train_and_test/isic/resunet-isic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "arbitrary-fruit",
   "metadata": {},
   "source": [
    "# Residual UNet - ISIC2018\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69f8c2e9",
   "metadata": {},
   "source": [
    "## Import packages & functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "embedded-draft",
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function, division\n",
    "\n",
    "\n",
    "import os\n",
    "import sys\n",
    "sys.path.append('../..')\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "\n",
    "import copy\n",
    "import json\n",
    "import importlib\n",
    "import glob\n",
    "import pandas as pd\n",
    "from skimage import io, transform\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.image import imread\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "import torchmetrics\n",
    "from torch.optim import Adam, SGD\n",
    "from losses import DiceLoss, DiceLossWithLogtis\n",
    "from torch.nn import BCELoss, CrossEntropyLoss\n",
    "\n",
    "from utils import (\n",
    "    show_sbs,\n",
    "    load_config,\n",
    "    _print,\n",
    ")\n",
    "\n",
    "# Ignore warnings\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# plt.ion()   # interactive mode"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9723d261",
   "metadata": {},
   "source": [
    "## Set the seed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "champion-ambassador",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.manual_seed(0)\n",
    "np.random.seed(0)\n",
    "torch.cuda.manual_seed(0)\n",
    "import random\n",
    "random.seed(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f583e01",
   "metadata": {},
   "source": [
    "## Load the config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "flying-belize",
   "metadata": {},
   "outputs": [],
   "source": [
    "CONFIG_NAME = \"isic/isic2018_resunet.yaml\"\n",
    "CONFIG_FILE_PATH = os.path.join(\"./configs\", CONFIG_NAME)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "studied-movie",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0m\u001b[4m\u001b[96mConfig:\u001b[0m\n",
      "{\n",
      "  \"run\": {\n",
      "    \"mode\": \"train\",\n",
      "    \"device\": \"gpu\"\n",
      "  },\n",
      "  \"transforms\": \"none\",\n",
      "  \"dataset\": {\n",
      "    \"class_name\": \"ISIC2018Dataset\",\n",
      "    \"input_size\": 224,\n",
      "    \"training\": {\n",
      "      \"params\": {\n",
      "        \"data_dir\": \"/path/to/datasets/ISIC2018\"\n",
      "      }\n",
      "    },\n",
      "    \"validation\": {\n",
      "      \"params\": {\n",
      "        \"data_dir\": \"/path/to/datasets/ISIC2018\"\n",
      "      }\n",
      "    },\n",
      "    \"number_classes\": 2\n",
      "  },\n",
      "  \"data_loader\": {\n",
      "    \"train\": {\n",
      "      \"batch_size\": 16,\n",
      "      \"shuffle\": true,\n",
      "      \"num_workers\": 8,\n",
      "      \"pin_memory\": true\n",
      "    },\n",
      "    \"validation\": {\n",
      "      \"batch_size\": 16,\n",
      "      \"shuffle\": false,\n",
      "      \"num_workers\": 8,\n",
      "      \"pin_memory\": true\n",
      "    },\n",
      "    \"test\": {\n",
      "      \"batch_size\": 16,\n",
      "      \"shuffle\": false,\n",
      "      \"num_workers\": 4,\n",
      "      \"pin_memory\": false\n",
      "    }\n",
      "  },\n",
      "  \"training\": {\n",
      "    \"optimizer\": {\n",
      "      \"name\": \"Adam\",\n",
      "      \"params\": {\n",
      "        \"lr\": 0.0001\n",
      "      }\n",
      "    },\n",
      "    \"criterion\": {\n",
      "      \"name\": \"DiceLoss\",\n",
      "      \"params\": {}\n",
      "    },\n",
      "    \"scheduler\": {\n",
      "      \"factor\": 0.5,\n",
      "      \"patience\": 10\n",
      "    },\n",
      "    \"epochs\": 100\n",
      "  },\n",
      "  \"model\": {\n",
      "    \"save_dir\": \"../saved_models/isic2018_resunet\",\n",
      "    \"load_weights\": false,\n",
      "    \"name\": \"ResUnet\",\n",
      "    \"params\": {\n",
      "      \"in_ch\": 3,\n",
      "      \"out_ch\": 2\n",
      "    }\n",
      "  }\n",
      "}\n",
      "~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-~-~- \n",
      "\n"
     ]
    }
   ],
   "source": [
    "config = load_config(CONFIG_FILE_PATH)\n",
    "_print(\"Config:\", \"info_underline\")\n",
    "print(json.dumps(config, indent=2))\n",
    "print(20*\"~-\", \"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "yellow-gender",
   "metadata": {},
   "source": [
    "## Dataset and Dataloader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "external-stability",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datasets.isic import ISIC2018DatasetFast\n",
    "from torch.utils.data import DataLoader, Subset\n",
    "from torchvision import transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "induced-authority",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Length of trainig_dataset:\t1815\n",
      "Length of validation_dataset:\t259\n",
      "Length of test_dataset:\t\t520\n",
      "\n",
      " Training\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ------------------- params --------------------\n",
    "INPUT_SIZE = config['dataset']['input_size']\n",
    "# <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
    "\n",
    "\n",
    "# ----------------- dataset --------------------\n",
    "# preparing training dataset\n",
    "tr_dataset = ISIC2018DatasetFast(mode=\"tr\", one_hot=True)\n",
    "vl_dataset = ISIC2018DatasetFast(mode=\"vl\", one_hot=True)\n",
    "te_dataset = ISIC2018DatasetFast(mode=\"te\", one_hot=True)\n",
    "\n",
    "# We consider 1815 samples for training, 259 samples for validation and 520 samples for testing\n",
    "# !cat ~/deeplearning/skin/Prepare_ISIC2018.py\n",
    "\n",
    "print(f\"Length of trainig_dataset:\\t{len(tr_dataset)}\")\n",
    "print(f\"Length of validation_dataset:\\t{len(vl_dataset)}\")\n",
    "print(f\"Length of test_dataset:\\t\\t{len(te_dataset)}\")\n",
    "\n",
    "\n",
    "# prepare train dataloader\n",
    "tr_dataloader = DataLoader(tr_dataset, **config['data_loader']['train'])\n",
    "\n",
    "# prepare validation dataloader\n",
    "vl_dataloader = DataLoader(vl_dataset, **config['data_loader']['validation'])\n",
    "\n",
    "# prepare test dataloader\n",
    "te_dataloader = DataLoader(te_dataset, **config['data_loader']['test'])\n",
    "\n",
    "# -------------- test -----------------\n",
    "# test and visualize the input data\n",
    "for sample in tr_dataloader:\n",
    "    img = sample['image']\n",
    "    msk = sample['mask']\n",
    "    print(\"\\n Training\")\n",
    "    show_sbs(img[0], msk[0,1])\n",
    "    break\n",
    "    \n",
    "for sample in vl_dataloader:\n",
    "    img = sample['image']\n",
    "    msk = sample['mask']\n",
    "    print(\"Validation\")\n",
    "    show_sbs(img[0], msk[0,1])\n",
    "    break\n",
    "    \n",
    "for sample in te_dataloader:\n",
    "    img = sample['image']\n",
    "    msk = sample['mask']\n",
    "    print(\"Test\")\n",
    "    show_sbs(img[0], msk[0,1])\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adapted-perspective",
   "metadata": {},
   "source": [
    "### Device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "internal-delay",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Torch device: cuda\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "print(f\"Torch device: {device}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "narrow-stable",
   "metadata": {},
   "source": [
    "## Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "difficult-boxing",
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics = torchmetrics.MetricCollection(\n",
    "    [\n",
    "        torchmetrics.F1Score(),\n",
    "        torchmetrics.Accuracy(),\n",
    "        torchmetrics.Dice(),\n",
    "        torchmetrics.Precision(),\n",
    "        torchmetrics.Specificity(),\n",
    "        torchmetrics.Recall(),\n",
    "        # IoU\n",
    "        torchmetrics.JaccardIndex(2)\n",
    "    ],\n",
    "    prefix='train_metrics/'\n",
    ")\n",
    "\n",
    "# train_metrics\n",
    "train_metrics = metrics.clone(prefix='train_metrics/').to(device)\n",
    "\n",
    "# valid_metrics\n",
    "valid_metrics = metrics.clone(prefix='valid_metrics/').to(device)\n",
    "\n",
    "# test_metrics\n",
    "test_metrics = metrics.clone(prefix='test_metrics/').to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "passive-optimization",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_serializeable_metrics(computed_metrics):\n",
    "    res = {}\n",
    "    for k, v in computed_metrics.items():\n",
    "        res[k] = float(v.cpu().detach().numpy())\n",
    "    return res"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "protected-anime",
   "metadata": {},
   "source": [
    "## Define validate function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "consistent-tissue",
   "metadata": {},
   "outputs": [],
   "source": [
    "def validate(model, criterion, vl_dataloader):\n",
    "    model.eval()\n",
    "    with torch.no_grad():\n",
    "        \n",
    "        evaluator = valid_metrics.clone().to(device)\n",
    "        \n",
    "        losses = []\n",
    "        cnt = 0.\n",
    "        for batch, batch_data in enumerate(vl_dataloader):\n",
    "            imgs = batch_data['image']\n",
    "            msks = batch_data['mask']\n",
    "            \n",
    "            cnt += msks.shape[0]\n",
    "            \n",
    "            imgs = imgs.to(device)\n",
    "            msks = msks.to(device)\n",
    "            \n",
    "            preds = model(imgs)\n",
    "            loss = criterion(preds, msks)\n",
    "            losses.append(loss.item())\n",
    "            \n",
    "            \n",
    "            preds_ = torch.argmax(preds, 1, keepdim=False).float()\n",
    "            msks_ = torch.argmax(msks, 1, keepdim=False)\n",
    "            evaluator.update(preds_, msks_)\n",
    "        \n",
    "#             _cml = f\"curr_mean-loss:{np.sum(losses)/cnt:0.5f}\"\n",
    "#             _bl = f\"batch-loss:{losses[-1]/msks.shape[0]:0.5f}\"\n",
    "#             iterator.set_description(f\"Validation) batch:{batch+1:04d} -> {_cml}, {_bl}\")\n",
    "        \n",
    "        # print the final results\n",
    "        loss = np.sum(losses)/cnt\n",
    "        metrics = evaluator.compute()\n",
    "    \n",
    "    return evaluator, loss"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sacred-repeat",
   "metadata": {},
   "source": [
    "## Define train function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "flexible-crest",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(\n",
    "    model, \n",
    "    device, \n",
    "    tr_dataloader,\n",
    "    vl_dataloader,\n",
    "    config,\n",
    "    \n",
    "    criterion,\n",
    "    optimizer,\n",
    "    scheduler,\n",
    "    \n",
    "    save_dir='./',\n",
    "    save_file_id=None,\n",
    "):\n",
    "    \n",
    "    EPOCHS = tr_prms['epochs']\n",
    "    \n",
    "    torch.cuda.empty_cache()\n",
    "    model = model.to(device)\n",
    "\n",
    "    evaluator = train_metrics.clone().to(device)\n",
    "    \n",
    "    epochs_info = []\n",
    "    best_model = None\n",
    "    best_result = {}\n",
    "    best_vl_loss = np.Inf\n",
    "    for epoch in range(EPOCHS):\n",
    "        model.train()\n",
    "        \n",
    "        evaluator.reset()\n",
    "        tr_iterator = tqdm(enumerate(tr_dataloader))\n",
    "        tr_losses = []\n",
    "        cnt = 0\n",
    "        for batch, batch_data in tr_iterator:\n",
    "            imgs = batch_data['image']\n",
    "            msks = batch_data['mask']\n",
    "            \n",
    "            imgs = imgs.to(device)\n",
    "            msks = msks.to(device)\n",
    "            \n",
    "            optimizer.zero_grad()\n",
    "            preds = model(imgs)\n",
    "            loss = criterion(preds, msks)\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "            \n",
    "            # evaluate by metrics\n",
    "            preds_ = torch.argmax(preds, 1, keepdim=False).float()\n",
    "            msks_ = torch.argmax(msks, 1, keepdim=False)\n",
    "            evaluator.update(preds_, msks_)\n",
    "            \n",
    "            cnt += imgs.shape[0]\n",
    "            tr_losses.append(loss.item())\n",
    "            \n",
    "            # write details for each training batch\n",
    "            _cml = f\"curr_mean-loss:{np.sum(tr_losses)/cnt:0.5f}\"\n",
    "            _bl = f\"mean_batch-loss:{tr_losses[-1]/imgs.shape[0]:0.5f}\"\n",
    "            tr_iterator.set_description(f\"Training) ep:{epoch:03d}, batch:{batch+1:04d} -> {_cml}, {_bl}\")\n",
    "            \n",
    "        tr_loss = np.sum(tr_losses)/cnt\n",
    "        \n",
    "        # validate model\n",
    "        vl_metrics, vl_loss = validate(model, criterion, vl_dataloader)\n",
    "        if vl_loss < best_vl_loss:\n",
    "            # find a better model\n",
    "            best_model = model\n",
    "            best_vl_loss = vl_loss\n",
    "            best_result = {\n",
    "                'tr_loss': tr_loss,\n",
    "                'vl_loss': vl_loss,\n",
    "                'tr_metrics': make_serializeable_metrics(evaluator.compute()),\n",
    "                'vl_metrics': make_serializeable_metrics(vl_metrics.compute())\n",
    "            }\n",
    "        \n",
    "        # write the final results\n",
    "        epoch_info = {\n",
    "            'tr_loss': tr_loss,\n",
    "            'vl_loss': vl_loss,\n",
    "            'tr_metrics': make_serializeable_metrics(evaluator.compute()),\n",
    "            'vl_metrics': make_serializeable_metrics(vl_metrics.compute())\n",
    "        }\n",
    "        epochs_info.append(epoch_info)\n",
    "#         epoch_tqdm.set_description(f\"Epoch:{epoch+1}/{EPOCHS} -> tr_loss:{tr_loss}, vl_loss:{vl_loss}\")\n",
    "        evaluator.reset()\n",
    "    \n",
    "        scheduler.step(vl_loss)\n",
    "  \n",
    "    # save final results\n",
    "    res = {\n",
    "        'id': save_file_id,\n",
    "        'config': config,\n",
    "        'epochs_info': epochs_info,\n",
    "        'best_result': best_result\n",
    "    }\n",
    "    fn = f\"{save_file_id+'_' if save_file_id else ''}result.json\"\n",
    "    fp = os.path.join(config['model']['save_dir'],fn)\n",
    "    with open(fp, \"w\") as write_file:\n",
    "        json.dump(res, write_file, indent=4)\n",
    "\n",
    "    # save model's state_dict\n",
    "    fn = \"last_model_state_dict.pt\"\n",
    "    fp = os.path.join(config['model']['save_dir'],fn)\n",
    "    torch.save(model.state_dict(), fp)\n",
    "    \n",
    "    # save the best model's state_dict\n",
    "    fn = \"best_model_state_dict.pt\"\n",
    "    fp = os.path.join(config['model']['save_dir'], fn)\n",
    "    torch.save(best_model.state_dict(), fp)\n",
    "    \n",
    "    return best_model, model, res"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "shared-lobby",
   "metadata": {},
   "source": [
    "## Define test function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "mediterranean-driving",
   "metadata": {},
   "outputs": [],
   "source": [
    "def test(model, te_dataloader):\n",
    "    model.eval()\n",
    "    with torch.no_grad():\n",
    "        evaluator = test_metrics.clone().to(device)            \n",
    "        for batch_data in tqdm(te_dataloader):\n",
    "            imgs = batch_data['image']\n",
    "            msks = batch_data['mask']\n",
    "            \n",
    "            imgs = imgs.to(device)\n",
    "            msks = msks.to(device)\n",
    "            \n",
    "            preds = model(imgs)\n",
    "            \n",
    "            # evaluate by metrics\n",
    "            preds_ = torch.argmax(preds, 1, keepdim=False).float()\n",
    "            msks_ = torch.argmax(msks, 1, keepdim=False)\n",
    "            evaluator.update(preds_, msks_)\n",
    "            \n",
    "    return evaluator"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0bdff5a",
   "metadata": {},
   "source": [
    "## Load and prepare model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "chronic-gregory",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of parameters: 13043074\n"
     ]
    }
   ],
   "source": [
    "from models._resunet.res_unet import ResUnet as Net\n",
    "\n",
    "\n",
    "model = Net(**config['model']['params'])\n",
    "torch.cuda.empty_cache()\n",
    "model = model.to(device)\n",
    "print(\"Number of parameters:\", sum(p.numel() for p in model.parameters() if p.requires_grad))\n",
