{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "t_c = torch.tensor([0.5, 14.0, 15.0, 28.0, 11.0, 8.0, 3.0, -4.0, 6.0, 13.0, 21.0])\n",
    "# t_u = torch.tensor([32.9000, 57.2000, 59.0000, 82.4000, 51.8000, 46.4000, 37.4000, 24.8000, 42.8000, 55.4000, 69.8000])\n",
    "# t_u = torch.tensor([30.3057, 56.7230, 57.9168, 79.4823, 52.3995, 47.3290, 37.7892, 25.9138, 43.6609, 56.5834, 71.3901])\n",
    "t_u = torch.tensor([35.7, 55.9, 58.2, 81.9, 56.3, 48.9, 33.9, 21.8, 48.4, 60.4, 68.4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "def loss_fn(t_p, t_c):\n",
    "    squared_diffs = (t_p - t_c)**2\n",
    "    return squared_diffs.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([35.7000, 55.9000, 58.2000, 81.9000, 56.3000, 48.9000, 33.9000, 21.8000,\n",
       "        48.4000, 60.4000, 68.4000])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w = torch.ones(1)\n",
    "b = torch.zeros(1)\n",
    "\n",
    "t_p = model(t_u, w, b)\n",
    "t_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(1763.8846)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loss = loss_fn(t_p, t_c)\n",
    "loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "delta = 0.1\n",
    "\n",
    "loss_rate_of_change_w = (loss_fn(model(t_u, w + delta, b), t_c) - loss_fn(model(t_u, w - delta, b), t_c)) / (2.0 * delta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "learning_rate = 1e-2\n",
    "\n",
    "w = w - learning_rate * loss_rate_of_change_w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_rate_of_change_b = (loss_fn(model(t_u, w, b + delta), t_c) - loss_fn(model(t_u, w, b - delta), t_c)) / (2.0 * delta)\n",
    "\n",
    "b = b - learning_rate * loss_rate_of_change_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dloss_fn(t_p, t_c):\n",
    "    dsq_diffs = 2 * (t_p - t_c)\n",
    "    return dsq_diffs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dmodel_dw(t_u, w, b):\n",
    "    return t_u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dmodel_db(t_u, w, b):\n",
    "    return 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "def grad_fn(t_u, t_c, t_p, w, b):\n",
    "    dloss_dw = dloss_fn(t_p, t_c) * dmodel_dw(t_u, w, b)\n",
    "    dloss_db = dloss_fn(t_p, t_c) * dmodel_db(t_u, w, b)\n",
    "    return torch.stack([dloss_dw.mean(), dloss_db.mean()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 1763.884644\n",
      "Params: tensor([1., 0.])\n",
      "Grad: tensor([4517.2964,   82.6000])\n",
      "Epoch 1, Loss 5802484.500000\n",
      "Params: tensor([-44.1730,  -0.8260])\n",
      "Grad: tensor([-261257.4062,   -4598.9707])\n",
      "Epoch 2, Loss 19408031744.000000\n",
      "Params: tensor([2568.4011,   45.1637])\n",
      "Grad: tensor([15109615.0000,   266155.7188])\n",
      "Epoch 3, Loss 64915909902336.000000\n",
      "Params: tensor([-148527.7344,   -2616.3933])\n",
      "Grad: tensor([-873852544.,  -15392727.])\n",
      "Epoch 4, Loss 217130439561707520.000000\n",
      "Params: tensor([8589997.0000,  151310.8750])\n",
      "Grad: tensor([50538569728.,   890226304.])\n",
      "Epoch 5, Loss 726257020202974707712.000000\n",
      "Params: tensor([-496795712.,   -8750952.])\n",
      "Grad: tensor([-2922858414080.,   -51485540352.])\n",
      "Epoch 6, Loss 2429181687085405986357248.000000\n",
      "Params: tensor([28731787264.,   506104448.])\n",
      "Grad: tensor([169041222172672.,   2977625538560.])\n",
      "Epoch 7, Loss 8125117236949438203699396608.000000\n",
      "Params: tensor([-1661680353280.,   -29270151168.])\n",
      "Grad: tensor([-9776366694170624.,  -172208609558528.])\n",
      "Epoch 8, Loss 27176865195881116022129584766976.000000\n",
      "Params: tensor([96101982011392.,  1692815851520.])\n",
      "Grad: tensor([565408461421019136.,   9959550270570496.])\n",
      "Epoch 9, Loss 90901075478458130961171361977860096.000000\n",
      "Params: tensor([-5557982423154688.,   -97902688993280.])\n",
      "Grad: tensor([-32699952998104694784.,   -576002771350716416.])\n",
      "Epoch 10, Loss inf\n",
      "Params: tensor([321441537185546240.,   5662124642664448.])\n",
      "Grad: tensor([1891176184585880862720.,   33312666847799148544.])\n",
      "Epoch 11, Loss inf\n",
      "Params: tensor([-18590318302064541696.,   -327464524443549696.])\n",
      "Grad: tensor([-109374681759098253344768.,   -1926611913828915478528.])\n",
      "Epoch 12, Loss inf\n",
      "Params: tensor([1075156512834901245952.,   18938652381837000704.])\n",
      "Grad: tensor([6325598374588843695276032.,  111424089805529471254528.])\n",
      "Epoch 13, Loss inf\n",
      "Params: tensor([-62180826256335366520832.,  -1095302239868036317184.])\n",
      "Grad: tensor([-365835976043760417324924928.,   -6444125046330702902067200.])\n",
      "Epoch 14, Loss inf\n",
      "Params: tensor([3596178922111621805375488.,   63345948012332760170496.])\n",
      "Grad: tensor([21157835782059083454602018816.,   372690823035039034124533760.])\n",
      "Epoch 15, Loss inf\n",
      "Params: tensor([-207982187937383808858324992.,   -3663562284139497432023040.])\n",
      "Grad: tensor([-1223646909320076514166573105152.,   -21554280809479231605114404864.])\n",
      "Epoch 16, Loss inf\n",
      "Params: tensor([12028486061878242282806706176.,   211879247090395688732721152.])\n",
      "Grad: tensor([70768650898774906899853796704256.,  1246574867509841489693786505216.])\n",
      "Epoch 17, Loss inf\n",
      "Params: tensor([-695658002336352961404078129152.,  -12253869266414541122509471744.])\n",
      "Grad: tensor([-4092848885264420701125161829531648.,\n",
      "          -72094682944683965973455410561024.])\n",
      "Epoch 18, Loss inf\n",
      "Params: tensor([40232831252275689071711740755968.,   708692942754892796823053795328.])\n",
      "Grad: tensor([236706693175123219458221128344928256.,\n",
      "          4169539270698150009155162575208448.])\n",
      "Epoch 19, Loss inf\n",
      "Params: tensor([-2326833954750859692770806240116736.,\n",
      "          -40986700468425897220250066223104.])\n",
      "Grad: tensor([-13689745465297718916730354409333063680.,\n",
      "          -241141984747874879907129710614675456.])\n",
      "Epoch 20, Loss inf\n",
      "Params: tensor([134570618593728262689386270524702720.,\n",
      "          2370433119736956411345012858552320.])\n",
      "Grad: tensor([       inf, 1.3946e+37])\n",
      "Epoch 21, Loss inf\n",
      "Params: tensor([                                      -inf,\n",
      "        -137092134093907239497638400288096256.0000])\n",
      "Grad: tensor([-inf, -inf])\n",
      "Epoch 22, Loss nan\n",
      "Params: tensor([nan, inf])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 23, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 24, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 25, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 26, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 27, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 28, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 29, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 30, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 31, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 32, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 33, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 34, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 35, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 36, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 37, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 38, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 39, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 40, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 41, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 42, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 43, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 44, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 45, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 46, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 47, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 48, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 49, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 50, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 51, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 52, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 53, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 54, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 55, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 56, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 57, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 58, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 59, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 60, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 61, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 62, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 63, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 64, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 65, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 66, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 67, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 68, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 69, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 70, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 71, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 72, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 73, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 74, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 75, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 76, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 77, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 78, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 79, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 80, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 81, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 82, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 83, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 84, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 85, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 86, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 87, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 88, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 89, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 90, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 91, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 92, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 93, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 94, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 95, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 96, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 97, Loss nan\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 98, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n",
      "Epoch 99, Loss nan\n",
      "Params: tensor([nan, nan])\n",
      "Grad: tensor([nan, nan])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([nan, nan])"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0, 0.0])\n",
    "\n",
    "nepochs = 100\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    w, b = params\n",
    "    t_p = model(t_u, w, b)\n",
    "\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "    \n",
    "    # backward pass\n",
    "    grad = grad_fn(t_u, t_c, t_p, w, b)\n",
    "\n",
    "    print('Params:', params)\n",
    "    print('Grad:', grad)\n",
    "    \n",
    "    params = params - learning_rate * grad\n",
    "    \n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 1763.884644\n",
      "Params: tensor([1., 0.])\n",
      "Grad: tensor([4517.2964,   82.6000])\n",
      "Epoch 1, Loss 323.090546\n",
      "Params: tensor([ 0.5483, -0.0083])\n",
      "Grad: tensor([1859.5493,   35.7843])\n",
      "Epoch 2, Loss 78.929634\n",
      "Params: tensor([ 0.3623, -0.0118])\n",
      "Grad: tensor([765.4666,  16.5122])\n",
      "Epoch 3, Loss 37.552845\n",
      "Params: tensor([ 0.2858, -0.0135])\n",
      "Grad: tensor([315.0790,   8.5787])\n",
      "Epoch 4, Loss 30.540285\n",
      "Params: tensor([ 0.2543, -0.0143])\n",
      "Grad: tensor([129.6733,   5.3127])\n",
      "Epoch 5, Loss 29.351152\n",
      "Params: tensor([ 0.2413, -0.0149])\n",
      "Grad: tensor([53.3496,  3.9682])\n",
      "Epoch 6, Loss 29.148882\n",
      "Params: tensor([ 0.2360, -0.0153])\n",
      "Grad: tensor([21.9304,  3.4148])\n",
      "Epoch 7, Loss 29.113848\n",
      "Params: tensor([ 0.2338, -0.0156])\n",
      "Grad: tensor([8.9964, 3.1869])\n",
      "Epoch 8, Loss 29.107145\n",
      "Params: tensor([ 0.2329, -0.0159])\n",
      "Grad: tensor([3.6721, 3.0930])\n",
      "Epoch 9, Loss 29.105242\n",
      "Params: tensor([ 0.2325, -0.0162])\n",
      "Grad: tensor([1.4803, 3.0544])\n",
      "Epoch 10, Loss 29.104168\n",
      "Params: tensor([ 0.2324, -0.0166])\n",
      "Grad: tensor([0.5780, 3.0384])\n",
      "Epoch 11, Loss 29.103222\n",
      "Params: tensor([ 0.2323, -0.0169])\n",
      "Grad: tensor([0.2066, 3.0318])\n",
      "Epoch 12, Loss 29.102297\n",
      "Params: tensor([ 0.2323, -0.0172])\n",
      "Grad: tensor([0.0537, 3.0291])\n",
      "Epoch 13, Loss 29.101379\n",
      "Params: tensor([ 0.2323, -0.0175])\n",
      "Grad: tensor([-0.0093,  3.0279])\n",
      "Epoch 14, Loss 29.100470\n",
      "Params: tensor([ 0.2323, -0.0178])\n",
      "Grad: tensor([-0.0353,  3.0274])\n",
      "Epoch 15, Loss 29.099548\n",
      "Params: tensor([ 0.2323, -0.0181])\n",
      "Grad: tensor([-0.0459,  3.0272])\n",
      "Epoch 16, Loss 29.098631\n",
      "Params: tensor([ 0.2323, -0.0184])\n",
      "Grad: tensor([-0.0502,  3.0270])\n",
      "Epoch 17, Loss 29.097715\n",
      "Params: tensor([ 0.2323, -0.0187])\n",
      "Grad: tensor([-0.0520,  3.0270])\n",
      "Epoch 18, Loss 29.096796\n",
      "Params: tensor([ 0.2323, -0.0190])\n",
      "Grad: tensor([-0.0528,  3.0269])\n",
      "Epoch 19, Loss 29.095884\n",
      "Params: tensor([ 0.2323, -0.0193])\n",
      "Grad: tensor([-0.0531,  3.0268])\n",
      "Epoch 20, Loss 29.094959\n",
      "Params: tensor([ 0.2323, -0.0196])\n",
      "Grad: tensor([-0.0533,  3.0268])\n",
      "Epoch 21, Loss 29.094049\n",
      "Params: tensor([ 0.2323, -0.0199])\n",
      "Grad: tensor([-0.0533,  3.0267])\n",
      "Epoch 22, Loss 29.093134\n",
      "Params: tensor([ 0.2323, -0.0202])\n",
      "Grad: tensor([-0.0533,  3.0267])\n",
      "Epoch 23, Loss 29.092213\n",
      "Params: tensor([ 0.2323, -0.0205])\n",
      "Grad: tensor([-0.0533,  3.0266])\n",
      "Epoch 24, Loss 29.091297\n",
      "Params: tensor([ 0.2323, -0.0208])\n",
      "Grad: tensor([-0.0533,  3.0266])\n",
      "Epoch 25, Loss 29.090382\n",
      "Params: tensor([ 0.2323, -0.0211])\n",
      "Grad: tensor([-0.0533,  3.0265])\n",
      "Epoch 26, Loss 29.089460\n",
      "Params: tensor([ 0.2323, -0.0214])\n",
      "Grad: tensor([-0.0533,  3.0265])\n",
      "Epoch 27, Loss 29.088549\n",
      "Params: tensor([ 0.2323, -0.0217])\n",
      "Grad: tensor([-0.0532,  3.0264])\n",
      "Epoch 28, Loss 29.087635\n",
      "Params: tensor([ 0.2323, -0.0220])\n",
      "Grad: tensor([-0.0533,  3.0264])\n",
      "Epoch 29, Loss 29.086718\n",
      "Params: tensor([ 0.2323, -0.0223])\n",
      "Grad: tensor([-0.0533,  3.0263])\n",
      "Epoch 30, Loss 29.085808\n",
      "Params: tensor([ 0.2323, -0.0226])\n",
      "Grad: tensor([-0.0532,  3.0262])\n",
      "Epoch 31, Loss 29.084888\n",
      "Params: tensor([ 0.2324, -0.0229])\n",
      "Grad: tensor([-0.0533,  3.0262])\n",
      "Epoch 32, Loss 29.083965\n",
      "Params: tensor([ 0.2324, -0.0232])\n",
      "Grad: tensor([-0.0533,  3.0261])\n",
      "Epoch 33, Loss 29.083057\n",
      "Params: tensor([ 0.2324, -0.0235])\n",
      "Grad: tensor([-0.0533,  3.0261])\n",
      "Epoch 34, Loss 29.082142\n",
      "Params: tensor([ 0.2324, -0.0238])\n",
      "Grad: tensor([-0.0532,  3.0260])\n",
      "Epoch 35, Loss 29.081219\n",
      "Params: tensor([ 0.2324, -0.0241])\n",
      "Grad: tensor([-0.0533,  3.0260])\n",
      "Epoch 36, Loss 29.080309\n",
      "Params: tensor([ 0.2324, -0.0244])\n",
      "Grad: tensor([-0.0533,  3.0259])\n",
      "Epoch 37, Loss 29.079393\n",
      "Params: tensor([ 0.2324, -0.0247])\n",
      "Grad: tensor([-0.0532,  3.0259])\n",
      "Epoch 38, Loss 29.078474\n",
      "Params: tensor([ 0.2324, -0.0250])\n",
      "Grad: tensor([-0.0533,  3.0258])\n",
      "Epoch 39, Loss 29.077559\n",
      "Params: tensor([ 0.2324, -0.0253])\n",
      "Grad: tensor([-0.0533,  3.0258])\n",
      "Epoch 40, Loss 29.076653\n",
      "Params: tensor([ 0.2324, -0.0256])\n",
      "Grad: tensor([-0.0533,  3.0257])\n",
      "Epoch 41, Loss 29.075731\n",
      "Params: tensor([ 0.2324, -0.0259])\n",
      "Grad: tensor([-0.0532,  3.0257])\n",
      "Epoch 42, Loss 29.074812\n",
      "Params: tensor([ 0.2324, -0.0262])\n",
      "Grad: tensor([-0.0533,  3.0256])\n",
      "Epoch 43, Loss 29.073896\n",
      "Params: tensor([ 0.2324, -0.0265])\n",
      "Grad: tensor([-0.0533,  3.0256])\n",
      "Epoch 44, Loss 29.072985\n",
      "Params: tensor([ 0.2324, -0.0268])\n",
      "Grad: tensor([-0.0533,  3.0255])\n",
      "Epoch 45, Loss 29.072069\n",
      "Params: tensor([ 0.2324, -0.0271])\n",
      "Grad: tensor([-0.0533,  3.0254])\n",
      "Epoch 46, Loss 29.071148\n",
      "Params: tensor([ 0.2324, -0.0274])\n",
      "Grad: tensor([-0.0533,  3.0254])\n",
      "Epoch 47, Loss 29.070234\n",
      "Params: tensor([ 0.2324, -0.0277])\n",
      "Grad: tensor([-0.0533,  3.0253])\n",
      "Epoch 48, Loss 29.069323\n",
      "Params: tensor([ 0.2324, -0.0281])\n",
      "Grad: tensor([-0.0533,  3.0253])\n",
      "Epoch 49, Loss 29.068401\n",
      "Params: tensor([ 0.2325, -0.0284])\n",
      "Grad: tensor([-0.0532,  3.0252])\n",
      "Epoch 50, Loss 29.067486\n",
      "Params: tensor([ 0.2325, -0.0287])\n",
      "Grad: tensor([-0.0533,  3.0252])\n",
      "Epoch 51, Loss 29.066570\n",
      "Params: tensor([ 0.2325, -0.0290])\n",
      "Grad: tensor([-0.0533,  3.0251])\n",
      "Epoch 52, Loss 29.065655\n",
      "Params: tensor([ 0.2325, -0.0293])\n",
      "Grad: tensor([-0.0533,  3.0251])\n",
      "Epoch 53, Loss 29.064739\n",
      "Params: tensor([ 0.2325, -0.0296])\n",
      "Grad: tensor([-0.0533,  3.0250])\n",
      "Epoch 54, Loss 29.063829\n",
      "Params: tensor([ 0.2325, -0.0299])\n",
      "Grad: tensor([-0.0532,  3.0250])\n",
      "Epoch 55, Loss 29.062910\n",
      "Params: tensor([ 0.2325, -0.0302])\n",
      "Grad: tensor([-0.0533,  3.0249])\n",
      "Epoch 56, Loss 29.061989\n",
      "Params: tensor([ 0.2325, -0.0305])\n",
      "Grad: tensor([-0.0532,  3.0249])\n",
      "Epoch 57, Loss 29.061079\n",
      "Params: tensor([ 0.2325, -0.0308])\n",
      "Grad: tensor([-0.0533,  3.0248])\n",
      "Epoch 58, Loss 29.060169\n",
      "Params: tensor([ 0.2325, -0.0311])\n",
      "Grad: tensor([-0.0533,  3.0248])\n",
      "Epoch 59, Loss 29.059252\n",
      "Params: tensor([ 0.2325, -0.0314])\n",
      "Grad: tensor([-0.0533,  3.0247])\n",
      "Epoch 60, Loss 29.058331\n",
      "Params: tensor([ 0.2325, -0.0317])\n",
      "Grad: tensor([-0.0532,  3.0247])\n",
      "Epoch 61, Loss 29.057417\n",
      "Params: tensor([ 0.2325, -0.0320])\n",
      "Grad: tensor([-0.0533,  3.0246])\n",
      "Epoch 62, Loss 29.056507\n",
      "Params: tensor([ 0.2325, -0.0323])\n",
      "Grad: tensor([-0.0533,  3.0245])\n",
      "Epoch 63, Loss 29.055586\n",
      "Params: tensor([ 0.2325, -0.0326])\n",
      "Grad: tensor([-0.0532,  3.0245])\n",
      "Epoch 64, Loss 29.054670\n",
      "Params: tensor([ 0.2325, -0.0329])\n",
      "Grad: tensor([-0.0533,  3.0244])\n",
      "Epoch 65, Loss 29.053761\n",
      "Params: tensor([ 0.2325, -0.0332])\n",
      "Grad: tensor([-0.0533,  3.0244])\n",
      "Epoch 66, Loss 29.052843\n",
      "Params: tensor([ 0.2325, -0.0335])\n",
      "Grad: tensor([-0.0533,  3.0243])\n",
      "Epoch 67, Loss 29.051929\n",
      "Params: tensor([ 0.2325, -0.0338])\n",
      "Grad: tensor([-0.0533,  3.0243])\n",
      "Epoch 68, Loss 29.051014\n",
      "Params: tensor([ 0.2326, -0.0341])\n",
      "Grad: tensor([-0.0533,  3.0242])\n",
      "Epoch 69, Loss 29.050098\n",
      "Params: tensor([ 0.2326, -0.0344])\n",
      "Grad: tensor([-0.0532,  3.0242])\n",
      "Epoch 70, Loss 29.049183\n",
      "Params: tensor([ 0.2326, -0.0347])\n",
      "Grad: tensor([-0.0533,  3.0241])\n",
      "Epoch 71, Loss 29.048271\n",
      "Params: tensor([ 0.2326, -0.0350])\n",
      "Grad: tensor([-0.0533,  3.0241])\n",
      "Epoch 72, Loss 29.047346\n",
      "Params: tensor([ 0.2326, -0.0353])\n",
      "Grad: tensor([-0.0532,  3.0240])\n",
      "Epoch 73, Loss 29.046442\n",
      "Params: tensor([ 0.2326, -0.0356])\n",
      "Grad: tensor([-0.0533,  3.0240])\n",
      "Epoch 74, Loss 29.045530\n",
      "Params: tensor([ 0.2326, -0.0359])\n",
      "Grad: tensor([-0.0533,  3.0239])\n",
      "Epoch 75, Loss 29.044611\n",
      "Params: tensor([ 0.2326, -0.0362])\n",
      "Grad: tensor([-0.0533,  3.0239])\n",
      "Epoch 76, Loss 29.043699\n",
      "Params: tensor([ 0.2326, -0.0365])\n",
      "Grad: tensor([-0.0533,  3.0238])\n",
      "Epoch 77, Loss 29.042780\n",
      "Params: tensor([ 0.2326, -0.0368])\n",
      "Grad: tensor([-0.0533,  3.0238])\n",
      "Epoch 78, Loss 29.041870\n",
      "Params: tensor([ 0.2326, -0.0371])\n",
      "Grad: tensor([-0.0533,  3.0237])\n",
      "Epoch 79, Loss 29.040955\n",
      "Params: tensor([ 0.2326, -0.0374])\n",
      "Grad: tensor([-0.0532,  3.0236])\n",
      "Epoch 80, Loss 29.040039\n",
      "Params: tensor([ 0.2326, -0.0377])\n",
      "Grad: tensor([-0.0534,  3.0236])\n",
      "Epoch 81, Loss 29.039122\n",
      "Params: tensor([ 0.2326, -0.0380])\n",
      "Grad: tensor([-0.0533,  3.0235])\n",
      "Epoch 82, Loss 29.038214\n",
      "Params: tensor([ 0.2326, -0.0383])\n",
      "Grad: tensor([-0.0532,  3.0235])\n",
      "Epoch 83, Loss 29.037292\n",
      "Params: tensor([ 0.2326, -0.0386])\n",
      "Grad: tensor([-0.0533,  3.0234])\n",
      "Epoch 84, Loss 29.036379\n",
      "Params: tensor([ 0.2326, -0.0389])\n",
      "Grad: tensor([-0.0532,  3.0234])\n",
      "Epoch 85, Loss 29.035463\n",
      "Params: tensor([ 0.2326, -0.0392])\n",
      "Grad: tensor([-0.0532,  3.0233])\n",
      "Epoch 86, Loss 29.034557\n",
      "Params: tensor([ 0.2326, -0.0395])\n",
      "Grad: tensor([-0.0533,  3.0233])\n",
      "Epoch 87, Loss 29.033638\n",
      "Params: tensor([ 0.2327, -0.0398])\n",
      "Grad: tensor([-0.0532,  3.0232])\n",
      "Epoch 88, Loss 29.032721\n",
      "Params: tensor([ 0.2327, -0.0401])\n",
      "Grad: tensor([-0.0533,  3.0232])\n",
      "Epoch 89, Loss 29.031805\n",
      "Params: tensor([ 0.2327, -0.0405])\n",
      "Grad: tensor([-0.0533,  3.0231])\n",
      "Epoch 90, Loss 29.030895\n",
      "Params: tensor([ 0.2327, -0.0408])\n",
      "Grad: tensor([-0.0532,  3.0231])\n",
      "Epoch 91, Loss 29.029976\n",
      "Params: tensor([ 0.2327, -0.0411])\n",
      "Grad: tensor([-0.0532,  3.0230])\n",
      "Epoch 92, Loss 29.029066\n",
      "Params: tensor([ 0.2327, -0.0414])\n",
      "Grad: tensor([-0.0533,  3.0230])\n",
      "Epoch 93, Loss 29.028151\n",
      "Params: tensor([ 0.2327, -0.0417])\n",
      "Grad: tensor([-0.0532,  3.0229])\n",
      "Epoch 94, Loss 29.027235\n",
      "Params: tensor([ 0.2327, -0.0420])\n",
      "Grad: tensor([-0.0532,  3.0229])\n",
      "Epoch 95, Loss 29.026323\n",
      "Params: tensor([ 0.2327, -0.0423])\n",
      "Grad: tensor([-0.0533,  3.0228])\n",
      "Epoch 96, Loss 29.025410\n",
      "Params: tensor([ 0.2327, -0.0426])\n",
      "Grad: tensor([-0.0533,  3.0227])\n",
      "Epoch 97, Loss 29.024494\n",
      "Params: tensor([ 0.2327, -0.0429])\n",
      "Grad: tensor([-0.0533,  3.0227])\n",
      "Epoch 98, Loss 29.023582\n",
      "Params: tensor([ 0.2327, -0.0432])\n",
      "Grad: tensor([-0.0533,  3.0226])\n",
      "Epoch 99, Loss 29.022669\n",
      "Params: tensor([ 0.2327, -0.0435])\n",
      "Grad: tensor([-0.0532,  3.0226])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([ 0.2327, -0.0438])"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0, 0.0])\n",
    "\n",
    "nepochs = 100\n",
    "\n",
    "learning_rate = 1e-4\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    w, b = params\n",
    "    t_p = model(t_u, w, b)\n",
    "\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "    \n",
    "    # backward pass\n",
    "    grad = grad_fn(t_u, t_c, t_p, w, b)\n",
    "\n",
    "    print('Params:', params)\n",
    "    print('Grad:', grad)\n",
    "    \n",
    "    params = params - learning_rate * grad\n",
    "    \n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_un = 0.1 * t_u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 80.364342\n",
      "Params: tensor([1., 0.])\n",
      "Grad: tensor([-77.6140, -10.6400])\n",
      "Epoch 1, Loss 37.574917\n",
      "Params: tensor([1.7761, 0.1064])\n",
      "Grad: tensor([-30.8623,  -2.3864])\n",
      "Epoch 2, Loss 30.871077\n",
      "Params: tensor([2.0848, 0.1303])\n",
      "Grad: tensor([-12.4631,   0.8587])\n",
      "Epoch 3, Loss 29.756193\n",
      "Params: tensor([2.2094, 0.1217])\n",
      "Grad: tensor([-5.2218,  2.1327])\n",
      "Epoch 4, Loss 29.507149\n",
      "Params: tensor([2.2616, 0.1004])\n",
      "Grad: tensor([-2.3715,  2.6310])\n",
      "Epoch 5, Loss 29.392458\n",
      "Params: tensor([2.2853, 0.0740])\n",
      "Grad: tensor([-1.2492,  2.8241])\n",
      "Epoch 6, Loss 29.298828\n",
      "Params: tensor([2.2978, 0.0458])\n",
      "Grad: tensor([-0.8071,  2.8970])\n",
      "Epoch 7, Loss 29.208717\n",
      "Params: tensor([2.3059, 0.0168])\n",
      "Grad: tensor([-0.6325,  2.9227])\n",
      "Epoch 8, Loss 29.119417\n",
      "Params: tensor([ 2.3122, -0.0124])\n",
      "Grad: tensor([-0.5633,  2.9298])\n",
      "Epoch 9, Loss 29.030487\n",
      "Params: tensor([ 2.3178, -0.0417])\n",
      "Grad: tensor([-0.5355,  2.9295])\n",
      "Epoch 10, Loss 28.941875\n",
      "Params: tensor([ 2.3232, -0.0710])\n",
      "Grad: tensor([-0.5240,  2.9264])\n",
      "Epoch 11, Loss 28.853565\n",
      "Params: tensor([ 2.3284, -0.1003])\n",
      "Grad: tensor([-0.5190,  2.9222])\n",
      "Epoch 12, Loss 28.765556\n",
      "Params: tensor([ 2.3336, -0.1295])\n",
      "Grad: tensor([-0.5165,  2.9175])\n",
      "Epoch 13, Loss 28.677851\n",
      "Params: tensor([ 2.3388, -0.1587])\n",
      "Grad: tensor([-0.5150,  2.9126])\n",
      "Epoch 14, Loss 28.590431\n",
      "Params: tensor([ 2.3439, -0.1878])\n",
      "Grad: tensor([-0.5138,  2.9077])\n",
      "Epoch 15, Loss 28.503321\n",
      "Params: tensor([ 2.3491, -0.2169])\n",
      "Grad: tensor([-0.5129,  2.9028])\n",
      "Epoch 16, Loss 28.416496\n",
      "Params: tensor([ 2.3542, -0.2459])\n",
      "Grad: tensor([-0.5120,  2.8979])\n",
      "Epoch 17, Loss 28.329975\n",
      "Params: tensor([ 2.3593, -0.2749])\n",
      "Grad: tensor([-0.5111,  2.8930])\n",
      "Epoch 18, Loss 28.243738\n",
      "Params: tensor([ 2.3644, -0.3038])\n",
      "Grad: tensor([-0.5102,  2.8881])\n",
      "Epoch 19, Loss 28.157801\n",
      "Params: tensor([ 2.3695, -0.3327])\n",
      "Grad: tensor([-0.5093,  2.8832])\n",
      "Epoch 20, Loss 28.072151\n",
      "Params: tensor([ 2.3746, -0.3615])\n",
      "Grad: tensor([-0.5084,  2.8783])\n",
      "Epoch 21, Loss 27.986799\n",
      "Params: tensor([ 2.3797, -0.3903])\n",
      "Grad: tensor([-0.5076,  2.8734])\n",
      "Epoch 22, Loss 27.901731\n",
      "Params: tensor([ 2.3848, -0.4190])\n",
      "Grad: tensor([-0.5067,  2.8685])\n",
      "Epoch 23, Loss 27.816956\n",
      "Params: tensor([ 2.3899, -0.4477])\n",
      "Grad: tensor([-0.5059,  2.8636])\n",
      "Epoch 24, Loss 27.732466\n",
      "Params: tensor([ 2.3949, -0.4763])\n",
      "Grad: tensor([-0.5050,  2.8588])\n",
      "Epoch 25, Loss 27.648256\n",
      "Params: tensor([ 2.4000, -0.5049])\n",
      "Grad: tensor([-0.5042,  2.8539])\n",
      "Epoch 26, Loss 27.564342\n",
      "Params: tensor([ 2.4050, -0.5335])\n",
      "Grad: tensor([-0.5033,  2.8490])\n",
      "Epoch 27, Loss 27.480711\n",
      "Params: tensor([ 2.4101, -0.5620])\n",
      "Grad: tensor([-0.5024,  2.8442])\n",
      "Epoch 28, Loss 27.397358\n",
      "Params: tensor([ 2.4151, -0.5904])\n",
      "Grad: tensor([-0.5016,  2.8394])\n",
      "Epoch 29, Loss 27.314295\n",
      "Params: tensor([ 2.4201, -0.6188])\n",
      "Grad: tensor([-0.5007,  2.8346])\n",
      "Epoch 30, Loss 27.231512\n",
      "Params: tensor([ 2.4251, -0.6471])\n",
      "Grad: tensor([-0.4999,  2.8297])\n",
      "Epoch 31, Loss 27.149006\n",
      "Params: tensor([ 2.4301, -0.6754])\n",
      "Grad: tensor([-0.4990,  2.8249])\n",
      "Epoch 32, Loss 27.066790\n",
      "Params: tensor([ 2.4351, -0.7037])\n",
      "Grad: tensor([-0.4982,  2.8201])\n",
      "Epoch 33, Loss 26.984844\n",
      "Params: tensor([ 2.4401, -0.7319])\n",
      "Grad: tensor([-0.4973,  2.8153])\n",
      "Epoch 34, Loss 26.903173\n",
      "Params: tensor([ 2.4450, -0.7600])\n",
      "Grad: tensor([-0.4965,  2.8106])\n",
      "Epoch 35, Loss 26.821791\n",
      "Params: tensor([ 2.4500, -0.7881])\n",
      "Grad: tensor([-0.4957,  2.8058])\n",
      "Epoch 36, Loss 26.740675\n",
      "Params: tensor([ 2.4550, -0.8162])\n",
      "Grad: tensor([-0.4948,  2.8010])\n",
      "Epoch 37, Loss 26.659838\n",
      "Params: tensor([ 2.4599, -0.8442])\n",
      "Grad: tensor([-0.4940,  2.7963])\n",
      "Epoch 38, Loss 26.579279\n",
      "Params: tensor([ 2.4649, -0.8722])\n",
      "Grad: tensor([-0.4931,  2.7915])\n",
      "Epoch 39, Loss 26.498987\n",
      "Params: tensor([ 2.4698, -0.9001])\n",
      "Grad: tensor([-0.4923,  2.7868])\n",
      "Epoch 40, Loss 26.418974\n",
      "Params: tensor([ 2.4747, -0.9280])\n",
      "Grad: tensor([-0.4915,  2.7820])\n",
      "Epoch 41, Loss 26.339228\n",
      "Params: tensor([ 2.4796, -0.9558])\n",
      "Grad: tensor([-0.4906,  2.7773])\n",
      "Epoch 42, Loss 26.259752\n",
      "Params: tensor([ 2.4845, -0.9836])\n",
      "Grad: tensor([-0.4898,  2.7726])\n",
      "Epoch 43, Loss 26.180548\n",
      "Params: tensor([ 2.4894, -1.0113])\n",
      "Grad: tensor([-0.4890,  2.7679])\n",
      "Epoch 44, Loss 26.101616\n",
      "Params: tensor([ 2.4943, -1.0390])\n",
      "Grad: tensor([-0.4881,  2.7632])\n",
      "Epoch 45, Loss 26.022949\n",
      "Params: tensor([ 2.4992, -1.0666])\n",
      "Grad: tensor([-0.4873,  2.7585])\n",
      "Epoch 46, Loss 25.944542\n",
      "Params: tensor([ 2.5041, -1.0942])\n",
      "Grad: tensor([-0.4865,  2.7538])\n",
      "Epoch 47, Loss 25.866417\n",
      "Params: tensor([ 2.5089, -1.1217])\n",
      "Grad: tensor([-0.4856,  2.7491])\n",
      "Epoch 48, Loss 25.788546\n",
      "Params: tensor([ 2.5138, -1.1492])\n",
      "Grad: tensor([-0.4848,  2.7444])\n",
      "Epoch 49, Loss 25.710936\n",
      "Params: tensor([ 2.5186, -1.1766])\n",
      "Grad: tensor([-0.4840,  2.7398])\n",
      "Epoch 50, Loss 25.633600\n",
      "Params: tensor([ 2.5235, -1.2040])\n",
      "Grad: tensor([-0.4832,  2.7351])\n",
      "Epoch 51, Loss 25.556524\n",
      "Params: tensor([ 2.5283, -1.2314])\n",
      "Grad: tensor([-0.4823,  2.7305])\n",
      "Epoch 52, Loss 25.479700\n",
      "Params: tensor([ 2.5331, -1.2587])\n",
      "Grad: tensor([-0.4815,  2.7258])\n",
      "Epoch 53, Loss 25.403149\n",
      "Params: tensor([ 2.5379, -1.2860])\n",
      "Grad: tensor([-0.4807,  2.7212])\n",
      "Epoch 54, Loss 25.326851\n",
      "Params: tensor([ 2.5428, -1.3132])\n",
      "Grad: tensor([-0.4799,  2.7166])\n",
      "Epoch 55, Loss 25.250811\n",
      "Params: tensor([ 2.5476, -1.3403])\n",
      "Grad: tensor([-0.4791,  2.7120])\n",
      "Epoch 56, Loss 25.175035\n",
      "Params: tensor([ 2.5523, -1.3675])\n",
      "Grad: tensor([-0.4783,  2.7074])\n",
      "Epoch 57, Loss 25.099510\n",
      "Params: tensor([ 2.5571, -1.3945])\n",
      "Grad: tensor([-0.4775,  2.7028])\n",
      "Epoch 58, Loss 25.024248\n",
      "Params: tensor([ 2.5619, -1.4216])\n",
      "Grad: tensor([-0.4766,  2.6982])\n",
      "Epoch 59, Loss 24.949238\n",
      "Params: tensor([ 2.5667, -1.4485])\n",
      "Grad: tensor([-0.4758,  2.6936])\n",
      "Epoch 60, Loss 24.874483\n",
      "Params: tensor([ 2.5714, -1.4755])\n",
      "Grad: tensor([-0.4750,  2.6890])\n",
      "Epoch 61, Loss 24.799980\n",
      "Params: tensor([ 2.5762, -1.5024])\n",
      "Grad: tensor([-0.4742,  2.6845])\n",
      "Epoch 62, Loss 24.725737\n",
      "Params: tensor([ 2.5809, -1.5292])\n",
      "Grad: tensor([-0.4734,  2.6799])\n",
      "Epoch 63, Loss 24.651735\n",
      "Params: tensor([ 2.5857, -1.5560])\n",
      "Grad: tensor([-0.4726,  2.6753])\n",
      "Epoch 64, Loss 24.577986\n",
      "Params: tensor([ 2.5904, -1.5828])\n",
      "Grad: tensor([-0.4718,  2.6708])\n",
      "Epoch 65, Loss 24.504494\n",
      "Params: tensor([ 2.5951, -1.6095])\n",
      "Grad: tensor([-0.4710,  2.6663])\n",
      "Epoch 66, Loss 24.431250\n",
      "Params: tensor([ 2.5998, -1.6361])\n",
      "Grad: tensor([-0.4702,  2.6617])\n",
      "Epoch 67, Loss 24.358257\n",
      "Params: tensor([ 2.6045, -1.6628])\n",
      "Grad: tensor([-0.4694,  2.6572])\n",
      "Epoch 68, Loss 24.285505\n",
      "Params: tensor([ 2.6092, -1.6893])\n",
      "Grad: tensor([-0.4686,  2.6527])\n",
      "Epoch 69, Loss 24.212996\n",
      "Params: tensor([ 2.6139, -1.7159])\n",
      "Grad: tensor([-0.4678,  2.6482])\n",
      "Epoch 70, Loss 24.140741\n",
      "Params: tensor([ 2.6186, -1.7423])\n",
      "Grad: tensor([-0.4670,  2.6437])\n",
      "Epoch 71, Loss 24.068733\n",
      "Params: tensor([ 2.6232, -1.7688])\n",
      "Grad: tensor([-0.4662,  2.6392])\n",
      "Epoch 72, Loss 23.996967\n",
      "Params: tensor([ 2.6279, -1.7952])\n",
      "Grad: tensor([-0.4654,  2.6347])\n",
      "Epoch 73, Loss 23.925446\n",
      "Params: tensor([ 2.6326, -1.8215])\n",
      "Grad: tensor([-0.4646,  2.6302])\n",
      "Epoch 74, Loss 23.854168\n",
      "Params: tensor([ 2.6372, -1.8478])\n",
      "Grad: tensor([-0.4638,  2.6258])\n",
      "Epoch 75, Loss 23.783125\n",
      "Params: tensor([ 2.6418, -1.8741])\n",
      "Grad: tensor([-0.4631,  2.6213])\n",
      "Epoch 76, Loss 23.712328\n",
      "Params: tensor([ 2.6465, -1.9003])\n",
      "Grad: tensor([-0.4623,  2.6169])\n",
      "Epoch 77, Loss 23.641771\n",
      "Params: tensor([ 2.6511, -1.9265])\n",
      "Grad: tensor([-0.4615,  2.6124])\n",
      "Epoch 78, Loss 23.571455\n",
      "Params: tensor([ 2.6557, -1.9526])\n",
      "Grad: tensor([-0.4607,  2.6080])\n",
      "Epoch 79, Loss 23.501379\n",
      "Params: tensor([ 2.6603, -1.9787])\n",
      "Grad: tensor([-0.4599,  2.6035])\n",
      "Epoch 80, Loss 23.431538\n",
      "Params: tensor([ 2.6649, -2.0047])\n",
      "Grad: tensor([-0.4591,  2.5991])\n",
      "Epoch 81, Loss 23.361938\n",
      "Params: tensor([ 2.6695, -2.0307])\n",
      "Grad: tensor([-0.4584,  2.5947])\n",
      "Epoch 82, Loss 23.292570\n",
      "Params: tensor([ 2.6741, -2.0566])\n",
      "Grad: tensor([-0.4576,  2.5903])\n",
      "Epoch 83, Loss 23.223436\n",
      "Params: tensor([ 2.6787, -2.0825])\n",
      "Grad: tensor([-0.4568,  2.5859])\n",
      "Epoch 84, Loss 23.154539\n",
      "Params: tensor([ 2.6832, -2.1084])\n",
      "Grad: tensor([-0.4560,  2.5815])\n",
      "Epoch 85, Loss 23.085882\n",
      "Params: tensor([ 2.6878, -2.1342])\n",
      "Grad: tensor([-0.4553,  2.5771])\n",
      "Epoch 86, Loss 23.017447\n",
      "Params: tensor([ 2.6923, -2.1600])\n",
      "Grad: tensor([-0.4545,  2.5727])\n",
      "Epoch 87, Loss 22.949251\n",
      "Params: tensor([ 2.6969, -2.1857])\n",
      "Grad: tensor([-0.4537,  2.5684])\n",
      "Epoch 88, Loss 22.881283\n",
      "Params: tensor([ 2.7014, -2.2114])\n",
      "Grad: tensor([-0.4529,  2.5640])\n",
      "Epoch 89, Loss 22.813547\n",
      "Params: tensor([ 2.7060, -2.2370])\n",
      "Grad: tensor([-0.4522,  2.5597])\n",
      "Epoch 90, Loss 22.746044\n",
      "Params: tensor([ 2.7105, -2.2626])\n",
      "Grad: tensor([-0.4514,  2.5553])\n",
      "Epoch 91, Loss 22.678770\n",
      "Params: tensor([ 2.7150, -2.2882])\n",
      "Grad: tensor([-0.4506,  2.5510])\n",
      "Epoch 92, Loss 22.611717\n",
      "Params: tensor([ 2.7195, -2.3137])\n",
      "Grad: tensor([-0.4499,  2.5466])\n",
      "Epoch 93, Loss 22.544899\n",
      "Params: tensor([ 2.7240, -2.3392])\n",
      "Grad: tensor([-0.4491,  2.5423])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 94, Loss 22.478304\n",
      "Params: tensor([ 2.7285, -2.3646])\n",
      "Grad: tensor([-0.4483,  2.5380])\n",
      "Epoch 95, Loss 22.411938\n",
      "Params: tensor([ 2.7330, -2.3900])\n",
      "Grad: tensor([-0.4476,  2.5337])\n",
      "Epoch 96, Loss 22.345795\n",
      "Params: tensor([ 2.7374, -2.4153])\n",
      "Grad: tensor([-0.4468,  2.5294])\n",
      "Epoch 97, Loss 22.279875\n",
      "Params: tensor([ 2.7419, -2.4406])\n",
      "Grad: tensor([-0.4461,  2.5251])\n",
      "Epoch 98, Loss 22.214186\n",
      "Params: tensor([ 2.7464, -2.4658])\n",
      "Grad: tensor([-0.4453,  2.5208])\n",
      "Epoch 99, Loss 22.148710\n",
      "Params: tensor([ 2.7508, -2.4910])\n",
      "Grad: tensor([-0.4445,  2.5165])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([ 2.7553, -2.5162])"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0, 0.0])\n",
    "\n",
    "nepochs = 100\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    w, b = params\n",
    "    t_p = model(t_un, w, b)\n",
    "\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "    \n",
    "    # backward pass\n",
    "    grad = grad_fn(t_un, t_c, t_p, w, b)\n",
    "\n",
    "    print('Params:', params)\n",
    "    print('Grad:', grad)\n",
    "    \n",
    "    params = params - learning_rate * grad\n",
    "    \n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 80.364342\n",
      "Epoch 1, Loss 37.574917\n",
      "Epoch 2, Loss 30.871077\n",
      "Epoch 3, Loss 29.756193\n",
      "Epoch 4, Loss 29.507149\n",
      "Epoch 5, Loss 29.392458\n",
      "Epoch 6, Loss 29.298828\n",
      "Epoch 7, Loss 29.208717\n",
      "Epoch 8, Loss 29.119417\n",
      "Epoch 9, Loss 29.030487\n",
      "Epoch 10, Loss 28.941875\n",
      "Epoch 11, Loss 28.853565\n",
      "Epoch 12, Loss 28.765556\n",
      "Epoch 13, Loss 28.677851\n",
      "Epoch 14, Loss 28.590431\n",
      "Epoch 15, Loss 28.503321\n",
      "Epoch 16, Loss 28.416496\n",
      "Epoch 17, Loss 28.329975\n",
      "Epoch 18, Loss 28.243738\n",
      "Epoch 19, Loss 28.157801\n",
      "Epoch 20, Loss 28.072151\n",
      "Epoch 21, Loss 27.986799\n",
      "Epoch 22, Loss 27.901731\n",
      "Epoch 23, Loss 27.816956\n",
      "Epoch 24, Loss 27.732466\n",
      "Epoch 25, Loss 27.648256\n",
      "Epoch 26, Loss 27.564342\n",
      "Epoch 27, Loss 27.480711\n",
      "Epoch 28, Loss 27.397358\n",
      "Epoch 29, Loss 27.314295\n",
      "Epoch 30, Loss 27.231512\n",
      "Epoch 31, Loss 27.149006\n",
      "Epoch 32, Loss 27.066790\n",
      "Epoch 33, Loss 26.984844\n",
      "Epoch 34, Loss 26.903173\n",
      "Epoch 35, Loss 26.821791\n",
      "Epoch 36, Loss 26.740675\n",
      "Epoch 37, Loss 26.659838\n",
      "Epoch 38, Loss 26.579279\n",
      "Epoch 39, Loss 26.498987\n",
      "Epoch 40, Loss 26.418974\n",
      "Epoch 41, Loss 26.339228\n",
      "Epoch 42, Loss 26.259752\n",
      "Epoch 43, Loss 26.180548\n",
      "Epoch 44, Loss 26.101616\n",
      "Epoch 45, Loss 26.022949\n",
      "Epoch 46, Loss 25.944542\n",
      "Epoch 47, Loss 25.866417\n",
      "Epoch 48, Loss 25.788546\n",
      "Epoch 49, Loss 25.710936\n",
      "Epoch 50, Loss 25.633600\n",
      "Epoch 51, Loss 25.556524\n",
      "Epoch 52, Loss 25.479700\n",
      "Epoch 53, Loss 25.403149\n",
      "Epoch 54, Loss 25.326851\n",
      "Epoch 55, Loss 25.250811\n",
      "Epoch 56, Loss 25.175035\n",
      "Epoch 57, Loss 25.099510\n",
      "Epoch 58, Loss 25.024248\n",
      "Epoch 59, Loss 24.949238\n",
      "Epoch 60, Loss 24.874483\n",
      "Epoch 61, Loss 24.799980\n",
      "Epoch 62, Loss 24.725737\n",
      "Epoch 63, Loss 24.651735\n",
      "Epoch 64, Loss 24.577986\n",
      "Epoch 65, Loss 24.504494\n",
      "Epoch 66, Loss 24.431250\n",
      "Epoch 67, Loss 24.358257\n",
      "Epoch 68, Loss 24.285505\n",
      "Epoch 69, Loss 24.212996\n",
      "Epoch 70, Loss 24.140741\n",
      "Epoch 71, Loss 24.068733\n",
      "Epoch 72, Loss 23.996967\n",
      "Epoch 73, Loss 23.925446\n",
      "Epoch 74, Loss 23.854168\n",
      "Epoch 75, Loss 23.783125\n",
      "Epoch 76, Loss 23.712328\n",
      "Epoch 77, Loss 23.641771\n",
      "Epoch 78, Loss 23.571455\n",
      "Epoch 79, Loss 23.501379\n",
      "Epoch 80, Loss 23.431538\n",
      "Epoch 81, Loss 23.361938\n",
      "Epoch 82, Loss 23.292570\n",
      "Epoch 83, Loss 23.223436\n",
      "Epoch 84, Loss 23.154539\n",
      "Epoch 85, Loss 23.085882\n",
      "Epoch 86, Loss 23.017447\n",
      "Epoch 87, Loss 22.949251\n",
      "Epoch 88, Loss 22.881283\n",
      "Epoch 89, Loss 22.813547\n",
      "Epoch 90, Loss 22.746044\n",
      "Epoch 91, Loss 22.678770\n",
      "Epoch 92, Loss 22.611717\n",
      "Epoch 93, Loss 22.544899\n",
      "Epoch 94, Loss 22.478304\n",
      "Epoch 95, Loss 22.411938\n",
      "Epoch 96, Loss 22.345795\n",
      "Epoch 97, Loss 22.279875\n",
      "Epoch 98, Loss 22.214186\n",
      "Epoch 99, Loss 22.148710\n",
      "Epoch 100, Loss 22.083464\n",
      "Epoch 101, Loss 22.018436\n",
      "Epoch 102, Loss 21.953630\n",
      "Epoch 103, Loss 21.889046\n",
      "Epoch 104, Loss 21.824677\n",
      "Epoch 105, Loss 21.760530\n",
      "Epoch 106, Loss 21.696600\n",
      "Epoch 107, Loss 21.632881\n",
      "Epoch 108, Loss 21.569389\n",
      "Epoch 109, Loss 21.506104\n",
      "Epoch 110, Loss 21.443037\n",
      "Epoch 111, Loss 21.380190\n",
      "Epoch 112, Loss 21.317547\n",
      "Epoch 113, Loss 21.255119\n",
      "Epoch 114, Loss 21.192904\n",
      "Epoch 115, Loss 21.130901\n",
      "Epoch 116, Loss 21.069105\n",
      "Epoch 117, Loss 21.007528\n",
      "Epoch 118, Loss 20.946152\n",
      "Epoch 119, Loss 20.884983\n",
      "Epoch 120, Loss 20.824028\n",
      "Epoch 121, Loss 20.763273\n",
      "Epoch 122, Loss 20.702726\n",
      "Epoch 123, Loss 20.642384\n",
      "Epoch 124, Loss 20.582251\n",
      "Epoch 125, Loss 20.522322\n",
      "Epoch 126, Loss 20.462593\n",
      "Epoch 127, Loss 20.403069\n",
      "Epoch 128, Loss 20.343746\n",
      "Epoch 129, Loss 20.284622\n",
      "Epoch 130, Loss 20.225704\n",
      "Epoch 131, Loss 20.166983\n",
      "Epoch 132, Loss 20.108461\n",
      "Epoch 133, Loss 20.050135\n",
      "Epoch 134, Loss 19.992012\n",
      "Epoch 135, Loss 19.934088\n",
      "Epoch 136, Loss 19.876352\n",
      "Epoch 137, Loss 19.818825\n",
      "Epoch 138, Loss 19.761480\n",
      "Epoch 139, Loss 19.704338\n",
      "Epoch 140, Loss 19.647383\n",
      "Epoch 141, Loss 19.590630\n",
      "Epoch 142, Loss 19.534063\n",
      "Epoch 143, Loss 19.477690\n",
      "Epoch 144, Loss 19.421507\n",
      "Epoch 145, Loss 19.365517\n",
      "Epoch 146, Loss 19.309715\n",
      "Epoch 147, Loss 19.254107\n",
      "Epoch 148, Loss 19.198685\n",
      "Epoch 149, Loss 19.143446\n",
      "Epoch 150, Loss 19.088400\n",
      "Epoch 151, Loss 19.033545\n",
      "Epoch 152, Loss 18.978868\n",
      "Epoch 153, Loss 18.924377\n",
      "Epoch 154, Loss 18.870081\n",
      "Epoch 155, Loss 18.815960\n",
      "Epoch 156, Loss 18.762022\n",
      "Epoch 157, Loss 18.708269\n",
      "Epoch 158, Loss 18.654703\n",
      "Epoch 159, Loss 18.601313\n",
      "Epoch 160, Loss 18.548111\n",
      "Epoch 161, Loss 18.495083\n",
      "Epoch 162, Loss 18.442238\n",
      "Epoch 163, Loss 18.389570\n",
      "Epoch 164, Loss 18.337080\n",
      "Epoch 165, Loss 18.284777\n",
      "Epoch 166, Loss 18.232643\n",
      "Epoch 167, Loss 18.180687\n",
      "Epoch 168, Loss 18.128904\n",
      "Epoch 169, Loss 18.077299\n",
      "Epoch 170, Loss 18.025879\n",
      "Epoch 171, Loss 17.974623\n",
      "Epoch 172, Loss 17.923546\n",
      "Epoch 173, Loss 17.872641\n",
      "Epoch 174, Loss 17.821907\n",
      "Epoch 175, Loss 17.771343\n",
      "Epoch 176, Loss 17.720955\n",
      "Epoch 177, Loss 17.670738\n",
      "Epoch 178, Loss 17.620691\n",
      "Epoch 179, Loss 17.570814\n",
      "Epoch 180, Loss 17.521105\n",
      "Epoch 181, Loss 17.471563\n",
      "Epoch 182, Loss 17.422194\n",
      "Epoch 183, Loss 17.372992\n",
      "Epoch 184, Loss 17.323954\n",
      "Epoch 185, Loss 17.275085\n",
      "Epoch 186, Loss 17.226379\n",
      "Epoch 187, Loss 17.177839\n",
      "Epoch 188, Loss 17.129467\n",
      "Epoch 189, Loss 17.081255\n",
      "Epoch 190, Loss 17.033207\n",
      "Epoch 191, Loss 16.985327\n",
      "Epoch 192, Loss 16.937605\n",
      "Epoch 193, Loss 16.890047\n",
      "Epoch 194, Loss 16.842649\n",
      "Epoch 195, Loss 16.795412\n",
      "Epoch 196, Loss 16.748339\n",
      "Epoch 197, Loss 16.701424\n",
      "Epoch 198, Loss 16.654661\n",
      "Epoch 199, Loss 16.608065\n",
      "Epoch 200, Loss 16.561625\n",
      "Epoch 201, Loss 16.515343\n",
      "Epoch 202, Loss 16.469219\n",
      "Epoch 203, Loss 16.423250\n",
      "Epoch 204, Loss 16.377434\n",
      "Epoch 205, Loss 16.331776\n",
      "Epoch 206, Loss 16.286276\n",
      "Epoch 207, Loss 16.240925\n",
      "Epoch 208, Loss 16.195734\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 460, Loss 8.559597\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Epoch 1807, Loss 2.985381\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1808, Loss 2.985184\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2212, Loss 2.942211\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2665, Loss 2.930766\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3079, Loss 2.928410\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3524, Loss 2.927814\n",
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      "Epoch 3929, Loss 2.927688\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3930, Loss 2.927688\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4518, Loss 2.927650\n",
      "Epoch 4519, Loss 2.927651\n",
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      "Epoch 4790, Loss 2.927648\n",
      "Epoch 4791, Loss 2.927647\n",
      "Epoch 4792, Loss 2.927650\n",
      "Epoch 4793, Loss 2.927648\n",
      "Epoch 4794, Loss 2.927649\n",
      "Epoch 4795, Loss 2.927648\n",
      "Epoch 4796, Loss 2.927648\n",
      "Epoch 4797, Loss 2.927648\n",
      "Epoch 4798, Loss 2.927648\n",
      "Epoch 4799, Loss 2.927648\n",
      "Epoch 4800, Loss 2.927647\n",
      "Epoch 4801, Loss 2.927649\n",
      "Epoch 4802, Loss 2.927647\n",
      "Epoch 4803, Loss 2.927648\n",
      "Epoch 4804, Loss 2.927649\n",
      "Epoch 4805, Loss 2.927646\n",
      "Epoch 4806, Loss 2.927648\n",
      "Epoch 4807, Loss 2.927648\n",
      "Epoch 4808, Loss 2.927649\n",
      "Epoch 4809, Loss 2.927648\n",
      "Epoch 4810, Loss 2.927649\n",
      "Epoch 4811, Loss 2.927649\n",
      "Epoch 4812, Loss 2.927647\n",
      "Epoch 4813, Loss 2.927648\n",
      "Epoch 4814, Loss 2.927648\n",
      "Epoch 4815, Loss 2.927647\n",
      "Epoch 4816, Loss 2.927648\n",
      "Epoch 4817, Loss 2.927648\n",
      "Epoch 4818, Loss 2.927647\n",
      "Epoch 4819, Loss 2.927648\n",
      "Epoch 4820, Loss 2.927649\n",
      "Epoch 4821, Loss 2.927648\n",
      "Epoch 4822, Loss 2.927647\n",
      "Epoch 4823, Loss 2.927649\n",
      "Epoch 4824, Loss 2.927649\n",
      "Epoch 4825, Loss 2.927649\n",
      "Epoch 4826, Loss 2.927648\n",
      "Epoch 4827, Loss 2.927649\n",
      "Epoch 4828, Loss 2.927649\n",
      "Epoch 4829, Loss 2.927647\n",
      "Epoch 4830, Loss 2.927648\n",
      "Epoch 4831, Loss 2.927648\n",
      "Epoch 4832, Loss 2.927646\n",
      "Epoch 4833, Loss 2.927648\n",
      "Epoch 4834, Loss 2.927648\n",
      "Epoch 4835, Loss 2.927647\n",
      "Epoch 4836, Loss 2.927648\n",
      "Epoch 4837, Loss 2.927647\n",
      "Epoch 4838, Loss 2.927648\n",
      "Epoch 4839, Loss 2.927647\n",
      "Epoch 4840, Loss 2.927650\n",
      "Epoch 4841, Loss 2.927648\n",
      "Epoch 4842, Loss 2.927648\n",
      "Epoch 4843, Loss 2.927649\n",
      "Epoch 4844, Loss 2.927647\n",
      "Epoch 4845, Loss 2.927647\n",
      "Epoch 4846, Loss 2.927648\n",
      "Epoch 4847, Loss 2.927647\n",
      "Epoch 4848, Loss 2.927648\n",
      "Epoch 4849, Loss 2.927647\n",
      "Epoch 4850, Loss 2.927648\n",
      "Epoch 4851, Loss 2.927647\n",
      "Epoch 4852, Loss 2.927648\n",
      "Epoch 4853, Loss 2.927649\n",
      "Epoch 4854, Loss 2.927647\n",
      "Epoch 4855, Loss 2.927648\n",
      "Epoch 4856, Loss 2.927647\n",
      "Epoch 4857, Loss 2.927648\n",
      "Epoch 4858, Loss 2.927648\n",
      "Epoch 4859, Loss 2.927649\n",
      "Epoch 4860, Loss 2.927648\n",
      "Epoch 4861, Loss 2.927646\n",
      "Epoch 4862, Loss 2.927648\n",
      "Epoch 4863, Loss 2.927648\n",
      "Epoch 4864, Loss 2.927647\n",
      "Epoch 4865, Loss 2.927648\n",
      "Epoch 4866, Loss 2.927648\n",
      "Epoch 4867, Loss 2.927648\n",
      "Epoch 4868, Loss 2.927648\n",
      "Epoch 4869, Loss 2.927648\n",
      "Epoch 4870, Loss 2.927648\n",
      "Epoch 4871, Loss 2.927647\n",
      "Epoch 4872, Loss 2.927648\n",
      "Epoch 4873, Loss 2.927649\n",
      "Epoch 4874, Loss 2.927647\n",
      "Epoch 4875, Loss 2.927648\n",
      "Epoch 4876, Loss 2.927647\n",
      "Epoch 4877, Loss 2.927648\n",
      "Epoch 4878, Loss 2.927647\n",
      "Epoch 4879, Loss 2.927648\n",
      "Epoch 4880, Loss 2.927648\n",
      "Epoch 4881, Loss 2.927648\n",
      "Epoch 4882, Loss 2.927648\n",
      "Epoch 4883, Loss 2.927647\n",
      "Epoch 4884, Loss 2.927647\n",
      "Epoch 4885, Loss 2.927649\n",
      "Epoch 4886, Loss 2.927647\n",
      "Epoch 4887, Loss 2.927649\n",
      "Epoch 4888, Loss 2.927648\n",
      "Epoch 4889, Loss 2.927648\n",
      "Epoch 4890, Loss 2.927647\n",
      "Epoch 4891, Loss 2.927647\n",
      "Epoch 4892, Loss 2.927648\n",
      "Epoch 4893, Loss 2.927646\n",
      "Epoch 4894, Loss 2.927649\n",
      "Epoch 4895, Loss 2.927648\n",
      "Epoch 4896, Loss 2.927648\n",
      "Epoch 4897, Loss 2.927647\n",
      "Epoch 4898, Loss 2.927647\n",
      "Epoch 4899, Loss 2.927648\n",
      "Epoch 4900, Loss 2.927648\n",
      "Epoch 4901, Loss 2.927649\n",
      "Epoch 4902, Loss 2.927648\n",
      "Epoch 4903, Loss 2.927647\n",
      "Epoch 4904, Loss 2.927647\n",
      "Epoch 4905, Loss 2.927646\n",
      "Epoch 4906, Loss 2.927648\n",
      "Epoch 4907, Loss 2.927647\n",
      "Epoch 4908, Loss 2.927647\n",
      "Epoch 4909, Loss 2.927648\n",
      "Epoch 4910, Loss 2.927647\n",
      "Epoch 4911, Loss 2.927648\n",
      "Epoch 4912, Loss 2.927647\n",
      "Epoch 4913, Loss 2.927648\n",
      "Epoch 4914, Loss 2.927648\n",
      "Epoch 4915, Loss 2.927647\n",
      "Epoch 4916, Loss 2.927648\n",
      "Epoch 4917, Loss 2.927649\n",
      "Epoch 4918, Loss 2.927648\n",
      "Epoch 4919, Loss 2.927648\n",
      "Epoch 4920, Loss 2.927647\n",
      "Epoch 4921, Loss 2.927647\n",
      "Epoch 4922, Loss 2.927648\n",
      "Epoch 4923, Loss 2.927647\n",
      "Epoch 4924, Loss 2.927648\n",
      "Epoch 4925, Loss 2.927646\n",
      "Epoch 4926, Loss 2.927647\n",
      "Epoch 4927, Loss 2.927648\n",
      "Epoch 4928, Loss 2.927647\n",
      "Epoch 4929, Loss 2.927648\n",
      "Epoch 4930, Loss 2.927648\n",
      "Epoch 4931, Loss 2.927648\n",
      "Epoch 4932, Loss 2.927646\n",
      "Epoch 4933, Loss 2.927649\n",
      "Epoch 4934, Loss 2.927648\n",
      "Epoch 4935, Loss 2.927646\n",
      "Epoch 4936, Loss 2.927649\n",
      "Epoch 4937, Loss 2.927646\n",
      "Epoch 4938, Loss 2.927647\n",
      "Epoch 4939, Loss 2.927646\n",
      "Epoch 4940, Loss 2.927648\n",
      "Epoch 4941, Loss 2.927648\n",
      "Epoch 4942, Loss 2.927646\n",
      "Epoch 4943, Loss 2.927648\n",
      "Epoch 4944, Loss 2.927647\n",
      "Epoch 4945, Loss 2.927647\n",
      "Epoch 4946, Loss 2.927648\n",
      "Epoch 4947, Loss 2.927649\n",
      "Epoch 4948, Loss 2.927646\n",
      "Epoch 4949, Loss 2.927648\n",
      "Epoch 4950, Loss 2.927646\n",
      "Epoch 4951, Loss 2.927646\n",
      "Epoch 4952, Loss 2.927647\n",
      "Epoch 4953, Loss 2.927647\n",
      "Epoch 4954, Loss 2.927647\n",
      "Epoch 4955, Loss 2.927647\n",
      "Epoch 4956, Loss 2.927648\n",
      "Epoch 4957, Loss 2.927646\n",
      "Epoch 4958, Loss 2.927648\n",
      "Epoch 4959, Loss 2.927647\n",
      "Epoch 4960, Loss 2.927648\n",
      "Epoch 4961, Loss 2.927646\n",
      "Epoch 4962, Loss 2.927648\n",
      "Epoch 4963, Loss 2.927647\n",
      "Epoch 4964, Loss 2.927648\n",
      "Epoch 4965, Loss 2.927648\n",
      "Epoch 4966, Loss 2.927646\n",
      "Epoch 4967, Loss 2.927647\n",
      "Epoch 4968, Loss 2.927648\n",
      "Epoch 4969, Loss 2.927648\n",
      "Epoch 4970, Loss 2.927648\n",
      "Epoch 4971, Loss 2.927647\n",
      "Epoch 4972, Loss 2.927648\n",
      "Epoch 4973, Loss 2.927646\n",
      "Epoch 4974, Loss 2.927647\n",
      "Epoch 4975, Loss 2.927647\n",
      "Epoch 4976, Loss 2.927647\n",
      "Epoch 4977, Loss 2.927647\n",
      "Epoch 4978, Loss 2.927648\n",
      "Epoch 4979, Loss 2.927647\n",
      "Epoch 4980, Loss 2.927646\n",
      "Epoch 4981, Loss 2.927648\n",
      "Epoch 4982, Loss 2.927646\n",
      "Epoch 4983, Loss 2.927648\n",
      "Epoch 4984, Loss 2.927646\n",
      "Epoch 4985, Loss 2.927648\n",
      "Epoch 4986, Loss 2.927647\n",
      "Epoch 4987, Loss 2.927647\n",
      "Epoch 4988, Loss 2.927647\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4989, Loss 2.927648\n",
      "Epoch 4990, Loss 2.927646\n",
      "Epoch 4991, Loss 2.927648\n",
      "Epoch 4992, Loss 2.927647\n",
      "Epoch 4993, Loss 2.927646\n",
      "Epoch 4994, Loss 2.927647\n",
      "Epoch 4995, Loss 2.927648\n",
      "Epoch 4996, Loss 2.927647\n",
      "Epoch 4997, Loss 2.927647\n",
      "Epoch 4998, Loss 2.927647\n",
      "Epoch 4999, Loss 2.927648\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([  5.3671, -17.3012])"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0, 0.0])\n",
    "\n",
    "nepochs = 5000\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    w, b = params\n",
    "    t_p = model(t_un, w, b)\n",
    "\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "    \n",
    "    # backward pass\n",
    "    grad = grad_fn(t_un, t_c, t_p, w, b)\n",
    "\n",
    "    params = params - learning_rate * grad\n",
    "    \n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b\n",
    "\n",
    "def loss_fn(t_p, t_c):\n",
    "    sq_diffs = (t_p - t_c)**2\n",
    "    return sq_diffs.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "loss = loss_fn(model(t_u, *params), t_c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params.grad is None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss.backward()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([4517.2969,   82.6000])"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params.grad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "if params.grad is not None:\n",
    "    params.grad.zero_()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 80.364342\n",
      "Epoch 1, Loss 37.574917\n",
      "Epoch 2, Loss 30.871077\n",
      "Epoch 3, Loss 29.756193\n",
      "Epoch 4, Loss 29.507149\n",
      "Epoch 5, Loss 29.392458\n",
      "Epoch 6, Loss 29.298828\n",
      "Epoch 7, Loss 29.208717\n",
      "Epoch 8, Loss 29.119417\n",
      "Epoch 9, Loss 29.030487\n",
      "Epoch 10, Loss 28.941875\n",
      "Epoch 11, Loss 28.853565\n",
      "Epoch 12, Loss 28.765556\n",
      "Epoch 13, Loss 28.677851\n",
      "Epoch 14, Loss 28.590431\n",
      "Epoch 15, Loss 28.503321\n",
      "Epoch 16, Loss 28.416496\n",
      "Epoch 17, Loss 28.329973\n",
      "Epoch 18, Loss 28.243738\n",
      "Epoch 19, Loss 28.157801\n",
      "Epoch 20, Loss 28.072151\n",
      "Epoch 21, Loss 27.986799\n",
      "Epoch 22, Loss 27.901731\n",
      "Epoch 23, Loss 27.816954\n",
      "Epoch 24, Loss 27.732460\n",
      "Epoch 25, Loss 27.648256\n",
      "Epoch 26, Loss 27.564342\n",
      "Epoch 27, Loss 27.480711\n",
      "Epoch 28, Loss 27.397358\n",
      "Epoch 29, Loss 27.314293\n",
      "Epoch 30, Loss 27.231512\n",
      "Epoch 31, Loss 27.149006\n",
      "Epoch 32, Loss 27.066790\n",
      "Epoch 33, Loss 26.984844\n",
      "Epoch 34, Loss 26.903173\n",
      "Epoch 35, Loss 26.821791\n",
      "Epoch 36, Loss 26.740675\n",
      "Epoch 37, Loss 26.659838\n",
      "Epoch 38, Loss 26.579279\n",
      "Epoch 39, Loss 26.498987\n",
      "Epoch 40, Loss 26.418974\n",
      "Epoch 41, Loss 26.339228\n",
      "Epoch 42, Loss 26.259752\n",
      "Epoch 43, Loss 26.180548\n",
      "Epoch 44, Loss 26.101616\n",
      "Epoch 45, Loss 26.022947\n",
      "Epoch 46, Loss 25.944550\n",
      "Epoch 47, Loss 25.866417\n",
      "Epoch 48, Loss 25.788549\n",
      "Epoch 49, Loss 25.710936\n",
      "Epoch 50, Loss 25.633600\n",
      "Epoch 51, Loss 25.556524\n",
      "Epoch 52, Loss 25.479700\n",
      "Epoch 53, Loss 25.403145\n",
      "Epoch 54, Loss 25.326849\n",
      "Epoch 55, Loss 25.250811\n",
      "Epoch 56, Loss 25.175035\n",
      "Epoch 57, Loss 25.099510\n",
      "Epoch 58, Loss 25.024248\n",
      "Epoch 59, Loss 24.949238\n",
      "Epoch 60, Loss 24.874483\n",
      "Epoch 61, Loss 24.799980\n",
      "Epoch 62, Loss 24.725737\n",
      "Epoch 63, Loss 24.651735\n",
      "Epoch 64, Loss 24.577990\n",
      "Epoch 65, Loss 24.504494\n",
      "Epoch 66, Loss 24.431250\n",
      "Epoch 67, Loss 24.358257\n",
      "Epoch 68, Loss 24.285503\n",
      "Epoch 69, Loss 24.212996\n",
      "Epoch 70, Loss 24.140747\n",
      "Epoch 71, Loss 24.068733\n",
      "Epoch 72, Loss 23.996967\n",
      "Epoch 73, Loss 23.925446\n",
      "Epoch 74, Loss 23.854168\n",
      "Epoch 75, Loss 23.783129\n",
      "Epoch 76, Loss 23.712328\n",
      "Epoch 77, Loss 23.641771\n",
      "Epoch 78, Loss 23.571455\n",
      "Epoch 79, Loss 23.501379\n",
      "Epoch 80, Loss 23.431538\n",
      "Epoch 81, Loss 23.361933\n",
      "Epoch 82, Loss 23.292566\n",
      "Epoch 83, Loss 23.223436\n",
      "Epoch 84, Loss 23.154539\n",
      "Epoch 85, Loss 23.085882\n",
      "Epoch 86, Loss 23.017447\n",
      "Epoch 87, Loss 22.949249\n",
      "Epoch 88, Loss 22.881281\n",
      "Epoch 89, Loss 22.813547\n",
      "Epoch 90, Loss 22.746044\n",
      "Epoch 91, Loss 22.678768\n",
      "Epoch 92, Loss 22.611719\n",
      "Epoch 93, Loss 22.544899\n",
      "Epoch 94, Loss 22.478306\n",
      "Epoch 95, Loss 22.411940\n",
      "Epoch 96, Loss 22.345793\n",
      "Epoch 97, Loss 22.279875\n",
      "Epoch 98, Loss 22.214186\n",
      "Epoch 99, Loss 22.148710\n",
      "Epoch 100, Loss 22.083464\n",
      "Epoch 101, Loss 22.018436\n",
      "Epoch 102, Loss 21.953630\n",
      "Epoch 103, Loss 21.889046\n",
      "Epoch 104, Loss 21.824677\n",
      "Epoch 105, Loss 21.760530\n",
      "Epoch 106, Loss 21.696600\n",
      "Epoch 107, Loss 21.632881\n",
      "Epoch 108, Loss 21.569389\n",
      "Epoch 109, Loss 21.506104\n",
      "Epoch 110, Loss 21.443037\n",
      "Epoch 111, Loss 21.380190\n",
      "Epoch 112, Loss 21.317547\n",
      "Epoch 113, Loss 21.255119\n",
      "Epoch 114, Loss 21.192904\n",
      "Epoch 115, Loss 21.130901\n",
      "Epoch 116, Loss 21.069105\n",
      "Epoch 117, Loss 21.007528\n",
      "Epoch 118, Loss 20.946150\n",
      "Epoch 119, Loss 20.884983\n",
      "Epoch 120, Loss 20.824026\n",
      "Epoch 121, Loss 20.763273\n",
      "Epoch 122, Loss 20.702726\n",
      "Epoch 123, Loss 20.642384\n",
      "Epoch 124, Loss 20.582251\n",
      "Epoch 125, Loss 20.522322\n",
      "Epoch 126, Loss 20.462589\n",
      "Epoch 127, Loss 20.403067\n",
      "Epoch 128, Loss 20.343746\n",
      "Epoch 129, Loss 20.284622\n",
      "Epoch 130, Loss 20.225702\n",
      "Epoch 131, Loss 20.166983\n",
      "Epoch 132, Loss 20.108461\n",
      "Epoch 133, Loss 20.050135\n",
      "Epoch 134, Loss 19.992014\n",
      "Epoch 135, Loss 19.934088\n",
      "Epoch 136, Loss 19.876352\n",
      "Epoch 137, Loss 19.818821\n",
      "Epoch 138, Loss 19.761480\n",
      "Epoch 139, Loss 19.704332\n",
      "Epoch 140, Loss 19.647387\n",
      "Epoch 141, Loss 19.590626\n",
      "Epoch 142, Loss 19.534063\n",
      "Epoch 143, Loss 19.477690\n",
      "Epoch 144, Loss 19.421507\n",
      "Epoch 145, Loss 19.365517\n",
      "Epoch 146, Loss 19.309715\n",
      "Epoch 147, Loss 19.254107\n",
      "Epoch 148, Loss 19.198685\n",
      "Epoch 149, Loss 19.143446\n",
      "Epoch 150, Loss 19.088400\n",
      "Epoch 151, Loss 19.033545\n",
      "Epoch 152, Loss 18.978868\n",
      "Epoch 153, Loss 18.924377\n",
      "Epoch 154, Loss 18.870081\n",
      "Epoch 155, Loss 18.815960\n",
      "Epoch 156, Loss 18.762022\n",
      "Epoch 157, Loss 18.708269\n",
      "Epoch 158, Loss 18.654703\n",
      "Epoch 159, Loss 18.601313\n",
      "Epoch 160, Loss 18.548111\n",
      "Epoch 161, Loss 18.495081\n",
      "Epoch 162, Loss 18.442234\n",
      "Epoch 163, Loss 18.389570\n",
      "Epoch 164, Loss 18.337080\n",
      "Epoch 165, Loss 18.284777\n",
      "Epoch 166, Loss 18.232643\n",
      "Epoch 167, Loss 18.180687\n",
      "Epoch 168, Loss 18.128904\n",
      "Epoch 169, Loss 18.077303\n",
      "Epoch 170, Loss 18.025879\n",
      "Epoch 171, Loss 17.974623\n",
      "Epoch 172, Loss 17.923546\n",
      "Epoch 173, Loss 17.872641\n",
      "Epoch 174, Loss 17.821907\n",
      "Epoch 175, Loss 17.771343\n",
      "Epoch 176, Loss 17.720955\n",
      "Epoch 177, Loss 17.670738\n",
      "Epoch 178, Loss 17.620691\n",
      "Epoch 179, Loss 17.570814\n",
      "Epoch 180, Loss 17.521105\n",
      "Epoch 181, Loss 17.471563\n",
      "Epoch 182, Loss 17.422194\n",
      "Epoch 183, Loss 17.372992\n",
      "Epoch 184, Loss 17.323954\n",
      "Epoch 185, Loss 17.275085\n",
      "Epoch 186, Loss 17.226379\n",
      "Epoch 187, Loss 17.177839\n",
      "Epoch 188, Loss 17.129467\n",
      "Epoch 189, Loss 17.081255\n",
      "Epoch 190, Loss 17.033207\n",
      "Epoch 191, Loss 16.985327\n",
      "Epoch 192, Loss 16.937605\n",
      "Epoch 193, Loss 16.890047\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 489, Loss 8.030723\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1012, Loss 3.789584\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1413, Loss 3.148082\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2290, Loss 2.938820\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2777, Loss 2.929778\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3279, Loss 2.928034\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3768, Loss 2.927719\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4325, Loss 2.927656\n",
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      "Epoch 4328, Loss 2.927657\n",
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      "Epoch 4486, Loss 2.927652\n",
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      "Epoch 4488, Loss 2.927652\n",
      "Epoch 4489, Loss 2.927653\n",
      "Epoch 4490, Loss 2.927654\n",
      "Epoch 4491, Loss 2.927653\n",
      "Epoch 4492, Loss 2.927652\n",
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      "Epoch 4502, Loss 2.927654\n",
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      "Epoch 4505, Loss 2.927653\n",
      "Epoch 4506, Loss 2.927653\n",
      "Epoch 4507, Loss 2.927651\n",
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      "Epoch 4510, Loss 2.927653\n",
      "Epoch 4511, Loss 2.927651\n",
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      "Epoch 4527, Loss 2.927651\n",
      "Epoch 4528, Loss 2.927650\n",
      "Epoch 4529, Loss 2.927651\n",
      "Epoch 4530, Loss 2.927653\n",
      "Epoch 4531, Loss 2.927651\n",
      "Epoch 4532, Loss 2.927651\n",
      "Epoch 4533, Loss 2.927652\n",
      "Epoch 4534, Loss 2.927653\n",
      "Epoch 4535, Loss 2.927651\n",
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      "Epoch 4537, Loss 2.927650\n",
      "Epoch 4538, Loss 2.927651\n",
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      "Epoch 4540, Loss 2.927652\n",
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      "Epoch 4542, Loss 2.927651\n",
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      "Epoch 4545, Loss 2.927651\n",
      "Epoch 4546, Loss 2.927650\n",
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      "Epoch 4549, Loss 2.927651\n",
      "Epoch 4550, Loss 2.927653\n",
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      "Epoch 4781, Loss 2.927649\n",
      "Epoch 4782, Loss 2.927649\n",
      "Epoch 4783, Loss 2.927649\n",
      "Epoch 4784, Loss 2.927648\n",
      "Epoch 4785, Loss 2.927648\n",
      "Epoch 4786, Loss 2.927647\n",
      "Epoch 4787, Loss 2.927647\n",
      "Epoch 4788, Loss 2.927648\n",
      "Epoch 4789, Loss 2.927648\n",
      "Epoch 4790, Loss 2.927648\n",
      "Epoch 4791, Loss 2.927648\n",
      "Epoch 4792, Loss 2.927648\n",
      "Epoch 4793, Loss 2.927648\n",
      "Epoch 4794, Loss 2.927650\n",
      "Epoch 4795, Loss 2.927648\n",
      "Epoch 4796, Loss 2.927649\n",
      "Epoch 4797, Loss 2.927649\n",
      "Epoch 4798, Loss 2.927648\n",
      "Epoch 4799, Loss 2.927648\n",
      "Epoch 4800, Loss 2.927650\n",
      "Epoch 4801, Loss 2.927647\n",
      "Epoch 4802, Loss 2.927648\n",
      "Epoch 4803, Loss 2.927649\n",
      "Epoch 4804, Loss 2.927647\n",
      "Epoch 4805, Loss 2.927649\n",
      "Epoch 4806, Loss 2.927648\n",
      "Epoch 4807, Loss 2.927649\n",
      "Epoch 4808, Loss 2.927648\n",
      "Epoch 4809, Loss 2.927649\n",
      "Epoch 4810, Loss 2.927649\n",
      "Epoch 4811, Loss 2.927647\n",
      "Epoch 4812, Loss 2.927649\n",
      "Epoch 4813, Loss 2.927648\n",
      "Epoch 4814, Loss 2.927647\n",
      "Epoch 4815, Loss 2.927649\n",
      "Epoch 4816, Loss 2.927647\n",
      "Epoch 4817, Loss 2.927648\n",
      "Epoch 4818, Loss 2.927646\n",
      "Epoch 4819, Loss 2.927649\n",
      "Epoch 4820, Loss 2.927647\n",
      "Epoch 4821, Loss 2.927649\n",
      "Epoch 4822, Loss 2.927649\n",
      "Epoch 4823, Loss 2.927648\n",
      "Epoch 4824, Loss 2.927648\n",
      "Epoch 4825, Loss 2.927649\n",
      "Epoch 4826, Loss 2.927648\n",
      "Epoch 4827, Loss 2.927649\n",
      "Epoch 4828, Loss 2.927649\n",
      "Epoch 4829, Loss 2.927648\n",
      "Epoch 4830, Loss 2.927648\n",
      "Epoch 4831, Loss 2.927646\n",
      "Epoch 4832, Loss 2.927648\n",
      "Epoch 4833, Loss 2.927647\n",
      "Epoch 4834, Loss 2.927648\n",
      "Epoch 4835, Loss 2.927649\n",
      "Epoch 4836, Loss 2.927647\n",
      "Epoch 4837, Loss 2.927648\n",
      "Epoch 4838, Loss 2.927648\n",
      "Epoch 4839, Loss 2.927648\n",
      "Epoch 4840, Loss 2.927648\n",
      "Epoch 4841, Loss 2.927648\n",
      "Epoch 4842, Loss 2.927649\n",
      "Epoch 4843, Loss 2.927647\n",
      "Epoch 4844, Loss 2.927648\n",
      "Epoch 4845, Loss 2.927647\n",
      "Epoch 4846, Loss 2.927647\n",
      "Epoch 4847, Loss 2.927648\n",
      "Epoch 4848, Loss 2.927648\n",
      "Epoch 4849, Loss 2.927649\n",
      "Epoch 4850, Loss 2.927647\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4851, Loss 2.927649\n",
      "Epoch 4852, Loss 2.927648\n",
      "Epoch 4853, Loss 2.927647\n",
      "Epoch 4854, Loss 2.927649\n",
      "Epoch 4855, Loss 2.927648\n",
      "Epoch 4856, Loss 2.927649\n",
      "Epoch 4857, Loss 2.927649\n",
      "Epoch 4858, Loss 2.927647\n",
      "Epoch 4859, Loss 2.927648\n",
      "Epoch 4860, Loss 2.927648\n",
      "Epoch 4861, Loss 2.927649\n",
      "Epoch 4862, Loss 2.927647\n",
      "Epoch 4863, Loss 2.927647\n",
      "Epoch 4864, Loss 2.927648\n",
      "Epoch 4865, Loss 2.927646\n",
      "Epoch 4866, Loss 2.927648\n",
      "Epoch 4867, Loss 2.927648\n",
      "Epoch 4868, Loss 2.927648\n",
      "Epoch 4869, Loss 2.927648\n",
      "Epoch 4870, Loss 2.927647\n",
      "Epoch 4871, Loss 2.927649\n",
      "Epoch 4872, Loss 2.927648\n",
      "Epoch 4873, Loss 2.927647\n",
      "Epoch 4874, Loss 2.927648\n",
      "Epoch 4875, Loss 2.927648\n",
      "Epoch 4876, Loss 2.927649\n",
      "Epoch 4877, Loss 2.927648\n",
      "Epoch 4878, Loss 2.927648\n",
      "Epoch 4879, Loss 2.927647\n",
      "Epoch 4880, Loss 2.927648\n",
      "Epoch 4881, Loss 2.927648\n",
      "Epoch 4882, Loss 2.927647\n",
      "Epoch 4883, Loss 2.927649\n",
      "Epoch 4884, Loss 2.927648\n",
      "Epoch 4885, Loss 2.927647\n",
      "Epoch 4886, Loss 2.927649\n",
      "Epoch 4887, Loss 2.927648\n",
      "Epoch 4888, Loss 2.927647\n",
      "Epoch 4889, Loss 2.927646\n",
      "Epoch 4890, Loss 2.927647\n",
      "Epoch 4891, Loss 2.927648\n",
      "Epoch 4892, Loss 2.927646\n",
      "Epoch 4893, Loss 2.927649\n",
      "Epoch 4894, Loss 2.927648\n",
      "Epoch 4895, Loss 2.927648\n",
      "Epoch 4896, Loss 2.927649\n",
      "Epoch 4897, Loss 2.927647\n",
      "Epoch 4898, Loss 2.927648\n",
      "Epoch 4899, Loss 2.927648\n",
      "Epoch 4900, Loss 2.927648\n",
      "Epoch 4901, Loss 2.927649\n",
      "Epoch 4902, Loss 2.927647\n",
      "Epoch 4903, Loss 2.927647\n",
      "Epoch 4904, Loss 2.927646\n",
      "Epoch 4905, Loss 2.927647\n",
      "Epoch 4906, Loss 2.927647\n",
      "Epoch 4907, Loss 2.927647\n",
      "Epoch 4908, Loss 2.927647\n",
      "Epoch 4909, Loss 2.927648\n",
      "Epoch 4910, Loss 2.927649\n",
      "Epoch 4911, Loss 2.927646\n",
      "Epoch 4912, Loss 2.927648\n",
      "Epoch 4913, Loss 2.927648\n",
      "Epoch 4914, Loss 2.927647\n",
      "Epoch 4915, Loss 2.927649\n",
      "Epoch 4916, Loss 2.927648\n",
      "Epoch 4917, Loss 2.927647\n",
      "Epoch 4918, Loss 2.927647\n",
      "Epoch 4919, Loss 2.927647\n",
      "Epoch 4920, Loss 2.927647\n",
      "Epoch 4921, Loss 2.927646\n",
      "Epoch 4922, Loss 2.927649\n",
      "Epoch 4923, Loss 2.927647\n",
      "Epoch 4924, Loss 2.927646\n",
      "Epoch 4925, Loss 2.927647\n",
      "Epoch 4926, Loss 2.927648\n",
      "Epoch 4927, Loss 2.927647\n",
      "Epoch 4928, Loss 2.927649\n",
      "Epoch 4929, Loss 2.927648\n",
      "Epoch 4930, Loss 2.927648\n",
      "Epoch 4931, Loss 2.927646\n",
      "Epoch 4932, Loss 2.927648\n",
      "Epoch 4933, Loss 2.927646\n",
      "Epoch 4934, Loss 2.927646\n",
      "Epoch 4935, Loss 2.927649\n",
      "Epoch 4936, Loss 2.927647\n",
      "Epoch 4937, Loss 2.927647\n",
      "Epoch 4938, Loss 2.927647\n",
      "Epoch 4939, Loss 2.927647\n",
      "Epoch 4940, Loss 2.927647\n",
      "Epoch 4941, Loss 2.927646\n",
      "Epoch 4942, Loss 2.927649\n",
      "Epoch 4943, Loss 2.927647\n",
      "Epoch 4944, Loss 2.927648\n",
      "Epoch 4945, Loss 2.927647\n",
      "Epoch 4946, Loss 2.927649\n",
      "Epoch 4947, Loss 2.927646\n",
      "Epoch 4948, Loss 2.927649\n",
      "Epoch 4949, Loss 2.927648\n",
      "Epoch 4950, Loss 2.927647\n",
      "Epoch 4951, Loss 2.927648\n",
      "Epoch 4952, Loss 2.927647\n",
      "Epoch 4953, Loss 2.927647\n",
      "Epoch 4954, Loss 2.927647\n",
      "Epoch 4955, Loss 2.927648\n",
      "Epoch 4956, Loss 2.927646\n",
      "Epoch 4957, Loss 2.927648\n",
      "Epoch 4958, Loss 2.927647\n",
      "Epoch 4959, Loss 2.927647\n",
      "Epoch 4960, Loss 2.927647\n",
      "Epoch 4961, Loss 2.927648\n",
      "Epoch 4962, Loss 2.927647\n",
      "Epoch 4963, Loss 2.927648\n",
      "Epoch 4964, Loss 2.927648\n",
      "Epoch 4965, Loss 2.927648\n",
      "Epoch 4966, Loss 2.927648\n",
      "Epoch 4967, Loss 2.927648\n",
      "Epoch 4968, Loss 2.927647\n",
      "Epoch 4969, Loss 2.927647\n",
      "Epoch 4970, Loss 2.927646\n",
      "Epoch 4971, Loss 2.927647\n",
      "Epoch 4972, Loss 2.927647\n",
      "Epoch 4973, Loss 2.927647\n",
      "Epoch 4974, Loss 2.927647\n",
      "Epoch 4975, Loss 2.927647\n",
      "Epoch 4976, Loss 2.927647\n",
      "Epoch 4977, Loss 2.927648\n",
      "Epoch 4978, Loss 2.927647\n",
      "Epoch 4979, Loss 2.927648\n",
      "Epoch 4980, Loss 2.927647\n",
      "Epoch 4981, Loss 2.927648\n",
      "Epoch 4982, Loss 2.927648\n",
      "Epoch 4983, Loss 2.927646\n",
      "Epoch 4984, Loss 2.927648\n",
      "Epoch 4985, Loss 2.927647\n",
      "Epoch 4986, Loss 2.927648\n",
      "Epoch 4987, Loss 2.927648\n",
      "Epoch 4988, Loss 2.927648\n",
      "Epoch 4989, Loss 2.927646\n",
      "Epoch 4990, Loss 2.927648\n",
      "Epoch 4991, Loss 2.927647\n",
      "Epoch 4992, Loss 2.927647\n",
      "Epoch 4993, Loss 2.927647\n",
      "Epoch 4994, Loss 2.927648\n",
      "Epoch 4995, Loss 2.927647\n",
      "Epoch 4996, Loss 2.927646\n",
      "Epoch 4997, Loss 2.927647\n",
      "Epoch 4998, Loss 2.927648\n",
      "Epoch 4999, Loss 2.927647\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([  5.3671, -17.3012], requires_grad=True)"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b\n",
    "\n",
    "def loss_fn(t_p, t_c):\n",
    "    sq_diffs = (t_p - t_c)**2\n",
    "    return sq_diffs.mean()\n",
    "\n",
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "nepochs = 5000\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    t_p = model(t_un, *params)\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "    \n",
    "    # backward pass\n",
    "    if params.grad is not None:\n",
    "        params.grad.zero_()\n",
    "\n",
    "    loss.backward()\n",
    "\n",
    "    #params.grad.clamp_(-1.0, 1.0)\n",
    "    #print(params, params.grad)\n",
    "\n",
    "    params = (params - learning_rate * params.grad).detach().requires_grad_()\n",
    "\n",
    "params\n",
    "#t_p = model(t_un, *params)\n",
    "#t_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ASGD',\n",
       " 'Adadelta',\n",
       " 'Adagrad',\n",
       " 'Adam',\n",
       " 'Adamax',\n",
       " 'LBFGS',\n",
       " 'Optimizer',\n",
       " 'RMSprop',\n",
       " 'Rprop',\n",
       " 'SGD',\n",
       " 'SparseAdam',\n",
       " '__builtins__',\n",
       " '__cached__',\n",
       " '__doc__',\n",
       " '__file__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__path__',\n",
       " '__spec__',\n",
       " 'lr_scheduler']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch.optim as optim\n",
    "\n",
    "dir(optim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "learning_rate = 1e-5\n",
    "\n",
    "optimizer = optim.SGD([params], lr=learning_rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([ 0.9548, -0.0008], requires_grad=True)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t_p = model(t_u, *params)\n",
    "\n",
    "loss = loss_fn(t_p, t_c)\n",
    "\n",
    "loss.backward()\n",
    "\n",
    "optimizer.step()\n",
    "\n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([1.7761, 0.1064], requires_grad=True)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "optimizer = optim.SGD([params], lr=learning_rate)\n",
    "\n",
    "t_p = model(t_un, *params)\n",
    "\n",
    "loss = loss_fn(t_p, t_c)\n",
    "\n",
    "optimizer.zero_grad()\n",
    "\n",
    "loss.backward()\n",
    "\n",
    "optimizer.step()\n",
    "\n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 80.364342\n",
      "Epoch 1, Loss 37.574917\n",
      "Epoch 2, Loss 30.871077\n",
      "Epoch 3, Loss 29.756193\n",
      "Epoch 4, Loss 29.507149\n",
      "Epoch 5, Loss 29.392458\n",
      "Epoch 6, Loss 29.298828\n",
      "Epoch 7, Loss 29.208717\n",
      "Epoch 8, Loss 29.119417\n",
      "Epoch 9, Loss 29.030487\n",
      "Epoch 10, Loss 28.941875\n",
      "Epoch 11, Loss 28.853565\n",
      "Epoch 12, Loss 28.765556\n",
      "Epoch 13, Loss 28.677851\n",
      "Epoch 14, Loss 28.590431\n",
      "Epoch 15, Loss 28.503321\n",
      "Epoch 16, Loss 28.416496\n",
      "Epoch 17, Loss 28.329973\n",
      "Epoch 18, Loss 28.243738\n",
      "Epoch 19, Loss 28.157801\n",
      "Epoch 20, Loss 28.072151\n",
      "Epoch 21, Loss 27.986799\n",
      "Epoch 22, Loss 27.901731\n",
      "Epoch 23, Loss 27.816954\n",
      "Epoch 24, Loss 27.732460\n",
      "Epoch 25, Loss 27.648256\n",
      "Epoch 26, Loss 27.564342\n",
      "Epoch 27, Loss 27.480711\n",
      "Epoch 28, Loss 27.397358\n",
      "Epoch 29, Loss 27.314293\n",
      "Epoch 30, Loss 27.231512\n",
      "Epoch 31, Loss 27.149006\n",
      "Epoch 32, Loss 27.066790\n",
      "Epoch 33, Loss 26.984844\n",
      "Epoch 34, Loss 26.903173\n",
      "Epoch 35, Loss 26.821791\n",
      "Epoch 36, Loss 26.740675\n",
      "Epoch 37, Loss 26.659838\n",
      "Epoch 38, Loss 26.579279\n",
      "Epoch 39, Loss 26.498987\n",
      "Epoch 40, Loss 26.418974\n",
      "Epoch 41, Loss 26.339228\n",
      "Epoch 42, Loss 26.259752\n",
      "Epoch 43, Loss 26.180548\n",
      "Epoch 44, Loss 26.101616\n",
      "Epoch 45, Loss 26.022947\n",
      "Epoch 46, Loss 25.944550\n",
      "Epoch 47, Loss 25.866417\n",
      "Epoch 48, Loss 25.788549\n",
      "Epoch 49, Loss 25.710936\n",
      "Epoch 50, Loss 25.633600\n",
      "Epoch 51, Loss 25.556524\n",
      "Epoch 52, Loss 25.479700\n",
      "Epoch 53, Loss 25.403145\n",
      "Epoch 54, Loss 25.326849\n",
      "Epoch 55, Loss 25.250811\n",
      "Epoch 56, Loss 25.175035\n",
      "Epoch 57, Loss 25.099510\n",
      "Epoch 58, Loss 25.024248\n",
      "Epoch 59, Loss 24.949238\n",
      "Epoch 60, Loss 24.874483\n",
      "Epoch 61, Loss 24.799980\n",
      "Epoch 62, Loss 24.725737\n",
      "Epoch 63, Loss 24.651735\n",
      "Epoch 64, Loss 24.577990\n",
      "Epoch 65, Loss 24.504494\n",
      "Epoch 66, Loss 24.431250\n",
      "Epoch 67, Loss 24.358257\n",
      "Epoch 68, Loss 24.285503\n",
      "Epoch 69, Loss 24.212996\n",
      "Epoch 70, Loss 24.140747\n",
      "Epoch 71, Loss 24.068733\n",
      "Epoch 72, Loss 23.996967\n",
      "Epoch 73, Loss 23.925446\n",
      "Epoch 74, Loss 23.854168\n",
      "Epoch 75, Loss 23.783129\n",
      "Epoch 76, Loss 23.712328\n",
      "Epoch 77, Loss 23.641771\n",
      "Epoch 78, Loss 23.571455\n",
      "Epoch 79, Loss 23.501379\n",
      "Epoch 80, Loss 23.431538\n",
      "Epoch 81, Loss 23.361933\n",
      "Epoch 82, Loss 23.292566\n",
      "Epoch 83, Loss 23.223436\n",
      "Epoch 84, Loss 23.154539\n",
      "Epoch 85, Loss 23.085882\n",
      "Epoch 86, Loss 23.017447\n",
      "Epoch 87, Loss 22.949249\n",
      "Epoch 88, Loss 22.881281\n",
      "Epoch 89, Loss 22.813547\n",
      "Epoch 90, Loss 22.746044\n",
      "Epoch 91, Loss 22.678768\n",
      "Epoch 92, Loss 22.611719\n",
      "Epoch 93, Loss 22.544899\n",
      "Epoch 94, Loss 22.478306\n",
      "Epoch 95, Loss 22.411940\n",
      "Epoch 96, Loss 22.345793\n",
      "Epoch 97, Loss 22.279875\n",
      "Epoch 98, Loss 22.214186\n",
      "Epoch 99, Loss 22.148710\n",
      "Epoch 100, Loss 22.083464\n",
      "Epoch 101, Loss 22.018436\n",
      "Epoch 102, Loss 21.953630\n",
      "Epoch 103, Loss 21.889046\n",
      "Epoch 104, Loss 21.824677\n",
      "Epoch 105, Loss 21.760530\n",
      "Epoch 106, Loss 21.696600\n",
      "Epoch 107, Loss 21.632881\n",
      "Epoch 108, Loss 21.569389\n",
      "Epoch 109, Loss 21.506104\n",
      "Epoch 110, Loss 21.443037\n",
      "Epoch 111, Loss 21.380190\n",
      "Epoch 112, Loss 21.317547\n",
      "Epoch 113, Loss 21.255119\n",
      "Epoch 114, Loss 21.192904\n",
      "Epoch 115, Loss 21.130901\n",
      "Epoch 116, Loss 21.069105\n",
      "Epoch 117, Loss 21.007528\n",
      "Epoch 118, Loss 20.946150\n",
      "Epoch 119, Loss 20.884983\n",
      "Epoch 120, Loss 20.824026\n",
      "Epoch 121, Loss 20.763273\n",
      "Epoch 122, Loss 20.702726\n",
      "Epoch 123, Loss 20.642384\n",
      "Epoch 124, Loss 20.582251\n",
      "Epoch 125, Loss 20.522322\n",
      "Epoch 126, Loss 20.462589\n",
      "Epoch 127, Loss 20.403067\n",
      "Epoch 128, Loss 20.343746\n",
      "Epoch 129, Loss 20.284622\n",
      "Epoch 130, Loss 20.225702\n",
      "Epoch 131, Loss 20.166983\n",
      "Epoch 132, Loss 20.108461\n",
      "Epoch 133, Loss 20.050135\n",
      "Epoch 134, Loss 19.992014\n",
      "Epoch 135, Loss 19.934088\n",
      "Epoch 136, Loss 19.876352\n",
      "Epoch 137, Loss 19.818821\n",
      "Epoch 138, Loss 19.761480\n",
      "Epoch 139, Loss 19.704332\n",
      "Epoch 140, Loss 19.647387\n",
      "Epoch 141, Loss 19.590626\n",
      "Epoch 142, Loss 19.534063\n",
      "Epoch 143, Loss 19.477690\n",
      "Epoch 144, Loss 19.421507\n",
      "Epoch 145, Loss 19.365517\n",
      "Epoch 146, Loss 19.309715\n",
      "Epoch 147, Loss 19.254107\n",
      "Epoch 148, Loss 19.198685\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 422, Loss 9.336448\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 809, Loss 4.646592\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1211, Loss 3.365771\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1581, Loss 3.052152\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2003, Loss 2.957293\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2434, Loss 2.934493\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2891, Loss 2.929093\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3291, Loss 2.928018\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3729, Loss 2.927732\n",
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      "Epoch 4116, Loss 2.927668\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4117, Loss 2.927667\n",
      "Epoch 4118, Loss 2.927669\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4696, Loss 2.927649\n",
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      "Epoch 4731, Loss 2.927649\n",
      "Epoch 4732, Loss 2.927648\n",
      "Epoch 4733, Loss 2.927649\n",
      "Epoch 4734, Loss 2.927647\n",
      "Epoch 4735, Loss 2.927650\n",
      "Epoch 4736, Loss 2.927650\n",
      "Epoch 4737, Loss 2.927650\n",
      "Epoch 4738, Loss 2.927649\n",
      "Epoch 4739, Loss 2.927648\n",
      "Epoch 4740, Loss 2.927648\n",
      "Epoch 4741, Loss 2.927648\n",
      "Epoch 4742, Loss 2.927647\n",
      "Epoch 4743, Loss 2.927648\n",
      "Epoch 4744, Loss 2.927649\n",
      "Epoch 4745, Loss 2.927648\n",
      "Epoch 4746, Loss 2.927648\n",
      "Epoch 4747, Loss 2.927649\n",
      "Epoch 4748, Loss 2.927648\n",
      "Epoch 4749, Loss 2.927649\n",
      "Epoch 4750, Loss 2.927649\n",
      "Epoch 4751, Loss 2.927649\n",
      "Epoch 4752, Loss 2.927648\n",
      "Epoch 4753, Loss 2.927648\n",
      "Epoch 4754, Loss 2.927647\n",
      "Epoch 4755, Loss 2.927648\n",
      "Epoch 4756, Loss 2.927648\n",
      "Epoch 4757, Loss 2.927648\n",
      "Epoch 4758, Loss 2.927648\n",
      "Epoch 4759, Loss 2.927649\n",
      "Epoch 4760, Loss 2.927649\n",
      "Epoch 4761, Loss 2.927649\n",
      "Epoch 4762, Loss 2.927648\n",
      "Epoch 4763, Loss 2.927647\n",
      "Epoch 4764, Loss 2.927648\n",
      "Epoch 4765, Loss 2.927648\n",
      "Epoch 4766, Loss 2.927649\n",
      "Epoch 4767, Loss 2.927648\n",
      "Epoch 4768, Loss 2.927649\n",
      "Epoch 4769, Loss 2.927648\n",
      "Epoch 4770, Loss 2.927649\n",
      "Epoch 4771, Loss 2.927648\n",
      "Epoch 4772, Loss 2.927648\n",
      "Epoch 4773, Loss 2.927649\n",
      "Epoch 4774, Loss 2.927648\n",
      "Epoch 4775, Loss 2.927647\n",
      "Epoch 4776, Loss 2.927648\n",
      "Epoch 4777, Loss 2.927648\n",
      "Epoch 4778, Loss 2.927648\n",
      "Epoch 4779, Loss 2.927649\n",
      "Epoch 4780, Loss 2.927649\n",
      "Epoch 4781, Loss 2.927649\n",
      "Epoch 4782, Loss 2.927649\n",
      "Epoch 4783, Loss 2.927649\n",
      "Epoch 4784, Loss 2.927648\n",
      "Epoch 4785, Loss 2.927648\n",
      "Epoch 4786, Loss 2.927647\n",
      "Epoch 4787, Loss 2.927647\n",
      "Epoch 4788, Loss 2.927648\n",
      "Epoch 4789, Loss 2.927648\n",
      "Epoch 4790, Loss 2.927648\n",
      "Epoch 4791, Loss 2.927648\n",
      "Epoch 4792, Loss 2.927648\n",
      "Epoch 4793, Loss 2.927648\n",
      "Epoch 4794, Loss 2.927650\n",
      "Epoch 4795, Loss 2.927648\n",
      "Epoch 4796, Loss 2.927649\n",
      "Epoch 4797, Loss 2.927649\n",
      "Epoch 4798, Loss 2.927648\n",
      "Epoch 4799, Loss 2.927648\n",
      "Epoch 4800, Loss 2.927650\n",
      "Epoch 4801, Loss 2.927647\n",
      "Epoch 4802, Loss 2.927648\n",
      "Epoch 4803, Loss 2.927649\n",
      "Epoch 4804, Loss 2.927647\n",
      "Epoch 4805, Loss 2.927649\n",
      "Epoch 4806, Loss 2.927648\n",
      "Epoch 4807, Loss 2.927649\n",
      "Epoch 4808, Loss 2.927648\n",
      "Epoch 4809, Loss 2.927649\n",
      "Epoch 4810, Loss 2.927649\n",
      "Epoch 4811, Loss 2.927647\n",
      "Epoch 4812, Loss 2.927649\n",
      "Epoch 4813, Loss 2.927648\n",
      "Epoch 4814, Loss 2.927647\n",
      "Epoch 4815, Loss 2.927649\n",
      "Epoch 4816, Loss 2.927647\n",
      "Epoch 4817, Loss 2.927648\n",
      "Epoch 4818, Loss 2.927646\n",
      "Epoch 4819, Loss 2.927649\n",
      "Epoch 4820, Loss 2.927647\n",
      "Epoch 4821, Loss 2.927649\n",
      "Epoch 4822, Loss 2.927649\n",
      "Epoch 4823, Loss 2.927648\n",
      "Epoch 4824, Loss 2.927648\n",
      "Epoch 4825, Loss 2.927649\n",
      "Epoch 4826, Loss 2.927648\n",
      "Epoch 4827, Loss 2.927649\n",
      "Epoch 4828, Loss 2.927649\n",
      "Epoch 4829, Loss 2.927648\n",
      "Epoch 4830, Loss 2.927648\n",
      "Epoch 4831, Loss 2.927646\n",
      "Epoch 4832, Loss 2.927648\n",
      "Epoch 4833, Loss 2.927647\n",
      "Epoch 4834, Loss 2.927648\n",
      "Epoch 4835, Loss 2.927649\n",
      "Epoch 4836, Loss 2.927647\n",
      "Epoch 4837, Loss 2.927648\n",
      "Epoch 4838, Loss 2.927648\n",
      "Epoch 4839, Loss 2.927648\n",
      "Epoch 4840, Loss 2.927648\n",
      "Epoch 4841, Loss 2.927648\n",
      "Epoch 4842, Loss 2.927649\n",
      "Epoch 4843, Loss 2.927647\n",
      "Epoch 4844, Loss 2.927648\n",
      "Epoch 4845, Loss 2.927647\n",
      "Epoch 4846, Loss 2.927647\n",
      "Epoch 4847, Loss 2.927648\n",
      "Epoch 4848, Loss 2.927648\n",
      "Epoch 4849, Loss 2.927649\n",
      "Epoch 4850, Loss 2.927647\n",
      "Epoch 4851, Loss 2.927649\n",
      "Epoch 4852, Loss 2.927648\n",
      "Epoch 4853, Loss 2.927647\n",
      "Epoch 4854, Loss 2.927649\n",
      "Epoch 4855, Loss 2.927648\n",
      "Epoch 4856, Loss 2.927649\n",
      "Epoch 4857, Loss 2.927649\n",
      "Epoch 4858, Loss 2.927647\n",
      "Epoch 4859, Loss 2.927648\n",
      "Epoch 4860, Loss 2.927648\n",
      "Epoch 4861, Loss 2.927649\n",
      "Epoch 4862, Loss 2.927647\n",
      "Epoch 4863, Loss 2.927647\n",
      "Epoch 4864, Loss 2.927648\n",
      "Epoch 4865, Loss 2.927646\n",
      "Epoch 4866, Loss 2.927648\n",
      "Epoch 4867, Loss 2.927648\n",
      "Epoch 4868, Loss 2.927648\n",
      "Epoch 4869, Loss 2.927648\n",
      "Epoch 4870, Loss 2.927647\n",
      "Epoch 4871, Loss 2.927649\n",
      "Epoch 4872, Loss 2.927648\n",
      "Epoch 4873, Loss 2.927647\n",
      "Epoch 4874, Loss 2.927648\n",
      "Epoch 4875, Loss 2.927648\n",
      "Epoch 4876, Loss 2.927649\n",
      "Epoch 4877, Loss 2.927648\n",
      "Epoch 4878, Loss 2.927648\n",
      "Epoch 4879, Loss 2.927647\n",
      "Epoch 4880, Loss 2.927648\n",
      "Epoch 4881, Loss 2.927648\n",
      "Epoch 4882, Loss 2.927647\n",
      "Epoch 4883, Loss 2.927649\n",
      "Epoch 4884, Loss 2.927648\n",
      "Epoch 4885, Loss 2.927647\n",
      "Epoch 4886, Loss 2.927649\n",
      "Epoch 4887, Loss 2.927648\n",
      "Epoch 4888, Loss 2.927647\n",
      "Epoch 4889, Loss 2.927646\n",
      "Epoch 4890, Loss 2.927647\n",
      "Epoch 4891, Loss 2.927648\n",
      "Epoch 4892, Loss 2.927646\n",
      "Epoch 4893, Loss 2.927649\n",
      "Epoch 4894, Loss 2.927648\n",
      "Epoch 4895, Loss 2.927648\n",
      "Epoch 4896, Loss 2.927649\n",
      "Epoch 4897, Loss 2.927647\n",
      "Epoch 4898, Loss 2.927648\n",
      "Epoch 4899, Loss 2.927648\n",
      "Epoch 4900, Loss 2.927648\n",
      "Epoch 4901, Loss 2.927649\n",
      "Epoch 4902, Loss 2.927647\n",
      "Epoch 4903, Loss 2.927647\n",
      "Epoch 4904, Loss 2.927646\n",
      "Epoch 4905, Loss 2.927647\n",
      "Epoch 4906, Loss 2.927647\n",
      "Epoch 4907, Loss 2.927647\n",
      "Epoch 4908, Loss 2.927647\n",
      "Epoch 4909, Loss 2.927648\n",
      "Epoch 4910, Loss 2.927649\n",
      "Epoch 4911, Loss 2.927646\n",
      "Epoch 4912, Loss 2.927648\n",
      "Epoch 4913, Loss 2.927648\n",
      "Epoch 4914, Loss 2.927647\n",
      "Epoch 4915, Loss 2.927649\n",
      "Epoch 4916, Loss 2.927648\n",
      "Epoch 4917, Loss 2.927647\n",
      "Epoch 4918, Loss 2.927647\n",
      "Epoch 4919, Loss 2.927647\n",
      "Epoch 4920, Loss 2.927647\n",
      "Epoch 4921, Loss 2.927646\n",
      "Epoch 4922, Loss 2.927649\n",
      "Epoch 4923, Loss 2.927647\n",
      "Epoch 4924, Loss 2.927646\n",
      "Epoch 4925, Loss 2.927647\n",
      "Epoch 4926, Loss 2.927648\n",
      "Epoch 4927, Loss 2.927647\n",
      "Epoch 4928, Loss 2.927649\n",
      "Epoch 4929, Loss 2.927648\n",
      "Epoch 4930, Loss 2.927648\n",
      "Epoch 4931, Loss 2.927646\n",
      "Epoch 4932, Loss 2.927648\n",
      "Epoch 4933, Loss 2.927646\n",
      "Epoch 4934, Loss 2.927646\n",
      "Epoch 4935, Loss 2.927649\n",
      "Epoch 4936, Loss 2.927647\n",
      "Epoch 4937, Loss 2.927647\n",
      "Epoch 4938, Loss 2.927647\n",
      "Epoch 4939, Loss 2.927647\n",
      "Epoch 4940, Loss 2.927647\n",
      "Epoch 4941, Loss 2.927646\n",
      "Epoch 4942, Loss 2.927649\n",
      "Epoch 4943, Loss 2.927647\n",
      "Epoch 4944, Loss 2.927648\n",
      "Epoch 4945, Loss 2.927647\n",
      "Epoch 4946, Loss 2.927649\n",
      "Epoch 4947, Loss 2.927646\n",
      "Epoch 4948, Loss 2.927649\n",
      "Epoch 4949, Loss 2.927648\n",
      "Epoch 4950, Loss 2.927647\n",
      "Epoch 4951, Loss 2.927648\n",
      "Epoch 4952, Loss 2.927647\n",
      "Epoch 4953, Loss 2.927647\n",
      "Epoch 4954, Loss 2.927647\n",
      "Epoch 4955, Loss 2.927648\n",
      "Epoch 4956, Loss 2.927646\n",
      "Epoch 4957, Loss 2.927648\n",
      "Epoch 4958, Loss 2.927647\n",
      "Epoch 4959, Loss 2.927647\n",
      "Epoch 4960, Loss 2.927647\n",
      "Epoch 4961, Loss 2.927648\n",
      "Epoch 4962, Loss 2.927647\n",
