0 7 1 0 0 0 14 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 19 0 0 0 1 1 0 1 5 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 14 0 0 1 0 0 14 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 3 0 1 2 3 0 0 0 0 0 8 1 1 8 3 0 0 0 0]\n",
" [ 0 6 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 11 0 6 0 0 1 0 0 0 0 0 33 0 1 6 0 0 0 0]\n",
" [ 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 7 5 1 7 0 1 2 0 0 0 0 0 1 0 5 5 0 1 0]\n",
" [ 3 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 3 0 4 1 0 0 0 0 0 0 3 0 0 63 7 1 0 0 0]\n",
" [ 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 13 0 0 1 0 0 1 0 0 0 0 1 0 7 89 1 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 7 1 5 0 1 0 0 0 0 0 0 0 4 3 41 0 0 0]\n",
" [ 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 1 0 2 0 0 0 0 1 0 0 1 0 0 1 3 0 0 2 0]\n",
" [ 1 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 3 5 0 2 0 0 4 0 0 0 0 0 1 0 1 8 0 0 14 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 2 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0]]\n",
"val Loss: 1.6031 Acc: 0.5889\n",
"Confusion Matrix:\n",
"[[ 28 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 11 1 3 0 0 5 0 0 0 0 0 3 0 1 0 0 0]\n",
" [ 1 53 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 3 9 2 2 3 0 3 0 0 0 0 0 0 0 1 4 0 0 1 0]\n",
" [ 0 1 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 13 0 14 0 0 5 0 0 0 0 0 0 0 0 6 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 1 0 0 0 0 0 2 2 0 1 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 0 0 1 0 0 0 0 0 0 0 0 0 5 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 13 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 2 2 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 3 1 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 77 2 0 11 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 107 2 5 1 1 4 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 64 1 8 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 6 2 85 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 2 0 0 0 27 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 28 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 2 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 5 0 0 1 0 0 9 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 1 3 0 1 1 0 4 2 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 5 1 0 0 0 0 0 0 0 20 0 3 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 0 1 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 2 0 0 0 0 0 0 0 0 0 0 41 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 5 57 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 1 2 0 5 0 0 0 0 0 0 0 0 0 0 5 24 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 1]]\n",
"\n",
"Epoch 17/29\n",
"----------\n",
"train Loss: 1.8322 Acc: 0.5173\n",
"Confusion Matrix:\n",
"[[ 43 6 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 21 5 1 13 1 4 0 0 2 0 0 1 0 1 5 1 1 0 1 0]\n",
" [ 2 70 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 2 32 2 9 3 1 4 0 0 2 0 0 2 0 4 5 0 0 1 0]\n",
" [ 1 0 40 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 3 19 5 19 0 0 5 0 0 3 0 0 1 1 4 2 0 0 0]\n",
" [ 1 0 0 33 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 1 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 1 0 2 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 3 3 0 7 0 1 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 6 0 1 2 0 1 0 0 0 0 0 1 0 0 7 0 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 6 0 4 0 0 2 0 0 0 0 0 0 0 2 5 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 2 0 0 0 0 0 0 0 4 0 0 0 1 0 0 0 0 0 0 0 3 0 0 2 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 7 1 0 0 1 5 0 0 0 0 0 2 0 0 2 0 0 0 0]\n",
" [ 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 10 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 15 0 1 5 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 5 14 0 0 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 5 16 0 8 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 2 0 0 0 0 0 1 0 2 6 1 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 2 0 0 10 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 4 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0]\n",
" [ 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 2 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 5 0 1 3 0 0 0 0 0 0 0 4 1 3 7 1 0 4 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 1 1 0 4 0 0 0 0 0 1 0 0 0 3 0 5 0 0 0]\n",
" [ 9 3 0 2 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 0 110 16 2 10 0 8 1 0 0 0 0 1 0 0 2 1 0 0 0 0]\n",
" [ 2 14 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 18 151 5 10 2 2 5 1 0 0 0 0 4 0 2 10 1 0 0 0]\n",
" [ 0 1 10 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 89 0 22 0 1 6 0 0 2 0 0 0 2 4 5 0 0 0]\n",
" [ 3 2 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 2 132 0 0 0 0 1 0 0 0 0 0 4 1 0 0 1 0]\n",
" [ 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 135 0 1 0 0 0 3 0 0 1 2 3 6 0 0 0]\n",
" [ 5 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 3 0 0 0 47 4 0 1 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 1 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 0 0 0 0 114 0 0 1 0 0 1 0 0 2 1 0 0 0]\n",
" [ 1 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 4 0 0 37 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 2 1 10 0 0 1 0 11 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 14 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 10 0 0 0 1 1 0 2 11 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 13 0 9 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 0 3 3 4 0 0 0 0 0 6 0 1 8 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 7 0 9 2 0 5 0 0 0 0 2 38 0 1 2 0 0 1 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 1 3 0 0 2 0 0 0 0 1 9 1 2 7 0 1 0]\n",
" [ 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 7 6 1 1 1 0 0 0 1 0 0 1 0 0 56 12 2 0 0 0]\n",
" [ 3 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 9 0 4 2 0 4 0 0 0 0 0 3 0 3 83 2 0 3 0]\n",
" [ 0 1 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 3 8 1 6 0 0 1 0 0 0 0 1 0 2 6 40 0 0 0]\n",
" [ 1 2 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 3 0 0 0 0 1 0 0 0 0 0 0 2 0 0 4 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 1 8 0 4 2 0 0 0 0 0 0 0 1 0 0 5 0 0 17 0]\n",
" [ 0 0 6 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 3 0 4 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0]]\n",
"val Loss: 1.5851 Acc: 0.5919\n",
"Confusion Matrix:\n",
"[[ 31 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 9 1 1 0 0 5 0 0 1 0 0 2 0 2 0 0 0]\n",
" [ 2 48 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 2 16 2 2 2 0 3 0 0 0 0 0 0 0 0 6 1 0 0 0]\n",
" [ 0 0 19 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 16 0 13 0 0 4 0 0 0 0 0 0 0 1 7 0 2 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0]\n",
" [ 0 0 3 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 3 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 13 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 2 2 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 10 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 76 6 0 9 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 113 2 5 1 0 2 0 0 0 0 0 0 0 0 6 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 63 0 7 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 7 1 83 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0]\n",
" [ 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 2 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 27 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 3 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 4 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 3 0 0 3 0 1 1 0 5 1 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 5 0 0 0 0 0 0 0 0 18 0 2 5 1 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 0 0 0 1 0 0 3 0 0 6 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 1 0 1 0 0 0 0 0 0 0 0 0 0 41 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 1 0 0 0 0 0 3 0 3 59 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 1 2 0 5 0 0 0 0 0 0 0 0 0 0 3 27 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 0 15 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0]]\n",
"\n",
"Epoch 18/29\n",
"----------\n",
"train Loss: 1.8224 Acc: 0.5069\n",
"Confusion Matrix:\n",
"[[ 42 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 5 0 14 0 7 0 0 1 0 0 0 1 0 4 3 0 0 1 0]\n",
" [ 4 63 1 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 5 36 0 6 2 1 3 0 1 0 0 0 2 0 2 11 0 0 2 0]\n",
" [ 0 3 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 5 18 2 23 0 0 6 0 0 1 0 0 1 0 2 5 0 1 0]\n",
" [ 2 0 0 29 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 2 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 2 0 0 56 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 1 0 1 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 3 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 4 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 2 0 5 0 3 1 0 0 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9 1 1 1 0 1 0 0 0 0 1 1 0 0 7 0 0 2 0]\n",
" [ 0 0 5 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 4 5 1 2 0 0 4 0 0 0 0 0 1 1 0 6 0 0 0]\n",
" [ 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 2 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 3 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 1 0 0 0 0 0 0 0 0 7 0 0 2 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 4 0 0 0 1 7 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 12 2 0 0 0 0 0 0 0 13 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 0 0 0 0 4 16 0 0 0 1 1 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 18 0 8 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 7 1 0 0 3 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 5 0 0 0 0 0 0 0 0 0 1 1 0 1 8 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 3 0 1 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 1 0 0 0 0 0 0 0 0 0 0 0 2 2 4 0 0 0]\n",