    "\n",
    "os.makedirs(config['model']['save_dir'], exist_ok=True)\n",
    "model_path = f\"{config['model']['save_dir']}/model_state_dict.pt\"\n",
    "\n",
    "if config['model']['load_weights']:\n",
    "    model.load_state_dict(torch.load(model_path))\n",
    "    print(\"Loaded pre-trained weights...\")\n",
    "    \n",
    "    \n",
    "# criterion_dice = DiceLoss()\n",
    "criterion_dice = DiceLossWithLogtis()\n",
    "# criterion_ce  = BCELoss()\n",
    "criterion_ce  = CrossEntropyLoss()\n",
    "\n",
    "\n",
    "def criterion(preds, masks):\n",
    "    c_dice = criterion_dice(preds, masks)\n",
    "    c_ce = criterion_ce(preds, masks)\n",
    "    return 0.5*c_dice + 0.5*c_ce\n",
    "\n",
    "tr_prms = config['training']\n",
    "optimizer = globals()[tr_prms['optimizer']['name']](model.parameters(), **tr_prms['optimizer']['params'])\n",
    "scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer, 'min', **tr_prms['scheduler'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "294b3c95",
   "metadata": {},
   "source": [
    "## Start traning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "nutritional-diagram",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Training) ep:000, batch:0114 -> curr_mean-loss:0.01766, mean_batch-loss:0.02281: : 114it [00:32,  3.47it/s]\n",
      "Training) ep:001, batch:0114 -> curr_mean-loss:0.01351, mean_batch-loss:0.03505: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:002, batch:0114 -> curr_mean-loss:0.01135, mean_batch-loss:0.01732: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:003, batch:0114 -> curr_mean-loss:0.01134, mean_batch-loss:0.06120: : 114it [00:30,  3.73it/s]\n",
      "Training) ep:004, batch:0114 -> curr_mean-loss:0.01080, mean_batch-loss:0.01871: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:005, batch:0114 -> curr_mean-loss:0.01041, mean_batch-loss:0.02315: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:006, batch:0114 -> curr_mean-loss:0.00964, mean_batch-loss:0.01402: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:007, batch:0114 -> curr_mean-loss:0.01037, mean_batch-loss:0.06587: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:008, batch:0114 -> curr_mean-loss:0.00967, mean_batch-loss:0.01373: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:009, batch:0114 -> curr_mean-loss:0.00937, mean_batch-loss:0.01912: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:010, batch:0114 -> curr_mean-loss:0.00937, mean_batch-loss:0.00990: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:011, batch:0114 -> curr_mean-loss:0.00945, mean_batch-loss:0.04110: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:012, batch:0114 -> curr_mean-loss:0.00893, mean_batch-loss:0.01391: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:013, batch:0114 -> curr_mean-loss:0.00898, mean_batch-loss:0.01867: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:014, batch:0114 -> curr_mean-loss:0.00853, mean_batch-loss:0.02258: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:015, batch:0114 -> curr_mean-loss:0.00856, mean_batch-loss:0.01940: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:016, batch:0114 -> curr_mean-loss:0.00843, mean_batch-loss:0.01601: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:017, batch:0114 -> curr_mean-loss:0.00827, mean_batch-loss:0.01731: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:018, batch:0114 -> curr_mean-loss:0.00827, mean_batch-loss:0.02304: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:019, batch:0114 -> curr_mean-loss:0.00813, mean_batch-loss:0.01315: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:020, batch:0114 -> curr_mean-loss:0.00783, mean_batch-loss:0.04876: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:021, batch:0114 -> curr_mean-loss:0.00780, mean_batch-loss:0.03522: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:022, batch:0114 -> curr_mean-loss:0.00748, mean_batch-loss:0.00779: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:023, batch:0114 -> curr_mean-loss:0.00755, mean_batch-loss:0.01995: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:024, batch:0114 -> curr_mean-loss:0.00708, mean_batch-loss:0.01484: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:025, batch:0114 -> curr_mean-loss:0.00707, mean_batch-loss:0.01280: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:026, batch:0114 -> curr_mean-loss:0.00647, mean_batch-loss:0.01547: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:027, batch:0114 -> curr_mean-loss:0.00632, mean_batch-loss:0.01854: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:028, batch:0114 -> curr_mean-loss:0.00510, mean_batch-loss:0.02799: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:029, batch:0114 -> curr_mean-loss:0.00455, mean_batch-loss:0.02298: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:030, batch:0114 -> curr_mean-loss:0.00436, mean_batch-loss:0.00781: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:031, batch:0114 -> curr_mean-loss:0.00404, mean_batch-loss:0.00501: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:032, batch:0114 -> curr_mean-loss:0.00376, mean_batch-loss:0.01026: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:033, batch:0114 -> curr_mean-loss:0.00353, mean_batch-loss:0.01276: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:034, batch:0114 -> curr_mean-loss:0.00334, mean_batch-loss:0.00727: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:035, batch:0114 -> curr_mean-loss:0.00315, mean_batch-loss:0.00879: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:036, batch:0114 -> curr_mean-loss:0.00312, mean_batch-loss:0.00353: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:037, batch:0114 -> curr_mean-loss:0.00288, mean_batch-loss:0.00876: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:038, batch:0114 -> curr_mean-loss:0.00269, mean_batch-loss:0.01045: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:039, batch:0114 -> curr_mean-loss:0.00245, mean_batch-loss:0.01134: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:040, batch:0114 -> curr_mean-loss:0.00226, mean_batch-loss:0.00598: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:041, batch:0114 -> curr_mean-loss:0.00222, mean_batch-loss:0.00683: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:042, batch:0114 -> curr_mean-loss:0.00217, mean_batch-loss:0.00516: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:043, batch:0114 -> curr_mean-loss:0.00209, mean_batch-loss:0.00497: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:044, batch:0114 -> curr_mean-loss:0.00203, mean_batch-loss:0.00582: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:045, batch:0114 -> curr_mean-loss:0.00195, mean_batch-loss:0.00441: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:046, batch:0114 -> curr_mean-loss:0.00194, mean_batch-loss:0.00570: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:047, batch:0114 -> curr_mean-loss:0.00185, mean_batch-loss:0.00451: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:048, batch:0114 -> curr_mean-loss:0.00186, mean_batch-loss:0.00585: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:049, batch:0114 -> curr_mean-loss:0.00177, mean_batch-loss:0.00588: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:050, batch:0114 -> curr_mean-loss:0.00167, mean_batch-loss:0.00445: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:051, batch:0114 -> curr_mean-loss:0.00164, mean_batch-loss:0.00542: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:052, batch:0114 -> curr_mean-loss:0.00161, mean_batch-loss:0.00432: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:053, batch:0114 -> curr_mean-loss:0.00155, mean_batch-loss:0.00424: : 114it [00:30,  3.72it/s]\n",
      "Training) ep:054, batch:0114 -> curr_mean-loss:0.00154, mean_batch-loss:0.00681: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:055, batch:0114 -> curr_mean-loss:0.00150, mean_batch-loss:0.00339: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:056, batch:0114 -> curr_mean-loss:0.00148, mean_batch-loss:0.00485: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:057, batch:0114 -> curr_mean-loss:0.00150, mean_batch-loss:0.00815: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:058, batch:0114 -> curr_mean-loss:0.00145, mean_batch-loss:0.00520: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:059, batch:0114 -> curr_mean-loss:0.00144, mean_batch-loss:0.00403: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:060, batch:0114 -> curr_mean-loss:0.00142, mean_batch-loss:0.00357: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:061, batch:0114 -> curr_mean-loss:0.00135, mean_batch-loss:0.00468: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:062, batch:0114 -> curr_mean-loss:0.00133, mean_batch-loss:0.00265: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:063, batch:0114 -> curr_mean-loss:0.00132, mean_batch-loss:0.00605: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:064, batch:0114 -> curr_mean-loss:0.00129, mean_batch-loss:0.00368: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:065, batch:0114 -> curr_mean-loss:0.00132, mean_batch-loss:0.00366: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:066, batch:0114 -> curr_mean-loss:0.00127, mean_batch-loss:0.00356: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:067, batch:0114 -> curr_mean-loss:0.00126, mean_batch-loss:0.00362: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:068, batch:0114 -> curr_mean-loss:0.00126, mean_batch-loss:0.00343: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:069, batch:0114 -> curr_mean-loss:0.00123, mean_batch-loss:0.00268: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:070, batch:0114 -> curr_mean-loss:0.00126, mean_batch-loss:0.00261: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:071, batch:0114 -> curr_mean-loss:0.00123, mean_batch-loss:0.00330: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:072, batch:0114 -> curr_mean-loss:0.00122, mean_batch-loss:0.00422: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:073, batch:0114 -> curr_mean-loss:0.00120, mean_batch-loss:0.00234: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:074, batch:0114 -> curr_mean-loss:0.00119, mean_batch-loss:0.00288: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:075, batch:0114 -> curr_mean-loss:0.00118, mean_batch-loss:0.00270: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:076, batch:0114 -> curr_mean-loss:0.00118, mean_batch-loss:0.00258: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:077, batch:0114 -> curr_mean-loss:0.00116, mean_batch-loss:0.00225: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:078, batch:0114 -> curr_mean-loss:0.00129, mean_batch-loss:0.03023: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:079, batch:0114 -> curr_mean-loss:0.00120, mean_batch-loss:0.00488: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:080, batch:0114 -> curr_mean-loss:0.00116, mean_batch-loss:0.00252: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:081, batch:0114 -> curr_mean-loss:0.00115, mean_batch-loss:0.00333: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:082, batch:0114 -> curr_mean-loss:0.00116, mean_batch-loss:0.00302: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:083, batch:0114 -> curr_mean-loss:0.00114, mean_batch-loss:0.00305: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:084, batch:0114 -> curr_mean-loss:0.00114, mean_batch-loss:0.00323: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:085, batch:0114 -> curr_mean-loss:0.00113, mean_batch-loss:0.00257: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:086, batch:0114 -> curr_mean-loss:0.00113, mean_batch-loss:0.00249: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:087, batch:0114 -> curr_mean-loss:0.00114, mean_batch-loss:0.00284: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:088, batch:0114 -> curr_mean-loss:0.00112, mean_batch-loss:0.00310: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:089, batch:0114 -> curr_mean-loss:0.00112, mean_batch-loss:0.00278: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:090, batch:0114 -> curr_mean-loss:0.00117, mean_batch-loss:0.00486: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:091, batch:0114 -> curr_mean-loss:0.00113, mean_batch-loss:0.00284: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:092, batch:0114 -> curr_mean-loss:0.00112, mean_batch-loss:0.00277: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:093, batch:0114 -> curr_mean-loss:0.00111, mean_batch-loss:0.00203: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:094, batch:0114 -> curr_mean-loss:0.00112, mean_batch-loss:0.00264: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:095, batch:0114 -> curr_mean-loss:0.00110, mean_batch-loss:0.00242: : 114it [00:30,  3.69it/s]\n",
      "Training) ep:096, batch:0114 -> curr_mean-loss:0.00109, mean_batch-loss:0.00241: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:097, batch:0114 -> curr_mean-loss:0.00108, mean_batch-loss:0.00285: : 114it [00:30,  3.71it/s]\n",
      "Training) ep:098, batch:0114 -> curr_mean-loss:0.00110, mean_batch-loss:0.00239: : 114it [00:30,  3.70it/s]\n",
      "Training) ep:099, batch:0114 -> curr_mean-loss:0.00110, mean_batch-loss:0.00260: : 114it [00:30,  3.71it/s]\n"
     ]
    }
   ],
   "source": [
    "best_model, model, res = train(\n",
    "    model, \n",
    "    device, \n",
    "    tr_dataloader,\n",
    "    vl_dataloader,\n",
    "    config,\n",
    "    \n",
    "    criterion,\n",
    "    optimizer,\n",
    "    scheduler,\n",
    "\n",
    "    save_dir = config['model']['save_dir'],\n",
    "    save_file_id = None,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "dried-ordering",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 33/33 [00:03<00:00,  9.88it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'test_metrics/F1Score': tensor(0.8529, device='cuda:0'),\n",
       " 'test_metrics/Accuracy': tensor(0.9396, device='cuda:0'),\n",
       " 'test_metrics/Dice': tensor(0.8529, device='cuda:0'),\n",
       " 'test_metrics/Precision': tensor(0.8765, device='cuda:0'),\n",
       " 'test_metrics/Specificity': tensor(0.9688, device='cuda:0'),\n",
       " 'test_metrics/Recall': tensor(0.8306, device='cuda:0'),\n",
       " 'test_metrics/JaccardIndex': tensor(0.8352, device='cuda:0')}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "te_metrics = test(best_model, te_dataloader)\n",
    "te_metrics.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "related-player",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'../saved_models/isic2018_resunet'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f\"{config['model']['save_dir']}\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "third-stopping",
   "metadata": {},
   "source": [
    "# Test the best inferred model\n",
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "seventh-penetration",
   "metadata": {},
   "source": [
    "## Load the best model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "alert-prospect",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded best model weights...\n"
     ]
    }
   ],
   "source": [
    "best_model = Net(**config['model']['params'])\n",
    "torch.cuda.empty_cache()\n",
    "best_model = best_model.to(device)\n",
    "\n",
    "fn = \"best_model_state_dict.pt\"\n",
    "os.makedirs(config['model']['save_dir'], exist_ok=True)\n",
    "model_path = f\"{config['model']['save_dir']}/{fn}\"\n",
    "\n",
    "best_model.load_state_dict(torch.load(model_path))\n",
    "print(\"Loaded best model weights...\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "narrative-divide",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "rough-sheet",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 33/33 [00:03<00:00,  9.86it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'test_metrics/F1Score': tensor(0.8529, device='cuda:0'),\n",
       " 'test_metrics/Accuracy': tensor(0.9396, device='cuda:0'),\n",
       " 'test_metrics/Dice': tensor(0.8529, device='cuda:0'),\n",
       " 'test_metrics/Precision': tensor(0.8765, device='cuda:0'),\n",
       " 'test_metrics/Specificity': tensor(0.9688, device='cuda:0'),\n",
       " 'test_metrics/Recall': tensor(0.8306, device='cuda:0'),\n",
       " 'test_metrics/JaccardIndex': tensor(0.8352, device='cuda:0')}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "te_metrics = test(best_model, te_dataloader)\n",
    "te_metrics.compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "consistent-envelope",
   "metadata": {},
   "source": [
    "## Plot graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "sublime-academy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1600x300 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_file_path = f\"{config['model']['save_dir']}/result.json\"\n",
    "with open(result_file_path, 'r') as f:\n",