      "Epoch 4963, Loss 2.927648\n",
      "Epoch 4964, Loss 2.927648\n",
      "Epoch 4965, Loss 2.927648\n",
      "Epoch 4966, Loss 2.927648\n",
      "Epoch 4967, Loss 2.927648\n",
      "Epoch 4968, Loss 2.927647\n",
      "Epoch 4969, Loss 2.927647\n",
      "Epoch 4970, Loss 2.927646\n",
      "Epoch 4971, Loss 2.927647\n",
      "Epoch 4972, Loss 2.927647\n",
      "Epoch 4973, Loss 2.927647\n",
      "Epoch 4974, Loss 2.927647\n",
      "Epoch 4975, Loss 2.927647\n",
      "Epoch 4976, Loss 2.927647\n",
      "Epoch 4977, Loss 2.927648\n",
      "Epoch 4978, Loss 2.927647\n",
      "Epoch 4979, Loss 2.927648\n",
      "Epoch 4980, Loss 2.927647\n",
      "Epoch 4981, Loss 2.927648\n",
      "Epoch 4982, Loss 2.927648\n",
      "Epoch 4983, Loss 2.927646\n",
      "Epoch 4984, Loss 2.927648\n",
      "Epoch 4985, Loss 2.927647\n",
      "Epoch 4986, Loss 2.927648\n",
      "Epoch 4987, Loss 2.927648\n",
      "Epoch 4988, Loss 2.927648\n",
      "Epoch 4989, Loss 2.927646\n",
      "Epoch 4990, Loss 2.927648\n",
      "Epoch 4991, Loss 2.927647\n",
      "Epoch 4992, Loss 2.927647\n",
      "Epoch 4993, Loss 2.927647\n",
      "Epoch 4994, Loss 2.927648\n",
      "Epoch 4995, Loss 2.927647\n",
      "Epoch 4996, Loss 2.927646\n",
      "Epoch 4997, Loss 2.927647\n",
      "Epoch 4998, Loss 2.927648\n",
      "Epoch 4999, Loss 2.927647\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([  5.3671, -17.3012], requires_grad=True)"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b\n",
    "\n",
    "def loss_fn(t_p, t_c):\n",
    "    sq_diffs = (t_p - t_c)**2\n",
    "    return sq_diffs.mean()\n",
    "\n",
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "nepochs = 5000\n",
    "learning_rate = 1e-2\n",
    "\n",
    "optimizer = optim.SGD([params], lr=learning_rate)\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    \n",
    "    # forward pass\n",
    "    t_p = model(t_un, *params)\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss.backward()    \n",
    "    optimizer.step()\n",
    "\n",
    "t_p = model(t_un, *params)\n",
    "\n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Loss 1763.884644\n",
      "Epoch 1, Loss 1334.349121\n",
      "Epoch 2, Loss 967.815857\n",
      "Epoch 3, Loss 664.756348\n",
      "Epoch 4, Loss 424.630096\n",
      "Epoch 5, Loss 245.539536\n",
      "Epoch 6, Loss 123.854927\n",
      "Epoch 7, Loss 53.885216\n",
      "Epoch 8, Loss 27.729158\n",
      "Epoch 9, Loss 35.472927\n",
      "Epoch 10, Loss 65.865623\n",
      "Epoch 11, Loss 107.448486\n",
      "Epoch 12, Loss 149.893204\n",
      "Epoch 13, Loss 185.160660\n",
      "Epoch 14, Loss 208.152191\n",
      "Epoch 15, Loss 216.751862\n",
      "Epoch 16, Loss 211.386810\n",
      "Epoch 17, Loss 194.333359\n",
      "Epoch 18, Loss 168.973526\n",
      "Epoch 19, Loss 139.126602\n",
      "Epoch 20, Loss 108.509003\n",
      "Epoch 21, Loss 80.331757\n",
      "Epoch 22, Loss 57.027817\n",
      "Epoch 23, Loss 40.099060\n",
      "Epoch 24, Loss 30.076361\n",
      "Epoch 25, Loss 26.585762\n",
      "Epoch 26, Loss 28.510445\n",
      "Epoch 27, Loss 34.227798\n",
      "Epoch 28, Loss 41.889477\n",
      "Epoch 29, Loss 49.703087\n",
      "Epoch 30, Loss 56.173435\n",
      "Epoch 31, Loss 60.269627\n",
      "Epoch 32, Loss 61.500473\n",
      "Epoch 33, Loss 59.899094\n",
      "Epoch 34, Loss 55.932739\n",
      "Epoch 35, Loss 50.363575\n",
      "Epoch 36, Loss 44.088673\n",
      "Epoch 37, Loss 37.985172\n",
      "Epoch 38, Loss 32.781734\n",
      "Epoch 39, Loss 28.970186\n",
      "Epoch 40, Loss 26.764654\n",
      "Epoch 41, Loss 26.108040\n",
      "Epoch 42, Loss 26.719383\n",
      "Epoch 43, Loss 28.170134\n",
      "Epoch 44, Loss 29.973921\n",
      "Epoch 45, Loss 31.673698\n",
      "Epoch 46, Loss 32.912014\n",
      "Epoch 47, Loss 33.474720\n",
      "Epoch 48, Loss 33.304337\n",
      "Epoch 49, Loss 32.484787\n",
      "Epoch 50, Loss 31.204374\n",
      "Epoch 51, Loss 29.706341\n",
      "Epoch 52, Loss 28.237404\n",
      "Epoch 53, Loss 27.003424\n",
      "Epoch 54, Loss 26.138813\n",
      "Epoch 55, Loss 25.693235\n",
      "Epoch 56, Loss 25.635466\n",
      "Epoch 57, Loss 25.871410\n",
      "Epoch 58, Loss 26.270973\n",
      "Epoch 59, Loss 26.697638\n",
      "Epoch 60, Loss 27.034904\n",
      "Epoch 61, Loss 27.204889\n",
      "Epoch 62, Loss 27.176851\n",
      "Epoch 63, Loss 26.965380\n",
      "Epoch 64, Loss 26.620049\n",
      "Epoch 65, Loss 26.209972\n",
      "Epoch 66, Loss 25.806860\n",
      "Epoch 67, Loss 25.470259\n",
      "Epoch 68, Loss 25.237463\n",
      "Epoch 69, Loss 25.119513\n",
      "Epoch 70, Loss 25.103111\n",
      "Epoch 71, Loss 25.157188\n",
      "Epoch 72, Loss 25.242144\n",
      "Epoch 73, Loss 25.319366\n",
      "Epoch 74, Loss 25.359070\n",
      "Epoch 75, Loss 25.345070\n",
      "Epoch 76, Loss 25.275896\n",
      "Epoch 77, Loss 25.162645\n",
      "Epoch 78, Loss 25.024433\n",
      "Epoch 79, Loss 24.882936\n",
      "Epoch 80, Loss 24.757172\n",
      "Epoch 81, Loss 24.659727\n",
      "Epoch 82, Loss 24.595060\n",
      "Epoch 83, Loss 24.559795\n",
      "Epoch 84, Loss 24.544792\n",
      "Epoch 85, Loss 24.538088\n",
      "Epoch 86, Loss 24.528118\n",
      "Epoch 87, Loss 24.506195\n",
      "Epoch 88, Loss 24.468050\n",
      "Epoch 89, Loss 24.414021\n",
      "Epoch 90, Loss 24.348192\n",
      "Epoch 91, Loss 24.276789\n",
      "Epoch 92, Loss 24.206377\n",
      "Epoch 93, Loss 24.142193\n",
      "Epoch 94, Loss 24.087170\n",
      "Epoch 95, Loss 24.041588\n",
      "Epoch 96, Loss 24.003447\n",
      "Epoch 97, Loss 23.969360\n",
      "Epoch 98, Loss 23.935572\n",
      "Epoch 99, Loss 23.898945\n",
      "Epoch 100, Loss 23.857599\n",
      "Epoch 101, Loss 23.811182\n",
      "Epoch 102, Loss 23.760670\n",
      "Epoch 103, Loss 23.707891\n",
      "Epoch 104, Loss 23.654949\n",
      "Epoch 105, Loss 23.603601\n",
      "Epoch 106, Loss 23.554895\n",
      "Epoch 107, Loss 23.509031\n",
      "Epoch 108, Loss 23.465446\n",
      "Epoch 109, Loss 23.423058\n",
      "Epoch 110, Loss 23.380684\n",
      "Epoch 111, Loss 23.337336\n",
      "Epoch 112, Loss 23.292431\n",
      "Epoch 113, Loss 23.245888\n",
      "Epoch 114, Loss 23.198063\n",
      "Epoch 115, Loss 23.149569\n",
      "Epoch 116, Loss 23.101072\n",
      "Epoch 117, Loss 23.053108\n",
      "Epoch 118, Loss 23.005962\n",
      "Epoch 119, Loss 22.959620\n",
      "Epoch 120, Loss 22.913841\n",
      "Epoch 121, Loss 22.868263\n",
      "Epoch 122, Loss 22.822508\n",
      "Epoch 123, Loss 22.776289\n",
      "Epoch 124, Loss 22.729492\n",
      "Epoch 125, Loss 22.682161\n",
      "Epoch 126, Loss 22.634451\n",
      "Epoch 127, Loss 22.586586\n",
      "Epoch 128, Loss 22.538774\n",
      "Epoch 129, Loss 22.491146\n",
      "Epoch 130, Loss 22.443747\n",
      "Epoch 131, Loss 22.396524\n",
      "Epoch 132, Loss 22.349373\n",
      "Epoch 133, Loss 22.302151\n",
      "Epoch 134, Loss 22.254770\n",
      "Epoch 135, Loss 22.207170\n",
      "Epoch 136, Loss 22.159342\n",
      "Epoch 137, Loss 22.111336\n",
      "Epoch 138, Loss 22.063232\n",
      "Epoch 139, Loss 22.015093\n",
      "Epoch 140, Loss 21.966978\n",
      "Epoch 141, Loss 21.918909\n",
      "Epoch 142, Loss 21.870867\n",
      "Epoch 143, Loss 21.822821\n",
      "Epoch 144, Loss 21.774725\n",
      "Epoch 145, Loss 21.726547\n",
      "Epoch 146, Loss 21.678268\n",
      "Epoch 147, Loss 21.629892\n",
      "Epoch 148, Loss 21.581429\n",
      "Epoch 149, Loss 21.532902\n",
      "Epoch 150, Loss 21.484350\n",
      "Epoch 151, Loss 21.435778\n",
      "Epoch 152, Loss 21.387205\n",
      "Epoch 153, Loss 21.338610\n",
      "Epoch 154, Loss 21.289995\n",
      "Epoch 155, Loss 21.241346\n",
      "Epoch 156, Loss 21.192650\n",
      "Epoch 157, Loss 21.143892\n",
      "Epoch 158, Loss 21.095097\n",
      "Epoch 159, Loss 21.046257\n",
      "Epoch 160, Loss 20.997375\n",
      "Epoch 161, Loss 20.948483\n",
      "Epoch 162, Loss 20.899563\n",
      "Epoch 163, Loss 20.850632\n",
      "Epoch 164, Loss 20.801683\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 337, Loss 12.807572\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 711, Loss 4.291261\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1556, Loss 2.928102\n",
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      "Epoch 1982, Loss 2.927647\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1983, Loss 2.927647\n",
      "Epoch 1984, Loss 2.927648\n",
      "Epoch 1985, Loss 2.927647\n",
      "Epoch 1986, Loss 2.927647\n",
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      "Epoch 2016, Loss 2.927645\n",
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      "Epoch 2018, Loss 2.927647\n",
      "Epoch 2019, Loss 2.927645\n",
      "Epoch 2020, Loss 2.927647\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2396, Loss 2.927646\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2798, Loss 2.927646\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3610, Loss 2.927644\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4006, Loss 2.927645\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4389, Loss 2.927646\n",
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      "Epoch 4785, Loss 2.927646\n",
      "Epoch 4786, Loss 2.927645\n",
      "Epoch 4787, Loss 2.927645\n",
      "Epoch 4788, Loss 2.927646\n",
      "Epoch 4789, Loss 2.927646\n",
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      "Epoch 4791, Loss 2.927646\n",
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      "Epoch 4793, Loss 2.927645\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4794, Loss 2.927645\n",
      "Epoch 4795, Loss 2.927646\n",
      "Epoch 4796, Loss 2.927646\n",
      "Epoch 4797, Loss 2.927645\n",
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      "Epoch 4999, Loss 2.927646\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([  0.5368, -17.3048], requires_grad=True)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b\n",
    "\n",
    "def loss_fn(t_p, t_c):\n",
    "    sq_diffs = (t_p - t_c)**2\n",
    "    return sq_diffs.mean()\n",
    "\n",
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "nepochs = 5000\n",
    "learning_rate = 1e-1\n",
    "\n",
    "optimizer = optim.Adam([params], lr=learning_rate)\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    t_p = model(t_u, *params)\n",
    "    loss = loss_fn(t_p, t_c)\n",
    "\n",
    "    print('Epoch %d, Loss %f' % (epoch, float(loss)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss.backward()\n",
    "    optimizer.step()\n",
    "\n",
    "t_p = model(t_u, *params)\n",
    "\n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x115e028d0>]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "plt.plot(0.1 * t_u.numpy(), t_p.detach().numpy())\n",
    "plt.plot(0.1 * t_u.numpy(), t_c.numpy(), 'o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([ 7,  2,  1,  3,  8,  0,  5,  6, 10]), tensor([9, 4]))"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_samples = t_u.shape[0]\n",
    "n_val = int(0.2 * n_samples)\n",
    "\n",
    "shuffled_indices = torch.randperm(n_samples)\n",
    "\n",
    "train_indices = shuffled_indices[:-n_val]\n",
    "val_indices = shuffled_indices[-n_val:]\n",
    "\n",
    "train_indices, val_indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_u_train = t_u[train_indices]\n",
    "t_c_train = t_c[train_indices]\n",
    "\n",
    "t_u_val = t_u[val_indices]\n",
    "t_c_val = t_c[val_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Training loss 89.636589, Validation loss 38.639244\n",
      "Epoch 1, Training loss 44.926880, Validation loss 2.545443\n",
      "Epoch 2, Training loss 37.123985, Validation loss 0.556166\n",
      "Epoch 3, Training loss 35.668991, Validation loss 1.966753\n",
      "Epoch 4, Training loss 35.306217, Validation loss 2.938725\n",
      "Epoch 5, Training loss 35.131748, Validation loss 3.410529\n",
      "Epoch 6, Training loss 34.990128, Validation loss 3.620039\n",
      "Epoch 7, Training loss 34.854614, Validation loss 3.711267\n",
      "Epoch 8, Training loss 34.720608, Validation loss 3.751791\n",
      "Epoch 9, Training loss 34.587326, Validation loss 3.770980\n",
      "Epoch 10, Training loss 34.454620, Validation loss 3.781280\n",
      "Epoch 11, Training loss 34.322464, Validation loss 3.787878\n",
      "Epoch 12, Training loss 34.190853, Validation loss 3.792933\n",
      "Epoch 13, Training loss 34.059795, Validation loss 3.797347\n",
      "Epoch 14, Training loss 33.929268, Validation loss 3.801498\n",
      "Epoch 15, Training loss 33.799282, Validation loss 3.805542\n",
      "Epoch 16, Training loss 33.669830, Validation loss 3.809525\n",
      "Epoch 17, Training loss 33.540913, Validation loss 3.813503\n",
      "Epoch 18, Training loss 33.412533, Validation loss 3.817465\n",
      "Epoch 19, Training loss 33.284683, Validation loss 3.821422\n",
      "Epoch 20, Training loss 33.157356, Validation loss 3.825380\n",
      "Epoch 21, Training loss 33.030552, Validation loss 3.829336\n",
      "Epoch 22, Training loss 32.904278, Validation loss 3.833289\n",
      "Epoch 23, Training loss 32.778519, Validation loss 3.837246\n",
      "Epoch 24, Training loss 32.653286, Validation loss 3.841198\n",
      "Epoch 25, Training loss 32.528564, Validation loss 3.845149\n",
      "Epoch 26, Training loss 32.404358, Validation loss 3.849101\n",
      "Epoch 27, Training loss 32.280670, Validation loss 3.853049\n",
      "Epoch 28, Training loss 32.157486, Validation loss 3.856997\n",
      "Epoch 29, Training loss 32.034805, Validation loss 3.860938\n",
      "Epoch 30, Training loss 31.912642, Validation loss 3.864882\n",
      "Epoch 31, Training loss 31.790972, Validation loss 3.868822\n",
      "Epoch 32, Training loss 31.669817, Validation loss 3.872770\n",
      "Epoch 33, Training loss 31.549154, Validation loss 3.876711\n",
      "Epoch 34, Training loss 31.428989, Validation loss 3.880648\n",
      "Epoch 35, Training loss 31.309319, Validation loss 3.884587\n",
      "Epoch 36, Training loss 31.190151, Validation loss 3.888522\n",
      "Epoch 37, Training loss 31.071463, Validation loss 3.892457\n",
      "Epoch 38, Training loss 30.953268, Validation loss 3.896389\n",
      "Epoch 39, Training loss 30.835567, Validation loss 3.900322\n",
      "Epoch 40, Training loss 30.718344, Validation loss 3.904251\n",
      "Epoch 41, Training loss 30.601610, Validation loss 3.908180\n",
      "Epoch 42, Training loss 30.485352, Validation loss 3.912106\n",
      "Epoch 43, Training loss 30.369577, Validation loss 3.916032\n",
      "Epoch 44, Training loss 30.254290, Validation loss 3.919955\n",
      "Epoch 45, Training loss 30.139465, Validation loss 3.923877\n",
      "Epoch 46, Training loss 30.025112, Validation loss 3.927799\n",
      "Epoch 47, Training loss 29.911245, Validation loss 3.931718\n",
      "Epoch 48, Training loss 29.797834, Validation loss 3.935637\n",
      "Epoch 49, Training loss 29.684902, Validation loss 3.939548\n",
      "Epoch 50, Training loss 29.572428, Validation loss 3.943459\n",
      "Epoch 51, Training loss 29.460423, Validation loss 3.947375\n",
      "Epoch 52, Training loss 29.348873, Validation loss 3.951279\n",
      "Epoch 53, Training loss 29.237793, Validation loss 3.955189\n",
      "Epoch 54, Training loss 29.127167, Validation loss 3.959096\n",
      "Epoch 55, Training loss 29.016991, Validation loss 3.963000\n",
      "Epoch 56, Training loss 28.907280, Validation loss 3.966904\n",
      "Epoch 57, Training loss 28.798021, Validation loss 3.970800\n",
      "Epoch 58, Training loss 28.689205, Validation loss 3.974701\n",
      "Epoch 59, Training loss 28.580841, Validation loss 3.978595\n",
      "Epoch 60, Training loss 28.472923, Validation loss 3.982491\n",
      "Epoch 61, Training loss 28.365456, Validation loss 3.986380\n",
      "Epoch 62, Training loss 28.258430, Validation loss 3.990272\n",
      "Epoch 63, Training loss 28.151842, Validation loss 3.994159\n",
      "Epoch 64, Training loss 28.045706, Validation loss 3.998043\n",
      "Epoch 65, Training loss 27.939995, Validation loss 4.001928\n",
      "Epoch 66, Training loss 27.834719, Validation loss 4.005810\n",
      "Epoch 67, Training loss 27.729881, Validation loss 4.009686\n",
      "Epoch 68, Training loss 27.625481, Validation loss 4.013565\n",
      "Epoch 69, Training loss 27.521505, Validation loss 4.017441\n",
      "Epoch 70, Training loss 27.417961, Validation loss 4.021309\n",
      "Epoch 71, Training loss 27.314848, Validation loss 4.025184\n",
      "Epoch 72, Training loss 27.212156, Validation loss 4.029050\n",
      "Epoch 73, Training loss 27.109886, Validation loss 4.032919\n",
      "Epoch 74, Training loss 27.008038, Validation loss 4.036782\n",
      "Epoch 75, Training loss 26.906612, Validation loss 4.040641\n",
      "Epoch 76, Training loss 26.805607, Validation loss 4.044500\n",
      "Epoch 77, Training loss 26.705017, Validation loss 4.048361\n",
      "Epoch 78, Training loss 26.604837, Validation loss 4.052212\n",
      "Epoch 79, Training loss 26.505079, Validation loss 4.056064\n",
      "Epoch 80, Training loss 26.405731, Validation loss 4.059914\n",
      "Epoch 81, Training loss 26.306791, Validation loss 4.063765\n",
      "Epoch 82, Training loss 26.208258, Validation loss 4.067606\n",
      "Epoch 83, Training loss 26.110134, Validation loss 4.071452\n",
      "Epoch 84, Training loss 26.012411, Validation loss 4.075290\n",
      "Epoch 85, Training loss 25.915098, Validation loss 4.079127\n",
      "Epoch 86, Training loss 25.818184, Validation loss 4.082957\n",
      "Epoch 87, Training loss 25.721668, Validation loss 4.086793\n",
      "Epoch 88, Training loss 25.625546, Validation loss 4.090622\n",
      "Epoch 89, Training loss 25.529825, Validation loss 4.094450\n",
      "Epoch 90, Training loss 25.434504, Validation loss 4.098275\n",
      "Epoch 91, Training loss 25.339573, Validation loss 4.102098\n",
      "Epoch 92, Training loss 25.245029, Validation loss 4.105922\n",
      "Epoch 93, Training loss 25.150883, Validation loss 4.109741\n",
      "Epoch 94, Training loss 25.057116, Validation loss 4.113548\n",
      "Epoch 95, Training loss 24.963743, Validation loss 4.117363\n",
      "Epoch 96, Training loss 24.870750, Validation loss 4.121170\n",
      "Epoch 97, Training loss 24.778149, Validation loss 4.124976\n",
      "Epoch 98, Training loss 24.685926, Validation loss 4.128781\n",
      "Epoch 99, Training loss 24.594078, Validation loss 4.132582\n",
      "Epoch 100, Training loss 24.502617, Validation loss 4.136377\n",
      "Epoch 101, Training loss 24.411526, Validation loss 4.140173\n",
      "Epoch 102, Training loss 24.320820, Validation loss 4.143965\n",
      "Epoch 103, Training loss 24.230476, Validation loss 4.147751\n",
      "Epoch 104, Training loss 24.140516, Validation loss 4.151541\n",
      "Epoch 105, Training loss 24.050922, Validation loss 4.155325\n",
      "Epoch 106, Training loss 23.961700, Validation loss 4.159110\n",
      "Epoch 107, Training loss 23.872847, Validation loss 4.162889\n",
      "Epoch 108, Training loss 23.784355, Validation loss 4.166659\n",
      "Epoch 109, Training loss 23.696232, Validation loss 4.170433\n",
      "Epoch 110, Training loss 23.608473, Validation loss 4.174201\n",
      "Epoch 111, Training loss 23.521078, Validation loss 4.177965\n",
      "Epoch 112, Training loss 23.434036, Validation loss 4.181736\n",
      "Epoch 113, Training loss 23.347361, Validation loss 4.185493\n",
      "Epoch 114, Training loss 23.261038, Validation loss 4.189254\n",
      "Epoch 115, Training loss 23.175079, Validation loss 4.193009\n",
      "Epoch 116, Training loss 23.089470, Validation loss 4.196764\n",
      "Epoch 117, Training loss 23.004215, Validation loss 4.200517\n",
      "Epoch 118, Training loss 22.919310, Validation loss 4.204261\n",
      "Epoch 119, Training loss 22.834757, Validation loss 4.207996\n",
      "Epoch 120, Training loss 22.750555, Validation loss 4.211741\n",
      "Epoch 121, Training loss 22.666693, Validation loss 4.215477\n",
      "Epoch 122, Training loss 22.583183, Validation loss 4.219209\n",
      "Epoch 123, Training loss 22.500021, Validation loss 4.222942\n",
      "Epoch 124, Training loss 22.417192, Validation loss 4.226667\n",
      "Epoch 125, Training loss 22.334717, Validation loss 4.230398\n",
      "Epoch 126, Training loss 22.252573, Validation loss 4.234123\n",
      "Epoch 127, Training loss 22.170769, Validation loss 4.237837\n",
      "Epoch 128, Training loss 22.089306, Validation loss 4.241556\n",
      "Epoch 129, Training loss 22.008179, Validation loss 4.245266\n",
      "Epoch 130, Training loss 21.927383, Validation loss 4.248972\n",
      "Epoch 131, Training loss 21.846922, Validation loss 4.252682\n",
      "Epoch 132, Training loss 21.766794, Validation loss 4.256386\n",
      "Epoch 133, Training loss 21.686996, Validation loss 4.260079\n",
      "Epoch 134, Training loss 21.607525, Validation loss 4.263781\n",
      "Epoch 135, Training loss 21.528383, Validation loss 4.267475\n",
      "Epoch 136, Training loss 21.449570, Validation loss 4.271164\n",
      "Epoch 137, Training loss 21.371084, Validation loss 4.274851\n",
      "Epoch 138, Training loss 21.292919, Validation loss 4.278536\n",
      "Epoch 139, Training loss 21.215076, Validation loss 4.282219\n",
      "Epoch 140, Training loss 21.137552, Validation loss 4.285896\n",
      "Epoch 141, Training loss 21.060354, Validation loss 4.289568\n",
      "Epoch 142, Training loss 20.983467, Validation loss 4.293238\n",
      "Epoch 143, Training loss 20.906904, Validation loss 4.296906\n",
      "Epoch 144, Training loss 20.830662, Validation loss 4.300564\n",
      "Epoch 145, Training loss 20.754723, Validation loss 4.304226\n",
      "Epoch 146, Training loss 20.679100, Validation loss 4.307892\n",
      "Epoch 147, Training loss 20.603792, Validation loss 4.311543\n",
      "Epoch 148, Training loss 20.528788, Validation loss 4.315188\n",
      "Epoch 149, Training loss 20.454100, Validation loss 4.318840\n",
      "Epoch 150, Training loss 20.379723, Validation loss 4.322480\n",
      "Epoch 151, Training loss 20.305645, Validation loss 4.326127\n",
      "Epoch 152, Training loss 20.231880, Validation loss 4.329759\n",
      "Epoch 153, Training loss 20.158413, Validation loss 4.333397\n",
      "Epoch 154, Training loss 20.085255, Validation loss 4.337025\n",
      "Epoch 155, Training loss 20.012390, Validation loss 4.340654\n",
      "Epoch 156, Training loss 19.939837, Validation loss 4.344274\n",
      "Epoch 157, Training loss 19.867580, Validation loss 4.347894\n",
      "Epoch 158, Training loss 19.795616, Validation loss 4.351516\n",
      "Epoch 159, Training loss 19.723949, Validation loss 4.355124\n",
      "Epoch 160, Training loss 19.652582, Validation loss 4.358737\n",
      "Epoch 161, Training loss 19.581507, Validation loss 4.362344\n",
      "Epoch 162, Training loss 19.510729, Validation loss 4.365940\n",
      "Epoch 163, Training loss 19.440241, Validation loss 4.369545\n",
      "Epoch 164, Training loss 19.370041, Validation loss 4.373140\n",
      "Epoch 165, Training loss 19.300137, Validation loss 4.376733\n",
      "Epoch 166, Training loss 19.230516, Validation loss 4.380322\n",
      "Epoch 167, Training loss 19.161184, Validation loss 4.383909\n",
      "Epoch 168, Training loss 19.092140, Validation loss 4.387490\n",
      "Epoch 169, Training loss 19.023375, Validation loss 4.391068\n",
      "Epoch 170, Training loss 18.954903, Validation loss 4.394642\n",
      "Epoch 171, Training loss 18.886705, Validation loss 4.398210\n",
      "Epoch 172, Training loss 18.818796, Validation loss 4.401775\n",
      "Epoch 173, Training loss 18.751160, Validation loss 4.405341\n",
      "Epoch 174, Training loss 18.683804, Validation loss 4.408897\n",
      "Epoch 175, Training loss 18.616730, Validation loss 4.412454\n",
      "Epoch 176, Training loss 18.549932, Validation loss 4.416011\n",
      "Epoch 177, Training loss 18.483410, Validation loss 4.419563\n",
      "Epoch 178, Training loss 18.417160, Validation loss 4.423106\n",
      "Epoch 179, Training loss 18.351185, Validation loss 4.426651\n",
      "Epoch 180, Training loss 18.285482, Validation loss 4.430189\n",
      "Epoch 181, Training loss 18.220045, Validation loss 4.433727\n",
      "Epoch 182, Training loss 18.154884, Validation loss 4.437255\n",
      "Epoch 183, Training loss 18.089993, Validation loss 4.440779\n",
      "Epoch 184, Training loss 18.025366, Validation loss 4.444305\n",
      "Epoch 185, Training loss 17.961008, Validation loss 4.447823\n",
      "Epoch 186, Training loss 17.896912, Validation loss 4.451342\n",
      "Epoch 187, Training loss 17.833082, Validation loss 4.454858\n",
      "Epoch 188, Training loss 17.769518, Validation loss 4.458364\n",
      "Epoch 189, Training loss 17.706215, Validation loss 4.461869\n",
      "Epoch 190, Training loss 17.643175, Validation loss 4.465367\n",
      "Epoch 191, Training loss 17.580393, Validation loss 4.468874\n",
      "Epoch 192, Training loss 17.517870, Validation loss 4.472365\n",
      "Epoch 193, Training loss 17.455605, Validation loss 4.475858\n",
      "Epoch 194, Training loss 17.393593, Validation loss 4.479342\n",
      "Epoch 195, Training loss 17.331842, Validation loss 4.482827\n",
      "Epoch 196, Training loss 17.270348, Validation loss 4.486306\n",
      "Epoch 197, Training loss 17.209105, Validation loss 4.489780\n",
      "Epoch 198, Training loss 17.148113, Validation loss 4.493252\n",
      "Epoch 199, Training loss 17.087376, Validation loss 4.496719\n",
      "Epoch 200, Training loss 17.026890, Validation loss 4.500183\n",
      "Epoch 201, Training loss 16.966648, Validation loss 4.503644\n",
      "Epoch 202, Training loss 16.906660, Validation loss 4.507097\n",
      "Epoch 203, Training loss 16.846918, Validation loss 4.510555\n",
      "Epoch 204, Training loss 16.787416, Validation loss 4.514009\n",
      "Epoch 205, Training loss 16.728167, Validation loss 4.517443\n",
      "Epoch 206, Training loss 16.669161, Validation loss 4.520886\n",
      "Epoch 207, Training loss 16.610401, Validation loss 4.524329\n",
      "Epoch 208, Training loss 16.551878, Validation loss 4.527760\n",
      "Epoch 209, Training loss 16.493599, Validation loss 4.531187\n",
      "Epoch 210, Training loss 16.435560, Validation loss 4.534619\n",
      "Epoch 211, Training loss 16.377760, Validation loss 4.538035\n",
      "Epoch 212, Training loss 16.320198, Validation loss 4.541455\n",
      "Epoch 213, Training loss 16.262877, Validation loss 4.544868\n",
      "Epoch 214, Training loss 16.205788, Validation loss 4.548281\n",
      "Epoch 215, Training loss 16.148943, Validation loss 4.551685\n",
      "Epoch 216, Training loss 16.092325, Validation loss 4.555091\n",
      "Epoch 217, Training loss 16.035942, Validation loss 4.558488\n",
      "Epoch 218, Training loss 15.979793, Validation loss 4.561889\n",
      "Epoch 219, Training loss 15.923872, Validation loss 4.565278\n",
      "Epoch 220, Training loss 15.868186, Validation loss 4.568663\n",
      "Epoch 221, Training loss 15.812727, Validation loss 4.572048\n",
      "Epoch 222, Training loss 15.757503, Validation loss 4.575430\n",
      "Epoch 223, Training loss 15.702499, Validation loss 4.578803\n",
      "Epoch 224, Training loss 15.647725, Validation loss 4.582172\n",
      "Epoch 225, Training loss 15.593177, Validation loss 4.585541\n",
      "Epoch 226, Training loss 15.538854, Validation loss 4.588906\n",
      "Epoch 227, Training loss 15.484755, Validation loss 4.592263\n",
      "Epoch 228, Training loss 15.430880, Validation loss 4.595616\n",
      "Epoch 229, Training loss 15.377228, Validation loss 4.598977\n",
      "Epoch 230, Training loss 15.323795, Validation loss 4.602321\n",
      "Epoch 231, Training loss 15.270584, Validation loss 4.605670\n",
      "Epoch 232, Training loss 15.217592, Validation loss 4.609002\n",
      "Epoch 233, Training loss 15.164819, Validation loss 4.612342\n",
      "Epoch 234, Training loss 15.112264, Validation loss 4.615678\n",
      "Epoch 235, Training loss 15.059926, Validation loss 4.619005\n",
      "Epoch 236, Training loss 15.007804, Validation loss 4.622329\n",
      "Epoch 237, Training loss 14.955897, Validation loss 4.625651\n",
      "Epoch 238, Training loss 14.904207, Validation loss 4.628970\n",
      "Epoch 239, Training loss 14.852726, Validation loss 4.632280\n",
      "Epoch 240, Training loss 14.801461, Validation loss 4.635590\n",
      "Epoch 241, Training loss 14.750401, Validation loss 4.638896\n",
      "Epoch 242, Training loss 14.699559, Validation loss 4.642192\n",
      "Epoch 243, Training loss 14.648926, Validation loss 4.645489\n",
      "Epoch 244, Training loss 14.598495, Validation loss 4.648781\n",
      "Epoch 245, Training loss 14.548275, Validation loss 4.652073\n",
      "Epoch 246, Training loss 14.498265, Validation loss 4.655356\n",
      "Epoch 247, Training loss 14.448461, Validation loss 4.658635\n",
      "Epoch 248, Training loss 14.398861, Validation loss 4.661918\n",
      "Epoch 249, Training loss 14.349472, Validation loss 4.665192\n",
      "Epoch 250, Training loss 14.300274, Validation loss 4.668457\n",
      "Epoch 251, Training loss 14.251292, Validation loss 4.671717\n",
      "Epoch 252, Training loss 14.202505, Validation loss 4.674981\n",
      "Epoch 253, Training loss 14.153922, Validation loss 4.678236\n",
      "Epoch 254, Training loss 14.105541, Validation loss 4.681488\n",
      "Epoch 255, Training loss 14.057355, Validation loss 4.684738\n",
      "Epoch 256, Training loss 14.009371, Validation loss 4.687987\n",
      "Epoch 257, Training loss 13.961583, Validation loss 4.691224\n",
      "Epoch 258, Training loss 13.913994, Validation loss 4.694460\n",
      "Epoch 259, Training loss 13.866596, Validation loss 4.697696\n",
      "Epoch 260, Training loss 13.819401, Validation loss 4.700926\n",
      "Epoch 261, Training loss 13.772396, Validation loss 4.704148\n",
      "Epoch 262, Training loss 13.725590, Validation loss 4.707366\n",
      "Epoch 263, Training loss 13.678970, Validation loss 4.710582\n",
      "Epoch 264, Training loss 13.632549, Validation loss 4.713797\n",
      "Epoch 265, Training loss 13.586314, Validation loss 4.717009\n",
      "Epoch 266, Training loss 13.540273, Validation loss 4.720211\n",
      "Epoch 267, Training loss 13.494421, Validation loss 4.723407\n",
      "Epoch 268, Training loss 13.448759, Validation loss 4.726599\n",
      "Epoch 269, Training loss 13.403286, Validation loss 4.729795\n",
      "Epoch 270, Training loss 13.358000, Validation loss 4.732981\n",
      "Epoch 271, Training loss 13.312900, Validation loss 4.736167\n",
      "Epoch 272, Training loss 13.267986, Validation loss 4.739351\n",
      "Epoch 273, Training loss 13.223259, Validation loss 4.742527\n",
      "Epoch 274, Training loss 13.178716, Validation loss 4.745693\n",
      "Epoch 275, Training loss 13.134354, Validation loss 4.748863\n",
      "Epoch 276, Training loss 13.090178, Validation loss 4.752024\n",
      "Epoch 277, Training loss 13.046182, Validation loss 4.755192\n",
      "Epoch 278, Training loss 13.002372, Validation loss 4.758347\n",
      "Epoch 279, Training loss 12.958744, Validation loss 4.761492\n",
      "Epoch 280, Training loss 12.915287, Validation loss 4.764645\n",
      "Epoch 281, Training loss 12.872015, Validation loss 4.767788\n",
      "Epoch 282, Training loss 12.828922, Validation loss 4.770922\n",
      "Epoch 283, Training loss 12.786005, Validation loss 4.774055\n",
      "Epoch 284, Training loss 12.743266, Validation loss 4.777192\n",
      "Epoch 285, Training loss 12.700704, Validation loss 4.780319\n",
      "Epoch 286, Training loss 12.658318, Validation loss 4.783440\n",
      "Epoch 287, Training loss 12.616102, Validation loss 4.786556\n",
      "Epoch 288, Training loss 12.574066, Validation loss 4.789680\n",
      "Epoch 289, Training loss 12.532202, Validation loss 4.792786\n",
      "Epoch 290, Training loss 12.490509, Validation loss 4.795896\n",
      "Epoch 291, Training loss 12.448992, Validation loss 4.798995\n",
      "Epoch 292, Training loss 12.407642, Validation loss 4.802089\n",
      "Epoch 293, Training loss 12.366466, Validation loss 4.805191\n",
      "Epoch 294, Training loss 12.325457, Validation loss 4.808279\n",
      "Epoch 295, Training loss 12.284618, Validation loss 4.811361\n",
      "Epoch 296, Training loss 12.243946, Validation loss 4.814450\n",
      "Epoch 297, Training loss 12.203446, Validation loss 4.817522\n",
      "Epoch 298, Training loss 12.163113, Validation loss 4.820597\n",
      "Epoch 299, Training loss 12.122942, Validation loss 4.823666\n",
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      "Epoch 362, Training loss 9.899676, Validation loss 5.008775\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 363, Training loss 9.868852, Validation loss 5.011578\n",
      "Epoch 364, Training loss 9.838148, Validation loss 5.014381\n",
      "Epoch 365, Training loss 9.807575, Validation loss 5.017183\n",
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      "Epoch 371, Training loss 9.626751, Validation loss 5.033892\n",
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      "Epoch 381, Training loss 9.335182, Validation loss 5.061409\n",
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      "Epoch 388, Training loss 9.138136, Validation loss 5.080431\n",
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      "Epoch 400, Training loss 8.813338, Validation loss 5.112578\n",
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      "Epoch 412, Training loss 8.504261, Validation loss 5.144155\n",
      "Epoch 413, Training loss 8.479190, Validation loss 5.146764\n",
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      "Epoch 415, Training loss 8.429357, Validation loss 5.151960\n",
      "Epoch 416, Training loss 8.404596, Validation loss 5.154552\n",
      "Epoch 417, Training loss 8.379939, Validation loss 5.157147\n",
      "Epoch 418, Training loss 8.355381, Validation loss 5.159730\n",
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      "Epoch 422, Training loss 8.258158, Validation loss 5.170027\n",
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      "Epoch 433, Training loss 7.998944, Validation loss 5.198039\n",
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      "Epoch 619, Training loss 5.010071, Validation loss 5.603117\n",
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      "Epoch 649, Training loss 4.708913, Validation loss 5.657289\n",
      "Epoch 650, Training loss 4.699502, Validation loss 5.659041\n",
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      "Epoch 657, Training loss 4.634716, Validation loss 5.671250\n",
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      "Epoch 666, Training loss 4.554127, Validation loss 5.686737\n",
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      "Epoch 669, Training loss 4.527922, Validation loss 5.691838\n",
      "Epoch 670, Training loss 4.519258, Validation loss 5.693538\n",
      "Epoch 671, Training loss 4.510632, Validation loss 5.695230\n",
      "Epoch 672, Training loss 4.502043, Validation loss 5.696912\n",
      "Epoch 673, Training loss 4.493484, Validation loss 5.698604\n",
      "Epoch 674, Training loss 4.484967, Validation loss 5.700284\n",
      "Epoch 675, Training loss 4.476478, Validation loss 5.701977\n",
      "Epoch 676, Training loss 4.468030, Validation loss 5.703648\n",
      "Epoch 677, Training loss 4.459615, Validation loss 5.705315\n",
      "Epoch 678, Training loss 4.451236, Validation loss 5.706996\n",
      "Epoch 679, Training loss 4.442887, Validation loss 5.708660\n",
      "Epoch 680, Training loss 4.434576, Validation loss 5.710320\n",
      "Epoch 681, Training loss 4.426301, Validation loss 5.711988\n",
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      "Epoch 684, Training loss 4.401670, Validation loss 5.716953\n",
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      "Epoch 691, Training loss 4.345379, Validation loss 5.728448\n",
      "Epoch 692, Training loss 4.337471, Validation loss 5.730072\n",
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      "Epoch 694, Training loss 4.321750, Validation loss 5.733332\n",
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      "Epoch 696, Training loss 4.306158, Validation loss 5.736566\n",
      "Epoch 697, Training loss 4.298409, Validation loss 5.738188\n",
      "Epoch 698, Training loss 4.290696, Validation loss 5.739806\n",
      "Epoch 699, Training loss 4.283011, Validation loss 5.741406\n",
      "Epoch 700, Training loss 4.275358, Validation loss 5.743021\n",
      "Epoch 701, Training loss 4.267740, Validation loss 5.744627\n",
      "Epoch 702, Training loss 4.260150, Validation loss 5.746223\n",
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      "Epoch 704, Training loss 4.245068, Validation loss 5.749415\n",
      "Epoch 705, Training loss 4.237569, Validation loss 5.751013\n",
      "Epoch 706, Training loss 4.230102, Validation loss 5.752589\n",
      "Epoch 707, Training loss 4.222672, Validation loss 5.754170\n",
      "Epoch 708, Training loss 4.215267, Validation loss 5.755756\n",
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      "Epoch 710, Training loss 4.200556, Validation loss 5.758935\n",
      "Epoch 711, Training loss 4.193244, Validation loss 5.760504\n",
      "Epoch 712, Training loss 4.185960, Validation loss 5.762078\n",
      "Epoch 713, Training loss 4.178707, Validation loss 5.763643\n",
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      "Epoch 715, Training loss 4.164296, Validation loss 5.766771\n",
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      "Epoch 717, Training loss 4.150000, Validation loss 5.769891\n",
      "Epoch 718, Training loss 4.142900, Validation loss 5.771445\n",
      "Epoch 719, Training loss 4.135826, Validation loss 5.773000\n",
      "Epoch 720, Training loss 4.128779, Validation loss 5.774549\n",
      "Epoch 721, Training loss 4.121765, Validation loss 5.776100\n",
      "Epoch 722, Training loss 4.114775, Validation loss 5.777651\n",
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      "Epoch 727, Training loss 4.080276, Validation loss 5.785325\n",
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      "Epoch 729, Training loss 4.066672, Validation loss 5.788382\n",
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      "Epoch 731, Training loss 4.053183, Validation loss 5.791422\n",
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      "Epoch 733, Training loss 4.039803, Validation loss 5.794436\n",
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      "Epoch 735, Training loss 4.026535, Validation loss 5.797456\n",
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      "Epoch 737, Training loss 4.013372, Validation loss 5.800468\n",
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      "Epoch 739, Training loss 4.000322, Validation loss 5.803455\n",
      "Epoch 740, Training loss 3.993837, Validation loss 5.804963\n",
      "Epoch 741, Training loss 3.987378, Validation loss 5.806452\n",
      "Epoch 742, Training loss 3.980944, Validation loss 5.807942\n",
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      "Epoch 746, Training loss 3.955481, Validation loss 5.813878\n",
      "Epoch 747, Training loss 3.949184, Validation loss 5.815348\n",
      "Epoch 748, Training loss 3.942907, Validation loss 5.816831\n",
      "Epoch 749, Training loss 3.936658, Validation loss 5.818291\n",
      "Epoch 750, Training loss 3.930434, Validation loss 5.819747\n",
      "Epoch 751, Training loss 3.924241, Validation loss 5.821218\n",
      "Epoch 752, Training loss 3.918068, Validation loss 5.822688\n",
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      "Epoch 754, Training loss 3.905800, Validation loss 5.825599\n",
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      "Epoch 761, Training loss 3.863657, Validation loss 5.835719\n",
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      "Epoch 763, Training loss 3.851837, Validation loss 5.838585\n",
      "Epoch 764, Training loss 3.845964, Validation loss 5.840019\n",
      "Epoch 765, Training loss 3.840116, Validation loss 5.841448\n",
      "Epoch 766, Training loss 3.834294, Validation loss 5.842868\n",
      "Epoch 767, Training loss 3.828491, Validation loss 5.844289\n",
      "Epoch 768, Training loss 3.822717, Validation loss 5.845719\n",
      "Epoch 769, Training loss 3.816962, Validation loss 5.847136\n",
      "Epoch 770, Training loss 3.811234, Validation loss 5.848538\n",
      "Epoch 771, Training loss 3.805530, Validation loss 5.849965\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 772, Training loss 3.799846, Validation loss 5.851369\n",
      "Epoch 773, Training loss 3.794189, Validation loss 5.852777\n",
      "Epoch 774, Training loss 3.788556, Validation loss 5.854182\n",
      "Epoch 775, Training loss 3.782944, Validation loss 5.855582\n",
      "Epoch 776, Training loss 3.777354, Validation loss 5.856974\n",
      "Epoch 777, Training loss 3.771790, Validation loss 5.858370\n",
      "Epoch 778, Training loss 3.766248, Validation loss 5.859762\n",
      "Epoch 779, Training loss 3.760728, Validation loss 5.861158\n",
      "Epoch 780, Training loss 3.755230, Validation loss 5.862546\n",
      "Epoch 781, Training loss 3.749756, Validation loss 5.863925\n",
      "Epoch 782, Training loss 3.744306, Validation loss 5.865318\n",
      "Epoch 783, Training loss 3.738876, Validation loss 5.866693\n",
      "Epoch 784, Training loss 3.733468, Validation loss 5.868069\n",
      "Epoch 785, Training loss 3.728086, Validation loss 5.869444\n",
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      "Epoch 787, Training loss 3.717381, Validation loss 5.872201\n",
      "Epoch 788, Training loss 3.712066, Validation loss 5.873563\n",
      "Epoch 789, Training loss 3.706769, Validation loss 5.874931\n",
      "Epoch 790, Training loss 3.701494, Validation loss 5.876294\n",
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      "Epoch 795, Training loss 3.675448, Validation loss 5.883064\n",
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      "Epoch 800, Training loss 3.649936, Validation loss 5.889790\n",
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      "Epoch 802, Training loss 3.639876, Validation loss 5.892453\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1135, Training loss 2.734287, Validation loss 6.221161\n",
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      "Epoch 1400, Training loss 2.530808, Validation loss 6.366034\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1401, Training loss 2.530386, Validation loss 6.366461\n",
      "Epoch 1402, Training loss 2.529966, Validation loss 6.366873\n",
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      "Epoch 1781, Training loss 2.449775, Validation loss 6.476218\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1782, Training loss 2.449687, Validation loss 6.476420\n",
      "Epoch 1783, Training loss 2.449600, Validation loss 6.476597\n",
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      "Epoch 1855, Training loss 2.444201, Validation loss 6.489370\n",
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      "Epoch 1942, Training loss 2.439497, Validation loss 6.502479\n",
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      "Epoch 1959, Training loss 2.438758, Validation loss 6.504781\n",
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      "Epoch 1965, Training loss 2.438511, Validation loss 6.505580\n",
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      "Epoch 1969, Training loss 2.438349, Validation loss 6.506112\n",
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      "Epoch 1972, Training loss 2.438229, Validation loss 6.506492\n",
      "Epoch 1973, Training loss 2.438189, Validation loss 6.506628\n",
      "Epoch 1974, Training loss 2.438150, Validation loss 6.506755\n",
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      "Epoch 1978, Training loss 2.437993, Validation loss 6.507276\n",
      "Epoch 1979, Training loss 2.437955, Validation loss 6.507393\n",
      "Epoch 1980, Training loss 2.437917, Validation loss 6.507519\n",
      "Epoch 1981, Training loss 2.437880, Validation loss 6.507646\n",
      "Epoch 1982, Training loss 2.437840, Validation loss 6.507773\n",
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      "Epoch 1985, Training loss 2.437726, Validation loss 6.508147\n",
      "Epoch 1986, Training loss 2.437688, Validation loss 6.508288\n",
      "Epoch 1987, Training loss 2.437654, Validation loss 6.508415\n",
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      "Epoch 1989, Training loss 2.437578, Validation loss 6.508658\n",
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      "Epoch 1998, Training loss 2.437251, Validation loss 6.509778\n",
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      "Epoch 2000, Training loss 2.437180, Validation loss 6.510026\n",
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      "Epoch 2006, Training loss 2.436971, Validation loss 6.510740\n",
      "Epoch 2007, Training loss 2.436935, Validation loss 6.510862\n",
      "Epoch 2008, Training loss 2.436900, Validation loss 6.511003\n",
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      "Epoch 2010, Training loss 2.436833, Validation loss 6.511227\n",
      "Epoch 2011, Training loss 2.436800, Validation loss 6.511353\n",
      "Epoch 2012, Training loss 2.436766, Validation loss 6.511484\n",
      "Epoch 2013, Training loss 2.436732, Validation loss 6.511591\n",
      "Epoch 2014, Training loss 2.436698, Validation loss 6.511712\n",
      "Epoch 2015, Training loss 2.436666, Validation loss 6.511829\n",
      "Epoch 2016, Training loss 2.436633, Validation loss 6.511950\n",
      "Epoch 2017, Training loss 2.436599, Validation loss 6.512067\n",
      "Epoch 2018, Training loss 2.436567, Validation loss 6.512184\n",
      "Epoch 2019, Training loss 2.436535, Validation loss 6.512300\n",
      "Epoch 2020, Training loss 2.436501, Validation loss 6.512417\n",
      "Epoch 2021, Training loss 2.436469, Validation loss 6.512538\n",
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      "Epoch 2030, Training loss 2.436182, Validation loss 6.513582\n",
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      "Epoch 2173, Training loss 2.432812, Validation loss 6.527834\n",
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      "Epoch 2221, Training loss 2.432058, Validation loss 6.531739\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2222, Training loss 2.432044, Validation loss 6.531830\n",
      "Epoch 2223, Training loss 2.432030, Validation loss 6.531912\n",
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      "Epoch 2638, Training loss 2.429243, Validation loss 6.553489\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2639, Training loss 2.429240, Validation loss 6.553535\n",
      "Epoch 2640, Training loss 2.429237, Validation loss 6.553550\n",
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      "Epoch 2844, Training loss 2.428892, Validation loss 6.558997\n",
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      "Epoch 2943, Training loss 2.428803, Validation loss 6.560929\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2944, Training loss 2.428803, Validation loss 6.560945\n",
      "Epoch 2945, Training loss 2.428803, Validation loss 6.560955\n",
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      "Epoch 3101, Training loss 2.428721, Validation loss 6.563300\n",
      "Epoch 3102, Training loss 2.428720, Validation loss 6.563295\n",
      "Epoch 3103, Training loss 2.428720, Validation loss 6.563326\n",
      "Epoch 3104, Training loss 2.428720, Validation loss 6.563331\n",
      "Epoch 3105, Training loss 2.428718, Validation loss 6.563346\n",
      "Epoch 3106, Training loss 2.428719, Validation loss 6.563361\n",
      "Epoch 3107, Training loss 2.428719, Validation loss 6.563367\n",
      "Epoch 3108, Training loss 2.428717, Validation loss 6.563382\n",
      "Epoch 3109, Training loss 2.428718, Validation loss 6.563397\n",
      "Epoch 3110, Training loss 2.428719, Validation loss 6.563402\n",
      "Epoch 3111, Training loss 2.428717, Validation loss 6.563417\n",
      "Epoch 3112, Training loss 2.428718, Validation loss 6.563423\n",
      "Epoch 3113, Training loss 2.428716, Validation loss 6.563438\n",
      "Epoch 3114, Training loss 2.428715, Validation loss 6.563454\n",
      "Epoch 3115, Training loss 2.428717, Validation loss 6.563458\n",
      "Epoch 3116, Training loss 2.428715, Validation loss 6.563474\n",
      "Epoch 3117, Training loss 2.428715, Validation loss 6.563479\n",
      "Epoch 3118, Training loss 2.428716, Validation loss 6.563504\n",
      "Epoch 3119, Training loss 2.428713, Validation loss 6.563529\n",
      "Epoch 3120, Training loss 2.428715, Validation loss 6.563525\n",
      "Epoch 3121, Training loss 2.428714, Validation loss 6.563550\n",
      "Epoch 3122, Training loss 2.428714, Validation loss 6.563560\n",
      "Epoch 3123, Training loss 2.428713, Validation loss 6.563566\n",
      "Epoch 3124, Training loss 2.428713, Validation loss 6.563581\n",
      "Epoch 3125, Training loss 2.428713, Validation loss 6.563591\n",
      "Epoch 3126, Training loss 2.428711, Validation loss 6.563597\n",
      "Epoch 3127, Training loss 2.428712, Validation loss 6.563607\n",
      "Epoch 3128, Training loss 2.428710, Validation loss 6.563632\n",
      "Epoch 3129, Training loss 2.428711, Validation loss 6.563627\n",
      "Epoch 3130, Training loss 2.428710, Validation loss 6.563638\n",
      "Epoch 3131, Training loss 2.428711, Validation loss 6.563648\n",
      "Epoch 3132, Training loss 2.428710, Validation loss 6.563673\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3133, Training loss 2.428710, Validation loss 6.563679\n",
      "Epoch 3134, Training loss 2.428709, Validation loss 6.563703\n",
      "Epoch 3135, Training loss 2.428710, Validation loss 6.563723\n",
      "Epoch 3136, Training loss 2.428708, Validation loss 6.563738\n",
      "Epoch 3137, Training loss 2.428708, Validation loss 6.563739\n",
      "Epoch 3138, Training loss 2.428708, Validation loss 6.563759\n",
      "Epoch 3139, Training loss 2.428708, Validation loss 6.563759\n",
      "Epoch 3140, Training loss 2.428708, Validation loss 6.563779\n",
      "Epoch 3141, Training loss 2.428708, Validation loss 6.563780\n",
      "Epoch 3142, Training loss 2.428707, Validation loss 6.563795\n",
      "Epoch 3143, Training loss 2.428706, Validation loss 6.563796\n",
      "Epoch 3144, Training loss 2.428707, Validation loss 6.563816\n",
      "Epoch 3145, Training loss 2.428706, Validation loss 6.563836\n",
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      "Epoch 3147, Training loss 2.428706, Validation loss 6.563851\n",
      "Epoch 3148, Training loss 2.428706, Validation loss 6.563852\n",
      "Epoch 3149, Training loss 2.428705, Validation loss 6.563862\n",
      "Epoch 3150, Training loss 2.428706, Validation loss 6.563882\n",
      "Epoch 3151, Training loss 2.428704, Validation loss 6.563892\n",
      "Epoch 3152, Training loss 2.428703, Validation loss 6.563912\n",
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      "Epoch 3155, Training loss 2.428703, Validation loss 6.563943\n",
      "Epoch 3156, Training loss 2.428703, Validation loss 6.563953\n",
      "Epoch 3157, Training loss 2.428702, Validation loss 6.563968\n",
      "Epoch 3158, Training loss 2.428702, Validation loss 6.563978\n",
      "Epoch 3159, Training loss 2.428701, Validation loss 6.563989\n",
      "Epoch 3160, Training loss 2.428702, Validation loss 6.563999\n",
      "Epoch 3161, Training loss 2.428702, Validation loss 6.564009\n",
      "Epoch 3162, Training loss 2.428701, Validation loss 6.564030\n",
      "Epoch 3163, Training loss 2.428700, Validation loss 6.564025\n",
      "Epoch 3164, Training loss 2.428700, Validation loss 6.564035\n",
      "Epoch 3165, Training loss 2.428699, Validation loss 6.564045\n",
      "Epoch 3166, Training loss 2.428701, Validation loss 6.564060\n",
      "Epoch 3167, Training loss 2.428700, Validation loss 6.564071\n",
      "Epoch 3168, Training loss 2.428699, Validation loss 6.564091\n",
      "Epoch 3169, Training loss 2.428699, Validation loss 6.564106\n",
      "Epoch 3170, Training loss 2.428699, Validation loss 6.564106\n",
      "Epoch 3171, Training loss 2.428699, Validation loss 6.564112\n",
      "Epoch 3172, Training loss 2.428699, Validation loss 6.564142\n",
      "Epoch 3173, Training loss 2.428699, Validation loss 6.564147\n",
      "Epoch 3174, Training loss 2.428697, Validation loss 6.564152\n",
      "Epoch 3175, Training loss 2.428697, Validation loss 6.564163\n",
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      "Epoch 3177, Training loss 2.428697, Validation loss 6.564173\n",
      "Epoch 3178, Training loss 2.428696, Validation loss 6.564193\n",
      "Epoch 3179, Training loss 2.428695, Validation loss 6.564208\n",
      "Epoch 3180, Training loss 2.428696, Validation loss 6.564213\n",
      "Epoch 3181, Training loss 2.428695, Validation loss 6.564214\n",
      "Epoch 3182, Training loss 2.428695, Validation loss 6.564229\n",
      "Epoch 3183, Training loss 2.428695, Validation loss 6.564249\n",
      "Epoch 3184, Training loss 2.428696, Validation loss 6.564254\n",
      "Epoch 3185, Training loss 2.428696, Validation loss 6.564270\n",
      "Epoch 3186, Training loss 2.428696, Validation loss 6.564280\n",
      "Epoch 3187, Training loss 2.428694, Validation loss 6.564295\n",
      "Epoch 3188, Training loss 2.428693, Validation loss 6.564301\n",
      "Epoch 3189, Training loss 2.428694, Validation loss 6.564315\n",
      "Epoch 3190, Training loss 2.428694, Validation loss 6.564330\n",
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      "Epoch 3198, Training loss 2.428691, Validation loss 6.564397\n",
      "Epoch 3199, Training loss 2.428691, Validation loss 6.564422\n",
      "Epoch 3200, Training loss 2.428691, Validation loss 6.564418\n",
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      "Epoch 3206, Training loss 2.428689, Validation loss 6.564484\n",
      "Epoch 3207, Training loss 2.428689, Validation loss 6.564499\n",
      "Epoch 3208, Training loss 2.428688, Validation loss 6.564514\n",
      "Epoch 3209, Training loss 2.428688, Validation loss 6.564524\n",
      "Epoch 3210, Training loss 2.428688, Validation loss 6.564540\n",
      "Epoch 3211, Training loss 2.428688, Validation loss 6.564545\n",
      "Epoch 3212, Training loss 2.428688, Validation loss 6.564545\n",
      "Epoch 3213, Training loss 2.428687, Validation loss 6.564565\n",
      "Epoch 3214, Training loss 2.428688, Validation loss 6.564570\n",
      "Epoch 3215, Training loss 2.428687, Validation loss 6.564586\n",
      "Epoch 3216, Training loss 2.428686, Validation loss 6.564586\n",
      "Epoch 3217, Training loss 2.428687, Validation loss 6.564596\n",
      "Epoch 3218, Training loss 2.428686, Validation loss 6.564611\n",
      "Epoch 3219, Training loss 2.428687, Validation loss 6.564611\n",
      "Epoch 3220, Training loss 2.428685, Validation loss 6.564617\n",
      "Epoch 3221, Training loss 2.428686, Validation loss 6.564637\n",
      "Epoch 3222, Training loss 2.428686, Validation loss 6.564652\n",
      "Epoch 3223, Training loss 2.428686, Validation loss 6.564657\n",
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      "Epoch 3225, Training loss 2.428684, Validation loss 6.564678\n",
      "Epoch 3226, Training loss 2.428685, Validation loss 6.564688\n",
      "Epoch 3227, Training loss 2.428684, Validation loss 6.564703\n",
      "Epoch 3228, Training loss 2.428684, Validation loss 6.564713\n",
      "Epoch 3229, Training loss 2.428684, Validation loss 6.564723\n",
      "Epoch 3230, Training loss 2.428684, Validation loss 6.564734\n",
      "Epoch 3231, Training loss 2.428683, Validation loss 6.564744\n",
      "Epoch 3232, Training loss 2.428683, Validation loss 6.564754\n",
      "Epoch 3233, Training loss 2.428684, Validation loss 6.564754\n",
      "Epoch 3234, Training loss 2.428683, Validation loss 6.564764\n",
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      "Epoch 3239, Training loss 2.428681, Validation loss 6.564800\n",
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      "Epoch 3243, Training loss 2.428681, Validation loss 6.564841\n",
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      "Epoch 3260, Training loss 2.428678, Validation loss 6.565000\n",
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      "Epoch 3269, Training loss 2.428676, Validation loss 6.565101\n",
      "Epoch 3270, Training loss 2.428676, Validation loss 6.565111\n",
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      "Epoch 3310, Training loss 2.428669, Validation loss 6.565457\n",
      "Epoch 3311, Training loss 2.428668, Validation loss 6.565453\n",
      "Epoch 3312, Training loss 2.428668, Validation loss 6.565463\n",
      "Epoch 3313, Training loss 2.428668, Validation loss 6.565463\n",
      "Epoch 3314, Training loss 2.428670, Validation loss 6.565488\n",
      "Epoch 3315, Training loss 2.428668, Validation loss 6.565488\n",
      "Epoch 3316, Training loss 2.428668, Validation loss 6.565494\n",
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      "Epoch 3331, Training loss 2.428665, Validation loss 6.565606\n",
      "Epoch 3332, Training loss 2.428665, Validation loss 6.565606\n",
      "Epoch 3333, Training loss 2.428665, Validation loss 6.565612\n",
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      "Epoch 3335, Training loss 2.428665, Validation loss 6.565641\n",
      "Epoch 3336, Training loss 2.428665, Validation loss 6.565661\n",
      "Epoch 3337, Training loss 2.428665, Validation loss 6.565667\n",
      "Epoch 3338, Training loss 2.428664, Validation loss 6.565672\n",
      "Epoch 3339, Training loss 2.428663, Validation loss 6.565677\n",
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      "Epoch 3341, Training loss 2.428663, Validation loss 6.565698\n",
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      "Epoch 3343, Training loss 2.428664, Validation loss 6.565708\n",
      "Epoch 3344, Training loss 2.428664, Validation loss 6.565713\n",
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      "Epoch 3346, Training loss 2.428664, Validation loss 6.565723\n",
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      "Epoch 3351, Training loss 2.428662, Validation loss 6.565754\n",
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      "Epoch 3353, Training loss 2.428663, Validation loss 6.565764\n",
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      "Epoch 3356, Training loss 2.428663, Validation loss 6.565795\n",
      "Epoch 3357, Training loss 2.428661, Validation loss 6.565795\n",
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      "Epoch 3359, Training loss 2.428662, Validation loss 6.565816\n",
      "Epoch 3360, Training loss 2.428662, Validation loss 6.565835\n",
      "Epoch 3361, Training loss 2.428662, Validation loss 6.565845\n",
      "Epoch 3362, Training loss 2.428661, Validation loss 6.565856\n",
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      "Epoch 3364, Training loss 2.428662, Validation loss 6.565870\n",
      "Epoch 3365, Training loss 2.428661, Validation loss 6.565881\n",
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      "Epoch 3373, Training loss 2.428660, Validation loss 6.565932\n",
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      "Epoch 3375, Training loss 2.428660, Validation loss 6.565938\n",
      "Epoch 3376, Training loss 2.428661, Validation loss 6.565948\n",
      "Epoch 3377, Training loss 2.428660, Validation loss 6.565958\n",
      "Epoch 3378, Training loss 2.428659, Validation loss 6.565973\n",
      "Epoch 3379, Training loss 2.428659, Validation loss 6.565973\n",
      "Epoch 3380, Training loss 2.428660, Validation loss 6.565969\n",
      "Epoch 3381, Training loss 2.428659, Validation loss 6.565979\n",
      "Epoch 3382, Training loss 2.428659, Validation loss 6.565993\n",
      "Epoch 3383, Training loss 2.428659, Validation loss 6.566004\n",
      "Epoch 3384, Training loss 2.428658, Validation loss 6.565999\n",
      "Epoch 3385, Training loss 2.428658, Validation loss 6.566010\n",
      "Epoch 3386, Training loss 2.428658, Validation loss 6.566030\n",
      "Epoch 3387, Training loss 2.428658, Validation loss 6.566034\n",
      "Epoch 3388, Training loss 2.428658, Validation loss 6.566040\n",
      "Epoch 3389, Training loss 2.428658, Validation loss 6.566045\n",
      "Epoch 3390, Training loss 2.428658, Validation loss 6.566050\n",
      "Epoch 3391, Training loss 2.428657, Validation loss 6.566055\n",
      "Epoch 3392, Training loss 2.428658, Validation loss 6.566060\n",
      "Epoch 3393, Training loss 2.428658, Validation loss 6.566065\n",
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      "Epoch 3395, Training loss 2.428658, Validation loss 6.566091\n",
      "Epoch 3396, Training loss 2.428658, Validation loss 6.566095\n",
      "Epoch 3397, Training loss 2.428658, Validation loss 6.566101\n",
      "Epoch 3398, Training loss 2.428656, Validation loss 6.566101\n",
      "Epoch 3399, Training loss 2.428657, Validation loss 6.566106\n",
      "Epoch 3400, Training loss 2.428657, Validation loss 6.566111\n",
      "Epoch 3401, Training loss 2.428658, Validation loss 6.566116\n",
      "Epoch 3402, Training loss 2.428656, Validation loss 6.566121\n",
      "Epoch 3403, Training loss 2.428658, Validation loss 6.566127\n",
      "Epoch 3404, Training loss 2.428656, Validation loss 6.566132\n",
      "Epoch 3405, Training loss 2.428657, Validation loss 6.566137\n",
      "Epoch 3406, Training loss 2.428656, Validation loss 6.566152\n",
      "Epoch 3407, Training loss 2.428657, Validation loss 6.566153\n",
      "Epoch 3408, Training loss 2.428656, Validation loss 6.566158\n",
      "Epoch 3409, Training loss 2.428656, Validation loss 6.566172\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3410, Training loss 2.428657, Validation loss 6.566188\n",
      "Epoch 3411, Training loss 2.428655, Validation loss 6.566188\n",
      "Epoch 3412, Training loss 2.428656, Validation loss 6.566193\n",
      "Epoch 3413, Training loss 2.428656, Validation loss 6.566198\n",
      "Epoch 3414, Training loss 2.428656, Validation loss 6.566203\n",
      "Epoch 3415, Training loss 2.428655, Validation loss 6.566218\n",
      "Epoch 3416, Training loss 2.428655, Validation loss 6.566233\n",
      "Epoch 3417, Training loss 2.428655, Validation loss 6.566229\n",
      "Epoch 3418, Training loss 2.428656, Validation loss 6.566243\n",
      "Epoch 3419, Training loss 2.428655, Validation loss 6.566254\n",
      "Epoch 3420, Training loss 2.428654, Validation loss 6.566249\n",
      "Epoch 3421, Training loss 2.428655, Validation loss 6.566264\n",
      "Epoch 3422, Training loss 2.428655, Validation loss 6.566264\n",
      "Epoch 3423, Training loss 2.428654, Validation loss 6.566269\n",
      "Epoch 3424, Training loss 2.428654, Validation loss 6.566284\n",
      "Epoch 3425, Training loss 2.428654, Validation loss 6.566279\n",
      "Epoch 3426, Training loss 2.428655, Validation loss 6.566295\n",
      "Epoch 3427, Training loss 2.428654, Validation loss 6.566295\n",
      "Epoch 3428, Training loss 2.428654, Validation loss 6.566300\n",
      "Epoch 3429, Training loss 2.428653, Validation loss 6.566315\n",
      "Epoch 3430, Training loss 2.428654, Validation loss 6.566315\n",
      "Epoch 3431, Training loss 2.428654, Validation loss 6.566310\n",
      "Epoch 3432, Training loss 2.428654, Validation loss 6.566325\n",
      "Epoch 3433, Training loss 2.428653, Validation loss 6.566336\n",
      "Epoch 3434, Training loss 2.428654, Validation loss 6.566331\n",
      "Epoch 3435, Training loss 2.428653, Validation loss 6.566346\n",
      "Epoch 3436, Training loss 2.428653, Validation loss 6.566341\n",
      "Epoch 3437, Training loss 2.428653, Validation loss 6.566356\n",
      "Epoch 3438, Training loss 2.428653, Validation loss 6.566366\n",
      "Epoch 3439, Training loss 2.428654, Validation loss 6.566361\n",
      "Epoch 3440, Training loss 2.428652, Validation loss 6.566377\n",
      "Epoch 3441, Training loss 2.428653, Validation loss 6.566377\n",
      "Epoch 3442, Training loss 2.428653, Validation loss 6.566382\n",
      "Epoch 3443, Training loss 2.428652, Validation loss 6.566397\n",
      "Epoch 3444, Training loss 2.428653, Validation loss 6.566392\n",
      "Epoch 3445, Training loss 2.428653, Validation loss 6.566402\n",
      "Epoch 3446, Training loss 2.428652, Validation loss 6.566418\n",
      "Epoch 3447, Training loss 2.428653, Validation loss 6.566427\n",
      "Epoch 3448, Training loss 2.428652, Validation loss 6.566432\n",
      "Epoch 3449, Training loss 2.428652, Validation loss 6.566442\n",
      "Epoch 3450, Training loss 2.428652, Validation loss 6.566442\n",
      "Epoch 3451, Training loss 2.428653, Validation loss 6.566448\n",
      "Epoch 3452, Training loss 2.428653, Validation loss 6.566467\n",
      "Epoch 3453, Training loss 2.428652, Validation loss 6.566458\n",
      "Epoch 3454, Training loss 2.428652, Validation loss 6.566463\n",
      "Epoch 3455, Training loss 2.428652, Validation loss 6.566483\n",
      "Epoch 3456, Training loss 2.428652, Validation loss 6.566473\n",
      "Epoch 3457, Training loss 2.428651, Validation loss 6.566489\n",
      "Epoch 3458, Training loss 2.428652, Validation loss 6.566483\n",
      "Epoch 3459, Training loss 2.428651, Validation loss 6.566499\n",
      "Epoch 3460, Training loss 2.428651, Validation loss 6.566508\n",
      "Epoch 3461, Training loss 2.428651, Validation loss 6.566499\n",
      "Epoch 3462, Training loss 2.428651, Validation loss 6.566514\n",
      "Epoch 3463, Training loss 2.428651, Validation loss 6.566524\n",
      "Epoch 3464, Training loss 2.428651, Validation loss 6.566529\n",
      "Epoch 3465, Training loss 2.428651, Validation loss 6.566529\n",
      "Epoch 3466, Training loss 2.428651, Validation loss 6.566539\n",
      "Epoch 3467, Training loss 2.428651, Validation loss 6.566540\n",
      "Epoch 3468, Training loss 2.428651, Validation loss 6.566545\n",
      "Epoch 3469, Training loss 2.428651, Validation loss 6.566545\n",
      "Epoch 3470, Training loss 2.428650, Validation loss 6.566555\n",
      "Epoch 3471, Training loss 2.428651, Validation loss 6.566560\n",
      "Epoch 3472, Training loss 2.428650, Validation loss 6.566570\n",
      "Epoch 3473, Training loss 2.428650, Validation loss 6.566570\n",
      "Epoch 3474, Training loss 2.428651, Validation loss 6.566576\n",
      "Epoch 3475, Training loss 2.428650, Validation loss 6.566596\n",
      "Epoch 3476, Training loss 2.428649, Validation loss 6.566586\n",
      "Epoch 3477, Training loss 2.428650, Validation loss 6.566601\n",
      "Epoch 3478, Training loss 2.428651, Validation loss 6.566611\n",
      "Epoch 3479, Training loss 2.428650, Validation loss 6.566621\n",
      "Epoch 3480, Training loss 2.428649, Validation loss 6.566626\n",
      "Epoch 3481, Training loss 2.428650, Validation loss 6.566636\n",
      "Epoch 3482, Training loss 2.428649, Validation loss 6.566636\n",
      "Epoch 3483, Training loss 2.428649, Validation loss 6.566647\n",
      "Epoch 3484, Training loss 2.428647, Validation loss 6.566647\n",
      "Epoch 3485, Training loss 2.428649, Validation loss 6.566657\n",
      "Epoch 3486, Training loss 2.428650, Validation loss 6.566657\n",
      "Epoch 3487, Training loss 2.428650, Validation loss 6.566667\n",
      "Epoch 3488, Training loss 2.428649, Validation loss 6.566677\n",
      "Epoch 3489, Training loss 2.428649, Validation loss 6.566677\n",
      "Epoch 3490, Training loss 2.428649, Validation loss 6.566688\n",
      "Epoch 3491, Training loss 2.428648, Validation loss 6.566688\n",
      "Epoch 3492, Training loss 2.428649, Validation loss 6.566698\n",
      "Epoch 3493, Training loss 2.428648, Validation loss 6.566698\n",
      "Epoch 3494, Training loss 2.428649, Validation loss 6.566693\n",
      "Epoch 3495, Training loss 2.428648, Validation loss 6.566703\n",
      "Epoch 3496, Training loss 2.428649, Validation loss 6.566703\n",
      "Epoch 3497, Training loss 2.428649, Validation loss 6.566713\n",
      "Epoch 3498, Training loss 2.428648, Validation loss 6.566713\n",
      "Epoch 3499, Training loss 2.428648, Validation loss 6.566729\n",
      "Epoch 3500, Training loss 2.428648, Validation loss 6.566729\n",
      "Epoch 3501, Training loss 2.428647, Validation loss 6.566739\n",
      "Epoch 3502, Training loss 2.428648, Validation loss 6.566739\n",
      "Epoch 3503, Training loss 2.428647, Validation loss 6.566749\n",
      "Epoch 3504, Training loss 2.428648, Validation loss 6.566759\n",
      "Epoch 3505, Training loss 2.428647, Validation loss 6.566759\n",
      "Epoch 3506, Training loss 2.428647, Validation loss 6.566770\n",
      "Epoch 3507, Training loss 2.428647, Validation loss 6.566770\n",
      "Epoch 3508, Training loss 2.428648, Validation loss 6.566780\n",
      "Epoch 3509, Training loss 2.428647, Validation loss 6.566780\n",
      "Epoch 3510, Training loss 2.428649, Validation loss 6.566775\n",
      "Epoch 3511, Training loss 2.428648, Validation loss 6.566785\n",
      "Epoch 3512, Training loss 2.428648, Validation loss 6.566795\n",
      "Epoch 3513, Training loss 2.428647, Validation loss 6.566814\n",
      "Epoch 3514, Training loss 2.428647, Validation loss 6.566820\n",
      "Epoch 3515, Training loss 2.428648, Validation loss 6.566814\n",
      "Epoch 3516, Training loss 2.428649, Validation loss 6.566815\n",
      "Epoch 3517, Training loss 2.428647, Validation loss 6.566835\n",
      "Epoch 3518, Training loss 2.428647, Validation loss 6.566830\n",
      "Epoch 3519, Training loss 2.428647, Validation loss 6.566835\n",
      "Epoch 3520, Training loss 2.428647, Validation loss 6.566836\n",
      "Epoch 3521, Training loss 2.428648, Validation loss 6.566841\n",
      "Epoch 3522, Training loss 2.428647, Validation loss 6.566851\n",
      "Epoch 3523, Training loss 2.428646, Validation loss 6.566855\n",
      "Epoch 3524, Training loss 2.428647, Validation loss 6.566856\n",
      "Epoch 3525, Training loss 2.428646, Validation loss 6.566861\n",
      "Epoch 3526, Training loss 2.428646, Validation loss 6.566871\n",
      "Epoch 3527, Training loss 2.428647, Validation loss 6.566876\n",
      "Epoch 3528, Training loss 2.428646, Validation loss 6.566877\n",
      "Epoch 3529, Training loss 2.428647, Validation loss 6.566882\n",
      "Epoch 3530, Training loss 2.428646, Validation loss 6.566892\n",
      "Epoch 3531, Training loss 2.428647, Validation loss 6.566896\n",
      "Epoch 3532, Training loss 2.428646, Validation loss 6.566897\n",
      "Epoch 3533, Training loss 2.428646, Validation loss 6.566902\n",
      "Epoch 3534, Training loss 2.428645, Validation loss 6.566897\n",
      "Epoch 3535, Training loss 2.428646, Validation loss 6.566917\n",
      "Epoch 3536, Training loss 2.428646, Validation loss 6.566922\n",
      "Epoch 3537, Training loss 2.428645, Validation loss 6.566923\n",
      "Epoch 3538, Training loss 2.428645, Validation loss 6.566917\n",
      "Epoch 3539, Training loss 2.428646, Validation loss 6.566937\n",
      "Epoch 3540, Training loss 2.428645, Validation loss 6.566943\n",
      "Epoch 3541, Training loss 2.428645, Validation loss 6.566943\n",
      "Epoch 3542, Training loss 2.428646, Validation loss 6.566938\n",
      "Epoch 3543, Training loss 2.428645, Validation loss 6.566958\n",
      "Epoch 3544, Training loss 2.428646, Validation loss 6.566963\n",
      "Epoch 3545, Training loss 2.428645, Validation loss 6.566954\n",
      "Epoch 3546, Training loss 2.428645, Validation loss 6.566958\n",
      "Epoch 3547, Training loss 2.428645, Validation loss 6.566964\n",
      "Epoch 3548, Training loss 2.428646, Validation loss 6.566994\n",
      "Epoch 3549, Training loss 2.428645, Validation loss 6.566984\n",
      "Epoch 3550, Training loss 2.428645, Validation loss 6.566998\n",
      "Epoch 3551, Training loss 2.428645, Validation loss 6.566994\n",
      "Epoch 3552, Training loss 2.428644, Validation loss 6.567009\n",
      "Epoch 3553, Training loss 2.428644, Validation loss 6.567024\n",
      "Epoch 3554, Training loss 2.428645, Validation loss 6.567019\n",
      "Epoch 3555, Training loss 2.428645, Validation loss 6.567034\n",
      "Epoch 3556, Training loss 2.428644, Validation loss 6.567029\n",
      "Epoch 3557, Training loss 2.428644, Validation loss 6.567044\n",
      "Epoch 3558, Training loss 2.428644, Validation loss 6.567039\n",
      "Epoch 3559, Training loss 2.428646, Validation loss 6.567044\n",
      "Epoch 3560, Training loss 2.428646, Validation loss 6.567055\n",
      "Epoch 3561, Training loss 2.428644, Validation loss 6.567050\n",
      "Epoch 3562, Training loss 2.428644, Validation loss 6.567050\n",
      "Epoch 3563, Training loss 2.428645, Validation loss 6.567060\n",
      "Epoch 3564, Training loss 2.428645, Validation loss 6.567075\n",
      "Epoch 3565, Training loss 2.428643, Validation loss 6.567070\n",
      "Epoch 3566, Training loss 2.428643, Validation loss 6.567070\n",
      "Epoch 3567, Training loss 2.428645, Validation loss 6.567080\n",
      "Epoch 3568, Training loss 2.428645, Validation loss 6.567085\n",
      "Epoch 3569, Training loss 2.428644, Validation loss 6.567091\n",
      "Epoch 3570, Training loss 2.428642, Validation loss 6.567096\n",
      "Epoch 3571, Training loss 2.428643, Validation loss 6.567091\n",
      "Epoch 3572, Training loss 2.428644, Validation loss 6.567106\n",
      "Epoch 3573, Training loss 2.428644, Validation loss 6.567101\n",
      "Epoch 3574, Training loss 2.428645, Validation loss 6.567116\n",
      "Epoch 3575, Training loss 2.428643, Validation loss 6.567111\n",
      "Epoch 3576, Training loss 2.428643, Validation loss 6.567126\n",
      "Epoch 3577, Training loss 2.428643, Validation loss 6.567122\n",
      "Epoch 3578, Training loss 2.428644, Validation loss 6.567136\n",
      "Epoch 3579, Training loss 2.428643, Validation loss 6.567132\n",
      "Epoch 3580, Training loss 2.428643, Validation loss 6.567132\n",
      "Epoch 3581, Training loss 2.428643, Validation loss 6.567142\n",
      "Epoch 3582, Training loss 2.428643, Validation loss 6.567142\n",
      "Epoch 3583, Training loss 2.428644, Validation loss 6.567142\n",
      "Epoch 3584, Training loss 2.428643, Validation loss 6.567152\n",
      "Epoch 3585, Training loss 2.428643, Validation loss 6.567167\n",
      "Epoch 3586, Training loss 2.428643, Validation loss 6.567163\n",
      "Epoch 3587, Training loss 2.428643, Validation loss 6.567158\n",
      "Epoch 3588, Training loss 2.428643, Validation loss 6.567173\n",
      "Epoch 3589, Training loss 2.428643, Validation loss 6.567178\n",
      "Epoch 3590, Training loss 2.428643, Validation loss 6.567187\n",
      "Epoch 3591, Training loss 2.428643, Validation loss 6.567193\n",
      "Epoch 3592, Training loss 2.428643, Validation loss 6.567198\n",
      "Epoch 3593, Training loss 2.428643, Validation loss 6.567203\n",
      "Epoch 3594, Training loss 2.428643, Validation loss 6.567213\n",
      "Epoch 3595, Training loss 2.428642, Validation loss 6.567218\n",
      "Epoch 3596, Training loss 2.428643, Validation loss 6.567223\n",
      "Epoch 3597, Training loss 2.428643, Validation loss 6.567233\n",
      "Epoch 3598, Training loss 2.428642, Validation loss 6.567218\n",
      "Epoch 3599, Training loss 2.428643, Validation loss 6.567238\n",
      "Epoch 3600, Training loss 2.428641, Validation loss 6.567244\n",
      "Epoch 3601, Training loss 2.428642, Validation loss 6.567248\n",
      "Epoch 3602, Training loss 2.428643, Validation loss 6.567254\n",
      "Epoch 3603, Training loss 2.428643, Validation loss 6.567264\n",
      "Epoch 3604, Training loss 2.428643, Validation loss 6.567254\n",
      "Epoch 3605, Training loss 2.428643, Validation loss 6.567259\n",
      "Epoch 3606, Training loss 2.428641, Validation loss 6.567264\n",
      "Epoch 3607, Training loss 2.428642, Validation loss 6.567269\n",
      "Epoch 3608, Training loss 2.428642, Validation loss 6.567259\n",
      "Epoch 3609, Training loss 2.428641, Validation loss 6.567265\n",
      "Epoch 3610, Training loss 2.428642, Validation loss 6.567274\n",
      "Epoch 3611, Training loss 2.428643, Validation loss 6.567279\n",
      "Epoch 3612, Training loss 2.428643, Validation loss 6.567295\n",
      "Epoch 3613, Training loss 2.428642, Validation loss 6.567300\n",
      "Epoch 3614, Training loss 2.428641, Validation loss 6.567290\n",
      "Epoch 3615, Training loss 2.428641, Validation loss 6.567300\n",
      "Epoch 3616, Training loss 2.428641, Validation loss 6.567305\n",
      "Epoch 3617, Training loss 2.428641, Validation loss 6.567310\n",
      "Epoch 3618, Training loss 2.428642, Validation loss 6.567315\n",
      "Epoch 3619, Training loss 2.428643, Validation loss 6.567306\n",
      "Epoch 3620, Training loss 2.428641, Validation loss 6.567310\n",
      "Epoch 3621, Training loss 2.428641, Validation loss 6.567320\n",
      "Epoch 3622, Training loss 2.428642, Validation loss 6.567326\n",
      "Epoch 3623, Training loss 2.428641, Validation loss 6.567330\n",
      "Epoch 3624, Training loss 2.428642, Validation loss 6.567331\n",
      "Epoch 3625, Training loss 2.428641, Validation loss 6.567336\n",
      "Epoch 3626, Training loss 2.428641, Validation loss 6.567346\n",
      "Epoch 3627, Training loss 2.428641, Validation loss 6.567351\n",
      "Epoch 3628, Training loss 2.428640, Validation loss 6.567356\n",
      "Epoch 3629, Training loss 2.428640, Validation loss 6.567361\n",
      "Epoch 3630, Training loss 2.428642, Validation loss 6.567351\n",
      "Epoch 3631, Training loss 2.428640, Validation loss 6.567357\n",
      "Epoch 3632, Training loss 2.428641, Validation loss 6.567367\n",
      "Epoch 3633, Training loss 2.428642, Validation loss 6.567381\n",
      "Epoch 3634, Training loss 2.428641, Validation loss 6.567382\n",
      "Epoch 3635, Training loss 2.428641, Validation loss 6.567397\n",
      "Epoch 3636, Training loss 2.428641, Validation loss 6.567397\n",
      "Epoch 3637, Training loss 2.428641, Validation loss 6.567397\n",
      "Epoch 3638, Training loss 2.428640, Validation loss 6.567407\n",
      "Epoch 3639, Training loss 2.428641, Validation loss 6.567407\n",
      "Epoch 3640, Training loss 2.428640, Validation loss 6.567402\n",
      "Epoch 3641, Training loss 2.428641, Validation loss 6.567402\n",
      "Epoch 3642, Training loss 2.428640, Validation loss 6.567412\n",
      "Epoch 3643, Training loss 2.428641, Validation loss 6.567427\n",
      "Epoch 3644, Training loss 2.428641, Validation loss 6.567427\n",
      "Epoch 3645, Training loss 2.428641, Validation loss 6.567427\n",
      "Epoch 3646, Training loss 2.428640, Validation loss 6.567437\n",
      "Epoch 3647, Training loss 2.428641, Validation loss 6.567437\n",
      "Epoch 3648, Training loss 2.428640, Validation loss 6.567437\n",
      "Epoch 3649, Training loss 2.428640, Validation loss 6.567433\n",
      "Epoch 3650, Training loss 2.428639, Validation loss 6.567443\n",
      "Epoch 3651, Training loss 2.428640, Validation loss 6.567443\n",
      "Epoch 3652, Training loss 2.428640, Validation loss 6.567443\n",
      "Epoch 3653, Training loss 2.428639, Validation loss 6.567453\n",
      "Epoch 3654, Training loss 2.428639, Validation loss 6.567453\n",
      "Epoch 3655, Training loss 2.428641, Validation loss 6.567468\n",
      "Epoch 3656, Training loss 2.428639, Validation loss 6.567468\n",
      "Epoch 3657, Training loss 2.428640, Validation loss 6.567468\n",
      "Epoch 3658, Training loss 2.428640, Validation loss 6.567478\n",
      "Epoch 3659, Training loss 2.428640, Validation loss 6.567474\n",
      "Epoch 3660, Training loss 2.428640, Validation loss 6.567474\n",
      "Epoch 3661, Training loss 2.428639, Validation loss 6.567484\n",
      "Epoch 3662, Training loss 2.428639, Validation loss 6.567499\n",
      "Epoch 3663, Training loss 2.428640, Validation loss 6.567499\n",
      "Epoch 3664, Training loss 2.428639, Validation loss 6.567499\n",
      "Epoch 3665, Training loss 2.428641, Validation loss 6.567499\n",
      "Epoch 3666, Training loss 2.428639, Validation loss 6.567509\n",
      "Epoch 3667, Training loss 2.428639, Validation loss 6.567509\n",
      "Epoch 3668, Training loss 2.428639, Validation loss 6.567505\n",
      "Epoch 3669, Training loss 2.428639, Validation loss 6.567515\n",
      "Epoch 3670, Training loss 2.428641, Validation loss 6.567515\n",
      "Epoch 3671, Training loss 2.428639, Validation loss 6.567515\n",
      "Epoch 3672, Training loss 2.428640, Validation loss 6.567515\n",
      "Epoch 3673, Training loss 2.428639, Validation loss 6.567540\n",
      "Epoch 3674, Training loss 2.428639, Validation loss 6.567540\n",
      "Epoch 3675, Training loss 2.428638, Validation loss 6.567540\n",
      "Epoch 3676, Training loss 2.428639, Validation loss 6.567540\n",
      "Epoch 3677, Training loss 2.428638, Validation loss 6.567550\n",
      "Epoch 3678, Training loss 2.428639, Validation loss 6.567546\n",
      "Epoch 3679, Training loss 2.428639, Validation loss 6.567546\n",
      "Epoch 3680, Training loss 2.428639, Validation loss 6.567556\n",
      "Epoch 3681, Training loss 2.428638, Validation loss 6.567565\n",
      "Epoch 3682, Training loss 2.428639, Validation loss 6.567575\n",
      "Epoch 3683, Training loss 2.428639, Validation loss 6.567585\n",
      "Epoch 3684, Training loss 2.428638, Validation loss 6.567586\n",
      "Epoch 3685, Training loss 2.428639, Validation loss 6.567595\n",
      "Epoch 3686, Training loss 2.428639, Validation loss 6.567596\n",
      "Epoch 3687, Training loss 2.428638, Validation loss 6.567591\n",
      "Epoch 3688, Training loss 2.428639, Validation loss 6.567611\n",
      "Epoch 3689, Training loss 2.428639, Validation loss 6.567601\n",
      "Epoch 3690, Training loss 2.428640, Validation loss 6.567611\n",
      "Epoch 3691, Training loss 2.428639, Validation loss 6.567611\n",
      "Epoch 3692, Training loss 2.428639, Validation loss 6.567606\n",
      "Epoch 3693, Training loss 2.428639, Validation loss 6.567626\n",
      "Epoch 3694, Training loss 2.428638, Validation loss 6.567616\n",
      "Epoch 3695, Training loss 2.428638, Validation loss 6.567621\n",
      "Epoch 3696, Training loss 2.428638, Validation loss 6.567626\n",
      "Epoch 3697, Training loss 2.428638, Validation loss 6.567632\n",
      "Epoch 3698, Training loss 2.428638, Validation loss 6.567641\n",
      "Epoch 3699, Training loss 2.428639, Validation loss 6.567632\n",
      "Epoch 3700, Training loss 2.428638, Validation loss 6.567636\n",
      "Epoch 3701, Training loss 2.428638, Validation loss 6.567647\n",
      "Epoch 3702, Training loss 2.428639, Validation loss 6.567647\n",
      "Epoch 3703, Training loss 2.428638, Validation loss 6.567657\n",
      "Epoch 3704, Training loss 2.428638, Validation loss 6.567657\n",
      "Epoch 3705, Training loss 2.428639, Validation loss 6.567652\n",
      "Epoch 3706, Training loss 2.428638, Validation loss 6.567662\n",
      "Epoch 3707, Training loss 2.428637, Validation loss 6.567662\n",
      "Epoch 3708, Training loss 2.428638, Validation loss 6.567653\n",
      "Epoch 3709, Training loss 2.428638, Validation loss 6.567673\n",
      "Epoch 3710, Training loss 2.428637, Validation loss 6.567667\n",
      "Epoch 3711, Training loss 2.428639, Validation loss 6.567688\n",
      "Epoch 3712, Training loss 2.428638, Validation loss 6.567677\n",
      "Epoch 3713, Training loss 2.428638, Validation loss 6.567683\n",
      "Epoch 3714, Training loss 2.428638, Validation loss 6.567688\n",
      "Epoch 3715, Training loss 2.428638, Validation loss 6.567683\n",
      "Epoch 3716, Training loss 2.428638, Validation loss 6.567703\n",
      "Epoch 3717, Training loss 2.428639, Validation loss 6.567693\n",
      "Epoch 3718, Training loss 2.428638, Validation loss 6.567703\n",
      "Epoch 3719, Training loss 2.428638, Validation loss 6.567703\n",
      "Epoch 3720, Training loss 2.428638, Validation loss 6.567708\n",
      "Epoch 3721, Training loss 2.428638, Validation loss 6.567698\n",
      "Epoch 3722, Training loss 2.428638, Validation loss 6.567708\n",
      "Epoch 3723, Training loss 2.428638, Validation loss 6.567714\n",
      "Epoch 3724, Training loss 2.428638, Validation loss 6.567719\n",
      "Epoch 3725, Training loss 2.428639, Validation loss 6.567724\n",
      "Epoch 3726, Training loss 2.428637, Validation loss 6.567734\n",
      "Epoch 3727, Training loss 2.428638, Validation loss 6.567734\n",
      "Epoch 3728, Training loss 2.428638, Validation loss 6.567729\n",
      "Epoch 3729, Training loss 2.428638, Validation loss 6.567734\n",
      "Epoch 3730, Training loss 2.428638, Validation loss 6.567739\n",
      "Epoch 3731, Training loss 2.428638, Validation loss 6.567749\n",
      "Epoch 3732, Training loss 2.428638, Validation loss 6.567750\n",
      "Epoch 3733, Training loss 2.428636, Validation loss 6.567744\n",
      "Epoch 3734, Training loss 2.428636, Validation loss 6.567745\n",
      "Epoch 3735, Training loss 2.428637, Validation loss 6.567764\n",
      "Epoch 3736, Training loss 2.428637, Validation loss 6.567775\n",
      "Epoch 3737, Training loss 2.428637, Validation loss 6.567780\n",
      "Epoch 3738, Training loss 2.428638, Validation loss 6.567790\n",
      "Epoch 3739, Training loss 2.428638, Validation loss 6.567794\n",
      "Epoch 3740, Training loss 2.428637, Validation loss 6.567790\n",
      "Epoch 3741, Training loss 2.428637, Validation loss 6.567790\n",
      "Epoch 3742, Training loss 2.428637, Validation loss 6.567785\n",
      "Epoch 3743, Training loss 2.428637, Validation loss 6.567800\n",
      "Epoch 3744, Training loss 2.428638, Validation loss 6.567800\n",
      "Epoch 3745, Training loss 2.428638, Validation loss 6.567815\n",
      "Epoch 3746, Training loss 2.428636, Validation loss 6.567810\n",
      "Epoch 3747, Training loss 2.428636, Validation loss 6.567810\n",
      "Epoch 3748, Training loss 2.428636, Validation loss 6.567805\n",
      "Epoch 3749, Training loss 2.428638, Validation loss 6.567810\n",
      "Epoch 3750, Training loss 2.428638, Validation loss 6.567821\n",
      "Epoch 3751, Training loss 2.428637, Validation loss 6.567821\n",
      "Epoch 3752, Training loss 2.428638, Validation loss 6.567835\n",
      "Epoch 3753, Training loss 2.428638, Validation loss 6.567831\n",
      "Epoch 3754, Training loss 2.428636, Validation loss 6.567831\n",
      "Epoch 3755, Training loss 2.428638, Validation loss 6.567826\n",
      "Epoch 3756, Training loss 2.428637, Validation loss 6.567841\n",
      "Epoch 3757, Training loss 2.428637, Validation loss 6.567841\n",
      "Epoch 3758, Training loss 2.428636, Validation loss 6.567836\n",
      "Epoch 3759, Training loss 2.428636, Validation loss 6.567841\n",
      "Epoch 3760, Training loss 2.428637, Validation loss 6.567851\n",
      "Epoch 3761, Training loss 2.428637, Validation loss 6.567846\n",
      "Epoch 3762, Training loss 2.428637, Validation loss 6.567851\n",
      "Epoch 3763, Training loss 2.428637, Validation loss 6.567861\n",
      "Epoch 3764, Training loss 2.428638, Validation loss 6.567856\n",
      "Epoch 3765, Training loss 2.428638, Validation loss 6.567861\n",
      "Epoch 3766, Training loss 2.428636, Validation loss 6.567871\n",
      "Epoch 3767, Training loss 2.428636, Validation loss 6.567876\n",
      "Epoch 3768, Training loss 2.428637, Validation loss 6.567871\n",
      "Epoch 3769, Training loss 2.428636, Validation loss 6.567882\n",
      "Epoch 3770, Training loss 2.428637, Validation loss 6.567866\n",
      "Epoch 3771, Training loss 2.428636, Validation loss 6.567877\n",
      "Epoch 3772, Training loss 2.428636, Validation loss 6.567882\n",
      "Epoch 3773, Training loss 2.428638, Validation loss 6.567892\n",
      "Epoch 3774, Training loss 2.428636, Validation loss 6.567887\n",
      "Epoch 3775, Training loss 2.428637, Validation loss 6.567892\n",
      "Epoch 3776, Training loss 2.428636, Validation loss 6.567902\n",
      "Epoch 3777, Training loss 2.428636, Validation loss 6.567887\n",
      "Epoch 3778, Training loss 2.428636, Validation loss 6.567902\n",
      "Epoch 3779, Training loss 2.428637, Validation loss 6.567912\n",
      "Epoch 3780, Training loss 2.428636, Validation loss 6.567897\n",
      "Epoch 3781, Training loss 2.428636, Validation loss 6.567912\n",
      "Epoch 3782, Training loss 2.428636, Validation loss 6.567912\n",
      "Epoch 3783, Training loss 2.428636, Validation loss 6.567907\n",
      "Epoch 3784, Training loss 2.428637, Validation loss 6.567923\n",
      "Epoch 3785, Training loss 2.428637, Validation loss 6.567923\n",
      "Epoch 3786, Training loss 2.428636, Validation loss 6.567918\n",
      "Epoch 3787, Training loss 2.428636, Validation loss 6.567933\n",
      "Epoch 3788, Training loss 2.428636, Validation loss 6.567933\n",
      "Epoch 3789, Training loss 2.428635, Validation loss 6.567928\n",
      "Epoch 3790, Training loss 2.428638, Validation loss 6.567933\n",
      "Epoch 3791, Training loss 2.428636, Validation loss 6.567943\n",
      "Epoch 3792, Training loss 2.428636, Validation loss 6.567938\n",
      "Epoch 3793, Training loss 2.428636, Validation loss 6.567938\n",
      "Epoch 3794, Training loss 2.428638, Validation loss 6.567953\n",
      "Epoch 3795, Training loss 2.428636, Validation loss 6.567953\n",