" [ 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 2 1 0 2 3 0 0 0 0 0 0 0 2 0 1 12 0 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 1 2 0 5 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0]\n",
" [ 8 6 0 1 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 111 18 1 10 1 4 2 0 0 0 1 0 0 0 3 1 0 0 1 0]\n",
" [ 3 17 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 20 152 5 3 3 3 10 0 0 0 0 0 4 0 1 7 0 0 0 0]\n",
" [ 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 92 3 21 0 2 3 0 0 2 1 0 0 3 1 5 0 0 0]\n",
" [ 4 5 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 132 0 1 2 0 0 0 0 0 1 0 4 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 16 0 140 0 0 0 0 0 2 0 0 1 1 1 6 0 0 0]\n",
" [ 5 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 4 0 0 0 46 6 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 8 0 1 1 0 113 1 0 0 0 0 0 0 0 1 0 1 1 0]\n",
" [ 1 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 14 0 2 0 0 33 0 0 1 0 1 0 0 0 0 0 0 0]\n",
" [ 13 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 5 0 10 0 1 1 0 13 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 13 0 0 0 0 2 0 0 13 0 0 0 0 0 0 0 1 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 11 0 17 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 5 0 1 3 3 0 0 0 0 0 6 3 0 9 2 0 0 0 0]\n",
" [ 0 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 11 0 5 1 0 1 0 0 2 0 0 34 1 1 4 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 3 1 7 0 0 2 0 0 0 0 2 5 1 4 8 0 0 0]\n",
" [ 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 5 6 0 6 1 0 0 0 1 0 0 2 0 0 48 14 3 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 19 3 5 2 0 0 0 0 0 0 0 0 0 8 78 0 0 1 0]\n",
" [ 1 0 11 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 8 0 4 0 1 1 0 0 0 0 1 1 2 0 42 0 2 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1 5 0 2 2 0]\n",
" [ 1 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 6 0 2 0 0 2 0 0 0 0 1 2 0 2 7 0 0 15 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 1 0 0 1 0 0 0 0 0 0 1 0 7 0 0 0]]\n",
"val Loss: 1.5851 Acc: 0.5943\n",
"Confusion Matrix:\n",
"[[ 33 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 1 9 2 2 0 0 4 0 0 1 0 0 1 0 1 0 0 0]\n",
" [ 2 55 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 3 8 2 2 3 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0]\n",
" [ 0 1 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 12 0 17 0 0 5 0 0 0 0 0 0 0 0 5 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 4 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 3 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 9 2 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 13 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 3 0 3 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 0 0 0 2 1 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 73 4 1 10 0 1 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 106 2 5 2 1 4 0 0 0 0 0 2 0 0 5 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 62 0 13 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 1 93 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 1 0 0 1 28 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 1 1 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 3 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 3 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 7 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 2 0 1 3 0 1 1 0 5 2 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 5 2 0 0 0 0 0 0 0 21 0 3 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 0 0 0 1 0 0 3 0 0 5 0 1 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 39 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 6 55 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 8 0 0 0 0 0 0 0 0 0 0 2 29 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 19/29\n",
"----------\n",
"train Loss: 1.8206 Acc: 0.5151\n",
"Confusion Matrix:\n",
"[[ 46 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 3 1 19 0 7 0 0 0 0 0 1 1 0 2 0 0 0 3 0]\n",
" [ 5 68 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 28 4 13 3 2 4 0 1 0 0 0 1 0 4 2 1 0 1 0]\n",
" [ 0 0 36 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 4 20 1 23 1 0 7 0 0 1 0 0 0 3 1 5 0 0 0]\n",
" [ 0 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 1 61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 1 0 1 0 3 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 2 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 4 1 0 4 0 2 0 0 1 1 0 0 1 0 4 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 7 1 3 2 0 1 0 0 0 0 0 2 0 1 5 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 4 0 0 0 3 0 0 0 0 0 1 0 3 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 3 0 1 0 0 0 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 4 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 3 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 2 2 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 5 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 8 0 1 1 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 2 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 10 1 0 0 0 0 0 0 0 11 1 0 6 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 2 17 0 1 0 1 2 0 0 0 0 0 2 0 0 1 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 16 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 3 0 0 2 0 0 0 0 0 0 0 2 0 3 2 2 0 1 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 1 0 2 6 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 4 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 4 2 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 1 3 0 5 2 0 1 0 0 0 0 1 3 1 2 7 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 1 1 4 0 4 0 1 0 0 0 0 0 1 0 0 0 3 0 0 0]\n",
" [ 6 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 115 15 1 16 4 2 0 0 0 0 0 0 0 0 7 3 0 0 0 0]\n",
" [ 1 16 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 141 5 7 5 2 8 0 0 1 0 0 4 1 2 12 1 0 0 0]\n",
" [ 0 1 4 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 9 89 0 29 0 1 4 0 0 1 0 0 0 1 0 5 0 0 0]\n",
" [ 3 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 6 0 129 0 1 0 0 0 0 0 0 1 0 3 1 1 0 1 0]\n",
" [ 0 1 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 17 1 134 0 0 0 0 0 3 0 0 0 2 0 5 0 0 0]\n",
" [ 5 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 3 0 1 0 48 5 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 3 6 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 11 0 0 0 0 113 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 15 0 4 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 10 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 9 0 1 0 0 19 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 0 0 0 0 1 0 0 15 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 1 14 0 1 1 0 0 12 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 4 0 2 2 1 0 0 1 1 0 8 1 0 9 2 0 0 0 0]\n",
" [ 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 12 1 3 3 0 4 0 0 0 0 1 34 0 1 3 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 3 4 0 1 2 0 0 0 0 2 7 1 5 3 0 0 0]\n",
" [ 3 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 5 0 5 1 0 0 0 1 0 0 0 0 0 56 11 0 0 0 0]\n",
" [ 3 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 3 14 0 0 1 0 0 0 0 0 0 0 3 1 9 77 2 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 2 7 1 11 0 0 1 0 0 0 0 1 0 0 6 41 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 0 0 1 0 1 0 0 1 0 0 1 0 0 2 3 1 1 1 0]\n",
" [ 1 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 2 2 0 4 0 0 3 0 0 0 0 0 1 1 0 6 0 0 19 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 0 3 0 0 0 0 0 1 0 0 1 1 2 5 0 0 0]]\n",
"val Loss: 1.5974 Acc: 0.5901\n",
"Confusion Matrix:\n",
"[[ 34 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 1 0 10 1 1 0 0 2 0 0 0 0 0 5 0 1 0 2 0]\n",
" [ 0 56 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 2 9 2 2 2 0 1 0 0 0 0 0 0 0 0 5 1 0 2 0]\n",
" [ 0 1 20 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 13 0 16 0 0 3 0 0 0 0 0 0 0 2 3 0 3 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 1 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 0 2 0]\n",
" [ 0 0 3 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 3 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 1 1 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 0 0 0 12 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 2 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 1 3 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 69 6 0 11 0 0 1 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 109 2 5 1 0 4 0 0 0 0 0 2 0 0 7 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 61 0 10 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 1 88 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 3 0 0 0 24 1 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 1 0 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 2 0 0 3 0 1 1 0 5 2 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 4 0 0 0 0 0 0 0 1 21 0 3 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 5 0 1 0 0 0 0 0 0 0 0 2 0 0 4 0 3 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 43 6 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 4 58 0 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 1 2 0 5 0 0 0 0 0 0 0 0 0 1 5 20 0 1 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 1]]\n",
"\n",
"Epoch 20/29\n",
"----------\n",
"train Loss: 1.8066 Acc: 0.5273\n",
"Confusion Matrix:\n",
"[[ 51 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 17 6 0 13 1 5 0 0 4 0 0 1 0 0 2 2 1 0 0 0]\n",
" [ 3 78 0 0 3 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 3 26 1 8 2 2 4 0 0 0 0 0 2 0 1 6 0 0 1 0]\n",