    "    results = json.loads(''.join(f.readlines()))\n",
    "epochs_info = results['epochs_info']\n",
    "\n",
    "tr_losses = [d['tr_loss'] for d in epochs_info]\n",
    "vl_losses = [d['vl_loss'] for d in epochs_info]\n",
    "tr_dice = [d['tr_metrics']['train_metrics/Dice'] for d in epochs_info]\n",
    "vl_dice = [d['vl_metrics']['valid_metrics/Dice'] for d in epochs_info]\n",
    "tr_js = [d['tr_metrics']['train_metrics/JaccardIndex'] for d in epochs_info]\n",
    "vl_js = [d['vl_metrics']['valid_metrics/JaccardIndex'] for d in epochs_info]\n",
    "tr_acc = [d['tr_metrics']['train_metrics/Accuracy'] for d in epochs_info]\n",
    "vl_acc = [d['vl_metrics']['valid_metrics/Accuracy'] for d in epochs_info]\n",
    "\n",
    "\n",
    "_, axs = plt.subplots(1, 4, figsize=[16,3])\n",
    "\n",
    "axs[0].set_title(\"Loss\")\n",
    "axs[0].plot(tr_losses, 'r-', label=\"train loss\")\n",
    "axs[0].plot(vl_losses, 'b-', label=\"validatiton loss\")\n",
    "axs[0].legend()\n",
    "\n",
    "axs[1].set_title(\"Dice score\")\n",
    "axs[1].plot(tr_dice, 'r-', label=\"train dice\")\n",
    "axs[1].plot(vl_dice, 'b-', label=\"validation dice\")\n",
    "axs[1].legend()\n",
    "\n",
    "axs[2].set_title(\"Jaccard Similarity\")\n",
    "axs[2].plot(tr_js, 'r-', label=\"train JaccardIndex\")\n",
    "axs[2].plot(vl_js, 'b-', label=\"validatiton JaccardIndex\")\n",
    "axs[2].legend()\n",
    "\n",
    "axs[3].set_title(\"Accuracy\")\n",
    "axs[3].plot(tr_acc, 'r-', label=\"train Accuracy\")\n",
    "axs[3].plot(vl_acc, 'b-', label=\"validation Accuracy\")\n",
    "axs[3].legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bigger-psychology",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'tr_loss': 0.01765826751706357,\n",
       "  'vl_loss': 0.01665387788794676,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.7042753100395203,\n",
       "   'train_metrics/Accuracy': 0.8778968453407288,\n",
       "   'train_metrics/Dice': 0.704275369644165,\n",
       "   'train_metrics/Precision': 0.7482556104660034,\n",
       "   'train_metrics/Specificity': 0.9373994469642639,\n",
       "   'train_metrics/Recall': 0.665178120136261,\n",
       "   'train_metrics/JaccardIndex': 0.7003304958343506},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.719133198261261,\n",
       "   'valid_metrics/Accuracy': 0.8942004442214966,\n",
       "   'valid_metrics/Dice': 0.719133198261261,\n",
       "   'valid_metrics/Precision': 0.7204065918922424,\n",
       "   'valid_metrics/Specificity': 0.9352084398269653,\n",
       "   'valid_metrics/Recall': 0.7178642749786377,\n",
       "   'valid_metrics/JaccardIndex': 0.7195340394973755}},\n",
       " {'tr_loss': 0.013512488013292476,\n",
       "  'vl_loss': 0.013367147346721193,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.7761762142181396,\n",
       "   'train_metrics/Accuracy': 0.906277060508728,\n",
       "   'train_metrics/Dice': 0.7761763334274292,\n",
       "   'train_metrics/Precision': 0.8119072318077087,\n",
       "   'train_metrics/Specificity': 0.9518215656280518,\n",
       "   'train_metrics/Recall': 0.7434576153755188,\n",
       "   'train_metrics/JaccardIndex': 0.7611567378044128},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.7787103652954102,\n",
       "   'valid_metrics/Accuracy': 0.9160117506980896,\n",
       "   'valid_metrics/Dice': 0.7787104249000549,\n",
       "   'valid_metrics/Precision': 0.7742539048194885,\n",
       "   'valid_metrics/Specificity': 0.9468936324119568,\n",
       "   'valid_metrics/Recall': 0.783218502998352,\n",
       "   'valid_metrics/JaccardIndex': 0.769530713558197}},\n",
       " {'tr_loss': 0.011348178637914421,\n",
       "  'vl_loss': 0.012314356144330676,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8124628663063049,\n",
       "   'train_metrics/Accuracy': 0.9215303063392639,\n",
       "   'train_metrics/Dice': 0.8124629259109497,\n",
       "   'train_metrics/Precision': 0.8505592942237854,\n",
       "   'train_metrics/Specificity': 0.9617818593978882,\n",
       "   'train_metrics/Recall': 0.7776328325271606,\n",
       "   'train_metrics/JaccardIndex': 0.7948094010353088},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.7834614515304565,\n",
       "   'valid_metrics/Accuracy': 0.922344446182251,\n",
       "   'valid_metrics/Dice': 0.7834614515304565,\n",
       "   'valid_metrics/Precision': 0.8266420960426331,\n",
       "   'valid_metrics/Specificity': 0.9636873602867126,\n",
       "   'valid_metrics/Recall': 0.7445680499076843,\n",
       "   'valid_metrics/JaccardIndex': 0.7768304347991943}},\n",
       " {'tr_loss': 0.011338339282133033,\n",
       "  'vl_loss': 0.012407981578447644,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.81388920545578,\n",
       "   'train_metrics/Accuracy': 0.921733558177948,\n",
       "   'train_metrics/Dice': 0.81388920545578,\n",
       "   'train_metrics/Precision': 0.8473925590515137,\n",
       "   'train_metrics/Specificity': 0.9605591297149658,\n",
       "   'train_metrics/Recall': 0.7829343676567078,\n",
       "   'train_metrics/JaccardIndex': 0.795878529548645},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.7895441055297852,\n",
       "   'valid_metrics/Accuracy': 0.9174826741218567,\n",
       "   'valid_metrics/Dice': 0.7895441651344299,\n",
       "   'valid_metrics/Precision': 0.7609502077102661,\n",
       "   'valid_metrics/Specificity': 0.9400665163993835,\n",
       "   'valid_metrics/Recall': 0.8203709721565247,\n",
       "   'valid_metrics/JaccardIndex': 0.7773206233978271}},\n",
       " {'tr_loss': 0.010800583200842224,\n",
       "  'vl_loss': 0.012212367821844388,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8221879005432129,\n",
       "   'train_metrics/Accuracy': 0.9254457354545593,\n",
       "   'train_metrics/Dice': 0.8221879601478577,\n",
       "   'train_metrics/Precision': 0.8588035106658936,\n",
       "   'train_metrics/Specificity': 0.9637340307235718,\n",
       "   'train_metrics/Recall': 0.7885670065879822,\n",
       "   'train_metrics/JaccardIndex': 0.8039913177490234},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.7818620204925537,\n",
       "   'valid_metrics/Accuracy': 0.9192895293235779,\n",
       "   'valid_metrics/Dice': 0.7818619608879089,\n",
       "   'valid_metrics/Precision': 0.7977257966995239,\n",
       "   'valid_metrics/Specificity': 0.9547944068908691,\n",
       "   'valid_metrics/Recall': 0.7666168212890625,\n",
       "   'valid_metrics/JaccardIndex': 0.773745596408844}},\n",
       " {'tr_loss': 0.010406789914307187,\n",
       "  'vl_loss': 0.011301130545415473,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.828485369682312,\n",
       "   'train_metrics/Accuracy': 0.9276861548423767,\n",
       "   'train_metrics/Dice': 0.828485369682312,\n",
       "   'train_metrics/Precision': 0.8601994514465332,\n",
       "   'train_metrics/Specificity': 0.963675320148468,\n",
       "   'train_metrics/Recall': 0.7990266680717468,\n",
       "   'train_metrics/JaccardIndex': 0.8097876906394958},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8047487139701843,\n",
       "   'valid_metrics/Accuracy': 0.9235866665840149,\n",
       "   'valid_metrics/Dice': 0.8047487139701843,\n",
       "   'valid_metrics/Precision': 0.7769477963447571,\n",
       "   'valid_metrics/Specificity': 0.9442780017852783,\n",
       "   'valid_metrics/Recall': 0.8346129655838013,\n",
       "   'valid_metrics/JaccardIndex': 0.7912964820861816}},\n",
       " {'tr_loss': 0.00964175595314378,\n",
       "  'vl_loss': 0.01472196408680507,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8416103720664978,\n",
       "   'train_metrics/Accuracy': 0.9331167936325073,\n",
       "   'train_metrics/Dice': 0.8416103720664978,\n",
       "   'train_metrics/Precision': 0.8723785877227783,\n",
       "   'train_metrics/Specificity': 0.9667335152626038,\n",
       "   'train_metrics/Recall': 0.8129385113716125,\n",
       "   'train_metrics/JaccardIndex': 0.8225992918014526},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.7592717409133911,\n",
       "   'valid_metrics/Accuracy': 0.9036929607391357,\n",
       "   'valid_metrics/Dice': 0.7592717409133911,\n",
       "   'valid_metrics/Precision': 0.7184863090515137,\n",
       "   'valid_metrics/Specificity': 0.9266524314880371,\n",
       "   'valid_metrics/Recall': 0.8049662709236145,\n",
       "   'valid_metrics/JaccardIndex': 0.7492015361785889}},\n",
       " {'tr_loss': 0.010367872063121848,\n",
       "  'vl_loss': 0.012064613632023566,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8308960199356079,\n",
       "   'train_metrics/Accuracy': 0.9289513826370239,\n",
       "   'train_metrics/Dice': 0.8308960795402527,\n",
       "   'train_metrics/Precision': 0.8659666776657104,\n",
       "   'train_metrics/Specificity': 0.9654262065887451,\n",
       "   'train_metrics/Recall': 0.7985554933547974,\n",
       "   'train_metrics/JaccardIndex': 0.8123196959495544},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.797613263130188,\n",
       "   'valid_metrics/Accuracy': 0.9253291487693787,\n",
       "   'valid_metrics/Dice': 0.7976133227348328,\n",
       "   'valid_metrics/Precision': 0.8162049055099487,\n",
       "   'valid_metrics/Specificity': 0.9591612219810486,\n",
       "   'valid_metrics/Recall': 0.7798498272895813,\n",
       "   'valid_metrics/JaccardIndex': 0.7879024744033813}},\n",
       " {'tr_loss': 0.009667291695421392,\n",
       "  'vl_loss': 0.011026994400733226,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8407322764396667,\n",
       "   'train_metrics/Accuracy': 0.9327031970024109,\n",
       "   'train_metrics/Dice': 0.8407322764396667,\n",
       "   'train_metrics/Precision': 0.8708751797676086,\n",
       "   'train_metrics/Specificity': 0.9662973284721375,\n",
       "   'train_metrics/Recall': 0.8126060962677002,\n",
       "   'train_metrics/JaccardIndex': 0.8216975927352905},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8127866983413696,\n",
       "   'valid_metrics/Accuracy': 0.9298883080482483,\n",
       "   'valid_metrics/Dice': 0.8127866983413696,\n",
       "   'valid_metrics/Precision': 0.8190277814865112,\n",
       "   'valid_metrics/Specificity': 0.9585504531860352,\n",
       "   'valid_metrics/Recall': 0.8066400289535522,\n",
       "   'valid_metrics/JaccardIndex': 0.8009597063064575}},\n",
       " {'tr_loss': 0.009371890341119004,\n",
       "  'vl_loss': 0.009833620868364356,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8446589708328247,\n",
       "   'train_metrics/Accuracy': 0.9348272085189819,\n",
       "   'train_metrics/Dice': 0.8446589112281799,\n",
       "   'train_metrics/Precision': 0.8816817998886108,\n",
       "   'train_metrics/Specificity': 0.9695709347724915,\n",
       "   'train_metrics/Recall': 0.8106200695037842,\n",
       "   'train_metrics/JaccardIndex': 0.8259416818618774},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8252504467964172,\n",
       "   'valid_metrics/Accuracy': 0.9368366003036499,\n",
       "   'valid_metrics/Dice': 0.8252504467964172,\n",
       "   'valid_metrics/Precision': 0.8632341027259827,\n",
       "   'valid_metrics/Specificity': 0.9708753228187561,\n",
       "   'valid_metrics/Recall': 0.7904685735702515,\n",
       "   'valid_metrics/JaccardIndex': 0.8141276836395264}},\n",
       " {'tr_loss': 0.009368966942647928,\n",
       "  'vl_loss': 0.010376269148813712,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.845063328742981,\n",
       "   'train_metrics/Accuracy': 0.9345038533210754,\n",
       "   'train_metrics/Dice': 0.845063328742981,\n",
       "   'train_metrics/Precision': 0.8749399185180664,\n",
       "   'train_metrics/Specificity': 0.967327892780304,\n",
       "   'train_metrics/Recall': 0.8171597719192505,\n",
       "   'train_metrics/JaccardIndex': 0.8259789347648621},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8126841187477112,\n",
       "   'valid_metrics/Accuracy': 0.9318963289260864,\n",
       "   'valid_metrics/Dice': 0.8126841187477112,\n",
       "   'valid_metrics/Precision': 0.8446959257125854,\n",
       "   'valid_metrics/Specificity': 0.9665206670761108,\n",
       "   'valid_metrics/Recall': 0.7830101251602173,\n",
       "   'valid_metrics/JaccardIndex': 0.8022812604904175}},\n",
       " {'tr_loss': 0.00944894122437012,\n",
       "  'vl_loss': 0.010704828562883796,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8450770378112793,\n",
       "   'train_metrics/Accuracy': 0.9348031282424927,\n",
       "   'train_metrics/Dice': 0.8450770378112793,\n",
       "   'train_metrics/Precision': 0.8791916966438293,\n",
       "   'train_metrics/Specificity': 0.9687315225601196,\n",
       "   'train_metrics/Recall': 0.8135108947753906,\n",
       "   'train_metrics/JaccardIndex': 0.8262099027633667},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.813015341758728,\n",
       "   'valid_metrics/Accuracy': 0.928838849067688,\n",
       "   'valid_metrics/Dice': 0.813015341758728,\n",
       "   'valid_metrics/Precision': 0.8062004446983337,\n",
       "   'valid_metrics/Specificity': 0.9541623592376709,\n",
       "   'valid_metrics/Recall': 0.8199464678764343,\n",
       "   'valid_metrics/JaccardIndex': 0.8003783226013184}},\n",
       " {'tr_loss': 0.00892609515876481,\n",
       "  'vl_loss': 0.010431593190519046,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8531944751739502,\n",
       "   'train_metrics/Accuracy': 0.9378450512886047,\n",
       "   'train_metrics/Dice': 0.853194534778595,\n",
       "   'train_metrics/Precision': 0.8818985223770142,\n",
       "   'train_metrics/Specificity': 0.9690468907356262,\n",
       "   'train_metrics/Recall': 0.8263001441955566,\n",
       "   'train_metrics/JaccardIndex': 0.8340597152709961},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8219972252845764,\n",
       "   'valid_metrics/Accuracy': 0.9320103526115417,\n",
       "   'valid_metrics/Dice': 0.8219972252845764,\n",
       "   'valid_metrics/Precision': 0.8122091889381409,\n",
       "   'valid_metrics/Specificity': 0.9552627801895142,\n",
       "   'valid_metrics/Recall': 0.8320240378379822,\n",
       "   'valid_metrics/JaccardIndex': 0.8085691928863525}},\n",
       " {'tr_loss': 0.008976374151949712,\n",
       "  'vl_loss': 0.012133620938278994,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8528521656990051,\n",
       "   'train_metrics/Accuracy': 0.9379315972328186,\n",
       "   'train_metrics/Dice': 0.8528521656990051,\n",
       "   'train_metrics/Precision': 0.8850681781768799,\n",
       "   'train_metrics/Specificity': 0.9701089859008789,\n",
       "   'train_metrics/Recall': 0.8228989243507385,\n",
       "   'train_metrics/JaccardIndex': 0.8338866233825684},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.7952426671981812,\n",
       "   'valid_metrics/Accuracy': 0.9191997051239014,\n",
       "   'valid_metrics/Dice': 0.7952426671981812,\n",
       "   'valid_metrics/Precision': 0.7619179487228394,\n",
       "   'valid_metrics/Specificity': 0.9395678639411926,\n",
       "   'valid_metrics/Recall': 0.8316158056259155,\n",
       "   'valid_metrics/JaccardIndex': 0.7821236848831177}},\n",
       " {'tr_loss': 0.008529879436020023,\n",
       "  'vl_loss': 0.010144919185794918,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8601192831993103,\n",
       "   'train_metrics/Accuracy': 0.9407693147659302,\n",
       "   'train_metrics/Dice': 0.8601193428039551,\n",
       "   'train_metrics/Precision': 0.8889360427856445,\n",
       "   'train_metrics/Specificity': 0.9708836674690247,\n",
       "   'train_metrics/Recall': 0.8331122398376465,\n",
       "   'train_metrics/JaccardIndex': 0.8410756587982178},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8294364809989929,\n",
       "   'valid_metrics/Accuracy': 0.9334717988967896,\n",
       "   'valid_metrics/Dice': 0.8294364213943481,\n",
       "   'valid_metrics/Precision': 0.8032934069633484,\n",
       "   'valid_metrics/Specificity': 0.9511770606040955,\n",
       "   'valid_metrics/Recall': 0.8573383092880249,\n",
       "   'valid_metrics/JaccardIndex': 0.8146060705184937}},\n",
       " {'tr_loss': 0.00856319160582934,\n",
       "  'vl_loss': 0.011049743065732786,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.858493983745575,\n",
       "   'train_metrics/Accuracy': 0.9400604963302612,\n",
       "   'train_metrics/Dice': 0.858493983745575,\n",
       "   'train_metrics/Precision': 0.8869313597679138,\n",
       "   'train_metrics/Specificity': 0.9703370928764343,\n",
       "   'train_metrics/Recall': 0.8318235874176025,\n",
       "   'train_metrics/JaccardIndex': 0.83940589427948},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.817633867263794,\n",
       "   'valid_metrics/Accuracy': 0.9296147227287292,\n",
