{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spacer training Notebook\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:53:53.402352Z",
     "iopub.status.busy": "2026-05-22T00:53:53.402139Z",
     "iopub.status.idle": "2026-05-22T00:53:53.407402Z",
     "shell.execute_reply": "2026-05-22T00:53:53.406352Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "# ── Example data paths (swap these for your own files) ──────────────────────\n",
    "# Run `python create_example_data.py` once to generate the files below.\n",
    "\n",
    "GENE_CSV   = 'data/example_genes.csv'    # reference gene list (377 genes)\n",
    "ADATA_H5AD = 'data/example_spatial.h5ad' # 600 cells × 98 genes, spatial grid\n",
    "SAMPLE_CSV   = 'data/example_sample.csv'   # multi-sample CSV (points at h5ad above)\n",
    "IMMUNE_CELL = 'macrophage'  # 'tcell' | 'macrophage' | 'bcell' etc.\n",
    "\n",
    "# Synthetic label layout:\n",
    "#   T-cell     infiltration  → upper half  (Y < 200)\n",
    "#   Macrophage infiltration  → right half  (X > 190)\n",
    "#\n",
    "# To train on real data, replace the three variables above and set\n",
    "#   immune_cell, radius, resolution in the BagsDataset call below.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:53:53.408889Z",
     "iopub.status.busy": "2026-05-22T00:53:53.408686Z",
     "iopub.status.idle": "2026-05-22T00:53:58.857333Z",
     "shell.execute_reply": "2026-05-22T00:53:58.856661Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "import os\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scanpy as sc\n",
    "from torch.utils.data import DataLoader, random_split\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from tqdm import tqdm\n",
    "from model.dataset import BagsDataset, custom_collate_fn\n",
    "from model.model import MIL, EarlyStopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:53:58.860741Z",
     "iopub.status.busy": "2026-05-22T00:53:58.860308Z",
     "iopub.status.idle": "2026-05-22T00:53:58.863529Z",
     "shell.execute_reply": "2026-05-22T00:53:58.863097Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "def load_all_genes(reference_gene_file):\n",
    "    all_genes = pd.read_csv(reference_gene_file)\n",
    "    return all_genes['Gene'].values.tolist()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Load reference gene list\n",
    "all_genes = pd.read_csv(GENE_CSV)   # swap GENE_CSV for 'data/human_filtered.csv' on real data\n",
    "all_genes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:53:58.865286Z",
     "iopub.status.busy": "2026-05-22T00:53:58.865044Z",
     "iopub.status.idle": "2026-05-22T00:53:58.879231Z",
     "shell.execute_reply": "2026-05-22T00:53:58.878377Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TAP2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IFI6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TOP2A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PBK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TPX2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>GENE0295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>GENE0296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>GENE0297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>GENE0298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>GENE0299</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>377 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Gene\n",
       "0        TAP2\n",
       "1        IFI6\n",
       "2       TOP2A\n",
       "3         PBK\n",
       "4        TPX2\n",
       "..        ...\n",
       "372  GENE0295\n",
       "373  GENE0296\n",
       "374  GENE0297\n",
       "375  GENE0298\n",
       "376  GENE0299\n",
       "\n",
       "[377 rows x 1 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_genes = pd.read_csv(GENE_CSV)\n",
    "all_genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:53:58.906063Z",
     "iopub.status.busy": "2026-05-22T00:53:58.905791Z",
     "iopub.status.idle": "2026-05-22T00:53:58.908242Z",
     "shell.execute_reply": "2026-05-22T00:53:58.907842Z"
    }
   },
   "outputs": [],
   "source": [
    "all_genes = all_genes['Gene'].values.tolist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ── Option A: single AnnData file ───────────────────────────────────────────\n",
    "adata = sc.read_h5ad(ADATA_H5AD)\n",
    "dataset = BagsDataset(\n",
    "    adata,\n",
    "    immune_cell=IMMUNE_CELL,\n",
    "    radius=50,\n",
    "    max_instances=500,\n",
    "    n_genes=500,\n",
    "    resolution='low',\n",
    "    k=2,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:53:58.909885Z",
     "iopub.status.busy": "2026-05-22T00:53:58.909654Z",
     "iopub.status.idle": "2026-05-22T00:54:09.885955Z",
     "shell.execute_reply": "2026-05-22T00:54:09.884655Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Immune cell: T\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 0 2]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tumor cells shape after filtering: (27567, 18085)\n",
      "Selecting top 3000 genes based on mean expression\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/work/DPDS/s439765/envs/spatial_tcr/lib/python3.9/site-packages/anndata/_core/anndata.py:1820: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "  utils.warn_names_duplicates(\"var\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tumor_cells.obs[T] is already binary. Skipping binarization.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/work/DPDS/s439765/envs/spatial_tcr/lib/python3.9/site-packages/anndata/_core/anndata.py:1820: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "  utils.warn_names_duplicates(\"var\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preprocessed data: (52518, 3056)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   0%|                                       | 0/52518 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   1%|▎                          | 612/52518 [00:00<00:08, 6105.43it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   2%|▌                         | 1249/52518 [00:00<00:08, 6255.78it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   4%|▉                         | 1898/52518 [00:00<00:07, 6357.64it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   5%|█▎                        | 2534/52518 [00:00<00:08, 6015.56it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   6%|█▌                        | 3145/52518 [00:00<00:08, 6043.88it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   7%|█▊                        | 3753/52518 [00:00<00:08, 6049.80it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   8%|██▏                       | 4360/52518 [00:00<00:08, 6005.99it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   9%|██▍                       | 4965/52518 [00:00<00:07, 6015.95it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  11%|██▊                       | 5617/52518 [00:00<00:07, 6170.74it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  12%|███                       | 6235/52518 [00:01<00:07, 6079.43it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  13%|███▍                      | 6844/52518 [00:01<00:07, 6051.75it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  14%|███▋                      | 7450/52518 [00:01<00:07, 6003.34it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  15%|███▉                      | 8051/52518 [00:01<00:07, 5936.61it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  16%|████▎                     | 8648/52518 [00:01<00:07, 5941.93it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  18%|████▌                     | 9266/52518 [00:01<00:07, 6010.63it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  19%|████▉                     | 9868/52518 [00:01<00:07, 5917.79it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  20%|████▉                    | 10463/52518 [00:01<00:07, 5925.04it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  21%|█████▎                   | 11057/52518 [00:01<00:06, 5924.04it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  22%|█████▌                   | 11663/52518 [00:01<00:06, 5963.54it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  23%|█████▊                   | 12261/52518 [00:02<00:06, 5965.52it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  24%|██████                   | 12858/52518 [00:02<00:06, 5952.41it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  26%|██████▍                  | 13454/52518 [00:02<00:06, 5931.40it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  27%|██████▋                  | 14048/52518 [00:02<00:06, 5885.96it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  28%|██████▉                  | 14643/52518 [00:02<00:06, 5904.41it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  29%|███████▎                 | 15257/52518 [00:02<00:06, 5970.72it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  30%|███████▌                 | 15855/52518 [00:02<00:06, 5919.82it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  31%|███████▊                 | 16466/52518 [00:02<00:06, 5971.80it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  33%|████████▏                | 17105/52518 [00:02<00:05, 6095.00it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  34%|████████▍                | 17741/52518 [00:02<00:05, 6171.41it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  35%|████████▋                | 18359/52518 [00:03<00:05, 6037.51it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  36%|█████████                | 18964/52518 [00:03<00:05, 6004.10it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  37%|█████████▎               | 19565/52518 [00:03<00:05, 5978.02it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  38%|█████████▌               | 20180/52518 [00:03<00:05, 6027.21it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  40%|█████████▉               | 20794/52518 [00:03<00:05, 6055.32it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  41%|██████████▏              | 21405/52518 [00:03<00:05, 6070.15it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  42%|██████████▍              | 22013/52518 [00:03<00:05, 5967.59it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  43%|██████████▊              | 22615/52518 [00:03<00:05, 5980.29it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  44%|███████████              | 23214/52518 [00:03<00:04, 5957.57it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  45%|███████████▎             | 23810/52518 [00:03<00:04, 5951.49it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  47%|███████████▋             | 24426/52518 [00:04<00:04, 6010.55it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  48%|███████████▉             | 25028/52518 [00:04<00:04, 5953.89it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  49%|████████████▏            | 25648/52518 [00:04<00:04, 6023.35it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  50%|████████████▍            | 26251/52518 [00:04<00:04, 5922.35it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  51%|████████████▊            | 26844/52518 [00:04<00:04, 5872.38it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  52%|█████████████            | 27453/52518 [00:04<00:04, 5931.17it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  53%|█████████████▎           | 28047/52518 [00:04<00:04, 5866.21it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  55%|█████████████▋           | 28634/52518 [00:04<00:04, 5843.88it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  56%|█████████████▉           | 29238/52518 [00:04<00:03, 5901.20it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  57%|██████████████▏          | 29861/52518 [00:04<00:03, 5997.96it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  58%|██████████████▌          | 30464/52518 [00:05<00:03, 6003.93it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  59%|██████████████▊          | 31091/52518 [00:05<00:03, 6082.78it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  60%|███████████████          | 31700/52518 [00:05<00:03, 6080.99it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  62%|███████████████▍         | 32309/52518 [00:05<00:03, 6029.88it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  63%|███████████████▋         | 32913/52518 [00:05<00:03, 6002.50it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  64%|███████████████▉         | 33514/52518 [00:05<00:03, 5955.16it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  65%|████████████████▏        | 34111/52518 [00:05<00:03, 5958.49it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  66%|████████████████▌        | 34716/52518 [00:05<00:02, 5984.57it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  67%|████████████████▊        | 35320/52518 [00:05<00:02, 5999.21it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  68%|█████████████████        | 35920/52518 [00:05<00:02, 5974.00it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  70%|█████████████████▍       | 36534/52518 [00:06<00:02, 6020.07it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  71%|█████████████████▋       | 37165/52518 [00:06<00:02, 6102.28it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  72%|█████████████████▉       | 37776/52518 [00:06<00:02, 6011.79it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  73%|██████████████████▎      | 38378/52518 [00:06<00:03, 4313.65it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  74%|██████████████████▌      | 38977/52518 [00:06<00:02, 4701.99it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  75%|██████████████████▊      | 39633/52518 [00:06<00:02, 5162.20it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  77%|███████████████████▏     | 40264/52518 [00:06<00:02, 5461.95it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  78%|███████████████████▍     | 40886/52518 [00:06<00:02, 5664.57it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  79%|███████████████████▊     | 41506/52518 [00:07<00:01, 5809.11it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  80%|████████████████████     | 42109/52518 [00:07<00:01, 5800.43it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  81%|████████████████████▎    | 42705/52518 [00:07<00:01, 5829.18it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  