" [ 0 0 45 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 20 1 21 0 0 6 0 0 0 0 0 0 1 1 8 0 1 0]\n",
" [ 2 1 0 29 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 2 57 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 3 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 1 0 4 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 7 0 2 1 0 0 0 0 1 0 0 2 1 0 0 0 0]\n",
" [ 0 4 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 1 1 2 0 2 0 0 0 0 0 0 0 1 5 1 0 2 0]\n",
" [ 0 0 6 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 6 0 0 3 0 0 0 0 0 2 0 3 6 0 0 0]\n",
" [ 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 2 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 1 0 0 0 0 0 0 0 0 2 1 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 7 0 0 2 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 8 0 0 1 1 8 0 0 0 0 0 1 0 0 0 0 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 12 1 0 0 0 0 0 0 0 9 4 1 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 2 21 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 22 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 1 0 0 5 3 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 4 0 2 0 0 0 0 0 0 0 0 2 0 2 5 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 5 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 1 2 0 0 0 1 0 0 0 0 0 2 0 3 0 0 0]\n",
" [ 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 12 0 0 6 0 2 1 0 2 0 0 0 0 0 1 0 3 11 0 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 2 0 5 0 0 0 0 0 0 0 0 0 1 0 6 0 0 0]\n",
" [ 7 5 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 108 16 1 13 3 4 2 0 0 0 0 0 0 0 5 3 0 0 0 0]\n",
" [ 1 10 2 2 4 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 13 157 4 6 2 1 10 0 1 0 0 0 1 0 2 12 0 0 0 0]\n",
" [ 0 1 6 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 89 0 29 0 1 4 0 0 1 0 2 1 1 1 2 0 0 0]\n",
" [ 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 4 1 135 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 19 0 134 0 1 0 0 0 3 0 0 1 1 1 3 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 6 0 2 0 52 4 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 13 0 1 0 0 114 0 0 1 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 13 0 4 1 1 36 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 12 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 5 0 15 0 0 1 0 7 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 18 0 1 0 0 0 0 0 6 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 1 7 0 10 0 1 0 0 0 17 0 0 0 0 0 0 0 0 0]\n",
" [ 2 3 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 11 5 0 2 2 0 1 0 0 1 0 4 1 0 4 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 9 0 2 1 0 2 0 0 0 0 1 37 1 5 2 0 0 0 0]\n",
" [ 0 3 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 3 5 0 0 2 0 0 0 0 1 6 0 1 6 0 2 0]\n",
" [ 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 5 1 0 0 0 0 0 0 1 0 1 66 8 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 3 16 0 3 0 0 0 0 0 0 0 0 2 0 11 78 0 0 2 0]\n",
" [ 1 1 2 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 7 0 2 0 0 0 0 0 0 0 0 2 1 6 46 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 1 2 0 1 0 0 2 0 0 0 0 0 1 5 0 0 2 0]\n",
" [ 1 10 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 5 0 2 0 0 2 0 0 0 0 0 1 0 0 8 0 0 20 0]\n",
" [ 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 6 1 5 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0]]\n",
"val Loss: 1.5793 Acc: 0.5943\n",
"Confusion Matrix:\n",
"[[ 34 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 10 2 1 0 0 2 0 0 0 0 0 2 0 1 0 0 0]\n",
" [ 1 54 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 4 11 2 2 3 0 1 0 1 0 0 0 0 0 0 4 0 0 1 0]\n",
" [ 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 13 0 18 0 0 3 0 0 0 0 0 0 0 0 7 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 6 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 13 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 1 0 2 0 1 0 0 0 0 0 0 0 0 3 0 0 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 3 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 1 0 0 0 0 1 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 76 2 0 12 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 111 2 4 2 0 3 0 0 0 0 0 0 0 0 5 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 64 0 13 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 1 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 3 0 0 1 26 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 3 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 2 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 7 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 1 2 0 1 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 7 1 0 0 0 0 0 0 0 20 0 2 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 4 0 0 0 0 0 0 0 0 0 0 39 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 1 0 0 0 0 0 0 0 0 2 0 6 57 0 0 2 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 3 28 0 0 1]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 1 0 16 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 21/29\n",
"----------\n",
"train Loss: 1.8186 Acc: 0.5223\n",
"Confusion Matrix:\n",
"[[ 44 3 1 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 17 6 0 20 2 3 0 0 5 0 0 0 2 0 1 1 0 0 2 0]\n",
" [ 3 72 2 0 1 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 5 28 1 8 0 1 3 0 0 0 0 0 4 0 1 9 0 0 3 0]\n",
" [ 1 1 43 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 21 2 20 1 0 6 0 0 1 0 0 1 1 1 4 0 0 0]\n",
" [ 0 0 0 30 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 1 55 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 5 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 3 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 4 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 2 0 7 0 1 0 0 0 0 0 0 0 1 0 4 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 7 1 2 1 0 0 1 0 0 0 0 1 0 2 3 0 0 2 0]\n",
" [ 0 0 6 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 1 5 0 0 2 0 0 0 0 0 2 1 3 6 0 1 0]\n",
" [ 2 1 2 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 4 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 6 0 0 1 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 2 7 1 0 1 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 7 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 0 0 0 0 0 0 17 0 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 29 0 0 0 0 0 0 0 1 22 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 1 19 1 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 4 2 1 0 5 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 4 0 1 0 0 1 0 0 0 0 0 1 1 1 6 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 6 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 2 3 0 1 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 2 2 0 3 3 0 1 0 0 1 0 0 1 0 1 9 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 1 1 0 6 0 0 0 0 0 0 0 0 0 1 3 7 0 0 0]\n",
" [ 6 3 1 1 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 109 14 1 14 2 5 3 0 1 0 0 0 1 0 4 2 0 0 0 0]\n",
" [ 1 15 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 24 149 2 7 6 2 8 0 0 1 0 0 3 0 2 5 1 0 1 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 97 2 17 0 0 6 0 0 1 0 1 0 1 3 7 0 0 0]\n",
" [ 6 3 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 135 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 16 3 140 0 0 0 0 0 1 0 0 0 2 2 1 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 6 0 0 0 56 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 6 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 12 0 1 0 2 108 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 16 1 3 0 1 29 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 4 0 13 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 17 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 10 0 18 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 6 0 4 1 3 0 0 0 0 0 6 2 0 6 3 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 5 0 0 3 0 0 0 0 2 40 0 4 3 1 0 0 0]\n",
" [ 1 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 5 4 7 0 1 1 0 0 0 0 1 3 2 2 3 0 0 0]\n",
" [ 2 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 0 5 0 0 1 0 0 0 0 1 1 1 60 9 1 0 0 0]\n",
" [ 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 14 0 0 2 0 1 0 0 0 0 0 3 0 11 85 0 0 1 0]\n",
" [ 0 1 8 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 1 5 0 0 0 0 0 0 0 0 0 3 5 43 0 0 0]\n",
" [ 2 0 1 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 0 1 0 0 1 0 0 0 0 0 0 4 0 0 2 0]\n",
" [ 2 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 7 0 1 0 0 2 0 0 0 0 0 1 0 0 7 0 0 20 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 9 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0]]\n",
"val Loss: 1.6041 Acc: 0.5841\n",
"Confusion Matrix:\n",
"[[ 29 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 10 1 1 0 0 4 0 0 1 0 0 5 0 1 0 0 0]\n",
" [ 1 52 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 4 15 2 2 2 0 0 0 0 0 0 0 0 0 0 4 1 0 1 0]\n",
" [ 0 1 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 15 0 14 0 0 3 0 0 0 0 0 0 0 2 4 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 14 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 2 0 0 0 0 1 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 73 7 0 10 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 113 2 4 0 0 2 0 0 0 0 0 0 0 1 6 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 66 0 7 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 6 1 89 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 3 0 0 0 24 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 75 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 5 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 2 0 0 1 0 4 2 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 5 1 0 0 0 0 0 0 0 19 0 3 5 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 2 0 0 0 0 0 0 0 0 0 0 41 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 1 0 0 0 0 0 5 0 3 58 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 4 27 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 15 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1]]\n",