      "Epoch 3796, Training loss 2.428636, Validation loss 6.567948\n",
      "Epoch 3797, Training loss 2.428635, Validation loss 6.567973\n",
      "Epoch 3798, Training loss 2.428636, Validation loss 6.567968\n",
      "Epoch 3799, Training loss 2.428636, Validation loss 6.567973\n",
      "Epoch 3800, Training loss 2.428636, Validation loss 6.567978\n",
      "Epoch 3801, Training loss 2.428635, Validation loss 6.567984\n",
      "Epoch 3802, Training loss 2.428636, Validation loss 6.567978\n",
      "Epoch 3803, Training loss 2.428635, Validation loss 6.567984\n",
      "Epoch 3804, Training loss 2.428636, Validation loss 6.567988\n",
      "Epoch 3805, Training loss 2.428634, Validation loss 6.567994\n",
      "Epoch 3806, Training loss 2.428636, Validation loss 6.567999\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3807, Training loss 2.428637, Validation loss 6.567994\n",
      "Epoch 3808, Training loss 2.428636, Validation loss 6.567999\n",
      "Epoch 3809, Training loss 2.428636, Validation loss 6.568004\n",
      "Epoch 3810, Training loss 2.428636, Validation loss 6.568009\n",
      "Epoch 3811, Training loss 2.428637, Validation loss 6.568004\n",
      "Epoch 3812, Training loss 2.428636, Validation loss 6.568009\n",
      "Epoch 3813, Training loss 2.428636, Validation loss 6.568014\n",
      "Epoch 3814, Training loss 2.428635, Validation loss 6.568019\n",
      "Epoch 3815, Training loss 2.428636, Validation loss 6.568025\n",
      "Epoch 3816, Training loss 2.428636, Validation loss 6.568024\n",
      "Epoch 3817, Training loss 2.428636, Validation loss 6.568029\n",
      "Epoch 3818, Training loss 2.428636, Validation loss 6.568034\n",
      "Epoch 3819, Training loss 2.428634, Validation loss 6.568039\n",
      "Epoch 3820, Training loss 2.428635, Validation loss 6.568034\n",
      "Epoch 3821, Training loss 2.428635, Validation loss 6.568039\n",
      "Epoch 3822, Training loss 2.428635, Validation loss 6.568045\n",
      "Epoch 3823, Training loss 2.428634, Validation loss 6.568049\n",
      "Epoch 3824, Training loss 2.428634, Validation loss 6.568045\n",
      "Epoch 3825, Training loss 2.428635, Validation loss 6.568049\n",
      "Epoch 3826, Training loss 2.428636, Validation loss 6.568055\n",
      "Epoch 3827, Training loss 2.428635, Validation loss 6.568045\n",
      "Epoch 3828, Training loss 2.428636, Validation loss 6.568050\n",
      "Epoch 3829, Training loss 2.428636, Validation loss 6.568055\n",
      "Epoch 3830, Training loss 2.428636, Validation loss 6.568050\n",
      "Epoch 3831, Training loss 2.428636, Validation loss 6.568055\n",
      "Epoch 3832, Training loss 2.428636, Validation loss 6.568060\n",
      "Epoch 3833, Training loss 2.428635, Validation loss 6.568066\n",
      "Epoch 3834, Training loss 2.428634, Validation loss 6.568060\n",
      "Epoch 3835, Training loss 2.428635, Validation loss 6.568066\n",
      "Epoch 3836, Training loss 2.428636, Validation loss 6.568070\n",
      "Epoch 3837, Training loss 2.428636, Validation loss 6.568076\n",
      "Epoch 3838, Training loss 2.428635, Validation loss 6.568081\n",
      "Epoch 3839, Training loss 2.428636, Validation loss 6.568076\n",
      "Epoch 3840, Training loss 2.428635, Validation loss 6.568081\n",
      "Epoch 3841, Training loss 2.428635, Validation loss 6.568086\n",
      "Epoch 3842, Training loss 2.428634, Validation loss 6.568091\n",
      "Epoch 3843, Training loss 2.428635, Validation loss 6.568086\n",
      "Epoch 3844, Training loss 2.428634, Validation loss 6.568091\n",
      "Epoch 3845, Training loss 2.428636, Validation loss 6.568096\n",
      "Epoch 3846, Training loss 2.428635, Validation loss 6.568101\n",
      "Epoch 3847, Training loss 2.428634, Validation loss 6.568107\n",
      "Epoch 3848, Training loss 2.428634, Validation loss 6.568101\n",
      "Epoch 3849, Training loss 2.428634, Validation loss 6.568107\n",
      "Epoch 3850, Training loss 2.428636, Validation loss 6.568111\n",
      "Epoch 3851, Training loss 2.428634, Validation loss 6.568117\n",
      "Epoch 3852, Training loss 2.428635, Validation loss 6.568111\n",
      "Epoch 3853, Training loss 2.428636, Validation loss 6.568121\n",
      "Epoch 3854, Training loss 2.428636, Validation loss 6.568127\n",
      "Epoch 3855, Training loss 2.428634, Validation loss 6.568131\n",
      "Epoch 3856, Training loss 2.428636, Validation loss 6.568137\n",
      "Epoch 3857, Training loss 2.428635, Validation loss 6.568131\n",
      "Epoch 3858, Training loss 2.428636, Validation loss 6.568137\n",
      "Epoch 3859, Training loss 2.428634, Validation loss 6.568142\n",
      "Epoch 3860, Training loss 2.428634, Validation loss 6.568147\n",
      "Epoch 3861, Training loss 2.428635, Validation loss 6.568142\n",
      "Epoch 3862, Training loss 2.428635, Validation loss 6.568147\n",
      "Epoch 3863, Training loss 2.428635, Validation loss 6.568132\n",
      "Epoch 3864, Training loss 2.428635, Validation loss 6.568152\n",
      "Epoch 3865, Training loss 2.428635, Validation loss 6.568157\n",
      "Epoch 3866, Training loss 2.428635, Validation loss 6.568172\n",
      "Epoch 3867, Training loss 2.428635, Validation loss 6.568168\n",
      "Epoch 3868, Training loss 2.428634, Validation loss 6.568168\n",
      "Epoch 3869, Training loss 2.428635, Validation loss 6.568163\n",
      "Epoch 3870, Training loss 2.428636, Validation loss 6.568172\n",
      "Epoch 3871, Training loss 2.428634, Validation loss 6.568168\n",
      "Epoch 3872, Training loss 2.428634, Validation loss 6.568168\n",
      "Epoch 3873, Training loss 2.428634, Validation loss 6.568182\n",
      "Epoch 3874, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3875, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3876, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3877, Training loss 2.428635, Validation loss 6.568173\n",
      "Epoch 3878, Training loss 2.428635, Validation loss 6.568188\n",
      "Epoch 3879, Training loss 2.428635, Validation loss 6.568188\n",
      "Epoch 3880, Training loss 2.428634, Validation loss 6.568188\n",
      "Epoch 3881, Training loss 2.428634, Validation loss 6.568203\n",
      "Epoch 3882, Training loss 2.428634, Validation loss 6.568198\n",
      "Epoch 3883, Training loss 2.428636, Validation loss 6.568198\n",
      "Epoch 3884, Training loss 2.428634, Validation loss 6.568213\n",
      "Epoch 3885, Training loss 2.428635, Validation loss 6.568213\n",
      "Epoch 3886, Training loss 2.428635, Validation loss 6.568209\n",
      "Epoch 3887, Training loss 2.428634, Validation loss 6.568209\n",
      "Epoch 3888, Training loss 2.428634, Validation loss 6.568204\n",
      "Epoch 3889, Training loss 2.428635, Validation loss 6.568223\n",
      "Epoch 3890, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3891, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3892, Training loss 2.428632, Validation loss 6.568223\n",
      "Epoch 3893, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3894, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3895, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3896, Training loss 2.428634, Validation loss 6.568233\n",
      "Epoch 3897, Training loss 2.428634, Validation loss 6.568229\n",
      "Epoch 3898, Training loss 2.428635, Validation loss 6.568229\n",
      "Epoch 3899, Training loss 2.428634, Validation loss 6.568229\n",
      "Epoch 3900, Training loss 2.428634, Validation loss 6.568224\n",
      "Epoch 3901, Training loss 2.428633, Validation loss 6.568239\n",
      "Epoch 3902, Training loss 2.428634, Validation loss 6.568239\n",
      "Epoch 3903, Training loss 2.428634, Validation loss 6.568239\n",
      "Epoch 3904, Training loss 2.428634, Validation loss 6.568254\n",
      "Epoch 3905, Training loss 2.428634, Validation loss 6.568250\n",
      "Epoch 3906, Training loss 2.428634, Validation loss 6.568250\n",
      "Epoch 3907, Training loss 2.428634, Validation loss 6.568245\n",
      "Epoch 3908, Training loss 2.428633, Validation loss 6.568245\n",
      "Epoch 3909, Training loss 2.428634, Validation loss 6.568260\n",
      "Epoch 3910, Training loss 2.428633, Validation loss 6.568260\n",
      "Epoch 3911, Training loss 2.428634, Validation loss 6.568255\n",
      "Epoch 3912, Training loss 2.428633, Validation loss 6.568260\n",
      "Epoch 3913, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3914, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3915, Training loss 2.428634, Validation loss 6.568274\n",
      "Epoch 3916, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3917, Training loss 2.428635, Validation loss 6.568270\n",
      "Epoch 3918, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3919, Training loss 2.428633, Validation loss 6.568265\n",
      "Epoch 3920, Training loss 2.428634, Validation loss 6.568280\n",
      "Epoch 3921, Training loss 2.428633, Validation loss 6.568280\n",
      "Epoch 3922, Training loss 2.428634, Validation loss 6.568280\n",
      "Epoch 3923, Training loss 2.428634, Validation loss 6.568295\n",
      "Epoch 3924, Training loss 2.428634, Validation loss 6.568291\n",
      "Epoch 3925, Training loss 2.428635, Validation loss 6.568291\n",
      "Epoch 3926, Training loss 2.428634, Validation loss 6.568305\n",
      "Epoch 3927, Training loss 2.428634, Validation loss 6.568305\n",
      "Epoch 3928, Training loss 2.428634, Validation loss 6.568300\n",
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      "Epoch 3930, Training loss 2.428633, Validation loss 6.568295\n",
      "Epoch 3931, Training loss 2.428633, Validation loss 6.568311\n",
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      "Epoch 3938, Training loss 2.428633, Validation loss 6.568316\n",
      "Epoch 3939, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3940, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3941, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3942, Training loss 2.428634, Validation loss 6.568316\n",
      "Epoch 3943, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3944, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3945, Training loss 2.428634, Validation loss 6.568341\n",
      "Epoch 3946, Training loss 2.428633, Validation loss 6.568346\n",
      "Epoch 3947, Training loss 2.428632, Validation loss 6.568356\n",
      "Epoch 3948, Training loss 2.428633, Validation loss 6.568361\n",
      "Epoch 3949, Training loss 2.428634, Validation loss 6.568366\n",
      "Epoch 3950, Training loss 2.428634, Validation loss 6.568371\n",
      "Epoch 3951, Training loss 2.428633, Validation loss 6.568361\n",
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      "Epoch 3953, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3954, Training loss 2.428635, Validation loss 6.568371\n",
      "Epoch 3955, Training loss 2.428632, Validation loss 6.568381\n",
      "Epoch 3956, Training loss 2.428633, Validation loss 6.568371\n",
      "Epoch 3957, Training loss 2.428633, Validation loss 6.568377\n",
      "Epoch 3958, Training loss 2.428634, Validation loss 6.568381\n",
      "Epoch 3959, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3960, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3961, Training loss 2.428634, Validation loss 6.568387\n",
      "Epoch 3962, Training loss 2.428633, Validation loss 6.568377\n",
      "Epoch 3963, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3964, Training loss 2.428634, Validation loss 6.568387\n",
      "Epoch 3965, Training loss 2.428633, Validation loss 6.568397\n",
      "Epoch 3966, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3967, Training loss 2.428633, Validation loss 6.568397\n",
      "Epoch 3968, Training loss 2.428633, Validation loss 6.568402\n",
      "Epoch 3969, Training loss 2.428634, Validation loss 6.568397\n",
      "Epoch 3970, Training loss 2.428635, Validation loss 6.568402\n",
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      "Epoch 3973, Training loss 2.428633, Validation loss 6.568402\n",
      "Epoch 3974, Training loss 2.428635, Validation loss 6.568412\n",
      "Epoch 3975, Training loss 2.428634, Validation loss 6.568422\n",
      "Epoch 3976, Training loss 2.428633, Validation loss 6.568412\n",
      "Epoch 3977, Training loss 2.428634, Validation loss 6.568418\n",
      "Epoch 3978, Training loss 2.428633, Validation loss 6.568412\n",
      "Epoch 3979, Training loss 2.428633, Validation loss 6.568418\n",
      "Epoch 3980, Training loss 2.428634, Validation loss 6.568418\n",
      "Epoch 3981, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 3982, Training loss 2.428633, Validation loss 6.568418\n",
      "Epoch 3983, Training loss 2.428634, Validation loss 6.568428\n",
      "Epoch 3984, Training loss 2.428633, Validation loss 6.568418\n",
      "Epoch 3985, Training loss 2.428634, Validation loss 6.568428\n",
      "Epoch 3986, Training loss 2.428633, Validation loss 6.568433\n",
      "Epoch 3987, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 3988, Training loss 2.428633, Validation loss 6.568433\n",
      "Epoch 3989, Training loss 2.428634, Validation loss 6.568433\n",
      "Epoch 3990, Training loss 2.428632, Validation loss 6.568443\n",
      "Epoch 3991, Training loss 2.428634, Validation loss 6.568433\n",
      "Epoch 3992, Training loss 2.428632, Validation loss 6.568443\n",
      "Epoch 3993, Training loss 2.428634, Validation loss 6.568433\n",
      "Epoch 3994, Training loss 2.428631, Validation loss 6.568443\n",
      "Epoch 3995, Training loss 2.428633, Validation loss 6.568443\n",
      "Epoch 3996, Training loss 2.428634, Validation loss 6.568453\n",
      "Epoch 3997, Training loss 2.428633, Validation loss 6.568459\n",
      "Epoch 3998, Training loss 2.428633, Validation loss 6.568453\n",
      "Epoch 3999, Training loss 2.428632, Validation loss 6.568459\n",
      "Epoch 4000, Training loss 2.428633, Validation loss 6.568449\n",
      "Epoch 4001, Training loss 2.428634, Validation loss 6.568459\n",
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      "Epoch 4003, Training loss 2.428633, Validation loss 6.568459\n",
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      "Epoch 4007, Training loss 2.428633, Validation loss 6.568469\n",
      "Epoch 4008, Training loss 2.428634, Validation loss 6.568474\n",
      "Epoch 4009, Training loss 2.428634, Validation loss 6.568464\n",
      "Epoch 4010, Training loss 2.428632, Validation loss 6.568474\n",
      "Epoch 4011, Training loss 2.428634, Validation loss 6.568474\n",
      "Epoch 4012, Training loss 2.428633, Validation loss 6.568484\n",
      "Epoch 4013, Training loss 2.428632, Validation loss 6.568474\n",
      "Epoch 4014, Training loss 2.428632, Validation loss 6.568484\n",
      "Epoch 4015, Training loss 2.428632, Validation loss 6.568489\n",
      "Epoch 4016, Training loss 2.428633, Validation loss 6.568484\n",
      "Epoch 4017, Training loss 2.428632, Validation loss 6.568474\n",
      "Epoch 4018, Training loss 2.428632, Validation loss 6.568480\n",
      "Epoch 4019, Training loss 2.428632, Validation loss 6.568500\n",
      "Epoch 4020, Training loss 2.428634, Validation loss 6.568490\n",
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      "Epoch 4022, Training loss 2.428633, Validation loss 6.568490\n",
      "Epoch 4023, Training loss 2.428632, Validation loss 6.568500\n",
      "Epoch 4024, Training loss 2.428634, Validation loss 6.568490\n",
      "Epoch 4025, Training loss 2.428633, Validation loss 6.568500\n",
      "Epoch 4026, Training loss 2.428633, Validation loss 6.568500\n",
      "Epoch 4027, Training loss 2.428632, Validation loss 6.568505\n",
      "Epoch 4028, Training loss 2.428632, Validation loss 6.568515\n",
      "Epoch 4029, Training loss 2.428632, Validation loss 6.568505\n",
      "Epoch 4030, Training loss 2.428633, Validation loss 6.568515\n",
      "Epoch 4031, Training loss 2.428632, Validation loss 6.568505\n",
      "Epoch 4032, Training loss 2.428633, Validation loss 6.568515\n",
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      "Epoch 4144, Training loss 2.428632, Validation loss 6.568703\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4145, Training loss 2.428632, Validation loss 6.568694\n",
      "Epoch 4146, Training loss 2.428632, Validation loss 6.568698\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4307, Training loss 2.428632, Validation loss 6.568893\n",
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      "Epoch 4332, Training loss 2.428632, Validation loss 6.568948\n",
      "Epoch 4333, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4334, Training loss 2.428630, Validation loss 6.568958\n",
      "Epoch 4335, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4336, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4337, Training loss 2.428632, Validation loss 6.568938\n",
      "Epoch 4338, Training loss 2.428630, Validation loss 6.568943\n",
      "Epoch 4339, Training loss 2.428632, Validation loss 6.568938\n",
      "Epoch 4340, Training loss 2.428630, Validation loss 6.568953\n",
      "Epoch 4341, Training loss 2.428630, Validation loss 6.568938\n",
      "Epoch 4342, Training loss 2.428632, Validation loss 6.568953\n",
      "Epoch 4343, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4344, Training loss 2.428631, Validation loss 6.568949\n",
      "Epoch 4345, Training loss 2.428632, Validation loss 6.568953\n",
      "Epoch 4346, Training loss 2.428632, Validation loss 6.568949\n",
      "Epoch 4347, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4348, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4349, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4350, Training loss 2.428632, Validation loss 6.568953\n",
      "Epoch 4351, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4352, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4353, Training loss 2.428631, Validation loss 6.568949\n",
      "Epoch 4354, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4355, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4356, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4357, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4358, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4359, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4360, Training loss 2.428632, Validation loss 6.568959\n",
      "Epoch 4361, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4362, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4363, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4364, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4365, Training loss 2.428632, Validation loss 6.568959\n",
      "Epoch 4366, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4367, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4368, Training loss 2.428630, Validation loss 6.568974\n",
      "Epoch 4369, Training loss 2.428632, Validation loss 6.568974\n",
      "Epoch 4370, Training loss 2.428632, Validation loss 6.568959\n",
      "Epoch 4371, Training loss 2.428632, Validation loss 6.568974\n",
      "Epoch 4372, Training loss 2.428632, Validation loss 6.568969\n",
      "Epoch 4373, Training loss 2.428630, Validation loss 6.568974\n",
      "Epoch 4374, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4375, Training loss 2.428631, Validation loss 6.568969\n",
      "Epoch 4376, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4377, Training loss 2.428631, Validation loss 6.568969\n",
      "Epoch 4378, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4379, Training loss 2.428631, Validation loss 6.568969\n",
      "Epoch 4380, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4381, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4382, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4383, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4384, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4385, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4386, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4387, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4388, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4389, Training loss 2.428632, Validation loss 6.568999\n",
      "Epoch 4390, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4391, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4392, Training loss 2.428632, Validation loss 6.568994\n",
      "Epoch 4393, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4394, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4395, Training loss 2.428630, Validation loss 6.568994\n",
      "Epoch 4396, Training loss 2.428632, Validation loss 6.568979\n",
      "Epoch 4397, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4398, Training loss 2.428630, Validation loss 6.568990\n",
      "Epoch 4399, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4400, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4401, Training loss 2.428631, Validation loss 6.568990\n",
      "Epoch 4402, Training loss 2.428632, Validation loss 6.568994\n",
      "Epoch 4403, Training loss 2.428632, Validation loss 6.568990\n",
      "Epoch 4404, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4405, Training loss 2.428630, Validation loss 6.568994\n",
      "Epoch 4406, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4407, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4408, Training loss 2.428630, Validation loss 6.568990\n",
      "Epoch 4409, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4410, Training loss 2.428632, Validation loss 6.568990\n",
      "Epoch 4411, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4412, Training loss 2.428630, Validation loss 6.569004\n",
      "Epoch 4413, Training loss 2.428631, Validation loss 6.569004\n",
      "Epoch 4414, Training loss 2.428630, Validation loss 6.569004\n",
      "Epoch 4415, Training loss 2.428631, Validation loss 6.569000\n",
      "Epoch 4416, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4417, Training loss 2.428631, Validation loss 6.569000\n",
      "Epoch 4418, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4419, Training loss 2.428632, Validation loss 6.569004\n",
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      "Epoch 4421, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4422, Training loss 2.428631, Validation loss 6.569000\n",
      "Epoch 4423, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4424, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4425, Training loss 2.428630, Validation loss 6.569015\n",
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      "Epoch 4427, Training loss 2.428631, Validation loss 6.569010\n",
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      "Epoch 4429, Training loss 2.428632, Validation loss 6.569010\n",
      "Epoch 4430, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4431, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4432, Training loss 2.428630, Validation loss 6.569010\n",
      "Epoch 4433, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4434, Training loss 2.428632, Validation loss 6.569010\n",
      "Epoch 4435, Training loss 2.428630, Validation loss 6.569025\n",
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      "Epoch 4437, Training loss 2.428632, Validation loss 6.569010\n",
      "Epoch 4438, Training loss 2.428631, Validation loss 6.569025\n",
      "Epoch 4439, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4440, Training loss 2.428632, Validation loss 6.569025\n",
      "Epoch 4441, Training loss 2.428631, Validation loss 6.569020\n",
      "Epoch 4442, Training loss 2.428631, Validation loss 6.569025\n",
      "Epoch 4443, Training loss 2.428633, Validation loss 6.569025\n",
      "Epoch 4444, Training loss 2.428631, Validation loss 6.569025\n",
      "Epoch 4445, Training loss 2.428630, Validation loss 6.569025\n",
      "Epoch 4446, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4447, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4448, Training loss 2.428631, Validation loss 6.569020\n",
      "Epoch 4449, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4450, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4451, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4452, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4453, Training loss 2.428632, Validation loss 6.569039\n",
      "Epoch 4454, Training loss 2.428631, Validation loss 6.569035\n",
      "Epoch 4455, Training loss 2.428630, Validation loss 6.569030\n",
      "Epoch 4456, Training loss 2.428630, Validation loss 6.569030\n",
      "Epoch 4457, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4458, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4459, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4460, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4461, Training loss 2.428631, Validation loss 6.569045\n",
      "Epoch 4462, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4463, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4464, Training loss 2.428630, Validation loss 6.569045\n",
      "Epoch 4465, Training loss 2.428630, Validation loss 6.569030\n",
      "Epoch 4466, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4467, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4468, Training loss 2.428631, Validation loss 6.569045\n",
      "Epoch 4469, Training loss 2.428630, Validation loss 6.569045\n",
      "Epoch 4470, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4471, Training loss 2.428631, Validation loss 6.569045\n",
      "Epoch 4472, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4473, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4474, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4475, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4476, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4477, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4478, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4479, Training loss 2.428630, Validation loss 6.569040\n",
      "Epoch 4480, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4481, Training loss 2.428632, Validation loss 6.569056\n",
      "Epoch 4482, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4483, Training loss 2.428632, Validation loss 6.569056\n",
      "Epoch 4484, Training loss 2.428631, Validation loss 6.569051\n",
      "Epoch 4485, Training loss 2.428630, Validation loss 6.569056\n",
      "Epoch 4486, Training loss 2.428631, Validation loss 6.569051\n",
      "Epoch 4487, Training loss 2.428631, Validation loss 6.569051\n",
      "Epoch 4488, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4489, Training loss 2.428630, Validation loss 6.569051\n",
      "Epoch 4490, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4491, Training loss 2.428632, Validation loss 6.569051\n",
      "Epoch 4492, Training loss 2.428630, Validation loss 6.569066\n",
      "Epoch 4493, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4494, Training loss 2.428632, Validation loss 6.569051\n",
      "Epoch 4495, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4496, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4497, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4498, Training loss 2.428630, Validation loss 6.569061\n",
      "Epoch 4499, Training loss 2.428632, Validation loss 6.569066\n",
      "Epoch 4500, Training loss 2.428632, Validation loss 6.569066\n",
      "Epoch 4501, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4502, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4503, Training loss 2.428633, Validation loss 6.569061\n",
      "Epoch 4504, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4505, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4506, Training loss 2.428632, Validation loss 6.569076\n",
      "Epoch 4507, Training loss 2.428632, Validation loss 6.569076\n",
      "Epoch 4508, Training loss 2.428632, Validation loss 6.569061\n",
      "Epoch 4509, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4510, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4511, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4512, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4513, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4514, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4515, Training loss 2.428630, Validation loss 6.569071\n",
      "Epoch 4516, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4517, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4518, Training loss 2.428630, Validation loss 6.569086\n",
      "Epoch 4519, Training loss 2.428630, Validation loss 6.569086\n",
      "Epoch 4520, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4521, Training loss 2.428631, Validation loss 6.569086\n",
      "Epoch 4522, Training loss 2.428632, Validation loss 6.569081\n",
      "Epoch 4523, Training loss 2.428631, Validation loss 6.569086\n",
      "Epoch 4524, Training loss 2.428630, Validation loss 6.569081\n",
      "Epoch 4525, Training loss 2.428630, Validation loss 6.569081\n",
      "Epoch 4526, Training loss 2.428631, Validation loss 6.569086\n",
      "Epoch 4527, Training loss 2.428632, Validation loss 6.569081\n",
      "Epoch 4528, Training loss 2.428632, Validation loss 6.569086\n",
      "Epoch 4529, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4530, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4531, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4532, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4533, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4534, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4535, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4536, Training loss 2.428631, Validation loss 6.569092\n",
      "Epoch 4537, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4538, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4539, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4540, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4541, Training loss 2.428632, Validation loss 6.569092\n",
      "Epoch 4542, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4543, Training loss 2.428631, Validation loss 6.569092\n",
      "Epoch 4544, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4545, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4546, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4547, Training loss 2.428632, Validation loss 6.569107\n",
      "Epoch 4548, Training loss 2.428631, Validation loss 6.569092\n",
      "Epoch 4549, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4550, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4551, Training loss 2.428632, Validation loss 6.569092\n",
      "Epoch 4552, Training loss 2.428630, Validation loss 6.569107\n",
      "Epoch 4553, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4554, Training loss 2.428632, Validation loss 6.569107\n",
      "Epoch 4555, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4556, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4557, Training loss 2.428631, Validation loss 6.569107\n",
      "Epoch 4558, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4559, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4560, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4561, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4562, Training loss 2.428630, Validation loss 6.569112\n",
      "Epoch 4563, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4564, Training loss 2.428632, Validation loss 6.569127\n",
      "Epoch 4565, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4566, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4567, Training loss 2.428630, Validation loss 6.569117\n",
      "Epoch 4568, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4569, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4570, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4571, Training loss 2.428630, Validation loss 6.569122\n",
      "Epoch 4572, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4573, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4574, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4575, Training loss 2.428630, Validation loss 6.569132\n",
      "Epoch 4576, Training loss 2.428631, Validation loss 6.569141\n",
      "Epoch 4577, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4578, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4579, Training loss 2.428632, Validation loss 6.569122\n",
      "Epoch 4580, Training loss 2.428631, Validation loss 6.569132\n",
      "Epoch 4581, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4582, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4583, Training loss 2.428631, Validation loss 6.569141\n",
      "Epoch 4584, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4585, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4586, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4587, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4588, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4589, Training loss 2.428631, Validation loss 6.569141\n",
      "Epoch 4590, Training loss 2.428632, Validation loss 6.569147\n",
      "Epoch 4591, Training loss 2.428632, Validation loss 6.569137\n",
      "Epoch 4592, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4593, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4594, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4595, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4596, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4597, Training loss 2.428631, Validation loss 6.569137\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4598, Training loss 2.428632, Validation loss 6.569142\n",
      "Epoch 4599, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4600, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4601, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4602, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4603, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4604, Training loss 2.428632, Validation loss 6.569157\n",
      "Epoch 4605, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4606, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4607, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4608, Training loss 2.428630, Validation loss 6.569157\n",
      "Epoch 4609, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4610, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4611, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4612, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4613, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4614, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4615, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4616, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4617, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4618, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4619, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4620, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4621, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4622, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4623, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4624, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4625, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4626, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4627, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4628, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4629, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4630, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4631, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4632, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4633, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4634, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4635, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4636, Training loss 2.428630, Validation loss 6.569152\n",
      "Epoch 4637, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4638, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4639, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4640, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4641, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4642, Training loss 2.428630, Validation loss 6.569152\n",
      "Epoch 4643, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4644, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4645, Training loss 2.428632, Validation loss 6.569172\n",
      "Epoch 4646, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4647, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4648, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4649, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4650, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4651, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4652, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4653, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4654, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4655, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4656, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4657, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4658, Training loss 2.428632, Validation loss 6.569167\n",
      "Epoch 4659, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4660, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4661, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4662, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4663, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4664, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4665, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4666, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4667, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4668, Training loss 2.428631, Validation loss 6.569173\n",
      "Epoch 4669, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4670, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4671, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4672, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4673, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4674, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4675, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4676, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4677, Training loss 2.428632, Validation loss 6.569182\n",
      "Epoch 4678, Training loss 2.428632, Validation loss 6.569173\n",
      "Epoch 4679, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4680, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4681, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4682, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4683, Training loss 2.428632, Validation loss 6.569182\n",
      "Epoch 4684, Training loss 2.428632, Validation loss 6.569173\n",
      "Epoch 4685, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4686, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4687, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4688, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4689, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4690, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4691, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4692, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4693, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4694, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4695, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4696, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4697, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4698, Training loss 2.428632, Validation loss 6.569183\n",
      "Epoch 4699, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4700, Training loss 2.428630, Validation loss 6.569188\n",
      "Epoch 4701, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4702, Training loss 2.428630, Validation loss 6.569183\n",
      "Epoch 4703, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4704, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4705, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4706, Training loss 2.428632, Validation loss 6.569183\n",
      "Epoch 4707, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4708, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4709, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4710, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4711, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4712, Training loss 2.428630, Validation loss 6.569183\n",
      "Epoch 4713, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4714, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4715, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4716, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4717, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4718, Training loss 2.428631, Validation loss 6.569198\n",
      "Epoch 4719, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4720, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4721, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4722, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4723, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4724, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4725, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4726, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4727, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4728, Training loss 2.428630, Validation loss 6.569198\n",
      "Epoch 4729, Training loss 2.428630, Validation loss 6.569188\n",
      "Epoch 4730, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4731, Training loss 2.428632, Validation loss 6.569203\n",
      "Epoch 4732, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4733, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4734, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4735, Training loss 2.428632, Validation loss 6.569203\n",
      "Epoch 4736, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4737, Training loss 2.428632, Validation loss 6.569199\n",
      "Epoch 4738, Training loss 2.428630, Validation loss 6.569198\n",
      "Epoch 4739, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4740, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4741, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4742, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4743, Training loss 2.428632, Validation loss 6.569203\n",
      "Epoch 4744, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4745, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4746, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4747, Training loss 2.428631, Validation loss 6.569199\n",
      "Epoch 4748, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4749, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4750, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4751, Training loss 2.428631, Validation loss 6.569199\n",
      "Epoch 4752, Training loss 2.428632, Validation loss 6.569208\n",
      "Epoch 4753, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4754, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4755, Training loss 2.428630, Validation loss 6.569213\n",
      "Epoch 4756, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4757, Training loss 2.428630, Validation loss 6.569199\n",
      "Epoch 4758, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4759, Training loss 2.428630, Validation loss 6.569194\n",
      "Epoch 4760, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4761, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4762, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4763, Training loss 2.428631, Validation loss 6.569199\n",
      "Epoch 4764, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4765, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4766, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4767, Training loss 2.428631, Validation loss 6.569209\n",
      "Epoch 4768, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4769, Training loss 2.428630, Validation loss 6.569213\n",
      "Epoch 4770, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4771, Training loss 2.428631, Validation loss 6.569209\n",
      "Epoch 4772, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4773, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4774, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4775, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4776, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4777, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4778, Training loss 2.428632, Validation loss 6.569214\n",
      "Epoch 4779, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4780, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4781, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4782, Training loss 2.428631, Validation loss 6.569214\n",
      "Epoch 4783, Training loss 2.428630, Validation loss 6.569223\n",
      "Epoch 4784, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4785, Training loss 2.428632, Validation loss 6.569209\n",
      "Epoch 4786, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4787, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4788, Training loss 2.428631, Validation loss 6.569214\n",
      "Epoch 4789, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4790, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4791, Training loss 2.428631, Validation loss 6.569209\n",
      "Epoch 4792, Training loss 2.428632, Validation loss 6.569214\n",
      "Epoch 4793, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4794, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4795, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4796, Training loss 2.428630, Validation loss 6.569214\n",
      "Epoch 4797, Training loss 2.428632, Validation loss 6.569223\n",
      "Epoch 4798, Training loss 2.428632, Validation loss 6.569214\n",
      "Epoch 4799, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4800, Training loss 2.428632, Validation loss 6.569229\n",
      "Epoch 4801, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4802, Training loss 2.428631, Validation loss 6.569214\n",
      "Epoch 4803, Training loss 2.428630, Validation loss 6.569223\n",
      "Epoch 4804, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4805, Training loss 2.428631, Validation loss 6.569219\n",
      "Epoch 4806, Training loss 2.428632, Validation loss 6.569224\n",
      "Epoch 4807, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4808, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4809, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4810, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4811, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4812, Training loss 2.428632, Validation loss 6.569224\n",
      "Epoch 4813, Training loss 2.428631, Validation loss 6.569219\n",
      "Epoch 4814, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4815, Training loss 2.428631, Validation loss 6.569219\n",
      "Epoch 4816, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4817, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4818, Training loss 2.428630, Validation loss 6.569224\n",
      "Epoch 4819, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4820, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4821, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4822, Training loss 2.428630, Validation loss 6.569224\n",
      "Epoch 4823, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4824, Training loss 2.428632, Validation loss 6.569239\n",
      "Epoch 4825, Training loss 2.428632, Validation loss 6.569229\n",
      "Epoch 4826, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4827, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4828, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4829, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4830, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4831, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4832, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4833, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4834, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4835, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4836, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4837, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4838, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4839, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4840, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4841, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4842, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4843, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4844, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4845, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4846, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4847, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4848, Training loss 2.428630, Validation loss 6.569239\n",
      "Epoch 4849, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4850, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4851, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4852, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4853, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4854, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4855, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4856, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4857, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4858, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4859, Training loss 2.428632, Validation loss 6.569244\n",
      "Epoch 4860, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4861, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4862, Training loss 2.428631, Validation loss 6.569249\n",
      "Epoch 4863, Training loss 2.428630, Validation loss 6.569254\n",
      "Epoch 4864, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4865, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4866, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4867, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4868, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4869, Training loss 2.428631, Validation loss 6.569254\n",
      "Epoch 4870, Training loss 2.428630, Validation loss 6.569249\n",
      "Epoch 4871, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4872, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4873, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4874, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4875, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4876, Training loss 2.428630, Validation loss 6.569249\n",
      "Epoch 4877, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4878, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4879, Training loss 2.428632, Validation loss 6.569254\n",
      "Epoch 4880, Training loss 2.428632, Validation loss 6.569244\n",
      "Epoch 4881, Training loss 2.428632, Validation loss 6.569250\n",
      "Epoch 4882, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4883, Training loss 2.428630, Validation loss 6.569254\n",
      "Epoch 4884, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4885, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4886, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4887, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4888, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4889, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4890, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4891, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4892, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4893, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4894, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4895, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4896, Training loss 2.428629, Validation loss 6.569255\n",
      "Epoch 4897, Training loss 2.428629, Validation loss 6.569245\n",
      "Epoch 4898, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4899, Training loss 2.428632, Validation loss 6.569260\n",
      "Epoch 4900, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4901, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4902, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4903, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4904, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4905, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4906, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4907, Training loss 2.428632, Validation loss 6.569264\n",
      "Epoch 4908, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4909, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4910, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4911, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4912, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4913, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4914, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4915, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4916, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4917, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4918, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4919, Training loss 2.428632, Validation loss 6.569260\n",
      "Epoch 4920, Training loss 2.428632, Validation loss 6.569265\n",
      "Epoch 4921, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4922, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4923, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4924, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4925, Training loss 2.428632, Validation loss 6.569275\n",
      "Epoch 4926, Training loss 2.428632, Validation loss 6.569265\n",
      "Epoch 4927, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4928, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4929, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4930, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4931, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4932, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4933, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4934, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4935, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4936, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4937, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4938, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4939, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4940, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4941, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4942, Training loss 2.428630, Validation loss 6.569280\n",
      "Epoch 4943, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4944, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4945, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4946, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4947, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4948, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4949, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4950, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4951, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4952, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4953, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4954, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4955, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4956, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4957, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4958, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4959, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4960, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4961, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4962, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4963, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4964, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4965, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4966, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4967, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4968, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4969, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4970, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4971, Training loss 2.428630, Validation loss 6.569281\n",
      "Epoch 4972, Training loss 2.428632, Validation loss 6.569285\n",
      "Epoch 4973, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4974, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4975, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4976, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4977, Training loss 2.428630, Validation loss 6.569295\n",
      "Epoch 4978, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4979, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4980, Training loss 2.428632, Validation loss 6.569290\n",
      "Epoch 4981, Training loss 2.428632, Validation loss 6.569281\n",
      "Epoch 4982, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4983, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4984, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4985, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4986, Training loss 2.428632, Validation loss 6.569290\n",
      "Epoch 4987, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4988, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4989, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4990, Training loss 2.428630, Validation loss 6.569300\n",
      "Epoch 4991, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4992, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4993, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4994, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4995, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4996, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 4997, Training loss 2.428630, Validation loss 6.569295\n",
      "Epoch 4998, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4999, Training loss 2.428632, Validation loss 6.569291\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([  5.4878, -17.4613], requires_grad=True)"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def model(t_u, w, b):\n",
    "    return w * t_u + b\n",
    "\n",
    "def loss_fn(t_p, t_c):\n",
    "    sq_diffs = (t_p - t_c)**2\n",
    "    return sq_diffs.mean()\n",
    "\n",
    "params = torch.tensor([1.0, 0.0], requires_grad=True)\n",
    "\n",
    "nepochs = 5000\n",
    "learning_rate = 1e-2\n",
    "\n",
    "optimizer = optim.SGD([params], lr=learning_rate)\n",
    "\n",
    "t_un_train = 0.1 * t_u_train\n",
    "t_un_val = 0.1 * t_u_val\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    \n",
    "    # forward pass\n",
    "    t_p_train = model(t_un_train, *params)\n",
    "    loss_train = loss_fn(t_p_train, t_c_train)\n",
    "\n",
    "    t_p_val = model(t_un_val, *params)\n",
    "    loss_val = loss_fn(t_p_val, t_c_val)\n",
    "\n",
    "    print('Epoch %d, Training loss %f, Validation loss %f' % (epoch, float(loss_train), float(loss_val)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss_train.backward()    \n",
    "    optimizer.step()\n",
    "\n",
    "t_p = model(t_un, *params)\n",
    "\n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Training loss 2.428631, Validation loss 6.569300\n",
      "Epoch 1, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 2, Training loss 2.428630, Validation loss 6.569296\n",
      "Epoch 3, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4, Training loss 2.428630, Validation loss 6.569281\n",
      "Epoch 5, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 6, Training loss 2.428632, Validation loss 6.569296\n",
      "Epoch 7, Training loss 2.428631, Validation loss 6.569305\n",
      "Epoch 8, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 9, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 10, Training loss 2.428630, Validation loss 6.569296\n",
      "Epoch 11, Training loss 2.428631, Validation loss 6.569286\n",
      "Epoch 12, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 13, Training loss 2.428631, Validation loss 6.569301\n",
      "Epoch 14, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 15, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 16, Training loss 2.428630, Validation loss 6.569296\n",
      "Epoch 17, Training loss 2.428631, Validation loss 6.569301\n",
      "Epoch 18, Training loss 2.428632, Validation loss 6.569310\n",
      "Epoch 19, Training loss 2.428632, Validation loss 6.569301\n",
      "Epoch 20, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 21, Training loss 2.428631, Validation loss 6.569305\n",
      "Epoch 22, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 23, Training loss 2.428630, Validation loss 6.569301\n",
      "Epoch 24, Training loss 2.428631, Validation loss 6.569310\n",
      "Epoch 25, Training loss 2.428632, Validation loss 6.569305\n",
      "Epoch 26, Training loss 2.428632, Validation loss 6.569296\n",
      "Epoch 27, Training loss 2.428631, Validation loss 6.569301\n",
      "Epoch 28, Training loss 2.428631, Validation loss 6.569310\n",
      "Epoch 29, Training loss 2.428631, Validation loss 6.569301\n",
      "Epoch 30, Training loss 2.428630, Validation loss 6.569306\n",
      "Epoch 31, Training loss 2.428630, Validation loss 6.569316\n",
      "Epoch 32, Training loss 2.428630, Validation loss 6.569306\n",
      "Epoch 33, Training loss 2.428631, Validation loss 6.569301\n",
      "Epoch 34, Training loss 2.428631, Validation loss 6.569306\n",
      "Epoch 35, Training loss 2.428631, Validation loss 6.569316\n",
      "Epoch 36, Training loss 2.428631, Validation loss 6.569306\n",
      "Epoch 37, Training loss 2.428632, Validation loss 6.569311\n",
      "Epoch 38, Training loss 2.428631, Validation loss 6.569310\n",
      "Epoch 39, Training loss 2.428631, Validation loss 6.569301\n",
      "Epoch 40, Training loss 2.428631, Validation loss 6.569316\n",
      "Epoch 41, Training loss 2.428631, Validation loss 6.569306\n",
      "Epoch 42, Training loss 2.428631, Validation loss 6.569311\n",
      "Epoch 43, Training loss 2.428630, Validation loss 6.569321\n",
      "Epoch 44, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 45, Training loss 2.428631, Validation loss 6.569316\n",
      "Epoch 46, Training loss 2.428631, Validation loss 6.569306\n",
      "Epoch 47, Training loss 2.428631, Validation loss 6.569325\n",
      "Epoch 48, Training loss 2.428631, Validation loss 6.569316\n",
      "Epoch 49, Training loss 2.428632, Validation loss 6.569331\n",
      "Epoch 50, Training loss 2.428632, Validation loss 6.569321\n",
      "Epoch 51, Training loss 2.428632, Validation loss 6.569311\n",
      "Epoch 52, Training loss 2.428631, Validation loss 6.569326\n",
      "Epoch 53, Training loss 2.428631, Validation loss 6.569316\n",
      "Epoch 54, Training loss 2.428631, Validation loss 6.569325\n",
      "Epoch 55, Training loss 2.428631, Validation loss 6.569316\n",
      "Epoch 56, Training loss 2.428631, Validation loss 6.569306\n",
      "Epoch 57, Training loss 2.428631, Validation loss 6.569321\n",
      "Epoch 58, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 59, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 60, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 61, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 62, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 63, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 64, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 65, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 66, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 67, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 68, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 69, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 70, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 71, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 72, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 73, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 74, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 75, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 76, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 77, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 78, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 79, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 80, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 81, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 82, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 83, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 84, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 85, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 86, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 87, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 88, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 89, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 90, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 91, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 92, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 93, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 94, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 95, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 96, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 97, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 98, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 99, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 100, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 101, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 102, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 103, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 104, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 105, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 106, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 107, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 108, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 109, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 110, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 111, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 112, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 113, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 114, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 115, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 116, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 117, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 118, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 119, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 120, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 121, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 122, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 123, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 124, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 125, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 126, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 127, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 128, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 129, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 130, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 131, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 132, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 133, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 134, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 135, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 136, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 137, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 138, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 139, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 140, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 141, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 142, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 143, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 144, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 145, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 146, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 147, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 148, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 149, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 150, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 151, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 152, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 153, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 154, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 155, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 156, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 157, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 158, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 159, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 160, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 161, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 162, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 163, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 164, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 165, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 166, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 167, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 168, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 169, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 170, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 171, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 172, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 173, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 174, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 175, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 176, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 177, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 178, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 179, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 180, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 181, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 182, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 183, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 184, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 185, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 186, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 187, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 188, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 189, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 190, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 191, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 192, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 193, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 194, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 195, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 196, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 197, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 198, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 199, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 200, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 201, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 202, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 203, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 204, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 205, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 206, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 207, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 208, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 209, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 210, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 211, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 212, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 213, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 214, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 215, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 216, Training loss 2.428630, Validation loss 6.569311\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 373, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 675, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 700, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 707, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 720, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 722, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 723, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 724, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 725, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 726, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 727, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 728, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 729, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 730, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 731, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 732, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 733, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 734, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 735, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 736, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 737, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 738, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 739, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 740, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 741, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 742, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 743, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 744, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 745, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 746, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 747, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 748, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 749, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 750, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 751, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 752, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 753, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 754, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 755, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 756, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 757, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 758, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 759, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 760, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 761, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 762, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 763, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 764, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 765, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 766, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 767, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 768, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 769, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 770, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 771, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 772, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 773, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 774, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 775, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 776, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 777, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 778, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 779, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 780, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 781, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 782, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 783, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 784, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 785, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 786, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 787, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 788, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 791, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 792, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 793, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 794, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 796, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 798, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 800, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 801, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 802, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 820, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 829, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1080, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1084, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1087, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1088, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1089, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1090, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1091, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1092, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1093, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1094, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1095, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1096, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1097, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1098, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1099, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1100, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1101, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1109, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1110, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1111, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1118, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1119, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1120, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1121, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1123, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1124, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1125, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1128, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1129, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1430, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1451, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1453, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1477, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1478, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1479, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1480, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1481, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1482, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1483, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1484, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1485, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1486, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1487, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1488, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1489, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1490, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1491, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1492, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1493, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1495, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1500, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1729, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1818, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1819, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 1820, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1830, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1840, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1848, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 1851, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 2158, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2159, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 2552, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2553, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 2554, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 2814, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2815, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 2816, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3000, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3001, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3002, Training loss 2.428630, Validation loss 6.569311\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3190, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3310, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3311, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3313, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3314, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3407, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3408, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3409, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3410, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3411, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3412, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3413, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3414, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3415, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3416, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3417, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3418, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3419, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3420, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3421, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3422, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3423, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3424, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3425, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3426, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3427, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3429, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3430, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3431, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3432, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3438, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3439, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3440, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3441, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3442, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3450, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3451, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3452, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3456, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3458, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3459, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3460, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3461, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3462, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3528, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3529, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3530, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3531, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3532, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3533, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3534, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3535, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3536, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3537, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3538, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3539, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3540, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3541, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3542, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3543, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3544, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3545, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3546, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3547, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3548, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3549, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3550, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3551, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3552, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3553, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3554, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3555, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3556, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3557, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3558, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3559, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3560, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3561, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3562, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3563, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3564, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3565, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3566, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3567, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3568, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3569, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3570, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3571, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3572, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3573, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3574, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3575, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3576, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3577, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3578, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3579, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3580, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3581, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3582, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3583, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3584, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3585, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3586, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3587, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3588, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3589, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3590, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3591, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3592, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3593, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3594, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3595, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3596, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3597, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3598, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3599, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3600, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3601, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3602, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3603, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3604, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3605, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3606, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3607, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3608, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3609, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3610, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3611, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3612, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3613, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3614, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3615, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3616, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3617, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3618, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3619, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3620, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3621, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3622, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3623, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3624, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3625, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3626, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3627, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3628, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3629, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3630, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3631, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3632, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3633, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3634, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3635, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3636, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3637, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3638, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3639, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3640, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3641, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3642, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3643, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3644, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3645, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3646, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3647, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3648, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3649, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3650, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3651, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3652, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3653, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3654, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3655, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3656, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3657, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3658, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3659, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3660, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3661, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3662, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3663, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3664, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3665, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3666, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3667, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3668, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3669, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3670, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3671, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3672, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3673, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3674, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3675, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3676, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3677, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3678, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3679, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3680, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3681, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3682, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3683, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3684, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3685, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3686, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3687, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3688, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3689, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3690, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3691, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3692, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3693, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3694, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3695, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3696, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3697, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3698, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3699, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3700, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3701, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3702, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3703, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3704, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3705, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3706, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3707, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3708, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3709, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3710, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3711, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3712, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3713, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3714, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3715, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3716, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3717, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3718, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3719, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3720, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3721, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3722, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3723, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3724, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3725, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3726, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3727, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3728, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3729, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3730, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3731, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3732, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3733, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3734, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3735, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3736, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3737, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3738, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3739, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3740, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3741, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3742, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3743, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3744, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3745, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3746, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3747, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3748, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3749, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3750, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3751, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3752, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3753, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3754, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3755, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3756, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3757, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3758, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3759, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3760, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3761, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3762, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3763, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3764, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3765, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3766, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3767, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3768, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3769, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3770, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3771, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3772, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3773, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3774, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3775, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3776, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3777, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3778, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3779, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3780, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3781, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3782, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3783, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3784, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3785, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3786, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3787, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3788, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3789, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3790, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3791, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3792, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3793, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3794, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3795, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3796, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3797, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3798, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3799, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3800, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3801, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3802, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3803, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3804, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3805, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3806, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3807, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3808, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3809, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3810, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3811, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3812, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3813, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3814, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3815, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3816, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3817, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3818, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3819, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3820, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3821, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3822, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3823, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3824, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3825, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3826, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3827, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3828, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3829, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3830, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3843, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3844, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3845, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3846, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3847, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3848, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3849, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 3850, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 3855, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4128, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4290, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4291, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4292, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4299, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4301, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4313, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4314, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4321, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4323, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4325, Training loss 2.428630, Validation loss 6.569311\n",