83%|████████████████████▋    | 43328/52518 [00:07<00:01, 5941.20it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  84%|████████████████████▉    | 43939/52518 [00:07<00:01, 5989.62it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  85%|█████████████████████▏   | 44544/52518 [00:07<00:01, 5943.47it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  86%|█████████████████████▍   | 45143/52518 [00:07<00:01, 5911.50it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  87%|█████████████████████▊   | 45737/52518 [00:07<00:01, 5837.05it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  88%|██████████████████████   | 46336/52518 [00:07<00:01, 5880.04it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  89%|██████████████████████▎  | 46944/52518 [00:07<00:00, 5934.82it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  91%|██████████████████████▋  | 47556/52518 [00:08<00:00, 5986.05it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  92%|██████████████████████▉  | 48163/52518 [00:08<00:00, 6008.05it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  93%|███████████████████████▏ | 48803/52518 [00:08<00:00, 6119.82it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  94%|███████████████████████▌ | 49417/52518 [00:08<00:00, 6125.66it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  95%|███████████████████████▊ | 50030/52518 [00:08<00:00, 5923.41it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  96%|████████████████████████ | 50624/52518 [00:08<00:00, 5871.57it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  98%|████████████████████████▍| 51247/52518 [00:08<00:00, 5974.14it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:  99%|████████████████████████▋| 51868/52518 [00:08<00:00, 6042.09it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50: 100%|████████████████████████▉| 52474/52518 [00:08<00:00, 6041.79it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50: 100%|█████████████████████████| 52518/52518 [00:08<00:00, 5917.07it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total batches created: 603\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# Load dataset and create DataLoader(details data structure in data preparation section)\n",
    "adata = sc.read_h5ad('data/example_data.h5ad')\n",
    "dataset = BagsDataset(\n",
    "    adata,\n",
    "    immune_cell='tcell',\n",
    "    radius=50,\n",
    "    max_instances=500,\n",
    "    n_genes=3000,\n",
    "    resolution='low',\n",
    "    k=2,  # Ensure 'k' matches the number of bags per batch\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to run the model for multiple datasets jointly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# ── Option B: multi-sample CSV ───────────────────────────────────────────────\n",
    "adatas = pd.read_csv(SAMPLE_CSV)\n",
    "adatas  # make sure columns are: adata, radius, resolution\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:09.888541Z",
     "iopub.status.busy": "2026-05-22T00:54:09.888293Z",
     "iopub.status.idle": "2026-05-22T00:54:09.896761Z",
     "shell.execute_reply": "2026-05-22T00:54:09.895893Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adata</th>\n",
       "      <th>radius</th>\n",
       "      <th>resolution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>data/example_spatial.h5ad</td>\n",
       "      <td>50</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>data/example_spatial.h5ad</td>\n",
       "      <td>50</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       adata  radius resolution\n",
       "0  data/example_spatial.h5ad      50        low\n",
       "1  data/example_spatial.h5ad      50        low"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ── Option B: multi-sample CSV ─────────────────────────────────────────────\n",
    "adatas = pd.read_csv(SAMPLE_CSV)\n",
    "adatas  # make sure columns are: adata, radius, resolution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:09.899079Z",
     "iopub.status.busy": "2026-05-22T00:54:09.898839Z",
     "iopub.status.idle": "2026-05-22T00:54:10.030576Z",
     "shell.execute_reply": "2026-05-22T00:54:10.030083Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/work/DPDS/s439765/envs/spatial_tcr/lib/python3.9/site-packages/anndata/_core/anndata.py:1820: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "  utils.warn_names_duplicates(\"var\")\n",
      "/work/DPDS/s439765/envs/spatial_tcr/lib/python3.9/site-packages/anndata/_core/anndata.py:1820: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "  utils.warn_names_duplicates(\"var\")\n",
      "/work/DPDS/s439765/envs/spatial_tcr/lib/python3.9/site-packages/anndata/_core/anndata.py:1820: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "  utils.warn_names_duplicates(\"var\")\n",
      "/work/DPDS/s439765/envs/spatial_tcr/lib/python3.9/site-packages/anndata/_core/anndata.py:1820: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "  utils.warn_names_duplicates(\"var\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Immune cell: Macrophage\n",
      "Reading adata from data/example_spatial.h5ad\n",
      "[1 0]\n",
      "Tumor cells shape after filtering: (400, 98)\n",
      "Selecting top 500 genes based on mean expression\n",
      "tumor_cells.obs[Macrophage] is already binary. Skipping binarization.\n",
      "Processing: adata=example_spatial.h5ad, radius=50, resolution=low\n",
      "Reading adata from data/example_spatial.h5ad\n",
      "[1 0]\n",
      "Tumor cells shape after filtering: (400, 98)\n",
      "Selecting top 500 genes based on mean expression\n",
      "tumor_cells.obs[Macrophage] is already binary. Skipping binarization.\n",
      "Processing: adata=example_spatial.h5ad, radius=50, resolution=low\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   0%|                                         | 0/600 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50: 100%|████████████████████████████| 600/600 [00:00<00:00, 13481.96it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50:   0%|                                         | 0/600 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Creating Bags with radius 50: 100%|████████████████████████████| 600/600 [00:00<00:00, 13821.22it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total batches created: 360\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "dataset = BagsDataset(\n",
    "    SAMPLE_CSV,\n",
    "    immune_cell=IMMUNE_CELL,\n",
    "    max_instances=500,\n",
    "    n_genes=500,\n",
    "    k=2,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:10.032976Z",
     "iopub.status.busy": "2026-05-22T00:54:10.032776Z",
     "iopub.status.idle": "2026-05-22T00:54:10.047849Z",
     "shell.execute_reply": "2026-05-22T00:54:10.047414Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using device: cpu\n",
      "=====================================\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "if device.type == \"cuda\":\n",
    "    print(f\"Using device: {device} ({torch.cuda.get_device_name(torch.cuda.current_device())})\")\n",
    "else:\n",
    "    print(f\"Using device: {device}\")\n",
    "print(\"=====================================\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:10.049958Z",
     "iopub.status.busy": "2026-05-22T00:54:10.049715Z",
     "iopub.status.idle": "2026-05-22T00:54:12.479085Z",
     "shell.execute_reply": "2026-05-22T00:54:12.478337Z"
    }
   },
   "outputs": [],
   "source": [
    "model = MIL(all_genes).to(device)\n",
    "criterion = nn.BCELoss().to(device)\n",
    "optimizer = optim.AdamW(model.parameters(), lr=0.01, weight_decay=0.02)\n",
    "early_stopping = EarlyStopping(patience=5, delta=0.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:12.481539Z",
     "iopub.status.busy": "2026-05-22T00:54:12.481073Z",
     "iopub.status.idle": "2026-05-22T00:54:12.483800Z",
     "shell.execute_reply": "2026-05-22T00:54:12.483383Z"
    }
   },
   "outputs": [],
   "source": [
    "output_dir = 'sample_output'\n",
    "os.makedirs(output_dir, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:12.485486Z",
     "iopub.status.busy": "2026-05-22T00:54:12.485223Z",
     "iopub.status.idle": "2026-05-22T00:54:12.488369Z",
     "shell.execute_reply": "2026-05-22T00:54:12.487958Z"
    }
   },
   "outputs": [],
   "source": [
    "train_size = int(0.9 * len(dataset))\n",
    "val_size = len(dataset) - train_size\n",
    "train_dataset, val_dataset = random_split(dataset, [train_size, val_size])\n",
    "    \n",
    "train_loader = DataLoader(train_dataset, batch_size=1, shuffle=True, collate_fn=custom_collate_fn)\n",
    "val_loader = DataLoader(val_dataset, batch_size=1, shuffle=True, collate_fn=custom_collate_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:12.489952Z",
     "iopub.status.busy": "2026-05-22T00:54:12.489706Z",
     "iopub.status.idle": "2026-05-22T00:54:12.493355Z",
     "shell.execute_reply": "2026-05-22T00:54:12.492923Z"
    }
   },
   "outputs": [],
   "source": [
    "best_val_loss = float('inf')\n",
    "best_model_path = os.path.join(output_dir, 'best_model.pth')\n",
    "\n",
    "# Save spacer scores before training\n",
    "spacer_scores_before_training = model.immunogenicity.ig.clone().detach().cpu()\n",
    "spacer_scores_before_training = [score.item() for score in spacer_scores_before_training]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:12.494953Z",
     "iopub.status.busy": "2026-05-22T00:54:12.494712Z",
     "iopub.status.idle": "2026-05-22T00:54:12.499450Z",
     "shell.execute_reply": "2026-05-22T00:54:12.499041Z"
    }
   },
   "outputs": [],
   "source": [
    "def save_metrics(epoch, train_loss, val_loss, val_auroc, a, b, alpha, beta, output_dir):\n",
    "    file_path = os.path.join(output_dir, 'training_metrics.csv')\n",
    "    if not os.path.exists(file_path):\n",
    "        # Create the CSV file with headers\n",
    "        with open(file_path, 'w') as f:\n",
    "            f.write('Epoch,Train Loss,Val Loss,Val AUROC,a,b,alpha,beta\\n')\n",
    "    \n",
    "    # Append metrics for the current epoch\n",
    "    with open(file_path, 'a') as f:\n",
    "        f.write(f'{epoch},{train_loss},{val_loss},{val_auroc},{a},{b},{alpha},{beta}\\n')\n",
    "\n",
    "def save_spacer_scores(epoch, all_genes, spacer_scores_before_training, spacer_scores_after_training, output_dir):\n",
    "    # Create a DataFrame with IG scores before and after the current epoch\n",
    "    spacer_score_data = {\n",
    "        'Gene': all_genes,\n",
    "        'SPACER Score Before Training': spacer_scores_before_training,\n",
    "        'SPACER Score After Training': spacer_scores_after_training,\n",
    "    }\n",
    "    df = pd.DataFrame(spacer_score_data)\n",
    "    \n",
    "    # Calculate the difference and add it as a new column\n",
    "    df['Difference'] = df['SPACER Score After Training'] - df['SPACER Score Before Training']\n",
    "    df = df.sort_values(by='Difference', ascending=False)\n",
    "\n",
    "    # Save to a CSV file for each epoch\n",
    "    output_path = os.path.join(output_dir, f'spacer_score_changes_epoch_{epoch+1}.csv')\n",
    "    df.to_csv(output_path, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:12.501019Z",
     "iopub.status.busy": "2026-05-22T00:54:12.500821Z",
     "iopub.status.idle": "2026-05-22T00:54:12.503243Z",
     "shell.execute_reply": "2026-05-22T00:54:12.502487Z"
    }
   },
   "outputs": [],
   "source": [
    "num_epochs = 2\n",
    "selection = 'positive' # Choose 'positive(induce)' or 'negative(repel)' based on your research focus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:12.504855Z",
     "iopub.status.busy": "2026-05-22T00:54:12.504707Z",
     "iopub.status.idle": "2026-05-22T00:54:14.117356Z",
     "shell.execute_reply": "2026-05-22T00:54:14.116925Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/324 [00:00<?, ?batch/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.03]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.03]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.02]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.02]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.01]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.01]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.01]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1.01]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1]   "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=1]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.991]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.991]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.986]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.986]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.98] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.98]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.973]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.973]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.966]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.966]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.957]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.957]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.953]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.953]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.946]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.946]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.945]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.945]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.934]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.934]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.931]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.931]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.923]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.923]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.918]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.918]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.911]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.911]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.902]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.902]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.908]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.908]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.898]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.898]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.89] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.89]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.886]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.886]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.879]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.879]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.879]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.879]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.875]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.875]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.864]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.864]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.868]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.868]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.868]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.868]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.851]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.851]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.843]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.843]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.84] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.84]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.832]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.832]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.838]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.838]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.839]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.839]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.835]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.835]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.831]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.831]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.831]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.826]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.826]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.815]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.815]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.808]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.808]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.817]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.817]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.796]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.796]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.81] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.81]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.811]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.811]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.799]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.799]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.791]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.791]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.798]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.798]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.788]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.788]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.786]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.786]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.776]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.776]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.79] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.79]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.768]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.768]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.782]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.782]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.766]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.766]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.769]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.769]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.763]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.763]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.759]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.759]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.749]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.749]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.756]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.756]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.746]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.746]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.764]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.764]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.753]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.753]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.752]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.752]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.757]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.757]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.751]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.751]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.748]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.748]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.731]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.731]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.741]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.741]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.719]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.719]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.73] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.73]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.743]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.743]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.736]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.736]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.738]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.738]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.727]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.727]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  12%|█▏        | 38/324 [00:00<00:00, 372.75batch/s, loss=0.719]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.719]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.719]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.726]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.726]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.708]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.708]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.732]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.732]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.74] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.74]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.725]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.725]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.697]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.697]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.704]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.704]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.72] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.72]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.749]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.749]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.721]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.714]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.714]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.68] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.68]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.705]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.705]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.694]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.694]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.697]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.697]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.712]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.712]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.68] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.68]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.688]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.688]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.708]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.708]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.682]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.682]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.713]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.713]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.704]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.704]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.691]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.691]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.677]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.677]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.73] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.73]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.703]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.703]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.672]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.672]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.7]  "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.7]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.675]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.675]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.737]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.737]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.685]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.685]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.673]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.673]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.68] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.68]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.677]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.677]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.665]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.665]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  24%|██▍       | 77/324 [00:00<00:00, 378.78batch/s, loss=0.674]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.674]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.674]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.68] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.68]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.656]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.656]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.656]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.656]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.691]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.691]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.652]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.652]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.669]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.669]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.684]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.684]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.666]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.666]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.683]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.683]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.675]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.675]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.648]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.648]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.659]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.659]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.648]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.648]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.652]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.652]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.67] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.67]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.673]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.673]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.66] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.66]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.649]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.649]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.647]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.647]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.642]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.642]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.66] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.66]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.641]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.641]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.653]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.653]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.632]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.632]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.726]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.726]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.667]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.667]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.68] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.68]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.666]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.666]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.633]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.633]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.649]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.649]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.676]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.627]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.627]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.63] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.63]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.637]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.637]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.656]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.656]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.667]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.667]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.707]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.62] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.62]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  