"\n",
"Epoch 22/29\n",
"----------\n",
"train Loss: 1.8083 Acc: 0.5176\n",
"Confusion Matrix:\n",
"[[ 47 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 16 5 1 17 0 4 2 0 5 0 0 0 0 0 3 3 0 0 2 0]\n",
" [ 3 79 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 9 23 2 10 2 4 3 0 1 0 0 0 0 0 2 3 0 0 1 0]\n",
" [ 1 1 41 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 18 3 19 0 0 7 0 0 1 0 0 2 0 3 6 0 1 0]\n",
" [ 0 1 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 5 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 3 54 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 3 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 4 2 0 7 0 1 0 0 0 0 0 0 1 0 1 2 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9 2 1 1 0 3 0 0 0 0 0 4 0 1 5 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 6 0 0 3 0 0 0 0 0 0 0 3 11 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 2 2 0 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 5 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 1 0 0 0 0 0 0 0 3 1 1 1 0 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 9 0 0 1 1 7 0 0 0 0 0 2 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 9 1 0 0 0 0 0 0 0 13 0 0 6 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 1 19 1 1 0 1 4 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 18 0 7 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 1 0 0 2 0 2 1 0 0 0 0 0 0 0 1 0 2 3 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 1 0 6 0 0 0 0 0 0 0 0 0 0 1 0 1 5 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 3 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 1 1 0 0 0 0 0 0 0 0 2 1 3 0 1 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 14 0 2 1 0 3 5 0 0 0 0 0 0 0 1 1 2 9 0 0 2 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 5 0 0 0 0 0 0 0 0 0 2 2 6 0 0 0]\n",
" [ 8 4 0 1 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 96 21 1 21 0 5 2 0 0 0 0 0 0 0 5 1 1 0 0 0]\n",
" [ 4 17 1 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 16 144 5 6 2 1 8 0 1 0 0 0 8 0 2 10 0 0 0 0]\n",
" [ 0 3 8 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 88 0 28 0 0 4 0 0 2 0 0 0 2 0 7 0 0 0]\n",
" [ 2 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 3 0 133 1 0 1 0 0 0 0 0 0 0 3 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 141 0 0 0 0 0 1 0 0 2 2 0 1 0 0 0]\n",
" [ 2 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 2 0 2 0 47 4 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 1 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 16 0 0 0 0 111 0 0 0 1 0 2 0 0 1 0 0 1 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 12 0 5 0 1 33 0 0 1 0 0 0 0 0 1 0 0 0]\n",
" [ 7 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 3 0 12 0 1 0 0 17 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 14 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 11 0 1 0 0 1 0 0 12 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 14 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 5 1 4 3 1 1 0 0 0 0 3 1 0 7 1 0 0 0 0]\n",
" [ 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 0 2 0 0 3 0 0 0 0 1 38 0 5 5 0 0 2 0]\n",
" [ 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 2 5 1 0 1 0 0 0 0 0 9 0 2 4 0 2 0]\n",
" [ 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 0 4 1 0 0 1 0 0 0 0 0 1 63 8 0 0 0 0]\n",
" [ 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 0 1 12 0 1 0 0 1 0 0 0 0 0 2 2 6 87 1 0 0 0]\n",
" [ 0 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 3 8 0 5 0 0 1 0 0 0 0 0 1 2 5 43 0 0 0]\n",
" [ 1 0 2 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 4 0 0 0 0 0 0 0 0 0 0 0 2 2 0 3 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 4 0 1 1 0 3 0 0 0 0 0 1 0 2 5 0 0 21 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 9 0 1 0 0 0 0 0 1 0 0 1 1 1 3 0 0 0]]\n",
"val Loss: 1.6060 Acc: 0.5877\n",
"Confusion Matrix:\n",
"[[ 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 9 1 1 0 0 1 0 0 0 0 0 6 0 1 0 0 0]\n",
" [ 0 49 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 4 15 2 2 1 0 3 0 0 0 0 0 0 0 0 7 1 0 0 0]\n",
" [ 0 1 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 13 0 14 0 0 4 0 0 0 0 0 0 0 2 4 0 3 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 2 0 0 0 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 2 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 9 2 0 0 0 0 0 0 0 6 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 0 0 0 0 0 11 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 3 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 1 0 0 0 0 1 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 78 5 0 7 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 112 2 4 0 0 3 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 60 0 8 0 0 2 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 86 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 1 87 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 3 0 0 0 26 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 75 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 26 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 1 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 6 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 3 0 1 3 0 0 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 3 1 0 0 0 0 0 0 0 21 0 4 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 0 1 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 1 0 0 0 0 0 0 0 0 0 0 42 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 1 0 0 0 0 0 5 0 4 58 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 2 2 0 5 0 0 0 0 0 0 0 0 0 0 5 25 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 1 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 14 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 1]]\n",
"\n",
"Epoch 23/29\n",
"----------\n",
"train Loss: 1.8014 Acc: 0.5251\n",
"Confusion Matrix:\n",
"[[ 49 7 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 5 1 16 0 2 0 0 2 0 0 0 1 0 0 2 0 0 1 0]\n",
" [ 1 72 1 1 3 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 2 0 3 33 1 8 0 3 1 0 1 0 0 0 1 0 4 7 0 0 0 0]\n",
" [ 2 0 39 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 17 0 25 0 0 5 0 0 0 0 0 0 2 4 5 0 1 0]\n",
" [ 0 0 0 27 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 4 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 3 0 0 58 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 1 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 5 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 1 9 0 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0]\n",
" [ 3 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 10 0 1 1 0 1 0 0 0 0 0 3 0 1 1 0 0 0 0]\n",
" [ 0 0 6 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 8 0 3 0 0 4 0 0 0 0 0 0 1 2 5 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 4 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 0 0 0 0 0 0 0 5 0 0 2 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 3 8 0 0 2 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 11 1 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 11 1 0 0 0 0 0 0 0 12 1 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 1 13 0 1 0 1 5 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 20 0 5 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 1 0 0 5 4 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 1 3 1 2 6 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 2 1 0 3 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 3 2 2 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 13 0 3 3 0 1 4 0 0 0 0 0 0 0 2 1 2 10 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 1 2 0 8 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 3 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 117 22 2 9 3 3 3 0 0 0 0 0 0 1 2 1 0 0 0 0]\n",
" [ 3 10 0 1 2 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 20 154 3 7 5 3 6 0 1 0 0 0 3 0 5 6 0 0 0 0]\n",
" [ 0 1 6 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 9 87 2 18 0 0 7 0 0 4 0 0 0 1 3 4 0 1 0]\n",
" [ 4 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 6 3 0 134 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 14 1 143 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0]\n",
" [ 4 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 10 0 1 0 49 3 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 1 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 15 0 0 1 1 109 0 0 0 0 0 1 0 0 1 1 0 0 0]\n",
" [ 0 0 9 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 14 1 2 0 0 34 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 10 0 12 0 1 0 0 11 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 15 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 15 0 0 0 1 0 0 2 9 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 19 0 0 1 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 6 6 0 4 1 2 0 0 0 0 0 6 0 0 8 3 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 1 3 0 0 3 0 0 0 0 3 41 1 1 3 0 0 1 0]\n",
" [ 0 1 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 2 5 0 2 2 0 0 0 0 3 5 1 1 5 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 1 3 0 0 0 0 2 0 0 0 0 0 69 9 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 15 0 4 0 0 2 0 0 0 0 0 0 0 12 84 0 0 0 0]\n",
" [ 0 1 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 10 0 10 0 1 1 0 0 0 1 0 0 1 3 40 0 0 0]\n",
" [ 2 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 0 0 0 1 0 0 0 0 0 1 4 0 0 2 0]\n",
" [ 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 9 0 2 0 0 1 0 0 0 0 0 0 0 0 5 0 0 21 0]\n",