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      "Epoch 4427, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4428, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4429, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4430, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4431, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4432, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4433, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4434, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4435, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4436, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4437, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4438, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4439, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4440, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4441, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4442, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4443, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4444, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4445, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4446, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4447, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4448, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4449, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4450, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4451, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4452, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4453, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4454, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4455, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4456, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4457, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4458, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4459, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4460, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4461, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4462, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4463, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4464, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4465, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4466, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4467, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4468, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4469, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4470, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4471, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4472, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4473, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4474, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4475, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4476, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4477, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4478, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4479, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4480, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4481, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4482, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4483, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4484, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4485, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4486, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4487, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4488, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4489, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4490, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4491, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4492, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4493, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4494, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4495, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4496, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4497, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4498, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4499, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4500, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4501, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4502, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4503, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4504, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4505, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4506, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4507, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4508, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4509, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4510, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4511, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4512, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4513, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4514, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4515, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4516, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4517, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4518, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4519, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4520, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4521, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4522, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4523, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4524, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4525, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4526, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4527, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4528, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4529, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4530, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4531, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4532, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4533, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4534, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4535, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4536, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4537, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4538, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4539, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4540, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4541, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4542, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4543, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4544, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4545, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4546, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4547, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4548, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4549, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4550, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4551, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4552, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4553, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4554, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4555, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4556, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4557, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4558, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4559, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4560, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4561, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4562, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4563, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4564, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4565, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4566, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4567, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4568, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4569, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4570, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4571, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4572, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4573, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4574, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4575, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4576, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4577, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4578, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4579, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4580, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4581, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4582, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4583, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4584, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4585, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4586, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4587, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4588, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4589, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4590, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4591, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4592, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4593, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4594, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4595, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4596, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4597, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4598, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4599, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4600, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4601, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4602, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4603, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4604, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4605, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4606, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4607, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4608, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4609, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4610, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4611, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4612, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4613, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4614, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4615, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4616, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4617, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4618, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4619, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4620, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4621, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4622, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4623, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4624, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4625, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4626, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4627, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4628, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4629, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4630, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4631, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4632, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4633, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4634, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4635, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4636, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4637, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4638, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4639, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4640, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4641, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4642, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4643, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4644, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4645, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4646, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4647, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4648, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4649, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4650, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4651, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4652, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4653, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4654, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4655, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4656, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4657, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4658, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4659, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4660, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4661, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4662, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4663, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4664, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4665, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4666, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4667, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4668, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4669, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4670, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4671, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4672, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4673, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4674, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4675, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4676, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4677, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4678, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4679, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4680, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4681, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4682, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4683, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4684, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4685, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4686, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4687, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4688, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4689, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4690, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4691, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4692, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4693, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4694, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4695, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4696, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4697, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4698, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4699, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4700, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4701, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4702, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4703, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4704, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4705, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4706, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4707, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4708, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4709, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4710, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4711, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4712, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4713, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4714, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4715, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4716, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4717, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4718, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4719, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4720, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4721, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4722, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4723, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4724, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4725, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4726, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4727, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4728, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4729, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4730, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4731, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4732, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4733, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4734, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4735, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4736, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4737, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4738, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4739, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4740, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4741, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4742, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4743, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4744, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4745, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4746, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4747, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4748, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4749, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4750, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4751, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4752, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4753, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4754, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4755, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4756, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4757, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4758, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4759, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4760, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4761, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4762, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4763, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4764, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4765, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4766, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4767, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4768, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4769, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4770, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4771, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4772, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4773, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4774, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4775, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4776, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4777, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4778, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4779, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4780, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4781, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4782, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4783, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4784, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4785, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4786, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4787, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4788, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4789, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4790, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4791, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4792, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4793, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4794, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4795, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4796, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4797, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4798, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4799, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4800, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4801, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4802, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4803, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4804, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4805, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4806, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4807, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4808, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4809, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4810, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4811, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4812, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4813, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4814, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4815, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4816, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4817, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4818, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4819, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4820, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4821, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4822, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4823, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4824, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4825, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4826, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4827, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4828, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4829, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4830, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4831, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4832, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4833, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4834, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4835, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4836, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4837, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4838, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4839, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4840, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4841, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4842, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4843, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4844, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4845, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4846, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4847, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4848, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4849, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4850, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4851, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4852, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4853, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4854, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4855, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4856, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4857, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4858, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4859, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4860, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4861, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4862, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4863, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4864, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4865, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4866, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4867, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4868, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4869, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4870, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4871, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4872, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4873, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4874, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4875, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4876, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4877, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4878, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4879, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4880, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4881, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4882, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4883, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4884, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4885, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4886, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4887, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4888, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4889, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4890, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4891, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4892, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4893, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4894, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4895, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4896, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4897, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4898, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4899, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4900, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4901, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4902, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4903, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4904, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4905, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4906, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4907, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4908, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4909, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4910, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4911, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4912, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4913, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4914, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4915, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4916, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4917, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4918, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4919, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4920, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4921, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4922, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4923, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4924, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4925, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4926, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4927, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4928, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4929, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4930, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4931, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4932, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4933, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4934, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4935, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4936, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4937, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4938, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4939, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4940, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4941, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4942, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4943, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4944, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4945, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4946, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4947, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4948, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4949, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4950, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4951, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4952, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4953, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4954, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4955, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4956, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4957, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4958, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4959, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4960, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4961, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4962, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4963, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4964, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4965, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4966, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4967, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4968, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4969, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4970, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4971, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4972, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4973, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4974, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4975, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4976, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4977, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4978, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4979, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4980, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4981, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4982, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4983, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4984, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4985, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4986, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4987, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4988, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4989, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4990, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4991, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4992, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4993, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4994, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4995, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4996, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4997, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4998, Training loss 2.428630, Validation loss 6.569311\n",
      "Epoch 4999, Training loss 2.428630, Validation loss 6.569311\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(nepochs):\n",
    "    \n",
    "    # forward pass\n",
    "    t_p_train = model(t_un_train, *params)\n",
    "    loss_train = loss_fn(t_p_train, t_c_train)\n",
    "\n",
    "    with torch.no_grad():\n",
    "        t_p_val = model(t_un_val, *params)\n",
    "        loss_val = loss_fn(t_p_val, t_c_val)\n",
    "\n",
    "    print('Epoch %d, Training loss %f, Validation loss %f' % (epoch, float(loss_train), float(loss_val)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss_train.backward()    \n",
    "    optimizer.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
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     ]
    }
   ],
   "source": [
    "for epoch in range(nepochs):\n",
    "    # ...\n",
    "    print(loss_val.requires_grad)  # prints False\n",
    "    # ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "def forward(t_u, t_c, is_train):\n",
    "    with torch.set_grad_enabled(is_train):\n",
    "        t_p = model(t_u, *params)\n",
    "        loss = loss_fn(t_p, t_c)\n",
    "    return loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "model = nn.Linear(1, 1) # We'll look into the arguments in a minute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'x' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-111-f45d190d8a2e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# DON'T DO THIS\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m          \u001b[0;31m# DO THIS\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'x' is not defined"
     ]
    }
   ],
   "source": [
    "y = model.forward(x)  # DON'T DO THIS\n",
    "y = model(x)          # DO THIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Parameter containing:\n",
       "tensor([[0.8208]], requires_grad=True)"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.7944], grad_fn=<AddBackward0>)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.ones(1)\n",
    "\n",
    "model(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944],\n",
       "        [0.7944]], grad_fn=<ThAddmmBackward>)"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.ones(10, 1)\n",
    "\n",
    "model(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_u = torch.unsqueeze(t_u, 1)\n",
    "t_c = torch.unsqueeze(t_c, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = nn.Linear(1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<generator object Module.parameters at 0x116081f10>"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.parameters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Parameter containing:\n",
       " tensor([[-0.6506]], requires_grad=True), Parameter containing:\n",
       " tensor([0.7924], requires_grad=True)]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(model.parameters())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = nn.Linear(1, 1)\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "optimizer = optim.SGD(model.parameters(), lr=learning_rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_u_train = t_u[train_indices]\n",
    "t_c_train = t_c[train_indices]\n",
    "\n",
    "t_u_val = t_u[val_indices]\n",
    "t_c_val = t_c[val_indices]\n",
    "\n",
    "t_un_train = 0.1 * t_u_train\n",
    "t_un_val = 0.1 * t_u_val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Training loss 377.888733, Validation loss 340.187164\n",
      "Epoch 1, Training loss 93.240906, Validation loss 43.281433\n",
      "Epoch 2, Training loss 44.177326, Validation loss 2.966456\n",
      "Epoch 3, Training loss 35.631279, Validation loss 0.495764\n",
      "Epoch 4, Training loss 34.054108, Validation loss 1.925004\n",
      "Epoch 5, Training loss 33.675919, Validation loss 2.942267\n",
      "Epoch 6, Training loss 33.504379, Validation loss 3.439312\n",
      "Epoch 7, Training loss 33.368816, Validation loss 3.660394\n",
      "Epoch 8, Training loss 33.239883, Validation loss 3.756605\n",
      "Epoch 9, Training loss 33.112530, Validation loss 3.799221\n",
      "Epoch 10, Training loss 32.985870, Validation loss 3.819282\n",
      "Epoch 11, Training loss 32.859776, Validation loss 3.829930\n",
      "Epoch 12, Training loss 32.734207, Validation loss 3.836667\n",
      "Epoch 13, Training loss 32.609146, Validation loss 3.841775\n",
      "Epoch 14, Training loss 32.484612, Validation loss 3.846200\n",
      "Epoch 15, Training loss 32.360588, Validation loss 3.850352\n",
      "Epoch 16, Training loss 32.237076, Validation loss 3.854382\n",
      "Epoch 17, Training loss 32.114067, Validation loss 3.858366\n",
      "Epoch 18, Training loss 31.991577, Validation loss 3.862327\n",
      "Epoch 19, Training loss 31.869585, Validation loss 3.866277\n",
      "Epoch 20, Training loss 31.748100, Validation loss 3.870224\n",
      "Epoch 21, Training loss 31.627115, Validation loss 3.874163\n",
      "Epoch 22, Training loss 31.506630, Validation loss 3.878105\n",
      "Epoch 23, Training loss 31.386641, Validation loss 3.882041\n",
      "Epoch 24, Training loss 31.267151, Validation loss 3.885976\n",
      "Epoch 25, Training loss 31.148149, Validation loss 3.889915\n",
      "Epoch 26, Training loss 31.029636, Validation loss 3.893846\n",
      "Epoch 27, Training loss 30.911612, Validation loss 3.897779\n",
      "Epoch 28, Training loss 30.794085, Validation loss 3.901713\n",
      "Epoch 29, Training loss 30.677040, Validation loss 3.905640\n",
      "Epoch 30, Training loss 30.560465, Validation loss 3.909571\n",
      "Epoch 31, Training loss 30.444387, Validation loss 3.913491\n",
      "Epoch 32, Training loss 30.328775, Validation loss 3.917418\n",
      "Epoch 33, Training loss 30.213654, Validation loss 3.921340\n",
      "Epoch 34, Training loss 30.098999, Validation loss 3.925263\n",
      "Epoch 35, Training loss 29.984819, Validation loss 3.929183\n",
      "Epoch 36, Training loss 29.871111, Validation loss 3.933101\n",
      "Epoch 37, Training loss 29.757866, Validation loss 3.937020\n",
      "Epoch 38, Training loss 29.645102, Validation loss 3.940933\n",
      "Epoch 39, Training loss 29.532793, Validation loss 3.944841\n",
      "Epoch 40, Training loss 29.420946, Validation loss 3.948755\n",
      "Epoch 41, Training loss 29.309563, Validation loss 3.952663\n",
      "Epoch 42, Training loss 29.198643, Validation loss 3.956569\n",
      "Epoch 43, Training loss 29.088175, Validation loss 3.960474\n",
      "Epoch 44, Training loss 28.978170, Validation loss 3.964376\n",
      "Epoch 45, Training loss 28.868612, Validation loss 3.968281\n",
      "Epoch 46, Training loss 28.759508, Validation loss 3.972181\n",
      "Epoch 47, Training loss 28.650858, Validation loss 3.976079\n",
      "Epoch 48, Training loss 28.542654, Validation loss 3.979972\n",
      "Epoch 49, Training loss 28.434891, Validation loss 3.983866\n",
      "Epoch 50, Training loss 28.327579, Validation loss 3.987761\n",
      "Epoch 51, Training loss 28.220713, Validation loss 3.991641\n",
      "Epoch 52, Training loss 28.114285, Validation loss 3.995536\n",
      "Epoch 53, Training loss 28.008293, Validation loss 3.999422\n",
      "Epoch 54, Training loss 27.902737, Validation loss 4.003298\n",
      "Epoch 55, Training loss 27.797615, Validation loss 4.007183\n",
      "Epoch 56, Training loss 27.692936, Validation loss 4.011058\n",
      "Epoch 57, Training loss 27.588684, Validation loss 4.014933\n",
      "Epoch 58, Training loss 27.484865, Validation loss 4.018810\n",
      "Epoch 59, Training loss 27.381472, Validation loss 4.022677\n",
      "Epoch 60, Training loss 27.278507, Validation loss 4.026552\n",
      "Epoch 61, Training loss 27.175961, Validation loss 4.030418\n",
      "Epoch 62, Training loss 27.073841, Validation loss 4.034285\n",
      "Epoch 63, Training loss 26.972143, Validation loss 4.038143\n",
      "Epoch 64, Training loss 26.870869, Validation loss 4.042006\n",
      "Epoch 65, Training loss 26.770012, Validation loss 4.045869\n",
      "Epoch 66, Training loss 26.669563, Validation loss 4.049720\n",
      "Epoch 67, Training loss 26.569536, Validation loss 4.053576\n",
      "Epoch 68, Training loss 26.469923, Validation loss 4.057426\n",
      "Epoch 69, Training loss 26.370716, Validation loss 4.061273\n",
      "Epoch 70, Training loss 26.271925, Validation loss 4.065120\n",
      "Epoch 71, Training loss 26.173531, Validation loss 4.068964\n",
      "Epoch 72, Training loss 26.075554, Validation loss 4.072807\n",
      "Epoch 73, Training loss 25.977976, Validation loss 4.076643\n",
      "Epoch 74, Training loss 25.880798, Validation loss 4.080482\n",
      "Epoch 75, Training loss 25.784031, Validation loss 4.084318\n",
      "Epoch 76, Training loss 25.687651, Validation loss 4.088150\n",
      "Epoch 77, Training loss 25.591675, Validation loss 4.091977\n",
      "Epoch 78, Training loss 25.496098, Validation loss 4.095804\n",
      "Epoch 79, Training loss 25.400904, Validation loss 4.099631\n",
      "Epoch 80, Training loss 25.306110, Validation loss 4.103450\n",
      "Epoch 81, Training loss 25.211708, Validation loss 4.107265\n",
      "Epoch 82, Training loss 25.117695, Validation loss 4.111086\n",
      "Epoch 83, Training loss 25.024075, Validation loss 4.114896\n",
      "Epoch 84, Training loss 24.930830, Validation loss 4.118706\n",
      "Epoch 85, Training loss 24.837976, Validation loss 4.122515\n",
      "Epoch 86, Training loss 24.745506, Validation loss 4.126323\n",
      "Epoch 87, Training loss 24.653419, Validation loss 4.130118\n",
      "Epoch 88, Training loss 24.561707, Validation loss 4.133926\n",
      "Epoch 89, Training loss 24.470377, Validation loss 4.137722\n",
      "Epoch 90, Training loss 24.379427, Validation loss 4.141511\n",
      "Epoch 91, Training loss 24.288853, Validation loss 4.145308\n",
      "Epoch 92, Training loss 24.198645, Validation loss 4.149097\n",
      "Epoch 93, Training loss 24.108812, Validation loss 4.152882\n",
      "Epoch 94, Training loss 24.019346, Validation loss 4.156662\n",
      "Epoch 95, Training loss 23.930258, Validation loss 4.160441\n",
      "Epoch 96, Training loss 23.841530, Validation loss 4.164222\n",
      "Epoch 97, Training loss 23.753174, Validation loss 4.167995\n",
      "Epoch 98, Training loss 23.665176, Validation loss 4.171763\n",
      "Epoch 99, Training loss 23.577549, Validation loss 4.175535\n",
      "Epoch 100, Training loss 23.490278, Validation loss 4.179304\n",
      "Epoch 101, Training loss 23.403364, Validation loss 4.183070\n",
      "Epoch 102, Training loss 23.316814, Validation loss 4.186822\n",
      "Epoch 103, Training loss 23.230623, Validation loss 4.190585\n",
      "Epoch 104, Training loss 23.144787, Validation loss 4.194331\n",
      "Epoch 105, Training loss 23.059299, Validation loss 4.198083\n",
      "Epoch 106, Training loss 22.974167, Validation loss 4.201835\n",
      "Epoch 107, Training loss 22.889391, Validation loss 4.205578\n",
      "Epoch 108, Training loss 22.804958, Validation loss 4.209323\n",
      "Epoch 109, Training loss 22.720871, Validation loss 4.213062\n",
      "Epoch 110, Training loss 22.637138, Validation loss 4.216797\n",
      "Epoch 111, Training loss 22.553753, Validation loss 4.220531\n",
      "Epoch 112, Training loss 22.470709, Validation loss 4.224258\n",
      "Epoch 113, Training loss 22.388004, Validation loss 4.227993\n",
      "Epoch 114, Training loss 22.305645, Validation loss 4.231714\n",
      "Epoch 115, Training loss 22.223619, Validation loss 4.235434\n",
      "Epoch 116, Training loss 22.141939, Validation loss 4.239151\n",
      "Epoch 117, Training loss 22.060591, Validation loss 4.242865\n",
      "Epoch 118, Training loss 21.979580, Validation loss 4.246579\n",
      "Epoch 119, Training loss 21.898905, Validation loss 4.250288\n",
      "Epoch 120, Training loss 21.818565, Validation loss 4.253993\n",
      "Epoch 121, Training loss 21.738552, Validation loss 4.257694\n",
      "Epoch 122, Training loss 21.658873, Validation loss 4.261395\n",
      "Epoch 123, Training loss 21.579517, Validation loss 4.265085\n",
      "Epoch 124, Training loss 21.500496, Validation loss 4.268775\n",
      "Epoch 125, Training loss 21.421797, Validation loss 4.272470\n",
      "Epoch 126, Training loss 21.343422, Validation loss 4.276151\n",
      "Epoch 127, Training loss 21.265371, Validation loss 4.279839\n",
      "Epoch 128, Training loss 21.187645, Validation loss 4.283519\n",
      "Epoch 129, Training loss 21.110237, Validation loss 4.287191\n",
      "Epoch 130, Training loss 21.033142, Validation loss 4.290872\n",
      "Epoch 131, Training loss 20.956375, Validation loss 4.294537\n",
      "Epoch 132, Training loss 20.879925, Validation loss 4.298195\n",
      "Epoch 133, Training loss 20.803785, Validation loss 4.301858\n",
      "Epoch 134, Training loss 20.727957, Validation loss 4.305527\n",
      "Epoch 135, Training loss 20.652443, Validation loss 4.309179\n",
      "Epoch 136, Training loss 20.577250, Validation loss 4.312829\n",
      "Epoch 137, Training loss 20.502363, Validation loss 4.316480\n",
      "Epoch 138, Training loss 20.427778, Validation loss 4.320132\n",
      "Epoch 139, Training loss 20.353506, Validation loss 4.323771\n",
      "Epoch 140, Training loss 20.279539, Validation loss 4.327412\n",
      "Epoch 141, Training loss 20.205879, Validation loss 4.331046\n",
      "Epoch 142, Training loss 20.132523, Validation loss 4.334679\n",
      "Epoch 143, Training loss 20.059467, Validation loss 4.338305\n",
      "Epoch 144, Training loss 19.986717, Validation loss 4.341932\n",
      "Epoch 145, Training loss 19.914267, Validation loss 4.345553\n",
      "Epoch 146, Training loss 19.842112, Validation loss 4.349174\n",
      "Epoch 147, Training loss 19.770256, Validation loss 4.352791\n",
      "Epoch 148, Training loss 19.698696, Validation loss 4.356404\n",
      "Epoch 149, Training loss 19.627430, Validation loss 4.360015\n",
      "Epoch 150, Training loss 19.556465, Validation loss 4.363620\n",
      "Epoch 151, Training loss 19.485786, Validation loss 4.367219\n",
      "Epoch 152, Training loss 19.415401, Validation loss 4.370814\n",
      "Epoch 153, Training loss 19.345304, Validation loss 4.374411\n",
      "Epoch 154, Training loss 19.275503, Validation loss 4.377997\n",
      "Epoch 155, Training loss 19.205982, Validation loss 4.381592\n",
      "Epoch 156, Training loss 19.136749, Validation loss 4.385174\n",
      "Epoch 157, Training loss 19.067804, Validation loss 4.388752\n",
      "Epoch 158, Training loss 18.999144, Validation loss 4.392331\n",
      "Epoch 159, Training loss 18.930769, Validation loss 4.395905\n",
      "Epoch 160, Training loss 18.862675, Validation loss 4.399470\n",
      "Epoch 161, Training loss 18.794859, Validation loss 4.403041\n",
      "Epoch 162, Training loss 18.727325, Validation loss 4.406597\n",
      "Epoch 163, Training loss 18.660072, Validation loss 4.410159\n",
      "Epoch 164, Training loss 18.593090, Validation loss 4.413717\n",
      "Epoch 165, Training loss 18.526390, Validation loss 4.417264\n",
      "Epoch 166, Training loss 18.459963, Validation loss 4.420817\n",
      "Epoch 167, Training loss 18.393810, Validation loss 4.424358\n",
      "Epoch 168, Training loss 18.327930, Validation loss 4.427900\n",
      "Epoch 169, Training loss 18.262323, Validation loss 4.431436\n",
      "Epoch 170, Training loss 18.196985, Validation loss 4.434969\n",
      "Epoch 171, Training loss 18.131920, Validation loss 4.438495\n",
      "Epoch 172, Training loss 18.067118, Validation loss 4.442024\n",
      "Epoch 173, Training loss 18.002586, Validation loss 4.445548\n",
      "Epoch 174, Training loss 17.938324, Validation loss 4.449068\n",
      "Epoch 175, Training loss 17.874323, Validation loss 4.452584\n",
      "Epoch 176, Training loss 17.810587, Validation loss 4.456095\n",
      "Epoch 177, Training loss 17.747118, Validation loss 4.459600\n",
      "Epoch 178, Training loss 17.683905, Validation loss 4.463108\n",
      "Epoch 179, Training loss 17.620958, Validation loss 4.466607\n",
      "Epoch 180, Training loss 17.558264, Validation loss 4.470100\n",
      "Epoch 181, Training loss 17.495829, Validation loss 4.473598\n",
      "Epoch 182, Training loss 17.433661, Validation loss 4.477083\n",
      "Epoch 183, Training loss 17.371740, Validation loss 4.480570\n",
      "Epoch 184, Training loss 17.310080, Validation loss 4.484053\n",
      "Epoch 185, Training loss 17.248674, Validation loss 4.487536\n",
      "Epoch 186, Training loss 17.187515, Validation loss 4.491009\n",
      "Epoch 187, Training loss 17.126614, Validation loss 4.494473\n",
      "Epoch 188, Training loss 17.065966, Validation loss 4.497943\n",
      "Epoch 189, Training loss 17.005564, Validation loss 4.501409\n",
      "Epoch 190, Training loss 16.945414, Validation loss 4.504863\n",
      "Epoch 191, Training loss 16.885511, Validation loss 4.508317\n",
      "Epoch 192, Training loss 16.825857, Validation loss 4.511776\n",
      "Epoch 193, Training loss 16.766445, Validation loss 4.515216\n",
      "Epoch 194, Training loss 16.707283, Validation loss 4.518663\n",
      "Epoch 195, Training loss 16.648361, Validation loss 4.522104\n",
      "Epoch 196, Training loss 16.589684, Validation loss 4.525541\n",
      "Epoch 197, Training loss 16.531254, Validation loss 4.528974\n",
      "Epoch 198, Training loss 16.473057, Validation loss 4.532403\n",
      "Epoch 199, Training loss 16.415102, Validation loss 4.535828\n",
      "Epoch 200, Training loss 16.357389, Validation loss 4.539241\n",
      "Epoch 201, Training loss 16.299913, Validation loss 4.542663\n",
      "Epoch 202, Training loss 16.242676, Validation loss 4.546077\n",
      "Epoch 203, Training loss 16.185669, Validation loss 4.549491\n",
      "Epoch 204, Training loss 16.128904, Validation loss 4.552889\n",
      "Epoch 205, Training loss 16.072371, Validation loss 4.556292\n",
      "Epoch 206, Training loss 16.016069, Validation loss 4.559686\n",
      "Epoch 207, Training loss 15.960003, Validation loss 4.563085\n",
      "Epoch 208, Training loss 15.904170, Validation loss 4.566475\n",
      "Epoch 209, Training loss 15.848560, Validation loss 4.569862\n",
      "Epoch 210, Training loss 15.793184, Validation loss 4.573240\n",
      "Epoch 211, Training loss 15.738035, Validation loss 4.576620\n",
      "Epoch 212, Training loss 15.683114, Validation loss 4.579998\n",
      "Epoch 213, Training loss 15.628423, Validation loss 4.583364\n",
      "Epoch 214, Training loss 15.573953, Validation loss 4.586736\n",
      "Epoch 215, Training loss 15.519708, Validation loss 4.590094\n",
      "Epoch 216, Training loss 15.465690, Validation loss 4.593452\n",
      "Epoch 217, Training loss 15.411894, Validation loss 4.596807\n",
      "Epoch 218, Training loss 15.358317, Validation loss 4.600153\n",
      "Epoch 219, Training loss 15.304969, Validation loss 4.603502\n",
      "Epoch 220, Training loss 15.251835, Validation loss 4.606848\n",
      "Epoch 221, Training loss 15.198918, Validation loss 4.610189\n",
      "Epoch 222, Training loss 15.146218, Validation loss 4.613523\n",
      "Epoch 223, Training loss 15.093741, Validation loss 4.616856\n",
      "Epoch 224, Training loss 15.041482, Validation loss 4.620181\n",
      "Epoch 225, Training loss 14.989434, Validation loss 4.623506\n",
      "Epoch 226, Training loss 14.937605, Validation loss 4.626822\n",
      "Epoch 227, Training loss 14.885984, Validation loss 4.630137\n",
      "Epoch 228, Training loss 14.834584, Validation loss 4.633453\n",
      "Epoch 229, Training loss 14.783388, Validation loss 4.636760\n",
      "Epoch 230, Training loss 14.732409, Validation loss 4.640059\n",
      "Epoch 231, Training loss 14.681636, Validation loss 4.643361\n",
      "Epoch 232, Training loss 14.631077, Validation loss 4.646655\n",
      "Epoch 233, Training loss 14.580723, Validation loss 4.649944\n",
      "Epoch 234, Training loss 14.530575, Validation loss 4.653233\n",
      "Epoch 235, Training loss 14.480640, Validation loss 4.656522\n",
      "Epoch 236, Training loss 14.430906, Validation loss 4.659798\n",
      "Epoch 237, Training loss 14.381378, Validation loss 4.663070\n",
      "Epoch 238, Training loss 14.332062, Validation loss 4.666340\n",
      "Epoch 239, Training loss 14.282940, Validation loss 4.669611\n",
      "Epoch 240, Training loss 14.234026, Validation loss 4.672873\n",
      "Epoch 241, Training loss 14.185309, Validation loss 4.676129\n",
      "Epoch 242, Training loss 14.136793, Validation loss 4.679395\n",
      "Epoch 243, Training loss 14.088481, Validation loss 4.682643\n",
      "Epoch 244, Training loss 14.040371, Validation loss 4.685894\n",
      "Epoch 245, Training loss 13.992454, Validation loss 4.689137\n",
      "Epoch 246, Training loss 13.944736, Validation loss 4.692370\n",
      "Epoch 247, Training loss 13.897215, Validation loss 4.695608\n",
      "Epoch 248, Training loss 13.849891, Validation loss 4.698841\n",
      "Epoch 249, Training loss 13.802764, Validation loss 4.702069\n",
      "Epoch 250, Training loss 13.755830, Validation loss 4.705284\n",
      "Epoch 251, Training loss 13.709087, Validation loss 4.708507\n",
      "Epoch 252, Training loss 13.662540, Validation loss 4.711720\n",
      "Epoch 253, Training loss 13.616182, Validation loss 4.714928\n",
      "Epoch 254, Training loss 13.570018, Validation loss 4.718136\n",
      "Epoch 255, Training loss 13.524043, Validation loss 4.721344\n",
      "Epoch 256, Training loss 13.478262, Validation loss 4.724542\n",
      "Epoch 257, Training loss 13.432661, Validation loss 4.727731\n",
      "Epoch 258, Training loss 13.387257, Validation loss 4.730923\n",
      "Epoch 259, Training loss 13.342034, Validation loss 4.734110\n",
      "Epoch 260, Training loss 13.296999, Validation loss 4.737289\n",
      "Epoch 261, Training loss 13.252155, Validation loss 4.740471\n",
      "Epoch 262, Training loss 13.207493, Validation loss 4.743648\n",
      "Epoch 263, Training loss 13.163013, Validation loss 4.746819\n",
      "Epoch 264, Training loss 13.118715, Validation loss 4.749987\n",
      "Epoch 265, Training loss 13.074604, Validation loss 4.753143\n",
      "Epoch 266, Training loss 13.030676, Validation loss 4.756305\n",
      "Epoch 267, Training loss 12.986928, Validation loss 4.759456\n",
      "Epoch 268, Training loss 12.943359, Validation loss 4.762611\n",
      "Epoch 269, Training loss 12.899972, Validation loss 4.765752\n",
      "Epoch 270, Training loss 12.856762, Validation loss 4.768897\n",
      "Epoch 271, Training loss 12.813731, Validation loss 4.772032\n",
      "Epoch 272, Training loss 12.770876, Validation loss 4.775167\n",
      "Epoch 273, Training loss 12.728199, Validation loss 4.778296\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 307, Training loss 11.377375, Validation loss 4.882258\n",
      "Epoch 308, Training loss 11.340446, Validation loss 4.885246\n",
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      "Epoch 360, Training loss 9.616245, Validation loss 5.034869\n",
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      "Epoch 593, Training loss 5.171238, Validation loss 5.575613\n",
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      "Epoch 630, Training loss 4.782159, Validation loss 5.643752\n",
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      "Epoch 633, Training loss 4.753145, Validation loss 5.649083\n",
      "Epoch 634, Training loss 4.743551, Validation loss 5.650855\n",
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      "Epoch 640, Training loss 4.686824, Validation loss 5.661406\n",
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      "Epoch 647, Training loss 4.622397, Validation loss 5.673606\n",
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      "Epoch 660, Training loss 4.507586, Validation loss 5.695821\n",
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      "Epoch 663, Training loss 4.481956, Validation loss 5.700885\n",
      "Epoch 664, Training loss 4.473485, Validation loss 5.702565\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 665, Training loss 4.465043, Validation loss 5.704241\n",
      "Epoch 666, Training loss 4.456642, Validation loss 5.705917\n",
      "Epoch 667, Training loss 4.448274, Validation loss 5.707585\n",
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      "Epoch 673, Training loss 4.398783, Validation loss 5.717544\n",
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      "Epoch 675, Training loss 4.382559, Validation loss 5.720832\n",
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      "Epoch 678, Training loss 4.358469, Validation loss 5.725755\n",
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      "Epoch 681, Training loss 4.334678, Validation loss 5.730664\n",
      "Epoch 682, Training loss 4.326815, Validation loss 5.732289\n",
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      "Epoch 687, Training loss 4.287971, Validation loss 5.740362\n",
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      "Epoch 696, Training loss 4.220046, Validation loss 5.754751\n",
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      "Epoch 698, Training loss 4.205292, Validation loss 5.757905\n",
      "Epoch 699, Training loss 4.197961, Validation loss 5.759479\n",
      "Epoch 700, Training loss 4.190660, Validation loss 5.761053\n",
      "Epoch 701, Training loss 4.183388, Validation loss 5.762631\n",
      "Epoch 702, Training loss 4.176149, Validation loss 5.764197\n",
      "Epoch 703, Training loss 4.168938, Validation loss 5.765759\n",
      "Epoch 704, Training loss 4.161757, Validation loss 5.767321\n",
      "Epoch 705, Training loss 4.154603, Validation loss 5.768883\n",
      "Epoch 706, Training loss 4.147482, Validation loss 5.770436\n",
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      "Epoch 714, Training loss 4.091555, Validation loss 5.782802\n",
      "Epoch 715, Training loss 4.084691, Validation loss 5.784337\n",
      "Epoch 716, Training loss 4.077856, Validation loss 5.785872\n",
      "Epoch 717, Training loss 4.071051, Validation loss 5.787393\n",
      "Epoch 718, Training loss 4.064273, Validation loss 5.788915\n",
      "Epoch 719, Training loss 4.057524, Validation loss 5.790437\n",
      "Epoch 720, Training loss 4.050801, Validation loss 5.791950\n",
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      "Epoch 727, Training loss 4.004521, Validation loss 5.802505\n",
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      "Epoch 900, Training loss 3.199271, Validation loss 6.024158\n",
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      "Epoch 904, Training loss 3.186633, Validation loss 6.028476\n",
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      "Epoch 999, Training loss 2.940392, Validation loss 6.121936\n",
      "Epoch 1000, Training loss 2.938281, Validation loss 6.122833\n",
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      "Epoch 1052, Training loss 2.839674, Validation loss 6.167096\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1053, Training loss 2.837979, Validation loss 6.167898\n",
      "Epoch 1054, Training loss 2.836289, Validation loss 6.168700\n",
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      "Epoch 1100, Training loss 2.765679, Validation loss 6.204149\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1325, Training loss 2.561565, Validation loss 6.337888\n",
      "Epoch 1326, Training loss 2.561016, Validation loss 6.338358\n",
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      "Epoch 1600, Training loss 2.471268, Validation loss 6.437405\n",
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      "Epoch 1603, Training loss 2.470741, Validation loss 6.438212\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1604, Training loss 2.470567, Validation loss 6.438484\n",
      "Epoch 1605, Training loss 2.470396, Validation loss 6.438754\n",
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      "Epoch 1830, Training loss 2.445104, Validation loss 6.487082\n",
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      "Epoch 1934, Training loss 2.439345, Validation loss 6.502944\n",
      "Epoch 1935, Training loss 2.439301, Validation loss 6.503090\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1936, Training loss 2.439257, Validation loss 6.503217\n",
      "Epoch 1937, Training loss 2.439214, Validation loss 6.503368\n",
      "Epoch 1938, Training loss 2.439170, Validation loss 6.503500\n",
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      "Epoch 1940, Training loss 2.439083, Validation loss 6.503763\n",
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      "Epoch 1949, Training loss 2.438702, Validation loss 6.504978\n",
      "Epoch 1950, Training loss 2.438659, Validation loss 6.505110\n",
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      "Epoch 1952, Training loss 2.438576, Validation loss 6.505373\n",
      "Epoch 1953, Training loss 2.438536, Validation loss 6.505504\n",
      "Epoch 1954, Training loss 2.438495, Validation loss 6.505631\n",
      "Epoch 1955, Training loss 2.438455, Validation loss 6.505773\n",
      "Epoch 1956, Training loss 2.438413, Validation loss 6.505894\n",
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      "Epoch 1959, Training loss 2.438294, Validation loss 6.506294\n",
      "Epoch 1960, Training loss 2.438252, Validation loss 6.506420\n",
      "Epoch 1961, Training loss 2.438214, Validation loss 6.506552\n",
      "Epoch 1962, Training loss 2.438174, Validation loss 6.506679\n",
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      "Epoch 1965, Training loss 2.438057, Validation loss 6.507059\n",
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      "Epoch 1968, Training loss 2.437940, Validation loss 6.507448\n",
      "Epoch 1969, Training loss 2.437902, Validation loss 6.507575\n",
      "Epoch 1970, Training loss 2.437865, Validation loss 6.507702\n",
      "Epoch 1971, Training loss 2.437825, Validation loss 6.507823\n",
      "Epoch 1972, Training loss 2.437788, Validation loss 6.507950\n",
      "Epoch 1973, Training loss 2.437749, Validation loss 6.508081\n",
      "Epoch 1974, Training loss 2.437713, Validation loss 6.508213\n",
      "Epoch 1975, Training loss 2.437675, Validation loss 6.508339\n",
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      "Epoch 1978, Training loss 2.437563, Validation loss 6.508719\n",
      "Epoch 1979, Training loss 2.437527, Validation loss 6.508831\n",
      "Epoch 1980, Training loss 2.437490, Validation loss 6.508952\n",
      "Epoch 1981, Training loss 2.437454, Validation loss 6.509094\n",
      "Epoch 1982, Training loss 2.437418, Validation loss 6.509206\n",
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      "Epoch 1985, Training loss 2.437309, Validation loss 6.509580\n",
      "Epoch 1986, Training loss 2.437273, Validation loss 6.509697\n",
      "Epoch 1987, Training loss 2.437238, Validation loss 6.509828\n",
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      "Epoch 1989, Training loss 2.437166, Validation loss 6.510072\n",
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      "Epoch 1991, Training loss 2.437097, Validation loss 6.510314\n",
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      "Epoch 2018, Training loss 2.436202, Validation loss 6.513512\n",
      "Epoch 2019, Training loss 2.436170, Validation loss 6.513622\n",
      "Epoch 2020, Training loss 2.436139, Validation loss 6.513739\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2259, Training loss 2.431426, Validation loss 6.535397\n",
      "Epoch 2260, Training loss 2.431413, Validation loss 6.535468\n",
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      "Epoch 2500, Training loss 2.429663, Validation loss 6.548722\n",
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      "Epoch 2557, Training loss 2.429447, Validation loss 6.551028\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2558, Training loss 2.429442, Validation loss 6.551060\n",
      "Epoch 2559, Training loss 2.429439, Validation loss 6.551100\n",
      "Epoch 2560, Training loss 2.429436, Validation loss 6.551141\n",
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      "Epoch 2567, Training loss 2.429414, Validation loss 6.551401\n",
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      "Epoch 2767, Training loss 2.428972, Validation loss 6.557498\n",
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      "Epoch 2892, Training loss 2.428835, Validation loss 6.560205\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2893, Training loss 2.428833, Validation loss 6.560235\n",
      "Epoch 2894, Training loss 2.428832, Validation loss 6.560246\n",
      "Epoch 2895, Training loss 2.428832, Validation loss 6.560262\n",
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      "Epoch 2897, Training loss 2.428832, Validation loss 6.560302\n",
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      "Epoch 2899, Training loss 2.428828, Validation loss 6.560333\n",
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      "Epoch 3081, Training loss 2.428724, Validation loss 6.563183\n",
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      "Epoch 3200, Training loss 2.428689, Validation loss 6.564545\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3201, Training loss 2.428688, Validation loss 6.564560\n",
      "Epoch 3202, Training loss 2.428687, Validation loss 6.564560\n",
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      "Epoch 3207, Training loss 2.428687, Validation loss 6.564611\n",
      "Epoch 3208, Training loss 2.428686, Validation loss 6.564627\n",
      "Epoch 3209, Training loss 2.428686, Validation loss 6.564617\n",
      "Epoch 3210, Training loss 2.428687, Validation loss 6.564632\n",
      "Epoch 3211, Training loss 2.428686, Validation loss 6.564652\n",
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      "Epoch 3213, Training loss 2.428684, Validation loss 6.564682\n",
      "Epoch 3214, Training loss 2.428684, Validation loss 6.564692\n",
      "Epoch 3215, Training loss 2.428685, Validation loss 6.564703\n",
      "Epoch 3216, Training loss 2.428684, Validation loss 6.564703\n",
      "Epoch 3217, Training loss 2.428685, Validation loss 6.564713\n",
      "Epoch 3218, Training loss 2.428683, Validation loss 6.564723\n",
      "Epoch 3219, Training loss 2.428684, Validation loss 6.564734\n",
      "Epoch 3220, Training loss 2.428684, Validation loss 6.564744\n",
      "Epoch 3221, Training loss 2.428684, Validation loss 6.564754\n",
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      "Epoch 3224, Training loss 2.428683, Validation loss 6.564770\n",
      "Epoch 3225, Training loss 2.428682, Validation loss 6.564780\n",
      "Epoch 3226, Training loss 2.428682, Validation loss 6.564790\n",
      "Epoch 3227, Training loss 2.428683, Validation loss 6.564800\n",
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      "Epoch 3233, Training loss 2.428681, Validation loss 6.564871\n",
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      "Epoch 3239, Training loss 2.428679, Validation loss 6.564922\n",
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      "Epoch 3380, Training loss 2.428658, Validation loss 6.566050\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3381, Training loss 2.428657, Validation loss 6.566051\n",
      "Epoch 3382, Training loss 2.428658, Validation loss 6.566075\n",
      "Epoch 3383, Training loss 2.428658, Validation loss 6.566080\n",
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      "Epoch 3385, Training loss 2.428658, Validation loss 6.566086\n",
      "Epoch 3386, Training loss 2.428657, Validation loss 6.566091\n",
      "Epoch 3387, Training loss 2.428658, Validation loss 6.566106\n",
      "Epoch 3388, Training loss 2.428657, Validation loss 6.566111\n",
      "Epoch 3389, Training loss 2.428657, Validation loss 6.566116\n",
      "Epoch 3390, Training loss 2.428657, Validation loss 6.566121\n",
      "Epoch 3391, Training loss 2.428657, Validation loss 6.566127\n",
      "Epoch 3392, Training loss 2.428657, Validation loss 6.566132\n",
      "Epoch 3393, Training loss 2.428657, Validation loss 6.566137\n",
      "Epoch 3394, Training loss 2.428657, Validation loss 6.566137\n",
      "Epoch 3395, Training loss 2.428657, Validation loss 6.566142\n",
      "Epoch 3396, Training loss 2.428655, Validation loss 6.566167\n",
      "Epoch 3397, Training loss 2.428655, Validation loss 6.566172\n",
      "Epoch 3398, Training loss 2.428657, Validation loss 6.566173\n",
      "Epoch 3399, Training loss 2.428657, Validation loss 6.566177\n",
      "Epoch 3400, Training loss 2.428656, Validation loss 6.566183\n",
      "Epoch 3401, Training loss 2.428655, Validation loss 6.566188\n",
      "Epoch 3402, Training loss 2.428656, Validation loss 6.566193\n",
      "Epoch 3403, Training loss 2.428655, Validation loss 6.566208\n",
      "Epoch 3404, Training loss 2.428655, Validation loss 6.566223\n",
      "Epoch 3405, Training loss 2.428656, Validation loss 6.566229\n",
      "Epoch 3406, Training loss 2.428656, Validation loss 6.566243\n",
      "Epoch 3407, Training loss 2.428654, Validation loss 6.566243\n",
      "Epoch 3408, Training loss 2.428655, Validation loss 6.566238\n",
      "Epoch 3409, Training loss 2.428656, Validation loss 6.566254\n",
      "Epoch 3410, Training loss 2.428654, Validation loss 6.566259\n",
      "Epoch 3411, Training loss 2.428655, Validation loss 6.566274\n",
      "Epoch 3412, Training loss 2.428655, Validation loss 6.566274\n",
      "Epoch 3413, Training loss 2.428655, Validation loss 6.566269\n",
      "Epoch 3414, Training loss 2.428655, Validation loss 6.566284\n",
      "Epoch 3415, Training loss 2.428655, Validation loss 6.566295\n",
      "Epoch 3416, Training loss 2.428655, Validation loss 6.566290\n",
      "Epoch 3417, Training loss 2.428655, Validation loss 6.566305\n",
      "Epoch 3418, Training loss 2.428653, Validation loss 6.566305\n",
      "Epoch 3419, Training loss 2.428653, Validation loss 6.566310\n",
      "Epoch 3420, Training loss 2.428655, Validation loss 6.566325\n",
      "Epoch 3421, Training loss 2.428652, Validation loss 6.566320\n",
      "Epoch 3422, Training loss 2.428653, Validation loss 6.566336\n",
      "Epoch 3423, Training loss 2.428653, Validation loss 6.566336\n",
      "Epoch 3424, Training loss 2.428653, Validation loss 6.566341\n",
      "Epoch 3425, Training loss 2.428653, Validation loss 6.566356\n",
      "Epoch 3426, Training loss 2.428653, Validation loss 6.566356\n",
      "Epoch 3427, Training loss 2.428653, Validation loss 6.566351\n",
      "Epoch 3428, Training loss 2.428653, Validation loss 6.566366\n",
      "Epoch 3429, Training loss 2.428653, Validation loss 6.566377\n",
      "Epoch 3430, Training loss 2.428653, Validation loss 6.566372\n",
      "Epoch 3431, Training loss 2.428653, Validation loss 6.566387\n",
      "Epoch 3432, Training loss 2.428652, Validation loss 6.566382\n",
      "Epoch 3433, Training loss 2.428653, Validation loss 6.566397\n",
      "Epoch 3434, Training loss 2.428652, Validation loss 6.566417\n",
      "Epoch 3435, Training loss 2.428653, Validation loss 6.566422\n",
      "Epoch 3436, Training loss 2.428653, Validation loss 6.566432\n",
      "Epoch 3437, Training loss 2.428652, Validation loss 6.566447\n",
      "Epoch 3438, Training loss 2.428652, Validation loss 6.566438\n",
      "Epoch 3439, Training loss 2.428653, Validation loss 6.566457\n",
      "Epoch 3440, Training loss 2.428653, Validation loss 6.566448\n",
      "Epoch 3441, Training loss 2.428651, Validation loss 6.566453\n",
      "Epoch 3442, Training loss 2.428650, Validation loss 6.566473\n",
      "Epoch 3443, Training loss 2.428652, Validation loss 6.566463\n",
      "Epoch 3444, Training loss 2.428652, Validation loss 6.566479\n",
      "Epoch 3445, Training loss 2.428651, Validation loss 6.566488\n",
      "Epoch 3446, Training loss 2.428651, Validation loss 6.566479\n",
      "Epoch 3447, Training loss 2.428653, Validation loss 6.566494\n",
      "Epoch 3448, Training loss 2.428653, Validation loss 6.566504\n",
      "Epoch 3449, Training loss 2.428651, Validation loss 6.566508\n",
      "Epoch 3450, Training loss 2.428651, Validation loss 6.566509\n",
      "Epoch 3451, Training loss 2.428652, Validation loss 6.566519\n",
      "Epoch 3452, Training loss 2.428652, Validation loss 6.566519\n",
      "Epoch 3453, Training loss 2.428651, Validation loss 6.566525\n",
      "Epoch 3454, Training loss 2.428651, Validation loss 6.566529\n",
      "Epoch 3455, Training loss 2.428649, Validation loss 6.566535\n",
      "Epoch 3456, Training loss 2.428651, Validation loss 6.566545\n",
      "Epoch 3457, Training loss 2.428650, Validation loss 6.566545\n",
      "Epoch 3458, Training loss 2.428650, Validation loss 6.566550\n",
      "Epoch 3459, Training loss 2.428651, Validation loss 6.566560\n",
      "Epoch 3460, Training loss 2.428650, Validation loss 6.566575\n",
      "Epoch 3461, Training loss 2.428651, Validation loss 6.566566\n",
      "Epoch 3462, Training loss 2.428650, Validation loss 6.566586\n",
      "Epoch 3463, Training loss 2.428650, Validation loss 6.566576\n",
      "Epoch 3464, Training loss 2.428650, Validation loss 6.566581\n",
      "Epoch 3465, Training loss 2.428651, Validation loss 6.566581\n",
      "Epoch 3466, Training loss 2.428650, Validation loss 6.566601\n",
      "Epoch 3467, Training loss 2.428650, Validation loss 6.566611\n",
      "Epoch 3468, Training loss 2.428650, Validation loss 6.566611\n",
      "Epoch 3469, Training loss 2.428650, Validation loss 6.566621\n",
      "Epoch 3470, Training loss 2.428649, Validation loss 6.566621\n",
      "Epoch 3471, Training loss 2.428649, Validation loss 6.566631\n",
      "Epoch 3472, Training loss 2.428649, Validation loss 6.566642\n",
      "Epoch 3473, Training loss 2.428650, Validation loss 6.566642\n",
      "Epoch 3474, Training loss 2.428649, Validation loss 6.566652\n",
      "Epoch 3475, Training loss 2.428649, Validation loss 6.566652\n",
      "Epoch 3476, Training loss 2.428649, Validation loss 6.566662\n",
      "Epoch 3477, Training loss 2.428649, Validation loss 6.566667\n",
      "Epoch 3478, Training loss 2.428649, Validation loss 6.566677\n",
      "Epoch 3479, Training loss 2.428649, Validation loss 6.566677\n",
      "Epoch 3480, Training loss 2.428648, Validation loss 6.566688\n",
      "Epoch 3481, Training loss 2.428648, Validation loss 6.566688\n",
      "Epoch 3482, Training loss 2.428649, Validation loss 6.566698\n",
      "Epoch 3483, Training loss 2.428649, Validation loss 6.566708\n",
      "Epoch 3484, Training loss 2.428648, Validation loss 6.566708\n",
      "Epoch 3485, Training loss 2.428648, Validation loss 6.566718\n",
      "Epoch 3486, Training loss 2.428648, Validation loss 6.566718\n",
      "Epoch 3487, Training loss 2.428648, Validation loss 6.566729\n",
      "Epoch 3488, Training loss 2.428648, Validation loss 6.566729\n",
      "Epoch 3489, Training loss 2.428648, Validation loss 6.566739\n",
      "Epoch 3490, Training loss 2.428647, Validation loss 6.566739\n",
      "Epoch 3491, Training loss 2.428647, Validation loss 6.566734\n",
      "Epoch 3492, Training loss 2.428648, Validation loss 6.566744\n",
      "Epoch 3493, Training loss 2.428647, Validation loss 6.566744\n",
      "Epoch 3494, Training loss 2.428649, Validation loss 6.566754\n",
      "Epoch 3495, Training loss 2.428648, Validation loss 6.566754\n",
      "Epoch 3496, Training loss 2.428649, Validation loss 6.566770\n",
      "Epoch 3497, Training loss 2.428648, Validation loss 6.566780\n",
      "Epoch 3498, Training loss 2.428648, Validation loss 6.566780\n",
      "Epoch 3499, Training loss 2.428647, Validation loss 6.566790\n",
      "Epoch 3500, Training loss 2.428647, Validation loss 6.566790\n",
      "Epoch 3501, Training loss 2.428647, Validation loss 6.566810\n",
      "Epoch 3502, Training loss 2.428647, Validation loss 6.566814\n",
      "Epoch 3503, Training loss 2.428647, Validation loss 6.566805\n",
      "Epoch 3504, Training loss 2.428646, Validation loss 6.566825\n",
      "Epoch 3505, Training loss 2.428647, Validation loss 6.566830\n",
      "Epoch 3506, Training loss 2.428647, Validation loss 6.566825\n",
      "Epoch 3507, Training loss 2.428647, Validation loss 6.566826\n",
      "Epoch 3508, Training loss 2.428647, Validation loss 6.566831\n",
      "Epoch 3509, Training loss 2.428646, Validation loss 6.566851\n",
      "Epoch 3510, Training loss 2.428647, Validation loss 6.566845\n",
      "Epoch 3511, Training loss 2.428647, Validation loss 6.566846\n",
      "Epoch 3512, Training loss 2.428646, Validation loss 6.566851\n",
      "Epoch 3513, Training loss 2.428646, Validation loss 6.566871\n",
      "Epoch 3514, Training loss 2.428645, Validation loss 6.566866\n",
      "Epoch 3515, Training loss 2.428646, Validation loss 6.566867\n",
      "Epoch 3516, Training loss 2.428645, Validation loss 6.566891\n",