       "   'valid_metrics/Dice': 0.8176338076591492,\n",
       "   'valid_metrics/Precision': 0.7998108863830566,\n",
       "   'valid_metrics/Specificity': 0.9513227343559265,\n",
       "   'valid_metrics/Recall': 0.836269199848175,\n",
       "   'valid_metrics/JaccardIndex': 0.8039758205413818}},\n",
       " {'tr_loss': 0.008431984913168532,\n",
       "  'vl_loss': 0.009516683410723698,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8598141074180603,\n",
       "   'train_metrics/Accuracy': 0.9405599236488342,\n",
       "   'train_metrics/Dice': 0.8598141670227051,\n",
       "   'train_metrics/Precision': 0.8873431086540222,\n",
       "   'train_metrics/Specificity': 0.9703836441040039,\n",
       "   'train_metrics/Recall': 0.8339418172836304,\n",
       "   'train_metrics/JaccardIndex': 0.8407047986984253},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8322377800941467,\n",
       "   'valid_metrics/Accuracy': 0.9388149976730347,\n",
       "   'valid_metrics/Dice': 0.832237720489502,\n",
       "   'valid_metrics/Precision': 0.8621230125427246,\n",
       "   'valid_metrics/Specificity': 0.9700844287872314,\n",
       "   'valid_metrics/Recall': 0.8043549656867981,\n",
       "   'valid_metrics/JaccardIndex': 0.82027268409729}},\n",
       " {'tr_loss': 0.008273866546876502,\n",
       "  'vl_loss': 0.010811475051646067,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8629688620567322,\n",
       "   'train_metrics/Accuracy': 0.9418659210205078,\n",
       "   'train_metrics/Dice': 0.8629688620567322,\n",
       "   'train_metrics/Precision': 0.890082061290741,\n",
       "   'train_metrics/Specificity': 0.9710710644721985,\n",
       "   'train_metrics/Recall': 0.8374586701393127,\n",
       "   'train_metrics/JaccardIndex': 0.8439033031463623},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8151729702949524,\n",
       "   'valid_metrics/Accuracy': 0.9356388449668884,\n",
       "   'valid_metrics/Dice': 0.8151730298995972,\n",
       "   'valid_metrics/Precision': 0.8895937204360962,\n",
       "   'valid_metrics/Specificity': 0.9782886505126953,\n",
       "   'valid_metrics/Recall': 0.7522426843643188,\n",
       "   'valid_metrics/JaccardIndex': 0.806501567363739}},\n",
       " {'tr_loss': 0.008271401098444443,\n",
       "  'vl_loss': 0.009796379126867273,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.862869381904602,\n",
       "   'train_metrics/Accuracy': 0.9418689608573914,\n",
       "   'train_metrics/Dice': 0.8628694415092468,\n",
       "   'train_metrics/Precision': 0.8907172679901123,\n",
       "   'train_metrics/Specificity': 0.9712844491004944,\n",
       "   'train_metrics/Recall': 0.8367099761962891,\n",
       "   'train_metrics/JaccardIndex': 0.8438352942466736},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8332063555717468,\n",
       "   'valid_metrics/Accuracy': 0.9377630949020386,\n",
       "   'valid_metrics/Dice': 0.8332063555717468,\n",
       "   'valid_metrics/Precision': 0.8427330255508423,\n",
       "   'valid_metrics/Specificity': 0.9642443060874939,\n",
       "   'valid_metrics/Recall': 0.8238926529884338,\n",
       "   'valid_metrics/JaccardIndex': 0.8202033638954163}},\n",
       " {'tr_loss': 0.00813302092520987,\n",
       "  'vl_loss': 0.010168441387907418,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8656395077705383,\n",
       "   'train_metrics/Accuracy': 0.9430903792381287,\n",
       "   'train_metrics/Dice': 0.8656395673751831,\n",
       "   'train_metrics/Precision': 0.8943651914596558,\n",
       "   'train_metrics/Specificity': 0.9722904562950134,\n",
       "   'train_metrics/Recall': 0.8387016654014587,\n",
       "   'train_metrics/JaccardIndex': 0.8467117547988892},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8229372501373291,\n",
       "   'valid_metrics/Accuracy': 0.934338390827179,\n",
       "   'valid_metrics/Dice': 0.8229372501373291,\n",
       "   'valid_metrics/Precision': 0.8376584649085999,\n",
       "   'valid_metrics/Specificity': 0.9635506272315979,\n",
       "   'valid_metrics/Recall': 0.8087244629859924,\n",
       "   'valid_metrics/JaccardIndex': 0.8108298778533936}},\n",
       " {'tr_loss': 0.007829530812163655,\n",
       "  'vl_loss': 0.011020560867537863,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8730586767196655,\n",
       "   'train_metrics/Accuracy': 0.9460229277610779,\n",
       "   'train_metrics/Dice': 0.8730586767196655,\n",
       "   'train_metrics/Precision': 0.8983055353164673,\n",
       "   'train_metrics/Specificity': 0.9731088280677795,\n",
       "   'train_metrics/Recall': 0.8491920828819275,\n",
       "   'train_metrics/JaccardIndex': 0.8542177677154541},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8128736615180969,\n",
       "   'valid_metrics/Accuracy': 0.9294126629829407,\n",
       "   'valid_metrics/Dice': 0.8128736615180969,\n",
       "   'valid_metrics/Precision': 0.8131702542304993,\n",
       "   'valid_metrics/Specificity': 0.9565833806991577,\n",
       "   'valid_metrics/Recall': 0.8125773072242737,\n",
       "   'valid_metrics/JaccardIndex': 0.8006857633590698}},\n",
       " {'tr_loss': 0.0077956937479250355,\n",
       "  'vl_loss': 0.010430883745659272,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8732361197471619,\n",
       "   'train_metrics/Accuracy': 0.946025013923645,\n",
       "   'train_metrics/Dice': 0.8732361793518066,\n",
       "   'train_metrics/Precision': 0.8971981406211853,\n",
       "   'train_metrics/Specificity': 0.9727398753166199,\n",
       "   'train_metrics/Recall': 0.8505208492279053,\n",
       "   'train_metrics/JaccardIndex': 0.8543469905853271},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8267062902450562,\n",
       "   'valid_metrics/Accuracy': 0.9354241490364075,\n",
       "   'valid_metrics/Dice': 0.8267062902450562,\n",
       "   'valid_metrics/Precision': 0.8373053669929504,\n",
       "   'valid_metrics/Specificity': 0.9631103277206421,\n",
       "   'valid_metrics/Recall': 0.8163721561431885,\n",
       "   'valid_metrics/JaccardIndex': 0.8141347169876099}},\n",
       " {'tr_loss': 0.007480096166373613,\n",
       "  'vl_loss': 0.009629513593714209,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8772928714752197,\n",
       "   'train_metrics/Accuracy': 0.947534441947937,\n",
       "   'train_metrics/Dice': 0.8772928714752197,\n",
       "   'train_metrics/Precision': 0.8974355459213257,\n",
       "   'train_metrics/Specificity': 0.9725698232650757,\n",
       "   'train_metrics/Recall': 0.858034610748291,\n",
       "   'train_metrics/JaccardIndex': 0.8584157824516296},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8333661556243896,\n",
       "   'valid_metrics/Accuracy': 0.9406235218048096,\n",
       "   'valid_metrics/Dice': 0.8333661556243896,\n",
       "   'valid_metrics/Precision': 0.8856250047683716,\n",
       "   'valid_metrics/Specificity': 0.9763655662536621,\n",
       "   'valid_metrics/Recall': 0.786931037902832,\n",
       "   'valid_metrics/JaccardIndex': 0.8223021030426025}},\n",
       " {'tr_loss': 0.007546463933037004,\n",
       "  'vl_loss': 0.009763370034317253,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8773565292358398,\n",
       "   'train_metrics/Accuracy': 0.9478173851966858,\n",
       "   'train_metrics/Dice': 0.8773565292358398,\n",
       "   'train_metrics/Precision': 0.902123212814331,\n",
       "   'train_metrics/Specificity': 0.9740846157073975,\n",
       "   'train_metrics/Recall': 0.8539133667945862,\n",
       "   'train_metrics/JaccardIndex': 0.8586759567260742},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8341752290725708,\n",
       "   'valid_metrics/Accuracy': 0.9377450942993164,\n",
       "   'valid_metrics/Dice': 0.8341752290725708,\n",
       "   'valid_metrics/Precision': 0.8384842872619629,\n",
       "   'valid_metrics/Specificity': 0.962822675704956,\n",
       "   'valid_metrics/Recall': 0.8299102187156677,\n",
       "   'valid_metrics/JaccardIndex': 0.8208553791046143}},\n",
       " {'tr_loss': 0.007078616288246859,\n",
       "  'vl_loss': 0.009998483115871901,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8843852877616882,\n",
       "   'train_metrics/Accuracy': 0.950480043888092,\n",
       "   'train_metrics/Dice': 0.8843852281570435,\n",
       "   'train_metrics/Precision': 0.9030336141586304,\n",
       "   'train_metrics/Specificity': 0.97397381067276,\n",
       "   'train_metrics/Recall': 0.8664914965629578,\n",
       "   'train_metrics/JaccardIndex': 0.8658215999603271},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8282932043075562,\n",
       "   'valid_metrics/Accuracy': 0.9379931688308716,\n",
       "   'valid_metrics/Dice': 0.8282931447029114,\n",
       "   'valid_metrics/Precision': 0.867283821105957,\n",
       "   'valid_metrics/Specificity': 0.9717918038368225,\n",
       "   'valid_metrics/Recall': 0.7926574349403381,\n",
       "   'valid_metrics/JaccardIndex': 0.817000150680542}},\n",
       " {'tr_loss': 0.0070749938303281456,\n",
       "  'vl_loss': 0.0102784748128022,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8849399089813232,\n",
       "   'train_metrics/Accuracy': 0.9508631825447083,\n",
       "   'train_metrics/Dice': 0.884939968585968,\n",
       "   'train_metrics/Precision': 0.9063972234725952,\n",
       "   'train_metrics/Specificity': 0.9750280380249023,\n",
       "   'train_metrics/Recall': 0.8644751310348511,\n",
       "   'train_metrics/JaccardIndex': 0.8665202856063843},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8260027766227722,\n",
       "   'valid_metrics/Accuracy': 0.9338679313659668,\n",
       "   'valid_metrics/Dice': 0.8260027766227722,\n",
       "   'valid_metrics/Precision': 0.8201330304145813,\n",
       "   'valid_metrics/Specificity': 0.9575678706169128,\n",
       "   'valid_metrics/Recall': 0.8319571614265442,\n",
       "   'valid_metrics/JaccardIndex': 0.8125678300857544}},\n",
       " {'tr_loss': 0.006466419961991061,\n",
       "  'vl_loss': 0.009840103678951852,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8954703211784363,\n",
       "   'train_metrics/Accuracy': 0.9552452564239502,\n",
       "   'train_metrics/Dice': 0.895470380783081,\n",
       "   'train_metrics/Precision': 0.9147186279296875,\n",
       "   'train_metrics/Specificity': 0.9771279692649841,\n",
       "   'train_metrics/Recall': 0.8770155310630798,\n",
       "   'train_metrics/JaccardIndex': 0.877678394317627},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8334201574325562,\n",
       "   'valid_metrics/Accuracy': 0.9396101236343384,\n",
       "   'valid_metrics/Dice': 0.8334201574325562,\n",
       "   'valid_metrics/Precision': 0.8689597249031067,\n",
       "   'valid_metrics/Specificity': 0.9719206094741821,\n",
       "   'valid_metrics/Recall': 0.8006734251976013,\n",
       "   'valid_metrics/JaccardIndex': 0.8216384649276733}},\n",
       " {'tr_loss': 0.006319306934503813,\n",
       "  'vl_loss': 0.010263440145258738,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.8976076245307922,\n",
       "   'train_metrics/Accuracy': 0.9559754133224487,\n",
       "   'train_metrics/Dice': 0.897607684135437,\n",
       "   'train_metrics/Precision': 0.9129021167755127,\n",
       "   'train_metrics/Specificity': 0.9764395356178284,\n",
       "   'train_metrics/Recall': 0.8828171491622925,\n",
       "   'train_metrics/JaccardIndex': 0.8798424601554871},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8310841917991638,\n",
       "   'valid_metrics/Accuracy': 0.9340292811393738,\n",
       "   'valid_metrics/Dice': 0.8310841917991638,\n",
       "   'valid_metrics/Precision': 0.8039161562919617,\n",
       "   'valid_metrics/Specificity': 0.9512096643447876,\n",
       "   'valid_metrics/Recall': 0.8601527810096741,\n",
       "   'valid_metrics/JaccardIndex': 0.8161179423332214}},\n",
       " {'tr_loss': 0.005101280277671893,\n",
       "  'vl_loss': 0.010362769761140742,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9183529615402222,\n",
       "   'train_metrics/Accuracy': 0.9647634029388428,\n",
       "   'train_metrics/Dice': 0.9183530211448669,\n",
       "   'train_metrics/Precision': 0.9304066300392151,\n",
       "   'train_metrics/Specificity': 0.9810310006141663,\n",
       "   'train_metrics/Recall': 0.9066076278686523,\n",
       "   'train_metrics/JaccardIndex': 0.9025435447692871},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8358511328697205,\n",
       "   'valid_metrics/Accuracy': 0.9396704435348511,\n",
       "   'valid_metrics/Dice': 0.8358511328697205,\n",
       "   'valid_metrics/Precision': 0.8588108420372009,\n",
       "   'valid_metrics/Specificity': 0.968875527381897,\n",
       "   'valid_metrics/Recall': 0.8140870928764343,\n",
       "   'valid_metrics/JaccardIndex': 0.8233577013015747}},\n",
       " {'tr_loss': 0.004552386471226852,\n",
       "  'vl_loss': 0.010518038652578375,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9267936944961548,\n",
       "   'train_metrics/Accuracy': 0.9683191180229187,\n",
       "   'train_metrics/Dice': 0.9267936944961548,\n",
       "   'train_metrics/Precision': 0.9363174438476562,\n",
       "   'train_metrics/Specificity': 0.9825451374053955,\n",
       "   'train_metrics/Recall': 0.9174617528915405,\n",
       "   'train_metrics/JaccardIndex': 0.9119733572006226},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8337699770927429,\n",
       "   'valid_metrics/Accuracy': 0.9362037777900696,\n",
       "   'valid_metrics/Dice': 0.8337699770927429,\n",
       "   'valid_metrics/Precision': 0.8200362324714661,\n",
       "   'valid_metrics/Specificity': 0.9567226767539978,\n",
       "   'valid_metrics/Recall': 0.8479716181755066,\n",
       "   'valid_metrics/JaccardIndex': 0.8194901347160339}},\n",
       " {'tr_loss': 0.004362605388992089,\n",
       "  'vl_loss': 0.011051384581101907,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.929157018661499,\n",
       "   'train_metrics/Accuracy': 0.9693254828453064,\n",
       "   'train_metrics/Dice': 0.929157018661499,\n",
       "   'train_metrics/Precision': 0.9381933808326721,\n",
       "   'train_metrics/Specificity': 0.9830410480499268,\n",
       "   'train_metrics/Recall': 0.9202930331230164,\n",
       "   'train_metrics/JaccardIndex': 0.9146443605422974},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8323505520820618,\n",
       "   'valid_metrics/Accuracy': 0.934278130531311,\n",
       "   'valid_metrics/Dice': 0.8323505520820618,\n",
       "   'valid_metrics/Precision': 0.8023373484611511,\n",
       "   'valid_metrics/Specificity': 0.9504597187042236,\n",
       "   'valid_metrics/Recall': 0.8646965026855469,\n",
       "   'valid_metrics/JaccardIndex': 0.817154049873352}},\n",
       " {'tr_loss': 0.0040409656821367825,\n",
       "  'vl_loss': 0.01081552980719386,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9346928000450134,\n",
       "   'train_metrics/Accuracy': 0.9717176556587219,\n",
       "   'train_metrics/Dice': 0.9346927404403687,\n",
       "   'train_metrics/Precision': 0.943619966506958,\n",
       "   'train_metrics/Specificity': 0.9845247268676758,\n",
       "   'train_metrics/Recall': 0.9259329438209534,\n",
       "   'train_metrics/JaccardIndex': 0.9209668636322021},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8330835700035095,\n",
       "   'valid_metrics/Accuracy': 0.9365640878677368,\n",
       "   'valid_metrics/Dice': 0.8330835700035095,\n",
       "   'valid_metrics/Precision': 0.8272265791893005,\n",
       "   'valid_metrics/Specificity': 0.9592475295066833,\n",
       "   'valid_metrics/Recall': 0.8390241265296936,\n",
       "   'valid_metrics/JaccardIndex': 0.819275975227356}},\n",
       " {'tr_loss': 0.003758965980661802,\n",
       "  'vl_loss': 0.011405966686926294,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9390597343444824,\n",
       "   'train_metrics/Accuracy': 0.9735618233680725,\n",
       "   'train_metrics/Dice': 0.9390597343444824,\n",
       "   'train_metrics/Precision': 0.946312427520752,\n",
       "   'train_metrics/Specificity': 0.9852107167243958,\n",
       "   'train_metrics/Recall': 0.9319173097610474,\n",
       "   'train_metrics/JaccardIndex': 0.9259594678878784},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.836010754108429,\n",
       "   'valid_metrics/Accuracy': 0.9386154413223267,\n",
       "   'valid_metrics/Dice': 0.836010754108429,\n",
       "   'valid_metrics/Precision': 0.8428439497947693,\n",
       "   'valid_metrics/Specificity': 0.9640402793884277,\n",
       "   'valid_metrics/Recall': 0.8292874693870544,\n",
       "   'valid_metrics/JaccardIndex': 0.8227290511131287}},\n",
       " {'tr_loss': 0.003533499895212736,\n",
       "  'vl_loss': 0.011619513099258011,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9426853656768799,\n",