" [ 0 0 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 2 0 0 0 0 0 1 0 0 1 0 0 4 0 0 0]]\n",
"val Loss: 1.5876 Acc: 0.5931\n",
"Confusion Matrix:\n",
"[[ 31 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 11 1 1 0 0 3 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 1 52 0 0 1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 3 14 2 2 2 0 1 0 0 0 0 0 0 0 1 4 1 0 0 0]\n",
" [ 0 1 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 12 0 15 0 0 5 0 0 0 0 0 0 0 0 6 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 2 0 2 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0]\n",
" [ 0 0 3 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 3 0 0 2 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 9 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 13 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 3 1 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 10 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 5 0 12 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 110 2 5 1 0 3 0 0 0 0 0 0 0 1 6 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 64 0 7 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 4 1 90 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 2 0 0 0 26 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 27 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 0 1 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 1 3 0 1 1 0 4 2 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 6 1 0 0 0 0 0 0 0 20 0 3 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 5 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 4 0 0 0 0 0 0 0 0 0 0 39 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 1 0 0 1 0 0 0 0 0 4 0 6 55 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 6 0 0 0 0 0 0 0 0 0 0 3 30 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]]\n",
"\n",
"Epoch 24/29\n",
"----------\n",
"train Loss: 1.8053 Acc: 0.5251\n",
"Confusion Matrix:\n",
"[[ 41 6 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 4 0 22 1 6 1 0 1 0 0 1 0 0 4 1 0 0 1 0]\n",
" [ 6 75 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 4 25 0 7 1 2 5 0 0 1 0 0 3 0 5 5 0 0 2 0]\n",
" [ 1 0 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 18 0 20 0 0 8 0 0 0 0 0 2 2 2 2 0 1 0]\n",
" [ 1 0 0 30 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 1 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 1 0 2 0 2 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 7 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 8 0 2 0 0 0 0 0 1 0 0 3 0 0 0 0 0]\n",
" [ 0 8 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 2 0 2 0 0 0 0 0 1 0 4 7 0 0 0 0]\n",
" [ 0 1 10 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 5 0 4 0 0 2 0 0 0 0 0 0 1 0 3 0 0 0]\n",
" [ 2 0 2 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 1 0 0 1 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 5 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 8 0 0 0 1 9 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 10 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 12 1 0 0 0 0 0 0 0 9 1 1 3 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 3 20 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 22 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 3 0 2 0 0 0 0 0 0 0 0 0 1 4 3 1 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 4 0 1 9 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 5 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 1 0 2 0 1 0]\n",
" [ 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 15 0 1 3 0 2 1 0 0 0 0 0 0 0 2 1 1 9 0 0 2 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 1 0 2 0 3 0 0 0 0 0 0 0 0 1 1 1 5 0 0 1]\n",
" [ 4 2 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 114 19 0 15 1 6 0 0 0 0 0 0 0 0 3 3 0 0 0 0]\n",
" [ 3 17 1 1 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 19 145 6 5 5 2 10 0 1 0 0 0 1 0 2 8 0 0 0 0]\n",
" [ 0 1 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 101 1 22 0 0 7 0 0 0 0 0 1 1 1 4 0 0 0]\n",
" [ 7 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 0 124 1 0 1 0 1 0 0 0 0 0 5 4 0 0 1 0]\n",
" [ 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 2 140 0 0 0 0 0 3 0 0 0 4 0 6 0 0 0]\n",
" [ 4 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 5 0 0 0 45 4 0 1 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 2 6 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 0 0 0 2 112 0 0 0 0 0 1 0 0 2 2 0 0 0]\n",
" [ 0 1 10 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 13 1 3 0 0 32 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 13 4 0 7 0 0 0 0 18 0 0 1 0 0 2 1 0 0 0 0]\n",
" [ 0 14 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 12 0 0 0 1 3 0 1 9 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 12 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 4 0 3 1 1 0 0 1 1 0 9 0 1 7 2 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 9 0 2 0 0 2 0 0 0 0 0 42 1 4 3 0 0 0 0]\n",
" [ 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 4 0 8 0 1 1 0 0 0 0 2 6 2 1 5 0 1 0]\n",
" [ 2 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 0 6 0 1 1 0 1 0 0 1 0 1 60 8 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 15 0 2 1 0 1 0 0 0 0 1 2 1 8 80 0 0 2 0]\n",
" [ 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 6 1 7 0 1 1 0 0 0 0 0 0 3 8 44 0 0 0]\n",
" [ 0 0 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 1 0 1 1 0 0 0 0 0 0 6 0 0 2 0]\n",
" [ 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 1 6 1 2 1 0 2 0 0 1 0 0 1 0 0 1 0 0 24 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 8 2 3 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0]]\n",
"val Loss: 1.5882 Acc: 0.5883\n",
"Confusion Matrix:\n",
"[[ 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 13 1 1 0 0 0 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 2 53 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 4 9 2 3 2 0 1 0 0 0 0 0 0 0 2 4 0 0 0 0]\n",
" [ 0 1 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 14 0 15 0 0 3 0 0 0 0 0 0 0 0 6 0 2 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 1 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 6 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 13 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 5 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 3 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 2 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 8 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 2 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 79 2 0 13 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 108 2 6 1 1 2 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 64 0 10 0 0 1 0 0 0 0 0 0 0 1 3 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 4 1 90 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 2 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 0 0 0 75 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 26 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 4 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 6 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 3 0 0 3 0 0 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 7 1 0 0 0 0 0 0 0 20 0 4 2 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 1 0 0 0 0 0 1 0 0 4 0 0 3 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 4 0 0 0 0 0 0 0 0 0 0 40 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 4 0 8 54 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 1 2 0 7 0 0 0 0 0 0 0 0 0 1 4 25 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 25/29\n",
"----------\n",
"train Loss: 1.8136 Acc: 0.5180\n",
"Confusion Matrix:\n",
"[[ 41 5 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 18 5 0 22 1 5 0 0 1 0 0 0 2 0 4 2 0 0 0 0]\n",
" [ 7 70 0 0 3 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 3 26 1 8 2 2 4 0 1 0 0 1 1 0 3 8 0 0 1 0]\n",
" [ 0 1 44 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 1 0 19 4 14 0 0 8 0 0 1 0 1 1 2 1 5 0 1 0]\n",
" [ 0 1 0 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 62 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 1 0 0 2 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 6 2 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 8 0 3 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 10 0 1 1 0 2 0 0 0 0 0 1 0 2 6 0 0 1 0]\n",
" [ 0 1 6 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 3 6 1 6 0 1 3 0 0 0 0 0 0 0 2 1 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 0 1 1 2 2 0 0 0 1 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 0 0 3 0 0 0 0 0 0 0 0 3 0 0 0]\n",
" [ 4 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 0 0 0 0 0 1 0 0 4 0 0 0 2 5 0 0 0 0 0 1 0 1 5 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 8 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 11 0 1 4 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 3 17 0 2 0 0 4 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 19 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 7 2 0 0 1 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 1 11 0 0 0 0]\n",
" [ 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 1 0 0 0 0 0 0 0 0 3 2 1 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 16 0 2 2 0 6 0 0 0 0 0 0 0 0 2 0 3 7 1 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 2 2 4 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0]\n",
" [ 9 5 0 2 4 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 104 18 3 10 1 4 2 0 1 0 0 0 0 0 5 1 0 0 0 0]\n",
" [ 3 12 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 15 158 2 4 5 3 5 0 2 0 0 1 3 0 4 9 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 8 84 2 21 0 1 6 0 0 2 0 0 0 1 0 7 0 0 0]\n",
" [ 5 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 4 0 128 0 0 0 0 1 0 0 0 0 0 3 0 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 3 139 0 0 0 0 0 1 0 0 0 0 1 5 0 0 0]\n",