37%|███▋      | 120/324 [00:00<00:00, 398.68batch/s, loss=0.679]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.679]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.679]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.64] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.64]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.629]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.629]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.678]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.678]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.623]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.623]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.635]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.635]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.63] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.63]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.659]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.659]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.632]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.632]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.647]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.647]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.661]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.661]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.638]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.638]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.627]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.627]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.634]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.634]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.703]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.703]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.588]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.588]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.645]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.645]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.597]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.597]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.636]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.636]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.626]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.626]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.614]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.614]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.605]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.605]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.635]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.635]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.631]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.631]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.646]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.646]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.601]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.601]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.633]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.633]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.647]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.647]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.61] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.61]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.594]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.594]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.636]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.636]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.576]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.576]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.615]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.615]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.629]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.629]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  50%|█████     | 162/324 [00:00<00:00, 404.40batch/s, loss=0.613]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.613]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.613]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.604]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.604]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.666]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.666]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.641]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.641]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.655]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.655]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.58] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.58]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.592]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.592]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.572]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.572]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.597]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.597]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.609]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.609]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.631]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.631]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.629]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.629]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.6]  "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.6]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.625]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.625]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.594]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.594]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.557]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.557]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.651]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.59] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.59]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.64]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.64]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.559]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.559]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.679]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.679]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.654]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.654]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.568]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.568]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.582]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.582]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.598]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.598]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.618]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.618]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.63] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.63]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.617]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.617]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.534]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.534]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.617]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.617]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.618]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.618]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.602]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.602]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.6]  "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.6]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.551]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.551]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.64] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.64]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.643]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.537]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.537]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.626]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.626]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.558]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.558]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.562]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.562]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.57] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.57]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.541]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.541]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.587]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.587]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.568]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.568]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  63%|██████▎   | 203/324 [00:00<00:00, 405.72batch/s, loss=0.543]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.543]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.543]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.586]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.586]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.539]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.539]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.608]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.608]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.548]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.548]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.612]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.607]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.607]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.578]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.578]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.555]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.555]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.552]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.552]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.645]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.645]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.549]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.549]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.559]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.559]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.562]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.562]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.595]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.595]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.513]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.513]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.604]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.604]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.59] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.59]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.554]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.554]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.566]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.566]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.588]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.588]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.663]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.663]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.565]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.565]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.508]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.508]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.523]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.523]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.633]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.633]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.493]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.493]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.504]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.504]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.543]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.543]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.475]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.475]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.531]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.531]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.502]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.502]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.546]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.546]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.539]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.539]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.554]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.554]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.553]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.553]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.514]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.514]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.697]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.697]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.515]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.515]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.488]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.488]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.604]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.604]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.553]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.553]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.577]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.577]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.436]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.436]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  