      "Epoch 3517, Training loss 2.428645, Validation loss 6.566881\n",
      "Epoch 3518, Training loss 2.428646, Validation loss 6.566886\n",
      "Epoch 3519, Training loss 2.428646, Validation loss 6.566892\n",
      "Epoch 3520, Training loss 2.428646, Validation loss 6.566892\n",
      "Epoch 3521, Training loss 2.428645, Validation loss 6.566902\n",
      "Epoch 3522, Training loss 2.428646, Validation loss 6.566907\n",
      "Epoch 3523, Training loss 2.428645, Validation loss 6.566912\n",
      "Epoch 3524, Training loss 2.428647, Validation loss 6.566913\n",
      "Epoch 3525, Training loss 2.428647, Validation loss 6.566917\n",
      "Epoch 3526, Training loss 2.428646, Validation loss 6.566913\n",
      "Epoch 3527, Training loss 2.428647, Validation loss 6.566933\n",
      "Epoch 3528, Training loss 2.428647, Validation loss 6.566933\n",
      "Epoch 3529, Training loss 2.428646, Validation loss 6.566938\n",
      "Epoch 3530, Training loss 2.428644, Validation loss 6.566948\n",
      "Epoch 3531, Training loss 2.428645, Validation loss 6.566953\n",
      "Epoch 3532, Training loss 2.428645, Validation loss 6.566954\n",
      "Epoch 3533, Training loss 2.428645, Validation loss 6.566948\n",
      "Epoch 3534, Training loss 2.428646, Validation loss 6.566968\n",
      "Epoch 3535, Training loss 2.428645, Validation loss 6.566974\n",
      "Epoch 3536, Training loss 2.428645, Validation loss 6.566978\n",
      "Epoch 3537, Training loss 2.428646, Validation loss 6.566969\n",
      "Epoch 3538, Training loss 2.428645, Validation loss 6.566984\n",
      "Epoch 3539, Training loss 2.428646, Validation loss 6.566998\n",
      "Epoch 3540, Training loss 2.428646, Validation loss 6.567009\n",
      "Epoch 3541, Training loss 2.428644, Validation loss 6.567004\n",
      "Epoch 3542, Training loss 2.428645, Validation loss 6.567019\n",
      "Epoch 3543, Training loss 2.428645, Validation loss 6.567024\n",
      "Epoch 3544, Training loss 2.428645, Validation loss 6.567019\n",
      "Epoch 3545, Training loss 2.428644, Validation loss 6.567034\n",
      "Epoch 3546, Training loss 2.428643, Validation loss 6.567029\n",
      "Epoch 3547, Training loss 2.428644, Validation loss 6.567044\n",
      "Epoch 3548, Training loss 2.428644, Validation loss 6.567039\n",
      "Epoch 3549, Training loss 2.428645, Validation loss 6.567055\n",
      "Epoch 3550, Training loss 2.428644, Validation loss 6.567050\n",
      "Epoch 3551, Training loss 2.428644, Validation loss 6.567065\n",
      "Epoch 3552, Training loss 2.428644, Validation loss 6.567060\n",
      "Epoch 3553, Training loss 2.428644, Validation loss 6.567070\n",
      "Epoch 3554, Training loss 2.428644, Validation loss 6.567075\n",
      "Epoch 3555, Training loss 2.428643, Validation loss 6.567070\n",
      "Epoch 3556, Training loss 2.428643, Validation loss 6.567085\n",
      "Epoch 3557, Training loss 2.428644, Validation loss 6.567080\n",
      "Epoch 3558, Training loss 2.428643, Validation loss 6.567096\n",
      "Epoch 3559, Training loss 2.428644, Validation loss 6.567091\n",
      "Epoch 3560, Training loss 2.428643, Validation loss 6.567086\n",
      "Epoch 3561, Training loss 2.428643, Validation loss 6.567101\n",
      "Epoch 3562, Training loss 2.428644, Validation loss 6.567116\n",
      "Epoch 3563, Training loss 2.428643, Validation loss 6.567111\n",
      "Epoch 3564, Training loss 2.428643, Validation loss 6.567106\n",
      "Epoch 3565, Training loss 2.428643, Validation loss 6.567122\n",
      "Epoch 3566, Training loss 2.428643, Validation loss 6.567126\n",
      "Epoch 3567, Training loss 2.428643, Validation loss 6.567122\n",
      "Epoch 3568, Training loss 2.428643, Validation loss 6.567136\n",
      "Epoch 3569, Training loss 2.428643, Validation loss 6.567132\n",
      "Epoch 3570, Training loss 2.428643, Validation loss 6.567146\n",
      "Epoch 3571, Training loss 2.428643, Validation loss 6.567142\n",
      "Epoch 3572, Training loss 2.428643, Validation loss 6.567152\n",
      "Epoch 3573, Training loss 2.428644, Validation loss 6.567152\n",
      "Epoch 3574, Training loss 2.428644, Validation loss 6.567163\n",
      "Epoch 3575, Training loss 2.428643, Validation loss 6.567163\n",
      "Epoch 3576, Training loss 2.428643, Validation loss 6.567173\n",
      "Epoch 3577, Training loss 2.428644, Validation loss 6.567173\n",
      "Epoch 3578, Training loss 2.428643, Validation loss 6.567183\n",
      "Epoch 3579, Training loss 2.428642, Validation loss 6.567187\n",
      "Epoch 3580, Training loss 2.428642, Validation loss 6.567198\n",
      "Epoch 3581, Training loss 2.428642, Validation loss 6.567213\n",
      "Epoch 3582, Training loss 2.428642, Validation loss 6.567218\n",
      "Epoch 3583, Training loss 2.428643, Validation loss 6.567227\n",
      "Epoch 3584, Training loss 2.428643, Validation loss 6.567233\n",
      "Epoch 3585, Training loss 2.428643, Validation loss 6.567223\n",
      "Epoch 3586, Training loss 2.428643, Validation loss 6.567228\n",
      "Epoch 3587, Training loss 2.428643, Validation loss 6.567233\n",
      "Epoch 3588, Training loss 2.428641, Validation loss 6.567238\n",
      "Epoch 3589, Training loss 2.428643, Validation loss 6.567248\n",
      "Epoch 3590, Training loss 2.428642, Validation loss 6.567238\n",
      "Epoch 3591, Training loss 2.428642, Validation loss 6.567244\n",
      "Epoch 3592, Training loss 2.428643, Validation loss 6.567248\n",
      "Epoch 3593, Training loss 2.428641, Validation loss 6.567254\n",
      "Epoch 3594, Training loss 2.428642, Validation loss 6.567274\n",
      "Epoch 3595, Training loss 2.428643, Validation loss 6.567259\n",
      "Epoch 3596, Training loss 2.428642, Validation loss 6.567269\n",
      "Epoch 3597, Training loss 2.428642, Validation loss 6.567274\n",
      "Epoch 3598, Training loss 2.428643, Validation loss 6.567279\n",
      "Epoch 3599, Training loss 2.428642, Validation loss 6.567285\n",
      "Epoch 3600, Training loss 2.428641, Validation loss 6.567294\n",
      "Epoch 3601, Training loss 2.428642, Validation loss 6.567285\n",
      "Epoch 3602, Training loss 2.428642, Validation loss 6.567289\n",
      "Epoch 3603, Training loss 2.428642, Validation loss 6.567295\n",
      "Epoch 3604, Training loss 2.428641, Validation loss 6.567300\n",
      "Epoch 3605, Training loss 2.428641, Validation loss 6.567309\n",
      "Epoch 3606, Training loss 2.428642, Validation loss 6.567306\n",
      "Epoch 3607, Training loss 2.428641, Validation loss 6.567315\n",
      "Epoch 3608, Training loss 2.428641, Validation loss 6.567320\n",
      "Epoch 3609, Training loss 2.428642, Validation loss 6.567326\n",
      "Epoch 3610, Training loss 2.428640, Validation loss 6.567316\n",
      "Epoch 3611, Training loss 2.428641, Validation loss 6.567321\n",
      "Epoch 3612, Training loss 2.428642, Validation loss 6.567330\n",
      "Epoch 3613, Training loss 2.428641, Validation loss 6.567336\n",
      "Epoch 3614, Training loss 2.428641, Validation loss 6.567341\n",
      "Epoch 3615, Training loss 2.428642, Validation loss 6.567346\n",
      "Epoch 3616, Training loss 2.428642, Validation loss 6.567347\n",
      "Epoch 3617, Training loss 2.428641, Validation loss 6.567356\n",
      "Epoch 3618, Training loss 2.428640, Validation loss 6.567361\n",
      "Epoch 3619, Training loss 2.428640, Validation loss 6.567367\n",
      "Epoch 3620, Training loss 2.428642, Validation loss 6.567371\n",
      "Epoch 3621, Training loss 2.428641, Validation loss 6.567362\n",
      "Epoch 3622, Training loss 2.428641, Validation loss 6.567377\n",
      "Epoch 3623, Training loss 2.428641, Validation loss 6.567377\n",
      "Epoch 3624, Training loss 2.428640, Validation loss 6.567387\n",
      "Epoch 3625, Training loss 2.428642, Validation loss 6.567402\n",
      "Epoch 3626, Training loss 2.428641, Validation loss 6.567402\n",
      "Epoch 3627, Training loss 2.428639, Validation loss 6.567402\n",
      "Epoch 3628, Training loss 2.428640, Validation loss 6.567412\n",
      "Epoch 3629, Training loss 2.428639, Validation loss 6.567412\n",
      "Epoch 3630, Training loss 2.428641, Validation loss 6.567412\n",
      "Epoch 3631, Training loss 2.428640, Validation loss 6.567408\n",
      "Epoch 3632, Training loss 2.428641, Validation loss 6.567418\n",
      "Epoch 3633, Training loss 2.428641, Validation loss 6.567418\n",
      "Epoch 3634, Training loss 2.428641, Validation loss 6.567418\n",
      "Epoch 3635, Training loss 2.428640, Validation loss 6.567428\n",
      "Epoch 3636, Training loss 2.428641, Validation loss 6.567443\n",
      "Epoch 3637, Training loss 2.428639, Validation loss 6.567443\n",
      "Epoch 3638, Training loss 2.428641, Validation loss 6.567443\n",
      "Epoch 3639, Training loss 2.428639, Validation loss 6.567443\n",
      "Epoch 3640, Training loss 2.428640, Validation loss 6.567453\n",
      "Epoch 3641, Training loss 2.428638, Validation loss 6.567449\n",
      "Epoch 3642, Training loss 2.428640, Validation loss 6.567449\n",
      "Epoch 3643, Training loss 2.428640, Validation loss 6.567459\n",
      "Epoch 3644, Training loss 2.428641, Validation loss 6.567459\n",
      "Epoch 3645, Training loss 2.428640, Validation loss 6.567473\n",
      "Epoch 3646, Training loss 2.428641, Validation loss 6.567473\n",
      "Epoch 3647, Training loss 2.428640, Validation loss 6.567473\n",
      "Epoch 3648, Training loss 2.428640, Validation loss 6.567484\n",
      "Epoch 3649, Training loss 2.428640, Validation loss 6.567484\n",
      "Epoch 3650, Training loss 2.428641, Validation loss 6.567484\n",
      "Epoch 3651, Training loss 2.428639, Validation loss 6.567490\n",
      "Epoch 3652, Training loss 2.428640, Validation loss 6.567490\n",
      "Epoch 3653, Training loss 2.428639, Validation loss 6.567490\n",
      "Epoch 3654, Training loss 2.428641, Validation loss 6.567490\n",
      "Epoch 3655, Training loss 2.428640, Validation loss 6.567500\n",
      "Epoch 3656, Training loss 2.428640, Validation loss 6.567514\n",
      "Epoch 3657, Training loss 2.428639, Validation loss 6.567514\n",
      "Epoch 3658, Training loss 2.428639, Validation loss 6.567514\n",
      "Epoch 3659, Training loss 2.428640, Validation loss 6.567524\n",
      "Epoch 3660, Training loss 2.428640, Validation loss 6.567520\n",
      "Epoch 3661, Training loss 2.428639, Validation loss 6.567520\n",
      "Epoch 3662, Training loss 2.428639, Validation loss 6.567530\n",
      "Epoch 3663, Training loss 2.428639, Validation loss 6.567530\n",
      "Epoch 3664, Training loss 2.428638, Validation loss 6.567530\n",
      "Epoch 3665, Training loss 2.428639, Validation loss 6.567530\n",
      "Epoch 3666, Training loss 2.428640, Validation loss 6.567545\n",
      "Epoch 3667, Training loss 2.428639, Validation loss 6.567555\n",
      "Epoch 3668, Training loss 2.428640, Validation loss 6.567555\n",
      "Epoch 3669, Training loss 2.428639, Validation loss 6.567555\n",
      "Epoch 3670, Training loss 2.428638, Validation loss 6.567571\n",
      "Epoch 3671, Training loss 2.428639, Validation loss 6.567580\n",
      "Epoch 3672, Training loss 2.428639, Validation loss 6.567575\n",
      "Epoch 3673, Training loss 2.428639, Validation loss 6.567595\n",
      "Epoch 3674, Training loss 2.428639, Validation loss 6.567586\n",
      "Epoch 3675, Training loss 2.428638, Validation loss 6.567595\n",
      "Epoch 3676, Training loss 2.428639, Validation loss 6.567596\n",
      "Epoch 3677, Training loss 2.428639, Validation loss 6.567601\n",
      "Epoch 3678, Training loss 2.428639, Validation loss 6.567611\n",
      "Epoch 3679, Training loss 2.428640, Validation loss 6.567601\n",
      "Epoch 3680, Training loss 2.428639, Validation loss 6.567621\n",
      "Epoch 3681, Training loss 2.428639, Validation loss 6.567611\n",
      "Epoch 3682, Training loss 2.428639, Validation loss 6.567621\n",
      "Epoch 3683, Training loss 2.428638, Validation loss 6.567626\n",
      "Epoch 3684, Training loss 2.428638, Validation loss 6.567626\n",
      "Epoch 3685, Training loss 2.428638, Validation loss 6.567616\n",
      "Epoch 3686, Training loss 2.428639, Validation loss 6.567626\n",
      "Epoch 3687, Training loss 2.428638, Validation loss 6.567632\n",
      "Epoch 3688, Training loss 2.428639, Validation loss 6.567641\n",
      "Epoch 3689, Training loss 2.428638, Validation loss 6.567642\n",
      "Epoch 3690, Training loss 2.428637, Validation loss 6.567636\n",
      "Epoch 3691, Training loss 2.428638, Validation loss 6.567642\n",
      "Epoch 3692, Training loss 2.428638, Validation loss 6.567647\n",
      "Epoch 3693, Training loss 2.428639, Validation loss 6.567657\n",
      "Epoch 3694, Training loss 2.428639, Validation loss 6.567657\n",
      "Epoch 3695, Training loss 2.428638, Validation loss 6.567667\n",
      "Epoch 3696, Training loss 2.428638, Validation loss 6.567667\n",
      "Epoch 3697, Training loss 2.428638, Validation loss 6.567662\n",
      "Epoch 3698, Training loss 2.428637, Validation loss 6.567672\n",
      "Epoch 3699, Training loss 2.428638, Validation loss 6.567673\n",
      "Epoch 3700, Training loss 2.428639, Validation loss 6.567677\n",
      "Epoch 3701, Training loss 2.428637, Validation loss 6.567683\n",
      "Epoch 3702, Training loss 2.428638, Validation loss 6.567677\n",
      "Epoch 3703, Training loss 2.428639, Validation loss 6.567678\n",
      "Epoch 3704, Training loss 2.428638, Validation loss 6.567688\n",
      "Epoch 3705, Training loss 2.428638, Validation loss 6.567693\n",
      "Epoch 3706, Training loss 2.428638, Validation loss 6.567703\n",
      "Epoch 3707, Training loss 2.428638, Validation loss 6.567693\n",
      "Epoch 3708, Training loss 2.428638, Validation loss 6.567713\n",
      "Epoch 3709, Training loss 2.428638, Validation loss 6.567703\n",
      "Epoch 3710, Training loss 2.428638, Validation loss 6.567708\n",
      "Epoch 3711, Training loss 2.428638, Validation loss 6.567719\n",
      "Epoch 3712, Training loss 2.428638, Validation loss 6.567719\n",
      "Epoch 3713, Training loss 2.428638, Validation loss 6.567709\n",
      "Epoch 3714, Training loss 2.428638, Validation loss 6.567719\n",
      "Epoch 3715, Training loss 2.428637, Validation loss 6.567724\n",
      "Epoch 3716, Training loss 2.428638, Validation loss 6.567734\n",
      "Epoch 3717, Training loss 2.428638, Validation loss 6.567734\n",
      "Epoch 3718, Training loss 2.428638, Validation loss 6.567724\n",
      "Epoch 3719, Training loss 2.428638, Validation loss 6.567744\n",
      "Epoch 3720, Training loss 2.428638, Validation loss 6.567739\n",
      "Epoch 3721, Training loss 2.428637, Validation loss 6.567749\n",
      "Epoch 3722, Training loss 2.428637, Validation loss 6.567750\n",
      "Epoch 3723, Training loss 2.428638, Validation loss 6.567755\n",
      "Epoch 3724, Training loss 2.428637, Validation loss 6.567769\n",
      "Epoch 3725, Training loss 2.428635, Validation loss 6.567774\n",
      "Epoch 3726, Training loss 2.428638, Validation loss 6.567784\n",
      "Epoch 3727, Training loss 2.428638, Validation loss 6.567780\n",
      "Epoch 3728, Training loss 2.428638, Validation loss 6.567784\n",
      "Epoch 3729, Training loss 2.428637, Validation loss 6.567795\n",
      "Epoch 3730, Training loss 2.428638, Validation loss 6.567799\n",
      "Epoch 3731, Training loss 2.428638, Validation loss 6.567795\n",
      "Epoch 3732, Training loss 2.428638, Validation loss 6.567805\n",
      "Epoch 3733, Training loss 2.428637, Validation loss 6.567809\n",
      "Epoch 3734, Training loss 2.428637, Validation loss 6.567805\n",
      "Epoch 3735, Training loss 2.428636, Validation loss 6.567805\n",
      "Epoch 3736, Training loss 2.428637, Validation loss 6.567815\n",
      "Epoch 3737, Training loss 2.428637, Validation loss 6.567815\n",
      "Epoch 3738, Training loss 2.428638, Validation loss 6.567815\n",
      "Epoch 3739, Training loss 2.428637, Validation loss 6.567825\n",
      "Epoch 3740, Training loss 2.428637, Validation loss 6.567810\n",
      "Epoch 3741, Training loss 2.428638, Validation loss 6.567825\n",
      "Epoch 3742, Training loss 2.428637, Validation loss 6.567836\n",
      "Epoch 3743, Training loss 2.428637, Validation loss 6.567821\n",
      "Epoch 3744, Training loss 2.428637, Validation loss 6.567836\n",
      "Epoch 3745, Training loss 2.428636, Validation loss 6.567836\n",
      "Epoch 3746, Training loss 2.428637, Validation loss 6.567831\n",
      "Epoch 3747, Training loss 2.428637, Validation loss 6.567846\n",
      "Epoch 3748, Training loss 2.428636, Validation loss 6.567846\n",
      "Epoch 3749, Training loss 2.428637, Validation loss 6.567841\n",
      "Epoch 3750, Training loss 2.428636, Validation loss 6.567856\n",
      "Epoch 3751, Training loss 2.428636, Validation loss 6.567856\n",
      "Epoch 3752, Training loss 2.428637, Validation loss 6.567871\n",
      "Epoch 3753, Training loss 2.428637, Validation loss 6.567856\n",
      "Epoch 3754, Training loss 2.428637, Validation loss 6.567866\n",
      "Epoch 3755, Training loss 2.428636, Validation loss 6.567866\n",
      "Epoch 3756, Training loss 2.428636, Validation loss 6.567866\n",
      "Epoch 3757, Training loss 2.428637, Validation loss 6.567877\n",
      "Epoch 3758, Training loss 2.428636, Validation loss 6.567877\n",
      "Epoch 3759, Training loss 2.428636, Validation loss 6.567872\n",
      "Epoch 3760, Training loss 2.428636, Validation loss 6.567887\n",
      "Epoch 3761, Training loss 2.428636, Validation loss 6.567887\n",
      "Epoch 3762, Training loss 2.428638, Validation loss 6.567882\n",
      "Epoch 3763, Training loss 2.428638, Validation loss 6.567887\n",
      "Epoch 3764, Training loss 2.428636, Validation loss 6.567897\n",
      "Epoch 3765, Training loss 2.428636, Validation loss 6.567892\n",
      "Epoch 3766, Training loss 2.428635, Validation loss 6.567897\n",
      "Epoch 3767, Training loss 2.428637, Validation loss 6.567907\n",
      "Epoch 3768, Training loss 2.428637, Validation loss 6.567903\n",
      "Epoch 3769, Training loss 2.428637, Validation loss 6.567907\n",
      "Epoch 3770, Training loss 2.428636, Validation loss 6.567918\n",
      "Epoch 3771, Training loss 2.428636, Validation loss 6.567903\n",
      "Epoch 3772, Training loss 2.428635, Validation loss 6.567918\n",
      "Epoch 3773, Training loss 2.428636, Validation loss 6.567918\n",
      "Epoch 3774, Training loss 2.428637, Validation loss 6.567913\n",
      "Epoch 3775, Training loss 2.428636, Validation loss 6.567928\n",
      "Epoch 3776, Training loss 2.428636, Validation loss 6.567928\n",
      "Epoch 3777, Training loss 2.428636, Validation loss 6.567923\n",
      "Epoch 3778, Training loss 2.428636, Validation loss 6.567933\n",
      "Epoch 3779, Training loss 2.428636, Validation loss 6.567938\n",
      "Epoch 3780, Training loss 2.428636, Validation loss 6.567948\n",
      "Epoch 3781, Training loss 2.428635, Validation loss 6.567933\n",
      "Epoch 3782, Training loss 2.428636, Validation loss 6.567948\n",
      "Epoch 3783, Training loss 2.428638, Validation loss 6.567944\n",
      "Epoch 3784, Training loss 2.428636, Validation loss 6.567953\n",
      "Epoch 3785, Training loss 2.428636, Validation loss 6.567948\n",
      "Epoch 3786, Training loss 2.428635, Validation loss 6.567973\n",
      "Epoch 3787, Training loss 2.428636, Validation loss 6.567968\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3788, Training loss 2.428636, Validation loss 6.567973\n",
      "Epoch 3789, Training loss 2.428636, Validation loss 6.567978\n",
      "Epoch 3790, Training loss 2.428635, Validation loss 6.567984\n",
      "Epoch 3791, Training loss 2.428636, Validation loss 6.567978\n",
      "Epoch 3792, Training loss 2.428635, Validation loss 6.567984\n",
      "Epoch 3793, Training loss 2.428636, Validation loss 6.567988\n",
      "Epoch 3794, Training loss 2.428634, Validation loss 6.567994\n",
      "Epoch 3795, Training loss 2.428636, Validation loss 6.567999\n",
      "Epoch 3796, Training loss 2.428637, Validation loss 6.567994\n",
      "Epoch 3797, Training loss 2.428636, Validation loss 6.567999\n",
      "Epoch 3798, Training loss 2.428636, Validation loss 6.568004\n",
      "Epoch 3799, Training loss 2.428636, Validation loss 6.568009\n",
      "Epoch 3800, Training loss 2.428637, Validation loss 6.568004\n",
      "Epoch 3801, Training loss 2.428636, Validation loss 6.568009\n",
      "Epoch 3802, Training loss 2.428636, Validation loss 6.568014\n",
      "Epoch 3803, Training loss 2.428635, Validation loss 6.568019\n",
      "Epoch 3804, Training loss 2.428636, Validation loss 6.568025\n",
      "Epoch 3805, Training loss 2.428636, Validation loss 6.568024\n",
      "Epoch 3806, Training loss 2.428636, Validation loss 6.568029\n",
      "Epoch 3807, Training loss 2.428636, Validation loss 6.568034\n",
      "Epoch 3808, Training loss 2.428634, Validation loss 6.568039\n",
      "Epoch 3809, Training loss 2.428635, Validation loss 6.568034\n",
      "Epoch 3810, Training loss 2.428635, Validation loss 6.568039\n",
      "Epoch 3811, Training loss 2.428635, Validation loss 6.568045\n",
      "Epoch 3812, Training loss 2.428634, Validation loss 6.568049\n",
      "Epoch 3813, Training loss 2.428634, Validation loss 6.568045\n",
      "Epoch 3814, Training loss 2.428635, Validation loss 6.568049\n",
      "Epoch 3815, Training loss 2.428636, Validation loss 6.568055\n",
      "Epoch 3816, Training loss 2.428635, Validation loss 6.568045\n",
      "Epoch 3817, Training loss 2.428636, Validation loss 6.568050\n",
      "Epoch 3818, Training loss 2.428636, Validation loss 6.568055\n",
      "Epoch 3819, Training loss 2.428636, Validation loss 6.568050\n",
      "Epoch 3820, Training loss 2.428636, Validation loss 6.568055\n",
      "Epoch 3821, Training loss 2.428636, Validation loss 6.568060\n",
      "Epoch 3822, Training loss 2.428635, Validation loss 6.568066\n",
      "Epoch 3823, Training loss 2.428634, Validation loss 6.568060\n",
      "Epoch 3824, Training loss 2.428635, Validation loss 6.568066\n",
      "Epoch 3825, Training loss 2.428636, Validation loss 6.568070\n",
      "Epoch 3826, Training loss 2.428636, Validation loss 6.568076\n",
      "Epoch 3827, Training loss 2.428635, Validation loss 6.568081\n",
      "Epoch 3828, Training loss 2.428636, Validation loss 6.568076\n",
      "Epoch 3829, Training loss 2.428635, Validation loss 6.568081\n",
      "Epoch 3830, Training loss 2.428635, Validation loss 6.568086\n",
      "Epoch 3831, Training loss 2.428634, Validation loss 6.568091\n",
      "Epoch 3832, Training loss 2.428635, Validation loss 6.568086\n",
      "Epoch 3833, Training loss 2.428634, Validation loss 6.568091\n",
      "Epoch 3834, Training loss 2.428636, Validation loss 6.568096\n",
      "Epoch 3835, Training loss 2.428635, Validation loss 6.568101\n",
      "Epoch 3836, Training loss 2.428634, Validation loss 6.568107\n",
      "Epoch 3837, Training loss 2.428634, Validation loss 6.568101\n",
      "Epoch 3838, Training loss 2.428634, Validation loss 6.568107\n",
      "Epoch 3839, Training loss 2.428636, Validation loss 6.568111\n",
      "Epoch 3840, Training loss 2.428634, Validation loss 6.568117\n",
      "Epoch 3841, Training loss 2.428635, Validation loss 6.568111\n",
      "Epoch 3842, Training loss 2.428636, Validation loss 6.568121\n",
      "Epoch 3843, Training loss 2.428636, Validation loss 6.568127\n",
      "Epoch 3844, Training loss 2.428634, Validation loss 6.568131\n",
      "Epoch 3845, Training loss 2.428636, Validation loss 6.568137\n",
      "Epoch 3846, Training loss 2.428635, Validation loss 6.568131\n",
      "Epoch 3847, Training loss 2.428636, Validation loss 6.568137\n",
      "Epoch 3848, Training loss 2.428634, Validation loss 6.568142\n",
      "Epoch 3849, Training loss 2.428634, Validation loss 6.568147\n",
      "Epoch 3850, Training loss 2.428635, Validation loss 6.568142\n",
      "Epoch 3851, Training loss 2.428635, Validation loss 6.568147\n",
      "Epoch 3852, Training loss 2.428635, Validation loss 6.568132\n",
      "Epoch 3853, Training loss 2.428635, Validation loss 6.568152\n",
      "Epoch 3854, Training loss 2.428635, Validation loss 6.568157\n",
      "Epoch 3855, Training loss 2.428635, Validation loss 6.568172\n",
      "Epoch 3856, Training loss 2.428635, Validation loss 6.568168\n",
      "Epoch 3857, Training loss 2.428634, Validation loss 6.568168\n",
      "Epoch 3858, Training loss 2.428635, Validation loss 6.568163\n",
      "Epoch 3859, Training loss 2.428636, Validation loss 6.568172\n",
      "Epoch 3860, Training loss 2.428634, Validation loss 6.568168\n",
      "Epoch 3861, Training loss 2.428634, Validation loss 6.568168\n",
      "Epoch 3862, Training loss 2.428634, Validation loss 6.568182\n",
      "Epoch 3863, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3864, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3865, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3866, Training loss 2.428635, Validation loss 6.568173\n",
      "Epoch 3867, Training loss 2.428635, Validation loss 6.568188\n",
      "Epoch 3868, Training loss 2.428635, Validation loss 6.568188\n",
      "Epoch 3869, Training loss 2.428634, Validation loss 6.568188\n",
      "Epoch 3870, Training loss 2.428634, Validation loss 6.568203\n",
      "Epoch 3871, Training loss 2.428634, Validation loss 6.568198\n",
      "Epoch 3872, Training loss 2.428636, Validation loss 6.568198\n",
      "Epoch 3873, Training loss 2.428634, Validation loss 6.568213\n",
      "Epoch 3874, Training loss 2.428635, Validation loss 6.568213\n",
      "Epoch 3875, Training loss 2.428635, Validation loss 6.568209\n",
      "Epoch 3876, Training loss 2.428634, Validation loss 6.568209\n",
      "Epoch 3877, Training loss 2.428634, Validation loss 6.568204\n",
      "Epoch 3878, Training loss 2.428635, Validation loss 6.568223\n",
      "Epoch 3879, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3880, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3881, Training loss 2.428632, Validation loss 6.568223\n",
      "Epoch 3882, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3883, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3884, Training loss 2.428634, Validation loss 6.568219\n",
      "Epoch 3885, Training loss 2.428634, Validation loss 6.568233\n",
      "Epoch 3886, Training loss 2.428634, Validation loss 6.568229\n",
      "Epoch 3887, Training loss 2.428635, Validation loss 6.568229\n",
      "Epoch 3888, Training loss 2.428634, Validation loss 6.568229\n",
      "Epoch 3889, Training loss 2.428634, Validation loss 6.568224\n",
      "Epoch 3890, Training loss 2.428633, Validation loss 6.568239\n",
      "Epoch 3891, Training loss 2.428634, Validation loss 6.568239\n",
      "Epoch 3892, Training loss 2.428634, Validation loss 6.568239\n",
      "Epoch 3893, Training loss 2.428634, Validation loss 6.568254\n",
      "Epoch 3894, Training loss 2.428634, Validation loss 6.568250\n",
      "Epoch 3895, Training loss 2.428634, Validation loss 6.568250\n",
      "Epoch 3896, Training loss 2.428634, Validation loss 6.568245\n",
      "Epoch 3897, Training loss 2.428633, Validation loss 6.568245\n",
      "Epoch 3898, Training loss 2.428634, Validation loss 6.568260\n",
      "Epoch 3899, Training loss 2.428633, Validation loss 6.568260\n",
      "Epoch 3900, Training loss 2.428634, Validation loss 6.568255\n",
      "Epoch 3901, Training loss 2.428633, Validation loss 6.568260\n",
      "Epoch 3902, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3903, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3904, Training loss 2.428634, Validation loss 6.568274\n",
      "Epoch 3905, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3906, Training loss 2.428635, Validation loss 6.568270\n",
      "Epoch 3907, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3908, Training loss 2.428633, Validation loss 6.568265\n",
      "Epoch 3909, Training loss 2.428634, Validation loss 6.568280\n",
      "Epoch 3910, Training loss 2.428633, Validation loss 6.568280\n",
      "Epoch 3911, Training loss 2.428634, Validation loss 6.568280\n",
      "Epoch 3912, Training loss 2.428634, Validation loss 6.568295\n",
      "Epoch 3913, Training loss 2.428634, Validation loss 6.568291\n",
      "Epoch 3914, Training loss 2.428635, Validation loss 6.568291\n",
      "Epoch 3915, Training loss 2.428634, Validation loss 6.568305\n",
      "Epoch 3916, Training loss 2.428634, Validation loss 6.568305\n",
      "Epoch 3917, Training loss 2.428634, Validation loss 6.568300\n",
      "Epoch 3918, Training loss 2.428633, Validation loss 6.568300\n",
      "Epoch 3919, Training loss 2.428633, Validation loss 6.568295\n",
      "Epoch 3920, Training loss 2.428633, Validation loss 6.568311\n",
      "Epoch 3921, Training loss 2.428633, Validation loss 6.568311\n",
      "Epoch 3922, Training loss 2.428634, Validation loss 6.568311\n",
      "Epoch 3923, Training loss 2.428634, Validation loss 6.568316\n",
      "Epoch 3924, Training loss 2.428634, Validation loss 6.568311\n",
      "Epoch 3925, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3926, Training loss 2.428635, Validation loss 6.568321\n",
      "Epoch 3927, Training loss 2.428633, Validation loss 6.568316\n",
      "Epoch 3928, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3929, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3930, Training loss 2.428633, Validation loss 6.568321\n",
      "Epoch 3931, Training loss 2.428634, Validation loss 6.568316\n",
      "Epoch 3932, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3933, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3934, Training loss 2.428634, Validation loss 6.568341\n",
      "Epoch 3935, Training loss 2.428633, Validation loss 6.568346\n",
      "Epoch 3936, Training loss 2.428632, Validation loss 6.568356\n",
      "Epoch 3937, Training loss 2.428633, Validation loss 6.568361\n",
      "Epoch 3938, Training loss 2.428634, Validation loss 6.568366\n",
      "Epoch 3939, Training loss 2.428634, Validation loss 6.568371\n",
      "Epoch 3940, Training loss 2.428633, Validation loss 6.568361\n",
      "Epoch 3941, Training loss 2.428634, Validation loss 6.568371\n",
      "Epoch 3942, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3943, Training loss 2.428635, Validation loss 6.568371\n",
      "Epoch 3944, Training loss 2.428632, Validation loss 6.568381\n",
      "Epoch 3945, Training loss 2.428633, Validation loss 6.568371\n",
      "Epoch 3946, Training loss 2.428633, Validation loss 6.568377\n",
      "Epoch 3947, Training loss 2.428634, Validation loss 6.568381\n",
      "Epoch 3948, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3949, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3950, Training loss 2.428634, Validation loss 6.568387\n",
      "Epoch 3951, Training loss 2.428633, Validation loss 6.568377\n",
      "Epoch 3952, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3953, Training loss 2.428634, Validation loss 6.568387\n",
      "Epoch 3954, Training loss 2.428633, Validation loss 6.568397\n",
      "Epoch 3955, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3956, Training loss 2.428633, Validation loss 6.568397\n",
      "Epoch 3957, Training loss 2.428633, Validation loss 6.568402\n",
      "Epoch 3958, Training loss 2.428634, Validation loss 6.568397\n",
      "Epoch 3959, Training loss 2.428635, Validation loss 6.568402\n",
      "Epoch 3960, Training loss 2.428632, Validation loss 6.568392\n",
      "Epoch 3961, Training loss 2.428633, Validation loss 6.568402\n",
      "Epoch 3962, Training loss 2.428633, Validation loss 6.568402\n",
      "Epoch 3963, Training loss 2.428635, Validation loss 6.568412\n",
      "Epoch 3964, Training loss 2.428634, Validation loss 6.568422\n",
      "Epoch 3965, Training loss 2.428633, Validation loss 6.568412\n",
      "Epoch 3966, Training loss 2.428634, Validation loss 6.568418\n",
      "Epoch 3967, Training loss 2.428633, Validation loss 6.568412\n",
      "Epoch 3968, Training loss 2.428633, Validation loss 6.568418\n",
      "Epoch 3969, Training loss 2.428634, Validation loss 6.568418\n",
      "Epoch 3970, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 3971, Training loss 2.428633, Validation loss 6.568418\n",
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      "Epoch 3973, Training loss 2.428633, Validation loss 6.568418\n",
      "Epoch 3974, Training loss 2.428634, Validation loss 6.568428\n",
      "Epoch 3975, Training loss 2.428633, Validation loss 6.568433\n",
      "Epoch 3976, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 3977, Training loss 2.428633, Validation loss 6.568433\n",
      "Epoch 3978, Training loss 2.428634, Validation loss 6.568433\n",
      "Epoch 3979, Training loss 2.428632, Validation loss 6.568443\n",
      "Epoch 3980, Training loss 2.428634, Validation loss 6.568433\n",
      "Epoch 3981, Training loss 2.428632, Validation loss 6.568443\n",
      "Epoch 3982, Training loss 2.428634, Validation loss 6.568433\n",
      "Epoch 3983, Training loss 2.428631, Validation loss 6.568443\n",
      "Epoch 3984, Training loss 2.428633, Validation loss 6.568443\n",
      "Epoch 3985, Training loss 2.428634, Validation loss 6.568453\n",
      "Epoch 3986, Training loss 2.428633, Validation loss 6.568459\n",
      "Epoch 3987, Training loss 2.428633, Validation loss 6.568453\n",
      "Epoch 3988, Training loss 2.428632, Validation loss 6.568459\n",
      "Epoch 3989, Training loss 2.428633, Validation loss 6.568449\n",
      "Epoch 3990, Training loss 2.428634, Validation loss 6.568459\n",
      "Epoch 3991, Training loss 2.428632, Validation loss 6.568449\n",
      "Epoch 3992, Training loss 2.428633, Validation loss 6.568459\n",
      "Epoch 3993, Training loss 2.428633, Validation loss 6.568474\n",
      "Epoch 3994, Training loss 2.428632, Validation loss 6.568469\n",
      "Epoch 3995, Training loss 2.428632, Validation loss 6.568459\n",
      "Epoch 3996, Training loss 2.428633, Validation loss 6.568469\n",
      "Epoch 3997, Training loss 2.428634, Validation loss 6.568474\n",
      "Epoch 3998, Training loss 2.428634, Validation loss 6.568464\n",
      "Epoch 3999, Training loss 2.428632, Validation loss 6.568474\n",
      "Epoch 4000, Training loss 2.428634, Validation loss 6.568474\n",
      "Epoch 4001, Training loss 2.428633, Validation loss 6.568484\n",
      "Epoch 4002, Training loss 2.428632, Validation loss 6.568474\n",
      "Epoch 4003, Training loss 2.428632, Validation loss 6.568484\n",
      "Epoch 4004, Training loss 2.428632, Validation loss 6.568489\n",
      "Epoch 4005, Training loss 2.428633, Validation loss 6.568484\n",
      "Epoch 4006, Training loss 2.428632, Validation loss 6.568474\n",
      "Epoch 4007, Training loss 2.428632, Validation loss 6.568480\n",
      "Epoch 4008, Training loss 2.428632, Validation loss 6.568500\n",
      "Epoch 4009, Training loss 2.428634, Validation loss 6.568490\n",
      "Epoch 4010, Training loss 2.428633, Validation loss 6.568500\n",
      "Epoch 4011, Training loss 2.428633, Validation loss 6.568490\n",
      "Epoch 4012, Training loss 2.428632, Validation loss 6.568500\n",
      "Epoch 4013, Training loss 2.428634, Validation loss 6.568490\n",
      "Epoch 4014, Training loss 2.428633, Validation loss 6.568500\n",
      "Epoch 4015, Training loss 2.428633, Validation loss 6.568500\n",
      "Epoch 4016, Training loss 2.428632, Validation loss 6.568505\n",
      "Epoch 4017, Training loss 2.428632, Validation loss 6.568515\n",
      "Epoch 4018, Training loss 2.428632, Validation loss 6.568505\n",
      "Epoch 4019, Training loss 2.428633, Validation loss 6.568515\n",
      "Epoch 4020, Training loss 2.428632, Validation loss 6.568505\n",
      "Epoch 4021, Training loss 2.428633, Validation loss 6.568515\n",
      "Epoch 4022, Training loss 2.428633, Validation loss 6.568515\n",
      "Epoch 4023, Training loss 2.428632, Validation loss 6.568525\n",
      "Epoch 4024, Training loss 2.428632, Validation loss 6.568530\n",
      "Epoch 4025, Training loss 2.428633, Validation loss 6.568525\n",
      "Epoch 4026, Training loss 2.428633, Validation loss 6.568530\n",
      "Epoch 4027, Training loss 2.428632, Validation loss 6.568521\n",
      "Epoch 4028, Training loss 2.428632, Validation loss 6.568530\n",
      "Epoch 4029, Training loss 2.428633, Validation loss 6.568521\n",
      "Epoch 4030, Training loss 2.428632, Validation loss 6.568530\n",
      "Epoch 4031, Training loss 2.428632, Validation loss 6.568541\n",
      "Epoch 4032, Training loss 2.428633, Validation loss 6.568541\n",
      "Epoch 4033, Training loss 2.428632, Validation loss 6.568545\n",
      "Epoch 4034, Training loss 2.428632, Validation loss 6.568545\n",
      "Epoch 4035, Training loss 2.428633, Validation loss 6.568555\n",
      "Epoch 4036, Training loss 2.428633, Validation loss 6.568555\n",
      "Epoch 4037, Training loss 2.428633, Validation loss 6.568555\n",
      "Epoch 4038, Training loss 2.428634, Validation loss 6.568570\n",
      "Epoch 4039, Training loss 2.428632, Validation loss 6.568570\n",
      "Epoch 4040, Training loss 2.428633, Validation loss 6.568570\n",
      "Epoch 4041, Training loss 2.428632, Validation loss 6.568570\n",
      "Epoch 4042, Training loss 2.428633, Validation loss 6.568565\n",
      "Epoch 4043, Training loss 2.428632, Validation loss 6.568565\n",
      "Epoch 4044, Training loss 2.428632, Validation loss 6.568570\n",
      "Epoch 4045, Training loss 2.428633, Validation loss 6.568581\n",
      "Epoch 4046, Training loss 2.428631, Validation loss 6.568581\n",
      "Epoch 4047, Training loss 2.428633, Validation loss 6.568565\n",
      "Epoch 4048, Training loss 2.428632, Validation loss 6.568576\n",
      "Epoch 4049, Training loss 2.428632, Validation loss 6.568576\n",
      "Epoch 4050, Training loss 2.428633, Validation loss 6.568581\n",
      "Epoch 4051, Training loss 2.428632, Validation loss 6.568581\n",
      "Epoch 4052, Training loss 2.428633, Validation loss 6.568591\n",
      "Epoch 4053, Training loss 2.428633, Validation loss 6.568591\n",
      "Epoch 4054, Training loss 2.428633, Validation loss 6.568586\n",
      "Epoch 4055, Training loss 2.428634, Validation loss 6.568586\n",
      "Epoch 4056, Training loss 2.428631, Validation loss 6.568586\n",
      "Epoch 4057, Training loss 2.428633, Validation loss 6.568591\n",
      "Epoch 4058, Training loss 2.428632, Validation loss 6.568601\n",
      "Epoch 4059, Training loss 2.428633, Validation loss 6.568586\n",
      "Epoch 4060, Training loss 2.428632, Validation loss 6.568586\n",
      "Epoch 4061, Training loss 2.428632, Validation loss 6.568596\n",
      "Epoch 4062, Training loss 2.428633, Validation loss 6.568596\n",
      "Epoch 4063, Training loss 2.428631, Validation loss 6.568601\n",
      "Epoch 4064, Training loss 2.428632, Validation loss 6.568601\n",
      "Epoch 4065, Training loss 2.428632, Validation loss 6.568611\n",
      "Epoch 4066, Training loss 2.428632, Validation loss 6.568596\n",
      "Epoch 4067, Training loss 2.428633, Validation loss 6.568596\n",
      "Epoch 4068, Training loss 2.428632, Validation loss 6.568606\n",
      "Epoch 4069, Training loss 2.428633, Validation loss 6.568611\n",
      "Epoch 4070, Training loss 2.428632, Validation loss 6.568611\n",
      "Epoch 4071, Training loss 2.428633, Validation loss 6.568611\n",
      "Epoch 4072, Training loss 2.428632, Validation loss 6.568622\n",
      "Epoch 4073, Training loss 2.428631, Validation loss 6.568606\n",
      "Epoch 4074, Training loss 2.428633, Validation loss 6.568617\n",
      "Epoch 4075, Training loss 2.428633, Validation loss 6.568617\n",
      "Epoch 4076, Training loss 2.428632, Validation loss 6.568622\n",
      "Epoch 4077, Training loss 2.428633, Validation loss 6.568622\n",
      "Epoch 4078, Training loss 2.428632, Validation loss 6.568617\n",
      "Epoch 4079, Training loss 2.428632, Validation loss 6.568617\n",
      "Epoch 4080, Training loss 2.428632, Validation loss 6.568617\n",
      "Epoch 4081, Training loss 2.428632, Validation loss 6.568627\n",
      "Epoch 4082, Training loss 2.428633, Validation loss 6.568632\n",
      "Epoch 4083, Training loss 2.428632, Validation loss 6.568632\n",
      "Epoch 4084, Training loss 2.428632, Validation loss 6.568632\n",
      "Epoch 4085, Training loss 2.428632, Validation loss 6.568642\n",
      "Epoch 4086, Training loss 2.428632, Validation loss 6.568627\n",
      "Epoch 4087, Training loss 2.428632, Validation loss 6.568627\n",
      "Epoch 4088, Training loss 2.428632, Validation loss 6.568642\n",
      "Epoch 4089, Training loss 2.428632, Validation loss 6.568642\n",
      "Epoch 4090, Training loss 2.428632, Validation loss 6.568642\n",
      "Epoch 4091, Training loss 2.428632, Validation loss 6.568637\n",
      "Epoch 4092, Training loss 2.428632, Validation loss 6.568637\n",
      "Epoch 4093, Training loss 2.428632, Validation loss 6.568637\n",
      "Epoch 4094, Training loss 2.428632, Validation loss 6.568647\n",
      "Epoch 4095, Training loss 2.428632, Validation loss 6.568652\n",
      "Epoch 4096, Training loss 2.428632, Validation loss 6.568652\n",
      "Epoch 4097, Training loss 2.428632, Validation loss 6.568652\n",
      "Epoch 4098, Training loss 2.428633, Validation loss 6.568647\n",
      "Epoch 4099, Training loss 2.428632, Validation loss 6.568647\n",
      "Epoch 4100, Training loss 2.428632, Validation loss 6.568647\n",
      "Epoch 4101, Training loss 2.428633, Validation loss 6.568662\n",
      "Epoch 4102, Training loss 2.428631, Validation loss 6.568662\n",
      "Epoch 4103, Training loss 2.428632, Validation loss 6.568647\n",
      "Epoch 4104, Training loss 2.428632, Validation loss 6.568657\n",
      "Epoch 4105, Training loss 2.428632, Validation loss 6.568657\n",
      "Epoch 4106, Training loss 2.428632, Validation loss 6.568657\n",
      "Epoch 4107, Training loss 2.428633, Validation loss 6.568672\n",
      "Epoch 4108, Training loss 2.428631, Validation loss 6.568672\n",
      "Epoch 4109, Training loss 2.428632, Validation loss 6.568672\n",
      "Epoch 4110, Training loss 2.428632, Validation loss 6.568667\n",
      "Epoch 4111, Training loss 2.428632, Validation loss 6.568667\n",
      "Epoch 4112, Training loss 2.428632, Validation loss 6.568667\n",
      "Epoch 4113, Training loss 2.428632, Validation loss 6.568667\n",
      "Epoch 4114, Training loss 2.428633, Validation loss 6.568683\n",
      "Epoch 4115, Training loss 2.428633, Validation loss 6.568683\n",
      "Epoch 4116, Training loss 2.428631, Validation loss 6.568683\n",
      "Epoch 4117, Training loss 2.428632, Validation loss 6.568678\n",
      "Epoch 4118, Training loss 2.428631, Validation loss 6.568678\n",
      "Epoch 4119, Training loss 2.428632, Validation loss 6.568678\n",
      "Epoch 4120, Training loss 2.428632, Validation loss 6.568683\n",
      "Epoch 4121, Training loss 2.428632, Validation loss 6.568693\n",
      "Epoch 4122, Training loss 2.428632, Validation loss 6.568678\n",
      "Epoch 4123, Training loss 2.428632, Validation loss 6.568678\n",
      "Epoch 4124, Training loss 2.428632, Validation loss 6.568688\n",
      "Epoch 4125, Training loss 2.428632, Validation loss 6.568688\n",
      "Epoch 4126, Training loss 2.428632, Validation loss 6.568693\n",
      "Epoch 4127, Training loss 2.428633, Validation loss 6.568703\n",
      "Epoch 4128, Training loss 2.428632, Validation loss 6.568703\n",
      "Epoch 4129, Training loss 2.428633, Validation loss 6.568703\n",
      "Epoch 4130, Training loss 2.428632, Validation loss 6.568698\n",
      "Epoch 4131, Training loss 2.428632, Validation loss 6.568698\n",
      "Epoch 4132, Training loss 2.428632, Validation loss 6.568698\n",
      "Epoch 4133, Training loss 2.428632, Validation loss 6.568703\n",
      "Epoch 4134, Training loss 2.428632, Validation loss 6.568694\n",
      "Epoch 4135, Training loss 2.428632, Validation loss 6.568698\n",
      "Epoch 4136, Training loss 2.428632, Validation loss 6.568698\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4137, Training loss 2.428632, Validation loss 6.568708\n",
      "Epoch 4138, Training loss 2.428632, Validation loss 6.568708\n",
      "Epoch 4139, Training loss 2.428632, Validation loss 6.568713\n",
      "Epoch 4140, Training loss 2.428632, Validation loss 6.568713\n",
      "Epoch 4141, Training loss 2.428632, Validation loss 6.568708\n",
      "Epoch 4142, Training loss 2.428632, Validation loss 6.568708\n",
      "Epoch 4143, Training loss 2.428632, Validation loss 6.568719\n",
      "Epoch 4144, Training loss 2.428634, Validation loss 6.568719\n",
      "Epoch 4145, Training loss 2.428632, Validation loss 6.568724\n",
      "Epoch 4146, Training loss 2.428632, Validation loss 6.568724\n",
      "Epoch 4147, Training loss 2.428633, Validation loss 6.568734\n",
      "Epoch 4148, Training loss 2.428631, Validation loss 6.568719\n",
      "Epoch 4149, Training loss 2.428633, Validation loss 6.568719\n",
      "Epoch 4150, Training loss 2.428632, Validation loss 6.568729\n",
      "Epoch 4151, Training loss 2.428632, Validation loss 6.568729\n",
      "Epoch 4152, Training loss 2.428632, Validation loss 6.568734\n",
      "Epoch 4153, Training loss 2.428632, Validation loss 6.568734\n",
      "Epoch 4154, Training loss 2.428633, Validation loss 6.568739\n",
      "Epoch 4155, Training loss 2.428631, Validation loss 6.568748\n",
      "Epoch 4156, Training loss 2.428632, Validation loss 6.568744\n",
      "Epoch 4157, Training loss 2.428632, Validation loss 6.568739\n",
      "Epoch 4158, Training loss 2.428631, Validation loss 6.568748\n",
      "Epoch 4159, Training loss 2.428632, Validation loss 6.568754\n",
      "Epoch 4160, Training loss 2.428632, Validation loss 6.568744\n",
      "Epoch 4161, Training loss 2.428632, Validation loss 6.568749\n",
      "Epoch 4162, Training loss 2.428632, Validation loss 6.568754\n",
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      "Epoch 4164, Training loss 2.428631, Validation loss 6.568759\n",
      "Epoch 4165, Training loss 2.428632, Validation loss 6.568764\n",
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      "Epoch 4167, Training loss 2.428632, Validation loss 6.568764\n",
      "Epoch 4168, Training loss 2.428632, Validation loss 6.568754\n",
      "Epoch 4169, Training loss 2.428632, Validation loss 6.568760\n",
      "Epoch 4170, Training loss 2.428632, Validation loss 6.568754\n",
      "Epoch 4171, Training loss 2.428631, Validation loss 6.568760\n",
      "Epoch 4172, Training loss 2.428632, Validation loss 6.568754\n",
      "Epoch 4173, Training loss 2.428632, Validation loss 6.568755\n",
      "Epoch 4174, Training loss 2.428632, Validation loss 6.568769\n",
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      "Epoch 4180, Training loss 2.428632, Validation loss 6.568779\n",
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      "Epoch 4183, Training loss 2.428632, Validation loss 6.568770\n",
      "Epoch 4184, Training loss 2.428632, Validation loss 6.568775\n",
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      "Epoch 4189, Training loss 2.428631, Validation loss 6.568775\n",
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      "Epoch 4199, Training loss 2.428632, Validation loss 6.568790\n",
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      "Epoch 4201, Training loss 2.428632, Validation loss 6.568790\n",
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      "Epoch 4203, Training loss 2.428632, Validation loss 6.568805\n",
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      "Epoch 4206, Training loss 2.428631, Validation loss 6.568795\n",
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      "Epoch 4208, Training loss 2.428632, Validation loss 6.568806\n",
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      "Epoch 4210, Training loss 2.428632, Validation loss 6.568806\n",
      "Epoch 4211, Training loss 2.428630, Validation loss 6.568796\n",
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      "Epoch 4307, Training loss 2.428631, Validation loss 6.568913\n",
      "Epoch 4308, Training loss 2.428631, Validation loss 6.568908\n",
      "Epoch 4309, Training loss 2.428631, Validation loss 6.568913\n",
      "Epoch 4310, Training loss 2.428632, Validation loss 6.568913\n",
      "Epoch 4311, Training loss 2.428631, Validation loss 6.568918\n",
      "Epoch 4312, Training loss 2.428631, Validation loss 6.568923\n",
      "Epoch 4313, Training loss 2.428632, Validation loss 6.568928\n",
      "Epoch 4314, Training loss 2.428631, Validation loss 6.568923\n",
      "Epoch 4315, Training loss 2.428632, Validation loss 6.568933\n",
      "Epoch 4316, Training loss 2.428631, Validation loss 6.568928\n",
      "Epoch 4317, Training loss 2.428631, Validation loss 6.568943\n",
      "Epoch 4318, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4319, Training loss 2.428631, Validation loss 6.568943\n",
      "Epoch 4320, Training loss 2.428631, Validation loss 6.568943\n",
      "Epoch 4321, Training loss 2.428632, Validation loss 6.568948\n",
      "Epoch 4322, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4323, Training loss 2.428630, Validation loss 6.568958\n",
      "Epoch 4324, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4325, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4326, Training loss 2.428632, Validation loss 6.568938\n",
      "Epoch 4327, Training loss 2.428630, Validation loss 6.568943\n",
      "Epoch 4328, Training loss 2.428632, Validation loss 6.568938\n",
      "Epoch 4329, Training loss 2.428630, Validation loss 6.568953\n",
      "Epoch 4330, Training loss 2.428630, Validation loss 6.568938\n",
      "Epoch 4331, Training loss 2.428632, Validation loss 6.568953\n",
      "Epoch 4332, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4333, Training loss 2.428631, Validation loss 6.568949\n",
      "Epoch 4334, Training loss 2.428632, Validation loss 6.568953\n",
      "Epoch 4335, Training loss 2.428632, Validation loss 6.568949\n",
      "Epoch 4336, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4337, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4338, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4339, Training loss 2.428632, Validation loss 6.568953\n",
      "Epoch 4340, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4341, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4342, Training loss 2.428631, Validation loss 6.568949\n",
      "Epoch 4343, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4344, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4345, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4346, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4347, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4348, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4349, Training loss 2.428632, Validation loss 6.568959\n",
      "Epoch 4350, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4351, Training loss 2.428632, Validation loss 6.568963\n",
      "Epoch 4352, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4353, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4354, Training loss 2.428632, Validation loss 6.568959\n",
      "Epoch 4355, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4356, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4357, Training loss 2.428630, Validation loss 6.568974\n",
      "Epoch 4358, Training loss 2.428632, Validation loss 6.568974\n",
      "Epoch 4359, Training loss 2.428632, Validation loss 6.568959\n",
      "Epoch 4360, Training loss 2.428632, Validation loss 6.568974\n",
      "Epoch 4361, Training loss 2.428632, Validation loss 6.568969\n",
      "Epoch 4362, Training loss 2.428630, Validation loss 6.568974\n",
      "Epoch 4363, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4364, Training loss 2.428631, Validation loss 6.568969\n",
      "Epoch 4365, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4366, Training loss 2.428631, Validation loss 6.568969\n",
      "Epoch 4367, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4368, Training loss 2.428631, Validation loss 6.568969\n",
      "Epoch 4369, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4370, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4371, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4372, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4373, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4374, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4375, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4376, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4377, Training loss 2.428631, Validation loss 6.568984\n",
      "Epoch 4378, Training loss 2.428632, Validation loss 6.568999\n",
      "Epoch 4379, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4380, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4381, Training loss 2.428632, Validation loss 6.568994\n",
      "Epoch 4382, Training loss 2.428632, Validation loss 6.568984\n",
      "Epoch 4383, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4384, Training loss 2.428630, Validation loss 6.568994\n",
      "Epoch 4385, Training loss 2.428632, Validation loss 6.568979\n",
      "Epoch 4386, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4387, Training loss 2.428630, Validation loss 6.568990\n",
      "Epoch 4388, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4389, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4390, Training loss 2.428631, Validation loss 6.568990\n",
      "Epoch 4391, Training loss 2.428632, Validation loss 6.568994\n",
      "Epoch 4392, Training loss 2.428632, Validation loss 6.568990\n",
      "Epoch 4393, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4394, Training loss 2.428630, Validation loss 6.568994\n",
      "Epoch 4395, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4396, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4397, Training loss 2.428630, Validation loss 6.568990\n",
      "Epoch 4398, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4399, Training loss 2.428632, Validation loss 6.568990\n",
      "Epoch 4400, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4401, Training loss 2.428630, Validation loss 6.569004\n",
      "Epoch 4402, Training loss 2.428631, Validation loss 6.569004\n",
      "Epoch 4403, Training loss 2.428630, Validation loss 6.569004\n",
      "Epoch 4404, Training loss 2.428631, Validation loss 6.569000\n",
      "Epoch 4405, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4406, Training loss 2.428631, Validation loss 6.569000\n",
      "Epoch 4407, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4408, Training loss 2.428632, Validation loss 6.569004\n",
      "Epoch 4409, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4410, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4411, Training loss 2.428631, Validation loss 6.569000\n",
      "Epoch 4412, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4413, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4414, Training loss 2.428630, Validation loss 6.569015\n",
      "Epoch 4415, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4416, Training loss 2.428631, Validation loss 6.569010\n",
      "Epoch 4417, Training loss 2.428630, Validation loss 6.569015\n",
      "Epoch 4418, Training loss 2.428632, Validation loss 6.569010\n",
      "Epoch 4419, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4420, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4421, Training loss 2.428630, Validation loss 6.569010\n",
      "Epoch 4422, Training loss 2.428632, Validation loss 6.569015\n",
      "Epoch 4423, Training loss 2.428632, Validation loss 6.569010\n",
      "Epoch 4424, Training loss 2.428630, Validation loss 6.569025\n",
      "Epoch 4425, Training loss 2.428631, Validation loss 6.569010\n",
      "Epoch 4426, Training loss 2.428632, Validation loss 6.569010\n",
      "Epoch 4427, Training loss 2.428631, Validation loss 6.569025\n",
      "Epoch 4428, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4429, Training loss 2.428632, Validation loss 6.569025\n",
      "Epoch 4430, Training loss 2.428631, Validation loss 6.569020\n",
      "Epoch 4431, Training loss 2.428631, Validation loss 6.569025\n",
      "Epoch 4432, Training loss 2.428633, Validation loss 6.569025\n",
      "Epoch 4433, Training loss 2.428631, Validation loss 6.569025\n",
      "Epoch 4434, Training loss 2.428630, Validation loss 6.569025\n",
      "Epoch 4435, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4436, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4437, Training loss 2.428631, Validation loss 6.569020\n",
      "Epoch 4438, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4439, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4440, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4441, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4442, Training loss 2.428632, Validation loss 6.569039\n",
      "Epoch 4443, Training loss 2.428631, Validation loss 6.569035\n",
      "Epoch 4444, Training loss 2.428630, Validation loss 6.569030\n",
      "Epoch 4445, Training loss 2.428630, Validation loss 6.569030\n",
      "Epoch 4446, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4447, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4448, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4449, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4450, Training loss 2.428631, Validation loss 6.569045\n",
      "Epoch 4451, Training loss 2.428632, Validation loss 6.569035\n",
      "Epoch 4452, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4453, Training loss 2.428630, Validation loss 6.569045\n",
      "Epoch 4454, Training loss 2.428630, Validation loss 6.569030\n",
      "Epoch 4455, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4456, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4457, Training loss 2.428631, Validation loss 6.569045\n",
      "Epoch 4458, Training loss 2.428630, Validation loss 6.569045\n",
      "Epoch 4459, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4460, Training loss 2.428631, Validation loss 6.569045\n",
      "Epoch 4461, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4462, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4463, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4464, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4465, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4466, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4467, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4468, Training loss 2.428630, Validation loss 6.569040\n",
      "Epoch 4469, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4470, Training loss 2.428632, Validation loss 6.569056\n",
      "Epoch 4471, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4472, Training loss 2.428632, Validation loss 6.569056\n",
      "Epoch 4473, Training loss 2.428631, Validation loss 6.569051\n",
      "Epoch 4474, Training loss 2.428630, Validation loss 6.569056\n",
      "Epoch 4475, Training loss 2.428631, Validation loss 6.569051\n",
      "Epoch 4476, Training loss 2.428631, Validation loss 6.569051\n",
      "Epoch 4477, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4478, Training loss 2.428630, Validation loss 6.569051\n",
      "Epoch 4479, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4480, Training loss 2.428632, Validation loss 6.569051\n",
      "Epoch 4481, Training loss 2.428630, Validation loss 6.569066\n",
      "Epoch 4482, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4483, Training loss 2.428632, Validation loss 6.569051\n",
      "Epoch 4484, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4485, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4486, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4487, Training loss 2.428630, Validation loss 6.569061\n",
      "Epoch 4488, Training loss 2.428632, Validation loss 6.569066\n",
      "Epoch 4489, Training loss 2.428632, Validation loss 6.569066\n",
      "Epoch 4490, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4491, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4492, Training loss 2.428633, Validation loss 6.569061\n",
      "Epoch 4493, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4494, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4495, Training loss 2.428632, Validation loss 6.569076\n",
      "Epoch 4496, Training loss 2.428632, Validation loss 6.569076\n",
      "Epoch 4497, Training loss 2.428632, Validation loss 6.569061\n",
      "Epoch 4498, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4499, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4500, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4501, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4502, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4503, Training loss 2.428631, Validation loss 6.569076\n",
      "Epoch 4504, Training loss 2.428630, Validation loss 6.569071\n",
      "Epoch 4505, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4506, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4507, Training loss 2.428630, Validation loss 6.569086\n",
      "Epoch 4508, Training loss 2.428630, Validation loss 6.569086\n",
      "Epoch 4509, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4510, Training loss 2.428631, Validation loss 6.569086\n",
      "Epoch 4511, Training loss 2.428632, Validation loss 6.569081\n",
      "Epoch 4512, Training loss 2.428631, Validation loss 6.569086\n",
      "Epoch 4513, Training loss 2.428630, Validation loss 6.569081\n",
      "Epoch 4514, Training loss 2.428630, Validation loss 6.569081\n",
      "Epoch 4515, Training loss 2.428631, Validation loss 6.569086\n",
      "Epoch 4516, Training loss 2.428632, Validation loss 6.569081\n",
      "Epoch 4517, Training loss 2.428632, Validation loss 6.569086\n",
      "Epoch 4518, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4519, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4520, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4521, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4522, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4523, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4524, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4525, Training loss 2.428631, Validation loss 6.569092\n",
      "Epoch 4526, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4527, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4528, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4529, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4530, Training loss 2.428632, Validation loss 6.569092\n",
      "Epoch 4531, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4532, Training loss 2.428631, Validation loss 6.569092\n",
      "Epoch 4533, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4534, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4535, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4536, Training loss 2.428632, Validation loss 6.569107\n",
      "Epoch 4537, Training loss 2.428631, Validation loss 6.569092\n",
      "Epoch 4538, Training loss 2.428630, Validation loss 6.569092\n",
      "Epoch 4539, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4540, Training loss 2.428632, Validation loss 6.569092\n",
      "Epoch 4541, Training loss 2.428630, Validation loss 6.569107\n",
      "Epoch 4542, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4543, Training loss 2.428632, Validation loss 6.569107\n",
      "Epoch 4544, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4545, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4546, Training loss 2.428631, Validation loss 6.569107\n",
      "Epoch 4547, Training loss 2.428630, Validation loss 6.569102\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4548, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4549, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4550, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4551, Training loss 2.428630, Validation loss 6.569112\n",
      "Epoch 4552, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4553, Training loss 2.428632, Validation loss 6.569127\n",
      "Epoch 4554, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4555, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4556, Training loss 2.428630, Validation loss 6.569117\n",
      "Epoch 4557, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4558, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4559, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4560, Training loss 2.428630, Validation loss 6.569122\n",
      "Epoch 4561, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4562, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4563, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4564, Training loss 2.428630, Validation loss 6.569132\n",
      "Epoch 4565, Training loss 2.428631, Validation loss 6.569141\n",
      "Epoch 4566, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4567, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4568, Training loss 2.428632, Validation loss 6.569122\n",
      "Epoch 4569, Training loss 2.428631, Validation loss 6.569132\n",
      "Epoch 4570, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4571, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4572, Training loss 2.428631, Validation loss 6.569141\n",
      "Epoch 4573, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4574, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4575, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4576, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4577, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4578, Training loss 2.428631, Validation loss 6.569141\n",
      "Epoch 4579, Training loss 2.428632, Validation loss 6.569147\n",
      "Epoch 4580, Training loss 2.428632, Validation loss 6.569137\n",
      "Epoch 4581, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4582, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4583, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4584, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4585, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4586, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4587, Training loss 2.428632, Validation loss 6.569142\n",
      "Epoch 4588, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4589, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4590, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4591, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4592, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4593, Training loss 2.428632, Validation loss 6.569157\n",
      "Epoch 4594, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4595, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4596, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4597, Training loss 2.428630, Validation loss 6.569157\n",
      "Epoch 4598, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4599, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4600, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4601, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4602, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4603, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4604, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4605, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4606, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4607, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4608, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4609, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4610, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4611, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4612, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4613, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4614, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4615, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4616, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4617, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4618, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4619, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4620, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4621, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4622, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4623, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4624, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4625, Training loss 2.428630, Validation loss 6.569152\n",
      "Epoch 4626, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4627, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4628, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4629, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4630, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4631, Training loss 2.428630, Validation loss 6.569152\n",
      "Epoch 4632, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4633, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4634, Training loss 2.428632, Validation loss 6.569172\n",
      "Epoch 4635, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4636, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4637, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4638, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4639, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4640, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4641, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4642, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4643, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4644, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4645, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4646, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4647, Training loss 2.428632, Validation loss 6.569167\n",
      "Epoch 4648, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4649, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4650, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4651, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4652, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4653, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4654, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4655, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4656, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4657, Training loss 2.428631, Validation loss 6.569173\n",
      "Epoch 4658, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4659, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4660, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4661, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4662, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4663, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4664, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4665, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4666, Training loss 2.428632, Validation loss 6.569182\n",
      "Epoch 4667, Training loss 2.428632, Validation loss 6.569173\n",
      "Epoch 4668, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4669, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4670, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4671, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4672, Training loss 2.428632, Validation loss 6.569182\n",
      "Epoch 4673, Training loss 2.428632, Validation loss 6.569173\n",
      "Epoch 4674, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4675, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4676, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4677, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4678, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4679, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4680, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4681, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4682, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4683, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4684, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4685, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4686, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4687, Training loss 2.428632, Validation loss 6.569183\n",
      "Epoch 4688, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4689, Training loss 2.428630, Validation loss 6.569188\n",
      "Epoch 4690, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4691, Training loss 2.428630, Validation loss 6.569183\n",
      "Epoch 4692, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4693, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4694, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4695, Training loss 2.428632, Validation loss 6.569183\n",
      "Epoch 4696, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4697, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4698, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4699, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4700, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4701, Training loss 2.428630, Validation loss 6.569183\n",
      "Epoch 4702, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4703, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4704, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4705, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4706, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4707, Training loss 2.428631, Validation loss 6.569198\n",
      "Epoch 4708, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4709, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4710, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4711, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4712, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4713, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4714, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4715, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4716, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4717, Training loss 2.428630, Validation loss 6.569198\n",
      "Epoch 4718, Training loss 2.428630, Validation loss 6.569188\n",
      "Epoch 4719, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4720, Training loss 2.428632, Validation loss 6.569203\n",
      "Epoch 4721, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4722, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4723, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4724, Training loss 2.428632, Validation loss 6.569203\n",
      "Epoch 4725, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4726, Training loss 2.428632, Validation loss 6.569199\n",
      "Epoch 4727, Training loss 2.428630, Validation loss 6.569198\n",
      "Epoch 4728, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4729, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4730, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4731, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4732, Training loss 2.428632, Validation loss 6.569203\n",
      "Epoch 4733, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4734, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4735, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4736, Training loss 2.428631, Validation loss 6.569199\n",
      "Epoch 4737, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4738, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4739, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4740, Training loss 2.428631, Validation loss 6.569199\n",
      "Epoch 4741, Training loss 2.428632, Validation loss 6.569208\n",
      "Epoch 4742, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4743, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4744, Training loss 2.428630, Validation loss 6.569213\n",
      "Epoch 4745, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4746, Training loss 2.428630, Validation loss 6.569199\n",
      "Epoch 4747, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4748, Training loss 2.428630, Validation loss 6.569194\n",
      "Epoch 4749, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4750, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4751, Training loss 2.428631, Validation loss 6.569208\n",
      "Epoch 4752, Training loss 2.428631, Validation loss 6.569199\n",
      "Epoch 4753, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4754, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4755, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4756, Training loss 2.428631, Validation loss 6.569209\n",
      "Epoch 4757, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4758, Training loss 2.428630, Validation loss 6.569213\n",
      "Epoch 4759, Training loss 2.428630, Validation loss 6.569203\n",
      "Epoch 4760, Training loss 2.428631, Validation loss 6.569209\n",
      "Epoch 4761, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4762, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4763, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4764, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4765, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4766, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4767, Training loss 2.428632, Validation loss 6.569214\n",
      "Epoch 4768, Training loss 2.428631, Validation loss 6.569213\n",
      "Epoch 4769, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4770, Training loss 2.428630, Validation loss 6.569209\n",
      "Epoch 4771, Training loss 2.428631, Validation loss 6.569214\n",
      "Epoch 4772, Training loss 2.428630, Validation loss 6.569223\n",
      "Epoch 4773, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4774, Training loss 2.428632, Validation loss 6.569209\n",
      "Epoch 4775, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4776, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4777, Training loss 2.428631, Validation loss 6.569214\n",
      "Epoch 4778, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4779, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4780, Training loss 2.428631, Validation loss 6.569209\n",
      "Epoch 4781, Training loss 2.428632, Validation loss 6.569214\n",
      "Epoch 4782, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4783, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4784, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4785, Training loss 2.428630, Validation loss 6.569214\n",
      "Epoch 4786, Training loss 2.428632, Validation loss 6.569223\n",
      "Epoch 4787, Training loss 2.428632, Validation loss 6.569214\n",
      "Epoch 4788, Training loss 2.428632, Validation loss 6.569219\n",
      "Epoch 4789, Training loss 2.428632, Validation loss 6.569229\n",
      "Epoch 4790, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4791, Training loss 2.428631, Validation loss 6.569214\n",
      "Epoch 4792, Training loss 2.428630, Validation loss 6.569223\n",
      "Epoch 4793, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4794, Training loss 2.428631, Validation loss 6.569219\n",
      "Epoch 4795, Training loss 2.428632, Validation loss 6.569224\n",
      "Epoch 4796, Training loss 2.428631, Validation loss 6.569223\n",
      "Epoch 4797, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4798, Training loss 2.428630, Validation loss 6.569219\n",
      "Epoch 4799, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4800, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4801, Training loss 2.428632, Validation loss 6.569224\n",
      "Epoch 4802, Training loss 2.428631, Validation loss 6.569219\n",
      "Epoch 4803, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4804, Training loss 2.428631, Validation loss 6.569219\n",
      "Epoch 4805, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4806, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4807, Training loss 2.428630, Validation loss 6.569224\n",
      "Epoch 4808, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4809, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4810, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4811, Training loss 2.428630, Validation loss 6.569224\n",
      "Epoch 4812, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4813, Training loss 2.428632, Validation loss 6.569239\n",
      "Epoch 4814, Training loss 2.428632, Validation loss 6.569229\n",
      "Epoch 4815, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4816, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4817, Training loss 2.428631, Validation loss 6.569220\n",
      "Epoch 4818, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4819, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4820, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4821, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4822, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4823, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4824, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4825, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4826, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4827, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4828, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4829, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4830, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4831, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4832, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4833, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4834, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4835, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4836, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4837, Training loss 2.428630, Validation loss 6.569239\n",
      "Epoch 4838, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4839, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4840, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4841, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4842, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4843, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4844, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4845, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4846, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4847, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4848, Training loss 2.428632, Validation loss 6.569244\n",
      "Epoch 4849, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4850, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4851, Training loss 2.428631, Validation loss 6.569249\n",
      "Epoch 4852, Training loss 2.428630, Validation loss 6.569254\n",
      "Epoch 4853, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4854, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4855, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4856, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4857, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4858, Training loss 2.428631, Validation loss 6.569254\n",
      "Epoch 4859, Training loss 2.428630, Validation loss 6.569249\n",
      "Epoch 4860, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4861, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4862, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4863, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4864, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4865, Training loss 2.428630, Validation loss 6.569249\n",
      "Epoch 4866, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4867, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4868, Training loss 2.428632, Validation loss 6.569254\n",
      "Epoch 4869, Training loss 2.428632, Validation loss 6.569244\n",
      "Epoch 4870, Training loss 2.428632, Validation loss 6.569250\n",
      "Epoch 4871, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4872, Training loss 2.428630, Validation loss 6.569254\n",
      "Epoch 4873, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4874, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4875, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4876, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4877, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4878, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4879, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4880, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4881, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4882, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4883, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4884, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4885, Training loss 2.428629, Validation loss 6.569255\n",
      "Epoch 4886, Training loss 2.428629, Validation loss 6.569245\n",
      "Epoch 4887, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4888, Training loss 2.428632, Validation loss 6.569260\n",
      "Epoch 4889, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4890, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4891, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4892, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4893, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4894, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4895, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4896, Training loss 2.428632, Validation loss 6.569264\n",
      "Epoch 4897, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4898, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4899, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4900, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4901, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4902, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4903, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4904, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4905, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4906, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4907, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4908, Training loss 2.428632, Validation loss 6.569260\n",
      "Epoch 4909, Training loss 2.428632, Validation loss 6.569265\n",
      "Epoch 4910, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4911, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4912, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4913, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4914, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4915, Training loss 2.428632, Validation loss 6.569265\n",
      "Epoch 4916, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4917, Training loss 2.428631, Validation loss 6.569270\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4918, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4919, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4920, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4921, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4922, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4923, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4924, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4925, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4926, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4927, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4928, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4929, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4930, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4931, Training loss 2.428630, Validation loss 6.569280\n",
      "Epoch 4932, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4933, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4934, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4935, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4936, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4937, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4938, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4939, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4940, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4941, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4942, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4943, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4944, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4945, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4946, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4947, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4948, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4949, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4950, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4951, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4952, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4953, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4954, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4955, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4956, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4957, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4958, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4959, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4960, Training loss 2.428630, Validation loss 6.569281\n",
      "Epoch 4961, Training loss 2.428632, Validation loss 6.569285\n",
      "Epoch 4962, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4963, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4964, Training loss 2.428631, Validation loss 6.569281\n",
      "Epoch 4965, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4966, Training loss 2.428630, Validation loss 6.569295\n",
      "Epoch 4967, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4968, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4969, Training loss 2.428632, Validation loss 6.569290\n",
      "Epoch 4970, Training loss 2.428632, Validation loss 6.569281\n",
      "Epoch 4971, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4972, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4973, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4974, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4975, Training loss 2.428632, Validation loss 6.569290\n",
      "Epoch 4976, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4977, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4978, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4979, Training loss 2.428630, Validation loss 6.569300\n",