" [ 3 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 3 0 1 0 48 9 0 2 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 2 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 4 110 1 0 1 0 0 2 0 0 2 0 0 0 0]\n",
" [ 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 14 0 7 0 0 33 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 6 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 12 3 0 14 0 0 1 0 14 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 1 15 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 13 0 0 0 1 0 0 2 10 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 14 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 7 4 0 4 2 2 0 0 1 0 0 6 1 1 1 3 1 0 0 0]\n",
" [ 1 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 4 0 0 3 0 0 0 0 0 36 1 4 3 0 0 0 0]\n",
" [ 0 3 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 6 0 4 0 0 0 0 0 0 0 0 8 1 0 8 0 0 0]\n",
" [ 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 5 0 5 2 0 0 0 1 0 0 0 0 0 65 4 0 0 0 0]\n",
" [ 1 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 14 0 2 2 0 1 0 0 0 0 0 0 2 7 84 2 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 2 6 1 7 0 0 1 0 0 0 0 0 0 4 3 43 0 1 0]\n",
" [ 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 1 0 0 0 0 1 0 1 5 0 2 0 0]\n",
" [ 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 1 6 0 1 0 0 2 0 0 0 0 0 1 0 1 7 0 0 21 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 6 0 0 0 0 0 0 0 0 0 1 0 6 0 0 0]]\n",
"val Loss: 1.5921 Acc: 0.5805\n",
"Confusion Matrix:\n",
"[[ 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 9 1 1 0 0 5 0 0 0 0 0 6 0 2 0 1 0]\n",
" [ 0 49 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 3 17 2 2 2 0 3 0 0 0 0 0 0 0 1 4 1 0 1 0]\n",
" [ 0 1 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 14 0 15 0 0 4 0 0 0 0 0 0 0 0 6 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 0 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 1 2 0 0 1 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 5 0 0 2 0]\n",
" [ 0 0 3 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 3 0 0 0 0 5 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 6 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 13 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 3 1 0 0 0 0 1 3 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 73 8 0 11 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 111 2 3 1 0 4 0 0 0 0 0 2 0 0 5 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 60 0 11 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 87 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 4 1 89 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 4 0 0 1 26 2 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 75 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 1 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 6 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 3 0 1 1 0 5 3 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 3 1 0 0 0 0 0 0 0 22 0 4 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 0 0 0 2 1 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 1 0 0 0 0 0 0 0 0 0 0 43 6 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 5 0 5 57 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 2 0 6 0 0 0 0 0 0 0 0 0 0 3 28 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 15 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 26/29\n",
"----------\n",
"train Loss: 1.8257 Acc: 0.5162\n",
"Confusion Matrix:\n",
"[[ 46 3 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 20 4 1 14 2 3 0 0 1 1 0 0 1 0 5 2 2 0 1 0]\n",
" [ 4 68 1 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 7 35 1 6 1 2 5 0 0 0 0 0 2 0 4 3 0 0 2 0]\n",
" [ 0 0 40 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 6 21 1 17 0 0 7 0 0 1 0 0 0 1 3 4 0 0 0]\n",
" [ 0 0 0 32 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 1 57 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 2 0 1 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 3 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 3 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 0 11 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 2 3 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 1 0 1 3 0 0 0 0 0 0 0 2 10 0 0 0 0]\n",
" [ 0 2 5 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 4 0 4 0 0 4 0 0 0 0 1 1 0 2 1 0 1 0]\n",
" [ 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 1 0 1 2 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 2 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 2 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 3 6 0 0 0 0 8 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 4 0 5 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 14 0 1 3 0 1 0 0 1 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 18 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 20 0 6 0 0 0 0 0 4 0 0 0 0 0 1 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 2 1 0 0 0 0 0 0 0 0 0 3 2 2 0 4 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 5 0 0 0 0 0 0 0 0 0 0 1 0 1 10 0 0 0 0]\n",
" [ 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 2 3 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 1 3 0 0 0]\n",
" [ 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 3 1 0 4 2 0 1 0 0 0 0 0 2 1 1 8 0 0 1 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 5 0 0 0 0 0 0 0 0 2 2 2 3 0 0 0]\n",
" [ 9 2 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 111 19 1 16 1 4 1 0 1 0 0 0 1 1 1 0 0 0 0 0]\n",
" [ 1 13 0 2 2 1 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 12 157 2 9 3 3 6 0 0 0 0 0 4 1 3 7 1 0 0 0]\n",
" [ 1 2 7 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 7 86 1 24 0 0 3 0 0 4 0 1 0 0 3 3 0 0 0]\n",
" [ 2 2 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 3 1 126 1 1 0 0 4 0 0 0 1 0 2 1 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 13 2 140 0 0 1 0 0 1 0 1 1 0 1 5 0 0 0]\n",
" [ 7 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 3 0 2 0 44 6 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 11 0 1 0 1 109 0 0 1 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 1 7 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 8 1 2 0 0 39 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 7 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 7 0 11 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 14 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 16 0 0 0 0 1 0 0 9 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 13 0 15 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 4 0 3 0 0 0 0 0 10 1 0 7 4 0 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 3 1 0 1 0 0 0 0 1 36 0 3 7 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 6 2 5 1 1 1 0 0 0 1 0 5 3 1 6 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 9 2 0 2 1 0 0 0 0 0 0 1 0 1 62 7 2 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 1 11 0 2 1 0 2 0 0 0 0 0 1 0 13 82 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 3 9 1 8 0 1 1 0 0 0 0 1 0 2 2 45 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 5 0 1 0 0 0 0 0 0 0 0 1 2 0 1 2 0]\n",
" [ 2 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 1 0 0 1 0 0 0 0 0 1 0 0 6 1 0 21 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 4 0 2 0 0 0 0 0 1 0 0 0 0 1 3 0 0 0]]\n",
"val Loss: 1.5897 Acc: 0.5889\n",
"Confusion Matrix:\n",
"[[ 29 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 10 1 1 0 0 4 0 0 1 0 0 5 0 1 0 0 0]\n",
" [ 0 50 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 4 10 2 2 3 0 3 0 0 0 0 0 0 0 3 4 0 0 1 0]\n",
" [ 0 0 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11 0 15 0 0 4 0 0 0 0 0 0 0 0 6 0 1 0]\n",
" [ 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 1 2 0 0 0 0 0 0 0 0 2 4 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 3 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 6 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 1 0 0 2 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 8 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 13 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 0 3 3 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 2 4 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 2 4 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 79 2 0 11 0 0 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 107 2 5 2 1 5 0 0 0 0 0 1 0 0 6 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 62 0 9 0 0 1 0 0 0 0 0 0 0 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 5 1 90 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 2 0 0 1 26 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 76 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 2 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 3 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 6 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 1 3 0 1 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 6 1 0 0 0 0 0 0 0 20 0 4 4 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 3 0 0 4 0 2 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 42 5 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 3 0 9 55 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 6 0 0 0 0 0 0 0 0 0 0 3 29 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0]\n",
" [ 0 8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 13 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 27/29\n",
"----------\n",
"train Loss: 1.8227 Acc: 0.5294\n",
"Confusion Matrix:\n",
"[[ 51 4 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 18 1 2 19 2 5 0 0 1 0 0 0 1 0 0 3 0 0 1 0]\n",
" [ 1 71 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 5 29 2 10 3 0 7 0 0 0 0 0 3 0 2 5 1 0 1 0]\n",
" [ 0 0 49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 4 24 0 15 0 0 4 0 0 0 0 1 0 2 3 3 0 0 0]\n",