77%|███████▋  | 248/324 [00:00<00:00, 420.42batch/s, loss=0.53] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.53]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.53]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.465]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.465]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.487]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.487]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.503]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.503]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.58] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.58]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.541]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.541]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.589]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.589]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.593]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.593]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.471]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.471]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.463]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.463]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.52] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.52]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.471]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.471]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.449]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.449]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.467]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.467]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.442]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.442]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.46] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.46]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.425]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.425]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.393]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.393]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.609]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.609]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.469]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.469]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.462]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.462]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.397]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.397]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.51] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.51]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.451]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.451]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.538]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.538]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.403]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.403]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.595]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.595]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.479]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.479]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.416]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.416]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.579]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.579]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2:  90%|█████████ | 293/324 [00:00<00:00, 428.62batch/s, loss=0.462]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/2: 100%|██████████| 324/324 [00:00<00:00, 416.36batch/s, loss=0.462]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch [1/2], Loss: 0.6657, AUROC: 0.7575\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.551]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.546]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.384]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.411]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.393]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.356]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.509]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.509]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.352]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.395]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.546]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.474]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.386]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.375]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.503]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.494]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.424]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.533]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.339]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.343]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.592]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.614]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.391]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.581]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.493]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.524]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.54] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.402]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.403]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.361]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.422]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.423]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.434]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.363]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.399]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|██████████| 36/36 [00:00<00:00, 986.86batch/s, val_loss=0.399]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation Loss: 0.4481, Validation AUROC: 0.9977\n",
      "Best model saved with validation loss 0.4481\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/324 [00:00<?, ?batch/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.587]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.587]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.836]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.836]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.385]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.385]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.593]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.593]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.587]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.587]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.59] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.59]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.42]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.42]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.439]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.439]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.483]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.483]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.407]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.407]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.368]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.368]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.455]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.455]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.503]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.503]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.363]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.363]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.492]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.492]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.32] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.32]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.39]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.39]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.619]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.619]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.483]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.483]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.487]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.487]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.535]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.535]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.402]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.402]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.362]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.362]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.377]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.377]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.365]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.365]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.32] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.32]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.459]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.459]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.468]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.468]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.431]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.431]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.359]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.359]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.33] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.33]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.416]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.416]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.378]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.378]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.329]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.329]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.283]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.283]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.39] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.39]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.301]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.301]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.439]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.439]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.34] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.34]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:   0%|          | 0/324 [00:00<?, ?batch/s, loss=0.589]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.589]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.589]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.354]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.354]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.329]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.329]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.52] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.52]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.301]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.301]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.41] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.41]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.252]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.252]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.433]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.433]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.336]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.336]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.545]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.545]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.397]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.397]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.236]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.236]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.259]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.259]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.285]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.285]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.254]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.254]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.388]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.388]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.419]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.419]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.389]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.389]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.271]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.271]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.263]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.263]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.338]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.338]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.418]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.418]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.455]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.455]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.303]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.303]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.519]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.519]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.295]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.295]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.308]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.308]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.342]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.342]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.365]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.365]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.38] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.38]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.23]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.23]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.266]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.266]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.363]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.363]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.313]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.313]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.42] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.42]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.242]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.242]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.394]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.394]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.335]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.335]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.304]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.304]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.378]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.378]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.461]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.461]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.195]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.195]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  