       "   'train_metrics/Accuracy': 0.9750854969024658,\n",
       "   'train_metrics/Dice': 0.9426854252815247,\n",
       "   'train_metrics/Precision': 0.9480642676353455,\n",
       "   'train_metrics/Specificity': 0.9856361746788025,\n",
       "   'train_metrics/Recall': 0.9373672008514404,\n",
       "   'train_metrics/JaccardIndex': 0.9301248788833618},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8302190899848938,\n",
       "   'valid_metrics/Accuracy': 0.9364069104194641,\n",
       "   'valid_metrics/Dice': 0.830219030380249,\n",
       "   'valid_metrics/Precision': 0.8364626169204712,\n",
       "   'valid_metrics/Specificity': 0.9625319838523865,\n",
       "   'valid_metrics/Recall': 0.824068009853363,\n",
       "   'valid_metrics/JaccardIndex': 0.81721031665802}},\n",
       " {'tr_loss': 0.0033418202018442233,\n",
       "  'vl_loss': 0.01276141738799548,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9452725052833557,\n",
       "   'train_metrics/Accuracy': 0.9762256145477295,\n",
       "   'train_metrics/Dice': 0.9452725648880005,\n",
       "   'train_metrics/Precision': 0.9512959718704224,\n",
       "   'train_metrics/Specificity': 0.9865477681159973,\n",
       "   'train_metrics/Recall': 0.9393247961997986,\n",
       "   'train_metrics/JaccardIndex': 0.9331537485122681},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8217887282371521,\n",
       "   'valid_metrics/Accuracy': 0.9361716508865356,\n",
       "   'valid_metrics/Dice': 0.8217886686325073,\n",
       "   'valid_metrics/Precision': 0.8683227300643921,\n",
       "   'valid_metrics/Specificity': 0.9724929332733154,\n",
       "   'valid_metrics/Recall': 0.7799884676933289,\n",
       "   'valid_metrics/JaccardIndex': 0.811322808265686}},\n",
       " {'tr_loss': 0.003153239407117373,\n",
       "  'vl_loss': 0.012094465289336834,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9483919739723206,\n",
       "   'train_metrics/Accuracy': 0.9775552153587341,\n",
       "   'train_metrics/Dice': 0.9483919739723206,\n",
       "   'train_metrics/Precision': 0.9533357620239258,\n",
       "   'train_metrics/Specificity': 0.9870815277099609,\n",
       "   'train_metrics/Recall': 0.9434992074966431,\n",
       "   'train_metrics/JaccardIndex': 0.9367866516113281},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8295040726661682,\n",
       "   'valid_metrics/Accuracy': 0.936370313167572,\n",
       "   'valid_metrics/Dice': 0.8295040726661682,\n",
       "   'valid_metrics/Precision': 0.838835597038269,\n",
       "   'valid_metrics/Specificity': 0.9633449912071228,\n",
       "   'valid_metrics/Recall': 0.8203779458999634,\n",
       "   'valid_metrics/JaccardIndex': 0.8166974782943726}},\n",
       " {'tr_loss': 0.003116229991364413,\n",
       "  'vl_loss': 0.011934915794829144,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9487101435661316,\n",
       "   'train_metrics/Accuracy': 0.9776740670204163,\n",
       "   'train_metrics/Dice': 0.9487100839614868,\n",
       "   'train_metrics/Precision': 0.9528142809867859,\n",
       "   'train_metrics/Specificity': 0.9869142770767212,\n",
       "   'train_metrics/Recall': 0.9446411728858948,\n",
       "   'train_metrics/JaccardIndex': 0.9371448755264282},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.830792248249054,\n",
       "   'valid_metrics/Accuracy': 0.9370213747024536,\n",
       "   'valid_metrics/Dice': 0.830792248249054,\n",
       "   'valid_metrics/Precision': 0.8424678444862366,\n",
       "   'valid_metrics/Specificity': 0.9643665552139282,\n",
       "   'valid_metrics/Recall': 0.8194358348846436,\n",
       "   'valid_metrics/JaccardIndex': 0.8180317878723145}},\n",
       " {'tr_loss': 0.0028785103116153684,\n",
       "  'vl_loss': 0.012931830461881335,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.952817976474762,\n",
       "   'train_metrics/Accuracy': 0.9794756770133972,\n",
       "   'train_metrics/Dice': 0.952817976474762,\n",
       "   'train_metrics/Precision': 0.9575750231742859,\n",
       "   'train_metrics/Specificity': 0.9882500171661377,\n",
       "   'train_metrics/Recall': 0.9481080174446106,\n",
       "   'train_metrics/JaccardIndex': 0.941999077796936},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8286870718002319,\n",
       "   'valid_metrics/Accuracy': 0.9346693754196167,\n",
       "   'valid_metrics/Dice': 0.8286870121955872,\n",
       "   'valid_metrics/Precision': 0.8200907707214355,\n",
       "   'valid_metrics/Specificity': 0.9572746753692627,\n",
       "   'valid_metrics/Recall': 0.8374653458595276,\n",
       "   'valid_metrics/JaccardIndex': 0.8149473667144775}},\n",
       " {'tr_loss': 0.0026894583138470478,\n",
       "  'vl_loss': 0.012822755285211512,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9556370377540588,\n",
       "   'train_metrics/Accuracy': 0.9806805849075317,\n",
       "   'train_metrics/Dice': 0.9556370377540588,\n",
       "   'train_metrics/Precision': 0.959332287311554,\n",
       "   'train_metrics/Specificity': 0.9887115955352783,\n",
       "   'train_metrics/Recall': 0.9519701600074768,\n",
       "   'train_metrics/JaccardIndex': 0.9453235864639282},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.831469714641571,\n",
       "   'valid_metrics/Accuracy': 0.9386022090911865,\n",
       "   'valid_metrics/Dice': 0.831469714641571,\n",
       "   'valid_metrics/Precision': 0.8623412251472473,\n",
       "   'valid_metrics/Specificity': 0.9701995849609375,\n",
       "   'valid_metrics/Recall': 0.8027321696281433,\n",
       "   'valid_metrics/JaccardIndex': 0.8195974826812744}},\n",
       " {'tr_loss': 0.0024516402371740865,\n",
       "  'vl_loss': 0.012522794306278229,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9597554802894592,\n",
       "   'train_metrics/Accuracy': 0.9824494123458862,\n",
       "   'train_metrics/Dice': 0.9597555994987488,\n",
       "   'train_metrics/Precision': 0.9621033668518066,\n",
       "   'train_metrics/Specificity': 0.989450991153717,\n",
       "   'train_metrics/Recall': 0.9574190974235535,\n",
       "   'train_metrics/JaccardIndex': 0.950214684009552},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8343906402587891,\n",
       "   'valid_metrics/Accuracy': 0.9385382533073425,\n",
       "   'valid_metrics/Dice': 0.8343905806541443,\n",
       "   'valid_metrics/Precision': 0.8486379981040955,\n",
       "   'valid_metrics/Specificity': 0.965962290763855,\n",
       "   'valid_metrics/Recall': 0.82061368227005,\n",
       "   'valid_metrics/JaccardIndex': 0.8215596675872803}},\n",
       " {'tr_loss': 0.0022615386773485783,\n",
       "  'vl_loss': 0.0135356953590533,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9624766111373901,\n",
       "   'train_metrics/Accuracy': 0.9836452007293701,\n",
       "   'train_metrics/Dice': 0.9624767303466797,\n",
       "   'train_metrics/Precision': 0.9653685688972473,\n",
       "   'train_metrics/Specificity': 0.9903706312179565,\n",
       "   'train_metrics/Recall': 0.9596019983291626,\n",
       "   'train_metrics/JaccardIndex': 0.9534857869148254},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8308637738227844,\n",
       "   'valid_metrics/Accuracy': 0.9365560412406921,\n",
       "   'valid_metrics/Dice': 0.8308637738227844,\n",
       "   'valid_metrics/Precision': 0.8358770608901978,\n",
       "   'valid_metrics/Specificity': 0.9622873663902283,\n",
       "   'valid_metrics/Recall': 0.825910210609436,\n",
       "   'valid_metrics/JaccardIndex': 0.8177545666694641}},\n",
       " {'tr_loss': 0.0022178516859193806,\n",
       "  'vl_loss': 0.013439973952917518,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9634007215499878,\n",
       "   'train_metrics/Accuracy': 0.9840354919433594,\n",
       "   'train_metrics/Dice': 0.9634007215499878,\n",
       "   'train_metrics/Precision': 0.9655365943908691,\n",
       "   'train_metrics/Specificity': 0.990402340888977,\n",
       "   'train_metrics/Recall': 0.9612742066383362,\n",
       "   'train_metrics/JaccardIndex': 0.9545873403549194},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8322324752807617,\n",
       "   'valid_metrics/Accuracy': 0.9373190402984619,\n",
       "   'valid_metrics/Dice': 0.8322324752807617,\n",
       "   'valid_metrics/Precision': 0.8406410217285156,\n",
       "   'valid_metrics/Specificity': 0.9636741876602173,\n",
       "   'valid_metrics/Recall': 0.823990523815155,\n",
       "   'valid_metrics/JaccardIndex': 0.8192249536514282}},\n",
       " {'tr_loss': 0.0021724469415822963,\n",
       "  'vl_loss': 0.013258005028525834,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9641028642654419,\n",
       "   'train_metrics/Accuracy': 0.9843350052833557,\n",
       "   'train_metrics/Dice': 0.9641028642654419,\n",
       "   'train_metrics/Precision': 0.9658260345458984,\n",
       "   'train_metrics/Specificity': 0.9904747605323792,\n",
       "   'train_metrics/Recall': 0.9623857140541077,\n",
       "   'train_metrics/JaccardIndex': 0.9554277658462524},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8321573138237,\n",
       "   'valid_metrics/Accuracy': 0.9383280277252197,\n",
       "   'valid_metrics/Dice': 0.8321573138237,\n",
       "   'valid_metrics/Precision': 0.8552379608154297,\n",
       "   'valid_metrics/Specificity': 0.9681040644645691,\n",
       "   'valid_metrics/Recall': 0.810289740562439,\n",
       "   'valid_metrics/JaccardIndex': 0.8198786377906799}},\n",
       " {'tr_loss': 0.0020862365731605156,\n",
       "  'vl_loss': 0.01365203910927975,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.965446949005127,\n",
       "   'train_metrics/Accuracy': 0.9849264621734619,\n",
       "   'train_metrics/Dice': 0.965446949005127,\n",
       "   'train_metrics/Precision': 0.9674866199493408,\n",
       "   'train_metrics/Specificity': 0.9909435510635376,\n",
       "   'train_metrics/Recall': 0.9634158611297607,\n",
       "   'train_metrics/JaccardIndex': 0.9570537209510803},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.832051694393158,\n",
       "   'valid_metrics/Accuracy': 0.9377523064613342,\n",
       "   'valid_metrics/Dice': 0.832051694393158,\n",
       "   'valid_metrics/Precision': 0.8474145531654358,\n",
       "   'valid_metrics/Specificity': 0.9657790660858154,\n",
       "   'valid_metrics/Recall': 0.8172359466552734,\n",
       "   'valid_metrics/JaccardIndex': 0.8194044232368469}},\n",
       " {'tr_loss': 0.0020251813157366656,\n",
       "  'vl_loss': 0.013506157690493757,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9664953947067261,\n",
       "   'train_metrics/Accuracy': 0.9853835701942444,\n",
       "   'train_metrics/Dice': 0.9664955139160156,\n",
       "   'train_metrics/Precision': 0.9685181379318237,\n",
       "   'train_metrics/Specificity': 0.9912304282188416,\n",
       "   'train_metrics/Recall': 0.9644811749458313,\n",
       "   'train_metrics/JaccardIndex': 0.9583210945129395},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8323426842689514,\n",
       "   'valid_metrics/Accuracy': 0.9376447200775146,\n",
       "   'valid_metrics/Dice': 0.8323426842689514,\n",
       "   'valid_metrics/Precision': 0.8446849584579468,\n",
       "   'valid_metrics/Specificity': 0.9649209380149841,\n",
       "   'valid_metrics/Recall': 0.8203558921813965,\n",
       "   'valid_metrics/JaccardIndex': 0.8195285797119141}},\n",
       " {'tr_loss': 0.0019471989498158133,\n",
       "  'vl_loss': 0.014274747445316389,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9676606059074402,\n",
       "   'train_metrics/Accuracy': 0.98588627576828,\n",
       "   'train_metrics/Dice': 0.967660665512085,\n",
       "   'train_metrics/Precision': 0.9693000912666321,\n",
       "   'train_metrics/Specificity': 0.991441547870636,\n",
       "   'train_metrics/Recall': 0.9660267233848572,\n",
       "   'train_metrics/JaccardIndex': 0.9597278833389282},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8301892876625061,\n",
       "   'valid_metrics/Accuracy': 0.9361622929573059,\n",
       "   'valid_metrics/Dice': 0.8301893472671509,\n",
       "   'valid_metrics/Precision': 0.8333387970924377,\n",
       "   'valid_metrics/Specificity': 0.9615338444709778,\n",
       "   'valid_metrics/Recall': 0.8270635604858398,\n",
       "   'valid_metrics/JaccardIndex': 0.8170185089111328}},\n",
       " {'tr_loss': 0.00193972267805709,\n",
       "  'vl_loss': 0.013757229340352607,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.968153715133667,\n",
       "   'train_metrics/Accuracy': 0.9861006140708923,\n",
       "   'train_metrics/Dice': 0.968153715133667,\n",
       "   'train_metrics/Precision': 0.9697346091270447,\n",
       "   'train_metrics/Specificity': 0.9915615916252136,\n",
       "   'train_metrics/Recall': 0.9665780067443848,\n",
       "   'train_metrics/JaccardIndex': 0.9603253602981567},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8319072723388672,\n",
       "   'valid_metrics/Accuracy': 0.9384543895721436,\n",
       "   'valid_metrics/Dice': 0.8319072723388672,\n",
       "   'valid_metrics/Precision': 0.8581928014755249,\n",
       "   'valid_metrics/Specificity': 0.9689820408821106,\n",
       "   'valid_metrics/Recall': 0.807184100151062,\n",
       "   'valid_metrics/JaccardIndex': 0.8197950124740601}},\n",
       " {'tr_loss': 0.0018507677117573,\n",
       "  'vl_loss': 0.01425550233673405,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9694151878356934,\n",
       "   'train_metrics/Accuracy': 0.9866490364074707,\n",
       "   'train_metrics/Dice': 0.9694151878356934,\n",
       "   'train_metrics/Precision': 0.9708414077758789,\n",
       "   'train_metrics/Specificity': 0.9918676018714905,\n",
       "   'train_metrics/Recall': 0.9679931402206421,\n",
       "   'train_metrics/JaccardIndex': 0.9618560075759888},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8320944905281067,\n",
       "   'valid_metrics/Accuracy': 0.9379344582557678,\n",
       "   'valid_metrics/Dice': 0.8320944905281067,\n",
       "   'valid_metrics/Precision': 0.8498188257217407,\n",
       "   'valid_metrics/Specificity': 0.9665015935897827,\n",
       "   'valid_metrics/Recall': 0.8150944113731384,\n",
       "   'valid_metrics/JaccardIndex': 0.8195610046386719}},\n",
       " {'tr_loss': 0.0018575053610749154,\n",
       "  'vl_loss': 0.014054620099113714,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9692891836166382,\n",
       "   'train_metrics/Accuracy': 0.9865926504135132,\n",
       "   'train_metrics/Dice': 0.9692891836166382,\n",
       "   'train_metrics/Precision': 0.9706130027770996,\n",
       "   'train_metrics/Specificity': 0.9918021559715271,\n",
       "   'train_metrics/Recall': 0.9679690599441528,\n",
       "   'train_metrics/JaccardIndex': 0.9617016315460205},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8299341201782227,\n",
       "   'valid_metrics/Accuracy': 0.9369991421699524,\n",
       "   'valid_metrics/Dice': 0.8299341201782227,\n",
       "   'valid_metrics/Precision': 0.8456986546516418,\n",
       "   'valid_metrics/Specificity': 0.9654296636581421,\n",
       "   'valid_metrics/Recall': 0.8147465586662292,\n",
       "   'valid_metrics/JaccardIndex': 0.817430317401886}},\n",
       " {'tr_loss': 0.0017707464585373224,\n",
       "  'vl_loss': 0.014685213508292974,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9705962538719177,\n",
       "   'train_metrics/Accuracy': 0.9871627688407898,\n",
       "   'train_metrics/Dice': 0.970596194267273,\n",
       "   'train_metrics/Precision': 0.9718864560127258,\n",
       "   'train_metrics/Specificity': 0.9921568632125854,\n",
       "   'train_metrics/Recall': 0.9693093299865723,\n",
       "   'train_metrics/JaccardIndex': 0.9632918834686279},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8303133249282837,\n",
       "   'valid_metrics/Accuracy': 0.9371740221977234,\n",
       "   'valid_metrics/Dice': 0.8303133845329285,\n",
       "   'valid_metrics/Precision': 0.846566379070282,\n",
       "   'valid_metrics/Specificity': 0.96566241979599,\n",
       "   'valid_metrics/Recall': 0.8146727085113525,\n",
       "   'valid_metrics/JaccardIndex': 0.8178113698959351}},\n",
       " {'tr_loss': 0.001668845818021409,\n",
       "  'vl_loss': 0.014862682310770838,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9723124504089355,\n",
       "   'train_metrics/Accuracy': 0.9879100322723389,\n",
       "   'train_metrics/Dice': 0.9723124504089355,\n",
       "   'train_metrics/Precision': 0.9734472036361694,\n",
       "   'train_metrics/Specificity': 0.9925897717475891,\n",
       "   'train_metrics/Recall': 0.9711803197860718,\n",
       "   'train_metrics/JaccardIndex': 0.9653843641281128},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8302565217018127,\n",