      "Epoch 4980, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4981, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4982, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4983, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4984, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4985, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 4986, Training loss 2.428630, Validation loss 6.569295\n",
      "Epoch 4987, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4988, Training loss 2.428632, Validation loss 6.569291\n",
      "Epoch 4989, Training loss 2.428631, Validation loss 6.569300\n",
      "Epoch 4990, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4991, Training loss 2.428630, Validation loss 6.569296\n",
      "Epoch 4992, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4993, Training loss 2.428630, Validation loss 6.569281\n",
      "Epoch 4994, Training loss 2.428630, Validation loss 6.569291\n",
      "Epoch 4995, Training loss 2.428632, Validation loss 6.569296\n",
      "Epoch 4996, Training loss 2.428631, Validation loss 6.569305\n",
      "Epoch 4997, Training loss 2.428631, Validation loss 6.569296\n",
      "Epoch 4998, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4999, Training loss 2.428630, Validation loss 6.569296\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(nepochs):\n",
    "    \n",
    "    # forward pass\n",
    "    t_p_train = model(t_un_train)\n",
    "    loss_train = loss_fn(t_p_train, t_c_train)\n",
    "\n",
    "    with torch.no_grad():\n",
    "        t_p_val = model(t_un_val)\n",
    "        loss_val = loss_fn(t_p_val, t_c_val)\n",
    "\n",
    "    print('Epoch %d, Training loss %f, Validation loss %f' % (epoch, float(loss_train), float(loss_val)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss_train.backward()    \n",
    "    optimizer.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Parameter containing:\n",
       " tensor([[5.4878]], requires_grad=True), Parameter containing:\n",
       " tensor([-17.4613], requires_grad=True))"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.weight, model.bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_fn = nn.MSELoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Training loss 103.222046, Validation loss 50.142578\n",
      "Epoch 1, Training loss 48.570103, Validation loss 3.796587\n",
      "Epoch 2, Training loss 39.051891, Validation loss 0.447808\n",
      "Epoch 3, Training loss 37.296520, Validation loss 1.792198\n",
      "Epoch 4, Training loss 36.876732, Validation loss 2.822379\n",
      "Epoch 5, Training loss 36.687138, Validation loss 3.333092\n",
      "Epoch 6, Training loss 36.537609, Validation loss 3.561284\n",
      "Epoch 7, Training loss 36.395458, Validation loss 3.660715\n",
      "Epoch 8, Training loss 36.255051, Validation loss 3.704718\n",
      "Epoch 9, Training loss 36.115433, Validation loss 3.725378\n",
      "Epoch 10, Training loss 35.976421, Validation loss 3.736291\n",
      "Epoch 11, Training loss 35.837982, Validation loss 3.743140\n",
      "Epoch 12, Training loss 35.700115, Validation loss 3.748306\n",
      "Epoch 13, Training loss 35.562820, Validation loss 3.752771\n",
      "Epoch 14, Training loss 35.426094, Validation loss 3.756952\n",
      "Epoch 15, Training loss 35.289936, Validation loss 3.761003\n",
      "Epoch 16, Training loss 35.154335, Validation loss 3.765011\n",
      "Epoch 17, Training loss 35.019299, Validation loss 3.768989\n",
      "Epoch 18, Training loss 34.884808, Validation loss 3.772966\n",
      "Epoch 19, Training loss 34.750885, Validation loss 3.776943\n",
      "Epoch 20, Training loss 34.617508, Validation loss 3.780907\n",
      "Epoch 21, Training loss 34.484684, Validation loss 3.784876\n",
      "Epoch 22, Training loss 34.352406, Validation loss 3.788838\n",
      "Epoch 23, Training loss 34.220673, Validation loss 3.792802\n",
      "Epoch 24, Training loss 34.089485, Validation loss 3.796766\n",
      "Epoch 25, Training loss 33.958836, Validation loss 3.800728\n",
      "Epoch 26, Training loss 33.828732, Validation loss 3.804693\n",
      "Epoch 27, Training loss 33.699165, Validation loss 3.808653\n",
      "Epoch 28, Training loss 33.570129, Validation loss 3.812611\n",
      "Epoch 29, Training loss 33.441616, Validation loss 3.816569\n",
      "Epoch 30, Training loss 33.313652, Validation loss 3.820530\n",
      "Epoch 31, Training loss 33.186199, Validation loss 3.824485\n",
      "Epoch 32, Training loss 33.059284, Validation loss 3.828444\n",
      "Epoch 33, Training loss 32.932884, Validation loss 3.832393\n",
      "Epoch 34, Training loss 32.807014, Validation loss 3.836344\n",
      "Epoch 35, Training loss 32.681660, Validation loss 3.840302\n",
      "Epoch 36, Training loss 32.556824, Validation loss 3.844252\n",
      "Epoch 37, Training loss 32.432503, Validation loss 3.848203\n",
      "Epoch 38, Training loss 32.308689, Validation loss 3.852152\n",
      "Epoch 39, Training loss 32.185394, Validation loss 3.856102\n",
      "Epoch 40, Training loss 32.062603, Validation loss 3.860045\n",
      "Epoch 41, Training loss 31.940323, Validation loss 3.863989\n",
      "Epoch 42, Training loss 31.818537, Validation loss 3.867930\n",
      "Epoch 43, Training loss 31.697266, Validation loss 3.871871\n",
      "Epoch 44, Training loss 31.576487, Validation loss 3.875816\n",
      "Epoch 45, Training loss 31.456217, Validation loss 3.879753\n",
      "Epoch 46, Training loss 31.336432, Validation loss 3.883693\n",
      "Epoch 47, Training loss 31.217148, Validation loss 3.887629\n",
      "Epoch 48, Training loss 31.098352, Validation loss 3.891566\n",
      "Epoch 49, Training loss 30.980051, Validation loss 3.895500\n",
      "Epoch 50, Training loss 30.862234, Validation loss 3.899430\n",
      "Epoch 51, Training loss 30.744904, Validation loss 3.903362\n",
      "Epoch 52, Training loss 30.628054, Validation loss 3.907286\n",
      "Epoch 53, Training loss 30.511694, Validation loss 3.911216\n",
      "Epoch 54, Training loss 30.395811, Validation loss 3.915143\n",
      "Epoch 55, Training loss 30.280407, Validation loss 3.919067\n",
      "Epoch 56, Training loss 30.165476, Validation loss 3.922989\n",
      "Epoch 57, Training loss 30.051029, Validation loss 3.926913\n",
      "Epoch 58, Training loss 29.937040, Validation loss 3.930829\n",
      "Epoch 59, Training loss 29.823528, Validation loss 3.934743\n",
      "Epoch 60, Training loss 29.710489, Validation loss 3.938656\n",
      "Epoch 61, Training loss 29.597910, Validation loss 3.942571\n",
      "Epoch 62, Training loss 29.485796, Validation loss 3.946483\n",
      "Epoch 63, Training loss 29.374147, Validation loss 3.950394\n",
      "Epoch 64, Training loss 29.262957, Validation loss 3.954301\n",
      "Epoch 65, Training loss 29.152227, Validation loss 3.958210\n",
      "Epoch 66, Training loss 29.041960, Validation loss 3.962113\n",
      "Epoch 67, Training loss 28.932137, Validation loss 3.966015\n",
      "Epoch 68, Training loss 28.822769, Validation loss 3.969916\n",
      "Epoch 69, Training loss 28.713856, Validation loss 3.973814\n",
      "Epoch 70, Training loss 28.605392, Validation loss 3.977712\n",
      "Epoch 71, Training loss 28.497375, Validation loss 3.981610\n",
      "Epoch 72, Training loss 28.389799, Validation loss 3.985498\n",
      "Epoch 73, Training loss 28.282673, Validation loss 3.989385\n",
      "Epoch 74, Training loss 28.175991, Validation loss 3.993273\n",
      "Epoch 75, Training loss 28.069750, Validation loss 3.997164\n",
      "Epoch 76, Training loss 27.963940, Validation loss 4.001048\n",
      "Epoch 77, Training loss 27.858572, Validation loss 4.004923\n",
      "Epoch 78, Training loss 27.753635, Validation loss 4.008808\n",
      "Epoch 79, Training loss 27.649130, Validation loss 4.012687\n",
      "Epoch 80, Training loss 27.545063, Validation loss 4.016564\n",
      "Epoch 81, Training loss 27.441420, Validation loss 4.020441\n",
      "Epoch 82, Training loss 27.338203, Validation loss 4.024303\n",
      "Epoch 83, Training loss 27.235420, Validation loss 4.028172\n",
      "Epoch 84, Training loss 27.133051, Validation loss 4.032037\n",
      "Epoch 85, Training loss 27.031113, Validation loss 4.035903\n",
      "Epoch 86, Training loss 26.929598, Validation loss 4.039762\n",
      "Epoch 87, Training loss 26.828489, Validation loss 4.043624\n",
      "Epoch 88, Training loss 26.727808, Validation loss 4.047487\n",
      "Epoch 89, Training loss 26.627539, Validation loss 4.051342\n",
      "Epoch 90, Training loss 26.527681, Validation loss 4.055195\n",
      "Epoch 91, Training loss 26.428242, Validation loss 4.059042\n",
      "Epoch 92, Training loss 26.329205, Validation loss 4.062891\n",
      "Epoch 93, Training loss 26.230583, Validation loss 4.066734\n",
      "Epoch 94, Training loss 26.132364, Validation loss 4.070577\n",
      "Epoch 95, Training loss 26.034552, Validation loss 4.074419\n",
      "Epoch 96, Training loss 25.937145, Validation loss 4.078254\n",
      "Epoch 97, Training loss 25.840139, Validation loss 4.082090\n",
      "Epoch 98, Training loss 25.743532, Validation loss 4.085925\n",
      "Epoch 99, Training loss 25.647322, Validation loss 4.089756\n",
      "Epoch 100, Training loss 25.551512, Validation loss 4.093582\n",
      "Epoch 101, Training loss 25.456099, Validation loss 4.097404\n",
      "Epoch 102, Training loss 25.361076, Validation loss 4.101230\n",
      "Epoch 103, Training loss 25.266445, Validation loss 4.105048\n",
      "Epoch 104, Training loss 25.172207, Validation loss 4.108870\n",
      "Epoch 105, Training loss 25.078358, Validation loss 4.112683\n",
      "Epoch 106, Training loss 24.984894, Validation loss 4.116500\n",
      "Epoch 107, Training loss 24.891815, Validation loss 4.120301\n",
      "Epoch 108, Training loss 24.799122, Validation loss 4.124114\n",
      "Epoch 109, Training loss 24.706814, Validation loss 4.127913\n",
      "Epoch 110, Training loss 24.614887, Validation loss 4.131716\n",
      "Epoch 111, Training loss 24.523333, Validation loss 4.135515\n",
      "Epoch 112, Training loss 24.432161, Validation loss 4.139308\n",
      "Epoch 113, Training loss 24.341370, Validation loss 4.143102\n",
      "Epoch 114, Training loss 24.250946, Validation loss 4.146894\n",
      "Epoch 115, Training loss 24.160896, Validation loss 4.150682\n",
      "Epoch 116, Training loss 24.071218, Validation loss 4.154470\n",
      "Epoch 117, Training loss 23.981911, Validation loss 4.158252\n",
      "Epoch 118, Training loss 23.892973, Validation loss 4.162030\n",
      "Epoch 119, Training loss 23.804405, Validation loss 4.165802\n",
      "Epoch 120, Training loss 23.716200, Validation loss 4.169583\n",
      "Epoch 121, Training loss 23.628359, Validation loss 4.173349\n",
      "Epoch 122, Training loss 23.540876, Validation loss 4.177112\n",
      "Epoch 123, Training loss 23.453756, Validation loss 4.180877\n",
      "Epoch 124, Training loss 23.366999, Validation loss 4.184641\n",
      "Epoch 125, Training loss 23.280598, Validation loss 4.188404\n",
      "Epoch 126, Training loss 23.194553, Validation loss 4.192154\n",
      "Epoch 127, Training loss 23.108862, Validation loss 4.195915\n",
      "Epoch 128, Training loss 23.023527, Validation loss 4.199662\n",
      "Epoch 129, Training loss 22.938540, Validation loss 4.203405\n",
      "Epoch 130, Training loss 22.853912, Validation loss 4.207150\n",
      "Epoch 131, Training loss 22.769627, Validation loss 4.210894\n",
      "Epoch 132, Training loss 22.685692, Validation loss 4.214629\n",
      "Epoch 133, Training loss 22.602102, Validation loss 4.218366\n",
      "Epoch 134, Training loss 22.518856, Validation loss 4.222098\n",
      "Epoch 135, Training loss 22.435959, Validation loss 4.225824\n",
      "Epoch 136, Training loss 22.353399, Validation loss 4.229554\n",
      "Epoch 137, Training loss 22.271177, Validation loss 4.233274\n",
      "Epoch 138, Training loss 22.189299, Validation loss 4.236992\n",
      "Epoch 139, Training loss 22.107758, Validation loss 4.240709\n",
      "Epoch 140, Training loss 22.026556, Validation loss 4.244420\n",
      "Epoch 141, Training loss 21.945688, Validation loss 4.248134\n",
      "Epoch 142, Training loss 21.865149, Validation loss 4.251842\n",
      "Epoch 143, Training loss 21.784946, Validation loss 4.255548\n",
      "Epoch 144, Training loss 21.705070, Validation loss 4.259249\n",
      "Epoch 145, Training loss 21.625528, Validation loss 4.262948\n",
      "Epoch 146, Training loss 21.546314, Validation loss 4.266641\n",
      "Epoch 147, Training loss 21.467426, Validation loss 4.270333\n",
      "Epoch 148, Training loss 21.388863, Validation loss 4.274018\n",
      "Epoch 149, Training loss 21.310625, Validation loss 4.277699\n",
      "Epoch 150, Training loss 21.232712, Validation loss 4.281376\n",
      "Epoch 151, Training loss 21.155115, Validation loss 4.285061\n",
      "Epoch 152, Training loss 21.077843, Validation loss 4.288734\n",
      "Epoch 153, Training loss 21.000887, Validation loss 4.292403\n",
      "Epoch 154, Training loss 20.924252, Validation loss 4.296070\n",
      "Epoch 155, Training loss 20.847931, Validation loss 4.299734\n",
      "Epoch 156, Training loss 20.771923, Validation loss 4.303403\n",
      "Epoch 157, Training loss 20.696234, Validation loss 4.307056\n",
      "Epoch 158, Training loss 20.620852, Validation loss 4.310718\n",
      "Epoch 159, Training loss 20.545786, Validation loss 4.314362\n",
      "Epoch 160, Training loss 20.471025, Validation loss 4.318015\n",
      "Epoch 161, Training loss 20.396570, Validation loss 4.321659\n",
      "Epoch 162, Training loss 20.322426, Validation loss 4.325299\n",
      "Epoch 163, Training loss 20.248590, Validation loss 4.328939\n",
      "Epoch 164, Training loss 20.175056, Validation loss 4.332572\n",
      "Epoch 165, Training loss 20.101828, Validation loss 4.336202\n",
      "Epoch 166, Training loss 20.028898, Validation loss 4.339830\n",
      "Epoch 167, Training loss 19.956274, Validation loss 4.343451\n",
      "Epoch 168, Training loss 19.883951, Validation loss 4.347071\n",
      "Epoch 169, Training loss 19.811920, Validation loss 4.350688\n",
      "Epoch 170, Training loss 19.740187, Validation loss 4.354302\n",
      "Epoch 171, Training loss 19.668755, Validation loss 4.357918\n",
      "Epoch 172, Training loss 19.597614, Validation loss 4.361532\n",
      "Epoch 173, Training loss 19.526768, Validation loss 4.365130\n",
      "Epoch 174, Training loss 19.456213, Validation loss 4.368731\n",
      "Epoch 175, Training loss 19.385950, Validation loss 4.372325\n",
      "Epoch 176, Training loss 19.315977, Validation loss 4.375920\n",
      "Epoch 177, Training loss 19.246290, Validation loss 4.379508\n",
      "Epoch 178, Training loss 19.176893, Validation loss 4.383094\n",
      "Epoch 179, Training loss 19.107782, Validation loss 4.386677\n",
      "Epoch 180, Training loss 19.038958, Validation loss 4.390257\n",
      "Epoch 181, Training loss 18.970417, Validation loss 4.393831\n",
      "Epoch 182, Training loss 18.902159, Validation loss 4.397406\n",
      "Epoch 183, Training loss 18.834179, Validation loss 4.400970\n",
      "Epoch 184, Training loss 18.766485, Validation loss 4.404536\n",
      "Epoch 185, Training loss 18.699068, Validation loss 4.408093\n",
      "Epoch 186, Training loss 18.631929, Validation loss 4.411653\n",
      "Epoch 187, Training loss 18.565069, Validation loss 4.415202\n",
      "Epoch 188, Training loss 18.498482, Validation loss 4.418756\n",
      "Epoch 189, Training loss 18.432169, Validation loss 4.422306\n",
      "Epoch 190, Training loss 18.366133, Validation loss 4.425846\n",
      "Epoch 191, Training loss 18.300367, Validation loss 4.429391\n",
      "Epoch 192, Training loss 18.234869, Validation loss 4.432924\n",
      "Epoch 193, Training loss 18.169649, Validation loss 4.436454\n",
      "Epoch 194, Training loss 18.104698, Validation loss 4.439986\n",
      "Epoch 195, Training loss 18.040010, Validation loss 4.443506\n",
      "Epoch 196, Training loss 17.975590, Validation loss 4.447028\n",
      "Epoch 197, Training loss 17.911438, Validation loss 4.450545\n",
      "Epoch 198, Training loss 17.847549, Validation loss 4.454060\n",
      "Epoch 199, Training loss 17.783922, Validation loss 4.457568\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 413, Training loss 8.766699, Validation loss 5.117292\n",
      "Epoch 414, Training loss 8.740545, Validation loss 5.119931\n",
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      "Epoch 445, Training loss 7.981165, Validation loss 5.199984\n",
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      "Epoch 466, Training loss 7.519354, Validation loss 5.252060\n",
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      "Epoch 468, Training loss 7.477426, Validation loss 5.256935\n",
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      "Epoch 817, Training loss 3.621119, Validation loss 5.897459\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 818, Training loss 3.616199, Validation loss 5.898781\n",
      "Epoch 819, Training loss 3.611297, Validation loss 5.900107\n",
      "Epoch 820, Training loss 3.606420, Validation loss 5.901421\n",
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      "Epoch 830, Training loss 3.558712, Validation loss 5.914449\n",
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      "Epoch 900, Training loss 3.274696, Validation loss 5.999148\n",
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      "Epoch 1144, Training loss 2.737111, Validation loss 6.219589\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1145, Training loss 2.735838, Validation loss 6.220299\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1424, Training loss 2.525548, Validation loss 6.371286\n",
      "Epoch 1425, Training loss 2.525146, Validation loss 6.371689\n",
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      "Epoch 1837, Training loss 2.446196, Validation loss 6.484422\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1838, Training loss 2.446125, Validation loss 6.484589\n",
      "Epoch 1839, Training loss 2.446052, Validation loss 6.484760\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2173, Training loss 2.433007, Validation loss 6.526864\n",
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      "Epoch 2565, Training loss 2.429496, Validation loss 6.550464\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2566, Training loss 2.429492, Validation loss 6.550499\n",
      "Epoch 2567, Training loss 2.429491, Validation loss 6.550545\n",
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      "Epoch 2695, Training loss 2.429137, Validation loss 6.554930\n",
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      "Epoch 2899, Training loss 2.428848, Validation loss 6.559909\n",
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      "Epoch 2941, Training loss 2.428813, Validation loss 6.560695\n",
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      "Epoch 2943, Training loss 2.428812, Validation loss 6.560725\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2944, Training loss 2.428812, Validation loss 6.560751\n",
      "Epoch 2945, Training loss 2.428812, Validation loss 6.560766\n",
      "Epoch 2946, Training loss 2.428810, Validation loss 6.560791\n",
      "Epoch 2947, Training loss 2.428809, Validation loss 6.560802\n",
      "Epoch 2948, Training loss 2.428809, Validation loss 6.560827\n",
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      "Epoch 2950, Training loss 2.428806, Validation loss 6.560853\n",
      "Epoch 2951, Training loss 2.428805, Validation loss 6.560874\n",
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      "Epoch 2958, Training loss 2.428801, Validation loss 6.561006\n",
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      "Epoch 2965, Training loss 2.428796, Validation loss 6.561123\n",
      "Epoch 2966, Training loss 2.428796, Validation loss 6.561128\n",
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      "Epoch 2969, Training loss 2.428793, Validation loss 6.561194\n",
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      "Epoch 2987, Training loss 2.428783, Validation loss 6.561490\n",
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      "Epoch 2990, Training loss 2.428780, Validation loss 6.561536\n",
      "Epoch 2991, Training loss 2.428779, Validation loss 6.561547\n",
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      "Epoch 2994, Training loss 2.428778, Validation loss 6.561612\n",
      "Epoch 2995, Training loss 2.428776, Validation loss 6.561617\n",
      "Epoch 2996, Training loss 2.428776, Validation loss 6.561638\n",
      "Epoch 2997, Training loss 2.428775, Validation loss 6.561663\n",
      "Epoch 2998, Training loss 2.428774, Validation loss 6.561668\n",
      "Epoch 2999, Training loss 2.428774, Validation loss 6.561674\n",
      "Epoch 3000, Training loss 2.428774, Validation loss 6.561699\n",
      "Epoch 3001, Training loss 2.428774, Validation loss 6.561709\n",
      "Epoch 3002, Training loss 2.428773, Validation loss 6.561730\n",
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      "Epoch 3005, Training loss 2.428771, Validation loss 6.561790\n",
      "Epoch 3006, Training loss 2.428771, Validation loss 6.561791\n",
      "Epoch 3007, Training loss 2.428770, Validation loss 6.561806\n",
      "Epoch 3008, Training loss 2.428769, Validation loss 6.561836\n",
      "Epoch 3009, Training loss 2.428768, Validation loss 6.561837\n",
      "Epoch 3010, Training loss 2.428768, Validation loss 6.561852\n",
      "Epoch 3011, Training loss 2.428767, Validation loss 6.561872\n",
      "Epoch 3012, Training loss 2.428767, Validation loss 6.561888\n",
      "Epoch 3013, Training loss 2.428765, Validation loss 6.561898\n",
      "Epoch 3014, Training loss 2.428766, Validation loss 6.561918\n",
      "Epoch 3015, Training loss 2.428765, Validation loss 6.561934\n",
      "Epoch 3016, Training loss 2.428765, Validation loss 6.561944\n",
      "Epoch 3017, Training loss 2.428765, Validation loss 6.561965\n",
      "Epoch 3018, Training loss 2.428763, Validation loss 6.561975\n",
      "Epoch 3019, Training loss 2.428763, Validation loss 6.561995\n",
      "Epoch 3020, Training loss 2.428763, Validation loss 6.562005\n",
      "Epoch 3021, Training loss 2.428762, Validation loss 6.562016\n",
      "Epoch 3022, Training loss 2.428762, Validation loss 6.562036\n",
      "Epoch 3023, Training loss 2.428762, Validation loss 6.562046\n",
      "Epoch 3024, Training loss 2.428761, Validation loss 6.562057\n",
      "Epoch 3025, Training loss 2.428760, Validation loss 6.562077\n",
      "Epoch 3026, Training loss 2.428760, Validation loss 6.562087\n",
      "Epoch 3027, Training loss 2.428758, Validation loss 6.562108\n",
      "Epoch 3028, Training loss 2.428758, Validation loss 6.562118\n",
      "Epoch 3029, Training loss 2.428759, Validation loss 6.562138\n",
      "Epoch 3030, Training loss 2.428757, Validation loss 6.562168\n",
      "Epoch 3031, Training loss 2.428758, Validation loss 6.562173\n",
      "Epoch 3032, Training loss 2.428757, Validation loss 6.562203\n",
      "Epoch 3033, Training loss 2.428756, Validation loss 6.562204\n",
      "Epoch 3034, Training loss 2.428755, Validation loss 6.562219\n",
      "Epoch 3035, Training loss 2.428754, Validation loss 6.562239\n",
      "Epoch 3036, Training loss 2.428753, Validation loss 6.562250\n",
      "Epoch 3037, Training loss 2.428755, Validation loss 6.562265\n",
      "Epoch 3038, Training loss 2.428753, Validation loss 6.562270\n",
      "Epoch 3039, Training loss 2.428753, Validation loss 6.562301\n",
      "Epoch 3040, Training loss 2.428752, Validation loss 6.562301\n",
      "Epoch 3041, Training loss 2.428751, Validation loss 6.562316\n",
      "Epoch 3042, Training loss 2.428751, Validation loss 6.562337\n",
      "Epoch 3043, Training loss 2.428752, Validation loss 6.562352\n",
      "Epoch 3044, Training loss 2.428750, Validation loss 6.562377\n",
      "Epoch 3045, Training loss 2.428750, Validation loss 6.562397\n",
      "Epoch 3046, Training loss 2.428749, Validation loss 6.562393\n",
      "Epoch 3047, Training loss 2.428749, Validation loss 6.562418\n",
      "Epoch 3048, Training loss 2.428748, Validation loss 6.562423\n",
      "Epoch 3049, Training loss 2.428747, Validation loss 6.562449\n",
      "Epoch 3050, Training loss 2.428748, Validation loss 6.562459\n",
      "Epoch 3051, Training loss 2.428747, Validation loss 6.562464\n",
      "Epoch 3052, Training loss 2.428746, Validation loss 6.562490\n",
      "Epoch 3053, Training loss 2.428747, Validation loss 6.562495\n",
      "Epoch 3054, Training loss 2.428745, Validation loss 6.562510\n",
      "Epoch 3055, Training loss 2.428744, Validation loss 6.562515\n",
      "Epoch 3056, Training loss 2.428745, Validation loss 6.562551\n",
      "Epoch 3057, Training loss 2.428743, Validation loss 6.562566\n",
      "Epoch 3058, Training loss 2.428743, Validation loss 6.562571\n",
      "Epoch 3059, Training loss 2.428744, Validation loss 6.562586\n",
      "Epoch 3060, Training loss 2.428743, Validation loss 6.562602\n",
      "Epoch 3061, Training loss 2.428742, Validation loss 6.562622\n",
      "Epoch 3062, Training loss 2.428741, Validation loss 6.562637\n",
      "Epoch 3063, Training loss 2.428742, Validation loss 6.562652\n",
      "Epoch 3064, Training loss 2.428742, Validation loss 6.562653\n",
      "Epoch 3065, Training loss 2.428741, Validation loss 6.562668\n",
      "Epoch 3066, Training loss 2.428739, Validation loss 6.562684\n",
      "Epoch 3067, Training loss 2.428739, Validation loss 6.562699\n",
      "Epoch 3068, Training loss 2.428739, Validation loss 6.562704\n",
      "Epoch 3069, Training loss 2.428739, Validation loss 6.562724\n",
      "Epoch 3070, Training loss 2.428738, Validation loss 6.562749\n",
      "Epoch 3071, Training loss 2.428737, Validation loss 6.562759\n",
      "Epoch 3072, Training loss 2.428737, Validation loss 6.562765\n",
      "Epoch 3073, Training loss 2.428737, Validation loss 6.562785\n",
      "Epoch 3074, Training loss 2.428736, Validation loss 6.562796\n",
      "Epoch 3075, Training loss 2.428735, Validation loss 6.562806\n",
      "Epoch 3076, Training loss 2.428735, Validation loss 6.562816\n",
      "Epoch 3077, Training loss 2.428734, Validation loss 6.562821\n",
      "Epoch 3078, Training loss 2.428735, Validation loss 6.562847\n",
      "Epoch 3079, Training loss 2.428735, Validation loss 6.562857\n",
      "Epoch 3080, Training loss 2.428733, Validation loss 6.562867\n",
      "Epoch 3081, Training loss 2.428734, Validation loss 6.562877\n",
      "Epoch 3082, Training loss 2.428733, Validation loss 6.562888\n",
      "Epoch 3083, Training loss 2.428733, Validation loss 6.562903\n",
      "Epoch 3084, Training loss 2.428732, Validation loss 6.562933\n",
      "Epoch 3085, Training loss 2.428732, Validation loss 6.562953\n",
      "Epoch 3086, Training loss 2.428731, Validation loss 6.562953\n",
      "Epoch 3087, Training loss 2.428731, Validation loss 6.562973\n",
      "Epoch 3088, Training loss 2.428730, Validation loss 6.562984\n",
      "Epoch 3089, Training loss 2.428730, Validation loss 6.563004\n",
      "Epoch 3090, Training loss 2.428730, Validation loss 6.563009\n",
      "Epoch 3091, Training loss 2.428729, Validation loss 6.563025\n",
      "Epoch 3092, Training loss 2.428728, Validation loss 6.563040\n",
      "Epoch 3093, Training loss 2.428727, Validation loss 6.563041\n",
      "Epoch 3094, Training loss 2.428727, Validation loss 6.563061\n",
      "Epoch 3095, Training loss 2.428727, Validation loss 6.563061\n",
      "Epoch 3096, Training loss 2.428727, Validation loss 6.563091\n",
      "Epoch 3097, Training loss 2.428727, Validation loss 6.563092\n",
      "Epoch 3098, Training loss 2.428726, Validation loss 6.563121\n",
      "Epoch 3099, Training loss 2.428726, Validation loss 6.563137\n",
      "Epoch 3100, Training loss 2.428726, Validation loss 6.563157\n",
      "Epoch 3101, Training loss 2.428725, Validation loss 6.563152\n",
      "Epoch 3102, Training loss 2.428725, Validation loss 6.563173\n",
      "Epoch 3103, Training loss 2.428725, Validation loss 6.563188\n",
      "Epoch 3104, Training loss 2.428725, Validation loss 6.563193\n",
      "Epoch 3105, Training loss 2.428723, Validation loss 6.563203\n",
      "Epoch 3106, Training loss 2.428723, Validation loss 6.563214\n",
      "Epoch 3107, Training loss 2.428723, Validation loss 6.563239\n",
      "Epoch 3108, Training loss 2.428723, Validation loss 6.563234\n",
      "Epoch 3109, Training loss 2.428721, Validation loss 6.563254\n",
      "Epoch 3110, Training loss 2.428721, Validation loss 6.563265\n",
      "Epoch 3111, Training loss 2.428721, Validation loss 6.563280\n",
      "Epoch 3112, Training loss 2.428722, Validation loss 6.563285\n",
      "Epoch 3113, Training loss 2.428721, Validation loss 6.563305\n",
      "Epoch 3114, Training loss 2.428720, Validation loss 6.563321\n",
      "Epoch 3115, Training loss 2.428720, Validation loss 6.563336\n",
      "Epoch 3116, Training loss 2.428718, Validation loss 6.563341\n",
      "Epoch 3117, Training loss 2.428719, Validation loss 6.563356\n",
      "Epoch 3118, Training loss 2.428718, Validation loss 6.563372\n",
      "Epoch 3119, Training loss 2.428718, Validation loss 6.563377\n",
      "Epoch 3120, Training loss 2.428719, Validation loss 6.563392\n",
      "Epoch 3121, Training loss 2.428718, Validation loss 6.563397\n",
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      "Epoch 3123, Training loss 2.428717, Validation loss 6.563428\n",
      "Epoch 3124, Training loss 2.428716, Validation loss 6.563433\n",
      "Epoch 3125, Training loss 2.428716, Validation loss 6.563448\n",
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      "Epoch 3127, Training loss 2.428715, Validation loss 6.563469\n",
      "Epoch 3128, Training loss 2.428716, Validation loss 6.563484\n",
      "Epoch 3129, Training loss 2.428715, Validation loss 6.563499\n",
      "Epoch 3130, Training loss 2.428715, Validation loss 6.563524\n",
      "Epoch 3131, Training loss 2.428715, Validation loss 6.563530\n",
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      "Epoch 3134, Training loss 2.428713, Validation loss 6.563560\n",
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      "Epoch 3136, Training loss 2.428712, Validation loss 6.563586\n",
      "Epoch 3137, Training loss 2.428712, Validation loss 6.563591\n",
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      "Epoch 3140, Training loss 2.428712, Validation loss 6.563632\n",
      "Epoch 3141, Training loss 2.428711, Validation loss 6.563632\n",
      "Epoch 3142, Training loss 2.428710, Validation loss 6.563657\n",
      "Epoch 3143, Training loss 2.428710, Validation loss 6.563663\n",
      "Epoch 3144, Training loss 2.428710, Validation loss 6.563673\n",
      "Epoch 3145, Training loss 2.428710, Validation loss 6.563698\n",
      "Epoch 3146, Training loss 2.428709, Validation loss 6.563718\n",
      "Epoch 3147, Training loss 2.428709, Validation loss 6.563718\n",
      "Epoch 3148, Training loss 2.428708, Validation loss 6.563734\n",
      "Epoch 3149, Training loss 2.428709, Validation loss 6.563754\n",
      "Epoch 3150, Training loss 2.428708, Validation loss 6.563754\n",
      "Epoch 3151, Training loss 2.428708, Validation loss 6.563774\n",
      "Epoch 3152, Training loss 2.428707, Validation loss 6.563789\n",
      "Epoch 3153, Training loss 2.428707, Validation loss 6.563790\n",
      "Epoch 3154, Training loss 2.428706, Validation loss 6.563810\n",
      "Epoch 3155, Training loss 2.428706, Validation loss 6.563810\n",
      "Epoch 3156, Training loss 2.428706, Validation loss 6.563826\n",
      "Epoch 3157, Training loss 2.428706, Validation loss 6.563831\n",
      "Epoch 3158, Training loss 2.428706, Validation loss 6.563846\n",
      "Epoch 3159, Training loss 2.428706, Validation loss 6.563847\n",
      "Epoch 3160, Training loss 2.428704, Validation loss 6.563867\n",
      "Epoch 3161, Training loss 2.428705, Validation loss 6.563882\n",
      "Epoch 3162, Training loss 2.428704, Validation loss 6.563897\n",
      "Epoch 3163, Training loss 2.428704, Validation loss 6.563907\n",
      "Epoch 3164, Training loss 2.428704, Validation loss 6.563918\n",
      "Epoch 3165, Training loss 2.428703, Validation loss 6.563928\n",
      "Epoch 3166, Training loss 2.428703, Validation loss 6.563938\n",
      "Epoch 3167, Training loss 2.428703, Validation loss 6.563948\n",
      "Epoch 3168, Training loss 2.428703, Validation loss 6.563963\n",
      "Epoch 3169, Training loss 2.428702, Validation loss 6.563973\n",
      "Epoch 3170, Training loss 2.428701, Validation loss 6.563983\n",
      "Epoch 3171, Training loss 2.428702, Validation loss 6.564004\n",
      "Epoch 3172, Training loss 2.428701, Validation loss 6.564014\n",
      "Epoch 3173, Training loss 2.428701, Validation loss 6.564024\n",
      "Epoch 3174, Training loss 2.428700, Validation loss 6.564034\n",
      "Epoch 3175, Training loss 2.428700, Validation loss 6.564050\n",
      "Epoch 3176, Training loss 2.428699, Validation loss 6.564040\n",
      "Epoch 3177, Training loss 2.428700, Validation loss 6.564051\n",
      "Epoch 3178, Training loss 2.428700, Validation loss 6.564075\n",
      "Epoch 3179, Training loss 2.428699, Validation loss 6.564095\n",
      "Epoch 3180, Training loss 2.428699, Validation loss 6.564101\n",
      "Epoch 3181, Training loss 2.428699, Validation loss 6.564101\n",
      "Epoch 3182, Training loss 2.428698, Validation loss 6.564121\n",
      "Epoch 3183, Training loss 2.428697, Validation loss 6.564137\n",
      "Epoch 3184, Training loss 2.428698, Validation loss 6.564142\n",
      "Epoch 3185, Training loss 2.428697, Validation loss 6.564147\n",
      "Epoch 3186, Training loss 2.428697, Validation loss 6.564157\n",
      "Epoch 3187, Training loss 2.428696, Validation loss 6.564163\n",
      "Epoch 3188, Training loss 2.428697, Validation loss 6.564183\n",
      "Epoch 3189, Training loss 2.428696, Validation loss 6.564198\n",
      "Epoch 3190, Training loss 2.428696, Validation loss 6.564203\n",
      "Epoch 3191, Training loss 2.428695, Validation loss 6.564204\n",
      "Epoch 3192, Training loss 2.428695, Validation loss 6.564219\n",
      "Epoch 3193, Training loss 2.428696, Validation loss 6.564224\n",
      "Epoch 3194, Training loss 2.428694, Validation loss 6.564244\n",
      "Epoch 3195, Training loss 2.428694, Validation loss 6.564249\n",
      "Epoch 3196, Training loss 2.428694, Validation loss 6.564264\n",
      "Epoch 3197, Training loss 2.428694, Validation loss 6.564275\n",
      "Epoch 3198, Training loss 2.428694, Validation loss 6.564290\n",
      "Epoch 3199, Training loss 2.428694, Validation loss 6.564315\n",
      "Epoch 3200, Training loss 2.428693, Validation loss 6.564310\n",
      "Epoch 3201, Training loss 2.428693, Validation loss 6.564335\n",
      "Epoch 3202, Training loss 2.428693, Validation loss 6.564331\n",
      "Epoch 3203, Training loss 2.428692, Validation loss 6.564356\n",
      "Epoch 3204, Training loss 2.428693, Validation loss 6.564351\n",
      "Epoch 3205, Training loss 2.428692, Validation loss 6.564361\n",
      "Epoch 3206, Training loss 2.428692, Validation loss 6.564372\n",
      "Epoch 3207, Training loss 2.428691, Validation loss 6.564382\n",
      "Epoch 3208, Training loss 2.428691, Validation loss 6.564392\n",
      "Epoch 3209, Training loss 2.428692, Validation loss 6.564402\n",
      "Epoch 3210, Training loss 2.428691, Validation loss 6.564417\n",
      "Epoch 3211, Training loss 2.428691, Validation loss 6.564423\n",
      "Epoch 3212, Training loss 2.428690, Validation loss 6.564437\n",
      "Epoch 3213, Training loss 2.428691, Validation loss 6.564443\n",
      "Epoch 3214, Training loss 2.428690, Validation loss 6.564438\n",
      "Epoch 3215, Training loss 2.428690, Validation loss 6.564474\n",
      "Epoch 3216, Training loss 2.428689, Validation loss 6.564478\n",
      "Epoch 3217, Training loss 2.428690, Validation loss 6.564498\n",
      "Epoch 3218, Training loss 2.428690, Validation loss 6.564504\n",
      "Epoch 3219, Training loss 2.428690, Validation loss 6.564519\n",
      "Epoch 3220, Training loss 2.428688, Validation loss 6.564519\n",
      "Epoch 3221, Training loss 2.428689, Validation loss 6.564529\n",
      "Epoch 3222, Training loss 2.428689, Validation loss 6.564545\n",
      "Epoch 3223, Training loss 2.428687, Validation loss 6.564550\n",
      "Epoch 3224, Training loss 2.428687, Validation loss 6.564569\n",
      "Epoch 3225, Training loss 2.428688, Validation loss 6.564570\n",
      "Epoch 3226, Training loss 2.428688, Validation loss 6.564575\n",
      "Epoch 3227, Training loss 2.428687, Validation loss 6.564590\n",
      "Epoch 3228, Training loss 2.428688, Validation loss 6.564591\n",
      "Epoch 3229, Training loss 2.428687, Validation loss 6.564611\n",
      "Epoch 3230, Training loss 2.428686, Validation loss 6.564616\n",
      "Epoch 3231, Training loss 2.428686, Validation loss 6.564631\n",
      "Epoch 3232, Training loss 2.428686, Validation loss 6.564632\n",
      "Epoch 3233, Training loss 2.428685, Validation loss 6.564637\n",
      "Epoch 3234, Training loss 2.428684, Validation loss 6.564657\n",
      "Epoch 3235, Training loss 2.428685, Validation loss 6.564672\n",
      "Epoch 3236, Training loss 2.428684, Validation loss 6.564682\n",
      "Epoch 3237, Training loss 2.428685, Validation loss 6.564692\n",
      "Epoch 3238, Training loss 2.428685, Validation loss 6.564703\n",
      "Epoch 3239, Training loss 2.428684, Validation loss 6.564713\n",
      "Epoch 3240, Training loss 2.428684, Validation loss 6.564713\n",
      "Epoch 3241, Training loss 2.428684, Validation loss 6.564723\n",
      "Epoch 3242, Training loss 2.428684, Validation loss 6.564734\n",
      "Epoch 3243, Training loss 2.428684, Validation loss 6.564744\n",
      "Epoch 3244, Training loss 2.428682, Validation loss 6.564749\n",
      "Epoch 3245, Training loss 2.428684, Validation loss 6.564760\n",
      "Epoch 3246, Training loss 2.428682, Validation loss 6.564760\n",
      "Epoch 3247, Training loss 2.428683, Validation loss 6.564770\n",
      "Epoch 3248, Training loss 2.428684, Validation loss 6.564780\n",
      "Epoch 3249, Training loss 2.428681, Validation loss 6.564790\n",
      "Epoch 3250, Training loss 2.428683, Validation loss 6.564800\n",
      "Epoch 3251, Training loss 2.428681, Validation loss 6.564811\n",
      "Epoch 3252, Training loss 2.428682, Validation loss 6.564811\n",
      "Epoch 3253, Training loss 2.428679, Validation loss 6.564821\n",
      "Epoch 3254, Training loss 2.428681, Validation loss 6.564831\n",
      "Epoch 3255, Training loss 2.428682, Validation loss 6.564851\n",
      "Epoch 3256, Training loss 2.428681, Validation loss 6.564871\n",
      "Epoch 3257, Training loss 2.428681, Validation loss 6.564891\n",
      "Epoch 3258, Training loss 2.428679, Validation loss 6.564892\n",
      "Epoch 3259, Training loss 2.428680, Validation loss 6.564897\n",
      "Epoch 3260, Training loss 2.428679, Validation loss 6.564912\n",
      "Epoch 3261, Training loss 2.428679, Validation loss 6.564917\n",
      "Epoch 3262, Training loss 2.428679, Validation loss 6.564937\n",
      "Epoch 3263, Training loss 2.428678, Validation loss 6.564938\n",
      "Epoch 3264, Training loss 2.428679, Validation loss 6.564943\n",
      "Epoch 3265, Training loss 2.428679, Validation loss 6.564943\n",
      "Epoch 3266, Training loss 2.428678, Validation loss 6.564963\n",
      "Epoch 3267, Training loss 2.428679, Validation loss 6.564969\n",
      "Epoch 3268, Training loss 2.428677, Validation loss 6.564969\n",
      "Epoch 3269, Training loss 2.428679, Validation loss 6.564989\n",
      "Epoch 3270, Training loss 2.428678, Validation loss 6.564994\n",
      "Epoch 3271, Training loss 2.428677, Validation loss 6.565014\n",
      "Epoch 3272, Training loss 2.428677, Validation loss 6.565014\n",
      "Epoch 3273, Training loss 2.428679, Validation loss 6.565020\n",
      "Epoch 3274, Training loss 2.428676, Validation loss 6.565040\n",
      "Epoch 3275, Training loss 2.428677, Validation loss 6.565040\n",
      "Epoch 3276, Training loss 2.428677, Validation loss 6.565055\n",
      "Epoch 3277, Training loss 2.428676, Validation loss 6.565065\n",
      "Epoch 3278, Training loss 2.428677, Validation loss 6.565080\n",
      "Epoch 3279, Training loss 2.428676, Validation loss 6.565090\n",
      "Epoch 3280, Training loss 2.428676, Validation loss 6.565090\n",
      "Epoch 3281, Training loss 2.428675, Validation loss 6.565101\n",
      "Epoch 3282, Training loss 2.428677, Validation loss 6.565115\n",
      "Epoch 3283, Training loss 2.428675, Validation loss 6.565121\n",
      "Epoch 3284, Training loss 2.428674, Validation loss 6.565131\n",
      "Epoch 3285, Training loss 2.428675, Validation loss 6.565126\n",
      "Epoch 3286, Training loss 2.428675, Validation loss 6.565142\n",
      "Epoch 3287, Training loss 2.428674, Validation loss 6.565152\n",
      "Epoch 3288, Training loss 2.428674, Validation loss 6.565157\n",
      "Epoch 3289, Training loss 2.428675, Validation loss 6.565172\n",
      "Epoch 3290, Training loss 2.428674, Validation loss 6.565183\n",
      "Epoch 3291, Training loss 2.428674, Validation loss 6.565183\n",
      "Epoch 3292, Training loss 2.428673, Validation loss 6.565193\n",
      "Epoch 3293, Training loss 2.428674, Validation loss 6.565198\n",
      "Epoch 3294, Training loss 2.428673, Validation loss 6.565213\n",
      "Epoch 3295, Training loss 2.428673, Validation loss 6.565223\n",
      "Epoch 3296, Training loss 2.428673, Validation loss 6.565219\n",
      "Epoch 3297, Training loss 2.428673, Validation loss 6.565234\n",
      "Epoch 3298, Training loss 2.428672, Validation loss 6.565254\n",
      "Epoch 3299, Training loss 2.428672, Validation loss 6.565274\n",
      "Epoch 3300, Training loss 2.428672, Validation loss 6.565279\n",
      "Epoch 3301, Training loss 2.428673, Validation loss 6.565284\n",
      "Epoch 3302, Training loss 2.428673, Validation loss 6.565289\n",
      "Epoch 3303, Training loss 2.428672, Validation loss 6.565304\n",
      "Epoch 3304, Training loss 2.428671, Validation loss 6.565295\n",
      "Epoch 3305, Training loss 2.428672, Validation loss 6.565310\n",
      "Epoch 3306, Training loss 2.428671, Validation loss 6.565315\n",
      "Epoch 3307, Training loss 2.428670, Validation loss 6.565320\n",
      "Epoch 3308, Training loss 2.428672, Validation loss 6.565336\n",
      "Epoch 3309, Training loss 2.428671, Validation loss 6.565341\n",
      "Epoch 3310, Training loss 2.428670, Validation loss 6.565346\n",
      "Epoch 3311, Training loss 2.428670, Validation loss 6.565361\n",
      "Epoch 3312, Training loss 2.428670, Validation loss 6.565371\n",
      "Epoch 3313, Training loss 2.428670, Validation loss 6.565376\n",
      "Epoch 3314, Training loss 2.428669, Validation loss 6.565392\n",
      "Epoch 3315, Training loss 2.428670, Validation loss 6.565396\n",
      "Epoch 3316, Training loss 2.428671, Validation loss 6.565397\n",
      "Epoch 3317, Training loss 2.428669, Validation loss 6.565402\n",
      "Epoch 3318, Training loss 2.428670, Validation loss 6.565407\n",
      "Epoch 3319, Training loss 2.428669, Validation loss 6.565423\n",
      "Epoch 3320, Training loss 2.428669, Validation loss 6.565428\n",
      "Epoch 3321, Training loss 2.428669, Validation loss 6.565443\n",
      "Epoch 3322, Training loss 2.428668, Validation loss 6.565453\n",
      "Epoch 3323, Training loss 2.428668, Validation loss 6.565468\n",
      "Epoch 3324, Training loss 2.428668, Validation loss 6.565478\n",
      "Epoch 3325, Training loss 2.428668, Validation loss 6.565473\n",
      "Epoch 3326, Training loss 2.428667, Validation loss 6.565484\n",
      "Epoch 3327, Training loss 2.428668, Validation loss 6.565484\n",
      "Epoch 3328, Training loss 2.428667, Validation loss 6.565494\n",
      "Epoch 3329, Training loss 2.428667, Validation loss 6.565509\n",
      "Epoch 3330, Training loss 2.428667, Validation loss 6.565514\n",
      "Epoch 3331, Training loss 2.428667, Validation loss 6.565514\n",
      "Epoch 3332, Training loss 2.428666, Validation loss 6.565525\n",
      "Epoch 3333, Training loss 2.428668, Validation loss 6.565530\n",
      "Epoch 3334, Training loss 2.428667, Validation loss 6.565549\n",
      "Epoch 3335, Training loss 2.428666, Validation loss 6.565545\n",
      "Epoch 3336, Training loss 2.428667, Validation loss 6.565555\n",
      "Epoch 3337, Training loss 2.428667, Validation loss 6.565566\n",
      "Epoch 3338, Training loss 2.428666, Validation loss 6.565580\n",
      "Epoch 3339, Training loss 2.428666, Validation loss 6.565580\n",
      "Epoch 3340, Training loss 2.428666, Validation loss 6.565586\n",
      "Epoch 3341, Training loss 2.428666, Validation loss 6.565596\n",
      "Epoch 3342, Training loss 2.428666, Validation loss 6.565596\n",
      "Epoch 3343, Training loss 2.428666, Validation loss 6.565602\n",
      "Epoch 3344, Training loss 2.428665, Validation loss 6.565617\n",
      "Epoch 3345, Training loss 2.428665, Validation loss 6.565627\n",
      "Epoch 3346, Training loss 2.428666, Validation loss 6.565637\n",
      "Epoch 3347, Training loss 2.428664, Validation loss 6.565657\n",
      "Epoch 3348, Training loss 2.428664, Validation loss 6.565657\n",
      "Epoch 3349, Training loss 2.428664, Validation loss 6.565667\n",
      "Epoch 3350, Training loss 2.428664, Validation loss 6.565682\n",
      "Epoch 3351, Training loss 2.428664, Validation loss 6.565687\n",
      "Epoch 3352, Training loss 2.428664, Validation loss 6.565692\n",
      "Epoch 3353, Training loss 2.428664, Validation loss 6.565698\n",
      "Epoch 3354, Training loss 2.428665, Validation loss 6.565698\n",
      "Epoch 3355, Training loss 2.428664, Validation loss 6.565708\n",
      "Epoch 3356, Training loss 2.428663, Validation loss 6.565723\n",
      "Epoch 3357, Training loss 2.428664, Validation loss 6.565728\n",
      "Epoch 3358, Training loss 2.428663, Validation loss 6.565733\n",
      "Epoch 3359, Training loss 2.428664, Validation loss 6.565739\n",
      "Epoch 3360, Training loss 2.428664, Validation loss 6.565739\n",
      "Epoch 3361, Training loss 2.428663, Validation loss 6.565749\n",
      "Epoch 3362, Training loss 2.428662, Validation loss 6.565764\n",
      "Epoch 3363, Training loss 2.428663, Validation loss 6.565769\n",
      "Epoch 3364, Training loss 2.428663, Validation loss 6.565770\n",
      "Epoch 3365, Training loss 2.428663, Validation loss 6.565780\n",
      "Epoch 3366, Training loss 2.428663, Validation loss 6.565780\n",
      "Epoch 3367, Training loss 2.428663, Validation loss 6.565800\n",
      "Epoch 3368, Training loss 2.428663, Validation loss 6.565805\n",
      "Epoch 3369, Training loss 2.428662, Validation loss 6.565810\n",
      "Epoch 3370, Training loss 2.428662, Validation loss 6.565811\n",
      "Epoch 3371, Training loss 2.428662, Validation loss 6.565830\n",
      "Epoch 3372, Training loss 2.428662, Validation loss 6.565840\n",
      "Epoch 3373, Training loss 2.428662, Validation loss 6.565851\n",
      "Epoch 3374, Training loss 2.428661, Validation loss 6.565861\n",
      "Epoch 3375, Training loss 2.428662, Validation loss 6.565876\n",
      "Epoch 3376, Training loss 2.428660, Validation loss 6.565876\n",
      "Epoch 3377, Training loss 2.428661, Validation loss 6.565881\n",
      "Epoch 3378, Training loss 2.428661, Validation loss 6.565881\n",
      "Epoch 3379, Training loss 2.428659, Validation loss 6.565896\n",
      "Epoch 3380, Training loss 2.428660, Validation loss 6.565907\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3381, Training loss 2.428661, Validation loss 6.565902\n",
      "Epoch 3382, Training loss 2.428659, Validation loss 6.565912\n",
      "Epoch 3383, Training loss 2.428660, Validation loss 6.565922\n",
      "Epoch 3384, Training loss 2.428661, Validation loss 6.565927\n",
      "Epoch 3385, Training loss 2.428660, Validation loss 6.565937\n",
      "Epoch 3386, Training loss 2.428660, Validation loss 6.565933\n",
      "Epoch 3387, Training loss 2.428660, Validation loss 6.565943\n",
      "Epoch 3388, Training loss 2.428660, Validation loss 6.565953\n",
      "Epoch 3389, Training loss 2.428659, Validation loss 6.565968\n",
      "Epoch 3390, Training loss 2.428659, Validation loss 6.565978\n",
      "Epoch 3391, Training loss 2.428659, Validation loss 6.565973\n",
      "Epoch 3392, Training loss 2.428658, Validation loss 6.565973\n",
      "Epoch 3393, Training loss 2.428659, Validation loss 6.565989\n",
      "Epoch 3394, Training loss 2.428659, Validation loss 6.565999\n",
      "Epoch 3395, Training loss 2.428658, Validation loss 6.565994\n",
      "Epoch 3396, Training loss 2.428659, Validation loss 6.566004\n",
      "Epoch 3397, Training loss 2.428660, Validation loss 6.566014\n",
      "Epoch 3398, Training loss 2.428658, Validation loss 6.566039\n",
      "Epoch 3399, Training loss 2.428658, Validation loss 6.566040\n",
      "Epoch 3400, Training loss 2.428659, Validation loss 6.566045\n",
      "Epoch 3401, Training loss 2.428658, Validation loss 6.566050\n",
      "Epoch 3402, Training loss 2.428658, Validation loss 6.566055\n",
      "Epoch 3403, Training loss 2.428658, Validation loss 6.566060\n",
      "Epoch 3404, Training loss 2.428658, Validation loss 6.566065\n",
      "Epoch 3405, Training loss 2.428657, Validation loss 6.566070\n",
      "Epoch 3406, Training loss 2.428658, Validation loss 6.566075\n",
      "Epoch 3407, Training loss 2.428658, Validation loss 6.566081\n",
      "Epoch 3408, Training loss 2.428658, Validation loss 6.566086\n",
      "Epoch 3409, Training loss 2.428657, Validation loss 6.566086\n",
      "Epoch 3410, Training loss 2.428658, Validation loss 6.566111\n",
      "Epoch 3411, Training loss 2.428656, Validation loss 6.566116\n",
      "Epoch 3412, Training loss 2.428657, Validation loss 6.566116\n",
      "Epoch 3413, Training loss 2.428656, Validation loss 6.566122\n",
      "Epoch 3414, Training loss 2.428657, Validation loss 6.566127\n",
      "Epoch 3415, Training loss 2.428657, Validation loss 6.566132\n",
      "Epoch 3416, Training loss 2.428657, Validation loss 6.566137\n",
      "Epoch 3417, Training loss 2.428657, Validation loss 6.566142\n",
      "Epoch 3418, Training loss 2.428655, Validation loss 6.566157\n",
      "Epoch 3419, Training loss 2.428656, Validation loss 6.566163\n",
      "Epoch 3420, Training loss 2.428656, Validation loss 6.566167\n",
      "Epoch 3421, Training loss 2.428657, Validation loss 6.566168\n",
      "Epoch 3422, Training loss 2.428655, Validation loss 6.566173\n",
      "Epoch 3423, Training loss 2.428656, Validation loss 6.566178\n",
      "Epoch 3424, Training loss 2.428655, Validation loss 6.566184\n",
      "Epoch 3425, Training loss 2.428655, Validation loss 6.566213\n",
      "Epoch 3426, Training loss 2.428655, Validation loss 6.566218\n",
      "Epoch 3427, Training loss 2.428655, Validation loss 6.566233\n",
      "Epoch 3428, Training loss 2.428655, Validation loss 6.566233\n",
      "Epoch 3429, Training loss 2.428655, Validation loss 6.566248\n",
      "Epoch 3430, Training loss 2.428654, Validation loss 6.566254\n",
      "Epoch 3431, Training loss 2.428655, Validation loss 6.566254\n",
      "Epoch 3432, Training loss 2.428655, Validation loss 6.566264\n",
      "Epoch 3433, Training loss 2.428654, Validation loss 6.566264\n",
      "Epoch 3434, Training loss 2.428655, Validation loss 6.566259\n",
      "Epoch 3435, Training loss 2.428654, Validation loss 6.566284\n",
      "Epoch 3436, Training loss 2.428654, Validation loss 6.566284\n",
      "Epoch 3437, Training loss 2.428655, Validation loss 6.566280\n",
      "Epoch 3438, Training loss 2.428653, Validation loss 6.566295\n",
      "Epoch 3439, Training loss 2.428655, Validation loss 6.566305\n",
      "Epoch 3440, Training loss 2.428654, Validation loss 6.566300\n",
      "Epoch 3441, Training loss 2.428653, Validation loss 6.566315\n",
      "Epoch 3442, Training loss 2.428655, Validation loss 6.566315\n",
      "Epoch 3443, Training loss 2.428654, Validation loss 6.566320\n",
      "Epoch 3444, Training loss 2.428653, Validation loss 6.566336\n",
      "Epoch 3445, Training loss 2.428654, Validation loss 6.566331\n",
      "Epoch 3446, Training loss 2.428653, Validation loss 6.566331\n",
      "Epoch 3447, Training loss 2.428653, Validation loss 6.566346\n",
      "Epoch 3448, Training loss 2.428653, Validation loss 6.566351\n",
      "Epoch 3449, Training loss 2.428653, Validation loss 6.566366\n",
      "Epoch 3450, Training loss 2.428653, Validation loss 6.566366\n",
      "Epoch 3451, Training loss 2.428653, Validation loss 6.566361\n",
      "Epoch 3452, Training loss 2.428653, Validation loss 6.566377\n",
      "Epoch 3453, Training loss 2.428653, Validation loss 6.566382\n",
      "Epoch 3454, Training loss 2.428654, Validation loss 6.566382\n",
      "Epoch 3455, Training loss 2.428652, Validation loss 6.566397\n",
      "Epoch 3456, Training loss 2.428653, Validation loss 6.566402\n",
      "Epoch 3457, Training loss 2.428652, Validation loss 6.566422\n",
      "Epoch 3458, Training loss 2.428653, Validation loss 6.566427\n",
      "Epoch 3459, Training loss 2.428653, Validation loss 6.566437\n",
      "Epoch 3460, Training loss 2.428653, Validation loss 6.566437\n",
      "Epoch 3461, Training loss 2.428651, Validation loss 6.566442\n",
      "Epoch 3462, Training loss 2.428652, Validation loss 6.566453\n",
      "Epoch 3463, Training loss 2.428652, Validation loss 6.566453\n",
      "Epoch 3464, Training loss 2.428651, Validation loss 6.566458\n",
      "Epoch 3465, Training loss 2.428651, Validation loss 6.566468\n",
      "Epoch 3466, Training loss 2.428652, Validation loss 6.566468\n",
      "Epoch 3467, Training loss 2.428651, Validation loss 6.566473\n",
      "Epoch 3468, Training loss 2.428652, Validation loss 6.566493\n",
      "Epoch 3469, Training loss 2.428651, Validation loss 6.566483\n",
      "Epoch 3470, Training loss 2.428652, Validation loss 6.566489\n",
      "Epoch 3471, Training loss 2.428652, Validation loss 6.566509\n",
      "Epoch 3472, Training loss 2.428652, Validation loss 6.566499\n",
      "Epoch 3473, Training loss 2.428651, Validation loss 6.566514\n",
      "Epoch 3474, Training loss 2.428651, Validation loss 6.566524\n",
      "Epoch 3475, Training loss 2.428650, Validation loss 6.566525\n",
      "Epoch 3476, Training loss 2.428651, Validation loss 6.566530\n",
      "Epoch 3477, Training loss 2.428650, Validation loss 6.566525\n",
      "Epoch 3478, Training loss 2.428650, Validation loss 6.566540\n",
      "Epoch 3479, Training loss 2.428652, Validation loss 6.566550\n",
      "Epoch 3480, Training loss 2.428651, Validation loss 6.566550\n",
      "Epoch 3481, Training loss 2.428651, Validation loss 6.566555\n",
      "Epoch 3482, Training loss 2.428649, Validation loss 6.566565\n",
      "Epoch 3483, Training loss 2.428651, Validation loss 6.566566\n",
      "Epoch 3484, Training loss 2.428650, Validation loss 6.566571\n",
      "Epoch 3485, Training loss 2.428650, Validation loss 6.566580\n",
      "Epoch 3486, Training loss 2.428650, Validation loss 6.566581\n",
      "Epoch 3487, Training loss 2.428651, Validation loss 6.566586\n",
      "Epoch 3488, Training loss 2.428649, Validation loss 6.566586\n",
      "Epoch 3489, Training loss 2.428650, Validation loss 6.566606\n",
      "Epoch 3490, Training loss 2.428649, Validation loss 6.566616\n",
      "Epoch 3491, Training loss 2.428649, Validation loss 6.566616\n",
      "Epoch 3492, Training loss 2.428649, Validation loss 6.566627\n",
      "Epoch 3493, Training loss 2.428649, Validation loss 6.566627\n",
      "Epoch 3494, Training loss 2.428648, Validation loss 6.566637\n",
      "Epoch 3495, Training loss 2.428650, Validation loss 6.566637\n",
      "Epoch 3496, Training loss 2.428649, Validation loss 6.566647\n",
      "Epoch 3497, Training loss 2.428650, Validation loss 6.566647\n",
      "Epoch 3498, Training loss 2.428649, Validation loss 6.566657\n",
      "Epoch 3499, Training loss 2.428649, Validation loss 6.566668\n",
      "Epoch 3500, Training loss 2.428649, Validation loss 6.566672\n",
      "Epoch 3501, Training loss 2.428648, Validation loss 6.566682\n",
      "Epoch 3502, Training loss 2.428648, Validation loss 6.566682\n",
      "Epoch 3503, Training loss 2.428648, Validation loss 6.566692\n",
      "Epoch 3504, Training loss 2.428648, Validation loss 6.566692\n",
      "Epoch 3505, Training loss 2.428649, Validation loss 6.566703\n",
      "Epoch 3506, Training loss 2.428649, Validation loss 6.566703\n",
      "Epoch 3507, Training loss 2.428648, Validation loss 6.566713\n",
      "Epoch 3508, Training loss 2.428649, Validation loss 6.566713\n",
      "Epoch 3509, Training loss 2.428648, Validation loss 6.566723\n",
      "Epoch 3510, Training loss 2.428648, Validation loss 6.566733\n",
      "Epoch 3511, Training loss 2.428648, Validation loss 6.566733\n",
      "Epoch 3512, Training loss 2.428647, Validation loss 6.566744\n",
      "Epoch 3513, Training loss 2.428648, Validation loss 6.566729\n",
      "Epoch 3514, Training loss 2.428648, Validation loss 6.566739\n",
      "Epoch 3515, Training loss 2.428648, Validation loss 6.566749\n",
      "Epoch 3516, Training loss 2.428647, Validation loss 6.566749\n",
      "Epoch 3517, Training loss 2.428647, Validation loss 6.566760\n",
      "Epoch 3518, Training loss 2.428648, Validation loss 6.566764\n",
      "Epoch 3519, Training loss 2.428647, Validation loss 6.566774\n",
      "Epoch 3520, Training loss 2.428648, Validation loss 6.566774\n",
      "Epoch 3521, Training loss 2.428647, Validation loss 6.566784\n",
      "Epoch 3522, Training loss 2.428647, Validation loss 6.566784\n",
      "Epoch 3523, Training loss 2.428647, Validation loss 6.566804\n",
      "Epoch 3524, Training loss 2.428648, Validation loss 6.566810\n",
      "Epoch 3525, Training loss 2.428648, Validation loss 6.566810\n",
      "Epoch 3526, Training loss 2.428647, Validation loss 6.566820\n",
      "Epoch 3527, Training loss 2.428647, Validation loss 6.566825\n",
      "Epoch 3528, Training loss 2.428647, Validation loss 6.566830\n",
      "Epoch 3529, Training loss 2.428647, Validation loss 6.566821\n",
      "Epoch 3530, Training loss 2.428647, Validation loss 6.566825\n",
      "Epoch 3531, Training loss 2.428648, Validation loss 6.566845\n",
      "Epoch 3532, Training loss 2.428647, Validation loss 6.566851\n",
      "Epoch 3533, Training loss 2.428646, Validation loss 6.566841\n",
      "Epoch 3534, Training loss 2.428647, Validation loss 6.566861\n",
      "Epoch 3535, Training loss 2.428645, Validation loss 6.566866\n",
      "Epoch 3536, Training loss 2.428646, Validation loss 6.566871\n",
      "Epoch 3537, Training loss 2.428646, Validation loss 6.566862\n",
      "Epoch 3538, Training loss 2.428645, Validation loss 6.566866\n",
      "Epoch 3539, Training loss 2.428646, Validation loss 6.566886\n",
      "Epoch 3540, Training loss 2.428646, Validation loss 6.566881\n",
      "Epoch 3541, Training loss 2.428647, Validation loss 6.566886\n",
      "Epoch 3542, Training loss 2.428647, Validation loss 6.566887\n",
      "Epoch 3543, Training loss 2.428647, Validation loss 6.566907\n",
      "Epoch 3544, Training loss 2.428646, Validation loss 6.566902\n",
      "Epoch 3545, Training loss 2.428646, Validation loss 6.566907\n",
      "Epoch 3546, Training loss 2.428647, Validation loss 6.566907\n",
      "Epoch 3547, Training loss 2.428646, Validation loss 6.566913\n",
      "Epoch 3548, Training loss 2.428647, Validation loss 6.566922\n",
      "Epoch 3549, Training loss 2.428646, Validation loss 6.566927\n",
      "Epoch 3550, Training loss 2.428644, Validation loss 6.566928\n",
      "Epoch 3551, Training loss 2.428646, Validation loss 6.566933\n",
      "Epoch 3552, Training loss 2.428644, Validation loss 6.566943\n",
      "Epoch 3553, Training loss 2.428645, Validation loss 6.566948\n",
      "Epoch 3554, Training loss 2.428645, Validation loss 6.566948\n",
      "Epoch 3555, Training loss 2.428645, Validation loss 6.566954\n",
      "Epoch 3556, Training loss 2.428644, Validation loss 6.566963\n",
      "Epoch 3557, Training loss 2.428644, Validation loss 6.566968\n",
      "Epoch 3558, Training loss 2.428645, Validation loss 6.566969\n",
      "Epoch 3559, Training loss 2.428645, Validation loss 6.566974\n",
      "Epoch 3560, Training loss 2.428646, Validation loss 6.566978\n",
      "Epoch 3561, Training loss 2.428646, Validation loss 6.566994\n",
      "Epoch 3562, Training loss 2.428645, Validation loss 6.567004\n",
      "Epoch 3563, Training loss 2.428643, Validation loss 6.566999\n",
      "Epoch 3564, Training loss 2.428645, Validation loss 6.567014\n",
      "Epoch 3565, Training loss 2.428644, Validation loss 6.567029\n",
      "Epoch 3566, Training loss 2.428645, Validation loss 6.567024\n",
      "Epoch 3567, Training loss 2.428645, Validation loss 6.567029\n",
      "Epoch 3568, Training loss 2.428645, Validation loss 6.567024\n",
      "Epoch 3569, Training loss 2.428644, Validation loss 6.567039\n",
      "Epoch 3570, Training loss 2.428645, Validation loss 6.567035\n",
      "Epoch 3571, Training loss 2.428644, Validation loss 6.567050\n",
      "Epoch 3572, Training loss 2.428643, Validation loss 6.567045\n",
      "Epoch 3573, Training loss 2.428644, Validation loss 6.567055\n",
      "Epoch 3574, Training loss 2.428643, Validation loss 6.567070\n",
      "Epoch 3575, Training loss 2.428643, Validation loss 6.567065\n",
      "Epoch 3576, Training loss 2.428643, Validation loss 6.567065\n",
      "Epoch 3577, Training loss 2.428644, Validation loss 6.567075\n",
      "Epoch 3578, Training loss 2.428644, Validation loss 6.567080\n",
      "Epoch 3579, Training loss 2.428644, Validation loss 6.567075\n",
      "Epoch 3580, Training loss 2.428645, Validation loss 6.567086\n",
      "Epoch 3581, Training loss 2.428645, Validation loss 6.567086\n",
      "Epoch 3582, Training loss 2.428643, Validation loss 6.567081\n",
      "Epoch 3583, Training loss 2.428643, Validation loss 6.567096\n",
      "Epoch 3584, Training loss 2.428644, Validation loss 6.567091\n",
      "Epoch 3585, Training loss 2.428644, Validation loss 6.567106\n",
      "Epoch 3586, Training loss 2.428643, Validation loss 6.567121\n",
      "Epoch 3587, Training loss 2.428643, Validation loss 6.567116\n",
      "Epoch 3588, Training loss 2.428643, Validation loss 6.567132\n",
      "Epoch 3589, Training loss 2.428644, Validation loss 6.567127\n",
      "Epoch 3590, Training loss 2.428645, Validation loss 6.567132\n",
      "Epoch 3591, Training loss 2.428643, Validation loss 6.567127\n",
      "Epoch 3592, Training loss 2.428642, Validation loss 6.567137\n",
      "Epoch 3593, Training loss 2.428643, Validation loss 6.567137\n",
      "Epoch 3594, Training loss 2.428644, Validation loss 6.567147\n",
      "Epoch 3595, Training loss 2.428644, Validation loss 6.567147\n",
      "Epoch 3596, Training loss 2.428642, Validation loss 6.567157\n",
      "Epoch 3597, Training loss 2.428643, Validation loss 6.567157\n",
      "Epoch 3598, Training loss 2.428643, Validation loss 6.567168\n",
      "Epoch 3599, Training loss 2.428643, Validation loss 6.567168\n",
      "Epoch 3600, Training loss 2.428644, Validation loss 6.567188\n",
      "Epoch 3601, Training loss 2.428642, Validation loss 6.567193\n",
      "Epoch 3602, Training loss 2.428643, Validation loss 6.567203\n",
      "Epoch 3603, Training loss 2.428643, Validation loss 6.567208\n",
      "Epoch 3604, Training loss 2.428642, Validation loss 6.567213\n",
      "Epoch 3605, Training loss 2.428643, Validation loss 6.567218\n",
      "Epoch 3606, Training loss 2.428643, Validation loss 6.567228\n",
      "Epoch 3607, Training loss 2.428643, Validation loss 6.567218\n",
      "Epoch 3608, Training loss 2.428643, Validation loss 6.567223\n",
      "Epoch 3609, Training loss 2.428642, Validation loss 6.567228\n",
      "Epoch 3610, Training loss 2.428643, Validation loss 6.567233\n",
      "Epoch 3611, Training loss 2.428643, Validation loss 6.567243\n",
      "Epoch 3612, Training loss 2.428643, Validation loss 6.567248\n",
      "Epoch 3613, Training loss 2.428642, Validation loss 6.567249\n",
      "Epoch 3614, Training loss 2.428642, Validation loss 6.567254\n",
      "Epoch 3615, Training loss 2.428642, Validation loss 6.567259\n",
      "Epoch 3616, Training loss 2.428643, Validation loss 6.567268\n",
      "Epoch 3617, Training loss 2.428642, Validation loss 6.567254\n",
      "Epoch 3618, Training loss 2.428642, Validation loss 6.567264\n",
      "Epoch 3619, Training loss 2.428642, Validation loss 6.567269\n",
      "Epoch 3620, Training loss 2.428643, Validation loss 6.567274\n",
      "Epoch 3621, Training loss 2.428642, Validation loss 6.567279\n",
      "Epoch 3622, Training loss 2.428642, Validation loss 6.567269\n",
      "Epoch 3623, Training loss 2.428641, Validation loss 6.567289\n",
      "Epoch 3624, Training loss 2.428641, Validation loss 6.567295\n",
      "Epoch 3625, Training loss 2.428642, Validation loss 6.567300\n",
      "Epoch 3626, Training loss 2.428642, Validation loss 6.567305\n",
      "Epoch 3627, Training loss 2.428642, Validation loss 6.567315\n",
      "Epoch 3628, Training loss 2.428642, Validation loss 6.567300\n",
      "Epoch 3629, Training loss 2.428641, Validation loss 6.567310\n",
      "Epoch 3630, Training loss 2.428641, Validation loss 6.567315\n",
      "Epoch 3631, Training loss 2.428642, Validation loss 6.567320\n",
      "Epoch 3632, Training loss 2.428641, Validation loss 6.567310\n",
      "Epoch 3633, Training loss 2.428642, Validation loss 6.567316\n",
      "Epoch 3634, Training loss 2.428641, Validation loss 6.567326\n",
      "Epoch 3635, Training loss 2.428641, Validation loss 6.567330\n",
      "Epoch 3636, Training loss 2.428642, Validation loss 6.567346\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3637, Training loss 2.428640, Validation loss 6.567351\n",
      "Epoch 3638, Training loss 2.428641, Validation loss 6.567341\n",
      "Epoch 3639, Training loss 2.428641, Validation loss 6.567347\n",
      "Epoch 3640, Training loss 2.428641, Validation loss 6.567356\n",
      "Epoch 3641, Training loss 2.428641, Validation loss 6.567361\n",
      "Epoch 3642, Training loss 2.428642, Validation loss 6.567366\n",
      "Epoch 3643, Training loss 2.428641, Validation loss 6.567376\n",
      "Epoch 3644, Training loss 2.428640, Validation loss 6.567362\n",
      "Epoch 3645, Training loss 2.428641, Validation loss 6.567381\n",
      "Epoch 3646, Training loss 2.428640, Validation loss 6.567387\n",
      "Epoch 3647, Training loss 2.428639, Validation loss 6.567387\n",
      "Epoch 3648, Training loss 2.428640, Validation loss 6.567387\n",
      "Epoch 3649, Training loss 2.428641, Validation loss 6.567397\n",
      "Epoch 3650, Training loss 2.428640, Validation loss 6.567412\n",
      "Epoch 3651, Training loss 2.428641, Validation loss 6.567412\n",
      "Epoch 3652, Training loss 2.428640, Validation loss 6.567412\n",
      "Epoch 3653, Training loss 2.428640, Validation loss 6.567412\n",
      "Epoch 3654, Training loss 2.428641, Validation loss 6.567422\n",
      "Epoch 3655, Training loss 2.428641, Validation loss 6.567422\n",
      "Epoch 3656, Training loss 2.428640, Validation loss 6.567418\n",
      "Epoch 3657, Training loss 2.428640, Validation loss 6.567428\n",
      "Epoch 3658, Training loss 2.428640, Validation loss 6.567428\n",
      "Epoch 3659, Training loss 2.428640, Validation loss 6.567428\n",
      "Epoch 3660, Training loss 2.428641, Validation loss 6.567443\n",
      "Epoch 3661, Training loss 2.428640, Validation loss 6.567443\n",
      "Epoch 3662, Training loss 2.428641, Validation loss 6.567453\n",
      "Epoch 3663, Training loss 2.428640, Validation loss 6.567453\n",
      "Epoch 3664, Training loss 2.428640, Validation loss 6.567453\n",
      "Epoch 3665, Training loss 2.428640, Validation loss 6.567463\n",
      "Epoch 3666, Training loss 2.428641, Validation loss 6.567459\n",
      "Epoch 3667, Training loss 2.428640, Validation loss 6.567459\n",
      "Epoch 3668, Training loss 2.428640, Validation loss 6.567459\n",
      "Epoch 3669, Training loss 2.428639, Validation loss 6.567469\n",
      "Epoch 3670, Training loss 2.428640, Validation loss 6.567469\n",
      "Epoch 3671, Training loss 2.428639, Validation loss 6.567483\n",
      "Epoch 3672, Training loss 2.428641, Validation loss 6.567483\n",
      "Epoch 3673, Training loss 2.428639, Validation loss 6.567494\n",
      "Epoch 3674, Training loss 2.428640, Validation loss 6.567494\n",
      "Epoch 3675, Training loss 2.428639, Validation loss 6.567489\n",
      "Epoch 3676, Training loss 2.428640, Validation loss 6.567489\n",
      "Epoch 3677, Training loss 2.428639, Validation loss 6.567500\n",
      "Epoch 3678, Training loss 2.428640, Validation loss 6.567500\n",
      "Epoch 3679, Training loss 2.428640, Validation loss 6.567500\n",
      "Epoch 3680, Training loss 2.428639, Validation loss 6.567510\n",
      "Epoch 3681, Training loss 2.428639, Validation loss 6.567510\n",
      "Epoch 3682, Training loss 2.428639, Validation loss 6.567524\n",
      "Epoch 3683, Training loss 2.428638, Validation loss 6.567524\n",
      "Epoch 3684, Training loss 2.428640, Validation loss 6.567535\n",
      "Epoch 3685, Training loss 2.428639, Validation loss 6.567530\n",
      "Epoch 3686, Training loss 2.428639, Validation loss 6.567530\n",
      "Epoch 3687, Training loss 2.428639, Validation loss 6.567530\n",
      "Epoch 3688, Training loss 2.428640, Validation loss 6.567541\n",
      "Epoch 3689, Training loss 2.428639, Validation loss 6.567541\n",
      "Epoch 3690, Training loss 2.428640, Validation loss 6.567541\n",
      "Epoch 3691, Training loss 2.428639, Validation loss 6.567555\n",
      "Epoch 3692, Training loss 2.428639, Validation loss 6.567565\n",
      "Epoch 3693, Training loss 2.428639, Validation loss 6.567575\n",
      "Epoch 3694, Training loss 2.428639, Validation loss 6.567580\n",
      "Epoch 3695, Training loss 2.428640, Validation loss 6.567585\n",
      "Epoch 3696, Training loss 2.428639, Validation loss 6.567595\n",
      "Epoch 3697, Training loss 2.428639, Validation loss 6.567585\n",
      "Epoch 3698, Training loss 2.428638, Validation loss 6.567591\n",
      "Epoch 3699, Training loss 2.428638, Validation loss 6.567596\n",
      "Epoch 3700, Training loss 2.428639, Validation loss 6.567601\n",
      "Epoch 3701, Training loss 2.428638, Validation loss 6.567611\n",
      "Epoch 3702, Training loss 2.428638, Validation loss 6.567611\n",
      "Epoch 3703, Training loss 2.428639, Validation loss 6.567606\n",
      "Epoch 3704, Training loss 2.428638, Validation loss 6.567616\n",
      "Epoch 3705, Training loss 2.428639, Validation loss 6.567616\n",
      "Epoch 3706, Training loss 2.428639, Validation loss 6.567626\n",
      "Epoch 3707, Training loss 2.428639, Validation loss 6.567626\n",
      "Epoch 3708, Training loss 2.428639, Validation loss 6.567621\n",
      "Epoch 3709, Training loss 2.428639, Validation loss 6.567641\n",
      "Epoch 3710, Training loss 2.428638, Validation loss 6.567632\n",
      "Epoch 3711, Training loss 2.428638, Validation loss 6.567641\n",
      "Epoch 3712, Training loss 2.428639, Validation loss 6.567642\n",
      "Epoch 3713, Training loss 2.428638, Validation loss 6.567637\n",
      "Epoch 3714, Training loss 2.428638, Validation loss 6.567657\n",
      "Epoch 3715, Training loss 2.428639, Validation loss 6.567647\n",
      "Epoch 3716, Training loss 2.428638, Validation loss 6.567667\n",
      "Epoch 3717, Training loss 2.428638, Validation loss 6.567657\n",
      "Epoch 3718, Training loss 2.428639, Validation loss 6.567662\n",
      "Epoch 3719, Training loss 2.428638, Validation loss 6.567672\n",
      "Epoch 3720, Training loss 2.428637, Validation loss 6.567662\n",
      "Epoch 3721, Training loss 2.428639, Validation loss 6.567682\n",
      "Epoch 3722, Training loss 2.428638, Validation loss 6.567673\n",
      "Epoch 3723, Training loss 2.428638, Validation loss 6.567677\n",
      "Epoch 3724, Training loss 2.428639, Validation loss 6.567688\n",
      "Epoch 3725, Training loss 2.428638, Validation loss 6.567688\n",
      "Epoch 3726, Training loss 2.428637, Validation loss 6.567683\n",
      "Epoch 3727, Training loss 2.428638, Validation loss 6.567688\n",
      "Epoch 3728, Training loss 2.428638, Validation loss 6.567693\n",
      "Epoch 3729, Training loss 2.428637, Validation loss 6.567683\n",
      "Epoch 3730, Training loss 2.428637, Validation loss 6.567703\n",
      "Epoch 3731, Training loss 2.428638, Validation loss 6.567698\n",
      "Epoch 3732, Training loss 2.428638, Validation loss 6.567714\n",
      "Epoch 3733, Training loss 2.428638, Validation loss 6.567708\n",
      "Epoch 3734, Training loss 2.428637, Validation loss 6.567718\n",
      "Epoch 3735, Training loss 2.428638, Validation loss 6.567719\n",
      "Epoch 3736, Training loss 2.428638, Validation loss 6.567714\n",
      "Epoch 3737, Training loss 2.428638, Validation loss 6.567734\n",
      "Epoch 3738, Training loss 2.428638, Validation loss 6.567724\n",
      "Epoch 3739, Training loss 2.428637, Validation loss 6.567724\n",
      "Epoch 3740, Training loss 2.428638, Validation loss 6.567734\n",
      "Epoch 3741, Training loss 2.428638, Validation loss 6.567739\n",
      "Epoch 3742, Training loss 2.428637, Validation loss 6.567749\n",
      "Epoch 3743, Training loss 2.428638, Validation loss 6.567739\n",
      "Epoch 3744, Training loss 2.428638, Validation loss 6.567739\n",
      "Epoch 3745, Training loss 2.428637, Validation loss 6.567750\n",
      "Epoch 3746, Training loss 2.428637, Validation loss 6.567755\n",
      "Epoch 3747, Training loss 2.428638, Validation loss 6.567774\n",
      "Epoch 3748, Training loss 2.428638, Validation loss 6.567784\n",
      "Epoch 3749, Training loss 2.428637, Validation loss 6.567784\n",
      "Epoch 3750, Training loss 2.428638, Validation loss 6.567799\n",
      "Epoch 3751, Training loss 2.428638, Validation loss 6.567784\n",
      "Epoch 3752, Training loss 2.428637, Validation loss 6.567794\n",
      "Epoch 3753, Training loss 2.428637, Validation loss 6.567790\n",
      "Epoch 3754, Training loss 2.428637, Validation loss 6.567794\n",
      "Epoch 3755, Training loss 2.428637, Validation loss 6.567805\n",
      "Epoch 3756, Training loss 2.428637, Validation loss 6.567810\n",
      "Epoch 3757, Training loss 2.428638, Validation loss 6.567805\n",
      "Epoch 3758, Training loss 2.428638, Validation loss 6.567815\n",
      "Epoch 3759, Training loss 2.428637, Validation loss 6.567800\n",
      "Epoch 3760, Training loss 2.428637, Validation loss 6.567815\n",
      "Epoch 3761, Training loss 2.428637, Validation loss 6.567815\n",
      "Epoch 3762, Training loss 2.428638, Validation loss 6.567811\n",
      "Epoch 3763, Training loss 2.428637, Validation loss 6.567825\n",
      "Epoch 3764, Training loss 2.428637, Validation loss 6.567825\n",
      "Epoch 3765, Training loss 2.428637, Validation loss 6.567840\n",
      "Epoch 3766, Training loss 2.428637, Validation loss 6.567835\n",
      "Epoch 3767, Training loss 2.428636, Validation loss 6.567835\n",
      "Epoch 3768, Training loss 2.428637, Validation loss 6.567831\n",
      "Epoch 3769, Training loss 2.428637, Validation loss 6.567835\n",
      "Epoch 3770, Training loss 2.428637, Validation loss 6.567846\n",
      "Epoch 3771, Training loss 2.428638, Validation loss 6.567846\n",
      "Epoch 3772, Training loss 2.428637, Validation loss 6.567841\n",
      "Epoch 3773, Training loss 2.428637, Validation loss 6.567856\n",
      "Epoch 3774, Training loss 2.428636, Validation loss 6.567852\n",
      "Epoch 3775, Training loss 2.428636, Validation loss 6.567852\n",
      "Epoch 3776, Training loss 2.428636, Validation loss 6.567866\n",
      "Epoch 3777, Training loss 2.428637, Validation loss 6.567866\n",
      "Epoch 3778, Training loss 2.428637, Validation loss 6.567881\n",
      "Epoch 3779, Training loss 2.428636, Validation loss 6.567866\n",
      "Epoch 3780, Training loss 2.428637, Validation loss 6.567876\n",
      "Epoch 3781, Training loss 2.428636, Validation loss 6.567872\n",
      "Epoch 3782, Training loss 2.428637, Validation loss 6.567876\n",
      "Epoch 3783, Training loss 2.428637, Validation loss 6.567887\n",
      "Epoch 3784, Training loss 2.428637, Validation loss 6.567882\n",
      "Epoch 3785, Training loss 2.428637, Validation loss 6.567887\n",
      "Epoch 3786, Training loss 2.428636, Validation loss 6.567897\n",
      "Epoch 3787, Training loss 2.428637, Validation loss 6.567902\n",
      "Epoch 3788, Training loss 2.428638, Validation loss 6.567897\n",
      "Epoch 3789, Training loss 2.428636, Validation loss 6.567907\n",
      "Epoch 3790, Training loss 2.428635, Validation loss 6.567907\n",
      "Epoch 3791, Training loss 2.428636, Validation loss 6.567903\n",
      "Epoch 3792, Training loss 2.428637, Validation loss 6.567907\n",
      "Epoch 3793, Training loss 2.428637, Validation loss 6.567917\n",
      "Epoch 3794, Training loss 2.428637, Validation loss 6.567913\n",
      "Epoch 3795, Training loss 2.428636, Validation loss 6.567917\n",
      "Epoch 3796, Training loss 2.428635, Validation loss 6.567913\n",
      "Epoch 3797, Training loss 2.428635, Validation loss 6.567913\n",
      "Epoch 3798, Training loss 2.428636, Validation loss 6.567928\n",
      "Epoch 3799, Training loss 2.428637, Validation loss 6.567938\n",
      "Epoch 3800, Training loss 2.428637, Validation loss 6.567923\n",
      "Epoch 3801, Training loss 2.428636, Validation loss 6.567938\n",
      "Epoch 3802, Training loss 2.428636, Validation loss 6.567938\n",
      "Epoch 3803, Training loss 2.428637, Validation loss 6.567933\n",
      "Epoch 3804, Training loss 2.428636, Validation loss 6.567948\n",
      "Epoch 3805, Training loss 2.428635, Validation loss 6.567948\n",
      "Epoch 3806, Training loss 2.428635, Validation loss 6.567944\n",
      "Epoch 3807, Training loss 2.428635, Validation loss 6.567968\n",
      "Epoch 3808, Training loss 2.428636, Validation loss 6.567963\n",
      "Epoch 3809, Training loss 2.428636, Validation loss 6.567968\n",
      "Epoch 3810, Training loss 2.428635, Validation loss 6.567973\n",
      "Epoch 3811, Training loss 2.428636, Validation loss 6.567978\n",
      "Epoch 3812, Training loss 2.428636, Validation loss 6.567973\n",
      "Epoch 3813, Training loss 2.428637, Validation loss 6.567978\n",
      "Epoch 3814, Training loss 2.428635, Validation loss 6.567984\n",
      "Epoch 3815, Training loss 2.428636, Validation loss 6.567988\n",
      "Epoch 3816, Training loss 2.428636, Validation loss 6.567984\n",
      "Epoch 3817, Training loss 2.428637, Validation loss 6.567988\n",
      "Epoch 3818, Training loss 2.428635, Validation loss 6.567994\n",
      "Epoch 3819, Training loss 2.428635, Validation loss 6.567999\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3820, Training loss 2.428636, Validation loss 6.568004\n",
      "Epoch 3821, Training loss 2.428635, Validation loss 6.567999\n",
      "Epoch 3822, Training loss 2.428634, Validation loss 6.568004\n",
      "Epoch 3823, Training loss 2.428635, Validation loss 6.568009\n",
      "Epoch 3824, Training loss 2.428636, Validation loss 6.568014\n",
      "Epoch 3825, Training loss 2.428635, Validation loss 6.568009\n",
      "Epoch 3826, Training loss 2.428636, Validation loss 6.568014\n",
      "Epoch 3827, Training loss 2.428635, Validation loss 6.568019\n",
      "Epoch 3828, Training loss 2.428635, Validation loss 6.568025\n",
      "Epoch 3829, Training loss 2.428634, Validation loss 6.568029\n",
      "Epoch 3830, Training loss 2.428636, Validation loss 6.568025\n",
      "Epoch 3831, Training loss 2.428636, Validation loss 6.568029\n",
      "Epoch 3832, Training loss 2.428636, Validation loss 6.568035\n",
      "Epoch 3833, Training loss 2.428636, Validation loss 6.568045\n",
      "Epoch 3834, Training loss 2.428637, Validation loss 6.568039\n",
      "Epoch 3835, Training loss 2.428635, Validation loss 6.568045\n",
      "Epoch 3836, Training loss 2.428635, Validation loss 6.568049\n",
      "Epoch 3837, Training loss 2.428635, Validation loss 6.568055\n",
      "Epoch 3838, Training loss 2.428635, Validation loss 6.568060\n",
      "Epoch 3839, Training loss 2.428635, Validation loss 6.568055\n",
      "Epoch 3840, Training loss 2.428635, Validation loss 6.568060\n",
      "Epoch 3841, Training loss 2.428635, Validation loss 6.568065\n",
      "Epoch 3842, Training loss 2.428636, Validation loss 6.568070\n",
      "Epoch 3843, Training loss 2.428635, Validation loss 6.568065\n",
      "Epoch 3844, Training loss 2.428634, Validation loss 6.568070\n",
      "Epoch 3845, Training loss 2.428635, Validation loss 6.568075\n",
      "Epoch 3846, Training loss 2.428635, Validation loss 6.568080\n",
      "Epoch 3847, Training loss 2.428635, Validation loss 6.568086\n",
      "Epoch 3848, Training loss 2.428634, Validation loss 6.568080\n",
      "Epoch 3849, Training loss 2.428634, Validation loss 6.568086\n",
      "Epoch 3850, Training loss 2.428635, Validation loss 6.568090\n",
      "Epoch 3851, Training loss 2.428634, Validation loss 6.568081\n",
      "Epoch 3852, Training loss 2.428634, Validation loss 6.568086\n",
      "Epoch 3853, Training loss 2.428634, Validation loss 6.568081\n",
      "Epoch 3854, Training loss 2.428636, Validation loss 6.568086\n",
      "Epoch 3855, Training loss 2.428635, Validation loss 6.568091\n",
      "Epoch 3856, Training loss 2.428636, Validation loss 6.568096\n",
      "Epoch 3857, Training loss 2.428635, Validation loss 6.568101\n",
      "Epoch 3858, Training loss 2.428636, Validation loss 6.568096\n",
      "Epoch 3859, Training loss 2.428635, Validation loss 6.568101\n",
      "Epoch 3860, Training loss 2.428635, Validation loss 6.568106\n",
      "Epoch 3861, Training loss 2.428635, Validation loss 6.568111\n",
      "Epoch 3862, Training loss 2.428635, Validation loss 6.568106\n",
      "Epoch 3863, Training loss 2.428635, Validation loss 6.568111\n",
      "Epoch 3864, Training loss 2.428634, Validation loss 6.568117\n",
      "Epoch 3865, Training loss 2.428634, Validation loss 6.568122\n",
      "Epoch 3866, Training loss 2.428634, Validation loss 6.568117\n",
      "Epoch 3867, Training loss 2.428635, Validation loss 6.568122\n",
      "Epoch 3868, Training loss 2.428633, Validation loss 6.568127\n",
      "Epoch 3869, Training loss 2.428634, Validation loss 6.568132\n",
      "Epoch 3870, Training loss 2.428635, Validation loss 6.568142\n",
      "Epoch 3871, Training loss 2.428635, Validation loss 6.568137\n",
      "Epoch 3872, Training loss 2.428633, Validation loss 6.568142\n",
      "Epoch 3873, Training loss 2.428634, Validation loss 6.568147\n",
      "Epoch 3874, Training loss 2.428635, Validation loss 6.568152\n",
      "Epoch 3875, Training loss 2.428635, Validation loss 6.568147\n",
      "Epoch 3876, Training loss 2.428634, Validation loss 6.568152\n",
      "Epoch 3877, Training loss 2.428635, Validation loss 6.568167\n",
      "Epoch 3878, Training loss 2.428635, Validation loss 6.568152\n",
      "Epoch 3879, Training loss 2.428636, Validation loss 6.568167\n",
      "Epoch 3880, Training loss 2.428634, Validation loss 6.568167\n",
      "Epoch 3881, Training loss 2.428634, Validation loss 6.568167\n",
      "Epoch 3882, Training loss 2.428634, Validation loss 6.568182\n",
      "Epoch 3883, Training loss 2.428635, Validation loss 6.568178\n",
      "Epoch 3884, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3885, Training loss 2.428635, Validation loss 6.568178\n",
      "Epoch 3886, Training loss 2.428635, Validation loss 6.568182\n",
      "Epoch 3887, Training loss 2.428634, Validation loss 6.568178\n",
      "Epoch 3888, Training loss 2.428635, Validation loss 6.568178\n",
      "Epoch 3889, Training loss 2.428634, Validation loss 6.568188\n",
      "Epoch 3890, Training loss 2.428634, Validation loss 6.568192\n",
      "Epoch 3891, Training loss 2.428634, Validation loss 6.568188\n",
      "Epoch 3892, Training loss 2.428635, Validation loss 6.568188\n",
      "Epoch 3893, Training loss 2.428634, Validation loss 6.568183\n",
      "Epoch 3894, Training loss 2.428634, Validation loss 6.568203\n",
      "Epoch 3895, Training loss 2.428634, Validation loss 6.568198\n",
      "Epoch 3896, Training loss 2.428635, Validation loss 6.568198\n",
      "Epoch 3897, Training loss 2.428633, Validation loss 6.568213\n",
      "Epoch 3898, Training loss 2.428635, Validation loss 6.568208\n",
      "Epoch 3899, Training loss 2.428634, Validation loss 6.568208\n",
      "Epoch 3900, Training loss 2.428633, Validation loss 6.568208\n",
      "Epoch 3901, Training loss 2.428633, Validation loss 6.568223\n",
      "Epoch 3902, Training loss 2.428634, Validation loss 6.568219\n",
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      "Epoch 3904, Training loss 2.428635, Validation loss 6.568219\n",
      "Epoch 3905, Training loss 2.428635, Validation loss 6.568233\n",
      "Epoch 3906, Training loss 2.428634, Validation loss 6.568229\n",
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      "Epoch 3910, Training loss 2.428633, Validation loss 6.568229\n",
      "Epoch 3911, Training loss 2.428634, Validation loss 6.568229\n",
      "Epoch 3912, Training loss 2.428635, Validation loss 6.568234\n",
      "Epoch 3913, Training loss 2.428635, Validation loss 6.568244\n",
      "Epoch 3914, Training loss 2.428634, Validation loss 6.568239\n",
      "Epoch 3915, Training loss 2.428634, Validation loss 6.568239\n",
      "Epoch 3916, Training loss 2.428635, Validation loss 6.568254\n",
      "Epoch 3917, Training loss 2.428634, Validation loss 6.568249\n",
      "Epoch 3918, Training loss 2.428633, Validation loss 6.568249\n",
      "Epoch 3919, Training loss 2.428633, Validation loss 6.568249\n",
      "Epoch 3920, Training loss 2.428634, Validation loss 6.568264\n",
      "Epoch 3921, Training loss 2.428633, Validation loss 6.568260\n",
      "Epoch 3922, Training loss 2.428634, Validation loss 6.568260\n",
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      "Epoch 3924, Training loss 2.428635, Validation loss 6.568255\n",
      "Epoch 3925, Training loss 2.428635, Validation loss 6.568270\n",
      "Epoch 3926, Training loss 2.428635, Validation loss 6.568270\n",
      "Epoch 3927, Training loss 2.428634, Validation loss 6.568270\n",
      "Epoch 3928, Training loss 2.428634, Validation loss 6.568285\n",
      "Epoch 3929, Training loss 2.428633, Validation loss 6.568280\n",
      "Epoch 3930, Training loss 2.428634, Validation loss 6.568280\n",
      "Epoch 3931, Training loss 2.428633, Validation loss 6.568275\n",
      "Epoch 3932, Training loss 2.428634, Validation loss 6.568285\n",
      "Epoch 3933, Training loss 2.428634, Validation loss 6.568280\n",
      "Epoch 3934, Training loss 2.428633, Validation loss 6.568280\n",
      "Epoch 3935, Training loss 2.428634, Validation loss 6.568275\n",
      "Epoch 3936, Training loss 2.428634, Validation loss 6.568290\n",
      "Epoch 3937, Training loss 2.428632, Validation loss 6.568290\n",
      "Epoch 3938, Training loss 2.428634, Validation loss 6.568290\n",
      "Epoch 3939, Training loss 2.428634, Validation loss 6.568285\n",
      "Epoch 3940, Training loss 2.428633, Validation loss 6.568301\n",
      "Epoch 3941, Training loss 2.428633, Validation loss 6.568301\n",
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      "Epoch 3947, Training loss 2.428633, Validation loss 6.568326\n",
      "Epoch 3948, Training loss 2.428633, Validation loss 6.568321\n",
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      "Epoch 3950, Training loss 2.428633, Validation loss 6.568316\n",
      "Epoch 3951, Training loss 2.428634, Validation loss 6.568336\n",
      "Epoch 3952, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3953, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3954, Training loss 2.428633, Validation loss 6.568326\n",
      "Epoch 3955, Training loss 2.428634, Validation loss 6.568331\n",
      "Epoch 3956, Training loss 2.428633, Validation loss 6.568331\n",
      "Epoch 3957, Training loss 2.428632, Validation loss 6.568341\n",
      "Epoch 3958, Training loss 2.428633, Validation loss 6.568346\n",
      "Epoch 3959, Training loss 2.428634, Validation loss 6.568366\n",
      "Epoch 3960, Training loss 2.428634, Validation loss 6.568376\n",
      "Epoch 3961, Training loss 2.428634, Validation loss 6.568366\n",
      "Epoch 3962, Training loss 2.428633, Validation loss 6.568371\n",
      "Epoch 3963, Training loss 2.428635, Validation loss 6.568366\n",
      "Epoch 3964, Training loss 2.428633, Validation loss 6.568371\n",
      "Epoch 3965, Training loss 2.428634, Validation loss 6.568366\n",
      "Epoch 3966, Training loss 2.428633, Validation loss 6.568371\n",
      "Epoch 3967, Training loss 2.428634, Validation loss 6.568372\n",
      "Epoch 3968, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3969, Training loss 2.428633, Validation loss 6.568372\n",
      "Epoch 3970, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3971, Training loss 2.428634, Validation loss 6.568372\n",
      "Epoch 3972, Training loss 2.428633, Validation loss 6.568381\n",
      "Epoch 3973, Training loss 2.428633, Validation loss 6.568387\n",
      "Epoch 3974, Training loss 2.428633, Validation loss 6.568392\n",
      "Epoch 3975, Training loss 2.428634, Validation loss 6.568397\n",