13%|█▎        | 42/324 [00:00<00:00, 412.89batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.372]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.372]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.706]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.706]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.338]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.338]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.274]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.274]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.326]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.326]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.177]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.177]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.31] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.31]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.28]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.28]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.284]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.284]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.222]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.222]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.548]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.548]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.218]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.218]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.383]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.383]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.29] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.29]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.451]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.451]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.218]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.218]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.228]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.228]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.271]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.271]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.454]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.454]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.396]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.396]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.194]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.194]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.402]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.402]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.243]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.243]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.483]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.483]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.337]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.337]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.457]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.457]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.234]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.234]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.311]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.311]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.223]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.223]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.221]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.221]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.229]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.229]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.196]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.196]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.44] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.44]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.485]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.485]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.203]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.203]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.326]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.326]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.324]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.324]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.316]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.316]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.38] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.38]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.294]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.294]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.206]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.206]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  27%|██▋       | 88/324 [00:00<00:00, 438.12batch/s, loss=0.262]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.262]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.262]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.32] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.32]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.218]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.218]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.43] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.43]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.281]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.281]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.75] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.75]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.476]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.187]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.187]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.966]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.966]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.247]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.247]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.145]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.145]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.255]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.255]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.293]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.293]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.162]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.162]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.354]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.354]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.418]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.418]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.191]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.191]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.199]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.199]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.155]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.155]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.231]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.231]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.334]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.334]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.472]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.472]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.158]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.158]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.327]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.246]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.246]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.191]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.191]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.141]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.141]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.256]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.256]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.385]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.385]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.155]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.155]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.116]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.116]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.275]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.275]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.212]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.212]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.482]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.482]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.229]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.229]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.192]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.192]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.265]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.265]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.203]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.203]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.146]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.146]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.299]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.299]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.18] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.18]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.367]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.345]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.345]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.351]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.351]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.145]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.145]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.161]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.161]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  42%|████▏     | 135/324 [00:00<00:00, 451.42batch/s, loss=0.48] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.48]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.48]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.379]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.379]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.129]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.129]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.192]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.192]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.362]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.362]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.107]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.107]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.154]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.154]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.274]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.274]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.129]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.129]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.148]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.148]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.167]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.167]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.332]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.332]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.975]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.975]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.198]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.198]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.573]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.573]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.267]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.267]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.287]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.287]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.106]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.106]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.137]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.137]