       "   'valid_metrics/Accuracy': 0.9372940063476562,\n",
       "   'valid_metrics/Dice': 0.8302565813064575,\n",
       "   'valid_metrics/Precision': 0.8484910130500793,\n",
       "   'valid_metrics/Specificity': 0.9662482738494873,\n",
       "   'valid_metrics/Recall': 0.8127893805503845,\n",
       "   'valid_metrics/JaccardIndex': 0.8178562521934509}},\n",
       " {'tr_loss': 0.0016446171302769137,\n",
       "  'vl_loss': 0.01501483133630863,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.97275710105896,\n",
       "   'train_metrics/Accuracy': 0.9881044626235962,\n",
       "   'train_metrics/Dice': 0.9727571606636047,\n",
       "   'train_metrics/Precision': 0.9739069938659668,\n",
       "   'train_metrics/Specificity': 0.9927183985710144,\n",
       "   'train_metrics/Recall': 0.9716099500656128,\n",
       "   'train_metrics/JaccardIndex': 0.9659280776977539},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8296301960945129,\n",
       "   'valid_metrics/Accuracy': 0.9363974928855896,\n",
       "   'valid_metrics/Dice': 0.8296302556991577,\n",
       "   'valid_metrics/Precision': 0.8386946320533752,\n",
       "   'valid_metrics/Specificity': 0.9632896780967712,\n",
       "   'valid_metrics/Recall': 0.820759654045105,\n",
       "   'valid_metrics/JaccardIndex': 0.8168025016784668}},\n",
       " {'tr_loss': 0.0016121858848931047,\n",
       "  'vl_loss': 0.014894935270073791,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9733968377113342,\n",
       "   'train_metrics/Accuracy': 0.9883847832679749,\n",
       "   'train_metrics/Dice': 0.9733968377113342,\n",
       "   'train_metrics/Precision': 0.9746320247650146,\n",
       "   'train_metrics/Specificity': 0.9929219484329224,\n",
       "   'train_metrics/Recall': 0.9721647500991821,\n",
       "   'train_metrics/JaccardIndex': 0.9667116403579712},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8297621011734009,\n",
       "   'valid_metrics/Accuracy': 0.9361130595207214,\n",
       "   'valid_metrics/Dice': 0.8297620415687561,\n",
       "   'valid_metrics/Precision': 0.8343755006790161,\n",
       "   'valid_metrics/Specificity': 0.9619066715240479,\n",
       "   'valid_metrics/Recall': 0.8251993656158447,\n",
       "   'valid_metrics/JaccardIndex': 0.8166929483413696}},\n",
       " {'tr_loss': 0.0015519841345791646,\n",
       "  'vl_loss': 0.015249766323096964,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9742571115493774,\n",
       "   'train_metrics/Accuracy': 0.9887545108795166,\n",
       "   'train_metrics/Dice': 0.9742571115493774,\n",
       "   'train_metrics/Precision': 0.9749828577041626,\n",
       "   'train_metrics/Specificity': 0.9930124878883362,\n",
       "   'train_metrics/Recall': 0.9735324382781982,\n",
       "   'train_metrics/JaccardIndex': 0.967760443687439},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8300527930259705,\n",
       "   'valid_metrics/Accuracy': 0.9367921948432922,\n",
       "   'valid_metrics/Dice': 0.8300527334213257,\n",
       "   'valid_metrics/Precision': 0.8423494100570679,\n",
       "   'valid_metrics/Specificity': 0.9643924832344055,\n",
       "   'valid_metrics/Recall': 0.8181099891662598,\n",
       "   'valid_metrics/JaccardIndex': 0.8173667192459106}},\n",
       " {'tr_loss': 0.001539549777494646,\n",
       "  'vl_loss': 0.015187912523516357,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9746567606925964,\n",
       "   'train_metrics/Accuracy': 0.9889299273490906,\n",
       "   'train_metrics/Dice': 0.9746567606925964,\n",
       "   'train_metrics/Precision': 0.975456953048706,\n",
       "   'train_metrics/Specificity': 0.9931458830833435,\n",
       "   'train_metrics/Recall': 0.9738578796386719,\n",
       "   'train_metrics/JaccardIndex': 0.9682512283325195},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.830751895904541,\n",
       "   'valid_metrics/Accuracy': 0.9374427795410156,\n",
       "   'valid_metrics/Dice': 0.830751895904541,\n",
       "   'valid_metrics/Precision': 0.8485124111175537,\n",
       "   'valid_metrics/Specificity': 0.9662152528762817,\n",
       "   'valid_metrics/Recall': 0.813719630241394,\n",
       "   'valid_metrics/JaccardIndex': 0.8182985782623291}},\n",
       " {'tr_loss': 0.0014997185097581427,\n",
       "  'vl_loss': 0.015191961094219253,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9750146865844727,\n",
       "   'train_metrics/Accuracy': 0.9890865087509155,\n",
       "   'train_metrics/Dice': 0.9750146269798279,\n",
       "   'train_metrics/Precision': 0.975830078125,\n",
       "   'train_metrics/Specificity': 0.9932503700256348,\n",
       "   'train_metrics/Recall': 0.9742006063461304,\n",
       "   'train_metrics/JaccardIndex': 0.9686905741691589},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8311564326286316,\n",
       "   'valid_metrics/Accuracy': 0.9375132322311401,\n",
       "   'valid_metrics/Dice': 0.8311564326286316,\n",
       "   'valid_metrics/Precision': 0.8478072881698608,\n",
       "   'valid_metrics/Specificity': 0.9659701585769653,\n",
       "   'valid_metrics/Recall': 0.8151470422744751,\n",
       "   'valid_metrics/JaccardIndex': 0.8186244964599609}},\n",
       " {'tr_loss': 0.0014836786022363615,\n",
       "  'vl_loss': 0.015538239513585007,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9754406213760376,\n",
       "   'train_metrics/Accuracy': 0.989276111125946,\n",
       "   'train_metrics/Dice': 0.9754406213760376,\n",
       "   'train_metrics/Precision': 0.9765846729278564,\n",
       "   'train_metrics/Specificity': 0.9934654831886292,\n",
       "   'train_metrics/Recall': 0.9742992520332336,\n",
       "   'train_metrics/JaccardIndex': 0.9692165851593018},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8301439881324768,\n",
       "   'valid_metrics/Accuracy': 0.9361507892608643,\n",
       "   'valid_metrics/Dice': 0.830143928527832,\n",
       "   'valid_metrics/Precision': 0.833365797996521,\n",
       "   'valid_metrics/Specificity': 0.961546778678894,\n",
       "   'valid_metrics/Recall': 0.8269469141960144,\n",
       "   'valid_metrics/JaccardIndex': 0.8169794678688049}},\n",
       " {'tr_loss': 0.0015048647807403045,\n",
       "  'vl_loss': 0.015770244897562565,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9751269221305847,\n",
       "   'train_metrics/Accuracy': 0.9891359210014343,\n",
       "   'train_metrics/Dice': 0.9751269817352295,\n",
       "   'train_metrics/Precision': 0.9759855270385742,\n",
       "   'train_metrics/Specificity': 0.9932944178581238,\n",
       "   'train_metrics/Recall': 0.9742697477340698,\n",
       "   'train_metrics/JaccardIndex': 0.9688287973403931},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8285255432128906,\n",
       "   'valid_metrics/Accuracy': 0.9367950558662415,\n",
       "   'valid_metrics/Dice': 0.8285255432128906,\n",
       "   'valid_metrics/Precision': 0.8486918210983276,\n",
       "   'valid_metrics/Specificity': 0.966445803642273,\n",
       "   'valid_metrics/Recall': 0.8092954158782959,\n",
       "   'valid_metrics/JaccardIndex': 0.8163274526596069}},\n",
       " {'tr_loss': 0.0014464265202523592,\n",
       "  'vl_loss': 0.015897694241586338,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9761285185813904,\n",
       "   'train_metrics/Accuracy': 0.9895713925361633,\n",
       "   'train_metrics/Dice': 0.9761285781860352,\n",
       "   'train_metrics/Precision': 0.976793646812439,\n",
       "   'train_metrics/Specificity': 0.9935174584388733,\n",
       "   'train_metrics/Recall': 0.9754642248153687,\n",
       "   'train_metrics/JaccardIndex': 0.9700577259063721},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8288761377334595,\n",
       "   'valid_metrics/Accuracy': 0.9360191226005554,\n",
       "   'valid_metrics/Dice': 0.8288760781288147,\n",
       "   'valid_metrics/Precision': 0.8366385102272034,\n",
       "   'valid_metrics/Specificity': 0.9627078175544739,\n",
       "   'valid_metrics/Recall': 0.8212563991546631,\n",
       "   'valid_metrics/JaccardIndex': 0.8160241842269897}},\n",
       " {'tr_loss': 0.0014358833945322957,\n",
       "  'vl_loss': 0.015638014984867287,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9762098789215088,\n",
       "   'train_metrics/Accuracy': 0.9896042346954346,\n",
       "   'train_metrics/Dice': 0.9762099385261536,\n",
       "   'train_metrics/Precision': 0.9766255617141724,\n",
       "   'train_metrics/Specificity': 0.9934672117233276,\n",
       "   'train_metrics/Recall': 0.9757944941520691,\n",
       "   'train_metrics/JaccardIndex': 0.9701555967330933},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8290597796440125,\n",
       "   'valid_metrics/Accuracy': 0.9362727999687195,\n",
       "   'valid_metrics/Dice': 0.8290597796440125,\n",
       "   'valid_metrics/Precision': 0.8393064737319946,\n",
       "   'valid_metrics/Specificity': 0.9635312557220459,\n",
       "   'valid_metrics/Recall': 0.819060206413269,\n",
       "   'valid_metrics/JaccardIndex': 0.8163267374038696}},\n",
       " {'tr_loss': 0.0014247481559836832,\n",
       "  'vl_loss': 0.01598521790909491,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.976340651512146,\n",
       "   'train_metrics/Accuracy': 0.9896676540374756,\n",
       "   'train_metrics/Dice': 0.976340651512146,\n",
       "   'train_metrics/Precision': 0.9773492217063904,\n",
       "   'train_metrics/Specificity': 0.9936770796775818,\n",
       "   'train_metrics/Recall': 0.9753342270851135,\n",
       "   'train_metrics/JaccardIndex': 0.970321536064148},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8282972574234009,\n",
       "   'valid_metrics/Accuracy': 0.9355736374855042,\n",
       "   'valid_metrics/Dice': 0.8282972574234009,\n",
       "   'valid_metrics/Precision': 0.8330373167991638,\n",
       "   'valid_metrics/Specificity': 0.961611270904541,\n",
       "   'valid_metrics/Recall': 0.8236108422279358,\n",
       "   'valid_metrics/JaccardIndex': 0.815318763256073}},\n",
       " {'tr_loss': 0.0013519498486246288,\n",
       "  'vl_loss': 0.01591511381408883,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9777308702468872,\n",
       "   'train_metrics/Accuracy': 0.9902704358100891,\n",
       "   'train_metrics/Dice': 0.9777308702468872,\n",
       "   'train_metrics/Precision': 0.9782995581626892,\n",
       "   'train_metrics/Specificity': 0.9939368963241577,\n",
       "   'train_metrics/Recall': 0.9771628975868225,\n",
       "   'train_metrics/JaccardIndex': 0.9720299243927002},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8298867344856262,\n",
       "   'valid_metrics/Accuracy': 0.9371917247772217,\n",
       "   'valid_metrics/Dice': 0.8298866748809814,\n",
       "   'valid_metrics/Precision': 0.8485980033874512,\n",
       "   'valid_metrics/Specificity': 0.9663098454475403,\n",
       "   'valid_metrics/Recall': 0.8119826912879944,\n",
       "   'valid_metrics/JaccardIndex': 0.8175323009490967}},\n",
       " {'tr_loss': 0.0013279880302093574,\n",
       "  'vl_loss': 0.015805698212049184,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.977992057800293,\n",
       "   'train_metrics/Accuracy': 0.9903827905654907,\n",
       "   'train_metrics/Dice': 0.9779921174049377,\n",
       "   'train_metrics/Precision': 0.9783835411071777,\n",
       "   'train_metrics/Specificity': 0.9939582347869873,\n",
       "   'train_metrics/Recall': 0.9776008725166321,\n",
       "   'train_metrics/JaccardIndex': 0.9723506569862366},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8293500542640686,\n",
       "   'valid_metrics/Accuracy': 0.9366686344146729,\n",
       "   'valid_metrics/Dice': 0.8293500542640686,\n",
       "   'valid_metrics/Precision': 0.8435257077217102,\n",
       "   'valid_metrics/Specificity': 0.9648138284683228,\n",
       "   'valid_metrics/Recall': 0.8156429529190063,\n",
       "   'valid_metrics/JaccardIndex': 0.8168011903762817}},\n",
       " {'tr_loss': 0.001319085175463976,\n",
       "  'vl_loss': 0.01579835429845169,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9783135056495667,\n",
       "   'train_metrics/Accuracy': 0.9905257225036621,\n",
       "   'train_metrics/Dice': 0.9783136248588562,\n",
       "   'train_metrics/Precision': 0.9789578914642334,\n",
       "   'train_metrics/Specificity': 0.994121789932251,\n",
       "   'train_metrics/Recall': 0.9776699542999268,\n",
       "   'train_metrics/JaccardIndex': 0.9727492332458496},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8300829529762268,\n",
       "   'valid_metrics/Accuracy': 0.9366981983184814,\n",
       "   'valid_metrics/Dice': 0.8300830125808716,\n",
       "   'valid_metrics/Precision': 0.8409400582313538,\n",
       "   'valid_metrics/Specificity': 0.9639526605606079,\n",
       "   'valid_metrics/Recall': 0.8195027112960815,\n",
       "   'valid_metrics/JaccardIndex': 0.8173215389251709}},\n",
       " {'tr_loss': 0.0012932365693500876,\n",
       "  'vl_loss': 0.01603907806992991,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9786657094955444,\n",
       "   'train_metrics/Accuracy': 0.9906817674636841,\n",
       "   'train_metrics/Dice': 0.9786657094955444,\n",
       "   'train_metrics/Precision': 0.9795358180999756,\n",
       "   'train_metrics/Specificity': 0.9942858219146729,\n",
       "   'train_metrics/Recall': 0.9777971506118774,\n",
       "   'train_metrics/JaccardIndex': 0.9731857776641846},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8297942876815796,\n",
       "   'valid_metrics/Accuracy': 0.9366338849067688,\n",
       "   'valid_metrics/Dice': 0.8297942876815796,\n",
       "   'valid_metrics/Precision': 0.8412363529205322,\n",
       "   'valid_metrics/Specificity': 0.9640694856643677,\n",
       "   'valid_metrics/Recall': 0.8186593055725098,\n",
       "   'valid_metrics/JaccardIndex': 0.8170796632766724}},\n",
       " {'tr_loss': 0.0013196241859726341,\n",
       "  'vl_loss': 0.016318962265625885,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9781962037086487,\n",
       "   'train_metrics/Accuracy': 0.9904747009277344,\n",
       "   'train_metrics/Dice': 0.9781962633132935,\n",
       "   'train_metrics/Precision': 0.978864848613739,\n",
       "   'train_metrics/Specificity': 0.994096040725708,\n",
       "   'train_metrics/Recall': 0.9775285124778748,\n",
       "   'train_metrics/JaccardIndex': 0.9726046919822693},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8282564282417297,\n",
       "   'valid_metrics/Accuracy': 0.9359491467475891,\n",
       "   'valid_metrics/Dice': 0.8282564282417297,\n",
       "   'valid_metrics/Precision': 0.8381692171096802,\n",
       "   'valid_metrics/Specificity': 0.963245153427124,\n",
       "   'valid_metrics/Recall': 0.8185753226280212,\n",
       "   'valid_metrics/JaccardIndex': 0.8155539035797119}},\n",
       " {'tr_loss': 0.001267699660225348,\n",
       "  'vl_loss': 0.016335538685551942,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9790773391723633,\n",
       "   'train_metrics/Accuracy': 0.990856409072876,\n",
       "   'train_metrics/Dice': 0.9790772795677185,\n",
       "   'train_metrics/Precision': 0.9794015288352966,\n",
       "   'train_metrics/Specificity': 0.9942418932914734,\n",
       "   'train_metrics/Recall': 0.9787532687187195,\n",
       "   'train_metrics/JaccardIndex': 0.9736899137496948},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8273597359657288,\n",
       "   'valid_metrics/Accuracy': 0.9361751079559326,\n",
       "   'valid_metrics/Dice': 0.8273597955703735,\n",
       "   'valid_metrics/Precision': 0.8448563814163208,\n",
       "   'valid_metrics/Specificity': 0.9653845429420471,\n",
       "   'valid_metrics/Recall': 0.810573160648346,\n",
       "   'valid_metrics/JaccardIndex': 0.815102219581604}},\n",
       " {'tr_loss': 0.0012613139400058542,\n",
       "  'vl_loss': 0.016043562571514527,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9791017770767212,\n",
       "   'train_metrics/Accuracy': 0.9908707141876221,\n",
       "   'train_metrics/Dice': 0.9791017770767212,\n",
       "   'train_metrics/Precision': 0.9798208475112915,\n",
       "   'train_metrics/Specificity': 0.9943636059761047,\n",
       "   'train_metrics/Recall': 0.9783837199211121,\n",
       "   'train_metrics/JaccardIndex': 0.9737231731414795},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8288258910179138,\n",
       "   'valid_metrics/Accuracy': 0.9365025162696838,\n",
       "   'valid_metrics/Dice': 0.8288258910179138,\n",
       "   'valid_metrics/Precision': 0.8433824777603149,\n",
       "   'valid_metrics/Specificity': 0.9648136496543884,\n",
       "   'valid_metrics/Recall': 0.8147632479667664,\n",
       "   'valid_metrics/JaccardIndex': 0.8163280487060547}},\n",
       " {'tr_loss': 0.0012613433333673097,\n",