" [ 1 0 0 31 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 63 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 4 1 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 1 1 5 0 2 0 0 0 0 0 0 0 0 2 2 0 0 1 0]\n",
" [ 1 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 6 0 2 3 0 1 0 0 0 0 0 1 0 3 4 0 0 2 0]\n",
" [ 0 1 7 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 2 1 5 0 0 3 0 0 0 0 0 0 1 3 5 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 3 0 2 1 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 2 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0]\n",
" [ 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 3 0 0 3 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 3 0 0 1 1 0 0 0 0 0 0 0 4 2 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 8 0 0 1 1 8 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 9 3 0 0 0 0 0 0 0 10 2 1 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 0 0 0 0 2 13 1 2 0 1 0 0 0 0 0 0 1 0 1 1 0 0 0 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 15 0 10 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 1 1 4 2 1 0 1 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 3 0 3 1 0 0 0 0 0 0 0 1 1 1 6 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 4 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 2 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0]\n",
" [ 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 2 4 0 1 0 0 1 0 0 0 0 0 7 1 0 10 1 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 8 0 1 0 0 0 0 0 0 0 1 1 4 0 0 0]\n",
" [ 6 5 0 3 3 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 109 20 1 12 1 5 0 0 0 0 1 0 0 0 3 0 0 0 0 0]\n",
" [ 0 14 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 16 156 4 6 3 1 12 0 0 0 0 0 5 0 2 7 0 0 1 0]\n",
" [ 0 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 10 87 3 22 0 1 3 0 0 1 0 0 0 1 1 6 0 0 0]\n",
" [ 5 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 5 0 131 0 1 0 0 1 0 0 0 0 0 1 2 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 5 144 0 0 0 0 0 2 0 0 0 0 1 6 0 0 0]\n",
" [ 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 5 0 0 0 51 3 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 11 1 0 0 2 113 0 0 1 0 0 1 0 0 2 0 0 0 0]\n",
" [ 1 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 15 0 2 0 0 36 0 0 1 0 0 0 0 0 2 0 0 0]\n",
" [ 10 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 7 0 9 0 0 0 0 13 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 16 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11 0 1 0 0 0 0 1 14 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 6 1 19 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0]\n",
" [ 1 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 8 1 4 1 2 0 0 1 0 0 8 0 1 3 3 1 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 10 0 3 0 0 3 0 0 0 0 0 37 0 2 6 2 0 1 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 7 3 4 0 1 2 0 0 0 0 0 7 0 2 5 0 2 0]\n",
" [ 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 9 1 0 6 4 0 0 0 0 0 0 1 0 0 58 7 1 0 0 0]\n",
" [ 0 4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 11 0 1 3 0 2 0 0 0 0 0 0 0 12 82 0 0 2 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 2 9 1 10 0 1 3 0 0 0 0 0 0 4 1 39 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0]\n",
" [ 2 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 5 0 4 0 0 2 0 0 0 0 0 1 0 2 7 1 0 18 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 0 2 0 0 0 0 0 0 0 0 0 1 3 3 0 0 0]]\n",
"val Loss: 1.5790 Acc: 0.5913\n",
"Confusion Matrix:\n",
"[[ 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 11 1 3 0 0 4 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 1 52 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 4 12 2 2 3 0 2 0 0 0 0 0 0 0 0 4 0 0 1 0]\n",
" [ 0 1 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 12 0 17 0 0 3 0 0 0 0 0 0 0 0 6 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 0 0 0 0 0 0 2 2 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 9 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 12 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 2 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 9 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 76 3 0 12 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 110 2 4 2 0 3 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 60 0 12 0 0 1 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 3 1 91 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0]\n",
" [ 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 2 0 0 1 26 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 76 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 7 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 1 3 0 1 1 0 4 2 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 5 1 0 0 0 0 0 0 0 19 0 4 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 0 0 0 0 0 1 0 0 3 1 0 5 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 43 5 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 0 0 0 0 4 0 7 56 0 0 1 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 3 29 0 0 1]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 1 1 0 0 16 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Epoch 28/29\n",
"----------\n",
"train Loss: 1.7966 Acc: 0.5319\n",
"Confusion Matrix:\n",
"[[ 45 2 1 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 20 4 2 18 2 2 0 0 2 0 0 0 1 0 4 2 0 0 1 0]\n",
" [ 3 68 1 0 4 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 6 29 1 9 2 4 3 0 1 0 0 0 1 1 1 5 0 0 2 0]\n",
" [ 0 0 40 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 25 0 19 0 0 3 0 0 1 0 0 2 2 3 6 0 0 0]\n",
" [ 0 0 1 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 53 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 6 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 2 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 2 0 7 0 2 0 0 1 0 0 0 0 0 2 1 0 0 1 0]\n",
" [ 1 5 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 5 1 1 2 0 2 0 0 0 0 0 1 0 4 2 0 0 1 0]\n",
" [ 1 0 5 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 8 1 4 0 0 4 0 0 0 0 0 0 0 2 6 0 0 0]\n",
" [ 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 1 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 6 0 0 1 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 7 0 0 1 1 7 0 0 0 0 0 1 0 0 1 0 0 0 0]\n",
" [ 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 3 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 10 2 0 0 0 0 0 0 0 14 1 0 2 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 0 17 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 18 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 2 0 2 1 0 0 0 0 0 0 1 2 0 2 4 1 0 1 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 1 0 1 0 1 0 0 0 0 0 0 0 0 3 0 2 5 1 0 0 0]\n",
" [ 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 1 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 2 0 0 0 0 0 0 0 0 0 1 0 3 0 1 0]\n",
" [ 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 14 0 0 3 0 1 2 0 0 0 0 0 0 0 3 0 1 12 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 1 6 0 0 0 0 0 0 0 0 0 1 0 7 0 0 0]\n",
" [ 5 2 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 112 15 0 13 0 7 2 0 1 0 0 0 0 0 9 2 0 0 0 0]\n",
" [ 3 12 2 0 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 20 155 5 5 1 1 10 0 0 0 0 1 3 0 0 8 0 0 0 0]\n",
" [ 0 1 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 9 90 3 20 0 0 7 0 0 1 0 1 0 1 0 6 0 0 0]\n",
" [ 5 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 3 0 131 0 1 1 0 1 0 0 0 1 0 3 0 0 0 0 0]\n",
" [ 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 2 145 0 0 0 0 0 1 0 0 0 1 1 3 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 5 0 0 0 52 3 0 0 0 0 1 0 0 0 1 0 0 0 0]\n",
" [ 1 5 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 10 0 0 0 0 112 0 0 0 0 0 2 0 0 2 1 0 1 0]\n",
" [ 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 9 0 4 0 0 38 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 10 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 5 0 11 1 1 0 0 14 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 1 11 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 2 15 0 0 0 0 1 0 0 11 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 14 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0]\n",
" [ 2 1 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 11 4 0 4 1 1 1 0 0 1 0 3 1 0 6 0 0 0 0 0]\n",
" [ 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 0 7 0 0 2 0 0 1 0 0 38 0 4 3 1 0 1 0]\n",
" [ 0 1 3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 3 1 8 1 0 2 0 0 1 0 1 4 3 0 7 0 1 0]\n",
" [ 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 3 1 3 1 0 1 0 0 0 0 1 0 0 69 5 0 0 0 0]\n",
" [ 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 16 0 6 2 0 0 0 0 0 0 0 1 0 5 84 0 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 7 0 4 0 1 1 0 0 1 0 3 0 3 1 45 0 0 0]\n",
" [ 2 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 1 0 2 0 0 0 0 0 1 0 0 2 2 0 1 2 0]\n",
" [ 0 12 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 4 0 3 0 0 1 0 0 0 0 0 1 0 3 7 0 0 19 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 8 0 3 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0]]\n",
"val Loss: 1.5929 Acc: 0.5823\n",
"Confusion Matrix:\n",
"[[ 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 10 2 2 0 0 4 0 0 0 0 0 6 0 1 0 0 0]\n",
" [ 3 48 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 3 14 2 2 3 0 3 0 0 0 0 0 0 0 2 3 0 0 0 0]\n",
" [ 0 1 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 13 0 18 0 0 3 0 0 0 0 0 0 0 2 3 0 2 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 1 0 1 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 1 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0]\n",