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.171]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.171]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.298]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.298]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.103]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.103]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.734]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.734]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.297]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.297]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.264]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.264]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.201]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.201]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.099]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.099]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.238]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.238]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.289]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.289]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.149]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.149]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.34] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.34]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.172]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.172]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.252]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.252]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.185]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.185]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.272]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.272]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.144]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.144]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.883]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.883]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.139]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.139]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.125]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.125]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.286]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.286]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.424]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.424]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.296]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.296]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.12] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.12]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.183]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.183]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  56%|█████▌    | 181/324 [00:00<00:00, 453.60batch/s, loss=0.15] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.15]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.15]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.19]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.19]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.234]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.234]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.175]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.175]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.463]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.463]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.188]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.188]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.121]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.121]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.23] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.23]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.267]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.267]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.12] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.12]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.0951]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.0951]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.136] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.136]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.212]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.212]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.143]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.143]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.319]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.319]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.768]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.768]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.256]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.256]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.0941]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.0941]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.186] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.186]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.303]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.303]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.168]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.168]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.124]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.124]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.173]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.173]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.429]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.429]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.401]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.401]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.25] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.25]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.173]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.173]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.183]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.183]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.378]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.378]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.108]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.108]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.177]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.177]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.303]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.303]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.108]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.108]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.114]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.114]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.128]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.128]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.297]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.297]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.107]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.107]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.111]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.111]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.411]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.411]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.0966]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.0966]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.182] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.182]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.189]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.189]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.088]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.088]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.156]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.156]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.141]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.141]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.328]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.328]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  70%|███████   | 227/324 [00:00<00:00, 455.36batch/s, loss=0.103]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.103]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.103]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.265]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.265]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.239]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.239]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.312]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.126]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.126]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.194]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.194]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.151]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.151]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.205]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.205]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.313]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.313]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.136]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.136]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0876]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0876]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.115] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.115]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.112]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.112]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.147]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.147]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.177]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.177]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.189]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.189]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0768]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0768]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.183] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.183]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.123]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.123]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.169]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.169]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.157]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.157]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.132]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.132]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.142]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.142]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.115]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.115]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.246]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.246]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.196]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.196]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0999]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0999]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.364] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.364]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.152]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.152]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.149]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.149]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.084]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.084]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.216]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.175]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.175]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.241]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.241]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.291]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.291]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0937]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0937]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.155] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.155]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0907]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.0907]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.11]  "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.11]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.153]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.153]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.184]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.184]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.138]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.138]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.195]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.195]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.295]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.295]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.142]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.142]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  84%|████████▍ | 273/324 [00:00<00:00, 456.60batch/s, loss=0.099]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.099]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.099]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.453]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.453]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.276]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.276]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.86] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.86]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.0778]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.0778]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2:  98%|█████████▊| 319/324 [00:00<00:00, 449.99batch/s, loss=0.115] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 