      "Epoch 3976, Training loss 2.428634, Validation loss 6.568387\n",
      "Epoch 3977, Training loss 2.428632, Validation loss 6.568397\n",
      "Epoch 3978, Training loss 2.428633, Validation loss 6.568407\n",
      "Epoch 3979, Training loss 2.428633, Validation loss 6.568397\n",
      "Epoch 3980, Training loss 2.428633, Validation loss 6.568407\n",
      "Epoch 3981, Training loss 2.428633, Validation loss 6.568397\n",
      "Epoch 3982, Training loss 2.428632, Validation loss 6.568402\n",
      "Epoch 3983, Training loss 2.428633, Validation loss 6.568407\n",
      "Epoch 3984, Training loss 2.428633, Validation loss 6.568412\n",
      "Epoch 3985, Training loss 2.428633, Validation loss 6.568402\n",
      "Epoch 3986, Training loss 2.428632, Validation loss 6.568412\n",
      "Epoch 3987, Training loss 2.428634, Validation loss 6.568402\n",
      "Epoch 3988, Training loss 2.428634, Validation loss 6.568412\n",
      "Epoch 3989, Training loss 2.428634, Validation loss 6.568413\n",
      "Epoch 3990, Training loss 2.428632, Validation loss 6.568422\n",
      "Epoch 3991, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 3992, Training loss 2.428632, Validation loss 6.568422\n",
      "Epoch 3993, Training loss 2.428633, Validation loss 6.568413\n",
      "Epoch 3994, Training loss 2.428633, Validation loss 6.568422\n",
      "Epoch 3995, Training loss 2.428633, Validation loss 6.568413\n",
      "Epoch 3996, Training loss 2.428632, Validation loss 6.568418\n",
      "Epoch 3997, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 3998, Training loss 2.428634, Validation loss 6.568428\n",
      "Epoch 3999, Training loss 2.428633, Validation loss 6.568438\n",
      "Epoch 4000, Training loss 2.428633, Validation loss 6.568428\n",
      "Epoch 4001, Training loss 2.428632, Validation loss 6.568438\n",
      "Epoch 4002, Training loss 2.428634, Validation loss 6.568443\n",
      "Epoch 4003, Training loss 2.428633, Validation loss 6.568438\n",
      "Epoch 4004, Training loss 2.428634, Validation loss 6.568443\n",
      "Epoch 4005, Training loss 2.428632, Validation loss 6.568443\n",
      "Epoch 4006, Training loss 2.428633, Validation loss 6.568453\n",
      "Epoch 4007, Training loss 2.428633, Validation loss 6.568443\n",
      "Epoch 4008, Training loss 2.428634, Validation loss 6.568453\n",
      "Epoch 4009, Training loss 2.428632, Validation loss 6.568443\n",
      "Epoch 4010, Training loss 2.428633, Validation loss 6.568453\n",
      "Epoch 4011, Training loss 2.428633, Validation loss 6.568458\n",
      "Epoch 4012, Training loss 2.428633, Validation loss 6.568453\n",
      "Epoch 4013, Training loss 2.428632, Validation loss 6.568458\n",
      "Epoch 4014, Training loss 2.428633, Validation loss 6.568459\n",
      "Epoch 4015, Training loss 2.428633, Validation loss 6.568469\n",
      "Epoch 4016, Training loss 2.428632, Validation loss 6.568459\n",
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      "Epoch 4018, Training loss 2.428633, Validation loss 6.568459\n",
      "Epoch 4019, Training loss 2.428633, Validation loss 6.568469\n",
      "Epoch 4020, Training loss 2.428633, Validation loss 6.568469\n",
      "Epoch 4021, Training loss 2.428632, Validation loss 6.568479\n",
      "Epoch 4022, Training loss 2.428633, Validation loss 6.568484\n",
      "Epoch 4023, Training loss 2.428633, Validation loss 6.568474\n",
      "Epoch 4024, Training loss 2.428632, Validation loss 6.568484\n",
      "Epoch 4025, Training loss 2.428632, Validation loss 6.568474\n",
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      "Epoch 4028, Training loss 2.428632, Validation loss 6.568484\n",
      "Epoch 4029, Training loss 2.428632, Validation loss 6.568484\n",
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      "Epoch 4032, Training loss 2.428632, Validation loss 6.568494\n",
      "Epoch 4033, Training loss 2.428633, Validation loss 6.568499\n",
      "Epoch 4034, Training loss 2.428633, Validation loss 6.568490\n",
      "Epoch 4035, Training loss 2.428634, Validation loss 6.568499\n",
      "Epoch 4036, Training loss 2.428633, Validation loss 6.568500\n",
      "Epoch 4037, Training loss 2.428633, Validation loss 6.568510\n",
      "Epoch 4038, Training loss 2.428632, Validation loss 6.568515\n",
      "Epoch 4039, Training loss 2.428634, Validation loss 6.568510\n",
      "Epoch 4040, Training loss 2.428632, Validation loss 6.568500\n",
      "Epoch 4041, Training loss 2.428633, Validation loss 6.568510\n",
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      "Epoch 4043, Training loss 2.428633, Validation loss 6.568505\n",
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      "Epoch 4050, Training loss 2.428633, Validation loss 6.568525\n",
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      "Epoch 4061, Training loss 2.428633, Validation loss 6.568560\n",
      "Epoch 4062, Training loss 2.428633, Validation loss 6.568565\n",
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      "Epoch 4076, Training loss 2.428633, Validation loss 6.568595\n",
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      "Epoch 4078, Training loss 2.428633, Validation loss 6.568581\n",
      "Epoch 4079, Training loss 2.428633, Validation loss 6.568591\n",
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      "Epoch 4081, Training loss 2.428633, Validation loss 6.568595\n",
      "Epoch 4082, Training loss 2.428633, Validation loss 6.568595\n",
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      "Epoch 4084, Training loss 2.428634, Validation loss 6.568591\n",
      "Epoch 4085, Training loss 2.428632, Validation loss 6.568591\n",
      "Epoch 4086, Training loss 2.428633, Validation loss 6.568601\n",
      "Epoch 4087, Training loss 2.428632, Validation loss 6.568606\n",
      "Epoch 4088, Training loss 2.428632, Validation loss 6.568606\n",
      "Epoch 4089, Training loss 2.428633, Validation loss 6.568601\n",
      "Epoch 4090, Training loss 2.428632, Validation loss 6.568601\n",
      "Epoch 4091, Training loss 2.428633, Validation loss 6.568601\n",
      "Epoch 4092, Training loss 2.428632, Validation loss 6.568601\n",
      "Epoch 4093, Training loss 2.428633, Validation loss 6.568616\n",
      "Epoch 4094, Training loss 2.428633, Validation loss 6.568616\n",
      "Epoch 4095, Training loss 2.428631, Validation loss 6.568616\n",
      "Epoch 4096, Training loss 2.428632, Validation loss 6.568612\n",
      "Epoch 4097, Training loss 2.428632, Validation loss 6.568612\n",
      "Epoch 4098, Training loss 2.428632, Validation loss 6.568612\n",
      "Epoch 4099, Training loss 2.428632, Validation loss 6.568622\n",
      "Epoch 4100, Training loss 2.428632, Validation loss 6.568626\n",
      "Epoch 4101, Training loss 2.428632, Validation loss 6.568626\n",
      "Epoch 4102, Training loss 2.428632, Validation loss 6.568626\n",
      "Epoch 4103, Training loss 2.428633, Validation loss 6.568622\n",
      "Epoch 4104, Training loss 2.428634, Validation loss 6.568622\n",
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      "Epoch 4110, Training loss 2.428631, Validation loss 6.568632\n",
      "Epoch 4111, Training loss 2.428632, Validation loss 6.568632\n",
      "Epoch 4112, Training loss 2.428632, Validation loss 6.568647\n",
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      "Epoch 4114, Training loss 2.428632, Validation loss 6.568647\n",
      "Epoch 4115, Training loss 2.428631, Validation loss 6.568642\n",
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      "Epoch 4119, Training loss 2.428632, Validation loss 6.568657\n",
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      "Epoch 4121, Training loss 2.428632, Validation loss 6.568657\n",
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      "Epoch 4127, Training loss 2.428631, Validation loss 6.568653\n",
      "Epoch 4128, Training loss 2.428632, Validation loss 6.568653\n",
      "Epoch 4129, Training loss 2.428631, Validation loss 6.568663\n",
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      "Epoch 4148, Training loss 2.428632, Validation loss 6.568693\n",
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      "Epoch 4167, Training loss 2.428632, Validation loss 6.568714\n",
      "Epoch 4168, Training loss 2.428632, Validation loss 6.568724\n",
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      "Epoch 4171, Training loss 2.428632, Validation loss 6.568724\n",
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      "Epoch 4175, Training loss 2.428631, Validation loss 6.568744\n",
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      "Epoch 4177, Training loss 2.428632, Validation loss 6.568744\n",
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      "Epoch 4183, Training loss 2.428632, Validation loss 6.568754\n",
      "Epoch 4184, Training loss 2.428632, Validation loss 6.568759\n",
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      "Epoch 4188, Training loss 2.428632, Validation loss 6.568754\n",
      "Epoch 4189, Training loss 2.428632, Validation loss 6.568749\n",
      "Epoch 4190, Training loss 2.428632, Validation loss 6.568754\n",
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      "Epoch 4192, Training loss 2.428632, Validation loss 6.568769\n",
      "Epoch 4193, Training loss 2.428631, Validation loss 6.568759\n",
      "Epoch 4194, Training loss 2.428632, Validation loss 6.568765\n",
      "Epoch 4195, Training loss 2.428631, Validation loss 6.568759\n",
      "Epoch 4196, Training loss 2.428631, Validation loss 6.568765\n",
      "Epoch 4197, Training loss 2.428632, Validation loss 6.568774\n",
      "Epoch 4198, Training loss 2.428632, Validation loss 6.568769\n",
      "Epoch 4199, Training loss 2.428632, Validation loss 6.568774\n",
      "Epoch 4200, Training loss 2.428631, Validation loss 6.568765\n",
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      "Epoch 4208, Training loss 2.428632, Validation loss 6.568775\n",
      "Epoch 4209, Training loss 2.428631, Validation loss 6.568780\n",
      "Epoch 4210, Training loss 2.428632, Validation loss 6.568775\n",
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      "Epoch 4212, Training loss 2.428632, Validation loss 6.568775\n",
      "Epoch 4213, Training loss 2.428632, Validation loss 6.568775\n",
      "Epoch 4214, Training loss 2.428632, Validation loss 6.568789\n",
      "Epoch 4215, Training loss 2.428632, Validation loss 6.568795\n",
      "Epoch 4216, Training loss 2.428631, Validation loss 6.568785\n",
      "Epoch 4217, Training loss 2.428632, Validation loss 6.568790\n",
      "Epoch 4218, Training loss 2.428631, Validation loss 6.568785\n",
      "Epoch 4219, Training loss 2.428632, Validation loss 6.568790\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4220, Training loss 2.428632, Validation loss 6.568785\n",
      "Epoch 4221, Training loss 2.428631, Validation loss 6.568786\n",
      "Epoch 4222, Training loss 2.428632, Validation loss 6.568800\n",
      "Epoch 4223, Training loss 2.428632, Validation loss 6.568790\n",
      "Epoch 4224, Training loss 2.428632, Validation loss 6.568795\n",
      "Epoch 4225, Training loss 2.428631, Validation loss 6.568790\n",
      "Epoch 4226, Training loss 2.428632, Validation loss 6.568795\n",
      "Epoch 4227, Training loss 2.428631, Validation loss 6.568790\n",
      "Epoch 4228, Training loss 2.428633, Validation loss 6.568795\n",
      "Epoch 4229, Training loss 2.428631, Validation loss 6.568786\n",
      "Epoch 4230, Training loss 2.428631, Validation loss 6.568810\n",
      "Epoch 4231, Training loss 2.428632, Validation loss 6.568800\n",
      "Epoch 4232, Training loss 2.428632, Validation loss 6.568806\n",
      "Epoch 4233, Training loss 2.428632, Validation loss 6.568800\n",
      "Epoch 4234, Training loss 2.428632, Validation loss 6.568806\n",
      "Epoch 4235, Training loss 2.428632, Validation loss 6.568800\n",
      "Epoch 4236, Training loss 2.428631, Validation loss 6.568801\n",
      "Epoch 4237, Training loss 2.428633, Validation loss 6.568815\n",
      "Epoch 4238, Training loss 2.428632, Validation loss 6.568820\n",
      "Epoch 4239, Training loss 2.428632, Validation loss 6.568810\n",
      "Epoch 4240, Training loss 2.428632, Validation loss 6.568816\n",
      "Epoch 4241, Training loss 2.428633, Validation loss 6.568810\n",
      "Epoch 4242, Training loss 2.428631, Validation loss 6.568816\n",
      "Epoch 4243, Training loss 2.428631, Validation loss 6.568810\n",
      "Epoch 4244, Training loss 2.428632, Validation loss 6.568811\n",
      "Epoch 4245, Training loss 2.428631, Validation loss 6.568826\n",
      "Epoch 4246, Training loss 2.428631, Validation loss 6.568816\n",
      "Epoch 4247, Training loss 2.428632, Validation loss 6.568821\n",
      "Epoch 4248, Training loss 2.428632, Validation loss 6.568816\n",
      "Epoch 4249, Training loss 2.428631, Validation loss 6.568821\n",
      "Epoch 4250, Training loss 2.428632, Validation loss 6.568816\n",
      "Epoch 4251, Training loss 2.428632, Validation loss 6.568821\n",
      "Epoch 4252, Training loss 2.428631, Validation loss 6.568811\n",
      "Epoch 4253, Training loss 2.428632, Validation loss 6.568836\n",
      "Epoch 4254, Training loss 2.428631, Validation loss 6.568826\n",
      "Epoch 4255, Training loss 2.428631, Validation loss 6.568831\n",
      "Epoch 4256, Training loss 2.428631, Validation loss 6.568826\n",
      "Epoch 4257, Training loss 2.428632, Validation loss 6.568831\n",
      "Epoch 4258, Training loss 2.428632, Validation loss 6.568826\n",
      "Epoch 4259, Training loss 2.428633, Validation loss 6.568827\n",
      "Epoch 4260, Training loss 2.428632, Validation loss 6.568841\n",
      "Epoch 4261, Training loss 2.428632, Validation loss 6.568841\n",
      "Epoch 4262, Training loss 2.428632, Validation loss 6.568836\n",
      "Epoch 4263, Training loss 2.428632, Validation loss 6.568841\n",
      "Epoch 4264, Training loss 2.428632, Validation loss 6.568836\n",
      "Epoch 4265, Training loss 2.428631, Validation loss 6.568841\n",
      "Epoch 4266, Training loss 2.428632, Validation loss 6.568836\n",
      "Epoch 4267, Training loss 2.428631, Validation loss 6.568837\n",
      "Epoch 4268, Training loss 2.428632, Validation loss 6.568851\n",
      "Epoch 4269, Training loss 2.428631, Validation loss 6.568841\n",
      "Epoch 4270, Training loss 2.428632, Validation loss 6.568847\n",
      "Epoch 4271, Training loss 2.428632, Validation loss 6.568841\n",
      "Epoch 4272, Training loss 2.428632, Validation loss 6.568847\n",
      "Epoch 4273, Training loss 2.428632, Validation loss 6.568841\n",
      "Epoch 4274, Training loss 2.428631, Validation loss 6.568842\n",
      "Epoch 4275, Training loss 2.428632, Validation loss 6.568856\n",
      "Epoch 4276, Training loss 2.428632, Validation loss 6.568861\n",
      "Epoch 4277, Training loss 2.428632, Validation loss 6.568851\n",
      "Epoch 4278, Training loss 2.428631, Validation loss 6.568857\n",
      "Epoch 4279, Training loss 2.428632, Validation loss 6.568851\n",
      "Epoch 4280, Training loss 2.428632, Validation loss 6.568857\n",
      "Epoch 4281, Training loss 2.428632, Validation loss 6.568851\n",
      "Epoch 4282, Training loss 2.428631, Validation loss 6.568852\n",
      "Epoch 4283, Training loss 2.428632, Validation loss 6.568867\n",
      "Epoch 4284, Training loss 2.428632, Validation loss 6.568867\n",
      "Epoch 4285, Training loss 2.428631, Validation loss 6.568862\n",
      "Epoch 4286, Training loss 2.428631, Validation loss 6.568867\n",
      "Epoch 4287, Training loss 2.428631, Validation loss 6.568862\n",
      "Epoch 4288, Training loss 2.428632, Validation loss 6.568867\n",
      "Epoch 4289, Training loss 2.428631, Validation loss 6.568862\n",
      "Epoch 4290, Training loss 2.428631, Validation loss 6.568862\n",
      "Epoch 4291, Training loss 2.428631, Validation loss 6.568877\n",
      "Epoch 4292, Training loss 2.428631, Validation loss 6.568867\n",
      "Epoch 4293, Training loss 2.428632, Validation loss 6.568872\n",
      "Epoch 4294, Training loss 2.428631, Validation loss 6.568867\n",
      "Epoch 4295, Training loss 2.428631, Validation loss 6.568872\n",
      "Epoch 4296, Training loss 2.428632, Validation loss 6.568867\n",
      "Epoch 4297, Training loss 2.428632, Validation loss 6.568868\n",
      "Epoch 4298, Training loss 2.428631, Validation loss 6.568882\n",
      "Epoch 4299, Training loss 2.428632, Validation loss 6.568882\n",
      "Epoch 4300, Training loss 2.428632, Validation loss 6.568877\n",
      "Epoch 4301, Training loss 2.428630, Validation loss 6.568882\n",
      "Epoch 4302, Training loss 2.428633, Validation loss 6.568877\n",
      "Epoch 4303, Training loss 2.428631, Validation loss 6.568882\n",
      "Epoch 4304, Training loss 2.428632, Validation loss 6.568877\n",
      "Epoch 4305, Training loss 2.428631, Validation loss 6.568878\n",
      "Epoch 4306, Training loss 2.428633, Validation loss 6.568872\n",
      "Epoch 4307, Training loss 2.428631, Validation loss 6.568892\n",
      "Epoch 4308, Training loss 2.428632, Validation loss 6.568888\n",
      "Epoch 4309, Training loss 2.428631, Validation loss 6.568892\n",
      "Epoch 4310, Training loss 2.428631, Validation loss 6.568888\n",
      "Epoch 4311, Training loss 2.428632, Validation loss 6.568892\n",
      "Epoch 4312, Training loss 2.428631, Validation loss 6.568883\n",
      "Epoch 4313, Training loss 2.428631, Validation loss 6.568897\n",
      "Epoch 4314, Training loss 2.428631, Validation loss 6.568902\n",
      "Epoch 4315, Training loss 2.428632, Validation loss 6.568892\n",
      "Epoch 4316, Training loss 2.428631, Validation loss 6.568898\n",
      "Epoch 4317, Training loss 2.428632, Validation loss 6.568892\n",
      "Epoch 4318, Training loss 2.428631, Validation loss 6.568898\n",
      "Epoch 4319, Training loss 2.428631, Validation loss 6.568892\n",
      "Epoch 4320, Training loss 2.428631, Validation loss 6.568893\n",
      "Epoch 4321, Training loss 2.428631, Validation loss 6.568888\n",
      "Epoch 4322, Training loss 2.428631, Validation loss 6.568908\n",
      "Epoch 4323, Training loss 2.428632, Validation loss 6.568903\n",
      "Epoch 4324, Training loss 2.428632, Validation loss 6.568908\n",
      "Epoch 4325, Training loss 2.428631, Validation loss 6.568903\n",
      "Epoch 4326, Training loss 2.428631, Validation loss 6.568908\n",
      "Epoch 4327, Training loss 2.428632, Validation loss 6.568903\n",
      "Epoch 4328, Training loss 2.428631, Validation loss 6.568903\n",
      "Epoch 4329, Training loss 2.428631, Validation loss 6.568918\n",
      "Epoch 4330, Training loss 2.428630, Validation loss 6.568918\n",
      "Epoch 4331, Training loss 2.428632, Validation loss 6.568913\n",
      "Epoch 4332, Training loss 2.428631, Validation loss 6.568918\n",
      "Epoch 4333, Training loss 2.428632, Validation loss 6.568913\n",
      "Epoch 4334, Training loss 2.428631, Validation loss 6.568928\n",
      "Epoch 4335, Training loss 2.428632, Validation loss 6.568918\n",
      "Epoch 4336, Training loss 2.428632, Validation loss 6.568933\n",
      "Epoch 4337, Training loss 2.428631, Validation loss 6.568928\n",
      "Epoch 4338, Training loss 2.428632, Validation loss 6.568943\n",
      "Epoch 4339, Training loss 2.428631, Validation loss 6.568918\n",
      "Epoch 4340, Training loss 2.428631, Validation loss 6.568933\n",
      "Epoch 4341, Training loss 2.428632, Validation loss 6.568938\n",
      "Epoch 4342, Training loss 2.428631, Validation loss 6.568933\n",
      "Epoch 4343, Training loss 2.428632, Validation loss 6.568948\n",
      "Epoch 4344, Training loss 2.428633, Validation loss 6.568938\n",
      "Epoch 4345, Training loss 2.428631, Validation loss 6.568948\n",
      "Epoch 4346, Training loss 2.428630, Validation loss 6.568948\n",
      "Epoch 4347, Training loss 2.428631, Validation loss 6.568953\n",
      "Epoch 4348, Training loss 2.428632, Validation loss 6.568948\n",
      "Epoch 4349, Training loss 2.428631, Validation loss 6.568944\n",
      "Epoch 4350, Training loss 2.428632, Validation loss 6.568948\n",
      "Epoch 4351, Training loss 2.428631, Validation loss 6.568948\n",
      "Epoch 4352, Training loss 2.428630, Validation loss 6.568944\n",
      "Epoch 4353, Training loss 2.428631, Validation loss 6.568948\n",
      "Epoch 4354, Training loss 2.428632, Validation loss 6.568944\n",
      "Epoch 4355, Training loss 2.428631, Validation loss 6.568958\n",
      "Epoch 4356, Training loss 2.428630, Validation loss 6.568944\n",
      "Epoch 4357, Training loss 2.428633, Validation loss 6.568958\n",
      "Epoch 4358, Training loss 2.428631, Validation loss 6.568958\n",
      "Epoch 4359, Training loss 2.428631, Validation loss 6.568963\n",
      "Epoch 4360, Training loss 2.428632, Validation loss 6.568958\n",
      "Epoch 4361, Training loss 2.428631, Validation loss 6.568954\n",
      "Epoch 4362, Training loss 2.428631, Validation loss 6.568958\n",
      "Epoch 4363, Training loss 2.428632, Validation loss 6.568958\n",
      "Epoch 4364, Training loss 2.428631, Validation loss 6.568958\n",
      "Epoch 4365, Training loss 2.428631, Validation loss 6.568958\n",
      "Epoch 4366, Training loss 2.428631, Validation loss 6.568954\n",
      "Epoch 4367, Training loss 2.428632, Validation loss 6.568958\n",
      "Epoch 4368, Training loss 2.428632, Validation loss 6.568954\n",
      "Epoch 4369, Training loss 2.428631, Validation loss 6.568968\n",
      "Epoch 4370, Training loss 2.428632, Validation loss 6.568958\n",
      "Epoch 4371, Training loss 2.428631, Validation loss 6.568954\n",
      "Epoch 4372, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4373, Training loss 2.428632, Validation loss 6.568973\n",
      "Epoch 4374, Training loss 2.428631, Validation loss 6.568968\n",
      "Epoch 4375, Training loss 2.428631, Validation loss 6.568964\n",
      "Epoch 4376, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4377, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4378, Training loss 2.428631, Validation loss 6.568964\n",
      "Epoch 4379, Training loss 2.428631, Validation loss 6.568968\n",
      "Epoch 4380, Training loss 2.428630, Validation loss 6.568964\n",
      "Epoch 4381, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4382, Training loss 2.428632, Validation loss 6.568968\n",
      "Epoch 4383, Training loss 2.428632, Validation loss 6.568979\n",
      "Epoch 4384, Training loss 2.428631, Validation loss 6.568968\n",
      "Epoch 4385, Training loss 2.428631, Validation loss 6.568964\n",
      "Epoch 4386, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4387, Training loss 2.428632, Validation loss 6.568964\n",
      "Epoch 4388, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4389, Training loss 2.428631, Validation loss 6.568979\n",
      "Epoch 4390, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4391, Training loss 2.428632, Validation loss 6.568979\n",
      "Epoch 4392, Training loss 2.428631, Validation loss 6.568994\n",
      "Epoch 4393, Training loss 2.428630, Validation loss 6.568979\n",
      "Epoch 4394, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4395, Training loss 2.428631, Validation loss 6.568989\n",
      "Epoch 4396, Training loss 2.428632, Validation loss 6.568979\n",
      "Epoch 4397, Training loss 2.428632, Validation loss 6.568994\n",
      "Epoch 4398, Training loss 2.428631, Validation loss 6.568989\n",
      "Epoch 4399, Training loss 2.428631, Validation loss 6.568974\n",
      "Epoch 4400, Training loss 2.428632, Validation loss 6.568989\n",
      "Epoch 4401, Training loss 2.428632, Validation loss 6.568989\n",
      "Epoch 4402, Training loss 2.428631, Validation loss 6.568989\n",
      "Epoch 4403, Training loss 2.428631, Validation loss 6.568989\n",
      "Epoch 4404, Training loss 2.428632, Validation loss 6.568994\n",
      "Epoch 4405, Training loss 2.428631, Validation loss 6.568989\n",
      "Epoch 4406, Training loss 2.428631, Validation loss 6.568985\n",
      "Epoch 4407, Training loss 2.428632, Validation loss 6.568989\n",
      "Epoch 4408, Training loss 2.428632, Validation loss 6.568989\n",
      "Epoch 4409, Training loss 2.428631, Validation loss 6.568985\n",
      "Epoch 4410, Training loss 2.428631, Validation loss 6.568989\n",
      "Epoch 4411, Training loss 2.428632, Validation loss 6.568985\n",
      "Epoch 4412, Training loss 2.428631, Validation loss 6.568999\n",
      "Epoch 4413, Training loss 2.428630, Validation loss 6.568985\n",
      "Epoch 4414, Training loss 2.428632, Validation loss 6.568999\n",
      "Epoch 4415, Training loss 2.428632, Validation loss 6.568999\n",
      "Epoch 4416, Training loss 2.428631, Validation loss 6.568985\n",
      "Epoch 4417, Training loss 2.428631, Validation loss 6.568999\n",
      "Epoch 4418, Training loss 2.428631, Validation loss 6.568995\n",
      "Epoch 4419, Training loss 2.428630, Validation loss 6.568999\n",
      "Epoch 4420, Training loss 2.428631, Validation loss 6.568999\n",
      "Epoch 4421, Training loss 2.428632, Validation loss 6.568999\n",
      "Epoch 4422, Training loss 2.428632, Validation loss 6.568999\n",
      "Epoch 4423, Training loss 2.428632, Validation loss 6.568995\n",
      "Epoch 4424, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4425, Training loss 2.428631, Validation loss 6.568995\n",
      "Epoch 4426, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4427, Training loss 2.428632, Validation loss 6.569009\n",
      "Epoch 4428, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4429, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4430, Training loss 2.428631, Validation loss 6.569005\n",
      "Epoch 4431, Training loss 2.428632, Validation loss 6.569009\n",
      "Epoch 4432, Training loss 2.428631, Validation loss 6.569005\n",
      "Epoch 4433, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4434, Training loss 2.428632, Validation loss 6.569009\n",
      "Epoch 4435, Training loss 2.428632, Validation loss 6.569005\n",
      "Epoch 4436, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4437, Training loss 2.428630, Validation loss 6.569005\n",
      "Epoch 4438, Training loss 2.428631, Validation loss 6.569020\n",
      "Epoch 4439, Training loss 2.428631, Validation loss 6.569009\n",
      "Epoch 4440, Training loss 2.428630, Validation loss 6.569005\n",
      "Epoch 4441, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4442, Training loss 2.428632, Validation loss 6.569005\n",
      "Epoch 4443, Training loss 2.428630, Validation loss 6.569020\n",
      "Epoch 4444, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4445, Training loss 2.428632, Validation loss 6.569005\n",
      "Epoch 4446, Training loss 2.428631, Validation loss 6.569020\n",
      "Epoch 4447, Training loss 2.428630, Validation loss 6.569015\n",
      "Epoch 4448, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4449, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4450, Training loss 2.428630, Validation loss 6.569020\n",
      "Epoch 4451, Training loss 2.428632, Validation loss 6.569020\n",
      "Epoch 4452, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4453, Training loss 2.428630, Validation loss 6.569020\n",
      "Epoch 4454, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4455, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4456, Training loss 2.428631, Validation loss 6.569015\n",
      "Epoch 4457, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4458, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4459, Training loss 2.428632, Validation loss 6.569026\n",
      "Epoch 4460, Training loss 2.428631, Validation loss 6.569030\n",
      "Epoch 4461, Training loss 2.428632, Validation loss 6.569045\n",
      "Epoch 4462, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4463, Training loss 2.428630, Validation loss 6.569026\n",
      "Epoch 4464, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4465, Training loss 2.428632, Validation loss 6.569030\n",
      "Epoch 4466, Training loss 2.428630, Validation loss 6.569040\n",
      "Epoch 4467, Training loss 2.428630, Validation loss 6.569040\n",
      "Epoch 4468, Training loss 2.428631, Validation loss 6.569026\n",
      "Epoch 4469, Training loss 2.428632, Validation loss 6.569026\n",
      "Epoch 4470, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4471, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4472, Training loss 2.428630, Validation loss 6.569040\n",
      "Epoch 4473, Training loss 2.428631, Validation loss 6.569036\n",
      "Epoch 4474, Training loss 2.428632, Validation loss 6.569040\n",
      "Epoch 4475, Training loss 2.428632, Validation loss 6.569036\n",
      "Epoch 4476, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4477, Training loss 2.428630, Validation loss 6.569040\n",
      "Epoch 4478, Training loss 2.428632, Validation loss 6.569036\n",
      "Epoch 4479, Training loss 2.428631, Validation loss 6.569040\n",
      "Epoch 4480, Training loss 2.428631, Validation loss 6.569036\n",
      "Epoch 4481, Training loss 2.428631, Validation loss 6.569050\n",
      "Epoch 4482, Training loss 2.428631, Validation loss 6.569036\n",
      "Epoch 4483, Training loss 2.428631, Validation loss 6.569050\n",
      "Epoch 4484, Training loss 2.428632, Validation loss 6.569050\n",
      "Epoch 4485, Training loss 2.428632, Validation loss 6.569036\n",
      "Epoch 4486, Training loss 2.428631, Validation loss 6.569050\n",
      "Epoch 4487, Training loss 2.428631, Validation loss 6.569046\n",
      "Epoch 4488, Training loss 2.428632, Validation loss 6.569050\n",
      "Epoch 4489, Training loss 2.428632, Validation loss 6.569050\n",
      "Epoch 4490, Training loss 2.428630, Validation loss 6.569050\n",
      "Epoch 4491, Training loss 2.428631, Validation loss 6.569050\n",
      "Epoch 4492, Training loss 2.428631, Validation loss 6.569046\n",
      "Epoch 4493, Training loss 2.428632, Validation loss 6.569050\n",
      "Epoch 4494, Training loss 2.428631, Validation loss 6.569046\n",
      "Epoch 4495, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4496, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4497, Training loss 2.428630, Validation loss 6.569046\n",
      "Epoch 4498, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4499, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4500, Training loss 2.428630, Validation loss 6.569061\n",
      "Epoch 4501, Training loss 2.428632, Validation loss 6.569056\n",
      "Epoch 4502, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4503, Training loss 2.428631, Validation loss 6.569061\n",
      "Epoch 4504, Training loss 2.428630, Validation loss 6.569056\n",
      "Epoch 4505, Training loss 2.428632, Validation loss 6.569061\n",
      "Epoch 4506, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4507, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4508, Training loss 2.428632, Validation loss 6.569061\n",
      "Epoch 4509, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4510, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4511, Training loss 2.428631, Validation loss 6.569056\n",
      "Epoch 4512, Training loss 2.428632, Validation loss 6.569071\n",
      "Epoch 4513, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4514, Training loss 2.428633, Validation loss 6.569071\n",
      "Epoch 4515, Training loss 2.428632, Validation loss 6.569071\n",
      "Epoch 4516, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4517, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4518, Training loss 2.428632, Validation loss 6.569066\n",
      "Epoch 4519, Training loss 2.428631, Validation loss 6.569071\n",
      "Epoch 4520, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4521, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4522, Training loss 2.428632, Validation loss 6.569071\n",
      "Epoch 4523, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4524, Training loss 2.428633, Validation loss 6.569081\n",
      "Epoch 4525, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4526, Training loss 2.428631, Validation loss 6.569066\n",
      "Epoch 4527, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4528, Training loss 2.428632, Validation loss 6.569066\n",
      "Epoch 4529, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4530, Training loss 2.428630, Validation loss 6.569077\n",
      "Epoch 4531, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4532, Training loss 2.428631, Validation loss 6.569077\n",
      "Epoch 4533, Training loss 2.428632, Validation loss 6.569091\n",
      "Epoch 4534, Training loss 2.428631, Validation loss 6.569081\n",
      "Epoch 4535, Training loss 2.428631, Validation loss 6.569077\n",
      "Epoch 4536, Training loss 2.428630, Validation loss 6.569091\n",
      "Epoch 4537, Training loss 2.428631, Validation loss 6.569077\n",
      "Epoch 4538, Training loss 2.428632, Validation loss 6.569091\n",
      "Epoch 4539, Training loss 2.428631, Validation loss 6.569087\n",
      "Epoch 4540, Training loss 2.428632, Validation loss 6.569077\n",
      "Epoch 4541, Training loss 2.428631, Validation loss 6.569091\n",
      "Epoch 4542, Training loss 2.428631, Validation loss 6.569087\n",
      "Epoch 4543, Training loss 2.428631, Validation loss 6.569091\n",
      "Epoch 4544, Training loss 2.428631, Validation loss 6.569087\n",
      "Epoch 4545, Training loss 2.428631, Validation loss 6.569091\n",
      "Epoch 4546, Training loss 2.428631, Validation loss 6.569091\n",
      "Epoch 4547, Training loss 2.428632, Validation loss 6.569087\n",
      "Epoch 4548, Training loss 2.428632, Validation loss 6.569091\n",
      "Epoch 4549, Training loss 2.428631, Validation loss 6.569087\n",
      "Epoch 4550, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4551, Training loss 2.428631, Validation loss 6.569087\n",
      "Epoch 4552, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4553, Training loss 2.428632, Validation loss 6.569102\n",
      "Epoch 4554, Training loss 2.428631, Validation loss 6.569087\n",
      "Epoch 4555, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4556, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4557, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4558, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4559, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4560, Training loss 2.428630, Validation loss 6.569102\n",
      "Epoch 4561, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4562, Training loss 2.428631, Validation loss 6.569102\n",
      "Epoch 4563, Training loss 2.428631, Validation loss 6.569097\n",
      "Epoch 4564, Training loss 2.428630, Validation loss 6.569097\n",
      "Epoch 4565, Training loss 2.428632, Validation loss 6.569112\n",
      "Epoch 4566, Training loss 2.428632, Validation loss 6.569097\n",
      "Epoch 4567, Training loss 2.428630, Validation loss 6.569112\n",
      "Epoch 4568, Training loss 2.428631, Validation loss 6.569107\n",
      "Epoch 4569, Training loss 2.428630, Validation loss 6.569112\n",
      "Epoch 4570, Training loss 2.428631, Validation loss 6.569107\n",
      "Epoch 4571, Training loss 2.428631, Validation loss 6.569107\n",
      "Epoch 4572, Training loss 2.428632, Validation loss 6.569122\n",
      "Epoch 4573, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4574, Training loss 2.428631, Validation loss 6.569112\n",
      "Epoch 4575, Training loss 2.428632, Validation loss 6.569127\n",
      "Epoch 4576, Training loss 2.428632, Validation loss 6.569127\n",
      "Epoch 4577, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4578, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4579, Training loss 2.428631, Validation loss 6.569117\n",
      "Epoch 4580, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4581, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4582, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4583, Training loss 2.428631, Validation loss 6.569122\n",
      "Epoch 4584, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4585, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4586, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4587, Training loss 2.428630, Validation loss 6.569132\n",
      "Epoch 4588, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4589, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4590, Training loss 2.428631, Validation loss 6.569127\n",
      "Epoch 4591, Training loss 2.428632, Validation loss 6.569122\n",
      "Epoch 4592, Training loss 2.428631, Validation loss 6.569132\n",
      "Epoch 4593, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4594, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4595, Training loss 2.428632, Validation loss 6.569142\n",
      "Epoch 4596, Training loss 2.428632, Validation loss 6.569132\n",
      "Epoch 4597, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4598, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4599, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4600, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4601, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4602, Training loss 2.428632, Validation loss 6.569147\n",
      "Epoch 4603, Training loss 2.428632, Validation loss 6.569137\n",
      "Epoch 4604, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4605, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4606, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4607, Training loss 2.428630, Validation loss 6.569137\n",
      "Epoch 4608, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4609, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4610, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4611, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4612, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4613, Training loss 2.428631, Validation loss 6.569137\n",
      "Epoch 4614, Training loss 2.428631, Validation loss 6.569142\n",
      "Epoch 4615, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4616, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4617, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4618, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4619, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4620, Training loss 2.428630, Validation loss 6.569157\n",
      "Epoch 4621, Training loss 2.428630, Validation loss 6.569147\n",
      "Epoch 4622, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4623, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4624, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4625, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4626, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4627, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4628, Training loss 2.428631, Validation loss 6.569152\n",
      "Epoch 4629, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4630, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4631, Training loss 2.428631, Validation loss 6.569147\n",
      "Epoch 4632, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4633, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4634, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4635, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4636, Training loss 2.428631, Validation loss 6.569157\n",
      "Epoch 4637, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4638, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4639, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4640, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4641, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4642, Training loss 2.428632, Validation loss 6.569152\n",
      "Epoch 4643, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4644, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4645, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4646, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4647, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4648, Training loss 2.428630, Validation loss 6.569152\n",
      "Epoch 4649, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4650, Training loss 2.428631, Validation loss 6.569167\n",
      "Epoch 4651, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4652, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4653, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4654, Training loss 2.428631, Validation loss 6.569152\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4655, Training loss 2.428630, Validation loss 6.569158\n",
      "Epoch 4656, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4657, Training loss 2.428632, Validation loss 6.569172\n",
      "Epoch 4658, Training loss 2.428632, Validation loss 6.569162\n",
      "Epoch 4659, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4660, Training loss 2.428630, Validation loss 6.569167\n",
      "Epoch 4661, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4662, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4663, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4664, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4665, Training loss 2.428631, Validation loss 6.569158\n",
      "Epoch 4666, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4667, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4668, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4669, Training loss 2.428631, Validation loss 6.569168\n",
      "Epoch 4670, Training loss 2.428632, Validation loss 6.569167\n",
      "Epoch 4671, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4672, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4673, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4674, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4675, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4676, Training loss 2.428631, Validation loss 6.569162\n",
      "Epoch 4677, Training loss 2.428631, Validation loss 6.569172\n",
      "Epoch 4678, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4679, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4680, Training loss 2.428631, Validation loss 6.569173\n",
      "Epoch 4681, Training loss 2.428630, Validation loss 6.569172\n",
      "Epoch 4682, Training loss 2.428630, Validation loss 6.569162\n",
      "Epoch 4683, Training loss 2.428632, Validation loss 6.569168\n",
      "Epoch 4684, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4685, Training loss 2.428630, Validation loss 6.569168\n",
      "Epoch 4686, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4687, Training loss 2.428631, Validation loss 6.569168\n",
      "Epoch 4688, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4689, Training loss 2.428632, Validation loss 6.569182\n",
      "Epoch 4690, Training loss 2.428632, Validation loss 6.569173\n",
      "Epoch 4691, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4692, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4693, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4694, Training loss 2.428630, Validation loss 6.569173\n",
      "Epoch 4695, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4696, Training loss 2.428631, Validation loss 6.569173\n",
      "Epoch 4697, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4698, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4699, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4700, Training loss 2.428631, Validation loss 6.569173\n",
      "Epoch 4701, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4702, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4703, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4704, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4705, Training loss 2.428631, Validation loss 6.569182\n",
      "Epoch 4706, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4707, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4708, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4709, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4710, Training loss 2.428632, Validation loss 6.569183\n",
      "Epoch 4711, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4712, Training loss 2.428630, Validation loss 6.569188\n",
      "Epoch 4713, Training loss 2.428630, Validation loss 6.569178\n",
      "Epoch 4714, Training loss 2.428630, Validation loss 6.569183\n",
      "Epoch 4715, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4716, Training loss 2.428632, Validation loss 6.569188\n",
      "Epoch 4717, Training loss 2.428632, Validation loss 6.569178\n",
      "Epoch 4718, Training loss 2.428632, Validation loss 6.569183\n",
      "Epoch 4719, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4720, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4721, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4722, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4723, Training loss 2.428631, Validation loss 6.569178\n",
      "Epoch 4724, Training loss 2.428630, Validation loss 6.569183\n",
      "Epoch 4725, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4726, Training loss 2.428631, Validation loss 6.569198\n",
      "Epoch 4727, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4728, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4729, Training loss 2.428632, Validation loss 6.569193\n",
      "Epoch 4730, Training loss 2.428631, Validation loss 6.569198\n",
      "Epoch 4731, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4732, Training loss 2.428630, Validation loss 6.569193\n",
      "Epoch 4733, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4734, Training loss 2.428631, Validation loss 6.569183\n",
      "Epoch 4735, Training loss 2.428631, Validation loss 6.569188\n",
      "Epoch 4736, Training loss 2.428632, Validation loss 6.569198\n",
      "Epoch 4737, Training loss 2.428631, Validation loss 6.569203\n",
      "Epoch 4738, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4739, Training loss 2.428631, Validation loss 6.569193\n",
      "Epoch 4740, Training loss 2.428630, Validation loss 6.569198\n",
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      "Epoch 4742, Training loss 2.428630, Validation loss 6.569193\n",
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      "Epoch 4746, Training loss 2.428632, Validation loss 6.569198\n",
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      "Epoch 4751, Training loss 2.428630, Validation loss 6.569188\n",
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      "Epoch 4841, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4842, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4843, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4844, Training loss 2.428631, Validation loss 6.569224\n",
      "Epoch 4845, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4846, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4847, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4848, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4849, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4850, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4851, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4852, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4853, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4854, Training loss 2.428631, Validation loss 6.569239\n",
      "Epoch 4855, Training loss 2.428631, Validation loss 6.569229\n",
      "Epoch 4856, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4857, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4858, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4859, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4860, Training loss 2.428630, Validation loss 6.569239\n",
      "Epoch 4861, Training loss 2.428630, Validation loss 6.569229\n",
      "Epoch 4862, Training loss 2.428630, Validation loss 6.569234\n",
      "Epoch 4863, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4864, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4865, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4866, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4867, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4868, Training loss 2.428631, Validation loss 6.569234\n",
      "Epoch 4869, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4870, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4871, Training loss 2.428632, Validation loss 6.569244\n",
      "Epoch 4872, Training loss 2.428632, Validation loss 6.569234\n",
      "Epoch 4873, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4874, Training loss 2.428631, Validation loss 6.569249\n",
      "Epoch 4875, Training loss 2.428630, Validation loss 6.569254\n",
      "Epoch 4876, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4877, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4878, Training loss 2.428631, Validation loss 6.569249\n",
      "Epoch 4879, Training loss 2.428631, Validation loss 6.569240\n",
      "Epoch 4880, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4881, Training loss 2.428631, Validation loss 6.569254\n",
      "Epoch 4882, Training loss 2.428630, Validation loss 6.569249\n",
      "Epoch 4883, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4884, Training loss 2.428632, Validation loss 6.569249\n",
      "Epoch 4885, Training loss 2.428632, Validation loss 6.569240\n",
      "Epoch 4886, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4887, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4888, Training loss 2.428630, Validation loss 6.569249\n",
      "Epoch 4889, Training loss 2.428630, Validation loss 6.569240\n",
      "Epoch 4890, Training loss 2.428631, Validation loss 6.569244\n",
      "Epoch 4891, Training loss 2.428632, Validation loss 6.569254\n",
      "Epoch 4892, Training loss 2.428632, Validation loss 6.569244\n",
      "Epoch 4893, Training loss 2.428632, Validation loss 6.569250\n",
      "Epoch 4894, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4895, Training loss 2.428630, Validation loss 6.569254\n",
      "Epoch 4896, Training loss 2.428630, Validation loss 6.569244\n",
      "Epoch 4897, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4898, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4899, Training loss 2.428630, Validation loss 6.569250\n",
      "Epoch 4900, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4901, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4902, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4903, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4904, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4905, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4906, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4907, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4908, Training loss 2.428629, Validation loss 6.569255\n",
      "Epoch 4909, Training loss 2.428629, Validation loss 6.569245\n",
      "Epoch 4910, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4911, Training loss 2.428632, Validation loss 6.569260\n",
      "Epoch 4912, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4913, Training loss 2.428631, Validation loss 6.569250\n",
      "Epoch 4914, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4915, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4916, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4917, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4918, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4919, Training loss 2.428632, Validation loss 6.569264\n",
      "Epoch 4920, Training loss 2.428632, Validation loss 6.569255\n",
      "Epoch 4921, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4922, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4923, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4924, Training loss 2.428631, Validation loss 6.569255\n",
      "Epoch 4925, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4926, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4927, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4928, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4929, Training loss 2.428631, Validation loss 6.569264\n",
      "Epoch 4930, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4931, Training loss 2.428632, Validation loss 6.569260\n",
      "Epoch 4932, Training loss 2.428632, Validation loss 6.569265\n",
      "Epoch 4933, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4934, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4935, Training loss 2.428631, Validation loss 6.569260\n",
      "Epoch 4936, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4937, Training loss 2.428630, Validation loss 6.569260\n",
      "Epoch 4938, Training loss 2.428632, Validation loss 6.569265\n",
      "Epoch 4939, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4940, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4941, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4942, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4943, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4944, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4945, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4946, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4947, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4948, Training loss 2.428630, Validation loss 6.569265\n",
      "Epoch 4949, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4950, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4951, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4952, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4953, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4954, Training loss 2.428630, Validation loss 6.569280\n",
      "Epoch 4955, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4956, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4957, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4958, Training loss 2.428631, Validation loss 6.569265\n",
      "Epoch 4959, Training loss 2.428632, Validation loss 6.569270\n",
      "Epoch 4960, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4961, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4962, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4963, Training loss 2.428630, Validation loss 6.569270\n",
      "Epoch 4964, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4965, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4966, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4967, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4968, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4969, Training loss 2.428631, Validation loss 6.569270\n",
      "Epoch 4970, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4971, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4972, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4973, Training loss 2.428630, Validation loss 6.569280\n",
      "Epoch 4974, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4975, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4976, Training loss 2.428630, Validation loss 6.569275\n",
      "Epoch 4977, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4978, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4979, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4980, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4981, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4982, Training loss 2.428631, Validation loss 6.569275\n",
      "Epoch 4983, Training loss 2.428630, Validation loss 6.569280\n",
      "Epoch 4984, Training loss 2.428632, Validation loss 6.569285\n",
      "Epoch 4985, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4986, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4987, Training loss 2.428631, Validation loss 6.569280\n",
      "Epoch 4988, Training loss 2.428631, Validation loss 6.569290\n",
      "Epoch 4989, Training loss 2.428630, Validation loss 6.569295\n",
      "Epoch 4990, Training loss 2.428630, Validation loss 6.569285\n",
      "Epoch 4991, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4992, Training loss 2.428632, Validation loss 6.569290\n",
      "Epoch 4993, Training loss 2.428632, Validation loss 6.569280\n",
      "Epoch 4994, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4995, Training loss 2.428631, Validation loss 6.569295\n",
      "Epoch 4996, Training loss 2.428631, Validation loss 6.569285\n",
      "Epoch 4997, Training loss 2.428631, Validation loss 6.569291\n",
      "Epoch 4998, Training loss 2.428632, Validation loss 6.569290\n",
      "Epoch 4999, Training loss 2.428631, Validation loss 6.569295\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(Parameter containing:\n",
       " tensor([[5.4878]], requires_grad=True), Parameter containing:\n",
       " tensor([-17.4613], requires_grad=True))"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "model = nn.Linear(1, 1)\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "optimizer = optim.SGD(model.parameters(), lr=learning_rate)\n",
    "\n",
    "loss_fn = nn.MSELoss()\n",
    "\n",
    "nepochs = 5000\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    t_p_train = model(t_un_train)\n",
    "    loss_train = loss_fn(t_p_train, t_c_train)\n",
    "\n",
    "    with torch.no_grad():\n",
    "        t_p_val = model(t_un_val)\n",
    "        loss_val = loss_fn(t_p_val, t_c_val)\n",
    "\n",
    "    print('Epoch %d, Training loss %f, Validation loss %f' % (epoch, float(loss_train), float(loss_val)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss_train.backward()    \n",
    "    optimizer.step()\n",
    "    \n",
    "model.weight, model.bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sequential(\n",
       "  (0): Linear(in_features=1, out_features=10, bias=True)\n",
       "  (1): Tanh()\n",
       "  (2): Linear(in_features=10, out_features=1, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = nn.Sequential(\n",
    "            nn.Linear(1, 10),\n",
    "            nn.Tanh(),\n",
    "            nn.Linear(10, 1))\n",
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[torch.Size([10, 1]), torch.Size([10]), torch.Size([1, 10]), torch.Size([1])]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[param.shape for param in model.parameters()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.weight torch.Size([10, 1])\n",
      "0.bias torch.Size([10])\n",
      "2.weight torch.Size([1, 10])\n",
      "2.bias torch.Size([1])\n"
     ]
    }
   ],
   "source": [
    "for name, param in model.named_parameters():\n",
    "    print(name, param.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sequential(\n",
       "  (hidden_linear): Linear(in_features=1, out_features=10, bias=True)\n",
       "  (hidden_activation): Tanh()\n",
       "  (output_linear): Linear(in_features=10, out_features=1, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import OrderedDict\n",
    "\n",
    "model = nn.Sequential(OrderedDict([\n",
    "    ('hidden_linear', nn.Linear(1, 10)),\n",
    "    ('hidden_activation', nn.Tanh()),\n",
    "    ('output_linear', nn.Linear(10, 1))\n",
    "]))\n",
    "\n",
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hidden_linear.weight torch.Size([10, 1])\n",
      "hidden_linear.bias torch.Size([10])\n",
      "output_linear.weight torch.Size([1, 10])\n",
      "output_linear.bias torch.Size([1])\n"
     ]
    }
   ],
   "source": [
    "for name, param in model.named_parameters():\n",
    "    print(name, param.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Parameter containing:\n",
       "tensor([[-0.0950],\n",
       "        [ 0.5718],\n",
       "        [-0.1405],\n",
       "        [-0.3802],\n",
       "        [ 0.8591],\n",
       "        [-0.8780],\n",
       "        [-0.1615],\n",
       "        [-0.3330],\n",
       "        [ 0.9726],\n",
       "        [-0.6343]], requires_grad=True)"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.hidden_linear.weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0, Training loss 188.202881, Validation loss 136.222977\n",
      "Epoch 1, Training loss 150.089111, Validation loss 91.237564\n",
      "Epoch 2, Training loss 125.055519, Validation loss 62.170696\n",
      "Epoch 3, Training loss 107.771858, Validation loss 42.034805\n",
      "Epoch 4, Training loss 95.981758, Validation loss 28.695263\n",
      "Epoch 5, Training loss 87.523048, Validation loss 20.033142\n",
      "Epoch 6, Training loss 80.909752, Validation loss 14.547966\n",
      "Epoch 7, Training loss 75.393440, Validation loss 11.149405\n",
      "Epoch 8, Training loss 70.702812, Validation loss 8.716105\n",
      "Epoch 9, Training loss 66.611610, Validation loss 6.617854\n",
      "Epoch 10, Training loss 62.936260, Validation loss 5.115901\n",
      "Epoch 11, Training loss 59.520077, Validation loss 3.834637\n",
      "Epoch 12, Training loss 56.252563, Validation loss 3.043854\n",
      "Epoch 13, Training loss 53.085567, Validation loss 2.144593\n",
      "Epoch 14, Training loss 50.177406, Validation loss 2.155064\n",
      "Epoch 15, Training loss 47.875084, Validation loss 0.764214\n",
      "Epoch 16, Training loss 48.680031, Validation loss 5.711440\n",
      "Epoch 17, Training loss 70.819298, Validation loss 6.539827\n",
      "Epoch 18, Training loss 45.117634, Validation loss 1.705493\n",
      "Epoch 19, Training loss 43.745403, Validation loss 1.002231\n",
      "Epoch 20, Training loss 62.779263, Validation loss 22.550776\n",
      "Epoch 21, Training loss 109.944939, Validation loss 15.391956\n",
      "Epoch 22, Training loss 87.499474, Validation loss 5.273516\n",
      "Epoch 23, Training loss 86.618271, Validation loss 5.433077\n",
      "Epoch 24, Training loss 85.102760, Validation loss 0.968221\n",
      "Epoch 25, Training loss 76.580666, Validation loss 0.880462\n",
      "Epoch 26, Training loss 72.048180, Validation loss 0.838404\n",
      "Epoch 27, Training loss 69.421997, Validation loss 0.805673\n",
      "Epoch 28, Training loss 62.210373, Validation loss 0.736177\n",
      "Epoch 29, Training loss 59.585712, Validation loss 4.289258\n",
      "Epoch 30, Training loss 72.343330, Validation loss 3.939681\n",
      "Epoch 31, Training loss 69.813751, Validation loss 3.661477\n",
      "Epoch 32, Training loss 55.094055, Validation loss 0.636955\n",
      "Epoch 33, Training loss 52.274673, Validation loss 1.619797\n",
      "Epoch 34, Training loss 79.979195, Validation loss 30.219894\n",
      "Epoch 35, Training loss 108.668747, Validation loss 14.255305\n",
      "Epoch 36, Training loss 90.254997, Validation loss 7.105915\n",
      "Epoch 37, Training loss 81.673286, Validation loss 1.263896\n",
      "Epoch 38, Training loss 69.352409, Validation loss 1.787565\n",
      "Epoch 39, Training loss 67.121910, Validation loss 4.780434\n",
      "Epoch 40, Training loss 74.308563, Validation loss 2.865013\n",
      "Epoch 41, Training loss 73.233864, Validation loss 2.153057\n",
      "Epoch 42, Training loss 54.405811, Validation loss 0.759353\n",
      "Epoch 43, Training loss 55.133430, Validation loss 6.451164\n",
      "Epoch 44, Training loss 77.712212, Validation loss 6.876225\n",
      "Epoch 45, Training loss 53.713181, Validation loss 0.691898\n",
      "Epoch 46, Training loss 43.604458, Validation loss 0.508772\n",
      "Epoch 47, Training loss 41.269554, Validation loss 1.270763\n",
      "Epoch 48, Training loss 48.032284, Validation loss 5.719485\n",
      "Epoch 49, Training loss 75.484917, Validation loss 36.249390\n",
      "Epoch 50, Training loss 109.997620, Validation loss 16.181046\n",
      "Epoch 51, Training loss 90.736908, Validation loss 8.593626\n",
      "Epoch 52, Training loss 66.301231, Validation loss 1.291996\n",
      "Epoch 53, Training loss 66.447350, Validation loss 3.765539\n",
      "Epoch 54, Training loss 70.372856, Validation loss 2.293092\n",
      "Epoch 55, Training loss 62.951084, Validation loss 1.423502\n",
      "Epoch 56, Training loss 63.198341, Validation loss 1.914119\n",
      "Epoch 57, Training loss 56.967697, Validation loss 3.535026\n",
      "Epoch 58, Training loss 60.448292, Validation loss 4.247518\n",
      "Epoch 59, Training loss 83.741844, Validation loss 18.616880\n",
      "Epoch 60, Training loss 60.130928, Validation loss 3.645747\n",
      "Epoch 61, Training loss 54.595108, Validation loss 1.627113\n",
      "Epoch 62, Training loss 45.136234, Validation loss 1.051045\n",
      "Epoch 63, Training loss 42.040958, Validation loss 1.308910\n",
      "Epoch 64, Training loss 48.324543, Validation loss 9.004208\n",
      "Epoch 65, Training loss 86.159454, Validation loss 38.434875\n",
      "Epoch 66, Training loss 66.450066, Validation loss 10.269223\n",
      "Epoch 67, Training loss 61.564934, Validation loss 5.869538\n",
      "Epoch 68, Training loss 62.936230, Validation loss 1.013806\n",
      "Epoch 69, Training loss 51.716278, Validation loss 2.381294\n",
      "Epoch 70, Training loss 75.816269, Validation loss 19.148706\n",
      "Epoch 71, Training loss 60.622791, Validation loss 5.168776\n",
      "Epoch 72, Training loss 57.950203, Validation loss 1.010424\n",
      "Epoch 73, Training loss 52.307419, Validation loss 9.175933\n",
      "Epoch 74, Training loss 67.611069, Validation loss 3.528175\n",
      "Epoch 75, Training loss 45.746189, Validation loss 0.829644\n",
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      "Epoch 80, Training loss 140.068970, Validation loss 98.133278\n",
      "Epoch 81, Training loss 118.656036, Validation loss 35.475739\n",
      "Epoch 82, Training loss 66.085724, Validation loss 4.641664\n",
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      "Epoch 84, Training loss 59.866032, Validation loss 0.895948\n",
      "Epoch 85, Training loss 65.109222, Validation loss 1.823038\n",
      "Epoch 86, Training loss 51.824162, Validation loss 13.114482\n",
      "Epoch 87, Training loss 83.479126, Validation loss 33.456787\n",
      "Epoch 88, Training loss 73.680527, Validation loss 12.505135\n",
      "Epoch 89, Training loss 70.435104, Validation loss 1.182821\n",
      "Epoch 90, Training loss 71.140129, Validation loss 6.281937\n",
      "Epoch 91, Training loss 63.649334, Validation loss 3.879307\n",
      "Epoch 92, Training loss 53.341606, Validation loss 11.221026\n",
      "Epoch 93, Training loss 66.935478, Validation loss 14.394190\n",
      "Epoch 94, Training loss 60.886833, Validation loss 0.892655\n",
      "Epoch 95, Training loss 44.398464, Validation loss 5.035343\n",
      "Epoch 96, Training loss 55.381866, Validation loss 8.758650\n",
      "Epoch 97, Training loss 72.161636, Validation loss 20.945646\n",
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      "Epoch 100, Training loss 49.205479, Validation loss 1.090995\n",
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      "Epoch 102, Training loss 28.567255, Validation loss 11.722998\n",
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      "Epoch 104, Training loss 111.190788, Validation loss 37.687496\n",
      "Epoch 105, Training loss 59.561481, Validation loss 19.396229\n",
      "Epoch 106, Training loss 57.900440, Validation loss 14.422561\n",
      "Epoch 107, Training loss 76.874557, Validation loss 2.293505\n",
      "Epoch 108, Training loss 62.418526, Validation loss 1.554102\n",
      "Epoch 109, Training loss 47.591389, Validation loss 3.106505\n",
      "Epoch 110, Training loss 68.639534, Validation loss 22.656759\n",
      "Epoch 111, Training loss 49.282101, Validation loss 0.836678\n",
      "Epoch 112, Training loss 47.802265, Validation loss 7.640678\n",
      "Epoch 113, Training loss 61.553417, Validation loss 2.550550\n",
      "Epoch 114, Training loss 42.272652, Validation loss 1.500478\n",
      "Epoch 115, Training loss 30.040598, Validation loss 2.379789\n",
      "Epoch 116, Training loss 67.994682, Validation loss 33.760410\n",
      "Epoch 117, Training loss 48.602020, Validation loss 2.709499\n",
      "Epoch 118, Training loss 39.010429, Validation loss 0.689597\n",
      "Epoch 119, Training loss 25.319740, Validation loss 6.079014\n",
      "Epoch 120, Training loss 29.407255, Validation loss 1.655716\n",
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      "Epoch 124, Training loss 36.422245, Validation loss 1.106288\n",
      "Epoch 125, Training loss 34.035793, Validation loss 4.153983\n",
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      "Epoch 127, Training loss 13.693490, Validation loss 6.818150\n",
      "Epoch 128, Training loss 11.972682, Validation loss 13.425880\n",
      "Epoch 129, Training loss 27.356056, Validation loss 7.566709\n",
      "Epoch 130, Training loss 121.439262, Validation loss 72.712173\n",
      "Epoch 131, Training loss 37.457455, Validation loss 19.578720\n",
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      "Epoch 133, Training loss 40.228813, Validation loss 4.104677\n",
      "Epoch 134, Training loss 15.372277, Validation loss 0.218190\n",
      "Epoch 135, Training loss 44.690418, Validation loss 51.018627\n",
      "Epoch 136, Training loss 82.666664, Validation loss 54.855400\n",
      "Epoch 137, Training loss 97.822487, Validation loss 9.706301\n",
      "Epoch 138, Training loss 82.150467, Validation loss 5.589798\n",
      "Epoch 139, Training loss 52.402649, Validation loss 8.421597\n",
      "Epoch 140, Training loss 39.936687, Validation loss 5.207246\n",
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      "Epoch 144, Training loss 104.084183, Validation loss 46.545895\n",
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      "Epoch 146, Training loss 51.843533, Validation loss 1.983348\n",
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      "Epoch 151, Training loss 34.184357, Validation loss 1.060184\n",
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      "Epoch 153, Training loss 25.034809, Validation loss 1.284300\n",
      "Epoch 154, Training loss 71.483078, Validation loss 68.057541\n",
      "Epoch 155, Training loss 40.979176, Validation loss 9.935998\n",
      "Epoch 156, Training loss 76.494057, Validation loss 54.759197\n",
      "Epoch 157, Training loss 46.107635, Validation loss 4.339132\n",
      "Epoch 158, Training loss 37.477112, Validation loss 1.985982\n",
      "Epoch 159, Training loss 39.105511, Validation loss 6.102532\n",
      "Epoch 160, Training loss 34.030655, Validation loss 2.856300\n",
      "Epoch 161, Training loss 43.981998, Validation loss 10.805421\n",
      "Epoch 162, Training loss 29.222395, Validation loss 0.467854\n",
      "Epoch 163, Training loss 38.589378, Validation loss 13.657401\n",
      "Epoch 164, Training loss 25.249800, Validation loss 1.932532\n",
      "Epoch 165, Training loss 24.337599, Validation loss 10.132791\n",
      "Epoch 166, Training loss 31.664259, Validation loss 4.977683\n",
      "Epoch 167, Training loss 67.619545, Validation loss 26.857227\n",
      "Epoch 168, Training loss 23.754499, Validation loss 3.971027\n",
      "Epoch 169, Training loss 22.655516, Validation loss 0.707431\n",
      "Epoch 170, Training loss 30.962572, Validation loss 21.926662\n",
      "Epoch 171, Training loss 42.295425, Validation loss 12.824355\n",
      "Epoch 172, Training loss 91.616867, Validation loss 34.835369\n",
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      "Epoch 175, Training loss 32.020359, Validation loss 13.407646\n",
      "Epoch 176, Training loss 52.059875, Validation loss 9.690411\n",
      "Epoch 177, Training loss 48.745232, Validation loss 26.712757\n",
      "Epoch 178, Training loss 48.534966, Validation loss 2.163431\n",
      "Epoch 179, Training loss 19.877708, Validation loss 1.041355\n",
      "Epoch 180, Training loss 21.132433, Validation loss 15.709188\n",
      "Epoch 181, Training loss 42.937286, Validation loss 4.825353\n",
      "Epoch 182, Training loss 53.461582, Validation loss 42.147942\n",
      "Epoch 183, Training loss 22.093172, Validation loss 0.398994\n",
      "Epoch 184, Training loss 53.332195, Validation loss 41.447304\n",
      "Epoch 185, Training loss 18.916389, Validation loss 0.214236\n",
      "Epoch 186, Training loss 42.256966, Validation loss 38.892761\n",
      "Epoch 187, Training loss 20.877779, Validation loss 0.107939\n",
      "Epoch 188, Training loss 54.534122, Validation loss 41.747375\n",
      "Epoch 189, Training loss 17.882389, Validation loss 1.458125\n",
      "Epoch 190, Training loss 32.477169, Validation loss 35.439907\n",
      "Epoch 191, Training loss 35.287922, Validation loss 12.893023\n",
      "Epoch 192, Training loss 97.834808, Validation loss 46.786503\n",
      "Epoch 193, Training loss 49.841408, Validation loss 28.322666\n",
      "Epoch 194, Training loss 39.605408, Validation loss 0.831564\n",
      "Epoch 195, Training loss 35.953609, Validation loss 1.215887\n",
      "Epoch 196, Training loss 26.564907, Validation loss 0.168763\n",
      "Epoch 197, Training loss 39.062096, Validation loss 38.804512\n",
      "Epoch 198, Training loss 37.067982, Validation loss 3.312617\n",
      "Epoch 199, Training loss 56.114605, Validation loss 45.140800\n",
      "Epoch 200, Training loss 16.560074, Validation loss 1.862582\n",
      "Epoch 201, Training loss 30.512438, Validation loss 36.655014\n",
      "Epoch 202, Training loss 42.767860, Validation loss 25.523722\n",
      "Epoch 203, Training loss 105.190063, Validation loss 50.266003\n",
      "Epoch 204, Training loss 55.226822, Validation loss 25.896603\n",
      "Epoch 205, Training loss 44.051586, Validation loss 0.855164\n",
      "Epoch 206, Training loss 38.701439, Validation loss 0.981959\n",
      "Epoch 207, Training loss 37.248146, Validation loss 2.565227\n",
      "Epoch 208, Training loss 31.758528, Validation loss 0.221515\n",
      "Epoch 209, Training loss 31.157368, Validation loss 4.594879\n",
      "Epoch 210, Training loss 32.976360, Validation loss 3.429501\n",
      "Epoch 211, Training loss 52.636204, Validation loss 12.871094\n",
      "Epoch 212, Training loss 26.567341, Validation loss 3.869768\n",
      "Epoch 213, Training loss 26.956455, Validation loss 0.482947\n",
      "Epoch 214, Training loss 32.669899, Validation loss 14.785099\n",
      "Epoch 215, Training loss 35.504002, Validation loss 4.678892\n",
      "Epoch 216, Training loss 43.344357, Validation loss 21.257896\n",
      "Epoch 217, Training loss 36.975319, Validation loss 6.096017\n",
      "Epoch 218, Training loss 55.468185, Validation loss 24.002811\n",
      "Epoch 219, Training loss 55.376633, Validation loss 4.462302\n",
      "Epoch 220, Training loss 30.634056, Validation loss 19.813473\n",
      "Epoch 221, Training loss 46.870419, Validation loss 6.600374\n",
      "Epoch 222, Training loss 54.354000, Validation loss 31.929436\n",
      "Epoch 223, Training loss 18.294641, Validation loss 4.994111\n",
      "Epoch 224, Training loss 16.564240, Validation loss 10.644855\n",
      "Epoch 225, Training loss 20.402826, Validation loss 0.892590\n",
      "Epoch 226, Training loss 49.642616, Validation loss 45.827824\n",
      "Epoch 227, Training loss 10.153070, Validation loss 9.513924\n",
      "Epoch 228, Training loss 16.540611, Validation loss 53.753967\n",
      "Epoch 229, Training loss 142.842117, Validation loss 133.952667\n",
      "Epoch 230, Training loss 140.536774, Validation loss 105.325859\n",
      "Epoch 231, Training loss 51.767754, Validation loss 2.548903\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 232, Training loss 75.779999, Validation loss 66.181656\n",
      "Epoch 233, Training loss 49.276592, Validation loss 3.114651\n",
      "Epoch 234, Training loss 57.732765, Validation loss 5.054900\n",
      "Epoch 235, Training loss 42.667252, Validation loss 0.304515\n",
      "Epoch 236, Training loss 42.240395, Validation loss 3.882009\n",
      "Epoch 237, Training loss 50.448311, Validation loss 12.433903\n",
      "Epoch 238, Training loss 69.159485, Validation loss 8.507136\n",
      "Epoch 239, Training loss 52.538158, Validation loss 3.046782\n",
      "Epoch 240, Training loss 35.436962, Validation loss 2.210200\n",
      "Epoch 241, Training loss 39.319572, Validation loss 5.540761\n",
      "Epoch 242, Training loss 56.817757, Validation loss 10.055670\n",
      "Epoch 243, Training loss 31.915648, Validation loss 2.608111\n",
      "Epoch 244, Training loss 33.952797, Validation loss 2.927378\n",
      "Epoch 245, Training loss 45.910721, Validation loss 12.795069\n",
      "Epoch 246, Training loss 25.914827, Validation loss 0.867138\n",
      "Epoch 247, Training loss 25.890924, Validation loss 10.627375\n",
      "Epoch 248, Training loss 49.526424, Validation loss 27.620127\n",
      "Epoch 249, Training loss 88.138260, Validation loss 26.037930\n",
      "Epoch 250, Training loss 66.045830, Validation loss 15.144862\n",
      "Epoch 251, Training loss 56.069714, Validation loss 3.872609\n",
      "Epoch 252, Training loss 49.248440, Validation loss 16.001856\n",
      "Epoch 253, Training loss 32.939468, Validation loss 0.189991\n",
      "Epoch 254, Training loss 42.697109, Validation loss 15.051481\n",
      "Epoch 255, Training loss 27.330790, Validation loss 0.296701\n",
      "Epoch 256, Training loss 36.071030, Validation loss 16.448675\n",
      "Epoch 257, Training loss 20.720432, Validation loss 6.269170\n",
      "Epoch 258, Training loss 21.576187, Validation loss 0.138368\n",
      "Epoch 259, Training loss 37.128868, Validation loss 23.658079\n",
      "Epoch 260, Training loss 17.745440, Validation loss 6.157141\n",
      "Epoch 261, Training loss 16.423040, Validation loss 4.894213\n",
      "Epoch 262, Training loss 17.194422, Validation loss 16.405067\n",
      "Epoch 263, Training loss 43.417061, Validation loss 33.598572\n",
      "Epoch 264, Training loss 95.684822, Validation loss 41.874802\n",
      "Epoch 265, Training loss 62.213341, Validation loss 24.533224\n",
      "Epoch 266, Training loss 45.660385, Validation loss 0.982519\n",
      "Epoch 267, Training loss 41.417206, Validation loss 1.244154\n",
      "Epoch 268, Training loss 35.080063, Validation loss 0.834175\n",
      "Epoch 269, Training loss 32.161068, Validation loss 0.124771\n",
      "Epoch 270, Training loss 34.732376, Validation loss 6.241729\n",
      "Epoch 271, Training loss 28.876099, Validation loss 0.221656\n",
      "Epoch 272, Training loss 36.169716, Validation loss 11.507915\n",
      "Epoch 273, Training loss 25.954403, Validation loss 8.108714\n",
      "Epoch 274, Training loss 34.910492, Validation loss 8.980914\n",
      "Epoch 275, Training loss 58.543877, Validation loss 21.839834\n",
      "Epoch 276, Training loss 22.528044, Validation loss 4.045698\n",
      "Epoch 277, Training loss 20.933481, Validation loss 1.101960\n",
      "Epoch 278, Training loss 21.463192, Validation loss 22.174334\n",
      "Epoch 279, Training loss 34.351654, Validation loss 14.951490\n",
      "Epoch 280, Training loss 122.159889, Validation loss 81.444267\n",
      "Epoch 281, Training loss 38.658566, Validation loss 43.586983\n",
      "Epoch 282, Training loss 48.206474, Validation loss 2.703720\n",
      "Epoch 283, Training loss 39.871964, Validation loss 0.795329\n",
      "Epoch 284, Training loss 38.422169, Validation loss 1.722051\n",
      "Epoch 285, Training loss 43.432766, Validation loss 3.595771\n",
      "Epoch 286, Training loss 32.739765, Validation loss 2.548962\n",
      "Epoch 287, Training loss 36.592903, Validation loss 6.449761\n",
      "Epoch 288, Training loss 49.917240, Validation loss 9.332778\n",
      "Epoch 289, Training loss 35.475891, Validation loss 2.484617\n",
      "Epoch 290, Training loss 45.239147, Validation loss 12.740651\n",
      "Epoch 291, Training loss 25.851179, Validation loss 2.198431\n",
      "Epoch 292, Training loss 20.379223, Validation loss 3.290876\n",
      "Epoch 293, Training loss 8.714318, Validation loss 37.830826\n",
      "Epoch 294, Training loss 75.022636, Validation loss 58.051228\n",
      "Epoch 295, Training loss 159.541946, Validation loss 120.602791\n",
      "Epoch 296, Training loss 47.797390, Validation loss 72.927505\n",
      "Epoch 297, Training loss 107.440742, Validation loss 83.612381\n",
      "Epoch 298, Training loss 73.991348, Validation loss 4.536131\n",
      "Epoch 299, Training loss 63.351067, Validation loss 3.381332\n",
      "Epoch 300, Training loss 56.858784, Validation loss 63.311806\n",
      "Epoch 301, Training loss 46.030972, Validation loss 1.515953\n",
      "Epoch 302, Training loss 45.351604, Validation loss 1.027595\n",
      "Epoch 303, Training loss 43.572350, Validation loss 1.980765\n",
      "Epoch 304, Training loss 47.501587, Validation loss 2.806103\n",
      "Epoch 305, Training loss 39.008751, Validation loss 0.459046\n",
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      "Epoch 307, Training loss 36.230633, Validation loss 0.922534\n",
      "Epoch 308, Training loss 35.035900, Validation loss 0.470299\n",
      "Epoch 309, Training loss 34.598839, Validation loss 3.687891\n",
      "Epoch 310, Training loss 40.643818, Validation loss 7.182279\n",
      "Epoch 311, Training loss 57.168510, Validation loss 11.634871\n",
      "Epoch 312, Training loss 28.984745, Validation loss 5.933853\n",
      "Epoch 313, Training loss 37.044231, Validation loss 9.646644\n",
      "Epoch 314, Training loss 46.073238, Validation loss 15.849907\n",
      "Epoch 315, Training loss 24.174543, Validation loss 10.009675\n",
      "Epoch 316, Training loss 23.997524, Validation loss 9.400969\n",
      "Epoch 317, Training loss 58.246986, Validation loss 68.210258\n",
      "Epoch 318, Training loss 17.521654, Validation loss 38.478924\n",
      "Epoch 319, Training loss 73.554535, Validation loss 73.137482\n",
      "Epoch 320, Training loss 126.250175, Validation loss 70.848183\n",
      "Epoch 321, Training loss 74.592575, Validation loss 46.058987\n",
      "Epoch 322, Training loss 34.245995, Validation loss 1.002867\n",
      "Epoch 323, Training loss 39.051819, Validation loss 26.076437\n",
      "Epoch 324, Training loss 66.236496, Validation loss 6.409334\n",
      "Epoch 325, Training loss 30.788387, Validation loss 0.843072\n",
      "Epoch 326, Training loss 44.236454, Validation loss 34.023029\n",
      "Epoch 327, Training loss 21.919897, Validation loss 0.714438\n",
      "Epoch 328, Training loss 24.444828, Validation loss 25.117496\n",
      "Epoch 329, Training loss 53.161980, Validation loss 13.115885\n",
      "Epoch 330, Training loss 48.422729, Validation loss 42.416992\n",
      "Epoch 331, Training loss 26.559732, Validation loss 30.033060\n",
      "Epoch 332, Training loss 33.718811, Validation loss 7.343309\n",
      "Epoch 333, Training loss 48.165497, Validation loss 44.842503\n",
      "Epoch 334, Training loss 28.461878, Validation loss 33.712616\n",
      "Epoch 335, Training loss 31.664104, Validation loss 8.464482\n",
      "Epoch 336, Training loss 47.180805, Validation loss 45.871552\n",
      "Epoch 337, Training loss 29.748632, Validation loss 35.001251\n",
      "Epoch 338, Training loss 25.714991, Validation loss 1.176640\n",
      "Epoch 339, Training loss 50.154232, Validation loss 45.441277\n",
      "Epoch 340, Training loss 25.212942, Validation loss 31.315773\n",
      "Epoch 341, Training loss 35.060459, Validation loss 7.699202\n",
      "Epoch 342, Training loss 46.899517, Validation loss 46.499641\n",
      "Epoch 343, Training loss 25.705200, Validation loss 33.997471\n",
      "Epoch 344, Training loss 42.867279, Validation loss 10.228229\n",
      "Epoch 345, Training loss 49.139164, Validation loss 47.390430\n",
      "Epoch 346, Training loss 15.042575, Validation loss 13.406125\n",
      "Epoch 347, Training loss 19.012171, Validation loss 1.248621\n",
      "Epoch 348, Training loss 36.998222, Validation loss 45.769810\n",
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      "Epoch 350, Training loss 28.078112, Validation loss 41.545265\n",
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      "Epoch 356, Training loss 17.216650, Validation loss 1.877899\n",
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      "Epoch 365, Training loss 14.568661, Validation loss 0.181796\n",
      "Epoch 366, Training loss 29.986315, Validation loss 52.103443\n",
      "Epoch 367, Training loss 39.965855, Validation loss 17.694658\n",
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      "Epoch 369, Training loss 24.000937, Validation loss 43.438965\n",
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      "Epoch 373, Training loss 9.115666, Validation loss 13.691843\n",
      "Epoch 374, Training loss 10.472707, Validation loss 1.941965\n",
      "Epoch 375, Training loss 25.781254, Validation loss 61.697708\n",
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      "Epoch 379, Training loss 31.179502, Validation loss 0.361096\n",
      "Epoch 380, Training loss 26.440594, Validation loss 3.821286\n",
      "Epoch 381, Training loss 9.874971, Validation loss 0.412758\n",
      "Epoch 382, Training loss 29.112020, Validation loss 76.077827\n",
      "Epoch 383, Training loss 29.454191, Validation loss 0.022819\n",
      "Epoch 384, Training loss 34.478737, Validation loss 10.811291\n",
      "Epoch 385, Training loss 25.032215, Validation loss 7.166121\n",
      "Epoch 386, Training loss 28.590616, Validation loss 1.819534\n",
      "Epoch 387, Training loss 40.271229, Validation loss 19.264463\n",
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      "Epoch 391, Training loss 69.458809, Validation loss 63.936295\n",
      "Epoch 392, Training loss 74.463448, Validation loss 27.431007\n",
      "Epoch 393, Training loss 29.067432, Validation loss 12.048976\n",
      "Epoch 394, Training loss 52.094978, Validation loss 4.281846\n",
      "Epoch 395, Training loss 16.452782, Validation loss 16.148310\n",
      "Epoch 396, Training loss 17.629173, Validation loss 5.933511\n",
      "Epoch 397, Training loss 12.617379, Validation loss 7.837291\n",
      "Epoch 398, Training loss 15.389823, Validation loss 78.134842\n",
      "Epoch 399, Training loss 112.993164, Validation loss 98.364777\n",
      "Epoch 400, Training loss 41.142368, Validation loss 23.878611\n",
      "Epoch 401, Training loss 38.405659, Validation loss 0.828503\n",
      "Epoch 402, Training loss 34.547344, Validation loss 51.214653\n",
      "Epoch 403, Training loss 39.254570, Validation loss 2.491954\n",
      "Epoch 404, Training loss 23.677151, Validation loss 27.314154\n",
      "Epoch 405, Training loss 15.852333, Validation loss 11.616129\n",
      "Epoch 406, Training loss 8.793417, Validation loss 0.207769\n",
      "Epoch 407, Training loss 45.027637, Validation loss 114.482285\n",
      "Epoch 408, Training loss 79.377785, Validation loss 34.663124\n",
      "Epoch 409, Training loss 58.254799, Validation loss 1.278180\n",
      "Epoch 410, Training loss 48.029125, Validation loss 1.171317\n",
      "Epoch 411, Training loss 42.781277, Validation loss 0.615607\n",
      "Epoch 412, Training loss 40.977932, Validation loss 0.607557\n",
      "Epoch 413, Training loss 39.608486, Validation loss 1.678879\n",
      "Epoch 414, Training loss 39.446770, Validation loss 0.025169\n",
      "Epoch 415, Training loss 44.196629, Validation loss 5.697085\n",
      "Epoch 416, Training loss 37.846905, Validation loss 0.000107\n",
      "Epoch 417, Training loss 43.788918, Validation loss 7.524011\n",
      "Epoch 418, Training loss 22.593975, Validation loss 2.051311\n",
      "Epoch 419, Training loss 27.712803, Validation loss 65.471336\n",
      "Epoch 420, Training loss 89.986618, Validation loss 59.887814\n",
      "Epoch 421, Training loss 38.308334, Validation loss 55.598518\n",
      "Epoch 422, Training loss 61.069874, Validation loss 3.322539\n",
      "Epoch 423, Training loss 57.035530, Validation loss 2.175529\n",
      "Epoch 424, Training loss 50.286526, Validation loss 1.444543\n",
      "Epoch 425, Training loss 13.180573, Validation loss 8.389235\n",
      "Epoch 426, Training loss 11.484343, Validation loss 16.819561\n",
      "Epoch 427, Training loss 10.670385, Validation loss 5.457948\n",
      "Epoch 428, Training loss 16.053450, Validation loss 58.524544\n",
      "Epoch 429, Training loss 62.000626, Validation loss 38.533688\n",
      "Epoch 430, Training loss 73.061760, Validation loss 102.291138\n",
      "Epoch 431, Training loss 27.717735, Validation loss 1.804701\n",
      "Epoch 432, Training loss 53.724480, Validation loss 85.089462\n",
      "Epoch 433, Training loss 18.259604, Validation loss 2.765673\n",
      "Epoch 434, Training loss 11.434959, Validation loss 68.852829\n",
      "Epoch 435, Training loss 58.186176, Validation loss 55.769241\n",
      "Epoch 436, Training loss 83.345345, Validation loss 115.517097\n",
      "Epoch 437, Training loss 16.518278, Validation loss 38.997032\n",
      "Epoch 438, Training loss 35.749031, Validation loss 18.215260\n",
      "Epoch 439, Training loss 58.167870, Validation loss 72.794998\n",
      "Epoch 440, Training loss 27.533468, Validation loss 53.655640\n",
      "Epoch 441, Training loss 66.348068, Validation loss 47.843258\n",
      "Epoch 442, Training loss 75.025475, Validation loss 66.969254\n",
      "Epoch 443, Training loss 20.232737, Validation loss 40.620796\n",
      "Epoch 444, Training loss 38.433277, Validation loss 7.143627\n",
      "Epoch 445, Training loss 43.261150, Validation loss 55.580956\n",
      "Epoch 446, Training loss 25.915512, Validation loss 0.839074\n",
      "Epoch 447, Training loss 35.084541, Validation loss 50.741440\n",
      "Epoch 448, Training loss 18.160593, Validation loss 0.358871\n",
      "Epoch 449, Training loss 29.691891, Validation loss 49.831829\n",
      "Epoch 450, Training loss 34.415703, Validation loss 0.814875\n",
      "Epoch 451, Training loss 14.281769, Validation loss 42.354343\n",
      "Epoch 452, Training loss 30.099306, Validation loss 20.354542\n",
      "Epoch 453, Training loss 49.924877, Validation loss 66.877884\n",
      "Epoch 454, Training loss 12.603898, Validation loss 3.599426\n",
      "Epoch 455, Training loss 14.218846, Validation loss 29.876402\n",
      "Epoch 456, Training loss 23.523329, Validation loss 2.887733\n",
      "Epoch 457, Training loss 39.628216, Validation loss 64.125160\n",