" [ 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 2 0 0 0 0 5 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 11 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 5 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 3 2 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 2 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 2 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 77 4 0 9 0 0 0 0 2 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 108 2 5 2 0 3 0 0 0 0 0 1 0 1 6 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 61 0 13 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 89 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 3 1 91 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 1 0 0 0 27 0 0 1 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 2 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 3 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 2 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 7 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 3 0 1 1 0 4 1 0 6 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 6 1 0 0 0 0 0 0 0 17 0 5 3 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 2 1 0 4 0 2 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 43 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 3 0 11 53 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 2 0 7 0 0 0 0 0 0 0 0 0 1 4 24 0 0 1]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 2 0]\n",
" [ 2 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 14 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1]]\n",
"\n",
"Epoch 29/29\n",
"----------\n",
"train Loss: 1.8324 Acc: 0.5187\n",
"Confusion Matrix:\n",
"[[ 43 4 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 6 1 22 2 4 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 2 69 0 0 2 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 7 24 1 11 0 1 7 0 1 0 0 1 1 0 3 8 1 0 3 0]\n",
" [ 1 0 50 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 21 2 17 0 0 4 0 0 2 0 0 0 0 1 5 0 0 0]\n",
" [ 1 0 0 29 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 1 4 0 0 49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 7 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [ 0 0 0 0 1 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 2 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 7 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 8 0 2 0 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 2 3 0 0 0 0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 9 0 1 3 0 0 0 0 0 0 0 1 1 0 3 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 7 1 6 0 0 2 0 0 0 0 0 0 0 3 5 0 0 0]\n",
" [ 2 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 4 0 3 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0]\n",
" [ 1 1 0 0 1 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 8 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 1 0 1 0 8 0 0 0 0 0 0 0 0 2 0 0 1 0]\n",
" [ 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 0 5 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 10 2 0 0 0 0 0 0 0 9 0 0 5 0 1 0 0 2 0 0 1 0 0 0 0 0 0 0 0]\n",
" [ 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 2 19 0 2 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 23 0 5 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 1 0 0 2 0 2 0 0 0 0 0 0 0 0 1 0 5 3 0 0 2 0]\n",
" [ 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 4 0 1 1 0 0 0 0 0 0 0 0 1 1 8 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 2 3 0 0 0]\n",
" [ 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 1 0 0 0 0 0 0 0 0 3 1 2 0 0 0]\n",
" [ 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 4 0 2 3 0 0 0 0 0 0 0 2 0 2 7 1 0 0 0]\n",
" [ 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 3 0 4 0 0 0 0 0 0 0 0 0 2 3 6 0 0 0]\n",
" [ 4 3 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 125 12 2 10 1 1 1 0 2 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 1 18 0 1 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 18 147 4 6 4 1 10 0 0 0 0 1 2 0 1 10 2 0 0 0]\n",
" [ 0 0 7 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 7 84 1 26 0 0 3 0 0 2 0 1 0 1 2 6 0 0 0]\n",
" [ 4 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 1 0 133 1 0 0 0 2 0 0 0 1 0 3 0 0 0 0 0]\n",
" [ 2 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 1 140 0 1 0 0 0 1 0 0 0 2 3 4 0 0 0]\n",
" [ 3 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 5 0 1 0 47 7 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 5 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 8 0 1 0 2 114 0 0 0 0 0 0 0 0 1 1 0 0 0]\n",
" [ 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 14 0 2 0 0 33 0 0 1 0 1 0 0 0 1 0 0 0]\n",
" [ 9 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 13 5 0 9 0 1 0 0 14 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 17 0 0 0 0 1 0 0 11 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 10 1 14 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0]\n",
" [ 1 3 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 1 5 0 1 1 0 0 0 0 9 2 0 4 0 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 12 0 2 0 0 5 0 0 0 0 0 34 0 3 3 0 0 1 0]\n",
" [ 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 8 6 3 3 0 2 1 0 0 1 0 0 2 2 1 4 0 0 0]\n",
" [ 4 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 4 0 4 2 0 0 0 0 0 0 0 0 0 65 5 2 0 0 0]\n",
" [ 2 5 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 3 11 0 2 2 0 3 0 0 0 0 0 0 0 11 79 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 10 3 4 0 1 0 0 0 0 0 1 1 0 4 41 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 2 2 0 3 0 0 0 0 0 0 0 0 0 0 1 3 1 1 2 0]\n",
" [ 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 1 8 0 1 0 0 0 0 0 0 0 0 2 0 1 10 0 0 18 0]\n",
" [ 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 4 1 5 0 0 0 0 0 0 0 1 1 1 0 4 0 0 0]]\n",
"val Loss: 1.5975 Acc: 0.5865\n",
"Confusion Matrix:\n",
"[[ 33 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 9 1 2 0 0 1 0 0 0 0 0 5 0 1 0 0 0]\n",
" [ 2 53 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 4 11 2 2 3 0 3 0 0 0 0 0 0 0 1 3 0 0 0 0]\n",
" [ 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 16 0 15 0 0 5 0 0 0 0 0 0 0 0 5 0 1 0]\n",
" [ 1 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 3 0 1 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 2 1 2 0 0 0 0 0 0 0 0 3 1 0 0 0 0]\n",
" [ 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0]\n",
" [ 0 0 4 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 3 0 0 2 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0]\n",
" [ 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 2 0 0 0 0 6 0 0 0 0 0 1 0 1 0 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 6 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 15 0 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 2 0 1 0 0 0 0 0 0 0 0 4 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0 0 1 0 3 1 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 3 1 0 0 0 0 1 2 0 0 0 0]\n",
" [ 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 9 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0]\n",
" [ 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 78 2 0 8 0 0 1 0 1 0 0 0 0 0 2 1 0 0 0 0]\n",
" [ 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 106 2 4 2 1 7 0 0 0 0 0 0 0 0 5 0 0 0 0]\n",
" [ 0 0 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 66 0 10 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0]\n",
" [ 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 1 92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 2 0 0 1 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 76 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 2 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 3 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 1 6 0 0 0 0 0 0 0 0 0 0]\n",
" [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 7 0 0 1 0 0 8 0 0 0 0 0 0 0 0 0]\n",
" [ 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 3 0 0 3 0 1 1 0 4 1 0 5 0 0 0 1 0]\n",
" [ 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 5 1 0 0 0 0 0 0 0 20 0 5 1 0 0 0 0]\n",
" [ 0 0 5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0 0 0 0 1 0 0 2 1 0 6 0 0 0]\n",
" [ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 3 0 0 0 0 0 0 0 0 0 0 40 5 0 0 0 0]\n",
" [ 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 0 1 0 0 0 0 1 4 0 10 50 0 0 1 0]\n",
" [ 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 3 0 7 0 0 0 0 0 0 0 0 0 0 2 25 0 1 0]\n",
" [ 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 0]\n",
" [ 1 8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 1 0 0 15 0]\n",
" [ 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0]]\n",
"\n",
"Training complete in 17m 33s\n",
"Best val Acc: 0.594255\n"
]
}
],
"source": [
"model_conv = train_model(model_conv, criterion, optimizer_conv,\n",
" exp_lr_scheduler, num_epochs=30)"
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "FrvMovYIufeS",
"outputId": "30e3a34a-e963-4c4c-becb-bcaf04f46d8e"
},
"execution_count": 53,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1688182355.8515925\n",
"Sat Jul 1 03:32:35 2023\n"
]
}
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"id": "qPq7-3EfW2lF",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 923
},
"outputId": "b5754188-6b34-46c6-a5b9-36f6e1082e70"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"visualize_model(model_conv)\n",
"\n",
"plt.ioff()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ZbmJT9frW2lF"
},
"source": [
"## Further Learning\n",
"\n",
"If you would like to learn more about the applications of transfer learning,\n",
"checkout our [Quantized Transfer Learning for Computer Vision Tutorial](https://pytorch.org/tutorials/intermediate/quantized_transfer_learning_tutorial.html).\n",
"\n",
"\n",
"\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.10"
},
"colab": {
"provenance": [],
"gpuType": "V100"
},
"accelerator": "GPU",
"gpuClass": "standard"
},
"nbformat": 4,
"nbformat_minor": 0
}