       "  'vl_loss': 0.016096887901482896,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9791277050971985,\n",
       "   'train_metrics/Accuracy': 0.9908831119537354,\n",
       "   'train_metrics/Dice': 0.9791277050971985,\n",
       "   'train_metrics/Precision': 0.9799492359161377,\n",
       "   'train_metrics/Specificity': 0.9944007396697998,\n",
       "   'train_metrics/Recall': 0.9783076047897339,\n",
       "   'train_metrics/JaccardIndex': 0.9737560749053955},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8291917443275452,\n",
       "   'valid_metrics/Accuracy': 0.9358951449394226,\n",
       "   'valid_metrics/Dice': 0.8291917443275452,\n",
       "   'valid_metrics/Precision': 0.8337509036064148,\n",
       "   'valid_metrics/Specificity': 0.9617583751678467,\n",
       "   'valid_metrics/Recall': 0.8246822357177734,\n",
       "   'valid_metrics/JaccardIndex': 0.8161520957946777}},\n",
       " {'tr_loss': 0.0012348219372598922,\n",
       "  'vl_loss': 0.01621054343044988,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9795286655426025,\n",
       "   'train_metrics/Accuracy': 0.9910524487495422,\n",
       "   'train_metrics/Dice': 0.9795287847518921,\n",
       "   'train_metrics/Precision': 0.9797132611274719,\n",
       "   'train_metrics/Specificity': 0.9943275451660156,\n",
       "   'train_metrics/Recall': 0.9793442487716675,\n",
       "   'train_metrics/JaccardIndex': 0.9742470979690552},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8283446431159973,\n",
       "   'valid_metrics/Accuracy': 0.9367673397064209,\n",
       "   'valid_metrics/Dice': 0.8283447027206421,\n",
       "   'valid_metrics/Precision': 0.8490552306175232,\n",
       "   'valid_metrics/Specificity': 0.966568648815155,\n",
       "   'valid_metrics/Recall': 0.8086204528808594,\n",
       "   'valid_metrics/JaccardIndex': 0.816184937953949}},\n",
       " {'tr_loss': 0.0012641669623040628,\n",
       "  'vl_loss': 0.01621364223911035,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9790633916854858,\n",
       "   'train_metrics/Accuracy': 0.990854799747467,\n",
       "   'train_metrics/Dice': 0.9790633916854858,\n",
       "   'train_metrics/Precision': 0.9798682928085327,\n",
       "   'train_metrics/Specificity': 0.9943779110908508,\n",
       "   'train_metrics/Recall': 0.9782597422599792,\n",
       "   'train_metrics/JaccardIndex': 0.9736764430999756},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8288331627845764,\n",
       "   'valid_metrics/Accuracy': 0.9355939626693726,\n",
       "   'valid_metrics/Dice': 0.8288331031799316,\n",
       "   'valid_metrics/Precision': 0.8312166929244995,\n",
       "   'valid_metrics/Specificity': 0.9609729647636414,\n",
       "   'valid_metrics/Recall': 0.8264632225036621,\n",
       "   'valid_metrics/JaccardIndex': 0.8156969547271729}},\n",
       " {'tr_loss': 0.001229512376438816,\n",
       "  'vl_loss': 0.016490513868773767,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9796010851860046,\n",
       "   'train_metrics/Accuracy': 0.9910867214202881,\n",
       "   'train_metrics/Dice': 0.9796010851860046,\n",
       "   'train_metrics/Precision': 0.9800828099250793,\n",
       "   'train_metrics/Specificity': 0.9944342374801636,\n",
       "   'train_metrics/Recall': 0.9791197776794434,\n",
       "   'train_metrics/JaccardIndex': 0.9743388295173645},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8287786841392517,\n",
       "   'valid_metrics/Accuracy': 0.9359085559844971,\n",
       "   'valid_metrics/Dice': 0.8287786841392517,\n",
       "   'valid_metrics/Precision': 0.8355551958084106,\n",
       "   'valid_metrics/Specificity': 0.9623727202415466,\n",
       "   'valid_metrics/Recall': 0.8221112489700317,\n",
       "   'valid_metrics/JaccardIndex': 0.815880537033081}},\n",
       " {'tr_loss': 0.0012228142044227314,\n",
       "  'vl_loss': 0.016433369353931384,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9799561500549316,\n",
       "   'train_metrics/Accuracy': 0.9912440180778503,\n",
       "   'train_metrics/Dice': 0.9799561500549316,\n",
       "   'train_metrics/Precision': 0.9806824922561646,\n",
       "   'train_metrics/Specificity': 0.9946044087409973,\n",
       "   'train_metrics/Recall': 0.9792308807373047,\n",
       "   'train_metrics/JaccardIndex': 0.9747797846794128},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8292648792266846,\n",
       "   'valid_metrics/Accuracy': 0.9364700317382812,\n",
       "   'valid_metrics/Dice': 0.8292648792266846,\n",
       "   'valid_metrics/Precision': 0.8411524295806885,\n",
       "   'valid_metrics/Specificity': 0.9640886783599854,\n",
       "   'valid_metrics/Recall': 0.8177086710929871,\n",
       "   'valid_metrics/JaccardIndex': 0.8166043758392334}},\n",
       " {'tr_loss': 0.0011978704076947915,\n",
       "  'vl_loss': 0.016478722332527278,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9802000522613525,\n",
       "   'train_metrics/Accuracy': 0.9913482069969177,\n",
       "   'train_metrics/Dice': 0.9801999926567078,\n",
       "   'train_metrics/Precision': 0.9806650280952454,\n",
       "   'train_metrics/Specificity': 0.9945966601371765,\n",
       "   'train_metrics/Recall': 0.9797354936599731,\n",
       "   'train_metrics/JaccardIndex': 0.9750797152519226},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8296006917953491,\n",
       "   'valid_metrics/Accuracy': 0.9366537928581238,\n",
       "   'valid_metrics/Dice': 0.8296006321907043,\n",
       "   'valid_metrics/Precision': 0.8422975540161133,\n",
       "   'valid_metrics/Specificity': 0.964414656162262,\n",
       "   'valid_metrics/Recall': 0.8172808289527893,\n",
       "   'valid_metrics/JaccardIndex': 0.8169615864753723}},\n",
       " {'tr_loss': 0.00118646753423388,\n",
       "  'vl_loss': 0.016529933135942143,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9803180694580078,\n",
       "   'train_metrics/Accuracy': 0.9913989305496216,\n",
       "   'train_metrics/Dice': 0.9803180694580078,\n",
       "   'train_metrics/Precision': 0.9806708097457886,\n",
       "   'train_metrics/Specificity': 0.9945970773696899,\n",
       "   'train_metrics/Recall': 0.9799655675888062,\n",
       "   'train_metrics/JaccardIndex': 0.9752250909805298},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8287791013717651,\n",
       "   'valid_metrics/Accuracy': 0.9365522861480713,\n",
       "   'valid_metrics/Dice': 0.8287791013717651,\n",
       "   'valid_metrics/Precision': 0.8442597985267639,\n",
       "   'valid_metrics/Specificity': 0.965086042881012,\n",
       "   'valid_metrics/Recall': 0.8138558268547058,\n",
       "   'valid_metrics/JaccardIndex': 0.8163309097290039}},\n",
       " {'tr_loss': 0.001184011272798721,\n",
       "  'vl_loss': 0.016438354396451853,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9804900288581848,\n",
       "   'train_metrics/Accuracy': 0.991474986076355,\n",
       "   'train_metrics/Dice': 0.9804900884628296,\n",
       "   'train_metrics/Precision': 0.9809499979019165,\n",
       "   'train_metrics/Specificity': 0.9946762323379517,\n",
       "   'train_metrics/Recall': 0.9800304770469666,\n",
       "   'train_metrics/JaccardIndex': 0.9754388928413391},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8283637762069702,\n",
       "   'valid_metrics/Accuracy': 0.9364922046661377,\n",
       "   'valid_metrics/Dice': 0.8283637166023254,\n",
       "   'valid_metrics/Precision': 0.8451317548751831,\n",
       "   'valid_metrics/Specificity': 0.9653858542442322,\n",
       "   'valid_metrics/Recall': 0.812248170375824,\n",
       "   'valid_metrics/JaccardIndex': 0.8160061836242676}},\n",
       " {'tr_loss': 0.0011809820622287834,\n",
       "  'vl_loss': 0.016431612110045887,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9804274439811707,\n",
       "   'train_metrics/Accuracy': 0.9914488792419434,\n",
       "   'train_metrics/Dice': 0.9804273843765259,\n",
       "   'train_metrics/Precision': 0.9810388088226318,\n",
       "   'train_metrics/Specificity': 0.9947026371955872,\n",
       "   'train_metrics/Recall': 0.979816734790802,\n",
       "   'train_metrics/JaccardIndex': 0.9753623008728027},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8283008337020874,\n",
       "   'valid_metrics/Accuracy': 0.9357685446739197,\n",
       "   'valid_metrics/Dice': 0.8283008337020874,\n",
       "   'valid_metrics/Precision': 0.8355878591537476,\n",
       "   'valid_metrics/Specificity': 0.9624261260032654,\n",
       "   'valid_metrics/Recall': 0.8211397528648376,\n",
       "   'valid_metrics/JaccardIndex': 0.8154577016830444}},\n",
       " {'tr_loss': 0.0011570220412917373,\n",
       "  'vl_loss': 0.016824509473841162,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9808029532432556,\n",
       "   'train_metrics/Accuracy': 0.9916118383407593,\n",
       "   'train_metrics/Dice': 0.9808030128479004,\n",
       "   'train_metrics/Precision': 0.9812803864479065,\n",
       "   'train_metrics/Specificity': 0.9947687387466431,\n",
       "   'train_metrics/Recall': 0.9803260564804077,\n",
       "   'train_metrics/JaccardIndex': 0.9758266806602478},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8294187188148499,\n",
       "   'valid_metrics/Accuracy': 0.936390221118927,\n",
       "   'valid_metrics/Dice': 0.8294187188148499,\n",
       "   'valid_metrics/Precision': 0.8394479751586914,\n",
       "   'valid_metrics/Specificity': 0.9635443687438965,\n",
       "   'valid_metrics/Recall': 0.8196262717247009,\n",
       "   'valid_metrics/JaccardIndex': 0.8166533708572388}},\n",
       " {'tr_loss': 0.0012886824322346157,\n",
       "  'vl_loss': 0.016636047756809987,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9797447919845581,\n",
       "   'train_metrics/Accuracy': 0.9911571741104126,\n",
       "   'train_metrics/Dice': 0.9797448515892029,\n",
       "   'train_metrics/Precision': 0.9810726046562195,\n",
       "   'train_metrics/Specificity': 0.9947198629379272,\n",
       "   'train_metrics/Recall': 0.9784207344055176,\n",
       "   'train_metrics/JaccardIndex': 0.9745227694511414},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8293997049331665,\n",
       "   'valid_metrics/Accuracy': 0.936744749546051,\n",
       "   'valid_metrics/Dice': 0.8293996453285217,\n",
       "   'valid_metrics/Precision': 0.8443726301193237,\n",
       "   'valid_metrics/Specificity': 0.9650691747665405,\n",
       "   'valid_metrics/Recall': 0.8149484395980835,\n",
       "   'valid_metrics/JaccardIndex': 0.8168880939483643}},\n",
       " {'tr_loss': 0.0012045995914697976,\n",
       "  'vl_loss': 0.01628815057655099,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9801392555236816,\n",
       "   'train_metrics/Accuracy': 0.9913181066513062,\n",
       "   'train_metrics/Dice': 0.9801392555236816,\n",
       "   'train_metrics/Precision': 0.9801942110061646,\n",
       "   'train_metrics/Specificity': 0.99446040391922,\n",
       "   'train_metrics/Recall': 0.9800843000411987,\n",
       "   'train_metrics/JaccardIndex': 0.9750015735626221},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.829348087310791,\n",
       "   'valid_metrics/Accuracy': 0.9365156888961792,\n",
       "   'valid_metrics/Dice': 0.8293481469154358,\n",
       "   'valid_metrics/Precision': 0.841436505317688,\n",
       "   'valid_metrics/Specificity': 0.9641696810722351,\n",
       "   'valid_metrics/Recall': 0.8176022171974182,\n",
       "   'valid_metrics/JaccardIndex': 0.8166929483413696}},\n",
       " {'tr_loss': 0.001162943803287078,\n",
       "  'vl_loss': 0.01659223678949717,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9807995557785034,\n",
       "   'train_metrics/Accuracy': 0.9916088581085205,\n",
       "   'train_metrics/Dice': 0.9807996153831482,\n",
       "   'train_metrics/Precision': 0.9811015129089355,\n",
       "   'train_metrics/Specificity': 0.9947169423103333,\n",
       "   'train_metrics/Recall': 0.9804978370666504,\n",
       "   'train_metrics/JaccardIndex': 0.9758213758468628},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8281336426734924,\n",
       "   'valid_metrics/Accuracy': 0.9359287619590759,\n",
       "   'valid_metrics/Dice': 0.8281337022781372,\n",
       "   'valid_metrics/Precision': 0.8383851051330566,\n",
       "   'valid_metrics/Specificity': 0.9633235335350037,\n",
       "   'valid_metrics/Recall': 0.8181299567222595,\n",
       "   'valid_metrics/JaccardIndex': 0.8154562711715698}},\n",
       " {'tr_loss': 0.0011544584083696698,\n",
       "  'vl_loss': 0.01654806244097161,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9809106588363647,\n",
       "   'train_metrics/Accuracy': 0.9916579723358154,\n",
       "   'train_metrics/Dice': 0.9809107780456543,\n",
       "   'train_metrics/Precision': 0.9812789559364319,\n",
       "   'train_metrics/Specificity': 0.9947671890258789,\n",
       "   'train_metrics/Recall': 0.980542778968811,\n",
       "   'train_metrics/JaccardIndex': 0.9759594202041626},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8283892273902893,\n",
       "   'valid_metrics/Accuracy': 0.9363078474998474,\n",
       "   'valid_metrics/Dice': 0.8283892273902893,\n",
       "   'valid_metrics/Precision': 0.8424904942512512,\n",
       "   'valid_metrics/Specificity': 0.964576244354248,\n",
       "   'valid_metrics/Recall': 0.8147522807121277,\n",
       "   'valid_metrics/JaccardIndex': 0.8158948421478271}},\n",
       " {'tr_loss': 0.0011562536627095265,\n",
       "  'vl_loss': 0.016570268680690337,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9808899164199829,\n",
       "   'train_metrics/Accuracy': 0.9916493892669678,\n",
       "   'train_metrics/Dice': 0.9808899164199829,\n",
       "   'train_metrics/Precision': 0.9813070297241211,\n",
       "   'train_metrics/Specificity': 0.994775652885437,\n",
       "   'train_metrics/Recall': 0.9804731607437134,\n",
       "   'train_metrics/JaccardIndex': 0.9759340286254883},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8282091617584229,\n",
       "   'valid_metrics/Accuracy': 0.9357145428657532,\n",
       "   'valid_metrics/Dice': 0.8282091617584229,\n",
       "   'valid_metrics/Precision': 0.8352346420288086,\n",
       "   'valid_metrics/Specificity': 0.9623221158981323,\n",
       "   'valid_metrics/Recall': 0.8213008642196655,\n",
       "   'valid_metrics/JaccardIndex': 0.8153576254844666}},\n",
       " {'tr_loss': 0.0011351272905086355,\n",
       "  'vl_loss': 0.016733006045625016,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9812710285186768,\n",
       "   'train_metrics/Accuracy': 0.9918183088302612,\n",
       "   'train_metrics/Dice': 0.9812712073326111,\n",
       "   'train_metrics/Precision': 0.9819777011871338,\n",
       "   'train_metrics/Specificity': 0.9949660301208496,\n",
       "   'train_metrics/Recall': 0.9805654883384705,\n",
       "   'train_metrics/JaccardIndex': 0.9764086604118347},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8285515904426575,\n",
       "   'valid_metrics/Accuracy': 0.9357399940490723,\n",
       "   'valid_metrics/Dice': 0.8285515904426575,\n",
       "   'valid_metrics/Precision': 0.8342244029045105,\n",
       "   'valid_metrics/Specificity': 0.961968719959259,\n",
       "   'valid_metrics/Recall': 0.8229554295539856,\n",
       "   'valid_metrics/JaccardIndex': 0.8156081438064575}},\n",
       " {'tr_loss': 0.0011371393367319725,\n",
       "  'vl_loss': 0.016657578093664988,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9811940789222717,\n",
       "   'train_metrics/Accuracy': 0.9917823672294617,\n",
       "   'train_metrics/Dice': 0.9811940789222717,\n",
       "   'train_metrics/Precision': 0.9816269278526306,\n",
       "   'train_metrics/Specificity': 0.9948651194572449,\n",
       "   'train_metrics/Recall': 0.9807615876197815,\n",
       "   'train_metrics/JaccardIndex': 0.976311206817627},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8293924927711487,\n",
       "   'valid_metrics/Accuracy': 0.9363639950752258,\n",
       "   'valid_metrics/Dice': 0.8293924331665039,\n",
       "   'valid_metrics/Precision': 0.8391995429992676,\n",
       "   'valid_metrics/Specificity': 0.9634688496589661,\n",
       "   'valid_metrics/Recall': 0.8198118805885315,\n",
       "   'valid_metrics/JaccardIndex': 0.8166170120239258}},\n",
       " {'tr_loss': 0.001130477373408713,\n",
       "  'vl_loss': 0.016650309146140994,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9813108444213867,\n",
       "   'train_metrics/Accuracy': 0.991833508014679,\n",
       "   'train_metrics/Dice': 0.9813107848167419,\n",
       "   'train_metrics/Precision': 0.9817531108856201,\n",
       "   'train_metrics/Specificity': 0.9949005246162415,\n",
       "   'train_metrics/Recall': 0.9808688759803772,\n",