2/2: 100%|██████████| 324/324 [00:00<00:00, 449.16batch/s, loss=0.115]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch [2/2], Loss: 0.2922, AUROC: 0.9920\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.292]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.107]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0797]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.249] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.106]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.205]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0891]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.181] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0667]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0636]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0658]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.233] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.313]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.118]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.393]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.115]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.202]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.096]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.11] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.111]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.128]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.147]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.079]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.11] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.259]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0836]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.184] "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.108]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.276]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.103]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.399]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.365]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.337]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0622]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0642]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/36 [00:00<?, ?batch/s, val_loss=0.0617]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|██████████| 36/36 [00:00<00:00, 1078.31batch/s, val_loss=0.0617]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation Loss: 0.1656, Validation AUROC: 1.0000\n",
      "Best model saved with validation loss 0.1656\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for epoch in range(num_epochs):\n",
    "    model.train()\n",
    "    running_loss = 0.0\n",
    "        \n",
    "    # Lists to store outputs and labels for AUROC calculation\n",
    "    all_outputs = []\n",
    "    all_labels = []\n",
    "        \n",
    "    with tqdm(train_loader, unit=\"batch\") as tepoch:\n",
    "        for i, batch_data in enumerate(tepoch):\n",
    "            tepoch.set_description(f\"Epoch {epoch+1}/{num_epochs}\")\n",
    "            optimizer.zero_grad()\n",
    "\n",
    "            # Unpack the batch data\n",
    "            distances_list, gene_expressions_list, labels_list, core_idxs_list, gene_names_list, cell_ids_list = batch_data\n",
    "                \n",
    "            # Move data to device and prepare labels\n",
    "            distances_list = [distances.to(device) for distances in distances_list]\n",
    "            gene_expressions_list = [gene_exp.to(device) for gene_exp in gene_expressions_list]\n",
    "            labels = torch.stack(labels_list).float().to(device)\n",
    "            current_genes_list = gene_names_list  # List of gene names for each bag\n",
    "\n",
    "            # Forward pass\n",
    "            outputs = model(distances_list, gene_expressions_list, current_genes_list)\n",
    "                \n",
    "            if outputs is None:\n",
    "                 continue  # Skip this batch if the model returns None\n",
    "                \n",
    "            if outputs.shape[0] != labels.shape[0]:\n",
    "                # Handle mismatch in batch sizes if necessary\n",
    "                continue\n",
    "                \n",
    "            # Compute BCE loss\n",
    "            if selection == 'negative':\n",
    "                labels = 1 - labels\n",
    "            loss = criterion(outputs, labels)\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "        \n",
    "            running_loss += loss.item()\n",
    "            tepoch.set_postfix(loss=loss.item())\n",
    "                \n",
    "            # Accumulate outputs and labels for AUROC calculation\n",
    "            all_outputs.extend(outputs.detach().cpu().numpy())\n",
    "            all_labels.extend(labels.cpu().numpy())\n",
    "\n",
    "    train_loss = running_loss / len(train_loader)\n",
    "        \n",
    "    # Compute Training AUROC\n",
    "    try:\n",
    "        epoch_auc = roc_auc_score(all_labels, all_outputs)\n",
    "    except ValueError:\n",
    "        epoch_auc = float('nan')  # Handle case where AUROC can't be computed\n",
    "        \n",
    "    print(f'Epoch [{epoch+1}/{num_epochs}], Loss: {train_loss:.4f}, AUROC: {epoch_auc:.4f}')\n",
    "        \n",
    "    # Validation phase\n",
    "    model.eval()\n",
    "    val_loss = 0.0\n",
    "    val_all_outputs = []\n",
    "    val_all_labels = []\n",
    "    with torch.no_grad():\n",
    "        with tqdm(val_loader, unit=\"batch\") as vtepoch:\n",
    "            for val_batch_data in vtepoch:\n",
    "                # Unpack validation batch data\n",
    "                val_distances_list, val_gene_expressions_list, val_labels_list, val_core_idxs_list, val_gene_names_list, val_cell_ids_list = val_batch_data\n",
    "                    \n",
    "                # Move data to device and prepare labels\n",
    "                val_distances_list = [distances.to(device) for distances in val_distances_list]\n",
    "                val_gene_expressions_list = [gene_exp.to(device) for gene_exp in val_gene_expressions_list]\n",
    "                val_labels = torch.stack(val_labels_list).float().to(device)\n",
    "                val_current_genes_list = val_gene_names_list  # List of gene names for each bag\n",
    "                    \n",
    "                # Forward pass\n",
    "                val_outputs = model(val_distances_list, val_gene_expressions_list, val_current_genes_list)\n",
    "                    \n",
    "                if val_outputs is None:\n",
    "                    continue  # Skip this batch if the model returns None\n",
    "                    \n",
    "                if val_outputs.shape[0] != val_labels.shape[0]:\n",
    "                    # Handle mismatch in batch sizes if necessary\n",
    "                    continue\n",
    "                    \n",
    "                # Compute BCE loss\n",
    "                if selection == 'negative':\n",
    "                    val_labels = 1 - val_labels\n",
    "                loss = criterion(val_outputs, val_labels)\n",
    "                val_loss += loss.item()\n",
    "                vtepoch.set_postfix(val_loss=loss.item())\n",
    "                    \n",
    "                # Accumulate outputs and labels for AUROC calculation\n",
    "                val_all_outputs.extend(val_outputs.detach().cpu().numpy())\n",
    "                val_all_labels.extend(val_labels.cpu().numpy())\n",
    "            \n",
    "        val_loss /= len(val_loader)\n",
    "            \n",
    "            # Compute Validation AUROC\n",
    "        try:\n",
    "            val_epoch_auc = roc_auc_score(val_all_labels, val_all_outputs)\n",
    "        except ValueError:\n",
    "            val_epoch_auc = float('nan')  # Handle case where AUROC can't be computed\n",
    "            \n",
    "        print(f'Validation Loss: {val_loss:.4f}, Validation AUROC: {val_epoch_auc:.4f}')\n",
    "\n",
    "    # Save the best model\n",
    "    if val_loss < best_val_loss:\n",
    "        best_val_loss = val_loss\n",
    "        torch.save(model.state_dict(), best_model_path)\n",
    "        print(f\"Best model saved with validation loss {val_loss:.4f}\")\n",
    "            \n",
    "    torch.save(model.state_dict(), os.path.join(output_dir, f'model_epoch_{epoch+1}.pth'))\n",
    "        \n",
    "    a = model.distance.a.clone().detach().cpu().numpy()\n",
    "    b = model.gene_expression.b.clone().detach().cpu()\n",
    "    alpha = model.alpha.clone().detach().cpu()\n",
    "    beta = model.beta.clone().detach().cpu()\n",
    "    # Save metrics\n",
    "    save_metrics(epoch+1, train_loss, val_loss, val_epoch_auc,a,b,alpha,beta, output_dir)\n",
    "\n",
    "    # Save SPACER scores after each epoch\n",
    "    spacer_scores_after_training = model.immunogenicity.ig.clone().detach().cpu()\n",
    "    spacer_scores_after_training = [score.item() for score in spacer_scores_after_training]\n",
    "    save_spacer_scores(epoch, all_genes, spacer_scores_before_training, spacer_scores_after_training, output_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training Results Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:14.119470Z",
     "iopub.status.busy": "2026-05-22T00:54:14.119299Z",
     "iopub.status.idle": "2026-05-22T00:54:14.909774Z",
     "shell.execute_reply": "2026-05-22T00:54:14.909360Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Training & validation loss / AUROC curves\n",
    "metrics_df = pd.read_csv(os.path.join(output_dir, 'training_metrics.csv'))\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "axes[0].plot(metrics_df['Epoch'], metrics_df['Train Loss'],\n",
    "             marker='o', label='Train Loss', color='steelblue')\n",
    "axes[0].plot(metrics_df['Epoch'], metrics_df['Val Loss'],\n",
    "             marker='s', linestyle='--', label='Val Loss', color='tomato')\n",
    "axes[0].set_xlabel('Epoch')\n",
    "axes[0].set_ylabel('Loss')\n",
    "axes[0].set_title('Training & Validation Loss')\n",
    "axes[0].legend()\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "axes[1].plot(metrics_df['Epoch'], metrics_df['Val AUROC'],\n",
    "             marker='s', color='darkorange', label='Val AUROC')\n",
    "axes[1].axhline(y=0.5, color='gray', linestyle='--', alpha=0.7, label='Random baseline')\n",
    "axes[1].set_ylim(0, 1)\n",
    "axes[1].set_xlabel('Epoch')\n",
    "axes[1].set_ylabel('AUROC')\n",
    "axes[1].set_title('Validation AUROC per Epoch')\n",
    "axes[1].legend()\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.suptitle('Training Summary', fontsize=14)\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(output_dir, 'training_curves.png'), dpi=150, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:14.912056Z",
     "iopub.status.busy": "2026-05-22T00:54:14.911846Z",
     "iopub.status.idle": "2026-05-22T00:54:15.700581Z",
     "shell.execute_reply": "2026-05-22T00:54:15.700156Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1600x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Top genes by SPACER score change (last epoch)\n",
    "import glob\n",
    "\n",
    "spacer_files = sorted(glob.glob(os.path.join(output_dir, 'spacer_score_changes_epoch_*.csv')))\n",
    "if spacer_files:\n",
    "    last_df = pd.read_csv(spacer_files[-1]).sort_values('Difference', ascending=False)\n",
    "    top_n = 20\n",
    "    top_up = last_df.head(top_n)\n",
    "    top_dn = last_df.tail(top_n).sort_values('Difference', ascending=True)\n",
    "\n",
    "    fig, axes = plt.subplots(1, 2, figsize=(16, 7))\n",
    "\n",
    "    axes[0].barh(top_up['Gene'], top_up['Difference'], color='tomato')\n",
    "    axes[0].axvline(x=0, color='black', linewidth=0.8)\n",
    "    axes[0].set_xlabel('SPACER Score Change')\n",
    "    axes[0].set_title(f'Top {top_n} Genes — Highest Score Increase')\n",
    "    axes[0].invert_yaxis()\n",
    "    axes[0].grid(True, axis='x', alpha=0.3)\n",
    "\n",
    "    axes[1].barh(top_dn['Gene'], top_dn['Difference'], color='steelblue')\n",
    "    axes[1].axvline(x=0, color='black', linewidth=0.8)\n",
    "    axes[1].set_xlabel('SPACER Score Change')\n",
    "    axes[1].set_title(f'Top {top_n} Genes — Highest Score Decrease')\n",
    "    axes[1].invert_yaxis()\n",
    "    axes[1].grid(True, axis='x', alpha=0.3)\n",
    "\n",
    "    plt.suptitle(f'SPACER Score Changes — Epoch {len(spacer_files)}', fontsize=14)\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(os.path.join(output_dir, 'spacer_score_changes.png'), dpi=150, bbox_inches='tight')\n",
    "    plt.show()\n",
    "else:\n",
    "    print(\"No SPACER score files found in output_dir.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-22T00:54:15.702475Z",
     "iopub.status.busy": "2026-05-22T00:54:15.702256Z",
     "iopub.status.idle": "2026-05-22T00:54:16.552936Z",
     "shell.execute_reply": "2026-05-22T00:54:16.552507Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Model parameter evolution across epochs\n",
    "def _parse_param(val):\n",
    "    s = str(val).strip().strip('[]')\n",
    "    try:\n",
    "        return float(s)\n",
    "    except ValueError:\n",
    "        return float('nan')\n",
    "\n",
    "fig, axes = plt.subplots(2, 2, figsize=(12, 8))\n",
    "param_cfg = {\n",
    "    'a':     ('Distance Shape (a)',       'purple'),\n",
    "    'b':     ('Gene Expression Scale (b)', 'green'),\n",
    "    'alpha': ('Alpha (score scaling)',     'darkorange'),\n",
    "    'beta':  ('Beta (score bias)',         'crimson'),\n",
    "}\n",
    "for ax, (col, (title, color)) in zip(axes.ravel(), param_cfg.items()):\n",
    "    vals = metrics_df[col].apply(_parse_param)\n",
    "    ax.plot(metrics_df['Epoch'], vals, marker='o', color=color)\n",
    "    ax.set_xlabel('Epoch')\n",
    "    ax.set_title(title)\n",
    "    ax.grid(True, alpha=0.3)\n",
    "\n",
    "plt.suptitle('Model Parameter Evolution', fontsize=14)\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(output_dir, 'parameter_evolution.png'), dpi=150, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "spatial_tcr",
   "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": "3.9.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}