      "Epoch 458, Training loss 19.130424, Validation loss 2.442740\n",
      "Epoch 459, Training loss 31.685608, Validation loss 63.196972\n",
      "Epoch 460, Training loss 49.783428, Validation loss 39.658810\n",
      "Epoch 461, Training loss 59.182068, Validation loss 74.083878\n",
      "Epoch 462, Training loss 34.884762, Validation loss 56.248684\n",
      "Epoch 463, Training loss 29.651270, Validation loss 9.148705\n",
      "Epoch 464, Training loss 43.057957, Validation loss 63.553944\n",
      "Epoch 465, Training loss 19.300592, Validation loss 1.768371\n",
      "Epoch 466, Training loss 22.521582, Validation loss 54.202221\n",
      "Epoch 467, Training loss 52.627018, Validation loss 57.626835\n",
      "Epoch 468, Training loss 54.725819, Validation loss 69.824806\n",
      "Epoch 469, Training loss 38.865402, Validation loss 55.313530\n",
      "Epoch 470, Training loss 12.580521, Validation loss 11.027719\n",
      "Epoch 471, Training loss 11.407351, Validation loss 18.625309\n",
      "Epoch 472, Training loss 11.704053, Validation loss 2.430834\n",
      "Epoch 473, Training loss 15.717930, Validation loss 40.555984\n",
      "Epoch 474, Training loss 27.397310, Validation loss 10.554416\n",
      "Epoch 475, Training loss 39.354874, Validation loss 68.634689\n",
      "Epoch 476, Training loss 37.756283, Validation loss 1.952485\n",
      "Epoch 477, Training loss 20.004597, Validation loss 2.517909\n",
      "Epoch 478, Training loss 15.131277, Validation loss 37.403671\n",
      "Epoch 479, Training loss 47.462051, Validation loss 18.303637\n",
      "Epoch 480, Training loss 24.698439, Validation loss 35.381359\n",
      "Epoch 481, Training loss 32.593765, Validation loss 5.752198\n",
      "Epoch 482, Training loss 29.601234, Validation loss 0.321716\n",
      "Epoch 483, Training loss 32.332241, Validation loss 12.059843\n",
      "Epoch 484, Training loss 24.397844, Validation loss 1.371361\n",
      "Epoch 485, Training loss 26.084641, Validation loss 16.082611\n",
      "Epoch 486, Training loss 31.266491, Validation loss 8.009584\n",
      "Epoch 487, Training loss 32.468773, Validation loss 28.051119\n",
      "Epoch 488, Training loss 19.670639, Validation loss 80.431931\n",
      "Epoch 489, Training loss 76.698692, Validation loss 27.206100\n",
      "Epoch 490, Training loss 41.259727, Validation loss 30.592096\n",
      "Epoch 491, Training loss 31.002378, Validation loss 41.035580\n",
      "Epoch 492, Training loss 28.527620, Validation loss 20.089811\n",
      "Epoch 493, Training loss 7.381019, Validation loss 28.396112\n",
      "Epoch 494, Training loss 6.148661, Validation loss 13.707011\n",
      "Epoch 495, Training loss 7.070354, Validation loss 25.129822\n",
      "Epoch 496, Training loss 20.255722, Validation loss 3.556656\n",
      "Epoch 497, Training loss 61.997990, Validation loss 118.711823\n",
      "Epoch 498, Training loss 36.366695, Validation loss 8.789732\n",
      "Epoch 499, Training loss 26.564434, Validation loss 6.624624\n",
      "Epoch 500, Training loss 27.082666, Validation loss 0.158440\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 501, Training loss 33.792725, Validation loss 15.058035\n",
      "Epoch 502, Training loss 22.999510, Validation loss 1.917233\n",
      "Epoch 503, Training loss 26.154413, Validation loss 16.972994\n",
      "Epoch 504, Training loss 36.225079, Validation loss 17.544306\n",
      "Epoch 505, Training loss 44.739883, Validation loss 27.032108\n",
      "Epoch 506, Training loss 22.614887, Validation loss 17.033224\n",
      "Epoch 507, Training loss 27.514246, Validation loss 6.954543\n",
      "Epoch 508, Training loss 34.052082, Validation loss 27.799284\n",
      "Epoch 509, Training loss 23.210176, Validation loss 0.854998\n",
      "Epoch 510, Training loss 46.492729, Validation loss 32.972263\n",
      "Epoch 511, Training loss 25.235857, Validation loss 24.412657\n",
      "Epoch 512, Training loss 38.442402, Validation loss 20.609032\n",
      "Epoch 513, Training loss 40.567562, Validation loss 34.149380\n",
      "Epoch 514, Training loss 22.353720, Validation loss 18.765388\n",
      "Epoch 515, Training loss 51.071659, Validation loss 5.401290\n",
      "Epoch 516, Training loss 47.510014, Validation loss 41.184189\n",
      "Epoch 517, Training loss 27.008287, Validation loss 26.131903\n",
      "Epoch 518, Training loss 46.641083, Validation loss 2.342072\n",
      "Epoch 519, Training loss 15.746004, Validation loss 15.911375\n",
      "Epoch 520, Training loss 32.671375, Validation loss 6.361736\n",
      "Epoch 521, Training loss 68.008949, Validation loss 53.950584\n",
      "Epoch 522, Training loss 19.205702, Validation loss 24.545385\n",
      "Epoch 523, Training loss 83.711960, Validation loss 80.442184\n",
      "Epoch 524, Training loss 43.961456, Validation loss 31.447292\n",
      "Epoch 525, Training loss 41.824856, Validation loss 1.053161\n",
      "Epoch 526, Training loss 35.643154, Validation loss 1.285066\n",
      "Epoch 527, Training loss 33.709511, Validation loss 0.050582\n",
      "Epoch 528, Training loss 35.379066, Validation loss 5.247728\n",
      "Epoch 529, Training loss 27.379818, Validation loss 2.129989\n",
      "Epoch 530, Training loss 26.359686, Validation loss 7.283662\n",
      "Epoch 531, Training loss 30.520712, Validation loss 3.004439\n",
      "Epoch 532, Training loss 38.587780, Validation loss 15.722445\n",
      "Epoch 533, Training loss 35.461624, Validation loss 14.195788\n",
      "Epoch 534, Training loss 30.090078, Validation loss 13.159118\n",
      "Epoch 535, Training loss 27.648323, Validation loss 0.502773\n",
      "Epoch 536, Training loss 38.783154, Validation loss 21.935839\n",
      "Epoch 537, Training loss 25.968584, Validation loss 17.935608\n",
      "Epoch 538, Training loss 39.721130, Validation loss 27.684561\n",
      "Epoch 539, Training loss 40.309593, Validation loss 27.946930\n",
      "Epoch 540, Training loss 32.085064, Validation loss 22.583761\n",
      "Epoch 541, Training loss 23.773037, Validation loss 0.544181\n",
      "Epoch 542, Training loss 42.324738, Validation loss 30.307945\n",
      "Epoch 543, Training loss 30.793989, Validation loss 24.597527\n",
      "Epoch 544, Training loss 28.070444, Validation loss 5.844359\n",
      "Epoch 545, Training loss 42.737434, Validation loss 32.342392\n",
      "Epoch 546, Training loss 30.538023, Validation loss 25.975777\n",
      "Epoch 547, Training loss 29.500246, Validation loss 6.500345\n",
      "Epoch 548, Training loss 47.673904, Validation loss 34.589119\n",
      "Epoch 549, Training loss 34.871269, Validation loss 27.505531\n",
      "Epoch 550, Training loss 22.731823, Validation loss 1.908493\n",
      "Epoch 551, Training loss 37.851341, Validation loss 30.787136\n",
      "Epoch 552, Training loss 19.971989, Validation loss 22.563145\n",
      "Epoch 553, Training loss 35.036434, Validation loss 18.950003\n",
      "Epoch 554, Training loss 44.372993, Validation loss 45.060871\n",
      "Epoch 555, Training loss 23.530357, Validation loss 28.920845\n",
      "Epoch 556, Training loss 27.107143, Validation loss 21.706369\n",
      "Epoch 557, Training loss 48.173080, Validation loss 115.684212\n",
      "Epoch 558, Training loss 66.390884, Validation loss 35.222492\n",
      "Epoch 559, Training loss 45.122311, Validation loss 1.058616\n",
      "Epoch 560, Training loss 41.154778, Validation loss 1.262471\n",
      "Epoch 561, Training loss 36.575596, Validation loss 1.554519\n",
      "Epoch 562, Training loss 22.754656, Validation loss 0.958644\n",
      "Epoch 563, Training loss 40.853607, Validation loss 133.349945\n",
      "Epoch 564, Training loss 159.546539, Validation loss 165.078186\n",
      "Epoch 565, Training loss 66.520279, Validation loss 50.219646\n",
      "Epoch 566, Training loss 25.462946, Validation loss 3.095728\n",
      "Epoch 567, Training loss 67.614502, Validation loss 133.379990\n",
      "Epoch 568, Training loss 34.770576, Validation loss 20.793236\n",
      "Epoch 569, Training loss 21.460367, Validation loss 6.822656\n",
      "Epoch 570, Training loss 21.968239, Validation loss 1.074276\n",
      "Epoch 571, Training loss 37.889248, Validation loss 29.155888\n",
      "Epoch 572, Training loss 18.526667, Validation loss 18.408997\n",
      "Epoch 573, Training loss 19.476912, Validation loss 2.208320\n",
      "Epoch 574, Training loss 29.198713, Validation loss 32.442387\n",
      "Epoch 575, Training loss 38.650066, Validation loss 20.203663\n",
      "Epoch 576, Training loss 40.496353, Validation loss 39.622116\n",
      "Epoch 577, Training loss 15.762302, Validation loss 19.307135\n",
      "Epoch 578, Training loss 15.439899, Validation loss 12.406163\n",
      "Epoch 579, Training loss 16.986393, Validation loss 31.109192\n",
      "Epoch 580, Training loss 25.503172, Validation loss 6.515719\n",
      "Epoch 581, Training loss 49.960712, Validation loss 49.659386\n",
      "Epoch 582, Training loss 29.820614, Validation loss 9.589415\n",
      "Epoch 583, Training loss 30.336761, Validation loss 42.628086\n",
      "Epoch 584, Training loss 43.744892, Validation loss 18.890295\n",
      "Epoch 585, Training loss 43.046333, Validation loss 49.756493\n",
      "Epoch 586, Training loss 14.160836, Validation loss 7.037714\n",
      "Epoch 587, Training loss 17.252279, Validation loss 36.237598\n",
      "Epoch 588, Training loss 23.200548, Validation loss 8.237538\n",
      "Epoch 589, Training loss 28.585365, Validation loss 50.378639\n",
      "Epoch 590, Training loss 46.975754, Validation loss 14.294964\n",
      "Epoch 591, Training loss 48.032913, Validation loss 57.675846\n",
      "Epoch 592, Training loss 12.971696, Validation loss 0.937576\n",
      "Epoch 593, Training loss 38.460987, Validation loss 85.891808\n",
      "Epoch 594, Training loss 44.287258, Validation loss 4.745943\n",
      "Epoch 595, Training loss 44.159676, Validation loss 47.581436\n",
      "Epoch 596, Training loss 12.893234, Validation loss 1.748327\n",
      "Epoch 597, Training loss 15.007483, Validation loss 50.972797\n",
      "Epoch 598, Training loss 22.392046, Validation loss 17.425232\n",
      "Epoch 599, Training loss 28.679102, Validation loss 96.122849\n",
      "Epoch 600, Training loss 47.543114, Validation loss 28.269625\n",
      "Epoch 601, Training loss 36.034168, Validation loss 35.457458\n",
      "Epoch 602, Training loss 7.373916, Validation loss 12.309338\n",
      "Epoch 603, Training loss 5.772570, Validation loss 38.147228\n",
      "Epoch 604, Training loss 11.154088, Validation loss 4.419096\n",
      "Epoch 605, Training loss 12.534155, Validation loss 65.521225\n",
      "Epoch 606, Training loss 24.072351, Validation loss 16.132362\n",
      "Epoch 607, Training loss 31.890762, Validation loss 104.615929\n",
      "Epoch 608, Training loss 44.505833, Validation loss 23.969719\n",
      "Epoch 609, Training loss 35.682739, Validation loss 40.558723\n",
      "Epoch 610, Training loss 22.485481, Validation loss 7.944152\n",
      "Epoch 611, Training loss 13.755894, Validation loss 39.500271\n",
      "Epoch 612, Training loss 12.487520, Validation loss 6.762916\n",
      "Epoch 613, Training loss 14.526956, Validation loss 83.823288\n",
      "Epoch 614, Training loss 36.293686, Validation loss 10.965183\n",
      "Epoch 615, Training loss 12.473163, Validation loss 28.571835\n",
      "Epoch 616, Training loss 7.025993, Validation loss 0.148857\n",
      "Epoch 617, Training loss 10.693221, Validation loss 46.935284\n",
      "Epoch 618, Training loss 14.392536, Validation loss 2.075433\n",
      "Epoch 619, Training loss 17.191282, Validation loss 62.120628\n",
      "Epoch 620, Training loss 22.674177, Validation loss 0.466242\n",
      "Epoch 621, Training loss 36.907848, Validation loss 149.399170\n",
      "Epoch 622, Training loss 56.383503, Validation loss 31.861504\n",
      "Epoch 623, Training loss 38.425472, Validation loss 11.380044\n",
      "Epoch 624, Training loss 21.024338, Validation loss 56.872856\n",
      "Epoch 625, Training loss 26.874065, Validation loss 7.566489\n",
      "Epoch 626, Training loss 30.141432, Validation loss 118.427444\n",
      "Epoch 627, Training loss 108.852219, Validation loss 90.488960\n",
      "Epoch 628, Training loss 50.793339, Validation loss 103.906647\n",
      "Epoch 629, Training loss 45.282104, Validation loss 4.029670\n",
      "Epoch 630, Training loss 37.716530, Validation loss 3.089066\n",
      "Epoch 631, Training loss 33.504486, Validation loss 0.088238\n",
      "Epoch 632, Training loss 28.486599, Validation loss 5.733911\n",
      "Epoch 633, Training loss 5.826125, Validation loss 0.156021\n",
      "Epoch 634, Training loss 6.942131, Validation loss 19.861603\n",
      "Epoch 635, Training loss 7.206227, Validation loss 0.354024\n",
      "Epoch 636, Training loss 9.220537, Validation loss 31.359549\n",
      "Epoch 637, Training loss 9.296906, Validation loss 1.143404\n",
      "Epoch 638, Training loss 12.968779, Validation loss 50.579048\n",
      "Epoch 639, Training loss 14.485423, Validation loss 1.728449\n",
      "Epoch 640, Training loss 15.783423, Validation loss 60.113430\n",
      "Epoch 641, Training loss 18.105858, Validation loss 0.185341\n",
      "Epoch 642, Training loss 39.818043, Validation loss 152.154175\n",
      "Epoch 643, Training loss 46.286499, Validation loss 19.286074\n",
      "Epoch 644, Training loss 27.433193, Validation loss 11.218178\n",
      "Epoch 645, Training loss 9.511884, Validation loss 54.619686\n",
      "Epoch 646, Training loss 16.303671, Validation loss 6.282052\n",
      "Epoch 647, Training loss 12.243665, Validation loss 46.544937\n",
      "Epoch 648, Training loss 12.733078, Validation loss 1.987065\n",
      "Epoch 649, Training loss 11.855659, Validation loss 37.244419\n",
      "Epoch 650, Training loss 9.067559, Validation loss 0.330118\n",
      "Epoch 651, Training loss 11.765249, Validation loss 43.394512\n",
      "Epoch 652, Training loss 11.221633, Validation loss 1.002309\n",
      "Epoch 653, Training loss 12.204603, Validation loss 38.116428\n",
      "Epoch 654, Training loss 9.028028, Validation loss 0.269124\n",
      "Epoch 655, Training loss 11.300458, Validation loss 41.661358\n",
      "Epoch 656, Training loss 10.759435, Validation loss 1.003477\n",
      "Epoch 657, Training loss 12.317498, Validation loss 40.645874\n",
      "Epoch 658, Training loss 9.757420, Validation loss 0.460163\n",
      "Epoch 659, Training loss 11.221479, Validation loss 39.032219\n",
      "Epoch 660, Training loss 9.822432, Validation loss 0.727022\n",
      "Epoch 661, Training loss 12.089879, Validation loss 43.152405\n",
      "Epoch 662, Training loss 10.691300, Validation loss 0.814905\n",
      "Epoch 663, Training loss 11.322901, Validation loss 36.591904\n",
      "Epoch 664, Training loss 8.939461, Validation loss 0.471187\n",
      "Epoch 665, Training loss 11.540578, Validation loss 43.775433\n",
      "Epoch 666, Training loss 11.087568, Validation loss 1.124731\n",
      "Epoch 667, Training loss 11.478027, Validation loss 36.592518\n",
      "Epoch 668, Training loss 8.801947, Validation loss 0.456213\n",
      "Epoch 669, Training loss 11.142157, Validation loss 43.077888\n",
      "Epoch 670, Training loss 10.876488, Validation loss 1.167559\n",
      "Epoch 671, Training loss 11.457314, Validation loss 37.516209\n",
      "Epoch 672, Training loss 9.013797, Validation loss 0.577465\n",
      "Epoch 673, Training loss 10.955992, Validation loss 42.375607\n",
      "Epoch 674, Training loss 10.565631, Validation loss 1.131929\n",
      "Epoch 675, Training loss 11.255712, Validation loss 38.112278\n",
      "Epoch 676, Training loss 9.172834, Validation loss 0.714093\n",
      "Epoch 677, Training loss 10.799375, Validation loss 41.908962\n",
      "Epoch 678, Training loss 10.307647, Validation loss 1.123594\n",
      "Epoch 679, Training loss 10.955499, Validation loss 38.327633\n",
      "Epoch 680, Training loss 9.213286, Validation loss 0.833600\n",
      "Epoch 681, Training loss 10.593033, Validation loss 41.677181\n",
      "Epoch 682, Training loss 10.105482, Validation loss 1.149819\n",
      "Epoch 683, Training loss 10.588325, Validation loss 38.211670\n",
      "Epoch 684, Training loss 9.128176, Validation loss 0.921269\n",
      "Epoch 685, Training loss 10.302027, Validation loss 41.569450\n",
      "Epoch 686, Training loss 9.906311, Validation loss 1.181555\n",
      "Epoch 687, Training loss 10.161787, Validation loss 37.869038\n",
      "Epoch 688, Training loss 8.937228, Validation loss 0.963430\n",
      "Epoch 689, Training loss 9.923927, Validation loss 41.355625\n",
      "Epoch 690, Training loss 9.627297, Validation loss 1.165796\n",
      "Epoch 691, Training loss 9.705654, Validation loss 37.497025\n",
      "Epoch 692, Training loss 8.684975, Validation loss 0.945702\n",
      "Epoch 693, Training loss 9.500686, Validation loss 40.734276\n",
      "Epoch 694, Training loss 9.205831, Validation loss 1.062758\n",
      "Epoch 695, Training loss 9.287020, Validation loss 37.342953\n",
      "Epoch 696, Training loss 8.430835, Validation loss 0.873989\n",
      "Epoch 697, Training loss 9.107669, Validation loss 39.589294\n",
      "Epoch 698, Training loss 8.679281, Validation loss 0.897348\n",
      "Epoch 699, Training loss 8.950351, Validation loss 37.354042\n",
      "Epoch 700, Training loss 8.184861, Validation loss 0.771480\n",
      "Epoch 701, Training loss 8.793702, Validation loss 38.205734\n",
      "Epoch 702, Training loss 8.171039, Validation loss 0.731493\n",
      "Epoch 703, Training loss 8.678603, Validation loss 37.094109\n",
      "Epoch 704, Training loss 7.900351, Validation loss 0.653907\n",
      "Epoch 705, Training loss 8.552493, Validation loss 36.994228\n",
      "Epoch 706, Training loss 7.761649, Validation loss 0.596057\n",
      "Epoch 707, Training loss 8.452141, Validation loss 36.414326\n",
      "Epoch 708, Training loss 7.584990, Validation loss 0.538302\n",
      "Epoch 709, Training loss 8.355862, Validation loss 36.015327\n",
      "Epoch 710, Training loss 7.435797, Validation loss 0.487119\n",
      "Epoch 711, Training loss 8.267857, Validation loss 35.562492\n",
      "Epoch 712, Training loss 7.292552, Validation loss 0.439862\n",
      "Epoch 713, Training loss 8.190248, Validation loss 35.135700\n",
      "Epoch 714, Training loss 7.163505, Validation loss 0.398488\n",
      "Epoch 715, Training loss 8.117473, Validation loss 34.720303\n",
      "Epoch 716, Training loss 7.044286, Validation loss 0.360993\n",
      "Epoch 717, Training loss 8.053308, Validation loss 34.322601\n",
      "Epoch 718, Training loss 6.936958, Validation loss 0.328299\n",
      "Epoch 719, Training loss 7.994324, Validation loss 33.945602\n",
      "Epoch 720, Training loss 6.839259, Validation loss 0.299235\n",
      "Epoch 721, Training loss 7.941756, Validation loss 33.589752\n",
      "Epoch 722, Training loss 6.751310, Validation loss 0.273824\n",
      "Epoch 723, Training loss 7.894009, Validation loss 33.256294\n",
      "Epoch 724, Training loss 6.671659, Validation loss 0.251403\n",
      "Epoch 725, Training loss 7.851204, Validation loss 32.944523\n",
      "Epoch 726, Training loss 6.599725, Validation loss 0.231722\n",
      "Epoch 727, Training loss 7.812306, Validation loss 32.653755\n",
      "Epoch 728, Training loss 6.534360, Validation loss 0.214320\n",
      "Epoch 729, Training loss 7.777192, Validation loss 32.382736\n",
      "Epoch 730, Training loss 6.474928, Validation loss 0.198947\n",
      "Epoch 731, Training loss 7.745055, Validation loss 32.129990\n",
      "Epoch 732, Training loss 6.420486, Validation loss 0.185268\n",
      "Epoch 733, Training loss 7.715753, Validation loss 31.893980\n",
      "Epoch 734, Training loss 6.370510, Validation loss 0.173089\n",
      "Epoch 735, Training loss 7.688674, Validation loss 31.673222\n",
      "Epoch 736, Training loss 6.324281, Validation loss 0.162176\n",
      "Epoch 737, Training loss 7.663684, Validation loss 31.466194\n",
      "Epoch 738, Training loss 6.281400, Validation loss 0.152389\n",
      "Epoch 739, Training loss 7.640303, Validation loss 31.271629\n",
      "Epoch 740, Training loss 6.241337, Validation loss 0.143562\n",
      "Epoch 741, Training loss 7.618533, Validation loss 31.088375\n",
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      "Epoch 744, Training loss 6.168420, Validation loss 0.128388\n",
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      "Epoch 747, Training loss 7.559835, Validation loss 30.595989\n",
      "Epoch 748, Training loss 6.103202, Validation loss 0.115929\n",
      "Epoch 749, Training loss 7.542264, Validation loss 30.448267\n",
      "Epoch 750, Training loss 6.073010, Validation loss 0.110559\n",
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      "Epoch 752, Training loss 6.043994, Validation loss 0.105666\n",
      "Epoch 753, Training loss 7.508903, Validation loss 30.173077\n",
      "Epoch 754, Training loss 6.016316, Validation loss 0.101244\n",
      "Epoch 755, Training loss 7.492840, Validation loss 30.044455\n",
      "Epoch 756, Training loss 5.989521, Validation loss 0.097218\n",
      "Epoch 757, Training loss 7.477777, Validation loss 29.921490\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 758, Training loss 5.963907, Validation loss 0.093596\n",
      "Epoch 759, Training loss 7.462490, Validation loss 29.803152\n",
      "Epoch 760, Training loss 5.938882, Validation loss 0.090307\n",
      "Epoch 761, Training loss 7.448397, Validation loss 29.689976\n",
      "Epoch 762, Training loss 5.914982, Validation loss 0.087368\n",
      "Epoch 763, Training loss 7.433597, Validation loss 29.580393\n",
      "Epoch 764, Training loss 5.891379, Validation loss 0.084717\n",
      "Epoch 765, Training loss 7.420451, Validation loss 29.475752\n",
      "Epoch 766, Training loss 5.868964, Validation loss 0.082371\n",
      "Epoch 767, Training loss 7.405783, Validation loss 29.373480\n",
      "Epoch 768, Training loss 5.846460, Validation loss 0.080281\n",
      "Epoch 769, Training loss 7.393759, Validation loss 29.276485\n",
      "Epoch 770, Training loss 5.825420, Validation loss 0.078450\n",
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      "Epoch 772, Training loss 5.803681, Validation loss 0.076864\n",
      "Epoch 773, Training loss 7.368289, Validation loss 29.090553\n",
      "Epoch 774, Training loss 5.784067, Validation loss 0.075475\n",
      "Epoch 775, Training loss 7.352008, Validation loss 28.998819\n",
      "Epoch 776, Training loss 5.762666, Validation loss 0.074370\n",
      "Epoch 777, Training loss 7.344203, Validation loss 28.916538\n",
      "Epoch 778, Training loss 5.744689, Validation loss 0.073330\n",
      "Epoch 779, Training loss 7.324984, Validation loss 28.827160\n",
      "Epoch 780, Training loss 5.723008, Validation loss 0.072728\n",
      "Epoch 781, Training loss 7.322224, Validation loss 28.753975\n",
      "Epoch 782, Training loss 5.707390, Validation loss 0.071892\n",
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      "Epoch 784, Training loss 5.684138, Validation loss 0.071919\n",
      "Epoch 785, Training loss 7.303893, Validation loss 28.603157\n",
      "Epoch 786, Training loss 5.672472, Validation loss 0.070995\n",
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      "Epoch 788, Training loss 5.645159, Validation loss 0.072034\n",
      "Epoch 789, Training loss 7.292970, Validation loss 28.466742\n",
      "Epoch 790, Training loss 5.641004, Validation loss 0.070352\n",
      "Epoch 791, Training loss 7.221300, Validation loss 28.340471\n",
      "Epoch 792, Training loss 5.604286, Validation loss 0.073414\n",
      "Epoch 793, Training loss 7.298248, Validation loss 28.352285\n",
      "Epoch 794, Training loss 5.615631, Validation loss 0.069384\n",
      "Epoch 795, Training loss 7.155879, Validation loss 28.161469\n",
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      "Epoch 800, Training loss 5.498729, Validation loss 0.086030\n",
      "Epoch 801, Training loss 7.470628, Validation loss 28.287867\n",
      "Epoch 802, Training loss 5.621630, Validation loss 0.060902\n",
      "Epoch 803, Training loss 6.803507, Validation loss 27.577587\n",
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      "Epoch 805, Training loss 7.805369, Validation loss 28.462618\n",
      "Epoch 806, Training loss 5.726019, Validation loss 0.052983\n",
      "Epoch 807, Training loss 6.359599, Validation loss 26.940634\n",
      "Epoch 808, Training loss 5.288883, Validation loss 0.166409\n",
      "Epoch 809, Training loss 8.493363, Validation loss 28.801378\n",
      "Epoch 810, Training loss 6.023999, Validation loss 0.073018\n",
      "Epoch 811, Training loss 5.803058, Validation loss 26.015696\n",
      "Epoch 812, Training loss 5.028078, Validation loss 0.269966\n",
      "Epoch 813, Training loss 8.906699, Validation loss 28.549423\n",
      "Epoch 814, Training loss 6.236202, Validation loss 0.105061\n",
      "Epoch 815, Training loss 5.589180, Validation loss 25.492640\n",
      "Epoch 816, Training loss 4.815384, Validation loss 0.332908\n",
      "Epoch 817, Training loss 8.616336, Validation loss 27.937098\n",
      "Epoch 818, Training loss 6.094061, Validation loss 0.074158\n",
      "Epoch 819, Training loss 5.621906, Validation loss 25.478970\n",
      "Epoch 820, Training loss 4.889806, Validation loss 0.324735\n",
      "Epoch 821, Training loss 8.824062, Validation loss 28.216688\n",
      "Epoch 822, Training loss 6.162384, Validation loss 0.087523\n",
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      "Epoch 824, Training loss 4.777040, Validation loss 0.355441\n",
      "Epoch 825, Training loss 8.618803, Validation loss 27.868124\n",
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      "Epoch 828, Training loss 4.821342, Validation loss 0.352040\n",
      "Epoch 829, Training loss 8.761008, Validation loss 28.045935\n",
      "Epoch 830, Training loss 6.088619, Validation loss 0.073907\n",
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      "Epoch 833, Training loss 8.601940, Validation loss 27.772127\n",
      "Epoch 834, Training loss 5.995631, Validation loss 0.059314\n",
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      "Epoch 836, Training loss 4.760314, Validation loss 0.378018\n",
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      "Epoch 838, Training loss 6.018751, Validation loss 0.062956\n",
      "Epoch 839, Training loss 5.467178, Validation loss 25.156378\n",
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      "Epoch 841, Training loss 8.573495, Validation loss 27.663910\n",
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      "Epoch 850, Training loss 5.878161, Validation loss 0.046122\n",
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      "Epoch 858, Training loss 5.816151, Validation loss 0.041082\n",
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      "Epoch 865, Training loss 8.447283, Validation loss 27.299620\n",
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      "Epoch 868, Training loss 4.549717, Validation loss 0.473154\n",
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      "Epoch 900, Training loss 4.360684, Validation loss 0.558995\n",
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      "Epoch 961, Training loss 7.680632, Validation loss 25.534277\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 962, Training loss 4.983005, Validation loss 0.089282\n",
      "Epoch 963, Training loss 5.095335, Validation loss 24.773336\n",
      "Epoch 964, Training loss 4.024413, Validation loss 0.713026\n",
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      "Epoch 966, Training loss 4.953629, Validation loss 0.094823\n",
      "Epoch 967, Training loss 5.086253, Validation loss 24.760117\n",
      "Epoch 968, Training loss 4.005338, Validation loss 0.722155\n",
      "Epoch 969, Training loss 7.610851, Validation loss 25.390299\n",
      "Epoch 970, Training loss 4.923534, Validation loss 0.100848\n",
      "Epoch 971, Training loss 5.077470, Validation loss 24.745378\n",
      "Epoch 972, Training loss 3.987208, Validation loss 0.730973\n",
      "Epoch 973, Training loss 7.576739, Validation loss 25.321468\n",
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      "Epoch 977, Training loss 7.541708, Validation loss 25.251902\n",
      "Epoch 978, Training loss 4.865322, Validation loss 0.113258\n",
      "Epoch 979, Training loss 5.059925, Validation loss 24.712692\n",
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      "Epoch 984, Training loss 3.933387, Validation loss 0.757469\n",
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      "Epoch 986, Training loss 4.808396, Validation loss 0.126456\n",
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      "Epoch 993, Training loss 7.406108, Validation loss 24.994844\n",
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      "Epoch 995, Training loss 5.025905, Validation loss 24.633804\n",
      "Epoch 996, Training loss 3.882033, Validation loss 0.783430\n",
      "Epoch 997, Training loss 7.372884, Validation loss 24.935219\n",
      "Epoch 998, Training loss 4.725337, Validation loss 0.147616\n",
      "Epoch 999, Training loss 5.017658, Validation loss 24.611500\n",
      "Epoch 1000, Training loss 3.865397, Validation loss 0.791989\n",
      "Epoch 1001, Training loss 7.339838, Validation loss 24.877291\n",
      "Epoch 1002, Training loss 4.698221, Validation loss 0.155020\n",
      "Epoch 1003, Training loss 5.009546, Validation loss 24.588322\n",
      "Epoch 1004, Training loss 3.849026, Validation loss 0.800492\n",
      "Epoch 1005, Training loss 7.307092, Validation loss 24.821371\n",
      "Epoch 1006, Training loss 4.671402, Validation loss 0.162587\n",
      "Epoch 1007, Training loss 5.001568, Validation loss 24.564255\n",
      "Epoch 1008, Training loss 3.832910, Validation loss 0.808937\n",
      "Epoch 1009, Training loss 7.274592, Validation loss 24.767376\n",
      "Epoch 1010, Training loss 4.644831, Validation loss 0.170321\n",
      "Epoch 1011, Training loss 4.993721, Validation loss 24.539305\n",
      "Epoch 1012, Training loss 3.817030, Validation loss 0.817334\n",
      "Epoch 1013, Training loss 7.242318, Validation loss 24.715311\n",
      "Epoch 1014, Training loss 4.618500, Validation loss 0.178221\n",
      "Epoch 1015, Training loss 4.986044, Validation loss 24.513720\n",
      "Epoch 1016, Training loss 3.801403, Validation loss 0.825668\n",
      "Epoch 1017, Training loss 7.210284, Validation loss 24.665138\n",
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      "Epoch 1282, Training loss 3.965367, Validation loss 1.214599\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1283, Training loss 4.545243, Validation loss 19.430742\n",
      "Epoch 1284, Training loss 4.122947, Validation loss 1.234282\n",
      "Epoch 1285, Training loss 4.321803, Validation loss 18.548204\n",
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      "Epoch 1287, Training loss 4.070440, Validation loss 17.752331\n",
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      "Epoch 1289, Training loss 3.902465, Validation loss 17.374872\n",
      "Epoch 1290, Training loss 4.372883, Validation loss 1.333792\n",
      "Epoch 1291, Training loss 3.854694, Validation loss 17.395788\n",
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      "Epoch 1299, Training loss 3.922723, Validation loss 18.147549\n",
      "Epoch 1300, Training loss 4.302906, Validation loss 1.225157\n",
      "Epoch 1301, Training loss 3.951964, Validation loss 18.356657\n",
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      "Epoch 1436, Training loss 5.145938, Validation loss 1.381360\n",
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      "Epoch 1438, Training loss 5.549652, Validation loss 1.412836\n",
      "Epoch 1439, Training loss 6.304076, Validation loss 26.093103\n",
      "Epoch 1440, Training loss 6.277809, Validation loss 0.743363\n",
      "Epoch 1441, Training loss 7.307718, Validation loss 31.231268\n",
      "Epoch 1442, Training loss 5.401064, Validation loss 0.882097\n",
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      "Epoch 1444, Training loss 3.950226, Validation loss 0.651061\n",
      "Epoch 1445, Training loss 2.961954, Validation loss 19.895950\n",
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      "Epoch 1458, Training loss 3.085118, Validation loss 2.088658\n",
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      "Epoch 1461, Training loss 3.081038, Validation loss 19.744387\n",
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      "Epoch 1467, Training loss 3.733250, Validation loss 21.196714\n",
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      "Epoch 1486, Training loss 2.257689, Validation loss 2.499019\n",
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      "Epoch 1500, Training loss 1.982884, Validation loss 2.830920\n",
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      "Epoch 1534, Training loss 4.270907, Validation loss 2.740012\n",
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      "Epoch 1558, Training loss 1.669033, Validation loss 3.680263\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1559, Training loss 2.856539, Validation loss 19.957199\n",
      "Epoch 1560, Training loss 3.637913, Validation loss 3.274216\n",
      "Epoch 1561, Training loss 2.357083, Validation loss 18.978867\n",
      "Epoch 1562, Training loss 1.746184, Validation loss 3.779813\n",
      "Epoch 1563, Training loss 3.010276, Validation loss 20.274897\n",
      "Epoch 1564, Training loss 3.899933, Validation loss 3.232160\n",
      "Epoch 1565, Training loss 2.544573, Validation loss 19.573702\n",
      "Epoch 1566, Training loss 2.387805, Validation loss 3.368933\n",
      "Epoch 1567, Training loss 2.831439, Validation loss 20.142277\n",
      "Epoch 1568, Training loss 3.329229, Validation loss 3.172372\n",
      "Epoch 1569, Training loss 2.379409, Validation loss 18.937799\n",
      "Epoch 1570, Training loss 1.512792, Validation loss 4.002896\n",
      "Epoch 1571, Training loss 2.388624, Validation loss 18.966249\n",
      "Epoch 1572, Training loss 2.963042, Validation loss 3.690866\n",
      "Epoch 1573, Training loss 2.073430, Validation loss 18.237715\n",
      "Epoch 1574, Training loss 1.473709, Validation loss 4.367939\n",
      "Epoch 1575, Training loss 2.458739, Validation loss 19.001280\n",
      "Epoch 1576, Training loss 3.269362, Validation loss 3.738612\n",
      "Epoch 1577, Training loss 2.073964, Validation loss 18.188154\n",
      "Epoch 1578, Training loss 1.399405, Validation loss 4.480791\n",
      "Epoch 1579, Training loss 2.180485, Validation loss 18.388893\n",
      "Epoch 1580, Training loss 2.802650, Validation loss 3.979746\n",
      "Epoch 1581, Training loss 1.948645, Validation loss 17.947327\n",
      "Epoch 1582, Training loss 1.502175, Validation loss 4.501919\n",
      "Epoch 1583, Training loss 2.560792, Validation loss 19.163906\n",
      "Epoch 1584, Training loss 3.499230, Validation loss 3.755034\n",
      "Epoch 1585, Training loss 2.103515, Validation loss 18.402050\n",
      "Epoch 1586, Training loss 1.566072, Validation loss 4.265531\n",
      "Epoch 1587, Training loss 2.670512, Validation loss 19.491961\n",
      "Epoch 1588, Training loss 3.569521, Validation loss 3.642209\n",
      "Epoch 1589, Training loss 2.160016, Validation loss 18.604923\n",
      "Epoch 1590, Training loss 1.645096, Validation loss 4.149814\n",
      "Epoch 1591, Training loss 2.786562, Validation loss 19.794632\n",
      "Epoch 1592, Training loss 3.693829, Validation loss 3.565529\n",
      "Epoch 1593, Training loss 2.247950, Validation loss 18.922394\n",
      "Epoch 1594, Training loss 1.885293, Validation loss 3.932382\n",
      "Epoch 1595, Training loss 2.898785, Validation loss 20.153280\n",
      "Epoch 1596, Training loss 3.757942, Validation loss 3.451221\n",
      "Epoch 1597, Training loss 2.334766, Validation loss 19.193991\n",
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      "Epoch 1599, Training loss 2.886297, Validation loss 20.217352\n",
      "Epoch 1600, Training loss 3.666731, Validation loss 3.428002\n",
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      "Epoch 1607, Training loss 2.847608, Validation loss 20.099482\n",
      "Epoch 1608, Training loss 3.667705, Validation loss 3.548485\n",
      "Epoch 1609, Training loss 2.236711, Validation loss 18.990767\n",
      "Epoch 1610, Training loss 1.748320, Validation loss 4.062819\n",
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      "Epoch 1616, Training loss 3.507890, Validation loss 3.732690\n",
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      "Epoch 1623, Training loss 1.493130, Validation loss 16.516754\n",
      "Epoch 1624, Training loss 1.244460, Validation loss 5.473438\n",
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      "Epoch 1627, Training loss 1.627073, Validation loss 16.864882\n",
      "Epoch 1628, Training loss 1.129763, Validation loss 5.763474\n",
      "Epoch 1629, Training loss 1.329182, Validation loss 15.819125\n",
      "Epoch 1630, Training loss 1.090606, Validation loss 5.961350\n",
      "Epoch 1631, Training loss 1.583164, Validation loss 16.377069\n",
      "Epoch 1632, Training loss 2.375767, Validation loss 5.218410\n",
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      "Epoch 1787, Training loss 2.730048, Validation loss 4.788177\n",
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      "Epoch 1800, Training loss 1.512528, Validation loss 15.895735\n",
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      "Epoch 1822, Training loss 0.718360, Validation loss 8.869383\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1823, Training loss 0.752463, Validation loss 12.871406\n",
      "Epoch 1824, Training loss 0.846952, Validation loss 8.349653\n",
      "Epoch 1825, Training loss 1.175071, Validation loss 14.180986\n",
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      "Epoch 1827, Training loss 0.957713, Validation loss 14.557492\n",
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      "Epoch 1829, Training loss 1.371208, Validation loss 15.587436\n",
      "Epoch 1830, Training loss 2.168011, Validation loss 6.109621\n",
      "Epoch 1831, Training loss 1.171566, Validation loss 15.624527\n",
      "Epoch 1832, Training loss 1.049658, Validation loss 6.555319\n",
      "Epoch 1833, Training loss 1.485025, Validation loss 16.226818\n",
      "Epoch 1834, Training loss 2.204556, Validation loss 5.693777\n",
      "Epoch 1835, Training loss 1.278912, Validation loss 16.064791\n",
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      "Epoch 1838, Training loss 2.461280, Validation loss 5.401408\n",
      "Epoch 1839, Training loss 1.335119, Validation loss 16.084913\n",
      "Epoch 1840, Training loss 0.993175, Validation loss 6.519165\n",
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      "Epoch 1846, Training loss 0.941502, Validation loss 6.876034\n",
      "Epoch 1847, Training loss 1.016452, Validation loss 14.608644\n",
      "Epoch 1848, Training loss 0.923856, Validation loss 7.037514\n",
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      "Epoch 1854, Training loss 2.422798, Validation loss 5.592981\n",
      "Epoch 1855, Training loss 1.277195, Validation loss 15.849144\n",
      "Epoch 1856, Training loss 0.966751, Validation loss 6.678167\n",
      "Epoch 1857, Training loss 1.078591, Validation loss 14.954230\n",
      "Epoch 1858, Training loss 1.084036, Validation loss 6.681724\n",
      "Epoch 1859, Training loss 1.576572, Validation loss 15.982947\n",
      "Epoch 1860, Training loss 2.440977, Validation loss 5.832497\n",
      "Epoch 1861, Training loss 1.178661, Validation loss 15.336428\n",
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      "Epoch 1863, Training loss 0.962859, Validation loss 14.217435\n",
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      "Epoch 1867, Training loss 1.528680, Validation loss 15.412815\n",
      "Epoch 1868, Training loss 2.448116, Validation loss 6.202423\n",
      "Epoch 1869, Training loss 1.082151, Validation loss 14.836801\n",
      "Epoch 1870, Training loss 0.879564, Validation loss 7.472214\n",
      "Epoch 1871, Training loss 0.907032, Validation loss 13.659358\n",
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      "Epoch 1873, Training loss 0.829271, Validation loss 12.579033\n",
      "Epoch 1874, Training loss 0.848353, Validation loss 9.194908\n",
      "Epoch 1875, Training loss 1.148736, Validation loss 11.083939\n",
      "Epoch 1876, Training loss 1.120045, Validation loss 11.033483\n",
      "Epoch 1877, Training loss 1.811363, Validation loss 9.411529\n",
      "Epoch 1878, Training loss 0.660175, Validation loss 11.512391\n",
      "Epoch 1879, Training loss 0.697187, Validation loss 9.655783\n",
      "Epoch 1880, Training loss 0.831292, Validation loss 12.253823\n",
      "Epoch 1881, Training loss 1.304987, Validation loss 8.565061\n",
      "Epoch 1882, Training loss 1.127146, Validation loss 13.750037\n",
      "Epoch 1883, Training loss 1.905053, Validation loss 7.456195\n",
      "Epoch 1884, Training loss 0.878754, Validation loss 14.078150\n",
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      "Epoch 1886, Training loss 1.253095, Validation loss 15.013952\n",
      "Epoch 1887, Training loss 2.003778, Validation loss 6.554221\n",
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      "Epoch 1890, Training loss 1.523747, Validation loss 16.112720\n",
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      "Epoch 1899, Training loss 0.909900, Validation loss 7.125154\n",
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      "Epoch 1942, Training loss 0.800965, Validation loss 7.856517\n",
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      "Epoch 1946, Training loss 2.296839, Validation loss 6.400755\n",
      "Epoch 1947, Training loss 1.043697, Validation loss 14.829389\n",
      "Epoch 1948, Training loss 0.858816, Validation loss 7.570285\n",
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      "Epoch 1963, Training loss 1.521549, Validation loss 16.352262\n",
      "Epoch 1964, Training loss 2.203014, Validation loss 5.856551\n",
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      "Epoch 1966, Training loss 0.968443, Validation loss 6.789563\n",
      "Epoch 1967, Training loss 1.206992, Validation loss 15.373535\n",
      "Epoch 1968, Training loss 1.635902, Validation loss 6.368152\n",
      "Epoch 1969, Training loss 1.358123, Validation loss 15.901987\n",
      "Epoch 1970, Training loss 1.931066, Validation loss 6.108801\n",
      "Epoch 1971, Training loss 1.201087, Validation loss 15.760814\n",
      "Epoch 1972, Training loss 1.311953, Validation loss 6.421900\n",
      "Epoch 1973, Training loss 1.641183, Validation loss 16.547550\n",
      "Epoch 1974, Training loss 2.371983, Validation loss 5.761636\n",
      "Epoch 1975, Training loss 1.210988, Validation loss 15.586431\n",
      "Epoch 1976, Training loss 0.915791, Validation loss 7.211170\n",
      "Epoch 1977, Training loss 0.939862, Validation loss 14.094127\n",
      "Epoch 1978, Training loss 0.798269, Validation loss 7.858292\n",
      "Epoch 1979, Training loss 0.802941, Validation loss 13.213839\n",
      "Epoch 1980, Training loss 0.744731, Validation loss 8.255027\n",
      "Epoch 1981, Training loss 0.789410, Validation loss 13.022106\n",
      "Epoch 1982, Training loss 0.929304, Validation loss 8.036937\n",
      "Epoch 1983, Training loss 1.270090, Validation loss 14.306899\n",
      "Epoch 1984, Training loss 2.069675, Validation loss 6.981104\n",
      "Epoch 1985, Training loss 0.898304, Validation loss 14.132913\n",
      "Epoch 1986, Training loss 0.821061, Validation loss 7.813734\n",
      "Epoch 1987, Training loss 0.954616, Validation loss 14.043756\n",
      "Epoch 1988, Training loss 1.311095, Validation loss 7.276778\n",
      "Epoch 1989, Training loss 1.386713, Validation loss 15.250756\n",
      "Epoch 1990, Training loss 2.166613, Validation loss 6.485138\n",
      "Epoch 1991, Training loss 1.010789, Validation loss 14.772713\n",
      "Epoch 1992, Training loss 0.851979, Validation loss 7.513112\n",
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      "Epoch 1996, Training loss 2.226872, Validation loss 6.415857\n",
      "Epoch 1997, Training loss 1.017047, Validation loss 14.723892\n",
      "Epoch 1998, Training loss 0.838036, Validation loss 7.649049\n",
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      "Epoch 2002, Training loss 1.462335, Validation loss 7.248359\n",
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      "Epoch 2007, Training loss 1.454224, Validation loss 15.659546\n",
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      "Epoch 2009, Training loss 1.059391, Validation loss 15.003463\n",
      "Epoch 2010, Training loss 0.859260, Validation loss 7.467719\n",
      "Epoch 2011, Training loss 0.906088, Validation loss 14.083794\n",
      "Epoch 2012, Training loss 0.921949, Validation loss 7.517830\n",
      "Epoch 2013, Training loss 1.232476, Validation loss 14.721223\n",
      "Epoch 2014, Training loss 1.927358, Validation loss 6.735042\n",
      "Epoch 2015, Training loss 0.975525, Validation loss 14.643030\n",
      "Epoch 2016, Training loss 0.992325, Validation loss 7.294531\n",
      "Epoch 2017, Training loss 1.337590, Validation loss 15.262608\n",
      "Epoch 2018, Training loss 2.045158, Validation loss 6.481330\n",
      "Epoch 2019, Training loss 1.012684, Validation loss 14.875121\n",
      "Epoch 2020, Training loss 0.897834, Validation loss 7.355424\n",
      "Epoch 2021, Training loss 1.107551, Validation loss 14.756696\n",
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      "Epoch 2061, Training loss 1.118312, Validation loss 15.194471\n",
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      "Epoch 2064, Training loss 1.716174, Validation loss 6.591503\n",
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      "Epoch 2067, Training loss 1.386809, Validation loss 15.842360\n",
      "Epoch 2068, Training loss 1.974054, Validation loss 6.384395\n",
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      "Epoch 2070, Training loss 0.861083, Validation loss 7.597077\n",
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      "Epoch 2075, Training loss 0.953941, Validation loss 14.743025\n",
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      "Epoch 2077, Training loss 0.933726, Validation loss 14.201784\n",
      "Epoch 2078, Training loss 1.154757, Validation loss 7.527117\n",
      "Epoch 2079, Training loss 1.228770, Validation loss 14.962362\n",
      "Epoch 2080, Training loss 1.816348, Validation loss 6.895328\n",
      "Epoch 2081, Training loss 0.944603, Validation loss 14.745373\n",
      "Epoch 2082, Training loss 0.853432, Validation loss 7.824052\n",
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      "Epoch 2084, Training loss 1.318635, Validation loss 7.357197\n",
      "Epoch 2085, Training loss 1.140206, Validation loss 14.992713\n",
      "Epoch 2086, Training loss 1.609046, Validation loss 7.009108\n",
      "Epoch 2087, Training loss 1.003561, Validation loss 15.039635\n",
      "Epoch 2088, Training loss 1.110715, Validation loss 7.358173\n",
      "Epoch 2089, Training loss 1.268940, Validation loss 15.446454\n",
      "Epoch 2090, Training loss 1.803831, Validation loss 6.743443\n",
      "Epoch 2091, Training loss 0.984863, Validation loss 15.115900\n",
      "Epoch 2092, Training loss 0.861572, Validation loss 7.764314\n",
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      "Epoch 2098, Training loss 1.018121, Validation loss 7.530123\n",
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      "Epoch 2100, Training loss 1.685415, Validation loss 6.913295\n",
      "Epoch 2101, Training loss 0.969600, Validation loss 15.159135\n",
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      "Epoch 2110, Training loss 1.045218, Validation loss 7.494368\n",
      "Epoch 2111, Training loss 1.191521, Validation loss 15.549868\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2112, Training loss 1.609407, Validation loss 6.968179\n",
      "Epoch 2113, Training loss 0.979162, Validation loss 15.404468\n",
      "Epoch 2114, Training loss 0.916729, Validation loss 7.747438\n",
      "Epoch 2115, Training loss 1.078879, Validation loss 15.150620\n",
      "Epoch 2116, Training loss 1.417175, Validation loss 7.254855\n",
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      "Epoch 2118, Training loss 1.124530, Validation loss 7.513968\n",
      "Epoch 2119, Training loss 1.151864, Validation loss 15.551125\n",
      "Epoch 2120, Training loss 1.525919, Validation loss 7.102480\n",
      "Epoch 2121, Training loss 0.980976, Validation loss 15.480667\n",
      "Epoch 2122, Training loss 0.967605, Validation loss 7.700116\n",
      "Epoch 2123, Training loss 1.122434, Validation loss 15.402038\n",
      "Epoch 2124, Training loss 1.484459, Validation loss 7.189229\n",
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      "Epoch 2127, Training loss 1.124702, Validation loss 15.424454\n",
      "Epoch 2128, Training loss 1.489887, Validation loss 7.210814\n",
      "Epoch 2129, Training loss 0.962879, Validation loss 15.417302\n",
      "Epoch 2130, Training loss 0.961224, Validation loss 7.784621\n",
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      "Epoch 2141, Training loss 0.956378, Validation loss 15.411991\n",
      "Epoch 2142, Training loss 0.984729, Validation loss 7.811263\n",
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      "Epoch 2159, Training loss 1.086313, Validation loss 15.411024\n",
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      "Epoch 2169, Training loss 0.942415, Validation loss 15.425210\n",
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      "Epoch 2384, Training loss 1.317869, Validation loss 7.685707\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2385, Training loss 0.922264, Validation loss 15.378556\n",
      "Epoch 2386, Training loss 0.993807, Validation loss 8.042880\n",
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      "Epoch 2655, Training loss 0.988157, Validation loss 15.337775\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2656, Training loss 1.213730, Validation loss 7.825916\n",
      "Epoch 2657, Training loss 0.926763, Validation loss 15.373541\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2964, Training loss 1.095442, Validation loss 7.991999\n",
      "Epoch 2965, Training loss 0.935346, Validation loss 15.284553\n",
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      "Epoch 2998, Training loss 1.090851, Validation loss 8.001263\n",
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      "Epoch 3000, Training loss 1.090997, Validation loss 8.001279\n",
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      "Epoch 3180, Training loss 1.073584, Validation loss 8.035675\n",
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      "Epoch 3183, Training loss 0.920886, Validation loss 15.203099\n",
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      "Epoch 3221, Training loss 0.918625, Validation loss 15.190433\n",
      "Epoch 3222, Training loss 1.069956, Validation loss 8.041984\n",
      "Epoch 3223, Training loss 0.918513, Validation loss 15.189780\n",
      "Epoch 3224, Training loss 1.069795, Validation loss 8.042267\n",
      "Epoch 3225, Training loss 0.918391, Validation loss 15.189121\n",
      "Epoch 3226, Training loss 1.069616, Validation loss 8.042562\n",
      "Epoch 3227, Training loss 0.918279, Validation loss 15.188451\n",
      "Epoch 3228, Training loss 1.069461, Validation loss 8.042827\n",
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      "Epoch 3230, Training loss 1.069278, Validation loss 8.043135\n",
      "Epoch 3231, Training loss 0.918048, Validation loss 15.187143\n",
      "Epoch 3232, Training loss 1.069122, Validation loss 8.043396\n",
      "Epoch 3233, Training loss 0.917928, Validation loss 15.186506\n",
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      "Epoch 3250, Training loss 1.067618, Validation loss 8.045889\n",
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      "Epoch 3255, Training loss 0.916671, Validation loss 15.179401\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3256, Training loss 1.067123, Validation loss 8.046698\n",
      "Epoch 3257, Training loss 0.916559, Validation loss 15.178754\n",
      "Epoch 3258, Training loss 1.066963, Validation loss 8.046956\n",
      "Epoch 3259, Training loss 0.916447, Validation loss 15.178143\n",
      "Epoch 3260, Training loss 1.066797, Validation loss 8.047230\n",
      "Epoch 3261, Training loss 0.916333, Validation loss 15.177505\n",
      "Epoch 3262, Training loss 1.066632, Validation loss 8.047501\n",
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      "Epoch 3264, Training loss 1.066469, Validation loss 8.047761\n",
      "Epoch 3265, Training loss 0.916108, Validation loss 15.176212\n",
      "Epoch 3266, Training loss 1.066310, Validation loss 8.048009\n",
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      "Epoch 3268, Training loss 1.066140, Validation loss 8.048297\n",
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      "Epoch 3270, Training loss 1.065982, Validation loss 8.048554\n",
      "Epoch 3271, Training loss 0.915769, Validation loss 15.174287\n",
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      "Epoch 3280, Training loss 1.065167, Validation loss 8.049866\n",
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      "Epoch 3290, Training loss 1.064367, Validation loss 8.051123\n",
      "Epoch 3291, Training loss 0.914660, Validation loss 15.167994\n",
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      "Epoch 3302, Training loss 1.063407, Validation loss 8.052598\n",
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      "Epoch 3307, Training loss 0.913782, Validation loss 15.162999\n",
      "Epoch 3308, Training loss 1.062935, Validation loss 8.053340\n",
      "Epoch 3309, Training loss 0.913674, Validation loss 15.162362\n",
      "Epoch 3310, Training loss 1.062781, Validation loss 8.053567\n",
      "Epoch 3311, Training loss 0.913565, Validation loss 15.161747\n",
      "Epoch 3312, Training loss 1.062620, Validation loss 8.053806\n",
      "Epoch 3313, Training loss 0.913456, Validation loss 15.161133\n",
      "Epoch 3314, Training loss 1.062462, Validation loss 8.054052\n",
      "Epoch 3315, Training loss 0.913349, Validation loss 15.160510\n",
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      "Epoch 3321, Training loss 0.913027, Validation loss 15.158673\n",
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      "Epoch 3327, Training loss 0.912703, Validation loss 15.156837\n",
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      "Epoch 3486, Training loss 1.049758, Validation loss 8.071534\n",
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      "Epoch 3488, Training loss 1.049616, Validation loss 8.071712\n",
      "Epoch 3489, Training loss 0.904498, Validation loss 15.109116\n",
      "Epoch 3490, Training loss 1.049479, Validation loss 8.071863\n",
      "Epoch 3491, Training loss 0.904400, Validation loss 15.108553\n",
      "Epoch 3492, Training loss 1.049335, Validation loss 8.072071\n",
      "Epoch 3493, Training loss 0.904306, Validation loss 15.107976\n",
      "Epoch 3494, Training loss 1.049203, Validation loss 8.072222\n",
      "Epoch 3495, Training loss 0.904207, Validation loss 15.107394\n",
      "Epoch 3496, Training loss 1.049057, Validation loss 8.072397\n",
      "Epoch 3497, Training loss 0.904113, Validation loss 15.106843\n",
      "Epoch 3498, Training loss 1.048924, Validation loss 8.072576\n",
      "Epoch 3499, Training loss 0.904018, Validation loss 15.106281\n",
      "Epoch 3500, Training loss 1.048783, Validation loss 8.072741\n",
      "Epoch 3501, Training loss 0.903921, Validation loss 15.105685\n",
      "Epoch 3502, Training loss 1.048645, Validation loss 8.072898\n",
      "Epoch 3503, Training loss 0.903828, Validation loss 15.105156\n",
      "Epoch 3504, Training loss 1.048508, Validation loss 8.073060\n",
      "Epoch 3505, Training loss 0.903732, Validation loss 15.104593\n",
      "Epoch 3506, Training loss 1.048369, Validation loss 8.073223\n",
      "Epoch 3507, Training loss 0.903637, Validation loss 15.104031\n",
      "Epoch 3508, Training loss 1.048232, Validation loss 8.073385\n",
      "Epoch 3509, Training loss 0.903542, Validation loss 15.103461\n",
      "Epoch 3510, Training loss 1.048093, Validation loss 8.073566\n",
      "Epoch 3511, Training loss 0.903446, Validation loss 15.102884\n",
      "Epoch 3512, Training loss 1.047955, Validation loss 8.073733\n",
      "Epoch 3513, Training loss 0.903351, Validation loss 15.102322\n",
      "Epoch 3514, Training loss 1.047818, Validation loss 8.073895\n",
      "Epoch 3515, Training loss 0.903256, Validation loss 15.101752\n",
      "Epoch 3516, Training loss 1.047680, Validation loss 8.074051\n",
      "Epoch 3517, Training loss 0.903162, Validation loss 15.101190\n",
      "Epoch 3518, Training loss 1.047546, Validation loss 8.074204\n",
      "Epoch 3519, Training loss 0.903069, Validation loss 15.100649\n",
      "Epoch 3520, Training loss 1.047408, Validation loss 8.074376\n",
      "Epoch 3521, Training loss 0.902974, Validation loss 15.100094\n",
      "Epoch 3522, Training loss 1.047271, Validation loss 8.074546\n",
      "Epoch 3523, Training loss 0.902880, Validation loss 15.099524\n",
      "Epoch 3524, Training loss 1.047135, Validation loss 8.074697\n",
      "Epoch 3525, Training loss 0.902787, Validation loss 15.098969\n",
      "Epoch 3526, Training loss 1.047000, Validation loss 8.074870\n",
      "Epoch 3527, Training loss 0.902693, Validation loss 15.098407\n",
      "Epoch 3528, Training loss 1.046865, Validation loss 8.075015\n",
      "Epoch 3529, Training loss 0.902597, Validation loss 15.097830\n",
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      "Epoch 3531, Training loss 0.902505, Validation loss 15.097275\n",
      "Epoch 3532, Training loss 1.046594, Validation loss 8.075324\n",
      "Epoch 3533, Training loss 0.902413, Validation loss 15.096724\n",
      "Epoch 3534, Training loss 1.046459, Validation loss 8.075494\n",
      "Epoch 3535, Training loss 0.902314, Validation loss 15.096158\n",
      "Epoch 3536, Training loss 1.046315, Validation loss 8.075665\n",
      "Epoch 3537, Training loss 0.902223, Validation loss 15.095588\n",
      "Epoch 3538, Training loss 1.046187, Validation loss 8.075815\n",
      "Epoch 3539, Training loss 0.902128, Validation loss 15.095048\n",
      "Epoch 3540, Training loss 1.046045, Validation loss 8.075967\n",
      "Epoch 3541, Training loss 0.902037, Validation loss 15.094478\n",
      "Epoch 3542, Training loss 1.045916, Validation loss 8.076117\n",
      "Epoch 3543, Training loss 0.901942, Validation loss 15.093926\n",
      "Epoch 3544, Training loss 1.045778, Validation loss 8.076280\n",
      "Epoch 3545, Training loss 0.901849, Validation loss 15.093365\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3546, Training loss 1.045645, Validation loss 8.076436\n",
      "Epoch 3547, Training loss 0.901758, Validation loss 15.092820\n",
      "Epoch 3548, Training loss 1.045510, Validation loss 8.076598\n",
      "Epoch 3549, Training loss 0.901663, Validation loss 15.092258\n",
      "Epoch 3550, Training loss 1.045374, Validation loss 8.076749\n",
      "Epoch 3551, Training loss 0.901572, Validation loss 15.091703\n",
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      "Epoch 3554, Training loss 1.045106, Validation loss 8.077043\n",
      "Epoch 3555, Training loss 0.901386, Validation loss 15.090605\n",
      "Epoch 3556, Training loss 1.044972, Validation loss 8.077197\n",
      "Epoch 3557, Training loss 0.901296, Validation loss 15.090054\n",
      "Epoch 3558, Training loss 1.044843, Validation loss 8.077336\n",
      "Epoch 3559, Training loss 0.901202, Validation loss 15.089495\n",
      "Epoch 3560, Training loss 1.044702, Validation loss 8.077516\n",
      "Epoch 3561, Training loss 0.901108, Validation loss 15.088914\n",
      "Epoch 3562, Training loss 1.044573, Validation loss 8.077661\n",
      "Epoch 3563, Training loss 0.901016, Validation loss 15.088367\n",
      "Epoch 3564, Training loss 1.044437, Validation loss 8.077802\n",
      "Epoch 3565, Training loss 0.900924, Validation loss 15.087811\n",
      "Epoch 3566, Training loss 1.044307, Validation loss 8.077946\n",
      "Epoch 3567, Training loss 0.900834, Validation loss 15.087272\n",
      "Epoch 3568, Training loss 1.044173, Validation loss 8.078098\n",
      "Epoch 3569, Training loss 0.900742, Validation loss 15.086731\n",
      "Epoch 3570, Training loss 1.044040, Validation loss 8.078235\n",
      "Epoch 3571, Training loss 0.900651, Validation loss 15.086184\n",
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      "Epoch 3573, Training loss 0.900560, Validation loss 15.085636\n",
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      "Epoch 3575, Training loss 0.900466, Validation loss 15.085052\n",
      "Epoch 3576, Training loss 1.043642, Validation loss 8.078684\n",
      "Epoch 3577, Training loss 0.900372, Validation loss 15.084504\n",
      "Epoch 3578, Training loss 1.043505, Validation loss 8.078853\n",
      "Epoch 3579, Training loss 0.900284, Validation loss 15.083950\n",
      "Epoch 3580, Training loss 1.043378, Validation loss 8.078978\n",
      "Epoch 3581, Training loss 0.900191, Validation loss 15.083402\n",
      "Epoch 3582, Training loss 1.043242, Validation loss 8.079131\n",
      "Epoch 3583, Training loss 0.900102, Validation loss 15.082866\n",
      "Epoch 3584, Training loss 1.043117, Validation loss 8.079256\n",
      "Epoch 3585, Training loss 0.900011, Validation loss 15.082322\n",
      "Epoch 3586, Training loss 1.042981, Validation loss 8.079391\n",
      "Epoch 3587, Training loss 0.899920, Validation loss 15.081759\n",
      "Epoch 3588, Training loss 1.042853, Validation loss 8.079548\n",
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      "Epoch 3590, Training loss 1.042716, Validation loss 8.079706\n",
      "Epoch 3591, Training loss 0.899739, Validation loss 15.080661\n",
      "Epoch 3592, Training loss 1.042592, Validation loss 8.079834\n",
      "Epoch 3593, Training loss 0.899644, Validation loss 15.080103\n",
      "Epoch 3594, Training loss 1.042450, Validation loss 8.080001\n",
      "Epoch 3595, Training loss 0.899554, Validation loss 15.079540\n",
      "Epoch 3596, Training loss 1.042324, Validation loss 8.080130\n",
      "Epoch 3597, Training loss 0.899464, Validation loss 15.079008\n",
      "Epoch 3598, Training loss 1.042192, Validation loss 8.080282\n",
      "Epoch 3599, Training loss 0.899373, Validation loss 15.078445\n",
      "Epoch 3600, Training loss 1.042061, Validation loss 8.080426\n",
      "Epoch 3601, Training loss 0.899282, Validation loss 15.077898\n",
      "Epoch 3602, Training loss 1.041932, Validation loss 8.080561\n",
      "Epoch 3603, Training loss 0.899191, Validation loss 15.077344\n",
      "Epoch 3604, Training loss 1.041798, Validation loss 8.080703\n",
      "Epoch 3605, Training loss 0.899104, Validation loss 15.076811\n",
      "Epoch 3606, Training loss 1.041673, Validation loss 8.080835\n",
      "Epoch 3607, Training loss 0.899015, Validation loss 15.076279\n",
      "Epoch 3608, Training loss 1.041544, Validation loss 8.080960\n",
      "Epoch 3609, Training loss 0.898922, Validation loss 15.075708\n",
      "Epoch 3610, Training loss 1.041409, Validation loss 8.081100\n",
      "Epoch 3611, Training loss 0.898836, Validation loss 15.075183\n",
      "Epoch 3612, Training loss 1.041286, Validation loss 8.081229\n",
      "Epoch 3613, Training loss 0.898744, Validation loss 15.074651\n",
      "Epoch 3614, Training loss 1.041148, Validation loss 8.081390\n",
      "Epoch 3615, Training loss 0.898655, Validation loss 15.074096\n",
      "Epoch 3616, Training loss 1.041024, Validation loss 8.081518\n",
      "Epoch 3617, Training loss 0.898562, Validation loss 15.073548\n",
      "Epoch 3618, Training loss 1.040887, Validation loss 8.081677\n",
      "Epoch 3619, Training loss 0.898475, Validation loss 15.072990\n",
      "Epoch 3620, Training loss 1.040765, Validation loss 8.081782\n",
      "Epoch 3621, Training loss 0.898381, Validation loss 15.072439\n",
      "Epoch 3622, Training loss 1.040626, Validation loss 8.081944\n",
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      "Epoch 3624, Training loss 1.040508, Validation loss 8.082063\n",
      "Epoch 3625, Training loss 0.898203, Validation loss 15.071352\n",
      "Epoch 3626, Training loss 1.040370, Validation loss 8.082211\n",
      "Epoch 3627, Training loss 0.898115, Validation loss 15.070797\n",
      "Epoch 3628, Training loss 1.040246, Validation loss 8.082340\n",
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      "Epoch 3630, Training loss 1.040118, Validation loss 8.082470\n",
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      "Epoch 3634, Training loss 1.039859, Validation loss 8.082754\n",
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      "Epoch 3636, Training loss 1.039730, Validation loss 8.082876\n",
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      "Epoch 3638, Training loss 1.039605, Validation loss 8.082997\n",
      "Epoch 3639, Training loss 0.897583, Validation loss 15.067554\n",
      "Epoch 3640, Training loss 1.039474, Validation loss 8.083132\n",
      "Epoch 3641, Training loss 0.897495, Validation loss 15.066996\n",
      "Epoch 3642, Training loss 1.039350, Validation loss 8.083263\n",
      "Epoch 3643, Training loss 0.897403, Validation loss 15.066466\n",
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      "Epoch 3658, Training loss 1.038327, Validation loss 8.084321\n",
      "Epoch 3659, Training loss 0.896696, Validation loss 15.062099\n",
      "Epoch 3660, Training loss 1.038197, Validation loss 8.084436\n",
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      "Epoch 3664, Training loss 1.037942, Validation loss 8.084692\n",
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      "Epoch 3667, Training loss 0.896349, Validation loss 15.059977\n",
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      "Epoch 3795, Training loss 0.890894, Validation loss 15.025818\n",
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      "Epoch 3845, Training loss 0.888838, Validation loss 15.012624\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3846, Training loss 1.026885, Validation loss 8.094727\n",
      "Epoch 3847, Training loss 0.888754, Validation loss 15.012088\n",
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      "Epoch 4135, Training loss 0.877500, Validation loss 14.936604\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4136, Training loss 1.010696, Validation loss 8.106537\n",
      "Epoch 4137, Training loss 0.877427, Validation loss 14.936107\n",
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      "Epoch 4415, Training loss 0.867238, Validation loss 14.862549\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4416, Training loss 0.996196, Validation loss 8.115387\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Epoch 4640, Training loss 0.985132, Validation loss 8.121606\n",
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      "Epoch 4718, Training loss 0.981373, Validation loss 8.123669\n",
      "Epoch 4719, Training loss 0.856573, Validation loss 14.780115\n",
      "Epoch 4720, Training loss 0.981279, Validation loss 8.123713\n",
      "Epoch 4721, Training loss 0.856504, Validation loss 14.779586\n",
      "Epoch 4722, Training loss 0.981181, Validation loss 8.123765\n",
      "Epoch 4723, Training loss 0.856437, Validation loss 14.779050\n",
      "Epoch 4724, Training loss 0.981088, Validation loss 8.123809\n",
      "Epoch 4725, Training loss 0.856366, Validation loss 14.778500\n",
      "Epoch 4726, Training loss 0.980989, Validation loss 8.123863\n",
      "Epoch 4727, Training loss 0.856301, Validation loss 14.777948\n",
      "Epoch 4728, Training loss 0.980899, Validation loss 8.123907\n",
      "Epoch 4729, Training loss 0.856229, Validation loss 14.777398\n",
      "Epoch 4730, Training loss 0.980797, Validation loss 8.123969\n",
      "Epoch 4731, Training loss 0.856161, Validation loss 14.776836\n",
      "Epoch 4732, Training loss 0.980704, Validation loss 8.124022\n",
      "Epoch 4733, Training loss 0.856093, Validation loss 14.776304\n",
      "Epoch 4734, Training loss 0.980608, Validation loss 8.124057\n",
      "Epoch 4735, Training loss 0.856025, Validation loss 14.775753\n",
      "Epoch 4736, Training loss 0.980513, Validation loss 8.124120\n",
      "Epoch 4737, Training loss 0.855955, Validation loss 14.775191\n",
      "Epoch 4738, Training loss 0.980415, Validation loss 8.124178\n",
      "Epoch 4739, Training loss 0.855887, Validation loss 14.774652\n",
      "Epoch 4740, Training loss 0.980323, Validation loss 8.124215\n",
      "Epoch 4741, Training loss 0.855819, Validation loss 14.774094\n",
      "Epoch 4742, Training loss 0.980228, Validation loss 8.124273\n",
      "Epoch 4743, Training loss 0.855750, Validation loss 14.773551\n",
      "Epoch 4744, Training loss 0.980130, Validation loss 8.124321\n",
      "Epoch 4745, Training loss 0.855681, Validation loss 14.772985\n",
      "Epoch 4746, Training loss 0.980036, Validation loss 8.124380\n",
      "Epoch 4747, Training loss 0.855611, Validation loss 14.772428\n",
      "Epoch 4748, Training loss 0.979937, Validation loss 8.124444\n",
      "Epoch 4749, Training loss 0.855541, Validation loss 14.771870\n",
      "Epoch 4750, Training loss 0.979842, Validation loss 8.124478\n",
      "Epoch 4751, Training loss 0.855474, Validation loss 14.771322\n",
      "Epoch 4752, Training loss 0.979748, Validation loss 8.124524\n",
      "Epoch 4753, Training loss 0.855407, Validation loss 14.770782\n",
      "Epoch 4754, Training loss 0.979654, Validation loss 8.124582\n",
      "Epoch 4755, Training loss 0.855339, Validation loss 14.770247\n",
      "Epoch 4756, Training loss 0.979558, Validation loss 8.124641\n",
      "Epoch 4757, Training loss 0.855269, Validation loss 14.769681\n",
      "Epoch 4758, Training loss 0.979462, Validation loss 8.124686\n",
      "Epoch 4759, Training loss 0.855201, Validation loss 14.769135\n",
      "Epoch 4760, Training loss 0.979369, Validation loss 8.124721\n",
      "Epoch 4761, Training loss 0.855131, Validation loss 14.768580\n",
      "Epoch 4762, Training loss 0.979270, Validation loss 8.124787\n",
      "Epoch 4763, Training loss 0.855063, Validation loss 14.768026\n",
      "Epoch 4764, Training loss 0.979178, Validation loss 8.124832\n",
      "Epoch 4765, Training loss 0.854995, Validation loss 14.767468\n",
      "Epoch 4766, Training loss 0.979082, Validation loss 8.124890\n",
      "Epoch 4767, Training loss 0.854925, Validation loss 14.766911\n",
      "Epoch 4768, Training loss 0.978987, Validation loss 8.124934\n",
      "Epoch 4769, Training loss 0.854858, Validation loss 14.766385\n",
      "Epoch 4770, Training loss 0.978891, Validation loss 8.124998\n",
      "Epoch 4771, Training loss 0.854788, Validation loss 14.765823\n",
      "Epoch 4772, Training loss 0.978793, Validation loss 8.125049\n",
      "Epoch 4773, Training loss 0.854720, Validation loss 14.765259\n",
      "Epoch 4774, Training loss 0.978697, Validation loss 8.125108\n",
      "Epoch 4775, Training loss 0.854650, Validation loss 14.764697\n",
      "Epoch 4776, Training loss 0.978603, Validation loss 8.125153\n",
      "Epoch 4777, Training loss 0.854583, Validation loss 14.764147\n",
      "Epoch 4778, Training loss 0.978508, Validation loss 8.125206\n",
      "Epoch 4779, Training loss 0.854513, Validation loss 14.763593\n",
      "Epoch 4780, Training loss 0.978411, Validation loss 8.125259\n",
      "Epoch 4781, Training loss 0.854445, Validation loss 14.763039\n",
      "Epoch 4782, Training loss 0.978317, Validation loss 8.125307\n",
      "Epoch 4783, Training loss 0.854378, Validation loss 14.762495\n",
      "Epoch 4784, Training loss 0.978223, Validation loss 8.125365\n",
      "Epoch 4785, Training loss 0.854308, Validation loss 14.761937\n",
      "Epoch 4786, Training loss 0.978124, Validation loss 8.125420\n",
      "Epoch 4787, Training loss 0.854241, Validation loss 14.761379\n",
      "Epoch 4788, Training loss 0.978034, Validation loss 8.125462\n",
      "Epoch 4789, Training loss 0.854175, Validation loss 14.760840\n",
      "Epoch 4790, Training loss 0.977943, Validation loss 8.125504\n",
      "Epoch 4791, Training loss 0.854107, Validation loss 14.760293\n",
      "Epoch 4792, Training loss 0.977847, Validation loss 8.125543\n",
      "Epoch 4793, Training loss 0.854038, Validation loss 14.759743\n",
      "Epoch 4794, Training loss 0.977750, Validation loss 8.125607\n",
      "Epoch 4795, Training loss 0.853970, Validation loss 14.759178\n",
      "Epoch 4796, Training loss 0.977659, Validation loss 8.125648\n",
      "Epoch 4797, Training loss 0.853900, Validation loss 14.758627\n",
      "Epoch 4798, Training loss 0.977558, Validation loss 8.125716\n",
      "Epoch 4799, Training loss 0.853832, Validation loss 14.758070\n",
      "Epoch 4800, Training loss 0.977466, Validation loss 8.125751\n",
      "Epoch 4801, Training loss 0.853764, Validation loss 14.757519\n",
      "Epoch 4802, Training loss 0.977372, Validation loss 8.125818\n",
      "Epoch 4803, Training loss 0.853695, Validation loss 14.756954\n",
      "Epoch 4804, Training loss 0.977274, Validation loss 8.125870\n",
      "Epoch 4805, Training loss 0.853628, Validation loss 14.756396\n",
      "Epoch 4806, Training loss 0.977183, Validation loss 8.125912\n",
      "Epoch 4807, Training loss 0.853561, Validation loss 14.755868\n",
      "Epoch 4808, Training loss 0.977087, Validation loss 8.125956\n",
      "Epoch 4809, Training loss 0.853491, Validation loss 14.755303\n",
      "Epoch 4810, Training loss 0.976990, Validation loss 8.126019\n",
      "Epoch 4811, Training loss 0.853422, Validation loss 14.754745\n",
      "Epoch 4812, Training loss 0.976893, Validation loss 8.126068\n",
      "Epoch 4813, Training loss 0.853356, Validation loss 14.754195\n",
      "Epoch 4814, Training loss 0.976804, Validation loss 8.126113\n",
      "Epoch 4815, Training loss 0.853286, Validation loss 14.753633\n",
      "Epoch 4816, Training loss 0.976706, Validation loss 8.126164\n",
      "Epoch 4817, Training loss 0.853217, Validation loss 14.753065\n",
      "Epoch 4818, Training loss 0.976610, Validation loss 8.126228\n",
      "Epoch 4819, Training loss 0.853151, Validation loss 14.752522\n",
      "Epoch 4820, Training loss 0.976521, Validation loss 8.126258\n",
      "Epoch 4821, Training loss 0.853083, Validation loss 14.751965\n",
      "Epoch 4822, Training loss 0.976425, Validation loss 8.126304\n",
      "Epoch 4823, Training loss 0.853014, Validation loss 14.751414\n",
      "Epoch 4824, Training loss 0.976327, Validation loss 8.126379\n",
      "Epoch 4825, Training loss 0.852944, Validation loss 14.750849\n",
      "Epoch 4826, Training loss 0.976231, Validation loss 8.126425\n",
      "Epoch 4827, Training loss 0.852878, Validation loss 14.750302\n",
      "Epoch 4828, Training loss 0.976141, Validation loss 8.126465\n",
      "Epoch 4829, Training loss 0.852810, Validation loss 14.749742\n",
      "Epoch 4830, Training loss 0.976046, Validation loss 8.126508\n",
      "Epoch 4831, Training loss 0.852744, Validation loss 14.749212\n",
      "Epoch 4832, Training loss 0.975953, Validation loss 8.126554\n",
      "Epoch 4833, Training loss 0.852676, Validation loss 14.748666\n",
      "Epoch 4834, Training loss 0.975860, Validation loss 8.126610\n",
      "Epoch 4835, Training loss 0.852607, Validation loss 14.748097\n",
      "Epoch 4836, Training loss 0.975765, Validation loss 8.126654\n",
      "Epoch 4837, Training loss 0.852540, Validation loss 14.747551\n",
      "Epoch 4838, Training loss 0.975670, Validation loss 8.126722\n",
      "Epoch 4839, Training loss 0.852470, Validation loss 14.746968\n",
      "Epoch 4840, Training loss 0.975574, Validation loss 8.126762\n",
      "Epoch 4841, Training loss 0.852403, Validation loss 14.746410\n",
      "Epoch 4842, Training loss 0.975480, Validation loss 8.126825\n",
      "Epoch 4843, Training loss 0.852332, Validation loss 14.745831\n",
      "Epoch 4844, Training loss 0.975382, Validation loss 8.126884\n",
      "Epoch 4845, Training loss 0.852264, Validation loss 14.745277\n",
      "Epoch 4846, Training loss 0.975290, Validation loss 8.126923\n",
      "Epoch 4847, Training loss 0.852199, Validation loss 14.744738\n",
      "Epoch 4848, Training loss 0.975199, Validation loss 8.126973\n",
      "Epoch 4849, Training loss 0.852131, Validation loss 14.744187\n",
      "Epoch 4850, Training loss 0.975103, Validation loss 8.127017\n",
      "Epoch 4851, Training loss 0.852062, Validation loss 14.743637\n",
      "Epoch 4852, Training loss 0.975006, Validation loss 8.127068\n",
      "Epoch 4853, Training loss 0.851997, Validation loss 14.743094\n",
      "Epoch 4854, Training loss 0.974918, Validation loss 8.127102\n",
      "Epoch 4855, Training loss 0.851930, Validation loss 14.742544\n",
      "Epoch 4856, Training loss 0.974824, Validation loss 8.127154\n",
      "Epoch 4857, Training loss 0.851862, Validation loss 14.741994\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4858, Training loss 0.974730, Validation loss 8.127202\n",
      "Epoch 4859, Training loss 0.851793, Validation loss 14.741433\n",
      "Epoch 4860, Training loss 0.974634, Validation loss 8.127263\n",
      "Epoch 4861, Training loss 0.851727, Validation loss 14.740879\n",
      "Epoch 4862, Training loss 0.974544, Validation loss 8.127310\n",
      "Epoch 4863, Training loss 0.851656, Validation loss 14.740314\n",
      "Epoch 4864, Training loss 0.974445, Validation loss 8.127357\n",
      "Epoch 4865, Training loss 0.851589, Validation loss 14.739764\n",
      "Epoch 4866, Training loss 0.974350, Validation loss 8.127400\n",
      "Epoch 4867, Training loss 0.851522, Validation loss 14.739203\n",
      "Epoch 4868, Training loss 0.974258, Validation loss 8.127476\n",
      "Epoch 4869, Training loss 0.851452, Validation loss 14.738627\n",
      "Epoch 4870, Training loss 0.974162, Validation loss 8.127517\n",
      "Epoch 4871, Training loss 0.851386, Validation loss 14.738077\n",
      "Epoch 4872, Training loss 0.974070, Validation loss 8.127557\n",
      "Epoch 4873, Training loss 0.851318, Validation loss 14.737520\n",
      "Epoch 4874, Training loss 0.973974, Validation loss 8.127608\n",
      "Epoch 4875, Training loss 0.851251, Validation loss 14.736956\n",
      "Epoch 4876, Training loss 0.973884, Validation loss 8.127661\n",
      "Epoch 4877, Training loss 0.851181, Validation loss 14.736405\n",
      "Epoch 4878, Training loss 0.973784, Validation loss 8.127727\n",
      "Epoch 4879, Training loss 0.851114, Validation loss 14.735833\n",
      "Epoch 4880, Training loss 0.973695, Validation loss 8.127748\n",
      "Epoch 4881, Training loss 0.851049, Validation loss 14.735297\n",
      "Epoch 4882, Training loss 0.973602, Validation loss 8.127800\n",
      "Epoch 4883, Training loss 0.850978, Validation loss 14.734726\n",
      "Epoch 4884, Training loss 0.973502, Validation loss 8.127868\n",
      "Epoch 4885, Training loss 0.850913, Validation loss 14.734164\n",
      "Epoch 4886, Training loss 0.973415, Validation loss 8.127908\n",
      "Epoch 4887, Training loss 0.850845, Validation loss 14.733619\n",
      "Epoch 4888, Training loss 0.973319, Validation loss 8.127968\n",
      "Epoch 4889, Training loss 0.850775, Validation loss 14.733043\n",
      "Epoch 4890, Training loss 0.973223, Validation loss 8.128019\n",
      "Epoch 4891, Training loss 0.850708, Validation loss 14.732489\n",
      "Epoch 4892, Training loss 0.973129, Validation loss 8.128068\n",
      "Epoch 4893, Training loss 0.850640, Validation loss 14.731932\n",
      "Epoch 4894, Training loss 0.973038, Validation loss 8.128109\n",
      "Epoch 4895, Training loss 0.850573, Validation loss 14.731381\n",
      "Epoch 4896, Training loss 0.972944, Validation loss 8.128160\n",
      "Epoch 4897, Training loss 0.850507, Validation loss 14.730824\n",
      "Epoch 4898, Training loss 0.972852, Validation loss 8.128193\n",
      "Epoch 4899, Training loss 0.850441, Validation loss 14.730292\n",
      "Epoch 4900, Training loss 0.972760, Validation loss 8.128244\n",
      "Epoch 4901, Training loss 0.850374, Validation loss 14.729732\n",
      "Epoch 4902, Training loss 0.972667, Validation loss 8.128298\n",
      "Epoch 4903, Training loss 0.850305, Validation loss 14.729159\n",
      "Epoch 4904, Training loss 0.972572, Validation loss 8.128345\n",
      "Epoch 4905, Training loss 0.850239, Validation loss 14.728610\n",
      "Epoch 4906, Training loss 0.972478, Validation loss 8.128393\n",
      "Epoch 4907, Training loss 0.850169, Validation loss 14.728038\n",
      "Epoch 4908, Training loss 0.972383, Validation loss 8.128438\n",
      "Epoch 4909, Training loss 0.850102, Validation loss 14.727466\n",
      "Epoch 4910, Training loss 0.972293, Validation loss 8.128491\n",
      "Epoch 4911, Training loss 0.850035, Validation loss 14.726920\n",
      "Epoch 4912, Training loss 0.972197, Validation loss 8.128535\n",
      "Epoch 4913, Training loss 0.849966, Validation loss 14.726352\n",
      "Epoch 4914, Training loss 0.972102, Validation loss 8.128587\n",
      "Epoch 4915, Training loss 0.849901, Validation loss 14.725805\n",
      "Epoch 4916, Training loss 0.972011, Validation loss 8.128638\n",
      "Epoch 4917, Training loss 0.849833, Validation loss 14.725245\n",
      "Epoch 4918, Training loss 0.971918, Validation loss 8.128693\n",
      "Epoch 4919, Training loss 0.849764, Validation loss 14.724676\n",
      "Epoch 4920, Training loss 0.971822, Validation loss 8.128748\n",
      "Epoch 4921, Training loss 0.849698, Validation loss 14.724123\n",
      "Epoch 4922, Training loss 0.971730, Validation loss 8.128796\n",
      "Epoch 4923, Training loss 0.849629, Validation loss 14.723540\n",
      "Epoch 4924, Training loss 0.971633, Validation loss 8.128859\n",
      "Epoch 4925, Training loss 0.849562, Validation loss 14.722980\n",
      "Epoch 4926, Training loss 0.971544, Validation loss 8.128895\n",
      "Epoch 4927, Training loss 0.849495, Validation loss 14.722437\n",
      "Epoch 4928, Training loss 0.971450, Validation loss 8.128936\n",
      "Epoch 4929, Training loss 0.849429, Validation loss 14.721883\n",
      "Epoch 4930, Training loss 0.971358, Validation loss 8.128971\n",
      "Epoch 4931, Training loss 0.849363, Validation loss 14.721330\n",
      "Epoch 4932, Training loss 0.971264, Validation loss 8.129034\n",
      "Epoch 4933, Training loss 0.849293, Validation loss 14.720757\n",
      "Epoch 4934, Training loss 0.971168, Validation loss 8.129090\n",
      "Epoch 4935, Training loss 0.849226, Validation loss 14.720186\n",
      "Epoch 4936, Training loss 0.971077, Validation loss 8.129145\n",
      "Epoch 4937, Training loss 0.849157, Validation loss 14.719618\n",
      "Epoch 4938, Training loss 0.970983, Validation loss 8.129189\n",
      "Epoch 4939, Training loss 0.849091, Validation loss 14.719065\n",
      "Epoch 4940, Training loss 0.970890, Validation loss 8.129232\n",
      "Epoch 4941, Training loss 0.849024, Validation loss 14.718514\n",
      "Epoch 4942, Training loss 0.970797, Validation loss 8.129292\n",
      "Epoch 4943, Training loss 0.848957, Validation loss 14.717950\n",
      "Epoch 4944, Training loss 0.970706, Validation loss 8.129322\n",
      "Epoch 4945, Training loss 0.848891, Validation loss 14.717408\n",
      "Epoch 4946, Training loss 0.970613, Validation loss 8.129376\n",
      "Epoch 4947, Training loss 0.848820, Validation loss 14.716825\n",
      "Epoch 4948, Training loss 0.970513, Validation loss 8.129439\n",
      "Epoch 4949, Training loss 0.848754, Validation loss 14.716243\n",
      "Epoch 4950, Training loss 0.970427, Validation loss 8.129485\n",
      "Epoch 4951, Training loss 0.848685, Validation loss 14.715700\n",
      "Epoch 4952, Training loss 0.970328, Validation loss 8.129543\n",
      "Epoch 4953, Training loss 0.848621, Validation loss 14.715143\n",
      "Epoch 4954, Training loss 0.970243, Validation loss 8.129560\n",
      "Epoch 4955, Training loss 0.848554, Validation loss 14.714593\n",
      "Epoch 4956, Training loss 0.970146, Validation loss 8.129625\n",
      "Epoch 4957, Training loss 0.848487, Validation loss 14.714022\n",
      "Epoch 4958, Training loss 0.970053, Validation loss 8.129667\n",
      "Epoch 4959, Training loss 0.848420, Validation loss 14.713471\n",
      "Epoch 4960, Training loss 0.969961, Validation loss 8.129719\n",
      "Epoch 4961, Training loss 0.848352, Validation loss 14.712904\n",
      "Epoch 4962, Training loss 0.969868, Validation loss 8.129763\n",
      "Epoch 4963, Training loss 0.848287, Validation loss 14.712343\n",
      "Epoch 4964, Training loss 0.969777, Validation loss 8.129811\n",
      "Epoch 4965, Training loss 0.848217, Validation loss 14.711768\n",
      "Epoch 4966, Training loss 0.969679, Validation loss 8.129878\n",
      "Epoch 4967, Training loss 0.848150, Validation loss 14.711207\n",
      "Epoch 4968, Training loss 0.969588, Validation loss 8.129913\n",
      "Epoch 4969, Training loss 0.848084, Validation loss 14.710658\n",
      "Epoch 4970, Training loss 0.969496, Validation loss 8.129971\n",
      "Epoch 4971, Training loss 0.848017, Validation loss 14.710086\n",
      "Epoch 4972, Training loss 0.969403, Validation loss 8.130004\n",
      "Epoch 4973, Training loss 0.847951, Validation loss 14.709533\n",
      "Epoch 4974, Training loss 0.969314, Validation loss 8.130053\n",
      "Epoch 4975, Training loss 0.847883, Validation loss 14.708972\n",
      "Epoch 4976, Training loss 0.969218, Validation loss 8.130108\n",
      "Epoch 4977, Training loss 0.847817, Validation loss 14.708408\n",
      "Epoch 4978, Training loss 0.969128, Validation loss 8.130157\n",
      "Epoch 4979, Training loss 0.847749, Validation loss 14.707854\n",
      "Epoch 4980, Training loss 0.969032, Validation loss 8.130206\n",
      "Epoch 4981, Training loss 0.847683, Validation loss 14.707294\n",
      "Epoch 4982, Training loss 0.968943, Validation loss 8.130245\n",
      "Epoch 4983, Training loss 0.847615, Validation loss 14.706730\n",
      "Epoch 4984, Training loss 0.968850, Validation loss 8.130295\n",
      "Epoch 4985, Training loss 0.847548, Validation loss 14.706173\n",
      "Epoch 4986, Training loss 0.968753, Validation loss 8.130355\n",
      "Epoch 4987, Training loss 0.847480, Validation loss 14.705586\n",
      "Epoch 4988, Training loss 0.968662, Validation loss 8.130404\n",
      "Epoch 4989, Training loss 0.847414, Validation loss 14.705026\n",
      "Epoch 4990, Training loss 0.968569, Validation loss 8.130451\n",
      "Epoch 4991, Training loss 0.847348, Validation loss 14.704466\n",
      "Epoch 4992, Training loss 0.968480, Validation loss 8.130482\n",
      "Epoch 4993, Training loss 0.847282, Validation loss 14.703916\n",
      "Epoch 4994, Training loss 0.968388, Validation loss 8.130531\n",
      "Epoch 4995, Training loss 0.847216, Validation loss 14.703362\n",
      "Epoch 4996, Training loss 0.968295, Validation loss 8.130578\n",
      "Epoch 4997, Training loss 0.847147, Validation loss 14.702787\n",
      "Epoch 4998, Training loss 0.968200, Validation loss 8.130628\n",
      "Epoch 4999, Training loss 0.847083, Validation loss 14.702230\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(tensor([[16.0549],\n",
       "         [13.6323]], grad_fn=<ThAddmmBackward>), tensor([[13.],\n",
       "         [11.]]))"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "model = nn.Sequential(OrderedDict([\n",
    "    ('hidden_linear', nn.Linear(1, 10)),\n",
    "    ('hidden_activation', nn.Tanh()),\n",
    "    ('output_linear', nn.Linear(10, 1))\n",
    "]))\n",
    "\n",
    "learning_rate = 1e-2\n",
    "\n",
    "optimizer = optim.SGD(model.parameters(), lr=learning_rate)\n",
    "\n",
    "loss_fn = nn.MSELoss()\n",
    "\n",
    "nepochs = 5000\n",
    "\n",
    "for epoch in range(nepochs):\n",
    "    # forward pass\n",
    "    t_p_train = model(t_un_train)\n",
    "    loss_train = loss_fn(t_p_train, t_c_train)\n",
    "\n",
    "    with torch.no_grad():\n",
    "        t_p_val = model(t_un_val)\n",
    "        loss_val = loss_fn(t_p_val, t_c_val)\n",
    "\n",
    "    print('Epoch %d, Training loss %f, Validation loss %f' % (epoch, float(loss_train), float(loss_val)))\n",
    "        \n",
    "    # backward pass\n",
    "    optimizer.zero_grad()\n",
    "    loss_train.backward()    \n",
    "    optimizer.step()\n",
    "    \n",
    "model(t_un_val), t_c_val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x115bb2e80>]"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "plt.plot(t_u.numpy(), t_c.numpy(), 'o')\n",
    "plt.plot(t_u.numpy(), model(0.1 * t_u).detach().numpy(), 'x')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x115e626d8>]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "plt.plot(t_un.numpy(), t_c.numpy(), 'o')\n",
    "plt.plot(t_un.numpy(), model(t_un, w, b).numpy(), 'r-')\n",
    "\n",
    "#plt.plot(t_u.numpy(), model(0.1 * t_u).detach().numpy(), 'x')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}