       "   'train_metrics/JaccardIndex': 0.9764560461044312},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8293028473854065,\n",
       "   'valid_metrics/Accuracy': 0.9364510178565979,\n",
       "   'valid_metrics/Dice': 0.8293028473854065,\n",
       "   'valid_metrics/Precision': 0.840739905834198,\n",
       "   'valid_metrics/Specificity': 0.9639573097229004,\n",
       "   'valid_metrics/Recall': 0.8181727528572083,\n",
       "   'valid_metrics/JaccardIndex': 0.8166168928146362}},\n",
       " {'tr_loss': 0.0011348434141516357,\n",
       "  'vl_loss': 0.01666742010926648,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9811977744102478,\n",
       "   'train_metrics/Accuracy': 0.9917810559272766,\n",
       "   'train_metrics/Dice': 0.9811977744102478,\n",
       "   'train_metrics/Precision': 0.981278657913208,\n",
       "   'train_metrics/Specificity': 0.9947640299797058,\n",
       "   'train_metrics/Recall': 0.9811169505119324,\n",
       "   'train_metrics/JaccardIndex': 0.9763134121894836},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8292105793952942,\n",
       "   'valid_metrics/Accuracy': 0.9367236495018005,\n",
       "   'valid_metrics/Dice': 0.8292105793952942,\n",
       "   'valid_metrics/Precision': 0.8448582887649536,\n",
       "   'valid_metrics/Specificity': 0.9652330875396729,\n",
       "   'valid_metrics/Recall': 0.8141319751739502,\n",
       "   'valid_metrics/JaccardIndex': 0.8167444467544556}},\n",
       " {'tr_loss': 0.001144344154899278,\n",
       "  'vl_loss': 0.016817803030768876,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9811221361160278,\n",
       "   'train_metrics/Accuracy': 0.991752564907074,\n",
       "   'train_metrics/Dice': 0.9811221361160278,\n",
       "   'train_metrics/Precision': 0.9817528128623962,\n",
       "   'train_metrics/Specificity': 0.9949024319648743,\n",
       "   'train_metrics/Recall': 0.9804922342300415,\n",
       "   'train_metrics/JaccardIndex': 0.976223349571228},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.828454315662384,\n",
       "   'valid_metrics/Accuracy': 0.9361191987991333,\n",
       "   'valid_metrics/Dice': 0.8284543752670288,\n",
       "   'valid_metrics/Precision': 0.8396646976470947,\n",
       "   'valid_metrics/Specificity': 0.9636956453323364,\n",
       "   'valid_metrics/Recall': 0.817539393901825,\n",
       "   'valid_metrics/JaccardIndex': 0.8158074021339417}},\n",
       " {'tr_loss': 0.0011179101168493594,\n",
       "  'vl_loss': 0.016663756437283225,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9814913868904114,\n",
       "   'train_metrics/Accuracy': 0.9919118285179138,\n",
       "   'train_metrics/Dice': 0.9814913868904114,\n",
       "   'train_metrics/Precision': 0.9818777441978455,\n",
       "   'train_metrics/Specificity': 0.9949347972869873,\n",
       "   'train_metrics/Recall': 0.9811053276062012,\n",
       "   'train_metrics/JaccardIndex': 0.9766796827316284},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8287800550460815,\n",
       "   'valid_metrics/Accuracy': 0.9358540773391724,\n",
       "   'valid_metrics/Dice': 0.8287800550460815,\n",
       "   'valid_metrics/Precision': 0.8348291516304016,\n",
       "   'valid_metrics/Specificity': 0.962141215801239,\n",
       "   'valid_metrics/Recall': 0.8228179812431335,\n",
       "   'valid_metrics/JaccardIndex': 0.8158433437347412}},\n",
       " {'tr_loss': 0.0011233903257273773,\n",
       "  'vl_loss': 0.016873747282967144,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.981415331363678,\n",
       "   'train_metrics/Accuracy': 0.9918761849403381,\n",
       "   'train_metrics/Dice': 0.981415331363678,\n",
       "   'train_metrics/Precision': 0.9815005660057068,\n",
       "   'train_metrics/Specificity': 0.9948261976242065,\n",
       "   'train_metrics/Recall': 0.981330156326294,\n",
       "   'train_metrics/JaccardIndex': 0.9765834212303162},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8287084102630615,\n",
       "   'valid_metrics/Accuracy': 0.9363219738006592,\n",
       "   'valid_metrics/Dice': 0.8287084102630615,\n",
       "   'valid_metrics/Precision': 0.8413898944854736,\n",
       "   'valid_metrics/Specificity': 0.9642096757888794,\n",
       "   'valid_metrics/Recall': 0.8164035677909851,\n",
       "   'valid_metrics/JaccardIndex': 0.8161219954490662}},\n",
       " {'tr_loss': 0.00116716138197535,\n",
       "  'vl_loss': 0.0165427984187962,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.980839729309082,\n",
       "   'train_metrics/Accuracy': 0.9916347861289978,\n",
       "   'train_metrics/Dice': 0.980839729309082,\n",
       "   'train_metrics/Precision': 0.9821242094039917,\n",
       "   'train_metrics/Specificity': 0.9950128197669983,\n",
       "   'train_metrics/Recall': 0.9795586466789246,\n",
       "   'train_metrics/JaccardIndex': 0.9758778214454651},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8295094966888428,\n",
       "   'valid_metrics/Accuracy': 0.9367759823799133,\n",
       "   'valid_metrics/Dice': 0.829509437084198,\n",
       "   'valid_metrics/Precision': 0.8443533778190613,\n",
       "   'valid_metrics/Specificity': 0.9650541543960571,\n",
       "   'valid_metrics/Recall': 0.8151784539222717,\n",
       "   'valid_metrics/JaccardIndex': 0.8169847726821899}},\n",
       " {'tr_loss': 0.001126695303733848,\n",
       "  'vl_loss': 0.01659724973573648,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.981434166431427,\n",
       "   'train_metrics/Accuracy': 0.9918834567070007,\n",
       "   'train_metrics/Dice': 0.981434166431427,\n",
       "   'train_metrics/Precision': 0.9814069271087646,\n",
       "   'train_metrics/Specificity': 0.9947987794876099,\n",
       "   'train_metrics/Recall': 0.9814614057540894,\n",
       "   'train_metrics/JaccardIndex': 0.9766058921813965},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.829578161239624,\n",
       "   'valid_metrics/Accuracy': 0.9366018772125244,\n",
       "   'valid_metrics/Dice': 0.8295782208442688,\n",
       "   'valid_metrics/Precision': 0.8416781425476074,\n",
       "   'valid_metrics/Specificity': 0.9642249345779419,\n",
       "   'valid_metrics/Recall': 0.817821204662323,\n",
       "   'valid_metrics/JaccardIndex': 0.8169099688529968}},\n",
       " {'tr_loss': 0.0011190321157909622,\n",
       "  'vl_loss': 0.016748742247180128,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9814960360527039,\n",
       "   'train_metrics/Accuracy': 0.9919151067733765,\n",
       "   'train_metrics/Dice': 0.9814960360527039,\n",
       "   'train_metrics/Precision': 0.9820189476013184,\n",
       "   'train_metrics/Specificity': 0.9949756264686584,\n",
       "   'train_metrics/Recall': 0.9809736609458923,\n",
       "   'train_metrics/JaccardIndex': 0.9766863584518433},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8278815746307373,\n",
       "   'valid_metrics/Accuracy': 0.9357523322105408,\n",
       "   'valid_metrics/Dice': 0.8278816342353821,\n",
       "   'valid_metrics/Precision': 0.8370288014411926,\n",
       "   'valid_metrics/Specificity': 0.9629195332527161,\n",
       "   'valid_metrics/Recall': 0.8189321756362915,\n",
       "   'valid_metrics/JaccardIndex': 0.8151615858078003}},\n",
       " {'tr_loss': 0.0011106026535930712,\n",
       "  'vl_loss': 0.017085141484341565,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9816203713417053,\n",
       "   'train_metrics/Accuracy': 0.9919705986976624,\n",
       "   'train_metrics/Dice': 0.9816203713417053,\n",
       "   'train_metrics/Precision': 0.9822908043861389,\n",
       "   'train_metrics/Specificity': 0.9950530529022217,\n",
       "   'train_metrics/Recall': 0.9809507727622986,\n",
       "   'train_metrics/JaccardIndex': 0.9768415689468384},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8284369111061096,\n",
       "   'valid_metrics/Accuracy': 0.9359728097915649,\n",
       "   'valid_metrics/Dice': 0.8284369111061096,\n",
       "   'valid_metrics/Precision': 0.8377665877342224,\n",
       "   'valid_metrics/Specificity': 0.9631027579307556,\n",
       "   'valid_metrics/Recall': 0.8193126916885376,\n",
       "   'valid_metrics/JaccardIndex': 0.8156931400299072}},\n",
       " {'tr_loss': 0.0011150824706539634,\n",
       "  'vl_loss': 0.01697015210008069,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9816861748695374,\n",
       "   'train_metrics/Accuracy': 0.9919945001602173,\n",
       "   'train_metrics/Dice': 0.9816862344741821,\n",
       "   'train_metrics/Precision': 0.9817629456520081,\n",
       "   'train_metrics/Specificity': 0.9948995113372803,\n",
       "   'train_metrics/Recall': 0.9816094636917114,\n",
       "   'train_metrics/JaccardIndex': 0.976919412612915},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8282469511032104,\n",
       "   'valid_metrics/Accuracy': 0.936138927936554,\n",
       "   'valid_metrics/Dice': 0.8282468914985657,\n",
       "   'valid_metrics/Precision': 0.8407654762268066,\n",
       "   'valid_metrics/Specificity': 0.9640556573867798,\n",
       "   'valid_metrics/Recall': 0.8160956501960754,\n",
       "   'valid_metrics/JaccardIndex': 0.8156800866127014}},\n",
       " {'tr_loss': 0.0010984098251406154,\n",
       "  'vl_loss': 0.01703694267162485,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.981825590133667,\n",
       "   'train_metrics/Accuracy': 0.9920580387115479,\n",
       "   'train_metrics/Dice': 0.981825590133667,\n",
       "   'train_metrics/Precision': 0.9822164177894592,\n",
       "   'train_metrics/Specificity': 0.9950294494628906,\n",
       "   'train_metrics/Recall': 0.9814350605010986,\n",
       "   'train_metrics/JaccardIndex': 0.9770944118499756},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.82912677526474,\n",
       "   'valid_metrics/Accuracy': 0.9365522861480713,\n",
       "   'valid_metrics/Dice': 0.82912677526474,\n",
       "   'valid_metrics/Precision': 0.842838704586029,\n",
       "   'valid_metrics/Specificity': 0.9646214246749878,\n",
       "   'valid_metrics/Recall': 0.8158538341522217,\n",
       "   'valid_metrics/JaccardIndex': 0.8165677189826965}},\n",
       " {'tr_loss': 0.0010861249455858854,\n",
       "  'vl_loss': 0.016909478714107085,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.981979489326477,\n",
       "   'train_metrics/Accuracy': 0.992124617099762,\n",
       "   'train_metrics/Dice': 0.981979489326477,\n",
       "   'train_metrics/Precision': 0.9822880029678345,\n",
       "   'train_metrics/Specificity': 0.9950487017631531,\n",
       "   'train_metrics/Recall': 0.981671154499054,\n",
       "   'train_metrics/JaccardIndex': 0.9772850275039673},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8292093276977539,\n",
       "   'valid_metrics/Accuracy': 0.9363325238227844,\n",
       "   'valid_metrics/Dice': 0.8292093276977539,\n",
       "   'valid_metrics/Precision': 0.8395111560821533,\n",
       "   'valid_metrics/Specificity': 0.9635822772979736,\n",
       "   'valid_metrics/Recall': 0.8191573023796082,\n",
       "   'valid_metrics/JaccardIndex': 0.8164703845977783}},\n",
       " {'tr_loss': 0.0010824975303628229,\n",
       "  'vl_loss': 0.016973103335465242,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.98215252161026,\n",
       "   'train_metrics/Accuracy': 0.9922003149986267,\n",
       "   'train_metrics/Dice': 0.9821525812149048,\n",
       "   'train_metrics/Precision': 0.9824772477149963,\n",
       "   'train_metrics/Specificity': 0.9951017498970032,\n",
       "   'train_metrics/Recall': 0.9818280935287476,\n",
       "   'train_metrics/JaccardIndex': 0.9775000810623169},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8291023373603821,\n",
       "   'valid_metrics/Accuracy': 0.9364065527915955,\n",
       "   'valid_metrics/Dice': 0.8291023373603821,\n",
       "   'valid_metrics/Precision': 0.840946614742279,\n",
       "   'valid_metrics/Specificity': 0.9640386700630188,\n",
       "   'valid_metrics/Recall': 0.81758713722229,\n",
       "   'valid_metrics/JaccardIndex': 0.8164492845535278}},\n",
       " {'tr_loss': 0.001096475887376579,\n",
       "  'vl_loss': 0.017114884834952337,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9818828105926514,\n",
       "   'train_metrics/Accuracy': 0.9920820593833923,\n",
       "   'train_metrics/Dice': 0.9818828701972961,\n",
       "   'train_metrics/Precision': 0.9821608066558838,\n",
       "   'train_metrics/Specificity': 0.9950128197669983,\n",
       "   'train_metrics/Recall': 0.981605052947998,\n",
       "   'train_metrics/JaccardIndex': 0.9771649241447449},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8283991813659668,\n",
       "   'valid_metrics/Accuracy': 0.9360781908035278,\n",
       "   'valid_metrics/Dice': 0.8283991813659668,\n",
       "   'valid_metrics/Precision': 0.8393329381942749,\n",
       "   'valid_metrics/Specificity': 0.9635968804359436,\n",
       "   'valid_metrics/Recall': 0.8177465796470642,\n",
       "   'valid_metrics/JaccardIndex': 0.8157411813735962}},\n",
       " {'tr_loss': 0.001099195881405481,\n",
       "  'vl_loss': 0.016846734699595387,\n",
       "  'tr_metrics': {'train_metrics/F1Score': 0.9818759560585022,\n",
       "   'train_metrics/Accuracy': 0.9920799136161804,\n",
       "   'train_metrics/Dice': 0.9818758964538574,\n",
       "   'train_metrics/Precision': 0.9822537302970886,\n",
       "   'train_metrics/Specificity': 0.9950398206710815,\n",
       "   'train_metrics/Recall': 0.9814983606338501,\n",
       "   'train_metrics/JaccardIndex': 0.9771568775177002},\n",
       "  'vl_metrics': {'valid_metrics/F1Score': 0.8281275629997253,\n",
       "   'valid_metrics/Accuracy': 0.9357014894485474,\n",
       "   'valid_metrics/Dice': 0.8281275629997253,\n",
       "   'valid_metrics/Precision': 0.8353829979896545,\n",
       "   'valid_metrics/Specificity': 0.9623766541481018,\n",
       "   'valid_metrics/Recall': 0.8209969997406006,\n",
       "   'valid_metrics/JaccardIndex': 0.8152930736541748}}]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "epochs_info"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "stunning-injection",
   "metadata": {},
   "source": [
    "## Save images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "crude-snake",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 33/33 [00:19<00:00,  1.72it/s]\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image\n",
    "import cv2\n",
    "def skin_plot(img, gt, pred):\n",
    "    img = np.array(img)\n",
    "    gt = np.array(gt)\n",
    "    pred = np.array(pred)\n",
    "    edged_test = cv2.Canny(pred, 100, 255)\n",
    "    contours_test, _ = cv2.findContours(edged_test, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n",
    "    edged_gt = cv2.Canny(gt, 100, 255)\n",
    "    contours_gt, _ = cv2.findContours(edged_gt, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n",
    "    for cnt_test in contours_test:\n",
    "        cv2.drawContours(img, [cnt_test], -1, (0, 0, 255), 1)\n",
    "    for cnt_gt in contours_gt:\n",
    "        cv2.drawContours(img, [cnt_gt], -1, (0,255,0), 1)\n",
    "    return img\n",
    "\n",
    "#---------------------------------------------------------------------------------------------\n",
    "\n",
    "\n",
    "save_imgs_dir = f\"{config['model']['save_dir']}/visualized\"\n",
    "\n",
    "if not os.path.isdir(save_imgs_dir):\n",
    "    os.mkdir(save_imgs_dir)\n",
    "\n",
    "with torch.no_grad():\n",
    "    for batch in tqdm(te_dataloader):\n",
    "        imgs = batch['image']\n",
    "        msks = batch['mask']\n",
    "        ids = batch['id']\n",
    "        \n",
    "        preds = best_model(imgs.to(device))\n",
    "        \n",
    "        txm = imgs.cpu().numpy()\n",
    "        tbm = torch.argmax(msks, 1).cpu().numpy()\n",
    "        tpm = torch.argmax(preds, 1).cpu().numpy()\n",
    "        tid = ids\n",
    "        \n",
    "        for idx in range(len(tbm)):\n",
    "            img = np.moveaxis(txm[idx, :3], 0, -1)*255.\n",
    "            img = np.ascontiguousarray(img, dtype=np.uint8)\n",
    "            gt = np.uint8(tbm[idx]*255.)\n",
    "            pred = np.where(tpm[idx]>0.5, 255, 0)\n",
    "            pred = np.ascontiguousarray(pred, dtype=np.uint8)\n",
    "            \n",
    "            res_img = skin_plot(img, gt, pred)\n",
    "            \n",
    "            fid = tid[idx]\n",
    "            Image.fromarray(img).save(f\"{save_imgs_dir}/{fid}_img.png\")\n",
    "            Image.fromarray(res_img).save(f\"{save_imgs_dir}/{fid}_img_gt_pred.png\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "interesting-modern",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'../saved_models/isic2018_resunet/visualized'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f\"{config['model']['save_dir']}/visualized\""
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}